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<a>PROJECT</a> | <a>PROJECT</a> | ||
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<li><a href="https://2018.igem.org/Team:BIT-China/ExperimentsFeedback">Feedback</a></li> | <li><a href="https://2018.igem.org/Team:BIT-China/ExperimentsFeedback">Feedback</a></li> | ||
<li><a href="https://2018.igem.org/Team:BIT-China/ExperimentsOutput">Output</a></li> | <li><a href="https://2018.igem.org/Team:BIT-China/ExperimentsOutput">Output</a></li> | ||
− | <li><a href="https://2018.igem.org/Team:BIT-China/ | + | <li><a href="https://2018.igem.org/Team:BIT-China/Results">Results</a></li> |
</ul> | </ul> | ||
</li> | </li> | ||
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<ul> | <ul> | ||
<li><a href="https://2018.igem.org/Team:BIT-China/Model">Overview</a></li> | <li><a href="https://2018.igem.org/Team:BIT-China/Model">Overview</a></li> | ||
− | <li><a href="https://2018.igem.org/Team:BIT-China/FluorescentProbesModel">Fluorescent | + | <li><a href="https://2018.igem.org/Team:BIT-China/FluorescentProbesModel">Fluorescent Probe Model </a></li> |
<li><a href="https://2018.igem.org/Team:BIT-China/H2O2DecompositionModel">H<sub>2</sub>O<sub>2</sub> | <li><a href="https://2018.igem.org/Team:BIT-China/H2O2DecompositionModel">H<sub>2</sub>O<sub>2</sub> | ||
Decomposition Model</a></li> | Decomposition Model</a></li> | ||
<li><a href="https://2018.igem.org/Team:BIT-China/roGFP2-Orp1MichaelisEquationModel">roGFP2-Orp1 | <li><a href="https://2018.igem.org/Team:BIT-China/roGFP2-Orp1MichaelisEquationModel">roGFP2-Orp1 | ||
− | Michaelis | + | Michaelis equation Model</a></li> |
</ul> | </ul> | ||
</li> | </li> | ||
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</ul> | </ul> | ||
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<a href="https://2018.igem.org/Team:BIT-China"><img id="imgA" class="imgA-new-pos" src="https://static.igem.org/mediawiki/2018/4/46/T--BIT-China--iGEM2018-A_img.png" /></a> | <a href="https://2018.igem.org/Team:BIT-China"><img id="imgA" class="imgA-new-pos" src="https://static.igem.org/mediawiki/2018/4/46/T--BIT-China--iGEM2018-A_img.png" /></a> | ||
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<div class="cd-section"> | <div class="cd-section"> | ||
<div class="HP-title"> | <div class="HP-title"> | ||
− | <a class="HP-title-1" style="border-bottom:3px solid #131313;text-decoration: none;"> | + | <a class="HP-title-1" style="border-bottom:3px solid #131313;text-decoration: none;">APPLIED DESIGN</a> |
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<div class="HP-content"> | <div class="HP-content"> | ||
<p class="HP-content-p HP-margin-toTitle2"> | <p class="HP-content-p HP-margin-toTitle2"> | ||
− | + | Oxidation damage, aging and relative diseases are highly related to human health. Antioxidants are currently effective treatments. However, detection approaches to antioxidant are quite limited, especially in living-cells. Traditional methods largely focused on direct redox reaction which may have non-proper relation to living systems. Living cells are integrated with multiple natural anti-oxidant systems, including anti-oxidant enzyme system, reductive system, post-damage repair system, etc. All these make it sophisticated to evaluate real effects from exogenous antioxidant. To date, substantial efforts have been devoted to developing alternative strategies that can overcome the disadvantages and difficulties of online antioxidant detection in living cells .There is still no ideal result. | |
− | + | One promising and challenging method for accomplishing this purpose is to construct a "living antioxidant detection device" via synthetic biology method. Yeast was used as host cell as it can present a simple and accurate measuring platform for us. Furthermore, we constructed multiple functional gene circuits to implement ROS regulating, endogenous redox reaction testing, and feedback regulation, etc. These results together demonstrate the excellent potential of this project in detecting antioxidant easily, accurately, fast and economically. | |
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</p> | </p> | ||
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<p class="HP-content-p HP-margin-toContentP"> | <p class="HP-content-p HP-margin-toContentP"> | ||
