Development and proof-of-concept demonstration of a clinical metagenomics method for the rapid detection of bloodstream infection.

BACKGROUND: The timely and accurate diagnosis of bloodstream infection (BSI) is critical for patient management. With longstanding challenges for routine blood culture, metagenomics is a promising approach to rapidly provide sequence-based detection and characterisation of bloodborne bacteria. Long-read sequencing technologies have successfully supported the use of clinical metagenomics for syndromes such as respiratory illness, and modified approaches may address two requisite factors for metagenomics to be used as a BSI diagnostic: depletion of the high level of host DNA to then detect the low abundance of microbes in blood. METHODS: Blood samples from healthy donors were spiked with different concentrations of four prevalent causative species of BSI. All samples were then subjected to a modified saponin-based host DNA depletion protocol and optimised DNA extraction, whole genome amplification and debranching steps in preparation for sequencing, followed by bioinformatical analyses. Two related variants of the protocol are presented: 1mL of blood processed without bacterial enrichment, and 5mL of blood processed following a rapid bacterial enrichment protocol-SepsiPURE. RESULTS: After first identifying that a large proportion of host mitochondrial DNA remained, the host depletion process was optimised by increasing saponin concentration to 3% and scaling the reaction to allow more sample volume. Compared to non-depleted controls, the 3% saponin-based depletion protocol reduced the presence of host chromosomal and mitochondrial DNA < 106 and < 103 fold respectively. When the modified depletion method was further combined with a rapid bacterial enrichment method (SepsiPURE; with 5mL blood samples) the depletion of mitochondrial DNA improved by a further > 10X while also increasing detectable bacteria by > 10X. Parameters during DNA extraction, whole genome amplification and long-read sequencing were also adjusted, and subsequently amplicons were detected for each input bacterial species at each of the spiked concentrations, ranging from 50-100 colony forming units (CFU)/mL to 1-5 CFU/mL. CONCLUSION: In this proof-of-concept study, four prevalent BSI causative species were detected in under 12 h to species level (with antimicrobial resistance determinants) at concentrations relevant to clinical blood samples. The use of a rapid and precise metagenomic protocols has the potential to advance the diagnosis of BSI.

Routine Metagenomics Service for ICU Patients with Respiratory Infection.

Rationale: Respiratory metagenomics (RMg) needs evaluation in a pilot service setting to determine utility and inform implementation into routine clinical practice. Objectives: Feasibility, performance, and clinical impacts on antimicrobial prescribing and infection control were recorded during a pilot RMg service. Methods: RMg was performed on 128 samples from 87 patients with suspected lower respiratory tract infection (LRTI) on two general and one specialist respiratory ICUs at Guy's and St Thomas' NHS Foundation Trust, London. Measurements and Main Results: During the first 15 weeks, RMg provided same-day results for 110 samples (86%), with a median turnaround time of 6.7 hours (interquartile range = 6.1-7.5 h). RMg was 93% sensitive and 81% specific for clinically relevant pathogens compared with routine testing. Forty-eight percent of RMg results informed antimicrobial prescribing changes (22% escalation; 26% deescalation) with escalation based on speciation in 20 out of 24 cases and detection of acquired-resistance genes in 4 out of 24 cases. Fastidious or unexpected organisms were reported in 21 samples, including anaerobes (n = 12), Mycobacterium tuberculosis, Tropheryma whipplei, cytomegalovirus, and Legionella pneumophila ST1326, which was subsequently isolated from the bedside water outlet. Application to consecutive severe community-acquired LRTI cases identified Staphylococcus aureus (two with SCCmec and three with luk F/S virulence determinants), Streptococcus pyogenes (emm1-M1uk clone), S. dysgalactiae subspecies equisimilis (STG62647A), and Aspergillus fumigatus with multiple treatments and public health impacts. Conclusions: This pilot study illustrates the potential of RMg testing to provide benefits for antimicrobial treatment, infection control, and public health when provided in a real-world critical care setting. Multicenter studies are now required to inform future translation into routine service.

