We greatly acknowledge Thierry Galli (Center of Psychiatry and Neurosciences, INSERM) for providing the VAMP7-pHluorin plasmid. We thank Tarn Duong for advice on statistical analysis and members of the GOUD laboratory for fruitful discussions. The authors greatly acknowledge the Cell and Tissue Imaging Facility (PICT-IBiSA @Burg, PICT-EM @Burg and PICT-IBiSA @Pasteur) and Nikon Imaging Center, Institut Curie (Paris), member of the French National Research Infrastructure France-BioImaging (ANR10-INBS-04). H.L. was supported by the Association pour la Recherche sur le Cancer (ARC) and P.M. received funding from the European Union&#8217;s Horizon 2020 research and innovation programme under Marie Sk&#322;odowska-Curie grant agreement No 666003. This work was supported by grants from INFECT-ERA (ANR-14-IFEC-0002-04), the Labex CelTisPhyBio (ANR-10-LBX-0038) and Idex Paris Sciences et Lettres (ANR-10-IDEX-0001-02 PSL), as well as the Centre National de la Recherche Scientifique and Institut Curie.&#160;

1. Preparation of micropatterned cells
<ol>
	<li>Transfection of cells
	<ol>
		<li>One day before transfection, seed 2.5 x 106 hTERT-RPE1 cells into one well of a 12 well plate (2 x 2 cm) in 1 mL of medium.</li>
		<li>On the day of transfection, prepare the transfection mixture with VAMP7-pHluorin plasmid (100 &#181;L of buffer, 0.8 &#181;g of DNA, 3 &#181;L of transfection mixture). Incubate for 10 min. 
		NOTE: VAMP7 is a lysosomal v-SNARE, fused with a luminal pHluorin tag. The pHluorin probe is quenched by low pH, but during exocytosis protons are released and pHluorin starts emitting a signal10,11.</li>
		<li>Add the transfection mix to the cells in their medium.</li>
		<li>Change the medium 4 h after adding the transfection mix on the cells.</li>
		<li>Use the cells for experiments during the next 24&#8211;48 h.</li>
	</ol>
	</li>
	<li>Micropattern preparation (photolithography method)
	<ol>
		<li>Wash the coverslips (25 mm of diameter) in ethanol and let them dry for 5 min.</li>
		<li>Activate coverslips by illumination under deep UV for 5 min.</li>
		<li>Create a humid chamber by thoroughly humidifying a paper towel on which a paraffin film is placed. Add drops (30 &#956;L for 22 mm coverslip) of Poly-L-Lysine-graft-Polyethylene Glycol (PLL-g-PEG) solution (0.1 mg/mL, 10 mM HEPES, pH = 7.4) and place coverslips with the activated surface on them. Close the humid chamber with a top and incubate coverslips for 1 h.</li>
		<li>Wash coverslips 2x in PBS and 1x in distilled water and let them dry.</li>
		<li>Wash the quartz photomask with distilled water and then with ethanol or propanol. Dry the photomask with filtered airflow. 
		NOTE: The quartz photomask is coated on one side with antireflective chrome that contains holes in the form of micropatterns. A photomask containing ring-shaped micropatterns of 37 &#181;m is used in this protocol. When deep UV is shined on the photomask, the light can only pass through these holes12.</li>
		<li>Expose the photomask (chrome-coated side) to deep UV for 5 min to clean the surface.</li>
		<li>Add small water drops (10 &#181;L for a 20 mm coverslip) on the chrome-coated side of the photomask. Place the coverslip with their PLL-g-PEG-treated side on the drop and dry the extra water. Make sure that no air bubbles form between the mask and the coverslips. 
		NOTE: The capillary force of the water will immobilize the coverslips.</li>
		<li>Expose the photomask to deep UV for 5 min with the non-chrome-coated side up (the coverslips are attached on the lower surface). 
		NOTE: The light can only pass through the holes and modify the PLL-g-PEG-treated surface of coverslips below the photomask.</li>
		<li>Remove the coverslips from the photomask by adding excess water. 
		NOTE: Coverslips should quickly float off.</li>
		<li>Incubate the coverslips in a solution of extracellular matrix proteins (50 &#956;g/mL of fibronectin, 5 &#956;g/mL of fluorescent fibrinogen diluted in water) on paraffin film in a humid chamber (as in step 1.2.3) for 1 h under a laminar flow hood to avoid contamination. 
		NOTE: The experiment can be paused at this point by storing the coverslips in PBS at 4 &#176;C.</li>
	</ol>
	</li>
	<li>Cell seeding on micropatterned surfaces
	<ol>
		<li>Use a magnetic coverslip holder that fits the size of the micropatterned coverslips to mount the coverslips. On the day of acquisition, heat the coverslip holder to 37 &#176;C to avoid thermal shock for the cells during subsequent steps.</li>
		<li>Prepare the pattern medium by supplementing DMEM/F12 medium with 20 mM HEPES and 2% of penicillin/streptomycin.</li>
