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Perforin

Q: What is perforin and what is its role in the immune system?

Perforin is a pore-forming protein that is secreted by cytotoxic T lymphocytes and natural killer cells. It plays a crucial role in the immune system's ability to eliminate virus-infected or cancerous cells. Perforin polymerizes and inserts into target cell membranes, creating pores that allow the entry of granzymes and initiate programmed cell death. Understanding the mechanisms and regulation of perforin is essential for advancing immunotherapies and treatments for immune-related disorders.

Q: How can PubCompare.ai help with Perforin research?

PubCompare.ai allows researchers to screen protocol literature more efficiently and leverage AI to pinpoint critical insights. The platform can help researchers identify the most effective protocols related to Perforin for their specific research goals. PubCompare.ai's AI-driven analysis can highlight key differences in protocol effectiveness, enabling researchers to choose the best option for reproducibility and accuracy in their Perforin studies.

Q: What are the common usage challenges with Perforin?

One of the main challenges with Perforin is ensuring the reproducibility and reliability of experimental protocols. Researchers need to carefully optimize various factors, such as the concentration of Perforin, the incubation time, and the target cell line, to obtain consistent and meaningful results. Additionally, understanding the different variations or types of Perforin and their specific applications can be crucial for designing effective experiments and therapies.

Q: How can PubCompare.ai help address usage challenges with Perforin?

PubCompare.ai's AI-powered protocol comparison capabilities can greatly assist researchers in addressing usage challenges with Perforin. The platform allows users to quickly screen and identify the most reliable and effective protocols from the literature, pre-prints, and patents. By comparing key protocol details and their associated outcomes, PubCompare.ai can help researchers choose the best methods to ensure reproducibility and accuracy in their Perforin experiments. This data-driven approach can save time and enhance the quality of Perforin research.

Q: What are the different variations or types of Perforin, and how do they differ in their applications?

Perforin comes in several different isoforms or variants, each with potentially unique characteristics and applications. For example, some variants may be more effective at pore formation in certain cell types or under specific environmental conditions. Understanding these differences can be crucial for selecting the appropriate Perforin for your research or therapeutic needs. PubCompare.ai can assist in exploring the nuances of different Perforin types and their suitability for your specific experminents.

Perforin is a pore-forming protein secreted by cytotoxic T lymphocytes and natural killer cells.
It plays a crucial role in the immune system's ability to eliminate virus-infected or cancerous cells.
Perforin polymerizes and inserts into target cell membranes, creating pores that allow the entry of granzymes and initiate programmed cell death.
Understanding the mechanisms and regulation of perforin is essential for advanciing immunotherapies and treeatments for immune-related disorders.

Most cited protocols related to «Perforin»

Transcriptional Analysis of T Cell Subsets

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Publication 2014

Anabolism beta-Actin CD4 Positive T Lymphocytes CD8-Positive T-Lymphocytes CDK9 protein, human Cells Cyclin T1 Deoxycholate DNA, Complementary Nitrocellulose Oligonucleotide Primers Perforin PRDM1 protein, human Protease Inhibitors Proteins SDS-PAGE Sodium Chloride T-Lymphocyte TBX21 protein, human Tissue, Membrane Triton X-100 Tromethamine Western Blot

Identifying Cytolytic Activity Genes from TCGA

TCGA RNA-seq data in form of normalized RNA-Seq by Expectation-Maximization (RSEM) values from multiple cancer data sets was downloaded from the Firehose Broad GDAC (http://gdac.broadinstitute.org/, DOI for data release: 10.7908/C11G0KM9) using the TCGA2STAT package for R^{41 (link)}, and used to find overlap between TCGA gene expression indicative of cytolytic activity and genes from our pooled screen where loss-of-function confers resistance to T cell killing. We first identified the genes correlated with a previously identified cytolytic activity signature (CYT), namely the geometric mean of granzyme A (GZMA) and perforin 1 (PRF1) expression^{15 (link)}. To identify these genes in the TCGA data, we calculated the geometric mean of GZMA and PRF1 in each data set and searched for any genes with a positive correlation to this quantity across patients (Pearson’s r > 0, P < 0.05). We then examined the intersection between genes whose expression was correlated with cytolytic activity (TCGA datasets) and the enriched genes found in the CRISPR screen (554 genes). Individual heatmaps for the two sets of clustered genes were regenerated for each cancer type and can be found at https://bioinformatics.cancer.gov/publications/restifo.
For the top 20 ranked gene candidates from any of the screens, we obtained patient mutation data from the TCGA database using cBioPortal^{42 (link),43 (link)}. For mutation frequency counts, tumours containing likely loss-of-function genetic aberrations (defined as homozygous deletion, missense, nonsense, frame-shift, truncated or splice-site mutations) were included in the analysis.

