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Surface energetics of adsorbent-biomass interactionsduring expanded bed chromatography. Implications

for process performance

by

Rami Reddy Vennapusa

A thesis submitted in partial fulfillment

of the requirements for the degree of

Doctor of Philosophy

in Biochemical Engineering

Approved, Thesis committee

Prof. Dr. Marcelo Fernández-Lahore

Prof. Dr . Jürgen Fritz

Prof. Dr. Briger Anspach

Date of Defense: September 3, 2008

School of Engineering and Science



II

ORIGINALITY STATEMENT

‘I hereby declare that this submission is my own work and to the best of knowledge itcontains no materials previously published or written by another researcher, or substantial proportions of material which have been accepted for the award of any other degree or diploma at Jacobs University or any other educational institutions, except where dueacknowledgement is made in the thesis. I also declare that the intellectual content of thisthesis is the product of my own work, except to the extent that assistance from my thesissupervisor in the project’s design and conception or in style, presentation and linguisticexpression is acknowledged.’

Signature …………………………….

Date ……………………..



III

Abstract

Common limitations encountered during the direct recovery of bioproducts from an

unclarified feedstock are related to the presence of biomass in such processing systems.

Biomass related effects can be described as biomass-to-support interaction and cell-to-cell

aggregation. In the current thesis work biomass related effects were studied in an important

integrated primary unit operation mode viz Expanded bed adsorption (EBA), which was

proved to suffer from the detrimental effects by the presence of biomass.

Current work involves the investigation and understanding of the biomass interaction and

aggregation onto various EBA process surfaces at local or molecular level. In doing so

Streamline materialsTM of various chemistries were taken as process surface and intactyeast cell, yeast homogenates, and disrupted bacterial paste were employed as model

colloids to understand their deposition and subsequent aggregation.

Deposition and aggregation was studied with surface energetics according to XDLVO

theory. These predictions based on the application of XDLVO theory were confirmed by

independent experimental methods, like biomass deposition experiments and laser

diffraction spectroscopy.

Biomass components and beaded adsorbents were characterized by contact angle

determinations with three diagnostic liquids and zeta potential measurements.

Subsequently, free energy of interactionvs. distance profiles between interacting surfaces

was calculated in aqueous media provided by its operating mobile phase. The effect of

various chromatographic conditions based on the mode of operation was explored in

relation to yeast interaction and aggregation.

Calculations indicated that the interaction and aggregation is mainly due to the existence of

a reversible secondary energy minimum. The extent and depth of pocket varied based on

the operating process conditions for different interacting pairs.

Understanding biomass-related effects will overcome or at least mitigate the process

limitations. Exploring the effect of various types of additives for their ability to inhibit



IV

either biomass deposition, cell aggregation, or a combination of both effects, a non ionic

polymer PVP 360 was found to alleviate biomass deposition on weak anion exchangers.

The predictions made by the XDLVO theory were well correlated with the physicochemical

parameter α, in relation to ion exchangers where only interaction is happening. On the other

hand a discrete modifications of XDLVO energies was observed with the lump parameter α

for hydrophobic and pseudo affinity process surfaces where interaction and aggregation is

taking place. Establishing a correlation defined a safe operational windows for EBA

process when U≤ |50| kT and α ≤ 0.15.

Fundamental knowledge which could predict feedstock behaviour during primary unit

operations of downstream processing would alleviate the current bottleneck during

processing of bioproducts.



VI

Not only the academic support important to conclude a thesis but also the emotional

support especially when you are so far away from home. I would like thank Marcelo and

his family members for being to my host family and supporting emotionally during my stay

away from my home.

My most profound thanks, my most heartfelt appreciation; my deepest gratitude goes to my

family without whom none of this could have been accomplished. To my mum and dad,

thanks for your unwavering confidence in me, for your love and sacrifice and for the moral

energy. Thanks you so much for all the prayers and taking interest in my progress. Actually

I have no words to thanks my dad and mom for their enumerous moral support. Thanks to

my brothers Vasu and Kesav and their families for their love and encouragement. Deepest

appreciation to my brother Kesav a doctor by profession, who took care of my sanity during

course of my PhD. I also would like thank all my family members my grandfather, to my

memory of grandmother and my siblings for constant caring and great moral support.

Friends are every thing once you cross the sea; I have many friends back from India and

here to thank who have directly and indirectly helped during the work. Thank you

everyone.

Finally the most important one Lord God almighty. With out his blessings nothing would

have been possible today. I am infinitely grateful to my God for being my courage and

refuge. Since there are no words to thank God for taking care of me all though my current

life as heartfelt appreciation the current work is dedicated in his name.



VII

Dedication

To Lord Sri Venkateswara SwamyTTD, Tirumala

India.



VIII

Table of contents

ABSTRACT …………………………………………………………………. III

ACKNOWLEDGEMENTS ………………………………………………… V

1 GENERAL INTRODUCTION …………………………………………… 11

1.1 Introduction to Biotechnology ………………………………………….. 11

1.2 Downstream Processing ………………………………………………… 12

1.2.1 Process integration ………………………………………………... 13

1.2.2 Expanded bed adsorption ………………………………………… 14

1.2.3 Operating principle ………………………………………………. 15

1.3 Problem statement and Research objective ……………………………. 17

1.4 Goal of the work …………………………………………………………. 21

1.5 References ……………………………………………………………….. 23

2.0 RESULTS / ORGANIZATION OF THESIS ………………………….. 27

2.1 Assessing adsorbent-biomass interactions during expanded bed adsorption

Onto ion exchangers utilizing surface energetics ……………………… 28

2.1.1 Abstract ……………………………………………………………. 28

2.1.2 Introduction ……………………………………………………….. 29

2.1.3 Theory ……………………………………………………………… 31

2.1.4 Materials and Methods …………………………………………… 35

2.1.5 Results and discussions …………………………………………… 38

2.1.6 Conclusion …………………………………………………………. 572.1.7 Acknowledgements ………………………………………………... 58

2.1.8 Nomenclature ……………………………………………………… 59

2.19 References …………………………………………………………… 61



IX

2.2 Colloid deposition experiments as a diagnostic tool for biomass attachment onto

bioproduct adsorbent surfaces ………………………………………….. 65

2.2.1 Abstract ……………………………………………………………… 65

2.2.2 Introduction …………………………………………………………. 66

2.2.3 Materials and Methods …………………………………………….. 69

2.2.4 Results and Discussions …………………………………………..... 72

2.2.5 Conclusion …………………………………………………………... 84

2.2.6 Acknowledgements ………………………………………………..... 85

2.2.7 Nomenclature ……………………………………………………….. 85

2.2.8 References …………………………………………………………… 87

2.3 Surface energetics to assess biomass attachment onto hydrophobic interaction

adsorbents in expanded beds ……………………………………………… 90

2.3.1 Abstract ………………………………………………………………. 90

2.3.2 Introduction …………………………………………………….......... 91

2.3.3 Materials and Methods ……………………………………………… 93

2.3.4 Results and Discussions ……………………………………………… 97

2.3.5 Conclusions …………………………………………………………… 112

2.3.6 Acknowledgements …………………………………………………… 123

2.3.7 Nomenclature …………………………………………………………. 124

2.3.8 References …………………………………………………………….. 125

2.4 Surface energetics to assess biomass attachment onto immobilized metal affinity

adsorbents in expanded beds ……………………………………………… 128

2.4.1 Abstract ……………………………………………………………..... 128

2.4.2 Introduction ………………………………………………………….. 129


2.4.4 Results and Discussions ……………………………………………... 135

2.4.5 Conclusions …………………………………………………………... 151


2.4.7 Nomenclature ………………………………………………………… 1522.4.8 References …………………………………………………………….. 153



X

2.5 Surface energetics to assess biomass deposition onto fluidized chromatographic

supports …………………………………………………………………...... 156

2.5.1 Abstract ………………………………………………………………. 156

2.5.2 Introduction ………………………………………………………….. 157


2.5.4 Results and Discussions ……………………………………………… 163

2.5.5 Conclusions …………………………………………………………… 174


2.5.7 Nomenclature …………………………………………………………. 175

2.5.8 References …………………………………………………………….. 177

2.6 The effect of chemical additives on biomass deposition onto beaded

chromatographic supports ………………………………………………... 179

2.6.1 Abstract ………………………………………………………………. 179

2.6.2 Introduction ………………………………………………………….. 180

2.6.3 Materials and Methods ………………………………………………. 183

2.6.4 Results and Discussions ………………………………………………. 187

2.5.5 Conclusions …………………………………………………………… 2022.6.6 Acknowledgements …………………………………………………… 202

2.6.7 References …………………………………………………………… 203

3.0 GENERAL CONCLUSIONS AND REMARKS ………………………….. 207

4.0 Appendix …………………………………………………………………….. 214



Introduction

11

1 General Introduction

1.1 Introduction to Biotechnology

Biotechnology is known to exist as such since the late 17th century. This “traditional”

biotechnology was mostly concerned with processing of food e.g. wine, beer, cheese and

other diary products. In the late 19th century a new wave in the biotechnology industry

started when complex organic molecules like antibiotics and enzymes were produced for

the first time by biosynthesis (Enfors and Häggström 2005). With the knowledge gained on

microbial physiology, biochemistry and genetics it was possible to think about genetic

manipulations of the cells during the 70’s and the so called “genetic engineering” was born.

The advances in genetic engineering led to a new era in biotechnology with products like

insulin, erythropoietin, and interferon. These biopharmaceutical products have a high

market value. In the current century, the biopharmaceutical industry in one the fastest

growing sectors in the global economy (Pavlou and Reichert 2004). Proteins constitute an

important class of biopharmaceutical products, but also have food and biotechnology

applications (Headon and Walsh 1994). Advances in the recombinant DNA and cell culture

technology have permitted the large scale production of virtually any protein by

fermentation routes at increased titers (Walsh 2006), thereby shifting the bottleneck in

biopharmaceutical process development to the purification of such bioproducts (Smith2005; Thiel 2004).

Also microbial bioprocess can be divided in main two parts: a) the fermentation step, as the

(bio) synthesizing step, and b) downstream processing, for the primary recovery and

purification of the desired product (Ref. Figure 2). Since considerable efforts were made on

the genetic manipulation of cells and on the improvement of fermentation strategies, a

considerable increase in production level was already accomplished. However, optimizeddownstream processes have to be designed for the subsequent recovery of these products so

as to match “upstream” performance.



Introduction

12

1.2 Downstream processing

The most cost intensive component of biotech-processing is DOWNSTREAM

PROCESSING (DSP), which accounts for ≥ 50-85% of the total processing cost. Increasing

competition in biotech markets, and the development of new (niche) markets, which are possible due to the utilization of recombinant DNA technology and modern cell culture

techniques in the industry have triggered the development of novel and efficient (bio)

separation technologies (Gupta and Mattiasson 1994).

Biotechnological process fluids are generally of complex nature and contain solid

(biological) particles of various sizes, as well as solutes of various molecular masses and

chemistries (Anspach et al. 1999; Thömmes 1997). The required purity of the products inthe biotechnological industry ranges from partially purified concentrates e.g. food enzymes

to highly purified preparations e.g. purity demand≥ 99.99% in the case of therapeutic

proteins used for intravenous dosage. A direct consequence of the latter is that purification

processes comprise a relatively large number of unit operations whose complexity depends

on the final product purity required (Wheelright 1991). It is common place to observe

downstream processes having a total number of processing steps between seven and

fourteen (Bonnerjea et al. 1986; Fish and Lilly 1984; Wheelright 1991). Each additional

step or unit operation will affect the overall process economy by increasing operational cost

and process time. Additional steps will also produce a certain degree of product loss and

thus, the overall yield after a certain processing “train” will substantially decrease. For

example, assuming single step yields in the range 70-95%,≈ 60% of the product will be

lost after six processing steps (Maitra and Verma 2003) (Ref. Figure 1). Therefore, the

process economics, yield and time are interrelated and an optimum balance between them

has to be found in order to design a successful downstream process.



Introduction

13

Figure 1: Series of steps and their yields in Downstream Processing.

1.2.1 Process Integration

Integration is the creation of link between previously separate unit operations or combining

individual steps in to one unit operation, by which product losses and process economics

can be minimized.

Process integration has been actively researched in the field of biochemical engineering

over the last decade and these efforts continue today. The reason is that “integration” could

be one of the keys for the rational, cost-effective and productive design of (bio) separation

processes. From the preceding paragraphs it is understood that increasing the processing

steps would lead to a suboptimal process.

Draeger and Chase in the year 1994 (Chase 1994) presented a novel integrated concept

based on fluidized adsorbent beads for the direct sequestration of bioproducts. Expanded

bed adsorption (EBA) was introduced as an advantageous unit operation; details are given

in following sections (McCormick 1993).

100 9585.5

72.6

61.7

46.341.6

0

20

40

60

80

100

P r o d u

c t S L

S

D I S R U P

C L A R

I F / C O N

C

C H R O

M # 1

C H R O

M # 2

G F

Individual ste

Global process

Yield (%)

Processing steps



Introduction

15

1.2.3 Operating principle

Standard chromatographic columns (“packed beds”) are characterized by adsorbent beads

which are physically confined within the bed. On the other hand, EBA systems allow the

introduction of a crude feedstock e.g. containing biological particulates, without the danger of clogging. This is due to the fact that the particulate matter and cell or cell debris can flow

within the inter-particular space created upon the solid-liquid fluidization. EBA columns

are fed from the bottom while a movable adapter is held away from the adsorbent bead

population, thus letting the same to “expand”. As buffer is pumped from below, these beads

become not only fluidized but also classified according to their size and density. This

fluidization and classification occurs when their sedimentation velocity equals to the

upward liquid velocity (Figure 3b). To accentuate this effect commercial adsorbent beadshave been modified to include inert quartz or metal alloy cores, and beads have a defined

size/density range (StreamlineTM GE Healthcare, Uppsala, Sweden; FastLineTM Upfront,

Copenhagen, Denmark). Adsorbent beads used in EBA have a size range within 50 to 400

mm. When stable fluidization / classification occurs (“expansion”) the local mobility of the

matrix particles is reduced (Figure 4). Therefore, EBA systems mimic packed bed

chromatography in the sense of creating a number of equilibrium stages (“plates”)

alongside the column length (Hubbuch et al. 2005). EBA mode of operation is shown in

Figure 3.



Introduction

16

a) Sedimentedbed b) Equilibration

ClassifiedFluidization

c) SampleApplication

d) Elution

+

Bio-product cell

a) Sedimentedbed b) Equilibration

ClassifiedFluidization


d) Elutiona) Sedimented

bed b) EquilibrationClassified

Fluidization


d) Elution

++

Bio-product cell

Figure 3: The unclarified feedstock when applied to the EBA column. The particulates and the cell debrisare supposed to move freely around the adsorbent beads and eventually leave through the top of the column.The compound of interest interacts with the beadsvia specific ligands and becomes adsorbed. Afterwards, thematrix is allowed to settle and the plunger is moved down flow. Elution can be performed either in the packed bed mode or alternatively in the expanded bed mode at decreased superficial velocity (Lihme et al. 1999).

Particle size gradient Particle density gradient

+ +

Plug flow

Particle size gradient Particle density gradient

+ +

Plug flow

Particle density gradient

+ +

Plug flow

Figure 4: The phenomenon of proper fluidization and classification during the expanded bed adsorption.



Introduction

19

cells

Bio-product Bead

cells

Bio-product Bead

BeadBead

cells

Bio-product Bead

cells

Bio-product Bead

BeadBead

cells

Bio-product Bead

cells

Bio-product Bead

BeadBead

Figure 5: Interacting expanded system causing impaired hydrodynamics and decreasingsorption performance.

Bio-product Bead

cells

Local level (distance 1.5 )

Bio-product Bead

cells


BeadBead

cells


Figure 6: Illustration signifying biomass interaction to adsorbent (at a local level).

The biomass deposition phenomena is hampering the industrial utilization of EBA since its

introduction in 1994 (Curbelo et al. 2003). Some advancement was made in the 90’s to

alleviate such limitation with partial success. Several methods were developed to analyze

the extent of biomass–adsorbent interactions. The methods include finite bath adsorption,

pulse response and residence distribution analysis (Hubbuch et al. 2005). All these

techniques can only provide an overall indication of the state of fouling. Few recent studies

attempted to understand this phenomenon more in detail (Lin et al. 2006). The

aforementioned diagnostic methods address the degree of interaction of biomass to a

Interaction

Aggregation



Introduction

20

limited range of material types, particularly anion-exchangers. For example, zeta potential

was introduced as a significant parameter for process design, due to the obvious ionic

interaction prevailing in ion-exchange systems. However, this approach cannot explain the

interaction and aggregation of biomass onto hydrophobic and pseudo-affinity beads as

electrostatic interactions play a minor role in such cases. This is due to processing

conditions under which high-conductivity buffers are employed (Gallardo-Moreno et al.

2002; Klotz et al. 1985). Exploring further in this direction Peter Brixius during his doctoral

work in Jülich and Novo Nordisk A/S (Brixius 2003) addressed the existence of some other

forces like Van der Waals and hydrophobic forces involved in the adhesion of biomass

apart from the electrostatic forces. However, Brixius’ work mainly dealt with charge-

mediated attraction forces onto anion exchangers. Some insight on physicochemical

parameters affecting the adhesion of biomass on ion exchanger adsorbents was provided

(Vergnault et al. 2004). A few authors also tried to understand fouling on chromatographic

beads utilizing confocal laser microscopy (Siu et al. 2006). Also manufacturers have tried

to alleviate biomass interaction by introducing novel type of equipment for EBA by

designing novel bead structures (Viloria-Cols et al. 2004). Among the various methods

tried to overcome the interaction of biomass to process surfaces thermal pretreatment of

biomass before loading on the column was reported in literature (Ng et al. 2007).

Despite all these efforts, a comprehensive picture of the interfacial forces acting between

cells and beads was unavailable until now. Particularly, previous work has focused on cell-

to-bead interaction but the role of cell-to-cell aggregation was neglected since this

phenomenon can not be captured by existing methods, like the biomass-impulse test earlier

developed by Feuser (Feuser et al. 1999). Today, we have realized the importance of

aggregation under certain processing conditions (Fernandez-Lahore et al. 2000). Fouling is

a common phenomena in the integrated process where there direct contact between crudefeedstock and reactive solids e.g., membrane operations, magnetic separations, direct

capture techniques (Bierau et al. 2001; Theodossiou et al. 2001; Ventura et al. 2008)



Introduction

21

1.4 Goal of the work

Complementing all the above research findings by different authors on the biomass

adhesion, current work further progressed with the objective to have more quantitative

fundamental understanding at local level between biomass and adsorbent bead, which are

commonly utilized in EBA technology. It was targeted to determine the basic underlying

phenomenon of the interfacial forces (Lifshitz-van der Waals, hydrophobic attractive or

hydrophilic repulsive and electrostatic) at micrometer scale between a biological particle

and process surface or between two biological particles (Figure 6). Understandings the

phenomena at molecular level will allow developing an improved process performance of

EBA making the process more robust and less complex in the process scenario with all its

added advantages. Additionally the fundamental understanding could help to propose a

universal tool for process/material design when direct sequestration is in focus.

For having this comprehensive picture, surface thermodynamics was utilized. XDLVO

theory was used to determine the interactions and aggregation onto the process surface.

XDLVO calculations were performedvia experimental determination of contact angles and

zeta potentials values for the interacting surfaces or particles. Experimental XDLVO

quantitative information was validated independently with the biomass deposition

experiments (Tari et al. 2008) and laser diffraction experiments.

Under the frame of current research work the following aspects were studied

1) Interaction of three different biomass types intact yeast, yeast homogenates and

E.coli homogenates with the Streamline ion exchangers. Aggregation of only intact

yeast was studied with this type.

2) Interaction and aggregation of Saccharomycess cervisiae with the Streamline

hydrophobic and chelating (pseudo affinity) supports.3) Influence of chemical additives on the interaction and aggregation of

Saccharomycess cervisiae with different Streamline materials.



Introduction

22

Surface energetics or physicochemical properties of the above-mentioned supports and bio-

foulants are studied in detail at various process conditions in order to have a clear picture in

the problem-creating scenario while downstream processing.

The biomass adhesion on the different substrata has been studied by many authors

(Absolom et al. 1983; Bos et al. 1999) by applying classical DLVO (CDLVO) and

extended DLVO (XDLVO) theory, which was proven to be more advantageous and can be

applied to biological particles (Bos et al. 1999). The detailed theoretical part of XDLVO is

described in chapter I within this thesis.



References

23

1.5 References

Absolom DR, Lamberti FV, Policova Z, Zingg W, Van Oss CJ, Neumann AW. 1983.

Surface thermodynamics of bacterial adhesion. Appl Environ Microbiol 46(1):90-7.

Ameskamp N, Priesner C, Lehmann J, Lütkemeyer D. 1999. Pilot scale recovery of monoclonal antibodies by expanded bed ion exchange adsorption. Bioseparation

8(1):169-188.

Anspach FB, Curbelo D, Hartmann R, Garke G, Deckwer WD. 1999. Expanded-bed

chromatography in primary protein purification. J Chromatogr A 865(1-2):129-144.

Bierau H, Hinton RJ, Lyddiatt A. 2001. Direct process integration of cell disruption and

fluidised bed adsorption in the recovery of labile microbial enzymes. Bioseparation

10(1-3):73-85.Bonnerjea J, Oh S, Hoare M, Dunnill P. 1986. Protein Purification: The Right Step at the

Right Time. Nat Biotech 4(11):954-958.

Bos R, Van der Mei HC, Busscher HJ. 1999. Physico-chemistry of initial microbial

adhesive interactions--its mechanisms and methods for study. FEMS Microbiol Rev

23(2):179-230.

Brixius PJ. 2003. On the influence of feedstock properties and composition on process

development of expanded bed adsorption. Dusseldorf, Germany: Heinrich Heine

University.

Chase HA. 1994. Purification of proteins by adsorption chromatography in expanded beds.

Trends Biotechnol 12(8):296-303.

Curbelo DR, Garke G, Guilarte RC, Anspach FB, Deckwer WD. 2003. Cost Comparison of

Protein Capture from Cultivation Broths by Expanded and Packed Bed Adsorption.

Eng Life Sci 3(10):406-415.

Enfors S, Häggström L. 2005. Bioprocess Technology - Fundamentals and Applications A

textbook for introduction of the theory and practice of biotechnical processes. 1-350

p.

Erickson JC, Finch JD, Greene DC. 1994. Direct capture of recombinant proteins from

animal cell culture media using a fluidized bed adsorber. In: Griffiths B, Spier RE,

BertholdW, editors. Animal cell technology:Products for today, prospects for

tomorrow. Oxford: Butterworth-Heinemann:557-560.



References

24

Fernandez-Lahore HM, Geilenkirchen S, Boldt K, Nagel A, Kula MR, Thommes J. 2000.

The influence of cell adsorbent interactions on protein adsorption in expanded beds.

J Chromatogr A 873(2):195-208.

Feuser J, Walter J, Kula MR, Thommes J. 1999. Cell/adsorbent interactions in expanded bed adsorption of proteins. Bioseparation 8(1-5):99-109.

Fish NM, Lilly MD. 1984. The Interactions Between Fermentation and Protein Recovery.

Nat Biotech 2(7):623-627.

Gallardo-Moreno AM, Gonzalez-Martin ML, Perez-Giraldo C, Garduno E, Bruque JM,

Gomez-Garcia AC. 2002. Thermodynamic Analysis of Growth Temperature

Dependence in the Adhesion of Candida parapsilosis to Polystyrene. Appl Environ

Microbiol 68(5):2610-2613.

GEHealthCare. 2001-04. Cost comparison: expanded bed adsorption (EBA)vs

conventional recovery in the industrial scale processing of proteins. Application

note STREAMLINE expanded bed adsorption. p 1150-21 AA.

GEHealthCare. 2002-11. A comparison of STREAMLINE expanded bed adsorption with

the combined techniques of filtration and conventional fixed bed chromatography

for the capture of an Fc-fusion protein from CHO cell culture. Application note

STREAMLINE expanded bed adsorption. p 1144-87 AB.

Gupta MN, Mattiasson B. 1994. Novel technologies in downstream processing. Chem Ind

17:673-675.

Headon DR, Walsh G. 1994. The industrial production of enzymes. Biotechnol Adv

12(4):635-646.

Hubbuch J, Thommes J, Kula MR. 2005. Biochemical engineering aspects of expanded bed

adsorption. Adv Biochem Eng Biotechnol 92:101-23.

Klotz SA, Drutz DJ, Zajic JE. 1985. Factors Governing Adherence of Candida Species to

Plastic Surfaces. Infect Immun 50(1):97-191.Lihme A, Zafirakos E, Hansen M, Olander M. 1999. Simplified and more robust EBA

processes by elution in expanded bed mode. Bioseparation 8(1):93-97.

Lin DQ, Fernandez-Lahore HM, Kula MR, Thommes J. 2001. Minimising

biomass/adsorbent interactions in expanded bed adsorption processes: a

methodological design approach. Bioseparation 10(1-3):7-19.



References

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Lin DQ, Zhong LN, Yao SJ. 2006. Zeta potential as a diagnostic tool to evaluate the

biomass electrostatic adhesion during ion-exchange expanded bed application.

Biotechnol Bioeng 95(1):185-91.

Maitra SS, Verma AK. 2003. End of Small Volume High Value Myth in Biotechnology,Process Design for a Mega-plant Producing gamma Interferon for Mega Profit. IE

(I) Journal CH 84.

McCormick DK. 1993. Expanded Bed Adsorption. Nat Biotech 11(9):1059-1059.

Ng MYT, Tan WS, Abdullah N, Ling TC, Tey BT. 2007. Direct purification of

recombinant hepatitis B core antigen from two different pre-conditioned unclarified

Escherichia coli feedstocks via expanded bed adsorption chromatography. J

Chromatogr A 1172(1):47-56.

Pavlou AK, Reichert JM. 2004. Recombinant protein therapeutics-success rates, market

trends and values to 2010. Nat Biotech 22(12):1513-1519.

Poulin F, Jacquemart R, DeCrescenzo G, Jolicoeur M, Legros R. 2008. A Study of the

Interaction of HEK-293 Cells with Streamline Chelating Adsorbent in Expanded

Bed Operation. Biotechnol Prog 24(1):279-282.

Siu SC, Boushaba R, Topoyassakul V, Graham A, Choudhury S, Moss G, Titchener-

Hooker NJ. 2006. Visualising fouling of a chromatographic matrix using confocal

scanning laser microscopy. Biotechnol Bioeng 95(4):714-723.

Smith C. 2005. Striving for purity: advances in protein purification. Nat Meth 2(1):71-77.

Smith MP, Bulmer MA, Hjorth R, Titchener-Hooker NJ. 2002. Hydrophobic interaction

ligand selection and scale-up of an expanded bed separation of an intracellular

enzyme from Saccharomyces cerevisiae. J Chromatogr A 968(1-2):121-128.

Tari C, Vennapusa RR, Cabrera RB, Fernandez-Lahore M. 2008. Colloid deposition

experiments as a diagnostic tool for biomass attachment onto bioproduct adsorbent

surfaces. J Chem Technol Biotechnol 83:183-191.Theodossiou I, Sondergaard M, Thomas OR. 2001. Design of expanded bed supports for

the recovery of plasmid DNA by anion exchange adsorption. Bioseparation 10(1-

3):31-44.

Thiel KA. 2004. Biomanufacturing, from bust to boom...to bubble? Nat Biotech

22(11):1365-1372.

Thömmes J. 1997. Fluidized bed adsorption as a primary recovery step in protein

purification. Adv Biochem Eng/Biotechnol 58:185-230.



References

26

Ventura AM, Fernandez Lahore HM, Smolko EE, Grasselli M. 2008. High-speed protein

purification by adsorptive cation-exchange hollow-fiber cartridges. J Membr Sci

321(2):350-355.

Vergnault H, Mercier-Bonin M, Willemot RM. 2004. Physicochemical parameters involvedin the interaction of Saccharomyces cerevisiae cells with ion-exchange adsorbents

in expanded bed chromatography. Biotechnol Prog 20(5):1534-42.

Viloria-Cols ME, Hatti-Kaul R, Mattiasson B. 2004. Agarose-coated anion exchanger

prevents cell-adsorbent interactions. J Chromatogr A 1043(2):195-200.

Walsh G. 2006. Biopharmaceutical benchmarks 2006. Nat Biotech 24(7):769-776.

Walter J, Feuser J. Novel approach and technology in expanded bed adsorption techniques

for primary recovery of proteins at large technical scale; 2002; Florida. Downstream

EBA ’02, Sweden, Amersham Biosciences. p 37-39.

Wheelright SM. 1991. Protein purification: Design and scale up of downstream processing.

New York: Oxford University Press.



Results

27

2.0 Organization of dissertation

The dissertation is organized in the form of the manuscripts originated during the course of

my PhD work

Assessing adsorbent-biomass interactions during expanded bed adsorption onto ionexchangers utilizing surface energeticsR.R. Vennapusa, S.M. Hunegnaw, R.B. Cabrera, M. Fernandez-Lahore, published inJournal of Chromatography A. 2008, 1181, (1-2), 9-20.

Colloid deposition experiments as a diagnostic tool for biomass attachment onto bioproductadsorbent surfacesC.Tari† , R.R. Vennapusa†, R.B. Cabrera, M. Fernandez-Lahore, published in Journal of

Chemical Technology & Biotechnology, 2008, 83, 183-191.

Surface energetics to assess biomass attachment onto hydrophobic interaction adsorbents inexpanded bedsR.R. Vennapusa, C. Tari, R. B. Cabrera, M. Fernandez-Lahore. Biochemical EngineeringJournal (accepted).

Surface energetics to assess biomass attachment onto immobilized metal affinity adsorbentsin expanded bedsR.R. Vennapusa, M. Aasim, R.B. Cabrera, M. Fernandez-Lahore. Biotechnology and

Bioprocess Engineering (Submitted).

Surface energetics to assess microbial adhesion onto fluidized chromatography adsorbentsR.R. Vennapusa, S. Binner, R.B. Cabrera, M. Fernandez-Lahore. Engineering in LifeSciences (accepted)

The effect of chemical additives on biomass deposition onto beaded chromatographicsupportsR.R. Vennapusa, M. Fernandez-Lahore. Journal of Biotechnology (Submitted).

† : Equal authorship



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2.1 Assessing adsorbent-biomass interactions during expandedbed adsorption onto ion-exchangers utilizing surface energetics

Rami Reddy Vennapusa, Sara M. Hunegnaw, Rosa B. Cabrera, and Marcelo Fernández-LahoreDownstream Processing Laboratory, Jacobs University, Campus Ring 1, D-28759, Bremen,

Germany.

2.1.1 Abstract

Biomass adhesion onto an adsorbent matrix or “interaction” as well as biological particle

co-adhesion or “aggregation” can severely affect the overall performance of many direct-

contact methods for downstream processing of bioproducts. Studies to quantitativelydescribe this biomass-adsorbent interaction were developed utilizing surface energetics. An

indirect thermodynamic approachvia contact angle and zeta potential measurements was

utilized. Intact yeast cells, yeast homogenates, and disrupted bacterial paste were employed

as model system. Various surfaces that are relevant to biochemical and environmental

applications were characterized. The extended Derjaguin, Landau, Verwey, Overbeek

(XDLVO) theory was found to appropriately predict biomass adhesion behaviour. It was

observed that cell attachment onto anion exchange supports is promoted by strong andclose interaction within a secondary energy minimum followed by moderate multilayer cell

aggregation. On the other hand, cell interaction with cation exchange materials can take

place within a reversible secondary energy minimum and at longer separation distance. The

influence particle charge and size, as well as the influence of the nature of the material

under study were summarized in the form of energy vs. distance profiles. These

investigations lead to many process-related conclusions: a) Process buffer conductivity

windows can be recommended for anion-exchange chromatography (AEX) vs. cation-

exchange chromatography (CEX) systems, b) Increased hydrodynamic shear is required to

prevent biomass attachment onto AEX as compared to CEX, and c) Aggregation

phenomena is a function of contact time and biomass concentration. Understanding

biomass-adsorbent interaction at the particle (local) level is opening the pave for optimized

operation of Expanded Bed Adsorption methods at the process (macro) scale. A universal

methodological approach is presented to guide both process and material design.



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2.1.2 Introduction

The current key component of biotech manufacturing is product downstream processing.

Recovery and purification processes comprise a relatively large number of unit operations,

which complexity depends on the final product purity required and which typically accountfor ≥ 50-85% of the total bioprocessing cost. The required purity of the products in the life

science industry ranges from partially purified biocatalysts to highly purified therapeutic

agents. In any case, bioprocess fluids are generally of complex nature and contain

suspended solids like biological particles of various sizes, as well as solutes of various

molecular masses and chemical structures. Moreover, the need for additional unit

operations during downstreaming will cause a degree of product loss and will substantially

decrease overall process yield. For example, assuming single step yields in the range 70-95%, ~ 60% of the product will be lost after six processing steps.

