Convergent evolution and topologically disruptive polymorphisms among multidrug-resistant tuberculosis in Peru

Background Multidrug-resistant tuberculosis poses a major threat to the success of tuberculosis control programs worldwide. Understanding how drug-resistant tuberculosis evolves can inform the development of new therapeutic and preventive strategies. Methods Here, we use novel genome-wide analysis techniques to identify polymorphisms that are associated with drug resistance, adaptive evolution and the structure of the phylogenetic tree. A total of 471 samples from different patients collected between 2009 and 2013 in the Lima suburbs of Callao and Lima South were sequenced on the Illumina MiSeq platform with 150bp paired-end reads. After alignment to the reference H37Rv genome, variants were called using standardized methodology. Genome-wide analysis was undertaken using custom written scripts implemented in R software. Results High quality homoplastic single nucleotide polymorphisms were observed in genes known to confer drug resistance as well as genes in the Mycobacterium tuberculosis ESX secreted protein pathway, pks12, and close to toxin/anti-toxin pairs. Correlation of homoplastic variant sites identified that many were significantly correlated, suggestive of epistasis. Variation in genes coding for ESX secreted proteins also significantly disrupted phylogenetic structure. Mutations in ESX genes in key antigenic epitope positions were also found to disrupt tree topology. Conclusion Variation in these genes have a biologically plausible effect on immunogenicity and virulence. This makes functional characterization warranted to determine the effects of these polymorphisms on bacterial fitness and transmission

Multi-compartment profiling of cacterial and host metabolites identifies intestinal dysbiosis and its functional consequences in the critically ill child

Adverse physiology and antibiotic exposure devastate the intestinal microbiome in critical illness. Time and cost implications limit the immediate clinical potential of microbial sequencing to identify or treat intestinal dysbiosis. Here, we examined whether metabolic profiling is a feasible method of monitoring intestinal dysbiosis in critically ill children. Prospective multicenter cohort study. Three U.K.-based PICUs. Mechanically ventilated critically ill (n = 60) and age-matched healthy children (n = 55). Collection of urine and fecal samples in children admitted to the PICU. A single fecal and urine sample was collected in healthy controls. Untargeted and targeted metabolic profiling using 1H-nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry or urine and fecal samples. This was integrated with analysis of fecal bacterial 16S ribosomal RNA profiles and clinical disease severity indicators. We observed separation of global urinary and fecal metabolic profiles in critically ill compared with healthy children. Urinary excretion of mammalian-microbial co-metabolites hippurate, 4-cresol sulphate, and formate were reduced in critical illness compared with healthy children. Reduced fecal excretion of short-chain fatty acids (including butyrate, propionate, and acetate) were observed in the patient cohort, demonstrating that these metabolites also distinguished between critical illness and health. Dysregulation of intestinal bile metabolism was evidenced by increased primary and reduced secondary fecal bile acid excretion. Fecal butyrate correlated with days free of intensive care at 30 days (r = 0.38; p = 0.03), while urinary formate correlated inversely with vasopressor requirement (r = -0.2; p = 0.037). Disruption to the functional activity of the intestinal microbiome may result in worsening organ failure in the critically ill child. Profiling of bacterial metabolites in fecal and urine samples may support identification and treatment of intestinal dysbiosis in critical illness.This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Prospective Surveillance and Rapid Whole-Genome Sequencing Detects Two Unsuspected Outbreaks of Carbapenemase-Producing Klebsiella pneumoniae in a UK Teaching Hospital

