Studies of Corrosion-Causing Bacterium Shed New Light on Decay Mechanisms
Genomic, proteomics, and computational research on Desulfovibrio vulgaris give insight to the bug's metabolism for corrosion and inorganic contaminant immobilization
Contact: Weiwen Zhang
Contact: Fred Brockman
Results: Benefiting from the recently sequenced genome of the model sulfate-reducing bacterium (SRB), Desulfovibrio vulgaris, microbiologist Weiwen Zhang and a team of scientists at Pacific Northwest National Laboratory (PNNL) are applying a suite of post-genomics technologies, including microarray, proteomic, and computational analyses, to obtain a broader understanding of D. vulgaris' metabolism.
Results of their research have recently appeared in several scientific journals, such as Journal of Molecular Evolution, Antonie Van Leeuwenhoek, Bioinformatics, Proteomics, the Biochemical and Biophysical Research Communications, and Genetics.
Why it matters: Iron corrosion is a serious economic problem, as evidenced most recently by the closure of the nation's largest oil field, Alaska's Prudhoe Bay, because of pipeline corrosion. Whereas aerobic corrosion of iron is a chemical process, anaerobic corrosion of iron is frequently linked to SRB activity. SRB are a group of obligate anaerobic (meaning they cannot survive when exposed to oxygen) microorganisms that exist in diverse environments. On a more positive note, some SRB strains can enzymatically reduce many metals including chromium (VI), iron (III), and uranium (VI) by using them as an alternative terminal electron acceptor. This reduction stops the movement of the metals in groundwater, making SRB of value for contaminant remediation. However, the biomolecular mechanisms for iron corrosion and metal reduction and their connections to central metabolism and basal cellular processes are poorly understood.
Methods: By applying whole-genome oligonucleotide microarray analysis of D. vulgaris and high-efficiency capillary liquid chromatography-tandem mass spectrometry (LC-MS/MS), the group has investigated D. vulgaris grown on various electron donors or under stress conditions. Among their results, the researchers have identified enzymes that may allow D. vulgaris to produce energy in two previously unknown ways, and identified the key enzymes involved in protecting D. vulgaris from exposure to oxygen. These discoveries have implications for understanding how SRB persist, and remain active, in a wide range of environments.
In addition, the researchers, in collaboration with scientists at Georgetown University and the University of Maryland, used the whole-genome mRNA data and global proteomics data collected from cells under several experimental conditions. They performed multiple regression analysis to better understand the gene-by-gene correspondence between mRNA and protein abundances. They found that 54% of the variations in mRNA abundance can be explained by the presence of motifs upstream of the gene, while the gene coding sequence alone explains 30% of the variations in mRNA abundance.
The results also demonstrated that upstream regulatory motifs and coding sequence information contribute to the overall mRNA expression in a combinatorial rather than an additive manner. In addition, a novel data-driven statistical model was developed to integrate whole-genome microarray and proteomic data. A major application of the model is to predict protein abundance for those proteins not detected by global proteomics analysis. Together, these findings enable more robust biological inferences and hypotheses to be made, and allow improved simulation of whole-cell metabolism.
In a third area of research, the scientists are seeking to understand how different species of microbes impact each others' ability to choose what energy-capture system (i.e., sets of proteins) to synthesize. The interaction between Desulfovibrio vulgaris and Methanosarcina barkeri is being studied using whole-genome DNA microarrays and global proteomics. Recently, some Desulfovibrio vulgaris proteins involved in the switch from a syntrophic lifestyle to a sulfate-reducing lifestyle have been identified. Such studies are particularly important for understanding how D. vulgaris behaves in multiple-species microbial communities that exist in nature.
Scientific team: Weiwen Zhang, Hans Scholten, Dave Culley, Fred Brockman, Marina Gritsenko, Ron Moore, Kostas Petritis, Dick Smith, and Dave Camp, all PNNL; former PNNL staff member Eric Strittmatter; Lei Nie, Georgetown University; Gang Wu, University of Maryland; and Mike Hogan and Luigi Vitiritti, NimbleGen Systems, Inc.
Sources: Nie L, G Wu, and W Zhang. 2006. "Correlation between mRNA and protein abundance in Desulfovibrio vulgaris: A multiple regression to identify sources of variations." Biochemical and Biophysical Research Communications 339(2):603-610.
Nie L, G Wu, FJ Brockman, and W Zhang. 2006. "Integrated analysis of transcriptomic and proteomic data of Desulfovibrio vulgaris: Zero-Inflated Poisson regression models to predict abundance of undetected proteins." Bioinformatics 22(13):1641-1647.
Nie L, G Wu, and W Zhang. 2006. "Correlation of mRNA expression and protein abundance affected by multiple sequence features related to translational efficiency in Desulfovibrio vulgaris: A quantitative analysis." Genetics. Available online October 8, 2006
Scholten JC, DE Culley, FJ Brockman, G Wu, and W Zhang. 2006. "Evolution of the syntrophic interaction between Desulfovibrio vulgaris and Methanosarcina barkeri: Involvement of an ancient horizontal gene transfer." Biochemical and Biophysical Research Communications. Available online November 7, 2006
Wu G, L Nie, and W Zhang. 2006. "Relation between mRNA expression and sequence information in Desulfovibrio vulgaris: Combinatorial contributions of upstream regulatory motifs and coding sequence features to variations in mRNA abundance." Biochemical and Biophysical Research Communications 344(1):114-121.
Zhang W, DE Culley, G Wu, and FJ Brockman. 2006. "Two-Component Signal Transduction Systems of Desulfovibrio vulgaris: Structural and Phylogenetic Analysis and Deduction of Putative Cognate Pairs." Journal of Molecular Evolution 62:473-487.
Zhang W, DE Culley, H Scholten, M Hogan, L Vitiritti, and FJ Brockman. 2006. "Global Transcriptomic Analysis of Desulfovibrio vulgaris Grown on Different Carbon Sources." Antonie Van Leeuwenhoek 89(2):221-237.
Zhang W, DE Culley, M Hogan, L Vitiritti, and FJ Brockman. 2006. "Oxidative Stress and Heat-Shock Responses in by Genome-Wide Transcriptomic Analysis." Antonie Van Leeuwenhoek 90:41-55.
Zhang W, MA Gritsenko, RJ Moore, DE Culley, L Nie, K Petritis, EF Strittmatter, DG Camp, II, RD Smith, and FJ Brockman. 2006. "A proteomic view of Desulfovibrio vulgaris metabolism as determined by liquid chromatography coupled with tandem mass spectrometry." Proteomics 6(15):4286-4299.
Zhang W, DE Culley, MA Gritsenko, RJ Moore, L Nie, JC Scholten, K Petritis, EF Strittmatter, DG Camp II, RD Smith, and FJ Brockman. 2006. "LC-MS/MS based proteomic analysis and functional inference of hypothetical proteins in Desulfovibrio vulgaris." Biochemical and Biophysical Research Communications 349(4):1412-9
Sponsor: U.S. Department of Energy Office of Biological and Environmental Research.