Dissecting docking and tethering of secretory vesicles at the target membrane
2006; Springer Nature; Volume: 25; Issue: 16 Linguagem: Inglês
10.1038/sj.emboj.7601256
ISSN1460-2075
AutoresRuud F. Toonen, Olexiy Kochubey, Heidi de Wit, Attila Gulyás-Kovács, Bas Konijnenburg, Jakob B. Sørensen, Jürgen Klingauf, Matthijs Verhage,
Tópico(s)Calcium signaling and nucleotide metabolism
ResumoArticle10 August 2006free access Dissecting docking and tethering of secretory vesicles at the target membrane Ruud F Toonen Ruud F Toonen Department of Functional Genomics, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam (VUA) and VU Medical Center (VUmc), Amsterdam, The Netherlands Search for more papers by this author Olexiy Kochubey Olexiy Kochubey Department of Membrane Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, GermanyPresent address: Laboratory of Synaptic Mechanisms, Brain Mind Institute, EPFL, Station 15, 1015, Lausanne, Switzerland Search for more papers by this author Heidi de Wit Heidi de Wit Department of Functional Genomics, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam (VUA) and VU Medical Center (VUmc), Amsterdam, The Netherlands Search for more papers by this author Attila Gulyas-Kovacs Attila Gulyas-Kovacs Department of Membrane Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, GermanyPresent address: Laboratory of Cardiac/Membrane Physiology, Rockefeller University, 1230 York Avenue, NY 10021, USA Search for more papers by this author Bas Konijnenburg Bas Konijnenburg Department of Functional Genomics, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam (VUA) and VU Medical Center (VUmc), Amsterdam, The Netherlands Search for more papers by this author Jakob B Sørensen Corresponding Author Jakob B Sørensen Department of Membrane Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany Search for more papers by this author Jurgen Klingauf Corresponding Author Jurgen Klingauf Department of Membrane Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany Search for more papers by this author Matthijs Verhage Corresponding Author Matthijs Verhage Department of Functional Genomics, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam (VUA) and VU Medical Center (VUmc), Amsterdam, The Netherlands Search for more papers by this author Ruud F Toonen Ruud F Toonen Department of Functional Genomics, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam (VUA) and VU Medical Center (VUmc), Amsterdam, The Netherlands Search for more papers by this author Olexiy Kochubey Olexiy Kochubey Department of Membrane Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, GermanyPresent address: Laboratory of Synaptic Mechanisms, Brain Mind Institute, EPFL, Station 15, 1015, Lausanne, Switzerland Search for more papers by this author Heidi de Wit Heidi de Wit Department of Functional Genomics, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam (VUA) and VU Medical Center (VUmc), Amsterdam, The Netherlands Search for more papers by this author Attila Gulyas-Kovacs Attila Gulyas-Kovacs Department of Membrane Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, GermanyPresent address: Laboratory of Cardiac/Membrane Physiology, Rockefeller University, 1230 York Avenue, NY 10021, USA Search for more papers by this author Bas Konijnenburg Bas Konijnenburg Department of Functional Genomics, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam (VUA) and VU Medical Center (VUmc), Amsterdam, The Netherlands Search for more papers by this author Jakob B Sørensen Corresponding Author Jakob B Sørensen Department of Membrane Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany Search for more papers by this author Jurgen Klingauf Corresponding Author Jurgen Klingauf Department of Membrane Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany Search for more papers by this author Matthijs Verhage Corresponding Author Matthijs Verhage Department of Functional Genomics, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam (VUA) and VU Medical Center (VUmc), Amsterdam, The Netherlands Search for more papers by this author Author Information Ruud F Toonen1,‡, Olexiy Kochubey2,‡, Heidi de Wit1,‡, Attila Gulyas-Kovacs2,‡, Bas Konijnenburg1, Jakob B Sørensen 2, Jurgen Klingauf 2 and Matthijs Verhage 1 1Department of Functional Genomics, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam (VUA) and VU Medical Center (VUmc), Amsterdam, The Netherlands 2Department of Membrane Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany ‡These authors contributed equally to this work *Corresponding authors: Department of Membrane Biophysics, Max Planck Institute for Biophysical Chemistry, 37077 Göttingen, Germany. Tel.: +49 551 201 1297; Fax: +49 551 201 1688; E-mail: [email protected] or Tel.: +49 551 201 1629; Fax: +49 551 201 1688; E-mail: [email protected] of Functional Genomics, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit (VU) Amsterdam and VU Medical Center (VUmc), De Boelelaan 1087, 1081 HV Amsterdam, The Netherlands. Tel: +31 20 598 6936; Fax: +31 20 598 6926; E-mail: [email protected] The EMBO Journal (2006)25:3725-3737https://doi.org/10.1038/sj.emboj.7601256 Present address: Laboratory of Synaptic Mechanisms, Brain Mind Institute, EPFL, Station 15, 1015, Lausanne, Switzerland Present address: Laboratory of Cardiac/Membrane Physiology, Rockefeller University, 1230 York Avenue, NY 10021, USA PDFDownload PDF of article text and main figures. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Secretory vesicles dock at their target in preparation for fusion. Using single-vesicle total internal reflection fluorescence microscopy in chromaffin cells, we show that most approaching vesicles dock only transiently, but that some are captured by at least two different tethering modes, weak and strong. Both vesicle delivery and tethering depend on Munc18-1, a known docking factor. By decreasing the amount of cortical actin by Latrunculin A application, morphological docking can be restored artificially in docking-deficient munc18-1 null cells, but neither strong tethering nor fusion, demonstrating that morphological docking is not sufficient for secretion. Deletion of the t-SNARE and Munc18-1 binding partner syntaxin, but not the v-SNARE synaptobrevin/VAMP, also reduces strong tethering and fusion. We conclude that docking vesicles either undock immediately or are captured by minimal tethering machinery and converted in a munc18-1/syntaxin-dependent, strongly tethered, fusion-competent state. Introduction Neurons and neurosecretory cells employ conserved mechanisms for regulated secretion of neurotransmitter and hormones. Probably, the most intensively studied gene families involved in these processes are those that encode SNARE proteins (Sollner and Rothman, 1996). Zipping-up of four SNARE domains of the SNARE proteins is recognized as a central molecular mechanism to drive fusion of synaptic vesicles and dense core vesicles (Jahn et al, 2003). Thus, genetic deletion or enzymatic cleavage of SNARE genes/proteins invariably blocks fusion in many different systems (see for review, Rizo and Sudhof, 2002; Toonen and Verhage, 2003), and evidence is accumulating that SNAREs participate in several sequential processes in the exocytosis pathway, leading up to and including the formation of a fusion pore between the vesicle interior and the outside of the cell (Gil et al, 2002; Sørensen et al, 2003; Han et al, 2004; Borisovska et al, 2005). However, the assembly of SNARE complex is not likely to be the first event to occur when secretory vesicles reach their target. Genetic deletion experiments suggest that SNAREs are not necessary to morphologically dock different classes of secretory vesicles at their respective target membranes (Hunt et al, 1994; Broadie et al, 1995; O'Connor et al, 1997; Schoch et al, 2001; Washbourne et al, 2002; Sørensen et al, 2003; Borisovska et al, 2005). Hence, unknown processes distinct from and upstream of SNARE-complex assembly are expected to be involved in capturing arriving vesicles. One indication for the identity of such upstream machinery was obtained in studies of large dense core vesicles (LDCVs) in neuroendocrine cells. The Sec1/Munc18-like (SM) protein Munc18-1 binds to the t-SNARE syntaxin (Rizo and Sudhof, 2002), and munc18-1 null mutant mice display a complete block of neurotransmission (Verhage et al, 2000). This, together with the reported affinity of Munc18-1 for actin (Bhaskar et al, 2004), prompted us to test its potential role in vesicle docking. Deletion of munc18-1 expression produced a marked defect in LDCVs docking to the plasma membrane in adrenal chromaffin cells (Voets et al, 2001) and somatotrophs of the anterior pituitary (Korteweg et al, 2005), whereas deletion of the SNARE genes SNAP25 or synaptobrevin/VAMP in chromaffin cells did not (Sørensen et al, 2003; Borisovska et al, 2005). Unfortunately, a more systematic analysis of the protein cascade that orchestrates the reception of secretory vesicles at their target is hampered by the current poor definition of the docking process itself. Docking is typically assessed on the basis of electron micrographs; however, this method does not allow the study of vesicle dynamics in living cells, and thus precludes the identification of different docked states. More recently, total internal reflection fluorescence microscopy (TIRFM) has been exploited to study the dynamics of individual, fluorescent vesicles at the membrane in living cells (Lang et al, 1997; Steyer et al, 1997; Oheim and Stuhmer, 2000; Steyer and Almers, 2001), and it became clear that a complex pattern of vesicle trafficking exists in the submembrane region of secretory cells (Lang et al, 