So, we design a detection system based on living cells that create a living-cell stage for | So, we design a detection system based on living cells that create a living-cell stage for | ||
− | + | antioxidants' performance. This improves biological relevance and credibility and the living cell | |
is yeast, <i>Saccharomyces Cerevisiae</i>. | is yeast, <i>Saccharomyces Cerevisiae</i>. | ||
</p> | </p> | ||
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<li> | <li> | ||
− | ● Second, aging of the yeast Saccharomyces cerevisiae in stationary culture, often referred to | + | ● Second, aging of the yeast <i>Saccharomyces cerevisiae</i> in stationary culture, often referred to |
as 'chronological aging', is a frequently applied system to study aging of eukaryotic cells. | as 'chronological aging', is a frequently applied system to study aging of eukaryotic cells. | ||
</li> | </li> | ||
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<div class="cd-section"> | <div class="cd-section"> | ||
<div class="HP-title-2 HP-margin-Title2Up"> | <div class="HP-title-2 HP-margin-Title2Up"> | ||
− | <a style="text-decoration:none;color:#131313;">To address these problems, we need to consider the | + | <a style="text-decoration:none;color:#131313;">To address these problems, </a> |
+ | </div> | ||
+ | <div class="HP-title-2 HP-margin-Title2Up"> | ||
+ | <a style="text-decoration:none;color:#131313;">we need to consider the | ||
following things:</a> | following things:</a> | ||
</div> | </div> | ||
− | |||
<div class="HP-content-all"> | <div class="HP-content-all"> | ||
<div class="HP-content"> | <div class="HP-content"> | ||
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<div class="HP-content"> | <div class="HP-content"> | ||
<p class="HP-content-p HP-margin-toTitle2"> | <p class="HP-content-p HP-margin-toTitle2"> | ||
− | The following is a comparison between the CAA assay and | + | The following is a comparison between the CAA assay and our project, which illustrates our design and improvement specifically. |
− | + | ||
</p> | </p> | ||
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<p class="HP-content-p HP-margin-toTitle2"> | <p class="HP-content-p HP-margin-toTitle2"> | ||
Cell-based method MTT appeared in the same period as CAA. Their ideas and strategy are similar | Cell-based method MTT appeared in the same period as CAA. Their ideas and strategy are similar | ||
− | and | + | and don't need not be detailed here. MTT improved the disadvantage that CAA can only throw a |
single species of radical into cells. And the detection process is simpler. However, it was | single species of radical into cells. And the detection process is simpler. However, it was | ||
criticized because the text conditions is too extreme for living cells, which may not be | criticized because the text conditions is too extreme for living cells, which may not be | ||
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<i>Yca1</i> encodes synthesis of metacaspase, a homologue of the mammalian caspase, and plays a | <i>Yca1</i> encodes synthesis of metacaspase, a homologue of the mammalian caspase, and plays a | ||
crucial role in the regulation of yeast apoptosis. According to the literature, knock out <i>yca1</i> | crucial role in the regulation of yeast apoptosis. According to the literature, knock out <i>yca1</i> | ||
− | can improve the yeast tolerance to ROS, so we just do it. As a result, engineered | + | can improve the yeast tolerance to ROS, so we just do it. As a result, engineered strain can |
work at high ROS level. | work at high ROS level. | ||
</p> | </p> | ||
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<li> | <li> | ||
− | ● Last, excessive accumulation of ROS will affect the survival of engineered | + | ● Last, excessive accumulation of ROS will affect the survival of engineered strain. |
Feedback Module can ensure modest cell survival. | Feedback Module can ensure modest cell survival. | ||
</li> | </li> | ||
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<p class="HP-content-p HP-margin-toTitle2"> | <p class="HP-content-p HP-margin-toTitle2"> | ||
