Johannes Jaeger

Dynamic control of positional information in the early Drosophila embryo

Morphogen gradients contribute to pattern formation by determining positional information in morphogenetic fields. Interpretation of positional information is thought to rely on direct, concentration-threshold-dependent mechanisms for establishing multiple differential domains of target gene expression. In Drosophila, maternal gradients establish the initial position of boundaries for zygotic gap gene expression, which in turn convey positional information to pair-rule and segment-polarity genes, the latter forming a segmental pre-pattern by the onset of gastrulation. Here we report, on the basis of quantitative gene expression data, substantial anterior shifts in the position of gap domains after their initial establishment. Using a data-driven mathematical modelling approach, we show that these shifts are based on a regulatory mechanism that relies on asymmetric gap–gap cross-repression and does not require the diffusion of gap proteins. Our analysis implies that the threshold-dependent interpretation of maternal morphogen concentration is not sufficient to determine shifting gap domain boundary positions, and suggests that establishing and interpreting positional information are not independent processes in the Drosophila blastoderm.

The gap gene network

Gap genes are involved in segment determination during the early development of the fruit fly Drosophila melanogaster as well as in other insects. This review attempts to synthesize the current knowledge of the gap gene network through a comprehensive survey of the experimental literature. I focus on genetic and molecular evidence, which provides us with an almost-complete picture of the regulatory interactions responsible for trunk gap gene expression. I discuss the regulatory mechanisms involved, and highlight the remaining ambiguities and gaps in the evidence. This is followed by a brief discussion of molecular regulatory mechanisms for transcriptional regulation, as well as precision and size-regulation provided by the system. Finally, I discuss evidence on the evolution of gap gene expression from species other than Drosophila. My survey concludes that studies of the gap gene system continue to reveal interesting and important new insights into the role of gene regulatory networks in development and evolution.

Quantitative and predictive model of transcriptional control of the Drosophila melanogaster even skipped gene

Here we present a quantitative and predictive model of the transcriptional readout of the proximal 1.7 kb of the control region of the Drosophila melanogaster gene even skipped (eve). The model is based on the positions and sequence of individual binding sites on the DNA and quantitative, time-resolved expression data at cellular resolution. These data demonstrated new expression features, first reported here. The model correctly predicts the expression patterns of mutations in trans, as well as point mutations, insertions and deletions in cis. It also shows that the nonclassical expression of stripe 7 driven by this fragment is activated by the protein Caudal (Cad), and repressed by the proteins Tailless (Tll) and Giant (Gt).

Regulative feedback in pattern formation: towards a general relativistic theory of positional information.

Positional specification by morphogen gradients is traditionally viewed as a two-step process. A gradient is formed and then interpreted, providing a spatial metric independent of the target tissue, similar to the concept of space in classical mechanics. However, the formation and interpretation of gradients are coupled, dynamic processes. We introduce a conceptual framework for positional specification in which cellular activity feeds back on positional information encoded by gradients, analogous to the feedback between mass-energy distribution and the geometry of space-time in Einsteins general theory of relativity. We discuss how such general relativistic positional information (GRPI) can guide systems-level approaches to pattern formation.

Parameter estimation and determinability analysis applied to Drosophila gap gene circuits

BackgroundMathematical modeling of real-life processes often requires the estimation of unknown parameters. Once the parameters are found by means of optimization, it is important to assess the quality of the parameter estimates, especially if parameter values are used to draw biological conclusions from the model.ResultsIn this paper we describe how the quality of parameter estimates can be analyzed. We apply our methodology to assess parameter determinability for gene circuit models of the gap gene network in early Drosophila embryos.ConclusionOur analysis shows that none of the parameters of the considered model can be determined individually with reasonable accuracy due to correlations between parameters. Therefore, the model cannot be used as a tool to infer quantitative regulatory weights. On the other hand, our results show that it is still possible to draw reliable qualitative conclusions on the regulatory topology of the gene network. Moreover, it improves previous analyses of the same model by allowing us to identify those interactions for which qualitative conclusions are reliable, and those for which they are ambiguous.

Known Maternal Gradients are not Sufficient for the Establishment of Gap Domains in Drosophila melanogaster

Gap genes are among the first transcriptional targets of maternal morphogen gradients in the early Drosophila embryo. However, it remains unclear whether these gradients are indeed sufficient to establish the boundaries of localized gap gene expression patterns. In this study, we address this question using gap gene circuits, which are data-driven mathematical tools for extracting regulatory information from quantitative wild-type gene expression data. We present new, quantitative data on the mRNA expression patterns for the gap genes Krüppel (Kr), knirps (kni) and giant (gt) during the early blastoderm stage of Drosophila development. This data set shows significant differences in timing of gap gene expression compared to previous observations, and reveals that early gap gene expression is highly variable in both space and time. Gene circuit models fit to this data set were used for a detailed regulatory analysis of early gap gene expression. Our analysis shows that the proper balance of maternal repression and activation is essential for the correct positioning of gap domains, and that such balance can only be achieved for early expression of kni. In contrast, our results suggest that early expression of gt requires local neutralization of repressive input in the anterior region of the embryo, and that known maternal gradients are completely insufficient to position the boundaries of the early central Kr domain, or in fact any Kr-like domain in the central region of the blastoderm embryo. Based on this, we propose that unknown additional regulators must be involved in early gap gene regulation.

