Overview
Mosquitoes transmit various diseases, causing significant global health and economic issues, yet current control methods, including the integrated method attractive targeted sugar baits (ATSBs), are not fully effective. To improve the effectivenss of traditional ATSBs in disease vector control, AIS-China 2024 intends to introduce Moskilla, a novel ATSB designed for mosquito-borne diseases. Compared to traditional sugar baits, Moskilla incorporates HMBPP-producing E. coli as the attractant for blood-feeding mosquitoes and shRNA mosquitocide delivered by inactivated dry yeast. Additionally, a kill switch has been engineered into E. coli to enhance the biosafety of Moskilla. Our Moskilla has demonstrated not only eco-friendliness and safety but also effectiveness and specificity to mosquito populations. We hope that our Moskilla can provide a promising new solution for the prevention and control of vector borne diseases.
Target 1. Overproduction of HMBPP in E. coli
In our project, HMBPP is used to attract blood-feeding mosquitoes. Since HMBPP cannot be chemically synthesized, we selected E. coli as the chasis for HMBPP production, utilizing its inherent MEP pathway, which is similar to that of Plasmodium (Emami et al., 2017; Viktoria et al., 2021). To enhance HMBPP yield, we implemented dual metabolic engineering strategies: overexpression of the upstream genes in the MEP pathway and downregulating the expression of the downstream IspH enzyme.
∙ Strategy 1. Overexpression of MEP pathway
DXS, DXR, IspD, and IspF are recognized as key rate-limiting enzymes in the MEP pathway, with DXS and DXR catalyzing the initial, rate-determining step of isoprenoid biosynthesis. The co-overexpression of DXS, IspDF with IDI in the MEP pathway has been shown to significantly amplify lycopene production by 6-fold (Zhaobao W. et al., 2020; Zhou, J. et al., 2017). Furthermore, IspG, functioning as a HMBPP synthase, is pivotal for our project's goal of enhancing HMBPP production. (Figure 1b)
To this end, we have strategically chosen DXS, DXR, IspD, IspF, and IspG to develop 4 distinct MEP overexpression cassettes (Figure 1a), aiming to identify the optimal set of rate-limiting enzymes in the MEP pathway. And the PCR and gel electrophoresis were carried out to prove the successful construction of these MEP overexpression cassettes (Figure 1c).
However, quantifying HMBPP requires LC-MS or GC-MS, equipment not currently available in our lab, making the process laborious and time-consuming. To assess the overexpression efficiency of our four cassettes, we introduced a lycopene expression cassette as reporter into the E. coli strain DH5a with these 4 cassettes, creating strains 1-4 (Figure 1a). into the E. coli strain DH5a with these 4 cassettes, creating strains 1-4 (Figure 1a).
We measured the A470/A600 ratio of these strains to analyze lycopene production per cell unit. All strains 1-4 demonstrated a notable increase in lycopene yield relative to the control strain with the reporter cassette alone. Notably, strain 3, harboring the MEP overexpression cassette 3, outperformed with a 2.03-fold enhancement in overexpression efficiency, indicating that the combination of DXS, IspG, and IspDF is the most promising candidate. (Figure 1d)
Figure 1. Using lycopene as reporter, the best MEP overexpression cassette is selected for higher yield of HMBPP. (a) Various MEP pathway overexpression cassettes expression in E. coli strain DH5a (b) Production of lycopene via the endogenous MEP pathway in E. coli. (c) Gel electrophoresis analysis of transformed MEP pathway overexpression cassettes. (d) Relative lycopene production while using various MEP Overexpression Cassettes in E. coli.
