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Holistic valorization of rapeseed meal utilizing green solvents extraction and
biopolymer production with Pseudomonas putida
Phavit Wongsirichota, Maria Gonzalez-Miquela,b and James Winterburna*
a School of Chemical Engineering and Analytical Science, The University of Manchester,
Oxford Rd, Manchester, M13 9PL, United Kingdom
b Departamento de Ingenieria Quimica Industrial y del Medio Ambiente, ETS Ingenieros
Industriales, Universidad Politécnica de Madrid, Calle de José Gutiérrez Abascal 2,
Madrid, 28006, Spain
* Corresponding author
Email: [email protected], Phone: +44 (0) 161 306 4891
Abstract:
A rapeseed meal (RSM) valorization scheme was developed to utilize valuable fractions
including phenolics (mainly sinapic acid), proteins and polysaccharides. This involved
solvent extraction of phenolics, alkali extraction of proteins and fermentation of residual
polysaccharide using Pseudomonas putida. For the first time, sustainable Deep eutectic
solvents (DESs) were used in the extraction of rapeseed meal phenolics. With yields up
to 85.69 % wt. DESs were able to outperform methanol (59.54 % wt.) at sinapic acid
extraction. As shown by Conductor like Screening Model for Real Solvents (COSMO-
RS), this is because DESs have greater capacity for H-bonding.
Post-extraction RSM hydrolysate was shown to be a viable media for cultivation of P.
putida with maximum cell dry weight of 4.89 g l−1 for DES-extracted RSM. 8-carbon and
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10-carbon chain length polyhydroxyalkanoate biopolymers were synthesized.
Biopolymer accumulation was reduced in RSM derived media due to high nitrogen
concentration. These findings are beneficial for the development of a sustainable
biorefining scheme based on rapeseed meal.
Highlights:
• Valorization scheme investigated for rapeseed phenolics, proteins and
polysaccharides
• Deep eutectic solvents outperformed methanol in extracting rapeseed meal
phenolics
• Rapeseed meal hydrolysate shown to be viable media for Pseudomonas putida
• Successful synthesis of medium chain-length polyhydroxyalkanoates (8- and 10-
carbon)
Keywords: Rapeseed meal, valorization; phenolics; deep eutectic solvents;
polyhydroxyalkanoates
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1. Introduction
Over 70 million tons of rapeseed is grown annually for oil production (USDA, 2018),
by mass, over 60% of the grain will end up as waste called rapeseed meal (RSM)
(D'Avino et al., 2015). While, RSM can be sold as animal feed, this is limited by anti-
nutritional compounds such as glucosinolates. In order to reduce these compounds,
further processing, such as methanol extraction will be needed (Qian et al., 2013). More
importantly, RSM contains protein, phenolics, and polysaccharides, which could be
potentially valorized.
RSM phenolics are of major interest due to their significant anti-oxidative properties
(Nowak et al., 1992). Consequently, derivatives of RSM phenolics, such as 4-
vinylsyringol could potentially be used in the food industry due to their anti-oxidative
capabilities and flavors (Harbaum-Piayda et al., 2010). RSM phenolics’ anti-
inflammatory, anti-mutagenic properties and ability to improve drug permeability could
also lead to medical applications (Vuorela et al., 2005).
The major phenolic compounds in RSM are phenolic acids in both free and esterified
forms. Sinapic acid makes up the majority of the phenolics, mainly existing as the
choline ester, sinapine. Other phenolic acids include trans-ferulic, p-hydroxybenzoic,
coumaric and syringic acids (Naczk et al., 1998).
High sinapic acid yields have been achieved by extractions utilizing traditional
solvents such as methanol and acetone (Das Purkayastha et al., 2013). However, the
use of these conventional solvents has inherent disadvantages due to their toxic,
flammable, and/or corrosive properties, which can negatively impact operator safety and
the environment (Anastas and Eghbali, 2010).
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There is growing interest in the use of deep eutectic solvents (DESs) for extraction of
bioactive compounds from various biomass such as sea buckthorn leaves (Cui et al.,
2018), green tea (Jeong et al., 2017), cannabis (Křížek et al., 2018) and citrus by-
products (Ozturk et al., 2018a; Ozturk et al., 2018b) DESs are mixtures comprising of a
hydrogen bond acceptor (HBA) and a hydrogen bond donor (HBD). HBAs are typically a
quaternary ammonia salt. HBD can range widely from sugars to alcohols and organic
acids. However, despite their potential, DESs have not yet been applied to the
extraction of RSM phenolics.
Aside from the phenolics, RSM also contains potentially valuable proteins and
polysaccharides. Whilst there exists an extensive literature on RSM proteins, there is
less data on the utilization of the polysaccharides. RSM polysaccharides have been
utilized in both solid-state fermentation (Ebune et al., 1995) and fermentation with
hydrolyzed media (Chen et al., 2011). To the best of the authors’ knowledge, RSM-
derived polysaccharides have not been used in biopolymer production, warranting
further investigation.
An ideal organism for fermenting RSM should be able to metabolize the various
saccharides present in cellulose and hemicellulose. A good candidate is Pseudomonas
putida, which can metabolize a wide range of carbon sources, including saccharides
(Stanier et al., 1966). These saccharides can then be converted via de novo fatty acid
synthesis to polyhydroxyalkanoates (PHA) (Prieto et al., 2016). PHAs are polyesters
produced for energy storage whose accumulation is typically triggered by a limitation of
nutrients such as nitrogen in the presence of excess carbon substrate (Kachrimanidou
et al., 2014). Due to their biodegradability and thermoplastic properties, PHAs have a
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wide range of potential applications from substitute for conventional plastics to
biomaterials (Singh et al., 2015). Waste biomass have often been used as a carbon
source for PHA production, such as palm oil effluent (Mumtaz et al., 2010) and waste
plant oils (Ciesielski et al., 2015).
