Establishing a Malonyl-CoA Biosensor for the Two Model Cyanobacteria Synechocystis sp. PCC 6803 and Synechococcus elongatus PCC 7942.

IF 3.7 2区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

ACS Synthetic Biology Pub Date : 2025-07-18 Epub Date: 2025-06-30 DOI:10.1021/acssynbio.5c00320

Ivana Cengic, Elton P Hudson

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Abstract

Malonyl-CoA, produced by the first committed step of fatty acid biosynthesis, is a precursor for many valuable bioproducts, making it an important metabolic engineering target. Here, we establish a malonyl-CoA biosensor for the model cyanobacteria Synechocystis sp. PCC 6803 and Synechococcus elongatus PCC 7942. The developed biosensor utilizes FapR, a malonyl-CoA-regulated transcriptional repressor from Bacillus subtilis, and novel FapR-regulated and cyanobacteria-compatible hybrid promoters for expressing Yfp, the biosensor output reporter. A l-rhamnose-inducible promoter P_rhaBAD, characterized in combination with ribosome binding sites of varied strengths, was evaluated for titratable FapR expression. Additionally, the placement and quantity of the FapR-recognized operator within the hybrid promoter was evaluated for its effect on biosensor performance. The optimal operator placement was found to differ for the biosensor variants that achieved maximum reporter expression in the two considered model cyanobacteria. Overall, this biosensor provides new opportunities for further development of cyanobacterial cell factories.

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两种模式蓝藻聚囊藻PCC 6803和长聚球菌PCC 7942丙二酰辅酶a生物传感器的建立

丙二酰辅酶a是脂肪酸生物合成的第一步产物，是许多有价值生物制品的前体，是重要的代谢工程靶点。本研究为蓝藻聚囊球菌PCC 6803和长聚球菌PCC 7942建立了丙二酰辅酶a生物传感器。开发的生物传感器利用来自枯草芽孢杆菌的丙二酰辅酶a调控的转录抑制因子FapR，以及新的FapR调控和蓝藻兼容的杂交启动子来表达生物传感器输出报告基因Yfp。l-鼠李糖诱导的启动子PrhaBAD与不同强度的核糖体结合位点结合，评估了可滴定的FapR表达。此外，fapr识别的操作符在杂交启动子中的位置和数量对生物传感器性能的影响进行了评估。研究发现，在两种考虑的蓝藻模型中，实现最大报告基因表达的生物传感器变体的最佳操作符位置不同。总的来说，这种生物传感器为蓝藻细胞工厂的进一步发展提供了新的机会。

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来源期刊

ACS Synthetic Biology 生物-

CiteScore

8.00

自引率

10.60%

发文量

380

审稿时长

6-12 weeks

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.