The present study compared different concentrations of propidium monoazide (PMA), time of exposure to light and different light intensities to determine the optimal conditions for the quantification of viable Escherichia coli in cell suspension and in food matrix. The influence of cell density and the effectiveness of PMA in viable but non-culturable (VBNC) E. coli cells were evaluated and also applied in food matrix. For that purpose, different concentrations of PMA (20 μM, 40 μM, 50 μM, 60 μM and 80 μM) under different times of exposure (5 min, 10 min, 15 min, 20 min and 30 min) to lights of different intensities (500 W and 650 W) were evaluated. After determining the optimal conditions, the PMA-qPCR methods were applied to different compositions of live and heat-killed E. coli suspensions (v:v; 0:1; 1:0; 1:1) in concentrations ranging from 3 Log to 7 Log CFU/mL. The same dilutions were prepared with E. coli in VBNC state and applied in food matrix. The results obtained from qPCR, PMA-qPCR and plate counts were compared. The results suggested that a PMA treatment of 50 μM PMA for 15 min under 650 W light intensity was optimal under our conditions. For E. coli cell suspensions, the amplification of heat-killed cells was inhibited greatly by PMA when concentrations were ≤ 5 Log CFU/mL. For the samples of oyster inoculated with heat-killed cells, E. coli was not detected by PMA-qPCR in concentrations ≤4 Log CFU/g. Regarding the results with VBNC state, we considered the PMA-qPCR method to be applicable for enumerating E. coli VBNC cells in oyster samples. Based on our findings, we further recommend the use of PMA-qPCR with the aim of reducing the amplification of dead cells for improving its performance, since false-positives could still occur depending on the level of E. coli in the sample. The application of the PMA-qPCR for quantification of bacteria, compared to the use of culture-dependent methods, is quite promising. However, further studies are recommended, especially using different food matrices.

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http://dx.doi.org/10.1016/j.ijfoodmicro.2019.108467DOI Listing

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