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Large Phenotypic Enhancement of Structured Random RNA Pools.

  • Author(s): Chizzolini, Fabio
  • Passalacqua, Luiz FM
  • Oumais, Mona
  • Dingilian, Armine I
  • Szostak, Jack W
  • Lupták, Andrej
  • et al.
Abstract

Laboratory evolution of functional RNAs has applications in many areas of chemical and synthetic biology. In vitro selections critically depend on the presence of functional molecules, such as aptamers and ribozymes, in the starting sequence pools. For selection of novel functions the pools are typically transcribed from random-sequence DNA templates, yielding a highly diverse set of RNAs that contain a multitude of folds and biochemical activities. The phenotypic potential, the frequency of functional RNAs, is very low, requiring large complexity of starting pools, surpassing 1015 different sequences, to identify highly active isolates. Furthermore, the majority of random sequences is not structured and has a high propensity for aggregation; the in vitro selection process thus involves not just enrichment of functional RNAs, but also their purification from aggregation-prone "free-riders". We reasoned that purification of the nonaggregating, monomeric subpopulation of a random-sequence RNA pool will yield pools of folded, functional RNAs. We performed six rounds of selection for monomeric sequences and show that the enriched population is compactly folded. In vitro selections originating from various mixtures of the compact pool and a fully random pool showed that sequences from the compact pool always dominate the population once a biochemical activity is detectable. A head-to-head competition of the two pools starting from a low (5 × 1012) sequence diversity revealed that the phenotypic potential of the compact pool is about 1000-times higher than the fully random pool. A selection for folded and monomeric RNA pools thus greatly increases the frequency of functional RNAs from that seen in random-sequence pools, providing a facile experimental approach to isolation of highly active functional RNAs from low-diversity populations.

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