Models and methods for mining B cell repertoire dynamics from next-generation sequencing studies

Speaker
דר' גור יערי, הפקולטה להנדסה ב"א
Date
09/12/2013 - 15:00Add to Calendar 2013-12-09 15:00:00 2013-12-09 15:00:00 Models and methods for mining B cell repertoire dynamics from next-generation sequencing studies The ability of our immune system to recognize ever-evolving threats is critical to survival. Initial recognition of pathogens depends on generating a diverse repertoire of antibodies through recombination of gene segments. This naïve repertoire is dynamically modified as activated B cells undergo cycles of division, somatic hypermutation and affinity-dependent selection. This affinity maturation process produces expanded memory B cell clones expressing mutated antibodies with high-affinity for the pathogen. 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 three crucial steps in lymphocyte receptor repertoire analysis: process raw data, 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 several studies involving next generation antibody sequencing datasets. 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.   Room 301, Physics Bld. 202 המחלקה לפיזיקה physics.dept@mail.biu.ac.il Asia/Jerusalem public
Place
Room 301, Physics Bld. 202
Abstract

The ability of our immune system to recognize ever-evolving threats is critical to survival. Initial recognition of pathogens depends on generating a diverse repertoire of antibodies through recombination of gene segments. This naïve repertoire is dynamically modified as activated B cells undergo cycles of division, somatic hypermutation and affinity-dependent selection. This affinity maturation process produces expanded memory B cell clones expressing mutated antibodies with high-affinity for the pathogen. 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 three crucial steps in lymphocyte receptor repertoire analysis: process raw data, 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 several studies involving next generation antibody sequencing datasets. 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.

 

תאריך עדכון אחרון : 05/12/2013