Abstract
The vast repertoire of immunoglobulins produced by the immune system is a consequence of the huge amount of antigens to which we are exposed every day. The diversity of these immunoglobulins is due to different mechanisms (including VDJ recombination, somatic hypermutation, and antigen selection). Understanding how the immune system is capable of generating this diversity and which are the molecular bases of the composition of immunoglobulins are key challenges in the immunological field. During the last decades, several techniques have emerged as promising strategies to achieve these goals, but it is their combination which appears to be the fruitful solution for increasing the knowledge about human cellular and serum antibody repertoires.
In this chapter, we address the diverse strategies focused on the analysis of immunoglobulin repertoires as well as the characterization of the genomic and peptide sequences. Moreover, the advantages of combining various –omics approaches are discussed through review different published studies, showing the benefits in clinical areas.
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References
Bandeira, N., et al. (2008). Automated de novo protein sequencing of monoclonal antibodies. Nature Biotechnology, 26(12), 1336–1338.
Castellana, N., & Bafna, V. (2010). Proteogenomics to discover the full coding content of genomes: A computational perspective. Journal of Proteomics, 73(11), 2124–2135. Available at: http://dx.doi.org/10.1016/j.jprot.2010.06.007.
Castellana, N. E., et al. (2011). Resurrection of a clinical antibody: Template proteogenomic de novo proteomic sequencing and reverse engineering of an anti-lymphotoxin-alpha antibody. Proteomics, 11(3), 395–405.
Christiansen, M., et al. (2007). Chapter 4: Maritime transportation. In Handbooks in operations research and management science, 14(C) (pp. 189–284). Amsterdam: Elsevier.
Díez, P., et al. (2015). Integration of Proteomics and Transcriptomics data sets for the analysis of B-cell lymphoma cell line in the context of the Chromosome-Centric Human Proteome Project. J. Proteome Res. 14(9):3530–40.
de Groot, A., et al. (2014). RNA sequencing and proteogenomics reveal the importance of leaderless mRNAs in the radiation-tolerant bacterium Deinococcus deserti. Genome Biology and Evolution, 6(4), 932–948.
Elias, J. E., & Gygi, S. P. (2010). Target-decoy search strategy for mass spectrometry-based proteomics. Methods in Molecular Biology (Clifton, NJ), 604(2), 55–71.
Fanayan, S., et al. (2013). Proteogenomic analysis of human colon carcinoma cell lines LIM1215, LIM1899, and LIM2405. Journal of Proteome Research, 12, 1732–1742.
Faulkner, S., Dun, M. D., & Hondermarck, H. (2015). Proteogenomics: Emergence and promise. Cellular and Molecular Life Sciences, 72(5), 953–957. Available at: http://link.springer.com/10.1007/s00018-015-1837-y.
Fullwood, M. J., et al. (2009). Next-generation DNA sequencing of paired-end tags (PET) for transcriptome and genome analyses. Genome Research, 19(4), 521–532.
Günther, O. P., et al. (2014). Novel multivariate methods for integration of genomics and proteomics data: Applications in a kidney transplant rejection study. Omics: A Journal of Integrative Biology, 18(11), 682–695.
Haider, S., & Pal, R. (2013). Integrated analysis of transcriptomic and proteomic data. Current Genomics, 14(2), 91–110.
Heck, A. J. R. (2008). Native mass spectrometry: A bridge between interactomics and structural biology. Nature Methods, 5(11), 927–933.
Hert, D. G., Fredlake, C. P., & Barron, A. E. (2008). Advantages and limitations of next-generation sequencing technologies: A comparison of electrophoresis and non-electrophoresis methods. Electrophoresis, 29, 4618–4626.
Hozumi, N., & Tonegawa, S. (1976). Evidence for somatic rearrangement of immunoglobulin genes coding for variable and constant regions. Proceedings of the National Academy of Sciences of the United States of America, 73(10), 3628–3632.
Hughes, C., Ma, B., & Lajoie, G. A. (2010). De novo sequencing methods in proteomics. Methods in Molecular Biology (Clifton, NJ), 604, 105–121.
Jordan, M. A., & Baxter, A. G. (2008). Quantitative and qualitative approaches to GOD: The first 10 years of the clonal selection theory. Immunology and Cell Biology, 86(1), 72–9.
Kostareli, E., et al. (2012). Immunoglobulin gene repertoire in chronic lymphocytic leukemia: Insight into antigen selection and microenvironmental interactions. Mediterranean Journal of Hematology and Infectious Diseases, 4(1), e2012052.
Lavinder, J. J., et al. (2015). Next-generation sequencing and protein mass spectrometry for the comprehensive analysis of human cellular and serum antibody repertoires. Current Opinion in Chemical Biology, 24, 112–120.
