Programmable low-cost DNA-based platform for viral RNA detection

Lifeng Zhou; Arun Richard Chandrasekaran; Jibin Abraham Punnoose; Gaston Bonenfant; Stephon Charles; Oksana Levchenko; Pheonah Badu; Cassandra Cavaliere; Cara T. Pager; Ken Halvorsen

Having shown successful detection of ZIKV RNA using a single target sequence, we recognized that we could exploit the large genome size (~11,000 nucleotides) to increase our detection signal through multiple targets. Once the long viral RNA is fragmented, the number of available target sequences increases dramatically. Since our detection signal is proportional to the number of looped nanoswitches, a nanoswitch mixture for different target sequences within the viral genome is expected to provide an increased signal. To test this, we developed an algorithm for choosing multiple sequence regions in the viral genome that can be targeted by the nanoswitches (Note S1). First, we chose the default target length as 30 nucleotides based on results from screening nanoswitches with different detection arm lengths (Fig. S3) . Then, the algorithm selectively excluded target sequences that could form stable secondary structures (Fig. S4 ) and cross-binding with nanoswitch backbone oligos (Fig. S5) , and enforced GC content and uniqueness of sequences. Based on these criteria, we chose 18 target regions along the entire ZIKV RNA for testing and designed the nanoswitches. To facilitate use of our Matlab-based software, we have built a graphical user interface (Fig. S6 ) and made it freely available (File S1).