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BackgroundReported bacteraemia outcomes following inactive empirical antibiotics (as judged by in vitro testing) are conflicting, potentially reflecting heterogeneous effects of species, minimum inhibitory concentration (MIC) breakpoints defining resistance/susceptibility, and times to rescue therapy.MethodsWe investigated adult inpatients with Escherichia coli bacteraemia at Oxford University Hospitals, UK, from 04-February-2014 to 30-June-2021 receiving empirical amoxicillin-clavulanate with/without other antibiotics. We analysed 30-day all-cause mortality from index blood culture using Cox models by in vitro amoxicillin-clavulanate susceptibility (activity) using the EUCAST resistance breakpoint (>8/2mg/L), categorical MIC, and a higher resistance breakpoint (>32/2mg/L), adjusting for other antibiotic activity and multiple confounders including comorbidities, vital signs, and blood tests.Results1720 E. coli bacteraemias (1626 patients) were treated with empirical amoxicillin-clavulanate. 30-day mortality was 193/1400 (14%) [any active baseline therapy] and 52/320 (16%) [inactive baseline therapy] (p=0.17). With EUCAST breakpoints, there was no evidence that mortality differed for inactive vs. active amoxicillin-clavulanate (adjusted HR, aHR=1.27 [95%CI 0.83-1.93;p=0.28]), nor of an association with other antibiotic activity (p>0.18). Considering categorical amoxicillin-clavulanate MIC, MICs>32/2 were associated with mortality (aHR=1.85 vs. MIC=2/2 [0.99-3.73;p=0.054]). Using the higher resistance breakpoint, MICs>32/2 were independently associated with higher mortality (aHR=1.82 [1.07-3.10;p=0.027]), as were MICs>32/2 with active baseline aminoglycoside (aHR=2.34 [1.40-3.89;p=0.001), but not MICs>32/2 with active baseline non-aminoglycoside antibiotic(s) (aHR=0.87 [0.40-1.89;p=0.72).ConclusionsEUCAST-defined amoxicillin-clavulanate resistance was not associated with increased mortality, but a higher resistance breakpoint was. Additional active baseline non-aminoglycoside antibiotics prevented amoxicillin-clavulanate resistance-associated mortality, but active baseline aminoglycosides did not. Granular phenotyping and comparison with clinical outcomes may improve AMR breakpoints.SummaryIn patients with E. coli bacteraemia, high-level resistance to baseline empirical amoxicillin-clavulanate (minimum inhibitory concentration >32/2 mg/L) was associated with increased 30-day mortality, which was not compensated for by single-dose aminoglycosides.

BackgroundAntimicrobial resistance (AMR) inE. coliis a global problem associated with substantial morbidity and mortality. AMR-associated genes are typically annotated based on similarity to a variants in a curated reference database with an implicit assumption that uncatalogued genetic variation within these is phenotypically unimportant. In this study we evaluated the potential for discovering new AMR-associated gene families and characterising variation within existing ones to improve genotype-to-susceptibility-phenotype prediction inE. coli.MethodsWe assembled a global dataset of 9001E. colisequences of which 8586 had linked antibiotic susceptibility data. Raw reads were assembled using Shovill and AMR genes extracted using the NCBI AMRFinder tool. Mash was used to calculate the similarity between extracted genes using Jaccard distances. We empirically reclustered extracted gene sequences into AMR-associated gene families (70% match) and alleles (ARGs, 100% match).ResultsThe performance of the AMRFinder database for genotype-to-phenotype predictions using strict 100% identity and coverage thresholds did not meet FDA thresholds for any of the eight antibiotics evaluated. Relaxing filters to default settings improved sensitivity with a specificity cost. For all antibiotics, a small number of genes explained most resistance although a proportion could not be explained by known ARGs; this ranged from 75.1% for co-amoxiclav to 3.4% for ciprofloxacin. Only 17,177/36,637 (47%) of ARGs detected had a 100% identity and coverage match in the AMRFinder database. After empirically reclassifying genes at 100% nucleotide sequence identity, we identified 1292 unique ARGs of which 158 (12%) were present ≥10 times, 374 (29%) were present 2-9 times and 760 (59%) only once. Simulated accumulation curves revealed that discovery of new (100%-match) ARGs present more than once in the dataset plateaued relatively quickly whereas new singleton ARGs were discovered even after many thousands of isolates had been included. We identified a strong correlation (Spearman coefficient 0.76 (95% CI 0.72-0.79, pblaTEM-1, we demonstrated that uncatalogued variation, including synonymous variation, is associated with potentially important phenotypic differences (e.g. two common, uncataloguedblaTEM-1alleles with only synonymous mutations compared to the known reference were associated with reduced resistance to co-amoxiclav [aOR 0.57, 95%CI 0.34-0.93, p=0.03] and piperacillin-tazobactam [aOR 0.54, 95%CI 0.32-0.87, p=0.01]).ConclusionsOverall we highlight substantial uncatalogued genetic variation with respect to known ARGs, although a relatively small proportion of these alleles are repeatedly observed in a large international dataset suggesting strong selection pressures. The current approach of using fuzzy matching for ARG detection, ignoring the unknown effects of uncatalogued variation, is unlikely to be acceptable for future clinical deployment. The association of synonymous mutations with potentially important phenotypic differences suggests that relying solely on amino acid-based gene detection to predict resistance is unlikely to be sufficient. Finally, the inability to explain all resistance using existing knowledge highlights the importance of new target gene discovery.

