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The CRyPTIC Consortium,

Publications and source records attributed to The CRyPTIC Consortium,.

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Genome-wide association studies of global Mycobacterium tuberculosis resistance to thirteen antimicrobials in 10,228 genomes

The emergence of drug resistant tuberculosis is a major global public health concern that threatens the ability to control the disease. Whole genome sequencing as a tool to rapidly diagnose resistant infections can transform patient treatment and clinical practice. While resistance mechanisms are well understood for some drugs, there are likely many mechanisms yet to be uncovered, particularly for new and repurposed drugs. We sequenced 10,228 Mycobacterium tuberculosis (MTB) isolates worldwide and determined the minimum inhibitory concentration (MIC) on a grid of twofold concentration dilutions for 13 antimicrobials using quantitative microtiter plate assays. We performed oligopeptide- and oligonucleotide-based genome-wide association studies using linear mixed models to discover resistance-conferring mechanisms not currently catalogued. Use of MIC over binary resistance phenotypes increased heritability for the new and repurposed drugs by 26-37%, increasing our ability to detect novel associations. For all drugs, we discovered uncatalogued variants associated with MIC, including in the Rv1218c promoter binding site of the transcriptional repressor Rv1219c (isoniazid), upstream of the vapBC20 operon that cleaves 23S rRNA (linezolid) and in the region encoding an -helix lining the active site of Cyp142 (clofazimine, all p<10-7.7). We observed that artefactual signals of cross resistance could be unravelled based on the relative effect size on MIC. Our study demonstrates the ability of very large-scale studies to substantially improve our knowledge of genetic variants associated with antimicrobial resistance in M. tuberculosis.

genomics↗

A data compendium of Mycobacterium tuberculosis antibiotic resistance

The Comprehensive Resistance Prediction for Tuberculosis: an International Consortium (CRyPTIC) presents here a compendium of 15,211 Mycobacterium tuberculosis global clinical isolates, all of which have undergone whole genome sequencing (WGS) and have had their minimum inhibitory concentrations to 13 antitubercular drugs measured in a single assay. It is the largest matched phenotypic and genotypic dataset for M. tuberculosis to date. Here, we provide a summary detailing the breadth of data collected, along with a description of how the isolates were collected and uniformly processed in CRyPTIC partner laboratories across 23 countries. The compendium contains 6,814 isolates resistant to at least one drug, including 2,129 samples that fully satisfy the clinical definitions of rifampicin resistant (RR), multi-drug resistant (MDR), pre-extensively drug resistant (pre-XDR) or extensively drug resistant (XDR). Accurate prediction of resistance status (sensitive/resistant) to eight antitubercular drugs by using a genetic mutation catalogue is presented along with the presence of suspected resistance-conferring mutations for isolates resistant to the newly introduced drugs bedaquiline, clofazimine, delamanid and linezolid. Finally, a case study of rifampicin mono-resistance demonstrates how this compendium could be used to advance our genetic understanding of rare resistance phenotypes. The compendium is fully open-source and it is hoped that the dataset will facilitate and inspire future research for years to come.

microbiology↗

Minos: variant adjudication and joint genotyping of cohorts of bacterial genomes

Short-read variant calling for bacterial genomics is a mature field, and there are many widely-used software tools. Different underlying approaches (eg pileup, local or global assembly, paired-read use, haplotype use) lend each tool different strengths, especially when considering non-SNP (single nucleotide polymorphism) variation or potentially distant reference genomes. It would therefore be valuable to be able to integrate the results from multiple variant callers, using a robust statistical approach to "adjudicate" at loci where there is disagreement between callers. To this end, we present a tool, Minos, for variant adjudication by mapping reads to a genome graph of variant calls. Minos allows users to combine output from multiple variant callers without loss of precision. Minos also addresses a second problem of joint genotyping SNPs and indels in bacterial cohorts, which can also be framed as an adjudication problem. We benchmark on 62 samples from 3 species (Mycobacterium tuberculosis, Staphylococcus aureus, Klebsiella pneumoniae) and an outbreak of 385 M. tuberculosis samples. Finally, we joint genotype a large M. tuberculosis cohort (N{approx}15k) for which the rifampicin phenotype is known. We build a map of non-synonymous variants in the RRDR (rifampicin resistance determining region) of the rpoB gene and extend current knowledge relating RRDR SNPs to heterogeneity in rifampicin resistance levels. We replicate this finding in a second M. tuberculosis cohort (N{approx}13k). Minos is released under the MIT license, available at https://github.com/iqbal-lab-org/minos.

bioinformatics↗

BashTheBug: a crowd of volunteers reproducibly and accurately measure the minimum inhibitory concentrations of 13 antitubercular drugs from photographs of 96-well broth microdilution plates.

Tuberculosis is a respiratory disease that is treatable with antibiotics. An increasing prevalence of resistance means that to ensure a good treatment outcome it is desirable to test the susceptibility of each infection to different antibiotics. Conventionally this is done by culturing a clinical sample and then exposing aliquots to a panel of antibiotics, thereby determining the minimum inhibitory concentration (MIC) of each drug. Using 96-well broth micro dilution plates with each well containing a lyophilised pre-determined amount of an antibiotic is a convenient and cost-effective way to measure the MICs of several drugs at once for a clinical sample. Although accurate, this is an expensive and slow process that requires highly-skilled and experienced laboratory scientists. Here we show that, through the BashTheBug project hosted on the Zooniverse citizen science platform, a crowd of volunteers can reproducibly and accurately determine the MICs for 13 drugs and that simply taking the median or mode of 11-17 independent classifications is sufficient. There is therefore a potential role for crowds to support (but not supplant) the role of experts in antibiotic susceptibility testing.

microbiology↗

GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes

The dN/dS ratio provides evidence of adaptation or functional constraint in protein-coding genes by quantifying the relative excess or deficit of amino acid-replacing versus silent nucleotide variation. Inexpensive sequencing promises a better understanding of parameters such as dN/dS, but analysing very large datasets poses a major statistical challenge. Here I introduce genomegaMap for estimating within-species genome-wide variation in dN/dS, and I apply it to 3,979 genes across 10,209 tuberculosis genomes to characterize the selection pressures shaping this global pathogen. GenomegaMap is a phylogeny-free method that addresses two major problems with existing approaches: (i) it is fast no matter how large the sample size and (ii) it is robust to recombination, which causes phylogenetic methods to report artefactual signals of adaptation. GenomegaMap uses population genetics theory to approximate the distribution of allele frequencies under general, parent-dependent mutation models. Coalescent simulations show that substitution parameters are well-estimated even when genomegaMaps simplifying assumption of independence among sites is violated. I demonstrate the ability of genomegaMap to detect genuine signatures of selection at antimicrobial resistance-conferring substitutions in M. tuberculosis and describe a novel signature of selection in the cold-shock DEAD-box protein A gene deaD/csdA. The genomegaMap approach helps accelerate the exploitation of big data for gaining new insights into evolution within species.

genomics↗