Team:NJTech China/Poster

Pheromone Revolution: Mating Pathway-based Promoter Engineering

Presented by Team NJTech_China 2020

Siyi Zheng1, Yujiao Wang1, Yongyan Zhi1, Yinghao Chen1, Yiqing Zhang1, Yicheng Lu1, Jiacheng Li1, Huilan Wu1, Ran Lu2, Ying Liu2, Yuxin Huang2, Guannan Liu3

1iGEM Student Team Member, 2iGEM Team Advisor, 3iGEM Team Primary PI


Cell fusion is a fundamental biological process required for the entire development of most eukaryotic organisms, from fertilization to organogenesis. Pheromone-mediated mating in the budding yeast Saccharomyces cerevisiae provides a genetically accessible model system to investigate cell-cell fusion. However, the high price of pheromone limits the development of related research. In our project, we constructed mutants to reshape signaling pathway, trying to build a chassis that responds to cheaper inducers. We characterized the intensity of three mostly pheromone responsive promoters, pfus2, pprm1, and pfig1. We innovatively evaluated the efficiency of these promoters (natural and synthetic) with pheromone responsive elements (PREs) of various copy numbers and directions. Our results expand the promoter toolbox to finely tune gene expression levels for efficient cell factories and biosensors.
The expression of more than 200 genes is up-regulated after exposure of haploid yeasts to mating pheromone. The promoters of these genes display diversified expression capabilities and can be used to construct customized exogenous and endogenous gene expression cassettes. Ste12 acts as the major transcription activator to activate the promoters in mating genes. Pheromone-responsive promoters generally have multiple copies of putative Ste12 binding sites, which are also called pheromone-responsive elements (PRE). PRE can endow the minimal GAL1 core promoter with the ability to respond to pheromone. The arrangement of PRE may affect the basal and pheromone responsive expression level.

We characterized the expression level of three natural pheromone responsive promoters, pfus2, pprm1, and pfig1. To study the effect of PREs on the promoter activity, we constructed two distinct pprm1. In pprm1 Pro, we reversed the orientation of PRE in natural pprm1, while in pprm1 Ultra, we doubled the copy number of the PRE in natural pprm1.

Fig. 1 A. The orientation, sequence, and copy number of PREs in three pheromone-inducible promoters.
B. Two distinct pprm1 with different orientations and copy numbers, pprm1 Pro and pprm1 Ultra.

The diversity and plasticity of pheromone-responsive promoters allow it used in the construction of reporters in biosensors. However, the expensive pheromone limits the application of such promoters in cell factories. To broaden the application range of pheromone-responsive promoters, we reconstructed the pheromone signaling pathway, trying to build a chassis that responds to cheaper inducers. According to the literature, we learned that the scaffold protein Ste5 plays an important role in the pheromone signaling pathway. The highly active mutant of Ste5 can activate the MAPK pathway in the absence of pheromone, inducing the expression of pheromone-responsive genes. We used the highly active mutant of Ste5 to enable the cheap inducer galactose to induce the expression of mating genes in engineered yeast. As a result, the pheromone-responsive promoters can be used for the construction of cell factories.

Fig. 2 The highly active mutant of Ste5 used to activate pheromone signaling pathway

In addition to wet-lab experiments, we constructed a neural network algorithm to predict the expression level of pheromone-responsive promoters at different pheromone concentrations. After using the pheromone promoter expression library to test the model, the algorithm can accurately predict the expression level of pheromone responsive promoters based on the promoter sequence, providing support for promoter modification. Besides, we also constructed a molecular dynamics model considering the mechanism of the pheromone signaling pathway, providing help for the setting of experimental conditions and data processing in promoter characterization.
1. Promoter engineering
Gene expression is controlled by many factors, including promoter strength, cis and trans factors, cell growth stage, and other gene-level regulation. Compared to other regulation methods, promoter-based modification allows researchers to select inducers according to specific purposes or laboratory conditions and to achieve desired induction effect. Promoter engineering is the subject focusing on creating functional promoter libraries for precise control of gene expression for metabolic optimization or control analysis.