Population-representative estimates of SARS-CoV-2 infection prevalence and antibody levels in specific geographic areas at different time points are needed to optimise policy responses. However, even population-wide surveys are potentially impacted by biases arising from differences in participation rates across key groups. Here, we use spatio-temporal regression and post-stratification models to UK’s national COVID-19 Infection Survey (CIS) to obtain representative estimates of PCR positivity (6,496,052 tests) and antibody prevalence (1,941,333 tests) for different regions, ages and ethnicities (7-December-2020 to 4-May-2022). Not accounting for vaccination status through post-stratification led to small underestimation of PCR positivity, but more substantial overestimations of antibody levels in the population (up to 21%), particularly in groups with low vaccine uptake in the general population. There was marked variation in the relative contribution of different areas and age-groups to each wave. Future analyses of infectious disease surveys should take into account major drivers of outcomes of interest that may also influence participation, with vaccination being an important factor to consider.

The rise of antimicrobial resistance (AMR) is one of the greatest public health challenges, already causing up to 1.2 million deaths annually and rising. Current gold-standard antimicrobial susceptibility tests (ASTs) are low-throughput and can take up to 48 hours, with implications for patient care. We present advances towards a novel, rapid AST, based on the deep-learning of single-cell specific phenotypes directly associated with antimicrobial susceptibility inEscherichia coli. Our models can reliably (80% single-cell accuracy) classify untreated and treated susceptible cells, across a range of antibiotics and phenotypes - including phenotypes not visually distinct to a trained, human observer. Applying models trained on lab-reference susceptible strains to clinical isolates ofE. colitreated with ciprofloxacin, we demonstrate our models reveal significant (p

Following primary SARS-CoV-2 vaccination, understanding the relative extent of protection against SARS-CoV-2 infection from boosters or from breakthrough infections (i.e. infection in the context of previous vaccination) has important implications for vaccine policy. In this study, we investigated correlates of protection against Omicron BA.4/5 infections and anti-spike IgG antibody trajectories after a third/booster vaccination or breakthrough infection following second vaccination in 154,149 adults ≥18y from the United Kingdom general population. We found that higher anti-spike IgG antibody levels were associated with increased protection against Omicron BA.4/5 infection and that breakthrough infections were associated with higher levels of protection at any given antibody level than booster vaccinations. Breakthrough infections generated similar antibody levels to third/booster vaccinations, and the subsequent declines in antibody levels were similar to or slightly slower than those after third/booster vaccinations. Taken together our findings show that breakthrough infection provides longer lasting protection against further infections than booster vaccinations. For example, considering antibody levels associated with 67% protection against infection, a third/booster vaccination did not provide long-lasting protection, while a Delta/Omicron BA.1 breakthrough infection could provide 5-10 months of protection against Omicron BA.4/5 reinfection. 50-60% of the vaccinated UK population with a breakthrough infection would still be protected by the end of 2022, compared to

BackgroundMonitoring infection trends is vital to informing public health strategy. Detecting and quantifying changes in growth rates can inform policymakers’ rationale for implementing or continuing interventions aimed at reducing impact. Substantial changes in SARS-CoV-2 prevalence with emergence of variants provides opportunity to investigate different methods to do this.MethodsWe included PCR results from all participants in the UK’s COVID-19 Infection Survey between 1 August 2020-30 June 2022. Change-points for growth rates were identified using iterative sequential regression (ISR) and second derivatives of generalised additive models (GAMs).Consistency between methods and timeliness of detection were compared.FindingsOf 8,799,079 visits, 147,278 (1·7%) were PCR-positive. Over the time period, change-points associated with emergence of major variants were estimated to occur a median 4 days earlier (IQR 0-8) in GAMs versus ISR, with only 2/48 change-points identified by only one method. Estimating recent change-points using successive data periods, four change-points (4/96) identified by GAMs were not found when adding later data or by ISR; 77% (74/96) of change-points identified by successive GAMs were identified by ISR. Change-points were detected 3-5 weeks after they occurred in both methods but could be detected earlier within specific subgroups.InterpretationChange-points in growth rates of SARS-CoV-2 can be detected in near real-time using ISR and second derivatives of GAMs. To increase certainty about changes in epidemic trajectories both methods could be run in parallel. Running either method in near real-time on different infection surveillance data streams could provide timely warnings of changing underlying epidemiology.FundingUK Health Security Agency, Department of Health and Social Care (UK), Welsh Government, Department of Health (on behalf of the Northern Ireland Government), Scottish Government, National Institute for Health Research.

