Cell recovery and DNA extraction methods skew relative abundance estimations of foodborne pathogens and spoilage organisms on stainless steel surfaces

Studies investigating surface microbiota in food facilities often include estimates of relative abundance. However, obtaining accurate relative abundance values can be challenging. Differences among microbes can lead to different degrees of cell recovery from the surface and different DNA extraction yields that skew downstream relative abundance estimates. Here, we evaluated (1) the impact of cell recovery from surfaces using sponge swabs and (2) DNA extraction protocol on the relative abundance estimates of relative abundance on artificially inoculated surfaces. Our results showed that Escherichia coli (Gram-negative cell), Listeria monocytogenes (Gram-positive cell), Bacillus cereus (bacterial spore), Alicyclobacillus suci (bacterial spore), Exophiala phaeomuriformis (fungal cell), Aspergillus fischeri (fungal spore) differed significantly (p<0.05) in their recovery rates from stainless steel surfaces, ranging from 2.9%{+/-}3.0% recovery to 94.9%{+/-}3.0% recovery. Modification of the DNA extraction protocol by extending the bead-beating step by 10 min generally improved DNA yields, though the impact varied by organism. For example, DNA yields of E. coli increased from 70 to 84 ng/mL while that of L. monocytogenes increased only from 23.2 to 29.2 ng/mL. Amplicon sequencing results indicated that the differences in cell recovery and DNA extraction among microbial species skewed the relative abundance estimates from inoculated surfaces. For example, the estimated relative abundance of L. monocytogenes was 9-17%, which was lower than its actual relative abundance (25%). These results underscore the limitations of surface microbiota characterization in food facilities and highlighted the need to improve current recovery and DNA extraction methods. ImportanceAmplicon sequencing has been used to characterize microbial communities on facility surfaces. However, few studies have evaluated the accuracy of the amplicon sequencing workflow for quantifying spoilage and pathogenic organisms in these microbial communities. Here, we assessed the accuracy for amplicon sequencing to evaluate the relative abundance of spoilage and pathogenic organisms commonly found in food processing environments. The results revealed biases in relative abundances due to limitations in cell recover and DNA extraction methods. These findings revealed the potential biases in surface microbiota characterization in food facilities, and the need to refine current recovery and extraction methods to enhance the accuracy of microbiota characterization.