2000; Johns et al, 2001) and synapses (Zenisek et al, 2000). It remains unresolved how this complex pattern relates to the docked and fusion-competent vesicle pools previously characterized by other approaches and which molecular factors are involved. In order to address these questions, here we have combined TIRFM analysis of submembrane vesicles with molecular manipulations of known docking and fusion proteins, electrophysiological analysis of releasable vesicle pools and ultrastructural morphometry. Thus, we have a complementary set of assays to monitor events from the first arrival of secretory vesicles at the membrane to their final fusion. Given its clear docking phenotype, we used munc18-1 null mutant chromaffin cells as a starting point for molecular manipulations. Using this set of assays, we found that most approaching vesicles do not dock stably, but that two distinguishable tethering states exist and that only the most long-retaining (strongly tethered) state is a prerequisite for fusion. Furthermore, we show that Munc18-1 and the t-SNARE syntaxin are essential for this strongly tethered state. Results Docking and secretion defects in the absence of Munc18-1 are rescued by acute expression of the disrupted gene To be able to study vesicle docking with total internal reflection fluorescence (TIRF) imaging in living cells, we cultured chromaffin cells from munc18-1 null mutant adrenals in which we previously observed a docking defect (Voets et al, 2001). As expected, the docking and secretion defects were preserved in cultured cells, and both could be rescued by acute expression of the disrupted gene (Figure 1A–G). Rescue of the docking phenotype was already complete 4 h after infection. EGFP alone had no detectable effect on vesicle distribution, and the total number of vesicles was similar among all groups (Supplementary Figure S1). The capacitance and amperometric responses to flash uncaging of caged Ca2+ were also restored to control levels within 4 h after reintroduction of the munc18-1 gene (Figure 1E–G and Supplementary Figure S2). All phases of exocytosis (see Voets, 2000) were restored to a similar extent (Figure 1F) and the fusion time constants for different vesicle pools were indistinguishable from control cells (Figure 1G). Figure 1.Overexpression of Munc18-1 rescues secretion in munc18-1 null chromaffin cells. (A) Fluorescent image of null mutant cells incubated with SFV munc18-IRES-egfp. The two cells in the white box were retrieved on ultrathin sections in the electron microscope; bar =10 μm. (B) Electron micrographs of the same cells, one of which is infected to induce munc18-1 expression (bright cell in panel A) and shows an increase in docked vesicles. The neighboring uninfected null mutant cell (dark in panel A) shows severely impaired vesicle docking. (C) Magnification of the submembrane region (outlined in panel B); bar =200 nm. (D) Cumulative plots of vesicle distribution in null mutant, wild type cells and null cells after acute overexpression of munc18-1. Inset shows average number ±s.e.m. of morphologically docked vesicles for each experimental condition. The number of vesicles was quantified in the following number of cells (n) and animals (N): null+EGFP: n=19, N=4; wild type+EGFP: n=20, N=4; wild type+Munc18: n=20, N=4 (***P<0.001, Student's t-test with N=4). (E) Secretory responses in munc18-1 heterozygote cells (control, n=36 cells, N=8 animals), in munc18-1 null cells (null, n=21, N=4) and in null cells overexpressing munc18-1 (null+M18-1, n=21, N=5). Secretion was elicited by flash photolysis of caged-Ca2+ (at arrow), which resulted in similar intracellular [Ca2+] steps in all experimental groups (see Supplementary Figure S2). Secretion was assayed simultaneously with membrane capacitance measurements and amperometry, which measure the increase in plasma membrane area and the liberation of catecholamines, respectively, as a result of vesicle fusion. Averaged traces are shown; the individual amperometric spikes are therefore barely recognizable. The amperometric current was integrated over time to obtain the cumulative charge, which mirrors the capacitance increase except for an additional diffusional delay (right ordinate axis); (F) Amplitudes of the different kinetic components of the flash responses. Left: The capacitance increase occurring within the first 0.5 s after the flash and during the following 4.5 s. Right: Following kinetic analysis, the amplitudes of the fast burst component (representing the fusion of the readily releasable vesicle pool) and the slow burst component (representing the fusion of the slowly releasable vesicle pool) are shown. ***P<0.001 (Mann–Whitney). (G) Time constants for fusion of the fast and slow burst components of the flash responses. Download figure Download PowerPoint Vesicle docking and secretion varies