We have recently developed a prototype system for long-term monitoring of single-cell behaviors in complex tissues. Our system comes from the synergistic integration and optimization of two leading technologies in microscopy and computational cell tracking: the inverted selective plane illumination microscope (iSPIM) and the StarryNite software package. We have demonstrated order-of-magnitude improvements on virtually all fronts compared to the standard technologies in use, notably imaging speed, reduction of phototoxicity, accuracy of cell tracking, and lower demand for computing power, all achieved at a reduced cost with comparable or better image quality. Our system has been applied to multiple model organisms as well as cell culture, demonstrating its versatility.
We aim to bring the system to maturity and into the hands of the research community as a powerful and versatile tool for single-cell studies in complex, differentiating cell populations.
Long-term monitoring of single cells in the context of complex tissues is crucial for the understanding of cell biological changes in physiological contexts and disease. Here we propose to develop a mature system to monitor individual cells in complex tissues based on a novel microscopy and computer-based automated image analysis system. Our system will provide a powerful tool to enable the research community to achieve better understanding on a wide range of health relative questions at unprecedented temporal and spatial resolution, from birth defects to brain function and viral infection.
|Katzman, Braden; Tang, Doris; Santella, Anthony et al. (2018) AceTree: a major update and case study in the long term maintenance of open-source scientific software. BMC Bioinformatics 19:121|
|Shah, Pavak Kirit; Santella, Anthony; Jacobo, Adrian et al. (2017) An In Toto Approach to Dissecting Cellular Interactions in Complex Tissues. Dev Cell 43:530-540.e4|
|Roy, Debasmita; Michaelson, David; Hochman, Tsivia et al. (2016) Cell cycle features of C. elegans germline stem/progenitor cells vary temporally and spatially. Dev Biol 409:261-271|
|Santella, Anthony; Kovacevic, Ismar; Herndon, Laura A et al. (2016) Digital development: a database of cell lineage differentiation in C. elegans with lineage phenotypes, cell-specific gene functions and a multiscale model. Nucleic Acids Res 44:D781-5|
|Kumar, Abhishek; Christensen, Ryan; Guo, Min et al. (2016) Using Stage- and Slit-Scanning to Improve Contrast and Optical Sectioning in Dual-View Inverted Light Sheet Microscopy (diSPIM). Biol Bull 231:26-39|
|Stavoe, Andrea K H; Hill, Sarah E; Hall, David H et al. (2016) KIF1A/UNC-104 Transports ATG-9 to Regulate Neurodevelopment and Autophagy at Synapses. Dev Cell 38:171-85|
|Elewa, Ahmed; Shirayama, Masaki; Kaymak, Ebru et al. (2015) POS-1 Promotes Endo-mesoderm Development by Inhibiting the Cytoplasmic Polyadenylation of neg-1 mRNA. Dev Cell 34:108-18|
|Santella, Anthony; Catena, Raúl; Kovacevic, Ismar et al. (2015) WormGUIDES: an interactive single cell developmental atlas and tool for collaborative multidimensional data exploration. BMC Bioinformatics 16:189|
|Du, Zhuo; Santella, Anthony; He, Fei et al. (2015) The Regulatory Landscape of Lineage Differentiation in a Metazoan Embryo. Dev Cell 34:592-607|
|Du, Zhuo; He, Fei; Yu, Zidong et al. (2015) E3 ubiquitin ligases promote progression of differentiation during C. elegans embryogenesis. Dev Biol 398:267-79|
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