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Henares D, Lo SW, Perez-Argüello A, Redin A, Ciruela P, Garcia-Garcia JJ, Brotons P, Yuste J, Sá-Leão R, Muñoz-Almagro C. Comparison of next generation technologies and bioinformatics pipelines for capsular typing of Streptococcus pneumoniae. J Clin Microbiol 2023; 61:e0074123. [PMID: 38092657 PMCID: PMC10729682 DOI: 10.1128/jcm.00741-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 10/01/2023] [Indexed: 12/20/2023] Open
Abstract
Whole genome sequencing (WGS)-based approaches for pneumococcal capsular typing have become an alternative to serological methods. In silico serotyping from WGS has not yet been applied to long-read sequences produced by third-generation technologies. The objective of the study was to determine the capsular types of pneumococci causing invasive disease in Catalonia (Spain) using serological typing and WGS and to compare the performance of different bioinformatics pipelines using short- and long-read data from WGS. All invasive pneumococcal pediatric isolates collected in Hospital Sant Joan de Déu (Barcelona) from 2013 to 2019 were included. Isolates were assigned a capsular type by serological testing based on anticapsular antisera and by different WGS-based pipelines: Illumina sequencing followed by serotyping with PneumoCaT, SeroBA, and Pathogenwatch vs MinION-ONT sequencing coupled with serotyping by Pathogenwatch from pneumococcal assembled genomes. A total of 119 out of 121 pneumococcal isolates were available for sequencing. Twenty-nine different serotypes were identified by serological typing, with 24F (n = 17; 14.3%), 14 (n = 10; 8.4%), and 15B/C (n = 8; 6.7%) being the most common serotypes. WGS-based pipelines showed initial concordance with serological typing (>91% of accuracy). The main discrepant results were found at the serotype level within a serogroup: 6A/B, 6C/D, 9A/V, 11A/D, and 18B/C. Only one discrepancy at the serogroup level was observed: serotype 29 by serological testing and serotype 35B/D by all WGS-based pipelines. Thus, bioinformatics WGS-based pipelines, including those using third-generation sequencing, are useful for pneumococcal capsular assignment. Possible discrepancies between serological typing and WGS-based approaches should be considered in pneumococcal capsular-type surveillance studies.
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Affiliation(s)
- Desiree Henares
- Department of RDI Microbiology, Hospital Sant Joan de Déu, Barcelona, Spain
- Infectious Diseases and Microbiome, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
- CIBER Center for Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
| | - Stephanie W. Lo
- Parasites and Microbes Programme, Wellcome Sanger Institute, Hinxton, United Kingdom
- Milner Center for Evolution, Life Sciences Department, University of Bath, Bath, United Kingdom
| | - Amaresh Perez-Argüello
- Department of RDI Microbiology, Hospital Sant Joan de Déu, Barcelona, Spain
- Infectious Diseases and Microbiome, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
| | - Alba Redin
- Department of RDI Microbiology, Hospital Sant Joan de Déu, Barcelona, Spain
- Infectious Diseases and Microbiome, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
| | - Pilar Ciruela
- CIBER Center for Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- Surveillance and Public Health Emergency Response, Public Health Agency of Catalonia (ASPCAT), Barcelona, Spain
| | - Juan Jose Garcia-Garcia
- CIBER Center for Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- Pediatrics Department, Hospital Sant Joan de Déu, Barcelona, Spain
- Department of Surgery and Medical-Surgical Specialties, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, Barcelona, Spain
| | - Pedro Brotons
- Department of RDI Microbiology, Hospital Sant Joan de Déu, Barcelona, Spain
- Infectious Diseases and Microbiome, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
