Overview of the gut microbiome
Recent technological advancements allow us to explore, at new depths, the relationship between us as hosts and our intestinal microbes. As discussed by Staley et al.,1 developing a meaningful understanding of the dynamics of the gut microbiome requires viewing the microbiome as an ecosystem where the microbes interact with, and relate to, one another in complex ways. This approach resists the simple classification of microbes as “good” or “bad”. Furthermore, when understood as a dynamic community, it places an emphasis on moving beyond composition to include measures of functionality. The most common measure of microbial composition utilizes the 16s rRNA amplicon sequencing technique. Approaches to measure the function of the gut microbiome range from shotgun metagenomics, which provides a measure of functional genes, to metabolomics, which is a direct measure of a given metabolite of interest. Investigators studying the gut microbiome often utilize a combination of techniques that incorporate measures of both composition and function.1
Role of the microbiome in health and disease
The gut microbiome is increasingly understood to play an important role in health and disease. It has been implicated in conditions including inflammatory bowel disease,2 cardiovascular disease,3 neurodegenerative disorders,4 and frailty.5 Additionally, investigators have recently utilized fecal metagenomes to develop the Gut Microbiome Health Index (GMHI), which is being studied for its capacity to independently predict presence of disease based on prevalence of certain microbial species.6
Most of our understanding of the health impact of the microbiome comes from cross-sectional observational studies, thus causality cannot be established. However, direct evidence for the role of the microbiome in disease pathogenesis and its role as a therapeutic target is being obtained in a growing list of conditions based on microbiota transplant therapy (MTT) intervention trials.7-9 The wide application of MTT-based clinical trials only recently became feasible following development of an oral-encapsulated MTT product.10 As investigators continue to unlock the potential of this therapy, it is reasonable to assume that diet will play a critical role in optimizing outcomes given the impact of diet on nutrient flow to the gut microbes.11
Effect of diet on the microbiome
Diet impacts the composition and function of the microbiome by serving as a source of exogenous substrates for the gut microbiota.12 Tanes et al. demonstrate the negative effects of altering this nutrient flow with use of a fiber-free diet.13 Another example of the impact of limiting nutrient flow is observed with exclusive meal replacement shake intake and decreased stability of the microbiome in healthy individuals.14 Microbiome stability and resilience are 2 important features of microbiome health, where stability is a measure of day-to-day variation and resilience a measure of the ability of the microbiome to recover following a perturbation.15 In direct contrast to these findings in healthy individuals is the use of exclusive enteral nutrition (EEN) as an effective therapy for Crohn’s disease.16 The mechanism of action of EEN in Crohn’s disease has not been fully elucidated, but changes to the microbiome have been hypothesized to contribute to its efficacy.17 Ultimately, however, these contrasting results underscore the need to develop a deeper understanding of the personalized nature of microbiome response to diet.
The individualized response of the fecal gut microbiota to diet has been shown to occur at the level of both taxonomic composition14 and function.18 In some instances, predicting expected response to diet is as simple as whether or not an individual harbors microbes capable of performing specific functions, as seen with methane production.19 In this instance, the presence or absence of methanogens dictates whether methane can be produced. However, the property of functional redundancy makes it challenging to predict microbiome response to diet as multiple microbes are capable of performing the same function.20 While this research is still in its early stages, the presence of individualized responses to diet offers an opportunity to one day utilize microbiome characteristics for microbiome-based personalized nutrition recommendations.
Typical design of and recommendations for designing and conducting diet-microbiome studies in humans
Given the personalized nature of microbiome and diet response, it can be challenging to capture diet-microbiome interactions with traditional cross-sectional study designs. Cross-sectional studies remain a valuable tool in the diet-microbiome space, but they can only identify associations. The complex nature of diet-microbiome interactions requires certain considerations when designing diet-microbiome intervention studies. In fact, because of the importance of trial design in advancing the understanding of diet-microbiome interactions, several reviews have been published on this topic to help improve and advance diet-microbiome research.21, 22 In general, a longitudinal, cross-over study design is preferred due to the individualized nature of diet-microbiome interactions. In addition, timing of dietary intake collection and stool sample collection are of particular importance. In order to optimize timing between dietary intake and stool sample collection, Johnson et al. proposed collection of consecutive days of dietary intake data and stool samples in a staggered and overlapping fashion at relevant timepoints.21
Another challenge researchers are working to address is how to best quantify substrate availability (i.e., nutrient flow) to the microbes. Traditionally, nutrient composition of the diet (e.g., grams protein, carbohydrate, fiber) has been used to quantify dietary intake. However, traditional nutrient composition doesn’t account for variability in intake of specific foods or the impact of the food matrix on digestibility (i.e., what reaches the colonic microbes).23 As an alternative to traditional quantification of nutrients in diet-microbiome studies, Johnson et al. developed methodology to utilize food choices, which proved to be a more sensitive measure of diet variability compared to nutrient analysis.14 This approach may capture food characteristics that are overlooked at the nutrient level, but more work is needed to understand the best approach to quantifying substrate availability to the microbes.
The gut microbiome is a metabolically active symbiont that is increasingly understood to play an important role in health and disease. Diet serves as a primary source of substrate for the microbes, capable of modifying its composition and function. Response to diet, however, is highly individualized. While this presents a formidable challenge to researchers, it lays the foundation for a future that includes microbiome-based, personalized nutrition.