Plasmids are key vectors of bacterial antibiotic resistance, but understanding of risk factors associated with plasmid antibiotic resistance gene (ARG) carriage is limited. We curated >14000 publicly available plasmid genomes and associated metadata. Duplicate and replicate plasmids were excluded; where possible, sample metadata was validated externally (BacDive database). Using Logistic Generalised Additive Models (GAMs) we assessed the influence of biotic/abiotic risk factors (e.g. plasmid genetic factors, isolation source, collection date) on ARG carriage, modelled as a binary outcome. Separate GAMs were built for 10 major ARG types. Multivariable analysis indicated that plasmid ARG carriage patterns across time (collection years), isolation sources (human/livestock) and host bacterial taxa were consistent with antibiotic selection pressure as a driver of plasmid-mediated antibiotic resistance. Among livestock vs human plasmids, carbapenem resistance was infrequent (0.42% vs 12%), while tetracycline resistance was enriched (adjusted odds-ratio [OR]=2.65, 95% confidence interval [CI] 1.89–3.72), reflecting known prescribing practices. More recently acquired ARG types (e.g. colistin and carbapenem) showed increases in plasmid carriage during the date range analysed (1994–2019), potentially reflecting recent onset of selection pressure; they also co-occurred less commonly with ARGs of other types and virulence genes. Carbapenem resistance was more likely to reside on conjugative vs non-mobilisable plasmids (adjusted OR=3.59 95%CI 2.80–4.61), and on plasmids with a higher density of insertion sequences. Overall, this suggests that following acquisition, plasmid ARGs tend to accumulate under antibiotic selection pressure and co-associate with other adaptive genes (other ARG types, virulence genes), potentially re-enforcing plasmid ARG carriage through co-selection.

BackgroundThe SARS-CoV-2 Delta variant has been replaced by the highly transmissible Omicron BA.1 variant, and subsequently by Omicron BA.2. It is important to understand how these changes in dominant variants affect reported symptoms, while also accounting for symptoms arising from other co-circulating respiratory viruses.MethodsIn a nationally representative UK community study, the COVID-19 Infection Survey, we investigated symptoms in PCR-positive infection episodes vs. PCR-negative study visits over calendar time, by age and vaccination status, comparing periods when the Delta, Omicron BA.1 and BA.2 variants were dominant.ResultsBetween October-2020 and April-2022, 120,995 SARS-CoV-2 PCR-positive episodes occurred in 115,886 participants, with 70,683 (58%) reporting symptoms. The comparator comprised 4,766,366 PCR-negative study visits (483,894 participants); 203,422 (4%) reporting symptoms. Symptom reporting in PCR-positives varied over time, with a marked reduction in loss of taste/smell as Omicron BA.1 dominated, maintained with BA.2 (44%/45% 17 October 2021, 16%/13% 2 January 2022, 15%/12% 27 March 2022). Cough, fever, shortness of breath, myalgia, fatigue/weakness and headache also decreased after Omicron BA.1 dominated, but sore throat increased, the latter to a greater degree than concurrent increases in PCR-negatives. Fatigue/weakness increased again after BA.2 dominated, although to a similar degree to concurrent increases in PCR-negatives. Symptoms were consistently more common in adults aged 18-65 years than in children or older adults.ConclusionsIncreases in sore throat (also common in the general community), and a marked reduction in loss of taste/smell, make Omicron harder to detect with symptom-based testing algorithms, with implications for institutional and national testing policies.SummaryIn a UK community study, loss of taste/smell was markedly less commonly reported with Omicron BA.1/BA.2 than Delta SARS-CoV-2 infections, with smaller declines in reported shortness of breath, myalgia and fatigue/weakness, but increases in sore throat, challenging symptom-based testing algorithms.

Given high SARS-CoV-2 incidence, coupled with slow and inequitable vaccine roll-out in many settings, there is a need for evidence to underpin optimum vaccine deployment, aiming to maximise global population immunity. We evaluate whether a single vaccination in individuals who have already been infected with SARS-CoV-2 generates similar initial and subsequent antibody responses to two vaccinations in those without prior infection. We compared anti-spike IgG antibody responses after a single vaccination with ChAdOx1, BNT162b2, or mRNA-1273 SARS-CoV-2 vaccines in the COVID-19 Infection Survey in the UK general population. In 100,849 adults median (50 (IQR: 37–63) years) receiving at least one vaccination, 13,404 (13.3%) had serological/PCR evidence of prior infection. Prior infection significantly boosted antibody responses, producing higher peak levels and/or longer half-lives after one dose of all three vaccines than those without prior infection receiving one or two vaccinations. In those with prior infection, the median time above the positivity threshold was >1 year after the first vaccination. Single-dose vaccination targeted to those previously infected may provide at least as good protection to two-dose vaccination among those without previous infection.