Abbreviations: G-3-P, Glyceraldehyde 3-phosphate;DXP, 1-deoxy-D-xylulose 5-phosphate; MEP, methylerythritol phosphate; CDP-ME, methylerythritol cytidyl diphosphate; CDP-ME, 4-Diphosphocytidyl-2-C-methyl-D-erythritol; CDP-MEP, 4-Diphosphocytidyl-2-C-methyl-D-erythritol 2-phosphate; MEcPP, 2-C-methyl-D-erythritol-2,4-cyclodiphosphate; HMBPP, 4-hydroxy-3-methyl-butenyl-1-diphosphate; IPP, Isopentenyl diphosphate; DMAPP, Dimethylallyl pyrophosphate; GGPP, Geranylgeranyl Diphosphate; DXS, DXP synthase; DXR, DXP reductoisomerase; IspD, CDP-ME cytidylyltransferase; IspE, CDP-ME kinase; IspF, MEC synthase; IspG, HMBPP synthase; IspH, HMBPP reductase; IDI, IPP:DMAPP isomerase; crtE, geranylgeranyl pyrophosphate synthase; crtB, phytoene synthase; crtI, phytoene dehydrogenase.
Strategy 2. Down-regulation of IspH
Another key challenge in this endeavor was regulating the expression of the ispH gene, which converts HMBPP into downstream metabolites, thereby limiting its accumulation. However, research indicated that knocking out the ispH gene entirely would lead to the death of E. coli, making it an unviable strategy for our project (Kumar et al., 2021). This necessitated an alternative approach to downregulate ispH without compromising cell viability.
To address this challenge, we employed a small RNA (sRNA)-mediated approach to repress ispH expression. Each sRNA(IspH) was engineered with a target-binding sequence that is complementary to the IspH mRNA, enabling hybridization, and a SgrS scaffold that facilitates the recruitment of the Hfq protein in E. Coli, prompting sRNA binding to ispH mRNA and expedites its degradation by RNase E (Seung Min Yoo et al., 2013). (Figure 2a)
Further, it has been revealed that the mutation in the SgrS scaffold can enhance the efficiency of sRNA-mediated gene repression (Minho Noh et al., 2019). To identify the most effective candidate for IspH downregulation, we designed 4 variants of sRNA(IspH)s, each with a specialized scaffold derived from SgrS. (Figure 2b)
PCR and gel electrophoresis verified the successful construction of these sRNA(IspH)s overexpression cassettes (Figure 2c), and growth curves demonstrated that the designed sRNA(IspH) expression did not impede bacterial growth (Figure 2d), validating the potential of our sRNA-mediated strategy.
Figure 2. 4 variants of sRNA(IspH)s are engineered in E. coli for down-regulation of IspH. (a) A graphical abstract of the molecular mechanism underlying the down-regulation of IspH expression by sRNA(IspH)s. (b) Genetic circuit and nucleotide sequences of sRNA(IspH)s expression. The green and blue sequences indicate the target-binding sequences and SgrS-S scaffold variants respectively. (c) Gel electrophoresis analysis of transformed sRNA(IspH)s expression cassettes. (d) Growth curve of control (E. coli strain DH5a) and strains expressing sRNA(IspH)s.
To determine the most effective sRNA candidate for IspH downregulation, the four sRNA(IspH) variants expression cassettes were assembled to the MEP overexpression cassette 3, containing DXS, IspG, and IspDF. The E. coli strain DH5a carrying these composite expression cassettes were then designated as sRNA1, sRNA2, sRNA3 and sRNA4, respectively. The yields of HMBPP were measured using Liquid Chromatography-Mass Spectrometry (LC-MS).
The LC-MS results for the HMBPP standard revealed a mass/charge ratio (m/z) of approximately 260.993. HMBPP was detectable in the majority of the fermentation products, with the exception of the negative control, indicating that MEP overexpression significantly enhanced HMBPP production (Figure 3).
Unexpectedly, the introduction of sRNA1(IspH), sRNA3(IspH), and sRNA4(IspH) led to reductions in HMBPP yields by 17.46%, 23.03%, and 13.80%, respectively, compared to the positive control.
However, the expression of sRNA2(IspH), with its SgrS-S 6-nts stem scaffold, achieved the most notable downregulation effect, increasing HMBPP yield by approximately 1.1-fold with the highest yield of 0.45 mM.
The superior performance of sRNA2 confirms our integrated approach, combining MEP pathway overexpression with sRNA-mediated IspH downregulation, as an effective strategy to enhance HMBPP production (Figure 4).