Currently, integrated RSM valorization of all three components remain largely
unexplored, with the only example being Li and Guo (2017). As fermentation was not
conducted, the viability of sugars from post-extraction RSM remains to be proven.
In this study, extractions of sinapic acids were conducted using a range of DESs.
Conductor like Screening Model for Real Solvents (COSMO-RS) simulations were used
to better understand the underlying molecular interactions. Finally, bioreactor cultures of
P. putida were grown using post-extraction RSM as media. This study presents the first
proof-of-concept study of the full valorization of RSM components, incorporating
extraction of high-value components using sustainable DESs, as well as biopolymer
production from the residual saccharides.
2. Materials and Methods
2.1 Materials
Defatted RSM was supplied by Cargill PLC (UK), which was passed through a 1 mm
sieve (Endecotts, UK) prior to use. P. putida KT2440 was procured from DMSZ,
Germany and stock cultures were prepared according to the supplier’s instructions.
Chemical used were procured from Sigma-Aldrich (UK), Fisher Scientific (UK), Alfa
Aesar (UK) VWR International (UK) and Merck (UK), which were as follows: Nutrient
agar II, sinapic acid (≥98 %), glucose (≥99 %), galactose (≥99 %), arabinose (≥98 %),
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xylose (≥99 %), 3-hydroxydecanoic acid (≥98 %), 3-hydroxyoctanoic acid (≥97 %),
octanoic acid (≥99 %), decanoic acid (≥98 %), dodecanoic acid (≥98 %), Folin-ciocalteu
reagent (2 N), sodium carbonate (≥99 %), ethylene glycol (≥99.8 %), trisodium citrate
(≥99 %), K2HPO4 (≥98 %), KH2PO4 (≥98 %), Na2HPO4 (≥98.5 %), FeSO4·7H2O (≥99 %),
CaCl2·2H2O (≥99 %), MnCl2·4H2O(≥98 %), CoSO4·7H2O (≥99 %), CuCl2·2H2O (≥99 %),
MgSO4·7H2O (≥98 %), methanol (≥99.8 %), NaNO3 (≥99 %), , NaOH (98 %), NH4Cl (≥98
%). H2SO4 (98 %), HCl (1 M), glacial acetic acid, choline chloride (99 %), glycerol (99 %)
and NaCl (99 %).
2.2 RSM phenolics characterization
Consecutive extractions were conducted using methanol (3 extractions) followed by
acetone (final extraction). All extractions were performed in a water bath for 2 hours at
40 ºC and stirred at 1500 rpm. The solid-to-liquid ratio was 1 g per 10 ml. Samples were
centrifuged at 3000 rpm for 20 minutes using a Sigma 6-16S (SciQuip, UK). The
supernatants were then collected and stored at −20 ºC prior to further analysis.
Colorimetric measurement of total phenolics was conducted using the Folin-ciocalteu
method based on Szydłowska-Czerniak et al. (2011).
The supernatant was hydrolyzed using a method based on Naczk et al. (1992).
Measurements of individual phenolic acids were conducted using high performance
liquid chromatography (HPLC) using an UltiMate® 3000 system (Thermo Fisher
Scientific, UK) and a 150 mm Nucleosil® C18 column (Macherey-nagel, Germany).
HPLC method used was based on Cai and Arntfield (2001). Sample injection volume of
5 µl was used, and sinapic acid was detected using UV absorbance at 330 nm. Other
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phenolic acids, including syringic acid, p-coumaric acid, ferulic acid and benzoic acid
were measured at 250 and 278 nm.
2.3 DESs preparation
DESs were prepared at ratios shown in table 1. The components were mixed for 24
hours between 250 - 500 rpm and 60 ºC. The DESs were then dried at 50 ºC in a
VT6025 vacuum oven (Thermo Fisher Scientific, UK) for 24 hours. Aqueous DESs were
prepared by addition of distilled water, at a DES to water ratio of 7:3 v/v (Nam et al.,
2015).
Hydrogen Bond Acceptor Hydrogen Bond Donor Molar ratio Abbreviations
Choline chloride Glucose 1 : 1 ChCl: GC (1: 1)
Choline chloride Glucose 1.5 : 1 ChCl: GC (1.5: 1)
Choline chloride Glucose 2 : 1 ChCl: GC (2: 1)
Choline chloride Glycerol 1 : 2 ChCl: Gly (1: 2)
Choline chloride Glycerol 1 : 1.5 ChCl: Gly (1: 1.5)
Choline chloride Glycerol 1 : 1 ChCl: Gly (1: 1)
Choline chloride Ethylene Glycol 1 : 3 ChCl: EG (1: 3)
Choline chloride Ethylene Glycol 1 : 2 ChCl: EG (1: 2)
Choline chloride Ethylene Glycol 1 : 1.5 ChCl: EG (1: 1.5)
Table 1 Composition of DESs used
2.4 Sinapic acid solubility
Sinapic acid was added in excess to 2 ml solvents. The samples were stirred for 2
hours at 1000 rpm and 30 ºC. Analysis of sinapic acid concentration was conducted as
described in the previous section.
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2.5 Solvent extraction of phenolics from RSM
Extractions of RSM phenolics were conducted with aqueous DES and aqueous
methanol, at 40 ºC, 50 ºC and 60 ºC, for 2 hours at 1000 rpm. The solid-to-liquid ratio
was 1 g per 10 ml. After extraction, the samples were centrifuged at 3000 rpm for 20
minutes and the supernatant removed. HPLC analysis was conducted as described
above. Sinapic acid yields with respect to total sinapic acid were calculated using
equation (1).