Patel S.J., Sanjana N.E., Kishton R.J., Eidizadeh A., Vodnala S.K., Cam M., Gartner J.J., Jia L., Steinberg S.M., Yamamoto T.N., Merchant A.S., Mehta G.U., Chichura A., Shalem O., Tran E., Eil R., Sukumar M., Guijarro E.P., Day C.P., Robbins P., Feldman S., Merlino G., Zhang F, & Restifo N.P. (2017). Identification of essential genes for cancer immunotherapy. Nature, 548(7669), 537-542.

Publication 2017

Clustered Regularly Interspaced Short Palindromic Repeats Deletion Mutation Gene Expression Genes GZMA protein, human Homozygote Malignant Neoplasms Mutation Mutation, Nonsense Neoplasms Operator, Genetic Patients Perforin Reading Frames Reproduction RNA-Seq Screenings, Genetic T-Lymphocyte

Breast Cancer Survival Analysis: ANXA1, CYT, and MATH

The patient clinical data and gene expression data (mRNA expression z-score of RNA-seq) were downloaded through cBioPortal from the latest The Cancer Genome Atlas (TCGA) cohort (TCGA provisional) as described previously [37 (link),38 (link),39 (link),40 (link),41 (link)]. Among 1081 female breast cancer patients with mRNA expression from RNA sequence data, survival data were available in 1079 patients. Level 3 Z-score normalized gene expression data, as well as overall survival data from 1904 patients in a Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort [42 (link)], were also downloaded from cBioPortal. Patients were classified as either high or low ANXA1 expression using the median of their mRNA expression as the cut-off [11 (link),15 (link)]. Disease-free survival (DFS) was defined from the time of completion of primary treatment until clinical confirmation of tumor recurrence. Overall survival (OS) was defined using time of death. For disease-specific survival (DSS) analyses, the patients who died of other causes were excluded. CYT is the immune cytolytic activity score. It has previously been defined by calculating the geometric mean expression values of granzyme A (GZMA) and perforin (PRF1) [43 (link)]. These proteins are pivotal cytolytic effector molecules. MATH is the mutant-allele tumor heterogeneity level. This is derived by calculating the median of its mutant-allele fractions at tumor-specific mutated loci, which has been described in detail [44 (link),45 (link),46 (link)].

Okano M., Oshi M., Butash A.L., Katsuta E., Tachibana K., Saito K., Okayama H., Peng X., Yan L., Kono K., Ohtake T, & Takabe K. (2019). Triple-Negative Breast Cancer with High Levels of Annexin A1 Expression Is Associated with Mast Cell Infiltration, Inflammation, and Angiogenesis. International Journal of Molecular Sciences, 20(17), 4197.

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Publication 2019

Alleles Gene Expression Genetic Heterogeneity Genome GZMA protein, human Malignant Neoplasm of Breast Malignant Neoplasms Neoplasms Patients Perforin Proteins Recurrence RNA, Messenger RNA-Seq RNA Sequence Woman

Comprehensive Tumor Immune Profiling by GSEA

Gene Set Enrichment Analysis (GSEA) was performed comparing Grade 3 vs. Grade 1+2 tumors, using the Hallmark gene sets (36 (link)) with the software provided by the Broad Institute (https://software.broadinstitute.org/gsea/index.jsp), as described before (23 (link)–25 (link), 29 (link)).
Measurements of immune activities, such as relative fractions of different types of immune cells in TME or T cell receptor (TCR) diversity, were estimated from tumor gene expression with CIBERSORT, a bioinformatic algorithm using the TCGA-BRCA cohort (37 (link)). The counts of neoantigen load were represented as Insertion and deletion (Indel) mutation, which was collated from the Pan-Cancer Atlas study of Thorsson et al (37 (link)). Cytolytic activity score (CYT) was defined as the geometric mean of grandzyme A (GZMA) and Perforin 1 (PRF1) expression values in transcripts per million (TPM), as described previously (38 (link), 39 (link)). Additionally, given METABRIC and GSE25066 transcriptomes were derived from the microarray, we used the geometric mean of GZMA and PRF1 expression values to estimate cytolytic activity in these two cohorts.

