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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.

We aimed to assess the frequency of value preferences in recording of vital signs in electronic healthcare records (EHRs) and associated patient and hospital factors. We used EHR data from Oxford University Hospitals, UK, between 01-January-2016 and 30-June-2019 and a maximum likelihood estimator to determine the prevalence of value preferences in measurements of systolic and diastolic blood pressure (SBP/DBP), heart rate (HR) (readings ending in zero), respiratory rate (multiples of 2 or 4), and temperature (readings of 36.0 °C). We used multivariable logistic regression to investigate associations between value preferences and patient age, sex, ethnicity, deprivation, comorbidities, calendar time, hour of day, days into admission, hospital, day of week and speciality. In 4,375,654 records from 135,173 patients, there was an excess of temperature readings of 36.0 °C above that expected from the underlying distribution that affected 11.3% (95% CI 10.6–12.1%) of measurements, i.e. these observations were likely inappropriately recorded as 36.0 °C instead of the true value. SBP, DBP and HR were rounded to the nearest 10 in 2.2% (1.4–2.8%) and 2.0% (1.3–5.1%) and 2.4% (1.7–3.1%) of measurements. RR was also more commonly recorded as multiples of 2. BP digit preference and an excess of temperature recordings of 36.0 °C were more common in older and male patients, as length of stay increased, following a previous normal set of vital signs and typically more common in medical vs. surgical specialities. Differences were seen between hospitals, however, digit preference reduced over calendar time. Vital signs may not always be accurately documented, and this may vary by patient groups and hospital settings. Allowances and adjustments may be needed in delivering care to patients and in observational analyses and predictive tools using these factors as outcomes or exposures.

Genomic analysis of a diverse collection of Clostridioides difficile ribotype 078 isolates from Ireland and 9 countries in Europe provided evidence for complex regional and international patterns of dissemination that are not restricted to humans. These isolates are associated with C. difficile colonization and clinical illness in humans and pigs.

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.

Antimicrobial resistance (AMR) poses a threat to global public health. To mitigate the impacts of AMR, it is important to identify the molecular mechanisms of AMR and thereby determine optimal therapy as early as possible. Conventional machine learning-based drug-resistance analyses assume genetic variations to be homogeneous, thus not distinguishing between coding and intergenic sequences. In this study, we represent genetic data from Mycobacterium tuberculosis as a graph, and then adopt a deep graph learning method—heterogeneous graph attention network (‘HGAT–AMR’)—to predict anti-tuberculosis (TB) drug resistance. The HGAT–AMR model is able to accommodate incomplete phenotypic profiles, as well as provide ‘attention scores’ of genes and single nucleotide polymorphisms (SNPs) both at a population level and for individual samples. These scores encode the inputs, which the model is ‘paying attention to’ in making its drug resistance predictions. The results show that the proposed model generated the best area under the receiver operating characteristic (AUROC) for isoniazid and rifampicin (98.53 and 99.10%), the best sensitivity for three first-line drugs (94.91% for isoniazid, 96.60% for ethambutol and 90.63% for pyrazinamide), and maintained performance when the data were associated with incomplete phenotypes (i.e. for those isolates for which phenotypic data for some drugs were missing). We also demonstrate that the model successfully identifies genes and SNPs associated with drug resistance, mitigating the impact of resistance profile while considering particular drug resistance, which is consistent with domain knowledge.

Background Natural and vaccine-induced immunity will play a key role in controlling the SARS-CoV-2 pandemic. SARS-CoV-2 variants have the potential to evade natural and vaccine-induced immunity. Methods In a longitudinal cohort study of healthcare workers (HCWs) in Oxfordshire, UK, we investigated the protection from symptomatic and asymptomatic PCR-confirmed SARS-CoV-2 infection conferred by vaccination (Pfizer-BioNTech BNT162b2, Oxford-AstraZeneca ChAdOx1 nCOV-19) and prior infection (determined using anti-spike antibody status), using Poisson regression adjusted for age, sex, temporal changes in incidence and role. We estimated protection conferred after one versus two vaccinations and from infections with the B.1.1.7 variant identified using whole genome sequencing. Results 13,109 HCWs participated; 8285 received the Pfizer-BioNTech vaccine (1407 two doses) and 2738 the Oxford-AstraZeneca vaccine (49 two doses). Compared to unvaccinated seronegative HCWs, natural immunity and two vaccination doses provided similar protection against symptomatic infection: no HCW vaccinated twice had symptomatic infection, and incidence was 98% lower in seropositive HCWs (adjusted incidence rate ratio 0.02 [95%CI Conclusion Natural infection resulting in detectable anti-spike antibodies and two vaccine doses both provide robust protection against SARS-CoV-2 infection, including against the B.1.1.7 variant.

Tuberculosis is a respiratory disease that is treatable with antibiotics. An increasing prevalence of resistance means that to ensure a good treatment outcome it is desirable to test the susceptibility of each infection to different antibiotics. Conventionally this is done by culturing a clinical sample and then exposing aliquots to a panel of antibiotics, thereby determining the minimum inhibitory concentration (MIC) of each drug. Using 96-well broth micro dilution plates with each well containing a lyophilised pre-determined amount of an antibiotic is a convenient and cost-effective way to measure the MICs of several drugs at once for a clinical sample. Although accurate, this is an expensive and slow process that requires highly-skilled and experienced laboratory scientists. Here we show that, through the BashTheBug project hosted on the Zooniverse citizen science platform, a crowd of volunteers can reproducibly and accurately determine the MICs for 13 drugs and that simply taking the median or mode of 11-17 independent classifications is sufficient. There is therefore a potential role for crowds to support (but not supplant) the role of experts in antibiotic susceptibility testing.

