Evaluating the impact of genomic epidemiology of methicillin-resistant Staphylococcus aureus (MRSA) on hospital infection prevention and control decisions.

Genomic epidemiology enhances the ability to detect and refute methicillin-resistant Staphylococcus aureus (MRSA) outbreaks in healthcare settings, but its routine introduction requires further evidence of benefits for patients and resource utilization. We performed a 12 month prospective study at Cambridge University Hospitals NHS Foundation Trust in the UK to capture its impact on hospital infection prevention and control (IPC) decisions. MRSA-positive samples were identified via the hospital microbiology laboratory between November 2018 and November 2019. We included samples from in-patients, clinic out-patients, people reviewed in the Emergency Department and healthcare workers screened by Occupational Health. We sequenced the first MRSA isolate from 823 consecutive individuals, defined their pairwise genetic relatedness, and sought epidemiological links in the hospital and community. Genomic analysis of 823 MRSA isolates identified 72 genetic clusters of two or more isolates containing 339/823 (41 %) of the cases. Epidemiological links were identified between two or more cases for 190 (23 %) individuals in 34/72 clusters. Weekly genomic epidemiology updates were shared with the IPC team, culminating in 49 face-to-face meetings and 21 written communications. Seventeen clusters were identified that were consistent with hospital MRSA transmission, discussion of which led to additional IPC actions in 14 of these. Two outbreaks were also identified where transmission had occurred in the community prior to hospital presentation; these were escalated to relevant IPC teams. We identified 38 instances where two or more in-patients shared a ward location on overlapping dates but carried unrelated MRSA isolates (pseudo-outbreaks); research data led to de-escalation of investigations in six of these. Our findings provide further support for the routine use of genomic epidemiology to enhance and target IPC resources.

Benchmarking CRISPR-BP34 for point-of-care melioidosis detection in low-income and middle-income countries: a molecular diagnostics study.

BACKGROUND: Melioidosis is a neglected but often fatal tropical disease. The disease has broad clinical manifestations, which makes diagnosis challenging and time consuming. To improve diagnosis, we aimed to evaluate the performance of the CRISPR-Cas12a system (CRISPR-BP34) to detect Burkholderia pseudomallei DNA across clinical specimens from patients suspected to have melioidosis. METHODS: We conducted a prospective, observational cohort study of adult patients (aged ≥18 years) with melioidosis at Sunpasitthiprasong Hospital, a tertiary care hospital in Thailand. Participants were eligible for inclusion if they had culture-confirmed B pseudomallei infection from any clinical samples. Data were collected from patient clinical records and follow-up telephone calls. Routine clinical samples (blood, urine, respiratory secretion, pus, and other body fluids) were collected for culture. We documented time taken for diagnosis, and mortality at day 28 of follow-up. We also performed CRISPR-BP34 detection on clinical specimens collected from 330 patients with suspected melioidosis and compared its performance with the current gold-standard culture-based method. Discordant results were validated by three independent qualitative PCR tests. This study is registered with the Thai Clinical Trial Registry, TCTR20190322003. FINDINGS: Between Oct 1, 2019, and Dec 31, 2022, 876 patients with culture-confirmed melioidosis were admitted or referred to Sunpasitthiprasong Hospital, 433 of whom were alive at diagnosis and were enrolled in this study. Median time from sample collection to diagnosis by culture was 4·0 days (IQR 3·0-5·0) among all patients with known survival status at day 28, which resulted in delayed treatment. 199 (23%) of 876 patients died before diagnosis and 114 (26%) of 433 patients in follow-up were treated, but died within 28 days of admission. To test the CRISPR-BP34 assay, we enrolled and collected clinical samples from 114 patients with melioidosis and 216 patients without melioidosis between May 26 and Dec 31, 2022. Application of CRISPR-BP34 reduced the median sample-to-diagnosis time to 1·1 days (IQR 0·7-1·5) for blood samples, 2·3 h (IQR 2·3-2·4) for urine, and 3·3 h (3·1-3·4) for respiratory secretion, pus, and other body fluids. The overall sensitivity of CRISPR-BP34 was 93·0% (106 of 114 samples [95% CI 86·6-96·9]) compared with 66·7% (76 of 114 samples [57·2-75·2]) for culture. The overall specificity of CRISPR-BP34 was 96·8% (209 of 216 samples [95% CI 93·4-98·7]), compared with 100% (216 of 216 samples [98·3-100·0]) for culture. INTERPRETATION: The sensitivity, specificity, speed, and window of clinical intervention offered by CRISPR-BP34 support its prospective use as a point-of-care diagnostic tool for melioidosis. Future development should be focused on scalability and cost reduction. FUNDING: Chiang Mai University Thailand and Wellcome Trust UK.

