Integrated minimum-set primers and unique probe design algorithms for differential detection on symptom-related pathogens.
BACKGROUND
Differential detection on symptom-related pathogens (SRP) is critical for fast identification and accurate control against epidemic diseases. Conventional polymerase chain reaction (PCR) requires a large number of unique primers to amplify selected SRP target sequences. With multiple-use primers (mu-primers), multiple targets can be amplified and detected in one PCR experiment under standard reaction condition and reduced detection complexity. However, the time complexity of designing mu-primers with the best heuristic method available is too vast. We have formulated minimum-set mu-primer design problem as a set covering problem (SCP), and used modified compact genetic algorithm (MCGA) to solve this problem optimally and efficiently. We have also proposed new strategies of primer/probe design algorithm (PDA) on combining both minimum-set (MS) mu-primers and unique (UniQ) probes. Designed primer/probe set by PDA-MS/UniQ can amplify multiple genes simultaneously upon physical presence with minimum-set mu-primer amplification (MMA) before intended differential detection with probes-array hybridization (PAH) on the selected target set of SRP.


RESULTS
The proposed PDA-MS/UniQ method pursues a much smaller number of primers set compared with conventional PCR. In the simulation experiment for amplifying 12 669 target sequences, the performance of our method with 68% reduction on required mu-primers number seems to be superior to the compared heuristic approaches in both computation efficiency and reduction percentage. Our integrated PDA-MS/UniQ method is applied to the differential detection on 9 plant viruses from 4 genera with MMA and PAH of 11 mu-primers instead of 18 unique ones in conventional PCR while amplifying overall 9 target sequences. The results of wet lab experiments with integrated MMA-PAH system have successfully validated the specificity and sensitivity of the primers/probes designed with our integrated PDA-MS/UniQ method.
Huang
Yu-Cheng
YC
Bioinformatics Laboratory, Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.
Chang
Chun-Fan
CF
Chan
Chen-Hsiung
CH
Yeh
Tze-Jung
TJ
Chang
Ya-Chun
YC
Chen
Chaur-Chin
CC
Kao
Cheng-Yan
CY
D000465:Algorithms; D001483:Base Sequence; D003141:Communicable Diseases / Q000175:diagnosis; D019295:Computational Biology; D017931:DNA Primers; D015342:DNA Probes / Q000235:genetics*; D015195:Drug Design; D006801:Humans; D008957:Models, Genetic; D010942:Plant Viruses / Q000235:genetics / Q000472:pathogenicity; D012985:Software Design; D013816:Thermodynamics; D014774:Virulence / Q000235:genetics
D017931:DNA Primers; D015342:DNA Probes