Understanding the trajectory, duration, and determinants of antibody responses after SARS-CoV-2 infection can inform subsequent protection and risk of reinfection, however large-scale representative studies are limited. Here we estimated antibody response after SARS-CoV-2 infection in the general population using representative data from 7,256 United Kingdom COVID-19 infection survey participants who had positive swab SARS-CoV-2 PCR tests from 26-April-2020 to 14-June-2021. A latent class model classified 24% of participants as ‘non-responders’ not developing anti-spike antibodies, who were older, had higher SARS-CoV-2 cycle threshold values during infection (i.e. lower viral burden), and less frequently reported any symptoms. Among those who seroconverted, using Bayesian linear mixed models, the estimated anti-spike IgG peak level was 7.3-fold higher than the level previously associated with 50% protection against reinfection, with higher peak levels in older participants and those of non-white ethnicity. The estimated anti-spike IgG half-life was 184 days, being longer in females and those of white ethnicity. We estimated antibody levels associated with protection against reinfection likely last 1.5-2 years on average, with levels associated with protection from severe infection present for several years. These estimates could inform planning for vaccination booster strategies., Most people who are infected with SARS-CoV-2 seroconvert within a few weeks, but the determinants and duration of the antibody response are not known. Here, the authors characterise these features of the immune response using data from a large representative community sample of the UK population.

BackgroundDespite robust efforts, patients and staff acquire SARS-CoV-2 infection in hospitals. In this retrospective cohort study, we investigated whether whole-genome sequencing (WGS) could enhance the epidemiological investigation of healthcare-associated SARS-CoV-2 acquisition.Methods and findingsFrom 17-November-2020 to 5-January-2021, 803 inpatients and 329 staff were diagnosed with SARS-CoV-2 infection across four teaching hospitals in Oxfordshire, UK. We classified cases according to epidemiological definitions, sought epidemiological evidence of a potential source for each nosocomial infection, and evaluated if epidemiologically-linked cases had genomic evidence supporting transmission. We compared epidemiological and genomic outbreak identification.Using national epidemiological definitions, 109/803 (14%) inpatient infections were classified as definite/probable nosocomial, 615 (77%) as community-acquired and 79 (10%) as indeterminate. There was strong epidemiological evidence to support definite/probable cases as nosocomial: 107/109 (98%) had a prior-negative PCR in the same hospital stay before testing positive, and 101(93%) shared time and space with known infected patients/staff. Many indeterminate cases were likely infected in hospital: 53/79 (67%) had a prior-negative PCR and 75 (95%) contact with a potential source. 89/615 (11% of all 803 patients) with apparent community-onset had a recent hospital exposure.WGS highlighted SARS-CoV-2 is mainly imported into hospitals: within 764 samples sequenced 607 genomic clusters were identified (>1 SNP distinct). Only 43/607 (7%) clusters contained evidence of onward transmission (subsequent cases within ≤1 SNP). 20/21 epidemiologically-identified outbreaks contained multiple genomic introductions. Most (80%) nosocomial acquisition occurred in rapid super-spreading events in settings with a mix of COVID-19 and non-COVID-19 patients. Hospitals not routinely admitting COVID-19 patients had low rates of transmission. Undiagnosed/unsequenced individuals prevent genomic data from excluding nosocomial acquisition.ConclusionsOur findings suggest current surveillance definitions underestimate nosocomial acquisition and reveal most nosocomial transmission occurs from a relatively limited number of highly infectious individuals.

F-type plasmids are diverse and of great clinical significance, often carrying genes conferring antimicrobial resistance (AMR) such as extended-spectrum β-lactamases, particularly in Enterobacterales. Organising this plasmid diversity is challenging, and current knowledge is largely based on plasmids from clinical settings. Here, we present a network community analysis of a large survey of F-type plasmids from environmental (influent, effluent and upstream/downstream waterways surrounding wastewater treatment works) and livestock settings. We use a tractable and scalable methodology to examine the relationship between plasmid metadata and network communities. This reveals how niche (sampling compartment and host genera) partition and shape plasmid diversity. We also perform pangenome-style analyses on network communities. We show that such communities define unique combinations of core genes, with limited overlap. Building plasmid phylogenies based on alignments of these core genes, we demonstrate that plasmid accessory function is closely linked to core gene content. Taken together, our results suggest that stable F-type plasmid backbone structures can persist in environmental settings while allowing dramatic variation in accessory gene content that may be linked to niche adaptation. The association of F-type plasmids with AMR may reflect their suitability for rapid niche adaptation.

