Magaa Lakshmi Dhinakaran^1,2, Tristan Zhi Xian Tay^1,2, Sohnnakshee Murugesu^1,2, Aguilar Normi Luisa Cinco^1,2, Pandiyan Srinithiksha^1,2 and Maurice Han Tong Lin^2,3,4*

¹School of Medicine, College of Medical Sciences, University of Guyana, Guyana
²Management Development Institute of Singapore, Singapore
³Newcastle Australia Institute of Higher Education, University of Newcastle, Australia
⁴HOHY PTE LTD, Singapore

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

Received: January 09, 2026; Published: January 29, 2026

Abstract

Parabacteroids distasonis is a key component of the human gut microbiome, and noted for its ability to produce metabolites that are beneficial for overall gut health. Hence, P. distasonis may be a potential target for metabolic engineering, which can benefit from a whole cell kinetic model. Currently, there are no reported kinetic models for the P. distasonis. Therefore, this study aims to create a whole cell simulatable kinetic model of P. distasonis APCS2/PD using an ab initio approach by identifying enzymes from its published genome. The resulting model, pdiMLD26, encompasses of 703 metabolites, 290 enzymes and 752 enzymatic reactions; which acts as a foundational framework for future research.

 Keywords: Whole-cell Model; Kinetic Model; Gut Microbiome; Differential Equations; AdvanceSyn Toolkit

