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:GGGG&&&�0�0�0�0�0�0�0$34��6J�0��&"&&&�0��GG��2�+�+�+&~�G�G�0�+&�0�+�+d-�-G�����"p�]���*�|-�0�20�2�-,7V+.7�-7��-�&&�+&&&&&�0�0�+&&&�2&&&&��������������������������������������������������������������������7&&&&&&&&&f	o:	Title: Importance of optimization of fermentative parameters for enhanced metabolite 
Corresponding author: Rajesh K. Srivastava
Department of Biotechnology, GIT, Gitam Institute of Technology and Management (GITAM) (Deemed to be University), Visakhatpatnam, A. P. India, Mobile: +919703842963; Email:  HYPERLINK "mailto:rajeshksrivastava73@yahoo.co.in"rajeshksrivastava73@yahoo.co.in; 
Abstract
Optimization of multiple variables and constraints are needed to solve the problems of fermentation process and are reported in recent years. It can help in development of high-performance, robust, cost-effective bioprocesses for variable types of metabolites for our needs of lives. Several statistical models can provide innovative solutions for fermentation problems and Response Surface Methodology (RSM) has applied to optimize the fermentation variables (i.e. pH, temperature and substrate concentration). Optimization of fermentation medium and fermentation process conditions has been achieved by applying the borrowing, component swapping, biological mimicry, one-factor-at-a-time and factorial design. Plackett and Burman design, central composite design, response surface methodology, evolutionary operation, evolutionary operation factorial design, artificial neural network, fuzzy logic and genetic algorithms are also reported to apply for optimization of fermentation which has helped in formation, concentration and yield of a particular fermentation end product in fermentation processes. Optimization of fermentation medium and process conditions has reported to maximize the products quantity and yield with maximization of the more profits from fermentation process. Evolutionary algorithms (EAs) can help in optimal design of batch fermentation technology with development of computer-based solving problems and it generates optimal or near optimal solutions to fermentation industries problems. This paper will discuss about different mode of fermentation with their different fermentative parameters for maximization of yield or titre of metabolites. 
Keywords: Metabolites; Fermentation; Optimal solutions, Yield; Titre; Fermentative parameters; Substrate concentration
Introduction:
Fermentation is reported as basics industrial activities for metabolites synthesis and shown as important field of our research interest for system engineering because of its complex, biological, non-linear phenomena and dynamic processes [1]. It has developed the major problems due to fluctuations in the quality of the raw material, influence of temperature, long process time and biomass concentration. So optimization method or techniques can help us to decide suitable parameters for fermentation processes via optimal determination the concentration of the medium components and also most suitable reaction conditions for maximizing the fermentation products with minimum byproducts [1, 2].  
Many aims are associated with the optimization of fermentation processes which can be helped in increase the yield of the final product with process meeting with good or standard levels for manufacturing practices. Most of fermentation processes is reported to carry on in available equipment with final scale of operation for wild or genetically modified microorganisms with capability to overproduce recombinant protein or any other metabolites. Advantage of fermentation has been reported with vast majority of the bioprocesses via utilization of Escherichia coli, Saccharomyces cerevisiae and Pichia pastoris. Insurance of an efficient approach of scaling up fermentation processes for biopharmaceutical purposes has been discussed with multidisciplinary environment which can help in large scale metabolite production [3]. 
Rationally introduction of hydrophobic mutations has reported into the N-terminus of Streptomyces griseus trypsin (SGT) Exmt (R145I) via replacing of the propeptide with peptide with the sequence Phe-Pro-Val-Asp-Asp-Asp-Asp-Lys (FPVDDDDK). Mutant Exmt (R145I) has shown the highest amidase specific activity.  Engineering the �-factor signal peptide has improved (3.75-fold) the trypsin production (amidase activity) around 178 U�m.L-1 in a 3-L fermenter. Identification has done by mass spectrometry for all of the residues in autolysis processes and then mutated the proteins with resulted protein has evaluated. Variant tbcf (K101A) has shown high stability (228 U.m.L-1) and production (186 mg�L-1). Engineering of the N-terminal peptide and self-degradation sites in Pichia pastoris has shown recombinant strain construction for potential for large-scale production of active trypsin (potential applications in the leather processing, bioethanol, detergent and pharmaceutical industry) via improving expression of trypsin with efficient designed of signal peptide [4]. 
