U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights


New Sequence-Based Approach to Environmental Genomics Published in Science
Published: September 13, 2004
Posted: October 12, 2004

In a recent issue of Science (9/3/04), Ed DeLong (MIT) and colleagues, including scientists from the DOE Joint Genome Institute in Walnut Creek, California, describe the use of genome based analyses of methane-oxidizing Archaea (evolutionarily ancient microorganisms) from deep-sea sediments to study the biological mechanisms controlling anaerobic methane oxidation. This will lead to a better understanding of the significant impacts on the flux of greenhouse gases from ocean to atmosphere and the roles of these microorganisms in those processes which, in turn, may illuminate the ways oceanic microbes participate in global carbon cycling and climate processes. One current model suggests that relatives of methane-producing Archaea developed the capacity to reverse methanogenesis and thereby to consume methane to produce cellular carbon and energy. The results published today show that nearly all of the genes that are typically associated with methane production are present in one specific group of these methane-consuming organisms, but appear to be "run backwards" so that rather than generating methane, they consume it instead. A significant contribution to this science came from the DOE Joint Genome Institute that carried out the sequencing of genomic libraries constructed from deep-sea sediment organisms, without a requirement for individual growth and culturing of each organism in the sediments. These genome-based observations provide a foundation for metabolic modeling of methane oxidation in the absence of oxygen in the deeper parts of the oceans.

Contact: Dan Drell, SC-72, (301) 903-4742
Topic Areas:

  • Research Area: Genomic Analysis and Systems Biology
  • Research Area: Microbes and Communities
  • Research Area: DOE Joint Genome Institute (JGI)
  • Research Area: Computational Biology, Bioinformatics, Modeling

Division: SC-23.2 Biological Systems Science Division, BER
      (formerly SC-72 Life Sciences Division, OBER)

 

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