{"title":"驱动细胞命运转变的相互关联的反馈回路的工作原理。","authors":"Mubasher Rashid, Abhiram Hegade","doi":"10.1038/s41540-024-00483-w","DOIUrl":null,"url":null,"abstract":"<p><p>Interconnected feedback loops are prevalent across biological mechanisms, including cell fate transitions enabled by epigenetic mechanisms in carcinomas. However, the operating principles of these networks remain largely unexplored. Here, we identify numerous interconnected feedback loops implicated in cell lineage decisions, which we discover to be the hallmarks of lower- and higher-dimensional state space. We demonstrate that networks having higher centrality nodes have restricted state space while those with lower centrality nodes have higher dimensional state space. The topologically distinct networks with identical node or loop counts have different steady-state distributions, highlighting the crucial influence of network structure on emergent dynamics. Further, regardless of topology, networks with autoregulated nodes exhibit multiple steady states, thereby \"liberating\" network dynamics from absolute topological control. These findings unravel the design principles of multistable networks implicated in fate decisions and can have crucial implications in engineering or comprehending multi-fate decision circuits.</p>","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"2"},"PeriodicalIF":3.5000,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11693754/pdf/","citationCount":"0","resultStr":"{\"title\":\"Operating principles of interconnected feedback loops driving cell fate transitions.\",\"authors\":\"Mubasher Rashid, Abhiram Hegade\",\"doi\":\"10.1038/s41540-024-00483-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Interconnected feedback loops are prevalent across biological mechanisms, including cell fate transitions enabled by epigenetic mechanisms in carcinomas. However, the operating principles of these networks remain largely unexplored. Here, we identify numerous interconnected feedback loops implicated in cell lineage decisions, which we discover to be the hallmarks of lower- and higher-dimensional state space. We demonstrate that networks having higher centrality nodes have restricted state space while those with lower centrality nodes have higher dimensional state space. The topologically distinct networks with identical node or loop counts have different steady-state distributions, highlighting the crucial influence of network structure on emergent dynamics. Further, regardless of topology, networks with autoregulated nodes exhibit multiple steady states, thereby \\\"liberating\\\" network dynamics from absolute topological control. These findings unravel the design principles of multistable networks implicated in fate decisions and can have crucial implications in engineering or comprehending multi-fate decision circuits.</p>\",\"PeriodicalId\":19345,\"journal\":{\"name\":\"NPJ Systems Biology and Applications\",\"volume\":\"11 1\",\"pages\":\"2\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2025-01-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11693754/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NPJ Systems Biology and Applications\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1038/s41540-024-00483-w\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICAL & COMPUTATIONAL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NPJ Systems Biology and Applications","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1038/s41540-024-00483-w","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
Operating principles of interconnected feedback loops driving cell fate transitions.
Interconnected feedback loops are prevalent across biological mechanisms, including cell fate transitions enabled by epigenetic mechanisms in carcinomas. However, the operating principles of these networks remain largely unexplored. Here, we identify numerous interconnected feedback loops implicated in cell lineage decisions, which we discover to be the hallmarks of lower- and higher-dimensional state space. We demonstrate that networks having higher centrality nodes have restricted state space while those with lower centrality nodes have higher dimensional state space. The topologically distinct networks with identical node or loop counts have different steady-state distributions, highlighting the crucial influence of network structure on emergent dynamics. Further, regardless of topology, networks with autoregulated nodes exhibit multiple steady states, thereby "liberating" network dynamics from absolute topological control. These findings unravel the design principles of multistable networks implicated in fate decisions and can have crucial implications in engineering or comprehending multi-fate decision circuits.
期刊介绍:
npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology.
We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.