Actinomycetes microbial system has reported excellent sources for production of novel bioactive compounds which can be utilized as potential drug candidates for antibiotics or any other drugs development. Industrial efforts has developed novel strategies for many antimicrobials drug especially antibiotics from past two decades.  But effective of drugs has severely reduced with increasing threat of multidrug-resistant pathogens and the development of new technologies has to discover or develop with identification of the secondary metabolite production with attracted interest in whole-genome sequencing methods for biosynthetic gene clusters.  Gene clusters can be changed by genome mining and cloned them to express them in heterologous hosts for higher throughput. Now metabolic engineering approaches can be enabled to optimize production yields and to directly manipulate the pathways to generate modified products [5]. 
Temperature, pH, hydrolytic enzyme volume, and fermentative microbe�s inoculums volume are reported as main process parameters of fermentation process and these have played vital role in cellulosic ethanol production [6]. Analyzing one variable at a time (OVAT) approach has applied in several fermentative processes including ethanol and it is laborious and time consuming for identification of various independent variables with their effects analysis in fermentative processes [7]. Statistically based experimental designs (Plackett-Burman design, Box Behnken design and Taguchi orthogonal array design) have reported to summarize the collection and sorting of variables for consideration, determination of variable amount with analysis of the variable for different parameters with their variable error effect. Better quality with low cost bioprocess has been generated from Taguchi design of experiments (DOE) approaches with maximization of robustness for products and processes [6, 8]. 
Pichia pastoris, is reported as a methylotrophic yeast with system of capability for the production of heterologous proteins (biopharmaceuticals recombinant products / industrial enzymes). To maximize and optimize the production of these products, design of expression vectors, optimization of gene copy number, co-expression of secretory proteins (chaperones), engineering of glycosylation and secretory pathways has been focused by molecular research [9]. And physiological effects of different cultivation strategies have been studied with molecular effects of the gene construct (cellular stress through over expression or incorrect post-translational processing). System optimization is is urgently required for understanding the behavior of new molecular constructs [10]. 
Recombinant protein production is related to variations in biomass growth with strain design and screening process for cultivation systems for speci�c production processes in bioreactors. Speci�c formation rates of recombinant proteins (q)  with speci�c growth rates (�)  is analyzed for comparing different systems (PAOX1/methanol and GAP/glucose) with pivotal concept for bioprocess engineering of P. pastoris [10, 11]. 
Wild strain of P. pastoris has shown its ability to grow on many different carbon and energy sources (glycerol, glucose and methanol) in manufacturing processes of metabolites in fed-batch cultivation. It has shown the choice of carbon-substrate at feasible operational range with different speci�c growth rate (�) and their optimum productivity (q). Values of the growth characteristics (i.e., �max (maximum specific growth rate), Yx/s (biomass to substrate yield), ms (speci�c maintenance rate)) of microbial strain has found to play crucial role in formation of recombinant protein via deciding the physiologically impaired nature due to the introduction and expression of a foreign gene and shown in figure 1[12]. In proposed paper, author will discuss the different fermentation processes with their fermentative parameters for enhanced metabolite production. He will discuss the different types of microbial systems for metabolites synthesis.
Fermentation processes
The complex microbial ecosystem are found in fermentation processes for undigested food in human intestinal tract and reported to produce a wide range of metabolites via interaction with the host's cells  with influence the physiological processes in the colon. Metabolites are absorbed in human bodies and influenced the overall mammalian biochemistry via eliciting systemic effects. Different kind of secondary metabolites (antibiotics, phytohormones, food grade pigments, alkaloids) are produced by solid state fermentation (SSF). Physiology in SSF processes has shown several similarities with physiology in liquid medium as adapted for efficient processes (idiophase in solid medium) [13].  