Takahashi H., Oshi M., Asaoka M., Yan L, & Takabe K. (2020). Molecular biological features of Nottingham histological Grade 3 breast cancers. Annals of surgical oncology, 27(11), 4475-4485.

Publication 2020

Cells Deletion Mutation Genes Genes, Neoplasm INDEL Mutation Malignant Neoplasms Microarray Analysis Mutation Neoplasms Perforin T-Cell Receptor Transcriptome

Urine-based Molecular Biomarkers for Kidney Transplant

After transplantation, urine was collected on days 3, 7, 15, and 30 and in months 2, 3, 4, 5, 6, 9, and 12; as well as at the time of each kidney-allograft biopsy and 2 weeks thereafter. Urine-cell pellets were prepared at the clinical sites, stored at −80°C, and shipped to the Gene Expression Monitoring (GEM) Core at Weill Cornell Medical College, New York.
The staff at GEM Core isolated RNA from the pellets and assessed RNA quantity and purity (Table S3 in the Supplementary Appendix). Absolute levels of the mRNAs prespecified in the study protocol (CD3ε, perforin, granzyme B, proteinase inhibitor 9, CD103, IP-10, CXCR3, and transforming growth factor β1 [TGF-β1]) and 18S ribosomal RNA (rRNA) were quantified in preamplification-enhanced real-time quantitative polymerase-chain-reaction (PCR) assays with the use of oligonucleotide primers and TaqMan probes (Table S4 in the Supplementary Appendix) designed by the GEM Core, and the results (mRNA copies per microgram of total RNA and 18S rRNA copies [×10⁻⁶] per microgram of total RNA) were reported to the statistical analysis and clinical coordinating center. The staff members at GEM Core were unaware of the clinical information, including the results of kidney-allograft biopsies, before transfer of the mRNA data set to the statistical analysis and clinical coordinating center.
Urine specimens were classified as passing quality control if the 18S rRNA copy number was greater than or equal to 5×10⁷ per microgram of total RNA isolated from the urine pellet and if the TGF-β1 mRNA copy number was greater than or equal to 100 copies per microgram of total RNA isolated from the urine pellet. If either threshold was not met, the specimen was classified as failing quality control.

Suthanthiran M., Schwartz J.E., Ding R., Abecassis M., Dadhania D., Samstein B., Knechtle S.J., Friedewald J., Becker Y.T., Sharma V.K., Williams N.M., Chang C.S., Hoang C., Muthukumar T., August P., Keslar K.S., Fairchild R.L., Hricik D.E., Heeger P.S., Han L., Liu J., Riggs M., Ikle D.N., Bridges N.D, & Shaked A. (2013). Urinary-Cell mRNA Profile and Acute Cellular Rejection in Kidney Allografts. The New England journal of medicine, 369(1), 20-31.

Publication 2013

Allografts alpha HML-1 Biological Assay Biopsy CD3E protein, human Cells CXCR3 protein, human Granzyme B Kidney Oligonucleotide Primers Pellets, Drug Perforin Protease Inhibitors Real-Time Polymerase Chain Reaction RNA, Messenger RNA, Ribosomal, 18S TGF-beta1 Transplantation Urine

Most recents protocols related to «Perforin»

Chimeric NKp30 Mouse T Cells

Not available on PMC !

Example 4

This example demonstrates that chimeric NKp30 mouse T cells specifically respond to tumor cells expressing NKp30 ligands. These results indicate that Human NKp30 Receptors are functional in mouse T cells.

Effector T cells derived from B6 (open), perforin-deficient (Pfp−/−, filled) mice that were modified with NKp30 receptors were co-cultured with RMA or RMA/B7-H6 cells, respectively, at a ratio of 1:1 5-hr LDH release assays. The data are presented as mean±SD of triplicates and are representative results from two independent experiments. The T cells lysed a significantly higher percentage of NKp30 ligand-positive cells (RMA/B7-H6, FIG. 10B) than ligand-negative cells (cell line RMA, FIG. 10A). Specific lysis was substantially decreased with the Pfp−/− cells. These results demonstrated that specific lysis of RMA/B7-H6 by NKp30-modified murine T cells required perforin.

