Engineering Success
The process was, as every year, a lengthy one, and the core of our project. Our
lab team was thankfully able to enter the lab this summer and carry out a great
deal of work to validate our dry lab designs, which will be detailed below. We
are pleased to report that despite not having enough time to achieve our end
goals, we believe our project was at the very least partially successful.
Initial research
After pinpointing the problem of Carbapenem-resistance Enterobacteriaceae (CRE),
we investigated several leads we had on detection methods. Ideas such as using
bait-prey interactions between biosensors proved far too complicated to design
and using specifically engineered bacteriophages to infect CRE with genes
encoding fluorescent reporters would have proven too lengthy and expensive.
Instead, our attention was drawn to an area previously explored by both teams
and academics from our university – the use of CRISPR as a detection tool by
engineering a guide RNA (gRNA) able to sense the presence of our target gene -
known as CRISPR activation, or CRISPRa for short. As for the latter, as
mentioned on the Description page, we settled upon the detection
of a particular Carbapenemase known as OXA-48 (Fig.1). This was because its
activity is slower than other Carbapenemases, which made it more difficult to
quickly detect using available tests such as the Carba NP test – a result
requires sampling and sequencing for a positive result.
Fig. 1. The overall structure of the OXA-48 Carbapenemase. It is made up of 4 identical chains (each labelled in a different colour) which assemble to form the full protein.
Detecting DNA, however, has a chance of giving false positives as DNA can be
left over from dead bacteria after, for example, treatment of a surface with
biocides, resulting in unnecessary measures being taken. We therefore
endeavoured to detect the mRNA of OXA-48, due to its relatively short lifespan
being indicative of recently alive CPE within the sample (protein sequence
obtained from [1]).
CRISPRa
Fig. 2. Plasmid map of our ‘operator’ plasmid, encoding our cgRNAs and the CRISPRa system.
Our CRISPRa system was engineered with all the controls in mind – each component
of the circuit is thus inducible. To make this easier, we settled upon using E.
coli cells of the MG1655-Z1 line, as they contain the elements TetR, LacI and
AraC, eliminating the need to introduce them ourselves (obtained from [2]).
Instead of using a normal Cas9 protein, however, we opted to use a deactivated
variant (dCas9), which has had its nuclease function abolished – the protein
would simply stay bound to the DNA sequence indicated in the gRNA.
The gRNA we engineered to sense the presence of the OXA-48 mRNA can be extended
to create a binding domain for the RNA-binding protein MS2 without compromising
its ability to bind to dCas9. MS2 would provide a scaffold for the binding of a
fusion protein composed of MCP and the transcriptional enhancer SoxS [3] –
effectively causing the upregulation of transcription downstream of the dCas9
binding site (protospacer adjacent motif or PAM). By placing the PAM just
upstream of the promoter of our reporter, we can cause its greatly increased
production.
The gRNA – recognising two things at once
In a CRISPR system, a gRNA recognises its PAM sequence via Watson-Crick base
pairing in order to guide the Cas9 protein to its cleavage site. We added
another condition to this binding – the presence of our target mRNA – this
turned our gRNA into a conditional gRNA (cgRNA).
Fig.3. Representation of our switch in an ‘off’ state.
As seen in the above figure, the cgRNA is made up of a number of distinct
domains. In its natively folded state, the dCas9 binding handle (grey) adopts a
conformation which prevents its binding to dCas9 – the system is thus in an
‘off’ state.
Fig. 4. Representation of our switch in an ‘on’ state.
However, when the OXA-48 mRNA is present (the trigger, in purple), the two RNA
molecules anneal, causing a significant conformational change in the secondary
structure of the cgRNA, allowing it to bind dCas9 and switching the system into
its ‘on’ state, allowing the complex to bind to the PAM and activate
transcription as detalied in the CRISPRa section above.
We simulated the secondary structure of our cgRNA in its natively folded form
and when annealed to the mRNA in NUPACK, as seen in Fig. 5.
Fig. 5. (left) Diagram of the secondary structure of the cgRNA in its natively folded state. (right) Diagram of the secondary structure of the cgRNA when annealed to the target mRNA.
On the left of the figure, the dCas9 binding handle is misfolded, but the bonds
in the blocking domain, shown in blue, are not particularly stable – this is
indicative of the fact that the cgRNA can be brought out of this conformational
state. On the right of the figure, the conformation is drastically changed, and
the dCas9 binding handle (at the top in this figure) has folded correctly.
The plasmids
All of these components and more were cloned into one of two plasmids, as seen
in the schematic in Fig.6. As for reporters, we chose to keep the original sfGFP
as well as introducing a new one – a fluorescent RNA aptamer known as iSpinach;
this RNA produces a strong green fluorescent signal when combined with the
non-toxic fluorogenic compound DFHBI.
Fig. 6. Schematic diagram of the two plasmids in our system.
Above is the schematic of the helper plasmid, encoding our trigger as well as
dCas9 and a chloramphenicol resistance gene to assist with selection. Below is
the schematic of a reporter plasmid, containing the two reporters – sfGFP and
iSpinach – as well as a cgRNA, the MCP-SoxS CRISPRa system, and a kanamycin gene
to assist with selection.
The design is modular to allow for a large amount of control (Fig. 7)– the
production of the cgRNA is inducible by arabinose (1) and the production of the
trigger is inducible with anhydrotetracycline (ATC, 2), while both are required
for the activation of dCas9 (3). Only when this occurs does MCP-SoxS (4)
exercise its enhancing activity upon the sfGFP promoter (5).
