This work was funded by the Danish Council for Independent Research [grant number 5054-00165B].

1. Liposome Preparation
NOTE: Briefly, preparation of liposomes usually includes three crucial steps: 1) preparation of dry lipid films of the desired lipid composition; 2) rehydration of the lipids for formation of liposomes; and 3) controlling the size and lamellarity of the liposome population.
<ol>
	<li>Weigh out the lipids and dissolve them in tert-butanol:water (9:1) in glass vials.
	<ol>
		<li>Dissolve POPC (1-palmitoyl-2-oleoyl-glycero-3-phosphocholine; MW = 760 g/mol) to 50 mM.</li>
		<li>Dissolve cholesterol (MW = 387 g/mol) to 25 mM.</li>
		<li>Dissolve DOPE-Atto488 (1,2-dioleoyl-sn-glycero-3-phosphoethanolamine-Atto488; MW = 1,316 g/mol) to 0.1 mM.</li>
		<li>Dissolve DOPE-Atto655 (1,2-dioleoyl-sn-glycero-3-phosphoethanolamine-Atto655; MW = 1,368 g/mol) to 0.1 mM.</li>
		<li>Dissolve DSPE-PEG2000-biotin (1,2-distearyl-sn-glycero-3-phosphatethanolamine-N-[biotinyl(polyethylene glycol)-2000]; MW = 3,017 g/mol) to 0.1 mM. 
		NOTE: Heat lipids to 55 &#176;C and use magnetic stirring in order to ensure complete dissolution of the lipids. Alternatively, use a sonication bath. Unused lipid stocks can be stored at -20 &#176;C for several months.</li>
	</ol>
	</li>
	<li>Mix the lipid stocks prepared in step 1.1 to a molar ratio of POPC:cholesterol:DOPE-Atto488:DOPE-Atto655:DOPE-PEG-biotin 68.95:30:0.5:0.5:0.05, by adding 138 &#181;L of POPC, 120 &#181;L of cholesterol, 500 &#181;L of each fluorescently labeled lipid, and 50 &#181;L of DSPE-PEG-biotin to a fresh glass vial. 
	NOTE: The exact liposome composition can easily be modified in order to address the specific question of interest. See discussion for more detail.</li>
	<li>Loosen the lid of the glass vial, and snap-freeze the vial in liquid nitrogen.</li>
	<li>Lyophilize the frozen lipid mixture overnight.</li>
	<li>Add 1 mL of 200 mM D-sorbitol buffer (sorbitol buffer) to the dry lipids.</li>
	<li>Heat the mixture to 45 &#176;C and expose to magnetic stirring for at least 1 h. 
	NOTE: The buffer should reflect the specific question that is being addressed (e.g., physiological conditions for studying membrane-protein interactions, or a specific clinically approved buffer for studying drug delivery liposomes). However, if a specific buffer is not required for the study, a buffer without ions can be applied for rehydration in order to reduce the multilamellarity of the liposomes.</li>
	<li>Freeze the lipid suspension by dipping the vial in liquid nitrogen, and wait until the suspension is completely frozen.</li>
	<li>Dip the frozen suspension in a heating bath at 55 &#176;C until the mixture is completely thawed.</li>
	<li>Repeat steps 1.7 and 1.8 until the liposome suspension has been exposed to a total of 11 freeze/thaw cycles. 
	NOTE: Repeated freeze/thaw cycles have shown to reduce liposome multilamellarity23, which is paramount for the accuracy of the single liposome assay, as multilamellar liposomes will skew the fluorescence intensity versus liposome size ratio of the liposomes. The multilamellarity is usually inherently low when including more than 0.5% PEGylated lipid in the formulation (such as commonly done in liposomes for drug delivery)24.</li>
	<li>Extrude the liposome suspension once through an 800 nm polycarbonate filter using a mini extrusion kit. Follow the manufacturer&#39;s instructions for assembly of the extrusion kit (see Table of Materials).</li>
	<li>Store the liposomes at 4 &#176;C overnight.</li>
</ol>
2. Surface Preparation of Imaging Chamber
<ol>
	<li>Prepare bovine serum albumin (BSA; 1 mg/mL), BSA-biotin (1 mg/mL) and streptavidin (0.025 mg/mL) in 10 mM HEPES (4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid) 95 mM NaCl buffer (HEPES buffer). 
	NOTE: To prevent liposomal burst, the sorbitol buffer used for rehydration and the HEPES buffer used for surface preparation should be isotonic. It is thus recommended to check the osmolarity of the buffers before the experiment.</li>
	<li>Mix 1,200 &#181;L of BSA and 120 &#181;L of BSA-biotin and add 300 &#181;L of the mixture to each well in an 8 well slide for microscopy. 
	NOTE: Here we use a commercially available 8 well microscope slide with a glass bottom (see Table of Materials), but the protocol can easily be adapted to customized microscope chambers.</li>
	<li>Incubate the slide for 20 min at room temperature (RT).</li>
	<li>Wash the slide 8x with 300 &#181;L of HEPES buffer. 
	NOTE: Be careful not to leave the wells without buffer for more than a few seconds, as drying out the surface will damage it. Furthermore, be careful not to scratch the surface with the pipette tip as this will also damage it. Thus, when aspirating buffer from a well, do it from the edge or corner.</li>
	<li>Add 250 &#181;L of streptavidin and incubate for 10 min at RT.</li>
	<li>Repeat the 8 washes described in step 2.4.</li>
	<li>Store the microscope slide with 300 &#181;L of sorbitol buffer in each well at 4 &#176;C. Evaporation of the solvent will damage the surface, so put the microscope slide in a Petri dish and seal it with parafilm unless the prepared slide is used immediately.</li>
</ol>
3. Liposome Immobilization
<ol>
	<li>Dilute the liposome suspension to about 20 &#181;M total lipid in sorbitol buffer. The procedure in section 1 will yield a liposome suspension of approximately 10 mM total lipid.</li>
