Endogenous bioelectrical signaling coordinates cell behaviors toward correct anatomical outcomes. Lack of a model explaining spatialized dynamics of bioelectric states has hindered the understanding of the etiology of some birth defects and the development of predictive interventions. Nicotine, a known neuroteratogen, induces serious defects in brain patterning and learning. Our bio-realistic computational model explains nicotine’s effects via the disruption of endogenous bioelectrical gradients and predicts that exogenous HCN2 ion channels would restore the endogenous bioelectric prepatterns necessary for brain patterning. Voltage mapping in vivo confirms these predictions, and exogenous expression of the HCN2 ion channel rescues nicotine-exposed embryos, resulting in normal brain morphology and molecular marker expression, with near-normal learning capacity. By combining molecular embryology, electrophysiology, and computational modeling, we delineate a biophysical mechanism of developmental brain damage and its functional rescue.
Bio: I am a Research Scientist II at the Allen Discovery Center at Tufts University. My research focus is on understanding how bioelectrical signals (ion fluxes and membrane voltage patterns within somatic cells) control embryonic neural system (brain and eye) development, regeneration, and repair. Using Xeopus laevis (frog) as the model system, my research combines novel biophysical approaches and state-of-art imaging (voltage-reporter dyes and optogenetics) with developmental biology, neurobiology, molecular biology, and computational approaches to discover the basic principles underlying bioelectric control of brain and eye development. This knowledge will give us the capability to use bioelectric signal manipulation for neural regeneration and repair in cases of birth-defects, traumatic injuries, diseases, and cancer (all of which can be seen as issues of loss of shape information). This knowledge will also help develop new pharmaceuticals (drugs targeting ion channels - ionoceuticals) and will have long term impact in bioengineering.