We screened out a lot of promoters for <a style="color:#131313;" href="https://2018.igem.org/Team:BIT-China/ExperimentsRegulator"><b>regulator | We screened out a lot of promoters for <a style="color:#131313;" href="https://2018.igem.org/Team:BIT-China/ExperimentsRegulator"><b>regulator | ||
− | components</b></a> ( | + | components</b></a> (GAL1p), <a style="color:#131313;" href="https://2018.igem.org/Team:BIT-China/ExperimentsFeedback"><b>feedback |
components</b></a> | components</b></a> | ||
− | ( | + | (CTT1p, GLR1p |
− | , | + | , TRX2p, TRR1p, TSA1p, SOD2p, GSH1p, GSH2p, GAL1p |
− | and | + | and MSY1p), and <a style="color:#131313;" href="https://2018.igem.org/Team:BIT-China/ExperimentsOutput"><b>output |
− | components</b></a>( | + | components</b></a>(FBA1p, TEF1p, TEF2p, ENO2p, PCK1p, |
− | + | PDC1p and PGI1p) | |
to find the promoter with the most suitable expression for detection. Additionally, because of | to find the promoter with the most suitable expression for detection. Additionally, because of | ||
the plug-and-play characteristic, the selected promoters with different expression strength | the plug-and-play characteristic, the selected promoters with different expression strength | ||
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<p class="HP-content-p HP-margin-toContentP"> | <p class="HP-content-p HP-margin-toContentP"> | ||
Considering that fluorescence intensity of roGFP2-orp1 can only characterize the relative level | Considering that fluorescence intensity of roGFP2-orp1 can only characterize the relative level | ||
− | of intracellular ROS qualitatively, but | + | of intracellular ROS qualitatively, but can't give the absolute content of intracellular ROS |
quantitatively, we established the model based on Michealis equation and some assumptions, | quantitatively, we established the model based on Michealis equation and some assumptions, | ||
which can convert fluorescence intensity of roGFP2-orp1 into the intracellular H<sub>2</sub>O<sub>2</sub> | which can convert fluorescence intensity of roGFP2-orp1 into the intracellular H<sub>2</sub>O<sub>2</sub> | ||
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<ul class="HP-content-p HP-margin-toContentP"> | <ul class="HP-content-p HP-margin-toContentP"> | ||
<li> | <li> | ||
− | ● Our engineering | + | ● Our engineering strain. |
</li> | </li> | ||
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<ul class="HP-content-p HP-margin-toContentP"> | <ul class="HP-content-p HP-margin-toContentP"> | ||
<li> | <li> | ||
− | ● Culture Our Engineering | + | ● Culture Our Engineering Strain. |
</li> | </li> | ||
<li> | <li> | ||
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<ul class="HP-content-p HP-margin-toTitle2"> | <ul class="HP-content-p HP-margin-toTitle2"> | ||
<li> | <li> | ||
− | 1 | + | [1] Halliwell B, Whiteman M. Measuring reactive species and oxidative damage in vivo and |
in cell culture: how should you do it and what do the results mean [J]. British journal of | in cell culture: how should you do it and what do the results mean [J]. British journal of | ||
pharmacology, 2004, 142(2): 231-255. | pharmacology, 2004, 142(2): 231-255. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 2 | + | [2] Liu R H, Finley J. Potential cell culture models for antioxidant research[J]. Journal of |
agricultural and food chemistry, 2005, 53(10): 4311-4314. | agricultural and food chemistry, 2005, 53(10): 4311-4314. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 3 | + | [3] Wolfe K L, Liu R H. Cellular antioxidant activity (CAA) assay for assessing |
antioxidants, foods, and dietary supplements. [J]. Journal of Agricultural & Food | antioxidants, foods, and dietary supplements. [J]. Journal of Agricultural & Food | ||
Chemistry, 2007, 55(22):8896. | Chemistry, 2007, 55(22):8896. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 4 | + | [4] Cao G, Alessio H M, Cutler R G. Oxygen-radical absorbance capacity assays for |
antioxidants. Free Rad Biol Med 1:303-311[J]. Free Radical Biology & Medicine, 1993, | antioxidants. Free Rad Biol Med 1:303-311[J]. Free Radical Biology & Medicine, 1993, | ||
14(3):303-311. | 14(3):303-311. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 5 | + | [5] Andrea Ghiselli, Mauro Serafini, Giuseppe Maiani, et al. A fluorescence-based method |
