Ligand‐Responsive Artificial Protein–Protein Communication for Field‐Deployable Cell‐Free Biosensing

Natural protein-protein communications, such as those between transcription factors (TFs) and RNA polymerases/ribosomes, underpin cell-free biosensing systems operating on the transcription/translation (TXTL) paradigm. However, their deployment in field analysis is hampered by the delayed response (hour-level) and the complex composition of in vitro TXTL systems. For this purpose, we present a de novo-designed ligand-responsive artificial protein-protein communication (LIRAC) by redefining the connection between TFs and non-interacting CRISPR/Cas enzymes. By rationally designing a chimeric DNA adaptor and precisely regulating its binding affinities to both proteins, LIRAC immediately transduces target-induced TF allostery into rapid CRISPR/Cas enzyme activation within a homogeneous system. Consequently, LIRAC obviates the need for RNA/protein biosynthesis inherent to conventional TXTL-based cell-free systems, substantially reducing reaction complexity and time (from hours to 10 minutes) with improved sensitivity and tunable dynamic range. Moreover, LIRAC exhibits excellent versatility and programmability for rapidly and sensitively detecting diverse contaminants, including antibiotics, heavy metal ions, and preservatives. It also enables the creation of a multi-protein communication-based tristate logic for the intelligent detection of multiple contaminants. Integrated with portable devices, LIRAC has been proven effective in the field analysis of environmental samples and personal care products, showcasing its potential for environmental and health monitoring.

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Publication Details

Journal
Angewandte Chemie International Edition
Published
2024-11-18
DOI
https://doi.org/10.1002/anie.202416671
Citations
16
Primary Topic
Gene Regulatory Network Analysis
Type
article
Field-Weighted Citation Impact
3.74
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article

Ligand‐Responsive Artificial Protein–Protein Communication for Field‐Deployable Cell‐Free Biosensing

Aori Qileng, Chunyang Lei, Chunlai Chen, Siqian Liu et al.
16 citations
Angewandte Chemie International Edition
Gene Regulatory Network Analysis
3.74
article

Ligand‐Responsive Artificial Protein–Protein Communication for Field‐Deployable Cell‐Free Biosensing

Aori Qileng, Chunyang Lei, Chunlai Chen, Siqian Liu, Zhou Nie, Yingju Liu, Shuqi Zhou, Dingyi Wang, Ke Wang
article en
16 citations

Abstract

Natural protein-protein communications, such as those between transcription factors (TFs) and RNA polymerases/ribosomes, underpin cell-free biosensing systems operating on the transcription/translation (TXTL) paradigm. However, their deployment in field analysis is hampered by the delayed response (hour-level) and the complex composition of in vitro TXTL systems. For this purpose, we present a de novo-designed ligand-responsive artificial protein-protein communication (LIRAC) by redefining the connection between TFs and non-interacting CRISPR/Cas enzymes. By rationally designing a chimeric DNA adaptor and precisely regulating its binding affinities to both proteins, LIRAC immediately transduces target-induced TF allostery into rapid CRISPR/Cas enzyme activation within a homogeneous system. Consequently, LIRAC obviates the need for RNA/protein biosynthesis inherent to conventional TXTL-based cell-free systems, substantially reducing reaction complexity and time (from hours to 10 minutes) with improved sensitivity and tunable dynamic range. Moreover, LIRAC exhibits excellent versatility and programmability for rapidly and sensitively detecting diverse contaminants, including antibiotics, heavy metal ions, and preservatives. It also enables the creation of a multi-protein communication-based tristate logic for the intelligent detection of multiple contaminants. Integrated with portable devices, LIRAC has been proven effective in the field analysis of environmental samples and personal care products, showcasing its potential for environmental and health monitoring.

Angewandte Chemie International EditionVol. 64(4)
South China Agricultural University (CN), Hunan University (CN), Chinese Academy of Sciences (CN), Research Center for Eco-Environmental Sciences (CN), Center for Life Sciences (CN), Tsinghua University (CN)
Life in Land
Openalex Percentile: Top 6%
Gene Regulatory Network Analysis
3.74
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