Team:USTC/Results
That is so amazing! We finally made NDM this year! The results page will deliver the fresh results from us. Our results include these sections:
Permeability Improvement: In this section, we will demonstrate our synthetic bioloical base constrcuction, characterization of permeability improvement. This is the fundation of CACCI construction, as well as NDM.
Chemotaxis Modification: This section introduces results of chemotaxis engineering.
Adhesion Assay: This section explicitly explain adhesion methods, adhesion dynamics and adhesion protocols recommended for all users, which is an important part of our results.
Film Determination: This section introduced how we finally determinated our film, from plastic film to our final candidate. See how difficult and interesting it is!
Calibration: This is our final step demonstrating the feasibility of NDM. See how perfect our project is!
Extraction of Permeability Improvement Fragements
We successfully get gene fragements that are used for improving bacterial permeability, which including,
- SCVE, a viroporin originally from SARS virus, is synthesized by Sangon Co. ctd.
- OprF, a bigger porin compared with OmpF in E. coli, is extracted from P.aeruginosa， PAO1 genome by PCR.
T7 is a strong promoter which we got form Parts Registry. T7 will be used to trigger the expression of both OprF and SCVE.
Figure 3: T7 extraction from parts Cas9 is got from 2015 Part Distribution.
- gRNA-AcrB and gRNA-EmrE, these two fragments are for silencing bacterial transmembrane protein AcrB and EmrE to strongly block drug efflux system. These two parts are synthesized by Sangon Biotech Company.
Construction of Permeability Improving Plasmid
- Construction of plasimid with T7-SCVE (BBa_K1593667) . We finally ligated the T7 with SCVE and got T7-SCVE (BBa_K1593667).
- Construction of plasimid containing T7-OprF (BBa_K1593210). This is the result of T7 with OprF.
Growth Characterization
We firstly characterized the growth rate of genetically modified CACCI along with wild type BL21 using optical density at 600 nm, which is called OD 600, in order to demonstrate that the overexpression of porin(OprF with T7,BBa_K1593209) or viroporin(SCVE with T7, (BBa_K1593667) won't severely affect the growth of bacteria, at least it won't significantly inhibit bacteria growth and become a kill switch.
All bacteria are cultured previously in LB medium about 12 h. And then the measurement of bacteria growth through time began at 8 A.M. the other day.
As the images above illustrated, we found E. coli BL21 wild type has the best growth characteristics with a maximal OD600=3.427. Whereas E. coli BL21 with OprF (BBa_K1593210) has a relatively low optical density as its OD600 after 12 h is 2.808 compared to the wildtype. In the same way, characterization of E. coli BL21 with SCVE, http://parts.igem.org/Part:BBa_K1593667 showed a slightly smaller OD600, as its finally turned to 2.835. E. coli BL21 with T7-OprF (BBa_K1593210) and E. coli BL21 with T7-SCVE, (BBa_K1593667) are showing 19% decreased maximal cell density and 18.5% decreased maximal cell density respectively in comparison with wild type.
Consequently, the result implies that the genetical modification on bacterial permeability, at least the overexpression of OprF and SCVE with a strong promoter T7, won't significantly influence the bacterial growth. Thus, genetically modified bacteria can be used in the following experiments.
Later on, we will characterize the basic permeability capability of E. coli BL21 with T7-OprF (BBa_K1593210) and E. coli BL21 with T7-SCVE, (BBa_K1593667).
ONPG Assay
ONPG, that is the abbreviation of ortho-Nitrophenyl-β-galactoside. ONPG is a colorimetric and spectrophotometric substrate, previously used for detecting β-galactosidase activity. ONPG is actually colorless at normal situation, however if it triggers the degradation reaction catalyzed by β-galactosidase, we will get galactose and ortho-nitrophenol. Surprisingly, the compound ortho-nitrophenol has a yellow color, which means we are able to detect the chemical reaction through OD detection. Besides, owing to the existence of β-galactosidase in bacteria, a more intense optical density we detected, that means there are more ONPG uptaked by bacteria. Therefore, using ONPG we are able to distinguish the permeability capability of different bacteria.
Here's our result.
Note: The wavelength for detecting the bacterial concentration and absortion of ONPG are respectively 600nm and 406nm.
