Large-scale network analysis reveals the sequence space architecture of antibody repertoires
Loading...
Authors
Author (Corporation)
Publication date
01.12.2019
Typ of student thesis
Course of study
Type
01A - Journal article
Editors
Editor (Corporation)
Supervisor
Parent work
Nature Communications
Special issue
DOI of the original publication
Link
Series
Series number
Volume
10
Issue / Number
Pages / Duration
1321
Patent number
Publisher / Publishing institution
Nature
Place of publication / Event location
Edition
Version
Programming language
Assignee
Practice partner / Client
Abstract
The architecture of mouse and human antibody repertoires is defined by the sequence similarity networks of the clones that compose them. The major principles that define the architecture of antibody repertoires have remained largely unknown. Here, we establish a high-performance computing platform to construct large-scale networks from comprehensive human and murine antibody repertoire sequencing datasets (>100,000 unique sequences). Leveraging a network-based statistical framework, we identify three fundamental principles of antibody repertoire architecture: reproducibility, robustness and redundancy. Antibody repertoire networks are highly reproducible across individuals despite high antibody sequence dissimilarity. The architecture of antibody repertoires is robust to the removal of up to 50–90% of randomly selected clones, but fragile to the removal of public clones shared among individuals. Finally, repertoire architecture is intrinsically redundant. Our analysis provides guidelines for the large-scale network analysis of immune repertoires and may be used in the future to define disease-associated and synthetic repertoires.
Keywords
Subject (DDC)
600 - Technik, Medizin, angewandte Wissenschaften
Event
Exhibition start date
Exhibition end date
Conference start date
Conference end date
Date of the last check
ISBN
ISSN
2041-1723
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
Review
Peer review of the complete publication
Open access category
Gold
Citation
MIHO, Enkelejda, Rok ROŠKAR, Victor GREIFF und Sai T. REDDY, 2019. Large-scale network analysis reveals the sequence space architecture of antibody repertoires. Nature Communications. 1 Dezember 2019. Bd. 10, S. 1321. DOI 10.1038/s41467-019-09278-8. Verfügbar unter: https://doi.org/10.26041/fhnw-9968