Activation-inducing marker assay

Abstract

The present disclosure relates to the field of biology. In particular, the present disclosure relates to T cell activation-inducing marker assays useful, for example, in determining whether a subject was previously exposed to an antigen of interest, such as by infection with a pathogen; and kits and compositions related to the determination of the T cell activation inducing marker.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This patent application claims priority to U.S. Provisional Patent Application No. 63 / 479,902, filed on January 13, 2023, the entire contents of which are incorporated herein by reference. Technical Field

[0003] The present disclosure relates to the field of biology. Specifically, the present disclosure relates to a T cell activation induction marker assay, which can be used, for example, to determine whether a subject has been previously exposed to an antigen of interest, such as by infection with a pathogen, and a kit related to the T cell activation induction marker assay. Background Art

[0004] Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), poses an ongoing and significant threat to public health. The presence of neutralizing antibodies against SARS-CoV-2 is an indicator of protective immunity acquired from past infection (or vaccination). In addition to humoral immune responses, T cells play a key role in orchestrating adaptive immune responses and acting as effectors against viral infection. Previous studies of acute and convalescent COVID-19 patients have reported that T cell responses are associated with disease remission, suggesting that SARS-CoV-2-specific CD4+ T cell and CD8+ T cell responses are involved in the resolution of primary SARS-CoV-2 infection. See Liao et al. (2020); Moderbacher et al. (2020); Zhou et al. (2020). Furthermore, previous studies have reported that SARS-CoV-2-specific CD4+ and CD8+ T cells were detected in 100% and approximately 70% of convalescent individuals shortly after resolution. See Grifoni et al., 2020.

[0005] To fully understand the immune response triggered by SARS-CoV-2 infection, it is necessary to consider the various components of the immune response, including B cells, CD4+ T cells, and CD8+ T cells, because the reaction kinetics of these different components may be independent of each other. Various assays are routinely used to measure the number and quality of antigen-specific T cells in humans. See Ten Brinke et al. (2017). Enzyme-linked immunospot ("ELISpot") and intracellular cytokine staining ("ICS") assays are particularly commonly used in such studies. See, for example, Saade et al. (2012); Slota et al. (2011); Smith et al. (2015). The ELISpot assay involves stimulating peripheral blood mononuclear cells ("PBMCs") with antigen in a multiwell plate with a membrane coated with an anti-cytokine capture antibody. Cytokines produced by antigen-specific T cells will bind to the capture antibody and are therefore detectable using an enzyme-conjugated secondary antibody and a chromogenic substrate. The ELISpot assay is highly sensitive, for example, cells producing fewer than 100 cytokine molecules can be detected. See Shirai et al. (1993). As a result, the ELISpot assay has become one of the most commonly used and highly validated assays for detecting antigen-specific T cell responses in clinical trials. See, for example, Britten et al. (2008); Moodie et al. (2010). However, the ELISpot assay has several major drawbacks that limit its use as a tool for studying immune responses to infection, including limitations on the number of parameters that can be studied, lack of phenotypic information, and preferential detection of effector cells. Given these limitations, the ELISpot assay cannot fully elucidate and may underestimate total antigen-specific T cell responses.

[0006] As an alternative, intracellular cytokine staining (ICS) assays can be used to provide additional information about the quantity and quality of antigen-induced T cells. Briefly, antigen-stimulated PBMCs are stained with fluorescently labeled anti-cytokine antibodies and analyzed by flow cytometry. ICS assays allow detailed phenotypic and functional analysis of antigen-specific T cell populations. However, ICS assays are also limited by the number of parameters that can be assessed. Therefore, ICS assays may be biased towards detecting specific types of T cells. For example, ICS assay panels used in clinical trials are typically assays for IFNγ, IL2, and TNFα, and therefore detect responses that are biased towards Th1. See Coughlan et al. (2015); Horton et al. (2007). T cell responses to infection (or vaccination) are often highly heterogeneous, and therefore, detection based on the expression of one or more cytokines may underestimate the frequency of antigen-specific cells. See De Rosa et al. (2004).

[0007] In view of these limitations, recent studies have promoted the use of activation-induced marker (AIM) assays, which can be used to identify and measure antigen-specific T cell responses based on the upregulation of surface markers stimulated by TCRs. The AIM assay can be used to generate a broader picture of overall antigen-specific T cell responses. However, the AIM assay has not been fully evaluated and has not been compared with more conventional cytokine-based methods. In addition, given the large number of surface markers that may be upregulated, it is impossible to predict which individual markers or marker combinations can be used to accurately detect antigen-specific T cells without repeated trials. Summary of the Invention

[0008] Although significant progress has been made in the development of assays for detecting humoral immune responses and cellular immune responses to infection, in view of the diversity of possible antigens (including antigens from pathogens) and the limitations of current assays, additional improvements are still needed in this field. Specifically, there is currently a demand for assays and methods for accurately detecting and / or measuring antigen-specific T cell responses caused by SARS-CoV-2 infection and other viral infections in human or animal subjects. Such assays and methods can be used for, for example, diagnosing past infections of such viruses, and providing guidance for determining when a subject may benefit from booster vaccinations. Therefore, T cell AIM assays and kits and methods related to the T cell AIM assays are provided herein. In some aspects, these AIM assays, kits and methods can be used for detecting SARS-CoV-2 specific CD4+ and CD8+ T cells, thereby allowing detection and / or diagnosis of infection, and may be used as a tool for guiding arrangements for vaccination and treatment decisions. In other cases, such assays, kits and methods can be used for detecting CD4+ and CD8+ T cells specific to other clinically relevant viruses.

[0009] In a first general aspect, the present disclosure provides a kit comprising a plurality of antibodies, wherein each antibody is capable of specifically binding to a single cell surface marker selected from the group consisting of CD3, CD4, CD8, CD14, CD19, LAG3, CD25, CD69, OX40, 41BB, CD38, CD40L, CD107 and CD274.

[0010] In some aspects, the multiple antibodies include antibodies that are jointly bound to at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 or 14 different cell surface markers selected from the group. For example, the kit may include antibodies that are specific for any pair of cell surface markers as described herein (e.g., CD69 and OX40, or CD25 and 41BB). In other aspects, the kit may include antibodies that are each specific for a biomarker of any combination selected from cell surface markers as described herein. For example, in some aspects, the multiple antibodies include antibodies that specifically bind to any combination of CD25, CD69, OX40, 41BB, CD40L, CD107, CD38 and / or CD274 (e.g., to monitor cell activation in the presence of an antigen stimulant or after treatment with an antigen stimulant). In some aspects, the plurality of antibodies includes antibodies that specifically bind to CD3, CD4, CD8, CD14, and / or CD19 (e.g., to isolate CD4+ and / or CD8+ cells); and / or antibodies that specifically bind to LAG3 (e.g., to identify depleted cells). In some aspects, the kit may include antibodies specific for all 14 cell surface biomarkers described in the previous paragraph. It should be understood that the kits described herein can utilize monoclonal or polyclonal antibodies and / or antibody fragments as binding agents to detect the cell surface markers described herein.

[0011] In some aspects, the plurality of antibodies includes antibodies that specifically bind: a) CD69 and OX40; b) CD25 and 41BB; c) CD25 and CD38; d) CD25 and OX40; e) CD274 and 41BB; and / or f) CD274 and CD69.

[0012] In some aspects, the kit may include fluorophore-conjugated antibodies (e.g., to allow the use of a flow cytometer or other instrument to detect antibodies bound to an antigen). In some aspects, different fluorophores may be used for each cell surface marker. For example, an exemplary panel may include any or all of the following fluorophore-antibody conjugates: FITC / CD8, PE / CD25, PERCPCy5.5 / CD3, BV421 / CD137, BV510 / CD4, BV605 / LAG3, BV650 / CD274, BV711 / CD134 (OX40), BV785 / CD38, APC / CD69, PE-Cy7 / CD154, PE-Dazzle / CD107, Alexa 700 / CD14, and / or Alexa 700 / CD19). It should be understood that any fluorophore disclosed herein may be used as a conjugate of any cell surface marker (or any other antigen) described herein. In some aspects, the kit can include multiple fluorophore-conjugated antibodies, wherein each fluorophore-conjugated antibody in the fluorophore-conjugated antibodies is specific to different cell surface markers, and wherein different fluorophores are used for each cell surface marker. In some aspects, the multiple fluorophore-conjugated antibodies are provided as a single mixture, optionally including some or all of the fluorophore-conjugated antibodies of optimized concentration or ratio. In some aspects, the kit according to the present disclosure can include one or more alternative fluorophore-conjugated binding agents (e.g., antibody fragments, aptamers, or any other binding agent capable of specific binding to cell surface markers as described herein) to replace any of the antibodies described in any of the exemplary aspects of each exemplary aspect described herein.

[0013] The various antibodies included as part of a test kit as described herein can be provided in dry (e.g., lyophilized) or liquid form. In some aspects, the various antibodies can be provided as a single mixture, while in other aspects, the various antibodies can be provided in separate compartments or containers (e.g., antibodies specific for each cell surface marker or for any subset of cell surface markers can be provided in different compartments or containers). In some aspects, the test kit can include a buffer or other solvent that can be used to prepare an antibody solution (e.g., to perform a determination as described herein) using the various antibodies.