First, we detected the bacterial solutions to control the initial concentrations.
The OD values for E.coli BL21, E.coli BL21 with T7-OprF (BBa_K1593210) , E.coli BL21 with T7-SCVE(BBa_K1593667) are respectively 2.856,1.806 and 1.889. Based on these, we know that the concentrations of these three bacteria are close.
Then we add ONPG to the bacterial solutions and detect the OD.
From this figure, we can see a rising trend in all bacterial solutions. The OD values for E.coli BL21 with T7-OprF(BBa_K1593210) and E.coli BL21 with T7-SCVE(BBa_K1593667) are respectively 0.2520 and 0.2588,both are higher than E.coli BL21,the wild type. We can infer that the absorbtion of modified bacteria is higher than the wild type.
There is a more visual figure for comparing the absorbtions. We made a zero calibration using the OD value of wild type as the zero level.
In general, the OD values of both two modified bacteria are rising. For E.coli BL21 with T7-OprF(BBa_K1593210), the rising is relatively smooth. For E.coli BL21 with T7-SCVE(BBa_K1593667),the value goes down first, then goes up .And the E.coli BL21 with T7-SCVE(BBa_K1593667) has a higher absorbtion than E.coli BL21 with T7-OprF(BBa_K1593210).
NPN Assay
N-Phenyl-1-naphthylamine(NPN),C16H13N, CAS:90-30-2, FW: 219.29, is a nonpolar probe, whose fluorescence signal is relatively strong in a phospholipid environment, but weak in aqueous surroundings. Consequently, using this feature, we are able to characterize bacteria permeability by measuring the fluorescence intensity of the bacteria solution. When NPN molecules are absorbed by bacteria, we will observe a significantly rising fluorescence intensity. The more fluorescence intensity we got, the more permeable the bacteria are. Here are what we got from NPN uptake assay and the conclusion on genetically engineered bacteria permeability improvement.
Here's our results, the first picture illustrate the total fluorescence intensity measurement by BMG Labtech CLARIOstar®.
Note: The fluorescence intensity signal at excitation wavelength range is 305nm to 335nm and emission wavelength range is 370nm to 410nm, which is recommended by previous research.
The total fluorescence intensity of E. coli BL21 wild type is 126451. On the other hand, the fluorescence intensity in E. coli BL21 with T7-OprF (BBa_K1593210) and E. coli BL21 with T7-SCVE, (BBa_K1593667) are respectively 207322 and 151820, which are significantly larger than the wildtype assay.
Though we have already got the exact data on NPN uptake, we still need to revise its effectiveness because of the different bacteria concentration of E. coli BL21 wild type, E. coli BL21 with T7-OprF (BBa_K1593210) and E. coli BL21 with T7-SCVE, (BBa_K1593667). Here is the exact bacteria concentration data, based on OD600nm,
| Strain | OD600nm |
|---|---|
| E. coli BL21 wild type | 3.663 |
| E. coli BL21 with T7-OprF (BBa_K1593210) | 2.431 |
| E. coli BL21 with T7-SCVE, (BBa_K1593667) | 2.441 |
After correcting these data, we are able to get bacteria absorption uptake capability in average, which is a more accurate value to characterize bacterial permeability property.
The fluorescence intensity in average of E. coli BL21 wild type is 34521.16. On the contrary, the fluorescence intensity revised by bacterial concentration in E. coli BL21 with T7-OprF (BBa_K1593210) and E. coli BL21 with T7-SCVE, (BBa_K1593667) are respectively 85282.60 and 62195.8, which are relatively 2.5 folds and approximately 2 folds to E. coli wild type, that is a significantly improvement compared to wild type.
Consequently, through NPN uptake assay, we are able to conclude that the small molecule uptake capability of bacteria improved after our genetical modification. Thus E. coli BL21 with T7-OprF (BBa_K1593210) and E. coli BL21 with T7-SCVE, (BBa_K1593667) are both able to use as the candidate bacteria strains for NDM measurement.