Regulations of secondary metabolites (SMs) are shown its traditionally importance for design of culture media, process control and reactor design with strain improvement strategies (genetic improvement). Nutritional stimuli (nutritional shift-down) studies are reported as environmental cues for induction of secondary metabolism or mechanisms for these signals with sensation and transduction for activation of regulatory networks [14]. Spinosyns is secondary products and has high insecticidal activity with wide application. It is produced by metabolic pathway of Saccharopolyspora spinosa strain CGMCC4.1365 with low spinosad yield. And Response surface methodology (RMS) and artificial neural network (ANN) modeling have been applied to optimize the medium components for spinosad production in this fermentation. Experiments have been performed using a rotatable central composite design, and its data are used to construct an ANN model and an RSM model. Genetic algorithm (GA) has helped in the input space of the ANN model for optimal values of medium component concentrations. The regression coefficients (R) for the ANN and RSM models are reported the 0.9866 and 0.9458 respectively, with higher fitness with ANN model via maximal spinosad yield (401.26 mg.L-1). The hybrid ANN/GA approach has provided a viable alternative to the conventional RSM approach for the modeling and optimization of fermentation processes [15]. 
For metabolites production there are several modes of fermentation employed in industries based on microbial strains and metabolites nature. We are discussing some metabolites production below and also shown in table1.
Batch process of fermentation:
 Development of a optimized submerged batch fermentation strategy has shown a systems biology studies for metabolic switching in microbial strain of S. coelicolor A3(2) as highly time-resolved system for cultivation conditions ensuring high reproducibility and also distinct phases of culture growth ( due to nutrient depletion for transition triggering) with secondary metabolite production and fermentative parameter are reported in figure1. With help of labeling and cultivation experiments, presence of D- glucose, L-glutamate has been analyzed as preferred carbon source, whereas D- glucose alone are found to incapable of maintaining culture growth due to a metabolic bottleneck at the oxidation of pyruvate to acetyl-CoA. Effect of phosphate and L-glutamate depletion has been analyzed on metabolic transition to antibiotic production phase and D- glucose and L-glutamate are necessary to maintain high growth rates via preventing secondary metabolite production before nutrient depletion [16, 17].   
Effect of different initial reducing sugar concentration has been studied on ethanol production in batch fermentation of immobilized Saccharomyces cerevisiae CICC 1308 with sweet sorghum cultivar stalk juice. Kinetic model has been applied for increase of initial sugar concentration with significant inhibition on the maximum specific growth rate.  But no influence has reported on the maximum specific ethanol production rate. Hinshelwood model has described the effects of different initial reducing sugar concentration on the kinetic parameters of ethanol fermentation for this strain and substrates. Hinshelwood model has helped in dynamics of ethanol fermentation with initial reducing sugar concentration of 85�156 g.L-1 for this microbial strain and substrates [18]. 
At temperature of 55�C thermophilic anaerobic digestion, microcrystalline cellulose has been used batch experiments as the sole carbon source with anaerobic digestion sludge (ADS) as the seed sludge. In this digestion, 566.0 mL.L-1 methane has produced with 14.7% degradation of the substrate in 380 hours of batch period and thermophilic degradation efficiency are achieved by  mixed culture at 55�C for 18 days via 100% cellulose degradation in 140 hours with metabolites of acetate (6770.2 mg.L-1), methanol (2674.3 mg.L-1) production. Enriched mixed culture are dominant members of the cellulose-degrading consortium of genus of some clones of Thermoanaerobacterium, Bacillus,  Tepidiphilus  and also unknown strain as confirmed by 16S rDNA analysis [19]. 
Siahe sardasht grape is reported as famous variety of grape in Iran. It has used for formation of  red grape juice concentrate industry and its pomace is a favorable medium for growth yeasts of Saccharomyces cerevesiae SC1, utilized for best ethanol production in batch fermentation  at pH 4.5, temperature 32�C.  This pomace has shown a sugar concentration of 100 g/L which is utilized with KH2PO4 better phosphorous source and (NH4)2SO4 as best nitrogen source for ethanol production [20]. Traditional fermentation has produced 7�8% (v/v) maximum ethanol concentration in 50 70	 h of batch period. And electrostatic fermentation method has shown the capability for accelerating fermentation processes by reducing the fermentation period from 70 to 20	 h with glucose and Saccharomyces cerevisiae for ethanol production. This technique has applied to the batch fermentation of 1 liter fermenting mixture  with dry yeast without pre-culture and achieved ethanol yield (14% v/v) at high gravity level (12.3% v/v) in 24	 hours with almost complete consumption of glucose. The scale-up capability of the method has shown with 2L fermenting mixture without external energy consumption due to its electrostatic nature [21]. 
