Analysing single-cell T-cell receptor sequencing data with Scirpy
A recent publication by Gregor Sturm et al. (Bioinformatics 2020) presents Scirpy, a Scanpy extension for analysing single-cell T-cell receptor sequencing data. It simplifies analysis and visualization of immune repertoires from single cells.
- Why we care about single-cell T-cell receptor sequencing
- Biology of antigen presentation
- Conclusions
Why we care about single-cell T-cell receptor sequencing
Scirpy makes it possible to work with single-cell T-cell sequencing data easily. It extends the Scanpy software written in Python that is well established for single-cell sequencing data analysis.
I learned from my colleague that another tool, pyVDJ, can be use to analyse such data. I have not used it yet. In case you have experience with either or both tools, I will appreciate your feedback.
For those who are new to the business of immunology, T cell receptors (TCRs) are important because they recognize antigens, say from bacterial or viral infection, cancer, or self-antigens from autoimmune diseases. One can sequence mRNAs encoding TCRs to determine what proteins will be translated and expressed by these T cells. When we sequence TCR sequences in single cells, we can classify a population of T cells, and compare populations of T cells between conditions or between individuals.
An example of applying TCR sequencing can be found in this paper: RNA sequencing identifies clonal structure of T-cell repertoires in patients with adult T-cell leukemia/lymphoma.
Biology of antigen presentation
If you are interested, here are some basic bology of antigen presentation.
T-cell receptors and V(D)J recombination
T-cell receptors, or TCRs, are generated through random rearrangement of genomic loci. The loci are known as V (variable) region, the D (diversity) region, and the J (joining) region. The rearrangement is therefore sometimes called V(D)J rearrangement.
The process of V(D)J rearrangement can be visually expressed in the following graphic (source: Wikimedia).
If you are interested in or even fascinated by this process, you can read more about V(D)J recombination in this paper Unraveling V(D)J Recombination.
V(D)J rearragement generates TCRs in T cells and the repertoires of antibodies (immunoglobulins) in B cells. In human, 95% T-cell receptors contain alpha and beta chains, encoded by TRA (Entrez Gene ID 6955, chromosome 14) and TRB (Entrez GeneID 6957, chromosome 7) genes, respectively. The TCR alpha chain is generated by VJ recombination, and the beta chain is generated by VDJ recombination.
Human Leucocyte Antigens, MHC-I and MHC-II class molecules in human
Besides T-cell receptors, MHC-I and MHC-II class molecules, known as human leucocyte antigens (HLAs) in human, are critical for antigen presentation and recognition.
Human leucocyte antigen (HLA) genes encode proteins that present antigens. They constitute Major Histocompatibility Class (MHC) in human, which is a large genomic locus in vertebrates that contain a set of closely linked polymorphic genes which code for cell-surface proteins that are essential for the adaptive immune system. The MHC gene family is divided into three classes: I (expressed on all nucleated cells), II (expressed mainly in professional antigen-presenting cells, and III (other various genes including the complement cascade, cytokine signalling, and heat shock proteins). HLA encodes class I and class II proteins.
Together, MHC (encoded by HLA in human) and TCRs (encoded by TRA and TRB, as well as other genes with the process of V(D)J recombination) work together to alow human cells to present antigens to T cells and initiate adaptive immune response.
Awesome-vdj: tools and datasets for antigen presentation recognition
The GitHub repository slowkow/awesome-vdj collects tools and datasets for antigen presentation and recognition.
Conclusions
Scipy is an interesting tool to try if you want to analyse single-cell TCR sequencing data.
Update on 23.07.2020: An opinion piece by Gutierrez et al. is a good educational read about roles of T-cells in combating SARS-CoV-2 infection and the necessity of TCR repertoire analysis is an interesting and educational read. It was also discussed by Derek Lowe in his blog In The Pipeline.