Quantitative dissection of transcription in development yields evidence for transcription factor-driven chromatin accessibility

  1. Elizabeth Eck
  2. Jonathan Liu
  3. Maryam Kazemzadeh-Atoufi
  4. Sydney Ghoreishi
  5. Shelby A Blythe
  6. Hernan G Garcia  Is a corresponding author
  1. University of California, Berkeley, United States
  2. Northwestern University, United States

Abstract

Thermodynamic models of gene regulation can predict transcriptional regulation in bacteria, but in eukaryotes chromatin accessibility and energy expenditure may call for a different framework. Here we systematically tested the predictive power of models of DNA accessibility based on the Monod-Wyman-Changeux (MWC) model of allostery, which posits that chromatin fluctuates between accessible and inaccessible states. We dissected the regulatory dynamics of hunchback by the activator Bicoid and the pioneer-like transcription factor Zelda in living Drosophila embryos and showed that no thermodynamic or non-equilibrium MWC model can recapitulate hunchback transcription. Therefore, we explored a model where DNA accessibility is not the result of thermal fluctuations but is catalyzed by Bicoid and Zelda, possibly through histone acetylation, and found that this model can predict hunchback dynamics. Thus, our theory-experiment dialogue uncovered potential molecular mechanisms of transcriptional regulatory dynamics, a key step toward reaching a predictive understanding of developmental decision-making.

Data availability

Processed microscopy data have been deposited in Dryad (https://datadryad.org/stash/share/zakb7AqU2233pgWIs1mMAKyDiTQi4BXtnP0-Uu93xI0).

Article and author information

Author details

  1. Elizabeth Eck

    Biophysics, University of California, Berkeley, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Jonathan Liu

    Physics, University of California, Berkeley, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0204-0105
  3. Maryam Kazemzadeh-Atoufi

    Materials Science and Engineering, Northwestern University, Evanston, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Sydney Ghoreishi

    Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Shelby A Blythe

    Department of Molecular Biosciences, Northwestern University, Evanston, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4986-2579
  6. Hernan G Garcia

    Molecular and Cell Biology, Physics, University of California, Berkeley, Berkeley, United States
    For correspondence
    hggarcia@berkeley.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5212-3649

Funding

National Science Foundation (Graduate Student Fellowship)

  • Elizabeth Eck

National Institutes of Health (DP2 OD024541-01)

  • Hernan G Garcia

National Science Foundation (1652236)

  • Hernan G Garcia

University of California, Berkeley (Chancellor's Fellowship)

  • Elizabeth Eck

Department of Defense (Graduate Student Fellowship)

  • Jonathan Liu

Burroughs Wellcome Fund (Career Award)

  • Hernan G Garcia

Sloan Research Foundation

  • Hernan G Garcia

Human Frontiers Science Program

  • Hernan G Garcia

Searle Scholars Program

  • Hernan G Garcia

Shurl and Kay Curci Foundation

  • Hernan G Garcia

Hellman Foundation

  • Hernan G Garcia

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2020, Eck et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 3,994
    views
  • 583
    downloads
  • 43
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Elizabeth Eck
  2. Jonathan Liu
  3. Maryam Kazemzadeh-Atoufi
  4. Sydney Ghoreishi
  5. Shelby A Blythe
  6. Hernan G Garcia
(2020)
Quantitative dissection of transcription in development yields evidence for transcription factor-driven chromatin accessibility
eLife 9:e56429.
https://doi.org/10.7554/eLife.56429

Share this article

https://doi.org/10.7554/eLife.56429

Further reading

    1. Physics of Living Systems
    Emmanuel Akabuogu, Victor Carneiro da Cunha Martorelli ... Thomas A Waigh
    Research Article

    Bacterial biofilms are communities of bacteria usually attached to solid strata and often differentiated into complex structures. Communication across biofilms has been shown to involve chemical signaling and, more recently, electrical signaling in Gram-positive biofilms. We report for the first time, community-level synchronized membrane potential dynamics in three-dimensional Escherichia coli biofilms. Two hyperpolarization events are observed in response to light stress. The first requires mechanically sensitive ion channels (MscK, MscL, and MscS) and the second needs the Kch-potassium channel. The channels mediated both local spiking of single E. coli biofilms and long-range coordinated electrical signaling in E. coli biofilms. The electrical phenomena are explained using Hodgkin-Huxley and 3D fire-diffuse-fire agent-based models. These data demonstrate that electrical wavefronts based on potassium ions are a mechanism by which signaling occurs in Gram-negative biofilms and as such may represent a conserved mechanism for communication across biofilms.

    1. Cell Biology
    2. Physics of Living Systems
    Krishna Rijal, Pankaj Mehta
    Research Article

    The Gillespie algorithm is commonly used to simulate and analyze complex chemical reaction networks. Here, we leverage recent breakthroughs in deep learning to develop a fully differentiable variant of the Gillespie algorithm. The differentiable Gillespie algorithm (DGA) approximates discontinuous operations in the exact Gillespie algorithm using smooth functions, allowing for the calculation of gradients using backpropagation. The DGA can be used to quickly and accurately learn kinetic parameters using gradient descent and design biochemical networks with desired properties. As an illustration, we apply the DGA to study stochastic models of gene promoters. We show that the DGA can be used to: (1) successfully learn kinetic parameters from experimental measurements of mRNA expression levels from two distinct Escherichia coli promoters and (2) design nonequilibrium promoter architectures with desired input–output relationships. These examples illustrate the utility of the DGA for analyzing stochastic chemical kinetics, including a wide variety of problems of interest to synthetic and systems biology.