Two purified fractions from grape seed extract (GSE) are reported which are GSE-M (70% monomers and 28% procyanidins) and GSE-O (21% monomers and 78% procyanidins). With utilization of above mentioned substrates, samples are collected for analysis of phenolic metabolites at different fermentation period with bacterial cell enumeration by fluorescent in situ hybridization. And promoted growth of Lactobacillus/ Enterococcus with decreased Clostridium histolyticum group has reported during fermentation.  Effects with GSE-M for Lactobacillus/Enterococcus (at 5 and 10 h) and GSE-O for C. histolyticum (at 10 h) are shown with main changes in polyphenol catabolism at first 10 h.  And correlation coefficients (P > 0.05) are not found between changes in microbial populations and precursor flavan-3-ols or microbial metabolites [22]. 
Optimization of production medium is needed for maximum metabolite yield and is done by using a wide range of techniques from classical one-factor-at-a-time to modern statistical and mathematical techniques (arti�cial neural network (ANN) or genetic algorithm (GA) etc or both). There are advantages and disadvantages are reported with applied techniques. Application of various optimization techniques in combination are reported to desirable results for media optimization in fermentation process of metabolite production. Merits and demerits of various conventional or modern optimization techniques are decided by logical selection basis for the designing of fermentation medium. Rationale for the selection of suitable optimization technique for media designing is employed during the fermentation process of various metabolite productions [23].
Fed-batch process of fermentation
Different fermentation processes are reported for metabolites production with help of effective microbial strain and batch, fed-batch and repeated fed-batch processes are utilized by Schizochytrium sp. for the effective docosahexaenoic acid (DHA)-rich microbial lipids production. Compared to other different fermentation processes, fed-batch process are reported as more efficient cultivation strategy and for this metabolite or other metabolite, different feeding strategies has used. For this metabolite, glucose concentration feed-back feeding strategy has achieved the highest fermentation results with final cell dry weight (72.37 g.L-1), total lipids content (48.86 g.L-1), DHA content (18.38 g.L-1) and DHA productivity (138.8 m g.L-1h-1. The repeated fed-batch process has shown advantages in reduction of time and cost for seed culture and inoculation in each fermentation cycles. Fermentation characteristics and lipid characterization of the repeated fed-batch process are shown as promising industrialization prospect for the production of DHA-rich microbial lipids [24]. 
Pichia pastoris is most industrially important hosts for heterologous protein production and its optimization of cultivation condition in fermentation has shown high protein productivity.  Product-specific strains are reported with many challenges which can be promoter strength, methanol utilization type and oxygen demand [25]. Strategies of genetic and process engineering has helped in optimization of codon usage and gene dosage as well as engineering of promoters, protein secretion pathways and methanol metabolic pathways  with proved beneficial to innate protein expression levels. Large-scale production of proteins has reported with high cell density fermentation with optimization of process parameters (methanol feed rate, induction temperature and specific growth rate). Regulation of the P. pastoris alcohol oxidase 1 (AOX1) promoter and the development of methanol-free systems are discussed with mixed substrate feeding. Substrate and product monitoring techniques are applied for P. pastoris, utilized for production of biodiesel and other value-added products via metabolic engineering [26] and some metabolites form fed-batch cultivation are shown in figure 2. 
Volumetric mass transfer coefficient (kLa) is reported a key parameter of fermentation and found its important in production of docosahexaenoic acid (DHA) by Schizochytrium sp. S31with glycerol substrates utilization and effects of kLa are reported on the fermentations of baffled and unbaffled flask cultures.  Fed-batch cultures are able to maintain high kLa value with effectively increased in DHA concentration, productivity and conversion yield (Yx/s, g/g). 1802 h-1  value of kLa in the fed-batch culture, DHA concentration (28.93 g.L-1) are, DHA productivity (301 m g.L-1h-1) and conversion yield Yx/s (0.44 g/g)  are reported significantly higher than previous similar studies [27].  
