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Preparation of Multifunctional Silk-Based Microcapsules Loaded with DNA Plasmids Encoding RNA Aptamers and Riboswitches
Published on: October 8, 2021
A microbial sensor for organophosphate hydrolysis exploiting an engineered specificity switch in a transcription
Ramesh K Jha1, Theresa L Kern2, Youngchang Kim3
1Bioscience Division, PO Box 1663, Los Alamos National Laboratory, Los Alamos NM 87545, USA cems@lanl.gov.
Researchers engineered a novel whole-cell biosensor using a modified transcription factor (TF) to detect p-nitrophenol (pNP). This biosensor demonstrates high sensitivity and selectivity for detecting specific chemicals, enabling new applications in environmental monitoring.
Area of Science:
- Synthetic Biology
- Biotechnology
- Molecular Engineering
Background:
- Whole-cell biosensors require diverse transcription factors (TFs) for detecting various molecules.
- Existing TFs often lack specificity for target anthropogenic compounds.
Purpose of the Study:
- To engineer a novel specificity into an Acinetobacter TF, PobR, for sensing p-nitrophenol (pNP).
- To develop a smart microbial cell-based biosensor for detecting pNP and its derivatives.
Main Methods:
- Utilized homology modeling and ligand docking to identify TF binding pockets.
- Employed conservative mutations to engineer TF specificity.
- Constructed a whole-cell biosensor with a fluorescent reporter system.
- Developed a coupled assay involving phosphotriesterase (PTE) for insecticide hydrolysis detection.
Main Results:
- Engineered PobR variants with novel specificity for pNP, with two mutants switching specificity from 4-hydroxybenzoate (4HB).
- Developed a smart microbial cell (pNPmut1) responsive to pNP produced from paraoxon hydrolysis.
- Demonstrated fluorescence correlation with PTE catalytic efficiency.
- Achieved high selectivity (4HB vs. pNP) and sensitivity (∼2 μM pNP detection).
Conclusions:
- Successfully engineered a transcription factor for specific pNP detection.
- Created a functional whole-cell biosensor with potential applications in chemical sensing and environmental monitoring.
- Validated computational modeling approaches for TF engineering.
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