基于基因线路的合成生物传感器设计与应用

doi:10.12211/2096-8280.2025-031

摘要/Abstract

摘要：

合成生物传感器利用基因编码的生物识别元件特异性识别靶标并将其转换成可量化的生物信号，然后通过基因线路介导的功能器件实现生物信号的定制化处理与多模态信号输出，具有生物相容性高、成本低、环境友好等优势，已在环境监测、生物制造过程监控、精准医学诊疗等领域展现出重要应用潜力。合成生物学方法和前沿技术的突破性进展，特别是模块化的工程设计原理、基因线路的可编程动态调控策略和人工智能辅助的生物元件挖掘与从头设计，为合成生物传感器的开发提供了前所未有的助力。然而，当前合成生物传感器的产业化应用仍在多个性能指标方面面临制约：即敏感性（Sensitivity）、特异性（Specificity）、响应速度（Speed）、稳定性（Stability）和安全性（Biosafety）——简称5S挑战。本文系统梳理了基于基因线路的合成生物传感器信号识别机制与设计范式，深入剖析了各类型合成生物传感器的技术优势与应用瓶颈，并归纳了代表性的基因线路传感功能扩展模块与应用案例。最后，本文还介绍了合成生物传感器的关键特征以及典型优化方法，探讨了未来加速推进合成生物传感器实现广泛实际应用的挑战与机遇。

关键词: 合成生物传感器, 基因线路, 变构转录因子, 双组分系统, 核糖开关, 核糖核酸调节子, CRISPR

Abstract:

Synthetic biosensors leverage genetically encoded biorecognition components to specifically identify targets and convert them into quantifiable biological signals. These signals can then be processed through genetic circuits to achieve customized signal processing and produce multimodal signal outputs. Synthetic biosensors offer several compelling advantages including high biocompatibility, low cost and sustainability, and have shown significant application potential in environmental monitoring, biomanufacturing, and precision diagnostics. Advances in synthetic biology methods and technological developments, particularly the adoption of various engineering design principles, genetic circuit-enabled programmable signal processing, and AI-assisted mining and de novo design of biological components, have provided unprecedented momentum for developing new generation synthetic biosensors. However, the practical applications of synthetic biosensors have been restricted by certain technical limitations in sensing performance including sensitivity, specificity, speed, stability and biosafety, termed as the '5S' challenges. Here we summarize the signal recognition mechanisms and design principles of representative genetic circuit-enabled synthetic biosensors, and provide an in-depth analysis of their technical advantages and remaining challenges for use in the field. Furthermore, we highlight typical genetic circuit-enabled functional expansion modules for myriad application scenarios. Finally, we introduce the key features of synthetic biosensors and the latest optimization methods for improving sensing performance. We conclude by discussing the challenges and opportunities for accelerating the development of new generation synthetic biosensors for achieving sustainable, affordable and reliable real-world detection in diverse settings.

Key words: synthetic biosensor, genetic circuit, allosteric transcription factor, two-component system, riboswitch, riboregulator, CRISPR

中图分类号:

邓稼轩, 陈升言, 王宝俊. 基于基因线路的合成生物传感器设计与应用[J]. 合成生物学, DOI: 10.12211/2096-8280.2025-031.

DENG Jiaxuan, CHEN Shengyan, WANG Baojun. Genetic circuit-enabled synthetic biosensors： design and applications[J]. Synthetic Biology Journal, DOI: 10.12211/2096-8280.2025-031.

