Biology subjects

Vigneault, F.

Publications and source records attributed to Vigneault, F..

5 recordsLinked to original sources

bioRxiv2018

Mice developing mammary tumors evolve T cell sequences shared with human breast cancer patients

Cancer immunotherapy by checkpoint blockade proves that an effective immune response to a tumor can be induced clinically. However, little is known about the evolution of tumor-associated T-cell receptor (TCR) repertoires without intervention. Here we studied TCR repertoire evolution in mice spontaneously developing mammary tumors; we sequenced peripheral blood alpha and beta TCRs of CD4+CD62L+CD44- T cells monthly for 8 months in 10 FVB/NJ mice transgenic at the Erbb2 locus, all developing tumors; 5 FVB/NJ mice without the transgene were age-matched controls. Sequences were either private (restricted to one mouse) or public (shared among mice); public sequences were either exclusive to the tumor group or inclusive among different groups. We now report that 1), public AA sequences were each encoded by many different nucleotide sequences (NT) recombinations (convergent recombination; CR); 2) mice developing tumors evolved tumor-exclusive public sequences, derived initially from private or from inclusive public sequences; and 3) tumor-exclusive public sequences in mice were also present among published public TCR sequences from human breast cancer patients. These cross-species tumor-exclusive TCR sequences manifested high CR; but the AA sequences shared by mice and humans did not share NT sequences. Thus, tumor-exclusive TCR AA sequences across species are selected from different NT recombination events. The roles of tumor-exclusive TCR repertoires in advancing or inhibiting tumor development and the effects of tumor immunotherapy on these T cells remain to be seen.

cancer biology↗

bioRxiv2018

Mosaic deletion patterns of the human antibody heavy chain gene locus

Analysis of antibody repertoires by high-throughput sequencing is of major importance in understanding adaptive immune responses. Our knowledge of variations in the genomic loci encoding antibody genes is incomplete, mostly due to technical difficulties in aligning short reads to these highly repetitive loci. The partial knowledge results in conflicting V-D-J gene assignments between different algorithms, and biased genotype and haplotype inference. Previous studies have shown that haplotypes can be inferred by taking advantage of IGHJ6 heterozygosity, observed in approximately one third of the population. Here, we propose a robust novel method for determining V-D-J haplotypes by adapting a Bayesian framework. Our method extends haplotype inference to IGHD- and IGHV-based analysis, thereby enabling inference of complex genetic events like deletions and copy number variations in the entire population. We generated the largest multi individual data set, to date, of naive B-cell repertoires, and tested our method on it. We present evidence for allele usage bias, as well as a mosaic, tiled pattern of deleted and present IGHD and IGHV nearby genes, across the population. The inferred haplotypes and deletion patterns may have clinical implications for genetic predispositions to diseases. Our findings greatly expand the knowledge that can be extracted from antibody repertoire sequencing data.

genomics↗

bioRxiv2018

T-cell receptor αβ chain pairing is associated with CD4+ and CD8+ lineage specification

While a highly diverse T-cell receptor (TCR) repertoire is the hallmark of a healthy adaptive immune system, relatively little is understood about how the CD4+ and CD8+ TCR repertoires differ from one another. We here utilize high-throughput single T-cell sequencing to obtain approximately 100,000 TCR {beta} chain pairs from human subjects, stratified into CD4+ and CD8+ lineages. We reveal that substantial information about T-cell lineage is encoded by V{beta} gene pairs and, to a lesser extent, by several other TCR features such as CDR3 length and charge. We further find that the strength of association between the {beta} chain and T-cell lineage is surprisingly weak, similar in strength to that of the chain. Using machine learning classifiers to predict T-cell lineage from TCR features, we demon-strate that {beta} chain pairs are significantly more informative than individual chains alone. These findings provide unprecedented insight into the CD4+ and CD8+ TCR repertoires and highlight the importance of {beta} chain pairing in TCR function and specificity.

immunology↗

bioRxiv2017

Single-cell sequencing reveals αβ chain pairing shapes the T cell repertoire

A diverse T cell repertoire is a critical component of the adaptive immune system, providing protection against invading pathogens and neoplastic changes, relying on the recognition of foreign antigens and neoantigen peptides by T cell receptors (TCRs). However, the statistical properties and function of the T cell pool in an individual, under normal physiological conditions, are poorly understood. In this study, we report a comprehensive, quantitative characterization of the T cell repertoire from over 1.9 million cells, yielding over 200,000 high quality paired {beta} sequences in 5 healthy human subjects. The dataset was obtained by leveraging recent biotechnology developments in deep RNA sequencing of lymphocytes via single-cell barcoding in emulsion. We report non-random associations and non-monogamous pairing between the and {beta} chains, lowering the theoretical diversity of the T cell repertoire, and increasing the frequency of public clones shared among individuals. T cell clone size distributions closely followed a power law, with markedly longer tails for CD8+ cytotoxic T cells than CD4+ helper T cells. Furthermore, clonality estimates based on paired chains from single T cells were lower than that from single chain data. Taken together, these results highlight the importance of sequencing {beta} pairs to accurately quantify lymphocyte receptor diversity.

immunology↗

bioRxiv2017

Tumor-infiltrating immune repertoires captured by single-cell barcoding in emulsion

Tumor-infiltrating lymphocytes (TILs) are critical to anti-cancer immune responses, but their diverse phenotypes and functions remain poorly understood and challenging to study. We therefore developed a single-cell barcoding technology for deep characterization of TILs without the need for cell-sorting or culture. Our emulsion-based method captures full-length, natively paired B-cell and T-cell receptor (BCR and TCR) sequences from lymphocytes among millions of input cells. We validated the method with 3 million B-cells from healthy human blood and 350,000 B-cells from an HIV elite controller, before processing 400,000 cells from an unsorted dissociated ovarian adenocarcinoma and recovering paired BCRs and TCRs from over 11,000 TILs. We then extended the barcoding method to detect DNA-labeled antibodies, allowing ultra-high throughput, simultaneous protein detection and RNA sequencing from single cells.

immunology↗