with the amount of Munc18-1 expressed Given its confirmed role in docking, we asked if the extent of docking and secretion varies as a function of the cellular Munc18-1 level, exploiting the fact that munc18-1 heterozygous null mutant mice have a reduced munc18-1 expression (in adrenals exactly 50% reduction; Voets et al, 2001). Conversely, we used Semliki Forest viral overexpression of munc18-1-IRES-egfp in wild type cells. The extent of munc18-1 overexpression was 10- to 20-fold higher than endogenous expression, based on semiquantitative analysis of immunocytochemical stainings (data not shown). Reduced expression of Munc18-1 in chromaffin cells from heterozygous mice led to a proportional reduction in morphologically docked vesicles (Figure 2A–C). Overexpression of Munc18-1, on the other hand, produced a significant increase in the number of vesicles docked at the target membrane (Figure 2A–C). The total number of vesicles remained unaltered (Supplementary Figure S1). Hence, under- or overexpression resulted in parallel changes in the number of docked vesicles. Figure 2.The number of docked vesicles is influenced by Munc18-1 expression level. As the expression level of Munc18-1 rises, the number of morphologically docked vesicles at the plasma membrane increases. (A) Electron micrographs of the submembrane area of munc18-1 null mutants overexpressing egfp or munc18-1, munc18-1 heterozygotes, and wild type cells overexpressing egfp or munc18-1. Bars, 100 nm. (B) Average number ±s.e.m. of morphologically docked vesicles for each experimental condition (***P<0.001, Student's t-test with N=4). (C) Cumulative plots of vesicle distribution for each experimental condition (except null+Munc18-1, which is shown in Figure 1D, and has the same distribution as wild type+EGFP). The number of vesicles was quantified in the following number of cells (n) and animals (N): null+EGFP: n=19, N=4; heterozygotes: n=20, N=4; wild type+EGFP: n=20, N=4; wild type+Munc18: n=20, N=4. Neither over- nor underexpression of Munc18-1 affected the total number of secretory vesicles in chromaffin cells (Supplementary Figure S1). Download figure Download PowerPoint Although docking was reduced in the heterozygous chromaffin cells, the secretory responses to flash photolysis of caged-Ca2+ were close to control responses in amplitude (Figure 3A–C and Supplementary Figure S3). Kinetic analysis revealed that the sustained component was significantly decreased in the heterozygotes (Figure 3B), but this reduction was rather small. However, munc18-1 overexpression markedly increased secretion in capacitance measurements and amperometry (Figure 3D–F). Increases were observed in both burst and sustained phases of release (Figure 3E), suggesting that an early secretory step was potentiated. Thus, the number of morphologically docked and, to some extent, fusogenic vesicles varies with the amount of Munc18-1 expressed. This identifies Munc18-1 not only as an essential docking factor, but also as a rate-limiting, positive factor in the secretory cascade. Figure 3.Modulation of secretion by gene dose: exocytosis in munc18-1 heterozygote cells and in wild type cells overexpressing Munc18-1. (A) Secretory responses in munc18-1 heterozygote cells (hetero, n=60, N=5) and wild type cells (wild type, n=58, N=5). For explanation, see the legend to Figure 1E and F and Supplementary Figure S3. (B) Left: Amplitudes of the fast and the slow burst components. Right: Sustained rate of secretion, measured between 0.5 and 5 s after the flash stimulation. (**) Mann–Whitney test: P<0.01. (C) Time constants for fusion of the fast and slow burst components of the flash responses. (D) Secretory responses in non-infected wild type cells (n=50, N=7) and in wild type cells overexpressing Munc18-1 (wild type+Munc18-1, n=52, N=7). (E, F) Amplitudes and time constants of different kinetic components of the flash responses; as in panels C and D. ***P<0.001 (Mann–Whitney). Download figure Download PowerPoint Three docking states can be distinguished, two of which are Munc18-1 dependent To investigate docking in living cells, we used TIRF imaging of secretory vesicles labeled with neuropeptide Y fused to Venus (NPY-Venus; Nagai et al, 2002). Within the layer illuminated by the evanescent wave (d1/e=120±10 nm in our setup), many secretory vesicles were detectable in all genotypes (Figure 4A–C), but the total number was two-fold lower in the munc18-1 null mutant (0.13±0.01 versus 0.24±0.03 vesicles/μm2 in the wild type, P<0.005; Figure 4D). This reduction is in accordance with the morphological docking defect observed in the electron microscope (see Figure 1D, the shaded area indicates the 3d1/e TIRF illuminated volume). Acute expression of munc18-IRES-NPY-Venus in null cells completely restored the number of detected vesicles (0.22±0.03 vesicles/μm2; Figure 