Tracking the microbial communities from the farm to the processing facility of a washed-rind cheese operation

Milk residue and the accompanying biofilm accumulation in milking systems can compromise the microbial quality of milk and the downstream processes of cheese production. Over a six-month study, the microbial ecosystems of milk (<i>n</i> = 24), tap water (<i>n</i> = 24) and environmental swabs (<i>n</i> = 384) were cultured by plating decimal dilutions to obtain viable counts of total aerobic mesophilic lactose-utilizing bacteria (lactose-M17), lactic acid bacteria (MRS), yeasts and molds (Yeast, Glucose, Chloramphenicol (YGC) medium). Viable aerobic lactose-M17 plate counts of milk remained well below 4.7 log CFU/ml over five of the months, except for 1 week in November where milk at the facility exceeded 5 log CFU/ml. Swab samples of the farm milking equipment showed consistent viable counts after sanitation, while the bulk tank swabs contained the lowest counts. Viable counts from swabs of the facility were generally below the detection limit in the majority of samples with occasional residual contamination on some food contact surfaces. Extracted DNA was amplified using primers targeting the V3-V4 region of the 16S rRNA gene, and the amplicons were sequenced by MiSeq to determine the shared microbiota between the farm and the processing facility (8 genera). Culture independent analysis of bacterial taxa in milk, water and residual contamination after sanitation with swab samples revealed the shared and distinct microbiota between the sample types of both facilities. Amplicon sequence variants (ASVs) of the V3-V4 region of the 16S rRNA gene revealed that the microbiota of milk samples had lower diversity than water or environmental swabs (279 ASVs compared to 3,444 in water and 8,747 in environmental swabs). <i>Brevibacterium</i> and <i>Yaniella</i> (both <i>Actinomycetota</i>) were observed in all sampling types. Further studies will include whole genome sequencing of <i>Brevibacterium</i> spp. isolates to determine their functionality and diversity within the system.