[0014] In some aspects, the kit further comprises a cell viability marker, wherein the cell viability marker comprises a binding agent that selectively binds to live cells or dead cells and / or a dye that stains live cells or dead cells. For example, in some aspects, the cell viability marker comprises Fixable near-infrared dyes or by Any other sales Stain (e.g., fixable blue / purple / lemon yellow / aqua / yellow / green / olive / orange / red / fixable far-red stain). DAPI (4',6-diamidino-2-phenylindole) and other known dyes that can be used to distinguish between live and dead eukaryotic cells, such as 7-AAD (7-aminoactinomycin D), Hoechst dye or propidium iodide, can also be used. Such dyes are available from multiple manufacturers and generally work based on the reaction of fluorescent active dyes with cellular proteins (amines) or by the increase or shift in fluorescence that occurs after DNA intercalation. When used at typical concentrations for staining purposes, many of these dyes cannot penetrate the membranes of living cells, so only cell surface proteins can react with the dye, resulting in dim staining of living cells. In contrast, active dyes can penetrate the damaged membranes of dead cells and stain both internal and external amines, and therefore dead cells are strongly stained. Similarly, some cell viability marker dyes (e.g., DNA intercalating dyes) may exhibit limited permeability when applied to live cell membranes, but exhibit a greater ability to penetrate and stain dead cells when applied at concentrations typically used for live / dead staining.

[0015] In some aspects, the kit may further comprise one or more secondary binding agents, wherein each secondary binding agent is capable of specifically binding to a cytokine (e.g., IFN-γ, TNF-α, IL-2, IL-4, IL-6, or IL-10). Each secondary binding agent may comprise an antibody, an antibody fragment, an aptamer, or any other binding agent capable of specifically binding to a cytokine or any epitope or fragment thereof. The secondary binding agents can be used in assays described herein, for example, to detect and measure cytokine expression levels, thereby providing an additional set of parameters that can be used (alone or in combination with cell surface marker expression level data) to determine whether a subject has previously been infected with the SARS-CoV-2 virus (or to perform any other assay described herein).

[0016] In some aspects, the kit may further comprise one or more antigens (e.g., one or more peptides) capable of activating peripheral blood mononuclear cells ("PBMCs"), such as CD4+ T cells or CD8+ T cells. In some aspects, the antigen comprises at least one fragment of a polypeptide sequence of a protein produced by a strain of the SARS-CoV-2 virus. The antigen may comprise a peptide having a length of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 amino acids, or a length within the range defined by any pair of integers between 2 and 20. In some aspects, the at least one fragment comprises a peptide having a polypeptide sequence of a portion of a spike protein, a membrane protein, an outer membrane protein, or a nucleocapsid protein of a strain of the SARS-CoV-2 virus.

[0017] In some aspects, the kit further comprises one or more fluorescence minus one ("FMO") control samples, wherein each FMO control sample comprises antibodies specific for all but one of the cell surface markers.

[0018] In some aspects, the kit further comprises one or more solvents and / or buffer solutions.

[0019] In a second general aspect, the present disclosure provides a method for determining whether a subject has been infected with a SARS-CoV-2 virus, the method comprising: a) generating a processed sample by contacting a plurality of CD4+ T cells and / or CD8+ T cells obtained from the subject with at least one antigen, wherein the antigen comprises a peptide fragment of a protein of the strain of the SARS-CoV-2 virus; b) contacting the CD4+ T cells and / or CD8+ T cells in the processed sample with a plurality of fluorophore-conjugated antibodies to produce a labeled sample, wherein each antibody is specific for a protein selected from the group consisting of CD3, CD4, CD8, CD14, CD19, LAG3, CD25, CD69, and the like. , OX40, 41BB, CD38, CD40L, CD107 and / or CD274 cell surface markers; c) detecting CD4+ T cells and / or CD8+ T cells expressing multiple cell surface markers selected from CD3, CD4, CD8, CD14, CD19, LAG3, CD25, CD69, OX40, 41BB, CD38, CD40L, CD107 and / or CD274 in the labeled sample based on the fluorescent signal generated by the fluorophore-conjugated antibody; and d) determining that the subject has been infected with the SARS-CoV-2 virus based on the detected CD4+ T cells and / or CD8+ T cells. In some aspects, steps a), b), c) and / or d) are performed using a kit according to any exemplary aspect described herein.

[0020] In some aspects, the detecting step c) further comprises detecting the CD4+ T cells and / or CD8+ T cells expressing multiple cell surface markers in the labeled sample using at least 2, 3, 4, 5, 6, 7 or 8 replicate samples.

[0021] In some aspects, the detection step c) further comprises a step of normalizing the fluorescent signal generated by the fluorophore-conjugated antibody. The normalization step can be performed, for example, using a negative control sample consisting of a peptide diluent (e.g., water) or comprising water, another solvent, and / or a buffer. For example, a negative control can comprise the same volume of the same peptide diluent as a test sample for receiving SARS-CoV-2 viral antigens (peptide fragments or peptide fragment pools of proteins comprising strains of SARS-CoV-2 viruses). Alternatively, a negative control can comprise the same volume of the same peptide diluent as a test sample for receiving viral antigens of interest (peptide fragments or peptide fragment pools of proteins comprising any strain of the virus of interest). In some aspects, the peptide diluent can be, for example, water, or comprise dimethyl sulfoxide (DMSO) and phosphate-buffered saline. In some aspects, a positive control sample comprising a peptide pool containing multiple viral antigens can also be used alone or in combination with a negative control. In some aspects, the peptide pool comprises a collection of peptides comprising MHC class II restricted T cell epitopes from human cytomegalovirus (CMV), Epstein-Barr virus, influenza virus, tetanus toxin, and adenovirus 5 ("CEFTA").

[0022] In some aspects, the normalization step comprises: i) testing whether the fluorescent signal generated by the fluorophore-conjugated antibody that binds to the CD4+ T cells and / or CD8+ T cells in the labeled sample is higher or lower than the fluorescent signal obtained using the negative control sample; and ii) testing whether the fluorescent signal generated by the fluorophore-conjugated antibody that binds to the CD4+ T cells and / or CD8+ T cells in the labeled sample is higher or lower than the signal obtained using the positive control sample. In some aspects, the normalization step further comprises subtracting the fluorescent signal obtained using the negative control sample from the fluorescent signal generated by the fluorophore-conjugated antibody that binds to the CD4+ T cells and / or CD8+ T cells in the labeled sample when the negative control fluorescent signal is low. In some aspects, when the negative control fluorescence is high, the fluorescent signal generated by the fluorophore-conjugated antibody that binds to the CD4+ T cells and / or CD8+ T cells can be set to zero. In some aspects, the normalization step further comprises normalizing the fluorescent signal generated by the fluorophore-conjugated antibody that binds to the CD4+T cells and / or CD8+T cells in the labeled sample to the fluorescent signal obtained using the positive control sample when the positive control fluorescent signal is high. In some aspects, when the positive control fluorescence is low, the fluorescent signal generated by the fluorophore-conjugated antibody that binds to the CD4+T cells and / or CD8+T cells can be set to a non-zero constant value, such as a value of one, two, or three. Comparison of the fluorescent signal generated by the fluorophore-conjugated antibody that binds to the CD4+T cells and / or CD8+T cells in the labeled sample with the positive and / or negative controls can be based on fluorescent signals obtained from multiple replicates.

[0023] In some aspects, determining step d) further comprises determining that the subject has been infected with the SARS-CoV-2 virus based on the expression level of one or more cytokines obtained from the CD4+T cells and / or CD8+T cells in the treated sample. In some aspects, determining step d) further comprises determining that the subject has been infected with the SARS-CoV-2 virus based on the change in the amount of CD4+T cells and / or CD8+T cells expressing the multiple cell surface markers in the labeled sample compared to the median or average amount determined using samples obtained from one or more SARS-CoV-2 original donors. The change in the amount of the multiple cell surface markers can be measured, for example, as: a) a percentage difference compared to the median amount; b) a fold change difference compared to the median amount; or b) a numerical difference compared to the median amount. In other aspects, similar assays can be performed on any other virus of interest being assayed (e.g., compared to using samples obtained from one or more original donors). The amount of CD4+ T cells and / or CD8+ T cells expressing various cell surface markers in the labeled samples is based on the variation in the amount of CD4+ T cells and / or CD8+ T cells expressing various cell surface markers in the labeled samples compared to the median or mean amount measured in samples obtained from the donor.

[0024] In some aspects, methods for determining whether a subject has been infected with SARS-CoV-2 virus (or another virus of interest), or any other method described herein, can utilize a plurality of fluorophore-conjugated antibodies used in step b), including antibodies specific for: a) CD69 and OX40; b) CD25 and 41BB; c) CD25 and CD38; d) CD25 and OX40; e) CD274 and 41BB; and / or f) CD274 and CD69. For example, any combination of the above marker pairs can be used in the contacting or detecting steps of the methods described in the preceding paragraphs.

