SARS-CoV-2 infects adipose tissue in a fat depot- and viral lineage-dependent manner.

Visceral adiposity is a risk factor for severe COVID-19, and a link between adipose tissue infection and disease progression has been proposed. Here we demonstrate that SARS-CoV-2 infects human adipose tissue and undergoes productive infection in fat cells. However, susceptibility to infection and the cellular response depends on the anatomical origin of the cells and the viral lineage. Visceral fat cells express more ACE2 and are more susceptible to SARS-CoV-2 infection than their subcutaneous counterparts. SARS-CoV-2 infection leads to inhibition of lipolysis in subcutaneous fat cells, while in visceral fat cells, it results in higher expression of pro-inflammatory cytokines. Viral load and cellular response are attenuated when visceral fat cells are infected with the SARS-CoV-2 gamma variant. A similar degree of cell death occurs 4-days after SARS-CoV-2 infection, regardless of the cell origin or viral lineage. Hence, SARS-CoV-2 infects human fat cells, replicating and altering cell function and viability in a depot- and viral lineage-dependent fashion.

In silico analysis of mutant epitopes in new SARS-CoV-2 lineages suggest global enhanced CD8+ T cell reactivity and also signs of immune response escape.

SARS-CoV-2 variants of concern have emerged since the COVID-19 outburst, notably the lineages detected in the UK, South Africa, and Brazil. Their increased transmissibility and higher viral load put them in the spotlight. Much has been investigated on the ability of those new variants to evade antibody recognition. However, little attention has been given to pre-existing and induced SARS-CoV-2-specific CD8+ T cell responses by new lineages. In this work, we predicted SARS-CoV-2-specific CD8+ T cell epitopes from the main variants of concern and their potential to trigger or hinder CD8+ T cell response by using HLA binding and TCR reactivity in silico predictions. Also, we estimated the population's coverage for different lineages, which accounts for the ability to present a set of peptides based on the most frequent HLA alleles of a given population. We considered binding predictions to 110 ccClass I HLA alleles from 29 countries to investigate differences in the fraction of individuals expected to respond to a given epitope set from new and previous lineages. We observed a higher population coverage for the variant detected in the UK (B.1.1.7), and South Africa (B.1.351), as well as for the Brazilian P.1 lineage, but not P.2, compared to the reference lineage. Moreover, individual mutations such as Spike N501Y and Nucleocapsid D138Y were predicted to have an overall stronger affinity through HLA-I than the reference sequence while Spike E484K shows signs of evasion. In summary, we provided evidence for the existence of potentially immunogenic and conserved epitopes across new SARS-CoV-2 variants, but also mutant peptides exhibiting diminished or abolished HLA-I binding. It also highlights the augmented population coverage for three new lineages. Whether these changes imply more T cell reactivity or potential to evade from CD8+ T cell responses requires experimental verification.

Class I HLA Allele Predicted Restricted Antigenic Coverages for Spike and Nucleocapsid Proteins Are Associated With Deaths Related to COVID-19.

The world is dealing with one of the worst pandemics ever. SARS-CoV-2 is the etiological agent of COVID-19 that has already spread to more than 200 countries. However, infectivity, severity, and mortality rates do not affect all countries equally. Here we consider 140 HLA alleles and extensively investigate the landscape of 3,723 potential HLA-I A and B restricted SARS-CoV-2-derived antigens and how 37 countries in the world are predicted to respond to those peptides considering their HLA-I distribution frequencies. The clustering of HLA-A and HLA-B allele frequencies partially separates most countries with the lowest number of deaths per million inhabitants from the other countries. We further correlated the patterns of in silico predicted population coverage and epidemiological data. The number of deaths per million inhabitants correlates to the predicted antigen coverage of S and N derived peptides and its module is influenced if a given set of frequent or rare HLA alleles are analyzed in a given population. Moreover, we highlighted a potential risk group carrying HLAs associated with an elevated number of deaths per million inhabitants. In addition, we identified three potential antigens bearing at least one amino acid of the four-length insertion that differentiates SARS-CoV-2 from previous coronavirus strains. We believe these data can contribute to the search for peptides with the potential to be used in vaccine strategies considering the role of herd immunity to hamper the spread of the disease. Importantly, to the best of our knowledge, this work is the first to use a populational approach in association with COVID-19 outcome.