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

UNLABELLED: Amplicon sequencing investigations of surface microbiota in food facilities often report the relative abundance of bacteria and fungi. However, physiological differences among cell types can result in variable cell recovery and DNA yields, thereby skewing relative abundance estimates. Here, we evaluated (i) variations in cell recovery among different bacterial and fungal species after surface swabbing and (ii) the impact of DNA extraction protocols on relative abundance estimates from artificially inoculated stainless steel surfaces. Our results showed that Escherichia coli (Gram-negative cell), Listeria monocytogenes (Gram-positive), 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. Vegetative cells (E. coli and L. monocytogenes) exhibited lower average recovery rates from surface swabbing (2.9%-6.6%) than spores (35.2%-94.9%). Extending the bead-beating step in DNA extraction by 10 min generally improved 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. Cell recovery and DNA extraction impacted relative abundance estimates from amplicon sequencing. Starting off at equal relative abundances of 25%, L. monocytogenes was underestimated (9%-17%) in downstream calculations, while B. cereus was overestimated (36%-44%). These results underscore the limitations of amplicon sequencing for microbiota characterization on food facility surfaces and highlight the need to improve current swabbing and DNA extraction methods. IMPORTANCE: Amplicon 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 of 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 recovery 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.