"
Team:Peking/Project/BioSensors
From 2013.igem.org
XingjiePan (Talk | contribs) |
Spring zhq (Talk | contribs) |
||
| Line 282: | Line 282: | ||
<img id="BiosensorOverviewBackground" src="https://static.igem.org/mediawiki/igem.org/7/7a/Peking2013_Biosensorsbackground_ZYH.jpg" /> | <img id="BiosensorOverviewBackground" src="https://static.igem.org/mediawiki/igem.org/7/7a/Peking2013_Biosensorsbackground_ZYH.jpg" /> | ||
<h1 id="BiosensorOverviewTitle">Biosensor</h1> | <h1 id="BiosensorOverviewTitle">Biosensor</h1> | ||
| - | <p id="BiosensorOverviewContent">A biosensor typically consists of a detector and a reporter | + | <p id="BiosensorOverviewContent">A biosensor typically consists of a detector and a reporter; the input signal activates the detector, through which the reporter is stimulated to emit the output signal. One advantage of biosensors is that the detection profile of a particular biosensor is usually limited to a few specific signals, thus to make the output of biosensors highly informative. Another advantage is the responding procedure of a biosensor: it usually involves no more than transcription and translation, both of which are automatically operated by the living cells themselves; so it is more convenient to use, compared with conventional chemical methods that rely heavily on complicated measuring devices. Additionally, originating from functional elements of natural biological systems, biosensors are subject to various tuning methods such as directed evolution, point mutagenesis or other genetic manipulations. |
</br></br> | </br></br> | ||
Bacteria living in aromatics-rich environment naturally have aromatic sensors. In Pseudomonas putida, there are XylR detecting toluene, XylS detecting benzoate, and DmpR detecting phenol. In Escherichia coli, there are HcaR detecting phenyl propionic acid, MhpR detecting 3-hydroxyl cinnamic acid and PaaX detecting phenyl acetic acid. These natural sensors function as transcriptional factors regulating expression of downstream genes that degrade aromatic compounds as alternative carbon source. we collected information concerning aromatic sensors from previous papers and focused on constructing biosensors with low basal signal, high induction ration and wide detection range to detect aromatic pollutants in environment. | Bacteria living in aromatics-rich environment naturally have aromatic sensors. In Pseudomonas putida, there are XylR detecting toluene, XylS detecting benzoate, and DmpR detecting phenol. In Escherichia coli, there are HcaR detecting phenyl propionic acid, MhpR detecting 3-hydroxyl cinnamic acid and PaaX detecting phenyl acetic acid. These natural sensors function as transcriptional factors regulating expression of downstream genes that degrade aromatic compounds as alternative carbon source. we collected information concerning aromatic sensors from previous papers and focused on constructing biosensors with low basal signal, high induction ration and wide detection range to detect aromatic pollutants in environment. | ||
Revision as of 07:19, 24 September 2013
Biosensor
A biosensor typically consists of a detector and a reporter; the input signal activates the detector, through which the reporter is stimulated to emit the output signal. One advantage of biosensors is that the detection profile of a particular biosensor is usually limited to a few specific signals, thus to make the output of biosensors highly informative. Another advantage is the responding procedure of a biosensor: it usually involves no more than transcription and translation, both of which are automatically operated by the living cells themselves; so it is more convenient to use, compared with conventional chemical methods that rely heavily on complicated measuring devices. Additionally, originating from functional elements of natural biological systems, biosensors are subject to various tuning methods such as directed evolution, point mutagenesis or other genetic manipulations. Bacteria living in aromatics-rich environment naturally have aromatic sensors. In Pseudomonas putida, there are XylR detecting toluene, XylS detecting benzoate, and DmpR detecting phenol. In Escherichia coli, there are HcaR detecting phenyl propionic acid, MhpR detecting 3-hydroxyl cinnamic acid and PaaX detecting phenyl acetic acid. These natural sensors function as transcriptional factors regulating expression of downstream genes that degrade aromatic compounds as alternative carbon source. we collected information concerning aromatic sensors from previous papers and focused on constructing biosensors with low basal signal, high induction ration and wide detection range to detect aromatic pollutants in environment. Concerning the complex consistence in environmental water samples, the orthogonality of inducers should be confirmed. Then it's possible to use several sensors to test the multi-component sample.
After obtaining these sensors’ coding sequence via PCR or synthesis, we constructed a biosensor circuit composed of two parts: (Fig 1) (1) A constitutive Pc promoter linked with sensor’s coding sequence that encodes the regulating protein; (2) The corresponding inducible promoter located in the front of RBS-sfGFP fluorescence reporter We tested fluorescence intensity to show induction ratio of each expression system when exposed to their inducers through ELIZA and flow cytometry. Naturally, the performances of these transcriptional factors are not well characterized and needs further tuning to be biosensors.
Based on the data, we selectively changed Pc and RBS strength, tuning expression intensity of these transcriptional factors and sfGFP respectively, to optimize induction behavior.(Fig 2)
Up to now, we have constructed several well-performed types of aromatic biosensors including NahR, XylS, HbpR and DmpR. (Fig 3)
The well-characterized aromatic biosensors consist a comprehensive aromatic detection toolkit. Various aromatic compounds are involved in our toolkit’s detection range. The performance of these biosensors propose a possibility for pathway coupling, complex sample analysis and further band pass circuit application.
To apply the well-characterization biosensors we built in multicomponent analysis, the nonexistence of synergistic or antagonistic effects, in another word, orthogonality, among inducers should be confirmed. We tested the orthogonality for all our fine-tuned biosensors. (please click here for further information) The result shows that within a general inducer concentration, the orthogonality of our biosensors fits the requirements of multi-components sample detection. (Fig. 4)
Fig 1. Schematic diagram of expression system The transcriptional factor (TF) is ligated with Pc promoter on low-copy backbone pSB4K5. Reporter gene sfGFP is located downstream of promoter which is regulated by corresponding TF. The backbone is high-copy pUC57 simple. The dark purple arrowhead refers to Pc promoter, while the promoter regulated by corresponding TF is shown in cyan, dark green oval stands for Ribosome Binding Site (RBS), terminator is in dark red hexagon, dark blue square represents gene coding sequence.
Fig 2. Tuning on Pc promoter and RBS intensity In order to obtain optimal induction performance, we constructed Pc promoter library, selecting J23106, J23105, J23114, J23117, J23109, J23113 and linked it with transcriptional factors. Besides, we constructed RBS library, adopting B0031, B0032, B0034 and put it upstream of reporter gene sfGFP. The arrowheads with blue gradient refer to different intensity of Pc promoter. The ovals with green gradient stand for distinct intensity of RBS.
Fig 3 well-performed aromatic biosensors and their detective range Each color in the middle ring represents the detection range of a biosensor. Structural formula with color background stands for the aromatic compounds detected by our biosensors .┝ means plug in, connecting an enzyme with existing biosensor .
Fig. 4 Summary of the orthogonality between four sensors’ inducers. The inducers between XylS and NahR, XylS and HbpR, NahR and HbpR, XylS and DmpR, NahR and DmpR, and HbpR and DmpR are all highly orthogonal.