	<li>Place the slide on the microscope and focus on the surface of the chamber using the increased laser reflection signal from the glass/buffer interface as a guide.</li>
	<li>Wash the chamber 4x with 300 &#181;L of fresh HEPES buffer.</li>
	<li>Add 10 &#181;L of diluted liposome stock (20 &#181;M total lipid) to a microcentrifuge tube.</li>
	<li>Take out 100 &#181;L of buffer from the chamber, add to the microcentrifuge tube prepared in step 3.4, mix properly, and put the 110 &#181;L back into the chamber.</li>
	<li>Put the specimen under the microscope, and use a rudimental microscope setting capable of detecting signal from the liposome fluorophore(s) to observe the liposomes being immobilized on the surface.</li>
	<li>Aim for a liposome surface density that is simultaneously sparse enough to indentify individual liposomes and dense enough that it facilitates high-throughput measurements. Typically using a 50 &#181;m x 50 &#181;m field of view, 300&#8722;400 liposomes per frame is optimal (Figure 2). This can usually be achieved within 5&#8722;10 min. 
	NOTE: If only rapidly moving fluorescent particles are detected in the field of view, an absence or too low concentration of any of the components critical for the immobilization process (BSA-biotin, streptavidin, DOPE-PEG-biotin) might be the cause. If no liposomes are detected it might either be related to a low concentration of liposomes, improper settings for the fluorescence detection, or potentially imaging with a focal plane not at the glass surface.</li>
	<li>Once an appropriate liposome surface density is reached, wash the chamber 3x with 200 &#181;L of HEPES buffer. 
	NOTE: Be aware that the immobilization kinetics also depend on liposome properties such as size and charge and should thus always be optimized for each liposome formulation.</li>
</ol>
4. Image Acquisition
NOTE: This section will depend a lot on the microscope system available to the researcher performing the experiment. Thus, overall guidelines on how to perform the imaging will be described. However, the exact settings and how to apply them will vary between the different microscope setups. For example, some systems allow choosing any emission filter combination desired, while other microscopes are equipped with specific, preset filters.
<ol>
	<li>Set up the microscope for imaging single liposomes. To ensure optimal image quality and subsequent data analysis use a high greyscale resolution and a pixel scheme that allows for oversampling individual liposomes. A bit depth of 16 and at least 1,024 x 1,024 pixels for a 50 &#181;m x 50 &#181;m area is recommended. If available, line-averaging can beneficially be applied to reduce noise (e.g., 3 scans per line).</li>
	<li>Select an excitation laser power that both ensures nonsignificant frame-to-frame bleaching and strong enough signal to clearly discriminate individual liposomes from the background. The optimal setting will depend on the specific microscope used as well as the fluorophore combination. Make sure that detectors are not saturated, as this will bias intensity quantification.</li>
	<li>Imaging both the DOPE-Atto488 and DOPE-Atto655 fluorophores in the liposomes requires imaging multiple channels. Thus, make sure each channel is imaged sequentially to avoid cross-excitation. For example, first take one image by exciting at 488 nm and reading emission at 495&#8722;560 nm. Thereafter, take another image by exciting at 633 nm but reading emission only at 660&#8722;710 nm. The specifics will depend on the microscope system (e.g., which lasers and filters) available.</li>
	<li>Make sure to cover different areas of the surface, acquiring at least 10 images of the sample, thus imaging at least 3,000 individual liposomes. If the surface density is lower than 300 liposomes/frame, acquire more images. Make sure to refocus the microscope for every new image. 
	NOTE: For two-channel imaging, make sure to name the image files so that pairs of images with the same liposomes in different fluorescence channels can easily be identified during data analysis.</li>
	<li>In order to quantify the experimental uncertainty relating to the measurement of compositional inhomogeneity, image the same area of liposomes before and after refocusing (see Figure 3 and description in the text).</li>
	<li>Export the images from the microscope software as .tiff files. Export the two channels of the same liposomes individually.</li>
</ol>
5. Data Analysis
NOTE: Specially developed automated 2D Gaussian fitting routines have previously been employed6,11,12. However, to increase the applicability of the method a data analysis process that can be easily implemented in all laboratories is described.
<ol>
	<li>Load the corresponding pair of .tiff images of two different fluorescence channels in the same imaging field into the FIJI (FIJI Is Just ImageJ) software.</li>
	<li>In the Image menu, choose Color, and use the Merge Channel function to create a composite of the two channels.</li>
	<li>Observe if the liposomes imaged in two different channels display good colocalization or whether visible drift occurred. 
