Dataset Information

Proteomic Analysis for Cul5 E3 Ligase Complex as a Key Negative Feedback Regulator of TCR/Il2 Signaling and Anti-Tumor Activity in Cd8+ T Cells

ABSTRACT: To investigate the mechanism by which Cul5 regulates CD8+ T cell cytokine-dependent differentiation and TCR-dependent activation, we performed quantitative mass spectrometry (MS) by data-independent acquisition (DIA)-MS of total proteins in the Cul5 KO and NC primary CD8+ T cells in the following conditions: 1) Cytokine dependent expansion and differentiation (T0); 2) 8 hours cytokine withdraw prior to TCR stimulation (T8); and 3) 16 hours TCR stimulation post 8-hour cytokine withdraw (T16). Principal component analysis (PCA) and correlation analysis revealed that replicates in each condition clustered together while different conditions separated from each other, suggesting significant proteomic changes among different conditions of the same T cells as well as between Cul5 KO and NC T cells in each condition. Together with similar total protein quantities among all detected samples, DIA-MS analyses were of high quality. Additionally, the strong reductions of Cul5 abundances in the Cul5 KO cells from all three conditions compared to the NC cells confirms high KO efficiency. Of note, the proteomic analysis showed that the Cul5 protein level was significantly increased upon TCR stimulation post cytokine starvation in the NC cells, suggesting a potential negative feedback regulatory role of Cul5 in CD8+ T cell activation. Consistent with this idea, we observed more markedly upregulation of Cul5 expression upon of TCR stimulation of na•ve primary CD8+ cells. To identify Cul5 interacting proteins in CD8+ T cells, we overexpressed Cul5 with a C terminal HA-tag (Cul5-HA) in mouse primary CD8+ T cells by retroviral transduction. The cells were subjected to TCR stimulation for 12 hr, and Cul5-HA was immunoprecipitated by anti-HA, followed by DIA-MS analysis (co-IP-MS). Compared to the negative control samples (cells transduced with the empty vector), 65 proteins were enriched (p value <0.05 and fold change >1.5) in the anti-HA IP samples. Altogether, we report that Cul5 KO alters CD8+ T cell proteome and the Cul5 interactome.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Spleen, T Cell

SUBMITTER: Wenxue Li

LAB HEAD: Yansheng Liu

PROVIDER: PXD036793 | Pride | 2024-01-03

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	20220314_WuLab_ko_0_1.raw	Raw
	20220314_WuLab_ko_0_2.raw	Raw
	20220314_WuLab_ko_0_3_rep.raw	Raw
	20220314_WuLab_ko_16_1.raw	Raw
	20220314_WuLab_ko_16_2.raw	Raw

Items per page:

