An end-to-end heterogeneous graph attention network for Mycobacterium tuberculosis drug-resistance prediction.

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.

Ten Years of Population-Level Genomic Escherichia coli and Klebsiella pneumoniae Serotype Surveillance Informs Vaccine Development for Invasive Infections.

BACKGROUND: The incidence of bloodstream infections (BSIs) caused by Escherichia coli and Klebsiella pneumoniae is increasing, with substantial associated morbidity, mortality, and antimicrobial resistance. Unbiased serotyping studies to guide vaccine target selection are limited. METHODS: We conducted unselected, population-level genomic surveillance of bloodstream E. coli and Klebsiella pneumoniae isolates from 2008 to 2018 in Oxfordshire, United Kingdom. We supplemented this with an analysis of publicly available global sequencing data (n = 3678). RESULTS: We sequenced 3478 E. coli isolates (3278 passed quality control) and 556 K. pneumoniae isolates (535 [K-antigen] and 549 [O-antigen] passed quality control). The 4 most common E. coli O-antigens (O1/O2/O6/O25) were identified in 1499/3278 isolates; the incidence of these O-types increased over time (incidence rate ratio per year [IRRy] = 1.14, 95% confidence interval [CI]: 1.11-1.16). These O-types accounted for 616/1434 multidrug-resistant (MDR) and 173/256 extended-spectrum beta-lactamase (ESBL)-resistant isolates in Oxfordshire but only 19/90 carbapenem-resistant isolates across all studies. For Klebsiella pneumoniae, the most common O-antigens (O2v2/O1v1/O3b/O1v2) accounted for 410/549 isolates; the incidence of BSIs caused by these also increased annually (IRRy = 1.09; 95% CI: 1.05-1.12). These O-types accounted for 122/148 MDR and 106/123 ESBL isolates in Oxfordshire and 557/734 carbapenem-resistant isolates across all studies. Conversely we observed substantial capsular antigen diversity. Analysis of 3678 isolates from global studies demonstrated the generalizability of these findings. For E. coli, based on serotyping, the ExPEC4V and ExPEC10V vaccines under investigation would cover 46% and 72% of Oxfordshire isolates respectively, and 47% and 71% of MDR isolates. CONCLUSIONS: O-antigen targeted vaccines may be useful in reducing the morbidity, mortality, and antimicrobial resistance associated with E. coli and K. pneumoniae BSIs.

Diagnosis of SARS-CoV-2 Infection with LamPORE, a High-Throughput Platform Combining Loop-Mediated Isothermal Amplification and Nanopore Sequencing.

LamPORE is a novel diagnostic platform for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA combining loop-mediated isothermal amplification with nanopore sequencing, which could potentially be used to analyze thousands of samples per day on a single instrument. We evaluated the performance of LamPORE against reverse transcriptase PCR (RT-PCR) using RNA extracted from spiked respiratory samples and stored nose and throat swabs collected at two UK hospitals. The limit of detection of LamPORE was 10 genome copies/µl of extracted RNA, which is above the limit achievable by RT-PCR, but was not associated with a significant reduction of sensitivity in clinical samples. Positive clinical specimens came mostly from patients with acute symptomatic infection, and among them, LamPORE had a diagnostic sensitivity of 99.1% (226/228; 95% confidence interval [CI], 96.9% to 99.9%). Among negative clinical specimens, including 153 with other respiratory pathogens detected, LamPORE had a diagnostic specificity of 99.6% (278/279; 98.0% to 100.0%). Overall, 1.4% (7/514; 0.5% to 2.9%) of samples produced an indeterminate result on first testing, and repeat LamPORE testing on the same RNA extract had a reproducibility of 96.8% (478/494; 94.8% to 98.1%). LamPORE has a similar performance as RT-PCR for the diagnosis of SARS-CoV-2 infection in symptomatic patients and offers a promising approach to high-throughput testing.

Stringent thresholds in SARS-CoV-2 IgG assays lead to under-detection of mild infections.

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.

Nanopore metagenomic sequencing of influenza virus directly from respiratory samples: diagnosis, drug resistance and nosocomial transmission, United Kingdom, 2018/19 influenza season.

