Abstract

   Bovine mastitis remains a primary focus of dairy cattle disease
   research due to its considerable negative economic impact on the dairy
   industry. Subclinical mastitis (SCM), commonly caused by Staphylococcus
   aureus, lacks overt clinical signs and the diagnosis is based on
   bacteriological culture and somatic cell counts of milk, both of which
   have limitations. The main objective of this study was to identify,
   characterize and quantify the differential abundance of milk whey
   proteins from cows with S. aureus SCM compared to whey from healthy
   cows. Using two-dimensional differential gel electrophoresis (2D-DIGE)
   coupled with liquid chromatography and tandem mass spectrometry, 28
   high-abundant proteins were detected in whey from mastitic milk, 9 of
   which had host defense functions. These included acute phase proteins
   involved in innate immunity and antimicrobial functions (e.g.,
   serotransferrin, complement C3, fibrinogen gamma-B chain and cathepsin
   B), and proteins associated with the immune response to pathogens
   (e.g., polymeric immunoglobulin receptor-like protein, MHC class I
   antigen and beta-2-microglobulin). These results provide a unique 2D
   map of the modulated milk proteome during S. aureus mastitis. The
   broader importance is that the identified proteins, particularly those
   with host-defense biological functions, represent potential candidate
   biomarkers of subclinical mastitis in dairy cows.

   Keywords: mastitis, bovine, proteomics, whey, milk proteins,
   Staphylococcus aureus, 2D-DIGE

1. Introduction

   Bovine mastitis is one of the most prevalent and costly diseases
   currently affecting dairy herds. The negative economic impact is
   primarily due to lowered milk production, penalties for high somatic
   cell count (SCC), discarded milk, increased culling rate or death from
   infection, and treatment costs. More than 80% of costs associated with
   mastitis are due to lowered milk production and discarded milk
   [[30]1,[31]2].

   Staphylococcus aureus is one of the most frequently isolated contagious
   mastitis pathogens causing either clinical or subclinical mammary gland
   infection. Subclinical infection is problematic in dairy cattle because
   it goes undetected clinically which leads to damage to the mammary
   tissues and subsequent decrease in milk production [[32]3]. Moreover,
   subclinical mastitis often leads to persistent and chronic infections
   because the bacteria have the ability to survive within the mammary
   epithelial cells [[33]4,[34]5]. The inflammatory response during
   establishment of the infection is characterized by a number of changes
   in milk composition due to infiltration of cellular components such as
   neutrophils, macrophages and soluble immune factors such as complement
   proteins and acute phase proteins which together synchronize to clear
   the infection and the pathogen [[35]6,[36]7]. Because these innate
   immune mediators are usually pathogen-dependent and play an important
   role in early stages of infection their identification can offer
   insights into the host inflammatory and immune responses during
   mastitis.

   Currently, there are no effective and efficient detection tests
   available to identify cattle with S. aureus-induced subclinical
   mastitis. Recently, proteomics has been widely applied to elucidate
   pathogenic mechanisms of mastitis during natural and experimental
   infections in different animal species [[37]8,[38]9,[39]10]. While
   specific cytokine levels and the effects of the innate immune response
   during bacterial mastitis have been documented [[40]7,[41]8], changes
   in milk protein expression profiles during naturally occurring
   subclinical S. aureus intramammary infection requires further
   investigation in order to identify valid biomarkers with the potential
   to faciliate diagnosis.

   The aim of this study was to investigate the changes of the protein
   profiles in milk whey in response to naturally occurring subclinical
   intramammary infection with S. aureus with the goal of identifying
   putative biomarkers for diagnostic purposes. In particular, the present
   study describes the differential abundance of whey proteins as
   proteomic signatures of S. aureus-positive whey fractions compared to
   uninfected milk samples. To our knowledge, this is the first study that
   utilizes two-dimensional differential gel electrophoresis (2D-DIGE), to
   characterize protein abundance in milk whey from cows with S. aureus
   mastitis. The results also provide insight into the role of milk
   proteins in host–pathogen interaction during S. aureus intramammary
   infection.

