Alexander V. Spirov

Canalization of gene expression in the Drosophila blastoderm by gap gene cross regulation.

Developing embryos exhibit a robust capability to reduce phenotypic variations that occur naturally or as a result of experimental manipulation. This reduction in variation occurs by an epigenetic mechanism called canalization, a phenomenon which has resisted understanding because of a lack of necessary molecular data and of appropriate gene regulation models. In recent years, quantitative gene expression data have become available for the segment determination process in the Drosophila blastoderm, revealing a specific instance of canalization. These data show that the variation of the zygotic segmentation gene expression patterns is markedly reduced compared to earlier levels by the time gastrulation begins, and this variation is significantly lower than the variation of the maternal protein gradient Bicoid. We used a predictive dynamical model of gene regulation to study the effect of Bicoid variation on the downstream gap genes. The model correctly predicts the reduced variation of the gap gene expression patterns and allows the characterization of the canalizing mechanism. We show that the canalization is the result of specific regulatory interactions among the zygotic gap genes. We demonstrate the validity of this explanation by showing that variation is increased in embryos mutant for two gap genes, Krüppel and knirps, disproving competing proposals that canalization is due to an undiscovered morphogen, or that it does not take place at all. In an accompanying article in PLoS Computational Biology (doi:10.1371/journal.pcbi.1000303), we show that cross regulation between the gap genes causes their expression to approach dynamical attractors, reducing initial variation and providing a robust output. These results demonstrate that the Bicoid gradient is not sufficient to produce gap gene borders having the low variance observed, and instead this low variance is generated by gap gene cross regulation. More generally, we show that the complex multigenic phenomenon of canalization can be understood at a quantitative and predictive level by the application of a precise dynamical model.

Canalization of gene expression and domain shifts in the Drosophila blastoderm by dynamical attractors.

The variation in the expression patterns of the gap genes in the blastoderm of the fruit fly Drosophila melanogaster reduces over time as a result of cross regulation between these genes, a fact that we have demonstrated in an accompanying article in PLoS Biology (see Manu et al., doi:10.1371/journal.pbio.1000049). This biologically essential process is an example of the phenomenon known as canalization. It has been suggested that the developmental trajectory of a wild-type organism is inherently stable, and that canalization is a manifestation of this property. Although the role of gap genes in the canalization process was established by correctly predicting the response of the system to particular perturbations, the stability of the developmental trajectory remains to be investigated. For many years, it has been speculated that stability against perturbations during development can be described by dynamical systems having attracting sets that drive reductions of volume in phase space. In this paper, we show that both the reduction in variability of gap gene expression as well as shifts in the position of posterior gap gene domains are the result of the actions of attractors in the gap gene dynamical system. Two biologically distinct dynamical regions exist in the early embryo, separated by a bifurcation at 53% egg length. In the anterior region, reduction in variation occurs because of stability induced by point attractors, while in the posterior, the stability of the developmental trajectory arises from a one-dimensional attracting manifold. This manifold also controls a previously characterized anterior shift of posterior region gap domains. Our analysis shows that the complex phenomena of canalization and pattern formation in the Drosophila blastoderm can be understood in terms of the qualitative features of the dynamical system. The result confirms the idea that attractors are important for developmental stability and shows a richer variety of dynamical attractors in developmental systems than has been previously recognized.

Gene Expression Noise in Spatial Patterning: hunchback Promoter Structure Affects Noise Amplitude and Distribution in Drosophila Segmentation

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.

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.

Sharp borders from fuzzy gradients

Critical boundaries in the early Drosophila embryo are set by morphogenetic gradients. A new quantitative study shows that the placement of one such boundary is more accurate than the gradient thought to set it. Genetic analysis of the accuracy of the process implicates a gene not previously thought to be involved.

Measuring Gene Expression Noise in Early Drosophila Embryos: Nucleus-to-nucleus Variability

In recent years the analysis of noise in gene expression has widely attracted the attention of experimentalists and theoreticians. Experimentally, the approaches based on in vivo fluorescent reporters in single cells appear to be straightforward and effective tools for bacteria and yeast. However, transferring these approaches to multicellular organisms presents many methodological problems. Here we describe our approach to measure between-nucleus variability (noise) in the primary morphogenetic gradient of Bicoid (Bcd) in the precellular blastoderm stage of fruit fly (Drosophila) embryos. The approach is based on the comparison of results for fixed immunostained embryos with observations of live embryos carrying fluorescent Bcd (Bcd-GFP). We measure the noise using two-dimensional Singular Spectrum Analysis (2D SSA). We have found that the nucleus-to-nucleus noise in Bcd intensity, both for live (Bcd-GFP) and for fixed immunstained embryos, tends to be signal-independent. In addition, the character of the noise is sensitive to the nuclear masking technique used to extract quantitative intensities. Further, the method of decomposing the raw quantitative expression data into a signal (expression surface) and residual noise affects the character of the residual noise. We find that careful masking of confocal images and use of appropriate computational tools to decompose raw expression data into trend and noise makes it possible to extract and study the biological noise of gene expression.