BackgroundInfluenza virus presents a considerable challenge to public health by causing seasonal epidemics and occasional pandemics. Nanopore metagenomic sequencing has the potential to be deployed for near-patient testing, providing rapid infection diagnosis, rationalising antimicrobial therapy, and supporting infection-control interventions.AimTo evaluate the applicability of this sequencing approach as a routine laboratory test for influenza in clinical settings.MethodsWe conducted Oxford Nanopore Technologies (Oxford, United Kingdom (UK)) metagenomic sequencing for 180 respiratory samples from a UK hospital during the 2018/19 influenza season, and compared results to routine molecular diagnostic standards (Xpert Xpress Flu/RSV assay; BioFire FilmArray Respiratory Panel 2 assay). We investigated drug resistance, genetic diversity, and nosocomial transmission using influenza sequence data.ResultsCompared to standard testing, Nanopore metagenomic sequencing was 83% (75/90) sensitive and 93% (84/90) specific for detecting influenza A viruses. Of 59 samples with haemagglutinin subtype determined, 40 were H1 and 19 H3. We identified an influenza A(H3N2) genome encoding the oseltamivir resistance S331R mutation in neuraminidase, potentially associated with an emerging distinct intra-subtype reassortant. Whole genome phylogeny refuted suspicions of a transmission cluster in a ward, but identified two other clusters that likely reflected nosocomial transmission, associated with a predominant community-circulating strain. We also detected other potentially pathogenic viruses and bacteria from the metagenome.ConclusionNanopore metagenomic sequencing can detect the emergence of novel variants and drug resistance, providing timely insights into antimicrobial stewardship and vaccine design. Full genome generation can help investigate and manage nosocomial outbreaks.

Genomic Epidemiology of Complex, Multispecies, Plasmid-Borne blaKPC Carbapenemase in Enterobacterales in the United Kingdom from 2009 to 2014.

Carbapenem resistance in Enterobacterales is a public health threat. Klebsiella pneumoniae carbapenemase (encoded by alleles of the blaKPC family) is one of the most common transmissible carbapenem resistance mechanisms worldwide. The dissemination of blaKPC historically has been associated with distinct K. pneumoniae lineages (clonal group 258 [CG258]), a particular plasmid family (pKpQIL), and a composite transposon (Tn4401). In the United Kingdom, 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 polyspecies, 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 characterization. We observed the dissemination of blaKPC (predominantly blaKPC-2; 573/604 [95%] 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 [77%] isolates), blaKPC spread appears to have been supported by highly fluid, modular exchange of larger genetic segments among plasmid populations dominated by IncFIB (580/604 isolates), IncFII (545/604 isolates), and IncR (252/604 isolates) replicons. The subset of reconstructed plasmid sequences (21 isolates, 77 plasmids) also highlighted modular exchange among 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.

Investigation of the impact of the NICE guidelines regarding antibiotic prophylaxis during invasive dental procedures on the incidence of infective endocarditis in England: an electronic health records study.

BACKGROUND: Infective endocarditis is an uncommon but serious infection, where evidence for giving antibiotic prophylaxis before invasive dental procedures is inconclusive. In England, antibiotic prophylaxis was offered routinely to patients at risk of infective endocarditis until March 2008, when new guidelines aimed at reducing unnecessary antibiotic use were issued. We investigated whether changes in infective endocarditis incidence could be detected using electronic health records, assessing the impact of inclusion criteria/statistical model choice on inferences about the timing/type of any change. METHODS: Using national data from Hospital Episode Statistics covering 1998-2017, we modelled trends in infective endocarditis incidence using three different sets of inclusion criteria plus a range of regression models, identifying the most likely date for a change in trends if evidence for one existed. We also modelled trends in the proportions of different organism groups identified during infection episodes, using secondary diagnosis codes and data from national laboratory records. Lastly, we applied non-parametric local smoothing to visually inspect any changes in trend around the guideline change date. RESULTS: Infective endocarditis incidence increased markedly over the study (22.2-41.3 per million population in 1998 to 42.0-67.7 in 2017 depending on inclusion criteria). The most likely dates for a change in incidence trends ranged from September 2001 (uncertainty interval August 2000-May 2003) to May 2015 (March 1999-January 2016), depending on inclusion criteria and statistical model used. For the proportion of infective endocarditis cases associated with streptococci, the most likely change points ranged from October 2008 (March 2006-April 2010) to August 2015 (September 2013-November 2015), with those associated with oral streptococci decreasing in proportion after the change point. Smoothed trends showed no notable changes in trend around the guideline date. CONCLUSIONS: Infective endocarditis incidence has increased rapidly in England, though we did not detect any change in trends directly following the updated guidelines for antibiotic prophylaxis, either overall or in cases associated with oral streptococci. Estimates of when changes occurred were sensitive to inclusion criteria and statistical model choice, demonstrating the need for caution in interpreting single models when using large datasets. More research is needed to explore the factors behind this increase.

