Search

Your search keyword '"Frejno, Martin"' showing total 43 results
Start Over Author "Frejno, Martin"
43 results on '"Frejno, Martin"'

1. Mass spectrometry-based draft of the mouse proteome

Author

Giansanti, Piero, Samaras, Patroklos, Bian, Yangyang, Meng, Chen, Coluccio, Andrea, Frejno, Martin, Jakubowsky, Hannah, Dobiasch, Sophie, Hazarika, Rashmi R., Rechenberger, Julia, Calzada-Wack, Julia, Krumm, Johannes, Mueller, Sebastian, Lee, Chien-Yun, Wimberger, Nicole, Lautenbacher, Ludwig, Hassan, Zonera, Chang, Yun-Chien, Falcomatà, Chiara, Bayer, Florian P., Bärthel, Stefanie, Schmidt, Tobias, Rad, Roland, Combs, Stephanie E., The, Matthew, Johannes, Frank, Saur, Dieter, de Angelis, Martin Hrabe, Wilhelm, Mathias, Schneider, Günter, and Kuster, Bernhard

Published
2022
Full Text
View/download PDF

2. Unifying the analysis of bottom-up proteomics data with CHIMERYS

Author

Frejno, Martin, primary, Berger, Michelle T, additional, Tueshaus, Johanna, additional, Hogrebe, Alexander, additional, Seefried, Florian, additional, Graber, Michael, additional, Samaras, Patroklos, additional, Fredj, Samia Ben, additional, Sukumar, Vishal, additional, Eljagh, Layla, additional, Bronshtein, Igor, additional, Mamisashvili, Lizi, additional, Schneider, Markus, additional, Gessulat, Siegfried, additional, Schmidt, Tobias, additional, Kuster, Bernhard, additional, Zolg, Daniel P, additional, and Wilhelm, Mathias, additional

Published
2024
Full Text
View/download PDF

3. Pharmacoproteomic characterisation of human colon and rectal cancer

Author

Frejno, Martin, Knapp, Stefan, and Feller, Stephan

Subjects
616.99
Abstract

Colorectal cancer (CRC) is one of the top three most common cancers and among the top four causes of cancer-related deaths worldwide (Torre et al., 2015). CRC patients are well characterised on the transcriptome and proteome level, but proteomics data on representative cell lines as model systems for pre-clinical drug sensitivity studies lag behind. Here, label-free quantitative mass spectrometry was used to characterise the kinomes and full proteomes of 65 CRC cell lines, collectively termed the CRC65 cell line panel. This data was integrated with proteomics data on patient samples, as well as public transcriptome and drug sensitivity datasets, which were reanalysed from raw data in order to unify and streamline the data processing. Protein/mRNA ratios were constant across these datasets, enabling linear prediction of protein abundance from mRNA abundance after appropriate adjustment, which was used for mRNA-guided missing value imputation. An exploration of secondary imputation methods prompted the development of a complementary method for minimum-guided missing value imputation. Combining the proteomics datasets on cell lines and patients led to the discovery of integrated proteomic subtypes of CRC and enabled the identification of representative cell lines for each of them. Modelling publicly available dose-response data generated by four large-scale drug sensitivity studies as a function of kinome/full proteome profiles fuelled the prediction of drug sensitivity for cell lines and patients, allowed the identification of drugs differentially effective between the different integrated proteomic subtypes and revealed MERTK as a predictive biomarker for resistance towards MEK1/2 inhibitors. This predictive role of MERTK was subsequently confirmed using in vitro experiments, while immunohistochemistry of TMAs from 1,074 tumours generated as part of the QUASAR2 clinical trial unveiled that MERTK is also a prognostic biomarker in CRC. This dataset will be made available to the scientific community to facilitate the design of prospective clinical studies.

