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Published in final edited form as: Birth Defects Res. 2018 Sep 21;111(14):991–998. doi: 10.1002/bdr2.1389

Tissue Biomechanics during Cranial Neural Tube Closure Measured by Brillouin Microscopy and Optical Coherence Tomography

Jitao Zhang 1,#, Raksha Raghunathan 2,#, Justin Rippy 2, Chen Wu 2, Richard H Finnell 3, Kirill V Larin 2,3,4,†, Giuliano Scarcelli 1,†
PMCID: PMC6428642  NIHMSID: NIHMS986307  PMID: 30239173

Abstract

Background:

Embryonic development involves the interplay of driving forces that shape the tissue and the mechanical resistance that the tissue offers in response. While increasing evidence has suggested the crucial role of physical mechanisms underlying embryo development, tissue biomechanics is not well understood due to the lack of techniques that can quantify the stiffness of tissue in-situ with 3D high-resolution and in a non-contact manner.

Methods:

We used two all-optical techniques, Optical Coherence Tomography (OCT) and Brillouin microscopy, to map the longitudinal modulus of the tissue from mouse embryos in-situ.

Results:

We acquired 2D mechanical maps of the neural tube region of embryos at embryonic day (E) 8.5 (n=2) and E 9.5 (n=2) with submicron spatial resolution. We found the modulus of tissue varied distinctly within the neural tube region of the same embryo and between embryos at different development stages, suggesting our technique has enough sensitivity and spatial resolution to monitor the tissue mechanics during embryonic development in a non-contact and non-invasive manner.

Conclusions:

We demonstrated the capability of OCT-guided Brillouin microscopy to quantify tissue longitudinal modulus of mouse embryos in-situ, and observed distinct change in the modulus during the closure of cranial neural tube. Although this preliminary work cannot provide definitive conclusions on biomechanics of neural tube closure yet due to the limited number of samples, it provides an approach of quantifying the tissue mechanics during embryo development in-situ, thus could be helpful in investigating the role of tissue biomechanics in the regulation of embryonic development. Our next study involving more embryo samples will investigate systematic changes in tissue mechanics during embryonic development.

Keywords: tissue biomechanics, embryo, development, OCT, Brillouin microscopy

Introduction

Extensive research efforts have uncovered how mechanical forces regulate cell functions through the process of mechanotransduction, a mechanism by which cells sense and convert mechanical stimuli to biochemical signals that elicit a range of specific cellular responses(Ingber, 2006; Vogel and Sheetz, 2006). Mechanical cues have also been found to play crucial roles during developmental processes (Barriga and others, 2018; Davidson, 2012; Davidson and others, 2010; Heer and Martin, 2017; Martin and Goldstein, 2014; Miller and Davidson, 2013; Schoenwolf and Smith, 1990; Wozniak and Chen, 2009), where the morphological evolution involving cell alignment, cell folding and tissue reshaping are contributed by both force and mechanical properties of local tissue. For example, the development of the central nervous system of vertebrate animals starts from neurulation, a folding process in which a flat neural plate is transformed into a closed neural tube, and the failure of this process may result in severe birth defect such as spina bifida (Blom and others, 2006; Botto and others, 1999; Copp and Greene, 2010; Copp and others, 2013; Wallingford and others, 2013). The process of neural tube closure (NTC) is regulated by biomechanics through the interaction of generated internal forces and the stiffness of the embryonic tissue (Nikolopoulou and others, 2017; Vijayraghavan and Davidson, 2017; Zhou and others, 2015). Thus, understanding how the tissue deforms and reshapes under applied loads during NTC requires a detailed characterization of tissue biomechanics.

