Creatinine measurement is central to renal diagnostics and is routinely performed using urine samples. However, conventional approaches such as the Jaffé reaction suffer from interference, while electrochemical biosensors typically require reference electrodes that increase system complexity, size, and cost. Although chemiresistive sensors offer a simpler architecture, high-performance detection in liquid environments remains significantly less explored, particularly when sensitivity, selectivity, and stability must be achieved simultaneously.
Researchers from Tohoku University in Japan, with collaboration from the City College of New York, reported the study in a 2026 article published (DOI: 10.1038/s41378-025-01155-3) in Microsystems & Nanoengineering. The team developed a creatinine biosensor based on a platinum nanoparticle–polymer composite functionalized with three enzymes. Instead of depending on a conventional reference electrode, the device reads how enzyme-generated hydrogen peroxide reshapes charge transport within the nanocomposite, producing a creatinine-dependent electrical signal in a simplified two-electrode format. A key design feature is that the nanoparticle network is tuned near the percolation threshold, where small redox-induced perturbations drastically reconfigure conduction pathways through hopping and tunneling mechanisms.
The sensor spans a 10-μm electrode gap and detects creatinine concentrations from 1 to 300 mg/dL, covering clinically relevant urinary levels. Direct-current measurements show a response time of approximately 35 seconds, with signal magnitude increasing monotonically with concentration.
Impedance spectroscopy further reveals that the most sensitive response arises from a high-frequency charge-transport resistance component, indicating that fast interfacial electron-transfer processes dominate the sensing mechanism. Control experiments without enzymes show negligible response, confirming that biochemical recognition governs signal generation.
Beyond creatinine detection, this work demonstrates a general strategy for simplifying biosensing architectures without compromising performance. By combining enzymatic specificity with a percolation-tuned nanomaterial network, the system separates signal generation (biology) from signal amplification (materials physics). This principle could enable a new class of compact, low-cost, and disposable biosensors suitable for real-time monitoring and point-of-care applications.
The approach is readily extendable to other biomarkers by modifying the recognition chemistry, suggesting broad applicability for personalized diagnostics. Its small sample volume and simple two-electrode design make it particularly attractive for portable and home-use systems, including applications requiring normalization of urinary biomarkers using creatinine.
Future work will focus on validation in real biological samples, such as urine and blood, to confirm robustness under practical conditions.
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References
DOI
10.48130/biocontam-0025-0016
Original Source URL
https://doi.org/10.1038/s41378-025-01155-3
Funding Information
This work was supported in part by the Micro/Nanomachining Education Center (MNC), Tohoku University and Micro System Integration Center (μSiC), Tohoku University. This work was supported by JST SPRING, Grant Number JPMJSP2114, the Japan Agency for Medical Research and Development (AMED), Grant No. JP21zf0127001, Grant-in-Aid for Transformative Research Areas, Grant No. 24H02231, Grant-in-Aid for Scientific Research (B), Grant No. 25K01142, Adopting Sustainable Partnerships for Innovative Research Ecosystem in Semiconductor area, Grant No. JPMJAP2413.
About Microsystems & Nanoengineering
Microsystems & Nanoengineering is an online-only, open access international journal devoted to publishing original research results and reviews on all aspects of Micro and Nano Electro Mechanical Systems from fundamental to applied research. The journal is published by Springer Nature in partnership with the Aerospace Information Research Institute, Chinese Academy of Sciences, supported by the State Key Laboratory of Transducer Technology.