Abstract Background The increasing incidence of carbapenemase-producing Enterobacteriaceae (CPE) is a global health concern, as treatment options are extremely limited. The prevalence of CPE in UK hospitals is unknown, as national screening guidelines only recommend screening in patients considered to be at high-risk of CPE. Patients in intensive care units (ICU) are at high-risk of healthcare-associated infections caused by multidrug-resistant organisms (MDRO). Methods We conducted a six-month prospective surveillance study to determine the prevalence of MDRO in a UK teaching hospital ICU. Between June and December 2016, all adult patients admitted to ICU were screened for MDRO on admission, on discharge, and weekly during their ICU stay. Surveillance samples included stool or rectal swabs, urine, sputum or tracheal aspirates, and wound swabs (if wounds were present). Isolates were characterized phenotypically before undergoing whole-genome sequencing (WGS), epidemiological, and phylogenetic analyses. Results During the first week of the study we identified stool carriage of a multidrug-resistant Klebsiella pneumoniae strain in two patients neither of whom had recognized risk factors for CPE. Both isolates were resistant to all antibiotics tested, apart from colistin, and were PCR-positive for the blaNDM-1 gene. Enhanced surveillance by the infection control team identified four additional patients in several wards who had stool carriage (n = 3) or bloodstream infection (n = 1) with a blaNDM-1K. pneumoniae isolate. Epidemiological links were identified between these six patients. Five months later, a second outbreak of multidrug-resistant K. pneumoniae was detected, involving stool carriage by four patients on two different wards. Environmental screening identified environmental contamination with multidrug-resistant K. pneumoniae on one ward. DNA sequence analysis confirmed that a novel blaNDM-1K. pneumoniaelineage (ST78) was responsible for both outbreaks in the hospital. Conclusion We identified two unsuspected blaNDM-1K. pneumoniae outbreaks in patients with no recognized risk factors for CPE. This highlights the importance of prospective surveillance for MDRO in high-risk settings, such as ICUs, and supports the use of rapid WGS to support outbreak investigations in real-time. Disclosures All authors: No reported disclosures. </jats:sec

Evaluation of the MODS Culture Technique for the Diagnosis of Tuberculous Meningitis

Tuberculous meningitis (TBM) is a devastating condition. The rapid instigation of appropraite chemotherapy is vital to reduce morbidity and mortality. However rapid diagnosis remains elusive; smear microscopy has extremely low sensitivity on cerebrospinal fluid (CSF) in most laboratories and PCR requires expertise with advanced infrastructure and has sensitivity of only around 60% under optimal conditions. Neither technique allows for the microbiological isolation of M. tuberculosis and subsequent drug susceptibility testing. We evaluated the recently developed microscopic observation drug susceptibility (MODS) assay format for speed and accuracy in diagnosing TBM.Two hundred and thirty consecutive CSF samples collected from 156 patients clinically suspected of TBM on presentation at a tertiary referal hospital in Vietnam were enrolled into the study over a five month period and tested by Ziehl-Neelsen (ZN) smear, MODS, Mycobacterial growth Indicator tube (MGIT) and Lowenstein-Jensen (LJ) culture. Sixty-one samples were from patients already on TB therapy for >1day and 19 samples were excluded due to untraceable patient records. One hundred and fifty samples from 137 newly presenting patients remained. Forty-two percent (n = 57/137) of patients were deemed to have TBM by clinical diagnostic and microbiological criteria (excluding MODS). Sensitivity by patient against clinical gold standard for ZN smear, MODS MGIT and LJ were 52.6%, 64.9%, 70.2% and 70.2%, respectively. Specificity of all microbiological techniques was 100%. Positive and negative predictive values for MODS were 100% and 78.7%, respectively for HIV infected patients and 100% and 82.1% for HIV negative patients. The median time to positive was 6 days (interquartile range 5-7), significantly faster than MGIT at 15.5 days (interquartile range 12-24), and LJ at 24 days (interquartile range 18-35 days) (P<0.01).We have shown MODS to be a sensitive, rapid technique for the diagnosis of TBM with high sensitivity, ease of performance and low cost (0.53 USD/sample)

Screening of healthcare workers for SARS-CoV-2 highlights the role of asymptomatic carriage in COVID-19 transmission.

