Difference between revisions of "Part:BBa K2947000"
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MODELING(with UGT33:BBa_K2947001)
 
MODELING(with UGT33:BBa_K2947001)
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<html><head></head><body><a>https://2019.igem.org/Team:GDSYZX/Model</a></body></html>
 
  
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By Using Image J software to analyze the relative brightness of protein bands, we obtained the data of gray value of two genes/4h varying with time. There is a positive correlation between gray value / 4H and protein expression, so we use the standardized gray value / 4H to reflect protein expression. Then we use SPSS software to draw the scatter plot of gray value / 4H about time to judge the overall trend. Among them, we changed the SPSS output format to English. (The relative gray value is equal to the following gray value divided by the gray value of 4h)
+
<html><head></head><body>detial:<a>https://2019.igem.org/Team:GDSYZX/Model</a></body></html>
  
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We found that these scatters showed a quadratic function parabola trend, so
+
By Using Image J software to analyze the relative brightness of protein bands, we obtained the data of gray value of two genes/4h varying with time. There is a positive correlation between relative gray value and protein expression, so we use the standardized relative gray value to reflect relative protein expression level. Then we use SPSS software to draw the scatter plot of relative gray value about time to judge the overall trend. (The relative gray value is equal to the following gray value divided by the gray value of 4h)
−
we square the time data. Next, we test Pearson correlation coefficient of time, time squared and gray value / 4H to check whether there is a linear correlation between them.
+
 
 +
We We found that these scatters showed a quadratic function parabola trend, so
 +
we square the time data. Next, we test Pearson correlation coefficient of time, time squared and relative gray value to check whether there is a linear correlation between them.
  
 
Then we found that the correlation between UGT33 gene variables was quite high, P value was less than 0.05, with a high significance. The correlation coefficient of 4HPAAS gene was higher than 0.6, P value was higher than 0.05, but less than 0.2. Although the degree was not significant, the correlation coefficient was higher. It can be concluded that the binary linear regression equation can be constructed between the relative gray value of two gene sequences and the square term of time .
 
Then we found that the correlation between UGT33 gene variables was quite high, P value was less than 0.05, with a high significance. The correlation coefficient of 4HPAAS gene was higher than 0.6, P value was higher than 0.05, but less than 0.2. Although the degree was not significant, the correlation coefficient was higher. It can be concluded that the binary linear regression equation can be constructed between the relative gray value of two gene sequences and the square term of time .
−
By using the least square method, we get the regression equation between relative gray value and time.
+
By using the least square method, we get the regression equation between relative gray value and time.  
 +
A linear regression equation model is inserted here.
 +
 
 +
<html><img href="https://2019.igem.org/wiki/images/2/21/T--GDSYZX--formula1.png"></html>
  
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Relative gray value = beta0 + beta1 * time + beta2 * time squared
+
<html><img href="https://2019.igem.org/wiki/images/2/26/T--GDSYZX--formula2.png"></html>
  
 
Then we analyze the fitting degree of the two models and calculate the R-square of the regression equation. We find that the goodness of fit of the two models is good, and the R-square is close to 1. Therefore, both models are better. In the case of significance level 0.05, the F-test of the two models is significant, which shows that all independent variable time has a higher linear significance for relative gray value on the whole, and the p-value of coefficient T test is less than 0.05. It also shows that each independent variable time has a higher linear significance for relative gray value.
 
Then we analyze the fitting degree of the two models and calculate the R-square of the regression equation. We find that the goodness of fit of the two models is good, and the R-square is close to 1. Therefore, both models are better. In the case of significance level 0.05, the F-test of the two models is significant, which shows that all independent variable time has a higher linear significance for relative gray value on the whole, and the p-value of coefficient T test is less than 0.05. It also shows that each independent variable time has a higher linear significance for relative gray value.
 +
From the fitting results, the relative gray value of UGT33 and 4HPAAS is proportional to time and inversely proportional to the square of time. From the results calculated from the model, it can be concluded that when Time=12.32, the relative gray value of UGT33 reaches a maximum value of 4.55; when Time=10.68, the relative gray value of 4HPAAS reaches a maximum value of 3.92. Since we measure every four hours, we can assume that when the time reaches about 9-12 hours, the expression reaches a maximum. It can also be seen from the two fitted images that the relative gray value increases with time and then increases and then decreases the parabolic trend.
 +
Based on this modeling analysis, we conclude that 12 hours is sufficient for the experiment.
  
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The image is analyzed: the point is the gray value data measured in our experiment divided by the gray value of 4 hours, and the curve is the image of regression equation calculated by least square method. In the images of UGT33 and 4HPAAS, we can see that the monotonic trend of the curve model is basically the same. Because the relative gray value basically reflects the amount of protein expression, with the increase of time, it can be considered that the amount of protein expression increases correspondingly, but the speed decreases gradually. This can be explained by the reduction of reactants. Since we don't have many time points, we can think that when time reaches 9-12 minutes, the amount of expression reaches its maximum. Even the largest data points are above the curve in both images. Then the relative gray value decreases with the increase of time.
 
