Name: lens-free video microscopy for the dynamic and quantitative analysis of adherent cell culture
Uploaded: 2018-02-23T14:00:00.000+00:00
Duration: 9 min 4 s
Description: Watch this Scientific Journal Video about Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture at JoVE.com

The authors have nothing to acknowledge.

1. Cell Culture Monitoring Acquisition
<ol>
	<li>Grow HeLa cells in DMEM + glutamine (e.g., GlutaMAX) medium supplemented with 10% (v/v) heat-inactivated fetal calf serum and 1% penicillin and streptomycin.</li>
	<li>Coat 6-well glass bottom culture plates with fibronectin (25 &#181;g/mL) for 1 h. Then seed 2 x 104 cells per well.</li>
	<li>During the acquisition, change the medium every 3 days.</li>
	<li>For the time-lapse acquisition, use the video lens-free microscope (commercially available). 
	NOTE: This is based on the lens-free computational imaging technique as described by Ozcan et al.16 which was modified to perform continuous monitoring in an incubator at a controlled temperature of 37 &#176;C12,15. It features a complementary metal oxide semiconductor (CMOS) image sensor with a pixel pitch of 1.67 &#181;m and an imaging area of 6.4 x 4.6 mm2. Multiple wavelength illumination is provided by a multichip light emitting diode (LEDs) device, which delivers red, green and blue illumination. The wavelengths are centered, on 636, 521, and 452 nm respectively, with a spectral bandwidth of 25, 45, and 25 nm respectively. The red-green-blue (RGB) LEDs are located above a 150 &#181;m pinhole at a distance of approximately 5 cm from the cells. The light power measured close to the LED is as low as 10 &#181;W at each wavelength and the illumination time is only one second per acquisition. Hence, no photo-toxicity problems are expected when cell cultures are observed under the lens-free video microscope.</li>
	<li>Put the cell culture container put in contact with the CMOS sensor (Figure 1). Use a container with a glass coverslip at the bottom, which is important for the quality of the lens-free acquisition. Plastic containers can also be used but the lens-free acquisition will be degraded owing to the poor optical quality of these containers.</li>
	<li>Control the video lens-free microscope with the acquisition software (commercially available), which performs both the time-lapse acquisition and the holographic reconstruction. The parameters that need to be entered by the user in the software interface are the frame rate, the duration of the experiment, and the type of cell culture, i.e. adherent cells or floating cells.</li>
	<li>Set the input parameters of the acquisition software. Set the frame rate set to one acquisition every 10 minutes and set the cell culture type to &#39;adherent&#39;. 
	NOTE: A frame rate of one acquisition every 10 minutes is a good compromise as it ensures a reliable cell tracking while the size of the resulting dataset to be analyzed is still reasonable. The fastest frame rate achievable with this lens-free microscopy setup is one acquisition every 5 minutes. Further increasing the framerate results in excessive heating of the CMOS sensor which can affect the viability of the cells in culture.</li>
	<li>Start the time-lapse acquisition, and the holographic reconstruction algorithm (commercially available) will automatically process the lens-free acquisition to obtain the phase image of the cell culture. The holographic reconstruction algorithm is based on a multi-wavelength phase retrieval algorithm17 and provides an RGB reconstructed phase image in the range of [-&#960;, +&#960;] for each single cell over a large field of view of 29.4 mm2. The principle of lens-free in-line holography is to illuminate a thin sample (at z=0) with a plane wave (of amplitude 1 after normalization) and to detect on a CMOS sensor the subsequent diffraction intensity image at a short distance z=Z, typically 1 mm after the sample. In our setup, the illumination is sequentially switched to 3 wavelengths (&#955;1=0.450 &#181;m, &#955;2=0.540 &#181;m, &#955;3=0.647 &#181;m) to measure three diffraction patterns of the same sample.</li>
</ol>
2. Cell Culture Data Analysis
<ol>
