TY - JOUR
T1 - Interpreting the B-cell receptor repertoire with single-cell gene expression using Benisse
AU - Zhang, Ze
AU - Chang, Woo Yong
AU - Wang, Kaiwen
AU - Yang, Yuqiu
AU - Wang, Xinlei
AU - Yao, Chen
AU - Wu, Tuoqi
AU - Wang, Li
AU - Wang, Tao
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Nature Limited.
PY - 2022/6
Y1 - 2022/6
N2 - B-cell receptors (BCRs) are a crucial player in the development and activation of B cells, and their mature forms are secreted as antibodies, which execute functions such as the neutralization of invading pathogens. All current analytical approaches for BCRs solely investigate the BCR sequences and ignore their correlations with the transcriptomics of the B cells, yielding conclusions of unknown functional relevance regarding the roles of BCRs and B cells, and could generate biased interpretation. Many single-cell RNA-sequencing (scRNA-seq) techniques can now capture both the gene expression and BCR of each B cell, which could potentially address this issue. Here, we investigated 43,938 B cells from 13 scRNA-seq datasets with matched scBCR sequencing, and we observed an association between the BCRs and the B cells’ transcriptomics. Motivated by this, we developed the Benisse model (BCR embedding graphical network informed by scRNA-seq) to provide refined analyses of BCRs guided by single-cell gene expression. Benisse revealed a gradient of B-cell activation along BCR trajectories. We discovered a stronger coupling between BCRs and B-cell gene expression during COVID-19 infections. We found that BCRs form a directed pattern of continuous and linear evolution to achieve the highest antigen targeting efficiency, compared with the convergent evolution pattern of T-cell receptors. Overall, a simultaneous digestion of the BCR and gene expression of B cells, viewed through the lens of Benisse, will lead to a more insightful interpretation of the functional relevance of the BCR repertoire in different biological contexts.
AB - B-cell receptors (BCRs) are a crucial player in the development and activation of B cells, and their mature forms are secreted as antibodies, which execute functions such as the neutralization of invading pathogens. All current analytical approaches for BCRs solely investigate the BCR sequences and ignore their correlations with the transcriptomics of the B cells, yielding conclusions of unknown functional relevance regarding the roles of BCRs and B cells, and could generate biased interpretation. Many single-cell RNA-sequencing (scRNA-seq) techniques can now capture both the gene expression and BCR of each B cell, which could potentially address this issue. Here, we investigated 43,938 B cells from 13 scRNA-seq datasets with matched scBCR sequencing, and we observed an association between the BCRs and the B cells’ transcriptomics. Motivated by this, we developed the Benisse model (BCR embedding graphical network informed by scRNA-seq) to provide refined analyses of BCRs guided by single-cell gene expression. Benisse revealed a gradient of B-cell activation along BCR trajectories. We discovered a stronger coupling between BCRs and B-cell gene expression during COVID-19 infections. We found that BCRs form a directed pattern of continuous and linear evolution to achieve the highest antigen targeting efficiency, compared with the convergent evolution pattern of T-cell receptors. Overall, a simultaneous digestion of the BCR and gene expression of B cells, viewed through the lens of Benisse, will lead to a more insightful interpretation of the functional relevance of the BCR repertoire in different biological contexts.
UR - http://www.scopus.com/inward/record.url?scp=85131332179&partnerID=8YFLogxK
U2 - 10.1038/s42256-022-00492-6
DO - 10.1038/s42256-022-00492-6
M3 - Article
AN - SCOPUS:85131332179
SN - 2522-5839
VL - 4
SP - 596
EP - 604
JO - Nature Machine Intelligence
JF - Nature Machine Intelligence
IS - 6
ER -