ELISPOT Assays in 384-Well Format: Up to 30 Data Points with One Million Cells

Reagent Tracker™ Platform Verifies and Provides Audit Trails for the Error-Free Implementation of T-Cell ImmunoSpot® Assays

ELISPOT and FluoroSpot assays, collectively called ImmunoSpot assays, permit to reliable detection of rare antigen-specific T cells in freshly isolated cell material, such as peripheral blood mononuclear cells (PBMC). Establishing their frequency within all PBMC permits to assess the magnitude of antigen-specific T-cell immunity; the simultaneous measurement of their cytokine signatures reveals these T-cells' lineage and effector functions, that is, the quality of T-cell-mediated immunity. Because of their unparalleled sensitivity, ease of implementation, robustness, and frugality in PBMC utilization, T-cell ImmunoSpot assays are increasingly becoming part of the standard immune monitoring repertoire. For regulated workflows, stringent audit trails of the data generated are a requirement. While this has been fully accomplished for the analysis of T-cell ImmunoSpot assay results, such are missing for the wet laboratory implementation of the actual test performed. Here we introduce a solution for enhancing and verifying the error-free implementation of T-cell ImmunoSpot assays.

Artificial Intelligence-Based Counting Algorithm Enables Accurate and Detailed Analysis of the Broad Spectrum of Spot Morphologies Observed in Antigen-Specific B-Cell ELISPOT and FluoroSpot Assays

Antigen-specific B-cell ELISPOT and multicolor FluoroSpot assays, in which the membrane-bound antigen itself serves as the capture reagent for the antibodies that B cells secrete, inherently result in a broad range of spot sizes and intensities. The diversity of secretory footprint morphologies reflects the polyclonal nature of the antigen-specific B cell repertoire, with individual antibody-secreting B cells in the test sample differing in their affinity for the antigen, fine epitope specificity, and activation/secretion kinetics. To account for these heterogeneous spot morphologies, and to eliminate the need for setting up subjective counting parameters well-by-well, CTL introduces here its cutting-edge deep learning-based IntelliCount™ algorithm within the ImmunoSpot® Studio Software Suite, which integrates CTL's proprietary deep neural network. Here, we report detailed analyses of spots with a broad range of morphologies that were challenging to analyze using standard parameter-based counting approaches. IntelliCount™, especially in conjunction with high dynamic range (HDR) imaging, permits the extraction of accurate, high-content information of such spots, as required for assessing the affinity distribution of an antigen-specific memory B-cell repertoire ex vivo. IntelliCount™ also extends the range in which the number of antibody-secreting B cells plated and spots detected follow a linear function; that is, in which the frequencies of antigen-specific B cells can be accurately established. Introducing high-content analysis of secretory footprints in B-cell ELISPOT/FluoroSpot assays, therefore, fundamentally enhances the depth in which an antigen-specific B-cell repertoire can be studied using freshly isolated or cryopreserved primary cell material, such as peripheral blood mononuclear cells.

Unbiased, High-Throughput Identification of T Cell Epitopes by ELISPOT

Recent systematic immune monitoring efforts suggest that, in humans, epitope recognition by T cells is far more complex than has been assumed based on minimalistic murine models. The increased complexity is due to the higher number of HLA loci in humans, the typical heterozygosity for these loci in the outbred population, and the high number of peptides that each HLA restriction element can bind with an affinity that suffices for antigen presentation. The sizable array of potential epitopes on any given antigen is due to each individual's unique HLA allele makeup. Of this individualized potential epitope space, chance events occurring in the course of the T cell response determine which epitopes induce dominant T cell expansions. Establishing the actually-engaged T cell repertoire in each human subject, including the individualized peptides targeted, therefore requires the systematic testing of all peptides that constitute the potential epitope space in that person. The goal of comprehensive, high-throughput epitope mapping can be readily established by the methods described in this chapter.

