Salmonella invades and replicates inside intestinal epithelial cells both in Salmonella-specific vacuoles and free in the cytosol (hyper-replication). A high-throughput fluorescence microscopy-based protocol is described here to quantify the intracellular phenotypes of Salmonella by two complementary image analyses through ImageJ, reaching single-cell resolution and scoring.
Salmonella is an enteric pathogen able to invade the intestinal epithelium and replicate in enterocytes, both inside Salmonella-specific vacuoles and free in the cytosol (cytosolic hyper-replication). These different phenotypes of intracellular replication drive to different pathways of pathogenesis, i.e., cytosolic hyper-replication induces inflammatory cell death and extrusion into the gut lumen, while vacuolar replication leads to trans-epithelium penetration and systemic spread. Significant effort was made to create microscopy tools to study the behavior of Salmonella inside invaded cells, such as the pCHAR-Duo fluorescence reporter plasmid that allows discrimination between vacuolar and cytosolic bacteria by differential expression of mCherry and GFP. However, intracellular phenotypes are often manually scored, a time-consuming procedure that limits analysis to a small number of samples and cells. To overcome these limitations, two complementary and automated image analyses were developed using ImageJ, a freely available image analysis software. In the high-throughput protocol, epithelial cells were infected with Salmonella carrying pCHAR-Duo using 96-well plates. Imaging was performed using an automated fluorescence microscope. Then, two image analysis methods were applied to measure the intracellular behavior of Salmonella at different detail levels. The first method measures the overall intracellular bacterial load and the extent of cytosolic hyper-replication. It is fast and allows the scoring of a high number of cells and samples, making it suitable for high-throughput assays such as screening experiments. The second method performs single-cell analysis to determine the percentage of infected cells, the mean vacuolar load of Salmonella, and the cytosolic hyper-replication rate giving greater details about Salmonella behavior inside epithelial cells. The protocols can be performed by specifically designed ImageJ scripts to automatically run batch analyses of the major steps of Salmonella-enterocyte interaction.
Salmonella is the most frequently reported bacterial agent causing outbreaks of foodborne disease in the European Union1. The primary pathological manifestation of Salmonella infection is enteritis, which is the result of the pathogen behavior in the gut following ingestion and the consequent local inflammatory response2. However, Salmonella can also disseminate to extra-intestinal sites and cause systemic infection, especially in immunocompromised individuals. The type of interaction between Salmonella and the intestinal epithelium conditions the outcome of the infection. Once in the gut lumen, Salmonella invades and replicates inside intestinal epithelial cells. At the intracellular level, Salmonella can present two different replication phenotypes, the cytosolic hyper-replication and the intravacuolar slow replication within Salmonella-containing vacuoles (SCVs). The cytosolic hyper-replication induces inflammatory host cell death and Salmonella extrusion into the gut lumen3; the vacuolar replication leads to a trans-epithelium penetration and systemic spread4. Therefore, the extent of invasion and vacuolar vs. cytosolic replication influences the course of infection.
The genus Salmonella is very diverse, including thousands of serotypes with different host-ranges and abilities to cause disease. For example, S. Typhimurium is defined as a generalist serovar, because it infects multiple unrelated hosts, and represents one of the major causes of human salmonellosis. Differently, S. Derby is considered a swine-adapted serovar, as it is mostly isolated from the swine, but it is also reported in the top five of the serovars responsible for human infection1. However, knowledge about the bacterial behavior inside the epithelial cells is essentially limited to the study of a few reference strains, as S. Typhimurium SL1344, that do not represent the vast natural diversity of Salmonella pathogenicity. Characterizing the interaction of different strains of Salmonella with epithelial cells would contribute to understanding their different pathogenicity. For this reason, a high-throughput fluorescence microscopy-based protocol was developed to analyze the intracellular behavior of a large number of strains in a fast and largely automated way. In this protocol, infection of epithelial cells was performed in 96-well imaging plates and image acquisition was made using an automated fluorescence microscope. The pCHAR-Duo plasmid was used to observe the invasion and replication phenotypes of Salmonella inside epithelial cells through fluorescent microscopy5. This plasmid carries the gene encoding the red fluorescent reporter mCherry, constitutively expressed by all the transformed bacterial cells, and the gene encoding the green fluorescent reporter GFP, whose expression is activated by glucose-6-phosphate present exclusively in the cytosol of eukaryotic cells and absent in SCVs. Therefore, the plasmid allows discrimination between vacuolar and cytosolic bacteria by differential expression of mCherry and GFP reporters.