		<li>Place coverslips into the holder with the micropatterned side up and add pattern medium as soon as the coverslip is on the holder base. Add the seal and immobilize with the magnetic device. Fill the coverslip holder with the pattern medium and close it with the glass lid. 
		NOTE: Be quick, to not allow the coverslip to dry. Do not wash the coverslip holder with ethanol between experiments, because the seal might retain some ethanol, which can react with PLL-g-PEG and result in cell stress. Wash the coverslip holder only with soapy water. Moreover, the joint can be incubated in the pattern medium at 37 &#176;C for 1 h to dilute residual product.</li>
		<li>Collect transfected hTERT-RPE1 cells by trypsinization (0.5 mL for one 12 well plate) and add 1 mL of 10% FBS DMEM/F12 medium.</li>
		<li>Add 0.5 x 106 transfected hTERT-RPE1 cells to the coverslip holder and reclose it. Incubate for 10 min in the incubator.</li>
		<li>Wash the coverslip holder 5x with pattern medium to remove nonattached cells and residual FBS by adding the pattern medium with one pipette and aspirating the medium with another pipette to create a washing flow. Always keep a small volume of pattern medium in the coverslip holder to avoid drying of the cells on the micropatterned coverslip, which will lead to cell death.</li>
		<li>Incubate in the incubator for 3 h to allow full cell spreading.</li>
	</ol>
	</li>
</ol>
2. Acquisition of exocytosis data
<ol>
	<li>Imaging of exocytosis events
	<ol>
		<li>Place coverslip holder under a TIRM. The signal has to be detected by a sensitive camera set up with the best imaging format available. 
		NOTE:&#160;In this experiment, a 100x lens objective and an EMCCD camera with 512 x 512 pixel detection region was used giving rise to a pixel size of 160 nm.</li>
		<li>Search for a cell expressing VAMP7-pHluorin that is fully spread (Figure 1A). 
		NOTE: Cells expressing VAMP7 are clearly identifiable, because they exhibit a green signal.</li>
		<li>Change the angle of the laser until a TIRF angle that allows the visualization of VAMP7-pHluorin exocytosis events is reached. Perform a 5 min acquisition at a frequency compatible with the exocytosis rate and time scale (typically 3 Hz, Figure 1D) using the microscope software. 
		NOTE: hTERT-RPE1 cells have a lysosomal secretory rate of around 0.3 Hz on micropatterns. Lysosomal exocytosis has a typical duration of 1 s. It is characterized by a peak intensity followed by an exponential decay. The diffusion of the probe should be evident at this time (Figure 1B, C).</li>
		<li>For each cell, also perform an acquisition of the micropattern using the microscope software (Figure 1A).</li>
	</ol>
	</li>
	<li>Acquisition of exocytosis coordinates
	<ol>
		<li>Open the acquired movie with ImageJ/FIJI. Use File | Import | Image Sequence. Find exocytosis events by eye. An exocytosis event is characterized by the appearance of a bright signal that spreads outwards (Figure 1).</li>
		<li>Use the point tool to mark the center of the exocytic event. Use Analyze | Measure to measure X and Y coordinates, as well as the temporal coordinate (slice number). Perform these measurements for all exocytosis events of the movie.</li>
		<li>Save the results (Results | File | Save As). Prepare a text file for each analyzed cell named &#8220;Results(cell_name).txt&#8221; that contains the slice, X coordinates, and Y coordinates for all exocytosis events in that order. 
		 
		The text file is supposed to look like this: 
		ID&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; X&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; Y&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; Feret&#39;s diameter&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; Radius 
		RPE1_WT_Cell1&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; 167&#160;&#160;&#160;&#160;&#160; 136&#160;&#160;&#160;&#160;&#160; 230&#160;&#160;&#160;&#160;&#160; 115 
		RPE1_WT_Cell2&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; 164&#160;&#160;&#160;&#160;&#160; 160&#160;&#160;&#160;&#160;&#160; 230&#160;&#160;&#160;&#160;&#160; 115 
		 
		NOTE: Be careful to replace all commas with points.</li>
		<li>Measure the center and diameter of each cell using the &#8220;Oval Tool&#8221;. Fit a perfect circle (do not use an oval) and use &#8220;Measure&#8221; to obtain the X and Y coordinates and Feret&#39;s diameter. Save each cell&#8217;s identity (ID), X and Y coordinates, Feret&#8217;s diameter, and radius (diameter/2) in a text file named &#8220;Spherical parameter.txt&#8221;. 
		 
