key: cord-275960-1m6poddy
authors: Thieme, C. J.; Anft, M.; Paniskaki, K.; Blazquez-Navarro, A.; Doevelaar, A.; Seibert, F. S.; Hoelzer, B.; Konik, M. J.; Brenner, T.; Tempfer, C.; Watzl, C.; Dolff, S.; Dittmer, U.; Westhoff, T. H.; Witzke, O.; Stervbo, U.; Roch, T.; Babel, N.
title: The SARS-CoV-2 T-cell immunity is directed against the spike, membrane, and nucleocapsid protein and associated with COVID 19 severity
date: 2020-05-16
journal: nan
DOI: 10.1101/2020.05.13.20100636
sha: 
doc_id: 275960
cord_uid: 1m6poddy

Identification of immunogenic targets of SARS-CoV-2 is crucial for monitoring of antiviral immunity and vaccine design. Currently, mainly anti-spike (S)-protein adaptive immunity is investigated. However, also the nucleocapsid (N)- and membrane (M)-proteins should be considered as diagnostic and prophylactic targets. The aim of our study was to explore and compare the immunogenicity of SARS-CoV-2 S-, M- and N-proteins in context of different COVID-19 manifestations. Analyzing a cohort of COVID-19 patients with moderate, severe, and critical disease severity, we show that overlapping peptide pools (OPP) of all three proteins can activate SARS-CoV-2-reactive T-cells with a stronger response of CD4+ compared to CD8+ T-cells. Although interindividual variations for the three proteins were observed, M protein induced the highest frequencies of CD4+ T-cells, suggesting its relevance as diagnostic and vaccination target. Importantly, patients with critical COVID-19 demonstrated the strongest T-cell response, including the highest frequencies of cytokine-producing bi- and trifunctional T-cells, for all three proteins. Although the higher magnitude and superior functionality of SARS-CoV-2-reactive T-cells in critical patients can also be a result of a stronger immunogenicity provided by severe infection, it disproves the hypothesis of insufficient SARS-CoV-2-reactive immunity in critical COVID-19. To this end, activation of effector T-cells with differentiated memory phenotype found in our study could cause hyper-reactive response in critical cases leading to immunopathogenesis. Conclusively, since the S-, M-, and N-proteins induce T-cell responses with individual differences, all three proteins should be evaluated for diagnostics and therapeutic strategies to avoid underestimation of cellular immunity and to deepen our understanding of COVID-19 immunity.

Clearance of viral pathogens requires an effective T cell response directed against protein antigens expressed by the virus 1 . The T cell response against the severe acute respiratory syndrome-related coronavirus (SARS-CoV)-2 virus, which causes the ongoing pandemic, is presumably initiated by respiratory professional antigen presenting cells (APC) that can engulf viral antigens as shown for the 2002/03 SARS-CoV 2 . The activated T cells can migrate to the site of infection, where they facilitate viral clearance, but can also contribute to immune pathogenesis. There is mounting evidence that the latter is the major reason for critical COVID-19 disease manifestations 3, 4 .

The SARS-CoV-2 contains four structural proteins: the spike glycoprotein (S), the envelope (E) protein, the membrane (M) protein and the nucleocapsid (N) protein 5 . The S-protein mediates host cell entry by binding to the angiotensin-converting enzyme 2 (ACE2) 6 . Due to its surfaceexposure and crucial role for infecting the host cell, the S-protein is an attractive therapeutic target, for instance for antibodies that block the S/ACE2 interaction. In fact, it was shown that patients recovered from COVID-19 developed virus neutralizing anti-S immunoglobulin (Ig) titers 7 . Given the requirement for T cell help in generation of high affinity IgG antibodies, this finding indicates that S-protein reactive T cell immunity was formed in those patients 8,9 . Accordingly, very recent studies identified SARS-CoV-2 S-protein reactive T cell responses in patients suffering from moderate, severe, and critical COVID-19 4, 10 . Furthermore, it was shown that the amount of SARS-CoV-2 reactive T cells increased with disease progression 11 .