Background Thresholds for SARS-CoV-2 antibody assays have typically been determined using samples from symptomatic, often hospitalised, patients. In this setting the sensitivity and specificity of the best performing assays can both exceed 98%. However, antibody assay performance following mild infection is less clear. Methods We assessed quantitative IgG responses in a cohort of healthcare workers in Oxford, UK, with a high pre-test probability of Covid-19, in particular the 991/11,475(8.6%) who reported loss of smell/taste. We use anosmia/ageusia and other risk factors as probes for Covid-19 infection potentially undiagnosed by immunoassays by investigating their relationship with antibody readings either side of assay thresholds. Results The proportion of healthcare workers reporting anosmia/ageusia increased at antibody readings below diagnostic thresholds using an in-house ELISA (n = 9324) and the Abbott Architect chemiluminescent microparticle immunoassay (CMIA; n = 11,324): 426/906 (47%) reported anosmia/ageusia with a positive ELISA, 59/449 (13.1%) with high-negative and 326/7969 (4.1%) with low-negative readings. Similarly, by CMIA, 518/1093 (47.4%) with a positive result reported anosmia/ageusia, 106/686 (15.5%) with a high-negative and 358/9563 (3.7%) with a low-negative result. Adjusting for the proportion of staff reporting anosmia/ageusia suggests the sensitivity of both assays in mild infection is lower than previously reported: Oxford ELISA 89.8% (95%CI 86.6–92.8%) and Abbott CMIA 79.3% (75.9–82.7%). Conclusion Following mild SARS-CoV-2 infection 10–30% of individuals may have negative immunoassay results. While lowered diagnostic thresholds may result in unacceptable specificity, our findings have implications for epidemiological analyses and result interpretation in individuals with a high pre-test probability. Samples from mild PCR-confirmed infections should be included in SARS-CoV-2 immunoassay evaluations.

Summary Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic in 2020. Testing is crucial for mitigating public health and economic effects. Serology is considered key to population-level surveillance and potentially individual-level risk assessment. However, immunoassay performance has not been compared on large, identical sample sets. We aimed to investigate the performance of four high-throughput commercial SARS-CoV-2 antibody immunoassays and a novel 384-well ELISA. Methods We did a head-to-head assessment of SARS-CoV-2 IgG assay (Abbott, Chicago, IL, USA), LIAISON SARS-CoV-2 S1/S2 IgG assay (DiaSorin, Saluggia, Italy), Elecsys Anti-SARS-CoV-2 assay (Roche, Basel, Switzerland), SARS-CoV-2 Total assay (Siemens, Munich, Germany), and a novel 384-well ELISA (the Oxford immunoassay). We derived sensitivity and specificity from 976 pre-pandemic blood samples (collected between Sept 4, 2014, and Oct 4, 2016) and 536 blood samples from patients with laboratory-confirmed SARS-CoV-2 infection, collected at least 20 days post symptom onset (collected between Feb 1, 2020, and May 31, 2020). Receiver operating characteristic (ROC) curves were used to assess assay thresholds. Findings At the manufacturers' thresholds, for the Abbott assay sensitivity was 92·7% (95% CI 90·2–94·8) and specificity was 99·9% (99·4–100%); for the DiaSorin assay sensitivity was 96·2% (94·2–97·7) and specificity was 98·9% (98·0–99·4); for the Oxford immunoassay sensitivity was 99·1% (97·8–99·7) and specificity was 99·0% (98·1–99·5); for the Roche assay sensitivity was 97·2% (95·4–98·4) and specificity was 99·8% (99·3–100); and for the Siemens assay sensitivity was 98·1% (96·6–99·1) and specificity was 99·9% (99·4–100%). All assays achieved a sensitivity of at least 98% with thresholds optimised to achieve a specificity of at least 98% on samples taken 30 days or more post symptom onset. Interpretation Four commercial, widely available assays and a scalable 384-well ELISA can be used for SARS-CoV-2 serological testing to achieve sensitivity and specificity of at least 98%. The Siemens assay and Oxford immunoassay achieved these metrics without further optimisation. This benchmark study in immunoassay assessment should enable refinements of testing strategies and the best use of serological testing resource to benefit individuals and population health. Funding Public Health England and UK National Institute for Health Research.

