Applied Physics Seminar: " Incoherent inputs enhance robustness of biological oscillators"

Robustness is a critical ability of biological oscillators to function in environmental perturbations. Although central architectures that support robust oscillations have been extensively studied, networks containing the same core vary drastically in their potential to oscillate, and it remains elusive what peripheral modifications to the core contribute to the large variation. We computationally generate a complete atlas of two- and three-node oscillators, to systematically analyze the association between network structures and robustness. We found that, while certain core topologies are essential for producing a robust oscillator, local structures can substantially modulate the degree of the robustness. Most strikingly, local nodes receiving incoherent (positive plus negative) or coherent (both positive or both negative) inputs promote or attenuate the overall network robustness significantly in an additive manner. These motifs are validated in larger-scale networks. Additionally, we found that incoherent inputs are enriched in almost all known natural and synthetic oscillators, suggesting that incoherent inputs may be a generalizable design principle that
promotes oscillatory robustness. Our findings underscore the importance of local modifications besides robust cores, which explain why auxiliary structures not required for oscillation are
evolutionarily conserved, and further suggest simple ways to evolve or design robust oscillators.
Experimentally, we develop an artificial cell-cycle system in microfluidics to quantitatively investigate how network structures are linked to the essential clock functions. We also investigate how
multiple clocks coordinate in essential developmental processes of early zebrafish embryos, including synchronous cleavages and somitogenesis, where we aim to understand how collective
spatio-temporal patterns emerge from complex interactive networks of cells and molecules. We integrate mathematical modeling, time-lapse fluorescence microscopy, and single cell tracking to answer these questions.
We are recruiting! Students who are interested in our work, please
check out our website for further information:
http://www-personal.umich.edu/~qiongy/