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

Research Article Volume 10 Issue 2

Ab Initio Whole Cell Kinetic Model of Streptococcus thermophilus STH_CIRM_65 (stheVS26)

Sragvi Verma 1,2 , Diya Nanthakumarvani 1,2 , Leesha Haarshiny Perumal 1,2 , Atoshi Abirami RajKumar 1,2 , Cheryl Kai Ning Kang1,2 , Shafeeqa Abul-Hasan1,2 and Maurice HT Ling2,3,4 *

1 Department of Applied Sciences, Northumbria University, United Kingdom
2 Management Development Institute of Singapore, Singapore
3 Newcastle Australia Institute of Higher Education, University of Newcastle, Australia
4 HOHY PTE LTD, Singapore

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

Received: December 29, 2025; Published: January 31, 2026

Abstract

Streptococcus thermophilus is a lactic acid bacterium, which is used in yogurt production, and known for its ability to produce folate, exopolysaccharides; thus, making it a highly valuable organism for food biotechnology and probiotic applications. Mathematical kinetic models, which extend beyond steady-state predictions in genome-scale models, are useful tools for directing metabolic engineering efforts. Although a genome-scale models of S. thermophilus is available, a comprehensive whole-cell kinetic model is lacking. In this study, we describe a simulatable kinetic model of S. thermophilus STH_CIRM_65, constructed in an ab initio fashion by locating enzymes from the genome sequence and mapping them to corresponding reactions in KEGG. The resulting model, stheVS26, encompasses 322 metabolites, 400 enzymes along with their transcription and translation processes, and 336 enzyme reactions. This model provides a foundational platform for the simulation and prediction of cellular behaviour, allowing for informed design decisions in metabolic engineering.

Keywords: Whole-cell Model; Kinetic Model; Differential Equations; AdvanceSyn Toolkit; Yoghurt; Exopolysaccharides