The use of representative community samples to assess SARS-CoV-2 lineage competition: Alpha outcompetes Beta and wild-type in England from January to March 2021.

Genomic surveillance for SARS-CoV-2 lineages informs our understanding of possible future changes in transmissibility and vaccine efficacy and will be a high priority for public health for the foreseeable future. However, small changes in the frequency of one lineage over another are often difficult to interpret because surveillance samples are obtained using a variety of methods all of which are known to contain biases. As a case study, using an approach which is largely free of biases, we here describe lineage dynamics and phylogenetic relationships of the Alpha and Beta variant in England during the first 3 months of 2021 using sequences obtained from a random community sample who provided a throat and nose swab for rt-PCR as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. Overall, diversity decreased during the first quarter of 2021, with the Alpha variant (first identified in Kent) becoming predominant, driven by a reproduction number 0.3 higher than for the prior wild-type. During January, positive samples were more likely to be Alpha in those aged 18 to 54 years old. Although individuals infected with the Alpha variant were no more likely to report one or more classic COVID-19 symptoms compared to those infected with wild-type, they were more likely to be antibody-positive 6 weeks after infection. Further, viral load was higher in those infected with the Alpha variant as measured by cycle threshold (Ct) values. The presence of infections with non-imported Beta variant (first identified in South Africa) during January, but not during February or March, suggests initial establishment in the community followed by fade-out. However, this occurred during a period of stringent social distancing. These results highlight how sequence data from representative community surveys such as REACT-1 can augment routine genomic surveillance during periods of lineage diversity.

Determination and quantification of microbial communities and antimicrobial resistance on food through host DNA-depleted metagenomics.

Food products carry bacteria unless specifically sterilised. These bacteria can be pathogenic, commensal or associated with food spoilage, and may also be resistant to antimicrobials. Current methods for detecting bacteria on food rely on culturing for specific bacteria, a time-consuming process, or 16S rRNA metabarcoding that can identify different taxa but not their genetic content. Directly sequencing metagenomes of food is inefficient as its own DNA vastly outnumbers the bacterial DNA present. We optimised host DNA depletion enabling efficient sequencing of food microbiota, thereby increasing the proportion of non-host DNA sequenced 13-fold (mean; range: 1.3-40-fold) compared to untreated samples. The method performed best on chicken, pork and leafy green samples which had high mean prokaryotic read proportions post-depletion (0.64, 0.74 and 0.74, respectively), with lower mean prokaryotic read proportions in salmon (0.50) and prawn samples (0.19). We show that bacterial compositions and concentrations of antimicrobial resistance (AMR) genes differed by food type, and that salmon metagenomes were influenced by the production/harvesting method. The approach described in this study is an efficient and effective method of identifying and quantifying the predominant bacteria and AMR genes on food.

Clinical Performance of Direct RT-PCR Testing of Raw Saliva for Detection of SARS-CoV-2 in Symptomatic and Asymptomatic Individuals.

RT-PCR tests based on RNA extraction from nasopharyngeal swabs (NPS) are promoted as the "gold standard" for SARS-CoV-2 detection. However, the use of saliva samples offers noninvasive self-collection more suitable for high-throughput testing. This study evaluated performance of the TaqPath COVID-19 Fast PCR Combo kit 2.0 assay for detection of SARS-CoV-2 in raw saliva relative to a lab-developed direct RT-PCR test (SalivaDirect-based PCR, SDB-PCR) and an RT-PCR test based on RNA extraction from NPS. Saliva and NPS samples were collected from symptomatic and asymptomatic individuals (N = 615). Saliva samples were tested for SARS-CoV-2 using the TaqPath COVID-19 Fast PCR Combo kit 2.0 and the SDB-PCR, while NPS samples were tested by RT-PCR in RNA extracts according to the Irish national testing system. TaqPath COVID-19 Fast PCR Combo kit 2.0 detected SARS-CoV-2 in 52 saliva samples, of which 51 were also positive with the SDB-PCR. Compared to the NPS "gold standard" biospecimen method, 49 samples displayed concordant results, while three samples (35

Hybrid metagenome assemblies link carbohydrate structure with function in the human gut microbiome.