Sinapicacid yield (%wt )= Sinapicacid∈sample (g l−1 )×100 %Sinapic acid∈RSM (gg−1 )×Solid loading (g l−1)
(1)
Scaled-up extraction of RSM using methanol and the best performing DES (ChCl: Gly,
1:1) was conducted using 250 g RSM in 2.5 l at 60 ºC and 200 rpm. The residues were
separated using a Pyrex coarse grain Buchner funnel (Corning, USA). The DES
extracted RSM were then washed three times using 1 l of distilled water at 180 rpm for
5 minutes. The post-extraction RSMs were vacuum dried for 48 hours at 50 ºC.
2.6 Measurement of DES viscosities
Viscosity measurements were conducted using an DMA™ 4500 M density meter
equipped with an AMVn Automated Micro Viscometer (Anton Paar, UK).
2.7 Preparation of fermentation media
Synthetic media formulation was based on previous works conducted with P. putida
by Hartmann et al., (2006); Le Meur et al., (2012) and Davis et al., (2013). Preculture
media was prepared with 2.9 g l−1 trisodium citrate as a carbon source. Additional
nutrients were as follows: 7.5 g l−1 K2HPO4, 3.7 g l−1 KH2PO4, 2.38 g l−1 Na2HPO4, and
0.896 g l−1 NH4Cl. Sterilization was done via autoclaving at 121 ºC for 20 minutes (BMM
Weston, UK). After autoclaving, filter sterilized solutions of other trace elements were
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added at a concentration of 1 ml l−1. The trace element solution consisted of
FeSO4·7H2O (2.78 g l−1), CaCl2·2H2O (1.47 g l−1), MnCl2·4H2O (1.98 g l−1), CoSO4·7H2O
(2.81 g l−1), CuCl2·2H2O (0.17 g l−1) in 1 M HCl. 1 ml l−1 of filter sterilized MgSO4·7H2O
solution (1 M) was also added.
For the control experiment, a similar media was prepared which utilized glucose,
xylose, galactose and arabinose as a carbon sources, at concentrations of 5.5, 1.5, 3.5,
and 5 g l−1, respectively. NH4Cl (0.896 g l−1) was used as a nitrogen source, resulting in
an initial carbon to nitrogen ratio of 26 g g−1. The sugar content was selected based on
results from 100 ml scale diluted hydrolysis of RSM using the procedure in the following
section.
2.8 RSM hydrolysis
RSM hydrolysis was needed to produce monosaccharides for use as fermentation
carbon sources. Prior to hydrolysis, proteins were removed from post-phenolic
extraction RSM by using 0.4% w/v sodium hydroxide, as per a method by Klockeman et
al. (1997). Subsequently, the RSM was washed with distilled water and centrifuged. The
RSMs were vacuum dried for 48 hours at 50 ºC. Diluted acid hydrolysis was conducted
on 200 g of RSMs using 2 l of 6 % wt. H2SO4. Hydrolysis was conducted for 1 hour at
121 ºC within an autoclave. Hydrolysate was neutralized to pH 7 ± 0.5 using solid
NaOH. Phosphates and trace elements were added at the same concentration as the
control. The hydrolysates were filter sterilized using a 0.45 µm Nalgene™ Rapid-Flow™
filter (Fisher Scientific, UK).
2.9 Fermentation of P. putida
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Cells were initially grown on nutrient agar II, for 24 hours at 30 ºC. Pre-cultures of 200
ml were grown at 30 ºC and 200 rpm for 24 hours. The bioreactor working volume and
total volume were 2 l and 3 l, respectively (Applikon, UK). Temperature was maintained
at 30 ± 2 ºC. pH was maintained at 7 ± 1 using 3 M HCl and 3 M NaOH solutions.
Struktol J647 was used as antifoam. Dissolved oxygen was maintained above 30%
during fermentation using cascade control with stirrer speed between 600 to 1500 rpm.
2.10 Measurement of bacterial growth
Bioreactor samples were centrifuged at 13,400 rpm for 5 minutes (Eppendorf,
Germany). The supernatant was removed for further analysis. The cell pellet was
resuspended in 0.7 % wt. NaCl solution. Optical density at 600 nm (OD600) was
determined using a UV mini 1240 UV spectrophotometer (Shimazdu, UK). For cell dry
weight measurements, centrifuged cell pellets were washed with distilled water and
dried at 70 ºC.
2.11 HPLC analysis of sugars
HPLC used was an UltiMate® 3000 system with a RefractoMax 520 refractive index
detector (Thermo Fisher Scientific, UK). The columns used were an Aminex HPX-87P
and Aminex HPX-87H (Bio-rad, UK) with an isocratic elution using 0.6 ml min−1 of water
and 0.05 mM H2SO4, respectively. Sample injection volume was 10 µl and column
temperature was 50 ºC.
2.12 Total nitrogen analysis
A TOC-VCPH Total Organic Carbon analyzer with a TNM-1 TN analyzer unit
(Shimadzu, UK) was used for total nitrogen analysis, standard solutions of NaNO 3 was
used for calibration.
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2.13 GC-FID of PHAs
Methanolysis was used to treat the dried cells based on Lageveen et al. (1988). The
derivatized PHA was detected using Gas Chromatography with a Flame Ionization
Detector (GC-FID). GC-FID was conducted on an Ultimate 1300 GC system (Thermo
Fisher Scientific, UK), using a Zebron ZB-SemiVolatiles Capillary GC Column, 30m x
0.25mm x 0.25µm (Phenomenex, UK). Sample injection volume of 1 µl was used.
Helium was employed as a carrier gas at 1 ml min−1 with a split ratio of 50:1.