The vacuolar and cytosolic bacteria on microscopy images are commonly quantified by manual scoring6, but this is a time-consuming method that limits analysis to a small number of samples. Therefore, two complementary and automated image analyses were developed-area analysis and single-cell analysis-using ImageJ7, a freely available image analysis software. The area analysis measures the overall intracellular bacterial load and the extent of cytosolic hyper-replication by using data of areas occupied by epithelial cells, red and green Salmonellae in each acquired microscopy image. This method can be applied to images acquired at low magnification; therefore, it allows to score a high number of epithelial cells with few images, shortening the acquisition time. The single-cell analysis uses cell segmentation to determine the percentage of infected cells, the mean vacuolar load, and the percentage of infected cells undergoing cytosolic hyper-replication with single-cell resolution.
In this protocol, all steps of the image analysis are described in detail to be performed manually, but the same analysis can be automated by our specifically designed ImageJ scripts. These scripts also allow to run batch analyses to automatically analyze multiple images and thus speed up the execution of the method.
1. Infection of epithelial cells with Salmonella carrying pCHAR-Duo reporter plasmid
NOTE: A multichannel pipette is recommended.
2. Sample fixation and epithelial cell staining
NOTE: Maintain the samples protected from direct light exposure. Volumes are indicated for wells of a 96-well plate. Volume optimization is required for different cell culture plates or supports.
3. Image acquisition with an automated fluorescence microscope
NOTE: Here, low magnification (10x/0.3 NA, 1 µm/pixel objective) in step 3.1.1 for the area analysis and high magnification (40x/0.75 NA, 0.255 µm/pixel objective) in step 3.1.2 for the single-cell analysis are used in acquisition protocol. Other magnifications can be used, but optimization of image acquisition and analysis is required. If allowed by the available microscope, acquire images as Tile Regions (TRs), a "mosaic" of contiguous fields called tiles, to record large sample areas. Set the autofocus at the center of a TR instead of setting one for each tile, to reduce sample exposure during the autofocus procedure.
4. Image analysis using ImageJ
NOTE: Step 4.1 and step 4.2 are specifically designed for the experiment and acquisition described above. Other experimental settings could require optimization of analysis. The analysis of a single Acquisition.czi file is described. For the batch analysis, find the single-cell analysis script and area analysis script as supplemental files (Supplemental File 1 and Supplemental File 2). Labels used in the scripts and ImageJ commands are in bold in the sections below.
Infection of epithelial cells with Salmonella strains
This protocol was developed to analyze the cellular invasion and the cytosolic replication (Figure 1A) vs vacuolar load (Figure 1B) of Salmonella inside epithelial cells. The protocol was validated by using the three following Salmonella strains, S. Typhimurium SL1344 reference strain (S. Tm), S. Derby ER1175 wildtype (S. Derby wt) and the isogenic mutant of S. Derby ER1175 without sipA gene (S. Derby ΔsipA). S. Derby ER1175 strain was isolated from swine and belongs to the IZSLER surveillance collection of Salmonella isolates. The strains were selected in order to represent the phenotype diversity covered by the protocol. In particular, these strains were chosen because their behavior inside epithelial cells was already known to differ in terms of invasion or replication9; therefore, they were valuable controls to test whether the protocol allowed to quantitatively distinguish differences in intracellular Salmonella phenotypes. In particular, S. Tm and S. Derby wt were included because we had previously demonstrated that S. Tm has higher invasion and intracellular replication efficiency than S. Derby wt9 while S. Derby ΔsipA was added as a hyper-replication impaired strain since the virulence effector SipA plays a crucial role in the onset of hyper-replication10,11. It was previously reported for S. Tm that cytosolic replication starts 4 h post-invasion, and then the cytosolic population rapidly hyper-replicates to fill the epithelial cell by 8 h11,12. Consistently, 8 h long infection was suitable to observe and quantify the cytosolic hyper-replication phenotype also in S. Derby wt and S. Derby ΔsipA.
