Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

We have developed a novel protocol for studying heterocellular population dynamics in response to perturbations. This manuscript describes an imaging-based platform that produces quantitative datasets for simultaneous characterization of multiple cellular phenotypes of heterocellular populations in a robust manner.

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The overall goal of this methodology is to quantitatively evaluate the dynamic phenotypic responses of heterocellular populations to pertubations while discriminating between subpopulations. Most physiological interactions happen in the presence of multiple cell types. This method can help cell biologists assess how heterogeneous cells respond to identical environmental pressures and how different ones influence one another.

This technique has several advantages, it discriminates between multiple cell types, it allows for simultaneous analysis on subpopulations including birth and death rates and morphological dynamics. While this protocol can be used to study many biological processes, we will demonstrate the work flow using H3255 tumor cells and CCD19LU fibroblast cells treated with Erlotinib, a chemotherapeutic drug. To begin, after preparing cell suspensions in tubes according to the text protocol, invert the tubes to mix the cells in solution to standardize seeding.

Then pipette 10 microliters of each cell suspension into a micro centrifuge tube, and add 10 microliters of trypan blue. Pipette 10 microliters of the solution into a cell counting slide and insert the slide into an automated cell counter. Repeat the cell count at least three times, or until obtained counts are consistent.

Using a multi channel pipette, seed a total of 1, 500 cells in 100 microliters of RPMI in the wells of a 96 well plate. Plate each cell suspension in triplicate with identical plate setups for each time point. Incubate the cells overnight.

Add DMSO to Erlotinib powder to make a 10 millimolar Erlotinib stock solution. Then, use cell culture medium to dilute the drug to two time the highest final concentration of 10 micromolar. Serially dilute the drug four times at a 1:10 ratio, for a total of five drug concentrations and a no drug control.

Pipette 100 microliters of drug solution into the appropriate wells of the 96 well plate of cells for a final drug concentration of 1x diluted in medium. Then to stain the cells for fluorescence based classification, prepare five micrograms per milliliter of nuclear stain and five micromolar dead cell stain in PBS. For morphology based classification, prepare five micrograms per milliliter of nuclear stain, five micromolar dead cell stain and five micromolar cell stain in PBS.

Add 20 microliters of dye solution to each well. Then, incubate the samples at 37 degree celsius protected from light for 30 minutes. To acquire images, use 70%ethanol to wipe the bottom of the plate and place the plate into the imaging chamber.

In the set up tab under channel selection, click the plus button to add the appropriate channels to the image. Under layout selection, set a z stack of test images every two microns, starting at zero microns and ending at 20 microns, to identify the plane of focus. Click snapshot, under each channel to evaluate intensities and optimize exposure times.

Enter higher or lower values under time as required. Nuclei in cells must be in focus in order to ensure the accuracy of the downstream analysis. On the plate schematic, highlight the appropriate wells.

Then in the wells schematic, highlight the 25 fields to be imaged in a similar manner. Under run experiment, identify the plate in plate name, then, click the start button to run the image acquisition protocol with a 10x objective to generate greyscale TIFF images in the chosen channels. After installing the open source softwares, CellProfiler and CellProfiler analysis, open CellProfiler, click File, Import, Pipeline from file and select the appropriate file.

Select the fluorescence based classification pipeline to classify cells as either, H3255 or CCD19LU based on EGFP intensity and to calculate morphology features. Click, View output settings, then select the location of the image files for analysis and the destination for the extracted data. Before running the analysis, the protocol should be tested in test mode to check the parameter values.

It is important that nuclear and cellular segmentation are accurate. This protocol was designed to identify cells with varying nuclei stain, ensure that the pixel value by which the nuclei are expanded, is large enough to mask the nuclei with the highest DNA stain, but small enough not to mask surrounding nuclei. To classify populations based on fluorescence, first, rescale GFP intensity range, then measure the GFP intensity of each identified nuclei and classify objects based on a user defined threshold.

Next, click analyze images to begin the analysis. When the analysis is complete, go to the default output folder to view the calculated data. For morphology based classification, run appropriate protocol in cell profiler to generate whole cell morphology features.

Open Cell Profiler Analysis software, select the database properties file generated in Cell Profiler and click, open. Click the Classifier tab at the top left of the screen. To call random cell images from the experiment, click fetch, images will appear in the unclassified window.

Manually classify cells as positive or negative, which here, represents H3255 or CCD19LU by selecting and dragging cells to the appropriate bin. After classifying at least 50 cells per subpopulation, click, Train Classifier and then click, Check Progress. Finally, click, Score All to generate a table with cell counts for each subpopulation.

In a heterocellular cold culture of H3255 tumor and CCD19LU fibroblast cells, nuclei were identified and segmented based on DNA staining. Cell populations were classified either by artificially induced fluorescence or training in machine learning algorithm to identify cell types based on morphology differences. There is a high concordance between the fluorescence and morphology based methodologies.

The two classification methods were independently implied to the same images and agreed 97.4%and 92.5%on the untreated and treated populations respectively. Here, changes in the cell morphology and response to Erlotinib treatment were investigated. After three days of drug treatment, a decrease in nuclei area and an increase in cellular area were observed from the H3255 cells.

This was possibly due to cell death. To test whether Erlotinib had a cytotoxic or cytostatic effect on cells, dead cells were identified based on propidium iodide staining. Both cytotoxic and cytostatic effects of Erlotinib on H3255 cells were observed, with an increase in the number of deaths and a decrease in the number of births following drug treatment.

Once mastered, this technique can be done in two non-consecutive hours if it is performed properly. Following this procedure, other methods such as, RA interference or CRISPR can be performed in order to address additional questions investigating functional genomics. After its development, this technique paved the way for researchers in the cancer biology field to explore the influence of stromal cells on tumor progression in multiple cancer types.

After watching this video, you should have a good understanding of how to study heterocellular responses to environmental stimuli, specifically how to analyze microscopy based imaging data in a high throughput manner.

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Journal (Biology)

Journal (Biology)

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

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