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Drug susceptibility testing of M. tuberculosis is rooted in a binary susceptible/resistant paradigm.Whilst there are considerable advantages in measuring the minimum inhibitory concentrations (MICs) of a panel of drugs for an isolate it is n ecessary to measure the epidemiological cutoff values (ECOFF/ECVs) to permit comparison with qualitative data. Here we present ECOFF/ECVs for 13 anti-TB compounds, including bedaquiline and delamanid, derived from 20,637 clinical isolates collected by 14 laboratories based in 11 countries on five continents. Each isolate was incubated for 14 days on a dry 96-well broth microdilution plate and then read. Resistance to most of the drugs due to prior exposure is expected and the MIC distributions for many of the compounds are complex and therefore a phenotypically wild-type population could not be defined. Since a majority of samples also underwent genetic sequencing, we defined a genotypically wild-type population and measured the MIC of the 99th percentile by direct measurement and via fitting a Gaussian using interval regression.The proposed ECOFF/ECV values were then validated by comparing to the MIC distributions of high-confidence genetic variants that confer resistance and to qualitative drug susceptibility tests obtained via Mycobacterial Growth Indicator Tube and the Microscopic-Observation Drug-Susceptibility assay.These ECOFF/ECV values will inform and encourage the more widespread adoption of broth microdilution – this is a cheap culture-based method that tests the susceptibility of 12-14 antibiotics on a single 96-well plate and so could help personalise the treatment of tuberculosis.

Summary Background Decisions about the continued need for control measures to contain the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rely on accurate and up-to-date information about the number of people testing positive for SARS-CoV-2 and risk factors for testing positive. Existing surveillance systems are generally not based on population samples and are not longitudinal in design. Methods Samples were collected from individuals aged 2 years and older living in private households in England that were randomly selected from address lists and previous Office for National Statistics surveys in repeated cross-sectional household surveys with additional serial sampling and longitudinal follow-up. Participants completed a questionnaire and did nose and throat self-swabs. The percentage of individuals testing positive for SARS-CoV-2 RNA was estimated over time by use of dynamic multilevel regression and poststratification, to account for potential residual non-representativeness. Potential changes in risk factors for testing positive over time were also assessed. The study is registered with the ISRCTN Registry, ISRCTN21086382. Findings Between April 26 and Nov 1, 2020, results were available from 1 191 170 samples from 280 327 individuals; 5231 samples were positive overall, from 3923 individuals. The percentage of people testing positive for SARS-CoV-2 changed substantially over time, with an initial decrease between April 26 and June 28, 2020, from 0·40% (95% credible interval 0·29–0·54) to 0·06% (0·04–0·07), followed by low levels during July and August, 2020, before substantial increases at the end of August, 2020, with percentages testing positive above 1% from the end of October, 2020. Having a patient-facing role and working outside your home were important risk factors for testing positive for SARS-CoV-2 at the end of the first wave (April 26 to June 28, 2020), but not in the second wave (from the end of August to Nov 1, 2020). Age (young adults, particularly those aged 17–24 years) was an important initial driver of increased positivity rates in the second wave. For example, the estimated percentage of individuals testing positive was more than six times higher in those aged 17–24 years than in those aged 70 years or older at the end of September, 2020. A substantial proportion of infections were in individuals not reporting symptoms around their positive test (45–68%, dependent on calendar time. Interpretation Important risk factors for testing positive for SARS-CoV-2 varied substantially between the part of the first wave that was captured by the study (April to June, 2020) and the first part of the second wave of increased positivity rates (end of August to Nov 1, 2020), and a substantial proportion of infections were in individuals not reporting symptoms, indicating that continued monitoring for SARS-CoV-2 in the community will be important for managing the COVID-19 pandemic moving forwards. Funding Department of Health and Social Care.

Serological detection of antibodies to SARS-CoV-2 is essential for establishing rates of seroconversion in populations, detection of seroconversion after vaccination, and for seeking evidence for a level of antibody that may be protective against COVID-19 disease. Several high-performance commercial tests have been described, but these require centralised laboratory facilities that are comparatively expensive, and therefore not available universally. Red cell agglutination tests have a long history in blood typing, and general serology through linkage of reporter molecules to the red cell surface. They do not require special equipment, are read by eye, have short development times, low cost and can be applied as a Point of Care Test (POCT). We describe a red cell agglutination test for the detection of antibodies to the SARS-CoV-2 receptor binding domain (RBD). We show that the Haemagglutination Test (HAT) has a sensitivity of 90% and specificity of 99% for detection of antibodies after a PCR diagnosed infection. The HAT can be titrated, detects rising titres in the first five days of hospital admission, correlates well with a commercial test that detects antibodies to the RBD, and can be applied as a point of care test. The developing reagent is composed of a previously described nanobody to a conserved glycophorin A epitope on red cells, linked to the RBD from SARS-CoV-2. It can be lyophilised for ease of shipping. We have scaled up production of this reagent to one gram, which is sufficient for ten million tests, at a cost of ~0.27 UK pence per test well. Aliquots of this reagent are ready to be supplied to qualified groups anywhere in the world that need to detect antibodies to SARS-CoV-2, but do not have the facilities for high throughput commercial tests.

