We set out to analyse human Dystrophin protein dynamics in vivo in the physiological environment of the muscle fibres of zebrafish embryos (Figure 1). We engineered expression constructs based on the full-length 427 kd human cDNA sequence (huDys; Figure 1A; ‘Materials and methods’). Expression of huDys or GFP control in zebrafish embryos was achieved through the injection of the DNA constructs into newly fertilized embryos at the early 1 cell stage, aiming to obtain mosaic expression to facilitate single cell analysis (Figure 1B,C). From 24 hpf onwards, huDys (Figure 1C, green) accumulated progressively at both ends of transgenic fibres (hereafter referred to as ‘tips’), as observed for endogenous zebrafish Dystrophin (Figure 1C, red). GFP control showed no tip accumulation (Figure 1D). In addition, huDys was often detected accumulating at putative neuromuscular junctions (NMJ), like endogenous Dystrophin (arrows in Figure 1E,F). We conclude that human Dystrophin localises in zebrafish skeletal muscle like zebrafish Dystrophin, making it likely, in a first approach, that the zebrafish embryo could be a suitable host to study human Dystrophin in vivo.

Figure 1

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To allow the in vivo study of huDys dynamics, the expression construct was modified to produce huDys tagged with GFP at its C-terminus (huDysGFP; Figure 1A; ‘Materials and methods’). This produces a bright fluorescent signal easily detectable at fibre tips (Figure 1G, arrows). Occasionally, some cells showed accumulations at membrane protrusions (Figure 1G, yellow arrowheads) and NMJs (Figure 1G, red arrowhead). The latter was confirmed by double staining with α-bungarotoxin (Figure 1H, inset). Compared to GFP alone, huDysGFP was generally less bright (Figure 2A) but was, nevertheless, more readily detected in muscle than non-muscle tissue (Figure 2B), suggesting that binding and stabilization at the membrane differ between tissues.

Figure 2

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To determine whether human Dystrophin mRNA becomes localised in zebrafish muscle like the endogenous transcripts, in situ mRNA hybridization with a human Dystrophin-specific probe was performed on injected embryos. In most cases, localisation of human Dystrophin mRNA was observed at fibre tips (Figure 1I,J). Thus, GFP-tagged Dystrophin localises similarly to its untagged counterpart, and to the endogenous Dystrophin mRNA and protein, and it is suitable for in vivo imaging.

Both endogenous Dystrophin and huDysGFP accumulate at the fibre tips, yet the endogenous form is not readily detected in cytoplasm in immunofluorescence assays, that is, it is not clear that the fluorescence detected is higher than background (Figure 1F), in contrast most fibres expressing huDysGFP show weak but detectable fluorescence in the cytoplasm (Figure 1G,H). We investigated this difference.

As intensity around 3 units above the background is easily detected under our imaging conditions (‘Materials and methods’), we can distinguish huDysGFP in a cytoplasmic voxel (a three dimensional pixel of 0.024 µm³) down to a number per voxel around 60 times lower than in the brightest fibre tip voxel (avoiding saturation of the detector by setting it to under 255 on 8-bit grayscale). As less than 1% of the entire cell volume is in the tip region, it is possible that even in cells with cytoplasmic huDysGFP below detectable levels there could be as much huDysGFP in the cytoplasm as in the tip region. This could equally be the case for endogenous Dystrophin. Therefore, the observed difference may be partially due to lower sensitivity of the antibody detection of cytoplasmic endogenous Dystrophin compared to the higher sensitivity of GFP detection. However, higher levels of cytoplasmic accumulation are likely an artefact of the overexpression of exogenous Dystrophin. Therefore, to confidently analyse Dystrophin binding dynamics, the presence of this cytoplasmic pool has to be taken into account and a deeper characterisation is required.

We analysed in more detail how each pool, tips, and cytoplasm, distribute. As predicted, in the majority of the muscle fibres, most huDysGFP is in the cytoplasm, with only a minority at the tips (Figure 3A), even though the higher concentration at the tips might have suggested otherwise (Figure 1G,H). Even in cells with cytoplasmic levels close to the detection limit, there is at least as much huDysGFP dispersed in the whole cytoplasm as that concentrated at the tips (Figure 3A). Across a population of fibres, more huDysGFP fluorescence was detected in the cytoplasm of fibres with higher total huDysGFP levels (blue triangles in Figure 3A). In contrast, the fluorescence at the tips does not increase with the total fluorescence of the fibre (green circles in Figure 3A), indicating that tip binding is limited by the presence of a limited number of binding sites that easily saturate. Thus, the accumulation of huDysGFP in the fibre cytoplasm does not appear to affect the binding at the tips. Also, fibre tips generally had greater fluorescence intensity than fibre cytoplasm (Figure 3B,C). High intensities at the tips can be achieved even with low cytoplasmic huDysGFP concentrations (Figure 3B). Moreover, at low overall fibre intensities, there is clear preference for accumulation at the tips (Figure 3C). All these data indicate that human Dystrophin is preferentially bound at the zebrafish fibre tips regardless of the amount of cytoplasmic Dystrophin.

Figure 3

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To study Dystrophin dynamics in our system, we still have to take into account the presence of a cytoplasmic pool. Dystrophin is a high molecular mass protein with multiple actin binding sites. We asked whether huDysGFP can diffuse freely in muscle fibre cytoplasm or whether it may be bound to cytoplasmic structures such as actin fibres.

We developed a modified FRAP approach to analyse protein dynamics in vivo. Even in the best imaging conditions, one faces the challenge of low signal-to-noise ratio that worsens as tissue thickness increases and protein abundance decreases. Although we are able to detect cytoplasmic huDysGFP, the signal is weak and the signal-to-noise ratio in single pixels or even small volumes is low (Figure 4A). To address these issues, we increase the signal by increasing laser power and studying large areas (‘Materials and methods’). Under these conditions, we acquire a consistent signal both for GFP and huDysGFP. However, using a high laser power to image over large areas results in significant photobleaching during imaging, and, even at 100% laser power, bleaching is so slow that significant diffusion occurs during bleaching (Weiss, 2004). We compensate for both using a mathematical model applied to the FRAP experimental data (‘Materials and methods’). This was integrated in a user-friendly application written to allow easy data analysis of multiple experiments (see ‘Materials and methods’).