Bibliography
T. Mattila-Sandholm et al. Fluorometric assessment of Gram-negative bacterial permeabilization. Journal of Applied Microbiology 2000, 88, 213–219
Scott Banta et al. Genetic Manipulation of Outer Membrane Permeability: Generating Porous Heterogeneous Catalyst Analogs in Escherichia coli dx.doi.org/10.1021/sb400202s ACS Synth. Biol. 2014, 3, 848−854
Genetic Fragments Extraction
- micF and SoxS, these two antibiotic substance responding promoters were extracted from E. coli Top 10(K-12 strain) by conducting polymerase chain reaction on its genome.
- cheZ, this is the chemotaxis modified fragment.
- BBa_R0010, this is promoter of lac, which triggers the expression of cheZ.
](https://static.igem.org/mediawiki/2015/3/34/Ustc-oprf_ep_r0010.jpeg)
Construction of plasimid with lac-cheZ BBa_K1593997
This is our final construction of lac-cheZ BBa_K1593997
Growth characteristics
We detected OD600(nm) to identify the effect of cheZ (BBa_K1593997) expressed on E. coli BL21 with time induced by IPTG or not.
 induced by IPTG or not](https://static.igem.org/mediawiki/2015/d/d6/Ustc-growth.png)
As the images above illustrated, we found E. coli BL21 wild type has the best growth characteristics with a maximal OD600=2.6. Whereas E. coli BL21 with cheZ (BBa_K1593997) induced by ITPG has a relatively low optical density as its OD600 after 9 h is 2.3 compared to the wildtype. In the same way, characterization of E. coli BL21 with cheZ (BBa_K1593997) not induced by IPTG showed a slightly smaller OD600, as its finally turned to 2.1. The exogenous protein expression affects the growth of bacteria, which was indicated by slight slower grow-up in E. coli containing cheZ plasmid. In total, cheZ doesn't have obvious negative impact on bacteria grown.
SDS-PAGE
After induced by IPTG in 1mM about 4 h, cheZ was found in SDS-PAGE gel, compared to the wild type (Top10) and bacteria without IPTG induction. Through this result, we concluded that cheZ has been successfully expressed with the IPTG induction.
See protocol in Protocols
Characterization of Optimal Conditions on Polylysine(PLL) Coated Assay
To see the details on the mechanism of polylysine adhesion, please refer to Project-CACCI.
To get the final PLL-coated protocol, check Protocols for further information.
Our original characterization of optimal conditions on polylysine(PLL)-coated assay requires several factors to get, including:
- Best bacterial developmental interval along with recommended dilution conditions.
- Best PLL-Coated Concentration and Pre-treatment Time.
- Best PLL-Coated Time, given full consideration to the completion of bacterial adhesion time.
- Best Measurement Interval, which illustrates the possible time for bacterial response on antibiotics pressure.
- Possible Determination Interval, which refers to antibiotics response interval.
Here we present all the optimistic conditions for users to get the effective results on antibiotics using our CACCI and SPRING.
Best Bacterial Developmental Interval Along with Recommended Dilution Conditions
According to experience on E. coli development based on OD detector. We concluded that bacteria exploding during Logarithmic Period(OD:535nm about 0.4~0.5) are at the most energetic moments with proper bacterial density. Consequently, we highly recommend user to culture bacteria at Logarithmic Period and then dilute bacterial solution about twenty times to fifty times.
Best PLL-Coated Concentration and Pre-treatment Time.
Best PLL-Coated Conditions, which include PLL-Pretreatment time, PLL-Coated concentration and PLL-Coated time are measured for best adhesive condictions for bacterial treatment.
As for PLL-Pretreatment time, we adopt traditional pretreatment time, incubating about 12~16 h, for recommendation, which is originally used for neurons coated on neural science research. And when it comes to PLL-coated concentration, experience on neurons adhesion is also precious. According to previous research, PLL concentration in the interval of 20 ug/mL to 100 ug/mL is quite effective for bacterial adhesion.
Adhesion Assay with PLL treatment
Here we deliver the PLL treatment results comparing with no PLL treatment assay. During pre-experiment adhesion assay, PAO1, a strain of Pseudomonas aeruginosa, is used for adhesion effects.
