ArticleBiosensors & bioelectronics2022
Protein sensors combining both on-and-off model for antibody homogeneous assay.
Article in Biosensors & bioelectronics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Advancing protein biosensors: redefining detection through innovations in materials, mechanisms, and applications for precision medicine and global diagnostics.RSC advances · 2025Review
- Advances in Surrogate Neutralization Tests for High-Throughput Screening and the Point-of-Care.Analytical chemistry · 2025Review
- Article
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Authors and funding
16 authors.
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Abstract
Protein sensors based on allosteric enzymes responding to target binding with rapid changes in enzymatic activity are potential tools for homogeneous assays. However, a high signal-to-noise ratio (S/N) is difficult to achieve in their construction. A high S/N is critical to discriminate signals from the background, a phenomenon that might largely vary among serum samples from different individuals. Herein, based on the modularized luciferase NanoLuc, we designed a novel biosensor called NanoSwitch. This sensor allows direct detection of antibodies in 1 μl serum in 45 min without washing steps. In the detection of Flag and HA antibodies, NanoSwitches respond to antibodies with S/N ratios of 33-fold and 42-fold, respectively. Further, we constructed a NanoSwitch for detecting SARS-CoV-2-specific antibodies, which showed over 200-fold S/N in serum samples. High S/N was achieved by a new working model, combining the turn-off of the sensor with human serum albumin and turn-on with a specific antibody. Also, we constructed NanoSwitches for detecting antibodies against the core protein of hepatitis C virus (HCV) and gp41 of the human immunodeficiency virus (HIV). Interestingly, these sensors demonstrated a high S/N and good performance in the assays of clinical samples; this was partly attributed to the combination of off-and-on models. In summary, we provide a novel type of protein sensor and a working model that potentially guides new sensor design with better performance.
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