In order to to ensure that our engineered yeast can penetrate the mucus layer and reach the stomach wall infected by Helicobacter pylori. We designed the delivery system. The construction of the whole system can be divided into two parts: one for gel encapsulation and the other for micro-motor preparation. Through five cycles of D-B-T-L, we adopted an integrated approach to merge the preparation process, enhancing its precision, integration, and scalability.
Big Cycle 1: Gel encapsulation
Using calcium alginate for gel encapsulation not only helps protect the yeast in gastric acid and facilitates its release on the stomach wall, but also allows the yeast to aggregate into a 100μm-sized structure, which is suitable for micro-motor delivery.
D-B-T-L: Feasibility of Emulsion-Internal Gelation Method
Design
After conducting literature research and some iHP work, we decided to use the emulsion-internal gelation technology for the preliminary preparation of gel microbeads.
Build
We mixed a small amount of yeast suspension with sodium alginate, and dispersed the mixture in liquid paraffin containing 1% Span 80, and emulsified it using a computer-controlled magnetic stirrer at 200 rpm to promote emulsification and calcium carbonate dispersion. Finally, acetic acid was added to initiate gel formation.
Test
The gel was observed and photographed under an optical microscope, and gel image analysis was conducted on Cellpose using a micrometer scale to obtain data such as the average diameter and morphology of the gel. By observation and counting, the average number of yeast cells encapsulated in each gel bead was determined.
Figure 1: Size distribution of the hydrogel beads. The histogram displays the frequency distribution of the hydrogel bead diameters, based on a sample of N=231 beads. The y-axis represents the count of beads within each diameter range.
However, the analysis found that the gel diameter is significantly greater than 100μm, with a large variance. Additionally, there are fewer yeast cells encapsulated, while there are more undissolved calcium carbonate particles.
Learn
The experimental results indicate that, with the emulsion-internal gelation technology, we can produce calcium alginate gels with well-preserved morphology and good mechanical properties. To better meet the requirements of our delivery system in terms of gel diameter and yeast encapsulation, we further reviewed the literature and optimized experimental parameters, including magnetic stirring speed, Span80 concentration, yeast cell suspension concentration, and the proportion of calcium carbonate added, through practical adjustments.
D-B-T-L: Optimization of Microsphere size
Design
This time, we redesigned the reagent formulation, ratios, and stirring speed in the emulsion–internal gelation method for preparing gel microspheres, and carried out multiple experiments, analyses, and optimizations.
Build
We dispersed a 1%–2% sodium alginate solution (with more concentrated yeast suspension) in liquid paraffin containing 0.5%–1% Span 80, and stirred the mixture with a computer-controlled magnetic stirrer at 250–400 rpm to promote emulsification and the dispersion of calcium carbonate. Finally, acetic acid was added to initiate the gelation process.
Test
As described in the first cycle, the gel was observed and imaged under an optical microscope, and Cellpose software was used for gel image analysis to obtain data such as the average diameter and morphology of the gels. By observation and counting, the average number of yeast cells encapsulated in each gel bead was determined.
Figure 2: Size distribution of the gel diameter. Shows the frequency distribution of the diameters for the gel sample (N=44). The y-axis represents the count of beads found within each diameter range.
It can be seen that the average diameter of the gels is close to the ideal value (100 μm) with a small variance. Observations also showed that the average number of yeast cells contained within a single gel exceeded 80.
Learn
Using the emulsion–internal gelation technique, calcium alginate gel microspheres encapsulating a considerable number of yeast cells can be obtained, with an ideal average diameter and relatively small variance. However, as a further improvement, upgrading to microfluidic technology may be a way to achieve further variance reduction and quantitative production.
Big Cycle 2: Micromotor Construction
D-B-T-L: Feasibility of Micromotor Construction via Lyophilization and Powder Spraying
Design
We designed a two-step magnesium-based microelectrode preparation method—lyophilization followed by spraying—based on literature on drug delivery. Specifically, gel microspheres are lyophilized using a vacuum freeze dryer to form fine particles, which are then fixed onto glass slides and sprayed with magnesium powder of 20 nm particle size.
Build
We contacted Dr. Tong from our university’s School of Life Sciences to borrow a vacuum freeze dryer and seek guidance for conducting the lyophilization experiments. We also reached out to several micro-nano processing companies in hopes of collaborating on the magnesium powder spraying.
Test
We used an optical microscope to observe the morphology of the lyophilized gels, evaluating their diameter and degree of adhesion.
However, the connection between the lyophilization experiments and magnesium powder spraying turned out to be less promising. Direct vacuum freeze-drying without protectants led to significant shrinkage, collapse, and adhesion of the gel microspheres, making it impossible to obtain dried gels with a diameter of 100 μm, and thus failing to meet the requirements for spraying. Moreover, the micro-nano processing companies we contacted lacked the necessary safety qualifications for storing and handling fine magnesium powders, preventing them from carrying out experiments and testing.
Learn
We also contacted a company with experience in gel lyophilization and were informed that freeze-drying of calcium alginate gels requires precise temperature control and careful selection of protectants. The setbacks in both parts of the experiment led us to reconsider the feasibility and scalability of the three-step microelectrode preparation method—emulsion–internal gelation for gel preparation, lyophilization, and magnesium powder spraying. Our discussion concluded that this approach suffers from drawbacks such as large variance in gel diameters, separated preparation steps, and numerous influencing factors.
Meanwhile, in discussions with Professor Xuan Zhang from the Department of Pharmaceutics, School of Pharmacy, we were advised to prioritize an all-liquid-phase preparation method to avoid the liquid-to-solid drying transition of the gels as much as possible.
