Team:BEAS China/Demonstrate

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Summary of Demonstration

In this part, we showed the key results of NEZHA to demonstrate its potential for real world application.

For Heavy Metal Sensor, our Amplifier 3 (RinA_p80α-TEV-tevS-AAV Tag) design could maintain sensors output amplitude and sensitivity and also exhibit a lower basal background. The detection limit is lower than 10-7M.

For Heavy Metal Adsorption, NEZHA can be used for heavy metal absorption in a modular and flexible way. A NEZHA cell can adsorb 6000-10000 Hg2+ in two hours.

For Biocontainment, we successfully designed a ncAA-dependent Toxin-antitoxin system. When the ncAA system is OFF, there is no sign of any bacterial growth under the microscope. When the ncAA system is ON, bacterial’s growth is back to normal.

Sensor

Basic Biosensor for Heavy Metal Detection

We first tested the signal amplifying methodology on the basic sensor J101-merR-PmerR-gfp. This sensor (Fig. 1B) has a constitutive promoter (J23101) that drives the expression of an arsenic receptor MerR, which would de-repress its cognate promoter MerR on murcury binding and trigger the expression of a reporter gene, GFP. However, the output of this sensor is very low so it would not meet the requirement for real applications.

We utilized mathematic model to see which key parameter we should consider to optimize to improve the performance of the circuits. See our model. We found that intra-cellular receptor density, as to say kMmerR, is a critical factor regulating the sensory ability.

We then select two more constitutive promoters of varying strengths from iGEM promoter library (Fig. 1A), and chose two weak promoters (that is, J115 and J109) to replace J101 in the mercury sensor. The sensors were then compared under various HgNO3 induction conditions (Fig. 1B). The results showed that the weaker the promoter (that is, the lower the MerR receptor concentration), the more sensitive and higher the dynamic range of the sensor, which is the same as the math model indicated.

Figure 1: A Different constitutively J23 family promoter measured strength (Data source: iGEM) B Tuning mercury receptor MerR’s intracellular density by varying the strength of J23 prmoter

We fitted the sensors’ dose–response curves to a Hill function-based biochemical model to describe their input-output relationships. (Fig 2a and Table 1)

  • The Hill constant EC50 is the inducer concentration that provokes half-maximal activation of a sensor; EC50 is negatively correlated with sensitivity.

  • KTop is the sensor’s maximum output expression level; KTop is positively correlated with output amplitude.

Figure 2: The equation used to fit the sensors’ dose–response curves to a Hill function based biochemical model to describe their input-GFPput relationships
Table 1: Best fits for the characterized response of the various sensors circuits in this study

Here, EC50 showed a 2.7-fold decrease and KTop showed a 3.5-fold increase from high to low MerR levels (Fig. 3a & 3b ), confirming that the mercury sensor’s sensitivity and output amplitude were both increased while the MerR intracellular concentration was decreased.

Figure 3: The maximum output (KTop) and EC50 of the sensor’s dose response against the relevant intracellular MerR concentrations

Amplifier to improve sensor performance

To further improve the output expression, we proceeded to introduce three amplifier design between the sensor module and the reporter. The relative design are described in Design.

  • Amplifier1: Rinp80α

  • Amplifier2: TEV-C1434

  • Amplifier3: Rinp80α-TEV-tevS-AAV Tag

As is shown in Fig. 4, we can see：

  • Amplifier1: Compared to Basic Sensor, the fluorescence output signal is much higher than Basic Sensor. However, The fluorescent signal leakage of this design at low mercury induction levels is very high.

  • Amplifier2: Compared to Amplifier1, the fluorescent signal leakage of this design at low mercury induction levels is very low. However, the fluorescence output signal is much smaller than Amplifier1.

  • Amplifier3: this design fully protected the GFP reporter from degradation at high mercury induction levels, while achieving significantly lower basal expression through continuous degradation of the reporter GFP at low mercury induction levels.

    • Figure 4: Characterization of an mercury sensor with three different amplifiers

    We fitted the sensors’ dose–response curves to a Hill function-based biochemical model to describe their input-output relationships (Table 2) . Here, both in Amplifier 1 & 2, EC50 showed a significant increase, while in Amplifier 3, EC50 deceased to the same level as Basic sensor (J23109). KTop showed a higher value in all three designs, in which Amplifier 1 & 3 are highest.

    Table 2: Best fits for the characterized response of the various sensors circuits in this study
    Figure 5: The maximum output (KTop) and EC50 of the sensor’s dose response with different amplifiers

    The characterization of Amplifier 3 shows that this design fully protected the GFP reporter from degradation at high mercury induction levels, while achieving significantly lower basal expression through continuous degradation of the reporter GFP at low mercury induction levels.

    In summary, Amplifier 3 is sufficient to reduce the sensor’s basal background while also being able to maintain both the sensor’s output amplitude and sensitivity, leading to expanded output dynamic range. What’s more, this strategy can also be applied to other heavy metal sensor circuits, such as As 3+ (arsR)，Pb 2+ (pbrR), etc.

    Adsorption

    Deletion of csgA gene

    Since there is already a copy of CsgA gene on C321 wild type’s genome, we need to knock out this wildtype gene CsgA. Using CRISPR, gene CsgA successfully knocked out the gene on C321’s genome (C321ΔCsgA strain) (Fig 6). The strain C321ΔCsgA would then be used as chassis cell in afterward experiments. See why we use C321 strain in our project.

    Figure 6: A gRNA squence used in this project for csgA gene deletion B The gel imaging showed that csgA gene was deleted from the C321 genome

    SpyCatcher-GFP

    We designed an experiment to measure the capture ability of CsgA–SpyTag、INP–SpyTag and CsgA–INP-SpyTag. We used sfGFP–SpyCatcher protein expressed and lysed from E.coli BL21 as the indicator.

