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Background Bedaquiline is a core drug for the treatment of multidrug-resistant tuberculosis; however, the understanding of resistance mechanisms is poor, which is hampering rapid molecular diagnostics. Some bedaquiline-resistant mutants are also cross-resistant to clofazimine. To decipher bedaquiline and clofazimine resistance determinants, we combined experimental evolution, protein modelling, genome sequencing, and phenotypic data. Methods For this in-vitro and in-silico data analysis, we used a novel in-vitro evolutionary model using subinhibitory drug concentrations to select bedaquiline-resistant and clofazimine-resistant mutants. We determined bedaquiline and clofazimine minimum inhibitory concentrations and did Illumina and PacBio sequencing to characterise selected mutants and establish a mutation catalogue. This catalogue also includes phenotypic and genotypic data of a global collection of more than 14 000 clinical Mycobacterium tuberculosis complex isolates, and publicly available data. We investigated variants implicated in bedaquiline resistance by protein modelling and dynamic simulations. Findings We discerned 265 genomic variants implicated in bedaquiline resistance, with 250 (94%) variants affecting the transcriptional repressor (Rv0678) of the MmpS5–MmpL5 efflux system. We identified 40 new variants in vitro, and a new bedaquiline resistance mechanism caused by a large-scale genomic rearrangement. Additionally, we identified in vitro 15 (7%) of 208 mutations found in clinical bedaquiline-resistant isolates. From our in-vitro work, we detected 14 (16%) of 88 mutations so far identified as being associated with clofazimine resistance and also seen in clinically resistant strains, and catalogued 35 new mutations. Structural modelling of Rv0678 showed four major mechanisms of bedaquiline resistance: impaired DNA binding, reduction in protein stability, disruption of protein dimerisation, and alteration in affinity for its fatty acid ligand. Interpretation Our findings advance the understanding of drug resistance mechanisms in M tuberculosis complex strains. We have established an extended mutation catalogue, comprising variants implicated in resistance and susceptibility to bedaquiline and clofazimine. Our data emphasise that genotypic testing can delineate clinical isolates with borderline phenotypes, which is essential for the design of effective treatments. Funding Leibniz ScienceCampus Evolutionary Medicine of the Lung, Deutsche Forschungsgemeinschaft, Research Training Group 2501 TransEvo, Rhodes Trust, Stanford University Medical Scientist Training Program, National Institute for Health and Care Research Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Bill & Melinda Gates Foundation, Wellcome Trust, and Marie Skłodowska-Curie Actions.

Background: Bedaquiline is a core drug for the treatment of multidrug-resistant tuberculosis; however, the understanding of resistance mechanisms is poor, which is hampering rapid molecular diagnostics. Some bedaquiline-resistant mutants are also cross-resistant to clofazimine. To decipher bedaquiline and clofazimine resistance determinants, we combined experimental evolution, protein modelling, genome sequencing, and phenotypic data. Methods: For this in-vitro and in-silico data analysis, we used a novel in-vitro evolutionary model using subinhibitory drug concentrations to select bedaquiline-resistant and clofazimine-resistant mutants. We determined bedaquiline and clofazimine minimum inhibitory concentrations and did Illumina and PacBio sequencing to characterise selected mutants and establish a mutation catalogue. This catalogue also includes phenotypic and genotypic data of a global collection of more than 14 000 clinical Mycobacterium tuberculosis complex isolates, and publicly available data. We investigated variants implicated in bedaquiline resistance by protein modelling and dynamic simulations. Findings: We discerned 265 genomic variants implicated in bedaquiline resistance, with 250 (94%) variants affecting the transcriptional repressor (Rv0678) of the MmpS5–MmpL5 efflux system. We identified 40 new variants in vitro, and a new bedaquiline resistance mechanism caused by a large-scale genomic rearrangement. Additionally, we identified in vitro 15 (7%) of 208 mutations found in clinical bedaquiline-resistant isolates. From our in-vitro work, we detected 14 (16%) of 88 mutations so far identified as being associated with clofazimine resistance and also seen in clinically resistant strains, and catalogued 35 new mutations. Structural modelling of Rv0678 showed four major mechanisms of bedaquiline resistance: impaired DNA binding, reduction in protein stability, disruption of protein dimerisation, and alteration in affinity for its fatty acid ligand. Interpretation: Our findings advance the understanding of drug resistance mechanisms in M tuberculosis complex strains. We have established an extended mutation catalogue, comprising variants implicated in resistance and susceptibility to bedaquiline and clofazimine. Our data emphasise that genotypic testing can delineate clinical isolates with borderline phenotypes, which is essential for the design of effective treatments. Funding: Leibniz ScienceCampus Evolutionary Medicine of the Lung, Deutsche Forschungsgemeinschaft, Research Training Group 2501 TransEvo, Rhodes Trust, Stanford University Medical Scientist Training Program, National Institute for Health and Care Research Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Bill & Melinda Gates Foundation, Wellcome Trust, and Marie Skłodowska-Curie Actions.

