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      Plasmids manipulate bacterial behaviour through translational regulatory crosstalk

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          Abstract

          Beyond their role in horizontal gene transfer, conjugative plasmids commonly encode homologues of bacterial regulators. Known plasmid regulator homologues have highly targeted effects upon the transcription of specific bacterial traits. Here, we characterise a plasmid translational regulator, RsmQ, capable of taking global regulatory control in Pseudomonas fluorescens and causing a behavioural switch from motile to sessile lifestyle. RsmQ acts as a global regulator, controlling the host proteome through direct interaction with host mRNAs and interference with the host’s translational regulatory network. This mRNA interference leads to large-scale proteomic changes in metabolic genes, key regulators, and genes involved in chemotaxis, thus controlling bacterial metabolism and motility. Moreover, comparative analyses found RsmQ to be encoded on a large number of divergent plasmids isolated from multiple bacterial host taxa, suggesting the widespread importance of RsmQ for manipulating bacterial behaviour across clinical, environmental, and agricultural niches. RsmQ is a widespread plasmid global translational regulator primarily evolved for host chromosomal control to manipulate bacterial behaviour and lifestyle.

          Abstract

          Plasmids contain homologs of bacterial signaling proteins and use them to manipulate host cells to their benefit. This study describes a widespread plasmid-borne translational regulator that subverts ecological traits in soil bacteria, inducing community organization and promoting plasmid transmission.

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          Most cited references97

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

            Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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              Highly accurate protein structure prediction with AlphaFold

              Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort 1 – 4 , the structures of around 100,000 unique proteins have been determined 5 , but this represents a small fraction of the billions of known protein sequences 6 , 7 . Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence—the structure prediction component of the ‘protein folding problem’ 8 —has been an important open research problem for more than 50 years 9 . Despite recent progress 10 – 14 , existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14) 15 , demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm. AlphaFold predicts protein structures with an accuracy competitive with experimental structures in the majority of cases using a novel deep learning architecture.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: Writing – review & editing
                Role: InvestigationRole: Methodology
                Role: Formal analysisRole: MethodologyRole: Writing – review & editing
                Role: Investigation
                Role: InvestigationRole: Project administrationRole: Resources
                Role: Investigation
                Role: ConceptualizationRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Biol
                PLoS Biol
                plos
                PLOS Biology
                Public Library of Science (San Francisco, CA USA )
                1544-9173
                1545-7885
                14 February 2023
                February 2023
                14 February 2023
                : 21
                : 2
                : e3001988
                Affiliations
                [1 ] Department of Molecular Microbiology, John Innes Centre, Colney Lane, Norwich, United Kingdom
                [2 ] School of Biological Sciences, University of East Anglia, Norwich Research Park, Norwich, Norfolk, United Kingdom
                [3 ] Department of Evolution, Ecology and Behaviour Institute of Infection, Veterinary and Ecological Sciences University of Liverpool, Crown Street, Liverpool, United Kingdom
                [4 ] Department of Animal and Plant Sciences, University of Sheffield, Sheffield, United Kingdom
                [5 ] School of Biosciences, University of Birmingham, Edgbaston, Birmingham, United Kingdom
                [6 ] Division of Evolution and Genomic Sciences, School of Biological Sciences, University of Manchester, Manchester, United Kingdom
                Max Planck Institute for Terrestrial Microbiology: Max-Planck-Institut fur terrestrische Mikrobiologie, GERMANY
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-0069-2727
                https://orcid.org/0000-0003-1959-6820
                Article
                PBIOLOGY-D-22-01641
                10.1371/journal.pbio.3001988
                9928087
                36787297
                fea84019-2188-4304-9ed5-28fb8f4caee8
                © 2023 Thompson et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 27 July 2022
                : 4 January 2023
                Page count
                Figures: 8, Tables: 0, Pages: 35
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/R018154/1
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BBS/E/J/000PR9797
                Award Recipient :
                Funded by: Royal Thai Government Scholarship
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/T004363/1
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/R014884/1
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/R014884/1
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/R014884/2
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/R018154/1
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000270, Natural Environment Research Council;
                Award ID: NE/R008825/1
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000270, Natural Environment Research Council;
                Award ID: NE/R008825/2
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000270, Natural Environment Research Council;
                Award ID: NE/P017584/1
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/R014884/1
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/T010568/1
                Award Recipient :
                JGM and CMAT were supported by BBSRC Responsive mode Grant BB/R018154/1 to JGM. JGM and RHL were supported by BBSRC Institute Strategic Programme Grant BBS/E/J/000PR9797 to the John Innes Centre. SP was supported by a Royal Thai Government PhD Scholarship. AP was supported by UKRI-BBSRC Grant BB/T004363/1 to JGM. JPH was supported by BB/R014884/1. MAB, SF and SMB were supported by BBSRC grants BB/R014884/1, BB/R014884/2, BB/R018154/1 and NERC grants NE/R008825/1, NE/R008825/2. EH is supported by a NERC Independent Research Fellowship NE/P017584/1. RWJ is supported by BBSRC grants BB/R014884/1 and BB/T010568/1. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Genetics
                Gene Types
                Regulator Genes
                Biology and Life Sciences
                Genetics
                Gene Expression
                Protein Translation
                Biology and Life Sciences
                Organisms
                Bacteria
                Pseudomonas
                Pseudomonas Fluorescens
                Biology and life sciences
                Genetics
                DNA
                Forms of DNA
                Plasmids
                Biology and life sciences
                Biochemistry
                Nucleic acids
                DNA
                Forms of DNA
                Plasmids
                Biology and Life Sciences
                Genetics
                Genetic Elements
                Mobile Genetic Elements
                Plasmids
                Biology and Life Sciences
                Genetics
                Genomics
                Mobile Genetic Elements
                Plasmids
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogens
                Virulence Factors
                Pathogen Motility
                Biology and Life Sciences
                Genetics
                Gene Expression
                Gene Regulation
                Transcriptional Control
                Biology and life sciences
                Biochemistry
                Nucleic acids
                RNA
                Messenger RNA
                Biology and Life Sciences
                Biochemistry
                Proteins
                Proteomes
                Custom metadata
                All relevant data are within the paper and its Supporting Information files, with the following exceptions: Processed RNA-seq data is deposited in ArrayExpress (E-MTAB-11868). Experimental data for the proteomic experiments is deposited in ProteomeXchange (PXD033640). Scripts and bioinformatic analyses can be found at www.github.com/jpjh/PLASMAN_RsmQ.

                Life sciences
                Life sciences

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