Published
2016

4. Mass-spectrometry-based draft of the Arabidopsis proteome

Author

Mergner, Julia, Frejno, Martin, List, Markus, Papacek, Michael, Chen, Xia, Chaudhary, Ajeet, and Samaras, Patroklos

Subjects
Computational biology -- Usage, Proteomics -- Methods, Arabidopsis thaliana -- Genetic aspects -- Identification and classification, Mass spectrometry -- Usage, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Plants are essential for life and are extremely diverse organisms with unique molecular capabilities.sup.1. Here we present a quantitative atlas of the transcriptomes, proteomes and phosphoproteomes of 30 tissues of the model plant Arabidopsis thaliana. Our analysis provides initial answers to how many genes exist as proteins (more than 18,000), where they are expressed, in which approximate quantities (a dynamic range of more than six orders of magnitude) and to what extent they are phosphorylated (over 43,000 sites). We present examples of how the data may be used, such as to discover proteins that are translated from short open-reading frames, to uncover sequence motifs that are involved in the regulation of protein production, and to identify tissue-specific protein complexes or phosphorylation-mediated signalling events. Interactive access to this resource for the plant community is provided by the ProteomicsDB and ATHENA databases, which include powerful bioinformatics tools to explore and characterize Arabidopsis proteins, their modifications and interactions. A quantitative atlas of the transcriptomes, proteomes and phosphoproteomes of 30 tissues of the model plant Arabidopsis thaliana provides a valuable resource for plant research., Author(s): Julia Mergner [sup.1] , Martin Frejno [sup.1] , Markus List [sup.2] , Michael Papacek [sup.3] , Xia Chen [sup.4] , Ajeet Chaudhary [sup.4] , Patroklos Samaras [sup.1] , Sandra [...]

Published
2020
Full Text
View/download PDF

5. Proteome activity landscapes of tumor cell lines determine drug responses

Author

Frejno, Martin, Meng, Chen, Ruprecht, Benjamin, Oellerich, Thomas, Scheich, Sebastian, Kleigrewe, Karin, Drecoll, Enken, Samaras, Patroklos, Hogrebe, Alexander, Helm, Dominic, Mergner, Julia, Zecha, Jana, Heinzlmeir, Stephanie, Wilhelm, Mathias, Dorn, Julia, Kvasnicka, Hans-Michael, Serve, Hubert, Weichert, Wilko, and Kuster, Bernhard

Published
2020
Full Text
View/download PDF

7. Supplementary Figure 6 from Adaptation to HIF1α Deletion in Hypoxic Cancer Cells by Upregulation of GLUT14 and Creatine Metabolism

Author

Valli, Alessandro, primary, Morotti, Matteo, primary, Zois, Christos E., primary, Albers, Patrick K., primary, Soga, Tomoyoshi, primary, Feldinger, Katharina, primary, Fischer, Roman, primary, Frejno, Martin, primary, McIntyre, Alan, primary, Bridges, Esther, primary, Haider, Syed, primary, Buffa, Francesca M., primary, Baban, Dilair, primary, Rodriguez, Miguel, primary, Yanes, Oscar, primary, Whittington, Hannah J., primary, Lake, Hannah A., primary, Zervou, Sevasti, primary, Lygate, Craig A., primary, Kessler, Benedikt M., primary, and Harris, Adrian L., primary

Published
2023
Full Text
View/download PDF

8. Supplementary Figure 5 from Adaptation to HIF1α Deletion in Hypoxic Cancer Cells by Upregulation of GLUT14 and Creatine Metabolism

Author

Valli, Alessandro, primary, Morotti, Matteo, primary, Zois, Christos E., primary, Albers, Patrick K., primary, Soga, Tomoyoshi, primary, Feldinger, Katharina, primary, Fischer, Roman, primary, Frejno, Martin, primary, McIntyre, Alan, primary, Bridges, Esther, primary, Haider, Syed, primary, Buffa, Francesca M., primary, Baban, Dilair, primary, Rodriguez, Miguel, primary, Yanes, Oscar, primary, Whittington, Hannah J., primary, Lake, Hannah A., primary, Zervou, Sevasti, primary, Lygate, Craig A., primary, Kessler, Benedikt M., primary, and Harris, Adrian L., primary

Published
2023
Full Text
View/download PDF

9. Supplementary Figure 8 from Adaptation to HIF1α Deletion in Hypoxic Cancer Cells by Upregulation of GLUT14 and Creatine Metabolism