	<li>For cell-tracking, use the Trackmate algorithm, an open source Fiji plugin for the automated tracking of single particles18. At first, load the full time-lapse acquisition into Fiji (load image sequence command). Owing to the large size of the datasets, which features typically 400 RGB frames of 29.7 Mb, it is faster to load them in 8-bit format. Next the Trackmate Fiji plugin guides the user through several stages of the cell-tracking algorithm, namely a cell detection stage, a cell tracker stage and several filters applied to the cell detections and the computed tracks. At every stage, configure the algorithms and display the results immediately so that, if necessary, one can easily navigate back and forth to readjust the settings. The various menus of the Trackmate interface are shown in Figure 2 with the actual settings used for the HeLa cells experiment.</li>
	<li>Set the input parameters of the acquisition software as following (see Figure 2). 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 tracks to 3.5. 
	NOTE: These settings will obviously differ from one experiment to another, especially the &#39;estimated blob diameter&#39; which corresponds to the cell size (here given in pixels of 1.67 &#181;m). The same remark applies to the &#39;linking max distance&#39; which account for the maximum distance travelled by a cell within two consecutive frames (here given in pixels of 1.67 &#181;m). Its optimal value would depend on cell motility but also on cell density.</li>
	<li>At the end of the cell-tracking process, generate the results in the form of three text files (&#39;Analysis&#39; button, see Figure 2). The most useful file, named &#39;Spots in tracks statistics&#39;, consists of a table listing all detected cells with their respective (x,y) positions in the acquisition, their frame number and their track number. On the basis of this data, perform cell segmentation and detect cell divisions using dedicated algorithms (see supplementary code files). The two other files are named &#39;Links in tracks statistics&#39; and &#39;Track statistics&#39; and include all the results dealing with the tracks, e.g. track durations, number of detected gaps, track initial frame, etc.</li>
	<li>Use the cell segmentation algorithm (see supplementary code file) to automatically extract several metrics describing the cell morphology from the reconstructed phase image. These metrics are the cell surface area (S), the cell major axis length (L), the cell minor axis length (l) and the cell aspect ratio (L/l).The phase recovered from lens-free microscopy is proportional to the density and thickness of the specimen layer as discussed previously15.</li>
	<li>In addition to the morphological features of the cell, extract quantitative cell dry mass (CDM) measurements from the reconstructed phase13,19,20 
	<img alt="Equation 1" src="/files/ftp_upload/56580/56580eq1v3.jpg" />&#160;Eq. (1) 
	where&#160;&#966;(x,y) is the reconstructed phase shift19, &#955; the wavelength and&#160;&#945; = 1.8 x 10-4 m3/kg the specific refractive index which relates the variation of refractive index to dry mass1,19.</li>
	<li>Evaluate the cell thickness using an estimation of the difference between the cell refractive index and that of the culture media. The relation between the cell thickness h(x,y) and the measured phase shift is given by20: 
	<img alt="Equation 2" src="/files/ftp_upload/56580/56580eq2v3.jpg" />&#160;Eq. (2.1) 
	<img alt="Equation 3" src="/files/ftp_upload/56580/56580eq3v3.jpg" />Eq. (2.2) 
	with&#160;&#916;n(x,y) = ncell (x,y) - nmedium (x,y), the refractive index difference between the cell and the culture media. In the following, assume a constant value of &#916;n = 0.025, which is estimated from the refractive index measured in HeLa cell nuclei (n = 1.35511) and that of phosphate-buffered saline (PBS) culture media (n=1.33). Although the cell thickness value is only indicative as it is based on an assumption, its relative variations are meaningful and can be exploited to detect dividing cells.</li>
	<li>Use the dedicated algorithm (see supplementary code file) to detect the occurrence of cell divisions and then extract cell tracks that are associated to the detected cell divisions, In order to detect a cell division, cells with a measured thickness larger than 8 &#181;m are first identified, then check whether a new cell appears closely in space and time. In this way, the detection of cell divisions relies on two robust criteria. Alternative and more elaborate methods for cell division detection can be applied to the lensfree time-lapse acquisition21,22,23.</li>
</ol>

