Winter, Peter, Mohler, William, Bao, Zhirong, Christensen, Ryan, Kovacevic, Ismar, Kumar, Abhishek, Santella, Anthony, Wu, Yicong, Bokinsky, Alexandra, McCreedy, Evan, Colon-Ramos, Daniel, Marquina, Javier, Shroff, Hari
[
International Worm Meeting,
2015]
Despite identification of many key neurodevelopmental mechanisms from work on individual cells or simple, defined circuits, our understanding of how known mechanisms work together to direct the assembly of entire nervous systems remains limited. Examining the development of simple nervous systems, like the 302 neurons of Caenorhabditis elegans, offers one way to examine how a limited set of guidance cues can function to direct the assembly of complex neural circuits. The majority of C. elegans neurons (222) are born during embryogenesis, but study of embryonic neurodevelopmental events has proven difficult due to changes in embryo morphology and muscular activity which cause rapid twisting and movement, interfering with imaging and analysis. To examine this period of nematode development, we have developed a computer algorithm for the MIPAV software application which allows a user to computationally straighten images of twisted-up embryos, effectively canceling embryo movement and greatly simplifying the analysis of developmental events in moving embryos. We have also added the capability to track the 3-dimensional position of user-defined cells or structures over time, allowing for quantitative analysis of cell movement, growth and shape change. We have used this annotation capability to track the position of seam cells (as a proxy for overall embryo morphology) from the 1.5-fold stage through hatching in five embryos. We have found that position appears highly stereotyped, with the average anterior-posterior trajectory of a seam cell conserved to approximately 5 um. We have also tracked the movements of the CAN, ALA, and AIY neurons, as well as ALA neurite outgrowth, as a proof-of-concept for neuronal tracking. We observed a clear difference in positional variability between CAN, which undergoes embryonic migration, and AIY/ALA, with CAN showing significantly greater positional variability along the anterior-posterior axis. We plan to apply the untwisting and annotation capabilities we have developed to track the development of all 222 neurons in the embryo, which we anticipate will result in the first comprehensive map showing morphological development of an entire nervous system.
Bao, Zhirong, Harvey, Brandon, Karaj, Nensi, Guo, Min, Vazquez Martinez, Nabor, Duncan, Leighton, Schwartz, Gabi, Levin, Michael, Xu, Stephen, McCreedy, Evan, Mohler, William, Moyle, Mark, Christensen, Ryan, Colon-Ramos, Daniel, Del Toro-Pedrosa, Daniel, Wu, Yicong, Bokinsky, Alexandra, Santella, Anthony, Lauziere, Andrew, Shroff, Hari, Ardiel, Evan
[
International Worm Meeting,
2021]
The limited number of cells and invariant cell lineage of the Caenorhabditis elegans embryo make it an excellent system for examining complex developmental events, such as tissue movement and neurodevelopment. Prior work from the WormGUIDES project has digitized the position of all nuclei for the first half of embryogenesis, creating a computational map of the embryo that can be used to overlay developmentally relevant information like gene expression or neurite outgrowth. Creating a similar map for the second half of embryogenesis is difficult due to embryo elongation and movement. We have developed software to computationally untwist the moving embryo, allowing for analysis of cell position during this period of development, and have begun expanding our computational map into the second half of embryogenesis. Our current map includes 202 nuclei across the embryo, including 32 neuronal nuclei, 81 body wall muscle nuclei, 20 intestinal, and 20 seam cell nuclei. We also include a tract-based model of the nerve ring, showing how it is positioned relative to neuronal and body wall muscle nuclei as the embryo elongates. In addition to our partial nuclear atlas, we describe improvements to our untwisting and tracking workflow, including a deep-learning image restoration capability which improves image quality during rapid embryo movements, and a semi-automated tracking upgrade to our untwisting software which improves tracking throughput. As we continue to add nuclei and neuronal morphology to the atlas, we plan to integrate our post twitching model with previous pre-twitching work to develop a digital atlas spanning the entirety of embryogenesis.