Area analysis
The area analysis in step 4.1 provides a measurement of the overall colonization of epithelial cells by Salmonella (infection ratio), together with a measurement of the hyper-replication (hyper-replication ratio). In the area analysis workflow described in Figure 2, the random noise is reduced, and then channels are split and processed independently. A threshold is set for each channel in order to exclude the background from the area measurement. Then, the area occupied by thresholded pixels is measured for each channel. The output of area analysis is a table reporting, for each acquisition file, the extension of the areas occupied by epithelial cell nuclei (blue channel), intracellular mCherry-expressing Salmonellae (red channel), and cytosolic hyper-replicating Salmonellae that express GFP (green channel) along with mCherry. The infection ratio is calculated by dividing the area occupied by mCherry-expressing Salmonellae by the area occupied by host cell nuclei. The results of the tested strains showed that S. Tm displays a significantly higher infection ratio compared to both S. Derby strains, as expected (Figure 3A). Therefore, these results demonstrate the efficacy of area analysis in detecting differences in the ability of Salmonella strains to colonize epithelial cells. Salmonella hyper-replication ratio is measured by dividing the area occupied by GFP-expressing Salmonellae by the area occupied by intracellular mCherry-expressing Salmonellae. Consistently with the role of SipA in determining hyper-replication, a significantly reduced hyper-replication ratio for S. Derby ΔsipA strain was measured compared to S. Derby wt, (Figure 3B). No hyper-replication difference was observed between S. Tm and S. Derby wt. Overall, area analysis effectively revealed different hyper-replication levels among the assayed strains.
Single-cell analysis
The single-cell analysis allows quantifying Salmonella invasion and vacuolar load vs. cytosolic replication inside epithelial cells with single-cell resolution. As described in step 4.2, for each acquisition file, blue, red, and green channels were processed independently (Figure 4). Specifically, the blue channel, corresponding to epithelial cells, was processed in step 4.2.3 to obtain cell segmentation. Then, segmented cells were added to the Region of Interest (ROI) Manager to obtain a list of ROIs, corresponding to all segmented cells uniquely labeled with y-x coordinates. In order to remove out-of-focus pixels of GFP- expressing hyper-replicating Salmonellae, the pixels of the green channel were subtracted from those of the red channel. The output table of single cell analysis reports, for each ROI, the area and the percentage of the ROI's area occupied by Salmonellae expressing the mCherry constitutive reporter only or the GFP cytosol-responsive reporter. The percentage of the cell's area occupied by mCherry-only expressing Salmonellae was processed in step 4.2.4 to calculate the percentage of infected cells and the mean vacuolar load (Figure 5A). Analysis of the vacuolar load showed that the S. Derby strains generate a mean vacuolar load significantly lower than S. Tm (Figure 5B). Conversely, only a slight and not significant reduction of the percentage of infected cells was observed in S. Derby strains compared to S. Tm (Figure 5A). The percentage of the cell's area occupied by GFP-expressing Salmonellae was processed in step 4.2.5 to obtain the hyper-replication rate. No difference was observed between S. Tm and S. Derby wt, while S. Derby ΔsipA displayed a significant decrease of hyper-replication, consistent with the result of the area analysis (Figure 5C) and the role of SipA in inducing hyper-replication.
Figure 1: Salmonella cytosolic hyper-replication and vacuolar load. Representative images of (A) the Salmonella hyper-replication and (B) the vacuolar load acquired at high magnification (40x) are shown. Panel B shows the different focus planes of cells containing hyper-replicating Salmonellae (z:7/8), compared to non-hyper-replicating Salmonellae (z:4/8). White scale bars are 10 µm. Please click here to view a larger version of this figure.
Figure 2: Workflow of the area analysis. The workflow of the area analysis is shown for a representative low magnification (10x) acquisition of INT407 cells infected for 8 h with Salmonella carrying the pCHAR-Duo plasmid (MOI 100). First, the random noise is reduced, and then the channels are split into C1, C2, and C3 and processed independently. A threshold is set for each channel in order to exclude the background from the area of measurement. Then, the area occupied by the thresholded pixels only-corresponding to cell nuclei in C1, all intracellular Salmonellae in C2, and cytosolic Salmonellae in C3-is measured for each channel. The images analyzed here are the results of four tiles acquired at 10x magnification fused together by stitching. White scale bars are 100 µm. Please click here to view a larger version of this figure.
Figure 3: Results of the area analysis. The results of the area analysis are shown. (A) Infection ratio is calculated by dividing the area occupied by mCherry-expressing Salmonellae (C2 channel), representing all the intracellular bacteria, by the area occupied by host cell nuclei (C1 channel). (B) Hyper-replication ratio was measured by dividing the area occupied by GFP-expressing Salmonellae (C3 channel), representing cytosolic hyper-replicating bacteria only, by the area occupied by all intracellular mCherry-expressing Salmonellae. Each dot represents a replicate. The analysis was conducted on three biological replicates, each tested in triplicate. The black lines indicate the mean values. The significance was calculated using a two-tailed t-test, and p values are reported. Please click here to view a larger version of this figure.