There exist many important techniques that highlight the crucial role of mechanics during embryonic development (Campas, 2016; Sugimura and others, 2016). Previously, the unconfined uniaxial compression test has been used to quantify the mechanical properties of the neural plate and dorsal tissue of the Xenopus laevis (African claw-toed frog), and it was determined that dorsal tissues had a stiffness that was more than 4 fold increased from gastrulation to neurulation (Zhou and others, 2009). However, the experiments were performed on isolated explants of dorsal tissue, and it would be challenging for in-situ measurement due to the limitation of the method. Laser ablation uses an ultrashort pulsed laser to ablate a portion of a structure to create a mechanical imbalance that leads to a measureable response; thus it can probe localized mechanics at both the cell and tissue scale in-situ (Rauzi and others, 2008). Together with an imaging modality and a tissue-level strain-mapping workflow, Galea et.al have recently shown that the neural fold apposition of mouse embryo results from constriction of the open posterior neuropore, which is biomechanically coupled to the zippering point by an F-actin network (Galea and others, 2017). But laser ablation method is invasive, may introduce collateral damage, and its quantitative analysis requires the prior knowledge of either tension or material properties since they are always coupled together (Rauzi and others, 2010; Rauzi and others, 2008). Other indentation methods, such as cantilevers and atomic force microscopy (AFM), have been broadly used to quantify the stress-strain relation by applying force on the sample surface (Krieg and others, 2008). However, they all require physical contact and thus can only be performed on the surface of the tissue. Microrheology, optical tweezers, and magnetic tweezers measure the mechanical properties by monitoring the motion of beads injected into the cell or tissue (Daniels and others; Weber and others, 2012; Welte and others). But several constraints have hindered their use in live embryonic tissue, including the risk of tissue damage upon injection of beads and the difficulty of calibration for quantitative measurement in-situ. Elastography is a non-invasive method that maps the elastic properties of a sample from structural images of physical deformation induced by a known stress field (Kruse and others, 2000; Ophir and others, 2002; Schmitt, 1998). This is a promising technique, but its spatial resolution and precision are limited by the sensitivity and boundary conditions. Microdroplet-based sensor has successfully measured mechanical stresses by tracing the droplet’s deformation after it is micro-injected between cells in tissue (Serwane and others, 2017), is limited to point-sample measurements. During embryonic development, the mechanical properties of the tissue experience both spatial and temporal regulation, which requires measuring techniques to have high spatial resolution within developing 3D tissues, and to be non-invasive and fast.

Spontaneous Brillouin light scattering is an optical phenomenon that arises from the interaction between incoming light and acoustic waves generated from fluctuation within the sample (Dil, 1982). Because of the Doppler effect, the scattered light undergoes an induced frequency shift (Brillouin shift) that is determined by the velocity of the acoustic wave. Since the propagation of an acoustic wave is related to the mechanical properties of the material, Brillouin shift is directly linked to the longitudinal modulus (i.e. the ratio of uniaxial stress to uniaxial strain) of the material. As an all-optical technique, Brillouin spectroscopy based on Fabry-Perot interferometer (FPI) has long been used for material characterization (Vaughan and Randall, 1980) and remote environmental sensing (Hickman and others, 1991); however FPI-based Brillouin spectroscopy requires long acquisition times. In 2008, a parallel dispersive imaging spectrometer based on a virtually imaged phased array (VIPA) was first developed and combined with a confocal microscope to enable Brillouin imaging (Scarcelli and Yun, 2008).

Brillouin microscopy has been recently used to characterize the mechanical properties of eye tissue (Besner and others, 2016; Scarcelli and others, 2015a) in vivo, fibrous proteins of the extracellular matrix (Palombo and others, 2014), and cellular mechanics (Antonacci and Braakman, 2016; Elsayad and others, 2016; Scarcelli and others, 2015b; Zhang and others, 2017). Very recently, we acquired the first mechanical images of a mouse embryo with the Brillouin microscope (Raghunathan and others, 2017), demonstrating that this technique had the promising capability of characterizing the biomechanics of embryonic tissue in-situ.

Optical coherence tomography (OCT) (Huang and others, 1991) is a well-developed optical imaging modality capable of live 4D embryonic imaging with high spatial and temporal resolutions(Wang and others, 2015). Due to its ability to provide high resolution cross-sectional images, OCT has been preferred over other imaging modalities for small animal embryos (Raghunathan and others, 2016). Although histological sectioning has been the gold standard for embryonic imaging, its invasive and time consuming nature combined with the necessity to fix the tissue makes live imaging impossible (Walls and others, 2008). Other noninvasive imaging modalities such as ultrasound biomicroscopy (UBM), micro-magnetic resonance imaging (micro-MRI), and micro-computed tomography (micro-CT) have been used to image small animal embryos. However, limited spatial resolution of UBM (Foster and others, 2003; Phoon and Turnbull, 2003), long acquisition times of micro-MRI and its use of external contrast agents (Nieman and others, 2005), and ionizing radiation in micro-CT are all undesirable for imaging live embryos (Badea, 2018).

