Potent cross-reactive antibodies following Omicron breakthrough in vaccinees.

Highly transmissible Omicron variants of SARS-CoV-2 currently dominate globally. Here, we compare neutralization of Omicron BA.1, BA.1.1, and BA.2. BA.2 RBD has slightly higher ACE2 affinity than BA.1 and slightly reduced neutralization by vaccine serum, possibly associated with its increased transmissibility. Neutralization differences between sub-lineages for mAbs (including therapeutics) mostly arise from variation in residues bordering the ACE2 binding site; however, more distant mutations S371F (BA.2) and R346K (BA.1.1) markedly reduce neutralization by therapeutic antibody Vir-S309. In-depth structure-and-function analyses of 27 potent RBD-binding mAbs isolated from vaccinated volunteers following breakthrough Omicron-BA.1 infection reveals that they are focused in two main clusters within the RBD, with potent right-shoulder antibodies showing increased prevalence. Selection and somatic maturation have optimized antibody potency in less-mutated epitopes and recovered potency in highly mutated epitopes. All 27 mAbs potently neutralize early pandemic strains, and many show broad reactivity with variants of concern.

Antibody escape of SARS-CoV-2 Omicron BA.4 and BA.5 from vaccine and BA.1 serum.

The Omicron lineage of SARS-CoV-2, which was first described in November 2021, spread rapidly to become globally dominant and has split into a number of sublineages. BA.1 dominated the initial wave but has been replaced by BA.2 in many countries. Recent sequencing from South Africa's Gauteng region uncovered two new sublineages, BA.4 and BA.5, which are taking over locally, driving a new wave. BA.4 and BA.5 contain identical spike sequences, and although closely related to BA.2, they contain further mutations in the receptor-binding domain of their spikes. Here, we study the neutralization of BA.4/5 using a range of vaccine and naturally immune serum and panels of monoclonal antibodies. BA.4/5 shows reduced neutralization by the serum from individuals vaccinated with triple doses of AstraZeneca or Pfizer vaccine compared with BA.1 and BA.2. Furthermore, using the serum from BA.1 vaccine breakthrough infections, there are, likewise, significant reductions in the neutralization of BA.4/5, raising the possibility of repeat Omicron infections.

Evidence of escape of SARS-CoV-2 variant B.1.351 from natural and vaccine-induced sera.

The race to produce vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began when the first sequence was published, and this forms the basis for vaccines currently deployed globally. Independent lineages of SARS-CoV-2 have recently been reported: UK, B.1.1.7; South Africa, B.1.351; and Brazil, P.1. These variants have multiple changes in the immunodominant spike protein that facilitates viral cell entry via the angiotensin-converting enzyme-2 (ACE2) receptor. Mutations in the receptor recognition site on the spike are of great concern for their potential for immune escape. Here, we describe a structure-function analysis of B.1.351 using a large cohort of convalescent and vaccinee serum samples. The receptor-binding domain mutations provide tighter ACE2 binding and widespread escape from monoclonal antibody neutralization largely driven by E484K, although K417N and N501Y act together against some important antibody classes. In a number of cases, it would appear that convalescent and some vaccine serum offers limited protection against this variant.

Reduced neutralization of SARS-CoV-2 B.1.1.7 variant by convalescent and vaccine sera.

SARS-CoV-2 has caused over 2 million deaths in little over a year. Vaccines are being deployed at scale, aiming to generate responses against the virus spike. The scale of the pandemic and error-prone virus replication is leading to the appearance of mutant viruses and potentially escape from antibody responses. Variant B.1.1.7, now dominant in the UK, with increased transmission, harbors 9 amino acid changes in the spike, including N501Y in the ACE2 interacting surface. We examine the ability of B.1.1.7 to evade antibody responses elicited by natural SARS-CoV-2 infection or vaccination. We map the impact of N501Y by structure/function analysis of a large panel of well-characterized monoclonal antibodies. B.1.1.7 is harder to neutralize than parental virus, compromising neutralization by some members of a major class of public antibodies through light-chain contacts with residue 501. However, widespread escape from monoclonal antibodies or antibody responses generated by natural infection or vaccination was not observed.

Antibody evasion by the P.1 strain of SARS-CoV-2.

Terminating the SARS-CoV-2 pandemic relies upon pan-global vaccination. Current vaccines elicit neutralizing antibody responses to the virus spike derived from early isolates. However, new strains have emerged with multiple mutations, including P.1 from Brazil, B.1.351 from South Africa, and B.1.1.7 from the UK (12, 10, and 9 changes in the spike, respectively). All have mutations in the ACE2 binding site, with P.1 and B.1.351 having a virtually identical triplet (E484K, K417N/T, and N501Y), which we show confer similar increased affinity for ACE2. We show that, surprisingly, P.1 is significantly less resistant to naturally acquired or vaccine-induced antibody responses than B.1.351, suggesting that changes outside the receptor-binding domain (RBD) impact neutralization. Monoclonal antibody (mAb) 222 neutralizes all three variants despite interacting with two of the ACE2-binding site mutations. We explain this through structural analysis and use the 222 light chain to largely restore neutralization potency to a major class of public antibodies.

Reduced neutralization of SARS-CoV-2 B.1.617 by vaccine and convalescent serum.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has undergone progressive change, with variants conferring advantage rapidly becoming dominant lineages, e.g., B.1.617. With apparent increased transmissibility, variant B.1.617.2 has contributed to the current wave of infection ravaging the Indian subcontinent and has been designated a variant of concern in the United Kingdom. Here we study the ability of monoclonal antibodies and convalescent and vaccine sera to neutralize B.1.617.1 and B.1.617.2, complement this with structural analyses of Fab/receptor binding domain (RBD) complexes, and map the antigenic space of current variants. Neutralization of both viruses is reduced compared with ancestral Wuhan-related strains, but there is no evidence of widespread antibody escape as seen with B.1.351. However, B.1.351 and P.1 sera showed markedly more reduction in neutralization of B.1.617.2, suggesting that individuals infected previously by these variants may be more susceptible to reinfection by B.1.617.2. This observation provides important new insights for immunization policy with future variant vaccines in non-immune populations.

Antibody Status and Incidence of SARS-CoV-2 Infection in Health Care Workers.

BACKGROUND: The relationship between the presence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the risk of subsequent reinfection remains unclear. METHODS: We investigated the incidence of SARS-CoV-2 infection confirmed by polymerase chain reaction (PCR) in seropositive and seronegative health care workers attending testing of asymptomatic and symptomatic staff at Oxford University Hospitals in the United Kingdom. Baseline antibody status was determined by anti-spike (primary analysis) and anti-nucleocapsid IgG assays, and staff members were followed for up to 31 weeks. We estimated the relative incidence of PCR-positive test results and new symptomatic infection according to antibody status, adjusting for age, participant-reported gender, and changes in incidence over time. RESULTS: A total of 12,541 health care workers participated and had anti-spike IgG measured; 11,364 were followed up after negative antibody results and 1265 after positive results, including 88 in whom seroconversion occurred during follow-up. A total of 223 anti-spike-seronegative health care workers had a positive PCR test (1.09 per 10,000 days at risk), 100 during screening while they were asymptomatic and 123 while symptomatic, whereas 2 anti-spike-seropositive health care workers had a positive PCR test (0.13 per 10,000 days at risk), and both workers were asymptomatic when tested (adjusted incidence rate ratio, 0.11; 95% confidence interval, 0.03 to 0.44; P = 0.002). There were no symptomatic infections in workers with anti-spike antibodies. Rate ratios were similar when the anti-nucleocapsid IgG assay was used alone or in combination with the anti-spike IgG assay to determine baseline status. CONCLUSIONS: The presence of anti-spike or anti-nucleocapsid IgG antibodies was associated with a substantially reduced risk of SARS-CoV-2 reinfection in the ensuing 6 months. (Funded by the U.K. Government Department of Health and Social Care and others.).

Hostile: accurate decontamination of microbial host sequences.

MOTIVATION: Microbial sequences generated from clinical samples are often contaminated with human host sequences that must be removed for ethical and legal reasons. Care must be taken to excise host sequences without inadvertently removing target microbial sequences to the detriment of downstream analyses such as variant calling and de novo assembly. RESULTS: To facilitate accurate host decontamination of both short and long sequencing reads, we developed Hostile, a tool capable of accurate host read removal using a laptop. We demonstrate that our approach removes at least 99.6% of real human reads and retains at least 99.989% of simulated bacterial reads. Using Hostile with a masked reference genome further increases bacterial read retention (≥99.997%) with negligible (≤0.001%) reduction in human read removal performance. Compared with an existing tool, Hostile removes 21%-23% more human short reads and 21-43 times fewer bacterial reads, typically in less time. AVAILABILITY AND IMPLEMENTATION: Hostile is implemented as an MIT-licensed Python package available from https://github.com/bede/hostile together with supplementary material.