Complex carbohydrates that escape small intestinal digestion, are broken down in the large intestine by enzymes encoded by the gut microbiome. This is a symbiotic relationship between microbes and host, resulting in metabolic products that influence host health and are exploited by other microbes. However, the role of carbohydrate structure in directing microbiota community composition and the succession of carbohydrate-degrading microbes, is not fully understood. In this study we evaluate species-level compositional variation within a single microbiome in response to six structurally distinct carbohydrates in a controlled model gut using hybrid metagenome assemblies. We identified 509 high-quality metagenome-assembled genomes (MAGs) belonging to ten bacterial classes and 28 bacterial families. Bacterial species identified as carrying genes encoding starch binding modules increased in abundance in response to starches. The use of hybrid metagenomics has allowed identification of several uncultured species with the functional potential to degrade starch substrates for future study.

Dynamics of Salmonella enterica and antimicrobial resistance in the Brazilian poultry industry and global impacts on public health.

Non-typhoidal Salmonella enterica is a common cause of diarrhoeal disease; in humans, consumption of contaminated poultry meat is believed to be a major source. Brazil is the world's largest exporter of chicken meat globally, and previous studies have indicated the introduction of Salmonella serovars through imported food products from Brazil. Here we provide an in-depth genomic characterisation and evolutionary analysis to investigate the most prevalent serovars and antimicrobial resistance (AMR) in Brazilian chickens and assess the impact to public health of products contaminated with S. enterica imported into the United Kingdom from Brazil. To do so, we examine 183 Salmonella genomes from chickens in Brazil and 357 genomes from humans, domestic poultry and imported Brazilian poultry products isolated in the United Kingdom. S. enterica serovars Heidelberg and Minnesota were the most prevalent serovars in Brazil and in meat products imported from Brazil into the UK. We extended our analysis to include 1,259 publicly available Salmonella Heidelberg and Salmonella Minnesota genomes for context. The Brazil genomes form clades distinct from global isolates, with temporal analysis suggesting emergence of these Salmonella Heidelberg and Salmonella Minnesota clades in the early 2000s, around the time of the 2003 introduction of the Enteritidis vaccine in Brazilian poultry. Analysis showed genomes within the Salmonella Heidelberg and Salmonella Minnesota clades shared resistance to sulphonamides, tetracyclines and beta-lactams conferred by sul2, tetA and blaCMY-2 genes, not widely observed in other co-circulating serovars despite similar selection pressures. The sul2 and tetA genes were concomitantly carried on IncC plasmids, whereas blaCMY-2 was either co-located with the sul2 and tetA genes on IncC plasmids or independently on IncI1 plasmids. Long-term surveillance data collected in the UK showed no increase in the incidence of Salmonella Heidelberg or Salmonella Minnesota in human cases of clinical disease in the UK following the increase of these two serovars in Brazilian poultry. In addition, almost all of the small number of UK-derived genomes which cluster with the Brazilian poultry-derived sequences could either be attributed to human cases with a recent history of foreign travel or were from imported Brazilian food products. These findings indicate that even should Salmonella from imported Brazilian poultry products reach UK consumers, they are very unlikely to be causing disease. No evidence of the Brazilian strains of Salmonella Heidelberg or Salmonella Minnesota were observed in UK domestic chickens. These findings suggest that introduction of the Salmonella Enteritidis vaccine, in addition to increasing antimicrobial use, could have resulted in replacement of salmonellae in Brazilian poultry flocks with serovars that are more drug resistant, but less associated with disease in humans in the UK. The plasmids conferring resistance to beta-lactams, sulphonamides and tetracyclines likely conferred a competitive advantage to the Salmonella Minnesota and Salmonella Heidelberg serovars in this setting of high antimicrobial use, but the apparent lack of transfer to other serovars present in the same setting suggests barriers to horizontal gene transfer that could be exploited in intervention strategies to reduce AMR. The insights obtained reinforce the importance of One Health genomic surveillance.

