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We previously demonstrated a central role for HLA genes in determining the T-cell receptor (TCR) repertoire. However, these studies also suggested that other genetic factors might also play a role in the development of this repertoire. In order to assess the role of non-HLA genes in the development of the TCR repertoire, we have analysed and compared the TCR repertoires of individuals in three families consisting of both monozygotic twins as well as an HLA-identical sib. TCR repertoire analysis was performed with both V-segment-specific MoAb and the polymerase chain reaction using TCRBV segment-specific oligonucleotide primers. We observed that in every case the TCR repertoires of identical twins were more similar to each other than to their HLA-identical sib. Furthermore, in one family we were able to show by genotype analysis that most of the differences in repertoire between the identical twins and their HLA-identical sib were caused by polymorphisms in the TCR genes that influence expression levels. These studies document an important role for non-HLA genes in determining the TCR repertoire in man and raise the possibility that such TCR polymorphisms may play a signiflcant role in determining disease susceptibility.

CMV Reactivation Rather Than Persistent Alloantigen Drives a Specific Cross-Reactive T Cell Receptor Repertoire O. Nguyen, K. Kedzierska, N. Bird, G.P. Westall, T.C. Kotsimbos, N.A. Mifsud. Medicine, Monash University, Melbourne, VIC, Australia; Allergy, Immunology and Respiratory Medicine, The Alfred Hospital, Melbourne, VIC, Australia; Microbiology and Immunology, The University of Melbourne, Parkville, VIC, Australia.

Thymic organ cultures are currently the only system capable of supporting a full programme of T-cell development in vitro. Unmanipulated thymus lobes are useful for studying some aspects of T-cell development but are limited for studies on interactions between thymocytes and stromal cells by their cellular heterogeneity. However, techniques have now been developed for the association of defined stromal and lymphoid populations in organ culture where optimal conditions for the interaction are maintained. This approach is now being applied to study the role of individual stromal cell types in T-cell development and selection of the T cell receptor repertoire.

Analysis of the αβ T cell receptor (TCR) repertoire in patients with myelodysplastic syndrome (MDS) using the technique of TCR β chain spectratyping has provided valuable insights into the pathophysiology of cytopenias in a subset of patients. TCR β chain spectratypes represent complex datasets, however, and statistical tools for their comprehensive analysis are limited. To enable global comparison of spectratype data from different individuals, we developed a robust statistical method based on k-means clustering analysis, and applied this method to analysis of the αβ TCR repertoires in the peripheral blood of 50 MDS patients and 23 age-matched healthy controls. From each of the 23 CDR3 length distributions (one for each of 23 Vβ families) comprising each spectratype, 4 features were extracted: the number of peaks in the distribution, the relative height of the largest peak, the skewness of the distribution, and the kurtosis. K-means clustering was applied at the Vβ family level to the extracted feature data from the CDR3 length distributions across the 73 subjects. This analysis typically identified two distinct clusters: a “normal” cluster characterized by a higher number of peaks, lower maximum relative height, lower skewness, and lower kurtosis, and a second “abnormal” cluster with the opposite characteristics. Thus, each CDR3 length distribution was classified as normal or abnormal according to its assignment to one of these two clusters. The mean number of abnormal CDR3 length distributions per individual was 1.6 (range, 0 to 5) for the age-matched controls and 3.7 (range, 1 to 18) (p=0.03) for the MDS patients. K-means clustering was also applied at the individual level to composite datasets consisting of the four features extracted from each of the 23 CRD3 length distributions in each individual’s spectratype. This higher-level clustering again generated 2 clusters. The “normal” cluster contained all of the age-matched control subjects as well as 39 MDS patients, while the “abnormal” cluster contained the remaining 11 MDS patients, all of whom had profoundly abnormal TCR Vβ spectratypes. The median age in the abnormal group was higher than in the normal group, 67 versus 61 years, respectively (p=0.031). When the individuals in the two groups were analyzed according to the IPSS and WHO classification systems, 82% of patients in the abnormal group had high-risk disease (IPSS int-2 and high), compared with only 45% in the normal group (p=0.03), and 73% of patients in the abnormal group had advanced disease by WHO classification (>5% blasts), as opposed to 41% in the normal group (p=0.027). The 11 MDS patients in the abnormal cluster also had a higher median expression level of the Wilms’ tumor-1 (WT1) gene, as determined by quantitative RT-PCR, in the peripheral blood (0.034 versus 0.0062, p=0.047), and a higher median bone marrow blast count (10% versus 2%, p=0.056). The two groups of MDS patients were evaluated for potential differences in three variables that could potentially confound the analysis of TCR Vβ spectratyping: peripheral blood lymphopenia, active infection, and a history of transfusion. The median peripheral blood lymphocyte count (1310 × 103/ml versus 1410 × 103/ml, respectively; p=0.37), a history of transfusion (70% versus 70%), and the incidence of MDS-related infection (27% versus 21%, respectively, p=0.69), as defined by a viral, fungal or bacterial infection identified after the diagnosis of MDS but before sample acquisition, were also not significantly different between the normal and abnormal groups. In order to evaluate the stability of spectratypes over time and during therapy, serial Vβ spectratyping analysis of bone marrow mononuclear cells was performed in 4 patients before and after treatment with azacytidine and etanercept. In all 4 cases, the spectratypes remained stably abnormal over months of observation, during which time 2 patients achieved complete and 2 achieved partial remissions of their disease. In conclusion, we have developed a new statistical algorithm for spectratyping analysis that enabled the identification of a group of MDS patients with high-risk disease and highly abnormal αβ TCR repertoires. These findings further highlight the biological and clinical heterogeneity of MDS and provide the rationale for further studies of the αβ TCR repertoire in MDS.

