Evidence map›Paper›PMID 42607266›Full record

ArticleACS nano2026

High-Throughput On-Chip Screening Enables Rapid Adaptation of DNA Aptamers to SARS-CoV-2 Evolution.

Yujie He, Zhenglin Yang, Yu-An Kuo, Yuting Wu, Diego Fonseca-Albert, Kyle K Le, Jeffrey Guo, Yanxing Wang, Anh-Thu Nguyen, Yuan-I Chen and 9 more

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Article in ACS nano, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

19 authors.

Yujie HeDepartment of Biomedical Engineering, University of Texas at Austin, Austin, Texas78712, United States.ORCID 0000-0002-6984-3052
Zhenglin YangDepartment of Chemistry, University of Texas at Austin, Austin, Texas78712, United States.
Yu-An KuoDepartment of Biomedical Engineering, University of Texas at Austin, Austin, Texas78712, United States.
Yuting WuDepartment of Chemistry, University of Texas at Austin, Austin, Texas78712, United States.ORCID 0000-0003-3196-5916
Diego Fonseca-AlbertDepartment of Biomedical Engineering, University of Texas at Austin, Austin, Texas78712, United States.
Kyle K LeDepartment of Biomedical Engineering, University of Texas at Austin, Austin, Texas78712, United States.
Jeffrey GuoDepartment of Biomedical Engineering, University of Texas at Austin, Austin, Texas78712, United States.
Yanxing WangDepartment of Biomedical Engineering, University of Texas at Austin, Austin, Texas78712, United States.ORCID 0000-0001-7239-8482
Anh-Thu NguyenDepartment of Biomedical Engineering, University of Texas at Austin, Austin, Texas78712, United States.
Yuan-I ChenDepartment of Biomedical Engineering, University of Texas at Austin, Austin, Texas78712, United States.ORCID 0000-0002-9559-2779
Sohyun KimDepartment of Biomedical Engineering, University of Texas at Austin, Austin, Texas78712, United States.
Wei-Ru ChenDepartment of Biomedical Engineering, University of Texas at Austin, Austin, Texas78712, United States.ORCID 0000-0001-8162-2204
Saeed SeifiDepartment of Biomedical Engineering, University of Texas at Austin, Austin, Texas78712, United States.
Soonwoo HongDepartment of Biomedical Engineering, University of Texas at Austin, Austin, Texas78712, United States.ORCID 0000-0002-7618-9052
Trung Duc NguyenDepartment of Biomedical Engineering, University of Texas at Austin, Austin, Texas78712, United States.
Yinong ChenDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland21218, United States.
Pengyu RenDepartment of Biomedical Engineering, University of Texas at Austin, Austin, Texas78712, United States.ORCID 0000-0002-5613-1910
Yi LuDepartment of Chemistry, University of Texas at Austin, Austin, Texas78712, United States.ORCID 0000-0003-1221-6709
Hsin-Chih YehDepartment of Biomedical Engineering, University of Texas at Austin, Austin, Texas78712, United States.ORCID 0000-0001-6654-5626

Funding

DEVELOPMENT OF A NEXT-GENERATION NUCLEIC ACID FORCE FIELDR01GM106137 · NIGMS · WASHINGTON UNIVERSITY · PI JAY PONDER, Pengyu Ren · 2013 to 2026
$3.5M
Cancer Prevention and Research Institute of Texas RP210088National Institutes of Health (NIH) DA060543National Institutes of Health (NIH) GM141931National Institutes of Health (NIH) R01GM106137National Science Foundation (NSF) CBET2235455National Science Foundation (NSF) CBET2432379National Science Foundation (NSF) CHE2404334Welch Foundation F-0020Welch Foundation F-2120
6 · The paper itself

Abstract

Rapid pathogen evolution threatens public health by eroding the effectiveness of vaccines, therapeutics, and diagnostic tools. Although spike-protein-targeting monoclonal antibodies (mAbs) were developed within 10-12 months of the initial outbreak to serve as key theranostic agents, their redesign has struggled to keep pace with viral evolution, rendering many neutralizing antibodies ineffective. Here, we demonstrate a high-throughput aptamer engineering platform that combines a random-rational hybrid library diversification with repurposed MiSeq screening to rapidly reprogram aptamers against emerging SARS-CoV-2 spike variants. Interactions between 3 different spike proteins and 11,792 unique aptamer variant designs were profiled within days (a single run from pool amplification to screen analysis). Starting from a 40-nt aptamer originally selected against wild-type (WT) spike protein, our screen identified a Delta-binding mutant with a 4-fold affinity improvement and an Omicron-binding mutant that converted undetectable binding into nanomolar affinity. We also identified a WT-selective mutant with substantially reduced affinity for Delta as well as bases that contribute to spike recognition. Integrating high-throughput binding data with molecular dynamics simulations further helped to rationalize the sequence-dependent structural features underlying variant-specific aptamer-spike interactions. Finally, we developed fluorescent strand-displacement sensors based on both WT- and Omicron-selective mutants, enabling highly specific detection of spike protein variants with robust performance. Together, these findings demonstrate a rapid and sequence-resolved aptamer engineering platform for adapting aptamers to evolving pathogens.

Indexed as

Aptamers, NucleotideHigh-Throughput Screening AssaysSARS-CoV-2Spike Glycoprotein, CoronavirusCOVID-19HumansMutationAptamers, NucleotideSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2biomedical engineeringbiosensorsDNA aptamershigh-throughput screeningSARS-CoV-2viral evolution

Identifiers

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.