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The authors have nothing to disclose.

In this paper, we show that lens-free video microscopy can be used inside an incubator to capture the kinetics of thousands of cells. In order to describe the overall methodology we explained how a 2.7 day time-lapse acquisition of HeLa cells in culture can be analyzed with standard cell-tracking algorithms. The result is a dataset featuring 2.2 x 106 cell measurements and 10,584 cell cycle tracks. The acquisitions were performed on a culture of Hela cells with a relatively large cell-to-cell distance (cell density &#60;500 cells/mm2) and cell morphology that can be approximated with a disc. These two features facilitate the application of an automatic cell-tracking analysis which makes it possible to gather such a large dataset. Other cell lines with smaller cell-to-cell distance or with more complex morphologies would be more difficult to track and subsequent datasets would be smaller.
We believe that this approach is interesting for many studies, for instance for cell proliferation and cell size studies. The latter are an important area of research in fundamental biology and many questions remain unanswered as nicely discussed in a review by Ginzberg et al.29. The protocol proposed in this work provides thus a means to measure important metrics required for cell proliferation studies, i.e. the cell cycle duration, the cell dry mass, the cell dry mass ratio between the end and the start of the cycle and the cell dry mass growth rate. Besides the study of cell proliferation, this method will be of interest for the study of cell migration, since it can produce a large number of tracks, each one lasting several hours. The present protocol goes beyond the state of the art14,30 by demonstrating for the first time the acquisition of thousands of cell tracks during more than 10 h.
In conclusion, we have developed an easy-to-use lens-free technique that allows to track simultaneously thousands of label-free cells over several days of culture.

Monitoring cultured mammalian cells throughout several cell cycles and measuring accurately cell size and cell dry mass is a challenging task. Several label-free optical techniques are able to perform this task1,2: phase-shifting interferometry3, digital holographic microscopy (DHM)4,5,6,7, quadriwave lateral shearing interferometry8,9 and quantitative phase tomography10,11. These methods have led to many new insights into the understanding of the cell cycle of mammalian cells. However they are seldom coupled with automatic cell tracking algorithms and their throughput remains limited when measuring cell mass trajectories1 (N&#60;20 in respectively3,4,5,6). Hence a novel optical method is needed to measure cell mass trajectories with large statistics (N&#62;1000).
In this paper, we demonstrate the capability of lens-free video microscopy to simultaneously image thousands of cells directly inside the incubator, and then quantify single cell metrics along thousands of individual cell cycle tracks. Lens-free microscopy is a quantitative phase imaging technique which allows the acquisition of phase image of densely packed cells over a very large field of view (typically several tens of mm2, here 29.4 mm2)12,13,14,15. Several metrics at the single cell level are determined, e.g., cell area, cell dry mass, cell thickness, cell major axis length and cell aspect ratio12,15, from each image. Then, by applying a cell-tracking algorithm, these features can be plotted for every single cell as a function of the experiment time14,15. Furthermore, by detecting the occurrence of cell divisions in the cell tracks, it is possible to extract other important information such as the initial cell dry mass (just after the cell division), the final cell dry mass (just before the cell division) and the cell cycle duration, i.e., the time between two consecutive divisions15. All these measurements can be computed with very good statistics (N&#62;1000) since the large field of view would typically allow the analysis of 200 to 10,000 cells in a single lens-free acquisition.
In order to explain this methodology based on lens-free video microscopy, we describe the protocol to monitor and quantify a HeLa cell culture for 2.7 days. Data analysis is a four-step process based on multi-wavelength holographic reconstruction, cell-tracking, cell segmentation and cell division algorithms. Here it is shown that the spatial resolution and the relatively fast frame rate (one acquisition every 10 minutes) obtained with this lens-free video microscopy setup is compatible with standard cell-tracking algorithms. The full analysis of this dataset results in the measurement of 10,584 cell tracks over complete cell cycles.
To summarize, lens-free video microscopy is a powerful tool to automatically monitor thousands of unlabeled, unsynchronized, and unmodified cells per experiment; each cell being tracked over several cell cycles. Our measurements thus provide the mean value of several cell parameters, but more importantly, the inter-cell variability over a large population of cells.

<table><tbody><tr><td>Cytonote lens-free video microscope&amp;nbsp;</td><td>Iprasense</td><td></td><td></td></tr><tr><td>Horus acquisition software</td><td>Iprasense</td><td></td><td></td></tr><tr><td>6-well glass bottom culture plates</td><td>MatTek corporation</td><td>Part No: P06G-0-14-F&amp;nbsp;</td><td></td></tr><tr><td>DMEM + GlutaMAX medium&amp;nbsp;</td><td>Gibco</td><td></td><td></td></tr><tr><td>heat-inactivated fetal calf serum&amp;nbsp;</td><td>Eurobio</td><td></td><td></td></tr><tr><td>penicillin and streptomycin&amp;nbsp;</td><td>Gibco</td><td></td><td></td></tr><tr><td>Fibronectin&amp;nbsp;</td><td>Sigma Aldrich</td><td></td><td></td></tr><tr><td>Matlab, image processing toolbox&amp;nbsp;</td><td>Mathworks</td><td></td><td></td></tr></tbody></table>

lens-free video microscopy for the dynamic and quantitative analysis of adherent cell culture

