Collaborating Investigator(s): Gabrielle Kardon, PhD
Institution: University of Utah

Gabrielle Kardon is an Associate Professor of Human Genetics at the University of Utah. The Kardon Lab is focused on the development and regeneration of muscle and the role of the surrounding muscle connective tissue and adjacent tendons in regulating these processes. How muscle, connective tissue, and tendon are assembled into a functional limb musculoskeletal system is largely unknown and defective in multiple human genetic syndromes. Using sophisticated mouse genetic reagents to manipulate these three tissues, the Kardon Lab is dissecting the molecular mechanisms and cell-cell interactions required for normal limb development and that is aberrant in human genetic syndromes.

Understanding normal limb and diaphragm development and determining the genetic and cellular mechanisms underlying limb and diaphragm birth defects has great impact. This increased understanding will pave the way for future therapeutic treatments of these defects. Diaphragmatic birth defects (Congenital Diaphragmatic Hernias) are both common (1:3000 births) and 50% fatal. The estimated cost of treatment of CDH patients in the US is $250 million/year, and thus there is a strong incentive to devise early interventions. In adults, successful regeneration of muscle damaged during injury and disease is critical for proper function of the musculoskeletal system. The 4D (3D + time) data sets generated by this Driving Biomedical Project of diaphragm development limb muscle development and regeneration will be broadly useful to the research community.

This Driving Biomedical Project interacts extensively with Visualization and Image and Geometric Analysis TR&Ds to address several major technical challenges in the analysis of 4D confocal and multiphoton data sets. Of primary concern is the size of the data sets. The Kardon Lab continues to develop new genetic tools to fluorescently label tissues and as their ability to image more tissues simultaneously and to image them while developing or regenerating ex vivo grows, the size of the data sets increases exponentially. Current confocal data sets are generally in the range of 5 GB, but 4D datasets based on the new multiphoton data sets are 1–5 TB. The Image and Geometric Analysis and Visualization TR&Ds are addressing the required scalability of software tools through their development of level-of-detail and streaming methods for such large datasets. Another serious need addressed by the TR&Ds is the lack of quantitative tools to analyze such large image datasets. For instance, quantification of differences in the number and proliferative status of cells or size and shape of tissues between mutant and control mice is critical for understanding how muscle develops and regenerates. The Image and Geometric Analysis and Visualization TR&Ds develop interactive methods for localization, segmentation, and quantification of collective cell migration.