Christian Panse

Last Name

Panse

First Name

Christian

ORCID

0000-0003-1975-3064

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06216 - Bioinformatics (FGCZ) / Bioinformatics (FGCZ)

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Publications 1 - 10 of 26

Unraveling the proteomic changes involved in the resistance response of Cajanus platycarpus to herbivory by Helicoverpa armigera
Rathinam, Maniraj; Roschitzki, Bernd; Grossmann, Jonas; et al. (2020)
Applied Microbiology and Biotechnology
The pigeonpea wild relative Cajanus platycarpus is resistant to Helicoverpa armigera, one of the major pests responsible for yield losses in Cajanus cajan. Deciphering the molecular mechanism underlying host plant resistance is pertinent to identify proteins that aid in the mitigation of the insect pest. The present study adopted comparative proteomics as a tool to interpret the resistance mechanism(s) in C. platycarpus vis-à-vis C. cajan during continued herbivory (up to 96 h). Over-representation analysis of the differentially expressed proteins implicated a multi-dimensional resistance response accomplished by both physical and chemical barriers in C. platycarpus. While the chemical basis for resistance was depicted by the upregulation of proteins playing a rate limiting role in the phenylpropanoid pathway, the physical basis was provided by the regulation of proteins involved in microtubule assembly and synthesis of lignins. Upregulation of proteins in the polyamine pathway indicated the role of metabolite conjugates to be negatively affecting herbivore growth. Reallocation of resources and diversion of metabolic flux to support the production of secondary metabolites could be the probable approach in the wild relative against herbivory. Our study provided deeper insights into the pod borer resistance mechanism in C. platycarpus for utility in crop improvement. Key points • Pod borer resistance in Cajanus platycarpus is multi-dimensional. • Pod borer resistance has been arbitrated to cell wall rigidity and secondary metabolites. • Phenylpropanoid pathway derivatives apparently shaped the plant chemical defense against pod borer. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
Bridging data management platforms and visualization tools to enable ad-hoc and smart analytics in life sciences
Panse, Christian; Trachsel, Christian; Türker, Can (2022)
Journal of Integrative Bioinformatics
Core facilities have to offer technologies that best serve the needs of their users and provide them a competitive advantage in research. They have to set up and maintain instruments in the range of ten to a hundred, which produce large amounts of data and serve thousands of active projects and customers. Particular emphasis has to be given to the reproducibility of the results. More and more, the entire process from building the research hypothesis, conducting the experiments, doing the measurements, through the data explorations and analysis is solely driven by very few experts in various scientific fields. Still, the ability to perform the entire data exploration in real-time on a personal computer is often hampered by the heterogeneity of software, the data structure formats of the output, and the enormous data sizes. These impact the design and architecture of the implemented software stack. At the Functional Genomics Center Zurich (FGCZ), a joint state-of-the-art research and training facility of ETH Zurich and the University of Zurich, we have developed the B-Fabric system, which has served for more than a decade, an entire life sciences community with fundamental data science support. In this paper, we sketch how such a system can be used to glue together data (including metadata), computing infrastructures (clusters and clouds), and visualization software to support instant data exploration and visual analysis. We illustrate our in-daily life implemented approach using visualization applications of mass spectrometry data.
rawDiag - an R package supporting rational LC-MS method optimization for bottom-up proteomics
Trachsel, Christian; Panse, Christian; Kockmann, Tobias; et al. (2018)
bioRxiv
Gas-Phase Fragmentation of ADP-Ribosylated Peptides: Arginine-Specific Side-Chain Losses and Their Implication in Database Searches
Gehrig, Peter M.; Nowak, Kathrin; Panse, Christian; et al. (2021)
Journal of the American Society for Mass Spectrometry
ADP-ribosylation is a reversible post-translational modification of proteins that has been linked to many biological processes. The identification of ADP-ribosylated proteins and particularly of their acceptor amino acids remains a major challenge. The attachment sites of the modification are difficult to localize by mass spectrometry (MS) because of the labile nature of the linkage and the complex fragmentation pattern of the ADP-ribose in MS/MS experiments. In this study we performed a comprehensive analysis of higher-energy collisional dissociation (HCD) spectra acquired from ADP-ribosylated peptides which were modified on arginine, serine, glutamic acid, aspartic acid, tyrosine, or lysine residues. In addition to the fragmentation of the peptide backbone, various cleavages of the ADP-ribosylated amino acid side chains were investigated. We focused on gas-phase fragmentations that were specific either to ADP-ribosylated arginine or to ADP-ribosylated serine and other O-linked ADP-ribosylations. The O-glycosidic linkage between ADP-ribose and serine, glutamic acid, or aspartic acid was the major cleavage site, making localization of these modification sites difficult. In contrast, the bond between ADP-ribose and arginine was relatively stable. The main cleavage site was the inner bond of the guanidine group, which resulted in the formation of ADP-ribosylated carbodiimide and of ornithine in place of modified arginine. Taking peptide fragment ions resulting from this specific cleavage into account, a considerably larger number of peptides containing ADP-ribosylated arginine were identified in database searches. Furthermore, the presence of diagnostic ions and of losses of fragments from peptide ions allowed us, in most cases, to distinguish between ADP-ribosylated arginine and serine residues.
