Department of Physics
The development, homeostasis and evolution of organisms are highly complex phenomena that span many scales of time and space. Cellular components (such as genes and proteins) strongly interact with each other to process information to execute developmental programs and robust response to their environment. One approach we take is to study quantitatively small subsets of components and the interactions among them. We aim to characterize the elementary building blocks of cellular networks, understand their functions and limitations, and derive design principles. In particular, our lab is interested in the combined action of different modes of regulation, such as global and specific, transcriptional and post-transcrptional, etc.
However, many biological processes are not limited to a small subset of interactions, and are better described as collective phenomena. We thus need to complement our studies with a more global, phenomenological or statistical, approach. To bridge the gap between small circuits and collective behavior, we will focus on the way by which cells assume different roles and different states in a multi-cellular community. These may be bacterial cells in a community structure or in an animal host, germ cells in the gonads of a worm (the roundworm C. elegans), or adult cells in a regenerating animal (the flatworm S. mediterranea).
Our studies combine theoretical approaches (deriving from statistical mechanics, condensed matter physics and dynamical systems) with experimental methods of molecular biology, imaging, and large-scale approaches.
In bacteria, one mode of communication involves the production, release, and community-wide detection of molecules called autoinducers. In the simplest model, the concentration of these molecules reflects the density of cells, and provides “quorum sensing” capability. A close inspection of quorum sensing pathway in pathogenic bacteria suggests other models for the information content and capacity carried by this signal. Interestingly, regulation by small RNA molecules is abundant in these pathways, suggesting a computational model similar to that of perceptron in neural networks. Our lab uses quantitative single-cell measurements in concert with theoretical analysis (rooted in statistical physics and information theory) to understand the capacity of this mode of communication.
In multi-cellular organisms, cells communicate with each other to coordinate development and function. In many cases, communication is mediated by small molecules, or proteins. Recent findings suggest that small RNA molecules, involved in gene silencing, may be transported among cells and can provide an alternative mode of communication. When communicating through small molecules, the information is encoded in the concentration (“amplitude”) of the signal, whereas in the RNA-based mode the information is encoded in the sequence. This raises the exciting possibility that the two are comparable to analog and digital information channels, respectively. With this in mind, some aspects of microRNA regulation can be modeled as digital processing of analog information. Another perspective is that of quasi-equilibrium vs. out-of-equilibrium regulation (which is probably better describing RNA regulation, as well as the recently described phenomena of RNAp accumulation at developmental promoters). Our lab utilizes concepts of information and communication theory to take an alternative viewpoint at several problems in C.elegans post-embryonic development and S.mediterranea regeneration. We also hope to look at the ability of nematodes to communicate through “environmental RNAi” .
Another interesting aspect of biological communication is the interaction between pathogen bacteria and their hosts. Here one is required to make a distinction between passive sensing of local environment and actual communication, and an ecological and evolutionary perspective is needed. We will use the recently established model of C. elegans – P. aeruginosa pathogenesis for quantitative characterization of the inter-species interactions.
Levine, E., and Hwa, T. (2007). Stochastic fluctuations in biochemical pathways. Proc. Natl. Acad. Sci. 104: 9224.
Levine, E., Zhang, Z., Kuhlman, T., and Hwa, T. (2007). Quantitative characteristics of gene regulation by small RNA. PLoS Biol 5: e229.
Levine, E., MacHale, P., and Levine, H. (2007). MicroRNAs may sharpen spatial expression patterns. PLoS Comp. Biol.. 3(11): e233.
Levine, E., and Hwa, T. (2008). Small RNAs establish gene expression thresholds. Current Opinion in Microbiology 11: 574-579.
Page created and maintained by Xaq Pitkow