How multiple farming conditions correlate with the composition of the raw cow's milk lactic microbiome

Abstract

Questionnaires on farming conditions were retrieved from 2129 dairy farms and clustered, resulting in 106 representative raw cow's milk samples analysed in winter and summer. Substantiating the efficiency of our survey, some farming conditions affected the milk physicochemical composition. Culturing identified several species of lactic acid bacteria (LAB) per milk, whose number increased through 16S ribosomal RNA (rRNA) gene sequencing and shotgun metagenome analyses. Season, indoor versus outdoor housing, cow numbers, milk substitutes, ratio cattle/rest area, house care system during lactation, and urea and medium-chain fatty acids correlated with the overall microbiome composition and the LAB diversity within it. Shotgun metagenome detected variations in gene numbers and uniqueness per milk. LAB functional pathways differed among milk samples. Focusing on amino acid metabolisms and matching the retrieved annotated genes versus non-starter lactic acid bacteria (NSLAB) references from KEGG and corresponding to those identified, all samples had the same gene spectrum for each pathway. Conversely, gene redundancy varied among samples and agreed with NSLAB diversity. Milk samples with higher numbers of NSLAB species harboured higher number of copies per pathway, which would enable steady-state towards perturbations. Some farming conditions, which affected the microbiome richness, also correlated with the NSLAB composition and functionality.

Effect of Seasonality on Microbiological Variability of Raw Cow Milk from Apulian Dairy Farms in Italy

“…In addition, our data showed a significantly higher abundance of Limosilactobacillus fermentum in summer milk. In agreement, other studies have reported an enrichment of LAB genera during the hot season ( 15 , 20 , 54 ).…”

“…As the convergent result of a multitude of abiotic and biotic factors having a stochastic, deterministic, and temporary impact on the microbiota ( 2 , 3 , 15 , 20 ), milk has been recognized as one of the most complex and unpredictable food matrices.…”

“…These findings are in line with previously published studies arguing that mean temperatures ranging from T min 5°C to T max 11°C (with a minimum and maximum registered peak temperature of 0°C and 20°C, respectively) ( 33 ) and constant rainfall (increased humidity) during the cold season favor the growth of pathobionts ( 34 – 37 ). Additionally, the outdoor system (61% of interviewed farms) and pasture time during the cold season may drive the microbial taxa balancing on cow teats, milking parlors, and bedding surfaces ( 8 , 20 ). Specifically, while grazing, cattle may come into contact with microorganisms that typically belong with soil and plants, i.e., Xanthomonadaceae , Pseudomonadaceae , and Enterobacteriaceae ( 38 – 40 ), which may be later transferred to bedding surfaces.…”

Fermented Foods, Health and the Gut Microbiome

“…While the majority of cheeses are produced from cow’s milk, cheese from sheep, goats, buffalo, camels, and even donkeys is manufactured [ 43 ]. Genera common to all raw milk include Lactococcus , Lactobacillus , Leuconostoc , Streptococcus , and Enterococcus , although certain varieties are more strongly associated with one type or another, which impacts the microbiome of a final product [ 44 , 45 , 46 ]. For example, while the predominant genera in cow’s milk include Pseudomonas , Bacillus , Lactococcus , and Acinetobacter , the genera most common to raw camel’s milk include Enterococcus , Lactococcus , and Pediococcus [ 47 , 48 ].…”

Genetic diversity of Lactobacillus delbrueckii isolated from raw milk in Hokkaido, Japan

“…However, the bacterial flora in raw milk collected in tanks on farms after milking is affected by the season, farm environment, cow hygiene and rearing environment, and storage conditions of raw milk. Lactobacillus delbrueckii evaluated in this study was isolated from milk sampled from a tank in a milk plant, and its flora may be influenced by various factors (Hagi et al, 2010;Hagi et al, 2013;Cao et al, 2021;Hornik et al, 2021;Nikoloudaki et al, 2021).…”