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Antigen Presentation

Antigen Presentation refers to the process by which antigenic peptides are displayed on the surface of cells, typically by major histocompatibility complex (MHC) molecules, allowing recognition by T cells.
This critical step in the immune response enables T cells to identify and respond to foreign or abnormal antigens.
The presentation of antigens is a complex and highly regulated process, involving the processing and transport of peptides derived from intracellular or extracellular sources.
Defects in antigen presentation can contribute to autoimmune diseases, immunodeficiencies, and cancer.
Understanding the nuances of antigen presentation is essenteal for the development of effective immunotherapies and vaccines.

Most cited protocols related to «Antigen Presentation»

1
Evaluating Tumor Immune Microenvironment in Bladder Cancer
Immunological characteristics of the TME in BLCA include the expression of immunomodulators, activity of the cancer immunity cycle, infiltration level of TIICs, and the expression of inhibitory immune checkpoints. We first collected information on 122 immunomodulators including MHC, receptors, chemokines, and immune stimulators from the study of Charoentong et al. (Table S2) 28 (link). The cancer immunity cycle reflects the anticancer immune response and comprises seven steps: release of cancer cell antigens (Step 1), cancer antigen presentation (Step 2), priming and activation (Step 3), trafficking of immune cells to tumors (Step 4), infiltration of immune cells into tumors (Step 5), recognition of cancer cells by T cells (Step 6), and killing of cancer cells (Step 7) (Table S3) 29 (link). The activities of these steps determine the fate of the tumor cells. Xu et al. evaluated the activities of these steps using a single sample gene set enrichment analysis (ssGSEA) based on the gene expression of individual samples 30 (link). Thereafter, several algorithms were developed to calculate the infiltration level of TIICs in TME using bulk RNA-seq data. Different algorithms and marker gene sets of TIICs initiate calculation errors. To avoid these errors, we comprehensively calculated the infiltration level of TIICs using seven independent algorithms: Cibersort-ABS, MCP-counter, quanTIseq, TIMER, xCell, TIP, and TISIDB (Table S4) 30 (link)-36 (link). We also identified the effector genes of TIICs from previous studies (Table S5). Finally, we collected 22 inhibitory immune checkpoints with therapeutic potential from Auslander's study (Table S6) 37 (link).
Ayers et al. developed and validated a pan-cancer T cell-inflamed score, which could define pre-existing cancer immunity, as well as predict the clinical response of ICB 38 (link). The eighteen genes included in the T cell-inflamed score algorithm and their coefficients are shown in Table S7. Here, we computed the T cell inflamed score as a weighted linear combination of the scores from the 18 genes. Hyperprogression is an adverse event associated with ICB. We summarized several predictors of hyperprogression (Table S8) 39 -41 . The amplification and high mRNA expression of MDM2, MDM4, DNMT3A, CCND1, FGF19, FGF4, and FGF3 are positively correlated with hyperprogression. In addition, the deletion and low mRNA expression of CDKN2A and CDKN2B are also positively correlated with hyperprogression.
To confirm the role of Siglec15 in modulating cancer immunity in BLCA, we analyzed the correlation between Siglec15 and the immunological characteristics of TME with respect to the above aspects. The findings from this study were validated in three independent external cohorts, including GSE31684, GSE32894, and IMvigor210.
Hu J., Yu A., Othmane B., Qiu D., Li H., Li C., Liu P., Ren W., Chen M., Gong G., Guo X., Zhang H., Chen J, & Zu X. (2021). Siglec15 shapes a non-inflamed tumor microenvironment and predicts the molecular subtype in bladder cancer. Theranostics, 11(7), 3089-3108.
