Browsing by Author "Wu, Lucia R."

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Continuously tunable nucleic acid hybridization probes
    (Springer Nature, 2015) Wu, Lucia R.; Wang, J. Sherry; Fang, John Z.; Reiser, Emily; Pinto, Alessandro; Pekker, Irena; Boykin, Richard; Ngouenet, Celine; Webster, Philippa J.; Beechem, Joseph; Zhang, David Yu
    In silico–designed nucleic acid probes and primers often do not achieve favorable specificity and sensitivity tradeoffs on the first try, and iterative empirical sequence-based optimization is needed, particularly in multiplexed assays. We present a novel, on-the-fly method of tuning probe affinity and selectivity by adjusting the stoichiometry of auxiliary species, which allows for independent and decoupled adjustment of the hybridization yield for different probes in multiplexed assays. Using this method, we achieved near-continuous tuning of probe effective free energy. To demonstrate our approach, we enforced uniform capture efficiency of 31 DNA molecules (GC content, 0–100%), maximized the signal difference for 11 pairs of single-nucleotide variants and performed tunable hybrid capture of mRNA from total RNA. Using the Nanostring nCounter platform, we applied stoichiometric tuning to simultaneously adjust yields for a 24-plex assay, and we show multiplexed quantitation of RNA sequences and variants from formalin-fixed, paraffin-embedded samples.
  • Thumbnail Image
    Item
    Direct capture and sequencing reveal ultra-short single-stranded DNA in biofluids
    (Cell Press, 2022) Cheng, Lauren Y.; Dai, Peng; Wu, Lucia R.; Patel, Abhijit A.; Zhang, David Yu
    resulting fluorescence images and compared with tissue histopathology maps. The EGFﾖAlexa 647 signal correlated well with EGFR expression as indicated by immunohistochemistry. A classification algorithm for presence of neoplasia based on the signal from both contrast agents resulted in an area under the curve of 0.83. Regions
  • Thumbnail Image
    Item
    Predicting DNA hybridization kinetics from sequence
    (Springer Nature, 2018) Zhang, Jinny X.; Fang, John Z.; Duan, Wei; Wu, Lucia R.; Zhang, Angela W.; Dalchau, Neil; Yordanov, Boyan; Petersen, Rasmus; Phillips, Andrew; Zhang, David Yu
    Hybridization is a key molecular process in biology and biotechnology, but so far there is no predictive model for accurately determining hybridization rate constants based on sequence information. Here, we report a weighted neighbour voting (WNV) prediction algorithm, in which the hybridization rate constant of an unknown sequence is predicted based on similarity reactions with known rate constants. To construct this algorithm we first performed 210 fluorescence kinetics experiments to observe the hybridization kinetics of 100 different DNA target and probe pairs (36 nt sub-sequences of the CYCS and VEGF genes) at temperatures ranging from 28 to 55 °C. Automated feature selection and weighting optimization resulted in a final six-feature WNV model, which can predict hybridization rate constants of new sequences to within a factor of 3 with ∼91% accuracy, based on leave-one-out cross-validation. Accurate prediction of hybridization kinetics allows the design of efficient probe sequences for genomics research.