Optimization problem of a fed-batch fermentation process for alcohol production is reported with minimization of a time optimal global criterion. And dynamic programming methods have solved this global optimization problem via deducing a local criterion to maximum at each sampling step with non linear programming techniques. Under a few realistic constraints, the optimization problem is translated into the regulation problem of the substrate concentration in the fermentor. And optimal value is reported to a function of a certain growth model in fed-batch fermentation with implementation of quotient between measurement and optimal value under a control law with real life experiments via validation of problem transformation [28].
Heterotrophically culturing microalgae has been used for great potential of production of lipid-based biofuels (biodiesel) with renewable hydrocarbons nature and it has attracted more attention for having fast growth and high lipid yield under light limitation. High cell density culture broth can reduce downstream processing costs. And oleaginous microalga (Chlorella sorokiniana) has shwon high cell density culture with glucose [30]. It has shown the best growth performance with batch culture (pH 7.0) with ammonium. And two-stage fed-batch fermentation has also shown optimal conditions. First stage, algal biomass and productivity (24.2 g L"1 d"1)   has shown linearly and lipid content has increased from 14.5% to 38.7% in the second stage. This fermentation strategy has enhanced algal biomass (103.8 gL"1) and lipid concentrations (40.2 g.L"1). Lipid and fatty acid profiles in C. sorokiniana have accumulated a large amount of neutral lipids (92.9% of total lipids), triacylglycerols (82.8% of neutral lipids), and high contents of palmitic, oleic and linoleic acids and these have found ideal form of lipid for making biodiesel [31]. 
Fed-batch enzymatic hydrolysis has used as efficient procedure for enhancing the sugar concentration in the hydrolysate via achieving in higher conversion rates with suitable kinetic regimes. And enzymatic hydrolysis is reported as the rate limiting step in the process development for biofuel and it is hampered by low sugar concentration. High solid enzymatic saccharification can solve this problem but low rate of reaction can also be occurred [32]. Enhancement of concentration of sugars in enzymatic hydrolysate of delignified Prosopis juliflora has reported by using a fed-batch enzymatic hydrolysis approach with elevated solid load up to 20% (w/v). Kinetics of batch (80.78 g.L-1) and fed-batch (127 g.L-1) enzymatic hydrolysis is carried out using kinetic regimes for formation of .maximum sugar concentration. Fed-batch strategy has enhanced the final sugar concentration.  Saccharomyces cerevisiae has produced the ethanol (34.78 g.L-1 in batch) and 52.83 g.L-1 (in fed-batch). And model simulations have applied in higher insoluble solids in the feed with both smaller reactor volume and shorter residence time [33]. 
Oxytetracycline (OTC) is produced from Streptomyces rimosus in batch and fed-batch cultures in shake flask as well bioreactor levels (with semi-defined medium). Effect of glucose concentration has reported on OTC production and growth kinetics with optimal glucose concentration (15 g.L-1) in production medium. Higher glucose concentrations have caused higher biomass formation with less volumetric and specific antibiotic production at semi-industrial scale with 15 L bioreactor in batch culture. In bioreactor, cell growth 18% and OTC (38%) production are higher than the shake flask culture and glucose is found to totally consume after 48 h [34]. 
For the same metabolite, fed-batch experiment has used with mono-glucose feeding and it has helped overcome of carbon limitations in complete medium feeding  with increase of  OTC production. Using constant glucose feeding strategy with rate (0.33 g.L-1h-1), it has produced 1072 mg.L-1 of OTC with feeding with complete medium with 45% higher biomass. Improvement in this process has achieved by keeping the dissolved oxygen (DO) value (60% saturation) by cascading the glucose feeding pump with the DO controller and  resulted in higher antibiotic production, (1414 mg.L-1) after 108 h [35].