		The text file is supposed to look like this: 
		ID&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; X&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; Y&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; Feret&#39;s diameter&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; Radius 
		RPE1_WT_Cell1&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; 167&#160;&#160;&#160;&#160;&#160; 136&#160;&#160;&#160;&#160;&#160; 230&#160;&#160;&#160;&#160;&#160; 115 
		RPE1_WT_Cell2&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; 164&#160;&#160;&#160;&#160;&#160; 160&#160;&#160;&#160;&#160;&#160; 230&#160;&#160;&#160;&#160;&#160; 115 
		 
		NOTE: Be careful to replace all commas with points.</li>
		<li>Measure the thickness of the micropattern ring (adhesion length) with the straight tool and save the cell ID, cell radius (from the file: &#8220;Spherical parameter.txt&#8221;), and adhesion length in a text file named &#8220;Pattern parameter.txt&#8221;. Calculate the normalized adhesion length by dividing the adhesion length by cell radius. 
		NOTE: Be careful to replace all commas by points. 
		 
		The file should look like this: 
		ID&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; Cell radius&#160;&#160;&#160;&#160;&#160;&#160; adhesion length&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; Normalized adhesion length 
		RPE1_WT_Cell1&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; 115&#160;&#160;&#160;&#160;&#160; 34&#160;&#160;&#160;&#160;&#160;&#160;&#160; 0.295652174 
		RPE1_WT_Cell2&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; 115&#160;&#160;&#160;&#160;&#160; 35&#160;&#160;&#160;&#160;&#160;&#160;&#160; 0.304347826</li>
	</ol>
	</li>
</ol>
3. Single cell spatial analysis
<ol>
	<li>R package and installation 
	NOTE: The R package for this analysis takes advantage of the Spatstat package13 to compute the two-dimensional (2D) density and Ripley&#8217;s K function. The code is open-source and uses text files that have been previously described.
	<ol>
		<li>Download and install R from https://www.r-project.org/ (version 3.5.2 was used in this analysis).</li>
		<li>Download the package (and the demo dataset) from: https://github.com/GoudTeam/JoVE-paper</li>
		<li>Install the package on R Studio using &#8220;Tools&#8221; using &#8220;Install Packages&#8221;. Select &#8220;Package Archive File (.zip; .tar.gz)&#8221; for the category &#8220;Install from:&#8221; and choose the package file. Press &#8220;Install&#8221;.</li>
		<li>Load the package with the function &#8220;library(&#34;ExocytosisSpatialAnalysis&#34;)&#8221; by writing this command in R studio and pressing &#8220;Enter&#8221;.</li>
		<li>Run the package with the function &#8220;ESA()&#8221; by writing this command in R studio and pressing &#8220;Enter&#8221;. 
		NOTE: A user interface will open.</li>
		<li>Select the directory for the dataset (.txt files) and a directory for output plots. 
		NOTE: Parameters of the analysis (see text below) can be changed through a user interface.</li>
		<li>This script will automatically start and perform the analysis. It provides .pdf files of corresponding plots and .txt files containing numerical results.&#160;</li>
	</ol>
	</li>
</ol>

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The authors have nothing to disclose.

We monitored exocytosis events from the lysosomal compartment by TIRFM live cell imaging of VAMP7-pHluorin in ring-shaped micropattern-normalized cells and performed a rigorous statistical analysis of the spatial parameters of exocytosis events. Employing the transformed Ripley&#8217;s K function and a statistical test based on the nearest neighbor distance, we confirmed that secretion from lysosomes is not a random process8,9. Both statistical analyses convincin...

