1
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Abante J, Wang PL, Salzman J. DIVE: a reference-free statistical approach to diversity-generating and mobile genetic element discovery. Genome Biol 2023; 24:240. [PMID: 37864197 PMCID: PMC10589994 DOI: 10.1186/s13059-023-03038-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Accepted: 08/14/2023] [Indexed: 10/22/2023] Open
Abstract
Diversity-generating and mobile genetic elements are key to microbial and viral evolution and can result in evolutionary leaps. State-of-the-art algorithms to detect these elements have limitations. Here, we introduce DIVE, a new reference-free approach to overcome these limitations using information contained in sequencing reads alone. We show that DIVE has improved detection power compared to existing reference-based methods using simulations and real data. We use DIVE to rediscover and characterize the activity of known and novel elements and generate new biological hypotheses about the mobilome. Building on DIVE, we develop a reference-free framework capable of de novo discovery of mobile genetic elements.
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Affiliation(s)
- Jordi Abante
- Biomedical Data Science, Stanford University, 1265 Welch Rd, Palo Alto, 94305, CA, USA
- Center for Computational, Evolutionary and Human Genomics, Stanford University, 327 Campus Drive, Stanford, 94305, CA, USA
- Current address: Department of Biomedical Sciences, Universitat de Barcelona, Casanova 143, Barcelona, 08036, Spain
| | - Peter L Wang
- Biomedical Data Science, Stanford University, 1265 Welch Rd, Palo Alto, 94305, CA, USA
- Department of Biochemistry, Stanford University, 279 Campus Drive, Stanford, 94305, CA, USA
| | - Julia Salzman
- Biomedical Data Science, Stanford University, 1265 Welch Rd, Palo Alto, 94305, CA, USA.
- Department of Biochemistry, Stanford University, 279 Campus Drive, Stanford, 94305, CA, USA.
- Department of Statistics, Stanford University, 390 Serra Mall, Stanford, 94305, CA, USA.
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2
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Chen J, Basting PJ, Han S, Garfinkel DJ, Bergman CM. Reproducible evaluation of transposable element detectors with McClintock 2 guides accurate inference of Ty insertion patterns in yeast. Mob DNA 2023; 14:8. [PMID: 37452430 PMCID: PMC10347736 DOI: 10.1186/s13100-023-00296-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 06/09/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND Many computational methods have been developed to detect non-reference transposable element (TE) insertions using short-read whole genome sequencing data. The diversity and complexity of such methods often present challenges to new users seeking to reproducibly install, execute, or evaluate multiple TE insertion detectors. RESULTS We previously developed the McClintock meta-pipeline to facilitate the installation, execution, and evaluation of six first-generation short-read TE detectors. Here, we report a completely re-implemented version of McClintock written in Python using Snakemake and Conda that improves its installation, error handling, speed, stability, and extensibility. McClintock 2 now includes 12 short-read TE detectors, auxiliary pre-processing and analysis modules, interactive HTML reports, and a simulation framework to reproducibly evaluate the accuracy of component TE detectors. When applied to the model microbial eukaryote Saccharomyces cerevisiae, we find substantial variation in the ability of McClintock 2 components to identify the precise locations of non-reference TE insertions, with RelocaTE2 showing the highest recall and precision in simulated data. We find that RelocaTE2, TEMP, TEMP2 and TEBreak provide consistent estimates of [Formula: see text]50 non-reference TE insertions per strain and that Ty2 has the highest number of non-reference TE insertions in a species-wide panel of [Formula: see text]1000 yeast genomes. Finally, we show that best-in-class predictors for yeast applied to resequencing data have sufficient resolution to reveal a dyad pattern of integration in nucleosome-bound regions upstream of yeast tRNA genes for Ty1, Ty2, and Ty4, allowing us to extend knowledge about fine-scale target preferences revealed previously for experimentally-induced Ty1 insertions to spontaneous insertions for other copia-superfamily retrotransposons in yeast. CONCLUSION McClintock ( https://github.com/bergmanlab/mcclintock/ ) provides a user-friendly pipeline for the identification of TEs in short-read WGS data using multiple TE detectors, which should benefit researchers studying TE insertion variation in a wide range of different organisms. Application of the improved McClintock system to simulated and empirical yeast genome data reveals best-in-class methods and novel biological insights for one of the most widely-studied model eukaryotes and provides a paradigm for evaluating and selecting non-reference TE detectors in other species.
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Affiliation(s)
- Jingxuan Chen
- Institute of Bioinformatics, University of Georgia, Athens, GA USA
| | | | - Shunhua Han
- Institute of Bioinformatics, University of Georgia, Athens, GA USA
| | - David J. Garfinkel
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA USA
| | - Casey M. Bergman
- Institute of Bioinformatics, University of Georgia, Athens, GA USA
- Department of Genetics, University of Georgia, Athens, GA USA
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3
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Wang L, Zhang X, Zhou X, Bi Y, Wang M, Guo Q, Yang F. Insertion of IS Pa1635 in IS CR1 Creates a Hybrid Promoter for blaPER-1 Resulting in Resistance to Novel β-lactam/β-lactamase Inhibitor Combinations and Cefiderocol. Antimicrob Agents Chemother 2023; 67:e0013523. [PMID: 37212660 PMCID: PMC10269150 DOI: 10.1128/aac.00135-23] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 04/13/2023] [Indexed: 05/23/2023] Open
Abstract
Eleven blaPER-1-positive Pseudomonas aeruginosa clinical isolates showed variable susceptibility to ceftazidime-avibactam (CZA). The genetic contexts of blaPER-1 were identical (ISCR1-blaPER-1-gst) except for the ST697 isolate HS204 (ISCR1-ISPa1635-blaPER-1-gst). The insertion of ISPa1635 in ISCR1 upstream of blaPER-1 created a hybrid promoter, which elevated the blaPER-1 transcription level and resulted in increased resistance to CZA, ceftolozane-tazobactam, cefepime-zidebactam, and cefiderocol. Diversity in the promoter activity of blaPER-1 partially explains the variable susceptibility to CZA in PER-producing isolates.
