Gut Microbiome Functional Profiling for Metabolic Health through Integrated Multi-Omics Evidence
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Abstract
The human gut microbiome is increasingly recognized as a critical determinant of host metabolic health, influencing a wide array of physiological processes from energy harvest to immune system modulation. Traditional microbiome research has predominantly relied on amplicon sequencing techniques that catalog microbial taxonomy, leaving a significant gap in our understanding of the actual functional capabilities and real-time metabolic outputs of these complex communities. This paper presents a comprehensive exploration of gut microbiome functional profiling through the integration of multi-omics evidence, specifically combining metagenomics, metatranscriptomics, and metabolomics. By moving beyond compositional descriptions, integrated multi-omics approaches allow for a high-resolution mapping of microbial pathways and the identification of specific bioactive metabolites that interact with host cellular receptors. This research synthesizes current literature, proposes a robust methodological framework for multi-omics data acquisition and integration, and discusses the implications of functional redundancy, cross-feeding networks, and biomarker discovery in the context of metabolic disorders such as obesity and type 2 diabetes. The findings underscore the necessity of system-level analyses to elucidate the mechanistic underpinnings of microbiome-host interactions. Ultimately, decoding the functional dynamics of the gut microbiome provides a foundation for developing targeted nutritional interventions and next-generation live biotherapeutics designed to restore metabolic homeostasis and prevent systemic metabolic dysregulation.
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References
1. Li, Yongwei, et al. "Potential Therapeutic Targets for Androgenetic Alopecia (AGA) in Obese Individuals as Revealed by a Gut Microbiome Analysis: A Mendelian Randomization Study." Nutrients 17.11 (2025): 1892.
2. Wang, G., Zhou, Y., Deng, K., Cheah, W. P., Qu, R., Ren, J., & Shen, L. (2026). SurgCoT: Advancing Spatiotemporal Reasoning in Surgical Videos through a Chain-of-Thought Benchmark. arXiv preprint arXiv:2604.20319.
3. Sinha, D., Tong, Y., Zepeda, M. A. F., Hanstad, G., Nelson, E. C., Theisen, C. O., ... & Gamm, D. M. (2023). Silica nanocapsules as a nonviral delivery platform for iPSC-RPE.Investigative Ophthalmology & Visual Science,64(8), 774-774.
4. Thompson, J. D., Higgins, D. G., & Gibson, T. J. (1994). CLUSTAL W: Improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Research, 22(22), 4673–4680.
5. Jing F, Ye Y, Zhou Y, et al. Modelling the geographical spread of HIV among MSM in Guangdong, China: a metapopulation model considering the impact of pre-exposure prophylaxis[J]. Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 2021, 380(2214): 20210126.
6. Jiang, Z., Hou, Z., Yu, X., Zhao, Z., Bu, J., Li, C.,... & Wang, C. (2025). SPECT-derived myocardial perfusion and viability as predictors of response to left bundle branch pacing for cardiac resynchronization therapy. Europace, 27 (12), euaf301.
7. World Health Organization. (2016). Guideline: updates on HIV and infant feeding: the duration of breastfeeding, and support from health services to improve feeding practices among mothers living with HIV.
8. Xu, X., Bowtell, J., Young, W. R., Fong, D. T., & Williams, G. K. (2026). Increased common corticospinal input during eyes-closed unilateral stance in people with chronic ankle instability. Scientific Reports.
9. Wang, G., Ren, J., Shen, L., Cheah, W. P., & Qu, R. (2026). M-MambaS: Multimodal Mamba for small lesion segmentation.Pattern Recognition, 113923.
10. Chai L, Zhang J, Fernando W G D, et al. Detection of blackleg resistance gene Rlm1 in double-low rapeseed accessions from Sichuan province, by kompetitive allele-specific PCR[J]. The Plant Pathology Journal, 2021, 37(2): 194.
11. Kermany, D. S., Goldbaum, M., Cai, W., Valentim, C. C. S., Liang, H., Baxter, S. L., et al. (2018). Identifying medical diagnoses and treatable diseases by image-based deep learning. Cell, 172(5), 1122–1131.
12. Chen, Z., Gao, P., Lee, Y., Barthelemy, J., Zhou, L., & Wang, L. (2025, June). Optimizing Efficiency and Visual-Textual Alignment for LLM-Based Radiology Report Generation. In 2025 IEEE International Conference on Multimedia and Expo (ICME) (pp. 1-6). IEEE.
13. Zhao, K., Li, G., Li, C., Jiang, T., Wang, W., & Yang, Z. (2026). Identification Markers for Salvia miltiorrhiza and Its Close Relatives Based on Cell Wall Component Characteristics. Engineered Science, 40, 2122.
14. Li, Z. R., Wang, Y. Y., Zhang, C., Shi, J. S., Yu, X., Ying, N. T.,... & Guo, T. (2025). Features and functional mechanisms of super-enhancers in cardiovascular disorders, cancer, autoimmune diseases and neurodegenerative disorders. Cellular Signalling, 112252.
