FB2026_01 , released March 12, 2026
FB2026_01 , released March 12, 2026
Reference Report
Open Close
Reference
Citation
Yang, R., Li, E., Kwon, Y.J., Mani, M., Beitel, G.J. (2019). QuBiT: a quantitative tool for analyzing epithelial tubes reveals unexpected patterns of organization in the Drosophila trachea.  Development 146(12): dev172759.
FlyBase ID
FBrf0242347
Publication Type
Research paper
Abstract
Biological tubes are essential for animal survival, and their functions are dependent on tube shape. Analyzing the contributions of cell shape and organization to the morphogenesis of small tubes has been hampered by the limitations of existing programs in quantifying cell geometry on highly curved tubular surfaces and calculating tube-specific parameters. We therefore developed QuBiT (Quantitative Tool for Biological Tubes) and used it to analyze morphogenesis of the embryonic Drosophila trachea (airway). In the main tube, we find previously unknown anterior-to-posterior (A-P) gradients of cell apical orientation and aspect ratio, and periodicity in the organization of apical cell surfaces. Inferred cell intercalation during development dampens an A-P gradient of the number of cells per cross-section of the tube, but does not change the patterns of cell connectivity. Computationally 'unrolling' the apical surface of wild-type trachea and the hindgut reveals previously unrecognized spatial patterns of the apical marker Uninflatable and a non-redundant role for the Na+/K+ ATPase in apical marker organization. These unexpected findings demonstrate the importance of a computational tool for analyzing small diameter biological tubes.
PubMed ID
PubMed Central ID
PMC6602340 (PMC) (EuropePMC)
Associated Information
Comments
Associated Files
Other Information
Secondary IDs
    Language of Publication
    English
    Additional Languages of Abstract
    Parent Publication
    Publication Type
    Journal
    Abbreviation
    Development
    Title
    Development
    Publication Year
    1987-
    ISBN/ISSN
    0950-1991
    Data From Reference
    Alleles (2)
    Genes (5)