The rise of antimicrobial-resistant Neisseria gonorrhoeae is a significant public health concern. Against this background, rapid culture-independent diagnostics may allow targeted treatment and prevent onward transmission. We have previously shown metagenomic sequencing of urine samples from men with urethral gonorrhea can recover near-complete N. gonorrhoeae genomes. However, disentangling the N. gonorrhoeae genome from metagenomic samples and robustly identifying antimicrobial resistance determinants from error-prone Nanopore sequencing is a substantial bioinformatics challenge. Here, we show an N. gonorrhoeae diagnostic workflow for analysis of metagenomic sequencing data obtained from clinical samples using R9.4.1 Nanopore sequencing. We compared results from simulated and clinical infections with data from known reference strains and Illumina sequencing of isolates cultured from the same patients. We evaluated three Nanopore variant callers and developed a random forest classifier to filter called SNPs. Clair was the most suitable variant caller after SNP filtering. A minimum depth of 20× reads was required to confidently identify resistant determinants over the entire genome. Our findings show that metagenomic Nanopore sequencing can provide reliable diagnostic information in N. gonorrhoeae infection.

Members of the genus

A hypervirulent Klebsiella pneumoniae (hvKp) pathotype is undergoing global dissemination. In contrast to the usual health care-associated epidemiology of classical K. pneumoniae (cKp) infections, hvKp causes tissue-invasive infections in otherwise healthy individuals from the community, often involving multiple sites. An accurate test to identify hvKp strains is needed for improved patient care and epidemiologic studies. To fill this knowledge gap, clinical criteria or random blood isolates from North American and United Kingdom strain collections were used to assemble hvKp-rich (n = 85) and cKp-rich (n = 90) strain cohorts, respectively. The isolates were then assessed for multiple candidate biomarkers hypothesized to accurately differentiate the two cohorts. The genes peg-344, iroB, iucA, plasmid-borne rmpA gene ((p)rmpA), and (p)rmpA2 all demonstrated >0.95 diagnostic accuracy for identifying strains in the hvKp-rich cohort. Next, to validate this epidemiological analysis, all strains were assessed experimentally in a murine sepsis model. peg-344, iroB, iucA, (p)rmpA, and (p)rmpA2 were all associated with a hazard ratio of >25 for severe illness or death, additionally supporting their utility for identifying hvKp strains. Quantitative siderophore production of ≥30 μg/ml also strongly predicted strains as members of the hvKp-rich cohort (accuracy, 0.96) and exhibited a hazard ratio of 31.7 for severe illness or death. The string test, a widely used marker for hvKp strains, performed less well, achieving an accuracy of only 0.90. Last, using the most accurate biomarkers to define hvKp, prevalence studies were performed on two Western strain collections. These data strongly support the utility of several laboratory markers for identifying hvKp strains with a high degree of accuracy.

The global emergence of Klebsiella pneumoniae carbapenemase-producing K. pneumoniae (KPC-Kp) multilocus sequence type ST258 is widely recognized. Less is known about the molecular and epidemiological details of non-ST258 K. pneumoniae in the setting of an outbreak mediated by an endemic plasmid. We describe the interplay of blaKPC plasmids and K. pneumoniae strains and their relationship to the location of acquisition in a U.S. health care institution. Whole-genome sequencing (WGS) analysis was applied to KPC-Kp clinical isolates collected from a single institution over 5 years following the introduction of blaKPC in August 2007, as well as two plasmid transformants. KPC-Kp from 37 patients yielded 16 distinct sequence types (STs). Two novel conjugative blaKPC plasmids (pKPC_UVA01 and pKPC_UVA02), carried by the hospital index case, accounted for the presence of blaKPC in 21/37 (57%) subsequent cases. Thirteen (35%) isolates represented an emergent lineage, ST941, which contained pKPC_UVA01 in 5/13 (38%) and pKPC_UVA02 in 6/13 (46%) cases. Seven (19%) isolates were the epidemic KPC-Kp strain, ST258, mostly imported from elsewhere and not carrying pKPC_UVA01 or pKPC_UVA02. Using WGS-based analysis of clinical isolates and plasmid transformants, we demonstrate the unexpected dispersal of blaKPC to many non-ST258 lineages in a hospital through spread of at least two novel blaKPC plasmids. In contrast, ST258 KPC-Kp was imported into the institution on numerous occasions, with other blaKPC plasmid vectors and without sustained transmission. Instead, a newly recognized KPC-Kp strain, ST941, became associated with both novel blaKPC plasmids and spread locally, making it a future candidate for clinical persistence and dissemination.