Team:OUC-China/Measurement

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What should be mentioned is that the data obtained by this method is only used for the optimization of the method, not for the quantitative measurement of the data in other parts of the project.

Introduction

Although the plate reader has been widely used in various laboratories at present, and OD600 and fluorescence measurement have become simple experimental operations, in the developing countries, it is difficult to meet the standard that every biological laboratory can be equipped with a plate reader. As far as our team is concerned, this summer we went to three laboratories to borrow a plate reader. It not only takes time and energy but also makes measured fluorescence data units be not uniform, which requires subsequent normalization processing. Therefore, we start from two aspects, hoping to solve the problem of lack of plate reader. At the same time, a method of normalized fluorescence which is out of range of the plate reader was used to process the data.

Fluorescence Measured By Image Analysis

We tried to find a simple method that can replace the plate reader to measure fluorescence. While searching for information, we learned that GFP has not only a secondary absorption peak (blue light) with a peak of 485nm but also a maximum absorption spectrum with a peak of 395nm (ultraviolet), which means that we can excite GFP with UV-light. Coincidentally, our verification that the constructed logic gate works is represented by 0/1. Therefore, we can simply observe the cell fluorescence under the UV-light lamp to qualitatively judge the success of the experiment.

We chose the logic gate OR as the representative to verify the reliability of our qualitative measurement method. After 10h of conventional shaking flask culture, we added 400mL bacteria suspension to the EP tube after re-suspension by PBS according to the Protocol. We use Gel Imaging System’s UV-light to excite fluorescence, and figure 1 shows the result.

Figure 1. The brightness of the resuspended bacterial suspension in the EP tube and the 0/1 qualitative characterization of the brightness

Under UV light, 5 EP tubes were placed from left to right. The samples contained were negative control sample 1, sample 2 (neither aTc nor HSL was added), sample 3 (only aTc was added), sample 4 (only HSL was added), and sample 5 (both aTc and HSL were added). Different fluorescent positions in EP tubes were selected and the system qualitatively detected 0/1.

Through visual observation and simple qualitative identification by software, the result shows that our qualitative analysis method is feasible. But it is less applicable. In most cases, quantitative fluorescence values are expected. Therefore, we consider whether we can use image processing software to analyze luminance to quantitatively characterize the fluorescence value. While analyzing the agar-gel electrophoretic images, we could use the software SensiAnsys to accurately analyze the concentration of the DNA. Therefore, we tried to analyze the fluorescence intensity of the sample with SensiAnsys, and the result of figure 2A shows that the truth table from the software is the same as what we get during our wet-lab experiments. We also confirm that the measurement of the optical density is under the similar OD of each sample (figure 2B, C). The software can also show the optical density scan of the wave map to improve our analysis (figure 3).

Figure 2. Quantitative analysis results of optical density.

(A) When the concentration of bacterial suspension was relatively consistent, the value of the negative control group was at a lower level while the strain with higher expression of fluorescence showed a higher value. Error bar: SD (n=3), n.c.=negative control. (B) After a dilution of the negative control group and the measurement of OD, it shows that the OD of the sample is relatively consistent through the One-way ANOVA analysis (P>0.05).(C) The working curve of the bacteria shows that when it grows to 10h, it could maintain a stable OD level. Error bar: SD (n=9).

Figure 3. Optical density scan results.

After the sample detection positions in the EP tube were selected, it was found that the peaks of samples 3, 4 and 5 were higher than those of samples 1 and 2 through automatic optical density scanning, which conforms to the 0/1 representation of OR logic gate.

It is showed that our method can relatively characterize the fluorescent without a plate reader. In addition, we further consider that there are laboratories not equipped with either a plate reader or a gel imaging system. The handheld UV analyzer is a small UV lamp that delivers 365nm of UV. It can not only be turned on and off at any time, but also easy to get access to with a very low cost. In the case of UV light, experimenters can take pictures with a phone or camera and use Photoshop or other image processing software to analyze the light and shade.