Significant differences exist in the availability of healthcare worker (HCW) SARS-CoV-2 testing between countries, and existing programmes focus on screening symptomatic rather than asymptomatic staff. Over a 3 week period (April 2020), 1032 asymptomatic HCWs were screened for SARS-CoV-2 in a large UK teaching hospital. Symptomatic staff and symptomatic household contacts were additionally tested. Real-time RT-PCR was used to detect viral RNA from a throat+nose self-swab. 3% of HCWs in the asymptomatic screening group tested positive for SARS-CoV-2. 17/30 (57%) were truly asymptomatic/pauci-symptomatic. 12/30 (40%) had experienced symptoms compatible with coronavirus disease 2019 (COVID-19)>7 days prior to testing, most self-isolating, returning well. Clusters of HCW infection were discovered on two independent wards. Viral genome sequencing showed that the majority of HCWs had the dominant lineage B∙1. Our data demonstrates the utility of comprehensive screening of HCWs with minimal or no symptoms. This approach will be critical for protecting patients and hospital staff.This work was supported by the Wellcome Trust Senior Research Fellowships 108070/Z/15/Z to MPW, 215515/Z/19/Z to SGB and 207498/Z/17/Z to IGG; Collaborative award 206298/B/17/Z to IGG; Principal Research Fellowship 210688/Z/18/Z to PJL; Investigator Award 200871/Z/16/Z to KGCS; Addenbrooke’s Charitable Trust (to MPW, SGB, IGG and PJL); the Medical Research Council (CSF MR/P008801/1 to NJM); NHS Blood and Transfusion (WPA15-02 to NJM); National Institute for Health Research (Cambridge Biomedical Research Centre at CUHNFT), to JRB, MET, AC and GD, Academy of Medical Sciences and the Health Foundation (Clinician Scientist Fellowship to MET), Engineering and Physical Sciences Research Council (EP/P031447/1 and EP/N031938/1 to RS),Cancer Research UK (PRECISION Grand Challenge C38317/A24043 award to JY). Components of this work were supported by the COVID-19 Genomics UK Consortium, (COG-UK), which is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) and Genome Research Limited, operating as the Wellcome Sanger Institut

How achievable are COVID-19 clinical trial recruitment targets? A UK observational cohort study and trials registry analysis

Objectives: To analyse enrolment to interventional trials during the first wave of the COVID-19 pandemic in England and describe the barriers to successful recruitment in the circumstance of a further wave or future pandemics. Design: We analysed registered interventional COVID-19 trial data and concurrently did a prospective observational study of hospitalised patients with COVID-19 who were being assessed for eligibility to one of the RECOVERY, C19-ACS or SIMPLE trials. Setting: Interventional COVID-19 trial data were analysed from the clinicaltrials.gov and International Standard Randomized Controlled Trial Number databases on 12 July 2020. The patient cohort was taken from five centres in a respiratory National Institute for Health Research network. Population and modelling data were taken from published reports from the UK government and Medical Research Council Biostatistics Unit. Participants: 2082 consecutive admitted patients with laboratory-confirmed SARS-CoV-2 infection from 27 March 2020 were included. Main outcome measures: Proportions enrolled, and reasons for exclusion from the aforementioned trials. Comparisons of trial recruitment targets with estimated feasible recruitment numbers. Results: Analysis of trial registration data for COVID-19 treatment studies enrolling in England showed that by 12 July 2020, 29 142 participants were needed. In the observational study, 430 (20.7%) proceeded to randomisation. 82 (3.9%) declined participation, 699 (33.6%) were excluded on clinical grounds, 363 (17.4%) were medically fit for discharge and 153 (7.3%) were receiving palliative care. With 111 037 people hospitalised with COVID-19 in England by 12 July 2020, we determine that 22 985 people were potentially suitable for trial enrolment. We estimate a UK hospitalisation rate of 2.38%, and that another 1.25 million infections would be required to meet recruitment targets of ongoing trials. Conclusions: Feasible recruitment rates, study design and proliferation of trials can limit the number, and size, that will successfully complete recruitment. We consider that fewer, more appropriately designed trials, prioritising cooperation between centres would maximise productivity in a further wave