Exocytosis is a universal cellular process in which a vesicle fuses with the plasma membrane and releases its content. The vesicle can either fuse totally with the plasma membrane (full fusion) or create a fusion pore that stays open during a limited time (kiss-and-run)1. For instance, newly synthesized proteins are released into the extracellular medium from vesicles that come from the Golgi complex. This biosynthetic, anterograde pathway is primordial, especially in multicellular organisms, to secrete signaling peptides (e.g., hormones, neurotransmitters) and extracellular matrix components (e.g., collagen), as well as to traffic transmembrane proteins to the plasma membrane. Additionally, secretions can occur from different endosomes: 1) recycling endosomes in order to reuse transmembrane proteins; 2) multivesicular bodies (MVBs) to release exosomes; and 3) lysosomes for the release of proteolytic enzymes. Endosomal secretion has been shown to be important for neurite outgrowth, pseudopodia formation, plasma membrane repair, and ATP-dependent signaling2.
To study exocytosis at the single cell level, several techniques have been employed. Patch-clamp allows for the detection of single exocytosis events with a high temporal resolution in a wide variety of living cells3. However, this method does not provide information on the localization of exocytosis events, nor from which compartment it occurs. Electron microscopy allows direct visualization of exocytic events with high spatial resolution, and in combination with immunolabeling provides information about the specificity of the compartments and molecules involved. A disadvantage of this approach is the lack of information on the dynamics of the process, as well as its inability to perform high-throughput studies. Light microscopy approaches such as total internal reflection fluorescence microscopy (TIRFM), which exploits the evanescent field to illuminate fluorophores at the vicinity of the coverslip (100 nm), provides good temporal and spatial resolution to study exocytosis events. However, this method is only compatible with adherent cells and can only be applied to the ventral/inferior part of cells.
Of note, the plasma membrane reveals significant heterogeneity based on adhesive complexes that are present only in restricted areas. This heterogeneity restricts, for instance, the uptake of different ligands4. Similarly, it has recently been reported that secretion from the Golgi complex is concentrated at &#8220;hot spots&#8221; in the plasma membrane5. Moreover, it is known that certain cargos are secreted through focal-adhesion-associated exocytosis6. Thus, special attention should be paid to the question of whether exocytosis events are randomly distributed in space, or whether they are concentrated at specific areas of the plasma membrane. Several statistical tools based on Ripley&#8217;s K function have been proposed to explore these questions7,8,9. Our approach combines these tools with micropatterning to control cell shape and plasma membrane heterogeneity. In addition to providing a means to distinguish between adhesive and nonadhesive areas, this technique also allows comparison across different cells and conditions and increases the power of statistical analyses.
Here we employ a variety of statistical tools to study the spatial distribution of exocytosis events from the lysosomal compartment monitored by TIRFM live cell imaging of VAMP7-pHluorin in ring-shaped micropattern-normalized hTert-RPE1 cells. It was confirmed that secretion from lysosomes is not a random process8,9 and that exocytosis events exhibit clustering. Of note, we found that exocytosis events are also clustered in nonadhesive areas, indicating that adhesion molecules are not the only structures that can induce secretory hot spots at the plasma membrane. Nevertheless, cell adhesion did enhance clustering. Consistently, our analysis identified enriched areas of exocytosis that were located at the border between the adhesive and nonadhesive areas.

<table><tbody><tr><td>Chamlide Magnetic Chamber</td><td>Chamlide</td><td></td><td></td></tr><tr><td>DMEM/F12</td><td>Gibco</td><td>21041-025</td><td></td></tr><tr><td>Fibrinogen</td><td>Molecular Probes, Invitrogen</td><td>F35200</td><td></td></tr><tr><td>Fibronectin bovine plasma</td><td>Sigma</td><td>F1141</td><td></td></tr><tr><td>HEPES (1M)</td><td>Gibco</td><td>15630-056</td><td></td></tr><tr><td>hTert RPE1 cell line</td><td>https://www.atcc.org</td><td></td><td></td></tr><tr><td>ImageJ</td><td>http://rsbweb.nih.gov/ij/</td><td>n/a</td><td>Authored by W. Rasband, NIH/NIMH</td></tr><tr><td>JetPRIME Transfection reagent</td><td>Polyplus</td><td>114-07</td><td></td></tr><tr><td>Penicilin/Streptomycin</td><td>Gibco</td><td>15140-122</td><td></td></tr><tr><td>Photomask</td><td>Delta Mask</td><td></td><td></td></tr><tr><td>PLL-g-PEG solution</td><td>Surface Solutions</td><td>PLL(20)-g[3.5]- PEG(2)</td><td></td></tr><tr><td>R Software</td><td>https://www.r-project.org/</td><td>n/a</td><td></td></tr><tr><td>Trypsin (TrypLE Express 1X)</td><td>Gibco</td><td>12605-010</td><td></td></tr><tr><td>UV ozone oven</td><td>Jelight Company Inc</td><td>342-220</td><td></td></tr><tr><td>VAMP7-pHFluorin plasmid</td><td>n/a</td><td>n/a</td><td>Paper reference :http://www.ncbi.nlm.nih.gov/pubmed/?term=Role+of+HRB+in+clathrin-dependent+endocytosis.&lt;br/&gt; J Biol Chem. 2008 Dec 5;283(49):34365-73. doi: 10.1074/jbc.M804587200.&lt;br/&gt; Role of HRB in clathrin-dependent endocytosis.&lt;br/&gt; Chaineau M, Danglot L, Proux-Gillardeaux V, Galli T.</td></tr></tbody></table>

quantifying spatiotemporal parameters of cellular exocytosis in micropatterned cells