for measuring total plasma antioxidant capability[J]. Free Radical Biology and Medicine, | for measuring total plasma antioxidant capability[J]. Free Radical Biology and Medicine, | ||
1995, 18(1):29-36. | 1995, 18(1):29-36. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 6 | + | [6] Miller N J, Rice-Evans C, Davies M J, et al. A novel method for measuring antioxidant |
capacity and its application to monitoring the antioxidant status in premature neonates[J]. | capacity and its application to monitoring the antioxidant status in premature neonates[J]. | ||
Clinical Science, 1993, 84(4):407-412. | Clinical Science, 1993, 84(4):407-412. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 7 | + | [7] Winston G W, Regoli F, Dugas Jr A J, et al. A rapid gas chromatographic assay for |
determining oxyradical scavenging capacity of antioxidants and biological fluids[J]. Free | determining oxyradical scavenging capacity of antioxidants and biological fluids[J]. Free | ||
Radical Biology and Medicine, 1998, 24(3): 480-493. | Radical Biology and Medicine, 1998, 24(3): 480-493. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 8 | + | [8] Adom K K, Liu R H. Rapid peroxyl radical scavenging capacity (PSC) assay for assessing |
both hydrophilic and lipophilic antioxidants[J]. Journal of Agricultural & Food Chemistry, | both hydrophilic and lipophilic antioxidants[J]. Journal of Agricultural & Food Chemistry, | ||
2005, 53(17):6572. | 2005, 53(17):6572. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 9 | + | [9] Jakubowski W, Biliński T, Bartosz G. Oxidative stress during aging of stationary |
− | cultures of the yeast Saccharomyces cerevisiae.[J]. Free Radical Biology & Medicine, 2000, | + | cultures of the yeast <i>Saccharomyces cerevisiae</i>.[J]. Free Radical Biology & Medicine, 2000, |
28(5):659-664. | 28(5):659-664. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 10 | + | [10] Madeo, F., Fro¨hlich, E., and Fro¨hlich, K. U. (1997). A yeast mutant showing |
diagnostic markers of early and late apoptosis. J. Cell Biol. 139, 729–734. | diagnostic markers of early and late apoptosis. J. Cell Biol. 139, 729–734. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 11 | + | [11] Liu R H, Finley J. Potential cell culture models for antioxidant research.[J]. Journal |
of Agricultural & Food Chemistry, 2005, 53(10):4311. | of Agricultural & Food Chemistry, 2005, 53(10):4311. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 12 | + | [12] Cheli F, Baldi A. Nutrition‐Based Health: Cell‐Based Bioassays for Food Antioxidant |
Activity Evaluation[J]. Journal of Food Science, 2011, 76(9): R197-R205. | Activity Evaluation[J]. Journal of Food Science, 2011, 76(9): R197-R205. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 13 | + | [13] Dickinson B C, Chang C J. Chemistry and biology of reactive oxygen species in signaling |
or stress responses[J]. Nature Chemical Biology, 2011, 7(8):504-11. | or stress responses[J]. Nature Chemical Biology, 2011, 7(8):504-11. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 14 | + | [14] Amorati R, Valgimigli L. Advantages and limitations of common testing methods for |
antioxidants[J]. Free Radical Research, 2015, 49(5):633-49. | antioxidants[J]. Free Radical Research, 2015, 49(5):633-49. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 15 | + | [15] |
https://www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-human-nutrition-research-center/nutrient-data-laboratory/docs/oxygen-radical-absorbance-capacity-orac-of-selected-foods-release-2-2010/ | https://www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-human-nutrition-research-center/nutrient-data-laboratory/docs/oxygen-radical-absorbance-capacity-orac-of-selected-foods-release-2-2010/ | ||
</li> | </li> | ||
<li> | <li> | ||
− | 16 | + | [16] Frankel E N, Meyer A S. The problems of using one‐dimensional methods to evaluate |
multifunctional food and biological antioxidants[J]. Journal of the Science of Food and | multifunctional food and biological antioxidants[J]. Journal of the Science of Food and | ||
Agriculture, 2000, 80(13): 1925-1941. | Agriculture, 2000, 80(13): 1925-1941. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 17 | + | [17] Bonini M G, Rota C, Tomasi A, et al. The oxidation of 2′, 7′-dichlorofluorescin to |
