Methods for Sequence and Structural Analysis of B and T Cell Receptor Repertoires

Overview

Journal Comput Struct Biotechnol J

Specialty Biotechnology

Date 2020 Aug 18

PMID 32802272

Citations 18

Authors

Shunsuke Teraguchi

Dianita S Saputri

Mara Anais Llamas-Covarrubias

Ana Davila

Diego Diez

Sedat Aybars Nazlica

John Rozewicki

Hendra S Ismanto

Jan Wilamowski

Jiaqi Xie

Zichang Xu

Martin de Jesus Loza-Lopez

Floris J van Eerden

Songling Li

Daron M Standley

Affiliations

Soon will be listed here.

Abstract

B cell receptors (BCRs) and T cell receptors (TCRs) make up an essential network of defense molecules that, collectively, can distinguish self from non-self and facilitate destruction of antigen-bearing cells such as pathogens or tumors. The analysis of BCR and TCR repertoires plays an important role in both basic immunology as well as in biotechnology. Because the repertoires are highly diverse, specialized software methods are needed to extract meaningful information from BCR and TCR sequence data. Here, we review recent developments in bioinformatics tools for analysis of BCR and TCR repertoires, with an emphasis on those that incorporate structural features. After describing the recent sequencing technologies for immune receptor repertoires, we survey structural modeling methods for BCR and TCRs, along with methods for clustering such models. We review downstream analyses, including BCR and TCR epitope prediction, antibody-antigen docking and TCR-peptide-MHC Modeling. We also briefly discuss molecular dynamics in this context.

Citing Articles

Pan-cancer secreted proteome and skeletal muscle regulation: insight from a proteogenomic data-driven knowledge base.

Parry T, Gilmore L, Khamoui A Funct Integr Genomics. 2025; 25(1):14.

PMID: 39812750 DOI: 10.1007/s10142-024-01524-7.

Clark E, Talatala E, Ye W, Davis R, Collins S, Hillel A Laryngoscope. 2024; 134(7):3245-3252.

PMID: 38450771 PMC: 11182723. DOI: 10.1002/lary.31376.

Identification of PLAC8 as a Potential Biomarker for the Diagnosis of Interstitial Cystitis.

Li P, Xu M, Zhang Z, Zhang X, Xie F, Zhang X Comb Chem High Throughput Screen. 2024; 27(13):1938-1947.

PMID: 38441011 DOI: 10.2174/0113862073273817231107050852.

SPLASH: A statistical, reference-free genomic algorithm unifies biological discovery.

Chaung K, Baharav T, Henderson G, Zheludev I, Wang P, Salzman J Cell. 2023; 186(25):5440-5456.e26.

PMID: 38065078 PMC: 10861363. DOI: 10.1016/j.cell.2023.10.028.

Improved prediction of MHC-peptide binding using protein language models.

Hashemi N, Hao B, Ignatov M, Paschalidis I, Vakili P, Vajda S Front Bioinform. 2023; 3:1207380.

PMID: 37663788 PMC: 10469926. DOI: 10.3389/fbinf.2023.1207380.

References

Kobayashi E, Mizukoshi E, Kishi H, Ozawa T, Hamana H, Nagai T . A new cloning and expression system yields and validates TCRs from blood lymphocytes of patients with cancer within 10 days. Nat Med. 2013; 19(11):1542-6. DOI: 10.1038/nm.3358. View

Glanville J, Huang H, Nau A, Hatton O, Wagar L, Rubelt F . Identifying specificity groups in the T cell receptor repertoire. Nature. 2017; 547(7661):94-98. PMC: 5794212. DOI: 10.1038/nature22976. View

Mashiach E, Schneidman-Duhovny D, Andrusier N, Nussinov R, Wolfson H . FireDock: a web server for fast interaction refinement in molecular docking. Nucleic Acids Res. 2008; 36(Web Server issue):W229-32. PMC: 2447790. DOI: 10.1093/nar/gkn186. View

Tay M, Poh C, Renia L, Macary P, Ng L . The trinity of COVID-19: immunity, inflammation and intervention. Nat Rev Immunol. 2020; 20(6):363-374. PMC: 7187672. DOI: 10.1038/s41577-020-0311-8. View

Rozewicki J, Li S, Amada K, Standley D, Katoh K . MAFFT-DASH: integrated protein sequence and structural alignment. Nucleic Acids Res. 2019; 47(W1):W5-W10. PMC: 6602451. DOI: 10.1093/nar/gkz342. View

