"A theoretical framework for gene induction and experimental comparisons".
Karen M. Ong a, John A. Blackford Jr.b , Benjamin L. Kagan b, 1 , S. Stoney Simons Jr. b, @, and Carson C. Chow a, @,
a Laboratory of Biological Modeling, National Institute
of Diabetes and Digestive and Kidney Diseases,
b Steroid Hormones Section, National Institute of Diabetes
and Digestive and Kidney Diseases/Clinical Endocrinology Branch, National
Institutes of Health, Bethesda, MD 20892
1 Present address: Department of Oncology, Lombardi Cancer
Center, Georgetown University, Washington, DC 20057.
@ To whom correspondence may be addressed:
E-mail: carsonc@mail.nih.gov
or steroids@niddk.nih.gov
Author contributions: S.S.S. and C.C.C. designed research; K.M.O.,
J.A.B., B.L.K., S.S.S., and C.C.C. performed research; K.M.O. and C.C.C.
performed the mathematical analysis; K.M.O., S.S.S., and C.C.C. analyzed
data; and K.M.O., S.S.S., and C.C.C. wrote the paper.
Approved March 2, 2010 (received for review September 25, 2009)
Ligand-mediated gene induction by steroid receptors is a multistep process characterized by a dose–response curve for gene product that follows a first-order Hill equation. This behavior has classically been explained by steroid binding to receptor being the rate-limiting step. However, this predicts a constant potency of gene induction (EC50) for a given receptor-steroid complex, which is challenged by the findings that various cofactors/reagents can alter this parameter in a gene-specific manner. These properties put strong constraints on the mechanisms of gene induction and raise two questions: How can a first-order Hill dose–response curve (FHDC) arise from a multistep reaction sequence, and how do cofactors modify potency? Here we introduce a theoretical framework in which a sequence of steps yields an FHDC for the final product as a function of the initial agonist concentration. An exact determination of all constants is not required to describe the final FHDC. The theory predicts mechanisms for cofactor/reagent effects on gene-induction potency and maximal activity and it assigns a relative order to cofactors in the sequence of steps. The theory is supported by several observations from glucocorticoid receptor-mediated gene induction. It identifies the mechanism and matches the measured dose–response curves for different concentrations of the combination of cofactor Ubc9 and receptor. It also predicts that an FHDC cannot involve the DNA binding of preformed receptor dimers, which is validated experimentally. The theory is general and can be applied to any biochemical reaction that shows an FHDC.
keywords: dose-response, Michaelis-Menten, gene
expression, steroid receptors, glucocorticoids,
pharmacology
http://www.pnas.org/content/early/2010/03/22/0911095107/suppl/DCSupplemental
1. Frenster JH, and Hovsepian JA,
"Models of
successive levels of resolution during individual gene transcription".
1. Each cell retains all of its embryonic genes for a lifetime.
2. Controls for embryonic genes are often absent in adults.
3. Uncontrolled embryonic genes can replicate wildly.
4. Replicating genes participate in intra-cellular competition.
5. The basis for gene competition is selective transcription.
6. MicroRNAs can reprogram embryomic transcription.
7. Gene reprogramming can produce normal phenotypes.
8. Normal phenotypes can by-pass chromosomal lesions.
9. MicroRNA therapy may need to be permanent.
10. Transplantation of microRNAs could be preferred.
1. Pathways within cell genomes involve a flow of information.
2. Information can flow by direct contact or by third parties.
3. Direct contact within whole genomes is difficult to regulate.
4. DNA-DNA direct contects are influenced by agents.
5. Nuclear agents include hydrophilic ionic and hydrophobic conforming ligands.
6. Third parties within genomes involve RNAs and proteins.
7. RNAs and proteins are easy to regulate or reverse.
8. Information can be shared, lost, or transformed.
9. System information can be hidden during system isolation.
10. Local information can be permanently lost during system entropy.
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