Team:Uppsala University/Project
From 2012.igem.org
Sabrijamal (Talk | contribs) |
|||
Line 6: | Line 6: | ||
<div id="headlines"> | <div id="headlines"> | ||
- | <a href="#overview">Project | + | <a href="#overview">Project Overview</a> | <a href="#DNA">DNA level</a> | <a href="#antibiotic_resistance">Antibiotic resistance</a> | <a href="#translation">Translational level</a> |
</div> | </div> | ||
</div> | </div> | ||
Line 21: | Line 21: | ||
<td colspan="2"> | <td colspan="2"> | ||
<table> | <table> | ||
- | <tr><td class="subtext"><h2> | + | <tr><td class="subtext"><h2>The Problem Of Antibiotic resistance</h2></td> |
<td valign="bottom"><a id="top" href="#top">Back to top</a></td></tr> | <td valign="bottom"><a id="top" href="#top">Back to top</a></td></tr> | ||
</table> | </table> | ||
Line 29: | Line 29: | ||
<tr> | <tr> | ||
<td valign="top"> | <td valign="top"> | ||
- | <p> | + | <p>Antibiotic resistance is a major global health problem. During the last couple of decades, antibiotic resistance has become increasingly problematic, and there is no doubt that new approaches to solve this problem at a technical level are needed to alleviate the problem. |
- | <p> | + | |
- | <p> | + | The data below is taken from the european center for disease prevention and control (ECDC) and shows the proportion of resistant isolates of Klebsiella pneumoniae in the member states of the European Union from 2000 to 2010.</p> |
- | <p> | + | |
- | <p> | + | |
- | <p> | + | <table id="ptable"> |
+ | <b>Spread of Kleibsella Resistant to Aminoglycoside Transferases</b> | ||
+ | <tr> | ||
+ | <td id="ptd1"> | ||
+ | <a href="https://static.igem.org/mediawiki/2012/5/5a/Antib_2000.png"><img src="https://static.igem.org/mediawiki/2012/5/5a/Antib_2000.png" id="rnapic"></a> | ||
+ | </td> | ||
+ | <td id="ptd1"> | ||
+ | <a href="https://static.igem.org/mediawiki/2012/4/4e/Antib_2005.png"><img src="https://static.igem.org/mediawiki/2012/4/4e/Antib_2005.png" id="rnapic"></a> | ||
+ | </td> | ||
+ | <td id="ptd1"> | ||
+ | <a href="https://static.igem.org/mediawiki/2012/0/06/Antib_2010.png"><img src="https://static.igem.org/mediawiki/2012/0/06/Antib_2010.png" id="rnapic"></a> | ||
+ | </td> | ||
+ | </tr> | ||
+ | </table> | ||
+ | |||
+ | |||
+ | |||
+ | |||
+ | |||
+ | |||
+ | <p>Misuse and overuse of antibiotics are contributing factors to the severity of the problem, and it seems that we need new approaches to solve it. | ||
+ | <p>One approach to the problem is to keep developing new kinds of antibiotics, but unfortunately there is no certainty that we can keep up with the resistance development. We are fighting a never ending battle against bacterial evolution that we at the moment seem to be losing. An outside-the-box solution is to approach problem from the other way. Why don’t we try to make the bacteria sensitive to already developed antibiotics once again? This is our approach. We accomplish it by engineering silencing artificial small RNAs against the resistance genes.</p> | ||
+ | <p>The graph below shows that it is possible to artificially engineer small RNA molecules to lower the resistance of Escherichia coli against the antibiotic kanamycin.</p> | ||
+ | |||
+ | |||
+ | <table id="ptable"> | ||
+ | <b>Spread of Kleibsella Resistant to Aminoglycoside Transferases</b> | ||
+ | <tr> | ||
+ | <td id="ptd1"> | ||
+ | <a href="https://static.igem.org/mediawiki/2012/6/65/Etestfile_medium_overview.png"><img src="https://static.igem.org/mediawiki/2012/6/65/Etestfile_medium_overview.png" id="intpic"></a> | ||
+ | </td> | ||
+ | </tr> | ||
+ | </table> | ||
+ | |||
+ | <p> | ||
+ | The graph above shows that two strains of kanamycin resistant E.coli expressing two different synthetic small RNAs show significant decrease in antibiotic resistance compared to expression of a wild-type regulating small RNA.</p> | ||
+ | </td> | ||
+ | <td> | ||
+ | </td> | ||
+ | </tr> | ||
+ | |||
+ | <tr> | ||
+ | <td colspan="2"> | ||
+ | <a name="indev"></a> | ||
+ | </td> | ||
+ | </tr> | ||
+ | |||
+ | <tr> | ||
+ | <td colspan="2"> | ||
+ | <table> | ||
+ | <tr><td class="subtext"><h2>In Development</h2></td> | ||
+ | <td valign="bottom"><a id="top" href="#top">Back to top</a></td></tr> | ||
+ | </table> | ||
+ | </td> | ||
+ | </tr> | ||
+ | |||
+ | <tr> | ||
+ | <td> | ||
+ | <p>Targeting resistance with sRNAs is one approach to an alleviation of the problem with antibiotic resistance, but there are several more. It has been shown that site directed mutagenesis on certain proteins which natively repress antibiotic resistance genes can create superrepressor proteins. Another possible way to lower resistance to antibiotics is to overexpress proteins that repress DNA-repair, such as the LexA protein. It might be possible to use these proteins to repress antibiotic resistance, and this is something we are actively investigating.</p> | ||
+ | <p>Our team is investigating methods to radically increase plasmid loss rate among bacteria by inducing plasmid-cutting enzymes in the bacteria. We are using TAL Effector Nucleases, a new fusion protein originating from a plant pathogen DNA binder and a FokI DNA cleavage domain </p> | ||
+ | |||
+ | <p> | ||