Figure 4

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To validate our experimental conditions and FRAP analysis method in the muscle cells of zebrafish embryos, we first analysed GFP diffusion within the cytoplasm. We studied diffusion along the long axis of the muscle cell (Figure 4B). The selected fibre is oriented such that the image X-axis aligns to the fibre long axis (i.e., roughly anterior-posterior in the animal) and the Y-axis is dorso-ventral (Figure 4C–F). In each cell, one or two large rectangles of different sizes (narrow and wide) were bleached, avoiding nuclei (Figure 4B). The bleached rectangles are shorter along the X-axis than in Y and cross the entire cell transversely. This makes recovery almost entirely due to mobility along the X-axis, simplifying modelling and fitting. We analyse the profile along the X-axis taken immediately after bleaching GFP-expressing fibres (Figure 5A). This profile is not a top-hat but a Gaussian, much wider than the region actually bleached, consistent with diffusion during the bleaching phase. This diffusion is taken into account in the modelling as neglecting it would lead to significant error (Castle et al., 2011; González-Pérez et al., 2011; Müller et al., 2012) (‘Materials and methods’).

Figure 5

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We fit the recovery for each individual case to obtain the diffusion constant (D) and a bleaching-due-to-imaging parameter (β) (Figure 5B). We tested modelling of the recovery at short and long times post-bleaching. When analysing long (≥10 s) timescales, it is essential to take β into account, while for short times bleaching due to imaging is insignificant (Figure 5B, Table 1). The Gaussian profile and the ability to fit a simple diffusion model to the recovery are strong evidence for GFP diffusion. D_GFP best-fit values (fitted to data over ∼40 s) averaged 13.2 μm² s⁻¹, ranging from 8.6 to 20.8 μm² s⁻¹ (Table 1). This matches the range 7.6–15.8 μm² s⁻¹ previously reported for muscle cells (Arrio-Dupont et al., 2000; Kinsey et al., 2011), which indicates that our approach for in vivo FRAP analysis is able to achieve similar results to those previously reported for isolated cells in culture.

We used the FRAP method described above to analyse cytoplasmic huDysGFP dynamics. The Dystrophin profile immediately after bleaching, similar to that of GFP, is not a top-hat but a Gaussian, wider than the region actually bleached, and consistent with diffusion during the bleaching phase (Figure 5C). However, the Gaussian's amplitude is narrower and the depth greater for huDysGFP than GFP, consistent with slower diffusion (compare Figure 5A,C). Indeed, D_huDysGFP best-fit values (fitted to data over ∼40 s) ranged from 1.4 to 10.1 μm² s⁻¹, with a mean of 4.4 μm² s⁻¹ (Figure 5D; Table 1). Again, the Gaussian profile and our ability to fit a simple diffusion model to the recovery are strong evidence for huDysGFP diffusion, and rule out large scale (above μm) directed motion along the long axis of the cell, or significant binding of huDysGFP to immobile structures.

huDysGFP has significantly lower D than GFP, reflecting the different protein sizes of 454 kD and 27 kD, respectively (Figure 5E, p < 0.0001). By comparing narrow and wide bleaches in the same cell across our population of muscle fibres, we found that D_huDysGFP appears to vary between cells, that is, there is real variability in huDysGFP cytoplasmic dynamics from one cell to another. The difference between D_huDysGFP values for a pair of experiments in the same cell is significantly smaller than between values in different cells (Figure 5E,F; Table 1). Pairs of D values obtained from the same cell are well correlated (R_huDysGFP = 0.9813; Figure 5F). This indicates that Dystrophin's diffusion in the cytoplasm shows important variations from cell to cell but that it is consistent within one cell. Further, this finding highlights the limitations of reducing noise by ‘pooling’ FRAP results from more than one cell. Therefore, each FRAP curve was analysed independently throughout this study and pooling was deliberately avoided. The original data and relevant analysis files for each case are available online (Bajanca et al., 2015) to complement representative examples shown in figures and main data summarised in tables. We conclude that, although there is fibre-specific variation of D, there is no evidence that cytoplasmic Dystrophin either binds cytoskeletal elements or is actively transported towards fibre tips.

The fibre tip region presumably contains huDysGFP bound to the Dystroglycan complex at the membrane (Guyon et al., 2003; Böhm et al., 2008) and a portion diffusing in the adjacent cytoplasm. FRAP can test whether huDysGFP is able to bind stably at the tips and reveal binding dynamics, but this is a challenging task. Diffusion of cytoplasmic protein into the bleached area, combined with bleaching-due-to-imaging, masks the real binding dynamics. We tested diffusion-plus-binding models to analyse the tip FRAP curves but these require too many variables to be reliably fitted, reflecting the complexity of the binding dynamics, as will be shown. The relatively featureless, and noisy, recovery curves of in vivo FRAP within a complex tissue cannot adequately constrain this number of variables (Sadegh Zadeh et al., 2006). Instead, to understand human Dystrophin dynamics at the tip, we use direct semi-quantitative analysis of bleaching and recovery. A FRAP protocol that bleached only part of the tip allowed comparison of bleached and unbleached regions of the tip (Figure 6A). We combined this with analysis of the cytoplasm intensity near the tip in each cell to measure how much recovery to expect due to diffusion. In addition, recovery is followed at an initial fast acquisition rate to detect fast recovery, and then at a slower pace over longer time periods with reduced bleaching-due-to-imaging (Figure 6A).

Figure 6

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On most tips, we identified three signatures of a population of Dystrophin that is bound at the tip and immobile (not turning over) on the timescale of our experiment. First, there is only partial recovery in the bleached region of the tip regardless of the huDysGFP expression levels (Figure 6B–F). Second, the normalized intensity difference between the unbleached and bleached regions in most tips (black crosses in Figure 6C–E) reaches a plateau above zero (Table 2). At the end of the experiment, both halves of the tip have received the same amount of light (and thus bleaching) for ∼250 s after the intentional bleaching phase, so the difference observed is created by the huDysGFP bleached earlier that did not turn over. Third, in the unbleached half of the tip, which receives the same bleaching-due-to-imaging as the cytoplasm, both the normalized and the absolute drops in intensity from start to end of the experiment are much larger than in the cytoplasm (compare drops in the tips with those in the cytoplasms in Figure 6F). Thus, our FRAP data consistently confirm that a population of huDysGFP is effectively bound and immobile at zebrafish muscle fibre tips.