Continuous mode of fermentation
Continuous mode of fermentation has been carried out in an open fermentor with addition of nutrients and removal of product at a steady rate throughout the processes. It has helped in increasing product yields with continuous reaction in no idle time via reducing labour costs. It has   higher risk of contamination as its disadvantage and it has occurred due to the constant adjustments but it is feasible with inoculation of genetically stable cells. Feasibility of continuous production of penicillin antibiotic via immobilized Penicillium chrysogenum has been reported by using a three-phase magneto airlift fermentor of 2.4-L external loop airlift and transverse magnetic field. Application of the magnetic field to a bed of ferromagnetic beads has helped in hydrodynamics of the reactor and the rate of the bioconversion process inside it. It has taken period of one hundred hours  and maximum penicillin concentration ( up to 48%) are reported from magnetic field intensity (0 to 35 mT) via increased residence time of the substrate  with positive effect of the magnetic field  in effective fluid-solid interfacial area during fermentation processes [36]. 
Continuous cultivation has controlled the cell growth rate via conditions of the reactor operation. And, it is an important tool for study cell cycling, metabolic regulation and microbial product formation with most efficient operations conditions  due to not having any down time (time to clean, load, unload, prepare.). This process has helped in maintenance of high cellular activity in genetic variation. Problems in maintaining asepsis condition is big challenge for a long process in continuous cultivation and clavulanic acid production are reported by S. clavuligerus. At chemostat bioreactor culture (D=0.05 h"1), metabolic process for clavulanic acid (CA) production is reported with limitation of sources of carbon, nitrogen or phosphate  with effect on specific productivity are  shown with value of 0.32 and 3.65 mg clav g.biomass h"1 respectively [37] . 
Utilization of Streptomyces clavuligerus for CA production is reported in continuous culture with cell recycling and batch is reported without cell recycling. High cell concentration using cell recycling are reported by utilize a hollow fiber ultrafiltration module to separate cells from the filtrate broth. And without cell recycling in batch mode cultivations are found conventionally with CA concentration (470 mg.L-1) whereas highest productivity (22.2 mg.L-1. h-1) is attained in the continuous cultivation with cell recycling [38]. 
Immobilization technique with involve of agar (as matrix) has used for penicillin production by P. chrysogenum ATCC 10238 at reactor level. Some modifications in this immobilization technique have helped in decreasing the germination lag time for higher spore concentration. It has also increased porosity of gel with decreasing the mass transfer barrier. This approach has applied in production of penicillin in continuous system with immobilized agar beads within 3�4 h from the onset. It has produced penicillin up to 25 days in a steady state manner with higher productivity (2.5 times or more) with stability compared to productivity of the corresponding batch fermentation [39]. 
Production of ethanol has designed and tested for continuously process with a cell-recycling two-tank system. This has composed of two fermenters and each is equipped with a settler for recycling flocculent yeast. Enhanced productivity of ethanol is reported from sucrose at high cell-recycling (r = 0.8�0.9 h"1) at optimal dilution (0.48 h"1) rates with several advantages (high cell concentration in the fermenters, relief of substrate and product inhibition) in the two-tank cell-recycling system [40].  Increased recycling ratios have caused an increase in biomass concentration and product concentration in the tank. The ethanol productivity is increased with the dilution rate (higher dilution rates help in increasing non-conversion amounts of sugar). Sugar feed concentration of 160 g.L-1 (at r = 0.9 and 0.2 h"1) in continuous fermentation has shown highest productivity with less than 2% of the unconverted sugar in the product steam. Cell recycling ratios has helped to a achieve productivity in range of 6.9 7.5 g.L-1.h"1 with feeding concentrations of 80 200 g.L-1. But batch fermentation at these sugar concentrations is shown the productivities of 3.85 4.48 g.L-1.h"1 [41].  




Conclusions
Optimization of multiple variables and constraints has helped in solving of fermentation process problems via development of high-performance, robust, cost-effective bioprocesses for metabolites. Statistical modeling strategies are used as innovative solutions for fermentation optimization and borrowing, component swapping, biological mimicry, one-factor-at-a-time and factorial design reported with Plackett and Burman design, central composite design, response surface methodology, artificial neural network, and genetic algorithms for optimization of fermentation parameters. Formation, concentration and yield of a particular product are found to maximum value in fermentation optimization. Temperature, pH, hydrolytic enzyme volume, and fermentative microbe�s inoculums volume are reported as main process parameters of fermentation process in ethanol production. Pichia pastoris has helped in production of bio-pharmaceutically important recombinant products / industrial enzymes and design of expression vectors, optimization of gene copy number, co-expression of secretory proteins (chaperones), engineering of glycosylation and secretory pathways are found to optimize for maximum concentration.  Maximum specific growth rate (�max), biomass to substrate yield (Yx/s) and speci�c maintenance rate (ms)) of microbial strain are shown the crucial role in formation of recombinant protein or any other metabolites. Fermentation processes for metabolites production are found different mode which are batch, fed-batch and continuous mode and its selection will decide on basis of metabolite and microbial strain metabolic pathways.
