Minimum Set Primers and Unique Probes Design Algorithms for

Differential Detection of Symptom-Related Pathogens

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Introduction

Methodology

Computational Results

Bio-Experiment

Conclusion

Reference

In this work, we have developed an integrated algorithm for differential detection of several pathogens simultaneously. We have formulated the multiple-use primer design problem as a minimum set covering problem (SCP). We have used the modified compact genetic algorithm to solve the SCP, and successfully reduced the number of primers required for amplification of multiple sequences. From the results of simulation, we have illustrated that our MCGA based method is faster than the best densest subgraph heuristics (DSH) and has comparable reduction rates. We have applied the integrated algorithm to the detection of 9 plants viruses with success.      For large scale primer reduction simulations using LTH, DSH, and MCGA, MCGA outperforms LTH in terms of solution quality. MCGA achieves comparable solution quality to DSH, but with much smaller time complexity. In some cases, the reduction rates of MCGA based method is slightly lower than those of DSH. However, the standard deviation of 30 repeated runs for MCGA is much smaller than those of DSH and LTH. This implies that MCGA based method is more robust and can achieve consistent reduction rates. In real-world applications, a more robust algorithm is more practical and more applicable.      The primers for amplification of the 9 plant viruses revealed unexpected results for two viruses, PAV and HCRSV. The amplified sequences of the two viruses are not clearly observable from the gel. The major cause might be the competition among multiple-use primers. For PAV, the most prominent band is not the one expected. As for HCRSV, other primers will anneal to the target sequence, most likely between the specific primer pair LMu-04 and LMu-08. Therefore the target sequences will be cut into two or more fragments. Though the bands for targeted amplified sequences are not clearly observable for PAV and HCRSV, the triplicate dot hybridization has nonetheless detected these sequences. The integrated primer/probe design algorithm can detect the 9 plant viruses specifically. And the overall algorithm is successful.      Genome-wide and comparative genomic analysis with microarray is very expensive, and thus limits the potential application of microarray technology to various topics. The costs come mostly from the synthesis of probes and primers. Our algorithm can reduce the number of primers required to amplify a large number of target sequences, thus saving large amount of investments.      Our method can also be applied to design and construction of diagnostic chips. The capability to simultaneously detect various pathogens can be proved valuable in the biomedical industry and molecular biology studies.