The reason this paper got my attention is the method:
Real time imaging of single Qdots
Between 12-21 days in vitro, healthy cultures that met our rigorous standards (3) were selected for experiments. High K+ Tyrode solution (90 mM K+) was prepared by equimolar replacement of NaCl in normal Tyrode. In the case of 50 mM Tris solution, 10 mM HEPES was omitted and the concentration of NaCl was reduced to 108 mM in order to maintain the same osmolarity as in normal Tyrode. During the experiment, Trisbuffered solution replaced the HEPES-buffered solution 1 min before imaging started. Loading of Qdots was carried out in static bath with Qdot-containing Tyrode (~800 μL). Then cells were thoroughly washed with Qdot-free Tyrode for at least 10 min. Switching of perfusion solution was carried out with a precision of ~2 s. All solutions contained 5 μM NBQX and 50 μM D-APV to prevent recurrent activity and synaptic plasticity. All experiments were performed at room temperature.
Image acquisition was conducted as previously described (3). The extensive depth of field of the optical system (0.7–1.0 μm) minimized any impact of possible variations in zdistance (4). In order to avoid cytotoxic effects of UV light, Qdots were excited at 470 nm (D470-40x, Chroma) and photoluminescent emission was collected at 605 nm (D605-20m, Chroma). In most experiments, subsequently loaded FM4-64 was excited at 490 nm (D490-20x, Chroma) and its emission was collected at 660 nm (D660-50m, Chroma). Experiments with single Qdot loading were generally carried out at a 3 Hz frame rate (exposure time = 100 ms per frame). High-frequency (30 Hz) Qdot imaging experiments were conducted with the same setup but with a different video capture board and acquisition program (Piper Control, Stanford Photonics). The specimen was illuminated continuously and the exposure time was 30 ms per frame. The field stimulation was either a single square pulse (duration, 0.05s) or 10-Hz, 5-s train. Every imaging trial was started 5s before the first (or the only) stimulation pulse and ended 15s after.
Data analysis
All frames acquired by MetaFluor or Piper Control were saved as TIFF files and analyzed off-line with MetaFluor or ImageJ. Unless stated otherwise, the regions of interest (ROIs) were circles with a diameter of 9 pixels (~1.3 μm), centered on FM4-64 positive puncta representing functional boutons, typically ~1 μm across. These ROIs were retrospectively projected onto Qdot images. The average intensities of Qdot photoluminescence in these ROIs were exported to Excel files. The starting time of each frame was registered by MetaFluor together with ROI intensity. Each field stimulation pulse was recorded with Clampex (Axon Instruments) and used in the analysis program described below. Individual fusion events in single Qdot experiments were detected by a program custom written in LabVIEW (National Instruments). For the analysis of 3-Hz imaging data, the program searched for upticks and downsteps independently. For (1) positive deflections (K&R), it detected an event whose high-pass-filtered trace crossed a threshold, ~2.5 times the standard deviation of pre-stimulus intensity (60-s pre-stimulation baseline); for (2) irreversible negative steps (FCF), it created a negative step function whose amplitude equaled the difference in photoluminescence intensity before and after 12 stimuli (i.e. 60-s pre-stimulation baseline vs. 60-s post-stimulation baseline). The program located an event by moving the template along a low-pass-filtered trace and looking for the best fit. For analysis of 3 Hz imaging, the onset of an uptick or a downstep was determined as the time point when the intensity reached 20% of its peak or final level, respectively. To avoid spurious events arising from background noise, negative deflections were analyzed only if their amplitude fell within the range of 20-100 a.u. 30 Hz imaging traces were analyzed in a similar manner. Positive deflections were defined as more than 2.5 times the standard deviation of pre-stimulus baseline and their onset was determined as the time point when the intensity reached the plateau amplitude. As in the analysis of 3-Hz imaging, negative deflections were identified by sliding a negative step function based on the difference between per- and post-stimulation baselines along the time axis. Traces whose amplitude fell within the range of 200-1300 a.u. were analyzed. Traces containing blinking events were only included in analyses for measuring blinking amplitude and frequency. Statistical analyses were carried out with Excel, SigmaPlot and StatView. All plots were generated by SigmaPlot. All error bars represent standard error of the mean (s.e.m.). For fair comparison of different regression fits with different numbers of free parameters, we compared fits with different numbers of free parameters by the use of Akaike’s information criterion (where AIC=n/log(SSE/n)+2(p+1), SSE is the sum of squared errors, n is the number of data points and p is the number of parameters estimated by least squares).
