Gene regulation ? how genes are turned on in the right place, at the right time and in the right amount ? is a problem central to most areas of biology and medicine. Our understanding of gene regulation began with classical studies in bacteria, which introduced the idea that proteins called ?transcription factors? (TFs) determine which gene is turned on by binding to regulatory DNA sequences and recruiting RNA polymerase (RNAP). The situation in eukaryotes, however, is far more complicated. We focus in this proposal on two critical aspects of eukaryotic gene regulation that are not addressed in the bacterial paradigm. First, eukaryotic DNA is packaged into chromatin and accessibility to TF binding sites is dynamically re-organised by continuously expending external sources of energy, such as ATP. Second, in eukaryotes multi-protein co- regulators such as mediator and CREB-binding protein (CBP) intercede between TFs and RNAP, serving as ?integrators? of regulatory information. Pioneering studies from several laboratories have identified many of the molecular components involved in this regulatory complexity, however, the quantitative concepts used to reason about how eukaryotic gene regulation are still largely based on the bacterial paradigm. This is an alarming discrepancy in light of the central importance of gene regulation. In recent work, we used mathematical models rooted in physics to show that this bacterial paradigm cannot account for experimentally measured data in eukaryotes. We examined, in particular, the question of how sharply a gene is turned on in response to a TF, an important property in many contexts. We introduced new concepts for analyzing information integration by co-regulators and energy expenditure and showed how these processes could explain the observed sharpness. In this proposal, we seek to build upon this highly-productive, inter-disciplinary collaboration. We will integrate mathematical theory with quantitative experiments in the well-studied model organism Drosophila melanogaster to identify which molecular mechanisms of information integration and energy expenditure are involved in regulating the developmental gene hunchback, whose sharp expression is crucial for patterning the early fruitfly embryo. As in the classical bacterial studies, we anticipate that a deep analysis of this particular gene will provide a new foundation on which to understand in quantitative terms the regulation of other eukaryotic genes and thus, that this study will have broad impact across biology and medicine.

Public Health Relevance

For a gene to function properly, it must be active in the right place, at the right time and in the right amount. Changes in any of these features can lead to disease. This proposal uses mathematical theory and experiment to understand how information about the appropriate place, time and amount of gene activity is encoded in the genome, to help determine the causes of disease directly from DNA sequence.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM122928-02
Application #
9469533
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Resat, Haluk
Project Start
2017-04-10
Project End
2021-03-31
Budget Start
2018-04-01
Budget End
2019-03-31
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Harvard Medical School
Department
Biology
Type
Schools of Medicine
DUNS #
047006379
City
Boston
State
MA
Country
United States
Zip Code
Vincent, Ben J; Staller, Max V; Lopez-Rivera, Francheska et al. (2018) Hunchback is counter-repressed to regulate even-skipped stripe 2 expression in Drosophila embryos. PLoS Genet 14:e1007644
Bentovim, Lital; Harden, Timothy T; DePace, Angela H (2017) Transcriptional precision and accuracy in development: from measurements to models and mechanisms. Development 144:3855-3866
Samee, Md Abul Hassan; Lydiard-Martin, Tara; Biette, Kelly M et al. (2017) Quantitative Measurement and Thermodynamic Modeling of Fused Enhancers Support a Two-Tiered Mechanism for Interpreting Regulatory DNA. Cell Rep 21:236-245