statistical optimization of bg11 medium for enhanced

Int J Pharma Bio Sci 2019 July; 10(3): (B) 58-70

This article can be downloaded from www.ijpbs.net

B-58

Original Research Article Biotechnology

International Journal of Pharma and Bio Sciences ISSN

0975-6299

STATISTICAL OPTIMIZATION OF BG11 MEDIUM FOR ENHANCED

ZEAXANTHIN PRODUCTIVITY IN Synechococcus marinus (NIOT-208)

S.PRIYANKA*1,2, R. KIRUBAGARAN2 AND J.T. MARY LEEMA2

1Sathyabama Institute of Science and Technology, Chennai-600119, Tamil Nadu, India.

2Ocean Science and Technology for Islands, National Institute of Ocean Technology (NIOT),

Chennai-600100, Tamil Nadu, India.

ABSTRACT

Zeaxanthin is a xanthophyll carotenoid pigment highly valued for its nutraceutical potential. It is a strong antioxidant with wide applications in food, feed, cosmetic and pharmaceutical industries. Zeaxanthin is produced by many Cyanophycean microalgae, but very few zeaxanthin accumulating strains have been reported. In this study, a two-step statistical optimization strategy involving Plackett-Burman (PB) design and response surface methodology (RSM) were successfully utilized to optimize the BG11 culture medium components for enhanced zeaxanthin production from marine Cyanophycean microalgae, Synechococcus marinus (NIOT- 208). The media components (independent variables) of BG11 medium was screened using Plackett-Burman design to identify three crucial nutrients (Na2EDTA, K2HPO4 and NaNO3), which significantly enhanced zeaxanthin yield. Central composite design (CCD) of response surface methodology was used to optimize the concentration of significant variables. The experiments were designed using “Design Expert” software version 9.03 and the results were analyzed using two way ANOVA and a high coefficient of determination (R

2=0.984) with a low p value (0.002) indicates that the results are reliable and significant

(p<0.05). Validation experiments performed with optimized medium ingredients, NaNO3 (250 mg L-1

), K2HPO4 (40 mg L

-1) and Na2EDTA (14 mg L

-1) enhanced the zeaxanthin yield to 14.61 ± 1.29 mg L

-1 which is very close

to the predicted value of 14.48 mg L-1

. The high zeaxanthin yield accomplished by culture medium optimization

resulted in 8.46 fold increase in zeaxanthin yield when compared to BG-11 medium (1.72 ± 0.22 mg L-1

). The two-step statistical optimization of culture medium thus facilitated enhanced zeaxanthin yield in S. marinus. Further, the present study has also demonstrated purification of zeaxanthin using preparative RP-HPLC and the purified zeaxanthin was characterized using FT-Raman spectroscopic analysis and HR-MS. RP-HPLC of purified zeaxanthin indicated a high resolution molecular mass of 568.31 daltons and FT Raman spectroscopy analysis yielded three strong Raman bands corresponding to C=C stretching, C–C stretching and C–CH3 at 1537, 1173 and 1032 cm

−1 respectively, which are characteristic to the carotenoid zeaxanthin.

KEYWORDS: zeaxanthin, Synechococcus marinus, Plackett-Burman, response surface methodology, Raman spectroscopy.

Corresponding Author

Received on: 15-12-2018

Revised and Accepted on: 06-06-2019

DOI: http://dx.doi.org/10.22376/ijpbs.2019.10.3.b58-70

Creative commons version 4.0

S. PRIYANKA *

Ocean Science and Technology for Islands, National Institute of Ocean

Technology (NIOT), Chennai-600100, Tamil Nadu, India.

E-Mail ID : [email protected]

Mobile : 8056395946



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INTRODUCTION Microalgae possess the ability to enhance the nutritional value of conventional dietaries and have a positive effect on the health of humans and animals due to their biochemical composition.

1 Consequently, increased

interest has been paid for large scale cultivation of microalgae for the production of high value biochemicals, lipids, carotenoids, polysaccharides and colorants.

2 Carotenoids are natural pigments present in

algae and higher plants which are involved in the light harvesting mechanism and protection of algal cell organelles against the singlet oxygen induced damage and prevent the formation of reactive oxygen species (ROS).

3,4 In recent years, several microalgal pigments

like zeaxanthin, lutein, β-carotene and phycobiliproteins have a huge market demand because of their high end applications.

5,6 However, the actual content of these

pigments in algal cell is determined by the selection of appropriate strain, culture conditions, nutrient composition of the culture medium and environmental conditions.

7 Zeaxanthin (3, 3’-dihydroxy-β-carotene) is

well known for its ability to prevent cancer and age-related macular degeneration (AMD), which is one among the leading cause of blindness in the developed countries.

8,9 It is widely used as a colorant in cosmetic,

food and pharmaceutical industries.10

Commercial demand for zeaxanthin is mainly met by synthetic resources.

11 Despite the availability of a variety of

synthetic pigments and colorants at cheaper prices, there is a renewed interest for natural source of pigments partly driven by public apathy against synthetic pigments and also due to the highly beneficial isomers of natural pigments.

12,13 The production of zeaxanthin by

Flavobacterium sp., β-carotene by Dunaliella and astaxanthin by Haematococcus pluvialis were already reported.