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Publication 2021
Antigen Presentation Antigens Biological Response Modifiers CCND1 protein, human CDKN2A Gene Chemokine Deletion Mutation Dietary Fiber FGF4 protein, human Gene Expression Genes Immune Checkpoint Blockade Malignant Neoplasms MDM2 protein, human Neoplasms Response, Immune RNA, Messenger RNA-Seq T-Lymphocyte Therapeutics
2
Quantifying Immune and Angiogenesis Activities
Infiltration levels for immune cell types and activity levels for angiogenesis and antigen presentation were quantified using the ssGSEA [30 (link)] implementation in R package gsva [71 (link)]. ssGSEA is a rank-based method that computes an overexpression measure for a gene list of interest relative to all other genes in the genome. Normalized RNA-Seq or microarray datasets mentioned above were provided as input without further processing (i.e. no standardization or log transformation). A typical execution is gsva(data, list_of_signatures, method=”ssgsea”). The output for each signature is a near-Gaussian list of decimals that can be used in visualization/statistical analysis without further processing.
Şenbabaoğlu Y., Gejman R.S., Winer A.G., Liu M., Van Allen E.M., de Velasco G., Miao D., Ostrovnaya I., Drill E., Luna A., Weinhold N., Lee W., Manley B.J., Khalil D.N., Kaffenberger S.D., Chen Y., Danilova L., Voss M.H., Coleman J.A., Russo P., Reuter V.E., Chan T.A., Cheng E.H., Scheinberg D.A., Li M.O., Choueiri T.K., Hsieh J.J., Sander C, & Hakimi A.A. (2016). Tumor immune microenvironment characterization in clear cell renal cell carcinoma identifies prognostic and immunotherapeutically relevant messenger RNA signatures. Genome Biology, 17, 231.
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Publication 2016
angiogen Antigen Presentation Cells Genes Genome Microarray Analysis RNA-Seq
3
Predicting Immunotherapy Response Using Multimodal Data
We used logistic regression for our model to predict PD as the best RECIST response vs. nonPD rather than responder vs. progressor to better reflect the real-world setting where all outcomes (PD, SD, MR, PR, CR) are possible.. We evaluated genomic, transcriptomic, and clinical features. Categorical features were converted to binary features for each categorical value. To be conservative, no gene-level mutations or expression values were individually considered. Global genomic tumor characteristics such as TMB, purity, ploidy, heterogeneity, aneuploidy were considered. Features were generated from the transcriptome including ssGSEA values for genesets representing Cancer Hallmark pathways, and MHC-II and -I antigen presentation genes, as well as gene expression signatures following the methodology as described in their respective publications as described above and in Supplemental Table 6. Clinical characteristics including LDH and ECOG at start of anti-PD1 ICB, number of metastatic organs, gender, Mstage, number of different metastatic sites, metastatic sites, and melanoma subtype were evaluated (Supplemental Table 1). Features were chosen in a forward-selection based process, where features that were statistically significantly predictive (p<0.05) when added to the base model were ranked based on the ability of the combined model to discriminate outcomes (using ROC AUC as the metric), and the best feature chosen to be added to the base model. Potential features were evaluated also based on a manual review considering biological interpretability and clinical applicability. This process was then iterated with the new base model, and stopped when no features under consideration were statistically significantly predictive.
The set of tumors with both WES and RNAseq is smaller than the set of tumors with only WES; when the features chosen in model development for ipilimumab-naive tumors resulted in WES features only being chosen, model development was repeated in the superset of tumors requiring only clinical and WES data, and this model in the larger set is reported in the main text.
To estimate the “out-of-bag” AUC, we used k-fold cross-validation (splitting the data set into k subsets, training on k-1 subsets, and calculating AUC on the held out subset), and calculated the mean cross-validation AUC. Given the partially manual review of features, feature selection was not included in cross-validation. For the ipilimumab-treated subset (n=34), we chose k=5 folds, and for the larger ipilimumab-naive subset (n=85), we chose k=10 folds to maintain a cross-validation holdout set of >5 tumors. Cross-validation scores were calculated using the cross_val_score function from the Python sklearn package.
To further evaluate the statistical support for our models, we calculated the Akaike Information Criteria and Bayesian Information Criteria of each subsequent model after adding an additional feature in forward selection in the ipilimumab-experienced and ipilimumab-naive subgroups (Extended Data Figure 8cd), and also evaluated the addition of mutational burden as an additional feature to the selected models.
