The proteomic advantage: label-free quantification of proteins expressed in bovine milk during experimentally induced coliform mastitis.

Coliform mastitis remains a primary focus of dairy cattle disease research due in part to the lack of efficacious treatment options for the deleterious side effects of exposure to LPS, including profound intra-mammary inflammation. To facilitate new veterinary drug approvals, reliable biomarkers are needed to evaluate the efficacy of adjunctive therapies for the treatment of inflammation associated with coliform mastitis. Most attempts to characterize the host response to LPS, however, have been accomplished using ELISAs. Because a relatively limited number of bovine-specific antibodies are commercially available, reliance on antibodies can be very limiting for biomarker discovery. Conversely, proteomic approaches boast the capability to analyze an unlimited number of protein targets in a single experiment, independent of antibody availability. Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS), a widely used proteomic strategy for the identification of proteins in complex mixtures, has gained popularity as a means to characterize proteins in various bovine milk fractions, both under normal physiological conditions as well as during clinical mastitis. The biological complexity of bovine milk has, however, precluded the complete annotation of the bovine milk proteome. Conventional approaches to reducing sample complexity, including fractionation and the removal of high abundance proteins, has improved proteome coverage, but the dynamic range of proteins present, and abundance of a relatively small number of proteins, continues to hinder comparative proteomic analyses of bovine milk. Nonetheless, advances in both liquid chromatography and mass spectrometry instrumentation, including nano-flow liquid chromatography (nano-LC), nano-spray ionization, and faster scanning speeds and ionization efficiency of mass spectrometers, have improved analyses of complex samples. In the current paper, we review the proteomic approaches used to conduct comparative analyses of milk from healthy cows and cows with clinical mastitis, as well as proteins related to the host response that have been identified in mastitic milk. Additionally, we present data that suggests the potential utility of LC-MS/MS label-free quantification as an alternative to costly labeling strategies for the relative quantification of individual proteins in complex mixtures. Temporal expression patterns generated using spectral counts, an LC-MS/MS label-free quantification strategy, corresponded well with ELISA data for acute phase proteins with commercially available antibodies. Combined, the capability to identify low abundance proteins, and the potential to generate temporal expression profiles, indicate the advantages of using proteomics as a screening tool in biomarker discovery analyses to assess biologically relevant proteins modulated during disease, including previously uncharacterized targets.

Confirmation of peanut protein using peptide markers in dark chocolate using liquid chromatography-tandem mass spectrometry (LC-MS/MS).

Detection of peptides from the peanut allergen Ara h 1 by liquid chromatography-mass spectrometry (LC-MS) was used to identify and estimate total peanut protein levels in dark chocolate. A comparison of enzymatic digestion subsequent to and following extraction of Ara h 1 from the food matrix revealed better limits of detection (LOD) for the pre-extraction digestion (20 ppm) than for the postextraction digestion (50 ppm). Evaluation of LC-MS instruments and scan modes showed the LOD could be further reduced to 10 ppm via a triple-quadrupole and multiple-reaction monitoring. Improvements in extraction techniques combined with an increase in the amount of chocolate extracted (1 g) improved the LOD to 2 ppm of peanut protein. This method provides an unambiguous means of confirming the presence of the peanut protein in foods using peptide markers from a major allergen, Ara h 1, and can easily be modified to detect other food allergens.

Detection, confirmation, and quantification of staphylococcal enterotoxin B in food matrixes using liquid chromatography--mass spectrometry.

Although immunoassay-based methods are sensitive and widely used for measuring protein toxins in food matrixes, there is a need for methods that can directly confirm the molecular identity of the toxin in situations where immunoassay tests yield a positive result. A method has been developed that uses mass spectrometry to identify a protein toxin, staphylococcal enterotoxin B (SEB), in a model food matrix, apple juice. The approach employs ultrafiltration to remove low molecular weight components from the sample, after which the remaining high molecular weight fraction, containing the protein, is digested with trypsin. The tryptic fragments are separated from residual biopolymers and analyzed by liquid chromatography-electrospray mass spectrometry. The background is still sufficiently complex that tandem mass spectrometry (MS/MS) is used to confirm the identity of target peptides. Limits of detection are 80 ng of SEB for MS and 100 ng for full scan MS/MS, using a tryptic fragment as the analytical target. Lower detection limits can be obtained using selected ion monitoring and multiple reaction monitoring. The presence of SEB can be confirmed at concentrations as low as 5 parts-per-billion by increasing the size of the sample to 10 mL. The method is applicable to the detection of SEB in other water-soluble food matrixes.

Confirmation of the allergenic peanut protein, Ara h 1, in a model food matrix using liquid chromatography/tandem mass spectrometry (LC/MS/MS).

Enzymatic digestion of total protein along with liquid chromatography/tandem mass spectrometry (LC/MS/MS) was used to confirm the presence of a major peanut allergen in food. Several peptides obtained from the enzymatic digestion of the most abundant peanut allergen, Ara h 1, were identified as specific peptide biomarkers for peanut protein. Using ice cream as a model food matrix, a method was developed for the detection of the allergen peptide biomarkers. A key component of the method was the use of molecular mass cutoff filters to enrich the Ara h 1 in the protein extracts. By applying the method to ice cream samples containing various levels of peanut protein, levels as low as 10 mg/kg of Ara h 1 could routinely be detected. This method provides an unambiguous means of confirming the presence of the peanut allergen, Ara h 1, in foods and can easily be modified to detect other food allergens.