reactive oxygen species: a self-fulfilling prophesy [J]. Free Radical Biology and Medicine, | reactive oxygen species: a self-fulfilling prophesy [J]. Free Radical Biology and Medicine, | ||
2006, 40(6): 968-975. | 2006, 40(6): 968-975. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 18 | + | [18] Papi A, Orlandi M, Bartolini G, et al. Cytotoxic and antioxidant activity of |
4-methylthio-3-butenyl isothiocyanate from Raphanus sativus L. (Kaiware Daikon) sprouts[J]. | 4-methylthio-3-butenyl isothiocyanate from Raphanus sativus L. (Kaiware Daikon) sprouts[J]. | ||
Journal of agricultural and food chemistry, 2008, 56(3): 875-883. | Journal of agricultural and food chemistry, 2008, 56(3): 875-883. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 19 | + | [19] Ge Q, Ge P, Jiang D, et al. A novel and simple cell-based electrochemical biosensor for |
evaluating the antioxidant capacity of Lactobacillus plantarum strains isolated from | evaluating the antioxidant capacity of Lactobacillus plantarum strains isolated from | ||
Chinese dry-cured ham[J]. Biosensors and Bioelectronics, 2018, 99: 555-563. | Chinese dry-cured ham[J]. Biosensors and Bioelectronics, 2018, 99: 555-563. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 20 | + | [20] Meyer A J, Dick T P. Fluorescent protein-based redox probes[J]. Antioxidants & redox |
signaling, 2010, 13(5): 621-650. | signaling, 2010, 13(5): 621-650. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 21 | + | [21] Morgan B, Sobotta M C, Dick T P. Measuring EGSH and H₂O₂ with roGFP2-based redox |
probes[J]. Free Radical Biology & Medicine, 2011, 51(11):1943-1951. | probes[J]. Free Radical Biology & Medicine, 2011, 51(11):1943-1951. | ||
</li> | </li> | ||
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− | 22 | + | [22] Khan M A S, Chock P B, Stadtman E R. Knockout of caspase-like gene, YCA1, abrogates |
− | apoptosis and elevates oxidized proteins in Saccharomyces cerevisiae[J]. Proceedings of the | + | apoptosis and elevates oxidized proteins in <i>Saccharomyces cerevisiae</i>[J]. Proceedings of the |
National Academy of Sciences of the United States of America, 2005, 102(48):17326-17331. | National Academy of Sciences of the United States of America, 2005, 102(48):17326-17331. | ||
</li> | </li> | ||
<li> | <li> | ||
− | 23 | + | [23] Rinnerthaler M, Büttner S, Laun P, et al. Yno1p/Aim14p, a NADPH-oxidase ortholog, |
controls extra mitochondrial reactive oxygen species generation, apoptosis, and actin cable | controls extra mitochondrial reactive oxygen species generation, apoptosis, and actin cable | ||
formation in yeast.[J]. Proceedings of the National Academy of Sciences of the United | formation in yeast.[J]. Proceedings of the National Academy of Sciences of the United |
Latest revision as of 02:34, 18 October 2018
Oxidation damage, aging and relative diseases are highly related to human health. Antioxidants are currently effective treatments. However, detection approaches to antioxidant are quite limited, especially in living-cells. Traditional methods largely focused on direct redox reaction which may have non-proper relation to living systems. Living cells are integrated with multiple natural anti-oxidant systems, including anti-oxidant enzyme system, reductive system, post-damage repair system, etc. All these make it sophisticated to evaluate real effects from exogenous antioxidant. To date, substantial efforts have been devoted to developing alternative strategies that can overcome the disadvantages and difficulties of online antioxidant detection in living cells .There is still no ideal result. One promising and challenging method for accomplishing this purpose is to construct a "living antioxidant detection device" via synthetic biology method. Yeast was used as host cell as it can present a simple and accurate measuring platform for us. Furthermore, we constructed multiple functional gene circuits to implement ROS regulating, endogenous redox reaction testing, and feedback regulation, etc. These results together demonstrate the excellent potential of this project in detecting antioxidant easily, accurately, fast and economically.
