Abstract 2580 Redesigning Internal Standards for Better Detection of True Positives and False Negatives in qPCR Assays

We developed a novel synthetic, gene-specific internal standard to identify inhibitors that may interfere with the detection of target genes.This internal standard was specifically designed for detecting 'Candidatus Liberibacter asiaticus' (CLas), the bacterium responsible for Huanglongbing (HLB), a devastating disease in citrus crops.Internal standards are commonly used in qPCR assays for CLas detection to minimize the risk of false negative diagnoses.However, endogenous standards such as citrus COX and MDH are significantly more abundant than the CLas target genes, such as 16S rDNA or RNR.The standards' abundance makes them less susceptible to inhibitors.Additionally, due to sequence differences, their detection responds differently to inhibitors compared to CLas target genes, limiting their reliability for accurately assessing inhibition effects on the target gene.To overcome these limitations, we designed a synthetic internal standard that incorporates the primers of the gene of interest along with three to four downstream nucleotides.This design ensures that primer annealing, DNA polymerase binding, and initial nucleotide incorporation mirror those of the target gene.Additionally, we tailored the region between the primers to closely match the GC content and melting temperature of the target gene.Despite these similarities, sequence differences allow for the independent detection of both the internal standard and the target gene, enabling effective duplex qPCR.By adding an average of 21 molecules of the internal standard to each qPCR reaction, the primer competition during qPCR does not hinder the detection of even a single molecule of CLas target gene.Statistical analysis of the internal standard's Ct values enables the identification of reactions where inhibitors may have prevented CLas detection.Furthermore, analyzing the difference between the Ct values of the target gene and the internal standard helps distinguish between true and false positive diagnoses.