During somite segmentation, clock genes oscillate within the posterior presomitic mesoderm (PSM). The temporal information ties up with the posteriorly moving FGF gradient, leading to the formation of a presumptive somite within the PSM. We previously investigated Erk activity downstream of FGF signaling by collecting stained zebrafish embryos, and discovered that the steep gradient of Erk activity was generated in the PSM, and the Erk activity border regularly shifted in a stepwise manner. However, since these interpretations come from static analyses, we needed to firmly confirm them by applying an analysis that has higher spatiotemporal resolutions. Here we developed a live imaging system for Erk activity in zebrafish embryos, using a Förster resonance energy transfer (FRET)-based Erk biosensor. With this system, we firmly showed that Erk activity exhibits stepwise regression within the PSM. Although our static analyses could not detect the stepwise pattern of Erk activity in clock-deficient embryos, our system revealed that, in clock-deficient embryos, the stepwise regression of Erk activity occurs at an irregular timing, eventually leading to formation of irregularly-sized somites. Therefore, our system overcame the limitation of static analyses and revealed that clock-dependent spatiotemporal regulation of Erk is required for proper somitogenesis in zebrafish.
The metameric structures of the vertebrate body, including the axial skeleton and skeletal muscle, are derived from a linear array of embryonic segments called somites1,2,3,4. The somites, which lie on each side of the embryonic midline, are generated by the periodic segmentation of the anterior end of the presomitic mesoderm (PSM). A “clock and wavefront” model was proposed in the 1970s to explain the periodic segmentation of somites5. In this model, the clock (a cellular oscillator) and the wavefront (a posteriorly moving front that arrests the clock, leading to rapid cell-fate changes) are present in the PSM. Through the identification of the cellular oscillators and wavefront in various vertebrates, such as the mouse, chick, and zebrafish2,6, this model has provided key insights on the process of somite segmentation7,8,9,10,11,12. The cellular oscillators include Hes7 (a Hes family transcription factor) and Lunatic fringe (Lfng, a Notch effector) in the mouse13,14, and her1 and her7 (Hes family transcription factors) and deltaC (a Notch ligand) in the zebrafish15,16. Fibroblast growth factor (FGF) and Wnt signaling produce gradients that weaken at the anterior end, and the gradients move continuously toward the posterior end alongside tail elongation2,17,18,19,20. Because of changes in somite size induced by the inhibition and stimulation of FGF signaling, the wavefront represents the FGF threshold2,20,21.
To understand how segmental pre-patterns are determined within the PSM, we previously investigated Erk activity downstream of FGF signaling by collecting stained zebrafish embryos21. We discovered that the fgf8a gradient (wavefront) was converted into a step-like gradient of Erk activity with a sharp border in the PSM, and that the Erk activity border regularly shifted in a stepwise manner. However, the stepwise pattern of Erk activity could not be detected in clock-deficient embryos (her1 and her7 double morphants). These findings suggested that the Erk activity border regularly shifted by the clock (her1 and her7) in a stepwise manner within the uniform PSM. However, since these interpretations come from static observations, whether stepwise regression of Erk activity occurs in the uniform PSM of living zebrafish embryos and what is the role of Erk stepwise regression need to be further investigated.
In this study, we used a Förster resonance energy transfer (FRET)-based Erk biosensor and succeeded to visualize Erk activity within living zebrafish embryos. Erk biosensor detected high Erk activity in the posterior PSM with a sharp border. Time-lapse FRET imaging revealed that the Erk activity border shifts stepwisely along with a regular timing in control embryos, but, in clock-deficient embryos, the stepwise regression of Erk activity occurs at irregular timing. Furthermore, we found a positive correlation between the timing and corresponding somite size in clock-deficient embryos, suggesting that Erk stepwise regression with a regular timing is required for cyclic formation of normal sized somites. Therefore, our system succeeded to visualize Erk activity in living zebrafish embryos and revealed a novel spatiotemporal regulation of Erk in the PSM required for proper formation of somites in zebrafish.
