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      Strategies for Fermentation Medium Optimization: An In-Depth Review.

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          Abstract

          Optimization of production medium is required to maximize the metabolite yield. This can be achieved by using a wide range of techniques from classical "one-factor-at-a-time" to modern statistical and mathematical techniques, viz. artificial neural network (ANN), genetic algorithm (GA) etc. Every technique comes with its own advantages and disadvantages, and despite drawbacks some techniques are applied to obtain best results. Use of various optimization techniques in combination also provides the desirable results. In this article an attempt has been made to review the currently used media optimization techniques applied during fermentation process of metabolite production. Comparative analysis of the merits and demerits of various conventional as well as modern optimization techniques have been done and logical selection basis for the designing of fermentation medium has been given in the present review. Overall, this review will provide the rationale for the selection of suitable optimization technique for media designing employed during the fermentation process of metabolite production.

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          Most cited references65

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          Box-Behnken design: an alternative for the optimization of analytical methods.

          The present paper describes fundamentals, advantages and limitations of the Box-Behnken design (BBD) for the optimization of analytical methods. It establishes also a comparison between this design and composite central, three-level full factorial and Doehlert designs. A detailed study on factors and responses involved during the optimization of analytical systems is also presented. Functions developed for calculation of multiple responses are discussed, including the desirability function, which was proposed by Derringer and Suich in 1980. Concept and evaluation of robustness of analytical methods are also discussed. Finally, descriptions of applications of this technique for optimization of analytical methods are presented.
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            Carbon source regulation of antibiotic production.

            Antibiotics are low-molecular-mass products of secondary metabolism, nonessential for the growth of producing organisms, but very important for human health. They have unusual structures and are most often formed during the late growth phase of the producing microorganisms. Their production arises from intracellular intermediates, which are condensed into more complex structures through defined biochemical pathways. Their synthesis can be influenced by manipulating the type and concentration of nutrients formulating the culture media. Among them, the effect of the carbon source has been the subject of continuous studies for both industry and research groups. Glucose and other carbohydrates have been reported to interfere with antibiotic synthesis and this effect depends on the rapid utilization of the preferred carbon source. Different mechanisms have been described in bacteria and fungi to explain the negative effects of carbon catabolites on antibiotic production. They show important differences depending on the microbe being considered. Their understanding and manipulation have been useful for both perfecting fermentation conditions to produce anti-infectives and for strain improvement. To improve the production of antibiotics, carbon source repression can be decreased or abolished by mutations resulting in antimetabolite resistance. Enzymes reported as regulated by the carbon source have been used as targets for strain improvement. During the last few years, important advances have been reported elucidating the essential aspects of carbon source regulation on antibiotic production at biochemical and molecular levels. The aim of this review is to describe these advances, giving special emphasis to those reported for the genus Streptomyces.
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              A study of oxygen transfer in shake flasks using a non-invasive oxygen sensor.

              We describe a study of oxygen transfer in shake flasks using a non-invasive optical sensor. This study investigates the effect of different plugs, presence of baffles, and the type of media on the dissolved oxygen profiles during Escherichia coli fermentation. We measured the volumetric mass transfer coefficient (k(L)a) under various conditions and also the resistances of the various plugs. Finally, we compared shake flask k(L)a with that from a stirred tank fermentor. By matching k(L)a's we were able to obtain similar growth and recombinant protein product formation kinetics in both a fermentor and a shake flask. These results provide a quantitative comparison of fermentations in a shake flask vs. a bench-scale fermentor and should be valuable in guiding scale-up efforts. Copyright 2003 Wiley Periodicals, Inc.
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                Author and article information

                Journal
                Front Microbiol
                Frontiers in microbiology
                Frontiers Media SA
                1664-302X
                1664-302X
                2016
                : 7
                Affiliations
                [1 ] Microbiology Division, Council of Scientific and Industrial Research - Central Drug Research InstituteLucknow, India; Department of Biotechnology, Institute of Engineering and TechnologyLucknow, India.
                [2 ] Department of Biosciences, Jamia Millia Islamia (A Central University)New Delhi, India; Research and Scientific Studies Unit, College of Nursing and Allied Health Sciences, Jazan UniversityJazan, Saudi Arabia.
                [3 ] Microbiology Division, Council of Scientific and Industrial Research - Central Drug Research Institute Lucknow, India.
                [4 ] Fermentation Technology Division, Council of Scientific and Industrial Research - Central Drug Research InstituteLucknow, India; Department of Biotechnology, Shri Ramswaroop Memorial UniversityLucknow, India.
                Article
                10.3389/fmicb.2016.02087
                5216682
                28111566
                54fa26d1-614d-4ff8-a438-2eedee779165
                History

                ANN,OFAT,RSM,genetic algorithm,media optimization
                ANN, OFAT, RSM, genetic algorithm, media optimization

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