Live imaging of the pHluorin tagged Soluble N-ethylmaleimide-sensitive-factor Attachment protein REceptor (v-SNARE) Vesicle-associated membrane protein 7 (VAMP7) by total internal reflection fluorescence microscopy (TIRFM) is a straightforward way to explore secretion from the lysosomal compartment. Taking advantage of cell culture on micropatterned surfaces to normalize cell shape, a variety of statistical tools were employed to perform a spatial analysis of secretory patterns. Using Ripley&#8217;s K function and a statistical test based on the nearest neighbor distance (NND), we confirmed that secretion from lysosomes is not a random process but shows significant clustering. Of note, our analysis revealed that exocytosis events are also clustered in nonadhesion areas, indicating that adhesion molecules are not the only structures that can induce secretory hot spots at the plasma membrane. Still, we found that cell adhesion enhances clustering. In addition to precisely defined adhesive and nonadhesive areas, the circular geometry of these micropatterns allows the use of polar coordinates, simplifying analyses. We used Kernel Density Estimation (KDE) and the cumulative distribution function on polar coordinates of exocytosis events to identify enriched areas of exocytosis. In ring-shaped micropattern cells, clustering occurred at the border between the adhesive and nonadhesive areas. Our analysis illustrates how statistical tools can be employed to investigate spatial distributions of diverse biological processes.

The spatiotemporal characteristics of exocytosis events were analyzed from lysosomes visualized by VAMP7-pHluorin10,11 in hTert-RPE1 cells. hTert-RPE1 cells are nontransformed cells that adopt well to micropatterning and have been extensively used in previous micropattern-based studies4,14. VAMP7 is a lysosomal v-SNARE15 that was tagged with the super ecliptic pHluorin at its N-ter...

Watch this Scientific Journal Video about Quantifying Spatiotemporal Parameters of Cellular Exocytosis in Micropatterned Cells at JoVE.com

Quantifying Spatiotemporal Parameters of Cellular Exocytosis in Micropatterned Cells

Live imaging of lysosomal exocytosis on micropatterned cells allows a spatial quantification of this process. Morphology normalization using micropatterns is an outstanding tool to uncover general rules about the spatial distribution of cellular processes.

Live imaging of the pHluorin tagged Soluble N-ethylmaleimide-sensitive-factor Attachment protein REceptor (v-SNARE) Vesicle-associated membrane protein 7 ...

quantifying-spatiotemporal-parameters-cellular-exocytosis

Research

JoVE Journal

Biology

6.0K Views.  Institut Curie, 75005 Paris, France. Live imaging of lysosomal exocytosis on micropatterned cells allows a spatial quantification of this process. Morphology normalization using micropatterns is an outstanding tool to uncover general rules about the spatial distribution of cellular processes.

Video: Quantifying Spatiotemporal Parameters of Cellular Exocytosis in Micropatterned Cells

Improved Visualization and Quantitative Analysis of Drug Effects Using Micropatterned Cells

To date, most HCA (High Content Analysis) studies are carried out with adherent cell lines grown on a homogenous substrate in tissue-culture treated micro-plates. Under these conditions, cells spread and divide in all directions resulting in an inherent variability in cell shape, morphology and behavior. The high cell-to-cell variance of the overall population impedes the success of HCA, especially for drug development. The ability of micropatterns to normalize the shape and internal polarity of every individual cell provides a tremendous opportunity for solving this critical bottleneck 1-2.
To facilitate access and use of the micropatterning technology, CYTOO has developed a range of ready to use micropatterns, available in coverslip and microwell formats. In this video article, we provide detailed protocols of all the procedures from cell seeding on CYTOOchip micropatterns, drug treatment, fixation and staining to automated acquisition, automated image processing and final data analysis. With this example, we illustrate how micropatterns can facilitate cell-based assays. Alterations of the cell cytoskeleton are difficult to quantify in cells cultured on homogenous substrates, but culturing cells on micropatterns results in a reproducible organization of the actin meshwork due to systematic positioning of the cell adhesion contacts in every cell. Such normalization of the intracellular architecture allows quantification of even small effects on the actin cytoskeleton as demonstrated in these set of protocols using blebbistatin, an inhibitor of the actin-myosin interaction.

Adhesive micropatterns that normalize cellular architecture can be used to increase sensitivity in the detection of drug effects, improve reproducibility and simplify automated image acquisition and analysis. Such technology will benefit drug/siRNA screening assays, performed on conventional cell culture supports and consequently suffering from excessive cell-to-cell variability.

To date, most HCA (High Content Analysis) studies are carried out with adherent cell lines grown on a homogenous substrate in tissue-culture treated ...

