High Throughput Validation of Orphan Riboswitch Candidates

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Riboswitches are cis‐acting gene controlling RNA elements often found in 5′ UTRs of bacterial mRNAs. The discovery of riboswitches and identification of their cognate ligands have led to the revelation of several important biological pathways and processes. At least 40 different riboswitch classes have been experimentally validated, but many more are waiting to be validated (orphan riboswitches). Computational approaches including comparative genomics have proven to be very successful in identifying riboswitch candidates with a high level of confidence. However, these riboswitch candidates need to be experimentally validated by identifying their cognate ligands which can be challenging and may take much more time. Our recent bioinformatics approach to discover rare riboswitch classes by focusing on GC‐rich, long intergenic regions (IGRs) in bacteria continues to add new riboswitch candidates to the growing collection of orphan riboswitches. Therefore, a high throughput and systematic method for the validation of orphan riboswitches is crucial to keep up with the pace of new riboswitch discovery by computational approaches. We are developing a higher throughput strategy to experimentally validate orphan riboswitches. This systematic process of validation includes using bioinformatics to update consensus structure models, biochemical investigation by in‐line probing, and genetic validation using reporter assays. For the initial investigation, we subjected five different orphan riboswitch candidates, SLH, chrB‐a, algC, aceE, and Bifido‐metK to this systemic validation process. We identified Bifido‐metK as the sixth class of riboswitches (SAM‐VI) that sense either S‐adenosylmethionine (SAM) or S‐adenosylhomocysteine (SAH), and the results from the other riboswitch candidates have provided valuable information about their structures and functions. Thus, our improved validation methods should help to expedite the experimental validation of riboswitch candidates and make the riboswitch discovery more productive.Support or Funding InformationM.E.S. was supported by an NIH Cellular and Molecular Biology Training 13 Grant (T32GM007223). This work was also supported by NIH grants to R.B. (GM022778 and DE022340). R.R.B. is also supported by the Howard Hughes Medical Institute.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.