Besides the S-protein, also the N-and M-proteins were suggested as potential targets for diagnostic and prophylactic approaches 3, 5 . In fact, B cell responses against the N-protein seemed to be the first to arise 4-8 days after symptom onset for the 2002/03 SARS-CoV infection 12, 13 , which indicates that also N-reactive T cell response are prevalent during this timeframe. However, data on T cell responses towards the N-and M-proteins for the pandemic SARS-CoV-2 infection are currently not available. For this reason, we sought to identify, characterize, and compare S-, M-, and N-reactive T cell responses in COVID-19 patients with different clinical manifestation.

We analyzed 57 blood samples drawn at different time points after hospital admission of a cohort of 28 COVID-19 patients with moderate (28 samples), severe (16 samples), and critical (13 samples) disease manifestation (Table S1 ). The samples were grouped according to the COVID-19 severity at the sampling time into moderate, severe, critical manifestation using the German Robert-Koch-Institute symptom classification as previously described 4 . In agreement   with other studies 14 , we observed significantly more males within critical COVID-19 patients   compared to the moderate and severe cases. However, bivariate regression analysis revealed   no significant influence of gender on the main findings when comparing different COVID-19 severity (Table S2 ). There were no significant differences in sampling time with respect to the PCR-testing or hospitalization between the groups (Table S3) .

By stimulation with S-, M-, or N-overlapping peptide pools (OPP) (Fig. S1 ), we could show that all three proteins have the capacity to induce SARS-CoV-2-reactive CD4 + and CD8 + T cells (Fig.   1a ). Overall, we detected a CD4 + T cell response in 54 out of 57 and a CD8 + T cell response in Comparing the magnitude of response against the three proteins, we also found that the M-protein OPP induced the highest frequencies of reactive CD4 + T cells (Fig. 2a) . Compared to the S-and N-reactive CD4 + T cells we found a consistent trend of higher frequencies of Mreactive CD4 + T cells expressing cytokines and effector molecules such as interleukin (IL)-2, interferon γ (IFNγ), tumor necrosis factor α (TNFα), and granzyme B (GrzB) . N-protein induced the lowest responses in comparison to the other proteins ( Fig. 2b-f, Fig. S2 ). Despite the differences in magnitude, there was a high correlation between the frequencies of S-, N-, and M-reactive CD4 + T cells (Fig. 2g-i) .

Interestingly, the pattern observed for S-, N-, and M-protein reactivity of CD4 + T cells were not found in CD8 + T cells (Fig. 2j-o) . In fact, a tendency of higher frequencies of S-or N-protein reactive CD8 + T cells compared to M-protein was observed, but without reaching statistical significance after correction for multiple testing. Similar to CD4 + restricted immunity, we . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 16, 2020. . observed a high correlation in frequencies of CD8 + T cells reactive to S-, N-, and M-proteins (Fig 2p-r) .

The exact role of SARS-CoV-2-reactive T-cell immunity for COVID-19 progression is currently unknown. We therefore investigated differences in the T cell immunity between moderate, severe and critical COVID-19 patients. A defective switch between innate and adaptive immunity has been described to differentiate patients with favorable and unfavorable outcome after SARS-CoV infection in previous studies 16 . Surprisingly, and in contrast to the endemic SARS-CoV infection, we detected the highest magnitude of CD4 + and CD8 + T cells reactive to S-, M-, and N-proteins in critical COVID-19 (Fig. 3) .

Examining a limited number of subjectively selected functions of virus-reactive T cells may generate distorted and incomplete interpretation of the function and phenotype of these cells 17 . Polyfunctional T cells, that express more than one cytokine or effector molecule, have been described as a hallmark of protective immunity in viral infections [17] [18] [19] . Addressing this point, we analyzed the IFNγ, TNFα, IL-2, and IL-4 cytokines as well as the effector molecule GrzB expression in parallel to differentiation stage phenotyping. Of interest, not only the quantity but also the functionality of T-cell immunity was superior in patients with critical COVID-19 severity. Polyfunctional T cells showed higher frequencies in critical COVID-19 patients compared to moderate and severe cases (Fig. 3e ,f,n,o). Antigen-reactive IFNγ-, IL2-, and TNFα-producing CD4 + T cells constituted over 50% of trifunctional CD4 + T cells, while cytotoxic GrzB-producing IFNγ-and TNFα-expressing CD4 + T cells constituted 25% of trifunctional CD4 + T cells (Fig. S3b) . The cytokine and effector molecule expression of bifunctional CD4 + T cells was also dominated by IFNγ, TNFα, IL2, and to a lesser extend GrzB ( Fig. S3c ). As expected, the majority of polyfunctional CD8 + T cells produced the cytotoxic effector molecule GrzB, most commonly in combination with IFNγ and TNFα (Fig. S3b-c) .