DNA Thermo-Protection Facilitates Whole-Genome Sequencing of Mycobacteria Direct from Clinical Samples.

Mycobacterium tuberculosis is the leading cause of death from bacterial infection. Improved rapid diagnosis and antimicrobial resistance determination, such as by whole-genome sequencing, are required. Our aim was to develop a simple, low-cost method of preparing DNA for sequencing direct from M. tuberculosis-positive clinical samples (without culture). Simultaneous sputum liquefaction, bacteria heat inactivation (99°C/30 min), and enrichment for mycobacteria DNA were achieved using an equal volume of thermo-protection buffer (4 M KCl, 0.05 M HEPES buffer, pH 7.5, 0.1% dithiothreitol [DTT]). The buffer emulated intracellular conditions found in hyperthermophiles, thus protecting DNA from rapid thermodegradation, which renders it a poor template for sequencing. Initial validation experiments employed mycobacteria DNA, either extracted or intracellular. Next, mock clinical samples (infection-negative human sputum spiked with 0 to 105Mycobacterium bovis BCG cells/ml) underwent liquefaction in thermo-protection buffer and heat inactivation. DNA was extracted and sequenced. Human DNA degraded faster than mycobacteria DNA, resulting in target enrichment. Four replicate experiments achieved M. tuberculosis detection at 101 BCG cells/ml, with 31 to 59 M. tuberculosis complex reads. Maximal genome coverage (>97% at 5× depth) occurred at 104 BCG cells/ml; >91% coverage (1× depth) occurred at 103 BCG cells/ml. Final validation employed M. tuberculosis-positive clinical samples (n = 20), revealing that initial sample volumes of ≥1 ml typically yielded higher mean depths of M. tuberculosis genome coverage, with an overall range of 0.55 to 81.02. A mean depth of 3 gave >96% 1-fold tuberculosis (TB) genome coverage (in 15/20 clinical samples). A mean depth of 15 achieved >99% 5-fold genome coverage (in 9/20 clinical samples). In summary, direct-from-sample sequencing of M. tuberculosis genomes was facilitated by a low-cost thermo-protection buffer.

Application of machine learning techniques to tuberculosis drug resistance analysis.

MOTIVATION: Timely identification of Mycobacterium tuberculosis (MTB) resistance to existing drugs is vital to decrease mortality and prevent the amplification of existing antibiotic resistance. Machine learning methods have been widely applied for timely predicting resistance of MTB given a specific drug and identifying resistance markers. However, they have been not validated on a large cohort of MTB samples from multi-centers across the world in terms of resistance prediction and resistance marker identification. Several machine learning classifiers and linear dimension reduction techniques were developed and compared for a cohort of 13 402 isolates collected from 16 countries across 6 continents and tested 11 drugs. RESULTS: Compared to conventional molecular diagnostic test, area under curve of the best machine learning classifier increased for all drugs especially by 23.11%, 15.22% and 10.14% for pyrazinamide, ciprofloxacin and ofloxacin, respectively (P < 0.01). Logistic regression and gradient tree boosting found to perform better than other techniques. Moreover, logistic regression/gradient tree boosting with a sparse principal component analysis/non-negative matrix factorization step compared with the classifier alone enhanced the best performance in terms of F1-score by 12.54%, 4.61%, 7.45% and 9.58% for amikacin, moxifloxacin, ofloxacin and capreomycin, respectively, as well increasing area under curve for amikacin and capreomycin. Results provided a comprehensive comparison of various techniques and confirmed the application of machine learning for better prediction of the large diverse tuberculosis data. Furthermore, mutation ranking showed the possibility of finding new resistance/susceptible markers. AVAILABILITY AND IMPLEMENTATION: The source code can be found at http://www.robots.ox.ac.uk/ davidc/code.php. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis.

