immunoSEQ® T-MAP™ COVID: A tool to uncover and monitor the T-cell response in COVID-19

t-map-hero-latest
Table of Contents
    Add a header to begin generating the table of contents

    Understanding the effects of SARS-CoV-2 on the immune system and which immune response correlates are important for protection is critical in turning the tide of the pandemic. There are many ways to measure the immune response to infection or vaccination. In a previous article, we discussed why monitoring T cells, which are an important component of the adaptive immune system, provides a better indicator of immune responses to SARS-CoV-2 infection than antibody-based tests. T-cell responses are more consistent across patients, arise earlier in the course of infection, and last longer than antibody responses. (1–4) To learn more on the role of T cells in SARS-CoV-2 infection, view our webinar page.

    Identifying and quantifying the T cells that recognize and respond to SARS-CoV-2 antigens in individuals and across populations has the potential to determine if people have been previously infected with SARS-CoV-2, to monitor immune responses to vaccine candidates, and to help identify predictive markers and develop therapeutics.

    Monitoring the T-cell response to SARS-CoV-2 will be important, even for researchers not directly involved in COVID-19 research. As more people worldwide become infected with SARS-CoV-2, monitoring the T-cell response in infected individuals can help researchers to understand how COVID-19 affects those with other conditions. Integrating a patient’s T-cell response to SARS-CoV-2 infection or vaccination into these various research applications holds untold potential clinical benefit.

    immunoSEQ T-MAP COVID: a molecular T-cell monitoring tool for SARS-CoV-2

    Our focus is on monitoring the adaptive immune system. Our immunoSEQ Assay is a highly sensitive, multiplex PCR-based method that can sequence the entire T-cell repertoire from a variety of samples, including peripheral blood mononuclear cells (PBMCs), whole blood, and/or formalin-fixed paraffin-embedded (FFPE) tissue. Given the importance of T cells in the immune response to SARS-CoV-2, we have harnessed over a decade of expertise to launch immunoSEQ T-MAP COVID, which provides resources to study and analyze the T-cell response to SARS-CoV-2.

    Unlike other T-cell-based methods, which focus on a limited set of T cells, immunoSEQ T-MAP COVID offers a comprehensive view of the T-cell response to SARS-CoV-2 and provides a suite of resources for researchers, including:

    • a Search Tool within the immunoSEQ Analyzer that allows you to compare your immunoSEQ Assay data with data from our internal ImmuneCODE database
    • a T-cell Classifier that can determine if samples indicate a past T-cell response to SARS-CoV-2.

    With immunoSEQ T-MAP COVID, researchers can access the underlying technology that powers the first and only EUA-approved T-cell-based test for COVID-19.

     Data available through immunoSEQ T-MAP COVID

    There is a wealth of data on SARS-CoV-2-specific T-cell receptor (TCR) sequences as well as TCR–antigen pairs available through immunoSEQ T-MAP COVID. These data were acquired as part of the ImmuneCODE database—a collaboration between Adaptive Biotechnologies, Microsoft, Illumina, Labcorp/Covance, and health organizations across the world. It contains detailed population-level data on TCR repertoires from over 1400 people exposed to, infected with, or recovered from SARS-CoV-2 (Figure 1). Samples came from subjects enrolled in the ImmuneRACE study, a prospective study across the United States to determine how the immune system detects and responds to the virus, and from patient blood samples collected by institutions worldwide. Samples from healthy, naïve controls are also included for comparison. Altogether, the database represents a geographically and ethnically diverse population. (5) New subjects are regularly added to the ImmuneCODE database, improving the power of immunoSEQ T-MAP COVID.

    Over 300 million unique TCR sequences have been identified with the immunoSEQ Assay, generating over 1 TB of raw data. That number is rising every day as more subjects are added. Samples in the ImmuneCODE database were analyzed by the immunoSEQ Assay, to identify SARS-CoV-2-specific TCR sequences, and our proprietary MIRA (Multiplexed assay for Identification of T cell Receptor Antigen specificity) platform, which pairs virus-specific TCRs with their antigens (Figure 1).