Expanded Bed Adsorption (EBA) has been proposed as an “integrative” downstream

processing technology allowing the direct capture of targeted species from an unclarified

feedstock e.g. a cell containing fermentation broth. This unit operation has the potential to

combine solids removal, product concentration, and partial purification in a single

processing step. The application of EBA implies, however, that intact cell particles or celldebris present in the feedstock will interact –in a minor or larger extent- with fluidized

adsorbent beads. It is already known that interaction between biomass and the adsorbent

phase may lead to the development of poor system hydrodynamics and therefore, impaired

sorption performance under real process conditions (Anspach et al. 1999; Hubbuch et al.

2005). Detrimental processing conditions can also be expected in any other downstream

operation where direct contacting between a crude feedstock and a reactive solid phase is

supposed to occur (Bierau et al. 2001; Theodossiou et al. 2001). Moreover, biomass

interaction would result in increased buffer consumption in order to remove and wash away

sticky biological particles (GEHealthCare 2001; Northelfer and Walter 2002). These

phenomena i.e. decreased sorption performance and buffer consumption is detrimental to

cost-efficient processing utilizing direct sequestration unit operations.

Earlier studies on biomass-adsorbent interactions were restricted to simple diagnostic tests

to determine the extent of cell –or cell debris- attachment to the desired chromatographic

supports (Feuser et al. 1999). The development of residence time distribution methods as



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30

applied to turbid feedstock, and their subsequent application to evaluate system

hydrodynamics under real process conditions, has established a clear picture of the

deleterious potential of biomass-adsorbent interactions (Fernandez-Lahore et al. 1999).

Further studies pointed out that interactions between (positively charged) anion exchangersand (negatively charged) biological particles resulted the most problematic system to deal

with (Fernandez-Lahore et al. 2000; Lin et al. 2001). Due to the obvious electrostatic nature

of such interaction, a single property of these interacting bodies i.e. the zeta potential has

been recently proposed for a better understanding and prediction of biomass-adsorbent

interactions (Lin et al. 2003; Lin et al. 2006). Other investigations on microbial adhesion to

solid surfaces have lead to similar conclusions in the sense that electrostatic interaction

between microbial cells and process surfaces is an important factor affecting such

phenomena (Mills et al. 1994; Vergnault et al. 2007). These conclusions, however, were

based on proving biomass adhesion on a single material type in solutions of different ionic

strength. Furthermore, these studies were restricted to ion-exchangers, to yeast cells having

a certain degree of hydrophobic character, and to an experimental evaluation based on the

microbial-adhesion-to-solvents test. On the other hand, some studies have found a better

correlation between surface energy, calculated by the three liquid contact angle method,

and microbial adhesion on different solid supports at constant solution chemistry (Li and

Logan 2004).

Taken into consideration the complexity of interfacial phenomena at the (sub) micrometer

scale, a more comprehensive approach would consider interaction forces other than those

purely electrostatic in nature and would employ principles of colloid chemistry to explain

biomass-adsorbent attachment at the local (particle) level (Van Oss 1994). It is known that

biological particles like microbial cells can be considered “soft” colloidal particles and thus

their adhesion to substrata should be studied as a physicochemical phenomenon. It isevident that, besides hydrodynamic effects, biomass adhesion to process supports has the

potential to be strongly influenced by long-range (electrodynamic Lifshitz – van der Waals,

electrostatic) and short-range (acid-base) interfacial interactions. Within theclassical

DLVO (Derjaguin, Landau, Verwey, Overbeek) theory, Lifshitz-Van der Waals (LW) and

electrostatic interactions (EL) are considered while in theextended approach (XDLVO) the

so called acid-base (AB) component is also accounted for. Application of these principles

to process science would lead to the development of appropriate tools for better bioprocess



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31

design and prediction and would guide the development of improved materials for

downstream processing. The later is especially true when direct sequestration methods are

in focus.

Accurate understanding and prediction of interfacial forces during biomass adhesion onto

process supports require the utilisation of quantitative models which, in turn, require

experimental measurements to be performed. EL interactions arise from the existence of

overlapping double layers of counter-ions near charged surfaces in aqueous media and are

accessible by determination of the zeta potential. On the other hand, LW interactions are

caused by the specific alignment and coupling of molecular dipoles. Additionally, the

extended approach has been adopted to explain cell-surface interactions in the presence of

other forces like hydrophobic (Van Oss 1995), hydration (Strevett and Chen 2003), and

electrostatic (Camesano and Logan 2000). LW and AB forces are experimentally accessible

via contact angle measurement with three diagnostic liquids.

The aim of this paper was to contribute to a more in-depth understanding of biomass-

adsorbent adhesion and to propose a universal tool for process / material design. In doing

so, the physicochemical properties of biomass-derived material, taken as colloidal particles,

vs. the physicochemical properties of the adsorbent beads, taken as a process surface, were

determined indirectlyvia contact angle and zeta potential measurements. Subsequently,

total interfacial interaction energy values were calculated as a function of surface distance

in aqueous media e.g. process buffer. Calculated interaction energy values were correlated

to process performance.

2.1.3 Theory

2.1.3.1 Total interaction energy

The total interaction energy between a colloidal particle and a solid surface can be

expressed in terms of the classical DLVO theory as:

ELmwc

LW mwc

DLVOmwc U U U += (1)

where UDLVO is the total interaction energy in aqueous media, ULW is the LW interaction

term, and UEL

is the EL interaction term. The subscript m is utilised for thechromatographic matrix (adsorbent bead), w refers to the watery environment, and c to the



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32

colloidal (cell) particle. This classical DLVO approach can be extended to include a third

short-range (≤ 5 nm) Lewis AB term so as to include “hydrophobic attractive” and

“hydrophilic repulsive” forces into account (Van Oss 1994).

ABmwc

ELmwc

LW mwc

XDLVOmwc U U U U ++= (2)

where UDLVO is the total interaction energy and UAB is the AB interaction term.

2.1.3.2 Lifshitz-van der Waals acid-base approach

Surface energy parameters (tensions) can be calculated from contact angle measurements

on the colloidal particles and adsorbent surface utilising the LW-AB approach. These

parameters (or components) can be determined by performing contact angle measurementsutilising three probe liquids (i.e. two high-energy polar liquids and one high-energy non-

polar liquid) with known surface tension parameters and employing the extended Young’s

equation:

( ) ( +−−+ ++=+ l sl s LW l

LW s

TOT l γ γ γ γ γ γ γ θ 2cos1 (3)

where θ is the contact angle,γLW is the LW surface tension parameter,γ+ is the electron-

acceptor parameter, andγ- is the electron-donor parameter. The subscript s and l is utilised

for solid and liquid respectively. The polar AB component is given by:

−+= γ γ γ 2 AB (4)

and the total surface tension of a pure substance can be represented by the sum of the polar

AB and the non-polar LW surface tension parameters. The later represents a single

electrodynamic property of a certain material.

2.1.3.3 Free energy of interaction

The mentioned surface energy parameters can be employed to evaluate the free energy of

interaction between two defined surfaces (ΔGLW - ΔGAB) e.g. the cell particles and the

adsorbent bead (interaction) or between two cells (aggregation).ΔG represents here the

interaction energy per unit area between two (assumed)infinite planar surfaces bearing the

properties of the adsorbent bead and the cell or two cells, respectively. Moreover, contacts



Results

33

between any of these two surfaces are evaluated at the so-called minimum cut-off distance

(h0) i.e. the distance between the outer electron shells of adjoining non-covalently

interacting molecules. The value for h0 is commonly assumed to be 0.158 nm. However, the

mentioned LW and AB interaction energy components follow a unique decay profile withsurface separation distance. Dimensions of the preceding equations are Joule. Nevertheless,

for interaction energies the kT scale is preferred since 1 kT represents the Brownian motion

energy of a microbial particle.

The ULW energy-distance profile can be expressed according to the existing geometric

constraints in order to obtain the actual interaction energy as:

( ) ⎥⎦

⎤⎢⎣

⎡

⎟⎟

⎠ ⎞

⎜⎜

⎝ ⎛

++

++−=

cc

cc LW mwc Rh

h Rh

Rh

R AhU

2ln

26(Sphere-Plate) (5a)

( )( )mc

mc LW cwc R Rh

R R AhU

+−=

6(Sphere-Sphere) (5b)

where R c and R m are the radius of the interacting bodies i.e. ~ 5μm for yeast and∼200 μm

for the adsorbent bead. A is the Hamaker constant that can be obtained fromΔGLW, as

calculated from contact angle measurements, according to

LW Gh A Δ−= 2012π (6a)

( ( LW w

LW c

LW m

LW w

LW mwcG γ γ γ γ −−=Δ 2 (6b)

The UAB energy-distance profile can be expressed according to the existing geometric

constraints in order to obtain the actual interaction energy as:

⎥⎦

⎤⎢⎣

⎡ −Δ=λ

λ π hh

G RhU ABc

ABmwc

0exp2)( (Plate-Sphere) (7a)

⎥⎦

⎤⎢⎣

⎡ −Δ=λ

λ π hh

G RhU ABc

ABcwc

0exp)( (Sphere-Sphere) (7b)

where λ is a characteristic decay length for AB interactions in water (λ ~ 0.6 nm) and

where:



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34

( ( ( +−−++++−−−−+ +−−++−+=Δ cmcmwcmwwcmw ABmwcG γ γ γ γ γ γ γ γ γ γ γ γ 222 (8)

In order to account for UEL

energy-distance profile the following expression can beemployed assuming either plate-sphere or sphere-sphere geometry, respectively:

( ) ( )( ) ( ){ }⎥

⎦

⎤⎢⎣

⎡ −−+−−−+

++= h

hh

RhU cm

cmcmcr

ELmwc κ

κ κ

ζ ζ ζ ζ

ζ ζ ε ε π 2exp1lnexp1exp1ln2)( 22

220 (9a)

( )( )

( )( )

( ){ }⎥⎦

⎤⎢⎣

⎡ −−+−−−+

+++= h

hh

R R R R

hU cm

cm

mc

cmmcr ELcwc κ

κ κ

ζ ζ ζ ζ ζ ζ ε ε π 2exp1ln

exp1exp1ln2)( 22

220 (9b)

where ε0εr is the dielectric permittivity of the suspending fluid,ζm is the zeta potential of

the adsorbent bead, andζc is the zeta potential of the cell particle. Zeta potential values are

measured by electrophoretic mobility experiments.κ is the inverse Debye screening length

and can be calculated on the basis of the relationship below:

T k

z ne

r

ii

0

22

ε ε κ ∑= (10)

where e is the electron charge, ni is the number concentration of ioni in solution, zi is the

valence of ioni, k is the Boltzman constant, and T is the absolute temperature.



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2.1.4 Materials and Methods

2.1.4.1 Materials

Chromatographic matrices and columns were purchased from GE Healthcare (Munich,

Germany). Solvents utilised for contact angle measurements (1-bromonaphtalene and

formamide) were obtained from Fluka (Buchs, Switzerland) with 99% and 99.5% purity,

respectively. Water was Milli-Q quality. All other chemicals were of analytical grade.

The goniometric system (OCA 20) was obtained from DataPhysics Instruments GmbH

(Filderstadt, Germany). Zeta potential was measured with a Zetasizer Nano ZS from

Malvern Instruments (Worcestershire, United Kingdom).

2.1.4.2 Biomass

Yeast cells (Saccharomyces cerevisiae ) were cultivated, harvested at late exponential

phase, and washed three times with dilute buffer solutions (Ganeva et al. 2004). Fresh E.

coli DH5α biomass was produced according to standard methods (Sambrook and Russell

2006). Cell disruption was performed by bead milling, as previously described (Fernandez-

Lahore et al. 1999).

2.1.4.3 Surface preparation for contact angle measurements

Preparation of the intact yeast cells for contact angle measurements was performed

essentially according to Henriques et al. (Henriques et al. 2002). Fresh (washed) cells were

suspended to 10% (w/v) in 50 mM citrate phosphate buffer (pH 3, 5, 7 or 9). Suspended

cells were further allowed to equilibrate in the respective buffer for 30 minutes and the

suspension was poured onto an agar plate containing 10% glycerol and 2% agar-agar. The

plate was allowed to dry for 24-36 hours at room temperature on a properly levelled surface

and free from dust.

Agarose-based adsorbent beads harbouring various ligand chemistries were thoroughly

equilibrated in 50 mM sodium acetate (pH 4) or 20 mM phosphate buffer (pH 7). Once

equilibrated, matrix beads were frozen in liquid nitrogen and crushed mechanically.

Crushing efficiency was assessed by microscopic examination and particle size

determination. Crushed matrix was made 40% (w/v) in buffer and allowed to remain in



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36

contact with the liquid phase for additional 30 minutes with gentle mixing. Fine bead

fragments were poured onto a glycerol-containing agar plate and allowed to dry, as

described before.

Immobilized biomass or adsorbent fragments (< 10μm diameter) on squares pieces of the

agar-supported surface were utilised for measuring the contact angles.

2.1.4.4 Contact angle measurements

For the contact angle estimation, the sessile drop technique was utilized (Sharma and Rao

2002). Data acquisition and analysis was performed utilising SCA20 commercial software

(DataPhysics Instruments GmbH, Filderstadt, Germany). Measurements were performed at

room temperature, using three different diagnostic liquids: water, formamide and 1-

bromonaphtalene. Assays were performed in triplicate and at least 20 contact angles per

samples were measured. Contact angles were measured for biomass samples as a function

of pH in the range from 3.0 to 7.0. Measurements for adsorbent materials were performed

at pH 4.0 and pH 7.0 in diluted buffer solutions. The solution chemistry employed reflected

common process conditions.

2.1.4.5 Zeta potential determinations

Particle zeta potential was determined for the cell particles and for the chromatographic

supports under study. Biomass-derived particles were suspended to 1% (w/v) in 20 mM

phosphate or citrate-phosphate buffers. Fragmented Sepharose beads were utilized instead

of Streamline beads due to their lower density and to avoid sedimentation during

measurements. Particles were contacted with buffer until equilibrium was reached and

further diluted to appropriate particle count (~200) before measuring the zeta potential. Zeta

potentials were calculated from the electrophoretic mobility data as per theSmoluchowski’s equation (Ottewill and Shaw 1972). All the measurements were done in

triplicate.



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2.1.4.6 Biomass-pulse experiments

Experiments were performed on an ÄKTA Explorer system (GE-Healthcare, Munich,

Germany) utilising a modified XK-10 chromatographic column filled with the sample

adsorbent (2.0 ml) and irrigated from the bottom with the mobile phase. The solid phasewas fluidised at a fluid velocity of 7.5-8.3⋅10-4 m⋅s-1 in order to promote the formation of a

stable expanded bed. A biomass pulse (~ 2 ml of 0.03% w/v biomass suspension) were

loaded into the system through a three way injection port. Cell concentration in the pulse

before and after passage through the expanded bed was detected on-line by measuring the

optical density at 600 nm. Results were expressed as Cell Transmition Index (CTI) (Feuser

et al. 1999).

2.1.4.7 Partition experiments

Solid-liquid partitioning experiments were performed with adsorbent beads and biomass in

glass flasks (4 cm height, 1.5 cm diameter), which were closed with plastic caps.

Chromatographic beads (0.5 ml) were contacted with a cell suspension (2.0 ml of 0.03%

w/v) under gentle orbital stirring. Samples were taken after 15 min and 3 h to evaluate the

fast and slow phases of cell deposition (Fernandez-Lahore et al. 2000). The optical density

of the samples was evaluated by absorbance at 600 nm. The fraction of non-bound cells or biomass particles to each material type was defined as the Cell Partition Index (CPI).



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2.1.5 Results and Discussions


The diagnostic liquids water, formamide, and 1-bromonaphtalene were employed to

measure contact angles on lawns of hydrated biomass or crushed agarose beads utilising the

sessile drop technique. The surface free energy componentsγLW and γAB, as well as, the

electron-donating and electron-accepting parameters for these liquids can be found in the

literature (Bos et al. 1999). Biomass and adsorbent fragments were equilibrated in 20 mM

phosphate buffer pH 7, which provides a chemical environment similar to that found under

ion-exchange sorption processing in industrial practice. In this work, biomass or crushed

adsorbent lawns were prepared on agar layers (Henriques et al. 2002). This method permits

contact angle measurements under the assumption that only bound water is present on thesample surface and proved to be suitable to handle a variety of materials by forming an

even and homogeneous surface.

Table 1: Contact angle measurements for agarose-based beaded supports. Determinationswere performed on lawns of crushed agrose-based adsorbents in in 20mM Phosphate buffer, pH 7.

Support type Contact angle ( θ)

Water Formamide 1-Bromonaphtalene

Sepharose 4B 9.5 ± 2 10 ± 1 44 ± 1

Q Sepharose XL 12 ± 1 14 ± 2 52 ± 1

DEAE Sepharose 9.6 ± 3 13 ± 2 41 ± 1

SP Sepharose 6.7 ± 3 13 ± 1 39 ± 1

Table 1 shows the contact angle values for the anion-exchanger DEAE-Sepharose, the

cation exchanger SP-Sepharose, and the agarose base material 4B-Sepharose. An additional

composite ion-exchanger, Q-Sepharose-XL was also included. Sepharose materials were

utilised for obtaining small particles suitable for contact angle measurements since

Streamline materials have a difficult-to-brake quartz core but similar chemical structure. In

the later case, particle diameter was lower than 10μm to assure no interference with



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39

measurement of contact angles. Contact angle values with polar liquids were similar for all

the chromatographic supports under consideration. Low values were observed for water (7-

12°) and formamide (10-14°), which reflects the general very hydrophilic nature of the

beads under study. However, 1-bromonaphtalene contact angles were able to discriminate between Agarose- based beads (Sepharose series) and the Agarose-Dextran composite (XL

material). The contact angle value with the apolar solvent for the later was 20% higher,

which might indicate an increased hydrophilic character for XL-Sepharose in comparison

with standard materials. This is in agreement with the known higher hydrophilic character

of Dextran T-70 in comparison with polymeric Agarose as judged by the free energy of

interaction of these molecules in water:ΔGsws was reported as -9.2 mJ·m-2 for agarose and

+17.6 mJ·m-2 for Dextran (Van Oss 1994). Moreover, comparison between 1-

bromonaphtalene contact angle values for functionalised vs. non-functionalised Sepharose

materials showed decreased values for the first group i.e. 44° (base material) vs. 39°- 41°

(SP and DEAE materials, respectively). This might reflect an increased hydrophobic

character of the functionalised adsorbent due to the influence of ligand immobilisation

chemistry. Contact angles were determined with the various adsorbents and all the three

liquids at pH 4 but no major changes were observed (data not shown).

Table 2: Contact angle measurements for biological materials. Determinations were performed in 20mM Phosphate buffer at pH 7.

Biomass type Contact angle ( θ )Water Formamide 1-Bromonaphtalene

Intact yeast cells 15 ± 2 14 ± 1 54 ± 1

Yeast homogenate 18 ± 1 22 ± 2 53 ± 1

Bacterial homogenate 28 ± 4 30 ± 2 54 ± 3

Table 2 shows the contact angle values obtained for biomass types which are relevant to

process situations: intact yeast cells, disrupted yeast cells, and disrupted bacterial cells.

Saccharomyces cerevisiae and Escherichia coli were employed as model biomass systems.

Cell disruption was accomplished by bead milling which generated yeast cell fragments

with a size ~ 2-3 μm and bacterial fragments with a size ~ 1μm. As opposed to theobserved trend when analysing the adsorbent materials, contact angle values for the apolar



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41

In which the AB component equals

+−= sv sv AB sv γ γ γ 2

The electron-donating (−

svγ ) and the electron-aceptor (+

svγ ) free energy components give anindication on the biomass or material ability to exert acid-base interactions on an scale

taking water as an arbitrary reference. Since 1-bromonaphtalene is apolar ( ABlvγ = 0), this

liquid can be utilised to calculate the LW component of the biomass/material:

( )2

21cos⎪⎭

⎪⎬⎫

⎪⎩

⎪⎨⎧ += θ γ

γ lv LW sv

On the other hand, since water and formamide are polar, these liquids can be employed in

combination to calculate the electron-donating and electron-accepting parameters of the

sample surface from:

( ) −++− +=−+ lv svlv sv LW lv

LW svlv γ γ γ γ γ γ θ γ 2221cos

According to van Oss (Van Oss 1997) the hydrophilic/ hydrophobic character of a certain

material can be defined in terms of the variation of the free energy of interaction betweentwo moieties of that material immersed in water. This is given after:

( ) ( )+−−+−+−+ −−+−−−=Δ w sw sww s s LW w

LW s

TOT swsG γ γ γ γ γ γ γ γ γ γ 42

2

Calculation of ΔGsws yielded positive values for all the adsorbents i.e. > +25 mJ·m-2, which

demonstrates their hydrophilic nature. However, further inspection of Table 3 showed that

a lower γLW

value was obtained for the XL material and therefore the more polar character of this composite in comparison with the Agarose beads can be confirmed. Moreover, an

increased value for the electron-acceptor parameter characterises the composite adsorbent.

On the basis of the contact angle values obtained with polar liquids and the calculation of

the corresponding surface free energy parameters, the tested adsorbents can be considered

to have a polar character according to the following series:

Q-XL > Beaded agarose > DEAE = SP



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42

Calculation of ΔGsws also yielded positive values for all the biomass types under

consideration (Table 4). Concerning microorganisms it is generally accepted thatΔG > 0

characterises hydrophilic cell surfaces and therefore, the tendency of these biological

particles to aggregate in aqueous environments is very limited. This is particularly true for cells suspended in dilute buffer solutions, which are common during adsorption onto ion-

exchangers.

Table 3: Surface energy parameters for agarose and beaded chromatographic supportscalculated from contact angle measurements at pH 7.

Support typeSurface energy parameters [mJ m -2]

γLW

γ+

γ-

γAB

γTOT

ΔG sws

Agarosea 40.9 0.1 23.8 2.9 43.9 -9.2Dextran T-70a 41.8 1.0 47.2 13.7 55.5 +17.6Sepharose 4B 32.8 2.9 53.6 24.9 57.7 +28.1

Q Sepharose XL 28.9 3.9 53.2 28.8 57.8 +26.6DEAE Sepharose 34.1 2.3 54.5 22.3 56.7 +30.7

SP Sepharose 35.0 2.0 55.7 21.1 56.4 +31.9

(a) Taken from van Oss (Van Oss 1994).

Table 4: Surface energy parameters for several common biomass types at pH 7 ascalculated from contact angle measurements.

Biomass typeSurface energy parameters (mJ m -2)

γLW γ+ γ - γAB γTOT ΔG sws

Intact yeast cells 27.9 4.4 51.5 30.1 58.3 +24.3Yeast homogenate 28.4 3.3 53.2 26.4 55.2 +28.1

Bacterial homogenate 27.9 2.7 49.2 23.1 51.3 +26.0



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2.1.5.3 Interfacial free energy of adhesion: interaction and aggregation

Biomass adhesion to process supports can be considered as a complex phenomenon

including at least two distinct phases: a) The interaction phase characterised by rapidkinetics, where a biological particle approaches the adsorbent bead, and b) The aggregation

phase characterised by cell to cell clumping. The later phase shows lower kinetics and it is

affected by the process contact time and the biomass concentration in the feedstock

(Fernandez-Lahore et al. 1999).

Table 5 depicts the values for interfacial free energy of interaction between several ion-

exchangers and model biomass particles, at closest distance of approximation.ΔGLW values

for agarose-based chromatographic supports were very similar, irrespective of the ligand

chemistry. This may indicate the strong influence of the base material e.g. cross-linked

agarose on the calculated LW energy component. As expected LW energy values were

negative, indicating an attractive interaction. The composite material Q-XL showed a 30%

decreasedΔGLW value (-0.9 mJ·m-2), which again indicates the different structural nature of

the later. On the basis of experimentalΔGLW values it was possible to calculate an average

Hamaker constant for agarose-based materials equal to 4⋅10-21 J or 0.34 k T. This is in

agreement with commonly assumed values for microbial systems (~ 0.49k T). Variations in

ΔGLW values within a range± 50% were observed when comparing beaded agarose

supports with other biomass-interacting materials, like polystyrene, ceramic, or glass.

Repulsive forces were found to play a role during biomass interaction phenomena. This

forces, based on electron donor / electron acceptor or Lewis acid-base, can be seen as

responsible for abnormalities found in the DLVO theoretical interpretation of interfacial

interactions in aqueous media. Table 5 shows an average value for the studiedchromatographic supports in the range +26 to +30 mJ·m-2. These values for the AB

component are 20 times higher than those found for the attractive LW component. AB

forces are known to surpass other DLVO forces by as much as two decimal orders of

magnitude and therefore are extremely important in understanding biomass-support

interactions. The decay with distance of the AB interaction energy is assumed to describe

the distance dependence of the boundary layer ordering. Moreover, ΔGAB values were

shown to change when other systems were examined. For example, the E. coli / PES system



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44

showed a low value (+2.5 mJ·m-2) and the yeast / Q-Hyper Z or the mammalian cell / glass

showed moderate values (~ +20 mJ·m-2). From these data it becomes clear that acid-base

forces exerted in dilute buffer solutions have the potential to strongly influence biomass

interactions during normal processing conditions. Moreover,ΔGAB

forces are the dominantcomponent of the calculated total interfacial free energy of interaction (ΔGTOT as per Table

5) in several process systems of biochemical and environmental importance.

Table 5: Interfacial free energy of interaction between biomass and process materials.Calculations were performed assuming interactions under process buffer conditions at pH7.

Biomass type Support ΔG (mJ·m -2)ΔG LW ΔG AB ΔG TOT

Intact yeast cells Agarose beads -1.3 +27.6 +26.3XL-Q -0.9 +26.3 +25.5DEAE -1.4 +28.7 +27.4SP -1.5 +29.7 +28.0

Yeast homog. Agarose beads -1.4 +29.7 +28.3XL-Q -0.9 +28.3 +27.3DEAE -1.5 +30.9 +29.3SP -1.6 +31.9 +30.2

Bacterial homog. Agarose beads -1.3 +28.6 +27.3

XL-Q -0.9 +27.3 +26.5DEAE -1.4 +29.7 +28.3SP -1.5 +30.7 +29.0

E. coli a PES -2.0 +2.5 +0.5

S. cerveviseae b Q-Hyper Z -0.7 +18.4 +17.7

Mammaliancellsc

Glass -2.5 +20.9 +17.3

aTaken from (Gallardo-Moreno et al. 2002) , btaken from (Vergnault et al. 2004),ctakenfrom (Li and Logan 2004; Van Oss 1994).



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increased. These values keep constant by decreasing the pH down to 4 in diluted buffer

solution.

Table 7: Zeta potential values for beaded adsorbents.

Zeta potential (mV)

pH (-) 4 7

Cond. (mS/cm) ≤ 9 ~15 ≤ 9 ~15

Support type

Sepharose 4B -3.2a nd -2.0a ndQ Sepharose XL b

+27a

/ +18c

nd + 15a

/ +14c

+8d

DEAE Sepharosee +15a / +24c /+13d nd +8.7a / +21c /

+11d +6d

SP Sepharosee -14a / -29c nd -24a / -30c nd

Zeta potentials values for silica particles (Si-m) were reported as -36.5 mV by Li and Logan(Li and Logan 2004).nd: not determineda Own determinations b Experiments were performed in sodium acetate buffer at pH (1mS/cm) andsodium/potassium phosphate buffer at pH 7 (4 mS/cm).c Published values after Lin et al.(Lin et al. 2006)as performed in 50 mM sodium phosphate buffer pH 7.2 or values after Lin et al (Lin et al. 2003) in 10 mM KNO3 pH 7.2.d Zeta potential measurements according to Lin et al (Lin et al. 2006)in 50 mM phosphate buffer and sodium chloride as added salt.e Experiments were performed in 20 mM sodium/potassium phosphate buffer at pH 4 and pH 7.

Cell or cell debris particles are also known to bear surface charge. Table 8 depicts zeta

potential values for several model biomass types like intact yeast cells, yeast homogenate particles, and bacterial debris. It can be observed that intact yeast cells have negative zeta

potential values raging from∼-30 mV to∼-10 mV in salt solution from 1.0 to 100 mM,

respectively, at neutral pH. At lower pH (∼4) zeta potential values ranged from∼-18 mV

to ∼-2 mV. Biological particles originated by cell disruption have had a tendency to be

less negative (yeast debris∼-12 mV) or more negative (bacterial debris∼-30 mV) than

intact yeast and bacterial cells, respectively. This fact reflects both the influence of



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47

feedstock treatment and the biological nature of the feedstock (Brixius 2003; Lin et al.

2007).

Values reported here for zeta potential of biomass and process materials were obtained by ameta-analysis of the current literature and confirmed by own measurements. Special

emphasis was placed on conditions that are significant in industrial practice, like feedstock

loading (buffer conductivity≤ 2-9 mS·cm-1) and product elution (buffer conductivity≥ 15

mS·cm-1). Extremes of pH (4 and 7) were considered to evaluate to potential effect of pH

change on electrostatic interactions.

Table 8: Zeta potential values for biological particles.Zeta potential (mV)

pH (-) 4 7

Cond. (mS/cm) ~2-4 ~15 ~2-4 ~15

Biomass type

Intact yeast cells -7a / -7 b / -9c -2c -15a / -9 b / -21c -16c / -7d

Yeast homogenate -4a / -3d nd -12a / -14d -5d E. coli homogenate+ -10a / -5d nd -30a / -35d -22d

nd: Not determined. (+) Published values for intact E.coli cells are -17 at pH 4 and -27 at pH 7 in 50 mM phosphate buffer (Lin et al. 2006). Mammalian cells were reported to havezeta potential values~ -25 mV (Van Oss 1994).a Own measurements in 20mM sodium/potassium phosphate buffer. b Data from Lin et al.(Lin et al. 2006)c According to Kang et al. (Kang and Choi 2005)d Taken from Lin et al.(Lin et al. 2007)

2.1.5.5 Adhesion and interaction phenomena: free energy vs. distance profiles

Integration of the various existing interfacial forces between an adsorbent bead and a

biological particle (interaction) or between two biological particles (aggregation) can be

performed by calculating Energy (U) vs. distance (H) profiles. Figure 1 depicts such

interfacial energy curve for the adhesion of an intact yeast cell onto a DEAE Streamline™

bead. From this figure, it can be realised how different interfacial forces can contribute to



Results

48

cell-bead interaction. While LW and EL forces are attractive in this case, AB forces are

repulsive. The total energy profile obtained after application of the DLVO theory would

predict an infinite (primary) energy pocket where a cell would be irreversibly trapped in

close contact with the adsorbent bead. However, previous experimental findings haveshown that intact cell yeasts can be detached from adsorbent beads by applying an

increased shear stress to the system. Calculations based on the XDLVO theory better

explain this phenomenon by showing a secondary energy minimum having a finite

magnitude.

Figure 1: Interfacial free energy components as a function of distance for a DEAEfunctionalized adsorbent particle and an intact yeast cell in aqueous media: (— ) LW: (— )EL: (— ) AB. Total interaction energy profiles are shown according to the DLVO theory(— ) and the (— ) XDLVO theory.

In order to better elucidate the appropriateness of the XDLVO theory to predict microbial

adhesion within the frame of biochemical engineering systems, calculation were run with

several cell / support pairs. Figure 2 depicts the total energy vs. distance profiles for

selected agarose and non-agarose based materials and several biomass types. Adsorbent

beads suitable for expanded bed operation showed, in agreement with previous reports,



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49

strong interaction with intact cells. It is now clear that this interaction occurs at a distance

of 4-5 nm and within (secondary) energy wells between -200 kT for DEAE (taken as a

reference) and -400 kT for Q-Hyper-Z, a ceramic composite material. These findings can

explain why the utilisation of dynamic flow distribution and the introduction of denser particles can alleviate biomass adhesion to fluidised adsorbent: the increased shear /

hydrodynamic stress provide enough energy to detach cell particles from the (finite)

secondary minimum.

Other system behaved differently. The PES / bacteria pair, which is know as a strong

interacting system (Absolom et al. 1983), showed an infinite primary minimum. This is due

to the hydrophobic nature of the solid substrate and the low contribution of repulsive AB

forces. On the other hand, the mammalian / glass pair showed a moderate secondary energywell (-60 kT) occurring at 15-20 nm distance. This is also in agreement with hydrodynamic

limitations found during the purification of monoclonal antibodies onto porous glass cation

exchangers in the fluidised mode (Thommes et al. 1995).

Figure 2: Total interaction free energy profiles for several process systems according to theextended approach: (— ) DEAE/yeast cells, (— ) PES/bacterial cells, (— ) Q ceramic/yeastcells, and (— ) glass particles/mammalian cells.



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50

Interaction energy as a function of biomass type in the feedstock can be observed in Figure

3. Calculation performed for intact yeast cells, yeast homogenate, and bacterial homogenate

suggest that a much strong interaction would occur between the intact cell and the DEAE

Streamline adsorbent bead than with any of the two homogenates. This is in fullyagreement with experimental evidence reported earlier by Fernandez Lahore et al

(Fernandez-Lahore et al. 2000; Fernandez-Lahore et al. 1999). Additionally, from this

figure the effect of particle size on the overall energy vs. distance profile can be

understood. Lin et al. (Lin et al. 2003) have realised the importance of biological particle

size, besides the obvious electrostatic effects between two opposite charged spheres, during

biomass interactions in EBA. Both factors, in addition to the contribution of LW, AB, and

BR forces are nicely summarised in a single U vs. H curve.