Figure 3. LC-MS analysis of the fermentation product of Negative control (NC), Positive control (PC) and sRNA1-4.
Notes: 1. NC indicates E. coli strain DH5a as negative control. 2. PC indicates E. coli strain DH5a with DXS, IspD, IspF, IspG overexpression cassette as positive control. 3. sRNA1-4 indicate E. coli strain DH5a with sRNA1 (IspH), sRNA2 (IspH), sRNA3 (IspH), sRNA4 (IspH) respectively while overexpressing DXS, IspD, IspF, IspG.
Figure 4. Analysis of HMBPP production when expressing various sRNA(IspH)s. (a) Standard curve of HMBPP. (b) The yield of HMBPP in NC, PC, sRNA1-4 fermentation products.
Note: The fact that the HMBPP concentration in the NC product is 0 does not imply the absence of HMBPP; rather, it suggests that its concentration is below the LC-MS instrument's detection threshold.
Target 2. Producing shRNA mosquitocides in yeast
We selected RNA interference (RNAi) technology for its specificity, safety, and sustainability in mosquito population control. Our research identified four crucial survival genes in mosquitoes: 5-HTR1, Rbfox1, Shaker, and Irx (Figure 6a). (Keshava et al., 2021; Keshava et al., 2023; Corey et al.., 2023; Keshave et al., 2021)
Targeting these genes, various short hairpin RNAs (shRNAs) were designed and performed BLAST searches of the sequences against a total RNA database, confirming their specificity to mosquitoes. The DNA oligonucleotides encoding the shRNAs were then synthesized and incorporated into the pRS426 yeast shuttle vector, positioned downstream of pTDH3 and upstream of tTDH1 for optimal expression. After constructing the shRNAs expressing cassette in S. cerevisiae CEN.PK2-1C, the yeast cells were cultivated, collected, inactivated and then freeze-dried to create RNAi-based mosquitocides, lethal to mosquitoes upon ingestion. (Figure 5)
Figure 5. Developing process of RNAi yeast mosquitocides.
TIn the end, 6 shRNAs were engineered to target mosquitoes' vital survival genes (Figure 6a, 6b). To validate the successful assembly of our shRNAs in the yeast expression cassette, PCR and electrophoresis were performed and the result corresponds to our expectation, indicating our success (Figure 6c).
In our experimental validation, mosquitoes were divided into a control group and an experimental group. The experimental group was provided with freeze-dried, inactivated yeast cells engineered to express a variety of shRNAs, including shRNA1 (5-HTR1), shRNA2 (5-HTR1), shRNA3 (5-HTR1), shRNA (Rbfox1), shRNA (Shaker), and shRNA (Irx). Over a five-day observation period, we monitored the impact of these shRNAs on mosquito survival. (Figure 6b)
Our findings revealed that while the control group exhibited a natural mortality rate of 5%, all experimental groups experienced a complete 100% mortality rate by the 3rd day after feeding. This outcome not only confirms the potency of our RNAi-based mosquitocides but also underscores their rapid effect, holding significant promise for the swift control of mosquito populations.
Figure 6. 6 variants of shRNAs targeting mosquitoes' vital survival genes are expressed in S. cerevisiae CEN. PK2-1C. (a) Mosquitoes' vital survival genes 5-HTR1, Rbfox1, Shaker, Irx are chosen to silence, encoding for serotonin receptor, RNA binding proteins, voltage-gated potassium channels and Iroquois-class homeodomain-containing proteins respectively. They involve critical functions including neural, immune, reproductive and muscular development. (b) Genetic circuit and nucleotide sequences of shRNAs expression. (c) Gel electrophoresis analysis of transformed shRNAs expression cassettes. (d, e) Survival curve of mosquitoes consuming freeze dried inactivated yeast cells expressing various shRNAs. Note: 1-6 indicates expression cassettes of shRNA1 (5-HTR1), shRNA2 (5-HTR1), shRNA3 (5-HTR1), shRNA (Rbfox1), shRNA (Shaker), respectively.
