Acta Scientific Nutritional Health (ASNH)(ISSN: 2582-1423)

Review Article Volume 9 Issue 1

Ab Initio Whole Cell Kinetic Model of Bifidobacterium bifidum BGN4 (bbfMA24)

Madhunisha Arivazhagan1,2, Ashmitha Senthilkumar1,2, Keng Yao Yeo1,2, Tanisha Saisudhanbabu1,2, Minh Anh Le1,2, Travina BS Wong1,2, Victor R Lukianto1,2 and Maurice HT Ling1,2,3*

1 School of Life Sciences, Management Development Institute of Singapore, Singapore
2Department of Applied Sciences, Northumbria University, United Kingdom
3HOHY PTE LTD, Singapore

*Corresponding Author: Maurice HT Ling, School of Life Sciences, Management Development Institute of Singapore, Singapore.

Received: December 13, 2024; Published: December 27, 2024

Abstract

Bifidobacterium bifidum is a common probiotic in human gut and has been shown to be beneficial in many disorders. B. bifidum BGN4 is recognised by US FDA as “generally recognised as safe” for use in infant formulations among other food applications, leading to potential engineered probiotics applications. Mathematical kinetic models provide time-course profile of modelled metabolites, which can be used to guide metabolic engineering approaches. However, there is no kinetic model of B. bifidum to-date. In this study, we present a whole cell simulatable kinetic model of B. bifidum BGN4, bbfMA24, constructed using ab initio approach by identifying enzymes from its published genome. The resulting model consists of 236 metabolites, 68 enzymes with corresponding transcriptions and translations, and 162 enzymatic reactions; which can be a baseline model for incorporating other cellular and growth processes, or as a system to examine cellular resource allocations necessary for engineering.