Bioengineering

A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions

Inter-cellular communication is an integral part of a complex system that helps in maintaining basic cellular activities. As a result, the malfunctioning of such signaling can lead to many disorders. To understand cell-to-cell signaling, it is essential to study the spatial and temporal nature of the secreted molecules from the cell without disturbing the local environment. Various assays have been developed to study protein secretion, however, these methods are typically based on fluorescent probes which disrupt the relevant signaling pathways. To overcome this limitation, a label-free technique is required.
In this paper, we describe the fabrication and application of a label-free localized surface plasmon resonance imaging (LSPRi) technology capable of detecting protein secretions from a single cell. The plasmonic nanostructures are lithographically patterned onto a standard glass coverslip and can be excited using visible light on commercially available light microscopes. Only a small fraction of the coverslip is covered by the nanostructures and hence this technique is well suited for combining common techniques such as fluorescence and bright-field imaging.
A multidisciplinary approach is used in this protocol which incorporates sensor nanofabrication and subsequent biofunctionalization, binding kinetics characterization of ligand and analyte, the integration of the chip and live cells, and the analysis of the measured signal. As a whole, this technology enables a general label-free approach towards mapping cellular secretions and correlating them with the responses of nearby cells.

Inter-cellular communication is critical for controlling various physiological activities within and outside the cell. This paper describes a protocol for measuring the spatio-temporal nature of single cell secretions. To achieve this, a multidisciplinary approach is used which integrates label-free nanoplasmonic sensing with live cell imaging.

Inter-cellular communication is an integral part of a complex system that helps in maintaining basic cellular activities. As a result, the malfunctioning ...

Investigating Mast Cell Secretory Granules; from Biosynthesis to Exocytosis

Mast Cells (MC) are secretory cells of the immune system that accomplish their physiological and pathological functions by releasing pre-formed and newly synthesized allergic, inflammatory and immunoregulatory mediators. MCs&#8217; mediators affect multiple tissues and organs culminating in allergic and immune responses. The synthesis, storage and release of the MC mediators are highly regulated. The pre-formed mediators are packed in cytoplasmic secretory granules&#160;(SG) that fuse with the plasma membrane and release their content by regulated exocytosis. We present a protocol, based on the co-expression of a gene of interest with a reporter gene that is targeted to the SGs and is released in a regulated fashion alongside the endogenous SG mediators. The protocol enables high resolution four dimensional confocal analyses of the MC SGs and monitoring their timeline from biogenesis to triggered exocytosis. Thus, using this protocol for screening genes of interest for their phenotypic and functional impact allows deciphering the molecular mechanisms that govern the biogenesis and exocytosis of the MC SGs and identifying the regulators involved. Thereby, further insights into the cellular mechanisms that account for MCs function in health and disease should be provided.

The goal of the present&#160;protocol was to develop a method that will allow functional genomic analyses of mast cell secretion. The protocol is based on quantitative assessment of the release of a fluorescent reporter gene cotrasfected with the gene of interest and real time&#160;analyses of the secretory granule&#39;s morphology.

Mast Cells (MC) are secretory cells of the immune system that accomplish their physiological and pathological functions by releasing pre-formed and newly ...

Immunology and Infection

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

A fundamental goal in biology is to understand how patterns emerge during development. Several groups have shown that patterning can be achieved in vitro when stem cells are spatially confined onto micropatterns, thus setting up experimental models which offer unique opportunities to identify, in vitro, the fundamental principles of biological organisation.
Here we describe our own implementation of the methodology. We adapted a photo-patterning technique to reduce the need for specialized equipment to make it easier to establish the method in a standard cell biology laboratory. We also developed a free, open-source and easy to install image analysis framework in order to precisely measure the preferential positioning of sub-populations of cells within colonies of standard shapes and sizes. This method makes it possible to reveal the existence of patterning events even in seemingly disorganized populations of cells. The technique provides quantitative insights and can be used to decouple influences of the environment (e.g., physical cues or endogenous signaling), on a given patterning process.

The method presented here uses micropatterning together with quantitative imaging to reveal spatial organization within mammalian cultures. The technique is easy to establish in a standard cell biology laboratory and offers a tractable system to study patterning in vitro.

A fundamental goal in biology is to understand how patterns emerge during development. Several groups have shown that patterning can be achieved in vitro ...