[0025] In a third general aspect, the present disclosure provides a method for determining that a subject is in need of SARS-CoV-2 virus vaccination (e.g., booster vaccination), the method comprising: a) generating a processed sample by contacting a plurality of CD4+ T cells and / or CD8+ T cells obtained from the subject with at least one antigen, wherein the antigen comprises a peptide fragment of a protein of the strain of SARS-CoV-2 virus; b) contacting the CD4+ T cells and / or CD8+ T cells in the processed sample with a plurality of fluorophore-conjugated antibodies to produce a labeled sample, wherein each antibody is specific for a protein selected from the group consisting of CD3, CD4, CD8, CD14, CD19, LAG3, CD25, and / or CD8. , CD69, OX40, 41BB, CD38, CD40L, CD107 and / or CD274 cell surface markers; c) based on the fluorescent signal generated by the fluorophore-conjugated antibody, detecting the CD4+T cells and / or CD8+T cells expressing multiple cell surface markers selected from CD3, CD4, CD8, CD14, CD19, LAG3, CD25, CD69, OX40, 41BB, CD38, CD40L, CD107 and / or CD274 in the labeled sample; and d) based on the detected CD4+T cells and / or CD8+T cells, determining that the subject needs SARS-CoV-2 virus vaccination. In other aspects, similar determinations can be made about the need for vaccination against any other virus of interest (e.g., by using antigens comprising peptide fragments of proteins of a strain of the virus of interest, and detecting CD4+T cells and / or CD8+T cells as described above).

[0026] It should be understood that in some aspects, the method of determining that a subject is in need of vaccination with the SARS-CoV-2 virus or vaccination against another virus of interest may further comprise any of the steps, components, or parameters of the method of determining that a subject has been infected with the SARS-CoV-2 virus or other virus of interest described herein.

[0027] To accomplish the foregoing and related ends, the one or more aspects comprise the features hereinafter fully described and particularly pointed out in the claims. The following description and the accompanying drawings set forth in detail certain illustrative features of the one or more aspects. However, these features are indicative of but a few of the various ways in which the principles of the various aspects may be employed, and this description is intended to include all such aspects and their equivalents. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The drawings set forth herein illustrate and describe exemplary aspects of the disclosure and are not intended to limit the scope of the invention, which is defined by the claims.

[0029] Figures 1 to 2 is a cartoon representation showing an exemplary AIM assay workflow that can be used to determine whether a subject has been infected with the SARS-CoV-2 virus (or another virus of interest) as described herein.

[0030] Figure 3 Summarized are flow cytometric analysis and gating strategies for exemplary AIM assays according to the present disclosure.

[0031] Figure 4 Shown are a series of curves summarizing the flow cytometric analysis and gating strategy for the cell surface markers CD25 and 41BB.

[0032] Figure 5 is a table showing exemplary cell surface marker pairs that can be used in the kits and / or methods described herein.

[0033] Figure 6 is a graph showing the percentage of activated CD4+ T cells detected using the cell surface markers CD25 and 41BB, measured using a kit according to the present disclosure in samples obtained from a population of recovered COVID-19 subjects compared to samples obtained from a population of naive COVID-19 donors.

[0034] Figures 7 and 8 Data obtained from ELISpot assays demonstrating T cell activation and IFN-γ release from COVID-19 convalescent donors following SARS-CoV-2 peptide stimulation are summarized.

[0035] Figures 9A to 9CFigure 2 is a graph summarizing cytokine release data demonstrating T cell activation and IFN-γ release from COVID-19 convalescent donors following SARS-CoV-2 peptide stimulation.

[0036] FIG. 10A to FIG. 10B Figure 2 shows the number of activated CD4+ T cells (CD25 and 41BB) detected using cell surface markers after performing an AIM assay using a kit according to the present disclosure on samples obtained from SARS-CoV-2 naive donors versus COVID-19 convalescent donors who were seropositive or seronegative for SARS-CoV-2 antibodies. Figure 10A ) and activated CD8+ T cells ( Figure 10B ) percentages.

[0037] Figures 11 to 14 Figure 2 is a graph showing the fold change in CD4+ and CD8+ T cell responses of COVID-19 convalescent donors assessed using the AIM assay according to the present disclosure ( Figure 11 、 Figure 13 ) and the difference ( Figure 12 、 Figure 14 ) chart.

[0038] Figures 15 and 16 Two graphs are shown that illustrate the use of water ( Figure 15 ) and CEFTA pools ( Figure 16 ) Normalization of three cell surface marker pairs (CD25 and OX40, CD25 and CD38, and CD25 and 41BB).

[0039] Figure 17 is a hierarchical cluster diagram showing the clustering of various CD4 T cell and CD8 T cell surface marker pairs tested with the AIM assay according to the present disclosure using samples from COVID-19 naive and COVID-19 convalescent donors.

[0040] Figure 18 is a graph showing the receiver operating characteristic (ROC) curve of a random forest model trained using the AIM data for the set of cell surface markers described herein to determine whether a sample is from a COVID-19 convalescent patient or a COVID-19 naive donor.

[0041] Figure 19 is a graph comparing the random forest model importance scores versus the negative logarithm of the Mann-Whitney U test p-value. This graph is annotated to highlight several cell surface marker pairs that stand out as relatively important features.

[0042] Figure 20is a hierarchical clustering diagram showing the Figure 19 Clustering of the six features represented by the annotations in .

[0043] Figure 21 is a table summarizing the available data supporting the various cell surface marker pairs described herein.

[0044] Figure 22 It is shown that the Figure 11 The graphs shown are graphs of the raw data.

[0045] Figure 23 It is shown that the Figure 12 The graphs shown are graphs of the raw data.

[0046] Figure 24 It is shown that the Figure 13 The graphs shown are graphs of the raw data.

[0047] Figure 25 It is shown that the Figure 14 The graphs shown are graphs of the raw data.

[0048] Figure 26 It is shown that the Figure 19 The graphs shown are graphs of the raw data.

[0049] Figure 27 It is shown that the Figure 20 The graphs shown are graphs of the raw data.

[0050] Figures 28 to 30 is a graph showing responses (CD4+ cells) of donor samples observed during a study evaluating the AIM assay described herein for detection and / or diagnosis of CMV infection. Figure 28 shows the response of CMV+ donor samples, while Figures 29 to 30 The responses of the original donor samples are shown ( Figure 30 yes Figure 29 (enlarged version of ).

[0051] Figures 31 to 33 is a graph showing responses (CD8+ cells) of donor samples observed during a study evaluating the AIM assay described herein for detection and / or diagnosis of CMV infection. Figure 31 shows the response of CMV+ donor samples, while Figures 32 to 33 The responses of the original donor samples are shown ( Figure 33 yes Figure 32 (enlarged version of ).

[0052] Figure 34is a graph showing the percentage of activated CD4+ T cells detected using the cell surface markers CD25 and 41BB after performing an AIM assay for detecting and / or diagnosing CMV infection using a kit according to the present disclosure. DETAILED DESCRIPTION

[0053] The detailed description set forth below in conjunction with the accompanying drawings is intended as a description of various configurations and is not intended to represent the only configuration in which the concepts described herein may be practiced. The detailed description includes specific details for the purpose of providing a thorough understanding of the various concepts. However, it will be apparent to those skilled in the art that these concepts may be practiced without these specific details.

[0054] The study of cellular immune responses provides a robust way to understand previous exposure to pathogens or antigens from other sources. Following infection, cellular immune responses to pathogens are long-lasting, whereas for some pathogens, antibody production responses tend to decrease over time. In the case of the global COVID-19 pandemic caused by the SARS-CoV-2 virus, the production of antiviral serum antibodies is often undetectable after about 6 months. T cell-mediated immune responses provide long-term protection against severe disease, and early studies have shown that this response is detectable over the longer term. See Sette et al. (2021). The current commercially available gold standard for assessing T cell responses is the ELISpot test. Although reliable, the method is unable to perform subtyping of antigen-responsive T cells and has limited ability to measure the spectrum of T cell activation.

[0055] Marker Panel for AIM Assay

[0056] The present disclosure addresses these and other shortcomings by providing diagnostic kits and methods based on flow cytometry marker panels that can be used to accurately assess CD4+ and / or CD8+ T cell immune responses to SARS-CoV-2 peptides (or viral peptides associated with any other virus of interest) in donors recovering from COVID-19. In some aspects, such panels include one or more cell surface markers for CD4+ and CD8+ T cells (e.g., CD3, CD4, CD8, CD14, CD19, LAG3, CD25, CD69, OX40, 41BB, CD38, CD40L, CD107, and / or CD274), and optionally at least one cell viability marker (e.g., a binding agent, such as an antibody, dye, or stain, that can be used to selectively distinguish live from dead cells). In some aspects, the panel can include one or more cell surface markers that can be used for immunophenotyping and / or identifying exhausted cells (e.g., CD3, CD4, CD8, CD14, CD19, and / or LAG3), and one or more cell surface markers that can be activated and induced after exposure to antigenic stimulation (e.g., CD25, CD69, OX40, 41BB, CD38, CD40L, CD107, and / or CD274). In some aspects, the panel can include any combination of the aforementioned cell surface markers and / or cell viability markers (e.g., any 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15 markers listed in this paragraph or otherwise disclosed herein). As described in further detail below, it has been discovered that certain combinations of the cell surface markers described herein (e.g., CD69 and OX40; CD25 and 41BB; CD25 and CD38; CD25 and OX40; CD274 and 41BB; and / or CD274 and CD69) are particularly useful for detecting and assessing the response of CD4+ and / or CD8+ cells following exposure to one (or more) SARS-CoV-2 viral antigens or antigens associated with an alternative virus of interest, thereby allowing for efficient and accurate determination of whether a subject is infected or has previously been infected with the virus.