Here, with the help of the structural guidance provided by OCT, we demonstrated the mechanical mapping of the neural tube at the cranial region during the early development of mouse embryo by using a Brillouin microscope. Within this preliminary study, we found that the dorsal tissue was distinctly stiffened over time as the embryos developed from embryonic day (E) 8.5 (n=2) to E 9.5 (n=2). Specifically, after neural tube closure (E 9.5), we found that the tissue at the point of fusion was softer than that in the adjacent region, and the modulus of the dorsal tissue itself had a gradient along dorsal-ventral direction. In addition, we identified the ectodermal layer that covered the closed neural tube based on Brillouin metric, and found it was generally softer than the dorsal tissue. This work indicates that tissue mechanics probably changes significantly during the closure of cranial neural tube, and it is thus worthy to further investigate if tissue mechanics plays crucial role during normal development of embryo.

Materials and Methods

EMBRYO PREPARATION

CD-1 mice were set up for timed overnight mating and were checked for a vaginal plug every morning. The presence of a vaginal plug was considered E 0.5. On E 8.5 (n=2) and E 9.5 (n=2), the mother was euthanized by carbon dioxide inhalation and the embryos were dissected out. These embryos were then embedded in 1% agarose with phosphate-buffered saline before being imaged using a home-built swept source OCT system at the University of Houston. All procedures were performed under an approved protocol by the University of Houston Institutional Animal Care and Use Committee. The embryos embedded in agar were first imaged with OCT at the University of Houston and immediately transported to the University of Maryland on ice and imaged with Brillouin microscopy, within 24 hours. The embryos were embedded in agarose to maintain the same orientation of the embryo while being imaged using both modalities. This helped us to image the same region of the neural tube despite having to transport embryos between campuses.

OCT SETUP

The OCT system consisted of a swept source laser (HSL2000, Santec USA, Corp., Hackensack, New Jersey) with a central wavelength of ~1310 nm, scan range of ~150 nm, A- scan rate of ~30 kHz, output power of ~39mW, and axial resolution of ~11μm (in air). More information on the system can be found in our previous work (Manapuram and others, 2008). The images were rescaled to physical dimensions by assuming that the refractive indices of 1% agarose and the embryos were 1.38.

BRILLOUIN MICROSCOPY

The configuration of the Brillouin microscope has been previously reported (Raghunathan and others, 2017; Scarcelli and others, 2015b). Briefly, a two-stage VIPA spectrometer was used to acquire the Brillouin signal (Scarcelli and Yun, 2011), and a spectral coronagraphy was integrated into the spectrometer to enhance its noise-rejection capability (Edrei and others, 2017). An objective lens with an effective numerical aperture of 0.4 was used to achieve a spatial resolution of 0.8 μm × 0.8 μm × 3.3 μm. The acquisition time of the spectrometer was 50 ms for single point measurement. The 2D Brillouin imaging was acquired by scanning the embryo with a 3D motorized stage. The scanning step size was set as 4 μm and 1 μm in lateral and axial direction, respectively. During measurement, the cross-sections around the cranial region of the embryo were mapped by Brillouin microscope, which was guided by the 3D image previously acquired with OCT (Figure 1).

Figure 1.

Figure 1.

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Representative 3D images of mouse embryos acquired by OCT. (a) E8.5, (b) E9.5. The red dashed line indicated the cross-section of the neural tube scanned by Brillouin microscope. Both scale bars are 100 μm.

The measured Brillouin shift vB of the backward scattered light is related to the longitudinal modulus M′ of the sample via the relationship vB=2n/λ⋅M′/ρ, where n is the refractive index, λ is the laser wavelength, and ρ is the material density. Previous experiments indicate that M′ has a linear relationship with Young’s modulus E′ under log-log scale (Scarcelli and others, 2011); thus the relative changes of longitudinal modulus and Young’s modulus can be approximated as δE′/E′=(1/a)δM′/M′, where a is a factor related to the material. For cells, 1/a has been calibrated to be ~15 (Scarcelli and others, 2015b). For ruminant retina tissue, this relationship was still valid and 1/a was estimated to be ~14.3 (Weber, Yun, Scarcelli, & Franze, 2017). We used these values to estimate the elastic modulus change of neural tube tissue of embryos.