Antibiotic resistance determination using Enterococcus faecium whole-genome sequences: a diagnostic accuracy study using genotypic and phenotypic data.

BACKGROUND: DNA sequencing could become an alternative to in vitro antibiotic susceptibility testing (AST) methods for determining antibiotic resistance by detecting genetic determinants associated with decreased antibiotic susceptibility. Here, we aimed to assess and improve the accuracy of antibiotic resistance determination from Enterococcus faecium genomes for diagnosis and surveillance purposes. METHODS: In this retrospective diagnostic accuracy study, we first conducted a literature search in PubMed on Jan 14, 2021, to compile a catalogue of genes and mutations predictive of antibiotic resistance in E faecium. We then evaluated the diagnostic accuracy of this database to determine susceptibility to 12 different, clinically relevant antibiotics using a diverse population of 4382 E faecium isolates with available whole-genome sequences and in vitro culture-based AST phenotypes. Isolates were obtained from various sources in 11 countries worldwide between 2000 and 2018. We included isolates tested with broth microdilution, Vitek 2, and disc diffusion, and antibiotics with at least 50 susceptible and 50 resistant isolates. Phenotypic resistance was derived from raw minimum inhibitory concentrations and measured inhibition diameters, and harmonised primarily using the breakpoints set by the European Committee on Antimicrobial Susceptibility Testing. A bioinformatics pipeline was developed to process raw sequencing reads, identify antibiotic resistance genetic determinants, and report genotypic resistance. We used our curated database, as well as ResFinder, AMRFinderPlus, and LRE-Finder, to assess the accuracy of genotypic predictions against phenotypic resistance. FINDINGS: We curated a catalogue of 228 genetic markers involved in resistance to 12 antibiotics in E faecium. Very accurate genotypic predictions were obtained for ampicillin (sensitivity 99·7% [95% CI 99·5-99·9] and specificity 97·9% [95·8-99·0]), ciprofloxacin (98·0% [96·4-98·9] and 98·8% [95·9-99·7]), vancomycin (98·8% [98·3-99·2] and 98·8% [98·0-99·3]), and linezolid resistance (after re-testing false negatives: 100·0% [90·8-100·0] and 98·3% [97·8-98·7]). High sensitivity was obtained for tetracycline (99·5% [99·1-99·7]), teicoplanin (98·9% [98·4-99·3]), and high-level resistance to aminoglycosides (97·7% [96·6-98·4] for streptomycin and 96·8% [95·8-97·5] for gentamicin), although at lower specificity (60-90%). Sensitivity was expectedly low for daptomycin (73·6% [65·1-80·6]) and tigecycline (38·3% [27·1-51·0]), for which the genetic basis of resistance is not fully characterised. Compared with other antibiotic resistance databases and bioinformatic tools, our curated database was similarly accurate at detecting resistance to ciprofloxacin and linezolid and high-level resistance to streptomycin and gentamicin, but had better sensitivity for detecting resistance to ampicillin, tigecycline, daptomycin, and quinupristin-dalfopristin, and better specificity for ampicillin, vancomycin, teicoplanin, and tetracycline resistance. In a validation dataset of 382 isolates, similar or improved diagnostic accuracies were also achieved. INTERPRETATION: To our knowledge, this work represents the largest published evaluation to date of the accuracy of antibiotic susceptibility predictions from E faecium genomes. The results and resources will facilitate the adoption of whole-genome sequencing as a tool for the diagnosis and surveillance of antimicrobial resistance in E faecium. A complete characterisation of the genetic basis of resistance to last-line antibiotics, and the mechanisms mediating antibiotic resistance silencing, are needed to close the remaining sensitivity and specificity gaps in genotypic predictions. FUNDING: Wellcome Trust, UK Department of Health, British Society for Antimicrobial Chemotherapy, Academy of Medical Sciences and the Health Foundation, Medical Research Council Newton Fund, Vietnamese Ministry of Science and Technology, and European Society of Clinical Microbiology and Infectious Disease.

