Introduction

Our research topic is: Application of new biofilm in industrial wastewater treatment. After determining the market position of the product based on HP researches, we modified the biofilm of E. coli to adsorb heavy metal ions in sewage. Meanwhile, Modeling provided guides for both the experimental process and the input of the for actual wastewater treatment to satisfy the effluent discharge standard. The hardware device was designed based on the combination of both experimental results and modeling data to remove heavy metal in actual industrial sewage until it meets the national standard. Then the discharged sewage would be managed with subsequent treatment in the followup industrial processes.

Proof of heavy metal ions adsorption under experiments

Cu²⁺ Cd²⁺ adsorption

Aiming at removing Cu²⁺ Cd²⁺ in industrial sewage, we genetically engineered E.coli MG1655, which is a kind of commonly used model organism in molecular biology study, to enable the modified bacteria to adsorb Cu²⁺ Cd²⁺ by the metallothionein(MT) linked with CsgA protein on the bacterial biofilm. We have chosen two kinds of metallothionein(MT): ShMT3 and SmtA for their ability of binding with multiple heavy metals, including Cu²⁺ Cd²⁺ . Also, we added SUMO tag before CsgA-MT to enhance the expression of MT.

To test the ability of the modified bacteria harboring MT constructs(SUMO-csgA-shMT3, csgA-shMT3, SUMO-csgA-SmtA, csgA-SmtA) to adsorb Cu²⁺ Cd²⁺ , we measured the amount of Cu²⁺ Cd²⁺ that bound with MT on bacterial biofilm using ICP-MS. After a series of preliminary experiments, we chose to verify the adsorbing ability under 1800μM CuSO$_4$ and 300μM CdCl$_2$ respectively.

The modified bacteria and the control group harboring pET28a-SUMO empty plasmid and incubated them along with a certain concentration of heavy metal ion and 1 mM IPTG for 8h before the measurement.

The results demonstrate that there is a significant difference of the ability to adsorb metals between control group and modified bacteria harboring MT constructs(SUMO-csgA-shMT3, csgA-shMT3, SUMO-csgA-SmtA, csgA-SmtA). Also, MT constructs with SUMO tag(SUMO-csgA-shMT3, SUMO-csgA-SmtA) performed better in adsorbing Cu²⁺ Cd²⁺ . In conclusion, the genetically engineered E.coli MG1655 harboring SUMO-csgA-MT has the ability to adsorb Cu²⁺ Cd²⁺ by the MT on the bacterial biofilm.

Ag⁺ adsorption

To test MBP construct ability to adsorb silver ions, we measured supernatant silver ions concentration of E.coli harboring pGEX-4T-1,pGEX-4T-1-csgA-MBP3 in the presence of 3-12 μM AgNO$_3$ for 36h.

Silver ions concentration we added are higher than the national standards for silver ion emissions(0.93μM). Adsorption is significant difference between these two strains in the presence of AgNO$_3$ addition (3 μM to 9 μM). Additionally, the csgA-MBP3 group had less silver ions in the supernatant and higher adsorption rate than the control group.

Compared with MG1655 harboring pGEX-4T-1, bacteria inserted CsgA-MBP3 fragments has high adsorption rate (60%-70%) to adsorb silver ions in sewage effectively.

According to experiment adsorption data，we built mathematical model to reduce the concentration of silver ions after adsorption below the national standard.

According to the results of the concentration of absorbed metal ions under a range of the concentration of metal ions input, values of significant parameters called binding affinity can be determined by fitting.

Proof of heavy metal ions adsorption in real environments

Since the situations in real environments are more complicated than that under the condition of experiment, more factors should be considered such as the building of device and simulation of corresponding changes in concentration of metal ions.

According to the equation: $\pmb{\frac{\partial [metal]}{\partial t} = -v*\frac{\partial [metal]}{\partial x} - \frac{n(\frac{\partial [CsgA·MBP/MT]}{\partial x})(\frac{\partial [metal]}{\partial x})^{n}}{(K_D + (\frac{\partial [metal]}{\partial x})^{n})*t}}$(Details in the modeling page), we can predict the values of suitable number of MBBR carriers, number of modified cells and speed of water.

Figure 5: The distribution of the concentration of meta ions in the device with input concentration of metal ions ranging in 0~12 $\mu M$.

The concentration in the end of the distance(x-axis) symbolizes the output concentration of the metal ions.

In this example for silver ions, the input concentration of it is random from 0 to 12 $\mu M$ for each time step with v(speed of flow) = 100 m/h and initial concentration of CsgA·MBP is 1.2M. The output concentration is less than 0.9 $\mu M$(national standard) which proves the absorption function of our water-purified device. The values of the parameters can be changed according to specific needs. (Details can be seen in the modeling page)

In conclusion, in a certain period, the water-purified device can restrict the output concentration of metal ions under that of the national standard which achieve our goal of absorption.

Proof of hardware model application

This model is a prototype of our design that integrates experimental and modeling results. The water purification improvement process can be intuitively delivered through hardware design.

We planned to utilize our product to replace the ion exchange or chemical precipitation method. Our product will not introduce other harmful chemicals into the water. As a result, we could use this biological method for refined adsorption.

We put bioreactor into sewage，measured heavy metal ions concentration and various parameters in water. Modeling analyze the strain and carriers delivery method. According to modeling, **we put the modified E. coli into bioreactor. E. coli adsorbs heavy metals, and the sewage is discharged under the national emission standard.

Figure 6: Our specially designed hardware.
To find out more about the hardware, click Hardware.

To find out more about the closed cycle, click Our Proposed Implementation.