Emergence of division of labor in tissues through cell interactions and spatial cues.
Cell Rep
; 42(5): 112412, 2023 05 30.
Article
em En
| MEDLINE
| ID: mdl-37086403
ABSTRACT
Most cell types in multicellular organisms can perform multiple functions. However, not all functions can be optimally performed simultaneously by the same cells. Functions incompatible at the level of individual cells can be performed at the cell population level, where cells divide labor and specialize in different functions. Division of labor can arise due to instruction by tissue environment or through self-organization. Here, we develop a computational framework to investigate the contribution of these mechanisms to division of labor within a cell-type population. By optimizing collective cellular task performance under trade-offs, we find that distinguishable expression patterns can emerge from cell-cell interactions versus instructive signals. We propose a method to construct ligand-receptor networks between specialist cells and use it to infer division-of-labor mechanisms from single-cell RNA sequencing (RNA-seq) and spatial transcriptomics data of stromal, epithelial, and immune cells. Our framework can be used to characterize the complexity of cell interactions within tissues.
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Base de dados:
MEDLINE
Assunto principal:
Comunicação Celular
/
Sinais (Psicologia)
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article