Title |
Sequencing of the Cheese Microbiome and Its Relevance to Industry
|
---|---|
Published in |
Frontiers in Microbiology, May 2018
|
DOI | 10.3389/fmicb.2018.01020 |
Pubmed ID | |
Authors |
Bhagya. R. Yeluri Jonnala, Paul L. H. McSweeney, Jeremiah J. Sheehan, Paul D. Cotter |
Abstract |
The microbiota of cheese plays a key role in determining its organoleptic and other physico-chemical properties. It is essential to understand the various contributions, positive or negative, of these microbial components in order to promote the growth of desirable taxa and, thus, characteristics. The recent application of high throughput DNA sequencing (HTS) facilitates an even more accurate identification of these microbes, and their functional properties, and has the potential to reveal those microbes, and associated pathways, responsible for favorable or unfavorable characteristics. This technology also facilitates a detailed analysis of the composition and functional potential of the microbiota of milk, curd, whey, mixed starters, processing environments, and how these contribute to the final cheese microbiota, and associated characteristics. Ultimately, this information can be harnessed by producers to optimize the quality, safety, and commercial value of their products. In this review we highlight a number of key studies in which HTS was employed to study the cheese microbiota, and pay particular attention to those of greatest relevance to industry. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Ireland | 2 | 18% |
United States | 1 | 9% |
Ecuador | 1 | 9% |
Spain | 1 | 9% |
United Kingdom | 1 | 9% |
Brazil | 1 | 9% |
Unknown | 4 | 36% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 7 | 64% |
Scientists | 4 | 36% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 253 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 36 | 14% |
Researcher | 33 | 13% |
Student > Bachelor | 31 | 12% |
Student > Master | 28 | 11% |
Student > Doctoral Student | 16 | 6% |
Other | 45 | 18% |
Unknown | 64 | 25% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 69 | 27% |
Biochemistry, Genetics and Molecular Biology | 41 | 16% |
Immunology and Microbiology | 15 | 6% |
Unspecified | 8 | 3% |
Veterinary Science and Veterinary Medicine | 7 | 3% |
Other | 30 | 12% |
Unknown | 83 | 33% |