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Biology subjects

Michael J.T. Stubbington

Publications and source records attributed to Michael J.T. Stubbington.

2 recordsLinked to original sources

Single-cell transcriptome analysis of fish immune cells provides insight into the evolution of vertebrate immunity

The immune system of vertebrate species consists of many different cell types that have distinct functional roles and are subject to different evolutionary pressures. Here, we first analysed gene conservation of all major immune cell types in human and mouse. Our results revealed higher gene turnover and faster evolution of trans-membrane proteins in NK cells compared to other immune cell populations, and especially T cells, but similar conservation of nuclear and cytoplasmic protein coding genes. To validate these findings in a distant vertebrate species, we used single-cell RNA-Sequencing of lck:GFP cells in zebrafish to obtain the first transcriptome of specific immune cell types in a non-mammalian species. Unsupervised clustering and single-cell TCR locus reconstruction identified three cell populations, T-cells, a novel type of NK-like cells and a smaller population of myeloid-like cells. Differential expression analysis uncovered new immune cell specific genes, including novel immunoglobulin-like receptors, and neofunctionalization of recently duplicated paralogs. Evolutionary analyses confirmed a higher gene turnover and lower conservation of trans-membrane proteins in NK cells compared to T cells in fish species, suggesting that this is a general property of immune cell types across all vertebrates.

Immunology

Simultaneously inferring T cell fate and clonality from single cell transcriptomes

The heterodimeric T cell receptor (TCR) comprises two protein chains that pair to determine the antigen specificity of each T lymphocyte. The enormous sequence diversity within TCR repertoires allows specific TCR sequences to be used as lineage markers for T cells that derive from a common progenitor. We have developed a computational method, called TraCeR, to reconstruct full-length, paired TCR sequences from T lymphocyte single-cell RNA-seq by combining existing assembly and alignment programs with a \"synthetic genome\" library comprising all possible TCR sequences. We validate this method with PCR to quantify its accuracy and sensitivity, and compare to other TCR sequencing methods. Our inferred TCR sequences reveal clonal relationships between T cells, which we put into the context of each cells functional state from the complete transcriptional landscape quantified from the remaining RNA-seq data. This provides a powerful tool to link T cell specificity with functional response in a variety of normal and pathological conditions. We demonstrate this by determining the distribution of members of expanded T cell clonotypes in response to Salmonella infection in the mouse. We show that members of the same clonotype span early activated CD4+ T cells, as well as mature effector and memory cells.

Bioinformatics