High precision Neisseria gonorrhoeae variant and antimicrobial resistance calling from metagenomic Nanopore sequencing.

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.

Genomic Sequencing from Sputum for Tuberculosis Disease Diagnosis, Lineage Determination, and Drug Susceptibility Prediction.

Universal access to drug susceptibility testing for newly diagnosed tuberculosis patients is recommended. Access to culture-based diagnostics remains limited, and targeted molecular assays are vulnerable to emerging resistance mutations. Improved protocols for direct-from-sputum Mycobacterium tuberculosis sequencing would accelerate access to comprehensive drug susceptibility testing and molecular typing. We assessed a thermo-protection buffer-based direct-from-sample M. tuberculosis whole-genome sequencing protocol. We prospectively analyzed 60 acid-fast bacilli smear-positive clinical sputum samples in India and Madagascar. A diversity of semiquantitative smear positivity-level samples were included. Sequencing was performed using Illumina and MinION (monoplex and multiplex) technologies. We measured the impact of bacterial inoculum and sequencing platforms on genomic read depth, drug susceptibility prediction performance, and typing accuracy. M. tuberculosis was identified by direct sputum sequencing in 45/51 samples using Illumina, 34/38 were identified using MinION-monoplex sequencing, and 20/24 were identified using MinION-multiplex sequencing. The fraction of M. tuberculosis reads from MinION sequencing was lower than from Illumina, but monoplexing grade 3+ samples on MinION produced higher read depth than Illumina (P < 0.05) and MinION multiplexing (P < 0.01). No significant differences in sensitivity and specificity of drug susceptibility predictions were seen across sequencing modalities or within each technology when stratified by smear grade. Illumina sequencing from sputum accurately identified 1/8 (rifampin) and 6/12 (isoniazid) resistant samples, compared to 2/3 (rifampin) and 3/6 (isoniazid) accurately identified with Nanopore monoplex. Lineage agreement levels between direct and culture-based sequencing were 85% (MinION-monoplex), 88% (Illumina), and 100% (MinION-multiplex). M. tuberculosis direct-from-sample whole-genome sequencing remains challenging. Improved and affordable sample treatment protocols are needed prior to clinical deployment.

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.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infectivity by Viral Load, S Gene Variants and Demographic Factors, and the Utility of Lateral Flow Devices to Prevent Transmission.

BACKGROUND: How severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectivity varies with viral load is incompletely understood. Whether rapid point-of-care antigen lateral flow devices (LFDs) detect most potential transmission sources despite imperfect clinical sensitivity is unknown. METHODS: We combined SARS-CoV-2 testing and contact tracing data from England between 1 September 2020 and 28 February 2021. We used multivariable logistic regression to investigate relationships between polymerase chain reaction (PCR)-confirmed infection in contacts of community-diagnosed cases and index case viral load, S gene target failure (proxy for B.1.1.7 infection), demographics, SARS-CoV-2 incidence, social deprivation, and contact event type. We used LFD performance to simulate the proportion of cases with a PCR-positive contact expected to be detected using 1 of 4 LFDs. RESULTS: In total, 231 498/2 474 066 (9%) contacts of 1 064 004 index cases tested PCR-positive. PCR-positive results in contacts independently increased with higher case viral loads (lower cycle threshold [Ct] values), for example, 11.7% (95% confidence interval [CI] 11.5-12.0%) at Ct = 15 and 4.5% (95% CI 4.4-4.6%) at Ct = 30. B.1.1.7 infection increased PCR-positive results by ~50%, (eg, 1.55-fold, 95% CI 1.49-1.61, at Ct = 20). PCR-positive results were most common in household contacts (at Ct = 20.1, 8.7% [95% CI 8.6-8.9%]), followed by household visitors (7.1% [95% CI 6.8-7.3%]), contacts at events/activities (5.2% [95% CI 4.9-5.4%]), work/education (4.6% [95% CI 4.4-4.8%]), and least common after outdoor contact (2.9% [95% CI 2.3-3.8%]). Contacts of children were the least likely to test positive, particularly following contact outdoors or at work/education. The most and least sensitive LFDs would detect 89.5% (95% CI 89.4-89.6%) and 83.0% (95% CI 82.8-83.1%) of cases with PCR-positive contacts, respectively. CONCLUSIONS: SARS-CoV-2 infectivity varies by case viral load, contact event type, and age. Those with high viral loads are the most infectious. B.1.1.7 increased transmission by ~50%. The best performing LFDs detect most infectious cases.