The visualization of the segmental pre-pattern in living zebrafish embryos
Somite segmentation and segmental pre-pattern formation are dynamic processes during development. Because of the activation of Erk by FGF in newly-formed somites (somites I and II: SI and SII), which form from the somite (somite 0: S0), and posterior PSM regions20,21, and due to the relationship between the sharp border in Erk activity and the segmental pre-pattern at the posterior PSM21, we visualized the dynamic changes in Erk activity in living zebrafish embryos using a FRET-based Erk biosensor22. Erk biosensor mRNAs were injected into zebrafish embryos, and Erk activity was calculated using the FRET/CFP ratio in embryos at the 8-somite stage (8SS). Although the Erk biosensor was delivered into the entire body of the embryo, high FRET/CFP signals were detected in specific regions of the embryos, such as in the forebrain, SII, SI, S0, and posterior PSM, as well as at the midbrain–hindbrain boundary (Fig. 1a). In addition, its pattern was similar to that of phosphorylated Erk (pErk, the active form), which was detected with an anti-pErk (pErk) antibody21 (Fig. 1b). To determine whether the Erk biosensor can monitor Erk activity in living zebrafish embryos, we inhibited FGF/Erk signaling with a pharmacological inhibitor for FGFR1 or MEK. After treatment with either the FGFR1 inhibitor (SU5402) or the MEK inhibitor (PD184352), the high FRET/CFP signals in the posterior PSM of 8SS embryos gradually decreased to their basal levels (Fig. 1c–h and Movies 1 and 2), confirming that the FRET/CFP signals indeed reflect FGF-dependent Erk activity, and that the Erk biosensor can monitor Erk activity in living zebrafish embryos.
By immunostaining with the anti-pErk antibody and quantitative analysis of the stained embryos, we recently showed that pErk forms a sharp border in the posterior PSM, and that the sharp border displays stepwise shifts that strongly correlate with somite segmentation, suggesting that the border of Erk activity represents a segmental pre-pattern in the posterior PSM (a determination front in the clock and wavefront model)21. In agreement with this notion, we could observe sharp border of Erk activity in the posterior PSM by using Erk biosensor (Fig. 2a and Supplementary Fig. S1). We next investigated the temporal changes in Erk activity by time-lapse FRET imaging (Fig. 2 and Movie 3). We generated a kymograph along the PSM and extracted a contour of the FRET/CFP ratio, which corresponded to the position of the Erk activity border (Fig. 2b and c, and see Methods). We found that the Erk activity border shifted toward the posterior end in a stepwise manner (Fig. 2b and c). To evaluate its periodicity, we computed the change-points of the contour at which the curve of the contour changes suddenly (arrowheads in Fig. 2c) and investigated the distribution of the intervals using all combinations of the change-points (Fig. 2d, and see Methods). The distribution showed a regular periodic pattern, with a periodicity that was consistent with that of the segmentation cycle (Fig. 2d). Thus, the time-lapse readouts by Erk biosensor firmly showed that stepwise regression of Erk activity occurs in the PSM of zebrafish embryos.
Based on our static analyses, we assumed that the sharp border of Erk activity represents the segmental pre-pattern within the uniform PSM21. To confirm this assumption, we performed retrograde tracking of multiple cells residing in the somite boundary. With this assay, we found that boundary cells of the somite were positioned with similar distance throughout the retrograde time-lapse observations, and that they were originated from the border of Erk activity within the PSM (Fig. 3 and Movie 4). These results firmly show that the sharp border of Erk activity corresponds to the segmental pre-pattern.
The segmentation clock is not required for the formation and stepwise shift of the segmental pre-pattern in the posterior PSM
Clock-deficient embryos in the mouse (Hes7-deficient) and zebrafish (her1 and her7 double morphants and/or mutants) displayed severe skeletal and segmental defects13,23. In these mutants, however, somites are still formed, although the somite size was variable13,21,23. These findings suggest that the clock controls the regularity of the somite size rather than the formation of somites, and that a clock-independent mechanism, which spontaneously generates irregularly-sized somites, is embedded within somitogenesis. Currently, it is unclear how irregular somites form in clock-deficient embryos. To answer this question, we monitored the dynamic changes in Erk activity in embryos with a disrupted segmentation clock. The segmentation clock was disrupted by knocking down two clock genes, her1 and her721,23. In the manipulated embryos, Erk was activated in the forebrain, SI, and posterior PSM, as well as at the midbrain–hindbrain boundary (Supplementary Fig. S2a). In the posterior PSM, the sharp border of Erk activity was generated in a manner similar to that of control embryos (Supplementary Figs S1b and S2b), suggesting that the segmentation clock does not affect the formation of Erk activity border in the PSM.
