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Directed Evolution of Aptamer Discovery Technologies

Diana Wu, Chelsea K.L. Gordon, John H. Shin, Michael Eisenstein, H. Tom Soh
doi: https://doi.org/10.1101/2021.11.23.469732
Diana Wu
1Department of Radiology, Stanford University, Stanford, CA 94305, USA
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Chelsea K.L. Gordon
1Department of Radiology, Stanford University, Stanford, CA 94305, USA
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John H. Shin
2Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
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Michael Eisenstein
1Department of Radiology, Stanford University, Stanford, CA 94305, USA
3Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA
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H. Tom Soh
1Department of Radiology, Stanford University, Stanford, CA 94305, USA
2Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
3Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA
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  • For correspondence: tsoh@stanford.edu
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Abstract

Conspectus Although antibodies are a powerful tool for molecular biology and clinical diagnostics, there are many emerging applications for which nucleic acid-based aptamers can be advantageous. However, generating high-quality aptamers with sufficient affinity and specificity for biomedical applications is a challenging feat for most research laboratories. In this Account, we describe four techniques developed in our lab to accelerate the discovery of high quality aptamer reagents that can achieve robust binding even for challenging molecular targets. The first method is particle display, in which we convert solution-phase aptamers into aptamer particles that can be screened via fluorescence-activated cell sorting (FACS) to quantitatively isolate individual aptamer particles based on their affinity. This enables the efficient isolation of high-affinity aptamers in fewer selection rounds than conventional methods, thereby minimizing selection biases and reducing the emergence of artifacts in the final aptamer pool. We subsequently developed the multi-parametric particle display (MPPD) method, which employs two-color FACS to isolate aptamer particles based on both affinity and specificity, yielding aptamers that exhibit excellent target binding even in complex matrices like serum. The third method is a click chemistry-based particle display (click-PD) that enables the generation and high-throughput screening of “non-nattural” aptamers with a wide range of base modifications. We have shown that these base-modified aptamers can achieve robust affinity and specificity for targets that have proven challenging or inaccessible with natural nucleotide-based aptamer libraries. Lastly, we describe the non-natural aptamer array (N2A2) platform, in which a modified benchtop sequencing instrument is used to characterize base-modified aptamers in a massively parallel fashion, enabling the efficient identification of molecules with excellent affinity and specificity for their targets. This system first generates aptamer clusters on the flow-cell surface that incorporate alkyne-modified nucleobases, and then performs a click reaction to couple those nucleobases to an azide-modified chemical moiety. This yields a sequence-defined array of tens of millions of base-modified sequences, which can then be characterized in a high-throughput fashion. Collectively, we believe that these advancements are helping to make aptamer technology more accessible, efficient, and robust, thereby enabling the use of these affinity reagents for a wider range of molecular recognition and detection-based applications.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted November 24, 2021.
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Directed Evolution of Aptamer Discovery Technologies
Diana Wu, Chelsea K.L. Gordon, John H. Shin, Michael Eisenstein, H. Tom Soh
bioRxiv 2021.11.23.469732; doi: https://doi.org/10.1101/2021.11.23.469732
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Directed Evolution of Aptamer Discovery Technologies
Diana Wu, Chelsea K.L. Gordon, John H. Shin, Michael Eisenstein, H. Tom Soh
bioRxiv 2021.11.23.469732; doi: https://doi.org/10.1101/2021.11.23.469732

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