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BCIT Citations Collection

Gene expression noise in embryonic spatial patterning
Proceedings of 2011 21st International Conference on Noise and Fluctuations in Toronto, ON, Canada on 12-16 June 2011. 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 subsequent 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., Conference paper, Published.
Gene expression noise in spatial patterning
Positional information in developing embryos is specified by spatial gradients of transcriptional regulators. One of the classic systems for studying this is the activation of the hunchback (hb) gene in early fruit fly (Drosophila) segmentation by the maternally-derived gradient of the Bicoid (Bcd) protein. Gene regulation is subject to intrinsic noise which can produce variable expression. This variability must be constrained in the highly reproducible and coordinated events of development. We identify means by which noise is controlled during gene expression by characterizing the dependence of hb mRNA and protein output noise on hb promoter structure and transcriptional dynamics. We use a stochastic model of the hb promoter in which the number and strength of Bcd and Hb (self-regulatory) binding sites can be varied. Model parameters are fit to data from WT embryos, the self-regulation mutant hb(14F), and lacZ reporter constructs using different portions of the hb promoter. We have corroborated model noise predictions experimentally. The results indicate that WT (self-regulatory) Hb output noise is predominantly dependent on the transcription and translation dynamics of its own expression, rather than on Bcd fluctuations. The constructs and mutant, which lack self-regulation, indicate that the multiple Bcd binding sites in the hb promoter (and their strengths) also play a role in buffering noise. The model is robust to the variation in Bcd binding site number across a number of fly species. This study identifies particular ways in which promoter structure and regulatory dynamics reduce hb output noise. Insofar as many of these are common features of genes (e.g. multiple regulatory sites, cooperativity, self-feedback), the current results contribute to the general understanding of the reproducibility and determinacy of spatial patterning in early development., Peer-reviewed article, Publisher. Received July 4, 2010; Accepted December 28, 2010; Published February 3, 2011.
Mid-embryo patterning and precision in Drosophila segmentation
In early development, genes are expressed in spatial patterns which later define cellular identities and tissue locations. The mechanisms of such pattern formation have been studied extensively in early Drosophila (fruit fly) embryos. The gap gene hunchback (hb) is one of the earliest genes to be expressed in anterior-posterior (AP) body segmentation. As a transcriptional regulator for a number of downstream genes, the spatial precision of hb expression can have significant effects in the development of the body plan. To investigate the factors contributing to hb precision, we used fine spatial and temporal resolution data to develop a quantitative model for the regulation of hb expression in the mid-embryo. In particular, modelling hb pattern refinement in mid nuclear cleavage cycle 14 (NC14) reveals some of the regulatory contributions of simultaneously-expressed gap genes. Matching the model to recent data from wild-type (WT) embryos and mutants of the gap gene Krüppel (Kr) indicates that a mid-embryo Hb concentration peak important in thoracic development (at parasegment 4, PS4) is regulated in a dual manner by Kr, with low Kr concentration activating hb and high Kr concentration repressing hb. The processes of gene expression (transcription, translation, transport) are intrinsically random. We used stochastic simulations to characterize the noise generated in hb expression. We find that Kr regulation can limit the positional variability of the Hb mid-embryo border. This has been recently corroborated in experimental comparisons of WT and Kr- mutant embryos. Further, Kr regulation can decrease uncertainty in mid-embryo hb expression (i.e. contribute to a smooth Hb boundary) and decrease between-copy transcriptional variability within nuclei. Since many tissue boundaries are first established by interactions between neighbouring gene expression domains, these properties of Hb-Kr dynamics to diminish the effects of intrinsic expression noise may represent a general mechanism contributing to robustness in early development., Peer-reviewed article, Published. Received: December 5, 2014; Accepted: December 15, 2014; Published: March 20, 2015.
Shaped singular spectrum analysis for quantifying gene expression, with application to the early drosophila embryo
In recent years, with the development of automated microscopy technologies, the volume and complexity of image data on gene expression have increased tremendously. The only way to analyze quantitatively and comprehensively such biological data is by developing and applying new sophisticated mathematical approaches. Here, we present extensions of 2D singular spectrum analysis (2D-SSA) for application to 2D and 3D datasets of embryo images. These extensions, circular and shaped 2D-SSA, are applied to gene expression in the nuclear layer just under the surface of the Drosophila (fruit fly) embryo. We consider the commonly used cylindrical projection of the ellipsoidal Drosophila embryo. We demonstrate how circular and shaped versions of 2D-SSA help to decompose expression data into identifiable components (such as trend and noise), as well as separating signals from different genes. Detection and improvement of under- and overcorrection in multichannel imaging is addressed, as well as the extraction and analysis of 3D features in 3D gene expression patterns., Peer-reviewed article, Published. Received 4 July 2014; Revised 10 September 2014; Accepted 10 September 2014.