Acknowledgement: 
In this paper contribution, only author (Rajesh K. Srivastava) has taken all the responsibility for designing and writing this manuscript. There is no people and grant involved. But I am thankful to Gitam Institute of Technology and Management (GITAM) (Deemed to be University), Visakhatpatnam, A. P. India for providing me the time and mental support.
Abbreviations:
ADS: Anaerobic digestion sludge; ANN: Artificial neural network; CA: Clavulanic acid; D : Dilution rate in time inverse; DHA: Docosahexaenoic acid; DO: Dissolved oxygen; DOE: Design of experiment; g.L-1: Gram per litre; GA: Genetic algorithm; GAP : Glyceraldehyde 3-phosphate; GSE: Grape seed extract; kLa: Volumetric mass transfer coefficient;  ms: speci�c maintenance rate; mT: milli.tesla; OTC: Oxytetracycline;  OVAT: One variable at a time; P: Correlation coefficients;   PAOX1: Alcohol oxidase 1�promoter;  q: Speci�c formation rates; r: rate of feed; R: Regression coefficients; RMS: Response surface methodology; SMs: Secondary metabolites; SSF: Solid state fermentation;  U.m.L-1: Unit milli per litre; Yx/s : Biomass to substrate yield; �: Speci�c growth rates; �max: Maximum specific growth rate; 
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Figure 1 Some reported fermentative parameters needs to optimize for maximization of metabolites in different modes of bioreactors







Figure 2 Fed-batch mode of bioreactor utilized for maximization of metabolites synthesis










Table1 Metabolites from different fermentation mode with their parameters
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$d�a$gd5$�hd�^�ha$gd5Metabolites/ products ParametersReferencesBatch mode of Streptomyces griseusHigher trypsin production with amidase activity (3 fold) Optimal designed of signal peptide[4]Batch mode for yeast Kluyveromyces sp from sugarcane bagasse pith hydrolysateCellulosic ethanol production (17.44 g.L-1) with 88% yield of the theoretical  and specific productivity (0.36 g.L-1h-1)  Optimal temperature, pH, hydrolytic enzyme volume, microbe�s inoculums volume[6, 29]Batch mode of S. coelicolor A3(2) fermentationSecondary (antibiotic) productionEffect of phosphate and L-glutamate depletion[16, 17]Batch mode of Pichia pastorisRecombinant products / industrial enzymesExpression vectors, optimization of gene copy number, co-expression of secretory proteins [9]Batch fermentation of immobilized Saccharomyces cerevisiae CICC 1308Ethanol production from sweet sorghum cultivar stalk juiceEffect of initial sugar concentration and maximum specific growth rate[18]Batch fermentation of individual to enriched mixed culture566.0 to 2674.3 mg.L-1 methane anaerobic digestion sludge (ADS) at 55�C  with 100% cellulose degradation in 140 hCellulose-degrading consortium of genus of microbes by 16S r DNA analysis[19]Saccharomyces cerevesiae SC1 in batch fermentationEthanol production from red grape juice pomaceAt pH 4.5, temperature 32�C[20]Saccharomyces cerevisiae in batch fermentation of 1 liter fermenterEthanol yield (14% v/v) at high gravity level (12.3% v/v)Consumption pattern of glucose in less time by electrostatic fermentation method[21]Repeated fed-batch process for reduction of time and cost for seed culture and inoculation  DHA content (18.38 g.L-1) and DHA productivity (138.8 mgL-1 h-1)Glucose concentration feed-back feeding strategy
