Single-cell RNA-sequencing reveals dysregulation of molecular programs associated with SARS-CoV-2 severity and outcomes in patients with chronic lung disease (preprint)

Rationale: Patients with chronic lung disease have an increased risk for severe coronavirus disease-19 (COVID-19) and poor outcomes. Objectives: To identify molecular characteristics of diseased lung epithelial and immune cells that may account for worse COVID-19 outcomes in patients with chronic lung diseases. Methods: We analyzed the transcriptomes of 605,904 single cells isolated from healthy (79 samples) and diseased human lungs (31 chronic obstructive pulmonary disease (COPD), 82 idiopathic pulmonary fibrosis (IPF) and 18 non-IPF interstitial lung disease samples). Measurements and Main Results: Cellular distribution and relative expression of SARS-CoV-2 entry factors (ACE2, TMPRSS2) was similar in disease and control lungs. Epithelial cells isolated from diseased lungs expressed higher levels of genes linked directly to efficiency of viral replication and the innate immune response. Unique ACE2-correlated gene sets were identified for each diagnosis group in the type II alveolar cells. Diseased lungs have a significant increase in the proportion of CD4, CD8 and NK cells compared to control lungs. Components of the interferon pathway, the IL6 cytokine pathway and the major histocompatibility complex (MHC) class II genes are upregulated in several diseased immune cell types. These differences in inflammatory gene expression programs highlight how chronic lung disease alters the inflammatory microenvironment encountered upon viral exposure to the peripheral lung. Conclusions: Chronic lung disease is accompanied by changes in cell-type-specific gene expression programs that prime the lung epithelium for and influence innate and adaptive immune responses to SARS-CoV-2 infection.

Impact of clade specific mutations on structural fidelity of SARS-CoV-2 proteins (preprint)

The SARS-CoV-2 is a positive stranded RNA virus with a genome size of ~29.9 kilobase pairs which spans 29 open reading frames. Studies have revealed that the genome encodes about 16 non-structural proteins (nsp), four structural proteins, and six or seven accessory proteins. Based on prevalent knowledge on SARS-CoV and other coronaviruses, functions have been assigned for majority of the proteins. While, researchers across the globe are engrossed in identifying a potential pharmacological intervention to control the viral outbreak, none of the work has come up with new antiviral drugs or vaccines yet. One possible approach that has shown some positive results is by treating infected patients with the plasma collected from convalescent COVID-19 patients. Several vaccines around the world have entered their final trial phase in humans and we expect that these will in time be available for application to worldwide population to combat the disease. In this work we analyse the effect of prevalent mutations in the major pathogenesis related proteins of SARS-COV2 and attempt to pinpoint the effects of those mutations on the structural stability of the proteins. Our observations and analysis direct us to identify that all the major mutations have a negative impact in context of stability of the viral proteins under study and the mutant proteins suffer both structural and functional alterations as a result of the mutations. Our binary scoring scheme identifies L84S mutation in ORF8 as the most disruptive of the mutations under study. We believe that, the virus is under the influence of an evolutionary phenomenon similar to Muller s ratchet where the continuous accumulation of these mutations is making the virus less virulent which may also explain the reduction in fatality rates worldwide. Keywords: SARS-COV2, Covid19, Mutations, Structural Analysis

Viral surface geometry shapes influenza and coronavirus spike evolution (preprint)

The evolution of circulating viruses is shaped by their need to evade the adaptive immune system. The spike protein which mediates entry to the host cell is the main target of antibody response. Because of the dense presentation of spikes on the viral surface, not all antigenic sites are targeted equally by antibodies, leading to complex immunodominance patterns. We used 3D coarse-grained computational models to estimate the antibody pressure on the seasonal flu H1N1 and the SARS subgenus spikes. Analyzing publically available sequences, we show that antibody pressure, through the geometrical organization of these spikes on the viral surface, shaped their mutability. Studying the mutability patterns of SARS-CoV-2 and the 2009 H1N1 pandemic spikes, we find that they are not predominantly shaped by antibody pressure. However, for SARS-CoV-2, we find that over time, it acquired, at low frequency, several mutations at antibody-accessible positions, which could indicate possible escape as define by our model. Hence, we offer a geometry-based approach to estimate and assess whether a pandemic virus is changing its mutational pattern to that indicative of a circulating virus.