A2B-COVID: A Tool for Rapidly Evaluating Potential SARS-CoV-2 Transmission Events.

Identifying linked cases of infection is a critical component of the public health response to viral infectious diseases. In a clinical context, there is a need to make rapid assessments of whether cases of infection have arrived independently onto a ward, or are potentially linked via direct transmission. Viral genome sequence data are of great value in making these assessments, but are often not the only form of data available. Here, we describe A2B-COVID, a method for the rapid identification of potentially linked cases of COVID-19 infection designed for clinical settings. Our method combines knowledge about infection dynamics, data describing the movements of individuals, and evolutionary analysis of genome sequences to assess whether data collected from cases of infection are consistent or inconsistent with linkage via direct transmission. A retrospective analysis of data from two wards at Cambridge University Hospitals NHS Foundation Trust during the first wave of the pandemic showed qualitatively different patterns of linkage between cases on designated COVID-19 and non-COVID-19 wards. The subsequent real-time application of our method to data from the second epidemic wave highlights its value for monitoring cases of infection in a clinical context.

Ventilator-associated pneumonia in critically ill patients with COVID-19.

BACKGROUND: Pandemic COVID-19 caused by the coronavirus SARS-CoV-2 has a high incidence of patients with severe acute respiratory syndrome (SARS). Many of these patients require admission to an intensive care unit (ICU) for invasive ventilation and are at significant risk of developing a secondary, ventilator-associated pneumonia (VAP). OBJECTIVES: To study the incidence of VAP and bacterial lung microbiome composition of ventilated COVID-19 and non-COVID-19 patients. METHODS: In this retrospective observational study, we compared the incidence of VAP and secondary infections using a combination of microbial culture and a TaqMan multi-pathogen array. In addition, we determined the lung microbiome composition using 16S RNA analysis in a subset of samples. The study involved 81 COVID-19 and 144 non-COVID-19 patients receiving invasive ventilation in a single University teaching hospital between March 15th 2020 and August 30th 2020. RESULTS: COVID-19 patients were significantly more likely to develop VAP than patients without COVID (Cox proportional hazard ratio 2.01 95% CI 1.14-3.54, p = 0.0015) with an incidence density of 28/1000 ventilator days versus 13/1000 for patients without COVID (p = 0.009). Although the distribution of organisms causing VAP was similar between the two groups, and the pulmonary microbiome was similar, we identified 3 cases of invasive aspergillosis amongst the patients with COVID-19 but none in the non-COVID-19 cohort. Herpesvirade activation was also numerically more frequent amongst patients with COVID-19. CONCLUSION: COVID-19 is associated with an increased risk of VAP, which is not fully explained by the prolonged duration of ventilation. The pulmonary dysbiosis caused by COVID-19, and the causative organisms of secondary pneumonia observed are similar to that seen in critically ill patients ventilated for other reasons.

Comprehensive global genome dynamics of Chlamydia trachomatis show ancient diversification followed by contemporary mixing and recent lineage expansion.

Chlamydia trachomatis is the world's most prevalent bacterial sexually transmitted infection and leading infectious cause of blindness, yet it is one of the least understood human pathogens, in part due to the difficulties of in vitro culturing and the lack of available tools for genetic manipulation. Genome sequencing has reinvigorated this field, shedding light on the contemporary history of this pathogen. Here, we analyze 563 full genomes, 455 of which are novel, to show that the history of the species comprises two phases, and conclude that the currently circulating lineages are the result of evolution in different genomic ecotypes. Temporal analysis indicates these lineages have recently expanded in the space of thousands of years, rather than the millions of years as previously thought, a finding that dramatically changes our understanding of this pathogen's history. Finally, at a time when almost every pathogen is becoming increasingly resistant to antimicrobials, we show that there is no evidence of circulating genomic resistance in C. trachomatis.

Mycoplasma genitalium: whole genome sequence analysis, recombination and population structure.

