{"title":"在细胞链的物理模型中出现了多种集体运动模式。","authors":"Ying Zhang, Effie E Bastounis, Calina Copos","doi":"10.1038/s41540-025-00529-7","DOIUrl":null,"url":null,"abstract":"<p><p>Collective cell migration is central to processes like development and cancer metastasis. While mechanisms of collective motility are increasingly understood, their classification remains incomplete. Here, we study the migration of small cell chains, namely cohesive pairs. Experiments with Dictyostelium discoideum (Dd) revealed two motility modes: the individual contributor (IC) mode, where each cell generates its own traction dipole, and the supracellular (S) mode, characterized by a single dipole. Dd pairs favored the IC mode, while Madin-Darby canine kidney (MDCK) doublets predominantly used the S mode. A 2D biophysical model recapitulated many experimental observations; the IC mode emerged naturally in ameboid Dd doublets when both cells exerted similar traction stresses, while the S mode dominated with stronger leaders. Contrary to amebas, MDCK-like cell chains showed a bias towards the IC mode when increasing cell-cell adhesion. Extending the model to longer chains, we show its potential for understanding emergent migration patterns across cell types and scales.</p>","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"52"},"PeriodicalIF":3.5000,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12098859/pdf/","citationCount":"0","resultStr":"{\"title\":\"Emergence of multiple collective motility modes in a physical model of cell chains.\",\"authors\":\"Ying Zhang, Effie E Bastounis, Calina Copos\",\"doi\":\"10.1038/s41540-025-00529-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Collective cell migration is central to processes like development and cancer metastasis. While mechanisms of collective motility are increasingly understood, their classification remains incomplete. Here, we study the migration of small cell chains, namely cohesive pairs. Experiments with Dictyostelium discoideum (Dd) revealed two motility modes: the individual contributor (IC) mode, where each cell generates its own traction dipole, and the supracellular (S) mode, characterized by a single dipole. Dd pairs favored the IC mode, while Madin-Darby canine kidney (MDCK) doublets predominantly used the S mode. A 2D biophysical model recapitulated many experimental observations; the IC mode emerged naturally in ameboid Dd doublets when both cells exerted similar traction stresses, while the S mode dominated with stronger leaders. Contrary to amebas, MDCK-like cell chains showed a bias towards the IC mode when increasing cell-cell adhesion. Extending the model to longer chains, we show its potential for understanding emergent migration patterns across cell types and scales.</p>\",\"PeriodicalId\":19345,\"journal\":{\"name\":\"NPJ Systems Biology and Applications\",\"volume\":\"11 1\",\"pages\":\"52\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2025-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12098859/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NPJ Systems Biology and Applications\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1038/s41540-025-00529-7\",\"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/s41540-025-00529-7","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}
Emergence of multiple collective motility modes in a physical model of cell chains.
Collective cell migration is central to processes like development and cancer metastasis. While mechanisms of collective motility are increasingly understood, their classification remains incomplete. Here, we study the migration of small cell chains, namely cohesive pairs. Experiments with Dictyostelium discoideum (Dd) revealed two motility modes: the individual contributor (IC) mode, where each cell generates its own traction dipole, and the supracellular (S) mode, characterized by a single dipole. Dd pairs favored the IC mode, while Madin-Darby canine kidney (MDCK) doublets predominantly used the S mode. A 2D biophysical model recapitulated many experimental observations; the IC mode emerged naturally in ameboid Dd doublets when both cells exerted similar traction stresses, while the S mode dominated with stronger leaders. Contrary to amebas, MDCK-like cell chains showed a bias towards the IC mode when increasing cell-cell adhesion. Extending the model to longer chains, we show its potential for understanding emergent migration patterns across cell types and scales.
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.