Recent discoveries of biologically fundamental non-coding RNAs are inspiring novel antibacterial, antitumor, and antiviral therapies that might disable or manipulate the molecules involved. However, in silico folding models cannot yet confidently predict RNA conformations in vitro, slowing the development of these potentially life-saving efforts. To develop the next-generation of robust and rigorously tested RNA bioengineering rules, we are exploring an unconventional strategy: last year, we released a citizen science project enabling non-experts to develop and test folding hypotheses in internet-scale RNA design competitions that are rigorously scored through wet-lab feedback. Launched in early 2011, the 25,000-player EteRNA project already outperforms existing previous methods for designing novel RNA structures which fold properly in vitro. The critical next stage is to sustain and formalize the RNA nanoengineering insights preserved within the EteRNA community. We propose steps to consolidate the community's experimentally validated human computation into a suite of automated design algorithms (EteRNAbot) usable by the entire RNA nanoenginering community. Beyond compiling such cases, we will crowd-source the rigorous search and resolution of in silico and in vitro design failures with thousands of new experiments. Finally, we will deploy the EteRNA- 3D interface for both expert and crowd-sourced three-dimensional design, leveraging a growing database of 3D building blocks and the ROSETTA RNA folding/design algorithms. We will evaluate success in each aim via synthesis and single-nucleotide- resolution chemical mapping of novel designs through our high-throughput wet-lab pipeline. More generally, we will evaluate success by assessing the extent of utilization and citation of the automated design tools;the extent of mining and citation of the publically available RNA Mapping Database generated for the project;and the adoption of the EteRNA paradigm for Internet-scale scientific discovery in biomedical computation problems beyond nucleic acid design.
RNA molecules play fundamental roles in transmitting and regulating genetic information in all living systems, including disease-causing bacteria, retroviruses like HIV, and tumor cells. New potentially life-saving therapies that target these RNAs are being hindered by the slow rate of designing RNA sequences with new folds and interactions. The proposed research seeks to resolve this bottleneck by enabling tens of thousands of citizen scientists to hypothesize new rules for robust RNA design and to test these ideas via high-throughput RNA synthesis and chemical experimentation.
|Yesselman, Joseph D; Tian, Siqi; Liu, Xin et al. (2018) Updates to the RNA mapping database (RMDB), version 2. Nucleic Acids Res 46:D375-D379|
|Omabegho, Tosan; Gurel, Pinar S; Cheng, Clarence Y et al. (2018) Controllable molecular motors engineered from myosin and RNA. Nat Nanotechnol 13:34-40|
|Denny, Sarah Knight; Bisaria, Namita; Yesselman, Joseph David et al. (2018) High-Throughput Investigation of Diverse Junction Elements in RNA Tertiary Folding. Cell 174:377-390.e20|
|Anderson-Lee, Jeff; Fisker, Eli; Kosaraju, Vineet et al. (2016) Principles for Predicting RNA Secondary Structure Design Difficulty. J Mol Biol 428:748-757|
|Yesselman, Joseph D; Das, Rhiju (2016) Modeling Small Noncanonical RNA Motifs with the Rosetta FARFAR Server. Methods Mol Biol 1490:187-98|
|Lee, Seungmyung; Kim, Hanjoo; Tian, Siqi et al. (2015) Automated band annotation for RNA structure probing experiments with numerous capillary electrophoresis profiles. Bioinformatics 31:2808-15|
|Yesselman, Joseph D; Das, Rhiju (2015) RNA-Redesign: a web server for fixed-backbone 3D design of RNA. Nucleic Acids Res 43:W498-501|
|Cordero, Pablo; Das, Rhiju (2015) Rich RNA Structure Landscapes Revealed by Mutate-and-Map Analysis. PLoS Comput Biol 11:e1004473|
|Treuille, Adrien; Das, Rhiju (2014) Scientific rigor through videogames. Trends Biochem Sci 39:507-9|
|Seetin, Matthew G; Kladwang, Wipapat; Bida, John P et al. (2014) Massively parallel RNA chemical mapping with a reduced bias MAP-seq protocol. Methods Mol Biol 1086:95-117|
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