ObjectivesTo determine the extent to which variation in hospital antibiotic prescribing is associated with mortality risk in acute/general medicine inpatients.DesignEcological analysis, using electronic health records from Hospital Episode Statistics (HES) and antibiotic data from IQVIA.Setting135 acute National Health Service (NHS) hospital Trusts in England.Participants36,124,372 acute/general medicine inpatients (16 years old at admission) admitted between 01/April/2010-31/March/2017 (median age 66 years, 50.4% female, 83.8% white ethnicity).Main outcome measuresRandom-effects meta-regression was used to investigate whether heterogeneity in the adjusted probability of death within 30-days of admission was associated with hospital-level antibiotic use, measured in defined-daily-doses (DDD)/1,000 bed-days. Models also considered DDDs/1,000 admissions and DDDs for selected antibiotics, including narrow-spectrum/broad-spectrum, inpatient/outpatient, parenteral/oral, piperacillin-tazobactam and meropenem, and Public Health England interpretations of World Health Organization Access, Watch, and Reserve antibiotics. Secondary analyses examined 14-day mortality and non-elective re-admission to hospital within 30-days of discharge.ResultsThere was a 15-fold variation in hospital-level DDDs/1,000 bed-days and comparable or greater variation in broad-spectrum, parenteral, and Reserve antibiotic use. After adjusting for a wide range of admission factors to reflect varying case-mix across hospitals, the adjusted probability of 30-day mortality changed by -0.010% (95% CI: -0.064 to +0.044) for each increase in hospital-level antibiotic use of 500 DDDs/1,000 bed-days. Analyses focusing on other metrics of antibiotic use, sub-populations, and 14-day mortality also showed no consistent association with the adjusted probability of death.DiscussionWe find no evidence that the wide variation in antibiotic use across NHS hospitals is associated with case-mix adjusted mortality risk in acute/general medicine inpatients. Our results indicate that hospital antibiotic use in the acute/general medicine population could be safely cut by up to one-third.What is already known on this topicPrevious studies have reported wide variation in both recommended antibiotic prescribing duration and total antibiotic consumption among acute hospitals.In hospitals with more acute patients, systematic under-treatment might reasonably be expected to harm patients, and though a growing body of evidence shows reducing hospital antibiotic overuse may be done safely, there is a lack of good data to indicate how much it may be possible to safely reduce useExamination of the possibility that substantially driving down antibiotic use could compromise clinical outcomes is needed to reassure practitioners and the public that substantially reducing antibiotic use is safe.What this study addsAfter adjusting for a wide range of admission factors to reflect varying case-mix across acute hospitals, we observed no consistent association between 24 metrics of hospital-level antibiotic use and the adjusted probability of death in a large national cohort of over 36 million acute/general medicine inpatientsThese findings indicate that at many hospitals patients are receiving considerably more antibiotics than necessary to treat their acute infections, and we estimate system-wide reductions of up to one-third of antibiotic defined-daily-doses (DDDs) could be achieved safely among medical admissions.The magnitude of the antibiotic reductions that could be safely achieved dwarf the 1% year-on-year reductions required of NHS hospitals.

Carbapenem resistance in Enterobacterales is a public health threat. Klebsiella pneumoniae carbapenemase (encoded by alleles of the blaKPC family) is one of the commonest transmissible carbapenem resistance mechanisms worldwide. The dissemination of blaKPC has historically been associated with distinct K. pneumoniae lineages (clonal group 258 [lsqb]CG258[rsqb]), a particular plasmid family (pKpQIL), and a composite transposon (Tn4401). In the UK, blaKPC has represented a large-scale, persistent, management challenge for some hospitals, particularly in North-West England. The dissemination of blaKPC has evolved to be polyclonal and poly-species, but the genetic mechanisms underpinning this evolution have not been elucidated in detail; this study used short-read whole genome sequencing of 604 blaKPC-positive isolates (Illumina) and long-read assembly (PacBio)/polishing (Illumina) of 21 isolates for characterisation. We observed the dissemination of blaKPC (predominantly blaKPC-2; 573/604 [lsqb]95%[rsqb] isolates) across eight species and more than 100 known sequence types. Although there was some variation at the transposon level (mostly Tn4401a, 584/604 (97%) isolates; predominantly with ATTGA-ATTGA target site duplications, 465/604 [lsqb]77%[rsqb] isolates), blaKPC spread appears to have been supported by highly fluid, modular exchange of larger genetic segments amongst plasmid populations dominated by IncFIB (580/604 isolates), IncFII (545/604 isolates) and IncR replicons (252/604 isolates). The subset of reconstructed plasmid sequences (21 isolates, 77 plasmids) also highlighted modular exchange amongst non-blaKPC and blaKPC plasmids, and the common presence of multiple replicons within blaKPC plasmid structures (>60%). The substantial genomic plasticity observed has important implications for our understanding of the epidemiology of transmissible carbapenem resistance in Enterobacterales, for the implementation of adequate surveillance approaches, and for control.

SARS-CoV-2 IgG screening of 1,000 antenatal serum samples in the Oxford area, United Kingdom, between 14 April and 15 June 2020, yielded a 5.3% seroprevalence, mirroring contemporaneous regional data. Among the 53 positive samples, 39 showed in vitro neutralisation activity, correlating with IgG titre (Pearson’s correlation p

Sequencing data from host-associated microbes can often be contaminated by the body of the investigator or research subject. Human DNA is typically removed from microbial reads either by subtractive alignment (dropping all reads that map to the human genome) or using a read classification tool to predict those of human origin, and then discarding them. To inform best practice guidelines, we benchmarked 8 alignment-based and 2 classification-based methods of human read detection using simulated data from 10 clinically prevalent bacteria and 3 viruses, into which contaminating human reads had been added.While the majority of methods successfully detected > 99% of the human reads, they were distinguishable by variance. The most precise methods, with negligible variance, were Bowtie2 and SNAP, both of which misclassified few, if any, bacterial reads (and no viral reads) as human. While correctly detecting a similar number of human reads, methods based on taxonomic classification, such as Kraken2 and Centrifuge, often misclassified bacterial reads as human, the extent of which was species-specific. Among the most sensitive methods of human read detection was BWA, although this also made the greatest number of false positive classifications. Across all methods, the set of human reads not identified as such, although often representing < 0.1% of the total reads, were non-randomly distributed along the human genome with many originating from the repeat-rich sex chromosomes.For viral reads and longer (> 300bp) bacterial reads, the highest performing approaches were classification-based, using Kraken2 or Centrifuge. For shorter (150-300bp) bacterial reads, combining multiple methods of human read detection maximised the recovery of human reads from contaminated short read datasets without being compromised by false positives. The highest-performing approach with shorter bacterial reads was a two-stage classification using Bowtie2 followed by SNAP. Using this approach, we re-examined 11,577 publicly archived bacterial readsets for hitherto undetected human contamination. We were able to extract a sufficient number of reads to call known human SNPs, including those with clinical significance, in 6% of the samples. These results show that phenotypically-distinct human sequence is widespread in publicly-archived (and nominally pure) bacterial datasets.

