Mycobacterium tuberculosis Genes Proof of Concept Experimentation

The inhA Gene

Mycobacterium tuberculosis is a species of pathogenic bacteria that is prone to developing new AMR strains (WHO, 2023). Lambert iGEM chose to use M. tuberculosis as a proof of concept in which we demonstrate the repression of a selected critical gene in order to inhibit essential functions. Among M. tuberculosis genes, we specifically chose to target the inhA gene due to its low mutation rate and its critical role in tuberculosis pathogenicity and survival, making it an ideal proof of concept for both designing and testing our constructs.

InhA, found in M. tuberculosis, encodes the NADH-dependent enoyl-acyl carrier protein reductase responsible for synthesizing type II fatty acids (Global Tuberculosis Report 2023). These fatty acids are crucial for the lipid pathogenicity of Mycobacterium species, particularly as components of mycolic acids in the mycobacterial cell envelope, which are linked to M. tuberculosis’s virulence (Marrakchi et al., 2014). Therefore, by inhibiting mycolic acid synthesis using our CRISPRi system, we aim to disable M. tuberculosis’s pathogenicity and eliminate the bacteria without resorting to antibiotics (see Fig. 1). Without mycolic acids, the bacterial cell walls lose stability and shape, disrupting their function and inhibiting M. tuberculosis’s virulence. Our choice of a gene with low mutation rates demonstrates how our approach could efficiently target the gene with the dCas9-sgRNA complex, enhancing binding and gene downregulation in practical applications (S. Qi et al., 2013).

Figure 1. Graphic depicting the effect of the downregulation of the inhA gene on M. tuberculosis cells

PCR and PCR Cleanup

Before beginning testing with the DNA constructs provided by Integrated DNA Technologies (IDT) and TWIST Bioscience, we first utilized polymerase chain reaction (PCR) kits from Thermo Scientific then performed PCR cleanup using kits from Qiagen in order to purify our six toehold and trigger combinations (see Table 1). By using purified DNA, we were able to reduce experimental variability and acquire more consistent results (PCR Basics | Thermo Fisher Scientific).

Initial Experimentation

We then moved on to our first experiment, which aimed to characterize the six inhA toeholds designed using NUPACK at the lowest trigger concentration recommended by Dr. Megan McSweeney from Georgia Institute of Technology (McSweeney et al., 2023). By testing each toehold switch at a minimal trigger concentration, we could identify which design achieved the most GFP expression with the least input, or the most reactive toehold switch (see Table 2).

Additionally, we included the deGFP plasmid as a positive control to test the functionality of our TXTL kits, as well as a negative control for each construct containing only the toehold switch in order to test the baseline fluorescence and unfolding of each construct. Ideally, the positive control would have a very strong fluorescence signal due to production of GFP, and the negative control would have very low fluorescence when compared to the experimental groups, indicating minimal unfolding of our toeholds without a trigger present (see Fig. 2).

Figure 2. Results from initial inhA toehold control experimentation

Analysis

Results from the control reaction shows significantly higher expression rates for positive control when compared to negative control. This separation supports normal activation of our TXTL Pro Kit controls. The RFU fall off and plateau seen between 4 and 8 hours is due to an issue with our plate readers mechanics.

Toehold Characterization

After testing at the lowest trigger concentration, we decided to characterize the most efficient toehold over a large range of suggested trigger concentrations - 5 nM to 20 nM. This would allow us to determine the sensitivity of our toehold construct over a range of trigger concentrations - an important feature of a good biosensor. Experimentation was conducted with inhA toehold 5 (BBa_K5096076) using trigger (BBa_K5096045) concentrations of 10 nM, 15 nM, and 20 nM following specific volumes and concentrations (see Table 3). As in the first experiment both a positive control with the deGFP plasmid as well as a negative control were also included.

Figure 3. Characterization curve for inhA toehold 4 with 10 nM to 20 nM trigger concentration

Figure 4. Characterization curve for inhA toehold 5 with 10 nM to 20 nM trigger concentration

Figure 5. Characterization curve for inhA toehold 6 with 10 nM to 20 nM trigger concentration

Analysis

Comparison between our three toeholds and their concentration curves show that inhA toehold 5 at 1nM when supplied with 15nM of trigger DNA had significantly higher expression rate than every other construct combination (see Fig. 4). In comparison, inhA toehold’s 4 and 6 did not experience any significant activation at any trigger concentration value (see Fig. 3 and Fig. 5). Even though the expression rate of toehold 5, roughly 200 RFU, is much lower than the positive control values, the separation between toehold 5 and the other toeholds supports successful binding of toehold 5 to its complementary trigger. Lambert iGEM also decided to create a deterministic ODE model to simulate our toehold reaction (See Fig. 6) (see Modeling Toeholds).

Figure 6. Deterministic ODE model simulating our inhA toehold reaction

Modeling

Our modeling committee also utilized MATLAB, a platform that enables wetlab committees to simulate various reactions, predicting experimental success. This approach allows the wetlab committees to focus on the most optimal concentrations and configurations, streamlining our experiments and enhancing efficiency. The reciprocal relationship between the modeling and wetlab results facilitates refinement of both the mathematical predictions and experimental design, ultimately improving the accuracy of our toehold application (see Modeling Toeholds).

Conclusion

Our experimentation with the inhA gene from Mycobacterium tuberculosis has yielded promising results in our effort to combat antibiotic resistance using CRISPRi and toehold switches. We successfully characterized six toehold constructs, with inhA toehold 5 emerging as the most efficient design. This toehold demonstrated the highest GFP expression at a trigger concentration of 15 nM, indicating its potential as an effective biosensor. While the expression levels were lower than our positive control, the clear separation between toehold 5 and other constructs supports its successful binding to the complementary trigger. These findings provide a solid foundation for further development of our approach, potentially leading to new strategies for targeting critical genes in antimicrobial-resistant bacteria without relying on conventional antimicrobials. In the future we will focus on optimizing the toehold design for even greater sensitivity and exploring its application in conjunction with our CRISPRi system.

Future Considerations

Lambert iGEM’s future research directions aim to expand and work with toehold biosensors and CRISPRi systems. One of several key objectives includes optimizing our toehold constructs and finding ideal concentrations specific to each toehold. Additionally, to further validate our proof of concept we intend to produce another toehold for a different disease. We also aim to combine our CRISPRi and toehold systems in a single reaction, simulating a real-life application of our project. Due to time constraints this year, we could not test our toeholds in our own cell-free extracts, but we would like to explore this aspect in the future. Similarly, we would like to advance in vivo experimentation to more accurately model our intended implementation. This progression will require investigating effective methods for delivering our system into cells.

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