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Nucleic acid-guided protein-empowered aquatic contaminants sensing

Fang Zhang* (Co-first Author), Shiau Wei Liew (Co-first Author), Sin Yu Lam (Co-first Author), Chun Kit Kwok*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

The rapid evolution of nucleic acid-guided proteins (e.g., CRISPR/Cas12a, Argonaute) has positioned them as transformative tools for aquatic contaminant sensing. Their programmability, compatibility with diverse signal transducers, and field-deployable designs enable unprecedented on-site environmental monitoring. This review outlines the fundamental mechanisms of nucleic acid (NA)-guided proteins, critically analyzes implementation strategies (including field-deployable platforms), and systematically highlights their applications in the sensing of aquatic pollutants. We further discuss current challenges and future research directions to further advance multiplexing, sensitivity enhancement, artificial intelligence (AI)-assisted engineering, and integrated on-site detection areas. By providing comprehensive insights into this emerging field, we hope that this review will serve as an important resource for researchers developing next-generation NA-guided proteins-based environmental surveillance tools to address ‘One Health’ challenges at aquatic interfaces. © 2025 Elsevier Inc.
Original languageEnglish
Pages (from-to)853-868
JournalTrends in Chemistry
Volume7
Issue number12
Online published30 Oct 2025
DOIs
Publication statusPublished - Dec 2025

Funding

This work was supported by National Natural Science Foundation of China (NSFC) Projects ( 32471343 , 32222089 ); Research Grants Council (RGC) of the Hong Kong Special Administrative Region ( RFS2425-1S02 , CityU 11100123 , CityU 11100222 , and CityU 11100421 ); Croucher Foundation Project ( 9509003 ); State Key Laboratory of Marine Pollution Seed Collaborative Research Fund ( SCRF0070 ); City University of Hong Kong projects ( 9680376 , 7030001 and 9678302 ) to C.K.K.; the Hong Kong PhD Fellowship Scheme to S.W.L. and The Hong Kong Polytechnic University Start-up Fund for RAPs under the Strategic Hiring Scheme ( A0058760 ) to F.Z.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Research Keywords

  • aquatic contaminants
  • argonaute
  • CRISPR-Cas
  • environmental monitoring
  • nucleic acids
  • sensing

RGC Funding Information

  • RGC-funded

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