Normalization Of Fluorescence Which Is Out Of Range Of The Plate Reader

GFP, as a widely used reporter protein in iGEM, the most common quantitative detection method of GFP is to use the plate reader. Fluorescence is still typically reported only in arbitrary or normalized units, however, rather than in units defined using an independent calibrant, which is problematic for scientific reproducibility and even more so when it comes to effective engineering. Also, after the data are obtained, correct normalization of plate reader data is required to remove autofluorescence from the measurements of the sample of interest. Incorrect normalization can decrease the dynamic range of the measured fluorescent output, particularly in the case of GFP. This year, we first employed the method of "Time OD normalization". The ratio of fluorescence to OD of cells was taken first, and then the ratio of the non-fluorescent cell (n. c.) was subtracted from the ratio of fluorescent cells.

There is no perfect apparatus or measurement methods. Unfortunately, the fluorescence value exceeded the range of fluorescence intensity that be allowed when we measured fluorescence with the plate reader. By consulting teachers and investigating the experiments of some iGEM teams, we found that this phenomenon is common. However, to our confusion, we cannot conclude a general and accurate as well as reasonable normalization method. In addition, due to the impact of the epidemic, some countries or regions were unable to obtain the standardized fluorescent kits provided by iGEM, which made the normalization of standards more difficult. The relationship between the sample’s concentration and fluorescence value is nonlinear. In general, a working curve should be made first. Gradient dilution is carried out on samples with known concentration to draw the relationship between the sample’s concentration and fluorescence value within a certain range, which is the same as what iGEM's standardization Protocol presents.

In the absence of a standardized fluorescence kit, OUC-China this year described a method of integrating normalized fluorescence and dilution.

Estimation And Assay Of Exceeded Fluorescence

Figure 4. Our original measurement data, including the fluorescence beyond the range and the fluorescence after a fourfold dilution.

We used E8 (red in Figure 4) before and after dilution as the 100% control groups in two data table, the ratio relationship expressed as decimal was obtained by dividing the diluted fluorescence value by the value of E8. The same processing method is employed in the data without dilution (Figure 5).

Figure 5. The ratio with E8 is the 100% control group (black), and the ratio of unknown fluorescence is calculated by linear fitting to 100% of the control group (red).

Take the ratio obtained before dilution as the X-axis and the ratio after dilution as the Y-axis for linear fitting. The regression coefficient is calculated and shown in Figure 6. The slope of the fitted line was 1.0571, close to 1, and the correlation coefficient was 0.9594, showing a good correlation, which confirmed the feasibility of this method. We calculated the ratio between the unknown fluorescence and the 100% control group based on the obtained line (red in Figure 5).

Figure 6. Ratio linear fitting results before and after dilution

The OVERFLW fluorescence value is estimated according to the credible proportional relation obtained. (red in Figure 7)

Figure 7. The calculated fluorescence value at OVERFLW

Normalization Assay

We want to use our estimated fluorescence values for our normalized data characterization. To test the feasibility of this method, we determined the normalization method we used by comparing the correlation between the final normalized values before dilution and after dilution. We mainly use two formulas to calculate the final normalized value.

⦁ (Fexptl/Absexptl) − (Fn.c./Absn.c.)

Figure 8. Results after normalized calculation (left: before dilution, right: after dilution)

Figure 8 shows the results after normalization before and after dilution. The value obtained before dilution was taken as the X-axis and the value after dilution as the Y-axis for linear fitting, and the regression coefficient was calculated. The results showed that the correlation coefficient was 0.9609 with a good correlation (Figure 9).

Figure 9. Normalization linear fitting results before and after dilution

⦁ (Fexptl-Fn.c.)/(Absexptl-Absn.c.)

Figure 10. Results after normalized calculation (left: before dilution, right: after dilution)

Figure 10 shows the results after normalization before and after dilution. The value obtained before dilution was taken as the X-axis and the value after dilution as the Y-axis for linear fitting, and the regression coefficient was calculated. The results showed that the correlation coefficient was 0.9048 (Figure 11).

Figure 11. Normalization linear fitting results before and after dilution

By comparing the correlation coefficients of the two methods, we found that the normalization using (Fexptl/Absexptl) − (fn.c./absn.c.) is better, and this formula is also applied to the calculation of the normalization of our experimental results.

We choose experimental results diluted by a factor of 4 to estimate the fluorescence value beyond the measuring range. It is a pity that due to time is limited, we have no way to make large amounts of data analysis, and have not yet found the necessary connection between dilution ratio and linear equation. We will make characterization of it with more data in future experiments, seeking whether there is a relationship, and contribute to the normalization method.