Issue 22, 2024

CRISPR/Cas-based colorimetric biosensors: a promising tool for the diagnosis of bacterial foodborne pathogens in food products

Abstract

Some physical phenomena and various chemical substances newly introduced in nanotechnology have allowed scientists to develop valuable devices in the field of food sciences. Regarding such progress, the identification of foodborne pathogenic microorganisms is an imperative subject nowadays. These bacterial species have been found to cause severe health impacts after food ingestion and can result in high mortality in acute cases. The rapid detection of foodborne bacterial species at low concentrations is in high demand in recent diagnostics. CRISPR/Cas-mediated biosensors possess the potential to overcome several challenges in classical assays such as complex pretreatments, long turnaround time, and insensitivity. Among them, colorimetric nanoprobes based on the CRISPR strategy afford promising devices for POCT (point-of-care testing) since they can be visualized with the naked eye and do not require diagnostic apparatus. In this study, we briefly classify and discuss the working principles of the different CRISPR/Cas protein agents that have been employed in biosensors so far. We assess the current status of the CRISPR system, specifically focusing on colorimetric biosensing platforms. We discuss the utilization of each Cas effector in the detection of foodborne pathogens and examine the restrictions of the existing technology. The challenges and future opportunities are also indicated and addressed.

Graphical abstract: CRISPR/Cas-based colorimetric biosensors: a promising tool for the diagnosis of bacterial foodborne pathogens in food products

Article information

Article type
Critical Review
Submitted
31 मार्च 2024
Accepted
14 मई 2024
First published
15 मई 2024

Anal. Methods, 2024,16, 3448-3463

CRISPR/Cas-based colorimetric biosensors: a promising tool for the diagnosis of bacterial foodborne pathogens in food products

E. A. M. Saleh, E. Ali, G. M. Muxamadovna, A. F. Kassem, I. Kaur, A. Kumar, H. S. Jabbar, E. R. Alwaily, A. Elawady and A. A. Omran, Anal. Methods, 2024, 16, 3448 DOI: 10.1039/D4AY00578C

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