Propidium monoazide combined with real-time quantitative PCR to quantify viable Alternaria spp. contamination in tomato products

• PMA treatment combined with qPCR selectively detects viable cells of Alternaria spp.
• This method has a detection limit of 102 conidia/g of tomato.
• A reduction of 7 cycles in the ΔCq between live and heat killed conidia was achieved.

Alternaria is a common contaminating genus of fungi in fruits, grains, and vegetables that causes severe economic losses to farmers and the food industry. Furthermore, it is claimed that Alternaria spp. are able to produce phytotoxic metabolites, and mycotoxins that are unsafe for human and animal health. DNA amplification techniques are being increasingly applied to detect, identify, and quantify mycotoxigenic fungi in foodstuffs, but the inability of these methods to distinguish between viable and nonviable cells might lead to an overestimation of mycotoxin-producing living cells. A promising technique to overcome this problem is the pre-treatment of samples with nucleic acid intercalating dyes, such as propidium monoazide (PMA), prior to quantitative PCR (qPCR). PMA selectively penetrates cells with a damaged membrane inhibiting DNA amplification during qPCRs. In our study, a primer pair (Alt4–Alt5) to specifically amplify and quantify Alternaria spp. by qPCR was designed. Quantification data of qPCR achieved a detection limit of 102 conidia/g of tomato. Here, we have optimized for the first time a DNA amplification-based PMA sample pre-treatment protocol for detecting viable Alternaria spp. cells. Artificially inoculated tomato samples treated with 65 μM of PMA, showed a reduction in the signal by almost 7 cycles in qPCR between live and heat-killed Alternaria spp. conidia. The tomato matrix had a protective effect on the cells against PMA toxicity, reducing the efficiency to distinguish between viable and nonviable cells. The results reported here indicate that the PMA-qPCR method is a suitable tool for quantifying viable Alternaria cells, which could be useful for estimating potential risks of mycotoxin contamination.