Ancient times, searching for anti-aging ways and secret of life's aging attract have been attracting countless passionate people.
Since 19th century, people have gradually realized the significance of antioxidants in solving the anti-aging puzzle and launched tireless exploration.
With the development of analytical methods and detection methods (such as L-band electron spin resonance (ESR), various probes, magnetic resonance imaging spin trapping and so on),researchers have more confidence and ability to detect antioxidants. Besides, driven by the public's eagerness for health and beauty, many chemical detection methods emerged around the 20th century. (such as, oxygen radical absorbance capacity (ORAC), total oxyradical scavenge capacity (TOSC), the peroxyl scavenging capacity (PSC), the ferric reducing/antioxidant power assay (FRAP), Trolox equivalent antioxidant capacity (TEAC) and so on)
The main measurement principle of chemistry methods is to characterize the reducibility of antioxidants by redox reaction with kinds of oxyradical. Chemistry methods has the advantages of handy, efficiency and accuracy.
However, this measurement principle is one-dimensional. On the one hand, its detecting conditions are almost different from the physiological environment that cell live in so that chemistry methods can't evaluate the antioxidant capability of antioxidants in the complicated metabolic process. On the other hand, living cells are integrated with multiple natural anti-oxidant systems, including anti-oxidant enzyme system, reductive system, post-damage repair system and so on in which antioxidants play a significant role and chemistry methods can't provide the stage of living cell. By the way, in 2012, USDA's Nutrient Data Laboratory (NDL) removed the USDA ORAC Database for Selected Foods from the NDL website because of the poor authenticity and low credibility of the chemistry methods. To sum up, the disadvantages of the chemical methods are two key words, low biological relevance and low credibility.
So, we design a detection system based on living cells that create a living-cell stage for antioxidants' performance. This improves biological relevance and credibility and the living cell is yeast, Saccharomyces Cerevisiae.
We chose yeast as the chassis cell of the product rather than HepG2 liver cancer cells, macrophage cells or Caco-2 colon cancer cells ect. Why?
- ● First, as we all know, the early researches on the mechanism of human diseases were explained by means of model organism yeast.
- ● Second, aging of the yeast Saccharomyces cerevisiae in stationary culture, often referred to as 'chronological aging', is a frequently applied system to study aging of eukaryotic cells.
- ● Last but not least, recently, human beings have the ability to synthesize yeast genome, which is an amazing breakthrough in the history of understanding of nature. Therefore, we choose yeast because of its practical application value and great potential in future.
Gradually. people realized the defects of the chemical methods, and began to detect antioxidants through animal model and human study which has higher biological relevance and credibility, after all the 21st century is a century for life science. Unfortunately, animal model and human study are time-consuming and expensive so that the initial antioxidants detect is not suitable. There's no doubt that cell-based detect is faster and cost-effective.
That's also the reason why we design cell-based detect system.
In 2007, Cell-based detection was first reported in the literature (CAA assay), which was a breakthrough in the history of antioxidants detection methods and was referenced widely. CAA assay characterizes the consumption of antioxidants on synthetic ROS (ABAP for Peroxyl Radicals) after entering cells by the fluorescence intensity of DCFH-DA fluorescent probes. Regretfully, it also has some shortcoming.