Microbiomes of Urine and the Prostate Are Linked to Human Prostate Cancer Risk Groups.

BACKGROUND: Bacteria play a suspected role in the development of several cancer types, and associations between the presence of particular bacteria and prostate cancer have been reported. OBJECTIVE: To provide improved characterisation of the prostate and urine microbiome and to investigate the prognostic potential of the bacteria present. DESIGN, SETTING, AND PARTICIPANTS: Microbiome profiles were interrogated in sample collections of patient urine (sediment microscopy: n = 318, 16S ribosomal amplicon sequencing: n = 46; and extracellular vesicle RNA-seq: n = 40) and cancer tissue (n = 204). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Microbiomes were assessed using anaerobic culture, population-level 16S analysis, RNA-seq, and whole genome DNA sequencing. RESULTS AND LIMITATIONS: We demonstrate an association between the presence of bacteria in urine sediments and higher D'Amico risk prostate cancer (discovery, n = 215 patients, p < 0.001; validation, n = 103, p < 0.001, χ2 test for trend). Characterisation of the bacterial community led to the (1) identification of four novel bacteria (Porphyromonas sp. nov., Varibaculum sp. nov., Peptoniphilus sp. nov., and Fenollaria sp. nov.) that were frequently found in patient urine, and (2) definition of a patient subgroup associated with metastasis development (p = 0.015, log-rank test). The presence of five specific anaerobic genera, which includes three of the novel isolates, was associated with cancer risk group, in urine sediment (p = 0.045, log-rank test), urine extracellular vesicles (p = 0.039), and cancer tissue (p = 0.035), with a meta-analysis hazard ratio for disease progression of 2.60 (95% confidence interval: 1.39-4.85; p = 0.003; Cox regression). A limitation is that functional links to cancer development are not yet established. CONCLUSIONS: This study characterises prostate and urine microbiomes, and indicates that specific anaerobic bacteria genera have prognostic potential. PATIENT SUMMARY: In this study, we investigated the presence of bacteria in patient urine and the prostate. We identified four novel bacteria and suggest a potential prognostic utility for the microbiome in prostate cancer.

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.

Multicentre evaluation of two multiplex PCR platforms for the rapid microbiological investigation of nosocomial pneumonia in UK ICUs: the INHALE WP1 study.

BACKGROUND: Culture-based microbiological investigation of hospital-acquired or ventilator-associated pneumonia (HAP or VAP) is insensitive, with aetiological agents often unidentified. This can lead to excess antimicrobial treatment of patients with susceptible pathogens, while those with resistant bacteria are treated inadequately for prolonged periods. Using PCR to seek pathogens and their resistance genes directly from clinical samples may improve therapy and stewardship. METHODS: Surplus routine lower respiratory tract samples were collected from intensive care unit patients about to receive new or changed antibiotics for hospital-onset lower respiratory tract infections at 15 UK hospitals. Testing was performed using the BioFire FilmArray Pneumonia Panel (bioMérieux) and Unyvero Pneumonia Panel (Curetis). Concordance analysis compared machine and routine microbiology results, while Bayesian latent class (BLC) analysis estimated the sensitivity and specificity of each test, incorporating information from both PCR panels and routine microbiology. FINDINGS: In 652 eligible samples; PCR identified pathogens in considerably more samples compared with routine microbiology: 60.4% and 74.2% for Unyvero and FilmArray respectively vs 44.2% by routine microbiology. PCR tests also detected more pathogens per sample than routine microbiology. For common HAP/VAP pathogens, FilmArray had sensitivity of 91.7%-100.0% and specificity of 87.5%-99.5%; Unyvero had sensitivity of 50.0%-100.0%%, and specificity of 89.4%-99.0%. BLC analysis indicated that, compared with PCR, routine microbiology had low sensitivity, ranging from 27.0% to 69.4%. INTERPRETATION: Conventional and BLC analysis demonstrated that both platforms performed similarly and were considerably more sensitive than routine microbiology, detecting potential pathogens in patient samples reported as culture negative. The increased sensitivity of detection realised by PCR offers potential for improved antimicrobial prescribing.

