Novel Biomarkers of Mastitis in Goat Milk Revealed by MALDI-TOF-MS-Based Peptide Profiling

Abstract

Mastitis is the most common infection of dairy goats impairing milk production and quality, which is usually recognized by mammary gland visual inspection and palpation. Subclinical forms of the disease are also widely represented, which lack the typical signs of the clinical ones but are still associated with reduced production and safety for human consumption of milk, generally presenting a high bacterial count. In order to obtain novel analytical tools for rapid and non-invasive diagnosis of mastitis in goats, we analyzed milk samples from healthy, subclinical and clinical mastitic animals with a MALDI-TOF-MS-based peptidomic platform, generating disease group-specific spectral profiles whose signal intensity and mass values were analyzed by statistics. Peculiar spectral signatures of mastitis with respect to the control were identified, while no significant spectral differences were observed between clinical and subclinical milk samples. Discriminant signals were assigned to specific peptides through nanoLC-ESI-Q-Orbitrap-MS/MS experiments. Some of these molecules were predicted to have an antimicrobial activity based on their strong similarity with homolog bioactive compounds from other mammals. Through the definition of a panel of peptide biomarkers, this study provides a very rapid and low-cost method to routinely detect mastitic milk samples even though no evident clinical signs in the mammary gland are observed.

Keywords: biomarker; mastitis; milk goat; peptide profiling; peptidomic.

Figure 1

Classification of goat milk samples by different parameters. (A) Classification according to the clinical examination of goats; (B) classification according to bacteriological analysis of goat milk samples; (C) classification according to the combination of clinical examination and bacteriological analysis; (D) classification according to the combination of clinical examination, bacteriological analysis and evaluation of milk somatic cell count (SCC) values.

Figure 2

Average MALDI-TOF mass spectra of control milk samples (red), subclinical mastitic milk samples with SCC values < 500 × 10³ cells/mL (green), subclinical mastitic milk samples with SCC values = 500–1500 × 10³ cells/mL (blue), subclinical mastitic milk samples with SCC values > 1500 × 10³ cells/mL (apple green), clinical mastitic milk samples with SCC values < 500 × 10³ cells/mL (violet), clinical mastitic milk samples with SCC values = 500–1500 × 10³ cells/mL (dark green), clinical mastitic milk samples with SCC values > 1500 × 10³ cells/mL (dark blue).

Figure 3

Average intensity trends of serum amyloid A3 peptide markers identified by MALDI-TOF-MS profiling of subclinical, clinical and control milk samples.

Figure 4

Determination of milk amyloid A in mastitic goat milk samples. Protein from subclinical (left) and clinical (right) samples with different SCC was titrated by sandwich ELISA according to what reported in the experimental section. Samples were analyzed in duplicate and data are reported as mean values ± SEM. The program GraphPad Prism 6 (GraphPad Software, San Diego, CA, USA) was used to perform two-way ANOVA, followed by the Tukey post-hoc test. * p < 0.05; ** p < 0.01; *** p < 0.001.

Figure 5

Evaluation of the various proteolytic enzymes putatively involved in the release of the milk peptides. A logarithmic scatter plot graph plotted using odds ratio (X-axis) and the total sites cleaved by the enzyme at termini (Y-axis).