Figure 3: Total energy vs. distance profiles for an anion-exchange (DEAE)chromatographic support and various types of biomass-derived particles. (— ) intact yeastcells; (— ) yeast homogenate; (— ) bacterial homogenate.



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51

Process operational parameters and process materials are of prime importance to biomass

adhesion effects. Figure 4 depict the energy vs. distance profiles for agarose based supports

in contact with intact yeast cells. Interaction of yeast cells with these adsorbent beads, as

judged by the depth of the energy pocket, can be ordered as follows:

Q XL(-370 kT) > DEAE (-200 kT) >> BASE (-12 kT)≈ SP (-10 kT)

The depth of the energy pocket correlates with the proximity of such interaction between

cells and adsorbent beads, as follows:

Q XL (4 nm) > DEAE (5 nm) > BASE (10 nm) > SP (20 nm )

The strongest and closest interactions predicted by the XDLVO theory in the mentioned

scale, therefore, fully correlates with previous work on biomass interaction and

hydrodynamics in expanded beds. In the same line of thought (Fernandez-Lahore et al.

2001), it has been reported that ionic strength operation windows could help in alleviating

hydrodynamic and sorption performance constraint during EBA operation with anion-

exchangers. Figure 5 shows energy vs. distance calculations for various buffer conditions

i.e. low vs. high pH and low vs. high conductivity within the range expected to occur

during real operations. Moreover, with ion-exchange operations it was found that an

increased conductivity reduced the depth of the energy pocket from -200 kT to – 40 kT.

Charge-masking effects and double layer compression mainly dominate this effect. The

influence of the pH, within the range 4 to 7, was only marginal for yeast / anion-exchanger

interacting pair. Calculations performed with experimental data gathered from CEX

materials and intact yeast cells revealed an opposite behaviour. The later showed the

development of a secondary energy well at low to very-low salt concentration in therunning buffer (data not shown). This situation could lead to unexpected biomass

interactions with materials known as “non-interacting” (SP) and with mobile phase

compositions that are not suspected to promote impaired hydrodynamic conditions.



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52

Figure 4 : The influence of the functional ligand on the total interfacial energy when anintact yeast cell and an agarose-based bead are the interacting bodies. (— ) DEAE, (— ) Q-XL,(— ) SP, (— ) BASE.

Figure 5: Energy vs. distance curves showing the influence of the buffer pH andconductivity on the interaction between an anion-exchange bead and an intact yeastcell.(— ) low conductivity pH 7,(— ) high conductivity pH 7, (— ) low conductivity pH 4,(•••) high conductivity pH 4. Low conductivity: 2 ms cm-1, High conductivity: 14mS cm-1.



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53

2.1.5.6 Aggregation phenomena: the cell to cell interface

As mentioned before, biomass adhesion kinetics recognises two main phases as revealed by

partitioning experiments (Fernandez-Lahore et al. 2000). The second, slow, biomass

concentration dependent phase was linked to cell-to-cell aggregation (homo-coagulation).Therefore, it is also important to study the interfacial free energy between two cell particles

to have a clear picture of biomass adhesion onto surfaces during bioprocessing.

Mathematical expressions derived for sphere-sphere contact were utilised. Figure 6 depicts

cell aggregation at pH 4 and 7. The figure also presents calculated profiles for low and high

salt concentrations at these two pH values. It can be observed that at low salt concentrations

-and with little influence of the pH value- the secondary energy pocket is almost inexistent.

At high salt concentration, however, the depth of the energy trap increases moderately (∼5-10 kT) due to the compression of the double layer at increased ion concentration in the

solution. Consequently, for particles repelling each other by charge-mediated effect the

probability of aggregation is higher than in diluted buffer. This situation is analogous to the

interaction between a (negatively charged) cation-exchanger bead and a (negatively

charged) cell particle, as mentioned before. Interaction effects of this kind, however, are

expected to have more impact on the retention of intact cells than on the adhesion of cell

debris since the size of the particles involved is higher in the first case. Moreover,aggregation might be worsened by the presence of bivalent ions since they were reported to

depress the monopolar electron-donor parameter of the surface tension. This would result in

depressing their mutual repulsion (Van Oss et al. 1987). According to these studies, the

calculated Hamaker constant was 1.4.10-21 for biomass aggregation.



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54

Figure 6 : Interfacial energy between two yeast cells as function of solution chemistry.(— ) 2 mS cm-1 pH 7, (•••) 14 mS cm-1 pH 7,(— ) 2 mS cm-1 pH 4,(— ) 14 mS cm-1 pH 4.

2.1.5.7 The energy pocket as predictor of process performance

A correlation between the magnitude and sign of the secondary energy pocket and standard

indexes employed to evaluate biomass adhesion onto fluidised adsorbent was established.

These indexes, as obtained by cell pulse experiments or partition experiments are known to

correlate with the quality of bed fluidization and sorption performance in EBA. This

correlation is depicted in Figure 7. Three main groups of data points can be observed:

a) A first group (U values > -20k T) showed almost complete cell transmition (CTI≥ 90%).

Process conditions represented by these points are not expected to create hydrodynamic

disturbances and thus, maximised sorption performance will be reached. This group is

represented by the cation exchangers in dilute buffer solutions, and the anion exchangers at

moderate-high salt containing buffers. The agarose-base material is also included here.

b) A second group (-20k T < U < -200 k T) showed a linear correlation with the celltransmition index, from 40% to 90%. Process conditions represented by this group require



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55

process optimisation for appropriate sorption performance. Interventionsvia operational

window optimisation or solution chemistry design are mandatory. In the worst cases,

material engineering could restore process performance. This group is mainly composed by

several anion exchangers operating in diluted buffer at pH 4 – 7 and by the cationexchangers in moderate-high salt containing buffers. This group also contain adsorbent

materials other than ion-exchangers (data not shown).

c) A third group was obtained at strongly negative energy pocket (≤ -300 kT) where cell

transmission was extremely reduced e.g. < 30%. The later situation is most commonly

associated with a complete bed collapse upon feedstock application. This group is

represented by strongly adhesive systems, especially when AEX brush-type composite

materials are employed in diluted buffer solutions or when DEAE supports are subjected tolong contact times.

The effect of hydrodynamic forces on the detachment of biological particles on

chromatographic supports and other process materials can be explained on the basis of the

finite value obtained for the calculated minimum of energy. A finite (secondary) minimum

is present at 4-5 nm distance between the interacting bodies, even in those cases where

strong biomass attachment is known to occur and to cause impaired sorption performance.Under such circumstances, detachment of adhering cells will be promoted upon applying

enough energy to overcome the energy pocket. Since interaction energies are proportional

to the particle radius, the effect of the mentioned energy secondary minimum is expected to

be more significant for larger particles. This is in agreement with the strong biomass

adhesion observed for intact yeast cells (4μm diameter) onto fluidised beads as compared

to cell debris (< 1μm diameter).

The surface energetics approach presented in this work can be useful in guiding process

developments. Calculations can be performed easily utilising a personal computer and

commercial software. This assists in finding conditions for reduced interaction and

aggregation with a minimum of experimental effort. Moreover, our approach can help in

the development of novel (less interacting) materials for direct capture applications. In a

recent publication, Kang and Choi (Kang and Choi 2005) have demonstrated the effect of

surface modification as a controlling factor in microbial adhesion. These authors, in



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56

agreement with this work, have also explained the interaction between microbial cells and

solid substrates on the basis of the XDLVO theory.

The surface energetic approach has a universal nature as predictor of process performancesince it is not restricted to the type of material, the nature / size of the biomass particles, and

the environmental conditions prevailing within the running phase. As such, it is not

restricted to process situations that are dominated by coulomb-type interactions. For

example, Gallardo-Moreno etal. (Gallardo-Moreno et al. 2002) have found a good

correlation between thermodynamic prediction and adhesion behaviour of Candida

parapsilosis to polystyrene.

It is worth to mention at this point that interactions other than the ones described here may

influence interaction between biological and/or polymeric particles. For example, steric

interaction may arise between a polymer-coated surface, which is the case for some

microbial and adsorbent surfaces. A crude feedstock may also contain variable amounts of

bridging cations or macromolecular polymers (Dainiak et al. 2002; Mattiasson et al. 1996).



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Figure 7: Correlation graph between the depth of the secondary energy pocket and the cellor partition transmission index (CTI). (• ) DEAE, (▲) Q- XL, (▼) Q- Hyper D, (■) SP,

(× ) Base.

2.1.6 Conclusions

A universal approach was developed to understand biomass adhesion to process supports,

with special reference to downstream processing systems where the direct sequestration of

targeted species is intended from the crude feedstock. Besides the influence of coulomb-

type interactions, this approach takes into account other forces so as to present a more

comprehensive visualisation of the underlying thermodynamic phenomena of adhesion.

This is conveniently performed by utilisation of energy-distance profiles. In this way, the

distance and strength of interaction can be explored for support-biomass interaction, as well

as, for cell-cell aggregation.

The LW interaction, which is predominantly attractive in microbial systems, was not

influenced by the ionic strength but both the range and magnitude of the EL interactions

decrease with increasing ionic strength due to shielding of surface charges. AB interactions

were found to be a function of the nature of the process solid phase onto which cell



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58

adhesion took place. As a consequence, depending on the liquid phase ionic strength and

the nature of the process material, a (finite) secondary minimum may exist allowing the

reversible capture of biological particles.

At the distance at which the energy pocket occurs, a correlation exists between the depth of

such energy minima and the degree of biomass entrapment as described by the “Cell

transmition index” and the “Cell partition index”. This correlation is valid for both cation

and anion exchangers under a variety of common operational conditions, which are relevant

to industrial practice. According to the XDLVO methodological approach interactions are

predicted to be alleviated by working within operational windows at moderate conductivity

values for AEX i.e. when employing diluted buffer for sample application. On the contrary,

high conductivity values might hamper CEX operations i.e. under elution conditions were

high salt concentration are commonly utilised. The evaluation of the complete range of

interfacial forces, as proposed here, represents a first step to global modelling. This would

further establish a link between shear / hydrodynamic effects and cell adhesion onto

process surfaces.

Calculations required are simple to produce and are based on two experimental

measurements that are contact angle measurements and zeta potential determinations. This

approach is useful for process design where reduced optimisation time would be required.

But particularly the method provides an excellent tool for novel material design. This in not

only restricted to the development of improved expanded bed adsorbents. Reactive solid

phases utilised in other direct-capture unit operations like finite bath systems, separations

based on magnetic particles, macroporous systems, and big-beads packed beds can be

tailored with assistance of the surface energetics approach.

2.1.7 Acknowledgements

This work was partially funded by the BID 1201/OC AR 649 PICT 08352 and the start-up

grant from Jacobs University [IUB] (2130-90050). The authors would like thank Dr. H. C.

van der Mei for valuable discussions.



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2.1.8 Nomenclature

A Hamker constant [J] / [kT]

CPI Cell partition index [-]

CTI Cell transmission index [-]

BR Born repulsion

DEAE Diethylaminoethyl-

EBA Expanded Bed Adsorption

∆ G Total interfacial free energy [mJ⋅m-2]

ho Distance at a closet approach [m]

H Distance [m]

IC Intact cells

IEX Ion exchange Chromatography

PES Plastic

R Radius [m]

Si-m Silica

SP Sulphopropyl-

T Temperature [K]

U Total interaction energy [kT]

Greek letters

γ Surface tension [mJ⋅m-2]

γ+ Electron-acceptor component of surface tension (Lewis acid) [mJ⋅m-2]

γ- Electron-donor component of surface tension (Lewis base) [mJ⋅m-2]

λ Characteristic decay length [m]

ε0 Permittivity of vacuum [J⋅m-1⋅V-2]



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εr Relative permittivity or dielectric constant for water [-]

κ Inverse of Debye length [m-1]

k Boltzmann constant [J⋅K -1]

ζ Zeta potential [V]

Superscripts

AB Acid-Base

DLVO Derjaguin, Landau, Verwey and Overbeek Theory

EL Electrostatic

LW Lifshitz-Van der Waals

TOT Total

XDLVO Extended DLVO Theory

Subscripts

c Cell particle

m Chromatographic matrix

l Liquid

s Solid

v Vapour

w Aqueous buffer



References

61

2.1.9 References

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Surface thermodynamics of bacterial adhesion. Appl Environ Microbiol 46(1):90-7.

Anspach FB, Curbelo D, Hartmann R, Garke G, Deckwer WD. 1999. Expanded-bedchromatography in primary protein purification. J Chromatogr A 865(1-2):129-44.

Bierau H, Hinton RJ, Lyddiatt A. 2001. Direct process integration of cell disruption and

fluidised bed adsorption in the recovery of labile microbial enzymes. Bioseparation

10(1-3):73-85.



23(2):179-230.Brixius PJ. 2003. On the influence of feedstock properties and composition on process

development of expanded bed adsorption. PhD thesis.

Camesano TA, Logan BE. 2000. Probing electrostatic interactions using atomic force

microscopy. Environ Sci Technol 34(16):3354-3362.

Dainiak MB, Galaev IY, Mattiasson B. 2002. Polyelectrolyte-coated ion exchangers for

cell-resistant expanded bed adsorption. Biotechnol Prog 18(4):815-20.




Fernandez-Lahore HM, Kleef R, Kula M, Thommes J. 1999. The influence of complex

biological feedstock on the fluidization and bed stability in expanded bed

adsorption. Biotechnol Bioeng 64(4):484-96.

Fernandez-Lahore HM, Lin DQ, Hubbuch JJ, Kula MR, Thommes J. 2001. The Use of Ion-

Selective Electrodes for Evaluating Residence Time Distributions in Expanded Bed

Adsorption Systems. Biotechnol. Prog. 17(6):1128-1136.

Feuser J, Walter J, Kula MR, Thommes J. 1999. Cell/adsorbent interactions in expanded

bed adsorption of proteins. Bioseparation 8(1-5):99-109.


Gomez-Garcia AC. 2002. Thermodynamic analysis of growth temperature

dependence in the adhesion of Candida parapsilosis to polystyrene. Appl Environ

Microbiol 68(5):2610-3.



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Ganeva V, Galutzov B, Teissie J. 2004. Flow process for electroextraction of intracellular

enzymes from the fission yeast, Schizosaccharomyces pombe. Biotechnol Lett

26(11):933-7.

GEHealthCare. 2001. Cost comparison: expanded bed adsorption (EBA) vs conventionalrecovery in the industrial scale processing of proteins. Application note

STREAMLINE expanded bed adsorption 18-1150-21 AA:1.

Henriques M, Gasparetto K, Azeredo J, Oliveira R. 2002. Experimental methodology to

quantify Candida albicans cell surface hydrophobicity. Biotechnol Lett 24:1111–

1115.

Hubbuch J, Thommes J, Kula MR. 2005. Biochemical engineering aspects of expanded bed

adsorption. Adv Biochem Eng Biotechnol 92:101-23.

Kang S, Choi H. 2005. Effect of surface hydrophobicity on the adhesion of S. cerevisiae

onto modified surfaces by poly(styrene-ran-sulfonic acid) random copolymers.

Colloids Surf B Biointerfaces 10(46(2)):70-7.

Li B, Logan BE. 2004. Bacterial adhesion to glass and metal-oxide surfaces. Colloids Surf

B Biointerfaces 36(2):81-90.

Lin DQ, Brixius PJ, Hubbuch JJ, Thommes J, Kula MR. 2003. Biomass/adsorbent

electrostatic interactions in expanded bed adsorption: a zeta potential study.


Lin DQ, Dong JN, Yao SJ. 2007. Target Control of Cell Disruption To Minimize the

Biomass Electrostatic Adhesion during Anion-Exchange Expanded Bed Adsorption.

Biotechnol Prog 23(1):162-7.




Lin DQ, Zhong LN, Yao SJ. 2006. Zeta potential as a diagnostic tool to evaluate the biomass electrostatic adhesion during ion-exchange expanded bed application.


Mattiasson B, Galaev I, Garg N. 1996. Polymer-shielded dye-affinity chromatography. J

Mol Recognit 9(5-6):509-14.

Mills AL, Herman JS, Hornberger GM, Dejesus TH. 1994. Effect of Solution Ionic

Strength and Iron Coatings on Mineral Grains on the Sorption of Bacterial Cells to

Quartz Sand. Appl Environ Microbiol 60(9):3300-3306.



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Northelfer F, Walter JK. 2002. A comparsion of STREAMLINE expanded bed adsorption

with the combined techniques of filtration and conventional fixed bed

chromatography for the capture of an Fc-fusion protein from CHO cell culture.

Application note streamline expanded bed adsorption 18(1144-87 AB):1.Ottewill RH, Shaw JN. 1972. Electrophoretic studies on polystyrene lattices. J Electroanal

Chem 37:133-142.

Sambrook J, Russell DW. 2006. The condensed protocols from Molecular cloning: a

laboratory manual. Cold Spring Harbor, N.Y: Cold Spring Harbor Laboratory Press.

v, 800 p. p.

Sharma PK, Rao KH. 2002. Analysis of different approaches for evaluation of surface

energy of microbial cells by contact angle goniometry. Adv Colloid Interface Sci

98(3):341-463.

Strevett KA, Chen G. 2003. Microbial surface thermodynamics and applications. Res

Microbiol 154(5):329-35.

Theodossiou I, Sondergaard M, Thomas ORT. 2001. Design of expanded bed supports for

the recovery of plasmid DNA by anion exchange adsorption. Bioseparation 10(1-

3):31-44.

Thommes J, Weiher M, Karau A, Kula M-R. 1995. Hydrodynamics and Performance in

Fluidized Bed Adsorption. Biotechnol Bioeng 48(4):367-374.

Van der Mei HC, Bos R, Busscher HJ. 1998. A reference guide to microbial cell surface

hydrophobicity based on contact angles. Colloids Surf B Biointerfaces 11(4):213-

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Van Oss CJ. 1994. Interfacial forces in aqueous media. New York: M. Dekker. viii,440p. p.

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2.2 Colloid deposition experiments as a diagnostic tool forbiomass attachment onto bioproduct adsorbent surfaces

Canan Tari1† , Rami Reddy Vennapusa2† , Rosa B. Cabrera2, and Marcelo Fernández-Lahore2.

1Department of Food Engineering, Izmir Institute of Technology, Urla, Izmir 35430,Turkey.2Downstream Processing Laboratory, Jacobs University, Campus Ring 1, D-28759,Bremen, Germany.† These authors contributed equally to the work.

2.2.1 Abstract

BACKGROUND: Detrimental processing conditions can be expected in any downstream

operation where direct contacting between a crude feedstock and a reactive solid phase is

supposed to occur. In this paper we have investigated the factors influencing intact yeast

cells deposition onto anion- and cation- exchangers currently utilised for expanded bed

adsorption of biotechnological products. The aim of this study was two-fold: a) To confirm

previous findings relating biomass deposition with surface energetics according to the

XDLVO theory; and b) To provide a simple experimental tool to evaluate biomassdeposition onto process surfaces.

RESULTS: Biomass deposition experiments were performed on automated workstation

utilizing a packed-bed format. Two commercial ion-exchangers intended for the direct

capture of bioproducts in the presence of suspended biological particles were employed.

Intact yeast cells in the late exponential phase of growth were selected as model bio-

colloids. Cell deposition was systematically evaluated as a function of fluid phase

conductivity and quantitatively expressed as a biomass deposition parameter (α).

CONCLUSION:α ≤ 0.15 was established as criteria to reflect negligible biomass adhesion

to the process support(s). Biomass deposition experiments further confirmed predictions

made on the basis of free interfacial energy calculationsas per the extended DLVO

approach.



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2.2.2 Introduction

Detrimental processing conditions can be expected in any downstream operation where

direct contacting between a crude feedstock and a reactive solid phase is supposed to occur.

This type of unit operations has the potential to combine solids removal, productconcentration, and partial purification in a single processing step. However, it is already

known that suspended biological particles will interact with adsorbent materials. In the

particular case of Expanded Bed Adsorption (EBA) interaction phenomena may lead to the

development of poor system hydrodynamics and therefore, impaired sorption performance

under real process conditions (Hubbuch et al. 2005). Biomass deposition would also result

in increased buffer consumption (Northelfer and Walter 2002).

The principles of colloid chemistry can be applied to explain biomass-adsorbent attachment

at the local (particle) level (Van Oss 1994). Biomass adhesion to process supports has the

potential to be strongly influenced by long-range electrodynamic Lifshitz – van der Waals

(LW) and electrostatic (EL) and short-range acid-base (AB) interfacial interactions. EL

interactions arise from the existence of overlapping double layers of counter-ions near

charged surfaces in aqueous media and are accessible by determination of the zeta

potential. LW and AB forces are experimentally accessiblevia contact angle measurement

with three diagnostic liquids.

Earlier studies on biomass-adsorbent interactions pointed out that interactions between

(positively charged) anion exchangers and (negatively charged) biological particles resulted

the most problematic system to deal with. Due to the obvious electrostatic nature of such

interaction, a single property of these interacting bodies i.e. the zeta potential has been

recently proposed for a better understanding and prediction of biomass-adsorbent

interactions (Lin et al. 2003; Lin et al. 2006). It is now understood that Coulomb-typeinteraction are predominant when the basic nature of the process material and the

characteristics of the microbial species / strains is kept similar. Moreover, charge effects are

only predominant in deposition systems where strongly charged materials are under

consideration. Therefore, a single measure like the particle zeta-potential cannot be

considered a universal approach to process / material design. Some studies have found a

better correlation between surface energy, calculated by the three liquid contact angle

method, and microbial adhesion on different solid supports at constant solution chemistry

(Li and Logan 2004).



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The mechanistic understanding of the transport and deposition of microbial cell onto

natural and process surfaces has significant interest in various environmental and

bioprocess situations. A better description of the factors controlling the transport of

biological particles is important for the appropriate design of direct contact downstreamoperations, as well as, for the development of novel adsorbent materials. Traditionally,

microbial deposition has been studied employing packed-beds. A population of biological

particles is introduced into such systems and the suspended cell or cell-debris effluent is

monitored as a function of process time. This type of experiments can provide useful and

quantitative information when assessing factors like cell size and shape, microorganisms

strain, growth phase, bead size, surface coatings, fluid velocity, and ionic strength on cell

deposition onto process media (Tufenkji 2007).

Mathematical models of microbial transport in porous media most commonly utilises the

advection-dispersion equation as derived by mass balance principles (Brown and Jaffe

2001; Rijnaarts et al. 1996). A common approach to evaluate biomass deposition in

laboratory packed-bed experiments employs the “clean-bed” filtration model or colloid

filtration theory (CFT). This model is valid for steady-state systems which are initially free

of biomass particles and where axial dispersion can be neglected ( Pe ≥ 20) (Unice and

Logan 2000). Within the CFT, mass transport phenomena are accounted by the “single-

collector contact efficiency” (η0) while the physicochemical phenomena related to biomass

attachment are reflected by the “attachment efficiency parameter” (α) (Redman et al. 2004).

At larger biomass loads,α values are controlled not only by cell-support interactions but

also by the amount of previously attached biomass particles. This implies that attached

biomass particles onto the process surface can effectively reduce deposition by a so called

collector “blocking” effect (Rijnaarts et al. 1996). On the other hand, increased biomass

attachment can result from cell-to-cell aggregation a phenomena known as system

“ripening” (Nascimento et al. 2006).

In this paper we have investigated the factors influencing intact yeast cells deposition onto

anion- and cation- exchangers currently utilised for expanded bed adsorption of

biotechnological products. These two systems represent examples of “interacting” vs. “non-

interacting” situations, which are relevant in industrial practice. The aim of this study was

two-fold: a) To confirm previous findings relating biomass deposition with surface



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Utilising experimental data from breakthrough of cells from packed beds the attachment

efficiency parameter (α) can be calculated asα = k d / k d,fav(Redman et al. 2004).



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72

2.2.4 Results and Discussion

2.2.4.1 Physicochemical properties of the cell particles / beaded adsorbents

The electrokinetic potential of the interacting particles e.g. the yeast cells vs. the beaded

adsorbents were studied as a function of fluid phase conductivity. Figure 1 depicts zeta

potential values for intact yeast cells, cation-exchange beads, and anion-exchange beads in

phosphate buffers of varying conductivities. The zeta-potential has been reported as a main

parameter affecting yeast cell deposition onto beaded adsorbents, particularly onto anion-

exchangers (Lin et al. 2006). Intact yeast cells, harvested at the late exponential phase of

growth, showed zeta-potential values≈ -25 mV at very low buffer concentration (0.7

mS.cm-1). At standard ion-exchange mobile phase composition e.g.∼20 mM phosphate pH

7.6, zeta-potential values were -18 mV. Lower zeta-potential values were observed with

increasing conductivity i.e. -6 mV at 34 mS⋅cm-1. A similar trend was observed when

studying the effect of mobile phase conductivity on the electrokinetic behaviour of the

cation-exchanger beads. SP Sepharose fragments were utilised for such studies in order to

avoid errors derived from the settling of the intact adsorbent particles. Lower zeta-potential

values obtained were -36 mV (0.7 mS⋅cm-1) while maximum values were -14 mV (34

mS⋅cm-1).

A second factor recognized to influence biomass deposition onto process surfaces is cell or

cell-debris size and shape (Hubbuch et al. 2006). In this study, both factors are kept

constant since only intact yeast cells (8μm diameter) of spherical shape were utilised as

model biomass.

Besides electrostatic forces (EL), electrodynamic Lifshitz – Van der Waals forces (LW) are

known to mediate biomass interactions. The LW interaction, which is predominantlyattractive in microbial systems, is not influenced by the ionic strength (Bos et al. 1999) but

both the range and magnitude of the EL interactions decrease with increasing ionic strength

due to shielding of surface charges. LW forces between intact yeast cells and agarose-based

material can be described by a Hamaker constant (A). The value for A, in this particular

system, was previously calculated as 0.34k T from contact angle measurements; details will

be published elsewhere. Obtained Hamaker constant value are in agreement with assumed

values for various microbial systems (Bos et al. 1999).



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The so-called acid-base (AB) forces are also included in the XDLVO approach (Van Oss

1994). AB interactions were found to be a function of the nature of the process solid phase

onto which cell adhesion took place. For agarose-based supports and yeast cells an average

ΔGAB value was calculated as +30 mJ⋅m-2, indicating the repulsive nature of the AB

component (Vennapusa et al. 2006). This value is valid at closest distance of approximation

between the interacting bodies (1.57Å).

Figure 1: Zeta potentials of intact yeast cells and adsorbent beads as a function of fluid phase conductivity at pH 7.6.▲ , intact yeast cells;■, SP beads; ●, DEAE beads.

2.2.4.2 Biomass deposition experiments

Deposition experiments were performed in an automated chromatographic system for

increase throughput and convenience of use. Figure 2 depicts the schematic illustration of

the chromatographic set up. In packed-bed systems, physical straining of bio-colloids is

considered to be significant on the basis of geometrical consideration when d p/dc > 0.05

(Rijnaarts et al. 1996). In the system under study in this work d p/dc ≈ 0.04 and thus physical

straining can be neglected. Although straining has been observed when d p/dc values were as

low as 0.002 (Tufenkji et al. 2004) experiments performed with the cation-exchange

material supported the previous assumption . No physical entrapment of the bio-colloids



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75

(a)

(b)

Figure 3: Typical experimental data as obtained from packed-bed experiments utilizingchromatographic beads as colloid collectors. Intact yeast cells were employed as a model.(a) Favorable deposition onto DEAE functionalized beads, (b) Unfavorable deposition ontoSP functionalized support. The arrows indicate (A) Cell pulse injection and (B) Columnregeneration with 0.5 mol L-1 NaOH.



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Employing the above described methodology, systematic studies were performed to

evaluate yeast cell deposition onto anion- and cation-exchangers. Figure 4a shows the

family of deposition curves obtained by variation of fluid phase conductivity when DEAE-

Streamline™ beads were utilised as collectors. These adsorbent beads are weak anionexchangers and thus they are positively charged. Results are presented as normalised

concentration (C/C0) vs. pore volumes. In order to calculate C/C0 absorbance data was

employed since cell concentration was linearly related to such measurement within the

concentration range involved in this study. The length of the biomass pulse, equivalent to∼

10 PV, was sufficient to produce a semi-complete breakthrough of suspended biological

particles i.e. the effluent cell concentration never reached C0. It can be observed that total

cell deposition took place at very-low to low conductivity values e.g. almost no cells were

detected when conductivity was≤ 2.0 mS⋅cm-1. An increased conductivity of the mobile

phase has allowed for a progressive increased in the number of cells leaving the system.

These results can be explained considering a predominant role of EL forces in a system

characterised by collectors and colloids harbouring opposite charges. Since other forces

were kept constant, as well as the colloid size, the only mechanism expected to govern

deposition is related to Coulomb-type effects. This is in agreement with previous studies

focusing on zeta-potential as a diagnostic parameter for biomass / support interactions (Lin

et al. 2006).

Similar experiments were performed utilising SP- Streamline™(negatively charged) beads.

The biomass breakthrough curves are presented in Figure 4b. As it can be observed from

this Figure, lower conductivity values in the fluid phase have resulted in negligible

deposition of cells onto the cation-exchange collectors. However, increased conductivity (≥

14 mS⋅cm-1) has promoted biomass deposition onto the cation-exchanger. This finding

might have an impact on bioprocess design since this material has been considered as “non-interacting” with particulate feedstock (Feuser et al. 1999). However, deposition of intact

yeast cells onto SP- Streamline™beads can be inferred from XDLVO calculations as

shown below. Practical consequences related to this behaviour during EBA capture of

bioproducts could arise during product elution i.e. since high conductivity buffers are

commonly employed, aggregative fluidization may develop resulting in a diluted product

fraction.



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Figure 4: Normalized cell-effluent concentrations plotted against pore volumes pumpedthrough the packed bed at different fluid phase conductivity values (pH 7.6). (a) DEAEyeast cells. (b) SP / yeast cells. × 0.66 mS cm-1; 2.00 mScm-1; 8.4 mScm-1 (5.5 mScm-1 in fig. b); 14.00 mS cm-1; 36 mS cm-1.



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2.2.4.3 Parameter calculation

Bio-colloid depositions experiments, as shown in Figure 4, depict cell breakthrough

behaviour compatible with collector blocking or cell release from the packed-bed system.

This is demonstrated by the fact that in most experiments the normalised cell concentration(C/C0) did not raise a steady-state value after the initial dispersive curve region. Therefore,

the initial clean bed C/C0 for each experiment was taken for parameter calculations. This

allowed the application of the colloid filtration theory which is valid under clean bed

conditions (Redman et al. 2004).

Table 1 present calculated values for both k d (s-1) and α (-) as a function of fluid phase

conductivity. k d,fav data corresponds to the experimental run performed with the DEAE-Streamline™beads as collectors under lowest conductivity (0.6 mS⋅cm-1).

Table 1: Calculated parameters from packed-bed experiments where chromatographicsupports were employed as cell collectors. Calculation were performed according to(Redman et al. 2004).

DEAE Streamline TM - Intact yeast

SP StreamlineTM

– Intact yeast

Conductivity( mS cm-1 ) C/C o k d α

0.66 0.003 0.246 1.002.0 0.006 0.211 0.8588.4 0.075 0.107 0.43514.0 0.244 0.058 0.23638.6 0.254 0.056 0.229

Conductivity( mS cm-1 ) C/C o k d α

0.66 0.654 0.017 0.0712.0 0.568 0.023 0.0955.5 0.519 0.027 0.11014.0 0.445 0.033 0.136

38.6 0.333 0.045 0.184



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Evidence is suggesting that simple models for calculatingα based on deposition in the

secondary energy minimum can result in accurate prediction of biomass attachment to

porous media (Tufenkji 2007). For the DEAE-Streamline™ / yeast system, α values

decreased from∼1 at very low conductivity to 0.23 at∼39 mS⋅cm-1

. On the other hand, for the SP-Streamline™/ yeast system,α values increased from 0.07 (∼0.6 mS⋅cm-1) to 0.18 (∼

39 mS⋅cm-1). As a referenceα = 1, has the meaning of complete cell deposition onto the

packed collectors. Figure 5 summarizes these results in a graphic form. Minimumα values

were obtained for the anion-exchanger system, which are nearly equivalent toα values

obtained for SP-Streamline™beads at 39 mS⋅cm-1. These results indicate that biomass

deposition experiments are an appropriate design tool to evaluate biomass deposition onto

process surfaces. On the basis of the preceding experimental evidence,α is proposed as adiagnostic parameter that provides information on biomass attachment onto process

surfaces. Applying the proposed methodology, changes inα can be effectively utilised to

monitor biomass-support interactions even in such cases where such interaction was

overlooked in the past (Feuser et al. 1999).

Figure 5: Changes in the attachment efficiency parameter (α) as a function of fluid phaseconductivity. Deposition of intact yeast cell was studied for () DEAE and ( ) SPchromatographic materials.