1 - 5 of 36

Similar Datasets

Project description:Gene expression profiling of human CD8+ CD161hi and CD161lo central and effector memory and naïve T cell subsets. The mechanisms by which IL-17 secreting cells are regulated have not been completely elucidated. We previously identified a population of rhodamine-effluxing memory CD8+ T cells with high expression of CD161 that contributes to immune reconstitution after lymphopenia-inducing chemotherapy. Here we find that CD161hi CD8+ T cells share transcriptional programming with Th17 cells, but most do not secrete IL-17 or proliferate to stimulation through the T cell receptor (TCR). Transcriptional analysis of subsets identified by expression of CD161 and CD62L revealed a novel mechanism of TCR signaling pathway regulation in CD161hi CD8+ T cells that is distinct from that described in anergic or tolerant cells and renders them functionally dependent on costimulation through innate cytokine receptors or CD28. CD161hi CD8+ T cells, induced to proliferate by a TCR signal delivered with costimulation, demonstrated plasticity that was dependent on the nature of costimulation and resulted in expansion of IL-17 secreting cells that could not proliferate to a TCR signal alone or differentiation to Tc1-like cells that proliferated to TCR stimulation in the absence of costimulation. The data show an association between TCR signaling pathway downregulation and type 17 programming in CD161hi CD8+ T cells, whose dysregulation could mediate IL-17 dependent inflammatory diseases. T cell subsets were sort-purified from healthy adults and analyzed by gene expression profiling. Isolation: Effluxing CD161hi and non-effluxing CD161lo CD8+ TCM and TEM subsets were purified using magnetic bead separation and cell sorting to achieve >98% purity, as previously described (35). CD8+ T cells were positively selected using CD8 Microbeads (Miltenyi Biotec, Germany), loaded with Rh123 (Sigma, St. Louis, MO) and cultured for 30 min to allow Rh123 efflux, then labeled with fluorochrome-conjugated antibodies to CD4, CD16, TCRγδ, Vα24, CD8, CD95, CD62L and CD161. CD161hi and CD161lo TCM and TEM subsets were sort-purified on a FACS ARIA equipped with 405 nm, 488 nm and 633 nm lasers (BD Biosciences). CD161hi TCM and TEM subsets were identified as CD62L+/Rh123lo/CD161hi and CD62L-/Rh123lo/CD161hi events, respectively, in the CD4-/CD16-/TcRγδ-/Vα24-/CD8+/CD95+ population. CD161lo TCM and TEM subsets were identified as CD62L+/Rh123hi/CD161int/neg and CD62L-/Rh123hi/CD161int/neg events, respectively, in the CD4-/CD16-/TcRγδ-/Vα24-/CD8+/CD95+ population. Gene expression profiling: RNA was extracted from sort-purified subsets from 6 healthy individuals using the RNeasy Plus Minikit (Qiagen, Valencia, CA) and biotinylated, followed by generation of amplified cRNA for array hybridization using the Illumina TotalPrep RNA Amplification Kit (Applied Biosystems, Foster City, CA). Amplified biotinylated cRNA was then purified before quality control to ensure high quality cRNA was available for hybridization. Labeled cRNA was hybridized to Illumina WG-6 Expression BeadChips v3.0 (Illumina, San Diego, CA), which quantitate expression of 48,802 transcripts derived from the NCBI RefSeq (Build 36.2, Release 22) and UniGene databases (Build 199). BeadChips were washed before reading and image extraction, and then scanned on an Illumina BeadArray Reader. The resulting TIFF images were processed using GenomeStudio Gene Expression Module (GEM) software. Data quality was assessed using the Control Summary feature in GenomeStudio GEM. For a given analysis set, a GenomeStudio Probe-level Final Report was generated by combining the Sample Probe Profile and Control Probe Profile tables. The Final Report comprising the full dataset was initially processed using the Bioconductor package lumi by employing a background correction estimate and quantile normalization. A small adjustment (i.e. 20 counts) was made to the entire dataset to make all intensity signals non-negative and these values were log2-transformed. The dataset was initially filtered using the ‘shorth’ function of the Bioconductor package genefilter, resulting in retention of 31,084 of 48,802 original probes. Each pairwise comparison was further filtered by discarding probes whose signal intensity was less than a defined signal “noise floor” across all arrays in the data subset. This was achieved by calculating the median of the ‘negative control’ probe signals for each array, averaging these values, and setting the noise floor as 3 times this average. Differential gene expression was then determined using the Bioconductor package limma, and a false discovery rate (FDR) method applied to correct for multiple testing. Significant differential gene expression was defined by a log2 ratio > 0.585 (± 1.5-fold) and FDR (adjusted p value) < 0.05.

