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.

Project description:Activation of peripheral T lymphocytes in the absence of pathogen induced inflammation or costimulatory signals results in tolerance. Two different tolerance mechanisms have been described, deletion and anergy. We recently demonstrated that an important variable which is responsible for the decision between anergy and deletion for CD8 T cells is the strength of signaling through the T cell receptor(Redmond and Sherman, Immunity 22:275,2005). However, it is not know what the downstream signals are that result in death(deletion) vs. survival(anergy)of the activated cells. Marth and co-workers have previously shown that CD8 T cell apoptosis under conditions similar to those that occur during tolerance in vivo may involve a change in protein glycosylation (Van Dyken et.al., Mol.Cell.Bio.27:1096,2007).In order to assess the role of protein glycosylation in the decision between deletion vs.anergy in immune tolerance, we have prepared purified TCR transgenic CD8 T cells stimulated in vivo using a strong antigenic signal (anergy conditions) or a weak antigenic signal (deletion conditions) with cognate antigen. We wish to assess transcriptional differences in genes involved in protein glycosylation in these 2 cell populations. The control population will be naive trangenic CD8 cells. Dr. Sherman's lab aims to assess the role of protein glycosylation in the decision between deletion vs. anergy in immune tolerance, they have prepared purified TCR transgenic CD8 T cells stimulated in vivo using a strong antigenic signal (anergy conditions) or a weak antigenic signal (deletion conditions) with cognate antigen. Dr. Sherman's lab wishes to assess transcriptional differences in genes involved in protein glycosylation in these 2 cell populations. Then control population will be naïve transgenic CD8 cells. RNA preparations of mouse CD8 T cells from the B10D2 strain with three different conditions (Naïve, Deleted, and Anergic) were sent to the Microarray Core (E). The RNA was amplified, labeled, and hybridized to both the GLYCOv3 and Mouse 430A_2.0 microarrays.

Project description:Activation of peripheral T lymphocytes in the absence of pathogen induced inflammation or costimulatory signals results in tolerance. Two different tolerance mechanisms have been described, deletion and anergy. We recently demonstrated that an important variable which is responsible for the decision between anergy and deletion for CD8 T cells is the strength of signaling through the T cell receptor(Redmond and Sherman, Immunity 22:275,2005). However, it is not know what the downstream signals are that result in death(deletion) vs. survival(anergy)of the activated cells. Marth and co-workers have previously shown that CD8 T cell apoptosis under conditions similar to those that occur during tolerance in vivo may involve a change in protein glycosylation (Van Dyken et.al., Mol.Cell.Bio.27:1096,2007).In order to assess the role of protein glycosylation in the decision between deletion vs. anergy in immune tolerance, we have prepared purified TCR transgenic CD8 T cells stimulated in vivo using a strong antigenic signal (anergy conditions) or a weak antigenic signal (deletion conditions) with cognate antigen. We wish to assess transcriptional differences in genes involved in protein glycosylation in these 2 cell populations. The control population will be naive trangenic CD8 cells. Dr. Sherman's lab aims to assess the role of protein glycosylation in the decision between deletion vs. anergy in immune tolerance, they have prepared purified TCR transgenic CD8 T cells stimulated in vivo using a strong antigenic signal (anergy conditions) or a weak antigenic signal (deletion conditions) with cognate antigen. Dr. Sherman's lab wishes to assess transcriptional differences in genes involved in protein glycosylation in these 2 cell populations. Then control population will be naïve transgenic CD8 cells. RNA preparations of mouse CD8 T cells from the B10D2 strain with three different conditions (Naïve, Deleted, and Anergic) were sent to the Microarray Core (E). The RNA was amplified, labeled, and hybridized to the GLYCOv4 microarrays.