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

Human metapneumovirus (HMPV) has been recognized as an important pathogen which can cause a spectrum of respiratory tract disease. Here, we report Nanopore metagenomic sequencing of the first full length HMPV genome directly from a throat swab from a UK patient with complex lung disease and immunocompromise. We found a predominance (26.4%) of HMPV reads in the metagenomic sequencing data and consequently assembled the full genome at a high depth of coverage (mean 4,786). Through phylogenetic analyses, we identified this HMPV strain to originate from a unique genetic group in A2b, showing the presence of this group in the UK. Our study demonstrated the effectiveness of Nanopore metagenomic sequencing for diagnosing infectious diseases and recovering complete sequences for genomic characterization, highlighting the applicability of Nanopore sequencing in clinical settings.

Background Rates of Clostridium difficile infection vary widely across Europe, as do prevalent ribotypes. The extent of Europe-wide diversity within each ribotype is however unknown. Methods Inpatient diarrhoeal faecal samples submitted on one day in summer and winter (2012-2013) to laboratories in 482 European hospitals were cultured for C. difficile, and isolates ribotyped; those from the 10 most prevalent ribotypes were Illumina whole-genome sequenced. Pairwise single nucleotide differences (SNPs) were obtained from recombination-corrected maximum-likelihood phylogenies. Within each ribotype, country-based sequence clustering was assessed using the ratio of the median SNPs between isolates within versus across different countries using permutation tests. Time-scaled Bayesian phylogenies where used to reconstruct the historic location of each lineage. Results Sequenced isolates (n=624) were from 19 countries. Five ribotypes had within-country clustering: ribotype-356, only in Italy; ribotype-018, predominantly in Italy; ribotype-176, with distinct Czech and German clades; ribotype-001/072, including distinct German, Slovakian, and Spanish clades; and ribotype-027, with multiple predominantly country-specific clades including in Hungary, Italy, Germany, Romania and Poland. By contrast, we found no within-country clustering for ribotypes 078, 015, 002, 014, and 020, consistent with a Europe-wide distribution. Fluoroquinolone-resistance was significantly more common in within-country clustered ribotypes (p=0.009). Fluoroquinolone-resistant isolates were also more tightly geographically clustered, median (IQR) 43 (0-213) miles between each isolate and the most closely genetically-related isolate vs. 421 (204-680) in non-resistant pairs (p

Background No previous study has used whole-genome sequencing (WGS) to investigate risk factors for C. difficile(CD) transmission between symptomatic cases, or assessed the impact of recent acquisition on patient outcome. Methods This retrospective cohort study included consecutive diarrhoeal samples positive by cytotoxin assay in Leeds, UK(Aug10-Apr12). All samples underwent culture, ribotyping and WGS(Illumina). Sequenced isolates were compared using single nucleotide variants(SNVs). Independent predictors of acquisition from another case, onward transmission, 120-day recurrence and 30-day mortality were identified using logistic regression with backwards elimination. Results 640/660(97·0%) CD cases were sequenced. 567(89%) cases shared a ribotype with a prior case but only 227(35%) were ≤2 SNVs from a prior case, supporting recent acquisition. Plausible recent ward-based acquisition from a symptomatic case 0·1). Conclusions Greater transmission of certain lineages suggests CD may have different reservoirs and modes of transmission. Acquiring CD from a recent case is associated with poorer clinical outcomes. Clinical characteristics shown to be associated with increased healthcare-associated CD transmission could be used to target preventative interventions.

Farm animals have been identified as reservoirs of Clostridium difficile PCR-ribotype 078 (RT078). Since 2005, the incidence of human clinical cases (frequently severe), with this genotype has increased. We aimed to understand this change, by studying the recent evolutionary history of RT078. Phylogenetic analysis of international genomes (isolates from 2006–2014) revealed several recent clonal expansions. A common ancestor of each expansion had independently acquired different alleles of the tetracycline resistance gene tetM. Consequently, an unusually high proportion of RT078 genomes were tetM positive (76.5%). Additional tetracycline resistance determinants were also identified, some for the first time in C. difficile (efflux pump tet40). Each tetM-clonal expansion lacked geographic structure, indicating rapid international spread. Resistance determinants for C. difficile-infection-triggering antimicrobials including fluoroquinolones and clindamycin were comparatively rare in RT078. Tetracyclines are used intensively in agriculture; this selective pressure, plus rapid spread via the food-chain may explain the increased RT078 prevalence in humans.

