SummaryOrgan development depends on the integration of coordinated long-range communication between cells. The cerebrospinal fluid composition and flow properties regulate several aspects of central nervous system development, including progenitor proliferation, neurogenesis, and migration [1, 2, 3]. One understudied component of the cerebrospinal fluid, described over a century ago in vertebrates, is the Reissner fiber. This extracellular thread forming early in development results from the assembly of the SCO-spondin protein in the third and fourth brain ventricles and central canal of the spinal cord [4]. Up to now, the function of the Reissner fiber has remained elusive, partly due to the lack of genetic invalidation models [4]. Here, by mutating the scospondin gene, we demonstrate that the Reissner fiber is critical for the morphogenesis of a straight posterior body axis. In zebrafish mutants where the Reissner fiber is lost, ciliogenesis and cerebrospinal fluid flow are intact but body axis morphogenesis is impaired. Our results also explain the frequently observed phenotype that mutant embryos with defective cilia exhibit defects in body axis curvature. Here, we reveal that these mutants systematically fail to assemble the Reissner fiber. We show that cilia promote the formation of the Reissner fiber and that the fiber is necessary for proper body axis morphogenesis. Our study sets the stage for future investigations of the mechanisms linking the Reissner fiber to the control of body axis curvature during vertebrate development.
The zebrafish larva stands out as an emergent model organism for translational studies involving gene or drug screening thanks to its size, genetics, and permeability. At the larval stage, locomotion occurs in short episodes punctuated by periods of rest. Although phenotyping behavior is a key component of large-scale screens, it has not yet been automated in this model system. We developed ZebraZoom, a program to automatically track larvae and identify maneuvers for many animals performing discrete movements. Our program detects each episodic movement and extracts large-scale statistics on motor patterns to produce a quantification of the locomotor repertoire. We used ZebraZoom to identify motor defects induced by a glycinergic receptor antagonist. The analysis of the blind mutant atoh7 revealed small locomotor defects associated with the mutation. Using multiclass supervised machine learning, ZebraZoom categorized all episodes of movement for each larva into one of three possible maneuvers: slow forward swim, routine turn, and escape. ZebraZoom reached 91% accuracy for categorization of stereotypical maneuvers that four independent experimenters unanimously identified. For all maneuvers in the data set, ZebraZoom agreed with four experimenters in 73.2–82.5% of cases. We modeled the series of maneuvers performed by larvae as Markov chains and observed that larvae often repeated the same maneuvers within a group. When analyzing subsequent maneuvers performed by different larvae, we found that larva–larva interactions occurred as series of escapes. Overall, ZebraZoom reached the level of precision found in manual analysis but accomplished tasks in a high-throughput format necessary for large screens.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.