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. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Risk Factors Associated with Carbapenemase-Producing Enterobacterales (CPE) Positivity in the Hospital Wastewater Environment.

Hospital wastewater is an increasingly recognized reservoir for resistant Gram-negative organisms. Factors involved in establishment and persistence of Klebsiella pneumoniae carbapenemase-producing organisms (KPCOs) in hospital wastewater plumbing are unclear. This study was conducted at a hospital with endemic KPCOs linked to wastewater reservoirs and robust patient perirectal screening for silent KPCO carriage. Over 5 months, both rooms occupied and rooms not occupied by KPCO-positive patients were sampled at three wastewater sites within each room (sink drain, sink P-trap, and toilet or hopper). Risk factors for KPCO positivity were assessed using logistic regression. Whole-genome sequencing (WGS) identified environmental seeding by KPCO-positive patients. A total of 219/475 (46%) room sampling events were KPCO positive in at least one wastewater site. KPCO-positive patient exposure was associated with increased risk of environmental positivity for the room and toilet/hopper. Previous positivity and intensive care unit room type were consistently associated with increased risk. Tube feeds were associated with increased risk for the drain, while exposure to patients with Clostridioides difficile was associated with decreased risk. Urinary catheter exposure was associated with increased risk of P-trap positivity. P-trap heaters reduced risk of P-trap and sink drain positivity. WGS identified genomically linked environmental seeding in 6 of 99 room occupations by 40 KPCO-positive patients. In conclusion, KPCO-positive patients seed the environment in at least 6% of opportunities; once positive for KPCOs, wastewater sites are at greater risk of being positive subsequently. Increased nutrient exposure, e.g., due to tube food disposal down sinks, may increase risk; frequent flushing may be protective.IMPORTANCEKlebsiella pneumoniae carbapenemase-producing organisms (KPCOs) are bacteria that are resistant to most antibiotics and thus are challenging to treat when they cause infections in patients. These organisms can be acquired by patients who are hospitalized for other reasons, complicating their hospital stay and even leading to death. Hospital wastewater sites, such as sink drains and toilets, have played a role in many reported outbreaks over the past decade. The significance of our research is in identifying risk factors for environmental positivity for KPCOs, which will facilitate further work to prevent transmission of these organisms to patients from the hospital environment.

Metagenomic Nanopore Sequencing of Influenza Virus Direct from Clinical Respiratory Samples.

Influenza is a major global public health threat as a result of its highly pathogenic variants, large zoonotic reservoir, and pandemic potential. Metagenomic viral sequencing offers the potential for a diagnostic test for influenza virus which also provides insights on transmission, evolution, and drug resistance and simultaneously detects other viruses. We therefore set out to apply the Oxford Nanopore Technologies sequencing method to metagenomic sequencing of respiratory samples. We generated influenza virus reads down to a limit of detection of 102 to 103 genome copies/ml in pooled samples, observing a strong relationship between the viral titer and the proportion of influenza virus reads (P = 4.7 × 10-5). Applying our methods to clinical throat swabs, we generated influenza virus reads for 27/27 samples with mid-to-high viral titers (cycle threshold [CT ] values, <30) and 6/13 samples with low viral titers (CT values, 30 to 40). No false-positive reads were generated from 10 influenza virus-negative samples. Thus, Nanopore sequencing operated with 83% sensitivity (95% confidence interval [CI], 67 to 93%) and 100% specificity (95% CI, 69 to 100%) compared to the current diagnostic standard. Coverage of full-length virus was dependent on sample composition, being negatively influenced by increased host and bacterial reads. However, at high influenza virus titers, we were able to reconstruct >99% complete sequences for all eight gene segments. We also detected a human coronavirus coinfection in one clinical sample. While further optimization is required to improve sensitivity, this approach shows promise for the Nanopore platform to be used in the diagnosis and genetic analysis of influenza virus and other respiratory viruses.