4,15 As these microalgae accumulate

carotenoids upto 4–10% (w/w) of their cell dry weight, they are considered as a commercially important source for industrial scale production.

16,17 Among the

Cyanophycean microalgae, Prochlorococcus and Synechococcus sp are reported to produce zeaxanthin as their prime carotenoid. Flomboum et al,

18

documented that Synechococcus sp alone accounts for almost 16.7% of the total daily primary production in marine environment. There is a great need for high production of zeaxanthin by Cyanophycean algae and make it avail through the effective manipulation of culture medium components and conditions.

19 Recent

statistic approaches are readily supported for achieving high yield of production.

20,21 Hence, a two-step

sequential statistical method was used for optimization of culture medium components and conditions. The Plackett-Burman statistical design was used as a first step to screen the crucial factors influencing the zeaxanthin yield. The multiple interaction between the significant variables and their effects on response variable were efficiently explained with the help of response surface methodology (RSM).

22,23 The main aim

of RSM is to determine the optimal operational parameters for the maximal production of zeaxanthin. Several researchers have used RSM in growth media optimization.

24,25,26 However, less information is

available regarding the use of statistical method of optimization strategies for the production of zeaxanthin from microalgae. To the best of our knowledge,

optimization of culture medium components and conditions of laboratory cultured Synechococcus marinus (NIOT 208) for zeaxanthin production using two-step statistical technique has not been demonstrated previously. In view of the potential commercial applications of zeaxanthin, a two-step sequential statistical strategy to optimize the culture medium components and conditions for its enhanced production from S. marinus is presented.

MATERIALS AND METHODS

Microorganism and culture conditions The Cyanophycean microalgae, Synechococcus marinus (NIOT-208) used in this study was obtained from culture collections of National Institute of Ocean Technology (NIOT), Chennai. The S.marinus strain was isolated from Rangat bay (12

0 29’ 16.47” N; 92

0 57’

17.89” E), Andaman & Nicobar Islands, India. The axenic cultures were maintained in modified BG 11 medium,

27 which consists of 0.2124 g L

-1 NaNo3, 0.0428

g L-1

NH4Cl, 0.02 mg L-1

K2HPo4, 0.0056 g L-1

Na2 EDTA and 0.01 g L

-1 Na2CO3 and 250 µl L

-1 of trace metal

solution (FeCl3.6H2O - 3.150 g L-1

; MnCl2.4H2o - 0.180 g L

-1; ZnSO4.7H2o - 0.022 g L

-1 CoCl3.6H2o – 0.01 g L

-1;

MnSO4.5H20 - 0.01 g L-1

and Na2MoO4.2H20 - 0.006 g L-

1) with light intensity of 120 µmol photon m

2 s

-1,

photoperiod of 16:8 light/dark regimes at a temperature of 25 ± 1

oC, salinity 34.23 psu and pH 8.01 unless

otherwise mentioned. The seawater used in this study was from Kovalam coast (12º50’N, 79º45’E), Chennai, India (salinity 34 ± 0.5 psu and pH 8 ± 0.2). The filtered (0.22 µm mixed cellulose acetate filter; Millipore) sea water (salinity 34.23 psu and pH 8.01) used for the culture medium preparations were autoclaved (121

oC

for 20 min), allowed to cool, and stabilized overnight prior to its use. Experiments were carried out in 1000 mL Erlenmeyer flasks with 500 mL of medium. All the experimental cultures were inoculated under aseptic conditions in the Laminar air flow (LAF) (Clean air systems, India) with 10 % (v/v; average cell concentration of 0.25 g L

-1 dry weight) of exponentially

growing cultures. They were maintained for a culture period of 11 days at 25 ± 1°C in 16 h light: 8h dark light regime under 15 W white fluorescent lamp illumination

27

(120 µmol photon m-2

s-1

). Analytical Methods Estimation of Biomass The samples were collected under aseptic conditions for evaluation on alternate days for a period of 11 days. For determination of algal growth, the optical density of the BG 11 culture fluid was measured at 560 nm in spectrophotometer

28 (Unicam UV 300, UV-Vis

spectrophotometer, USA). For initial and final biomass determination, 5 ml of the culture was centrifuged at 3800 x g for 10 minutes at 4

o C (Sigma centrifuge), the

pellet was filtered through a pre-weighed and pre-dried glass fiber filter paper (Millipore GF/C 47 nominal pore size 1.2 µm) and washed thrice using sterile water to remove media debris. For filtration, the vacuum pressure differentials were maintained at 35-55 mm Hg.

29 The filter papers containing algal cells were dried

at 70 oC in a hot air oven to the constant weight and

were cooled to a room temperature in a Vacuum desiccator prior to weighing.

30 From the optical density



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(O.D) values, biomass concentration was derived by plotting O.D against biomass for each treatment using standard calibration curves.

