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Content archived on 2024-05-29

An orthogonal episome: An artificial genetic system based on a novel type of nucleic acids

Objective

Information storage and propagation in biological systems is based on just two types of nucleic acids, DNA and RNA. Our aim is to design and build artificial genetic systems based on alternative nucleic acid architectures and "invade" biological information processing with an orthologous autonomously replicating episome (which we name the "orthosome"). We propose to build the orthosome from sugar modified oligonucleotides HNA (hexitol nucleic acids) and CeNA (cyclohexene nucleic acids) because of their conformational analogy, helix forming properties and resistance to enzymatic degradation. We will first establish an orthosome capable of in vitro replication and interconversion into DNA and/or RNA.

The tools of protein design and repertoire selection will be used to create an alternative replication and transcription machinery capable of replicating and transcribing the orthosome. We will then establish a "bridgehead" in a living cell, whereby we establish orthogonality as well as communication links with the cellular replication and translation machinery through transliteration of essential sequences encoded in the orthosome. We will use a selection screen for the transmission of a genetic message encoded in HNA or CeNA, to identify bacterials strains capable of using HNA or CeNA as a template. An in vitro orthosome would allow the bulk production of nucleic acid-like polymers which can be used as nucleic acid based therapeutics such as aptamers, ribozymes or siRNA or have benefits in the emerging fields of bionanotechnology and nucleic acid computing. A living cell harboring the orthosome will constitute the first organism with an expanded genetic system based on a 3rd type of nucleic acid.

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Keywords

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Programme(s)

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Topic(s)

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Call for proposal

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FP6-2004-NEST-PATH
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Funding Scheme

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STREP - Specific Targeted Research Project

Coordinator

KATHOLIEKE UNIVERSITEIT LEUVEN
EU contribution
No data
Total cost

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Participants (2)

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