US11872248B2. Nucleic acids encoding chimeric receptor comprising NKP30 receptor and CD28 and CD3 zeta domains and human T cell containing (2024-01-16). THE TRUSTEES OF DARTMOUTH COLLEGE [US]. Inventors: Tong Zhang [US], Charles L. Sentman [US].

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Patent 2024

Biological Assay Cell Lines Cells Chimera Homo sapiens Ligands Mus Natural Cytotoxicity Triggering Receptor 3 NCR3LG1 protein, human Neoplasms Perforin T-Lymphocyte

Comprehensive Phenotypic Profiling of Immune Cells

Frozen PBMC and SVC were thawed and stained with an extracellular primary antibody panel containing the following antibodies from BD Biosciences: BUV496 CD16 (Cat# 612944), BUV563 CD56 (Cat# 565704), BUV661 CD38 (Cat# 612969), BUV737 CD69 (Cat# 612817), BUV805 CD45 (Cat# 612891), BB700 NKG2A (Cat# 747926), APC Vio770 CCR5 (Cat# 557755), V500 CD14 (Cat# 561391), BV510 CD19 (Cat# 562947), BV650 CD98 (Cat# 744505), BV711 Sialyl Lewis x (Cat# 563910), PE-Cy5 CD54 (Cat# 555512). From Biolegend: Biotin NKp46 (Cat# 331906), A700 CD63 (Cat# 353024), BV421 Bcl-2 (Cat# 658709), BV510 CD123 (Cat# 306022), BV750 CD3 (Cat# 344845), BV785 HLA-DR (Cat# 307642), PE CD26 (Cat# 302706), PE-Cy7 NKG2D (Cat# 320812), PE-Cy7 CD162 (Cat# 328816), BB515 CD49e (Cat# 130-110-534, Miltenyi), PE-Cy5.5 KIR2DL1/S1 (Cat# A66898, Beckman Coulter), PE-Cy5.5 KIR2DL2/L3/S2 (Cat# A66900, Beckman Coulter). Staining was performed in FACS buffer (PBS with 2mM EDTA (Cat# AM9260G, Ambion), 2% FCS (Cat# F7524, Sigma). After 20 min incubation at room temperature (RT) and in the dark, the cells were washed twice with FACS buffer and further stained with a secondary antibody panel containing streptavidin (Cat# 624294, BD Biosciences) for 15 min at RT in dark. Cells were washed twice with FACS buffer before adding Fix/perm Buffer (diluted ¼ with eBioscience reagents: Fix/perm diluent (Cat#00.5223.56) and Fix/perm concentrate (Cat#00.5123.43)) and incubated for 45 min RT in dark. Cells were then washed twice with perm/MQ buffer (Perm Buffer 10X (Cat#00.8333.56) diluted 1/10 with MQ water). Further, the cells were stained with an intracellular antibody panel containing the following antibodies from BD Biosciences: BUV395 Ki67 (Cat# 564071), BB755-P Perforin (Cat# 624391, BD Horizon custom reagents), BB790-P Granzyme B (Cat# 624296, BD Horizon custom reagents), and eF660 Eomes (Cat# 50-4877-41, eBioscience), PE-Dazzle594 T-bet (Cat# 644828, Biolegend). Live/dead Fixable Aqua Dead Cell stain kit (Invitrogen, 1:100 dilution) was used to distinguish between dead and live cells. After 30 min incubation, the cells were washed twice with perm/MQ buffer and kept in FACS buffer for immediate flow cytometry analysis. Samples were run on a 29-color Symphony (BD Biosciences) with 405, 488, 561 and 639 lasers using the BD FACSDiva™ software (BD Biosciences). Flow cytometry data generated was analyzed using FlowJo V10 (Treestar, USA).

Haugstøyl M.E., Cornillet M., Strand K., Stiglund N., Sun D., Lawrence-Archer L., Hjellestad I.D., Busch C., Mellgren G., Björkström N.K, & Fernø J. (2023). Phenotypic diversity of human adipose tissue-resident NK cells in obesity. Frontiers in Immunology, 14, 1130370.