Genomics for antimicrobial resistance surveillance to support infection prevention and control in health-care facilities.

Integration of genomic technologies into routine antimicrobial resistance (AMR) surveillance in health-care facilities has the potential to generate rapid, actionable information for patient management and inform infection prevention and control measures in near real time. However, substantial challenges limit the implementation of genomics for AMR surveillance in clinical settings. Through a workshop series and online consultation, international experts from across the AMR and pathogen genomics fields convened to review the evidence base underpinning the use of genomics for AMR surveillance in a range of settings. Here, we summarise the identified challenges and potential benefits of genomic AMR surveillance in health-care settings, and outline the recommendations of the working group to realise this potential. These recommendations include the definition of viable and cost-effective use cases for genomic AMR surveillance, strengthening training competencies (particularly in bioinformatics), and building capacity at local, national, and regional levels using hub and spoke models.

Genomics for public health and international surveillance of antimicrobial resistance.

Historically, epidemiological investigation and surveillance for bacterial antimicrobial resistance (AMR) has relied on low-resolution isolate-based phenotypic analyses undertaken at local and national reference laboratories. Genomic sequencing has the potential to provide a far more high-resolution picture of AMR evolution and transmission, and is already beginning to revolutionise how public health surveillance networks monitor and tackle bacterial AMR. However, the routine integration of genomics in surveillance pipelines still has considerable barriers to overcome. In 2022, a workshop series and online consultation brought together international experts in AMR and pathogen genomics to assess the status of genomic applications for AMR surveillance in a range of settings. Here we focus on discussions around the use of genomics for public health and international AMR surveillance, noting the potential advantages of, and barriers to, implementation, and proposing recommendations from the working group to help to drive the adoption of genomics in public health AMR surveillance. These recommendations include the need to build capacity for genome sequencing and analysis, harmonising and standardising surveillance systems, developing equitable data sharing and governance frameworks, and strengthening interactions and relationships among stakeholders at multiple levels.

Innovations in genomic antimicrobial resistance surveillance.

Whole-genome sequencing of antimicrobial-resistant pathogens is increasingly being used for antimicrobial resistance (AMR) surveillance, particularly in high-income countries. Innovations in genome sequencing and analysis technologies promise to revolutionise AMR surveillance and epidemiology; however, routine adoption of these technologies is challenging, particularly in low-income and middle-income countries. As part of a wider series of workshops and online consultations, a group of experts in AMR pathogen genomics and computational tool development conducted a situational analysis, identifying the following under-used innovations in genomic AMR surveillance: clinical metagenomics, environmental metagenomics, gene or plasmid tracking, and machine learning. The group recommended developing cost-effective use cases for each approach and mapping data outputs to clinical outcomes of interest to justify additional investment in capacity, training, and staff required to implement these technologies. Harmonisation and standardisation of methods, and the creation of equitable data sharing and governance frameworks, will facilitate successful implementation of these innovations.

Evidence review and recommendations for the implementation of genomics for antimicrobial resistance surveillance: reports from an international expert group.

Nearly a century after the beginning of the antibiotic era, which has been associated with unparalleled improvements in human health and reductions in mortality associated with infection, the dwindling pipeline for new antibiotic classes coupled with the inevitable spread of antimicrobial resistance (AMR) poses a major global challenge. Historically, surveillance of bacteria with AMR typically relied on phenotypic analysis of isolates taken from infected individuals, which provides only a low-resolution view of the epidemiology behind an individual infection or wider outbreak. Recent years have seen increasing adoption of powerful new genomic technologies with the potential to revolutionise AMR surveillance by providing a high-resolution picture of the AMR profile of the bacteria causing infections and providing real-time actionable information for treating and preventing infection. However, many barriers remain to be overcome before genomic technologies can be adopted as a standard part of routine AMR surveillance around the world. Accordingly, the Surveillance and Epidemiology of Drug-resistant Infections Consortium convened an expert working group to assess the benefits and challenges of using genomics for AMR surveillance. In this Series, we detail these discussions and provide recommendations from the working group that can help to realise the massive potential benefits for genomics in surveillance of AMR.