Patient and Strain Characteristics Associated With Clostridium difficile Transmission and Adverse Outcomes.

Background: No study has used whole-genome sequencing (WGS) to investigate risk factors for Clostridium difficile (CD) transmission between cases, or assessed the impact of recent acquisition on patient outcome. Methods: This 20 month retrospective cohort study included consecutive cytotoxin-positive diarrheal samples, which 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: Of 660 CD cases, 640 (97%) were sequenced, of which 567 (89%) shared a ribotype with a prior case, but only 227 (35%) were ≤2 SNVs from a prior case, supporting recent acquisition. Plausible (<2 SNVs) recent ward-based acquisition from a symptomatic case was more frequent in certain ribotypes; 64% (67/105) for ribotype-027 cases, compared with 11% (6/57) for ribotype-078. Independent risk factors (adjusted P < .05) for CD acquisition included older age, longer inpatient duration, and ribotype; these factors, and male sex, increased onward transmission. Patients with a plausible donor had a greater risk of recurrence (adjusted P = .001) and trended towards greater 30-day mortality (adjusted P = .06). Ribotype had no additional mortality or recurrence impact after adjusting for acquisition (P > .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 associated with increased healthcare-associated CD transmission could be used to target preventative interventions.

Validating a 14-Drug Microtiter Plate Containing Bedaquiline and Delamanid for Large-Scale Research Susceptibility Testing of Mycobacterium tuberculosis.

The UKMYC5 plate is a 96-well microtiter plate designed by the CRyPTIC Consortium (Comprehensive Resistance Prediction for Tuberculosis: an International Consortium) to enable the measurement of MICs of 14 different antituberculosis (anti-TB) compounds for >30,000 clinical Mycobacterium tuberculosis isolates. Unlike the MYCOTB plate, on which the UKMYC5 plate is based, the UKMYC5 plate includes two new (bedaquiline and delamanid) and two repurposed (clofazimine and linezolid) compounds. UKMYC5 plates were tested by seven laboratories on four continents by use of a panel of 19 external quality assessment (EQA) strains, including H37Rv. To assess the optimal combination of reading method and incubation time, MICs were measured from each plate by two readers, using three methods (mirrored box, microscope, and Vizion digital viewing system), after 7, 10, 14, and 21 days of incubation. In addition, all EQA strains were subjected to whole-genome sequencing and phenotypically characterized by the 7H10/7H11 agar proportion method (APM) and by use of MGIT960 mycobacterial growth indicator tubes. We concluded that the UKMYC5 plate is optimally read using the Vizion system after 14 days of incubation, achieving an interreader agreement of 97.9% and intra- and interlaboratory reproducibility rates of 95.6% and 93.1%, respectively. The mirrored box had a similar reproducibility. Strains classified as resistant by APM, MGIT960, or the presence of mutations known to confer resistance consistently showed elevated MICs compared to those for strains classified as susceptible. Finally, the UKMYC5 plate records intermediate MICs for one strain for which the APM measured MICs close to the applied critical concentration, providing early evidence that the UKMYC5 plate can quantitatively measure the magnitude of resistance to anti-TB compounds that is due to specific genetic variation.

Automated detection of bacterial growth on 96-well plates for high-throughput drug susceptibility testing of Mycobacterium tuberculosis.

M. tuberculosis grows slowly and is challenging to work with experimentally compared with many other bacteria. Although microtitre plates have the potential to enable high-throughput phenotypic testing of M. tuberculosis, they can be difficult to read and interpret. Here we present a software package, the Automated Mycobacterial Growth Detection Algorithm (AMyGDA), that measures how much M. tuberculosis is growing in each well of a 96-well microtitre plate. The plate used here has serial dilutions of 14 anti-tuberculosis drugs, thereby permitting the MICs to be elucidated. The three participating laboratories each inoculated 38 96-well plates with 15 known M. tuberculosis strains (including the standard H37Rv reference strain) and, after 2 weeks' incubation, measured the MICs for all 14 drugs on each plate and took a photograph. By analysing the images, we demonstrate that AMyGDA is reproducible, and that the MICs measured are comparable to those measured by a laboratory scientist. The AMyGDA software will be used by the Comprehensive Resistance Prediction for Tuberculosis: an International Consortium (CRyPTIC) to measure the drug susceptibility profile of a large number (>30000) of samples of M. tuberculosis from patients over the next few years.