When we performed time-lapse FRET imaging and generated kymographs in clock-deficient embryos, we could find different dynamics of Erk activity border as compared to controls (compare Fig. 2 to Fig. 4): Erk activity border was generated in clock-deficient embryos as like controls, but the border shifted stepwisely with irregular timing (Fig. 4b–d). To test whether the sharp border of Erk activity could establish the segmental pre-pattern in the posterior PSM, even in clock-deficient embryos, we performed the retrograde tracking of multiple cells residing in the somite boundary in clock-deficient embryos. In agreement with data from control embryos (Fig. 3 and Movie 4), boundary cells residing in the somite were derived from the border of Erk activity within the PSM (Fig. 5 and Movie 6), suggesting that the border of Erk activity corresponds to the segmental pre-pattern, irrespective of the presence or absence of the segmentation clock.
The segmentation clock may reduce the temporal irregularity of Erk stepwise regression, eventually leading to the formation of somites with a constant size
Based on time-lapse observations in clock-deficient embryos (Fig. 4 and Movie 5), we assumed that the temporal irregularity of Erk stepwise regression reflects to the size variations of the corresponding somite. To test the possibility, we timed the interval between a sequential stepwise shift, and then measured the size of the corresponding somite, which is generated during the stepwise cycle (Fig. 6a,b). In control embryos, both the time interval of the sequential shift (29.4 ± 4.6 min, coefficient of variation (CV) = 0.16) and the corresponding somite size (48.5 ± 3.6 µm, CV = 0.07) were constant (Fig. 6c). However, in clock-deficient embryos, both the time interval (36.9 ± 12.5 min, CV = 0.34) and size (53.1 ± 13.9 µm, CV = 0.26) were highly variable as compared to controls. Although there were high variations in clock-deficient embryos, we were able to identify a positive linear correlation between them (Fig. 6d). For instance, when a time interval between the sequential stepwise shift was 20 or 45 min in clock-deficient embryos, the corresponding somite was smaller (39 μm) or larger (58 μm), respectively (Fig. 6d). This correlation suggests that the irregular somite formation in clock-deficient embryos depends on the temporal irregularity of stepwise shift of Erk activity. It also suggests a previously unidentified role for the segmentation clock in the posterior PSM: The segmentation clock reduces the temporal irregularity of the Erk stepwise regression and fine-tunes the corresponding somite size.
Our previous static analyses using anti-pErk antibody suggested that Erk activity is highly dynamic in the PSM during somitogenesis21. However, because the temporal resolution of static analyses was quite low, a live imaging system(s) that monitors Erk activity dynamics in the PSM is required. In this study, we introduced Erk biosensor into zebrafish embryos and could succeed to observe Erk activity dynamics in the PSM with a high resolution. In addition, we firmly confirmed the existence of a dynamic event that Erk activity shifts in a stepwise manner in the PSM, which is required for proper somitogeneis.
Our kymograph analyses suggest that central values of the FRET/CFP ratio, marked by white color in 3-color heat maps (e.g. Figs 2 and 4), correspond to Erk activity borders. This is supported by two lines of evidence. Firstly, the positions of these central values matched with the anterior extremities of Erk activity estimated from the signal intensity plot (Supplementary Fig. S1a), whose positions are also consistent with those of the segmental pre-patterns21. Secondly, retrograde tracking of multiple cells residing boundary cells of the somite revealed that these central values correspond to the segmental pre-pattern in the PSM (Figs 3 and 5). Taken together, we proposed that Erk activity borders, indicated by central values of the FRET/CFP ratio, show stepwise regression with constant or irregular timing in control or clock-deficient embryos, respectively (Figs 2 and 4, and Movies 3 and 5).
Our time-lapse readout suggests that proper formation of somites with a constant size is required for clock-dependent temporal regulation of Erk activity in the PSM. However, there is no direct evidence that the clock (her1 and her7) temporally modulates Erk activity in the zebrafish, although the mRNA expression of negative Erk regulators, such as sprouty and dusp, oscillates in the mouse and chick6. Thus, for further investigation, it will be important to identify the functional relationship between the clock and Erk activity in the zebrafish, which may be different from that reported in the mouse and chick6.
