Heterogeneity of T cells is a hallmark of a successful adaptive immune response, harnessing the vast diversity of antigen-specific T cells into a coordinated evolution of effector and memory outcomes. The T cell receptor (TCR) repertoire is highly diverse to account for the highly heterogeneous antigenic world. During the response to a virus multiple individual clones of antigen specific CD8+ (Ag-specific) T cells can be identified against a single epitope and multiple epitopes are recognised. Advances in single-cell technologies have provided the potential to study Ag-specific T cell heterogeneity at both surface phenotype and transcriptome levels, thereby allowing investigation of the diversity within the same apparent sub-population. We propose a new method (VDJPuzzle) to reconstruct the native TCRαβ from single cell RNA-seq data of Ag-specific T cells and then to link these with the gene expression profile of individual cells. We applied this method using rare Ag-specific T cells isolated from peripheral blood of a subject who cleared hepatitis C virus infection. We successfully reconstructed productive TCRαβ in 56 of a total of 63 cells (89%), with double α and double β in 18, and 7% respectively, and double TCRαβ in 2 cells. The method was validated via standard single cell PCR sequencing of the TCR. We demonstrate that single-cell transcriptome analysis can successfully distinguish Ag-specific T cell populations sorted directly from resting memory cells in peripheral blood and sorted after ex vivo stimulation. This approach allows a detailed analysis of the TCR diversity and its relationship with the transcriptional profile of different clones.
BackgroundHepatitis C virus (HCV) is a rapidly evolving RNA virus that has been classified into seven genotypes. All HCV genotypes cause chronic hepatitis, which ultimately leads to liver diseases such as cirrhosis. The genotypes are unevenly distributed across the globe, with genotypes 1 and 3 being the most prevalent. Until recently, molecular epidemiological studies of HCV evolution within the host and at the population level have been limited to the analyses of partial viral genome segments, as it has been technically challenging to amplify and sequence the full-length of the 9.6 kb HCV genome. Although recent improvements have been made in full genome sequencing methodologies, these protocols are still either limited to a specific genotype or cost-inefficient.ResultsIn this study we describe a genotype-specific protocol for the amplification and sequencing of the near-full length genome of all six major HCV genotypes. We applied this protocol to 122 HCV positive clinical samples, and had a successful genome amplification rate of 90 %, when the viral load was greater than 15,000 IU/ml. The assay was shown to have a detection limit of 1–3 cDNA copies per reaction. The method was tested with both Illumina and PacBio single molecule, real-time (SMRT) sequencing technologies. Illumina sequencing resulted in deep coverage and allowed detection of rare variants as well as HCV co-infection with multiple genotypes. The application of the method with PacBio RS resulted in sequence reads greater than 9 kb that covered the near full-length HCV amplicon in a single read and enabled analysis of the near full-length quasispecies.ConclusionsThe protocol described herein can be utilised for rapid amplification and sequencing of the near-full length HCV genome in a cost efficient manner suitable for a wide range of applications.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2575-8) contains supplementary material, which is available to authorized users.
Pirozyan et al. Innate Associations With Checkpoint Responses markers were expressed in practically all patients and the major observation was an increase in CD39 on CD4 T cells during treatment. The results confirm the association of Eomes transcription factor with T cell exhaustion but levels of expression and the ratio with T-bet over Eomes did not differ between the patient groups. Thus, peripheral blood expression of T cell exhaustion markers does not distinguish between responders and non-responders to anti-PD-1 therapy. CD4 T cell expression of IFNγ also differed in pre-treatment samples, indicating that predictors of response unrelated to exhaustion may be present in peripheral blood. The association of response with innate cell populations and CD4 T cell responses requires further study.
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