Immunological memory is maintained by heterogeneous subsets of virus-specific T and B cells in non-lymphoid tissue sites of infection and multiple lymphoid organs. A comprehensive assessment of memory responses is therefore difficult to accomplish in humans. Here, we reveal the cellular complexity and functional diversity of SARS-CoV-2-specific memory T and B cells in lymphoid and mucosal tissues of previously infected organ donors up to 6 months post-infection (see fig. S9 for summary schematic). SARS-CoV-2-specific CD4+ T, CD8+ T, and B cells predominantly localized in the lung and lung-associated LNs and were maintained as memory cell populations. Tissue-resident T and B cells, known to participate in protection against secondary viral infections, were found most abundantly in the lung and were correlated across multiple sites. Moreover, SARS-CoV-2-specific GC B cells and TFH cells were discovered in lung-associated LNs, suggesting persisting GC responses months after resolution of infection. Together, these results indicate that the maintenance of SARS-CoV-2-specific immune memory is characterized by localized, ongoing coordination of cellular and humoral immunity within tissues.
SARS-CoV-2-specific memory B cells were distributed across multiple sites. While frequencies were highest in lung and LNs, there were also significant frequencies in BM. In all sites, virus-specific memory B cells exhibited a predominantly IgG+ memory phenotype. The finding of S/RBD-specific BRM in lung and lymphoid sites was notable, as was the low frequency of IgA+ SARS-CoV-2-specific memory B cells in mucosal tissue and associate LNs.
This work has certain limitations. Namely, our study focuses on four seropositive donors across seven decades of life to provide a representative profile of tissue-specific antiviral immune responses. In addition to the challenges of obtaining live cells for immunological studies from organ donors, the findings here also depended on SARS-CoV-2 seropositive subjects who had not been vaccinated, thus limiting the size of the donor pool and the timeframe of collection (prior to December 2020). The consistency in cell type and site-specific trends and correlations across all profiled donors, as well as corroboration of larger scale blood studies, demonstrates how this project provides new insights into tissue-specific immune memory maintenance and persistence of humoral and cellular responses following SARS-CoV-2 infection.
In conclusion, we reveal here that immunological memory from SARS-CoV-2 infection is maintained as heterogeneous subsets across multiple sites, with active and preferential maintenance in lung and associated LNs, as well as site-specific functional adaptations. These findings support the development of site-specific strategies for monitoring immune memory to infections and vaccines, and for fortifying immune responses at the infection sites.
MATERIALS AND METHODS
The objective of this study was to measure adaptive immune responses to SARS-CoV-2 in blood and tissues of seropositive individuals after resolution of infection. We measured the frequency of SARS-CoV-2-specific CD4+ T, CD8+ T, and B cells in seropositive organ donors compared to pre-pandemic seronegative donors to understand the maintenance of immunological memory to SARS-CoV-2 as T and B cell subsets across the body, the functional immune response in tissues, and the immune memory relationships across circulating and tissue-resident SARS-CoV-2-specific T and B cell populations.
Isolation of single-cell suspensions from tissue samples
SARS-CoV-2 serology testing
Blood from deceased organ donors (D495, D498, HDL113) was collected and serum obtained following centrifugation using serum separating clot activator tubes (Fisher Scientific, cat# 22040546). SARS-CoV-2 serology testing for N protein was then performed by the Center for Advanced Laboratory Medicine (CALM) at Columbia University Irving Medical Center to determine previous exposure to SARS-CoV-2 for inclusion in the study.
Pseudovirus (PSV) Neutralization Assay
In vitro T cell stimulations with SARS-CoV-2 peptide megapools (MPs)
AIM+ antigen-specific CD4+ T cells were identified as positive following Boolean OR gating of the CD40L+OX40+, 4-1BB+OX40+, 4-1BB+CD40L+ subsets (see Fig. S1 for gating strategy). The resultant gate was used to quantify AIM+CD4+T cell frequency. AIM+ antigen-specific CD8+ T cells were identified as 4-1BB+CD25+. Antigen-specific TFH calculated as a frequency of non-naïve (NN) CD4+ T cells were gated on total CD4+ T cells excluding CD45RA+CCR7+ CD4+ T cells. Antigen-specific CD4+ and CD8+ T cells were measured as DMSO-background-subtracted data. For quantification of the frequency of total SARS-CoV-2-specific CD4+ T cells, a weighted average was taken for percentage of AIM+ CD4+ T cells identified for samples stimulated with MP_S or MP_CD4_R MPs. For quantification of the frequency of total SARS-CoV-2-specific CD8+ T cells, a weighted average was taken for percentage of AIM+ CD8+ T cells identified for samples stimulated with MP_S, MP_CD8_A, or MP_CD8_B MPs.
For flow cytometry analysis of SARS-CoV-2 antigen-reactive T cells, cells were stained in 96-well U-bottom plates protected from light using fluorochrome-conjugated antibodies (see Table S2 for antibodies in the T cell flow cytometry panel). Briefly, cells were washed with FACS-buffer (PBS with 2% heat-inactivated FBS), then resuspended with surface staining antibody cocktail for 20 min at room temperature. Surface-stained cells were fixed for 30 min at RT in fixation buffer (Tonbo, cat# TNB-0607-KIT), washed with permeabilization buffer (Tonbo, cat# TNB-0607-KIT), and washed again with FACS buffer. Flow cytometry data were collected using the 5-laser Cytek Aurora flow cytometer (Cytek Bio) and analyzed using FlowJo V 10.7 software and Prism 9.0.1. software.
