Dataset Information

Metabolic reconstruction of the archaeon methanogen Methanosarcina Acetivorans.

ABSTRACT:

Background

Methanogens are ancient organisms that are key players in the carbon cycle accounting for about one billion tones of biological methane produced annually. Methanosarcina acetivorans, with a genome size of ~5.7 mb, is the largest sequenced archaeon methanogen and unique amongst the methanogens in its biochemical characteristics. By following a systematic workflow we reconstruct a genome-scale metabolic model for M. acetivorans. This process relies on previously developed computational tools developed in our group to correct growth prediction inconsistencies with in vivo data sets and rectify topological inconsistencies in the model.

Results

The generated model iVS941 accounts for 941 genes, 705 reactions and 708 metabolites. The model achieves 93.3% prediction agreement with in vivo growth data across different substrates and multiple gene deletions. The model also correctly recapitulates metabolic pathway usage patterns of M. acetivorans such as the indispensability of flux through methanogenesis for growth on acetate and methanol and the unique biochemical characteristics under growth on carbon monoxide.

Conclusions

Based on the size of the genome-scale metabolic reconstruction and extent of validated predictions this model represents the most comprehensive up-to-date effort to catalogue methanogenic metabolism. The reconstructed model is available in spreadsheet and SBML formats to enable dissemination.

SUBMITTER: Satish Kumar V

PROVIDER: S-EPMC3048526 | biostudies-literature | 2011 Feb

REPOSITORIES: biostudies-literature

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Publications

Metabolic reconstruction of the archaeon methanogen Methanosarcina Acetivorans.

Satish Kumar Vinay V Ferry James G JG Maranas Costas D CD

BMC systems biology 20110215

<h4>Background</h4>Methanogens are ancient organisms that are key players in the carbon cycle accounting for about one billion tones of biological methane produced annually. Methanosarcina acetivorans, with a genome size of ~5.7 mb, is the largest sequenced archaeon methanogen and unique amongst the methanogens in its biochemical characteristics. By following a systematic workflow we reconstruct a genome-scale metabolic model for M. acetivorans. This process relies on previously developed comput ...[more]

PMID: 21324125

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Project description:Methanosarcina acetivorans strain C2A is an acetate- and methanol-utilizing methane-producing organism for which the genome, the largest yet sequenced among the Archaea, reveals extensive physiological diversity. LC linear ion trap-FTICR mass spectrometry was employed to analyze acetate- vs methanol-grown cells metabolically labeled with 14N vs 15N, respectively, to obtain quantitative protein abundance ratios. DNA microarray analyses of acetate- vs methanol-grown cells was also performed to determine gene expression ratios. The combined approaches were highly complementary, extending the physiological understanding of growth and methanogenesis. Of the 1081 proteins detected, 255 were > or =3-fold differentially abundant. DNA microarray analysis revealed 410 genes that were > or =2.5-fold differentially expressed of 1972 genes with detected expression. The ratios of differentially abundant proteins were in good agreement with expression ratios of the encoding genes. Taken together, the results suggest several novel roles for electron transport components specific to acetate-grown cells, including two flavodoxins each specific for growth on acetate or methanol. Protein abundance ratios indicated that duplicate CO dehydrogenase/acetyl-CoA complexes function in the conversion of acetate to methane. Surprisingly, the protein abundance and gene expression ratios indicated a general stress response in acetate- vs methanol-grown cells that included enzymes specific for polyphosphate accumulation and oxidative stress. The microarray analysis identified transcripts of several genes encoding regulatory proteins with identity to the PhoU, MarR, GlnK, and TetR families commonly found in the Bacteria domain. An analysis of neighboring genes suggested roles in controlling phosphate metabolism (PhoU), ammonia assimilation (GlnK), and molybdopterin cofactor biosynthesis (TetR). Finally, the proteomic and microarray results suggested roles for two-component regulatory systems specific for each growth substrate.

Project description:BackgroundCorrect annotation of function is essential if one is to take full advantage of the vast amounts of genomic sequence data. The accuracy of sequence-based functional annotations is often variable, particularly if the sequence homology to a known function is low. Indeed recent work has shown that even proteins with very high sequence identity can have different folds and functions, and therefore caution is needed in assigning functions by sequence homology in the absence of experimental validation. Experimental methods are therefore needed to efficiently evaluate annotations in a way that complements current high throughput technologies. Here, we describe the use of nuclear magnetic resonance (NMR)-based ligand screening as a tool for testing functional assignments of putative enzymes that may be of variable reliability.ResultsThe target genes for this study are putative enzymes from the methanogenic archaeon Methanosarcina acetivorans (MA) that have been selected after manual genome re-annotation and demonstrate detectable in vivo expression at the level of the transcriptome. The experimental approach begins with heterologous E. coli expression and purification of individual MA gene products. An NMR-based ligand screen of the purified protein then identifies possible substrates or products from a library of candidate compounds chosen from the putative pathway and other related pathways. These data are used to determine if the current sequence-based annotation is likely to be correct. For a number of case studies, additional experiments (such as in vivo genetic complementation) were performed to determine function so that the reliability of the NMR screen could be independently assessed.ConclusionsIn all examples studied, the NMR screen was indicative of whether the functional annotation was correct. Thus, the case studies described demonstrate that NMR-based ligand screening is an effective and rapid tool for confirming or negating the annotated gene function of putative enzymes. In particular, no protein-specific assay needs to be developed, which makes the approach broadly applicable for validating putative functions using an automated pipeline strategy.

Dataset Information

Metabolic reconstruction of the archaeon methanogen Methanosarcina Acetivorans.

Background

Results

Conclusions

Publications

Metabolic reconstruction of the archaeon methanogen Methanosarcina Acetivorans.

Similar Datasets

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