Journal article icon

Journal article

Structural diversity of B-cell receptor repertoires along the B-cell differentiation axis in humans and mice

Abstract:
Most current analysis tools for antibody next-generation sequencing data work with primary sequence descriptors, leaving accompanying structural information unharnessed. We have used novel rapid methods to structurally characterize the complementary-determining regions (CDRs) of more than 180 million human and mouse B-cell receptor (BCR) repertoire sequences. These structurally annotated CDRs provide unprecedented insights into both the structural predetermination and dynamics of the adaptive immune response. We show that B-cell types can be distinguished based solely on these structural properties. Antigen-unexperienced BCR repertoires use the highest number and diversity of CDR structures and these patterns of naïve repertoire paratope usage are highly conserved across subjects. In contrast, more differentiated B-cells are more personalized in terms of CDR structure usage. Our results establish the CDR structure differences in BCR repertoires and have applications for many fields including immunodiagnostics, phage display library generation, and “humanness” assessment of BCR repertoires from transgenic animals. The software tool for structural annotation of BCR repertoires, SAAB+, is available at https://github.com/oxpig/saab_plus.
Publication status:
Published
Peer review status:
Peer reviewed

Actions


Access Document


Files:
Publisher copy:
10.1371/journal.pcbi.1007636

Authors


More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
ORCID:
0000-0003-3806-8302
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Doctoral Training Centre - MPLS
Role:
Author
ORCID:
0000-0002-5663-5297
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Doctoral Training Centre - MPLS
Role:
Author
ORCID:
0000-0003-4029-6902
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Doctoral Training Centre - MPLS
Role:
Author
ORCID:
0000-0001-5931-2437


Publisher:
Public Library of Science
Journal:
PLOS Computational Biology More from this journal
Volume:
16
Issue:
2
Article number:
e1007636
Publication date:
2020-02-18
Acceptance date:
2020-01-07
DOI:
EISSN:
1553-7358
ISSN:
1553-734X


Language:
English
Keywords:
Pubs id:
1083521
Local pid:
pubs:1083521
Deposit date:
2020-02-19

Terms of use



Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP