Blood gene expression predicts intensive care unit admission in hospitalised patients with COVID-19.

Background: The COVID-19 pandemic has created pressure on healthcare systems worldwide. Tools that can stratify individuals according to prognosis could allow for more efficient allocation of healthcare resources and thus improved patient outcomes. It is currently unclear if blood gene expression signatures derived from patients at the point of admission to hospital could provide useful prognostic information. Methods: Gene expression of whole blood obtained at the point of admission from a cohort of 78 patients hospitalised with COVID-19 during the first wave was measured by high resolution RNA sequencing. Gene signatures predictive of admission to Intensive Care Unit were identified and tested using machine learning and topological data analysis, TopMD. Results: The best gene expression signature predictive of ICU admission was defined using topological data analysis with an accuracy: 0.72 and ROC AUC: 0.76. The gene signature was primarily based on differentially activated pathways controlling epidermal growth factor receptor (EGFR) presentation, Peroxisome proliferator-activated receptor alpha (PPAR-α) signalling and Transforming growth factor beta (TGF-ß) signalling. Conclusions: Gene expression signatures from blood taken at the point of admission to hospital predicted ICU admission of treatment naïve patients with COVID-19.

The P323L substitution in the SARS-CoV-2 polymerase (NSP12) confers a selective advantage during infection.

BACKGROUND: The mutational landscape of SARS-CoV-2 varies at the dominant viral genome sequence and minor genomic variant population. During the COVID-19 pandemic, an early substitution in the genome was the D614G change in the spike protein, associated with an increase in transmissibility. Genomes with D614G are accompanied by a P323L substitution in the viral polymerase (NSP12). However, P323L is not thought to be under strong selective pressure. RESULTS: Investigation of P323L/D614G substitutions in the population shows rapid emergence during the containment phase and early surge phase during the first wave. These substitutions emerge from minor genomic variants which become dominant viral genome sequence. This is investigated in vivo and in vitro using SARS-CoV-2 with P323 and D614 in the dominant genome sequence and L323 and G614 in the minor variant population. During infection, there is rapid selection of L323 into the dominant viral genome sequence but not G614. Reverse genetics is used to create two viruses (either P323 or L323) with the same genetic background. L323 shows greater abundance of viral RNA and proteins and a smaller plaque morphology than P323. CONCLUSIONS: These data suggest that P323L is an important contribution in the emergence of variants with transmission advantages. Sequence analysis of viral populations suggests it may be possible to predict the emergence of a new variant based on tracking the frequency of minor variant genomes. The ability to predict an emerging variant of SARS-CoV-2 in the global landscape may aid in the evaluation of medical countermeasures and non-pharmaceutical interventions.

Characterisation of SARS-CoV-2 genomic variation in response to molnupiravir treatment in the AGILE Phase IIa clinical trial.

Molnupiravir is an antiviral, currently approved by the UK Medicines and Healthcare products Regulatory Agency (MHRA) for treating at-risk COVID-19 patients, that induces lethal error catastrophe in SARS-CoV-2. How this drug-induced mechanism of action might impact the emergence of resistance mutations is unclear. To investigate this, we used samples from the AGILE Candidate Specific Trial (CST)-2 (clinical trial number NCT04746183). The primary outcomes of AGILE CST-2 were to measure the drug safety and antiviral efficacy of molnupiravir in humans (180 participants randomised 1:1 with placebo). Here, we describe the pre-specified exploratory virological endpoint of CST-2, which was to determine the possible genomic changes in SARS-CoV-2 induced by molnupiravir treatment. We use high-throughput amplicon sequencing and minor variant analysis to characterise viral genomics in each participant whose longitudinal samples (days 1, 3 and 5 post-randomisation) pass the viral genomic quality criteria (n = 59 for molnupiravir and n = 65 for placebo). Over the course of treatment, no specific mutations were associated with molnupiravir treatment. We find that molnupiravir significantly increased the transition:transversion mutation ratio in SARS-CoV-2, consistent with the model of lethal error catastrophe. This study highlights the utility of examining intra-host virus populations to strengthen the prediction, and surveillance, of potential treatment-emergent adaptations.

Blood gene expression predicts intensive care unit admission in hospitalised patients with COVID-19

Background The COVID-19 pandemic has created pressure on healthcare systems worldwide. Tools that can stratify individuals according to prognosis could allow for more efficient allocation of healthcare resources and thus improved patient outcomes. It is currently unclear if blood gene expression signatures derived from patients at the point of admission to hospital could provide useful prognostic information. Methods Gene expression of whole blood obtained at the point of admission from a cohort of 78 patients hospitalised with COVID-19 during the first wave was measured by high resolution RNA sequencing. Gene signatures predictive of admission to Intensive Care Unit were identified and tested using machine learning and topological data analysis, TopMD. Results The best gene expression signature predictive of ICU admission was defined using topological data analysis with an accuracy: 0.72 and ROC AUC: 0.76. The gene signature was primarily based on differentially activated pathways controlling epidermal growth factor receptor (EGFR) presentation, Peroxisome proliferator-activated receptor alpha (PPAR-α) signalling and Transforming growth factor beta (TGF-β) signalling. Conclusions Gene expression signatures from blood taken at the point of admission to hospital predicted ICU admission of treatment naïve patients with COVID-19.

Evaluating the Immune Response in Treatment-Naive Hospitalised Patients With Influenza and COVID-19.

The worldwide COVID-19 pandemic has claimed millions of lives and has had a profound effect on global life. Understanding the body's immune response to SARS-CoV-2 infection is crucial in improving patient management and prognosis. In this study we compared influenza and SARS-CoV-2 infected patient cohorts to identify distinct blood transcript abundances and cellular composition to better understand the natural immune response associated with COVID-19, compared to another viral infection being influenza, and identify a prognostic signature of COVID-19 patient outcome. Clinical characteristics and peripheral blood were acquired upon hospital admission from two well characterised cohorts, a cohort of 88 patients infected with influenza and a cohort of 80 patients infected with SARS-CoV-2 during the first wave of the pandemic and prior to availability of COVID-19 treatments and vaccines. Gene transcript abundances, enriched pathways and cellular composition were compared between cohorts using RNA-seq. A genetic signature between COVID-19 survivors and non-survivors was assessed as a prognostic predictor of COVID-19 outcome. Contrasting immune responses were detected with an innate response elevated in influenza and an adaptive response elevated in COVID-19. Additionally ribosomal, mitochondrial oxidative stress and interferon signalling pathways differentiated the cohorts. An adaptive immune response was associated with COVID-19 survival, while an inflammatory response predicted death. A prognostic transcript signature, associated with circulating immunoglobulins, nucleosome assembly, cytokine production and T cell activation, was able to stratify COVID-19 patients likely to survive or die. This study provides a unique insight into the immune responses of treatment naïve patients with influenza or COVID-19. The comparison of immune response between COVID-19 survivors and non-survivors enables prognostication of COVID-19 patients and may suggest potential therapeutic strategies to improve survival.

Analysis of SARS-CoV-2 known and novel subgenomic mRNAs in cell culture, animal model, and clinical samples using LeTRS, a bioinformatic tool to identify unique sequence identifiers.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a complex strategy for the transcription of viral subgenomic mRNAs (sgmRNAs), which are targets for nucleic acid diagnostics. Each of these sgmRNAs has a unique 5' sequence, the leader-transcriptional regulatory sequence gene junction (leader-TRS junction), that can be identified using sequencing. High-resolution sequencing has been used to investigate the biology of SARS-CoV-2 and the host response in cell culture and animal models and from clinical samples. LeTRS, a bioinformatics tool, was developed to identify leader-TRS junctions and can be used as a proxy to quantify sgmRNAs for understanding virus biology. LeTRS is readily adaptable for other coronaviruses such as Middle East respiratory syndrome coronavirus or a future newly discovered coronavirus. LeTRS was tested on published data sets and novel clinical samples from patients and longitudinal samples from animal models with coronavirus disease 2019. LeTRS identified known leader-TRS junctions and identified putative novel sgmRNAs that were common across different mammalian species. This may be indicative of an evolutionary mechanism where plasticity in transcription generates novel open reading frames, which can then subject to selection pressure. The data indicated multiphasic abundance of sgmRNAs in two different animal models. This recapitulates the relative sgmRNA abundance observed in cells at early points in infection but not at late points. This pattern is reflected in some human nasopharyngeal samples and therefore has implications for transmission models and nucleic acid-based diagnostics. LeTRS provides a quantitative measure of sgmRNA abundance from sequencing data. This can be used to assess the biology of SARS-CoV-2 (or other coronaviruses) in clinical and nonclinical samples, especially to evaluate different variants and medical countermeasures that may influence viral RNA synthesis.

Analysis of SARS-CoV-2 in Nasopharyngeal Samples from Patients with COVID-19 Illustrates Population Variation and Diverse Phenotypes, Placing the Growth Properties of Variants of Concern in Context with Other Lineages.

New variants of SARS-CoV-2 are continuing to emerge and dominate the global sequence landscapes. Several variants have been labeled variants of concern (VOCs) because they may have a transmission advantage, increased risk of morbidity and/or mortality, or immune evasion upon a background of prior infection or vaccination. Placing the VOCs in context with the underlying variability of SARS-CoV-2 is essential in understanding virus evolution and selection pressures. Dominant genome sequences and the population genetics of SARS-CoV-2 in nasopharyngeal swabs from hospitalized patients were characterized. Nonsynonymous changes at a minor variant level were identified. These populations were generally preserved when isolates were amplified in cell culture. To place the Alpha, Beta, Delta, and Omicron VOCs in context, their growth was compared to clinical isolates of different lineages from earlier in the pandemic. The data indicated that the growth in cell culture of the Beta variant was more than that of the other variants in Vero E6 cells but not in hACE2-A549 cells. Looking at each time point, Beta grew more than the other VOCs in hACE2-A549 cells at 24 to 48 h postinfection. At 72 h postinfection there was no difference in the growth of any of the variants in either cell line. Overall, this work suggested that exploring the biology of SARS-CoV-2 is complicated by population dynamics and that these need to be considered with new variants. In the context of variation seen in other coronaviruses, the variants currently observed for SARS-CoV-2 are very similar in terms of their clinical spectrum of disease. IMPORTANCE SARS-CoV-2 is the causative agent of COVID-19. The virus has spread across the planet, causing a global pandemic. In common with other coronaviruses, SARS-CoV-2 genomes can become quite diverse as a consequence of replicating inside cells. This has given rise to multiple variants from the original virus that infected humans. These variants may have different properties and in the context of a widespread vaccination program may render vaccines less effective. Our research confirms the degree of genetic diversity of SARS-CoV-2 in patients. By comparing the growth of previous variants to the pattern seen with four variants of concern (VOCs) (Alpha, Beta, Delta, and Omicron), we show that, at least in cells, Beta variant growth exceeds that of Alpha, Delta, and Omicron VOCs at 24 to 48 h in both Vero E6 and hACE2-A549 cells, but by 72 h postinfection, the amount of virus is not different from that of the other VOCs.

Mutations that adapt SARS-CoV-2 to mink or ferret do not increase fitness in the human airway.

SARS-CoV-2 has a broad mammalian species tropism infecting humans, cats, dogs, and farmed mink. Since the start of the 2019 pandemic, several reverse zoonotic outbreaks of SARS-CoV-2 have occurred in mink, one of which reinfected humans and caused a cluster of infections in Denmark. Here we investigate the molecular basis of mink and ferret adaptation and demonstrate the spike mutations Y453F, F486L, and N501T all specifically adapt SARS-CoV-2 to use mustelid ACE2. Furthermore, we risk assess these mutations and conclude mink-adapted viruses are unlikely to pose an increased threat to humans, as Y453F attenuates the virus replication in human cells and all three mink adaptations have minimal antigenic impact. Finally, we show that certain SARS-CoV-2 variants emerging from circulation in humans may naturally have a greater propensity to infect mustelid hosts and therefore these species should continue to be surveyed for reverse zoonotic infections.

Amplicon and Metagenomic Analysis of Middle East Respiratory Syndrome (MERS) Coronavirus and the Microbiome in Patients with Severe MERS.

