Both sampling seasonality and geographic origin contribute significantly to variations in raw milk microbiota, but sampling seasonality is the more determining factor
| Autor: | Lai-Yu Kwok, Feiyan Zhao, Zhongjie Yu, Xiaocen Guo, Shengli Li, Zhihong Sun |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Rhodospirillales
Lactococcus Bacillus medicine.disease_cause Milking fluids and secretions RNA Ribosomal 16S Lactobacillus Genetics medicine Animals Food science Acinetobacter biology Microbiota Psychrobacter food and beverages Lactococcus piscium Seasonality Raw milk biology.organism_classification medicine.disease Milk Streptococcus agalactiae Food Microbiology Cattle Female Animal Science and Zoology Acinetobacter lwoffii Food Science |
| Zdroj: | Journal of Dairy Science. 104:10609-10627 |
| ISSN: | 0022-0302 |
| DOI: | 10.3168/jds.2021-20480 |
| Popis: | Accurately profiling and characterizing factors shaping raw milk microbiota would provide practical information for detecting microbial contamination and unusual changes in milk. The current work was an observational study aiming to profile the microbiota of raw milk collected across wide geographic regions in China in different seasons and to investigate the contribution of geographical, seasonal, and environmental factors in shaping the raw milk microbiota. A total of 355 raw cow milk samples from healthy Holsteins and 41 environmental samples (farm soil and surface of milking room floor) were collected from 5 dairy farms in 5 Chinese provinces (namely, Daqing in Heilongjiang province, Jiaozuo in Henan province, Qingyuan in Guangdong province, Suqian in Jiangsu province, and Yinchuan in Ningxia Hui Autonomous Region) in January, May, and September 2018. The microbial communities in raw milk and farm environmental samples were determined using the PacBio small-molecule real-time circular consensus sequencing, which generated high-fidelity microbiota profiles based on full-length 16S rRNA genes; such technology was advantageous in producing accurate species-level information. Our results showed that both seasonality and sampling region were significant factors influencing the milk microbiota; however, the raw milk microbiota was highly diverse according to seasonality, and sampling region was the less determining factor. The wide variation in raw milk microbial communities between samples made it difficult to define a representative species-level core milk microbiota. Nevertheless, 3 most universal milk-associated species were identified: Lactococcus lactis, Enhydrobacter aerosaccus, and Acinetobacter lwoffii, which were consistently detected in 99%, 95%, and 94% of all analyzed milk samples, respectively (n = 355). The top taxa accounting for the overall seasonal microbiota variation were Bacillus (Bacillus cereus, Bacillus flexus, Bacillus safensis), Lactococcus (Lactococcus lactis, Lactococcus piscium, Lactococcus raffinolactis), Lactobacillus (Lactobacillus helveticus, Lactobacillus delbrueckii), Lactiplantibacillus plantarum, Streptococcus agalactiae, Enhydrobacter aerosaccus, Pseudomonas fragi, and Psychrobacter cibarius. Unlike the milk microbiota, the environmental microbiota did not exhibit obvious pattern of seasonal or geographic variation. However, this study was limited by the relatively low number and types of environmental samples, making it statistically not meaningful to perform further correlation analysis between the milk and environmental microbiota. Nevertheless, this study generated novel information on raw milk microbiota across wide geographic regions of China and found that seasonality was more significant in shaping the raw milk microbiota compared with geographic origin. |
| Databáze: | OpenAIRE |
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