Smartphone-based Colorimetric Protein Quantification in Human Urine Using Gold ‎Nanoparticles ‎

Authors

  • Beatriz Quintas BIOSCOPE Research Group, LAQV LAQV-REQUIMTE, Chemistry Department, NOVA School of Science and Technology, NOVA University of Lisbon, 2829-516, Caparica, Portugal.
  • Joana Galhano BIOSCOPE Research Group, LAQV LAQV-REQUIMTE, Chemistry Department, NOVA School of Science and Technology, NOVA University of Lisbon, 28292829-516, Caparica, Portugal. & PROTEOMASS Scientific Society, 2825 2825-466, Costa de Caparica, Portugal. https://orcid.org/0000-0002-7149-1682
  • Elisabete Oliveira
  • Hugo M. Santos BIOSCOPE Research Group, LAQV LAQV-REQUIMTE, Chemistry Department, NOVA School of Science and Technology, NOVA University of Lisbon, 2829-516, Caparica, Portugal. & PROTEOMASS Scientific Society, 2825 2825-466, Costa de Caparica, Portugal. https://orcid.org/0000-0002-6032-8679

DOI:

https://doi.org/10.5584/translationalchemistry.v1i2.248

Keywords:

Protein quantification, Proteinuria, Colourimetric detection, RGB analysis, Smartphone-based analysis, Point-of-care testing

Abstract

Proteinuria, the presence of elevated protein levels in urine, is an important biomarker associated with various diseases. This study presents a portable, smartphone-based approach for colourimetric protein detection using gold nanoparticles (AuNPs). By inducing the aggregation of AuNPs in the presence of albumin, facilitated by sodium chloride, distinct colour changes were observed and quantified via smartphone image analysis. The method was tested using three smartphone models on urine samples from six volunteers, demonstrating a detection limit of 1.19 μg/mL and the ability to visually detect protein concentrations as low as 25 μg/mL. Furthermore, we successfully quantified the urinary proteome of a CRC patient, obtaining a protein concentration of 37 ± 3 μg/mL, which closely agrees with the value of 41 ± 1 μg/mL determined by the Bradford assay. This technique offers a rapid, cost-effective, and non-invasive tool for urinary protein detection, with promising applications in routine clinical diagnostics and disease monitoring.

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Published

2025-12-05