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Integrative Analysis of Whole Genome Sequencing and Phenotypic Resistance Toward Prediction of Trimethoprim-Sulfamethoxazole Resistance in Staphylococcus aureus

As whole genome sequencing is becoming more accessible and affordable for clinical microbiological diagnostics, the reliability of genotypic antimicrobial resistance (AMR) prediction from sequencing data is an important issue to address. Computational AMR prediction can be performed at multiple leve...

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Autores principales: Nurjadi, Dennis, Zizmann, Elfi, Chanthalangsy, Quan, Heeg, Klaus, Boutin, Sébastien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7840696/
https://www.ncbi.nlm.nih.gov/pubmed/33519755
http://dx.doi.org/10.3389/fmicb.2020.607842
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author Nurjadi, Dennis
Zizmann, Elfi
Chanthalangsy, Quan
Heeg, Klaus
Boutin, Sébastien
author_facet Nurjadi, Dennis
Zizmann, Elfi
Chanthalangsy, Quan
Heeg, Klaus
Boutin, Sébastien
author_sort Nurjadi, Dennis
collection PubMed
description As whole genome sequencing is becoming more accessible and affordable for clinical microbiological diagnostics, the reliability of genotypic antimicrobial resistance (AMR) prediction from sequencing data is an important issue to address. Computational AMR prediction can be performed at multiple levels. The first-level approach, such as simple AMR search relies heavily on the quality of the information fed into the database. However, AMR due to mutations are often undetected, since this is not included in the database or poorly documented. Using co-trimoxazole (trimethoprim-sulfamethoxazole) resistance in Staphylococcus aureus, we compared single-level and multi-level analysis to investigate the strengths and weaknesses of both approaches. The results revealed that a single mutation in the AMR gene on the nucleotide level may produce false positive results, which could have been detected if protein sequence analysis would have been performed. For AMR predictions based on chromosomal mutations, such as the folP gene of S. aureus, natural genetic variations should be taken into account to differentiate between variants linked to genetic lineage (MLST) and not over-estimate the potential resistant variants. Our study showed that careful analysis of the whole genome data and additional criterion such as lineage-independent mutations may be useful for identification of mutations leading to phenotypic resistance. Furthermore, the creation of reliable database for point mutations is needed to fully automatized AMR prediction.
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spelling pubmed-78406962021-01-29 Integrative Analysis of Whole Genome Sequencing and Phenotypic Resistance Toward Prediction of Trimethoprim-Sulfamethoxazole Resistance in Staphylococcus aureus Nurjadi, Dennis Zizmann, Elfi Chanthalangsy, Quan Heeg, Klaus Boutin, Sébastien Front Microbiol Microbiology As whole genome sequencing is becoming more accessible and affordable for clinical microbiological diagnostics, the reliability of genotypic antimicrobial resistance (AMR) prediction from sequencing data is an important issue to address. Computational AMR prediction can be performed at multiple levels. The first-level approach, such as simple AMR search relies heavily on the quality of the information fed into the database. However, AMR due to mutations are often undetected, since this is not included in the database or poorly documented. Using co-trimoxazole (trimethoprim-sulfamethoxazole) resistance in Staphylococcus aureus, we compared single-level and multi-level analysis to investigate the strengths and weaknesses of both approaches. The results revealed that a single mutation in the AMR gene on the nucleotide level may produce false positive results, which could have been detected if protein sequence analysis would have been performed. For AMR predictions based on chromosomal mutations, such as the folP gene of S. aureus, natural genetic variations should be taken into account to differentiate between variants linked to genetic lineage (MLST) and not over-estimate the potential resistant variants. Our study showed that careful analysis of the whole genome data and additional criterion such as lineage-independent mutations may be useful for identification of mutations leading to phenotypic resistance. Furthermore, the creation of reliable database for point mutations is needed to fully automatized AMR prediction. Frontiers Media S.A. 2021-01-14 /pmc/articles/PMC7840696/ /pubmed/33519755 http://dx.doi.org/10.3389/fmicb.2020.607842 Text en Copyright © 2021 Nurjadi, Zizmann, Chanthalangsy, Heeg and Boutin. http://creativecommons.org/licenses/by/4.0/ 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.
spellingShingle Microbiology
Nurjadi, Dennis
Zizmann, Elfi
Chanthalangsy, Quan
Heeg, Klaus
Boutin, Sébastien
Integrative Analysis of Whole Genome Sequencing and Phenotypic Resistance Toward Prediction of Trimethoprim-Sulfamethoxazole Resistance in Staphylococcus aureus
title Integrative Analysis of Whole Genome Sequencing and Phenotypic Resistance Toward Prediction of Trimethoprim-Sulfamethoxazole Resistance in Staphylococcus aureus
title_full Integrative Analysis of Whole Genome Sequencing and Phenotypic Resistance Toward Prediction of Trimethoprim-Sulfamethoxazole Resistance in Staphylococcus aureus
title_fullStr Integrative Analysis of Whole Genome Sequencing and Phenotypic Resistance Toward Prediction of Trimethoprim-Sulfamethoxazole Resistance in Staphylococcus aureus
title_full_unstemmed Integrative Analysis of Whole Genome Sequencing and Phenotypic Resistance Toward Prediction of Trimethoprim-Sulfamethoxazole Resistance in Staphylococcus aureus
title_short Integrative Analysis of Whole Genome Sequencing and Phenotypic Resistance Toward Prediction of Trimethoprim-Sulfamethoxazole Resistance in Staphylococcus aureus
title_sort integrative analysis of whole genome sequencing and phenotypic resistance toward prediction of trimethoprim-sulfamethoxazole resistance in staphylococcus aureus
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7840696/
https://www.ncbi.nlm.nih.gov/pubmed/33519755
http://dx.doi.org/10.3389/fmicb.2020.607842
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