Evaluation of Whole-Genome Sequencing for Mycobacterial Species Identification and Drug Susceptibility Testing in a Clinical Setting: a Large-Scale Prospective Assessment of Performance against Line Probe Assays and Phenotyping.

Use of whole-genome sequencing (WGS) for routine mycobacterial species identification and drug susceptibility testing (DST) is becoming a reality. We compared the performances of WGS and standard laboratory workflows prospectively, by parallel processing at a major mycobacterial reference service over the course of 1 year, for species identification, first-line Mycobacterium tuberculosis resistance prediction, and turnaround time. Among 2,039 isolates with line probe assay results for species identification, 74 (3.6%) failed sequencing or WGS species identification. Excluding these isolates, clinically important species were identified for 1,902 isolates, of which 1,825 (96.0%) were identified as the same species by WGS and the line probe assay. A total of 2,157 line probe test results for detection of resistance to the first-line drugs isoniazid and rifampin were available for 728 M. tuberculosis complex isolates. Excluding 216 (10.0%) cases where there were insufficient sequencing data for WGS to make a prediction, overall concordance was 99.3% (95% confidence interval [CI], 98.9 to 99.6%), sensitivity was 97.6% (91.7 to 99.7%), and specificity was 99.5% (99.0 to 99.7%). A total of 2,982 phenotypic DST results were available for 777 M. tuberculosis complex isolates. Of these, 356 (11.9%) had no WGS comparator due to insufficient sequencing data, and in 154 (5.2%) cases the WGS prediction was indeterminate due to discovery of novel, previously uncharacterized mutations. Excluding these data, overall concordance was 99.2% (98.7 to 99.5%), sensitivity was 94.2% (88.4 to 97.6%), and specificity was 99.4% (99.0 to 99.7%). Median processing times for the routine laboratory tests versus WGS were similar overall, i.e., 20 days (interquartile range [IQR], 15 to 31 days) and 21 days (15 to 29 days), respectively (P = 0.41). In conclusion, WGS predicts species and drug susceptibility with great accuracy, but work is needed to increase the proportion of predictions made.

The Hospital Water Environment as a Reservoir for Carbapenem-Resistant Organisms Causing Hospital-Acquired Infections-A Systematic Review of the Literature.

Over the last 20 years there have been 32 reports of carbapenem-resistant organisms in the hospital water environment, with half of these occurring since 2010. The majority of these reports have described associated clinical outbreaks in the intensive care setting, affecting the critically ill and the immunocompromised. Drains, sinks, and faucets were most frequently colonized, and Pseudomonas aeruginosa the predominant organism. Imipenemase (IMP), Klebsiella pneumoniae carbapenemase (KPC), and Verona integron-encoded metallo-ß-lactamase (VIM) were the most common carbapenemases found. Molecular typing was performed in almost all studies, with pulse field gel electrophoresis being most commonly used. Seventy-two percent of studies reported controlling outbreaks, of which just more than one-third eliminated the organism from the water environment. A combination of interventions seems to be most successful, including reinforcement of general infection control measures, alongside chemical disinfection. The most appropriate disinfection method remains unclear, however, and it is likely that replacement of colonized water reservoirs may be required for long-term clearance.

Contribution to Clostridium Difficile Transmission of Symptomatic Patients With Toxigenic Strains Who Are Fecal Toxin Negative.

