Quantitative TLC-based assay for the detection of urease inhibitors in complex mixtures.

Authors

Paul E Cotacachi-Latacumba, Mario O Salazar, I Ayelen Ramallo, Ricardo L E Furlan

Published in

Analytica chimica acta. Volume 1423. Pages 346178. Nov 15, 2026. Epub Aug 27, 2026.

Abstract

Urease inhibitors are increasingly relevant in agricultural and food chemistry because urease activity influences nitrogen-use efficiency, ammonia emissions, microbial survival, and food quality. Although numerous solution-based assays are available, no quantitative thin-layer chromatography (TLC)-based bioautographic method has been reported for detecting and localizing urease inhibitors directly within complex mixtures. This study aimed to develop and validate a quantitative TLC bioautographic assay suitable for effect-directed analysis of food-related matrices.
The assay combines chromatographic separation, urease immobilization in an agar layer, and ammonia detection through the Berthelot reaction to quantitatively visualize urease inhibition zones while avoiding false-positive responses associated with pH indicator-based detection. Validation showed linearity for thiourea over 0.47-15 μg/spot (R² > 0.999), with LOD and LOQ values of 0.15 ± 0.08 and 0.46 ± 0.25 μg/spot, respectively, and intra-plate and intraday RSDs of 7.6-11.8% and 9.9%, respectively. Parallel screening of essential oils enabled rapid comparative evaluation of urease-inhibitory activity, while direct gas chromatography-mass spectrometry analysis of active chromatographic zones allowed microscale identification of eugenol as the principal bioactive constituent without preparative isolation.
This work presents the first quantitative TLC-based bioautographic assay for urease inhibitors and establishes an integrated effect-directed analytical workflow that combines quantitative activity localization with direct molecular identification. The methodology provides a simple and cost-effective platform for screening and characterizing urease inhibitors in complex food- and agriculture-related matrices, facilitating the discovery of bioactive compounds with potential applications in food preservation, quality control, and sustainable agricultural practices.

PMID:
42838678
Bibliographic data and abstract were imported from PubMed on 07 Oct 2026.

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