Author

Valli, Alessandro, primary, Morotti, Matteo, primary, Zois, Christos E., primary, Albers, Patrick K., primary, Soga, Tomoyoshi, primary, Feldinger, Katharina, primary, Fischer, Roman, primary, Frejno, Martin, primary, McIntyre, Alan, primary, Bridges, Esther, primary, Haider, Syed, primary, Buffa, Francesca M., primary, Baban, Dilair, primary, Rodriguez, Miguel, primary, Yanes, Oscar, primary, Whittington, Hannah J., primary, Lake, Hannah A., primary, Zervou, Sevasti, primary, Lygate, Craig A., primary, Kessler, Benedikt M., primary, and Harris, Adrian L., primary

Published
2023
Full Text
View/download PDF

10. Supplementary Figure 7 from Adaptation to HIF1α Deletion in Hypoxic Cancer Cells by Upregulation of GLUT14 and Creatine Metabolism

Author

Valli, Alessandro, primary, Morotti, Matteo, primary, Zois, Christos E., primary, Albers, Patrick K., primary, Soga, Tomoyoshi, primary, Feldinger, Katharina, primary, Fischer, Roman, primary, Frejno, Martin, primary, McIntyre, Alan, primary, Bridges, Esther, primary, Haider, Syed, primary, Buffa, Francesca M., primary, Baban, Dilair, primary, Rodriguez, Miguel, primary, Yanes, Oscar, primary, Whittington, Hannah J., primary, Lake, Hannah A., primary, Zervou, Sevasti, primary, Lygate, Craig A., primary, Kessler, Benedikt M., primary, and Harris, Adrian L., primary

Published
2023
Full Text
View/download PDF

11. Supplementary Figure 3 from Adaptation to HIF1α Deletion in Hypoxic Cancer Cells by Upregulation of GLUT14 and Creatine Metabolism

Author

Valli, Alessandro, primary, Morotti, Matteo, primary, Zois, Christos E., primary, Albers, Patrick K., primary, Soga, Tomoyoshi, primary, Feldinger, Katharina, primary, Fischer, Roman, primary, Frejno, Martin, primary, McIntyre, Alan, primary, Bridges, Esther, primary, Haider, Syed, primary, Buffa, Francesca M., primary, Baban, Dilair, primary, Rodriguez, Miguel, primary, Yanes, Oscar, primary, Whittington, Hannah J., primary, Lake, Hannah A., primary, Zervou, Sevasti, primary, Lygate, Craig A., primary, Kessler, Benedikt M., primary, and Harris, Adrian L., primary

Published
2023
Full Text
View/download PDF

12. Supplementary Figure 2 from Adaptation to HIF1α Deletion in Hypoxic Cancer Cells by Upregulation of GLUT14 and Creatine Metabolism

Author

Valli, Alessandro, primary, Morotti, Matteo, primary, Zois, Christos E., primary, Albers, Patrick K., primary, Soga, Tomoyoshi, primary, Feldinger, Katharina, primary, Fischer, Roman, primary, Frejno, Martin, primary, McIntyre, Alan, primary, Bridges, Esther, primary, Haider, Syed, primary, Buffa, Francesca M., primary, Baban, Dilair, primary, Rodriguez, Miguel, primary, Yanes, Oscar, primary, Whittington, Hannah J., primary, Lake, Hannah A., primary, Zervou, Sevasti, primary, Lygate, Craig A., primary, Kessler, Benedikt M., primary, and Harris, Adrian L., primary

Published
2023
Full Text
View/download PDF

13. Data from Adaptation to HIF1α Deletion in Hypoxic Cancer Cells by Upregulation of GLUT14 and Creatine Metabolism

Author

Valli, Alessandro, primary, Morotti, Matteo, primary, Zois, Christos E., primary, Albers, Patrick K., primary, Soga, Tomoyoshi, primary, Feldinger, Katharina, primary, Fischer, Roman, primary, Frejno, Martin, primary, McIntyre, Alan, primary, Bridges, Esther, primary, Haider, Syed, primary, Buffa, Francesca M., primary, Baban, Dilair, primary, Rodriguez, Miguel, primary, Yanes, Oscar, primary, Whittington, Hannah J., primary, Lake, Hannah A., primary, Zervou, Sevasti, primary, Lygate, Craig A., primary, Kessler, Benedikt M., primary, and Harris, Adrian L., primary

