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      Prevalence, Incidence, and Risk Factors for Intestinal Colonization Due to Fluoroquinolone-Resistant ST131 Escherichia coli: a Longitudinal Study in Highly Dependent, Long-Term Care Facility Residents

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          ABSTRACT

          Escherichia coli ST131 clade C is an important driver for fluoroquinolone resistance (FQ-R). We conducted a prospective observational study in residents from two long-term care facilities (LTCFs) in Seville, Spain, in 2018. Fecal swabs and environmental samples were obtained. E. coli isolates were screened for clade C, FQ-R ST131 by PCR, and molecular typing by PFGE; representatives from pulsotypes were studied by whole-genome-sequencing (WGS) and assigned to lineages (cgSTs). Prevalence of colonization at each time point, incidence density, and risk factors for acquisition were studied. Seventy-six FQ-R ST131 E. coli isolates belonging to 34 cgSTs were obtained; 24 belonging to subclade C1 (116 isolates, 65.9%) and 10 to C2 (60, 34.1%). C1 lineages showed lower virulence scores than C2 (median [IQR], 19 [18 to 20] versus 21 [20 to 21.5], P = 0.001) and higher number of plasmids (4 [3 to 5] versus 2 [2 to 3], P = 0.01). aac(6’)-Ib-cr and bla OXA-1 were less frequent in C1 than C2 (2 [8.3%] versus 6 [60%], P = 0.003 for both); ESBL genes were detected in eight (33.3%) C1 (5 bla CTX-M-27) and three (30%) C2 (all bla CTX-M-15). Of the 82 residents studied, 49 were colonized at some point (59.7%), with a pooled prevalence of 38.6%. Incidence density of new lineage acquisition was 2.22 per 100 resident weeks (1.28 and 0.93 C1 and C2 subclades, respectively). Independent risk factors for acquisitions were having a colonized roommate (HR = 4.21; 95% CI = 1.71 to 10.36; P = 0.002) and urinary or fecal incontinence (HR = 2.82; 95% CI = 1.21 to 6.56; P = 0.01). LTCFs are important reservoirs of clade C ST131 E. coli. The risk factors found suggest that cross-transmission is the most relevant transmission mechanisms.

          IMPORTANCE We aimed at investigating the microbiological and epidemiological features of clade C fluoroquinolone-resistant ST131 E. coli isolates colonizing highly dependent residents in long-term care facilities (LTCFs) during 40 weeks and the risk factors of acquisition. Isolates from C1 and C2 subclades were characterized in this environment. The clonality of the isolates was characterized and they were assigned to lineages (cgSTs), Resistance genes, virulence factors, and plasmids were also described. This study suggests that cross-transmission is the most relevant transmission mechanisms; however, environmental colonization might also play a role. We believe the data provide useful information to depict the epidemiology of these bacteria by merging detailed microbiological and epidemiological information.

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          Identification of acquired antimicrobial resistance genes

          Objectives Identification of antimicrobial resistance genes is important for understanding the underlying mechanisms and the epidemiology of antimicrobial resistance. As the costs of whole-genome sequencing (WGS) continue to decline, it becomes increasingly available in routine diagnostic laboratories and is anticipated to substitute traditional methods for resistance gene identification. Thus, the current challenge is to extract the relevant information from the large amount of generated data. Methods We developed a web-based method, ResFinder that uses BLAST for identification of acquired antimicrobial resistance genes in whole-genome data. As input, the method can use both pre-assembled, complete or partial genomes, and short sequence reads from four different sequencing platforms. The method was evaluated on 1862 GenBank files containing 1411 different resistance genes, as well as on 23 de- novo-sequenced isolates. Results When testing the 1862 GenBank files, the method identified the resistance genes with an ID = 100% (100% identity) to the genes in ResFinder. Agreement between in silico predictions and phenotypic testing was found when the method was further tested on 23 isolates of five different bacterial species, with available phenotypes. Furthermore, ResFinder was evaluated on WGS chromosomes and plasmids of 30 isolates. Seven of these isolates were annotated to have antimicrobial resistance, and in all cases, annotations were compatible with the ResFinder results. Conclusions A web server providing a convenient way of identifying acquired antimicrobial resistance genes in completely sequenced isolates was created. ResFinder can be accessed at www.genomicepidemiology.org. ResFinder will continuously be updated as new resistance genes are identified.
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            CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database

