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Results: 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. 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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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