ABSTRACT
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 3,200 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 organisations 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, 1,565 positive samples (172 per 100,000 population) from 1,376 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. 1,035 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 sublineage associated with 6 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; 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. Major pointsIn Norfolk and surrounding regions O_LI100 distinct UK lineages were identified. C_LIO_LI16 UK lineages found in key workers were not observed in patients or in community care. C_LIO_LI172 genomes from SARS-CoV-2 positive samples sequenced per 100,000 population representing 42.6% of all positive cases. C_LIO_LISARS-CoV-2 genomes from 1035 cases sequenced to a high quality. C_LIO_LIOnly 5 countries, out of 103, have sequenced more SARS-CoV-2 genomes than have been sequenced in Norfolk for this paper. C_LIO_LISamples covered the entire first wave, March to August 2020. C_LIO_LIStable evolutionary rate of 2 SNPs per month. C_LIO_LID614G mutation is the dominant genotype and associated with increased transmission. C_LIO_LINo evidence of reinfection in 42 cases with longitudinal samples. C_LIO_LIWGS identified a sublineage associated with care facilities. C_LIO_LIWGS ruled out nosocomial outbreaks. C_LIO_LIRapid WGS confirmed the relatedness of cases from an outbreak at a food processing facility. C_LI
ABSTRACT
The COVID-19 pandemic has spread to almost every country in the world since it started in China in late 2019. Controlling the pandemic requires a multifaceted approach including whole genome sequencing to support public health interventions at local and national levels. One of the most widely used methods for sequencing is the ARTIC protocol, a tiling PCR approach followed by Oxford Nanopore sequencing (ONT) of up to 96 samples at a time. There is a need, however, for a flexible, platform agnostic, method that can provide multiple throughput options depending on changing requirements as the pandemic peaks and troughs. Here we present CoronaHiT, a method capable of multiplexing up to 96 small genomes on a single MinION flowcell or >384 genomes on Illumina NextSeq, using transposase mediated addition of adapters and PCR based addition of barcodes to ARTIC PCR products. We demonstrate the method by sequencing 95 and 59 SARS-CoV-2 genomes for routine and rapid outbreak response runs, respectively, on Nanopore and Illumina platforms and compare to the standard ARTIC LoCost nanopore method. Of the 154 samples sequenced using the three approaches, genomes with [≥] 90% coverage (GISAID criteria) were generated for 64.3% of samples for ARTIC LoCost, 71.4% for CoronaHiT-ONT, and 76.6% for CoronaHiT-Illumina and have almost identical clustering on a maximum likelihood tree. In conclusion, we demonstrate that CoronaHiT can multiplex up to 96 SARS-CoV-2 genomes per MinION flowcell and that Illumina sequencing can be performed on the same libraries, which will allow significantly higher throughput. CoronaHiT provides increased coverage for higher Ct samples, thereby increasing the number of high quality genomes that pass the GISAID QC threshold. This protocol will aid the rapid expansion of SARS-CoV-2 genome sequencing globally, to help control the pandemic.
ABSTRACT
Laboratory investigation of bacterial infections generally takes two days: one to grow the bacteria and another to identify them and to test their susceptibility. Meanwhile the patient is treated empirically, based on likely pathogens and local resistance rates. Many patients are over-treated to prevent under-treatment of a few, compromising antibiotic stewardship. Molecular diagnostics have potential to improve this situation by accelerating precise diagnoses and the early refinement of antibiotic therapy. They include: (i) the use of 'biomarkers' to swiftly distinguish patients with bacterial infection, and (ii) molecular bacteriology to identify pathogens and their resistance genes in clinical specimens, without culture. Biomarker interest centres on procalcitonin, which has given good results particularly for pneumonias, though broader biomarker arrays may prove superior in the future. PCRs already are widely used to diagnose a few infections (e.g. tuberculosis) whilst multiplexes are becoming available for bacteraemia, pneumonia and gastrointestinal infection. These detect likely pathogens, but are not comprehensive, particularly for resistance genes; there is also the challenge of linking pathogens and resistance genes when multiple organisms are present in a sample. Next-generation sequencing offers more comprehensive profiling, but obstacles include sensitivity when the bacterial load is low, as in bacteraemia, and the imperfect correlation of genotype and phenotype. In short, rapid molecular bacteriology presents great potential to improve patient treatments and antibiotic stewardship but faces many technical challenges; moreover it runs counter to the current nostrum of defining resistance in pharmacodynamic terms, rather than by the presence of a mechanism, and the policy of centralising bacteriology services.