Liu D., Schilling B., Liu D., Sucker A., Livingstone E., Jerby-Arnon L., Zimmer L., Gutzmer R., Satzger I., Loquai C., Grabbe S., Vokes N., Margolis C.A., Conway J., He M.X., Elmarakeby H., Dietlein F., Miao D., Tracy A., Gogas H., Goldinger S.M., Utikal J., Blank C.U., Rauschenberg R., von Bubnoff D., Krackhardt A., Weide B., Haferkamp S., Kiecker F., Izar B., Garraway L., Regev A., Flaherty K., Paschen A., Van Allen E.M, & Schadendorf D. (2019). Integrative molecular and clinical modeling of clinical outcomes to PD1 blockade in patients with metastatic melanoma. Nature Medicine, 25(12), 1916-1927.
Publication 2019
Aneuploidy Antigen Presentation ARID1A protein, human Biopharmaceuticals Electrocorticography Gender Gene Expression Profiling Genes Genetic Heterogeneity Genome I-antigen Ipilimumab Malignant Neoplasms Melanoma Mutation Neoplasms Python Transcriptome
4
Derivation and Validation of T Cell-Inflamed GEP
The previously described T cell–inflamed GEP was derived by using a stepwise derivation process of discovery, validation, and refinement of candidate gene sets across a wide variety of solid tumors (15 (link)). The GEP was composed of 18 inflammatory genes related to antigen presentation, chemokine expression, cytolytic activity, and adaptive immune resistance, including CCL5, CD27, CD274 (PD-L1), CD276 (B7-H3), CD8A, CMKLR1, CXCL9, CXCR6, HLA-DQA1, HLA-DRB1, HLA-E, IDO1, LAG3, NKG7, PDCD1LG2 (PDL2), PSMB10, STAT1, and TIGTT. For GEP analysis, total RNA was isolated from 5-μm-thick FFPE sections of tumor tissue fixed on positively charged slides (Ambion RecoverAll total nucleic acid isolation kit for FFPE; catalog no. AM1975) at ALMAC, United Kingdom. Total RNA concentrations were measured using the NanoDrop ND1000 (Thermo Fisher Scientific) in 1.5 μl of test sample.
Gene expression analysis was conducted on the NanoString nCounter gene expression platform (NanoString Technologies, Seattle, WA) as described previously (15 (link)). Per sample, 50 ng of total RNA was mixed in a final volume of 5 to 7 μl with a 3′-biotinylated capture probe and 5′-reporter probe tagged with a fluorescent barcode, from the desired custom gene expression codeset (HUIMR680_V2_C2406+PLS_SPI-KE80_C2765 for Batch 1 and HUIMR800_C3176 for Batch 2), containing probes designed to function as positive and negative hybridization controls. Probes and target transcripts were hybridized overnight at 65°C for 14 to 18 hours as per manufacturers’ recommendations. Hybridized samples were run on the NanoString nCounter preparation station by using a high-sensitivity protocol where excess capture and reporter probes were removed and transcript-specific ternary complexes were immobilized on a streptavidin-coated cartridge. The cartridge samples were scanned at maximum resolution by using the nCounter digital analyzer. GEP scores were calculated as a weighted sum of normalized expression values for the 18 genes. Quality control of the gene expression data followed an approach similar to that of the NanoString clinical-grade assay, with the use of joint criteria that assessed the relationships between housekeeping genes and the negative control probes plus a weighted score evaluating the GEP gene counts versus background-subtracted counts. For housekeeping normalization, raw counts for the individual genes were log10 transformed and then normalized by subtracting the arithmetric mean of the log10 counts for a set of 11 housekeeping genes.