References

1. Wu WKK. “Parabacteroides distasonis: An Emerging Probiotic?” Gut9 (2023): 1635-1636.
2. Cui Y., et al. “Roles of Intestinal Parabacteroides in Human Health and Diseases”. FEMS Microbiology Letters 369 (1 (2022): fnac072.
3. Fernandez-Julia P., et al. “Cross-Feeding Interactions Between Human Gut Commensals Belonging to the Bacteroides and Bifidobacterium Genera When Grown on Dietary Glycans”. Microbiome Research Reports2 (2022): 12.
4. Chamarande J., et al. “Parabacteroides distasonis Properties Linked to the Selection of New Biotherapeutics”. Nutrients19 (2022): 4176.
5. Cuffaro B., et al. “In Vitro Characterization of Gut Microbiota-Derived Commensal Strains: Selection of Parabacteroides distasonis Strains Alleviating TNBS-Induced Colitis in Mice”. Cells9 (2020): 2104.
6. Wang K., et al. “Parabacteroides distasonis Alleviates Obesity and Metabolic Dysfunctions via Production of Succinate and Secondary Bile Acids”. Cell Reports1 (2019): 222-235.e5.
7. Duan J., et al. “Therapeutic Potential of Parabacteroides distasonis in Gastrointestinal and Hepatic Disease”. MedComm12 (2024): e70017.
8. Wei H., et al. “Gut Commensal Parabacteroides distasonis Exerts Neuroprotective Effects in Acute Ischemic Stroke with Hyperuricemia via Regulating Gut Microbiota-Gut-Brain Axis”. Journal of Translational Medicine1 (2024): 999.
9. Yaqub MO., et al. “Microbiome-Driven Therapeutics: From Gut Health to Precision Medicine”. Gastrointestinal Disorders1 (2025): 7.
10. Khanijou JK., et al. “Metabolomics and Modelling Approaches for Systems Metabolic Engineering”. Metabolic Engineering Communications 15 (2022): e00209.
11. Gudmundsson S and Nogales J. “Recent Advances in Model-Assisted Metabolic Engineering”. Current Opinion in Systems Biology 28 (2021): 100392.
12. 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 Applications1 (2020): 6.
13. Lee YQ., et al. “Genome-scale metabolic model-guided systematic framework for designing customized live biotherapeutic products”. NPJ Systems Biology and Applications1 (2025): 73.
14. Prabhu S., et al. “Derivative-Free Domain-Informed Data-Driven Discovery of Sparse Kinetic Models”. Industrial & Engineering Chemistry Research5 (2025): 2601-2615.
15. Yeo KY., et al. “Ab Initio Whole Cell Kinetic Model of Yarrowia lipolytica CLIB122 (yliYKY24)”. Medicon Medical Sciences4 (2025): 01-06.
16. Foster CJ., et al. “Building Kinetic Models for Metabolic Engineering”. Current Opinion in Biotechnology 67 (2021): 35-41.
17. Lázaro J., et al. “Enhancing genome-scale metabolic models with kinetic data: resolving growth and citramalate production trade-offs in Escherichia coli”. Bioinformatics Advances1 (2025): vbaf166.
18. Cortés-Martín A., et al. “Isolation and Characterization of a Novel Lytic Parabacteroides Distasonis Bacteriophage φPDS1 from the Human Gut”. Gut Microbes1 (2024): 2298254.
19. Okuda S., et al. “KEGG Atlas mapping for global analysis of metabolic pathways”. Nucleic Acids Research 36 (2008): W423-W426.
20. 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.
21. Stevanoska M., et al. “Physiologically Based Kinetic (PBK) Modeling as a New Approach Methodology (NAM) for Predicting Systemic Levels of Gut Microbial Metabolites”. Toxicology Letters 396 (2024): 94-102.
22. Rios Garza D., et al. “Metabolic Models of Human Gut Microbiota: Advances and Challenges”. Cell Systems2 (2023): 109-121.
23. Kwan ZJ., et al. “Ab Initio Whole Cell Kinetic Model of Stutzerimonas balearica DSM 6083 (pbmKZJ23)”. Acta Scientific Microbiology2 (2024): 28-31.
24. 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.
25. 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.
26. Müller-Hill B. “The lac Operon: A Short History of a Genetic Paradigm (Berlin, Germany)” (1996).
27. Churchward G., et al. “Transcription in Bacteria at Different DNA Concentrations”. Journal of Bacteriology2 (1982): 572-581.
28. 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.
29. Kubitschek HE. “Cell Volume Increase in Escherichia coli After Shifts to Richer Media”. Journal of Bacteriology1 (1990): 94-101.
30. Hu P., et al. “Global Functional Atlas of Escherichia coli Encompassing Previously Uncharacterized Proteins”. PLoS Biology4 (2009): e96.
31. So L-H., et al. “General Properties of Transcriptional Time Series in Escherichia coli”. Nature Genetics6 (2011): 554-560.
32. Schwanhäusser B., et al. “Corrigendum: Global Quantification of Mammalian Gene Expression Control”. Nature7439 (2013): 126-127.
33. Maurizi MR. “Proteases and Protein Degradation in Escherichia coli”. Experientia2 (1992): 178-201.
34. Murthy MV., et al. “UniKin1: A Universal, Non-Species-Specific Whole Cell Kinetic Model”. Acta Scientific Microbiology10 (2020): 04-08.
35. Bar-Even A., et al. “The Moderately Efficient Enzyme: Evolutionary and Physicochemical Trends Shaping Enzyme Parameters”. Biochemistry21 (2011): 4402-4410.
36. Ling MH. “AdvanceSyn Toolkit: An Open Source Suite for Model Development and Analysis in Biological Engineering”. MOJ Proteomics & Bioinformatics4 (2020): 83‒86.
37. 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.
38. 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.
39. Saisudhanbabu T., et al. “Ab Initio Whole Cell Kinetic Model of Limosilactobacillus fermentum EFEL6800 (lfeTS24)”. EC Clinical and Medical Case Reports4 (2025): 01-04.
40. Arivazhagan M., et al. “Ab Initio Whole Cell Kinetic Model of Bifidobacterium bifidum BGN4 (bbfMA24)”. Acta Scientific Nutritional Health1 (2025): 42-45.
41. Senthilkumar A., et al. “Ab Initio Whole Cell Kinetic Model of Lactobacillus acidophilus NCFM (lacAS24)”. Journal of Clinical Immunology and Microbiology1 (2025): 1-5.
42. Wong TB., et al. “Ab Initio Whole Cell Kinetic Models of Escherichia coli BL21 (ebeTBSW25) and MG1655 (ecoMAL25)”. Scholastic Medical Sciences2 (2025): 01-04.
43. Ambel WB., et al. “UniKin2 - A Universal, Pan-Reactome Kinetic Model”. International Journal of Research in Medical and Clinical Science2 (2025): 77-80.
44. 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.
45. Chagas M da S., et al. “Boolean Model of the Gene Regulatory Network of Pseudomonas aeruginosa CCBH4851”. Frontiers in Microbiology 14 (2023): 1274740.
46. Hao T., et al. “Reconstruction of Metabolic-Protein Interaction Integrated Network of Eriocheir sinensis and Analysis of Ecdysone Synthesis”. Genes4 (2024): 410.

Citation

Citation: Maurice Han Tong Ling., et al. “Ab Initio Whole Cell Kinetic Model of Parabacteroides distasonis APCS2/PD (pdiMLD26)”.Acta Scientific Medical Sciences 10.2 (2026): 52-56.

Copyright

Copyright: © 2026 Maurice Han Tong 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.