Determination of foodborne pathogenic bacteria by multiplex PCR-microchip capillary electrophoresis with genetic algorithm-support vector regression optimization

Li, Yongxin; Li, Yuanqian; Zheng, Bo; Qu, Lingli; Li, Can

doi:10.1016/j.aca.2009.04.006

Cited by 32 publications

(16 citation statements)

References 22 publications

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“….). Five of them [9][10][11][12][13] have been published in the section "Extraction and Sample handling", two [14,15] in the section "Chemometrics", two [16,17] in the section "Electrochemistry" and two [18,19] in the section "Separation methods".…”

Section: Interactionsmentioning

confidence: 99%

Experimental design in chemistry: A tutorial

Leardi

2009

Analytica Chimica Acta

635

349

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Section: Interactionsmentioning

confidence: 99%

Experimental design in chemistry: A tutorial

Leardi

2009

Analytica Chimica Acta

635

349

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“…A Multiplex PCR-based assay has been recently successfully performed targeting the 16S rRNA gene of eight different pathogens (E. coli, Clostridium perfringens, Campylobacter jejuni, Salmonella enterica, Listeria monocytogenes, Vibrio parahaemolyticus, Staphylococcus aureus, and Bacillus cereus) followed by a species-specific identification by separating PCR products in capillary electrophoresis-based single-strand conformation polymorphism (CE-SSCP) [15]. Multiplex PCR-based assays have also been developed by using sets of primers targeting different regions of foodborne pathogens (from 3 to 6 different pathogens) with subsequent post-PCR analysis [16,[18][19][20]. A further improved multiplex methodology has been developed to overcome amplification disparities due to the use of several primers; this universal primer-multiplex PCR system (UP-M-PCR) has been successfully applied to detect E. coli, L. monocytogenes, and Salmonella spp.…”

Section: Rapid Nucleic Acid-based Methodsmentioning

confidence: 99%

“…They could serve as a rapid screening method for pathogen detection and they have the potential to be fully automated. Recent multiplex PCR-based applications are reported in Table 1 [11][12][13][14][15][16]. In PCR-based assays, a nucleic acid target of definite length and sequence is amplified by repetitive cycles of strand denaturation, annealing, and extension of oligonucleotide primers by a thermostable DNA polymerase.…”

Section: Rapid Nucleic Acid-based Methodsmentioning

confidence: 99%

Recent developments in rapid multiplexed bioanalytical methods for foodborne pathogenic bacteria detection

et al. 2012

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Foodborne illnesses caused by pathogenic bacteria represent a widespread and growing problem to public health, and there is an obvious need for rapid detection of food pathogens. Traditional culture-based techniques require tedious sample workup and are time-consuming. It is expected that new and more rapid methods can replace current techniques. To enable large scale screening procedures, new multiplex analytical formats are being developed, and these allow the detection and/or identification of more than one pathogen in a single analytical run, thus cutting assay times and costs. We review here recent advancements in the field of rapid multiplex analytical methods for foodborne pathogenic bacteria. A variety of strategies, such as multiplex polymerase chain reaction assays, microarray-or multichannel-based immunoassays, biosensors, and fingerprint-based approaches (such as mass spectrometry, electronic nose, or vibrational spectroscopic analysis of whole bacterial cells), have been explored. In addition, various technological solutions have been adopted to improve detectability and to eliminate interferences, although in most cases a brief pre-enrichment step is still required. This review also covers the progress, limitations and future challenges of these approaches and emphasizes the advantages of new separative techniques to selectively fractionate bacteria, thus increasing multiplexing capabilities and simplifying sample preparation procedures.

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“…The genetic algorithm (GA) can solve the optimization problems in different fields (Li, Fang, & Cheng, 2009a, 2009b, 2009cOh, Jung, & Pedrycz, 2009). Kim combined Bayesian and the genetic algorithm to solve problems with large number of genes and limited numbers of experimental data points.…”

Section: Bayesian Exponential Model and Genetic Algorithmmentioning

confidence: 99%