Here, we demonstrate that lens-free video microscopy enables us to simultaneously capture the kinetics of thousands of cells directly inside the incubator and that it is possible to monitor and quantify single cells along several cell cycles. We describe the full protocol used to monitor and quantify a HeLa cell culture for 2.7 days. First, cell culture acquisition is performed with a lens-free video microscope, and then the data is analyzed following a four-step process: multi-wavelength holographic reconstruction, cell-tracking, cell segmentation and cell division detection algorithms. As a result, we show that it is possible to gather a dataset featuring more than 10,000 cell cycle tracks and more than 2 x 106 cell morphological measurements.

Watch this Scientific Journal Video about Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture at JoVE.com

Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture

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.

Here, we demonstrate that lens-free video microscopy enables us to simultaneously capture the kinetics of thousands of cells directly inside the incubator ...

lens-free-video-microscopy-for-dynamic-quantitative-analysis-adherent

Nanyang Technological University

Research

JoVE Journal

Biology

9.4K Views.  Université Grenoble Alpes. Lens-vrije videomicroscopie ons in staat stelt om te controleren van celculturen direct in de incubator. Hier beschrijven we het volledige protocol gebruikt voor het verwerven en analyseren van een 2.7 dag lang verwerving van gekweekte HeLa cellen, wat leidt tot een dataset van 2.2 x 106 metingen van individuele cel morfologie en 10584 celcyclus tracks.

Video: Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture

Live-cell Imaging of Migrating Cells Expressing Fluorescently-tagged Proteins in a Three-dimensional Matrix

Traditionally, cell migration has been studied on two-dimensional, stiff plastic surfaces. However, during important biological processes such as wound healing, tissue regeneration, and cancer metastasis, cells must navigate through complex, three-dimensional extracellular tissue. To better understand the mechanisms behind these biological processes, it is important to examine the roles of the proteins responsible for driving cell migration. Here, we outline a protocol to study the mechanisms of cell migration using the epithelial cell line (MDCK), and a three-dimensional, fibrous, self-polymerizing matrix as a model system. This optically clear extracellular matrix is easily amenable to live-cell imaging studies and better mimics the physiological, soft tissue environment. This report demonstrates a technique for directly visualizing protein localization and dynamics, and deformation of the surrounding three-dimensional matrix. 
Examination of protein localization and dynamics during cellular processes provides key insight into protein functions. Genetically encoded fluorescent tags provide a unique method for observing protein localization and dynamics. Using this technique, we can analyze the subcellular accumulation of key, force-generating cytoskeletal components in real-time as the cell maneuvers through the matrix. In addition, using multiple fluorescent tags with different wavelengths, we can examine the localization of multiple proteins simultaneously, thus allowing us to test, for example, whether different proteins have similar or divergent roles. Furthermore, the dynamics of fluorescently tagged proteins can be quantified using Fluorescent Recovery After Photobleaching (FRAP) analysis. This measurement assays the protein mobility and how stably bound the proteins are to the cytoskeletal network.
By combining live-cell imaging with the treatment of protein function inhibitors, we can examine in real-time the changes in the distribution of proteins and morphology of migrating cells. Furthermore, we also combine live-cell imaging with the use of fluorescent tracer particles embedded within the matrix to visualize the matrix deformation during cell migration. Thus, we can visualize how a migrating cell distributes force-generating proteins, and where the traction forces are exerted to the surrounding matrix. Through these techniques, we can gain valuable insight into the roles of specific proteins and their contributions to the mechanisms of cell migration.

Cellular processes such as cell migration have traditionally been studied on two-dimensional, stiff plastic surfaces. This report describes a technique for directly visualizing protein localization and analyzing protein dynamics in cells migrating in a more physiologically relevant, three-dimensional matrix.

Traditionally, cell migration has been studied on two-dimensional, stiff plastic surfaces. However, during important biological processes such as wound ...