[0057] Figures 1 to 2Summarize the flow cytometry analysis and gating strategy for exemplary AIM determination using the marker panel and kit described herein. As shown here, PBMCs from COVID-19 original subjects and COVID-19 convalescent patients can be collected and treated with one or more peptide fragments of one or more SARS-CoV-2 viral proteins as antigenic stimulation. The treated cells can then be separated from the supernatant in the cell culture for subsequent processing. In this example, a variety of fluorophore-conjugated antibodies for detecting one or more activation-induced cell surface markers, one or more cell surface markers that can be used for immunophenotyping and / or identification of exhausted cells, and at least one binding agent, dye or stain that can be used to distinguish between live and dead cells are used to perform AIM determination on the treated cells. In parallel, supernatants can be collected and labeled to measure the expression of various cytokines (e.g., IFN-γ, TNF-α, IL-2, IL-4, IL-6 and / or IL-10). In this case, a fluorescent bead-based assay is used. The labeled cells and supernatant can then be analyzed by flow cytometry.

[0058] In this example, flow cytometry is used to detect and measure the fluorescent signal produced by labeled cells and supernatant, for example, to measure the expression level of various cytokines, and to assess the immune response of PBMC in response to antigen stimulation. For example, flow cytometry can be used to detect the quantity, percentage or ratio of CD4+ and / or CD8+T cells expressing any one of the cell surface markers (or any combination) described herein in the sample. As demonstrated by the examples provided below, various combinations of cell surface markers described herein can be used to accurately detect and measure the immune response of CD4+ and / or CD8+T cells after being treated with one or more peptide fragments of one or more SARS-CoV-2 viral proteins. In this exemplary workflow, a portion (or repetition) of the sample originally collected is collected, and ELISpot IFN-γ is performed in parallel to verify the accuracy of AIM determinations.

[0059] Figure 3Summarize the flow cytometry analysis and gating strategy for exemplary AIM determination according to the present disclosure.As shown in this example, the exemplary gating strategy for flow cytometer can include: 1) single cells (Singles) (i.e., single cells) are gated based on light scattering properties (side scatter in this case); lymphocytes are gated based on light scattering properties (side scatter and forward scatter in this case); 3) living cells are gated (e.g., using cell viability markers described herein); T cells are gated (e.g., based on phenotype CD3+, CD14-, Cd19-); CD4+ and CD8+T cells are gated (e.g., using one or more markers described herein); and then CD4+ and / or CD8+T cells expressing one or more cell surface markers described herein are gated. In this example, the final gate identified CD4+T cells expressing CD40L and OX40, and CD8+T cells expressing CD25 and 41BB. The number of cells found expressing one or more selected cell surface markers can then be analyzed, for example, to determine whether the sample donor has been infected with the SARS-CoV-2 virus. This determination can be used to guide treatment or vaccination decisions, for example, by medical professionals. For example, a weak response can be used as an indicator that the sample donor needs a booster vaccination.

[0060] Figure 4 to Figure 1 0 provides data demonstrating the use of AIM assays based on cell surface markers as described herein. For example, Figures 4 to 6 Data for an AIM assay according to the present disclosure is provided, which uses a pair of cell surface markers described herein (CD25 and 41BB) to assess CD4+ and CD8+ T cell activation after treatment with SARS-CoV-2 viral antigens. Data for a negative control (water) and a positive control (using a CEFTA peptide pool) are also provided. As shown by such data (e.g., Figure 4 As shown in the curve, the percentage of CD4+ T cells that were found to be CD25+ and 41BB+ was significantly higher in the COVID-19 convalescent group (treated with SARS-CoV-2 viral antigens obtained from Miltenyi Biotec or Mabtech). In some aspects, the SARS-CoV-2 viral antigen can be contained in a “ All peptides or any combination of peptides present in "SARS-CoV-2 Select-premium grade" or in "PepPool: SARS-CoV-2 (SNMO), human" available from Mabtech.

[0061] This AIM assay was repeated using various pairs of cell surface markers described herein to assess the responses of CD4+ and CD8+ cells. Figure 5 The various cell surface marker pairs evaluated are summarized. For each treatment condition (e.g., water or peptide pool), five replicates were evaluated, and all marker pairs were used to set gates under each treatment condition. Initial results were averaged and normalized by background subtraction. Figure 6 An exemplary graph of one such assay result shows that an increase in CD4+ T cells expressing selected cell surface marker pairs was found in samples from COVID-19 convalescent donors compared to samples from COVID-19 naive donors.

[0062] Figure 7 Figures 9 to 10 provide additional data validating the use of the AIM assay based on the cell surface markers described herein. The ELISpot assay is a common assay that can be used to detect and measure T cell activation. Figures 7 and 8 As shown in Figure 9, ELISpot assays confirmed T cell activation and IFN-γ release in COVID-19 convalescent donors after SARS-CoV-2 peptide stimulation with the Mabtech peptide pool (when "Conv Ser Pos" and "Conv Ser Neg" samples were combined). As shown in Figure 9, increased secretion of cytokines: IL-2, IFN-γ, and TNF-α was observed in COVID-19 convalescent donors (when "Conv Ser Pos" and "Conv Ser Neg" samples were combined), while the secretion of cytokines IL-4, IL-6, and IL-10 was inconsistent between donors.

[0063] Diagnostic methods

[0064] In some aspects, the present disclosure provides methods for determining, for example, whether a subject has been infected with the SARS-CoV-2 virus using the marker panels described herein. Such methods can be performed using any of the various marker panels and / or kits described herein. In some aspects, such methods may involve generating a processed sample by contacting a plurality of CD4+T cells and / or CD8+T cells obtained from the subject with at least one antigen, wherein the antigen comprises a peptide fragment of a protein of a strain of the SARS-CoV-2 virus. PBMCs obtained from a subject (e.g., comprising CD4+T cells and / or CD8+T cells) can optionally be divided into separate portions (e.g., to create one or more replicates) prior to processing. One or more of the CD4+ T cells and / or CD8+ T cells in the treated sample can then be contacted with a plurality of fluorophore-conjugated antibodies to produce a labeled sample, wherein each antibody is specific for a cell surface marker selected from CD3, CD4, CD8, CD14, CD19, LAG3, CD25, CD69, OX40, 41BB, CD38, CD40L, CD107, and / or CD274. In some aspects, the treated sample or one or more portions of the cells contained therein can be separated into different replicates. Flow cytometry can be used to analyze the labeled sample (or one or more repetitions derived therefrom) to detect CD4+T cells and / or CD8+T cells expressing or not expressing a variety of cell surface markers selected from CD3, CD4, CD8, CD14, CD19, LAG3, CD25, CD69, OX40, 41BB, CD38, CD40L, CD107 and / or CD274 in the labeled sample based on the fluorescent signal generated by the fluorophore-conjugated antibody. Then, it can be determined whether the donor of the test sample has been infected with the SARS-CoV-2 virus based on the detected CD4+T cells and / or CD8+T cells. As shown in the experiments in the examples provided herein, sensitive detection of T cell responses in populations with different immune states often requires measuring multiple marker proteins. Therefore, it can be used to determine a cell surface marker combination that enables robust detection of infection or immune status without the need to measure each potential cell surface marker. The complexity of the immune system dictates that many cell surface markers may be important for a particular disease, but as more potential markers are tested, the more possible combinations there are, and the greater the likelihood that the background noise of the measurement will continue to increase. Therefore, in some aspects, data normalization can be used alone or in combination with machine learning models to enable the selection of a set of cell surface markers that are specific for SARS-CoV-2 infection.While this section describes diagnostic methods for SARS-CoV-2 infection, such methods can also be configured to diagnose other viral infections (by using antigens containing peptide fragments of proteins from the viral strain of interest).

[0065] As described above, various combinations of cell surface markers described herein can be used to determine whether the subject's CD4+ and / or CD8+ T cells show a response after stimulation with a SARS-CoV-2 antigen (or other viral antigens of interest). For example, in some aspects, a marker panel may include any combination of the following cell surface marker pairs: CD25 and OX40; CD25 and 41BB; CD25 and CD38; CD25 and CD40L; CD69 and OX40; and / or CD69 and CD38. As shown by the data provided herein, these pairs may be particularly useful for detecting responses in CD4+ T cells. Similarly, a panel may include (alone or as a supplement to one or more pairs of the aforementioned pairs) any combination of the following cell surface marker pairs: CD274 and CD69; CD274 and CD38; CD25 and CD274; CD274 and 41BB; and / or CD25 and 41BB. As shown by the data provided herein, these pairs may be particularly useful for detecting responses in CD8+ T cells. Figure 10 demonstrates this cell type specificity using CD25 and 41BB as a representative marker pair. Figure 10A and Figure 10B As demonstrated, this marker pair performs equally well as a means of detecting responses in both CD4+ and CD8+ cells from donors recovering from COVID-19.

[0066] Figures 11 to 14 Additional data on the selectivity of different marker pairs are provided. Specifically, these graphs summarize the data observed when various marker pairs were evaluated using CD4+ and CD8+ T cells from different COVID-19 convalescent donors. Each data point represents the response of a single COVID-19 convalescent donor to a single SARS-CoV-2 peptide pool (Miltenyi or Mabtech) compared to the median of the pool of COVID-19 naive donors. Notably, these graphs illustrate two different calculation methods that can be used to compare the activation levels of test samples, namely the use of the fold change method or differential analysis. These calculations are summarized below:

[0067] Step 1A . Determine the median signal value observed for a pool of replicate test samples (e.g., 5 replicates) from a single donor after stimulation with SARS-CoV-2 antigen.