Cristescu R., Mogg R., Ayers M., Albright A., Murphy E., Yearley J., Sher X., Liu X.Q., Lu H., Nebozhyn M., Zhang C., Lunceford J.K., Joe A., Cheng J., Webber A.L., Ibrahim N., Plimack E.R., Ott P.A., Seiwert T.Y., Ribas A., McClanahan T.K., Tomassini J.E., Loboda A, & Kaufman D. (2018). Pan-tumor genomic biomarkers for PD-1 checkpoint blockade–based immunotherapy. Science (New York, N.Y.), 362(6411), eaar3593.
Publication 2018
Acclimatization Acid Hybridizations, Nucleic Antigen Presentation Biological Assay CCL5 protein, human CD274 protein, human Chemokine CMKLR1 protein, human CXCL9 protein, human Gene Expression Gene Expression Profiling Genes Genes, Housekeeping HLA-DQA1 HLA-DRB1 Antigen HLA-E antigen Hypersensitivity Inflammation isolation Joints lambda Spi-1 Neoplasms Nucleic Acids PSMB10 protein, human STAT1 protein, human Streptavidin T-Lymphocyte Tissues
5
Isolation and Purification of Cryptococcus Polysaccharides
GXM is the major polysaccharide that comprises the capsule of C. neoformans, and, as noted above, it has many immunomodulatory functions. These immunomodulatory properties make GXM a useful tool for examining immune responses. Other methods exist for isolating GXM from C. neoformans, but the method described herein summarizes the protocol that our laboratory routinely uses to obtain purified GXM. GXM can be isolated from all serotypes of C. neoformans and C. gattii (A to D). Differences in GXM structure (Fig. 7.1) affect virulence, inhibition of neutrophil migration, and tissue accumulation of GXM (42 (link)-44 (link)). Because of these differences, the GXM isolated from different serotypes may have differing degrees of immunomodulation.
Mannoproteins (MPs) are major T-cell antigenic determinants isolated from C. neoformans (29 (link), 40 (link)). MPs are mannosylated proteins that contain both N- and O-linked glycans (Fig. 7.2) and can be recognized by mannose receptors on antigen-presenting cells, which results in efficient antigen uptake, processing, and presentation to T cells (45 ). They are readily purified from the Cap67 acapsular mutant of C. neoformans, because this mutant does not have GXM on its surface to interfere with MP purification. However, other laboratories have successfully isolated MP from various other strains, including the encapsulated strains B3501 (41 ) and 184-A (46 (link), 47 (link)), as well as other nonencapsulated strains, such as strain 602 (47 (link)). The MP isolation described in this protocol is used to isolate total MP, not individual MPs. Additional purification is necessary to subfractionate MPs or to purify individual MPs. This can be accomplished using standard techniques, including size-exclusion chromatography, ion-exchange chromatography, hydrophobic interaction chromatography, and elution of bands from excised gels (30 (link), 41 , 48 (link)). MPs have also been subfractionated based on the molar strength of methyl α-d manno-pyranoside required to elute it from Con A beads (41 ). Once purified, MP (either total MP or specific MPs) can serve as components of candidate vaccines against cryptococcosis. Additionally, because MPs are effectively taken up by mannose receptors on dendritic cells and macrophages, they can be used for in vitro studies to examine cytokine production, antigen presentation, and T cell activation. Finally, the biochemical properties of MPs can be investigated by assaying for functions such as enzymatic activity.
Wozniak K.L, & Levitz S.M. (2009). Isolation and Purification of Antigenic Components of Cryptococcus. Methods in Molecular Biology (Clifton, N.j.), 470, 71-83.