Results

TISSUE STIFFENS SIGNIFICANTLY AFTER NEURAL TUBE CLOSURE

Previous measurements on Xenopus laevis embryos reported tissue stiffening during the stage of elongation and neural tube closure (Barriga and others, 2018; Zhou and others, 2009). In our studies using a mouse model, we initially observed tissue stiffening of the neural folds by comparing embryos with open (E 8.5) and closed (E 9.5) neural tubes (Figure 2). The representative morphologies of two embryos was imaged with OCT (Fig.2a-2b), where the open and closed neural tube can be clearly seen. As shown in the co-localized Brillouin images, the closed neural tube (Fig. 2d) is distinctly stiffer than the opened neural tube (Fig.2c). We quantified the averaged Brillouin shift of the whole neural tube region (Fig.2e), and the results suggest that the Brillouin shift of the closed neural tube is 0.21 GHz higher than an opened one. Using a previous calibration between Brillouin-derived longitudinal modulus and Young’s modulus (Methods and Materials), this amount of frequency change would correspond to ~80% relative increase of Young’s modulus (δE′/E′).

Figure 2.

Figure 2.

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Tissue stiffening of the neural tube during embryonic development. (a) and (b) are OCT cross-sectional images of representative E8.5 and E9.5 embryos. Dashed yellow boxes indicate the imaged region by Brillouin microscope. (c) and (d) are corresponding Brillouin images at the same cross-sections; the red dashed lines indicate the neural folds. (e) averaged Brillouin shift of the neural tube tissues of E8.5 (n=2) and E9.5 (n=2) embryos. All scale bars are 100 μm.

MODULUS OF NEURAL TUBE TISSUE HAS A GRADIENT ALONG DORSAL-VENTRAL DIRECTION AND FUSION REGION IS MUCH SOFTER AFTER CLOSURE

We next assessed the modulus distribution on the neural folds after NTC. For this analysis, we scanned cross-sections at different locations close to the cranial neuropore of a E9.5 embryo (Fig.3). The OCT images suggest that the neural tubes are fully closed in all three locations (Fig.3a-3c), while the co-localized Brillouin images indicate there exists a modulus gradient along the neural tube (Fig.3d-3f). To quantify this variation, we first divided an individual neural tube into multiple sub-regions according to the modulus distribution, as indicated by the red box. We next calculated the average Brillouin shift in each sub-region, and the results are shown in Fig.3g-3i. We first noticed that the Brillouin shift of the fusion region is much smaller than that of the adjacent neural folds. The differences of Brillouin shift are within a range between 0.14 GHz and 0.28 GHz, indicating the adjacent neural tube is 60%−100% stiffer than the fusion region in terms of Young’s modulus. The curves in Fig. 3g-3i also suggest a modulus decrease in the neural tube from dorsal region to ventral region (green arrows). Since we did not observe similar phenomena in the open neural tube of E 8.5 embryo, we hypothesize that this modulus gradient is related to the translocation of neuroepithelial cells in ventral-dorsal direction during later development (McShane and others, 2015), and may play crucial role in facilitating the successful closure of the neural tube.

Figure 3.

Figure 3.

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Tissue modulus of the neural folds shows a gradient along dorsal-ventral direction. (a)-(c) are OCT cross-sectional images of the neural tube of a representative E9.5 mouse embryo. Dashed yellow boxes indicate the imaged region by Brillouin microscopy. (d)-(f) are corresponding Brillouin images at the same cross-sections; the neural tube is artificially segmented into different sub-regions (red lines) to quantify averaged modulus locally, and the results are shown in (g)-(i). Red arrows indicate the region of neural tube fusion is distinctly softer than other part of neural folds; Green arrows indicate the curve trend. All scale bars are 100 μm.

ECTODERM LAYER CAN BE DISTINGUISHED FROM NEURAL TUBE AND IS MUCH SOFTER

The closed neural tube is covered by a surface ectoderm which is usually indistinguishable from adjacent dorsal tissue without utilizing some variety of cell labeling (Fig.3a-3c). Using a mechanical phenotype as a signature, we can clearly distinguish the ectoderm layer from that of the neural tube proper, as outlined by the dashed white line in Fig.4a-4c. We subsequently quantified the modulus difference between the ectodermal layer and the neural tube tissue. For this purpose, we excluded the fusion region and outlined the neural tube as left side and right side; we then calculated the average Brillouin shift of each region (Fig. 4d-4f). We found that although the Brillouin shift of the left and right sides of the neural tube are quite close, the ectoderm layer has a much smaller Brillouin shift (0.22 GHz). This suggests that the ectoderm layer is approximately 80.4% softer than the closed neural tube in terms of the Young’s modulus.

Figure 4.

Figure 4.

