(309c) Systematic Mining of Noncoding RNAs for Regulating Complex Phenotypes

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An important question in strain engineering is: how to search the genome for targets that regulate a phenotype of interest? Given the natural role that noncoding RNAs play in coordinating complex stress-responses, there is increasing interest in exploiting these regulators to construct phenotypes of interest that can further expand the current potential for microbial cells. An emerging need in this frontier is the proper identification and selection of functional RNAs that can be engineered for optimal regulation of desired genes and relevant metabolic pathways. Thus far, the number of mechanisms and RNA scaffolds that are being exploited for these applications are highly constrained. Although a large number of “omics” approaches are being attempted to expand the number of RNAs that globally regulate phenotypes, it is unclear how to interpret this massive amount of data in the context of biological pathways and utilize it to uncover underlying biological mechanisms that can be relevant to strain engineering.

This talk will address characterization tools that we are developing to automate the identification of global regulators that could be exploited in constructing synthetic schemes to regulate complex phenotypes.  Specifically, we will present a general pipeline for mechanistically understanding and engineering desirable complex phenotypes based on a rational and predictive systems analysis of global regulation and on the intracellular assaying of relevant targets. Our approach has been applied to microbial organisms with extremophilic traits and has combined bioinformatics, genetics, biophysical models and synthetic parts for prediction of pathways.