Biology
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Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture
Chapters
Summary February 23rd, 2018
Lens-free video microscopy enables us to monitor cell cultures directly inside the incubator. Here we describe the full protocol used to acquire and analyze a 2.7 day long acquisition of cultured HeLa cells, leading to a dataset of 2.2 x 106 measurements of individual cell morphology and 10584 cell cycle tracks.
Transcript
The overall goal of this methodology is to acquire and analyze the dynamics of the large population of adherent cells monitored by means of lens-free video microscopy. So, we think that this technique is interesting in many fields of biology and for studying cell proliferation or cell cystitis or drug screening, or different bio process monitoring. So this technique is label free and it's very simple.
But it's very effective in studying large cell populations. What idea for this method, when we shifted from the field of detecting bacteria to the field of imaging mammalian cells. Then it was of use that the biologist, they will need time-lapse acquisition of the circuiture directly into the incubator.
Then we built a customized lens-free video microscope that is compatible with the incubator and we developed a holographic reconstruction algorithm to get the picture of thousands of cells that are present in the very large field of view. Begin this procedure by coating a 6 well glass bottom plate with fibronectin at room temperature for 1 hour. After 1 hour, remove excess fibronectin and rinse out the 6 well glass bottom plate with PBS.
Hela cells, grown in DMEM, plus glutamine medium, supplemented with 10%heat in activated fetal calf serum, and 1%penicillin and streptomycin are used in this demonstration. Seed twenty thousand cells per culture plate. It is important to use a container with a glass bottom.
For the quality of the lens-free acquisition. Place the culture plate into the incubator on top of the lens-free video microscope. The lens-free video microscope used for this time-lapse acquisition is commercially available.
It has a metal oxide semi-conductor image sensor with an imaging area of 29.4 square millimeters, and a pixel pitch of 1.67 micrometers. Multiple wave length illumination is provided by a multi-chip light emitting diode device located above a 150 micro meter pinhole at a distance of approximately 5 centimeters from the cells. Before starting the time-lapse acquisition, it's important to check that there is no condensation on the cover plate.
Because condensation will degrade the image quality of the acquisition. If condensation has occurred on the cover of the culture plate, clean the cover. Control the video lens-free microscope with a commercially available acquisition software.
Which performs both the time-lapse acquisition and the holographic reconstruction. Enter the required input parameters in the software interface. Set the frame rate, to 1 acquisition every 10 minutes, the cell culture type to adherent, and the duration of the experiment to 3 days.
Start the time-lapse acquisition. This image shows an example of the full field of view of a raw acquisition in the blue channel on a 29.4 square millimeter area in one frame. Panel B is the detail of panel A, and panel C is the detail of panel B.The holographic reconstruction algorithm will automatically process the lens-free acquisition to obtain the phase image of the cell culture.
An example image of cells before phase unwrapping is shown, followed by an image after phase unwrapping. Cell tracking is accomplished using the TrackMate algorithm, An open source Fiji plug-in for the automated tracking of single particles. After loading, the full time-lapse acquisition into Fiji and configuring the algorithms as described in the text protocol, set the input parameters.
Set the estimated blob diameter to 15 pixels, the detector threshold to 0.25, the linking maximum distance to 15 pixels, the gap closing max distance to 15 pixels, and the number of spots in track to 3.5. The first step in the cell tracking algorithm is the detection of cells in the lens-free acquisition. Results of the cell tracking algorithm are shown, with all cell tracks shown over fifty frames, or about 8 hours.
With a color code corresponding to the median velocity. The bottom panel is a detailed image of the yellow rectangle from the top panel. A representative video clip of cell tracking is shown here.
At the end of the cell tracking process, select the analysis button to generate the results in the form of 3 text files. On the basis of this data, perform cell segmentation and detect cell divisions using dedicated algorithms, as detailed in the text protocol and supplementary code files. Compiling all single cell measurements over the full time-lapse acquisition, produces scatter plots of several metrics as a function of time.
The total number of cells in the full field of view, increases from two thousand up to fifteen thousand in 2.7 days. Multiplied by the number of time points, this leads to a large data set of detected cells. Each characterized by its coordinates and morphological features, such as dry mass, area, average thickness, major access length, and aspect ratio.
The combination of cell tracking and cell segmentation algorithms, enables kinetic measurements at the single cell level. This example shows the analysis of the cell track lasting about sixty-six hours, and exhibiting 4 cell divisions at the time points circled in yellow. Several metrics were computed as a function of time:cell surface area, dry mass, average thickness, and cell motility.
The distribution of the cell cycle duration for 2.7 day observation was close to agouzian. With a mean of 16.5 hours. Cell cycle lengths, measured automatically, are well correlated to the ones measured manually.
Other parameters were also examined, such as the cell initial dry mass, the final dry mass, and the average growth rate during the cell cycle. Once mastered, the complete data analysis of the time-lapse acquisition, can be done in a few hours, depending on the CPU configuration and the hardware performance. While attempting this procedure it's very important to carefully the initial cell concentration.
If the initial cell concentration is too large, the cell track algorithm will fail at defining properly, the cell trajectories. But, if the cell concentration is too low, the statistics of the complete analysis will be also too low. Following this procedure, automated like cell tracking analyses can be performed to answer other questions in the fields of:biology, fundamental biology, or chemotaxis.
This new technique, also paves the way for the monitoring of cell lineage that will hopefully bring, interesting insight to study cell cycle. After watching this video, you should have a good understanding of how to conduct time-lapse acquisition by the means of lens-free video microscopy and how to analyze a large population of cells.
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