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 2 UK regions. From 2-step testing, all glutamate dehydrogenase (GDH)-positive specimens, regardless of fecal toxin result, from Oxford (April 2012 through April 2013) and Leeds (July 2012 through April 2013) 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: A total of 1447 of 12772 (11%) fecal samples were GDH positive, 866 of 1447 (60%) contained toxigenic C. difficile, and fecal toxin was detected in 511 of 866 (59%), representing 235 Leeds and 191 Oxford TS+/FT+ cases. TS+/FT+ cases were 3 times more likely to be plausibly acquired from a previous TS+/FT+ case than a TS+/FT- patient. Fifty-one of 265 (19%) 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 of 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.

Increasing burden of community-acquired pneumonia leading to hospitalisation, 1998-2014.

BACKGROUND: Community-acquired pneumonia (CAP) is a major cause of mortality and morbidity in many countries but few recent large-scale studies have examined trends in its incidence. METHODS: Incidence of CAP leading to hospitalisation in one UK region (Oxfordshire) was calculated over calendar time using routinely collected diagnostic codes, and modelled using piecewise-linear Poisson regression. Further models considered other related diagnoses, typical administrative outcomes, and blood and microbiology test results at admission to determine whether CAP trends could be explained by changes in case-mix, coding practices or admission procedures. RESULTS: CAP increased by 4.2%/year (95% CI 3.6 to 4.8) from 1998 to 2008, and subsequently much faster at 8.8%/year (95% CI 7.8 to 9.7) from 2009 to 2014. Pneumonia-related conditions also increased significantly over this period. Length of stay and 30-day mortality decreased slightly in later years, but the proportions with abnormal neutrophils, urea and C reactive protein (CRP) did not change (p>0.2). The proportion with severely abnormal CRP (>100 mg/L) decreased slightly in later years. Trends were similar in all age groups. Streptococcus pneumoniae was the most common causative organism found; however other organisms, particularly Enterobacteriaceae, increased in incidence over the study period (p<0.001). CONCLUSIONS: Hospitalisations for CAP have been increasing rapidly in Oxfordshire, particularly since 2008. There is little evidence that this is due only to changes in pneumonia coding, an ageing population or patients with substantially less severe disease being admitted more frequently. Healthcare planning to address potential further increases in admissions and consequent antibiotic prescribing should be a priority.

Reduction of invasive pneumococcal disease 3 years after the introduction of the 13-valent conjugate vaccine in the Oxfordshire region of England.

BACKGROUND: The 7-valent pneumococcal conjugate (PCV7) vaccine's impact on invasive pneumococcal disease (IPD) is well described, but few reports exist on the additional impact of the 13-valent vaccine (PCV13). METHODS: We calculated the IPD incidence across all ages in a surveillance project following implementation of PCV7 (in September 2006) and PCV13 (in April 2010) in children aged <2 years (11 hospitals; 4935 cases). RESULTS: The overall incidence decreased from 10 cases/100 000 persons per year in 1996-1997 to 8 cases/100 000 persons per year in 2007-2008 and 7 cases/100 000 in 2012-2013. Declines were greater in children aged <2 years (from 37 cases/100 000 in 1996-1997 to 29 and 14 cases/100 000 in 2007-2008 and 2012-2013, respectively). The incidence of IPD due to PCV7 serotypes decreased in all ages after PCV7 introduction (P < .001), whereas the incidence of IPD due to the additional 6 serotypes in PCV13 and to nonvaccine types (NVTs) increased in children aged ≥2 years (P < .001 for both comparisons). The incidence of IPD due to the 6 additional serotypes in PCV13 declined significantly after PCV13 introduction in all ages (P ≤ .01), and the incidence of IPD due to NVTs declined significantly in children aged ≥2 years (P = .003). In 2011-2013, the overall incidences of IPD due to PCV7 serotypes, the 6 additional serotypes in PCV13, and NVTs were 0.3, 2.8, and 4.4 cases/100 000; the incidences among children aged <2 years were 0.9, 2.4, and 10.8 cases/100 000, respectively. CONCLUSIONS: The annual incidence of IPD due to vaccine serotypes (1-3 cases/100 000) among children aged <2 years and nontarget groups demonstrates the success of PCV7 and PCV13. A substantially higher incidence of IPD due to NVTs indicates the importance of ongoing surveillance and extension of vaccine polyvalency.