Dr. Thomas Sharpton, Assistant Professor
Research Interests: Microbiome Ecology, Evolution, and Function
Dr. Thomas Sharpton’s research is broadly directed towards ascertaining how commensal microbiota and their genomic characteristics (i.e., the microbiome) relate to health. His laboratory specializes in the development and application of high-throughput computational and statistical tools that characterize microbiome biology, and investigates how microbiomes are distributed across space, time, and host physiology. The Sharpton lab aims to develop testable hypotheses about how hosts and their microbiome interact, and strives to understand the evolutionary and ecological processes that influence community assembly, maintenance, and function within a host. Ultimately, this knowledge will be used to discover disease mechanisms, identify predicative and diagnostic biomarkers of disease, and develop tools to treat disease through manipulation of the microbiome. All of the data resources and software that his lab develops are freely available.
Dr. Sharpton has spent many years conducting bioinformatic investigations of host-microbe interactions. As a Ph.D. student at the University of California, Berkeley, he conducted comparative genomic investigations of pathogenic fungi to identify evolutionary and ecological processes that contribute to human disease. His postdoctoral research at the J. David Gladstone Institutes focused on the development and application of high-throughput computational procedures and data resources to characterize the diversity of microbiomes from metagenomic data. While there, he developed several novel bioinformatics algorithms and data resources (e.g., PhylOTU, the Sifting Families database, shotmap), which he has used to explore the diversity and function of various microbiomes, especially those associated with the global ocean and the human body.
Current research in the Sharpton lab includes the development of bioinformatics tools that improve the analysis of microbiome function, investigations into the relationship between gut microbiome diversity and inflammatory bowel disease, and characterization of the composition of the oral microbiome associated with ancient human populations (e.g., the Khoesan) to ascertain how humans and their microbiomes have coevolved.
Foster, Z.S., Sharpton, T.J., and Grünwald, N.J. 2017. Metacoder: An R package for visualization and manipulation of community taxonomic diversity data. PLoS Comput Biol. 13(2):e1005404. doi: 10.1371/journal.pcbi.1005404.
Conley, M.N., Wong, C.P., Duyck, K.M., Hord, N., Ho, E., and Sharpton, T.J. 2016. Aging and serum MCP-1 are associated with gut microbiome composition in a murine model. PeerJ. PMID 27069796.
Gaulke, C.A., Barton, C.L., Proffitt, S., Tanguay, R.L., and Sharpton, T.J. 2016. Triclosan Exposure Is Associated with Rapid Restructuring of the Microbiome in Adult Zebrafish. PLoS One. PMID 27191725
Kent, M.L., Watral, V.G., Kirchoff, N.S., Spagnoli, S.T., and Sharpton, T.J. 2016. Effects of subclinical Mycobacterium chelonae infections on fecundity and embryo survival in zebrafish. Zebrafish PMID 27031171.
Nayfach, S., Bradley, P.H., Wyman, S.K., Laurent, T.J., Williams, A., Eisen, J.A., Pollard, K.S., and Sharpton, T.J. 2015. Automated and accurate estimation of gene family abundance from shotgun metagenomes. PLoS Comput. Biol. 11(11)e1004573.
Sharpton, T.J. and Gaulke, C.A. 2015. Modeling the context-dependent associations between the gut microbiome, its environment, and host health. MBio. 6(5):e01367-15. doi:10.1128.
O'Dwyer J.P., Kembel, S.W. and Sharpton, T.J. 2015. Backbones of evolutionary history test biodiversity theory for microbes. Proc. Natl. Acad. Sci., 112(27):8356-61.
Quandt, C.A., Kohler, A., Hesse, C.N., Sharpton, T.J., Martin, F. and Spatafora, J.W. 2015. Metagenome sequence of Elaphomyces granulatus from sporocarp tissue reveals Ascomycota ectomycorrhizal fingerprints of genome expansion and a Proteobacteria-rich microbiome. Environ. Microbiol. 17(8):2952-68.
Skewes-Cox, P., Sharpton, T.J., Ruby, J.G., Pollard, K.S., and DeRisi, J.L. 2014. Profile hidden Markov models for the detection of viruses within metagenomic sequence data. PLOS ONE. 9(8):e105067.
Sharpton, T.J. 2014. An introduction to the analysis of shotgun metagenomic data. Frontiers in Plant Genetics and Genomics. 16(5):209.
Kent, M.L., Soderlund, K., Thomann, E., Schreck, C.B., and Sharpton, T.J. 2014. Post-mortem sporulation of Ceratomyxa shasta (myxozoa) after death in adult chinook salmon. J. Parisitol. PMID: 24725089.
Kidd, J.M., Sharpton, T.J., Bobo, D., Norman, P.J., Martin, A.R., Carpenter, M.L., Sikora, M.,Gignoux, C.R., Nemat-Gorgani, N., Adams, A., Guadalupe, M., Guo, X., Feng, Q., Li, Y., Liu, X., Parham, P., Hoal, E.G. Feldman, M.W., Pollard, K.S., Wall, J.D., Bustamante, C.D. and Henn, B.M. 2014. Exome capture from saliva produces high quality genomic and metagenomic data. BMC Genomics 4(15):262.
Finucane, M.M., Sharpton, T.J., Laurent, T.J., Pollard, K.S. A taxonomic signature of obesity in the microbiome? Getting to the guts of the matter. 2014. PLOS ONE. 8;9(1):e84689.
Ladau, J., Sharpton, T.J., Jospin, G., Kembel, S.W., O'Dwyer, J.P., Koeppel, A., Green, J.L., and Pollard, K.S. 2013. Global marine bacterial diversity peaks at high latitudes in winter. Intl. Soc. of Microbial Ecology J., March 1, DOI:10.1038/ismej.2013.37. PMC Journal, in process.
Wylie, K.M., Truty, R.M., Sharpton, T.J., Mihindukulasuriya, K.A., Zhou, Y., Gao, H., Sodergren, E., Weinstock, G.M., Pollard, K.S. and Pollard, K.S. 2012. Novel bacterial taxa in the human microbiome. PLoS ONE, 7(6):e3529. PMCID:PMC3374617.
The Human Microbiome Project Consortium. 2012. A framework for human microbiome research. Nature, 486:215-221. PMCID:PMC3377744.
The Human Microbiome Project Consortium. 2012. Structure, function and diversity of the human microbiome in an adult reference population. Nature, 486:207-214. PMCID:PMC3564958.
Sharpton, T.J., Jospin, G., Wu, D., Langille, M., Pollard, K.S. and Eisen, J.A. 2012. Sifting through genomes with iterative-sequence clustering produces a large, phylogentically diverse protein-family resource. BMC Bioinformatics, 13:264.
Whiston, E., Wise, H.-Z., Jui, G., Sharpton, T.J., Cole, G.T., Tayor, J.W. 2012. Comparative transcriptomics of the saprobic and parasitic growth phases in Coccidioides spp. PLoS One, 7:e41034.
Sharpton, T.J., Riesenfed, S.J., Kembel, S.W., Ladau, J., O’Dwyer, J.P., Green, J.L., Eisen, J.A. and Pollard, K.S. 2011. PhylOTU: A high-throughput procedure quantified microbial community diversity and resolves novel taxa from metagenomic data. PLoS Comput. Biol. , 7(1):e1001061. Doi:10.1371/ Journal.pcbi1001061.
Neafsey, D.E., Barker, B.M., Sharpton, T.J. Stajich, J.E., Park, D. et al. 2010. Population genomic sequencing of Coccidiodes fungi reveals recent hybridization and transposon control. Genome Research 20:938-946.
Sharpton, T.J., Stajich, J.E., Rounsley, S.D., Gardner, M.J., Wortman, J.R., Jordar, V.S., Maiti, R., Kodira, C.D., Neafsey, D.E., Zeng, Q., Hung, C., McMahan, C., Muszewska, A., Grynberg, M., Mandel, A., Kellner, E.M., Barker, B.M., Galgiani, J.N., Orbach, M.J., Kirkland, T.N., Cole, G.T., Henn, M.R., Birren, B.W. and Taylor, J.W. 2009. Comparative genomic analyses of the human fungal pathogens Cocciodioides and their relatives. Genome Research, 19(10):1722-1731.
Sharpton, T.J., Neafsey, D.E., Galagan, J.E. and Taylor, J.W. 2008. Mechanisms of intron gain and loss in Cryptococcus. 2008. Genome Biology, 9:R24; doi:10.1186/gb-2008-9-1-r24.
Sharpton, T.J. and Jhaveri, A.J. 2006. Leveraging the knowledge of our peers: Online communities hold the promise to enhance scientific research. PLOS Biology, 4(6):904-905.