Based on a hepatitis B virus (HBV)-derived peptide matrix, HBV-specific CD4 T-cell responses could be evaluated in parallel with identification of HBV-specific CD4 T-cell epitopes.
CD4 T cells play important roles in the pathogenesis of chronic hepatitis B. As a versatile cell population, CD4 T cells have been classified as distinct functional subsets based on the cytokines they secreted: for example, IFN-γ for CD4 T helper 1 cells, IL-4 and IL-13 for CD4 T helper 2 cells, IL-21 for CD4 T follicular helper cells, and IL-17 for CD4 T helper 17 cells. Analysis of hepatitis B virus (HBV)-specific CD4 T cells based on cytokine secretion after HBV-derived peptides stimulation could provide information not only about the magnitude of HBV-specific CD4 T-cell response but also about the functional subsets of HBV-specific CD4 T cells. Novel approaches, such as transcriptomics and metabolomics analysis, could provide more detailed functional information about HBV-specific CD4 T cells. These approaches usually require isolation of viable HBV-specific CD4 T cells based on peptide-major histocompatibility complex-II multimers, while currently the information about HBV-specific CD4 T-cell epitopes is limited. Based on an HBV-derived peptide matrix, a method has been developed to evaluate HBV-specific CD4 T-cell responses and identify HBV-specific CD4 T-cell epitopes simultaneously using peripheral blood mononuclear cells samples from chronic HBV infection patients.
Currently, there are 3 main approaches to analyze antigen-specific T cells. The first approach is based on the interaction between the T-cell receptor and the peptide (epitope). Antigen-specific T cells could be directly stained with peptide-major histocompatibility complex (MHC) multimers. The advantage of this method is that it could obtain viable antigen-specific T cells, suitable for downstream transcriptomics/metabolomics analysis. A limitation of this method is that it could not provide information about the whole T-cell response to a specific antigen, as it requires validated epitope peptides while the number of identified epitopes for a specific antigen is limited for now. Compared to hepatitis B virus (HBV)-specific CD8 T-cell epitopes, fewer HBV-specific CD4 T-cell epitopes have been identified1,2, which made this method less applicable for analysis of HBV-specific CD4 T cells currently.
The second approach is based on the upregulation of a series of activation-induced markers after antigen peptide stimulation3. The commonly used markers include CD69, CD25, OX40, CD40L, PD-L1, 4-1BB4. This method has now been used to analyze antigen-specific T-cell responses in vaccinated individuals5,6, Human Immunodeficiency Virus infection patients7, and Severe Acute Respiratory Syndrome Coronavirus 2 infection patients8,9. Unlike the peptide-MHC multimers based assay, this method is not restricted by validated epitopes and could obtain viable cells for downstream analysis. A limitation of this method is that it could not provide information about the cytokine profile of antigen-specific T cells. Also, the expression of these activation-induced markers by some activated antigen-non-specific cells might contribute to the background signals in analysis, which could be a problem especially when the target antigen-specific T cells are rare. Currently, there is limited application of this method on HBV-specific CD4 T cells4. Whether this method could be utilized to analyze HBV-specific CD4 T cells in a reliable way needs further investigation.
The third approach is based on the cytokine secretion after antigen peptide stimulation. Like activation-induced marker-based analysis, this method is not restricted by validated epitopes. This method could directly reveal the cytokine profile of antigen-specific T cells. The sensitivity of this method is lower than the activation-induced marker-based method as it relies on the cytokine secretion of antigen-specific T cells and the number of cytokines tested is usually limited. Currently, this method is widely used in analysis of HBV-specific T cells. As cytokine secreting HBV-specific T cells could hardly be detected by direct ex vivo peptide stimulation10,11, the cytokine profile of HBV-specific T cells is usually analyzed after 10-day in vitro peptide stimulated expansion12,13,14,15,16. Arrangement of peptide pools in a matrix form has been utilized to facilitate identification of antigen-specific epitopes17,18. With the combination of peptide matrix and cytokine secretion analysis, a method has been developed to evaluate HBV-specific CD4 T-cell responses and identify HBV-specific CD4 T-cell epitopes simultaneously16. In this protocol, the details of this method are described. HBV core antigen is chosen as an example of demonstration in this protocol.
Written informed consent was obtained from each patient included in the study. The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki as reflected in a priori approval by the medical ethics committee of Southwest Hospital.