We analysed the dynamics of exchange of cytoplasmic freely diffusing huDysGFP with bound huDysGFP. Surprisingly, the FRAP curves revealed complex binding dynamics of Dystrophin at the tips that vary between fibres. We analysed the recovery pattern in the bleached region when switching to a slow acquisition regimen (transition from step 3 to 4 in Figure 6A). Despite the very slow turnover that characterizes the immobile-bound pool at the tips, for many fibres there is an almost immediate partial recovery (see Figure 6C–E). A shift of the dynamic equilibrium between dark-state and excitable GFP could result in apparent recovery following a switch to slow acquisition speed (Mueller et al., 2012). However, we verified that the extent to which this phenomenon occurs in huDysGFP could only justify a very small fraction of recovery (<1%, Figure 7A). We next evaluated the contribution of free diffusion of cytoplasmic huDysGFP into the bleached region, occurring as demonstrated with a D around 4 μm² s⁻¹. As the bleached region contains bound and unbound huDysGFP and both are subjected to bleaching, it is not straightforward to analyse the recovery against a control cytoplasmic region, which is not subjected to intentional bleaching. Therefore, we compared unbleached tip and cytoplasm traces, which were submitted to comparable experimental conditions, without intentional bleaching but with strong bleaching-due-to-imaging during the fast acquisition phase (Figure 6F). On switching to slow acquisition, any recovery on the unbleached tip would be expected to parallel the recovery on the cytoplasm. Nevertheless, the immediate recovery is in most cases larger than that expected from diffusion of cytoplasmic huDysGFP despite a steady state is reached soon after, characteristic of the large immobile pool (Figure 6F, compare open or hatched squares [unbleached tip] with the respective open or hatched triangles [cytoplasm]). In most cases, at least 50% of the total recovery of unnormalised unbleached minus cytoplasm curves occur within 10 s (Table 2). This indicates that there is an unaccounted third pool of huDysGFP, in addition to the immobile-bound pool and the cytoplasmic-free diffusible pool: a rapidly turning-over dynamic bound huDysGFP pool.

Figure 7

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Recovery that is presumably due to the bound mobile pool is seen in fibres with no detectable or very low levels of cytoplasmic unbound huDysGFP (Table 2). However, the extent of the recovery is still dependent on the amount of cytoplasmic huDysGFP in a fibre (Figure 6B,F). Note that in the scatter plot of fractional recovery against cytoplasmic huDysGFP intensity, fibre tips with negligible cytoplasmic huDysGFP show very low recovery (Figure 6B). This suggests that cytoplasmic protein is required for the dynamic recovery. Interestingly, tips with high cytoplasmic huDysGFP intensity near the tip do not necessarily recover more (compare Figure 6C,E,F) indicating real tip-to-tip variation in the dynamic bound pool. The two tips of the same fibre behave similarly in some but not all cases (Table 2).

Most of the recovery that is detected occurs within a few seconds in most cases (Table 2). Given that D_huDysGFP is a few μm² s⁻¹, diffusion times across the tip region will be of order a second. Thus, recovery of the dynamic bound pool is fast enough that it may be limited by diffusion. If there is a characteristic binding lifetime, it is at most a few seconds. In summary, our data indicate that most fibres have two pools of huDysGFP bound at their tips, a tightly bound pool stable for at least minutes and another with a sub-second to a few seconds turnover time.

To confirm that the mobility of bound Dystrophin can only be due to exchange with the free-diffusing pool, we tested for lateral mobility of bound huDysGFP, that is, we searched for evidence that huDysGFP can move along the membrane without unbinding and becoming part of the cytoplasmic pool. We examined intensity profiles along the X_T axis, parallel to the tip membrane (Figure 7B and Figure 4D). After deliberately bleaching part of the tip, we looked for a gradient in fluorescence recovery along X_T that could arise from mobility of bound Dystrophin. If the bound Dystrophin is mobile at the tip in the plane of the membrane, bleached bound huDysGFP would leave the deliberately bleached half of the tip and be replaced by fluorescent huDysGFP from the unbleached half. This would help drive fluorescence recovery and would be especially pronounced at the boundary between the bleached and unbleached halves of the tip, generating a gradient of fluorescence along the X_T axis. We see no evidence of such gradients (Figure 7B). In particular, in the middle panel of Figure 7B, although there is substantial recovery (compare the turquoise crosses with the immediately post-bleach orange triangles), there is no overall tendency in the intensity in the unbleached part of the tip to decrease from right to left as the bleached tip area is approached. The same applies to cases of little recovery (Figure 7C), where only substantial bleaching-due-to-imaging is observed on the unbleached tip half. The lack of evidence of lateral mobility of bound huDysGFP argues in favour of the existence of a bound-mobile pool with a fast turnover rate responsible for the fast fluorescence recovery observed in most fibres.

The experiments above were performed in wild-type zebrafish embryos. We asked whether the mobile-bound Dystrophin pool observed may result from competition of the exogenous human Dystrophin with endogenous zebrafish Dystrophin. To address this question, huDysGFP was expressed in Dystrophin-null zebrafish embryos (dmd^{ta222a/ta222a}).

We first evaluated the ability of human Dystrophin to rescue the zebrafish dystrophic fibres. Typically, in the absence of Dystrophin, the zebrafish muscle fibres detach upon contraction. At 3 days post fertilisation, nearly all dmd^{ta222a/ta222a} embryos show signs of dystrophy (Figure 8A). To quantify rescue efficiency, we first evaluated the percentage of cells that detach by mosaically expressing GFP in dmd^{ta222a/ta222a} embryos. Injecting a GFP control plasmid did not affect muscle fibres in siblings (N = 39), but about 23% of the GFP positive fibres in dmd^{ta222a/ta222a} embryos detached (Figure 8B). In marked contrast, cells expressing huDysGFP looked healthy and no detachment was found, suggesting full rescue of the dystrophic phenotype in dmd^{ta222a/ta222a} muscle fibres (Figure 8B; p = 0.000126 in Chi-square test for significance between GFP and huDysGFP).

