De novo prediction of the genomic components and capabilities for microbial plant biomass degradation from (meta-)genomes

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.

Inference of phenotype-defining functional modules of protein families for microbial plant biomass degraders

“…[28]), we have cross-linked the data from cellulolytic enzyme screens of the study by Hess et al with protein family annotations of the 15 draft genomes to identify potential plant biomass degraders from the cow rumen metagenome. Strikingly, all 4 families (GH5, GH9, GH10, and GH26), which have been described by Weimann et al to correspond to the (hemi-)cellulolytic enzymes of the cow rumen bins with degradation abilities confirmed by activity screens (see Table 3 in Weimann et al [28]), were grouped together in the PDM M1 in our study.…”

“…For the ranking of the modules, we used the learning set from our previous study [28], in which we had linked individual protein families to plant biomass degradation, and extended it by 20 additional phenotype-positive organisms. Despite of these additions, the number of confirmed degrader species is still small, compared with the estimated abundance of potential plant biomassdegrading species reported in two other studies [44,45].…”

“…Several methods for ranking genes or pathways by their assumed relevance for a certain phenotype have been described [28][29][30][31][32][33][34][35][36][37]. These methods measure the association of individual protein families [28], known pathways [29] or single nucleotide polymorphisms [30] with the presence or absence of phenotypes across a set of genomes.…”

“…These methods measure the association of individual protein families [28], known pathways [29] or single nucleotide polymorphisms [30] with the presence or absence of phenotypes across a set of genomes. In some instances, the search space is limited to proteins in predicted operon structures [31] or to pairs of functionally coupled proteins [32].…”

“…We have previously described a family-centric method for the identification of protein families involved in lignocellulose degradation [28]. This method uses an ensemble of linear L1-regularized support vector machine (SVM) classifiers trained with the genome annotations of known lignocellulose-degrading and non-lignocellulosedegrading species.…”