Publication 2009
Antigen-Presenting Cells Antigen Presentation Antigens Capsule Chromatography Concanavalin A Cryptococcus gattii Cryptococcus neoformans Cryptococcus neoformans Infections Cytokine Dendritic Cells enzyme activity Epitopes, T-Lymphocyte Gel Chromatography Gels Hydrophobic Interactions Immunomodulation Ion-Exchange Chromatographies isolation Macrophage mannoproteins Molar Neutrophil Polysaccharides Proteins Psychological Inhibition Receptor, Mannose Response, Immune Strains T-Lymphocyte Tissues Vaccines Virulence

Most recents protocols related to «Antigen Presentation»

1
Generating PDTO-specific T cells
Co-culture of PDTO and autologous immune cells will be based on the protocol described by Cattaneo et al. [21 (link)] Briefly, PDTO specific T cells will be induced through serial co-culture with dissociated PDTO. PBMC (~ 10.106 cells) will be thawed and set to resting condition with IL-2 (150 U/mL) overnight. Meanwhile, PDTO will be treated with IFNγ (200 ng/mL) for 24 hours to favor antigen presentation and will be dissociated to produce Antigen Presenting Tumor Cells (~ 0.5.106 cells APTC). PBMC and APTC will be next co-cultured (20:1 ratio) in a CD28 (5 μg/mL) coated culture plate for successive periods of 7 days to induce clonal expansion of PDTO specific T cells. T cells will be then evaluated for their tumor reactivity through the detection of activation (CD137) and functional (CD107a, IFNγ) markers by flow cytometry (Cytoflex, Beckman Coulter) and will be cryopreserved for later use for the evaluation or response to treatments.
Perréard M., Florent R., Divoux J., Grellard J.M., Lequesne J., Briand M., Clarisse B., Rousseau N., Lebreton E., Dubois B., Harter V., Lasne-Cardon A., Drouet J., Johnson A., Le Page A.L., Bazille C., Jeanne C., Figeac M., Goardon N., Vaur D., Micault E., Humbert M., Thariat J., Babin E., Poulain L., Weiswald L.B, & Bastit V. (2023). ORGAVADS: establishment of tumor organoids from head and neck squamous cell carcinoma to assess their response to innovative therapies. BMC Cancer, 23, 223.
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Publication 2023
Antigen-Presenting Cells Antigen Presentation Cells Clone Cells Flow Cytometry Interferon Type II Neoplasms T-Lymphocyte TNFRSF9 protein, human
2
In vitro and ex vivo IFN-γ ELISPOT Assays
Immune responses were evaluated with in vitro and ex vivo IFN-γ ELISPOT assays. For in vitro ELISPOT assays, PBMCs were thawed and stimulated with the target epitope. The next day, PBMCs were stimulated with IL-2 (120 U/mL) and incubated for 12-14 days. The PBMCs were then counted and plated in ELISPOT wells. Cells were restimulated with or without the target peptide. All conditions were performed in triplicates. For ex vivo IFN-γ ELISPOT assays, cells were thawed, rested, then plated on ELISPOT plates. Cells were stimulated with or without the target epitope for 24-48 h to ensure antigen presentation.
In vitro ELISPOT assays were performed with a cell density of 2.5 ×105 cells/well. Ex vivo ELISPOTs were performed with cell densities of 9 ×105 cells/well, for PBMCs, and 6.8×105 cells/well, for bone marrow mononuclear cells. Plates were analyzed with the ImmunoSpot Series 2.0 Analyzer (CTL, Shaker Heights, Ohio). Results were generated by subtracting the background obtained with negative controls. A detailed description of our setup was described previously (32 (link)). Statistical significance of ELISPOT responses was analyzed by the DFR method (33 (link)). For non-triplicate samples, responses were evaluated empirically and defined as true if the number of spots observed in the peptide stimulated wells were at least double of the spot counts in the control wells.
Grauslund J.H., Holmström M.O., Martinenaite E., Lisle T.L., Glöckner H.J., El Fassi D., Klausen U., Mortensen R.E., Jørgensen N., Kjær L., Skov V., Svane I.M., Hasselbalch H.C, & Andersen M.H. (2023). An arginase1- and PD-L1-derived peptide-based vaccine for myeloproliferative neoplasms: A first-in-man clinical trial. Frontiers in Immunology, 14, 1117466.
