Research ArticleDevelopmental Biology

Serotonergic regulation of melanocyte conversion: A bioelectrically regulated network for stochastic all-or-none hyperpigmentation

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Science Signaling  06 Oct 2015:
Vol. 8, Issue 397, pp. ra99
DOI: 10.1126/scisignal.aac6609

Driving melanocyte proliferation and invasion

Melanocytes play key physiological functions; one of the easiest to see is pigmentation. In frogs, the number, distribution, and shape of melanocytes are determined by a subpopulation of cells called “instructor cells,” which are regulated by changes in membrane potential. Forced depolarization of instructor cells can result in excessive melanocyte proliferation, altered melanocyte cell shape, and abnormal migration of melanocytes into multiple tissues, which results in darkly colored tadpoles through a stochastic all-or-none process; the embryos are either normally pigmented or hyperpigmented. Lobikin et al. unraveled the molecular signaling pathway and physiological circuit that mediates this melanocyte conversion process, and they used computational approaches to explain how this all-or-none, stochastic process can occur.


Experimentally induced depolarization of resting membrane potential in “instructor cells” in Xenopus laevis embryos causes hyperpigmentation in an all-or-none fashion in some tadpoles due to excess proliferation and migration of melanocytes. We showed that this stochastic process involved serotonin signaling, adenosine 3′,5′-monophosphate (cAMP), and the transcription factors cAMP response element–binding protein (CREB), Sox10, and Slug. Transcriptional microarray analysis of embryos taken at stage 15 (early neurula) and stage 45 (free-swimming tadpole) revealed changes in the abundance of 45 and 517 transcripts, respectively, between control embryos and embryos exposed to the instructor cell–depolarizing agent ivermectin. Bioinformatic analysis revealed that the human homologs of some of the differentially regulated genes were associated with cancer, consistent with the induced arborization and invasive behavior of converted melanocytes. We identified a physiological circuit that uses serotonergic signaling between instructor cells, melanotrope cells of the pituitary, and melanocytes to control the proliferation, cell shape, and migration properties of the pigment cell pool. To understand the stochasticity and properties of this multiscale signaling system, we applied a computational machine-learning method that iteratively explored network models to reverse-engineer a stochastic dynamic model that recapitulated the frequency of the all-or-none hyperpigmentation phenotype produced in response to various pharmacological and molecular genetic manipulations. This computational approach may provide insight into stochastic cellular decision-making that occurs during normal development and pathological conditions, such as cancer.

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