[0068] Step 1BBackground subtraction: For each donor, subtract the signal observed for the negative control (eg, water) from the median signal determined in step 1A.

[0069] Step 1C .Determine naive sample background: Determine the median signal observed in a collection of samples (e.g., 8 samples) obtained from COVID-19 naive donors after stimulation with SARS-CoV-2 antigen.

[0070] Step 2A Fold-change analysis: If fold-change analysis is desired, divide the background-subtracted signal value for each COVID-19 convalescent donor sample by the median of the background-subtracted data for the original donors (i.e., divide the result of step 1B by the result of step 1C).

[0071] Step 2B Differential analysis: If differential analysis is required, subtract the median of the background-subtracted data from the naive donors from the background-subtracted signal value from each COVID-19 convalescent donor (i.e., subtract the results of step 1C from the results of step 1B).

[0072] exist Figures 22 to 25 Provided for generating Figures 11 to 14 The original data.

[0073] exist Figures 11 to 14 In this case, each data point on the graph represents the signal of a single COVID-19 convalescent donor, calculated by fold-change or differential analysis methods, and plotted relative to the median signal of the original donors. As demonstrated by these figures, the marker pairs CD25 and 41BB; CD25 and CD38; CD25 and CD69; CD40L and CD25; CD40L and CD69; CD40L and OX40; CD69 and CD38; and OX40 41BB performed particularly well for analysis of CD4+ T cells. Similarly, marker pairs CD25 and 41BB; CD25 and CD38; CD25 and OX40; CD69 and CD107; CD69 and OX40; CD107 and CD25; C107 and CD38; CD274 and CD25; CD274 and CD38; CD274 and CD69; CD274 and OX40; and OX40 and 41BB are particularly outstanding for the analysis of CD8+ T cells. It should be understood that the above-mentioned calculation methods are only non-limiting examples. In some aspects, other calculation techniques known in the art can be used as part of the analysis of the fluorescent signals detected by the flow cytometer for performing the AIM assay described herein.

[0074] In some aspects, when using the marker panel described herein to carry out AIM determination, it may be necessary to perform normalization on the detected signal. In particular, when performing cross-sample analysis, it is often necessary to perform normalization (e.g., to correct cross-sample variability and cross-marker pair variability). Therefore, in some aspects, the AIM determination using any combination of cell surface markers (or its pair) may involve the normalization step of using positive controls and / or negative controls. For example, in some aspects, water can be used as a negative control, and the CEFTA peptide pool can be used as a positive control. In some aspects, the normalization process can be carried out as follows:

[0075] Step 1 Test whether the signal value obtained after stimulating the test sample with SARS-CoV-2 antigen is significantly higher than the signal value obtained when measuring the negative control consisting of water. Use one or more replicates to determine the statistical significance of the increase in signal value.

[0076] Step 2 If the signal value associated with the test sample is determined to be significantly higher in step 1, the signal value obtained from the assay of the negative control is subtracted from the signal value obtained from the test sample. Otherwise, the test sample signal value is set to zero.

[0077] Step 3 Test whether the signal value obtained after stimulating the test sample with SARS-CoV-2 antigen is significantly higher than the signal value obtained when measuring the positive control consisting of the CEFTA peptide pool. Use one or more replicates to determine the statistical significance of the increase in signal value.

[0078] Step 4 If the signal value associated with the test sample is determined to be significantly higher in step 3, the test sample signal value is set to 1. Otherwise, the signal obtained from the test sample is normalized to the signal obtained from the assay of the CEFTA peptide pool.

[0079] It should be understood that the steps shown above can be reordered (e.g., the positive control normalization described in steps 3 and 4 can be performed first). In addition, the above normalization methods are non-limiting examples. In some aspects, other normalization techniques known in the art can be used as part of the analysis of the fluorescent signal detected by the flow cytometer used to perform the AIM assay described herein. Figures 15 and 16 By using negative controls (water, Figure 15 ) and positive control (CEFTA peptide pool, Figure 16 ) is a representative example of the normalized signal values generated by normalization.

[0080] Figure 17Hierarchical clustering of various cell surface marker pairs described herein is shown. As demonstrated in this figure, multiple cell surface marker pairs can accurately distinguish COVID-19 convalescent samples from COVID-19 naive samples using the AIM assay described herein.

[0081] In some aspects, a computer-implemented classifier can be used to evaluate the marker panels described herein. The term "classifier" as used herein refers broadly to machine learning algorithms, such as support vector machines, AdaBoost classifiers, penalized logistic regression, elastic nets, regression tree systems, gradient tree boosting systems, naive Bayesian classifiers, neural networks, Bayesian neural networks, k-nearest neighbor classifiers, deep learning systems, and random forest classifiers.

[0082] A classification tree is an easily interpretable classifier with built-in feature selection. A classification tree recursively partitions the data space in order to maximize the proportion of observations from one class in each subspace. Classification trees are typically noisy. Random forests attempt to reduce this noise by taking the average of multiple trees. The result is a classifier with reduced error variance compared to classification trees. Methods (including software) for constructing random forest classifiers are known in the art. Prinzie and Poel (2007) "Random Multiclass Classification: Generalizing Random Forests to RandomMNL and RandomNB." Database and Expert Systems Applications. Lecture Notes in Computer Science. 4653; Denisko & Hoffman (2018) "Classification and interaction in random forests." PNAS 115 (8): 1690-1692, the contents of which are incorporated by reference in their entirety.

[0083] To classify a new observation using a random forest, each classification tree in the random forest is used to classify the new observation. The category to which the new observation is most often classified by the classification tree is the category to which the random forest classifies the new observation. Random forests reduce many of the problems found in classification trees, but at the expense of interpretability.

[0084] By way of non-limiting example, tools for implementing random forests as discussed herein are available in the statistical software computing language and environment R. For example, the R package "random forest" version 4.6-2 includes tools for creating, processing, and utilizing random forests.

[0085] In some aspects, a random forest classifier can be used to evaluate one or more signals generated by a test sample determined using the AIM assay described herein. An exemplary random forest classifier is trained using a set of 30 samples with known COVID-19 convalescent status and evaluated using 10 test samples. Figure 18 As shown in the ROC data provided in , this classifier correctly detected COVID-19 convalescent donors with 100% accuracy in a set of 10 samples. Additional random forest classifiers were generated using the same data set (divided into training and test sets) and various cell surface marker pairs described herein and were found to show comparable results (not shown). Figure 19 is a graph comparing the negative logarithm of the random forest model importance scores versus the p-value of the Mann-Whitney U test. This graph is annotated to highlight six cell surface marker pairs that stand out as relatively important features (i.e., CD274 and CD69; CD25 and CD38; CD274 and 441B; CD25 and OX40; CD25 and 41BB; and CD69 and OX40). Figure 20 A hierarchical clustering of these six cell surface marker pairs is shown. As demonstrated in this figure, all six pairs are able to accurately distinguish COVID-19 convalescent samples from COVID-19 naive samples using the AIM assay described herein. In some aspects, the kits and methods described herein can assay any of these six cell surface marker pairs, alone or in combination.

[0086] Figure 21 Figure 1 is a table that lists several sets of cell surface marker pairs that can be used in the panels described herein, as well as exemplary evidence supporting the use of such marker panels. It should be understood that any kit or method described herein can utilize any combination of cell surface markers shown in this figure or otherwise disclosed herein, and that the pairs shown in this table are exemplary and non-limiting.

[0087] Figures 22 to 25 Provided separately include for generating Figures 11 to 14 The graph shown in is a graph of the raw data. Similarly, Figures 26 to 27 Provided separately include for generating Figures 19 to 20 The graph shown in the figure is a graph of the raw data.

[0088] Figures 28 to 33 Graphs are provided showing the results of a study evaluating the AIM assay described herein for detecting and / or diagnosing CMV infection. Figure 28 Shown are responses (CD4+ cells) from CMV+ donor samples, whereas Figures 29 to 30The responses of the original donor samples are shown ( Figure 30 yes Figure 29 Similarly, Figure 31 Shown are responses (CD8+ cells) from CMV+ donor samples, whereas Figures 32 to 33 The responses of the original donor samples are shown ( Figure 33 yes Figure 32 (enlarged version of ). Figure 34 It is to be shown in after this AIM measures, the chart of the percentage ratio of the activated CD4+T cells detected by exemplary cell surface markers to CD25 and 41BB.As shown by these figures, this method is not limited to being used for detecting and / or diagnosing SARS-CoV-2 infection, and can also be used for detecting and / or diagnosing any other virus of interest.Therefore, it should be understood that any one of the methods described herein, determination and test kit can be used for detecting and / or diagnosing the infection caused by other viruses (for example, by using the antigen of the virus of interest to replace SARS-CoV-2 antigen in such methods, determination and / or test kit).In some aspects, virus can be such as influenza virus (for example, type A or influenza B virus), adenovirus, respiratory syncytial virus (RSV), parainfluenza virus (for example, type 1, type 2 or type 3), enterovirus, hepatitis virus, herpes virus, flavivirus, coronavirus, human immunodeficiency virus, infectious peritonitis virus or any other type of virus.