Published
2023
Full Text
View/download PDF

14. Supplemetary Data from Adaptation to HIF1α Deletion in Hypoxic Cancer Cells by Upregulation of GLUT14 and Creatine Metabolism

Author

Valli, Alessandro, primary, Morotti, Matteo, primary, Zois, Christos E., primary, Albers, Patrick K., primary, Soga, Tomoyoshi, primary, Feldinger, Katharina, primary, Fischer, Roman, primary, Frejno, Martin, primary, McIntyre, Alan, primary, Bridges, Esther, primary, Haider, Syed, primary, Buffa, Francesca M., primary, Baban, Dilair, primary, Rodriguez, Miguel, primary, Yanes, Oscar, primary, Whittington, Hannah J., primary, Lake, Hannah A., primary, Zervou, Sevasti, primary, Lygate, Craig A., primary, Kessler, Benedikt M., primary, and Harris, Adrian L., primary

Published
2023
Full Text
View/download PDF

15. Supplementary Figure 4 from Adaptation to HIF1α Deletion in Hypoxic Cancer Cells by Upregulation of GLUT14 and Creatine Metabolism

Author

Valli, Alessandro, primary, Morotti, Matteo, primary, Zois, Christos E., primary, Albers, Patrick K., primary, Soga, Tomoyoshi, primary, Feldinger, Katharina, primary, Fischer, Roman, primary, Frejno, Martin, primary, McIntyre, Alan, primary, Bridges, Esther, primary, Haider, Syed, primary, Buffa, Francesca M., primary, Baban, Dilair, primary, Rodriguez, Miguel, primary, Yanes, Oscar, primary, Whittington, Hannah J., primary, Lake, Hannah A., primary, Zervou, Sevasti, primary, Lygate, Craig A., primary, Kessler, Benedikt M., primary, and Harris, Adrian L., primary

Published
2023
Full Text
View/download PDF

16. Authorship Change Form from Adaptation to HIF1α Deletion in Hypoxic Cancer Cells by Upregulation of GLUT14 and Creatine Metabolism

Author

Valli, Alessandro, primary, Morotti, Matteo, primary, Zois, Christos E., primary, Albers, Patrick K., primary, Soga, Tomoyoshi, primary, Feldinger, Katharina, primary, Fischer, Roman, primary, Frejno, Martin, primary, McIntyre, Alan, primary, Bridges, Esther, primary, Haider, Syed, primary, Buffa, Francesca M., primary, Baban, Dilair, primary, Rodriguez, Miguel, primary, Yanes, Oscar, primary, Whittington, Hannah J., primary, Lake, Hannah A., primary, Zervou, Sevasti, primary, Lygate, Craig A., primary, Kessler, Benedikt M., primary, and Harris, Adrian L., primary

Published
2023
Full Text
View/download PDF

17. Supplementary Figure 1 from Adaptation to HIF1α Deletion in Hypoxic Cancer Cells by Upregulation of GLUT14 and Creatine Metabolism

Author

Valli, Alessandro, primary, Morotti, Matteo, primary, Zois, Christos E., primary, Albers, Patrick K., primary, Soga, Tomoyoshi, primary, Feldinger, Katharina, primary, Fischer, Roman, primary, Frejno, Martin, primary, McIntyre, Alan, primary, Bridges, Esther, primary, Haider, Syed, primary, Buffa, Francesca M., primary, Baban, Dilair, primary, Rodriguez, Miguel, primary, Yanes, Oscar, primary, Whittington, Hannah J., primary, Lake, Hannah A., primary, Zervou, Sevasti, primary, Lygate, Craig A., primary, Kessler, Benedikt M., primary, and Harris, Adrian L., primary