图/表 13

表1 基于基因线路的合成生物传感器设计与典型应用

Table 1 Typical genetic circuit-enabled synthetic biosensors and applications

领域	具体应用	检测靶标	传感基因线路元件	检测限	工作范围	参考文献
环境监测	重金属离子	As³⁺	转录因子ArsR、转录信号放大器	0.1 ppb	0.1-5 ppb	[32]
		Cd²⁺	转录因子CadR	0.39 μg/L	0-60 μg/L	[10]
		As³⁺	II型CRISPR系统		0-32 μM	[17]
		U⁶⁺	双组分系统UzcRS-UrpRS、AND gate、天然系统活性放大器	1 μM	1-5.2 μM	[33]
		Hg²⁺	toehold开关、转录因子MerR	5 nM	5-7.5 nM	[34]
		Au³⁺	转录因子HspR、重组酶系统	5 μM	5-100 μM	[35]
		Cu²⁺	P _CopA 启动子		0-50 mM	[36]
	爆炸残留物	2,4-DNT	yqjF启动子	4.8 mg/L	4.8-25 mg/L	[37]
	爆炸残留物	TNT	TNT核糖开关，记忆开关	25 μM		[38]
	农药	2-苯基苯酚	转录因子HbpR、转录信号放大器	1 μM	1-50 μM	[39]
	有机污染物	单环芳烃	双组分系统TodTS	0.04 mg/L	0.04-1 mg/L	[40]
	有机污染物	甲醇	双组分系统MxcQZ-OmpR		0-0.05%	[41]
	环境病原细菌	AHL	转录因子QscR	0.01 μM	0.01-5 μM	[42]
医学诊疗	监测体液物质	孕酮	从头设计转录因子DLA	0.16 μg/L	0.16- 60 μg/L	[43]
		人血清中的锌	转录因子ZntR、Zur		0-20 μM	[44]
		大麻素类化合物	基于CB2受体的酵母GPCR	1 nM		[45]
	检测疾病标志物以诊断疾病	转化生长因子-β	双组分系统Smad	0.024 ng/mL	0.024- 6.25 ng/mL	[15]
		胆盐	人工跨膜转录因子CadC-TcpP	28.3 μM	28.3- 58.99 μM	[46]
		血红素	转录因子HrtR，拨动开关	0.12 ppm		[47]
		肠炎标志物NO	转录因子NorR，重组酶记忆模块	30 μM		[48]
		RNA	CRISPR-Cas13a/C2c2系统			[49]
		DNA	CRISPR-Cas12a系统			[50]
	传感并治疗疾病	血液脂肪酸	人工转录因子LSR	5 μM	5-100 μM	[51]
		霍乱弧菌群体感应信号CAI-1	人工转录因子HR	细胞密度10⁸ CFU/ml		[52]
		原儿茶酸	转录因子 PcaV		0-1000 μM	[53]
		硫代硫酸盐	双组分系统 ThsRS	0.016 mM	0.016-1 mM	[54]
		阿司匹林	复合转录因子Myr-NPR1/NPR4-VanR-VP16		10-250 μM	[55]
		硝酸甘油	级联生化反应和转录因子CREB	75 µM		[56]
	调节肠道生态	鼠李糖、硫酸软骨素、IPTG	转录因子RhaR和LacI、双组分系统BT3334- BT0267、 CRISPR记忆模块	0.3 mM; 0.01 mM; 6 μM		[57]
生物制造	检测目标产物产量辅助菌株筛选	L-赖氨酸	转录因子LysG	40 mM	40-320 mM	[12]
		L-半胱氨酸	转录因子CcdR		0-50 mM	[58]
		苹果酸	转录因子MalR	5 g/L	5-15 g/L	[59]
	代谢动态调控	半乳糖醛酸	转录因子ExuR		1-100 mg/L	[60]
		葡萄糖	转录因子Mlc			[14]
		L-赖氨酸	转录因子LysG		0.05-8 mM	[61]
		长链脂肪酸	转录因子FadR、TetR			[62]
	优化发酵参数	L-乳酸、D-乳酸	转录因子EcLldR、PfPdhR		15-200 mM；0-50 mM	[13]
	辅助酶的定向进化	乳果糖	转录因子LacI-L5	5 μM	10-500 μM	[63]
		茶碱	茶碱核糖开关	10 μM	10-1000 μM	[64]
		生物碱	转录因子RamR		1-100 μM	[65]
		4'-O-甲基去甲酰胺	转录因子RamR	2.5 μM	2.5-100 μM	[66]
食品安全	检测食物毒性物质	腐胺	转录因子PuuR	5.37 mM		[67]
		毒素黄素	转录因子ToxR	50 nM	50-500 nM	[68]
		组胺	转录因子HinK	0.39 ppm	0.28-18 ppm	[69]
		四环素	转录因子TetR、聚合酶链回收（PSR）放大线路	12 ppb		[70]
	食品质量控制	柚皮素	柚皮素核糖开关		0-0.6 mM	[71]
细胞调控	调控细胞分裂与运动	光照	转录因子LexRO、基因逻辑门	0.059 mW/cm²		[72]