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Affiliation(s)
- Leilei Wang
- Institute of Antibiotics, Huashan Hospital, Fudan University, Shanghai, China
- Key Laboratory of Clinical Pharmacology of Antibiotics, Ministry of Health, Shanghai, China
| | - Xuefei Zhang
- Institute of Antibiotics, Huashan Hospital, Fudan University, Shanghai, China
- Key Laboratory of Clinical Pharmacology of Antibiotics, Ministry of Health, Shanghai, China
- Department of Clinical Laboratory, Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Xun Zhou
- Institute of Antibiotics, Huashan Hospital, Fudan University, Shanghai, China
- Key Laboratory of Clinical Pharmacology of Antibiotics, Ministry of Health, Shanghai, China
| | - Yingmin Bi
- Institute of Antibiotics, Huashan Hospital, Fudan University, Shanghai, China
- Key Laboratory of Clinical Pharmacology of Antibiotics, Ministry of Health, Shanghai, China
| | - Minggui Wang
- Institute of Antibiotics, Huashan Hospital, Fudan University, Shanghai, China
- Key Laboratory of Clinical Pharmacology of Antibiotics, Ministry of Health, Shanghai, China
| | - Qinglan Guo
- Institute of Antibiotics, Huashan Hospital, Fudan University, Shanghai, China
- Key Laboratory of Clinical Pharmacology of Antibiotics, Ministry of Health, Shanghai, China
| | - Fan Yang
- Institute of Antibiotics, Huashan Hospital, Fudan University, Shanghai, China
- Key Laboratory of Clinical Pharmacology of Antibiotics, Ministry of Health, Shanghai, China
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4
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Chen J, Basting PJ, Han S, Garfinkel DJ, Bergman CM. Reproducible evaluation of transposable element detectors with McClintock 2 guides accurate inference of Ty insertion patterns in yeast. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.13.528343. [PMID: 36824955 PMCID: PMC9948991 DOI: 10.1101/2023.02.13.528343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
BACKGROUND Many computational methods have been developed to detect non-reference transposable element (TE) insertions using short-read whole genome sequencing data. The diversity and complexity of such methods often present challenges to new users seeking to reproducibly install, execute, or evaluate multiple TE insertion detectors. RESULTS We previously developed the McClintock meta-pipeline to facilitate the installation, execution, and evaluation of six first-generation short-read TE detectors. Here, we report a completely re-implemented version of McClintock written in Python using Snakemake and Conda that improves its installation, error handling, speed, stability, and extensibility. McClintock 2 now includes 12 short-read TE detectors, auxiliary pre-processing and analysis modules, interactive HTML reports, and a simulation framework to reproducibly evaluate the accuracy of component TE detectors. When applied to the model microbial eukaryote Saccharomyces cerevisiae, we find substantial variation in the ability of McClintock 2 components to identify the precise locations of non-reference TE insertions, with RelocaTE2 showing the highest recall and precision in simulated data. We find that RelocaTE2, TEMP, TEMP2 and TEBreak provide a consistent and biologically meaningful view of non-reference TE insertions in a species-wide panel of ∼1000 yeast genomes, as evaluated by coverage-based abundance estimates and expected patterns of tRNA promoter targeting. Finally, we show that best-in-class predictors for yeast have sufficient resolution to reveal a dyad pattern of integration in nucleosome-bound regions upstream of yeast tRNA genes for Ty1, Ty2, and Ty4, allowing us to extend knowledge about fine-scale target preferences first revealed experimentally for Ty1 to natural insertions and related copia-superfamily retrotransposons in yeast. CONCLUSION McClintock (https://github.com/bergmanlab/mcclintock/) provides a user-friendly pipeline for the identification of TEs in short-read WGS data using multiple TE detectors, which should benefit researchers studying TE insertion variation in a wide range of different organisms. Application of the improved McClintock system to simulated and empirical yeast genome data reveals best-in-class methods and novel biological insights for one of the most widely-studied model eukaryotes and provides a paradigm for evaluating and selecting non-reference TE detectors for other species.
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Affiliation(s)
- Jingxuan Chen
- Institute of Bioinformatics, University of Georgia, Athens, GA
| | | | - Shunhua Han
- Institute of Bioinformatics, University of Georgia, Athens, GA
| | - David J. Garfinkel
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA
| | - Casey M. Bergman
- Institute of Bioinformatics, University of Georgia, Athens, GA
- Department of Genetics, University of Georgia, Athens, GA
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5
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Two modes of evolution shape bacterial strain diversity in the mammalian gut for thousands of generations. Nat Commun 2022; 13:5604. [PMID: 36153389 PMCID: PMC9509342 DOI: 10.1038/s41467-022-33412-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 09/14/2022] [Indexed: 11/17/2022] Open
Abstract
How and at what pace bacteria evolve when colonizing healthy hosts remains unclear. Here, by monitoring evolution for more than six thousand generations in the mouse gut, we show that the successful colonization of an invader Escherichia coli depends on the diversity of the existing microbiota and the presence of a closely related strain. Following colonization, two modes of evolution were observed: one in which diversifying selection leads to long-term coexistence of ecotypes and a second in which directional selection propels selective sweeps. These modes can be quantitatively distinguished by the statistics of mutation trajectories. In our experiments, diversifying selection was marked by the emergence of metabolic mutations, and directional selection by acquisition of prophages, which bring their own benefits and costs. In both modes, we observed parallel evolution, with mutation accumulation rates comparable to those typically observed in vitro on similar time scales. Our results show how rapid ecotype formation and phage domestication can be in the mammalian gut. Here, the authors show that a colonizing bacterial strain evolves in the gut by either generating ecotypes or continuously fixing beneficial mutations. They associate the first mode to metabolic mutations and the second to domestication of bacteriophages that are incorporated into the bacterial genome.