    Using the MIRA platform, over 160,000 high-confidence TCR sequences paired with their cognate SARS-CoV-2 antigens have been identified. The MIRA platform is a proprietary high-throughput multiplex assay that can use large numbers of query antigens (hundreds to thousands at a time and in parallel) to identify antigen-specific TCRs by combining immune assays with TCR sequencing. These data were obtained from naïve controls and exposed subjects to distinguish between the potential TCR sequences that the virus potentially could elicit (from the naïve cells) and the memory responses that the virus did elicit (from exposed cells). The subjects came from around the world, encompassing the various human leukocyte antigen (HLA) subtypes that dominate in different ethnicities.

    While all of the patients are de-identified, the data can still be associated with clinically relevant metadata such as age, sex, and disease severity. You can learn more about the data available through immunoSEQ T-MAP COVID in our webinars.

    Figure 1. Top: Data included in the ImmuneCODE database, which is accessible via immunoSEQ T-MAP COVID. Bottom: immunoSEQ T-MAP COVID contains detailed metadata on over 1400 individuals exposed to SARS-CoV-2, including over 160,000 TCR–antigen pairs, representing a diverse population. Adapted from Nolan et al. (5)

    What can immunoSEQ T-MAP COVID tell you?

    Figure 2 shows some of the capabilities of immunoSEQ T-MAP COVID. By comparing your samples to sequences within the ImmuneCODE database, you can determine if your samples contain any of the virus-specific TCRs and get insight on what viral antigens to which those TCRs are responding. This can allow you to monitor the immune response to SARS-CoV-2 infection or vaccination over time by longitudinally tracking virus-specific TCR sequences. You can also identify TCRs that are shared between cohorts or populations and determine whether they represent public or private clones. Finally, a first-of-its-kind Classifier feature can inform you if your samples show a T-cell signature of past SARS-CoV-2 exposure.

    Overview of immunoSEQ T-MAP COVID and how it can aid researchers to uncover and monitor the T-cell response to SARS-CoV-2

    Figure 2. Overview of immunoSEQ T-MAP COVID offering capabilities and features.

    How to access immunoSEQ T-MAP COVID

    You can easily compare your immunoSEQ Assay data with immunoSEQ T-MAP COVID through the immunoSEQ Analyzer, which is freely available to scientists across the globe.

    The interface provides a user-friendly way to explore data, compare analyses, and create figures without any prior coding or computer science background. Therefore, immunoSEQ T-MAP COVID can accelerate research in COVID-19 diagnostics, vaccine development, and therapeutics, as well as provide insights on the basic biology of the virus and our immune response to it.

    The T-cell Classifier feature of immunoSEQ T-MAP COVID can be utilized by contacting us here.

    Example data output from immunoSEQ T-MAP COVID

    Figure 3 highlights some of the output data that can be generated with immunoSEQ T-MAP COVID and how they can be used in vaccine research to identify immunogenic antigens. In this analysis, researchers were tracking COVID-19-associated TCRs over the course of natural infection in a single patient with COVID-19. T-cell clones were identified at 1 day post diagnosis and again 2 weeks later. Researchers identified 77 expanded clones, 19 of which were already part of immunoSEQ T-MAP COVID and paired with SARS-COV-2 antigens. A total of 17 clones reacted to peptides in the ORF1ab region of the viral genome; the other 2 clones reacted to the spike protein.

    These data suggest that a peptide in this ORF1ab region is fairly immunogenic in this individual. If the same is true for other people, this region may contain an appropriate peptide on which to base a vaccine. The researchers are planning to use the data to assess if other people mount responses to this same ORF1ab region and to measure how the number of expanded clones might relate to clinical correlates of disease, such as disease severity and the time to recovery. Similar analyses can be done pre- and post-treatment to monitor which T-cell clones expand. (1) 

    Figure 3. Example of data output from immunoSEQ T-MAP COVID. Data show the mapping of COVID-19-associated TCRs throughout natural infection in a single patient with COVID-19.

