Engineers want a controllable force generator for synthetic-cell concepts such as targeted drug delivery. Biological cells commonly use ATP to power motors, but some single-celled ciliates rely on a calcium pulse to trigger an ultrafast contraction, with ATP used later to recharge calcium stores. A team led by Georgia Tech adapted that ciliate strategy to control artificial protein networks without ATP-powered motors.
The researchers produced and purified Tetrahymena thermophila calcium-binding protein 2 (Tcb2). In vitro the protein forms a fibrous network that assembles and contracts when calcium is released. To control timing and location they used a light-sensitive calcium chelator — a "cage" molecule that holds calcium until illuminated — and projected patterned illumination so the network assembled and contracted in matching star and circle shapes. Pulsed light allowed repeated cycles: the network contracted many times and drove movement of microscopic particles, demonstrating a route to controllable actuation for synthetic delivery systems.
The team also developed a computer model and combined simulations with reinforcement learning to discover light patterns that make the network push or pull on demand. As one researcher put it, “The light cleaves a ‘cage’ molecule holding calcium, releasing calcium only where the pattern is projected.” The work came from Saad Bhamla’s bioinspired engineering lab and the study was funded in part by the National Science Foundation.
Difficult words
- ciliate — single-celled organism with hair-like ciliaciliates
- calcium chelator — molecule that binds and holds calcium ions
- in vitro — in a controlled lab environment outside an organism
- actuation — action of causing movement or mechanical force
- reinforcement learning — computer method that learns by trial and reward
- ultrafast — extremely quick, happening in a very short time
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Discussion questions
- How could controllable actuation in synthetic cells improve targeted drug delivery? Give two possible benefits or challenges.
- What are the advantages of using a light-sensitive method rather than ATP-powered motors for artificial protein systems?
- In what ways might reinforcement learning help researchers design experiments with biological networks like the one in this study?
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