The clock and wavefront model was proposed in 19765, but was then revised after the molecular mechanism of somite segmentation was taken into account24,25. In addition to these models, several theoretical models have been described to explain the different aspects of somitogenesis, including the mechanism of oscillatory gene expression in PSM cells9,26, clock synchronization among cells7,10,11,12, and spatial oscillatory patterning in the PSM8. However, since the removal of the clock from these models predict an impedance of somite individualization, these models have never addressed how the spontaneous formation of irregular somites are formed in clock-deficient embryos. With our live imaging system, we could succeed to visualize Erk activity in the PSM of clock-deficient embryos, and found that Erk stepwise regression occurs with irregular timing in clock-deficient embryos, leading to the formation of irregularly-sized somites (Figs 4 and 6). To our best knowledge, this is the first study to monitor the molecular events of irregular somite formation in clock-deficient embryos. Our time-lapse readouts will be useful to generate theoretical models that can explain both irregular somite formation in the absence of the segmentation clock and normal somite formation in the presence of the segmentation clock.
Synthesis of mRNA encoding the Erk biosensor
The Erk biosensor Eevee-ERKnls comprises an enhanced cyan-emitting mutant of GFP (ECFP), a WW domain, an EV linker, an Erk substrate, a yellow fluorescent protein for energy transfer (Ypet), and a nuclear localization signal (NLS)22. When Erk phosphorylates the Erk substrate, the WW domain binds to the Erk substrate, thereby bringing ECFP closer to Ypet and inducing FRET from ECFP to Ypet. The pCS2-Erk biosensor subcloned from pPBbsr2-3594NLS22 was used as a template for mRNA synthesis. Erk biosensor mRNAs were synthesized using the SP6 mMessage mMachine system (Thermo Fisher Scientific).
Morpholino oligonucleotides (MOs)
Control-MO (5′-CCTCTTACCTCAGTTACAATTTATA-3′), her1-MO (5′-TTCGACTTGCCATTTTTGGAGTAAC-3′), and her7-MO (5′-CAGTCTGTGCCAGGATTTTCATTGC-3′) were obtained from Gene Tools. Double knockdown of her1 and her7 using her1-MO and her7-MO phenocopies segmentation defects in the b567 mutant, which is a deletion mutant of her1 and her7 genes23. The efficacy of these morpholino oligonucleotides (MOs) was also verified in our laboratory21.
Preparation of zebrafish embryos for FRET imaging
Erk biosensor mRNA (100 pg), her1-MO (6.25 ng), and her7-MO (6.25 ng) were co-injected into the yolk of one-cell-stage zebrafish embryos as described previously27. As a control, Erk biosensor mRNA (100 pg) or Erk biosensor mRNA (100 pg) and control-MO (12.5 ng) were injected. Injected embryos were developed until the 7SS stage, dechorionated, and mounted laterally in 1% low melting point agarose at the indicated stages as described previously29.
Embryos mounted in 1% agarose were observed under an LSM710 confocal microscope (Zeiss) equipped with a 440 nm diode laser and a Plan-Apochromat 10×/0.45 objective lens in the lambda scanning mode. Using the linear unmixing mode, CFP and Ypet signals were separated from the initial spectra data. Using MetaMorph software (Molecular Devices), the Ypet image was divided by the CFP image to generate FRET/CFP ratio images. The FRET/CFP ratio images were presented in the intensity-modulated display mode, which shows differences in the FRET/CFP ratio as either 8-color or 3-color heat map from red (high) to blue (low).
Time-lapse FRET imaging
To determine whether the Erk biosensor could be used to monitor Erk activity in zebrafish embryos, 8SS embryos carrying the Erk biosensor were observed for 60 or 75 min at 5 min intervals at 28.5 °C. Between 15 and 20 min, the embryos were treated with SU5402 (0.2 μg/ml) or PD184352 (3.0 μM). To observe the dynamic changes in Erk activity in the PSM, Z-stack images (8 to 10 planes taken at 5 or 10 μm intervals) of 8SS embryos carrying the Erk biosensor were obtained at 5 min intervals at 28.5 °C.
