This proposal focuses on the generation, control, and exploitation of diversity in biology. Genetic diversity drives the evolution of organisms, hinders cures of cystic fibrosis, AIDS and cancer, plays a crucial role in bacterial and fungal infections, and accounts for individual differences in susceptibility to disease agents and the responses to drugs. Non-genetic diversity allows different cells to respond differently to the same environment, differences that can increase the infectivity of pathogens and their resistance to antibiotics. This team will use experiment and theory to study the origin and consequences of biological diversity over scales of size and time that range from the folding of individual proteins to the formation of new species. The goals of the research are: 1) Generating diversity: We will define the rate at which organisms generate diversity. We will determine the distribution of beneficial and deleterious mutations and assess the role of specialized forms of mutation. We will determine the maximum accuracy of regulatory circuits. 2) Controlling diversity: We will study how organisms control the effect of noise. The numbers of copies of any molecule in a cell fluctuates stochastically and cells must deal with errors that produce damaged molecules. We will investigate how evolution and engineering can minimize the effects of noise in processes as diverse as protein folding, gene expression, and circadian clocks. 3) Responding to environmental diversity: Organisms must optimize their response to temporally and spatially variable environments. We will investigate the ability of existing pathways to detect fluctuating environments and examine how organisms evolve to respond to them, 4) Exploiting diversity: We will investigate how selection acts on genetic diversity to produce new phenotypes. We will ask how selection produces a range of biological phenomena, including altered patterns of gene expression, alterations in the host range and social behavior of pathogens, new species, and stable community structures in ecosystems. The core of the proposal is the group of Bauer fellows, young interdisciplinary scientists who come from a variety of backgrounds and interact to form a single collaborative community that nucleates interactions amongst a wide range of research groups.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Specialized Center (P50)
Project #
5P50GM068763-09
Application #
8146096
Study Section
Special Emphasis Panel (ZGM1-CBCB-4 (SB))
Program Officer
Flicker, Paula F
Project Start
2003-09-08
Project End
2013-08-31
Budget Start
2011-09-01
Budget End
2012-08-31
Support Year
9
Fiscal Year
2011
Total Cost
$2,991,769
Indirect Cost
Name
Harvard University
Department
Microbiology/Immun/Virology
Type
Schools of Arts and Sciences
DUNS #
082359691
City
Cambridge
State
MA
Country
United States
Zip Code
02138
Wahl, Mary E; Murray, Andrew W (2016) Multicellularity makes somatic differentiation evolutionarily stable. Proc Natl Acad Sci U S A 113:8362-7
Kastman, Erik K; Kamelamela, Noelani; Norville, Josh W et al. (2016) Biotic Interactions Shape the Ecological Distributions of Staphylococcus Species. MBio 7:
Hormoz, Sahand; Singer, Zakary S; Linton, James M et al. (2016) Inferring Cell-State Transition Dynamics from Lineage Trees and Endpoint Single-Cell Measurements. Cell Syst 3:419-433.e8
Lavrentovich, Maxim O; Wahl, Mary E; Nelson, David R et al. (2016) Spatially Constrained Growth Enhances Conversional Meltdown. Biophys J 110:2800-8
Battle, Christopher; Broedersz, Chase P; Fakhri, Nikta et al. (2016) Broken detailed balance at mesoscopic scales in active biological systems. Science 352:604-7
Kim, Wook; Levy, Stuart B; Foster, Kevin R (2016) Rapid radiation in bacteria leads to a division of labour. Nat Commun 7:10508
Tamari, Zvi; Yona, Avihu H; Pilpel, Yitzhak et al. (2016) Rapid evolutionary adaptation to growth on an 'unfamiliar' carbon source. BMC Genomics 17:674
Muller, Nicolas; Piel, Matthieu; Calvez, Vincent et al. (2016) A Predictive Model for Yeast Cell Polarization in Pheromone Gradients. PLoS Comput Biol 12:e1004795
Renn, Suzy C P; O'Rourke, Cynthia F; Aubin-Horth, Nadia et al. (2016) Dissecting the Transcriptional Patterns of Social Dominance across Teleosts. Integr Comp Biol 56:1250-1265
Möbius, Wolfram; Murray, Andrew W; Nelson, David R (2015) How Obstacles Perturb Population Fronts and Alter Their Genetic Structure. PLoS Comput Biol 11:e1004615

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