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Analysis of Yeast Peroxisomes via Spatial Proteomics

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Peroxisomes

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2643))

Abstract

Peroxisomes are ubiquitous organelles with essential functions in numerous cellular processes such as lipid metabolism, detoxification of reactive oxygen species, and signaling. Knowledge of the peroxisomal proteome including multi-localized proteins and, most importantly, changes of its composition induced by altering cellular conditions or impaired peroxisome biogenesis and function is of paramount importance for a holistic view on peroxisomes and their diverse functions in a cellular context. In this chapter, we provide a spatial proteomics protocol specifically tailored to the analysis of the peroxisomal proteome of baker’s yeast that enables the definition of the peroxisomal proteome under distinct conditions and to monitor dynamic changes of the proteome including the relocation of individual proteins to a different cellular compartment. The protocol comprises subcellular fractionation by differential centrifugation followed by Nycodenz density gradient centrifugation of a crude peroxisomal fraction, quantitative mass spectrometric measurements of subcellular and density gradient fractions, and advanced computational data analysis, resulting in the establishment of organellar maps on a global scale.

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References

  1. Islinger M, Voelkl A, Fahimi HD, Schrader M (2018) The peroxisome: an update on mysteries 2.0. Histochem Cell Biol 150:443–471

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Kunze M, Pracharoenwattana I, Smith SM, Hartig A (2006) A central role for the peroxisomal membrane in glyoxylate cycle function. Biochim Biophys Acta 1763:1441–1452

    Article  CAS  PubMed  Google Scholar 

  3. Smith JJ, Aitchison JD (2013) Peroxisomes take shape. Nat Rev Mol Cell Biol 14:803–817

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Wanders RJA, Waterham HR (2006) Biochemistry of mammalian peroxisomes revisited. Annu Rev Biochem 75:295–332

    Article  CAS  PubMed  Google Scholar 

  5. Schummer A, Maier R, Gabay-Maskit S et al (2020) Pex14p phosphorylation modulates import of citrate synthase 2 into peroxisomes in Saccharomyces cerevisiae. Front Cell Dev Biol 8:549451

    Article  PubMed  PubMed Central  Google Scholar 

  6. Waterham HR, Ferdinandusse S, Wanders RJA (2016) Human disorders of peroxisome metabolism and biogenesis. Biochim Biophys Acta, Mol Cell Res 1863:922–933

    Article  CAS  PubMed  Google Scholar 

  7. Lingner T, Kataya AR, Antonicelli GE et al (2011) Identification of novel plant peroxisomal targeting signals by a combination of machine learning methods and in vivo subcellular targeting analyses. Plant Cell 23:1556–1572

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Emanuelsson O, Elofsson A, von Heijne G, Cristóbal S (2003) In silico prediction of the peroxisomal proteome in fungi, plants and animals. J Mol Biol 330:443–456

    Article  CAS  PubMed  Google Scholar 

  9. Nötzel C, Lingner T, Klingenberg H, Thoms S (2016) Identification of new fungal peroxisomal matrix proteins and revision of the PTS1 consensus. Traffic 17:1110–1124

    Article  PubMed  Google Scholar 

  10. Freitag J, Stehlik T, Stiebler AC, Bölker M (2018) The obvious and the hidden: prediction and function of fungal peroxisomal matrix proteins. Subcell Biochem 89:139–155

    Article  CAS  PubMed  Google Scholar 

  11. Yifrach E, Holbrook-Smith D, Bürgi J, et al (2021) Systematic multi-level analysis of an organelle proteome reveals new peroxisomal functions. bioRxiv 2021.12.08.471723

    Google Scholar 

  12. Schäfer H, Nau K, Sickmann A et al (2001) Identification of peroxisomal membrane proteins of Saccharomyces cerevisiae by mass spectrometry. Electrophoresis 22:2955–2968

    Article  PubMed  Google Scholar 

  13. Kikuchi M, Hatano N, Yokota S et al (2004) Proteomic analysis of rat liver peroxisome. Presence of peroxisome-specific isozyme of Lon protease. J Biol Chem 279:421–428