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Publication 2023

Antibodies BCL2 protein, human Biotin Buffers CCR5 protein, human Cells CY5.5 cyanine dye DPP4 protein, human Edetic Acid Flow Cytometry Freezing GZMB protein, human HLA-DR Antigens ICAM1 protein, human Immunoglobulins Interleukin-3 Receptor alpha Subunit KIR2DL1 protein, human KIR2DL2 protein, human NCR1 protein, human Perforin Progressive Encephalomyelitis with Rigidity Protoplasm SELPLG protein, human Sialyl Lewis X Antigen Stains Streptavidin Technique, Dilution

Multiparametric Phenotypic Analysis of T and NK Cells

For phenotypic analysis, cells were labeled simultaneously with a panel of anti-CD3-Cy-7APC (clone SP34-2; 1:300 dilution), CD4-APC (clone RPA-T4; 1:300 dilution), CD8-Alexa700 (clone RPA-T8; 1:300 dilution), CD95-FITC (clone DX2; 1:300 dilution) and CD28-Cy-5PE (clone CD28.2; 1:300 dilution) antibodies (BD Biosciences). Memory CD4 T cells were discriminated based on the expression of CD28 and CD95 as described previously^{96 (link),97 (link)}. To identify NK cells, PBMC were surface labeled with a panel of anti-CD3 (1:300 dilution), CD20 (clone 2H7; 1:300 dilution), CD14 (clone M5E2; 1:300 dilution), NKG2A (clone Z199; 1:300 dilution), and KIR2D (clone NKVFS1; 1:300 dilution) antibodies. After the cells were fixed and permeabilized, they were labeled with anti-perforin (clone deltaG9; 1:100 dilution) and Ki-67 (clone B56; 1:300 dilution) antibodies. Labeled cells were fixed with 0.5% paraformaldehyde and analyzed using an LSR II flow cytometer (BD Biosciences). The gating strategy is shown in Supplementary Fig. 5. All the antibodies were titrated using rhesus macaque PBMC.
To determine SIV-env and gag specific CD4 and CD8 T cell responses, cells were stimulated with overlapping peptides as described previously^{41 (link),81 (link),98 (link)}. Control cultures were set up for each sample without SIV peptides. After stimulation, cells were labeled with cell surface markers (anti-CD3, CD4, CD8, CD28 and CD95 at dilutions as above) and Vivid to discriminate live and dead cells⁹⁹. The cells were fixed (Fix/Perm kit; BD Biosciences), and after permeabilization were labeled with anti-IL-2-PE (clone MQ1-17H12; 1:300 dilution), IFN-γ-FITC (clone B27; 1:300 dilution), and TNF-α-Cy7PE (clone Mab11; 1:50 dilution). Labeled cells were fixed with 0.5% paraformaldehyde and analyzed using an LSR II flow cytometer (BD Biosciences).

Mattathil J.G., Volz A., Onabajo O.O., Maynard S., Bixler S.L., Shen X.X., Vargas-Inchaustegui D., Robert-Guroff M., Lebranche C., Tomaras G., Montefiori D., Sutter G, & Mattapallil J.J. (2023). Direct intranodal tonsil vaccination with modified vaccinia Ankara vaccine protects macaques from highly pathogenic SIVmac251. Nature Communications, 14, 1264.

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Publication 2023

Antibodies CD8-Positive T-Lymphocytes Cells Clone Cells Fluorescein-5-isothiocyanate Interferon Type II Macaca mulatta Memory T Cells Muromonab-CD3 Natural Killer Cells paraform Peptides Perforin Phenotype Progressive Encephalomyelitis with Rigidity Technique, Dilution Tumor Necrosis Factor-alpha

Tumor Immune Landscape Analysis

Tumor-infiltrated cells were estimated by single-sample gene set enrichment analysis (ssGSEA) using the GSVA package (Hänzelmann et al., 2013 (link)). Transcriptional data of tumor-infiltrating cells used for functional analysis were derived from Charoentong et al. (Rooney et al., 2015 (link)). The positive immune regulators were defined as the collection of “effector” cells, active dendritic cells (aDCs), natural killer cells (NKs), and natural killer T cells (NKTs). Negative immune regulators were defined as the collection of regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs). The “effector” cells were defined as active T cells (aCD4+T and aCD8+T) and effector memory T cells (CD4+Tem and CD8+Tem). Cytolytic activity (CYT) was used for evaluating immune activity and calculated as the geometric mean of granzyme A (GZMA) and perforin (PRF1) expression levels as previously defined (Cancer Genome Atlas Research Network, 2012 (link)). Functional enrichment analysis between groups was realized by GSVA based on gene expression data matrices.

