Tao Wang, Shuwen Ding, Jiao Xu, Guohao Cai, Yiqing Zhang, Yingxuan Qi, Yujia Jiang, Ping Zhang, Tianjing Wang, Fengxue Xin, Tao Shen, Guannan Liu
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引用次数: 0
Abstract
Copper ion poses serious threats to both the environment and human health. To develop a yeast biosensor with reduced background noise and enhanced detection sensitivity, we constructed a quorum-sensing module with amplified positive feedback. This biosensor employs a copper ion-pheromone communication system, which allows haploid a-type yeast (MATa) to express the α-pheromone gene (mfα2) under the control of the copper ion-inducible promoter pCUP1. The α-pheromone activates the mitogen-activated protein kinase (MAPK) signaling pathway, which in turn induces the expression of the green fluorescent protein (GFP) gene via the pheromone-inducible promoter pprm1. To improve the performance of the biosensor, we optimized the prm1 promoter and constructed the Ste5ΔN-CTM chassis. Specifically, the promoter intensity was improved by converting the three nonconsensus Pheromone Response Elements (PRE) in pprm1 into consensus PRE sequences, resulting in the prm1 Pro promoter. The Ste5ΔN-CTM strain continuously activates the MAPK signaling pathway. Next, to offset the loss of sensitivity and dynamic response range caused by endogenous pheromone degradation, we knocked out the pheromone degradation gene bar1 using CRISPR-Cas9 gene editing technology. Additionally, we established a functional model relating the copper ion concentration to the GFP signal output. In conclusion, this study designed a modular copper ion biosensor system by integrating sensing, amplification, and signal-reporting components, laying a foundation for the development of biosensors for other heavy metals.
期刊介绍:
The journal is particularly interested in studies on the design and synthesis of new genetic circuits and gene products; computational methods in the design of systems; and integrative applied approaches to understanding disease and metabolism.
Topics may include, but are not limited to:
Design and optimization of genetic systems
Genetic circuit design and their principles for their organization into programs
Computational methods to aid the design of genetic systems
Experimental methods to quantify genetic parts, circuits, and metabolic fluxes
Genetic parts libraries: their creation, analysis, and ontological representation
Protein engineering including computational design
Metabolic engineering and cellular manufacturing, including biomass conversion
Natural product access, engineering, and production
Creative and innovative applications of cellular programming
Medical applications, tissue engineering, and the programming of therapeutic cells
Minimal cell design and construction
Genomics and genome replacement strategies
Viral engineering
Automated and robotic assembly platforms for synthetic biology
DNA synthesis methodologies
Metagenomics and synthetic metagenomic analysis
Bioinformatics applied to gene discovery, chemoinformatics, and pathway construction
Gene optimization
Methods for genome-scale measurements of transcription and metabolomics
Systems biology and methods to integrate multiple data sources
in vitro and cell-free synthetic biology and molecular programming
Nucleic acid engineering.