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. 2024 Jun 13;19(6):e0304504.
doi: 10.1371/journal.pone.0304504. eCollection 2024.

SARS-CoV-2 Delta variant remains viable in environmental biofilms found in meat packaging plants

Affiliations

SARS-CoV-2 Delta variant remains viable in environmental biofilms found in meat packaging plants

Austin B Featherstone et al. PLoS One. .

Abstract

To determine why SARS-CoV-2 appears to thrive specifically well in meat packaging plants, we used SARS-CoV-2 Delta variant and meat packaging plant drain samples to develop mixed-species biofilms on materials commonly found within meat packaging plants (stainless steel (SS), PVC, and ceramic tile). Our data provides evidence that SARS-CoV-2 Delta variant remained viable on all the surfaces tested with and without an environmental biofilm after the virus was inoculated with the biofilm for 5 days at 7°C. We observed that SARS-CoV-2 Delta variant was able to remain infectious with each of the environmental biofilms by conducting plaque assay and qPCR experiments, however, we detected a significant reduction in viability post-exposure to Plant B biofilm on SS, PVC, and on ceramic tile chips, and to Plant C biofilm on SS and PVC chips. The numbers of viable SARS-CoV-2 Delta viral particles was 1.81-4.57-fold high than the viral inoculum incubated with the Plant B and Plant C environmental biofilm on SS, and PVC chips. We did not detect a significant difference in viability when SARS-CoV-2 Delta variant was incubated with the biofilm obtained from Plant A on any of the materials tested and SARS-CoV-2 Delta variant had higher plaque numbers when inoculated with Plant C biofilm on tile chips, with a 2.75-fold difference compared to SARS-CoV-2 Delta variant on tile chips by itself. In addition, we detected an increase in the biofilm biovolume in response to SARS-CoV-2 Delta variant which is also a concern for food safety due to the potential for foodborne pathogens to respond likewise when they come into contact with the virus. These results indicate a complex virus-environmental biofilm interaction which correlates to the different bacteria found in each biofilm. Our results also indicate that there is the potential for biofilms to protect SARS-CoV-2 from disinfecting agents and remaining prevalent in meat packaging plants.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. CFU counts from biofilm with SARS-CoV-2 Delta variant and biofilm without SARS-CoV-2 Delta variant samples on stainless steel, PVC, and tile chips.
(A-I) CFU counts for biofilm with SARS-CoV-2 Delta variant and biofilm without SARS-CoV-2 Delta variant samples on stainless steel, PVC, and tile chips (A-C) from Plant A, (D-F) from Plant B, and (G-I) from Plant C. Each sample was plated in duplicate. Results in this figure are the mean values and standard deviations (error bars) from three independent experiments. Statistical significance was analyzed by unpaired t-test. *: p < 0.05; **: p < 0.01; ***: p < 0.001; ****: p < 0.0001.
Fig 2
Fig 2. RT-qPCR analysis of SARS-CoV-2 Delta variant mixed with biofilm organisms and pre-incubated for 5 days on stainless steel, PVC, and ceramic tile chips.
(A-C) RT-qPCR analysis of SARS-CoV-2 Delta variant mixed with environmental biofilm organisms from Plant A on stainless steel, PVC and on ceramic tile chips, (D-F) RT-qPCR analysis of SARS-CoV-2 Delta variant mixed with environmental biofilm organisms from Plant B on stainless steel, PVC, and on ceramic tile chips, (G-I) RT-qPCR analysis of SARS-CoV-2 Delta variant mixed with environmental biofilm organisms from Plant C on stainless steel, PVC, and on ceramic tile chips. 1.0 x 104 PFU of SARS-CoV-2 Delta variant were added to a stainless steel, PVC, or ceramic tile chip along with a floor drain biofilm sample collected from the cooler of meat packaging plant A, B, or C. The RT-qPCR samples were analyzed in duplicate. Gene copy numbers were calculated from a standard curve of known quantities of SARS-CoV-2 Delta variant RNA in a 25 μL qPCR reaction. Results in this figure are the mean values and standard deviations (error bars) from three independent experiments. Statistical significance was analyzed by unpaired t-test. ns: not significant; **: p < 0.01; ***: p < 0.001.
Fig 3
Fig 3. Plaque assay results from biofilm with SARS-CoV-2 Delta variant and SARS-CoV-2 Delta variant without biofilm samples on stainless steel, PVC, and ceramic tile chips.
(A-I) Results from plaque assays on samples collected from (A-C) stainless steel, (D-F) PVC, and (G-I) ceramic tile chips. Each sample was filtered through a 0.45 μm filter and plated on Vero CCL-81 cells in duplicate. Results in this figure are the mean values and standard deviations (error bars) from three independent experiments. Statistical significance was analyzed by unpaired t-test. **: p < 0.01; ****: p < 0.0001.
Fig 4
Fig 4. Schematic representation of floor drain biofilm and virus experiment.
(A and B): Experimental set up with Biofilm with SARS-CoV-2 Delta variant, Biofilm without SARS-CoV-2 Delta variant, SARS-CoV-2 Delta variant—Biofilm, and Negative Control in duplicate. The experimental set is incubated at 7°C for 5 days. (C). After 5 days, the biofilm was harvested from SS, PVC, or ceramic tile chips using a cell lifter and forceps and rinsed with 1000 μL of LB-NS. (D) Harvested cells were stored in a screw-cap tube at -80°C until needed.
Fig 5
Fig 5. Results from evaporation dynamics assays of water droplets inoculated on different substrates: stainless steel (red, circles), PVC (green, diamonds) and ceramic tile (blue, triangles) samples.
(A) Weight fraction of liquid remaining on the substrates as a function of time (hours) after inoculation. The data points represent mean values over N = 6 replicates, and the error bars show the standard error (SE) over these replicates. The curves show exponential decay fits to these data points. (B) Half-life time of evaporation from the different materials, obtained from these exponential decay fits. This gives 88 ± 9 hours, 110 ± 16 hours, 127 ± 10 hours, respectively, where the error bars are quantified by the standard error (SE) of the data sets.

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