The role of viral genomics in understanding COVID-19 outbreaks in long-term care facilities.

We reviewed all genomic epidemiology studies on COVID-19 in long-term care facilities (LTCFs) that had been published to date. We found that staff and residents were usually infected with identical, or near identical, SARS-CoV-2 genomes. Outbreaks usually involved one predominant cluster, and the same lineages persisted in LTCFs despite infection control measures. Outbreaks were most commonly due to single or few introductions followed by a spread rather than a series of seeding events from the community into LTCFs. The sequencing of samples taken consecutively from the same individuals at the same facilities showed the persistence of the same genome sequence, indicating that the sequencing technique was robust over time. When combined with local epidemiology, genomics allowed probable transmission sources to be better characterised. The transmission between LTCFs was detected in multiple studies. The mortality rate among residents was high in all facilities, regardless of the lineage. Bioinformatics methods were inadequate in a third of the studies reviewed, and reproducing the analyses was difficult because sequencing data were not available in many facilities.

Prospective Evaluation of a Rapid Clinical Metagenomics Test for Bacterial Pneumonia.

Background: The diagnosis of bacterial pathogens in lower respiratory tract infections (LRI) using conventional culture methods remains challenging and time-consuming. Objectives: To evaluate the clinical performance of a rapid nanopore-sequencing based metagenomics test for diagnosis of bacterial pathogens in common LRIs through a large-scale prospective study. Methods: We enrolled 292 hospitalized patients suspected to have LRIs between November 2018 and June 2019 in a single-center, prospective cohort study. Rapid clinical metagenomics test was performed on-site, and the results were compared with those of routine microbiology tests. Results: 171 bronchoalveolar lavage fluid (BAL) and 121 sputum samples were collected from patients with six kinds of LRIs. The turnaround time (from sample registration to result) for the rapid metagenomics test was 6.4 ± 1.4 hours, compared to 94.8 ± 34.9 hours for routine culture. Compared with culture and real-time PCR validation tests, rapid metagenomics achieved 96.6% sensitivity and 88.0% specificity and identified pathogens in 63 out of 161 (39.1%) culture-negative samples. Correlation between enriched anaerobes and lung abscess was observed by Gene Set Enrichment Analysis. Moreover, 38 anaerobic species failed in culture was identified by metagenomics sequencing. The hypothetical impact of metagenomics test proposed antibiotic de-escalation in 34 patients compared to 1 using routine culture. Conclusions: Rapid clinical metagenomics test improved pathogen detection yield in the diagnosis of LRI. Empirical antimicrobial therapy could be de-escalated if rapid metagenomics test results were hypothetically applied to clinical management.

Evaluating the potential for respiratory metagenomics to improve treatment of secondary infection and detection of nosocomial transmission on expanded COVID-19 intensive care units.

BACKGROUND: Clinical metagenomics (CMg) has the potential to be translated from a research tool into routine service to improve antimicrobial treatment and infection control decisions. The SARS-CoV-2 pandemic provides added impetus to realise these benefits, given the increased risk of secondary infection and nosocomial transmission of multi-drug-resistant (MDR) pathogens linked with the expansion of critical care capacity. METHODS: CMg using nanopore sequencing was evaluated in a proof-of-concept study on 43 respiratory samples from 34 intubated patients across seven intensive care units (ICUs) over a 9-week period during the first COVID-19 pandemic wave. RESULTS: An 8-h CMg workflow was 92% sensitive (95% CI, 75-99%) and 82% specific (95% CI, 57-96%) for bacterial identification based on culture-positive and culture-negative samples, respectively. CMg sequencing reported the presence or absence of ß-lactam-resistant genes carried by Enterobacterales that would modify the initial guideline-recommended antibiotics in every case. CMg was also 100% concordant with quantitative PCR for detecting Aspergillus fumigatus from 4 positive and 39 negative samples. Molecular typing using 24-h sequencing data identified an MDR-K. pneumoniae ST307 outbreak involving 4 patients and an MDR-C. striatum outbreak involving 14 patients across three ICUs. CONCLUSION: CMg testing provides accurate pathogen detection and antibiotic resistance prediction in a same-day laboratory workflow, with assembled genomes available the next day for genomic surveillance. The provision of this technology in a service setting could fundamentally change the multi-disciplinary team approach to managing ICU infections. The potential to improve the initial targeted treatment and rapidly detect unsuspected outbreaks of MDR-pathogens justifies further expedited clinical assessment of CMg.