BACKGROUND: Although Mycoplasma genitalium is a common sexually transmitted pathogen causing clinically distinct diseases both in male and females, few genomes have been sequenced up to now, due mainly to its fastidious nature and slow growth. Hence, we lack a robust phylogenetic framework to provide insights into the population structure of the species. Currently our understanding of the nature and diversity of M. genitalium relies on molecular tests targeting specific genes or regions of the genome and knowledge is limited by a general under-testing internationally. This is set against a background of drug resistance whereby M. genitalium has developed resistance to mainly all therapeutic antimicrobials. RESULTS: We sequenced 28 genomes of Mycoplasma genitalium from temporally (1980-2010) and geographically (Europe, Japan, Australia) diverse sources. All the strain showed essentially the same genomic content without any accessory regions found. However, we identified extensive recombination across their genomes with a total of 25 regions showing heightened levels of SNP density. These regions include the MgPar loci, associated with host interactions, as well as other genes that could also be involved in this role. Using these data, we generated a robust phylogeny which shows that there are two main clades with differing degrees of genomic variability. SNPs found in region V of 23S rRNA and parC were consistent with azithromycin/erythromycin and fluoroquinolone resistances, respectively, and with their phenotypic MIC data. CONCLUSIONS: The sequence data here generated is essential for designing rational approaches to type and track Mycoplasma genitalium as antibiotic resistance increases. It represents a first approach to its population genetics to better appreciate the role of this organism as a sexually transmitted pathogen.

Whole-genome sequences of Chlamydia trachomatis directly from clinical samples without culture.

The use of whole-genome sequencing as a tool for the study of infectious bacteria is of growing clinical interest. Chlamydia trachomatis is responsible for sexually transmitted infections and the blinding disease trachoma, which affect hundreds of millions of people worldwide. Recombination is widespread within the genome of C. trachomatis, thus whole-genome sequencing is necessary to understand the evolution, diversity, and epidemiology of this pathogen. Culture of C. trachomatis has, until now, been a prerequisite to obtain DNA for whole-genome sequencing; however, as C. trachomatis is an obligate intracellular pathogen, this procedure is technically demanding and time consuming. Discarded clinical samples represent a large resource for sequencing the genomes of pathogens, yet clinical swabs frequently contain very low levels of C. trachomatis DNA and large amounts of contaminating microbial and human DNA. To determine whether it is possible to obtain whole-genome sequences from bacteria without the need for culture, we have devised an approach that combines immunomagnetic separation (IMS) for targeted bacterial enrichment with multiple displacement amplification (MDA) for whole-genome amplification. Using IMS-MDA in conjunction with high-throughput multiplexed Illumina sequencing, we have produced the first whole bacterial genome sequences direct from clinical samples. We also show that this method can be used to generate genome data from nonviable archived samples. This method will prove a useful tool in answering questions relating to the biology of many difficult-to-culture or fastidious bacteria of clinical concern.

C-reactive protein level and microbial aetiology in patients hospitalised with acute exacerbation of COPD.

Both viruses and bacteria are thought to cause exacerbations of chronic obstructive pulmonary disease (COPD); however, the relative importance of each remains uncertain. C-reactive protein (CRP) levels increase during exacerbations but the relationship with aetiology is not established. We aimed to explore the relationship between serum CRP and the rate of detection of viruses and bacteria. This was a prospectively recruited, observational study of patients hospitalised with exacerbations of COPD. Nasopharyngeal swabs were tested for respiratory viruses by reverse transcriptase-PCR. Sputum and blood were collected for bacterial culture and urine tested for pneumococcal antigen. CRP levels were measured on sera. CRP and other factors associated with viral, bacterial or mixed detection were assessed using multiple logistic regression analysis. 264 patients with exacerbations of COPD were studied: 26% tested positive for respiratory viruses only, 13% had bacteria only, 12% had mixed viral/bacterial detection, and 49% had no pathogens detected. CRP level and temperature were strongly associated with viral detection rate (p<0.001 and p=0.004, respectively) and mixed viral/bacterial detection rate (p=0.02 and p=0.03, respectively) on multivariate analysis. Bacterial detection rate was not associated with CRP level or body temperature. This study supports the role of viruses as important aetiological agents causing exacerbations of COPD.

