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Genomic Evidence for Simultaneous Optimization of Transcription and Translation through Codon Variants in the pmoCAB Operon of Type Ia Methanotrophs

Understanding the interplay between genotype and phenotype is a fundamental goal of functional genomics. Methane oxidation is a microbial phenotype with global-scale significance as part of the carbon biogeochemical cycle and a sink for greenhouse gas. Microorganisms that oxidize methane (methanotro...

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Autores principales: Villada, Juan C., Duran, Maria F., Lee, Patrick K. H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6650546/
https://www.ncbi.nlm.nih.gov/pubmed/31337658
http://dx.doi.org/10.1128/mSystems.00342-19
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author Villada, Juan C.
Duran, Maria F.
Lee, Patrick K. H.
author_facet Villada, Juan C.
Duran, Maria F.
Lee, Patrick K. H.
author_sort Villada, Juan C.
collection PubMed
description Understanding the interplay between genotype and phenotype is a fundamental goal of functional genomics. Methane oxidation is a microbial phenotype with global-scale significance as part of the carbon biogeochemical cycle and a sink for greenhouse gas. Microorganisms that oxidize methane (methanotrophs) are taxonomically diverse and widespread around the globe. In methanotrophic bacteria, enzymes in the methane oxidation metabolic module (KEGG module M00174, conversion of methane to formaldehyde) are encoded in four operons (pmoCAB, mmoXYZBCD, mxaFI, and xoxF). Recent reports have suggested that methanotrophs in Proteobacteria acquired methane monooxygenases through horizontal gene transfer. Here, we used a genomic meta-analysis to infer the transcriptional and translational advantages of coding sequences from the methane oxidation metabolic modules of different types of methanotrophs. By analyzing isolate and metagenome-assembled genomes from phylogenetically and geographically diverse sources, we detected an anomalous nucleotide composition bias in the coding sequences of particulate methane monooxygenase genes (pmoCAB) from type Ia methanotrophs. We found that this nucleotide bias increases the level of codon bias by decreasing the GC content in the third base of codons, a strategy that contrasts with that of other coding sequences in the module. Further codon usage analyses uncovered that codon variants of the type Ia pmoCAB coding sequences deviate from the genomic signature to match ribosomal protein-coding sequences. Subsequently, computation of transcription and translation metrics revealed that the pmoCAB coding sequences of type Ia methanotrophs optimize the usage of codon variants to maximize translation efficiency and accuracy, while minimizing the synthesis cost of transcripts and proteins. IMPORTANCE Microbial methane oxidation plays a fundamental role in the biogeochemical cycle of Earth’s system. Recent reports have provided evidence for the acquisition of methane monooxygenases by horizontal gene transfer in methane-oxidizing bacteria from different environments, but how evolution has shaped the coding sequences to execute methanotrophy efficiently remains unexplored. In this work, we provide genomic evidence that among the different types of methanotrophs, type Ia methanotrophs possess a unique coding sequence of the pmoCAB operon that is under positive selection for optimal resource allocation and efficient synthesis of transcripts and proteins. This adaptive trait possibly enables type Ia methanotrophs to respond robustly to fluctuating methane availability and explains their global prevalence.
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spelling pubmed-66505462019-07-29 Genomic Evidence for Simultaneous Optimization of Transcription and Translation through Codon Variants in the pmoCAB Operon of Type Ia Methanotrophs Villada, Juan C. Duran, Maria F. Lee, Patrick K. H. mSystems Research Article Understanding the interplay between genotype and phenotype is a fundamental goal of functional genomics. Methane oxidation is a microbial phenotype with global-scale significance as part of the carbon biogeochemical cycle and a sink for greenhouse gas. Microorganisms that oxidize methane (methanotrophs) are taxonomically diverse and widespread around the globe. In methanotrophic bacteria, enzymes in the methane oxidation metabolic module (KEGG module M00174, conversion of methane to formaldehyde) are encoded in four operons (pmoCAB, mmoXYZBCD, mxaFI, and xoxF). Recent reports have suggested that methanotrophs in Proteobacteria acquired methane monooxygenases through horizontal gene transfer. Here, we used a genomic meta-analysis to infer the transcriptional and translational advantages of coding sequences from the methane oxidation metabolic modules of different types of methanotrophs. By analyzing isolate and metagenome-assembled genomes from phylogenetically and geographically diverse sources, we detected an anomalous nucleotide composition bias in the coding sequences of particulate methane monooxygenase genes (pmoCAB) from type Ia methanotrophs. We found that this nucleotide bias increases the level of codon bias by decreasing the GC content in the third base of codons, a strategy that contrasts with that of other coding sequences in the module. Further codon usage analyses uncovered that codon variants of the type Ia pmoCAB coding sequences deviate from the genomic signature to match ribosomal protein-coding sequences. Subsequently, computation of transcription and translation metrics revealed that the pmoCAB coding sequences of type Ia methanotrophs optimize the usage of codon variants to maximize translation efficiency and accuracy, while minimizing the synthesis cost of transcripts and proteins. IMPORTANCE Microbial methane oxidation plays a fundamental role in the biogeochemical cycle of Earth’s system. Recent reports have provided evidence for the acquisition of methane monooxygenases by horizontal gene transfer in methane-oxidizing bacteria from different environments, but how evolution has shaped the coding sequences to execute methanotrophy efficiently remains unexplored. In this work, we provide genomic evidence that among the different types of methanotrophs, type Ia methanotrophs possess a unique coding sequence of the pmoCAB operon that is under positive selection for optimal resource allocation and efficient synthesis of transcripts and proteins. This adaptive trait possibly enables type Ia methanotrophs to respond robustly to fluctuating methane availability and explains their global prevalence. American Society for Microbiology 2019-07-23 /pmc/articles/PMC6650546/ /pubmed/31337658 http://dx.doi.org/10.1128/mSystems.00342-19 Text en Copyright © 2019 Villada et al. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Villada, Juan C.
Duran, Maria F.
Lee, Patrick K. H.
Genomic Evidence for Simultaneous Optimization of Transcription and Translation through Codon Variants in the pmoCAB Operon of Type Ia Methanotrophs
title Genomic Evidence for Simultaneous Optimization of Transcription and Translation through Codon Variants in the pmoCAB Operon of Type Ia Methanotrophs
title_full Genomic Evidence for Simultaneous Optimization of Transcription and Translation through Codon Variants in the pmoCAB Operon of Type Ia Methanotrophs
title_fullStr Genomic Evidence for Simultaneous Optimization of Transcription and Translation through Codon Variants in the pmoCAB Operon of Type Ia Methanotrophs
title_full_unstemmed Genomic Evidence for Simultaneous Optimization of Transcription and Translation through Codon Variants in the pmoCAB Operon of Type Ia Methanotrophs
title_short Genomic Evidence for Simultaneous Optimization of Transcription and Translation through Codon Variants in the pmoCAB Operon of Type Ia Methanotrophs
title_sort genomic evidence for simultaneous optimization of transcription and translation through codon variants in the pmocab operon of type ia methanotrophs
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6650546/
https://www.ncbi.nlm.nih.gov/pubmed/31337658
http://dx.doi.org/10.1128/mSystems.00342-19
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