The FRET/CFP ratio images were generated with MetaMorph. The region of the sharp border of Erk activity was determined by comparing each FRET/CFP ratio image with the corresponding signal intensity plot. The positions of SII, SI, and S0 were determined by both visual observation (differential interference contrast) and Erk activation domains.
To confirm the stepwise shift of the borders of Erk activity in the posterior PSM, kymographs, which are graphical representations of the spatial position over time, were generated with MetaMorph following procedure. Time-lapse FRET/CFP ratio images were processed by median filter with 15 pixels windows. Line of interest on anterior-posterior axis in the PSM was selected to extract the signal intensity for kymograph. At each point along the line, Erk activities of vertically neighboring 16 pixels were averaged.
From kymograph images, we calculated contours, a set of isolines, by contour function in Matlab. Consequently, two-dimensional trajectories of isolines were also obtained as shown in Figs 2c and 4c. Among isolines around intermediate Erk activity region, the clearest stepwise trajectory was selected as the Erk activity border as shown in Figs 2c and 4c. For this end, velocity (first order derivative) of isoline trajectories were calculated in kymograph image space and then the one showing the largest variation of the velocity was selected. Note that for easy visualization of the Erk activity border, its activity level was set to white color in Figs 2b and 4b.
The change points of the Erk activity border, which correspond to sudden posterior shifts of its trajectory, were detected as follows. The negative second derivative of the Erk activity border velocity, which represents convexity, was calculated by Savitzky-Golay filter, and its peaks were selected as the change points.
Retrograde cell tracking
By time-lapse FRET imaging in each embryo, we obtained a set of time series data as a Multi TIFF file. Using the “Reverse” function in ImageJ, we reversed time order of the Multi TIFF file. For cell tracking, we used the “Manual Tracking” plug-in in ImageJ. Multiple cells residing in the somite boundary were marked and tracked retrogradely.
Differences between means were analyzed by one-tailed Student’s t-test. The results of t-tests were considered significant when P < 0.01.
Dequeant, M. & Pourquie, O. Segmental patterning of the vertebrate embryonic axis. Nature Reviews Genetics 9, 370–382 (2008).
Hubaud, A. & Pourquie, O. Signalling dynamics in vertebrate segmentation. Nature Reviews Molecular Cell Biology 15, 709–721 (2014).
Saga, Y. & Takeda, H. The making of the somite: Molecular events in vertebrate segmentation. Nature Reviews Genetics 2, 835–845 (2001).
Pourquite, O. Building the spine: The vertebrate segmentation clock. Cold Spring Harbor Symposia on Quantitative Biology 72, 445–449 (2007).
Cooke, J. & Zeeman, E. C. A clock and wavefront model for control of the number of repeated structures during animal morphogenesis. J Theor Biol 58, 455–476 (1976).
Krol, A. et al. Evolutionary plasticity of segmentation clock networks. Development 138, 2783–2792 (2011).
Horikawa, K., Ishimatsu, K., Yoshimoto, E., Kondo, S. & Takeda, H. Noise-resistant and synchronized oscillation of the segmentation clock. Nature 441, 719–723 (2006).
Jaeger, J. & Goodwin, B. A cellular oscillator model for periodic pattern formation. Journal of Theoretical Biology 213, 171–181 (2001).
Lewis, J. Autoinhibition with transcriptional delay: A simple mechanism for the zebrafish somitogenesis oscillator. Current Biology 13, 1398–1408 (2003).
Masamizu, Y. et al. Real-time imaging of the somite segmentation clock: Revelation of unstable oscillators in the individual presomitic mesoderm cells. Proceedings of the National Academy of Sciences of the United States of America 103, 1313–1318 (2006).
Riedel-Kruse, I., Muller, C. & Oates, A. Synchrony dynamics during initiation, failure, and rescue of the segmentation clock. Science 317, 1911–1915 (2007).
Uriu, K., Morishita, Y. & Iwasa, Y. Random cell movement promotes synchronization of the segmentation clock. Proceedings of the National Academy of Sciences of the United States of America 107, 4979–4984 (2010).
Bessho, Y. et al. Dynamic expression and essential functions of Hes7 in somite segmentation. Genes & Development 15, 2642–2647 (2001).