	NOTE: In case of drift between the two fluorescence channels (recognized as a systematic and equal X-Y offset between the signal in the two channels), one of the frames can be translated using the Transform &#62; Translate function in the Image menu of FIJI. However, care should be taken with such image manipulation. It is thus recommended to instead avoid drift as much as possible when imaging the liposomes.</li>
	<li>Make sure the ComDet plugin (v.0.3.6.1 or newer) is installed, or do this in the Plugins menu.</li>
	<li>Open the ComDet plugin to detect particles by going to the Plugins menu and choosing ComDet v.0.3.6.1 &#62; Detect Particles.</li>
	<li>In ComDet, make sure to choose the Detect Particles on Both Channels Individually function. Set the Max Distance Between Co-localized Spots similar to the Approximate Particles Size. Usually, 4 pixels is appropriate for the settings described here.</li>
	<li>The signal-to-noise ratio should allow for detection of even dim particles with a low amount of fluorescence. In ComDet, set this ratio to 3 by setting the Sensitivity of Detection in both channels to Very Dim Particles (SNR = 3). 
	NOTE: While this SNR value is usually appropriate, it might be necessary to set it higher (e.g., if there is a lot of image noise that may be identified as liposomes and lead to false positives).</li>
	<li>Make sure the boxes with Calculate Colocalization and Plot Detected Particles in Both Channels are checked, before pressing OK.</li>
	<li>After running the analysis, two pop-up windows with Results and Summary will show. Export the data table Results containing the colocalization data (particle coordinates and integrated intensity of each particle detected) to a data handling software of choice by saving the table as a .txt file and importing it into the software.</li>
	<li>Make sure that each liposome is only included once in the data set and not both the channel1/channel2 as well as channel2/channel1 ratio. Thus, filter the data so only Abs_frame = 1 is plotted in step 5.11. 
	NOTE: By choosing Colocalized = 1, false positives from noise in the images can be removed from the analysis. However, any liposomes with only one of the two fluorescent components present will also be excluded from the analysis, thus potentially removing important data points from the analysis.</li>
	<li>Plot a histogram of the column with data containing the Intensity Ratio for each detected liposome.</li>
	<li>The degree of compositional inhomogeneity for the studied liposomal system is represented by the width of the intensity ratio distribution. To quantify the inhomogeneity, fit the intensity ratio histogram with a Gaussian function and extract the mean (&#181;) and standard deviation (sigma). See the Representative Results section.</li>
	<li>A value for the degree of inhomogeneity (DI) can now be calculated using the coefficient of variation defined as DI = sigma / &#181;.</li>
</ol>
6. Liposome Size Calibration
<ol>
	<li>Take out part of the liposome stock, and extrude 21x through a 50 nm polycarbonate filter as described in step 1.10.</li>
	<li>Dilute the liposomes by adding 10 &#181;L of the liposome suspension to 800 &#181;L of sorbitol buffer in a microcentrifuge tube.</li>
	<li>Transfer the diluted liposome sample to a polypropylene single-use cuvette.</li>
	<li>Measure the size using dynamic light scattering (DLS). Perform at least three independent runs to measure the size and polydispersity of the liposome suspension. 
	NOTE: If necessary, use a more concentrated liposome suspension for the measurement. Alternatives to DLS (e.g., nanoparticle tracking analysis) can also be applied for measuring the size of the liposomes. A description of how to execute such particle-size determination is beyond the scope of this protocol.</li>
	<li>Image the calibration liposomes on the microscope using exactly the same experimental settings as defined in steps 4.1 and 4.2.</li>
	<li>Extract the integrated intensity for each calibration liposome in the calibration images: Extract the filtered results sheet containing liposome fluorescence intensities as described in steps 5.1&#8722;5.10. From the results table, extract the &#34;IntegratedInt&#34; column.</li>
	<li>Because the total integrated intensity of a liposome labeled in its membrane is proportional to the surface area of the liposome and is thus proportional to the square of its diameter, plot a square root intensity histogram of the fluorescence intensity of the calibration liposomes.</li>
	<li>Fit the integrated intensity histogram produced in step 6.7 with a log normal distribution and extract the average fluorescence intensity of the calibration liposomes.</li>
	<li>To determine the relation between the square root intensity (IntSqrt) and liposome size, calculate the correction factor (C) using the average liposome diameter (Dia) weighed by the number obtained from the DLS measurements: Dia = C x IntSqrt is equivalent to C = Dia / IntSqrt.</li>
	<li>Calculate IntSqrt values for the liposomes in the compositional inhomogeneity experiment and convert these to diameters by multiplying with the correction factor.</li>
	<li>Plot the intensity ratio value as a function of diameter for the compositional inhomogeneity liposomes, thus achieving the inhomogeneity as a function of liposome size for a population of liposomes spanning from approximately 50 nm&#8722;800 nm.</li>
</ol>

