Image_1_Systematic pattern analyses of Vδ2+ TCRs reveal that shared “public” Vδ2+ γδ T cell clones are a consequence of rearrangement bias and a higher expansion status.pdf

BackgroundVγ9Vδ2+ T cells are a major innate T cell subset in human peripheral blood. Their Vδ2+ VDJ-rearrangements are short and simple in the fetal thymus and gradually increase in diversity and CDR3 length along with development. So-called “public” versions of Vδ2+ TCRs are shared among individuals of all ages. However, it is unclear whether such frequently occurring “public” Vγ9Vδ2+ T cell clones are derived from the fetal thymus and whether they are fitter to proliferate and persist than infrequent “private” clones.MethodsShared “public” Vδ2+ TCRs were identified from Vδ2+ TCR-repertoires collected from 89 individuals, including newborns (cord blood), infants, and adults (peripheral blood). Distance matrices of Vδ2+ CDR3 were generated by TCRdist3 and then embedded into a UMAP for visualizing the heterogeneity of Vδ2+ TCRs.ResultsVδ2+ CDR3 distance matrix embedded by UMAP revealed that the heterogeneity of Vδ2+ TCRs is primarily determined by the J-usage and CDR3aa length, while age or publicity-specific motifs were not found. The most prevalent public Vδ2+ TCRs showed germline-like rearrangement with low N-insertions. Age-related features were also identified. Public Vδ2+TRDJ1 TCRs from cord blood showed higher N-insertions and longer CDR3 lengths. Synonymous codons resulting from VDJ rearrangement also contribute to the generation of public Vδ2+ TCRs. Each public TCR was always produced by multiple different transcripts, even with different D gene usage, and the publicity of Vδ2+ TCRs was positively associated with expansion status.ConclusionTo conclude, the heterogeneity of Vδ2+ TCRs is mainly determined by TRDJ-usage and the length of CDR3aa sequences. Public Vδ2+ TCRs result from germline-like rearrangement and synonymous codons, associated with a higher expansion status.</p

Table_1_Systematic pattern analyses of Vδ2+ TCRs reveal that shared “public” Vδ2+ γδ T cell clones are a consequence of rearrangement bias and a higher expansion status.xlsx

BackgroundVγ9Vδ2+ T cells are a major innate T cell subset in human peripheral blood. Their Vδ2+ VDJ-rearrangements are short and simple in the fetal thymus and gradually increase in diversity and CDR3 length along with development. So-called “public” versions of Vδ2+ TCRs are shared among individuals of all ages. However, it is unclear whether such frequently occurring “public” Vγ9Vδ2+ T cell clones are derived from the fetal thymus and whether they are fitter to proliferate and persist than infrequent “private” clones.MethodsShared “public” Vδ2+ TCRs were identified from Vδ2+ TCR-repertoires collected from 89 individuals, including newborns (cord blood), infants, and adults (peripheral blood). Distance matrices of Vδ2+ CDR3 were generated by TCRdist3 and then embedded into a UMAP for visualizing the heterogeneity of Vδ2+ TCRs.ResultsVδ2+ CDR3 distance matrix embedded by UMAP revealed that the heterogeneity of Vδ2+ TCRs is primarily determined by the J-usage and CDR3aa length, while age or publicity-specific motifs were not found. The most prevalent public Vδ2+ TCRs showed germline-like rearrangement with low N-insertions. Age-related features were also identified. Public Vδ2+TRDJ1 TCRs from cord blood showed higher N-insertions and longer CDR3 lengths. Synonymous codons resulting from VDJ rearrangement also contribute to the generation of public Vδ2+ TCRs. Each public TCR was always produced by multiple different transcripts, even with different D gene usage, and the publicity of Vδ2+ TCRs was positively associated with expansion status.ConclusionTo conclude, the heterogeneity of Vδ2+ TCRs is mainly determined by TRDJ-usage and the length of CDR3aa sequences. Public Vδ2+ TCRs result from germline-like rearrangement and synonymous codons, associated with a higher expansion status.</p

DataSheet_1_Performance comparison of TCR-pMHC prediction tools reveals a strong data dependency.pdf

The interaction of T-cell receptors with peptide-major histocompatibility complex molecules (TCR-pMHC) plays a crucial role in adaptive immune responses. Currently there are various models aiming at predicting TCR-pMHC binding, while a standard dataset and procedure to compare the performance of these approaches is still missing. In this work we provide a general method for data collection, preprocessing, splitting and generation of negative examples, as well as comprehensive datasets to compare TCR-pMHC prediction models. We collected, harmonized, and merged all the major publicly available TCR-pMHC binding data and compared the performance of five state-of-the-art deep learning models (TITAN, NetTCR-2.0, ERGO, DLpTCR and ImRex) using this data. Our performance evaluation focuses on two scenarios: 1) different splitting methods for generating training and testing data to assess model generalization and 2) different data versions that vary in size and peptide imbalance to assess model robustness. Our results indicate that the five contemporary models do not generalize to peptides that have not been in the training set. We can also show that model performance is strongly dependent on the data balance and size, which indicates a relatively low model robustness. These results suggest that TCR-pMHC binding prediction remains highly challenging and requires further high quality data and novel algorithmic approaches.</p

γδ NKT cells fill empty iNKT liver niches in miR-181a/b-1 deficient mice.