4C and D). Figure 4.Dynamics of NPY-Venus-labeled vesicles in the submembrane region. Appearance of footprints with NPY-Venus-labeled granules in wild type (A), null (B) and null mutant cells expressing munc18-1-IRES-NPYVenus (C). Scale bar is 5 μm. Density of granules per unit area was noticeably smaller in null mutant cells. (D) Quantification of the density of labeled vesicles at the footprint of chromaffin cells in different genotypes, estimated from the average projection images (A–C). The number of vesicles was significantly smaller for null mutant cells than the other genotypes. (E) Lifetime distribution of vesicles hitting the plasma membrane during 180 s (600 frames) observations at 3.3 Hz. Frequencies are normalized to membrane unit area of the cell's footprint and observation time and logarithmically binned. Inset: Fitting the normalized residency time histogram of munc18-1-overexpressing cells with models of two (dotted blue line) or three (solid red line) exponentially distributed lifetime states suggests at least three different residency states: visitors (lifetime 10 s). In both genotypes, most vesicles only visit the TIRF plane (visitors) but significantly less do so in the null mutant compared to wild type cells. The long-retained state has very low frequency, and only becomes apparent owing to its reduction in the null mutant cells (see also panels F and G). Total number of vesicles is n=2997 (N=35), 2398 (N=30) and 3536 (N=34) for wild type, null and null+Munc18-1 cells, respectively. (F) Average vesicle abundance at any given time during image acquisition shows the significant contribution of long-retained vesicles to a snapshot analysis of docked vesicles and supports the existence of three distinct docking states. The inset zooms in on the short residency times corresponding to the unretained visitors (<1 s). (G) Average vesicle abundance at any given time during image acquisition grouped according to their residency times at the membrane (unretained: 10 s, respectively). The majority of vesicles found on TIRF images belonged to the tethered states (residency times between 1 and 180 s). * and ** indicate statistically significant differences between null and wild type (or null+Munc18-1) at P 0.24). Download figure Download PowerPoint To analyze the dynamic behavior of individual vesicles, we acquired TIRF images with 0.3 s interval for 3 min, and measured the number of vesicles that appeared in the TIRF field and their residency times at the membrane (see Materials and methods). To show all events in one histogram, the residency times were logarithmically transformed and their distribution was displayed using logarithmically increasing bin sizes (Figure 4E). By logarithmic transformation, exponentially distributed residency or lifetimes result in a skewed distribution with a peak at the time constant of each individual lifetime state (Sigworth and Sine, 1987). Different states can be distinguished as distinct peaks in the distribution. The first state, with a lifetime shorter than 1 s most likely represents vesicles that move in and out of the TIRF plane unretained by tethering forces at the plasma membrane (visitors). The majority of arriving vesicles in all genotypes belonged to this category but the number of visitors in null mutant cells was significantly lower compared to wild type. A second state (between 1 and 10 s in Figure 4E) is characterized by a distinct, longer lifetime and therefore indicates a form of minimal retention of these vesicles at the target: short-retained, or weak tethering. A third, more long-retained state is suggested by the pronounced tail in the residency time distributions (>10 s in Figure 4E). Fitting of the normalized histograms with two or three exponentially distributed lifetime states indeed supports the existence of three states with average lifetimes of 0.13 (τ1), 1.49 (τ2) and 14.8 (τ3) s (Figure 4E, inset). Interestingly, the distribution in munc18-1 null mutant cells suggested that especially the visitors and the long-retained vesicles occurred less frequently than in control cells (cf. Figure 4F). To correlate the residence time distribution in Figure 4E with our (snapshot) electron microscopical analysis of fixed cells, we calculated the average abundance of every vesicle bin at any given time during the image recording (vesicle snapshot occurrence, see Materials and methods; Figure 4F). Based on the histogram and curve fit in Figure 4E, vesicles were grouped into three classes (visiting vesicles with residence times 10 s). In Figure 4G, the average abundance of these three groups at any time is plotted for the three genotypes. Whereas the visiting vesicles dominate the residence time analysis (Figure 4E), the long-retained tethered vesicles dominate in single snapshots (Figure 4F), as applies to electron