Kinetic modelling, production optimization, functional characterization and phyto-toxicity evaluation of biosurfactant derived from crude oil biodegrading Pseudomonas sp. IITISM 19

Ray, Madhurya; Kumar, Vipin; Banerjee, Chiranjib

doi:10.1016/j.jece.2022.107190

Cited by 10 publications

(4 citation statements)

References 64 publications

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“…On the other hand, unstructured kinetic models generally contain few parameters, which, from a computational perspective, is usually advantageous. At present, a significant portion of recent studies concern bioethanol production [ 38 , 39 , 40 ], biosurfactant production [ 41 , 42 ], bacterial and fungal biomass production [ 43 , 44 ], as well as microalgal growth [ 45 , 46 , 47 ].…”

Section: Methods and Applications Of Mechanistic Modelingmentioning

confidence: 99%

Optimization and Scale-Up of Fermentation Processes Driven by Models

Wang

Yang

et al. 2022

Bioengineering

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In the era of sustainable development, the use of cell factories to produce various compounds by fermentation has attracted extensive attention; however, industrial fermentation requires not only efficient production strains, but also suitable extracellular conditions and medium components, as well as scaling-up. In this regard, the use of biological models has received much attention, and this review will provide guidance for the rapid selection of biological models. This paper first introduces two mechanistic modeling methods, kinetic modeling and constraint-based modeling (CBM), and generalizes their applications in practice. Next, we review data-driven modeling based on machine learning (ML), and highlight the application scope of different learning algorithms. The combined use of ML and CBM for constructing hybrid models is further discussed. At the end, we also discuss the recent strategies for predicting bioreactor scale-up and culture behavior through a combination of biological models and computational fluid dynamics (CFD) models.

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Section: Methods and Applications Of Mechanistic Modelingmentioning

confidence: 99%

Optimization and Scale-Up of Fermentation Processes Driven by Models

Wang

Yang

et al. 2022

Bioengineering

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“…Effects of pH, salt concentrations, temperature and dilution on surface tension of biosurfactant was investigated by one factor at a time strategy (OFAT) [31]. pH was adjusted in the range of 4.0-12.0 with HCl and NaOH to evaluate the effect of pH on growth.…”

Section: Surface Activity Assaysmentioning

confidence: 99%

The metabolic and physiological responses to spaceflight of a lipopeptide- producing Bacillus subtilis

Qin,

Liu,

Liu

et al. 2024

Preprint

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Background The outer space is an extreme environment that has attracted continuous interest in microbial adaptation and safety, due to its high mutagenesis frequency and genetic variability. To date, several studies have assessed the impact of the space environment on the microbiomes and microorganisms. While the survival of Bacillus subtilis after spaceflight is well established, how the phenotype and metabolic function of B. subtilis respond to space stress is rarely reported. Results In this study, we performed a space flight of the B. subtilis TD7 strain facilitated by the launch project of the Xinyidai Zairen Feichuan-Shiyan Chuan, and compared the strains after spaceflight with the wild-type in terms of their growth, morphology, biofilm formation and secondary metabolism. The spaceflight strain exhibited slower growth, higher cell density, different morphology and decreased biofilm formation. Importantly, a decrease in the lipopeptide production was observed after spaceflight. Thus, we used a multi-omics approach to uncover the molecular mechanisms underlying the changeable secondary metabolism. A total of 14 gene clusters for secondary metabolite biosynthesis were identified in both the wild-type strain and spaceflight strains through whole-genome sequencing, including nonribosomal peptide synthetase. The comparative transcriptome revealed 997 differentially expressed genes which involved in the TCA cycle, fatty acid degradation, amino acid biosynthesis, and quorum sensing systems. The differential expression analysis of 26 lipopeptide-related DEGs further elucidated the relationship between the space environment and the regulation of secondary metabolism. Conclusion Our study is the first study to provide new insight into the behaviors, metabolic functions and adaptation mechanisms of B. subtilis in response to spaceflight. This knowledge could contribute to a better understanding of the relationship between the space environment and microbial adaption mechanisms.

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“…Kinetic growth studies of microorganisms are crucial for understanding and optimizing fermentations and other biological processes. These studies provide insights into growth patterns, metabolic activities, population dynamics, nutrient utilization, and product formation [ [1] , [2] , [3] , [4] ]. They are especially important for applications in the fermentation process, i.e., bioremediation [ 1 ], biodegradation of pollutants [ 2 , 3 ], and biogas production [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Electromagnetic fields effects on microbial growth in cocoa fermentation: A controlled experimental approach using established growth models

Guzmán-Armenteros,

Villacís-Chiriboga,

Guerra

et al. 2024

Heliyon

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Kinetic modelling, production optimization, functional characterization and phyto-toxicity evaluation of biosurfactant derived from crude oil biodegrading Pseudomonas sp. IITISM 19

Cited by 10 publications

References 64 publications

Optimization and Scale-Up of Fermentation Processes Driven by Models

Optimization and Scale-Up of Fermentation Processes Driven by Models

The metabolic and physiological responses to spaceflight of a lipopeptide- producing Bacillus subtilis

Electromagnetic fields effects on microbial growth in cocoa fermentation: A controlled experimental approach using established growth models

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