Building on the conclusions of Big Cycle 1, we decided to explore the microfluidic method, integrating gel formation with microelectrode preparation.
D-B-T-L: Feasibility of Micromotor Construction via Microfluidic Method
Design
After reviewing the literature, we designed a “carbonate-based micromotor” powered by calcium carbonate (with calcium carbonate reacting with gastric acid to generate carbon dioxide bubbles that serve as thrust). Specifically, we prepared calcium alginate gels with nano-calcium carbonate particles on one end, encapsulating yeast to achieve an integrated fabrication. Referring to microfluidic methods for fabricating Janus structures, we collaborated with Dxfluidics to design microfluidic chip schematics for micromotor preparation.
Build
The designed microfluidic chip schematics were handed over to Dxfluidics for fabrication.
Figure 3: Design of the microfluidic chip.
Test
We contacted Engineer Shujing Wang from the Center for Quantitative Biology and, under her guidance, used microfluidic instruments and chips to attempt the fabrication of carbonate-based micromotors.
However, due to instrument limitations (specifically, the lack of an intermittent propulsion function), we were not able to successfully produce carbonate-based micromotors through the chip.
Learn
Although we did not obtain direct results in micromotor fabrication, our experimental design was affirmed by the engineer, provided that equipment limitations are not taken into account.
We now need alternative methods to verify the fabrication and functionality of the carbonate-based micromotors.
D-B-T-L: Feasibility of Micromotor Construction
Design
By connecting a syringe directly to the microfluidic tubing—without using the chip—we built a setup to simulate the junction conditions inside the chip for micromotor fabrication. With the larger tube diameter, we were no longer constrained to a 100 μm micromotor size, and instead prepared larger calcium alginate Janus structures with calcium carbonate on one end.
Build
Two syringes were filled separately with sodium alginate solution and sodium alginate solution dispersed with nano-calcium carbonate, then connected to microfluidic tubing. The parallel microfluidic tubing was positioned above a calcium chloride solution so that, upon pushing the syringes, Janus droplets were formed and solidified after dripping into the calcium chloride solution.
Test
The fabricated micromotor models were observed by the naked eye or under a stereomicroscope to estimate their diameter and evaluate the formation of the Janus structure. A 1M hydrochloric acid solution was used to simulate the gastric environment, into which the gel micromotor models were placed, and their motion was recorded on video.
Figure 4: Macroscopic simulation of carbonate-based micromotors.
The results showed that the gel micromotor models prepared using the simulated microfluidic method exhibited a well-defined Janus structure, with calcium carbonate retained on one end. Under simulated gastric pH conditions, they demonstrated good unidirectional motion capability.
Learn
Through preparation under simulated microfluidic conditions and validation in simulated gastric pH, we confirmed the feasibility of fabricating gel micromotors using the microfluidic method, as well as their motility in acidic environments. If conditions and time permit, we plan to fabricate gel micromotors of the desired size and further verify their functionality under gastric conditions with simulated mucus.
To ensure the engineered yeast remains in close proximity to Helicobacter pylori, we designed the adhesion system. Through three cycles of D-B-T-L, we constructed the system and successfully validated the feasibility of the entire setup.
D-B-T-L: Feasibility of Cell Wall Fusion Protein Expression
We use Sed1, a cell wall anchoring protein, as a tool to anchor target proteins to the yeast cell wall. To verify the anchoring function of Sed1, we first designed an EGFP-Sed1 fusion protein to characterize the feasibility of expressing Sed1 fusion proteins on the cell wall and established an experimental method for extracting cell wall fusion proteins.
Design
We designed an expression plasmid for the EGFP-Sed1 fusion protein, using the GAL1,10 promoter for induced expression, and added a 6xHis tag at the C-terminus for subsequent purification and detection. EGFP, as a reporter protein, allows for the characterization of the expression level and anchoring effect of the fusion protein through changes in fluorescence intensity.
Figure 1: PCR verification of positive clones and recombinant plasmid for EGFP-Sed1 construct. Lanes 2-4: Colony PCR products from single clones, showing the expected ~600 bp fragment. Lanes 5-7: PCR products from the corresponding purified plasmids, confirming the successful construction of the pESC-URA-pOpM-EGFP-Sed1 plasmid.
Build
Using a yeast competent cell preparation kit, we prepared yeast competent cells by chemical method, transformed the plasmid into yeast cells, and then cultured them on the corresponding nutrient-deficient medium to obtain positive transformants.
Figure 2: Transformation results.
Test
We cultured the transformants overnight in SD-URA medium containing 2% glucose, and then transferred the cells to SC-URA medium containing 2% galactose for induced expression. We took samples at 0h, 1h, 2h, 3h, 4h, 6h, 12h, 16h, 20h, and 24h after induction and measured the fluorescence intensity of the cells using a microplate reader to evaluate the expression level of the EGFP-Sed1 fusion protein. The results showed that as the induction time increased, the fluorescence intensity of the cells gradually increased, indicating that the EGFP-Sed1 fusion protein was successfully expressed and anchored to the cell wall, and the expression level showed a clear time gradient.
Figure 3: EGFP fluorescence intensity vs. time.
To further verify whether the EGFP-Sed1 fusion protein was successfully anchored to the cell wall, we used a cell wall protein extraction method. We used Lyticase to specifically hydrolyze the cell wall to specifically extract cell wall proteins while avoiding interference from intracellular proteins.
Due to the action of Lyticase, the EGFP we extracted was only a fragment, but the experimental results still indicated that the EGFP-Sed1 fusion protein was successfully expressed and anchored to the cell wall, and the expression level showed a clear time gradient.
