Team:ITB Indonesia/Results
GOALS
Shrimpal.id aim to help local shrimp farmer in Indonesia to prevent major losses caused by shrimp pathogen, Vibrio parahaemolyticus. This device able to detect Vibrio parahaemolyticus in relatively low cell density, establishing an early warning system for V.parahaemolyticus so further measures can be taken immediately. Our particular goal is to create a detection device that is efficient and right on target. We also want to spread biology synthetic concept, which is not very common in Indonesia, to the public to raise people’s awareness in biology synthetic as the basic concept of our device.
Wet Lab Target:
- Create and assemble DNA parts as a circuit of the detection device
- Characterize the assembled DNA by testing its ability in V.parahaemolyticus sensing and reporting
Modeling target:
- Predict the enzymatic mechanism which involved in the assembled system considering several important effecting factors
Human practice Target:
- Implement technology in a device that solve problems in shrimp ponds efficiently
- Disseminate biology synthetic concepts as broad as possible to various elements in the society
RESULTS
We started to build Shrimpal.id step by step. Once the project was finished, the conclusions reached at this following page:
Wet Lab
We have built a complete Part Collection of standardized Golden Gate and BioBricks basic parts. It is a fully functional DNA collection with their characterization of this parts.
We have purified and 16s rDNA characterized Vibrio parahaemolyticus that we used in our project. V. parahaemolyticus that we used was obtain from local isolate in Balai Perikanan Budidaya Air Payau Situbondo, Indonesia.
We already made V. parahaemolyticus standard curve to determine cell number based OD600
This standard curve used to convert the OD600 data of V.parahaemolyticus to its estimated cell numbers
Figure 1. V.parahaemolyticus standard curve
This standard curve used to convert the OD600 data of V. parahaemolyticus to its estimated cell numbers. OD600 values were measured using UV-Vis Spectrophotometer, while cell numbers were estimated using total plate count method. The OD600 values used are within the range of linearity (0,2-0,7) and the r2 value shows a good correlation between both variables. The equation obtained from the curve is shown below.
OD600 = (cell number) x 10-9 + 0,1232
We have characterize BBa_K381001 parts on Escherichia coli grown in different salinity and nitrate concentrations.
We have characterize full system integration of our composite part BBa_K3252044 on different levels of Vibrio parahaemolyticus filtered supernatant
Nitrate or nitrite has a negative correlation to the growth of Vibrio paahaemolyticus. The dynamics of ammonium, nitrate, and nitrite concentrations are complex, and so it can be difficult to interpret the multivariate associations of thesespatially - and temporally -indexed variables. Overall though, positive associations with nutrients indicates that availability of nitrogen and phosphorous provide a hospitable environment for the bacterium. Here we tried to characterize nitrate sensor ability of part BBa_K381001 that transformed into E.coli TOP10 grown in different level of salinity and here is the result :
Figure 2.Bar graphic of nitrate sensing in a range of salinity. The data shows that in a higher salinity (>10 ppt), nitrate sensing ability of the culture decrease since the higher nitrate concentration doesn’t result in higher fluorescence.
In this project we use nitrate reporter consists of sensitive promoter PyeaR with a GFP coding device and strong RBS to create nitrate-sensitive system which signal through GFP. In the normal condition, the promoter PyeaR is repressed by NsrR, a protein native to E.coli cells. But, when nitrate or nitrite enter the cell, it is converted to nitric oxide halting the repression and allowing the production of GFP.
In the previous characterization done by BCCS Bristol in iGEM 2010, this part can be used to detect nitrate in concentration range 2-100 mM. We previously predict that between this range of nitrate concentration this nitrate sensor could work well.
Figure 3. Nitrate sensing report of transformant E.coli grown in Normal-salinity LB (10 ppt)
Figure 3 shows that in a media with 10 ppt salinity, the correlation between nitrate concentration and fluorescence is considered linear (R2=0.916). In a higher nitrate concentration, the fluorescence level also raised.
Unfortunately the same correlation can’t be accomplish in salinity level higher than usual medium condition (>10 ppt). We predict that this phenomena probably caused by disruption of cell growth in a higher salt concentration. It supported by the growth curve data of E.coli grown in various media with different salinity as shown in figure 4.
