bioRxivBioengineeringPreprint
Periodic DNA encoding enables error-tolerant multi-class molecular detection by nanopore sequencing
Abstract
Biomarker analysis requires detecting analyte classes that span nucleic acids, proteins, small molecules, and metabolites, yet testing remains fragmented across target-specific assays and instruments. Here we report a molecular information-transduction strategy that converts target recognition across molecular classes into a common, error-tolerant DNA code readable by nanopore sequencing. Target recognition triggers a hybridization chain reaction that generates concatemers containing periodically repeated 10-nucleotide target-specific barcodes. A matched-filter decoder exploits this periodicity and the linear scaling of read length with match count to reject spurious matches by two to three orders of magnitude. Multi-class detection is demonstrated for a small molecule (ATP), two cardiovascular-associated microRNAs and thrombin in singleplex and multiplexed assays. By separating molecular recognition from sequence readout, this architecture provides a modular framework for converting heterogeneous analytes into a shared, redundancy-encoded signal for high-fidelity molecular sensing.
- assay: DNA methylation
- assay: whole-genome sequencing
- research focus: cell type annotation
- research focus: clustering
- approach: deep learning
- Citations
- 0
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