Prognostic models for 9 month mortality in tuberculous meningitis

Background: Tuberculous meningitis (TBM) is the most severe form of extra-pulmonary tuberculosis. We developed and validated prognostic models for 9-month mortality in HIV-uninfected and HIV-infected adults with TBM. Methods: We included 1699 subjects from four randomized clinical trials and one prospective observational study conducted at two major referral hospitals in Southern Vietnam from 2001-2015. Modelling was based on multivariable Cox proportional hazards regression. The final prognostic models were validated internally and temporally, and displayed using nomograms and a web-based app (https://thaole.shinyapps.io/tbmapp/). Results: A total of 951 HIV-uninfected and 748 HIV-infected subjects with TBM were included, of whom 219/951 (23.0%) and 384/748 (51.3%) died during 9-month follow-up. Common predictors for increased mortality in both populations were higher Medical Research Council (MRC) disease severity grade and lower cerebrospinal fluid lymphocyte cells count. In HIV-uninfected subjects, older age, previous tuberculosis, not receiving adjunctive dexamethasone, and focal neurological signs were additional risk factors; in HIV-infected subjects, lower weight, lower peripheral blood CD4 cell count, and abnormal plasma sodium were additional risk factors. The areas under the receiver operating characteristic curves (AUCs) for the final prognostic models were 0.77 (HIV-uninfected population) and 0.78 (HIV-infected population), demonstrating markedly better discrimination than the MRC grade (AUC 0.66 and 0.70) or the Glasgow Coma Score (AUC 0.68 and 0.71) alone. Conclusions: The developed models showed good performance and could be used in clinical practice to assist doctors in identifying TBM patients at high risk of death and at increased need of supportive care.This work was supported by the Academy of Medical Sciences and the Health Foundation (Clinician Scientist Fellowship to M. E. T.), the National Institute of Health Research Cambridge Biomedical Research Centre (M. E. T), and a Wellcome Trust Intermediate Fellowship (grant number WT097147MA) to J.D

Dynamic Prediction of Death in Patients With Tuberculous Meningitis Using Time-updated Glasgow Coma Scale and Plasma Sodium Measurements.

BACKGROUND: Pretreatment predictors of death from tuberculous meningitis (TBM) are well established, but whether outcome can be predicted more accurately after the start of treatment by updated clinical variables is unknown. Hence, we developed and validated models that dynamically predict mortality using time-updated Glasgow Coma Scale (GCS) and plasma sodium measurements, together with patient baseline characteristics. METHODS: We included 1048 adults from 4 TBM studies conducted in southern Vietnam from 2004 to 2016. We used a landmarking approach to predict death within 120 days after treatment initiation using time-updated data during the first 30 days of treatment. Separate models were built for patients with and without human immunodeficiency virus (HIV) infection. We used the area under the receiver operating characteristic curve (AUC) to evaluate performance of the models at days 10, 20, and 30 of treatment to predict mortality by 60, 90, and 120 days. Our internal validation was corrected for overoptimism using bootstrap. We provide a web-based application that computes mortality risk within 120 days. RESULTS: Higher GCS indicated better prognosis in all patients. In HIV-infected patients, higher plasma sodium was uniformly associated with good prognosis, whereas in HIV-uninfected patients the association was heterogeneous over time. The bias-corrected AUC of the models ranged from 0.82 to 0.92 and 0.81 to 0.85 in HIV-uninfected and HIV-infected individuals, respectively. The models outperformed the previously published baseline models. CONCLUSIONS: Time-updated GCS and plasma sodium measurements improved predictions based solely on information obtained at diagnosis. Our models may be used in practice to define those with poor prognosis during treatment.This work was supported by the Wellcome Trust (grant number 106680/B/14/Z) and the Wellcome Trust Intermediate Fellowship (grant number WT097147MA to J. D.). M. E. T. is a Clinician Scientist Fellow supported by the Academy of Medical Sciences, the Health Foundation, the MRC Newton Fund, and the National Institute for Health Research Cambridge Biomedical Research Centre

Recurrent SARS-CoV-2 mutations in immunodeficient patients

Long-term severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in immunodeficient patients are an important source of variation for the virus but are understudied. Many case studies have been published which describe one or a small number of long-term infected individuals but no study has combined these sequences into a cohesive dataset. This work aims to rectify this and study the genomics of this patient group through a combination of literature searches as well as identifying new case series directly from the COVID-19 Genomics UK (COG-UK) dataset. The spike gene receptor-binding domain and N-terminal domain (NTD) were identified as mutation hotspots. Numerous mutations associated with variants of concern were observed to emerge recurrently. Additionally a mutation in the envelope gene, T30I was determined to be the second most frequent recurrently occurring mutation arising in persistent infections. A high proportion of recurrent mutations in immunodeficient individuals are associated with ACE2 affinity, immune escape, or viral packaging optimisation.There is an apparent selective pressure for mutations that aid cell–cell transmission within the host or persistence which are often different from mutations that aid inter-host transmission, although the fact that multiple recurrent de novo mutations are considered defining for variants of concern strongly indicates that this potential source of novel variants should not be discounted