Extending the dynamic range of biomarker quantification through molecular equalization

Sharon S. Newman, Brandon D. Wilson, Daniel Mamerow, Benjamin C. Wollant, Hnin Nyein, Yael Rosenberg-Hasson, Holden T. Maecker, Michael Eisenstein and H. Tom Soh ()
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Sharon S. Newman: Stanford University
Brandon D. Wilson: Stanford University
Daniel Mamerow: Stanford University
Benjamin C. Wollant: Stanford University
Hnin Nyein: Stanford University
Yael Rosenberg-Hasson: Stanford University
Holden T. Maecker: Stanford University
Michael Eisenstein: Stanford University
H. Tom Soh: Stanford University

Nature Communications, 2023, vol. 14, issue 1, 1-10

Abstract: Abstract Precision medicine requires highly scalable methods of multiplexed biomarker quantification that can accurately describe patient physiology. Unfortunately, contemporary molecular detection methods are generally limited to a dynamic range of sensitivity spanning just 3–4 orders of magnitude, whereas the actual physiological dynamic range of the human plasma proteome spans more than 10 orders of magnitude. Current methods rely on sample splitting and differential dilution to compensate for this mismatch, but such measures greatly limit the reproducibility and scalability that can be achieved—in particular, the effects of non-linear dilution can greatly confound the analysis of multiplexed assays. We describe here a two-pronged strategy for equalizing the signal generated by each analyte in a multiplexed panel, thereby enabling simultaneous quantification of targets spanning a wide range of concentrations. We apply our ‘EVROS’ strategy to a proximity ligation assay and demonstrate simultaneous quantification of four analytes present at concentrations spanning from low femtomolar to mid-nanomolar levels. In this initial demonstration, we achieve a dynamic range spanning seven orders of magnitude in a single 5 µl sample of undiluted human serum, highlighting the opportunity to achieve sensitive, accurate detection of diverse analytes in a highly multiplexed fashion.

Date: 2023
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DOI: 10.1038/s41467-023-39772-z

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