Statistical optimization of media for maximization of biomass

Chapter 3. Screening and characterization of Clostridium strains on the

3.3 Results and discussion

3.3.4 Statistical optimization of media for maximization of biomass

Phenomenon of product inhibition exerts a limit on the maximum attainable titer in any process; therefore, further improvement in such a process can be achieved by improving the productivity rather than the product titer. Taking into account the product toxicity experienced by the strain, as observed from the butanol tolerance Page|64 Department of Biosciences & Bioengineering| TH-2103_126106021

experiments, optimization of media composition was carried out separately with the aim of maximizing the butanol and biomass productivity. A CCD was constructed to optimize the initial concentration of three media componentsviz., glucose, peptone, and trace elements (Table 3.4) and to study the effect of their interaction on model response.

The experimental results were analyzed through RSM for two objective functions: (i) maximization of biomass productivity and (ii) maximization of butanol productivity. As biomass formation and butanol production are two mutually exclusive parameters, the nutritional conditions required for growth and butanol production were optimized separately. The experiments resulted in wide range of biomass productivity from 0.08 g L^-1 h^-1 to 0.21 g L^-1 h^-1, while the butanol productivity varied from 0.12 g L^-1 h^-1 to 0.36 g L^-1 h^-1. The experimental data along with the corresponding RSM predicted values, for both the objective functions, are tabulated in Table 3.4.

Table 3.4. Tabular representation of CCD design of media parameters containing experimental and predicted values for maximum biomass productivity and maximum butanol productivity as two separate responses

Std.

order

Glucose (g L^-1)

Peptone (g L^-1)

Trace (mL L^-1)

Max. biomass productivity

Max. butanol productivity Exp. Pred. Exp. Pred.

1 40 30 10 0.2 0.202573 0.22 0.209913

2 120 30 10 0.16 0.147769 0.27 0.271022

3 40 70 10 0.17 0.172489 0.27 0.255798

4 120 70 10 0.1 0.098824 0.25 0.249146

5 40 30 30 0.2 0.195831 0.23 0.222809

6 120 30 30 0.13 0.133647 0.3 0.302557

7 40 70 30 0.16 0.166567 0.26 0.254255

8 120 70 30 0.09 0.085522 0.26 0.266242

9 12.73 50 20 0.21 0.200183 0.12 0.139161

10 147.27 50 20 0.08 0.085947 0.21 0.200627

11 80 16.36 20 0.19 0.193988 0.28 0.28587

12 80 83.64 20 0.13 0.128222 0.29 0.293917

13 80 50 3.18 0.15 0.159692 0.3 0.307283

14 80 50 36.82 0.15 0.142838 0.33 0.332504

15 80 50 20 0.17 0.175037 0.36 0.35758

16 80 50 20 0.18 0.175037 0.36 0.35758

17 80 50 20 0.17 0.175037 0.36 0.35758

18 80 50 20 0.18 0.175037 0.36 0.35758

Max.- Maximum; Exp.- Experimental; Pred.- Predicted

RSM based model construction yielded two polynomial equations (Eq. 3.2

and 3.3), which correlated the medium parameters with the predicted response of biomass productivity and butanol productivity.

Y =0.49+0.0020X₁+0.0021X₂+0.1X₃−2.16x10⁻⁵X₁²−3.75x10⁻⁵X₂²−

0.026X₃²−1.79x10⁻⁵X₁X₂−1.40×10⁻⁴X₁X₃−3.12x10⁻⁵X₂X₃ (3.2) Y =0.25+0.008X₁+0.008X₂−0.061X₃−4.17x10⁻⁵X₁²−5.98x10⁻⁵X₂²−

0.013X₃²−2.12x10⁻⁵X₁X₂−1.16×10⁻⁴X₁X₃−1.8x10⁻⁴X₂X₃ (3.3) where, Yis the predicted biomass and butanol productivity (g L^-1 h^-1), respectively, whileX_i (i=1-3) represents the medium components; glucose, peptone, and trace elements, respectively. Analysis of variance showed a high degree of significance for both biomass and butanol productivity as evident from thep-value less than 0.05 for both the objective functions (Tables 3.5 and 3.6). The regression analysis showed a correlation coefficient (R²) of 0.98 for both the objective functions, indicating that only 2% of the 18 experiments performed could not be fitted by the model. A normal distribution of residuals ensures an adequate fit of the model with the experimental data (Fig 3.4 and 3.5).

Table 3.5. Analysis of variance for the quadratic regression model obtained from CCD-RSM employed in optimization of media components for the biomass productivity fromClostridium acetobutylicumMTCC 11274

Source DF Seq SS Adj SS Adj MS F p value

Regression 9 0.21647 0.21647 0.024052 47.81 0

Linear 3 0.19615 0.19615 0.065383 129.96 0

Glucose 1 0.146419 0.146419 0.146419 291.03 0

Peptone 1 0.046543 0.046543 0.046543 92.51 0

Trace 1 0.003187 0.003187 0.003187 6.34 0.036

Square 3 0.01841 0.01841 0.006137 12.2 0.002

Glucose*Glucose 1 0.009443 0.013967 0.013967 27.76 0.001 Peptone*Peptone 1 0.001443 0.003059 0.003059 6.08 0.039 Trace*Trace 1 0.007525 0.007525 0.007525 14.96 0.005

