Difference between revisions of "Team:Munich/Targets"

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Before demonstrating if we could discriminate bacterial and viral sequences, we needed to determine if our detection circuit worked across pathogens. <i>Escherichia coli</i> 16S rRNA had been our first target, as Dr. Pardee had advised us to use the most simple and accessible  RNA sequence. For other targets, we were advised different pathogens through our series of <a class="myLink" href="/Team:Munich/HP/Gold_Integrated">interviews with experts</a>, but we could not easily access most of pathogens due to safety restrictions in our lab. We therefore looked at <i>B. subtilis</i> as a second bacterial target that shares sequence homology with <i>E. coli</i>, and we used <i>in vitro</i> transcribed RNA for viruses (Norovirus, Hepatitis C, and Q5 beta). We describe quickly the sequences chosen and then  present  our detection results.  
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Our strategy to create crRNAs, which bind both the Cas13a protein with organism specificity (crRNA Lbu does not bind Cas13a Lsh) and the target sequence with point-mutation sensitivity, is designed to allow easy prototyping of target binding sequences. Our crRNA template for transcription consists of two DNA strands sharing complementary regions that can therefore be amplified using PCR into a full double-stranded template. The non-template (NT) strand contains the T7 promoter site and the scaffold region of the transcript that will specifically bind the Cas13a. The template strand (T) contains part of the scaffold region, so that it is complementary to the NT strand, and the target binding region. In a one-batch reaction using the Klenow DNA polymerase and the T7 RNA polymerase, the two strands bind in the scaffold region, which serves as a primer for Klenow, they get amplified into a complete double stranded DNA template, and finally transcribed into our crRNA. This modular design allows a fast and cost-effective creation of crRNAs since only the pathogen specific T strand has to be newly designed and synthesized as a oligo to accommodate for new targets. This prototyping gives the opportunity to screen all kind of pathogens with our system easily. This can be combined with our software for target screening, which can be used to verify that the target strand design does not lead to off target binding in human transcriptome and microbiome.  
 
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                <p>Gel</p>
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<h3>Variety of detectable targets</h3>
 
<h3>Variety of detectable targets</h3>
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Before demonstrating if we could discriminate bacterial and viral sequences, we needed to determine if our detection circuit worked across pathogens. <i>Escherichia coli</i> 16S rRNA had been our first target, as Dr. Pardee had advised us to use the most simple and accessible  RNA sequence. For other targets, we were advised different pathogens through our series of <a class="myLink" href="/Team:Munich/HP/Gold_Integrated">interviews with experts</a>, but we could not easily access most of pathogens due to safety restrictions in our lab. We therefore looked at <i>B. subtilis</i> as a second bacterial target that shares sequence homology with <i>E. coli</i>, and we used <i>in vitro</i> transcribed RNA for viruses (Norovirus, Hepatitis C, and Q5 beta). We describe quickly the sequences chosen and then  present  our detection results.
 
<h4>Noro virus</h4>
 
<h4>Noro virus</h4>
 
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HCV is a small single stranded RNA virus of family <i>Flaviviridae</i> which is the major cause of the Hepatitis C and liver cancer. Common setting for transmission of HCV is also intra-hospital (nosocomial) transmission, when practices of hygiene and sterilization are not correctly followed in the clinic. It is estimated that 71 million people world-wide have chronic HCV infection, and there are no known vaccines<sup><a class="myLink" href="#ref_1">1</a></sup>. For our experiments, we took the 5’ UTR of the HCV virus and did <i> in vitro </i> transcription to get the target RNA and the crRNA.</p>
 
HCV is a small single stranded RNA virus of family <i>Flaviviridae</i> which is the major cause of the Hepatitis C and liver cancer. Common setting for transmission of HCV is also intra-hospital (nosocomial) transmission, when practices of hygiene and sterilization are not correctly followed in the clinic. It is estimated that 71 million people world-wide have chronic HCV infection, and there are no known vaccines<sup><a class="myLink" href="#ref_1">1</a></sup>. For our experiments, we took the 5’ UTR of the HCV virus and did <i> in vitro </i> transcription to get the target RNA and the crRNA.</p>
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<h4><i>Bacillus subtilis</i></h4>
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<h3><i>Bacillus subtilis</i></h3>
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We also focused on trying out our experiment with other bacterial RNAs and for this we chose the gram<sup/>+</sup> <i>B. subtilis</i> since it is widely used in microbiological research.  Plus, we wanted to see if one can detect the difference between the 16s rRNAs of <i>B. subtilis</i> and <i>E. coli</i>. For <i>B. subtilis</i>, we did not perform any <i>in vitro</i> transcription, rather we directly used the bacterial culture for the RNA extraction. However, we did encounter some problems possible RNase contamination from <i>in vivo</i> extracted RNA. </p>
 
We also focused on trying out our experiment with other bacterial RNAs and for this we chose the gram<sup/>+</sup> <i>B. subtilis</i> since it is widely used in microbiological research.  Plus, we wanted to see if one can detect the difference between the 16s rRNAs of <i>B. subtilis</i> and <i>E. coli</i>. For <i>B. subtilis</i>, we did not perform any <i>in vitro</i> transcription, rather we directly used the bacterial culture for the RNA extraction. However, we did encounter some problems possible RNase contamination from <i>in vivo</i> extracted RNA. </p>
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Revision as of 12:41, 1 November 2017


