Deep learning forward and reverse primer design to detect SARS-CoV-2 emerging variants (preprint)

Surges that have been observed at different periods in the number of COVID-19 cases are associated with the emergence of multiple SARS-CoV-2 (Severe Acute Respiratory Virus) variants. The design of methods to support laboratory detection are crucial in the monitoring of these variants. Hence, in this paper, we develop a semi-automated method to design both forward and reverse primer sets to detect SARS-CoV-2 variants. To proceed, we train deep Convolution Neural Networks (CNNs) to classify labelled SARS-CoV-2 variants and identify partial genomic features needed for the forward and reverse Polymerase Chain Reaction (PCR) primer design. Our proposed approach supplements existing ones while promoting the emerging concept of neural network assisted primer design for PCR. Our CNN model was trained using a database of SARS-CoV-2 full-length genomes from GISAID and tested on a separate dataset from NCBI, with 98\% accuracy for the classification of variants. This result is based on the development of three different methods of feature extraction, and the selected primer sequences for each SARS-CoV-2 variant detection (except Omicron) were present in more than 95 \% of sequences in an independent set of 5000 same variant sequences, and below 5 \% in other independent datasets with 5000 sequences of each variant. In total, we obtain 22 forward and reverse primer pairs with flexible length sizes (18-25 base pairs) with an expected amplicon length ranging between 42 and 3322 nucleotides. Besides the feature appearance, in-silico primer checks confirmed that the identified primer pairs are suitable for accurate SARS-CoV-2 variant detection by means of PCR tests.

SARS-CoV-2 lineage B.1.1.7 is associated with greater disease severity among hospitalised women but not men (preprint)

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage B.1.1.7 has been associated with an increased rate of transmission and disease severity among subjects testing positive in the community. Its impact on hospitalised patients is less well documented. Methods We collected viral sequences and clinical data of patients admitted with SARS-CoV-2 and hospital-onset COVID-19 infections (HOCIs), sampled 16/11/2020 - 10/01/2021, from eight hospitals participating in the COG-UK-HOCI study. Associations between the variant and the outcomes of all-cause mortality and intensive therapy unit (ITU) admission were evaluated using mixed effects Cox models adjusted by age, sex, comorbidities, care home residence, pregnancy and ethnicity. Results Sequences were obtained from 2341 inpatients (HOCI cases = 786) and analysis of clinical outcomes was carried out in 2147 inpatients with all data available. The hazard ratio (HR) for mortality of B.1.1.7 compared to other lineages was 1.01 (95% CI 0.79-1.28, P=0.94) and for ITU admission was 1.01 (95% CI 0.75-1.37, P=0.96). Analysis of sex-specific effects of B.1.1.7 identified increased risk of mortality (HR 1.30, 95% CI 0.95-1.78) and ITU admission (HR 1.82, 95% CI 1.15-2.90) in females infected with the variant but not males (mortality HR 0.82, 95% CI 0.61-1.10; ITU HR 0.74, 95% CI 0.52-1.04). Conclusions In common with smaller studies of patients hospitalised with SARS-CoV-2 we did not find an overall increase in mortality or ITU admission associated with B.1.1.7 compared to other lineages. However, women with B.1.1.7 may be at an increased risk of admission to intensive care and at modestly increased risk of mortality.

Can a Quantitative Assessment of SARS-CoV-2 PCR Predict Degree of Severity and Outcomes in Critical Care Patients with COVID-19 (preprint)

Real-Time polymerase chain reaction (qPCR) is the gold standard diagnostic method for acute SARS-CoV-2 infection. Cycle threshold (Ct) is defined as the number of heating and cooling cycles required during the PCR process. Ct-values are inversely proportional to the amount of target nucleic acid in a sample. Our aim in this retrospective study was to determine the impact of serial SARS-CoV-2 qPCR Ct-values, among critically ill COVID-19 patients both prior and during intensive care unit (ICU) stay, on: mortality, need for mechanical ventilation (MV) and development of acute kidney injury (AKI). There was a continuous increment in Ct-values over the ICU stay from 1st-week through to 3rd-week. Although not significant, lower ICU 1st-week Ct-values were associated with Black ethnicity, increased need for MV and mortality. However, patients who had developed AKI at any stage of their illness had significantly lower Ct-values compared to those with normal renal function. When ICU 1st-week Ct-values are subcategorised as <20, 20-30 and >30 the 28-day survival probability was less for patients with Ct-values of <20.To our knowledge this is the first report showing the impact of Ct-values and outcomes, especially AKI, among patients at different time point’s prior to and during ICU stay. 

