ArticleScientific reports2017
Deciphering the distance to antibiotic resistance for the pneumococcus using genome sequencing data.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Linkage of nucleotide and functional diversity varies across gut bacteria.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Comprehensive genomics, systems, and structural assessment for novel target identification in penicillin-resistantFrontiers in bioinformatics · 2026Article
- Utilizing whole genome sequencing data for machine learning driven prediction of antibiotic resistance inFrontiers in microbiology · 2026Article
- Bacterial genome-wide association studies: exploring the genetic variation underlying bacterial phenotypes.Applied and environmental microbiology · 2025Review
- Article
- Keeping up with the pathogens: improved antimicrobial resistance detection and prediction from Pseudomonas aeruginosa genomes.Genome medicine · 2024Article
- Convergent impact of vaccination and antibiotic pressures on pneumococcal populations.Cell chemical biology · 2024Review
- Genome-Wide Association Studies (GWAS) Approaches for the Detection of Genetic Variants Associated with Antibiotic Resistance: A Systematic Review.Microorganisms · 2023Review
- Negative regulation of MurZ and MurA underlies the essentiality of GpsB- and StkP-mediated protein phosphorylation in Streptococcus pneumoniae D39.Molecular microbiology · 2023Article
- Single nucleotide variants inMicrobial genomics · 2023Article
- Subspecies Classification and Comparative Genomic Analysis ofMicroorganisms · 2022Article
- Genome-Wide Association Study Reveals Host Factors Affecting Conjugation inMicroorganisms · 2022Article
- Genome-wide association, prediction and heritability in bacteria with application toNAR genomics and bioinformatics · 2022Article
- Genetic variation and function: revealing potential factors associated with microbial phenotypes.Biophysics reports · 2021Article
- Genome-Wide Association Studies for the Detection of Genetic Variants Associated With Daptomycin and Ceftaroline Resistance inFrontiers in microbiology · 2021Article
- Predicting Phenotypic Polymyxin Resistance in Klebsiella pneumoniae through Machine Learning Analysis of Genomic Data.mSystems · 2020Article
- Impacts of florfenicol on the microbiota landscape and resistome as revealed by metagenomic analysis.Microbiome · 2019Article
- Gain- and Loss-of-Function Screens Coupled to Next-Generation Sequencing for Antibiotic Mode of Action and Resistance Studies inAntimicrobial agents and chemotherapy · 2019Article
- The cell cycle regulator GpsB functions as cytosolic adaptor for multiple cell wall enzymes.Nature communications · 2019Article
- Antimicrobial Resistance inMicrobiology spectrum · 2018Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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