iGEM 2024 — Team ais-china

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{% block title %}Notebook{% endblock %}
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Notebook

## Notebook

Notebook of our wet lab work.

## Meeting Minutes

Documentation of our weekly meetings.

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{% block title %}Engineering Success{% endblock %}
{% block lead %}Demonstrate engineering success in a technical aspect of your project by going through at least one
iteration of the engineering design cycle. This achievement should be distinct from your Contribution for Bronze.{%
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Engineering

![](https://static.igem.wiki/teams/5186/fold.png)

![](https://static.igem.wiki/teams/5186/moskilla-logo.png)

Overview

Target 1. Overproduction of HMBPP in *E. coli*

Target 2. Producing shRNA mosquitocides in yeast

Target 3. Setting kill switch in *E. coli*

Implementation

Conclusion and Discussion

Reference

## 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)

![](https://static.igem.wiki/teams/5186/engineering-success/engineering-success-figure1.png)

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*. The data are the means ± SD of three parallel replicate experiments. Statistical significance comparing conditions with and without MEP Overexpression Cassette use one-way ANOVA test. \*\*\*P< 0.0001.

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.

![](https://static.igem.wiki/teams/5186/engineering-success/engineering-success-figure2.png)

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. The data are the means ± SD of three parallel replicate experiments.

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).

![](https://static.igem.wiki/teams/5186/engineering-success/engineering-success-figure3.png)

![](https://static.igem.wiki/teams/5186/engineering-success/engineering-success-figure-4.png)

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. The data are the means ± SD of three parallel replicate experiments. Statistical significance comparing conditions with and without sRNA Expression Cassette use one-way ANOVA test. \*\*\*P< 0.0001.

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)

![](https://static.igem.wiki/teams/5186/engineering-success/engineering-success-figure-5.png)

Figure 5. Developing process of RNAi yeast mosquitocides.

In 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.

![](https://static.igem.wiki/teams/5186/engineering-success/engineering-success-figure6-new.webp)

## 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.

![](https://static.igem.wiki/teams/5186/safety/ais-china-kill-switch.png)

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. The data are the means ± SD of three parallel replicate experiments.

## 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.

![](https://static.igem.wiki/teams/5186/engineering-success/engineering-success-figure-8.png)

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**](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27hardware%27%29%20%7D%7D) 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**](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27entrepreneurship%27%29%20%7D%7D) 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**](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27sustainability%27%29%20%7D%7D)
for more).

## Reference

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   [https://doi.org/doi:10.1126/science.aah4563](https://doi.org/doi%3A10.1126/science.aah4563)
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   <https://www.mdpi.com/1420-3049/25/14/3136>
4. Zhou, J., Yang, L., Wang, C., Choi, E. S., & Kim, S. W. Enhanced performance of
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