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2.2.4.4 Bio-colloid deposition in the secondary minimum

Figure 6 depicts total interfacial energy profiles as a function of the distance between two

interacting bodies (U vs. H) in aqueous media i.e. diluted buffer solutions. Calculations

were performed considering the role of LW, AB, and EL forces, as previously reported(Bos et al. 1999) by utilising data from contact angle measurement and zeta potential

determinations (Vennapusa et al. 2006). Therefore, the presented profiles are in accordance

to the extended DLVO approach. Since the radius of the chromatographic beads is much

higher than the radius of the intact yeast cell, total free energy was computed assuming a

plane-to-sphere geometry.

Figure 6a represents XDLVO energy profiles for the system where a DEAE-Streamline™

bead interacts with an intact yeast cell. It can be observed that a secondary energyminimum exists at a distance of ≈ 5nm, where deposition of the cell particle can occur. This

is essentially a reversible interaction that can be overcome by sufficient energy input for

example, in the form of shear or hydrodynamic stress. The magnitude (depth) of the energy

pocket, however, increases upon modification (reduction) of the liquid phase conductivity.

As a consequence, stronger deposition of cell particles is expected when working with

diluted buffers than when working with buffers / salt solutions with higher conductivities.

This situation is reflected by the biomass deposition experiments as presented in Figure 4a.Therefore, this kind of experiments can confirm the trends predicted by XDLVO

calculations. Both U vs. H calculations and deposition experiments are in full agreement

with the known biomass-interaction behaviour for DEAE-Streamline™(Fernandez-Lahore

et al. 2000; Fernandez-Lahore et al. 1999; Lin et al. 2001). Moreover, biomass deposition

experiments can offer a simple way to access interfacial phenomena in aqueous media.

These phenomena have relevance from the bioprocess point of view and have important

consequences for appropriate process optimisation and material design.



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Figure 6: Calculated XDLVO total interaction energy as a function of separation distance.a) DEAE / yeast cells b) SP / yeast cells. A family of curves representing variations in theconductivity value of the fluid phase is shown (— ) 2 mS cm-1; (— ) 4 mS cm-1; (— ) 9.55mS cm-1; (— )15.1 mS cm-1; (— ) 34 mS cm-1).



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Figure 7: Correlation graph between the attachment efficiency parameter (α) and the totalinteraction energy according to the XDLVO approach.

Besides biomass deposition, as expressed by the deposition parameter (α), the cell breakthrough profiles observed in Figure 4 might indicated that a blocking phenomenon is

also occurring in the systems under study. Blocking refers to the fact that cells which are

already attached to the solid support can interfere with the attachment of further cells being

contacted with the adsorbent beads. This phenomenon, usually accounted by the so called

excluded area parameter (β) has important environmental implications (Bolster et al. 2001).

During direct capture of bioproducts, due to the presence of much higher concentration of

biomass (∼8 % wet weight) in contact with the beaded adsorbents, blocking can besupposed to play a less significant role. Therefore, modeling approaches have been kept

simple enough so as to provide a single parameter (α), which reflects biomass attachment

as an important event having practical consequences for the performance of a direct

capturing unit operation.

Biomass multilayer formation would also occur at long contact time and / or high biomass

concentration, which is not the case for the biomass deposition experiment as described



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84

here. This phenomenon could be more important in cases where cell-to-cell aggregation or

“ripening” is favored, like during hydrophobic interaction chromatography. Understanding

of cell-to-cell aggregation would require independent experimental methods to be evaluated

(Ramachandran and Fogler 1998).

2.2.5 Conclusions

Biomass deposition experiments were performed in an automated workstation utilizing a

packed-bed format and intact yeast cells in the late exponential phase of growth as biomass

model.

Under carefully controlled experimental conditions, removal of biomass particles onto

chromatographic collectors was assumed to be dependent on a) mass transfer i.e. the

transfer of a biological particle from the bulk liquid phase to the adsorbent bead and b) the

capture of a biological particle onto an adsorbent bead by interfacial forces. Straining was

neglected since the size of the biomass-derived particles is much smaller than the process

beads. Detachment was also supposed to be insignificant under laminar flow conditions.

The description of “aggregation” (cell-to-cell), which implies multilayer adhesion, was

omitted since this phenomenon takes place at high biomass concentrations and long contact

times.

Cell deposition was systematically evaluated as a function of fluid phase conductivity and

quantitatively expressed as a biomass deposition parameter (α). Deposition onto

commercial anion-exchanger beads was observed to increase with decreasing conductivity

values in the mobile phase. The opposite behavior was observed when cation-exchange

beads were utilized as collectors in the packed-bed system. In both cases, experimental

deposition studies confirmed predictions based on the free energy of interaction accordingto the XDLVO theory. Coulomb-type interactions were dominating since EL forces are

affected by the ionic strength of the aqueous media surrounding the interaction bodies.

Other forces, which are relevant to the evaluation of biomass deposition, were kept

constant. The evaluation of LW and AB forces is mandatory when comparing microbial

strains and / or process materials apart from the model system employed in this work.



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86

d p Diameter of yeast cells [m]

EBA Expanded bed adsorption

EL Electrostatic interaction

H Separation distance [m]

k d Deposition rate coefficient [s-1]

k d fav Deposition rate coefficient for favorable deposition [s-1]

L Length of column [m]

PV Pore volume [ml]

P e Peclet number [-]

Re Reynolds number [-]

SP Sulphopropyl-

U Superficial fluid velocity [ms-1]

U Total interaction energy [kT]

XDLVO Extended DLVO

Greek letters

ε Porosity [-]

α Attachment efficiency parameter [-]

ο η Single collector contact efficiency [-]



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2.2.8 Referances

Bolster CH, Mills AL, Hornberger GM, Herman JS. 2001. Effect of surface coatings, grain

size, and ionic strength on the maximum attainable coverage of bacteria on sand

surfaces. J Contam Hydrol 50(3-4):287-305.Bos R, Van der Mei HC, Busscher HJ. 1999. Physico-chemistry of initial microbial


23(2):179-230.

Brown DG, Jaffe PR. 2001. Effects of Nonionic Surfactants on Bacterial Transport through

Porous Media. Environ Sci Technol 35(19):3877-3883.


The influence of cell adsorbent interactions on protein adsorption in expanded beds.J Chromatogr A 873(2):195-208.








26(11):933-7.

Hubbuch JJ, Brixius PJ, Lin DQ, Mollerup I, Kula MR. 2006. The influence of

homogenisation conditions on biomass-adsorbent interactions during ion-exchange

expanded bed adsorption. Biotechnol Bioeng 94(3):543-53.

Hubbuch JJ, Thommes J, Kula MR. 2005. Biochemical engineering aspects of expanded

bed adsorption. Adv Biochem Eng Biotechnol 92:101-23.

Li B, Logan BE. 2004. Bacterial adhesion to glass and metal-oxide surfaces. Colloids Surf

B Biointerfaces 36(2):81-90.









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Nascimento AG, Totola MR, Souza CS, Borges MT, Borges AC. 2006. Temporal and

spatial dynamics of blocking and ripening effects on bacterial transport through a

porous system: A possible explanation for CFT deviation. Colloids Surf B

Biointerfaces 53(2):241-244.

Northelfer F, Walter JK. 2002. A comparison of STREAMLINE expanded bed adsorption

with the combined techniques of filtration and conventional fixed bed

chromatography for the capture of an Fc-fusion protein from CHO cell culture.

Application note STREAMLINE expanded bed adsorption 18 1144-87 AB.

Ottewill RH, Shaw JN. 1972. Electrophoretic studies on polystyrene lattices. J Electroanal

Chem 37:133-142.

Ramachandran V, Fogler HS. 1998. Multilayer Deposition of Stable Colloidal Particles

during Flow within Cylindrical Pores. Langmuir 14(16):4435-4444.

Redman JA, Walker SL, Elimelech M. 2004. Bacterial Adhesion and Transport in Porous

Media: Role of the Secondary Energy Minimum. Environ Sci Technol 38(6):1777-

1785.

Rijnaarts HHM, Norde W, Bouwer EJ, Lyklema J, Zehnder AJB. 1996. BacterialDeposition in Porous Media Related to the Clean Bed Collision Efficiency and to

Substratum Blocking by Attached Cells. Environ Sci Technol 30(10):2869-2876.

Tufenkji N. 2007. Modeling microbial transport in porous media: Traditional approaches

and recent developments. Adv Water Resour 30(6-7):1455-1469.

Tufenkji N, Elimelech M. 2004. Correlation Equation for Predicting Single-Collector

Efficiency in Physicochemical Filtration in Saturated Porous Media. Environ Sci

Technol 38(2):529-536.Tufenkji N, Miller GF, Ryan JN, Harvey RW, Elimelech M. 2004. Transport of

Cryptosporidium Oocysts in Porous Media: Role of Straining and Physicochemical

Filtration. Environ Sci Technol 38(22):5932-5938.

Unice KM, Logan BE. 2000. Insignificant role of hydrodynamic dispersion on bacterial

transport. J Environ Engin 126(6):491-500.

Van Oss CJ. 1994. Interfacial forces in aqueous media. New York: M. Dekker. viii,440 p.



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Vennapusa RR, Cabrera R, Ganeva V, Fernandez-Lahore HM. 2006. Direct capture from

electro-permeabilized yeast cells on expanded beds: a biomass-adsorbent interaction

study via surface energetics. Book of abstracts, 6th European Symposium on

Biochemical Engineering Science.



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2.3 Surface energetics to assess biomass attachment ontohydrophobic interaction adsorbents in expanded beds

Rami Reddy Vennapusa1, Canan Tari2, Rosa Cabrera1, and Marcelo Fernandez-Lahore1*

1Downstream Processing Laboratory, Jacobs University gGmbH, Campus Ring 1, D-28759, Bremen, Germany.2Department of Food Engineering, Izmir Institute of

Technology, Urla, Izmir 35430, Turkey.

2.3.1 Abstract

Cell-to-support interaction and cell-to-cell aggregation phenomena have been studied in a

model system composed of intact yeast cells and Phenyl-Streamline adsorbents. Biomass

components and beaded adsorbents were characterized by contact angle determinationswith three diagnostic liquids and zeta potential measurements. Subsequently, free energy of

interaction vs. distance profiles between interacting surfaces was calculated in the aqueous

media provided by operating mobile phases. The effect of pH and ammonium sulphate

concentration within the normal operating ranges was evaluated. Calculation indicated that

moderate interaction between cell particles and adsorbent beads can develop in the presence

of salt. Cell-to-cell aggregation was suspected to occur at high salt concentration and

neutral pH. Predictions based on the application of the XDLVO approach were confirmed by independent experimental methods like biomass deposition experiments and laser

diffraction spectroscopy. Understanding biomass attachment onto hydrophobic supports

can help in alleviating process limitations normally encountered during expanded bed

adsorption of bioproducts.



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2.3.2 Introduction

Expanded Bed Adsorption (EBA) has been proposed as anintegrative downstream


feedstock e.g. a cell containing fermentation broth. This unit operation has the potential to

combine solids removal, product concentration, and partial purification in a single

processing step. The application of EBA implies, however, that intact cell particles or cell

debris present in the feedstock will interact –in a minor or larger extent- with fluidized



sorption performance under real process conditions. Moreover, biomass interaction would

result in increased buffer consumption in order to remove and wash away sticky biological

particles. Biomass components can also mask binding sites thus reducing their availability

to the targeted species. These phenomena i.e. decreased sorption performance and buffer

consumption is detrimental to cost-efficient processing utilizing expanded bed adsorption

(Fernandez-Lahore et al. 1999; Lin et al. 2001).

Previous studies on biomass-adsorbent interactions were restricted to simple diagnostic

tests to determine the extent of cell –or cell debris- attachment to the desiredchromatographic supports (Feuser et al. 1999). More recently, a single property of the

suspended biological particle i.e. the zeta potential has been proposed for a better

understanding and prediction of biomass-adsorbent interactions during expanded bed

adsorption. Since then a number of studies has been developed to illustrate the usefulness

of this approach when adsorption is performed onto anion-exchangers (Lin et al. 2003; Lin

et al. 2006). Such systems are obviously dominated by Coulomb-type interactions and

therefore, non-electrostatic interactions are anticipated to play a minor role (Vergnault et al.2007).

Experimental evidence gathered by many authors has addressed the importance of non-

electrostatic forces for biomass adhesion to process surfaces in the broader context

provided by a group of systems of technical and environmental relevance. For example,

hydrophobic interaction as measured by partition tests has been proposed as a generalized

assay to measure adhesion-potential of bacteria to low-energy surfaces (Stenstrom 1989).Complementarily, differences in the hydrophobic surface characteristics of bacterial strains



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were revealed by hydrophobic interaction chromatography (Smyth et al. 1978). Recently,

acid-base interactions have been employed to understand yeast deposition onto chemically

modified substrates (Kang and Choi 2005). However, very little is known on biomass

attachment onto chromatographic materials like hydrophobic interaction media (HIC) under

real downstream process conditions. The mentioned chromatographic mode represents a

widely utilized industrial operation (Mahn and Asenjo 2005), which is amenable for direct

sequestration of bioproducts. Since sorption performance limitations were already observed

due to biomass interference during HIC-based EBA, a better understanding and control of

such phenomena is needed (Smith et al. 2002).

A more comprehensive approach to understand biomass deposition onto chromatographic

supports has been proposed by utilizing principles of colloid theory to explain biomass-

adsorbent attachment at the local (particle) level (Vennapusa et al. 2008). This approach is

based on extended DLVO calculations performedvia experimentally determination of

contact angles and z-potential values for the interacting surfaces or particles. The

comprehensive method takes into account several types of possible interaction forces i.e.

Lifshitz-Van der Waals (LW) and acid-base (AB) and, therefore, it is not limited to those

purely electrostatic in nature (EL). Biomass adhesion behavior onto chromatographic beads

predicted on the basis of XDLVO calculations was validated by independent biomassdeposition experiments (Tari et al. 2008).

The aim of this paper was to contribute to a deeper understanding of biomass-adsorbent

interactions to further open the pave for optimized EBA processing in industry. Studies

targeted biomass adhesion to hydrophobic interaction materials which have not been

extensively studied so far. The physicochemical properties of biomass-derived material,

taken as colloidal particles, vs. the physicochemical properties of the adsorbent beads,taken as a process surface, were determined indirectlyvia contact angle and zeta potential

measurements. Subsequently, total interfacial interaction energy values were calculated as a

function of surface distance in aqueous media e.g. process buffer. Cell-to-support

interactions and cell-to-cell aggregation phenomena were independently confirmed by

colloid deposition experiments and laser diffraction spectroscopy, respectively.



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2.3.3.1 Materials

Chromatographic matrices (Phenyl Sepharose FF, high substitution; Phenyl Streamline) andcolumns (Tricorn 5/50) were purchased from GE Health Care (Munich, Germany).α-

bromonaphtalene and formamide were obtained from Fluka (Buchs, Switzerland). Water

was Milli-Q quality. All other chemicals were analytical grade.

2.3.3.2 Generation of biomass

Yeast cells (Saccharomyces cerevisiae ) wild strain was utilized. Five ml of 24 h culture

were inoculated in 500 ml of 3.5 % (w/v) YES medium (yeast extract with supplements of yeast extract, 5 g l-1; glucose, 30 g l-1; 225 mg l-1 adenine, histidine, leucine, uracail and

lysine hydrochloride) and grown at 30oC. Cells are harvested at late exponential phase by

centrifugation, and washed three times with 10mM phosphate buffer solutions, as

previously described (Ganeva et al. 2004). Cells were employed immediately after

preparation for further experimental measurements or routines.


Preparation of intact yeast cells for contact angle measurements was performed as

described (Henriques et al. 2002). To evaluate the effect of pH, washed cells were

suspended to 10% (w/v) in 20mM phosphate buffer, pH 7or 50mM sodium acetate buffer,

pH 4 and to evaluate the effect of salt concentration, biomass was suspended in 20mM

phosphate buffer (pH 7) and 50mM sodium acetate buffer (pH 4) containing added

ammonium sulphate (0.2, 0.4, 0.8, 1.2, 1.6 and 2.0M). Cells were equilibrated in the

appropriate buffer condition and the suspension subsequently poured onto agar platescontaining 10% glycerol and 2% agar-agar. The plate was allowed to dry for 24-36 hours at

room temperature on a properly leveled surface free from dust. Salt crystallization was

avoided. Agar plates without cell spreads were utilized as control.

Contact angles were measuredas per the sessile drop method (Sharma and Rao 2002)

utilizing a commercial goniometric system (OCA 20, Data Physics instruments GmbH,

Filderstadt, Germany). The three diagnostic liquidsα-bromonaphtalene, formamide, and



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water were employed (Bos et al. 1999). All the measurements were performed in triplicate

and at least 20 contact angles per samples were measured.

Contact angle determination on buffer-equilibrated chromatographic beads was performed

utilizing the same physicochemical conditions and experimental procedures described for

cell particles. Previous to pouring onto the agar plates, matrix beads were frozen in liquid

nitrogen and crushed mechanically. Crushing efficiency was assessed by microscopic

examination and particle size determination so as to assure particle fragment diameters≤ 10

μm. Phenyl Sepharose (high-sub) was utilized. Square pieces of the agar supported

chromatographic bead fragments were utilized for measuring contact angles.

2.3.3.4 Zeta potential determination

Zeta-potential measurements were performed with a ZetaSizer Nano-ZS (Malvern

instruments, Worcestershire, United Kingdom), as previously described (Vennapusa et al.

2008). Zeta-potential values were gathered employing biomass pretreated as described

before (under 2.3.3.3) and utilizing the same buffers utilized for contact angle

determination.

Zeta-potential values for crushed and equilibrated chromatographic beads were calculated

from the electrophoretic mobility data according the Smoluchowski’s equation (Ottewill

and Shaw 1972). Data was gathered under identical buffer compositions as shown for

biomass related determinations.

2.3.3.5 Particle size determination and cell aggregation behavior

Particle size determinations and cell aggregation studies were performed by laser diffraction employing a MasterSizer 2000, hydro 2000 G (Malvern instruments,

Worcestershire, United Kingdom), according to manufacturer instructions. Cell aggregation

was studied as a function of pH and ammonium sulphate concentration utilizing the buffers

systems already described. For each condition, kinetic studies were performed within a time

interval of 60 minutes (Voloshin et al. 2005). Measurements were performed utilizing cell

suspensions having an optical density≈ 0.1 for better reproducibility.



Results

95

Visual inspection of aggregate formation was performed with a confocal laser scanning

microscope, equipped with argon and helium/neon mixed gas laser with excitation

wavelengths of 488 or 543 nm (LSM 510, Carl Zeiss, Oberkochen, Germany). Washed

yeast cells in 20 mM phosphate buffer (pH 7) or buffered 1.6 M ammonium sulphate

solution were mounted on glass slides and observed. Scans at a resolution of 1024 x 1024

pixels were taken in the line-averaging mode. Micrographs were stored in LSM format

(Carl Zeiss LSM Image Browser).

2.3.3.6 Bio-colloid deposition experiments

Biomass deposition experiments were performed automatically employing an ÄKTA

Explorer 100 system (GE Health Care, Munich, Germany) as previously described (Tari etal. 2008). These experiments were run by introducing a population of yeast cells particles is

introduced into a system composed of collector (adsorbent) beads; the suspended biomass

effluent is monitored as a function of process time. This type of experiments can provide

useful and quantitative information when assessing factors like cell size and shape,

microorganisms strain, growth phase, bead size, surface coatings, fluid velocity, and ionic

strength on cell deposition onto process media (Tari et al. 2008). A common approach to

evaluate biomass deposition in laboratory packed-bed experiments employs the “clean-bed”

filtration model (CBFM). In this case, mass transport phenomena are accounted by the

“single-collector contact efficiency” (η0) while the physicochemical phenomena related to

biomass attachment are reflected by the “attachment efficiency parameter” (α).

Streamline Phenyl materials (high-sub) were packed in commercial chromatographic

columns (5 mm internal diameter, 50mm length). The quality of the packing was evaluated

by residence time distribution analysis employing 1% acetone as tracer (Bak and Thomas

2007). Biomass deposition studies were done by injecting a 4 ml biomass pulse (OD @ 600

nm ≈ 0.8 AU). Experiments were performed utilizing 20 mM phosphate buffer pH 7 or 50

mM acetate buffer pH 4. Buffers contained various amounts of ammonium sulphate as

added salt (0.0, 0.4, 0.8, 1.2, 1.6, 2.0 M). The operational flow rate was 76.4 cm.h-1.

Particle breakthrough curves were obtained by monitoring the effluent suspensions at 600

nm. On the basis of such data, the biomass deposition parameter (α) was calculated

(Redman et al. 2004). Biomass deposition experiments were performed in triplicate and

showed to be reproducible within ± 20%.



Results

96

2.3.3.7 Energy-distance profile calculations


expressed in terms of the extended DLVO theory as:

ABmwc

ELmwc

LW mwc


where UXDLVO is the total interaction energy in aqueous media, ULW is the LW interaction

term, and UEL is the EL interaction term. The subscriptm is utilized for the

chromatographic matrix (adsorbent bead), w refers to the watery environment, and c to the

colloidal (cell) particle. A third short-range (≤ 5 nm) Lewis AB term is included to account

for “hydrophobic attractive” and “hydrophilic repulsive” interactions (Van Oss 2003).

Material surface energy parameters (tensions) can be calculated from contact angle

measurements utilizing three diagnostic liquids, according to (Van Oss 1994). In turn, this

data can be employed to evaluate the free energy of interaction between two defined

surfaces (ΔGLW and ΔGAB). ΔG represents here the interaction energy per unit area

between two (assumed)infinite planar surfaces bearing the properties of the adsorbent bead

and the cell (interaction) or two cells (aggregation), respectively. Interaction between anyof these two surfaces are evaluated at a closest distance of approximation (h0 ≈ 0.158 nm)

(Bos et al. 1999). When integrated into mathematical expressions accounting the geometric

constraints existing between two interacting bodies,ΔG values can be utilized to calculate

the corresponding energy-distance profile (U vs. H). Details of this procedure were

published (Bos et al. 1999; Vennapusa et al. 2008).ΔGLW are also related to the Hamaker

constant, as follows:

LW Gh A Δ−= 2012π (2)

UEL energy-distance profile can be calculated, assuming either plate-sphere or sphere-

sphere geometry, upon experimental determination of particle zeta potential values. Zeta

potential values are measured by electrophoretic mobility experiments (Vennapusa et al.

2008). Calculations were performed employing a commercial software package (GraphPad

Prism, GraphPad Software Inc., San Diego, CA, USA).



Results

97

2.3.4 Results and discussions

2.3.4.1 Contact angle measurements and surface energy components

The diagnostic liquids water, formamide, andα-bromonaphtalene were employed tomeasure contact angles onto homogeneous lawns of the materials under study i.e. intact

yeast cells or crushed Phenyl-Sepharose beads. The sessile drop technique was employed.

The utilization of the agar plate method assured that contact angle values were obtained for

the mentioned materials in the hydrated state. Diagnostic liquids were chosen to have a

higher surface tension than the sample materials so as to allow for stable drop formation

and accurate contact angle determination. Both materials were carefully equilibrated with

either 20 mM phosphate buffer (pH 7) or 50 mM acetate buffer (pH 4), which are bufferscommonly encountered as mobile phases during hydrophobic interaction chromatography

(HIC). Since conditions for binding proteins and macromolecules onto this particular

chromatographic media are usually found at increased concentrations of ammonium

sulphate i.e. within the range 0.2 - 2.0 M, this salt was included during sample preparation.

Therefore, contact angles with three different liquids were performed as a function of pH

and salt concentration so as to evaluate material(s) properties within the normal HIC

operational range.

Table 1 summarizes the contact angle values obtained after measurements performed onto

homogeneous layers of intact yeast cells at pH 7 and pH 4. The agar plate technique

utilized allowed the measurement of contact angles under the assumption that only bound

water is present in the sample materials. Irrespective of pH (phosphate buffer pH 7 vs.

acetate buffer pH 4) and salt concentration (the ammonium sulphate concentration

increased from 0 to 2 M in the corresponding buffer solution), data gathered for contact

angles measured with both water and formamide overall showed low and nearly constant

values. Average values for water were≈ 10 and for formamide≈ 12. This indicates the very

hydrophilic nature of the samples. On the contrary, contact angles values gathered withα-

bromonaphtalene decreased from≈ 54 to ≈ 30 and from≈ 46 to ≈ 30 at pH 7 and pH 4,

respectively, upon addition of salt. A more progressive decrease in the contact angle values

was observed -as a function of salt concentration- at pH 7 than at pH 4. In the later case,

values for contact angles at varying salt concentrations tended to keep a constant level (≈

30) a condition which differentiates from the contact angle measured in plain buffer



Results

98

solution (≈ 46). This indicates that a non-polar liquid can be employed to discriminate

between biomass types or conditions in relation to surface hydrophobic character (Butkus

and Grasso 1998).



Results

100

Table 2 shows contact angle values obtained by performing measurements onto layered

fragments (< 10µm) of the hydrophobic interaction media, Phenyl-Sepharose. This method

was utilized since for soft gel particles other approaches e.g. the capillary raise method are

difficult to implement. Moreover, measurements onto layered materials showed good

reproducibility i.e within ±10% in triplicate measurements (Table 2). As described with

biomass, a range of conditions was explored. At pH 7 contact angle values were≈ 6-7 for

water and ≈ 8-11 for formamide, irrespective of salt concentration. On the other hand, a

step change in the contact angle withα-bromonaphtalene from≈ 48 (no salt) to≈ 30 (0.2 –

2.0 M ammonium sulphate) was noticed. At pH 4 recorded contact angle values were≈ 7-8

with water and≈ 9-10 with formamide but observed values withα-bromonaphtalene were

progressively reduced from≈ 36 (no salt) to≈ 22 (2.0 M ammonium sulphate). As a whole,these results stressed the known hydrophilic nature of the chromatographic beads, which

are composed by an agarose backbone. Contact angles values observed with the apolar

liquid also indicate an increased hydrophobic character in the presence of ammonium

sulphate.



R e s u l t s

1 0 1

T a b l e 2 : C o n t a c t a n g l e v a l u e s

f o r P h e n y l - S e p h a r o s e p a r t i c l e s

i n 2 0 m

M p h o s p h a t e

b u f f e r p H

7 , 5 0 m

M a c e t a t e

b u f f e r p H

4 a s a

f u n c t i o n o f

s a l t c o n c e n t r a t i o n .

( N H 4 ) 2 S O 4

( M )

W

a t e r ( ◦ )

F o r m a m

i d e

( ◦ )

α - B r o m o n a p h t e l e n e

( ◦ )

p H 7

p H 4

p H 7

p H 4

p H 7

p H 4

0 . 0

6 . 0 ± 1 . 0

7 . 0 ± 1 . 0

1 0 . 0

± 1 . 0

9 . 0 ± 1 . 0

4 8 . 0 ± 4 . 8

3 6 . 0 ± 3 . 5

0 . 2

6 . 0 ± 1 . 0

7 . 3 ± 0 . 5

8 . 0 ± 1 . 0

1 0 . 0 ± 1 . 0

2 8 . 0 ± 1 . 0

2 8 . 5 ± 0 . 5

0 . 4

6 . 0 ± 1 . 0

8 . 0 ± 1 . 0

8 . 0 ± 1 . 0

1 0 . 0 ± 1 . 0

2 3 . 7 ± 2 . 5

2 5 . 0 ± 2 . 2

0 . 8

7 . 0 ± 1 . 0

7 . 4 ± 0 . 5

1 1 . 0

± 1 . 0

9 . 0 ± 1 . 0

3 0 . 7 ± 3 . 1

2 3 . 0 ± 1 . 0

1 . 2

7 . 0 ± 1 . 0

7 . 0 ± 1 . 0

1 0 . 0

± 1 . 0

1 0 . 0 ± 1 . 0

2 4 . 0 ± 2 . 5

2 1 . 0 ± 1 . 0

1 . 6

6 . 0 ± 1 . 0

7 . 7 ± 0 . 5

8 . 0 ± 1 . 0

9 . 0 ± 1 . 0

3 0 . 3 ± 3 . 0

2 2 . 3

± 1 . 0

2 . 0

7 . 0 ± 1 . 0

8 . 0 ± 1 . 0

1 1 . 0

± 1 . 0

1 0 . 0 ± 1 . 0

3 2 . 0 ± 3 . 5

2 3 . 6 ± 1 . 9



Results

102

Global analysis of contact angle data suggests a decrease in the contact angle values, as a

function of ammonium sulphate concentration, measured withα-bromonaphtalene for cells

and chromatographic beads. Contact angle values obtained for Phenyl-Sepharose with

water and formamide were nearly constant irrespective of salt concentration. On the other hand, contact angles determined with the later two diagnostic liquids showed a trend to

decrease when yeast cells were tested in the presence of salt

Experimental contact angle determinations were utilized to calculate surface energy

parameters for both biomass and chromatographic media according to the acid-base

approach (Bos et al. 1999). Calculated parameters reflect the contribution of the various

energy components i.e. Lifshitz-van-der-Waals and Acid-base (electron-acceptor, electron-

donor) to the total surface energy of a defined material. Table 3 depicts the surface energycomponents (γ) calculated for layered intact yeast cells as a function of pH (7 and 4) and

ammonium sulphate concentration (0 – 2.0 M). As a general trend it was observed thatγLW

increased (e.g. from 28 mJ⋅m-2 to 38 mJ⋅m-2 at pH 7 and from 32 mJ⋅m-2 to 39 mJ⋅m-2 at pH

4) whileγAB decreased (e.g. from 30 mJ⋅m-2 to 18 mJ⋅m-2 at pH 7 and from 25 mJ⋅m-2 to 18

mJ⋅m-2 at pH 4) as salt concentration was increased. Table 4 shows surface energy

components for crushed chromatographic media as a function of pH and salt concentration,

as before. At pH 7,γLW increased from 31 mJ⋅m-2 (no salt) to 39 mJ⋅m-2 (0.4 - 2.0 M

ammonium sulphate) whileγAB decreased from 28 mJ⋅m-2 (no salt) to 17 mJ⋅m-2 (2.0 M

ammonium sulphate). At pH 4 a similar trend was noticed:γLW increased from 36 mJ⋅m-2

(no salt) to 41 mJ⋅m-2 (1.2 - 2.0 M ammonium sulphate) whileγAB decreased from 21 mJ⋅m-

2 (no salt) to 15 mJ⋅m-2 (2.0 M ammonium sulphate). As observed from Table 3 and 4, the

parameter Δ Giwi took always values +23-27 mJ⋅m-2 reflecting the hydrophilic nature of the

yeast cells and the chromatographic beads. For comparison, the Δ Giwi of hydrophilic

repulsion for Dextran T-150 is +41.2 mJ⋅m-2 (Van Oss 2003). Concerning the materials

acid-base character, particularly noticeable was a decrease of the values of the electron-

acceptor parameter i.e. up to 60% when comparingγ- in the absence and presence of salt,

respectively (Table 3 and Table 4).γ- values obtainedvia contact angle measurements more

often pertain only to the global or averaged surface properties of the materials under study.

Therefore, the agarose backbone onto which Phenyl ligands are immobilized is expected to

have a major contribution to the overall material properties. On the other hand, differences

in surface energy components might arise due to macromolecular changes within the cell



Results

103

envelop which can occur as a function of pH and salt concentration. The observed AB

repulsion in aqueous media often explains the formation of stable suspensions of biological

particles or stable dispersions of proteins and polysaccharides (Wu et al. 1999).



R e s u l t s

1 0 4

T a b l e 3 :

S u r f a c e e n e r g y p a r a m e t e r s o f

i n t a c t y e a s t c e l l s

i n 2 0 m M

p h o s p h a t e b u f f e r p H

7 , 5 0 m

M a c e t a t e

b u f f e r p H

4 a s a

f u n c t i o n o f

a m m o n i u m s u l p h a t e c o n c e n t r a t i o n .

( N H 4 ) 2 S O

4

( M )

γ L W

( m J ⋅ m - 2 )

γ +

( m J ⋅ m - 2 )

γ -

( m J ⋅ m -

2 )

γ A B

( m J ⋅ m - 2 )

γ t o t

( m J ⋅ m - 2 )

Δ G

i w i

( m J ⋅ m - 2 )

p H 7

p H 4

p H 7

p H 4

p H 7

p H 4

p H 7

p H 4

p H 7

p H 4

p H 7

p H 4

0 . 0

2 8 . 0

3 1 . 7

4 . 4

2 . 9

5 1 . 5

5 4 . 1

3 0 . 1

2 4 . 9

5 8 . 3

5 6 . 6

+ 2 3 . 5

+ 2 7 . 2

0 . 2

3 3 . 0

3 7 . 8

2 . 7

1 . 5

5 3 . 2

5 4 . 3

2 4 . 1

1 8 . 0

5 6 . 9

5 5 . 8

+ 2 6 . 0

+ 2 6 . 7

0 . 4

3 5 . 6

3 8 . 6

2 . 0

1 . 4

5 4 . 0

5 4 . 1

2 0 . 7

1 7 . 5

5 6 . 5

5 6 . 0

+ 2 6 . 8

+ 2 6 . 0

0 . 8

3 7 . 4

3 8 . 6

1 . 6

1 . 5

5 4 . 7

5 4 . 0

1 8 . 6

1 7 . 9

5 6 . 0

5 6 . 5

+ 2 7 . 2

+ 2 5 . 7

1 . 2

3 7 . 9

3 8 . 6

1 . 5

1 . 5

5 4 . 8

5 4 . 2

1 8 . 2

1 8 . 0

5 6 . 0

5 6 . 5

+ 2 7 . 0

+ 2 5 . 9

1 . 6

3 8 . 0

3 8 . 6

1 . 5

1 . 5

5 4 . 8

5 4 . 3

1 8 . 0

1 8 . 0

5 6 . 0

5 6 . 6

+ 2 7 . 1

+ 2 6 . 0

2 . 0

3 8 . 5

3 8 . 6

1 . 5

1 . 5

5 4 . 3

5 4 . 4

1 8 . 0

1 8 . 0

5 6 . 6

5 6 . 6

+ 2 6 . 0

+ 2 6 . 0



R e s u l t s

1 0 5

T a b l e 4 :

S u r f a c e e n e r g y p a r a m e t e r s o f P

h e n y l - S e p h a r o s e p a r t i c l e s

i n 2 0 m

M p h o s p h a t e

b u f f e r p H 7 , 5 0 m

M a c e t a t e

b u f f e r p H 4 a s a

f u n c t i o n o f

a m m o n i u m s u l p h a t e c o n c e n t r a t i o n .