Figure 4: Workflow of the single-cell analysis. The workflow of the single-cell analysis is shown for a representative high magnification acquisition (40x) of INT407 cells infected for 8 h with Salmonella carrying the pCHAR-Duo plasmid (MOI 100). First, channels are split into C1, C2, and C3 and processed independently. Blue channel (C1), corresponding to epithelial cells, is processed to obtain cell segmentation, and then each segmented cell is defined as a Region of Interest (ROI) uniquely labeled with y-x coordinates. The red channel (C2) is processed by subtracting the green channel (C3) to remove out-of-focus cytosolic hyper-replicating Salmonellae, leaving all vacuolar Salmonellae expressing mCherry only, and then random noise was reduced, and the threshold is set to exclude the background from measurements. Finally, the area occupied by vacuolar Salmonellae for each ROI is measured. The green channel (C3), corresponding to total cytosolic GFP-expressing Salmonellae, is processed similarly. The images analyzed here are the results of 16 tiles fused together by stitching. White scale bars are 100 µm. Please click here to view a larger version of this figure.
Figure 5: Results of the single-cell analysis. The results of the single-cell analysis are shown. (A) The percentage of infected cells is obtained by dividing the number of cells with a percentage of area occupied by mCherry-only expressing Salmonellae> 0.2 by the total number of cells. (B) The mean vacuolar load was obtained by calculating the mean percent area occupied by mCherry-only expressing Salmonellae in the infected cells. (C) The hyper-replication rate was calculated by dividing the number of cells with a percentage of area occupied by GFP-expressing Salmonellae≥20% by the total number of infected cells. Data from three to four biological replicates tested in triplicate are reported. The bars indicate the standard error of measurement. The significance was calculated using a two-tailed t-test, and p values are reported. Please click here to view a larger version of this figure.
Supplemental File 1: Area analysis script. Please click here to download this File.
Supplemental File 2: Single-cell analysis script. Please click here to download this File.
The way Salmonella colonizes intestinal epithelial cells, influences the infection outcome. Upon invasion, the cytosolic hyper-replication induces inflammation of the gut3, whereas vacuolar replication can lead to systemic spread4. Salmonella strains can vary in their ability to invade and replicate inside intestinal epithelial cells9. Indeed, Salmonella is an extremely diverse genus comprising more than 2,500 serovars, which have different abilities to cause disease. In addition, Salmonella is the most frequently reported cause of foodborne outbreaks in the European Union, indicating a large spread in the human population1. Therefore, the availability of reliable, high-throughput methods for the quantification of the intracellular phenotypes of Salmonella is of great importance to evaluate differences in virulence among large numbers of Salmonella strains and ultimately allow an accurate and strain-specific risk assessment of this pathogen.
The protocol described here measures the behavior of Salmonella inside epithelial cells in a fast and automated way. The infection of epithelial cells is performed in 96-well imaging microplates and an automated fluorescence microscope is used for image acquisition, making the protocol suitable for high-throughput applications. This protocol takes advantage of the pCHAR-Duo plasmid, which allows distinguishing vacuolar from cytosolic Salmonellae through the differential expression of two fluorescent reporters5. The intracellular phenotypes of Salmonella are often analyzed by manual scoring, a time-consuming procedure that is unsuitable for the analysis of large numbers of strains and cell cultures per strain and prone to operator's errors and inter-operator variation. To overcome these limitations, two complementary and automated image analyses were developed, the area analysis and the single-cell analysis. ImageJ, a freely available software, was used to develop the two analyses. In order to accelerate the protocol execution, ImageJ scripts for batch analysis of multiple acquisition files with no operator intervention are provided as supplemental files.
The area analysis was designed to quantify, in a few steps, the overall colonization of epithelial cells (infection ratio) and the hyper-replication level (hyper-replication ratio) through the measurement of the areas specifically occupied by the nuclei of epithelial cells and by Salmonellae expressing either mCherry or mCherry together with GFP. The area analysis is applied to images acquired at low magnification, where both vacuolar and hyper-replicating Salmonellae are in focus in the same z-plane, and a large number of epithelial cells is displayed per microscopic field, reducing the size and number of acquisition files. The area analysis allows for an automated, fast, and computationally-light analysis of large number of samples, making it suitable for high-throughput assays such as screening experiments.