Symptoms and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Positivity in the General Population in the United Kingdom.

BACKGROUND: "Classic" symptoms (cough, fever, loss of taste/smell) prompt severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) polymerase chain reaction (PCR) testing in the United Kingdom. Studies have assessed the ability of different symptoms to identify infection, but few have compared symptoms over time (reflecting variants) and by vaccination status. METHODS: Using the COVID-19 Infection Survey, sampling households across the United Kingdom, we compared symptoms in PCR-positives vs PCR-negatives, evaluating sensitivity of combinations of 12 symptoms (percentage symptomatic PCR-positives reporting specific symptoms) and tests per case (TPC) (PCR-positives or PCR-negatives reporting specific symptoms/ PCR-positives reporting specific symptoms). RESULTS: Between April 2020 and August 2021, 27 869 SARS-CoV-2 PCR-positive episodes occurred in 27 692 participants (median 42 years), of whom 13 427 (48%) self-reported symptoms ("symptomatic PCR-positives"). The comparator comprised 3 806 692 test-negative visits (457 215 participants); 130 612 (3%) self-reported symptoms ("symptomatic PCR-negatives"). Symptom reporting in PCR-positives varied by age, sex, and ethnicity, and over time, reflecting changes in prevalence of viral variants, incidental changes (eg, seasonal pathogens (with sore throat increasing in PCR-positives and PCR-negatives from April 2021), schools reopening) and vaccination rollout. After May 2021 when Delta emerged, headache and fever substantially increased in PCR-positives, but not PCR-negatives. Sensitivity of symptom-based detection increased from 74% using "classic" symptoms, to 81% adding fatigue/weakness, and 90% including all 8 additional symptoms. However, this increased TPC from 4.6 to 5.3 to 8.7. CONCLUSIONS: Expanded symptom combinations may provide modest benefits for sensitivity of PCR-based case detection, but this will vary between settings and over time, and increases tests/case. Large-scale changes to targeted PCR-testing approaches require careful evaluation given substantial resource and infrastructure implications.

Omicron-associated changes in SARS-CoV-2 symptoms in the United Kingdom.

BACKGROUND: The 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. METHODS: In 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. RESULTS: Between 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. CONCLUSIONS: Increases 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.

An Observational Cohort Study on the Incidence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection and B.1.1.7 Variant Infection in Healthcare Workers by Antibody and Vaccination Status.

BACKGROUND: Natural and vaccine-induced immunity will play a key role in controlling the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. SARS-CoV-2 variants have the potential to evade natural and vaccine-induced immunity. METHODS: In a longitudinal cohort study of healthcare workers (HCWs) in Oxfordshire, United Kingdom, we investigated the protection from symptomatic and asymptomatic polymerase chain reaction (PCR)-confirmed SARS-CoV-2 infection conferred by vaccination (Pfizer-BioNTech BNT162b2, Oxford-AstraZeneca ChAdOx1 nCOV-19) and prior infection (determined using anti-spike antibody status), using Poisson regression adjusted for age, sex, temporal changes in incidence and role. We estimated protection conferred after 1 versus 2 vaccinations and from infections with the B.1.1.7 variant identified using whole genome sequencing. RESULTS: In total, 13 109 HCWs participated; 8285 received the Pfizer-BioNTech vaccine (1407 two doses), and 2738 the Oxford-AstraZeneca vaccine (49 two doses). Compared to unvaccinated seronegative HCWs, natural immunity and 2 vaccination doses provided similar protection against symptomatic infection: no HCW vaccinated twice had symptomatic infection, and incidence was 98% lower in seropositive HCWs (adjusted incidence rate ratio 0.02 [95% confidence interval {CI} < .01-.18]). Two vaccine doses or seropositivity reduced the incidence of any PCR-positive result with or without symptoms by 90% (0.10 [95% CI .02-.38]) and 85% (0.15 [95% CI .08-.26]), respectively. Single-dose vaccination reduced the incidence of symptomatic infection by 67% (0.33 [95% CI .21-.52]) and any PCR-positive result by 64% (0.36 [95% CI .26-.50]). There was no evidence of differences in immunity induced by natural infection and vaccination for infections with S-gene target failure and B.1.1.7. CONCLUSIONS: Natural infection resulting in detectable anti-spike antibodies and 2 vaccine doses both provide robust protection against SARS-CoV-2 infection, including against the B.1.1.7 variant.