We performed purification verification on the extracted cell wall proteins, using IDA-Ni magnetic beads to separate the target protein with a His tag. We also performed SDS-PAGE and Western Blot verification on both the total protein and the purified protein. The results showed clear protein fragment bands, further verifying the successful expression and anchoring of the EGFP-Sed1 fusion protein.
Figure 4: SDS-PAGE results of extracted and purified cell wall EGFP-Sed1 protein.
Further Western Blot verification using an Anti-His antibody strongly supported our design hypothesis with the specific antigen-antibody interaction, proving the successful expression and anchoring of the EGFP-Sed1 fusion protein.
Figure 5: Western blot results of extracted and purified cell wall EGFP-Sed1 protein.
Learn
Through the above experiments, we successfully verified the expression and anchoring function of the EGFP-Sed1 fusion protein in yeast cells and established effective methods for cell wall protein expression and verification. The time-gradient change in fluorescence intensity and the results of SDS-PAGE and Western Blot all support our design hypothesis. This result provides a solid foundation for our subsequent use of Sed1 to anchor other target proteins (hCEACAM1ND), further advancing our understanding and application of the cell wall fusion protein expression system.
D-B-T-L: Feasibility of hCEACAM1ND-Sed1 (C1ND) Fusion Protein Expression
After successfully verifying the expression and anchoring function of the EGFP-Sed1 fusion protein, we further designed and verified the expression of the hCEACAM1ND-Sed1 fusion protein to achieve the specific application of the cell wall anchoring function in our project.
Design
Following the design idea of EGFP-Sed1, we designed the expression plasmid for the C1ND-Sed1 fusion protein, also using the GAL1,10 promoter for induced expression, and added a 6xHis tag at the C-terminus for subsequent purification and detection. As the target protein in our project, the successful expression and anchoring of C1ND are of great significance for achieving cell wall functionalization.
Figure 6: PCR verification of C1ND gene cloning and plasmid construction. Lanes 2-4: Colony PCR products from monoclonal yeasts, showing the expected insert fragment. Lanes 5-7: PCR products amplified from the corresponding purified recombinant plasmids (pESC-URA-pOpM-C1ND-Sed1), confirming the successful cloning of the HopQ gene. The DNA molecular weight marker (lane 1) is used for fragment size determination.
Build
Using the same method as for EGFP-Sed1, we prepared yeast competent cells, transformed the C1ND-Sed1 plasmid into yeast cells, and then cultured them on the corresponding nutrient-deficient medium to obtain positive transformants.
Figure 7: Transformation results.
Test
We used the induced expression and cell wall protein extraction methods established in the EGFP-Sed1 experiment to verify the expression of the C1ND-Sed1 fusion protein. We cultured the transformants overnight in SD-URA medium containing 2% glucose, and then transferred the cells to SC-URA medium containing 2% galactose for induced expression.
We took samples at different time points after induction and extracted cell wall proteins using the previously established Lyticase method. We also used IDA-Ni magnetic beads to separate the target protein with a His tag. Subsequently, we performed SDS-PAGE and Western Blot verification on both the total protein and the purified protein. The results obtained all indicated that we successfully expressed the C1ND-Sed1 fusion protein on the yeast cell wall, and the expression level showed a clear time gradient.
Figure 8: SDS-PAGE results of extracted and purified cell wall C1ND-Sed1 protein.
Figure 9: Western blot results of extracted and purified cell wall C1ND-Sed1 protein.
Learn
Through the above experiments, we successfully verified the expression and anchoring function of the C1ND-Sed1 fusion protein in yeast cells. The results of SDS-PAGE and Western Blot both support our design hypothesis, proving the successful expression and anchoring of the C1ND-Sed1 fusion protein. This result not only verifies the feasibility of our design but also provides a solid foundation for our subsequent experiments, advancing our understanding and application of the cell wall fusion protein expression system.
D-B-T-L: Recombinant Expression and Purification of Target Molecule HopQ
To verify the function of the C1ND-Sed1 fusion protein, we chose its target molecule, HopQ. HopQ is an important adhesion protein on the surface of H. pylori that can bind to hCEACAM1ND. To conduct subsequent binding capacity verification experiments, we first need to recombinantly express and purify the HopQ protein in E. coli.
Design
We designed the expression plasmid for HopQ, using the lac promoter for induced expression, and added a 6xHis tag at the C-terminus for subsequent purification and detection.
Figure 10: PCR verification of HopQ gene cloning and plasmid construction. Lanes 2-4: Colony PCR products from monoclonal yeasts, showing the expected insert fragment. Lanes 5-7: PCR products amplified from the corresponding purified recombinant plasmids (pET-15b-HopQAD-FLAG), confirming the successful cloning of the HopQ gene. The DNA molecular weight marker (lane 1) is used for fragment size determination.
Build
We transformed the HopQ expression plasmid into E. coli BL21(DE3) competent cells and then cultured them on LB medium containing ampicillin to obtain positive transformants.
Figure 11:Transformation results.
Test
We cultured the transformants overnight in LB medium containing ampicillin, and then transferred the cells to new LB medium for induced expression. We used IPTG as an inducer and took samples at different time points and different IPTG concentrations to verify the expression of the HopQ protein using SDS-PAGE and Western Blot. The results showed that the HopQ protein was successfully expressed, and clear protein bands could be detected at different time points after induction.
Figure 12: Time gradient of HopQ protein expression.
Figure 13: IPTG gradient of HopQ protein expression.
Figure 14: Western blot results of HopQ protein expression (time gradient).
Figure 15: Western blot results of HopQ protein expression (IPTG gradient).