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6
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Song R, Wang Z, Wang H, Zhang H, Wang X, Nguyen H, Holding D, Yu B, Clemente T, Jia S, Zhang C. InMut-finder: a software tool for insertion identification in mutagenesis using Nanopore long reads. BMC Genomics 2021; 22:908. [PMID: 34923956 PMCID: PMC8684674 DOI: 10.1186/s12864-021-08206-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 11/24/2021] [Indexed: 11/24/2022] Open
Abstract
Background Biological mutagens (such as transposon) with sequences inserted, play a crucial role to link observed phenotype and genotype in reverse genetic studies. For this reason, accurate and efficient software tools for identifying insertion sites based on the analysis of sequencing reads are desired. Results We developed a bioinformatics tool, a Finder, to identify genome-wide Insertions in Mutagenesis (named as “InMut-Finder”), based on target sequences and flanking sequences from long reads, such as Oxford Nanopore Sequencing. InMut-Finder succeeded in identify > 100 insertion sites in Medicago truncatula and soybean mutants based on sequencing reads of whole-genome DNA or enriched insertion-site DNA fragments. Insertion sites discovered by InMut-Finder were validated by PCR experiments. Conclusion InMut-Finder is a comprehensive and powerful tool for automated insertion detection from Nanopore long reads. The simplicity, efficiency, and flexibility of InMut-Finder make it a valuable tool for functional genomics and forward and reverse genetics. InMut-Finder was implemented with Perl, R, and Shell scripts, which are independent of the OS. The source code and instructions can be accessed at https://github.com/jsg200830/InMut-Finder. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-08206-9.
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Affiliation(s)
- Rui Song
- College of Grassland Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Ziyao Wang
- College of Grassland Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Hui Wang
- College of Grassland Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Han Zhang
- College of Grassland Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Xuemeng Wang
- College of Grassland Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Hanh Nguyen
- Department of Agronomy and Horticulture, Center for Plant Science Innovation, Beadle Center for Biotechnology, University of Nebraska, Lincoln, NE, 68588, USA
| | - David Holding
- Department of Agronomy and Horticulture, Center for Plant Science Innovation, Beadle Center for Biotechnology, University of Nebraska, Lincoln, NE, 68588, USA.,Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE, 68588, USA
| | - Bin Yu
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE, 68588, USA.,School of Biological Sciences, Center for Plant Science Innovation, Beadle Center for Biotechnology, University of Nebraska, Lincoln, NE, 68588, USA
| | - Tom Clemente
- Department of Agronomy and Horticulture, Center for Plant Science Innovation, Beadle Center for Biotechnology, University of Nebraska, Lincoln, NE, 68588, USA
| | - Shangang Jia
- College of Grassland Science and Technology, China Agricultural University, Beijing, 100193, China.
| | - Chi Zhang
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE, 68588, USA. .,School of Biological Sciences, Center for Plant Science Innovation, Beadle Center for Biotechnology, University of Nebraska, Lincoln, NE, 68588, USA.
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7
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Ross K, Varani AM, Snesrud E, Huang H, Alvarenga DO, Zhang J, Wu C, McGann P, Chandler M. TnCentral: a Prokaryotic Transposable Element Database and Web Portal for Transposon Analysis. mBio 2021; 12:e0206021. [PMID: 34517763 PMCID: PMC8546635 DOI: 10.1128/mbio.02060-21] [Citation(s) in RCA: 60] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 08/11/2021] [Indexed: 01/03/2023] Open
Abstract
We describe here the structure and organization of TnCentral (https://tncentral.proteininformationresource.org/ [or the mirror link at https://tncentral.ncc.unesp.br/]), a web resource for prokaryotic transposable elements (TE). TnCentral currently contains ∼400 carefully annotated TE, including transposons from the Tn3, Tn7, Tn402, and Tn554 families; compound transposons; integrons; and associated insertion sequences (IS). These TE carry passenger genes, including genes conferring resistance to over 25 classes of antibiotics and nine types of heavy metal, as well as genes responsible for pathogenesis in plants, toxin/antitoxin gene pairs, transcription factors, and genes involved in metabolism. Each TE has its own entry page, providing details about its transposition genes, passenger genes, and other sequence features required for transposition, as well as a graphical map of all features. TnCentral content can be browsed and queried through text- and sequence-based searches with a graphic output. We describe three use cases, which illustrate how the search interface, results tables, and entry pages can be used to explore and compare TE. TnCentral also includes downloadable software to facilitate user-driven identification, with manual annotation, of certain types of TE in genomic sequences. Through the TnCentral homepage, users can also access TnPedia, which provides comprehensive reviews of the major TE families, including an extensive general section and specialized sections with descriptions of insertion sequence and transposon families. TnCentral and TnPedia are intuitive resources that can be used by clinicians and scientists to assess TE diversity in clinical, veterinary, and environmental samples. IMPORTANCE The ability of bacteria to undergo rapid evolution and adapt to changing environmental circumstances drives the public health crisis of multiple antibiotic resistance, as well as outbreaks of disease in economically important agricultural crops and animal husbandry. Prokaryotic transposable elements (TE) play a critical role in this. Many carry "passenger genes" (not required for the transposition process) conferring resistance to antibiotics or heavy metals or causing disease in plants and animals. Passenger genes are spread by normal TE transposition activities and by insertion into plasmids, which then spread via conjugation within and across bacterial populations. Thus, an understanding of TE composition and transposition mechanisms is key to developing strategies to combat bacterial pathogenesis. Toward this end, we have developed TnCentral, a bioinformatics resource dedicated to describing and exploring the structural and functional features of prokaryotic TE whose use is intuitive and accessible to users with or without bioinformatics expertise.
