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Eric Allen e-mail: eallen@ucsd.edu |
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Research in our laboratory centers upon the use of environmentally-derived genome sequence information to explore the genetic potential, ecology, and evolution of environmental microbial populations. The nature of this work relies equally upon field-based collections, bioinformatics (genome assembly, annotation, and comparative analyses) and the tools of molecular ecology and genetics. Together, these approaches enable us to utilize environmental genome sequence data to understand natural microbial phenomena including environmental adaptation, evolutionary processes, lateral gene transfer events, biogeographical patterning, biogeochemical cycling, microbial interactions, and in situ metabolic activity.
Current investigations include exploring the genetic composition of microbial populations (Archaea & Bacteria) inhabiting hypersaline environments via cultivation- independent genomic approaches ("metagenomics"). Our primary study site for this project is a hypersaline lake system in NW Victoria, Australia (near the town of Sea Lake approx. 370 km NW of Melbourne). With over 1 billion bases (>1 Gbp) of environmental genome sequence data generated, near complete and complete genome sequences for resident microbial populations can be analyzed in the absence of cultivation requirements. Such a data set uniquely allows analysis of population structure (allelic variation) thus providing insight into natural mechanisms of genomic heterogeneity, diversification, and environmental selection. Additional projects are aiding in the analysis of various marine microbial metagenomic projects including the J. Craig Venter Institute's Global Ocean Sampling (GOS) expedition.
An omnipresent facet of the research in our laboratory is the use of genome sequence information (environmental or isolate-derived) to expand our understanding of microbial physiology and its relationship to environmental adapation and ecosystem function. Abiding by this paradigm, additional projects underway in our laboratory include:
Ecology & evolution of microbial polyunsaturated fatty acid biosynthesis
Biological controls on Hg methylation in marine & estuarine sediments
Analysis of microbial & meiofaunal diversity at the Land/Sea Interface
Allen EE, Bartlett DH. (1999) Monounsaturated but not polyunsaturated fatty acids are required for growth of the deep-sea bacterium Photobacterium profundum SS9 at high pressure and low temperature. Appl. Environ. Microbiol. 65:1710-1720.
Allen EE, Bartlett DH. (2000) FabF is required for piezoregulation of cis-vaccenic acid levels and piezophilic growth of the deep-sea bacterium Photobacterium profundum strain SS9. J. Bacteriol. 182:1264-1271.
Allen E, Bartlett DH. (2002) Structure and regulation of the omega-3 polyunsaturated fatty acid synthase genes from the deep-sea bacterium Photobacterium profundum strain SS9. Microbiology 148:1903-1914.
Palenik B et al. (2003) The genome of a motile marine Synechococcus. Nature 424:1037-1042.
Tyson GW et al. (2004) Community structure and metabolism through reconstruction of microbial genomes from the environment. Nature 428:37-43.
Allen EE, Banfield JF. (2005) Community genomics in microbial ecology and evolution. Nature Rev. Microbiol. 3:489-498.
Tyson GW et al. (2005) Genome-directed isolation of the key nitrogen fixer, Leptospirillum ferrodiazotrophum sp. nov., from an acidophilic microbial community. Appl. Environ. Microbiol. 71:6319-6324.
Baker BJ et al. (2006) Lineages of acidophilic archaea revealed by community genomic analysis. Science 314:1933-1935.
Allen EE et al. (2007) Genome dynamics in a natural archaeal population. Proc. Natl. Acad. Sci. U.S.A. 104:1883-1888.
Lo I et al. (2007) Strain-resolved community proteomics reveals that recombination shapes the genomes of acidophilic bacteria. Nature 446:537-541.
Robidart JC et al. (2008) Metabolic versatility of the Riftia pachyptila endosymtiont revealed through metagenomics. Environ. Microbiol. 10:727-737.
Podell S, Gaasterland T, Allen EE. (2008) A database of phylogenetically atypical genes in archaeal and bacterial genomes, identified using the DarkHorse algorithm. BMC Bioinformatics 9:419.
Eric Allen received his B.S. from the University of Oregon and his Ph.D. from the Scripps Institution of Oceanography at UC San Diego. He performed his postdoctoral research at the University of California, Berkley as an NSF Postdoctoral Fellow in Microbial Biology and joined the faculty of Biological Sciences and the Scripps Institution of Oceangraphy at UCSD in 2006.
