Search

BackgroundThe prevalence, association with disease status, and public health impact of infection with mixtures of M. tuberculosis strains is unclear, in part due to limitations of existing methods for detecting mixed infections.MethodsWe developed an algorithm to identify mixtures of M. tuberculosis strains using next generation sequencing data, assessing performance using simulated sequences. We identified mixed M. tuberculosis strains when there was at least one mixed nucleotide position, and where both the mixture’s components were present in similar isolates from other individuals. We determined risk factors for mixed infection among isolations of M. tuberculosis in England using logistic regression. We used survival analyses to assess the association between mixed infection and putative transmission.Findings6,560 isolations of TB were successfully sequenced in England 2016-2018. Of 3,691 (56%) specimens for which similar sequences had been isolated from at least two other individuals, 341 (9.2%) were mixed. Infection with lineages other than Lineage 4 were associated with mixed infection. Among the 1,823 individuals with pulmonary infection with Lineage 4 M. tuberculosis, mixed infection was associated with significantly increased risk of subsequent isolation of closely related organisms from a different individual (HR 1.43, 95% CI 1.05,1.94), indicative of transmission.InterpretationMixtures of transmissible strains occur in at least 5% of tuberculosis infections in England; when present in pulmonary disease, such mixtures are associated with an increased risk of tuberculosis transmission.FundingPublic Health England; NIHR Health Protection Research Unit Oxford; European Union.Research in ContextEvidence Before This StudyWe searched Pubmed using the search terms ‘tuberculosis’ and ‘mixed’ or ‘mixture’ for English Language articles published up to 1 April 2019. Studies, most performed without the benefit of genomic sequencing, report mixed TB infection from a range of medium and high prevalence areas and show it to be associated with delayed treatment response. Modelling suggests detection and treatment of mixed TB infection is an important goal for TB eradication campaigns. Although routine DNA sequencing of M. tuberculosis isolates is becoming widespread, efficient methods for detecting mixed infection from such data are underdeveloped, and the true prevalence of mixed infection and its association with transmission is unclear.Added Value of This StudyThis study investigated a large series of TB isolations obtained as part of a routine Mycobacterial sequencing program by two reference laboratories, in a low incidence area, England. We developed an efficient generalisable approach to identify transmitted mixed M. tuberculosis infection; our approach is capable of sensitive and specific detection of a single mixed nucleotide position. We identified mixed infection of similar strains (‘microvariation’) in about 9.2% of the M. tuberculosis samples which we were able to assess, and found evidence of increased transmission from individuals with mixed infection.Implications of All the Available EvidenceTB microvariation is a risk factor for TB transmission, even in the low incidence area studied. Although an efficient and highly specific technique identifying microvariation exists, it relies on comparison with similar sequences isolated from other patients. Sharing of sequence data from the many TB sequencing programs being deployed globally will increase the sensitivity of microvariation detection, and may assist targeted public health interventions.

A photocatalytic method for the alpha-selective hydroaminoalkylation of cinnamate esters has been developed. The reaction involves the regioselective addition of alpha-aminoalkyl radicals generated from aniline derivatives or aliphatic amines to the alpha-position of unsaturated esters. The scope of aromatic alkenes was extended to styrenes undergoing hydroaminoalkylation with anti-Markovnikov selectivity, which confirms the importance of the aromatic group at the beta-position. Simple scale-up is demonstrated under continuous-flow conditions, highlighting the practicality of the method.

11 págs, 4 figuras y fórmulas matemáticas. Material suplementario en: http://dx.doi.org/10.1093/molbev/msaa069, 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 analyzing very large data sets 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: 1) It is fast no matter how large the sample size and 2) 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 genomegaMap's 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 Mycobacterium 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., D.J.W. is a Sir Henry Dale Fellow, jointly funded by the Wellcome Trust and the Royal Society (grant no. 101237/Z/13/B) and is a Big Data Institute Robertson Fellow. The CRyPTIC Consortium was supported by grants from the Bill and Melinda Gates Foundation (OPP1133541) and a Wellcome Trust/Newton Fund-MRC Collaborative Award (200205/Z/15/Z). F.A.D. was supported by the Imperial Biomedical Research Centre

