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
Electronic supplementary material
The online version of this article (10.1186/s13036-019-0202-3) contains supplementary material, which is available to authorized users.
In order to promote efficient use of waste concrete in Chongqing, the building area estimation method is employed to estimate the waste concrete output from 2012 to 2018, and the gray model is used to predict the waste concrete output from 2019 to 2023. By Matlab programming, the waste concrete output in Chongqing will reach 3181.14t in 2023, which is 1.44 times that in 2012. The results show that the gray model can accurately forecast the output of waste concrete in Chongqing in the short and medium term.
Three-dimensional PDMS microstructures with 100 nm regular dot arrays were the most effective surface for epithelial cell attachment. These findings can aid in the manufacture of superior materials for use in implants to better integrate into recipient tissue.
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