    Insights from immunoSEQ T-MAP COVID

    The power of immunoSEQ T-MAP COVID is demonstrated in a recent publication by Snyder et al. (6) The authors used immunoSEQ T-MAP COVID to study data from over 1000 COVID-19 patients (5) to identify TCR-enhanced sequences. These data can assess both the breadth and the depth of the immune response, with breadth defined as the estimated proportion of enhanced TCR sequences in an individual’s T-cell repertoire, and depth defined as the relative frequency of these sequences in the repertoire.

    The analysis revealed publicly enhanced TCR sequences that could be useful as a biomarker to diagnose past or present SARS-CoV-2 infection. The ability of the TCR sequence biomarker to delineate SARS-CoV-2-positive samples from negative samples was tested in 325 COVID-19 samples and 1702 controls. The biomarker demonstrated high sensitivity, which increased with time from diagnosis (Figure 4).

    Figure 4. Sensitivity of a TCR sequence biomarker to detect SARS-CoV-2-positive samples among 325 COVID-19 patients. Adapted from Snyder et al. (6)

    The authors also used paired TCR–antigen data from the MIRA dataset to identify clinically relevant T-cell clones. These clones can be monitored over the course of natural infection or after the administration of vaccine candidates to provide valuable information on the immune system response. Using this information, Snyder et al. identified hotspots within the SARS-CoV-2 ORF beyond the Spike protein that induce a robust T-cell response in thousands of experiments. (6) They also identified common and potent viral antigens that induced a T-cell response in over 80% of the repertoires analyzed.

    Research applications of immunoSEQ T-MAP COVID

    COVID-19 impacts multiple research areas, across many disease states, especially those that have an impact on the immune system. It will be increasingly important to understand how COVID-19 affects patients with diseases such as cancer, autoimmune disorders, and other infectious diseases. In addition, understanding a patient’s COVID-19 history can be instrumental in clinical trials and vaccine development programs for non-SARS-CoV-2 infections. The immunoSEQ T-MAP COVID tools can be a useful resource for researchers as they try to study these diseases and potential treatments in a post-COVID-19 world (Figure 5).

    Figure 5. Examples of how immunoSEQ T-MAP COVID can be applied to research applications.

    Clinical research

    Some patients show prolonged effects of COVID-19 on the immune system. This means that in any type of clinical research carried out in the foreseeable future, it will be essential to know if a patient’s immune system has been affected by SARS-CoV-2.

    Researchers can use immunoSEQ T-MAP COVID to compare their samples with the COVID-19 samples accumulated in the ImmuneCODE database to determine if the patients in their trials may have been previously exposed to SARS-CoV-2. Assessing T-cell immune response to SARS-CoV-2 can provide insights into immune-related adverse events in drug trials, for vaccine trials it will be important to determine if individuals had a past T-cell immune response to SARS-CoV-2 and how this immune response changes/evolves longitudinally over time post-vaccine administration.

    Other infectious diseases

    T cells in the blood of subjects who were never exposed to SARS-CoV-2—that is, blood samples taken before 2020—have shown significant cross-reactivity to SARS-CoV-2 antigens. (7, 8) This cross-reactivity may be from memory T cells from exposure to other coronaviruses, such as those responsible for colds. It is also possible that these memory T cells could explain why some people suffer such severe disease from COVID-19 while others remain asymptomatic. (9) Thus, infectious disease researchers may find it useful to compare their samples with the COVID-19 samples gathered in immunoSEQ T-MAP COVID to look for cross-reactive T cells.