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Affiliation(s)
- Karen Ross
- Protein Information Resource, Department of Biochemistry and Molecular and Cellular Biology, Georgetown University Medical Center, Washington, DC, USA
| | - Alessandro M. Varani
- School of Agricultural and Veterinary Sciences, Universidade Estadual Paulista, Jaboticabal, Sao Paulo, Brazil
| | - Erik Snesrud
- Multidrug-Resistant Organism Repository and Surveillance Network, Walter Reed Army Institute of Research, Silver Spring, Maryland, USA
| | - Hongzhan Huang
- Protein Information Resource, Center for Bioinformatics and Computational Biology, University of Delaware, Newark, Delaware, USA
| | - Danillo Oliveira Alvarenga
- School of Agricultural and Veterinary Sciences, Universidade Estadual Paulista, Jaboticabal, Sao Paulo, Brazil
| | - Jian Zhang
- Protein Information Resource, Department of Biochemistry and Molecular and Cellular Biology, Georgetown University Medical Center, Washington, DC, USA
| | - Cathy Wu
- Protein Information Resource, Center for Bioinformatics and Computational Biology, University of Delaware, Newark, Delaware, USA
| | - Patrick McGann
- Multidrug-Resistant Organism Repository and Surveillance Network, Walter Reed Army Institute of Research, Silver Spring, Maryland, USA
| | - Mick Chandler
- Department of Biochemistry and Molecular and Cellular Biology, Georgetown University Medical Center, Washington, DC, USA
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Petitjean M, Juarez P, Meunier A, Daguindau E, Puja H, Bertrand X, Valot B, Hocquet D. The rise and the fall of a Pseudomonas aeruginosa endemic lineage in a hospital. Microb Genom 2021; 7. [PMID: 34473016 PMCID: PMC8715434 DOI: 10.1099/mgen.0.000629] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
The biological features that allow a pathogen to survive in the hospital environment are mostly unknown. The extinction of bacterial epidemics in hospitals is mostly attributed to changes in medical practice, including infection control, but the role of bacterial adaptation has never been documented. We analysed a collection of Pseudomonas aeruginosa isolates belonging to the Besançon Epidemic Strain (BES), responsible for a 12year nosocomial outbreak, using a genotype-to-phenotype approach. Bayesian analysis estimated the emergence of the clone in the hospital 5 years before its opening, during the creation of its water distribution network made of copper. BES survived better than the reference strains PAO1 and PA14 in a copper solution due to a genomic island containing 13 metal-resistance genes and was specifically able to proliferate in the ubiquitous amoeba Vermamoeba vermiformis. Mutations affecting amino-acid metabolism, antibiotic resistance, lipopolysaccharide biosynthesis, and regulation were enriched during the spread of BES. Seven distinct regulatory mutations attenuated the overexpression of the genes encoding the efflux pump MexAB-OprM over time. The fitness of BES decreased over time in correlation with its genome size. Overall, the resistance to inhibitors and predators presumably aided the proliferation and propagation of BES in the plumbing system of the hospital. The pathogen further spread among patients via multiple routes of contamination. The decreased prevalence of patients infected by BES mirrored the parallel and convergent genomic evolution and reduction that affected bacterial fitness. Along with infection control measures, this may have participated in the extinction of BES in the hospital setting.
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Affiliation(s)
- Marie Petitjean
- Hygiène Hospitalière, Centre Hospitalier Universitaire, 25030 Besançon, France.,UMR CNRS 6249, Université de Bourgogne Franche-Comté, 25030 Besançon, France
| | - Paulo Juarez
- UMR CNRS 6249, Université de Bourgogne Franche-Comté, 25030 Besançon, France
| | - Alexandre Meunier
- Hygiène Hospitalière, Centre Hospitalier Universitaire, 25030 Besançon, France
| | - Etienne Daguindau
- UMR INSERM 1098, Université de Bourgogne Franche-Comté, 25030 Besançon, France
| | - Hélène Puja
- UMR CNRS 6249, Université de Bourgogne Franche-Comté, 25030 Besançon, France
| | - Xavier Bertrand
- Hygiène Hospitalière, Centre Hospitalier Universitaire, 25030 Besançon, France.,UMR CNRS 6249, Université de Bourgogne Franche-Comté, 25030 Besançon, France
| | - Benoit Valot
- UMR CNRS 6249, Université de Bourgogne Franche-Comté, 25030 Besançon, France.,Bioinformatique et Big Data au Service de la Santé, UFR Science de la Santé, Université de Bourgogne Franche-Comté, 25030 Besançon, France
| | - Didier Hocquet
- Hygiène Hospitalière, Centre Hospitalier Universitaire, 25030 Besançon, France.,UMR CNRS 6249, Université de Bourgogne Franche-Comté, 25030 Besançon, France.,Bioinformatique et Big Data au Service de la Santé, UFR Science de la Santé, Université de Bourgogne Franche-Comté, 25030 Besançon, France.,Centre de Ressources Biologiques - Filière Microbiologique de Besançon, Centre Hospitalier Universitaire, 25030 Besançon, France
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9
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Mogro EG, Ambrosis NM, Lozano MJ. Easy identification of insertion sequence mobilization events in related bacterial strains with ISCompare. G3 (BETHESDA, MD.) 2021; 11:6303613. [PMID: 34849821 PMCID: PMC8496243 DOI: 10.1093/g3journal/jkab181] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 05/17/2021] [Indexed: 12/02/2022]
Abstract
Bacterial genomes are composed of core and accessory genomes. The first is composed of housekeeping and essential genes, while the second is highly enriched in mobile genetic elements, including transposable elements (TEs). Insertion sequences (ISs), the smallest TEs, have an important role in genome evolution, and contribute to bacterial genome plasticity and adaptability. ISs can spread in a genome, presenting different locations in nearly related strains, and producing phenotypic variations. Few tools are available which can identify differentially located ISs (DLISs) on assembled genomes. Here, we introduce ISCompare, a new program to profile IS mobilization events in related bacterial strains using complete or draft genome assemblies. ISCompare was validated using artificial genomes with simulated random IS insertions and real sequences, achieving the same or better results than other available tools, with the advantage that ISCompare can analyze multiple ISs at the same time and outputs a list of candidate DLISs. ISCompare provides an easy and straightforward approach to look for differentially located ISs on bacterial genomes.
