Pipeline validation for the identification of antimicrobial-resistant genes in carbapenem-resistant Klebsiella pneumoniae
Abstract Antimicrobial-resistant Klebsiella pneumoniae is a global threat to healthcare and an important cause of nosocomial infections. Antimicrobial resistance causes prolonged treatment periods, high mortality rates, and economic impacts. Whole Genome Sequencing (WGS) has been used in laboratory...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-09-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-42154-6 |
| _version_ | 1797559735730307072 |
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| author | Andressa de Almeida Vieira Bruna Candia Piccoli Thaís Regina y Castro Bruna Campestrini Casarin Luiza Funck Tessele Roberta Cristina Ruedas Martins Alexandre Vargas Schwarzbold Priscila de Arruda Trindade |
| author_facet | Andressa de Almeida Vieira Bruna Candia Piccoli Thaís Regina y Castro Bruna Campestrini Casarin Luiza Funck Tessele Roberta Cristina Ruedas Martins Alexandre Vargas Schwarzbold Priscila de Arruda Trindade |
| author_sort | Andressa de Almeida Vieira |
| collection | DOAJ |
| description | Abstract Antimicrobial-resistant Klebsiella pneumoniae is a global threat to healthcare and an important cause of nosocomial infections. Antimicrobial resistance causes prolonged treatment periods, high mortality rates, and economic impacts. Whole Genome Sequencing (WGS) has been used in laboratory diagnosis, but there is limited evidence about pipeline validation to parse generated data. Thus, the present study aimed to validate a bioinformatics pipeline for the identification of antimicrobial resistance genes from carbapenem-resistant K. pneumoniae WGS. Sequences were obtained from a publicly available database, trimmed, de novo assembled, mapped to the K. pneumoniae reference genome, and annotated. Contigs were submitted to different tools for bacterial (Kraken2 and SpeciesFinder) and antimicrobial resistance gene identification (ResFinder and ABRicate). We analyzed 201 K. pneumoniae genomes. In the bacterial identification by Kraken2, all samples were correctly identified, and in SpeciesFinder, 92.54% were correctly identified as K. pneumoniae, 6.96% erroneously as Pseudomonas aeruginosa, and 0.5% erroneously as Citrobacter freundii. ResFinder found a greater number of antimicrobial resistance genes than ABRicate; however, many were identified more than once in the same sample. All tools presented 100% repeatability and reproducibility and > 75% performance in other metrics. Kraken2 was more assertive in recognizing bacterial species, and SpeciesFinder may need improvements. |
| first_indexed | 2024-03-10T17:49:32Z |
| format | Article |
| id | doaj.art-133196e75b1340239ad60b24fe7a420f |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-10T17:49:32Z |
| publishDate | 2023-09-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-133196e75b1340239ad60b24fe7a420f2023-11-20T09:22:59ZengNature PortfolioScientific Reports2045-23222023-09-0113111110.1038/s41598-023-42154-6Pipeline validation for the identification of antimicrobial-resistant genes in carbapenem-resistant Klebsiella pneumoniaeAndressa de Almeida Vieira0Bruna Candia Piccoli1Thaís Regina y Castro2Bruna Campestrini Casarin3Luiza Funck Tessele4Roberta Cristina Ruedas Martins5Alexandre Vargas Schwarzbold6Priscila de Arruda Trindade7Laboratório de Biologia Molecular e Bioinformática Aplicada à Microbiologia Clínica, Programa de Pós-Graduação em Ciências Farmacêuticas, Universidade Federal de Santa MariaLaboratório de Biologia Molecular e Bioinformática Aplicada à Microbiologia Clínica, Programa de Pós-Graduação em Ciências Farmacêuticas, Universidade Federal de Santa MariaLaboratório de Biologia Molecular e Bioinformática Aplicada à Microbiologia Clínica, Programa de Pós-Graduação em Ciências Farmacêuticas, Universidade Federal de Santa MariaLaboratório de Biologia Molecular e Bioinformática Aplicada à Microbiologia Clínica, Programa de Pós-Graduação em Ciências Farmacêuticas, Universidade Federal de Santa MariaLaboratório de Biologia Molecular e Bioinformática Aplicada à Microbiologia Clínica, Programa de Pós-Graduação em Ciências Farmacêuticas, Universidade Federal de Santa MariaLaboratório de Parasitologia Médica (LIM-46), Departamento de Doenças Infecciosas e Parasitárias, Instituto de Medicina Tropical da Universidade de São Paulo, Faculdade de Medicina da Universidade de São PauloDepartamento de Clínica Médica, Universidade Federal de Santa MariaLaboratório de Biologia Molecular e Bioinformática Aplicada à Microbiologia Clínica, Programa de Pós-Graduação em Ciências Farmacêuticas, Universidade Federal de Santa MariaAbstract Antimicrobial-resistant Klebsiella pneumoniae is a global threat to healthcare and an important cause of nosocomial infections. Antimicrobial resistance causes prolonged treatment periods, high mortality rates, and economic impacts. Whole Genome Sequencing (WGS) has been used in laboratory diagnosis, but there is limited evidence about pipeline validation to parse generated data. Thus, the present study aimed to validate a bioinformatics pipeline for the identification of antimicrobial resistance genes from carbapenem-resistant K. pneumoniae WGS. Sequences were obtained from a publicly available database, trimmed, de novo assembled, mapped to the K. pneumoniae reference genome, and annotated. Contigs were submitted to different tools for bacterial (Kraken2 and SpeciesFinder) and antimicrobial resistance gene identification (ResFinder and ABRicate). We analyzed 201 K. pneumoniae genomes. In the bacterial identification by Kraken2, all samples were correctly identified, and in SpeciesFinder, 92.54% were correctly identified as K. pneumoniae, 6.96% erroneously as Pseudomonas aeruginosa, and 0.5% erroneously as Citrobacter freundii. ResFinder found a greater number of antimicrobial resistance genes than ABRicate; however, many were identified more than once in the same sample. All tools presented 100% repeatability and reproducibility and > 75% performance in other metrics. Kraken2 was more assertive in recognizing bacterial species, and SpeciesFinder may need improvements.https://doi.org/10.1038/s41598-023-42154-6 |
| spellingShingle | Andressa de Almeida Vieira Bruna Candia Piccoli Thaís Regina y Castro Bruna Campestrini Casarin Luiza Funck Tessele Roberta Cristina Ruedas Martins Alexandre Vargas Schwarzbold Priscila de Arruda Trindade Pipeline validation for the identification of antimicrobial-resistant genes in carbapenem-resistant Klebsiella pneumoniae Scientific Reports |
| title | Pipeline validation for the identification of antimicrobial-resistant genes in carbapenem-resistant Klebsiella pneumoniae |
| title_full | Pipeline validation for the identification of antimicrobial-resistant genes in carbapenem-resistant Klebsiella pneumoniae |
| title_fullStr | Pipeline validation for the identification of antimicrobial-resistant genes in carbapenem-resistant Klebsiella pneumoniae |
| title_full_unstemmed | Pipeline validation for the identification of antimicrobial-resistant genes in carbapenem-resistant Klebsiella pneumoniae |
| title_short | Pipeline validation for the identification of antimicrobial-resistant genes in carbapenem-resistant Klebsiella pneumoniae |
| title_sort | pipeline validation for the identification of antimicrobial resistant genes in carbapenem resistant klebsiella pneumoniae |
| url | https://doi.org/10.1038/s41598-023-42154-6 |
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