Published
2023
Full Text
View/download PDF

19. INFERYS rescoring: Boosting peptide identifications and scoring confidence of database search results

Author

Zolg, Daniel P., primary, Gessulat, Siegfried, additional, Paschke, Carmen, additional, Graber, Michael, additional, Rathke‐Kuhnert, Magnus, additional, Seefried, Florian, additional, Fitzemeier, Kai, additional, Berg, Frank, additional, Lopez‐Ferrer, Daniel, additional, Horn, David, additional, Henrich, Christoph, additional, Huhmer, Andreas, additional, Delanghe, Bernard, additional, and Frejno, Martin, additional

Published
2021
Full Text
View/download PDF

22. Identification of molecular targets for the targeted treatment of gastric cancer using dasatinib

Author

Montenegro, Raquel Carvalho, primary, Howarth, Alison, additional, Ceroni, Alessandro, additional, Fedele, Vita, additional, Farran, Batoul, additional, Mesquita, Felipe Pantoja, additional, Frejno, Martin, additional, Berger, Benedict-Tilman, additional, Heinzlmeir, Stephanie, additional, Sailem, Heba Z., additional, Tesch, Roberta, additional, Ebner, Daniel, additional, Knapp, Stefan, additional, Burbano, Rommel, additional, Kuster, Bernhard, additional, and Müller, Susanne, additional

Published
2020
Full Text
View/download PDF

23. ProteomicsDB: a multi-omics and multi-organism resource for life science research

Author

Samaras, Patroklos, primary, Schmidt, Tobias, additional, Frejno, Martin, additional, Gessulat, Siegfried, additional, Reinecke, Maria, additional, Jarzab, Anna, additional, Zecha, Jana, additional, Mergner, Julia, additional, Giansanti, Piero, additional, Ehrlich, Hans-Christian, additional, Aiche, Stephan, additional, Rank, Johannes, additional, Kienegger, Harald, additional, Krcmar, Helmut, additional, Kuster, Bernhard, additional, and Wilhelm, Mathias, additional

Published
2019
Full Text
View/download PDF

24. Challenges in Clinical Metaproteomics Highlighted by the Analysis of Acute Leukemia Patients with Gut Colonization by Multidrug-Resistant Enterobacteriaceae

Author

Rechenberger, Julia, Samaras, Patroklos, Jarzab, Anna, Behr, Juergen, Frejno, Martin, Djukovic, Ana, Sanz, Jaime, González-Barberá, Eva M., Salavert, Miguel, López-Hontangas, Jose Luis, Xavier, Karina B., Debrauwer, Laurent, Rolain, Jean-Marc, Sanz, Miguel, Garcia-Garcera, Marc, Wilhelm, Mathias, Ubeda, Carles, and Kuster, Bernhard

Subjects
ddc
Published
2019

25. Adaptation to HIF1α Deletion in Hypoxic Cancer Cells by Upregulation of GLUT14 and Creatine Metabolism

Author

Valli, Alessandro, primary, Morotti, Matteo, additional, Zois, Christos E., additional, Albers, Patrick K., additional, Soga, Tomoyoshi, additional, Feldinger, Katharina, additional, Fischer, Roman, additional, Frejno, Martin, additional, McIntyre, Alan, additional, Bridges, Esther, additional, Haider, Syed, additional, Buffa, Francesca M., additional, Baban, Dilair, additional, Rodriguez, Miguel, additional, Yanes, Oscar, additional, Whittington, Hannah J., additional, Lake, Hannah A., additional, Zervou, Sevasti, additional, Lygate, Craig A., additional, Kessler, Benedikt M., additional, and Harris, Adrian L., additional

Published
2019
Full Text
View/download PDF

26. A deep proteome and transcriptome abundance atlas of 29 healthy human tissues

Author

Wang, Dongxue, primary, Eraslan, Basak, additional, Wieland, Thomas, additional, Hallström, Björn, additional, Hopf, Thomas, additional, Zolg, Daniel Paul, additional, Zecha, Jana, additional, Asplund, Anna, additional, Li, Li‐hua, additional, Meng, Chen, additional, Frejno, Martin, additional, Schmidt, Tobias, additional, Schnatbaum, Karsten, additional, Wilhelm, Mathias, additional, Ponten, Frederik, additional, Uhlen, Mathias, additional, Gagneur, Julien, additional, Hahne, Hannes, additional, and Kuster, Bernhard, additional