( N H

4 ) 2 S O

4

( M )

γ L W

( m J ⋅ m - 2 )

γ +

( m J ⋅ m - 2 )

γ -

( m J ⋅ m - 2 )

γ A B

( m J ⋅ m - 2 )

γ t o t

( m J ⋅ m - 2 )

Δ G i w i

( m J ⋅ m

- 2 )

p H 7

p H 4

p H 7

p H 4

p H 7

p H 4

p H 7

p H 4

p H 7

p H 4

p H 7

p H 4

0

3 0 . 8

3 6 . 3

3 . 5

2 . 0

5 4 . 4

5 4 . 4

2 7 . 5

2 0 . 8

5 8 . 4

5 7 . 1

+ 2 6 . 5

+ 2 6 . 5

0 . 2

3 9 . 3

3 9 . 1

1 . 4

1 . 3

5 4 . 9

5 5 . 0

1 7 . 3

1 7 . 1

5 6 . 7

5 6 . 3

+ 2 6 . 3

+ 2 6 . 7

0 . 4

3 9 . 3

4 0 . 3

1 . 4

1 . 1

5 4 . 9

5 4 . 8

1 7 . 3

1 6 . 0

5 6 . 7

5 6 . 3

+ 2 6 . 3

+ 2 6 . 0

0 . 8

3 9 . 3

4 0 . 9

1 . 3

1 . 0

5 5 . 4

5 4 . 9

1 6 . 7

1 5 . 3

5 6 . 0

5 6 . 2

+ 2 7 . 3

+ 2 5 . 9

1 . 2

3 9 . 3

4 1 . 1

1 . 3

1 . 0

5 5 . 1

5 4 . 6

1 6 . 9

1 5 . 3

5 6 . 3

5 6 . 4

+ 2 6 . 8

+ 2 5 . 4

1 . 6

3 9 . 3

4 1 . 1

1 . 4

1 . 0

5 4 . 9

5 4 . 8

1 7 . 3

1 5 . 0

5 6 . 7

5 6 . 2

+ 2 6 . 3

+ 2 5 . 7

2 . 0

3 9 . 3

4 1 . 1

1 . 3

1 . 0

5 5 . 4

5 5 . 0

1 6 . 7

1 4 . 8

5 6 . 0

5 6 . 0

+ 2 7 . 3

+ 2 6 . 2



Results

108

The Hamaker constant ( A) for the interaction pair Phenyl-Sepharose / yeast cells was

calculated fromΔGLW according to Equation (2). When calculated for dilute buffer solution

i.e. phosphate buffer pH 7 and acetate buffer pH 4, a value of 0.42k T was obtained. The

calculated value for A in buffers containing ammonium sulphate was 1.1k T. Therefore, an

influence of salt concentration but not of pH was observed oninteraction Hamaker constant

values; interaction refers to support-cell phenomena (Butkus and Grasso 1998).

Utilizing the data provided before i.e.ΔGLW, ΔGAB, and zeta potential values, interaction

energy (U) vs. distance (H) profiles were calculated according to the XDLVO approach.

Figure 1(a/b) shows the calculated secondary energy pockets occurring at≈ 5 nm upon

interaction of a yeast cell and the adsorbent surface. Calculations assumed sphere-to-plate

geometry. This is justified since the adsorbent particles are bigger than the yeast particles

by the factor of ~40. The depth of such energy pockets shifted from low to moderate values

≈ -20-50 k T in dilute buffer solutions down to values≈ -120 k T at high salt concentrations.

A more gradual modification of the involved interaction energies took place at pH 7 than at

pH 4. This is agreements with previous findings utilizing bacterial cells (Stenstrom 1989).

Stronger interaction energies between cells and fluidized beads in the presence of

ammonium sulphate might explain observed biomass interference during direct HIC / EBAcapturing of bioproducts from a crude feedstock (Fernandez-Lahore et al. 2000).

Application of the extended DLVO approach is justified since due to the very polar nature

of the buffer solutions where cell-adsorbent interactions take place, these interactions are

known to be strongly influenced by polar Lewis acid-base (AB) or electron-acceptor /

electron-donor forces. Contributions by electric double layer (EL) forces and particularly

contributions by apolar Lifshitz-van der Waals (LW) forces are also expected to occur.Important to the particular system considered here EL and AB forces decay exponentially

with distance but as opposed to EL, the rate of decay of AB forces with distance is

independent on low to moderate variations in the ionic strength. On the other hand, LW

interactions decay gradually and proportional to the separation distance between two

bodies. As observed from Table 5, LW interactions were promoted upon salt addition. On

the other hand, the pronounced asymmetry of the polar properties of hydrophilic materials

like agarose-based chromatographic supports or biological particles promotes a strong ABrepulsion i.e. hydrophilic repulsion. Taken as a whole, calculations performed in relation to



Results

109

interaction phenomena i.e. cell-to support interactions have shown hydrophilic AB

repulsion, increased LW attraction, and marginal contribution of EL forces under standard

operational conditions.

The extended DLVO approach has served to explain the behavior of many other colloidal

systems. Brandt and Childress have demonstrated that short-range interactions between

synthetic membranes and bio-colloids can be better explained by taking into consideration

the role of AB forces (Brant and Childress 2002). Van Oss and coworkers have studied the

stability of a thixotropic suspension of 2μm hectorite particles and concluded that Lewis

acid-base interactions play a key role in the coagulation dynamics of such system (Grasso

et al. 2002).


Biomass deposition experiments were performed to evaluate yeast cells attachment to

hydrophobic interaction supports. This allowed an independent experimental verification of

the predictions made on the basis of energy vs. distance calculations (Figure 1 a/b).



Results

110

Figure 1: Energy vs. distance profiles for interaction between intact yeast cells andhydrophobic interaction beads, at varying ammonium sulphate concentration. A) 20 mM phosphate buffer pH 7 b) 50 mM acetate buffer pH 4.



Results

111

Figure 2 (a/b) depict the cell effluent profiles measured as a function of the chemical

environment provided by the mobile phase. Ammonium sulphate concentration was

systematically varied to observe its influence on cell attachment onto Phenyl-Streamline

beads. Cell deposition was evaluated a pH 7 and 4. Biomass deposition experiments

showed a profound effect of salt concentration on cell effluent profiles e.g. higher cell

deposition with increased ammonium sulphate concentrations. From Figure 2 (a/b) it can

also be noticed that and increased tendency exists for particles to be retained at pH 7 (a)

that at pH 4 (b) when cell deposition was evaluated as a function of increasing ammonium

sulphate concentration (0 – 2 M).



Results

112

Figure 2: Biomass deposition experiments as a function of salt concentration. a) Phosphate buffer pH 7 b) Acetate buffer pH 4.



R e s u l t s

1 1 4

T a b l e 6 : C a l c u l a t e d

l u m p e d

b i o m a s s - a

t t a c h m e n t p a r a m e t e r

f r o m b i o m

a s s d e p o s i t i o n e x p e r i m e n t s f o r

P h e n y l - S t r e a m l i n e T M p a r t i c l e s v s .

i n t a c t

y e a s t c e l l s i n 2 0 m

M p h o s p h a t e

b u f f e r p H

7 , 5 0 m

M a c e t a t e

b u f f e r p H

4 a s a

f u n c t i o n o f a m m o n i u m s u l p h a t e c o n c e n t r a t i o n .

( N

H 4 ) 2 S O 4

( M )

C / C

o ( - )

α ( - )

p H 7

p H 4

p H

7

p H 4

0 . 0

0 . 6 7 7

0 . 8 2 9

0 . 0 6 5

0 . 0 3 1

0 . 4

0 . 5 6 1

0 . 6 4 7

0 . 0 9 7

0 . 0 7 3

0 . 8

0 . 4 9 3

0 . 5 5 1

0 . 1 1 8

0 . 1 0 0

1 . 2

0 . 2 3 4

0 . 3 9 7

0 . 2 4 3

0 . 1 5 5

1 . 6

0 . 1 2 9

0 . 3 2 1

0 . 3 4 3

0 . 1 9 0

2 . 0

0 . 0 7 1

0 . 2 7 9

0 . 4 4 3

0 . 2 1 4



Results

115

Figure 3 shows the correlation between the attachment efficiency parameter and the depth

of the secondary free energy of interaction between a cell particle and a chromatographic

bead. Points corresponding to hydrophobic interaction systems are presented within the

frame of previous results gathered with ion-exchangers. It can be observed that conditions

were no salt is present, and irrespective of pH and buffer chemical composition, are

characterized by low deposition parameter values (≤ 0.15) which correlate with limited

energy pockets (≤ |25-50| kT). However, by adding ammonium sulphate to the flowing

phase an increase inα values was noticed. The magnitude of this increment depended on

pH. For buffers at neutral pH the parameter α changed from≈0.1 (0.4 M salt) to≈0.45 (2.0

M salt). On the other hand, at pH 4 moderate changes inα were observed e.g. from≈0.07

(0.4 M salt) to≈0.21 (2.0 M salt). Therefore, cell deposition in the presence of ammonium

sulphate generally resulted inα ≥ 0.15. The later criterion has been set as threshold for

problem-free operation during direct capture of bioproducts from a crude feedstock (Tari et

al. 2008). From a process performance point of view this could indicate hydrodynamic and

sorption performance limitations from example, during expanded bed adsorption of

bioproducts (Fernandez-Lahore et al. 2000). Sorption performance utilizing HIC / EBA

systems has previously been reported (Smith et al. 2002). Until now, however, it has been

difficult to correlate such behavior with simple cell transmission indexes (Feuser et al.

1999). Biomass-impulse experiments, however, have shown to correlate with ion-

exchanger sorption performance were electrostatic-driven cell-to-matrix interactions effects

are predominant.



Results

116

Figure 3: Correlation between depth of free energy of interaction pocket and lumpedattachment coefficient for several systems.

Analysis of the correlation between the depth of the interaction energy pockets and the

attachment efficiency values for hydrophobic interaction materials in the presence of

ammonium sulphate reveled differences with ion-exchange adsorbents. For HIC systems, a

modification inα values correlated with discrete modifications in energy pocket values

(Figure 3). Moreover, extreme values of both attachment efficiency and energy valleys

were not observed. These results, as a whole, might indicate that total deposition of biomass

particles is mediated not only by cell-to-matrix interaction but also by cell-to-cell

aggregation phenomena (ripening). Deposition experiments also seem to indicate that

ripening is occurring in a larger extent at pH 7 than at pH 4. Summarizing, for hydrophobic

interaction systems modifications within a secondary interaction energy pocket occurred

only from -70k T to -120 k T but α values increased up to 0.45 when ammonium sulphate

increased from 0 to 2 M (Figure 3).



Results

117

Experiments performed to evaluate the influence of the age of the culture on cell

attachment -as observed by biomass deposition experiments- showed increasedα values

when aged cells were employed. For example, in phosphate buffer pH 7 containing 1.0 M

ammonium sulphateα increased from 0.20 to 0.36 when fresh cells were compared to anaged culture (data not shown). At pH 4 a similar trend was observed withα increasing for

0.14 to 0.26 when considering late exponential phase vs. one day aged culture.

2.3.4.4 Cell-to-cell aggregation

Cell-to-cell aggregation might represent and important mechanism promoting overall cell

attachment during biomass deposition experiments. Therefore, increased values for the

lumped α parameter might indicate not only stronger cell-to-supportinteraction butenhanced cell-to-cell aggregation . Consequently, results from biomass deposition

experiments will reveal conditions prevailing during real process performance where both

interaction and aggregation phenomena can coexist.

Contact angle and zeta potential determinations, as reported in this work and elsewhere

(Lin et al. 2006) have been utilized to calculate energy vs. distance profiles between two

intact yeast cells. Sphere-to-sphere geometry was assumed. These XDLVO calculations

have indicated that:

a) At closest distance of approximationΔGLW took values between -1.5 mJ⋅m-2 (20

mM phosphate buffer pH 7) and -3.8 mJ⋅m-2 (50 mM acetate buffer pH 4) under the

chemical environment provided by the buffering solutions employed. By adding

increasing amounts of ammonium sulphate i.e. up to 2 MΔGLW values decreased to

-9.5 mJ⋅m-2, irrespective of system pH. Therefore, attraction between cell particles

due to LW forces is similar at both pH values but increased with salt concentration

(Table 7). Hamaker constant values were 0.6k T (diluted buffer solution) and 2.0k T

(added salt≥ 0.4 M) for yeast-to-yeast aggregation.

b) Under similar conditions,ΔGAB showed more repulsion when calculating interfacial

energy values at pH 4 (from +31.0 mJ⋅m-2 and up to +35.6 mJ⋅m-2 under buffer and

added salt conditions, respectively) than when calculating interfacial energy values

at pH 7 (from +25.0 mJ⋅m-2 and up to +36.0 mJ⋅m-2 under buffer and added salt



Results

118

conditions, respectively). Therefore, the model biomass utilized in this work might

have a tendency to be more stable e.g. less aggregation under acidic pH conditions

due to enhanced repulsion by AB forces (Table 7).

c) Coulomb-type interactions are repulsive in nature, but of marginal importance when

salt concentration is higher than 0.1 M ammonium sulphate e.g. EL are irrelevant

under normal processing conditions.

d) Calculations performed to evaluate energy vs. distance profiles for interaction

between two cells in aqueous media have shown secondary energy pockets taking

values within the range -3k T and -11 k T under diluted buffer conditions and≈ -30

k T in the presence of 2.0 M ammonium sulphate (data not shown).



R e s u l t s

1 1 9

T a b l e 7 :

I n t e r f a c i a l f r e e e n e r g y o f a g g r e g a t i o n o f

i n t a c t y e a s t c e l l s i n 2 0 m

M p h o s p h a t e

b u f f e r p H 7 , 5 0

m M

a c e t a t e b u f f e r p H

4 a s a

f u n c t i o n

o f a m m o n i u m s u l p h a t e c o n c e n t r a t i o n .

( N H

4 ) 2 S O 4

( M )

Δ G

L W

( m

J ⋅ m - 2 )

Δ G

A B

( m J ⋅ m - 2 )

Δ G

T o t

( m J ⋅ m - 2 )

p H 7

p H 4

p H 7

p H 4

p H 7

p H 4

0 . 0

- 1 . 5

- 3 . 8

+ 2 5 . 0

+ 3 1 . 0

+ 2 3 . 5

+ 2 7 . 2

0 . 2

- 4 . 5

- 8 . 8

+ 3 0 . 5

+ 3 5 . 5

+ 2 6 . 0

+ 2 6 . 7

0 . 4

- 6 . 7

- 9 . 5

+ 3 3 . 5

+ 3 5 . 6

+ 2 6 . 8

+ 2 6 . 0

0 . 8

- 8 . 4

- 9 . 5

+ 3 5 . 5

+ 3 5 . 2

+ 2 7 . 1

+ 2 5 . 7

1 . 2

- 8 . 8

- 9 . 5

+ 3 5 . 9

+ 3 5 . 4

+ 2 7 . 0

+ 2 5 . 9

1 . 6

- 8 . 9

- 9 . 5

+ 3 6 . 0

+ 3 5 . 5

+ 2 7 . 1

+ 2 6 . 0

2 . 0

- 9 . 5

- 9 . 5

+ 3 5 . 6

+ 3 5 . 6

+ 2 6 . 0

+ 2 6 . 0



Results

120

In order to elucidate cell aggregation behavior as a function of pH and salt concentration

laser diffraction spectroscopic measurements were employed (Voloshin et al. 2005). The

implementation of an independent method to specifically evaluate cell-to-cell aggregation

can help in understanding (lumped) deposition coefficient values. For example, highα

values in the absence of aggregation by light scattering can be attributed to strong cell-to-

support attachment. On the contrary, highα values and strong aggregation can indicate a

combined effect during biomass deposition. Figure 4 depicts particle size for isolated yeast

cells and formed aggregates, if any. Determinations were performed in 20 mM phosphate

buffer pH 7 and in 50 mM acetate buffer pH 4, so as to reproduce the conditions found

during biomass deposition experiments. Under these conditions, results indicated that cells

were suspended without any association and existed as≈ 8 μm particles (Figure 4a). This is

in perfect agreement with the known size of intact yeast cells. Similar experiments

performed in the presence of 1.6 M ammonium sulphate showed a faster cell-to-cell

aggregation at pH 7 that at pH 4 at short contact times (10 min) (Figure 4b). Furthermore,

longer contact times (45 min) promoted the formation of larger aggregates at pH 7 (≈ 400

μm) than at pH 4 (≈ 250 μm) (Figure 4c). Laser diffraction experiments performed in the

presence of salt were also able to show the shrinkage of individual yeast cell to≈ 5 μm

(data not shown). Cell clumping in the presence of salt was confirmed by confocal

microscopy (Figure 4d). Table 8 summarizes quantitative information obtained after laser

diffraction spectroscopic evaluation of the samples. Results are expressed as percentiles.

The d(0.1), d(0.5), and d(0.9) values shown in Table 8 are indicating that 10 %, 50% and 90% of

the particles measured were less than or the equal to the size stated in each case. Sample

replicates (n=5) have indicated that the shear exerted by the instrument during the

measurement process was not promoting aggregate disruption (Table 8).



Results

121

Figure 4: Laser diffraction experiments performed with intact yeast cells as a function of salt concentration, pH of the suspending buffer, and contact time. a) control yeast cells in plain buffer at pH 7 and 4; (b) Yeast cells after 10 minutes in contact with buffer containing1.6 M (NH4)2SO4; (c) yeast cells after 45minutes in contact with buffer containing 1.6 M(NH4)2SO4; d) Visual aggregation of yeast cells suspended in 1.6 M of salt.

Table 8: Laser diffraction experimental data gathered for intact yeast cells as a function saltconcentration, pH of the suspending buffer, and contact time.

Time(min)

pH (*) (NH 4)2SO 4

(M) d (0.1) (µm)

d (0.5) (µm)

d (0.9) (µm)

7 - 4.3 ± 1 5.6 ± 1 7.6 ± 110/45

4 - 4.6 ± 1 6.2 ± 1 8.7 ± 0.5

7 1.6 4.7 ± 0.5 160.5 ± 10 231.5 ± 20104 1.6 3.5 ± 0.5 5.3 ± 1 117.5 ± 5

7 1.6 5.2 ± 1 284.7 ± 15 409.0 ± 2545

4 1.6 4.3 ± 0.5 18.4 ± 4 275.3 ± 15

(*) pH 7: 20 mM phosphate buffer; pH 4: 50 mM acetate buffer

a)

c)

b)

d)



Results

122

2.3.5 Conclusions

A comprehensive approach to understand biomass deposition / adhesion onto process

supports, with special emphasis on hydrophobic interaction surfaces have included

interaction forces other than those purely electrostatic in nature and have utilized principlesof colloid theory to explain biomass-adsorbent attachment at the local (particle) level.

Within the classical DLVO theory approach, Lifshitz-Van der Waals (LW) and

electrostatic interactions (EL) were considered. Other forces like acid-base (AB)

interactions were included in theextended approach (XDLVO) so as to explain biomass

interaction and aggregation phenomena.

Interaction between biomass particles and chromatographic beads was understood bycalculating interfacial free energy (U) vs. distance (H) profiles. These calculations were

based on the experimental determination of contact angles with three diagnostic liquids and

the additional information gathered from zeta potential determinations. Hydrophobic

interaction chromatography is operated in a context characterized by an increased salt

concentration (high ionic strength and conductivity) in the mobile phase, as well as, by

uncharged beaded adsorbents. Therefore, it was expected that information provided by

contact angle determination would be more relevant to understand cell-to-support

interactions than the information providedvia zeta potential determinations.

Qualitative and quantitative evaluation of cell deposition experiments have revealed several

underlying phenomena like cell-to-support sticking, prevention of cell depositions by

already deposited biomass particles (blocking), and cell-to-cell aggregation (ripening).

Analysis of the correlation between the depth of the interaction energy pockets and the

deposition coefficient values for hydrophobic interaction materials in the presence of

ammonium sulphate reveled differences with ion-exchange adsorbents. For HIC systems,

modifications inα values were followed by discrete modifications in energy pocket depths.

Moreover, extreme values of both deposition coefficients and energy valleys were not

observed. These results, as a whole, might indicate that total deposition of biomass particles

is mediated not only by cell-to-material interaction but mainly by cell-to-cell aggregation

phenomena (ripening).



Results

123

Cell-to-cell aggregation has represented and important mechanism promoting overall cell

adhesion during biomass deposition experiments. These results would indicate that similar

phenomena would impact on real process performance. Cell aggregation behavior, as a

function of pH and salt concentration, was confirmed by laser diffraction spectroscopic

measurements. Besides direct attachment of cells to the beaded support, cell aggregation

has contributed to elevatedα-parameter values, particularly at pH 7, during biomass

deposition experiments.

Summarising, it was demonstrated that both cell-to-adsorbent (interaction) and cell-to-cell

(aggregation) phenomena are responsible to biomass deposition onto hydrophobic

interaction chromatographic materials. Interaction and aggregation was inferred from

XDLVO calculations on the basis of contact angle and zeta potential measurements.

Moreover, experimental confirmation was obtained by independent methods like biomass

deposition experiments and laser diffraction spectrometry.

Further work is being performed in our laboratory in order to extent the observations

reported in this paper to other adsorbent chemistries, biomass types of various

characteristics, and broader operational windows. For example, cell debris shows stronger

interactions with hydrophobic adsorbents than intact cells, because of the hydrophobicinner membrane. Additionally, the information provided by the XDLVO approach is being

utilised to alleviate process limitations.


CT was financially supported by TUBITAK, the Turkish Scientific and Technical Research

Council, Ankara Turkey. RRVP gratefully acknowledges a doctoral fellowship from

Jacobs University. The authors would like thank Professor Udo Fritsching and Ms. LydiaAchelis, Department of Process Technology, University of Bremen, for helpful assistance

during laser diffraction measurements.



Results

124

2.3.7 Nomenclature

AB Acid-Base

DLVO Classical DLVO theory (Derjaguin, Landau, Verwey and Overbeek)

HIC Hydrophobic interaction chromatography


EL Electrostatic


A Hamaker constant [k T]

IC Intact yeast cell particles

LW γ Apolar or Lifshitz-van der Waals component of surface tension [mJ⋅m-2]

ABγ Polar or acid–base component of surface tension [mJ⋅m-2]

−γ Electron-donor component of surface tension (Lewis base) [mJ⋅m-2]

+γ Electron-acceptor component of surface tension (Lewis acid) [mJ⋅m-2]

ε Dielectric constant of the medium [-]R Radius of the particle [m]

ζ Zeta potential [mV]

κ Inverse of Debye length [m]

H Distance between surfaces, measured from outer edge [m]

XDLVO Extended DLVO theory, according to Van Oss

ΔG Interfacial free energy @ 1.57 Å approach [mJ⋅m-2]

U Interfacial energy of interaction [k T]

k Boltzmann constant [J⋅K -1]

T Absolute temperature [K]

h0 Closest distance of approximation [1.57 Å]

α Lumped biomass attachment coefficient [-]



References

125

2.3.7 References

Bak H, Thomas ORT. 2007. Evaluation of commercial chromatographic adsorbents for the

direct capture of polyclonal rabbit antibodies from clarified antiserum. J

Chromatogr B 848(1):116-130.Bos R, Van der Mei HC, Busscher HJ. 1999. Physico-chemistry of initial microbial


23(2):179-230.

Brant JA, Childress AE. 2002. Assessing short-range membrane-colloid interactions using

surface energetics. J Membr Sci 203:257-273.

Butkus MA, Grasso D. 1998. Impact of Aqueous Electrolytes on Interfacial Energy. J

Colloid Interface Sci 200(1):172-181.Fernandez-Lahore HM, Geilenkirchen S, Boldt K, Nagel A, Kula MR, Thommes J. 2000.










26(11):933-7.

Grasso D, Subramaniam K, Butkus M, Strevett K, Bergendahl J. 2002. A review of non-

DLVO interactions in environmental colloidal systems. Rev Environ Sci Biotechnol

1(1):17-38.


quantify Candida albicans cell surface Hydrophobicity. Biotechnol Lett 24:1111–

1115.

Kang S, Choi H. 2005. Effect of surface hydrophobicity on the adhesion of S. cerevisiae

onto modified surfaces by poly(styrene-ran-sulfonic acid) random copolymers.

Colloids Surf B Biointerfaces 10(46 (2)):70-7.



References

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Mahn A, Asenjo JA. 2005. Prediction of protein retention in hydrophobic interaction

chromatography. Biotechnol Adv 23(5):359-368.


Chem 37:133-142.



1785.



98(3):341-463.Smith MP, Bulmer MA, Hjorth R, Titchener-Hooker NJ. 2002. Hydrophobic interaction



Smyth CJ, Jonsson P, Olsson E, Soderlind O, Rosengren J, Hjerten S, Wadstrom T. 1978.

Differences in Hydrophobic Surface Characteristics of Porcine Enteropathogenic

Escherichia-Coli with or without K88 Antigen as Revealed by Hydrophobic

Interaction Chromatography. Infect Immun 22(2):462-472.Stenstrom TA. 1989. Bacterial hydrophobicity, an overall parameter for the measurement

of adhesion potential to soil particles. Appl Environ Microbiol 55(1):142-147.



surfaces. J Chem Technol Biotechnol 83:183-191.

Van Oss CJ. 1994. Interfacial forces in aqueous media. New York: Marcel Dekker.

viii,440p. p.



References

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Van Oss CJ. 2003. Long-range and short-range mechanisms of hydrophobic attraction and

hydrophilic repulsion in specific and aspecific interactions. J Mol Recognit

16(4):177-190.

Vennapusa RR, Hunegnaw SM, Cabrera RB, Fernandez-Lahore M. 2008. Assessing

adsorbent-biomass interactions during expanded bed adsorption onto ion exchangers

utilizing surface energetics. J Chromatogr A 1181(1-2):9-20.

Vergnault H, Willemot RM, Mercier-Bonin M. 2007. Non-electrostatic interactions

between cultured Saccharomyces cerevisiae yeast cells and adsorbent beads in

expanded bed adsorption: Influence of cell wall properties. Process Biochem

42(2):244-251.

Voloshin S, Shleeva M, Syroeshkin A, Kaprelyants A. 2005. The Role of Intercellular

Contacts in the Initiation of Growth and in the Development of a Transiently

Nonculturable State by Cultures of Rhodococcus rhodochrous Grown in Poor

Media. Microbiology 74:420-427.

Wu W, Giese RF, Van Oss CJ. 1999. Stability versus flocculation of particle suspensions in

water-correlation with the extended DLVO approach for aqueous systems,

compared with classical DLVO theory. Colloids Surf B Biointerfaces 14:47-55.



Results

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2.4 Surface energetics to assess biomass attachment ontoimmobilized metal affinity adsorbents in expanded beds

Rami Reddy Vennapusa, Muhammad Aasim, Rosa Cabrera, and Marcelo Fernandez-Lahore*

Downstream Processing Laboratory, School of Engineering and Science, Jacobs UniversityBremen gGmbH, Campus Ring 1, D-28759, Bremen, Germany.

2.4.1 Abstract


model system composed of intact yeast cells and Chelating-StreamlineTM

adsorbents.Biomass components and beaded adsorbents were mainly characterized by contact angle

determinations with three diagnostic liquids. Complementarily, zeta potential

measurements were performed. These experimental values were employed to calculate free

energy of interaction vs. distance profiles in aqueous media. The effect of immobilized

metal-ion type and buffer pH on the interaction energy was evaluated. Calculations

indicated that moderate interaction between cell particles and adsorbent beads can develop

due to the presence of Cu2+

ions onto the solid phase. The strength of interaction increasedwith buffer pH, within the range 6.0 to 8.3 e.g. secondary energy pockets increased from

|15| to |60| k T. Cell-to-cell secondary energy minimum was≥ |14| k T showing low-to-

moderate tendency to aggregate, particularly at pH≥ 8. Extended DLVO predictions were

generally confirmed by biomass deposition experiments. However, an exception was found

when working with immobilized Cu2+ at pH 8 since yeast cells were able to sequestrate

such immobilized ions. Therefore, lower-than-expected values for the depositions

coefficient (α) were observed. Understanding biomass attachment onto Chelating supportscan help to better design and operate expanded bed adsorption of bioproducts.



Results

130

secreted fromS. cerevisiae were also processed employing this technique (Noronha et al.

1999). Generally, recoveries over 80% of the product were achieved in successful cases,

but at least two major weak features must be further improved: low dynamic capacity and

efficiency of Clean In Place (CIP) procedures for eliminating contaminants. The later are

directly linked to biomass interference with the sorption process. The combination of

IMAC and EBA techniques has potential to provide a unique approach to simplifying the

whole downstream process, reduce the number of steps and start-up investment, and thus

make the purification more economical.

Experimental evidence has addressed the importance of non-electrostatic forces for biomass

adhesion to process surfaces in the broader context provided by a group of systems of

technical and environmental relevance. In this regard, a more comprehensive approach tounderstand biomass deposition onto chromatographic supports has been proposed by

utilizing principles of colloid theory to explain biomass-adsorbent attachment at the local

(particle) level (Vennapusa et al. 2008). This approach is based on extended DLVO

calculations performedvia experimentally determined contact angles and z-potentials for

the interacting bodies. This comprehensive method takes into account several types of

possible interaction forces. Lifshitz-Van der Waals (LW) and acid-base (AB) forces are

considered and, therefore, the approach is not limited to those purely electrostatic in nature(EL). Moreover, biomass attachment behavior onto chromatographic beads predicted on the

basis of XDLVO calculations was validated by independent biomass deposition

experiments (Tari et al. 2008).

The aim of this paper was to contribute to a deeper understanding of biomass-adsorbent

interactions. This would further open the pave for optimized EBA processing in industry. In

this work, studies have targeted biomass adhesion to Chelating materials that have not been

extensively studied so far. The physicochemical properties of biomass-derived material (bio

colloid particles) vs. the physicochemical properties of the adsorbent beads (the process

surface) were determined indirectlyvia contact angle and zeta potential measurements.

Subsequently, Gibbs free (interfacial) energy of interaction was calculated as a function of

surface distance in aqueous media e.g. process buffer. Calculations were experimentally

confirmed by independent biomass deposition experiments.



Results

131


2.4.3.1 Materials

Chromatographic matrices and columns were purchased from GE Health Care (Munich,Germany). α-bromonaphtalene and formamide were obtained from Fluka (Buchs,

Switzerland). Water was Milli-Q quality. All other chemicals were analytical grade.


Yeast cells (Saccharomyces cerevisiae ) were cultivated in shake-flasks, harvested at late

exponential phase by centrifugation, and washed three times with 10mM phosphate buffer

solutions, as previously described (Ganeva et al. 2004). Cells were employed immediatelyafter preparation for further experimental procedures.



described (Henriques et al. 2002). Washed cells were suspended to 10% (w/v) in IMAC

buffer [20mM phosphate buffer, pH 7.6 / 250 mM sodium chloride / 1 mM imidazol]. Cells

were further equilibrated in the buffer solution and the suspension subsequently poured

onto agar plates containing 10% glycerol and 2% agar-agar. The plate was allowed to dry

for 24-36 hours at room temperature on a properly leveled surface free from dust. Salt

crystallization was avoided. Agar plates without cell spreads were utilized as control.

Contact angles were measuredas per the sessile drop method utilizing a commercial

goniometric system (OCA 20, Data Physics instruments GmbH, Filderstadt, Germany). The

three diagnostic liquidsα-bromonaphtalene, formamide, and water were employed (Bos et

al. 1999). All the measurements were performed in triplicate and at least 20 contact angles per samples were measured.



cell particles. Chelating Sepharose was utilized (GE Healthcare, Munich, Germany).

Previous to pouring onto the agar plates, matrix beads were frozen in liquid nitrogen and

crushed mechanically. Crushing efficiency was assessed by microscopic examination and particle size determination so as to assure particle fragment diameters≤ 10 μm. Square



Results

132

pieces of the agar-supported chromatographic bead fragments were utilized for measuring

contact angles.