Figure 4. E.coli TOP10 growth curve in various salinity. Higher salinity produce relatively lower cell density
We can see that the higher salinity level, the lower cell growth. Culture grown in 25ppt LB grew a little lower than normal LB, while the variation with 35 and 45 ppt salinity shows even lower growth. Culture grown in sea water LB probably produce a higher growth because sea water might contains lots of supporting materials for cell growth.
However, E.coli that we used still managed to grow even in a relatively higher salinity. This behaviour might caused by adaptation mechanism of cell in stress condition. One of the possible mechanism is hyperosmotic response. Hyperosmotic condition causes water loss from cytoplasm. E. coli responds to osmotic shock by increasing K+ ion influx through Trk, Kdp, and Kup uptake systems. The cell also excretes putrescine (a divalent cationic molecule), to balance out intracellular ionic strength. Glutamate synthesis follows to further balance the intracellular ionic strength. At this point, the cells’ turgor pressure are restored. The role of K+/glutamate is replaced by trehalose, a nonionic compatible solute. K+ and glutamate levels drop as trehalose level increases. Normal cell functions are restored after trehalose accumulation occurs (Moat, et al,2003).
This salinity problem actually could be handled by transforming salinity resistant plasmid into the cell, for example part BBa_K729005. This part produce IrrE protein originates from Deinococcus radiodurans that upregulate the production of several stress-responsive protein, protein kinase, metabolic protein, and detoxification protein, but we didn’t use this method because our design already used two relatively large plasmid. Transforming this other plasmid could possibly aggravate the cell’s metabolic burden.
Here we tried to characterize our new composite part
Figure 5 GFP/OD600 level in different supernatant concentrations. Higher supernataht concentration produces higher level of GFP/OD600 readings
From figure above (Fig. 5), it can be seen that the GFP/OD600 level positively correlates with the concentration of supernatant in the medium. This pattern starts to be observable after 1 hour of incubation, while at the initial incubation time (hour=0) there is no conclusive pattern observed. However, GFP/OD600 read after the first hour of incubation decreased steadily until the end of our observation time (3 hours).This is caused by the breakdown of the signal molecule, autoinducer (AI) While it is highly stable in low pH, its half-life is reduced to <3 hours in slightly alkaline condition (Leadbetter and Greenberg, 2000). The pH of salt water itself ranges from 7,5-8,5. The sample added contains no viable V. parahaemolyticus cells, hence no additional AI is produced during incubation period.
We are very proud of this finding as this shows that our system works as expected. The supernatant of Vibrio parahaemolyticus is supposed to be containing its very own autoinducer, which would be recognized by our constructed part LuxN, and induced the latter cascading process which ends up expressing green fluorescence protein. The increased GFP level along with increased supernatant level means the system works in a well manner.
These findings also indicate that the best formula for the observation is 50% filtered Vibrio parahaemolyticus supernatant, while the best time to observe the Vibrio parahaemolyticus level is after one hour of incubation. This insight would later be very meaningful in the development of the project.
HUMAN PRACTICE
WUntil now, we have achieved impressive human practices events that we held. See our page for detailed information.
CONSIDERATIONS FOR REPLICATING THE PROJECT
- Ligation reaction for parts assembly need to be optimized
- Parts composite stability: We are using two relatively large plasmids transformed into one cell that technically not easy to maintain. We recommend to increase antibiotic dosage and perform routine subculture, or using transformant cell from glycerol stock for each experiment
- To asses composite part’s ability in V.parahaemolyticus sensing and reporting, make sure the V.parahaemolyticus supernatant already filtered
- In PCR colony reactions to check the gene transformation, make sure the cells are diluted first in NFW and not too cloudy nor too clear
- Better use an automatic sampler and absorbance/fluorescence reader to check the culture, if possible
FUTURE PLANS
We have successfully constructed and cloned part composite that build our sensor device. Our future aim is to determine and increase the sensitivity of detection. We also want to evaluate biosafety and biosecurity issues that might be encountered in the actual usage.
Moreover, hopefully in the future we could design and develop integrated circuit to process the data and the software that will deliver V.parahaemolyticus level to the shrimp farmer and give suggestion on further measures
REFERENCE
- Leadbetter, Jared R. and EP Greenberg. 2000. Metabolism of acyl-homoserine lactone quorum-sensing signals by Variovorax paradoxus. Journal of Bacteriology. 182 (24): 6921-26
- Moat, A. G., Foster, J. W., & Spector, M. P. (Eds.). (2003). Microbial physiology. John Wiley & Sons. P.583-584
