41 research outputs found

    What Is Resistance? Impact of Phenotypic versus Molecular Drug Resistance Testing on Therapy for Multi- and Extensively Drug-Resistant Tuberculosis.

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    Rapid and accurate drug susceptibility testing (DST) is essential for the treatment of multi- and extensively drug-resistant tuberculosis (M/XDR-TB). We compared the utility of genotypic DST assays with phenotypic DST (pDST) using Bactec 960 MGIT or Löwenstein-Jensen to construct M/XDR-TB treatment regimens for a cohort of 25 consecutive M/XDR-TB patients and 15 possible anti-TB drugs. Genotypic DST results from Cepheid GeneXpert MTB/RIF (Xpert) and line probe assays (LPAs; Hain GenoType MTBDRplus 2.0 and MTBDRsl 2.0) and whole-genome sequencing (WGS) were translated into individual algorithm-derived treatment regimens for each patient. We further analyzed if discrepancies between the various methods were due to flaws in the genotypic or phenotypic test using MIC results. Compared with pDST, the average agreement in the number of drugs prescribed in genotypic regimens ranged from just 49% (95% confidence interval [CI], 39 to 59%) for Xpert and 63% (95% CI, 56 to 70%) for LPAs to 93% (95% CI, 88 to 98%) for WGS. Only the WGS regimens did not contain any drugs to which pDST showed resistance. Importantly, MIC testing revealed that pDST likely underestimated the true rate of resistance for key drugs (rifampin, levofloxacin, moxifloxacin, and kanamycin) because critical concentrations (CCs) were too high. WGS can be used to rule in resistance even in M/XDR strains with complex resistance patterns, but pDST for some drugs is still needed to confirm susceptibility and construct the final regimens. Some CCs for pDST need to be reexamined to avoid systematic false-susceptible results in low-level resistant isolates

    Supplementary Data for "Population structure of multidrug resistant Klebsiella oxytoca within the UK and Ireland identifies sharing of virulence and resistance genes with K. pneumoniae"

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    Supplemental Data for "Population structure of multidrug resistant Klebsiella oxytoca within the UK and Ireland identifies sharing of virulence and resistance genes with K. pneumoniae" Danesh Moradigaravand, Veronique Martin, Sharon J. Peacock and Julian Parkhill 1- Multi-fasta files of genes in pan-genome 2- Metadata of genes in pan-genom

    Supplemental data for "Whole genome sequencing reveals high-resolution epidemiological links between clinical and environmental Klebsiella pneumoniae

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    Data for "Whole genome sequencing reveals high-resolution epidemiological links between clinical and environmental Klebsiella pneumoniae" Authors: Chakkaphan Runcharoen*, Danesh Moradigaravand*, Elizabeth Blane, Suporn Paksanont, Jeeranan Thammachote, Suthatip Anun, Julian Parkhill, Narisara Chantratita** and Sharon J. Peacock** * Joint first author ** Joint senior author 1- List of genes in the pan-genome of 77 Klebsiella pneumoniae isolates from Thailand 2- Multiple alignment of the genes in the pan-genom

    Pan-genome multi-fasta files for the Serratia marcescens population study

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    multifasta files for the pan-genome analysis conducted in "Recent independent emergence of multiple multi-drug resistant Serratia marcescens clones within the United Kingdom and Ireland" 2016 Authors: Danesh Moradigaravand, Christine J. Boinett, Veronique Martin, Sharon J. Peacock and Julian Parkhil

    Pan-genome data for the genes in "Prediction of antibiotic resistance in Escherichia coli from large-scale pan-genome data"

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    The pan-genome data for the paper under review. Files are in fasta format

    Assembly data for newly sequenced genomes used in "Prediction of antibiotic resistance in Escherichia coli from large-scale pan-genome data"

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    These are 256 assembly files for the genomes sequenced for the manuscript. The file "accession.txt" contains tags and accession number

    Supplemental Data for 'The dissemination of multidrug resistant Enterobacter cloacae throughout the UK and Ireland'

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    The dissemination of multidrug resistant Enterobacter cloacae throughout the UK and Ireland Danesh Moradigaravand, Sandra Reuter, Veronique Martin, Sharon J. Peacock and Julian Parkhill List of files and folders: 1- RCode.R: R code for the regression analysis 2- Metadata.csv: MIC and MLST data used as input for regression models 3- gene_presence_absence.csv: Output of pan-genome analysis used as input for regression models 4- SNP.out: List of SNPs identified used as input for regression models 5- pan_genome_sequences folder contains sequences of the genes in the pan-genom
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