From Toggle to Tuning: Controlling Turing Patterns in Gene Circuits
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915647064113152 |
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| author | Matas-Gil, Antonio Endres, Robert G. |
| author_facet | Matas-Gil, Antonio Endres, Robert G. |
| contents | Controlling spatial patterns in synthetic biological systems remains challenging due to poor parameter robustness and limited experimental tunability. We introduce two complementary mechanisms-the pattern switch and the pattern dial-to systematically control Turing pattern formation in gene circuits. The switch toggles pattern onset via a single parameter, while the dial enables transitions between distinct pattern types using weakly nonlinear amplitude equations. Analyzing network size reveals a key trade-off: small networks are easier to control but less robust, while larger networks gain robustness at the cost of tunability-suggesting a sweet spot for both evolvability and designability. Our results offer practical design rules for engineering programmable patterns in living systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_01652 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | From Toggle to Tuning: Controlling Turing Patterns in Gene Circuits Matas-Gil, Antonio Endres, Robert G. Biological Physics Mathematical Physics Dynamical Systems Pattern Formation and Solitons Quantitative Methods Controlling spatial patterns in synthetic biological systems remains challenging due to poor parameter robustness and limited experimental tunability. We introduce two complementary mechanisms-the pattern switch and the pattern dial-to systematically control Turing pattern formation in gene circuits. The switch toggles pattern onset via a single parameter, while the dial enables transitions between distinct pattern types using weakly nonlinear amplitude equations. Analyzing network size reveals a key trade-off: small networks are easier to control but less robust, while larger networks gain robustness at the cost of tunability-suggesting a sweet spot for both evolvability and designability. Our results offer practical design rules for engineering programmable patterns in living systems. |
| title | From Toggle to Tuning: Controlling Turing Patterns in Gene Circuits |
| topic | Biological Physics Mathematical Physics Dynamical Systems Pattern Formation and Solitons Quantitative Methods |
| url | https://arxiv.org/abs/2512.01652 |