Exploiting genomics for antimicrobial resistance surveillance at One Health interfaces.

The intersection of human, animal, and ecosystem health at One Health interfaces is recognised as being of key importance in the evolution and spread of antimicrobial resistance (AMR) and represents an important, and yet rarely realised opportunity to undertake vital AMR surveillance. A working group of international experts in pathogen genomics, AMR, and One Health convened to take part in a workshop series and online consultation focused on the opportunities and challenges facing genomic AMR surveillance in a range of settings. Here we outline the working group's discussion of the potential utility, advantages of, and barriers to, the implementation of genomic AMR surveillance at One Health interfaces and propose a series of recommendations for addressing these challenges. Embedding AMR surveillance at One Health interfaces will require the development of clear beneficial use cases, especially in low-income and middle-income countries. Evidence of directionality, risks to human and animal health, and potential trade implications were also identified by the working group as key issues. Addressing these challenges will be vital to enable genomic surveillance technology to reach its full potential for assessing the risk of transmission of AMR between the environment, animals, and humans at One Health interfaces.

BurkHostGEN: a study protocol for evaluating variations in the Burkholderia pseudomallei and host genomes associated with melioidosis infection.

Background: Melioidosis is a frequently fatal disease caused by an environmental bacterium Burkholderia pseudomallei. The disease is prevalent in northeast Thailand, particularly among rice field farmers who are at risk of bacterial exposure through contact with contaminated soil and water. However, not all exposure results in disease, and infection can manifest diverse outcomes. We postulate that genetic factors, whether from the bacterium, the host or the combination of both, may influence disease outcomes. To address this hypothesis, we aim to collect, sequence, and analyse genetic data from melioidosis patients and controls, along with isolates of B. pseudomallei obtained from patients. Additionally, we will study the metagenomics of the household water supply for both patients and controls, including the presence of B. pseudomallei. Methods: BurkHostGEN is an ongoing observational study being conducted at Sunpasitthiprasong Hospital, Ubon Ratchathani, Thailand. We are obtaining consent from 600 melioidosis patients and 700 controls, spanning both sexes, to collect 1 mL of blood for host DNA analysis, 3 mL of blood for RNA analysis, as well as 5 L of household water supply for metagenomic analysis. Additionally, we are isolating B. pseudomallei from the melioidosis patients to obtain bacterial DNA. This comprehensive approach will allow us to identify B. pseudomallei and their paired host genetic factors associated with disease acquisition and severity. Ethical approvals have been obtained for BurkHostGEN. Host and bacterial genetic data will be uploaded to European Genome-Phenome Archive (EGA) and European Nucleotide Archive (ENA), respectively. Conclusions: BurkHostGEN holds the potential to discover bacterial and host genetic factors associated with melioidosis infection and severity of illness. It can also support various study designs, including biomarker validation, disease pathogenesis, and epidemiological analysis not only for melioidosis but also for other infectious diseases.

Placental Streptococcus agalactiae DNA is associated with neonatal unit admission and foetal pro-inflammatory cytokines in term infants.

Streptococcus agalactiae (Group B Streptococcus; GBS) is a common cause of sepsis in neonates. Previous work detected GBS DNA in the placenta in ~5% of women before the onset of labour, but the clinical significance of this finding is unknown. Here we re-analysed this dataset as a case control study of neonatal unit (NNU) admission. Of 436 infants born at term (≥37 weeks of gestation), 7/30 with placental GBS and 34/406 without placental GBS were admitted to the NNU (odds ratio (OR) 3.3, 95% confidence interval (CI) 1.3-7.8). We then performed a validation study using non-overlapping subjects from the same cohort. This included a further 239 cases of term NNU admission and 686 term controls: 16/36 with placental GBS and 223/889 without GBS were admitted to the NNU (OR 2.4, 95% CI 1.2-4.6). Of the 36 infants with placental GBS, 10 were admitted to the NNU with evidence of probable but culture-negative sepsis (OR 4.8, 95% CI 2.2-10.3), 2 were admitted with proven GBS sepsis (OR 66.6, 95% CI 7.3-963.7), 6 were admitted and had chorioamnionitis (inflammation of the foetal membranes) (OR 5.3, 95% CI 2.0-13.4), and 5 were admitted and had funisitis (inflammation of the umbilical cord) (OR 6.7, 95% CI 12.5-17.7). Foetal cytokine storm (two or more pro-inflammatory cytokines >10 times median control levels in umbilical cord blood) was present in 36% of infants with placental GBS DNA and 4% of cases where the placenta was negative (OR 14.2, 95% CI 3.6-60.8). Overall, ~1 in 200 term births had GBS detected in the placenta, which was associated with infant NNU admission and morbidity.

