Tight regulation of protein translation drives the proteome to undergo changes under influence of extracellular or intracellular signals. Despite mass spectrometry-based proteomics being an excellent method to study differences in protein abundance in complex proteomes, analyzing minute or rapid changes in protein synthesis and abundance remains challenging. Therefore, several dedicated techniques to directly detect and quantify newly synthesized proteins have been developed, notably puromycin-based, bio-orthogonal noncanonical amino acid tagging-based, and stable isotope labeling by amino acids in cell culture-based methods, combined with mass spectrometry. These techniques have enabled the investigation of perturbations, stress, or stimuli on protein synthesis. Improvements of these methods are still necessary to overcome various remaining limitations. Recent improvements include enhanced enrichment approaches and combinations with various stable isotope labeling techniques, which allow for more accurate analysis and comparison between conditions on shorter timeframes and in more challenging systems. Here, we aim to review the current state in this field.
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http://dx.doi.org/10.1016/j.cbpa.2021.07.001 | DOI Listing |
J Proteome Res
January 2025
European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, U.K.
The PRIDE database is the largest public data repository of mass spectrometry-based proteomics data and currently stores more than 40,000 data sets covering a wide range of organisms, experimental techniques, and biological conditions. During the past few years, PRIDE has seen a significant increase in the amount of submitted data-independent acquisition (DIA) proteomics data sets. This provides an excellent opportunity for large-scale data reanalysis and reuse.
View Article and Find Full Text PDFCurr Opin Nephrol Hypertens
January 2025
Control of the immune response B and lymphoproliferation, CNRS UMR 7276, INSERM UMR 1262, University of Limoges, Centre de référence de l'amylose AL et autres maladies par dépôts d'immunoglobuline monoclonale, Limoges, France; Service de néphrologie et Centre National de référence amylose AL et autres maladies à dépôts d'immunoglobulines monoclonales, Centre Hospitalier Universitaire, Université de Poitiers, Poitiers, France.
Acc Chem Res
January 2025
Department of Chemistry, Washington University, St. Louis, Missouri 63130, United States.
ConspectusProtein higher-order structure (HOS) is key to biological function because the mechanisms of protein machinery are encoded in protein three-dimensional structures. Mass spectrometry (MS)-based protein footprinting is advancing protein structure characterization by mapping solvent-accessible regions of proteins and changes in H-bonding, thereby providing higher order structural information. Footprinting provides insights into protein dynamics, conformational changes, and interactions, and when conducted in a differential way, can readily reveal those regions that undergo conformational change in response to perturbations such as ligand binding, mutation, thermal stress, or aggregation.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Ruhr University Bochum, Medical Faculty, Core Unit Bioinformatics - CUBiMed.RUB, Universitätsstr. 105, 44789 Bochum, Germany.
Due to computational resource limitations, in mass spectrometry based proteomics only a limited set of peptide sequences is used for the matching against measured spectra. We present an approach to represent proteins by graphs and allow not only the canonical sequences but also known isoforms and annotated amino acid variations, e.g.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, 420 Delaware St SE, MMC 609, Minneapolis, MN, 55455, USA.
Within ovarian cancer research, patient-derived xenograft (PDX) models recapitulate histologic features and genomic aberrations found in original tumors. However, conflicting data from published studies have demonstrated significant transcriptional differences between PDXs and original tumors, challenging the fidelity of these models. We employed a quantitative mass spectrometry-based proteomic approach coupled with generation of patient-specific databases using RNA-seq data to investigate the proteogenomic landscape of serially-passaged PDX models established from two patients with distinct subtypes of ovarian cancer.
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