This proposed collaborative project will investigate fundamental processes driving chordate embryogenesis. The project will combine the skills and expertise of two research groups: one that works in the area of developmental biology, and the other in the area of image analysis and computer vision. The goal of the project is take a whole-embryo embryo approach to investigating morphogenesis in live embryos in all 4 dimensions (x,y, z and t). Specifically, we will collect and analyze confocal microscopy images to derive quantitative data on the division, shape, volume and movements of all cells in both selected developing organs and in whole embryos. This project presents many challenges in sample selection and labeling, image capture, and image analysis and visualization. Most model organisms are fundamentally unsuited to the challenge of capturing the shape and movement of every cell in an entire tissue. Those that are suitable typically are distantly related to the chordates, and thus lack organs and tissues relevant to human health and disease. The ascidians (sea squirts), however, are close relatives of the vertebrates that combine a chordate body plan with a small and simple embryonic architecture suitable for imaging in toto. The data to be collected in such observations, particularly at the high resolution needed to observe cellular behavior, will be enormous. The extraction of large-scale quantitative information from timelapse image sets poses substantial challenges in terms of image segmentation and analysis. We have already made significant progress in segmenting 3D ascidian images and further refinements of these approaches are proposed here. The segmented data will allow the quantitative analysis of many complex cell behaviors, including the fundamental changes in cell shape and motility driving gastrulation, neurulation and convergent extension. These analyses will lead to specific hypotheses regarding the cellular and molecular machinery driving morphogenesis. To further investigate the molecular basis for these cellular phenomena, we will also extend our imaging and analysis efforts to investigate the dynamic patterns of subcellular localization of several proteins with key roles in morphogenesis.

Public Health Relevance

Organs and tissues are built during embryogenesis through the precise interactions of a myriad of cells and cell types. Advances in tissue repair and engineering will require that the rules and mechanisms that govern how cells come together to form organs and tissues be elucidated. The project proposed here will combine the efforts of developmental biologists and computer engineers to capture and analyze images from live embryos with the goal of understanding cell behaviors in forming organs.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Research Project (R01)
Project #
5R01HD059217-05
Application #
8681486
Study Section
Special Emphasis Panel (ZRG1-CB-P (55))
Program Officer
Henken, Deborah B
Project Start
2008-07-01
Project End
2017-04-30
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
5
Fiscal Year
2014
Total Cost
$316,851
Indirect Cost
$98,958
Name
University of California Santa Barbara
Department
Neurosciences
Type
Organized Research Units
DUNS #
094878394
City
Santa Barbara
State
CA
Country
United States
Zip Code
93106
Delibaltov, Diana L; Gaur, Utkarsh; Kim, Jennifer et al. (2016) CellECT: cell evolution capturing tool. BMC Bioinformatics 17:88
Delibaltov, Diana L; Ghosh, Pratim; Rodoplu, Volkan et al. (2013) A linear program formulation for the segmentation of Ciona membrane volumes. Med Image Comput Comput Assist Interv 16:444-51
Veeman, Michael T; Smith, William C (2013) Whole-organ cell shape analysis reveals the developmental basis of ascidian notochord taper. Dev Biol 373:281-9
Obara, Boguslaw; Veeman, Michael; Choi, Jae Hyeok et al. (2011) Segmentation of ascidian notochord cells in DIC timelapse images. Microsc Res Tech 74:727-34
Delibaltov, Diana; Ghosh, Pratim; Veeman, Michael et al. (2011) AN AUTOMATIC FEATURE BASED MODEL FOR CELL SEGMENTATION FROM CONFOCAL MICROSCOPY VOLUMES. Proc IEEE Int Symp Biomed Imaging :199-203
Abdollahian, Golnaz; Veeman, Michael; Smith, William et al. (2011) A CURVICYLINDRICAL COORDINATE SYSTEM FOR THE VISUALIZATION AND SEGMENTATION OF THE ASCIDIAN TAIL. Proc IEEE Int Symp Biomed Imaging :182-186