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(a)-(c) are Brillouin images of neural tubes at different levels of a representative E9.5 embryo (same as Fig. 3d-3f); (d)-(f) are averaged Brillouin shifts (mean ± s.d.) of neural tube tissues (region indicated by red dashed line) and ectoderm layers (region indicated by white dashed line); NT(left) and NT(right) indicate the left and right part of the neural fold, respectively. All scale bars are 100 μm.

Discussion

The process of neural tube fusion and closure involves several critically important cell activities such as apical constriction, convergent extension and cell migration, which facilitate NTC by thickening, lengthening, elevating and bending the neural tube tissue. The tissue stiffening we observed with Brillouin technique could be a consequence of such cell activities. For example, a previous study has observed an increase in cell density dorsolaterally compared with the more ventromedial neural folds, which is caused by both the translocation of neuroepithelial cells in a ventral-to-dorsal direction, and rapid cell proliferation locally (McShane and others, 2015). Since the tissue stiffness is closely related to the cell density (Koser, Moeendarbary, Hanne, Kuerten, & Franze, 2015; Weber, Yun, Scarcelli, & Franze, 2017), the modulus gradient we observed in Fig.3 could be also related to cell translocations, which will need to be investigated and verified in future studies. The tissue stiffening also suggests that the force generated by actomyosin may also need to be increased accordingly to accomplish a successful closure.

In the late stage of NTC, the cellular protrusions from the leading edge of the apposed neural folds make initial contacts between the folds and achieve the epithelial adhesion (Pai and others, 2012), which eventually results in a stable epithelial fusion across the midline of the neural tube. The distinctly soft region at the midline shown in Fig.3 provides a hint of epithelial fusion during NTC, and suggests that it has a different mechanical phenotype from that of the neural folds.

It is important to note that the mechanical property sensed by Brillouin technique is a high-frequency longitudinal modulus M′, whose relation to quasi-static Young’s modulus E′ measured by conventional method is not clearly known. However, several empirical studies have found the two types of moduli to be correlated (Scarcelli and others, 2011; Scarcelli and others, 2015b; Weber and others, 2017). For an accurate conversion from M′ to E′ a material-dependent calibration is required; here, we have estimated the relative changes of Young’s modulus of neural tube tissue based on a previous calibration based on retina tissue. In future, a direct calibration on neural tube tissue will be necessary.

Besides the longitudinal modulus, the value of Brillouin shift is also related to the density and refractive index of the tissue, the effects of which have not been evaluated with the current technique. However, previous studies suggest that these two parameters are usually coupled with each other for biological samples such as cells and tissues (Barer and others, 1953; Schürmann and others, 2016), and the ratio of n/ρ is nearly constant for cells (Scarcelli and others, 2015b). In the future, a direct measurement of refractive index and/or density of embryonic tissue would be necessary for accurate determination of the longitudinal modulus. Additionally, since these measurements were conducted post-mortem, the absolute values for from M′ (and E′) might be somewhat different in live embryos, however the contrast expected to be the same – subject of our future studies.

Due to the elastic scattering from embryonic tissue, the Brillouin signal dropped quickly as the image depth increased. The penetration depth of our current Brillouin setup is therefore limited to ~200 μm. This limitation could be mitigated by using an advanced illumination strategy based on adaptive optics technique (Edrei and Scarcelli, 2018).

The sample numbers in this study was limited due to issues encountered during transportation of samples between the two labs. This does not allow us to draw general conclusions on biomechanics of neural tube closure yet. A following study that involves larger number of embryo samples will be conducted to systematically investigate qualitative changes in tissue mechanics during the closure of neural tube.

Conclusion

Embryogenesis is an intrinsically biomechanical process that involves the interplay of driving forces that shape the tissue morphology and the mechanical resistance that the tissue offers as a response. The mechanical properties of the embryonic tissue thus are crucial during the development. Although increasing attention has been paid to understanding the importance of mechanical cues during development, the mechanical properties of embryonic tissue are not fully characterized due to a lack of availability of a proper technique. Within this preliminary work, by using OCT and Brillouin microscopy, we observed the biomechanical changes in murine embryonic tissue during early development. We demonstrated that this novel technology was sensitive to the mechanical change of the neural tube tissue during the course of neural tube closure, indicating the promising capability of the Brillouin technique in quantifying tissue biomechanics during embryogenesis.

Acknowledgements

This work is supported by National Institute of Health under contract numbers: R01HD081216, R01HD083809, P01HD067244, R01HL120140, K25EB015885, R33CA204582 and R01HD086765.

