Genetic circuit-enabled synthetic biosensors： design and applications Synthetic Biology Journal    DOI: 10.12211/2096-8280.2025-031

Fig. 6 Circuit designs and applications of multilayered biocomputing modules
(a) Gene circuit of a dual-parameter biosensor based on an AND logic gate and its response heatmap^[104]; (b) Gene circuit of a metabolic control sensor integrating a multi-input genetic logic circuit ^[163];

Extracts from the Article

在环境监测领域，Wang等［21］构建了基于AND逻辑门的多参数传感器，通过整合天然双组分信号转导系统与合成细胞间通讯模块，实现了砷、汞、铜离子的同步检测；Wan等［32］开发的级联信号放大系统通过设计多层级联放大器模块显著提升了砷、汞离子传感器的检测灵敏度（检测限小于0.1 ppb、0.01 pbb）。在医学诊断方面，Chien等［162］通过AND逻辑门耦合缺氧与乳酸传感器，使工程菌的肿瘤靶向特异性提升；Woo等［104］开发的硫代硫酸盐-硝酸盐双输入AND门传感器，通过同时识别两种炎症标志物，显著提高了肠炎诊断的特异性（图6a）。在生物制造领域，Moser等［163］设计的多输入组合逻辑基因线路可同时监测葡萄糖、氧气及乙酸盐的浓度，为代谢过程的精准调控提供了新工具（图6b）。这些案例展示了基因线路计算模块在复杂生物传感中的巨大潜力，为开发智能传感系统提供了技术支撑。

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• Table 1  Typical genetic circuit-enabled synthetic biosensors and applications
• Fig. 1  Mechanisms and applications of transcriptional regulatory protein-enabled synthetic biosensors(a-c) Mechanisms of allosteric transcription factors, transmembrane transcription factors, and two-component systems-enabled biosensors; (d) Response curves of biosensors based on activation-type and repression-type transcription factor; (e) Gene circuit of a thiosulfate-sensing sensor based on the two-component system ThsRS^[54]; (f) Gene circuit of a transcription factor-enabled biosensor for monitoring glucose uptake^[14]; (g) Gene circuit of a target-dependent RNA polymerase-enabled biosensor^[95].
• Fig. 2  Mechanisms of riboswitches-enabled synthetic biosensors(a) Riboswitch-enabled sensors based on transcriptional activation and transcriptional repression.(b) Riboswitch-enabled sensors based on translational activation and translational repression..
• Fig. 3  Mechanisms and applications of riboregulator-enabled synthetic biosensors(a) Mechanism of the toehold switch^[124]; (b) A ribozyme-based sensing platform RENDR^[125]; (c) Gene circuit of a sensor for reporting bacterial DNA transfer in soil using split ribozymes^[133]; (d) Mechanism of the group I intron-enabled RNA trans-splicing system SENTR and its application for intracellular mRNA detection ^[122].
• Fig. 4  Mechanisms of CRISPR-enabled synthetic biosensors(a) RNA sensing enabled by reprogrammed tracrRNA in type II CRISPR system^[17]; (b) RNA sensing enabled by RNA-triggered RNA processing^[142]; (c) RNA sensing enabled by strand displacement reactions^[143].
• Table 2  Advantages and limitations of genetic circuit-enabled synthetic biosensors based on different signal recognition mechanisms
• Fig. 5  Typical biomemory modules for recording biosensing signals(a) Gene circuit for a biomemory module based on toggle switch; (b) Gene circuit of a zinc ion memory module based on the recombinase flip mechanism^[153]; (c) Principle of the CAMERA recording system based on CRISPR/Cas^[158]; (d) Gene circuit of the DNA sensing and recording module (CATCH) based on CRISPR/Cas^[159].
• Fig. 7  Synthetic biosensing systems with multimodal outputs for integration with various detection platforms(a) A agarose hydrogel-encapsulated arsenic ion sensor for visual array display on a smartphone platform^[32]; (b) A sensor that visualizes biosensing signals through the formation of bacterial spatial motility patterns^[36]; (c) A sensing system coupling a fluorescent sensor with a photoelectric chip to convert optical signals into wireless signals^[48].
• Fig. 8  Strategies for increasing the sensitivity of genetic circuit-enabled synthetic biosensors(a) Typical response curves and characteristics of genetic circuit-enabled synthetic biosensors.; (b) Dynamic range optimization based on promoter engineering; (c) Limit of detection optimization by gradient regulation of biorecognition components concentration and target enrichment technology; (d) Dynamic range optimization using sensing signal amplifiers based on activator transcription factors, positive feedback loops and cascade repressors ^[7]; (e) Leakage optimization utilizing antisense RNA-mediated translation blocking, decoy DNA binding site competitive inhibition, and output protein degradation tags^[1].
• Fig. 9  Strategies for increasing the specificity of genetic circuit-enabled synthetic biosensors(a) Semi-rational design and saturation mutagenesis of the transcription factor LysG to prevent its binding to L-lysine (L-Lys) while retaining its ability to bind L-arginine (L-Arg) and L-histidine (L-His)^[191]; (b) Semi-rational design and saturation mutagenesis of the TynA-FeaR sensing system for specific detection of phenylethylamine. (DA: dopamine; PEA: phenylethylamine; Tyra: tyramine; Trypta: tryptamine)^[192]; (c) Coupling transcription factors ZraR and ZntR through an AND gate for specific respond to Zn²⁺^[7,21].
• Fig. 10  Examples of improving the response speed of genetic circuit-enabled synthetic biosensors(a) An E. coli-based sensor with a synthetic electron transfer chain that express an electrical protein switch enable rapid detection of an endocrine disruptor 4-hydroxytamoxifen (4-HT)^[6]; (b) Reversible response kinetics curve and sensing mechanism of a protein phosphorylation signaling network with rapid activation and deactivation^[197].
• Fig. 11  Examples of stability and biosafety optimization for genetic circuit-enabled synthetic biosensors(a) A plasmid copy number control platform in Escherichia coli based on dynamic regulation of translation initiation factors^[204]; (b) A biocontaining CRISPR-Cas9 dual-modal kill switch (CRISPRks) for E. coli under the dual control of chemical inducer anhydrotetracycline (aTc) and temperature changes^[212].