Interaction 3 0.001909 0.001909 0.000636 1.27 0.35

Glucose*Peptone 1 0.001653 0.001653 0.001653 3.29 0.107 Glucose*Trace 1 0.000253 0.000253 0.000253 0.5 0.498 Peptone*Trace 1 0.000003 0.000003 0.000003 0.01 0.939 Residual Error 8 0.004025 0.004025 0.000503

Lack-of-Fit 5 0.003956 0.003956 0.000791 34.53 0.007

Pure Error 3 0.000069 0.000069 0.000023

Total 17 0.220494

* p-value higher than 0.05 shows insignificance

# X₁, X₂, X₃ represents the media components glucose, peptone, and trace elements, respectively

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Table 3.6. Analysis of variance for the quadratic regression model obtained from CCD-RSM employed in optimization of media components for the butanol productivity fromClostridium acetobutylicumMTCC 11274

Source DF Seq SS Adj SS Adj MS F p value

Regression 9 0.065083 0.065083 0.007231 59.21 0

Linear 3 0.005407 0.005407 0.001802 14.76 0.001

Glucose 1 0.004561 0.004561 0.004561 37.34 0

Peptone 1 0.000078 0.000078 0.000078 0.64 0.447

Trace 1 0.000078 0.000078 0.000078 0.64 0.447

Square 3 0.057103 0.057103 0.019034 155.86 0

Glucose*Glucose 1 0.057103 0.057103 0.019034 155.86 0 Peptone*Peptone 1 0.057103 0.057103 0.019034 155.86 0 Trace*Trace 1 0.002246 0.002246 0.002246 18.39 0.003

Interaction 3 0.002574 0.002574 0.000858 7.02 0.012

Glucose*Peptone 1 0.002296 0.002296 0.002296 18.8 0.002 Glucose*Trace 1 0.000174 0.000174 0.000174 1.42 0.267 Peptone*Trace 1 0.000104 0.000104 0.000104 0.85 0.383 Residual Error 8 0.000977 0.000977 0.000122

Lack-of-Fit 5 0.000963 0.000963 0.000193 41.27 0.006

Pure Error 3 0.000014 0.000014 0.000005

Total 17 0.06606

* p-value higher than 0.05 shows insignificance

# X₁, X₂, X₃ represents the media components glucose, peptone, and trace elements, respectively

Fig. 3.4. Normality plot of residuals where the response was biomass productivity.

The linear and quadratic effects of all the three parameters were found to be significant on the growth of the strain. No significant interaction among the media components was found for biomass productivity within the selected concentration range. In case of butanol productivity, both linear (except peptone) and quadratic

Fig. 3.5. Normality plot of residuals where the response was butanol productivity.

Table 3.7. Comparison of biomass and butanol productivity from C. acetobutylicum MTCC 11274 grown in un-optimized media and CCD-RSM based optimized media composition

Media component (g L^-1)

Un-optimized media

Media optimized for biomass productivity

Media optimized for butanol productivity

Glucose 80 33.11 82.04

Peptone 40 21.12 49.66

K₂HPO₄ 0.5 0.5 0.5

KH₂PO₄ 0.5 0.5 0.5

MgSO₄.7H₂O 0.2 0.36 0.46

MnSO₄.H₂O 0.01 0.018 0.023

FeSO4.7H2O 0.01 0.018 0.023

NaCl 0.01 0.018 0.023

PABA 0.01 0.01 0.01

Biotin 0.01 0.01 0.01

Ammonium acetate 2.2 2.2 2.2

Biomass productivity

(g L^-1 h^-1) 0.135 0.28 ND

Butanol productivity

(g L^-1 h^-1) 0.22 ND 0.36

% Increase in biomass

productivity^a ND 103.5 ND

% Increase in butanol

productivity^b ND ND 63.6

a & b - represents the percentage increase of the biomass and butanol productivity in the optimized medium as compared to the un-optimized medium under flask conditions; ND - Not determined

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effects of all the parameters along with interaction between glucose and peptone were found to be significant. Maximum biomass productivity of 0.28 g L^-1h^-1was predicted by the RSM for concentrations of glucose, peptone, and trace elements of 33.12 g L^-1, 21.12 g L^-1and 18.1 mL L^-1, respectively. Similarly, maximum butanol productivity of 0.36 g L^-1h^-1was predicted for 82.04 g L^-1of glucose, 49.66 g L^-1of peptone and 23.2 mL L^-1 of trace elements. Concentrations of glucose, peptone, and trace elements were found to be significantly different in the medium optimized for butanol and biomass productivity implying mutually exclusive nature of these two parameters.

The RSM predicted media composition was validated by corresponding experimental values. CCD-RSM based media optimization resulted in 103.5% increment in biomass productivity and 63.6% increment in butanol productivity as compared to the biomass (0.135 g L^-1 h^-1) and butanol productivity (0.22 g L^-1 h^-1) obtained from the un- optimized media composition (Table 3.7).

Various studies have been targeted towards increasing butanol titer (Kaushal et al., 2017; Kao et al., 2013; Yadav et al., 2014). However, limited reports are available with respect to improved butanol productivity for Clostridium spp. via media optimization. One such study was carried out by Moon et al. (2011), where maximization of butanol and 1, 3-PDO was achieved during active growth phase of C. pasteurianumDSM 525 through medium optimization.