<p>FACS analysis of liver lymphocytes of miR-181a/b-1^–/–x TcrdH2BeGFP mice (–/–) compared to TcrdH2BeGFP and miR-181a/b-1^+/–x TcrdH2BeGFP controls (here referred to as ctrl.). (A + B) Analysis of αβ and γδ NKT cells in miR181a/b-1 deficient mice compared to controls. (A) Representative contour plots illustrating the gating strategy for the indicated cell populations in (B). (B) Scatter plot shows frequencies of the indicated cell populations among lymphocytes after doublets were excluded, gated as depicted in (A), pooled data from three independent experiments with each 3–4 mice per group, mean. (C) Bar graph shows total γδ NKT cell numbers, pooled data from 3 independent experiments, each n = 3–4 mice per group, mean + SD. (D) Flow cytometric analysis of 1:1 mixed bone marrow chimeras. Scatter plot shows ratios of miR-181a/b-1^–/–(KO) and miR-181a/b-1 sufficient wild type (WT) donor cells among all lymphocytes, αβ vNKT, αβ iNKT and γδ NKT lymphocytes, respectively, pooled data from two independent experiments with each 4 mice per group, harmonic mean. (E) Scatter plot shows frequencies of INFγ⁺ cells among γδ T cells, pooled data from three independent experiments with each 2–5 mice per group, mean. (F) Vγ usage of liver γδ T cells (gated on Tcrβ^–GFP^hi cells). Bar graph shows pooled data from five experiments with 3–6 mice per group, mean + SD. (G) Analysis of liver Vγ1⁺Vδ6.3⁺ γδ T cells. Scatter plot shows frequencies of Vγ1⁺Vδ6.3⁺ cells among γδ T cells, pooled data from five independent experiments with each 2–5 mice per group, mean. Statistical analyses were performed using the Mann-Whitney test.</p

Unchanged peripheral lymph node γδ T cell compartment in the absence of miR-181a/b-1.

<p>FACS analysis of γδ T cells in pLN of miR-181a/b-1^–/–x TcrdH2BeGFP mice (–/–) compared to miR-181a/b-1 sufficient controls, TcrdH2BeGFP and miR-181a/b-1^+/–x TcrdH2BeGFP mice (here referred to as ctrl.). (A) Total γδ T cells numbers in pLN of the indicated phenotypes. Scatter plot shows pooled data from five independent experiment with n = 2–5 mice per group, mean. (B) Scatter plot shows absolute numbers of NK1.1⁺ γδ T cells, pooled data from five independent experiments with each 2–5 mice per group, mean. (C) Vγ usage of γδ T cells (gated on Tcrβ^–GFP^hi cells). Bar graph shows pooled data from 5 experiments with 3–6 mice per group, mean + SD. (D + E) Intracellular cytokine staining for IFN-γ and IL-17A gated on γδ T cells. (D) Representative contour plots of two independent experiments with similar outcome, with each n = 2–5 mice per group. Numbers indicate mean +/–SD from pooled data. (E) Bar gaph shows pooled data from the two independent experiments, mean + SD. Statistical analyses were performed using the Mann-Whitney test.</p

Thymic γδ T cells in the absence of miR-181a/b-1.

