Microbial communities play important roles in marine ecosystems, including broadly impacting food webs and biogeochemical cycles. To shed light on the functional roles of these communities, this project aims to develop computational tools to extract functional information from high-throughput genome sequence data, to model the geographic and environmental distributions of microbial functions, and to visually display global maps of marine microbial functional diversity through an Environmental Niche Atlas.
The goal of this project is to quantify patterns of functional diversity in marine microbial communities. We will do this by developing computational tools to catalog and estimate the global distributions of all microbial gene families and their associated functions from high-throughput sequence data. We have the following objectives:
- Build a database of gene families from sequenced genomes that is both more comprehensive than currently available resources and readily updated in response to the exponential increase in genomic data.
- Design a bioinformatics pipeline for identifying all representatives of these gene families in a metagenomic data set.
- Develop metrics to quantify gene family abundance, universality, and phylogenetic diversity from metagenomic data.
- Implement statistical models for predicting gene family diversity and distributions across the global marine environment and different environmental conditions.
- Draw maps of predicted global gene family distributions.
- Analyze metagenomic data from public databases and collaborators to identify diversity hotspots, pinpoint microbial biomarkers for sensitive environments, and uncover new associations between community gene functions and ecosystem properties.
We aim to characterize the physiology of microbial communities at marine sampling sites and to combine this information with environmental data to estimate global distributions for all microbial gene families. Comparison of our results with global taxonomic distributions will shed light on patterns of selection, convergent evolution, and lateral gene transfer. The resources from this project will generate testable hypotheses about the roles of microbial functions in ecosystem health, food webs, and biogeochemical cycles of different marine environments.
Castelle, C. J., L. A. Hug, K. C. Wrighton, B. C. Thomas, K. H. Williams, D. Wu, S. G. Tringe, S. W. Singer, J. A. Eisen, & J. F. Banfield. (2013). Extraordinary phylogenetic diversity and metabolic versatility in aquifer sediment. Nat Commun, 4, 2120. doi: 10.1038/ncomms3120
Jiang, X., M. G. Langille, R. Y. Neches, M. Elliot, S. A. Levin, J. A. Eisen, J. S. Weitz, & J. Dushoff. (2012). Functional biogeography of ocean microbes revealed through non-negative matrix factorization. PLoS One, 7(9), e43866. doi: 10.1371/journal.pone.0043866
Kembel, S.W., M. Wu, J. A. Eisen, & J.L. Green. (2012). Incorporating 16S Gene Copy Number Information Improves Estimates of Microbial Diversity and Abundance. PLoS Comput Biol, 8(10), e1002743. doi: 10.1371/journal.pcbi.1002743.g001
Ladau, J., T. J. Sharpton, M. M. Finucane, G. Jospin, S. W. Kembel, J. O'Dwyer, A. F. Koeppel, J. L. Green, & K. S. Pollard. (2013). Global marine bacterial diversity peaks at high latitudes in winter. ISME J, 7(9), 1669-1677. doi: 10.1038/ismej.2013.37
Rinke, C., P. Schwientek, A. Sczyrba, N. N. Ivanova, I. J. Anderson, J. F. Cheng, A. Darling, S. Malfatti, B. K. Swan, E. A. Gies, J. A. Dodsworth, B. P. Hedlund, G. Tsiamis, S. M. Sievert, W. T. Liu, J. A. Eisen, S. J. Hallam, N. C. Kyrpides, R. Stepanauskas, E. M. Rubin, P. Hugenholtz, & T. Woyke. (2013). Insights into the phylogeny and coding potential of microbial dark matter. Nature, 499(7459), 431-437. doi: 10.1038/nature12352
Sharpton, T.J., G. Jospin, D. Wu, Langille M.GI., K. Pollard, & J.A. Eisen. (2012). Sifting through genomes with iterative-sequence clustering produces a large, phylogenetically diverse protein-family resource. BMC Bioinformatics, 13(264). doi: 10.1186/1471-2105-13-264
Shih, P. M., D. Wu, A. Latifi, S. D. Axen, D. P. Fewer, E. Talla, A. Calteau, F. Cai, N. Tandeau de Marsac, R. Rippka, M. Herdman, K. Sivonen, T. Coursin, T. Laurent, L. Goodwin, M. Nolan, K. W. Davenport, C. S. Han, E. M. Rubin, J. A. Eisen, T. Woyke, M. Gugger, & C. A. Kerfeld. (2013). Improving the coverage of the cyanobacterial phylum using diversity-driven genome sequencing. Proc Natl Acad Sci U S A, 110(3), 1053-1058. doi: 10.1073/pnas.1217107110
Software and databases:
In Search of the Bacterial Garden of Eden - KQED Science
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