[0089] In some aspects, the methods and kits disclosed herein can also be used to determine whether a subject has been successfully vaccinated. Some individuals, especially those with compromised immune systems, may find it difficult to produce an immune response after vaccination. The present method provides a means of assessing the CD4+ and / or CD8+ responses of a subject, and therefore provides information that can be used to determine whether such individuals need further vaccinations (e.g., additional boosters, or new vaccinations (e.g., using different antigenic stimulations)). In some aspects, it may be necessary to measure the response of an individual at least 1, 2, 3, or 4 times per year, measure the response of an individual at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 months after administering a previous vaccination, or measure the response of an individual according to any other schedule (e.g., as directed by a medical professional). It can be determined that a subject has been successfully vaccinated based on a detected response that is higher than a predetermined threshold (e.g., measured as an actual increase, percentage increase, or multiple change increase compared to a baseline value and / or a value obtained using an original control). The foregoing methods can similarly be used to evaluate vaccine candidates or to compare the efficacy of different vaccines (eg, by measuring the responses elicited in a population of test subjects).

[0090] AIM Assay Kit

[0091] In some aspects, the present disclosure provides a kit that can be used for (e.g., using a flow cytometer) to measure AIM to identify and / or measure the response of CD4+ and / or CD8+ cells after exposure to antigens (e.g., viral antigens associated with any virus of interest). Such kits may include a variety of binding agents (e.g., antibodies, antibody fragments, aptamers or other binding agents) that can specifically bind to a panel of one or more cell surface markers comprising cell surface markers as described herein, and optionally at least one binding agent, dye or stain that can be used to distinguish signals of live and dead cells. For example, monoclonal and polyclonal antibodies for cell surface markers as described herein are commercially available from ThermoFisher Scientific, Abcam plc, Bio-Rad Laboratories, Inc. and various other commercial suppliers. Commercial antibodies and / or monoclonal or polyclonal antibodies generated by users via conventional techniques can be used to practice kits, assays and methods as described herein. See, for example, Hendriksen et al. (2002). In some aspects, binding agents are combined with other binding agents into a mixture. In some aspects, the individual concentrations of the binding agents and conjugated fluorophores in the mixture are selected to allow sensitive, independent detection of each of the cell surface markers targeted by the panel without further titration. In some aspects, the kit may further comprise one or more buffers, solvents, or other reagents useful in conjunction with the AIM assay (e.g., a buffer for resuspending the binding agent, a solvent for dilution, positive and / or negative control samples).

[0092] As used herein, the term "antibody fragment" refers to one or more portions of an antibody that retain the ability to specifically interact with and bind to a cell surface marker epitope. Examples of binding fragments include, but are not limited to, a Fab fragment, which is a monovalent fragment consisting of a VL, VH, CL, and CH1 domain; a F(ab)2 fragment, which is a bivalent fragment comprising two Fab fragments connected by a disulfide bridge at the hinge region; a Fd fragment consisting of a VH and CH1 domain; a Fv fragment consisting of the VL and VH domains of a single arm of an antibody; a dAb fragment (Ward et al., (1989)), which consists of a VH domain; and an isolated complementarity determining region (CDR). In addition, although the two domains VL and VH of the Fv fragment are encoded by separate genes, they can be joined by a synthetic linker using recombinant methods that enables the two domains to be made into a single protein chain in which the VL and VH regions are paired to form a monovalent antibody molecule known as a "single-chain Fv" (scFv). See, for example, Bird et al. (1988); and Huston et al. (1988). In addition, some animals (e.g., Camelidae) naturally produce single-chain antibodies that can be used in biochemical assays. Such single-chain antibodies are also intended to be encompassed within the term "antibody fragment." These antibody fragments are obtained using conventional techniques known to those skilled in the art, and the fragments are screened for utility in the same manner as intact antibodies.

[0093] Antibody fragments can also be incorporated into single domain antibodies, giant antibodies, minibodies, intrabodies, diabodies, triabodies, tetrabodies, v-NARs and bis-scFvs. See, for example, Hollinger and Hudson (2005). Antibody fragments can also be grafted onto scaffolds based on polypeptides, such as fibronectin type III (Fn3). See, for example, U.S. Patent No. 6,703,199, which describes fibronectin polypeptide monoclonal antibodies. Antibody fragments can also be incorporated into single chain molecules comprising a pair of tandem Fv segments (VH-CH1-VH-CH1), which together with complementary light chain polypeptides form a pair of antigen binding regions. See Zapata et al. (1995). In addition to antibody fragments, marker proteins can also be detected by other binding agents, such as aptamers. Aptamers are nucleic acid-derived binding agents that can be composed of DNA, RNA, or a mixture of DNA and RNA nucleotides and can be designed or selected to specifically bind to a target protein, such as a surface marker protein described herein. In view of the foregoing, it will be understood that the kits and methods may utilize any antibody or antigen-binding antibody fragment known in the art, including but not limited to the various examples described herein.

[0094] Finally, it should be understood that although various aspects of this specification have been highlighted by reference to specific embodiments, those skilled in the art will readily appreciate that these disclosed embodiments merely illustrate the principles of the subject matter disclosed herein. Therefore, it should be understood that the disclosed subject matter is in no way limited to the specific compounds, compositions, articles, devices, methodologies, protocols and / or reagents described herein, unless expressly stated to be so. Furthermore, those of ordinary skill in the art will recognize that certain changes, modifications, substitutions, alterations, additions, deletions, and subcombinations thereof may be made in accordance with the teachings herein without departing from the spirit of this specification.

[0095] The use of the terms "may" or "may" with reference to an embodiment or an aspect of an embodiment also carries the alternative meaning of "may not" or "may not." Thus, if this specification discloses an embodiment or an aspect of an embodiment as may or may be included as part of the inventive subject matter, a negative limitation or exclusive proviso is also expressly intended to mean that the embodiment or an aspect of an embodiment may not or may not be included as part of the inventive subject matter. In a similar manner, the use of the term "optionally" with respect to an embodiment or an aspect of an embodiment means that such embodiment or aspect of an embodiment may or may not be included as part of the inventive subject matter. Whether such a negative limitation or exclusive proviso applies will be based on whether the negative limitation or exclusive proviso is recited in the claimed subject matter.

[0096] Although the numerical ranges and values setting forth the broad scope of the invention are approximate, the numerical ranges and values listed in the specific examples are reported as precisely as possible. However, any numerical range or value inherently contains certain errors necessarily resulting from the standard deviation found in its respective testing measurements. The description of a numerical range herein is intended merely to serve as a shorthand method of referencing each individual value falling within the range. Unless otherwise indicated herein, each individual value of a numerical range is incorporated into this specification as if individually referenced herein.

[0097] Unless otherwise specified herein or obviously contradictory with context, the terms "one", "a (kind)", "the" and similar indicators used in the context of describing the present invention (especially in the context of the following claims) should be interpreted as covering both singular and plural. In addition, unless otherwise explicitly stated, ordinal indicators for identifying elements - such as "first", "second", "third", etc. - are used to distinguish elements, and are not intended to indicate or imply the necessary or limited number of such elements, and are not intended to indicate the specific position or order of such elements. Unless otherwise specified herein or obviously contradictory with context, all methods described herein can be carried out in any suitable order. The use of any and all examples or illustrative language (such as "for example") provided herein is only intended to better illustrate the present invention, rather than to limit the scope of the claimed invention. Any language in this specification should not be interpreted as indicating that any element not claimed for protection is essential for the practice of the present invention.

[0098] When used in the claims, whether as filed or added by amendment, the open transition term "comprising" (and its equivalent open transition phrases such as includes, contains, and having) encompasses all expressly recited elements, limitations, steps, and / or features, alone or in combination with unrecited subject matter; the named elements, limitations, and / or features are essential, but other unnamed elements, limitations, and / or features may be added and still form a construction within the scope of the claims. The specific embodiments disclosed herein may be further limited in the claims using the closed transition phrases "consisting of" or "consisting essentially of" in place of or as a modification of "comprising." When used in the claims, whether as filed or added by amendment, the closed transition phrase "consisting of" excludes any element, limitation, step, or feature not expressly recited in the claims. The closed transition phrase "consisting essentially of" limits the scope of the claim to the expressly recited elements, limitations, steps, and / or features, and any other elements, limitations, steps, and / or features that do not materially affect the basic and novel characteristics of the claimed subject matter. Thus, the open transition phrase "comprising" is defined to include all specifically enumerated elements, limitations, steps and / or features and any optional, additional unspecified elements, limitations, steps and / or features. The closed transition phrase "consisting of" is defined to include only those elements, limitations, steps and / or features specifically listed in the claims, while the closed transition phrase "consisting essentially of" is defined to include only those elements, limitations, steps and / or features specifically listed in the claims, as well as those elements, limitations, steps and / or features that do not materially affect the basic and novel characteristics of the claimed subject matter. Thus, the open transition phrase "comprising" (and its equivalent open transition phrases) includes, within its meaning, as a limitation, the claimed subject matter specified by the closed transition phrase "consisting of" or "consisting essentially of." Thus, embodiments described herein or so claimed with the phrase "comprising" are herein explicitly or inherently described, enabled and supported with respect to the phrases "consisting essentially of" and "consisting of."

[0099] All patents, patent publications, and other publications cited and identified in this specification are individually and expressly incorporated herein by reference in their entirety for the purpose of describing and disclosing, for example, the compositions and methods described in such publications that may be used in connection with the present invention. These publications are provided solely for their disclosure prior to the filing date of the present application. Nothing in this regard should be construed as an admission that the inventors are not entitled to antedate such disclosure by virtue of prior invention or for any other reason. Statements regarding the dates or contents of these documents are based on information available to the applicant, and the applicant cannot guarantee the accuracy of the dates or contents of all such documents.

