Linker-Preserved Iron Metal-Organic Framework-Based Lateral Flow Assay for Sensitive Transglutaminase 2 Detection in Urine Through Machine Learning-Assisted Colorimetric Analysis

A groundbreaking demonstration of the utilization of the metal-organic framework MIL-101(Fe) as an exceptionally perceptive visual label in colorimetric lateral flow assays (LFA) is described. This pioneering approach enables the precise identification of transglutaminase 2 (TGM2), a recognized biomarker for chronic kidney disease (CKD), in urine specimens, which offers a remarkably sensitive naked-eye detection mechanism. The surface of MIL-101(Fe) was modified with oxalyl chloride, adipoyl chloride, and poly(acrylic) acid (PAA); these not only improved the labeling material stability in a complex matrix but also achieved a systematic control in the detection limit of the TGM2 concentration using our LFA platform. The advanced LFA with the MIL-101(Fe)-PAA label can detect TGM2 concentrations down to 0.012, 0.009, and 0.010 nM in Tris-HCl buffer, urine, and desalted urine, respectively, which are approximately 55-fold lower than those for a conventional AuNP-based LFAs. Aside from rapid TGM2 detection (i.e., within 20 min), the performance of the MIL-101(Fe)-PAA-based LFA on reproducibility [coefficients of variation (CV) < 2.9%] and recovery (95.9-103.2%) along with storage stability within 25 days of observation (CV < 6.0%) shows an acceptable parameter range for quantitative analysis. A sophisticated sensing method grounded in machine learning principles was also developed, specifically aimed at precisely deducing the TGM2 concentration by analyzing immunoreaction sites. More importantly, our developed LFA offers potential for clinical measurement of TGM2 concentration in normal human urine and CKD patients' samples.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:9

Enthalten in:

ACS sensors - 9(2024), 3 vom: 22. März, Seite 1321-1330

Sprache:

Englisch

Beteiligte Personen:

Supianto, Mulya [VerfasserIn]
Yoo, Dong Kyu [VerfasserIn]
Hwang, Hagyeong [VerfasserIn]
Oh, Han Bin [VerfasserIn]
Jhung, Sung Hwa [VerfasserIn]
Lee, Hye Jin [VerfasserIn]

Links:

Volltext

Themen:

E1UOL152H7
EC 2.3.2.13
Iron
Journal Article
Lateral flow assay
MIL-101
Machine learning
Metal−organic framework
Metal-Organic Frameworks
Naked-eye detection
Protein Glutamine gamma Glutamyltransferase 2
Transglutaminase 2
Urine sample

Anmerkungen:

Date Completed 25.03.2024

Date Revised 28.03.2024

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1021/acssensors.3c02250

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM369608445