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Microbiome-based environmental monitoring of a dairy processing facility highlights the challenges associated with low microbial-load samples.

ABSTRACT: Efficient and accurate identification of microorganisms throughout the food chain can potentially allow the identification of sources of contamination and the timely implementation of control measures. High throughput DNA sequencing represents a potential means through which microbial monitoring can be enhanced. While Illumina sequencing platforms are most typically used, newer portable platforms, such as the Oxford Nanopore Technologies (ONT) MinION, offer the potential for rapid analysis of food chain microbiomes. Initial assessment of the ability of rapid MinION-based sequencing to identify microbes within a simple mock metagenomic mixture is performed. Subsequently, we compare the performance of both ONT and Illumina sequencing for environmental monitoring of an active food processing facility. Overall, ONT MinION sequencing provides accurate classification to species level, comparable to Illumina-derived outputs. However, while the MinION-based approach provides a means of easy library preparations and portability, the high concentrations of DNA needed is a limiting factor.

SUBMITTER: McHugh AJ

PROVIDER: S-EPMC7884712 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Microbiome-based environmental monitoring of a dairy processing facility highlights the challenges associated with low microbial-load samples.

McHugh Aoife J AJ Yap Min M Crispie Fiona F Feehily Conor C Hill Colin C Cotter Paul D PD

NPJ science of food 20210215 1

Efficient and accurate identification of microorganisms throughout the food chain can potentially allow the identification of sources of contamination and the timely implementation of control measures. High throughput DNA sequencing represents a potential means through which microbial monitoring can be enhanced. While Illumina sequencing platforms are most typically used, newer portable platforms, such as the Oxford Nanopore Technologies (ONT) MinION, offer the potential for rapid analysis of fo ...[more]

PMID: 33589631

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Project description:BackgroundThe blanket usage of antimicrobials at the end of lactation (or "drying off") in dairy cattle is under increasing scrutiny due to concerns about antimicrobial resistance. To lower antimicrobial usage in dairy farming, farmers are now encouraged to use "selective dry cow therapy" whereby only cows viewed as at high risk of mastitis are administered antimicrobial agents. It is important to gain a better understanding of how this practice affects the udder-associated microbiota and the potential knock-on effects on antimicrobial-resistant bacterial populations circulating on the farm. However, there are challenges associated with studying low biomass environments such as milk, due to known contamination effects on microbiome datasets. Here, we obtained milk samples from cattle at drying off and at calving to measure potential shifts in bacterial load and microbiota composition, with a critical assessment of contamination effects.ResultsSeveral samples had no detectable 16S rRNA gene copies and crucially, exogenous contamination was detected in the initial microbiome dataset. The affected samples were removed from the final microbiome analysis, which compromised the experimental design and statistical analysis. There was no significant difference in bacterial load between treatments (P > 0.05), but load was lower at calving than at drying off (P = 0.039). Escherichia coli counts by both sequence and culture data increased significantly in the presence of reduced bacterial load and a decreasing trend of microbiome richness and diversity. The milk samples revealed diverse microbiomes not reflecting a typical infection profile and were largely comprised of gut- and skin-associated taxa, with the former decreasing somewhat after prolonged sealing of the teats.ConclusionsThe drying off period had a key influence on microbiota composition and bacterial load, which appeared to be independent of antimicrobial usage. The interactions between drying off treatment protocol and milk microbiome dynamics are clearly complex, and our evaluations of these interactions were restricted by low biomass samples and contamination effects. Therefore, our analysis will inform the design of future studies to establish whether different selection protocols could be implemented to further minimise antimicrobial usage.

Dataset Information

Microbiome-based environmental monitoring of a dairy processing facility highlights the challenges associated with low microbial-load samples.

Publications

Microbiome-based environmental monitoring of a dairy processing facility highlights the challenges associated with low microbial-load samples.

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