Learn
Through the above experiments, we successfully achieved the recombinant expression of the HopQ protein in E. coli and obtained the optimal parameters for recombinant protein expression (0.5mM IPTG, 16h, 25°C). From this, we further obtained a large amount of high-purity recombinant HopQ protein, providing a solid foundation for subsequent binding capacity verification experiments.
D-B-T-L: Establishing a Modified Immunocytofluorescence (ICF) Assay to Verify the Binding Capacity of hCEACAM1ND-Sed1 (C1ND) Fusion Protein with the Adhesion Target Protein HopQ
After successfully verifying the expression and anchoring function of the C1ND-Sed1 fusion protein, we further designed and established a Modified Immunocytofluorescence (ICF) Assay to verify the binding capacity of the C1ND-Sed1 fusion protein with its adhesion target protein HopQ. This experiment is of great significance for evaluating the function of our designed cell wall fusion protein in practical applications.
Design
We designed a Modified Immunocytofluorescence (ICF) Assay, using the HopQ protein as an intermediate molecule for fluorescent staining to characterize the protein-protein binding capacity through fluorescent signals.
Specifically, we first incubated the yeast cells expressing the C1ND-Sed1 fusion protein with purified HopQ protein, allowing HopQ to bind to C1ND-Sed1. Subsequently, we used an Anti-His antibody to recognize the HopQ protein and detected it with a fluorescently labeled secondary antibody. By observing the fluorescent signal of the cells under a fluorescence microscope, we can evaluate the binding capacity of C1ND-Sed1 and HopQ.
We also designed multiple control groups, including wild-type yeast cells that do not express C1ND-Sed1 and experimental groups without the addition of HopQ protein, to ensure the reliability and specificity of the experimental results.
| Blank Control | Background Control | Background Control | Experimental Group |
|---|
| Yeast Cells | C1ND- | C1ND- | C1ND+ | C1ND+ |
| HopQ Protein | HopQ- | HopQ+ | HopQ- | HopQ+ |
Build
According to the design plan, we prepared yeast cells expressing the C1ND-Sed1 fusion protein and purified the HopQ protein. Subsequently, we incubated different yeast cells with the HopQ protein to ensure a sufficient binding reaction. Then, we performed the primary antibody incubation with the Anti-His antibody, followed by the secondary antibody incubation with a fluorescently labeled secondary antibody. Finally, we observed and captured the fluorescent signals of the cells using a fluorescence microscope.
Test
We observed the cell fluorescence signals of different experimental groups under a fluorescence microscope. The results showed that in the experimental group (C1ND +, HopQ +), a clear fluorescent signal appeared on the surface of the yeast cells, indicating that the C1ND-Sed1 fusion protein successfully bound to HopQ. In the blank control group (C1ND -, HopQ -) and the background control group (C1ND -, HopQ +), almost no fluorescent signal was detected, indicating that the experimental results have good specificity and reliability.
Figure 16: Modified Immunocytofluorescence (ICF) Assay Results. The first column (Fig A,D,G,J) shows results in CFW channel, locating yeast cell walls; the second column (Fig B,E,H,K) shows results in Cy3 channel, locating HopQ receptor protein; the third column (Fig C,F,I,L) shows merged images of the first two columns. The first row (Fig A-C) is the experimental group (C1ND +, HopQ +); the second and third rows (Fig D-I) is the background control group (C1ND-, HopQ+; C1ND+, HopQ- ); the fourth row (Fig J-L) is the blank group (C1ND-, HopQ-).
Learn
We successfully established a Modified Immunocytofluorescence (ICF) Assay to determine the binding capacity of C1ND-Sed1 and HopQ. The experimental results show that the C1ND-Sed1 fusion protein can effectively bind to HopQ, verifying the function of the adhesion system and supporting the function of our designed cell wall fusion protein in practical applications. This result not only supports our design hypothesis but also provides an important experimental basis for our subsequent research, advancing our understanding and application of cell wall fusion protein functionalization.
To achieve specific treatment, we engineered a group of the GPCR receptors to specifically sense the H. pylori biomarker N-α-methylhistamine, and induce the secretion of the downstream AiiA protein. The development of the entire system could be demonstrated as two engineering big cycles: Yeast Knockout, Sensory System Construction and Validation.
Big Cycle 1: Yeast Knockout
We designed knockouts of the STE2 and SST2 genes in the mating pathway of Saccharomyces cerevisiae STE2 encodes the native GPCR receptor, while SST2 encodes an RGS protein that attenuates GPCR signaling. Deletion of both genes benefits the enhancement of synthetic pathway sensitivity and specificity.
D-B-T-L: Construction of pML104-KanMx4 Plasmid via In-Fusion Cloning
Design
Based on a literature review, pML104 is established as a single-plasmid system vector for CRISPR-Cas9 genome editing in S. cerevisiae.
gene, and it utilizes the URA3 gene as the selectable marker in yeast1.
We have designed a double-stranded DNA construct that serves as the template to transcribe
sgRNAs targeting Ste2 and Sst2 of Saccharomyces cerevisiae for improving the efficiency of mating pathway engineering2.
To avoid issues of redundant selection marker during the final design of the system plasmid ,
we opted to replace the URA3 marker with the KanMx4 gene.
Build
The pML104-KanMx4 plasmid was constructed using In-Fusion cloning. The pML104 vector was linearized using the primers KanVec-F and KanVec-R, and the KanMx4 gene fragment was amplified with the primers KanMx4-F and KanMx4-R. The linearized vector and KanMx4 fragment were then assembled via In-Fusion cloning.
