Comparative Analysis of Fecal Microbiota in Vegetarians and Omnivores
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Participants
2.2. Fecal Sample Collection and DNA Extraction
2.3. Analysis of 16S rRNA Sequences
2.4. Statistical Analysis
3. Results
3.1. Characterization of Subjects
3.2. Dietary Profiles
3.3. Analysis of Fecal Microbial Composition in Vegetarians and Omnivores
3.4. Analysis of Fecal Microbial Diversity in Vegetarians and Omnivores
3.5. Correlation between Food and the Fecal Microbial Community
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Akagbosu, B.; Tayyebi, Z.; Shibu, G.; Paucar Iza, Y.A.; Deep, D.; Parisotto, Y.F.; Fisher, L.; Pasolli, H.A.; Thevin, V.; Elmentaite, R.; et al. Novel antigen-presenting cell imparts T-dependent tolerance to gut microbiota. Nature 2022, 610, 752–760. [Google Scholar] [CrossRef] [PubMed]
- Federici, S.; Kredo-Russo, S.; Valdés-Mas, R.; Kviatcovsky, D.; Weinstock, E.; Matiuhin, Y.; Silberberg, Y.; Atarashi, K.; Furuichi, M.; Oka, X.; et al. Targeted suppression of human IBD-associated gut microbiota commensals by phage consortia for treatment of intestinal inflammation. Cell 2022, 185, 2879–2898. [Google Scholar] [CrossRef] [PubMed]
- Wang, Z.; Usyk, M.; Vázquez-Baeza, Y.; Chen, G.C.; Isasi, C.R.; Williams-Nguyen, J.S.; Hua, S.; McDonald, D.; Thyagarajan, B.; Daviglus, M.L.; et al. Microbial co-occurrence complicates associations of gut microbiome with US immigration, dietary intake and obesity. Genome Biol. 2021, 22, 336. [Google Scholar] [CrossRef] [PubMed]
- Davenport, E.R.; Sanders, J.G.; Song, S.J.; Amato, K.R.; Clark, A.G.; Knight, R. The human microbiome in evolution. BMC Biol. 2017, 15, 127. [Google Scholar] [CrossRef]
- Amamoto, R.; Shimamoto, K.; Suwa, T.; Park, S.; Matsumoto, H.; Shimizu, K.; Katto, M.; Makino, H.; Matsubara, S.; Aoyagi, Y. Relationships between dietary diversity and gut microbial diversity in the elderly. Benef. Microbes 2022, 13, 453–464. [Google Scholar] [CrossRef]
- Thingholm, L.B.; Ruehlemann, M.C.; Koch, M.; Fuqua, B.; Laucke, G.; Boehm, R.; Bang, C.; Franzosa, E.A.; Huebenthal, M.; Rahnavard, A. Obese Individuals with and without Type 2 Diabetes Show Different Gut Microbial Functional Capacity and Composition. Cell Host Microbe 2019, 26, 252–275. [Google Scholar] [CrossRef]
- Kesika, P.; Suganthy, N.; Sivamaruthi, B.S.; Chaiyasut, C. Role of gut-brain axis, gut microbial composition, and probiotic intervention in Alzheimer’s disease. Life Sci. 2020, 264, 118627. [Google Scholar] [CrossRef]
- Ramirez, J.; Guarner, F.; Bustos Fernandez, L.; Maruy, A.; Sdepanian, V.L.; Cohen, H. Antibiotics as Major Disruptors of Gut Microbiota. Front. Cell. Infect. Microbiol. 2020, 10, 572912. [Google Scholar] [CrossRef]
- Šumilo, D.; Brocklehurst, P. What is the relationship between mode of birth, antibiotics, and childhood health? BMJ (Clin. Res. Ed.) 2022, 377, O1526. [Google Scholar] [CrossRef]