1. Design of the HBV-derived peptide matrix
2. Isolation of peripheral blood mononuclear cells (PBMCs)
3. In Vitro Expansion of PBMCs Using a HBV Peptide Matrix
4. Analysis of HBV-specific CD4 T-Cell responses by intracellular flow cytometry
5. Identification of HBV-specific HLA-DR Restricted CD4 T-cell Epitopes
The frequency of cytokine secreting CD4 T cells are calculated as the sum of both single producers and double producers. As demonstrated in Figure 1, the frequency of TNF-α secreting CD4 T cells and the frequency of IFN-γ secreting CD4 T cells in background control (DMSO) are 0.154% and 0.013% respectively. The frequency of TNF-α secreting CD4 T cells and the frequency of IFN-γ secreting CD4 T cells specific for peptide pool Core11 are 0.206 and 0.017 respectively, so both TNF-α secreting CD4 T-cell response and IFN-γ secreting CD4 T-cell response for this peptide pool are considered as negative. The frequency of TNF-α secreting CD4 T cells and the frequency of IFN-γ secreting CD4 T cells specific for peptide pool Core09 are 2.715% and 0.973% respectively, so both TNF-α secreting CD4 T-cell response and IFN-γ secreting CD4 T-cell response for this peptide pool are considered as positive.
As demonstrated in Figure 2, positive wells are indicated with gray background. When calculating HBV core-specific TNF-α secreting CD4 T-cell response rate, data of peptide pools Core01, Core02, Core04, Core05, Core06, Core07, Core08, Core09, and Core10 should be included. When calculating HBV core-specific IFN-γ secreting CD4 T-cell response rate, data of peptide pools Core01, Core02, Core03, Core04, Core05, Core06, Core07, Core08, Core09, and Core10 are included.
As demonstrated in Figure 3, candidate peptides for epitope identification are indicated in red. Core01 has the highest response rate for both TNF-α secreting CD4 T cells and IFN-γ secreting CD4 T cells in column peptide pools. Peptides C1-15, C31-45, C61-75, and C91-105 in this peptide pool are set as candidate peptides as the row peptide pools containing those peptides also shows positive results in T-cell response. The PBMCs expanded with the peptide pools Core07, Core08, Core09, and Core10 are used for epitope identification of peptides C1-15, C31-45, C61-75, and C91-105, respectively. Core09 has the highest response rate for both TNF-α secreting CD4 T cells and IFN-γ secreting CD4 T cells in row peptide pools. Peptides C61-75, C66-80, C71-85, C76-90, C81-95, and C86-100 in this peptide pool are set as candidate peptides as the column peptide pools containing those peptides also shows positive result in T-cell response. The PBMCs expanded with the peptide pools Core01, Core02, Core03, Core04, Core05, and Core06 are used for epitope identification of peptides C61-75, C66-80, C71-85, C76-90, C81-95 and C86-100, respectively.
As demonstrated in Figure 4, for peptide pool Core08 expanded PBMCs, after stimulation with peptide C31-45 pulsed BLCLs, the frequency of TNF-α secreting CD4 T cells and the frequency of IFN-γ secreting CD4 T cells are 0.995% and 0.131% respectively, which are more than 2 times higher than background controls (peptide C31-45 pulsed BLCLs with HLA-DR pre-blocking, DMSO pulsed BLCLs). Thus, peptide C31-45 is verified as a HLA-DR restricted CD4 T-cell epitope. For peptide pool Core10 expanded PBMCs, after stimulation with peptide C91-105 pulsed BLCLs, the frequency of TNF-α secreting CD4 T cells and the frequency of IFN-γ secreting CD4 T cells are 0.221% and 0.000% respectively, which do not exceed the 2 times of background controls (peptide C91-45 pulsed BLCLs with HLA-DR pre-blocking, DMSO pulsed BLCLs), so peptide C91-105 is not verified as HLA-DR restricted CD4 T-cell epitope.
Figure 1: Flow cytometry demonstration of TNF-α/IFN-γ secreting CD4 T cells in peptide pools expanded PBMCs after stimulated with their respective peptide pools. Please click here to view a larger version of this figure.
Figure 2: Demonstration of the analysis HBV core-specific TNF-α/IFN-γ secreting CD4 T cells. The TNF/DMSO and IFN-Ƴ/DMSO indicate the ratios of the frequencies of TNF-α/IFN-γ secreting CD4 T cells in each well of peptide pool stimulated PBMCs divided by the frequency of TNF-α/IFN-γ secreting CD4 T cells in the well of DMSO control. Gray background indicates wells with positive CD4 T-cell response judged by comparison with background control. Please click here to view a larger version of this figure.