Figure 8

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Next, huDysGFP intensity in the whole fibre and locally at the fibre tips was measured in wild-type embryos, where it coexists with the endogenous Dystrophin and in dmd^{ta222a/ta222a} dystrophic embryos (Figure 8C). In the absence of competition with the endogenous protein, huDysGFP appears to occupy more of the available binding sites, showing a 2.5-fold increase in the intensity ratio tips:cytoplasm compared to that found in wild-type background. This indicates that fibres expressing the same intensity in the cytoplasm can accumulate more at the fibre tips in the mutant background, consistent with the view that huDysGFP overexpression in the wild-type background does not displace all endogenous zebrafish Dystrophin.

Finally, tip FRAP curves of huDysGFP in dmd^{ta222a/ta222a} and siblings were analysed. Regardless of the genotype, most tips show the three typical signatures of an immobile-bound population described above: only partial recovery in the tip bleached region independently of the cytoplasmic intensity (Figure 8D,E; Table 3), the normalized intensity difference between the unbleached and bleached regions in most tips reaches a plateau above zero (Figure 8F; Table 3), and unbleached tip half intensity shows higher drop than the cytoplasm in the fast acquisition phase (see original curves in Bajanca et al., 2015). Also regardless of the genotype, the tip intensity registers a rapid recovery that is uncharacteristic of an immobile fraction while higher than the estimated contribution of the cytoplasmic pool. Evidence is clear when comparing events on switching between fast and slow acquisition in the unbleached tip half and cytoplasm unnormalised intensity curves. At least 50% of the total recovery occurs within 10 s in most fibre tips, too fast for the immobile-bound pool (Figure 8G; Table 3). Overall, our analysis found no significant differences between huDysGFP binding dynamics in wild-type, dmd^{ta222a/ta222a} or their siblings. These results suggest that the presence of two bound populations of huDysGFP with different turnover times is not due to competition with endogenous zebrafish Dystrophin.

We asked whether the labile membrane-bound pool may be a consequence of weaker binding between the human Dystrophin protein and the zebrafish endogenous protein complexes. To address this question, we analysed the dynamics of overexpressed zebrafish Dystrophin: GFP-tagged zebrafish Dystrophin (zfDysGFP). Similar to huDysGFP, the overexpression of zfDysGFP results in mosaic expression and variable levels of accumulation both at the muscle fibre tips and cytoplasm (Figure 9A; Table 4). The cytoplasmic zfDysGFP diffusion dynamics was analysed by FRAP. D_zfDysGFP best-fit values (fitted to data over ∼40 s) ranged from 0.6 to 6.7 μm² s⁻¹, with a mean of 2.9 μm² s⁻¹ (Figure 9B). zfDysGFP has statistically significantly lower D than GFP (p < 0.001) but shows no difference with huDysGFP (Figure 9B).

Figure 9

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Next, we analysed zfDysGFP dynamics at the fibre tips, in a wild-type context, where it competes for binding with endogenous Dystrophin, or in dmd^{ta222a/ta222a} mutants (Figure 9A,C). Exogenous zfDysGFP is able to rescue the dystrophic phenotype in dmd^{ta222a/ta222a} mutants (32/32, p = 0.003; Figure 9C). Like huDysGFP, most zfDysGFP tips show the typical signatures of an immobile-bound population regardless of the genotype (Figure 9D–F; Table 4). There are no statistically significant differences between the fractional recoveries of Dystrophin of the different species and in the different genetic backgrounds (Figure 9E). However, the final unbleached minus bleached intensity of huDysGFP is statistically significantly lower than zfDysGFP (Figure 9F). Using a two-way ANOVA to test the effect of genotypic background (wild-type or dmd^{ta222a/ta222a}) and Dystrophin origin (human or zebrafish) on the immobile fraction, we observed a significant effect of Dystrophin origin (human vs zebrafish) [F(1,87) = 11.21, p = 0.0012] but not of the host genotype [F(1,87) = 0.02326, p = 0.8791], and there was no significant interaction between origin and genotype [F(1,87) = 1.367, p = 0.2455]. While a final unbleached minus bleached intensity above zero indicates the existence of an immobile-bound fraction, its value is not a direct measurement of the amount of immobile-bound Dystrophin. However, we cannot exclude the possibility that huDysGFP forms less, or less stable, immobile-bound links than zfDysGFP, in the zebrafish environment. The background genotype appears not to influence this trait, suggesting that if there is a difference in the immobile fraction that is independent from competition with endogenous Dystrophin.

Like huDysGFP, most zfDysGFP-expressing fibres show a fast recovery phase that is higher than the estimated contribution of the cytoplasmic pool. Typically, at least 50% of the total recovery of unbleached tip half minus cytoplasm intensity curves occurs within 10 s in the majority of the cases, regardless of species and genotype (Figure 9G; Table 4). This recovery is very fast and the characteristic immobile pool plateau is soon reached, suggesting the existence of an additional bound pool of zfDysGFP with rapid turnover. These results show that, like huDysGFP, zfDysGFP can be found in three populations, one diffusible and two bound with different binding lifetimes. Therefore, regardless of any differences between huDysGFP and zfDysGFP, our results confirm that the mobile-bound pool previously found for the human Dystrophin is not caused by weaker interactions with a different species environment.

Analysis of FRAP curves of both huDysGFP and zfDysGFP indicated that when a low level of diffusible Dystrophin is detected in cytoplasm, there can be a significant amount of bound-mobile pool. However, there is the possibility that the labile-bound pool is caused by an excess of cytoplasmic Dystrophin resulting from overexpression. We questioned whether a mobile-bound pool can also be found in endogenous zebrafish Dystrophin, where a cytoplasmic pool of the protein is not known. We have analysed Gt(dmd-Citrine)^ct90a zebrafish embryos, in which Citrine was inserted by gene-trap into the endogenous Dystrophin locus, creating fluorescently tagged zfDys (Trinh et al., 2011; Ruf-Zamojski et al., 2015).