- Rothschild, D.; Weissbrod, O.; Barkan, E.; Kurilshikov, A.; Korem, T.; Zeevi, D.; Costea, P.I.; Godneva, A.; Kalka, I.N. Environment dominates over host genetics in shaping human gut microbiota. Nature 2018, 555, 210–215. [Google Scholar] [CrossRef]
- De Filippis, F.; Pasolli, E.; Tett, A.; Tarallo, S.; Naccarati, A.; De Angelis, M.; Neviani, E.; Cocolin, L.; Gobbetti, M.; Segata, N. Distinct Genetic and Functional Traits of Human Intestinal Prevotella copri Strains Are Associated with Different Habitual Diets. Cell Host Microbe 2019, 25, 444–453. [Google Scholar] [CrossRef] [PubMed]
- Clarke, S.F.; Murphy, E.F.; Nilaweera, K.; Ross, P.R.; Shanahan, F.; O’Toole, P.W.; Cotter, P.D. The gut microbiota and its relationship to diet and obesity: New insights. Gut Microbes 2012, 3, 186–202. [Google Scholar] [CrossRef] [PubMed]
- Medawar, E.; Huhn, S.; Villringer, A.; Witte, A.V. The effects of plant-based diets on the body and the brain: A systematic review. Transl. Psychiatr. 2019, 9, 226. [Google Scholar] [CrossRef]
- Mohammed, A. Prevalence of vegan/vegetarian diet and eating behavior among Saudi adults and its correlation with body mass index: A cross-sectional study. Front. Nutr. 2022, 9, 966629. [Google Scholar]
- Xiao, W.; Zhang, Q.; Yu, L.; Tian, F.; Chen, W.; Zhai, Q. Effects of vegetarian diet-associated nutrients on gut microbiota and intestinal physiology. Food Sci. Hum. Wellness 2022, 11, 208–217. [Google Scholar] [CrossRef]
- Beisner, J.; Gonzalez-Granda, A.; Basrai, M.; Damms-Machado, A.; Bischoff, S.C. Fructose-Induced Intestinal Microbiota Shift Following Two Types of Short-Term High-Fructose Dietary Phases. Nutrients 2020, 12, 3444. [Google Scholar] [CrossRef]
- Sun, C.; Wang, Q.; Xu, C.; Wang, W.; Ma, J.; Gu, L.; Liu, Z.; Hou, J.; Jiang, Z. Reproducibility and Validity of a Semi-Quantitative Food Frequency Questionnaire for Assessing Dietary Intake of Vegetarians and Omnivores in Harbin, China. Nutrients 2022, 14, 3975. [Google Scholar] [CrossRef]
- Yang, Y. Chinese Food Composition Table, 6th ed.; Peking University Medical Press: Beijing, China, 2019. [Google Scholar]
- Xiao, L.; Zhou, J.; Galling, B.; Chen, R.S.; Wang, G. The association of body mass index (BMI) with treatment outcomes in patients with major depressive disorder. J. Affect. Disord. 2021, 281, 799–804. [Google Scholar] [CrossRef]
- Federica, D.C.; Francesca, A.; Alessandra, R.; Andrea, Q.; Sofia, R.; Danila, C.; Romina, C.; Stefano, G.C.; Valerio, N.; Francesco, D.P.; et al. Gut Microbiota Markers in Obese Adolescent and Adult Patients: Age-Dependent Differential Patterns. Front. Microbiol. 2018, 9, 1210. [Google Scholar]
- Choong-Kyun, N.; Sun, K.B.; Gana, H.; Youn, C.J.; Jae, L.K. Effects of the Administration of Probiotics on Fecal Microbiota Diversity and Composition in Healthy Individuals. J. Neurogastroenterol. Motil. 2018, 24, 452–459. [Google Scholar]
- Salzberg, S.L. FLASH: Fast length adjustment of short reads to improve genome assemblies. Bioinformatics 2011, 27, 2957–2963. [Google Scholar]
