CRISPR-enabled sensors for rapid monitoring of environmental contaminants

Date published

2025-03-01

Free to read from

2025-03-12

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier

Department

Type

Article

ISSN

0165-9936

Format

Citation

Wang Y, Pan Y, Han W, et al., (2025) CRISPR-enabled sensors for rapid monitoring of environmental contaminants. TrAC Trends in Analytical Chemistry, Volume 184, March 2025, Article number 118128

Abstract

There is increasing attention on the impacts of contaminants on environmental and human health. To better understand the potential threat to ecosystems and human health, biosensing has played an important role in monitoring contaminants and biomarkers. In the past decade, the integration of CRISPR-Cas systems with technologies like microfluidic devices and isothermal amplification methods has paved the way for developing advanced sensors for environmental surveillance. Here we discuss the recent progress of various CRISPR-Cas systems to develop new biosensing devices, ranging from the fundamental mechanisms to their practical applications. We present a comprehensive and critical overview on the current state-of-the-art of CRISPR-Cas-based sensing platforms, including for both nucleic acid and non-nucleic acid contaminants, as well as portable engineered systems for on-site detection. We also provide the prospects of CRISPR-Cas systems for next-generation environmental surveillance, together with emerging technologies such as data science and artificial intelligence.

Description

Software Description

Software Language

Github

Keywords

CRISPR-Cas, Portable sensors, Water contaminants, Environmental monitoring, 3401 Analytical Chemistry, 34 Chemical Sciences, Biotechnology, Bioengineering, 3 Good Health and Well Being

DOI

Rights

Attribution 4.0 International

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Relationships

Resources

Funder/s

Royal Academy of Engineering, Natural Environment Research Council, Biotechnology and Biological Sciences Research Council, National Natural Science Foundation of China, Leverhulme Trust
The work is supported by UK Royal Academy of Engineering (FF\1920\1\36), UKRI BBSRC EBIC Engineering Biological Innovation Centre (BB/Y008332/1) and (BB/X012840/1), and UKRI BBSRC EBNet, National Key R&D Program of China (2023YFF1204500), "Pioneer" and "Leading Goose" R&D Program of Zhejiang (2024C03011). ZY thanks Leverhulme Trust Research Leadership Awards (RL-2022-041) and UKRI NERC Fellowship grant (NE/R013349/2).