Background: Utz et al., in a study of identical twins discordant for MS, showed that antigen-stimulated T cells from the MS twins have a major shift in their T-cell receptor (TCR) repertoires when compared with the healthy twins. We hypothesized that a shift in the TCR repertoire precedes the onset of MS and tested this hypothesis by studying unstimulated naive T cells because the TCR repertoires of these cells are largely unaffected by disease. Objective: To investigate whether unstimulated naive T cells from MS patients have a detectable shift in their TCR repertoires. Methods: We analyzed the TCR J beta (TCRBJ) repertoires of naive T cells from identical twin pairs discordant for MS, healthy identical twin pairs, healthy unrelated pairs, and unrelated MS patient pairs. The correlation coefficient ( r value) was used as a measure of similarity of TCRBJ repertoires in each pair of individuals. Fisher’s z transformation was then used to test for the significance of the difference between the r values from different pairs. Results: The TCRBJ repertoires of the discordant MS twin pairs were significantly different from those of the healthy identical twin pairs, whereas MS patient pairs had TCRBJ repertoires similar to those of the healthy unrelated pairs formed from healthy twin pairs and discordant MS twin pairs. Conclusions: MS patients have a major shift in their naive T-cell TCRBJ repertoires compared with healthy individuals, implying that this shift precedes the disease onset. This shift could represent the nongenetic factor that explains MS discordance in genetically identical individuals.

Orofacial granulomatosis (OFG) is a clinicopathologic entity describing oral lesions with noncaseating granulomas including a spectrum of diseases such as the Melkersson-Rosenthal syndrome. The involvement of abnormal T-cell responses has been suggested in the pathogenesis of OFG although few and contrasting data are currently available on this issue. In a patient with OFG, we observed virtually complete CD4 and CD8 T-cell receptor (TCR) ?-chain variable region (BV) repertoires at the lesion level and in circulation. However, oligoclonal profiles were found in CD4 and, to a greater extent, in CD8 subsets. These findings were seen in association with a massive peripheral T-cell activation, decreased naive T cells, reduced thymic output, altered cytokine production, and increased apoptosis. Our data, pointing to a random influx of T cells at the site of inflammation, argue against the hypothesis of a main allergen acting at the level of oral mucosa. The profound dysregulation of the peripheral T-cell compartment suggests that OFG should be regarded as a systemic disorder with localized manifestations.

Background The T-cell receptor (TCR), located on the surface of T cells, is responsible for the recognition of the antigen-major histocompatibility complex, leading to the initiation of an inflammatory response. Analysing the TCR repertoire may help to gain a better understanding of the immune system features and of the aetiology and progression of diseases, in particular those with unknown antigenic triggers. The extreme diversity of the TCR repertoire represents a major analytical challenge; this has led to the development of specialized methods which aim to characterize the TCR repertoire in-depth. Currently, next generation sequencing based technologies are most widely employed for the high-throughput analysis of the immune cell repertoire. Results Here, we report on the latest methodological advancements in the field by describing and comparing the available tools; from the choice of the starting material and library preparation method, to the sequencing technologies and data analysis. Finally, we provide a practical example and our own experience by reporting some exemplary results from a small internal benchmark study, where current approaches from the literature and the market are employed and compared. Conclusions Several valid methods for clonotype identification and TCR repertoire analysis exist, however, a gold standard method for the field has not yet been identified. Depending on the purpose of the scientific study, some approaches may be more suitable than others. Finally, due to possible method specific biases, scientists must be careful when comparing results obtained using different methods. Electronic supplementary material The online version of this article (doi:10.1186/s12896-017-0379-9) contains supplementary material, which is available to authorized users.

T cell receptor (TCR) is a heterodimer consisting of TCRα and TCRβ chains that are generated by somatic recombination of multiple gene segments. Nascent TCR repertoire undergoes thymic selections where non-functional and potentially autoreactive receptors are removed. During the last years, the development of high-throughput sequencing technology has allowed a large scale assessment of TCR repertoire and multiple analysis tools are now also available. In our recent manuscript, Human thymic T cell repertoire is imprinted with strong convergence to shared sequences[1], we show highly overlapping thymic TCR repertoires in unrelated individuals. In the current Data in Brief article, we provide a more detailed characterization of the basic features of these thymic and related peripheral blood TCR repertoires. The thymus samples were collected from eight infants undergoing corrective cardiac surgery, two of whom were monozygous twins [2]. In parallel with the surgery, a small aliquot of peripheral blood was drawn from four of the donors. Genomic DNA was extracted from mechanically released thymocytes and circulating leukocytes. The sequencing of TCRα and TCRβ repertoires was performed at ImmunoSEQ platform (Adaptive Biotechnologies). The obtained repertoire data were analysed applying relevant features from immunoSEQ® 3.0 Analyzer (Adaptive Biotechnologies) and a freely available VDJTools software package for programming language R [3]. The current data analysis displays the basic features of the sequenced repertoires including observed TCR diversity, various descriptive TCR diversity measures, and V and J gene usage. In addition, multiple methods to calculate repertoire overlap between two individuals are applied. The raw sequence data provide a large database of reference TCRs in healthy individuals at an early developmental stage. The data can be exploited to improve existing computational models on TCR repertoire behaviour as well as in the generation of new models.