Deciphering the distance to antibiotic resistance for the pneumococcus using genome sequencing data

Advances in genome sequencing technologies and genome-wide association studies (GWAS) have provided unprecedented insights into the molecular basis of microbial phenotypes and enabled the identification of the underlying genetic variants in real populations. However, utilization of genome sequencing...

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Main Authors: Mobegi, Fredrick, Cremers, A.J.H., De Jonge, M.I., Bentley, S.D., Van Hijum, S.A.F.T., Zomer, A.
Format: Journal Article
Language:English
Published: NATURE PUBLISHING GROUP 2017
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/80735
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author Mobegi, Fredrick
Cremers, A.J.H.
De Jonge, M.I.
Bentley, S.D.
Van Hijum, S.A.F.T.
Zomer, A.
author_facet Mobegi, Fredrick
Cremers, A.J.H.
De Jonge, M.I.
Bentley, S.D.
Van Hijum, S.A.F.T.
Zomer, A.
author_sort Mobegi, Fredrick
building Curtin Institutional Repository
collection Online Access
description Advances in genome sequencing technologies and genome-wide association studies (GWAS) have provided unprecedented insights into the molecular basis of microbial phenotypes and enabled the identification of the underlying genetic variants in real populations. However, utilization of genome sequencing in clinical phenotyping of bacteria is challenging due to the lack of reliable and accurate approaches. Here, we report a method for predicting microbial resistance patterns using genome sequencing data. We analyzed whole genome sequences of 1,680 Streptococcus pneumoniae isolates from four independent populations using GWAS and identified probable hotspots of genetic variation which correlate with phenotypes of resistance to essential classes of antibiotics. With the premise that accumulation of putative resistance-conferring SNPs, potentially in combination with specific resistance genes, precedes full resistance, we retrogressively surveyed the hotspot loci and quantified the number of SNPs and/or genes, which if accumulated would confer full resistance to an otherwise susceptible strain. We name this approach the € distance to resistance'. It can be used to identify the creep towards complete antibiotics resistance in bacteria using genome sequencing. This approach serves as a basis for the development of future sequencing-based methods for predicting resistance profiles of bacterial strains in hospital microbiology and public health settings.
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spelling curtin-20.500.11937-807352021-01-07T07:46:47Z Deciphering the distance to antibiotic resistance for the pneumococcus using genome sequencing data Mobegi, Fredrick Cremers, A.J.H. De Jonge, M.I. Bentley, S.D. Van Hijum, S.A.F.T. Zomer, A. Science & Technology Multidisciplinary Sciences Science & Technology - Other Topics PENICILLIN-BINDING PROTEINS INVASIVE STREPTOCOCCUS-PNEUMONIAE BETA-LACTAM ANTIBIOTICS SICKLE-CELL-DISEASE FLUOROQUINOLONE RESISTANCE UNITED-STATES MOLECULAR EPIDEMIOLOGY PRESCRIPTION RATES IN-VITRO MUTATIONS Advances in genome sequencing technologies and genome-wide association studies (GWAS) have provided unprecedented insights into the molecular basis of microbial phenotypes and enabled the identification of the underlying genetic variants in real populations. However, utilization of genome sequencing in clinical phenotyping of bacteria is challenging due to the lack of reliable and accurate approaches. Here, we report a method for predicting microbial resistance patterns using genome sequencing data. We analyzed whole genome sequences of 1,680 Streptococcus pneumoniae isolates from four independent populations using GWAS and identified probable hotspots of genetic variation which correlate with phenotypes of resistance to essential classes of antibiotics. With the premise that accumulation of putative resistance-conferring SNPs, potentially in combination with specific resistance genes, precedes full resistance, we retrogressively surveyed the hotspot loci and quantified the number of SNPs and/or genes, which if accumulated would confer full resistance to an otherwise susceptible strain. We name this approach the € distance to resistance'. It can be used to identify the creep towards complete antibiotics resistance in bacteria using genome sequencing. This approach serves as a basis for the development of future sequencing-based methods for predicting resistance profiles of bacterial strains in hospital microbiology and public health settings. 2017 Journal Article http://hdl.handle.net/20.500.11937/80735 10.1038/srep42808 English http://creativecommons.org/licenses/by/4.0/ NATURE PUBLISHING GROUP fulltext
spellingShingle Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
PENICILLIN-BINDING PROTEINS
INVASIVE STREPTOCOCCUS-PNEUMONIAE
BETA-LACTAM ANTIBIOTICS
SICKLE-CELL-DISEASE
FLUOROQUINOLONE RESISTANCE
UNITED-STATES
MOLECULAR EPIDEMIOLOGY
PRESCRIPTION RATES
IN-VITRO
MUTATIONS
Mobegi, Fredrick
Cremers, A.J.H.
De Jonge, M.I.
Bentley, S.D.
Van Hijum, S.A.F.T.
Zomer, A.
Deciphering the distance to antibiotic resistance for the pneumococcus using genome sequencing data
title Deciphering the distance to antibiotic resistance for the pneumococcus using genome sequencing data
title_full Deciphering the distance to antibiotic resistance for the pneumococcus using genome sequencing data
title_fullStr Deciphering the distance to antibiotic resistance for the pneumococcus using genome sequencing data
title_full_unstemmed Deciphering the distance to antibiotic resistance for the pneumococcus using genome sequencing data
title_short Deciphering the distance to antibiotic resistance for the pneumococcus using genome sequencing data
title_sort deciphering the distance to antibiotic resistance for the pneumococcus using genome sequencing data
topic Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
PENICILLIN-BINDING PROTEINS
INVASIVE STREPTOCOCCUS-PNEUMONIAE
BETA-LACTAM ANTIBIOTICS
SICKLE-CELL-DISEASE
FLUOROQUINOLONE RESISTANCE
UNITED-STATES
MOLECULAR EPIDEMIOLOGY
PRESCRIPTION RATES
IN-VITRO
MUTATIONS
url http://hdl.handle.net/20.500.11937/80735