31

Scanning electron microscopy (SEM)

32

S. marinus cells (2 mL) were washed thrice in 0.1 M sodium phosphate buffer (pH 7.2) and then gently passed through a filter unit containing nucleopore filter (0.45 µM, 47 mm, Millipore, Germany). The nucleopore membrane containing the cells was fixed in 2% glutaraldehyde, prepared in 0.1 M sodium phosphate buffer (pH 7.2) for 4 h at 4 °C. The nucleopore membrane containing the cells were then washed with 0.1 M sodium phosphate buffer (pH 7.2) thrice at 4 °C and postfixed for 1 h in 1% osmium tetroxide in the same buffer in dark. The cells were dehydrated in a graded series of ethanol (30%, 50%, 70%, 90% and 100 % v/v) including absolute ethanol. The samples were dried in a critical point dryer (E3100, Quorum) and mounted on aluminium stub (12 mm Ø) with double sided carbon tape stubs, gold sputtered at a thickness of 200 A

o (SC7620 Quorum) and examined under SEM

(TESCAN VEGA3-SBU) equipped with secondary electron detector (Everhart-Thornley - YAG Crystal) at an accelerating voltage of 5 -10 kV. Zeaxanthin extraction and quantification Zeaxanthin concentration was determined using reverse phase High Performance Liquid chromatography (HPLC) system (Shimadzu-LC 2010, Japan) equipped with LC 2010 low pressure gradient HPLC pump, auto-degasser, auto-sampler and programmable UV -Vis detector. Elution was performed through a reversed-phase C-18 Phenomenex Luna (4.0 x 250 mm, 5 µm particle size) column with isocratic solvent methanol /

dichloromethane / acetonitrile / water (67.5 : 22.5 : 9.5 : 0.5, v/v/v/v) at a flow rate of 1 mL min

-1. The λ max for

zeaxanthin in the mobile phase was 453nm. Hence, the absorbance was recorded at 453 nm in a spectrophotometer (Unicam UV 300, UV-Vis spectrophotometer, USA). Data was acquired three-dimensionally (absorbance time-wavelength) using LC solutions software. The column was kept at room temperature (24–25 ºC). The samples and standard were filtered through a 0.22 µm syringe filter (acrodisc, Millipore, Germany) prior to injection. The zeaxanthin concentration in the microalga was calculated by comparing the peak area with that of authentic Zeaxanthin standard (Sigma Chemical Co., St. Louis, MO, USA). The stock standard was prepared by the addition of 1 mg zeaxanthin to 10 mL of mobile phase (0.1 mg/mL). The calibration curve of zeaxanthin was Y = 98057.52X; R

2 = 0.995 (Y is peak area; X is

zeaxanthin concentration). The calibration curve showed good linearity (R

2 = 0.995). For sample preparation, a

known quantity (10 mg) of freeze dried (Virtis, USA, -52

◦C) microalgal biomass was suitably disrupted and

extracted with 9 mL methanol:dichloromethane (3:1 v/v). The solvent extraction was repeated twice with 9 mL of solvent mixture of methanol-dichloromethane (3:1, v/v) until the pellet became colourless. The supernatant from three solvent extractions were pooled and saponified with 3 mL of 10 M KOH with 2.5 % ascorbic acid at 40 ºC for 30 min and then centrifuged at 3000 rpm for 10 min, concentrated using rotary evaporator and reconstituted with 2 mL mobile phase. The whole process was carried out in darkness.

33 Zeaxanthin yield

Pzeaxanthin was calculated using the following equation34

:

(Eq.1)

Screening of important media components using Plackett -Burman design The Plackett-Burman (PB) statistical design was used to identify the critical components of BG-11 medium for enhanced zeaxanthin yield. This design is very useful for screening the critical components with respect to their main effects. Design Expert version 9.03.1 (Stat-Ease Inc., Minneapolis, USA) was used to create the PB design. The seven independent variables screened included concentration of sodium nitrate (A), ammonium

chloride (B), trace metal solution (C), dipotassium hydrogen phosphate (D), disodium EDTA (E), sodium carbonate (F) in the BG-11 medium and initial pH (G). Each variable was studied over two specific levels, high and low denoted (+) and (-) respectively. For all screening and optimization experiments zeaxanthin yield (mg L

-1) was used as prime goal since it combines

the effect of zeaxanthin content (mg g-1

) and biomass productivity (g L

-1) as well. PB design belongs to the first

order model.

(Eq.2) Where Y is response of dependent variable (zeaxanthin yield) which is also the variable we target to predict, β0 is the intercept of the model and βi is the linear coefficient and Xi is the level of independent variable

35.

Table 1 displays the design matrix comprising 12 independent runs at their respective high (+) and low (-)

levels with their corresponding process responses. The effect of each variable (Xi) was calculated using Equation 3 (Eq.3) and the significance (p- value) was determined using Equation 4 (Eq.4)

35. The statistical

parameters analyzed were presented in Table 3.

Effect = (Eq. 3)



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where, R (H) = all responses when variable xi at high levels, R (L) = all responses when variable xi at low levels and N = total number of runs.

(Eq. 4)

Where, S.E. is the standard error of the concentration effect. All experiments were run in triplicates and mean value of the zeaxanthin yield was taken as response.