    Article  CAS  PubMed  Google Scholar 

  14. Yang X, Edward Purdue P, Lazarow PB (2001) Eci1p uses a PTS1 to enter peroxisomes: either its own or that of a partner, Dci1p. Eur J Cell Biol 80:126–138

    Article  CAS  PubMed  Google Scholar 

  15. Effelsberg D, Cruz-Zaragoza LD, Tonillo J et al (2015) Role of Pex21p for piggyback import of Gpd1p and Pnc1p into peroxisomes of Saccharomyces cerevisiae. J Biol Chem 290:25333–25342

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Shai N, Schuldiner M, Zalckvar E (2016) No peroxisome is an island – peroxisome contact sites. Biochim Biophys Acta, Mol Cell Res 1863:1061–1069

    Article  CAS  PubMed  Google Scholar 

  17. Marelli M, Smith JJ, Jung S et al (2004) Quantitative mass spectrometry reveals a role for the GTPase Rho1p in actin organization on the peroxisome membrane. J Cell Biol 167:1099–1112

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Islinger M, Lüers GH, Ka WL et al (2007) Rat liver peroxisomes after fibrate treatment: a survey using quantitative mass spectrometry. J Biol Chem 282:23055–23069

    Article  CAS  PubMed  Google Scholar 

  19. Wiese S, Gronemeyer T, Ofman R et al (2007) Proteomics characterization of mouse kidney peroxisomes by tandem mass spectrometry and protein correlation profiling. Mol Cell Proteomics 6:2045–2057

    Article  CAS  PubMed  Google Scholar 

  20. Wiese S, Gronemeyer T, Brites P et al (2012) Comparative profiling of the peroxisomal proteome of wildtype and Pex7 knockout mice by quantitative mass spectrometry. Int J Mass Spectrom 312:30–40

    Article  CAS  Google Scholar 

  21. Gronemeyer T, Wiese S, Ofman R et al (2013) The proteome of human liver peroxisomes: identification of five new peroxisomal constituents by a label-free quantitative proteomics survey. PLoS One 8:e57395

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Christopher JA, Stadler C, Martin CE et al (2021) Subcellular proteomics. Nat Rev Method Primers 1:1–24

    Article  Google Scholar 

  23. Gurvitz A, Rottensteiner H (2006) The biochemistry of oleate induction: transcriptional upregulation and peroxisome proliferation. Biochim Biophys Acta 1763:1392–1402

    Article  CAS  PubMed  Google Scholar 

  24. Thompson A, Schäfer J, Kuhn K et al (2003) Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS. Anal Chem 75:1895–1904

    Article  CAS  PubMed  Google Scholar 

  25. Itzhak DN, Davies C, Tyanova S et al (2017) A mass spectrometry-based approach for mapping protein subcellular localization reveals the spatial proteome of mouse primary neurons. Cell Rep 20:2706–2718

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Dunkley TPJ, Watson R, Griffin JL et al (2004) Localization of organelle proteins by isotope tagging (LOPIT). Mol Cell Proteomics 3:1128–1134

    Article  CAS  PubMed  Google Scholar 

  27. Mulvey CM, Breckels LM, Geladaki A et al (2017) Using hyperLOPIT to perform high-resolution mapping of the spatial proteome. Nat Protoc 12:1110–1135

    Article  CAS  PubMed  Google Scholar 

  28. Geladaki A, Kočevar Britovšek N, Breckels LM et al (2019) Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics. Nat Commun 10:1–15

    Article  CAS  Google Scholar 

  29. Nightingale D, Lilley K, Oliver S (2019) A protocol to map the spatial proteome using hyperLOPIT in Saccharomyces cerevisiae. Bio Protoc 9:e3303

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Ong SE, Blagoev B, Kratchmarova I et al (2002) Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol Cell Proteomics 1:376–386

    Article  CAS  PubMed  Google Scholar 

  31. Itzhak DN, Tyanova S, Cox J, Borner GHH (2016) Global, quantitative and dynamic mapping of protein subcellular localization. Elife 5:1–36

    Article  Google Scholar 

  32. Bradford MM (1976) A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72:248–254

    Article  CAS  PubMed  Google Scholar 

  33. Cox J, Mann M (2008) MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol 26:1367–1372

    Article  CAS  PubMed  Google Scholar 

  34. Cox J, Neuhauser N, Michalski A et al (2011) Andromeda: a peptide search engine integrated into the MaxQuant environment. J Proteome Res 10:1794–1805