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The authors declare no conflict of interest.

It is important to note that while we describe in detail how the single liposomes assay can be used to study the compositional inhomogeneity between individual liposomes, the platform is very versatile. As previously shown and discussed in the introduction, the protocol can easily be adapted to study aspects of membrane-membrane fusion, protein-membrane interactions, or liposomal drug carrier characterization. For any scientific questions being addressed, the power of the single liposome assay lies in the ability to dete...

Liposomes are spherical phospholipid-based vesicles that are heavily used both in basic and applied research. They function as excellent membrane model systems, because their physiochemical properties can be easily manipulated by varying the lipid components making up the liposome1,2. Also, liposomes constitute the most used drug delivery nanocarrier system, offering improved pharmacokinetics and pharmacodynamics as well as high biocompatibility3.
For many years, liposomes have primarily been studied using bulk techniques, giving only access to ensemble average read-out values. This has led the majority of these studies to assume that all liposomes in the ensemble are identical. However, such ensemble-averaged values are only correct if the underlying dataset is uniformly distributed around the mean value, but can represent a false and biased conclusion if the dataset includes multiple independent populations, for example. Additionally, assuming the ensemble mean to represent the whole population can overlook the information harbored within the inhomogeneity between liposomes. Only recently have quantitative assays emerged that are able to probe single liposomes, revealing large inhomogeneities between individual liposomes with respect to important physicochemical properties including liposome size4, lipid composition5,6, and encapsulation efficiency7, highlighting the importance of studying liposomes at the single liposome level.
A research area where ensemble averaging of liposome properties has been shown to bias results is studying liposome size-dependent protein-membrane interactions8,9. Traditionally, researchers studying such processes have been restricted to preparing liposomes with different ensemble average diameters by extrusion through filters with different pore sizes9. However, extracting the diameter of individual liposomes using single liposome assays has revealed large population overlaps, with liposomes extruded using 100 nm and 200 nm filters displaying up to 70% overlap in their size distribution4. This could severely bias bulk measurements of liposome size-dependent protein-membrane interactions10. Performing the membrane-protein interaction studies using the single liposome assay, researchers instead took advantage of the size-polydispersity within the sample, allowing them to study a wide range of liposome diameters within each single experiment, facilitating new discoveries of how membrane curvature and composition can affect protein recruitment to membranes4,11,12. Another field where the application of single liposome assays has proven instrumental is in mechanistic studies of protein-mediated membrane fusion13,14. For such kinetic measurements, the ability to study individual fusion events alleviated the need for the experimental synchronization of the fusion process, allowing new mechanistic insights that would otherwise have been lost in the spatiotemporal averaging done in bulk ensemble measurements. Additionally, single liposomes have been used as a membrane scaffold, allowing the measurement of individual proteins and offering new knowledge on transmembrane protein structural dynamics15,16. Furthermore, such proteoliposome-based setups made it possible to study the function of individual transmembrane transporters17 and pore-forming protein complexes18 as well as the mechanism of bioactive membrane-permeabilizing peptides19. Single liposomes have also been used as soft matter nanofluidics with surface-immobilized single liposomes serving as chambers for enzymatic reactions in volumes of 10-19 L, increasing the throughput and complexity of the screening assays with minimal product consumption20.
Recently, single liposome assays have been used for characterizing drug delivery liposomes at a previously unprecendented level of detail. Researchers were able to quantify significant inhomogeneities in the amount of polymer attached to the surface of individual liposomes21. The single liposome assays also allowed measurements of drug delivery liposomes in complex media, such as blood plasma, revealing how elements anchored to the liposome surface through lipid anchors can be susceptible to dissociation when liposomes are exposed to conditions mimicking those experienced during in vivo circulation22. Overall, the versatility and usefulness of the single liposome assays are substantiated by the great variety of problems these setups have been employed to address, and we envision that the methodology will continue to be developed and find use in new scientific fields.
Here we describe a fluorescence microscopy-based single liposome assay that allows individual liposomes to be studied in a high-throughput manner (Figure 1). To illustrate the method, we use it to quantify the size and compositional inhomogeneity between individual liposomes within an ensemble. The assay employs fluorescence microscope imaging of single liposomes immobilized on a passivated glass surface. We first describe the critical steps in the liposome fabrication process that ensures proper fluorescent liposome labeling and immobilization. Then, we describe the surface preparation needed to facilitate liposome immobilization before outlining the procedure for ensuring appropriate liposome surface densities. We discuss the microscopy parameters important for acquiring high-quality images and delineate how to perform simple data analysis, allowing the extraction of liposome size and compositional inhomogeneity. This generic protocol should provide a good basis for the interested researcher to develop the assay further for his or her specific research interest.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>8-well microscopy slides (&#181; slides)</td>
			<td>Ibidi</td>
			<td>80827</td>
			<td>Microscopy slides with glass bottom</td>
		</tr>
		<tr>
			<td>Avanti Mini Extrusion kit</td>
			<td>Avanti Polar Lipids</td>
			<td>610000</td>
			<td>Consumables (Whatman filters) can be aquired from GE Healthcare</td>
		</tr>
		<tr>
			<td>BSA</td>
			<td>Sigma</td>
			<td>A9418</td>
			<td></td>
		</tr>
		<tr>
			<td>BSA-Biotin</td>
			<td>Sigma</td>
			<td>A8549</td>
			<td></td>
		</tr>
		<tr>
			<td>Cholesterol</td>
			<td>Avanti Polar Lipids</td>
			<td>700000</td>
			<td>Traded trough Sigma</td>
		</tr>
		<tr>
			<td>Computer with FIJI (Fiji Is Just ImageJ)</td>
			<td></td>
			<td></td>
			<td>ComDet plugin must be installed. Also, a data handling software (Excel, MatLab, OpenOffice, GraphPad Prism etc.) able to load .txt files will be needed to plot the data</td>
		</tr>
		<tr>
			<td>DOPE-Atto488</td>
			<td>Atto-Tech</td>
			<td>AD488-165</td>
			<td></td>
		</tr>
		<tr>
			<td>DOPE-Atto655</td>
			<td>Atto-Tech</td>
			<td>AD655-165</td>
			<td></td>
		</tr>
		<tr>
			<td>DOPE-PEG-Biotin</td>
			<td>Avanti Polar Lipids</td>
			<td>880129</td>
			<td>Traded trough Sigma</td>
		</tr>
		<tr>
			<td>D-Sorbitol</td>
			<td>Sigma</td>
			<td>S-6021</td>
			<td></td>
		</tr>
		<tr>
			<td>Freeze-dryer</td>
			<td></td>
			<td></td>
			<td>e.g. ScanVac Coolsafe from Labogene</td>
		</tr>
		<tr>
			<td>Glass vials</td>
			<td>Brown Chromatography</td>
			<td>150903</td>
			<td>Glass vials that can resist snap-freezing in liquid nitrogen. The 8 mL version of the vials has a size that also fits with the syringes of the extrusion kit</td>
		</tr>
		<tr>
			<td>HCl</td>
			<td>Honeywell Fluka</td>
			<td>258148</td>
			<td></td>
		</tr>
		<tr>
			<td>Heating bath</td>
			<td></td>
			<td></td>
			<td>Capable of heating to minimum 65C</td>
		</tr>
		<tr>
			<td>Heating plate w. Magnet stirring</td>
			<td></td>
			<td></td>
			<td>Capable of heating to minimum 65C</td>
		</tr>
		<tr>
			<td>HEPES</td>
			<td>Sigma</td>
			<td>H3375</td>
			<td></td>
		</tr>
		<tr>
			<td>Liquid nitrogen</td>
			<td></td>
			<td></td>
			<td>Including container for storage, e.g. Rubber-bath</td>
		</tr>
		<tr>
			<td>Magnetic stirring bars</td>
			<td>VWR</td>
			<td>442-4520 (EU)</td>
			<td></td>
		</tr>
		<tr>
			<td>Microcentrifuge tubes 1.5 mL</td>
			<td>Eppendorf</td>
			<td>0030 120.086 (EU)</td>
			<td></td>
		</tr>
		<tr>
			<td>Microscope</td>
			<td></td>
			<td></td>
			<td>For the images in this protocol a Leica SP5 confocal microscope has been used</td>
		</tr>
		<tr>
			<td>Na HEPES</td>
			<td>Sigma</td>
			<td>H7006</td>
			<td></td>
		</tr>
		<tr>
			<td>NaCl</td>
			<td>Sigma</td>
			<td>S9888</td>
			<td></td>
		</tr>
		<tr>
			<td>NaOH</td>
			<td>Honeywell Fluka</td>
			<td>71686</td>
			<td></td>
		</tr>
		<tr>
			<td>POPC</td>
			<td>Avanti Polar Lipids</td>
			<td>850457</td>
			<td>Traded trough Sigma</td>
		</tr>
		<tr>
			<td>Streptavidin</td>
			<td>Sigma</td>
			<td>S4762</td>
			<td></td>
		</tr>
		<tr>
			<td>tert-Butanol (2-methyl-2-propanol)</td>
			<td>Honeywell Riedel-de Ha&#235;n</td>
			<td>24127</td>
			<td></td>
		</tr>
		<tr>
			<td>Ultrapure water</td>
			<td></td>
			<td></td>
			<td>e.g. MilliQ</td>
		</tr>
	</tbody>
</table>

