Experimental data from such fields as structural biology, proteomics, and genomics are providing enormous amounts of information about the intracellular world of bacteria. What is currently missing is a combined structural model of the bacterial cell that integrates these disparate sources of data in such a way that allows key biological processes to be simulated as they might occur in vivo. The goal of the proposed project, therefore, is to continue development of computational methods intended in the long-term to allow structural models of entire bacterial cells to be constructed and simulated. The laboratory has previously reported a structural model of the cytoplasm of the gram-negative bacterium Escherichia coli. Current and future work will seek to extend that work and focus on developing high-resolution models of the chromosome of E. coli and its nucleoid-associated proteins: current chromosome models are at levels of resolution too coarse to allow molecular-level interpretations of behavior. The resulting models will be used to explicitly simulate proteins searching for their genomic binding sites and to model aspects of short-time chromosomal dynamics that have recently become amenable to experimental study. In both cases it is anticipated that the ability to directly interpret the observed behavior in terms of the underlying chromosomal structure will provide important mechanistic insights unattainable by any other method. In addition to chromosomal work, efforts will continue to construct quantitatively-predictive models of the effects of crowded intracellular conditions on protein folding behavior. Accompanying these application-oriented studies will be method-development work focused on developing simple but realistic descriptions of interactions between all types of biomolecule that are found in the cell and on implementing methods to rapidly compute these and other interactions (e.g. hydrodynamics) on the cellular scale. Progress in each of these general project areas will be assessed by making repeated quantitative comparisons with experimental data that are already available in the literature for the exact same biomolecular systems. As well as potentially providing quantitative insights into a number of aspects of protein and chromosomal behavior in vivo, the proposed work will deliver to the community computer simulation code and accompanying potential functions suitable for modeling a wide range of biomolecular systems. The simulation code, the high-resolution models of the chromosome, and all other data accrued during pursuit of the proposed work, will be made freely available in downloadable form. The proposed work is relevant to public health because its long-term goal is the construction of a complete structural model of an important bacterial pathogen ? Escherichia coli ? and because it seeks to understand, through the use of molecular simulations, how the biological processes that underpin life operate in vivo. The former aspect of the work may lead to the identification of new therapeutic strategies for dealing with bacterial pathogens; the latter may illuminate intracellular disease states in higher organisms such as humans.

Public Health Relevance

Developing a molecular-level view of intracellular behavior represents an important step toward understanding how dysregulation of biological processes can lead to disease. The proposed project seeks to achieve such a view for the model bacterium Escherichia coli by working toward a long-term goal of constructing and simulating structural models of entire bacterial cells. Achieving such a goal will not only provide fundamental insights into intracellular behavior, it may also provide a route to identifying new ways to combat pathogenic bacteria.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Unknown (R35)
Project #
3R35GM122466-02S1
Application #
9704435
Study Section
Special Emphasis Panel (ZGM1)
Program Officer
Lyster, Peter
Project Start
2017-08-01
Project End
2022-07-31
Budget Start
2018-08-01
Budget End
2019-07-31
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of Iowa
Department
Biochemistry
Type
Schools of Medicine
DUNS #
062761671
City
Iowa City
State
IA
Country
United States
Zip Code
52242