Just as every human genome is unique, so too is the community of microbial populations that reside within and on the human body. This dynamic community - the microbiome - complements the human genome to maintain health by synthesizing vitamins, assisting in digestion, educating the immune system, and providing colonization resistance to pathogens. Although it is widely accepted that this microbial community is critical to maintaining health and that disturbances to the community induced through antibiotics or stress can facilitate disease, there is a general lack of understanding with regards to the ecological principles and specific mechanisms that shape host-associated communities. Toward this goal it is critical to develop a quantitative framework for describing the role of biodiversity in shaping and maintaining the stability of host-associated communities. The objective of this proposal is to evaluate and model the relationships between the diversity of the microbiota and its stability in host-associated microbial communities. The central hypothesis for the proposed research is that increased diversity within the gut microbiome will result in greater community-level stability, but less population-level stability. The rationale for this hypothesis comes from observations in the field of landscape ecology that variation in total plant biomass production is reduced in high diversity ecosystems, but the variation in biomass of individual plant populations is not stabilized by diversity. This hypothesis will be tested by generating mouse-associated microbial communities with varying levels of diversity that will be used to assess and mathematically model changes in the gut community using a combination of 16S rRNA and random sequencing approaches.
The specific aims of the proposed research are to 1) model the """"""""normal"""""""" mouse-associated microbial community;2) measure the effects of taxonomic diversity on stability;and 3) assess the effects of functional diversity on stability. Te combination of ecological and mathematical tools will provide a strong theoretical basis to understand the dynamics of host-associated microbial communities. These innovative studies will assess the level of variation between individual mice where factors such as genetics, diet, environment, age, and sex are controlled. The proposed research will have a significant impact on our understanding of host-associated microbial communities because for the first time, we will be able to measure and model the normal variation in the composition and function of the microbiome. Furthermore, the principles and ecological modeling that is pursued in the proposed research will impact our understanding of health and disease in humans.

Public Health Relevance

Fluctuations in the structure and function of the microbial communities associated with humans are known to affect health and disease. The proposed research will have a significant impact on public health by providing a quantitative framework that can be used to make predictions regarding the effects of antibiotics and pathogens on health.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM099514-01
Application #
8211723
Study Section
Special Emphasis Panel (ZGM1-GDB-2 (MC))
Program Officer
Sledjeski, Darren D
Project Start
2012-02-01
Project End
2016-01-31
Budget Start
2012-02-01
Budget End
2013-01-31
Support Year
1
Fiscal Year
2012
Total Cost
$362,211
Indirect Cost
$110,134
Name
University of Michigan Ann Arbor
Department
Microbiology/Immun/Virology
Type
Schools of Medicine
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Jenior, Matthew L; Leslie, Jhansi L; Young, Vincent B et al. (2017) Clostridium difficile Colonizes Alternative Nutrient Niches during Infection across Distinct Murine Gut Microbiomes. mSystems 2:
Zackular, Joseph P; Baxter, Nielson T; Chen, Grace Y et al. (2016) Manipulation of the Gut Microbiota Reveals Role in Colon Tumorigenesis. mSphere 1:
Baxter, Nielson T; Ruffin 4th, Mack T; Rogers, Mary A M et al. (2016) Microbiota-based model improves the sensitivity of fecal immunochemical test for detecting colonic lesions. Genome Med 8:37
Baxter, Nielson T; Koumpouras, Charles C; Rogers, Mary A M et al. (2016) DNA from fecal immunochemical test can replace stool for detection of colonic lesions using a microbiota-based model. Microbiome 4:59
Schloss, Patrick D; Girard, Rene A; Martin, Thomas et al. (2016) Status of the Archaeal and Bacterial Census: an Update. MBio 7:
Rogers, M A M; Aronoff, D M (2016) The influence of non-steroidal anti-inflammatory drugs on the gut microbiome. Clin Microbiol Infect 22:178.e1-178.e9
Schubert, Alyxandria M; Sinani, Hamide; Schloss, Patrick D (2015) Antibiotic-Induced Alterations of the Murine Gut Microbiota and Subsequent Effects on Colonization Resistance against Clostridium difficile. MBio 6:e00974
Baxter, Nielson T; Wan, Judy J; Schubert, Alyxandria M et al. (2015) Intra- and interindividual variations mask interspecies variation in the microbiota of sympatric peromyscus populations. Appl Environ Microbiol 81:396-404
Koenigsknecht, Mark J; Theriot, Casey M; Bergin, Ingrid L et al. (2015) Dynamics and establishment of Clostridium difficile infection in the murine gastrointestinal tract. Infect Immun 83:934-41
Schubert, Alyxandria M; Rogers, Mary A M; Ring, Cathrin et al. (2014) Microbiome data distinguish patients with Clostridium difficile infection and non-C. difficile-associated diarrhea from healthy controls. MBio 5:e01021-14

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