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http://dx.doi.org/10.4014/jmb.1406.06079

A New Multiplex-PCR for Urinary Tract Pathogen Detection Using Primer Design Based on an Evolutionary Computation Method  

Garcia, Liliana Torcoroma (Program of Bacteriology and Clinical Laboratory, Universidad de Santander - UDES)
Cristancho, Laura Maritza (Program of Bacteriology and Clinical Laboratory, Universidad de Santander - UDES)
Vera, Erika Patricia (Program of Bacteriology and Clinical Laboratory, Universidad de Santander - UDES)
Begambre, Oscar (School of Civil Engineering, Universidad Industrial de Santander)
Publication Information
Journal of Microbiology and Biotechnology / v.25, no.10, 2015 , pp. 1714-1727 More about this Journal
Abstract
This work describes a new strategy for optimal design of Multiplex-PCR primer sequences. The process is based on the Particle Swarm Optimization-Simplex algorithm (Mult-PSOS). Diverging from previous solutions centered on heuristic tools, the Mult-PSOS is selfconfigured because it does not require the definition of the algorithm's initial search parameters. The successful performance of this method was validated in vitro using Multiplex-PCR assays. For this validation, seven gene sequences of the most prevalent bacteria implicated in urinary tract infections were taken as DNA targets. The in vitro tests confirmed the good performance of the Mult-PSOS, with respect to infectious disease diagnosis, in the rapid and efficient selection of the optimal oligonucleotide sequences for Multiplex-PCRs. The predicted sequences allowed the adequate amplification of all amplicons in a single step (with the correct amount of DNA template and primers), reducing significantly the need for trial and error experiments. In addition, owing to its independence from the initial selection of the heuristic constants, the Mult-PSOS can be employed by non-expert users in computational techniques or in primer design problems.
Keywords
Primer design; multiplex-PCR; urinary tract infections; uropathogens; particle swarm optimization; metaheuristic optimization;
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