Hu Z., Liu Z., Zheng J., Peng Y., Lu X., Li J., Tan K, & Cui H. (2023). Microsatellite instability-related prognostic risk score (MSI-pRS) defines a subset of lung squamous cell carcinoma (LUSC) patients with genomic instability and poor clinical outcome. Frontiers in Genetics, 14, 1061002.

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Publication 2023

Biological Response Modifiers Cells Dendritic Cells Effector Memory T Cells Genes Genome GZMA protein, human Malignant Neoplasms Myeloid-Derived Suppressor Cells Natural Killer Cells Natural Killer T-Cells Neoplasms Perforin Regulatory T-Lymphocytes T-Lymphocyte Transcription, Genetic

Phenotypic and Functional Analysis of NK Cells

For phenotypic analysis of NK cells, PBMCs were thawed and immediately prepared for staining. Cells were first washed with dPBS and subsequently stained with FVS eFluor 780 (Thermo Fisher Scientific, Brussels, Belgium; 1/3500 dilution in dPBS) for 20 min at RT in the dark. Afterwards, the cells were stained with different antibody panels (3 × 10⁶ PBMCs/panel) for 30 min at 4 °C in the dark. Antibody dilutions were prepared in FACS buffer (dPBS containing 1% BSA (Sigma-Aldrich) and 0.1% sodium azide (Sigma-Aldrich)). All samples were stained with CD3, CD19 and CD14 to exclude T cells, B cells and monocytes respectively (DUMP panel) and with CD7, CD56 and CD16 (NK cell panel). CD7 was included to exclude CD56⁺ myeloid-derived cells as described by Milush et al.^{59 (link)}. Additional antibodies were used for the different panels including KIR2DL1, KIR2DL2/3, KIR3DL1, CD94, NKp46 and NKG2D (NK cell receptor panel); CXCR5, CCR7 and CD62L (chemokine receptor panel); PD-1, LAG-3 and Tim3 (ICM panel); NKG2A, NKG2C, CD94 and CD57 (memory NK cell panel); and CD8 and CD30.
Polyfunctionality of NK cells was assessed by intracellular cytokine staining (ICS) using the Cyto-Fast^TM Fix/Perm buffer set (BioLegend), according to manufacturer’s protocol. The cells from the ADCC assay were harvested and subsequently stained with FVS780. Next, cells were stained with surface antibodies to identify NK cells (NK cell panel). Afterwards, cells were permeabilized using 250 µL of the CytoFast^TM Fix/Perm solution for 20 min at RT. Permeable cells were washed with CytoFast^TM Perm/Wash solution and stained for 30 min at 4 °C with antibodies against Perforin, IL-2, TNF-α, IFN-γ and MIP-1β diluted in CytoFast^TM Perm/Wash solution. Excess antibody was removed by washing with CytoFast^TM Perm/Wash solution and cells were resuspended in FACS buffer prior to acquisition on a BD LSR Fortessa (BD Biosciences, Erembodegem, Belgium). Compensation was performed using Compbeads (BD Biosciences) according to manufacturer’s protocol. Fluorescence minus one (FMO) controls were included to determine positive gates. A detailed overview of antibodies used for flow cytometry can be found in Supplementary Table 3.

Laeremans T., den Roover S., Lungu C., D’haese S., Gruters R.A., Allard S.D, & Aerts J.L. (2023). Autologous dendritic cell vaccination against HIV-1 induces changes in natural killer cell phenotype and functionality. NPJ Vaccines, 8, 29.

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Publication 2023

2'-deoxyuridylic acid Adrenocortical Carcinoma, Hereditary Antibodies B-Lymphocytes Biological Assay Buffers Cells Chemokine Receptor CXCR5 Receptors Cytokine Flow Cytometry Fluorescence HAVCR2 protein, human Immunoglobulins Interferon Type II KIR2DL1 protein, human KIR2DL2 protein, human KIR3DL1 protein, human KLRD1 protein, human Memory Monocytes Myeloid Cells Natural Killer Cells NCR1 protein, human Perforin Permeability Phenotype Progressive Encephalomyelitis with Rigidity Protoplasm Receptors, Antigen, B-Cell Receptors, Natural Killer Cell SELL protein, human Sodium Azide T-Lymphocyte Technique, Dilution Tumor Necrosis Factor-alpha

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The Cytofix/Cytoperm kit is a laboratory product designed for fixing and permeabilizing cells. It provides the necessary solutions for the preparation of samples prior to intracellular staining and flow cytometric analysis.

