• Laborde, Luke F.
• Tan, Xiaoqing
• Macarisin, Dumitru
• Chung, Taejung
• Gonzalez-Escalona, Narjol
• Rolon, M. Laura
• Chen, Yi
• Kovac, Jasna

Abstract

<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p><jats:italic>Listeria monocytogenes </jats:italic>can survive in cold and wet environments, such as tree fruit packing facilities and it has been implicated in outbreaks and recalls of tree fruit products. However, little is known about microbiota that co-occurs with <jats:italic>L. monocytogenes</jats:italic> and its stability over seasons in tree fruit packing environments. In this 2-year longitudinal study, we aimed to characterize spatial and seasonal changes in microbiota composition and identify taxa indicative of <jats:italic>L. monocytogenes</jats:italic> contamination in wet processing areas of three tree fruit packing facilities (F1, F2, F3).</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>A total of 189 samples were collected during two apple packing seasons from floors under the washing, drying, and waxing areas. The presence of <jats:italic>L. monocytogenes</jats:italic> was determined using a standard culturing method, and environmental microbiota was characterized using amplicon sequencing. PERMANOVA was used to compare microbiota composition among facilities over two seasons, and abundance-occupancy analysis was used to identify shared and temporal core microbiota. Differential abundance analysis and random forest were applied to detect taxa indicative of <jats:italic>L. monocytogenes</jats:italic> contamination. Lastly, three <jats:italic>L. monocytogenes</jats:italic>-positive samples were sequenced using shotgun metagenomics with Nanopore MinION, as a proof-of-concept for direct detection of <jats:italic>L. monocytogenes</jats:italic>’ DNA in environmental samples.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>The occurrence of <jats:italic>L. monocytogenes</jats:italic> significantly increased from 28% in year 1 to 46% in year 2 in F1, and from 41% in year 1 to 92% in year 2 in F3, while all samples collected from F2 were <jats:italic>L. monocytogenes</jats:italic>-positive in both years. Samples collected from three facilities had a significantly different microbiota composition in both years, but the composition of each facility changed over years. A subset of bacterial taxa including <jats:italic>Pseudomonas</jats:italic>, <jats:italic>Stenotrophomonas</jats:italic>, and <jats:italic>Microbacterium</jats:italic>, and fungal taxa, including <jats:italic>Yarrowia</jats:italic>, <jats:italic>Kurtzmaniella</jats:italic>, <jats:italic>Cystobasidium</jats:italic>, <jats:italic>Paraphoma</jats:italic>, and <jats:italic>Cutaneotrichosporon</jats:italic>, were identified as potential indicators of <jats:italic>L. monocytogenes</jats:italic> within the monitored environments. Lastly, the DNA of <jats:italic>L. monocytogenes</jats:italic> was detected through direct Nanopore sequencing of metagenomic DNA extracted from environmental samples.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>This study demonstrated that a cross-sectional sampling strategy may not accurately reflect the representative microbiota of food processing facilities. Our findings also suggest that specific microorganisms are indicative of <jats:italic>L. monocytogenes</jats:italic>, warranting further investigation of their role in the survival and persistence of <jats:italic>L. monocytogenes</jats:italic>.</jats:p></jats:sec>

Topics

• impedance spectroscopy
• random
• size-exclusion chromatography
• drying
• washing