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Kekre M, Arevalo SA, Valencia MF, Lagrada ML, Macaranas PKV, Nagaraj G, Oaikhena AO, Olorosa AM, Aanensen DM. Integrating Scalable Genome Sequencing Into Microbiology Laboratories for Routine Antimicrobial Resistance Surveillance. Clin Infect Dis 2021; 73:S258-S266. [PMID: 34850836 PMCID: PMC8634525 DOI: 10.1093/cid/ciab796] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Antimicrobial resistance (AMR) is considered a global threat, and novel drug discovery needs to be complemented with systematic and standardized epidemiological surveillance. Surveillance data are currently generated using phenotypic characterization. However, due to poor scalability, this approach does little for true epidemiological investigations. There is a strong case for whole-genome sequencing (WGS) to enhance the phenotypic data. To establish global AMR surveillance using WGS, we developed a laboratory implementation approach that we applied within the NIHR Global Health Research Unit (GHRU) on Genomic Surveillance of Antimicrobial Resistance. In this paper, we outline the laboratory implementation at 4 units: Colombia, India, Nigeria, and the Philippines. The journey to embedding WGS capacity was split into 4 phases: Assessment, Assembly, Optimization, and Reassessment. We show that on-boarding WGS capabilities can greatly enhance the real-time processing power within regional and national AMR surveillance initiatives, despite the high initial investment in laboratory infrastructure and maintenance. Countries looking to introduce WGS as a surveillance tool could begin by sequencing select Global Antimicrobial Resistance Surveillance System (GLASS) priority pathogens that can demonstrate the standardization and impact genome sequencing has in tackling AMR.
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Affiliation(s)
- Mihir Kekre
- Centre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, Old Road Campus, Oxford, United Kingdom
- Wellcome Genome Campus, Hinxton, United Kingdom
| | - Stefany Alejandra Arevalo
- Colombian Integrated Program for Antimicrobial Resistance Surveillance—Coipars, CI Tibaitatá, Corporación Colombiana de Investigación Agropecuaria (AGROSAVIA), Tibaitatá–Mosquera, Cundinamarca, Colombia
| | - María Fernanda Valencia
- Colombian Integrated Program for Antimicrobial Resistance Surveillance—Coipars, CI Tibaitatá, Corporación Colombiana de Investigación Agropecuaria (AGROSAVIA), Tibaitatá–Mosquera, Cundinamarca, Colombia
| | | | | | - Geetha Nagaraj
- Central Research Laboratory, Kempegowda Institute of Medical Sciences, Bengaluru, India
| | - Anderson O Oaikhena
- Department of Pharmaceutical Microbiology, University of Ibadan, Ibadan, Nigeria
| | | | - David M Aanensen
- Centre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, Old Road Campus, Oxford, United Kingdom
- Wellcome Genome Campus, Hinxton, United Kingdom
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Jacobs MR, Colson JD, Rhoads DD. Recent advances in rapid antimicrobial susceptibility testing systems. Expert Rev Mol Diagn 2021; 21:563-578. [PMID: 33926351 DOI: 10.1080/14737159.2021.1924679] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
INTRODUCTION Until recently antimicrobial susceptibility testing (AST) methods based on the demonstration of phenotypic susceptibility in 16-24 h remained largely unchanged. AREAS COVERED Advances in rapid phenotypic and molecular-based AST systems. EXPERT OPINION AST has changed over the past decade, with many rapid phenotypic and molecular methods developed to demonstrate phenotypic or genotypic resistance, or biochemical markers of resistance such as β-lactamases associated with carbapenem resistance. Most methods still require isolation of bacteria from specimens before both legacy and newer methods can be used. Bacterial identification by MALDI-TOF mass spectroscopy is now widely used and is often key to the interpretation of rapid AST results. Several PCR arrays are available to detect the most frequent pathogens associated with bloodstream infections and their major antimicrobial resistance genes. Many advances in whole-genome sequencing of bacteria and fungi isolated by culture as well as directly from clinical specimens have been made but are not yet widely available. High cost and limited throughput are the major obstacles to uptake of rapid methods, but targeted use, continued development and decreasing costs are expected to result in more extensive use of these increasingly useful methods.
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Affiliation(s)
- Michael R Jacobs
- Emeritus Professor of Pathology and Emeritus Medical Director, Clinical Microbiology, Case Western Reserve University and University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Jordan D Colson
- Microbiology Fellow, Department of Pathology, Cleveland Clinic, Cleveland, OH, USA
| | - Daniel D Rhoads
- Section Head of Microbiology, Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH, USA
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Mitchell SL, Simner PJ. Next-Generation Sequencing in Clinical Microbiology: Are We There Yet? Clin Lab Med 2020; 39:405-418. [PMID: 31383265 DOI: 10.1016/j.cll.2019.05.003] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Next-generation sequencing (NGS) applications have been transitioning from research tools to diagnostic methods and are becoming more commonplace in clinical microbiology laboratories. These applications include (1) whole-genome sequencing, (2) targeted next-generation sequencing methods, and (3) metagenomic next-generation sequencing. The introduction of these methods into the clinical microbiology laboratory has led to the theoretic question of "Will NGS-based methods supplant traditional methods for strain typing, identification, and antimicrobial susceptibility prediction?" The authors address this question and discuss where we are at now with clinical NGS applications for infectious diseases, what does the future hold, and at what cost?
