Evaluation of propidium monoazide for 16S ribosomal RNA metabarcoding assessment of microbial communities in 60-day ripened raw goat milk cheese

Highlights

• Environmental contaminants in ripened cheese decreased with PMA treatment.
• PMA removes dead cell DNA but does not change overall cheese microbial diversity.
• PMA improves accuracy of viable microbiota detection in ripened goat cheese.

Abstract

Cheese ripening is a complex microbial process marked by significant shifts in microbial composition. Considering that propidium monoazide (PMA) depletes DNA from nonviable cells, we hypothesized that PMA treatment of cheese samples could affect the microbiota characterization of 60-d-ripened raw goat curd cheese by 16S rRNA metabarcoding sequencing. After ripening, PMA-treated and nontreated (control) samples from the same cheese units were processed for DNA extraction, library preparation, and 16S rRNA metabarcoding sequencing on an Illumina MiSeq platform. Downstream bioinformatic analyses for microbial diversity assessment were performed using QIIME 2 and the phyloseq package in R. Statistical analyses included permutational multivariate analysis of variance (PERMANOVA), Wilcoxon tests, and linear discriminant analysis effect size (LEfSe). No significant differences were observed in either α or β diversity metrics between PMA-treated and nontreated samples. However, PMA treatment significantly reduced the abundance of farm environment–associated Dickeya and Pectobacteriaceae taxa in cheese samples, thus improving the accuracy of determining the cheese microbial structure using next-generation sequencing technologies. Further longitudinal studies focusing on different sampling periods during ripening, as well as other cheese types, may shed light on the potential benefits of using PMA for improving the accuracy of cheese microbial community characterization by next-generation sequencing.