micrographs. Changes in cellular Munc18-1 level changed the ratio between the three groups. The long-retained tethered state was reduced by 1/3 in the absence of Munc18-1 and rescued by acute munc18-1 expression. Despite the fact that relatively few vesicles are captured in this state, more than 75% of all vesicles seen at the membrane footprint in wild type cells belonged to this class, owing to their long lifetime (Figure 4G). Transient occurrences (unretained visitors, <1 s) were also significantly decreased in munc18-1 null mutant cells (45% compared to wild type). Hence, the number of vesicles arriving per unit of time was reduced (Figure 4E), suggesting a distinct aspect of munc18-1 function in the delivery of vesicles to the target. This phenotype was again rescued by acute expression of the disrupted gene (Figure 4G). Together, these data identify different docking states. Most vesicles move in and out of the TIRF plane apparently without being retained, but some vesicles are retained for shorter or longer times by local tethering forces at the target. Munc18-1 most strongly affects vesicle delivery rate and long-retained tethering. The munc18-1-dependent changes in morphological docking in electron micrographs (Figures 1 and 2) may be explained by the combination of these changes in delivery rate and tethering. Autocorrelation analysis of vesicle movement reports tethering forces The decrease in long-retained vesicles in the absence of Munc18-1 may be influenced by the reduced vesicle delivery rate. To find independent evidence for Munc18-1's role in long-retained tethering, we examined the jittering movement of long-retained vesicles at the target membrane. Owing to the exponential decay of the evanescent wave, relative changes in the position of fluorescent vesicles perpendicular to the target (i.e. Z-position) can be quantified with extraordinary precision by analyzing changes in fluorescence intensity (Figure 5A). It was previously shown by autocorrelation analysis of such jittering movement that vesicles near the target show a tendency to reverse the direction of movement within a characteristic time τ (Johns et al, 2001). This change in the direction of axial movement is represented by a negative component in averaged autocorrelation functions (ACFs) of fluctuations in relative Z-velocity (ΔZ−ACF, see Materials and methods) and discriminates this behavior from pure diffusion or uncorrelated noise sources. Tethering or restricting forces are expected to reverse vesicles that start to diffuse away from the target membrane and thus result in a negative component in ΔZ-ACF analysis. We indeed observed a negative component in ΔZ-ACF in the 0.2–1 s range (Figure 5B), confirming the previously reported tendency of vesicles near the target to reverse direction (Johns et al, 2001). Immobile controls (40-nm fluorescent beads and vesicles in fixed cells) did not show this negative component, which excludes system artifacts (Figure 5B). We defined a single parameter to quantify this negative persistence of autocorrelation (NPA) by summing the first two points of the ΔZ-ACF that allowed us to compare different populations of vesicles and cells with different genotypes. Both theoretically and practically (Qian et al, 1991), the ACF approaches zero for larger τ and therefore this specific time window is assigned to the NPA. The NPA for live cells is a factor 100 larger than for fixed cells and fluorescent beads (Figure 5C) and the NPA increases when vesicles exhibit behavior distinct from random movement (Johns et al, 2001, and our computer simulations, not shown). Figure 5.Autocorrelation analysis reports tethering forces that are lost in the absence of Munc18-1. (A) Example of vesicle trajectory perpendicular to the plasma membrane (relative Z-position; see Materials and methods) during 30 s image acquisition at 30 Hz. (B) Velocity ACF (ΔZ-ACF) of vesicle movement in wild type chromaffin cells compared to fixed cells and fluorescent beads. The negative points in the beginning of the ACF reflect changes in the direction of Z-movement. These changes are absent in fixed cells and fluorescent beads. (C) The NPA for fixed cells, beads and live cells transfected with NPY-Venus. The absolute value of negative amplitude rises when the restricted movement of an object can be reliably resolved from the uncorrelated fluorescence noise. The NPA was calculated for 113 vesicles in fixed cells, 127 beads and 244 vesicles in wild type live cells. (D) ΔZ-ACF of wild type and munc18-1 null mutant vesicles reveals an increased freedom in vesicle movement in the absence of Munc18-1, which results in a more than eight-fold reduction of the negative ACF component in these cells. (E) Munc18-1 introduction on the null background rescues the NPA to wild type levels. *** indicates statistic
Referência(s)