We first searched for signs of cytoplasmic Dystrophin. As every muscle fibre expresses Citrine-tagged Dystrophin (zfDysCitrine; Figure 10A), and different tissues may have different background fluorescence, it is not easy to evaluate with confidence whether there are low levels of cytoplasmic zfDysCitrine above the background. We hypothesized that if there is zfDysCitrine in the cytoplasm, we should register a recovery after photobleaching. Control siblings lacking zfDysCitrine show a flat and noisy FRAP curve that reflects the background fluorescence (Figure 10B, plot a). In contrast, the very low zfDysCitrine intensity detected in the cytoplasm could be bleached to even lower levels, and a recovery curve is registered, indicating the presence of diffusible zfDysCitrine in the cytoplasm (Figure 10B, plot b). The switch from a dark state of Citrine was evaluated and contributes little to the recovery (Figure 10B, plot c). Another signature of the presence of diffusible zfDysCitrine was the inverted bell-shaped, instead of top-hat, Gaussian curve that results from diffusion during intentional bleaching (Figure 10C). Finally, zfDysCitrine recovery curves can be fit using a diffusion model (Figure 10D). D_zfDysCitrine best-fit values ranged from 0.9 to 4.3 μm² s⁻¹ and mean 2.2 μm² s⁻¹ (Figure 10E). There is no significant statistical difference between D_zfDysCitrine and D_zfDysGFP.

Figure 10

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To be able to analyse single fibres, some embryos were subjected to heat shock, which causes mosaic disruption of the somites (Ruf-Zamojski et al., 2015). Embryos not subjected to heat shock, at different developmental stages (30 hpf, 40 hpf and 48 hpf) were also analysed. However, no trend was obvious when analysing embryos of different developmental stages (Figure 10F; Table 5). Most tips showed the typical signatures of an immobile-bound pool, as expected, and no statistically significant differences were found between zfDysGFP and zfDysCitrine (Figure 10F–H; Table 5). There is fractional recovery in most bleached tips that tends to be low (Figure 10F, Table 5), which in accordance with the results obtained for huDysGFP and zfDysGFP cases when the cytoplasm intensity is just above detectable (Figures 6B, 8D, 9D; Tables 2–4). Therefore, we found no indications that endogenous zfDysCitrine behave differently from exogenous zfDysGFP regarding their immobile pool signatures.

Despite the low cytoplasmic intensity, many zfDysCitrine tips still show a very fast recovery. At least 50% of the total recovery of the unbleached tip half minus the cytoplasm happens in almost half of the cases within 10 s, and still very fast at less than 20 s in the majority of the remaining cases (Figure 10I; Table 5). This suggests the presence of a mobile-bound pool, regardless of the statistically significant difference in the time it takes for zfDysCitrine and zfDysGFP to recover (p = 0.0016). The tendency to take longer to recover is likely to reflect the dependency of the mobile-bound pool on cytoplasmic availability of free Dystrophin. This is in accordance with our previous observations that recovery of the mobile-bound pool is fast enough that it may be limited by diffusion. The data therefore indicate that endogenous Dystrophin with an inserted Citrine, like exogenous zfDysGFP and huDysGFP, can be found in two states, immobile and mobile, regardless of a very low, but detectable, cytoplasmic pool.

In various fields, transgenic and humanized animal models are a valuable resource where non-invasive methods to study human biology are lacking (Boverhof et al., 2011; Attfield and Dendrou, 2012; Akkina, 2013). Here, we show that exogenous zebrafish and human Dystrophin have subcellular localizations, at both mRNA and protein levels, equivalent to that of endogenous Dystrophin (Ruf-Zamojski et al., 2015). Furthermore, exogenous zebrafish and human Dystrophin have diffusion and binding dynamics similar to those of endogenous zebrafish Dystrophin, in spite of the artificially raised cytoplasmic levels caused by over-expression. Furthermore, we found that Dystrophin dynamics is not affected by the position of the fluorescent tag (internally close to the actin binding site [Citrine] or in C-terminal position [GFP]). Importantly, both zebrafish and human Dystrophins were able to rescue the dystrophic phenotype of dmd^{ta222a/ta222a} embryos. Taken together, these data indicate that the zebrafish embryo is a good model system to study the dynamics of human Dystrophin in live muscle cells in vivo using fluorescently tagged versions of the protein. It is important to keep in mind that human Dystrophin may behave differently in zebrafish than in human muscle. The FRAP analysis methodology developed in this study could be applied for studies on human primary muscle cell cultures, or even pluripotent human stem cells differentiated into muscle fibres (Chal et al., 2015). However, until a suitable 3D ex-vivo physiologically relevant human muscle system is readily available for routine experimentation, our methodology and findings provide a baseline for future comparative studies. For instance, the strategy presented here can be used to study the effects of shortening the protein on Dystrophin dynamics, as occurs in patients with BMD and planned exon-skipping gene therapies (Koenig et al., 1989; Cirak et al., 2011; Konieczny et al., 2013; Verhaart et al., 2014).

