Characterising within-hospital SARS-CoV-2 transmission events: a retrospective analysis integrating epidemiological and viral genomic data from a UK tertiary care setting across two pandemic waves (preprint)

Objectives - To characterise within-hospital SARS-CoV-2 transmission across two waves of the COVID-19 pandemic. Design - A retrospective Bayesian modelling study to reconstruct transmission chains amongst 2181 patients and healthcare workers using combined viral genomic and epidemiological data. Setting - A large UK NHS Trust with over 1400 beds and employing approximately 17,000 staff. Participants - 780 patients and 522 staff testing SARS-CoV-2 positive between 1st March 2020 and 25th July 2020 (Wave 1); and 580 patients and 299 staff testing SARS-CoV-2 positive between 30th November 2020 and 24th January 2021 (Wave 2). Main outcome measures - Transmission pairs including who-infected-whom; location of transmission events in hospital; number of secondary cases from each individual, including differences in onward transmission from community and hospital onset patient cases. Results - Staff-to-staff transmission was estimated to be the most frequent transmission type during Wave 1 (31.6% of observed hospital-acquired infections; 95% CI 26.9 to 35.8%), decreasing to 12.9% (95% CI 9.5 to 15.9%) in Wave 2. Patient-to-patient transmissions increased from 27.1% in Wave 1 (95% CI 23.3 to 31.4%) to 52.1% (95% CI 48.0 to 57.1%) in Wave 2, to become the predominant transmission type. Over 50% of hospital-acquired infections were concentrated in 8/120 locations in Wave 1 and 10/93 locations in Wave 2. Approximately 40% to 50% of hospital-onset patient cases resulted in onward transmission compared to less than 4% of definite community-acquired cases. Conclusions - Prevention and control measures that evolved during the COVID-19 pandemic may have had a significant impact on reducing infections between healthcare workers, but were insufficient during the second wave to prevent a high number of patient-to-patient transmissions. As hospital-acquired cases appeared to drive most onward transmissions, more frequent and rapid identification and isolation of these cases will be required to break hospital transmission chains in subsequent pandemic waves

Altered Sub-Genomic RNA Expression in SARS-CoV-2 B.1.1.7 Infections (preprint)

SARS-CoV-2 lineage B.1.1.7 viruses are more transmissible, may lead to greater clinical severity, and result in modest reductions in antibody neutralization. subgenomic RNA (sgRNA) is produced by discontinuous transcription of the SARS-CoV-2 genome and is a crucial step in the SARS-CoV-2 life cycle. Applying our tool (periscope) to ARTIC Network Oxford Nanopore genomic sequencing data from 4400 SARS-CoV-2 positive clinical samples, we show that normalised sgRNA expression profiles are significantly increased in B.1.1.7 infections (n=879). This increase is seen over the previous dominant circulating lineage in the UK, B.1.177 (n=943), which is independent of genomic reads, E gene cycle threshold and day of illness when sampling occurred. A noncanonical subgenomic RNA which could represent ORF9b is significantly enriched in B.1.1.7 SARS-CoV-2 infections, potentially as a result of a triple nucleotide mutation leading to amino acid substitution D3L in nucleocapsid in this lineage which increases complementarity with the genomic leader sequence. These findings provide a unique insight into the biology of B.1.1.7 and support monitoring of sgRNA profiles in sequence data to evaluate emerging potential variants of concern.

Diagnosis of SARS-CoV-2 infection with LamPORE, a high-throughput platform combining loop-mediated isothermal amplification and nanopore sequencing (preprint)

LamPORE is a novel diagnostic platform for the detection of SARS-CoV-2 RNA that combines loop-mediated isothermal amplification with nanopore sequencing, which could potentially be used to analyse thousands of samples per day on a single instrument. We evaluated the performance of LamPORE against RT-PCR using RNA extracted from spiked respiratory samples and from stored nose and throat swabs collected at two UK hospitals. The limit of detection of LamPORE was 7-10 genome copies/microlitre of extracted RNA. This is above the limit achievable by RT-PCR but was not associated with a significant reduction of sensitivity in clinical samples. Positive clinical specimens came mostly from patients with acute symptomatic infection, and among these LamPORE had a diagnostic sensitivity of 99.1% (226/228 [95% CI 96.9-99.9%]). Among negative clinical specimens, including 153 with other respiratory pathogens detected, LamPORE had a diagnostic specificity of 99.6% (278/279 [98.0-100.0%]). Overall, 1.4% (7/514 [0.5-2.9]) of samples produced an indeterminate result on first testing, and repeat LamPORE testing on the same RNA extract had a reproducibility of 96.8% (478/494 [94.8-98.1]). This indicates that LamPORE has a similar performance to RT-PCR for the diagnosis of SARS-CoV-2 infection in symptomatic patients, and offers a promising approach to high-throughput testing.

periscope: sub-genomic RNA identification in SARS-CoV-2 ARTIC Network Nanopore Sequencing Data (preprint)

We have developed periscope, a tool for the detection and quantification of sub-genomic RNA in ARTIC network protocol generated Nanopore SARS-CoV-2 sequence data. We applied periscope to 1155 SARS-CoV-2 sequences from Sheffield, UK. Using a simple local alignment to detect reads which contain the leader sequence we were able to identify and quantify reads arising from canonical and non-canonical sub-genomic RNA. We were able to detect all canonical sub-genomic RNAs at expected abundances, with the exception of ORF10, suggesting that this is not a functional ORF. A number of recurrent non-canonical sub-genomic RNAs are detected. We show that the results are reproducible using technical replicates and determine the optimum number of reads for sub-genomic RNA analysis. Finally variants found in genomic RNA are transmitted to sub-genomic RNAs with high fidelity in most cases. This tool can be applied to tens of thousands of sequences worldwide to provide the most comprehensive analysis of SARS-CoV-2 sub-genomic RNA to date.