Lefranc, M.-P., et al. (2015). IMGT®, the international ImMunoGeneTics information system® 25 years on. Nucleic Acids Research, 43(Database issue), D413–D422.
Li, Z., et al. (2004). The generation of antibody diversity through somatic hypermutation and class switch recombination. Genes and Development, 18(1), 1–11.
Lomakin, Y. a., et al. (2014). Heavy-light chain interrelations of MS-associated immunoglobulins probed by deep sequencing and rational variation. Molecular Immunology, 62(2), 305–314.
Lorenzen, K., et al. (2007). Structural biology of RNA polymerase III: Mass spectrometry elucidates subcomplex architecture. Structure (London, England: 1993), 15(10), 1237–1245.
Mathé, C., et al. (2002). Current methods of gene prediction, their strengths and weaknesses. Nucleic Acids Research, 30(19), 4103–4117.
McRedmond, J. P., et al. (2004). Integration of proteomics and genomics in platelets: A profile of platelet proteins and platelet-specific genes. Molecular & Cellular Proteomics, 3(2), 133–144.
Nesvizhskii, A. I. (2014). Proteogenomics: Concepts, applications and computational strategies. Nature Methods, 11(11), 1114–1125. Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4392723&tool=pmcentrez&rendertype=abstract.
Pham, V., et al. (2006). De novo proteomic sequencing of a monoclonal antibody raised against OX40 ligand. Analytical Biochemistry, 352(1), 77–86.
Ralph, D., & Matsen, F. A. (2015). Consistency of VDJ rearrangement and substitution parameters enables accurate B cell receptor sequence annotation, arXiv(q-bio.PE),1–40.
Reiter, L., et al. (2009). Protein identification false discovery rates for very large proteomics data sets generated by tandem mass spectrometry. Molecular & Cellular Proteomics, 8(11), 2405–2417.
Resemann, A., et al. (2010). Top-down de novo protein sequencing of a 13.6 kDa camelid single heavy chain antibody by matrix-assisted laser desorption ionization-time-of-flight/time-of-flight mass spectrometry. Analytical Chemistry, 82(8), 3283–3292.
Roberts, A., et al. (2011). Identification of novel transcripts in annotated genomes using RNA-Seq. Bioinformatics, 27(17), 2325–2329.
Rosati, S., et al. (2012). Exploring an orbitrap analyzer for the characterization of intact antibodies by native mass spectrometry. Angewandte Chemie – International Edition, 51(52), 12992–12996.
Schroeder, H. W., & Cavacini, L. (2013). Structure and function of immunoglobulins. Journal Allergy Clinical Immunology, 125(125), S41–S52.
Teh, S.-L., et al. (2011). Development of expressed sequence tag resources for Vanda Mimi Palmer and data mining for EST-SSR. Molecular Biology Reports, 38(6), 3903–3909.
van Duijn, E. (2010). Current limitations in native mass spectrometry based structural biology. Journal of the American Society for Mass Spectrometry, 21(6), 971–978.
Winnenburg, R., et al. (2008). PHI-base update: Additions to the pathogen – Host interaction database. Database, 36(October 2007), 572–576.
Woo, S., et al. (2014). Proteogenomic database construction driven from large scale RNA-Seq data. Journal of Proteome Research, 13(1), 21–28.
Ye, X., Blonder, J., & Veenstra, T. D. (2009). Targeted proteomics for validation of biomarkers in clinical samples. Briefings in Functional Genomics & Proteomics, 8(2), 126–135.
Zhang, B., et al. (2014). Proteogenomic characterization of human colon and rectal cancer. Nature, 513(7518), 382–387.
Zhang, J., et al. (2015). Altered long non-coding RNA transcriptomic profiles in brain microvascular endothelium after cerebral ischemia. Experimental Neurology, 277, 162–170.
Zhu, W., Lomsadze, A., & Borodovsky, M. (2010). Ab initio gene identification in metagenomic sequences. Nucleic Acids Research, 38(12), 1–15.
Acknowledgments
We gratefully acknowledge financial support from the Carlos III Health Institute of Spain (ISCIII, FIS PI11/02114, FIS PI14/01538), Fondos FEDER (EU) and Junta Castilla-León. BIO/SA07/15; Fundación Samuel Solórzano FS/23-2015. The Proteomics Unit belongs to ProteoRed, PRB2-ISCIII, FONDOS FEDER, supported by grant PT13/0001. P.D. is supported by a JCYL-EDU/346/2013 Ph.D. scholarship.
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Díez, P., Fuentes, M. (2016). Proteogenomics for the Comprehensive Analysis of Human Cellular and Serum Antibody Repertoires. In: Végvári, Á. (eds) Proteogenomics. Advances in Experimental Medicine and Biology, vol 926. Springer, Cham. https://doi.org/10.1007/978-3-319-42316-6_10
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DOI: https://doi.org/10.1007/978-3-319-42316-6_10
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