表1 基于基因线路的合成生物传感器设计与典型应用

Table 1 Typical genetic circuit-enabled synthetic biosensors and applications

领域	具体应用	检测靶标	传感基因线路元件	检测限	工作范围	参考文献
环境监测	重金属离子	As³⁺	转录因子ArsR、转录信号放大器	0.1 ppb	0.1-5 ppb	[32]
		Cd²⁺	转录因子CadR	0.39 μg/L	0-60 μg/L	[10]
		As³⁺	II型CRISPR系统		0-32 μM	[17]
		U⁶⁺	双组分系统UzcRS-UrpRS、AND gate、天然系统活性放大器	1 μM	1-5.2 μM	[33]
		Hg²⁺	toehold开关、转录因子MerR	5 nM	5-7.5 nM	[34]
		Au³⁺	转录因子HspR、重组酶系统	5 μM	5-100 μM	[35]
		Cu²⁺	P _CopA 启动子		0-50 mM	[36]
	爆炸残留物	2,4-DNT	yqjF启动子	4.8 mg/L	4.8-25 mg/L	[37]
	爆炸残留物	TNT	TNT核糖开关，记忆开关	25 μM		[38]
	农药	2-苯基苯酚	转录因子HbpR、转录信号放大器	1 μM	1-50 μM	[39]
	有机污染物	单环芳烃	双组分系统TodTS	0.04 mg/L	0.04-1 mg/L	[40]
	有机污染物	甲醇	双组分系统MxcQZ-OmpR		0-0.05%	[41]
	环境病原细菌	AHL	转录因子QscR	0.01 μM	0.01-5 μM	[42]
医学诊疗	监测体液物质	孕酮	从头设计转录因子DLA	0.16 μg/L	0.16- 60 μg/L	[43]
		人血清中的锌	转录因子ZntR、Zur		0-20 μM	[44]
		大麻素类化合物	基于CB2受体的酵母GPCR	1 nM		[45]
	检测疾病标志物以诊断疾病	转化生长因子-β	双组分系统Smad	0.024 ng/mL	0.024- 6.25 ng/mL	[15]
		胆盐	人工跨膜转录因子CadC-TcpP	28.3 μM	28.3- 58.99 μM	[46]
		血红素	转录因子HrtR，拨动开关	0.12 ppm		[47]
		肠炎标志物NO	转录因子NorR，重组酶记忆模块	30 μM		[48]
		RNA	CRISPR-Cas13a/C2c2系统			[49]
		DNA	CRISPR-Cas12a系统			[50]
	传感并治疗疾病	血液脂肪酸	人工转录因子LSR	5 μM	5-100 μM	[51]
		霍乱弧菌群体感应信号CAI-1	人工转录因子HR	细胞密度10⁸ CFU/ml		[52]
		原儿茶酸	转录因子 PcaV		0-1000 μM	[53]
		硫代硫酸盐	双组分系统 ThsRS	0.016 mM	0.016-1 mM	[54]
		阿司匹林	复合转录因子Myr-NPR1/NPR4-VanR-VP16		10-250 μM	[55]
		硝酸甘油	级联生化反应和转录因子CREB	75 µM		[56]
	调节肠道生态	鼠李糖、硫酸软骨素、IPTG	转录因子RhaR和LacI、双组分系统BT3334- BT0267、 CRISPR记忆模块	0.3 mM; 0.01 mM; 6 μM		[57]
生物制造	检测目标产物产量辅助菌株筛选	L-赖氨酸	转录因子LysG	40 mM	40-320 mM	[12]
		L-半胱氨酸	转录因子CcdR		0-50 mM	[58]
		苹果酸	转录因子MalR	5 g/L	5-15 g/L	[59]
	代谢动态调控	半乳糖醛酸	转录因子ExuR		1-100 mg/L	[60]
		葡萄糖	转录因子Mlc			[14]
		L-赖氨酸	转录因子LysG		0.05-8 mM	[61]
		长链脂肪酸	转录因子FadR、TetR			[62]
	优化发酵参数	L-乳酸、D-乳酸	转录因子EcLldR、PfPdhR		15-200 mM；0-50 mM	[13]
	辅助酶的定向进化	乳果糖	转录因子LacI-L5	5 μM	10-500 μM	[63]
		茶碱	茶碱核糖开关	10 μM	10-1000 μM	[64]
		生物碱	转录因子RamR		1-100 μM	[65]
		4'-O-甲基去甲酰胺	转录因子RamR	2.5 μM	2.5-100 μM	[66]
食品安全	检测食物毒性物质	腐胺	转录因子PuuR	5.37 mM		[67]
		毒素黄素	转录因子ToxR	50 nM	50-500 nM	[68]
		组胺	转录因子HinK	0.39 ppm	0.28-18 ppm	[69]
		四环素	转录因子TetR、聚合酶链回收（PSR）放大线路	12 ppb		[70]
	食品质量控制	柚皮素	柚皮素核糖开关		0-0.6 mM	[71]
细胞调控	调控细胞分裂与运动	光照	转录因子LexRO、基因逻辑门	0.059 mW/cm²		[72]