Forsberg, H., Crozet, F. & Brown, N. Waves of mouse Lunatic fringe expression, in four-hour cycles at two-hour intervals, precede somite boundary formation. Current Biology 8, 1027–1030 (1998).
Holley, S., Julich, D., Rauch, G., Geisler, R. & Nusslein-Volhard, C. her1 and the notch pathway function within the oscillator mechanism that regulates zebrafish somitogenesis. Development 129, 1175–1183 (2002).
Jiang, Y. et al. Notch signalling and the synchronization of the somite segmentation clock. Nature 408, 475–479 (2000).
Aulehla, A. et al. Wnt3A plays a major role in the segmentation clock controlling somitogenesis. Developmental Cell 4, 395–406 (2003).
Dubrulle, J., McGrew, M. & Pourquie, O. FGF signaling controls somite boundary position and regulates segmentation clock control of spatiotemporal Hox gene activation. Cell 106, 219–232 (2001).
Naiche, L., Holder, N. & Lewandoski, M. FGF4 and FGF8 comprise the wavefront activity that controls somitogenesis. Proceedings of the National Academy of Sciences of the United States of America 108, 4018–4023 (2011).
Sawada, A. et al. Fgf/MAPK signalling is a crucial positional cue in somite boundary formation. Development 128, 4873–4880 (2001).
Akiyama, R., Masuda, M., Tsuge, S., Bessho, Y. & Matsui, T. An anterior limit of FGF/Erk signal activity marks the earliest future somite boundary in zebrafish. Development 141, 1104–1109 (2014).
Komatsu, N. et al. Development of an optimized backbone of FRET biosensors for kinases and GTPases. Molecular Biology of the Cell 22, 4647–4656 (2011).
Henry, C. et al. Two linked hairy/Enhancer of split-related zebrafish genes, her1 and her7, function together to refine alternating somite boundaries. Development 129, 3693–3704 (2002).
Goldbeter, A., Gonze, D. & Pourquie, O. Sharp developmental thresholds defined through bistability by antagonistic gradients of retinoic acid and FGF signaling. Developmental Dynamics 236, 1495–1508 (2007).
Hester, S., Belmonte, J., Gens, J., Clendenon, S. & Glazier, J. AMulti-cell, Multi-scale Model of Vertebrate Segmentation and Somite Formation. Plos Computational Biology 7 (2011).
Hirata, H. et al. Instability of Hes7 protein is crucial for the somite segmentation clock. Nature Genetics 36, 750–754 (2004).
Matsui, T. et al. Canopy1, a positive feedback regulator of FGF signaling, controls progenitor cell clustering during Kupffer’s vesicle organogenesis. Proceedings of the National Academy of Sciences of the United States of America 108, 9881–9886 (2011).
Matsui, T., Sasaki, A., Akazawa, N., Otani, H. & Bessho, Y. Celf1 regulation of dmrt2a is required for somite symmetry and left-right patterning during zebrafish development. Development 139, 3553–3560 (2012).
Retnoaji, B., Akiyama, R., Matta, T., Bessho, Y. & Matsui, T. Retinoic acid controls proper head-to-trunk linkage in zebrafish by regulating an anteroposterior somitogenetic rate difference. Development 141, 158–165 (2014).
We are grateful to Michiyuki Matsuda for sharing the Erk biosensor, offering advice, initiating helpful discussions, and critically reading the paper. We also thank Kana Ishimatsu, and Sean Megason for critical discussions; Maiko Yokouchi for technical assistance; and Yasukazu Nakahata and Norihiro Kitagawa for valuable comments. D.W.K.S. was supported by the Hitachi Scholarship Doctoral Program from the Hitachi Global Foundation. This work was partially supported by Grants-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan (to R.A., H.N., Y.B., and T.M.), the Takeda Science Foundation (to T.M.), and the Platform Project for Supporting Drug Discovery and Life Science Research (Platform for Dynamic Approaches to Living System) from Japan Agency for Medical Research and Development (AMED) (to H.N.).
The authors declare no competing interests.
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Sari, D.W.K., Akiyama, R., Naoki, H. et al. Time-lapse observation of stepwise regression of Erk activity in zebrafish presomitic mesoderm. Sci Rep 8, 4335 (2018). https://doi.org/10.1038/s41598-018-22619-9
Journal of Statistical Physics (2019)