Difference between revisions of "Team:NKU China/InterLab"

Revision as of 14:21, 30 October 2017

Backgrounds

Aim

Interlab

Backgrounds

Good bricks make strong buildings. The same is true in the field of synthetic biology. To ensure the biobricks created in iGEM competitions are repeatable and reliable ,a robust measurement procedures been developed for green fluorescent protein (GFP) over the last three years by the Measurement Committee, through the InterLab study.Also,numbers of teams participate in this standardized measurement project.We’re honored to participate in the fourth International InterLab Measurement Study.

Aim

By providing a protocol in details as well as forms helping unify the analyse of data,the Measurement Committee hopes to handle the problems emerged while establishing a baseline for replicability of fluorescence measurements.So with the same devices,the same protocol and devices,we try to measure the fluorescence intensity controlled by this year’s devices and study the distribution pattern of those results with teams all over the world.

Methods

Cell Transformation

The following devices (from InterLab Measurement Kit) were transformed into Escherichia coli DH5α:

● Positive control
● Negative control
● Test Device 1: J23101+I13504
● Test Device 2: J23106+I13504
● Test Device 3: J23117+I13504
● Test Device 4: J23101.BCD2.E0040.B0015
● Test Device 5: J23106.BCD2.E0040.B0015
● Test Device 6: J23117.BCD2.E0040.B0015

Transformation Selection

2 colonies from each of plate were picked and inoculated on 5-10 mL LB medium + Chloramphenicol.
Grow the cells overnight (16-18 hours) at 37°C and 220 rpm.

Cell preservation

200 µL of each of the 16 overnight cell cultures was mixed with 400 µL 50% glycerol and the mixture was preserved at -20℃.

Calibration

1.OD₆₀₀ reference point

◻ Add 100 µl LUDOX into wells A1, B1, C1, D1 (or 1 mL LUDOX into cuvette)
◻ Add 100 µl of H₂O into wells A2, B2, C2, D2 (or 1 mL H₂O into cuvette)
◻ Measure absorbance 600 nm of all samples in all standard measurement modes in instrument
◻ Record the data in the table below or in your notebook
◻ Record the result in the sheets provided.The results are as followed

Form1. 96 hole plate background value calibration

	LUDOX-HS40	H₂O
Replicate 1	0.047	0.038
Replicate 1	0.045	0.038
Replicate 1	0.068	0.036
Replicate 1	0.049	0.038
Arith. Mean	0.05225	0.0375
Corrected Abs₆₀₀	0.01475
Reference OD₆₀₀	0.0425
OD₆₀₀/Abs₆₀₀	2.8813559

2.Fluorescence standard curve

Prepare the fluorescein stock solution:

◻ Spin down fluorescein stock tube to make sure pellet is at the bottom of tube.
◻ Prepare 2x fluorescein stock solution (100 µM) by resuspending fluorescein in 1mL of 1xPBS. [Note: it is important that the fluorescein is properly dissolved. To check this, after the resuspension you should pipette up and down and examine the solution in the pipette tip – if any particulates are visible in the pipette tip continue to mix the solution until they disappear.]
◻ Dilute the 2x fluorescein stock solution with 1xPBS to make a 1x fluorescein solution and resulting concentration of fluorescein stock solution 50 µM (500µL of 2x fluorescein in 500 µL 1x PBS will make 1 mL of 50 µM (1x) fluorescein solution.)

Prepare the serial dilutions of fluorescein:

◻ Add 100 µl of PBS into wells A2, B2, C2, D2....A12, B12, C12, D12
◻ Add 200 µl of fluorescein 1x stock solution into A1, B1, C1, D1
◻ Transfer 100 µl of fluorescein stock solution from A1 into A2.
◻ Mix A2 by pipetting up and down 3x and transfer 100 µl into A3…
◻ Mix A3 by pipetting up and down 3x and transfer 100 µl into A4...
◻ Mix A4 by pipetting up and down 3x and transfer 100 µl into A5...
◻ Mix A5 by pipetting up and down 3x and transfer 100 µl into A6...
◻ Mix A6 by pipetting up and down 3x and transfer 100 µl into A7...
◻ Mix A7 by pipetting up and down 3x and transfer 100 µl into A8...
◻ Mix A8 by pipetting up and down 3x and transfer 100 µl into A9...
◻ Mix A9 by pipetting up and down 3x and transfer 100 µl into A10...
◻ Mix A10 by pipetting up and down 3x and transfer 100 µl into A11...
◻ Mix A11 by pipetting up and down 3x and transfer 100 µl into liquid waste

TAKE CARE NOT TO CONTINUE SERIAL DILUTION INTO COLUMN 12.