图1 基于转录调控蛋白的合成生物传感器信号识别机制与应用（a-c）基于变构转录因子、跨膜转录因子和双组分系统的传感器信号识别机制；（d）激活和抑制型转录因子传感器的响应曲线（e）感应硫代硫酸盐的双组分系统ThsRS传感器基因线路示意图［54］；（f）监测葡萄糖摄取率的转录因子生物传感器基因线路示意图［14］；（g）基于靶标依赖性拆分T7 RNA聚合酶的生物传感器基因线路示意图［95］。（TF： Transcriptional factor； HK： Histidine kinase； RR： Response regulator； GOI： Gene of interest.）

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].

图2 基于核糖开关的合成生物传感器信号识别机制（a）转录激活型和转录抑制型核糖开关传感器信号识别机制；（b）翻译激活型和翻译抑制型核糖开关传感器信号识别机制。

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..

图3 基于核糖核酸调节子的合成生物传感器信号识别机制与应用（a） toehold开关信号识别机制［124］；（b）核酶传感平台RENDR的基因线路示意图［125］；（c）利用分裂核酶报告土壤中细菌DNA转移的基因线路示意图［133］；（d） I型断裂内含子反式剪接系统SENTR的信号识别机制以及传感细胞内目标mRNA分子的原理示意图［122］。（RENDER： Ribozyme-ENabled Detection of RNA；SENTR： Split-intron-enabled trans-splicing riboregulators.）

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].

图4 基于CRISPR技术的合成生物传感器信号识别机制（a）基于II型CRISPR系统重编程tracrRNA的细胞内RNA传感原理与应用案例［17］；（b）基于RNA触发RNA加工的传感系统［142］；（c）基于链置换反应的RNA传感［143］。（UAS： Upstream activating sequence； PAM： Protospacer adjacent motif； IHF： Integration host factor）

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].