We show that, in all three experimental conditions used (exogenous zfDysGFP and huDysGFP or endogenously-driven zfDysCitrine), part of Dystrophin is found in a cytoplasmic freely diffusing pool. Despite considerable apparent variation in measured diffusion constant (D) from fibre to fibre (1.4–10.1 μm² s⁻¹ for D_huDysGFP, 0.6 to 6.7 μm² s⁻¹ for D_zfDysGFP, 0.9 to 4.3 μm² s⁻¹ for D_zfDysCitrine, mean 4 μm² s⁻¹, 3 μm² s^—1, and 2 μm² s^—1, respectively), it is clear that the mobility of Dystrophin is on average around a fourth that of GFP, at approximately 13 μm² s⁻¹. However, whereas GFP is a small (3 × 3 × 4 nm) globular protein, Dystrophin is thought to be a rod perhaps 100 nm long (Pons et al., 1990; Arrio-Dupont et al., 2000; Bhasin et al., 2005; Kameta et al., 2010; Kinsey et al., 2011), so a diffusion constant only a quarter that of GFP is surprising. As Dystrophin appears to diffuse, perhaps so-called ‘active diffusion’ due to energy-using cellular processes (e.g., molecular motors) enhances its apparent mobility in a non-directed manner (Brangwynne et al., 2008, 2009; Weber et al., 2012). As whole Dystrophin structure has not been reported, one can imagine that a compact rapidly diffusing Dystrophin conformation may account for Dystrophin dynamics in vivo. For now, it is not known whether cytoplasmic Dystrophin also exists in low amounts in adult human skeletal muscle cells. However, many studies have shown that, in human embryos and foetuses, Dystrophin first appears in the cytoplasm (Wessels et al., 1991; Clerk et al., 1992; Chevron et al., 1994; Mora et al., 1996; Torelli et al., 1999). Interestingly, a cytoplasmic Dystrophin pool was also found in the adult heart (Peri et al., 1994) and in both regenerating fibres (Kääriäinen et al., 2000) and differentiating human primary muscle cultures (Miranda et al., 1988), where Dystrophin localisation was suggested to recapitulate the embryonic process of Dystrophin deposition, accumulating initially in the cytoplasm and muscle–tendon junctions at the fibre ends, prior to maturing towards costameric localisation. Therefore, it would be particularly interesting to analyse Dystrophin dynamics in the cytoplasm of human dystrophic muscle cells, which undergo repeated cycles of regeneration.

Our direct semi-quantitative FRAP analysis of bleaching and recovery allowed identification of two populations of immobile- and mobile-bound Dystrophin. The dynamic mobile-bound pool is found in fibres with undetectably low levels of cytoplasmic huDysGFP, zfDysGFP, or endogenously-driven zfDysCitrine, indicating that the mobile-bound state occurs independently of over-expression or high level cytoplasmic accumulation.

A proportion of the Dystrophin located at muscle fibre tips is in free exchange with the cytoplasmic diffusible pool, whereas a further portion binds stably at muscle fibre tips. Whether this immobile pool is generated by stabilisation of the mobile-bound pool, or by another route, remains to be determined (Figure 11). It is not clear whether the dynamics of early tip-localised Dystrophin is different from the later costameric Dystrophin. The tip region of zebrafish muscle fibres corresponds to myotendinous junction at the ends of human muscle fibres, where Dystrophin is also found enriched in humans (Zhao et al., 1992) and in several other mammals, namely mouse (Samitt and Bonilla, 1990), rat (Kääriäinen et al., 2000), and guinea pig (Masuda et al., 1992).

The immobile Dystrophin pool at the cell tips is bound tightly enough to transmit significant (10 pN/molecule) forces for significant (1 s) times, enough to unfold Dystrophin's spectrin domains (Bhasin et al., 2005). Dystrophin in the bound mobile pool presumably cannot transmit significant force. However, weak binding would allow response to weak short-lived (sub-pN/molecule, sub-second) forces or may fulfil another function, such as structure assembly, sensing, or signalling. Interestingly, studies of mutants of ezrin, which, like Dystrophin, binds both β-dystroglycan and actin, revealed immobile and mobile membrane bound forms (Coscoy et al., 2002; Spence et al., 2004). The dynamic membrane-bound ezrin was suggested to be an intermediate conformation state leading to actin anchoring and full complex assembly. Similarly, it is possible that Dystrophin binding to β-dystroglycan facilitates a conformation change to promote actin binding and stabilization of the complex (Friedel et al., 2006) (Figure 11). Membrane localization, turnover, and clustering of other adhesion molecules such as cadherins is known to be influenced by the tension experienced by the cells (Delanoë-Ayari et al., 2004; Yonemura et al., 2010; De Beco et al., 2015). Thus, it would be interesting to investigate whether muscle contraction might favour the conversion of some of the mobile-bound or cytoplasmic Dystrophin into immobile Dystrophin.

Our expression vectors contain a CMV promoter that drives human and zebrafish Dystrophin expression throughout the fish. Nonetheless, we observed that muscle cells accumulate Dystrophin protein much more frequently than other cell types, suggesting that human Dystrophin stabilization is tissue dependent. The availability of suitable docking sites or specific partner proteins may play a role in stabilization (Le Rumeur et al., 1804). In addition, sub-cellular accumulation of the mRNA itself may contribute to Dystrophin positioning at the tip. Like zebrafish Dystrophin mRNA, RNA encoding human Dystrophin localized near the tips of fibres. The expression constructs engineered in the present study do not contain the Dystrophin 5′- or 3′-UTR or introns. Instead, the coding sequence is preceded by a standard chimaeric intron. While previous studies showed a role for 5′ and 3′ UTR regions into controlling tissue-specific expression and transcriptional regulation of Dystrophin (see Larsen and Howard, 2014 and references therein), our results show that UTR regions are dispensable for accumulation of the mRNA at the tip. It is therefore unlikely that Dystrophin RNA accumulation at the tips is due to specific RNA transport since that would most likely require the presence of the untranslated regions (for review see Kloc et al., 2002; Holt and Bullock, 2009). Thus, the signals controlling the correct localization of the mRNA remain unclear. One possibility is anchorage by numerous nascent protein chains (Figure 11). This might then facilitate transition of Dystrophin into the strongly bound form.

The new analysis methods developed here broaden the applications of FRAP. Specifically, our modelling overcomes low signal-to-noise ratios and accounts for diffusion during intentional bleaching and unintentional bleaching during imaging. Bleaching due to imaging is here used to analyse binding dynamics. Indeed, at the high laser powers needed in vivo a specific bleaching step may not be necessary, or even optimal. These advances may be generally valuable for studies of embryos and thick tissues or biomaterials by allowing higher laser powers. Also, our results show that pooling results from different cells in a complex in vivo environment may lead to error and mask individual cell-to-cell variability. Finally, our model for one-dimensional diffusion may be especially useful in elongated cells such as muscle cells or neurons. The model was implemented in open-source software that fits diffusion coefficients to data without programming (‘Materials and methods’). Our methodology may have general application for analysis of protein dynamics in vivo.