- ● On the one hand, both fluorescent probes and free radicals are artificially added from the external environment, which means introducing exogenous interference and it is not a completely endogenous cell detection.
- ● On the other hand, the credibility of the DCFH-DA probe has been criticized in the literature and it is also a question whether the synthesized radicals (ABAP for Peroxyl Radicals) can represent the endogenous ROS accumulated in cells.
- ● On the one hand, in the system we designed the detection process needs to be completely intracellular without introducing exogenous interference.
- ● On the other hand, the signal we detect need to be representative of intracellular ROS. And we choose intracellular H2O2 as the final signal.
We choose intracellular H2O2 as the final signal to represent all kinds of ROS in cell and for this case our output component roGFP2-Orp1 has high H2O2-specificity. Why?
- ● Most intracellular ROS comes from mitochondria respiratory chain and all kinds of ROS will convert into H2O2 under the intracellular antioxidant enzyme system. Once H2O2 accumulated, it will transfer to the cytoplasm.
- ● H2O2 is the final form of all kinds of ROS.
- ● roGFP2-Orp1 exists in cytoplasm.
The choice of intracellular H2O2 as the final signal has higher representativeness than other choices.
The following is a comparison between the CAA assay and our project, which illustrates our design and improvement specifically.
● Accumulation mode of ROS
Artificially add ROS generator, exogenous.
● Representativeness of ROS
A single kind of radical
● Limit of Use
Consumables, non-renewable.
● Method of Regulation
Control Dose.
● output signal
Fluorescence intensity of DCFH-DA.
● Artificial Addition
● Limit of Use
Take one sample for one detection.
● ROS Kit, 88$.
● Method of Use
It needs series of operations.
(yon1 expression cassette)
● Accumulation mode of ROS
Accumulate ROS by overexpress yon1 gene., endogenous.
● Representativeness of ROS
Endogenous accumulation of Integrated ROS by yeast cells.
Simulate the natural process of yeast cells oxidation.
● Limit of use
Durables. Once Yeast Transformation = Permanent Use
● Method of Regulation
Regulate the expression level of inducible promoter.
(roGFP2-Orp1 expression cassette)
● output signal
Fluorescence intensity of roGFP2-Orp1 fusion protein.
● Intracellular synthesis.
● Intracellular Constant Expression.
The reaction of roGFP2-Orp1 to ROS is reversible.
Real-time Monitoring.
Once Yeast Transformation = Permanent Use.
● Method of Use
We integrated its advantages and improved its shortcomings. Actually, the output components helped us save a lot of money rather than buying DCFH-DA probe.
Cell-based method MTT appeared in the same period as CAA. Their ideas and strategy are similar and don't need not be detailed here. MTT improved the disadvantage that CAA can only throw a single species of radical into cells. And the detection process is simpler. However, it was criticized because the text conditions is too extreme for living cells, which may not be representative of physiological settings.
This critical voice also reminds us that modest cell survival is necessary, considering that increase the ROS content by regulator components will increase stress of cells. Therefore, to improve the stability and reliability of product, and make it more durable. We designed the tolerance module.
Yca1 encodes synthesis of metacaspase, a homologue of the mammalian caspase, and plays a crucial role in the regulation of yeast apoptosis. According to the literature, knock out yca1 can improve the yeast tolerance to ROS, so we just do it. As a result, engineered strain can work at high ROS level.
Today is the age of interdisciplinary integration. Cell-based detection combined with traditional electrochemistry, which is a landmark in the history of antioxidants detection. The cell-based electrochemical method uses NaAlg/GO hydrogels and 3D culture system to place cells in electrochemical workstation and adds nanoscale electrode materials for sensing intracellular ROS. It has good reproducibility and stability and is simple and rapid. However, it is still unable to achieve high-throughput screening for antioxidants and is difficult to popularize because of limitation of materials and instrument.