INHALE: the impact of using FilmArray Pneumonia Panel molecular diagnostics for hospital-acquired and ventilator-associated pneumonia on antimicrobial stewardship and patient outcomes in UK Critical Care-study protocol for a multicentre randomised controlled trial.

BACKGROUND: Hospital-acquired and ventilator-associated pneumonias (HAP and VAP) are common in critical care and can be life-threatening. Rapid microbiological diagnostics, linked to an algorithm to translate their results into antibiotic choices, could simultaneously improve patient outcomes and antimicrobial stewardship. METHODS: The INHALE Randomised Controlled Trial is a multi-centre, parallel study exploring the potential of the BioFire FilmArray molecular diagnostic to guide antibiotic treatment of HAP/VAP in intensive care units (ICU); it identifies pathogens and key antibiotic resistance in around 90 min. The comparator is standard care whereby the patient receives empirical antibiotics until microbiological culture results become available, typically after 48-72 h. Adult and paediatric ICU patients are eligible if they are about to receive antibiotics for a suspected lower respiratory infection (including HAP/VAP) for the first time or a change in antibiotic because of a deteriorating clinical condition. Breathing spontaneously or intubated, they must have been hospitalised for 48 h or more. Patients are randomised 1:1 to receive either antibiotics guided by the FilmArray molecular diagnostic and its trial-based prescribing algorithm or standard care, meaning empirical antibiotics based on local policy, adapted subsequently based upon local microbiology culture results. Co-primary outcomes are (i) non-inferiority in clinical cure of pneumonia at 14 days post-randomisation and (ii) superiority in antimicrobial stewardship at 24 h post-randomisation (defined as % of patients on active and proportionate antibiotics). Secondary outcomes include further stewardship reviews; length of ICU stay; co-morbidity indicators, including septic shock, change in sequential organ failure assessment scores, and secondary pneumonias; ventilator-free days; adverse events over 21 days; all-cause mortality; and total antibiotic usage. Both cost-effectiveness of the molecular diagnostic-guided therapy and behavioural aspects determining antibiotic prescribing are being explored. A sample size of 552 will be required to detect clinically significant results with 90% power and 5% significance for the co-primary outcomes. DISCUSSION: This trial will test whether the potential merits of rapid molecular diagnostics for pathogen and resistance detection in HAP/VAP are realised in patient outcomes and/or improved antibiotic stewardship. TRIAL REGISTRATION: ISRCTN Registry ISRCTN16483855 . Retrospectively registered on 15 July 2019.

Genomic epidemiology and the role of international and regional travel in the SARS-CoV-2 epidemic in Zimbabwe: a retrospective study of routinely collected surveillance data.

