Electrochemical peptide-based biosensor for the detection of the inflammatory disease biomarker, interleukin-1beta
- Authors
- Yang, Hyo Jeong; Raju, Chikkili Venkateswara; Choi, Chang-Hyung; Park, Jong Pil
- Issue Date
- Mar-2024
- Publisher
- Elsevier B.V.
- Keywords
- Affinity peptide; Au–Ag@MoS2/rGO; Clinical diagnosis; Crohn's disease; Electrochemical biosensor
- Citation
- Analytica Chimica Acta, v.1295
- Journal Title
- Analytica Chimica Acta
- Volume
- 1295
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/72777
- DOI
- 10.1016/j.aca.2024.342287
- ISSN
- 0003-2670
1873-4324
- Abstract
- This paper reports the development of a highly sensitive and selective electrochemical peptide-based biosensor for the detection of the inflammatory disease biomarker, interleukin-1beta (IL-1β). To this end, flower-like Au–Ag@MoS2-rGO nanocomposites were used as the signal amplification platform to achieve a label-free biosensor with a high sensitivity and selectivity. First, a high-affinity peptide for IL-1β was identified through biopanning with M13 random peptide libraries, and was newly designed by incorporating cysteine at the C-terminus. An IL-1β specific binding peptide was used as the bio-receptor, and the interaction between the IL-1β binding peptide and IL-1β was confirmed via enzyme-linked immunosorbent assay and various physicochemical and electrochemical analyses. Under optimal conditions, the biosensor achieved an ultrasensitive and specific IL-1β detection in a wide linear concentration range of 0–250 ng/mL with a picomolar-level detection limit (∼2.4 pM), low binding constant (∼0.62 pM), and a low coefficient of variation (<1.65 %). The biosensor was successfully utilized for IL-1β determination in the serum of Crohn's disease patients with a good correlation coefficient. In addition, the detection performance was comparable to that of commercially available IL-1β ELISA kit. This indicates that the electrochemical peptide-based biosensor may offer a potentially valuable platform for the clinical diagnosis of various inflammatory disease biomarkers. © 2024 Elsevier B.V.
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