Dynamics of SARS-CoV-2 VOC neutralization and novel mAb reveal protection against Omicron (preprint)

To evaluate SARS-CoV-2 variants we isolated SARS-CoV-2 temporally during the pandemic starting with first appearance of virus in the Western hemisphere near Seattle, WA, USA, and isolated each known major variant class, revealing the dynamics of emergence and complete take-over of all new cases by current Omicron variants. We assessed virus neutralization in a first-ever full comparison across variants and evaluated a novel monoclonal antibody (Mab). We found that convalescence greater than 5-months provides little-to-no protection against SARS-CoV-2 variants, vaccination enhances immunity against variants with the exception of Omicron BA.1, and paired testing of vaccine sera against ancestral virus compared to Omicron BA.1 shows that 3-dose vaccine regimen provides over 50-fold enhanced protection against Omicron BA.1 compared to a 2-dose regimen. We also reveal a novel Mab that effectively neutralizes Omicron BA.1 and BA.2 variants over clinically-approved Mabs. Our observations underscore the need for continued vaccination efforts, with innovation for vaccine and Mab improvement, for protection against variants of SARS-CoV-2. SummaryWe isolated SARS-CoV-2 temporally starting with emergence of virus in the Western hemisphere. Neutralization analyses across all variant lineages show that vaccine-boost regimen provides protection against Omicron BA.1. We reveal a Mab that protects against Omicron BA.1 and BA.2 variants.

Design of Specific Primer Sets for the Detection of B.1.1.7, B.1.351 and P.1 SARS-CoV-2 Variants using Deep Learning (preprint)

As the COVID-19 pandemic persists, new SARS-CoV-2 variants with potentially dangerous features have been identified by the scientific community. Variant B.1.1.7 lineage clade GR from Global Initiative on Sharing All Influenza Data (GISAID) was first detected in the UK, and it appears to possess an increased transmissibility. At the same time, South African authorities reported variant B.1.351, that shares several mutations with B.1.1.7, and might also present high transmissibility. Even more recently, a variant labeled P.1 with 17 non-synonymous mutations was detected in Brazil. In such a situation, it is paramount to rapidly develop specific molecular tests to uniquely identify, contain, and study new variants. Using a completely automated pipeline built around deep learning techniques, we design primer sets specific to variant B.1.1.7, B.1.351, and P.1, respectively. Starting from sequences openly available in the GISAID repository, our pipeline was able to deliver the primer sets in just under 16 hours for each case study. In-silico tests show that the sequences in the primer sets present high accuracy and do not appear in samples from different viruses, nor in other coronaviruses or SARS-CoV-2 variants. The presented methodology can be exploited to swiftly obtain primer sets for each independent new variant, that can later be a part of a multiplexed approach for the initial diagnosis of COVID-19 patients. Furthermore, since our approach delivers primers able to differentiate between variants, it can be used as a second step of a diagnosis in cases already positive to COVID-19, to identify individuals carrying variants with potentially threatening features.

Personalized Virus Load Curves of SARS-CoV-2 Infection (preprint)

We introduce an explicit function that describes virus-load curves on a patient-specific level. This function is based on simple and intuitive model parameters. It allows virus load analysis without solving a full virus load dynamic model. We validate our model on data from influenza A as well as SARS-CoV-2 infection data for Macaque monkeys and humans. Further, we compare the virus load function to an established target model of virus dynamics, which shows an excellent fit. Our virus-load function offers a new way to analyse patient virus load data, and it can be used as input to higher level models for the physiological effects of a virus infection, for models of tissue damage, and to estimate patient risks.

Survey of peridomestic mammal susceptibility to SARS-CoV-2 infection (preprint)

Wild animals have been implicated as the origin of SARS-CoV-2, but it is largely unknown how the virus affects most wildlife species and if wildlife could ultimately serve as a reservoir for maintaining the virus outside the human population. Here we show that several common peridomestic species, including deer mice, bushy-tailed woodrats, and striped skunks, are susceptible to infection and can shed the virus in respiratory secretions. In contrast, we demonstrate that cottontail rabbits, fox squirrels, Wyoming ground squirrels, black-tailed prairie dogs, house mice, and racoons are not susceptible to SARS-CoV-2 infection. Our work expands upon the existing knowledge base of susceptible species and provides evidence that human-wildlife interactions could result in continued transmission of SARS-CoV-2.

Human Pre-Implantation Embryos Are Permissive to SARS-CoV-2 Entry (preprint)

Vertical transmission of SARS-CoV-2, the virus responsible for COVID-19, from parents to early embryos during conception could be catastrophic, but is contingent on the susceptibility of cells of the embryo to infection. Because presence of the SARS-CoV-2 virus has been reported in the human reproductive system, we assessed whether pre-implantation embryos are permissive to SARS-CoV-2 entry. RNA-seq and immunostaining studies revealed presence of two key entry factors in the trophectoderm of blastocyst-stage embryos, the ACE2 receptor and the TMPRSS2 protease. Exposure of blastocysts to fluorescent reporter virions pseudotyped with the SARS-CoV-2 Spike (S) glycoprotein revealed S-ACE2 dependent entry and fusion. These results indicate that human pre-implantation embryos can be infected by SARS-CoV-2, a finding pertinent to natural human conceptions and assisted reproductive technologies during and after the COVID-19 pandemic.