21th century will become the new epoch of synthetic biology. As time goes on, synthetic biology is emerging in more and more fields and gives unique strategies to address kinds of problem. The plug-and-play characteristic of synthetic biological parts are conducive to the popularization of product.
In addition to the product design shown above, we have some special designs.
Feedback Module works based on dCas9 technology and endogenous antioxidant system of yeast. We transformed and made use of that system sensing intracellular ROS level and starting our embedded genetic circuit properly to control the ROS level by dCas9. What's the role of Feedback Module?
- ● First, intracellular ROS level increased by regulator components may fluctuate, which causes the detection signal unstable. Therefore, we designed the Feedback Module which can regulate the ROS level in a stable range. Second, our sensor roGFP2-Orp1 has detecting threshold for ROS. The output signal is linear within the threshold and nonlinear beyond the threshold. Feedback Module can control ROS level within the detection threshold.
- ● Last, excessive accumulation of ROS will affect the survival of engineered strain. Feedback Module can ensure modest cell survival.
We screened out a lot of promoters for regulator components (GAL1p), feedback components (CTT1p, GLR1p , TRX2p, TRR1p, TSA1p, SOD2p, GSH1p, GSH2p, GAL1p and MSY1p), and output components(FBA1p, TEF1p, TEF2p, ENO2p, PCK1p, PDC1p and PGI1p) to find the promoter with the most suitable expression for detection. Additionally, because of the plug-and-play characteristic, the selected promoters with different expression strength also provide the possibility and alternatives for future application under different conditions.
Modeling is an important part of synthetic biology. A science can only be truly perfected when it successfully applies mathematics.
Considering that fluorescence intensity of roGFP2-orp1 can only characterize the relative level of intracellular ROS qualitatively, but can't give the absolute content of intracellular ROS quantitatively, we established the model based on Michealis equation and some assumptions, which can convert fluorescence intensity of roGFP2-orp1 into the intracellular H2O2 concentration. As a result, the output signal of roGFP2-orp1 has a more intuitive meaning and higher application value.
If you want use our product to detect antioxidants, all you need to prepare is
- ● Our engineering strain.
- ● Mediums.
- ● An Instrument That Can Detect Fluorescence.
All you need to do is
- ● Culture Our Engineering Strain.
- ● Add Antioxidants.
- ● Monitor fluorescence intensity in Real-time.
- ● Conclude the intracellular H2O2 concentration by calculation program (the program is not yet designed).
- ● No extra operation.
We need to consider how its lifecycle can more broadly impact our lives and environments in positive and negative ways. There is on doubt that human practice is the best way.
one of the world's top 500 companies with a good reputation in the international grain and oil food market, became our first interviewee. We asked them about the market of current antioxidant products. And we learned that
- ● The sales of anti-oxidant products are on the rise.
- ● More and more people are pursuing anti-oxidant and anti-aging products.
Therefore, we have more reasons to believe that our product has a good application prospect in the market.
A leading innovative pharmaceutical company in Beijing, communicated with us about what our product can do.
- ● Most medicines would use antioxidants to prevent oxidation of medicines. So, our product could also be applied in pharmaceutical production.
- ● In addition to detect the antioxidant capability of antioxidants, we also can test whether the natural antioxidant products will deteriorate in quality over time.
Now, more and more antioxidant products are on the market, consumers are confused about the antioxidant effect of products and we learned it by questionnaires. Hopefully our product can help them.
You know the most amazing thing is that countless excellent natural antioxidants are hidden in nature, just countless starts twinkling in the Milky Way. When I was young, I looked up at starry sky and asked, "Are there aliens in the universe?". Someone answer, "The universe is big, bigger than you, bigger than anything. If it's just us, it is a waste of space." Today I wonder if there are excellent antioxidants in the nature to solve the problem of aging. There are so many substances in nature beyond our imagination. If not, it is a waste of space. Hopefully, our product can detect excellent antioxidants, which is our original dream.
We would do our best to make the product more beneficial to the world.
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