A high-throughput method for quantifying gene expression data from early Drosophila embryos

We describe an automated high-throughput method to measure protein levels in single nuclei in blastoderm embryos of Drosophila melanogaster by means of immunofluorescence. The method consists of a chain of specific algorithms assembled into an image processing pipeline. This pipeline transforms a confocal scan of an embryo stained with fluorescently tagged antibodies into a text file. This text file contains a numerical identifier for each nucleus, the coordinates of its centroid, and the average concentrations of three proteins in that nucleus. The central algorithmic component of the method is the automatic identification of nuclei by edge detection with the use of watersheds as an error-correction step. This method provides high-throughput quantification at cellular resolution.

Molecular basis for the inhibition of Drosophila eye development by Antennapedia

Hox genes encoding homeodomain transcriptional regulators are known to specify the body plan of multicellular organisms and are able to induce body plan transformations when misexpressed. These findings led to the hypothesis that duplication events and misexpression of Hox genes during evolution have been necessary for generating the observed morphological diversity found in metazoans. It is known that overexpressing Antennapedia (Antp) in the head induces antenna‐to‐leg as well as head‐to‐thorax transformation and eye reduction. At present, little is known about the exact molecular mechanism causing these phenotypes. The aim of this study is to understand the basis of inhibition of eye development. We demonstrate that Antp represses the activity of the eye regulatory cascade. By ectopic expression, we show that Antp antagonizes the activity of the eye selector gene eyeless. Using both in vitro and in vivo experiments, we demonstrate that this inhibitory mechanism involves direct protein–protein interactions between the DNA‐binding domains of EY and ANTP, resulting in mutual inhibition.

Efficient reverse-engineering of a developmental gene regulatory network.

Understanding the complex regulatory networks underlying development and evolution of multi-cellular organisms is a major problem in biology. Computational models can be used as tools to extract the regulatory structure and dynamics of such networks from gene expression data. This approach is called reverse engineering. It has been successfully applied to many gene networks in various biological systems. However, to reconstitute the structure and non-linear dynamics of a developmental gene network in its spatial context remains a considerable challenge. Here, we address this challenge using a case study: the gap gene network involved in segment determination during early development of Drosophila melanogaster. A major problem for reverse-engineering pattern-forming networks is the significant amount of time and effort required to acquire and quantify spatial gene expression data. We have developed a simplified data processing pipeline that considerably increases the throughput of the method, but results in data of reduced accuracy compared to those previously used for gap gene network inference. We demonstrate that we can infer the correct network structure using our reduced data set, and investigate minimal data requirements for successful reverse engineering. Our results show that timing and position of expression domain boundaries are the crucial features for determining regulatory network structure from data, while it is less important to precisely measure expression levels. Based on this, we define minimal data requirements for gap gene network inference. Our results demonstrate the feasibility of reverse-engineering with much reduced experimental effort. This enables more widespread use of the method in different developmental contexts and organisms. Such systematic application of data-driven models to real-world networks has enormous potential. Only the quantitative investigation of a large number of developmental gene regulatory networks will allow us to discover whether there are rules or regularities governing development and evolution of complex multi-cellular organisms.

A quantitative atlas of Even-skipped and Hunchback expression in Clogmia albipunctata (Diptera: Psychodidae) blastoderm embryos

BackgroundComparative studies of developmental processes are one of the main approaches to evolutionary developmental biology (evo-devo). Over recent years, there has been a shift of focus from the comparative study of particular regulatory genes to the level of whole gene networks. Reverse-engineering methods can be used to computationally reconstitute and analyze the function and dynamics of such networks. These methods require quantitative spatio-temporal expression data for model fitting. Obtaining such data in non-model organisms remains a major technical challenge, impeding the wider application of data-driven mathematical modeling to evo-devo.ResultsWe have raised antibodies against four segmentation gene products in the moth midge Clogmia albipunctata, a non-drosophilid dipteran species. We have used these antibodies to create a quantitative atlas of protein expression patterns for the gap gene hunchback (hb), and the pair-rule gene even-skipped (eve). Our data reveal differences in the dynamics of Hb boundary positioning and Eve stripe formation between C. albipunctata and Drosophila melanogaster. Despite these differences, the overall relative spatial arrangement of Hb and Eve domains is remarkably conserved between these two distantly related dipteran species.ConclusionsWe provide a proof of principle that it is possible to acquire quantitative gene expression data at high accuracy and spatio-temporal resolution in non-model organisms. Our quantitative data extend earlier qualitative studies of segmentation gene expression in C. albipunctata, and provide a starting point for comparative reverse-engineering studies of the evolutionary and developmental dynamics of the segmentation gene system.