Test
During the assembly process, we attempted to obtain the final linearized pML104 vector through PCR amplification, agarose gel electrophoresis, and gel extraction. The electrophoresis results of the PCR products obtained using the corresponding primer pairs are shown in the figure.
Figure 1: Electrophoresis results of the PCR products of pML104 obtained using the primers KanVec-F and KanVec-R.
However, no distinct DNA band was observed, and thus gel extraction could not be performed.
Learn
This result demonstrates that the current linearization method for the pML104 plasmid was unsuccessful. According to literature reports, the amplification efficiency and fidelity decrease markedly with increasing template length, particularly beyond 10 kb3.
We therefore hypothesize that the failure is primarily attributable to the large size of the pML104 plasmid (11,240 bp), which significantly reduces PCR efficiency and prevents the generation of a clear target band.
D-B-T-L: Optimization of Knock-out Plasmid Construction
Design
To address the issue identified in the previous cycle, we redesigned two pairs of primers to obtain two linearized fragments of the pML104 vector, thereby reducing the error rate in PCR step. We further streamlined the plasmid construction process by integrating the replacement of the selection marker and the insertion of the sgRNA sequence into a single In-Fusion cloning step.
Since two target genes were intended for knockout, we optimized the design to improve editing efficiency by incorporating two sgRNAs into a single transcriptional cassette, thereby constructing a plasmid capable of simultaneously disrupting both genes.
Build
We first used two pairs of primers to amplify two linearized fragments of the pML104 vector, designated as pML_p1 and pML_p2. These fragments were then assembled with the KanMX4 gene fragment and the sgRNA transcriptional cassette in a one-step In-Fusion cloning reaction.
Figure 2: Synthesizing schematic of knock-out plasmid.
Test
During the assembly process, we attempted to obtain the fragments pML_p1 and pML_p2 through PCR amplification, agarose gel electrophoresis, and gel extraction. The resulting plasmid was subsequently transformed into E. coli (DH5α) to obtain transformants. Subsequent sequencing results further confirmed the successful construction of the plasmid.
Figure 3: Knockout plasmid successfully transform into E. coli(DH5α).
Figure 4: Sequencing result.
Finally, the successfully constructed plasmid was transformed into S. cerevisiae.
Figure 5: Knockout plasmid successfully transform into S. cerevisiae.
Learn
Based on these results, we validated the feasibility of employing a segmented PCR followed by In-Fusion assembly for large plasmids. Moreover, we established a more efficient one-step In-Fusion cloning strategy for constructing knockout plasmids. These findings provide valuable insights for the subsequent construction of other plasmids within our sensing system.
Big Cycle 2: Sensory System Construction and Validation
Since almost no engineered yeast GPCR capable of recognizing N-α-methylhistamine has been reported to date, we designed two potential strategies for constructing the sensing system. The first approach was inspired by the work of Schulz et al. (2022)4, in which A chimeric GPCR design strategy was built to enable receptor function without altering the native G-protein complex. The second approach was inspired by Scott et al. (2021)5, aiming to modify the G-protein so that the human GPCR receptors can function effectively in S. cerevisiae.
D-B-T-L: Sensory System Plasmid Construction
Design
According to the two design strategies, we constructed a total of eleven plasmids.
In addition, through literature research, we identified a previously constructed yeast GPCR receptor capable of recognizing N-α-methylhistamine. Accordingly, we designed and constructed the plasmid hH3R-P2A-Gpa1-pESC-HIS, aiming to reproduce the reported results. Furthermore, to assist in validating our sensing system, we referred to iGEM 2022 NEU_CHINA Parts and constructed the P2Y2-P2A-Gpa1-pESC-HIS plasmid based on the eATP sensing mechanism. Finally, to verify proper protein expression, we also designed the hH3R-P2A-mCherry-pESC-HIS plasmid incorporating a fluorescent reporter gene.
In summary, our sensing system involves the construction of 14 plasmids, forming a total of 19 sensing systems for screening and functional verification.
Build
The synthesis schematic of our sensory system plasmids construction and synthesis is shown below:
Figure 6: Synthesizing schematic of modified vectors.
Figure 7: Synthesizing schematic of chimeric GPCRs.
Figure 8: Synthesizing schematic of G protein.
Figure 9: Synthesizing schematic adapted human GPCRs.
All plasmids were assembled using the In-Fusion cloning method.
Test
According to the synthesis schematic, all plasmids were successfully constructed and transformed into E. coli (DH5α) to obtain transformants. Subsequent sequencing results confirmed the successful construction of 11 out of the 14 designed plasmids. These 11 verified plasmids were then transformed into S. cerevisiae strains with STE2 and SST2 deletions, preparing for functional validation experiments.
Figure 10: Transformation of sensory system plasmid into E. coil DH5α.
Figure 11: Transformation of sensory system plasmid into S. cerevisiae.
Learn
Based on the sequencing results, we successfully constructed 10 out of the 14 designed plasmids and achieved successful transformation of 8 designed sensing systems into S. cerevisiae strains with STE2 and SST2 deletions. These results demonstrate the feasibility of our plasmid construction strategy and provide a solid foundation for subsequent functional validation experiments of the sensing systems. Due to the time limitation of the iGEM, we were unable to reconstruct the plasmids that failed sequencing; however, in future work, we aim to further optimize our construction workflow to improve accuracy and complete the screening of all designed sensing systems.
D-B-T-L: Function Validation
Design
To verify whether the sensory system responds to the Helicobacter pylori biomarker N-α-methylhistamine, we selected mCherry as the downstream reporter gene. We aimed to assess the functionality of the sensory system. Fluorescence intensity of the yeast culture was measured at different time points after adding the sample.