a quantitative fluorescence microscopy-based single liposome assay for detecting the compositional inhomogeneity between individual liposomes

Most research employing liposomes as membrane model systems or drug delivery carriers relies on bulk read-out techniques and thus intrinsically assumes all liposomes of the ensemble to be identical. However, new experimental platforms able to observe liposomes at the single-particle level have made it possible to perform highly sophisticated and quantitative studies on protein-membrane interactions or drug carrier properties on individual liposomes, thus avoiding errors from ensemble averaging. Here we present a protocol for preparing, detecting, and analyzing single liposomes using a fluorescence-based microscopy assay, facilitating such single-particle measurements. The setup allows for imaging individual liposomes in a massive parallel manner and is employed to reveal intra-sample size and compositional inhomogeneities. Additionally, the protocol describes the advantages of studying liposomes at the single liposome level, the limitations of the assay, and the important features to be considered when modifying it to study other research questions.

Following the protocol described makes it possible to image single liposomes in a massive parallel manner (Figure 1). The successful surface immobilization of liposomes should be immediately apparent upon the addition of the liposome solution to the chamber (step 3.6 in the protocol) as diffraction limited intensity spots should appear in the image (Figure 1B and Figure 1C</s...

Watch this Scientific Journal Video about A Quantitative Fluorescence Microscopy-based Single Liposome Assay for Detecting the Compositional Inhomogeneity Between Individual Liposomes at JoVE.com

A Quantitative Fluorescence Microscopy-based Single Liposome Assay for Detecting the Compositional Inhomogeneity Between Individual Liposomes

This protocol describes the fabrication of liposomes and how these can be immobilized on a surface and imaged individually in a massive parallel manner using fluorescence microscopy. This allows for the quantification of the size and compositional inhomogeneity between single liposomes of the population.

Most research employing liposomes as membrane model systems or drug delivery carriers relies on bulk read-out techniques and thus intrinsically assumes ...

a-quantitative-fluorescence-microscopy-based-single-liposome-assay

Research

JoVE Journal

Bioengineering

7.8K Views.  Technical University of Denmark. This protocol describes the fabrication of liposomes and how these can be immobilized on a surface and imaged individually in a massive parallel manner using fluorescence microscopy. This allows for the quantification of the size and compositional inhomogeneity between single liposomes of the population.