In conclusion, the present study reveals for the first time the complex dynamics of Dystrophin in maturing muscle cells within the intact animal. It reveals important cell-to-cell variations that most likely reflect fibre or tip maturation but could have another origin. Both developmental state and genetic background are thus expected to influence the stability of Dystrophin, which could prove important in the clinic. Unstable binding or overall shortage of a specific pool may affect Dystrophin turnover and muscle performance. In future, the methodology developed here can be used to test for the comparative performance of short Dystrophin forms in use in gene therapy trials, with the aim of focusing on stable versions that may favour a more successful clinical outcome.

Full-length 427-kd human Dystrophin (huDys) was produced by generating a human Dystrophin cDNA using long-range PCR (primers F1: SpeI_GACTAGTGTGTTCTTCATATGTATATCCTTCC; R1: MluI_CGACGCGTCATTGTGTCCTCTCTCATTG), digested with SpeI and MluI and cloned into pCI plasmid (Promega, Madison, WI, United States) downstream of a CMV promoter at the NheI and MluI restriction sites. Insertion of GFP tag: (1) primers F2 (TCACCTCGAGAAAGTCAAGGCACTTCGAGGAGAAATTG, matching the 3′ huDystrophin cDNA plus a 5′ XhoI site) and R2 (CCTCGCCCTTGCTCACCATGGTTGTGGCCATTGTGTCCTCTCTCATTGGCTTTCCAGGGGTATTTCTTC, designed to remove the Dystrophin stop codon and harbouring first 30 nucleotides of eGFP cDNA) were used on huDys; (2) eGFP cDNA was amplified with F3 (GAAGAAATACCCCTGGAAAGCCAATGAGAGAGGACACAATGGCCACAACCATGGTGAGCAAGGGCGAGG, containing a 5′ free tail encoding the Dystrophin cDNA end) and R3 (GGTACCACGCGTTTACTTGTACAGCTCGTCCATGCC, plus a MluI site); (3) finally, the two products were mixed, amplified with F2 and R3, digested with XhoI and MluI and inserted into pre-digested huDys to generate huDysGFP. GFP was expressed from pCMV-GFP (Addgene 11153). Full-length zebrafish Dystrophin (Lai et al., 2012) GFP tagged was synthesized by GenBrick and subcloned into pCI-Neo at the MluI-SalI site (GenScript USA Inc., Piscataway Township, NJ, United States). All constructs were fully sequenced.

Fish used were King's wild-type Danio rerio, dmd^ta222a/+, Tg(actc1b:mCherry)^pc4 (Cole et al., 2011), and Gt(dmd-Citrine)^ct90a (Trinh et al., 2011; Ruf-Zamojski et al., 2015) and were staged and reared as described (Westerfield, 1995). Plasmids were injected into 1-cell stage embryos at 20–40 pg/embryo. Phenolthiourea (0.003%) was added to inhibit pigmentation. Heat shock was performed at 6 s and embryos analysed at 48 hpf (Ruf-Zamojski et al., 2015). To image, 48 hpf dechorionated embryos were anaesthetized with tricaine (0.2 mg/ml) and embedded in 1.5% low melting point agarose diluted in fish water.

Standard protocols were used. Embryos were fixed in cold methanol for Dystrophin staining, or otherwise in paraformaldehyde 4%. Antibodies were mouse anti-Dystrophin MANDRA1 (1:100; Novocastra, Roche, Basel, Switzerland), mouse anti-human Dystrophin Dy8 (1:100; Novocastra, Roche), rabbit anti-GFP (1:500; Roche), goat anti-mouse Alexa-543, and goat anti-rabbit Alexa-488. NMJ were detected with conjugated bungarotoxin-594 (1:1000, Invitrogen, ThermoFisher Scientific, Waltham, MA, United States). In situ hybridization was performed as previously described (Hinits and Hughes, 2007), with a specific probe against human Dystrophin spectrin repeats 20–22.

An upright Zeiss Exciter laser scanning microscope (LSM) with a 40×/1.1 W Corr LD C-Apochromat objective, and an inverted Zeiss 710 LSM with a 20×/1.0 W Plan-Apochromat and a 40×/1.3 Plan-Apochromat objective were used for FRAP and Z-stacks. Acquisition and maximum intensity projections were made with ZEN 2009/2010 (Zeiss, Jena, Germany). Volocity version 6.0.1 (PerkinElmer, Waltham, MA, United States) was used for XYZ projection, to which a fine Gaussian filter was applied and brightness corrected for visualization purposes only. Images were uniformly contrasted with Adobe Photoshop CS4. Illustrations were made in Adobe Illustrator CS3. GraphPad Prism 6 was used for statistical analysis and graph plotting.

This parameter is a measure of the amount of fluorescence signal resulting from the expression of huDysGFP in a cell or defined sub-cellular region. Confocal Z-stacks of muscle fibres were acquired as 8-bit greyscale images with a voxel size of 0.147 µm × 0.147 µm × 1 µm (x,y,z). ImageJ v1.45a was used for the next steps. The fibre tips or cytoplasm regions were manually delimited on sum projections of the pixel intensities over z-stacks. The raw integrated density (sum of the values of the pixels) in the tips and cytoplasm areas was measured and corrected for the average background. An approximate best correction for the contribution of cytoplasm signal at the tip region, typically at up a 45° angle to the field of view, was made by subtracting the corresponding cytoplasmic signal to half the tip area.

Bleaching was performed at 100% intensity of an argon laser at 488 nm for GFP and 514 nm for Citrine. The acquisition region was a 300 × 60 pixel rectangle (44 µm × 8.8 µm), the interval between scanning rounds 0.2 s at a pixel dwell of 1.6 µs. For cytoplasmic studies, an open pinhole was used to optimize capture of the dim Dystrophin cytoplasmic signal, whereas a 1 Airy pinhole was generally used for GFP (except cells 6 and 7, Table 1). For studying the tips, the pinhole was set at 1 Airy to improve imaging resolution of the tip region and bleaching was performed on a 60 × 20 pixels rectangle with a single scan at pixel dwell of 12.8 µs, thus minimizing bleaching time. Conditions for zfDysCitrine FRAP were adapted to avoid depleting too much of the very low cytoplasmic pool. Also see Figures 4, 6A and Table 1.