The following oven temperature profile was used: Initially, the oven was maintained at
100 ºC for 3 minutes, followed by heating at a linear gradient of 25 ºC min−1 until 320 ºC,
and finally the oven was held at 320 ºC for 2 minutes. Inlet and detector temperatures
were at 300 ºC. Concentrations of different chain-length PHAs were determined by
comparison to standard solutions of methanolized 3-hydroxydecanoic and 3-
hydroxyoctanoic acids.
2.14 Fermentation yield coefficients
Yield coefficients were calculated using equations (2) to (4). As the amino acids can
also be catabolized by P. putida (Radkov and Moe, 2013), equation 3 which took the
nitrogen source into account was also used.
Y XC=CDW t−PHAt
C (2)
Y XC+N
=CDW t−PHA t
C+N (3)
Y PHAGC
=PHA t
GC (4)
Where:
X is the residual cell weight at time t (g l−1)
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C is the carbon source consumed by time t (g l−1)
CDW t is the cell dry weight at time t (g l−1)
PHA t is the PHA content in the culture at time t (g l−1)
N is the nitrogen source consumed by time t (g l−1)
GC is the glucose consumed by time t (g l−1)
For RSM cultures, the amount of nitrogen source consumed (i.e. proteins) was
estimated using equation (5).
For RSM :N=TN t−TN 0
NRSM(5)
Where:
TN t is the total nitrogen at time t (g l−1)
TN 0 is the total nitrogen at 0 h (g l−1)
N RSM is the mass ratio of nitrogen in RSM proteins
A value of 0.1384 was used for N RSM, based on the prominent amino acids in RSM
reported by Tzeng et al.(1988).
The specific growth rate, µ, was calculated based on equation (6) (Blanch and Clark,
1996).
lnCDW t
CDW 0=µ(t−t lag) (6)
Where:
CDW 0 is the cell dry weight at 0 h (g l−1)
t lag is the duration of the lag phase (h)
2.15 COSMO-RS
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Conductor like Screening Model for Real Solvents (COSMO-RS) was utilized to
calculate thermodynamic properties of sinapic acid in solution. Geometric optimization
and COSMO file calculation for sinapic acid was performed using Gaussian 09 at the
BVP86/TZVP/DGA1 quantum chemical level (Frisch et al., 2016). COSMO files for other
molecules were taken from COSMO-RS database. COSMOtherm version C3.0 release
17.05 was used at the corresponding parametrization (BP_TZVP_C30_1701) to
calculate σ-profiles, excess enthalpies and energetic contributions from hydrogen
bonding, misfits/electrostatic interactions and van der Waals forces (Klamt and Eckert,
2000). DESs were treated separately as choline cation, chloride anion, and the H-bond
donor, following the electroneutral approach (Hizaddin et al., 2014).
3. Results and discussion
3.1 Phenolic extractions
3.1.1 Choice of DES components
The main criteria when assessing the viability of the solvents for an integrated RSM
valorization process were solvent performance and the possible impact of residual
solvent. Importantly, toxicity needed to be considered due to potential impact on the
subsequent fermentation. Fortunately, there are many potential combinations of HBD
and HBA that can produce DES, many of which could be benign to the fermentation
process. Typically, HBAs are quaternary ammonium salts such as choline chloride
(Duan et al., 2016). In fact, choline compounds can actually be metabolized by
Pseudomonas species, including P. putida.(Galvão et al., 2006) Therefore, the use of
choline chloride based DESs was deemed appropriate for phenolic extraction.
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The choice of HBDs can vary widely from organic acids, polyols and sugars (Dai et
al., 2013). Glycerol (Abbott et al., 2007; Ozturk et al., 2018a) and glucose (Hayyan et
al., 2013) were chosen due to their prevalence within the literature for polyols and
sugar-based DESs, respectively. They also have additional benefits stemming from
their renewable nature and the ability of P. putida strains for both glucose and glycerol
catabolism (Stanier et al., 1966). Ethylene glycol (EG) was chosen to compare
performance to the chosen DESs, due to high extraction performance demonstrated
within literature (Abbott et al., 2007; Ozturk et al., 2018b). Finally, methanol (MeOH)
was used for comparison, as it is a commonly utilized traditional solvent for extraction of
RSM phenolics (Das Purkayastha et al., 2013).
3.1.2 RSM phenolic content
During the characterization process, sinapic acid was confirmed to be the most
abundant phenolic compound within the RSM. Total sinapic acid in the RSM was 8.97
mg g−1. This was much higher than the other phenolic acids such as syringic acid, p-
coumaric acid, ferulic acid and benzoic acid, which were not detected in significant
amounts. Based on the Folin–Ciocalteu method, the total phenolics in RSM were found
to be 16.14 mg g−1 (sinapic acid equivalent). At approximately 60 % wt., the proportion
of sinapic acid within total phenolics was found to be lower than RSM within literature,
which ranges from 70 to 97 % (Naczk et al., 1998; Naczk et al., 1992). However, the
amount of sinapic acid agrees with literature values, which can range significantly from
approximately 5.55 mg g−1 to 11.80 mg g−1 (Khattab et al., 2010; Vuorela et al., 2003).
Variations are likely due to different sources of RSM both in terms of agricultural source
and rapeseed processing method.
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3.1.3 Preliminary screening of DESs for phenolic extraction
A preliminary screening was initially conducted on DES at 40 ºC (Fig. 1a). With yields
ranging between 67.5 to 72.9 % wt., extractions using ChCl: Gly and ChCl: EG DESs
demonstrated slightly better sinapic acid yield than methanol at 59.5 % wt. The
difference became more pronounced once the extraction temperature was raised, with
sinapic acid yields between 78.9 and 85.7 % wt. for DES ChCl: Gly and ChCl: EG at 60
ºC, while yields for methanol remained constant with temperature. The correlation
between extraction temperature and yields for most of the DESs used was likely due to
improved mass transfer as a result of decreasing viscosity with increasing temperature.