The picture below showed the amount of bacteria(PAO1) under microscope without PLL treatment, which is abbreviated as PLL(-). To observe capability of bacterial adhesion, we wash observed place with PBS:
After elution, a significant decline in the number of bacteria is recorded. As a matter of fact, there is no bacteria in observed field after PBS washing.
To get the algorithm of bacterial counting, please refer to Modeling: Adhesion Dynamics.
As for treatment with PLL in 20 ug/mL, which is abbreviated as PLL(+,20), the impressive adhesion effect is observed. To ensure the exact effect, bacteria observing field is washed twice by PBS.
The number of bacteria doesn't decline, and on the contrary, we see slight increase of bacteria number. The possible reason is constant bacterial settlement during adhesion assay. After twice PBS wash, the number of bacteria is relatively stable as well. Consequently, we concluded PLL has significant adhesive ability on bacteria.
Best PLL-Coated Time
Then, we tried to figure out the cohesive effect of polylysine through time to get the best PLL-coated time. We gathered data just after PLL treatment(0s), after 1min and after 5min. And we also recorded bacteria number in the following 20 s. Here we provide the analysis of bacterial number variation after PLL treatment.We respectively use PAO1, a kind of Pseudomonas aeruginosa and HCB1, a kind of E. coli to handle the assay. PAO1 contains self-adhesive ability and HCB1 has strong mobile ability. Using these genetically natural bacteria, we would conclude with the effect of polylysine treatment.
As for PAO1, Without polylysine coated, bacteria have strong swimming ability. Because PAO1 is a kind of self-adhesive bacteria for experiment, thus we could see adhesive bacteria increasing during assay.
With 20 ug/mL polylysine treatement, bacterial adhesive effect due to strong electrostatic adhesion becomes stronger, and we, as well are able to observe the number of adherent bacteria gradually rising until reaching equilibrium.
After mathematical simulation we found that the adhesion rate of PAO1 by polylysine after treatment of PLL is increased, while for E. coli, the adhesion quantity rise, not fall.
As for HCB1, a kind of E. coli and the number of bacteria inside
observed field is stable and relatively declined because of its lack of capability of
adhesion.
After treated with 20ug/mL polylysine, adhesive bacteria number obviously
increased:
Modeling on adhesion process strictly demonstrated the adhesion assay fits Langmuir absorption isoform.
Simulation result:
\(\sigma =K\sigma _{0}\times (1-e^{-\frac{K_{\alpha}CV_{z}}{K\sigma _{0}}(t-t_{0})})\)
Constants
value and details:
To know more about our modeling, please check Modeling: Adhesion Dynamics
This significant reverse of bacterial adhesion tendency stronly proved that polylysine has effective adhesive ability for SPRING.
After we confirmed the feasibility of PLL treatment for bacterial adhesion, then the treating time should be taken into consideration because only in the case of stable adhesion is effective for SPRING to gather effective and stable data.
As the plot illustrates, bacteria number is growing at the beginning of PLL treatment because of opening strong electrostatic adsorption derived from PLL. And after 1min, the number of bacteria become stable, and there is nearly no difference on bacteria number comparing after 1 min treatment to after 5 min treatment.
Consequently, we recommended that PLL treatment after 5 min would be a promising set for SPRING to output stable data.
Best Measurement Interval
According to chemotaxis, bacteria responsing to surrounding pressure or beneficits will be presented as change of bacteria movement. Here we analyzed bacterial movement data treating with different antibiotics concentration, specificly, chloromycetin concentration. And we gathered bacterial movement data just after antibiotics treatment(0s), after 1 min treatment and after 5 min treatment, and we again recorded all pictures in the following 18 s to get the dynamic data. Then, we concluded from the percentage of bacterial movement as an important data to intercept the effect of bacterial response on antibiotics.