Table 1

Plackett-Burman design matrix for seven culture medium components with zeaxanthin yield as process response

Run Independent variables (Factors)

b

Zeaxanthin yielda

A B C D E F G

g Lˉ¹ g Lˉ¹ ml Lˉ¹ mg Lˉ¹ g Lˉ¹ g Lˉ¹ - mg Lˉ¹

1 0 (-1) 0.02 (-1) 0 (-1) 10 (-1) 0.002 (-1) 0.006 (-1) 7 (-1) 0.76 ± 0.03

2 0 (-1) 0.02 (-1) 1 (+1) 10 (-1) 0.018 (+1) 0.03 (+1) 7 (-1) 1.84 ± 0.32

3 0 (-1) 0.1 (+1) 1 (+1) 50 (+1) 0.002 (-1) 0.006 (-1) 7 (-1) 1.73 ± 0.08

4 1 (+1) 0.02 (-1) 0 (-1) 10 (-1) 0.018 (+1) 0.006 (-1) 9 (+1) 1.81 ± 0.07

5 1 (+1) 0.1 (+1) 0 (-1) 50 (+1) 0.018 (+1) 0.03 (+1) 7 (-1) 2.69 ± 0.11

6 0 (-1) 0.1 (+1) 1 (+1) 10 (-1) 0.018 (+1) 0.03 (+1) 9 (+1) 1.76 ± 0.22

7 0 (-1) 0.1 (+1) 0 (-1) 50 (+1) 0.018 (+1) 0.006 (-1) 9 (+1) 2.43 ± 0.06

8 1 (+1) 0.1 (+1) 1 (+1) 10 (-1) 0.002 (-1) 0.006 (-1) 9 (+1) 1.38 ± 0.09

9 1(+1) 0.02 (-1) 1 (+1) 50 (+1) 0.018 (+1) 0.006 (-1) 7 (-1) 2.88 ± 0.17

10 1 (+1) 0.1 (+1) 0 (-1) 10 (-1) 0.002 (-1) 0.03 (+1) 7 (-1) 1.46 ± 0.04

11 0 (-1) 0.02 (-1) 0 (-1) 50 (+1) 0.002 (-1) 0.03 (+1) 9 (+1) 1.5 ± 0.09

12 1 (+1) 0.02 (-1) 1 (+1) 50 (+1) 0.002 (-1) 0.03 (+1) 9 (+1) 2.05 ± 0.17 Where, A= sodium nitrate, B=ammonium chloride, C= trace metal solution, D= dipotassium hydrogen phosphate, E=disodium EDTA, F= sodium carbonate and G= pH.

avalues are mean ± S.D of triplicates (P<0.05).

bvalues in brackets indicate coded levels

Optimization of selected media components using response surface methodology (RSM)

A full factorial Central Composite Rotatable Design (CCRD)

was used for identifying the interaction effect

between the three components of the medium namely sodium nitrate (X1), disodium EDTA (X2) and dipotassium hydrogen phosphate (X3) which had a significant effect on the zeaxanthin yield. The concentration of three crucial nutrients as identified by PB statistical design (NaNO3, K2HPO4 and Na2EDTA) was studied in twenty experimental runs at five different levels coded as – α, −1, 0, 1 and +α , while other factors were set at the levels of BG11 medium (Table 2). The

value for alpha was fixed as 1.68179 in order to fulfil the rotatability of the experimental design.

36 The center

point (0 level) was repeated six times to ascertain the curvature and enabled to estimate pure error and lack of fit of the predicted model. All the experimental runs were run in triplicate and the average zeaxanthin yield was taken as response (Y). The experimental trial with the coded and actual levels of the three nutrient parameters and their respective response is given in Table 2. The obtained experimental results were further fitted through a response surface regression using the following second order polynomial equation

37:

(Eq.5)

Where Y is the predicted response or zeaxanthin yield. β0 is the regression coefficient and βi is the linear coefficient while βii signifies the quadratic coefficient. βij denotes the interaction coefficient and Xi represents the

coded levels of independent variables. The variables for statistical analysis were represented according to the following equation

38:

(Eq. 6)

Where Xi is the dimensionless coded value of variable Xi, while Xo is the value of Xi at center point and δX signifies the step change value.



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Table 2 Central composite design (CCD) representing the response zeaxanthin yield as influenced by variables: A-

NaNO3, B-Na2EDTA and C-K2HPO4 along with the corresponding values for predicted zeaxanthin yield