2.4.3.4 Zeta potential determination

Zeta-potential measurements were performed with a ZetaSizer Nano-ZS (Malvern

instruments, Worcestershire, United Kingdom), as previously described (Vennapusa et al.

2008). Zeta-potential values were gathered employing biomass pretreated under the

conditions described before.

Zeta-potential values for crushed and pre-equilibrated chromatographic beads were

calculated from the electrophoretic mobility data according the Smoluchowski’s equation

(Ottewill and Shaw 1972). Data was gathered under identical buffer compositions as shownfor biomass related determinations.

2.4.3.5 Cell aggregation behavior

Visual inspection of aggregate formation was performed with a confocal laser scanning

microscope, equipped with argon and helium/neon mixed gas laser with excitation

wavelengths of 488 or 543 nm (LSM 510, Carl Zeiss, Oberkochen, Germany). Washed

yeast cells in control buffer [20 mM phosphate buffer, pH 7.6] or IMAC buffer [20mM phosphate buffer, pH 7.6 / 250 mM sodium chloride / 1 mM imidazol] were mounted on

glass slides and visually inspected. Scans at a resolution of 1024 x 1024 pixels were taken

in the line-averaging mode. Micrographs were stored in LSM format for further analysis

(Carl Zeiss LSM Image Browser).

2.4.3.6 Bio-colloid deposition experiments

Biomass deposition experiments were performed automatically employing an ÄKTA

Explorer 100 system (GE Health Care, Munich, Germany) as previously described (Tari et

al. 2008). Streamline Chelating was packed in commercial chromatographic columns (5

mm internal diameter, 50 mm length). The quality of the packing was evaluated by

residence time distribution analysis employing 1% acetone as tracer (Bak and Thomas

2007). Chelating particles were loaded with metal ions utilizing standard procedures

(Clemmitt and Chase 2000). Biomass deposition studies were done by injecting a 4 ml

biomass pulse (OD≈ 0.8 AU). Experiments were performed utilizing IMAC buffer at pH



Results

133

6.0, 7.6, and 8.3. The operational flow rate was 76.4 cm.h-1. Particle breakthrough curves

were obtained by monitoring the effluent suspensions at 600 nm. On the basis of such data,

the biomass deposition parameter (α) was calculated (Redman et al. 2004).




ABmwc

ELmwc

LW mwc



term, and UEL

is the EL interaction term. The subscriptm is utilized for thechromatographic matrix (adsorbent bead), w refers to the watery environment, and c to the




measurements utilizing three diagnostic liquids (Van Oss 1994). In turn, this data can be

employed to evaluate the free energy of interaction between two defined surfaces (ΔGLW

and ΔGAB). ΔG represents here the interaction energy per unit area between two (assumed)

infinite planar surfaces bearing the properties of the adsorbent bead and the cell

(interaction) or two cells (aggregation), respectively. Interaction between any of these two

surfaces are evaluated at a closest distance of approximation [h0 ≈ 0.158 nm] (Bos et al.

1999). When integrated into mathematical expressions accounting the geometric constraints

existing between two interacting bodies,ΔG values can be utilized to calculate the

corresponding energy-distance profile (U vs. H). Details of this procedure were published

elsewhere (Bos et al. 1999; Vennapusa et al. 2008).ΔGLW is also related to the interaction Hamaker constant, as follows:

LW Gh A Δ−= 2012π (2)

UEL energy-distance curves can be calculated, assuming either plate-sphere or sphere-


potential values are measured by electrophoretic mobility experiments. Calculations were



Results

134

performed employing a commercial software package (GraphPad Prism, GraphPad

Software Inc., San Diego, CA, USA).



Results

136

Table 1: Contact angles obtained on crushed Chelating Sepharose with and withoutimmobilized metal ions. For IDA-Cu2+, determinations were performed a various pHvalues. Measurements were performed in 20 mM phosphate buffer, pH 7.6, containingsodium chloride.

Metal ion pH Contact angle ( θ) [°]

Water Formamideα -

Bromonaphtalene

No metal 7.6 7.0 ± 0.6 9.8 ± 0.8 53.0 ± 1.0

Zn2+ 7.6 8.0 ± 2.0 12.8 ± 2.0 57.0 ± 2.1

Ni2+ 7.6 8.0 ± 1.7 11.4 ± 2.0 54.0 ± 3.4

Co2+ 7.6 10.0 ± 2.0 12.6 ± 3.1 54.0 ± 2.0

Cu2+ 6.0 7.5 ± 0.5 9.5 ± 1.3 57.0 ± 5.5

Cu2+ 7.6 10.2 ± 2.4 12.1 ± 0.9 45.0 ± 3.0

Cu2+ 8.3 11.1 ± 0.4 11.0 ± 1.5 40.0 ± 2.2


parameters for the chromatographic media according to the acid-base approach (Bos et al.

1999). Table 2 depicts the surface energy components (γ) calculated as a function

immobilized metal-ion type.γLW values were≈ 28 mJ⋅m-2 for the free Chelating matrix and

the Ni2+ or Co2+ loaded beads. A decreased value for such parameter, however, was

observed with Zn2+ (26.5 mJ⋅m-2). On the other hand,γLW values increased for Cu2+ (32.3

mJ⋅m-2

).

An interesting behavior was observed in relation with acid-base character of the metal-

immobilized materials. Values taken by the electron-acceptor parameter (γ+) and the total

acid-base parameter (γAB) allowed differentiating between beads harboring different metal-

ions as follows :

Zn2+ > Ni2+ ≈ [IDA]≈ Co2+ >>Cu2+



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137

γ+ took values between 3.0 and 5.0 mJ⋅m-2 while for most Sepharose adsorbent values≈ 1-2

mJ⋅m-2 are typical (Vennapusa et al. 2008). Similar observations were made by

(Bayramoglu et al. 2006) when comparing L-histidine affinity membranes with or without

immobilised copper (II) ions. These variations in the acid-base character of the (metal ion)loaded chromatographic matrices are expected since IMAC adsorption is based on the

interaction between an immobilised transition-metal ion (electron pair acceptors) and

electron-donor groups e.g. on protein surfaces. For proteins, the apparent affinity for a

metal chelate depends strongly on the metal ion involved in coordination. In the case of the

iminodiacetic acid (IDA) chelator, the affinities of many retained proteins and their

respective retention times are in the following order: Cu2+ > Ni2+ > Zn2+ ≈ Co2+ (Gaberc-

Porekar and Menart 2001).

Table 2: Surface energy parameters calculated for Chelating Sepharose loaded with variousmetal ions, calculated according to the contact angle values reported in Table 1.

Metal ion pH Surface energy parameters [mJ·m -2]

γLW γ+ γ- γAB γTOT ΔG sws

No metal 7.6 28.5 4.4 53.8 30.7 59.2 +25.2Zn2+ 7.6 26.5 5.0 54.1 32.8 59.3 +25.0

Ni2+ 7.6 28.0 4.5 53.9 31.0 59.0 +25.3

Co2+ 7.6 28.0 4.4 53.5 30.7 58.7 +25.2

Cu2+ 6.0 26.5 5.3 53.3 33.5 59.9 +24.0

Cu2+ 7.6 32.3 3.0 53.7 25.0 57.4 +26.3

Cu2+ 8.3 34.6 2.4 53.3 22.5 57.1 +25.6

2.4.4.3 The effect of mobile-phase pH

Adsorption of a protein to the IMAC support is performed at a pH at which imidazole

nitrogen’s in histidyl residues are in the nonprotonated form, normally in neutral or slightly

basic medium (Chaga 2001; Ueda et al. 2003).



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138

Contact angle determinations were also performed as a function of pH, employing

immobilized copper ions. Table 1 also summarizes the contact angle values obtained in

IMAC buffer at pH 6.0, 7.6, and 8.3. Some tendencies were observed when pH raised: a)

water contact angles increased from 7.5 to 11.0, and b) formamide contact angles increased

from 9.5 to 11.1, but c)α-bromonaphtalene contact angles decreased from 57 to 40.

Table 2 depicts the surface energy components (γ) calculated for the IMAC adsorbent at

various pH values. As a general trend it was observed thatγLW increased with pH (e.g. from

26.5 mJ⋅m-2 at pH 6.0 to 34.6 mJ⋅m-2 at pH 8.3) whileγAB decreased (e.g. from 33.5 mJ⋅m-2

at pH 6.0 to 22.5 mJ⋅m-2 at pH 8.3). Clearly noticeable was the influence of pH on theγ+

since this parameter decreased from 5.3 mJ⋅m-2

at pH 6.0 to 2.4 mJ⋅m-2

at pH 8.3.

As observed from Table 2, the parameter Δ Giwi took always values +24-26 mJ⋅m-2,

irrespective of the type of transition metal ion immobilized or the buffer pH, reflecting the

highly hydrophilic nature of the chromatographic beads.

2.4.4.4 Characterization of the yeast particles

Contact angle determinations were performed on intact yeast cell lawns within the

physicochemical environment provided by the IMAC buffer. Contact angle values werecollected for three distinct pHs: 6.0, 7.6, and 8.3. Water and formamide contact angle

values were observed to increase with pH e.g. from 7.6 to 12.2 and from 10.4 to 18,

respectively. On the contraryα-bromonaphtalene contact angles dropped from 50 to 44.

Overall, this indicates an increased hydrophobic character for the yeast particles at higher

pH values [Refer to Table 3 (a)].



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Zeta potential measurements performed in IMAC buffer at various pHs were≈ |8| mV (data

not shown). Zeta potential values close to zero are expected due to the moderate-high

concentrations of salt which are present in such buffers e.g. from 0.25 to 1.0 M in sodium

chloride.

2.4.4.5 Biomass interaction phenomena

Interaction between biomass particles and chromatographic beads can be understood by

calculating interfacial free energy (U) vs. distance (H) profiles. These calculations are


the additional information gathered from zeta potential determinations.

Table 4 depicts the interfacial free energy of interaction between a biomass particles and a

Chelating bead, in aqueous media at pH 7.6, at closest distance of approximation (1.57 Å).

For the unloaded particle,ΔGLW and ΔGAB values were -1.1 mJ⋅m-2 and +28 mJ⋅m-2,

respectively. Upon loading the matrix with different transition metal ions, variations in the

preceding values were observed for Zn2+ (ΔGLW = -0.8 mJ⋅m-2 / ΔGAB = 27.4 mJ⋅m-2) and

for Cu2+ (ΔGLW = -1.7 mJ⋅m-2 / ΔGAB = 29.6 mJ⋅m-2) but not for Ni2+ and Co2+.

Interaction between Cu (II) loaded beads and yeast cells was further investigated as a

function of buffer pH (Table 4). It was noticed thatΔGLW decreased from -0.76 mJ⋅m-2 at

pH 6.0 to -2.6 mJ⋅m-2 at pH 8.3. AB values also followed a similar tendency e.g.ΔGAB

increased from 26.6 mJ⋅m-2 at pH 6.0 to 32.6 mJ⋅m-2 at pH 8.3. This data is indicating that

the pH values of the buffer where interaction is occurring are correlated with modification

in interaction energies.

The interaction Hamaker constant ( A) for the pair Chelating-Sepharose / yeast cells wascalculated from ΔGLW according to Equation (2). When calculated for IMAC buffer

solution (pH 7.6) an average value of 0.35 kT was obtained. A was lower for Zn2+ but

higher for Cu2+ i.e. 0.17 kT and 0.40 kT, respectively.



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Table 4: The interfacial Gibbs energy of interaction between intact yeast cells andChelating Sepharose, at closest distance of approximation. Interaction occurs in 20 mM phosphate buffer containing sodium chloride as added salt.

Loaded metal ion Buffer pH ΔG [mJ·m -2]

ΔG LW ΔG AB

No metal 7.6 -1.1 27.9

Zn2+ 7.6 -0.8 27.4

Ni2+ 7.6 -1.0 27.8

Co2+ 7.6 -1.0 27.7

Cu2+ 6.0 -0.76 26.6

Cu2+ 7.6 -1.7 29.6

Cu2+ 8.3 -2.6 32.6

Utilizing the data provided before i.e.ΔGLW, ΔGAB, and zeta potential values, interaction

energy (U) vs. distance (H) profiles were calculated according to the XDLVO approach.

Due to the relatively high conductivity of the mobile phase utilized in Chelating systems (≈

30 mS/cm), zeta-potential values for both yeast particles and chromatographic beads were

very low (< 8-10 mV).

Figure 1(a) and Figure 1(b) shows the calculated secondary energy pockets occurring at≈ 7

nm upon interaction of a yeast cell and the adsorbent surface. Calculations assumed sphere-

to-plate geometry. The depth of such energy pocket for the unloaded matrix showed a

moderate value≈ -20 k T at pH 7.6. Metal ion loaded systems showed a similar energy

profile. However, the presence of immobilized Cu2+ resulted in an increased pocket depth≈ -40 k T. In the later case, modification of pH has lead to a reduced (≈ -15 k T at pH 6.0) or

increased (≈ -60 k T at pH 8.3) energy pocket. Therefore, more cell deposition would be

expected when working with immobilized cupper ions at higher pH values.

Data indicated that cell-to-support interactions can be strongly influenced by polar Lewis

acid-base (AB) or electron-acceptor / electron-donor forces which are included in the

XDLVO approach. This has served to explain the behavior of many other colloidal



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142

systems. Brandt and Childress have demonstrated that short-range interactions between


the role of AB forces (Brant and Childress 2002; Brant and Childress 2004). Van Oss and

coworkers have studied the stability of a thixotropic suspension of 2μ

m hectorite particles

and concluded that Lewis acid-base interactions play a key role in the coagulation

dynamics of such system (Grasso et al. 2002). Van Oss also has reviewed the importance of

AB forces for the stability of many colloidal systems (Van Oss 1993; Van Oss 2003).

Figure1 (a): Free energy of interaction vs. distance profiles between intact yeast andChelating Sepharose loaded with different metal-ion types. Calculations were performed

assuming that interaction occurs in a buffer with a typical composition for immobilizedmetal affinity chromatography, at pH 7.6 / (— ) No metal, (— ) Zn2+, (--- ) Ni2+, (— ) Co2+, (— ) Cu2+



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143

Figure 1(b): Free energy of interaction vs. distance profiles between intact yeast andChelating Sepharose loaded with Cu (II) ions. Calculations were performed assuming thatinteraction occurs in a buffer with a typical composition for immobilized metal affinity

chromatography, at various pH values. (—

) pH 6, (—

) pH 7.6, (—

) pH 8.3.

2.4.4.6 Biomass aggregation phenomena

Contact angle and zeta potential determinations, as reported in this work have been utilized

to calculate energy vs. distance profiles between two intact yeast cells. The data gathered

on zeta potential showed that charge effects are of marginal importance for the Chelating

system. Sphere-to-sphere geometry was assumed. Table V depicts the interfacial interaction

free energy between two biological particles, in aqueous media as function of pH at theclosest distance of approximation (1.57 Å). The tendency of ΔGLW and ΔGAB interaction

energy of aggregation is similar to that of the interaction of yeast with IDA-Cu2+ as

function of pH (Table IV). Upon modification of buffer pH from 6.0 to 8.3, theΔGLW

interaction energy decreased from -2.6 mJ⋅m-2 to -4.6 mJ⋅m-2 while ΔGAB changed from

+28.4 mJ⋅m-2 to 33.8 mJ⋅m-2, respectively. Interaction free energies as function of distance

were calculated according to the XDLVO model (Figure 2) . Calculations, in aqueous

media, have indicated that secondary energy pockets can develop at H≈ 5-7 nm. The depth



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144

of such pockets indicated that attraction between cell particles is higher when the pH of the

buffer increased i.e. U≈ |14| at pH 8.3 and ≤ |8| at lower pH values. This trend was

confirmed by microscopic observations. Figure 3 depicts freely suspended cells in 20 mM

phosphate buffer in comparison with clumped cell in IMAC buffer. Cell aggregation wasverified by independent laser diffraction experiments (Data not shown).

Table 5: The interfacial Gibbs energy of aggregation between intact yeast cells, at closestdistance of approximation. Interaction occurs in 20 mM phosphate buffer containingsodium chloride as added salt.

Buffer pH ΔG LW [mJ·m -2] ΔG AB [mJ·m -2]

6.0 -2.6 28.4

7.6 -2.8 28.7

8.3 -4.6 33.8



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Figure 2: Free energy of interaction vs. distance profiles between intact yeast cells.Calculations were performed assuming that interaction occurs in a buffer with a typicalcomposition for immobilized metal affinity chromatography, at various pH values. (— ) pH6, (— ) pH 7.6, (— ) pH 8.3.

Figure 3 : Microscopic observation of yeast cell aggregation employing a confocal system:a) Cells in 20 mM phosphate buffer at pH 7.6, and b) Cells in sodium chloride containing buffer at the same pH.

a) b)



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146


Figure 4(a) depicts the cell effluent profiles measured as a function of the chemical

environment provided by the mobile phase. The transition metal ion immobilized on the

IDA moiety was varied to observe the influence of ion type on cell attachment. ChelatingStreamline beads were utilized. Biomass deposition experiments confirmed that an

increased deposition of yeast cell occur when Cu2+ is the fixed metal ion, at pH 7.6.

Figure 4 (a): Cell effluent profiles obtained after biomass deposition experiments. Intactyeast cells were utilized as model bio-colloids. Runs were performed in phosphate-based buffer solutions, at pH 7.6. Chelating Sepharose was utilized as collector particles.

Iminodiacetic beads were loaded with several metal ions: () No metal, ( ) Zn2+

, ( ) Ni2+

,( ) Co2+, ( ) Cu+2.

This fact is reflected by the “attachment efficiency” parameter (α). This is a lumped

number which depends on experimental conditions; the method has been adapted to a

chromatographic workstation that can operate in automatic mode.α values for the unloaded

material and the Zn2+, Ni2+, and Co2+ loaded support fall within the range 0.056-0.078.

Upon Cu2+ immobilization,α increased to 0.172 i.e. more yeast particles were trapped

within the collector bed (Table 4).



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148

Figure 4(b): Cell effluent profiles obtained after biomass deposition experiments. Intactyeast cells were utilized as model bio-colloids. Runs were performed in phosphate-based buffer solutions, at several pH values. Chelating Sepharose, loaded with Cu (II) ions, wasutilized as collector particles. () pH 6, ( ) pH 7.6, ( ) pH 8.3.

Cell-to-cell aggregation might represent and important mechanism promoting overall cell

attachment during biomass deposition experiments. Therefore, increased values for the

lumped α parameter might indicate not only stronger cell-to-supportinteraction but

enhanced cell-to-cellaggregation . For the Chelating system, cell aggregation effects are

predicted to be low-to-moderate according to XDLVO calculations. To evaluate whether

cell aggregation or attrition–in the absence of cell-to-matrix interaction- is influencing cell breakthrough profiles, biomass deposition experiments were run with plain material as

collectors but utilizing mobile phase compositions known to increase cell aggregation

(Ljungh and Wadström 1982). Experimental runs showed thatα values were fairly constant

(α ≈ 0.05) irrespective of the presence of ammonium sulphate, a salt that induces cell-to-

cell aggregation (Figure 5).



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149

Figure 5: Cell effluent profiles obtained after biomass deposition experiments. Intact yeastcells were utilized as model bio-colloids. Runs were performed in phosphate-based buffer solutions, at pH 7.6. Unloaded Chelating Sepharose beads were utilized as collectors. () 20mM phosphate buffer, ( ) Buffer containing added ammonium sulphate (0.8 M), () Buffer containing added ammonium sulphate (1.6 M).

As a whole, biomass deposition experiments have indicated that Cu (II) would promote

more cell deposition than other metal ions. Cell aggregation can occur in buffers containing

moderate-to-high concentration of added salts. However, in the absence of cell-to-support

interaction further deposition due to cell aggregation is not possible. Summarizing, IMAC

systems where biomass deposition could play a role seem to be limited to a) immobilized

Cu (II), b) at pH within the range 7.0 to 7.6, and c) with salt containing buffers.

2.4.4.8 Chelating systems in the context of EBA adsorbents

Figure 6 shows the correlation between the attachment efficiency parameter (α) and the

secondary-pocket-depth (free energy of interaction between a cell particle and a

chromatographic bead). Points corresponding to ion-exchangers and hydrophobic

interaction systems are presented as a reference (Tari et al. 2008). It can be observed that

Chelating materials are generally characterized by low deposition parameter values (α ≤

0.15) which correlate with limited energy pockets (≤ |20| k T). However, the effect of



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151

2.4.5 Conclusions

A comprehensive approach to understand biomass deposition onto Chelating

chromatogrpahic supports has utilized principles of colloid theory to explain biomass-

adsorbent attachment at the local (particle) level. Acid-base (AB) interactions wereincluded in the extended approach (XDLVO) so as to explain biomass interaction and

aggregation phenomena. Besides, Lifshitz-Van der Waals (LW) (EL) were considered.

Electrostatic interactions played a minor role due to the high conductivity of the process

buffer involved.

Interaction between biomass particles and chromatographic beads was studied by

calculating interfacial free energy (U) vs. distance (H) profiles. These calculations were based on the experimental determination of contact angles with three diagnostic liquids and

the additional information gathered from zeta potential determinations.

Qualitative and quantitative data from cell deposition experiments has revealed a

predominant role of cell-to-support interaction. Cell-to-cell aggregation showed a less

impact on total biomass deposition in Chelating systems. Analysis of the correlation

between the depth of the interaction energy pockets and the deposition coefficient values

for Chelating materials in the presence of sodium chloride at neutral pH reveled differences

with ion-exchange and hydrophobic interaction adsorbents. The strength of biomass

interaction was enhanced by having copper (II) ions immobilized onto the solid phase.

Summarising, it was demonstrated that cell-to-adsorbent (interaction) and –to a lesser

extent- cell-to-cell (aggregation) phenomena are responsible to biomass deposition onto

Chelating chromatographic materials. Interaction and aggregation was inferred from

XDLVO calculations on the basis of contact angle and zeta potential measurements.Moreover, experimental confirmation was obtained by independent methods like biomass

deposition experiments and confocal microscopy.


RRVP gratefully acknowledges a doctoral fellowship from Jacobs University. The authors

would thank Dr. Carl Bolster for his valuable discussions during the work.



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2.4.7 Nomenclature

AB Acid-Base

DLVO Classical DLVO theory (Derjaguin, Landau, Verwey and Overbeek)

CHE Chelating [Iminodiacetic Group - IDA]


EL Electrostatic


A Hamaker constant [k T]

IC Intact yeast cell particles

IMAC Immobilized metal affinity chromatography LW γ Apolar or Lifshitz-Van der Waals component of surface tension [mJ⋅m-2]

ABγ Polar or acid–base component of surface tension [mJ⋅m-2]

−γ Electron-donor component of surface tension (Lewis base) [mJ⋅m-2]


Ε Dielectric constant of the medium [-]

R Radius of the particle [m]

Ζ Zeta potential [mV]

κ Inverse of Debye length [m]

H Distance between surfaces, measured from outer edge [m]

XDLVO Extended DLVO theory, according to Van Oss


U Interfacial energy of interaction [k T]

K Boltzmann constant [J⋅K -1]

T Absolute temperature [K]


α Lumped biomass deposition coefficient [-]



References

153

2.4.8 References

Bak H, Thomas ORT. 2007. Evaluation of commercial chromatographic adsorbents for the

direct capture of polyclonal rabbit antibodies from clarified antiserum. J

Chromatogr B 848(1):116-130.Bayramoglu G, Celik G, Arica MY. 2006. Immunoglobulin G adsorption behavior of l-

histidine ligand attached and Lewis metal ions chelated affinity membranes.

Colloids Surf A Physicochem Eng Asp 287(1-3):75-85.



23(2):179-230.

Brant JA, Childress AE. 2002. Assessing short-range membrane-colloid interactions usingsurface energetics. J Membr Sci 203:257-273.

Brant JA, Childress AE. 2004. Colloidal adhesion to hydrophilic membrane surfaces. J

Membr Sci 241(2):235-248.


Colloid Interface Sci 200(1):172-181.

Chaga GS. 2001. Twenty-five years of immobilized metal ion affinity chromatography:

past, present and future. J Biochem Biophys Methods 49(1-3):313-334.

Clemmitt RH, Chase HA. 2000. Immobilised metal affinity chromatography of [beta]-

galactosidase from unclarified Escherichia coli homogenates using expanded bed

adsorption. J Chromatogr A 874(1):27-43.




Gaberc-Porekar V, Menart V. 2001. Perspectives of immobilized-metal affinity

chromatography. J Biochem Biophys Methods 49(1-3):335-360.


Gomez-Garcia AC. 2002. Thermodynamic Analysis of Growth Temperature

Dependence in the Adhesion of Candida parapsilosis to Polystyrene. Appl Environ

Microbiol 68(5):2610-2613.



26(11):933-7.



References

154



1(1):17-38.



1115.

Klotz SA, Drutz DJ, Zajic JE. 1985. Factors Governing Adherence of Candida Species to

Plastic Surfaces. Infect Immun 50(1):97-191.

Ljungh Å, Wadström T. 1982. Salt aggregation test for measuring cell surface

hydrophobicity of urinaryEscherichia coli. Eur J Clin Microbiol 1(6):388-393.

Noronha S, Kaufman J, Shiloach J. 1999. Use of Streamline chelating for capture and

purification of poly-His-tagged recombinant proteins. Bioseparation 8(1):145-151.


Chem 37:133-142.

Poulin F, Jacquemart R, De Crescenzo G, Jolicoeur M, Legros R. 2008. A Study of the




Media: Role of the Secondary Energy Minimum. Environ Sci Technol 38(6):1777-1785.




Ting. Y-P, Sun G. 2000. Use of polyvinyl alcohol as a cell immobilization matrix for

copper biosorption by yeast cells. J Chem Technol Biotechnol 75(7):541-546.

Ueda EKM, Gout PW, Morganti L. 2003. Current and prospective applications of metalion-protein binding. J Chromatogr A 988(1):1-23.

Van Oss CJ. 1993. Acid-base interfacial interactions in aqueous media. Colloids Surf A

Physicochem Eng Asp 78:1-49.

Van Oss CJ. 1994. Interfacial forces in aqueous media. New York: M. Dekker. viii,440p. p.



16(4):177-190.



References

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Willoughby NA, Kirschner T, Smith MP, Hjorth R, Titchener-Hooker NJ. 1999.

Immobilised metal ion affinity chromatography purification of alcohol

dehydrogenase from baker's yeast using an expanded bed adsorption system. J

Chromatogr A 840(2):195-204.



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2.5 Surface energetics to assess microbial adhesion ontofluidized chromatography adsorbents

Rami Reddy Vennapusa, Sabine Binner, Rosa Cabrera, and Marcelo Fernandez-Lahore*

Downstream Processing Laboratory, Jacobs University Bremen gGmbH, Campus Ring 1,D-28759, Bremen, Germany.

2.5.1 Abstract


model system composed of intact yeast cells and agarose-based chromatography adsorbent

surfaces. Biomass components and beaded adsorbents were characterized by contact angledeterminations with three diagnostic liquids and, complementarily, by zeta potential

measurements. Such experimental characterization of the interacting surfaces has allowed

the calculation of interfacial free energy of interaction in aqueous media vs. distance

profiles. The extent of biomass adhesion was inferred from calculations performed

assuming standard chromatographic conditions, but different adsorption modes. Several

stationary support / mobile phase systems were considered i.e. ion-exchange, hydrophobic

interaction, and pseudo-affinity. Calculated interaction energy minima revealed marginalattraction between cells and cation-exchangers or agarose-matrix beads (U≤ |10-20|k T) but

strong attraction with anion-exchangers (U≥ |200-1000| k T). Other systems including

hydrophobic interaction and chelating beads showed intermediate energy minima values (U

≈ |40-100| k T) for interaction with biological particles. However, calculations also showed

that working conditions in the presence of salt can promote cell aggregation besides cell-to-

support interaction. Predictions based on the application of the XDLVO approach were

confirmed by independent experimental methods like biomass deposition experiments andlaser diffraction spectroscopy. Understanding biomass attachment onto chromatographic

supports can help in alleviating process limitations normally encountered during direct

(primary) sequestration of bioproducts.



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2.5.2 Introduction

Expanded Bed Adsorption (EBA) has been proposed as anintegrative downstream


feedstock e.g. a cell containing fermentation broth. This unit operation has the potential tocombine solids removal, product concentration, and partial purification in a single

processing step. The application of EBA implies, however, that intact cell particles or cell

debris present in the feedstock will interact –in a minor or larger extent- with fluidized



sorption performance under real process conditions. Moreover, biomass interaction would

result in increased buffer consumption in order to remove and wash away sticky biological particles. Biomass components can also mask binding sites thus reducing their availability

to the targeted species. These phenomena i.e. decreased sorption performance and buffer

consumption is detrimental to cost-efficient processing utilizing expanded bed adsorption

and other direct sequestration unit operations(Fernandez-Lahore et al. 1999).

The deposition of microbial cells or biomass debris is related to the physico-chemical

characteristics of the cell-surface components. These surfaces are in most cases of anionic

nature due to the existence of negatively charged chemical groups like phosphate,

carboxylate, and sulphate moieties. However, the cell envelop can also exert hydrophobic

interaction due to the presence of S-layer proteins, amphipathic polymers, and lipids.

Therefore, microbial deposition onto (process) surfaces will be driven by the polymeric

components of the rigid outer boundary and eventually, by the presence of cell-surface

appendages (if present). On the other hand, biomass deposition will be governed by the

nature (material structure) and functionality (ligand type) of the surface e.g. the structure of

the chromatographic support.

Previous studies on biomass-adsorbent interactions were restricted to simple diagnostic

tests to determine the extent of cell –or cell debris- attachment to the desired

chromatographic supports (Feuser et al. 1999). The measurement of the zeta potential has

been proposed for a better understanding and prediction of biomass-adsorbent interactions

during ion-exchange expanded bed adsorption (Lin et al. 2006). Such systems are obviously

dominated by Coulomb-type interactions and therefore, non-electrostatic interactions areanticipated to play a minor role (Vergnault et al. 2007). Recent studies have highlighted



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2.5.3.1 Materials

Chromatographic matrices and columns were purchased from GE Health Care (Munich,Germany). α-bromonaphtalene and formamide were obtained from Fluka (Buchs,

Switzerland). Water was ultra pure quality. All other chemicals were analytical grade.


Yeast cells (Saccharomyces cerevisiae FY 86, wild type, haploid) were cultivated in shake-

flasks, harvested at late exponential phase by centrifugation, and washed three times with

10 mM phosphate buffer solutions, as previously described (Ganeva et al. 2004). Cells wereemployed immediately after preparation.



described (Henriques et al. 2002). Washed cells were suspended to 10% (w/v) in 20mM

phosphate buffer, pH 7 (ion-exchange buffer / Buffer A /σ = 4 mS·cm-1), Buffer A

containing 1.2 M ammonium sulphate (hydrophobic interaction buffer / Buffer B /σ = 145mS·cm-1), and 20 mM phosphate buffer adjusted to pH 7.6 with 250 mM sodium chloride

(Chelating buffer / Buffer C /σ = 30 mS·cm-1). Cells were subsequently poured onto agar

plates containing 10% glycerol and 2% agar-agar. The plate was allowed to dry for 24-36

hours at room temperature on a properly leveled surface free from dust. Salt crystallization

was avoided. Agar plates without cell spreads were utilized as control.

Contact angles were measuredas per the sessile drop method (Sharma and Rao 2002)

utilizing a commercial goniometric system (OCA 20, Data Physics instruments GmbH,

Filderstadt, Germany). The three diagnostic liquidsα-bromonaphtalene, formamide, and

water were employed. All the measurements were performed in triplicate and at least 20

contact angles per samples were measured.



cell particles. Previous to pouring onto the agar plates, matrix beads were frozen in liquidnitrogen and crushed mechanically. Crushing efficiency was assessed by microscopic



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161

studies were done by injecting a 4 ml biomass pulse (OD≈ 0.8 AU). Experiments were

performed utilizing the above described buffer solutions. The operational flow rate was

76.4 cm·h-1. Particle breakthrough curves were obtained by monitoring the effluent

suspensions at 600 nm. On the basis of such data, a lumped deposition parameter (α) wascalculated according to Redman et al. (Redman et al. 2004).




ABmwc

ELmwc

LW mwc



term, and UEL is the EL interaction term. The subscriptm is utilized for the

chromatographic matrix (adsorbent bead), w refers to the watery environment, and c to the




measurements utilizing three diagnostic liquids, according to Van Oss (Van Oss 1994). In

turn, this data can be employed to evaluate the free energy of interaction between two

defined surfaces (ΔGLW and ΔGAB). ΔG represents here the interaction energy per unit area

between two (assumed)infinite planar surfaces bearing the properties of the adsorbent bead

and the cell (interaction) or two cells (aggregation), respectively. Interaction between any

of these two surfaces are evaluated at a closest distance of approximation (h0 ≈ 0.158 nm)

(Bos et al. 1999). When integrated into mathematical expressions accounting the geometric

constraints existing between two interacting bodies,ΔG values can be utilized to calculatethe corresponding energy-distance profile (U vs. H). Details of this procedure were

published (Bos et al. 1999; Vennapusa et al. 2008).ΔGmwc and ΔGcwc was calculated

according to Vennapusa et al (Vennapusa et al. 2008).ΔGLW are also related to the

Hamaker constant, as follows:

LW Gh A Δ−= 2012π (2)



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UEL energy-distance profile can be calculated, assuming either plate-sphere or sphere-


potential values are measured by electrophoretic mobility experiments (Vennapusa et al.