Optimization of high-throughput 16S rRNA gene amplicon sequencing: an assessment of PCR pooling, mastermix use and contamination.

16S rRNA gene sequencing is widely used to characterize human and environmental microbiomes. Sequencing at scale facilitates better powered studies but is limited by cost and time. We identified two areas in our 16S rRNA gene library preparation protocol where modifications could provide efficiency gains, including (1) pooling of multiple PCR amplifications per sample to reduce PCR drift and (2) manual preparation of mastermix to reduce liquid handling. Using nasal samples from healthy human participants and a serially diluted mock microbial community, we compared alpha and beta diversity, and compositional abundance where the PCR amplification was conducted in triplicate, duplicate or as a single reaction, and where manually prepared or premixed mastermix was used. One hundred and fifty-eight 16S rRNA gene sequencing libraries were prepared, including a replicate experiment. Comparing PCR pooling strategies, we found no significant difference in high-quality read counts and alpha diversity, and beta diversity by Bray-Curtis index clustered by replicate on principal coordinate analysis (PCoA) and non-metric dimensional scaling (NMDS) analysis. Choice of mastermix had no significant impact on high-quality read and alpha diversity, and beta diversity by Bray-Curtis index clustered by replicate in PCoA and NMDS analysis. Importantly, we observed contamination and variability of rare species (<0.01 %) across replicate experiments; the majority of contaminants were accounted for by removal of species present at <0.1 %, or were linked to reagents (including a primer stock). We demonstrate no requirement for pooling of PCR amplifications or manual preparation of PCR mastermix, resulting in a more efficient 16S rRNA gene PCR protocol.

Applications to medical and surgical specialist training in the UK National Health Service, 2021-2022: a cross-sectional observational study to characterise the diversity of successful applicants.

OBJECTIVES: To compare success of applicants to specialty training posts in the UK by gender, ethnicity and disability status. DESIGN: Cross-sectional observational study. SETTING: National Health Service, UK. PARTICIPANTS: All specialty training post applications to Health Education England, UK, during the 2021-2022 recruitment cycle. INTERVENTION: Nil. PRIMARY AND SECONDARY OUTCOME MEASURES: Comparison of success at application to specialty training posts by gender, ethnicity, country of qualification (UK vs non-UK) and disability. The influence of ethnicity on success was investigated using a logistic regression model, where country of qualification was included as a covariate. RESULTS: 12 419/37 971 (32.7%) of applicants to specialty training posts were successful, representing 58 specialties. The difference in percentage of successful females (6480/17 523, 37.0%) and males (5625/19 340, 29.1%) was 7.9% (95% CI 6.93% to 8.86%), in favour of females. Segregation of applications to specialties by gender was observed; surgical specialties had the highest proportion of male applicants, while obstetrics and gynaecology had the highest proportion of female applicants. The proportion of successful recruits to specialties largely reflected the number of applications. 11/15 minority ethnic groups (excluding 'not stated') had significantly lower adjusted ORs for success compared with white-British applicants. 'Mixed white and black African' (OR 0.52, 95% CI 0.44 to 0.61, p≤0.001) were the least successful minority group in our study, while non-UK graduates had an adjusted ORs for success of 0.43 (95% CI 0.41 to 0.46, p≤0.001) compared with UK graduates. The difference in percentage of success by disabled applicants (179/464, 38.6%) and non-disabled applicants (11 940/36 418, 32.8%) was 5.79% (95% CI 1.23% to 10.4%), in favour of disabled applicants. No disabled applicants were accepted to 21/58 (36.2%) of specialties. CONCLUSIONS: Despite greater success by female applicants overall, there is an attraction issue to specialties by gender. Further, most ethnic minority groups are less successful at application when compared with white-British applicants. This requires continuous monitoring and evaluation of the reasons behind observed differences. TRIAL REGISTRATION: Not applicable.

