During vertebrate embryo development, the body axis is subdivided into repeated structures, called somites. Somites bud off from an un-segmented tissue called the pre-somitic mesoderm (PSM) in a sequential and periodic manner, tightly controlled by an in built molecular clock, called the "segmentation clock". According to current understanding, the clock is comprised of: (i) an autonomous cellular oscillator consisting of an intracellular negative feedback loop of Her genes within the PSM cells, (ii) Delta-ligand and Notch-receptor coupling that facilitates synchronization of oscillators among the PSM cells, (iii) Tissue level waves of gene expression that emerge in the posterior PSM and move coherently towards anterior, leading to global arrest of oscillations in the form of somites. However, the movement of cellular oscillators within the PSM before the formation of somitic furrows, a prominent feature of the tissue as observed through this work has not been experimentally considered as a constituent of the segmentation clock so far. Our work aims to incorporate movement of cellular oscillators in the framework of the segmentation clock. It is well known from theoretical studies that the characteristics of relative motion of oscillators affect their synchronization properties and the patterns of oscillations they form. Particularly, theoretical studies by Uriu et al., PNAS (2010) suggest that cell movements promotes synchronization of genetic oscillations. Here, we established experimental techniques and image analysis tools to attain quantitative insight on (i) diffusion co-efficient of cellular oscillators, (ii) dynamics of a population of oscillators, within the PSM aiming towards concomitant understanding of the relationship between movement and synchronization of cellular oscillators. In order to quantitatively relate cellular oscillators and their motion within the PSM, I established imaging techniques that enabled visualization of fluorescenctly labeled nuclei as readouts of cell positions in live embryo, and developed dedicated segmentation algorithm and implemented tracking protocol to obtain nuclei positions over time in 3D space. Furthermore, I provide benchmarking techniques in the form of artificial data that validate segmentation algorithm efficacy and, for the first time proposed the use of transgenic embryo chimeras to validate segmentation algorithm performance within the context of in vivo live imaging of embryonic tissues. Preliminary analysis of our data suggests that there is relatively high cell mixing in the posterior PSM, within the same spatial zone where synchronous oscillations emerge at maximum speed. Also, there are indications of gradient of cell mixing along the anterior-posterior axis of the embryo. By sampling single cell tracks with the help of nuclei markers, we have also been able to follow in vivo protein oscillations at single cell resolution that would allow quantitative characterization of coherence among a population of cellular oscillators over time. Our image analysis work flow allows testing of mutant embryos and perturbation of synchrony dynamics to understand the cause-effect relationship between movement and synchronization properties at cellular resolution. Essentially, through this work, we hope to bridge the time scales of events and cellular level dynamics that leads to highly coordinated tissue level patterns and thereby further our understanding of the segmentation clock mechanism.

During vertebrate embryo development, the body axis is subdivided into repeated structures, called somites. Somites bud off from an un-segmented tissue called the pre-somitic mesoderm (PSM) in a sequential and periodic manner, tightly controlled by an in built molecular clock, called the "segmentation clock". According to current understanding, the clock is comprised of: (i) an autonomous cellular oscillator consisting of an intracellular negative feedback loop of Her genes within the PSM cells, (ii) Delta-ligand and Notch-receptor coupling that facilitates synchronization of oscillators among the PSM cells, (iii) Tissue level waves of gene expression that emerge in the posterior PSM and move coherently towards anterior, leading to global arrest of oscillations in the form of somites. However, the movement of cellular oscillators within the PSM before the formation of somitic furrows, a prominent feature of the tissue as observed through this work has not been experimentally considered as a constituent of the segmentation clock so far. Our work aims to incorporate movement of cellular oscillators in the framework of the segmentation clock. It is well known from theoretical studies that the characteristics of relative motion of oscillators affect their synchronization properties and the patterns of oscillations they form. Particularly, theoretical studies by Uriu et al., PNAS (2010) suggest that cell movements promotes synchronization of genetic oscillations. Here, we established experimental techniques and image analysis tools to attain quantitative insight on (i) diffusion co-efficient of cellular oscillators, (ii) dynamics of a population of oscillators, within the PSM aiming towards concomitant understanding of the relationship between movement and synchronization of cellular oscillators. In order to quantitatively relate cellular oscillators and their motion within the PSM, I established imaging techniques that enabled visualization of fluorescenctly labeled nuclei as readouts of cell positions in live embryo, and developed dedicated segmentation algorithm and implemented tracking protocol to obtain nuclei positions over time in 3D space. Furthermore, I provide benchmarking techniques in the form of artificial data that validate segmentation algorithm efficacy and, for the first time proposed the use of transgenic embryo chimeras to validate segmentation algorithm performance within the context of in vivo live imaging of embryonic tissues. Preliminary analysis of our data suggests that there is relatively high cell mixing in the posterior PSM, within the same spatial zone where synchronous oscillations emerge at maximum speed. Also, there are indications of gradient of cell mixing along the anterior-posterior axis of the embryo. By sampling single cell tracks with the help of nuclei markers, we have also been able to follow in vivo protein oscillations at single cell resolution that would allow quantitative characterization of coherence among a population of cellular oscillators over time. Our image analysis work flow allows testing of mutant embryos and perturbation of synchrony dynamics to understand the cause-effect relationship between movement and synchronization properties at cellular resolution. Essentially, through this work, we hope to bridge the time scales of events and cellular level dynamics that leads to highly coordinated tissue level patterns and thereby further our understanding of the segmentation clock mechanism.