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      Surveillance of osteoarticular infections caused by Staphylococcus aureus in a paediatric hospital in Mexico City

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          Abstract

          Staphylococcus aureus is the main aetiologic agent of osteoarticular infections (OAIs) in paediatric patients. The aim of this prospective unicenter study was to describe the phenotypic and genotypic characteristics of S. aureus isolates obtained from OAIs in paediatric patients admitted to tertiary care hospital. Through a surveillance program called OsteoCode, a multidisciplinary team was created and we identified 27 patients with OAIs caused by S. aureus from 2019 to 2021. The susceptibility profile, virulence factors, biofilm formation, pulsed-field gel electrophoresis (PFGE), clonal complex (CC) and sequence type (ST) were determined. In addition, the clinical characteristics and evolution of the patients presented six months after the diagnosis of OAIs were described. Ninety-two percent of the isolates were methicillin-sensitive S. aureus (MSSA). In methicillin-resistant S. aureus (MRSA), SCC mec-II and SCC mec-V were detected. The pvl gene was only observed in MSSA (18.5%) and was associated with highest fever ( p=0.015), multiple localization ( p=0.017), and soft tissue sites of infection beyond the bone (pyomyositis, pulmonary abscess) ( p=0.017). Biofilm formation was detected in 55.6% of isolates. The most common CC were CC5 and CC30 which represent the most common linages for bone and joint infections worldwide. The isolates were distributed in different STs, and ST672 was predominant. MRSA were associated with a longer duration of intravenous treatment and a prolonged hospital stay ( p=0.023). Recurrent infection occurred in five children and orthopaedic complications in 33.3% of patients. This is the first study that reflects the epidemiology of S. aureus in OAIs in paediatric patients in Mexico; a clear predominance of MSSA distributed in different STs was observed. Our findings highlight that a multidisciplinary team is required for the diagnosis and treatment of OAIs.

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          MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

          The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
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            Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications

            The PubMLST.org website hosts a collection of open-access, curated databases that integrate population sequence data with provenance and phenotype information for over 100 different microbial species and genera.  Although the PubMLST website was conceived as part of the development of the first multi-locus sequence typing (MLST) scheme in 1998 the software it uses, the Bacterial Isolate Genome Sequence database (BIGSdb, published in 2010), enables PubMLST to include all levels of sequence data, from single gene sequences up to and including complete, finished genomes.  Here we describe developments in the BIGSdb software made from publication to June 2018 and show how the platform realises microbial population genomics for a wide range of applications.  The system is based on the gene-by-gene analysis of microbial genomes, with each deposited sequence annotated and curated to identify the genes present and systematically catalogue their variation.  Originally intended as a means of characterising isolates with typing schemes, the synthesis of sequences and records of genetic variation with provenance and phenotype data permits highly scalable (whole genome sequence data for tens of thousands of isolates) means of addressing a wide range of functional questions, including: the prediction of antimicrobial resistance; likely cross-reactivity with vaccine antigens; and the functional activities of different variants that lead to key phenotypes.  There are no limitations to the number of sequences, genetic loci, allelic variants or schemes (combinations of loci) that can be included, enabling each database to represent an expanding catalogue of the genetic variation of the population in question.  In addition to providing web-accessible analyses and links to third-party analysis and visualisation tools, the BIGSdb software includes a RESTful application programming interface (API) that enables access to all the underlying data for third-party applications and data analysis pipelines.
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              A greedy algorithm for aligning DNA sequences.

              For aligning DNA sequences that differ only by sequencing errors, or by equivalent errors from other sources, a greedy algorithm can be much faster than traditional dynamic programming approaches and yet produce an alignment that is guaranteed to be theoretically optimal. We introduce a new greedy alignment algorithm with particularly good performance and show that it computes the same alignment as does a certain dynamic programming algorithm, while executing over 10 times faster on appropriate data. An implementation of this algorithm is currently used in a program that assembles the UniGene database at the National Center for Biotechnology Information.
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                Author and article information

                Contributors
                URI : https://loop.frontiersin.org/people/1923762
                URI : https://loop.frontiersin.org/people/1923888
                URI : https://loop.frontiersin.org/people/1956365
                URI : https://loop.frontiersin.org/people/1956344
                URI : https://loop.frontiersin.org/people/1778846
                Journal
                Front Cell Infect Microbiol
                Front Cell Infect Microbiol
                Front. Cell. Infect. Microbiol.
                Frontiers in Cellular and Infection Microbiology
                Frontiers Media S.A.
                2235-2988
                08 December 2022
                2022
                : 12
                : 999268
                Affiliations
                [1] 1 Department of Paediatric Infectious Diseases, Instituto Nacional de Pediatria , Mexico City, Mexico
                [2] 2 Molecular Microbiology Laboratory, Instituto Nacional de Pediatria , Mexico City, Mexico
                [3] 3 Department of Orthopaedic Surgery, Instituto Nacional de Pediatria , Mexico City, Mexico
                [4] 4 Departament of Research Metodology, Instituto Nacional de Pediatria , Mexico City, Mexico
                Author notes

                Edited by: Shannon D. Manning, Michigan State University, United States

                Reviewed by: Anastassios Doudoulakakis, Panagiotis & Aglaia Kyriakou Children’s Hospital, Greece; Sima Sadat Seyedjavadi, Pasteur Institute of Iran (PII), Iran

                *Correspondence: Alejandra Aquino-Andrade, aaquinoa@ 123456pediatria.gob.mx

                This article was submitted to Clinical Microbiology, a section of the journal Frontiers in Cellular and Infection Microbiology

                Article
                10.3389/fcimb.2022.999268
                9774039
                36569208
                ba4ffcae-e49b-4879-9aa8-edf3cccff166
                Copyright © 2022 Aguilar-Gómez, Merida-Vieyra, Isunza-Alonso, Morales-Pirela, Colín-Martínez, Juárez-Benítez, García de la Puente and Aquino-Andrade

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 20 July 2022
                : 20 October 2022
                Page count
                Figures: 1, Tables: 3, Equations: 0, References: 94, Pages: 14, Words: 7984
                Funding
                Funded by: Instituto Nacional de Pediatria , doi 10.13039/100016928;
                Categories
                Cellular and Infection Microbiology
                Original Research

                Infectious disease & Microbiology
                staphylocoocus aureus,osteomyelitis,molecular epidemiology,panton valentine leukocidin,pediatrics,mexico

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