            Abstract The Comprehensive Antibiotic Resistance Database (CARD; https://card.mcmaster.ca) is a curated resource providing reference DNA and protein sequences, detection models and bioinformatics tools on the molecular basis of bacterial antimicrobial resistance (AMR). CARD focuses on providing high-quality reference data and molecular sequences within a controlled vocabulary, the Antibiotic Resistance Ontology (ARO), designed by the CARD biocuration team to integrate with software development efforts for resistome analysis and prediction, such as CARD’s Resistance Gene Identifier (RGI) software. Since 2017, CARD has expanded through extensive curation of reference sequences, revision of the ontological structure, curation of over 500 new AMR detection models, development of a new classification paradigm and expansion of analytical tools. Most notably, a new Resistomes & Variants module provides analysis and statistical summary of in silico predicted resistance variants from 82 pathogens and over 100 000 genomes. By adding these resistance variants to CARD, we are able to summarize predicted resistance using the information included in CARD, identify trends in AMR mobility and determine previously undescribed and novel resistance variants. Here, we describe updates and recent expansions to CARD and its biocuration process, including new resources for community biocuration of AMR molecular reference data.
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              Multilocus sequence typing of total-genome-sequenced bacteria.

              Accurate strain identification is essential for anyone working with bacteria. For many species, multilocus sequence typing (MLST) is considered the "gold standard" of typing, but it is traditionally performed in an expensive and time-consuming manner. As the costs of whole-genome sequencing (WGS) continue to decline, it becomes increasingly available to scientists and routine diagnostic laboratories. Currently, the cost is below that of traditional MLST. The new challenges will be how to extract the relevant information from the large amount of data so as to allow for comparison over time and between laboratories. Ideally, this information should also allow for comparison to historical data. We developed a Web-based method for MLST of 66 bacterial species based on WGS data. As input, the method uses short sequence reads from four sequencing platforms or preassembled genomes. Updates from the MLST databases are downloaded monthly, and the best-matching MLST alleles of the specified MLST scheme are found using a BLAST-based ranking method. The sequence type is then determined by the combination of alleles identified. The method was tested on preassembled genomes from 336 isolates covering 56 MLST schemes, on short sequence reads from 387 isolates covering 10 schemes, and on a small test set of short sequence reads from 29 isolates for which the sequence type had been determined by traditional methods. The method presented here enables investigators to determine the sequence types of their isolates on the basis of WGS data. This method is publicly available at www.cbs.dtu.dk/services/MLST.
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                Author and article information

                Contributors
                Role: Editor
                Role: ad hoc peer reviewer
                Journal
                Microbiol Spectr
                Microbiol Spectr
                spectrum
                Microbiology Spectrum
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2165-0497
                9 August 2022
                Jul-Aug 2022
                9 August 2022
                : 10
                : 4
                : e01673-22
                Affiliations
                [a ] Unidad Clínica de Enfermedades Infecciosas y Microbiología, Hospital Universitario Virgen Macarenagrid.411375.5, , Seville, Spain
                [b ] Instituto de Biomedicina de Sevilla and CSIC, Seville, Spain
                [c ] Departamento de Microbiología, Universidad de Sevilla, Seville, Spain
                [d ] Departamento de Medicina, Universidad de Sevilla, Seville, Spain
                [e ] Centro de Investigación en Red en Enfermedades Infecciosas (CIBERINFEC), Madrid, Spain
                Instituto Oswaldo Cruz
                Oswaldo Cruz Institute
                Author notes

                Elena Salamanca-Rivera and Lorena López-Cerero contributed equally to this study. Author order was determined by agreement of authors.

                Alvaro Pascual and Jesús Rodríguez-Baño contributed equally to this study as senior authors.

                The authors declare no conflict of interest.

                Author information
                https://orcid.org/0000-0001-8950-4384
                https://orcid.org/0000-0001-6732-9001
                Article
                01673-22 spectrum.01673-22
                10.1128/spectrum.01673-22
                9431526
                35943257
                9744a0df-2575-4832-84ce-f7d811829191
                Copyright © 2022 Salamanca-Rivera et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 6 May 2022
                : 13 July 2022
                Page count
                supplementary-material: 0, Figures: 1, Tables: 3, Equations: 0, References: 24, Pages: 12, Words: 6441
                Funding
                Funded by: MEC | Instituto de Salud Carlos III (ISCIII), FundRef https://doi.org/10.13039/501100004587;
                Award ID: AC16/00076
                Award Recipient : Award Recipient : Award Recipient : Award Recipient : Award Recipient :
                Funded by: MEC | Instituto de Salud Carlos III (ISCIII), FundRef https://doi.org/10.13039/501100004587;
                Award ID: REIPI 315 RD16/0016/0001
                Award Recipient : Award Recipient : Award Recipient : Award Recipient : Award Recipient :
                Funded by: MEC | Instituto de Salud Carlos III (ISCIII), FundRef https://doi.org/10.13039/501100004587;
                Award ID: AC16/00072
                Award Recipient : Award Recipient : Award Recipient : Award Recipient : Award Recipient :
                Categories
                Research Article
                open-peer-review, Open Peer Review
                bacteriology, Bacteriology
                Custom metadata
                July/August 2022

                escherichia coli,st131,fluorquinolone resistance,multidrug resistance,risk factors

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