Robust scaling and self-organisation of the Drosophila anteroposterior axis
Lead Research Organisation:
University of Cambridge
Department Name: Genetics
Abstract
BACKGROUND
An adult organism contains many different types of cells, organised into a complicated but orderly arrangement. Embryo patterning is the field of developmental biology concerned with how this complicated arrangement is created.
Embryo patterning is typically robust, producing reliable outputs despite variable inputs and conditions. It can scale (adapt proportionally to embryo size), for example during the production of twins. Finally, it requires a great deal of self-organisation (emergence of high level pattern from lower level processes), since the adult organism is much more complicated than the initial fertilised egg.
Embryo patterning has been studied for decades, using a mixture of "model organism" experiments and mathematical theory. However, prevailing theories struggle to account for the robustness, scalability and self-organisation observed during experimental manipulations, indicating a serious mismatch with biological reality.
This mismatch is particularly apparent in the early Drosophila (fruit fly) embryo, an important model system that is simpler, more extensively studied, and more conducive to genetic experiments than most other species. The early stages of Drosophila's anteroposterior (head-to-tail) patterning are more robust than we can account for, even though we know the 15 genes involved, the 4 initial signals laid down by the embryo's mother that they respond to, and some of the regulatory interactions between these components.
HYPOTHESIS
We believe that the robustness of Drosophila patterning emerges from the structure of the whole early anteroposterior patterning network (the full set of regulatory interactions between the 15 genes and their 4 inputs), combined with the fact that the mRNA and protein molecules expressed from these genes diffuse between nearby nuclei. While there are thousands of nuclei in the early Drosophila embryo, cell membranes do not form between them until after the initial anteroposterior pattern is laid down. We hypothesise that the patterning network exploits the spatial interactions between nuclei to generate pattern regulation at the level of the whole tissue; this idea contrasts with the mathematical models currently applied to the Drosophila embryo, which assume that the inputs to patterning will be interpreted (read-out) locally.
OBJECTIVES
We aim to resolve the structure of the patterning network, and explain why it so reliably produces an output close to the wild-type (normal) embryo pattern, even if the starting conditions in the embryo are quite strongly perturbed. We will then use this new understanding of patterning in the Drosophila embryo to extract new general principles that can be used to understand developmental patterning in other animal embryos, or in the synthetic embryo-like structures that can now be generated from stem cells.
APPROACH
This is an interdisciplinary proposal, which combines microscopy, genetics, and mathematical modelling. We will use cutting-edge imaging approaches to reveal how patterning unfolds within wild-type and mutant embryos, then use computational simulations to understand how these behaviours are produced by the underlying gene network.
POTENTIAL APPLICATIONS AND BENEFITS
This work will advance our basic understanding of embryonic development, by solving a long-standing and fundamental problem. Our findings will be directly relevant to developmental biologists (both Drosophila researchers and those studying other animal systems), plus mathematical biologists studying patterning from a theoretical perspective. The principles we uncover will also have practical applications in synthetic and stem cell biology, contributing to long-term translational applications in developmental disease, regeneration, and bioengineering.
An adult organism contains many different types of cells, organised into a complicated but orderly arrangement. Embryo patterning is the field of developmental biology concerned with how this complicated arrangement is created.
Embryo patterning is typically robust, producing reliable outputs despite variable inputs and conditions. It can scale (adapt proportionally to embryo size), for example during the production of twins. Finally, it requires a great deal of self-organisation (emergence of high level pattern from lower level processes), since the adult organism is much more complicated than the initial fertilised egg.
Embryo patterning has been studied for decades, using a mixture of "model organism" experiments and mathematical theory. However, prevailing theories struggle to account for the robustness, scalability and self-organisation observed during experimental manipulations, indicating a serious mismatch with biological reality.
This mismatch is particularly apparent in the early Drosophila (fruit fly) embryo, an important model system that is simpler, more extensively studied, and more conducive to genetic experiments than most other species. The early stages of Drosophila's anteroposterior (head-to-tail) patterning are more robust than we can account for, even though we know the 15 genes involved, the 4 initial signals laid down by the embryo's mother that they respond to, and some of the regulatory interactions between these components.
