The microbes that live in the human gut microbiota possess novel and ill-defined metabolic capabilities. Many of the metabolites produced by this microbial ecosystem are absorbed by the human host and ultimately excreted by the kidneys. Such solutes accumulate when the kidneys fail and comprise a significant portion of the """"""""uremic"""""""" solutes found at very high level in the plasma of patients maintained on dialysis. p-cresol sulfate (PCS), indoxyl sulfate (IS), and trimethylamine-N-oxide (TMAO) are three prominent uremic solutes that depend upon microbial metabolism of diet-derived molecules. Each exhibits inter-individual variability in the quantities produced, suggesting that microbiotas differ in their ability to produce these molecules. PCS and IS have been associated with poor outcomes in renal patients and TMAO has been linked to cardiovascular events in humans. The ultimate goal of this research is to understand how the human gut microbiota may be modulated to decrease the production of these compounds. The main objectives are to elucidate (i) the microbial genes and species that are the key contributors to PCS, IS, and TMAO production;(ii) the impact of diet on the production of these solutes;and (iii) the best method for reprogramming a high-producing microbiota to a low-producing phenotype via administration of other gut-derived species.
In Aim 1 a new machine learning software, ClusterFinder, will be used to query ~900 sequenced gut microbiota genomes to predict genes and gene cassettes that contribute to PCS, IS, or TMAO generation. Predictions will be validated in pure culture and in vivo, using a gnotobiotic mouse model in single and multiple species colonizations. Gene predictions will be genetically validated using gene deletion or heterologous expression.
In Aim 2 healthy omnivorous humans with stable high and low urinary TMAO, PCS and IS production will be identified. Microbiome-encoded genes and taxa associated with solute production phenotypes will be determined by analyzing stool samples for these individuals using 16S rRNA-based microbiota enumerations, metagenomics, and metatranscriptomics.
Aim 3 will address whether diet affects the production of TMAO, PCS, or IS using either gnotobiotic mice colonized with bacterial consortia validated in Aim 1, and a humanized mouse model, consisting of ex-germ-free mice colonized with the human fecal microbiota identified in Aim 2 of high- and low-producers of TMAO, PCS, or IS. Diets will include high vs. low fiber, high vs. low protein, or L-carnitine supplemented vs. vegetarian. Decreases in TMAO, PCS and/or IS production will be associated with changes in microbiota composition and function.
Aim 4 will identify the most effective method for microbiota reprogramming in humanized mice to decrease TMAO, PCS and IS production using transplants of an intact microbiota, donor microbiota generated culture collections, or type strain representatives. The use of antibiotics before transplant and the influence of dietary reinforcement will be tested as methods of aiding microbiota reprogramming.

Public Health Relevance

A vast and diverse community of microbes known as the gut microbiota colonizes the human intestine. The microbiota is largely a beneficial community, but also produces some potentially toxic compounds that can accumulate to high levels in the circulation of dialysis patients. This proposal defines how diet contributes to the production of these compounds and how the microbiota can be rationally altered to produce less of these compounds.

National Institute of Health (NIH)
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Research Project (R01)
Project #
Application #
Study Section
Gastrointestinal Mucosal Pathobiology Study Section (GMPB)
Program Officer
Kusek, John W
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Stanford University
Schools of Medicine
United States
Zip Code
Devlin, A Sloan; Marcobal, Angela; Dodd, Dylan et al. (2016) Modulation of a Circulating Uremic Solute via Rational Genetic Manipulation of the Gut Microbiota. Cell Host Microbe 20:709-715
Fischbach, Michael A; Segre, Julia A (2016) Signaling in Host-Associated Microbial Communities. Cell 164:1288-300
Meyer, Timothy W; Lenihan, Colin R (2015) Glomerular Effects of Age and APOL1. J Am Soc Nephrol 26:2901-3
Medema, Marnix H; Fischbach, Michael A (2015) Computational approaches to natural product discovery. Nat Chem Biol 11:639-48
Donia, Mohamed S; Fischbach, Michael A (2015) HUMAN MICROBIOTA. Small molecules from the human microbiota. Science 349:1254766
Donia, Mohamed S; Cimermancic, Peter; Schulze, Christopher J et al. (2014) A systematic analysis of biosynthetic gene clusters in the human microbiome reveals a common family of antibiotics. Cell 158:1402-14