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Publication 2023
Antigen Presentation Biological Assay Bone Marrow Cells Cells Enzyme-Linked Immunospot Assay Epitopes Exanthema Interferon Type II Peptides Response, Immune
3
TCR-Mediated Luciferase Reporter Assay
TCR-KO reporter cells were activated with blinatumomab or staphylococcal enterotoxin E in the presence of Raji target cells (4:1 E:T ratio) in 96-well white flat-bottom assay plates (Corning). After a 6-hour incubation at 37°C, 5% CO2, luciferase reporter induction was determined by addition of Bio-Glo-NL detection reagent (Promega). Plates were read on a GloMax Discover luminometer (Promega). Fold induction was calculated: RLUagonist/RLUno agonist. 4-PL curves were generated by GraphPad Prism Software.
A375 or SK-MEL5 cells were plated overnight to test the TCR-mediated reporter activation by peptide presented by APCs. The following day, serial titrations of the peptides were added followed by TCR-expressing TCR-KO cells (2.5:1 E:T ratio) as indicated. After a 6-hour incubation at 37°C, 5% CO2, luciferase reporter induction was determined as previously shown. In some cases, SK-MEL5 cells were treated with 200 ng/mL of interferon-gamma (IFN-γ; Peprotech) during the overnight plating.
To test the TCR-mediated reporter activation by processed whole antigen protein, THP-1-derived dendritic cells (THP-1-DCs) were generated as described32 (link) with slight modification. Briefly, immature-like DCs were generated by treatment with 100 ng/mL granulocyte-macrophage colony-stimulating factor and 100 ng/mL IL-4 (both from Peprotech) for 5 days at 37°C. Then, cells were harvested and matured with 100 ng/mL granulocyte-macrophage colony-stimulating factor, 200 ng/mL IL-4, 15 ng/mL tumor necrosis factor-alpha (Peprotech), and 268 μM Ionomycin (Sigma) in the presence of titrations of recombinant H3 or 2020 Fluzone Quadrivalent. After 48 hours at 37°C, loaded THP-1-DCs were co-cultured with TCR-expressing reporter cells as previously shown.
To test the TCR-mediated reporter activation by translation and antigen presentation of transfected nucleic acids, A375 cells were transfected with a titration of HPV16 E6 expression plasmid complexed with ViaFect transfection reagent (Promega). After 24 hours at 37°C, transfected A375 cells were co-cultured with HPV16 E7 TCR-expressing reporter cells as previously shown.
Grailer J., Cheng Z.J., Hartnett J., Slater M., Fan F, & Cong M. (2023). A Novel Cell-based Luciferase Reporter Platform for the Development and Characterization of T-Cell Redirecting Therapies and Vaccine Development. Journal of Immunotherapy (Hagerstown, Md. : 1997), 46(3), 96-106.
Publication 2023
Antigen Presentation Antigens Atrial Premature Complexes Biological Assay blinatumomab Cells Cultured Cells Dendrites Dendritic Cells E6 protein, Human papillomavirus type 16 Granulocyte-Macrophage Colony-Stimulating Factor Interferon Type II Ionomycin Luciferases Nucleic Acids oncogene protein E7, Human papillomavirus type 16 Peptides Plasmids Post-Translational Protein Processing prisma Promega Staphylococcal enterotoxin E THP-1 Cells Titrimetry Transfection Tumor Necrosis Factor-alpha
4
Generation of Bovine Antigen Presenting Cells
Bovine DRA, DRB3, and CD80 genes were cloned into the mammalian expression plasmid pcDNA4/myc-His-C (ThermoFisher, Waltham, MA, USA) via Gibson assembly master mix (New England Biolabs, Ipswich, MA, USA) according to manufacturer’s instructions. RNA was isolated from PBMCs using Qiagen RNeasy Kit (Qiagen, Hilden, Germany) following manufacturer’s instruction. cDNA was produced using SuperScriptIII reverse transcriptase with oligo dT primer (ThermoFisher, Waltham, MA, USA). Inserts and plasmids were amplified using Q5 high-fidelity 2x Master Mix (New England Biolabs, Ipswich, MA, USA) with gene specific primers in Supplemental Table 1 and used to transform TOP10 chemically competent E. coli (ThermoFisher, Waltham, MA, USA). Colonies were screened by Sanger sequencing with T7 promoter forward primer and BGH reverse primer. Positive colonies were cultured overnight in LB media, 100μg/mL carbenicillin and plasmids were isolated using ZymoPURE II plasmid midiprep kit (Zymo Research, Irvine, CA, USA).
