Engineered bacterial S-layer enhanced high electron mobility transistor sensors for ultrasensitive detection of tumor antigen

Journal Article (2026)
Author(s)

Jingya Tang (Chinese Academy of Sciences)

Chenyang Yang (Chinese Academy of Sciences)

Jianwen Sun (Tsinghua University)

Zhe Li (Precision Scientific (Beijing) Co. Ltd.)

Yue Men (Fujian Agriculture and Forestry University)

Zewen Liu (Tsinghua University)

Guoqi Zhang (TU Delft - Electronic Components, Technology and Materials)

Xian En Zhang (Shenzhen University of Advanced Technology)

Dian Bing Wang (Institute of Biophysics Chinese Academy of Sciences)

Research Group
Electronic Components, Technology and Materials
DOI related publication
https://doi.org/10.1016/j.bios.2026.118382
More Info
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Publication Year
2026
Language
English
Research Group
Electronic Components, Technology and Materials
Journal title
Biosensors and Bioelectronics
Volume number
298
Article number
118382
Downloads counter
28
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Abstract

Ultrasensitive and specific detection of low-abundance tumor biomarkers remains a major challenge for early and minimally invasive cancer diagnosis. Here, we present a high-performance biosensing platform that integrates a genetically engineered bacterial S-layer with an AlGaN/GaN high-electron-mobility transistor (HEMT) sensor for label-free detection of tumor antigens. As a proof-of-concept, the ovarian cancer antigen human epididymis protein 4 (HE4) was selected . Specifically, the S-layer protein rSbpA was fused with HE4-specific nanobody 1G8 to construct a bifunctional membrane capable of self-assembling into an ordered biorecognition layer on the sensor surface. Compared to conventional chemical crosslinking, S-layer-driven assembly increased antibody loading by 50 % and minimized nonspecific adsorption in plasma environments. The resulting HEMT sensor detected HE4 across a dynamic linear range (10−21 to 10−14 M), identifying patients with ovarian cancer with 100 % diagnostic accuracy (AUC = 1.0). This study establishes a versatile and modular biosensing strategy for ultra-low-abundance biomarker detection with broad potential applications in the precision diagnostics of cancer and other diseases.