@incollection{DasZografakisOeljeklausetal.2023,
  author    = {Das, Hirakjyoti and Zografakis, Alexandros and Oeljeklaus, Silke and Warscheid, Bettina},
  title     = {Analysis of Yeast Peroxisomes via Spatial Proteomics},
  series = {Peroxisomes},
  booktitle = {Peroxisomes},
  edition   = {accepted version},
  publisher = {Springer},
  doi       = {10.1007/978-1-0716-3048-8_2},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-327532},
  publisher      = {Universit{\"a}t W{\"u}rzburg},
  pages     = {13-31},
  year      = {2023},
  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.},
  language  = {en}
}
@article{MorgensternPeikertLuebbertetal.2021,
  author    = {Morgenstern, Marcel and Peikert, Christian D. and L{\"u}bbert, Philipp and Suppanz, Ida and Klemm, Cinzia and Alka, Oliver and Steiert, Conny and Naumenko, Nataliia and Schendzielorz, Alexander and Melchionda, Laura and M{\"u}hlh{\"a}user, Wignand W. D. and Knapp, Bettina and Busch, Jakob D. and Stiller, Sebastian B. and Dannenmaier, Stefan and Lindau, Caroline and Licheva, Mariya and Eickhorst, Christopher and Galbusera, Riccardo and Zerbes, Ralf M. and Ryan, Michael T. and Kraft, Claudine and Kozjak-Pavlovic, Vera and Drepper, Friedel and Dennerlein, Sven and Oeljeklaus, Silke and Pfanner, Nikolaus and Wiedemann, Nils and Warscheid, Bettina},
  title     = {Quantitative high-confidence human mitochondrial proteome and its dynamics in cellular context},
  series = {Cell Metabolism},
  volume    = {33},
  journal   = {Cell Metabolism},
  doi       = {10.1016/j.cmet.2021.11.001},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-371114},
  pages     = {2464-2483},
  year      = {2021},
  abstract  = {Mitochondria are key organelles for cellular energetics, metabolism, signaling, and quality control and have been linked to various diseases. Different views exist on the composition of the human mitochondrial proteome. We classified >8,000 proteins in mitochondrial preparations of human cells and defined a mitochondrial high-confidence proteome of >1,100 proteins (MitoCoP). We identified interactors of translocases, respiratory chain, and ATP synthase assembly factors. The abundance of MitoCoP proteins covers six orders of magnitude and amounts to 7\% of the cellular proteome with the chaperones HSP60-HSP10 being the most abundant mitochondrial proteins. MitoCoP dynamics spans three orders of magnitudes, with half-lives from hours to months, and suggests a rapid regulation of biosynthesis and assembly processes. 460 MitoCoP genes are linked to human diseases with a strong prevalence for the central nervous system and metabolism. MitoCoP will provide a high-confidence resource for placing dynamics, functions, and dysfunctions of mitochondria into the cellular context.},
  language  = {en}
}