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      Prophage induction can facilitate the in vitro dispersal of multicellular Streptomyces structures

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          Abstract

          Streptomyces are renowned for their prolific production of specialized metabolites with applications in medicine and agriculture. These multicellular bacteria present a sophisticated developmental cycle and play a key role in soil ecology. Little is known about the impact of Streptomyces phage on bacterial physiology. In this study, we investigated the conditions governing the expression and production of “Samy”, a prophage found in Streptomyces ambofaciens ATCC 23877. This siphoprophage is produced simultaneously with the activation of other mobile genetic elements. Remarkably, the presence and production of Samy increases bacterial dispersal under in vitro stress conditions. Altogether, this study unveiled a new property of a bacteriophage infection in the context of multicellular aggregate dynamics.

          Abstract

          Little is known about the impact of phages on Streptomyces physiology. In this study, induction of the prophage ’Samy’ was found to enhance the dispersal of multicellular aggregates of Streptomyces ambofaciens bacteria in response to stress, likely promoting lineage propagation.

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          Most cited references78

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          STAR: ultrafast universal RNA-seq aligner.

          Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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            Basic local alignment search tool.

            A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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              featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

              Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
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                Author and article information

                Contributors
                Role: Formal analysisRole: InvestigationRole: ValidationRole: Writing – review & editing
                Role: InvestigationRole: VisualizationRole: Writing – review & editing
                Role: InvestigationRole: Writing – review & editing
                Role: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: InvestigationRole: Writing – review & editing
                Role: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: SupervisionRole: Writing – original draft
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: SupervisionRole: Writing – original draft
                Role: Academic Editor
                Journal
                PLoS Biol
                PLoS Biol
                plos
                PLOS Biology
                Public Library of Science (San Francisco, CA USA )
                1544-9173
                1545-7885
                25 July 2024
                July 2024
                25 July 2024
                : 22
                : 7
                : e3002725
                Affiliations
                [1 ] Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), Gif-sur-Yvette, France
                [2 ] Université Paris-Saclay, INRAE, AgroParisTech, Micalis Institute, Jouy-en-Josas, France
                Monash University, AUSTRALIA
                Author notes

                The authors have declared that no competing interests exist.

                [¤a]

                Current address: Medical Research Council London Institute of Medical Sciences, London, United Kingdom

                [¤ b]

                Current address: Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom

                Author information
                https://orcid.org/0000-0003-2535-2208
                Article
                PBIOLOGY-D-24-00044
                10.1371/journal.pbio.3002725
                11302927
                39052683
                862753bc-3b74-410c-b71b-76b208d9fcbe
                © 2024 Jaffal 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
                : 5 January 2024
                : 28 June 2024
                Page count
                Figures: 4, Tables: 0, Pages: 23
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001665, Agence Nationale de la Recherche;
                Award ID: ANR-21-CE12-0044-01
                Award Recipient :
                This work was supported by the Agence Nationale pour la Recherche (ANR-21-CE12-0044-01/STREPTOMICS - https://anr.fr/Projet-ANR-21-CE12-0044 to SBM, HL, SL and VSL). The funding agency had no involvement in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Short Reports
                Biology and Life Sciences
                Organisms
                Viruses
                Bacteriophages
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbial Pathogens
                Fungal Pathogens
                Streptomyces
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogens
                Microbial Pathogens
                Fungal Pathogens
                Streptomyces
                Biology and Life Sciences
                Mycology
                Fungal Pathogens
                Streptomyces
                Biology and Life Sciences
                Genetics
                Genomics
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Genome Annotation
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Genome Annotation
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Transcriptome Analysis
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Transcriptome Analysis
                Biology and Life Sciences
                Genetics
                Genomics
                Microbial Genomics
                Viral Genomics
                Biology and Life Sciences
                Microbiology
                Microbial Genomics
                Viral Genomics
                Biology and Life Sciences
                Microbiology
                Virology
                Viral Genomics
                Research and Analysis Methods
                Microscopy
                Electron Microscopy
                Transmission Electron Microscopy
                Biology and Life Sciences
                Mycology
                Fungal Structure
                Mycelium
                Custom metadata
                vor-update-to-uncorrected-proof
                2024-08-06
                The RNA-seq data generated during this study have been deposited in the NCBI Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/) under the accession code GSE232795 ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE232795). The virome sequencing data are available in the bioproject PRJNA974565 on SRA ( https://www.ncbi.nlm.nih.gov/bioproject/974565). We used RNA-seq data available under the accession code GSE162865 ( https://www-ncbi-nlm-nih-gov.insb.bib.cnrs.fr/geo/query/acc.cgi?acc=GSE232795). Samy phage complete sequence is available on GenBank under the following accession number: OR263580.1. The Bioproject accession number of this study is PRJEB62744. The numeric data used to generate Figs 1A, 2A–2B, 3A–3B, 4A, 4D, 4F, 4G, S2, S3A–S3C, S4 and S11 are available in S1 Data. The scripts used to generate these figures, along with the script used to run the SARTools DESeq2-based R pipeline, are provided in S2 Data. The SARTools statistical report is included in S3 Data.

                Life sciences
                Life sciences

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