Developmental Biology

Monitoring the Effect of Osmotic Stress on Secretory Vesicles and Exocytosis

Amperometry recording of cells subjected to osmotic shock show that secretory cells respond to this physical stress by reducing the exocytosis activity and the amount of neurotransmitter released from vesicles in single exocytosis events. It has been suggested that the reduction in neurotransmitters expelled is due to alterations in membrane biophysical properties when cells shrink in response to osmotic stress and with assumptions made that secretory vesicles in the cell cytoplasm are not affected by extracellular osmotic stress. Amperometry recording of exocytosis monitors what is released from cells the moment a vesicle fuses with the plasma membrane, but does not provide information on the vesicle content before the vesicle fusion is triggered. Therefore, by combining amperometry recording with other complementary analytical methods that are capable of characterizing the secretory vesicles before exocytosis at cells is triggered offers a broader overview for examining how secretory vesicles and the exocytosis process are affected by osmotic shock. We here describe how complementing amperometry recording with intracellular electrochemical cytometry and transmission electron microscopy (TEM) imaging can be used to characterize alterations in secretory vesicles size and neurotransmitter content at chromaffin cells in relation to exocytosis activity before and after exposure to osmotic stress. By linking the quantitative information gained from experiments using all three analytical methods, conclusions were previously made that secretory vesicles respond to extracellular osmotic stress by shrinking in size and reducing the vesicle quantal size to maintain a constant vesicle neurotransmitter concentration. Hence, this gives some clarification regarding why vesicles, in response to osmotic stress, reduce the amount neurotransmitters released during exocytosis release. The amperometric recordings here indicate this is a reversible process and that vesicle after osmotic shock are refilled with neurotransmitters when placed cells are reverted into an isotonic environment.

Osmotic stress affects exocytosis and the amount of neurotransmitter released during this process. We demonstrate how combining electrochemical methods together with transmission electron microscopy can be used to study the effect of extracellular osmotic pressure on exocytosis activity, vesicle quantal size, and the amount of neurotransmitter released during exocytosis.

Amperometry recording of cells subjected to osmotic shock show that secretory cells respond to this physical stress by reducing the exocytosis activity ...

Neuroscience

Pattern Generation for Micropattern Traction Microscopy

Micropattern traction microscopy allows control of the shape of single cells and cell clusters. Furthermore, the ability to pattern at the micrometer length scale allows the use of these patterned contact zones for the measurement of traction forces, as each micropatterned dot allows for the formation of a single focal adhesion that then deforms the soft, underlying hydrogel. This approach has been used for a wide range of cell types, including endothelial cells, smooth muscle cells, fibroblasts, platelets, and epithelial cells. 
This review describes the evolution of techniques that allow the printing of extracellular matrix proteins onto polyacrylamide hydrogels in a regular array of dots of prespecified size and spacing. As micrometer-scale patterns are difficult to directly print onto soft substrates, patterns are first generated on rigid glass coverslips that are then used to transfer the pattern to the hydrogel during gelation. First, the original microcontact printing approach to generate arrays of small dots on the coverslip is described. A second step that removes most of the pattern to leave islands of small dots is required to control the shapes of cells and cell clusters on such arrays of patterned dots. 
Next, an evolution of this approach that allows for the generation of islands of dots using a single subtractive patterning step is described. This approach is greatly simplified for the user but has the disadvantage of a decreased lifetime for the master mold needed to make the patterns. Finally, the computational approaches that have been developed for the analysis of images of displaced dots and subsequent cell-generated traction fields are described, and updated versions of these analysis packages are provided.

We describe improvements to a standard method for measuring cellular traction forces, based on microcontact printing with a single subtractive patterning step of dot arrays of extracellular matrix proteins on soft hydrogels. This method allows for simpler and more consistent fabrication of island patterns, essential for controlling cell cluster shape.

Micropattern traction microscopy allows control of the shape of single cells and cell clusters. Furthermore, the ability to pattern at the micrometer ...

Temporal Quantification of MAPK Induced Expression in Single Yeast Cells

The quantification of gene expression at the single cell level uncovers novel regulatory mechanisms obscured in measurements performed at the population level. Two methods based on microscopy and flow cytometry are presented to demonstrate how such data can be acquired. The expression of a fluorescent reporter induced upon activation of the high osmolarity glycerol MAPK pathway in yeast is used as an example. The specific advantages of each method are highlighted. Flow cytometry measures a large number of cells (10,000) and provides a direct measure of the dynamics of protein expression independent of the slow maturation kinetics of the fluorescent protein. Imaging of living cells by microscopy is by contrast limited to the measurement of the matured form of the reporter in fewer cells. However, the data sets generated by this technique can be extremely rich thanks to the combinations of multiple reporters and to the spatial and temporal information obtained from individual cells. The combination of these two measurement methods can deliver new insights on the regulation of protein expression by signaling pathways.

Two complementary methods based on flow cytometry and microscopy are presented which enable the quantification, at the single cell level, of the dynamics of gene expression induced by the activation of a MAPK pathway in yeast.

