Temporal Control of Transcription by Zelda in living Drosophila embryos

Summary

In this preprint, the Lagha lab studies the role of pioneer transcription factors on the temporal control gene expression. Pioneer factors are known for their ability to bind their sites when the chromatin is closed. However, how pioneer factors prime enhancers to control the time of gene activation, and how this priming affects gene expression after mitosis, remains elusive.  In the Drosophila embryo, the maternally provided Zelda pioneer factor is responsible for the awakening of the zygotic genome. In this preprint, the authors examine the enhancer expression dynamics of a Zelda responsive element, and the dynamic properties of Zelda in living Drosophila embryos, through two cycles of cell division. In particular, they measure the temporal coordination in Zelda activation through a synthetic regulatory element. The authors also test how the initial state of activity of the enhancer (memory) impacts on gene activation. By examining Zelda dynamics in living embryos during mitosis, they find that Zelda accelerates transcription and fosters synchrony but is not the basis for transcriptional mitotic memory.

Why I chose the paper:

How gene regulation is precisely temporally controlled is one of the most interesting questions in developmental biology. One way to understand what’s going on is to characterize and study the dynamic activity of enhancers, and we need to find new ways to study how enhancers regulate gene expression.

This preprint offers a novel way to interpret enhancer dynamics through cell division and study transcriptional regulation by enhancers. The authors had previously shown how cells with memory activate transcription twice as fast as those with inactive mothers (1), but this time they focus on the role of Zelda in temporal coordination. I really like the fact that the authors are able to reproduce the activation kinetics of the endogenous shadow enhancer with their synthetic version that contains two Zelda binding sites. In addition, they implement an automated segmentation and tracking system that allows them to study hundreds of nuclei during multiple cell divisions. This system, once implemented, can save hours of tedious manual tracking, and provides a huge number of nuclei to analyse quantitatively. With this data, the authors move on to design a mathematical model to learn how memory could work. They model the time of reactivation after mitosis of cells with or without memory and find that inactive cells require at least three transitions to become active. The fitting to the model also shows that memory may be potentiated by reducing the number of steps required for post-mitotic transcriptional activation; something that couldn’t have been proposed without the model.

Unexpectedly, they find that Zelda does not play a role in setting the memory, since reducing Zelda levels leads to a reduction in activation kinetics but memory is still present. Neither does Zelda function as a mitotic bookmarking protein, since it is not retained on the chromosomes during mitosis. To pin down Zelda’s mode of action, the authors go one step further and perform fluorescent recovery after photo-bleaching and fluorescent correlation spectroscopy experiments. This thorough analysis of Zelda kinetic properties demonstrates that Zelda is highly dynamic and binds transiently to chromatin. The preprint concludes that Zelda accelerates the various transitions required prior to transcriptional activation.

How this work moves the field forward:

Regulatory sequences contain multiple transcription factor binding sites that are responsible for the spatio-temporal expression patterns of genes. We have long tried to decode the map to predict how the number, affinity and arrangement of sites determines transcription. This gets even more complicated if we consider that a single gene can respond to multiple enhancers, and these can exhibit overlapping spatiotemporal activity. This preprint advances our understanding of how enhancers coordinate gene expression, and emphasises how quantitative measurements coupled with mathematical modelling could provide precise and accurate models for transcription.

References :

1. Transcriptional Memory in the Drosophila Embryo. Ferraro T, Esposito E, Mancini L, Ng S, Lucas T, Coppey M, Dostatni N, Walczak AM, Levine M, Lagha M. Curr Biol. 2016 Jan 25;26(2):212-8.
2. Transcriptional precision and accuracy in development: from measurements to models and mechanisms. Bentovim L, Harden TT, DePace AH. Development. 2017 Nov 1;144(21):3855-3866.

Questions to the authors:

1. In the model, there are two possible parameters that define the memory function, (1) the number of transitions between discrete transcriptional states and (2) the duration of each transition. Have the authors considered to describe/identify the three transitions and/or metastable states, and explore parameter ‘a’ further?
2. I wonder if the authors could clarify further how the model supports their finding that the increase number of binding sites has an effect on the durations of the transitions and not on the number of states.

Tags: enhancer, fruit fly, gene expression, quantitative

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