Discordance Between the Predicted Versus the Actually Recognized CD8+ T Cell Epitopes of HCMV pp65 Antigen and Aleatory Epitope Dominance

CD8+ T cell immune monitoring aims at measuring the size and functions of antigen-specific CD8+ T cell populations, thereby providing insights into cell-mediated immunity operational in a test subject. The selection of peptides for ex vivo CD8+ T cell detection is critical because within a complex antigen exists a multitude of potential epitopes that can be presented by HLA class I molecules. Further complicating this task, there is HLA class I polygenism and polymorphism which predisposes CD8+ T cell responses towards individualized epitope recognition profiles. In this study, we compare the actual CD8+ T cell recognition of a well-characterized model antigen, human cytomegalovirus (HCMV) pp65 protein, with its anticipated epitope coverage. Due to the abundance of experimentally defined HLA-A*02:01-restricted pp65 epitopes, and because in silico epitope predictions are most advanced for HLA-A*02:01, we elected to focus on subjects expressing this allele. In each test subject, every possible CD8+ T cell epitope was systematically covered testing 553 individual peptides that walk the sequence of pp65 in steps of single amino acids. Highly individualized CD8+ T cell response profiles with aleatory epitope recognition patterns were observed. No correlation was found between epitopes' ranking on the prediction scale and their actual immune dominance. Collectively, these data suggest that accurate CD8+ T cell immune monitoring may necessitate reliance on agnostic mega peptide pools, or brute force mapping, rather than electing individual peptides as representative epitopes for tetramer and other multimer labeling of surface antigen receptors.

Low Avidity T Cells Do Not Hinder High Avidity T Cell Responses Against Melanoma

The efficacy of T cells depends on their functional avidity, i. e., the strength of T cell interaction with cells presenting cognate antigen. The overall T cell response is composed of multiple T cell clonotypes, involving different T cell receptors and variable levels of functional avidity. Recently, it has been proposed that the presence of low avidity tumor antigen-specific CD8 T cells hinder their high avidity counterparts to protect from tumor growth. Here we analyzed human cytotoxic CD8 T cells specific for the melanoma antigen Melan-A/MART-1. We found that the presence of low avidity T cells did not result in reduced cytotoxicity of tumor cells, nor reduced cytokine production, by high avidity T cells. In vivo in NSG-HLA-A2 mice, the anti-tumor effect of high avidity T cells was similar in presence or absence of low avidity T cells. These data indicate that low avidity T cells are not hindering anti-tumor T cell responses, a finding that is reassuring because low avidity T cells are an integrated part of natural T cell responses.

Comprehensive Evaluation of the Expressed CD8+ T Cell Epitope Space Using High-Throughput Epitope Mapping

T cell immunity is traditionally assessed through functional recall assays, which detect the consequences of the T cells' antigen encounter, or via fluorescently labeled multimers that selectively bind peptide-specific T cell receptors. Using either approach, if the wrong antigen or peptide of a complex antigenic system, such as a virus, is used for immune monitoring, either false negative data will be obtained, or the magnitude of the antigen-specific T cell compartment will go largely underestimated. In this work, we show how selection of the “right” antigen or antigenic peptides is critical for successful T cell immune monitoring against human cytomegalovirus (HCMV). Specifically, we demonstrate that individual HCMV antigens, along with previously reported epitopes, frequently failed to detect CD8+ T cell immunity in test subjects. Through systematic assessment of T cell reactivity against individual nonamer peptides derived from the HCMVpp65 protein, our data clearly establish that (i) systematic testing against all potential epitopes encoded by the genome of the antigen of interest is required to reliably detect CD8+ T cell immunity, and (ii) genome-wide, large scale systematic testing of peptides has become feasible through high-throughput ELISPOT-based “brute force” epitope mapping.

Reagent Tracker Dyes Permit Quality Control for Verifying Plating Accuracy in ELISPOT Tests

ELISPOT assays enable the detection of the frequency of antigen-specific T cells in the blood by measuring the secretion of cytokines, or combinations of cytokines, in response to antigenic challenges of a defined population of PBMC. As such, these assays are suited to establish the magnitude and quality of T cell immunity in infectious, allergic, autoimmune and transplant settings, as well as for measurements of anti-tumor immunity. The simplicity, robustness, cost-effectiveness and scalability of ELISPOT renders it suitable for regulated immune monitoring. In response to the regulatory requirements of clinical and pre-clinical immune monitoring trials, tamper-proof audit trails have been introduced to all steps of ELISPOT analysis: from capturing the raw images of assay wells and counting of spots, to all subsequent quality control steps involved in count verification. A major shortcoming of ELISPOT and other related cellular assays is presently the lack of audit trails for the wet laboratory part of the assay, in particular, the assurance that no pipetting errors have occurred during the plating of antigens and cells. Here, we introduce a dye-based reagent tracking platform that fills this gap, thereby increasing the transparency and documentation of ELISPOT test results.

