Back to Search Start Over

Labeling on a Chip of Cellular Fibronectin and Matrix Metallopeptidase-9 in Human Serum

Authors :
Briliant Adhi Prabowo
Carole Sousa
Susana Cardoso
Paulo Freitas
Elisabete Fernandes
Source :
Micromachines, Vol 13, Iss 10, p 1722 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

We present a microfluidic chip for protein labeling in the human serum-based matrix. Serum is a complex sample matrix that contains a variety of proteins, and a matrix is used in many clinical tests. In this study, the device performance was tested using commercial serum samples from healthy donors spiked with the following target proteins: cellular fibronectin (c-Fn) and matrix metallopeptidase 9 (MMP9). The microfluidic molds were fabricated using micro milling on acrylic and using stereolithography (SLA) three-dimensional (3D) printing for an alternative method and comparison. A simple quality control was performed for both fabrication mold methods to inspect the channel height of the chip that plays a critical role in the labeling process. The fabricated microfluidic chip shows a good reproducibility and repeatability of the performance for the optimized channel height of 150 µm. The spiked proteins of c-Fn and MMP9 in the human serum-based matrix, were successfully labeled by the functionalized magnetic nanoparticles (MNPs). The biomarker labeling occurring in the serum was compared using a simple matrix sample: phosphate buffer. The measured signals obtained by using a magnetoresistive (MR) biochip platform showed that the labeling using the proposed microfluidic chip is in good agreement for both matrixes, i.e., the analytical performance (sensitivity) obtained with the serum, near the relevant cutoff values, is within the uncertainty of the measurements obtained with a simple and more controlled matrix: phosphate buffer. This finding is promising for stroke patient stratification where these biomarkers are found at high concentrations in the serum.

Details

Language :
English
ISSN :
13101722 and 2072666X
Volume :
13
Issue :
10
Database :
Directory of Open Access Journals
Journal :
Micromachines
Publication Type :
Academic Journal
Accession number :
edsdoj.b01f2afff6a54644901a53521e50cd7e
Document Type :
article
Full Text :
https://doi.org/10.3390/mi13101722