The single-cell analysis was designed to quantify Salmonella phenotypes inside epithelial cells with single-cell resolution, obtained through cell segmentation and measurement of the cellular area and the percentage of area occupied by vacuolar and cytosolic hyper-replicating Salmonellae. The overall colonization of epithelial cells characterized through the area analysis is here broken down into three quantitative parameters, the percentage of infected cells, the mean vacuolar load, and the hyper-replication rate, allowing to evaluate and quantify the contribution of each phenotype to the overall colonization, therefore, complementing the results of area analysis. The greater details offered by the single-cell analysis come at the cost of slower image acquisition and analysis. In fact, in order to achieve single-cell resolution, image acquisition is performed at high magnification. This implies that multiple z-planes are needed to observe both vacuolar and cytosolic Salmonellae in focus and that the acquisition of a large number of fields per sample is needed to score a high number of epithelial cells, thus extending acquisition time in comparison with area analysis. Furthermore, the analysis of several large acquisition files is computationally demanding, thus requiring a suitable workstation (a 6-core, 32 GB RAM workstation was used). Therefore, single-cell analysis can be used as a stand-alone in limited throughput conditions or as a second-level method coupled to the area analysis to gain a deeper understanding of the Salmonella phenotypes inside epithelial cells.
The two complementary analyses were validated by using S. Tm, S. Derby wt, and S. Derby ΔsipA, chosen because their behavior inside epithelial cells was already known to differ in terms of invasion or replication9,10. The results of the area and single-cell analyses show that the protocol allowed to quantitatively distinguish differences in intracellular Salmonella phenotypes in accordance with the characteristics of the tested strains. Furthermore, these results demonstrate that the single-cell analysis allows for quantification of the contribution of each intracellular phenotype (invasion, vacuolar load and cytosolic replication) to the overall colonization scored using the area analysis.
This protocol was applied here to study in vitro pathogenicity of different strains of Salmonella, but it can have other applications such as the study of random mutants to identify genes involved in the invasion and/or replication inside epithelial cells. In addition, the protocol can be adapted to analyze the behavior of Salmonella inside other cell lines than INT407 cells. It can also be used as the starting point to develop similar methods for studying cell-pathogen interaction of other intracellular microorganisms.
The authors have nothing to disclose.
The authors would like to thank Dr. Olivia Steele-Mortimer for sharing pCHAR-Duo plasmid. This work was funded by the Italian Ministry of Health, grants PRC2019014 and PRC2021004.
96-well imaging microplate | Eppendorf | 30741030 | Cell culture and infection |
Ampicillin | Sigma-Aldrich | 59349 | Bacteria culture |
Axio observer inverted microscope | ZEISS | Automated fluorescence microscope | |
Axiocam 305 Mono | ZEISS | Microscope Camera | |
Breathable sealing membrane | Sigma-Aldrich | Z380059 | Infection assay |
Colibrì 5/7 | ZEISS | Led light source | |
Collagen I rat tail | Life Technologies | A1048301 | Collagen coating |
DAPI | Invitrogen | D3571 | Cell staining |
Fetal bovine serum | Gibco | 10099-141 | Cell culture and infection |
Gentamicin | Sigma-Aldrich | G12664 | Infection assay |
Glacial acetic acid | Carlo Erba | 401391 | Collagen coating |
HCS CellMask Blue | Invitrogen | H32720 | Cell staining |
ImageJ | National Institutes of Health and the Laboratory for Optical and Computational Instrumentation (LOCI, University of Wisconsin) | Image processing software | |
Minimum Essential Eagle's Medium | Sigma-Aldrich | M5650-500ML | Cell culture and infection |
Paraformaldehyde 4% | Invitrogen | FB002 | Cell fixation |
Potassium chloride | PanReac AppliChem | 131494.1211 | PBS preparation |
Potassium phosphate monobasic | Sigma-Aldrich | 60220 | PBS preparation |
Sodium Chloride | PanReac AppliChem | 131659.1214 | Bacteria culture and PBS preparation |
Sodium phosphate Dibasic | Sigma-Aldrich | 71640 | PBS preparation |
Tissue Culture Flask 25 cm2 plug seal screw cap | Euroclone | ET7025 | Cell culture |
Triton X-100 | Biorad | 1610407 | Cell staining |
Trypsin-EDTA (0.25%) | Gibco | 25200056 | Cell culture and infection |
Tryptone | Oxoid | LP0042B | Bacteria culture |
Yeast extract | Biolife | 4122202 | Bacteria culture |