Aaron Dinner Professor
Born Chicago, Illinois, 1972.
Harvard University, A.B., 1994, Ph.D., 1999
University of Oxford, 1999-2001.
University of California, Berkeley, 2001-2003.
University of Chicago, Professor, 2003-
2008 Alfred P. Sloan Fellow.
2006 NSF CAREER Award.
2005 Searle Scholar.
2003 Dreyfus New Faculty Award.
2000-2001 Linacre College EPA Cephalosporin Junior Research Fellow.
1999 Burroughs Wellcome Fund Hitchings-Elion Postdoctoral Fellow.
1994-1999 Howard Hughes Medical Institute Predoctoral Fellow.
OFFICE: Gordon Center E139E, 929 E 57th St.
PHONE: (773) 702-2330
FAX: (773) 834-5250
The Dinner group develops and applies theoretical methods for relating cellular behavior to molecular properties. We are particularly interested in how proteins regulate access to genes in the context of the development of the immune system. Understanding how such complex behavior arises from physical and chemical features is a problem in fundamental statistical mechanics, but its solution has direct implications for treating autoimmune pathologies and cancers as well as improving vaccination strategies.
One feature that makes theoretical studies of cellular behavior challenging is that the relevant dynamics span a hierarchy of time and length scales ranging from Angstroms and femtoseconds to micrometers and minutes. Experiments are now beginning to bridge gaps in spatial and temporal resolution, and models are vital for design and interpretation of such measurements. Our research thus blends atomic-resolution simulations with coarse-grained numerical and analytical approaches, often in collaboration with experimental groups.
Gene regulation during development and function of the immune system
Over the last decade, advances in techniques for characterizing molecular populations and positions in cells have driven a revolution in our systems-level understanding of biological design principles. In particular, a dialog between theory and experiment has revealed how cells process information about their environments to make decisions despite inherent noise. However, the bulk of this work has been in relatively simple unicellular organisms. There is now the opportunity to begin making similar progress in cells of higher organisms, which can reveal new emergent behaviors. We are thus integrating experimental data to construct phenomenological models for the gene regulatory networks that control myeloid and lymphoid cell fate choice in mammalian blood. These studies are important from a biological perspective because the cooperative nature of the dynamics hinders intuition of responses to experimental probes. Motivated by these studies, we have also explored systematic analytical treatments of master equation representations of cell signaling and gene expression. These models account for stochastic effects and the discrete nature of copy numbers of participating molecules.
Path sampling reveals the dynamics of DNA binding at atomic-resolution
DNA transcription, recombination, replication, and repair are all regulated by proteins that bind specific sites on DNA. Despite small copy numbers in cells, such proteins can locate target elements among billions of base pairs thousands of times faster than allowed by a three-dimensional random walk. To objectively evaluate how putative search mechanisms arise in specific molecular situations, which is essential to ultimately be able to make defined interventions, atomic-resolution simulations based on transferable potentials are required.
Building on the transition path sampling framework introduced by David Chandler and co-workers, we have introduced general means for harvesting and statistically characterizing rare events in complex systems and applied them to understand how a DNA repair protein searches for damage.
Nonequilibrium statistical mechanics
Because biological systems operate far from equilibrium, our research on specific problems often touches on general issues at the forefront of fundamental statistical mechanics. Here, my group and I are striving to develop systematic means for projecting complex dynamics onto a small number of degrees of freedom. Doing so is essential for connecting models with single-molecule measurements that probe dynamics, including in cellular contexts. A major contribution that we made in this area was the introduction of an umbrella-sampling-like algorithm for determining the steady-state probability distribution of an ergodic system arbitrarily far from equilibrium. We also proved analytically that projection shifts the distribution of single-trajectory entropies on which fluctuation theorems (FTs) are based towards one characteristic of an equilibrium process. Such studies are important because FTs provide hints of a unified theoretical framework for systems far from equilibrium.
1. Li, Y., Qu, X., Ma, A., Smith, G. J., Scherer, N. F. & Dinner, A. R. Models of single-molecule experiments with periodic perturbations reveal hidden dynamics in RNA folding. J. Phys. Chem. B, 113, 7579-7590 (2009).
2. Dickson, A., Warmflash, A., & Dinner, A. R. (2009) Nonequilibrium umbrella sampling in spaces of many order parameters. J. Chem. Phys., 130, 074104 (2009).
3. Warmflash, A. & Dinner, A. R. (2008) Signatures of combinatorial regulation in intrinsic biological noise. Proc. Natl. Acad. Sci. USA, 17262-17267 (2008).
4. Hu, J.; Ma, A.; Dinner, A. R. A two-step nucleotide-flipping mechanism enables kinetic discrimination of DNA lesions by AGT. Proc. Natl. Acad. Sci. USA, 105, 4615-4620 (2008).
5. Li, Y.; Bhimalapuram, P.; Zhao, T.; Dinner, A. R. How the nature of an observation affects single-trajectory entropies. J. Chem. Phys., 128, 074102 (2008).
6. Warmflash, A.; Bhimalapuram, P.; Dinner, A. R. Umbrella sampling for nonequilibrium processes. J. Chem. Phys., 127, 154112 (2007).
7. Warmflash, A. & Dinner, A. R. A model for TCR gene segment use. J. Immunol. 177, 3857-3864 (2006).
8. Laslo, P.; Spooner, C. J.; Warmflash, A.; Lancki, D.W.; Lee, H.-J.; Sciammas, R.; Gantner, B.N.; Dinner, A.R.; Singh, H. Multilineage transcriptional priming and stabilization of alternate hematopoietic cell fates. Cell, 126, 755-756 (2006).
9. Hu, J., Ma, A. & Dinner, A. R. Monte Carlo simulations of biomolecules: The MC module in CHARMM. J. Comp. Chem. 27, 203-216 (2006).
10. Ma, A.; Dinner, A. R. An automatic method for identifying reaction coordinates in complex systems. J. Phys. Chem. 109, 6769-6779 (2005).