Name: live-cell imaging of single-cell arrays (lisca) - a versatile technique to quantify cellular kinetics
Uploaded: 2021-03-18T14:30:00
Description: Watch this Scientific Journal Video about Live-cell Imaging of Single-Cell Arrays LISCA - a Versatile Technique to Quantify Cellular Kinetics at JoVE.com

This work was supported by grants from the German Science Foundation (DFG) to Collaborative Research Center (SFB) 1032. Support by the German Federal Ministry of Education, Research and Technology (BMBF) under the cooperative project 05K2018-2017-06716 Medisoft as well as a grant from the Bayerische Forschungsstiftung are gratefully acknowledged. Anita Reiser was supported by a DFG Fellowship through the Graduate School of Quantitative Biosciences Munich (QBM).

<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/62025/62025fig02.jpg" /> 
Figure 2: Data acquisition combining single-cell microarrays (A) with scanning time-lapse microscopy (B).&#160;As preparation of the time-lapse experiment, a single-cell array with a 2D micropattern of adhesion squares is prepared (1), followed by cell seeding and the alignment of the cells on the micropattern (2) as well as the connection of a perfusion system to the six-channel slide,...

<ol>
	<li>Altschuler, S. J., Wu, L. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cellular+heterogeneity:+do+differences+make+a+difference.">Cellular heterogeneity: do differences make a difference.</a> Cell. 141 (4), 559-563 (2010).</li><li>Locke, J. C., Elowitz, M. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Using+movies+to+analyse+gene+circuit+dynamics+in+single+cells.">Using movies to analyse gene circuit dynamics in single cells.</a> Nature Reviews Microbiology. 7 (5), 383-392 (2009).</li><li>Spencer, S. L., Gaudet, S., Albeck, J. G., Burke, J. M., Sorger, P. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Non-genetic+origins+of+cell-to-cell+variability+in+TRAIL-induced+apoptosis.">Non-genetic origins of cell-to-cell variability in TRAIL-induced apoptosis.</a> Nature. 459 (7245), 428-432 (2009).</li><li>El-Ali, J., Sorger, P. K., Jensen, K. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cells+on+chips.">Cells on chips.</a> Nature. 442 (7101), 403-411 (2006).</li><li>Segerer, F. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Versatile+method+to+generate+multiple+types+of+micropatterns.">Versatile method to generate multiple types of micropatterns.</a> Biointerphases. 11 (1), 011005 (2016).</li><li>Piel, M., Th&#233;ry, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Micropatterning in cell biology, part A/B/C. , (2014).</li><li>Reiser, A., Zorn, M. L., Murschhauser, A., R&#228;dler, J. O., Ertl, P., Rothbauer, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Cell-Based Microarrays: Methods and Protocols. , 41-54 (2018).</li><li>Picone, R., Baum, B., McKendry, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Methods in cell biology. 119, 73-90 (2014).</li><li>Reiser, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Single-cell time courses of mRNA transport and translation kinetics. , (2019).</li><li>. Softmatter LMU-Raedler Group Available from: <a target="_blank" href="https://github.com/SoftmatterLMU-RaedlerGroup/pyama">https://github.com/SoftmatterLMU-RaedlerGroup/pyama</a> (2020)</li><li>. MIAAB, 29262 Available from: <a target="_blank" href="https://github.com/SoftmatterLMU-RaedlerGroup/pyama">https://github.com/SoftmatterLMU-RaedlerGroup/pyama</a> (2020)</li><li>Reiser, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Correlation+of+mRNA+delivery+timing+and+protein+expression+in+lipid-based+transfection.">Correlation of mRNA delivery timing and protein expression in lipid-based transfection.</a> Integrative Biology. 11 (9), 362-371 (2019).</li><li>Reiser, A., Wosch&#233;e, D., Mehrotra, N., Krzyszto&#324;, R. S., Strey, H. H., R&#228;dler, J. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Supplementing+data+and+code+for:+"Correlation+of+mRNA+delivery+timing+and+protein+expression+in+lipid-based+transfection".">Supplementing data and code for: "Correlation of mRNA delivery timing and protein expression in lipid-based transfection".</a> Zenodo. , (2019).</li><li>Ferizi, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stability+analysis+of+chemically+modified+mRNA+using+micropattern-based+single-cell+arrays.">Stability analysis of chemically modified mRNA using micropattern-based single-cell arrays.</a> Lab on a Chip. 15 (17), 3561-3571 (2015).</li><li>Fr&#246;hlich, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multi-experiment+nonlinear+mixed+effect+modeling+of+single-cell+translation+kinetics+after+transfection.">Multi-experiment nonlinear mixed effect modeling of single-cell translation kinetics after transfection.</a> NPJ systems biology and applications. 4 (1), 1-12 (2018).</li><li>Krzyszto&#324;, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+kinetics+of+siRNA-mediated+mRNA+degradation.">Single-cell kinetics of siRNA-mediated mRNA degradation.</a> Nanomedicine: Nanotechnology, Biology and Medicine. 21, 102077 (2019).</li><li>R&#246;ttgermann, P. J., Alberola, A. P., R&#228;dler, J. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cellular+self-organization+on+micro-structured+surfaces.">Cellular self-organization on micro-structured surfaces.</a> Soft Matter. 10 (14), 2397-2404 (2014).</li><li>R&#246;ttgermann, P. J., Dawson, K. A., R&#228;dler, J. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Time-resolved+study+of+nanoparticle+induced+apoptosis+using+microfabricated+single+cell+arrays.">Time-resolved study of nanoparticle induced apoptosis using microfabricated single cell arrays.</a> Microarrays. 5 (2), 8 (2016).</li><li>Murschhauser, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+high-throughput+microscopy+method+for+single-cell+analysis+of+event-time+correlations+in+nanoparticle-induced+cell+death.">A high-throughput microscopy method for single-cell analysis of event-time correlations in nanoparticle-induced cell death.</a> Communications Biology. 2 (1), 1-11 (2019).</li><li>Chatzopoulou, E. I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chip-based+platform+for+dynamic+analysis+of+NK+cell+cytolysis+mediated+by+a+triplebody.">Chip-based platform for dynamic analysis of NK cell cytolysis mediated by a triplebody.</a> Analyst. 141 (7), 2284-2295 (2016).</li><li>Sztilkovics, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+adhesion+force+kinetics+of+cell+populations+from+combined+label-free+optical+biosensor+and+robotic+fluidic+force+microscopy.">Single-cell adhesion force kinetics of cell populations from combined label-free optical biosensor and robotic fluidic force microscopy.</a> Scientific Reports. 10 (1), 1-13 (2020).</li></ol>

Here we described LISCA as a versatile technique to follow cellular kinetics of intracellular fluorescent labels at the single-cell level. In order to perform a successful LISCA experiment, each of the described steps of the protocol section must be established individually and then all steps must be combined. Each of the three major aspects of LISCA feature crucial steps.
Single-cell microarray fabrication 
The quality of the microarray is crucial as the cellular alignment on th...

In recent years, the importance of single-cell experiments has become apparent. Data from single cells allow the investigation of cell-to-cell variability, the resolution of intracellular parameter correlations and the detection of cellular kinetics that remain hidden in ensemble measurements1,2,3. In order to investigate cellular kinetics of thousands of single cells in parallel, new approaches are needed that enable monitoring the cells under standardized conditions over a time period of several hours up to several days followed by a quantitative data analysis 4. Here, we present Live-cell Imaging of Single-Cell Arrays (LISCA), which combines the use of microstructured arrays with time-lapse microscopy and automated image analysis.
Several methods for generating microstructured single-cell arrays have been established and published in literature5,6. Here, we briefly describe Microscale Plasma-Initiated Protein Patterning (&#181;PIPP). A detailed protocol of the single-cell array fabrication using &#181;PIPP is also found in reference7. The use of single-cell arrays enables alignment of thousands of cells on standardized adhesion spots presenting defined microenvironments for each cell and thus reduces a source of experimental variability (Figure 1A). Single-cell arrays are used to monitor the time courses of fluorescent markers purposed to indicate a variety of cellular processes. Long-term microscopy in scanning time-lapse mode allows for monitoring a large area of the single-cell arrays and hence sampling single-cell data in high-throughput over an observation time of several hours or even days. This generates time-line stacks of images from each position of the array (Figure 1B). In order to reduce the large amount of image data and to extract the desired single-cell fluorescence time courses in an efficient way, automated image processing is required that takes advantage of the positioning of cells (Figure 1C).
The challenge of LISCA is to adapt the experimental protocols and computational tools to form a high-throughput assay that generates quantitative and reproducible data of cellular kinetics. In this article we provide a step-by-step description of the individual methods and how they are combined in a LISCA assay. As an example, we discuss the time course of enhanced green fluorescent protein (eGFP) expression after artificial mRNA delivery. eGFP expression following mRNA delivery is described by reaction rate equations modeling translation and degradation of mRNA. Fitting the model function for the time course of eGFP concentration to the LISCA readout of the fluorescence intensity for each individual cell over time yields best estimates of model parameters such as the mRNA degradation rate. As a representative result we discuss the mRNA delivery efficiency of two different lipid-based transfection agents and how their parameter distributions differ.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/62025/62025fig01.jpg" /> 
Figure 1: Representation of the LISCA workflow combining (A) micro-patterned single-cell arrays (B) scanning time-lapse microscopy and (C) automated image analysis of recorded image series.&#160;The single-cell arrays consist of a two-dimensional pattern of cell-adhesive squares with a cell-repellent interspace leading to an arrangement of the cells on the micropattern, as can be seen in the phase-contrast image as well as the fluorescence image of eGFP expressing cells (A). The entire microstructured area is imaged in a scanning time-lapse mode repeatedly taking images at a sequence of positions (B). Recorded image series are processed to read out the fluorescence intensity per cell over time (C). Scale bars: 500 &#181;m (A), 200 &#181;m (C).&#160;<a href="https://www.jove.com/files/ftp_upload/62025/62025fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Adtech Polymer Engineering PTFE Microtubing&#160;</td>
			<td>Fisher Scientific</td>
			<td>10178071</td>
			<td></td>
		</tr>
		<tr>
			<td>baking oven</td>
			<td>Binder</td>
			<td>9010-0190</td>
			<td></td>
		</tr>
		<tr>
			<td>CFI Plan Fluor DL 10x</td>
			<td>Nikon</td>
			<td>MRH20100</td>
			<td></td>
		</tr>
		<tr>
			<td>Desiccator</td>
			<td>Roth</td>
			<td>NX07.1</td>
			<td></td>
		</tr>
		<tr>
			<td>Eclipse Ti-E</td>
			<td>Nikon</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>eGFP mRNA</td>
			<td>Trilink</td>
			<td>L-7601</td>
			<td></td>
		</tr>
		<tr>
			<td>Female Luer to Tube Connector</td>
			<td>MEDNET</td>
			<td>FTL210-6005</td>
			<td></td>
		</tr>
		<tr>
			<td>Fetal bovine serum</td>
			<td>Thermo Fisher</td>
			<td>10270106</td>
			<td></td>
		</tr>
		<tr>
			<td>Fibronectin</td>
			<td>Yo Proteins</td>
			<td>663</td>
			<td></td>
		</tr>
		<tr>
			<td>Filter set eGFP</td>
			<td>AHF</td>
			<td>F46-002</td>
			<td></td>
		</tr>
		<tr>
			<td>Fisherbrand&#160;Translucent Platinum-Cured Silicone Tubing</td>
			<td>Fisher Scientific</td>
			<td>11768088</td>
			<td></td>
		</tr>
		<tr>
			<td>HEPES (1 M)</td>
			<td>Thermo Fisher</td>
			<td>15630080</td>
			<td></td>
		</tr>
		<tr>
			<td>Incubation Box</td>
			<td>Okolab</td>
			<td>OKO-H201</td>
			<td></td>
		</tr>
		<tr>
			<td>incubator</td>
			<td>Binder</td>
			<td>9040-0012</td>
			<td></td>
		</tr>
		<tr>
			<td>L-15 without phenol red</td>
			<td>Thermo Fisher</td>
			<td>21083027</td>
			<td></td>
		</tr>
		<tr>
			<td>Lipofectamine 2000</td>
			<td>Thermo Fisher</td>
			<td>11668027</td>
			<td></td>
		</tr>
		<tr>
			<td>Male Luer</td>
			<td></td>
			<td></td>
			<td>in-house fabricated consisting of teflon</td>
		</tr>
		<tr>
			<td>Male Luer to Tube Connector</td>
			<td>MEDNET</td>
			<td>MTLS210-6005</td>
			<td>alternative to in-house fabricated male luers</td>
		</tr>
		<tr>
			<td>NaCl (5 M)</td>
			<td>Thermo Fisher</td>
			<td>AM9760G</td>
			<td></td>
		</tr>
		<tr>
			<td>Needleless Valve to Male Luer Connector</td>
			<td>MEDNET</td>
			<td>NVFMLLPC</td>
			<td></td>
		</tr>
		<tr>
			<td>NIS Elements</td>
			<td>Nikon</td>
			<td></td>
			<td>Imaging software Version 5.02.00</td>
		</tr>
		<tr>
			<td>NOA81</td>
			<td>Thorlabs</td>
			<td>NOA81</td>
			<td>Fast Curing Optical Adhesive for tube system assembly</td>
		</tr>
		<tr>
			<td>Opti-MEM</td>
			<td>Thermo Fisher</td>
			<td>31985062</td>
			<td></td>
		</tr>
		<tr>
			<td>PCO edge 4.2 M-USB-HQ-PCO</td>
			<td>pco</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Phosphate buffered saline (PBS)</td>
			<td></td>
			<td></td>
			<td>in-house prepared</td>
		</tr>
		<tr>
			<td>Plasma Cleaner</td>
			<td>Diener Femto</td>
			<td>Pico-BRS</td>
			<td></td>
		</tr>
		<tr>
			<td>PLL(20 kDa)-g[3.5]-PEG(2 kDa)</td>
			<td>SuSoS AG</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>silicon wafer mit mircorstructures</td>
			<td></td>
			<td></td>
			<td>in-house fabricated</td>
		</tr>
		<tr>
			<td>Sola Light Engine</td>
			<td>Lumencor</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>sticky slide VI 0.4&#160;</td>
			<td>ibidi</td>
			<td>80608</td>
			<td></td>
		</tr>
		<tr>
			<td>Sylgard 184 Silicone Elastomer Kit</td>
			<td>Dow Corning</td>
			<td>1673921</td>
			<td></td>
		</tr>
		<tr>
			<td>Tango 2</td>
			<td>M&#228;rzh&#228;user</td>
			<td>00-24-626-0000</td>
			<td></td>
		</tr>
		<tr>
			<td>Ultrapure water</td>
			<td></td>
			<td></td>
			<td>in-house prepared</td>
		</tr>
		<tr>
			<td>uncoated coverslips</td>
			<td>ibidi</td>
			<td>10813</td>
			<td></td>
		</tr>
		<tr>
			<td>Injekt-F Solo, 1 mL</td>
			<td>Omilab</td>
			<td>9166017V</td>
			<td>with replacement sporn</td>
		</tr>
	</tbody>
</table>

live-cell imaging of single-cell arrays (lisca) - a versatile technique to quantify cellular kinetics

Live-cell Imaging of Single-Cell Arrays (LISCA) is a versatile method to collect time courses of fluorescence signals from individual cells in high throughput. In general, the acquisition of single-cell time courses from cultured cells is hampered by cell motility and diversity of cell shapes. Adhesive micro-arrays standardize single-cell conditions and facilitate image analysis. LISCA combines single-cell microarrays with scanning time-lapse microscopy and automated image processing. Here, we describe the experimental steps of taking single-cell fluorescence time courses in a LISCA format. We transfect cells adherent to a micropatterned array using mRNA encoding for enhanced green fluorescent protein (eGFP) and monitor the eGFP expression kinetics of hundreds of cells in parallel via scanning time-lapse microscopy. The image data stacks are automatically processed by newly developed software that integrates fluorescence intensity over selected cell contours to generate single-cell fluorescence time courses. We demonstrate that eGFP expression time courses after mRNA transfection are well described by a simple kinetic translation model that reveals expression and degradation rates of mRNA. Further applications of LISCA for event time correlations of multiple markers in the context of signaling apoptosis are discussed.

The LISCA approach enables to efficiently collect fluorescence time courses from single cells. As a representative example we outline how the LISCA method is applied to measure single-cell eGFP expression after transfection. The data of the LISCA experiment is used to assess mRNA delivery kinetics, which is important for the development of efficient mRNA drugs.
In particular we demonstrate the different impact of two lipid-based mRNA delivery systems with respect to the time point of translati...

Watch this Scientific Journal Video about Live-cell Imaging of Single-Cell Arrays LISCA - a Versatile Technique to Quantify Cellular Kinetics at JoVE.com

Live-cell Imaging of Single-Cell Arrays LISCA - a Versatile Technique to Quantify Cellular Kinetics

We present a method for the acquisition of fluorescence reporter time courses from single cells using micropatterned arrays. The protocol describes the preparation of single-cell arrays, the setup and operation of live-cell scanning time-lapse microscopy and an open-source image analysis tool for automated preselection, visual control and tracking of cell-integrated fluorescence time courses per adhesion site.

Live-cell Imaging of Single-Cell Arrays (LISCA) - a Versatile Technique to Quantify Cellular Kinetics

Live-cell Imaging of Single-Cell Arrays (LISCA) is a versatile method to collect time courses of fluorescence signals from individual cells in high ...

Live-Cell Imaging of Single-Cell Arrays called LISCA are also an automated readout of the fluorescent time courses of hundreds of individual cells. The advantage of the approach is that individual cell responses are recorded from spatially isolated cells in identical micro environments, allowing an efficient emission analysis with great statistics. To fabricate a single-cell array, use a scalpel to cut a single PDMs masterpiece containing six micro powder stripes out of the PDMs layer, and place the masterpiece on the lab bench with the micro pattern facing up.Use a razor blade to cut each of the six micropattern stripes into a PDMs stamp, cutting off some of the patterned areas to ensure that the edges of the stamp are open. Next, carefully scratch the protective foil of the cover slip of a six chamber slide to mark the channel positions of the slide and place the cover slip on the bench with the protective foil facing down. Use tweezers to place the stamps on the cover slip at the marked channel positions, with the micro patterns facing down, and check the attachment of the stamps under a microscope.The squares in contact with the slide will appear darker than the interspace. The pattern quality is decreased by squares that are not properly attached to the slide. If the stamps have securely attached treat the cover slip and the stamps with oxygen plasma at 0.2 millibars of pressure and approximately 40 Watts for three minutes to make the surfaces between the PDMs stamps and the cover slip hydrophilic.At the end of the plasma cleaning, place the cover slip into a biosafety cabinet and add 15 microliters of pegylated poly-l-lysine solution to each stamp so that the solution is absorbed into the hydrophilic pattern of the stamp. After 20 minutes, rinse the stamps with one milliliter of ultrapure water. Use tweezers to remove the stamps from the slide and rinse the cover slip a second time with a second milliliter of ultrapure water.When the cover slip has dried completely, attach a six channel sticky slide to the cover slip taking care that the micro patterned areas align with the bottom of the channels. And add 40 microliters of PBS and 40 microliters of fibronectin solution to each channel. To mix the two solutions, remove 40 microliters from one reservoir and add it to the opposite reservoir of the same channel three times to generate a homogenous solution.When all of the channels have been mixed, incubate the slide for 45 minutes at room temperature before washing each channel three times with 120 microliters of PBS per wash. Exchange the PBS to 37 degrees Celsius, fully supplemented cell growth medium in the channels by adding 120 microliters medium to one reservoir and remove it from the opposite reservoir. Add 40 microliters of a 400, 000 cells per milliliter cells suspension of interest and 40 microliters of cell growth medium to each channel, and mix the cell solution with the medium as demonstrated.After mixing, remove 40 microliters of suspension from each channel so that only the channels are filled with cell suspension, and place the slide into a cell culture incubator. After one hour, check for cell adhesion by phase contrast microscopy, and add 120 microliters of 37 degrees Celsius cell growth medium to each channel, then return the slide to the cell culture incubator for three more hours. To set up a perfusion system, connect a one milliliter syringe filled with 37 degrees Celsius cell growth medium to the inlet tube of the system, and use the valve to fill the tube with medium.Connect the inlet tube to the reservoir of one channel, taking care that no air bubbles are trapped, and connect a serial connector to the reservoir opposite to the inlet tube of the current channel. Connect the rest of the channels as demonstrated until the required number of channels are connected in series. And connect the outlet tube directly to the free reservoir of the final channel.Then fill the connected tube with medium to confirm that the perfusion system does not leak. For time-lapse imaging of the cells, to set up a time lapse protocol for recording a phase contrast image and a fluorescence image, set the optical configuration for phase contrast imaging and fluorescence imaging. Use a 10 times objective, the appropriate fluorescence filters and an automated focus correction system to ensure a better image quality for the longterm measurements.Select a 10 millisecond exposure time for the phase contrast imaging and a 750 millisecond exposure time for recording the EGFP fluorescence intensity. Set a time schedule with a 10-minute time interval between the consecutive loops through the position list and an observation time of 30 hours. Next, place the six channels slide on the single cellar raise in the sample holder of the 37 degrees Celsius heating chamber of the microscope and tape the perfusion system tubing to the stage.Insert the free ends of the outlet tubes into a 15 milliliter conical tube to collect the liquid waste. And set the position list for the scanning time lapse measurement, taking care that the number of positions will be able to be scanned within the defined time interval between consecutive loops through the position list. Then start the time lapse measurement.For transfection of the cells with a fluorescent marker, use a syringe to flush the tubing system with one milliliter of 37 degrees Celsius PBS, taking care that the microscope stage doesn't move. After flushing, fill the system with 300 microliters of serum reduced medium supplemented with the mRNA of interest, to a final concentration of 0.5 nanograms of mRNA per microliter, and allow the lipoplexes to incubate for one hour. At the end of the incubation, flush the system with one milliliter of 37 degrees Celsius complete cell growth medium to remove any unbound mRNA.At the end of the analysis, view the channels listed in the channel menu and scroll through the timeframes to inspect that preselected cells and their integrated fluorescent signals. Click on a cell of interest to highlight its fluorescence time course, or click on a time course to find the corresponding cell. Press shift while clicking on a cell to select or de-select it.De-select any cells that are not viable or not confined to an adhesion spot or that are attached to another cell to exclude them from further analysis. When all of the cells are selected or deselected appropriately, save the single cell time courses for the cell area and the integrated fluorescence in an appropriate directory. To quantify the translation onset time after the transfection, and the strength of the cellular EGFP expression, a three-stage translation model can be employed.The model solution for EGFP can be fitted to single cell time courses as illustrated. Here, histograms of the translation onset time and the expression rate of lipoplex transfected cells can be observed. As both parameters are estimated for each cell, the correlation of these parameters can be analyzed as demonstrated in the scatter plot, and compared to cells transfected with lipid nanoparticles.As illustrated, cells transfected with lipid nanoparticles exhibit less cell-to-cell variability compared to cells transfected with lipoplexes. And the population average demonstrates a faster onset of translation, as well as a higher expression rate. Our approach can also be adapted to alternative micro-patterning methods.Most important for LISCA is a good cell confinement and a combination of automated image analysis with a convenient user supervision. As you have seen, cell behavior is heterogeneous. And single-cell time lapse movies provide access to unbiased dynamics of the inherent biochemical networks.For example, in green expression, apoptosis or cell killing assays.

Research

JoVE Journal

Biology

Imaging Mismatch Repair and Cellular Responses to DNA Damage in Bacillus subtilis

Imaging Mismatch Repair and Cellular Responses to DNA Damage in Bacillus subtilis

Both prokaryotes and eukaryotes respond to DNA damage through a complex set of physiological changes. Alterations in gene expression, the redistribution ...

Live-cell Imaging and Quantitative Analysis of Embryonic Epithelial Cells in Xenopus laevis

Live-cell Imaging and Quantitative Analysis of Embryonic Epithelial Cells in Xenopus laevis

Embryonic epithelial cells serve as an ideal model to study morphogenesis where multi-cellular tissues undergo changes in their geometry, such as changes ...

Live Cell Imaging of Early Autophagy Events: Omegasomes and Beyond

Autophagy is a  cellular response triggered by the lack of nutrients, especially the absence of  amino acids. Autophagy is defined by the formation of ...

Single-cell Microinjection for Cell Communication Analysis

Gap junctions are intercellular channels that allow the communication of neighboring cells. This communication depends on the contribution of a ...

Techniques to Induce and Quantify Cellular Senescence

In response to cellular stress or damage, proliferating cells can induce a specific program that initiates a state of long-term cell-cycle arrest, termed ...

Single-cell Microfluidic Analysis of Bacillus subtilis

Single-cell Microfluidic Analysis of Bacillus subtilis

Microfluidic technology overcomes many of the limitations to traditional analytical methods in microbiology. Unlike bulk-culture methods, it offers ...

Analysis of Beta-cell Function Using Single-cell Resolution Calcium Imaging in Zebrafish Islets

Pancreatic beta-cells respond to increasing blood glucose concentrations by secreting the hormone insulin. The dysfunction of beta-cells leads to ...

LDL Cholesterol Uptake Assay Using Live Cell Imaging Analysis with Cell Health Monitoring

The regulation of LDL cholesterol uptake through LDLR-mediated endocytosis is an important area of study in various major pathologies including metabolic ...

A Versatile Method for Mounting Arabidopsis Leaves for Intravital Time-lapse Imaging

A Versatile Method for Mounting Arabidopsis Leaves for Intravital Time-lapse Imaging

The plant immune response associated with a genome-wide transcriptional reprogramming is initiated at the site of infection. Thus, the immune response is ...

Live Cell Imaging to Assess the Dynamics of Metaphase Timing and Cell Fate Following Mitotic Spindle Perturbations

Live cell time-lapse imaging is an important tool in cell biology that provides insight into cellular processes that might otherwise be overlooked, ...