Reconstructing B cell lineage trees with minimum spanning tree and genotype abundances

Abstract

B cell receptor (BCR) genes exposed to an antigen undergo somatic hypermutations and Darwinian antigen selection, generating a large BCR-antibody diversity. This process, known as B cell affinity maturation, increases antibody affinity, forming a specific B cell lineage that includes the unmutated ancestor and mutated variants. In a B cell lineage, cells with a higher antigen affinity will undergo clonal expansion, while those with a lower affinity will not proliferate and probably be eliminated. Therefore, cellular (genotype) abundance provides a valuable perspective on the ongoing evolutionary process. Phylogenetic tree inference is often used to reconstruct B cell lineage trees and represents the evolutionary dynamic of BCR affinity maturation. However, such methods should process B-cell population data derived from experimental sampling that might contain different cellular abundances. There are a few phylogenetic methods for tracing the evolutionary events occurring in B cell lineages; best-performing solutions are time-demanding and restricted to analysing a reduced number of sequences, while time-efficient methods do not consider cellular abundances. We propose ClonalTree, a low-complexity and accurate approach to construct B-cell lineage trees that incorporates genotype abundances into minimum spanning tree (MST) algorithms. Using both simulated and experimental data, we demonstrate that ClonalTree outperforms MST-based algorithms and achieves a comparable performance to a method that explores tree-generating space exhaustively. Furthermore, ClonalTree has a lower running time, being more convenient for building B-cell lineage trees from high-throughput BCR sequencing data, mainly in biomedical applications, where a lower computational time is appreciable. It is hundreds to thousands of times faster than exhaustive approaches, enabling the analysis of a large set of sequences within minutes or seconds and without loss of accuracy. The source code is freely available at github.com/julibinho/ClonalTree.

Robust and protective immune responses induced by heterologous prime‐boost vaccination with DNA‐protein dimeric RBD vaccines for COVID‐19

“…40 It is likely that the heterologous DNA/protein prime/ boost immunization enhances the somatic hypermutation and affinity maturation of B cells to generate antibodies with high affinity and diversity, resulting in broader activities against the SARS-CoV-2 variants, compared to the homologous immunization. 34,49 This mechanism is worth exploring in depth in our further studies.…”

Do Domain-Specific Protein Language Models Outperform General Models on Immunology-Related Tasks?

“…This method to infer sequences was preferred over Bayesian Maximum likelihood estimation approaches [52, 53] or Markov chain Monte Carlo sampling [54], as these heavily rely on the infinite sites assumptions, according to which every mutation occurs at a previously not mutated site. While this assumption is reasonable at a genome-wide scale, in the context of shorter junctions and somatic hypermutation rates, it is often not verified, as we have found in our data (Figure S4B).…”

ViCloD, an interactive web tool for visualizing B cell repertoires and analyzing intraclonal diversities: application to human B-cell tumors

“…For each clonal lineage, we try to reconstruct its evolutionary tree by using the N most abundant subclones. We use ClonalTree ( 43 ), a time-efficient and accurate approach to reconstruct B-cell lineage trees that incorporates genotype abundances into minimum spanning tree algorithms. ClonalTree requires a file in FASTA format containing sequences and their abundances as input.…”

“…Users can navigate among B-cell clonal lineages and explore their intraclonal diversity. For this purpose, we have developed a set of algorithms to analyze millions of IG sequences within a few minutes ( 31 , 43 ). Such methods are time efficient and compatible with both research and clinical settings.…”