Published
2019
Full Text
View/download PDF

27. Challenges in Clinical Metaproteomics Highlighted by the Analysis of Acute Leukemia Patients with Gut Colonization by Multidrug-Resistant Enterobacteriaceae

Author

Rechenberger, Julia, primary, Samaras, Patroklos, additional, Jarzab, Anna, additional, Behr, Juergen, additional, Frejno, Martin, additional, Djukovic, Ana, additional, Sanz, Jaime, additional, González-Barberá, Eva M., additional, Salavert, Miguel, additional, López-Hontangas, Jose Luis, additional, Xavier, Karina B., additional, Debrauwer, Laurent, additional, Rolain, Jean-Marc, additional, Sanz, Miguel, additional, Garcia-Garcera, Marc, additional, Wilhelm, Mathias, additional, Ubeda, Carles, additional, and Kuster, Bernhard, additional

Published
2019
Full Text
View/download PDF

28. A fitness assay for comparing RNAi effects across multiple C. elegans genotypes

Author

Kammenga Jan E, Klemstein Ulrike, Frejno Martin, Snoek Laurens B, Elvin Mark, and Poulin Gino B

Subjects
Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract Background RNAi technology by feeding of E. coli containing dsRNA in C. elegans has significantly contributed to further our understanding of many different fields, including genetics, molecular biology, developmental biology and functional genomics. Most of this research has been carried out in a single genotype or genetic background. However, RNAi effects in one genotype do not reveal the allelic effects that segregate in natural populations and contribute to phenotypic variation. Results Here we present a method that allows for rapidly comparing RNAi effects among diverse genotypes at an improved high throughput rate. It is based on assessing the fitness of a population of worms by measuring the rate at which E. coli is consumed. Critically, we demonstrate the analytical power of this method by QTL mapping the loss of RNAi sensitivity (in the germline) in a recombinant inbred population derived from a cross between Bristol and a natural isolate from Hawaii. Hawaii has lost RNAi sensitivity in the germline. We found that polymorphisms in ppw-1 contribute to this loss of RNAi sensitivity, but that other loci are also likely to be important. Conclusions In summary, we have established a fast method that improves the throughput of RNAi in liquid, that generates quantitative data, that is easy to implement in most laboratories, and importantly that enables QTL mapping using RNAi.

Published
2011
Full Text
View/download PDF

29. Optimized Enrichment of Phosphoproteomes by Fe-IMAC Column Chromatography

Author

Ruprecht, Benjamin, Koch, Heiner, Domasinska, Petra, Frejno, Martin, Kuster, Bernhard, Lemeer, Simone, Walker, John M., Comai, Lucio, Katz, Jonathan E., Mallick, Parag, Sub Biomol.Mass Spectrometry & Proteom., and Biomolecular Mass Spectrometry and Proteomics

Subjects
Proteomics, Phosphorylation, Phosphocapture, LC-MS
Abstract

Phosphorylation is among the most important post-translational modifications of proteins and has numerous regulatory functions across all domains of life. However, phosphorylation is often substoichiometric, requiring selective and sensitive methods to enrich phosphorylated peptides from complex cellular digests. Various methods have been devised for this purpose and we have recently described a Fe-IMAC HPLC column chromatography setup which is capable of comprehensive, reproducible, and selective enrichment of phosphopeptides out of complex peptide mixtures. In contrast to other formats such as StageTips or batch incubations using TiO2 or Ti-IMAC beads, Fe-IMAC HPLC columns do not suffer from issues regarding incomplete phosphopeptide binding or elution and enrichment efficiency scales linearly with the amount of starting material. Here, we provide a step-by-step protocol for the entire phosphopeptide enrichment procedure including sample preparation (lysis, digestion, desalting), Fe-IMAC column chromatography (column setup, operation, charging), measurement by LC-MS/MS (nHPLC gradient, MS parameters) and data analysis (MaxQuant). To increase throughput, we have optimized several key steps such as the gradient time of the Fe-IMAC separation (15 min per enrichment), the number of consecutive enrichments possible between two chargings (>20) and the column recharging itself (90 %) identification of more than 10,000 unique phosphopeptides from 1 mg of HeLa digest within 2 h of measurement time (Q Exactive Plus).