    Article  CAS  PubMed  Google Scholar 

  35. Tyanova S, Temu T, Cox J (2016) The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nat Protoc 11:2301–2319

    Article  CAS  PubMed  Google Scholar 

  36. Gatto L, Lilley KS (2012) MSnbase-an R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics 28:288–289

    Article  CAS  PubMed  Google Scholar 

  37. Breckels LM, Mulvey CM, Lilley KS, Gatto L (2016) A Bioconductor workflow for processing and analysing spatial proteomics data. F1000Res 5:2926

    Article  PubMed  Google Scholar 

  38. Tyanova S, Temu T, Sinitcyn P et al (2016) The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat Methods 13:731–740

    Article  CAS  PubMed  Google Scholar 

  39. Morgenstern M, Stiller SB, Lübbert P et al (2017) Definition of a high-confidence mitochondrial proteome at quantitative scale. Cell Rep 19:2836–2852

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Cramer J, Effelsberg D, Girzalsky W, Erdmann R (2015) Large-scale purification of peroxisomes for preparative applications. Cold Spring Harb Protoc 2015:db.prot083725

    Google Scholar 

  41. Delmotte N, Lasaosa M, Tholey A et al (2007) Two-dimensional reversed-phase x ion-pair reversed-phase HPLC: an alternative approach to high-resolution peptide separation for shotgun proteome analysis. J Proteome Res 6:4363–4373

    Article  CAS  PubMed  Google Scholar 

  42. Morgenstern M, Peikert CD, Lübbert P et al (2021) Quantitative high-confidence human mitochondrial proteome and its dynamics in cellular context. Cell Metab 33:2464–2483.e18

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Rappsilber J, Ishihama Y, Mann M (2003) Stop and go extraction tips for matrix-assisted laser desorption/ionization, nanoelectrospray, and LC/MS sample pretreatment in proteomics. Anal Chem 75:663–670

    Article  CAS  PubMed  Google Scholar 

  44. Albertini M, Rehling P, Erdmann R et al (1997) Pex14p, a peroxisomal membrane protein binding both receptors of the two PTS-dependent import pathways. Cell 89:83–92

    Article  CAS  PubMed  Google Scholar 

  45. Erdmann R, Kunau WH (1994) Purification and immunolocalization of the peroxisomal 3-oxoacyl-CoA thiolase from Saccharomyces cerevisiae. Yeast 10:1173–1182

    Article  CAS  PubMed  Google Scholar 

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Acknowledgments

This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 812968 (PERICO). Work included in this study has also been performed in partial fulfillment of the requirements for the doctoral theses of H. D. and A. Z. Furthermore, work in the lab of BW has been supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) Project ID 403222702/SFB 1381 and the Germany’s Excellence Strategy (CIBSS – EXC-2189 – Project ID 390939984).

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Authors and Affiliations

  1. Biochemistry II, Theodor Boveri-Institute, University of Würzburg, Würzburg, Germany

    Hirak Das, Alexandros Zografakis, Silke Oeljeklaus & Bettina Warscheid

  2. CIBSS Centre for Integrative Biological Signalling Studies, University of Freiburg, Freiburg, Germany

    Bettina Warscheid

Authors
  1. Hirak Das
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  2. Alexandros Zografakis
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  3. Silke Oeljeklaus
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  4. Bettina Warscheid
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Corresponding authors

Correspondence to Silke Oeljeklaus or Bettina Warscheid .

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Editors and Affiliations

  1. Faculty of Health and Life Sciences, Biosciences, University of Exeter, Exeter, Devon, UK

    Michael Schrader

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Das, H., Zografakis, A., Oeljeklaus, S., Warscheid, B. (2023). Analysis of Yeast Peroxisomes via Spatial Proteomics. In: Schrader, M. (eds) Peroxisomes. Methods in Molecular Biology, vol 2643. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3048-8_2

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  • DOI: https://doi.org/10.1007/978-1-0716-3048-8_2

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-3047-1

  • Online ISBN: 978-1-0716-3048-8

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