S. No

A: NaNO3 B:Na2EDTA C:K2HPO4 Zeaxanthin yield

a

Predicted value Actual value

g Lˉ¹ g Lˉ¹ mg Lˉ¹ mg L-1

mg Lˉ¹

1 0.25 (-1) 0.014 (+1) 20 (-1) 11.22 11.50 ± 0.22

2 0.75 (+1) 0.014 (+1) 40 (+1) 4.19 4.49 ± 0.76

3 0.5 (0) 0.01 (0) 13.18 (-1.687) 6.05 5.94 ± 0.34

4 0.75(+1) 0.006 (-1) 40 (+1) 5.79 5.61 ± 0.63

5 0.5 (0) 0.0033(-1.687) 30 (0) 10.00 9.80 ± 0.11

6 0.92 (+1.687) 0.01(0) 30 (0) 2.85 2.65 ± 0.45

7 0.75 (+1) 0.014 (+1) 20 (-1) 2.90 2.71 ± 0.08

8 0.25 (-1) 0.006 (-1) 20 (-1) 8.28 8.08 ± 0.54

9 0.5 (0) 0.01 (0) 30 (0) 11.67 11.78 ± 0.05

10 0.5 (0) 0.017 (+1.687) 30 (0) 11.13 11.18 ± 0.07

11 0.25 (-1) 0.006 (-1) 40 (+1) 7.91 8.26 ± 0.23

12 0.25 (-1) 0.014 (+1) 40 (+1) 14.48 14.14 ± 0.56

13 0.5 (0) 0.01 (0) 46.82 (+1.687) 6.82 6.79 ± 0.34

14 0.5(0) 0.01 (0) 30 (0) 11.67 11.87 ± 0.12

15 0.5 (0) 0.01 (0) 30 (0) 11.67 10.63 ± 0.19

16 0.5 (0) 0.01(0) 30 (0) 11.67 11.63 ± 0.38

17 0.5 (0) 0.01 (0) 30 (0) 11.67 11.27 ± 0.06

18 0.5(0) 0.01 (0) 30 (0) 11.67 12.86 ± 0.17

19 0.75 (+1) 0.006 (-1) 20 (-1) 8.12 8.56 ± 0.43

20 0.07 (-1.687) 0.01 (0) 30 (0) 11.63 11.63 ± 0.28 avalues are mean ± SD of triplicates (P<0.05), values in brackets indicate coded levels.

Extraction, isolation and purification of zeaxanthin39

Freeze dried (-52

ᵒC, Virtis, USA) S. marinus biomass (1

g) was mixed with 25 mL of methanol:dichloromethane (3:1) and subjected to ultrasound pretreatment in the ultrasonics bath (Sonics, USA) for 30 min. After ultrasound treatment, the mixture was saponified by the addition of 5% methanolic KOH (w/v) at 40

ᵒC for 30 min

under constant stirring. This extraction was repeated thrice until the algal pellet became colorless. The combined extract was centrifuged at 2500 g for 10 min and the supernatant was concentrated in a rotary evaporator at 40

ᵒC (Buchi, Switzerland). The extract

was redissolved in 30 mL deionized water and portioned with 40 mL ethyl acetate in a separating funnel. The upper ethyl acetate fraction was pooled and the procedure was repeated three times. The combined ethyl acetate fraction was washed in deionized water for the complete removal of KOH and concentrated in a rotary evaporator and reconstituted in methanol and further purification was done in preparatory RP-HPLC (Simadzu – LC20, Japan) equipped with a Phenomenex Luna C18 column (10 µm, 21.2 x 250 mm). The flow rate was 8 mL min

-1 and detected at 453 nm. The target

fraction was collected on the basis of the spectral characteristics of the standard. Purity of the collected fraction was confirmed in analytical RP-HPLC in an isocratic mobile phase of methanol: dichloromethane: acetonitrile: water (67.5:22.5:9.5:0.5, v/v/v/v) at a flow rate of 1 mL min

-1. The pure fraction was dissolved in

methanol and the exact molecular weight was determined using a high resolution mass spectrum (HRMS, Q-ToF, Waters, USA, IIT- Chennai, Chemistry department) instrument equipped with an electron spray ionization source (ESI).

FT Raman Spectroscopy of purified zeaxanthin40

Raman spectra were obtained using a Bruker Model RFS 27 FT-Raman spectrometer available at the sophisticated analytical instrument facility (SAIF), Indian Institute of Technology (IIT), Chennai, Tamil Nadu. FT-Raman spectra were recorded in the range of 200 cm

-1

– 3500 cm-1

. The excitation source in the FT-Raman module is neodymium-yttrium–aluminum–garnet (Nd/YAG) laser which emits continuous wave laser energy at a wavelength of 1064 nm, with a maximum power level of approximately 1.5 W at the sample. The spectra were obtained at a resolution of 2 cm

-1 with co-

addition of 2000 scans to enhance the signal-to-noise ratio. Wave numbers were accurate to ± 1cm

-1.

STATISTICAL ANALYSIS

Data presented were the average of three independent experiments. The results of the experimental design were analyzed and deciphered using Design Expert Version 9.03.1 (Stat Ease Inc. Minneapolis, Minnesota, USA) and the obtained values were subjected to two way ANOVA. The values are considered significant if p < 0.05.

RESULTS

Scanning electron micrograph (SEM) of S. marinus (NIOT-208) Figure 1 shows the SEM of S. marinus (NIOT-208) grown in BG 11 medium for 11 days. Synechococcus (NIOT-208) is a small (< 2 µm diameter) sheathless coccoid Cyanophycean microalgae. The morphological features observed revealed the features reported as characteristic to genus Synechococcus

41.



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Evaluating the significant nutrient factors using Plackett-Burman (PB) design Identifying the optimal concentration of major and minor nutrients is pivotal for augmenting carotenoid production from S. marinus. Major nutritional factors like nitrate and phosphate are essential for the formation of structural and functional components of the cell, whereas, minor nutrients like trace elements (copper, cobalt, manganese, zinc and molybdenum) act as cofactors for various enzymes involved in growth and carotenoid

biosynthesis in algae42

. Hence, in the current study initially six nutrient components and pH of the culture medium were screened using PB design. The PB design analyzed comprehensively the influence of seven independent (assigned) variables and five unassigned variables (commonly termed as dummy variables) on zeaxanthin yield in a PB experiment of 12 runs. The five dummy variables were included to estimate the experimental errors of the analyzed data.