2.AbstractComplete, accurate, cost-effective, and high-throughput reconstruction of bacterial genomes for large-scale genomic epidemiological studies is currently only possible with hybrid assembly, combining long- (typically using nanopore sequencing) and short-read (Illumina) datasets. Being able to utilise nanopore-only data would be a significant advance. Oxford Nanopore Technologies (ONT) have recently released a new flowcell (R10.4) and chemistry (Kit12), which reportedly generate per-read accuracies rivalling those of Illumina data. To evaluate this, we sequenced DNA extracts from four commonly studied bacterial pathogens, namely Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa and Staphylococcus aureus, using Illumina and ONT’s R9.4.1/Kit10, R10.3/Kit12, R10.4/Kit12 flowcells/chemistries. We compared raw read accuracy and assembly accuracy for each modality, considering the impact of different nanopore basecalling models, commonly used assemblers, sequencing depth, and the use of duplex versus simplex reads. “Super accuracy” (sup) basecalled R10.4 reads - in particular duplex reads - have high per-read accuracies and could be used to robustly reconstruct bacterial genomes without the use of Illumina data. However, the per-run yield of duplex reads generated in our hands with standard sequencing protocols was low (typically 3.Impact statementOur understanding of microbes has been greatly enhanced by the capacity to evaluate their genetic make-up using a technology known as whole genome sequencing. Sequencers represent microbial genomes as stretches of shorter sequence known as ‘reads’, which are then assembled using computational algorithms. Different types of sequencing approach have advantages and disadvantages with respect to the accuracy and length of the reads they generate; this in turn affects how reliably genomes can be assembled.Currently, to completely reconstruct bacterial genomes in a high-throughput and cost-effective manner, researchers tend to use two different types of sequencing data, namely Illumina (short-read) and nanopore (long-read) data. Illumina data are highly accurate; nanopore data are much longer, and this combination facilitates accurate and complete bacterial genomes in a so-called “hybrid assembly”. However, new developments in nanopore sequencing have reportedly greatly improved the accuracy of nanopore data, hinting at the possibility of requiring only a single sequencing approach for bacterial genomics.Here we evaluate these improvements in nanopore sequencing in the reconstruction of four bacterial reference strains, where the true sequence is already known. We show that although these improvements are extremely promising, for high-throughput, low-cost complete reconstruction of bacterial genomes hybrid assembly currently remains the optimal approach.4.Data summaryThe authors confirm all supporting data, code and protocols have been provided within the article, through supplementary data files, or in publicly accessible repositories.Nanopore fast5 and fastq data are available in the ENA under project accession: PRJEB51164.Assemblies have been made available at: https://figshare.com/articles/online_resource/q20_comparison_genome_assemblies/196838 67.Code and analysis outputs are available at: https://gitlab.com/ModernisingMedicalMicrobiology/assembly_comparison_analysis/-/tree/main (tagged version v0.5.5).

The antibiotic resistance crisis continues to threaten human health. Better predictions of the evolution of antibiotic resistance genes could contribute to the design of more sustainable treatment strategies. However, comprehensive prediction of antibiotic resistance gene evolution via laboratory approaches remains challenging. By combining site-specific integration and high-throughput sequencing, we quantified relative growth under the respective selection of cefotaxime or ceftazidime selection in ∼23,000 Escherichia coli MG1655 strains that each carried a unique, single-copy variant of the extended-spectrum β-lactamase gene blaCTX-M-14 at the chromosomal att HK022 site. Significant synergistic pleiotropy was observed within four subgenic regions, suggesting key regions for the evolution of resistance to both antibiotics. Moreover, we propose PEARP and PEARR, two deep-learning models with strong clinical correlations, for the prospective and retrospective prediction of blaCTX-M-14 evolution, respectively. Single to quintuple mutations of blaCTX-M-14 predicted to confer resistance by PEARP were significantly enriched among the clinical isolates harboring blaCTX-M-14 variants, and the PEARR scores matched the minimal inhibitory concentrations obtained for the 31 intermediates in all hypothetical trajectories. Altogether, we conclude that the measurement of local fitness landscape enables prediction of the evolutionary trajectories of antibiotic resistance genes, which could be useful for a broad range of clinical applications, from resistance prediction to designing novel treatment strategies.

A hospital outbreak of carbapenem-resistant Enterobacterales was detected by routine surveillance. Whole genome sequencing and subsequent analysis revealed a conserved promiscuous

Plasmids carry genes conferring antimicrobial resistance (AMR), and other clinically important traits; their ability to move within and between species may provide the machinery for rapid dissemination of such genes. Existing studies using complete plasmid assemblies, which are essential for reliable inference, have been small and/or limited to those carrying particularly antimicrobial resistance genes (ARGs). In this study, we sequenced 1,880 complete plasmids from 738 isolates from bloodstream infections (BSI) in 2009 (194 isolates) and 2018 (368 isolates) in Oxfordshire, UK, plus a stratified selection from intervening years (176 isolates). We demonstrate that plasmids are largely, but not entirely, constrained to host species, although there is substantial overlap between species of plasmid gene-repertoire. Most ARGs are carried by a relatively small number of plasmid groups with biological features that are predictable. Plasmids carrying ARGs (including those encoding carbapenemases) share a putative ‘backbone’ of core genes with those carrying no such genes. These findings suggest that future surveillance should, in addition to tracking plasmids currently associated with clinically important genes, focus on identifying and monitoring the dissemination of high-risk plasmid groups with the potential to rapidly acquire and disseminate these genes.