BACKGROUND: Advances in SARS-CoV-2 sequencing have enabled identification of new variants, tracking of its evolution, and monitoring of its spread. We aimed to use whole genome sequencing to describe the molecular epidemiology of the SARS-CoV-2 outbreak and to inform the implementation of effective public health interventions for control in Zimbabwe. METHODS: We performed a retrospective study of nasopharyngeal samples collected from nine laboratories in Zimbabwe between March 20 and Oct 16, 2020. Samples were taken as a result of quarantine procedures for international arrivals or to test for infection in people who were symptomatic or close contacts of positive cases. Samples that had a cycle threshold of less than 30 in the diagnostic PCR test were processed for sequencing. We began our analysis in July, 2020 (120 days since the first case), with a follow-up in October, 2020 (at 210 days since the first case). The phylogenetic relationship of the genome sequences within Zimbabwe and global samples was established using maximum likelihood and Bayesian methods. FINDINGS: Of 92 299 nasopharyngeal samples collected during the study period, 8099 were PCR-positive and 328 were available for sequencing, with 156 passing sequence quality control. 83 (53%) of 156 were from female participants. At least 26 independent introductions of SARS-CoV-2 into Zimbabwe in the first 210 days were associated with 12 global lineages. 151 (97%) of 156 had the Asp614Gly mutation in the spike protein. Most cases, 93 (60%), were imported from outside Zimbabwe. Community transmission was reported 6 days after the onset of the outbreak. INTERPRETATION: Initial public health interventions delayed onset of SARS-CoV-2 community transmission after the introduction of the virus from international and regional migration in Zimbabwe. Global whole genome sequence data are essential to reveal major routes of spread and guide intervention strategies. FUNDING: WHO, Africa CDC, Biotechnology and Biological Sciences Research Council, Medical Research Council, National Institute for Health Research, and Genome Research Limited.

An optimised protocol for detection of SARS-CoV-2 in stool.

BACKGROUND: SARS-CoV-2 has been detected in stool samples of COVID-19 patients, with potential implications for faecal-oral transmission. Compared to nasopharyngeal swab samples, the complexity of the stool matrix poses a challenge in the detection of the virus that has not yet been solved. However, robust and reliable methods are needed to estimate the prevalence and persistence of SARS-CoV-2 in the gut and to ensure the safety of microbiome-based procedures such as faecal microbiota transplant (FMT). The aim of this study was to establish a sensitive and reliable method for detecting SARS-CoV-2 in stool samples. RESULTS: Stool samples from individuals free of SARS-CoV-2 were homogenised in saline buffer and spiked with a known titre of inactivated virus ranging from 50 to 750 viral particles per 100 mg stool. Viral particles were concentrated by ultrafiltration, RNA was extracted, and SARS-CoV-2 was detected via real-time reverse-transcription polymerase chain reaction (RT-qPCR) using the CDC primers and probes. The RNA extraction procedure we used allowed for the detection of SARS-CoV-2 via RT-qPCR in most of the stool samples tested. We could detect as few as 50 viral particles per 100 mg of stool. However, high variability was observed across samples at low viral titres. The primer set targeting the N1 region provided more reliable and precise results and for this primer set our method had a limit of detection of 1 viral particle per mg of stool. CONCLUSIONS: Here we describe a sensitive method for detecting SARS-CoV-2 in stool samples. This method can be used to establish the persistence of SARS-CoV-2 in stool and ensure the safety of clinical practices such as FMT.

Large-scale sequencing of SARS-CoV-2 genomes from one region allows detailed epidemiology and enables local outbreak management.

The COVID-19 pandemic has spread rapidly throughout the world. In the UK, the initial peak was in April 2020; in the county of Norfolk (UK) and surrounding areas, which has a stable, low-density population, over 3200 cases were reported between March and August 2020. As part of the activities of the national COVID-19 Genomics Consortium (COG-UK) we undertook whole genome sequencing of the SARS-CoV-2 genomes present in positive clinical samples from the Norfolk region. These samples were collected by four major hospitals, multiple minor hospitals, care facilities and community organizations within Norfolk and surrounding areas. We combined clinical metadata with the sequencing data from regional SARS-CoV-2 genomes to understand the origins, genetic variation, transmission and expansion (spread) of the virus within the region and provide context nationally. Data were fed back into the national effort for pandemic management, whilst simultaneously being used to assist local outbreak analyses. Overall, 1565 positive samples (172 per 100 000 population) from 1376 cases were evaluated; for 140 cases between two and six samples were available providing longitudinal data. This represented 42.6 % of all positive samples identified by hospital testing in the region and encompassed those with clinical need, and health and care workers and their families. In total, 1035 cases had genome sequences of sufficient quality to provide phylogenetic lineages. These genomes belonged to 26 distinct global lineages, indicating that there were multiple separate introductions into the region. Furthermore, 100 genetically distinct UK lineages were detected demonstrating local evolution, at a rate of ~2 SNPs per month, and multiple co-occurring lineages as the pandemic progressed. Our analysis: identified a discrete sublineage associated with six care facilities; found no evidence of reinfection in longitudinal samples; ruled out a nosocomial outbreak; identified 16 lineages in key workers which were not in patients, indicating infection control measures were effective; and found the D614G spike protein mutation which is linked to increased transmissibility dominates the samples and rapidly confirmed relatedness of cases in an outbreak at a food processing facility. The large-scale genome sequencing of SARS-CoV-2-positive samples has provided valuable additional data for public health epidemiology in the Norfolk region, and will continue to help identify and untangle hidden transmission chains as the pandemic evolves.