Clinical Metagenomic Sequencing for Species Identification and Antimicrobial Resistance Prediction in Orthopedic Device Infection.

Diagnosis of orthopedic device-related infection is challenging, and causative pathogens may be difficult to culture. Metagenomic sequencing can diagnose infections without culture, but attempts to detect antimicrobial resistance (AMR) determinants using metagenomic data have been less successful. Human DNA depletion may maximize the amount of microbial DNA sequence data available for analysis. Human DNA depletion by saponin was tested in 115 sonication fluid samples generated following revision arthroplasty surgery, comprising 67 where pathogens were detected by culture and 48 culture-negative samples. Metagenomic sequencing was performed on the Oxford Nanopore Technologies GridION platform. Filtering thresholds for detection of true species versus contamination or taxonomic misclassification were determined. Mobile and chromosomal genetic AMR determinants were identified in Staphylococcus aureus-positive samples. Of 114 samples generating sequence data, species-level positive percent agreement between metagenomic sequencing and culture was 50/65 (77%; 95% confidence interval [CI], 65 to 86%) and negative percent agreement was 103/114 (90%; 95% CI, 83 to 95%). Saponin treatment reduced the proportion of human bases sequenced in comparison to 5-µm filtration from a median (interquartile range [IQR]) of 98.1% (87.0% to 99.9%) to 11.9% (0.4% to 67.0%), improving reference genome coverage at a 10-fold depth from 18.7% (0.30% to 85.7%) to 84.3% (12.9% to 93.8%). Metagenomic sequencing predicted 13/15 (87%) resistant and 74/74 (100%) susceptible phenotypes where sufficient data were available for analysis. Metagenomic nanopore sequencing coupled with human DNA depletion has the potential to detect AMR in addition to species detection in orthopedic device-related infection. Further work is required to develop pathogen-agnostic human DNA depletion methods, improving AMR determinant detection and allowing its application to other infection types.

Mortality risks associated with empirical antibiotic activity in Escherichia coli bacteraemia: an analysis of electronic health records.

BACKGROUND: Reported bacteraemia outcomes following inactive empirical antibiotics (based on in vitro testing) are conflicting, potentially reflecting heterogeneity in causative species, MIC breakpoints defining resistance/susceptibility, and times to rescue therapy. METHODS: We investigated adult inpatients with Escherichia coli bacteraemia at Oxford University Hospitals, UK, from 4 February 2014 to 30 June 2021 who were receiving empirical amoxicillin/clavulanate with/without other antibiotics. We used Cox regression to analyse 30 day all-cause mortality by in vitro amoxicillin/clavulanate susceptibility (activity) using the EUCAST resistance breakpoint (>8/2 mg/L), categorical MIC, and a higher resistance breakpoint (>32/2 mg/L), adjusting for other antibiotic activity and confounders including comorbidities, vital signs and blood tests. RESULTS: A total of 1720 E. coli bacteraemias (1626 patients) were treated with empirical amoxicillin/clavulanate. Thirty-day mortality was 193/1400 (14%) for any active baseline therapy and 52/320 (16%) for inactive baseline therapy (P = 0.17). With EUCAST breakpoints, there was no evidence that mortality differed for inactive versus active amoxicillin/clavulanate [adjusted HR (aHR) = 1.27 (95% CI 0.83-1.93); P = 0.28], nor of an association with active aminoglycoside (P = 0.93) or other active antibiotics (P = 0.18). Considering categorical amoxicillin/clavulanate MIC, MICs > 32/2 mg/L were associated with mortality [aHR = 1.85 versus MIC = 2/2 mg/L (95% CI 0.99-3.73); P = 0.054]. A higher resistance breakpoint (>32/2 mg/L) was independently associated with higher mortality [aHR = 1.82 (95% CI 1.07-3.10); P = 0.027], as were MICs > 32/2 mg/L with active empirical aminoglycosides [aHR = 2.34 (95% CI 1.40-3.89); P = 0.001], but not MICs > 32/2 mg/L with active non-aminoglycoside antibiotic(s) [aHR = 0.87 (95% CI 0.40-1.89); P = 0.72]. CONCLUSIONS: We found no evidence that EUCAST-defined amoxicillin/clavulanate resistance was associated with increased mortality, but a higher resistance breakpoint (MIC > 32/2 mg/L) was. Additional active baseline non-aminoglycoside antibiotics attenuated amoxicillin/clavulanate resistance-associated mortality, but aminoglycosides did not. Granular phenotyping and comparison with clinical outcomes may improve AMR breakpoints.