Multi-Color FLUOROSPOT Counting Using ImmunoSpot® Fluoro-X™ Suite

Multi-color FLUOROSPOT assays for simultaneous detection of several T-cell cytokines and/or classes/sub-classes of immunoglobulins secreted by B cells have recently become a major new avenue of development of ELISPOT technology. Advances in assay techniques and the availability of commercial test kits stimulated development of multi-color FLUOROSPOT data analysis platforms. The ImmunoSpot^® Fluoro-X™ Software Suite was developed by CTL as an integrated data acquisition, analysis, and management solution for automated high-throughput processing of multi-color T- and B-cell FLUOROSPOT assay plates. The Fluoro-X™ software counting module is based on SmartSpot™/AutoGate™ technologies and utilizes CTL's Center of Mass Distance algorithm for the detection of multi-color spots. The Fluoro-X™ software provides an objective, user error-free means for analyzing multi-color FLUOROSPOT data. An integrated quality control module, with optional GLP and CFR Part 11 compliant package and role-based security, enables data validation, review, and approval with complete audit trails. The extensive multi-format data output and presentation capabilities of the Fluoro-X™ software allow further analysis of FLUOROSPOT data using any commercial flow cytometry software and facilitate the generation of professional reports and presentation. In this article, we present a detailed step-by-step workflow for the analysis of a human four-color IFN-γ, IL-2, TNF-α, and GzB antigen-specific T-cell assay using the Fluoro-X Software Suite.

Delayed Activation Kinetics of Th2- and Th17 Cells Compared to Th1 Cells

During immune responses, different classes of T cells arise: Th1, Th2, and Th17. Mobilizing the right class plays a critical role in successful host defense and therefore defining the ratios of Th1/Th2/Th17 cells within the antigen-specific T cell repertoire is critical for immune monitoring purposes. Antigen-specific Th1, Th2, and Th17 cells can be detected by challenging peripheral blood mononuclear cells (PBMC) with antigen, and establishing the numbers of T cells producing the respective lead cytokine, IFN-γ and IL-2 for Th1 cells, IL-4 and IL-5 for Th2, and IL-17 for Th-17 cells, respectively. Traditionally, these cytokines are measured within 6 h in flow cytometry. We show here that 6 h of stimulation is sufficient to detect peptide-induced production of IFN-γ, but 24 h are required to reveal the full frequency of protein antigen-specific Th1 cells. Also the detection of IL-2 producing Th1 cells requires 24 h stimulation cultures. Measurements of IL-4 producing Th2 cells requires 48-h cultures and 96 h are required for frequency measurements of IL-5 and IL-17 secreting T cells. Therefore, accounting for the differential secretion kinetics of these cytokines is critical for the accurate determination of the frequencies and ratios of antigen-specific Th1, Th2, and Th17 cells.

Heterogeneity assessment of functional T cell avidity

The potency of cellular immune responses strongly depends on T cell avidity to antigen. Yet, functional avidity measurements are rarely performed in patients, mainly due to the technical challenges of characterizing heterogeneous T cells. The mean functional T cell avidity can be determined by the IFN-γ Elispot assay, with titrated amounts of peptide. Using this assay, we developed a method revealing the heterogeneity of functional avidity, represented by the steepness/hillslope of the peptide titration curve, documented by proof of principle experiments and mathematical modeling. Our data show that not only natural polyclonal CD8 T cell populations from cancer patients, but also monoclonal T cells differ strongly in their heterogeneity of functional avidity. Interestingly, clones and polyclonal cells displayed comparable ranges of heterogeneity. We conclude that besides the mean functional avidity, it is feasible and useful to determine its heterogeneity (hillslope) for characterizing T cell responses in basic research and patient investigation.

How frequently are predicted peptides actually recognized by CD8 cells?

Detection of antigen-specific CD8 cells frequently relies on the use of peptides that are predicted to bind to HLA Class I molecules or have been shown to induce immune responses. There is extensive knowledge on individual HLA alleles’ peptide-binding requirements, and immunogenic peptides for many antigens have been defined. The 32 individual peptides that comprise the CEF peptide pool represent such well-defined peptide determinants for Cytomegalo-, Epstein–barr-, and Influenza virus. We tested the accuracy of these peptide recognition predictions on 42 healthy human donors that have been high-resolution HLA-typed. According to the predictions, 241 recall responses should have been detected in these donors. Actual testing showed that 36 (15 %) of the predicted CD8 cell responses occurred in the high frequency range, 41 (17 %) in mid-frequencies, and 45 (19 %) were at the detection limit. In 119 instances (49 %), the predicted peptides were not targeted by CD8 cells detectably. The individual CEF peptides were recognized in an unpredicted fashion in 57 test cases. Moreover, the frequency of CD8 cells responding to a single peptide did not reflect on the number of CD8 cells targeting other determinants on the same antigen. Thus, reliance on one or a few predicted peptides provides a rather inaccurate assessment of antigen-specific CD8 cell immunity, strongly arguing for the use of peptide pools for immune monitoring.

