Deciphering the antigen specificities of antibodies by clustering their complementarity determining region sequences

Saputri, Dianita S.; Ismanto, Hendra S.; Nugraha, Dendi K.; Xu, Zichang; Horiguchi, Yasuhiko; Sakakibara, Shuhei; Standley, Daron M.; Cristea, Ileana M.

doi:https://doi.org/10.1128/msystems.00722-23

Deciphering the antigen specificities of antibodies by clustering their complementarity determining region sequences

Saputri, Dianita S.; Ismanto, Hendra S.; Nugraha, Dendi K. et al.

mSystems, 2023, 8(6), e00722-23

Number of Access:540（2025-08-20 06:41 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/93389

Link to primary information

File	Format	Terms of use	Size	Views	Date.Available	Description	information
mSystems_8_6	pdf	None	3.10 MB	119	2024.01.09

Creative Commons : Attribution

Item Information

Output File Export EndNote Basic Export Mendeley

Title	Deciphering the antigen specificities of antibodies by clustering their complementarity determining region sequences
Creator	CreatorName Saputri, Dianita S.
	CreatorName Ismanto, Hendra S.
	NRID 1000000963430 1000000963430 ORCID 0000-0002-6995-5695 0000-0002-6995-5695 researchmap permalink dendikrisna dendikrisna CreatorName Nugraha, Dendi K.
	CreatorName Xu, Zichang
	NRID 1000000183939 1000000183939 ORCID 0000-0002-1592-5861 0000-0002-1592-5861 researchmap permalink read0014308 read0014308 Scopus Author ID 7102798909 7102798909 CreatorName Horiguchi, Yasuhiko
	NRID 1000010618838 1000010618838 CreatorName Sakakibara, Shuhei
	NRID 1000000448028 1000000448028 researchmap permalink 7000011861 7000011861 CreatorName Standley, Daron M.
	CreatorName Cristea, Ileana M.
Subject	antibody
	antigen-specific
	B cell receptor
	clustering
	diphtheria
	pertussis
	tetanus
	repertoire
	SARS-CoV-2
	single-cell immune profile
Description	Saputri Dianita S., Ismanto Hendra S., Nugraha Dendi K., et al. Deciphering the antigen specificities of antibodies by clustering their complementarity determining region sequences. mSystems 8, e00722-23 (2023); https://doi.org/10.1128/msystems.00722-23.
Abstract	Recent advances in adaptive immune receptor repertoire sequencing have provided abundant B cell receptor (BCR) sequences under various conditions, including vaccination and disease. However, determining target antigen and epitope specificity of the corresponding antibodies is a major challenge due to their exceptional sequence diversity. Here, we introduce a novel method to cluster antibodies sharing antigenic targets based on their complementarity determining region (CDR) sequences. Using the proposed method, we demonstrate that SARS-CoV-2 spike protein receptor-binding domain (RBD) binders and non-RBD binders from publicly available BCR data were classified correctly, with a cluster purity of 95%. These clusters were then leveraged for annotating unlabeled COVID-19 patient BCR data, enabling the discovery of novel anti-RBD antibodies. We further validated the method by clustering BCR repertoires obtained from single-cell immune profiling of diphtheria-tetanus-pertussis (DTP)-vaccinated donors. Antibody expression and antigen-binding assays demonstrated that the clusters exhibited 96% antigen purity, surpassing the apparent 82% purity achieved by assigning antigens to the same B cells using fluorescently labeled DTP antigen probes. Moreover, antibodies within certain clusters were found to possess neutralizing activity, suggesting that CDR clusters contain epitope-level information. Together, this study offers a simple approach for antigen- and epitope-specific BCR discovery that is reproducible, inexpensive, and applicable to a wide range of antigen targets.
Publisher	American Society for Microbiology
Source Title	mSystems
Volume (Issue)	8(6)
Page	e00722-23
Date of Issued	2023-12-21
Language	English
Handle URL	https://hdl.handle.net/11094/93389
eISSN	23795077
Relation.isIdenticalTo	DOI (Publisher Version) https://doi.org/10.1128/msystems.00722-23
Access Rights	open access
CopyRight	This article is licensed under a Creative Commons Attribution 4.0 International License.
oaire:version	Version of Record
Category	学術雑誌論文 Journal Article