Bioengineering

Simultaneously Capturing Real-time Images in Two Emission Channels Using a Dual Camera Emission Splitting System: Applications to Cell Adhesion

Multi-color immunofluorescence microscopy to detect specific molecules in the cell membrane can be coupled with parallel plate flow chamber assays to investigate mechanisms governing cell adhesion under dynamic flow conditions. For instance, cancer cells labeled with multiple fluorophores can be perfused over a potentially reactive substrate to model mechanisms of cancer metastasis. However, multi-channel single camera systems and color cameras exhibit shortcomings in image acquisition for real-time live cell analysis. To overcome these limitations, we used a dual camera emission splitting system to simultaneously capture real-time image sequences of fluorescently labeled cells in the flow chamber. Dual camera emission splitting systems filter defined wavelength ranges into two monochrome CCD cameras, thereby simultaneously capturing two spatially identical but fluorophore-specific images. Subsequently, psuedocolored one-channel images are combined into a single real-time merged sequence that can reveal multiple target molecules on cells moving rapidly across a region of interest.

Dual camera emission splitting systems for two-color fluorescence microscopy generate real-time image sequences with exceptional optical and temporal resolution, a requirement of certain live cell assays including parallel plate flow chamber adhesion assays. When software is employed to merge images from simultaneously acquired emission channels, pseudocolored image sequences are produced.

Multi-color immunofluorescence microscopy to detect specific molecules in the cell membrane can be coupled with parallel plate flow chamber assays to ...

A Novel Method for Localizing Reporter Fluorescent Beads Near the Cell Culture Surface for Traction Force Microscopy

PA gels have long been used as a platform to study cell traction forces due to ease of fabrication and the ability to tune their elastic properties. When the substrate is coated with an extracellular matrix protein, cells adhere to the gel and apply forces, causing the gel to deform. The deformation depends on the cell traction and the elastic properties of the gel. If the deformation field of the surface is known, surface traction can be calculated using elasticity theory. Gel deformation is commonly measured by embedding fluorescent marker beads uniformly into the gel. The probes displace as the gel deforms. The probes near the surface of the gel are tracked. The displacements reported by these probes are considered as surface displacements. Their depths from the surface are ignored. This assumption introduces error in traction force evaluations. For precise measurement of cell forces, it is critical for the location of the beads to be known. We have developed a technique that utilizes simple chemistry to confine fluorescent marker beads, 0.1 and 1 &#181;m in diameter, in PA gels, within 1.6 &#956;m of the surface. We coat a coverslip with poly-D-lysine (PDL) and fluorescent beads. PA gel solution is then sandwiched between the coverslip and an adherent surface. The fluorescent beads transfer to the gel solution during curing. After polymerization, the PA gel contains fluorescent beads on a plane close to the gel surface.

Traditional techniques for fabricating polyacrylamide (PA) gels containing fluorescent probes involve sandwiching a gel between an adherent surface and a glass slide. Here, we show that coating this slide with poly-D-lysine (PDL) and fluorescent probes localizes the probes to within 1.6 &#181;m from the gel surface.

PA gels have long been used as a platform to study cell traction forces due to ease of fabrication and the ability to tune their elastic properties. When ...

Lensless On-chip Imaging of Cells Provides a New Tool for High-throughput Cell-Biology and Medical Diagnostics

Conventional optical microscopes image cells by use of objective lenses that work together with other lenses and optical components. While quite effective, this classical approach has certain limitations for miniaturization of the imaging platform to make it compatible with the advanced state of the art in microfluidics. In this report, we introduce experimental details of a lensless on-chip imaging concept termed LUCAS (Lensless Ultra-wide field-of-view Cell monitoring Array platform based on Shadow imaging) that does not require any microscope objectives or other bulky optical components to image a heterogeneous cell solution over an ultra-wide field of view that can span as large as ~18 cm2. Moreover, unlike conventional microscopes, LUCAS can image a heterogeneous cell solution of interest over a depth-of-field of ~5 mm without the need for refocusing which corresponds to up to ~9 mL sample volume. This imaging platform records the shadows (i.e., lensless digital holograms) of each cell of interest within its field of view, and automated digital processing of these cell shadows can determine the type, the count and the relative positions of cells within the solution. Because it does not require any bulky optical components or mechanical scanning stages it offers a significantly miniaturized platform that at the same time reduces the cost, which is quite important for especially point of care diagnostic tools. Furthermore, the imaging throughput of this platform is orders of magnitude better than conventional optical microscopes, which could be exceedingly valuable for high-throughput cell-biology experiments.