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Affiliation(s)
- Stephanie L Mitchell
- Department of Pathology, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh School of Medicine, 4401 Penn Avenue, Main Hospital, Floor B, #269, Pittsburgh, PA 15224, USA
| | - Patricia J Simner
- Division of Medical Microbiology, Department of Pathology, Johns Hopkins University School of Medicine, Meyer B1-193, 600 North Wolfe Street, Baltimore, MD 21287-7093, USA.
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Pettengill MA. Hindsight Is 2019-the Year in Clinical Microbiology. ACTA ACUST UNITED AC 2020; 42:87-92. [PMID: 32461708 PMCID: PMC7241978 DOI: 10.1016/j.clinmicnews.2020.05.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Much changed in clinical microbiology in 2019, and, like the organisms, we, as clinical microbiologists, are responsible to detect, characterize, and teach others about our discipline. Also, it is important for us to adapt to changes in the field. In this review, I highlight some of the papers, practices, and regulatory issues that defined 2019 for our field, from my perspective.
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Affiliation(s)
- Matthew A Pettengill
- Thomas Jefferson University, Department of Pathology, Anatomy, and Cell Biology, Philadelphia, Pennsylvania
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Point-Counterpoint: Should We Be Performing Metagenomic Next-Generation Sequencing for Infectious Disease Diagnosis in the Clinical Laboratory? J Clin Microbiol 2020; 58:JCM.01739-19. [PMID: 31619533 DOI: 10.1128/jcm.01739-19] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
INTRODUCTIONWith established applications of next-generation sequencing in inherited diseases and oncology, clinical laboratories are evaluating the use of metagenomics for identification of infectious agents directly from patient samples, to aid in the diagnosis of infections. Metagenomic next-generation sequencing for infectious diseases promises an unbiased approach to detection of microbes that does not depend on growth in culture or the targeting of specific pathogens. However, the issues of contamination, interpretation of results, selection of databases used for analysis, and prediction of antimicrobial susceptibilities from sequencing data remain challenges. In this Point-Counterpoint, Steve Miller and Charles Chiu discuss the pros of using direct metagenomic sequencing, while Kyle Rodino and Melissa Miller argue for the use of caution.
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Mendes RE, Jones RN, Woosley LN, Cattoir V, Castanheira M. Application of Next-Generation Sequencing for Characterization of Surveillance and Clinical Trial Isolates: Analysis of the Distribution of β-lactamase Resistance Genes and Lineage Background in the United States. Open Forum Infect Dis 2019; 6:S69-S78. [PMID: 30895217 PMCID: PMC6419912 DOI: 10.1093/ofid/ofz004] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
Background Sequencing technologies and techniques have seen remarkable transformation and innovation that have significantly affected sequencing capability. Data analyses have replaced sequencing as the main challenge. This paper provides an overview on applying next-generation sequencing (NGS) and analysis and discusses the benefits and challenges. In addition, this document shows results from using NGS and bioinformatics tools to screen for β-lactamase genes and assess the epidemiological structure of Escherichia coli– and Klebsiella pneumoniae–causing bloodstream (BSIs) and urinary tract (UTIs) infections in patients hospitalized in the United States during the SENTRY Antimicrobial Surveillance Program for 2016. Methods A total of 3525 isolates (2751 E. coli and 774 K. pneumoniae) causing BSIs (n = 892) and UTIs (n = 2633) in hospitalized patients in the United States were included. Isolates were tested for susceptibility by broth microdilution, and those that met a minimum inhibitory concentration (MIC)–based screening criteria had their genomes sequenced and analyzed. Results A total of 11.6% and 16.1% of E. coli–causing UTIs and BSIs, respectively, met the MIC-based criteria, whereas 11.0% and 13.7% of K. pneumoniae isolates causing UTIs and BSIs, respectively, met the criteria. Among E. coli, blaCTX-M variants (87.6% overall) prevailed (60.5% of CTX-M group 1 and 26.9% of group 9). A total of 60.3% of K. pneumoniae isolates carried blaCTX-M variants (52.7% and 7.6% of groups 1 and 9, respectively). Two E. coli (0.6%) and 13 K. pneumoniae (12.9%) isolates harbored blaKPC. Among KPC-producing K. pneumoniae (2 from BSIs and 11 from UTIs), 84.6% (11/13) were ST258 (CC258). Seventeen and 38 unique clonal complexes (CCs) were noted in E. coli that caused BSIs and UTIs, respectively, and CC131 (or ST131) was the most common CC among BSI (53.6%) and UTI (58.2%) isolates. Twenty-three and 26 CCs were noted among K. pneumoniae–causing BSIs and UTIs, respectively. CC258 (28.3%) prevailed in UTI pathogens, whereas CC307 (15.0%) was the most common CC among BSI isolates. Conclusions This study provides a benchmark for the distribution of β-lactamase genes and the population structure information for the most common Enterobacteriaceae species responsible for BSIs and UTIs in US medical centers during the 2016 SENTRY Program.