Resource Type	journal article
Local Type	Journal Article
DCMI Type	Text
DCTERMS.bibliographicCitation	mSystems. 2023, 8(6), p. e00722-23
DC.title	Deciphering the antigen specificities of antibodies by clustering their complementarity determining region sequences
DC.creator	Saputri, Dianita S.
	Ismanto, Hendra S.
	Nugraha, Dendi K.
	Xu, Zichang
	Horiguchi, Yasuhiko
	Sakakibara, Shuhei
	Standley, Daron M.
	Cristea, Ileana M.
DC.publisher	American Society for Microbiology
DC.language' scheme='DCTERMS.RFC1766	English
DC.type' scheme='DCTERMS.DCMIType	Text
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2023-12-21
DC.identifier	https://doi.org/10.1128/msystems.00722-23
DC.subject	antibody
	antigen-specific
	B cell receptor
	clustering
	diphtheria
	pertussis
	tetanus
	repertoire
	SARS-CoV-2
	single-cell immune profile
DC.description	Saputri Dianita S., Ismanto Hendra S., Nugraha Dendi K., et al. Deciphering the antigen specificities of antibodies by clustering their complementarity determining region sequences. mSystems 8, e00722-23 (2023); https://doi.org/10.1128/msystems.00722-23.
DCTERMS.abstract	Recent advances in adaptive immune receptor repertoire sequencing have provided abundant B cell receptor (BCR) sequences under various conditions, including vaccination and disease. However, determining target antigen and epitope specificity of the corresponding antibodies is a major challenge due to their exceptional sequence diversity. Here, we introduce a novel method to cluster antibodies sharing antigenic targets based on their complementarity determining region (CDR) sequences. Using the proposed method, we demonstrate that SARS-CoV-2 spike protein receptor-binding domain (RBD) binders and non-RBD binders from publicly available BCR data were classified correctly, with a cluster purity of 95%. These clusters were then leveraged for annotating unlabeled COVID-19 patient BCR data, enabling the discovery of novel anti-RBD antibodies. We further validated the method by clustering BCR repertoires obtained from single-cell immune profiling of diphtheria-tetanus-pertussis (DTP)-vaccinated donors. Antibody expression and antigen-binding assays demonstrated that the clusters exhibited 96% antigen purity, surpassing the apparent 82% purity achieved by assigning antigens to the same B cells using fluorescently labeled DTP antigen probes. Moreover, antibodies within certain clusters were found to possess neutralizing activity, suggesting that CDR clusters contain epitope-level information. Together, this study offers a simple approach for antigen- and epitope-specific BCR discovery that is reproducible, inexpensive, and applicable to a wide range of antigen targets.
DC.rights	This article is licensed under a Creative Commons Attribution 4.0 International License.
DC.format	93389
citation_title	Deciphering the antigen specificities of antibodies by clustering their complementarity determining region sequences
citation_author	Saputri, Dianita S.
	Ismanto, Hendra S.
	Nugraha, Dendi K.
	Xu, Zichang
	Horiguchi, Yasuhiko
	Sakakibara, Shuhei
	Standley, Daron M.
	Cristea, Ileana M.
citation_publisher	American Society for Microbiology
citation_language	English
citation_date	2023-12-21
citation_journal_title	mSystems
citation_volume	8
citation_issue	6
citation_firstpage	e00722-23
citation_doi	https://doi.org/10.1128/msystems.00722-23
citation_public_url	https://hdl.handle.net/11094/93389

Deciphering the antigen specificities of antibodies by clustering their complementarity determining region sequences

Link to primary information

Item Information

Show details