9
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Molecular Epidemiological Investigation of a Nosocomial Cluster of C. auris: Evidence of Recent Emergence in Italy and Ease of Transmission during the COVID-19 Pandemic

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Candida auris is an emerging MDR pathogen raising major concerns worldwide. In Italy, it was first and only identified in July 2019 in our hospital (San Martino Hospital, Genoa), where infection or colonization cases have been increasingly recognized during the following months. To gain insights into the introduction, transmission dynamics, and resistance traits of this fungal pathogen, consecutive C. auris isolates collected from July 2019 to May 2020 ( n = 10) were subjected to whole-genome sequencing (WGS) and antifungal susceptibility testing (AST); patients’ clinical and trace data were also collected. WGS resolved all isolates within the genetic clade I (South Asian) and showed that all but one were part of a cluster likely stemming from the index case. Phylogenetic molecular clock analyses predicted a recent introduction (May 2019) in the hospital setting and suggested that most transmissions were associated with a ward converted to a COVID-19-dedicated ICU during the pandemic. All isolates were resistant to amphotericin B, voriconazole, and fluconazole at high-level, owing to mutations in ERG11(K143R) and TACB1(A640V). Present data demonstrated that the introduction of MDR C. auris in Italy was a recent event and suggested that its spread could have been facilitated by the COVID-19 pandemic. Continued efforts to implement stringent infection prevention and control strategies are warranted to limit the spread of this emerging pathogen within the healthcare system.

          Related collections

          Most cited references38

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

          Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Pilon: An Integrated Tool for Comprehensive Microbial Variant Detection and Genome Assembly Improvement

            Advances in modern sequencing technologies allow us to generate sufficient data to analyze hundreds of bacterial genomes from a single machine in a single day. This potential for sequencing massive numbers of genomes calls for fully automated methods to produce high-quality assemblies and variant calls. We introduce Pilon, a fully automated, all-in-one tool for correcting draft assemblies and calling sequence variants of multiple sizes, including very large insertions and deletions. Pilon works with many types of sequence data, but is particularly strong when supplied with paired end data from two Illumina libraries with small e.g., 180 bp and large e.g., 3–5 Kb inserts. Pilon significantly improves draft genome assemblies by correcting bases, fixing mis-assemblies and filling gaps. For both haploid and diploid genomes, Pilon produces more contiguous genomes with fewer errors, enabling identification of more biologically relevant genes. Furthermore, Pilon identifies small variants with high accuracy as compared to state-of-the-art tools and is unique in its ability to accurately identify large sequence variants including duplications and resolve large insertions. Pilon is being used to improve the assemblies of thousands of new genomes and to identify variants from thousands of clinically relevant bacterial strains. Pilon is freely available as open source software.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Fast and accurate long-read alignment with Burrows–Wheeler transform

              Motivation: Many programs for aligning short sequencing reads to a reference genome have been developed in the last 2 years. Most of them are very efficient for short reads but inefficient or not applicable for reads >200 bp because the algorithms are heavily and specifically tuned for short queries with low sequencing error rate. However, some sequencing platforms already produce longer reads and others are expected to become available soon. For longer reads, hashing-based software such as BLAT and SSAHA2 remain the only choices. Nonetheless, these methods are substantially slower than short-read aligners in terms of aligned bases per unit time. Results: We designed and implemented a new algorithm, Burrows-Wheeler Aligner's Smith-Waterman Alignment (BWA-SW), to align long sequences up to 1 Mb against a large sequence database (e.g. the human genome) with a few gigabytes of memory. The algorithm is as accurate as SSAHA2, more accurate than BLAT, and is several to tens of times faster than both. Availability: http://bio-bwa.sourceforge.net Contact: rd@sanger.ac.uk
                Bookmark

                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                J Fungi (Basel)
                J Fungi (Basel)
                jof
                Journal of Fungi
                MDPI
                2309-608X
                15 February 2021
                February 2021
                : 7
                : 2
                : 140
                Affiliations
                [1 ]Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, 16132 Genoa, Italy; giulia.codda@ 123456gmail.com (G.C.); lorenzo.ball@ 123456edu.unige.it (L.B.); paolo.pelosi@ 123456unige.it (P.P.); anna.marchese@ 123456unige.it (A.M.)
                [2 ]Anesthesia and Intensive Care, San Martino Policlinico Hospital—IRCCS for Oncology and Neuroscience, 16132 Genoa, Italy
                [3 ]Infectious Diseases Unit, San Martino Policlinico Hospital—IRCCS for Oncology and Neuroscience, 16132 Genoa, Italy; daniele.roberto.giacobbe@ 123456gmail.com (D.R.G.); m.mikulska@ 123456unige.it (M.M.); lmagnasco90@ 123456gmail.com (L.M.); anton.vena@ 123456gmail.com (A.V.); matteo.bassetti@ 123456hsanmartino.it (M.B.)
                [4 ]Department of Health Sciences (DISSAL), University of Genoa, 16132 Genoa, Italy
                [5 ]Clinical Microbiology Unit, San Martino Policlinico Hospital—IRCCS for Oncology and Neuroscience, 16132 Genoa, Italy; willisonedward@ 123456gmail.com (E.W.); francesca.crea@ 123456hsanmartino.it (F.C.)
                Author notes
                Author information
                https://orcid.org/0000-0002-5863-5805
                https://orcid.org/0000-0003-2385-1759
                https://orcid.org/0000-0002-6343-3271
                https://orcid.org/0000-0002-0697-3992
                Article
                jof-07-00140
                10.3390/jof7020140
                7919374
                33672021
                6f804ed5-51b8-472d-858a-f3a2f336ed53
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 13 January 2021
                : 12 February 2021
                Categories
                Article

                mycotic infections,antifungal resistance,genomic epidemiology,covid-19,epidemic,emerging infections

                Comments

                Comment on this article