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We describe a method for the qualitative and quantitative analysis of stress granule formation in mammalian cells after the cells are challenged with bacteria and a number of different stresses. This protocol can be applied to investigate the cellular stress granule response in a wide range of host-bacterial interactions.
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 infections1. SG formation also affects signaling cascades and may have other still unknown consequences2. The characterization of this stress response to pathogens other than viruses, such as bacterial pathogens, is currently an emerging area of research3. 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.
Visualizing host-pathogen interactions on a cellular level is a powerful method for gaining insights into pathogenic strategies and for identifying key cellular pathways. Indeed, pathogens can be used as tools to pinpoint important cellular targets or structures, as pathogens have evolved to subvert central cellular processes as a strategy for their own survival or propagation. Visualization of cellular components can be achieved by recombinantly expressing fluorescently-tagged host proteins. While this allows for real-time analysis, the generation of cell lines with specifically-tagged host proteins is highly laborious and may result in undesirable side effects. More convenient is the detection of cellular factors using specific antibodies, because multiple host factors can be analyzed simultaneously and one is not limited to a particular cell type. A drawback is that only a static view can be captured as immunofluorescence analysis necessitates host cell fixation. However, an important advantage of immunofluorescence imaging is that it readily lends itself to both qualitative and quantitative analysis. This in turn can be used to obtain statistically significant differences to provide new insights into host-pathogen interactions.
Fluorescent image analysis programs are powerful analytical tools for performing 3D and 4D analysis. However, the high cost of software and its maintenance make methods based on free open source software more widely attractive. Careful image analysis using bio-analysis software is valuable as it substantiates visual analysis and, when assigning statistical significances, increases confidence in the correctness of a given phenotype. Previously, SGs have been analyzed using the free ImageJ software, which necessitates the manual identification of individual SGs4. Here we provide a protocol for the induction and analysis of cellular SG formation in the context of bacterial infections using the free open source bio-image analysis software ICY (http://icy.bioimageanalysis.org). The bio-image analysis software has a built-in spot detector program that is highly suitable for SG analysis. It allows the fine-tuning of the automated detection process in specified Regions Of Interest (ROIs). This overcomes the need for manual analysis of individual SGs and removes sampling bias.
Many environmental stresses induce the formation of SGs, which are phase dense cytosolic, non-membranous structures of 0.2 - 5 µm in diameter5,6. This cellular response is evolutionarily conserved in yeast, plants and mammals and occurs when global protein translation is inhibited. It involves aggregation of stalled translation initiation complexes into SGs, which are considered holding places for translationally-inactive mRNAs, allowing selective translation of a subset of cellular mRNAs. Upon removal of the stress, SGs dissolve and global rates of protein synthesis resume. SGs are composed of translation elongation initiation factors, proteins involved in RNA metabolism, RNA-binding proteins, as well as scaffolding proteins and factors involved in host cell signaling2, although the exact composition can vary depending on the stress applied. Environmental factors that induce SG formation include amino acid starvation, UV irradiation, heat shock, osmotic shock, endoplasmic reticulum stress, hypoxia and viral infection2,7,8. Much progress has been made in understanding how viruses induce and also subvert SG formation, while little is still known about how other pathogens, such as bacterial, fungal or protozoan pathogens, affect this cellular stress response1,7.
Shigella flexneri is a gram-negative facultative cytosolic pathogen of humans and the causative agent of severe diarrhea or shigellosis. Shigellosis is a major public health burden and leads to 28,000 deaths annually in children under 5 years of age9,10. S. flexneri infects the colonic epithelium and spreads cell-to-cell by hijacking the host's cytoskeletal components11,12. Infection of the epithelium supports the replication of S. flexneri within the cytosol but infected macrophages die through an inflammatory cell death process called pyroptosis. Infection leads to a massive recruitment of neutrophils and severe inflammation that is accompanied by heat, oxidative stress and tissue destruction. Thus, while infected cells are subject to internal stresses induced by infection, such as Golgi disruption, genotoxic stress and cytoskeletal rearrangements, infected cells are also subjected to environmental stresses due to the inflammatory process.