To avoid degradation of the phenolics the temperature was not increased beyond 60 ºC.
Figure 1: a) Sinapic acid yields from RSM using aqueous solvents, b) Solubility of
sinapic acid Error bars indicate standard error from triplicates
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The choice of HBD played an important role in the extraction efficiency. The maximum
phenolic yields for ChCl: GC (1: 1) was approximately 48% wt. at 60°C. At the same
temperature, ChCl: Gly (1: 1) was above to achieve at yield of 85 % wt. This agrees with
similar findings from Nam et al. (2015) regarding flavonoids extraction, where ChCl: Gly
also out performed ChCl: GC. This was due to the effect of HBD choice on both the
polarity and viscosity of the resulting DES. Glucose also contains a higher number of
hydroxy groups compared to glycerol and ethylene glycol. This means there is higher
probability of solvent-solvent interaction in ChCl: GC which could also reduce the
solvent-solute interaction, resulting in lower sinapic acid yields. Interestingly, changing
the proportion of HBD to HBA did not have significant impact on the sinapic acid yield
for the DESs. Further comparison with literature values for RSM is made difficult
because the majority of the papers utilized Folin–Ciocalteu data as the main
measurement, or because mg g−1 RSM values were used, which will be impacted by the
native amount present in different sources of RSM.
The solubility of pure sinapic acid was also assessed to determine if there are
differences in performance compared to the biomass (Fig. 1b). For pure sinapic acid
with both ChCl: Gly and ChCl: GC, solubility decreased with increasing proportion of
HBD. For example, sinapic acid concentrations were 1.56 and 0.65 g l−1 for ChCl: Gly (1:
1) and (1: 2) respectively. This was not the case for the EG based DESs. This was
mainly due to an increase in viscosity as the proportion of HBD increases. At 16.81 g l−1,
the solubility of sinapic acid in methanol was in fact far higher than the DES which
ranged between 0.27 to 1.66 g l−1. The much poorer performance of methanol on RSM
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could be because other compounds with RSM are being preferentially dissolved or co-
extracted, reducing extraction selectivity with respect to phenolics.
COSMO-RS simulations were conducted to better understand the interaction between
solute and solvents and potentially explain the trends observed in Fig. 1. In COSMO-
RS, the type of intermolecular behavior can be inferred from the molecules σ-profile
(Klamt and Eckert, 2000). The σ-profiles of a molecule can be divided into three
regions, displaying H-bond donor (σ < −0.0082 e Å−2), non-polar (−0.0082 e Å−2 < σ <
0.0082 e Å−2), and H-bond acceptor (0.0082 e Å−2 < σ) behaviours (González et al.,
2018). Comparison of the solute and solvent σ-profile can determine the potential of
solubility. If both histograms are complementary, for example, if one has a peak
indicating H-bond donor behavior, while the other has a peak indicating H-bond
acceptor behavior, there is a potential for good solubility (Lapkin et al., 2010). While this
analysis of σ-profile is typically conducted on liquid-liquid systems, such treatment of
solute-solution systems has precedence within literature such as those by Lapkin et al.
(2010), Gonzalez et al. (2018) and Pereira et al. (2016).
σ-profile of sinapic acid with respect to the solvent’s components are shown in Fig. 2a
and 2b. Sinapic acid displays significant peaks in the H-bond donor and H-bond
acceptor regions. The H-bond acceptor peak extended to σ of approximately 0.017 e
Å−2, displaying a maximum at σ of 0.011 e Å−2. This is due to the contributions from the
carboxylic acid and phenolic functional groups, as well as the oxygen atoms of the
hydroxyl groups. This is also demonstrated by the visualization of the σ surface shown
in Fig. 2d.
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Meanwhile, the H-bond donor peak extended to σ of approximately −0.022 e Å −2.
While maximum value of p(σ) for the H-bond acceptor peak is lower at around 2
compared to 4.5 for the H-bond donor peak, the broadness of the charge distribution
means that the H-bond donor behavior is no less significant. Again, both the phenolic
and carboxylic acid functional groups are the cause of this behavior, as shown in Fig. 2.
The potential for sinapic acid to act as a H-bond donor or acceptor has been seen in
literature. For example, Sinha et al. (2015) reported a range of H-bonding behaviors
between sinapic acid and a number of APIs. This was caused by either the carboxylic
acid acting as both H-bond donor and acceptor, or by the phenolic functional group
acting as a H-bond donor (Sinha et al., 2015).
The solubility of sinapic acid could be directly impacted by the ease of formation of H-
bonds between the solute and the solvents. This had been previously demonstrated by
orange peels phenolics, where increased H-bonding improved the solubility of orange
peel phenolics in DES, although this can be hindered by kinetic effects (Ozturk et al.,
2018b). Fig. 2 shows that as expected the DESs components displays significant H-
bond donor and acceptor behaviors. Among the designated HBDs, glucose is the most
polar as it has comparatively more polar functional groups (including hydroxymethyl and
hydroxyl groups) relative to glycerol and ethylene glycol which have similar σ-profiles.
Additionally, the polarity from the choline cation or the chloride anion may also aid
sinapic acid solubility. The σ-profile of methanol contains much smaller peaks in both H-
bond donor or acceptor regions compared to the DES components.
