Inferring the immune systems dynamics from high throughput antibody sequencing data

דר' גור יערי

אוניברסיטת בר אילן

Inferring the immune systems dynamics from high throughput antibody sequencing data

The ability of our immune system to recognize threats is critical to survival. It operates through clonal expansion and selection of lymphocytes (B and T cells), that produce an immense, diverse repertoire of receptors. Analyzing the collection of receptors expressed by naïve and memory B cells offers insights into the infection history of individuals. It can teach us about fundamental immune processes, and reveal disregulation. The recent development of high-throughput sequencing brings exciting possibilities, allowing for large-scale characterization of antibody repertoires. However, the statistical methods and models to plan these high-throughput experiments and analyze their results are lacking. Hereby, I will present several new computational tools that were designed to address crucial steps in lymphocyte receptor repertoire analysis: process raw data, infer an individual genotype from mRNA sequences, quantify affinity dependent selection and build a targeting model for the observed mutation spectrum. Examples of the applicability of these tools will be demonstrated through the analysis of next generation antibody sequencing dataset

​ built from samples of individuals with multiple sclerosis​

. I will share my view of the major obstacles that still need to be confronted before we can utilize lymphocyte receptor repertoire analysis for diagnosis and prognosis.