International symposium on integrative bioinformatics 2024 - editorial
Türker, Can; Panse, Christian; Sommer, Bjorn; et al. (2024)
Journal of Integrative Bioinformatics
Integrative Bioinformatics faces the challenge of integrating, aligning, modelling, and simulating data in a coherent fashion to gain deeper insights into complex biological systems. This special issue of the Journal of Integrative Bioinformatics consists of six articles accepted for the presentation at the "18th International Symposium on Integrative Bioinformatics" held in Z & uuml;rich on September 12-13, 2024. In addition, the symposium featured five keynote talks which will be discussed here as well.
Developmental stage-specific proteome analysis of the legume pod borer Maruca vitrata provides insights on relevant proteins
Chatterjee, Madhurima; Roschitzki, Bernd; Grossmann, Jonas; et al. (2024)
International Journal of Biological Macromolecules
The spotted pod borer, Maruca vitrata (Lepidoptera: Crambidae) is a destructive insect pest that inflicts significant productivity losses on important leguminous crops. Unravelling insect proteomes is vital to comprehend their fundamental molecular mechanisms. This research delved into the proteome profiles of four distinct stages -three larval and pupa of M. vitrata, utilizing LC-MS/MS label-free quantification-based methods. Employing comprehensive proteome analysis with fractionated datasets, we mapped 75 % of 3459 Drosophila protein orthologues out of which 2695 were identified across all developmental stages while, 137 and 94 were exclusive to larval and pupal stages respectively. Cluster analysis of 2248 protein orthologues derived from MaxQuant quantitative dataset depicted six clusters based on expression pattern similarity across stages. Consequently, gene ontology and protein-protein interaction network analyses using STRING database identified cluster 1 (58 proteins) and cluster 6 (25 proteins) associated with insect immune system and lipid metabolism. Furthermore, qRT-PCR-based expression analyses of ten selected proteins-coding genes authenticated the proteome data. Subsequently, functional validation of these chosen genes through gene silencing reduced their transcript abundance accompanied by a marked increase in mortality among dsRNA-injected larvae. Overall, this is a pioneering study to effectively develop a proteome atlas of M. vitrata as a potential resource for crop protection programs.
PPINGUIN: Peptide Profiling Guided Identification of Proteins improves quantitation of iTRAQ ratios
Bauer, Chris; Kleinjung, Frank; Rutishauser, Dorothea; et al. (2012)
BMC Bioinformatics
Background Recent development of novel technologies paved the way for quantitative proteomics. One of the most important among them is iTRAQ, employing isobaric tags for relative or absolute quantitation. Despite large progress in technology development, still many challenges remain for derivation and interpretation of quantitative results. One of these challenges is the consistent assignment of peptides to proteins. Results We have developed Peptide Profiling Guided Identification of Proteins (PPINGUIN), a statistical analysis workflow for iTRAQ data addressing the problem of ambiguous peptide quantitations. Motivated by the assumption that peptides uniquely derived from the same protein are correlated, our method employs clustering as a very early step in data processing prior to protein inference. Our method increases experimental reproducibility and decreases variability of quantitations of peptides assigned to the same protein. Giving further support to our method, application to a type 2 diabetes dataset identifies a list of protein candidates that is in very good agreement with previously performed transcriptomics meta analysis. Making use of quantitative properties of signal patterns identified, PPINGUIN can reveal new isoform candidates. Conclusions Regarding the increasing importance of quantitative proteomics we think that this method will be useful in practical applications like model fitting or functional enrichment analysis. We recommend to use this method if quantitation is a major objective of research.
cosmiq: cosmiq - COmbining Single Masses Into Quantities
Fischer, David; Panse, Christian; Laczko, Endre (2014)
Bioconductor
B-Fabric: the Swiss Army Knife for life sciences
Türker, Can; Akal, Fuat; Joho, Dieter; et al. (2010)
EDBT '10: Proceedings of the 13th International Conference on Extending Database Technology
This paper demonstrates B-Fabric, an all-in-one solution for two major purposes in life sciences. On the one hand, it is a system for the integrated management of experimental data and scientific annotations. On the other hand, it is a system infrastructure supporting on-the fly coupling of user applications, and thus serving as extensible platform for fast-paced, cutting-edge, collaborative research.
rawDiag: an R Package Supporting Rational LC-MS Method Optimization for Bottom-up Proteomics
Trachsel, Christian; Panse, Christian; Kockmann, Tobias; et al. (2018)
Journal of Proteome Research

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