Objectives We systematically reviewed studies using wastewater for AMR surveillance in human populations, to determine: (i) evidence of concordance between wastewater-human AMR prevalence estimates, and (ii) methodological approaches which optimised identifying such an association, and which could be recommended as standard. We used Lin’s concordance correlation coefficient (CCC) to quantify concordance between AMR prevalence estimates in wastewater and human compartments (where CCC = 1 reflects perfect concordance), and logistic regression to identify study features (e.g. sampling methods) associated with high agreement studies (defined as >70% of within-study wastewater-human AMR prevalence comparisons within ±10%). Results Of 8,867 records and 441 full-text methods reviewed, 33 studies were included. AMR prevalence data was extractable from 24 studies conducting phenotypic-only (n = 7), genotypic-only (n = 1) or combined (n = 16) AMR detection. Overall concordance of wastewater-human AMR prevalence estimates was reasonably high for both phenotypic (CCC = 0.85 [95% CI 0.8–0.89]) and genotypic approaches (CCC = 0.88 (95% CI 0.84–0.9)) despite diverse study designs, bacterial species investigated and phenotypic/genotypic targets. No significant relationships between methodological approaches and high agreement studies were identified using logistic regression; however, this was limited by inconsistent reporting of study features, significant heterogeneity in approaches and limited sample size. Based on a secondary, descriptive synthesis, studies conducting composite sampling of wastewater influent, longitudinal sampling >12 months, and time-/location-matched sampling of wastewater and human compartments generally had higher agreement. Conclusion Wastewater-based surveillance of AMR appears promising, with high overall concordance between wastewater and human AMR prevalence estimates in studies irrespective of heterogenous approaches. However, our review suggests future work would benefit from: time-/location-matched sampling of wastewater and human populations, composite sampling of influent, and sampling >12 months for longitudinal studies. Further research and clear and consistent reporting of study methods is required to identify optimal practice.

Healthcare-associated infection, Principles of antimicrobial prescribing, Antimicrobial resistance

Genome sequencing is pivotal to SARS-CoV-2 surveillance, elucidating the emergence and global dissemination of acquired genetic mutations. Amplicon sequencing has proven very effective for sequencing SARS-CoV-2, but prevalent mutations disrupting primer binding sites have necessitated the revision of sequencing protocols in order to maintain performance for emerging virus lineages. We compared the performance of Oxford Nanopore Technologies (ONT) Midnight and ARTIC tiling amplicon protocols using 196 Delta lineage SARS-CoV-2 clinical specimens, and 71 mostly Omicron lineage samples with S gene target failure (SGTF), reflecting circulating lineages in the United Kingdom during December 2021. 96-plexed nanopore sequencing was used. For Delta lineage samples, ARTIC v4 recovered the greatest proportion of ≥90% complete genomes (81.1%; 159/193), followed by Midnight (71.5%; 138/193) and ARTIC v3 (34.1%; 14/41). Midnight protocol however yielded higher average genome recovery (mean 98.8%) than ARTIC v4 (98.1%) and ARTIC v3 (75.4%), resulting in less ambiguous final consensus assemblies overall. Explaining these observations were ARTIC v4’s superior genome recovery in low viral titre/high cycle threshold (Ct) samples and inferior performance in high titre/low Ct samples, where Midnight excelled. We evaluated Omicron sequencing performance using a revised Midnight primer mix alongside prototype ARTIC v4.1 primers, head-to-head with the existing commercially available Midnight and ARTIC v4 protocols. The revised protocols both improved considerably the recovery of Omicron genomes and exhibited similar overall performance to one another. Revised Midnight protocol recovered ≥90% complete genomes for 85.9% (61/71) of Omicron samples vs. 88.7% (63/71) for ARTIC v4.1. Approximate cost per sample for Midnight (£12) is lower than ARTIC (£16) while hands-on time is considerably lower for Midnight (∼7 hours) than ARTIC protocols (∼9.5 hours).

Background The COVID-19 pandemic is rapidly evolving, with emerging variants and fluctuating control policies. Real-time population screening and identification of groups in whom positivity is highest could help monitor spread and inform public health messaging and strategy. Methods To develop a real-time screening process, we included results from nose and throat swabs and questionnaires taken 19 July 2020-17 July 2021 in the UK's national COVID-19 Infection Survey. Fortnightly, associations between SARS-CoV-2 positivity and 60 demographic and behavioural characteristics were estimated using logistic regression models adjusted for potential confounders, considering multiple testing, collinearity, and reverse causality. Findings Of 4,091,537 RT-PCR results from 482,677 individuals, 29,903 (0·73%) were positive. As positivity rose September-November 2020, rates were independently higher in younger ages, and those living in Northern England, major urban conurbations, more deprived areas, and larger households. Rates were also higher in those returning from abroad, and working in healthcare or outside of home. When positivity peaked December 2020-January 2021 (Alpha), high positivity shifted to southern geographical regions. With national vaccine roll-out from December 2020, positivity reduced in vaccinated individuals. Associations attenuated as rates decreased between February-May 2021. Rising positivity rates in June-July 2021 (Delta) were independently higher in younger, male, and unvaccinated groups. Few factors were consistently associated with positivity. 25/45 (56%) confirmed associations would have been detected later using 28-day rather than 14-day periods. Interpretation Population-level demographic and behavioural surveillance can be a valuable tool in identifying the varying characteristics driving current SARS-CoV-2 positivity, allowing monitoring to inform public health policy. Funding Department of Health and Social Care (UK), Welsh Government, Department of Health (on behalf of the Northern Ireland Government), Scottish Government, National Institute for Health Research.