+ | There might be even more creative solutions to the problem of antibiotic resistance. In a future perspective, it may be possible to with high selectivity engineer modular proteins targeting very specific sequences of DNA. Transcription activator-like effectors are modular proteins exhibiting exactly this function. We are planning an approach to use these proteins to cut specific DNA sequences with high specificity. </p> | ||
+ | |||
+ | |||
+ | |||
+ | </td> | ||
+ | <td> | ||
+ | <img src=""> | ||
+ | </td> | ||
+ | </tr> | ||
+ | |||
+ | <tr> | ||
+ | <td colspan="2"> | ||
+ | <a name="conclusion"></a> | ||
+ | </td> | ||
+ | </tr> | ||
+ | |||
+ | <tr> | ||
+ | <td colspan="2"> | ||
+ | <table> | ||
+ | <tr><td class="subtext"><h2>Conclusion</h2></td> | ||
+ | <td valign="bottom"><a id="top" href="#top">Back to top</a></td></tr> | ||
+ | </table> | ||
+ | </td> | ||
+ | </tr> | ||
+ | |||
+ | <tr> | ||
+ | <td> | ||
+ | <p>In conclusion, we have constructed several small synthetic antisense RNAs and shown that we can down-regulate resistance to kanamycin with more than 75 %. We are currently working with developing new small RNAs against other resistance genes and also combining small RNAs with targeting of gene networks described above to get a potential synergy effect when combining the different approaches. </p> | ||
+ | |||
+ | <p> | ||
+ | Our approach is fundamentally based on the idea that creative synthetic biology solutions are working means to solve global problems. Efficient cooperation with teams around the world will make the SynBio society more potent to engineer new solutions to difficult problems. This is why we also want to contribute to solving common problems other iGEM-teams have. Thus, the last approach we take to improve the common toolbox of the SynBio community is to add new characterized parts. We have constructed and characterized efficient low copy BioBrick standard vectors and added new chromoproteins. The intention is that these will be used in systems by other teams having the same vision as us; using synthetic biology as means to solve the daunting problems humanity are facing, and will be facing in the future.</p> | ||
+ | |||
</td> | </td> | ||
<td> | <td> |
Revision as of 03:00, 27 September 2012
|
|||||
Antibiotic resistance is a major global health problem. During the last couple of decades, antibiotic resistance has become increasingly problematic, and there is no doubt that new approaches to solve this problem at a technical level are needed to alleviate the problem. The data below is taken from the european center for disease prevention and control (ECDC) and shows the proportion of resistant isolates of Klebsiella pneumoniae in the member states of the European Union from 2000 to 2010. Misuse and overuse of antibiotics are contributing factors to the severity of the problem, and it seems that we need new approaches to solve it. One approach to the problem is to keep developing new kinds of antibiotics, but unfortunately there is no certainty that we can keep up with the resistance development. We are fighting a never ending battle against bacterial evolution that we at the moment seem to be losing. An outside-the-box solution is to approach problem from the other way. Why don’t we try to make the bacteria sensitive to already developed antibiotics once again? This is our approach. We accomplish it by engineering silencing artificial small RNAs against the resistance genes. The graph below shows that it is possible to artificially engineer small RNA molecules to lower the resistance of Escherichia coli against the antibiotic kanamycin. The graph above shows that two strains of kanamycin resistant E.coli expressing two different synthetic small RNAs show significant decrease in antibiotic resistance compared to expression of a wild-type regulating small RNA. |
|||||
|
|||||
Targeting resistance with sRNAs is one approach to an alleviation of the problem with antibiotic resistance, but there are several more. It has been shown that site directed mutagenesis on certain proteins which natively repress antibiotic resistance genes can create superrepressor proteins. Another possible way to lower resistance to antibiotics is to overexpress proteins that repress DNA-repair, such as the LexA protein. It might be possible to use these proteins to repress antibiotic resistance, and this is something we are actively investigating. Our team is investigating methods to radically increase plasmid loss rate among bacteria by inducing plasmid-cutting enzymes in the bacteria. We are using TAL Effector Nucleases, a new fusion protein originating from a plant pathogen DNA binder and a FokI DNA cleavage domain There might be even more creative solutions to the problem of antibiotic resistance. In a future perspective, it may be possible to with high selectivity engineer modular proteins targeting very specific sequences of DNA. Transcription activator-like effectors are modular proteins exhibiting exactly this function. We are planning an approach to use these proteins to cut specific DNA sequences with high specificity. |
|||||
|
|||||
