Difference between revisions of "Part:BBa K2599017"

Revision as of 12:24, 14 October 2018

T7 Promoter+RBS+GS linker+αS1-casein

NCTU_Formosa 2018 designed a Biobrick contains αS1-casein [http://2014.igem.org/Team:SF_Bay_Area_DIYbio/Parts#Alpha-s1_casein_.28CSN1S1.29] and a GS linker (BBa_K1974030) ahead as a Curcumin biosensor.

The goal of our system is to regulate the soil microbiota in order to reach the maximum crop productivity. To accurately predict the curcumin content from NPK content in soil, we create a bio-sensor. This sensor can precisely detect the curcumin containment in turmeric. After the detection of curcumin, results can be fitted into our productivity model and utilize artificial intelligent to increase the accuracy. With the cooperation of productivity model and curcumin transformation model, we can perfectly predict the crop productivity and maintain balance soil microbiota.

Introduction

Curcumin

Curcumin is a natural lipid-soluble yellow compound from the plant Curcuma. It is a potent antioxidant as well as antitumorigenic and anti- inflammatory molecule. Although Curcumin has been proved its therapeutic efficacy against many human ailments, but the problem is it is hard to absorb by human cells. To solve this problem, a paper has discovered a curcumin carrier protein called αS1-casein, shows high binding affinity with curcumin. We then utilize this property of αS1-casein to create a curcumin bio-sensor.

αS1-casein

Casiens are proteins commonly found in mammalian milk and is a mixture of four phosphoprotein. One of the phosphoprotein is αS1-casein, which contains no disulfide bonds and relatively little tertiary structure. As their primary function is nutritional, binding large amounts of calcium, zinc and other biologically important metals, amino acid substitutions or deletions have little impact on function.

The Binding Between Curcumin and αS1-casein

According to the reference, we found how this two bind together.

Curcumin has a β-diketone moiety, flanked by two phenolic groups, that helps bind to proteins through hydrophobic interactions.

The carboxyl-terminal of αS1-casein (100−199 residues) predominantly contains hydrophobic amino acids, which may be involved in the binding process. Residues 14−24 in αS1-casein are hydrophobic in nature and form a surface “patch” of hydrophobicity. Curcumin may probably be binding at these two sites, with two different ranges of affinity through hydrophobic interaction. One with high affinity [(2.01 ± 0.6) × 106 M−1] and the other with low affinity [(6.3 ± 0.4) × 104 M−1].

Experiment

Cloning

We got the amino acid sequence of αS1-casein from NCBI, and adjust the DNA sequence to optimize its expression in E. coli. We also added a GS linker ahead to enhance the function of sensor.

After the digestion and ligation with pet30a backbone. We expression the protein in E.coli BL21 DE3.

Chip Production

Modification protocol

1. Dipped the chips in 10mM Mua, RT 4hrs. Wash with 95% EtOH three times.

2. Add EDC+NHS mixture (100+100mM in DDW) on chips, RT 1hrs. DDW rinse.

3. Add αS1-casein on chips, RT 1hrs, wash with PBS three times.

4. Dipped the chips in blocking solution, RT 1.5hrs, wash with PBS three times.

Electrochemistry

Introduction

After choosingαS1-casein as our biosensor, we should choose a method to detect curcumin. We choose the electrochemical impedance spectroscopy (EIS) and Differential Pulse Voltammetry (DPV), the two detecting methods in electrochemistry.

Electrochemical Impedance Spectroscopy

EIS is simple, convenient, and rapid, so that it is quite suitable for detecting whether the biosensor effective or not. This method uses the principle that impedance will be changed by charge transfer, and then measure the change of impedance by Alternate Current. Therefore, if we find out that our measured result has the stronger change than negative control, we can say our method could produce a fierce Redox reaction. However, because EIS is not a suitable method for detecting small molecule, the error will be very large if we choose it to perform formula computing. So we decide to use DPV to improve this problem.

Differential Pulse Voltammetry

DPV uses the difference between before and after the pulse application in order to solve the influence of background noise. This principle is difference from EIS. We hope we can find out which method is more sensitive to curcumin, and create more accurate formula.

Data Analysis

First of all, we use EIS to check whether our biosensor can detect curcumin. We have two samples. Red line is connected to general chip, and blue line is the chip connected with αS1-casein (Fig 1). When our biosensor is connected with αS1-casein to detect curcumin, impedance value become larger. That is our biosensor connected with αS1-casein produce more fierce Redox reaction than another. This figure also represent that the biosensor connected with αS1-casein have more effect of detecting curcumin than none.

After we prove that adding αS1-casein can detect curcumin, we hope we can use more accurate method to show our data. We choose DPV to replicate the experiment above, and determine which method is sensitive. Comparing with fig1 and fig2, we can find out that chips with αS1-caseinis almost no change in EIS experiment, and change a lot in DPV experiment in contrast. In this way, we can explain that DPV is more sensitive and has better signal than EIS.

Measurement

1. Dilute Curcumin in PBS/PB buffer, react 30min

2. Rinse with PSB/PB buffer on time and dry the chip.

3. Wash the reference and counter electrode with DDW, dry them.

4. Set up the three electrode with electrochemical cell

5. Measure electrochemistry.

Sequence and Features