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Susan J. Schroeder

Susan J. Schroeder

Susan J. Schroeder

Associate Professor

Research Areas: Physical, Structural Biology
Office: SLSRC 3590

B.S., 1995, University of Rochester, Rochester, NY
Ph.D., 2002, University of Rochester, Rochester, NY
Postdoc, 2002-2005, Yale University, New Haven, Connecticut

Research Keywords: 
biophysical chemistry, viral RNA, virus-host interactions, nanopore sequencing, structural biology, RNA thermodynamics, RNA structure prediction 

NMR Structure of pRNA E-loop hairpin

Exploring RNA Structure, Function, and Energetics

The long-term scientific goal in the Schroeder lab is to understand RNA structure and function well enough to predict its three-dimensional structure. The novel functions and dynamic structures of viral RNA open doors to better understand the fundamental physical interactions that determine RNA structure, function, and energetics.

Experimental constraints define regions of RNA folding funnel

The Schroeder lab research focuses on three areas: satellite tobacco mosaic virus RNA (STMV); prohead RNA (pRNA); and RNA thermodynamic parameters for better RNA interference (RNAi) therapeutics. We are developing better ways to determine STMV RNA structures inside virus particles using crystallography data, chemical probing data, and computational predictions. The experimental and computational methods developed to study STMV RNA will be applied to other viral RNAs, such as Hepatitis B pregenomic RNA and MS2 bacteriophage RNA, which have well-defined in vitro assembly conditions for studies of RNA folding and virus assembly. pRNA is an essential component of a viral packaging motor and self-assembles into RNA nanoparticles. The Schroeder lab explores pRNA tertiary structure and dynamics using a variety of biophysical techniques, including NMR spectroscopy, crystallography, gel shift assays, and ultrafast femtosecond fluorescent spectroscopy.

RNA helices inside satellite tobacco mosaic virus

Measuring RNA thermodynamic parameters for terminal mismatches using UV spectroscopy contributes to the database that forms the core of most RNA prediction programs. Accurate stabilities of terminal mismatches are critical for understanding specificity in RNAi phenomena and reducing off-target effects for RNA therapeutics.