Biological Networks Regulating Cell Fate Choice Are Minimally Frustrated
- PMID: 32909810
- DOI: 10.1103/PhysRevLett.125.088101
Biological Networks Regulating Cell Fate Choice Are Minimally Frustrated
Abstract
Characterization of the differences between biological and random networks can reveal the design principles that enable the robust realization of crucial biological functions including the establishment of different cell types. Previous studies, focusing on identifying topological features that are present in biological networks but not in random networks, have, however, provided few functional insights. We use a Boolean modeling framework and ideas from the spin glass literature to identify functional differences between five real biological networks and random networks with similar topological features. We show that minimal frustration is a fundamental property that allows biological networks to robustly establish cell types and regulate cell fate choice, and that this property can emerge in complex networks via Darwinian evolution. The study also provides clues regarding how the regulation of cell fate choice can go awry in a disease like cancer and lead to the emergence of aberrant cell types.
Similar articles
-
Minimal frustration underlies the usefulness of incomplete regulatory network models in biology.Proc Natl Acad Sci U S A. 2023 Jan 3;120(1):e2216109120. doi: 10.1073/pnas.2216109120. Epub 2022 Dec 29. Proc Natl Acad Sci U S A. 2023. PMID: 36580597 Free PMC article.
-
The principles that govern transcription factor network functions in stem cells.Development. 2018 Mar 14;145(6):dev157420. doi: 10.1242/dev.157420. Development. 2018. PMID: 29540464 Review.
-
Pseudo-trajectory inference for identifying essential regulations and molecules in cell fate decisions.J Biol Phys. 2024 Nov 14;51(1):2. doi: 10.1007/s10867-024-09665-3. J Biol Phys. 2024. PMID: 39541052
-
CABeRNET: a Cytoscape app for augmented Boolean models of gene regulatory NETworks.BMC Bioinformatics. 2016 Feb 4;17:64. doi: 10.1186/s12859-016-0914-z. BMC Bioinformatics. 2016. PMID: 26846964 Free PMC article.
-
Systems biology approaches to understanding stem cell fate choice.IET Syst Biol. 2010 Jan;4(1):1-11. doi: 10.1049/iet-syb.2009.0011. IET Syst Biol. 2010. PMID: 20001088 Review.
Cited by
-
Systems biology approach suggests new miRNAs as phenotypic stability factors in the epithelial-mesenchymal transition.J R Soc Interface. 2020 Oct;17(171):20200693. doi: 10.1098/rsif.2020.0693. Epub 2020 Oct 14. J R Soc Interface. 2020. PMID: 33050781 Free PMC article.
-
Decoding the mechanisms underlying cell-fate decision-making during stem cell differentiation by random circuit perturbation.J R Soc Interface. 2020 Aug;17(169):20200500. doi: 10.1098/rsif.2020.0500. Epub 2020 Aug 12. J R Soc Interface. 2020. PMID: 32781932 Free PMC article.
-
Multistability and predominant hybrid phenotypes in a four node mutually repressive network of Th1/Th2/Th17/Treg differentiation.NPJ Syst Biol Appl. 2024 Oct 24;10(1):123. doi: 10.1038/s41540-024-00433-6. NPJ Syst Biol Appl. 2024. PMID: 39448615 Free PMC article.
-
Decoding the coupled decision-making of the epithelial-mesenchymal transition and metabolic reprogramming in cancer.iScience. 2022 Dec 5;26(1):105719. doi: 10.1016/j.isci.2022.105719. eCollection 2023 Jan 20. iScience. 2022. PMID: 36582834 Free PMC article.
-
Observation of universal ageing dynamics in antibiotic persistence.Nature. 2021 Dec;600(7888):290-294. doi: 10.1038/s41586-021-04114-w. Epub 2021 Nov 17. Nature. 2021. PMID: 34789881
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources