ArticleBiotechnology for biofuels2013
De novo prediction of the genomic components and capabilities for microbial plant biomass degradation from (meta-)genomes.
Article in Biotechnology for biofuels, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 21 citations in OpenAlex.
- Chitosan Oligosaccharide Production Potential ofFrontiers in microbiology · 2021Article
- "Candidatus Paraporphyromonas polyenzymogenes" encodes multi-modular cellulases linked to the type IX secretion system.Microbiome · 2018Article
- Development and characterization of stable anaerobic thermophilic methanogenic microbiomes fermenting switchgrass at decreasing residence times.Biotechnology for biofuels · 2018Article
- Natural diversity of cellulases, xylanases, and chitinases in bacteria.Biotechnology for biofuels · 2016Article
- Influence of Substrates on the Surface Characteristics and Membrane Proteome of Fibrobacter succinogenes S85.PloS one · 2015Article
- Comparative analysis of sugarcane bagasse metagenome reveals unique and conserved biomass-degrading enzymes among lignocellulolytic microbial communities.Biotechnology for biofuels · 2015Article
- Article
- Inference of phenotype-defining functional modules of protein families for microbial plant biomass degraders.Biotechnology for biofuels · 2014Article
- Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUnderstanding the biological mechanisms used by microorganisms for plant biomass degradation is of considerable biotechnological interest. Despite of the growing number of sequenced (meta)genomes of plant biomass-degrading microbes, there is currently no technique for the systematic determination of the genomic components of this process from these data.
resultsWe describe a computational method for the discovery of the protein domains and CAZy families involved in microbial plant biomass degradation. Our method furthermore accurately predicts the capability to degrade plant biomass for microbial species from their genome sequences. Application to a large, manually curated data set of microbial degraders and non-degraders identified gene families of enzymes known by physiological and biochemical tests to be implicated in cellulose degradation, such as GH5 and GH6. Additionally, genes of enzymes that degrade other plant polysaccharides, such as hemicellulose, pectins and oligosaccharides, were found, as well as gene families which have not previously been related to the process. For draft genomes reconstructed from a cow rumen metagenome our method predicted Bacteroidetes-affiliated species and a relative to a known plant biomass degrader to be plant biomass degraders. This was supported by the presence of genes encoding enzymatically active glycoside hydrolases in these genomes.
conclusionsOur results show the potential of the method for generating novel insights into microbial plant biomass degradation from (meta-)genome data, where there is an increasing production of genome assemblages for uncultured microbes.
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