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The microsomal epoxide hydrolase (mEH) is important in the detoxification of carcinogens in the liver and other tissues but is also a blood biomarker of hepatitis and liver cancer. Improved analytical methods are needed for the study of its role in the metabolism of xenobiotics and endogenous roles as a blood biomarker of diseases. The development of a double nanobody sandwich ELISA offers significant improvements over traditional polyclonal or monoclonal antibody-based assays, enhancing both the homogeneity and the stability of assay production. This study focuses on selecting and optimizing nanobody pairs for detecting human mEH. Four high-affinity nanobodies were identified and tested for thermal stability. Combinations of these nanobodies were evaluated, revealing that the MQ4− MQ30 pair achieved the best performance with a limit of detection (LOD) of 1 ng/mL. Additionally, polyHRP was also employed for signal amplification, enhancing detection capabilities despite challenges related to the small size and single epitope recognition of the nanobodies. Comparative studies using microplates and NHS@MF membranes were also performed. The superior performance of the NHS@MF membranes highlighted their potential as a promising alternative for pointof-care testing. The assay exhibited high specificity for human mEH and minimal cross-reactivity with related enzymes and effectively addressed matrix effects in plasma and tissue samples. These findings underscore the potential of double nanobody sandwich ELISAs for reliable and sensitive biomarker detection.
The microsomal epoxide hydrolase (mEH) is important in the detoxification of carcinogens in the liver and other tissues but is also a blood biomarker of hepatitis and liver cancer. Improved analytical methods are needed for the study of its role in the metabolism of xenobiotics and endogenous roles as a blood biomarker of diseases. The development of a double nanobody sandwich ELISA offers significant improvements over traditional polyclonal or monoclonal antibody-based assays, enhancing both the homogeneity and the stability of assay production. This study focuses on selecting and optimizing nanobody pairs for detecting human mEH. Four high-affinity nanobodies were identified and tested for thermal stability. Combinations of these nanobodies were evaluated, revealing that the MQ4− MQ30 pair achieved the best performance with a limit of detection (LOD) of 1 ng/mL. Additionally, polyHRP was also employed for signal amplification, enhancing detection capabilities despite challenges related to the small size and single epitope recognition of the nanobodies. Comparative studies using microplates and NHS@MF membranes were also performed. The superior performance of the NHS@MF membranes highlighted their potential as a promising alternative for pointof-care testing. The assay exhibited high specificity for human mEH and minimal cross-reactivity with related enzymes and effectively addressed matrix effects in plasma and tissue samples. These findings underscore the potential of double nanobody sandwich ELISAs for reliable and sensitive biomarker detection.
Surface-enhanced Raman scattering (SERS) is a powerful optical sensing platform that amplifies the target signals by Raman scattering. Despite SERS enabling a meager detection limit, even at the single-molecule level, SERS also tends to equally enhance unwanted molecules due to the non-specific binding of noise molecules in clinical samples, which complicates its use in complex samples such as bodily fluids, environmental water, or food matrices. To address this, we developed a novel non-fouling biomimetic SERS sensor by self-assembling an anti-adhesive, anti-fouling, and size-selective Lubricin (LUB) coating on gold nanoparticle (AuNP) functionalized glass slide surfaces via a simple drop-casting method. Compared to a conventional AuNPs-SERS substrate, the biomimetic SERS meets the requirements of simple preparation and enables direct droplet detection without any sample pre-treatment. Atomic force microscopy was used to confirm the self-assembled Lubricin coating on the AuNP surface, acting as an anti-fouling and size-selective protection layer. A series of Raman spectra were collected using melamine as the target analyte, which was spiked into 150 mM NaCl solution or undiluted milk. It was demonstrated that the LUB coating effectively prevents the detrimental fouling generated by the proteins and fats in milk, ensuring the clear detection of melamine. Our sensor showed high selectivity and could detect melamine in milk at concentrations as low as 1 ppm. Given that the EU/US legal limit for melamine in food is 2.5 ppm, this sensor offers a promising, cost-effective solution for routine screening and has potential applications for detecting food adulteration in the food safety, environmental monitoring, aquaculture, and biomedical fields.
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