ABSTRACT
Persistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections may act as viral reservoirs that could seed future outbreaks 1-5, give rise to highly divergent lineages 6-8, and contribute to cases with post-acute Coronavirus disease 2019 (COVID-19) sequelae (Long Covid) 9,10. However, the population prevalence of persistent infections, their viral load kinetics, and evolutionary dynamics over the course of infections remain largely unknown. We identified 381 infections lasting at least 30 days, of which 54 lasted at least 60 days. These persistently infected individuals had more than 50% higher odds of self-reporting Long Covid compared to the infected controls, and we estimate that 0.09-0.5% of SARS-CoV-2 infections can become persistent and last for at least 60 days. In nearly 70% of the persistent infections we identified, there were long periods during which there were no consensus changes in virus sequences, consistent with prolonged presence of non-replicating virus. Our findings also suggest reinfections with the same major lineage are rare and that many persistent infections are characterised by relapsing viral load dynamics. Furthermore, we found a strong signal for positive selection during persistent infections, with multiple amino acid substitutions in the Spike and ORF1ab genes emerging independently in different individuals, including mutations that are lineage-defining for SARS-CoV-2 variants, at target sites for several monoclonal antibodies, and commonly found in immunocompromised patients 11-14. This work has significant implications for understanding and characterising SARS-CoV-2 infection, epidemiology, and evolution.
Subject(s)
Coronavirus Infections , Severe Acute Respiratory Syndrome , COVID-19ABSTRACT
The Office for National Statistics COVID-19 Infection Survey is a large household-based surveillance study based in the United Kingdom. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing sequenced samples collected up until 13th November 2021. We observed four distinct sweeps or partial-sweeps, by lineages B.1.177, B.1.1.7/Alpha, B.1.617.2/Delta, and finally AY.4.2, a sublineage of B.1.617.2, with each sweeping lineage having a distinct growth advantage compared to their predecessors. Evolution was characterised by steady rates of evolution and increasing diversity within lineages, but with step increases in divergence associated with each sweeping major lineage, leading to a faster overall rate of evolution and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens, particularly as routine PCR testing is phased out or in settings where large-scale sequencing is not feasible.
Subject(s)
COVID-19ABSTRACT
Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete understanding of potentially druggable immune mediators of disease. To advance this, we present a comprehensive multi-omic blood atlas in patients with varying COVID-19 severity and compare with influenza, sepsis and healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity revealed cells, their inflammatory mediators and networks as potential therapeutic targets, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Tensor and matrix decomposition of the overall dataset revealed feature groupings linked with disease severity and specificity. Our systems-based integrative approach and blood atlas will inform future drug development, clinical trial design and personalised medicine approaches for COVID-19.
Subject(s)
COVID-19 , SepsisABSTRACT
We gratefully acknowledge the UK COVID-19 Genomics Consortium (COG UK) for funding, and Public Health Wales / Cardiff University and MRC-University of Glasgow Centre for Virus Research for making their COG-UK sequence data publicly available. COG-UK is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) and Genome Research Limited, operating as the Wellcome Sanger Institute. The research was supported by the Wellcome Trust Core Award Grant Number 203141/Z/16/Z with funding from the NIHR Oxford BRC. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. We are deeply grateful to Robert Esnouf and the BMRC Research Computing team for unfailing assistance with computational infrastructure. We also thank Benjamin Carpenter and James Docker for assistance in the laboratory, and Lorne Lonie, Maria Lopopolo, Chris Allen, John Broxholme and the WHG high-throughput genomics team for sequencing and quality control. The HIV clone p92BR025.8 was obtained through the Centre For AIDS Reagents from Drs Beatrice Hahn and Feng Gao, and the UNAIDS Virus Network (courtesy of the NIH AIDS Research and Reference Reagent Program). KAL is supported by The Wellcome Trust and The Royal Society (107652/Z/15/Z). MH, LF, MdC, GMC, NO, LAD, DB, CF and TG are supported by Li Ka Shing Foundation funding awarded to CF. PS is supported by a Wellcome Investigator Award (WT103767MA). SummarySARS-CoV-2, the causative agent of COVID-19, emerged in late 2019 causing a global pandemic, with the United Kingdom (UK) one of the hardest hit countries. Rapid sequencing and publication of consensus genomes have enabled phylogenetic analysis of the virus, demonstrating SARS-CoV-2 evolves relatively slowly1, but with multiple sites in the genome that appear inconsistent with the overall consensus phylogeny2. To understand these discrepancies, we used veSEQ3, a targeted RNA-seq approach, to quantify minor allele frequencies in 413 clinical samples from two UK locations. We show that SARS-CoV-2 infections are characterised by extensive within-host diversity, which is frequently shared among infected individuals with patterns consistent with geographical structure. These results were reproducible in data from two other sequencing locations in the UK, where we find evidence of mixed infection by major circulating lineages with patterns that cannot readily be explained by artefacts in the data. We conclude that SARS-CoV-2 diversity is transmissible, and propose that geographic patterns are generated by transient co-circulation of distinct viral populations. Co-transmission of mixed populations could open opportunities for resolving clusters of transmission and understanding pathogenesis.