Grant Information: Supported by R01HD081216, R01HD083809, P01HD067244, R01HL120140, K25EB015885, R33CA204582, R01HD086765 and 1R01HD095520 from National Institute of Health.

Footnotes

Declaration of Interest

The authors report no declaration of interest.

References

  1. Antonacci G, Braakman S. 2016. Biomechanics of subcellular structures by non-invasive Brillouin microscopy. Scientific Reports 6:37217. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Badea CT. 2018. Small Animal X-ray Computed Tomography. Handbook of X-ray Imaging: Physics and Technology [Google Scholar]
  3. Barer R, Ross K, Tkaczyk S. 1953. Refractometry of living cells. Nature 171(4356):720. [DOI] [PubMed] [Google Scholar]
  4. Barriga EH, Franze K, Charras G, Mayor R. 2018. Tissue stiffening coordinates morphogenesis by triggering collective cell migration in vivo. Nature 554:523. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Besner S, Scarcelli G, Pineda R, Yun S-H. 2016. In vivo Brillouin analysis of the aging crystalline lens. Investigative ophthalmology & visual science 57(13):5093–5100. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Blom HJ, Shaw GM, den Heijer M, Finnell RH. 2006. Neural tube defects and folate: case far from closed. Nature Reviews Neuroscience 7(9):724. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Botto LD, Moore CA, Khoury MJ, Erickson JD. 1999. Neural-tube defects. N Engl J Med 341(20):1509–1519. [DOI] [PubMed] [Google Scholar]
  8. Campas O 2016. A toolbox to explore the mechanics of living embryonic tissues. Semin Cell Dev Biol 55:119–130. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Copp AJ, Greene ND. 2010. Genetics and development of neural tube defects. J Pathol 220(2):217–230. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Copp AJ, Stanier P, Greene ND. 2013. Neural tube defects: recent advances, unsolved questions, and controversies. The Lancet Neurology 12(8):799–810. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Daniels BR, Masi BC, Wirtz D. Probing Single-Cell Micromechanics In Vivo: The Microrheology of C. elegans Developing Embryos. Biophysical Journal 90(12):4712–4719. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Davidson LA. 2012. Epithelial machines that shape the embryo. Trends Cell Biol 22(2):82–87. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Davidson LA, Joshi SD, Kim HY, Von Dassow M, Zhang L, Zhou J. 2010. Emergent morphogenesis: elastic mechanics of a self-deforming tissue. Journal of biomechanics 43(1):63–70. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Dil J 1982. Brillouin scattering in condensed matter. Reports on Progress in Physics 45(3):285. [Google Scholar]
  15. Edrei E, Gather MC, Scarcelli G. 2017. Integration of spectral coronagraphy within VIPA-based spectrometers for high extinction Brillouin imaging. Optics Express 25(6):6895–6903. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Edrei E, Scarcelli G. 2018. Brillouin micro-spectroscopy through aberrations via sensorless adaptive optics. Applied physics letters 112(16):163701. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Elsayad K, Werner S, Gallemi M, Kong J, Sanchez Guajardo ER, Zhang L, Jaillais Y, Greb T, Belkhadir Y. 2016. Mapping the subcellular mechanical properties of live cells in tissues with fluorescence emission-Brillouin imaging. Sci Signal 9(435):rs5. [DOI] [PubMed] [Google Scholar]
  18. Foster FS, Zhang M, Duckett AS, Cucevic V, Pavlin CJ. 2003. In vivo imaging of embryonic development in the mouse eye by ultrasound biomicroscopy. Investigative ophthalmology & visual science 44(6):2361–2366. [DOI] [PubMed] [Google Scholar]
  19. Galea GL, Cho YJ, Galea G, Mole MA, Rolo A, Savery D, Moulding D, Culshaw LH, Nikolopoulou E, Greene NDE, Copp AJ. 2017. Biomechanical coupling facilitates spinal neural tube closure in mouse embryos. Proc Natl Acad Sci U S A 114(26):E5177–e5186. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Heer NC, Martin AC. 2017. Tension, contraction and tissue morphogenesis. Development 144(23):4249–4260. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Hickman GD, Harding JM, Carnes M, Pressman A, Kattawar GW, Fry ES. 1991. Aircraft laser sensing of sound velocity in water: Brillouin scattering. Remote sensing of environment 36(3):165–178. [Google Scholar]