Robbiani D, Gaebler C, Muecksch F, Lorenzi J, Wang Z, Cho A . Convergent antibody responses to SARS-CoV-2 in convalescent individuals. Nature. 2020; 584(7821):437-442. PMC: 7442695. DOI: 10.1038/s41586-020-2456-9. View

Li W, Godzik A . Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics. 2006; 22(13):1658-9. DOI: 10.1093/bioinformatics/btl158. View

Shirai H, Ikeda K, Yamashita K, Tsuchiya Y, Sarmiento J, Liang S . High-resolution modeling of antibody structures by a combination of bioinformatics, expert knowledge, and molecular simulations. Proteins. 2014; 82(8):1624-35. DOI: 10.1002/prot.24591. View

Leem J, Dunbar J, Georges G, Shi J, Deane C . ABodyBuilder: Automated antibody structure prediction with data-driven accuracy estimation. MAbs. 2016; 8(7):1259-1268. PMC: 5058620. DOI: 10.1080/19420862.2016.1205773. View

10.

Pittala S, Bailey-Kellogg C . Learning context-aware structural representations to predict antigen and antibody binding interfaces. Bioinformatics. 2020; 36(13):3996-4003. PMC: 7332568. DOI: 10.1093/bioinformatics/btaa263. View

11.

Sethna Z, Elhanati Y, Callan C, Walczak A, Mora T . OLGA: fast computation of generation probabilities of B- and T-cell receptor amino acid sequences and motifs. Bioinformatics. 2019; 35(17):2974-2981. PMC: 6735909. DOI: 10.1093/bioinformatics/btz035. View

12.

Kovaltsuk A, Raybould M, Wong W, Marks C, Kelm S, Snowden J . Structural diversity of B-cell receptor repertoires along the B-cell differentiation axis in humans and mice. PLoS Comput Biol. 2020; 16(2):e1007636. PMC: 7048297. DOI: 10.1371/journal.pcbi.1007636. View

13.

Nazarov V, Pogorelyy M, Komech E, Zvyagin I, Bolotin D, Shugay M . tcR: an R package for T cell receptor repertoire advanced data analysis. BMC Bioinformatics. 2015; 16:175. PMC: 4445501. DOI: 10.1186/s12859-015-0613-1. View

14.

Dalkas G, Rooman M . SEPIa, a knowledge-driven algorithm for predicting conformational B-cell epitopes from the amino acid sequence. BMC Bioinformatics. 2017; 18(1):95. PMC: 5301386. DOI: 10.1186/s12859-017-1528-9. View

15.

Afik S, Yates K, Bi K, Darko S, Godec J, Gerdemann U . Targeted reconstruction of T cell receptor sequence from single cell RNA-seq links CDR3 length to T cell differentiation state. Nucleic Acids Res. 2017; 45(16):e148. PMC: 5766189. DOI: 10.1093/nar/gkx615. View

16.

Bolotin D, Poslavsky S, Davydov A, Frenkel F, Fanchi L, Zolotareva O . Antigen receptor repertoire profiling from RNA-seq data. Nat Biotechnol. 2017; 35(10):908-911. PMC: 6169298. DOI: 10.1038/nbt.3979. View

17.

Lindeman I, Emerton G, Mamanova L, Snir O, Polanski K, Qiao S . BraCeR: B-cell-receptor reconstruction and clonality inference from single-cell RNA-seq. Nat Methods. 2018; 15(8):563-565. DOI: 10.1038/s41592-018-0082-3. View

18.

Yokota R, Kaminaga Y, Kobayashi T . Quantification of Inter-Sample Differences in T-Cell Receptor Repertoires Using Sequence-Based Information. Front Immunol. 2017; 8:1500. PMC: 5694755. DOI: 10.3389/fimmu.2017.01500. View

19.

Setliff I, Shiakolas A, Pilewski K, Murji A, Mapengo R, Janowska K . High-Throughput Mapping of B Cell Receptor Sequences to Antigen Specificity. Cell. 2019; 179(7):1636-1646.e15. PMC: 7158953. DOI: 10.1016/j.cell.2019.11.003. View

20.

Bourquard T, Musnier A, Puard V, Tahir S, Ayoub M, Jullian Y . MAbTope: A Method for Improved Epitope Mapping. J Immunol. 2018; 201(10):3096-3105. DOI: 10.4049/jimmunol.1701722. View