Publication practices during the COVID-19 pandemic: Biomedical preprints and peer-reviewed literature (preprint)

The coronavirus pandemic introduced many changes to our society, and deeply affected the established in biomedical sciences publication practices. In this article, we present a comprehensive study of the changes in scholarly publication landscape for biomedical sciences during the COVID-19 pandemic, with special emphasis on preprints posted on bioRxiv and medRxiv servers. We observe the emergence of a new category of preprint authors working in the fields of immunology, microbiology, infectious diseases, and epidemiology, who extensively used preprint platforms during the pandemic for sharing their immediate findings. The majority of these findings were works-in-progress unfitting for a prompt acceptance by refereed journals. The COVID-19 preprints that became peer-reviewed journal articles were often submitted to journals concurrently with the posting on a preprint server, and the entire publication cycle, from preprint to the online journal article, took on average 63 days. This included an expedited peer-review process of 43 days and journals production stage of 15 days, however there was a wide variation in publication delays between journals. Only one third of COVID-19 preprints posted during the first nine months of the pandemic appeared as peer-reviewed journal articles. These journal articles display high Altmetric Attention Scores further emphasizing a significance of COVID-19 research during 2020. This article will be relevant to editors, publishers, open science enthusiasts, and anyone interested in changes that the 2020 crisis transpired to publication practices and a culture of preprints in life sciences.

High-throughput screening of the ReFRAME, Pandemic Box, and COVID Box drug repurposing libraries against SARS-CoV2 nsp15 endoribonuclease to identify small-molecule inhibitors of viral activity. (preprint)

SARS-CoV-2 has caused a global pandemic, and has taken over 1.7 million lives as of mid-December, 2020. Although great progress has been made in the development of effective countermeasures, with several pharmaceutical companies approved or poised to deliver vaccines to market, there is still an unmet need of essential antiviral drugs with therapeutic impact for the treatment of moderate-to-severe COVID-19. Towards this goal, a high-throughput assay was used to screen SARS-CoV-2 nsp15 uracil-dependent endonuclease (endoU) function against 13 thousand compounds from drug and lead repurposing compound libraries. While over 80% of initial hit compounds were pan-assay inhibitory compounds, three hits were confirmed as nsp15 endoU inhibitors in the 1-20 M range in vitro. Furthermore, Exebryl-1, a {beta}-amyloid anti-aggregation molecule for Alzheimers therapy, was shown to have antiviral activity between 10 to 66 M, in VERO, Caco-2, and Calu-3 cells. Although the inhibitory concentrations determined for Exebryl-1 exceed those recommended for therapeutic intervention, our findings show great promise for further optimization of Exebryl-1 as an nsp15 endoU inhibitor and as a SARS-CoV-2 antiviral. Author summaryDrugs to treat COVID-19 are urgently needed. To address this, we searched libraries of drugs and drug-like molecules for inhibitors of an essential enzyme of the virus that causes COVID-19, SARS-CoV-2 nonstructural protein (nsp)15. We found several molecules that inhibited the nsp15 enzyme function and one was shown to be active in inhibiting the SARS-CoV-2 virus. This demonstrates that searching for SARS-CoV-2 nsp15 inhibitors can lead inhibitors of SARS-CoV-2, and thus therapeutics for COVID-19. We are currently working to see if these inhibitors could be turned into a drug to treat COVID-19.

In silico detection of SARS-CoV-2 specific B-cell epitopes and validation in ELISA for serological diagnosis of COVID-19 (preprint)

Rapid generation of diagnostics is paramount to understand epidemiology and to control the spread of emerging infectious diseases such as COVID-19. Computational methods to predict serodiagnostic epitopes that are specific for the pathogen could help accelerate the development of new diagnostics. A systematic survey of 27 SARS-CoV-2 proteins was conducted to assess whether existing B-cell epitope prediction methods, combined with comprehensive mining of sequence databases and structural data, could predict whether a particular protein would be suitable for serodiagnosis. Nine of the predictions were validated with recombinant SARS-CoV-2 proteins in the ELISA format using plasma and sera from patients with SARS-CoV-2 infection, and a further 11 predictions were compared to the recent literature. Results appeared to be in agreement with 12 of the predictions, in disagreement with 3, while a further 5 were deemed inconclusive. We showed that two of our top five candidates, the N-terminal fragment of the nucleoprotein and the receptor-binding domain of the spike protein, have the highest sensitivity and specificity and signal-to-noise ratio for detecting COVID-19 sera/plasma by ELISA. Mixing the two antigens together for coating ELISA plates led to a sensitivity of 94% (N=80 samples from persons with RT-PCR confirmed SARS-CoV2 infection), and a specificity of 97.2% (N=106 control samples).