表2 基于基因线路的合成生物传感器不同信号识别机制与优劣势

Table 2 Advantages and limitations of genetic circuit-enabled synthetic biosensors based on different signal recognition mechanisms

信号识别机制	优势	劣势
变构转录因子	信号识别元件和工程化优化改造手段丰富，调控机制简单，可监测胞内代谢物	细胞代谢负担大，响应速度慢，天然元件性能低下依赖人工优化
原核生物双组分系统	检测信号广谱，可响应细胞外环境	工程化改造困难，信号转导依赖胞内环境，元件串扰大特异性较低，宿主兼容性差
核糖开关	可编程性高，细胞代谢负担低，响应快速，特异性高	受胞内环境干扰较大，开关比率低，优化手段较少，检测靶标类型有限
核糖核酸调节子	可编程性与正交性高，跨体系适配性优异，设计与优化便捷，响应快速，细胞代谢负担低	全细胞环境中敏感性、稳定性低，检测靶标单一
CRISPR系统	可编程性与正交性高，特异性高，传感功能丰富	泄漏水平较高，检测内源mRNA案例少，存在脱靶效应与细胞毒性

图5 典型合成生物传感信号记忆模块的设计原理（a）基于拨动开关的生物记忆模块基因线路示意图；（b）基于重组酶翻转机制的锌离子记忆模块基因线路示意图［153］；（c）基于CRISPR/Cas的CAMERA细胞环境信号记录系统原理示意图［158］；（d）基于CRISPR/Cas的DNA感知记录模块（CATCH）基因线路示意图［159］。（TF： Transcriptional factor； TR： Transcriptional repressor.）

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].

图6 基于多层次生物计算模块的生物传感基因线路设计与应用（a）基于AND逻辑门构建的双输入生物传感器基因线路示意图及其响应热图［104］（b）整合多靶标输入的代谢调控传感器基因线路示意图［163］。

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];

图7 与多种检测平台耦合的多模态输出合成生物传感系统设计（a）琼脂糖水凝胶封装砷离子传感器阵列，实现砷污染检测智能手机平台可视化阵列显示［32］；（b）通过细菌空间运动图案实现生物传感信号的可视化输出［36］；（c）荧光传感器与光电芯片耦合，将光信号转为无线信号输出［48］。

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].

图8 合成生物传感器的敏感性优化策略（a）基于基因线路的合成生物传感器的典型响应曲线和特征；（b）基于启动子工程的动态范围优化机制；（c）通过生物识别元件浓度梯度调节与靶标富集技术降低检测限；（d）利用基于激活转录因子、正反馈回路和双抑制因子的传感信号放大器优化动态范围［7］；（e）利用反义RNA转录介导的翻译阻断、诱饵DNA结合位点竞争性抑制、引入输出蛋白降解标签减少传感器泄漏［1］。（R： Regulator； OR： Operator site for regulator； TF： Transcriptional factor； TA： Transcriptional activator； TR： Transcriptional repressor.）

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].

图9 合成生物传感器的特异性优化策略（a）对转录因子LysG进行半理性设计与饱和突变，使其不结合L-赖氨酸（L-Lys），同时保持其L-组氨酸（L-His）和L-精氨酸（L-Arg）结合能力［191］；（b）对TynA-FeaR传感系统进行半理性设计与饱和突变，使其特异性检测苯乙胺。（DA：多巴胺；PEA：苯乙胺；Tyra：酪胺；Trypta：色胺）［192］；（c）将转录因子ZraR、ZntR通过AND gate耦合后特异性响应Zn2+［7，21］。

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].

图10 合成生物传感器的响应速度优化示例（a）基于大肠杆菌合成电子传递链的传感器设计，通过控制蛋白导电开关快速检测内分泌干扰素4-hydroxytamoxifen （4-HT）［6］；（b）快速激活和失活的蛋白质磷酸化信号转导网络的可逆性响应动力学曲线以及传感机制［197］。（IM： Inner membrane； OM： Outer membrane； PC： Phospho-couple）

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].

图11 基于基因线路的合成生物传感器稳定性和生物安全性优化示例（a）一种基于翻译起始因子动态调控的大肠杆菌质粒拷贝数控制及遗传稳定性提升方法［204］；（b）一种响应化学诱导剂无水四环素（aTc）和温度变化的CRISPR-Cas9大肠杆菌双模态杀伤开关设计（CRISPRks）［212］。

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].

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