Figure 1 Scanning electron micrograph showing morphology of strain Synechococcus marinus (NIOT-208)

grown in BG-11 medium for 11 days at 26ᵒC

Figure 2 Pareto chart for optimization of zeaxanthin production from S. marinus (NIOT 208)

The responses of PB experiments were presented in Table 1. Maximum zeaxanthin yield (2.88 ± 0.17 mg L

-1)

was noticed in run 9 (NaNO3-1 g L-1

, NH4Cl- 0.02 g L-1

, trace metal solution-1 ml L

-1, K2HPO4- 50 mg L

-1,

Na2EDTA- 0.018 g L-1

, Na2CO3-0.006 g L-1

, pH-7.0) and minimum yield (0.76 ± 0.03 mg L

-1) was observed in the

absence of sodium nitrate and trace metal solution (run 1). The variation reflected the importance of optimization to attain higher productivity.

43 Statistical analysis

(ANOVA) was done to visualize the significance of different factors for the zeaxanthin production (Table 3). With respect to the main effect of the independent variables (Figure 2), three out of the seven tested variables had a statistically significant (p < 0.05) impact

on the zeaxanthin yield. Among the significant variables Na2EDTA which is used as a chelating agent had the maximum positive effect (44.1%), followed by K2HPO4 (39.20%) on zeaxanthin yield. Conversely, another major nutrient NaNO3 (10.73%) had a significant negative effect on zeaxanthin yield, whereas other four variables did not have a significant effect on zeaxanthin yield. The Pareto chart (Figure 2) illustrates the order of significance of the independent variables to zeaxanthin yield. A positive sign of the tested variable indicates that higher zeaxanthin yield can be attained at a higher level of the positive sign variables, conversely higher zeaxanthin yield for the negative sign variables can be observed at their lower levels.

44 The R

2 of the present



B-64

study was 0.9838 which indicated 98.38% of the variability in response is attributed to the given variables. The value of adjusted determination coefficient (Adj. R

2= 0.9554) was also high

authenticating the validity of the model. The high correlation coefficient also signified a good correlation between observed and predicted values too (Table 3). In this study the predicted model showed a high F value (34.63) and very low P value (0.002) indicating its high significance. The three factors which had significant effect on zeaxanthin yield viz. Na2EDTA (F= 109.65); K2HPO4 (F = 97.44) and NaNO3 (F = 26.67) had high F

values and very low P values (Table 3). The normality probability plot of residuals (Figure 3) showed the points lying proximate to the diagonal line. Hence, it can be inferred that the residuals were normally distributed and the observed values were very close to the predicted values. This further substantiated that the model had fitted well with the expected results. Thus Plackett Burman based statistical design enabled to screen the factors having a significant impact in zeaxanthin yield. The identified three factors (Na2EDTA, K2HPO4 and NaNO3) were further optimized using RSM to identify the interaction effect.

Table 3

Analysis of variance (ANOVA) - [partial sum of squares – Type III] for the experimental results of the Plackett-Burman design

Source Standardized

Effects Sum of

Squares

Df Mean

Square F

Value p-value Prob> F

Percentage Contribution

Model - 3.79 7 0.54 34.63 0.002 -

A- NaNO3 0.37 0.42 1 0.42 26.67 0.0067 10.73

B-NH4Cl 0.10 0.03 1 0.03 1.93 0.2371 0.78

C-Trace metal 0.16 0.082 1 0.082 5.22 0.0844 2.10

D- K2HPO4 0.71 1.53 1 1.53 97.44 0.0006 39.20

E- Na2EDTA 0.76 1.72 1 1.72 109.65 0.0005 44.11

F- Na2Co3 0.051 7.803E – 003 1 7.803E-003 0.5 0.5191 0.20

G- pH -0.071 0.015 1 0.015 0.97 0.3813 0.39 R

2 = 0.9838, Adjacent R

2 =0.9554, Predicted R

2 = 0.8539, C.V% =6.74.

Optimization of significant media components using response surface methodology (RSM) The three critical factors (NaNO3, K2HPO4 and Na2EDTA) identified by the PB statistical screening method were further optimized by a central composite design (CCD) comprising 20 runs. Table 2 summarizes the twenty runs with the different combination of the

three factors at specified level along with their corresponding predicted and actual responses (zeaxanthin yield). Multiple regression analysis was applied to experimental data in Eq. (7)

45, to determine

the regression coefficients of the following second-order polynomial equation using Design Expert software for maximal zeaxanthin yield:

(Eq.7) Where: X1= sodium nitrate concentration (A), X2 = Disodium EDTA concentration (B) and X3 = Dipotassium hydrogen phosphate concentration (C). The statistical significance of the second order polynomial equation was evaluated by ANOVA

46

(Analysis of Variance). Table 4 shows ANOVA of the CCD experiment. The F test analysis results revealed that the predicted value was statistically significant with a high F value (68.2) for zeaxanthin yield and a very low p value (p < 0.0001). Only one out the three linear coefficients (X1-NaNO3 concentration) and two out of the three quadratic coefficients (X1

2 and X3

2) were

statistically significant (Table 4; < 0.01). Nevertheless, the interaction effect of NaNO3 vs Na2EDTA, NaNO3 vs K2HPO4 and K2HPO4 vs Na2EDTA was statistically significant. The high coefficient of determination R

2=

0.984 and low probability value obtained for zeaxanthin yield suggests that the model is adequate to predict the accuracy of the response trends

