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      Evolutionary history of carbon monoxide dehydrogenase/acetyl-CoA synthase, one of the oldest enzymatic complexes

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          Significance

          Before the emergence of oxygenic photosynthesis and the accumulation of oxygen on Earth, life was essentially composed of anaerobic microorganisms. However, very little is known about which metabolisms were present at the time. Anaerobic carbon fixation through the Wood–Ljungdahl pathway is believed to be among the most ancient, and still plays a pivotal role in modern ecosystems. However, its origin and evolutionary history has been disputed. We analysed the distribution and phylogeny of carbon monoxide dehydrogenase/acetyl-CoA synthase, the main enzymatic complex of the pathway in thousands of bacterial and archaeal genomes. We show that this complex was already at work in the last universal common ancestor and has been remarkably conserved in microorganisms over more than 3.5 billion years.

          Abstract

          Carbon monoxide dehydrogenase/acetyl-CoA synthase (CODH/ACS) is a five-subunit enzyme complex responsible for the carbonyl branch of the Wood–Ljungdahl (WL) pathway, considered one of the most ancient metabolisms for anaerobic carbon fixation, but its origin and evolutionary history have been unclear. While traditionally associated with methanogens and acetogens, the presence of CODH/ACS homologs has been reported in a large number of uncultured anaerobic lineages. Here, we have carried out an exhaustive phylogenomic study of CODH/ACS in over 6,400 archaeal and bacterial genomes. The identification of complete and likely functional CODH/ACS complexes in these genomes significantly expands its distribution in microbial lineages. The CODH/ACS complex displays astounding conservation and vertical inheritance over geological times. Rare intradomain and interdomain transfer events might tie into important functional transitions, including the acquisition of CODH/ACS in some archaeal methanogens not known to fix carbon, the tinkering of the complex in a clade of model bacterial acetogens, or emergence of archaeal–bacterial hybrid complexes. Once these transfers were clearly identified, our results allowed us to infer the presence of a CODH/ACS complex with at least four subunits in the last universal common ancestor (LUCA). Different scenarios on the possible role of ancestral CODH/ACS are discussed. Despite common assumptions, all are equally compatible with an autotrophic, mixotrophic, or heterotrophic LUCA. Functional characterization of CODH/ACS from a larger spectrum of bacterial and archaeal lineages and detailed evolutionary analysis of the WL methyl branch will help resolve this issue.

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          Most cited references39

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          Hidden Markov model speed heuristic and iterative HMM search procedure

          Background Profile hidden Markov models (profile-HMMs) are sensitive tools for remote protein homology detection, but the main scoring algorithms, Viterbi or Forward, require considerable time to search large sequence databases. Results We have designed a series of database filtering steps, HMMERHEAD, that are applied prior to the scoring algorithms, as implemented in the HMMER package, in an effort to reduce search time. Using this heuristic, we obtain a 20-fold decrease in Forward and a 6-fold decrease in Viterbi search time with a minimal loss in sensitivity relative to the unfiltered approaches. We then implemented an iterative profile-HMM search method, JackHMMER, which employs the HMMERHEAD heuristic. Due to our search heuristic, we eliminated the subdatabase creation that is common in current iterative profile-HMM approaches. On our benchmark, JackHMMER detects 14% more remote protein homologs than SAM's iterative method T2K. Conclusions Our search heuristic, HMMERHEAD, significantly reduces the time needed to score a profile-HMM against large sequence databases. This search heuristic allowed us to implement an iterative profile-HMM search method, JackHMMER, which detects significantly more remote protein homologs than SAM's T2K and NCBI's PSI-BLAST.
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            Methane metabolism in the archaeal phylum Bathyarchaeota revealed by genome-centric metagenomics.

            Methanogenic and methanotrophic archaea play important roles in the global flux of methane. Culture-independent approaches are providing deeper insight into the diversity and evolution of methane-metabolizing microorganisms, but, until now, no compelling evidence has existed for methane metabolism in archaea outside the phylum Euryarchaeota. We performed metagenomic sequencing of a deep aquifer, recovering two near-complete genomes belonging to the archaeal phylum Bathyarchaeota (formerly known as the Miscellaneous Crenarchaeotal Group). These genomes contain divergent homologs of the genes necessary for methane metabolism, including those that encode the methyl-coenzyme M reductase (MCR) complex. Additional non-euryarchaeotal MCR-encoding genes identified in a range of environments suggest that unrecognized archaeal lineages may also contribute to global methane cycling. These findings indicate that methane metabolism arose before the last common ancestor of the Euryarchaeota and Bathyarchaeota.
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              IMG/M: integrated genome and metagenome comparative data analysis system

              The Integrated Microbial Genomes with Microbiome Samples (IMG/M: https://img.jgi.doe.gov/m/) system contains annotated DNA and RNA sequence data of (i) archaeal, bacterial, eukaryotic and viral genomes from cultured organisms, (ii) single cell genomes (SCG) and genomes from metagenomes (GFM) from uncultured archaea, bacteria and viruses and (iii) metagenomes from environmental, host associated and engineered microbiome samples. Sequence data are generated by DOE's Joint Genome Institute (JGI), submitted by individual scientists, or collected from public sequence data archives. Structural and functional annotation is carried out by JGI's genome and metagenome annotation pipelines. A variety of analytical and visualization tools provide support for examining and comparing IMG/M's datasets. IMG/M allows open access interactive analysis of publicly available datasets, while manual curation, submission and access to private datasets and computationally intensive workspace-based analysis require login/password access to its expert review (ER) companion system (IMG/M ER: https://img.jgi.doe.gov/mer/). Since the last report published in the 2014 NAR Database Issue, IMG/M's dataset content has tripled in terms of number of datasets and overall protein coding genes, while its analysis tools have been extended to cope with the rapid growth in the number and size of datasets handled by the system.
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                pnas
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                6 February 2018
                22 January 2018
                : 115
                : 6
                : E1166-E1173
                Affiliations
                [1] aUnit Evolutionary Biology of the Microbial Cell, Department of Microbiology, Institut Pasteur , 75015 Paris, France;
                [2] b Université Paris Diderot, Sorbonne Paris Cité , Paris, France
                Author notes
                1To whom correspondence should be addressed. Email: simonetta.gribaldo@ 123456pasteur.fr .

                Edited by W. Ford Doolittle, Dalhousie University, Halifax, Canada, and approved December 12, 2017 (received for review September 21, 2017)

                Author contributions: S.G. designed research; P.S.A. performed research; P.S.A., G.B., and S.G. analyzed data; and P.S.A., G.B., and S.G. wrote the paper.

                Article
                PMC5819426 PMC5819426 5819426 201716667
                10.1073/pnas.1716667115
                5819426
                29358391
                dec10d7f-9c80-4e0b-8f85-ccb1413d3bae
                Copyright @ 2018

                Published under the PNAS license.

                History
                Page count
                Pages: 8
                Funding
                Funded by: Agence Nationale de la Recherche (ANR) 501100001665
                Award ID: ANR-16-CE02-0005-01
                Categories
                PNAS Plus
                Biological Sciences
                Evolution
                PNAS Plus

                LUCA,acetogens,methanogens,evolution,Wood–Ljungdahl pathway

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