Pandemic, Epidemic, Endemic: B Cell Repertoire Analysis Reveals Unique Anti-Viral Responses to SARS-CoV-2, Ebola and Respiratory Syncytial Virus

Abstract

Immunoglobulin gene heterogeneity reflects the diversity and focus of the humoral immune response towards different infections, enabling inference of B cell development processes. Detailed compositional and lineage analysis of long read IGH repertoire sequencing, combining examples of pandemic, epidemic and endemic viral infections with control and vaccination samples, demonstrates general responses including increased use of IGHV4-39 in both Zaire Ebolavirus (EBOV) and COVID-19 patient cohorts. We also show unique characteristics absent in Respiratory Syncytial Virus or yellow fever vaccine samples: EBOV survivors show unprecedented high levels of class switching events while COVID-19 repertoires from acute disease appear underdeveloped. Despite the high levels of clonal expansion in COVID-19 IgG1 repertoires there is a striking lack of evidence of germinal centre mutation and selection. Given the differences in COVID-19 morbidity and mortality with age, it is also pertinent that we find significant differences in repertoire characteristics between young and old patients. Our data supports the hypothesis that a primary viral challenge can result in a strong but immature humoral response where failures in selection of the repertoire risk off-target effects.

sciCSR infers B cell state transition and predicts class-switch recombination dynamics using single-cell transcriptomic data

“…We hypothesize that the use of information native to B cells, namely CSR and SHM, would improve the inference of cell state transitions in mature B cells as observed in scRNA-seq data. SHM level can be easily retrieved from BCR sequencing data, which are routinely obtained in parallel to transcriptome-wide single-cell profiling: SHM is inversely related to the sequence identity between the observed BCR sequence and the corresponding germline immunoglobulin gene 31 , 32 (Fig. 1b ).…”

“…1b ). The detection of CSR, on the other hand, is less trivial at the single-cell level: CSR is more easily characterized by either comparing the expression level of different IgH isotypes at the transcript or protein level for a cell population 33 , or by studying BCR clonotypes that comprise sequences of different isotypes 31 . In sciCSR a series of routines has been implemented to distinguish productive and sterile IgH transcripts from scRNA-seq data, by enumerating mRNA molecules (identifiable by observing combinations of cell barcode and unique molecular identifier (UMI)) with reads mapping to the VDJ, 5′ C or C regions in the IgH genomic locus (Fig.…”

Chickens, more than humans, focus the diversity of their immunoglobulin genes on the complementarity-determining region but utilise amino acids, indicative of a more cross-reactive antibody repertoire

“…A total of 311,870 chicken heavy immunoglobulin sequences and 95,161 chicken lambda light chain immunoglobulin sequences were analysed. Human immunoglobulin sequences were generated from whole blood samples taken from 24 healthy donors; these samples were collected and processed as part of a study conducted by ( 11 ). Human donors ranged between the ages of 23 and 76.…”

sciCSR infers B cell state transition and predicts class-switch recombination dynamics using single-cell transcriptomic data

“…We hypothesise that the use of information native to B cells, namely class-switch recombination (CSR) and somatic hypermutation (SHM), would improve the inference of cell state transitions in mature B cells as observed in scRNA-seq data. SHM level can be easily retrieved from BCR sequencing data of single cells which is routinely obtained in parallel to transcriptome-wide single-cell profiling: SHM is inversely related to the sequence identity between the observed BCR sequence and the corresponding germline immunoglobulin gene [57][58][59][60] (Figure 1b). The detection of CSR, on the other hand, is less trivial at the single-cell level: CSR is more easily characterized by either comparing the expression level of different immunoglobulin heavy chain (IgH) isotypes at the transcript or protein level for a cell population [61][62][63] , or by studying BCR clonotypes which comprise sequences of different isotypes 57,64,65 .…”

“…SHM level can be easily retrieved from BCR sequencing data of single cells which is routinely obtained in parallel to transcriptome-wide single-cell profiling: SHM is inversely related to the sequence identity between the observed BCR sequence and the corresponding germline immunoglobulin gene [57][58][59][60] (Figure 1b). The detection of CSR, on the other hand, is less trivial at the single-cell level: CSR is more easily characterized by either comparing the expression level of different immunoglobulin heavy chain (IgH) isotypes at the transcript or protein level for a cell population [61][62][63] , or by studying BCR clonotypes which comprise sequences of different isotypes 57,64,65 . In sciCSR a series of routines has been implemented to distinguish productive and sterile IgH transcripts from scRNA-seq data, by enumerating mRNA molecules (identifiable by observing combinations of cell barcode and unique molecular identifier (UMI)) with reads mapping to the VDJ, 5' C or C regions in the immunoglobulin heavy-chain (IgH) genomic locus (Figure 1c).…”