Chronic inflammatory diseases result from the interaction of genetic susceptibility factors and environmental factors, broadly defined as infectious, chemical, physical, nutritional, and behavioral factors. While major progress has been made in identifying genetic susceptibility factors, comparatively little is known about environmental risk factors or the forces that lead to variation in genetic susceptibility in nature. Within the body of a healthy individual, microbial cells are estimated to outnumber human cells by a factor of ten to one. Recent advances in the field of metagenomics have begun to define these microbial communities, but knowledge of their influence on immunity and susceptibility to disease remains in its infancy. Important questions remain regarding the extent to which the microbiota is influenced by genetic variation in the host genome and whether disease susceptibility may be mediated by the microbiota. We hypothesize that naturally occurring variation in the host genome influences the composition of the resident microbiota, and this in turn influences susceptibility to chronic inflammatory diseases. To test this hypothesis we will systematically manipulate the microbiota of genetically distinct mouse inbred strains that differ in susceptibility to chronic inflammatory diseases.
- to characterize the gut and skin microbiota that correlate with disease in models of chronic inflammation.
- to identify host genes influencing the composition of resident microbiota in the skin and gut.
- to culture and characterize microbial species influencing disease and determine their influence on the immune system
- to define the pathways involved in gene-microbiota interactions.
We have already fine-mapped microbial QTL down to an average of 4 Mb (e.g. Neisseria). To further reduce these fragments we will sequence the microbiota from additional AIL mice. Using this approach we are likely to reduce the QTLs to 1-2 Mb. We will then proceed to identify the putative candidate genes by targeted sequencing of the entire fragments in the parental strains. The expression of candidate genes will be examined in relevant tissues (immune cells, skin and gut epithelium). Depending on the gene in question, strategies to inactivate or overexpress it will be implemented.
- We will culture at least two OTUs with confirmed association to host genome variants in G4/G16. To further characterize the strains we will fully sequence their genomes using the Illumina MiSeq platform (see our published report Wang J et al. Genome Announc. 2014;2(1). pii: e01148-13).
- To confirm their role in disease, we will expose germ-free mice to bacterial communities differing in the presence/absence abundance of candidate bacteria, followed by disease induction. The same will be applied to knockout identified relevant genes. To confirm interaction, we will perform cross-fostering experiments under germ free conditions.
- To identify the potential pathways involved, we will perform a series of co-culture experiments involving immune cells isolated from control or mutant mice with and without candidate bacteria. The effect on cytokine production, cell death, activation, proliferation and gene expression will be evaluated.
The project is ideally suited for a Biologist/MD with a background or interest in microbiology, advanced molecular genetics or computational biology.
1- A diversity profile of the human skin microbiota. Grice EA, Kong HH, Renaud G, Young AC; NISC Comparative Sequencing Program, Bouffard GG, Blakesley RW, Wolfsberg TG, Turner ML, Segre JA. Genome Res. 2008 Jul;18(7):1043-50. Epub 2008 May 23. PMID: 18502944
2- Individuality in gut microbiota composition is a complex polygenic trait shaped by multiple environmental and host genetic factors. Benson AK, Kelly SA, Legge R, Ma F, Low SJ, Kim J, Zhang M, Oh PL, Nehrenberg D, Hua K, Kachman SD, Moriyama EN, Walter J, Peterson DA, Pomp D. Proc Natl Acad Sci U S A. 2010 Nov 2;107(44):18933-8. Epub 2010 Oct 11. PMID: 20937875
3- Srinivas G, Möller S, Wang J, Künzel S, Zillikens D, Baines JF, Ibrahim SM. Genome-wide mapping of gene–microbiota interactions in susceptibility to autoimmune skin blistering. Nature Communications, 2013; 4 DOI: 10.1038/ncomms3462