2. Yeast mating
Cell fusion is a fundamental biological process required for the entire development of most eukaryotic organisms, from fertilization to organogenesis. The mating of Saccharomyces cerevisiae is a model for studying cell fusion. It includes a series of processes such as mating pheromone recognition, zygote production, and diploid cell nucleus formation. More than 200 genes are up-regulated after exposure of haploid yeast cells to mating pheromone. The promoters of these genes display diversified expression capabilities and can be used to construct customized gene expression cassettes.
1. How to enrich the pheromone responsive promoter library?
There are hundreds of pheromone-responsive genes in haploid Saccharomyces cerevisiae. The promoters of these genes exhibit diverse expression activities and can be used in the construction of biosensors and cell factories. However, most pheromone responsive promoters have not been fully characterized, and the engineered promoters have not been constructed to suit real-world applications.

2. How to broaden the application scenario of pheromone responsive promoters?
The promoter library meets the needs of some real-world applications. However, the high price and instability of pheromone limit the application range of promoters, especially in cell factories.
1. Characterization and modification of natural pheromone-responsive promoters

Fig. 1 Ste12 induces pheromone-responsive gene expression under the regulation of signal pathway

Characterization and modification of promoters can enrich the promoter library to suit real-world applications. Ste12 acts as a major transcriptional activator to activate promoters of mating genes. Multiple copies of putative Ste12 binding sites are prevalent in pheromone-responsive promoters, which are also known as pheromone response elements (PREs).

Fig. 2 PREs in pfig1, pprm1, pfus2, pprm1 Pro and pprm1 Ultra
(The PRE consensus sequence is TGAAACA. Numbers between any two PREs indicate the spacing in nucleotides.)

Considering the activation function of PRE, we selected promoters with different copies of PRE: pfus2, pprm1, and pfig1. We analyzed the relationship between pheromone concentration and promoter activity for each promoter based on the data, demonstrating the diverse expression capability of pheromone-responsive promoters.
We designed our own promoters – promoter prm1 Pro and promoter prm1 Ultra. The Pro has reversed PREs while the Ultra has doubled copy number of PREs.

2. Mating signaling pathway modification

Fig. 3 Modification of pheromone responsive pathway

By modifying the signaling pathway, we expect to enable alternative inducers to trigger the activation of pheromone responsive promoters. The mating signaling pathway is mediated by G protein and MAPK cascade. In this pathway, Ste5 plays an important role responsible for associating the G protein with the MAPK components. The modular structure of Ste5 provides possibility for the modification of the mating signaling pathway.
So, based on literature, we created Ste5ΔN-CTM. By removing the N-terminal sequence involved in membrane localization, Ste5 activation is independent from Gβγ subunits. The CTM domain added to C-terminal of Ste5ΔΝ can anchor the protein to the plasma membrane. The Ste5ΔN-CTM protein activates the MAPK pathway in the absence of pheromone and triggers the expression of pheromone-responsive genes.
Construction and characterization of GFP reporter pathway of three promoters
Fig.1 The experimental process of promoter modification and characterization

We decided to study three pheromone-responsive promoters: pfus2, pprm1, and pfig1. We cloned three promoters, reporter gene gfp, and cyc1 terminator by PCR amplification. We constructed the recombinant plasmid and transformed it into Saccharomyces cerevisiae BY4741 through electro transformation.
We constructed pRS415-GFP-CYC1 , pRS415-6×PRE-pprm1-GFP-CYC1 and pRS415-3×PRE_R-pprm1-GFP-CYC1 plasmid by one step cloning. After construction of recombinant yeasts, we quantitatively characterized the activity of promoters through flow cytometer.

Construction of Δste5 strains
Fig.2 The experimental process of Δste5 strains

Fig.3 Construction of Δste5 strains

We aim to eliminate the interference of natural Ste5 on the modified signaling pathway. To achieve the ste5Δ strains, we used homologous recombination for gene knockout. Through nucleic acid electrophoresis and sequencing, we filtered out the ste5Δ strain.

Construction of pheromone-independent Ste5 highly active mutant
After the construction of the ste5Δ strain, we introduced the pgal1-Ste5ΔN-CTM gene into it, and named it the pheromone-independent Ste5 highly active mutant, PIDS for short. The engineered yeast can transform from the vegetative phase to the mating phase under the induction of galactose.

