MEBS, a software platform to evaluate large (meta)genomic collections according to their metabolic machinery: unraveling the sulfur cycle

Abstract

The increasing number of metagenomic and genomic sequences has dramatically improved our understanding of microbial diversity, yet our ability to infer metabolic capabilities in such datasets remains challenging. We describe the Multigenomic Entropy Based Score pipeline (MEBS), a software platform designed to evaluate, compare, and infer complex metabolic pathways in large “omic” datasets, including entire biogeochemical cycles. MEBS is open source and available through https://github.com/eead-csic-compbio/metagenome_Pfam_score. To demonstrate its use, we modeled the sulfur cycle by exhaustively curating the molecular and ecological elements involved (compounds, genes, metabolic pathways, and microbial taxa). This information was reduced to a collection of 112 characteristic Pfam protein domains and a list of complete-sequenced sulfur genomes. Using the mathematical framework of relative entropy (H΄), we quantitatively measured the enrichment of these domains among sulfur genomes. The entropy of each domain was used both to build up a final score that indicates whether a (meta)genomic sample contains the metabolic machinery of interest and to propose marker domains in metagenomic sequences such as DsrC (PF04358). MEBS was benchmarked with a dataset of 2107 non-redundant microbial genomes from RefSeq and 935 metagenomes from MG-RAST. Its performance, reproducibility, and robustness were evaluated using several approaches, including random sampling, linear regression models, receiver operator characteristic plots, and the area under the curve metric (AUC). Our results support the broad applicability of this algorithm to accurately classify (AUC = 0.985) hard-to-culture genomes (e.g., Candidatus Desulforudis audaxviator), previously characterized ones, and metagenomic environments such as hydrothermal vents, or deep-sea sediment. Our benchmark indicates that an entropy-based score can capture the metabolic machinery of interest and can be used to efficiently classify large genomic and metagenomic datasets, including uncultivated/unexplored taxa.

Understanding the Mechanisms Behind the Response to Environmental Perturbation in Microbial Mats: A Metagenomic-Network Based Approach

“…The peptide amino acid sequences were then scanned against Pfam-A v30 ( Finn et al, 2015 ). The abundance profile of each Pfam domain in the metagenomic samples was obtained from a Perl script extract_pfam.pl which is part of the MEBS software suite ( De Anda et al, 2017 ). The resulting FASTA files of sequence contigs have been deposited in the MG-RAST repository under project number mgp80319.…”

“…We used MEBS ( De Anda et al, 2017 ) to evaluate the metabolic machinery of C, O, N, S, and Fe cycles in the microbial mats across time by using a single value measured in bits (informational units). Briefly, FASTA peptide sequences for each microbial mat, obtained with Prodigal, are taken as input of the main script mebs.pl.…”

“…(1) The analysis of robust time series ecological networks (TS-ENs) at different taxonomic level to access general patterns of microbial relationships. (2) The application of MEBS (Multigenomic Entropy Based Score) to capture the enrichment of biogeochemical cycles or other complex metabolic pathways ( De Anda et al, 2017 ) to provide a quantifiable measure of community response to environmental perturbation. (3) The use of network motifs or building blocks of biological networks that have been applied to the study of development, regulatory, and neuronal networks ( Shen-Orr et al, 2002 ; Prill et al, 2005 ; Tran et al, 2013 ), and in ecological food webs of plants and animals ( Stouffer et al, 2007 ; Borrelli et al, 2015 ; Baiser et al, 2016 ).…”

The lost world of Cuatro Ciénegas Basin, a relictual bacterial niche in a desert oasis

“…The exception seems to be the abundant and morphologically diverse stromatolites and microbial mats found in the endangered oasis of Cuatro Ciénegas Basin (CCB) in Northern Mexico. In this extremely diverse wetland ( Minckley, 1969 ), the recycling of the deep aquifer by magmatic heat replicates many conditions of ancient oceans ( Wolaver et al, 2013 ), including its extremely unbalanced nutrient stoichiometry ( Elser et al, 2006 ) and sulphur and magnesium minerals that replicate marine osmolarity ( Wolaver et al, 2013 ; De Anda et al, 2017 ; Rebollar et al, 2012 ), despite being low in NaCl. Moreover, isotopic analysis suggests that the deep aquifer maintained the ancestral marine conditions in the wetland by dissolving the existing minerals from its sediments ( Wolaver et al, 2013 ).…”

1334 - Understanding the mechanisms behind the response of environmental perturbation in microbial mats: a metagenomic-network based approach

“…For a closer look into the dynamics of sulfur and methane cycles, we employed the completeness module implemented in MEBS. As established previously, the metabolic completeness is defined as the full repertoire of protein domains involved in a given metabolic pathway such as sulfate reduction or methanogenesis (De Anda et al, 2017). As observed in Figure 6B, the complete repertoire of protein domains required to utilize the organic sulfur compounds such as sulfonates as Dimethylsulfoniopropionate (DMSP), [3-(methylsulfanyl) propanoate (MTP)] (Jonkers et al, 1998;Curson et al, 2008;Bullock et al, 2014), as well as the methanogenesis from organic sulfur compounds (methanethiol and DMS) were found in the majority of microbial mat samples with exception of hot-spring mats from Yellowstone and stromatolite from Bahamas.…”