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Using the promoters of MerR family proteins as "rheostats" to engineer whole-cell heavy metal biosensors with adjustable sensitivity.


ABSTRACT:

Background

Whole cell biosensors provide a simple method for the detection of heavy metals. However, previous designs of them rely primarily on simulation of heavy metal resistance systems of bacteria.

Results

This study proposes a strategy for the rational design of metal detection circuits based on sensor proteins of the MerR family. Our results indicate the expression level of sensor protein can be used as a "rheostat" for tuning detection sensitivity with parabola curves to represent the relationships between the detection slopes and the sensor protein levels. This circuits design strategy (named as "Parabola Principle"), is used as a guide for the discovery of optimum metal detection circuits, and the design of biosensors with specific metal detection characteristics. For example, visible qualitative Hg (II) biosensors with a threshold of 0.05?mg/L are successfully constructed.

Conclusions

These results indicate the feasibility of developing a sensor that is much more tunable than what is presented.

Graphical abstract

SUBMITTER: Guo M 

PROVIDER: S-EPMC6702742 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Using the promoters of MerR family proteins as "rheostats" to engineer whole-cell heavy metal biosensors with adjustable sensitivity.

Guo Mingzhang M   Du Ruoxi R   Xie Zixin Z   He Xiaoyun X   Huang Kunlun K   Luo Yunbo Y   Xu Wentao W  

Journal of biological engineering 20190820


<h4>Background</h4>Whole cell biosensors provide a simple method for the detection of heavy metals. However, previous designs of them rely primarily on simulation of heavy metal resistance systems of bacteria.<h4>Results</h4>This study proposes a strategy for the rational design of metal detection circuits based on sensor proteins of the MerR family. Our results indicate the expression level of sensor protein can be used as a "rheostat" for tuning detection sensitivity with parabola curves to re  ...[more]

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