2008). Calculations were performed employing a commercial software package (GraphPad

Prism, GraphPad Software Inc., San Diego, CA, USA).



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2.5.4 Results and discussions

2.5.4.1 Contact angle measurements and surface energy components

The diagnostic liquids water, formamide, andα-bromonaphtalene were employed to

measure contact angles onto homogeneous lawns of the materials under study i.e. intact

yeast cells or crushed Sepharose beads. The sessile drop technique was employed. The

utilization of the agar plate method assured that contact angle values were obtained for the

mentioned materials in the hydrated state. Diagnostic liquids were chosen to have a higher

surface tension than the sample materials so as to allow for stable drop formation and

accurate contact angle determination. Materials were carefully equilibrated with buffers

commonly utilized in practice.

Contact angle determinations with three different liquids were performed so as to consider

conditions prevailing in ion-exchange, hydrophobic interaction, or pseudo-affinity

chromatography. Table 1 shows contact angle values obtained by performing

measurements onto layered fragments (< 10µm) of the various chromatographic supports,

including Q-XL, DEAE, SP, Chelating-Cu2+, Phenyl, and agarose-base matrix beads.

At neutral pH, adsorbent contact angle values were≈ 7-10 for water and≈ 10-13 for formamide, when considering the base-matrix, chelating matrix, the anion-exchanger

DEAE-Sepharose, and the cation-exchanger SP-Sepharose. On the other hand, for the

mentioned adsorbents the contact angle values withα-bromonaphtalene were≈ 39-45.

Overall, these values indicate the very hydrophilic nature of such materials. For the

composite support XL-Q Sepharose an increase in the contact angle value for α-

bromonaphtalene was noticed, which might indicate an even increased hydrophilic

character due to the presence of superficial Dextran chains. As expected due to the presenceof hydrophobic ligands, the Phenyl-Sepharose material showed decreased contact angle

values with α-bromonaphtalene. These data indicate that similarities and differences

between different supports can be actually observed on the basis of contact angle

determinations. Published work have shown that the addition of salt can actually influence

the contact angle values -and correspondingly the surface free energy components-

obtained for some types of mineral particles (Karagüzel et al. 2005).



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Table 2: Contact angle measurements for yeast cells. Determinations were performedunder conditions normally encountered in ion-exchange, hydrophobic interaction, andchelating systems.


parameters for chromatographic media and biomass particles according to the acid-base

approach (Bos et al. 1999). Table 3 depicts the surface energy components (γ) calculated

for various chromatographic supports under typical buffer conditions ion-exchange buffer /

20mM phosphate buffer pH 7.0 (Buffer A ), Hydrophobic interaction buffer (Buffer A

containing 1.2 M ammonium sulphate and Chelating buffer (20 mM phosphate buffer

adjusted to pH 7.6 with 250 mM sodium chloride and 1mM imidazole. These supports can be distinguished on the basis of their characteristicγLW and γ+ (electron acceptor

component of the AB surface tension) parameters. According to such parameters, the

chromatographic supports can be ordered as follows:

γLW → [Phenyl] > [Chelating] ≈ [Agarose-matrix] ≈ [DEAE≈ SP] > [Q-XL]

γ+ → [Q-XL] >> [Agarose-matrix] ≈ [Chelating] > [DEAE≈ SP] > [Phenyl]

As a whole these results indicate that each of the materials studied possess characteristic

surface energetic properties that are experimentally accessiblevia contact angle

measurements with three diagnostic liquids. For example, Phenyl supports presented high

γLW values (∼39 mJ·m-2) but low γ+ values (1.3 mJ·m-2) in comparison with the agarose-

backbone bead. On the contrary, the composite material Q-XL showed the inverse tendency

i.e. highγ+ values (3.9 mJ·m-2) but lowγLW values (∼29 mJ·m-2).

Yeast cell suspension Contact angle ( θ) (Degrees)

Water Formamideα -

Bromonaphtalene

IEX-type buffer 15.0 ± 2.2 14.0± 1.0 54.0± 1.8

HIC-type buffer 10.0 ± 0.5 12.0± 1.1 33.0± 2.4

Chelating-type buffer 11.7 ± 2.4 13.7± 1.7 49.3± 1.0



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Table 3: Surface energy parameters for beaded chromatographic supports calculated fromcontact angle measurements under standard buffer compositions.

Support type Surface energy parameters [mJ·m -2]


Q-XL 28.9 3.9 53.2 28.8 57.8 +26.6

DEAE 34.1 2.3 54.5 22.3 56.7 +30.7

SP 35.0 2.0 55.7 21.1 56.4 +31.9

Chelating- CU 2+ 32.3 3.0 53.7 25.0 57.4 +26.3

Phenyl 39.3 1.3 55.1 16.9 56.3 +26.8

Agarose bead 32.8 2.9 53.6 24.9 57.7 +28.1

Modification in the surface characteristics of intact yeast particles were also noticed upon

observation of the values taken by theγLW and γ+ parameters (Table 4), according to the

chemical environment provided by the proposed mobile phases:

γLW → [HIC Buffer ] >> [Chelating Buffer ] > [IEX Buffer ]

γ+ → [IEX Buffer ] > [Chelating Buffer ] >> [HIC Buffer ]

These results are indicative of an increased hydrophobic character for cells in the presence

of high concentrations of ammonium sulphate (HIC Buffer) and indicative of an increased

Lewis-acid character for cells in dilute phosphate buffer (IEX Buffer).

Summarizing, surface energy parameters are able to characterize the various

chromatographic systems under consideration. As observed from Table 3 and 4, the

parameter Δ Gsws took always values +24-31 mJ·m-2 reflecting the hydrophilic nature of the

yeast cells and the chromatographic beads. For comparison, the Δ Gsws of hydrophilic

repulsion for Dextran T-150 is +41.2 mJ·m-2 (Van Oss 2003).



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Table 4: Surface energy parameters for yeast cells calculated from contact anglemeasurements, under conditions provided by typical chromatographic mobile phases.

Yeast cellsuspension

Surface energy parameters [mJ·m -2]


IEX-type buffer 27.9 4.4 51.5 30.1 58.3 +24.3HIC-type buffer 37.9 1.5 54.8 18.2 56.0 +27.0Chelating-type

buffer30.3 3.5 53.4 27.3 57.6 +25.9

2.5.4.2 Interfacial free energy of interaction and energy-distance profilesInteraction between biomass particles and chromatographic beads can be understood by

calculating interfacial free energy (U) vs. distance (H) profiles. These calculations are


the additional information gathered from zeta potential determinations. Table 5 depicts the

interfacial free energy of interaction between a biomass particle and chromatographic

adsorbent surfaces in aqueous media at closest distance of approximation (1.57 Å).

Furthermore, this table also gives information on zeta-potential values for the mentionedadsorbents.

Hydrophobic interaction and immobilized-metal affinity chromatography are operated in a

context characterized by an increased salt concentration (high ionic strength and

conductivity) in the mobile phase, as well as, by uncharged beaded adsorbents. Therefore, it

is expected that the information provided by contact angle determination will be more

relevant to understand cell-to-support interactions than the information providedvia z- potential determinations. This situation is radically different from the case of the ion-

exchangers where, due to the low conductivity of the mobile phases and the charged nature

of the adsorbents, zeta-potential has been established as a parameter describing biomass

deposition onto process supports (Lin et al. 2006).



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The Hamaker constant ( A) for the interaction chromatographic systems under study were

calculated fromΔGLW according to Equation (2). A values, according to the adsorption

mode, can be ordered as follows:

HIC (1.1k T) > IMAC (0.40k T) > IEX (0.34k T)

Table 5: Interfacial free energy of interaction between intact yeast cells and agarose beadedsupports, at closest distance of approximation. Calculations were performed assuminginteraction under typical bioprocess conditions. Zeta-potential values for thechromatographic beads are provided.

Figure 1: Total free energy of interaction as function of distance between intact yeast cellsand several chromatographic supports, under conditions provided by commonly utilizing

mobile phases. (— ) Q XL, (— ) DEAE, (— ) Phenyl, (— ) IMAC-Cu+2

, (— ) Base, (— )SP.

Support ΔG [mJ·m -2] Zeta potential [mV ]

ΔGLW

ΔGAB

Q-XL -0.9 +26.3 +20.0DEAE -1.4 +28.7 +15.0

SP -1.5 +29.7 -30.0Chelating- CU 2+ -1.7 +29.6 -8.0

Phenyl -4.8 +36.5 -0.1Agarose bead -1.3 +27.6 -2.0



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Figure 1 depicts interaction energy (U) vs. distance (H) profiles calculated according to the

XDLVO approach, utilizing the data provided before (Table 5). Calculated secondary

energy minima occurring at≈ 5-10 nm upon interaction of a yeast cell and the adsorbent

surface were observed. Calculations assumed sphere-to-plate geometry. The depth of such

energy minima shifted from low to moderate values≈ -5-20 k T in dilute buffer solutions for

the agarose-base material or the cation-exchanger down to intermediate values≈ -40-120

k T at high salt concentrations for Chelating and Phenyl supports. Anion exchangers

showed, in 20 mM phosphate buffer, energy pockets in the range -200-400 kT. These

values increased to > |1000| kT in 10 mM phosphate buffer. The information provided by

analyzing U vs. H profiles is in full agreement with previous experimental data concerning

biomass interaction onto expanded bed adsorbents (Fernandez-Lahore et al. 1999).

Application of the extended DLVO approach is justified since due to the very polar nature

of the buffer solutions where cell-adsorbent interactions take place; these interactions are

known to be strongly influenced by polar Lewis acid-base (AB) or electron-acceptor /

electron-donor forces. Contributions by electric double layer (EL) forces and particularly

contributions by apolar Lifshitz-van der Waals (LW) forces are also expected to occur.

The extended DLVO approach has served to explain the behavior of many other colloidalsystems. Brandt and Childress have demonstrated that short-range interactions between


the role of AB forces(Brant and Childress 2002). Van Oss and coworkers have studied the

stability of a thixotropic suspension of 2μm hectorite particles and concluded that Lewis

acid-base interactions play a key role in the coagulation dynamics of such system (Grasso

et al. 2002).

2.5.4.3 Interfacial free energy of aggregation and energy-distance profiles

Contact angle and zeta potential determinations, as reported in this work have been utilized

to calculate energy vs. distance profiles between two intact yeast cells. Table 6 shows

ΔGLW, ΔGAB, and zeta-potential determinations for yeast cells in various buffers. Sphere-to-

sphere geometry was assumed. These XDLVO calculations can be observed in Figure 2 and

they have indicated that cell-to-cell aggregation might have the chance to occur under the

conditions provided by the hydrophobic interaction buffer e.g. at high conductivity values.In the later case, a secondary energy minima (∼-30 k T) can be anticipated at a distance of 5



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170

nm. Cell clumping in the presence of salt was confirmed by confocal microscopy and laser

diffraction studies (Data not shown).

On the other hand, moderate energy minima were observed for aggregation of cells

suspended in chelating buffer (∼-8 k T @ 5 nm). However, moderate cell clumping could

exist in buffers containing 250 mM sodium chloride i.e. IMAC buffer.

The secondary interfacial free energy well between to yeast cell was of a very limited depth

in the case of dilute phosphate buffer (∼-4 k T @ 5 nm). These low attractive forces would

be easily disrupted by the hydrodynamic stress normally encountered in most processing

schemes. Therefore, cell-to-cell aggregation would rarely take place when biological

particles are suspended in dilute buffer solution due to higher propensity of the cellcomplex to be disrupted by shear drag.

The mentioned aggregation behavior of yeast particles suspended in buffers of various

chemical compositions is also reflected by the values of the corresponding Hamaker

constants, as follows:

HIC (2.0k T) > IMAC (0.65k T) > IEX (0.34k T)and therefore, LW forces can be considered of importance regarding aggregation

phenomena, particularly for cells suspended in high conductivity buffers.

Table 6: Interfacial free energy of aggregation between yeast cells at closest distance of approximation. Calculations were performed assuming standard chromatographicconditions. Zeta potential values are provided.

Yeast cells ΔG [mJ·m-2

] Zeta potentials [mV ] ΔG LW ΔG AB

IEX-type buffer -1.5 +25.1 -18.0

HIC-type buffer -8.8 +35.9 -0.1

Chelating-type

buffer-2.8 +28.7 -8.0



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Figure 2: Interfacial free energy as function of distance between two yeast cells under mobile phases having typical chemical compositions for ion-exchange, hydrophobicinteraction, and immobilised-metal ion affinity chromatography. (— ) IEX buffer, (— )Chelating-Cu2+, (— ) HIC.


Biomass deposition experiments were performed to evaluate overall yeast cells deposition

onto ion-exchange, hydrophobic interaction, and pseudo-affinity chromatographic supports.

This allowed an independent experimental verification of the predictions made on the basis

of energy vs. distance calculations. Interaction phenomena taken place in each of these

chromatographic systems are verified utilizing mobile phase standard compositions i.e. IEX

buffer, IMAC buffer and HIC buffer.

Figure 3 depict the cell effluent profiles measured for the various chromatographic systems

i.e. diverse combinations of solid and mobile phases. Biomass deposition experiments

showed a characteristic cell effluent profile for each of the systems under study. Particle

retention was extremely high for Q-XL and DEAE materials, moderate for Phenyl and

Chelating supports, and very low for the cation-exchanger and the base matrix. Biomass



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deposition behavior was reflected by an “attachment efficiency” number (α), a lump

parameter describing such phenomena. Qualitative and quantitative evaluation of cell

deposition experiments revealed several underlying phenomena like cell-to-support

attachment (interaction), prevention of cell depositions by already deposited biomass particles (blocking), and cell-to-cell ripening (aggregation). Cell-to-cell aggregation might

represent and important mechanism promoting overall cell attachment during biomass

deposition experiments. Therefore, increased values for the lumpedα parameter might

indicate not only stronger cell-to-supportinteraction but enhanced cell-to-cellaggregation .

Consequently, results from biomass deposition experiments will reveal conditions

prevailing during real process performance where both interaction and aggregation

phenomena can coexist.

Figure 3: Biomass deposition experiments with intact yeast cells onto several processsurfaces. Mobile phases of standard chemical compositions were employed. () QXL, ( )DEAE, ( ) Phenyl,( ) IMAC Cu+2, ( ) Base, ( ) SP.



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Figure 4 shows the correlation between the attachment efficiency parameter and the depth

of the secondary free energy of interaction between a cell particle and a chromatographic

bead. Points corresponding to the various chromatographic systems can be observed. Three

main groups can be clearly distinguished:

a) Group I characterized byα ≤ 0.15 and U≤ |10-20| k T. This group contains systems

were both cell-to-support interaction and cell-to-cell aggregation is negligible and

therefore, overall biomass deposition phenomena can be neglected[CEX].Underlying interaction mechanisms within Group I are repulsive EL and AB forces

with moderate attractive LW forces. Cell-to-cell forces are predominantly repulsive

mainly due to AB and EL components.

b) Group II characterized by 0.2≤ α ≤ 0.4 and U ≈ |50-100| k T. This group is

composed by systems were mixed phenomena occur i.e. there is a degree of

biomass deposition onto the solid phase but additional cell entrapment can exists

due to aggregation [Phenyl and Chelating]. Underlying interaction mechanisms

within Group II attractive LW forces, moderately repulsive AB forces, and a

negligible EL component. Cell-to-cell forces are predominantly attractive mainly

due to LW forces.

c) Group III characterized byα > 0.90 and U > |200-1000| k T. This group represents

systems with strong cell-to-support interaction, mainly mediated by electrostatic

attraction (EL) between the interacting bodies. AB and LW forces play a minor role

in this case.

For expanded bed adsorption (EBA) which is the more studied system concerning biomassdeposition evidence exits in the open literature regarding problem-free operation was

consistently reported for CEX (Group I). On the contrary, biomass interference with

appropriate sorption performance was noticed for AEX (Group III). Information regarding

Group II chromatographic systems is scarce. However, recent reports also indicate that such

process combinations are suffering from biomass compatibility limitation (Poulin et al.

2008; Smith et al. 2002).



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Figure 4: Correlation between the depth of energy pocket and lump factor alpha for several process systems.( ) Cation exchangers, ( ) Base matrix, ( ) Chelating Cu2+, ( ) Phenyl,[( ) DEAE, ( ) Q-XL in 10mM PO4 buffer].

2.5.5 Conclusions

A comprehensive approach to understand biomass attachment onto chromatography

adsorbent surfaces with special emphasis on commonly utilized chromatographic systems

have included several interaction forces, according to the XDLVO approach. These

calculations were based on the experimental determination of contact angles with three

diagnostic liquids and the additional information gathered from zeta-potentialdeterminations.

Qualitative and quantitative evaluation of cell adhesion experiments have revealed several

underlying phenomena like cell-to-support sticking, prevention of cell depositions by

already deposited biomass particles (blocking), and cell-to-cell aggregation (ripening). A

correlation between the depth of the interaction energy pockets and the deposition

coefficient values was established and three distinct groups defined.



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ABγ Polar or acid–base component of surface tension [mJ⋅m-2]−γ Electron-donor component of surface tension (Lewis base) [mJ⋅m-2]


ζ Zeta potential [mV]


α Lumped biomass attachment coefficient [-]




References

177

2.5.8 Referances



23(2):179-230.Brant JA, Childress AE. 2002. Assessing short-range membrane-colloid interactions using

surface energetics. J Membr Sci 203:257-273.


Colloid Interface Sci 200(1):172-181.



adsorption. Biotechnol Bioeng 64(4):484-96.Feuser J, Walter J, Kula MR, Thommes J. 1999. Cell/adsorbent interactions in expanded




26(11):933-7.



1(1):17-38.



1115.

Karagüzel C, Can MF, Sönmez E, Celik MS. 2005. Effect of electrolyte on surface free

energy components of feldspar minerals using thin-layer wicking method. J. Colloid

Interface Sci. 285(1):192-200.





Chem 37:133-142.

Poulin F, Jacquemart R, DeCrescenzo G, Jolicoeur M, Legros R. 2008. A Study of the





References

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1785.



98(3):341-463.







Van Oss CJ. 1994. Interfacial forces in aqueous media. New York: M. Dekker. viii, 440p.

p.



16(4):177-190.


adsorbent-biomass interactions during expanded bed adsorption onto ion exchangersutilizing surface energetics. J Chromatogr A 1181(1-2):9-20.

Vergnault H, Willemot R-M, Mercier-Bonin M. 2007. Non-electrostatic interactions

between cultured Saccharomyces cerevisiae yeast cells and adsorbent beads in

expanded bed adsorption: Influence of cell wall properties. Process Biochem

42(2):244-251.

Voloshin S, Shleeva M, Syroeshkin A, Kaprelyants A. 2005. The Role of Intercellular

Contacts in the Initiation of Growth and in the Development of a Transiently Nonculturable State by Cultures of Rhodococcus rhodochrous Grown in Poor

Media. Microbiology 74:420-427.



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2.6 The effect of chemical additives on biomass deposition ontobeaded chromatographic supports

Rami Reddy Vennapusa and Marcelo Fernandez-Lahore* Downstream Processing Laboratory, School of Engineering and Science, Jacobs University

Bremen gGmbH, Campus Ring 1, D-28759, Bremen, Germany.

2.6.1 Abstract

Common limitations encountered during the direct recovery of bioproducts from an

unclarified feedstock are related to the presence of biomass in such processing systems.

Biomass-related effects can be described as biomass-to-support deposition and cell-to-cell

aggregation. In this work, a number of chemical additives were screened for their ability toinhibit either biomass deposition, cell aggregation, or a combination of both effects. Several

interacting pairs were screened. These were composed of i. a commercial chromatographic

matrix harbouring a variety of ligand types and ii. intact yeast cells -as a model biomass

type. Studies were performed on the basis of partitioning tests and colloid deposition

experiments. Results indicated that the incorporation of the synthetic polymer PVP 360 into

the mobile phase has alleviated biomass deposition onto weak-anion exchanger beads by a

factor of ≈3. This behaviour correlated well with calculations performed according to theXDLVO approach: the secondary (interaction) free energy pockets decreased from -230k T

to -100 k T in the absence and in the presence of PVP 360, respectively. Experiments

performed in parallel demonstrated that total binding capacity for the model protein (BSA)

decreased minimally, from 33.6 to 32.4 mg/ml. Other combinations of additives and

adsorbents were tested. However, no solution chemistry was able to inhibit biomass

deposition onto strong (composite) ion exchangers. Moreover, yeast cells deposition was

only marginally decreased when hydrophobic interaction and pseudo-affinity supports wereexplored. The utilization of non-toxic polymers could help to avoid detrimental biomass

deposition during expanded bed adsorption of bioproducts and other direct contact

sequestration methods.



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2.6.2 Introduction

Current bottleneck in the downstream processing of biological products can be alleviated

by application of direct sequestration methods. For example, the utilization of expanded

bed adsorption (EBA) may play an important role during product primary capture. This process strategy permits simultaneous solids separation and product concentration and

(partial) purification. Therefore, an integrative technology presents a clear benefit as it

reduces the number of process steps and contributes considerably to cost reduction, by

saving on process times and capital demands (Anspach et al. 1999).

To deliver appropriate sorption performance expanded bed systems have to allow for the

formation of a stable or perfectly classified fluidized bed, even in the presence of a turbidfeedstock. However, this is often not the case. It was early reported (Fernandez-Lahore et

al. 1999; Feuser et al. 1999) that interactions between the biomass components and the

fluidized chromatographic adsorbents may disturb the otherwise stable expansion of the

bed, by changing its hydrodynamic characteristics. Moreover, biomass deposition can

reduce the life expectancy of the (costly) matrix due to adsorbent fouling and due to the

harsh regeneration conditions subsequently required to release the bound cellular material

(Dainiak et al. 2002; Feuser et al. 1999). Deteriorated process performance in expanded bed

systems generates an increased processing time and capital investment (Curbelo et al.

2003). Therefore, the biofouling of chromatographic supports is a significant technical

challenge which has to be better understood to overcome the many limitations that have

been addressed in the last years.

The deposition of microbial cells or biomass debris is related to the physico-chemical

characteristics of the cell-surface components. These surfaces are in most cases of anionicnature due to the existence of negatively charged chemical groups like phosphate,

carboxylate, and sulphate moieties. However, the cell envelop can also exert hydrophobic

interaction due to the presence of S-layer proteins, amphipathic polymers, and lipids.

Therefore, microbial deposition onto (process) surfaces will be driven by the polymeric

components of the rigid outer boundary and eventually, by the presence of cell-surface

appendages (if present). On the other hand, biomass deposition will be governed by the

nature (material structure) and functionality (ligand type) of the surface e.g. the structure of

the chromatographic support.



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A semi-quantitative analysis of biomass interactions with several biomass-adsorbent pairs

was performed by Feuser et al (Feuser et al. 1999). Since then, several studies were devoted

to determine the importance and extent of biomass effects on the sorption performance of

fluidized beads (Fernandez-Lahore et al. 1999; Fernandez-Lahore et al. 2001). In order to

overcome such limitations a methodological design approach has been proposed to

determine appropriate operational windows so as to reduce biomass adsorbent interactions

to a minimum (Lin et al. 2001). Our group has recently made an attempt to understand – at

the local level - the deposition of biomass particles onto several process surfaces. This

novel approach might offer a more universal approach and valuable information to guide

process and material design (Vennapusa et al. 2008).

The shielding of chromatographic support surfaces with polymeric layers proved to inhibit

non-specific interactions and therefore to be a helpful strategy to optimize separation

methods, like high performance chromatography or capillary electrophoresis (Desilets et al.

1991; Petro and Berek 1993; Santarelli et al. 1988; Schomburg 1991). A similar strategy

was attempted during expanded bed adsorption by covering fluidised beads with

polyelectrolyte or agarose to reduce biomass interference (Dainiak et al. 2002; Viloria-Cols

et al. 2004). Other methods implemented to reduce non-specific interaction of biological

particles included a thermal treatment of the crude feedstock before contacting with thesolid phase (Ng et al. 2007). However, biomass deposition or cell aggregation is still

observed in many adsorbent-biomass systems e.g. with anion-exchangers, hydrophobic

interaction beads and (some) pseudo-affinity supports (Fernandez-Lahore et al. 2000;

Poulin et al. 2008; Silvino Dos Santos et al. 2002; Smith et al. 2002). There is room enough

for investigations concerning the potential effects of solution chemistry changes on biomass

deposition in bioprocessing systems.

The mechanistic understanding of transport and deposition of microbial cell onto process

surfaces has significant interest in various bioprocess situations. Traditionally, microbial

deposition has been studied employing packed-beds of collector particles. A population of

biological particles is introduced into such systems and the suspended biomass effluent is

monitored as a function of process time. This type of experiments can provide useful and

quantitative information when assessing factors like cell size and shape, microorganisms

strain, growth phase, bead size, surface coatings, fluid velocity, and ionic strength on celldeposition onto process media (Tari et al. 2008). A common approach to evaluate biomass



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deposition in laboratory packed-bed experiments employs the “clean-bed” filtration model

(CBFM). In this case, mass transport phenomena are accounted by the “single-collector

contact efficiency” (η0) while the physicochemical phenomena related to biomass

attachment are reflected by the “attachment efficiency parameter” (α).

This work has gathered information on the effect of several chemical additives, which were

incorporated into chromatographic mobile phases, on biomass deposition onto

chromatographic adsorbents. Additives belong to the group of synthetic polymers, non-

ionic surfactants, neutral detergents, and salts. Yeast cells were utilized as model biomass

particles. Various combinations of commercial adsorbents and additives were screened for

cell depositionvia partition and biomass deposition experiments. Theextended Derjaguin-

Landau-Verwey-Overbeek (XDLVO) theory was employed to explain the observed cell

deposition behaviour.



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2.6.3.1 Materials

Chromatography adsorbents and columns were purchased from GE Healthcare, Munich,

Germany. Solvents utilised for contact angle measurements:α-bromonaphtalene (99%

purity) and formamide (99.5% purity), were obtained from Fluka, Buchs, Switzerland.

Water was ultrapure quality. Polyethylene glycol (PEG 3350), polyvinyl alcohol (10 kDa;

Product number 8136), polyvinyl pyrrolidone (PVP 10 and PVP 360),

Polyoxyethylenlaurylether (Brij 35 and Brij 58) were obtained from Sigma-Aldrich Chemie

GmbH, Steinheim, Germnay. Tween 20, Pluronic F68, Nonidet P40, Tween 20 and Triton

X100 were from AppliChem GmbH, Darmstadt, Germany. Sodium polyphosphate (NaPP)

and sodium fluoride (NaF) were obtained from Riedel-de Haën, Seelze, Germany. All other chemicals were of analytical grade.


Saccharomyces cerevisiae wild strain FY 86, haploid, was obtained from Dr. V. Ganeva

(Sofia University, Bulgaria). The strain was maintained on agar plates made from yeast

extract 10 g/l, soy peptone 20 g/l and agar 20 g/l with D-glucose 20 g/l as additional carbon

source. Yeast cells were grown on YPD medium [1% (w/v) yeast extract, 2% (w/v) peptone, 2% (w/v) glucose] utilising 300 ml cotton-plugged-conical flasks on a rotary

shaker at 30°C. The culture volume was 100 ml and the shaker speed 150 rpm. Growth was

monitored turbidimetrically at 600 nm. After reaching exponential phase (OD600 = 1.9),

cells were collected by centrifugation at 2000 g , washed twice with 10 mM phosphate buffer

(pH 7.6) and re-suspended to give 7.5 × 108 cells·ml−1 (24 mg cell dry wt per ml) (Ganeva

et al. 2004).

2.6.3.3 Physiochemical characterization of particles


Contact angles were measuredas per the sessile drop method utilizing a commercial

goniometric system (OCA 20, Data Physics instruments GmbH, Filderstadt, Germany).

Three diagnostic liquids e.g.α-bromonaphtalene, formamide, and water were employed

(Bos et al. 1999). Details of the experimental procedure, as applied for biomass and crushed

chromatographic beads, were published elsewhere (Vennapusa et al. 2008).



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2.6.3.5 Zeta potential determinations

Particle zeta-potential values were measured with a Zetasizer Nano ZS from Malvern

Instruments (Worcestershire, United Kingdom). Fragmented Sepharose particles were

utilized instead of Streamline beads due to their lower density and to avoid sedimentationduring measurements. Before performing the measurement, particles were contacted with

20 mM sodium phosphate buffer at pH 7.6 for 2 h and further diluted to appropriate particle

count (~200 particles total count). Zeta potential measurements were also performed on

particles which were contacted with 1% solution of PVP 360 and then extensively washed

with phosphate buffer. Zeta potentials were calculated from the electrophoretic mobility

data according to the Smoluchowski’s equation (Ottewill and Shaw 1972). All the

measurements were performed in triplicate.

2.6.3.6 Deposition of yeast cells (Partition experiments)

Deposition of yeast cells onto chromatographic beads was studied by partition experiments.

These experiments were performed in glass flasks (4 cm height, 1.5 cm diameter) with

plastic caps. Vacuum dewatered chromatographic beads (0.5 g) were contacted with a cell

suspension (2.0 ml; 0.03% dry weight) under gentle orbital stirring. The optical density of

the cell suspension remaining in the supernatant was evaluated by absorbance at 600 nm.

Cell number was calculated according to the following expression:

x x y 1155.03363.0 2 += Equation 1

where y is the concentration of yeast of cells (% w/v wet basis) and x is the OD@600 nm.

Cell suspensions having an optical density higher than 1.0 were diluted before photometry.

Samples were taken after 3 h to evaluate total cell deposition (Fernandez-Lahore et al.

2000). Results were expressed as a Cell Partition Index (CPI) which was calculated

according to:

i

f

C

C CPI = Equation 2

whereC f is the final concentration of cells (t = 3h) andC i is the initial concentration of the

yeast cells (t = 0) in the supernatant.



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where μ is the viscosity of the polymer solution [Pa·s] and C is the concentration of PVP

360 [wt. %].



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2.6.4 Results and Discussions

2.6.4.1 The potential of additives to influence cell attachment

Certain chemical components may have the ability to modify the interactions between

microbial cells and chromatographic beads –in aqueous media- by promoting changes in

the free interfacial forces / free energy between bodies:

a) Ionic compounds can alter microbial deposition and transport through surface

charge modification (Brown and Jaffe 2001). Polyphosphates are highly negative

charged chemicals which were shown to decrease microbial adhesion to soils and

synthetic membranes. These compounds find applications as microbial dispersants

and to stabilise suspensions of mineral particles. Sodium polyphosphate [NaPP / n =17] compounds can reduce the zeta-potential of microbial particles (Papo et al.

2002; Sharma et al. 1985).

b) Polyvinylpyrrolidone [PVP] is a non-ionic polymer which has been shown to adsorb

onto oxide-surfaces through an acid-base interaction i.e. surface hydroxyl groups,

acting as Bronsted acids, can interact with PVP segments which are considered

Lewis base in aqueous media (Pattanaik and Bhaumik 2000). PVP was also shown

to interact with dye-affinity chromatography supports (Galaev et al. 1994). PVP 360

was utilized in this study.

c) Some studies have demonstrated that Polyethylene glycol [PEG] is preferentially

excluded from macromolecular surfaces. This might elicit an energetically

favourable sharing of the co-solvent hydration shells surrounding the biological

particle and the chromatography media, thus increasing the partition coefficients

(Gagnon et al. 1996). PEG 3350 was utilized in this study.

d) Poly (vinyl alcohol) [PVA] is a polymer having anionic character. This compound

has been reported to bind to controlled-porosity glass beads and to reduce the zeta

potential of such particles (Wisniewska et al. 2007). PVA adsorption would increase

with pH due to the presence of non-hydrolysed acetate groups i.e. the polymer gain

negative charge [89% hydrolysis in this work]. PVA adsorption depends on



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electrostatic forces, hydrogen bonding, and conformational state. PVA having a

MW of 10 kDa was utilized in this work.

e) Adsorbed polymer / surfactants on the solid surface can modify both physical

surface properties and the interaction between interacting bodies. Therefore, other

non-ionic surfactants have been included: Polyoxyethylene cetyl ether [Brij 58],

Polyoxyethylene sorbitan monolaureate [Tween 20], Polyoxyethylene-

polyoxypropylene block copolymer [Pluronic F68], and Ethylphenolpoly(ethylene

glycolether)n [Nonidet P40].

2.6.4.2 Screening additives with partitioning tests2.6.4.3 The effect of additives on cell deposition

A preliminary exploration (screening) on the potential effect(s) of a number of different

additives on yeast cell deposition onto commercial chromatographic beads was performed

utilizing simple partition tests (Fernandez-Lahore et al. 2000; Lin et al. 2001). Partitioning

tests were carefully optimized to accommodate a variety of yeast-adsorbent interaction

pairs. Under such experimental conditions, yeast cell deposition onto non-functionalized

agarose beads was less than 10% as judged by the cell partition index (CPI≥ 0.90).