Build
In our experiment, yeast cultures reaching a specific OD value were treated and added to black opaque microplates. Different concentrations of histamine and ATP gradient solutions were then added to each well. We measured the fluorescence intensity using a microplate reader at the specific time intervals throughout the incubation. Finally, we plotted the fluorescence intensity vs. time curves and analyzed the overall functionality of the sensory system.
Test
We carried out the experiments with the sample addition details outlined in Table below:
Table: 96-Well Plate Sample Addition Layout
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 |
|---|
| A | hH1R×FG
600nM histamine | hH1R×FG
600nM histamine | hH1R×FG
600nM histamine | hH2R×FG
600nM histamine | hH2R×FG
600nM histamine | hH2R×FG
600nM histamine | hH3R×FG
600nM histamine | hH3R×FG
600nM histamine | hH3R×FG
600nM histamine | hH4R×FG
600nM histamine | hH4R×FG
600nM histamine | hH4R×FG
600nM histamine |
| B | hH1R×FG
120nM histamine | hH1R×FG
120nM histamine | hH1R×FG
120nM histamine | hH2R×FG
120nM histamine | hH2R×FG
120nM histamine | hH2R×FG
120nM histamine | hH3R×FG
120nM histamine | hH3R×FG
120nM histamine | hH3R×FG
120nM histamine | hH4R×FG
120nM histamine | hH4R×FG
120nM histamine | hH4R×FG
120nM histamine |
| C | hH1R×FG
30nM histamine | hH1R×FG
30nM histamine | hH1R×FG
30nM histamine | hH2R×FG
30nM histamine | hH2R×FG
30nM histamine | hH2R×FG
30nM histamine | hH3R×FG
30nM histamine | hH3R×FG
30nM histamine | hH3R×FG
30nM histamine | hH4R×FG
30nM histamine | hH4R×FG
30nM histamine | hH4R×FG
30nM histamine |
| D | hH1R×FG
BLANK | hH1R×FG
BLANK | hH1R×FG
BLANK | hH2R×FG
BLANK | hH2R×FG
BLANK | hH2R×FG
BLANK | hH3R×FG
BLANK | hH3R×FG
BLANK | hH3R×FG
BLANK | hH4R×FG
BLANK | hH4R×FG
BLANK | hH4R×FG
BLANK |
| E | P2Y2×FG
7.5mM dATP | P2Y2×FG
7.5mM dATP | P2Y2×FG
7.5mM dATP | P2Y2×Blank
BLANK | P2mC×FG
BLANK | P2mC×Blank
BLANK | CH2R×FG
600nM histamine | CH2R×FG
600nM histamine | CH2R×FG
600nM histamine | P2pG×FG
600nM histamine | P2pG×FG
600nM histamine | P2pG×FG
600nM histamine |
| F | P2Y2×FG
3.75mM dATP | P2Y2×FG
3.75mM dATP | P2Y2×FG
3.75mM dATP | P2Y2×Blank
BLANK | P2mC×FG
BLANK | P2mC×Blank
BLANK | CH2R×FG
120nM histamin | CH2R×FG
120nM histamin | CH2R×FG
120nM histamin | P2pG×FG
120nM histamin | P2pG×FG
120nM histamin | P2pG×FG
120nM histamin |
| G | P2Y2×FG
1.875mM dATP | P2Y2×FG
1.875mM dATP | P2Y2×FG
1.875mM dATP | P2Y2×Blank
BLANK | P2mC×FG
BLANK | P2mC×Blank
BLANK | CH2R×FG
30nM histamine | CH2R×FG
30nM histamine | CH2R×FG
30nM histamine | P2pG×FG
30nM histamine | P2pG×FG
30nM histamine | P2pG×FG
30nM histamine |
| H | P2Y2×FG
BLANK | P2Y2×FG
BLANK | P2Y2×FG
BLANK | - | - | - | CH2R×FG
BLANK | CH2R×FG
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The fluorescence intensity versus time curves, as shown in the figure, were plotted based on measurements obtained using the microplate reader.
Figure 12: Fluorescence intensity versus time curves.
Analysis of the results indicates that the constructed sensing system did not demonstrate significant responsiveness to concentration or temporal gradients.
Learn
From the results, it was observed that the tested sensing systems did not exhibit the expected functionality. Based on our analysis, we propose the following possible reasons and future avenues for improvement:
First, we speculate that our knockout plasmids may have failed to achieve deletion of the two target proteins, which could have significantly impaired the functionality of the newly introduced system. In future work, the yeast knockout system could be further optimized, and whole-genome sequencing of yeast can be employed to confirm the knockout status.
Second, we hypothesize that the GPCR proteins encoded by the introduced plasmids may not fold correctly in yeast. Moving forward, plasmid design can be refined, and additional experiments can be conducted to verify protein expression and structural integrity.
Reference
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Laughery MF, Hunter T, Brown A, et al. New vectors for simple and streamlined CRISPR-Cas9 genome editing in Saccharomyces cerevisiae. Yeast. 2015;32(12):711-720. doi:10.1002/yea.3098 ↖
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Zhang Y, Wang J, Wang Z, et al. A gRNA-tRNA array for CRISPR-Cas9 based rapid multiplexed genome editing in Saccharomyces cerevisiae. Nat Commun. 2019;10(1):1053. Published 2019 Mar 5. doi:10.1038/s41467-019-09005-3 ↖
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Potapov V, Ong JL. Examining Sources of Error in PCR by Single-Molecule Sequencing. PLoS One. 2017;12(1):e0169774. Published 2017 Jan 6. doi:10.1371/journal.pone.0169774 ↖
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Schulz R, Korkut-Demirbaş M, Venturino A, Colombo G, Siegert S. Chimeric GPCRs mimic distinct signaling pathways and modulate microglia responses. Nat Commun. 2022;13(1):4728. Published 2022 Aug 15. doi:10.1038/s41467-022-32390-1 ↖
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Scott BM, Gutiérrez-Vázquez C, Sanmarco LM, et al. Self-tunable engineered yeast probiotics for the treatment of inflammatory bowel disease.Nat Med. 2021;27(7):1212-1222. doi:10.1038/s41591-021-01390-x ↖
Our therapy system is designed to employ the secretion of the AiiA protein to degrade the biofilm of Helicobacter pylori and attenuate its virulence. Through two cycles of D-B-T-L, we successfully demonstrated the feasibility of the therapy system.
