Quantitative Fluorescence Microscopy To Determine Molecular Occupancy of Phospholipid Vesicles

Abstract

Encapsulation of molecules in phospholipid vesicles provides unique opportunities to study chemical reactions in small volumes as well as the behavior of individual proteins, enzymes, and ribozymes in a confined region without requiring a tether to immobilize the molecule to a surface. These experiments generally depend on generating a predictable loading of vesicles with small numbers of target molecules and thus raise a significant measurement challenge, namely, to quantify molecular occupancy of vesicles at the single-molecule level. In this work, we describe an imaging experiment to measure the time-dependent fluorescence from individual dye molecules encapsulated in ~130 nm vesicles that are adhered to a glass surface. For determining a fit of the molecular occupancy data to a Poisson model, it is critical to count empty vesicles in the population since these dominate the sample when the mean occupancy is small, λ ≤ ~1. Counting empty vesicles was accomplished by subsequently labeling all the vesicles with a lipophilic dye and reimaging the sample. By counting both the empty vesicles and those containing fluors, and quantifying the number of fluors present, we demonstrate a self-consistent Poisson distribution of molecular occupancy for well-solvated molecules, as well as anomalies due to aggregation of dye, which can arise even at very low solution concentrations. By observation of many vesicles in parallel in an image, this approach provides quantitative information about the distribution of molecular occupancy in a population of vesicles.

Molecular Occupancy of Nanodot Arrays

“…Given the F/P ratio, the molecular occupancy could be determined from the number of steps for each site (heptamer, in this case). Since the initial fluorescence intensity is linear with the number of fluorophores, 57 it is unnecessary to count step numbers for the entire set of bleaching curves in order to efficiently obtain statistical results. Alternatively, the average molecular occupancy can be estimated by $$N=\frac{I}{h\cdot r\cdot c}$$where N is the molecular occupancy, that is, the number of molecules per nanodot; I is the initial intensity of the nanodot cluster; h is the bleaching step size, that is, the intensity of a single fluorophore signal; r is the F/P ratio of the labeled molecule, that is, the number of fluorophores per molecule; and c is the cluster size, that is, the number of nanodots per cluster.…”

“…However, this probability increases with increased fluorophore number because the variances of individual fluorophore intensities are added, which is a common problem in quantitative fluorescence microscopy. 57 Therefore, a large sample size is required for reliable measurements using eq 1. Our method provides sufficient sample size by monitoring thousands of sites in parallel.…”

Less than 5 Netrin-1 molecules initiate attraction but 200 Sema3A molecules are necessary for repulsion

“…In order to determine the minimum value of N v necessary to evoke attraction we performed experiments by decreasing the value of N v and considering only experiments where Netrin-1 was attracting. When the concentration c of guidance molecules inside vesicles is reduced, two factors determine the exact value of N v : first N v becomes a random variable following a Poisson distribution32 and second, the mean value of N v will depend on the efficiency of the encapsulating procedure, i.e. to what extent the bulk concentration of guidance molecules c is equal to its concentration inside vesicles c v .…”

Improved Glass Surface Passivation for Single-Molecule Nanoarrays

“…Step changes of intensity have been used to determine the molecular occupancy of lipid vesicles 13 , monitor single QD blinking 47 , or DNA cleavage by a restriction enzyme 25 . Here the average bleaching step size was simply used to determine the single fluorophore intensity (see, e.g.…”

“…The bleaching curves with two and three steps (Figure 3a) correspond to the second and third peaks, representing streptavidins with two and three fluorophores, which comprise the majority of the histogram (Figure 3b). The overlapping of adjacent Gaussians is due to the variation of single fluorophore intensity, commonly observed in bleaching experiments, 13 which makes identification of particles by a predetermined intensity threshold problematic. Finally, the probability of each Gaussian curve reveals the distribution of fluorophore number per streptavidin molecule, with an average of 2.86, close to the given F/P ratio of 3 (Figure 3c).…”