Abstract
Programming rapid, repeatable motions in soft materials has remained a challenge in active matter and biomimetic design. Here, we present a light-controlled chemomechanical network based on Tetrahymena thermophila calcium-binding protein 2 (Tcb2), a Ca2+-sensitive contractile protein. These networks—driven by Ca2+-triggered structural rearrangements—exhibit dynamic self-assembly, spatiotemporal growth, and contraction rates comparable to actomyosin systems. By coupling light-sensitive chelators for optically triggered Ca2+ release, we achieve precise growth and repeatable mechanical contractility of Tcb2 networks, revealing emergent phenomena such as boundary-localized active regions and density gradient-driven reversals in motion. A coupled reaction-diffusion and elastic model explains these dynamics, highlighting the interplay between chemical network assembly and mechanical response. We further demonstrate active transport of particles via network-mediated forces in vitro and implement reinforcement learning to program seconds-scale spatiotemporal actuation in silico. These results establish a platform for designing responsive active materials with rapid chemomechanical dynamics and tunable optical control, with applications in synthetic cells, sub-cellular force generation, and programmable biomaterials.
Data availability
Data supporting this study are available in Zenodo (https://doi.org/10.5281/zenodo.18318970101).
Code availability
Code for modeling and reinforcement learning control of Tcb2 network contraction is available via Zenodo (https://doi.org/10.5281/zenodo.18394283102).
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Acknowledgements
We wish to thank Douglas Chalker for providing the Tcb2-GFP-tagged Tetrahymena strain, Heidi Sleister and students for creating the GFP/mCherry versions of Tcb2 and Mary Elting, Fred Chang, Jane Maienschein, and Suri Vaikuntanathan for helpful discussions. A.R.D. acknowledges support from National Science Foundation (NSF) award MCB-2313725 and the University of Chicago Materials Research Science and Engineering Center funded by NSF award DMR-2011854. S.C. acknowledges support from NSF award MCB-2313723 and the David and Lucille Packard Fellowship for Science and Engineering. C.F. acknowledges support from the University of Chicago Data Science Institute (DSI) AI + Science Research Initiative. J.H. acknowledges support from NSF award MCB-2313727 and from the Marshall & Judith Flapan Professorship in Biology. S.B. acknowledges support from NSF award MCB-2313724, National Institutes of Health (NIH) award R35GM142588 and Schmidt Sciences, LLC. The authors acknowledge the University of Chicago’s Research Computing Center for computing resources.
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X.L., C.F., L.C., T.C., N.C., A.R.D., S.C., J.H., S.B. investigation; X.L. and C.F. formal analysis, X.L., C.F., L.C., N.C., A.R.D., S.C., J.H., S.B. methodology; A.R.D., S.C., J.H., S.B. funding acquisition; A.R.D., S.C., J.H., S.B. supervision; X.L. and C.F. writing original draft; X.L., C.F., A.R.D., S.C., J.H., S.B. writing-review and editing.
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Lei, X., Floyd, C., Casas-Ferrer, L. et al. Light-induced assembly and repeatable actuation in Ca2+-driven chemomechanical protein networks. Nat Commun (2026). https://doi.org/10.1038/s41467-026-69651-2
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DOI: https://doi.org/10.1038/s41467-026-69651-2
