Team:NJTech China/Prospective

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Prospective

In this special year, we were quarantined for a long time at home where we discussed and designed the project by reading literature. In summer, the team members returned to the lab under the regional and school regulations, conducted a series of wet-lab experiments, and have finally made encouraging progress. The impact of the epidemic was the main obstacle of fully realizing the concept of the project. We will continue the progress and plan future work in detail.

1. Modification of pheromone responsive promoters

The pheromone responsive promoter library contains hundreds of promoters, providing a variety of options for gene regulation in applications. Real-world applications may require rational and precise gene regulation methods, and natural promoters cannot be suitable for all applications. Promoter engineering provides researchers with approaches to construct engineered promoters, enabling the accurate regulation of genes in diverse application scenarios.

This year, we have obtained the characterization data of multiple natural pheromone responsive promoters through experiments. According to the rational design of transcription factor-binding sites, we changed the copy number or orientation of pheromone response elements (PREs), and constructed two engineered pprm1. We originally hoped to obtain a pheromone responsive promoter with strong expression activity, but the characterization results showed that the expression activities of the two engineered pprm1 at high induced concentrations were lower than the natural pprm1, suggesting that the working mechanism of PRE is still to be explored.

In the future, we will try more diverse promoter engineering strategies, including site-directed mutagenesis, error-prone PCR (Ep-PCR), sequence randomization of non-conserved region (NCR), hybrid-promoter design, and transcription factor-binding sites (TFBSs) modification, etc.¹. These diversified modification methods will eventually form a complex and rich library of engineered promoters. After that, neural network models can screen engineered promoters that meet actual needs from the library, and molecular dynamics models make it easier to accurately characterize promoters. We hope to obtain two types of promoters with different expression characteristics, called switch-like and rheostat-like promoters, as is shown in figure 1. Switch-like promoters can activate the stable expression of genes when the inducer concentration reaches a certain threshold, and rheostat-like promoters can continuously regulate gene expression levels within a larger inducer concentration range. We believe that these two types of promoters can achieve complex genetic circuit behavior and have application value in biosensors and cell factories.

Fig. 1 Switch-like and rheostat-like promoters

Cell factory

Cell metabolism in organisms is largely regulated at the transcriptional level, and the promoters are considered as basic regulatory elements responsible for transcription initiation. When exploring the expression ability of pheromone responsive promoters, we considered using engineered promoters for the construction of cell factories, as is shown in figure 2.

This year we constructed a signaling pathway mutant strain that can express mating genes in a galactose medium. In the future, we will try to transfer the complex enzyme system under the control of pheromone responsive promoters into signaling pathway mutant strains for metabolic engineering research. The regulation strategy can also be further optimized. The dual properties of galactose inducer and carbon source make the induction process difficult to control precisely. Other regulate methods such as light regulate can be tested later. Besides, the modification of the scaffold Ste5 disrupted part of the negative feedback regulation mechanism of the mating signal pathway, which may have a long-term impact on cell growth². More refined modification plans will be implemented to reduce damage to the normal metabolic process of cells.

Fig. 2 Schematic workflow for microbial factory optimization (modified from Naseri, G. et al. 2020)

CRISPRa zygotic regulation strategy

During the brainstorming session, team members conceived a set of gene regulation strategies in the zygote. By distributing the components of the gene regulation circuit for single cells to yeasts of different mating-types, the circuit only works after the cells are fused to form diploids. We believe that this strategy makes the intensity of pheromone response and the efficiency of cell fusion a regulatory point, and can achieve complex gene circuit behavior. After reading the literature, we found a CRISPRa system in yeasts³. We plan to put dCAS9, MCP-VP64, and scRNA into type-a yeasts, and introduce the regulated genes into type-α yeasts. The regulated genes can only be activated only after each component of the CRISPRa system is expressed and the yeasts are fused. We have constructed a molecular dynamics model to describe this regulation process. Because this system is difficult to construct and verify, we have not yet characterized this CRISPRa strategy in the wet lab. In the future, we will further verify the accuracy of the program and make necessary modifications to guarantee its implementation in the lab and practical application in the real world.

Fig. 3 CRISPRa zygotic regulation strategy

References

[1] Xu, N., Wei, L., and Liu, J. (2019) Recent advances in the applications of promoter engineering for the optimization of metabolite biosynthesis, World J Microb Biot 35.

[2] van Drogen, F., Mishra, R., Rudolf, F., Walczak, M. J., Lee, S. S., Reiter, W., Hegemann, B., Pelet, S., Dohnal, I., Binolfi, A., Yudina, Z., Selenko, P., Wider, G., Ammerer, G., and Peter, M. (2019) Mechanical stress impairs pheromone signaling via Pkc1-mediated regulation of the MAPK scaffold Ste5, Journal of Cell Biology 218, 3117-3133.

[3] Zalatan, J. G., Lee, M. E., Almeida, R., Gilbert, L. A., Whitehead, E. H., La Russa, M., Tsai, J. C., Weissman, J. S., Dueber, J. E., Qi, L. S., and Lim, W. A. (2015) Engineering Complex Synthetic Transcriptional Programs with CRISPR RNA Scaffolds, Cell 160, 339-350.