Despite the higher frequencies of single-, bi-, and trifunctional CD4 + and CD8 + T cells found in most T-cell subsets in critical cases, statistical significant differences were observed only for few subsets. With respect to the relatively low sample numbers and multiple correction testing, the lack of statistical significant differences is not surprising. As described above, SARS-CoV-2-reactive CD4 + T cells in our study were predominantly of TH1 phenotype. A TH2 dominated response was associated with immunopathology and -eosinophil infiltration after vaccination with N-protein expressing vaccinia virus in a mouse SARS-CoV model 20, 21 .

. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 16, 2020. . However, we have no indication of ongoing TH2 response in critical patients since only very few IL4-producing T cells were observed in all samples (Fig. 2e-n) .

In line with data showing an association between polyfunctionality and the stage of phenotypic differentiation 17 , we observed higher frequencies of CD8 + T cells with effector memory (TEM)/TEMRA phenotype in critical COVID-19 patients compared to moderate and severe cases (Fig S4) . Importantly, the presence of S-, N-, and M-reactive T-cells with an advanced differentiation phenotype early after diagnosis in our study indicates pre-existing cellular immunity as demonstrated in a recent study 10 . only one sample per patients using the last visit sample for an optimized timing match, we did not detect relevant differences to the analysis of all available samples (Fig. S4) . We also did not find any significant differences in the time after PCR-testing or after hospital admission between the groups. Nevertheless, it needs to be considered that the time point of infection in our cohort is, as in most similar studies, not known. The higher reactivity of T cells of critically ill patients might therefore mirror a longer course of response against the infection.

Another explanation might be that the higher magnitude and functionality of the T-cell response observed in critical COVID-19 cases might simply reflect a more severe infection . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 16, 2020. . https://doi.org/10.1101/2020.05.13.20100636 doi: medRxiv preprint course with a stronger immunogenic environment, provided by a higher viral burden and inflammatory bystander activation.

Independently of the reason for the higher magnitude and functionality of CD4 + and CD8 + T cells in critical patients, our data demonstrate the ability of critical COVID-19 patients to mount a sufficient cellular immunity. Although the observed TH1-dominanted polyfunctional cells are commonly regarded as a parameter for protective immunity 17, 19, 24 , they can also provide immune damage contributing to immunopathogenesis 25 . In this context, our finding on advanced differentiation stage of SARS-CoV-2-reactive T cells found at early time points raises the question about the beneficial effect of pre-existing immunity for the course of infection. One could speculate that even though it appears to be generally protective, preexisting SARS-CoV-2 reactive T-cells with effector phenotype, which are cross-reactive with common cold corona viruses 10 , in severe infection can lead to hyperactive response and immunopathogenesis.

Although further studies are required to explore the pathogenesis of COVID-19 progression in more details, our study enhances the understanding about the complex mechanisms of the anti-SARS-COV-2 immunity that should be considered for diagnostic test and vaccine development.

. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 16, 2020. . https://doi.org/10.1101/2020.05.13.20100636 doi: medRxiv preprint

This investigation is an analysis of a sub-cohort of a larger study that was published earlier 4 .

We recruited 28 patients with moderate (n=8), severe (n=10) and critical (n=10) COVID-19.

The degree of COVID-19 severity was evaluated according to the guidelines of the Robert Koch Institute, Germany, as previously described 4 is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 16, 2020. . https://doi.org/10.1101/2020.05.13.20100636 doi: medRxiv preprint 25D2) (BioLegend), CD137 (4-1BB)-PE-Cy7 (clone 4B4-1) (BioLegend), CD154 (CD40L)-A647;

(clone 24-31) (BioLegend), TNFa-eFluor450 (clone MAb11) (eBioscience), IFNg-BV650 (clone 4S.B3) (BioLegend), CD3-BV785 (clone OKT3) (BioLegend). All samples were acquired on a CytoFlex flow cytometer (Beckman Coulter).

