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14:55 min
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March 5th, 2022
DOI :
March 5th, 2022
•0:02
Introduction
1:46
Creation of Position List
3:57
Automated Image Acquisition for the Remaining Experiment
4:34
Setting Up Automated Data Analysis
6:08
Quantification of Hydrogel Deformation
6:37
Quantification of Cell-ECM and Cell-cell Forces
8:44
Segmentation of the Individual Cells in the Images
9:47
Mapping of the Pixel Intensities on the Cells
11:06
Mapping of the Forces and Motion on the Cells
11:51
Tracking of the Cellular Indentities across the Experiment
12:51
Generation of Time Tracks of the Assessed Cellular Properties
13:27
Generation of the Heat Maps of the Assessed Cellular Properties
13:53
Representative Results
14:30
Conclusion
Transcription
Adherent cells exert forces on their surrounding, and those forces include the forces cells exert on the substrate, shown here in green, and the forces cells exert on their neighbors, shown in red. These forces can be measured in cellular monolayers using a technique called monolayer stress microscopy. Briefly, the technique involves preparing hydrogels containing tiny fluorescent beads, just under the top surface, and big fluorescent beads that are glued to the glass.
On this hydrogel, one sees the cells and cultures them to confluence or whatever state one desires to measure forces. The measurement of forces requires imaging the cellular monolayer, taking transmitted light images of the cells, and fluorescent light images of the tiny and big beads. Each of these images are acquired in the same vocal plane.
These images are acquired when the cells are attached and detached from the hydrogel. And a comparison of these two sets of images provides us the data that is necessary to quantify all these forces. That is where AcTrM and AnViM come into play.
After you plate the cells, for you to acquire images at the exact same location, at any desired instance, that protocol is programmed into AcTrM and then to subsequently analyze this data and visualize the results, that is the purpose of AnViM. In the next few minutes, we will walk you through the process of acquiring images for a confluence cell monolayer. Action step zero prompts the user to select the acquisition type.
A fresh acquisition to start a new experiment, or a continued acquisition to resume an earlier experiment. Click Fresh Acquisition to create a position list. Action step one lists all of your next step.
And these actions will be taken in the stage position list window here. Click Live in Micro-Manager to visualize the sample for manual adjustments. In live view, we will look at the phase.
Here it is clear. Now, one will need to look at the beads. Here, the beads can be visualized in fluorescence.
So select the channel appropriate for the top beads. It is also important that you are able to see a few bottom beads, so let's look at a channel for the bottom beads. What you see here is a blurry image of bottom beads, and that's completely fine as long as you can tell that the bottom beads are there, which you can in this image.
Position list, click Mark. This is how you create a position list. After you have created a position list, which was discussed in the previous video, follow the steps listed in action step two using the multidimensional acquisition window.
Let's say we want to perform a long time-lapse. Here, I'm going to indicate the number of images we want to be taken. The first channel is going to be the phase channel.
The next one is going to be of the top beads and the one after that is going to be the bottom beads. Click close in the multidimensional acquisition window and click OK in AcTrM step two. Output will be saved in the directory identified in the multi dimensional acquisition window.
Action step three will ask if the experiment needs recovery. The answer will typically be yes. Here iTACS asks, do we want to perform a refined recovery?
This first portion is going to get us pretty close to a refined recovery, but the bottom portion is going to get us even closer to a higher accuracy of repositioning. If the recovery is going to be done using a limited field of view, this option is offered, but for this experiment, we will not be selecting that option. At this point, the acquisition of a set of reference images is complete and Micro-Manager can be closed.
For image acquisition, one will start AcTrM. Select the magnification and choose the directory that contains data folders. Select choices for repositioning the plate along with the channel used for repositioning.
An interface is provided for matching what is currently seen in the camera with the saved images. If there is overlap, the images will display a red and green color along with black, and manual adjustment can be performed. Otherwise, hit accept, and acquisition will proceed.
We can now start FIJI. Select the first option in the MSM dropdown menu labeled pre-processing. Then, select the folder containing the tnimgs folder.
Next, we will have to define what channel corresponds to what image. For this example, Channel 0 is the transmitted light image which is the phase contrast image of the cells. The bottom bead image is Channel 2, and the top bead image is Channel 1.
And then, it is asking you where the cells cross and which side of the image. In this case, the cells are a monolayer advancing towards the right edge so we will deselect Right, and continue. Here a small region of top beads, located far from the monolayer, serve the same purpose as bottom bead images which would appear sparser and larger than those shown here.
Now it is asking us whether we want to change the brightness and contrast so the beads appear prominently. So we adjust using the slider bars in the menu, and once the beads appear prominent click OK.And now, we'll do position correction. If there is any shift, it will get rid of it.
And after it's done, it will create the analysis folder. Inside the analysis folder, it will create the position folder, P0, and the choices we made in the previous pre-processing menus are stored in analysis choices, such as what edges were crossed, pixel size, and which image is phase contrast and others. In the monolayer stress microscopy, or MSM dropdown menu, select MSM gel deformation.
From here, we will select the option that is suitable for our bead distribution. And as the data is being processed, you can see that a new displacement folder has appeared in the position folder. This will be where all of the output files will be stored.
This indicates that the analysis is complete. We are going to look at how to compute the forces that are exerted across the cell-ECM junction and cell-cell junction and also the cytoskeleton of individual cells of the monolayer. For that, select the third option.
And one is going to choose the directory that contains tnimgs and the analysis folder, which means one will select the example directory rather than any of these directories. Hit select, and it will ask you, what is the shear modulus of this gel? The shear modulus is 1250 and the thickness of the hydrogel in this example is 118 microns.
