Phase-Locked Signals Elucidate Circuit Architecture of an Oscillatory Pathway

This paper introduces the concept of phase-locking analysis of oscillatory cellular signaling systems to elucidate biochemical circuit architecture. Phase-locking is a physical phenomenon that refers to a response mode in which system output is synchronized to a periodic stimulus; in some instances, the number of responses can be fewer than the number of inputs, indicative of skipped beats. While the observation of phase-locking alone is largely independent of detailed mechanism, we find that the properties of phase-locking are useful for discriminating circuit architectures because they reflect not only the activation but also the recovery characteristics of biochemical circuits. Here, this principle is demonstrated for analysis of a G-protein coupled receptor system, the M3 muscarinic receptor-calcium signaling pathway, using microfluidic-mediated periodic chemical stimulation of the M3 receptor with carbachol and real-time imaging of resulting calcium transients. Using this approach we uncovered the potential importance of basal IP3 production, a finding that has important implications on calcium response fidelity to periodic stimulation. Based upon our analysis, we also negated the notion that the Gq-PLC interaction is switch-like, which has a strong influence upon how extracellular signals are filtered and interpreted downstream. Phase-locking analysis is a new and useful tool for model revision and mechanism elucidation; the method complements conventional genetic and chemical tools for analysis of cellular signaling circuitry and should be broadly applicable to other oscillatory pathways

Manipulation and Elucidation of Intracellular Signaling Mechanisms through Periodic Stimulation Using Microfluidics.

Orchestration of cellular operations often requires faithful conversion of chemical signals from the environment into intracellular messages that cells must decipher with their internal protein machinery. Intracellular messages are conveyed by chemical messengers, such as calcium. Signals from the environment and chemical messengers are regularly frequency-encoded: biological information is stored in the periodicity, not just the amplitude, of signals. Despite the wealth of mathematical models available for predicting and interpreting the mechanisms mediating the conversion of extracellular signals into messenger signals, there is a paucity of experimental setups enabling manipulation and further elucidation of this crucial conversion process. These limitations were overcome by developing a microfluidic platform able to deliver periodic extracellular chemical signals to mammalian cells and amenable to real-time imaging of messenger signal dynamics. While microfluidic-mediated periodic chemical stimulation afforded greater control over the timing of calcium messenger signals, compared to continuous chemical stimulation, fidelity was compromised; however, this deficiency was surmounted to a degree by modulating periodic stimulation parameters. These results provided concrete strategies for effectively manipulating intracellular calcium signals, using physiologically-relevant stimulant concentrations and periodicities. Our theoretical results predicted that small changes in cellular components could yield precipitous changes in calcium response fidelity, showing that fidelity can be highly sensitive to both stimulation and intrinsic parameters. By demonstrating experimentally that these cellular components can dramatically modulate the fidelity of intracellular signals, these studies provide insight into how the body achieves high fidelity control of signaling. Compromised fidelity of intracellular signals, while potentially harmful, provided valuable insight into the chemical mechanisms mediating the conversion of extracellular signals into calcium signals. limitations, nor predict the effects of altering periodic stimulation parameters on the calcium response fidelity. Simple revisions to model mechanisms were able to account for all our experimental results, demonstrating that this approach is powerful for evaluating models and elucidating signaling mechanisms. Collectively, this thesis research delineated that by theoretically and experimentally analyzing cells’ abilities to convert periodic chemical signals into intracellular chemical messengers, manipulation and elucidation of cellular signaling mechanisms was achieved.Ph.D.Biomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/77906/1/andreja_1.pd

COSMOS: a platform for real-time morphology-based, label-free cell sorting using deep learning

Abstract Cells are the singular building blocks of life, and a comprehensive understanding of morphology, among other properties, is crucial to the assessment of underlying heterogeneity. We developed Computational Sorting and Mapping of Single Cells (COSMOS), a platform based on Artificial Intelligence (AI) and microfluidics to characterize and sort single cells based on real-time deep learning interpretation of high-resolution brightfield images. Supervised deep learning models were applied to characterize and sort cell lines and dissociated primary tissue based on high-dimensional embedding vectors of morphology without the need for biomarker labels and stains/dyes. We demonstrate COSMOS capabilities with multiple human cell lines and tissue samples. These early results suggest that our neural networks embedding space can capture and recapitulate deep visual characteristics and can be used to efficiently purify unlabeled viable cells with desired morphological traits. Our approach resolves a technical gap in the ability to perform real-time deep learning assessment and sorting of cells based on high-resolution brightfield images