Acousto-optogenetics bandpass stabilizer: A programmable platform for mapping single-cell phenotypic life trajectories.

Photobleaching-induced signal decay undermines the accuracy of fluorescence-based drug screening across multiple disease models (e.g., HER2/EGFR-targeted therapies). Traditional phototoxicity mitigation strategies, primarily through reduced illumination, inevitably compromise imaging resolution and further providing false positive/false negative. Here, we introduce an innovative active photobleaching intervention strategy to solve these problems with the potential for broad applicability across a wide range of cell species. We employ the ultra-low-frequency (500-2000 Hz) acoustic modulation to control 3D cellular rotation (precisely in x-y/y-z planes) with a linearly tunable rotational speed, establishing the first quantitative framework linking acoustic parameters to photobleaching kinetics. Our results indicate that acoustic frequency scanning exerts a bandpass-filter effect on photobleaching half-life, peaking at 1500 Hz and achieving approximately 30-fold fluorescence preservation compared to static conditions. By harnessing our newly developed Acousto-Optogenetics Bandpass Stabilizer, we transform phototoxicity into a tunable parameter, thereby enabling artifact-free drug response analysis. While maintaining maximal photostability, frequency-division multiplexing further permits real-time calcium flux monitoring during optogenetic activation. Complementing this, we engineer FlowMind, an AI-powered software, to automate single-cell dynamic library processing. As proof of concept, screening calcium channel blockers under optimal photostability conditions reveals significant variations in drug screening sensitivity. By integrating acoustic modulation with optogenetics, this paradigm not only pioneers the programmable control of photostability via acoustics, but also catalyzes a transformative shift in precision oncology, heralding a new era of patient-tailored therapeutic regimens with enhanced clinical predictability.