D-B-T-L: Establishing a Crystal Violet Staining Assay for Biofilm Growth on Pseudomonas aeruginosa
Due to the limitations of the iGEM competition, we were unable to directly experiment with the pathogenic Helicobacter pylori. Considering that biofilm formation is the most important factor in H. pylori’s pathogenicity and drug resistance, we selected Pseudomonas aeruginosa, which also produces biofilms, as an experimental substitute. To this end, we established a crystal violet staining assay to measure the biofilm growth of P. aeruginosa, to characterize its biofilm growth, and hopefully to provide a basis for further measurement of the therapeutic function of the treatment system.
Design
We designed a P. aeruginosa culture system in a 96-well plate. Under the same culture conditions, samples were taken at different culture times to record the growth of P. aeruginosa biofilm during the culture process.
After washing the plates with a uniform plate washing method, we stained the 96-well plates from which the suspended bacteria had been washed with 0.1% crystal violet to specifically obtain the biofilm signal. Then, after washing off the floating color, we thoroughly dried the 96-well plate, and then used a 30% acetic acid solution to wash off the crystal violet dye for quantitative analysis using a microplate reader.
Build
According to the above design, we added 50 μL of M63 medium inoculated with P. aeruginosa to each experimental well of the 96-well plate, and divided them into three groups, to which we added 50 μL of empty M63 medium, M63 dilution of Saccharomyces cerevisiae, and M63 dilution of Saccharomyces boulardii, respectively, and cultured at 37°C. We took samples at 7, 12, 16, 20, and 24 hours, and measured the biofilm formation using the 0.1% crystal violet staining method.
Figure 1: Expected results of crystal violet staining assay for biofilm growth on P. aeruginosa[1](#ref1)
Test
We used a microplate reader to measure the formation of P. aeruginosa biofilm in different treatment groups at different time points. The results are shown in the figure below:
Figure 2: Growth curve of P. aeruginosa biofilm formation.
Learn
Through the above experiments, we successfully established a crystal violet staining assay for biofilm on P. aeruginosa and obtained the biofilm formation of P. aeruginosa at different time points. The results showed that with the extension of culture time, the biofilm formation of P. aeruginosa gradually increased and reached the highest value at 24 hours. In addition, we also observed the effects of different treatment groups on biofilm formation. The addition of S. cerevisiae and S. boulardii inhibited the formation of P. aeruginosa biofilm. This result provides an important basis for us to further verify the effectiveness of the treatment system. At the same time, we expect that the results obtained with P. aeruginosa as an experimental substitute can also be verified on H. pylori.
Furthermore, we hope to use the previously established crystal violet staining assay to verify the inhibitory effect of the AiiA protein in our treatment system on the biofilm formation of P. aeruginosa, in the hope of providing a basis for further verifying the effectiveness of the treatment system.
Design
We designed a similar 96-well plate culture system, but only measured the biofilm formation after 24 hours of culture. We added 50 μL of M63 medium inoculated with P. aeruginosa to each experimental well of the 96-well plate, and divided them into five groups, to which we added 50 μL of empty M63 medium, M63 dilution with 1 μg/μL AiiA protein, M63 dilution with 2 μg/μL AiiA protein, M63 dilution with 5 μg/μL AiiA protein, and M63 dilution with 10 μg/μL AiiA protein, respectively, and cultured at 37°C for 24 hours. Then, the biofilm formation was measured by 0.1% crystal violet staining.
Build
According to the above design, we added the corresponding solution to each experimental well of the 96-well plate and placed it in a constant temperature incubator for continuous 24-hour constant temperature culture at 37°C.
Test
We used a microplate reader to measure the formation of P. aeruginosa biofilm in different treatment groups. The results are shown in the figure below:
Figure 3: Inhibitory effect of AiiA protein on biofilm formation of P. aeruginosa.
Learn
Through the above experiments, we verified the inhibitory effect of AiiA protein on the biofilm formation of P. aeruginosa. The results showed that in the presence of AiiA protein, the biofilm formation of P. aeruginosa was significantly reduced. This finding indicates that the AiiA protein can effectively interfere with the formation of P. aeruginosa biofilm. This result not only supports the design concept of our treatment system, but also provides a strong basis for verifying the efficacy of AiiA protein on H. pylori in the future.
Reference
- O’Toole GA. Microtiter dish biofilm formation assay. J Vis Exp. 2011;(47):2437. Published 2011 Jan 30. doi:10.3791/2437 ↖
Big Cycle 1: Mathematical Modeling of Microsphere Diffusion and Adhesion in the Stomach
In this Big Cycle, we aimed to construct a mathematical model describing the diffusion and adhesion of gel microspheres in the stomach. Through multiple D-B-T-L iterations, we gradually improved the realism of the gastric environment and refined the simulation of microsphere behavior.
