Expression of divergent methyl/alkyl coenzyme M reductases from uncultured archaea

Shao, Nana; Yang, Fan; Chou, Chau-Wen; Yavari, Shadi; Williams, Robert V.; Amster, I. Jonathan; Brown, Stuart M.; Drake, Ian J.; Duin, Evert C.; Whitman, William B.; Liu, Yuchen

doi:10.1038/s42003-022-04057-6

Cited by 16 publications

(18 citation statements)

References 67 publications

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“…However, contextualized gLM embeddings (Figure 2F) of the McrA proteins show distinct organization where ANME-1 McrA proteins form a tight cluster, while ANME-2 McrA proteins form a cluster closer to methanogens. This organization reflects the phylogenetic relationships between the organisms that McrAs are found in, and reflect distinct operonic and structural divergence of MCR complexes in ANME-1 compared to those found in ANME-2 and methanogens 27 . As proposed by Shao et al 27 , the preferred directionality in Reaction 1 (Figure 2G) in ANME-2 and some methanogens may be more dependent on thermodynamics.…”

Section: Contextualized Gene Embeddings Capture Gene Semanticsmentioning

confidence: 81%

“…This organization reflects the phylogenetic relationships between the organisms that McrAs are found in, and reflect distinct operonic and structural divergence of MCR complexes in ANME-1 compared to those found in ANME-2 and methanogens 27 . As proposed by Shao et al 27 , the preferred directionality in Reaction 1 (Figure 2G) in ANME-2 and some methanogens may be more dependent on thermodynamics. We also demonstrate that contextualized gLM embeddings are more suitable for determining the functional relationship between gene classes.…”

Section: Contextualized Gene Embeddings Capture Gene Semanticsmentioning

confidence: 81%

“…McrA protein encoding Methanogens and ANME genomes were selected from the accession ID list found in the supplement of Shao et al 27 . Sub-contigs containing mcrA were extracted with at most 15 genes before and after mcrA and the context-free and contextualized embeddings of McrA was calculated using the ESM2 and gLM respectively.…”

Section: Mcra Protein Analysismentioning

confidence: 99%

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Genomic language model predicts protein co-regulation and function

Hwang

Cornman²,

Овчинников

et al. 2023

Preprint

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Deciphering the relationship between a gene and its genomic context is fundamental to understanding and engineering biological systems. Machine learning has shown promise in learning latent relationships underlying the sequence-structure-function paradigm from massive protein sequence datasets. However, to date, limited attempts have been made in extending this continuum to include higher order genomic context information. Evolutionary processes dictate the specificity of genomic contexts in which a gene is found across phylogenetic distances, and these emergent genomic patterns can be leveraged to uncover functional relationships between gene products. Here, we trained a genomic language model (gLM) on millions of metagenomic scaffolds to learn the latent functional and regulatory relationships between genes. gLM learns contextualized protein embeddings that capture the genomic context as well as the protein sequence itself, and appears to encode biologically meaningful and functionally relevant information (e.g. phylogeny, enzymatic function). Our analysis of the attention patterns demonstrates that gLM is learning co-regulated functional modules (i.e. operons). Our findings illustrate that gLM's unsupervised deep learning of the metagenomic corpus is an effective approach to encode functional semantics and regulatory syntax of genes in their genomic contexts, providing a promising avenue for uncovering complex relationships between genes in a genomic region.

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Section: Contextualized Gene Embeddings Capture Gene Semanticsmentioning

confidence: 81%

Section: Contextualized Gene Embeddings Capture Gene Semanticsmentioning

confidence: 81%

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Genomic language model predicts protein co-regulation and function

Hwang

Cornman²,

Овчинников

et al. 2023

Preprint

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“…Those genomes range in size from 1.112 Mbp (WYZ-LMO11 sp004348015 of the Methanomethyliaceae family) to 5.752 Mbp ( Methanosarcina acetivorans ) and span five phyla, 17 classes, 21 orders, 38 families and 99 genera, which highlights the continued taxonomic expansion of Mcr containing archaea. 11 , 42 , 43 A list of these genomes with information on their size, quality and where available growth temperature ranges, isolation environments and growth substrates of species is available in Supplementary Table S1 .…”