Duplex molecular assay intended for point-of-care diagnosis of influenza A/B virus infection.

Early diagnosis and management of influenza virus infection directly correlates with the effectiveness in disease control. Current molecular influenza virus tests were designed for use in diagnostic testing facilities, where sophisticated equipment and highly trained technicians are available. A longer turnaround time for the centralized testing than when testing near the sample source could delay the initiation of medical intervention, thereby reducing the efficacy of antiviral treatment. The new assay, the SAMBA (simple amplification-based assay) Flu duplex test, is a dipstick-based molecular assay developed to provide a simple, accurate, and cost-effective solution for the diagnosis of influenza A/B viruses intended for near-patient testing. The test presents an alternative format of influenza virus molecular testing that utilizes isothermal amplification and visual detection of nucleic acid on a test strip. The entire test procedure (extraction, amplification, and detection) is integrated into an enclosed semiautomated system. Analytically, the SAMBA Flu duplex test detects 95 and 85 copies of viral genomes for influenza A and B viruses, respectively, with no cross-reactivity observed against other common respiratory pathogens. The clinical performance was established by blind testing of 328 nasal/throat and nasopharyngeal swab specimens from the United Kingdom and Belgium and comparing the results with the quantitative reverse transcription-PCR method routinely used in two public health laboratories. The SAMBA Flu duplex test showed a clinical sensitivity and specificity of 100% and 97.9% for influenza virus A and 100% and 100% for influenza virus B. The test provides a new technology that could facilitate simple and timely identification of influenza virus infection, potentially resulting in more efficient control measures.

Specificity and positive predictive value of SARS-CoV-2 nucleic acid amplification testing in a low-prevalence setting.

OBJECTIVES: When the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is low, many positive test results are false positives. Confirmatory testing reduces overdiagnosis and nosocomial infection and enables real-world estimates of test specificity and positive predictive value. This study estimates these parameters to evaluate the impact of confirmatory testing and to improve clinical diagnosis, epidemiological estimation and interpretation of vaccine trials. METHODS: Over 1 month we took all respiratory samples from our laboratory with a patient's first detection of SARS-CoV-2 RNA (Hologic Aptima SARS-CoV-2 assay or in-house RT-PCR platform), and repeated testing using two platforms. Samples were categorized by source, and by whether clinical details suggested COVID-19 or corroborative testing from another laboratory. We estimated specificity and positive predictive value using approaches based on maximum likelihood. RESULTS: Of 19 597 samples, SARS-CoV-2 RNA was detected in 107; 52 corresponded to first-time detection (0.27% of tests on samples without previous detection). Further testing detected SARS-CoV-2 RNA once or more ('confirmed') in 29 samples (56%), and failed to detect SARS-CoV-2 RNA ('not confirmed') in 23 (44%). Depending upon assumed parameters, point estimates for specificity and positive predictive value were 99.91-99.98% and 61.8-89.8% respectively using the Hologic Aptima SARS-CoV-2 assay, and 97.4-99.1% and 20.1-73.8% respectively using an in-house assay. CONCLUSIONS: Nucleic acid amplification testing for SARS-CoV-2 is highly specific. Nevertheless, when prevalence is low a significant proportion of initially positive results fail to confirm, and confirmatory testing substantially reduces the detection of false positives. Omitting additional testing in samples with higher prior detection probabilities focuses testing where it is clinically impactful and minimizes delay.

Development and implementation of a customised rapid syndromic diagnostic test for severe pneumonia.