- CIBER Center for Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- School of Medicine, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Jose Yuste
- Spanish Pneumococcal Reference Laboratory, National Center for Microbiology, Instituto de Salud Carlos III, Madrid, Spain
- CIBER of Respiratory Diseases (CIBERES), Instituto de salud Carlos III, Madrid, Spain
| | - Raquel Sá-Leão
- Laboratory of Molecular Microbiology of Human Pathogens, Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa (ITQB NOVA), Oeiras, Portugal
| | - Carmen Muñoz-Almagro
- Department of RDI Microbiology, Hospital Sant Joan de Déu, Barcelona, Spain
- Infectious Diseases and Microbiome, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
- CIBER Center for Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
- School of Medicine, Universitat Internacional de Catalunya, Barcelona, Spain
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Garza-Ramos U, Rodríguez-Medina N, Córdova-Fletes C, Rubio-Mendoza D, Alonso-Hernández CJ, López-Jácome LE, Morfín-Otero R, Rodríguez-Noriega E, Rojas-Larios F, Vázquez-Larios MDR, Ponce-de-Leon A, Choy-Chang EV, Franco-Cendejas R, Martinez-Guerra BA, Morales-de-La-Peña CT, Mena-Ramírez JP, López-Gutiérrez E, García-Romo R, Ballesteros-Silva B, Valadez-Quiroz A, Avilés-Benítez LK, Feliciano-Guzmán JM, Pérez-Vicelis T, Velázquez-Acosta MDC, Padilla-Ibarra C, López-Moreno LI, Corte-Rojas RE, Couoh-May CA, Quevedo-Ramos MA, López-García M, Chio-Ortiz G, Gil-Veloz M, Molina-Chavarria A, Mora-Domínguez JP, Romero-Romero D, May-Tec FJ, Garza-González E. Whole genome analysis of Gram-negative bacteria using the EPISEQ CS application and other bioinformatic platforms. J Glob Antimicrob Resist 2023; 33:61-71. [PMID: 36878463 DOI: 10.1016/j.jgar.2023.02.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/23/2023] [Accepted: 02/26/2023] [Indexed: 03/07/2023] Open
Abstract
OBJECTIVES To determine genomic characteristics and molecular epidemiology of carbapenem non-susceptible Klebsiella pneumoniae, Escherichia coli, Acinetobacter baumannii, and Pseudomonas aeruginosa from medical centres of Mexico using whole genome sequencing data analysed with the EPISEQⓇ CS application and other bioinformatic platforms. METHODS Clinical isolates collected from 28 centres in Mexico included carbapenem-non-susceptible K. pneumoniae (n = 22), E. coli (n = 24), A. baumannii (n = 16), and P. aeruginosa (n = 13). Isolates were subjected to whole genome sequencing using the Illumina (MiSeq) platform. FASTQ files were uploaded to the EPISEQⓇ CS application for analysis. Additionally, the tools Kleborate v2.0.4 and Pathogenwatch were used as comparators for Klebsiella genomes, and the bacterial whole genome sequence typing database was used for E. coli and A. baumannii. RESULTS For K. pneumoniae, both bioinformatic approaches detected multiple genes encoding aminoglycoside, quinolone, and phenicol resistance, and the presence of blaNDM-1 explained carbapenem non-susceptibility in 18 strains and blaKPC-3 in four strains. Regarding E. coli, both EPISEQⓇ CS and bacterial whole genome sequence typing database analyses detected multiple virulence and resistance genes: 20 of 24 (83.3%) strains carried blaNDM, 3 of 24 (12.4%) carried blaOXA-232, and 1 carried blaOXA-181. Genes that confer resistance to aminoglycosides, tetracyclines, sulfonamides, phenicols, trimethoprim, and macrolides were also detected by both platforms. Regarding A. baumannii, the most frequent carbapenemase-encoding gene detected by both platforms was blaOXA-72, followed by blaOXA-66. Both approaches detected similar genes for aminoglycosides, carbapenems, tetracyclines, phenicols, and sulfonamides. Regarding P. aeruginosa, blaVIM, blaIMP, and blaGES were the more frequently detected. Multiple virulence genes were detected in all strains. CONCLUSION Compared to the other available platforms, EPISEQⓇ CS enabled a comprehensive resistance and virulence analysis, providing a reliable method for bacterial strain typing and characterization of the virulome and resistome.
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Affiliation(s)
| | | | | | - Daira Rubio-Mendoza
- Facultad de Medicina, Universidad Autónoma de Nuevo León, Nuevo León, Mexico
| | | | | | - Rao Morfín-Otero
- Hospital Civil de Guadalajara Fray Antonio Alcalde, Universidad de Guadalajara, Jalisco, Mexico
| | | | | | | | - Alfredo Ponce-de-Leon
- Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de Mexico, Mexico
| | | | | | | | | | - Juan Pablo Mena-Ramírez
- Hospital General de Zona No. 21, IMSS. Centro Universitario de los Altos, Universidad de Guadalajara. Jalisco, Mexico
| | | | | | | | | | | | | | - Talia Pérez-Vicelis
- Hospital Regional de alta especialidad Bicentenario de la independencia, Estado de México, Mexico
| | | | | | | | | | | | | | | | | | - Mariana Gil-Veloz
- Hospital Regional de Alta Especialidad del Bajío, Guanajuato, Mexico
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Argimón S, David S, Underwood A, Abrudan M, Wheeler NE, Kekre M, Abudahab K, Yeats CA, Goater R, Taylor B, Harste H, Muddyman D, Feil EJ, Brisse S, Holt K, Donado-Godoy P, Ravikumar KL, Okeke IN, Carlos C, Aanensen DM. Rapid Genomic Characterization and Global Surveillance of Klebsiella Using Pathogenwatch. Clin Infect Dis 2021; 73:S325-S335. [PMID: 34850838 PMCID: PMC8634497 DOI: 10.1093/cid/ciab784] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Klebsiella species, including the notable pathogen K. pneumoniae, are increasingly associated with antimicrobial resistance (AMR). Genome-based surveillance can inform interventions aimed at controlling AMR. However, its widespread implementation requires tools to streamline bioinformatic analyses and public health reporting. METHODS We developed the web application Pathogenwatch, which implements analytics tailored to Klebsiella species for integration and visualization of genomic and epidemiological data. We populated Pathogenwatch with 16 537 public Klebsiella genomes to enable contextualization of user genomes. We demonstrated its features with 1636 genomes from 4 low- and middle-income countries (LMICs) participating in the NIHR Global Health Research Unit (GHRU) on AMR. RESULTS Using Pathogenwatch, we found that GHRU genomes were dominated by a small number of epidemic drug-resistant clones of K. pneumoniae. However, differences in their distribution were observed (eg, ST258/512 dominated in Colombia, ST231 in India, ST307 in Nigeria, ST147 in the Philippines). Phylogenetic analyses including public genomes for contextualization enabled retrospective monitoring of their spread. In particular, we identified hospital outbreaks, detected introductions from abroad, and uncovered clonal expansions associated with resistance and virulence genes. Assessment of loci encoding O-antigens and capsule in K. pneumoniae, which represent possible vaccine candidates, showed that 3 O-types (O1-O3) represented 88.9% of all genomes, whereas capsule types were much more diverse. CONCLUSIONS Pathogenwatch provides a free, accessible platform for real-time analysis of Klebsiella genomes to aid surveillance at local, national, and global levels. We have improved representation of genomes from GHRU participant countries, further facilitating ongoing surveillance.
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Affiliation(s)
- Silvia Argimón
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Sophia David
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Anthony Underwood
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Monica Abrudan
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Nicole E Wheeler
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Mihir Kekre
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Khalil Abudahab
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Corin A Yeats
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
- Centre for Genomic Pathogen Surveillance, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Old Road Campus, Oxford, United Kingdom
| | - Richard Goater
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Ben Taylor
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
- Centre for Genomic Pathogen Surveillance, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Old Road Campus, Oxford, United Kingdom
| | - Harry Harste
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Dawn Muddyman
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Edward J Feil
- Milner Centre for Evolution, University of Bath, Bath, United Kingdom
| | - Sylvain Brisse
- Institut Pasteur, Biodiversity and Epidemiology of Bacterial Pathogens, Paris, France
| | - Kathryn Holt
- Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, Victoria, Australia
- London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Pilar Donado-Godoy
- Colombian Integrated Program for Antimicrobial Resistance Surveillance (Coipars), CI Tibaitatá, Corporación Colombiana de Investigación Agropecuaria (AGROSAVIA), Tibaitatá–Mosquera, Cundinamarca, Colombia
| | - K L Ravikumar
- Central Research Laboratory, Kempegowda Institute of Medical Sciences, Bengaluru, India
| | - Iruka N Okeke
- Department of Pharmaceutical Microbiology, Faculty of Pharmacy, University of Ibadan, Oyo State, Nigeria
| | - Celia Carlos
- Antimicrobial Resistance Surveillance Reference Laboratory, Research Institute for Tropical Medicine, Muntinlupa, The Philippines
| | - David M Aanensen
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
- Centre for Genomic Pathogen Surveillance, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Old Road Campus, Oxford, United Kingdom
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Sánchez-Busó L, Yeats CA, Taylor B, Goater RJ, Underwood A, Abudahab K, Argimón S, Ma KC, Mortimer TD, Golparian D, Cole MJ, Grad YH, Martin I, Raphael BH, Shafer WM, Town K, Wi T, Harris SR, Unemo M, Aanensen DM. A community-driven resource for genomic epidemiology and antimicrobial resistance prediction of Neisseria gonorrhoeae at Pathogenwatch. Genome Med 2021; 13:61. [PMID: 33875000 PMCID: PMC8054416 DOI: 10.1186/s13073-021-00858-2] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 02/22/2021] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Antimicrobial-resistant (AMR) Neisseria gonorrhoeae is an urgent threat to public health, as strains resistant to at least one of the two last-line antibiotics used in empiric therapy of gonorrhoea, ceftriaxone and azithromycin, have spread internationally. Whole genome sequencing (WGS) data can be used to identify new AMR clones and transmission networks and inform the development of point-of-care tests for antimicrobial susceptibility, novel antimicrobials and vaccines. Community-driven tools that provide an easy access to and analysis of genomic and epidemiological data is the way forward for public health surveillance. METHODS Here we present a public health-focussed scheme for genomic epidemiology of N. gonorrhoeae at Pathogenwatch ( https://pathogen.watch/ngonorrhoeae ). An international advisory group of experts in epidemiology, public health, genetics and genomics of N. gonorrhoeae was convened to inform on the utility of current and future analytics in the platform. We implement backwards compatibility with MLST, NG-MAST and NG-STAR typing schemes as well as an exhaustive library of genetic AMR determinants linked to a genotypic prediction of resistance to eight antibiotics. A collection of over 12,000 N. gonorrhoeae genome sequences from public archives has been quality-checked, assembled and made public together with available metadata for contextualization. RESULTS AMR prediction from genome data revealed specificity values over 99% for azithromycin, ciprofloxacin and ceftriaxone and sensitivity values around 99% for benzylpenicillin and tetracycline. A case study using the Pathogenwatch collection of N. gonorrhoeae public genomes showed the global expansion of an azithromycin-resistant lineage carrying a mosaic mtr over at least the last 10 years, emphasising the power of Pathogenwatch to explore and evaluate genomic epidemiology questions of public health concern. CONCLUSIONS The N. gonorrhoeae scheme in Pathogenwatch provides customised bioinformatic pipelines guided by expert opinion that can be adapted to public health agencies and departments with little expertise in bioinformatics and lower-resourced settings with internet connection but limited computational infrastructure. The advisory group will assess and identify ongoing public health needs in the field of gonorrhoea, particularly regarding gonococcal AMR, in order to further enhance utility with modified or new analytic methods.
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Affiliation(s)
- Leonor Sánchez-Busó
- Centre for Genomic Pathogen Surveillance, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, Oxfordshire, UK.
- Genomics and Health Area, Foundation for the Promotion of Health and Biomedical Research in the Valencian Community (FISABIO-Public Health), Valencia, Spain.
| | - Corin A Yeats
- Centre for Genomic Pathogen Surveillance, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, Oxfordshire, UK
| | - Benjamin Taylor
- Centre for Genomic Pathogen Surveillance, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, Oxfordshire, UK
- Centre for Genomic Pathogen Surveillance, Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, Cambridgeshire, UK
| | - Richard J Goater
- Centre for Genomic Pathogen Surveillance, Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, Cambridgeshire, UK
- European Molecular Biology Lab, Heidelberg, Baden-Wuerttemberg, Germany
| | - Anthony Underwood
- Centre for Genomic Pathogen Surveillance, Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, Cambridgeshire, UK
| | - Khalil Abudahab
- Centre for Genomic Pathogen Surveillance, Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, Cambridgeshire, UK
| | - Silvia Argimón
- Centre for Genomic Pathogen Surveillance, Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, Cambridgeshire, UK
| | - Kevin C Ma
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Tatum D Mortimer
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Daniel Golparian
- World Health Organization Collaborating Centre for Gonorrhoea and Other STIs, Department of Laboratory Medicine, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Michelle J Cole
- National Infection Service, Public Health England, London, UK
| | - Yonatan H Grad
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Division of Infectious Diseases, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Irene Martin
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Brian H Raphael
- Division of STD prevention, National Center for HIV/AIDS, Viral Hepatitis, STD and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - William M Shafer
- Department of Microbiology and Immunology and Emory Antibiotic Resistance Center, Emory University School of Medicine, Atlanta, GA, USA
- Laboratories of Bacterial Pathogenesis, Veterans Affairs Medical Center, Decatur, GA, USA
| | - Katy Town
- Division of STD prevention, National Center for HIV/AIDS, Viral Hepatitis, STD and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Teodora Wi
- Department of the Global HIV, Hepatitis and STI Programmes, World Health Organization, Geneva, Switzerland
| | - Simon R Harris
- Microbiotica, Biodata Innovation Centre, Cambridge, Cambridgeshire, UK
| | - Magnus Unemo
- World Health Organization Collaborating Centre for Gonorrhoea and Other STIs, Department of Laboratory Medicine, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - David M Aanensen
- Centre for Genomic Pathogen Surveillance, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, Oxfordshire, UK.
- Centre for Genomic Pathogen Surveillance, Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, Cambridgeshire, UK.
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