Characterization of the effect of S. flexneri infection on the ability of cells to respond to environmental stresses using a number of SG markers has demonstrated that infection leads to qualitative and quantitative differences in SG composition3. However, little is known about other bacterial pathogens. Here we describe a methodology for the infection of host cells with the cytosolic pathogen S. flexneri, the stressing of cells with different environmental stresses, the labeling of SG components, and the qualitative and quantitative analysis of SG formation and composition in the context of infected and non-infected cells. This method is widely applicable to other bacterial pathogens. In addition, the image analysis of the SG formation may be used for infections by viruses or other pathogens. It can be used to analyze SG formation upon infection or the effect of infection on SG formation in response to exogenous stresses.
1. Preparation of Bacteria and Host Cells
2. Bacterial Challenge of Host Cells
3. Inducing Stress Granule Formation by the Addition of Exogenous Stressors
4. Fixation and Immunofluorescence Analysis of Stress Granule Formation
NOTE: Process the control and experimental coverslips at the same time to avoid staining differences that may impact image analysis in subsequent steps. The control samples include no infection with and without SG inducing treatment, and infected samples with and without SG inducing treatment.
5. Fluorescence Imaging
NOTE: Refer to the user manual of the microscope for optimization of the set up.
6. Image Analysis
NOTE: Here, SG analysis on collapsed stacks using freeware ICY is described. Image analysis of 3D reconstructions may also be done using other specialized software. SG detection may be performed via a fully automated workflow established for this protocol (available at http://icy.bioimageanalysis.org/protocol/Stress_granule_detection_in_fluorescence_imaging). To use this protocol, the nuclei need to be stained with a DNA stain for the software to find the center of each cell, and the cell edges need to be marked by either a cytoplasmic marker (such as eIF3b) or actin stain for the software to identify the cell boundaries. The automatic workflow can be used to validate manually-derived results or directly for analysis when cell boundaries are detected with high confidence, which will mostly depend on the density of cells and the marker used to detect the cell boundaries.
To explain and demonstrate the protocol described in this manuscript, we characterized the image of clotrimazole-induced SGs in HeLa cells infected or not with the cytosolic pathogen S. flexneri. An outline of the procedure is presented in Figure 1, and includes virulent and avirulent S. flexneri streaked on Congo Red plates, bacteria preparation, infection, addition of environmental stress, sample fixation and staining, sample imaging and q...
The protocol outlined here describes the induction, localization, and analysis of SGs in non-infected cells and cells infected with the cytosolic pathogen S. flexneri in the presence or absence of exogenous stress. Using free imaging software, the protocols allows for the precise qualitative and quantitative analysis of SG formation to identify and statistically address differences in given phenotypes.
There are several critical steps within the protocol for the infection, SG-inductio...
The authors have nothing to disclose.
PS is a recipient of the Bill and Melinda Gates Grand Challenge Grant OPP1141322. PV was supported by a Swiss National Science Foundation Early Postdoc Mobility fellowship and a Roux-Cantarini postdoctoral fellowship. PJS is supported by an HHMI grant and ERC-2013-ADG 339579-Decrypt.
Name | Company | Catalog Number | Comments |
Primary Antibodies | |||
eIF3b (N20), origin goat | Santa Cruz | sc-16377 | Robust and widely used SG marker. Cytosolic staining allows cell delineation. Dilution 1 in 300 |
eIF3b (A20), origin goat | Santa Cruz | sc-16378 | Same target as eIF3b (N20) and in our hands was identical to eIF3b (N20). Dilution 1 in 300 |
eIF3A (D51F4), origin rabbit (MC: monoclonal) | Cell Signaling | 3411 | Part of multiprotein eIF3 complex with eIF3b . Dilution 1 in 800 |
eIF4AI, origin goat | Santa Cruz | sc-14211 | Recommended by (Ref # 13). Dilution 1 in 200 |
eIF4B, origin rabbit | Abcam | ab186856 | Good stress granule marker in our hands. Dilution 1 in 300 |
