Abstract
Mesenchymal stem or stromal cells (MSCs) are of great interest in biomedical sciences and disease treatment because of their multipotency and wide range of applications for tissue repair and suppression of the immune system. Proteomic analysis of these unique cells has contributed to the identification of important pathways utilized by MSCs to differentiate into distinct tissues as well as important proteins responsible for their special function in vivo and in vitro. However, comparison of proteomic studies in MSCs still suffers from the heterogeneity of MSC preparations. In addition, as proteomics technology advances, several studies can be revisited in order to increase the depth of analysis and, therefore, elucidate more refined mechanisms involved in MSC functionalities. Here, we present detailed protocols to obtain MSCs, as well as protocols to perform in-depth profiling and quantification of alterations in MSC proteomes.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Caplan AI (1991) Mesenchymal stem cells. J Orthop Res 9:641–650
Bianco P (2014) Stem cells and bone: a historical perspective. Bone 70:2–9
Pittenger MF, Mackay AM, Beck SC et al (1999) Multilineage potential of adult human mesenchymal stem cells. Science 284: 143–147
Jiang Y, Jahagirdar BN, Reinhardt RL et al (2002) Pluripotency of mesenchymal stem cells derived from adult marrow. Nature 418:41–49
da Silva Meirelles L, Chagastelles PC, Nardi NB (2006) Mesenchymal stem cells reside in virtually all post-natal organs and tissues. J Cell Sci 119:2204–2213
Lavoie JR, Rosu-Myles M (2013) Uncovering the secretes of mesenchymal stem cells. Biochimie 95:2212–2221
Makridakis M, Roubelakis MG, Vlahou A (2013) Stem cells: insights into the secretome. Biochim Biophys Acta 1834:2380–2384
Faça VM (2012) Human mesenchymal stromal cell proteomics: contribution for identification of new markers and targets for medicine intervention. Expert Rev Proteomics 9: 217–230
Granéli C, Thorfve A, Ruetschi U et al (2014) Novel markers of osteogenic and adipogenic differentiation of human bone marrow stromal cells identified using a quantitative proteomics approach. Stem Cell Res 12:153–165
Ishihara T, Kakiya K, Takahashi K et al (2014) Discovery of novel differentiation markers in the early stage of chondrogenesis by glycoform-focused reverse proteomics and genomics. Biochim Biophys Acta 1840:645–655
Miranda HC, Herai RH, Thomé CH et al (2012) A quantitative proteomic and transcriptomic comparison of human mesenchymal stem cells from bone marrow and umbilical cord vein. Proteomics 12:2607–2617
Rocha B, Calamia V, Casas V et al (2014) Secretome analysis of human mesenchymal stem cells undergoing chondrogenic differentiation. J Proteome Res 13:1045–1054
Choi YH, Kurtz A, Stamm C (2011) Mesenchymal stem cells for cardiac cell therapy. Hum Gene Ther 22:3–17
Cox J, Mann M (2011) Quantitative, high-resolution proteomics for data-driven systems biology. Annu Rev Biochem 80:273–299
Bensimon A, Heck AJ, Aebersold R (2012) Mass spectrometry-based proteomics and network biology. Annu Rev Biochem 81: 379–405
Kim JM, Kim J, Kim YH et al (2013) Comparative secretome analysis of human bone marrow-derived mesenchymal stem cells during osteogenesis. J Cell Physiol 228:216–224
Faca V, Pitteri SJ, Newcomb L et al (2007) Contribution of protein fractionation to depth of analysis of the serum and plasma proteomes. J Proteome Res 6:3558–3565
Faça VM, Ventura AP, Fitzgibbon MP et al (2008) Proteomic analysis of ovarian cancer cells reveals dynamic processes of protein secretion and shedding of extra-cellular domains. PLoS One 3:e2425
Emanuelsson O, Brunak S, von Heijne G et al (2007) Locating proteins in the cell using TargetP, SignalP and related tools. Nat Protoc 2:953–971
Petersen TN, Brunak S, von Heijne G et al (2011) SignalP 4.0: discriminating signal peptides from transmembrane regions. Nat Methods 8:785–786
Faca V, Coram M, Phanstiel D et al (2006) Quantitative analysis of acrylamide labeled serum proteins by LC-MS/MS. J Proteome Res 5:2009–2018
Rauch A, Bellew M, Eng J et al (2006) Computational Proteomics Analysis System (CPAS): an extensible, open-source analytic system for evaluating and publishing proteomic data and high throughput biological experiments. J Proteome Res 5:112–121
Keller A, Nesvizhskii AI, Kolker E et al (2002) Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal Chem 74:5383–5392
Nesvizhskii AI, Keller A, Kolker E et al (2003) A statistical model for identifying proteins by tandem mass spectrometry. Anal Chem 75: 4646–4658
Acknowledgements
This work was supported by the São Paulo State Research Foundation, Brazil, grant 2011/09740-1; CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico), Brazil, Investigator Fellowship grant 301570/2011-6, Center for Integrative Systems Biology, University of São Paulo, grant 12.1.17598.1.3, and Center for Cell-Based Therapy (CTC-CEPID), grant 2013/08135-2.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media New York
About this protocol
Cite this protocol
Faça, V.M., Orellana, M.D., Greene, L.J., Covas, D.T. (2016). Proteomic Analysis of Mesenchymal Stem Cells. In: Gnecchi, M. (eds) Mesenchymal Stem Cells. Methods in Molecular Biology, vol 1416. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3584-0_31
Download citation
DOI: https://doi.org/10.1007/978-1-4939-3584-0_31
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-3582-6
Online ISBN: 978-1-4939-3584-0
eBook Packages: Springer Protocols