DOI 10.1016/j.synbio.2026.09.006
Advances and perspectives in genetically encoded biosensors for biomarker detection and theranostic circuits.
Аннотация
Effective biomarker detection is critical for timely and accurate clinical disease diagnosis. However, conventional analytical methodologies are often constrained by laborious procedures, reliance on specialized equipment, and an inherent inability to perform continuous in situ monitoring. To circumvent these limitations, synthetic biology has pioneered the development of genetically encoded biosensors as a rapid, highly sensitive, and cost-effective alternative. This review specifically focuses on transcriptional regulation-based biosensors, primarily those utilizing allosteric transcription factors (aTFs) and two-component systems (TCSs). By integrating these regulatory sensing modules into engineered microbial chassis, researchers can achieve continuous, real-time biomarker monitoring even within complex and otherwise inaccessible physiological environments. This review particularly focuses on microbial chassis rather than mammalian systems due to their highly tractable genetics, rapid response kinetics, and their unique potential to be deployed as autonomous living probiotics for in situ theranostics. Furthermore, coupling these sensors with engineered actuator genes enables the construction of intelligent therapeutic genetic circuits. This closed-loop theranostic paradigm facilitates simultaneous, real-time diagnosis and autonomous, localized therapeutic interventions, paving the way for personalized and dose-adaptive precision medicine. Finally, we summarize recent advancements in these biosensor platforms, explore their applications in targeted disease interventions, and discuss the contemporary challenges alongside future perspectives for their clinical translation.
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.