References

  1. Roux E., et al. “The Genomic Basis of the Streptococcus thermophilus Health-Promoting Properties”. BMC Genomics1 (2022): 210.
  2. Abubakr RAH., et al. “Genetic and Biotechnological Characterization of Folate-Producing Probiotics Isolated from Local Dairy Products”. Beni-Suef University Journal of Basic and Applied Sciences1 (2025): 62.
  3. Yu P., et al. “Short Communication: Lactose Utilization of Streptococcus thermophilus and Correlations with β-Galactosidase and Urease”. Journal of Dairy Science1 (2020): 166-171.
  4. Auestad N and Layman DK. “Dairy Bioactive Proteins and Peptides: A Narrative Review”. Nutrition Reviews2 (2021): 36-47.
  5. Helal A., et al. “Effect of Fermentation with Streptococcus thermophilus Strains on In Vitro Gastro-Intestinal Digestion of Whey Protein Concentrates”. Microorganisms7 (2023): 1742.
  6. Ayala-Niño A., et al. “Whey-Derived Antihypertensive Peptides Produced by Proteinase K Hydrolysis and Fermentation”. Waste and Biomass Valorization (2025).
  7. Vinderola G., et al. “The Concept of Postbiotics”. Foods (Basel, Switzerland)8 (2022): 1077.
  8. Allouche R., et al. “Streptococcus thermophilus: A Source of Postbiotics Displaying Anti-Inflammatory Effects in THP 1 Macrophages”. MDPI Molecules7 (2024): 1552.
  9. Pattapulavar V., et al. “Probiotic-Derived Postbiotics: A Perspective on Next-Generation Therapeutics”. Frontiers in Nutrition 12 (2022): 1624539.
  10. De Vuyst L., et al. “Exopolysaccharide-Producing Streptococcus thermophilus Strains as Functional Starter Cultures in the Production of Fermented Milks”. International Dairy Journal8 (2003): 707-717.
  11. Broadbent JR., et al. “Biochemistry, Genetics, and Applications of Exopolysaccharide Production in Streptococcus thermophilus: A Review”. Journal of Dairy Science2 (2003): 407-423.
  12. Sørensen KI., et al. “Enhancing the Sweetness of Yoghurt through Metabolic Remodeling of Carbohydrate Metabolism in Streptococcus thermophilus and Lactobacillus delbrueckii subsp. Bulgaricus”. Applied and Environmental Microbiology12 (2016): 3683-3692.
  13. Chaves ACSD., et al. “Metabolic Engineering of Acetaldehyde Production by Streptococcus thermophilus”. Applied and Environmental Microbiology11 (2002): 5656-5662.
  14. Kong L., et al. “CRISPR/dCas9-Based Metabolic Pathway Engineering for the Systematic Optimization of Exopolysaccharide Biosynthesis in Streptococcus thermophilus”. Journal of Dairy Science8 (2022): 6499-6512.
  15. Khanijou JK., et al. “Metabolomics and Modelling Approaches for Systems Metabolic Engineering. Metabolic Engineering Communications 15 (2022): e00209.
  16. Gudmundsson S., et al. “Recent Advances in Model-Assisted Metabolic Engineering”. Current Opinion in Systems Biology 28 (2022): 100392.
  17. Richelle A., et al. “Towards a Widespread Adoption of Metabolic Modeling Tools in Biopharmaceutical Industry: A Process Systems Biology Engineering Perspective”. npj Systems Biology and Applications 6 (1 (2020): 6.
  18. Lee YQ., et al. “Genome-scale metabolic model-guided systematic framework for designing customized live biotherapeutic products”. NPJ Systems Biology and Applications1 (2025): 73.
  19. Prabhu S., et al. “Derivative-Free Domain-Informed Data-Driven Discovery of Sparse Kinetic Models. Industrial and Engineering Chemistry Research5 (2025): 2601-2615.
  20. Yeo KY., et al. “Ab Initio Whole Cell Kinetic Model of Yarrowia lipolytica CLIB122 (yliYKY24)”. Medicon Medical Sciences4 (2025): 01-06.
  21. Foster CJ., et al. “Building Kinetic Models for Metabolic Engineering”. Current Opinion in Biotechnology 67 (2021): 35-41.
  22. Lázaro J., et al. “Enhancing genome-scale metabolic models with kinetic data: resolving growth and citramalate production trade-offs in Escherichia coli”. Bioinformatics Advances 5 (1 (2025): vbaf166.
  23. Rau MH., et al. “Genome-Scale Metabolic Modeling Combined with Transcriptome Profiling Provides Mechanistic Understanding of Streptococcus thermophilus CH8 Metabolism”. Applied and Environmental Microbiology 88 (16 (2022): e0078022.
  24. Okuda S., et al. “KEGG Atlas mapping for global analysis of metabolic pathways”. Nucleic Acids Research 36 (2008): W423-W426.
  25. Cho JL and Ling MH. “Adaptation of Whole Cell Kinetic Model Template, UniKin1, to Escherichia coli Whole Cell Kinetic Model, ecoJC20”. EC Microbiology 17 (2 (2021): 254-260.