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 2-fold 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 sample heritability for the new and repurposed drugs by 26% to 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 α-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.

Of the 10 million people estimated to have fallen ill with tuberculosis (TB) in 2019, nearly half million developed TB resistant to rifampicin (RIF), and over one million developed TB susceptible to RIF but resistant to isoniazid (INH). Drug resistance must be detected rapidly and accurately to initiate appropriate and effective treatment. The detection of RIF resistance has improved significantly in the past decade with the introduction of rapid diagnostic tools based on DNA detection. The introduction of these tests has dramatically increased the number of TB patients tested for RIF resistance, leading to a 129% increase of individuals started on second-line TB treatment between 2012 and 2019. The majority of patients with RIF-resistant TB can be detected by analysing the 81-base pair fragment of the rpoB gene region. However, the situation is not that clear for other anti-TB drugs due to the lack of knowledge of how phenotypic resistance is associated with mutations in the Mycobacterium tuberculosis (Mtb) genome. In response to this issue the WHO has developed a catalogue of Mtb mutations in the and their association with phenotypic drug resistance. The catalogue provides a reference standard for the interpretation of mutations conferring resistance to all first-line and a variety of second-line drugs. The report summarises the analysis of over 38,000 isolates with matched data on whole genome sequencing and phenotypic drug susceptibility testing from over 40 countries for 13 anti-TB medicines. It lists over 17,000 mutations, their frequency and association with or not with resistance and includes methods used, mutations identified and summaries of important findings for each drug. Tuberculosis laboratories around the world can use the catalogue as a support in the interpretation of genome sequencing results. The catalogue can also guide the development of new molecular drug susceptibility tests, including next-generation sequencing.

Computer-aided design (CAD) typically deals with geometries (points, lines, and planes) subject to constraints on distances and angles. Simple counting of freedoms and constraints, as used in the analysis of engineering structures, also provides a useful condition on the residual freedoms of a CAD drawing. Here, we derive general symmetry-extended counting equations to account more fully for the balance of freedoms and constraints in 2D point–line and 3D point–line–plane frameworks. General forms are given for symmetries of the freedoms of points, lines, and planes, and constraints based on distances and angles. The resulting toolkit can be used to give stronger conditions on dimensioning of CAD drawings. This importation to CAD of a physical point of view, in which residual freedoms correspond to the mechanisms and redundant constraints to the states of self-stress of a structure composed of bodies and joints, can often reveal hidden freedoms and redundancies in CAD systems. Point-group symmetry is not a panacea: Mechanisms that depend on specific geometries may escape detection by symmetry alone. One systematic limitation of this type is proved for polyhedra with planar faces and prescribed edge lengths.