Given high SARS-CoV-2 incidence, coupled with slow and inequitable vaccine roll-out, there is an urgent need for evidence to underpin optimum vaccine deployment, aiming to maximise global population immunity at speed. We evaluate whether a single vaccination in previously infected individuals generates similar initial and subsequent antibody responses to two vaccinations in those without prior infection. We compared anti-spike IgG antibody responses after a single dose of ChAdOx1, BNT162b2, or mRNA-1273 SARS-CoV-2 vaccines in the COVID-19 Infection Survey in the UK general population. In 100,849 adults who received at least one vaccination, 13,404 (13.3%) had serological and/or PCR evidence of prior infection. Prior infection significantly boosted antibody responses for all three vaccines, producing a higher peak level and longer half-life, and a response comparable to those without prior infection receiving two vaccinations. In those with prior infection, median time above the positivity threshold was estimated to last for >1 year after the first dose. Single-dose vaccination targeted to those previously infected may provide protection in populations with high rates of previous infection faced with limited vaccine supply, as an interim measure while vaccine campaigns are scaled up.

BackgroundHealthcare-associated wastewater reservoirs and asymptomatic gastrointestinal patient colonisation by carbapenemase-producing Enterobacterales (CPE) can be important in nosocomial CPE dissemination and infection. We characterised these niches and within-niche diversity in a blaKPC-associated CPE (KPC-E) endemic healthcare setting, to better understand transmission potential.MethodsWe systematically sampled wastewater sites and patients across three units (six wards) over 6-12 months in 2016 in a KPC-E endemic hospital. We used Illumina sequencing to characterise up to five isolates per sample. Recombination-adjusted phylogenies were used to define genetically related strains; assembly and mapping-based typing approaches were used to characterise antimicrobial resistance gene and insertion sequence profiles, and Tn4401 types/target site sequences. The wider accessory genome was evaluated in a subset of the largest clusters, and those crossing niches.FindingsWastewater site KPC-E-positivity was substantial (101/349 sites [28.9%] positive, 319/4,488 [7.1%] sampling events positive); 183/4,425 (4.1%) of patients were CPE culture-positive over the same timeframe. 13 species and 109 KPC-E strains were observed across niches, and 24% of wastewater and 26% of patient KPC-E-positive samples harboured ≥1 strain. Most diversity was explained by the individual niche, suggesting highly localised factors are important in selection and spread. Tn4401+target site sequence (TSS) diversity was greater in wastewater sites (p4401-associated transposition/evolution and dissemination. Shower/bath and sluice/mop-associated sites were more likely to be KPC-E-positive (Adjusted Odds Ratio [95% CI]: 2.69 [1.44-5.01], p=0.0019 and 2.60 [1.04-6.52], p=0.0410, respectively). Different strains had different transmission and blaKPC dissemination dynamics.InterpretationThere may be substantial KPC-E colonisation of wastewater sites and patients in KPC-E-endemic healthcare settings. Niche-specific factors, and different strains with different transmission dynamics influence carbapenemase gene dissemination. New transmission models incorporating complex, multi-level dynamics are needed to better quantify CPE dissemination to inform interventions and reduce transmission.FundingThis study was supported by the National Institute for Health Research, UK.RESEARCH IN CONTEXTEvidence before this studyWe searched PubMed to identify previous studies using whole genome sequencing (WGS) to characterise in-hospital dissemination and persistence of carbapenemase-producing Enterobacterales (CPEs) or the presence of CPEs in hospital wastewater reservoirs. In our search (01/Jan/1996-30/Sep/2021) we used the terms ((((CPE) OR (KPC)) AND (healthcare-associated OR nosocomial OR hospital-associated)) AND (genom*) AND ((environment OR patient))). We had no restrictions on language. We found sixty-six studies, but these were limited by: (i) evaluating single species or lineages only (n=34), (ii) including patients or environmental outbreaks only, and not both (n=23), (iii) sampling only small numbers (nex vivo or in vivo evolution), two studies did not use WGS, and one study was not primary research.Added value of this studyWe provide a comprehensive assessment of healthcare-associated CPE dissemination and persistence in hospital wastewater reservoirs through systematic sampling of a large number of environmental sites (n=349 sites, n=4,488 samples) and patients (n=4,425) over 6-12 months in a single hospital. For all CPE-positive environmental samples (n=319) and a subset of CPE-positive patient samples (n=97/399 [24.3%] samples from 76/183 [41.5%] CPE-positive patients), we sampled up to five CPE isolates per sample to capture within-niche diversity, and used short-read Illumina WGS (n=1,732 isolates successfully sequenced) to characterise within-niche diversity, changes in colonisation over time, and genetic overlap between patient and environmental niches.Implications of all the available evidenceThrough a detailed and resource-intensive study we captured the dynamics of seeding and dissemination of important carbapenemase genes amongst patients and environmental reservoirs within a hospital. We found differential colonisation and dissemination dynamics for different species and lineages within and between niches. Improved approaches incorporating variable within-niche diversity, accessory distances and horizontal gene transfer in transmission evaluations are required to better understand CPE dissemination and persistence, in order to direct interventions limiting transmission.