    Autoimmune disorders

    Some patients with COVID-19 experience autoimmune-like symptoms, which is not uncommon with viral infections. These symptoms could be caused by the dramatic T-cell response that the body elicits to fight off viral and other pathogens, damaging the bystander host cells in the process. Alternatively, it could be due to the autoreactive T cells that cause so much trouble in autoimmune disorders by mistakenly reacting to the body’s own cells as if they were pathogenic invaders and treating them as such. (10)

    Autoimmune signatures can often appear well after the causative infection and its symptoms have waned; they can appear even in people who had only mild or even no symptoms of the virus. This is what happened with those children who developed multisystem inflammatory syndrome (MIS-C) and Kawasaki-like disease after being infected with SARS-CoV-2. (11) It is vital to have a sensitive way to determine if people who present with such signatures have ever been exposed to SARS-CoV-2, or if their autoimmune problems stem from another issue. Sequencing their TCRs could do that. Comparing datasets from patients with autoimmune disorders with those from patients with COVID-19 using the immunoSEQ T-MAP COVID tool may help us to understand the mechanisms of COVID-19-related autoimmunity, and autoimmunity in general.

    Oncology

    The immune system plays a crucial role in cancer. Since immune cells would generally recognize and eliminate tumor cells, tumor cells have developed mechanisms to evade cytotoxic T cells by recruiting anti-inflammatory T cells and expressing proteins that engage with and inhibit T-cell activity (Figure 6).

    Figure 6. Cancer cells need to evade cytotoxic T cells to increase tumor burden. Adapted from Gonzalez et al. (12)

    Many patients with cancer are immunocompromised. While this may put them at risk for serious COVID-19-related events, some also hypothesize that this may protect patients from the overactive immune stimulation that some COVID-19 patients experience. (13, 14) Understanding the T-cell response in patients with cancer and COVID-19 is key to understanding the risks for and symptoms of cancer patients with COVID-19.

    In addition to understanding the effects of COVID-19 on cancer, monitoring the T-cell repertoire can have implications for understanding the impact of COVID-19 on cancer treatments. Immunotherapies have become a mainstay in oncology treatment, changing the treatment landscape for many tumor types. Immunotherapies galvanize the body’s own T-cell response of fighting tumor cells. Some of the most common immunotherapies, dubbed checkpoint inhibitors, target proteins found on T cells, allowing them to kill tumor cells. immunoSEQ Assay data have shown that the characteristics of a patient’s pre-treatment TCR repertoire can correlate with response to checkpoint inhibitors. (15) Tools such as immunoSEQ T-MAP COVID can help researchers to understand how COVID-19-related changes to the TCR repertoire may affect response to immunotherapies.

    Knowledge of the immune repertoire is also crucial for understanding immune-related adverse events in cancer patients, which may sometimes be difficult to distinguish from symptoms of COVID-19. immunoSEQ Assay data have shown that the same T cells that checkpoint inhibitors induce to recognize and attack tumors can cause autoimmune disease in the patients whose cancers are most responsive to the treatment. (16) Comparing immune repertoire datasets of cancer patients and COVID-19 patients with immunoSEQ T-MAP COVID can help to determine if COVID-19 or immunotherapies may be the cause of some immune-related adverse events.

    How to use immunoSEQ T-MAP COVID in your research

    In summary, immunoSEQ T-MAP COVID incorporates data from the immunoSEQ Assay and other resources to help researchers compare their immunoSEQ Data with a vast database containing SARS-CoV-2-specific TCRs and TCR–antigen pairs. You can now assess if samples showed a past T-cell immune response to SARS-CoV-2. This information can be instrumental in accelerating research and vaccine development for COVID-19 and is vital for understanding the effect of COVID-19 on the T-cell repertoire in various diseases. immunoSEQ T-MAP COVID is available to researchers worldwide and contains a suite of analysis tools via the immunoSEQ Analyzer that provides a simple, user-friendly way to create publication-worthy data and figures. If you think that the immunoSEQ Assay or immunoSEQ T-MAP COVID can help you in your research, contact us. A representative can advise you on anything from initial experimental design questions to data analysis queries.

     For Research Use Only. Not for use in diagnostic procedures.