Background: The diagnosis of pneumonia has been hampered by a reliance on bacterial cultures which take several days to return a result, and are frequently negative. In critically ill patients this leads to the use of empiric, broad-spectrum antimicrobials and compromises good antimicrobial stewardship. The objective of this study was to establish the performance of a syndromic molecular diagnostic approach, using a custom TaqMan array card (TAC) covering 52 respiratory pathogens, and assess its impact on antimicrobial prescribing. Methods: The TAC was validated against a retrospective multi-centre cohort of broncho-alveolar lavage samples. The TAC was assessed prospectively in patients undergoing investigation for suspected pneumonia, with a comparator cohort formed of patients investigated when the TAC laboratory team were unavailable. Co-primary outcomes were sensitivity compared to conventional microbiology and, for the prospective study, time to result. Metagenomic sequencing was performed to validate findings in prospective samples. Antibiotic free days (AFD) were compared between the study cohort and comparator group. Results: 128 stored samples were tested, with sensitivity of 97% (95% confidence interval (CI) 88-100%). Prospectively, 95 patients were tested by TAC, with 71 forming the comparator group. TAC returned results 51 hours (interquartile range 41-69 hours) faster than culture and with sensitivity of 92% (95% CI 83-98%) compared to conventional microbiology. 94% of organisms identified by sequencing were detected by TAC. There was a significant difference in the distribution of AFDs with more AFDs in the TAC group (p=0.02). TAC group were more likely to experience antimicrobial de-escalation (odds ratio 2.9 (95%1.5-5.5)). Conclusions: Implementation of a syndromic molecular diagnostic approach to pneumonia led to faster results, with high sensitivity and impact on antibiotic prescribing.

Patterns of within-host genetic diversity in SARS-CoV-2.

Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic diversity could theoretically help identify close contacts. Here we describe the patterns of within-host diversity in 1181 SARS-CoV-2 samples sequenced to high depth in duplicate. 95.1% of samples show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within- and between-host diversity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most samples result from infection by a single lineage, we identify multiple putative examples of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between samples could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses.

The COVID-19 pandemic has had major health impacts across the globe. The scientific community has focused much attention on finding ways to monitor how the virus responsible for the pandemic, SARS-CoV-2, spreads. One option is to perform genetic tests, known as sequencing, on SARS-CoV-2 samples to determine the genetic code of the virus and to find any differences or mutations in the genes between the viral samples. Viruses mutate within their hosts and can develop into variants that are able to more easily transmit between hosts. Genetic sequencing can reveal how genetically similar two SARS-CoV-2 samples are. But tracking how SARS-CoV-2 moves from one person to the next through sequencing can be tricky. Even a sample of SARS-CoV-2 viruses from the same individual can display differences in their genetic material or within-host variants. Could genetic testing of within-host variants shed light on factors driving SARS-CoV-2 to evolve in humans? To get to the bottom of this, Tonkin-Hill, Martincorena et al. probed the genetics of SARS-CoV-2 within-host variants using 1,181 samples. The analyses revealed that 95.1% of samples contained within-host variants. A number of variants occurred frequently in many samples, which were consistent with mutational hotspots in the SARS-CoV-2 genome. In addition, within-host variants displayed mutation patterns that were similar to patterns found between infected individuals. The shared within-host variants between samples can help to reconstruct transmission chains. However, the observed mutational hotspots and the detection of multiple strains within an individual can make this challenging. These findings could be used to help predict how SARS-CoV-2 evolves in response to interventions such as vaccines. They also suggest that caution is needed when using information on within-host variants to determine transmission between individuals.

Superspreaders drive the largest outbreaks of hospital onset COVID-19 infections.