Project description:The goal of this study was to examine differences in gene expression of tumor specific CD8 T cells in an in vivo tumor mouse model after inhibition of galectin-3 protein expression by genetic knockout. Galectin-3 is thought to modulate CD8 T cell response by cross-linking cell surface glycoproteins Galectin-3 is a 31 kD carbohydrate-binding lectin that is over-expressed by many human malignancies. It also modulates T cell responses through a diverse array of mechanisms including induction of apoptosis, TCR cross linking in CD8+ T cells, and T cell receptor (TCR) down regulation in CD4+ T cells. We found that patients responding to a granulocyte-macrophage colony-stimulating factor (GM-CSF) secreting allogeneic pancreatic tumor vaccine developed post immunization antibody responses to galectin-3 on a proteomic screen. We used the HER-2/neu (neu-N) transgenic mouse model to study galectin-3 binding on adoptively transferred high avidity neu-specific CD8+ T cells derived from TCR transgenic mice. Here, we show that galectin-3 binds preferentially to activated antigen-committed CD8+ T cells only in the tumor microenvironment (TME). Galectin-3 deficient mice exhibit improved CD8+ T cell effector function and increased expression of several inflammatory genes when compared with wild type (WT) mice. We also show that galectin-3 binds to LAG-3, and LAG-3 expression is necessary for galectin-3 mediated suppression of CD8+ T cells in vitro. Lastly, galectin-3 deficient mice have significantly elevated levels of circulating plasmacytoid dendritic cells (pDCs), which are superior to conventional dendritic cells (cDCs) in activating CD8+ T cells. Binding of galectin-3 to cell-surface glycoproteins on immune cells suppresses a pro-inflammatory immune response. Thus, inhibiting galectin-3 in conjunction with CD8+ T cell directed immunotherapies should enhance the tumor specific immune response. 3 different experimental groups were studied. Galectin-3 WT CD8 T cells adoptively transferred into Galectin-3 WT mice, galectin-3 WT CD8 T cells transferred into galectin-3 KO mice, and finally galectin-3 KO CD8 T cells transferred into galectin-3 KO mice. Galectin-3 WT CD8 T cells transferred into Galectin-3 WT mice were used as the reference group. Four biological replicates were submitted for each group, and adoptively transfered CD8 T cells were isolated 5 days post-adoptive transfer into tumor-bearing mice treated with a whole cell GM-CSF secreting vaccine. Cells were purified by cell sorting on the Thy1.2 surface marker.

Project description:Though T cell expansion and effector differentiation are triggered and, perhaps, maintained by antigen, the proliferative behaviors of CD4+ and CD8+ T cells responding to timed antigen presentation have rarely been compared side by side. Proliferation and effector differentiation of TCR transgenic and polyclonal T cells were analyzed following transient and continuous TCR signals. We found CD4+ T cell proliferation to be dependent on prolonged antigen presence, whereas CD8+ T cells were able to divide and differentiate into effector cells in the absence of it. We excluded CD4+ T cell proliferation to be abrogated by coinhibitory signals or the lack of inflammatory stimuli and found that autonomous proliferation of CD8* T cells was independent of any MHC class I signals. Gene expression analyses illustrated differences in global gene transcription between the two subsets following stimulation periods of different lengths. These T cell data reflect the MHC class difference in that class II but not class I molecules were stabilized on activated DCs in vivo, suggesting a coevolution of MHC molecules and their respective T cell subsets. Samples 1-12: Analysis on day 2. Purified CD4+ AND-TCR transgenic cells andÂ CD8+ OT1-TCR transgenic cells were separately stimulated with anti-CD3 and anti-CD28 antibodies. 48 hours later, the cells were sorted again to a purity of >99 %. Extracted total RNA was amplified twice and hybridized on Affymetrix Mouse 430A2 microarrays. First, we analysed the changes of the CD4+ and CD8+ T cells after stimulation. Second, we compared the differences of the changes between the two cell types after stimulation. For each of the four groups (CD4+ and CD8+, stimulated and unstimulated), we analysed three independent biological replicates. Samples 13-28: Analysis on day 5. AND and OT1 TCR-transgenic T cells were prepared as described before, but transferred into mice that do not or do present their respective antigens. 72 hours later, the cells were FACS-sorted twice to >99 % purity, directly into Trizol. For each of the six groups (CD4+ and CD8+, unstimulated, transient (2 days) and continuous (5 days) stimulation), three independent biological replicates were analyzed, except for CD4+ unstimulated and CD4+ transient, with two replicates each.

Dataset Information

Proteomic Analysis for Cul5 E3 Ligase Complex as a Key Negative Feedback Regulator of TCR/Il2 Signaling and Anti-Tumor Activity in Cd8+ T Cells

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets