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Abstract

Current methods in comparative genomic analyses for metabolic potential prediction of proteins involved in, or associated with the Dsr (dissimilatory sulphite reductase)-dependent dissimilatory sulphur metabolism are both time-intensive and computationally challenging, especially when considering metagenomic data. We developed DiSCo, a Dsr-dependent dissimilatory sulphur metabolism classification tool, which automatically identifies and classifies the protein type from sequence data. It takes user-supplied protein sequences and lists the identified proteins and their classification in terms of protein family and predicted type. It can also extract the sequence data from user-input to serve as basis for additional downstream analyses. DiSCo provides the metabolic functional prediction of proteins involved in Dsr-dependent dissimilatory sulphur metabolism with high levels of accuracy in a fast manner. We ran DiSCo against a dataset composed of over 190 thousand (meta)genomic records and efficiently mapped Dsr-dependent dissimilatory sulphur proteins in 1798 lineages across both prokaryotic domains. This allowed the identification of new micro-organisms belonging to Thaumarchaeota and Spirochaetes lineages with the metabolic potential to use the Dsr-pathway for energy conservation. DiSCo is implemented in Perl 5 and freely available under the GNU GPLv3 at https://github.com/Genome-Evolution-and-Ecology-Group-GEEG/DiSCo.

Funding
This study was supported by the:
  • Vienna Science and Technology Fund (Award VRG15-007)
    • Principle Award Recipient: FilipaL. Sousa
  • This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial License.
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2021-07-09
2024-04-25
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