42. The "Pred R-

Squared" of 0.949 was in reasonable agreement with "Adj R-Squared" of 0.969 which indicates good agreement between experimental and predicted values (Table 4). The effect of interaction of the selected variables on zeaxanthin yield was also studied against any two independent variables while keeping the other independent variables at their constant level. The response surface plots or contour plots were used to predict the optimal values for the selected variables for obtaining a maximal zeaxanthin yield (Figures 4A & 4B). The study of the contour plots and response surface plots revealed that the optimal values for the selected variables were: NaNO3 (250 mg L

-1), K2HPO4 (40 mg L

-1)

and Na2EDTA (14 mg L-1

). The optimal values drawn from Figures 4A and 4B were in close agreement with the optimized regression model Eq. (7).



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Table 4 Analysis of variance (ANOVA)- [partial sum of squares – Type III] for the experimental

results of the central-composite design (Quadratic Model)

Sum of Mean F p-value

Source Squares Df Square Value Prob> F

Model 214.61 9 23.85 68.2 < 0.0001

A-NaNO3 93.15 1 93.15 266.4 < 0.0001

B-Na2EDTA 1.54 1 1.54 4.42 0.0619

C-K2HPO4 0.72 1 0.72 2.06 0.1816

AB 33.34 1 33.34 95.36 < 0.0001

AC 1.93 1 1.93 5.52 0.0407

BC 6.57 1 6.57 18.8 0.0015

A2 35.4 1 35.4 101.23 < 0.0001

B2 2.23 1 2.23 6.37 0.0302

C2 49.4 1 49.4 141.29 < 0.0001

R2 = 0.984, pred R

2= 0.949, Adj R

2 =0.9695

Figure 3 The normality probability plot of the residuals in PB design

Validation of predicted variables The optimal concentration for the three nutrient components predicted by RSM was: NaNO3 (250 mg L

-

1), K2HPO4 (40 mg L

-1) and Na2EDTA (14 mg L

-1). The

optimized values were validated by performing separate experiments in triplicates with optimized BG11 medium and un-optimized BG11 medium. The zeaxanthin yield obtained using the optimized medium was 14.61 ± 1.29 mg L

-1 (Table 5) was in close agreement to the

predicted values of 14.48 mg L-1

by RSM. Apart from zeaxanthin yield, it also resulted in the increase of biomass from 0.68 ± 0.26 g L

-1 to 2.03± 0.56 g L

-1 (Table

5). The predicted value of zeaxanthin yield and interactions between the three parameters as revealed by three dimensional response surface plots were shown in Figures 4A and 4B. The optimization process resulted in 8.46 fold increase in the zeaxanthin yield when compared to un-optimized BG 11 medium. The good correlation between these observed yield and predicted response confirms that the predicted responses for the models were adequate for explaining

the observed response. Hence the models are reproducible. The results further demonstrated the usefulness of statistical optimization of culture medium components for enhanced zeaxanthin production in S. marinus. Purification and characterization of zeaxanthin The chromatogram of the authentic zeaxanthin standard analyzed by analytical RP-HPLC is displayed in Figure 5A. The chromatogram of crude zeaxanthin obtained from Synechococcus marinus is shown in Figure 5B. The purity of crude zeaxanthin extracted from S. marinus (NIOT-208) was 68.71%. The chromatogram of crude zeaxanthin showed one major peak and two minor peaks at 453 nm (Figure 5B). Purification of crude zeaxanthin was done using preparatory RP-HPLC and the major fraction eluted at 12.51 min (Figure 5C) was identified as zeaxanthin by comparing with standard and it also showed a high resolution molecular mass of 568.31 daltons.



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Figure 4

RSM contour and three dimensional response surface plots for the yield of zeaxanthin (A: sodium nitrate; B: disodium EDTA and C: Dipotassium hydrogen phosphate)

Table 5

Validation of the RSM model for zeaxanthin yield by S.marinus (NIOT 208)

Responses Before

optimizationa

Optimized media by RSM

b Fold

increase

Zeaxanthin yield (mg L-1

) 1.72 ± 0.22 14.61± 1.29 8.46

Biomass (g L-1

) 0.68 ± 0.26 2.03 ± 0.56 2.98 aBG 11 medium.

bBG-11 medium provided with NaNO3 (250 mg L

-1), Na2EDTA (14 mg L

-1)

and K2HPO4 (40 mg L-1).

Figure 5 RP-HPLC profile of zeaxanthin extracted from S. marinus at each step of purification. (5A) zeaxanthin

standard; (5B) zeaxanthin extracted from S.marinus; (5C) preparative RP-HPLC of zeaxanthin

zeaxanthin



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Figure 6 FT Raman spectra of zeaxanthin extracted and purified from S. marinus (NIOT-208)

FT Raman spectral analysis FT Raman spectra of zeaxanthin was analyzed within the spectral range of 200-3500 cm

-1. The isolated

zeaxanthin was subjected to FT-Raman spectral analysis and the following three characteristic strong Raman bands were recorded at 1537 cm

−1, 1173 cm

−1

and 1032 cm−1

(FT-Raman spectroscopy), corresponds to C=C stretching, C–C stretching and C–CH3

deformation modes of carotenoid zeaxanthin respectively (Figure 6). With respect to the carotenoid zeaxanthin, the characteristic peak relating to its molecular structure should lie within the spectral intervals of 640-1301 cm

-1 (1173 cm

-1) for carbon-carbon

single bond stretching (C-C) and 1526-3070 cm−1

(1537 cm

−1) carbon-carbon double bond stretching (C=C)

40.