Dissemination of carbapenemase-producing Enterobacterales in Ireland from 2012 to 2017: a retrospective genomic surveillance study.

The spread of carbapenemase-producing Enterobacterales (CPE) is of major public health concern. The transmission dynamics of CPE in hospitals, particularly at the national level, are not well understood. Here, we describe a retrospective nationwide genomic surveillance study of CPE in Ireland between 2012 and 2017. We sequenced 746 national surveillance CPE samples obtained between 2012 and 2017. After clustering the sequences, we used thresholds based on pairwise SNPs, and reported within-host diversity along with epidemiological data to infer recent putative transmissions. All clusters in circulating clones, derived from high-resolution phylogenies, of a species (Klebsiella pneumoniae, Escherichia coli, Klebsiella oxytoca, Enterobacter cloacae, Enterobacter hormaechei and Citrobacter freundii) were individually examined for evidence of transmission. Antimicrobial resistance trends over time were also assessed. We identified 352 putative transmission events in six species including widespread and frequent transmissions in three species. We detected putative outbreaks in 4/6 species with three hospitals experiencing prolonged outbreaks. The bla OXA-48 gene was the main cause of carbapenem resistance in Ireland in almost all species. An expansion in the number of sequence types carrying bla OXA-48 was an additional cause of the increasing prevalence of carbapenemase-producing K. pneumoniae and E. coli.

How public health authorities can use pathogen genomics in health protection practice: a consensus-building Delphi study conducted in the United Kingdom.

Pathogen sequencing guided understanding of SARS-CoV-2 evolution during the COVID-19 pandemic. Many health systems developed pathogen genomics services to monitor SARS-CoV-2. There are no agreed guidelines about how pathogen genomic information should be used in public health practice. We undertook a modified Delphi study in three rounds to develop expert consensus statements about how genomic information should be used. Our aim was to inform health protection policy, planning and practice. Participants were from organisations that produced or used pathogen genomics information in the United Kingdom. The first round posed questions derived from a rapid literature review. Responses informed statements for the subsequent rounds. Consensus was accepted when 70 % or more of the responses were strongly agree/agree, or 70 % were disagree/strongly disagree on the five-point Likert scale. Consensus was achieved in 26 (96 %) of 27 statements. We grouped the statements into six categories: monitoring the emergence of new variants; understanding the epidemiological context of genomic data; using genomic data in outbreak risk assessment and risk management; prioritising the use of limited sequencing capacity; sequencing service performance; and sequencing service capability. The expert consensus statements will help guide public health authorities and policymakers to integrate pathogen genomics in health protection practice.

A systematic review of economic evaluations of whole-genome sequencing for the surveillance of bacterial pathogens.

Whole-genome sequencing (WGS) has unparalleled ability to distinguish between bacteria, with many public health applications. The generation and analysis of WGS data require significant financial investment. We describe a systematic review summarizing economic analyses of genomic surveillance of bacterial pathogens, reviewing the evidence for economic viability. The protocol was registered on PROSPERO (CRD42021289030). Six databases were searched on 8 November 2021 using terms related to 'WGS', 'population surveillance' and 'economic analysis'. Quality was assessed with the Drummond-Jefferson checklist. Following data extraction, a narrative synthesis approach was taken. Six hundred and eighty-one articles were identified, of which 49 proceeded to full-text screening, with 9 selected for inclusion. All had been published since 2019. Heterogeneity was high. Five studies assessed WGS for hospital surveillance and four analysed foodborne pathogens. Four were cost-benefit analyses, one was a cost-utility analysis, one was a cost-effectiveness analysis, one was a combined cost-effectiveness and cost-utility analysis, one combined cost-effectiveness and cost-benefit analyses and one was a partial analysis. All studies supported the use of WGS as a surveillance tool on economic grounds. The available evidence supports the use of WGS for pathogen surveillance but is limited by marked heterogeneity. Further work should include analysis relevant to low- and middle-income countries and should use real-world effectiveness data.