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Affiliation(s)
- Ezequiel G Mogro
- Departamento de Ciencias Biológicas, Facultad de Ciencias Exactas, IBBM-Instituto de Biotecnología y Biología Molecular, CONICET, CCT-La Plata, Universidad Nacional de La Plata, La Plata 1900, Argentina
| | - Nicolás M Ambrosis
- Departamento de Ciencias Biológicas, Facultad de Ciencias Exactas, IBBM-Instituto de Biotecnología y Biología Molecular, CONICET, CCT-La Plata, Universidad Nacional de La Plata, La Plata 1900, Argentina
| | - Mauricio J Lozano
- Departamento de Ciencias Biológicas, Facultad de Ciencias Exactas, IBBM-Instituto de Biotecnología y Biología Molecular, CONICET, CCT-La Plata, Universidad Nacional de La Plata, La Plata 1900, Argentina
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10
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Intragenic Distribution of IS 6110 in Clinical Mycobacterium tuberculosis Strains: Bioinformatic Evidence for Gene Disruption Leading to Underdiagnosed Antibiotic Resistance. Microbiol Spectr 2021; 9:e0001921. [PMID: 34287057 PMCID: PMC8552512 DOI: 10.1128/spectrum.00019-21] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Antibiotic resistance is a global challenge for tuberculosis control, and accelerating its diagnosis is critical for therapy decisions and controlling transmission. Genotype-based molecular diagnostics now play an increasing role in accelerating the detection of such antibiotic resistance, but their accuracy depends on the instructed detection of genetic variations. Genetic mobile elements such as IS6110 are established sources of genetic variation in Mycobacterium tuberculosis, but their implication in clinical antibiotic resistance has thus far been unclear. Here, we describe the discovery of an intragenic IS6110 insertion into Rv0678 that caused antibiotic resistance in an in vitro-selected M. tuberculosis isolate. The subsequent development of bioinformatics scripts allowed genome-wide analysis of intragenic IS6110 insertions causing gene disruptions in 6,426 clinical M. tuberculosis strains. This analysis identified 10,070 intragenic IS6110 insertions distributed among 333 different genes. Focusing on genes whose disruption leads to antibiotic resistance, 12 clinical isolates were identified with high confidence to be resistant to bedaquiline, clofazimine, pyrazinamide, ethionamide, and para-aminosalicylic acid because of an IS6110-mediated gene disruption event. A number of these IS6110-mediated resistant strains had identical genomic distributions of IS6110 elements and likely represent transmission events of a single resistant isolate. These data provide strong evidence that IS6110-mediated gene disruption is a clinically relevant mechanism of antibiotic resistance in M. tuberculosis that should be considered for molecular diagnostics. Concomitantly, this analysis provides a list of 333 IS6110-disrupted genes in clinical tuberculosis isolates that can be deemed nonessential for human infection. IMPORTANCE To help control the spread of drug-resistant tuberculosis and to guide treatment choices, it is important that rapid and accurate molecular diagnostic tools are used. Current molecular diagnostic tools detect the most common antibiotic-resistance-conferring mutations in the form of single nucleotide changes, small deletions, or insertions. Mobile genetic elements, named IS6110, are also known to move within the M. tuberculosis genome and cause significant genetic variations, although the role of this variation in clinical drug resistance remains unclear. In this work, we show that both in vitro and in data analyzed from 6,426 clinical M. tuberculosis strains, IS6110 elements are found that disrupt specific genes essential for the function of a number of pivotal antituberculosis drugs. By providing ample evidence of clinically relevant IS6110-mediated drug resistance, we believe that this shows that this form of genetic variation must not be overlooked in molecular diagnostics of drug resistance.
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11
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digIS: towards detecting distant and putative novel insertion sequence elements in prokaryotic genomes. BMC Bioinformatics 2021; 22:258. [PMID: 34016050 PMCID: PMC8147514 DOI: 10.1186/s12859-021-04177-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 05/09/2021] [Indexed: 12/02/2022] Open
Abstract
Background The insertion sequence elements (IS elements) represent the smallest and the most abundant mobile elements in prokaryotic genomes. It has been shown that they play a significant role in genome organization and evolution. To better understand their function in the host genome, it is desirable to have an effective detection and annotation tool. This need becomes even more crucial when considering rapid-growing genomic and metagenomic data. The existing tools for IS elements detection and annotation are usually based on comparing sequence similarity with a database of known IS families. Thus, they have limited ability to discover distant and putative novel IS elements. Results In this paper, we present digIS, a software tool based on profile hidden Markov models assembled from catalytic domains of transposases. It shows a very good performance in detecting known IS elements when tested on datasets with manually curated annotation. The main contribution of digIS is in its ability to detect distant and putative novel IS elements while maintaining a moderate level of false positives. In this category it outperforms existing tools, especially when tested on large datasets of archaeal and bacterial genomes. Conclusion We provide digIS, a software tool using a novel approach based on manually curated profile hidden Markov models, which is able to detect distant and putative novel IS elements. Although digIS can find known IS elements as well, we expect it to be used primarily by scientists interested in finding novel IS elements. The tool is available at https://github.com/janka2012/digIS. Supplementary Information The online version contains supplementary material available at 10.1186/s12859-021-04177-6.
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Abstract
By evolving strains of E. coli that hyper-resist sedimentation, we discovered an uncharacterized mechanism that bacteria can use to remain in suspension indefinitely without expending energy. This unusual phenotype was traced to the anchoring of long colanic acid polymers (CAP) that project from the cell surface. Although each characterized mutant activated this same mechanism, the genes responsible and the strengths of the phenotypes varied. Mutations in rcsC, lpp, igaA, or the yjbEFGH operon were sufficient to stimulate sedimentation resistance, while mutations altering the cps promoter, cdgI, or yjbF provided phenotypic enhancements. The sedimentation resistances changed in response to temperature, growth phase, and carbon source and each mutant exhibited significantly reduced biofilm formation. We discovered that the degree of colony mucoidy exhibited by these mutants was not related to the degree of Rcs pathways activation or to the amount of CAP that was produced; rather, it was related to the fraction of CAP that was shed as a true exopolysaccharide. Therefore, these and other mutations that activate this phenotype are likely to be absent from genetic screens that relied on centrifugation to harvest bacteria. We also found that this anchored CAP form is not linked to LPS cores and may not be attached to the outer membrane.IMPORTANCEBacteria can partition in aqueous environments between surface-dwelling, planktonic, sedimentary, and biofilm forms. Residence in each location provides an advantage depending on nutritional and environmental stresses and a community of a single species is often observed to be distributed throughout two or more of these niches. Another adaptive strategy is to produce an extracellular capsule, which provides an environmental shield for the microbe and can allow escape from predators and immune systems. We discovered that bacteria can either shed or stably anchor capsules to dramatically alter their propensity to sediment. The degree to which the bacteria anchor their capsule is controlled by a stress sensing system, suggesting that anchoring may be used as an adaptive response to severe environmental challenges.