Purpose Speed of bloodstream infection diagnosis is vital to reduce morbidity and mortality. Whole genome sequencing (WGS) performed directly from liquid blood culture could provide single-assay species and antibiotic susceptibility prediction; however, high inhibitor and human cell/DNA concentrations limit pathogen recovery. We develop a method for the preparation of bacterial DNA for WGS-based diagnostics direct from liquid blood culture. Methodology We evaluate three commercial DNA extraction kits: BiOstic Bacteraemia, Amplex Hyplex and MolYsis Plus. Differential centrifugation, filtration, selective lysis and solid-phase reversible immobilization bead clean-up are tested to improve human cells/DNA and inhibitor removal. Using WGS (Illumina/MinION), we assess human DNA removal, pathogen recovery, and predict species and antibiotic susceptibility inpositive blood cultures of 44 Gram-negative and 54 Staphylococcus species. Results/Key findings BiOstic kit extractions yield the greatest mean DNA concentration, 94–301 ng µl−1, versus 0–2.5 ng µl−1 using Amplex and MolYsis kits. However, we note higher levels of inhibition (260/280 ratio 0.9–2.1) and human DNA (0.0–4.4×106 copies) in BiOstic extracts. Differential centrifugation (2000 g , 1 min) prior to BiOstic extraction reduces human DNA by 63–89 % with selective lysis minimizing by a further 62 %. Post-extraction bead clean-up lowers inhibition. Overall, 67 % of sequenced samples (Illumina MiSeq) contain 93 % concordance between WGS-based species and susceptibility predictions and clinical diagnosis. If >60 % of sequencing reads are human (7/98 samples) susceptibility prediction becomes compromised. Novel MinION-based WGS (n=9) currently gives rapid species identification but not susceptibility prediction. Conclusion Our method for DNA preparation allows WGS-based diagnosis direct from blood culture bottles, providing species and antibiotic susceptibility prediction in a single assay.

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.)

Background and Objectives: Serratia marcescens is an emerging nosocomial pathogen, and the carbapenemase blaNDM has been reported in several surveys in Romania. We aimed to investigate the molecular epidemiology of S. marcescens in two Romanian hospitals over 2010-2015; including a neonatal NDM-1- S. marcescens outbreak. Methods: Isolates were sequenced using Illumina technology together with carbapenem-non-susceptible NDM-1-positive and NDM-1-negative K. pneumoniae and E. cloacae to provide genomic context. A subset were sequenced with MinION to fully resolve NDM-1 plasmid structures. Resistance genes, plasmid replicons and insertion sequences were identified in silico for all isolates; an annotated phylogeny was reconstructed for S. marcescens. Fully resolved study NDM-1 plasmid sequences were compared with the most closely related publicly available NDM-1 plasmid reference. Results: 44/45 isolates were successfully sequenced (S. marcescens, n=33; K. pneumoniae, n=7; E. cloacae, n=4); ten with MinION. The S. marcescens phylogeny demonstrated several discrete clusters of NDM-1-positive and negative isolates. All NDM-1-positive isolates across species harboured a pKOX-NDM-1-like plasmid; more detailed comparisons of the plasmid structures demonstrated a number of differences, but largely conserved plasmid backbones across species and hospital sites. Conclusions: The molecular epidemiology is most consistent with the importation of a pKOX-NDM1-like plasmid into Romania and its dissemination amongst K. pneumoniae/E. cloacae and subsequently S. marcescens across hospitals. The data suggested multiple acquisitions of this plasmid by S. marcescens in the two hospitals studied; transmission events within centres, including a large outbreak on the Targu-Mures neonatal unit; and sharing of the pKOX-NDM-1-like plasmid between species within outbreaks.

Background: Approximately 30-40% of children

Summary Infection control effectiveness at 6 English hospitals was compared using whole-genome sequencing of C. difficile isolates. Proportions of isolates sufficiently genetically related to suggest transmission from a previous isolate ranged from 7% at the best institution to 22–26% in most others., Background. Variation in Clostridium difficile infection (CDI) rates between healthcare institutions suggests overall incidence could be reduced if the lowest rates could be achieved more widely. Methods. We used whole-genome sequencing (WGS) of consecutive C. difficile isolates from 6 English hospitals over 1 year (2013–14) to compare infection control performance. Fecal samples with a positive initial screen for C. difficile were sequenced. Within each hospital, we estimated the proportion of cases plausibly acquired from previous cases. Results. Overall, 851/971 (87.6%) sequenced samples contained toxin genes, and 451 (46.4%) were fecal-toxin-positive. Of 652 potentially toxigenic isolates >90-days after the study started, 128 (20%, 95% confidence interval [CI] 17–23%) were genetically linked (within ≤2 single nucleotide polymorphisms) to a prior patient’s isolate from the previous 90 days. Hospital 2 had the fewest linked isolates, 7/105 (7%, 3–13%), hospital 1, 9/70 (13%, 6–23%), and hospitals 3–6 had similar proportions of linked isolates (22–26%) (P ≤ .002 comparing hospital-2 vs 3–6). Results were similar adjusting for locally circulating ribotypes. Adjusting for hospital, ribotype-027 had the highest proportion of linked isolates (57%, 95% CI 29–81%). Fecal-toxin-positive and toxin-negative patients were similarly likely to be a potential transmission donor, OR = 1.01 (0.68–1.49). There was no association between the estimated proportion of linked cases and testing rates. Conclusions. WGS can be used as a novel surveillance tool to identify varying rates of C. difficile transmission between institutions and therefore to allow targeted efforts to reduce CDI incidence.