- Caporaso, J.G.; Kuczynski, J.; Stombaugh, J.; Bittinger, K.; Bushman, F.D.; Costello, E.K.; Fierer, N.; Pena, A.G. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 2010, 7, 335–336. [Google Scholar] [CrossRef]
- Bokulich, N.A.; Subramanian, S.; Faith, J.J.; Gevers, D.; Gordon, J.I.; Knight, R.; Mills, D.A.; Caporaso, J.G. Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nat. Methods 2013, 10, 57–59. [Google Scholar] [CrossRef]
- Edgar, R.C. UPARSE: Highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 2013, 10, 996–998. [Google Scholar] [CrossRef]
- Team, R.D.C. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2018. [Google Scholar]
- Wang, Q.; Garrity, G.M.; Tiedje, J.M.; Cole, J.R. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 2007, 73, 5261–5267. [Google Scholar] [CrossRef]
- Pruesse, E.; Quast, C.; Knittel, K.; Fuchs, B.M.; Ludwig, W.G.; Peplies, J.; Glockner, F.O. SILVA: A comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res. 2007, 35, 7188–7196. [Google Scholar] [CrossRef]
- Kovatcheva-Datchary, P.; Nilsson, A.; Akrami, R.; Lee, Y.S.; De Vadder, F.; Arora, T.; Hallen, A.; Martens, E.; Björck, I.; Bäckhed, F. Dietary Fiber-Induced Improvement in Glucose Metabolism Is Associated with Increased Abundance of Prevotella. Cell Metab. 2015, 22, 971–982. [Google Scholar] [CrossRef]
- Leong, C.; Haszard, J.J.; Heath, A.M.; Tannock, G.W.; Lawley, B.; Cameron, S.L.; Szymlek-Gay, E.A.; Gray, S.R.; Taylor, B.J.; Galland, B.C.; et al. Using compositional principal component analysis to describe children’s gut microbiota in relation to diet and body composition. Am. J. Clin. Nutr. 2020, 111, 70–78. [Google Scholar] [CrossRef]
- Nutrition Society, T.C. Dietary Guidelines for Chinese Residents (2022); People’s Medical Publishing House: Beijing, China, 2022. [Google Scholar]
- De, F.F.; Pellegrini, N.; Vannini, N.; Jeffery, I.B.; La, S.A.; Laghi, L.; Serrazanetti, D.I.; Di, C.R.; Ferrocino, I. High-level adherence to a Mediterranean diet beneficially impacts the gut microbiota and associated metabolome. Gut 2016, 65, 1812–1821. [Google Scholar]
- Simpson, R.C.; Shanahan, E.R.; Batten, M.; Reijers, I.L.M.; Read, M.; Silva, I.P.; Versluis, J.M.; Ribeiro, R.; Angelatos, A.S.; Tan, J.; et al. Diet-driven microbial ecology underpins associations between cancer immunotherapy outcomes and the gut microbiome. Nat. Med. 2022, 28, 2344–2352. [Google Scholar] [CrossRef]
- Arifuzzaman, M.; Won, T.H.; Li, T.T.; Yano, H.; Digumarthi, S.; Heras, A.F.; Zhang, W.; Parkhurst, C.N.; Kashyap, S.; Jin, W.B.; et al. Inulin fiber promotes microbiota-derived bile acids and type 2 inflammation. Nature 2022, 611, 578–584. [Google Scholar] [CrossRef]
- Caio, G.; Lungaro, L.; Segata, N.; Guarino, M.; Zoli, G.; Volta, U.; De Giorgio, R. Effect of Gluten-Free Diet on Gut Microbiota Composition in Patients with Celiac Disease and Non-Celiac Gluten/Wheat Sensitivity. Nutrients 2020, 12, 1832–1855. [Google Scholar] [CrossRef]