Lensfree on-chip imaging and characterization of cells is illustrated. This on-chip cell imaging approach provides a compact and cost-effective tool for medical diagnostics and high-throughput cell biology applications, making it especially suitable for resource poor settings.

Conventional optical microscopes image cells by use of objective lenses that work together with other lenses and optical components. While quite ...

Live Cell Response to Mechanical Stimulation Studied by Integrated Optical and Atomic Force Microscopy

To understand the mechanism by which living cells sense mechanical forces, and how they respond and adapt to their environment, a new technology able to investigate cells behavior at sub-cellular level with high spatial and temporal resolution was developed. Thus, an atomic force microscope (AFM) was integrated with total internal reflection fluorescence (TIRF) microscopy and fast-spinning disk (FSD) confocal microscopy. The integrated system is broadly applicable across a wide range of molecular dynamic studies in any adherent live cells, allowing direct optical imaging of cell responses to mechanical stimulation in real-time. Significant rearrangement of the actin filaments and focal adhesions was shown due to local mechanical stimulation at the apical cell surface that induced changes into the cellular structure throughout the cell body. These innovative techniques will provide new information for understanding live cell restructuring and dynamics in response to mechanical force. A detailed protocol and a representative data set that show live cell response to mechanical stimulation are presented.

This paper aims to instruct the reader in the operation of an integrated atomic force-optical imaging microscope for mechanical stimulation of live cells in culture. A step-by-step protocol is presented. A representative data set that shows live cell response to mechanical stimulation is presented.

To understand the mechanism by which living cells sense mechanical forces, and how they respond and adapt to their environment, a new technology able to ...

Visualizing Adhesion Formation in Cells by Means of Advanced Spinning Disk-Total Internal Reflection Fluorescence Microscopy

In living cells, processes such as adhesion formation involve extensive structural changes in the plasma membrane and the cell interior. In order to visualize these highly dynamic events, two complementary light microscopy techniques that allow fast imaging of live samples were combined: spinning disk microscopy (SD) for fast and high-resolution volume recording and total internal reflection fluorescence (TIRF) microscopy for precise localization and visualization of the plasma membrane. A comprehensive and complete imaging protocol will be shown for guiding through sample preparation, microscope calibration, image formation and acquisition, resulting in multi-color SD-TIRF live imaging series with high spatio-temporal resolution. All necessary image post-processing steps to generate multi-dimensional live imaging datasets, i.e. registration and combination of the individual channels, are provided in a self-written macro for the open source software ImageJ. The imaging of fluorescent proteins during initiation and maturation of adhesion complexes, as well as the formation of the actin cytoskeletal network, was used as a proof of principle for this novel approach. The combination of high resolution 3D microscopy and TIRF provided a detailed description of these complex processes within the cellular environment and, at the same time, precise localization of the membrane-associated molecules detected with a high signal-to-background ratio.

An advanced microscope that permit fast and high-resolution imaging of both, the isolated plasma membrane and the surrounding intracellular volume, will be presented. The integration of spinning disk and total internal reflection fluorescence microscopy in one setup allows live imaging experiments at high acquisition rates up to 3.5 s per image stack.

In living cells, processes such as adhesion formation involve extensive structural changes in the plasma membrane and the cell interior. In order to ...

Quantitative Analysis of Random Migration of Cells Using Time-lapse Video Microscopy