The neural network model for promoter activation prediction

To predict the promoter activity after pheromone treatment, we constructed a neural network model with the backpropagation algorithm (BP-ANN Model). The number of hidden layers is 2000. The well-trained model shows the correlation coefficient value of the training set is 0.91044, and the correlation coefficient value of the test set is 0.72843.
The promoter has the higher value in one aspect gets one point, and the promoter has the score over 4 by 7 is considered stronger than another. According to the predicted results and prm1 in the training set, we got conclusion: pfus2 > pfig1 > pprm1, pprm1 Ultra > pprm1 > pprm1 Pro.
The experimental results showed that in the natural promoters, from strong to weak is pfus2 > pfig1 > pprm1. The experimental results were consistent with the model prediction results. In the engineered promoters, from strong to weak, however, is pprm1 Ultra > pprm1 > pprm1 Pro.
The model prediction results have few defects. Some points of data are obviously not in line with the experiment. And some of the results do not conform to the general laws of induction. After we find a suitable promoter library in the future, the neural network model will become more accurate.

The signaling pathway model for S. cerevisiae mating
We used the molecular dynamics model to simulate the process of activation of GPCR by pheromone and the expression of GFP reporter gene.

Equation (1) describes the process of activation of GPCR by pheromone. We ignored the intermediate process of the signaling pathway for it does not affect fluorescence intensity. Transcription and translation of GFP can be described as Equation (2) and (3). When the reaction reaches equilibrium, we can get the relationship between PGFP and Phe.
In order to determine the parameter values, we designed a set of experiments to obtain the fluorescence intensity of GFP when induced by different concentrations of pheromone. GFP concentration was reflected by the fluorescence intensity for their linear relationship.
According to the experimental data, we have obtained the characteristic curve of promoter prm1. This result helps to determine how to select the pheromone concentration for a specific promoter activity.
Human Practices

This year, we collaborated with other iGEM teams in many aspects, including providing plasmids, suggestions on engineering and modeling, and so on.

Human Practices

Our team consulted some experts about on the application prospects and safety issues of the project, and we got some useful feedback.

Feedback from questionaires and interviews about CRISPR technology are beneficial for us to evaluate enviromental social, moral values when designing our project.

Science Communication
Our team also took part in numerous science communication activities to disseminate knowledge of synthetic biology to different communities.

Release articles in synthetic biology on WeChat Official Account

Hold a lecture on synthetic biology at Nanjing Tech University

Hold a lecture on synthetic biology at local government of Liren Town, Suqian, Jiangsu province

Publish an article on bilibili platform

Participate in the 6th Jiangsu Public Welfare Science Competition

Promote epidemic prevention knowledge with foreign students of our school
Application Scenario
Cell Factory

Fig. 1 Schematic workflow for microbial factory optimization (modified from Naseri, G. et al. 2020)

Compared with other signal transduction processes, mating-specific signal pathways are relatively independent of the asexual life history of yeast. By modifying mating-specific signaling pathways, cells can respond to specific induction conditions and change gene expression. During mixed fermentation, the specific reactions can be regulated by changing the induction conditions. For example, to avoid the toxic effect of the accumulated intermediates, cells can be induced at various stages. However, we are facing challenges including but not limited to the following one that galactose as the carbon source may affect cell growth.


Fig. 2 Diverse biosensors used for screening combinatorial libraries (modified from Naseri, G. et al. 2020)

Besides, we have learned that existing sensors based on physical indicators to detect chemicals in the environment have the problems of low sensitivity and high cost. If mating specific signaling pathways are modified to make yeast respond to specific signals, such as toxic and explosive substances in the environment, the levels of trace compounds in the environment can be quantitatively monitored by reporter genes. With respect to the biosensors applications of our system, specific detection targets need to be considered. Antibiotic in the environment provides a possibility.

Quorum sensing

Fig. 3 Circuit development of 2014 iGEM Team UCSF_UCB (From iGEM 2014 UCSF_UCB)

This promoter can also be used to improve iGEM projects. It can be applied in 2014 UCSF_UCB team's project to reduce population noise, and increase the speed of quorum sensing, or change the threshold of quorum sensing. Using these promoters with special properties, we can construct more complex cell factories and design multi-purpose mixed bacteria fermentation routes.