An inter-laboratory study to investigate the impact of the bioinformatics component on microbiome analysis using mock communities.

Despite the advent of whole genome metagenomics, targeted approaches (such as 16S rRNA gene amplicon sequencing) continue to be valuable for determining the microbial composition of samples. Amplicon microbiome sequencing can be performed on clinical samples from a normally sterile site to determine the aetiology of an infection (usually single pathogen identification) or samples from more complex niches such as human mucosa or environmental samples where multiple microorganisms need to be identified. The methodologies are frequently applied to determine both presence of micro-organisms and their quantity or relative abundance. There are a number of technical steps required to perform microbial community profiling, many of which may have appreciable precision and bias that impacts final results. In order for these methods to be applied with the greatest accuracy, comparative studies across different laboratories are warranted. In this study we explored the impact of the bioinformatic approaches taken in different laboratories on microbiome assessment using 16S rRNA gene amplicon sequencing results. Data were generated from two mock microbial community samples which were amplified using primer sets spanning five different variable regions of 16S rRNA genes. The PCR-sequencing analysis included three technical repeats of the process to determine the repeatability of their methods. Thirteen laboratories participated in the study, and each analysed the same FASTQ files using their choice of pipeline. This study captured the methods used and the resulting sequence annotation and relative abundance output from bioinformatic analyses. Results were compared to digital PCR assessment of the absolute abundance of each target representing each organism in the mock microbial community samples and also to analyses of shotgun metagenome sequence data. This ring trial demonstrates that the choice of bioinformatic analysis pipeline alone can result in different estimations of the composition of the microbiome when using 16S rRNA gene amplicon sequencing data. The study observed differences in terms of both presence and abundance of organisms and provides a resource for ensuring reproducible pipeline development and application. The observed differences were especially prevalent when using custom databases and applying high stringency operational taxonomic unit (OTU) cut-off limits. In order to apply sequencing approaches with greater accuracy, the impact of different analytical steps needs to be clearly delineated and solutions devised to harmonise microbiome analysis results.

Rapid metagenomics for diagnosis of bloodstream and respiratory tract nosocomial infections: current status and future prospects.

Introduction: Nosocomial infections represent a major problem for the health-care systems worldwide. Currently, diagnosis relies on microbiological culture, which is slow and has poor sensitivity. While waiting for a diagnosis, patients are treated with empiric broad spectrum antimicrobials, which are often inappropriate for the infecting pathogen. This results in poor patient outcomes, poor antimicrobial stewardship and increased costs for health-care systems.Areas covered: Clinical metagenomics (CMg), the application of metagenomic sequencing for the diagnosis of infection, has the potential to become a viable alternative to culture that can offer rapid results with high accuracy. In this article, we review current CMg methods for the diagnosis of nosocomial bloodstream (BSI) and lower respiratory-tract infections (LRTI).Expert opinion: CMg approaches are more accurate in LRTI compared to BSI. This is because BSIs are caused by low pathogen numbers in a high background of human cells. To overcome this, most approaches focus on cell-free DNA, but, to date, these tests are not accurate enough yet to replace blood culture. The higher pathogen numbers in LRTI samples make this a more suitable for CMg and accurate approaches have been developed, which are likely to be implemented in hospitals within the next 2-5 years.