Author_Institution :
Math. Dept., British Columbia Inst. of Technol., Burnaby, BC, Canada
Abstract :
Fruit flies serve as a model for understanding the genetic regulation involved in specifying the complex body plans of higher animals. The head-to-tail (anterior-posterior) axis of the fly (Drosophila) is established in the first hours of development. Maternally supplied factors form concentration gradients which direct embryonic (zygotic) genes where to be activated to express proteins. These protein patterns specify the positions and cell types of the body´s tissues. Recent research has shown, comparing between embryos, that the zygotic gene products are much more precisely positioned than the maternal gradients, indicating an embryonic error reduction mechanism. Within embryos, there is the additional aspect that DNA and mRNA operate at very low copy number, and the associated high relative noise has the potential to strongly affect protein expression patterns. In recent work, we have focused on the noise aspects of positional specification within individual embryos. We simulate activation of hunchback (hb), a primary target of the maternal Bicoid (Bcd) protein gradient, which forms an expression pattern dividing the embryo into anterior and posterior halves. We use a master equation approach to simulate the stochastic dynamics of hb regulation, using the known details of the hb promoter, the region of DNA responsible for transcribing hb mRNA. This includes the binding/unbinding of Bcd molecules at the promoter, hb transcription, subsequent translation to Hb protein, binding/unbinding of Hb at the promoter (self-regulation), and diffusion of the Bcd and Hb proteins. Model parameters were set by deterministically matching large scale pattern features for a series of experimental expression patterns: wild-type (WT) embryos; hb mutants lacking self-regulation; and constructs in which portions of the hb promoter were used to express a reporter gene (lacZ). The model was then solved stochastically to predict the noise output in these different experiments. In subsequ- - ent noise measurements we experimentally corroborated a number of the predictions. These include that mRNA is noisier than protein, and that Hb self-regulation reduces noise. Results indicate that WT (self-regulatory) Hb output noise is predominantly dependent on the transcription and translation dynamics of its own expression, and is uncorrelated with Bcd fluctuations. This contradicts prior work, which had assumed a complete dependence of Hb fluctuations on Bcd fluctuations. In the constructs and mutant, which lack self-regulation, we find that increasing the number and strength of Bcd binding sites (there are 6 in the core hb promoter) provides a rudimentary level of noise reduction. The model is robust to the various Bcd binding site numbers seen across different fly species. New directions in the project include incorporating a known inhibitor of hb, Krüppel, into the model to study its effect on the noise dynamics. Our study has identified particular ways in which hb output noise is controlled. Since these involve common modes of gene regulation (e.g. multiple regulatory sites, self-regulation), these results contribute to the general understanding of the reproducibility and determinacy of spatial patterning in early development.
Keywords :
DNA; biochemistry; biological tissues; cellular biophysics; fluctuations; genetics; genomics; master equation; molecular biophysics; molecular configurations; proteins; stochastic processes; DNA expression; Drosophila; anterior-posterior axis; binding sites; body tissues; cell types; direct embryonic genes; embryonic spatial patterning; fruit fly; gene expression noise; genetic regulation; head-to-tail axis; hunchback activation; mRNA transcription; master equation; maternal Bicoid protein gradient; noise dynamics; protein expression pattern; stochastic dynamics; stochastic process; zygotic genes; DNA; Embryo; Gene expression; Mathematical model; Noise; Proteins; RNA; Drosophila; embryo development; gene regulation; spatial pattern; transcription noise;