The measurement assay is illustrated as following:
PLL(-)
| Antibiotics Concentration(ug/mL) | Incubation Time(s) |
|---|---|
| 0 | 0 |
| 0 | 60 |
| 0 | 120 |
| 0 | 180 |
| 0 | 240 |
| 0 | 300 |
| 1 | 0 |
| 1 | 60 |
| 1 | 300 |
PLL(+,20)
| Antibiotics Concentration(ug/mL) | Incubation Time(s) |
|---|---|
| 0 | 0 |
| 0 | 60 |
| 0 | 120 |
| 0 | 180 |
| 0 | 240 |
| 0 | 300 |
| 0.1 | 0 |
| 0.1 | 60 |
| 0.1 | 300 |
| 0.5 | 0 |
| 0.5 | 60 |
| 0.5 | 300 |
| 1 | 0 |
| 1 | 60 |
| 1 | 300 |
When bacteria are treated with PLL, the movement of bacteria is been limited for strong
adhesion, after 5 min treatment, the proportion of movement decreased through
time.
However, when bacteria are not treated with PLL, incubated in 1ug/mL chloromycetin solution, we got the movement percentage of bacteria as following:
The amount of moving bacteria is relatively increasing after 5 min antibiotics treatment. Bacause of no PLL treatment, we could see the relative increase of bacteria movement percentage.
As for bacteria treated with 20 ug/mL PLL, different pattern is observed:
This is the bacterial movement percentage variation with time, treated with 0.1 ug/mL chloromycetin solution. Antibiotics pressure is not that strong, consequently, the movement of bacteria is not ignited significantly.
When it comes to 0.5 ug/mL chloromycetin solution, the proportion of the moving bacteria
is increased. And as a matter of fact, the increase is quite corresponding through time,
reflecting bacteria impressive response on antibiotics substance.
What if the concentration of chloromycetin solution up to 1 ug/mL?
A
quite linear increase of the proportion of the moving bacteria with time is observed.
Consequently, according to our experiment, genetically naturally bacteria could respond to chloromycetin solution from 0.1 ug/mL to more than 1ug/mL, which is quite promising after genetic modification.
Let's do some crasy science this time! We'll show you how we test and select the most important part in our project, the special artificial original film!
Modeling guide us choose the candidates
In our modeling, we start with single bacteria force, analyse the interaction between bacteria and film, and propose the request of Young modulus (<1GPa) of film eventually.
And there are various film candidates come into the front.
Processing Film
The film must be kind of soft and one of the surface should have enough reflectance while
another surface should have the ability to adhere to bacteria.
In fact, we don't hear any
of this type of film. So we need to produce the film by our own.
Film I
Low Pressure Polyethylene
Low pressure polyethylene is soft enough, and is too soft.
We use aerosol paint cover one of the surface. That can make the other surface of the film will become a reflect surface. And we use 400ul 20ug/ml PLL coating the same surface at the temperature of 4℃ to make this surface has the ability to adhere to bacteria.
But we fail with film I in the end that we can't get interference fringes. Because the surface of low pressure polyethylene is not as smooth as we want, that will cause a diffuse reflection. Thus we can not get interference inescapably.
So we need the film becoem more smooth and more elastic, and then come out film II-Rubbers
Film II
Rubbers-Condom
If you want the material smooth enough and thick enough and elastic enough, that is, of cause, condom!
When we plan to use paint cover, the truth give us a hard hit. Because the film shrink too much when we spray paint.
And we try silver mirror reaction as replacement. But still fail Because the ammonia erosion is too severe.
Finally we find the final film candidate that we missed-Glass
Film III
Cover slip
The Young modulus of Glass is about 50GPa. But according to our adhesion assay result and modeling, there will several numbers of fringes changes in the experiment.
So we spraying it, coating it, testing it, and we made it!
The glass have a great
potential to reflect, so we can get interference very easy.
With modeling guidance, we
can know the relation between fringes changes and antibiotics concentration.
\(A_{0}+\frac{B_{0}}{A}=\frac{1}{\Delta N}\)
Then we want to develop a calibration with three point.
The fitting result indicate that our modeling and normalization operation was exactly correct and effective. OUR CRAZY MIND HIT OUR MODEL, AND OUR MODEL EXACYLY HIT OUR RESULT! WE LOVE SCIENCE!
That means the Processed Glass worth the name of special artificial original film!
You can detect various of kinds of material in solution, as long as you follow our standard to make the engineered bacteria. See our future NDM improvement plan at Future NDM
There is one thing to be sure is that whatever bacteria you used, you need to build calibration ruler to measure the concentration quantificationally. According to our modeling in calibration we need to confirm three constants 'A0', 'B0', 'n'.
