Palladina O. L., Kaliga A. M.

COMPARATIVE ANALYSIS OF CONTEMPORARY METHODS FOR INVESTIGATING THE COMPOSITION OF THE HUMAN GUT MICROBIOME

---

Show/Download

About the author:

Palladina O. L., Kaliga A. M.

Heading:

METHODS AND METHODOLOGIES

Type of article:

Scientific article

Annotation:

The human gut microbiome is a complex system comprising trillions of microorganisms, including bacteria, archaea, fungi, and viruses, which influence metabolism and play a key role in digestion, vitamin synthesis, and immune response regulation. The impact of the microbiome on human health has gained particular importance in modern medicine, especially in sports physiology. It can determine adaptation to physical activity, recovery after training, and overall physical condition in athletes. This study focuses on a comparative analysis of the most common methods for studying the human gut microbiome, their technical features, and prospects for application in sports medicine. Investigating the gut microbiome is challenging due to its structural complexity and variability under the influence of numerous internal and external factors, such as diet, physical activity, environmental conditions, and the use of medical drugs. The study analyzes modern and widespread methods for studying the gut microbiome, including polymerase chain reaction (PCR), 16S rRNA gene sequencing, and metagenomic sequencing. A comparative characterization of these approaches is presented, including their technological features, sensitivity, specificity, and limitations concerning taxonomic and functional data interpretation. The importance of proper conditions for sample collection, storage, and transportation is emphasized to ensure the reliability of results, with a focus on analyzing fecal samples as the primary non-invasive method for studying the gut microbiome. The findings contribute to a deeper understanding of the mechanisms through which the microbiota affects the physical condition of athletes and provide a scientific basis for the individualization of training programs.

Tags:

Bibliography:

1. Hou K, Wu ZX, Chen XY, Wang JQ, Zhang D, Xiao C, et al. Microbiota in health and diseases. Signal Transduct Target Ther. 2022;7(1):135. DOI: 10.1038/s41392-022-00974-4.
2. Bradley E, Haran J. The human gut microbiome and aging. Gut Microbes. 2024;16(1):2359677. DOI: 10.1080/19490976.2024.2359677.
3. Fontana F, Longhi G, Tarracchini C, Mancabelli L, Lugli GA, Alessandri G, et al. The human gut microbiome of athletes: metagenomic and metabolic insights. Microbiome. 2023;11(1):27. DOI: 10.1186/s40168-023-01470-9.
4. Hughes RL, Holscher HD. Fueling Gut Microbes: A Review of the Interaction between Diet, Exercise, and the Gut Microbiota in Athletes. Adv Nutr. 2021;12(6):2190-2215. DOI: 10.1093/advances/nmab077.
5. Fan L, Xia Y, Wang Y, Han D, Liu Y, Li J, et al. Gut microbiota bridges dietary nutrients and host immunity. Sci China Life Sci. 2023;66(11):2466- 2514. DOI: 10.1007/s11427-023-2346-1.
6. Sangermani M, Desiati I, Jørgensen SM, Li JV, Andreassen T, Bathen TF, et al. Stability in fecal metabolites amid a diverse gut microbiome composition: a one-month longitudinal study of variability in healthy individuals. Gut Microbes. 2024;16(1):2427878. DOI: 10.1080/19490976.2024.2427878.
7. Portincasa P, Bonfrate L, Vacca M, De Angelis M, Farella I, Lanza E, et al. Gut Microbiota and Short Chain Fatty Acids: Implications in Glucose Homeostasis. Int J Mol Sci. 2022;23(3):1105. DOI: 10.3390/ijms23031105.
8. Zhang X, Li L, Butcher J, Stintzi A, Figeys D. Advancing functional and translational microbiome research using meta-omics approaches. Microbiome. 2019;7(1):154. DOI: 10.1186/s40168-019-0767-6.
9. National Academies of Sciences, Engineering, and Medicine, Division on Earth and Life Studies, Board on Life Sciences, Board on Environmental Studies and Toxicology, Committee on Advancing Understanding of the Implications of Environmental-Chemical Interactions with the Human Microbiome. Environmental Chemicals, the Human Microbiome, and Health Risk: A Research Strategy. Washington (DC): National Academies Press; 2017. Available from: https://www.ncbi.nlm.nih.gov/books/NBK481559/.
10. O’Brien MT, O’Sullivan O, Claesson MJ, Cotter PD. The Athlete Gut Microbiome and its Relevance to Health and Performance: A Review. Sports Med. 2022;52(1):119-128. DOI: 10.1007/s40279-022-01785-x.
11. Al Bander Z, Nitert MD, Mousa A, Naderpoor N. The Gut Microbiota and Inflammation: An Overview. Int J Environ Res Public Health. 2020;17(20):7618. DOI: 10.3390/ijerph17207618.
12. Wan X, Yang Q, Wang X, Bai Y, Liu Z. Isolation and Cultivation of Human Gut Microorganisms: A Review. Microorganisms. 2023;11(4):1080. DOI: 10.3390/microorganisms11041080.
13. Wensel CR, Pluznick JL, Salzberg SL, Sears CL. Next-generation sequencing: insights to advance clinical investigations of the microbiome. J Clin Invest. 2022;132(7):e154944. DOI: 10.1172/JCI154944.
14. Kim D, Jung JY, Oh HS, Jee SR, Park SJ, Lee SH, et al. Comparison of sampling methods in assessing the microbiome from patients with ulcerative colitis. BMC Gastroenterol. 2021;21(1):396. DOI: 10.1186/s12876-021-01975-3.
15. Miyauchi E, Taida T, Kawasumi M, Ohkusa T, Sato N, Ohno H. Analysis of colonic mucosa-associated microbiota using endoscopically collected lavage. Sci Rep. 2022;12(1):1758. DOI: 10.1038/s41598-022-05936-y.
16. Marquez-Ortiz RA, Leon M, Abril D, Escobar-Perez J, Florez-Sarmiento C, Parra-Izquierdo V, et al. Colonoscopy aspiration lavages for mucosal metataxonomic profiling of spondylarthritis-associated gastrointestinal tract alterations. Sci Rep. 2023;13(1):7015. DOI: 10.1038/s41598-023-33597-y.
17. Tang Q, Jin G, Wang G, Liu T, Liu X, Wang B, et al. Current Sampling Methods for Gut Microbiota: A Call for More Precise Devices. Front Cell Infect Microbiol. 2020 9;10:151. DOI: 10.3389/fcimb.2020.00151.