    We first expressed SpyCacther-GFP protein in B Cell, and collected the SpyCacther-GFP protein in the supernatant by cell disruption and high-speed centrifugation. Then we added a certain amount of SpyCacther-GFP protein to the bacterial culture medium of CsgA–SpyTag, INP–SpyTag and CsgA–INP-SpyTag, reacting for two hours.

    Then, we centrifuged the reaction system and measure the fluorescence of the supernatant. The decrease of florescence indicated the amount of sfGFP – SpyCatcher protein the A cell surface captured.

    As shown in the results in Fig 5a, we saw that the expression band of SpyCacther-GFP was clearly visible on the PAGE gel. In Fig 5b, we can see that after the reaction, the fluorescence values of different groups were decreased, and CsgA–INP-SpyTag was the most significant one.

    Figure 7: A PAGE Gel showed that SpyCatcher-GFP was succefully expressed and collected B Florescence measurement of csgA, INP, csgA+INP group

    SpyCatcher-MBP

    Next, we used the same strategy to carry out the heavy metal adsorption test of NEZHA. We first expressed SpyCacther-mecury binding protein(MBP) in B Cell, and collected the SpyCacther-MBP protein in the supernatant. Then we added a certain amount of SpyCacther-MBP protein to 1mL over-night bacterial culture medium of CsgA–INP-SpyTag with 10-5μM of Hg2+ concentration, reacting for two hours. Then, we centrifuged the reaction system and the supernatant was collected for testing using ICP-MS. The decrease of Hg2+ concentration level indicated the amount of Hg2+ captured in NEZHA.

    As shown in the results in Fig. 6b, NEZHA can absorb more than 50% of 10-5 μM Hg (II) in 120 minutes. That is to say, a NEZHA cell can absorb about 6000-10000 Hg2+. (Assume 1mL of bacteria contains 109 bacteria).

    Figure 8: A PAGE Gel showed that SpyCatcher-mercury binding protein was succefully expressed and collected B ICP-MS results of the MEZHA mercury adsorption

    The advantage of this design is that the A cells themselves do not need to be changed. We can just change the SpyCacther-MBP expressed in the B cells so that the adsorption of various heavy metal ions can be achieved.

    Further optimization are also needed to increase the efficiency of the metal binding protein, such as directed evolution of MBP or optimizing the reaction process of experiment.

    Biocontainment

    Phd-Doc test

    We first tested the effects of Phd-Doc. We used different inducible promoters to control the expression of Phd and Doc proteins, respectively. As can be seen from Fig 9B, bacterial growth was completely inhibited after induction of Doc protein expression. When both Phd and Doc proteins are expressed, the growth of bacteria is no longer affected by Doc toxic proteins.

    Figure 9: A The process for bacteria growth imaging B The imaging of bacteria growth of different groups after 24 hours

    Cl2Y aaRS Performance

    In the non-canonical amino acid system, the aminoacyl tRNA synthetase is under the control of the arabinose promoter, while the tRNA recognizing the TAG codon is regulated by a constitutively expressed promoter. As can be seen from Fig, when arabinose or ncAA was not added to the system, the expression level of GFP was almost zero. When arabinose and ncAA were added to the system, GFP was fully synthesized thus fluorescence signal can be detected.

    Figure 10: Characterization of Cl2Y RS system

    ncAA-dependent Phd

    To better quantify the effect of insertion the TAG codon into Phd antitoxin, we first fused a GFP fluorescent protein using the GS Linker to the C-terminus of the PhD protein. By doing so, we can simply characterize the performance of the TAG codon insertion by measuring fluorescence.

    First we tried to confirm that insertion of how many TAG codons could completely inhibit gene expression. We inserted 1-3 TAG codons just after the start codon, and then measured the fluorescence value of Phd-GS-sfGFP. The results showed the expression of the gene was well terminated in three designs, and the insertion of two TAG codons was the best.

    Figure 11: Characterization of Phd-TAG-GS-sfGFP system

    Next we attempted to introduce the ncAA system into the Phd-GS-sfGFP expression system with two TAG codons. When the ncAA system is expressed, we can see that the system that originally had no fluorescence produced a strong fluorescent signal. This shows that we have successfully established an Anticoxin (Phd) system that relies on ncAA. When ncAA is present in the system, Phd can be successfully expressed, and when ncAA is not present in the system, the expression of Phd is completely terminated.

    Figure 12: Characterization of Phd(2TAG)-Doc system

    ncAA-dependent Phd-Doc Bioncontainment System

    Next, we inserted two TAG stop codons after the Phd gene start codon and transferred the corresponding Phd and Doc plasmid to C321 to construct the ncAA-dependent Phd-Doc Biocontainment System.

    We then tested the system and the results are shown below: When the ncAA system is OFF, there is no sign of any bacterial growth under the microscope. When the ncAA system is ON, bacterial’s growth is back to normal. This shows that the TA system we built that is dependent on ncAA system is successful. This system will ensure that NEZHA will get rid of security problems in practical applications.

    Figure 13: A & B OD600 value and cell imaging for ncAA-dependent Phd-Doc Bioncontainment System after 24 hour's growth

    Future Plans

    For Heavy Metal Sensor, more amplifiers should be integrated into heavy mental sensor to further increase the output performance and decrease the detection limit.

    For Heavy Metal Adsorption, We should improve the heavy metal absorption efficiency of NEZHA through protein computing design or directed evolution.

    For Biocontainment, it should be integrated into the Sensor and Adsorption module. Also, in order to be more stable in cells, ncAA system should be integrated into the bacterial genome. What's more, we can introduce more ncAA-dependent toxin-antitoxin systems into our biocontainment design to further decrease the escape frequency.