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Figure 2: σ-profile of sinapic acid with respect to solvents components a) Methanol and
ChCl, b) DES H-bond donors, c) molecular structure of sinapic acid, white: H-atom, red:
O-atom, green, d) visualization of σ surfaces for sinapic acid, red and blue denote more
extreme σ values, red: positive, blue: negative, green: neutral
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In addition to the σ-profiles, excess enthalpy (ΔH) was calculated to directly compare
the molecular interaction within each solvent system. These calculations considered the
molar proportion of each component, rather than just an individual atom as with σ-
profiles. Additionally, it also took into account multiple types of molecular interactions:
van der Waals forces, electrostatic misfits and H-bonding (Klamt and Eckert, 2000).
High solubility of a solute is indicated by high exothermic behavior of the system, i.e.
more negative values of ΔH (Gonzalez-Miquel et al., 2013). This is shown in Fig. 3,
which in all cases, the maximum ΔH of the sinapic acid - solvent system is a net
negative for both DESs and methanol, indicating favorable intermolecular interactions
that enhance solubility. Maximum ΔH for DES ranges from −1.00 to −2.02 kcal mol−1,
much greater than the −0.39 kcal mol−1 methanol.
Figure 3: Excess enthalpy (ΔH) for sinapic acid in aqueous solvents, computed using
COSMO-RS with percentage contribution denoted
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As these ΔH values were calculated based on the σ-profiles shown in Fig. 2, it is not
surprising that the DESs have much greater magnitude of ΔH compared to methanol,
due to more complementary σ-profiles. The contributions from each type of molecular
interactions are also shown in Fig. 3. H-bonding represented at least 75% of the
molecular interaction for all systems, collaborating with the interpretations from the σ-
profiles. From Fig. 3 it appears that the choice of the DES’s HBD greatly affects the
magnitude of maximum ΔH, which collaborates with the experimental results in Fig 1.
For example, ChCl: Gly (1: 1) has a much higher absolute value of ΔH relative to ChCl:
GC (1: 1), with greater magnitude of attractive ΔH (misfit) and ΔH (H-bonding) by 54.6
% and 43.63 %, respectively. Meanwhile, repulsive ΔH (VDW) was also increased by
42.50 % when glucose was used instead of glycerol which reduced solubility. This was
likely due to the larger size of the glucose molecule. Therefore, judging from
comparison of ΔH, glycerol appears to be a better choice. This is because aside from
more types of interaction having an effect, the aforementioned solvent-solvent
interaction could also play a role.
When comparing Fig. 1 and Fig. 3, it can be seen that the thermodynamics alone are
not sufficient to explain the findings from RSM and pure sinapic acids. This is because
the kinetics also play an important role. The same H-bonding behavior displayed by
DESs also leads to very high viscosities (Ozturk et al., 2018b). However, the viscosities
of the aqueous DESs was much lower than viscosities of pure DESs due to the addition
of water. For example, at 40 °C the viscosities of pure ChCl: GC (2: 1), ChCl: Gly (1: 2)
and ChCl: EG (1:2) are approximately 4000, 143 and 22 mPa s, respectively (Hayyan et
al., 2013; Ozturk et al., 2018b). While for the aqueous DES, this was 18.2, 8.60 and
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4.80 mPa s for ChCl: GC (2: 1), ChCl: Gly (1: 2) and ChCl: EG (1:2), respectively. This
allows for better mass transfer when aqueous DESs was utilized. The relative viscosity
of the DESs reflects the polarity of the HBD, with glucose being the most polar, as seen
earlier in the σ-profiles.
Even though the magnitude of viscosities had decreased, aqueous DESs demonstrate
the same trends as the pure DESs from literature. As with pure there was a significant
decrease in viscosity with increasing temperature DESs (Hayyan et al., 2013; Ozturk et
al., 2018b). This confirms that mass transfer improves with temperature, which
contributed to the increasing sinapic acid yields in Fig. 1a. The effect of DES
composition was also the same as literature, with significant difference in the viscosity
of glucose based DESs (Hayyan et al., 2013), and less so for ChCl: Gly and ChCl: EG
(Ozturk et al., 2018b). Glucose-based DESs remained the most viscous, ranging from
52.5 mPa s for ChCl: GC (1: 1) at 40 °C to 9.4 mPa s for ChCl: GC (2: 1) at 60 °C. The
lowest value for ChCl: GC is still higher than the most viscous ChCl: Gly at 40 °C, which
was at 8.9 mPa s. This shows that ChCl: Gly and ChCl: EG were able to out preformed
ChCl: GC due to their more preferable kinetics. The viscosity of ChCl: EG could be up
to 53 % lower than ChCl: Gly at the same condition. This could explain the similar
sinapic acid yields between the two types, with the thermodynamically favorability of
ChCl: Gly being counteract by the better mass transfer of ChCl: EG.
Viscosity differences also explains the significant difference between the
performances of DESs and methanol on pure sinapic acid. The dissolutions were
assessed at 30 °C leading to viscosity being much more significant. The extremely low
viscosity for the aqueous methanol, coupled with very high viscosities of the DESs
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being the likely cause. This is in addition to the effects caused by the complex matrix
within the RSM, which was not present for pure sinapic acid.
While DESs are more thermodynamically favorable for sinapic acid extraction, the
correct operating conditions are necessary in order to maximize phenolic yields. It was
demonstrated that EG and glycerol-based DESs out preformed methanol for sinapic
acid extraction from RSM, providing a better choice in terms of sustainability, safety,
efficacy and, importantly, suitability with downstream fermentation of post-extraction
RSM.
