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MICROBIOLOGY
Global profiling of Shewanella oneidensis MR-1: Expression of hypothetical genes and improved functional annotations
aBIATECH, 19310 North Creek Parkway, Suite 115, Bothell, WA 98011; cNational Center for Biotechnology Information, National Institutes of Health, Bethesda, MD 20894; dBiological Sciences Division and eEnvironmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352; fCenter for Microbial Ecology, Michigan State University, East Lansing, MI 48824; gBiosciences Division, Argonne National Laboratory, Argonne, IL 60439; hGenome Analysis Group and mEnvironmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831; iWadsworth Center, Albany, NY 12201; jCenter for Comparative Molecular Biology and Evolution, Marine Biological Laboratory, Woods Hole, MA 02543; kDepartment of Earth Sciences, University of Southern California, Los Angeles, CA 90089; and lDepartment of Cell Biology, The Scripps Research Institute, La Jolla, CA 92037
Contributed by James M. Tiedje, December 17, 2004
The
-proteobacterium Shewanella oneidensis strain MR-1 is a metabolically versatile organism that can reduce a wide range of organic compounds, metal ions, and radionuclides. Similar to most other sequenced organisms,
40% of the predicted ORFs in the S. oneidensis genome were annotated as uncharacterized "hypothetical" genes. We implemented an integrative approach by using experimental and computational analyses to provide more detailed insight into gene function. Global expression profiles were determined for cells after UV irradiation and under aerobic and suboxic growth conditions. Transcriptomic and proteomic analyses confidently identified 538 hypothetical genes as expressed in S. oneidensis cells both as mRNAs and proteins (33% of all predicted hypothetical proteins). Publicly available analysis tools and databases and the expression data were applied to improve the annotation of these genes. The annotation results were scored by using a seven-category schema that ranked both confidence and precision of the functional assignment. We were able to identify homologs for nearly all of these hypothetical proteins (97%), but could confidently assign exact biochemical functions for only 16 proteins (category 1; 3%). Altogether, computational and experimental evidence provided functional assignments or insights for 240 more genes (categories 25; 45%). These functional annotations advance our understanding of genes involved in vital cellular processes, including energy conversion, ion transport, secondary metabolism, and signal transduction. We propose that this integrative approach offers a valuable means to undertake the enormous challenge of characterizing the rapidly growing number of hypothetical proteins with each newly sequenced genome.
computational biology | expression analysis | microarrays | proteomics | integrative microbiology
Freely available online through the PNAS open access option.
Abbreviations: COG, Clusters of Orthologous Groups; LC, liquid chromatography.
b To whom correspondence should be addressed. E-mail: ekolker{at}biatech.org.
© 2005 by The National Academy of Sciences of the USA
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