Shiga Toxin Detection Methods : A Short Review

TL;DR

This review discusses the importance of rapid, simple, and sensitive detection methods for Shiga toxins, emphasizing biosensors as promising tools to improve on-site identification of food contamination.

Contribution

It highlights recent advances in biosensor technologies for detecting Shiga toxins, addressing limitations of traditional methods and emphasizing their potential for field use.

Findings

Biosensors offer rapid detection compared to conventional methods.

Traditional detection methods are time-consuming and laborious.

Biosensors can be miniaturized for on-site testing.

Abstract

The Shiga toxins comprise a family of related protein toxins secreted by certain types of bacteria. Shigella dysenteriae, some strain of Escherichia coli and other bacterias can express toxins which caused serious complication during the infection. Shiga toxin and the closely related Shiga-like toxins represent a group of very similar cytotoxins that may play an important role in diarrheal disease and hemolytic-uremic syndrome. The outbreaks caused by this toxin raised serious public health crisis and caused economic losses. These toxins have the same biologic activities and according to recent studies also share the same binding receptor, globotriosyl ceramide (Gb3). Rapid detection of food contamination is therefore relevant for the containment of food-borne pathogens. The conventional methods to detect pathogens, such as microbiological and biochemical identification are time-consuming and laborious. The immunological or nucleic acid-based techniques require extensive sample preparation and are not amenable to miniaturization for on-site detection. In the present are necessary of techniques of rapid identification, simple and sensitive which can be employed in the countryside with minimally-sophisticated instrumentation. Biosensors have shown tremendous promise to overcome these limitations and are being aggressively studied to provide rapid, reliable and sensitive detection platforms for such applications.