3.1.4 Phenolic extraction scale-up
While both glycerol and EG-based DESs displayed high sinapic acid yields on RSM,
for large scale extraction ChCl: Gly was chosen as the better candidate because of
better performance (Fig. 1a) and favorable thermodynamic behavior as supported by
COSMO-RS calculations (Fig. 3). Methanol extraction was also conducted for
comparison and to also assess the possibility of residual methanol in the hydrolysate
having a negative impact on the fermentation. To provide sufficient post-extraction RSM
for the bioreactor, the scalability of the phenolic extraction process was evaluated. It
was found that mass transfer was improved as a result of the scale-up. This was likely
because the ratio between the agitator length and height of the liquid column was
increased, from 0.12 to 0.58, resulting in more effective suspension of RSM. Hence,
yields for both ChCl: Gly (1: 1) and methanol were improved by 6.5 and 12.4 % wt.,
respectively, as shown in table 2.
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Table 2: Sinapic acid extraction scale up
Extraction method Extracted sinapic acid
(mg g−1 RSM)
Yield
(% wt.)
10 ml 2.5 l 10 ml 2.5 l
ChCl: Gly (1: 1) (aq) 7.63 8.21 85.0 91.5
Methanol (aq) 4.98 6.10 55.6 68.0
3.2 Bioreactor fermentation of P. putida on RSM hydrolysate
P. putida was successfully cultivated on RSM hydrolysate at 2 l scale. As shown in
Fig. 4, growth was achieved for all RSM hydrolysates, whether or not the RSM had
undergone extraction. Specific growth rates from RSM hydrolysate range from 0.15 to
0.19 h−1 (Table 3). This is slightly slower than the control, at 0.30 h−1. However, these
growth rates are in the expected range, with previous studies reporting growth rates
ranging from 0.2 to 0.4 h−1 (Hartmann et al., 2006; Le Meur et al., 2012; Meijnen et al.,
2008). There appeared to be negligible inhibitory effect of phenolics in the hydrolysate
produced from untreated RSM. This could be due to natural resistance of P. putida
KT2440, but more likely because as a result of the solid loading used during hydrolysis,
the concentrations of phenolics were too low to have an impact. Similar bacterial growth
was also achieved when RSM was treated with methanol, which was removed by
vacuum drying.
RSM was shown to have adequate concentrations of carbon and nitrogen for healthy
growth of P. putida. The large amount of nitrogen from untreated RSM, up to 3.6 g l−1
(Fig. 4), results from the presence of native proteins within the RSM. NaOH extraction of
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the proteins resulted in a reduction of approximately 50% of the total nitrogen
concentration, as seen when comparing Fig. 4b, 4c and 4d. Even though there has
been recent application of ChCl: Gly for protein extraction (dos Santos et al., 2018).
Figure 4: Time course of P. putida fermentation a) synthetic media, b) Hydrolysate from
untreated RSM, c) Hydrolysate from RSM treated with ChCl: Gly (1:1) (aq), d)
Hydrolysate from RSM treated with MeOH (aq)
As this is a proof-of-concept study with a focus on phenolics, the method for protein
extraction was chosen based on the works by Klockeman et al., who achieved a 99%
extraction efficiency on defatted canola meal (Klockeman et al., 1997). The reduced
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extraction effectiveness for proteins was due to the change in mass transfer as a result
of scale up.
Due to the abundance of nitrogen, very high levels of growth were achieved on the
RSM hydrolysates compared to the control, with a maximum cell dried weight (CDW) of
9.05 g l−1 for the RSM hydrolysate compared to the 2.55 g l−1 for the synthetic media
culture, where growth stopped after 9 hours due to nitrogen limitation. The cell
concentrations for the culture grown on the other RSM hydrolysates were lower at 4.89
and 4.54 g l−1 for DES and methanol extracted RSM, respectively. This could be due to
the lower initial concentrations of sugars, especially glucose, relative to both the
untreated RSM hydrolysate and the control. This was caused by the increase in particle
size of the RSM from aggregation during the drying process, resulting in a reduced
surface area to volume ratio during hydrolysis. The hydrolysate produced from extracted
RSM would also contain more salts compared to untreated RSM, due to residual NaOH
from protein extraction. Higher salt concentration could have resulted in lower viable cell
concentration due to osmotic stress (Bojanovič et al., 2017).
In all of the cultures PHAs were produced, consisting of 8-carbon
polyhydroxyoctanoates and 10-carbon polyhydroxydecanoates, which were consistent
with PHA produced from unrelated carbon sources via fatty acid de novo synthesis
(Huijberts et al., 1992). PHA is produced naturally due to its role as an intracellular
organelle as well as for energy storage (Huijberts et al., 1992; Prieto et al., 2016). While
high growth was achieved on the RSM hydrolysates, there was very little PHA
accumulation, as seen from table 3 where PHA accumulation was not above 0.5 %
CDW due to the abundance of nitrogen.
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Table 3: Performance of P. putida bioreactor fermentations
Experiment µ (h−1)
Max
OD600
Max CDW
(g l−1)
Max
PHA
(g l−1)
Max
PHA
(% CDW)
Control 0.30 6.71 2.55 0.08 3.08
Native 0.15 16.50 9.05 0.02 0.30
DES & NaOH 0.13 8.37 4.89 0.01 0.35
MeOH & NaOH 0.19 9.72 4.54 0.02 0.41
However, in the control culture where nitrogen was depleted by 24 hours (Fig. 4a)
there was a sharp increase of both 8-carbon and 10-carbon PHAs after nitrogen
limitation occurred. The amount of PHA accumulated reached 3.08 % of the CDW
before glucose was depleted. For the cultures grown on RSM hydrolysates,
approximately 0.35 to 0.4 g l−1 of nitrogen was consumed, while the control only
contained an initial concentration of 0.2 g l−1. If nitrogen limitation was to be induced in
the RSM cultures, it is expected that significant PHA accumulation would occur. This
would require a carbon to nitrogen ratio of at least 30: 1. Media from both post-
extraction RSMs have a carbon to nitrogen ratio of approximately 2: 1. Therefore, it is
clear that an improvement in protein extraction is essential for the RSM hydrolysate to
become a viable media for PHA production. This is in addition to the inherent value of
the proteins which incentivize their extraction.
