13 May 2015 Next-generation DNA in pathogen detection, surveillance, and CLIA-waivable diagnostics
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Assays that target DNA and RNA (xNA) are regarded as the “gold standards” in pathogen detection, surveillance, and diagnostics. However, they are often considered inappropriate for use at points-of-sampling and in low resource environments. This paper discusses innovations created by scientists at the FfAME and Firebird that promise to change this. The first is an artificially expanded genetic information system (AEGIS), a species of DNA having eight nucleotide "letters" added to the four found naturally in DNA. AEGIS nucleobases pair with geometries similar to standard Watson- Crick pairs, but with hydrogen bonding patterns different from (and orthogonal to) patterns that join the A:T and G:C pairs. Thus, AEGIS DNA allows xNA capture and amplification to have very high specificity and very low noise. A second innovation is a self-avoiding molecular recognition system (SAMRS). SAMRS is a species of DNA that behaves the opposite of AEGIS; SAMRS oligonucleotides bind with Watson-Crick complementarity to natural DNA, but not to other SAMRS oligonucleotides. A third innovation is a molecule beacon design that signals the presence of a target xNA even in complex biological mixtures. A fourth innovation is isothermal amplification of xNA targets, without PCR instruments or the skills needed to interpret their output. Here, levels of detection are as few as 30 molecules. Finally, we offer a sample preparation architecture that, as its very first step, sterilizes a sample, rendering it non-hazardous to inexperienced users. It then allows complete xNA capture and CLIA-waivable amplification.
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Steven A. Benner, Steven A. Benner, Hyo-Joong Kim, Hyo-Joong Kim, Kristen B. Merritt, Kristen B. Merritt, Zunyi Yang, Zunyi Yang, D. Chris McLendon, D. Chris McLendon, Shuichi Hoshika, Shuichi Hoshika, Daniel Hutter, Daniel Hutter, } "Next-generation DNA in pathogen detection, surveillance, and CLIA-waivable diagnostics", Proc. SPIE 9490, Advances in Global Health through Sensing Technologies 2015, 94900K (13 May 2015); doi: 10.1117/12.2183481; https://doi.org/10.1117/12.2183481

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