Abstract
The human body generates a diverse set of high affinity antibodies, the soluble form of B cell receptors (BCRs), that bind to and neutralize invading pathogens. The natural development of BCRs must be understood in order to design vaccines for highly mutable pathogens such as influenza and HIV. BCR diversity is induced by naturally occurring combinatorial “V(D)J” rearrangement, mutation, and selection processes. Most current methods for BCR sequence analysis focus on separately modeling the above processes. Statistical phylogenetic methods are often used to model the mutational dynamics of BCR sequence data, but these techniques do not consider all the complexities associated with B cell diversification such as the V(D)J rearrangement process. In particular, standard phylogenetic approaches assume the DNA bases of the progenitor (or “naive”) sequence arise independently and according to the same distribution, ignoring the complexities of V(D)J rearrangement. In this paper, we introduce a novel approach to Bayesian phylogenetic inference for BCR sequences that is based on a phylogenetic hidden Markov model (phylo-HMM). This technique not only integrates a naive rearrangement model with a phylogenetic model for BCR sequence evolution but also naturally accounts for uncertainty in all unobserved variables, including the phylogenetic tree, via posterior distribution sampling.
Highlights
One of the most important features of the adaptive immune system is its ability to create a wide variety of high affinity antibodies, the soluble form of B cell receptors (BCRs), that bind to and neutralize pathogens in the body
Before one can perform ancestral sequence inference for clonal sequences that result from the same naive rearrangement event, one must first obtain an estimate of the clonal phylogenetic tree
We propose a Bayesian approach to phylogenetic inference for clonal sequences that is based on a phylogenetic hidden Markov model
Summary
One of the most important features of the adaptive immune system is its ability to create a wide variety of high affinity antibodies, the soluble form of B cell receptors (BCRs), that bind to and neutralize pathogens in the body. During the GC reaction, B cells mutate rapidly in a process called somatic hypermutation (SHM), and the high affinity clones are positively selected for via clonal expansion. We would like to better understand the GC mutation and selection processes, because insight into mutational pathways from naive to mature BCR sequences could aid in the development of vaccines for highly mutable pathogens such as influenza and HIV [1]. We have developed a new statistical inference framework that better estimates these mutational pathways and quantifies uncertainty in these estimates
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