Spatial bistability generates hunchback expression sharpness in the drosophila embryo
During embryonic development, the positional information provided by concentration gradients of maternal factors directs pattern formation by providing spatially dependent cues for gene expression. In the fruit fly, Drosophila melanogaster, a classic example of this is the sharp on-off activation of the hunchback (hb) gene at midembryo, in response to local concentrations of the smooth anterior-posterior Bicoid (Bcd) gradient. The regulatory region for hb contains multiple binding sites for the Bcd protein as well as multiple binding sites for the Hb protein. Some previous studies have suggested that Bcd is sufficient for properly sharpened Hb expression, yet other evidence suggests a need for additional regulation. We experimentally quantified the dynamics of hb gene expression in flies that were wild-type, were mutant for hb self-regulation or Bcd binding, or contained an artificial promoter construct consisting of six Bcd and two Hb sites. In addition to these experiments, we developed a reaction-diffusion model of hb transcription, with Bcd cooperative binding and hb self-regulation, and used Zero Eigenvalue Analysis to look for multiple stationary states in the reaction network. Our model reproduces the hb developmental dynamics and correctly predicts the mutant patterns. Analysis of our model indicates that the Hb sharpness can be produced by spatial bistability, in which hb self-regulation produces two stable levels of expression. In the absence of self-regulation, the bistable behavior vanishes and Hb sharpness is disrupted. Bcd cooperative binding affects the position where bistability occurs but is not itself sufficient for a sharp Hb pattern. Our results show that the control of Hb sharpness and positioning, by hb self-regulation and Bcd cooperativity, respectively, are separate processes that can be altered independently. Our model, which matches the changes in Hb position and sharpness observed in different experiments, provides a theoretical framework for understanding the data and in particular indicates that spatial bistability can play a central role in threshold-dependent reading mechanisms of positional information., Peer-reviewed article, Published. Received October 16, 2007; Accepted August 13, 2008; Published September 26, 2008.
Stochastic dynamics of gene expression in developing fly embryos
Proceedings of 2017 International Conference on Noise and Fluctuations (ICNF), Vilnius, Lithuania on 20-23 June 2017. Segmentation of the developing insect body is preceded by cell-specific gene expression. In fruit flies (Drosophila), pair-rule genes are expressed in spatial stripes specifying segment fates. Transcription of the even-skipped (eve) pair-rule gene was recently shown to proceed in noisy bursts. Here, we develop a stochastic model of eve transcription from DNA to mRNA. This indicates that eve transcription proceeds at two rates, with a slow rate providing basal production and a fast rate allowing for high mRNA output. This two-rate transcription may afford more reliability in mRNA output, and therefore the protein levels which specify cell type, than a simple on-off (one-rate) mechanism., Conference paper, Published.
Transcriptional bursting in drosophila development
Anterior-posterior (AP) body segmentation of the fruit fly (Drosophila) is first seen in the 7-stripe spatial expression patterns of the pair-rule genes, which regulate downstream genes determining specific segment identities. Regulation of pair-rule expression has been extensively studied for the even-skipped (eve) gene. Recent live imaging, of a reporter for the 2nd eve stripe, has demonstrated the stochastic nature of this process, with ‘bursts’ in the number of RNA transcripts being made over time. We developed a stochastic model of the spatial and temporal expression of eve stripe 2 (binding by transcriptional activators (Bicoid and Hunchback proteins) and repressors (Giant and Krüppel proteins), transcriptional initiation and termination; with all rate parameters constrained by features of the experimental data) in order to analyze the noisy experimental time series and test hypotheses for how eve transcription is regulated. These include whether eve transcription is simply OFF or ON, with a single ON rate, or whether it proceeds by a more complex mechanism, with multiple ON rates. We find that both mechanisms can produce long (multi-minute) RNA bursts, but that the short-time (minute-to-minute) statistics of the data is indicative of eve being transcribed with at least two distinct ON rates, consistent with data on the joint activation of eve by Bicoid and Hunchback. We also predict distinct statistical signatures for cases in which eve is repressed (e.g. along the edges of the stripe) vs. cases in which activation is reduced (e.g. by mutagenesis of transcription factor binding sites). Fundamental developmental processes such as gene transcription are intrinsically noisy; our approach presents a new way to quantify and analyze time series data during developmental patterning in order to understand regulatory mechanisms and how they propagate noise and impact embryonic robustness., Peer-reviewed article, Published. Received: November 21, 2016; Accepted: April 8, 2017; Published: April 24, 2017.