Team:OUC-China/Project/Overview

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Latest revision as of 01:31, 27 October 2012

Project overview

1. What is our motivation?

This summer, we have worked hard to construct various toolkits for red tide prevention and management. But why we choose red tide as our final problem to solve? There is mounting evidence of a global increase in nutrient levels of coastal waters through riverine and sewage inputs, and in both the numbers and frequency (as well as the species composition) of red tides. As we all know, red tide and other water bloom have become one of the major natural disasters, which may have a negative effect and cause economic losses to fisheries and aquaculture and, indeed, they may have great impacts on human health by means of algal toxins enrichment. So early warnings and countermeasure for alarming and containing red tide are of crucial importance[1].


2. What triggers water bloom?

The well-recognized culprit of water bloom is overload of nutrient (eutrophication).Take the Baltic Sea as example, dumping from sewage-treatment plants, farming and industry has poured about 20 million tons of nitrogen and 2 million tons of phosphorus into the Baltic over the past 50 years, which give rise to long-lasting algal blooms[2]. The net effect is an excess of phosphorous, which fuels nitrogen-fixing cyanobacteria and triggers algal blooms as the essential condition. Another crucial factor is an excess of nitrogen which can amplify the effect and enhance overgrowth of the cyanobacteria and alga (especially Pyrroptata). Although there is still not possible to conclude the extent to which the increase in red tides in coastal waters can be attributed to the increase in nutrient levels, what is now becoming clear is that N:P is far more important regulators[1].



Fig.1 Key factors controlling cyano-bacterial growth and dominance, including nutrient inputs/availability, water column transparency, mixing conditions, water residence times, temperature and grazing are shown. We can see that nutrient such as phosphorus, nitrogen and carbon are key factors that trigger red tide[3].


Fig. 3. Long-term development of monthly average Microcystis biomass and annual cycles of TN:TP mass ratios in Meiliang Bay, Lake Taihu.

Fig.2 Long-term development of montly average Microcystis biomass and annual cycles of TN:TP mass ratios. It is obvious that when total nitrogen: total phosphorus ranges from 10 to 30. The probability of occurrence of water bloom is higher than others[4].

3. How about our goals , achievements and prospects?

Our project is divided as three parts, phosphate and nitrate sensors which serve as the sensor device, ratio sensor and comparator as the decision-making devices, gas vesicle and phosphate accumulation as actuators. Our supreme goal is to construct an engineered E. coli that can detect particular ratios between nitrate and phosphate, accurately judge whether red tide is going to happen and immediately float on the water surface to issue warning signals like green fluorescence.


Although it is such an expansive project that we still have a long way to go, we have finished many great work and reached several milestones. For one thing, we accomplished the comparator experimental design as well as modeling simulation, for another we succeeded in constructing engineered E. coli that possess far shorter length and better property for bacteria to float within two hours.


In fact, there are many great ideas under construction. We have constructed a hybridized promoter pLac-ompR which can respond to certain intensity of light. With the aid of it, we can ligase our brand-new gvp generators downstream of it which enable cells to keep within the water surface. After that, we can bio-brick our ratio sensors or comparators together to detect the sign of red tide. We have confidence to further our exploring on new fields of synthetic biology and seek new application for our ideas.


4. What are sensors, decision-making devices and actuators?

Although our projects are divided into three parts, they actually act as a whole. It is coherent thinking pattern of synthetic biology[5], especially for making devices that should respond to the environmental signals rapidly. The picture below showcases our whole designs and their relationship.

*Sensors:

Our phosphate- and nitrate-sensitive devices are responsible for detection of environmental phosphate and nitrate. Besides, they transform the input signals into ‘readable information’(sRNA transcription rate)for decision-making devices which further analyses and processes information.

*Decision-making devices:

We are using small RNA to build decision-making devices, Comparator and Ratio Sensor, which process two independent inputs into detectable output. This is a model driven design and the experimental results matches with our models. It is also interesting to learn about the steep but intellectual process of our biological design.

*Actuators:

Floating on the water surfaces is the essential condition for engineered E. coli to survive and send out detectable signals (CaseI,II). Fortunately our new bio-brick, a gvp gene cluster, perfectly solve this problem. We can make it as constitutive actuator which is coupled with pLac-ompR to keep cells within water surfaces (CaseII). Besides that, we can also transform it into inducible actuators which give cells buoyancy only after they have made decisions.




Reference:

1. Ho, I.J.H.K.C., Are changes in N:P ratios in coastal waters the key to increased red tide blooms? Hydrobiologia, 1997. 352(141-147).

2. Gustafsson, B.G., et al., Reconstructing the development of baltic sea eutrophication 1850-2006. Ambio, 2012. 41(6): p. 534-48.

3. Paerl, H.W. and V.J. Paul, Climate change: links to global expansion of harmful cyanobacteria. Water Res, 2012. 46(5): p. 1349-63.

4. Paerl, H.W., et al., Controlling harmful cyanobacterial blooms in a hyper-eutrophic lake (Lake Taihu, China): the need for a dual nutrient (N & P) management strategy. Water Res, 2011. 45(5): p. 1973-83.

5. Voigt, C.A., Genetic parts to program bacteria. Curr Opin Biotechnol, 2006. 17(5): p. 548-57.



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