Transcriptional regulation via protein-DNA interactions plays an important role in the regulatory networks of all known organisms. Bacterial regulatory networks are now an especially fruitful target for detailed investigation: as antibiotic-resistant bacteria continue to emerge as a global health threat, new and innovative approaches to either preventing virulence or impairing bacterial growth are required. As our ability to predict and exploit bacterial behavior for therapeutic purposes hinges on our understanding of the logic behind their regulatory networks, it is of great utility to fully map those networks and the molecular mechanisms underlying them. Several challenges, both old and newly recognized, stand in the way of a comprehensive understanding of regulatory logic, even in well-studied models such as Escherichia coli. Progress in mapping bacterial regulatory networks has in general been slow, requiring a steady march of mapping binding sites of one transcription factor (TF) at a time. Even when such experiments are done, they can typically be performed only under a handful of physiological conditions, and thus may miss key contributions of a transcription factor in responding to specific environmental triggers. In addition, contrary to prevailing dogma over the last several decades, we and others have recently gathered substantial evidence that bacterial chromosomes are in fact not universally accessible to transcription, but rather, that they are packaged by densely protein occupied heterochromatin-like regions that we refer to as EPODs, which influence both overall chromosomal architecture and transcriptional regulation in particular. Progress in the area of fully charting bacterial regulation of transcription via DNA binding proteins thus simultaneously requires more efficient coverage of transcription factor space and an improved understanding of the role of larger-scale protein occupancy in gene regulation. We have optimized a technology referred to as IPODHR for overall profiling of protein occupancy on bacterial genomes, similar to the signal provided by ATAC-seq in eukaryotes. Building on IPODHR data sets as a cornerstone, we are pursuing several highly innovative and efficient approaches to expand our understanding of bacterial regulatory networks: Massively parallel profiling of TF occupancy. Tracking IPODHR signal across known TF binding sites, in tandem with appropriate bioinformatic analysis, provides occupancy information on dozens of known TFs in a single experiment. We will utilize this technology to profile TF binding under a broad range of conditions. Identification of orphan TFs. IPODHR profiles enable us to identify active regulatory sites under conditions of interest, and identify the responsible TFs through follow-up experiments and bioinformatics. Regulatory roles and molecular biology of EPODs. IPODHR has revealed the presence of EPODs across a wide range of bacterial taxa, and we will determine the full impact of EPODs on condition-dependent gene regulation, and the molecular mechanisms through which these regions are established.

Public Health Relevance

Bacteria rely on their regulatory networks to respond appropriately to challenges in their surroundings, enabling them to survive stress and take advantage of food sources. Our ability to manipulate bacterial behavior, whether for the purpose of combatting infection or optimizing biotechnological applications, will be greatly enhanced by improving our understanding of the wiring that drives bacterial decisions. We will utilize a recently developed suite of tools to rapidly dissect the regulatory networks of a wide variety of bacteria, and in the process gather a far deeper understanding of how the interplay of local and large-scale protein-DNA interactions govern bacterial behavior.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Unknown (R35)
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Special Emphasis Panel (ZGM1)
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Sledjeski, Darren D
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University of Michigan Ann Arbor
Schools of Medicine
Ann Arbor
United States
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Wolfe, Michael B; Goldstrohm, Aaron C; Freddolino, Peter L (2018) Global analysis of RNA metabolism using bio-orthogonal labeling coupled with next-generation RNA sequencing. Methods :