    References

    1.     Long Q-X, Liu B-Z, Deng H-J, Wu G-C, Deng K, Chen Y-K, et alAntibody responses to SARS-CoV-2 in patients with COVID-19. Nat Med. 2020;26(6):845–8.

    2.     Tan J, Sack BK, Oyen D, Zenklusen I, Piccoli L, Barbieri S, et alA public antibody lineage that potently inhibits malaria infection through dual binding to the circumsporozoite protein. Nat Med. 2018;24(4):401–7.

    3.     Staines HM, Kirwan DE, Clark DJ, Adams ER, Augustin Y, Byrne RL, et al.  Dynamics of IgG seroconversion and pathophysiology of COVID-19 infections. medRxiv. 2020;2020.06.07.20124636.

    4.     Long Q-X, Tang X-J, Shi Q-L, Li Q, Deng H-J, Yuan J, et alClinical and immunological assessment of asymptomatic SARS-CoV-2 infections. Nat Med. 2020;26(8):1200–4.

    5.     Nolan S, Vignali M, Klinger M, Dines JN, Kaplan IM, Svejnoha E, et al.  A large-scale database of T-cell receptor beta (TCRβ) sequences and binding associations from natural and synthetic exposure to SARS-CoV-2. Res Sq. 2020.

    6.     Snyder TM, Gittelman RM, Klinger M, May DH, Osborne EJ, Taniguchi R, et al.  Magnitude and Dynamics of the T-Cell Response to SARS-CoV-2 Infection at Both Individual and Population Levels. medRxiv. 2020.

    7.     Sette A, Crotty S.  Pre-existing immunity to SARS-CoV-2: the knowns and unknowns. Nat Rev Immunol. 2020;20(8):457–8.

    8. Grifoni A, Weiskopf D, Ramirez SI, Mateus J, Dan JM, Moderbacher CR, et al.  Targets of T Cell Responses to SARS-CoV-2 Coronavirus in Humans with COVID-19 Disease and Unexposed Individuals. Cell. 2020;181(7):1489-1501.e15.

    9. Mateus J, Grifoni A, Tarke A, Sidney J, Ramirez SI, Dan JM, et al.  Selective and cross-reactive SARS-CoV-2 T cell epitopes in unexposed humans. Science. 2020;370(6512):89–94.

    10. Benoist C, Mathis D.  Autoimmunity provoked by infection: how good is the case for T cell epitope mimicry? Nat Immunol. 2001;2(9):797–801.

    11. Galeotti C, Bayry J.  Autoimmune and inflammatory diseases following COVID-19. Nat Rev Rheumatol. 2020;16(8):413–4

    12. Gonzalez H, Hagerling C, Werb Z.  Roles of the immune system in cancer: from tumor initiation to metastatic progression. Genes Dev. 2018;32(19–20):1267–84.

    13. Bersanelli M.  Controversies about COVID-19 and anticancer treatment with immune checkpoint inhibitors. Immunotherapy. 2020;12(5):269–73.

    14. Bakouny Z, Hawley JE, Choueiri TK, Peters S, Rini BI, Warner JL, et al.  COVID-19 and Cancer: Current Challenges and Perspectives. Cancer Cell. 2020;38(5):629–46.

    15. Zhang J, Ji Z, Caushi JX, El Asmar M, Anagnostou V, Cottrell TR, et al.  Compartmental Analysis of T-cell Clonal Dynamics as a Function of Pathologic Response to Neoadjuvant PD-1 Blockade in Resectable Non-Small Cell Lung Cancer. Clin Cancer Res Off J Am Assoc Cancer Res. 2020;26(6):1327–37.

    16. Berner F, Bomze D, Diem S, Ali OH, Fässler M, Ring S, et al.  Association of Checkpoint Inhibitor-Induced Toxic Effects With Shared Cancer and Tissue Antigens in Non-Small Cell Lung Cancer. JAMA Oncol. 2019;5(7):1043–7.

    Contact Us Contact Us
    Contact Us

    Looking for more information? Help with experimental design or technical support? Interested in speaking to someone? Contact us!

    Learn More