3.28 Image-Based
Analysis
for Quantification
of Phagosomal
Acidification Using
pHrodo Reagent [8]
1. Proceed first to cell and mycobacteria detection (see steps 1–4
in Subheading 3.26).
2. Extend the size of GFP bacteria spots by four pixels of each
spot leading to define “bacterial phagosome region” as region
of interest (ROI).
3. Detect pHrodo fluorescence intensity (in the red channel) in
previously defined ROI.
4. Plot data as mean relative pHrodo intensity per phagosome.
5. Image and use the same analysis parameters to detect labeled
bacteria incubated in CO 2 independent medium at various pH
(pH 10 to pH 4).
6. Measure pHrodo mean intensity in corresponding detected
bacteria (at least n ¼ 100).
7. Plot intensity as a median pHrodo intensity per bacterium to
obtain standard curve representing pHrodo relative intensity
per bacterium in function of pH.
8. Estimate the relative phagosomal pH obtained by converting
pHrodo relative intensity per phagosome in pH value according to the standard curve.
3.29 Image-Based
Analysis
for Quantification
of Phagosomal
Vacuole Rupture [10]
1. Segment first cells, using the combined green (CCF4-AM) and
blue (CCF4) channels, in order to get an exhaustive cell detection. (Some cells are not properly loaded with CCF4-AM but
displayed a significant CCF4 staining). Use “no vacuole rupture” (heat-killed bacteria) and “vacuole rupture” (Bafilomycin) controls to set intensity thresholds.
2. Define the “cell region” as region of interest (ROI).
3. Measure the green and blue mean intensities for each cellular
object detected and calculate the ratio of blue (CCF4)/green
(CCF4-AM) intensities.
4. Segment spot on the red channel to detect the RFP-labeled
mycobacteria using a “spot” detection algorithm. Define
threshold intensity, i.e. pixels with intensity above the threshold, and identify as objects within the previously defined ROI.
5. Calculate all host-related parameters. Define “infected” and
“non-infected” cell populations and mean ratio of intensities
of CCF4/CCF4-AM for the two distinct cellular populations.
3.30 Image-Based
Analysis
for Quantification
of Oxidative Stress by
Reactive Oxygen
Species (ROS)
Measurement
1. Proceed first to cell and mycobacteria detection and quantification (see steps 1–8 in Subheading 3.26).
2. Define a manual threshold corresponding to the basal level of
ROS, using “non-infected” cell population and positive control for oxidative stress positive (LPS + IFNγ) to set intensity
thresholds.
High-Content Analysis of Host-Pathogen Interactions
695
Analysis
for Quantification
of Phagosomal
Acidification Using
pHrodo Reagent [8]
1. Proceed first to cell and mycobacteria detection (see steps 1–4
in Subheading 3.26).
2. Extend the size of GFP bacteria spots by four pixels of each
spot leading to define “bacterial phagosome region” as region
of interest (ROI).
3. Detect pHrodo fluorescence intensity (in the red channel) in
previously defined ROI.
4. Plot data as mean relative pHrodo intensity per phagosome.
5. Image and use the same analysis parameters to detect labeled
bacteria incubated in CO 2 independent medium at various pH
(pH 10 to pH 4).
6. Measure pHrodo mean intensity in corresponding detected
bacteria (at least n ¼ 100).
7. Plot intensity as a median pHrodo intensity per bacterium to
obtain standard curve representing pHrodo relative intensity
per bacterium in function of pH.
8. Estimate the relative phagosomal pH obtained by converting
pHrodo relative intensity per phagosome in pH value according to the standard curve.
3.29 Image-Based
Analysis
for Quantification
of Phagosomal
Vacuole Rupture [10]
1. Segment first cells, using the combined green (CCF4-AM) and
blue (CCF4) channels, in order to get an exhaustive cell detection. (Some cells are not properly loaded with CCF4-AM but
displayed a significant CCF4 staining). Use “no vacuole rupture” (heat-killed bacteria) and “vacuole rupture” (Bafilomycin) controls to set intensity thresholds.
2. Define the “cell region” as region of interest (ROI).
3. Measure the green and blue mean intensities for each cellular
object detected and calculate the ratio of blue (CCF4)/green
(CCF4-AM) intensities.
4. Segment spot on the red channel to detect the RFP-labeled
mycobacteria using a “spot” detection algorithm. Define
threshold intensity, i.e. pixels with intensity above the threshold, and identify as objects within the previously defined ROI.
5. Calculate all host-related parameters. Define “infected” and
“non-infected” cell populations and mean ratio of intensities
of CCF4/CCF4-AM for the two distinct cellular populations.
3.30 Image-Based
Analysis
for Quantification
of Oxidative Stress by
Reactive Oxygen
Species (ROS)
Measurement
1. Proceed first to cell and mycobacteria detection and quantification (see steps 1–8 in Subheading 3.26).
2. Define a manual threshold corresponding to the basal level of
ROS, using “non-infected” cell population and positive control for oxidative stress positive (LPS + IFNγ) to set intensity
thresholds.
High-Content Analysis of Host-Pathogen Interactions
695