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      Genetic Variants of the DSF Quorum Sensing System in Stenotrophomonas maltophilia Influence Virulence and Resistance Phenotypes Among Genotypically Diverse Clinical Isolates

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          Abstract

          The pathogenicity of Stenotrophomonas maltophilia is regulated in part by its quorum sensing (QS) system. The main QS signaling molecule in S. maltophilia is known as diffusible signal factor (DSF), and the rpf gene cluster is responsible for its synthesis and perception. Two cluster variants have been previously described, rpf-1 and rpf-2, which differ basically in the conditions under which DSF is produced. Here, correlations between the rpf variant and antibiotic susceptibility, LPS electrophoretic profiles and virulence-related phenotypes were evaluated for a collection of 78 geographically and genetically diverse clinical strains of S. maltophilia. In general there were associations between previously established genogroups and the genetic variant of the rpf cluster. However, only few genotype-phenotype correlations could be observed. Resistance to the β-lactam antibiotics ceftazidime and ticarcillin was associated with strains carrying the rpf-1 variant, whereas strains of variant rpf-2, particularly those of genogroup C, showed higher resistance levels to colistin. Strains of variant rpf-2 were also significantly more virulent to Galleria mellonella larvae than those of rpf-1, most likely due to an increased ability of rpf-2 strains to form biofilms. A comparative genomic analysis revealed the presence of proteins unique to individual genogroups. In particular, the strains of genogroup C share an operon that encodes for a new virulence determinant in S. maltophilia related to the synthesis of an alternative Flp/Tad pilus. Overall, this study establishes a link between the DSF-based QS system and the virulence and resistance phenotypes in this species, and identifies potential high-risk clones circulating in European hospitals.

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          Most cited references87

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          eBURST: inferring patterns of evolutionary descent among clusters of related bacterial genotypes from multilocus sequence typing data.

          The introduction of multilocus sequence typing (MLST) for the precise characterization of isolates of bacterial pathogens has had a marked impact on both routine epidemiological surveillance and microbial population biology. In both fields, a key prerequisite for exploiting this resource is the ability to discern the relatedness and patterns of evolutionary descent among isolates with similar genotypes. Traditional clustering techniques, such as dendrograms, provide a very poor representation of recent evolutionary events, as they attempt to reconstruct relationships in the absence of a realistic model of the way in which bacterial clones emerge and diversify to form clonal complexes. An increasingly popular approach, called BURST, has been used as an alternative, but present implementations are unable to cope with very large data sets and offer crude graphical outputs. Here we present a new implementation of this algorithm, eBURST, which divides an MLST data set of any size into groups of related isolates and clonal complexes, predicts the founding (ancestral) genotype of each clonal complex, and computes the bootstrap support for the assignment. The most parsimonious patterns of descent of all isolates in each clonal complex from the predicted founder(s) are then displayed. The advantages of eBURST for exploring patterns of evolutionary descent are demonstrated with a number of examples, including the simple Spain(23F)-1 clonal complex of Streptococcus pneumoniae, "population snapshots" of the entire S. pneumoniae and Staphylococcus aureus MLST databases, and the more complicated clonal complexes observed for Campylobacter jejuni and Neisseria meningitidis.
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            Hidden Markov model speed heuristic and iterative HMM search procedure

            Background Profile hidden Markov models (profile-HMMs) are sensitive tools for remote protein homology detection, but the main scoring algorithms, Viterbi or Forward, require considerable time to search large sequence databases. Results We have designed a series of database filtering steps, HMMERHEAD, that are applied prior to the scoring algorithms, as implemented in the HMMER package, in an effort to reduce search time. Using this heuristic, we obtain a 20-fold decrease in Forward and a 6-fold decrease in Viterbi search time with a minimal loss in sensitivity relative to the unfiltered approaches. We then implemented an iterative profile-HMM search method, JackHMMER, which employs the HMMERHEAD heuristic. Due to our search heuristic, we eliminated the subdatabase creation that is common in current iterative profile-HMM approaches. On our benchmark, JackHMMER detects 14% more remote protein homologs than SAM's iterative method T2K. Conclusions Our search heuristic, HMMERHEAD, significantly reduces the time needed to score a profile-HMM against large sequence databases. This search heuristic allowed us to implement an iterative profile-HMM search method, JackHMMER, which detects significantly more remote protein homologs than SAM's T2K and NCBI's PSI-BLAST.
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              The versatility and adaptation of bacteria from the genus Stenotrophomonas.

              The genus Stenotrophomonas comprises at least eight species. These bacteria are found throughout the environment, particularly in close association with plants. Strains of the most predominant species, Stenotrophomonas maltophilia, have an extraordinary range of activities that include beneficial effects for plant growth and health, the breakdown of natural and man-made pollutants that are central to bioremediation and phytoremediation strategies and the production of biomolecules of economic value, as well as detrimental effects, such as multidrug resistance, in human pathogenic strains. Here, we discuss the versatility of the bacteria in the genus Stenotrophomonas and the insight that comparative genomic analysis of clinical and endophytic isolates of S. maltophilia has brought to our understanding of the adaptation of this genus to various niches.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                03 June 2020
                2020
                : 11
                : 1160
                Affiliations
                [1] 1Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB) , Barcelona, Spain
                [2] 2Departament de Genètica i de Microbiologia, Universitat Autònoma de Barcelona (UAB) , Barcelona, Spain
                [3] 3Cellular Microbiology, Priority Research Area Infections, Research Center Borstel – Leibniz Lung Center , Borstel, Germany
                [4] 4Department of Clinical Microbiology-ISGlobal, Hospital Clínic, Universitat de Barcelona , Barcelona, Spain
                [5] 5Catalan Institution for Research and Advanced Studies (ICREA) , Barcelona, Spain
                Author notes

                Edited by: Jose L. Martinez, Consejo Superior de Investigaciones Científicas (CSIC), Spain

                Reviewed by: Ya-Wen He, Shanghai Jiao Tong University, China; Pablo Vinuesa, National Autonomous University of Mexico, Mexico

                *Correspondence: Xavier Daura, xavier.daura@ 123456uab.cat

                This article was submitted to Antimicrobials, Resistance and Chemotherapy, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2020.01160
                7283896
                32582100
                9228e7cc-62c3-45c6-9181-a2ccb0449685
                Copyright © 2020 Yero, Huedo, Conchillo-Solé, Martínez-Servat, Mamat, Coves, Llanas, Roca, Vila, Schaible, Daura and Gibert.

                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
                : 03 February 2020
                : 06 May 2020
                Page count
                Figures: 3, Tables: 1, Equations: 0, References: 97, Pages: 15, Words: 0
                Funding
                Funded by: Ministerio de Ciencia e Innovación 10.13039/501100004837
                Award ID: BIO2015-66674-R
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                quorum sensing (qs),diffusible signal factor (dsf),mlst (multilocus sequence typing),rpf cluster,biofilm,antibiotic resistance

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