SARS-CoV-2 evolution during treatment of chronic infection.

The spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is critical for virus infection through the engagement of the human ACE2 protein1 and is a major antibody target. Here we show that chronic infection with SARS-CoV-2 leads to viral evolution and reduced sensitivity to neutralizing antibodies in an immunosuppressed individual treated with convalescent plasma, by generating whole-genome ultra-deep sequences for 23 time points that span 101 days and using in vitro techniques to characterize the mutations revealed by sequencing. There was little change in the overall structure of the viral population after two courses of remdesivir during the first 57 days. However, after convalescent plasma therapy, we observed large, dynamic shifts in the viral population, with the emergence of a dominant viral strain that contained a substitution (D796H) in the S2 subunit and a deletion (ΔH69/ΔV70) in the S1 N-terminal domain of the spike protein. As passively transferred serum antibodies diminished, viruses with the escape genotype were reduced in frequency, before returning during a final, unsuccessful course of convalescent plasma treatment. In vitro, the spike double mutant bearing both ΔH69/ΔV70 and D796H conferred modestly decreased sensitivity to convalescent plasma, while maintaining infectivity levels that were similar to the wild-type virus.The spike substitution mutant D796H appeared to be the main contributor to the decreased susceptibility to neutralizing antibodies, but this mutation resulted in an infectivity defect. The spike deletion mutant ΔH69/ΔV70 had a twofold higher level of infectivity than wild-type SARS-CoV-2, possibly compensating for the reduced infectivity of the D796H mutation. These data reveal strong selection on SARS-CoV-2 during convalescent plasma therapy, which is associated with the emergence of viral variants that show evidence of reduced susceptibility to neutralizing antibodies in immunosuppressed individuals.

Locations and structures of influenza A virus packaging-associated signals and other functional elements via an in silico pipeline for predicting constrained features in RNA viruses.

Influenza A virus contains regions of its segmented genome associated with ability to package the segments into virions, but many such regions are poorly characterised. We provide detailed predictions of the key locations within these packaging-associated regions, and their structures, by applying a recently-improved pipeline for delineating constrained regions in RNA viruses and applying structural prediction algorithms. We find and characterise other known constrained regions within influenza A genomes, including the region associated with the PA-X frameshift, regions associated with alternative splicing, and constraint around the initiation motif for a truncated PB1 protein, PB1-N92, associated with avian viruses. We further predict the presence of constrained regions that have not previously been described. The extra characterisation our work provides allows investigation of these key regions for drug target potential, and points towards determinants of packaging compatibility between segments.

A scale-free analysis of the HIV-1 genome demonstrates multiple conserved regions of structural and functional importance.

HIV-1 replicates via a low-fidelity polymerase with a high mutation rate; strong conservation of individual nucleotides is highly indicative of the presence of critical structural or functional properties. Identifying such conservation can reveal novel insights into viral behaviour. We analysed 3651 publicly available sequences for the presence of nucleic acid conservation beyond that required by amino acid constraints, using a novel scale-free method that identifies regions of outlying score together with a codon scoring algorithm. Sequences with outlying score were further analysed using an algorithm for producing local RNA folds whilst accounting for alignment properties. 11 different conserved regions were identified, some corresponding to well-known cis-acting functions of the HIV-1 genome but also others whose conservation has not previously been noted. We identify rational causes for many of these, including cis functions, possible additional reading frame usage, a plausible mechanism by which the central polypurine tract primes second-strand DNA synthesis and a conformational stabilising function of a region at the 5' end of env.

A novel approach to finding conserved features in low-variability gene alignments characterises RNA motifs in SARS-CoV and SARS-CoV-2.

Collections of genetic sequences belonging to related organisms contain information on the evolutionary constraints to which the organisms have been subjected. Heavily constrained regions can be investigated to understand their roles in an organism's life cycle, and drugs can be sought to disrupt these roles. In organisms with low genetic diversity, such as newly-emerged pathogens, it is key to obtain this information early to develop new treatments. Here, we present methods that ensure we can leverage all the information available in a low-signal, low-noise set of sequences, to find contiguous regions of relatively conserved nucleic acid. We demonstrate the application of these methods by analysing over 5 million genome sequences of the recently-emerged RNA virus SARS-CoV-2 and correlating these results with an analysis of 119 genome sequences of SARS-CoV. We propose the precise location of a previously described packaging signal, and discuss explanations for other regions of high conservation.

Multiplex MinION sequencing suggests enteric adenovirus F41 genetic diversity comparable to pre-COVID-19 era.

