Menu

Close

Kinetic sculpting of the seven stripes of the Drosophila even-skipped gene

Augusto Berrocal, Nicholas C Lammers, Hernan G Garcia, Michael B Eisen

Preprint posted on June 11, 2018 https://www.biorxiv.org/content/early/2018/06/11/335901

Falling into lines: @guberrocal, @HernanGGarcia and @mbeisen use live imaging and computational modelling to reveal the transcriptional dynamics underlying the emergence of the eve stripes in the Drosophila embryo

Selected by Erik Clark

Background

Segmentation gene expression in the Drosophila blastoderm has long been used as a test case for unravelling mechanisms of transcriptional regulation. Over the years, one of the most scrutinised genes has been even-skipped (eve), a pair-rule gene expressed in seven regular stripes. Although it was originally assumed that the regularity of these stripes must stem from an underlying uniformity of mechanism (e.g. Turing pattern formation), it was quickly discovered that the various eve stripes are actually established piecemeal, from 5 different “stripe-specific” enhancer elements. Today, these enhancers are among the best studied in the animal kingdom.

In recent years, the MS2-MCP system for live imaging has shone a light on the dynamicity of transcriptional regulation, again using Drosophila blastoderm genes such as eve as study cases. Transgenically inserting MS2 stem-loop repeats into a coding sequence causes maternally deposited and fluorescently tagged MCP protein to be concentrated at the gene locus during active transcription, allowing one to directly visualise transcriptional bursts in individual nuclei over time. However, in order to determine how exactly transcription is regulated across time and space to pattern developmental gene expression, it is first necessary to overcome the problem of inferring the promoter state history of each nucleus from its temporal intensity profile (an aggregate pattern which is determined by the cumulative number of nascent transcripts present at the transcribing locus over time).

 

Key Findings

Berroccal and colleagues constructed an eve MS2 reporter transgene, and collected 11 high-resolution movies of blastoderm eve expression, each focused on a different set of stripes. They segmented the movies to get the locations and intensity profiles of ~3,000 individual nuclei, then registered all this data together to produce an overall picture of eve transcription along the anteroposterior axis during and after stripe formation.

The authors then ran the intensity traces through a custom hidden Markov model to infer the history of transcriptional bursts in each nucleus (see the companion preprint in Related Research, below). A simple two-state (ON/OFF) modelling framework is commonly used to characterise transcriptional regulation at the promoter level, characterised by three parameters, which determine (1) average burst frequency, (2) average burst duration, and (3) the rate at which new transcripts are initialised during a burst. The authors found that eve transcription is regulated predominantly at the level of burst frequency (increasing it within stripes, and decreasing it between stripes), while the other two parameter values did not seem to change much. They also found that the different eve stripes are regulated similarly at the promoter level, even though they are generated by different enhancer elements and patterned by different sets of transcription factors.

Reassuringly, the tissue-level picture of eve expression yielded by the analysis was broadly in line with previous quantitative descriptions derived from large numbers of fixed samples. However, the authors were able to put more precise timings on the resolution of individual stripes, and more accurately determine the magnitude of the posterior to anterior shifts undertaken by the eve stripes after they form. Overall, this study underlines the extremely dynamic nature of eve expression within the blastoderm – as the authors stress, “at no point does eve approach anything even remotely like a steady state”.

 

Kymograph of eve transcription along the anteroposterior axis over time; from Figure 3B of the preprint

 

Significance

We are going to see many more MS2 movies in developmental biology over the coming years. This windfall of live imaging data will need to be analysed rigorously, perhaps using a similar framework to the one laid out here. This preprint therefore represents an important technical development. It also represents a laudable example of Open Science best practise: all datasets are well-documented and available in an online labbook, and Michael Eisen even wrote a great explainer thread for the project on Twitter: https://twitter.com/mbeisen/status/1002430064225480704

Recently, Hernan Garcia and colleagues revealed a complementary live imaging technology (LlamaTags), which allows live imaging of transcription factors. This means that it is now possible to analyse both halves of the equation: we can characterise transcriptional dynamics at the single cell level, as seen in this preprint, but also relate these outputs to the changing concentrations of key regulatory proteins within these same cells. It seems that old friends like even-skipped will have much to teach us for many years to come.

 

Related Research

Lammers NC, Galstyan V, Reimer A, Medin SA, Wiggins CH, Garcia HG (2018) Binary transcriptional control of pattern formation in development. bioRxiv doi: 10.1101/335919

Bothma JP, Norstad MR, Alamos S, Garcia HG (2018) LlamaTags: a versatile tool to image transcription factor dynamics in live embryos. Cell 173 1810-22

Bothma JP, Garcia HG, Esposito E, Schlissel G, Gregor T, Levine M (2014) Dynamic regulation of eve stripe 2 expression reveals transcriptional bursts in living Drosophila embryos. PNAS 111 10598-10603

Tags: drosophila, even-skipped, live-imaging, ms2, patterning, transcription

Posted on: 10th July 2018 , updated on: 11th July 2018

Read preprint (No Ratings Yet)




  • Have your say

    Your email address will not be published. Required fields are marked *

    This site uses Akismet to reduce spam. Learn how your comment data is processed.

    Sign up to customise the site to your preferences and to receive alerts

    Register here
    Close