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      A novel replication initiation region encoded in a widespread Acinetobacter plasmid lineage carrying a blaNDM-1 gene

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          Abstract

          The blaNDM-1 gene and its variants encode metallo- beta-lactamases that confer resistance to almost all beta-lactam antibiotics. Genes encoding blaNDM-1 and its variants can be found in several Acinetobacter species, and they are usually linked to two different plasmid clades. The plasmids in one of these clades contain a gene encoding a Rep protein of the Rep_3 superfamily. The other clade consists of medium-sized plasmids in which the gene (s) involved in plasmid replication initiation ( rep)have not yet been identified. In the present study, we identified the minimal replication region of a blaNDM-1-carrying plasmid of Acinetobacter haemolyticus AN54 (pAhaeAN54e), a member of this second clade. This region of 834 paired bases encodes three small peptides, all of which have roles in plasmid maintenance. The plasmids containing this minimal replication region are closely related; almost all contain blaNDM genes, and they are found in multiple Acinetobacter species, including A. baumannii. None of these plasmids contain an annotated Rep gene, suggesting that their replication relies on the minimal replication region that they share with the plasmid pAhaeAN54e. These observations suggest that this plasmid lineage plays a crucial role in the dissemination of the blaNDM-1 gene and its variants.

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          Highly accurate protein structure prediction with AlphaFold

          John Jumper, Richard Evans, Alexander Pritzel … (2021)
          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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            BLAST+: architecture and applications

            Christiam Camacho, George Coulouris, Vahram Avagyan … (2009)
            Background Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications. Results We describe features and improvements of rewritten BLAST software and introduce new command-line applications. Long query sequences are broken into chunks for processing, in some cases leading to dramatically shorter run times. For long database sequences, it is possible to retrieve only the relevant parts of the sequence, reducing CPU time and memory usage for searches of short queries against databases of contigs or chromosomes. The program can now retrieve masking information for database sequences from the BLAST databases. A new modular software library can now access subject sequence data from arbitrary data sources. We introduce several new features, including strategy files that allow a user to save and reuse their favorite set of options. The strategy files can be uploaded to and downloaded from the NCBI BLAST web site. Conclusion The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences. We have also improved the user interface of the command-line applications.
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              Roary: rapid large-scale prokaryote pan genome analysis

              Andrew J Page, Carla A. Cummins, Martin Hunt … (2015)
              Summary: A typical prokaryote population sequencing study can now consist of hundreds or thousands of isolates. Interrogating these datasets can provide detailed insights into the genetic structure of prokaryotic genomes. We introduce Roary, a tool that rapidly builds large-scale pan genomes, identifying the core and accessory genes. Roary makes construction of the pan genome of thousands of prokaryote samples possible on a standard desktop without compromising on the accuracy of results. Using a single CPU Roary can produce a pan genome consisting of 1000 isolates in 4.5 hours using 13 GB of RAM, with further speedups possible using multiple processors. Availability and implementation: Roary is implemented in Perl and is freely available under an open source GPLv3 license from http://sanger-pathogens.github.io/Roary Contact: roary@sanger.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                Elena Bello-López:
                ORCID: https://orcid.org/0000-0002-5508-9714
                Role: Data curationRole: Formal analysisRole: Writing – review & editing
                Ángeles Pérez-Oseguera: Role: Data curationRole: Formal analysisRole: InvestigationRole: Writing – review & editing
                Walter Santos:
                ORCID: https://orcid.org/0000-0001-7025-2295
                Role: Formal analysisRole: InvestigationRole: Writing – review & editing
                Miguel Ángel Cevallos:
                ORCID: https://orcid.org/0000-0002-0447-812X
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Feng Gao: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS One
                Journal ID (publisher-id): plos
                Title: PLOS ONE
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Electronic): 1932-6203
                Publication date (Electronic): 31 May 2024
                Publication date Collection: 2024
                Volume: 19
                Issue: 5
                Electronic Location Identifier: e0303976
                Affiliations
                [1 ] Centro de Ciencias Genómicas, Programa de Genómica Evolutiva, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, México
                [2 ] Departamento de Microbiología, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, México
                Tianjin University, CHINA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-5508-9714
                https://orcid.org/0000-0001-7025-2295
                https://orcid.org/0000-0002-0447-812X
                Article
                Publisher ID: PONE-D-24-08483
                DOI: 10.1371/journal.pone.0303976
                PMC ID: 11142715
                PubMed ID: 38820537
                SO-VID: afa0a781-9105-4db5-a3f6-4164cb2c673f
                Copyright © © 2024 Bello-López et al
                License:

                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
                Date received : 4 March 2024
                Date accepted : 5 May 2024
                Page count
                Figures: 6, Tables: 1, Pages: 16
                Funding
                Funded by: PAPIIT
                Award ID: IN204421
                Award Recipient :
                ORCID: https://orcid.org/0000-0002-0447-812X
                Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica (IN204421), Universidad Nacional Autónoma de México. the funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Subject: Research Article
                Subject: Biology and life sciences
                Subject: Genetics
                Subject: DNA
                Subject: DNA replication
                Subject: Biology and life sciences
                Subject: Biochemistry
                Subject: Nucleic acids
                Subject: DNA
                Subject: DNA replication
                Subject: Biology and life sciences
                Subject: Molecular biology
                Subject: Molecular biology techniques
                Subject: DNA construction
                Subject: Plasmid Construction
                Subject: Research and analysis methods
                Subject: Molecular biology techniques
                Subject: DNA construction
                Subject: Plasmid Construction
                Subject: Biology and Life Sciences
                Subject: Organisms
                Subject: Bacteria
                Subject: Acinetobacter
                Subject: Biology and Life Sciences
                Subject: Microbiology
                Subject: Medical Microbiology
                Subject: Microbial Pathogens
                Subject: Bacterial Pathogens
                Subject: Acinetobacter
                Subject: Medicine and Health Sciences
                Subject: Pathology and Laboratory Medicine
                Subject: Pathogens
                Subject: Microbial Pathogens
                Subject: Bacterial Pathogens
                Subject: Acinetobacter
                Subject: Research and Analysis Methods
                Subject: Animal Studies
                Subject: Experimental Organism Systems
                Subject: Model Organisms
                Subject: Escherichia Coli
                Subject: Research and Analysis Methods
                Subject: Model Organisms
                Subject: Escherichia Coli
                Subject: Biology and Life Sciences
                Subject: Microbiology
                Subject: Medical Microbiology
                Subject: Microbial Pathogens
                Subject: Bacterial Pathogens
                Subject: Escherichia Coli
                Subject: Medicine and Health Sciences
                Subject: Pathology and Laboratory Medicine
                Subject: Pathogens
                Subject: Microbial Pathogens
                Subject: Bacterial Pathogens
                Subject: Escherichia Coli
                Subject: Biology and Life Sciences
                Subject: Organisms
                Subject: Bacteria
                Subject: Enterobacteriaceae
                Subject: Escherichia
                Subject: Escherichia Coli
                Subject: Biology and Life Sciences
                Subject: Organisms
                Subject: Bacteria
                Subject: Gut Bacteria
                Subject: Escherichia
                Subject: Escherichia Coli
                Subject: Research and Analysis Methods
                Subject: Animal Studies
                Subject: Experimental Organism Systems
                Subject: Prokaryotic Models
                Subject: Escherichia Coli
                Subject: Biology and Life Sciences
                Subject: Molecular Biology
                Subject: Molecular Biology Techniques
                Subject: Artificial Gene Amplification and Extension
                Subject: Polymerase Chain Reaction
                Subject: Research and Analysis Methods
                Subject: Molecular Biology Techniques
                Subject: Artificial Gene Amplification and Extension
                Subject: Polymerase Chain Reaction
                Subject: Medicine and Health Sciences
                Subject: Pharmacology
                Subject: Drugs
                Subject: Antimicrobials
                Subject: Antibiotics
                Subject: Biology and Life Sciences
                Subject: Microbiology
                Subject: Microbial Control
                Subject: Antimicrobials
                Subject: Antibiotics
                Subject: Biology and life sciences
                Subject: Genetics
                Subject: DNA
                Subject: Forms of DNA
                Subject: Plasmids
                Subject: Biology and life sciences
                Subject: Biochemistry
                Subject: Nucleic acids
                Subject: DNA
                Subject: Forms of DNA
                Subject: Plasmids
                Subject: Biology and Life Sciences
                Subject: Genetics
                Subject: Genetic Elements
                Subject: Mobile Genetic Elements
                Subject: Plasmids
                Subject: Biology and Life Sciences
                Subject: Genetics
                Subject: Genomics
                Subject: Mobile Genetic Elements
                Subject: Plasmids
                Subject: Biology and life sciences
                Subject: Biochemistry
                Subject: Proteins
                Subject: DNA-binding proteins
                Custom metadata
                Data Availability The sequence of the plasmid is already deposited in Genbank and the accession number is in the text.

                ScienceOpen disciplines: Uncategorized
                Data availability:
                ScienceOpen disciplines: Uncategorized

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