Morphodynamic Atlas for Drosophila Development

Background

Embryos of the fruit fly Drosophila melanogaster have, for over a century, drawn scientists from disparate fields into the study of developmental biology. In recent decades, physical biologists have made strides in understanding the role of morphogen gradients in patterning the body plan (Grimm et al., 2010) as well as the spatial precision with which gene expression patterns can be established and interpreted in the presence of noise (Petkova et al., 2019). These studies have benefited greatly from rigorously controlled quantification of gene expression, as well as the relatively simple geometry of Drosophila embryos. Because of this geometry, it is common to measure the expression levels of gap genes or the concentration of Bicoid with just a single spatial parameter, measuring only distance from the anterior pole of the embryo.

 

While this one-dimensional view of the embryo has proven useful for both theorists and experimentalists, its limitations become obvious during later morphological events such as gastrulation, where cell flows in multiple directions give physical form to the different germ layers (Streichan et al., 2018). Recent evidence from later stages in Drosophila development indicate that multi-dimensional cell flow may play important roles in generating tissue-level patterning (Gallagher et al., 2022). In this preprint, Mitchell et. al leverage advances in microscopy to generate in toto views of gene expression patterns and cell flows across developmental time and present an analysis pipeline that allows for quantitative comparisons of these features across embryos. This “Morphodynamic Atlas” and the accompanying tools open new doors for studying the relationships between tissue patterning, cell flows, and gene expression patterns. The authors also show that their technique can be applied to later stages of embryogenesis such as organ formation.

 

Main Findings

The “Morphodynamic Atlas” provides a data set of gene expression and cell flow patterns aligned across space and time

Physical models of development often employ continuous time and space variables, but variation across embryos in developmental timing and tissue deformation can complicate comparisons between these models and experimental data. Mitchell et. al use light sheet microscopy and computational tissue cartography techniques to map the 3-D volumetric imaging data onto a 2-D parameterization of the embryo’s surface. By live imaging the pair-rule gene runt across multiple embryos, they can use its expression pattern as a landmark for building a consensus timeline of development through germ band extension, retraction, and maturation. They also use a similar technique to align images of embryos based on total tissue deformation. Both fixed and live samples can then be compared to this continuous “morphological timeline” to place each image of an embryo at a precise point in developmental time. (Figure 1)

Figure 1: Live images of runt gene expression and a myosin marker (sqhGFP) are spatially and temporally aligned to define a continuous morphological timeline. Fixed images can then be accurately placed along this timeline based on their gene expression and tissue deformation. (Pre-print Fig. 1 A-C)

 

Drosophila embryonic development is defined by discrete morphological events of stationary cell flow

After generating the atlas of tissue deformation across developmental time, the authors were able to ask how tissue flow patterns evolve during embryogenesis. By comparing instantaneous tissue flow between each imaged time point, the authors observed discrete periods of autocorrelated flow patterns. In other words, the flow patterns across specific ranges of time were highly self-similar. Additionally, these periods of self-similar flow patterns corresponded to previously characterized morphological events such as germ band extension and retraction. These data indicate that tissue flow is quasi-stationary; sources of tissue flow on the embryo’s surface remain fixed during discrete periods of time, with changes in the flow pattern happening in between these morphological events. The authors also found that these flow patterns scale with temperature. Although changes in the temperature can speed up or slow down the overall rate of development, they do not affect the location or direction or tissue flow.

 

Why I chose this preprint

At first glance, the findings of this paper are not particularly shocking. The “discrete morphological events” of germ band extension and retraction have been well characterized, and temperature variations have long been known to affect the rate of development. Instead, I chose it because of the vision it presents for collecting, analyzing, and interpreting data.

 

Light sheet microscopy can give unprecedented spatial and temporal resolution of embryonic development, yet the full resolution of the data is rarely ever utilized. The authors of this preprint have developed a toolkit that gives researchers a new language to describe Drosophila development. Rather than reducing development to a handful of stages based on nuclear cycles or qualitative morphological changes, the authors have developed a way to examine changes in shape and gene expression as they naturally occur, on a continuous timescale. In doing so, the authors were able to recapitulate previously understood facets of development, uncover new features of morphological patterning, and provide a rich data set for researchers working to develop field theories of patterning. I am excited to see what discoveries, both experimental and theoretical, are made possible by this technique in the future.

 

Questions for the authors

• How does distortion from mapping the 3-D volume of the embryo into a 2-D plane affect the alignment? Does distortion at the poles of the embryo mean that small changes in the expression patterns are weighted differently at the poles versus in the middle of the embryo?
• At times when little to no autocorrelation in tissue flow was observed on the whole-embryo scale, are there shorter length scales at which high autocorrelation might be observed? E.g. are there sub-domains within the embryo that might still exhibit stationary flow?

 

Works Cited

Gallagher, K. D., Mani, M., & Carthew, R. W. (2022). Emergence of a geometric pattern of cell fates from tissue-scale mechanics in the Drosophila eye. ELife, 11. https://doi.org/10.7554/eLife.72806

Grimm, O., Coppey, M., & Wieschaus, E. (2010). Modelling the Bicoid gradient. Development, 137(14), 2253–2264. https://doi.org/10.1242/dev.032409

Petkova, M. D., Tkačik, G., Bialek, W., Wieschaus, E. F., & Gregor, T. (2019). Optimal Decoding of Cellular Identities in a Genetic Network. Cell, 176(4), 844-855.e15. https://doi.org/10.1016/j.cell.2019.01.007

Streichan, S. J., Lefebvre, M. F., Noll, N., Wieschaus, E. F., & Shraiman, B. I. (2018). Global morphogenetic flow is accurately predicted by the spatial distribution of myosin motors. ELife, 7. https://doi.org/10.7554/eLife.27454

 

Tags: fruit fly, microscopy, morphogenesis

doi: https://doi.org/10.1242/prelights.32405

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