The increasing frequency and magnitude of viral outbreaks in recent decades, epitomized by the COVID-19 pandemic, has resulted in an urgent need for rapid and sensitive diagnostic methods. Here, we present a methodology for virus detection and identification that uses a convolutional neural network to distinguish between microscopy images of fluorescently labeled intact particles of different viruses. Our assay achieves labeling, imaging, and virus identification in less than 5 min and does not require any lysis, purification, or amplification steps. The trained neural network was able to differentiate SARS-CoV-2 from negative clinical samples, as well as from other common respiratory pathogens such as influenza and seasonal human coronaviruses. We were also able to differentiate closely related strains of influenza, as well as SARS-CoV-2 variants. Additional and novel pathogens can easily be incorporated into the test through software updates, offering the potential to rapidly utilize the technology in future infectious disease outbreaks or pandemics. Single-particle imaging combined with deep learning therefore offers a promising alternative to traditional viral diagnostic and genomic sequencing methods and has the potential for significant impact.

Antibody responses are an important part of immunity after Coronavirus Disease 2019 (COVID-19) vaccination. However, antibody trajectories and the associated duration of protection after a second vaccine dose remain unclear. In this study, we investigated anti-spike IgG antibody responses and correlates of protection after second doses of ChAdOx1 or BNT162b2 vaccines for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the United Kingdom general population. In 222,493 individuals, we found significant boosting of anti-spike IgG by the second doses of both vaccines in all ages and using different dosing intervals, including the 3-week interval for BNT162b2. After second vaccination, BNT162b2 generated higher peak levels than ChAdOX1. Older individuals and males had lower peak levels with BNT162b2 but not ChAdOx1, whereas declines were similar across ages and sexes with ChAdOX1 or BNT162b2. Prior infection significantly increased antibody peak level and half-life with both vaccines. Anti-spike IgG levels were associated with protection from infection after vaccination and, to an even greater degree, after prior infection. At least 67% protection against infection was estimated to last for 2-3 months after two ChAdOx1 doses, for 5-8 months after two BNT162b2 doses in those without prior infection and for 1-2 years for those unvaccinated after natural infection. A third booster dose might be needed, prioritized to ChAdOx1 recipients and those more clinically vulnerable.

Background Gram-negative organisms are common causes of bloodstream infection (BSI) during the neonatal period and early childhood. Whilst several large studies have characterised these isolates in adults, equivalent data (particularly incorporating whole genome sequencing) is lacking in the paediatric population. Methods We perform an epidemiological and sequencing based analysis of Gram-negative bloodstream infections (327 isolates (296 successfully sequenced) from 287 patients) in children Results Here we show that the burden of infection lies predominantly in neonates and that most infections are caused by Escherichia coli, Klebsiella spp. and Enterobacter hormaechei. There is no evidence in our setting that the proportion of antimicrobial resistant isolates is increasing in the paediatric population although we identify some evidence of sub-breakpoint increases in gentamicin resistance. The population structure of E. coli BSI isolates in neonates and children mirrors that in adults with a predominance of STs 131/95/73/69 and the same proportions of O-antigen serotypes. In most cases in our setting there is no evidence of transmission/point-source acquisition and we demonstrate the utility of whole genome sequencing to refute a previously suspected outbreak. Conclusions Our findings support continued use of current empirical treatment guidelines and suggest that O-antigen targeted vaccines may have a role in reducing the incidence of neonatal sepsis.

Funder: Department of Health, Funder: Department of Health & Social Care, BackgroundInformation on SARS-CoV-2 in representative community surveillance is limited, particularly cycle threshold (Ct) values (a proxy for viral load).MethodsWe included all positive nose and throat swabs 26 April 2020 to 13 March 2021 from the UK's national COVID-19 Infection Survey, tested by RT-PCR for the N, S, and ORF1ab genes. We investigated predictors of median Ct value using quantile regression.ResultsOf 3,312,159 nose and throat swabs, 27,902 (0.83%) were RT-PCR-positive, 10,317 (37%), 11,012 (40%), and 6550 (23%) for 3, 2, or 1 of the N, S, and ORF1ab genes, respectively, with median Ct = 29.2 (~215 copies/ml; IQR Ct = 21.9-32.8, 14-56,400 copies/ml). Independent predictors of lower Cts (i.e. higher viral load) included self-reported symptoms and more genes detected, with at most small effects of sex, ethnicity, and age. Single-gene positives almost invariably had Ct > 30, but Cts varied widely in triple-gene positives, including without symptoms. Population-level Cts changed over time, with declining Ct preceding increasing SARS-CoV-2 positivity. Of 6189 participants with IgG S-antibody tests post-first RT-PCR-positive, 4808 (78%) were ever antibody-positive; Cts were significantly higher in those remaining antibody negative.ConclusionsMarked variation in community SARS-CoV-2 Ct values suggests that they could be a useful epidemiological early-warning indicator.FundingDepartment of Health and Social Care, National Institutes of Health Research, Huo Family Foundation, Medical Research Council UK; Wellcome Trust.