[0100] Finally, the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of the present invention, which is defined solely by the claims. Therefore, the present invention is not limited to exactly as shown and described.

[0101] References

[0102] 1.Sette, A., & Crotty, S. (2021). "Adaptive immunity to SARS-CoV-2andCOVID-19." Cell, 184(4), 861-880.

[0103] 2. Bowyer, G., Rampling, T., Powlson, J., Morter, R., Wright, D., Hill, AV, & Ewer, KJ (2018). "Activation-induced markers detect vaccine-specific CD4+Tcell responses not measured by assays conventionally used in clinical trials." Vaccines, 6(3), 50.

[0104] 3. Dan, JM, Mateus, J., Kato, Y., Hastie, KM, Yu, ED, Faliti, CE,... & Crotty, S. (2021). "Immunological memory to SARS-CoV-2 assessed for up to 8monthsafter infection." Science, 371(6529), eabf4063.

[0105] 4.Jung,J.H.,Rha,M.S.,Sa,M.,Choi,H.K.,Jeon,J.H.,Seok,H.,...&Shin,E.C.(2021).“SARS-CoV-2-specific T cell memory is sustained in COVID-19convalescent patients for 10months with successful development of stemcell-like memory T cells.”Nature Communications,12(1),1-12.

[0106] 5.Grifoni,A.,Weiskopf,D.,Ramirez,S.I.,Mateus,J.,Dan,J.M.,Moderbacher,C.R.,...&Sette,A.(2020).“Targets of T cell responses to SARS-CoV-2coronavirusin humans with COVID-19disease and unexposed individuals.”Cell,181(7),1489-1501.

[0107] 6.Hendriksen,C,and Jann H.“Production of polyclonal and monoclonalantibodies.”Handbook oflaboratory animal science 2(2002):391-411.

[0108] 7.Le Bert,N.,Tan,A.T.,Kunasegaran,K.,Tham,C.Y.,Hafezi,M.,Chia,A.,...&Bertoletti,A.(2020).“SARS-CoV-2-specific T cell immunity in cases of COVID-19and SARS,and uninfected controls.”Nature,584(7821),457-462.

[0109] 8.Peng,Y.,Mentzer,A.J.,Liu,G.,Yao,X.,Yin,Z.,Dong,D.,...&Dong,T.(2020).“Broad and strong memory CD4+and CD8+T cells induced by SARS-CoV-2 inUK convalescent individuals following COVID-19.”Nature Immunology,21(11),1336-1345.

[0110] 9.Moderbacher,C.R.,Ramirez,S.I.,Dan,J.M.,Grifoni,A.,Hastie,K.M.,Weiskopf,D.,...&Crotty,S.(2020).“Antigen-specific adaptive immunity to SARS-CoV-2 in acute COVID-19 and associations with age and disease severity.”Cell,183(4),996-1012.

[0111] 10.Zhou,R.,To,K.K.W.,Wong,Y.C.,Liu,L.,Zhou,B.,Li,X.,...&Chen,Z.(2020).“Acute SARS-CoV-2 infection impairs dendritic cell and T cellresponses.”Immunity,53(4),864-877.

[0112] 11.Liao,M.,Liu,Y.,Yuan,J.,Wen,Y.,Xu,G.,Zhao,J.,...&Zhang,Z.(2020).“Single-cell landscape of bronchoalveolar immune cells in patients withCOVID-19.”Nature Medicine,26(6),842-844.

[0113] 12.Ten Brinke,A.,Marek-Trzonkowska,N.,Mansilla,M.J.,Turksma,A.W.,Piekarska,K.,Iwaszkiewicz- D.,...&Gregori,S.(2017).“Monitoring T-cellresponses in translational studies:optimization of dye-based proliferationassay for evaluation of antigen-specific responses.”Frontiers in Immunology,8,1870.

[0114] 13.Saade,F.,Gorski,S.A.,&Petrovsky,N.(2012).“Pushing the frontiers ofT-cell vaccines:accurate measurement of human T-cell responses.”Expert Reviewof Vaccines,11(12),1459-1470.

[0115] 14.Slota,M.,Lim,J.B.,Dang,Y.,&Disis,M.L.(2011).“ELISpot for measuringhuman immune responses to vaccines.”Expert Review of Vaccines,10(3),299-306.

[0116] 15.Smith,S.G.,Smits,K.,Joosten,S.A.,van Meijgaarden,K.E.,Satti,I.,Fletcher,H.A.,...&TBVI TB Biomarker Working Group.(2015).“Intracellularcytokine staining and flow cytometry:considerations for application inclinical trials of novel tuberculosis vaccines.”PloS ONE,10(9),e0138042.

[0117] 16.Shirai,A.,Holmes,K.,&Klinman,D.(1993).“Detection and quantitationof cells secreting IL-6 under physiologic conditions in BALB / c mice.”TheJournal of Immunology,150(3),793-799.

[0118] 17.Britten,C.M.,Janetzki,S.,Van Der Burg,S.H.,Gouttefangeas,C.,&Hoos,A.(2008).“Toward the harmonization of immune monitoring in clinical trials:quo vadis?.”Cancer Immunology,Immunotherapy,57(3),285-288.

[0119] 18.Moodie,Z.,Price,L.,Gouttefangeas,C.,Mander,A.,Janetzki,S., M.,...&Britten,C.M.(2010).“Response definition criteria for ELISPOT assaysrevisited.”Cancer Immunology,Immunotherapy,59(10),1489-1501.

[0120] 19.Coughlan,L.,&Lambe,T.(2015).“Measuring cellular immunity toinfluenza:methods of detection,applications and challenges.”Vaccines,3(2),293-319.

[0121] 20.Horton,H.,Thomas,E.P.,Stucky,J.A.,Frank,I.,Moodie,Z.,Huang,Y.,...&De Rosa,S.C.(2007).“Optimization and validation of an 8-color intracellularcytokine staining(ICS)assay to quantify antigen-specific T cells induced byvaccination.”J.Immunological Methods,323(1),39-54.

[0122] 21.De Rosa,S.C.,Lu,F.X.,Yu,J.,Perfetto,S.P.,Falloon,J.,Moser,S.,...&Roederer,M.(2004).“Vaccination in humans generates broad T cell cytokineresponses.”J.Immunology,173(9),5372-5380.

[0123] 22.Holliger,P.,&Hudson,P.J.(2005).“Engineered antibody fragments andthe rise of single domains.”Nature Biotechnology,23(9),1126-1136.

[0124] 23.Zapata,G.,Ridgway,J.B.,Mordenti,J.,Osaka,G.,Wong,W.L.T.,Bennett,G.L.,&Carter,P.(1995).“Engineering linear F(ab')2 fragments for efficientproduction in Escherichia coli and enhanced antiproliferative activity.”Protein Engineering,Design and Selection,8(10),1057-1062.

[0125] 24.Bird,R.E.,Hardman,K.D.,Jacobson,J.W.,Johnson,S.,Kaufman,B.M.,Lee,S.M.,...&Whitlow,M.(1988).“Single-chain antigen-binding proteins.”Science,242(4877),423-426.

[0126] 25.Huston,J.S.,Levinson,D.,Mudgetthunter,M.,Tai,M.S.,Novotny,J.,Margolies,M.N.,...&Haber,E.(1988).Crea.R.;Oppermann,H.“Protein engineering ofantibody binding sites-recovery of specific activity in an anti-digoxinsingle-chain FV analog produced in Escherichia coli.”Proc.Natl.Acad.Sci.USA,85,5879-5883.

[0127] 26.Ward,E.S.,Güssow,D.,Griffiths,A.D.,Jones,P.T.,&Winter,G.(1989).“Binding activities of a repertoire of single immunoglobulin variable domainssecreted from Escherichia coli.”Nature,341(6242),544-546.

Claims

1. A kit comprising: A plurality of antibodies, wherein each antibody is capable of specifically binding to a single cell surface marker selected from a panel consisting of CD3, CD4, CD8, CD14, CD19, LAG3, CD25, CD69, OX40, 41BB, CD38, CD40L, CD107, and CD274.

2. The kit of claim 1, wherein the plurality of antibodies comprises antibodies that collectively bind at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 different cell surface markers selected from the panel.

3. The kit according to claim 1 or 2, wherein the kit further comprises a cell viability marker, wherein the cell viability marker comprises a binding agent that selectively binds to live cells or dead cells or a dye that stains live cells or dead cells.

4. The kit according to any one of claims 1 to 3, wherein the plurality of antibodies comprises antibodies that specifically bind to CD25, CD69, OX40, 41BB, CD38 and / or CD274. The kit according to claim 4 , wherein the plurality of antibodies further comprises an antibody that specifically binds to CD40L and / or CD107.

6. The kit according to any one of claims 1 to 5, wherein the plurality of antibodies comprises a) CD3, CD4, CD8, CD14 and CD19; b) LAG3; or c) a) and b).

7. The kit of any one of claims 1-6, wherein the plurality of antibodies comprises fluorophore-conjugated antibodies.

8. The kit according to claim 7, wherein a different fluorophore is used for each cell surface marker selected from the panel.