Human adenovirus F41 causes acute gastroenteritis in children, and has recently been associated with an apparent increase in paediatric hepatitis of unknown aetiology in the UK, with further cases reported in multiple countries. Relatively little is known about the genetic diversity of adenovirus F41 in UK children; and it is unclear what, if any, impact the COVID-19 pandemic has had on viral diversity in the UK. Methods that allow F41 to be sequenced from clinical samples without the need for viral culture are required to provide the genomic data to address these questions. Therefore, we evaluated an overlapping-amplicon method of sequencing adenovirus genomes from clinical samples using Oxford Nanopore technology. We applied this method to a small sample of adenovirus-species-F-positive extracts collected as part of standard care in the East of England region in January-May 2022. This method produced genomes with >75 % coverage in 13/22 samples and >50 % coverage in 19/22 samples. We identified two F41 lineages present in paediatric patients in the East of England in 2022. Where F41 genomes from paediatric hepatitis cases were available (n=2), these genomes fell within the diversity of F41 from the UK and continental Europe sequenced before and after the 2020-2021 phase of the COVID-19 pandemic. Our analyses suggest that overlapping amplicon sequencing is an appropriate method for generating F41 genomic data from high-virus-load clinical samples, and currently circulating F41 viral lineages were present in the UK and Europe before the COVID-19 pandemic.

Serology versus nucleic acid amplification to diagnose acute hepatitis E, United Kingdom, 2014-18.

OBJECTIVES: Diagnosing hepatitis E infection usually involves specific IgM testing, but sensitivity/specificity concerns mean many guidelines and practices include confirmatory tests. We studied whether additional information confirmatory tests provide justifies their use. METHODS: We examined 9131 records of anti-hepatitis E IgM assays, 7615 of IgG assays, and 1726 of RT-PCR assays from our regional laboratory, spanning October 2014-October 2018. We paired 495 IgM assay results with a RT-PCR result. We examined whether IgM results predicted PCR results, reviewed discrepant pairs, and investigated the correlation between IgG and PCR results in patients with strongly reactive IgM assays. RESULTS: Anti-hepatitis E IgM titres are bimodal. A high cut-off value optimises prediction of RNA detectability. 7/404 low-IgM samples had detectable RNA, 6 from immunosuppressed patients. 26/91 high-IgM samples did not have detectable RNA. In high-IgM samples, RNA detectability was not associated with IgG titre (one-tailed Mann-Whitney U test, p = 0.14). CONCLUSIONS: In immunocompetent patients, tests beyond IgM seldom add clinically useful information. In patients with immunocompromise, IgM and RNA could contribute information. Additional tests' extra costs/intervention delays cannot be justified. IgM assay cut-offs should reflect titres' bimodal distribution, with values standardised using international units.

SARS-CoV-2 screening: effectiveness and risk of increasing transmission.

Testing asymptomatic people for SARS-CoV-2 aims to reduce COVID-19 transmission. Screening programmes' effectiveness depends upon testing strategy, sample handling logistics, test sensitivity and individual behaviour, in addition to dynamics of viral transmission. The interaction between these factors is not fully characterized. We investigated the interaction between these factors to determine how to optimize reduction of transmission. We estimate that under idealistic assumptions 70% of transmission may be averted, but under realistic assumptions only 7% may be averted. We show that programmes that overwhelm laboratory capacity or reduce isolation of those with minor symptoms have increased transmission compared with those that do not: programmes need to be designed to avoid these issues, or they will be ineffective or even counter-productive. Our model allows optimal selection of whom to test, quantifies the balance between accuracy and timeliness, and quantifies potential impacts of behavioural interventions. We anticipate our model can be used to understand optimal screening strategies for other infectious diseases with substantially different dynamics.

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.

A new method for detecting signal regions in ordered sequences of real numbers, and application to viral genomic data.

We present a fast, robust and parsimonious approach to detecting signals in an ordered sequence of numbers. Our motivation is in seeking a suitable method to take a sequence of scores corresponding to properties of positions in virus genomes, and find outlying regions of low scores. Suitable statistical methods without using complex models or making many assumptions are surprisingly lacking. We resolve this by developing a method that detects regions of low score within sequences of real numbers. The method makes no assumptions a priori about the length of such a region; it gives the explicit location of the region and scores it statistically. It does not use detailed mechanistic models so the method is fast and will be useful in a wide range of applications. We present our approach in detail, and test it on simulated sequences. We show that it is robust to a wide range of signal morphologies, and that it is able to capture multiple signals in the same sequence. Finally we apply it to viral genomic data to identify regions of evolutionary conservation within influenza and rotavirus.