To generate artificial antigen presenting cells, HEK-293 cells were transfected with BoLA-DRA (NCBI Gene ID 506214), BoLA-DRB3 (NCBI Gene ID 282530), and bovine CD80 (NCBI Gene ID 407131) encoding plasmids and selected with antibiotics. HEK-293 cells were obtained from the American Type Culture Collection (Manassas, VA, USA) and cultured in complete Eagle’s Minimum Essential Medium (EMEM) (ThermoFisher, Waltham, MA, USA) supplemented with antibiotic/antimycotic solution (ThermoFisher, Waltham, MA, USA) and 10% fetal bovine serum. On the day prior to transfection 1x106 cells were seeded in each well of 6-well plates and cultured overnight at 37°C, 5% CO2. Just prior to transfection, the growth media was removed and replaced with 1mL fresh complete EMEM. Transfections were performed using Lipofectamine 2000 (ThermoFisher, Waltham, MA, USA) according to manufacturer’s instruction with 1μg of each plasmid. The day following transfection, the media was removed and replaced with complete EMEM containing 400μg/mL zeocin (ThermoFisher, Waltham, MA, USA). To obtain a homogenous population of co-transfected cells, single cell sorting was performed using a FACSAria Fusion cell sorter (BD Biosciences, Franklin Lakes, New Jersey, USA). Transfected cells were labeled with anti-BoLA DR-RPE, clone CC108 (Bio-Rad, Hercules, CA, USA) and anti-CD80-FITC, clone IL-A159 (Bio-Rad, Hercules, CA, USA). Double positive cells were sorted into 96-well plates and transferred to larger flasks once 90% confluence was achieved. To confirm transgene expression prior to use in antigen presentation assays, transfected HEK 293 cells were labeled as described above and analyzed on a FACS Symphony custom flow cytometer. Data was analyzed using Flow-Jo software (BD Biosciences, Franklin Lakes, New Jersey, USA).
Kaplan B.S., Hofstetter A.R., McGill J.L., Lippolis J.D., Norimine J., Dassanayake R.P, & Sacco R.E. (2023). Identification of a DRB3*011:01-restricted CD4+ T cell response against bovine respiratory syncytial virus fusion protein. Frontiers in Immunology, 14, 1040075.
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Publication 2023
Antibiotics Antigen-Presenting Cells Antigen Presentation Biological Assay BoLA-DRB3 antigen Bos taurus Carbenicillin Cells Clone Cells DNA, Complementary Eagle Escherichia coli Fetal Bovine Serum Fluorescein-5-isothiocyanate galiximab Genes HEK293 Cells Homozygote lipofectamine 2000 Mammals oligo (dT) Oligonucleotide Primers Plasmids RNA-Directed DNA Polymerase Transfection Transgenes Zeocin
5
Profiling Immune Landscapes in Cancer
To estimate the signature of MHC-II antigen presentation in cancer cells, we calculated the enrichment scores for each cell using the AddModuleScore function in Seurat with the gene list from the REACTOME_MHC_CLASS_II_ANTIGEN_PRESENTATION pathway (c2.cp.reactome.v7.2.symbols.gmt, download from https://www.gsea-msigdb.org/gsea/index.jsp). To explore the cytotoxic and exhausted functions of T and NK cells, we calculated the cytotoxic score and exhausted score for each cell using the canonical cytotoxic (GZMA, GZMB, GZMK, GNLY, IFNG, PRF1, and NKG7) and exhausted (LAG3, TIGIT, PCCD1, HAVCR2, CTLA4, LAYN, and ENTPD1) markers, respectively. With the same method, we used the gene list (Additional file 3: Table S2) in “LM22.xls” from CIBERSORT [22 (link)] to estimate the phenotype (M0, M1, or M2) for each macrophage. We also calculated the antigen presentation score for DCs with the previously reported markers (Additional file 3: Table S2) [23 (link)]. A mean value of module scores of a cell cluster (≥ 10 cells) from an individual sample was calculated to present the signature level.