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Lapp Z, Han JH, Wiens J, Goldstein EJC, Lautenbach E, Snitkin ES. Patient and Microbial Genomic Factors Associated with Carbapenem-Resistant Klebsiella pneumoniae Extraintestinal Colonization and Infection. mSystems 2021; 6:e00177-21. [PMID: 33727393 PMCID: PMC8546970 DOI: 10.1128/msystems.00177-21] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 02/23/2021] [Indexed: 11/30/2022] Open
Abstract
Carbapenem-resistant Klebsiella pneumoniae (CRKP) is a critical-priority antibiotic resistance threat that has emerged over the past several decades, spread across the globe, and accumulated resistance to last-line antibiotic agents. While CRKP infections are associated with high mortality, only a subset of patients acquiring CRKP extraintestinal colonization will develop clinical infection. Here, we sought to ascertain the relative importance of patient characteristics and CRKP genetic background in determining patient risk of infection. Machine learning models classifying colonization versus infection were built using whole-genome sequences and clinical metadata from a comprehensive set of 331 CRKP extraintestinal isolates collected across 21 long-term acute-care hospitals over the course of a year. Model performance was evaluated based on area under the receiver operating characteristic curve (AUROC) on held-out test data. We found that patient and genomic features were predictive of clinical CRKP infection to similar extents (AUROC interquartile ranges [IQRs]: patient = 0.59 to 0.68, genomic = 0.55 to 0.61, combined = 0.62 to 0.68). Patient predictors of infection included the presence of indwelling devices, kidney disease, and length of stay. Genomic predictors of infection included presence of the ICEKp10 mobile genetic element carrying the yersiniabactin iron acquisition system and disruption of an O-antigen biosynthetic gene in a sublineage of the epidemic ST258 clone. Altered O-antigen biosynthesis increased association with the respiratory tract, and subsequent ICEKp10 acquisition was associated with increased virulence. These results highlight the potential of integrated models including both patient and microbial features to provide a more holistic understanding of patient clinical trajectories and ongoing within-lineage pathogen adaptation.IMPORTANCE Multidrug-resistant organisms, such as carbapenem-resistant Klebsiella pneumoniae (CRKP), colonize alarmingly large fractions of patients in regions of endemicity, but only a subset of patients develop life-threatening infections. While patient characteristics influence risk for infection, the relative contribution of microbial genetic background to patient risk remains unclear. We used machine learning to determine whether patient and/or microbial characteristics can discriminate between CRKP extraintestinal colonization and infection across multiple health care facilities and found that both patient and microbial factors were predictive. Examination of informative microbial genetic features revealed variation within the ST258 epidemic lineage that was associated with respiratory tract colonization and increased rates of infection. These findings indicate that circulating genetic variation within a highly prevalent epidemic lineage of CRKP influences patient clinical trajectories. In addition, this work supports the need for future studies examining the microbial genetic determinants of clinical outcomes in human populations, as well as epidemiologic and experimental follow-ups of identified features to discern generalizability and biological mechanisms.
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Affiliation(s)
- Zena Lapp
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
| | | | - Jenna Wiens
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan, USA
| | - Ellie J C Goldstein
- R. M. Alden Research Laboratory, Culver City, California, USA
- David Geffen School of Medicine, University of California, Los Angeles, Santa Monica, California, USA
| | - Ebbing Lautenbach
- Department of Medicine (Infectious Diseases), University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Evan S Snitkin
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA
- Department of Internal Medicine/Division of Infectious Diseases, University of Michigan, Ann Arbor, Michigan, USA
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Blake KS, Choi J, Dantas G. Approaches for characterizing and tracking hospital-associated multidrug-resistant bacteria. Cell Mol Life Sci 2021; 78:2585-2606. [PMID: 33582841 PMCID: PMC8005480 DOI: 10.1007/s00018-020-03717-2] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Revised: 10/26/2020] [Accepted: 11/17/2020] [Indexed: 12/24/2022]
Abstract
Hospital-associated infections are a major concern for global public health. Infections with antibiotic-resistant pathogens can cause empiric treatment failure, and for infections with multidrug-resistant bacteria which can overcome antibiotics of "last resort" there exists no alternative treatments. Despite extensive sanitization protocols, the hospital environment is a potent reservoir and vector of antibiotic-resistant organisms. Pathogens can persist on hospital surfaces and plumbing for months to years, acquire new antibiotic resistance genes by horizontal gene transfer, and initiate outbreaks of hospital-associated infections by spreading to patients via healthcare workers and visitors. Advancements in next-generation sequencing of bacterial genomes and metagenomes have expanded our ability to (1) identify species and track distinct strains, (2) comprehensively profile antibiotic resistance genes, and (3) resolve the mobile elements that facilitate intra- and intercellular gene transfer. This information can, in turn, be used to characterize the population dynamics of hospital-associated microbiota, track outbreaks to their environmental reservoirs, and inform future interventions. This review provides a detailed overview of the approaches and bioinformatic tools available to study isolates and metagenomes of hospital-associated bacteria, and their multi-layered networks of transmission.
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Affiliation(s)
- Kevin S Blake
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
| | - JooHee Choi
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Gautam Dantas
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
- Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, 63130, USA.
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Guo J, Cao K, Deng C, Li Y, Zhu G, Fang W, Chen C, Wang X, Wu J, Guan L, Wu S, Guo W, Yao JL, Fei Z, Wang L. An integrated peach genome structural variation map uncovers genes associated with fruit traits. Genome Biol 2020; 21:258. [PMID: 33023652 PMCID: PMC7539501 DOI: 10.1186/s13059-020-02169-y] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Accepted: 09/23/2020] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Genome structural variations (SVs) have been associated with key traits in a wide range of agronomically important species; however, SV profiles of peach and their functional impacts remain largely unexplored. RESULTS Here, we present an integrated map of 202,273 SVs from 336 peach genomes. A substantial number of SVs have been selected during peach domestication and improvement, which together affect 2268 genes. Genome-wide association studies of 26 agronomic traits using these SVs identify a number of candidate causal variants. A 9-bp insertion in Prupe.4G186800, which encodes a NAC transcription factor, is shown to be associated with early fruit maturity, and a 487-bp deletion in the promoter of PpMYB10.1 is associated with flesh color around the stone. In addition, a 1.67 Mb inversion is highly associated with fruit shape, and a gene adjacent to the inversion breakpoint, PpOFP1, regulates flat shape formation. CONCLUSIONS The integrated peach SV map and the identified candidate genes and variants represent valuable resources for future genomic research and breeding in peach.
