Parallel Mapping of Antibiotic Resistance Alleles in Escherichia coli

PloS One
Sophie J WeissR T Gill

Abstract

Chemical genomics expands our understanding of microbial tolerance to inhibitory chemicals, but its scope is often limited by the throughput of genome-scale library construction and genotype-phenotype mapping. Here we report a method for rapid, parallel, and deep characterization of the response to antibiotics in Escherichia coli using a barcoded genome-scale library, next-generation sequencing, and streamlined bioinformatics software. The method provides quantitative growth data (over 200,000 measurements) and identifies contributing antimicrobial resistance and susceptibility alleles. Using multivariate analysis, we also find that subtle differences in the population responses resonate across multiple levels of functional hierarchy. Finally, we use machine learning to identify a unique allelic and proteomic fingerprint for each antibiotic. The method can be broadly applied to tolerance for any chemical from toxic metabolites to next-generation biofuels and antibiotics.

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Citations

Jun 28, 2018·Journal of Bioinformatics and Computational Biology·Turki TurkiJason T L Wang
Nov 1, 2016·Applied and Environmental Microbiology·Kaitlin E CreamerJoan L Slonczewski
Apr 5, 2017·Antimicrobial Agents and Chemotherapy·Jack R DavisonCarole A Bewley

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Methods Mentioned

BETA
genotyping
PCR
PCRs
electrophoresis
Bar-seq

Software Mentioned

QIIME ( Quantitative Insights into Microbial Ecology ) pipeline
PyCogent
PCoA
R
FASTQ
Procrustes
vegan
ANOSIM
Circos
metagenomeSeq

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