  26. Kwan ZJ., et al. “Ab Initio Whole Cell Kinetic Model of Stutzerimonas balearica DSM 6083 (pbmKZJ23)”. Acta Scientific Microbiology2 (2024): 28-31.
  27. Maiyappan S., et al. “Four Ab Initio Whole Cell Kinetic Models of Bacillus subtilis 168 (bsuLL25) 6051-HGW (bshSM25), N33 (bsuN33SS25), FUA2231 (bsuGR25)”. Journal of Clinical Immunology and Microbiology2 (2025): 1-6.
  28. Sim BJH., et al. “Multilevel Metabolic Modelling Using Ordinary Differential Equations”. Encyclopedia of Bioinformatics and Computational Biology (Second Edition), eds Ranganathan S, Cannataro M, Khan AM (Elsevier, Oxford) (2025): 491-498.
  29. Müller-Hill B. “The lac Operon: A Short History of a Genetic Paradigm (Berlin, Germany)”. (1996).
  30. Churchward G., et al. “Transcription in Bacteria at Different DNA Concentrations”. Journal of Bacteriology2 (1982): 572-581.
  31. 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.
  32. Kubitschek HE. “Cell Volume Increase in Escherichia coli After Shifts to Richer Media”. Journal of Bacteriology1 (1990): 94-101.
  33. Hu P., et al. “Global Functional Atlas of Escherichia coli Encompassing Previously Uncharacterized Proteins”. PLoS Biology4 (2009): e96.
  34. So L-H., et al. “General Properties of Transcriptional Time Series in Escherichia coli”. Nature Genetics6 (2011): 554-560.
  35. Schwanhäusser B., et al. “Corrigendum: Global Quantification of Mammalian Gene Expression Control”. Nature7439 (2013): 126-127.
  36. Maurizi MR. “Proteases and Protein Degradation in Escherichia coli”. Experientia2 (1992): 178-201.
  37. Murthy MV., et al. “UniKin1: A Universal, Non-Species-Specific Whole Cell Kinetic Model”. Acta Scientific Microbiology10 (2020): 04-08.
  38. Bar-Even A., et al. “The Moderately Efficient Enzyme: Evolutionary and Physicochemical Trends Shaping Enzyme Parameters”. Biochemistry21 (2011): 4402-4410.
  39. Ling MH. “AdvanceSyn Toolkit: An Open Source Suite for Model Development and Analysis in Biological Engineering”. MOJ Proteomics & Bioinformatics4 (2020): 83-86.
  40. 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 (2019): 012020.
  41. 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.
  42. Saisudhanbabu T., et al. “Ab Initio Whole Cell Kinetic Model of Limosilactobacillus fermentum EFEL6800 (lfeTS24)”. EC Clinical and Medical Case Reports4 (2025): 01-04.
  43. Arivazhagan M., et al. “Ab Initio Whole Cell Kinetic Model of Bifidobacterium bifidum BGN4 (bbfMA24). Acta Scientific Nutritional Health1 (2025): 42-45.
  44. Senthilkumar A., et al. “Ab Initio Whole Cell Kinetic Model of Lactobacillus acidophilus NCFM (lacAS24). Journal of Clinical Immunology and Microbiology1 (2025): 1-5.
  45. Wong TB., et al. “Ab Initio Whole Cell Kinetic Models of Escherichia coli BL21 (ebeTBSW25) and MG1655 (ecoMAL25)”. Scholastic Medical Sciences22 (2025): 01-04.
  46. Ambel WB., et al. “UniKin2 - A Universal, Pan-Reactome Kinetic Model. International Journal of Research in Medical and Clinical Science2 (2025): 77-80.
  47. Bar-Even A., et al. “The Moderately Efficient Enzyme: Futile Encounters and Enzyme Floppiness”. Biochemistry32 (2015): 4969-4977.
  48. 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.
  49. Chagas M da S., et al. “Boolean Model of the Gene Regulatory Network of Pseudomonas aeruginosa CCBH4851”. Frontiers in Microbiology 14 (2023): 1274740.
  50. Hao T., et al. “Reconstruction of Metabolic-Protein Interaction Integrated Network of Eriocheir sinensis and Analysis of Ecdysone Synthesis”. Genes4 (2024): 410.
  51. Thornburg ZR., et al. “Fundamental Behaviors Emerge From Simulations of a Living Minimal Cell”. Cell2 (2022): 345-360.e28.
  52. Bianchi DM., et al. “Toward the Complete Functional Characterization of a Minimal Bacterial Proteome”. The Journal of Physical Chemistry B36 (2022): 6820-6834.
  53. 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 Systems32 (2024): 27-245.e7.
  54. 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 Streptococcus thermophilus STH_CIRM_65 (stheVS26)". Acta Scientific Nutritional Health 10.2 (2026): 43-47.

Copyright

Copyright: © 2026 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.




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