Innovative Peptide-Based Plasmonic Optical Biosensor for the Determination of Cholesterol

Plasmonic-based biosensors have gained prominence as potent optical biosensing platforms in both scientific and medical research, attributable to their enhanced sensitivity and precision in detecting biomolecular and chemical interactions. However, the detection of low molecular weight analytes with high sensitivity and specificity remains a complex and unresolved issue, posing significant limitations for the advancement of clinical diagnostic tools and medical device technologies. Notably, abnormal cholesterol levels are a well-established indicator of various pathological conditions; yet, the quantitative detection of the free form of cholesterol is complicated by its small molecular size, pronounced hydrophobicity, and the necessity for mediator molecules to achieve efficient sensing. In the present study, a novel strategy for cholesterol quantification was developed, leveraging a plasmonic optical readout in conjunction with a highly specific cholesterol-binding peptide (C-pept) as a biorecognition element, anchored on a functionalized silica substrate. The resulting biosensor exhibited an exceptionally low detection limit of 21.95 µM and demonstrated a linear response in the 10-200 µM range. This peptide-integrated plasmonic sensor introduces a novel one-step competitive method for cholesterol quantification, positioning itself as a highly sensitive biosensing modality for implementation within the AVAC platform, which operates using reflective dark-field microscopy.

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Publication Details

Journal
Biosensors
Published
2024-11-13
DOI
https://doi.org/10.3390/bios14110551
Citations
3
Primary Topic
Advanced biosensing and bioanalysis techniques
Type
article
Field-Weighted Citation Impact
0.70

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article

Innovative Peptide-Based Plasmonic Optical Biosensor for the Determination of Cholesterol

Óscar Ahumada, Enrico Dainese, Sergio Oddi, Virginia Cebrián et al.
3 citations
Biosensors
Advanced biosensing and bioanalysis techniques
0.70
article

Innovative Peptide-Based Plasmonic Optical Biosensor for the Determination of Cholesterol

Óscar Ahumada, Enrico Dainese, Sergio Oddi, Virginia Cebrián, Ana Lia Bernardo, Anne Parra
article en
3 citations

Abstract

Plasmonic-based biosensors have gained prominence as potent optical biosensing platforms in both scientific and medical research, attributable to their enhanced sensitivity and precision in detecting biomolecular and chemical interactions. However, the detection of low molecular weight analytes with high sensitivity and specificity remains a complex and unresolved issue, posing significant limitations for the advancement of clinical diagnostic tools and medical device technologies. Notably, abnormal cholesterol levels are a well-established indicator of various pathological conditions; yet, the quantitative detection of the free form of cholesterol is complicated by its small molecular size, pronounced hydrophobicity, and the necessity for mediator molecules to achieve efficient sensing. In the present study, a novel strategy for cholesterol quantification was developed, leveraging a plasmonic optical readout in conjunction with a highly specific cholesterol-binding peptide (C-pept) as a biorecognition element, anchored on a functionalized silica substrate. The resulting biosensor exhibited an exceptionally low detection limit of 21.95 µM and demonstrated a linear response in the 10-200 µM range. This peptide-integrated plasmonic sensor introduces a novel one-step competitive method for cholesterol quantification, positioning itself as a highly sensitive biosensing modality for implementation within the AVAC platform, which operates using reflective dark-field microscopy.

BiosensorsVol. 14(11)
University of Teramo (IT), European Brain Research Institute (IT)
European Commission, Agencia Estatal de Investigación
Openalex Percentile: Top 29%
Advanced biosensing and bioanalysis techniques
0.70
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Innovative Peptide-Based Plasmonic Optical Biosensor for the Determination of Cholesterol — Óscar Ahumada, Enrico Dainese, et al. · Biosensors (2024) | TGRS Research Map | TGRS