Flow cytometry data were analyzed using FlowJo version 10.6.2 (BD Biosciences). Gating strategies are presented in supplementary Fig. S2 . Unspecific activation in unstimulated controls was subtracted from stimulated samples to account for specific activation. Antigenspecific responses above 0.001% were considered positive. Negative values were set to zero.

Multifunctional T cells were analyzed using Boolean gating of IL2, IL4, IFNγ, TNFα, and GrzB producing CD4 + and CD8 + T cells. Statistical analysis was performed using R, version 3.6.2 26 and GraphPad Prism v7, which was also used for graphical representation. Venn diagrams were prepared using Venny v2. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted May 16, 2020. . https://doi.org/10.1101/2020.05.13.20100636 doi: medRxiv preprint 

57 blood samples of a total of 28 COVID-19 patients were drawn at one or at multiple time points within one week after diagnosis. Peripheral blood mononuclear cells were stimulated for 16h with S-, M-, or N-protein overlapping peptide pools. The gating strategy is presented in Fig. S2 . a-f) Frequencies of (a) CD154 + CD137 + CD4 + T cells (antigen-specific CD4 + T cells), (b) interferon γ (IFNγ)-, (c) tumor necrosis factor α (TNFα)-, (d) interleukin (IL) 2-, (e) IL4-, and (f) granzyme B (GrzB)-producing antigen-specific CD4 + T cells. Statistical analysis was performed with Friedman test for non-parametric data and Dunn's multiple comparison test. Whiskers were calculated with the Tukey method. g-i) Correlation of M-, N-and S-protein OPP reactive (CD154+ CD137+) CD4+ T cells. Calculation was performed with Spearman's rank correlation coefficient. j-l) Frequencies of (j) CD137 + CD8 + T cells (antigen-specific CD8 + T cells), (k) IFNγ-, (l) TNFα-, (m) IL2-, (n) IL4-, and (o) GrzB-producing antigen-specific CD8 + T cells. Statistical analysis was performed with Friedman test for non-parametric data and Dunn's multiple comparison test. Whiskers were calculated with the Tukey method. p-r) Correlation of M-, N-and S-protein reactive (CD137+) CD8+ T cells. Calculation was performed with Spearman's rank correlation coefficient. is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted May 16, 2020. . https://doi.org/10.1101/2020.05.13.20100636 doi: medRxiv preprint

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M-, or Nprotein reactive T cells is presented in Fig. S2. a-d) Frequencies of (a) CD154 + CD137 + CD4 + T cells (antigen-specific CD4 + T cells), (b) interferon γ (IFNγ)-, (c) interleukin (IL) 2-, and (d) tumor necrosis factor α (TNFα)-producing antigen

A detailed composition of bi-and trifunctional cells is presented in Fig. S3. g-i) Frequencies of antigen-specific CD4 + (g) TEM, (h) TCM, and (i) TEMRA cells. j-m) Frequencies of (j) CD137 + CD8 + T cells (antigen-specific CD4 + T cells), (k) IFNγ-, (l) IL2-, (m) GrzB-producing antigen-specific CD8 + T cells. n-o) Frequencies of polyfunctional CD8 + T cells. (n) Bifunctional and (o) trifunctional CD4 + T cells were analyzed by Boolean gating of IL2-, IFNγ-, TNFα, IL4-, and GrzB-production. Composition of bi-and trifunctional cells is presented in Fig. S3. p-r) Frequencies of antigen-specific CD8 + (g) TEM, (h) TCM, and (i) TEMRA cells

We feel deep gratitude to the patients who donated their blood samples and clinical data for this project. We would like to acknowledge the excellent technical assistance as well as the expertise of immune diagnostic laboratory (Sarah Skrzypczyk, Eva Kohut, Julia Kurek, Jan Zapka) of Center for Translational Medicine at Marien Hospital Herne. This work was