それぞれ独立して進化したにも関わらず、オミクロン株はBA.5とBA.2.75で初代よりも強毒化していた

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オミクロンで弱毒化したなどと放言していた奴は出てこい
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◆Phenotyping the virulence of SARS-CoV-2 variants in hamsters by digital pathology and machine learning【bioRxiv　2023年8月1日】

ABSTRACT

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.

INTRODUCTION

As the COVID-19 pandemic progressed over the past three years, the virus responsible for the disease, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has continued to evolve giving rise to a number of variants, some of which were defined as “variants of concern” (VOCs) by the WHO. These VOCs contain mutations, especially but not solely in the spike encoding S-gene, which may confer a selective advantage for example by increasing their transmissibility and/or immune evasion compared to the progenitor virus. To date, the WHO has recognised five VOCs: B.1.1.7 (Alpha); B.1.351 (Beta); P.1 (Gamma); B.1.617.2 (Delta) and B.1.1.529 (Omicron; henceforth referred as BA.1 to differentiate it from other sub-lineages). Since the emergence of the original BA.1 in November 2021 different sub-lineages have emerged. Soon after the BA.1 emergence, BA.2 became the predominant variant followed by a variety of BA.2 descendants, including BA.5 and BA.2.75, which became predominant in some geographical regions. Although both BA.5 and BA.2.75 diversified from BA.2, these two Omicron sub-lineages are phylogenetically separated from each other, suggesting that BA.5 and BA.2.75 emerged independently. BQ.1.18 is a sub-lineage of BA.5 while the XBB variant is a recombinant between BJ.1 (a BA.2.10 derivative) and BM.1.1.1 (a descendant of BA.2.75), which was first detected in September 2022 in India and spread significantly at the end of 2022.

In general, each new variant spreading globally tends to be more transmissible than the previous dominant variant. As population immunity increases, due to either vaccination or continuous virus exposure, it is likely that COVID-19 will adopt an endemic pattern, possibly with seasonal peaks, primed by variants evading pre-existing immunity in the population.

Understanding in “real-time” the degree of vaccine escape of any new variant is critical to determine vaccination policies. To this end, in vitro seroneutralisation assays have proven to be a useful surrogate to predict vaccine escape of SARS-CoV-2 variants. Virus virulence is another key phenotypic characteristic of any new variant requiring early assessment. The risk of severe disease and hospitalisation varies, with Alpha, Gamma and Delta VOCs carrying an increased risk of ICU admission compared to Beta and BA.1. Hence, the combination of increasing pre-existing immunity in the population together with the intrinsic attenuated characteristics of Omicron, has led to an overall decrease in the incidence of severe disease and mortality associated with COVID-19.

It is however more difficult to predict the trajectory of new variants with respect to virus virulence. Although BA.1 has been shown to be attenuated, and assuming that its transmission potential is maintained, there are no universal evolutionary pressures that may keep this phenotypic trait in newly emerging sub-lineages or new VOCs.

We and others have shown that the observed reduction in virulence of the BA.1 variant correlates to a change in the virus entry pathways in vitro, and importantly in reduced virulence in experimentally infected hamsters. Throughout the pandemic, small animal models have been used extensively to assess the virulence of wild type SARS-CoV-2 and emerging VOCs. These studies have provided invaluable data on disease pathogenesis, virus transmission and the efficacy of different anti-viral compounds or vaccines. Importantly, hamsters have been shown to be naturally susceptible to SARS-CoV-2 infection and to be able to transmit the virus to humans. In hamsters, BA.1 is unable to infect lung epithelial cells (unlike the original B.1 virus, Delta and other variants). In addition, in experimentally infected hamsters it is also possible to recapitulate the increased virulence of the Delta variant compared to B.1 shown in the human population.

Hence, although no animal model can fully recapitulate a human disease, hamsters represent an excellent model to dissect SARS-CoV-2 pathogenesis and determine the degree of virulence of newly emerging variants. To this end, many studies using experimentally infected hamsters, have focused on measuring in vivo viral replication, on identifying virus infected cells, and on examining pathogenic potential by measuring weight loss and assessing various histopathological criteria in general by qualitative scores. Here, we have developed unbiased and automated “digital pathology” methods to assess SARS-CoV-2 virulence. Digital pathology is a broad term that refers to a variety of systems to digitize pathology slides and associated meta-data, their storage, review, analysis, and enabling infrastructure. Computational analysis of whole scanned tissue sections provides the opportunity to quantify cells or histological features in wide representative areas of infected organs. We applied these pipelines with recently evolved variants (BA.5, BQ.1.18, BXX, BA.2 and BA.2.75) and showed that some of them have gained a more virulent phenotype compared to the parent BA.1. This pipeline can contribute to the rapid assessment of newly emerging variants and should prove invaluable as the pandemic enters the next phase. Furthermore, we created an online repository to share with the scientific community high resolution digitized whole organ scanned slides from this study, providing a wider context to histopathology micrographs for experimental models of COVID-19.