Abstract
Flow cytometry is a powerful technology used in many fields of cell biology. It is also used as a routine method to count somatic cells in milk and to characterize bovine milk leukocytes. In this study, we used flow cytometry to simultaneously assess the viability, the percentage of the single subsets of leukocytes and to quantify the expression of CD11b, an immunological marker of cell activation status. Immunological markers were then related with on farm recorded parameters as milk electrical conductivity (MEC) and average milk flow rate (MFR). Composite milk samples were collected from 43 cows, nine of which had naturally infected udders and 34 of which had no infected udders. First, the milk samples were classified according to bacteriological test in positive and negative. The results showed that the negative samples to bacteriological test had: (i) significantly higher percentages of live lymphocytes; (ii) significantly lower percentages of CD11b+ leukocytes; (iii) significantly lower MEC and higher MFR values. Then, samples were classified in three groups according to somatic cell count (SCC): Group A (n = 15), samples with SCC ≤ 100,000 cells/mL, all negative to bacteriological analysis; Group B (n = 11), samples with 100,000 < SCC < 300,000 cells/m, with four samples positive to bacteriological analysis; Group C (n = 17), samples with SCC ≥ 300,000 cell/mL with five samples positive to bacteriological analysis. Multivariate discriminant analysis was used to verify which flow cytometry immunological markers and on farm recorded parameters could better discriminate among the different groups of SCCs. Linear discriminant analysis (LDA) indicated that 5 of the 10 parameters could best be used to reveal the differences between positive and negative samples among the considered groups of SCCs. Furthermore, the Canonical discriminant analysis (CDA) indicated that composite milk samples with different SCC and infection status were clearly separated from each other in a two-dimensional space. In conclusion, the study highlighted that: (1) the conventional flow cytometry analysis applied on milk samples is a useful tool to investigate immunological parameters as potential indicators of udder health; (2) the combined evaluation of live milk leukocytes and recorded farm parameters could be useful to assess udder health status in dairy cows. The results obtained from this pilot study on few data require new and larger trials to be confirmed.
Highlights
Somatic cell count (SCC) has been used for a long time as an indicator of udder health and it is an important parameter in the dairy industry since it affects the price of milk
Results showed that the percentage of live lymphocytes and the expression of CD11b on milk leukocytes could be considered as potential biomarkers of udder health status in dairy cows
The flow cytometry-detected parameters were compared with automated recorded data, milk electrical conductivity (MEC) and milk flow rate (MFR), to test whether considered parameters could be used to classify milk samples by categories of microbiological status and somatic cell count (SCC)
Summary
Somatic cell count (SCC) has been used for a long time as an indicator of udder health and it is an important parameter in the dairy industry since it affects the price of milk. Besides the determination of SCC, flow cytometry was used to characterize the relative proportion of lymphocytes, macrophages and polymorphonuclear leukocytes (PMN), called differential cell count (DCC) and was proposed as a valid tool to identify inflammatory processes in animals with low SCC [3,4]. Differential somatic cell count (DSCC), a method for routine mastitis screening by a milk analyzer has been described by Damm and coworkers [5]. Wall and colleagues [6] indicated that the combination of DSCC and SCC could lead to increased sensitivity in mastitis monitoring. A newly published study showed that the DSCC may be a marker to identify early changes in milk composition as a result of an alteration in the milk secretion mechanism [7]
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