Sequencing of pathogen DNA directly from clinical samples offers the possibilities of rapid diagnosis, faster antimicrobial resistance prediction and enhanced outbreak investigation. The approach is especially advantageous for infections caused by species which grow very slowly in culture, such as Mycobacteria tuberculosis. Since the pathogen of interest may represent as little as 0.01% of the total DNA, enrichment of the input material for target sequences by specific amplification and, or depletion of non-target DNA (human, other bacteria) is essential for success. Here, we investigated the potential of isothermal multiple displacement amplification by Phi29 polymerase. We directed the amplification reaction towards Mycobacteria DNA in sputum samples by exploiting in our oligonucleotide primer design, their high GC content (approximately 65%) relative to human DNA. Amplified DNA was then sequenced using the Oxford Nanopore Technology MinION. In addition, a model system comprising standardised ‘mock clinical samples’ was designed. Pooled infection negative human sputum samples were spiked with enumerated Mycobacterium bovis (BCG) Pasteur strain at concentrations spanning the typical range at which Mycobacterium tuberculosis is found in human sputum samples (106 - 101 BCG cells/ml). To assess the amount of BCG sequence enrichment achieved, sample DNA was sequenced both before, and after amplification. Reads from amplified samples, which mapped to a BCG reference genome, comprised short repeated sequences - apparently transcribed multiple times from the same fragment of BCG DNA. Therefore post-amplification, the samples were enriched for BCG sequences relative to unamplified sequences (8,101 BCG reference mapped reads, increasing to 28,617 at 106 BCG cells/ml sample), but BCG genome coverage declined markedly (for example 89.4% to 4.1%). In summary, the use of standardised mock clinical samples allowed direct comparison of data from different Mycobacteria enrichment experiments and sequencing runs. However, optimal conditions for multiple displacement amplification of minority Mycobacteria DNAs, remain to be identified.

Background: The World Health Organization recommends drug-susceptibility testing of Mycobacterium tuberculosis complex for all patients with tuberculosis to guide treatment decisions and improve outcomes. Whether DNA sequencing can be used to accurately predict profiles of susceptibility to first-line antituberculosis drugs has not been clear.\ud \ud \ud \ud Methods: We obtained whole-genome sequences and associated phenotypes of resistance or susceptibility to the first-line antituberculosis drugs isoniazid, rifampin, ethambutol, and pyrazinamide for isolates from 16 countries across six continents. For each isolate, mutations associated with drug resistance and drug susceptibility were identified across nine genes, and individual phenotypes were predicted unless mutations of unknown association were also present. To identify how whole-genome sequencing might direct first-line drug therapy, complete susceptibility profiles were predicted. These profiles were predicted to be susceptible to all four drugs (i.e., pansusceptible) if they were predicted to be susceptible to isoniazid and to the other drugs or if they contained mutations of unknown association in genes that affect susceptibility to the other drugs. We simulated the way in which the negative predictive value changed with the prevalence of drug resistance.\ud \ud \ud \ud Results: A total of 10,209 isolates were analyzed. The largest proportion of phenotypes was predicted for rifampin (9660 [95.4%] of 10,130) and the smallest was predicted for ethambutol (8794 [89.8%] of 9794). Resistance to isoniazid, rifampin, ethambutol, and pyrazinamide was correctly predicted with 97.1%, 97.5%, 94.6%, and 91.3% sensitivity, respectively, and susceptibility to these drugs was correctly predicted with 99.0%, 98.8%, 93.6%, and 96.8% specificity. Of the 7516 isolates with complete phenotypic drug-susceptibility profiles, 5865 (78.0%) had complete genotypic predictions, among which 5250 profiles (89.5%) were correctly predicted. Among the 4037 phenotypic profiles that were predicted to be pansusceptible, 3952 (97.9%) were correctly predicted.\ud \ud \ud \ud Conclusions: Genotypic predictions of the susceptibility of M. tuberculosis to first-line drugs were found to be correlated with phenotypic susceptibility to these drugs. (Funded by the Bill and Melinda Gates Foundation and others.)