Seeing through bones in 3D enabled us to better understand how stem cell populations respond to a drug intended to treat osteoporosis. By keeping the specimen intact and fluorescently tagging cells of interest, we were able to understand magnitude of cell proliferation in mouse femur, tibia, and vertebral column.
Advances in 3-D imaging and tissue clearing - a class of methods to make extracted organs physically transparent for analysis - are responsible for generating vast amounts of data, with single cleared organs reaching hundreds of gigabytes. In a project led by Alon Greenbaum and Ken Chan in Viviana Gradinaru's lab at Caltech, they extended these methods to work on hard, opaque bones, so that single bones could be imaged in 3-D to interrogate the cells inside. We provided computational assistance via scripting, image processing, and machine learning techniques to automate and aid in image analysis, cell counting, and statistical analysis.
In particular, we work on the following:
Automated pipelines for manipulating large bone image files to accommodate:
Stitching using Terastitcher
Image processing using Matlab
Visualization using Imaris
Automated cell counting using image statistics and neural network classification
Simulations of stereology experiments to validate the benefits of 3D imaging
Cell counting and defining regions of interest
Greenbaum, A., Chan, K. Y., Dobreva, T., Brown, D., Balani, D. H., Boyce, R., … Gradinaru, V. (2017). Bone CLARITY: Clearing, imaging, and computational analysis of osteoprogenitors within intact bone marrow. Science Translational Medicine, 9(387), eaah6518. https://doi.org/10.1126/scitranslmed.aah6518
A. Greenbaum, K. Chan, T. Dobreva, D. Brown, D. H. Balani, C. Challis, A. Lignell, L. Cai, H. M. Kronenberg, V. Gradinaru. "Tissue clearing of bones for enhanced optical and molecular access to osseous neuro-immune environments using PACT-deCAL". Session No. 468. Neuroscience 2016 Abstracts. San Diego, CA: Society for Neuroscience, 2016. Online.