Phenotyping the virulence of SARS-CoV-2 variants in hamsters by digital pathology and machine learning (preprint)

SARS-CoV-2 has continued to evolve throughout the COVID-19 pandemic, giving rise to multiple variants of concern (VOCs) with different biological properties. As the pandemic progresses, it will be essential to test in near real time the potential of any new emerging variant to cause severe disease. BA.1 (Omicron) was shown to be attenuated compared to the previous VOCs like Delta, but it is possible that newly emerging variants may regain a virulent phenotype. Hamsters have been proven to be an exceedingly good model for SARS-CoV-2 pathogenesis. Here, we aimed to develop robust quantitative pipelines to assess the virulence of SARS-CoV-2 variants in hamsters. We used various approaches including RNAseq, RNA in situ hybridization, immunohistochemistry, and digital pathology, including software assisted whole section imaging and downstream automatic analyses enhanced by machine learning, to develop methods to assess and quantify virus-induced pulmonary lesions in an unbiased manner. Initially, we used Delta and Omicron to develop our experimental pipelines. We then assessed the virulence of recent Omicron sub-lineages including BA.5, XBB, BQ.1.18, BA.2 and BA.2.75. We show that in experimentally infected hamsters, accurate quantification of alveolar epithelial hyperplasia and macrophage infiltrates represent robust markers for assessing the extent of virus-induced pulmonary pathology, and hence virus virulence. In addition, using these pipelines, we could reveal how some Omicron sub-lineages (e.g., BA.2.75) have regained virulence compared to the original BA.1. Finally, to maximise the utility of the digital pathology pipelines reported in our study, we developed an online repository containing representative whole organ histopathology sections that can be visualised at variable magnifications (https://covid-atlas.cvr.gla.ac.uk). Overall, this pipeline can provide unbiased and invaluable data for rapidly assessing newly emerging variants and their potential to cause severe disease.

Compositional analysis of Sindbis virus ribonucleoproteins reveals an extensive co-opting of key nuclear RNA-binding proteins (preprint)

The expansion of tropical mosquito habitats and associated arboviruses is a risk for human health, and it thus becomes fundamental to identify new antiviral strategies. In this study we employ a new approach to elucidate the composition of the ribonucleoproteins (RNPs) of a prototypical arbovirus called Sindbis (SINV). SINV RNPs contain 453 cellular and 6 viral proteins, many of these proteins are nuclear in uninfected cells and redistribute to the cytoplasm upon infection. These findings suggest that SINV RNAs act as spiderwebs, capturing host factors required for viral replication and gene expression in the cytoplasm. Functional perturbation of several of these host proteins causes profound effects in virus infection, as illustrated here with the tRNA ligase complex. Moreover, inhibition of viral RNP components with available drugs hampers the infection of a wide range of viruses, opening new avenues for the development of broad-spectrum therapies. Research highlightsO_LISINV RNA interactome includes 453 cellular and 6 viral proteins. C_LIO_LINuclear RBPs that interact with SINV RNA are selectively redistributed to the cytoplasm upon infection C_LIO_LIThe tRNA ligase complex plays major regulatory roles in SINV and SARS-CoV- 2 replication C_LIO_LIThe SINV RNA interactome is enriched in pan-viral regulators with therapeutic potential. C_LI