Dataset Information

Spatial distribution of endogenous tissue protease activity in gastric carcinoma mapped by MALDI mass spectrometry imaging

ABSTRACT: Aberrant protease activity has been implicated in the etiology of various prevalent diseases including neurodegeneration and cancer, in particular metastasis. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) has recently been established as a key technology for bioanalysis of multiple biomolecular classes such as proteins, lipids and glycans. However, it has not yet been systematically explored for investigation of a tissue’s endogenous protease activity. In this study, we demonstrate that different tissues, spray-coated with substance P as a tracer, digest this peptide with different time-courses. Furthermore, we reveal that distinct cleavage products originating from substance P are generated transiently and that proteolysis can be attenuated by protease inhibitors in a concentration-dependent manner. Further we applied a photometrical protease activity assay to verify our results. To show the translational potential of the method, we analyzed protease activity of gastric carcinoma in mice. Our results reveal differential distribution of protease activity – with strongest activity being observed in mouse tumor tissue, suggesting the general applicability of the workflow in animal pharmacology and clinical studies.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Gastric Cancer Cell Line

SUBMITTER: Torsten Mueller

LAB HEAD: Prof. Dr. Carsten Hopf

PROVIDER: PXD010369 | Pride | 2018-10-25

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	20180615_QE1_gastric_protease_NT_A_1_RAW.raw	Raw
	20180615_QE1_gastric_protease_NT_A_2_RAW.raw	Raw
	20180615_QE1_gastric_protease_NT_B_1_RAW.raw	Raw
	20180615_QE1_gastric_protease_NT_B_2_RAW.raw	Raw
	20180615_QE1_gastric_protease_NT_C_1_RAW.raw	Raw

Items per page:

1 - 5 of 29

Publications

Spatial Distribution of Endogenous Tissue Protease Activity in Gastric Carcinoma Mapped by MALDI Mass Spectrometry Imaging.

Erich Katrin K Reinle Kevin K Müller Torsten T Munteanu Bogdan B Sammour Denis A DA Hinsenkamp Isabel I Gutting Tobias T Burgermeister Elke E Findeisen Peter P Ebert Matthias P MP Krijgsveld Jeroen J Hopf Carsten C

Molecular & cellular proteomics : MCP 20181007 1

Aberrant protease activity has been implicated in the etiology of various prevalent diseases including neurodegeneration and cancer, in particular metastasis. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) has recently been established as a key technology for bioanalysis of multiple biomolecular classes such as proteins, lipids, and glycans. However, it has not yet been systematically explored for investigation of a tissue's endogenous protease activity. In t ...[more]

PMID: 30293968

Similar Datasets

Project description:Understanding the interplay of the proteome and the metabolome aids in understanding cellular phenotypes. To enable more robust inferences from such multi-omics analyses, combining proteomic and metabolomic datasets from the same sample provides major benefits by reducing technical variation between extracts during the pre-analytical phase, decreasing sample variation due to varying cellular content between aliquots, and limiting the required sample amount. We evaluated the advantages, practicality and feasibility of a single-sample workflow for combined proteome and metabolome analysis. In the workflow, termed MTBE-SP3, we combined a fully automated protein lysis and extraction protocol (autoSP3) with a semi-automated biphasic 75% EtOH/MTBE extraction for quantification of polar/non-polar metabolites. Additionally, we compared the resulting proteome of various biological matrices (FFPE tissue, fresh-frozen tissue, plasma, serum and cells) between autoSP3 and MTBE-SP3. Our analysis revealed that the single-sample workflow provided similar results to those obtained from autoSP3 alone, with an 85-98% overlap of proteins detected across the different biological matrices. Additionally, it provides distinct advantages by decreasing (tissue) heterogeneity by retrieving metabolomics and proteomic data from the identical biological material, and limiting the total amount of required material. Lastly, we applied MTBE-SP3 to a lung adenocarcinoma cohort of 10 patients. Integrating the metabolic and proteomic alterations between tumour and non-tumour adjacent tissue yielded consistent data independent of the method used. This revealed mitochondrial dysfunction in tumor tissue through deregulation of OGDH, SDH family enzymes and PKM. In summary, MTBE-SP3 enables the facile and confident parallel measurement of proteins and metabolites obtained from the same sample. This workflow is particularly applicable for studies with limited sample availability and offers the potential to enhance the integration of metabolomic and proteomic datasets.