Figure 3: Demonstration of the screening of candidate peptides for epitope identification. The TNF/DMSO and IFN-Ƴ/DMSO indicate the ratios of the frequencies of TNF-α/IFN-γ secreting CD4 T cells in each well of peptide pool stimulated PBMCs divided by the frequency of TNF-α/IFN-γ secreting CD4 T cells in the well of DMSO control. Gray background indicates wells with positive CD4 T-cell response judged by comparison with background control. Peptides in red indicate candidate peptides according to the screening criteria. Please click here to view a larger version of this figure.
Figure 4: Flow cytometry demonstration of epitope identification results. Please click here to view a larger version of this figure.
The most critical steps in this protocol are listed as follows: 1) enough PBMCs of high viability to start PBMCs expansion; 2) appropriate environment for PBMCs expansion; and 3) complete removal of residual peptide pools in PBMCs culture before epitope identification.
All the analysis in this protocol depends on the robust proliferation of CD4 T cells. In general, the number of PBMCs after 10-day expansion will be 2-3 times of the initial number. The cell number and the viability of PBMCs are 2 key factors in PBMCs expansion. If the purpose is only to analyze HBV-specific CD4 T cells without epitope identification, it is reasonable to reduce the initial PBMCs number, especially when the volume of blood sample is limited. While, in our experience, successful PBMCs expansion could barely be obtained if the start number of PBMCs is below 1.5×105 cells/well. When using fresh PBMCs for expansion, the cell viability will not be a problem. While when using cryopreserved PBMCs for expansion, the cryopreservation and thawing of PBMCs should be conducted very carefully to maintain the viability of PBMCs.
In functional analysis of HBV-specific T cells, IL-12 is usually used in PBMCs expansion to enhance the function of CD8 T cells. As IL-12 could induce differentiation of CD4 T cells towards CD4 T follicular helper cells, this cytokine should be avoided in functional analysis of HBV-specific CD4 T cells. In our protocol, only IL-2 (for T-cell expansion) and IL-7 (for T-cell survival) are supplemented to maintain the functional profile of HBV-specific CD4 T cells during expansion as intact as possible. We have tested 5 cytokines for functional analysis of HBV-specific CD4 T cells: TNF-α, IFN-γ, IL-4, IL-17, and IL-21. In our analyzed samples, TNF-α and IFN-γ are 2 major cytokines secreted by HBV-specific CD4 T cells16. In analyzing the functional profile of HBV-specific CD4 T cells, it is recommended to test as many as possible cytokines to obtain the detailed functional profile information. While in epitope identification, it is recommended to analyze only TNF-α and IFN-γ, for economic consideration.
Enough HBV-specific CD4 T cells are vital for successful epitope identification, so epitope identification should be considered in patients with high HBV-specific CD4 T-cell response, such as hepatitis B flare patients (strong HBV-specific TNF-α secreting CD4 T-cell response) and patients with viral clearance (strong HBV-specific IFN-γ CD4 T-cell response)16. It is very important to remove residual peptides in the peptide pool expanded PBMCs by repeated washing before incubating these cells with BLCLs for epitope identification. The residual peptides will bind to DMSO pulsed BLCLs, activate peptide-specific CD4 T cells, hereby increase the background to a great extent.
Some HBV antigen has variable sequences in different HBV genotypes (e.g., HBV surface antigen). A solution is to pre-determine the specific HBV genotypes in patients and design HBV genotype-specific peptide pools for patients with different HBV genotypes. While the HBV genotype is un-measurable in patients with low HBV viral loads (e.g., HBeAg negative patients with regular anti-viral treatment), in this scenario, the solution is to mix peptides from different HBV genotypes together into the same peptide pools, as we did in a previous study16. A drawback of this mixture strategy is that epitope might be identified as a peptide pair but not a single peptide, as some positions in the peptides matrix contain a peptide pair in the same fragment of the antigen.
A major drawback in this method is the time-consuming 10-day PBMCs expansion. Currently, ex vivo analysis of cytokine secretion could not detect HBV-specific CD4 T cells in a reliable way. Using peptide pulsed allogeneic BLCLs as stimulators usually detected more peptide-specific CD4 T cells in peptide expanded PBMCs, compared to simply stimulating with peptides16. It is worth investigating whether using peptide pulsed autologous B cells as antigen presentation cells could help to reliably detect HBV-specific CD4 T cells ex vivo.
The authors have nothing to disclose.
This work was supported by National Natural Science Foundation of China (81930061), Chongqing Natural Science Foundation (cstc2019jcyj-bshX0039, cstc2019jcyj-zdxmX0004), and Chinese Key
Project Specialized for Infectious Diseases (2018ZX10723203).