We demonstrated that some non-synonymous and synonymous mutations in $\textit{gyrA}$ in $\textit{Mycobacterium tuberculosis}$ result in systematic false-resistance results to fluoroquinolones using the Hain GenoType MTBDRsl assays (version 1 and 2) by preventing the binding of wild-type probes. Moreover, such mutations can prevent the binding of mutant probes, designed for the identification of specific resistance mutations. Although these mutations are likely rare globally, they occur in approximately 7% of multidrug-resistant tuberculosis strains in some settings.

Background: The control of Clostridium difficile infections is an international clinical challenge. The incidence of C difficile in England declined by roughly 80% after 2006, following the implementation of national control policies; we tested two hypotheses to investigate their role in this decline. First, if C difficile infection declines in England were driven by reductions in use of particular antibiotics, then incidence of C difficile infections caused by resistant isolates should decline faster than that caused by susceptible isolates across multiple genotypes. Second, if C difficile infection declines were driven by improvements in hospital infection control, then transmitted (secondary) cases should decline regardless of susceptibility. Methods: Regional (Oxfordshire and Leeds, UK) and national data for the incidence of C difficile infections and antimicrobial prescribing data (1998–2014) were combined with whole genome sequences from 4045 national and international C difficile isolates. Genotype (multilocus sequence type) and fluoroquinolone susceptibility were determined from whole genome sequences. The incidence of C difficile infections caused by fluoroquinolone-resistant and fluoroquinolone-susceptible isolates was estimated with negative-binomial regression, overall and per genotype. Selection and transmission were investigated with phylogenetic analyses. Findings: National fluoroquinolone and cephalosporin prescribing correlated highly with incidence of C difficile infections (cross-correlations >0·88), by contrast with total antibiotic prescribing (cross-correlations 0·2). Interpretation: Restricting fluoroquinolone prescribing appears to explain the decline in incidence of C difficile infections, above other measures, in Oxfordshire and Leeds, England. Antimicrobial stewardship should be a central component of C difficile infection control programmes.

Bacteria responsible for the greatest global mortality colonize the human microbiome far more frequently than they cause severe infections. Whether mutation and selection within the microbiome accompany infection is unknown. We investigatedde novomutation in 1163Staphylococcus aureusgenomes from 105 infected patients with nose-colonization. We report that 72% of infections emerged from the microbiome, with infecting and nose-colonizing bacteria showing parallel adaptive differences. We found 2.8-to-3.6-fold enrichments of protein-altering variants in genes responding torsp, which regulates surface antigens and toxicity;agr, which regulates quorum-sensing, toxicity and abscess formation; and host-derived antimicrobial peptides. Adaptive mutations in pathogenesis-associated genes were 3.1-fold enriched in infecting but not nose-colonizing bacteria. None of these signatures were observed in healthy carriers nor at the species-level, suggesting disease-associated, short-term, within-host selection pressures. Our results show that infection, like a cancer of the microbiome, emerges through spontaneous adaptive evolution, raising new possibilities for diagnosis and treatment.One Sentence SummaryLife-threateningS. aureusinfections emerge from nose microbiome bacteria in association with repeatable adaptive evolution.

Background The role of symptomatic patients who are toxigenic strain-positive (TS+) but fecal toxin-negative (FT-) in transmission of Clostridium difficile is currently unknown. Methods We investigated the contribution of symptomatic TS+/FT- and TS+/FT+ patients in C. difficile transmission in two UK regions. From two-step testing, all glutamate dehydrogenase (GDH)-positive specimens, regardless of fecal toxin result, from Oxford (April2012-April2013) and Leeds (July2012-April2013) microbiology laboratories underwent culture and whole-genome sequencing (WGS), using WGS to identify toxigenic strains. Plausible sources for each TS+/FT+ case, including TS+/FT- and TS+/FT+ patients, were determined using WGS, with and without hospital admission data. Results 1447/12772(11%) fecal samples were GDH-positive, 866/1447(60%) contained toxigenic C. difficile and fecal toxin was detected in 511/866(59%), representing 235 Leeds and 191 Oxford TS+/FT+ cases. TS+/FT+ cases were three times more likely to be plausibly acquired from a previous TS+/FT+ case than a TS+/FT- patient. 51(19%) of 265 TS+/FT+ cases diagnosed >3 months into the study were genetically-related (≤2 single nucleotide polymorphisms) to ≥1 previous TS+/FT+ case or TS+/FT- patient: 27(10%) to only TS+/FT+ cases, 9(3%) to only TS+/FT- patients, and 15(6%) to both. Only 10/265(4%) were genetically-related to a previous TS+/FT+ or TS+/FT- patient and shared the same ward simultaneously or within 28 days. Conclusions Symptomatic TS+/FT- patients were a source of C. difficile transmission, although they accounted for less onward transmission than TS+/FT+ cases. Although transmission from symptomatic patients with either fecal toxin status accounted for a low overall proportion of new cases, both groups should be infection control targets.

