Issue 20, 2024

Highly sensitive CD40L protein discrimination via label-free fiber sensing technologies

Abstract

The recombinant Cluster of Differentiation 40 Ligand (CD40L) can be expressed in various cells and is closely related to various types of cancer. This association underscores the critical need for expedited and precise measurement of CD40L levels in clinical fluid specimens. A novel optical fiber biosensor has been devised, employing single-mode fibers that are sandwiched around a coreless fiber, with the diameter refined by etching with hydrogen fluoride. This innovative configuration allows for light transmission through the evanescent field, thereby enhancing the sensor's sensitivity to changes in the surrounding refractive index. Employing chemical binding techniques, CD40 was securely immobilized onto the fiber's surface, facilitating the detection of CD40L. The sensor exhibited a sensitivity of 1.126 nm (μg mL−1)−1 and a detection limit of 0.68 nM. Furthermore, the sensor's specificity for CD40L was validated using authentic clinical serum samples spiked with artificial analytes. In addition, the specificity of CD40L of the proposed sensor was proved using natural clinical serum samples with added artificial analyte, assisted by the ELISA method, and the results ideally conformed with the detection of standard samples. With the aid of the ELISA method, the outcomes were found to be in excellent agreement with those from standard sample detection. Consequently, the findings indicate that this sensor provides a specific, label-free, and highly sensitive method for CD40L detection, showcasing its significant potential for applications in molecular biology research.

Graphical abstract: Highly sensitive CD40L protein discrimination via label-free fiber sensing technologies

Supplementary files

Article information

Article type
Paper
Submitted
19 Jun 2024
Accepted
06 Aug 2024
First published
16 Aug 2024

Analyst, 2024,149, 5014-5021

Highly sensitive CD40L protein discrimination via label-free fiber sensing technologies

M. Hu, X. Li, Y. Li, R. Wang, T. Kang, F. Xu, J. Bai, M. Jiang and Y. Zhu, Analyst, 2024, 149, 5014 DOI: 10.1039/D4AN00867G

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