Albumin Bovine V (BSA) | Beyotime | ST023 | |
APC-conjugated Anti-human TNF-α | eBioscience | 17-7349-82 | Keep protected from light |
Benzonase Nuclease | Sigma-Aldrich | E1014 | Limit cell clumping |
B lymphoblastoid cell lines (BLCLs) | FRED HUTCHINSON CANCER RESEARCH CENTER | IHW09126 | HLA-DRB1*0803 homozygote |
B lymphoblastoid cell lines (BLCLs) | FRED HUTCHINSON CANCER RESEARCH CENTER | IHW09121 | HLA-DRB1*1202 homozygote |
Cell Culture Flask (T75) | Corning | 430641 | |
Cell Culture Plate (96-well, flat bottom) | Corning | 3599 | Flat bottom |
Cell Culture Plate (96-well, round bottom) | Corning | 3799 | Round bottom |
Cell Strainer | Corning | CLS431751 | Pore size 70 μm, white, sterile |
Centrifuge Tube (15 mL) | KIRGEN | KG2611 | Sterile |
Centrifuge Tube (50 mL) | Corning | 430829 | Sterile |
Centrifuge, Refrigerated | Eppendorf | 5804R | |
Centrifuge, Refrigerated | Thermo | ST16R | |
Centrifuge, Refrigerated | Thermo | Legend Micro 21R | |
Cytofix/Cytoperm Kit (Transcription Factor Buffer Set) | BD Biosciences | 562574 | Prepare solution before use |
Dimethyl Sulfoxide (DMSO) | Sigma-Aldrich | D2650 | Keep at room temperature to prevent crystallization |
Dulbecco’s Phosphate Buffered Saline | Prepare ddH2O (1000 ml) containing NaCl (8000 mg), KCl (200 mg), KH2PO4 (200 mg), and Na2HPO4.7H2O (2160 mg). Adjust PH to 7.4. Sterilize through autoclave. | ||
Ficoll-Paque Premium | GE Healthcare | 17-5442-03 | |
Filter Tips (0.5-10) | Kirgen | KG5131 | Sterile |
Filter Tips (100-1000) | Kirgen | KG5333 | Sterile |
Filter Tips (1-200) | Kirgen | KG5233 | Sterile |
FITC-conjugated Anti-human CD4 | BioLegend | 300506 | Keep protected from light |
Fixable Viability Dye eFluor780 | eBioscience | 65-0865-14 | Keep protected from light |
GolgiStop Protein Transport Inhibitor (Containing Monensin) | BD Biosciences | 554724 | Protein Transport Inhibitor |
Haemocytometer | Brand | 718620 | |
HBV Core Antigen Derived Peptides | ChinaPeptides | ||
HEPES | Gibco | 15630080 | 100 ml |
Human Serum AB | Gemini Bio-Products | 100-51 | 100 ml |
Ionomycin | Sigma-Aldrich | I0634 | |
KCl | Sangon Biotech | A100395-0500 | |
KH2PO4 | Sangon Biotech | A100781-0500 | |
LSRFortessa Flow Cytometer | BD | ||
L-glutamine | Gibco | 25030081 | 100 ml |
Microcentrifuge Tube (1.5 mL) | Corning | MCT-150-C | Autoclaved sterilization before using |
Microplate Shakers | Scientific Industries | MicroPlate Genie | |
Mitomycin C | Roche | 10107409001 | |
Na2HPO4.7H2O | Sangon Biotech | A100348-0500 | |
NaCl | Sangon Biotech | A100241-0500 | |
PCR Tubes (0.2 mL) | Kirgen | KG2331 | |
PE/Cy7-conjugated Anti-human CD8 | BioLegend | 300914 | Keep protected from light |
PE-conjugated Anti-human IFN-γ | eBioscience | 12-7319-42 | Keep protected from light |
Penicillin Streptomycin | Gibco | 15140122 | 100 ml |
PerCP-Cy5.5-conjugated Anti-human CD3 | eBioscience | 45-0037-42 | Keep protected from light |
Phorbol 12-myristate 13-acetate (PMA) | Sigma-Aldrich | P1585 | |
Recombinant Human IL-2 | PeproTech | 200-02 | |
Recombinant Human IL-7 | PeproTech | 200-07 | |
RPMI Medium 1640 | Gibco | C11875500BT | 500 ml |
Sodium pyruvate,100mM | Gibco | 15360070 | |
Trypan Blue Stain (0.4%) | Gibco | 15250-061 | |
Ultra-LEAF Purified Anti-human HLA-DR | BioLegend | 307648 | |
Wizard Genomic DNA Purification Kit | Promega | A1125 |