Video: A Quantitative Fluorescence Microscopy-based Single Liposome Assay for Detecting the Compositional Inhomogeneity Between Individual Liposomes

Quantitative and Temporal Control of Oxygen Microenvironment at the Single Islet Level

Simultaneous oxygenation and monitoring of glucose stimulus-secretion coupling factors in a single technique is critical for modeling pathophysiological states of islet hypoxia, especially in transplant environments. Standard hypoxic chamber techniques cannot modulate both stimulations at the same time nor provide real-time monitoring of glucose stimulus-secretion coupling factors. To address these difficulties, we applied a multilayered microfluidic technique to integrate both aqueous and gas phase modulations via a diffusion membrane. This creates a stimulation sandwich around the microscaled islets within the transparent polydimethylsiloxane (PDMS) device, enabling monitoring of the aforementioned coupling factors via fluorescence microscopy. Additionally, the gas input is controlled by a pair of microdispensers, providing quantitative, sub-minute modulations of oxygen between 0-21%. This intermittent hypoxia is applied to investigate a new phenomenon of islet preconditioning. Moreover, armed with multimodal microscopy, we were able to look at detailed calcium and KATP channel dynamics during these hypoxic events. We envision microfluidic hypoxia, especially this simultaneous dual phase technique, as a valuable tool in studying islets as well as many ex vivo tissues.

Microfluidic oxygen control confers more than just convenience and speed over hypoxic chambers for biological experiments. Especially when implemented via diffusion through a membrane, microfluidic oxygen can provide simultaneous liquid and gas phase modulations at the microscale-level. This technique enables dynamic multi-parametric experiments critical for studying islet pathophysiology.

Simultaneous oxygenation and monitoring of glucose stimulus-secretion coupling factors in a single technique is critical for modeling pathophysiological ...

Drug-induced Sensitization of Adenylyl Cyclase: Assay Streamlining and Miniaturization for Small Molecule and siRNA Screening Applications

Sensitization of adenylyl cyclase (AC) signaling has been implicated in a variety of neuropsychiatric and neurologic disorders including substance abuse and Parkinson&#39;s disease. Acute activation of G&#945;i/o-linked receptors inhibits AC activity, whereas persistent activation of these receptors results in heterologous sensitization of AC and increased levels of intracellular cAMP. Previous studies have demonstrated that this enhancement of AC responsiveness is observed both in vitro and in vivo following the chronic activation of several types of G&#945;i/o-linked receptors including D2 dopamine and &#956; opioid receptors. Although heterologous sensitization of AC was first reported four decades ago, the mechanism(s) that underlie this phenomenon remain largely unknown. The lack of mechanistic data presumably reflects the complexity involved with this adaptive response, suggesting that nonbiased approaches could aid in identifying the molecular pathways involved in heterologous sensitization of AC. Previous studies have implicated kinase and Gb&#947; signaling as overlapping components that regulate the heterologous sensitization of AC. To identify unique and additional overlapping targets associated with sensitization of AC, the development and validation of a scalable cAMP sensitization assay is required for greater throughput. Previous approaches to study sensitization are generally cumbersome involving continuous cell culture maintenance as well as a complex methodology for measuring cAMP accumulation that involves multiple wash steps. Thus, the development of a robust cell-based assay that can be used for high throughput screening (HTS) in a 384&#160;well format would facilitate future studies. Using two D2 dopamine receptor cellular models (i.e.&#160;CHO-D2L and HEK-AC6/D2L), we have converted our 48-well sensitization assay (&#62;20 steps 4-5 days) to a five-step, single day assay in 384-well format. This new format is amenable to small molecule screening, and we demonstrate that this assay design can also be readily used for reverse transfection of siRNA in anticipation of targeted siRNA library screening.

Persistent activation of inhibitory G protein-coupled receptors results in sensitization of adenylyl cyclase signaling. To identify the essential molecular pathways, nonbiased approaches are necessary; however, this strategy requires the development of a scalable cell-based cAMP sensitization assay. Herein, we describe a sensitization assay for small molecule and siRNA screening.

Sensitization of adenylyl cyclase (AC) signaling has been implicated in a variety of neuropsychiatric and neurologic disorders including substance abuse ...

3D Orbital Tracking in a Modified Two-photon Microscope: An Application to the Tracking of Intracellular Vesicles

The objective of this video protocol is to discuss how to perform and analyze a three-dimensional fluorescent orbital particle tracking experiment using a modified two-photon microscope1. As opposed to conventional approaches (raster scan or wide field based on a stack of frames), the 3D orbital tracking allows to localize and follow with a high spatial (10 nm accuracy) and temporal resolution (50 Hz frequency response) the 3D displacement of a moving fluorescent particle on length-scales of hundreds of microns2. The method is based on a feedback algorithm that controls the hardware of a two-photon laser scanning microscope in order to perform a circular orbit around the object to be tracked: the feedback mechanism will maintain the fluorescent object in the center by controlling the displacement of the scanning beam3-5. To demonstrate the advantages of this technique, we followed a fast moving organelle, the lysosome, within a living cell6,7. Cells were plated according to standard protocols, and stained using a commercially lysosome dye. We discuss briefly the hardware configuration and in more detail the control software, to perform a 3D orbital tracking experiment inside living cells. We discuss in detail the parameters required in order to control the scanning microscope and enable the motion of the beam in a closed orbit around the particle. We conclude by demonstrating how this method can be effectively used to track the fast motion of a labeled lysosome along microtubules in 3D within a live cell. Lysosomes can move with speeds in the range of 0.4-0.5 &#181;m/sec, typically displaying a directed motion along the microtubule network8.

