ORCID Profile
0000-0001-5898-2535
Current Organisation
University of Oxford
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Publisher: Springer Science and Business Media LLC
Date: 20-04-2016
DOI: 10.1038/NCOMMS11465
Abstract: Nature Communications 6: Article number: 10063 (2015) Published: 21 December 2015 Updated: 20 April 2016 In Supplementary Data 3 of this Article, one of the Staphylococcus aureus accession codes is incorrect, as follows: SRR2101499 should be ERR1197981.
Publisher: Springer Science and Business Media LLC
Date: 21-12-2015
DOI: 10.1038/NCOMMS10063
Abstract: The rise of antibiotic-resistant bacteria has led to an urgent need for rapid detection of drug resistance in clinical s les, and improvements in global surveillance. Here we show how de Bruijn graph representation of bacterial ersity can be used to identify species and resistance profiles of clinical isolates. We implement this method for Staphylococcus aureus and Mycobacterium tuberculosis in a software package (‘Mykrobe predictor’) that takes raw sequence data as input, and generates a clinician-friendly report within 3 minutes on a laptop. For S . aureus , the error rates of our method are comparable to gold-standard phenotypic methods, with sensitivity/specificity of 99.1%/99.6% across 12 antibiotics (using an independent validation set, n =470). For M . tuberculosis , our method predicts resistance with sensitivity/specificity of 82.6%/98.5% (independent validation set, n =1,609) sensitivity is lower here, probably because of limited understanding of the underlying genetic mechanisms. We give evidence that minor alleles improve detection of extremely drug-resistant strains, and demonstrate feasibility of the use of emerging single-molecule nanopore sequencing techniques for these purposes.
Publisher: Cold Spring Harbor Laboratory
Date: 12-11-2020
DOI: 10.1101/2020.11.12.380378
Abstract: Bacterial genomes follow a U-shaped frequency distribution whereby most genomic loci are either rare (accessory) or common (core) the union of these is the pan-genome. The alignable fraction of two genomes from a single species can be low (e.g. 50-70%), such that no single reference genome can access all single nucleotide polymorphisms (SNPs). The pragmatic solution is to choose a close reference, and analyse SNPs only in the core genome. Given much bacterial adaptability hinges on the accessory genome, this is an unsatisfactory limitation. We present a novel pan-genome graph structure and algorithms implemented in the software pandora , which approximates a sequenced genome as a recombinant of reference genomes, detects novel variation and then pan-genotypes multiple s les. The method takes fastq as input and outputs a multi-s le VCF with respect to an inferred data-dependent reference genome, and is available at mcolq andora . Constructing a reference graph from 578 E. coli genomes, we analyse a erse set of 20 E. coli isolates. We show pandora recovers at least 13k more rare SNPs than single-reference based tools, achieves equal or better error rates with Nanopore as with Illumina data, 6-24x lower Nanopore error rates than other tools, and provides a stable framework for analysing erse s les without reference bias. We also show that our inferred recombinant VCF reference genome is significantly better than simply picking the closest RefSeq reference. This is a step towards comprehensive cohort analysis of bacterial pan-genomic variation, with potential impacts on genotype henotype and epidemiological studies.
Publisher: Microbiology Society
Date: 03-2018
DOI: 10.1099/JMM.0.000664
Publisher: Springer Science and Business Media LLC
Date: 14-09-2021
DOI: 10.1186/S13059-021-02473-1
Abstract: We present pandora , a novel pan-genome graph structure and algorithms for identifying variants across the full bacterial pan-genome. As much bacterial adaptability hinges on the accessory genome, methods which analyze SNPs in just the core genome have unsatisfactory limitations. Pandora approximates a sequenced genome as a recombinant of references, detects novel variation and pan-genotypes multiple s les. Using a reference graph of 578 Escherichia coli genomes, we compare 20 erse isolates. Pandora recovers more rare SNPs than single-reference-based tools, is significantly better than picking the closest RefSeq reference, and provides a stable framework for analyzing erse s les without reference bias.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Louise Pankhurst.