1.山东大学,微生物改造技术全国重点实验室,山东 青岛 266237
2.上海交通大学生命科学技术学院,微生物代谢国家重点实验室,上海 200240
侯爽(2000—),女,博士研究生。研究方向为生物传感器。
康照琪(1995—),男,博士后。研究方向为生物传感器。
高超(1981—),男,教授,博士生导师。研究方向为微生物生理与代谢、生物催化、系统代谢工程。
收稿:2026-04-30,
修回:2026-06-20,
网络首发:2026-06-23,
移动端阅览
侯爽, 康照琪, 刘一东, 吕传娟, 许平, 马翠卿, 高超. 基于合成生物学的环境污染物传感研究进展[J]. 合成生物学, 2026, 7. DOI: 10.12211/2096-8280.2026-033
HOU Shuang, KANG Zhaoqi, LIU Yidong, LÜ Chuanjuan, XU Ping, MA Cuiqing, GAO Chao. Advances in environmental pollutant sensing based on synthetic biology[J]. Synthetic Biology Journal, 2026, 7. DOI: 10.12211/2096-8280.2026-033
侯爽, 康照琪, 刘一东, 吕传娟, 许平, 马翠卿, 高超. 基于合成生物学的环境污染物传感研究进展[J]. 合成生物学, 2026, 7. DOI: 10.12211/2096-8280.2026-033 DOI:
HOU Shuang, KANG Zhaoqi, LIU Yidong, LÜ Chuanjuan, XU Ping, MA Cuiqing, GAO Chao. Advances in environmental pollutant sensing based on synthetic biology[J]. Synthetic Biology Journal, 2026, 7. DOI: 10.12211/2096-8280.2026-033 DOI:
当前全球环境污染呈现传统污染负荷居高不下与新污染风险持续凸显的复合特征。即时、原位、精准的环境污染物检测是评估生态风险、制定治理策略的关键。传统分析方法受设备昂贵、操作繁琐、分析周期长等限制,难以满足现场监测与大规模环境筛查的需求。基于合成生物学的生物传感器通过基因回路设计、蛋白质工程、功能模块组装等手段,可特异性识别污染物并将其浓度信息转化为可量化的理化信号,兼具高效、便捷与低成本等优势,为环境监测提供了创新手段。本文梳理了合成生物传感器的主要类型与工作原理,着重阐述其在重金属、无机非金属、有机物及病原微生物检测中的研究进展。同时,探讨了此类技术在追踪污染物的降解转化、空间分布、介质迁移、毒理效应等环境动态过程中的应用潜力,总结了其在实际应用中的优势与挑战。最后,本文展望了未来该领域需强化与人工智能、功能材料等多学科交叉,着力突破识别谱系有限、元件稳定性不足等瓶颈,为生态环境风险的精准预警与智能化管控提供关键技术支撑。
Global environmental pollution is currently a multifaceted challenge
exacerbated by the persistence of legacy pollutants and the growing threat of emerging contaminants. These substances originate primarily from anthropogenic activities and can accumulate in ecosystems through atmospheric deposition
aquatic transport
and biomagnification
ultimately leading to widespread systemic toxicity. Rapid
in situ
and precise pollution detection is essential for assessing ecological risks and formulating effective remediation strategies. However
traditional analytical methods
such as chromatography and mass spectrometry
remain challenging to apply to on-site testing and large-scale screening due to expensive equipment
labor-intensive sample preparation
and delayed readouts. Synthetic biology-enabled biosensors offer a reliable approach to environmental monitoring. These biosensors integrate genetic circuit design
protein engineering
and functional module assembly to specifically detect pollutants and convert concentration information into quantifiable physicochemical signals
providing improved detection efficiency
operational simplicity
and cost-effectiveness. By decoupling recognition
transduction
and output modules
these platforms can be tailored to different targets
sample matrices
and de
ployment scenarios while retaining a clear design logic. Crucially
these platforms are compatible with portable devices
supporting rapid field deployment
continuous
in situ
monitoring
and high-throughput analysis of environmental samples. In this review
we categorize the main types of synthetic biosensors and elucidate their core signal recognition and transduction mechanisms. We highlight recent advances in the use of these biosensors for detecting heavy metals
inorganic non-metal pollutants
organic compounds
and pathogenic microorganisms. Furthermore
we explore the application value of these platforms in tracking dynamic environmental pollution processes
including biodegradation kinetics
spatial distribution
cross-media migration
toxicological effects
and intelligent targeted bioremediation. We then discuss the advantages
challenges
and future directions of synthetic biosensors in environmental analysis
focusing on recognition element customization
process-level monitoring
field system integration
biosafety
and intelligent data interpretation. These advances may help synthetic biosensors move beyond single-target detection and support integrated environmental risk sensing
early warning
and remediation assessment.
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