Application in DAS system

Fig. 4 The DAS system (From iGEM 2015 Chalmers-Gothenburg)

In 2015, Chalmers-Gothenburg's team created an innovative system that is both time and material-efficient by automatically identifying and eliminating contamination in bioreactors. The detection system goes by the name DAS (detection, and amplification of the signal), and it is based on the pheromone response pathway in Saccharomyces cerevisiae. The promoter designed by our team, if it is applied to the DAS system of the Chalmers-Gothenburg team, may be able to detect pollutants more quickly and accurately, while the enhanced expression of signal substances can boost the observation of experimenters or staff.
Characterization of three natural pheromone responsive promoters and new findings from promoter characterization experiments

Fig.1 The fluorescence intensity of GFP expressed by different promoters induced by different concentrations of pheromone

We analyzed the intensity of promoters at different pheromone concentrations. Within 1-5uM, the higher the concentration of pheromone, the more obvious the induction effect is. Comparing the GFP expression level of these three promoters, pfus2 is the strongest, followed by pfig1, and pprm1 is the weakest.
According to previous predictions, the expression level of pfus2 should be the weakest, but the results showed that the intensity of pfus2 was higher than that of pprm1. The two PREs in promoter fus2 have opposite directions, while the three PREs in promoter prm1 are in the same direction, which indicates that the expression level of the promoter with PREs in the "tail-to-tail" orientation is higher than that with “head-to-tail" orientation.

Modification of natural promoters
Fig.2 The fluorescence intensity of GFP expressed by different modified pprm1 induced by different concentrations of pheromone

The pheromone concentration has no significant effect on the GFP expression intensity under the control of pprm1 Ultra, indicating that this engineered promoter remains a stable expression level when induced by pheromone. Unexpectedly, the fluorescence intensity of the promoter prm1 is higher than that of the Pro and Ultra under high concentration pheromone treatment. The fluorescence intensity of the natural is higher than that of the Pro, which means that the orientation of the PRE site on the promoter is critical to the expression level of the promoter.

Characterization of ste5Δ strains and PIDS

Fig.3 Pictures of mutant construction experiment results.
(A): Halo assay of ste5Δ strain;
(B): The growth of the Ste5ΔN-CTM strain and BY4741 wild type strain on the plate with galactose as the sole carbon source;
(C): The growth of the Ste5ΔN-CTM strain and BY4741 wild-type strain on the plate with glucose as the sole carbon source

To further verify the knockout of ste5, we conducted a halo assay experiment. The ste5Δ strain did not form a halo on the plate(Figure 3-A). This result is in line with the description of the ste5-deficient yeast strain in the literature.
After the construction of the ste5Δ strain, we introduced the pgal1-Ste5ΔN-CTM gene into it, and named it PIDS for short. We spread the PIDS strain on a plate with galactose as the sole carbon source. The results showed that the strain did not grow on the plate(Figure 3-B). The left side of the figure is the PIDS strain and the right side is the BY4741 strain. Meanwhile, on SC complete medium, both PIDS strain and BY4741 strain grew well(Figure 3-C).

The specific influence caused by different PRE orientations needs to be investigated and verified by further experiments. We will build a pheromone-responsive promoter library by characterizing natural promoters and constructing engineered promoters. The promoters will be precisely responded to the activator in the “S”-curve or linear relations like a sharp on/off switch or a graded rheostat. The system can be also put into signaling pathway mutants to test the feasibility of cell factories. The kinetic modeling to describe CRISPRa zygotic regulation system has been done. We have obtained the relationship between the dCas9, MCP-VP64, scRNA, pheromone, and GFP concentration. With the participation of the CRISPRa system, we can design a cross-cell fusion-detecting system. In the future, more work needs to be done to verify the accuracy of the model.
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1. Technique Support

Thanks to all technique support given by Snapgene, Genscript, NCBI, Genewiz, Chopchop, Biorender, Matlab, and Benchling.

2. Sponsors

Thanks to College of Biotechnology and Pharmaceutical Engineering of Nanjing Tech University, the 2011 College of Nanjing Tech University, Jiangsu Synergetic Innovation Center for Advanced Bio-Manufacture and Jiangsu Xiangshun Engineering Management Consulting Co., Ltd. for providing financial support to our team.