Outpatient iv antibiotic therapy is well developed in the United States, largely because of pressures from third-party payers to reduce costs of medical care. We have developed an outpatient iv antibiotic programme in Oxford, that has evolved from a desire to provide high quality iv therapy to AIDS patients with cytomegalovirus retinitis. We describe the rationale of the service and report on our first two years' experience. We treated 67 consecutive patients (eight with HIV infection) at home with iv antibiotics. This resulted in a saving of 2275 hospital days for those patients without HIV infection. HIV positive patients received 69 months of home iv therapy. Minor intravascular catheter complications occurred in only five patients (7.5%). The only serious complications were three episodes of catheter-related sepsis (4.5%), all occurring in AIDS patients who had lines in for more than six months. We have shown that home iv antibiotic therapy can be delivered safely to patients with a wide variety of infectious problems using the existing network of community nurses in the National Health Service. Essential components to the programme include a multidisciplinary team working between the hospital and community and a written shared care protocol. Such a programme can result in reduced lengths of hospital stay and patient, community nurse and physician satisfaction.

Objectives To investigate the prospects of newly available benchtop sequencers to provide rapid whole-genome data in routine clinical practice. Next-generation sequencing has the potential to resolve uncertainties surrounding the route and timing of person-to-person transmission of healthcare-associated infection, which has been a major impediment to optimal management. Design The authors used Illumina MiSeq benchtop sequencing to undertake case studies investigating potential outbreaks of methicillin-resistant Staphylococcus aureus (MRSA) and Clostridium difficile. Setting Isolates were obtained from potential outbreaks associated with three UK hospitals. Participants Isolates were sequenced from a cluster of eight MRSA carriers and an associated bacteraemia case in an intensive care unit, another MRSA cluster of six cases and two clusters of C difficile. Additionally, all C difficile isolates from cases over 6 weeks in a single hospital were rapidly sequenced and compared with local strain sequences obtained in the preceding 3 years. Main outcome measure Whole-genome genetic relatedness of the isolates within each epidemiological cluster. Results Twenty-six MRSA and 15 C difficile isolates were successfully sequenced and analysed within 5 days of culture. Both MRSA clusters were identified as outbreaks, with most sequences in each cluster indistinguishable and all within three single nucleotide variants (SNVs). Epidemiologically unrelated isolates of the same spa-type were genetically distinct (≥21 SNVs). In both C difficile clusters, closely epidemiologically linked cases (in one case sharing the same strain type) were shown to be genetically distinct (≥144 SNVs). A reconstruction applying rapid sequencing in C difficile surveillance provided early outbreak detection and identified previously undetected probable community transmission. Conclusions This benchtop sequencing technology is widely generalisable to human bacterial pathogens. The findings provide several good examples of how rapid and precise sequencing could transform identification of transmission of healthcare-associated infection and therefore improve hospital infection control and patient outcomes in routine clinical practice., Article summary Article focus To investigate the prospects of newly available benchtop sequencers to provide rapid whole-genome data in routine clinical practice. In particular to investigate the potential of such technology for identification of transmission events of healthcare-associated pathogens. Key messages We demonstrate benchtop sequencing can enhance hospital infection control through high precision support and rejection of transmission using genetic data. Whole-genome data provided additional genetic resolution over existing genetic typing strategies. We also show this technology offers turnaround times of under a week in a format that, in contrast to molecular typing, is organism independent. Strengths and limitations of this study The case studies presented provide several good examples of how rapid and precise sequencing could transform identification of transmission of healthcare-associated infection. Given this is a pilot study, further evaluations of the impact of this technology on hospital infection control are required. However, this study provides a clear rationale for future work undertaking formal comparisons of benchtop sequencing with existing local and national typing schemes.

BACKGROUND: It has been thought that Clostridium difficile infection is transmitted predominantly within health care settings. However, endemic spread has hampered identification of precise sources of infection and the assessment of the efficacy of interventions. METHODS: From September 2007 through March 2011, we performed whole-genome sequencing on isolates obtained from all symptomatic patients with C. difficile infection identified in health care settings or in the community in Oxfordshire, United Kingdom. We compared single-nucleotide variants (SNVs) between the isolates, using C. difficile evolution rates estimated on the basis of the first and last samples obtained from each of 145 patients, with 0 to 2 SNVs expected between transmitted isolates obtained less than 124 days apart, on the basis of a 95% prediction interval. We then identified plausible epidemiologic links among genetically related cases from data on hospital admissions and community location. RESULTS: Of 1250 C. difficile cases that were evaluated, 1223 (98%) were successfully sequenced. In a comparison of 957 samples obtained from April 2008 through March 2011 with those obtained from September 2007 onward, a total of 333 isolates (35%) had no more than 2 SNVs from at least 1 earlier case, and 428 isolates (45%) had more than 10 SNVs from all previous cases. Reductions in incidence over time were similar in the two groups, a finding that suggests an effect of interventions targeting the transition from exposure to disease. Of the 333 patients with no more than 2 SNVs (consistent with transmission), 126 patients (38%) had close hospital contact with another patient, and 120 patients (36%) had no hospital or community contact with another patient. Distinct subtypes of infection continued to be identified throughout the study, which suggests a considerable reservoir of C. difficile. CONCLUSIONS: Over a 3-year period, 45% of C. difficile cases in Oxfordshire were genetically distinct from all previous cases. Genetically diverse sources, in addition to symptomatic patients, play a major part in C. difficile transmission. (Funded by the U.K. Clinical Research Collaboration Translational Infection Research Initiative and others.)