  22. Huang D, Swanson EA, Lin CP, Schuman JS, Stinson WG, Chang W, Hee MR, Flotte T, Gregory K, Puliafito CA, et al. 1991. Optical coherence tomography. Science 254(5035):1178–1181. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Ingber DE. 2006. Cellular mechanotransduction: putting all the pieces together again. Faseb j 20(7):811–827. [DOI] [PubMed] [Google Scholar]
  24. Krieg M, Arboleda-Estudillo Y, Puech PH, Käfer J, Graner F, Müller DJ, Heisenberg CP. 2008. Tensile forces govern germ-layer organization in zebrafish. Nature Cell Biology 10:429. [DOI] [PubMed] [Google Scholar]
  25. Kruse SA, Smith JA, Lawrence AJ, Dresner MA, Manduca A, Greenleaf JF, Ehman RL. 2000. Tissue characterization using magnetic resonance elastography: preliminary results. Phys Med Biol 45(6):1579–1590. [DOI] [PubMed] [Google Scholar]
  26. Manapuram R, Manne V, Larin K. 2008. Development of phase-stabilized swept-source OCT for the ultrasensitive quantification of microbubbles. Laser Physics 18(9):1080–1086. [Google Scholar]
  27. Martin AC, Goldstein B. 2014. Apical constriction: themes and variations on a cellular mechanism driving morphogenesis. Development 141(10):1987–1998. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. McShane SG, Mole MA, Savery D, Greene ND, Tam PP, Copp AJ. 2015. Cellular basis of neuroepithelial bending during mouse spinal neural tube closure. Dev Biol 404(2):113–124. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Miller CJ, Davidson LA. 2013. The interplay between cell signalling and mechanics in developmental processes. Nature Reviews Genetics 14(10):733. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Nieman BJ, Bock NA, Bishop J, Chen XJ, Sled JG, Rossant J, Henkelman RM. 2005. Magnetic resonance imaging for detection and analysis of mouse phenotypes. NMR in biomedicine 18(7):447–468. [DOI] [PubMed] [Google Scholar]
  31. Nikolopoulou E, Galea GL, Rolo A, Greene ND, Copp AJ. 2017. Neural tube closure: cellular, molecular and biomechanical mechanisms. Development 144(4):552–566. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Ophir J, Alam SK, Garra BS, Kallel F, Konofagou EE, Krouskop T, Merritt CRB, Righetti R, Souchon R, Srinivasan S, Varghese T. 2002. Elastography: Imaging the elastic properties of soft tissues with ultrasound. Journal of Medical Ultrasonics 29(4):155. [DOI] [PubMed] [Google Scholar]
  33. Pai YJ, Abdullah NL, Mohd-Zin SW, Mohammed RS, Rolo A, Greene ND, Abdul-Aziz NM, Copp AJ. 2012. Epithelial fusion during neural tube morphogenesis. Birth Defects Res A Clin Mol Teratol 94(10):817–823. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Palombo F, Winlove CP, Edginton RS, Green E, Stone N, Caponi S, Madami M, Fioretto D. 2014. Biomechanics of fibrous proteins of the extracellular matrix studied by Brillouin scattering. Journal of The Royal Society Interface 11(101):20140739. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Phoon CK, Turnbull DH. 2003. Ultrasound biomicroscopy-Doppler in mouse cardiovascular development. Physiological genomics 14(1):3–15. [DOI] [PubMed] [Google Scholar]
  36. Raghunathan R, Singh M, Dickinson ME, Larin KV. 2016. Optical coherence tomography for embryonic imaging: a review. J Biomed Opt 21(5):50902. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Raghunathan R, Zhang J, Wu C, Rippy J, Singh M, Larin KV, Scarcelli G. 2017. Evaluating biomechanical properties of murine embryos using Brillouin microscopy and optical coherence tomography. Journal of Biomedical Optics 22(8):086013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Rauzi M, Lenne PF, Lecuit T. 2010. Planar polarized actomyosin contractile flows control epithelial junction remodelling. Nature 468(7327):1110–1114. [DOI] [PubMed] [Google Scholar]
  39. Rauzi M, Verant P, Lecuit T, Lenne P-F. 2008. Nature and anisotropy of cortical forces orienting Drosophila tissue morphogenesis. Nature Cell Biology 10:1401. [DOI] [PubMed] [Google Scholar]