ObjectivesTo inform point-of-care test (POCT) development, we quantified the primary care demand for laboratory microbiology tests by describing their frequencies overall, frequencies of positives, most common organisms identified, temporal trends in testing and patterns of cotesting on the same and subsequent dates.DesignRetrospective cohort study.SettingPrimary care practices in Oxfordshire.Participants393 905 patients (65% female; 49% aged 18–49).Primary and secondary outcome measuresThe frequencies of all microbiology tests requested between 2008 and 2018 were quantified. Patterns of cotesting were investigated with heat maps. All analyses were done overall, by sex and age categories.Results1 596 752 microbiology tests were requested. Urine culture±microscopy was the most common of all tests (n=673 612, 42%), was mainly requested without other tests and was the most common test requested in follow-up within 7 and 14 days. Of all urine cultures, 180 047 (27%) were positive and 172 651 (26%) showed mixed growth, and Escherichia coli was the most prevalent organism (132 277, 73% of positive urine cultures). Antenatal urine cultures and blood tests in pregnancy (hepatitis B, HIV and syphilis) formed a common test combination, consistent with their use in antenatal screening.ConclusionsThe greatest burden of microbiology testing in primary care is attributable to urine culture ± microscopy; genital and routine antenatal urine and blood testing are also significant contributors. Further research should focus on the feasibility and impact of POCTs for these specimen types.

2.AbstractSeveral bioinformatics genotyping algorithms are now commonly used to characterise antimicrobial resistance (AMR) gene profiles in whole genome sequencing (WGS) data, with a view to understanding AMR epidemiology and developing resistance prediction workflows using WGS in clinical settings. Accurately evaluating AMR in Enterobacterales, particularly Escherichia coli, is of major importance, because this is a common pathogen. However, robust comparisons of different genotyping approaches on relevant simulated and large real-life WGS datasets are lacking. Here, we used both simulated datasets and a large set of real E. coli WGS data (n=1818 isolates) to systematically investigate genotyping methods in greater detail.Simulated constructs and real sequences were processed using four different bioinformatic programs (ABRicate, ARIBA, KmerResistance, and SRST2, run with the ResFinder database) and their outputs compared. For simulations tests where 3,092 AMR gene variants were inserted into random sequence constructs, KmerResistance was correct for all 3,092 simulations, ABRicate for 3,082 (99.7%), ARIBA for 2,927 (94.7%) and SRST2 for 2,120 (68.6%). For simulations tests where two closely related gene variants were inserted into random sequence constructs, ABRicate identified the correct alleles in 11,382/46,279 (25%) of simulations, ARIBA in 2494/46,279 (5%), SRST in 2539/46,279 (5%) and KmerResistance in 38,826/46,279 (84%). In real data, across all methods, 1392/1818 (76%) isolates had discrepant allele calls for at least one gene.Our evaluations revealed poor performance in scenarios that would be expected to be challenging (e.g. identification of AMR genes at 3.Impact statementWhole-genome sequencing is widely used for studying the epidemiology of antimicrobial resistance (AMR) genes in bacteria; however, there is some concern that outputs are highly dependent on the bioinformatics methods used. This work evaluates these concerns in detail by comparing four different, commonly used AMR gene typing methods using large simulated and real datasets. The results highlight performance issues for most methods in at least one of several simulated and real-life scenarios. However most discrepancies between methods were due to differential labelling of the same sequences related to the assumptions made regarding the underlying structure of the reference resistance gene database (i.e. that resistance genes can be easily classified in well-defined groups). This study represents a major advance in quantifying and evaluating the nature of discrepancies between outputs of different AMR typing algorithms, with relevance for historic and future work using these algorithms. Some of the discrepancies can be resolved by choosing methods with fewer assumptions about the reference AMR gene database and manually resolving outputs generated using multiple programs. However, ideally new and better methods are needed.1.5RepositoriesSequencing data are available at the following NCBI BioProject accession number: PRJNA540750.

BackgroundSerological tests are widely used in various medical disciplines for diagnostic and monitoring purposes. Unfortunately, the sensitivity and specificity of test systems are often poor, leaving room for false-positive and false-negative results. However, conventional methods were used to increase specificity and decrease sensitivity and vice versa. Using SARS-CoV-2 serology as an example, we propose here a novel testing strategy: the ‘sensitivity improved two-test’ or ‘SIT²’ algorithm.MethodsSIT² involves confirmatory retesting of samples with results falling in a predefined retesting zone of an initial screening test, with adjusted cut-offs to increase sensitivity. We verified and compared the performance of SIT² to single tests and orthogonal testing (OTA) in an Austrian cohort (1117 negative, 64 post-COVID-positive samples) and validated the algorithm in an independent British cohort (976 negatives and 536 positives).ResultsThe specificity of SIT² was superior to single tests and non-inferior to OTA. The sensitivity was maintained or even improved using SIT² when compared with single tests or OTA. SIT² allowed correct identification of infected individuals even when a live virus neutralisation assay could not detect antibodies. Compared with single testing or OTA, SIT² significantly reduced total test errors to 0.46% (0.24–0.65) or 1.60% (0.94–2.38) at both 5% or 20% seroprevalence.ConclusionFor SARS-CoV-2 serology, SIT² proved to be the best diagnostic choice at both 5% and 20% seroprevalence in all tested scenarios. It is an easy to apply algorithm and can potentially be helpful for the serology of other infectious diseases.