SARS-CoV-2 variant biology: immune escape, transmission and fitness.

In late 2020, after circulating for almost a year in the human population, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exhibited a major step change in its adaptation to humans. These highly mutated forms of SARS-CoV-2 had enhanced rates of transmission relative to previous variants and were termed 'variants of concern' (VOCs). Designated Alpha, Beta, Gamma, Delta and Omicron, the VOCs emerged independently from one another, and in turn each rapidly became dominant, regionally or globally, outcompeting previous variants. The success of each VOC relative to the previously dominant variant was enabled by altered intrinsic functional properties of the virus and, to various degrees, changes to virus antigenicity conferring the ability to evade a primed immune response. The increased virus fitness associated with VOCs is the result of a complex interplay of virus biology in the context of changing human immunity due to both vaccination and prior infection. In this Review, we summarize the literature on the relative transmissibility and antigenicity of SARS-CoV-2 variants, the role of mutations at the furin spike cleavage site and of non-spike proteins, the potential importance of recombination to virus success, and SARS-CoV-2 evolution in the context of T cells, innate immunity and population immunity. SARS-CoV-2 shows a complicated relationship among virus antigenicity, transmission and virulence, which has unpredictable implications for the future trajectory and disease burden of COVID-19.

SARS-CoV-2 variant evasion of monoclonal antibodies based on in vitro studies.

Monoclonal antibodies (mAbs) offer a treatment option for individuals with severe COVID-19 and are especially important in high-risk individuals where vaccination is not an option. Given the importance of understanding the evolution of resistance to mAbs by SARS-CoV-2, we reviewed the available in vitro neutralization data for mAbs against live variants and viral constructs containing spike mutations of interest. Unfortunately, evasion of mAb-induced protection is being reported with new SARS-CoV-2 variants. The magnitude of neutralization reduction varied greatly among mAb-variant pairs. For example, sotrovimab retained its neutralization capacity against Omicron BA.1 but showed reduced efficacy against BA.2, BA.4 and BA.5, and BA.2.12.1. At present, only bebtelovimab has been reported to retain its efficacy against all SARS-CoV-2 variants considered here. Resistance to mAb neutralization was dominated by the action of epitope single amino acid substitutions in the spike protein. Although not all observed epitope mutations result in increased mAb evasion, amino acid substitutions at non-epitope positions and combinations of mutations also contribute to evasion of neutralization. This Review highlights the implications for the rational design of viral genomic surveillance and factors to consider for the development of novel mAb therapies.

Characteristics of Staphylococcus aureus Isolated from Patients in Busia County Referral Hospital, Kenya.

Staphylococcus aureus is an important pathogen associated with hospital, community, and livestock-acquired infections, with the ability to develop resistance to antibiotics. Nasal carriage by hospital inpatients is a risk for opportunistic infections. Antibiotic susceptibility patterns, virulence genes and genetic population structure of S. aureus nasal isolates, from inpatients at Busia County Referral Hospital (BCRH) were analyzed. A total of 263 inpatients were randomly sampled, from May to July 2015. The majority of inpatients (85.9%) were treated empirically with antimicrobials, including ceftriaxone (65.8%) and metronidazole (49.8%). Thirty S. aureus isolates were cultured from 29 inpatients with a prevalence of 11% (10.3% methicillin-susceptible S. aureus (MSSA), 0.8% methicillin resistant S. aureus (MRSA)). Phenotypic and genotypic resistance was highest to penicillin-G (96.8%), trimethoprim (73.3%), and tetracycline (13.3%) with 20% of isolates classified as multidrug resistant. Virulence genes, Panton-Valentine leukocidin (pvl), toxic shock syndrome toxin-1 (tsst-1), and sasX gene were detected in 16.7%, 23.3% and 3.3% of isolates. Phylogenetic analysis showed 4 predominant clonal complexes CC152, CC8, CC80, and CC508. This study has identified that inpatients of BCRH were carriers of S. aureus harbouring virulence genes and resistance to a range of antibiotics. This may indicate a public health risk to other patients and the community.