SARS-CoV-2 is notable both for its rapid spread, and for the heterogeneity of its patterns of transmission, with multiple published incidences of superspreading behaviour. Here, we applied a novel network reconstruction algorithm to infer patterns of viral transmission occurring between patients and health care workers (HCWs) in the largest clusters of COVID-19 infection identified during the first wave of the epidemic at Cambridge University Hospitals NHS Foundation Trust, UK. Based upon dates of individuals reporting symptoms, recorded individual locations, and viral genome sequence data, we show an uneven pattern of transmission between individuals, with patients being much more likely to be infected by other patients than by HCWs. Further, the data were consistent with a pattern of superspreading, whereby 21% of individuals caused 80% of transmission events. Our study provides a detailed retrospective analysis of nosocomial SARS-CoV-2 transmission, and sheds light on the need for intensive and pervasive infection control procedures.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, presents a global public health challenge. Hospitals have been at the forefront of this battle, treating large numbers of sick patients over several waves of infection. Finding ways to manage the spread of the virus in hospitals is key to protecting vulnerable patients and workers, while keeping hospitals running, but to generate effective infection control, researchers must understand how SARS-CoV-2 spreads. A range of factors make studying the transmission of SARS-CoV-2 in hospitals tricky. For instance, some people do not present any symptoms, and, amongst those who do, it can be difficult to determine whether they caught the virus in the hospital or somewhere else. However, comparing the genetic information of the SARS-CoV-2 virus from different people in a hospital could allow scientists to understand how it spreads. Samples of the genetic material of SARS-CoV-2 can be obtained by swabbing infected individuals. If the genetic sequences of two samples are very different, it is unlikely that the individuals who provided the samples transmitted the virus to one another. Illingworth, Hamilton et al. used this information, along with other data about how SARS-CoV-2 is transmitted, to develop an algorithm that can determine how the virus spreads from person to person in different hospital wards. To build their algorithm, Illingworth, Hamilton et al. collected SARS-CoV-2 genetic data from patients and staff in a hospital, and combined it with information about how SARS-CoV-2 spreads and how these people moved in the hospital . The algorithm showed that, for the most part, patients were infected by other patients (20 out of 22 cases), while staff were infected equally by patients and staff. By further probing these data, Illingworth, Hamilton et al. revealed that 80% of hospital-acquired infections were caused by a group of just 21% of individuals in the study, identifying a 'superspreader' pattern. These findings may help to inform SARS-CoV-2 infection control measures to reduce spread within hospitals, and could potentially be used to improve infection control in other contexts.

Genomic epidemiology of COVID-19 in care homes in the east of England.

COVID-19 poses a major challenge to care homes, as SARS-CoV-2 is readily transmitted and causes disproportionately severe disease in older people. Here, 1167 residents from 337 care homes were identified from a dataset of 6600 COVID-19 cases from the East of England. Older age and being a care home resident were associated with increased mortality. SARS-CoV-2 genomes were available for 700 residents from 292 care homes. By integrating genomic and temporal data, 409 viral clusters within the 292 homes were identified, indicating two different patterns - outbreaks among care home residents and independent introductions with limited onward transmission. Approximately 70% of residents in the genomic analysis were admitted to hospital during the study, providing extensive opportunities for transmission between care homes and hospitals. Limiting viral transmission within care homes should be a key target for infection control to reduce COVID-19 mortality in this population.

Nucleic acid dipstick test for molecular diagnosis of pandemic H1N1.

A new nucleic acid amplification-based rapid test for diagnosis of pandemic influenza (H1N1) 2009 virus was developed. The molecular test for pandemic H1N1, SAMBA (simple amplification-based assay), is based on isothermal amplification and visual detection on a dipstick characterized by high sensitivity, high specificity, a short turnaround time, and minimal technical requirements. The amplification step is monitored with an internal control to ensure correct interpretation of test results. The clinical performance of this assay was evaluated using blinded RNA samples extracted from nasal/throat swab specimens from 262 patients exhibiting influenza-like illness. Compared with the United Kingdom National Standard Method, based on quantitative reverse transcription-PCR, the sensitivity, specificity, positive predictive value, and negative predictive value of the new assay were 95.3% (95% confidence interval, 88.5 to 98.7%), 99.4% (95% confidence interval, 96.9 to 99.9%), 98.8% (95% confidence interval, 93.5 to 99.9%), and 97.8% (95% confidence interval, 94.4 to 99.4%), respectively. The SAMBA for pandemic H1N1 provides a new technology that could potentially facilitate timely diagnosis and management of infected individuals, thereby informing decision making with regard to patient isolation during a pandemic outbreak.

Evaluating the use of a 22-pathogen TaqMan array card for rapid diagnosis of respiratory pathogens in intensive care.

