High-throughput Pairing of T Cell Receptor Alpha and Beta Sequences

High-throughput Pairing of T Cell Receptor Alpha and Beta Sequences


Readers may find this paper by Bryan Howie and colleagues interesting. It solves an important problem (finding pairing pattern of TCR alpha and beta chains) using high-throughput sequencing and an elegant mathematical model.

The T cell receptor (TCR) protein is a heterodimer composed of an alpha chain and a beta chain. TCR genes undergo somatic DNA rearrangements to generate the diversity of T cell binding specificities needed for effective immunity. Recently, high-throughput immunosequencing methods have been developed to profile the TCR alpha (TCRA) and TCR beta (TCRB) repertoires. However, these methods cannot determine which TCRA and TCRB chains combine to form a specific TCR, which is essential for many functional and therapeutic applications. We describe and validate a method called pairSEQ, which can leverage the diversity of TCR sequences to accurately pair hundreds of thousands of TCRA and TCRB sequences in a single experiment. Our TCR pairing method uses standard laboratory consumables and equipment without the need for single-cell technologies. We show that pairSEQ can be applied to T cells from both blood and solid tissues, such as tumors.

Their probabilistic model is very familiar to me, because twelve years back I used it in a different context - for finding clustered proteins from noisy large-scale protein-protein interaction data. Here is the basic idea. If A has 10 friends and B has 10 friends, what is the probability that they have 9 common friends (by chance alone)? If the computed probability is very low and the actual measurement shows that they indeed have 9 common friends, that means A and B are strongly associated. In case of TCR alpha and beta chains in their experimental set-up, that strong association implies their combining to form heterodimers. For large-scale protein-protein interaction data in yeast, significant association appeared to show functional similarity.

The work for the above TCR paper was done by Adaptive Technologies, a very creative Seattle-based company that was founded by scientists from Fred Hutch Cancer Research Institute.



Written by M. //