Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Comparative Study
. 2018 Nov 19;18(1):189.
doi: 10.1186/s12866-018-1323-4.

Metagenomics of pasteurized and unpasteurized gouda cheese using targeted 16S rDNA sequencing

Affiliations
Comparative Study

Metagenomics of pasteurized and unpasteurized gouda cheese using targeted 16S rDNA sequencing

Joelle K Salazar et al. BMC Microbiol. .

Abstract

Background: The microbiome of cheese is diverse, even within a variety. The metagenomics of cheese is dependent on a vast array of biotic and abiotic factors. Biotic factors include the population of microbiota and their resulting cellular metabolism. Abiotic factors, including the pH, water activity, fat, salt, and moisture content of the cheese matrix, as well as environmental conditions (temperature, humidity, and location of aging), influence the biotic factors. This study assessed the metagenomics of commercial Gouda cheese prepared using pasteurized or unpasteurized cow milk or pasteurized goat milk via 16S rDNA sequencing.

Results: Results were analyzed and compared based on milk pasteurization and source, spatial variability (core, outer, and under the rind), and length of aging (2-4 up to 12-18 months). The dominant organisms in the Gouda cheeses, based on percentage of sequence reads identified at the family or genus levels, were Bacillaceae, Lactococcus, Lactobacillus, Streptococcus, and Staphylococcus. More genus- or family-level (e.g. Bacillaceae) identifications were observed in the Gouda cheeses prepared with unpasteurized cow milk (120) compared with those prepared with pasteurized cow milk (92). When assessing influence of spatial variability on the metagenomics of the cheese, more pronounced differences in bacterial genera were observed in the samples taken under the rind; Brachybacterium, Pseudoalteromonas, Yersinia, Klebsiella, and Weissella were only detected in these samples. Lastly, the aging length of the cheese greatly influenced the number of organisms observed. Twenty-seven additional genus-level identifications were observed in Gouda cheese aged for 12-18 months compared with cheese only aged 2-4 months.

Conclusions: Collectively, the results of this study are important in determining the typical microbiota associated with Gouda cheese and how the microbiome plays a role in safety and quality.

Keywords: 16 s rDNA; Cheese; Dairy; Gouda; Metagenome; Unpasteurized milk.

PubMed Disclaimer

Conflict of interest statement

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Rarefaction curves of all commercial Gouda cheeses assessed in this study
Fig. 2
Fig. 2
Percentage of bacterial genera in Gouda cheese based on milk pasteurization and source. The reads from all cheese sampling locations (core, inside, just under the rind) were included
Fig. 3
Fig. 3
Bacterial kronographs of core (a), under the rind (b), and inside (c) locations of the commercial Gouda cheese
Fig. 4
Fig. 4
Bacterial genera in commercial unpasteurized Gouda cheese from the same manufacturer based on aging length

Similar articles

Cited by

References

    1. Jarvis KG, et al. Cilantro microbiome before and after nonselective pre-enrichment for Salmonella using 16S rRNA and metagenomic sequencing. BMC Microbiol. 2015;15:160. doi: 10.1186/s12866-015-0497-2. - DOI - PMC - PubMed
    1. Lopez-Velasco G, et al. Changes in spinach phylloepiphytic bacteria communities following minimal processing and refrigerated storage described using pyrosequencing of 16S rRNA amplicons. J Appl Microbiol. 2011;110(5):1203–1214. doi: 10.1111/j.1365-2672.2011.04969.x. - DOI - PubMed
    1. Margot H, Stephan R, Tasara T. Mungo bean sprout microbiome and changes associated with culture based enrichment protocols used in detection of gram-negative foodborne pathogens. Microbiome. 2016;4(1):48. doi: 10.1186/s40168-016-0193-y. - DOI - PMC - PubMed
    1. Lee M, et al. Large-scale targeted metagenomics analysis of bacterial ecological changes in 88 kimchi samples during fermentation. Food Microbiol. 2017;66:173–183. doi: 10.1016/j.fm.2017.05.002. - DOI - PubMed
    1. Korsak N, et al. Short communication: evaluation of the microbiota of kefir samples using metagenetic analysis targeting the 16S and 26S ribosomal DNA fragments. J Dairy Sci. 2015;98(6):3684–3689. doi: 10.3168/jds.2014-9065. - DOI - PubMed

Publication types

LinkOut - more resources