Introduction. Pneumonia is highly prevalent in intensive care units (ICUs), with high associated mortality. Empirical treatment prioritizes breadth of coverage while awaiting laboratory diagnosis, often at the expense of antimicrobial stewardship. Microarrays use multiple parallel polymerase chain reactions to enable a rapid syndromic approach to laboratory diagnosis.Aim. To evaluate the clinical and laboratory implications of introducing a bespoke 22-pathogen TaqMan Array Card (TAC) for rapid pathogen detection in deep respiratory samples from adult ICUs.Methodology. TAC results from all ICU patients prospectively tested over a 9-month period at Cambridge's Clinical Microbiology and Public Health Laboratory were compared to those of corresponding conventional microbiological assays (culture-, PCR- or serology-based) in terms of result agreement and time-to-result availability. Clinical impact was assessed by retrospective review of medical records.Results. Seventy-one patients were included [45 (63 %) male, median age 59). Overall result agreement was 94 %, with TAC detecting more pathogens than conventional methods. TAC detected Streptococcus pneumoniae more readily than culture (7 vs 0 cases; P=0.02). TAC did not detect Aspergillus spp. in eight culture- or galactomannan-positive cases. The median turnaround time (1 day) was significantly shorter than that of bacterial/fungal culture, Pneumocystis jirovecii PCR and galactomannan testing (each 3 days; P<0.001), atypical bacteria serology (13 days; P<0.001) and Mycobacterium tuberculosis culture (46 days; P<0.001). Earlier result availability prompted discontinuation of unnecessary antimicrobials in 15/71 (21 %) cases, but had no bearing on patient isolation/deisolation.Conclusion. TAC provided greater overall yield of pathogen detection and faster turnaround times, permitting earlier discontinuation of unnecessary antimicrobials.

A blueprint for the implementation of a validated approach for the detection of SARS-Cov2 in clinical samples in academic facilities.

The COVID-19 pandemic is expanding at an unprecedented rate. As a result, diagnostic services are stretched to their limit, and there is a clear need for the provision of additional diagnostic capacity. Academic laboratories, many of which are closed due to governmental lockdowns, may be in a position to support local screening capacity by adapting their current laboratory practices. Here, we describe the process of developing a SARS-Cov2 diagnostic workflow in a conventional academic Containment Level 2 laboratory. Our outline includes simple SARS-Cov2 deactivation upon contact, the method for a quantitative real-time reverse transcriptase PCR detecting SARS-Cov2, a description of process establishment and validation, and some considerations for establishing a similar workflow elsewhere. This was achieved under challenging circumstances through the collaborative efforts of scientists, clinical staff, and diagnostic staff to mitigate to the ongoing crisis. Within 14 days, we created a validated COVID-19 diagnostics service for healthcare workers in our local hospital. The described methods are not exhaustive, but we hope may offer support to other academic groups aiming to set up something comparable in a short time frame.

Rapid implementation of SARS-CoV-2 sequencing to investigate cases of health-care associated COVID-19: a prospective genomic surveillance study.

BACKGROUND: The burden and influence of health-care associated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is unknown. We aimed to examine the use of rapid SARS-CoV-2 sequencing combined with detailed epidemiological analysis to investigate health-care associated SARS-CoV-2 infections and inform infection control measures. METHODS: In this prospective surveillance study, we set up rapid SARS-CoV-2 nanopore sequencing from PCR-positive diagnostic samples collected from our hospital (Cambridge, UK) and a random selection from hospitals in the East of England, enabling sample-to-sequence in less than 24 h. We established a weekly review and reporting system with integration of genomic and epidemiological data to investigate suspected health-care associated COVID-19 cases. FINDINGS: Between March 13 and April 24, 2020, we collected clinical data and samples from 5613 patients with COVID-19 from across the East of England. We sequenced 1000 samples producing 747 high-quality genomes. We combined epidemiological and genomic analysis of the 299 patients from our hospital and identified 35 clusters of identical viruses involving 159 patients. 92 (58%) of 159 patients had strong epidemiological links and 32 (20%) patients had plausible epidemiological links. These results were fed back to clinical, infection control, and hospital management teams, leading to infection-control interventions and informing patient safety reporting. INTERPRETATION: We established real-time genomic surveillance of SARS-CoV-2 in a UK hospital and showed the benefit of combined genomic and epidemiological analysis for the investigation of health-care associated COVID-19. This approach enabled us to detect cryptic transmission events and identify opportunities to target infection-control interventions to further reduce health-care associated infections. Our findings have important implications for national public health policy as they enable rapid tracking and investigation of infections in hospital and community settings. FUNDING: COVID-19 Genomics UK funded by the Department of Health and Social Care, UK Research and Innovation, and the Wellcome Sanger Institute.