◻ Repeat dilution series for rows B, C, D
◻ Measure fluorescence of all samples in all standard measurement modes in instrument
◻ Record the data in your notebook
◻ record the result in the sheets provided.The results are as followed

Form2. Data from standard curve measuring

uM Fluorescein	50.00	25	12.5	6.25	3.125	1.5625
Replicate 1	7854030	4609962	2203443	1291423	674526	352662
Replicate 2	8303792	4615166	2429090	1233826	617992	307043
Replicate 3	8273438	4571361	2484100	1223562	608128	305808
Replicate 4	8382457	4607376	2441882	1178477	663508	334506
Arith. Mean	8203429.25	4600966.25	2389628.75	1231822	641038.5	325004.75
Arith. Std.Dev.	237419.9359	20000.93448	126329.6521	46440.68562	32866.05776	22703.42781

uM Fluorescein	0.78125	0.390625	0.1953125	0.09765625	0.048828125	0
Replicate 1	171299	90477	46991	25016	13592	788
Replicate 2	138185	69205	35089	18071	9332	868
Replicate 3	139755	69437	34718	17996	9296	757
Replicate 4	158489	69550	35125	18928	7932	796
Arith. Mean	151932	74667.25	37980.75	20002.75	10038	802.25
Arith. Std.Dev.	15867.51688	10540.81168	6009.649706	3368.801308	2457.312353	46.94944089

Fig1. Fluorescein Standard Curve

Cell recovery

5µL of preservation mixture of each of the 16 colonies was inoculated in 5 mL LB medium (with 35 ng/µL chloramphenicol) in a 15 mL tube.Cells were incubated overnight for 15 h at 37℃ and 220 rpm.

Cell growth,Sampling and assay

1.The plate reader was set to read OD₆₀₀.
2.OD₆₀₀of the overnight cultures was measured and the data shown bellow. Later they were diluted according to the calculation in the form.

Form3. OD600 of the overnight cultures and dilution protocol

Colony 1

target Abs₆₀₀	0.02
target volume (mL)	12
sample	Abs₆₀₀ Reading	Volume of Preloading Culture	Volume of Preloading Media
positive control	0.4745	0.563380282	11.43661972
negative control	0.42725	0.633663366	11.36633663
device 1	0.5135	0.516129032	11.48387097
device 2	0.46625	0.574506284	11.42549372
device 3	0.45875	0.585009141	11.41499086
device 4	0.4835	0.551724138	11.44827586
device 5	0.35525	0.782396088	11.21760391
device 6	0.4955	0.536912752	11.46308725
media+chl	0.0485

Colony 2

target Abs₆₀₀	0.02
target volume (mL)	12
sample	Abs₆₀₀ Reading	Volume of Preloading Culture	Volume of Preloading Media
positive control	0.46	0.583232078	11.41676792
negative control	0.45	0.597758406	11.40224159
device 1	0.529	0.499479709	11.50052029
device 2	0.508	0.522306855	11.47769314
device 3	0.47175	0.567040756	11.43295924
device 4	0.4525	0.594059406	11.40594059
device 5	0.46825	0.57176891	11.42823109
device 6	0.4595	0.583941606	11.41605839
media+chl	0.0485

3.The cultures were diluted to a target OD600 of 0.02 in 10 mL LB medium(with 35 ng/µL chloramphenicol) in 50 mL falcon tubes.
4.The cultures were incubated at 37℃ and 220 rpm.
5.100µL samples of the culture were taken at 0,1,2,3,4,5 and6 hours of incubation.
6.The sample were placed on ice.
7.Samples were laid out according to the following figure.
8.Data was recorded.

Fig2. Guide for adding sample

Results Analysis

Brief introduction of devices measured

Quantification and standardization play important roles in synthetic biology.Although the parameter values are calculated by model equations, it is hard to select the biobricks that reliably implements a desired cellular function with quantitative values. To overcome this problem, the RBSs were designed to control the expression of downstream genes when necessary.[1]This year we are about to test RBS B0034 and another modified RBS called bicistronic device (BCD2)-J364100 with the same GFP gene:GFP E0040.

Visible Results

We hope that our experimental results are direct and easy to understand,so we just let E.coli themselves tell the story by making them grow into the shape of our team name.In this picture,N is written with negative control,K&U with positive control.The last six letters were written with E.coli containing devices 1-6.It’s quite interesting that we can see device 2 is the brightest,even brighter than positive control.Among device 4-6,4 is the brightest,which corresponds with our experimental data beleow well.