Reconstruction of the dynamics of drosophila genes expression from sets of images sharing a common pattern

Like all other insects, the body of the fruit fly Drosophila melanogaster is made up of repeated units called segments. At the early developmental stages prior to morphological differentiation, the segments are marked out by a chemical blueprint at cellular resolution. This blueprint is formed by the early patterns of segmentation gene expression, which become more spatially resolved over time. The precise characterization of this pattern and its temporal changes is of considerable biological significance. Such characterization faces a twofold technical barrier. First, although we are interested in the time course of expression, segmentation gene expression can only be visualized in fixed tissue and so the time course must be reconstructed from many embryos, each at a slightly different point in development. Second, available confocal microscopes can image only three gene products at once. We overcome this barrier by using data retrieved from a large number of scanned embryos which have been placed in temporal equivalence classes. Each embryo was scanned for the expression patterns of three genes. These three patterns vary from embryo to embryo because of individual differences and cannot be directly superimposed. However, if each embryo is stained for one common gene product and for two others, which vary among the dataset, it is possible to make some coordinate transformations of every embryo image so that the expression domains of the common gene will maximally coincide. To find these coordinate transformations is to solve the registration problem.We present a set of methods to reconstruct the dynamics of gene expression patterns from sets of images sharing a common pattern. For this purpose, we applied modern heuristic methods of optimization to find the elastic deformation necessary for image registration. We used the standard Genetic Algorithms technique by itself and in combination with the simplex method. By this approach, it is possible to retrace the detailed dynamics of developmental gene activity at the resolution on the level of individual nuclei for each of 4-6 thousand cells composing early fly embryo. The final result of this analysis will be the quantitative atlas of Drosophila genes expression (http://www.iephb.nw.ru/~spirov/atlas).

Experimental Determination of Drosophila Embryonic Coordinates by Genetic Algorithms, the Simplex method, and Their Hybrid

Modern large-scale functional genomics projects are inconceivable without the automated processing and computer-aided analysis of images. The project we are engaged in is aimed at the construction of heuristic models of segment determination in the fruit fly Drosophila melanogaster. The current emphasis in our work is the automated transformation of gene expression data in confocally scanned images into an electronic database of expression. We have developed and tested programs which use genetic algorithms for the elastic deformation of such images. In addition, genetic algorithms and the simplex method, both separately and in concert, were used for experimental determination of Drosophila embryonic curvilinear coordinates. Comparative tests demonstrate that the hybrid approach performs best. The intrinsic curvilinear coordinates of the embryo found by our optimization procedures appear to be well approximated by lines of isoconcentration of a known morphogen, Bicoid.

Design of a dynamic model of genes with multiple autonomous regulatory modules by evolutionary computations.

A new approach to design a dynamic model of genes with multiple autonomous regulatory modules by evolutionary computations is proposed. The approach is based on Genetic Algorithms (GA), with new crossover operators especially designed for these purposes. The new operators use local homology between parental strings to preserve building blocks found by the algorithm. The approach exploits the subbasin-portal architecture of the fitness functions suitable for this kind of evolutionary modeling. This architecture is significant for Royal Road class fitness functions. Two real-life Systems Biology problems with such fitness functions are implemented here: evolution of the bacterial promoter rrnPl and of the enhancer of the Drosophila even-skipped gene. The effectiveness of the approach compared to standard GA is demonstrated on several benchmark and real-life tasks.

Evolutionary techniques for image processing a large dataset of early Drosophila gene expression

Understanding how genetic networks act in embryonic development requires a detailed and statistically significant dataset integrating diverse observational results. The fruit fly (Drosophila melanogaster) is used as a model organism for studying developmental genetics. In recent years, several laboratories have systematically gathered confocal microscopy images of patterns of activity (expression) for genes governing early Drosophila development. Due to both the high variability between fruit fly embryos and diverse sources of observational errors, some new nontrivial procedures for processing and integrating the raw observations are required. Here we describe processing techniques based on genetic algorithms and discuss their efficacy in decreasing observational errors and illuminating the natural variability in gene expression patterns. The specific developmental problem studied is anteroposterior specification of the body plan.