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      Fourier-Transform InfraRed Spectroscopy Can Quickly Type Gram-Negative Bacilli Responsible for Hospital Outbreaks

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          Abstract

          The typing of epidemic bacterial pathogens in hospitals relies on DNA-based, expensive, and time-consuming techniques, that are often limited to retrospective studies. However, the quick identification of epidemic pathogens in the routine of the microbiology laboratories would expedite infection control procedures that limit the contamination of new patients. IR Biotyper (Bruker Daltonics GmbH) is a new typing machine based on Fourier-transform infrared (FTIR) spectroscopy which generates spectra, aiming at typing the micro-organisms within 3 h. This technique discriminates the isolates by exploring the differences of the surface cell polysaccharides. In this work, we evaluated the ability of the FTIR spectroscopy to recognize Gram-negative bacilli clones responsible for hospital outbreaks. Isolates of Pseudomonas aeruginosa ( n = 100), Klebsiella pneumoniae ( n = 16), Enterobacter cloacae ( n = 23), and Acinetobacter baumannii ( n = 20) were typed by the reference methods Multi-Locus Sequence Typing (defining sequence types – STs) along with or without pulsed field gel electrophoresis (PFGE) (defining pulsotypes), and by FTIR spectroscopy. The congruence of FTIR spectroscopy clustering was compared to those of MLST and PFGE by Adjusted Rand index and Adjusted Wallace coefficient. We found that FTIR spectroscopy accurately clustered P. aeruginosa, K. pneumoniae, and E. cloacae isolates belonging to the same ST. The performance of the FTIR spectroscopy was slightly lower for A. baumannii. Furthermore, FTIR spectroscopy also correctly clustered P. aeruginosa isolates having a similar pulsotype. Overall, the IR Biotyper can quickly (in less than 3 h) detect the spread of clones of P. aeruginosa, K. pneumoniae, E. cloacae, and A. baumannii. The use of this technique by clinical microbiology laboratories may help to tackle the spread of epidemic clones by the quick implementation of infection control measures.

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          Multilocus sequence typing of total-genome-sequenced bacteria.

          M. V. Larsen, S Cosentino, S. Rasmussen … (2012)
          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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            Using Fourier transform IR spectroscopy to analyze biological materials.

            Matthew J Baker, Júlio Trevisan, Paul Bassan … (2014)
            IR spectroscopy is an excellent method for biological analyses. It enables the nonperturbative, label-free extraction of biochemical information and images toward diagnosis and the assessment of cell functionality. Although not strictly microscopy in the conventional sense, it allows the construction of images of tissue or cell architecture by the passing of spectral data through a variety of computational algorithms. Because such images are constructed from fingerprint spectra, the notion is that they can be an objective reflection of the underlying health status of the analyzed sample. One of the major difficulties in the field has been determining a consensus on spectral pre-processing and data analysis. This manuscript brings together as coauthors some of the leaders in this field to allow the standardization of methods and procedures for adapting a multistage approach to a methodology that can be applied to a variety of cell biological questions or used within a clinical setting for disease screening or diagnosis. We describe a protocol for collecting IR spectra and images from biological samples (e.g., fixed cytology and tissue sections, live cells or biofluids) that assesses the instrumental options available, appropriate sample preparation, different sampling modes as well as important advances in spectral data acquisition. After acquisition, data processing consists of a sequence of steps including quality control, spectral pre-processing, feature extraction and classification of the supervised or unsupervised type. A typical experiment can be completed and analyzed within hours. Example results are presented on the use of IR spectra combined with multivariate data processing.
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              The negative impact of antibiotic resistance.

              N Friedman, E Temkin, Y Carmeli (2016)
              Antibacterial therapy is one of the most important medical developments of the twentieth century; however, the spread of resistance in healthcare settings and in the community threatens the enormous gains made by the availability of antibiotic therapy. Infections caused by resistant bacteria lead to up to two-fold higher rates of adverse outcomes compared with similar infections caused by susceptible strains. These adverse outcomes may be clinical or economic and reflect primarily the failure or delay of antibiotic treatment. The magnitude of these adverse outcomes will be more pronounced as disease severity, strain virulence, or host vulnerability increases. The negative impacts of antibacterial resistance can be measured at the patient level by increased morbidity and mortality, at the healthcare level by increased resource utilization, higher costs and reduced hospital activity and at the society level by antibiotic treatment guidelines favouring increasingly broad-spectrum empiric therapy. In this review we will discuss the negative impact of antibiotic resistance on patients, the healthcare system and society.
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                Author and article information

                Contributors
                Journal
                Journal ID (nlm-ta): Front Microbiol
                Journal ID (iso-abbrev): Front Microbiol
                Journal ID (publisher-id): Front. Microbiol.
                Title: Frontiers in Microbiology
                Publisher: Frontiers Media S.A.
                ISSN (Electronic): 1664-302X
                Publication date (Electronic): 26 June 2019
                Publication date Collection: 2019
                Volume: 10
                Electronic Location Identifier: 1440
                Affiliations
                [1] 1Laboratoire d’Hygiène Hospitalière, Centre Hospitalier Régional Universitaire , Besançon, France
                [2] 2UMR 6249, Laboratoire Chrono-Environnement, Centre National de la Recherche Scientifique-Université de Franche-Comté , Besançon, France
                [3] 3Centre de Ressources Biologiques – Filière Microbiologique de Besançon, Centre Hospitalier Régional Universitaire , Besançon, France
                Author notes

                Edited by: Bing Gu, Xuzhou Medical University, China

                Reviewed by: M. Oves, King Abdulaziz University, Saudi Arabia; Matthieu Eveillard, Université d’Angers, France

                *Correspondence: Didier Hocquet, dhocquet@ 123456chu-besancon.fr

                This article was submitted to Infectious Diseases, a section of the journal Frontiers in Microbiology

                Article
                DOI: 10.3389/fmicb.2019.01440
                PMC ID: 6606786
                PubMed ID: 31293559
                SO-VID: 9d38a872-6ffe-49c8-bc72-843c63f2bfab
                Copyright © Copyright © 2019 Martak, Valot, Sauget, Cholley, Thouverez, Bertrand and Hocquet.
                License:

                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
                Date received : 22 February 2019
                Date accepted : 07 June 2019
                Page count
                Figures: 3, Tables: 2, Equations: 0, References: 42, Pages: 9, Words: 0
                Categories
                Subject: Microbiology
                Subject: Original Research

                ScienceOpen disciplines: Microbiology & Virology
                Keywords: fourier-transform infrared spectroscopy,ftir,gram-negative bacilli,hospital outbreak,bacterial typing
                Data availability:
                ScienceOpen disciplines: Microbiology & Virology
                Keywords: fourier-transform infrared spectroscopy, ftir, gram-negative bacilli, hospital outbreak, bacterial typing

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