Date of Award:


Document Type:


Degree Name:

Master of Science (MS)


Nutrition, Dietetics, and Food Sciences

Department name when degree awarded

Nutrition, Dietetics, and Food Science

Committee Chair(s)

Donald J. McMahon (Committee Chair), Taylor Oberg (Committee Co-Chair)


Donald J. McMahon


Taylor Oberg


Mike Lefevre


Craig J. Oberg


This project was funded by BUILD Dairy to test the efficacy of using next generation sequencing to study Cheddar cheese microbiomes. The 15 different cheese samples used in this study were purchased in the retail market from various manufacturers and different origins of manufacture. Sequencing was done by the Center for Integrated Biosystems at Utah State University using Illumina MiSeq.

The aim of this project is to provide further understanding of how using next generation sequencing can benefit the study of bacterial communities and their influence during the aging process of Cheddar cheese and the possibility of identifying defect causing microorganisms. We tested Cheddar cheese samples microbiota by amplifying and sequencing the hypervariable V4 region of the 16S rRNA. Sequencing data was evaluated using two different denoising pipelines within Qiime 2: Deblur and DADA2. We used variant identification as a method of comparing starter and non-starter lactic acid bacteria in cheeses based on regions and manufacturers.

In the data denoised by both methods the samples clustered into two groups separated by the dominant starter lactic acid bacteria (SLAB). DADA2 identified over quadruple the number of amplicon sequence variants (ASVs), which represent a unique sequence within the samples, compared to Deblur. Using Deblur we identified 5 Lactococcus lactis ASVs and 3 Streptococcus thermophilus ASVs compared to DADA2 which identified 34 L. lactis ASVs and 35 St. thermophilus. Thus, it can be said that using DADA2 to denoise Cheddar cheese data provides a more realistic representation of the microbiome