Cyto•IQ: an adaptive cytometer for extracting the noisy dynamics of molecular interactions in live cells

David A. Ball; Stephen E. Moody; Jean Peccoud

doi:10.1117/12.842342

24 February 2010 Cyto•IQ: an adaptive cytometer for extracting the noisy dynamics of molecular interactions in live cells

David A. Ball, Stephen E. Moody, Jean Peccoud

Author Affiliations +

Proceedings Volume 7568, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues VIII; 75681D (2010) https://doi.org/10.1117/12.842342
Event: SPIE BiOS, 2010, San Francisco, California, United States

Abstract

We have developed a fundamentally new type of cytometer to track the statistics of dynamic molecular interactions in hundreds of individual live cells within a single experiment. This entirely new high-throughput experimental system, which we have named Cyto•IQ, reports statistical, rather than image-based data for a large cellular population. Like a flow cytometer, Cyto•IQ rapidly measures several fluorescent probes in a large population of cells to yield a reduced statistical model that is matched to the experimental goals set by the user. However, Cyto•IQ moves beyond flow cytometry by tracking multiple probes in individual cells over time. Using adaptive learning algorithms, we process data in real time to maximize the convergence of the statistical model parameter estimators. Software controlling Cyto•IQ integrates existing open source applications to interface hardware components, process images, and adapt the data acquisition strategy based on previously acquired data. These innovations allow the study of larger populations of cells, and molecular interactions with more complex dynamics, than is possible with traditional microscope-based approaches. Cyto•IQ supports research to characterize the noisy dynamics of molecular interactions controlling biological processes.

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David A. Ball, Stephen E. Moody, and Jean Peccoud "Cyto•IQ: an adaptive cytometer for extracting the noisy dynamics of molecular interactions in live cells", Proc. SPIE 7568, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues VIII, 75681D (24 February 2010); https://doi.org/10.1117/12.842342

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KEYWORDS

Luminescence

Data acquisition

Statistical analysis

Data modeling

Fluorescent proteins

Image segmentation

Molecular interactions

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