\(A_{0}+\frac{B_{0}}{A}=\frac{1}{\Delta N}\)
That means we need to test at least three point to confirm the formula.
Establishement of the Calibration Ruler
To build a calibration ruler between chloramphenicol concentration and
interference fringes pattern.
In this case we use our E. coli BL21 with T7-OprF (BBa_K1593210), a type of bacteria in the best perfomance during genetically modification.(See our modification at Results-Permeability Improvement). According to our experiment results, we found the E. coli BL21 with T7-OprF (BBa_K1593210) was more sensitive to chloramphenicol.
And according to adhesion pre-experiment we chose the concentration range with 0.5ug/ml~5ug/ml in the experiment.
The changes of fringe number and test concentration shown below(take three pictures in a row with the time interval 20s),
| Time(s) | 5.0ug/ml(Fringe number) | 1.0ug/ml(Fringe number) | 0.5ug/ml(Fringe number) |
|---|---|---|---|
| 0 | 42/43 | 51/49/52 | 44/43 |
| 20 | - | 50/51/50 | - |
| 40 | - | 50/46 | - |
| 60 | - | 48/48/50 | 45 |
| 80 | - | 48/49/49 | - |
| 100 | - | 51/53/49 | 45 |
| 120 | 42/43 | - | - |
| 140 | - | 51/48/52 | - |
| 160 | - | - | 41 |
| 180 | - | 48/52/54 | - |
| 200 | 48 | 55/47/49 | 43/43 |
| 220 | 43/47 | 51/52 | 45 |
| 240 | 48/46 | 53/51 | 44 |
| starting average | 42.5 | 50.5 | 43.5 |
| ending average | 46.4 | 51.75 | 44.2 |
| ΔN | 3.9 | 1.25 | 0.7 |
Then we can fit this data with calibration formula, assume n=3(through trying different value of n get the best value of n) then get the simplified formula:
\(A_{0}+\frac{B_{0}}{A}=\frac{1}{\Delta N}\)
Then the fitting result illstruates as,
And we can get the value of unknown constants:
| constant | value |
|---|---|
| A0 | 0.1339 |
| B0 | 0.6513 |
What an amazing result! The fitting result indicated that our modeling and normalization operation was exactly correct and effective. OUR CRAZY MIND HIT OUR MODEL, AND OUR MODEL EXACYLY HIT OUR RESULT! WE LOVE SCIENCE!
Reverification of Calibration
There may some arguement on our accuracy on calibration. So we need to conduct another experiment to reverficate our calibration ruler.
In order to test whether the calibration is correct and to confirm the coefficients, we choose two concentration as check point.
And use SPRING to measure its concentration. The real concentration and experiment results shown in table:
| time(s) | 1.8ug/ml(Fringe number) | 3.2ug/ml(Fringe number) |
|---|---|---|
| 0 | 78/80 | 77/76/77 |
| 20 | 77/77 | 79/77 |
| 40 | 78 | 75/72 |
| 60 | 79 | 74 |
| 80 | 81 | 75/75 |
| 100 | 75 | 72/73 |
| 120 | 80 | 74/74 |
| 140 | 83/82 | 71/75 |
| 160 | 81/79 | 72/76 |
| 180 | 82/82 | 75/74 |
| 200 | 82/81 | 75 |
| 220 | 80/82 | 74/74/75 |
| 240 | 81/80 | 74/75/74 |
| starting average | 79 | 77.2 |
| ending average | 81 | 74.3 |
| ΔN | 2.0 | 2.9 |
| experiment concentration | 1.80ug/ml | 3.09ug/ml |
The result showed that the experiment concentration is EXTREMELY CLOSE to the real concentration, which means OUR NDM IS ABLE TO TELL ANTIBIOTIC CONCENTRATION IN VERY ACCURATE WAY.
By the way, DO NOT FORGET, operating our NDM only cost you 100 SECONDS.
Yes, such fast and accurate hardware detecting antibiotics, that is our NDM, ONLY OUR NDM.
Note: To get the program of our calibration analysis, please visit Software. To know more information on how we analyzed our results, please visit Modeling: Calibration. To see our final measurement report with theoretical analysis, please visit Measurement.