[24]Pichia pastoris in fed-batch fermentationHigh protein productivity  via optimization of cultivation condition suchPromoter strength, methanol utilization type and oxygen demand[25]Schizochytrium sp. S31 from fed-batch processProduction of docosahexaenoic acid (DHA)  of 28.93 g.L-1Glycerol substrates utilization and effects of kLa 1802 h-1 value[27]Two-stage fed-batch fermentationC. sorokiniana accumulated a large amount of neutral lipids (92.9%), triacylglycerols (82.8%) and high contents of palmitic, oleic and linoleic acids for biofuelAlgal biomass and productivity at optimal conditions[31]Batch and fed-batch with different kineticSaccharomyces cerevisiae has produced the ethanol (34.78 g.L-1- batch) and 52.83 g.L-1 (fed-batch)Change of kinetics for enzymatic hydrolysis for sugar concentration in batch (80.78 g.L-1) and fed-batch (127 g.L-1)[33]Batch and fed-batch cultures in shake flask and bioreactor levelsOxytetracycline (OTC) produced from Streptomyces rimosusin in semi-defined medium. In bioreactor, cell growth (18%) and OTC (38%) production are higher than the shake flask culture in batch. In fed-batch, higher antibiotic production (1414 mg.L-1) after 108 hOTC production, growth kinetics with optimal glucose concentration and constant glucose feeding strategy with rate[35] Continuous mode of fermentationImmobilized Penicillium chrysogenum with enhanced penicillin concentration up to 48% .Three-phase magneto airlift fermentor of 2.4-L external loop airlift and transverse magnetic field intensity (0 to 35 mT).[36]








Dr. Rajesh Kumar Srivastava (Assistant Professor),              Date: October 07, 2018
Department of Biotechnology, 
GITAM Institute of Technology, 
GITAM University, Gandhi Nagar Campus, 
 Rushikonda, Visakhapatnam - 530 045, (A.P.), 
India. Mobile: +91 9703842963;
 E-mail:  HYPERLINK "mailto:rajeshksrivastava73@yahoo.co.in" rajeshksrivastava73@yahoo.co.in 

To 	
Editor-in-Chief (Dr. Ajay Kumar Ray)
Journal of Biochemical Engineering & Bioprocess Technology
SciTechnol, Department of Chemical and Biochemical Engineering
The University of Western Ontario
USA E-Mail: aray@eng.uwo.ca 
Email:  HYPERLINK "mailto:gloria_gg@rediffmail.com" \t "_blank" gloria_gg@rediffmail.com

Subject: Submission of review manuscript entitled �Importance of optimization of fermentative parameters for enhanced metabolite� to Journal of Biochemical Engineering & Bioprocess Technology
Respected Sir,
Please find attached a copy of the review manuscript entitled �Importance of optimization of fermentative parameters for enhanced metabolite� to Journal of Biochemical Engineering & Bioprocess Technology  along with separate title, abstract, methods, result, conclusion, table, legend to figure, line figures, references in word format and black white figure in normal text word format and compatible to the journal style for the publication in your esteemed journal " Journal of Biochemical Engineering & Bioprocess Technology  �.  The proposed manuscript is written by only Dr. Rajesh K. Srivastava and it is based on fermentation processes and metabolites are produced from different mode of fermentation process. It needs the optimization of fermentative parameters, which can help in maximization of metabolites. There are two figures and one table in this manuscript. I hope this manuscript will enhance the quality of this journal. I have duly read the terms and condition of the journal. I have already taken permission from Dr. Gloria GG, Managing Editor for submission of proposal publication of Review Article in Journal of Biochemical Engineering & Bioprocess Technology.
 So, I am really very much thankful to Dr. Gloria GG, Managing Editor who has encouraged me with his suggestion to prepare this review manuscript without any article processing charge. 
I am confident that the manuscript would find space in your esteemed journal �Journal of Biochemical Engineering & Bioprocess Technology� after being reviewed properly by the subject expert.
Thanking you with best of regards,  
Sincerely yours 

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Rajesh Kumar Srivastava,
Thanks and regards
Dr Rajesh Kumar Srivastava, Gitam University, India

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