In this video protocol we track - at high speed and in three dimensions - fluorescently labeled lysosomes within living cells, using the orbital tracking method in a modified two-photon microscope.

The objective of this video protocol is to discuss how to perform and analyze a three-dimensional fluorescent orbital particle tracking experiment using a ...

From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope

It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the regulation of many cellular functions. However, due to the fast dynamics and the tiny structures involved, a very high spatio-temporal resolution is required to catch the real behavior of molecules. Here we present the experimental protocol for studying the dynamics of fluorescently-labeled plasma-membrane proteins and lipids in live cells with high spatiotemporal resolution. Notably, this approach doesn&#8217;t need to track each molecule, but it calculates population behavior using all molecules in a given region of the membrane. The starting point is a fast imaging of a given region on the membrane. Afterwards, a complete spatio-temporal autocorrelation function is calculated correlating acquired images at increasing time delays, for example each 2, 3, n repetitions. It is possible to demonstrate that the width of the peak of the spatial autocorrelation function increases at increasing time delay as a function of particle movement due to diffusion. Therefore, fitting of the series of autocorrelation functions enables to extract the actual protein mean square displacement from imaging (iMSD), here presented in the form of apparent diffusivity vs average displacement. This yields a quantitative view of the average dynamics of single molecules with nanometer accuracy. By using a GFP-tagged variant of the Transferrin Receptor (TfR) and an ATTO488 labeled 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine (PPE) it is possible to observe the spatiotemporal regulation of protein and lipid diffusion on &#181;m-sized membrane regions in the micro-to-milli-second time range.

Spatial distribution and temporal dynamics of plasma membrane proteins and lipids is a hot topic in biology. Here this issue is addressed by a spatio-temporal image fluctuation analysis that provides conceptually the same physical quantities of single particle tracking, but it uses small molecular labels and standard microscopy setups.

It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the ...

Analyzing Mixing Inhomogeneity in a Microfluidic Device by Microscale Schlieren Technique

In this paper, we introduce the use of microscale schlieren technique to measure mixing inhomogeneity in a microfluidic device. The microscale schlieren system is constructed from a Hoffman modulation contrast microscope, which provides easy access to the rear focal plane of the objective lens, by removing the slit plate and replacing the modulator with a knife-edge. The working principle of microscale schlieren technique relies on detecting light deflection caused by variation of refractive index1-3. The deflected light either escapes or is obstructed by the knife-edge to produce a bright or a dark band, respectively. If the refractive index of the mixture varies linearly with its composition, the local change in light intensity in the image plane is proportional to the concentration gradient normal to the optical axis. The micro-schlieren image gives a two-dimensional projection of the disturbed light produced by three-dimensional inhomogeneity.
To accomplish quantitative analysis, we describe a calibration procedure that mixes two fluids in a T-microchannel. We carry out a numerical simulation to obtain the concentration gradient in the T-microchannel that correlates closely with the corresponding micro-schlieren image. By comparison, a relationship between the grayscale readouts of the micro-schlieren image and the concentration gradients presented in a microfluidic device is established. Using this relationship, we are able to analyze the mixing inhomogeneity from associate micro-schlieren image and demonstrate the capability of microscale schlieren technique with measurements in a microfluidic oscillator4. For optically transparent fluids, microscale schlieren technique is an attractive diagnostic tool to provide instantaneous full-field information that retains the three-dimensional features of the mixing process.

Herein, we describe a procedure that employs microscale schlieren technique to measure mixing inhomogeneity in a microfluidic device. Through calibration, distribution of concentration gradient can be derived from the micro-schlieren image.

In this paper, we introduce the use of microscale schlieren technique to measure mixing inhomogeneity in a microfluidic device. The microscale schlieren ...

Fluorescence Biomembrane Force Probe: Concurrent Quantitation of Receptor-ligand Kinetics and Binding-induced Intracellular Signaling on a Single Cell

Membrane receptor-ligand interactions mediate many cellular functions. Binding kinetics and downstream signaling triggered by these molecular interactions are likely affected by the mechanical environment in which binding and signaling take place. A recent study demonstrated that mechanical force can regulate antigen recognition by and triggering of the T-cell receptor (TCR). This was made possible by a new technology we developed and termed fluorescence biomembrane force probe (fBFP), which combines single-molecule force spectroscopy with fluorescence microscopy. Using an ultra-soft human red blood cell as the sensitive force sensor, a high-speed camera and real-time imaging tracking techniques, the fBFP is of ~1 pN (10-12 N), ~3 nm and ~0.5 msec in force, spatial and temporal resolution. With the fBFP, one can precisely measure single receptor-ligand binding kinetics under force regulation and simultaneously image binding-triggered intracellular calcium signaling on a single live cell. This new technology can be used to study other membrane receptor-ligand interaction and signaling in other cells under mechanical regulation.

We describe a technique for concurrently measuring force-regulated single receptor-ligand binding kinetics and real-time imaging of calcium signaling in a single T lymphocyte.

Membrane receptor-ligand interactions mediate many cellular functions. Binding kinetics and downstream signaling triggered by these molecular interactions ...