- Chen, X.; Sun, H.; Jiang, F.; Shen, Y.; Wei, P. Alteration of the gut microbiota associated with childhood obesity by 16S rRNA gene sequencing. PeerJ 2020, 8, e8317. [Google Scholar] [CrossRef]
- Liu, Y.; Tan, Y.F.; Zhang, J.Y.; Yu, M.; Li, M.W.; Sun, F.; Zhang, Y.; Qi, W. Difference of gut microbiota in people with overweight/obese and normal weight. Chin. J. Clin. Res. 2022, 35, 21–24. [Google Scholar]
- De, F.C.; Cavalieri, D.; Paola, M.D.; Ramazzotti, M.; Poullet, J.B.; Massart, S.; Collini, S.; Pieraccini, G.; Lionetti, P. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc. Natl. Acad. Sci. USA 2010, 107, 14691–14696. [Google Scholar]
- Orlich, M.J.; Singh, P.N.; Sabaté, J.; Jaceldo-Siegl, K.; Fan, J.; Knutsen, S.; Beeson, W.L.; Fraser, G.E. Vegetarian Dietary Patterns and Mortality in Adventist Health Study 2. JAMA Intern. Med. 2013, 173, 1230–1238. [Google Scholar] [CrossRef]
- Tharrey, M.; Mariotti, F.; Mashchak, A.; Barbillon, P.; Delattre, M.; Fraser, G.E. Patterns of plant and animal protein intake are strongly associated with cardiovascular mortality: The Adventist Health Study-2 cohort. Int. J. Epidemiol. 2018, 47, 1603–1612. [Google Scholar] [CrossRef]
- Wu, G.D.; Compher, C.; Chen, E.Z.; Smith, S.A.; Shah, R.D.; Bittinger, K.; Chehoud, C.; Albenberg, L.G.; Nessel, L.; Gilroy, E.; et al. Comparative metabolomics in vegans and omnivores reveal constraints on diet-dependent gut microbiota metabolite production. Gut 2016, 65, 63–72. [Google Scholar] [CrossRef]
- Ley, R.E.; Turnbaugh, P.J.; Klein, S.; Gordon, J.I. Microbial ecology: Human gut microbes associated with obesity. Nature 2006, 444, 1022–1023. [Google Scholar] [CrossRef]
- Falalyeyeva, T.; Chornenka, N.; Cherkasova, L.; Tsyryuk, O.; Kobyliak, N. Gut Microbiota Interactions with Obesity. Ref. Modul. Food Sci. 2022, 147, 112678. [Google Scholar]
- Cao, S.Y.; Zhao, C.N.; Xu, X.Y.; Tang, G.Y.; Li, H.B. Dietary plants, gut microbiota, and obesity: Effects and mechanisms. Trends Food Sci. Technol. 2019, 92, 194–204. [Google Scholar] [CrossRef]
- Ley, R.E.; Bäckhed, F.; Turnbaugh, P.; Lozupone, C.A.; Knight, R.D.; Gordon, J.I. Obesity alters gut microbial ecology. Proc. Natl. Acad. Sci. USA 2005, 102, 11070–11075. [Google Scholar] [CrossRef] [PubMed]
- Grigor’Eva, I.N. Gallstone Disease, Obesity and the Firmicutes/Bacteroidetes Ratio as a Possible Biomarker of Gut Dysbiosis. J. Pers. Med. 2020, 11, 13. [Google Scholar] [CrossRef]
- Turnbaugh, P.J.; Ley, R.E.; Mahowald, M.A.; Magrini, V.; Mardis, E.R.; Gordon, J.I. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 2006, 444, 1027–1031. [Google Scholar] [CrossRef]
- Niu, J.; Cui, M.; Yang, Y.; Li, J.; Yao, Y.; Guo, C.; Lu, A.; Qi, X.; Zhou, D.; Zhang, C.; et al. Microbiota-derived acetate enhances host antiviral response via NLRP3. Nat. Commun. 2023, 14, 642. [Google Scholar] [CrossRef]
- Ilario, F.; Raffaella, D.C.; Maria, D.A.; Silvia, T. Fecal Microbiota in Healthy Subjects Following Omnivore, Vegetarian and Vegan Diets: Culturable Populations and rRNA DGGE Profiling. PLoS ONE 2015, 10, e128669. [Google Scholar]