Hu J., Zhang L., Xia H., Yan Y., Zhu X., Sun F., Sun L., Li S., Li D., Wang J., Han Y., Zhang J., Bian D., Yu H., Chen Y., Fan P., Ma Q., Jiang G., Wang C, & Zhang P. (2023). Tumor microenvironment remodeling after neoadjuvant immunotherapy in non-small cell lung cancer revealed by single-cell RNA sequencing. Genome Medicine, 15, 14.
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Publication 2023
Antigen Presentation Antigens Cells CTLA4 protein, human ectonucleoside triphosphate diphosphohydrolase 1 Genes Genes, MHC Class II GZMA protein, human GZMB protein, human HAVCR2 protein, human Histocompatibility Antigens Class II Interferon Type II Macrophage Malignant Neoplasms Natural Killer Cells Phenotype PRF1 protein, human TIGIT protein, human

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Gm csf by R&D Systems
Sourced in United States, United Kingdom, Germany, France, China, Israel, Canada, Sweden
GM-CSF is a cytokine that stimulates the production and differentiation of granulocytes and macrophages from bone marrow progenitor cells. It is a key regulator of granulopoiesis and macrophage function.
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Bovine serum albumin (bsa) by Merck Group
Sourced in United States, Germany, United Kingdom, China, Italy, Japan, France, Sao Tome and Principe, Canada, Macao, Spain, Switzerland, Australia, India, Israel, Belgium, Poland, Sweden, Denmark, Ireland, Hungary, Netherlands, Czechia, Brazil, Austria, Singapore, Portugal, Panama, Chile, Senegal, Morocco, Slovenia, New Zealand, Finland, Thailand, Uruguay, Argentina, Saudi Arabia, Romania, Greece, Mexico
Bovine serum albumin (BSA) is a common laboratory reagent derived from bovine blood plasma. It is a protein that serves as a stabilizer and blocking agent in various biochemical and immunological applications. BSA is widely used to maintain the activity and solubility of enzymes, proteins, and other biomolecules in experimental settings.

More about "Antigen Presentation"

Antigen presentation is a crucial process in the immune system, where antigenic peptides are displayed on the surface of cells, typically by major histocompatibility complex (MHC) molecules.
This process enables T cells to identify and respond to foreign or abnormal antigens, initiating an immune response.
The presentation of antigens involves the processing and transport of peptides derived from intracellular or extracellular sources, and is a highly regulated process.
Defects in antigen presentation can contribute to various health conditions, including autoimmune diseases, immunodeficiencies, and cancer.
Understanding the nuances of antigen presentation is essential for the development of effective immunotherapies and vaccines.
Researchers often utilize techniques such as LPS (lipopolysaccharide) stimulation, CFSE (carboxyfluorescein succinimidyl ester) labeling, and FBS (fetal bovine serum) supplementation to study antigen presentation.
Flow cytometry using a FACSCalibur instrument can also be employed to analyze antigen-presenting cells and their interactions with T cells.
Additionally, L-glutamine, Brefeldin A, and EBioY-Ae antibodies are commonly used in antigen presentation research.
ELISA (enzyme-linked immunosorbent assay) and GM-CSF (granulocyte-macrophage colony-stimulating factor) are also relevant tools and factors in this field.
Bovine serum albumin (BSA) is frequently used as a blocking agent or protein supplement in antigen presentation experiments.
By understanding the complex processes involved in antigen presentation, researchers can develop more effective immunotherapies and vaccines, ultimately leading to improved patient outcomes and advancements in the field of immunology.