<p>(A) Expression analysis of miR-181a in FACS-sorted thymocytes pooled from 5 adult or 8 neonatal TcrdH2BeGFP mice. Expression levels of the indicated cell populations were analyzed by quantitative RT-PCR and normalized to snoRNA 412. Error bars show range of relative expression levels from triplicates. (B) Bar graph shows absolute γδ T cell numbers in miR-181a/b-1^–/–x TcrdH2BeGFP mice (–/–) compared to TcrdH2BeGFP and miR-181a/b-1^+/–x TcrdH2BeGFP controls (ctrl.), pooled data from five independent experiments with each 2–5 mice per group, mean + SD. (C) Expression analysis of miR-181d in FACS-sorted thymocytes pooled from 5 miR-181a/b-1^–/–x TcrdH2BeGFP mice (–/–) and TcrdH2BeGFP controls (ctrl.). One representative experiment of two independent experiments that gave similar results. Expression levels of the indicated cell populations were analyzed by quantitative RT-PCR and normalized to snoRNA 412. Error bars show range of relative expression levels from triplicates. (D–I) FACS analysis of thymic γδ T cells in–/–mice compared to ctrl mice (D, F-I) and mixed bone marrow chimeras (E). (D) Vγ usage of thymic γδ T cells (gated on Tcrβ^–GFP^hi cells). Scatter plot shows pooled data from five experiments with 3–6 mice per group, one dot represents one mouse, mean. (E) Flow cytometric analysis of 1:1 mixed bone marrow chimeras. Scatter plot shows ratios of miR-181a/b-1^–/–(KO) and miR-181a/b-1 sufficient wild type (WT) donor Vγ1⁺ and Vγ4⁺ cells among all lymphocytes, respectively. Data are pooled from two independent experiments with each 3 mice per group, harmonic mean. (F) Scatter plot shows absolute numbers of NK1.1⁺ cells, pooled data from five independent experiments with each 2–5 mice per group. (G) Scatter plot shows absolute numbers of NK1.1⁺ γδ T cells, pooled data from five independent experiments with each 2–5 mice per group. (H) Representative contour plots of cluster B (CD44^hiCD24^–) and cluster A (CD44^–/loCD24⁺) γδ thymocytes (gated on Tcrβ^–GFP^hi cells), numbers indicate mean +/–SD of pooled data from four independent experiments with each 2–5 mice per group. (I) Representative contour plots of CCR6⁺ and NK1.1⁺ cluster B cells, numbers indicate mean +/–SD of pooled data from four independent experiments with each 2–6 mice per group. Statistical analyses were performed using the Mann-Whitney test.</p

Vitamin A deficiency of recipient mice leads to increased Th1 cells and decreased FoxP3⁺ Treg cells during GvHD.

<p>STD or VAD recipient mice were analyzed for CD4⁺ T cell polarization status in SPL, mLN, liver and small intestine (SI) at day 21 after transplantation. (<b>A</b>) Each bar represents the percentage of FoxP3⁺ CD4⁺ T cells of CD4⁺ T cells isolated from the indicated organ. (<b>B</b>) Each bar represents the percentage of IFN-γ⁺ CD4⁺ T cells of CD4⁺ T cells isolated from the indicated organ.</p

Homing of allo-primed T cells to the intestine is dependent on dietary vitamin A.

<p>2×10⁷ splenocytes (C57BL/6) were transferred into lethally irradiated STD or VAD BALB/c recipients. Three days after transfer donor T cells from mesenteric lymph nodes of STD or VAD BALB/c mice were harvested and then split and differentially labeled with either TAMRA or CFSE. CFSE-labeled cells from STD recipients were mixed with TAMRA-labeled cells from VAD-recipients at a 1∶1 ratio. In cross-labeling experiments, TAMRA-labeled cells from STD-recipients and CFSE-labeled cells from VAD-recipients were used. Mixtures of 5×10⁶ T cells per mouse in total were injected into the tail vein of untreated wt C57BL/6 recipient mice. Eighteen hours after transfer recipient mice were sacrificed and the homing of CD4⁺ and CD8⁺ T cells was analyzed by flow cytometry. The ratio of transferred T cells primed in allogeneic VAD versus STD recipients was analyzed in pLN (pooled per mouse), SPL, mLN, liver, IEL and LPL. Labeling effects were excluded by normalizing the ratio to 1∶1 in each staining group. N = 6/group. Data are combined from two independent experiments.</p

γδ NKT cells replenish empty niches of missing liver αβ iNKT cells independent of TCR specificity for CD1d.

<p>FACS analysis of liver lymphocytes stained for CD1d/PBS-57 tetramer (CD1d tet) binding. Contour plots show representative CD1d tet binding versus γδ-GFP reporter fluorescence from two independent experiments, with each involving 3 mice per group of miR-181a/b-1 deficient (–/–) and miR-181a/b-1 sufficient (ctrl.) mice.</p

Dendritic epidermal T cells develop in the absence of miR-181a/b-1.

<p>(A) Analysis of Vγ5⁺ γδ T cells in the skin of miR-181a/b-1^–/–x TcrdH2BeGFP mice (–/–) compared to TcrdH2BeGFP mice (ctrl.). (left) Representative contour plots illustrating the gating for Vγ5⁺ γδ T cells. (right) Scatter plot shows frequencies of Vγ5⁺ γδ T cells, pooled data from two independent experiments with each n = 3 mice per group, mean. (B) Histological analysis of epidermal sheets from ears of miR-181a/b-1^–/–x TcrdH2BeGFP mice (–/–) compared to TcrdH2BeGFP mice (ctrl.). Epidermal sheets were stained for DETCs (yellow, overlay red and green) with CD3 (red) and TcrdGFP⁺ (green) cells indicate γδ T cells. Original magnification: 20x, scale bars: 20μm.</p