Tim Peto

This study validates an optimized Oxford Nanopore sequencing workflow for mycobacteria from primary MGIT cultures, showing high concordance with Illumina for species identification and SNP detection.

This study compares long-read and short-read sequencing for tuberculosis drug resistance and outbreak analysis, finding they are comparable with minimal differences in key clinical outputs.

This paper evaluates the performance of the gnomonicus tool for predicting antibiotic resistance in Mycobacterium tuberculosis using a diverse testset of 2,663 samples and compares it to TB-Profiler.

This paper develops an automated method to build a comprehensive catalogue of resistance-associated variants for M. tuberculosis, achieving comparable performance to existing catalogues without expert rules.

The paper develops an automated method to predict bedaquiline resistance in M. tuberculosis using a reproducible algorithmic approach, achieving high sensitivity and specificity in variant classification.

This study quantifies antibiotic resistance in tuberculosis using genomic data and MIC measurements to identify genetic determinants of resistance and hypersensitivity across multiple drugs.

This paper evaluates the performance of new Oxford Nanopore flowcells and chemistries for bacterial genome reconstruction, finding that while R10.4/Kit12 with 'super accuracy' basecalling shows promise, hybrid assembly remains more robust and cost-effective.

Flanker clusters gene flanking sequences to identify mobile genetic element patterns associated with antimicrobial resistance genes.

This study analyzes within-host SARS-CoV-2 diversity and transmission patterns using 1390 UK clinical samples, finding low within-host diversity and a narrow transmission bottleneck.

This study optimizes Oxford Nanopore Flowcell usage for hybrid assemblies by reducing sequencing time and cost through washing steps, enabling more isolates per flowcell.

The paper analyzes IncF plasmid diversity across environmental and livestock settings using network community analysis, revealing niche-driven partitioning and core gene-defined communities.

GenomegaMap estimates genome-wide dN/dS ratios across 10,209 tuberculosis genomes to identify selection pressures shaping the pathogen's evolution.

The paper develops a metagenomic metric to predict antibiotic resistance in Enterobacterales infections using pooled human faecal samples from LMICs and high-income settings.

This study evaluates SNP calling pipelines' performance on bacterial data, finding that reference genome selection strongly impacts accuracy, with Snippy performing consistently well across diverse genomes.

The paper evaluates methods for detecting human contamination in microbial sequencing data and finds that classification-based methods are most effective, though combining methods improves accuracy for short reads.

This study analyzes the genomic epidemiology of a blaKPC carbapenemase outbreak in Enterobacterales in the UK, revealing genetic plasticity and plasmid dynamics across multiple species and lineages.

This study compares hybrid assemblies of bacterial genomes using Illumina and long-read sequencing technologies, finding that combining ONT and Illumina reads provides high-quality, low-cost genome reconstruction.

The paper assesses cross-talk in multiplex Nanopore MinION sequencing and finds 0.056% of reads are misassigned due to chimeric reads.

Severe S. aureus infections arise from the nasal microbiome through adaptive evolution, with specific mutations enriched in infecting bacteria compared to colonizing ones.

This paper develops a tool to predict antibiotic resistance in S. aureus and M. tuberculosis from genome sequences with high accuracy and speed.