Rationale – The mammalian gastrointestinal (GI) tract contains hundreds of distinct species of commensal microbes under normal conditions, referred to as the ‘microbiota’. Recently, it has been appreciated that the microbiota exists in a mutualistic relationship with the host immune system. Mutations affecting the production of certain cytokines or resulting in the lack of immune cell subsets are known to increase the overall bacterial burden; however, how underlying immunological conditions influence the colonization of specific species of commensal microbes is poorly understood. PhyloChip, a recently innovated DNA microarray, is able to rapidly identify over 60,000 microbial taxa in samples of interest. Using this techonology, we can ascertain the exact effects of diverse immunological phenotypes on the microbiota of the GI tract. Currently, these chips are used extensively at UCSF by the lab of Susan Lynch, though their use has thus far been limited to particular diseases and related environmental studies. We believe that the development of a microbial database encompassing many different immunological states is necessary to better understand the true relationship between GI microbiota and the host immune system. Our first aim is to dissect the unique feature of the ‘microbial profile’ (fluctuation of specific microbial species) in fecal samples obtained from various mouse models of disease including: virus infection, malignancy, arthritis, colitis, asthma, dermatitis and diabetes, as well as genetically modified mice with impairments in immune factors such as cytokines, chemokines, transcription factors and variety of immune receptors (a vast number of them are available in the UCSF mouse inventory). Second, we will compile this information and build the Microbial Database as a web-based open resource for the scientific community. Gathering a microbial profile from each disease state or immunological phenotype will allow us to predict the impact of immune perturbations on the specific make-up of the microbiota and the potential impact on disease. This project is also an attempt to investigate the potential of PhyloChip as a novel diagnostic and prophylactic tool.
Plan – We propose following step1 to 3 to accomplish this pilot study.
Step1 - Standardize the sample collection. The use of mice provides some stability in terms of mouse to mouse variation. However, commensal microbiota is very sensitive to age, sex, diet and the environment in each animal facility. To minimize these confounding effects, we will employ co-housing method. The mice of interest (designated as tester mice which are genetically modified or disease mice) will be housed in the same cage with control mice (which are wild-type B6 mice raised in our animal facility). In the case of infectious disease models, tester mice will be orally administered with the feces homogenate collected from control mice before infection. This method will equilibrate the microbiota in gastrointestinal tract and allow us to dissect the pure influence of specific gene or disease on the colonization of microbial species.
Step2 - Analyze by PhyloChip. As a pilot experiment, we will collect fecal samples from 20~30 of the most commonly used genetically-modified mice maintained in our lab or available in UCSF mouse inventory (Rag1-/-, Rag2Il2rg-/-, mMt, b2m-/-, MHCII-/-, Tcra-/-, Tcrg-/-, Lta-/-, Fas-/-, Cd28-/-, Dap10-/-, Dap12-/-, Myd88-/-, Trif-/-, Ifnar1-/-, Il2-/-, Il4-/-, Il6-/-, Il10-/-, Il12rb-/-, Il15-/-, Il17ra-/-, Foxp3-DTR) and major experimental disease models studied in our lab or neighbor labs (Carcinogen-induced tumor, Experimental colitis, Type I diabetes, Listeria infection, Cytomegalovirus infection, Influenza infection, OVA-induced asthma). All samples will be processed by PhyloChip and we will perform comparative and phylogenetic analysis to reveal the effect of immunity on the all level of microbe’s taxon.
Step3 - Build pilot database. All accumulated data will be computationally reconstituted. We aim to build the data browser with which users can interactively explore the microbiota profile for particular gene or disease.
Criteria and Metrics for success – 1) Identification of the unique microbial profile in each sample. 2) Launch microbial database. We will share our data with other researchers all over the world who are interested in the microbiology and immunology, and will accept their feedback and suggestions to improve user-friendliness. Once these criteria are met, we will move to scale up the size of database. We will collect samples from another ~50 genetically-modified mouse strains and accept samples from other collaborators. Ultimately, our approach can be applied into human diseases.
Estimated cost - We are requesting $40,000 for a pilot study (Step1 and 2). To build-up public database, we will need $30,000. For scale-up database, it will need $30,000.
Collaborators - Shoko Iwai (Susan Lynch lab, Dept. of Medicine)
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