Fig3. Team name written with cultures in Interlab experiment.Letter N is written with group Negative Control,K and U with Positive Control,”-”with Device 1,C with Device 2,h with Device 3 and i,n,a with Device 4,5,6.There are obvious differences in fluorescence intensity they expressed.

Experimental Data

Form4. Experimental Data

ANOVA

Analysis of Variance Table

Response: value
              Df     Sum Sq    Mean Sq  F value    Pr(>F)    
promoter       2 1.5095e+12 7.5475e+11 428.6242 < 2.2e-16 ***
RBS            1 5.9784e+10 5.9784e+10  33.9512 2.577e-08 ***
Time           3 1.6484e+10 5.4947e+09   3.1204   0.02736 *  
colony         1 2.4858e+09 2.4858e+09   1.4117   0.23636    
replicate      3 1.9372e+09 6.4574e+08   0.3667   0.77711    
promoter:RBS   2 2.7491e+12 1.3746e+12 780.6174 < 2.2e-16 ***
Residuals    179 3.1520e+11 1.7609e+09                       
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Form5. Significant difference analysis

Data Analysis

Since there are several factors like different promoters,RBSs,and interactions of the two elements can infecting the expression of GFP while time also influence the result to some extent as difference appears in the weight of influence caused by promoters and RBSs as time went by.To get more useful information,we conduct a variance analysis to evaluate the effect of these factors.Sheets above are the results we get.
Basically we have a closer look at these data by dividing them by hour and seeing how different growth status can influence the results.And as we can see in all the sheets, in general the main factors with significant difference are promoters,interaction effects and replicates,which causes us great interest.
It’s obviously that at 0 h all cultures’ conditions are almost the same.From sheets describing the data of 2 h, we can see that there are significant difference among different promoters as well as interaction effects between promoters and RBSs(elements) while different elements didn’t show that significance.Analysing the results of 4 h, we can see that promoters and interaction effects are still the factors with significant difference,while the p-value of elements(RBSs) is much smaller than 2 h.It seems that the elements function later than promoters, however, more supporting information is needed.An interesting conclusion from 6 h’s result is the contribution of elements for significant difference are larger, which seems confirmed the suppose above.That’s a quite charming discovery, maybe this can help studying the temporal regulation of gene expression regulation.

Conclusion

All the forms we get from the analysis show that different promoters and different interaction effects between promoters and elements have significant difference.Also we find the tendency that as time goes by, different elements shows larger and larger difference.However, all these finding and problems are open questions and we welcome any innovation helps explaining all these findings and solving problems.We can be reached at nkuigem2017@163.com.

Discussion

The promoters in the devices we use this year is the same as last year's material. Generally the relative transcription initation strength of three promoters is consistent with the result characterized by RFP FI．
The results we get shows that under the standarlized protocol , different devices behaved differently and more functions can be inferred from special phenomenons.　
Firstly we felt it was harder to transform plasmid with device 1 and 6,which was confirmed by JLU.NPU also reported difficulty on device 4.
Then the index to measure-FI shows that positive control is not always the highest.This time device 2 made it.
Finally about describing the results,we think it would be better if the Fluorescein Standard Curve and microbes with GFP are in the same buffer like PBS to make errors from backgrounds least.It's also a good idea to give the equation turning FI of GFPs into their concentration.

@@ Line 260: / Line 260: @@
 ◻ record the result in the sheets provided.The results are as followed</div>
 <div class="interlab-table1">
-<div class="interlab-fn">Form1. Data from standard curve measuring</div>
+<div class="interlab-fn">Form2. Data from standard curve measuring</div>
 <table border="6" width="500px" style="margin: 0 auto;font-size:16px;color:#FFFFFF;">
      <tr>
@@ Line 416: / Line 416: @@
 <div class="interlab-list">1.The plate reader was set to read OD<sub>600</sub>.</br>
 .OD<sub>600</sub>of the overnight cultures was measured and the data shown bellow. Later they were diluted according to the calculation in the form.</div>
-<div class="interlab-fn">Form2. OD600 of the overnight cultures and dilution protocol</div>
+<div class="interlab-fn">Form3. OD600 of the overnight cultures and dilution protocol</div>
 <div class="interlab-subheader2">Colony 1</div>
 <div class="interlab-table2">
@@ Line 585: / Line 585: @@
 <div id="ExperimentalData"></div>
 <div class="interlab-header">Experimental Data</div>
-<div class="interlab-fn">Form3. Experimental Data</div>
+<div class="interlab-fn">Form4. Experimental Data</div>
@@ Line 646: / Line 646: @@
 ---
 Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</code></pre>
-<div class="interlab-fn">Form4. Significant difference analysis</div>
+<div class="interlab-fn">Form5. Significant difference analysis</div>
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" 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" 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