For flow cytometry analysis of SARS-CoV-2-specific B cells, biotinylated protein antigens multimerized on fluorescently-labeled streptavidin were used as probes to detect antigen-specific B cells (see Table S3 for antibodies used in the B cell flow cytometry panel). Avi-tagged full-length SARS-CoV-2 S (2P-stabilized, double streptavidin-tagged) and RBD proteins were generated in-house. Biotinylation was performed using biotin protein ligase standard reaction kit (Avidity, cat# Bir500A) following the manufacturers protocol and dialyzed against PBS. Biotinylated S was mixed with streptavidin BV421 (BioLegend, cat# 405225) and streptavidin BUV737 (BD Bioscience, cat # 612775) at 20:1 ratio (~6:1 molar ratio). Biotinylated RBD was mixed with streptavidin PE-Cy7 (BioLegend, cat# 405206) and streptavidin BUV661 (BD Bioscience, cat# 612979) at 2.2:1 ratio (~4:1 molar ratio). Streptavidin PE-Cy5.5 (Thermo Fisher Scientific, cat# SA1018) was used as a decoy probe for non-specific streptavidin-binding B cells. The probes were then mixed in Brilliant Stain Buffer (BD Bioscience, Cat# 566349) containing 5μM free d-biotin (Avidity, Cat# Bir500A). Cells (~107) were prepared in U-bottom 96-well plates and stained with 50μL antigen cocktail containing 400ng S (200ng per probe), 100ng RBD (50ng per probe), and 20ng streptavidin PE-Cy5.5 at 4°C for one hour followed by staining for surface markers in Brilliant Stain Buffer at 4°C for 30 min. Dead cells were stained using LIVE/DEAD Fixable Blue Stain Kit (Thermo Fisher Scientific, Cat# L34962) in PBS at 4°C for 30 min. Cells were then fixed and permeabilized using eBioscience Intracellular Fixation & Permeabilization Buffer Set (Thermo Fisher Scientific, Cat# 88-8824-00) before staining with antibodies against transcription factors in eBioscience Permeabilization Buffer (Thermo Fisher Scientific, Cat# 00-8333-56). Samples were acquired on Cytek Aurora and analyzed using FlowJo10.7.1 (BD Bioscience). In each experiment, PBMCs from a known COVID-19 convalescent subject and an unexposed subject were included to ensure consistent sensitivity and specificity of the assay.
Multiplex detection of cytokines
Cryopreserved supernatant from in vitro T cell stimulation experiments were sent to Eve Technologies Corp. (Calgary, Alberta) for quantification of 50 total human cytokines, chemokines, and growth factors. Luminex xMAP technology was used for multiplexed quantification of 2 human cytokines in one array (perforin, granzyme B) and 48 human cytokines, chemokines, and growth factors in a separate array (sCD40L, EGF, Eotaxin, FGF-2, Flt-3 ligand, Fractalkine, G-CSF, GM-CSF, GROα, IFNα2, IFNγ, IL-1α, IL-1β, IL-1ra, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12 (p40), IL-12 (p70), IL-13, IL-15, IL-17A, IL-17E/IL-25, IL-17F, IL-18, IL-22, IL-27, IP-10, MCP-1, MCP-3, M-CSF, MDC (CCL22), MIG, MIP-1α, MIP-1β, PDGF-AA, PDGF-AB/BB, RANTES, TGFα, TNFα, TNFβ, VEGF-A). The multiplexing analysis was performed using the Luminex 200 system with assay kits sourced by Millipore MILLIPEX (MilliporeSigma, Burlington, Massachusetts, USA) according to the manufacturer’s protocol.
Correlogram plot and visualization
Funding: This work was supported by National Institutes of Health grants AI100119,AI128949 (Human Immunology Project Consortium) and AI106697 (to DLF), AI142742 (Cooperative Centers for Human Immunology) (to AS, SC), National Institutes of Health grant contract Number 75N9301900065 (DW, AS), grant K23AI141686 (TJC), and a Helmsley Charitable Trust grant (TMB, DLF). The CCTI Flow Cytometry Core was supported by NIH S10RR027050 and S10OD020056. P.D. was supported by a Cancer Research Institute (CRI) Irvington Postdoctoral Fellowship; N.L, was supported by a National Science Foundation Graduate Research Fellowship Program (NSF-GRFP); P.S. was supported by the Canadian Institutes of Health Research (CIHR) Fellowship.
Author contributions: Conceptualization: MMLP, KR, YK, DLF, SC. Methodology: MMLP, KR, YK, NIB, ZZ. Investigation: MMLP, KR, YK, NIB, ZZ. Visualization: MMLP, KR, YK. Resources: AS, AG, DW, MK, RM, KMH, EOS, MAB, TMB, TJC, BBU, NL, PAS, PD, YSL, JIG, MCB. Supervision: DLF, SC. Writing – original draft: MMLP, KR, YK, DLF, SC. Writing – review and editing: MMLP, KR, YK, DLF, SC. Project administration: DLF, SC, SBW. Funding acquisition – DLF, SC, AS.
Competing interests: A.S. is a consultant for Gritstone, Flow Pharma, Merck, Epitogenesis, Gilead, and Avalia. S.C has consulted for Avalia, Roche and GSK. L.J.I. has filed for patent protection for various aspects of T cell epitope and vaccine design work. All remaining authors declare no competing interests.
Data and materials availability: All data needed to evaluate the conclusions of the paper are available in the paper or the Supplementary Materials.