Cell State Transitions Beyond the Small-Noise Limit
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866914581003108352 |
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| author | Wei, Jianzhe Zhu, Jingwen Chu, Pan Luo, Liang Fu, Xiongfei |
| author_facet | Wei, Jianzhe Zhu, Jingwen Chu, Pan Luo, Liang Fu, Xiongfei |
| contents | State transitions are fundamental in biological systems but challenging to observe directly. Here, we present the first single-cell observation of state transitions in a synthetic bacterial genetic circuit. Using a mother machine, we tracked over 1007 cells for 27 hours. First-passage analysis and dynamical reconstruction reveal that transitions occur outside the small-noise regime, challenging the applicability of classical Kramers' theory. The process lacks a single characteristic rate, questioning the paradigm of transitions between discrete cell states. We observe significant multiplicative noise that distorts the effective potential landscape yet increases transition times. These findings necessitate theoretical frameworks for biological state transitions beyond the small-noise assumption. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_07797 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Cell State Transitions Beyond the Small-Noise Limit Wei, Jianzhe Zhu, Jingwen Chu, Pan Luo, Liang Fu, Xiongfei Statistical Mechanics Cell Behavior Molecular Networks State transitions are fundamental in biological systems but challenging to observe directly. Here, we present the first single-cell observation of state transitions in a synthetic bacterial genetic circuit. Using a mother machine, we tracked over 1007 cells for 27 hours. First-passage analysis and dynamical reconstruction reveal that transitions occur outside the small-noise regime, challenging the applicability of classical Kramers' theory. The process lacks a single characteristic rate, questioning the paradigm of transitions between discrete cell states. We observe significant multiplicative noise that distorts the effective potential landscape yet increases transition times. These findings necessitate theoretical frameworks for biological state transitions beyond the small-noise assumption. |
| title | Cell State Transitions Beyond the Small-Noise Limit |
| topic | Statistical Mechanics Cell Behavior Molecular Networks |
| url | https://arxiv.org/abs/2510.07797 |