Characterization of the HCMV-Specific CD4 T Cell Responses that Are Associated with Protective Immunity

Most humans become infected with human cytomegalovirus (HCMV). Typically, the immune system controls the infection, but the virus persists and can reactivate in states of immunodeficiency. While substantial information is available on the contribution of CD8 T cells and antibodies to anti-HCMV immunity, studies of the T_H1, T_H2, and T_H17 subsets have been limited by the low frequency of HCMV-specific CD4 T cells in peripheral blood mononuclear cell (PBMC). Using the enzyme-linked Immunospot^® assay (ELISPOT) that excels in low frequency measurements, we have established these in a sizable cohort of healthy HCMV controllers. Cytokine recall responses were seen in all seropositive donors. Specifically, interferon (IFN)-γ and/or interleukin (IL)-17 were seen in isolation or with IL-4 in all test subjects. IL-4 recall did not occur in isolation. While the ratios of T_H1, T_H2, and T_H17 cells exhibited substantial variations between different individuals these ratios and the frequencies were relatively stable when tested in samples drawn up to five years apart. IFN-γ and IL-2 co-expressing polyfunctional cells were seen in most subjects. Around half of the HCMV-specific CD4 cells were in a reversible state of exhaustion. The data provided here established the T_H1, T_H2, and T_H17 characteristic of the CD4 cells that convey immune protection for successful immune surveillance against which reactivity can be compared when the immune surveillance of HCMV fails.

Normal Distribution of CD8+ T-Cell-Derived ELISPOT Counts within Replicates Justifies the Reliance on Parametric Statistics for Identifying Positive Responses

Accurate assessment of positive ELISPOT responses for low frequencies of antigen-specific T-cells is controversial. In particular, it is still unknown whether ELISPOT counts within replicate wells follow a theoretical distribution function, and thus whether high power parametric statistics can be used to discriminate between positive and negative wells. We studied experimental distributions of spot counts for up to 120 replicate wells of IFN-γ production by CD8+ T-cell responding to EBV LMP2A (426 - 434) peptide in human PBMC. The cells were tested in serial dilutions covering a wide range of average spot counts per condition, from just a few to hundreds of spots per well. Statistical analysis of the data using diagnostic Q-Q plots and the Shapiro-Wilk normality test showed that in the entire dynamic range of ELISPOT spot counts within replicate wells followed a normal distribution. This result implies that the Student t-Test and ANOVA are suited to identify positive responses. We also show experimentally that borderline responses can be reliably detected by involving more replicate wells, plating higher numbers of PBMC, addition of IL-7, or a combination of these. Furthermore, we have experimentally verified that the number of replicates needed for detection of weak responses can be calculated using parametric statistics.

ELISPOTs Produced by CD8 and CD4 Cells Follow Log Normal Size Distribution Permitting Objective Counting

Each positive well in ELISPOT assays contains spots of variable sizes that can range from tens of micrometers up to a millimeter in diameter. Therefore, when it comes to counting these spots the decision on setting the lower and the upper spot size thresholds to discriminate between non-specific background noise, spots produced by individual T cells, and spots formed by T cell clusters is critical. If the spot sizes follow a known statistical distribution, precise predictions on minimal and maximal spot sizes, belonging to a given T cell population, can be made. We studied the size distributional properties of IFN-γ, IL-2, IL-4, IL-5 and IL-17 spots elicited in ELISPOT assays with PBMC from 172 healthy donors, upon stimulation with 32 individual viral peptides representing defined HLA Class I-restricted epitopes for CD8 cells, and with protein antigens of CMV and EBV activating CD4 cells. A total of 334 CD8 and 80 CD4 positive T cell responses were analyzed. In 99.7% of the test cases, spot size distributions followed Log Normal function. These data formally demonstrate that it is possible to establish objective, statistically validated parameters for counting T cell ELISPOTs.