15. Wang, W., Wei, X., Sun, Z., Zhang, X., Pan, D., Hong, X., ... & Yang, D. (2026). Uncovering the toxicological impact of benzo [a] pyrene on Alzheimer's disease via network toxicology, machine learning, and single-cell transcriptomics. Journal of Alzheimer’s Disease, 109(3), 1220-1231.
16. Wang, G., Zhong, Z., Zhou, Y., Li, Y., Wu, E., Cheah, W. P., ... & Shen, L. (2026). X-PCR: A Benchmark for Cross-modality Progressive Clinical Reasoning in Ophthalmic Diagnosis.arXiv preprint arXiv:2604.20350.
17. Xu, X., Bowtell, J., Young, W. R., Fong, D. T., & Williams, G. K. (2025). Distinct patterns in neuromuscular adaptation to repeated perturbations in chronic ankle instability. Journal of NeuroEngineering and Rehabilitation.
18. Shen, Q., Sun, Z. H., Xu, Y. M., Hu, Q. B., Zhang, W. H., & Huang, S. A. (2025). Associations between complete-blood-count-derived inflammatory markers and gastric ulcer: A cross-sectional study. World Journal of Gastroenterology, 31(38), 111298.
19. GAO, T., LIANG, D., CHEN, X., & TAO, X. (2025). PREDICTIVE ANALYTICS IN PEDIATRIC MENTAL HEALTH: A MACHINE LEARNING APPROACHTO DEPRESSION DETECTION BY PHYSICAL ACTIVITY AND BEHAVIORAL HEALTH INDICATORS. INTERCIENCIA.
20. Poplin, R., Chang, P.-C., Alexander, D., Schwartz, S., Colthurst, T., Ku, A., et al. (2018). A universal SNP and small-indel variant caller using deep neural networks. Nature Biotechnology, 36(10), 983–987.
21. Zhang, Y., & Chen, Y. (2025, July). The role of machine learning in reducing healthcare costs: The impact of medication adherence and preventive care on hospitalization expenses. In Proceedings of the International Conference on Implementing Generative AI into Telecommunication and Digital Innovation 2025 (pp. 179-185).
22. Shi, M., & Chow, S. C. (2024). Statistical Analysis for Rating Scale in Clinical Trials.Therapeutic Innovation & Regulatory Science,58(5), 930-945.
23. Xi, Y., Zhao, Z., Zhou, Y., Yin, C., Li, Y., Xu, X.,... & Shen, W. (2026). Macrophage efferocytosis mediated by the TP63-RAC2 pathway promotes immunosuppressive remodeling in esophageal cancer. Cell Reports Medicine, 7 (1).
24. Yin, L., Tong, Y., Xie, R., Zhang, Z., Islam, Z. H., Zhang, K.,... & Wang, B. (2024). Targeted NAD+ repletion via biomimetic nanoparticle enables simultaneous management of intimal hyperplasia and accelerated re-endothelialization: a proof-of-concept study toward next-generation of endothelium-protective, anti-restenotic therapy. Journal of Controlled Release, 376, 806-815.
25. Li, Y., Liao, X., Yu, X., Xiao, Y., Tao, X., & Zhong, T. (2025). Mediating Role of the ANGPTL3/TFPI Protein Ratio in Regulating T-Cell Surface Glycoprotein CD5 Levels on Knee Osteoarthritis (KOA): A Mendelian Randomization Study. International Journal of Molecular Sciences, 26(10), 4471.
26. Yang, Y., Osorio, D., Davidson, L. A., Han, H., Mullens, D. A., Jayaraman, A., Safe, S., Ivanov, I., Cai, J. J., & Chapkin, R. S. (2022). Single-cell RNA sequencing reveals how the aryl hydrocarbon receptor shapes cellular differentiation potency in the mouse colon. Cancer Prevention Research, 15(1), 17–28.
27. Xu, X., Bowtell, J., Fong, D. T., Young, W. R., & Williams, G. K. (2025). Kinematics of balance controls in people with chronic ankle instability during unilateral stance on a moving platform. Scientific Reports, 15(1), 1126.
28. Chen, Z., Zhu, Q., & Zeng, Y. (2026). MWED-Former: A Multi-Scale Weather-Aware Transformer for Emergency Department Demand Forecasting with Weather Bias Correction. Fundamental Scientific Reports in Multidisciplinary Areas, 2 (02), 132-145.
29. Liu, Z. Q., Xiong, Y. J., Yu, X., Lv, T., & Xu, H. Y. (2026). Female reproductive factors, genetic susceptibility and incident osteoporosis risk. Climacteric, 1-8.
30. Kabra, M., Shahi, P. K., Wang, Y., Sinha, D., Spillane, A., Newby, G. A., ... & Pattnaik, B. R. (2022). Nonviral base editing of KCNJ13 mutation preserves vision in an inherited retinal channelopathy.bioRxiv, 2022-07.
31. Ma, H., Sun, J., Li, X., Luo, Y., Liu, J., & Li, J. (2024). Regulatory immune cells in organ transplantation. Frontiers in Immunology, 15, 1383563.