Single Qdot tracking
Imaging frames were reconstructed as imaging stacks by ImageJ. According to an established protocol (5), stacks of images were run through the custom made program, SINEMA (5). The detection parameters, set differently from the program’s default values, were 605 nm as emission wavelength, 1.3 as numerical aperture, 121 nm as pixel width, 1 as minimal interpolation distance, 3 as detection thresholds, 2.5 as initial diffusion coefficient, 0.95 as confidence level, 3 and 10 as minimal track length for MSD estimation (for 3-Hz and 30-Hz imaging rate respectively), no sliding window for MSD estimation, 3 as number of points used for MSD, 2 as temporal scope. The tracking results were exported to and analyzed in Matlab.
And their microscope settings were described in this paper (PMID: 12789339):
Fluorescence detection of single synaptic vesicles was performed with an inverted epifluorescence microscope (1.3 NA objective) and an intensified charge-coupled device camera operating in gated acquisition mode (XR/Mega-10, Stanford Photonics). Brief pulses of illumination (470/40 nm) were gated by an optical switch; fluorescence emission passed through a 515-nm long-pass filter. The exposure time per image (15 ms) helped maximize fluorescence signals while causing acceptably mild photobleaching (<10% over 121 images).
Here is the abstract:
Published Online February 12, 2009
Science DOI: 10.1126/science.1167373
Research Articles
Submitted on October 20, 2008
Accepted on January 27, 2009The Dynamic Control of Kiss-And-Run and Vesicular Reuse Probed with Single Nanoparticles
Qi Zhang 1, Yulong Li 1, Richard W. Tsien 1*1 Department of Molecular and Cellular Physiology, Stanford University, Stanford, CA 94305, USA.
* To whom correspondence should be addressed.
Richard W. Tsien , E-mail: rwtsien@stanford.eduVesicular secretion of neurotransmitter is essential for neuronal communication. Kiss-and-run is a mode of membrane fusion and retrieval without the full collapse of the vesicle into the plasma membrane and de novo regeneration. The significance of kiss-and-run during efficient neurotransmission has remained in doubt. We developed an approach for loading individual synaptic vesicles with single quantum dots. Their size and pH-dependent photoluminescence change allowed us to distinguish kiss-and-run from full-collapse fusion and to track single vesicles through multiple rounds of kiss-and-run and reuse, without perturbing vesicle cycling. Kiss-and-run dominated at the beginning of stimulus trains, reflecting the preference of vesicles with high release probability. Its incidence was increased by rapid firing, a response appropriate to shape the kinetics of neurotransmission during a wide range of firing patterns.
Fig. 1. Single Qdots loaded into synaptic boutons exhibit distinct patterns of photoluminescence change. (A) Neurons stimulated (10 Hz, 1 s) with 400 nM Qdots present, then thoroughly washed. The distribution of photoluminescent intensity was measured at FM4-64-defined ROIs. Best fit obtained with three evenly spaced Gaussians (0, 1 and 2), 63.9 a.u. apart. Spacing agrees with amplitude of blinking events (grey bars; mean, 61.3±4.5 a.u)(p > 0.25, t-test). Inset, circles mark functional boutons identified by FM4-64 staining, with (red) or without (white) single Qdot-loading. Scale bar = 3 μm. (B) pH-dependent Qdot photoluminescence. Cartoons: hypothetical Qdot signals arising from pH-dependence. (C) Photoluminescence traces recorded during 0.1-Hz, 2-min field stimulation (dashed lines). (D) Upon stimulation, changes in Qdot signal (ΔF) could be classified as noise (gray bars, centered at 0 a.u.) or a clear positive deflection (red bars, centered at ~9 a.u., >2.5 s.d. of noise), ~15% of size of subsequent negative deflections (blue bars, centered at ~ –63 a.u.).