Fig. 7. Schematic representation of the cgCRISPR sensing device.
Experimental layout
The flow of our experiments can be seen in the figure below - the lab work was
split into four stages: foundation, improvement, engineering, and production.
Unfortunately, due to time constraints and unforeseen circumstances brought by
supply chain issues, we were only able to assemble the first reporter plasmids
in time, reaching the first iteration cycle.
Fig. 8. Representation of our lab plan. Top to bottom: foundation phase, improvement phase, engineering phase, production phase.
We began by extracting the necessary components from existing plasmids
(PAJ-379-C1 and PAJ-390-C2 [4]) from Professor Alfonso Jaramillo’s lab at the
University of Warwick using PCR – this gave us the linearised backbones which we
would use in assembling the plasmids in the above sections. Our inserts were
provided by IDT and included the OXA-48 gene (sequence obtained from [1]). It
lacked a ribosome binding site as we did not want to proliferate Carbapenemase
resistance during our project. Other parts included the MCP-SoxS gene (sequence
obtained from [3]). We used Gibson and Goldengate assembly techniques to assemble
our helper and reporter plasmids, respectively.
Afterwards, MG1655-Z1 cells were transformed with the helper plasmid, giving
rise to the helper cell line. This cell line would be transformed with different
versions of the reporter plasmid containing different cgRNAs to screen for the
one which offered the greatest difference in fluorescence between a positive and
a negative result.
As alluded to in the diagram, as well as on our Human Practices page,
our system was designed to work in an in vitro scenario; the iSpinach aptamer
has been designed to function optimally in vitro. While we were not able to
pursue this cell-free application due to time and materiel constraints, we are
confident that a future iGEM team could validate the theoretical basis behind
this device working cell-free.
A detailed rundown and timeline of our lab work can be found on our Experiments page.
Model of gRNA function – leakage, specificity and sensitivity
In order to find out which of our designed cgRNAs was most appropriate despite a
lack of data, we prepared a mathematical model using which we tested a promising
sequence against a number of cgRNAs with mismatching spacers. The results of the
first comparison can be observed in Fig.9 below – while there is a significant
level of activation, the longer sensing loop could cause unintended activation,
which is why we followed this up by testing a sequence with a shorter sensing
loop which would give more specificity to the target sequence.
Fig.9. Graph of the results of the modelling of fluorescence over time when using a cgRNA with a longer sensing loop (green), when compared against mismatching cgRNAs (orange, grey) and a negative (blue) and positive (yellow) control.
The comparison of the other cgRNA to a mismatch using our model (Fig.10) yielded
better results, however. There is a large difference in fluorescence between the
use of the cgRNA we tested when compared against both the negative control and
against a mismatching gRNA. Moreover, over time the fluorescence appears to
approach the value exhibited by the positive control! This was, to us,
indicative of the fact that the increased specificity had no negative effect on
activation.
Fig.10. Graph of the results of the modelling of fluorescence over time when using a cgRNA with a shorter sensing loop (green), when compared against a mismatching cgRNA (grey) and a negative (blue) and positive (yellow) control.
We decided to investigate the sensitivity of this particular cgRNA as well and
simulated its activity with different ratios of cgRNA:trigger as evidenced in
Fig. 11. The results of this were satisfactory, as when compared to the absence
of the trigger, the 1:1 ratio yielded a large increase in observed fluorescence.
Fig 11. Comparison of fluorescence using the cgRNA with the shorter sensing loop at different concentrations – no trigger (orange), 1:1 cgRNA:trigger (green), 2:1 cgRNA:trigger (black), 5:1 cgRNA:trigger (grey).
As expected though, as the ratio of cgRNA to trigger increased, less activation
was observed – this raises an issue when working with low concentrations of
OXA-48 mRNA in the sample; nonetheless, we believe that this gRNA would make a
fine candidate for further development.
See the reactions and values for our model below:
References
[1] Mohammadi Bandari, N. Keyvani, H. Abootaleb, M. Klebsiella pneumoniae strain TFH21 OXA family beta-lactamase (blaOXA) gene, partial cds. Available at: https://www.ncbi.nlm.nih.gov/nucleotide/MZ275246.1 [Accessed 19/10/2021]
[2] Sekar, K. Gentile, AM. Bostick, JW. Tyo, KE. N-Terminal-Based Targeted, Inducible Protein Degradation in Escherichia coli. PLoS One. 2016 Feb 22; 11(2):e0149746. doi: 10.1371/journal.pone.0149746. eCollection 2016. PONE-D-15-42990 [pii] PubMed 26900850. Available at: https://www.addgene.org/65915/ [Accessed 20/10/2021]
[3] Dong, C. Fontana, J. Patel, A. et al. Synthetic CRISPR-Cas gene activators for transcriptional reprogramming in bacteria. Nat Commun 9, 2489 (2018). https://doi.org/10.1038/s41467-018-04901-6
[4] Gallzi, R., Duncan, J. N., Rostain, W., Quinn, C. M., Storch, M., Kushwaha, M., Jaramillo, A., Engineered RNA-interacting CRISPR Guide RNAs for Genetic Sensing and Diagnostics, The CRISPR Journal (2020), 3 (5), pp. 398-408, doi: http://doi.org/10.1089/crispr.2020.0029