Cell migration is a dynamic process, which is important for embryonic development, tissue repair, immune system function, and tumor invasion 1, 2. During directional migration, cells move rapidly in response to an extracellular chemotactic signal, or in response to intrinsic cues 3 provided by the basic motility machinery. Random migration occurs when a cell possesses low intrinsic directionality, allowing the cells to explore their local environment.
Cell migration is a complex process, in the initial response cell undergoes polarization and extends protrusions in the direction of migration 2. Traditional methods to measure migration such as the Boyden chamber migration assay is an easy method to measure chemotaxis in vitro, which allows measuring migration as an end point result. However, this approach neither allows measurement of individual migration parameters, nor does it allow to visualization of morphological changes that cell undergoes during migration.
Here, we present a method that allows us to monitor migrating cells in real time using video - time lapse microscopy. Since cell migration and invasion are hallmarks of cancer, this method will be applicable in studying cancer cell migration and invasion in vitro. Random migration of platelets has been considered as one of the parameters of platelet function 4, hence this method could also be helpful in studying platelet functions. This assay has the advantage of being rapid, reliable, reproducible, and does not require optimization of cell numbers. In order to maintain physiologically suitable conditions for cells, the microscope is equipped with CO2 supply and temperature thermostat. Cell movement is monitored by taking pictures using a camera fitted to the microscope at regular intervals. Cell migration can be calculated by measuring average speed and average displacement, which is calculated by Slidebook software.

This method allows monitoring of cells in real time and quantitative measurements of different cell migration parameters such as speed, displacement, and velocity. Unlike the traditional methods, this real time approach is not based on endpoint quantitative migration measurements; instead it allows monitoring and calculating different parameters continuously.

Cell migration is a dynamic process, which is important for embryonic development, tissue repair, immune system function, and tumor invasion 1, 2. During ...

Preparation and Structural Evaluation of Epithelial Cell Monolayers in a Physiologically Sized Microfluidic Culture Device

In vitro microfluidic experimentation holds great potential to reveal many insights into the microphysiological phenomena occurring in conditions such as acute respiratory distress syndrome (ARDS) and ventilator-induced lung injury (VILI). However, studies in microfluidic channels with dimensions physiologically relevant to the terminal bronchioles of the human lung currently face several challenges, especially due to difficulties in establishing appropriate cell culture conditions, including media flow rates, within a given culture environment. The presented protocol describes an image-based approach to evaluate the structure of NCI-H441 human lung epithelial cells cultured in an oxygen-impermeable microfluidic channel with dimensions physiologically relevant to the terminal bronchioles of the human lung. Using phalloidin-based filamentous-actin staining, the cytoskeletal structures of the cells are revealed by confocal laser scanning microscopy, allowing for the visualization of individual as well as layered cells. Subsequent quantification determines whether the cell culture conditions being employed are producing uniform monolayers suitable for further experimentation. The protocol describes cell culture and layer evaluation methods in microfluidic channels and traditional fixed-well environments. This includes channel construction, cell culture and requisite conditions, fixation, permeabilization and staining, confocal microscopic imaging, image processing, and data analysis.

The presented protocol describes the development and use of a phalloidin-based filamentous-actin staining technique with confocal laser scanning microscopy (CLSM) to visualize adherent cell layer structure in microfluidic dynamic-culture channels and traditional fixed-well static-culture chambers. This approach aids in evaluating cell layer confluency, monolayer formation, and layer-thickness uniformity.

In vitro microfluidic experimentation holds great potential to reveal many insights into the microphysiological phenomena occurring in conditions such as ...

A Graphical User Interface for Software-assisted Tracking of Protein Concentration in Dynamic Cellular Protrusions

Filopodia are dynamic, finger-like cellular protrusions associated with migration and cell-cell communication. In order to better understand the complex signaling mechanisms underlying filopodial initiation, elongation and subsequent stabilization or retraction, it is crucial to determine the spatio-temporal protein activity in these dynamic structures. To analyze protein function in filopodia, we recently developed a semi-automated tracking algorithm that adapts to filopodial shape-changes, thus allowing parallel analysis of protrusion dynamics and relative protein concentration along the whole filopodial length. Here, we present a detailed step-by-step protocol for optimized cell handling, image acquisition and software analysis. We further provide instructions for the use of optional features during image analysis and data representation, as well as troubleshooting guidelines for all critical steps along the way. Finally, we also include a comparison of the described image analysis software with other programs available for filopodia quantification. Together, the presented protocol provides a framework for accurate analysis of protein dynamics in filopodial protrusions using image analysis software.

We present a software solution for semi-automated tracking of relative protein concentration along the length of dynamic cellular protrusions.

Filopodia are dynamic, finger-like cellular protrusions associated with migration and cell-cell communication. In order to better understand the complex ...

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.

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) is a versatile method to collect time courses of fluorescence signals from individual cells in high ...

Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture

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