Project description:Activation of peripheral T lymphocytes in the absence of pathogen induced inflammation or costimulatory signals results in tolerance. Two different tolerance mechanisms have been described, deletion and anergy. We recently demonstrated that an important variable which is responsible for the decision between anergy and deletion for CD8 T cells is the strength of signaling through the T cell receptor(Redmond and Sherman, Immunity 22:275,2005). However, it is not know what the downstream signals are that result in death(deletion) vs. survival(anergy)of the activated cells. Here we analysze additional conditions: 1) Wild Type mice were injected injected only once with a strain of vaccinia virus that express hemagglutinin from influenza; 2) BIM KO Clone 4 transgenic T cells were transferred into B10D2 mice then injected daily for 3 days with 1ug of KdHA peptide and sorted by flow cytometry according to their expression of CD8 and thy1.1; 3) Mice injected with 1 ug (deleted condition) of influenza hemaglutinin antigen (HA), 24 hours post injection CD8 T CL4 cells were sorted by flow cytometry (FacsARIA) and 4) WildType mice injected with 100 ug (anergic condition) of influenza hemaglutinin antigen (HA), 24 hours post injection CD8 T CL4 cells were sorted by flow cytometry (FacsARIA). Dr. Sherman's lab aims to assess the role of protein glycosylation in the decision between deletion vs. anergy in immune tolerance, they have prepared purified TCR transgenic CD8 T cells stimulated in vivo using a strong antigenic signal (anergy conditions) or a weak antigenic signal (deletion conditions) with cognate antigen. Dr. Sherman's lab wishes to assess transcriptional differences in genes involved in protein glycosylation in these 2 cell populations. Then control population will be naïve transgenic CD8 cells. RNA preparations of mouse CD8 T cells from the B10D2 strain with three different conditions (Naïve, Deleted, and Anergic) were sent to the Microarray Core (E). The RNA was amplified, labeled, and hybridized to the GLYCOv4 microarrays.

Project description:Purpose: To identify potential underlying molecular programs associated with the observed dysfunctional TCRTg101 phenotype, RNA sequencing (seq) was performed on TCRTg101 isolated from livers of leukemia-bearing mice at several time points following their adoptive transfer (days 6-7, 13-14, and 167-18), andas well as on TCRTg101 isolated from control (leukemia-free) analysis Methods: TCRTg101 in livers and spleens of leukemia-bearing mice were isolated at various time points following adoptive transfer (day 0, day 6-7, day 13-14, day 16-18) by FACS and were re-suspended in Trizol (Life Technologies). TCRTg101 RNA was isolated via chloroform extraction. Low input RNA sequencing was performed in the University of Chicago Genomic. Genes with fewer than 10 reads in at least 6 samples were filtered out, resulting in a dataset of 11,164 genes. Differential gene expression analysis was performed on raw aligned read counts using DESeq2 (Love et al., 2014), with batch effects accounted for in the design formula. Genes were considered to be differentially expressed if they had an adjusted p-value < 0.05 using a Benjamini-Hochberg test (FDR). Counts per gene were regular log (rlog)-transformed, and batch effects were removed using the removeBatchEffect function from limma (Ritchie et al., 2015) for principal component analysis (PCA), sample clustering based on Euclidean distance, and heatmaps depicting z-scores of gene expression. rlog-transformed, batch-corrected counts were also used for weighted gene correlation network analysis (WGCNA) (Langfelder and Horvath, 2008) while additionally filtering out the 50% of genes with the lowest variance to reduce noise, resulting in a set of 5,582 genes. Adjacency was determined using a signed analysis and a soft thresholding power of 14, which was determined by scale-free fit index (Zhang and Horvath, 2005). 12 clusters of genes were initially identified, 2 of which contained a combined 4,269 genes (76.5% of the dataset), and roughly corresponded to genes whose expression increased or decreased over the experimental time course. Of the other 10 clusters, 2 were identified as containing genes which were transiently upregulated or downregulated. These two clusters contained 448 genes, combined. The remaining 865 genes were assigned to eight different clusters, which appeared to be the result of high variance within sample groups, either due to low overall gene expression or low outlier values. No conclusions were drawn regarding these clusters due to uncertainty in the data. Core Facility on the Illumina HiSeq 2500 platform in two batches. Reads were mapped onto the University of California Santa Cruz mouse genome using kallisto (Bray et al., 2016) Results: In total, 4,075 genes were found to be significantly differentially expressed across all pairwise comparisons Conclusion:Dysfunctional TCRTg101 acquire a transcriptional program canonically associated with T cell exhaustion

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Leukemia antigen specific TCR transgenic CD8+ T cell TCRTg101 RNA seq

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