Please use this identifier to cite or link to this item: http://hdl.handle.net/10362/158525
Title: Stepwise pathway for early evolutionary assembly of dissimilatory sulfite and sulfate reduction
Author: Neukirchen, Sinje
Pereira, Inês A.C.
Sousa, Filipa L.
Keywords: Microbiology
Ecology, Evolution, Behavior and Systematics
Issue Date: 2023
Abstract: Microbial dissimilatory sulfur metabolism utilizing dissimilatory sulfite reductases (Dsr) influenced the biochemical sulfur cycle during Earth’s history and the Dsr pathway is thought to be an ancient metabolic process. Here we performed comparative genomics, phylogenetic, and synteny analyses of several Dsr proteins involved in or associated with the Dsr pathway across over 195,000 prokaryotic metagenomes. The results point to an archaeal origin of the minimal DsrABCMK(N) protein set, having as primordial function sulfite reduction. The acquisition of additional Dsr proteins (DsrJOPT) increased the Dsr pathway complexity. Archaeoglobus would originally possess the archaeal-type Dsr pathway and the archaeal DsrAB proteins were replaced with the bacterial reductive-type version, possibly at the same time as the acquisition of the QmoABC and DsrD proteins. Further inventions of two Qmo complex types, which are more spread than previously thought, allowed microorganisms to use sulfate as electron acceptor. The ability to use the Dsr pathway for sulfur oxidation evolved at least twice, with Chlorobi and Proteobacteria being extant descendants of these two independent adaptations.
Description: Funding Information: FLS and SN acknowledge support from the Wiener Wissenschafts, Forschungs- und Technologiefonds (Austria) through the grant VRG15-007. FLS gratefully acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation program (grant agreement 803768). IACP acknowledges support from Fundação para a Ciência e Tecnologia (Portugal) through grants PTDC/BIA-MIC/6512/2014 and PTDC/BIA-BQM/29118/2017, R&D unit MOSTMICRO-ITQB (UIDB/04612/2020 and UIDP/04612/2020), and LS4FUTURE Associated Laboratory (LA/P/0087/2020). The computational results of this work have been achieved using the Life Science Compute Cluster (LiSC) of the University of Vienna. Funding Information: FLS and SN acknowledge support from the Wiener Wissenschafts, Forschungs- und Technologiefonds (Austria) through the grant VRG15-007. FLS gratefully acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation program (grant agreement 803768). IACP acknowledges support from Fundação para a Ciência e Tecnologia (Portugal) through grants PTDC/BIA-MIC/6512/2014 and PTDC/BIA-BQM/29118/2017, R&D unit MOSTMICRO-ITQB (UIDB/04612/2020 and UIDP/04612/2020), and LS4FUTURE Associated Laboratory (LA/P/0087/2020). The computational results of this work have been achieved using the Life Science Compute Cluster (LiSC) of the University of Vienna. Publisher Copyright: © 2023, The Author(s).
Peer review: yes
URI: http://hdl.handle.net/10362/158525
DOI: https://doi.org/10.1038/s41396-023-01477-y
ISSN: 1751-7362
Appears in Collections:Home collection (ITQB)



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