18. Nejati S, Wang J, Sedaghat S, Balog NK, Long AM, Rivera UH, et al. Smart capsule for targeted proximal colon microbiome sampling. Acta Biomater. 2022;154:83-96. DOI: 10.1016/j.actbio.2022.09.050.
19. Wu WK, Chen CC, Panyod S, Chen RA, Wu MS, Sheen LY, et al. Optimization of fecal sample processing for microbiome study – The journey from bathroom to bench. J Formos Med Assoc. 2019;118(2):545-555. DOI: 10.1016/j.jfma.2018.02.005.
20. Choo JM, Leong LE, Rogers GB. Sample storage conditions significantly influence faecal microbiome profiles. Sci Rep. 2015;5:16350. DOI: 10.1038/srep16350.
21. Dore J, Ehrlich SD, Levenez F, Pelletier E, Alberti A, Bertrand L, et al. IHMS_SOP 02 V1: Standard operating procedure for fecal samples self‐collection, laboratory analysis handled within 4 hours (x≤ 4 hours). Paris: IHMS Consortium; 2015. 13 p. Available from: http://www. microbiome‐standards.org.
22. Kim D, Hofstaedter CE, Zhao C, Mattei L, Tanes C, Clarke E, et al. Optimizing methods and dodging pitfalls in microbiome research. Microbiome. 2017;5(1):52. DOI: 10.1186/s40168-017-0267-5.
23. Kumar A, Gravdal K, Segal JP, Steed H, Brookes MJ, Al-Hassi HO. Variability in the Pre-Analytical Stages Influences Microbiome Laboratory Analyses. Genes (Basel). 2022;13(6):1069. DOI: 10.3390/genes13061069.
24. Galloway-Peña J, Hanson B. Tools for Analysis of the Microbiome. Dig Dis Sci. 2020;65(3):674-685. DOI: 10.1007/s10620-020-06091-y.
25. Allaband C, McDonald D, Vázquez-Baeza Y, Minich JJ, Tripathi A, Brenner DA, et al. Microbiome 101: Studying, Analyzing, and Interpreting Gut Microbiome Data for Clinicians. Clin Gastroenterol Hepatol. 2019;17(2):218-230. DOI: 10.1016/j.cgh.2018.09.017.
26. Jeong J, Mun S, Oh Y, Cho CS, Yun K, Ahn Y, et al. A qRT-PCR Method Capable of Quantifying Specific Microorganisms Compared to NGS-Based Metagenome Profiling Data. Microorganisms. 2022;10(2):324. DOI: 10.3390/microorganisms10020324.
27. Hughes RL, Frankenfeld CL, Gohl DM, Huttenhower C, Jackson SA, Vandeputte D, et al. Methods in Nutrition & Gut Microbiome Research: An American Society for Nutrition Satellite Session. Nutrients. 2023;15(11):2451. DOI: 10.3390/nu15112451.
28. Nearing JT, Douglas GM, Hayes MG, MacDonald J, Desai DK, Allward N, et al. Microbiome differential abundance methods produce different results across 38 datasets. Nat Commun. 2022;13(1):342. DOI: 10.1038/s41467-022-28034-z.
29. Gotschlich EC, Colbert RA, Gill T. Methods in microbiome research: Past, present, and future. Best Pract Res Clin Rheumatol. 2019;33(6):101498. DOI: 10.1016/j.berh.2020.101498.
30. Ji B, Nielsen J. From next-generation sequencing to systematic modeling of the gut microbiome. Front Genet. 2015;6:219. DOI: 10.3389/fgene.2015.00219.
31. Fricker AM, Podlesny D, Fricke WF. What is new and relevant for sequencing-based microbiome research? A mini-review. J Adv Res. 2019;19:105-112. DOI: 10.1016/j.jare.2019.
32. Panek M, Čipčić Paljetak H, Barešić A, Perić M, Matijašić M, Lojkić I, et al. Methodology challenges in studying human gut microbiota – effects of collection, storage, DNA extraction and next generation sequencing technologies. Sci Rep. 2018;8(1):5143. DOI: 10.1038/s41598-018-23296-4.
33. Casén C, Vebø HC, Sekelja M, Hegge FT, Karlsson MK, Ciemniejewska E, et al. Deviations in human gut microbiota: a novel diagnostic test for determining dysbiosis in patients with IBS or IBD. Aliment Pharmacol Ther. 2015;42(1):71-83. DOI: 10.1111/apt.13236.
34. Lutz KC, Jiang S, Neugent ML, De Nisco NJ, Zhan X, Li Q. A Survey of Statistical Methods for Microbiome Data Analysis. Front Appl Math Stat. 2022;8:884810. DOI: 10.3389/fams.2022.884810.
35. Walker-Daniels J. Microbiome Research Methodologies. Mater Methods. 2020;10:2883. DOI: 10.13070/mm.en.10.2883.

Publication of the article:

«Bulletin of problems biology and medicine», 2025 Issue 1, 176, 373-381 pages, index UDC 612.015.3:612.336.3:796.01

DOI:

10.29254/2077-4214-2025-1-176-373-381