- Carmen, L.; Eckert, E.M.; Eleonora, M.; Jorg, V.; Marzia, M.; Ilaria, P.; Andrea, D.C.; Veronica, C.; Federica, B.; Jakob, P. Assessing the Influence of Vegan, Vegetarian and Omnivore Oriented Westernized Dietary Styles on Human Gut Microbiota: A Cross Sectional Study. Front. Microbiol. 2018, 9, 317. [Google Scholar]
- Chelius, M.K.; Triplett, E.W. Immunolocalization of dinitrogenase reductase produced by Klebsiella pneumoniae in association with Zea mays L. Appl. Environ. Microbiol. 2019, 66, 783–787. [Google Scholar] [CrossRef] [PubMed]
- Xiao, T.; Liang, T.; Geng, D.; Wang, L.; Liu, L.; Zhou, X.; Pu, H.; Huang, J.; Zhou, S.; Tong, L. Correction to: Dietary Proteins Alter Fermentation Characteristics of Human Gut Microbiota In Vitro. Plant Foods Hum. Nutr. 2021, 77, 157–158. [Google Scholar] [CrossRef]
- Ogata, Y.; Suda, W.; Ikeyama, N.; Hattori, M.; Ohkuma, M.; Sakamoto, M.; Gill, S.R. Complete Genome Sequence of Phascolarctobacterium faecium JCM 30894, a Succinate-Utilizing Bacterium Isolated from Human Feces. Microbiol. Resour. Ann. 2019, 8, e01487-18. [Google Scholar] [CrossRef]
Characteristics | Total (n = 100) | Vegetarians (n = 36) | Omnivores (n = 64) | p |
---|---|---|---|---|
Age (years), mean ± SD | 32.8 ± 4.8 | 33.6 ± 5.1 | 32.3 ± 4.6 | 0.091 |
Height (cm), mean ± SD | 167.0 ± 7.4 | 165.0 ± 7.3 | 168.0 ± 7.2 | 0.086 |
Weight (kg), mean ± SD | 65.1 ± 5.9 | 59.5 ± 4.9 | 68.1 ± 6.3 | 0.051 |
BMI (kg/m2), mean ± SD | 23.1 ± 3.1 | 21.8 ± 2.5 | 23.8 ± 3.2 | 0.063 |
Male/Female | 48/52 | 16/20 | 32/32 | - |
Groups | Chao1 | Ace | Shannon | Simpson |
---|---|---|---|---|
V | 964.69 ± 134.63 * | 947.53 ± 98.65 * | 5.58 ± 0.01 * | 0.93 ± 0.01 |
R | 899.03 ± 151.82 | 880.33 ± 152.42 | 5.46 ± 0.58 | 0.91 ± 0.04 |
VN | 976.22 ± 235.67 a | 948.27 ± 227.49 a | 5.66 ± 0.72 a | 0.94 ± 0.05 a |
VO | 959.53 ± 134.63 b | 947.20 ± 98.65 a | 5.39 ± 0.01 bc | 0.92 ± 0.01 a |
RN | 949.34 ± 134.95 bc | 923.77 ± 130.16 a | 5.85 ± 0.51 a | 0.95 ± 0.03 a |
RO | 886.36 ± 174.57 d | 869.55 ± 180.84 b | 5.40 ± 0.63 b | 0.91 ± 0.05 a |
RC | 810.23 ± 40.35 e | 802.99 ± 44.57 c | 5.31 ± 0.04 bd | 0.89 ± 0.01 a |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Sun, C.; Li, A.; Xu, C.; Ma, J.; Wang, H.; Jiang, Z.; Hou, J. Comparative Analysis of Fecal Microbiota in Vegetarians and Omnivores. Nutrients 2023, 15, 2358. https://doi.org/10.3390/nu15102358
Sun C, Li A, Xu C, Ma J, Wang H, Jiang Z, Hou J. Comparative Analysis of Fecal Microbiota in Vegetarians and Omnivores. Nutrients. 2023; 15(10):2358. https://doi.org/10.3390/nu15102358
Chicago/Turabian StyleSun, Changbao, Ang Li, Cong Xu, Jiage Ma, Huan Wang, Zhanmei Jiang, and Juncai Hou. 2023. "Comparative Analysis of Fecal Microbiota in Vegetarians and Omnivores" Nutrients 15, no. 10: 2358. https://doi.org/10.3390/nu15102358
APA StyleSun, C., Li, A., Xu, C., Ma, J., Wang, H., Jiang, Z., & Hou, J. (2023). Comparative Analysis of Fecal Microbiota in Vegetarians and Omnivores. Nutrients, 15(10), 2358. https://doi.org/10.3390/nu15102358