D-B-T-L: Simulation of Gastric Diffusion
Design
Initially, we wanted to simulate the diffusion of gel microspheres in the stomach.
Build
Therefore, we used Python to build a simple gastric diffusion model.
Test
After visualization, we found that our model over-idealized the shape of the stomach (as a square) and might not be realistic enough.
Figure 1: Initial model of diffusion in stomach.
Learn
We then decided to improve the model step by step, first refining the shape of the stomach to be more realistic.
D-B-T-L: Parametric Stomach Modeling
Design
After improvement, we aimed to obtain a model closer to the real stomach shape.
Build
We used parametric equations to describe the shape of the stomach and obtained a result that was relatively realistic.
Figure 2: Using parametric equations to describe the shape of the stomach.
Test
Then, we performed the simulation again and obtained the following results:
Figure 3: Wrong fluid velocity field.
Learn
We found that because the greater and lesser curvatures of the stomach are not mutually injective with respect to y and x, there were problems when simulating the velocity field.
D-B-T-L: Improved Velocity Field Simulation
Design
Finally, we aimed to better simulate the velocity field of gastric fluid during diffusion.
Build
We rewrote the program using the PLT path method.
Test
We visualized the velocity field to check the accuracy of flow simulation.
Figure 4: Improved velocity field in stomach model.
Learn
After several iterations, we finally obtained a more reasonable model to simulate the diffusion process in the stomach.
Big Cycle 2: Adhesion System Modeling
This Big Cycle focuses on modeling and analyzing the adhesion mechanism between HopQ and C1ND proteins to understand the molecular interactions and stability under physiological conditions.
D-B-T-L: Static Structure Analysis
Design
Initially, we aimed to analyze the binding between HopQ and C1ND.
Build
We obtained the sequences of the two protein complexes and studied their interactions such as hydrogen bonds.
Test
After preliminary analysis, we realized that static interaction analysis cannot provide quantitative evidence or simulate physiological conditions.
Figure 4: Improved velocity field in stomach model.
Figure 5: Static structure of HopQ and C1ND.
Learn
We decided to turn to molecular dynamics (MD) simulations for dynamic analysis.
D-B-T-L: Molecular Dynamics Simulation
Design
After reflection, we used GROMACS to perform MD simulations to analyze the binding of HopQ and C1ND under physiological conditions.
Build
We prepared the protein complex system and parameterized it for MD simulation.
Figure 6: Preparation of molecular dynamics simulation.
Test
We then performed MD and quantitatively studied the binding situation of the two proteins through RMSD, hydrogen bond count, and Free Energy analysis.
Figure 7: Binding free energy analysis.
Learn
Finally, by tracking atomic motion trajectories, we dynamically resolved structural stability, local flexibility, and thermodynamic properties. This analysis provides a theoretical basis for the adhesion system.
Big Cycle 3: Modeling and Analysis of GPCR Signaling Pathway
This Big Cycle aims to investigate the activation mechanism of GPCRs after ligand binding, helping to identify variants that are both sensitive and functionally active.
D-B-T-L: Molecular Docking for GPCR-Ligand Screening
Design
We intended to select better combinations of G proteins and GPCRs through simulation to narrow down the scope.
Build
We used molecular docking to estimate the binding energy between ligands and GPCR–G protein complexes.
Test
After docking, we found that the differences in binding energies were not significant. Moreover, simple docking cannot reveal whether GPCRs are activated post-binding.
Figure 8: Result of molecular docking.
Learn
We realized the need for a method that can comprehensively study GPCR behavior after ligand binding.
D-B-T-L: Dynamic GPCR Analysis via MD
Design
We adopted molecular dynamics simulations to study dynamic changes of GPCRs after ligand binding, attempting to determine activation status.
Build
We prepared GPCR–ligand complexes and performed MD simulations.
Test
We analyzed RMSD, RMSF, and conducted PCA to explore conformational changes. However, PCA alone could not confirm activation.
Figure 9: Primary result of molecular dynamics simulation.
Learn
We realized that a solid structural criterion is needed to determine whether GPCRs are truly activated.
D-B-T-L: Activation Criterion Validation
Design
Through literature review, we found that GPCR activation in yeast involves a 12 Å reduction in the distance between the second and sixth transmembrane α-helices.
Build
We applied this structural criterion to analyze trajectory files from our MD simulations.
Test
We measured the distance changes between the α-helices of several GPCR variants to identify those meeting the activation condition.
Figure 10: Improved MD results showing GPCR activation analysis.
Learn
We successfully screened several GPCR variants with high activation potential, deepening our understanding of how dry-lab modeling complements wet-lab validation.
Big Cycle 4: Improved SEIR Model for Helicobacter pylori Infection
This Big Cycle models H. pylori infection dynamics and the impact of drug intervention using an extended SEIR model.
D-B-T-L: Basic SEIR with Drug Addition
Design
Initially, we wanted to incorporate the effect of medication into the SEIR model.
Build
We added a medicated population to the SEIR equations.
Test
We compared infection dynamics with and without drug intervention.
Figure 11: SEIR model without drug.
Figure 12: SEIR model with drug.
Learn
We found that this model starts from a special initial state and cannot intuitively reflect changes after drug introduction.
D-B-T-L: Improved SEIR Model with Delayed Drug Introduction
Design
We wanted to show how introducing the drug later could improve infection outcomes.
Build
We modified the model to introduce the drug only after the system reaches a steady state.
Test
After adjusting drug introduction timing, the results clearly demonstrated the effect of drug treatment.
Figure 13: Improved SEIR model with delayed drug introduction.
Learn
We successfully demonstrated the efficacy of our drug through dynamic SEIR modeling.