NanoSPC: a scalable, portable, cloud compatible viral nanopore metagenomic data processing pipeline.

Metagenomic sequencing combined with Oxford Nanopore Technology has the potential to become a point-of-care test for infectious disease in public health and clinical settings, providing rapid diagnosis of infection, guiding individual patient management and treatment strategies, and informing infection prevention and control practices. However, publicly available, streamlined, and reproducible pipelines for analyzing Nanopore metagenomic sequencing data are still lacking. Here we introduce NanoSPC, a scalable, portable and cloud compatible pipeline for analyzing Nanopore sequencing data. NanoSPC can identify potentially pathogenic viruses and bacteria simultaneously to provide comprehensive characterization of individual samples. The pipeline can also detect single nucleotide variants and assemble high quality complete consensus genome sequences, permitting high-resolution inference of transmission. We implement NanoSPC using Nextflow manager within Docker images to allow reproducibility and portability of the analysis. Moreover, we deploy NanoSPC to our scalable pathogen pipeline platform, enabling elastic computing for high throughput Nanopore data on HPC cluster as well as multiple cloud platforms, such as Google Cloud, Amazon Elastic Computing Cloud, Microsoft Azure and OpenStack. Users could either access our web interface (https://nanospc.mmmoxford.uk) to run cloud-based analysis, monitor process, and visualize results, as well as download Docker images and run command line to analyse data locally.

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.

The Duration, Dynamics, and Determinants of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antibody Responses in Individual Healthcare Workers.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoglobulin G (IgG) antibody measurements can be used to estimate the proportion of a population exposed or infected and may be informative about the risk of future infection. Previous estimates of the duration of antibody responses vary. METHODS: We present 6 months of data from a longitudinal seroprevalence study of 3276 UK healthcare workers (HCWs). Serial measurements of SARS-CoV-2 anti-nucleocapsid and anti-spike IgG were obtained. Interval censored survival analysis was used to investigate the duration of detectable responses. Additionally, Bayesian mixed linear models were used to investigate anti-nucleocapsid waning. RESULTS: Anti-spike IgG levels remained stably detected after a positive result, for example, in 94% (95% credibility interval [CrI] 91-96%) of HCWs at 180 days. Anti-nucleocapsid IgG levels rose to a peak at 24 (95% CrI 19-31) days post first polymerase chain reaction (PCR)-positive test, before beginning to fall. Considering 452 anti-nucleocapsid seropositive HCWs over a median of 121 days from their maximum positive IgG titer, the mean estimated antibody half-life was 85 (95% CrI 81-90) days. Higher maximum observed anti-nucleocapsid titers were associated with longer estimated antibody half-lives. Increasing age, Asian ethnicity, and prior self-reported symptoms were independently associated with higher maximum anti-nucleocapsid levels and increasing age and a positive PCR test undertaken for symptoms with longer anti-nucleocapsid half-lives. CONCLUSIONS: SARS-CoV-2 anti-nucleocapsid antibodies wane within months and fall faster in younger adults and those without symptoms. However, anti-spike IgG remains stably detected. Ongoing longitudinal studies are required to track the long-term duration of antibody levels and their association with immunity to SARS-CoV-2 reinfection.