In conclusion, we have constructed several small synthetic antisense RNAs and shown that we can down-regulate resistance to kanamycin with more than 75 %. We are currently working with developing new small RNAs against other resistance genes and also combining small RNAs with targeting of gene networks described above to get a potential synergy effect when combining the different approaches. Our approach is fundamentally based on the idea that creative synthetic biology solutions are working means to solve global problems. Efficient cooperation with teams around the world will make the SynBio society more potent to engineer new solutions to difficult problems. This is why we also want to contribute to solving common problems other iGEM-teams have. Thus, the last approach we take to improve the common toolbox of the SynBio community is to add new characterized parts. We have constructed and characterized efficient low copy BioBrick standard vectors and added new chromoproteins. The intention is that these will be used in systems by other teams having the same vision as us; using synthetic biology as means to solve the daunting problems humanity are facing, and will be facing in the future. |
|||||
|
|||||
Challenge
Background Our goal was to engineer the native sRNA spot42 to instead target the kanamycin resistance gene AAC(6’), isolated from an ESBL plasmid from an outbreak of multiresistent bacteria in a hospital in Sweden. In theory, the sRNA with its modified antisense region would Watson-crick base pair with the complementary mRNA sequence at the 5’UTR of the antibiotic resistance gene AAC(6´), blocking ribosomal binding. This would supposedly lead to an inhibition of the translation and henceforth a silencing of the antibiotic resistance gene AAC (6´). Earlier studies of how to design an artificial sRNA showed that there were unknown factors determining whether an sRNA would be effective in blocking translation or not. To find the optimal sRNA, a large randomised library of sRNAs was made to find sequences efficient enough to down regulate the antibiotic resistance with a combinatorial approach[1]. Constructing a randomized library of small RNAs The native Spot42 gene spf from E coli was cloned in a BioBrick plasmid, and placed in front of a synthetic constitutive promoter (J23101). Using this plasmid as template, primers binding to the Hfq binding region and the promoter with overhangs containing a randomized nucleotide sequence of 30 bp was designed (15 randomized nucleotides per primer). By running an inverse PCR on the plasmid with these primers and religating the mutagenized plasmids, a randomized library was created with a maximal theoretical size of 4^30 unique sRNA, only limited by the volume of the PCR reaction. In order to screen for small RNAs with an antisense region hybridizing in an silencing manner to the 5’ UTR of the antibiotic resistance gene AAC (6´), the randomized sRNAs were transformed into an E coli MG1655 strain carrying a reporter system containing the native 5´UTR of AAC(6’) followed by an additional 15 codons of the coding sequence of AAC(6’) translationally fused via a linker (J18922) to the yellow fluorescent protein SYFP2 (K864100). Since the reporter system and the sRNA library were on two different plasmids, two suitable plasmid backbones were chosen from different compatibility groups. To make the reporter system as similar to the expression levels of the natural resistance genes, a low copy origin such as pSC101 (BBa_K864001) and the sRNA library required a medium copy backbone such as p15A. Unfortunately, the low copy backbones of the pSB4X5 serie in the registry did not display the predicted behavior of a low copy plasmid, henceforth the decision to construct new plasmid backbones that could meet our requirements Read more A randomized antisense region of thirty bases resulted in an immense library of sRNAs, where the limiting factor was the transformation efficiency of or competent cells. To be able to find promising silencing sRNAs in this vast library, a Fluorescence Activated Cell Sorter (FACSAria II from BD) was used to sort out 20 000 cells that showed a downregulation of SYFP2 from a total of 10^7 cells. By using the cell sorter function on the FACS machine the amount of false postives were dramatically reduced. This is because the FACS it makes it possible to differentiate between cells with a very low fluorescence and cells that have no fluorescence at all, non-fluorescent cells were expected to might have picked up a loss of function mutations in the SYFP gene. The cells sorted based on lowered fluorescence were plated on selective agar plates and studied under UV light in order to screen for colonies containing a small RNA that had downregulated the SYFP2 gene. This was problematic due to radiative DNA-damage that was inflicted on the bacteria, and a substantial difference in cell growth was observed. This problem was resolved by switching to a Visi-Blue transilluminator, avoiding damage to the cells and also simplified future screening. Clones that showed lowered expression of SYFP2 were measured for fluorescence using flow cytometry. The fluorescence levels could be distinguished with a accuracy of just a few percent. The plasmids that contained sRNA down regulating SYFP2 were purified and transformed into DH5alpha, and then purified again to ensure pure plasmid clones free from reporter plasmids. Finally, the isolated sRNA plasmids were transformed into a new reporter strain to validate the down regulation with flow cytometry The reporter system together with the native spot42 has been sent as parts to the registry. This is to give future iGEM teams the possibility to repress any gene by replacing the RFP region with the 5´UTR of the gene of interest. |