The quantification of gene expression at the  single cell level uncovers novel regulatory mechanisms obscured in measurements  performed at the population ...

Quantitative Analysis of Cell Edge Dynamics during Cell Spreading

Cell spreading is a dynamic process in which a cell suspended in media attaches to a substrate and flattens itself from a rounded to a thin and spread-out shape. Following the cell-substrate attachment, the cell forms a thin sheet of lamellipodia emanating from the cell body. In the lamellipodia, globular actin (G-actin) monomers polymerize into a dense filamentous actin (F-actin) meshwork that pushes against the plasma membrane, thereby providing the mechanical forces required for the cell to spread. Notably, the molecular players that control the actin polymerization in lamellipodia are essential for many other cellular processes, such as cell migration and endocytosis. 
Since spreading cells form continuous lamellipodia that span the entire cell periphery and persistently expand outward, cell spreading assays have become an efficient tool to assess the kinetics of lamellipodial protrusions. Although several technical implementations of the cell spreading assay have been developed, a detailed description of the workflow, which would include both a step-by-step protocol and computational tools for data analysis, is currently lacking. Here, we describe the experimental procedures of the cell spreading assay and present an open-source tool for quantitative and unbiased analysis of cell edge dynamics during spreading. When combined with pharmacological manipulations and/or gene-silencing techniques, this protocol is amenable to a large-scale screen of molecular players regulating lamellipodial protrusions.

In this protocol, we present the experimental procedures of a cell spreading assay that is based on live-cell microscopy. We provide an open-source computational tool for the unbiased segmentation of fluorescently labeled cells and quantitative analysis of lamellipodia dynamics during cell spreading.

Cell spreading is a dynamic process in which a cell suspended in media attaches to a substrate and flattens itself from a rounded to a thin and spread-out ...

Automated Detection and Analysis of Exocytosis

Timelapse TIRF microscopy of pH-sensitive GFP (pHluorin) attached to vesicle SNARE proteins is an effective method to visualize single vesicle exocytic events in cell culture. To perform an unbiased, efficient identification and analysis of such events, a computer-vision based approach was developed and implemented in MATLAB. The analysis pipeline consists of a cell segmentation and exocytic-event identification algorithm. The computer-vision approach includes tools for investigating multiple parameters of single events, including the half-life of fluorescence decay and peak &#916;F/F, as well as whole-cell analysis of the frequency of exocytosis. These and other parameters of fusion are used in a classification approach to distinguish distinct fusion modes. Here a newly built GUI performs the analysis pipeline from start to finish. Further adaptation of Ripley&#39;s K function in R Studio is used to distinguish between clustered, dispersed, or random occurrence of fusion events in both space and time.

We developed automated computer vision software to detect exocytic events marked by pH-sensitive fluorescent probes. Here, we demonstrate the use of a graphical user interface and RStudio to detect fusion events, analyze and display spatiotemporal parameters of fusion, and classify events into distinct fusion modes.

Timelapse TIRF microscopy of pH-sensitive GFP (pHluorin) attached to vesicle SNARE proteins is an effective method to visualize single vesicle exocytic ...

Probing Structural and Dynamic Properties of Trafficking Subcellular Nanostructures by Spatiotemporal Fluctuation Spectroscopy

Imaging-derived mean square displacement (iMSD) is used to address the structural and dynamic properties of subcellular nanostructures, such as vesicles involved in the endo/exocytotic trafficking of solutes and biomolecules. iMSD relies on standard time-lapse imaging, is compatible with any optical setup, and does not need to dwell on single objects to extract trajectories. From each iMSD trace, a unique triplet of average structural and dynamic parameters (i.e., size, local diffusivity, anomalous coefficient) is calculated and combined to build the "iMSD signature" of the nanostructure under study. 
The potency of this approach is proved here with the exemplary case of macropinosomes. These vesicles evolve in time, changing their average size, number, and dynamic properties passing from early to late stages of intracellular trafficking. As a control, insulin secretory granules (ISGs) are used as a reference for subcellular structures that live in a stationary state in which the average structural and dynamic properties of the whole population of objects are invariant in time. The iMSD analysis highlights these peculiar features quantitatively and paves the way to similar applications at the sub-cellular level, both in the physiological and pathological states.

Imaging-derived mean square displacement (iMSD) analysis is applied to macropinosomes to highlight their intrinsic time-evolving nature in terms of structural and dynamic properties. Macropinosomes are then compared to insulin secretory granules (ISGs) as a reference for subcellular structures with time-invariant average structural/dynamic properties.

Imaging-derived mean square displacement (iMSD) is used to address the structural and dynamic properties of subcellular nanostructures, such as vesicles ...