Hence, FT Raman spectral analysis is a rapid, viable and non-destructive technique to establish the authenticity and assessment of the carotenoid zeaxanthin.

DISCUSSION

Algal growth inclusive of Cyanophycean microalgae is highly dependent on the availability of major nutrients like nitrogen and phosphate

47. In the present study, PB

and RSM was used to analyze the optimization of BG-11 media components for the enhanced zeaxanthin productivity of S. marinus. EDTA which was added to algal culture medium as chelating agent showed the highest percentage (44.11%) contribution to zeaxanthin productivity along with highest significance (F=109.65) and lowest p value (0.0005) (Table 3). An optimized concentration of chelating agent has been indicated in improving iron and phosphate uptake at higher pH and improves trace metal availability.

48,49 As iron is indirectly

involved in pigment biosynthesis, improvement of iron uptake at higher pH might have also contributed to enhancement of zeaxanthin yield of Cyanophycean alga S. marinus. In line with the present study, increased EDTA has been reported to enhance biomass and pigment production of Chlorococcum sp by Satpadi et al.

50 Nitrogen and phosphorous are the major nutrients

in Cyanophycean algal growth, cellular metabolism and pigment production.

47,51 In the present study, zeaxanthin

yield which is a product of biomass and zeaxanthin content was highly affected by the concentration of nitrogen source. With regard to keratogenesis,

zeaxanthin synthesis was found to increase with a significant decrease in the nitrogen concentration

52. In

the RSM study, higher concentration of nitrogen source (920 mg L

-1) showed lowest zeaxanthin production of

2.65 mg L-1

(run 6 of CCD). But a low nitrate concentration (250 mg L

-1) showed the highest

zeaxanthin production of 14.14 mg L-1

(run 12 of CCD). These findings agreed well with Nagarajan and Sujatha

53, who reported high carotenoid production in

Spirulina platensis was obtained at less nitrogen concentration. Notably, under nitrogen starvation, algal cell division is blocked while photosynthesis continues, thus leading to the accumulation of carotenoids, triglycerides and carbohydrates which do not require nitrogen source for their synthesis.

54,55 However, total

absence of nitrogen source affects the biomass production and consequently results in poor zeaxanthin synthesis, hence nitrate should thus be supplied at a moderate level.

56,57 So, the optimal concentration of

NaNO3 of 250 mg L-1

predicted for maximal zeaxanthin yield is justified. The importance of K2HPO4 in zeaxanthin yield was evident from the high F value (F = 97.44, p < 0.0006).

Phosphorus is a major nutrient

component which is vital for growth and normal development of algae.

50,47 Dipotassium hydrogen

phosphate was used as a PO4 source with a range of 13.18 - 46.82 mg L

-1 and a higher PO4 concentration of

40 mg L-1

(Run 12) yielded more amount of zeaxanthin. The findings were similar to Celekli et al

58, who reported

that moderate supply of phosphate increased the carotenoid synthesis in Cyanophycean algae, Spirulina platensis. FT Raman spectral analysis, indicated that the purified zeaxanthin had the characteristics closer to the reported values for zeaxanthin obtained from Porphyridium purpureum.

59 High biomass production,

zeaxanthin content and yield are key parameters affecting the economic feasibility of zeaxanthin production from microalgae. The two-step statistical optimization of culture components resulted in 8.46 fold higher zeaxanthin yield and signified the relevance of statistical optimization for improved zeaxanthin yield.

CONCLUSION

The optimized medium formulated as a result of two step statistical optimization involving Plackett-Burman method and RSM containing 250 mg L

-1 of sodium



B-68

nitrate, 14 mg L-1

of disodium EDTA and 40 mg L-1

of dipotassium hydrogen phosphate augmented zeaxanthin yield by 8.46 fold more than that obtained in the un-optimized BG11 medium. The enhanced zeaxanthin yield has established the prospects of S. marinus as a potential candidate for future commercialization of zeaxanthin production using this alga. The results substantiated the use of response surface methodology as a useful statistical tool for enhancing the zeaxanthin production of the Cyanophycean microalga, S. marinus. The study thus demonstrated the optimized production and purification process for zeaxanthin production from S. marinus (NIOT-208).

ACKNOWLEDGEMENTS

The authors are grateful to the Director, National Institute of Ocean Technology, and the Ministry of Earth

Sciences, Government of India for providing adequate research funding, infrastructure facilities and constant support to carry out this research work.

AUTHORS CONTRIBUTION STATEMENT The corresponding author S.Priyanka, carried out the experiments contributed to the interpretation of the results and took the lead in writing the manuscript. The authors, Dr.J.T.Mary Leema and Dr.R.Kirubagaran conceived and designed the experiments and contributed to the critical revision of the manuscript. All authors provided critical feedback and helped to shape the research, analysis and manuscript.

CONFLICT OF INTEREST

Conflict of interest declared none.

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statistical optimization of bg11 medium for enhanced

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