The anticipated noise level is provided here. Then, there is mean displacement is zero flag, which is not checked in this case. Select OK, and the implementation that calculates traction executes via a MATLAB function, which is how it is implemented in this version of AnViM.
Now it is ready to do the calculation for cell-cell or cytoskeletal forces. And the first question to ask is, is the monolayer confluent? In this particular case, we have an advancing monolayer and there is a no cell region on the right side of the frame.
So the answer is that the monolayer is not confluent, so we are going to say no. Now we are asked to draw a polygon around the largest non cell object. We select the appropriate methods for segmentation.
Here it is asking us to indicate the color of the cells in methods three and four, so here the cells are black so we will choose black. The segmentation that is produced from these different methods ends with some holes in the cell monolayer and some white regions in the no cell area. Here we can choose, fill spots automatically and hit OK.So now all spots are filled in the monolayer and no cell area.
And then, we'll then compute the mechanical stresses in the cellular monolayer. We have already performed part one where we segmented the cells from the no cell region, so we begin this step with part two that is segmentation of the individual cells and the images. One is going to select segmentation for individual cells.
And here it is asking us to choose the position directory. And there is some more information given here for these parameters. Then it asks you to draw a polygon around the smallest normal cell.
So what you draw here is used to calculate area and it is going to stipulate that anything smaller than this is not defined as a cell. And next it asks for the largest cell. So then we draw a polygon around the largest normal cell, and then it asks, which one is brighter?
Is the cell-cell interface brighter or are the cell centers brighter? So in this case, the cell-cell interface is brighter so I'm going to select cell-cell interface. So this indicates that the calculation has completed.
Let's begin by selecting map on cells intensities. First, iTACS asks the user to select the position directory, which is also known as the P0 folder. When finished, click Select.
Then the user is asked if he or she wants iTACS to detect cell division or quantify cellular fluorescence. In this case, we do not have any fluorescent proteins inside the cell so that's why we will elect to detect cell division. The next slide enables the user to define the size of the neighboring region, this is a unique analysis that AnViM performs where it looks at the properties of individual cells as well as the properties of the cells neighboring region.
Here, the user can choose the width of a cells neighboring region. In this case, we define the neighboring regions with 60 pixels. The first check box asks whether we want iTACS to collect properties of the cells, yes we do, and this check box asks whether we want iTACS to collect properties of the neighbors, yes, we want iTACS to do that as well.
Below these check boxes, iTACS provides more information about the check boxes if the user would like more detail about each check box. This indicates that the analysis is complete. Again, iTACS asks the user to select the position directory.
Then, the user is given the choice to map force data, create images of the force data, map velocity data, and create images of the velocity data. It's important to note that creating images does take time, so one can choose to do it now or wait to do it later. That's why the user is given the option to select the choices or not.
Here, iTACS asks the user to determine the size of the neighboring region again, and you can use the same size that you determined for mapping intensities, which was 60 pixels, in our case. And again, the user is asked to collect properties of the cells as well as its neighboring region. This indicates that the analysis is complete.
In the monolayer stress microscopy, or MSM dropdown menu, select results track data. First, iTACS asks the user to select the position directory, which is also known as the P0 folder. When finished, click Select.
Here, iTACS asks which frame number does the user want iTACS to start tracking data from. It is pretty safe to start tracking from frame number two, because the velocity cannot be determined for frame number one. Here, iTACS asks the user to indicate the maximum number of plots to fill simultaneously.
And essentially, this is a way to expedite data tracking. When finished, click OK, and the options for choosing variables during tracking are presented in a similar fashion to the options for generating heat maps. Common properties of interest are provided in the text box at the top of the window.
But if you would like to customize your variables, you simply need to delete everything in the text box and select the specific properties listed below. In the monolayer stress microscopy, or MSM dropdown menu, select results plot. After that, iTACS asks the user if the user wants to limit plotting to cells with unbroken track.
If you do not want to limit plotting to unbroken tracks, click No.But if you do want to limit plotting to cells with unbroken tracks, click Yes Here iTACS asks how many variables the user wants the program to plot. iTACS is capable of plotting up to three variables, and in this case, we'll only plot two variables to see the relationship between those factors. In the monolayer stress microscopy, or MSM dropdown menu, select results picture.
Here's the position directory, and when finished, click Select. iTACS then asks us to choose the starting frame. Here, we selected frame number two.
The options for making heat maps are presented in a similar fashion to the options for plotting time tracks of individual cells. With that, we conclude how to make a heat map. Here represents the time trace of cellular speed in cytoskeletal tension for cell number one.
The properties are shown on a shared vertical axis and the horizontal axis indicates time instance number, where the frames are acquired at 15 minute intervals. The second output is an array of heat maps one hour into the experiment. The properties shown here includes spread area, orientation, circularity, speed, direction of motion, maximum tension orientation, cytoskeletal tension, substrate tractions, and tension anisotropy of individual cells.
So this is a glimpse into one set of experiments. There are several other experimental situations where AnViM and AcTrM can help the user do the experiment reproducibly and these contacts are listed in the manuscript. Some of the key features of iTACS include automation of the experimental protocol, automated data analysis, and no engineering background is required.
The Integrative Toolkit to Analyze Cellular Signals (iTACS) platform automates the process of simultaneously measuring a wide variety of chemical and mechanical signals in adherent cells. iTACS is designed to facilitate community-driven development and enable researchers to use all platform features regardless of their educational background.