Molecular techniques for detection and identification of pathogens in food: advantages and limitations
Foodborne diseases, caused by pathogenic microorganisms, are a major public health problem worldwide. Microbiological methods commonly used in the detection of these foodborne pathogens are laborious and time consuming. This situation, coupled with the demand for immediate results and with technolog...
Main Authors: | , |
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Format: | Article |
Language: | Spanish |
Published: |
Instituto Nacional de Salud
2014-09-01
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Series: | Revista Peruana de Medicina Experimental y Salud Pública |
Subjects: | |
Online Access: | https://rpmesp.ins.gob.pe/index.php/rpmesp/article/view/93 |
Summary: | Foodborne diseases, caused by pathogenic microorganisms, are a major public health problem worldwide. Microbiological methods commonly used in the detection of these foodborne pathogens are laborious and time consuming. This situation, coupled with the demand for immediate results and with technological advances, has led to the development of a wide range of rapid methods in recent decades. On this basis, this review describes the advantages and limitations of the main molecular methods used in detection and identification of foodborne pathogens. To this end, we considered how recent the information was published, the objective analysis of the topic and its scope. Recent literature reports a significant number of alternative, sensitive and selective molecular techniques for detection, enumeration and identification of pathogenic microorganisms in food. Polymerase chain reaction (PCR) is the most popular platform, while high performance sequencing is emerging as a technique of wide applicability for the future. However, even with all the advantages of these new methodologies, their limitations should not be overlooked. For example, molecular methods are not standardized protocols, which hinders its use in some cases. For this reason, hard work should be done to overcome these limitations and improve the application of these techniques in complex matrices such as food systems. |
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ISSN: | 1726-4634 1726-4642 |