Authors: Lu Zhang, Gang Xue, Xiaolin Zhou, Jiandong Huang, Zhiyuan Li.
Journal: PLOS COMPUTATIONAL BIOLOGY
DOI: 10.1371/journal.pcbi.1011882
Link: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011882
Published: June 05, 2024
Document Type: Research Article
Abstract:
In embryonic development and organogenesis, cells sharing identical genetic codes acquire diverse gene expression states in a highly reproducible spatial distribution, crucial for multicellular formation and quantifiable through positional information. To understand the spontaneous growth of complexity, we constructed a one-dimensional division-decision model, simulating the growth of cells with identical genetic networks from a single cell. Our findings highlight the pivotal role of cell division in providing positional cues, escorting the system toward states rich in information. Moreover, we pinpointed lateral inhibition as a critical mechanism translating spatial contacts into gene expression. Our model demonstrates that the spatial arrangement resulting from cell division, combined with cell lineages, imparts positional information, specifying multiple cell states with increased complexity—illustrated through examples in C.elegans. This study constitutes a foundational step in comprehending developmental intricacies, paving the way for future quantitative formulations to construct synthetic multicellular patterns.
Author summary:
Embryonic development shapes our bodies from a single cell, determining the placement of the head and tail. But how do cells, all sharing the same genetic code, precisely know what to become? Our mathematical model cracks this code. Envision your information being provided by your neighbors and your ’mom’—the division lineage. Then, appropriate regulatory networks (such as lateral inhibition, the most effective network motif) transform this information into diverse yet robust gene expressions. This math model helps us see the rules behind spontaneously growing complexity, guiding us to create new patterns of cells. It’s a big step in understanding how bodies form and opens doors to building cool new structures.