Severely ill COVID-19 patients display augmented functional properties in SARS-CoV-2-reactive CD8+ T cells (preprint)

The molecular properties of CD8+ T cells that respond to SARS-CoV-2 infection are not fully known. Here, we report on the single-cell transcriptomes of >80,000 virus-reactive CD8+ T cells from 39 COVID-19 patients and 10 healthy subjects. COVID-19 patients segregated into two groups based on whether the dominant CD8+ T cell response to SARS-CoV-2 was exhausted or not. SARS-CoV-2-reactive cells in the exhausted subset were increased in frequency and displayed lesser cytotoxicity and inflammatory features in COVID-19 patients with mild compared to severe illness. In contrast, SARS-CoV-2-reactive cells in the non-exhausted subsets from patients with severe disease showed enrichment of transcripts linked to co-stimulation, pro-survival NF-{kappa}B signaling, and anti-apoptotic pathways, suggesting the generation of robust CD8+ T cell memory responses in patients with severe COVID-19 illness. CD8+ T cells reactive to influenza and respiratory syncytial virus from healthy subjects displayed polyfunctional features. Cells with such features were mostly absent in SARS-CoV-2 responsive cells from both COVID-19 patients and healthy controls non-exposed to SARS-CoV-2. Overall, our single-cell analysis revealed substantial diversity in the nature of CD8+ T cells responding to SARS-CoV-2.

Single-Cell Transcriptomic Analysis of SARS-CoV-2 Reactive CD4 + T Cells (preprint)

The contribution of CD4+ T cells to protective or pathogenic immune responses to SARS-CoV-2 infection remains unknown. Here, we present large-scale single-cell transcriptomic analysis of viral antigen-reactive CD4+ T cells from 32 COVID-19 patients. In patients with severe disease compared to mild disease, we found increased proportions of cytotoxic follicular helper (TFH) cells and cytotoxic T helper cells (CD4-CTLs) responding to SARS-CoV-2, and reduced proportion of SARS-CoV-2 reactive regulatory T cells. Importantly, the CD4-CTLs were highly enriched for the expression of transcripts encoding chemokines that are involved in the recruitment of myeloid cells and dendritic cells to the sites of viral infection. Polyfunctional T helper (TH)1 cells and TH17 cell subsets were underrepresented in the repertoire of SARS-CoV-2-reactive CD4+ T cells compared to influenza-reactive CD4+ T cells. Together, our analyses provide so far unprecedented insights into the gene expression patterns of SARS-CoV-2 reactive CD4+ T cells in distinct disease severities.Funding: This work was funded by NIH grants U19AI142742 (P.V., A.S., C.H.O), U19AI118626 (P.V., A.S., G.S.), R01HL114093 (P.V., F.A., G.S.,), R35-GM128938 (F.A), S10RR027366 (BD FACSAria-II), S10OD025052 (Illumina Novaseq6000), the William K. Bowes Jr Foundation (P.V.), and Whittaker foundation (P.V., C.H.O.). Supported by the Wessex Clinical Research Network and National Institute of Health Research UK. Conflict of Interest: The authors declare no competing financial interests.Ethical Approval: Ethical approval for this study from the Berkshire Research Ethics Committee 20/SC/0155 and the Ethics Committee of La Jolla Institute for Immunology (LJI) was in place. Written consent was obtained from all subjects.

Single-cell transcriptomic analysis of SARS-CoV-2 reactive CD4+ T cells (preprint)

The contribution of CD4+ T cells to protective or pathogenic immune responses to SARS-CoV-2 infection remains unknown. Here, we present large-scale single-cell transcriptomic analysis of viral antigen-reactive CD4+ T cells from 32 COVID-19 patients. In patients with severe disease compared to mild disease, we found increased proportions of cytotoxic follicular helper (TFH) cells and cytotoxic T helper cells (CD4-CTLs) responding to SARS-CoV-2, and reduced proportion of SARS-CoV-2 reactive regulatory T cells. Importantly, the CD4-CTLs were highly enriched for the expression of transcripts encoding chemokines that are involved in the recruitment of myeloid cells and dendritic cells to the sites of viral infection. Polyfunctional T helper (TH)1 cells and TH17 cell subsets were underrepresented in the repertoire of SARS-CoV-2-reactive CD4+ T cells compared to influenza-reactive CD4+ T cells. Together, our analyses provide so far unprecedented insights into the gene expression patterns of SARS-CoV-2 reactive CD4+ T cells in distinct disease severities.