Titre
Immunofluorescence Analysis of Stress Granule Formation After Bacterial Challenge of Mammalian Cells.
Type
article
Institution
Externe
Périodique
Auteur(s)
Vonaesch, P.
Auteure/Auteur
Sansonetti, P.J.
Auteure/Auteur
Schnupf, P.
Auteure/Auteur
Liens vers les personnes
ISSN
1940-087X
Statut éditorial
Publié
Date de publication
2017-07-03
Numéro
125
Peer-reviewed
Oui
Langue
anglais
Notes
Publication types: Journal Article ; Video-Audio Media
Publication Status: epublish
Publication Status: epublish
Résumé
Fluorescent imaging of cellular components is an effective tool to investigate host-pathogen interactions. Pathogens can affect many different features of infected cells, including organelle ultrastructure, cytoskeletal network organization, as well as cellular processes such as Stress Granule (SG) formation. The characterization of how pathogens subvert host processes is an important and integral part of the field of pathogenesis. While variable phenotypes may be readily visible, the precise analysis of the qualitative and quantitative differences in the cellular structures induced by pathogen challenge is essential for defining statistically significant differences between experimental and control samples. SG formation is an evolutionarily conserved stress response that leads to antiviral responses and has long been investigated using viral infections <sup>1</sup> . SG formation also affects signaling cascades and may have other still unknown consequences <sup>2</sup> . The characterization of this stress response to pathogens other than viruses, such as bacterial pathogens, is currently an emerging area of research <sup>3</sup> . For now, quantitative and qualitative analysis of SG formation is not yet routinely used, even in the viral systems. Here we describe a simple method for inducing and characterizing SG formation in uninfected cells and in cells infected with a cytosolic bacterial pathogen, which affects the formation of SGs in response to various exogenous stresses. Analysis of SG formation and composition is achieved by using a number of different SG markers and the spot detector plug-in of ICY, an open source image analysis tool.
PID Serval
serval:BIB_820950ADD86A
PMID
URL éditeur
Date de création
2022-08-12T13:26:15.389Z
Date de création dans IRIS
2025-05-21T00:05:22Z