9. The kit of any one of claims 8, wherein the fluorophore-conjugated antibodies are provided as a single mixture, and wherein each fluorophore-conjugated antibody is present in the mixture at a concentration that allows detection of each cell surface marker targeted by the mixture.

10. The kit according to any one of claims 1 to 8, wherein the kit further comprises one or more antigens capable of activating peripheral blood mononuclear cells (PBMCs); optionally wherein the PBMCs are CD4+ T cells and / or CD8+ T cells.

11. The kit of claim 9 or 10, wherein the one or more antigens comprise one or more peptides.

12. The kit according to claim 11, wherein the one or more peptides comprise at least a fragment of a polypeptide sequence of a protein produced by a strain of the SARS-CoV-2 virus, wherein the at least one fragment has a length of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 or 20 amino acids, or a length within the range defined by any pair of integers between 2 and 20.

13. The kit of claim 12, wherein the at least one fragment comprises a fragment of a spike protein, a membrane protein, an outer membrane protein, or a nucleocapsid protein of the strain of the SARS-CoV-2 virus.

14. The kit of any one of claims 1-13, wherein the kit further comprises one or more fluorescence minus one ("FMO") control samples, wherein each FMO control sample comprises antibodies specific for all but one of the cell surface markers.

15. The kit according to any one of claims 1 to 14, wherein the kit further comprises one or more solvents and / or buffer solutions.

16. The kit of any one of claims 1-15, wherein the kit further comprises one or more secondary binding agents, wherein each secondary binding agent is capable of specifically binding to a cytokine.

17. The kit of any one of claims 1-15, wherein the kit further comprises one or more secondary binding agents, wherein each secondary binding agent is capable of specifically binding to IFN-γ, TNF-α, IL-2, IL-4, IL-6, or IL-10.

18. The kit of any one of claims 1 to 17, wherein the plurality of antibodies comprises antibodies specific for: a) CD69 and OX40; b) CD25 and 41BB; c) CD25 and CD38; and / or d) CD25 and OX40.

19. The kit of any one of claims 1-17, wherein the plurality of antibodies comprises antibodies specific for: a) CD274 and 41BB; and / or b) CD274 and CD69.

20. The kit of any one of claims 1-17, wherein the plurality of antibodies comprises antibodies specific for: a) CD69 and OX40; b) CD25 and 41BB; c) CD25 and CD38; d) CD25 and OX40 e) CD274 and 41BB; and / or f) CD274 and CD69.

21. The kit of any one of claims 1-17, wherein the plurality of antibodies comprises one or more lyophilized antibodies.

22. A method for determining whether a subject has been infected with the SARS-CoV-2 virus, the method comprising: a) generating a processed sample by contacting a plurality of CD4+ T cells and / or CD8+ T cells obtained from the subject with at least one antigen, wherein the antigen comprises a peptide fragment of a protein of the strain of SARS-CoV-2 virus; b) contacting the CD4+ T cells and / or CD8+ T cells in the treated sample with a plurality of fluorophore-conjugated antibodies to produce a labeled sample, wherein each antibody is specific for a cell surface marker selected from the group consisting of CD3, CD4, CD8, CD14, CD19, LAG3, CD25, CD69, OX40, 41BB, CD38, CD40L, CD107 and / or CD274; c) detecting CD4+ T cells and / or CD8+ T cells expressing a plurality of cell surface markers selected from CD3, CD4, CD8, CD14, CD19, LAG3, CD25, CD69, OX40, 41BB, CD38, CD40L, CD107 and / or CD274 in the labeled sample based on the fluorescent signal generated by the fluorophore-conjugated antibody; as well as d) determining that the subject has been infected with the SARS-CoV-2 virus based on the detected CD4+ T cells and / or CD8+ T cells.

23. The method according to claim 22, wherein steps a), b), c) and / or d) are performed using a kit according to any one of claims 1 to 21.

24. The method according to claim 22 or 23, wherein the detecting step c) further comprises detecting the CD4+ T cells and / or CD8+ T cells expressing multiple cell surface markers in the labeled sample using at least 2, 3, 4, 5, 6, 7 or 8 replicate samples.

25. The method according to any one of claims 22 to 24, wherein the detecting step c) further comprises the step of normalizing the fluorescent signal generated by the fluorophore-conjugated antibody.

26. The method of claim 25, wherein the normalizing step is performed using: a negative control sample comprising at least one peptide diluent selected from water, another solvent, and / or a buffer; and / or A positive control sample comprising a peptide pool.

27. The method of claim 26, wherein the peptide pool comprises a collection of peptides comprising MHC class II restricted T cell epitopes from human cytomegalovirus, Epstein-Barr virus, influenza virus, tetanus toxin, and adenovirus 5 ("CEFTA").

28. The method of claim 26, wherein the normalizing step comprises: i) testing whether the fluorescent signal generated by the fluorophore-conjugated antibody bound to the CD4+ T cells and / or CD8+ T cells in the labeled sample is higher than the fluorescent signal obtained using the negative control sample; as well as ii) testing whether the fluorescent signal generated by the fluorophore-conjugated antibody bound to the CD4+ T cells and / or CD8+ T cells in the labeled sample is lower than the signal obtained using the positive control sample.

29. The method according to claim 28, further comprising: When the negative control fluorescent signal is low, the fluorescent signal obtained using the negative control sample is subtracted from the fluorescent signal generated by the fluorophore-conjugated antibody bound to the CD4+ T cells and / or CD8+ T cells in the labeled sample.

30. The method of claim 28, further comprising: When the negative control fluorescent signal is high, the fluorescent signal generated by the fluorophore-conjugated antibody bound to the CD4+ T cells and / or CD8+ T cells in the labeled sample is set to zero.

31. The method according to any one of claims 28 to 30, further comprising: When the positive control fluorescent signal is high, the fluorescent signal generated by the fluorophore-conjugated antibody bound to the CD4+ T cells and / or CD8+ T cells in the labeled sample is normalized to the fluorescent signal obtained using the positive control sample.

32. The method according to any one of claims 28 to 31, further comprising: When the positive control fluorescent signal is low, the fluorescent signal generated by the fluorophore-conjugated antibody bound to the CD4+ T cells and / or CD8+ T cells in the labeled sample is set to a non-zero constant value.

33. The method of any one of claims 28-32, wherein the comparison of the fluorescent signal generated by the fluorophore-conjugated antibody that binds to CD4+ T cells and / or CD8+ T cells in the labeled sample with the positive and / or negative controls is based on fluorescent signals obtained from multiple replicates.

34. The method of any one of claims 22-33, wherein determining step d) further comprises determining that the subject has been infected with the SARS-CoV-2 virus based on the expression levels of one or more cytokines obtained by CD4+ T cells and / or CD8+ T cells in the processed sample.

35. The method according to any one of claims 22-33, wherein the determining step d) further comprises determining that the subject has been infected with the SARS-CoV-2 virus based on a change in the amount of CD4+ T cells and / or CD8+ T cells expressing the plurality of cell surface markers in the labeled sample compared to a median or mean amount determined using samples obtained from one or more SARS-CoV-2 naive donors.

36. The method of claim 35, wherein said changes in said amounts of said plurality of cell surface markers are measured as: a) Percent difference compared to the median amount; b) the fold change compared to the median amount; or b) Numerical difference compared to the median amount.

37. The method of any one of claims 22-36, wherein the plurality of fluorophore-conjugated antibodies used in step b) comprises antibodies specific for: a) CD69 and OX40; b) CD25 and 41BB; c) CD25 and CD38; d) CD25 and OX40; e) CD274 and 41BB; and / or f) CD274 and CD69.

38. The method according to claim 37, wherein the plurality of cell surface markers used in step c) comprises: a) CD69 and OX40; b) CD25 and 41BB; c) CD25 and CD38; d) CD25 and OX40 e) CD274 and 41BB; and / or f) CD274 and CD69.

39. A method for determining whether a subject is in need of viral vaccination, the method comprising: a) generating a processed sample by contacting a plurality of CD4+ T cells and / or CD8+ T cells obtained from the subject with at least one antigen, wherein the antigen comprises a peptide fragment of a protein of a strain of a virus; b) contacting the CD4+ T cells and / or CD8+ T cells in the treated sample with a plurality of fluorophore-conjugated antibodies to produce a labeled sample, wherein each antibody is specific for a cell surface marker selected from the group consisting of CD3, CD4, CD8, CD14, CD19, LAG3, CD25, CD69, OX40, 41BB, CD38, CD40L, CD107 and / or CD274; c) detecting CD4+ T cells and / or CD8+ T cells expressing a plurality of cell surface markers selected from CD3, CD4, CD8, CD14, CD19, LAG3, CD25, CD69, OX40, 41BB, CD38, CD40L, CD107 and / or CD274 in the labeled sample based on the fluorescent signal generated by the fluorophore-conjugated antibody; as well as d) determining that the subject is in need of the viral vaccination based on the detected CD4+ T cells and / or CD8+ T cells.

40. The method of claim 39, wherein step c) further comprises: normalizing the fluorescent signal generated by the fluorophore-conjugated antibody to produce a normalized signal; as well as The normalized signal is compared to (1) the fluorescence signal generated by one or more naive CD4+ T cells and / or CD8+ T cells; or (2) the median or average fluorescence signal generated by multiple COVID-19 naive CD4+ T cells and / or CD8+ T cells.

41. The method of claim 39 or 40, wherein the virus is SARS-CoV-2.

Images