Keywords: : Bifidobacterium bifidum; bbfMA24

References

  1. Turroni F., et al. “Bifidobacterium bifidum as an Example of a Specialized Human Gut Commensal”. Frontiers in Microbiology 5 (2014): 437.
  2. Mitsuoka T. “Bifidobacteria and Their Role in Human Health”. Journal of Industrial Microbiology4 (1990): 263-267.
  3. Goodoory VC and Ford AC. “Antibiotics and Probiotics for Irritable Bowel Syndrome”. Drugs8 (2023): 687-699.
  4. Ruiz-Sánchez C., et al. “Evaluation of the Efficacy of Probiotics as Treatment in Irritable Bowel Syndrome”. Endocrinologia, Diabetes Y Nutricion1 (2024): 19-30.
  5. Ku S., et al. “Review on Bifidobacterium bifidum BGN4: Functionality and Nutraceutical Applications as a Probiotic Microorganism”. International Journal of Molecular Sciences9 (2016): 1544.
  6. Lu J., et al. “Probiotics and Non-Alcoholic Fatty Liver Disease: Unveiling the Mechanisms of Lactobacillus plantarum and Bifidobacterium bifidum in Modulating Lipid Metabolism, Inflammation, and Intestinal Barrier Integrity”. Foods (Basel, Switzerland)18 (2024): 2992.
  7. Scriven M., et al. “Neuropsychiatric Disorders: Influence of Gut Microbe to Brain Signalling”. Diseases (Basel, Switzerland)3 (2018): 78.
  8. Ojha S., et al. “Probiotics for Neurodegenerative Diseases: A Systemic Review”. Microorganisms4 (2023): 1083.
  9. Kang S., et al. “A Recombinant Bifidobacterium bifidum BGN4 Strain Expressing the Streptococcal Superoxide Dismutase Gene Ameliorates Inflammatory Bowel Disease”. Microbial Cell Factories1 (2022): 113.
  10. Zuo F., et al. “Engineer Probiotic Bifidobacteria for Food and Biomedical Applications - Current Status and Future Prospective”. Biotechnology Advances 45 (2020): 107654.
  11. Nguyen H-T., et al. “Biochemical Engineering Approaches for Increasing Viability and Functionality of Probiotic Bacteria”. International Journal of Molecular Sciences6 (2016): 867.
  12. Bodnár M., et al. “Synthesis of Galacto-Oligosaccharides in Milk by Using Bifidobacterium bifidum β-Galactosidases (Saphera 2600L and Nola Fit 5500) Immobilized on Chitosan Beads”. Food and Bioprocess Technology7 (2024): 1-20.
  13. Khanijou JK., et al. “Metabolomics and Modelling Approaches for Systems Metabolic Engineering”. Metabolic Engineering Communications 15 (2022): e00209.
  14. Gudmundsson S and Nogales J. “Recent Advances in Model-Assisted Metabolic Engineering”. Current Opinion in Systems Biology 28 (2021): 100392.
  15. Strutz J., et al. “Metabolic Kinetic Modeling Provides Insight into Complex Biological Questions, but Hurdles Remain”. Current Opinion in Biotechnology 59 (2019): 24-30.
  16. Wang R-S. “Ordinary Differential Equation (ODE), Model”. Encyclopedia of Systems Biology, eds Dubitzky W, Wolkenhauer O, Cho K-H, Yokota H (Springer New York, New York, NY) (2013): 1606-1608.
  17. Kim OD., et al. “A Review of Dynamic Modeling Approaches and Their Application in Computational Strain Optimization for Metabolic Engineering”. Frontiers in Microbiology 9 (2018): 1690.
  18. Cho JL and Ling MH. “Adaptation of Whole Cell Kinetic Model Template, UniKin1, to Escherichia coli Whole Cell Kinetic Model, ecoJC20”. EC Microbiology2 (2021): 254-260.
  19. Choudhury S., et al. “Reconstructing Kinetic Models for Dynamical Studies of Metabolism using Generative Adversarial Networks. Nature Machine Intelligence8 (2022): 710-719.
  20. Foster CJ., et al. “Building Kinetic Models for Metabolic Engineering”. Current Opinion in Biotechnology 67 (2021): 35-41.
  21. Yu DS., et al. “Complete Genome Sequence of the Probiotic Bacterium Bifidobacterium bifidum Strain BGN4”. Journal of Bacteriology17 (2012): 4757-4758.
  22. Okuda S., et al. “KEGG Atlas mapping for global analysis of metabolic pathways”. Nucleic Acids Research 36 (2008): W423-W426.
  23. Kwan ZJ., et al. “Ab Initio Whole Cell Kinetic Model of Stutzerimonas balearica DSM 6083 (pbmKZJ23)”. Acta Scientific Microbiology2 (2024): 28-31.
  24. Müller-Hill B. “The lac Operon: A Short History of a Genetic Paradigm (Berlin, Germany)”. (1996).
  25. Churchward G., et al. “Transcription in Bacteria at Different DNA Concentrations”. Journal of Bacteriology2 (1982): 572-581.
  26. Gray WJ and Midgley JE. “The Control of Ribonucleic Acid Synthesis in Bacteria. The Synthesis and Stability of Ribonucleic Acid in Rifampicin-Inhibited Cultures of Escherichia coli”. The Biochemical Journal2 (1971): 161-169.
  27. Kubitschek HE. “Cell Volume Increase in Escherichia coli After Shifts to Richer Media”. Journal of Bacteriology1 (1990): 94-101.
  28. Hu P., et al. “Global Functional Atlas of Escherichia coli Encompassing Previously Uncharacterized Proteins”. PLoS Biology4 (2009): e96.
  29. So L-H., et al. “General Properties of Transcriptional Time Series in Escherichia coli”. Nature Genetics6 (2011): 554-560.
  30. Schwanhäusser B., et al. “Corrigendum: Global Quantification of Mammalian Gene Expression Control”. Nature7439 (2013): 126-127.
  31. Maurizi MR. “Proteases and Protein Degradation in Escherichia coli”. Experientia2 (1992): 178-201.
  32. Murthy MV., et al. “UniKin1: A Universal, Non-Species-Specific Whole Cell Kinetic Model”. Acta Scientific Microbiology10 (2020): 04-08.
  33. Bar-Even A., et al. “The Moderately Efficient Enzyme: Evolutionary and Physicochemical Trends Shaping Enzyme Parameters”. Biochemistry21 (2011): 4402-4410.
  34. Ling MH. “AdvanceSyn Toolkit: An Open Source Suite for Model Development and Analysis in Biological Engineering”. MOJ Proteomics and Bioinformatics4 (2020): 83‒86.
  35. Yong B. “The Comparison of Fourth Order Runge-Kutta and Homotopy Analysis Method for Solving Three Basic Epidemic Models”. Journal of Physics: Conference Series 1317:012020 (2019).
  36. Ling MH. “COPADS IV: Fixed Time-Step ODE Solvers for a System of Equations Implemented as a Set of Python Functions”. Advances in Computer Science: an International Journal3 (2016): 5-11.
  37. Ahn-Horst TA., et al. “An Expanded Whole-Cell Model of E. coli Links Cellular Physiology with Mechanisms of Growth Rate Control”. npj Systems Biology and Applications1 (2022): 30.
  38. Chagas M da S., et al. “Boolean Model of the Gene Regulatory Network of Pseudomonas aeruginosa CCBH4851”. Frontiers in Microbiology 14 (2023): 1274740.
  39. Hao T., et al. “Reconstruction of Metabolic-Protein Interaction Integrated Network of Eriocheir sinensis and Analysis of Ecdysone Synthesis”. Genes4 (2024): 410.
  40. Thornburg ZR., et al. “Fundamental Behaviors Emerge From Simulations of a Living Minimal Cell”. Cell2 (2022): 345-360.e28.
  41. Bianchi DM., et al. “Toward the Complete Functional Characterization of a Minimal Bacterial Proteome. The Journal of Physical Chemistry B36 (2022): 6820-6834.
  42. Sun G., et al. “Cross-Evaluation of E. coli’s Operon Structures via a Whole-Cell Model Suggests Alternative Cellular Benefits for Low- Versus High-Expressing Operons”. Cell Systems3 (2024): 227-245.e7.
  43. Choi H and Covert MW. “Whole-cell modeling of E. coli confirms that in vitro tRNA aminoacylation measurements are insufficient to support cell growth and predicts a positive feedback mechanism regulating arginine biosynthesis”. Nucleic Acids Research12 (2023): 5911-5930.

Citation

Citation: Maurice HT Ling., et al. “Ab Initio Whole Cell Kinetic Model of Bifidobacterium bifidum BGN4 (bbfMA24)". Acta Scientific Nutritional Health 9.1 (2025): 42-45.

Copyright

Copyright: © 2025 Maurice HT Ling., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.




Metrics

Acceptance rate30%
Acceptance to publication20-30 days
Impact Factor1.316

Indexed In





News and Events


  • Certification for Review
    Acta Scientific certifies the Editors/reviewers for their review done towards the assigned articles of the respective journals.
  • Last Date to Submit Articles
    Journal accepting all the types of Articles for upcoing issue by on/before July 30, 2025
  • Issue of Publication Certificate
    Publication Certificate will be issued to the author after Online publication of an Article
  • Best Article
    One Article will be selected as Best Article from all the Articles of the corresponding Issue, once the issue released, and honored with A Best Article Certificate

Contact US