Engineered cells for selective detection and remediation of Hg2+ based on transcription factor MerR regulated cell surface displayed systems

Wang, Dan; Zheng, Yanan; Xu, Lina; Fan, Xiaosu; Wei, Na; Jin, Nanhao; Huang, Shan; Wu, Zihua

doi:10.1016/j.bej.2019.107289

Cited by 16 publications

(16 citation statements)

References 51 publications

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“…For signal generation, the lux and mcherry gene were selected for the luminescence signal and red color fluorescence, respectively. For enhancement of the fluorescent signal, the OmpA protein (residues 1–159) was used for the surface display of the mCherry protein [ 7 ]. In the case of luminescent signal detection, the copA promoter- lux and zntA promoter- lux gene modules were used to detect copper and mercury, respectively and the copA promoter- ompA - mcherry , zntA promoter- ompA - mcherry , and merR - mer promoter- ompA - mcherry systems were also constructed for fluorescent visible detection of copper, cadmium, and mercury gene module, respectively.…”

Section: Resultsmentioning

confidence: 99%

“…For the mercury-sensing plasmid (pMerp-mCherry), the gene of merR - mer promoter- ompA (1–159)- mcherry was synthesized and cloned into the pUC57 vector. The mer promoter is a bidirectional promoter derived from the Tn 501 transposon [ 7 ]. The repressor merR was placed before the mer promoter.…”

Section: Methodsmentioning

confidence: 99%

“…For analyzing the linearity, relative light units (RLU) for luminescence and relative fluorescence units (RFU) for fluorescence were evaluated using a Cytation 5 (BioTek Instruments Inc, Winooski, VT, USA) imaging reader. RFU was measured using the emission and excitation wavelengths of 610 and 587 nm, respectively [ 7 ].…”

Section: Methodsmentioning

confidence: 99%

“…Conventional methods of heavy metal measurement are inductively coupled with plasma-mass spectrometry (ICP-MS) and atomic absorption spectrometry (AAS). However, these methods require laborious sample pre-treatment (e.g., decomposition of nitric acid at a high temperature), expensive instruments, and skilled technicians [ 6 , 7 ]. Thus, these approaches are not practical for the detection of heavy metals in food products.…”

Section: Introductionmentioning

confidence: 99%

“…To overcome these obstacles, we tested three heavy metals—copper, cadmium, and mercury, respectively—in the detection range that was selected after considering the Korea Food and Drug Administration’s Food code and a recent study [ 4 ]. In addition, we constructed visible WCBs using mCherry [ 7 ], which will help in their commercialization.…”

Section: Introductionmentioning

confidence: 99%

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Development of Colorimetric Whole-Cell Biosensor for Detection of Heavy Metals in Environment for Public Health

Kim

Choi

Shin

et al. 2021

IJERPH

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Heavy metals cause various fetal diseases in humans. Heavy metals from factory wastewater can contaminate drinking water, fish, and crops. Inductively coupled plasma-mass spectrometry (ICP-MS) and atomic absorption spectrometry (AAS) are commonly used to analyze heavy metal contents; however, these methods require pre-treatment processes and are expensive and complex. To overcome these limitations, three metal-sensing materials using a whole-cell biosensor in Escherichia coli (E. coli) were developed. Strains were engineered to harbor three kinds of plasmids containing the copA, zntA, and mer promoters for sensing copper, cadmium, and mercury, respectively. The luciferase (lux) gene was inserted as a reporter into the plasmid, which was later replaced with a fused protein sequence containing OmpA (1–159) and mCherry for optical detection. The constructed strains could detect mercury, cadmium, and copper at 0.1–0.75 ppm, 0.2–0.75 ppm, and 2–7.5 ppm, respectively, with linearity values of 0.99030, 0.99676, and 0.95933, respectively. The immobilization linearity value was 0.99765. Notably, these three heavy metals could be detected by visual analysis of the strains. Overall, these findings establish this novel sensor as a potential approach for heavy metal detection in biological samples and foods.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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