Effect of Different Farming Practices on Lactic Acid Bacteria Content in Cow Milk

An observational study of the presence and variability of the microbiota composition of goat herd milk related to mainstream and artisanal farm management

Goat milk is produced on mainstream and artisanal farms. It was expected that the farm management may influence the microbial population of the milk. Therefore, we investigated the bacterial content and microbiota composition of raw milk in relation to Dutch goat farm management. After amplicon sequencing we analyzed the taxa at phylum and genus levels, and used the relative values enabling to provide information about the variation among the different samples. On ten farms our results indicated that the number of bacterial colony forming units and microbiota composition of the milk, directly after milking was variable among farms and not related to the farm management system. At the phylum level the phyla Firmicutes, Actinobacteria, Proteobacteria, and to a minor extend Bacteriodota were the dominant phyla in the raw goat milk, together usually comprising 90% of the total bacterial phyla. The most dominant genera were Staphylococcus, Pseudomonas, Lactococcus, Microbacteria, Acinetobacteria, and Corinebacteria. The number of bacterial phyla and genera does not differ between the mainstream and artisanal farms, although the Shannon index may be numerically higher in the mainstream farms as compared to artisanal farms. In addition, the variability is higher among artisanal farms, which may be due to less standardization of the management. The milk microbiota composition differed among farms. Repeated sampling of a farm showed that this changed over time. The lactic acid producing bacteria showed a similar pattern. Variable microbiota richness amount and diversity of microorganisms were present in different farming systems. We concluded that farm-specific management and sampling moment were the major determining factors for the milk microbiota composition.

Lactic acid bacteria in cow raw milk for cheese production: Which and how many?

Lactic Acid Bacteria (LAB) exert a fundamental activity in cheese production, as starter LAB in curd acidification, or non-starter LAB (NSLAB) during ripening, in particular in flavor formation. NSLAB originate from the farm and dairy environment, becoming natural contaminants of raw milk where they are present in very low concentrations. Afterward, throughout the different cheesemaking processes, they withstand chemical and physical stresses becoming dominant in ripened cheeses. However, despite a great body of knowledge is available in the literature about NSLAB effect on cheese ripening, the investigations regarding their presence and abundance in raw milk are still poor. With the aim to answer the initial question: "which and how many LAB are present in cow raw milk used for cheese production?," this review has been divided in two main parts. The first one gives an overview of LAB presence in the complex microbiota of raw milk through the meta-analysis of recent taxonomic studies. In the second part, we present a collection of data about LAB quantification in raw milk by culture-dependent analysis, retrieved through a systematic review. Essentially, the revision of data obtained by plate counts on selective agar media showed an average higher concentration of coccoid LAB than lactobacilli, which was found to be consistent with meta-taxonomic analysis. The advantages of the impedometric technique applied to the quantification of LAB in raw milk were also briefly discussed with a focus on the statistical significance of the obtainable data. Furthermore, this approach was also found to be more accurate in highlighting that microorganisms other than LAB are the major component of raw milk. Nevertheless, the variability of the results observed in the studies based on the same counting methodology, highlights that different sampling methods, as well as the "history" of milk before analysis, are variables of great importance that need to be considered in raw milk analysis.

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

Raw cow milk is one of the most complex and unpredictable food matrices shaped by the interaction between biotic and abiotic factors. Changes in dairy farming conditions impact the quality and safety of milk, which largely depend on seasonality. Changes in microbiome composition and relative metabolic pathways are derived from microbial interactions, as well as from seasonality, mammary, and extramammary conditions (e.g., farm management and outdoor environment). Breeding data from >600 Apulian farms were examined, and the associated physicochemical parameters were processed by a reductionist approach to obtain a raw cow milk sample subset. We investigated the microbiological variability in cultivable and 16S rRNA sequencing microbiota as affected by seasonal fluctuations at two time points (winter and summer seasons). We identified families (Xanthomonadaceae, Enterobacteriaceae, and Pseudomonadaceae) whose increased abundance during winter may cause a shift toward a pathobiont microbial niche that leads to lower milk quality. Apulian summer season conditions were advantageous to the presence of specific taxa, i.e., Streptococcaceae (i.e., Lactococcus) and Limosilactobacillus fermentum, which in turn may favor better milk preservation.

IMPORTANCE The strength of this study lies in the microbiological characterization of a wide range of farm management data to achieve a more comprehensive framework of Apulian milk. Specific regional pedoclimatic and management conditions impact the taxa present and their abundances within this ecological food niche. The obtained results lay the groundwork for comparison with other worldwide extensive farming areas.

Bacterial Community of Grana Padano PDO Cheese and Generical Hard Cheeses: DNA Metabarcoding and DNA Metafingerprinting Analysis to Assess Similarities and Differences

The microbiota of Protected Designation of Origin (PDO) cheeses plays an essential role in defining their quality and typicity and could be applied to protect these products from counterfeiting. To study the possible role of cheese microbiota in distinguishing Grana Padano (GP) cheese from generical hard cheeses (HC), the microbial structure of 119 GP cheese samples was studied by DNA metabarcoding and DNA metafingerprinting and compared with 49 samples of generical hard cheeses taken from retail. DNA metabarcoding highlighted the presence, as dominant taxa, of Lacticaseibacillus rhamnosus, Lactobacillus helveticus, Streptococcus thermophilus, Limosilactobacillus fermentum, Lactobacillus delbrueckii, Lactobacillus spp., and Lactococcus spp. in both GP cheese and HC. Differential multivariate statistical analysis of metataxonomic and metafingerprinting data highlighted significant differences in the Shannon index, bacterial composition, and species abundance within both dominant and subdominant taxa between the two cheese groups. A supervised Neural Network (NN) classification tool, trained by metagenotypic data, was implemented, allowing to correctly classify GP cheese and HC samples. Further implementation and validation to increase the robustness and improve the predictive capacity of the NN classifier will be needed. Nonetheless, the proposed tool opens interesting perspectives in helping protection and valorization of GP and other PDO cheeses.