The electric sense appears in a variety of animals, from the shark to the platypus, and it facilitates short-range prey detection where environments limit sight. Typically, hundreds or thousands of sensors work in concert. In skates, rays, and sharks, each electrosensor includes a small, innervated bulb, with a thin, gel-filled canal leading to a surface pore. While experiments have mapped single electrosensor activity, the mechanisms that integrate neural input from multiple electrosensors are still largely unknown. Here, we model the response of a precisely mapped subset of electrosensors responding in concert for a skate moving near stationary prey. Just as two ears help locate sound via time and intensity differences, we ask how a bilateral electrosensor array can contribute to electrical scene analysis. Our results show that the sensor array provides rich data for precise prey location, tuned by the morphology to render certain events, like the point of closest approach, “loud and clear.” This proof of principle makes a significant step in understanding the electric sense processing, and we recommend future experiments to compare and assess functions for the diversity of arrays found in other sharks and rays.
Gene expression is a process that is inherently stochastic because of the low number of molecules that are involved. In recent years it has become possible to measure the amount of stochasticity in gene expression, which has inspired a debate about the importance of stochasticity in gene expression. Little attention, however, has been paid to stochasticity in gene expression from an evolutionary perspective. We studied the evolutionary consequences of stochastic gene expression in one of the best-known systems of genetic regulation, the lac operon of E. coli, which regulates lactose uptake and metabolism. We used a computational approach, in which we let cells evolve their lac operon promoter function in a fluctuating, spatially explicit, environment. Cells can in this way adapt to the environment, but also change the amount of stochasticity in gene expression. We find that cells evolve their repressed transcription rates to higher values in a stochastic model than in a deterministic model. Higher repressed transcription rates means less stochasticity, and, hence, these cells appear to avoid stochastic gene expression in this particular system. We find that this can be explained by the fact that stochastic gene expression causes a larger delay in lactose uptake, compared with deterministic gene expression.
Programs of ontogenetic development and regeneration share many components. Differences in genetic requirements between regeneration and development may identify mechanisms specific to the stem cells that maintain cell populations in postembryonic stages, or identify other regeneration-specific functions. Here, we utilize a forward genetic approach that takes advantage of single cell type ablation and regeneration to isolate mechanisms specific to regeneration of the zebrafish melanocyte. Upon chemical ablation of melanocytes, zebrafish larvae reconstitute their larval pigment pattern from undifferentiated precursors or stem cells. We isolated two zebrafish mutants that develop embryonic melanocytes normally but fail to regenerate their melanocytes upon ablation. This phenotype suggests the regeneration-specific roles of the mutated genes. We further identified the mutations in gfpt1 and skiv2l2 and show their stage-specific roles in melanocyte regeneration. Interestingly, these mutants identify regeneration-specific functions not only in early stages of the regeneration process (skiv2l2), but also in late stages of differentiation of the regenerating melanocyte (gfpt1). We suggest that mechanisms of regeneration identified in this mutant screen may reveal fundamental differences between the mechanisms that establish differentiated cells during embryogenesis and those involved in larval or adult growth.