ze various accomplishments in the field of RNA structure Stuart Le Grice (CCR) and myself edited a special edition of the Methods journal entitled Advances in RNA Structure Determination. The edition included 19 contributions, including one from my group, each describing various methodologies used in RNA structure prediction and analysis. Examples of contributions included descriptions of methods for labeling RNAs at specific sites, the use of small angle x-ray scattering and atomic force microscopy, the use of SHAPE, hydroxyl radical footprinting, FRET, aptamer development, computational methodologies including coarse-grained simulation techniques, RNA folding and 3D structure prediction, a database of RNA motifs and a method for generating RNA-based nanorings. The issue is quite comprehensive, covering the current state of the art of RNA structure. Our previous discovery of the structure of the turnip crinkle virus tRNA-like translational enhancer (TCV TSS) has permitted us to pursue the use of a relatively new technique for understanding the structural characteristics of an RNA when optical tweezers are applied to pull the molecular structure apart. Essentially a force is applied to the 5 and 3 prime ends of the molecule, which is then monitored. Force changes are then correlated with structural features. The pulling experiments, in collaboration with Anne Simon, are being correlated to simulated steered molecular dynamics, which enables the visualization of the unfolding events of the molecule as a function of the pulling speed and forces applied. Coarse-grained and explicit solvent techniques are being used to elucidate the structural characteristics. This technique offers a unique methodology for understanding RNA structure and the characteristics of various RNA motifs found in the structure. The Zika virus is an emerging threat in the world. Although mostly prevalent in tropical zones it appears to be spreading to more temperate climates in the northern hemisphere due to the female Aedes aegypti mosquito. Warnings have been issued to pregnant women due to the potential for the virus to affect fetal development e.g. microcephaly. Zika virus is a Flavivirus and is related to the dengue viruses as well as other viruses in the Flaviviridae family. Due to our recent collaborations with R. Padmanabhan, and publications on the dengue virus, we collaborating on determining the structural characteristics of the virus some of which appear to be similar to the dengue structure. A minigenome is being constructed to further elucidate the mechanisms involved in Zika viral replication and translation. We are also pursuing, in collaboration with Shuo Gu, a comprehensive examination of potential RNA-RNA interactions that are found in cells. MySeq reads are being examined and correlated with computational analysis of potential interactions. The prevalence or lack thereof is being determined to enable a better understanding of how cellular RNA interacts with its cellular environment. The functionality of Drosha in cellular systems is important for understanding the processing of microRNAs and how they relate to normal cellular activity as well as diseases such as cancer.In another collaboration with Shuo Gu we are working on understanding the relationship of Drosha targeted stem-loop structures and the number of microRNA isforms that are produced. Experimental and computational approaches are being applied to determine these relationships. From initial results bent or distorted structures in the targeted Drosha stem seem to facilitate the production of alternate forms of microRNA. Structural predictions and experimental results are being compared and correlated. A collaboration with Esta Sterneck's laboratory was recently initiated. Her lab investigates cell signaling pathways involved in breast and glioblastoma tumorigenesis with a focus on the transcription factor CCAAT/enhancer binding protein delta (CEBPD) using in vitro cell culture and in vivo mouse model systems. Using a transgenic mouse model of breast cancer, Her group has shown that CEBPD exhibits a dual role in mammary tumorigenesis. On the one hand, CEBPD prevents tumor multiplicity and on the other hand, CEBPD promotes distant lung metastases. In addition, CEBPD promotes stem-like cancer cells, which have been implicated in tumor metastasis and treatment resistance, in breast and glioblastoma tumor cells through regulation of various signaling pathways and stemness. In addition, strategies for targeting the message of CEBPD are necessary to downregulate CEBPD-mediated tumor progression signaling. As a tie in to our nanobiology project, our laboratory is developing approaches for RNAi therapeutics to knock down the CEBPD mRNA by delivering strategically designed RNA nanostructures as their own entities or in combination with lipid carriers. Due to the need to robustly produce large quantities of RNA of various lengths and for various purposes, a collaboration with Mikhail Kashlev, an expert in transcription, has been established to accomplish this purpose using a common enzyme, E. coli RNA polymerase. This need has arisen, in part, due to the establishment of the RNA Biology Laboratory, potential needs as a therapeutic, as well as existing requirements of the NIH community. Currently, scaled production costs are quite high when ordering from companies that specialize in production. Costs become even more prohibitive when modified bases need to be included at specific positions within the RNA. Typically, chemical synthesis techniques are limited to under 100 bases and a common method of using RNA T7 polymerase, which may be useful for certain sequences does not perform well for all sequence compositions when modified bases are required. The use of E. coli RNA polymerase provides a potential avenue for the robust production of RNA for a variety of needs. Initial experiments applying this methodology look encouraging. The prediction of RNA secondary and 3D structures containing non-canonical base pair interactions is a difficult and important problem that needs better algorithms. We are developing a set of computational algorithms to enable the prediction of canonical and more importantly non-canonical base pair interactions in RNA. A large database has been compiled containing a multitude of structures including the non-canonical base pair interactions. The algorithms have shown significant utility, enabling the prediction of complex motifs at the secondary structure level. These results are then being used in conjunction with an RNA 3D structure generation program, which enables the prediction of 3D RNA structures that incorporate the complex non-canonical interactions. This set of algorithms are also being applied to the prediction of multi-sequence RNA nano-assemblies.
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