Research

Our laboratory pursues a wide variety of research applying innovative high throughput experimental methods, bioinformatics, and biophysical simulations to understand and model regulatory networks. Some of our current areas of interest include:

Global mapping of bacterial transcriptional regulatory states

Using a combination of IPODHR (a recently developed method for genome-wide profiling of protein-DNA interactions), ChIP-seq, RNA-seq, and bioinformatic analysis, we are elucidating the complete regulatory logic underlying starvation responses, persistence, and responses to antibiotic challenge in E. coli. Future applications of similar methods to less well-studied bacteria will enable the rapid mapping of previously uncharacterized regulatory networks with a compact set of experiments. 

Group members: Tom GossRebecca HurtoHaley M. AmemiyaChristine A. Ziegler

Bacterial chromosomal architecture and gene expression

Through application of IPODHR, we have characterized the presence of broad, heterochromatin-like regions of high protein occupancy and low gene expression on the chromosomes of a variety of bacterial species. We are using a combination of classical genetics, targeted protein pulldowns, expression profiling, and ongoing protein occupancy profiling experiments to determine the composition and physiological roles of these regions, as well as their effects on gene expression and on the evolutionary trajectories followed by bacterial populations.

Group members: Tom Goss, Scott Scholz

Structure-based functional annotation of bacterial genomes

Recent advances in high-throughput sequencing technology have lead to an explosion in the number of genomic sequences available, but our ability to provide high quality annotations lags far behind. The gap is particularly apparent in the field of microbiology, where thousands of taxa are potentially influential or useful in human health and disease, environmental settings, and synthetic biology applications. Our ability to take advantage of our growing body of sequence knowledge thus hinges primarily on computational annotations of newly sequenced genomes. Almost all currently available annotations are based on sequence-homology transfer, which is accurate for highly homologous sequences but drops in accuracy as sequence identities fall below 50%. Unfortunately, the vast majority of known protein sequences have less than 50% identity to any protein with high quality experimental annotations, and thus a different approach is called for. In collaboration with the Yang Zhang laboratory here at Michigan, we are developing and applying pipelines for whole-proteome structural prediction and functional annotation for bacterial genomes, and have already demonstrated performance competitive with, and in some cases superior to, existing sequence-based methods.

Group members: Catherine BarnierChengxin Zhang

Logic and dynamics of regulatory networks

Gene regulatory networks provide cells, especially those of free-living microbes, with the ability to sense and respond to their environments. In many cases, we have found that the behavior enabled by these networks goes beyond common models such as the lac operon; we observe that regulatory networks can and do evolve to anticipate future stresses, and even enable constructive responses to fundamentally new challenges. We use a combination of bioinformatics, mathematical modeling, and targeted experiments to identify the ecological reasons for existing regulatory structures, and build our ability to predict how cells may respond to future stresses.
Group members: Ali FarhatRucheng Diao

Gene regulation in metazoan energy usage and obesity

Obesity is a major risk factor in a wide variety of diseases including diabetes, cancer, and heart disease. We are working to understand the information flow governing how animals regulate both energy usage in the body, and subsequent changes to behavior as a result of energy availability, at the cellular level. Our interest in energy usage is focused on the ribonuclease Nocturnin, a gene known to regulate fat metabolism in both mice and humans through unknown mechanisms. We are collaborating with the laboratories of Dr. Ray Trievel and Dr. Aaron Goldstrohm to determine both the mechanism and targets of Nocturnin. At a behavioral level, in collaboration with Dr. Monica Dus, we are mapping the effects of high sugar diets on gene regulation in Drosophila neurons, and have identified major rearrangements of neuronal regulatory states in response to energy surplus.

Group members: Rucheng Diao