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The LSRFortessa is a flow cytometer designed for multiparameter analysis of cells and other particles. It features a compact design and offers a range of configurations to meet various research needs. The LSRFortessa provides high-resolution data acquisition and analysis capabilities.

Cytofix cytoperm by BD

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Cytofix/Cytoperm is a fixation and permeabilization solution developed by BD for use in flow cytometry and immunohistochemistry applications. It is designed to facilitate the intracellular staining of proteins and other cellular components while preserving cellular structure and antigenicity.

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What is perforin and what is its role in the immune system?

Perforin is a pore-forming protein that is secreted by cytotoxic T lymphocytes and natural killer cells. It plays a crucial role in the immune system's ability to eliminate virus-infected or cancerous cells. Perforin polymerizes and inserts into target cell membranes, creating pores that allow the entry of granzymes and initiate programmed cell death. Understanding the mechanisms and regulation of perforin is essential for advancing immunotherapies and treatments for immune-related disorders.

How can PubCompare.ai help with Perforin research?

PubCompare.ai allows researchers to screen protocol literature more efficiently and leverage AI to pinpoint critical insights. The platform can help researchers identify the most effective protocols related to Perforin for their specific research goals. PubCompare.ai's AI-driven analysis can highlight key differences in protocol effectiveness, enabling researchers to choose the best option for reproducibility and accuracy in their Perforin studies.

What are the common usage challenges with Perforin?

One of the main challenges with Perforin is ensuring the reproducibility and reliability of experimental protocols. Researchers need to carefully optimize various factors, such as the concentration of Perforin, the incubation time, and the target cell line, to obtain consistent and meaningful results. Additionally, understanding the different variations or types of Perforin and their specific applications can be crucial for designing effective experiments and therapies.

How can PubCompare.ai help address usage challenges with Perforin?

PubCompare.ai's AI-powered protocol comparison capabilities can greatly assist researchers in addressing usage challenges with Perforin. The platform allows users to quickly screen and identify the most reliable and effective protocols from the literature, pre-prints, and patents. By comparing key protocol details and their associated outcomes, PubCompare.ai can help researchers choose the best methods to ensure reproducibility and accuracy in their Perforin experiments. This data-driven approach can save time and enhance the quality of Perforin research.

What are the different variations or types of Perforin, and how do they differ in their applications?

Perforin comes in several different isoforms or variants, each with potentially unique characteristics and applications. For example, some variants may be more effective at pore formation in certain cell types or under specific environmental conditions. Understanding these differences can be crucial for selecting the appropriate Perforin for your research or therapeutic needs. PubCompare.ai can assist in exploring the nuances of different Perforin types and their suitability for your specific experminents.

More about "Perforin"

Perforin is a crucial player in the immune system's arsenal, enabling cytotoxic T cells and natural killer cells to eliminate virus-infected or cancerous cells.
This pore-forming protein polymerizes and inserts into target cell membranes, creating pores that allow the entry of granzymes and initiate programmed cell death.
Understanding the mechanisms and regulation of perforin is essential for advancing immunotherapies and treatments for immune-related disorders.
Perforin's role in the immune response can be further examined using various research tools and techniques.
The Cytofix/Cytoperm kit, for example, is a valuable tool for intracellular staining and flow cytometry analysis of perforin and other cytotoxic molecules.
The LSRFortessa or FACSCanto II flow cytometers can be utilized to accurately quantify perforin expression and cellular cytotoxicity.
To study perforin secretion, researchers may employ the Cytofix/Cytoperm and GolgiPlug or GolgiStop reagents, which help retain intracellular proteins like perforin for flow cytometric analysis.
Ionomycin is another useful tool, as it can stimulate perforin release from cytotoxic cells.
The FACSDiva software or FACSCalibur instrument can be employed for comprehensive flow cytometry data analysis and visualization.
By leveraging these techniques and tools, researchers can delve deeper into the mechanisms of perforin-mediated cytotoxicity, uncover novel insights, and advance the development of innovative immunotherapies and treatments for conditions involving immune system dysregulation.
The seamless integration of these methodologies with a solid understanding of perforin's biology can help optimize research workflows and enhance the reproducibility and accuracy of Perforin studies.