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Affiliation(s)
| | | | | | - Vincent Cattoir
- University Hospital of Rennes, Department of Clinical Microbiology, Rennes, France.,National Reference Center for Antimicrobial Resistance, Rennes, France.,University of Rennes 1, Unit Inserm U1230, Rennes, France
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Iwamoto T, Murase Y, Yoshida S, Aono A, Kuroda M, Sekizuka T, Yamashita A, Kato K, Takii T, Arikawa K, Kato S, Mitarai S. Overcoming the pitfalls of automatic interpretation of whole genome sequencing data by online tools for the prediction of pyrazinamide resistance in Mycobacterium tuberculosis. PLoS One 2019; 14:e0212798. [PMID: 30817803 PMCID: PMC6394917 DOI: 10.1371/journal.pone.0212798] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Accepted: 02/09/2019] [Indexed: 11/18/2022] Open
Abstract
OBJECTIVES Automated online software tools that analyse whole genome sequencing (WGS) data without the need for bioinformatics expertise can motivate the implementation of WGS-based molecular drug susceptibility testing (DST) in routine diagnostic settings for tuberculosis (TB). Pyrazinamide (PZA) is a key drug for current and future TB treatment regimens; however, it was reported that predictive power for PZA resistance by the available tools is low. Therefore, this low predictive power may make users hesitant to use the tools. This study aimed to elucidate why and to uncover the real performance of the tools when taking into account their variation calling lists (manual inspection), not just their automated reporting system (default setting) that was evaluated by previous studies. METHODS WGS data from 191 datasets comprising 108 PZA-resistant and 83 susceptible strains were used to evaluate the potential performance of the available online tools (TB Profiler, TGS-TB, PhyResSE, and CASTB) for predicting phenotypic PZA resistance. RESULTS When taking into consideration the variation calling lists, 73 variants in total (47 non-synonymous mutations and 26 indels) in pncA were detected by TGS-TB and PhyResSE, covering all mutations for the 108 PZA-resistant strains. The 73 variants were confirmed by Sanger sequencing. TB Profiler also detected all but three complete loss, two large deletion at the 3'-end, and one relatively large insertion of pncA. On the other hand, many of the 73 variants were lacking in the automated reporting systems except by TGS-TB; of these variants, CASTB detected only 20. By applying the 'non-wild type sequence' approach for predicting PZA resistance, accuracy of the results significantly improved compared with that of the automated results obtained by each tool. CONCLUSION Users can obtain more accurate predictions for PZA resistance than previously reported by manually checking the results and applying the 'non-wild type sequence' approach.
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Affiliation(s)
- Tomotada Iwamoto
- Department of Infectious Diseases, Kobe Institute of Health, Kobe City, Japan
- * E-mail: (TI); (SM)
| | - Yoshiro Murase
- Bacteriology Division, Department of Mycobacterium Reference and Research, Research Institute of Tuberculosis, Japan Anti-Tuberculosis Association, Kiyose City, Tokyo, Japan
| | - Shiomi Yoshida
- Clinical Research Center, National Hospital Organization Kinki-chuo Chest Medical Center, Sakai City, Osaka, Japan
| | - Akio Aono
- Bacteriology Division, Department of Mycobacterium Reference and Research, Research Institute of Tuberculosis, Japan Anti-Tuberculosis Association, Kiyose City, Tokyo, Japan
| | - Makoto Kuroda
- Pathogen Genomics Center, National Institute of Infectious Diseases, Shinjuku-ku, Tokyo, Japan
| | - Tsuyoshi Sekizuka
- Pathogen Genomics Center, National Institute of Infectious Diseases, Shinjuku-ku, Tokyo, Japan
| | - Akifumi Yamashita
- Pathogen Genomics Center, National Institute of Infectious Diseases, Shinjuku-ku, Tokyo, Japan
| | - Kengo Kato
- Pathogen Genomics Center, National Institute of Infectious Diseases, Shinjuku-ku, Tokyo, Japan
| | - Takemasa Takii
- Molecular Epidemiology Division, Research Institute of Tuberculosis, Japan Anti-Tuberculosis Association, Kiyose City, Tokyo, Japan
| | - Kentaro Arikawa
- Department of Infectious Diseases, Kobe Institute of Health, Kobe City, Japan
| | - Seiya Kato
- Research Institute of Tuberculosis, Japan Anti-Tuberculosis Association, Kiyose City, Tokyo, Japan
| | - Satoshi Mitarai
- Bacteriology Division, Department of Mycobacterium Reference and Research, Research Institute of Tuberculosis, Japan Anti-Tuberculosis Association, Kiyose City, Tokyo, Japan
- Basic Mycobacteriosis, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki City, Nagasaki, Japan
- * E-mail: (TI); (SM)
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