Robustness in Drosophila embryo patterning

Bicoid (Bcd) is a well studied morphogen involved in the patterning of the anterior-posterior (AP) axis of the Drosophila embryo (Driever and Nüsslein-Volhard, 1988a, b). Zygotic downstream genes read out this gradient and their expression domains determine the basic body plan of the embryo along this axis. The positions of these domains are remarkably insensitive to fluctuations in the external environment (Crauk and Dostatni, 2005; Houchmandzadeh et al, 2002; Lucchetta et al, 2005) and their relative proportions are maintained across embryos of different sizes. The latter feature is referred to as scaling and occurs within a single species (Houchmandzadeh et al, 2002; Lott et al, 2007) and also across different species (Gregor et al, 2005; Gregor et al, 2008; Lott et al, 2007).

Recent experiments also show that the Bicoid gradient itself is rather precise and that its length scale correlates to some extent to the embryo size (Gregor et al, 2007a; He et al, 2008). These new findings suggest that the precision and scaling of Bcd target genes may, at least in part, be attributed to that of the morphogen gradient itself. Therefore, we investigate single morphogen models that aim at explaining the precision and scaling of Bcd target genes at the level of the morphogen gradient. However, it is likely that other mechanisms (e.g. Bcd interactions with the staufen gene (Aegerter-Wilmsen et al, 2005), gap genes interactions (Jaeger et al, 2004a; Jaeger and Reinitz, 2006; Jaeger et al, 2007; Jaeger et al, 2004b; Manu et al, 2009a, b), Bcd interactions with maternal Hunchback and the terminal system (Ochoa-Espinosa et al, 2009) or bistability (Lopes et al, 2008)) also contribute to ensure precise domain localization and further increase robustness in AP patterning.

In our work, we measured precision in more than 150 staining images for the gap genes Krüppel (Kr), Giant (Gt) and Hunchback (Hb), as well as the pair-rule gene Even-skipped (Eve) in embryos with a single, double (wt) and quadruple dose of bcd. Our data indicated that the precision is maximal at mid-embryo as well as position-dependent rather than gene-dependent. This provided independent support for the conclusions drawn from direct measurements of Bcd (Gregor et al, 2007a; He et al, 2008) that the morphogen gradient itself is the main contributor to the precision of the target genes. It motivated our subsequent analytical investigation of noise propagation during Bcd gradient formation within a single-morphogen modeling framework. Our analysis showed that fluctuations in the parameters affecting morphogen production, degradation, diffusion as well as nuclear trapping can give rise naturally to highest precision at mid-embryo, provided the Bcd gradient is decoded at pre-steady state. Finally, we considered a variety of models to investigate the scaling of the morphogen gradient. In order to single out the most likely scenario, we experimentally investigated scaling at the level of the target genes. We observed somewhat elevated scaling for expression domain boundaries in the anterior part of the embryo and almost perfect scaling beyond ~40%L (L is the embryo size). This effect appeared to be position-dependent rather than gene-dependent. Based on these observations, we argue that the formation of the Bcd gradient itself is a main contributor to robust patterning along the anterior-posterior axis and that pre-steady state decoding is an efficient means to increase robustness.

We also work on the formation of the Bicoid gradient from its mRNA gradient, as suggested by a recent publication spirov. We model the active quasi-random transport of bcd mRNA from the anterior pole (along a non-polar cortical microtubules network), forming a complex with the mRNA-binding protein Staufen, in a pure diffusive way. Establishment of the Bcd protein gradient arises by local translation from the non-localized and evolving mRNA gradient. We use a simple and general formalism for the modeling of morphogen gradient formation which allows to obtain explicit analytical solutions in the 1D case. We can also estimate diffusive parameters. The model is also being compared to static source models (without mRNA transport) involving delocalization of the source (step- and Gaussian source).

Recommended reading

• Introduction to Systems Biology, Uri Alon
• Developmental Biology, Gilbert
• Review on A-P patterning in the Drosophila embryo nasiadkaephrussi
• Precision and Scaling of the Bicoid gradient houchmandzadehgregor05bergmanngregor07agregor07he
• Temperature robustness of the Bicoid gradient lucchetta

References

<biblio>

1. nasiadka Anterior-posterior patterning in the Drosophila embryo Advances in Developmental Biology and Biochemistry, 2002, 12, 155-204
2. ephrussi pmid=14744427
3. houmandzadeh pmid=11845210
4. gregor05 pmid=16352710
5. bergmann pmid=17298180
6. gregor07a pmid=17632061
7. gregor07 pmid=17632062
8. he pmid=18854140
9. lucchetta pmid=15858575
10. spirov pmid = 19168676

</biblio>