The model considers diffusion in one dimension, X, of a single species in a spatially uniform background and includes bleaching by each imaging scan. The differential equation for the concentration of fluorescent protein C_f(X, t) is

where D is the diffusion constant. The first two terms are the normal diffusion partial differential equation. The third term accounts for bleaching at each image acquisition. For each acquired image a fraction β of the fluorescent protein in the imaged area is assumed bleached. The sum is over the image acquisition times t_i. The indicator function Θ_FV(X) is one within the scanned field of view and zero outside of it. The delta function at time t_i of the acquisition of the i'th image (δ(t_i)), assumes that bleaching occurs in the entire imaged region instantaneously. The fitting procedure is a least-squares two-parameter fit, D and β, to the FRAP curve. The boundary conditions for this equation are that the first image after bleaching is given by a Gaussian fit to the profile in this first image, and zero-flux boundary conditions at the two tips of the model cell. The equation is solved within a box approximately as long as the cell and much larger than the imaged region. The entire cell is modelled as the protein diffuses in and out of the imaged region. The effect of varying cell length and position of the bleached region in the model was quantified and deemed minimal (Table 1).

To compare the experimental data with the model results, background subtracted pixel values are averaged along the Y_T-axis to obtain profiles of intensity as a function of X_T. Background is defined as the average intensity signal from a rectangular region outside the cell over pre-bleach images 4–20. A normalized profile for the first post-bleach point is constructed by dividing the first post-bleach profile by the average of the profiles in pre-bleach time points 4–20. A Gaussian A₀ − C₀exp[−(X − X₀)²/(2σ²)] is fit to this normalized post-bleach profile, providing an initial profile for the FRAP-curve simulation. The parameters of the profile at the end of bleaching, A₀, C₀, X₀, and σ are, respectively, the normalized intensity far from the region bleached, the maximum bleaching depth, the centre of the bleached region (along the X-axis), and the bleaching width. A₀ is set to A₀ = 1, the remaining three parameters are fit.

The normalized FRAP curve experimental points are compared with the average value in the computed profile in the bleached region. Fitting is done by minimizing the sum-of-the-squares of the difference between the two, to obtain the best-fit values of D and β. For fits to the initial recovery only, bleaching is small and so a one-parameter fit to D is done in this case.

Fibre tips are divided into two 60 × 20 pixels areas, each covering approximately half of a typical tip, together with some cytoplasm and some pixels outside the cell. (Figure 6A). One box is intentionally bleached (bleached tip), while the other is imaged in an identical way but not intentionally bleached (unbleached tip). A region of similar size in the cytoplasm at a distance from the bright tip region is also analysed. For all regions, the background is subtracted and time points 4 to 20 are used to generate an initial pre-bleach average image for normalization, as for the cytoplasmic studies described above. The background-subtracted intensity is assumed to be proportional to Dystrophin concentration. To understand Dystrophin dynamics at the tip, and to distinguish between different bound populations, direct semi-quantitative analysis of bleaching and recovery is used. FRAP data are analysed in three ways:

1. Direct analysis of the FRAP curve for the bleached half of the tip. Lack of recovery is strong evidence of immobility on the timescale of the experiment. Rapid, but partial, recovery, are indicative signatures of a mobile pool and an immobile pool.

2. Comparative analysis of unnormalized intensities in the unbleached tip region and cytoplasm. Photobleaching due to imaging lowers the final intensity; this effect and a small immobile pool may be indistinguishable. To counter this problem, the identical photobleaching-due-to-imaging received by the unbleached tip region and cytoplasm is used to probe the dynamics. Unnormalized intensity plots (background-subtracted) allow direct comparison of the amount that is unintentionally bleached and then recovers in the tip and the cytoplasm. Presumably, the size of the cytoplasmic component in a tip pixel is at most equal to that in a cytoplasmic pixel, and its FRAP dynamics are similar. Therefore, a permanent drop in tip intensity that is much larger than the drop in the cytoplasmic intensity indicates a large immobile pool. In addition, a dip for the tip signal that is much larger than that in the cytoplasm, and that rapidly recovers, indicates that there is a dynamic bound pool at that tip. Analysis of unnormalized minus cytoplasm intensity curves evaluates if at least 50% of the final recovery occurred at the first or second time points after switching from fast to slow (every 10 s) acquisition rates.

3. Analysis of the difference between bleached and unbleached tip regions. Both regions of the tip receive the same bleaching-due-to-imaging for ∼250 s. If the final difference is large, presumably there is a bound population with a bound lifetime of at least hundreds of seconds. However, if the difference is close to zero, then any bound species is dynamic on this timescale.

Tests were made to evaluate whether bleaching may cause a significant portion of huDysGFP to enter a transient dark state, which then contributes to the fractional recovery after photobleaching. Typically, huDysGFP was bleached in an entire muscle fibre in vivo. Cells expressing high levels (including in the cytoplasm) were chosen to allow better detection of potential low levels of a dark-state pool. Bleaching was performed using the Argon laser at 100%, at which intensity we measured a direct laser power of 0.39–0.5 mW. To image the whole cell, a 20×/1.0 W Plan-Apochromat (Zeiss) objective was used. Due to the size of a muscle cell, similar tests bleaching the entire cell are not possible to perform using exactly the same conditions as in our FRAP experiments, where a 40×/0.8 Achroplan (Zeiss) objective was used. However, the laser power per area is higher in the conditions we use both in cytoplasmic and tips FRAP experiments, which is demonstrated by Mueller et al. (2012) to further decrease the effect of dark state. After whole-cell bleaching very low recovery after photobleaching is detected (<1%), presumably due to a shift from dark state to excitable huDysGFP.

A user-friendly application to analyse cytoplasmic diffusion along the long axis of a cell is freely available (see instructions in Bajanca et al., 2015).

The original datasets and main individual FRAP analysis files are deposited in the Dryad Digital Repository (Bajanca et al., 2015).

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

We thank Glen Morris for anti-Dystrophin antibodies, Roland Roberts for cDNA probes, Tapan Pipalia for counting cells, Rainer Heintzmann for extensive and generous help on imaging, Jeff Chamberlain for sharing constructs and advice, Le Trinh for sharing Gt(dmd-Citrine)^ct90a line.

© 2015, Bajanca et al.

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