It is also interesting to note that concentrations of xylose, galactose and arabinose
only began to decrease significantly after glucose had been depleted (Fig. 4). This could
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be due to carbon catabolite repression (CCR), where glucose is preferentially
metabolized in the presence of multiple saccharides.
However, there is limited understanding on CCR in Pseudomonas species, especially
between saccharides. This is because Pseudomonas preferred carbon sources are not
saccharides such as glucose, but rather organic acids, which has been the focus of
CCR studies within the literature (Rojo, 2010). Nevertheless, catabolism of the other
sugars still contributed to cell growth as shown in Fig. 4b. As growth in the post-
extraction RSMs were limited, catabolism of the other sugars contributed to other
cellular processes instead Fig. 4c and 4d.
Despite P. putida being able to metabolize saccharides other than glucose, the
microorganism was unable to produce PHA even when other saccharides were in
abundance, as shown by Fig. 4 a). In fact, PHA content decreased after glucose
depletion, along with the other sugars. This again could be a result of CCR. For the
purpose of maximizing PHA production, a high glucose concentration must be
maintained, either through increasing the initial concentration or implementation of
batch-feeding strategies. From this observation, PHAs yield coefficients were also
defined with respect to glucose, Y PHAGC
. Since PHA accumulation peaked at the beginning
of the stationary phase (Fig. 4), the yield coefficients at this point were used for
comparison. As seen from table 4, yield coefficients for all cultures range from 0.006 to
0.020 g g−1, as the majority of the carbon was used for cell biomass. The RSM cultures
in fact had similar conversion rate as the control. This further suggests that if nitrogen
limitation were to be induced, higher PHA accumulation can be achieved when grown
on RSM.
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Table 4: Yield coefficients of P. putida bioreactor fermentations at the beginning of the
stationary phase
Yields coefficients (g g−1)
ExperimentY X
C
Y XC+N
Y PHAGC
Control 0.32 0.29 0.013
Native 0.94 0.32 0.006
DES + NaOH 2.59 0.68 0.020
MeOH + NaOH 1.43 0.48 0.013
Y XC: Yield coefficient for residual cell weight w.r.t. carbon sources;
Y XC+N
: Yield coefficient for residual cell weight w.r.t. carbon and nitrogen sources;
Y PHAGC
: Yield coefficient for PHA w.r.t. glucose;
Cell yield with respect to carbon sources, Y XC, for the control culture was at 0.32
(Table 4). This is similar to the growth of P. putida on synthetic media with sugars as a
carbon source found in literature. For example, La Meur et al. found that their
recombinant P. putida KT2440 had a yield of 0.5 g g−1 when grown on xylose (Le Meur
et al., 2012). On the other hand, yields from the RSM hydrolysate were extremely high,
reaching as high as 2.59 g g−1 for DES extracted RSM. This does concur with higher
growth seen on RSM hydrolysates. However, as the RSM yields are much higher than
1, it is likely that the carbon is not coming from the sugar alone. This difference could be
due to residual DES components acting as additional carbon sources. However, this
does not account for the hydrolysate produced from the methanol extracted or the
native RSMs.
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The additional carbon more likely came from the protein derivatives in the
hydrolysates. The high temperature and low pH conditions during acid hydrolysis could
have certainly induced protein hydrolysis (Williams, 2003). Additionally, catabolism of
both d- and l-amino acids has been reported on the strain of P. putida used (KT2440)
(Radkov and Moe, 2013), some of which are present in relatively large amounts in
RSM, such as lysine, phenylalanine and arginine (Tzeng et al., 1988). This corroborates
with the fact that the difference in Y XC between the hydrolysates and control was due to
the lower amount of sugars being consumed, since as stated previously, all cultures had
similar specific growth rates. Thus, it was more accurate to access the fermentation’s
performance based on the yield with respect to both the sugars and proteins, Y XC+N
. The
difference between Y XC+N
of the different fermentations is much lower compared to Y XC.
RSM hydrolysates have Y XC+N
only ranging from 0.32 to 0.68 g g−1, while Y XC+N
for the
control culture was also comparable at 0.29 g g−1. Y XC+N
values were also of similar
magnitude to yields coefficient expected from literature, such as the aforementioned
work by Le Meur et al.(2012). Davis et al. (2015) also reported a yield coefficient of 0.45
g g−1 for P. putida on glucose. These similar yield coefficients demonstrate that RSM
hydrolysate can act as an effective growth media for P. putida fermentation.
4. Conclusions
This study is the first to demonstrate an integrated process for DES extraction of high
value components followed by biopolymer production from RSM. DESs significantly
outperformed methanol for phenolic extractions, up to 85.7 % for ChCl: Gly. Selecting
appropriate DESs components can maximize extraction yield by optimizing the H-
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bonding interactions and DES viscosity. Successful scale-up of the extraction was
achieved, allowing for bioreactor fermentations of residue-derived hydrolysates.
Extremely high growth was achieved on the hydrolysates, yielding CDW of up to 4.89 g
l−1, with growth rates comparable to those obtained using synthetic media. 8-carbon and
10-carbon PHAs were also successfully synthesized using RSM hydrolysates.
Acknowledgements
The authors would like to thank Mrs. Carole Webb and the School of Chemistry, The
University of Manchester for their valuable assistance on gas and liquid
chromatography.
Appendix A. Supplementary data
Supplementary data provided with the online version of paper.
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