Multi-Drug Resistant Staphylococcus aureus Carriage in Abattoir Workers in Busia, Kenya.

Abattoir workers have been identified as high-risk for livestock-associated Staphylococcus aureus carriage. This study investigated S. aureus carriage in abattoir workers in Western Kenya. Nasal swabs were collected once from participants between February-November 2012. S. aureus was isolated using bacterial culture and antibiotic susceptibility testing performed using the VITEK 2 instrument and disc diffusion methods. Isolates underwent whole genome sequencing and Multi Locus Sequence Types were derived from these data. S. aureus (n = 126) was isolated from 118/737 (16.0%) participants. Carriage was higher in HIV-positive (24/89, 27.0%) than HIV−negative participants (94/648, 14.5%; p = 0.003). There were 23 sequence types (STs) identified, and half of the isolates were ST152 (34.1%) or ST8 (15.1%). Many isolates carried the Panton-Valentine leucocidin toxin gene (42.9%). Only three isolates were methicillin resistant S. aureus (MRSA) (3/126, 2.4%) and the prevalence of MRSA carriage was 0.4% (3/737). All MRSA were ST88. Isolates from HIV-positive participants (37.0%) were more frequently resistant to sulfamethoxazole/trimethoprim compared to isolates from HIV-negative participants (6.1%; p < 0.001). Similarly, trimethoprim resistance genes were more frequently detected in isolates from HIV-positive (81.5%) compared to HIV-negative participants (60.6%; p = 0.044). S. aureus in abattoir workers were representative of major sequence types in Africa, with a high proportion being toxigenic isolates. HIV-positive individuals were more frequently colonized by antimicrobial resistant S. aureus which may be explained by prophylactic antimicrobial use.

Large-Scale Evaluation of a Rapid Fully Automated Analysis Platform to Detect and Refute Outbreaks Based on MRSA Genome Comparisons.

Genomic epidemiology of methicillin-resistant Staphylococcus aureus (MRSA) could transform outbreak investigations, but its clinical introduction is hampered by the lack of automated data analysis tools to rapidly and accurately define transmission based on sequence relatedness. We aimed to evaluate a fully automated bioinformatics system for MRSA genome analysis versus a bespoke researcher-led manual informatics pipeline. We analyzed 781 MRSA genomes from 777 consecutive patients identified over a 9-month period in a clinical microbiology laboratory in the United Kingdom. Outputs were bacterial species identification, detection of mec genes, assignment to sequence types (STs), identification of pairwise relatedness using a definition of ≤25 single nucleotide polymorphisms (SNPs) apart, and use of genetic relatedness to identify clusters. There was full concordance between the two analysis methods for species identification, detection of mec genes, and ST assignment. A total of 3,311 isolate pairs ≤25 SNPs apart were identified by at least one method. These had a median (range) SNP difference between the two methods of 1.2 SNPs (0 to 22 SNPs), with most isolate pairs (87%) varying by ≤2 SNPs. This similarity increased when the research pipeline was modified to use a clonal-complex-specific reference (median 0 SNP difference, 91% varying by ≤2 SNPs). Both pipelines clustered 338 isolates/334 patients into 66 unique clusters based on genetic relatedness. We conclude that the automated transmission detection tool worked at least as well as a researcher-led manual analysis and indicates how such tools could support the rapid use of MRSA genomic epidemiology in infection control practice. IMPORTANCE It has been clearly established that genome sequencing of MRSA improves the accuracy of health care-associated outbreak investigations, including the confirmation and exclusion of outbreaks and identification of patients involved. This could lead to more targeted infection control actions but its use in clinical practice is prevented by several barriers, one of which is the availability of genome analysis tools that do not depend on specialist knowledge to analyze or interpret the results. We evaluated a prototype of a fully automated bioinformatics system for MRSA genome analysis versus a bespoke researcher-led manual informatics pipeline, using genomes from 777 patients over a period of 9 months. The performance was at least equivalent to the researcher-led manual genomic analysis. This indicates the feasibility of automated analysis and represents one more step toward the routine use of pathogen sequencing in infection prevention and control practice.