1. Staley C, Kaiser T, Khoruts A. Clinician Guide to Microbiome Testing. Digestive Diseases and Sciences. 2018;63(12):3167-3177.
2. Nishida A, Inoue R, Inatomi O, Bamba S, Naito Y, Andoh A. Gut microbiota in the pathogenesis of inflammatory bowel disease. Clin J Gastroenterol. Feb 2018;11(1):1-10.
3. Witkowski M, Weeks TL, Hazen SL. Gut Microbiota and Cardiovascular Disease. Circ Res. Jul 31 2020;127(4):553-570.
4. Mulak A, Bonaz B. Brain-gut-microbiota axis in Parkinson's disease. World J Gastroenterol. Oct 7 2015;21(37):10609-10620.
5. Haran JP, McCormick BA. Aging, Frailty, and the Microbiome-How Dysbiosis Influences Human Aging and Disease. Gastroenterology. Jan 2021;160(2):507-523.
6. Gupta VK, Kim M, Bakshi U, Cunningham KY, Davis JM, Lazaridis KN, et al. A predictive index for health status using species-level gut microbiome profiling. Nature Communications. 2020;11(1).
7. Hamazaki M, Sawada T, Yamamura T, Maeda K, Mizutani Y, Ishikawa E, et al. Fecal microbiota transplantation in the treatment of irritable bowel syndrome: a single-center prospective study in Japan. BMC Gastroenterology. 2022;22(1).
8. Wu Z, Zhang B, Chen F, Xia R, Zhu D, Chen B, et al. Fecal microbiota transplantation reverses insulin resistance in type 2 diabetes: A randomized, controlled, prospective study. Front Cell Infect Microbiol. 2022;12:1089991.
9. Kang DW, Adams JB, Gregory AC, Borody T, Chittick L, Fasano A, et al. Microbiota Transfer Therapy alters gut ecosystem and improves gastrointestinal and autism symptoms: an open-label study. Microbiome. Jan 23 2017;5(1):10.
10. Staley C, Hamilton MJ, Vaughn BP, Graiziger CT, Newman KM, Kabage AJ, et al. Successful Resolution of Recurrent Clostridium difficile Infection using Freeze-Dried, Encapsulated Fecal Microbiota; Pragmatic Cohort Study. Am J Gastroenterol. Jun 2017;112(6):940-947.
11. Khoruts A. Can FMT Cause or Prevent CRC? Maybe, But There Is More to Consider. Gastroenterology. Oct 2021;161(4):1103-1105.
12. Teigen LM, Geng Z, Sadowsky MJ, Vaughn BP, Hamilton MJ, Khoruts A. Dietary Factors in Sulfur Metabolism and Pathogenesis of Ulcerative Colitis. Nutrients. Apr 25 2019;11(4).
13. Tanes C, Bittinger K, Gao Y, Friedman ES, Nessel L, Paladhi UR, et al. Role of dietary fiber in the recovery of the human gut microbiome and its metabolome. Cell Host & Microbe. 2021;29(3):394-407.e395.
14. Johnson AJ, Vangay P, Al-Ghalith GA, Hillmann BM, Ward TL, Shields-Cutler RR, et al. Daily Sampling Reveals Personalized Diet-Microbiome Associations in Humans. Cell Host & Microbe. 2019;25(6):789-802.e785.
15. Fassarella M, Blaak EE, Penders J, Nauta A, Smidt H, Zoetendal EG. Gut microbiome stability and resilience: elucidating the response to perturbations in order to modulate gut health. Gut. Mar 2021;70(3):595-605.
16. Melton SL, Taylor KM, Gibson PR, Halmos EP. Review article: Mechanisms underlying the effectiveness of exclusive enteral nutrition in Crohn's disease. Aliment Pharmacol Ther. May 2023;57(9):932-947.
17. Gatti S, Galeazzi T, Franceschini E, Annibali R, Albano V, Verma AK, et al. Effects of the Exclusive Enteral Nutrition on the Microbiota Profile of Patients with Crohn's Disease: A Systematic Review. Nutrients. Aug 4 2017;9(8).
18. Teigen L, Mathai PP, Lopez S, Matson M, Elkin B, Kozysa D, et al. Differential hydrogen sulfide production by a human cohort in response to animal- and plant-based diet interventions. Clin Nutr. Jun 2022;41(6):1153-1162.
19. Teigen L, Mathai PP, Matson M, Lopez S, Kozysa D, Kabage AJ, et al. Methanogen Abundance Thresholds Capable of Differentiating In Vitro Methane Production in Human Stool Samples. Dig Dis Sci. Nov 2021;66(11):3822-3830.
20. Tian L, Wang XW, Wu AK, Fan Y, Friedman J, Dahlin A, et al. Deciphering functional redundancy in the human microbiome. Nat Commun. Dec 4 2020;11(1):6217.
21. Johnson AJ, Zheng JJ, Kang JW, Saboe A, Knights D, Zivkovic AM. A Guide to Diet-Microbiome Study Design. Front Nutr. 2020;7:79.
22. Shanahan ER, McMaster JJ, Staudacher HM. Conducting research on diet-microbiome interactions: A review of current challenges, essential methodological principles, and recommendations for best practice in study design. J Hum Nutr Diet. Aug 2021;34(4):631-644.
23. Aguilera JM. The food matrix: implications in processing, nutrition and health. Critical Reviews in Food Science and Nutrition. 2019;59(22):3612-3629.