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Oesinghaus, L.

Publications and source records attributed to Oesinghaus, L..

3 recordsLinked to original sources

Toehold-Mediated Strand Displacement in Random Sequence Pools

Toehold-mediated strand displacement (TMSD) has been used extensively for molecular sensing and computing in DNA-based molecular circuits. As these circuits grow in complexity, sequence similarity between components can lead to cross-talk causing leak, altered kinetics, or even circuit failure. For small non-biological circuits, such unwanted interactions can be designed against. In environments containing a huge number of sequences, taking all possible interactions into account becomes infeasible. Therefore, a general understanding of the impact of sequence backgrounds on TMSD reactions is of great interest. Here, we investigate the impact of random DNA sequences on TMSD circuits. We begin by studying individual interfering strands and use the obtained data to build machine learning models that estimate kinetics. We then investigate the influence of pools of random strands and find that the kinetics are determined by only a small subpopulation of strongly interacting strands. Consequently, their behavior can be mimicked by a small collection of such strands. The equilibration of the circuit with the background sequences strongly influences this behavior, leading to up to one order of magnitude difference in reaction speed. Finally, we compare two established and a novel technique that speed up TMSD reactions in random sequence pools: a threeletter alphabet, protection of toeholds by intramolecular secondary structure, or by an additional blocking strand. While all of these techniques were useful, only the latter can be used without sequence constraints. We expect that our insights will be useful for the construction of TMSD circuits that are robust to molecular noise.

bioengineering↗

Algorithmic design of 3D wireframe RNA polyhedra

We address the problem of de novo design and synthesis of nucleic acid nanostructures, a challenge that has been considered in the area of DNA nanotechnology since the 1980s and more recently in the area of RNA nanotechnology. Towards this goal, we introduce a general algorithmic design process and software pipeline for rendering 3D wireframe polyhedral nanostructures in single-stranded RNA. To initiate the pipeline, the user creates a model of the desired polyhedron using standard 3D graphic design software. As its output, the pipeline produces an RNA nucleotide sequence whose corresponding RNA primary structure can be transcribed from a DNA template and folded in the laboratory. As case examples, we design and characterize experimentally three 3D RNA nanostructures: a tetrahedron, a bipyramid and a prism. The design software is openly available, and also provides an export of the targeted 3D structure into the oxRNA molecular dynamics simulator for easy simulation and visualization.

bioengineering↗

Controlling gene expression in mammalian cells using multiplexed conditional guide RNAs for Cas12a

Spatiotemporal control of the activity of Cas proteins is of considerable interest for both basic research and therapeutics. Only few mechanisms have been demonstrated for regulating the activity of guide RNAs (gRNAs) for Cas12a in mammalian cells, however, and combining and compactly integrating multiple control instances on single transcripts has not been possible so far. Here, we show that conditional processing of the 3 tail is a viable general approach towards switchable Pol II-transcribed Cas12a gRNAs that can activate gene expression in mammalian cells in an input-dependent manner. Processing of the 3 tail can be achieved using microRNA and short hairpin RNA as inputs, via a guanine-responsive ribozyme, and also using an RNA strand displacement mechanism. We further show that Cas12a along with several independently switchable gRNAs can be integrated on a single transcript using stabilizing RNA triplexes, providing a route towards compact Cas12a-based gene regulation constructs with multi-input switching capabilities.

synthetic biology↗