Middle East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic infection that emerged in the Middle East in 2012. Symptoms range from mild to severe and include both respiratory and gastrointestinal illnesses. The virus is mainly present in camel populations with occasional zoonotic spill over into humans. The severity of infection in humans is influenced by numerous factors, and similar to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), underlying health complications can play a major role. Currently, MERS-CoV and SARS-CoV-2 are coincident in the Middle East and thus a rapid way of sequencing MERS-CoV to derive genotype information for molecular epidemiology is needed. Additionally, complicating factors in MERS-CoV infections are coinfections that require clinical management. The ability to rapidly characterize these infections would be advantageous. To rapidly sequence MERS-CoV, an amplicon-based approach was developed and coupled to Oxford Nanopore long read length sequencing. This and a metagenomic approach were evaluated with clinical samples from patients with MERS. The data illustrated that whole-genome or near-whole-genome information on MERS-CoV could be rapidly obtained. This approach provided data on both consensus genomes and the presence of minor variants, including deletion mutants. The metagenomic analysis provided information of the background microbiome. The advantage of this approach is that insertions and deletions can be identified, which are the major drivers of genotype change in coronaviruses. IMPORTANCE Middle East respiratory syndrome coronavirus (MERS-CoV) emerged in late 2012 in Saudi Arabia. The virus is a serious threat to people not only in the Middle East but also in the world and has been detected in over 27 countries. MERS-CoV is spreading in the Middle East and neighboring countries, and approximately 35% of reported patients with this virus have died. This is the most severe coronavirus infection so far described. Saudi Arabia is a destination for many millions of people in the world who visit for religious purposes (Umrah and Hajj), and so it is a very vulnerable area, which imposes unique challenges for effective control of this epidemic. The significance of our study is that clinical samples from patients with MERS were used for rapid in-depth sequencing and metagenomic analysis using long read length sequencing.

Tissue-Specific Immunopathology in Fatal COVID-19.

Rationale: In life-threatening coronavirus disease (COVID-19), corticosteroids reduce mortality, suggesting that immune responses have a causal role in death. Whether this deleterious inflammation is primarily a direct reaction to the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or an independent immunopathologic process is unknown.Objectives: To determine SARS-CoV-2 organotropism and organ-specific inflammatory responses and the relationships among viral presence, inflammation, and organ injury.Methods: Tissue was acquired from 11 detailed postmortem examinations. SARS-CoV-2 organotropism was mapped by using multiplex PCR and sequencing, with cellular resolution achieved by in situ viral S (spike) protein detection. Histologic evidence of inflammation was quantified from 37 anatomic sites, and the pulmonary immune response was characterized by using multiplex immunofluorescence.Measurements and Main Results: Multiple aberrant immune responses in fatal COVID-19 were found, principally involving the lung and reticuloendothelial system, and these were not clearly topologically associated with the virus. Inflammation and organ dysfunction did not map to the tissue and cellular distribution of SARS-CoV-2 RNA and protein between or within tissues. An arteritis was identified in the lung, which was further characterized as a monocyte/myeloid-rich vasculitis, and occurred together with an influx of macrophage/monocyte-lineage cells into the pulmonary parenchyma. In addition, stereotyped abnormal reticuloendothelial responses, including excessive reactive plasmacytosis and iron-laden macrophages, were present and dissociated from viral presence in lymphoid tissues.Conclusions: Tissue-specific immunopathology occurs in COVID-19, implicating a significant component of the immune-mediated, virus-independent immunopathologic process as a primary mechanism in severe disease. Our data highlight novel immunopathologic mechanisms and validate ongoing and future efforts to therapeutically target aberrant macrophage and plasma-cell responses as well as promote pathogen tolerance in COVID-19.

Amplicon-Based Detection and Sequencing of SARS-CoV-2 in Nasopharyngeal Swabs from Patients With COVID-19 and Identification of Deletions in the Viral Genome That Encode Proteins Involved in Interferon Antagonism.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). Sequencing the viral genome as the outbreak progresses is important, particularly in the identification of emerging isolates with different pathogenic potential and to identify whether nucleotide changes in the genome will impair clinical diagnostic tools such as real-time PCR assays. Although single nucleotide polymorphisms and point mutations occur during the replication of coronaviruses, one of the biggest drivers in genetic change is recombination. This can manifest itself in insertions and/or deletions in the viral genome. Therefore, sequencing strategies that underpin molecular epidemiology and inform virus biology in patients should take these factors into account. A long amplicon/read length-based RT-PCR sequencing approach focused on the Oxford Nanopore MinION/GridION platforms was developed to identify and sequence the SARS-CoV-2 genome in samples from patients with or suspected of COVID-19. The protocol, termed Rapid Sequencing Long Amplicons (RSLAs) used random primers to generate cDNA from RNA purified from a sample from a patient, followed by single or multiplex PCRs to generate longer amplicons of the viral genome. The base protocol was used to identify SARS-CoV-2 in a variety of clinical samples and proved sensitive in identifying viral RNA in samples from patients that had been declared negative using other nucleic acid-based assays (false negative). Sequencing the amplicons revealed that a number of patients had a proportion of viral genomes with deletions.