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Based on this modeling analysis, we think that 12 minutes is enough for the experiment.
 
 
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<span class='h3bb'>Sequence and Features</span>
 
<span class='h3bb'>Sequence and Features</span>

Revision as of 03:07, 20 October 2019


4HPAAS

4HPAAS(referring to 4-hydroxyphenylacetaldehyde synthase) protein coding region. It reduces L-tyrosine to produce 4-hydroxy-phenylacetaldehyde. It is the first enzyme in the biosynthesis of salidroside.


Usage and Biology

4HPAAS is one gene of the Aromatic acetaldehyde synthases(AASs). AASs, together with tryptophan decarboxylases(TDCs) and TyDCs, encompass a large family of pyridoxal phosphate(PLP)-dependent enzymes broadly referred to as the plant AAAD family.(Facchini et al., 2000; Kaminaga et al., 2006) As their respective names imply, TyDCs, YDCs, and AASs catalyze discrete decarboxylation or decarboxylation-deamination reactions using specific aromatic amino acids as substrates.

Previous research has shown that 4HPAAS functions in the direct conversion of tyrosin to 4-hydroxyphenylacetaldehyde(4-HPAA) in Rhodiola salidroside biosynthesis.(Michel et al., 2017)

1.In order to find a suitable detection time for salidroside, we explored the rule that the expression of 4HPAAS and UGT33 in Arabidopsis protoplasts in respond to the change of time. It was found that the expression of 4HPAAS and UGT33 reached the highest level 10 hours after transfection, so we speculated that this time should be the time with the highest synthesis rate of salidroside, so we chose 12 hours after transfection as the best time to detect salidroside.

A: Western blot was used to detect the expression of 4HPAAS and UGT33 in respond to the change of time; B: We used “i mage J” to analyze the relative expression of 4HPAAS in respond to the change time (set the band gray value of 4hours as 1); C: i mage J software and UGT33s with time (set the band gray value of 4 hours as 1).

2.The protoplast and salidroside standard samples of arabidopsis thaliana transfected with UGT33 and 4HPAAS genes were compared by liquid chromatography. The peak value of the product measured in sample No. 1 was basically consistent with the peak value of salidroside standard samples.

Therefore, we can determine that the transfected protoplast of arabidopsis thaliana can produce salidroside.

MODELING(with UGT33:BBa_K2947001)

detial:https://2019.igem.org/Team:GDSYZX/Model

By Using Image J software to analyze the relative brightness of protein bands, we obtained the data of gray value of two genes/4h varying with time. There is a positive correlation between relative gray value and protein expression, so we use the standardized relative gray value to reflect relative protein expression level. Then we use SPSS software to draw the scatter plot of relative gray value about time to judge the overall trend. (The relative gray value is equal to the following gray value divided by the gray value of 4h) 

We We found that these scatters showed a quadratic function parabola trend, so

we square the time data. Next, we test Pearson correlation coefficient of time, time squared and relative gray value to check whether there is a linear correlation between them.

Then we found that the correlation between UGT33 gene variables was quite high, P value was less than 0.05, with a high significance. The correlation coefficient of 4HPAAS gene was higher than 0.6, P value was higher than 0.05, but less than 0.2. Although the degree was not significant, the correlation coefficient was higher. It can be concluded that the binary linear regression equation can be constructed between the relative gray value of two gene sequences and the square term of time . By using the least square method, we get the regression equation between relative gray value and time. A linear regression equation model is inserted here.

Then we analyze the fitting degree of the two models and calculate the R-square of the regression equation. We find that the goodness of fit of the two models is good, and the R-square is close to 1. Therefore, both models are better. In the case of significance level 0.05, the F-test of the two models is significant, which shows that all independent variable time has a higher linear significance for relative gray value on the whole, and the p-value of coefficient T test is less than 0.05. It also shows that each independent variable time has a higher linear significance for relative gray value. From the fitting results, the relative gray value of UGT33 and 4HPAAS is proportional to time and inversely proportional to the square of time. From the results calculated from the model, it can be concluded that when Time=12.32, the relative gray value of UGT33 reaches a maximum value of 4.55; when Time=10.68, the relative gray value of 4HPAAS reaches a maximum value of 3.92. Since we measure every four hours, we can assume that when the time reaches about 9-12 hours, the expression reaches a maximum. It can also be seen from the two fitted images that the relative gray value increases with time and then increases and then decreases the parabolic trend. Based on this modeling analysis, we conclude that 12 hours is sufficient for the experiment.

Sequence and Features


Assembly Compatibility:
  • 10
    COMPATIBLE WITH RFC[10]
  • 12
    COMPATIBLE WITH RFC[12]
  • 21
    INCOMPATIBLE WITH RFC[21]
    Illegal BglII site found at 631
    Illegal BglII site found at 712
    Illegal BglII site found at 1156
  • 23
    COMPATIBLE WITH RFC[23]
  • 25
    COMPATIBLE WITH RFC[25]
  • 1000
    COMPATIBLE WITH RFC[1000]