We conducted voluntary Covid-19 testing programmes for symptomatic and asymptomatic staff at a UK teaching hospital using naso-/oro-pharyngeal PCR testing and immunoassays for IgG antibodies. 1128/10,034 (11.2%) staff had evidence of Covid-19 at some time. Using questionnaire data provided on potential risk-factors, staff with a confirmed household contact were at greatest risk (adjusted odds ratio [aOR] 4.82 [95%CI 3.45–6.72]). Higher rates of Covid-19 were seen in staff working in Covid-19-facing areas (22.6% vs. 8.6% elsewhere) (aOR 2.47 [1.99–3.08]). Controlling for Covid-19-facing status, risks were heterogenous across the hospital, with higher rates in acute medicine (1.52 [1.07–2.16]) and sporadic outbreaks in areas with few or no Covid-19 patients. Covid-19 intensive care unit staff were relatively protected (0.44 [0.28–0.69]), likely by a bundle of PPE-related measures. Positive results were more likely in Black (1.66 [1.25–2.21]) and Asian (1.51 [1.28–1.77]) staff, independent of role or working location, and in porters and cleaners (2.06 [1.34–3.15]).

Motivation Resistance co-occurrence within first-line anti-tuberculosis (TB) drugs is a common phenomenon. Existing methods based on genetic data analysis of Mycobacterium tuberculosis (MTB) have been able to predict resistance of MTB to individual drugs, but have not considered the resistance co-occurrence and cannot capture latent structure of genomic data that corresponds to lineages. Results We used a large cohort of TB patients from 16 countries across six continents where whole-genome sequences for each isolate and associated phenotype to anti-TB drugs were obtained using drug susceptibility testing recommended by the World Health Organization. We then proposed an end-to-end multi-task model with deep denoising auto-encoder (DeepAMR) for multiple drug classification and developed DeepAMR_cluster, a clustering variant based on DeepAMR, for learning clusters in latent space of the data. The results showed that DeepAMR outperformed baseline model and four machine learning models with mean AUROC from 94.4% to 98.7% for predicting resistance to four first-line drugs [i.e. isoniazid (INH), ethambutol (EMB), rifampicin (RIF), pyrazinamide (PZA)], multi-drug resistant TB (MDR-TB) and pan-susceptible TB (PANS-TB: MTB that is susceptible to all four first-line anti-TB drugs). In the case of INH, EMB, PZA and MDR-TB, DeepAMR achieved its best mean sensitivity of 94.3%, 91.5%, 87.3% and 96.3%, respectively. While in the case of RIF and PANS-TB, it generated 94.2% and 92.2% sensitivity, which were lower than baseline model by 0.7% and 1.9%, respectively. t-SNE visualization shows that DeepAMR_cluster captures lineage-related clusters in the latent space. Availability and implementation The details of source code are provided at http://www.robots.ox.ac.uk/∼davidc/code.php.

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

The superfamily of prokaryotic inwardly rectifying (KirBac) potassium channels is homologous to mammalian Kir channels. However, relatively little is known about their regulation or about their physiological role in vivo. In this study, we have used random mutagenesis and genetic complementation in K +-auxotrophic Escherichia coli and Saccharomyces cerevisiae to identify activatory mutations in a range of different KirBac channels. We also show that the KirBac6.1 gene (slr5078) is necessary for normal growth of the cyanobacterium Synechocystis PCC6803. Functional analysis and molecular dynamics simulations of selected activatory mutations identified regions within the slide helix, transmembrane helices, and C terminus that function as important regulators of KirBac channel activity, as well as a region close to the selectivity filter of KirBac3.1 that may have an effect on gating. In particular, the mutations identified in TM2 favor a model of KirBac channel gating in which opening of the pore at the helix-bundle crossing plays a far more important role than has recently been proposed. © 2010 by The American Society for Biochemistry and Molecular Biology, Inc.

Structures of inwardly-rectifying (Kir) potassium channels are now available in many different crystallographic states. We now analyse these structures in the context of functional data for mutations at over 180 positions within the Kir1.1 (ROMK) channel. This reveals an extensive network of physically interacting residues which stabilise the pre-open and open-states of the channel, but which breaks down upon channel closure. This approach not only validates a structural gating pathway for the Kir channel, but also provides insight into the structure of the transition state connecting these crystallographic states.

Aromatic clusters, found with increased frequency in a set of thermophilic proteins, confer an entropic advantage over mesophilic analogues through introduction of large-amplitude oscillations; this is a source of improved free energy at high temperatures.