Information stored in genes is realized through the process of transcription. While transcription of individual genes is understood as a biochemical reaction in a great deal of molecular detail, the transcription of gene ensembles cannot yet be studied in a framework of the reduced biochemical reaction. It is also likely that even if we were equipped to study ensemble activities with high molecular precision, we would miss essential macroscopic properties of the processes that govern transcription of gene ensembles in the cell. The most basic and fundamental is the process of transcription as a function of position of the genes on a chromosome. The fundamental nature of it can be underscored by the notion that at the deterministic basis of this process lays the structure of a chromosome - a critical piece of knowledge about the cell. Indeed, the relationship between structure and function is one of the fundamental principles in molecular biology. The relationship between molecular structure and function has been used very successfully to propose, understand, and verify mechanisms of action of individual protein and DNA molecules as well as their motifs. However, our understanding of organization of the higher order macromolecules, such as chromosomes, has been slow and ineffective largely due to the low-resolution capacity of indirect techniques and invasive nature of the direct ones. Whole genome DNA microarrays designed using complete sequence information made possible direct read-out of genome's activity at a single gene resolution and higher. My laboratory uses this technique to: i) directly study and model the structure of the Escherichia coli K12 (E. coli) chromosome; ii) determine how the structure of the chromosome influences its activity and vice versa. We demonstrated that variations in gene activity as a function of gene position contain useful information about the process of transcription and are not entirely random: significant short- (~ 5 kb) and long-range correlations (~ 90kb) can be detected in transcriptional spatial data series by using standard analytical tools borrowed from signal processing, information theory and statistics. I propose to extend the combined use of theoretical approaches with direct experimentation to determine: 1) the effects of internal and external perturbations, which are known to affect global chromosomal state(s), on the observed spatial correlations; 2) dynamic distribution of DNA biding proteins that are known to control global DNA properties; 3) 3-D structure of the bacterial chromosome. As a result of these studies I expect to be able to model mechanistic and structural basis for the chromosome activity. This work will reveal a new level of organization of prokaryotic genetic material and its role in bacterial physiology, and also will provide a framework for studying spatial interactions in the chromosomes of higher organisms.
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