Complete Genome Sequences of BK Polyomavirus Strains from Two Patients with Urinary Tract Infection, Sequenced Using the Ion Torrent Platform.

BK polyomavirus is an important pathogen in kidney transplant patients. We report here two complete genome sequences, those of isolates CAMB-1035 and CAMB-1055, identified in two urine samples tested for urinary tract infection at a hospital in eastern England, United Kingdom. Variation and phylogenetic analyses indicate that both isolates belong to subtype Ib-1.

Viral load is strongly associated with length of stay in adults hospitalised with viral acute respiratory illness.

BACKGROUND: Respiratory viruses are detectable in a large proportion of adults hospitalised with acute respiratory illness. For influenza and other viruses there is evidence that viral load and persistence are associated with certain clinical outcomes but it is not known if there is an association between viral load and hospital length of stay. METHODS: 306 adults hospitalised with viral acute respiratory illness were studied. Associations between viral load and length of stay were examined. Multiple linear regression analysis was performed to control for age, comorbidity, influenza vaccine status, duration of illness prior to hospitalisation, bacterial co-infection, clinical group and virus subtype. RESULTS: High viral load was associated with a longer duration of hospitalisation for all patients (p < 0.0001). This remained significant across all virus types and clinical groups and when adjusted for age, comorbidity, duration of illness prior to hospitalisation, bacterial co-infection and other factors. CONCLUSIONS: High viral loads are associated with prolonged hospital length of stay in adults with viral acute respiratory illness. This further supports existing evidence demonstrating that viral acute respiratory illness is a viral load driven process and suggests that viral load could be used in clinical practise to predict prolonged hospitalisation and prioritise antivirals. International Standard Randomised Controlled Trial Number (ISRCTN): 21521552.

A real-time Taqman method for hepatitis C virus genotyping.

BACKGROUND: There is the need for a rapid, inexpensive method for genotyping hepatitis C virus (HCV) to support clinical practice. OBJECTIVES: To develop a real-time (Rotor-Gene 3000) Taqman assay for HCV genotyping in a single tube. STUDY DESIGN: Seven type-specific probes, two for genotypes 1-3 and one for genotype 4 were designed around genotype-specific motifs in the 5' non-coding (NC) region to create two panels of probes. The first panel included two probes for genotype 1 detection and a single probe each for genotypes 2 and 3. The second panel had two probes for confirmation of genotypes 2 and 3 and a first line probe for genotype 4 detection. A comparative analysis of the Taqman assay against our in-house sequence-based method using 154 consecutive clinical samples, from HCV carriers in Cambridge, and four samples from the Quality Control for Molecular Diagnostics (QCMD) System was undertaken. RESULTS: 158 samples were analysed by conventional sequencing: 49% (n=78) were genotype 1, 11% (n=18) genotype 2, 30% (n=47) genotype 3 and 6% (n=10) genotype 4. For two samples, the sequence data was heterogeneous and difficult to analyse, suggesting mixed infection and for three samples, the viral load was insufficient for sequencing. Concordant results were obtained with the novel Taqman assay for 77/78 (99%) of genotype 1 isolates (positive with both genotype 1 probes), 17/18 (94%) of genotype 2 isolates, 43/47 (91%) of genotype 3 isolates and 10/10 (100%) genotype 4 isolates. One isolate, untypeable with sequencing was genotyped with the Taqman assay. CONCLUSIONS: The Taqman assay was sensitive, specific and reliable over a wide range of viral loads and could identify mixed infections. These results highlight the potential of the Taqman assay as a fast, accurate and convenient method for routine HCV genotyping.