Standard experiments were performed in 20 mM phosphate buffer (≈ 4.0 mS/cm) and

therefore a certain degree of deposition onto cation-exchanger materials (CPI≥ 0.7 for SP-

Streamline) was observed due to electrical double layer compression effects (Tari et al.

2008). Contact time was fixed to 3 h so as to evaluate the combined effects of the fast and

the slow phases of cell deposition (Fernandez-Lahore et al. 2000).

Anion-exchangers are known to strongly interact with microbial cells, mainly due tocharge-mediated (electrostatic) effects (Lin et al. 2006). Indeed, partition tests run with the

weak anion exchanger DEAE-Streamline and the strong (composite) anion exchanger Q-

Streamline XL showed high cell deposition i.e. a CPI equal to 0.28 and 0.14, respectively.

Subsequent incorporation of non-ionic polymers / surfactants to the liquid phase has

reduced cell deposition in an extent which depends on the additive and the solid phase

under consideration. Table 1 depict the result of screening tests performed for various

adsorbents and additives. When DEAE beads were employed as the solid phase, the basalcondition for cell deposition (i.e. CPI = 0.28 in buffer) was improved: CPI increased to 0.54



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in the presence of Tween 20, to 0.43 with added Pluronic F68, to 0.60 with Brij 58, and

0.34 with PEG. Particularly effective in inhibiting cell deposition onto DEAE beads was

PVP 360; in this case the CPI raised to 0.81. However, the same additive failed to avoid

cell attachment onto the Q-XL material. This could be explained by the presence of

external Dextran chains in the structure of the composite adsorbent. On the contrary,

polymeric sodium phosphate (NaPP), an ionic agent, showed almost no effect in preventing

cell deposition onto DEAE beads but inhibited such phenomena onto Q-XL beads. It could

be hypothesized that NaPP may interact primarily with yeast particles, rendering them more

negative when DEAE beads are present. Thus, cell-to-adsorbent interactions remain the

same. However, the presence of Q-XL beads may trigger the interaction of the (positively)

strongly charged Dextran chains with the (negatively) charged polyphosphate. This would

shield adsorbent charges thus reducing interaction with suspended cells. The distinct

behaviour of the two anion-exchangers rules out a predominant role for the increased

conductivity of the liquid phase in the presence of NaPP (≈ 9.1 mS/cm).

Further studies performed with the DEAE / yeast system in the presence of PVP 360

showed that CPI is fairly proportional to the concentration of the additive in the liquid

phase. A PVP concentration of 1% (w/v) resulted in maximum inhibition of cell deposition.

Kinetic studies also revealed that PVP 360 seems to interfere with cell depositionmechanisms at early stages i.e. the polymer might inhibit cell-to-support interaction (data

not shown). This phenomenon is discussed in more detail in the sections below.

Partition experiments were also performed with hydrophobic interaction supports (Phenyl-

Streamline) in 20 mM phosphate buffer (pH 7.6) containing 0.75 M ammonium sulphate.

The CPI for the control situation i.e. buffer without additive(s) was 0.75 which correlates

well with previous reported values (Fernandez-Lahore et al. 2000). Addition of non-ionic polymer / surfactants failed to improve the baseline situation e.g. CPI fell within the range

0.69-0.83. Therefore, only a marginal effect –if any- was observed for HIC systems. The

presence of high concentrations of ammonium sulphate is HIC systems might interfere with

the potential action of the additives utilised in this work.

Chelating Streamline was utilized to evaluate cell deposition as well. Zn (II) ions were

immobilized within the IDA groups present in the matrix. Partition experiments were

performed in 20 mM phosphate buffer (pH 7.6) containing 250 mM sodium chloride and 1



Results

190

mM imidazol. Baseline CPI was 0.90 which is similar to values previously reported in the

literature for IMAC (Fernandez-Lahore et al. 2000). For Chelating systems the addition of

non-ionic polymers / surfactants has had a slightly deleterious effect since CPI values

tended to be lower (0.69 – 0.87). This can be explained considering the effect of

considerable amounts of sodium chloride in the liquid phase and / or a possible bridging

effect exerted by the polymers.



R e s u l t s

1 9 1

T a b l e 1 : C e l l d e p o s i t i o n s o f

i n t a c t y e a s t c e l l s o n t o

S t r e a m l i n e b e a d s a s o b s e r v e d

b y p a r t i t i o n e x p e r i m e n t s .

A d d i t i v e s w e r e p r e s e n t a t a

f i n a l

c o n c e n t r a t i o n o f

1 % ( w / v ) . E x p e r i m e n

t s w e r e r u n

i n b u f f e r s h a v i n g a

t y p i c a l c o m p o s i t i o n ,

d e p e n d i n g o n

t h e c h r o m a t o g r a p h i c m o

d e i n v o l v e d

( s e e t e x t ) . C o n t a c t t i m e w a s

3 h . C o n t r o l C

P I ( a g a r o s e m a t r i x ) w a s

≥ 0 . 9 0 . T h e C h e l a t i n g m a t e r i a l w a s

l o a d e d w

i t h Z n ( I I ) i o n s . C P I v a l u e s

w e r e w i

t h i n ± 1 0 %

.

n . d : n o t d e t e r m i n e d

B e a d

t y p e

A d d i t i v e t y p e

↓

N o n e

T w e e n

2 0

P l u r o n i c F 6 8

P E G 3 3 5 0

P V P 3 6 0

P V A

B r i j 5 8

N A P P

Q - X L

0 . 1 4

n . d .

n . d .

n . d .

0 . 3 4

n . d .

0 . 4 0

0 . 8 7

D E A E

0 . 2 8

0 . 5 4

0 . 4 3

0 . 3 4

0 . 8 1

0 . 3 5

0 . 6 0

0 . 3 0

P h e n y l

0 . 7 5

0 . 7 0

0 . 8 0

0 . 7 9

0 . 6 9

n . d .

0 . 8 3

n . d .

C h e l a t i n g

0 . 9 0

0 . 9 4

0 . 9 1

n . d .

0 . 7 4

0 . 6 9

0 . 8 7 *

n . d .



Results

192

2.6.4.4 The effect of additives on protein binding

A useful additive has to inhibit cell deposition onto a defined type of chromatographic

support without interfering with protein (bioproduct) binding. This situation would lead to a

decreased biomass attachment without compromising adsorbent capacity for the targetedspecies. Therefore, partitioning studies were also performed to assess protein sequestration

from a cell suspension with and without a selected number of promising additives.

Partition studies were performed with DEAE-Streamline. In buffer, this material showed a

high affinity number (0.85); the introduction of cells into the system translated in a≤ 5%

reduction in the affinity (binding) for the model protein. It should be recall that this support

type has also a strong tendency to capture cells (Table 1). The addition of chemicals to thesolution phase, showed no dramatic effect on the (equilibrium) capacity of the adsorbent

(Table 2). Among the additives tested, PVP 360 showed a maximum protection against cell

deposition (CPI 0.81 vs. 0.28) while protein binding remained unaltered (Affinity number

0.80 vs. 0.83). Therefore, PVP was clearly acting without interfering with the charge-

mediated attraction between BSA and the adsorbent beads.

Partition studies were performed also with Q-Streamline XL. This material suffers from an

extremely high deposition of cells, probably due to the presence of densely charged

Dextran chains within its composite structure. As sodium polyphosphate was found to be

effective in inhibiting cell interactions with Q-XL, protein-binding capacities were checked

with buffers containing this chemical. Unfortunately, NaPP was found to interfere with

BSA binding as reflected by affinity numbers falling from 0.92 (cells, no chemical) to 0.13

(cells plus additives). It follows that NaPP most probably interacts with the adsorbent by

masking positively charged sites, therefore inhibiting both cell and protein uptake.



Results

194


Data gathered employing a range of adsorbents and chemical additives showed the

beneficial effect of PVP 360 on preventing cell deposition onto the weak anion-exchanger.

In order to confirm such data under dynamic conditions, biomass (yeast cells) depositionexperiments were run. DEAE-Streamline beads were utilized as collectors. Figure 1 depicts

the cell effluent profiles recorded as a function of PVP 360 concentration, within the range

0.01 to 1.0 %. Cell deposition behavior was characterized by a decreased interaction with

the adsorbent in the presence of increased concentrations of the additive in the flowing

phase. The observed lower deposition of cells was reflected by the “attachment efficiency”

parameter (α); α values are shown in Table 3. The baseline condition i.e. no additive

translated into aα value equal to 0.683 which has decreased by a factor of ≈ 8 due to the presence of the additive. Theα value obtained after running cell deposition experiments in

the presence of 50 mM sodium chloride, a condition known to improve system

hydrodynamics with DEAE adsorbents, was 0.213. Combination of 1% PVP 360 and 50

mM sodium chloride resulted in an minimum value for the attachment coefficient (α =

0.052). However, the incorporation of charge-screening ions into the chromatographic

mobile phase may also lead to a decreased capacity for the targeted proteins.



Results

195

Figure 1 : Biomass deposition experiments onto DEAE-beads. Intact yeast cells wereutilised as model biomass. Solution chemistry was provided by a 20 mM phosphate buffer

pH 7.6, which contained PVP 360 at various concentrations: () Control (no additive), ( )0.01% , ( ) 0.05%, ( ) 0.1%, ( ) 0.5 %, ( ) 1 % PVP 360.

Previous work has demonstrated that, as far as a threshold value for the attachment

coefficient e.g.α ≤ 0.15 is not reached, the level of biomass deposition remains low enough

so as to allow for proper bed fluidization and product capture. Therefore, the addition of

PVP within the range 0.2 to 0.5 % would be sufficient to prevent biomass interference with

EBA operation. On the basis of the gathered experimental evidence, anion-exchangerswould operate –in the presence of moderate amounts of PVP 360- similarly to cation-

exchangers. The later are materials which operate without major limitations with a variety

of feedstock compositions (Tari et al. 2008).



R e s u l t s

1 9 6

T a b l e 3 :

L u m p e d a t t a c h m e n t p a r a m e

t e r ( α ) c a l c u l a t e d

f r o m y e a s t

c e l l d e p o s i t i o n o n t o

D E A E b e a d s . R u n s w e r e p e r f o r m e d

i n 2 0 m

M

p h o s p h a t e b u f f e r a t p H 7 . 6 . P V P 3 6 0 w a s e m p l o y e d a s a n a d d i t i v e .

A d s o r b e n t t y p e

P V P 3 6 0 d

( % )

O t h e r a d d i t i v e

C / C

0

( - )

α ( - )

N a k e d

b e a d s a

0

N o n e

0 . 0 1 7

0 . 6 8 3

0

S a l t b

0 . 2 8 0

0 . 2 1 3

N a k e d

b e a d s a

0 . 0 1

N o n e

0 . 1 3 4

0 . 3 3 7

0 . 0 5

N o n e

0 . 2 5 6

0 . 2 2 8

0 . 1

N o n e

0 . 3 8 2

0 . 1 6 1

0 . 5

N o n e

0 . 5 2 8

0 . 1 0 7

1

N o n e

0 . 6 1 4

0 . 0 8 2

1

S a l t b

0 . 7 3 1

0 . 0 5 2

C

o a t e d b e a d s c

0

N o n e

0 . 5 1 4

0 . 1 1 2

a

D E A E - S t r e a m

l i n e b e a d s w e r e u t i l i z e

d .

b S o d i u m c h l o r i d e a t a

f i n a l c o n c e n t r a t i o n o f 5 0 m

M w

a s e m p l o y e d .

c B

y t r e a t m e n t w

i t h P V P 3 6 0 a n d e x t e n s i v e w a s h i n g w

i t h b u f f e r s o l u t i o n .

d P V

P 3 6 0 a d d e d

t o t h e f l o w i n g p h a s e a t a

f i x e d c o n c e n t r a t i o n .



R e s u l t s

1 9 7

T a b l e 4 : T

h e e f f e c t o f

P V P 3 6 0 c o n c e n t r a t i o n o n m o b i l e p h a s e v i s c o s i t y , o n c e l l d i f f u s i o n c o e f f i c i e n t , o n

t h e h y d r o d y n a m i c d r a g e x e r t e d o n

y e a s t p a r t i c l e s , a n d o n

t h e a d s o r b e n t b e a d s e t t l i n g v e l o c i t y .

C o n c e n t r a t i o n

P V P

( % w

/ v )

V i s c o s i t y a

( m P a · s )

D i f f u s i o n c o e f f i c i e n t b

( m 2 · s - 1 )

H y d r o d y n a m

i c d r a g c

( N )

S e t t l i n g v e l o c i t y d

( m · s - 1 )

0 . 0 1

0 . 8 9

6 . 0 x

1 0 - 1 4

9 . 5 x 1 0

- 1 1

4 . 9 x

1 0 - 3

0 . 0 5

0 . 9 2

5 . 8 x

1 0 - 1 4

9 . 8 x 1 0

- 1 1

4 . 7 x

1 0 - 3

0 . 1

0 . 9 7

5 . 6 x

1 0 - 1 4

1 . 0 x 1 0

- 1 0

4 . 5 x

1 0 - 3

0 . 5

1 . 3 7

3 . 9 x

1 0 - 1 4

1 . 4 x 1 0

- 1 0

3 . 2 x

1 0 - 3

1

2 . 1 3

2 . 5 x

1 0 - 1 4

2 . 2 x 1 0

- 1 0

2 . 0 x

1 0 - 3

a L i q u i d p h a s e .

C a l c u l a t e d a c c o r d i n g t o

( Y e h e t a l .

1 9 9 8 )

b F o r y e a s t c e l l s .

C a l c u l a t e d a c c o r d i n g

t o ( B r o w n

2 0 0 7 )

c F o r y e a s t c e l l s .


t o ( J o h n s o n e t a l .

2 0 0 7 )

d F o r a d s o r b e n t b e a d s .


t o ( B r o w n

2 0 0 7 )



Results

198

A potential drawback on the utilisation of PVP 360 in fluidised bed systems is the increase

of viscosity due to the presence of such polymer in solution. In turn, viscosity can affect

process characteristics (Table 4). For example, mass transfer properties of cells can be

altered via a reduced diffusion coefficient. Moreover, cell transport might be affected due

to increased hydrodynamic drag exerted on them. Bed hydrodynamics can be also

compromised by a reduced adsorbent particle settling velocity, which may promoted bead

elutriation. Therefore, it is advisable to keep the concentration of this additive to a

minimum compatible with its function as “cell-deposition-preventing” agent.

To get a better insight on the mode of action of PVP 360 as an additive preventing cell

deposition, DEAE beads were contacted with the additive (4 CV) and subsequently washed

with phosphate buffer (20 CV). Interestingly, cell deposition experiments performed onthese beads –but in the absence of any additive in the solution chemistry- also demonstrated

much less cell deposition than with untreated beads (α = 0.112) see table 3. It can be

concluded that PVP 360 might have been retained on the adsorbent surface by a

combination of physicochemical forces. This is in agreement with previous work with

hydrophilic polymers (Dainiak et al. 2002; Viloria-Cols et al. 2004). However, protein

binding sites remain available within the adsorbent structure. Due to its hydrodynamic

radius of gyration (~ 19 nm) (Armstrong et al. 2004) is unlikely that PVP 360 would havecomplete access to the pores existing in the chromatographic support (pore radius = 29 nm)

(Jungbauer 2005). Moreover, these experiments have demonstrated a beneficial effect of

the additive on cell deposition by decoupling cell attachment from viscosity-related effects

in the presence of PVP.

Other experimental findings employing biomass deposition experiments have generally

confirmed results obtained with partition tests (data not shown). These findings can be

summarised as follows: a) Biomass deposition experiments serve to confirm that other

additives like Tween 20 or Brij 58 were ineffective in inhibiting cell interaction with DEAE

beads; b) The utilization of such chemical additives failed to inhibit cell attachment to

Chelating materials; c) Introduction of PVP 360 and Brij 58 in hydrophobic interaction

systems was limited due to a lack of solubility in ammonium sulphate containing mobile

phases; d) PVP 360 was unable to prevent cell deposition onto Q-XL in agreement with

partition experiments.



Results

199

2.6.4.6 Interfacial free energy of interaction between bodies

The extended DLVO theory can be applied to understand the interaction of two bodies in

aqueous media, on the basis of colloid chemistry principles. In this case, the XDLVO

approach was employed to calculate energy vs. distance profiles between naked or PVP-

covered interaction particles e.g. yeast cells and adsorbent beads. Performing such

calculations require the input of experimentally determined parameters like contact angle

values with three diagnostic liquids and zeta potentials. Details on the mentioned approach

have been published elsewhere (Vennapusa et al. 2008).

Contact angle on hydrated PVP 360 layers were taken from published work (Faibish et al.

2002) and employed to calculate surface energy parameters. Calculations resulted in thefollowing values:

γLW 35.8 mJ·m-2, γ+ 2.2 mJ·m-2, γ- 34.2 mJ·m-2, and γAB 17.3 mJ·m-2

These values were assumed to be the ones corresponding to either yeast cells or adsorbent

beads when PVP 360 is present on their surface. Utilizing this information, the free

(interfacial) energy of interaction was calculated –at the closest distance of approximation

i.e. 1.57 Å and in aqueous media- for four different cases (Table 5):

a) A naked adsorbent DEAE-bead interacting with a naked yeast cell

b) A polymer coated bead interacting with a naked cell

c) A PVP coated bead interacting with a polymer coated cell

d) Two polymer coated yeast cells

Additionally, zeta potential determinations were performed for polymer coated DEAE

beads and intact yeast cells in 20 mM phosphate buffer (pH 7.6). These measurements haveshown that particle zeta potential values can be reduced in the presence of the additive

(Table 5). Similar observations have been made for silica-based particles (Goncharuk et al.

2001).



Results

200

Table 5 : The interfacial free energy of interaction between bodies in aqueous media, atclosest distance of approximation: a) intact yeast cells and DEAE-beads, and b) aggregation between two yeast cell particles. Calculations were performed assuming interaction andaggregation with and without chemical additive at pH 7.6 in 20 mM phosphate buffers.

System ΔGLW [mJ·m-2]ΔGAB [mJ·m-2] Zeta potential[mV]

Naked beada - Cell - 1.4 + 28.7 +15 / -18

Coated bead b - Cell - 1.6 + 20.0 + 5 / -18

Coated bead – Coated Cell

- 3.4 + 12.0 + 5 / -15

Two covered cells - 7.0 + 11.4 -15 / -15

a DEAE Streamline b PVP 360 treated adsorbent

The interaction systems mentioned above can be better understood by interfacial free

energy (U) as a function of distance (H) profiles. Figure 2 depict such energy / force curves

where it can be observed that:

a) Interaction between naked DEAE beads and intact yeast cells is characterized by a

strong interaction, as reported previously. Charge effects i.e. Coulomb-type

attraction is dominating. A secondary energy pocket would exist at 5nm; pocket

depth is -230 k T. This is in agreement with biomass deposition experiments

presented before (Figure 1 and Table 3;α = 0.683).

b) Interaction between a polymer coated adsorbent bead and a naked cell resulted in a

secondary energy pocket of a moderate depth (-100k T). The reduction in

interaction energy / forces can be explained on the basis of modifications observed

in the zeta potential values, particularly for the coated adsorbent bead. This is in

agreement with cell deposition experiment utilizing pre-treated DEAE beads as

collectors (Table 3;α = 0.112).



Results

201

c) The assumption of having PVP 360 molecules covering the cell surface would result

in a situation characterized by increased LW attraction, decreased AB repulsion,

and almost unaffected EL attraction (Figure 2; U≈ -160 k T). This behaviour

couldn’t be verified by biomass deposition experiments. Although a slight decreasein the zeta potential value for cells in the presence of PVP was noticed, evidence

more likely supports the idea that this additive preferentially interacts with the

adsorbent beads.

d) The presence of PVP 360 does not severely compromise colloidal stability of cell

particles in suspension and therefore no aggregation is expected to occur (Figure 2;

U ≈ - 20 k T).

Figure 2 : Energy (U) vs. distance (H) profiles calculated for the interaction between aDEAE-bead and a yeast cell, in 20 mM phosphate buffer at pH 7.6. Calculations were performed assuming 4 hypothetical cases (refer to text), as follows: (— ) DEAE/Cell, (— )[DEAE] pvp/[Cell] pvp, (— ) [DEAE] pvp/[Cell], (— ) [Cell] pvp/ [Cell] pvp.



Results

202

2.6.5 Conclusions

Several chemical additives were evaluated for their capacity to reduce cell deposition onto

a variety of chromatographic adsorbents.

A simple albeit effective method to reduce biomass deposition onto DEAE adsorbent beads

is presented. Addition of PVP 360, a pharmaceutical grade polymer, seems to preferentially

interact with the adsorbent under process-like conditions. Covered adsorbent beads retain

capacity for proteins but substantially reduce the interaction with suspended cells.

The preceding hypothesis is supported by biomass deposition experiments and XDLVO

calculations.

The utilization of safe additives may find practical application to improve the sorption

performance of direct contact methods in the downstream processing of bioproducts.


RRVP great fully acknowledges the doctoral fellowship from Jacobs university.



References

203

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Brown DG, Jaffe PR. 2001. Effects of Nonionic Surfactants on Bacterial Transport through

Porous Media. Environ Sci Technol 35(19):3877-3883.

Curbelo DR, Garke G, Guilarte RC, Anspach FB, Deckwer WD. 2003. Cost Comparison of

Protein Capture from Cultivation Broths by Expanded and Packed Bed Adsorption.

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Dainiak MB, Galaev IY, Mattiasson B. 2002. Polyelectrolyte-Coated Ion Exchangers for

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General Conclusions and Remarks

207

3.0 General conclusions and remarks

Expanded bed adsorption (EBA) is an interesting integrated bioprocess technology unit

operation where solid liquid separation, partial purification and concentration can be

simultaneously achieved. This integrated unit operation loses its significance due tointeraction or aggregation of biological particles onto the process surfaces during direct

sequestration of bioproducts. Many authors have repeatedly addressed this interference of

biomass during primary unit operations of downstream processing such as EBA.

Undoubtedly, biomass effects are detrimental to appropriate sorption performance in EBA.

Information on the underlying mechanisms which govern biomass deposition onto

chromatographic beads, under real process conditions, is still scarce.

To address the significant challenge of biomass interference on EBA performance, the

current thesis work puts emphasis on having a fundamental understanding of the feedstock

behavior during primary-sequestration unit operations in downstream processing. Principles

of colloid chemistry were applied to understand the fouling behavior of the

chromatographic supports. The physicochemical properties of yeast cells (model type of

biomass) and chromatographic supports (several types) were evaluated by contact angles

and zeta potentials measurements. From these experimental determinations, deposition ontothe process surface was predicted using the XDLVO theory. Calculations were confirmed

by independent experiments like biomass deposition in granular beads and laser diffraction

spectroscopy. The XDLVO theory and biomass deposition experiments were able to

explain the attachment behavior of cells as a function of varying solution chemistry, size of

the biological particle, and functionalisation type of the process surface. In this regard, the

approach developed in this work can be anticipated as a universal approach for

understanding the biomass adhesion onto process surfaces. Furthermore, the tools presented

here are useful in guiding process and material design and development.

This piece of work has arrived to remarkable conclusions on the behavior of particulate

feedstock component deposition onto different chromatographic supports of varied

chemistries, ranging from ion-exchangers and hydrophobic interaction supports to metal-

ion chelating surfaces. Besides the utilization of intact yeast cells, other systems like yeast

cell debris and E.coli homogenate were explored with special focus on the ion exchanger

type of chromatographic beads.




208

The following partial conclusions can be mentioned:

1) Ion exchanges surfaces to biomass

The extent of interaction of yeast cells (biomass) with anion- and cation- exchangers

can be explained on the basis of the calculated secondary energy minima e.g. reversible

adhesion can be predicted (Figure 1). The degree of interaction varied with the solution

chemistry e.g. upon changes in buffer pH and conductivity. A positive correlation was

found between energy minima and cell deposition, as evaluated by the so called cell

transmission index (CTI). Coulomb-type interactions, which are related to the measured

zeta potential of the interacting bodies, were confirmed to be dominant. The XDLVO

approach also gave us a clear idea about influence of biomass particle size on the extent of

fouling. The total forces acting during biomass adhesion are greatly altered with the size of

the cell or cell fragments. Secondary interfacial energy minima values were experimentally

validated via biocolloid deposition experiments (BDE). BDE is simple, straightforward and

automatable diagnostic tool, which was developed during the current work. This technique

allowed the calculation of a lumped parameter [α, attachment deposition coefficient]

reflecting biomass interaction and aggregation phenomena.

However, cell-to-cell aggregation is less likely to happen under the conditions

prevailing in an ion-exchange process. This can be explained due to dominant electrostatic

repulsion between (negatively charged) cells in low-conductivity mobile phases. The

conclusion drawn with regard to deposition of biomass onto ion-exchangers from the

fundamental understanding gathered during the current work is in full agreement with the

known EBA operational constraints.

2) Hydrophobic interaction surfaces to biomass

As hydrophobic interactions are expected to occur under high salt concentrations, a

marginal contribution of charge-mediated effects is anticipated under such chromatographic

mode of operation. The consideration of the XDLVO theory was very well justified in the

scenario of hydrophobic interaction chromatography (HIC). In the later case, the

interaction of biomass with the chromatographic beads could be explained due to Lifshitz-




209

Van der Waals (LW) and acid-base (AB) interaction forces. Biomass deposition onto HIC

supports is correlated to the development of a (reversible) energy secondary minimum,

which can be observed to arise from LW and AB forces. Calculations indicated that

moderate interactions between yeast cells and adsorbent beads can develop, especially in

presence of higher salt concentrations at pH 7.

It was also found that cell-to-cell aggregation is taking place in the context of

hydrophobic interaction conditions i.e. at high salt concentrations. Because of the high salt

concentration, the repulsive electrostatic forces are reduced allowing yeast cells to interact

with each other. Again, LW and AB forces were relevant to aggregation phenomena. Buffer

pH and conductivity were found to influence cell-to-bead interaction and cell-to-cell

aggregation. In both cases, predictions based on the XDLVO approach were validated by

biomass deposition experiments, laser diffraction spectroscopy, and confocal microscopy.

3) Chelating beads to biomass

Immobilized ion-metal affinity (“Chelating beads”) chromatography (IMAC) is run at

moderate salt concentrations (viz 250-750 mM sodium chloride). The interaction of

biomass with IMAC-Cu2+ was observed to be related to the development of a (reversible)secondary energy minimum. An influence of buffer pH and conductivity was observed

within normal operational windows. From XDLVO calculations it can be concluded that

favorable interaction of yeast cells with Chelating beads takes place at pH≥ 8. However,

biomass deposition experiments failed to confirm such prediction i.e. a decrease in

deposition coefficient at pH 8 was observed. This anomalous behavior can be explained

considering that Cu2+ can be actually sequestrated from the Chelating beads by yeast cells,

a fact usually exploited for biosorption of metal ions from wastewaters.

Cell-to-cell aggregation behavior also observed at IMAC process buffer conditions. The

aggregation phenomena especially with IMAC Cu2+ system were also discussed. The

extent of cell- cell aggregation was found to be less at IMAC buffer conditions when you

compare with that of the hydrophobic interaction buffer conditions.




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Figure 2 : General correlation betweenα and U.

Force vs. distance profiles were calculated for a large combination of model biomass and

adsorbent bead types. The energy minima values (absolute value / U) obtained for each of

the analyzed cases were correlated with the corresponding deposition coefficient values

(Figure 2). A positive correlation was obtained. It was concluded that total interactionenergy U≤ -25 to -50 kT and biomass deposition parameter α ≤ 0.15 would be a safe region

for EBA operation e.g. biomass interference can be neglected. Deviation in the correlation

was found in such cases where moderate or high cell-to-cell aggregation occurs, for

example in hydrophobic interaction systems.




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5) Remarks

1) The work highlighted the use of yeast as model biomass onto various process surfaces.

The tools developed for understanding of yeast interaction and aggregation onto the process

surfaces can be extended to any different model biomass or any kind of process surface.

From the preceding results and discussions, it allowed us to draw conclusion that

mechanistic tools developed here can be universally applied.

2) Local level understanding of biomass interaction can lead to development and design of

an optimized primary unit operation (like EBA). For example, the amount of hydrodynamic

force required to prevent the interaction or modification of the process surfaces with

polymeric brushes (length of brushes) to prevent interaction.

3) The data provided from this work can act as first step for global modeling of EBA.

4) The knowledge obtained from the physicochemical properties of biomass and absorbent

surfaces would allow easy access to process predictions without any trial and error

experiments in laboratory. Hence the developed approach here can be used to design EBA

process where reduced time and effort is required.

A fundamental knowledge about the roles of key variables affecting interactions

/aggregation described herein is of great importance, because their correct manipulation can

help to prevent or at least mitigate fouling.

6) Recommendations for further work

1) The current thesis work explored interaction of yeast as a model organism onto various

adsorbent surfaces. There is still room to understand the behavior of several other feed-

stocks like yeast and bacterial debris, mammalian cells and plant cells which are commonly

utilized in biotechnology industry as a host system for biopharmaceuticals production. It is

very important to understand the compatibility of various kind of biomass onto process

surfaces, which could allow drawing some general conclusion from where a global model

for EBA process design can be proposed.




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2) The biomass deposition transport phenomenon has to be better modeled where the three

parameters - collision efficiency (cell to process attachment), blocking (amount of process

surface blocked) and ripening (cell-to-cell aggregation), can be quantitatively obtained.

Further quantitative straining models have to be implemented to completely rule out the

role of physical attrition during these biomass deposition experiments.

3) XDVLO predictions made in the current work can be further directly verified

experimentally with force/ distance curves utilizing atomic force microscopy. This would

further broaden understanding and signifies the importance of the various forces to be taken

into consideration.

4) Age of biomass culture and its influence on interaction and aggregation especially with

the hydrophobic materials can be tested. Preliminary studies with the different age of the

culture showed the differences in the deposition phenomenon especially with hydrophobic

material type.

5) HIC/ EBA process limitations are not described in the literature (with any type of

biomass) which is actually prone to have deleterious effects by biomass interference

(observations from current research work). Hence there is room to explore more in thisdirection and define the solution/ operational windows for HIC materials in context of

EBA.

6) PVP 360 additive which was found to inhibit the interaction of yeast with DEAE beads

in this work can be further tested for its compatibility under real EBA operations.

7) Hydrodynamic shear and its impact on the secondary minimum can be explored in detail.



Appendix

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4.0 AppendixBiomass deposition experiments, which were performed during the current thesis work, are

geared towards in-depth understanding of the fate and transport of biomass through the

packed bed chromatographic adsorbents. These understandings could be helpful in

preventing the attachment or predicting the transport behavior of biomass during bioprocess

scenario where direct sequestration of bioproducts expected in presence of biological

particles like expanded bed adsorption.

The physicochemical parameter α can be obtained from such experiments relates to the

attachment efficiency of colloidal particles (yeast) onto the collector surfaces (process

surface). Obtaining such quantitative information is possible through the application of colloid filtration theory. The physicochemical parameter determined from these

experiments can at times lead to false quantative information which may be due to the

physical filtration means. This indicates the cell effluent profiles go down due to the

attrition effects which have been shown previously in many studies (Tufenkji et al. 2004).

Among many models developed to predict the potential for straining, Bradford (Bradford et

al. 2004) and Sakthivadivel (Sakthivadivel 1966; Sakthivadivel 1969) developed a modelto predict the potential of straining based on the system geometry. According to this

straining could have a significant influence when the ratio of the particle diameter to the

median grain diameter (d p/dc) is greater than 0.05. In the current study d p/dc ≈ 0.04, which

means that, physical filtration effects can be neglected. However there are some studies

showing that straining observed when d p/dc values were as low as 0.002 (Tufenkji et al.

2004). To prove that in the current thesis work straining can be neglected, biomass

deposition experiments were performed with colloids (yeast) utilized in the study with thenon-interacting adsorbent beads (Streamline SP). These experiments were performed in

dilute buffers conditions.

Figure 1 depicts the biomass deposition experiments performed with the yeast and

Streamline SP. At very low ionic strength of the buffer, the electrostatic double layer

repulsion between the particles and beads packed in the column is substantial such that

particle deposition (physicochemical phenomenon) can be neglected. Thus, in this type of

experiment, any particle removal in the packed bed is attributed to the influence of a



Appendix

215

physical mechanism such as straining. Hence it is expected that cell effluent concentrations

should be similar to the concentrations of cells before in contact with the collector. The

experimental evidence from the figure 1 suggest that there is a complete breakthrough of

the curve ( C/Co ≈ 1 ) indicating that straining does not play a role in the removal of

particles in porous media. This also could be reflected in theα ≤ 0.018 the minimum alpha

which represents absence of any type of interactions.

Figure 1: Biomass deposition experiments between intact yeast to cat-ion exchangers

(Streamline SP) at very dilute buffer conditions (0.66 mS.cm-1, pH 7.6).

From this experimental observation now it can be clearly stated that differences in the

physicochemical parameter α reported in this thesis work are mainly due to influence of physicochemical forces.

expanded bed adsorption - thermo

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