Target 3. Setting kill switch in E. coli
To address the public concerns towards biosafety, we developed a kill switch for E. coli by engineering several autolytic genes for IPTG-inducible expression: T4L, Pa-T4L, 2Pa-T4L, and X174E. Among them, Pa-T4L and 2Pa-T4L encode fusion protein of T4 phage lysozyme and 1-2 Pa peptide via a flexible GSA peptide linker. And ΦX174-E encodes a transmembrane pore-forming protein from ΦX174 bacteriophage that disrupts the host cell membrane (Figure 7a). (Jian Zha et al., 2021; Cuiping Pang et al., 2022)
After assembling these autolytic genes to IPTG-inducible expression cassette in E. coli, strains KS 1-4 were successfully constructed as it is shown in figure 7b. Based on the growth curve analysis, strains KS1-4 showed growth reduction post-induction and different kill switch designs have varying effectiveness in killing E. coli (figure 7c).
Reports suggest that T4L's lytic efficiency can be enhanced by fusing it with cell-penetrating peptides like Pa, yet the growth curves of strains KS 2, with an additional Pa peptide, were identical. Strain KS 1 with two Pa peptides, showed E. coli regaining growth, contradicting the report.
Ultimately, our tests show that ΦX174-E expression cassette (KS 4) outperforms T4L, Pa-T4L, and 2Pa-T4L, with the majority of cell lysis within one hour of induction. This makes gene E an optimal candidate for our kill switch setting.
Figure 7. Various autolytic genes expression cassettes are engineered for kill switch setting in E. coli strain DH5a. (a) Genetic circuit construction of strains KS 1-4. (b) Gel electrophoresis analysis of transformed autolytic genes expression cassettes. (c) Growth curve of control (E. coli strain DH5a) and strains KS 1-4.
Implementation
Taking practicality into account, we've crafted a hardware solution that integrates our synthetic biology products for everyday applications (Figure 8a). This includes engineered E. coli that produces HMBPP and freeze-dried yeast that expresses shRNA-based mosquitocides. With biosafety at the forefront, our E. coli is engineered with an X174E inducible expression system to prevent unintended biological release. With the successful construction of the hardware (Figure 8b), we're excited about our contribution to the iGEM community and our role in inspiring future innovations in mosquito control for community workers and synthetic biologists alike.
Figure 8. Hardware Design Schematics (a) and Prototype (b)
Conclusion and Discussion
ATSBs can significantly reduce mosquito populations, including those resistant to insecticides, by leveraging their sugar-feeding behavior against them, making it a promising method for mosquito control. However, the spread of mosquito-borne diseases by blood-sucking mosquitoes and the potential for broad-spectrum insecticides in ATSBs to harm non-target sugar-feeding beneficial insects limit their broad application. To enhance the attractiveness of ATSBs to blood-seeking mosquitoes and the specificity of the toxins to the mosquitoes, we plan to incorporate E. coli producing HMBPP and RNAi yeast mosquitocides into ATSBs, thereby creating our project, Moskilla.
Our project aims to increase HMBPP production in E. coli primarily by overexpressing the MEP pathway and downregulating the expression of the downstream gene IspH, and finally reached the highest yield of 0.45 mM of HMBPP. For the RNAi yeast mosquitocides, we have successfully used yeast to produce our designed shRNAs and demonstrated their 100% lethal effects on mosquitoes in 3 days. Additionally, to alleviate public concerns about the safety risks of using live bacteria, we have selected ΦX174-E as the most suitable autolysis gene as kill switch components.
Furthermore, we have optimized our hardware design to create a more secure bacterial storage space that reassures the public, striving to bring Moskilla into the real world (check our Hardware page for more). We are also conducting further research on how to make our project more competitive in the existing mosquito control product market (check our Entrepreneurship page for more).
By integrating innovative biotechnological approaches with environmental safety considerations, Moskilla not only promises to be a more effective mosquito control solution but also aims to minimize ecological impact. Our project's potential to reduce mosquito-borne diseases and protect non-target species highlights our commitment to creating a healthier and more sustainable world (check our Sustainability page for more).
Reference
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