Single Molecule Fluorescence Microscopy on Planar Supported Bilayers

In the course of a single decade single molecule microscopy has changed from being a secluded domain shared merely by physicists with a strong background in optics and laser physics to a discipline that is now enjoying vivid attention by life-scientists of all venues 1. This is because single molecule imaging has the unique potential to reveal protein behavior in situ in living cells and uncover cellular organization with unprecedented resolution below the diffraction limit of visible light 2. Glass-supported planar lipid bilayers (SLBs) are a powerful tool to bring cells otherwise growing in suspension in close enough proximity to the glass slide so that they can be readily imaged in noise-reduced Total Internal Reflection illumination mode 3,4. They are very useful to study the protein dynamics in plasma membrane-associated events as diverse as cell-cell contact formation, endocytosis, exocytosis and immune recognition. Simple procedures are presented how to generate highly mobile protein-functionalized SLBs in a reproducible manner, how to determine protein mobility within and how to measure protein densities with the use of single molecule detection. It is shown how to construct a cost-efficient single molecule microscopy system with TIRF illumination capabilities and how to operate it in the experiment.

Preparation of protein-functionalized planar glass-supported lipid bilayers, determination of protein mobility within and measurement of protein densities is shown here. A roadmap to building a noise-reduced Total Internal Reflection microscope is outlined, which allows visualizing single bilayer-resident fluorochromes with high spatiotemporal resolution.

In the course of a single decade single molecule microscopy has changed from being a secluded domain shared merely by physicists with a strong background ...

Multicolor Fluorescence Detection for Droplet Microfluidics Using Optical Fibers

Fluorescence assays are the most common readouts used in droplet microfluidics due to their bright signals and fast time response. Applications such as multiplex assays, enzyme evolution, and molecular biology enhanced cell sorting require the detection of two or more colors of fluorescence. Standard multicolor detection systems that couple free space lasers to epifluorescence microscopes are bulky, expensive, and difficult to maintain. In this paper, we describe a scheme to perform multicolor detection by exciting discrete regions of a microfluidic channel with lasers coupled to optical fibers. Emitted light is collected by an optical fiber coupled to a single photodetector. Because the excitation occurs at different spatial locations, the identity of emitted light can be encoded as a temporal shift, eliminating the need for more complicated light filtering schemes. The system has been used to detect droplet populations containing four unique combinations of dyes and to detect sub-nanomolar concentrations of fluorescein.

Multicolor fluorescence detection in droplet microfluidics typically involves bulky and complex epifluorescence microscope-based detection systems. Here we describe a compact and modular multicolor detection scheme that utilizes an array of optical fibers to temporally encode multicolor data collected by a single photodetector.

Fluorescence assays are the most common readouts used in droplet microfluidics due to their bright signals and fast time response. Applications such as ...

Engineering Molecular Recognition with Bio-mimetic Polymers on Single Walled Carbon Nanotubes

Semiconducting single-wall carbon nanotubes (SWNTs) are a class of optically active nanomaterial that fluoresce in the near infrared, coinciding with the optical window where biological samples are most transparent. Here, we outline techniques to adsorb amphiphilic polymers and polynucleic acids onto the surface of SWNTs to engineer their corona phases and create novel molecular sensors for small molecules and proteins. These functionalized SWNT sensors are both biocompatible and stable. Polymers are adsorbed onto the nanotube surface either by direct sonication of SWNTs and polymer or by suspending SWNTs using a surfactant followed by dialysis with polymer. The fluorescence emission, stability, and response of these sensors to target analytes are confirmed using absorbance and near-infrared fluorescence spectroscopy. Furthermore, we demonstrate surface immobilization of the sensors onto glass slides to enable single-molecule fluorescence microscopy to characterize polymer adsorption and analyte binding kinetics.

We present a protocol for engineering the corona phase of near infrared fluorescent single walled carbon nanotubes (SWNTs) using amphiphilic polymers and DNA to develop sensors for molecular targets without known recognition elements.

Semiconducting single-wall carbon nanotubes (SWNTs) are a class of optically active nanomaterial that fluoresce in the near infrared, coinciding with the ...

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

Sequencing technologies have undergone a paradigm shift from bulk to single-cell resolution in response to an evolving understanding of the role of cellular heterogeneity in biological systems. However, single-cell sequencing of large populations has been hampered by limitations in processing genomes for sequencing. In this paper, we describe a method for single-cell genome sequencing (SiC-seq) which uses droplet microfluidics to isolate, amplify, and barcode the genomes of single cells. Cell encapsulation in microgels allows the compartmentalized purification and tagmentation of DNA, while a microfluidic merger efficiently pairs each genome with a unique single-cell oligonucleotide barcode, allowing &gt;50,000 single cells to be sequenced per run. The sequencing data is demultiplexed by barcode, generating groups of reads originating from single cells. As a high-throughput and low-bias method of single-cell sequencing, SiC-seq will enable a broader range of genomic studies targeted at diverse cell populations.

Single-cell sequencing reveals genotypic heterogeneity in biological systems, but current technologies lack the throughput necessary for the deep profiling of community composition and function. Here, we describe a microfluidic workflow for sequencing &gt;50,000 single-cell genomes from diverse cell populations.

Sequencing technologies have undergone a paradigm shift from bulk to single-cell resolution in response to an evolving understanding of the role of ...