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Porous Silicon Fabry-Pérot Interferometer for N -Acetyl-β-d-Glucosaminidase Biomarker Monitoring.

Authors :
Kumar DN
Pinker N
Shtenberg G
Source :
ACS sensors [ACS Sens] 2020 Jul 24; Vol. 5 (7), pp. 1969-1976. Date of Electronic Publication: 2020 Jul 02.
Publication Year :
2020

Abstract

Bovine mastitis (BM) is a prominent inflammatory disease affecting the dairy industry worldwide, originated by pathogenic agent invasion onto the mammary gland. Early detection of new BM cases is of high importance for infection control within the herd. Conventional analytical techniques lack the ability to detect BM-predicting biomarkers, used as analytical indicators for health status evaluation, in real time or outside the laboratory boundaries. Herein, we describe a biosensing platform for label-free detection and identification of BM onset through targeting N -acetyl-β-d-glucosaminidase (NAGase) for potential evidence-based therapy. The lysosomal activity in dissimilar milk qualities was monitored by a gelatin-functionalized porous Si Fabry-Pérot interferometer, while estimating the biochemical reaction precipitating products within the nanostructure. The optical response was proportional to the inherent NAGase concentration found in real milk samples, influenced by two dominant BM causative pathogens (i.e., Escherichia coli and Streptococcus dysgalactiae ) at various somatic cell counts. Quantitative analysis of NAGase levels within the entire inflammatory spectrum (healthy, subclinical, and clinical BM) was obtained within the range of 1.0-4.2 μM/min (enzymatic activity per volume unit), while presenting a detection limit of 0.51 μM/min. The optical performances correspond with standardized biochemical activity assay in dissimilar milk qualities. Overall, the presented sensing concept exhibits the potential of BM-predicting biomarker detection using a simple and portable experimental setup for convenient early biodiagnostics and health status evaluation.

Details

Language :
English
ISSN :
2379-3694
Volume :
5
Issue :
7
Database :
MEDLINE
Journal :
ACS sensors
Publication Type :
Academic Journal
Accession number :
32573203
Full Text :
https://doi.org/10.1021/acssensors.0c00348