The peroxisome represents a ubiquitous single membrane-bound key organelle that executes various metabolic pathways such as fatty acid degradation by ␣-and ␤-oxidation, ether-phospholipid biosynthesis, metabolism of reactive oxygen species, and detoxification of glyoxylate in mammals. To fulfil this vast array of metabolic functions, peroxisomes accommodate ϳ50 different enzymes at least as identified until now. Interest in peroxisomes has been fueled by the discovery of a group of genetic diseases in humans, which are caused by either a defect in peroxisome biogenesis or the deficient activity of a distinct peroxisomal enzyme or transporter. Although this research has greatly improved our understanding of peroxisomes and their role in mammalian metabolism, deeper insight into biochemistry and functions of peroxisomes is required to expand our knowledge of this low abundance but vital organelle. In this work, we used classical subcellular fractionation in combination with MS-based proteomics methodologies to characterize the proteome of mouse kidney peroxisomes. We could identify virtually all known components involved in peroxisomal metabolism and biogenesis. Moreover through protein localization studies by using a quantitative MS screen combined with statistical analyses, we identified 15 new peroxisomal candidates. Of these, we further investigated five candidates by immunocytochemistry, which confirmed their localization in peroxisomes. As a result of this joint effort, we believe to have compiled the so far most comprehensive protein catalogue of mammalian peroxisomes.

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Molecular networking connects mass spectra of molecules based on the similarity of their fragmentation patterns. However, during ionization, molecules commonly form multiple ion species with different fragmentation behavior. As a result, the fragmentation spectra of these ion species often remain unconnected in tandem mass spectrometry-based molecular networks, leading to redundant and disconnected sub-networks of the same compound classes. To overcome this bottleneck, we develop Ion Identity Molecular Networking (IIMN) that integrates chromatographic peak shape correlation analysis into molecular networks to connect and collapse different ion species of the same molecule. The new feature relationships improve network connectivity for structurally related molecules, can be used to reveal unknown ion-ligand complexes, enhance annotation within molecular networks, and facilitate the expansion of spectral reference libraries. IIMN is integrated into various open source feature finding tools and the GNPS environment. Moreover, IIMN-based spectral libraries with a broad coverage of ion species are publicly available.

An atmospheric pressure microplasma ionization source based on a dielectric barrier discharge with a helium plasma cone outside the electrode region has been developed for liquid chromatography/mass spectrometry (LC/MS). For this purpose, the plasma was realized in a commercial atmospheric pressure ionization source. Dielectric barrier discharge ionization (DBDI) was compared to conventional electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI), and atmospheric pressure photoionization (APPI) in the positive ionization mode. Therefore, a heterogeneous compound library was investigated that covered polar compounds such as amino acids, water-soluble vitamins, and nonpolar compounds like polycyclic aromatic hydrocarbons and functionalized hydrocarbons. It turned out that DBDI can be regarded as a soft ionization technique characterized by only minor fragmentation similar to APCI. Mainly protonated molecules were detected. Additionally, molecular ions were observed for polycyclic aromatic hydrocarbons and derivatives thereof. During DBDI, adduct formation with acetonitrile occurred. For aromatic compounds, addition of one to four oxygen atoms and to a smaller extend one nitrogen and oxygen was observed which delivered insight into the complexity of the ionization processes. In general, compounds covering a wider range of polarities can be ionized by DBDI than by ESI. Furthermore, limits of detection compared to APCI are in most cases equal or even better.