"Differential Visual Proteomics": Enabling the Proteome-Wide Comparison of Protein Structures of Single-Cells.
Détails
ID Serval
serval:BIB_89180D353484
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
"Differential Visual Proteomics": Enabling the Proteome-Wide Comparison of Protein Structures of Single-Cells.
Périodique
Journal of proteome research
ISSN
1535-3907 (Electronic)
ISSN-L
1535-3893
Statut éditorial
Publié
Date de publication
06/09/2019
Peer-reviewed
Oui
Volume
18
Numéro
9
Pages
3521-3531
Langue
anglais
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
Publication Status: ppublish
Résumé
Proteins are involved in all tasks of life, and their characterization is essential to understand the underlying mechanisms of biological processes. We present a method called "differential visual proteomics" geared to study proteome-wide structural changes of proteins and protein-complexes between a disturbed and an undisturbed cell or between two cell populations. To implement this method, the cells are lysed and the lysate is prepared in a lossless manner for single-particle electron microscopy (EM). The samples are subsequently imaged in the EM. Individual particles are computationally extracted from the images and pooled together, while keeping track of which particle originated from which specimen. The extracted particles are then aligned and classified. A final quantitative analysis of the particle classes found identifies the particle structures that differ between positive and negative control samples. The algorithm and a graphical user interface developed to perform the analysis and to visualize the results were tested with simulated and experimental data. The results are presented, and the potential and limitations of the current implementation are discussed. We envisage the method as a tool for the untargeted profiling of the structural changes in the proteome of single-cells as a response to a disturbing force.
Mots-clé
Algorithms, Proteome/genetics, Proteomics/methods, Single-Cell Analysis/methods, Structure-Activity Relationship, differential proteomics, electron microscopy, image analysis, single-cell analysis, visual proteomics
Pubmed
Web of science
Open Access
Oui
Création de la notice
09/06/2023 15:02
Dernière modification de la notice
20/07/2023 5:57