Results: Targets

Our strategy to create crRNAs, which bind both the Cas13a protein with organism specificity (crRNA Lbu does not bind Cas13a Lsh) and the target sequence with point-mutation sensitivity, is designed to allow easy prototyping of target binding sequences. Our crRNA template for transcription consists of two DNA strands sharing complementary regions that can therefore be amplified using PCR into a full double-stranded template. The non-template (NT) strand contains the T7 promoter site and the scaffold region of the transcript that will specifically bind the Cas13a. The template strand (T) contains part of the scaffold region, so that it is complementary to the NT strand, and the target binding region. In a one-batch reaction using the Klenow DNA polymerase and the T7 RNA polymerase, the two strands bind in the scaffold region, which serves as a primer for Klenow, they get amplified into a complete double stranded DNA template, and finally transcribed into our crRNA. This modular design allows a fast and cost-effective creation of crRNAs since only the pathogen specific T strand has to be newly designed and synthesized as a oligo to accommodate for new targets. This prototyping gives the opportunity to screen all kind of pathogens with our system easily. This can be combined with our software for target screening, which can be used to verify that the target strand design does not lead to off target binding in human transcriptome and microbiome.

Gel

Variety of detectable targets

Before demonstrating if we could discriminate bacterial and viral sequences, we needed to determine if our detection circuit worked across pathogens. Escherichia coli 16S rRNA had been our first target, as Dr. Pardee had advised us to use the most simple and accessible RNA sequence. For other targets, we were advised different pathogens through our series of interviews with experts, but we could not easily access most of pathogens due to safety restrictions in our lab. We therefore looked at B. subtilis as a second bacterial target that shares sequence homology with E. coli, and we used in vitro transcribed RNA for viruses (Norovirus, Hepatitis C, and Q5 beta). We describe quickly the sequences chosen and then present our detection results.

Noro virus

Noro virus originally called Norwalk virus, of the family Caliciviridae, is one of the major cause of viral gastroenteritis in humans and it affects patients of all age groups. It is also the cause of high rate of deaths and is associated with hospital infections, therefore it is a highly relevant pathogen to test and detect. For our experiments, we took the 5’ UTR of the Noro virus and did in vitro transcription to get the target RNA and the crRNA. The 5’ UTR of the viruses are very specific to each individual virus so this should be an ideal sequence to specifically detect and differentiate viral RNAs.

Hepatitis C virus

HCV is a small single stranded RNA virus of family Flaviviridae which is the major cause of the Hepatitis C and liver cancer. Common setting for transmission of HCV is also intra-hospital (nosocomial) transmission, when practices of hygiene and sterilization are not correctly followed in the clinic. It is estimated that 71 million people world-wide have chronic HCV infection, and there are no known vaccines1. For our experiments, we took the 5’ UTR of the HCV virus and did in vitro transcription to get the target RNA and the crRNA.

Bacillus subtilis

We also focused on trying out our experiment with other bacterial RNAs and for this we chose the gram+ B. subtilis since it is widely used in microbiological research. Plus, we wanted to see if one can detect the difference between the 16s rRNAs of B. subtilis and E. coli. For B. subtilis, we did not perform any in vitro transcription, rather we directly used the bacterial culture for the RNA extraction. However, we did encounter some problems possible RNase contamination from in vivo extracted RNA.

Detection

When we combined the target RNA from different pathogens and their matching crRNA, we systematically saw an increase of cleaved RNase Alert compared to our controls without targets (see Figure 12). It is worth noting that B. subtilis showed the worst on/off ratio for activation, which we assume to be caused by contamination from the in vivo sample treatment. The Cas13a detection circuit is effective for RNA sequences from different viruses, gram+ and gram- bacteria, proving its universality.

Orthogonality of detection

We then set out to differentiate viral sequences from bacterial sequences. Assuming the risk of sample contamination from the patient’s own bacteria is high, we decided to first use the crRNA from a virus to screen against different targets. We chose the Norovirus crRNA and looked at the activation of Cas13a under the presents of 30 nM of Norovirus, E. coli or HCV as targets (figure 13). We found that only the Norovirus target lead to a great increase in RNase Alert cleavage, and that our detection mechanism is therefore highly orthogonal and specific.

Reproducibility

The in vitro transcription, purification and quantification of crRNA and target RNA is a highly reproducible method. This procedure is standard to our host lab (Chair for the Physics of Synthetic Biological Systems, TUM) and was used by many of our team members. We can assess that the RNAs were correctly quantified with the reproducibility of the Cas13a detection, that systematically gave us the same response range. We did not have a chance to reproduce systematically our orthogonality tests, but as the sequence specificity of Cas13a was shown in other papers (Gootenberg et al.), we are confident that we can reproduce those results.

Discussion and conclusion

We found that it was quite simple to prototype a variety of targets with our crRNA template system, where the target binding region could be easily exchanged with a new primer. We found that in most cases, the Cas13a detection circuit worked reliably. However, it should be noted that we were unsuccessful at detecting the virus Q5 beta (data not shown), and that in vivo-extracted targets still bear the risk of contamination. We did not experimental test the point-mutation sensitivity of Cas13a (as this was characterized elsewhere2), nor did we optimise the target sequence within one organism. However, we developed a software that can verify the secondary structure of the crRNA and screen cross-talk between targets and crRNA, so that sequence optimisation can be done more systematically. What we achieved here is a proof-of-principle that our discrimination between viral and bacterial sequences is pathogen and simple to implement. We are confident that with the right tools for sequence-optimisation, a general scheme for discriminating between the most common bacterial and viral infections can be built. We have already shown that our readout circuit can be used to detect Norovirus without false positives from other common pathogens.