Fermentation · 2020 · 21 citations · 30 references
AgricultureDairy ScienceMicrobiologyDairy MicrobiologyMicrobial EcologyMilk QualityMilk Microbial EcologyMilk MicrobiologyMilk SpoilageMilk StorageRaw Milk MicrobiologyStorage StabilityCold Storage RegimeCold Storage SystemsDairy Farm Milk Microbial CommunitiesMicrobial Diversity AnalysisMilk Microbiota CompositionRaw Milk Microbial ContaminationRaw Milk SpoilageStorage Effects On Raw Milk Microbiota
In general, it is a common practice among dairy producers to store the milk in the refrigerator directly after milking, in order to preserve it and prevent the development of spoilage microbes. However, the impact of keeping the milk in the refrigerator overnight on milk microbial diversity has been poorly investigated. This study aimed to provide a snapshot of the bacterial composition of goat milk after direct storage at −80 °C and after being kept overnight at 4 °C and then in storage at −80 °, using high-throughput sequencing (HTS). Goat milk samples from four different farms were analyzed, to reveal that milk bacterial diversity differed between the two different storage conditions. Goat milk directly stored at −80 °C was characterized by the presence of the Gram-negative contaminants Pseudomonas and Acinetobacter, in addition to the genera Corynebacterium, Chryseobacterium, Bacteroides and Clostridium. Milk samples that were kept overnight at 4 °C were characterized by a reduction in their bacterial biodiversity and the predominance of the Gram-negative, aerobic Phyllobacterium. Overall, HTS methodologies provide an in-depth identification and characterization of the goat raw milk microbiome. Further, they offer a better understanding of the contribution of cold storage conditions to milk microbiota formation. This study may assist dairy producers in improving raw milk and raw milk cheeses quality and guaranteeing consumers’ safety.
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Trimmomatic: a flexible trimmer for Illumina sequence data
Anthony Bolger, Marc Lohse, Björn Usadel · Bioinformatics · 2014 · 69.7K citations · Full text
DADA2: High-resolution sample inference from Illumina amplicon data
Benjamin J. Callahan, Paul J. McMurdie, Michael Rosen et al. · Nature Methods · 2016 · 36.3K citations