Published
2017

31. A deep proteome and transcriptome abundance atlas of 29 healthy human tissues

Author

Wang, Dongxue, primary, Eraslan, Basak, additional, Wieland, Thomas, additional, Hallström, Björn, additional, Hopf, Thomas, additional, Zolg, Daniel Paul, additional, Zecha, Jana, additional, Asplund, Anna, additional, Li, Li-hua, additional, Meng, Chen, additional, Frejno, Martin, additional, Schmidt, Tobias, additional, Schnatbaum, Karsten, additional, Wilhelm, Mathias, additional, Ponten, Frederik, additional, Uhlen, Mathias, additional, Gagneur, Julien, additional, Hahne, Hannes, additional, and Kuster, Bernhard, additional

Published
2018
Full Text
View/download PDF

32. ProteomicsDB

Author

Schmidt, Tobias, primary, Samaras, Patroklos, additional, Frejno, Martin, additional, Gessulat, Siegfried, additional, Barnert, Maximilian, additional, Kienegger, Harald, additional, Krcmar, Helmut, additional, Schlegl, Judith, additional, Ehrlich, Hans-Christian, additional, Aiche, Stephan, additional, Kuster, Bernhard, additional, and Wilhelm, Mathias, additional

Published
2017
Full Text
View/download PDF

33. Pharmacoproteomic characterisation of human colon and rectal cancer

Author

Frejno, Martin, primary, Zenezini Chiozzi, Riccardo, additional, Wilhelm, Mathias, additional, Koch, Heiner, additional, Zheng, Runsheng, additional, Klaeger, Susan, additional, Ruprecht, Benjamin, additional, Meng, Chen, additional, Kramer, Karl, additional, Jarzab, Anna, additional, Heinzlmeir, Stephanie, additional, Johnstone, Elaine, additional, Domingo, Enric, additional, Kerr, David, additional, Jesinghaus, Moritz, additional, Slotta‐Huspenina, Julia, additional, Weichert, Wilko, additional, Knapp, Stefan, additional, Feller, Stephan M, additional, and Kuster, Bernhard, additional

Published
2017
Full Text
View/download PDF

38. ProteomicsDB.

Author

Schmidt, Tobias, Samaras, Patroklos, Frejno, Martin, Gessulat, Siegfried, Barnert, Maximilian, Kienegger, Harald, Krcmar, Helmut, Schlegl, Judith, Ehrlich, Hans-Christian, and Aiche, Stephan

Published
2018
Full Text
View/download PDF

41. moCluster: Identifying Joint Patterns Across Multiple Omics Data Sets

Author

Meng, Chen, Helm, Dominic, Frejno, Martin, and Kuster, Bernhard

Abstract

Increasingly, multiple omics approaches are being applied to understand the complexity of biological systems. Yet, computational approaches that enable the efficient integration of such data are not well developed. Here, we describe a novel algorithm, termed moCluster, which discovers joint patterns among multiple omics data. The method first employs a multiblock multivariate analysis to define a set of latent variables representing joint patterns across input data sets, which is further passed to an ordinary clustering algorithm in order to discover joint clusters. Using simulated data, we show that moCluster’s performance is not compromised by issues present in iCluster/iCluster+ (notably, the nondeterministic solution) and that it operates 100× to 1000× faster than iCluster/iCluster+. We used moCluster to cluster proteomic and transcriptomic data from the NCI-60 cell line panel. The resulting cluster model revealed different phenotypes across cellular subtypes, such as doubling time and drug response. Applying moCluster to methylation, mRNA, and protein data from a large study on colorectal cancer patients identified four molecular subtypes, including one characterized by microsatellite instability and high expression of genes/proteins involved in immunity, such as PDL1, a target of multiple drugs currently in development. The other three subtypes have not been discovered before using single data sets, which clearly illustrates the molecular complexity of oncogenesis and the need for holistic, multidata analysis strategies.