Fig. 2. Upward transients in Qdot signal report pH changes within the vesicle lumen. Cartoons: hypothesized effect of acute or chronic block of the vesicular H+-ATPase with bafilomycin A1. Without Baf (normal), Qdot photoluminescence is diminished (maroon) by acidic luminal pH (gray). Deacidification upon vesicle fusion removes this quenching and Qdot brightens (red). Acute application of Baf (acutely blocked) prevents reacidification after vesicle retrieval; chronic Baf (chronically blocked) removes all pH gradients. Experimental traces illustrate typical photoluminescence patterns under three conditions. Patterns classified as K&R, FCF, or K&R+FCF (labeled rows) based on analysis of collected data (fig. S4).
Fig. 3. Prevalence of K&R changes over the course of stimulation as RRP vesicles are depleted. (A) Raster representation of traces (n = 302) from single Qdot loaded vesicles that responded to 0.1-Hz 2-min field stimulation. For each stimulus and subsequent interval, Qdot signals registered as non-response (gray), K&R (red), non-response following K&R (maroon), FCF (blue), or Qdot no longer present in ROI (black). Pooled traces from N = 8 coverslips, 3 separate cultures. (B) Traces corresponding to the first 12 rasters in (A). Photoluminescence changes color-coded for each stimulus and ensuing interval as in (A). (C) Numbers of K&R (red square) and FCF events (blue triangle), plotted for every stimulus. (D) K&R ratio for every stimulus (N = 8). Vertical bars, s.e.m. (E) Numbers of K&R (red squares) and FCF events (blue triangles), plotted for pre-stimulation hypertonic challenge (suc) and for each field stimulus. (F) Corresponding K&R ratio (filled red squares), compared with control [faded red squares, copied from (D)] (**, p < 0.01, χ2-test).
Fig. 4. Up-modulation of K&R prevalence with intense stimulation. (A) Sample traces from Qdot-loaded vesicles. (B) Categorization of vesicles with different fusion behaviors. (C) The K&R ratio during 10-Hz 2-min stimulation (analyzed with 5 s time bins to improve S/N) was significantly higher than that during 0.1-Hz stimulation (faded symbols, data from Fig. 3D). (D) Latency of first fusion in the different categories [same color coding as (B)]. Each plot normalized by the number of vesicles in that category. The higher its Pr/v, the more K&R events a vesicle could support (Pr/v = 0.051, 0.023, 0.010 and 0.001 for 3K+F, 2K+F, K+F and FCF only, respectively). (E) the interval between 2 consecutive K&R events (K-K, red) was significantly shorter than that between K&R and a subsequent FCF of the same vesicle (K-F, blue) (p < 0.01, K-S test).
Fig. 5. High-speed imaging of Qdots reveals adjustable fusion pore open time but constant vesicle reacidification rate with different levels of activity. (A) Insets, samples taken in normal Tyrode with single shocks, inter-stimulus interval >20 s. Two types of fits were overlaid: a single exponential decay (gray), and a plateau followed by an exponential (black), the latter fitting significantly better even after statistical penalization for the extra parameter (AIC score, –60.5; p < 0.001). Comparison of pooled data (black symbols, n = 43), and averages of the two kinds of fits (gray and black). (B) Samples in 50 mM Tris (green) and in 10 mM HEPES (black). (C) Corresponding pooled data in Tris (n = 37) and in HEPES [same as (A)]. (D) Samples (normal Tyrode) with 10-Hz (pink) and single-pulse stimulation (black). Smooth lines, corresponding fits as above. (E) Pooled data taken with 10 Hz (n = 46) and single pulse stimulation [same as (A)]. (F) Cumulative distributions of fit parameters. Plateau amplitude:distributions were not different (all p > 0.1, K-S test); plateau duration: only distribution for 10-Hz stimulation was longer (p < 0.01, K-S test); Decay τ: only distribution for 50 mM Tris was slower (p < 0.01, K-S test).
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