Dataset Information

Long-Term, Stochastic Editing of Regenerative Anatomy via Targeting Endogenous Bioelectric Gradients.

ABSTRACT: We show that regenerating planarians' normal anterior-posterior pattern can be permanently rewritten by a brief perturbation of endogenous bioelectrical networks. Temporary modulation of regenerative bioelectric dynamics in amputated trunk fragments of planaria stochastically results in a constant ratio of regenerates with two heads to regenerates with normal morphology. Remarkably, this is shown to be due not to partial penetrance of treatment, but a profound yet hidden alteration to the animals' patterning circuitry. Subsequent amputations of the morphologically normal regenerates in water result in the same ratio of double-headed to normal morphology, revealing a cryptic phenotype that is not apparent unless the animals are cut. These animals do not differ from wild-type worms in histology, expression of key polarity genes, or neoblast distribution. Instead, the altered regenerative bodyplan is stored in seemingly normal planaria via global patterns of cellular resting potential. This gradient is functionally instructive, and represents a multistable, epigenetic anatomical switch: experimental reversals of bioelectric state reset subsequent regenerative morphology back to wild-type. Hence, bioelectric properties can stably override genome-default target morphology, and provide a tractable control point for investigating cryptic phenotypes and the stochasticity of large-scale epigenetic controls.

SUBMITTER: Durant F

PROVIDER: S-EPMC5443973 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Long-Term, Stochastic Editing of Regenerative Anatomy via Targeting Endogenous Bioelectric Gradients.

Durant Fallon F Morokuma Junji J Fields Christopher C Williams Katherine K Adams Dany Spencer DS Levin Michael M

Biophysical journal 20170501 10

We show that regenerating planarians' normal anterior-posterior pattern can be permanently rewritten by a brief perturbation of endogenous bioelectrical networks. Temporary modulation of regenerative bioelectric dynamics in amputated trunk fragments of planaria stochastically results in a constant ratio of regenerates with two heads to regenerates with normal morphology. Remarkably, this is shown to be due not to partial penetrance of treatment, but a profound yet hidden alteration to the animal ...[more]

PMID: 28538159

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Project description:Depolarization of resting membrane potential in select cells in Xenopus larvae induces striking hyperpigmentation due to dysregulation of melanocytes. Here, we show that this non-cell-autonomous process is mediated by cAMP, CREB, and the transcription factors Sox10 and Slug. Our microarray analysis reveals specific transcripts responsive to Vmem levels within a few hours of depolarization, and a set of 517 transcripts whose expression remains altered during the full hyperpigmented phenotype over a week later, linking instructor cell-depolarization to a range of developmental processes and disease states. We also show that voltage-dependent conversion of melanocytes involves the MSH-secreting melanotrope cells of the pituitary, and formulate a model for the molecular pathway linking the bioelectric properties of melanocyte cellsâ microenvironment in vivo to the genetic and cellular changes induced in this melanoma-like phenotype. Remarkably, the phenotype is all-or-none: each individual animal either undergoes melanocyte conversion or not, as a whole. This group decision is stochastic, resulting in varying percentages of hyperpigmented individuals for a given experimental treatment. To understand the stochasticity and dynamic properties of this complex signaling system, we developed a novel computational method that automates the reverse-engineering of stochastic dynamic signaling models. We used this method to discover a network model that quantitatively explained our complex dataset, and even made correct predictions for new experiments that we validated in vivo. Taken together, these data (1) reveal new molecular details about a novel trigger of metastatic-like developmental cell behavior in vivo, (2) suggest new targets for biomedical intervention, and (3) demonstrate proof-of-principle of a computational method for understanding stochastic decision-making by cells during embryonic development and metastasis. Gene expression analysis was performed using samples treated with ivermectin from NF stage 10 onwards, collected at two developmental stages; stage 15 (early neurula) and stage 45 (free-swimming tadpole). Embryos were collected in eppendorf tubes (N=50 for stage 15, N=5 for stage 45) and frozen at -80Â°C. RNA extraction and microarray analysis were performed by the Beth Israel Deaconess Medical Center Genomics and Proteomics Center (Harvard) according to standard Affymetrix protocol, using a high throughput hybridization and scanning system. Microarray hybridization was performed using the Affy 3â IVT Express Kit. Fragmented and biotin labeled and amplified RNA was hybridized to the GeneChipÂ® Xenopus laevis Genome 2.0 array as per manufacturerâs protocol. The Affymetrix GeneChipÂ® X. laevis Genome 2.0 Array, has 32,400 probe sets representing more than 29,900 X. laevis transcripts.

Dataset Information

Long-Term, Stochastic Editing of Regenerative Anatomy via Targeting Endogenous Bioelectric Gradients.

Publications

Long-Term, Stochastic Editing of Regenerative Anatomy via Targeting Endogenous Bioelectric Gradients.

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