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CTL酶联免疫荧光斑点分析仪应用新发表关于“COVID”研究的文献

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bioRxiv preprint doi: https://doi.org/10.1101/2020.11.29.402677; this version posted November 29, 2020. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under aCC-BY-NC-ND 4.0 International license.
Deconvoluting the T cell response to SARS-CoV-2: specificity versus chance- and
cognate cross-reactivity
Alexander A. Lehmann1 , Greg A. Kirchenbaum1 , Ting Zhang1 , Pedro A. Reche2 and Paul V. Lehmann1
1 Cellular Technology Ltd., Shaker Heights, OH, United States
2 Laboratorio de Inmunomedicina & Inmunoinformatica, Departamento de Immunologia & O2, Facultad
de Medicina, Universidad Complutense de Madrid, Madrid, Spain.
* Corresponding Author:
Paul V. Lehmann, paul.lehmann@immunospot.com
Keywords: mega peptide pools, ELISPOT, ImmunoSpot, immune monitoring, COVID-19, T cell affinity
Running title: SARS-CoV-2 T cell monitoring
Abstract
SARS-CoV-2 infection takes a mild or clinically inapparent course in the majority of humans who contract
this virus. After such individuals have cleared the virus, only the detection of SARS-CoV-2-specific
immunological memory can reveal the exposure, and hopefully the establishment of immune
protection. With most viral infections, the presence of specific serum antibodies has provided a reliable
biomarker for the exposure to the virus of interest. SARS-CoV-2 infection, however, does not reliably
induce a durable antibody response, especially in sub-clinically infected individuals. Consequently, it is
plausible for a recently infected individual to yield a false negative result within only a few months after
exposure. Immunodiagnostic attention has therefore shifted to studies of specific T cell memory to
SARS-CoV-2. Most reports published so far agree that a T cell response is engaged during SARS-CoV-2
infection, but they also state that in 20-81% of non- SARS-CoV-2-exposed individuals, T cells respond to
SARS-CoV-2 antigens (mega peptide pools), allegedly due to T cell cross-reactivity with coronaviruses
causing Common Cold (CCC), or other antigens. Here we show that by introducing irrelevant mega
peptide pools as negative controls to account for chance cross-reactivity, and by establishing the antigen
dose-response characteristic of the T cells, one can clearly discern between cognate T cell memory
induced by SARS-CoV-2 infection vs. cross-reactive T cell responses in individuals who had not been
infected with SARS-CoV-2.
1. Introduction
Traditionally, the assessment of immune memory has relied upon measurements of serum antibodies
without queries of the T cell compartment. However, SARS-CoV-2 infection highlights the shortcoming
of such a serodiagnostic approach. While the majority of SARS-CoV-2 infected individuals initially
develop an antibody response to this virus, false negative results are a concern because not all infected
individuals attain high levels of serum antibody reactivity acutely after infection 1-3, and those who do
develop detectable antibody reactivity may decline to the limit of detection within a few months 4 . In
such cases, the detection of T cell memory might be the only evidence of such infection, and a surrogate
of acquired immune protection from SARS-CoV-2 reinfection.bioRxiv preprint doi: https://doi.org/10.1101/2020.11.29.402677; this version posted November 29, 2020. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under aCC-BY-NC-ND 4.0 International license.
Fueled additionally by evidence that T cell-mediated immunity is required for immune protection
against SARS-CoV-2 5-7, attention has turned to T cell immunodiagnostics trying to establish whether the
detection of T cell memory may be a more sensitive and reliable indicator of SARS-CoV-2 exposure than
antibodies 8-11. In most studies published so far SARS-CoV-2-specific T cell memory cells were detected in
the majority of infected individuals, but such were also found in 20-81% of control subjects who clearly
could not have been infected by the SARS-CoV-2 virus 9, 12-19. If generalizable, such results would imply
that T cell assays are unsuited to reliably identify who has, or has not, been infected by SARS-CoV-2
providing false positive results in up to 81% of the individuals tested. It should be noted right away,
however, that the notion of cross-reactive SARS-CoV-2 antigen recognition by T cells being common in
unexposed subjects might be related to the T cell assay and the test conditions used as it was not
observed by others 14, 20, 21. Progress with settling the issue of T cell cross-reactivity in SARS-CoV-2
antigen recognition, and identifying suitable test systems, will decide whether T cell diagnostics can
reliably detect specific immune memory to SARS-CoV-2 infection/exposure, and possibly identify the
immune protected status of those subjects.
Next to possible cross-reactivity, T cell immune diagnostics of SARS-CoV-2 infection faces the challenge
of having to reliably detect antigen-specific T cells in blood that occur in very low frequency. The
numbers of SARS-CoV-2-specific T cells in blood post-infection is about one tenth of the numbers of T
cells specific for viruses that induce strong T cell responses, such as influenza, Epstein Barr- (EBV) or
human cytomegalovirus (HCMV) 11, 22, and reliably detecting even the latter is at the border of current
technology. Further complicating matters, the frequencies of SARS-CoV-2-specific T cells are even lower
in subjects who underwent a mild or asymptomatic SARS-CoV-2 infection compared to those who
developed more severe COVID-19 12, 21, 23, 24. Owing to these low T cell frequencies, and the antigen
induced signal being small in magnitude, any contribution of cross-reactive T cell stimulation will
interfere with the reliable detection of genuine SARS-CoV-2-specific T cells. Setting up clear cut-off
criteria for identifying antigen-specific T cell memory is therefore paramount.
Because T cell assays rely upon detecting SARS-CoV-2 antigen-specific T cells in blood via memory T cell
re-activation ex vivo, the choice and formulation of the SARS-CoV-2 antigen itself used for the T cell
recall will critically define the assay result. As the epitope utilization in the T cell response to SARS-CoV-
2 is not known yet, by necessity, the aforementioned T cell diagnostic efforts tailored towards this virus
have relied either on pools of hundreds of peptides that cover the entire proteome of the virus, or on
pools of a multitude of predicted epitopes (mega peptide pools). Traditional T cell immune monitoring
efforts, however, have called for the utilization of select, highly purified individual peptides whose
specificity has been carefully established. Presently it is unproven whether pools of hundreds of
unpurified peptides are even suited for reliable T cell diagnostics, and whether false positive or false
negative results obtained using them are inherent to the recall antigen formulation. The chance for T
cell cross-reactivity can be expected to increase with every peptide added into a pool, multiplying the
chance for false positive results. Conversely, irrelevant peptides (those not recognized by T cells) also
present in the pool can be expected to compete with the actually recognized T cell epitopes for binding
to HLA-molecules, possibly causing false negative results 25. To our knowledge, it has not yet been
systematically addressed whether and how chance cross-reactivity or peptide competition affects T cell
immune monitoring results when mega peptide pools are used for testing. Instead of relying on third
party mega peptide pools as the proper negative control to establish the background noise of the T cell
assay, in all SARS-CoV-2 studies published so far, the mega peptide pool-induced T cell activation has
been compared to PBMC cultured in medium alone, in the absence of any exogenously added peptide. bioRxiv preprint doi: https://doi.org/10.1101/2020.11.29.402677; this version posted November 29, 2020. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under aCC-BY-NC-ND 4.0 International license.
In this report we introduce suitable negative control mega peptide pools, and using
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