HYPOTHESIS
We believe that the robustness of Drosophila patterning emerges from the structure of the whole early anteroposterior patterning network (the full set of regulatory interactions between the 15 genes and their 4 inputs), combined with the fact that the mRNA and protein molecules expressed from these genes diffuse between nearby nuclei. While there are thousands of nuclei in the early Drosophila embryo, cell membranes do not form between them until after the initial anteroposterior pattern is laid down. We hypothesise that the patterning network exploits the spatial interactions between nuclei to generate pattern regulation at the level of the whole tissue; this idea contrasts with the mathematical models currently applied to the Drosophila embryo, which assume that the inputs to patterning will be interpreted (read-out) locally.
OBJECTIVES
We aim to resolve the structure of the patterning network, and explain why it so reliably produces an output close to the wild-type (normal) embryo pattern, even if the starting conditions in the embryo are quite strongly perturbed. We will then use this new understanding of patterning in the Drosophila embryo to extract new general principles that can be used to understand developmental patterning in other animal embryos, or in the synthetic embryo-like structures that can now be generated from stem cells.
APPROACH
This is an interdisciplinary proposal, which combines microscopy, genetics, and mathematical modelling. We will use cutting-edge imaging approaches to reveal how patterning unfolds within wild-type and mutant embryos, then use computational simulations to understand how these behaviours are produced by the underlying gene network.
POTENTIAL APPLICATIONS AND BENEFITS
This work will advance our basic understanding of embryonic development, by solving a long-standing and fundamental problem. Our findings will be directly relevant to developmental biologists (both Drosophila researchers and those studying other animal systems), plus mathematical biologists studying patterning from a theoretical perspective. The principles we uncover will also have practical applications in synthetic and stem cell biology, contributing to long-term translational applications in developmental disease, regeneration, and bioengineering.
Technical Summary
Developmental biology still lacks a convincing mechanistic explanation for the robustness, scalability and self-organisation of embryo patterning. Positional Information approaches lack spatial interactions entirely, while reaction-diffusion models struggle to account for regulative behaviour. To progress past this impasse, we must study the gene regulatory networks that mediate robust patterns in real embryos, and determine how they manage what our existing models cannot.
This interdisciplinary proposal combines multiplexed confocal microscopy, genetic perturbations and computational modelling to understand the robustness of anteroposterior (AP) patterning in blastoderm stage Drosophila embryos. The overall objective is to explain how the robust scaling and self-organisation of the AP axis follows mechanistically from the structure and spatial coupling of the early AP patterning network. The work program addresses the key limitations of previous research on this system, which tends to focus on a small subset of the relevant patterning genes and ignores the crucial integrative role of gene product diffusion.
AIM 1 uses live-imaging approaches (MS2, SunTags, LlamaTags) to characterise how zygotic gene products spread through the syncytial blastoderm over time, as these spatial interactions likely mediate embryo-level regulation of the AP pattern. AIM 2 uses multiplexed hybridisation chain reaction imaging of finely-staged fixed mutant embryos to resolve the structure of the patterning network, a basic prerequisite for understanding its spatiotemporal dynamics. AIM 3 uses the same imaging pipeline to quantitatively characterise patterning dynamics after various gene dosage and/or egg length perturbations, to reveal how - and under what circumstances - robust patterning is achieved. Finally, AIM 4 uses mathematical modelling and simulation of the patterning system, informed by the results from aims 1-2, to understand how/why the behaviour from aim 3 is produced.
This interdisciplinary proposal combines multiplexed confocal microscopy, genetic perturbations and computational modelling to understand the robustness of anteroposterior (AP) patterning in blastoderm stage Drosophila embryos. The overall objective is to explain how the robust scaling and self-organisation of the AP axis follows mechanistically from the structure and spatial coupling of the early AP patterning network. The work program addresses the key limitations of previous research on this system, which tends to focus on a small subset of the relevant patterning genes and ignores the crucial integrative role of gene product diffusion.
AIM 1 uses live-imaging approaches (MS2, SunTags, LlamaTags) to characterise how zygotic gene products spread through the syncytial blastoderm over time, as these spatial interactions likely mediate embryo-level regulation of the AP pattern. AIM 2 uses multiplexed hybridisation chain reaction imaging of finely-staged fixed mutant embryos to resolve the structure of the patterning network, a basic prerequisite for understanding its spatiotemporal dynamics. AIM 3 uses the same imaging pipeline to quantitatively characterise patterning dynamics after various gene dosage and/or egg length perturbations, to reveal how - and under what circumstances - robust patterning is achieved. Finally, AIM 4 uses mathematical modelling and simulation of the patterning system, informed by the results from aims 1-2, to understand how/why the behaviour from aim 3 is produced.