eIF4B, origin rabbit | Cell Signaling | 3592 | Recommended by Ref # 13. Dilution 1 in 100 |
eIF4G, origin rabbit | Santa Cruz | sc-11373 | Widely used SG marker. (Ref # 13): may not work well in mouse cell lines. Dilution 1 in 300 |
G3BP1, origin rabbit (MC: monoclonal) | BD Biosciences | 611126 | Widely used SG marker. Dilution 1 in 300 |
Tia-1, origin goat | Santa Cruz | sc-1751 | Widely used SG marker. Can also be found in P bodies when SG are present (Ref # 13). Dilution 1 in 300 |
Alexa-conjugated Secondary Antibodies | |||
A488 anti-goat , origin donkey | Thermo Fisher | A-11055 | Cross absorbed. Dilution 1 in 500 |
A568 anti-goat, origin donkey | Thermo Fisher | A-11057 | Cross absorbed. Dilution 1 in 500 |
A488 anti-mouse, origin donkey | Thermo Fisher | A-21202 | Dilution 1 in 500 |
A568 anti-mouse, origin donkey | Thermo Fisher | A10037 | Dilution 1 in 500 |
A647 anti-mouse, origin donkey | Thermo Fisher | A31571 | Dilution 1 in 500 |
A488 anti-rabbit, origin donkey | Thermo Fisher | A-21206 | Dilution 1 in 500 |
A568 anti-rabbit, origin donkey | Thermo Fisher | A10042 | Dilution 1 in 500 |
Other Reagents | |||
Shigella flexneri | Available from various laboratories by request | ||
Tryptone Casein Soya (TCS) broth | BD Biosciences | 211825 | Standard growth medium for Shigella, application - bacterial growth |
TCS agar | BD Biosciences | 236950 | Standard growth agar for Shigella, application - bacterial growth |
Congo red | SERVA Electrophoresis GmbH | 27215.01 | Distrimination tool for Shigell that have lost the virulence plasmid, application - bacterial growth |
Poly L lysine | Sigma-Aldrich | P1274 | Useful to coating bacteria to increase infection, application - infection |
Gentamicin | Sigma-Aldrich | G1397 | Selective killing of extracellular but not cytosolic bacteria, application - infection |
HEPES | Life Technologies | 15630-056 | PH buffer useful when cells are incubated at room-temperature, application - cell culture |
DMEM | Life Technologies | 31885 | Standard culture medium for HeLa cells, application - cell culture |
Fetal calf serum | Biowest | S1810-100 | 5% supplementation used for HeLa cell culture medium, application - cell culture |
Non-essential amino acids | Life Technologies | 11140 | 1/100 dilution used for HeLa cell culture medium, application - cell culture |
DMSO | Sigma-Aldrich | D2650 | Reagent diluent, application - cell culture |
Sodium arsenite | Sigma-Aldrich | S7400 | Potent stress granule inducer (Note: highly toxic, special handling and disposal required), application - stress inducer |
Clotrimazole | Sigma-Aldrich | C6019 | Potent stress granule inducer (Note:health hazard, special handling and disposal required), application - stress inducer |
PFA | Electron Microscopy Scences | 15714 | 4% PFA is used for standard fixation of cells, application - fixation |
Triton X-100 | Sigma-Aldrich | T8787 | Used at 0.03% for permeabilizationof host cells before immunofluorescent staining, application - permeabilization |
A647-phalloidin | Thermo Fisher | A22287 | Dilution is at 1/40, best added during 2ary antibody staining, application - staining |
DAPI | Sigma-Aldrich | D9542 | Nucleid acid stain used to visualize both the host nucleus and bacteria, application - staining |
Parafilm | Sigma-Aldrich | BR701501 | Paraffin film useful for immunofluorescent staining of coverslips, application - staining |
Prolong Gold | Thermo Fisher | 36930 | Robust mounting medium that works well for most fluorophores , application - mounting |
Mowiol | Sigma-Aldrich | 81381 | Cheap and robust mounting medium that works well for most fluorophores, application - mounting |
24-well cell culture plate | Sigma-Aldrich | CLS3527 | Standard tissue culture plates, application - cell culture |
12-mm glass coverslips | NeuVitro | 1001/12 | Cell culture support for immunofluorescent applications, application - cell support |
forceps | Sigma-Aldrich | 81381 | Cheap and obust mounting medium that works well for most fluorophores, application - mounting |
Programs and Equipment | |||
Prism | GraphPad Software | Data analysisand graphing program with robust statistical test options, application - data analysis | |
Leica SP5 | Leica Microsystems | Confocal microsope, application - image acquisition | |
Imaris | Bitplane | Professional image analysis program, application - data analysis | |
Excel | Microsoft | Data analysis and graphing program, application - data analysis |
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