Published
2016
Full Text
View/download PDF

42. Ceramide Synthase 5 Is Essential to Maintain C16:0-Ceramide Pools and Contributes to the Development of Diet-induced Obesity.

Author

Gosejacob, Dominic, Jäger, Philipp S., Dorp, Katharina vom, Frejno, Martin, Carstensen, Anne C., Köhnke, Monika, Degen, Joachim, Dörmann, Peter, and Hoch, Michael

Subjects
*CERAMIDES, *DIET in disease, *OBESITY -- Nutritional aspects, *SPHINGOLIPIDS, *INSULIN resistance, *HOMEOSTASIS
Abstract

Ceramides are bioactive sphingolipids, which are composed of sphingoid bases carrying acyl chains of various lengths. Ceramides are synthesized by a family of six ceramide synthases (CerS) in mammals, which produce ceramides with different N-linked acyl chains. Increased ceramide levels are known to contribute to the development of obesity and insulin resistance. Recently, it has been demonstrated that the ceramide acylation pattern is of particular importance for an organism to maintain energy homeostasis. However, which of the CerS family members are involved in this process is not yet completely known. Using newly developed CerS5 knock-out mice, we show here that CerS5 is essential to maintain cellular C16:0 sphingolipid pools in lung, spleen, muscle, liver, and white adipose tissue. Glycerophospholipid levels in CerS5-deficient mice were not altered. We found a strong impact of CerS5-dependent ceramide synthesis in white adipose tissue after high fat diet feeding. In skeletal muscle, liver, and spleen, C16:0-ceramide levels were altered independent of feeding conditions. The loss of CerS5 is associated with reduced weight gain and improved systemic health, including maintenance of glucose homeostasis and reduced white adipose tissue inflammation after high fat diet challenge. Our findings indicate that reduction of endogenous C16:0-ceramide by genetic inhibition of CerS5 is sufficient to ameliorate obesity and its comorbidities. [ABSTRACT FROM AUTHOR]

Published
2016
Full Text
View/download PDF

43. Optimized Enrichment of Phosphoproteomes by Fe-IMAC Column Chromatography.

Author

Ruprecht B, Koch H, Domasinska P, Frejno M, Kuster B, and Lemeer S

Subjects
Cell Line, Chromatography, Liquid, Humans, Phosphopeptides, Software, Statistics as Topic, Tandem Mass Spectrometry, Workflow, Imidazoles chemistry, Iron chemistry, Phosphoproteins, Proteome, Proteomics methods
Abstract

Phosphorylation is among the most important post-translational modifications of proteins and has numerous regulatory functions across all domains of life. However, phosphorylation is often substoichiometric, requiring selective and sensitive methods to enrich phosphorylated peptides from complex cellular digests. Various methods have been devised for this purpose and we have recently described a Fe-IMAC HPLC column chromatography setup which is capable of comprehensive, reproducible, and selective enrichment of phosphopeptides out of complex peptide mixtures. In contrast to other formats such as StageTips or batch incubations using TiO 2 or Ti-IMAC beads, Fe-IMAC HPLC columns do not suffer from issues regarding incomplete phosphopeptide binding or elution and enrichment efficiency scales linearly with the amount of starting material. Here, we provide a step-by-step protocol for the entire phosphopeptide enrichment procedure including sample preparation (lysis, digestion, desalting), Fe-IMAC column chromatography (column setup, operation, charging), measurement by LC-MS/MS (nHPLC gradient, MS parameters) and data analysis (MaxQuant). To increase throughput, we have optimized several key steps such as the gradient time of the Fe-IMAC separation (15 min per enrichment), the number of consecutive enrichments possible between two chargings (>20) and the column recharging itself (<1 h). We show that the application of this protocol enables the selective (>90 %) identification of more than 10,000 unique phosphopeptides from 1 mg of HeLa digest within 2 h of measurement time (Q Exactive Plus).

Published
2017
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results