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A Universal Sequencing System for Unknown Oligomers

David Doran, Emma Clarke, Graham Keenan, Emma Carrick, Cole Mathis, Leroy Cronin

semanticscholar(2020)

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Abstract
No synthetic chemical system can produce complex oligomers with fidelities comparable to biological systems. To bridge this gap, chemists must be able to characterise synthetic oligomers. Currently there are no tools for identifying synthetic oligomers with sequence resolution. Herein, we present a system that allows us to do omics-level sequencing for synthetic oligomers and use this to explore unconstrained complex mixtures. The system, Oligomer-Soup-Sequencing (OLIGOSS), can sequence individual oligomers in heterogeneous and polydisperse mixtures from tandem mass spectrometry (MS/MS) data. Unlike existing software, OLIGOSS can sequence oligomers with different backbone chemistries. Using an input file format, OLIG, that formalizes the set of abstract properties, any MS/MS fragmentation pathway can be defined. This has been demonstrated on four model systems of linear oligomers. OLIGOSS can screen large sequence spaces, enabling reliable sequencing of synthetic oligomeric mixtures, with false discovery rates (FDRs) of 0-1.1%, providing sequence resolution comparable to bioinformatic tools.
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