Ten years ago, we built a microscope specifically designed to resolve a 10-year old controversy in the field of neurodegenerative disease. The invention, which we call a robotic microscope, tracks living single cells in a high-throughput manner as often and for as long as we want (days, months or more). The longitudinal single- cell datasets that the instrument generated can be analyzed with powerful statistical tools used in engineering and clinical trials known as survival analysis. The combination of longitudinal single-cell data and automated survival analysis enabled us, for the first time, to understand the biological importance of what we saw. Although the microscope was originally developed for hypothesis-driven research, we discovered that the new method is also extraordinarily sensitive and had major implications for high-throughput screening. We estimate that our latest generation robotic microscope is 100-1000-fold more sensitive than commercially available high-throughput systems based on single snapshots. The sensitivity has enabled us to make robust disease models with human induced pluripotent stem cells and to adapt these and other difficult-to-culture primary cells for use in unbiased high-content screens. In turn, this work ledto the discovery of new small molecules that show beneficial therapeutic effects in neuron models of two major neurodegenerative diseases. In this application, we have proposed three aims to develop this promising technology further. First, we are designing and developing a 3rd generation system that incorporates new advances in technology and our experience with the 2nd generation system. The system promises to improve our throughput fivefold and double the sensitivity of our existing system. Second, we will continue the ground-breaking computational work to develop new statistical tools for handling large sets of single-cell longitudinal data, whih will have critical applications for high-content screening. Finally, we will extend the biological applications of the microscope from a focus on elucidating cell autonomous phenomena in single cells to understand cell-cell interactions and the behavior of single cells in complex tissu.
We propose to accelerate the integration and translation of a novel robotic microscope technology that characterizes biological processes at the single-cell level. We have repeatedly shown its power to resolve critical biological questions and to discover new therapeutic targets and therapies. Here, we propose to develop the technology further and to disseminate it widely. First, we will build a 3rd generation system that incorporate myriad technological advances and that is 100-1000-fold more sensitive than commercially available HTS systems. Second, we will develop computational approaches that will enable the valid statistical analyses of the high-throughput longitudinal data we generate. Finally, we will further develop the single-cell capabilities of the instrument to study cell non-autonomous interactions and the behavior of single cells in complex live tissue.
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| Cobb, Melanie M; Ravisankar, Abinaya; Skibinski, Gaia et al. (2018) iPS cells in the study of PD molecular pathogenesis. Cell Tissue Res 373:61-77 |
| Epstein, Irina; Finkbeiner, Steven (2018) The Arc of cognition: Signaling cascades regulating Arc and implications for cognitive function and disease. Semin Cell Dev Biol 77:63-72 |
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| Haston, Kelly M; Finkbeiner, Steven (2016) Clinical Trials in a Dish: The Potential of Pluripotent Stem Cells to Develop Therapies for Neurodegenerative Diseases. Annu Rev Pharmacol Toxicol 56:489-510 |
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| Finkbeiner, Steven; Frumkin, Michael; Kassner, Paul D (2015) Cell-based screening: extracting meaning from complex data. Neuron 86:160-74 |
| Moruno Manchon, Jose Felix; Uzor, Ndidi-Ese; Dabaghian, Yuri et al. (2015) Cytoplasmic sphingosine-1-phosphate pathway modulates neuronal autophagy. Sci Rep 5:15213 |
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