  40. Scarcelli G, Besner S, Pineda R, Kalout P, Yun SH. 2015a. In vivo biomechanical mapping of normal and keratoconus corneas. JAMA ophthalmology 133(4):480–482. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Scarcelli G, Kim P, Yun SH. 2011. In vivo measurement of age-related stiffening in the crystalline lens by Brillouin optical microscopy. Biophysical journal 101(6):1539–1545. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Scarcelli G, Polacheck WJ, Nia HT, Patel K, Grodzinsky AJ, Kamm RD, Yun SH. 2015b. Noncontact three-dimensional mapping of intracellular hydromechanical properties by Brillouin microscopy. Nature methods 12(12):1132–1134. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Scarcelli G, Yun SH. 2008. Confocal Brillouin microscopy for three-dimensional mechanical imaging. Nature photonics 2(1):39–43. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Schmitt J 1998. OCT elastography: imaging microscopic deformation and strain of tissue. Opt Express 3(6):199–211. [DOI] [PubMed] [Google Scholar]
  45. Schoenwolf GC, Smith JL. 1990. Mechanisms of neurulation: traditional viewpoint and recent advances. Development 109(2):243–270. [DOI] [PubMed] [Google Scholar]
  46. Schürmann M, Scholze J, Müller P, Guck J, Chan CJ. 2016. Cell nuclei have lower refractive index and mass density than cytoplasm. Journal of biophotonics 9(10):1068–1076. [DOI] [PubMed] [Google Scholar]
  47. Serwane F, Mongera A, Rowghanian P, Kealhofer DA, Lucio AA, Hockenbery ZM, Campas O. 2017. In vivo quantification of spatially varying mechanical properties in developing tissues. Nat Methods 14(2):181–186. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Sugimura K, Lenne P-F, Graner F. 2016. Measuring forces and stresses in situ in living tissues. Development 143(2):186–196. [DOI] [PubMed] [Google Scholar]
  49. Vaughan JM, Randall JT. 1980. Brillouin scattering, density and elastic properties of the lens and cornea of the eye. Nature 284:489. [DOI] [PubMed] [Google Scholar]
  50. Vijayraghavan DS, Davidson LA. 2017. Mechanics of neurulation: From classical to current perspectives on the physical mechanics that shape, fold, and form the neural tube. Birth defects research 109(2):153–168. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Vogel V, Sheetz M. 2006. Local force and geometry sensing regulate cell functions. Nat Rev Mol Cell Biol 7(4):265–275. [DOI] [PubMed] [Google Scholar]
  52. Wallingford JB, Niswander LA, Shaw GM, Finnell RH. 2013. The continuing challenge of understanding, preventing, and treating neural tube defects. Science 339(6123):1222002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Walls JR, Coultas L, Rossant J, Henkelman RM. 2008. Three-dimensional analysis of vascular development in the mouse embryo. PloS one 3(8):e2853. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Wang S, Singh M, Lopez AL 3rd, Wu C, Raghunathan R, Schill A, Li J, Larin KV, Larina IV. 2015. Direct four-dimensional structural and functional imaging of cardiovascular dynamics in mouse embryos with 1.5 MHz optical coherence tomography. Opt Lett 40(20):4791–4794. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Weber GF, Bjerke MA, DeSimone DW. 2012. A mechanoresponsive cadherin-keratin complex directs polarized protrusive behavior and collective cell migration. Dev Cell 22(1):104–115. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Weber IP, Yun SH, Scarcelli G, Franze K. 2017. The role of cell body density in ruminant retina mechanics assessed by atomic force and Brillouin microscopy. Physical biology 14(6):065006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Welte MA, Gross SP, Postner M, Block SM, Wieschaus EF. Developmental Regulation of Vesicle Transport in Drosophila Embryos: Forces and Kinetics. Cell 92(4):547–557. [DOI] [PubMed] [Google Scholar]
  58. Wozniak MA, Chen CS. 2009. Mechanotransduction in development: a growing role for contractility. Nat Rev Mol Cell Biol 10(1):34–43. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Zhang J, Nou XA, Kim H, Scarcelli G. 2017. Brillouin flow cytometry for label-free mechanical phenotyping of the nucleus. Lab on a Chip 17(4):663–670. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Zhou J, Kim HY, Davidson LA. 2009. Actomyosin stiffens the vertebrate embryo during crucial stages of elongation and neural tube closure. Development 136(4):677–688. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Zhou J, Pal S, Maiti S, Davidson LA. 2015. Force production and mechanical accommodation during convergent extension. Development 142(4):692–701. [DOI] [PMC free article] [PubMed] [Google Scholar]

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