Network properties derived from deep sequencing of human B-cell receptor repertoires delineate B-cell populations

Abstract

The adaptive immune response selectively expands B-and T-cell clones following antigen recognition by B-and T-cell receptors (BCR and TCR), respectively. Next-generation sequencing is a powerful tool for dissecting the BCR and TCR populations at high resolution, but robust computational analyses are required to interpret such sequencing. Here, we develop a novel computational approach for BCR repertoire analysis using established next-generation sequencing methods coupled with network construction and population analysis. BCR sequences organize into networks based on sequence diversity, with differences in network connectivity clearly distinguishing between diverse repertoires of healthy individuals and clonally expanded repertoires from individuals with chronic lymphocytic leukemia (CLL) and other clonal blood disorders. Network population measures defined by the Gini Index and cluster sizes quantify the BCR clonality status and are robust to sampling and sequencing depths. BCR network analysis therefore allows the direct and quantifiable comparison of BCR repertoires between samples and intraindividual population changes between temporal or spatially separated samples and over the course of therapy.

Tissue distribution and clonal diversity of the T and B cell repertoire in type 1 diabetes

“…Previous efforts to characterize the TCR repertoire in T1D subjects have been limited to tissues obtained from few or even a mere single organ donor (12,13) or were restricted to peripheral blood samples (14,37). Furthermore, BCR sequencing data in human samples is limited, particularly in subjects with T1D (15,16). Thus, to our knowledge, this report contains the most comprehensive TCR and BCR data set from human pLN, spleen, and islet tissues from T1D donors available to date.…”

“…Moreover, TCR overlap among pathogenic CD4 + effector T cells and protective Treg have yet to be investigated in human T1D. Likewise, B cell receptor (BCR) sequencing efforts have been limited overall (15,16) and, in particular, in patients with T1D (17), despite a known role for B cells in contributing to T1D through their capacity to present antigens (18).…”

Biased estimates of clonal evolution and subclonal heterogeneity can arise from PCR duplicates in deep sequencing experiments

“…Metastatic cancer can now be monitored through deep sequencing of circulating tumor DNA [13], and the potential for poor DNA quality combined with deep sequencing requirements make PCR duplicates an important concern, especially if the results impact clinical decisions. Further, methods to study highly diverse mixtures like the immune repertoire [26][27][28] or viral heterogeneity [29] rely on accurate read depths to infer population dynamics. Our approach can also be applied to applications that require high accuracy of rare variant calls, such as in pooled populations or cancer, where SMTs have been used to group duplicate reads together in order to cancel out sequencing errors and obtain highly accurate variant calls [22].…”

Reconstructing and mining the B cell repertoire with ImmunediveRsity

“…The output consists (1) Fasta files: containing the CDRH3 sequences for each read and clonotype, as well as the sequence for each consensus lineage with a unique identifier. metrics include normalized clonal and lineages frequencies, global entropy measurements such as Shannon-Weaver index 18 and Gini coefficient 19,20 ( Fig. 1 and Fig.…”