Advertisement

Approaches to Characterize Organelle, Compartment, or Structure Purity

  • Stefanie J. Mueller
  • Sebastian N. W. Hoernstein
  • Ralf ReskiEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1511)

Abstract

The function of subcellular structures is defined by their specific sets of proteins, making subcellular protein localization one of the most important topics in organelle research. To date, many organelle proteomics workflows involve the (partial) purification of the desired subcellular structure and the subsequent analysis of the proteome using tandem mass spectrometry (MS/MS). This chapter gives an overview of the methods that have been used to assay the purity and enrichment of subcellular structures, with an emphasis on quantitative proteomics using differently enriched subcellular fractions. We introduce large-scale-based criteria for assignment of proteins to subcellular structures and describe in detail the use of 15N metabolic labeling in moss to characterize plastid and mitochondrial proteomes.

Key words

Metabolic labeling Quantitative proteomics Physcomitrella patens Mitochondria Plastid Compartment marker Density gradient purification 

Notes

Acknowledgments

This work was supported by the Excellence Initiative of the German federal and state governments (EXC294 to R.R.). We thank Anne Katrin Prowse for the proofreading of the manuscript.

References

  1. 1.
    Agrawal GK, Bourguignon J, Rolland N et al (2011) Plant organelle proteomics: collaborating for optimal cell function. Mass Spectrom Rev 30:772–853PubMedGoogle Scholar
  2. 2.
    Heazlewood JL, Tonti-Filippini JS, Gout AM et al (2004) Experimental analysis of the Arabidopsis mitochondrial proteome highlights signaling and regulatory components, provides assessment of targeting prediction programs, and indicates plant-specific mitochondrial proteins. Plant Cell 16:241–256CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Carrie C, Small I (2013) A reevaluation of dual-targeting of proteins to mitochondria and chloroplasts. Biochim Biophys Acta 1833:253–259CrossRefPubMedGoogle Scholar
  4. 4.
    Estavillo GM, Verhertbruggen Y, Scheller HV, et al (2014) Isolation of the plant cytosolic fraction for proteomic analysis. In: Plant proteomics: methods and protocols, 2nd edn. 1072:453–467. Humana Press, New York CityGoogle Scholar
  5. 5.
    Muhlhaus T, Weiss J, Hemme D et al (2011) Quantitative shotgun proteomics using a uniform 15N-labeled standard to monitor proteome dynamics in time course experiments reveals new insights into the heat stress response of Chlamydomonas reinhardtii. Mol Cell Proteomics 10(M110):004739PubMedGoogle Scholar
  6. 6.
    Mackenzie SA (2005) Plant organellar protein targeting: a traffic plan still under construction. Trends Cell Biol 15:548–554CrossRefPubMedGoogle Scholar
  7. 7.
    Lilley KS, Dunkley TP (2008) Determination of genuine residents of plant endomembrane organelles using isotope tagging and multivariate statistics. Methods Mol Biol 432:373–387CrossRefPubMedGoogle Scholar
  8. 8.
    Lundquist PK, Poliakov A, Bhuiyan NH et al (2012) The functional network of the Arabidopsis plastoglobule proteome based on quantitative proteomics and genome-wide coexpression analysis. Plant Physiol 158:1172–1192CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Bindschedler LV, Cramer R (2011) Quantitative plant proteomics. Proteomics 11:756–775CrossRefPubMedGoogle Scholar
  10. 10.
    van Wijk KJ, Baginsky S (2011) Plastid proteomics in higher plants: current state and future goals. Plant Physiol 155:1578–1588CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Douce R (1985) Mitochondria in higher plants. Structure, function and biogenesis. Academic Press, New YorkGoogle Scholar
  12. 12.
    Taylor NL, Stroher E, Millar AH (2014) Arabidopsis organelle isolation and characterization. Arabidopsis Protocols, 3rd edn 1062: 551–572. Humana Press, New York CityGoogle Scholar
  13. 13.
    Lang EGE, Mueller SJ, Hoernstein SNW et al (2011) Simultaneous isolation of pure and intact chloroplasts and mitochondria from moss as the basis for sub-cellular proteomics. Plant Cell Rep 30:205–215CrossRefPubMedGoogle Scholar
  14. 14.
    Salvi D, Rolland N, Joyard J et al (2008) Assessment of organelle purity using antibodies and specific assays: the example of the chloroplast envelope. Methods Mol Biol 432:345–356CrossRefPubMedGoogle Scholar
  15. 15.
    Ito J, Batth TS, Petzold CJ et al (2011) Analysis of the Arabidopsis cytosolic proteome highlights subcellular partitioning of central plant metabolism. J Proteome Res 10:1571–1582CrossRefPubMedGoogle Scholar
  16. 16.