Section: Resultsmentioning

confidence: 99%

The methanogen core and pangenome: conservation and variability across biology’s growth temperature extremes

2022

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Temperature is a key variable in biological processes. However, a complete understanding of biological temperature adaptation is lacking, in part because of the unique constraints among different evolutionary lineages and physiological groups. Here we compared the genomes of cultivated psychrotolerant and thermotolerant methanogens, which are physiologically related and span growth temperatures from -2.5 °C to 122 °C. Despite being phylogenetically distributed amongst three phyla in the archaea, the methanogenic genome core comprises about one third of a given methanogen’s genome, and the genome fraction shared by any two organisms decreases with increasing phylogenetic distance between them. Increased growth temperature is associated with reduced genome size, and thermotolerant organisms have larger core genome fractions, suggesting that genome reduction is governed by temperature rather than phylogeny. Thermotolerant methanogens are enriched in metal and other transporters, and psychrotolerant methanogens are enriched in proteins related to structure and motility. Observed amino acid compositional differences between temperature groups include proteome charge, polarity, and unfolding entropy. Our results suggest that in the methanogens, shared physiology maintains a large, conserved core even across large phylogenetic distances and biology’s temperature extremes.

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“…marburgensis under different assay conditions (data not shown). Nevertheless, multiple genetic modification tools for methanogens have been developed [20,21] along with expression of uncultured archaea Mcr [22] which may allow better conversion of longer alkyl-CoM (C3 and above) in the near future. To conclude, employing our cell-free lysate Mcr assay approach to investigate this enzyme family is a rapid and efficient assay to test the enzyme activity of these recombinant enzymes in order to provide a first milestone for further engineering of artificial cultivable alkanogens.…”

Section: Discussionmentioning

confidence: 99%

Methane and ethane production rates by methyl-coenzyme M reductase in cell extracts from different methanogens

Nguyen,

Keller,

Scheller

2024

Preprint

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Methyl-Coenzyme M reductase (Mcr) plays an important role in the regulation of the global carbon cycle. The enzyme catalyzes the reversible conversion of methyl-coenzyme M and coenzyme B to methane and the corresponding heterodisulfide CoM-S-S-CoB, which constitutes the first step of the anaerobic oxidation of methane. Mcr homologs of varies methanogenic archaea also catalyze the anaerobic oxidation of extended alkanes. Fully active, purified enzyme is exclusively achievableviastrictly anaerobic purification fromMethanothermobacter marburgensis. This microbe expresses two isoenzymes and most studies were performed with isoenzyme I that exhibits a limited substrate-promiscuity (c.a. 0.5%) towards the homologous substrate ethyl-coenzyme M. Here, cell-free lysates from the different species such asMethanosarcina mazei, Methanococcus maripaludis, Methanothermococcus okinawansis, andMt. marburgensiswere screened for Mcr activity and substrate promiscuity. An assay relying on titanium (III) citrate and cobalamin to regenerate coenzyme B and coenzyme M was used to test the ability of different cell extracts for the catalytic activity towards the C2-substrate ethyl-coenzyme M. Cell extracts fromM. mazeishowed a ratio of ethane-to methane-production of ca. 8% at 37 °C, and about 14% at 49 °C. The level of substrate-promiscuity towards ethyl-coenzyme M forM. marburgensiscell extracts under our assay conditions were much higher than previously reported for purified isoenzyme I, indicating that isoenzyme II is much more promiscuous for ethane formation than isoenzyme I. Our experiments demonstrate that Mcr activity can be quickly and conveniently studiedviacell-free lysates, and that substrate promiscuity towards ethane formation is generally larger than anticipated.

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Expression of divergent methyl/alkyl coenzyme M reductases from uncultured archaea

Cited by 16 publications

References 67 publications

Genomic language model predicts protein co-regulation and function

Genomic language model predicts protein co-regulation and function

The methanogen core and pangenome: conservation and variability across biology’s growth temperature extremes

Methane and ethane production rates by methyl-coenzyme M reductase in cell extracts from different methanogens

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