When in contact with an adhesive substrate, vesicles with fluid membranes will deform to maximize the adhesion area. The balance between adhesion energy, membrane bending rigidity and vesicle volume and membrane area constraints determines the shape of the adhering vesicle. Thus measurements of the shape of an adhering vesicle can be used to approximate the membrane-substrate adhesion energy. Experimentally the method is based on fluorescence confocal imaging of adhering GUVs. Details of the method are given in the references (1,2) which should be read first. In the following the application and image analysis tools used are described. Basic knowledge of MATLAB and ImageJ is assumed. I used a semi-automated approach to extract the membrane contour instead of a completely automated contour detection. While latter might be preferred, the used approach turned out to be quite effective for a typical measurement of a few 10’s of vesicles per condition.
Note: The imaging quality and resolution will determine the precision of the method and should be optimized first. It is advantageous to use a high NA water immersion objective to achieve high resolution and limit spherical aberrations. Because the adhering vesicle shapes considered must have rotational symmetry, it is sufficient to acquire a side view of a adhering vesicle. This is conveniently done with the fast “Galvo z-stage” which allows to acquire a (x,z) image with a single confocal scan. As will become clear further below it is quite advantageous to overlay the image with the location of the adhesive substrate. This can be done elegantly by visualizing the light reflected form the water-substrate interface. On Leica SP microscopes this is accomplished using the “Reflection” presetting. Check your specific microscope setup on how to acquire such an image. This short manual assumes that you have acquired an image similar to the one shown in Fig. 1A.
Figure 1.Confocal image (side-view) of an adhering vesicle. Membrane (green) and substrate (red).
1.txt. The coordinates are [x,y] pairs of points along the contour with the coordinates for the groundline in the first two rows.
tordeux_adhesive.m(links below) and all files are in the same path. Now you can calculate the area, volume and reduced volume from this contour. Call
getRV(data,scale)with the datafile and
scalethe pixelsize in units of 1/µm. Note: Make sure that “importdata” imports the data as a n x 2 double. Maybe you need to look in the importdata struct for it.
>> data=importdata("1.txt"); >> [rv,avg,dev,discarea]=getRV(data,7.2) rv = 0.8425 0.8424 avg = 1.0e+04 * 1.0164 8.1191 0.8425 dev = 1.0e+03 * 0.3614 4.3248 0.0001 discarea = 2.7559e+03
6. Each image is divided along the midpoint of the “ground line” selected in Fiji in Step 2. Thus for each image you get two values for vesicle area and volume. Here
rv is the reduced volume,
avg is the average area from the two mirror images,
avg the corresponding vesicle volume and average reduced volume
avg. As a rule of thumb the corresponding standard deviations in
dev should be a at least a factor of 10 smaller then the average values.
discarea is the total adhesion area calculated from the “Ground line”. The adhesion energy is calculated from these values:
>> tordeux_adhesive(rv,avg,dev,discarea) ans = 0.4467
If you found the analysis useful, please cite the corresponding articles.