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RISS 인기검색어
- 검색키워드
- 저자 : Senthilkumar Sivaprakasam (검색결과 5 건)
- 무료
- 기관 내 무료
- 유료
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Sivaprakasam, Senthilkumar,Mahadevan, Surianarayanan,Bhattacharya, Madhuchhanda Korean Society for Biotechnology and Bioengineerin 2007 Biotechnology and Bioprocess Engineering Vol.12 No.4
Biocalorimetry has proved to be a useful tool for scale up and control of bioreactors. The findings reported here are fundamental data required for scale up and control of a reactor for the treatment of saline tannery wastewater. The study deals with biokinetics of a halo-tolerant bacteria Pseudomonas aeruginosa isolated from tannery saline wastewater (soak liquor). Batch experiments were performed in a biocalorimeter and the isolated strain was grown in a glucose-limited mineral salt medium (MSM) at optimized growth conditions. Tessier model is found to fit well for the growth of P. aeruginosa in biocalorimeter. Biokinetic constants are evaluated and simulation is done to validate experimental results with theoretical values. Respirogram and heat profiles are seen to follow the biomass growth curve. Oxycalorific coefficient is validated with the theoretical values and those noticed in the published literature. There is a good correlation between experimentally determined heat yields and the theoretical values predicted by elemental and enthalpy balances. The heat yield and biomass yield values indicated the behavior of the isolated organism in a substrate-limited well defined growth media (MSM).
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Surianarayanan Mahadevan,Senthilkumar Sivaprakasam,Madhuchhanda Bhattacharya 한국생물공학회 2007 Biotechnology and Bioprocess Engineering Vol.12 No.4
Biocalorimetry has proved to be a useful tool for scale up and control of bioreactors. The findings reported here are fundamental data required for scale up and control of a reactor for the treatment of saline tannery wastewater. The study deals with biokinetics of a halo-tolerant bacteria Pseudomonas aeruginosa isolated from tannery saline wastewater (soak liquor). Batch experiments were performed in a biocalorimeter and the isolated strain was grown in a glucose-limited mineral salt medium (MSM) at optimized growth conditions. Tessier model is found to fit well for the growth of P. aeruginosa in biocalorimeter. Biokinetic constants are evaluated and simulation is done to validate experimental results with theoretical values. Respirogram and heat profiles are seen to follow the biomass growth curve. Oxycalorific coefficient is validated with the theoretical values and those noticed in the published literature. There is a good correlation between experimentally determined heat yields and the theoretical values predicted by elemental and enthalpy balances. The heat yield and biomass yield values indicated the behavior of the isolated organism in a substrate-limited well defined growth media (MSM).
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Surianarayanan Mahadevan,Balaji Dhandapani,Senthilkumar Sivaprakasam,Asit Baran Mandal 한국생물공학회 2010 Biotechnology and Bioprocess Engineering Vol.15 No.4
Biocalorimetry has proved to be an efficient tool for studying the energetics involved in several biochemical reactions. In this study, biocalorimetry was employed to simultaneously analyze biokinetics and bioenergetics involved during cultivation of a salt tolerant Pseudomonas aeruginosa for the production of alkaline protease. Batch experiments were performed in a bench scale biocalorimeter for alkaline protease production by P. aeruginosa using optimized process conditions. Tessier’s double substrate growth model was found to provide a good fit for the growth of P. aeruginosa in the biocalorimeter,and the biokinetic parameters were estimated. The heat flow profile resulting from metabolic activity of P. aeruginosa was shown to accurately depict both the kinetics of cell growth and protease production. Biokinetic and bioenergetic analysis on the growth of P. aeruginosa revealed that peptone is preferentially used as the substrate for its intracellular activities and glycerol acts as an energy source for its growth metabolism.
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Metabolic Engineering of Bacillus megaterium for the Production of β-alanine
Subbi Rami Reddy Tadi,Ganesh Nehru,Senthilkumar Sivaprakasam 한국생물공학회 2022 Biotechnology and Bioprocess Engineering Vol.27 No.6
The safe production of β-alanine (BA) has attracted significant attention by its multifaceted applications in pharmaceutical, polymer, and nutrition. The extant highyielding chemical and enzymatic methods of BA synthesis are handicapped by raw materials derived from petroleum resources, harsh reaction conditions, and catalyst instability. Consequently, this study explored a safe and alternative route via microbial fermentation, utilizing metabolic engineering of Bacillus megaterium to produce BA. The Bacillus subtilis panD gene (encoding L-aspartate-α-decarboxylase) was codon-optimized and overexpressed, which yielded 0.13 ± 0.05 g/L BA. Aspartate ammonia-lyase (AspA) and aspartate aminotransferase (AspB) based pathways were examined for BA production from glucose. NADHdependent glutamate dehydrogenase (gdh) was used to regenerate the cofactor NAD+ in the pathway with AspB. Dosing of the rate liming panD showed a positive effect on BA production. The BA titer was further increased to 1.4 ± 0.06 g/L by over-expression of phosphoenolpyruvate carboxylase (PPC). Optimizing (NH4)2SO4, Pyridoxine, and NaHCO3 allowed the production of 2.41 ± 0.15 g/L BA. Fed-batch fermentation of the final strain allowed 17.60 ± 0.13 g/L BA production in 22 h. The present study has effectively unlocked the potential of engineering the B. megaterium for the sustainable production of the other ASP (L-aspartic acid) and BA-derived products at a large scale.
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Sivakumar Rathinavelu,Satya Sai Pavan,Senthilkumar Sivaprakasam 한국생물공학회 2023 Biotechnology and Bioprocess Engineering Vol.28 No.1
Hyaluronic acid (HA), a glycosaminoglycan polymer, is widely used in the biomedical and cosmetic industries. Due to highly viscous nature of the HA fermentation broth, it is difficult to capture the dynamics of its bioprocess with physical sensors in real-time. The goal of this study was to track non-invasively the state variables involved in HA production process and deducing the critical process parameters based on the recorded process inputs. The framework employed in this study is based on a hybrid model that predicts HA and biomass concentration using online bioreactor data (pH, DO%, %CO2 evolved, feed rate, and agitation rate) to ensure real-time tracking of HA bioprocess dynamics. A HA fermentation dataset with data from historical batches and freshly performed fedbatch runs for various specific growth rate set-points (μsp) was created. The dataset was used to train the hybrid model, which was then used to predict biomass and HA concentration for test runs, with a mean squared error of prediction ranging from 0.018 to 0.049 (g/L)2. Furthermore, recurrent neural networks were evaluated in forecasting the specific growth rate (μ) and HA productivity rate (qHA) to observe the desired process trajectory. The current study addressed the scope of application of hybrid model based soft-sensor to predict the trend of process parameters of HA fermentation.
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