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Authors: Chour et al.

Link to paper: https://www.medrxiv.org/content/10.1101/2020.05.04.20085779v1

Journal/ Pre-Print: Medrxiv

Tags: Immunology, Clinical

Research Highlights 

1. A methodological paper, introducing a tool that allows to track virus-specific T cell populations by single-chain trimers (SCT) containing the peptide antigen, the MHC HLA allele and the β-2 microglobulin subunit, which can subsequently be incorporated into standard pMHC tetramer scaffolds or used for imaging.

2. HLA-matched individuals exhibit similar virus-specific T cell populations, but different time-trajectories of those populations (of note, they only look at two patients and one healthy donor).

3. They identify potentially immunodominant antigens for CD8 T-cells form the spike protein presented on HLA-A*02:01.

Summary 

Using the NetMHC4.0 binding prediction algorithm the authors tested all 9-11mer spike protein epitopes and identified 96 peptides that bind to the HLA-A*02:01 allele, which they synthesized as SCTs to generate tetramers for detection of antigen-specific T cells. They validated their system by detecting CMV-specific T cell populations. They also implemented improvements in the SCT designs. They then generated a spike protein library composed of 30 predicted A*02:01 antigens and used those SCT epitopes to detect spike protein antigen specific CD8 T cell population frequencies in two HLA-matched COVID patients and one healthy control. Their analysis suggests that five overlapping antigens may be immunodominant.

Impact for SARS-CoV2/COVID19 research efforts

Understand the immune response to SARS-CoV2/COVID19 at an antigen specific level

Study Type

· In vitro study (on blood-derived PBMCs)

· In silico (peptide prediction)

Strengths and limitations of the paper

Novelty: They adapt the SCT platform to allow detection of spike protein specific CD8 T cell populations using hemocytometry/imaging rather than Flow Cytometry (overcomes aerosol risks).

Standing in the field: Introducing an alternative method to detect T cells

Appropriate statistics: Very little data and no statistics

Viral model used: SARS-CoV-2

Translatability: Their platform is potentially useful to generate peptide libraries and detect various spike protein specific T cell populations in COVID patients

Main limitations: A proof of concept of their tool’s usability. Little insight into COVID-19. As the authors note only 60 (out of 96 putative antigens) could be expressed as SCTs. Of those 60, only the 30 most highly expressed SCTs were tested. A second bias is in the A*02:01 allele, which does not permit sampling of certain parts of the spike protein, such as the S1/S2 cleavage domain. Their next step is to create additional SCT libraries for different HLA alleles. They also don’t really compare their platform to other more widely used ones, it is not clear what advantage this has over normal refold of pMHC monomers. They could have actually tested for clonal expansion by sorting the populations. The time-trajectories of the response are hard to assess since the two patients had very different manifestations of the disease.