    Huang S, Taylor NL, Narsai R et al (2010) Functional and composition differences between mitochondrial complex II in Arabidopsis and rice are correlated with the complex genetic history of the enzyme. Plant Mol Biol 72:331–342CrossRefPubMedGoogle Scholar
  17. 17.
    Mueller SJ, Lang D, Hoernstein SN et al (2014) Quantitative analysis of the mitochondrial and plastid proteomes of the moss Physcomitrella patens reveals protein macrocompartmentation and microcompartmentation. Plant Physiol 164:2081–2095CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Huang S, Jacoby RP, Millar AH et al (2014) Plant mitochondrial proteomics. In: Plant Proteomics: methods and protocols, 2nd edn. 1072: 499–525Google Scholar
  19. 19.
    Yan W, Hwang D, Aebersold R (2008) Quantitative proteomic analysis to profile dynamic changes in the spatial distribution of cellular proteins. Methods Mol Biol 432:389–401CrossRefPubMedGoogle Scholar
  20. 20.
    Marelli M, Nesvizhskii AI, Aitchison JD (2008) Identifying bona fide components of an organelle by isotope-coded labeling of subcellular fractions : an example in peroxisomes. Methods Mol Biol 432:357–371CrossRefPubMedGoogle Scholar
  21. 21.
    Matthes A, Kohl K, Schulze WX (2014) SILAC and alternatives in studying cellular proteomes of plants. Methods Mol Biol 1188:65–83CrossRefPubMedGoogle Scholar
  22. 22.
    Tan Y-F, Millar AH, Tayor NL (2012) Components of mitochondrial oxidative phosphorylation vary in abundance following exposure to cold and chemical stresses. J Proteome Res 11:3860–3879CrossRefPubMedGoogle Scholar
  23. 23.
    Gouw JW, Tops BBJ, Krijgsveld J (2011) Metabolic labeling of model organisms using heavy nitrogen (15N). Gel-free proteomics: methods and protocols 753: 29–42. Humana Press, New York CityGoogle Scholar
  24. 24.
    Nelson CJ, Alexova R, Jacoby RP et al (2014) Proteins with high turnover rate in barley leaves estimated by proteome analysis combined with in planta isotope labeling. Plant Physiol 166:91–108CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Müller SJ, Gütle DD, Jacquot J-P et al (2015) Can mosses serve as model organisms for forest research. Annals of Forest Science. doi: 10.1007/s13595-015-0468-7Google Scholar
  26. 26.
    Rensing SA, Lang D, Zimmer AD et al (2008) The Physcomitrella genome reveals evolutionary insights into the conquest of land by plants. Science 319:64–69CrossRefPubMedGoogle Scholar
  27. 27.
    Schulte J, Reski R (2004) High throughput cryopreservation of 140,000 Physcomitrella patens mutants. Plant Biol (Stuttg) 6:119–127CrossRefGoogle Scholar
  28. 28.
    Schween G, Hohe A, Koprivova A et al (2003) Effects of nutrients, cell density and culture techniques on protoplast regeneration and early protonema development in a moss, Physcomitrella patens. J Plant Physiol 160:209–212CrossRefPubMedGoogle Scholar
  29. 29.
    Mason CB, Matthews S, Bricker TM et al (1991) Simplified procedure for the isolation of intact chloroplasts from Chlamydomonas reinhardtii. Plant Physiol 97(4):1576–1580CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Fraley C, Raftery AE (2003) Enhanced model-based clustering, density estimation, and discriminant analysis software: MCLUST. J Classif 20:263–286CrossRefGoogle Scholar
  31. 31.
    Hohe A, Decker EL, Gorr G et al (2002) Tight control of growth and cell differentiation in photoautotrophically growing moss (Physcomitrella patens) bioreactor cultures. Plant Cell Rep 20:1135–1140CrossRefGoogle Scholar
  32. 32.
    Wessel D, Flugge UI (1984) A method for the quantitative recovery of protein in dilute-solution in the presence of detergents and lipids. Anal Biochem 138:141–143CrossRefPubMedGoogle Scholar
  33. 33.
    Giege P, Heazlewood JL, Roessner-Tunali U et al (2003) Enzymes of glycolysis are functionally associated with the mitochondrion in Arabidopsis cells. Plant Cell 15:2140–2151CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Wieckowski MR, Giorgi C, Lebiedzinska M et al (2009) Isolation of mitochondria-associated membranes and mitochondria from animal tissues and cells. Nat Protoc 4:1582–1590CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Stefanie J. Mueller
    • 1
  • Sebastian N. W. Hoernstein
    • 1
  • Ralf Reski
    • 1
    • 2
    • 3
    • 4
    Email author
  1. 1.Plant Biotechnology, Faculty of BiologyUniversity of FreiburgFreiburgGermany
  2. 2.BIOSS Centre for Biological Signalling StudiesUniversity of FreiburgFreiburgGermany
  3. 3.FRIAS Freiburg Institute for Advanced StudiesUniversity of FreiburgFreiburgGermany
  4. 4.TIP Trinational Institute for Plant ResearchUniversity of FreiburgFreiburgGermany

Personalised recommendations