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Affiliation(s)
- Jian Guo
- Zhengzhou Fruit Research Institute, Chinese Academy of Agricultural Sciences, Zhengzhou, China
- College of Horticulture & Forestry Sciences, Huazhong Agricultural University, Wuhan, China
| | - Ke Cao
- Zhengzhou Fruit Research Institute, Chinese Academy of Agricultural Sciences, Zhengzhou, China
| | - Cecilia Deng
- The New Zealand Institute for Plant & Food Research Limited, Private Bag 92169, Auckland, 1142, New Zealand
| | - Yong Li
- Zhengzhou Fruit Research Institute, Chinese Academy of Agricultural Sciences, Zhengzhou, China
| | - Gengrui Zhu
- Zhengzhou Fruit Research Institute, Chinese Academy of Agricultural Sciences, Zhengzhou, China
| | - Weichao Fang
- Zhengzhou Fruit Research Institute, Chinese Academy of Agricultural Sciences, Zhengzhou, China
| | - Changwen Chen
- Zhengzhou Fruit Research Institute, Chinese Academy of Agricultural Sciences, Zhengzhou, China
| | - Xinwei Wang
- Zhengzhou Fruit Research Institute, Chinese Academy of Agricultural Sciences, Zhengzhou, China
| | - Jinlong Wu
- Zhengzhou Fruit Research Institute, Chinese Academy of Agricultural Sciences, Zhengzhou, China
| | - Liping Guan
- Zhengzhou Fruit Research Institute, Chinese Academy of Agricultural Sciences, Zhengzhou, China
| | - Shan Wu
- Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, NY, USA
| | - Wenwu Guo
- College of Horticulture & Forestry Sciences, Huazhong Agricultural University, Wuhan, China
| | - Jia-Long Yao
- The New Zealand Institute for Plant & Food Research Limited, Private Bag 92169, Auckland, 1142, New Zealand.
| | - Zhangjun Fei
- Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, NY, USA.
- US Department of Agriculture-Agricultural Research Service, Robert W. Holley Center for Agriculture and Health, Ithaca, NY, USA.
| | - Lirong Wang
- Zhengzhou Fruit Research Institute, Chinese Academy of Agricultural Sciences, Zhengzhou, China.
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Barreto HC, Frazão N, Sousa A, Konrad A, Gordo I. Mutation accumulation and horizontal gene transfer in Escherichia coli colonizing the gut of old mice. Commun Integr Biol 2020; 13:89-96. [PMID: 33014261 PMCID: PMC7518454 DOI: 10.1080/19420889.2020.1783059] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 06/09/2020] [Accepted: 06/10/2020] [Indexed: 12/03/2022] Open
Abstract
The ecology and environment of the microbes that inhabit the mammalian intestine undergoes several changes as the host ages. Here, we ask if the selection pressure experienced by a new strain colonizing the aging gut differs from that in the gut of young adults. Using experimental evolution in mice after a short antibiotic treatment, as a model for a common clinical situation, we show that a new colonizing E. coli strain rapidly adapts to the aging gut via both mutation accumulation and bacteriophage-mediated horizontal gene transfer (HGT). The pattern of evolution of E. coli in aging mice is characterized by a larger number of transposable element insertions and intergenic mutations compared to that in young mice, which is consistent with the gut of aging hosts harboring a stressful and iron limiting environment.
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Affiliation(s)
| | | | - Ana Sousa
- IBiMed, Institute for Biomedicine, Universidade de Aveiro, Aveiro, Portugal
| | - Anke Konrad
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Isabel Gordo
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
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Couchoud C, Bertrand X, Valot B, Hocquet D. Deciphering the role of insertion sequences in the evolution of bacterial epidemic pathogens with panISa software. Microb Genom 2020; 6:e000356. [PMID: 32213253 PMCID: PMC7371109 DOI: 10.1099/mgen.0.000356] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Accepted: 03/02/2020] [Indexed: 11/18/2022] Open
Abstract
Next-generation sequencing (NGS) is now widely used in microbiology to explore genome evolution and the structure of pathogen outbreaks. Bioinformatics pipelines readily detect single-nucleotide polymorphisms or short indels. However, bacterial genomes also evolve through the action of small transposable elements called insertion sequences (ISs), which are difficult to detect due to their short length and multiple repetitions throughout the genome. We designed panISa software for the ab initio detection of IS insertions in the genomes of prokaryotes. PanISa has been released as open source software (GPL3) available from https://github.com/bvalot/panISa. In this study, we assessed the utility of this software for evolutionary studies, by reanalysing five published datasets for outbreaks of human major pathogens in which ISs had not been specifically investigated. We reanalysed the raw data from each study, by aligning the reads against reference genomes and running panISa on the alignments. Each hit was automatically curated and IS-related events were validated on the basis of nucleotide sequence similarity, by comparison with the ISFinder database. In Acinetobacter baumannii, the panISa pipeline identified ISAba1 or ISAba125 upstream from the ampC gene, which encodes a cephalosporinase in all third-generation cephalosporin-resistant isolates. In the genomes of Vibrio cholerae isolates, we found that early Haitian isolates had the same ISs as Nepalese isolates, confirming the inferred history of the contamination of this island. In Enterococcus faecalis, panISa identified regions of high plasticity, including a pathogenicity island enriched in IS-related events. The overall distribution of ISs deduced with panISa was consistent with SNP-based phylogenic trees, for all species considered. The role of ISs in pathogen evolution has probably been underestimated due to difficulties detecting these transposable elements. We show here that panISa is a useful addition to the bioinformatics toolbox for analyses of the evolution of bacterial genomes. PanISa will facilitate explorations of the functional impact of ISs and improve our understanding of prokaryote evolution.
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Affiliation(s)
- Charlotte Couchoud
- Laboratoire d’Hygiène Hospitalière, Centre Hospitalier Régional Universitaire, Besançon, France
- UMR CNRS 6249 Chrono-environnement, Université de Bourgogne Franche-Comté, Besançon, France
| | - Xavier Bertrand
- Laboratoire d’Hygiène Hospitalière, Centre Hospitalier Régional Universitaire, Besançon, France
- UMR CNRS 6249 Chrono-environnement, Université de Bourgogne Franche-Comté, Besançon, France
| | - Benoit Valot
- UMR CNRS 6249 Chrono-environnement, Université de Bourgogne Franche-Comté, Besançon, France
- Bioinformatique et big data au service de la santé, UFR Santé, Université de Bourgogne Franche-Comté, Besançon, France
| | - Didier Hocquet
- Laboratoire d’Hygiène Hospitalière, Centre Hospitalier Régional Universitaire, Besançon, France
- UMR CNRS 6249 Chrono-environnement, Université de Bourgogne Franche-Comté, Besançon, France
- Bioinformatique et big data au service de la santé, UFR Santé, Université de Bourgogne Franche-Comté, Besançon, France
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Durrant MG, Li MM, Siranosian BA, Montgomery SB, Bhatt AS. A Bioinformatic Analysis of Integrative Mobile Genetic Elements Highlights Their Role in Bacterial Adaptation. Cell Host Microbe 2020; 27:140-153.e9. [PMID: 31862382 PMCID: PMC6952549 DOI: 10.1016/j.chom.2019.10.022] [Citation(s) in RCA: 98] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2019] [Revised: 06/18/2019] [Accepted: 10/29/2019] [Indexed: 11/26/2022]
Abstract
Mobile genetic elements (MGEs) contribute to bacterial adaptation and evolution; however, high-throughput, unbiased MGE detection remains challenging. We describe MGEfinder, a bioinformatic toolbox that identifies integrative MGEs and their insertion sites by using short-read sequencing data. MGEfinder identifies the genomic site of each MGE insertion and infers the identity of the inserted sequence. We apply MGEfinder to 12,374 sequenced isolates of 9 prevalent bacterial pathogens, including Mycobacterium tuberculosis, Staphylococcus aureus, and Escherichia coli, and identify thousands of MGEs, including candidate insertion sequences, conjugative transposons, and prophage elements. The MGE repertoire and insertion rates vary across species, and integration sites often cluster near genes related to antibiotic resistance, virulence, and pathogenicity. MGE insertions likely contribute to antibiotic resistance in laboratory experiments and clinical isolates. Additionally, we identified thousands of mobility genes, a subset of which have unknown function opening avenues for exploration. Future application of MGEfinder to commensal bacteria will further illuminate bacterial adaptation and evolution.
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Affiliation(s)
- Matthew G Durrant
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Michelle M Li
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | | | - Stephen B Montgomery
- Department of Genetics, Stanford University, Stanford, CA 94305, USA; Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Ami S Bhatt
- Department of Genetics, Stanford University, Stanford, CA 94305, USA; Department of Medicine (Hematology, Blood and Marrow Transplantation) Stanford University, Stanford, CA 94305, USA.
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Sentausa E, Basso P, Berry A, Adrait A, Bellement G, Couté Y, Lory S, Elsen S, Attrée I. Insertion sequences drive the emergence of a highly adapted human pathogen. Microb Genom 2019; 6. [PMID: 30946644 PMCID: PMC7643977 DOI: 10.1099/mgen.0.000265] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Pseudomonas aeruginosa is a highly adaptive opportunistic pathogen that can have serious health consequences in patients with lung disorders. Taxonomic outliers of P. aeruginosa of environmental origin have recently emerged as infectious for humans. Here, we present the first genome-wide analysis of an isolate that caused fatal haemorrhagic pneumonia. In two clones, CLJ1 and CLJ3, sequentially recovered from a patient with chronic pulmonary disease, insertion of a mobile genetic element into the P. aeruginosa chromosome affected major virulence-associated phenotypes and led to increased resistance to the antibiotics used to combat the infection. Comparative genome, proteome and transcriptome analyses revealed that this ISL3-family insertion sequence disrupted the genes for flagellar components, type IV pili, O-specific antigens, translesion polymerase and enzymes producing hydrogen cyanide. Seven-fold more insertions were detected in the later isolate, CLJ3, than in CLJ1, some of which modified strain susceptibility to antibiotics by disrupting the genes for the outer-membrane porin OprD and the regulator of β-lactamase expression AmpD. In the Galleria mellonella larvae model, the two strains displayed different levels of virulence, with CLJ1 being highly pathogenic. This study revealed insertion sequences to be major players in enhancing the pathogenic potential of a P. aeruginosa taxonomic outlier by modulating both its virulence and its resistance to antimicrobials, and explains how this bacterium adapts from the environment to a human host.
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Affiliation(s)
- Erwin Sentausa
- Université Grenoble Alpes, CNRS ERL5261, INSERM U1036, CEA, Laboratory Biology of Cancer and Infection, Bacterial Pathogenesis and Cellular Responses, Biosciences and Biotechnology Institute of Grenoble, 38000 Grenoble, France.,Present address: Evotec ID (Lyon) SAS, Marcy l'Étoile, France
| | - Pauline Basso
- Université Grenoble Alpes, CNRS ERL5261, INSERM U1036, CEA, Laboratory Biology of Cancer and Infection, Bacterial Pathogenesis and Cellular Responses, Biosciences and Biotechnology Institute of Grenoble, 38000 Grenoble, France.,Present address: Department of Microbiology and Immunology, University of California San Francisco (UCSF) School of Medicine, San Francisco, CA, USA
| | - Alice Berry
- Université Grenoble Alpes, CNRS ERL5261, INSERM U1036, CEA, Laboratory Biology of Cancer and Infection, Bacterial Pathogenesis and Cellular Responses, Biosciences and Biotechnology Institute of Grenoble, 38000 Grenoble, France
| | - Annie Adrait
- Université Grenoble Alpes, CEA, Inserm, BIG-BGE, 38000 Grenoble, France
| | - Gwendoline Bellement
- Université Grenoble Alpes, CNRS ERL5261, INSERM U1036, CEA, Laboratory Biology of Cancer and Infection, Bacterial Pathogenesis and Cellular Responses, Biosciences and Biotechnology Institute of Grenoble, 38000 Grenoble, France.,Université Grenoble Alpes, CEA, Inserm, BIG-BGE, 38000 Grenoble, France.,Present address: Biozentrum, University of Basel, Basel, Switzerland
| | - Yohann Couté
- Université Grenoble Alpes, CEA, Inserm, BIG-BGE, 38000 Grenoble, France
| | - Stephen Lory
- Department of Microbiology and Immunobiology, Harvard Medical School, Boston, MA, USA
| | - Sylvie Elsen
- Université Grenoble Alpes, CNRS ERL5261, INSERM U1036, CEA, Laboratory Biology of Cancer and Infection, Bacterial Pathogenesis and Cellular Responses, Biosciences and Biotechnology Institute of Grenoble, 38000 Grenoble, France
| | - Ina Attrée
- Université Grenoble Alpes, CNRS ERL5261, INSERM U1036, CEA, Laboratory Biology of Cancer and Infection, Bacterial Pathogenesis and Cellular Responses, Biosciences and Biotechnology Institute of Grenoble, 38000 Grenoble, France
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