2. Materials and Methods

2.1. Cows and Sample Collection

   Milk samples were obtained from 12 lactating cows from the dairy herd
   at the Livestock Research and Innovation Centre—Dairy Facility of the
   University of Guelph in Elora, Ontario, Canada. We have previously
   performed a high-throughput, in-depth proteomic analysis on these
   samples using a gel-free approach with liquid chromatography–tandem
   mass spectrometry (LC–MS/MS) and label-free protein quantification
   [[42]9]. Cows were in mid- to late-lactation and ranged in age from 4
   to 8 years. Six cows were culture-positive for S. aureus with a high
   somatic cell count of more than 2 × 10^5 cells/mL which had a previous
   history of subclinical mastitis i.e., no systemic or localized signs of
   mastitis and no history of major systemic diseases. The control group
   included six healthy cows that were microbiologically negative for S.
   aureus with low SCC of less than 2 × 10^5 cells/mL with no previous
   history of clinical mastitis three months preceding sample collection.
   The cows were also selected based on the results of clinical
   examination (absence of systemic and local signs) to exclude clinical
   mastitis. A quarter of the milk samples (30 mL) were collected
   aseptically, transported on ice and immediately mixed with a protease
   inhibitor cocktail (Roche Diagnostics GmbH, Mannheim, Germany) in
   preparation for proteomic analysis. Microbiological examination and SCC
   were performed within 24 h. The use of all animals in this study was
   approved by the Animal Care and Use Committee of the University of
   Guelph.

2.2. Somatic Cell Counts (SCC) and Microbiological Examination

   Somatic cell counts were determined using a commercial automated cell
   counter (DeLaval Cell Counter DCC; DeLaval Canada, Sussex, NB, Canada).
   The bacteriological analysis was performed according to the standard
   procedures of the National Mastitis Council [[43]10]. Briefly, a
   loopful of each quarter sterile milk sample was plated on Columbia
   blood agar (CBA) supplemented with 5% sheep red blood cells, incubated
   at 37 °C and examined 24 h and 48 h for positive or negative results
   based on bacterial colony growth. S. aureus bacteria were identified by
   culture characteristic on selective media, Gram-staining and
   biochemical reactions [[44]11].

2.3. Sample Processing and Two-Dimensional Differential Gel Electrophoresis
(2D-DIGE)

   For the preparation of whey, milk samples were centrifuged at 3000× g
   and 4 °C for 30 min, and the fat layer was removed with a spatula. The
   skimmed milk was decanted into a clean tube, centrifuged again at
   45,000× g and 4 °C for 30 min and the supernatant collected and stored
   at −80 °C. The protein concentration of the whey fractions was
   estimated using a BCA Protein Assay (BCA Protein Assay kit, Pierce™,
   ThermoFisher Scientific, Ottawa, ON, Canada) and 50 µg of whey protein
   was labeled with 400 pmol cyanine dyes, Cy3 (control group) and Cy5
   (mastitic group) (Amersham CyDye DIGE Fluors, GE Healthcare, Montreal,
   QC, Canada). Equal amounts of all experimental samples were properly
   combined to create the internal pooled standard, which was labeled with
   the Cy2 cyanine dye. The labeled protein samples were then mixed and
   diluted in rehydration buffer (8 M urea, 2 M thiourea, 2% CHAPS, 65 mM
   dithiothreitol, 0.8% ampholyte) and applied to 24-cm IPG strips (pH 3
   to 10, non-linear; GE Healthcare, Montreal, QC, Canada) by passive
   rehydration overnight at room temperature. After rehydration, IPG
   strips were focused on an Ettan IPGphor IEF system at 20 °C (GE
   Healthcare, Montreal, QC, Canada) using a gradient voltage increase for
   a total of about 90,000 Vh for 20 h. After focusing, IPG strips were
   reduced in equilibration buffer I (6 M urea, 2% SDS, 1.5 M Tris-HCl pH
   8.8, 30% glycerol, and 2% (w/v) dithiothreitol), at room temperature
   for 20 min, then alkylated in equilibration buffer II (6 M urea, 2%
   SDS, 1.5 M Tris-HCl pH 8.8, 30% glycerol, and 2.5% (w/v) iodoacetamide)
   at room temperature for 20 min. The IPG strips were run in the second
   dimension on 10% to 20% precast Tris-HCl polyacrylamide gels (Jule
   Biotechnologies, Inc. Milford, CT, USA) in 0.1% w/v SDS, 25 mM Tris–HCl
   pH 8.3 as running buffer for 200 V for 17 h.

   Gels were scanned on a Typhoon 9410 scanner (GE Healthcare, Montreal,
   QC, Canada). All images were analyzed with DeCyder software 6.5 (GE
   Healthcare, Montreal, QC, Canada) and differential in-gel analysis
   (DIA) modules (GE Healthcare, Montreal, QC, Canada) for the detection
   and matching of spots, while statistical analysis of protein level
   changes was performed with the DeCyder BVA (biological variation
   analysis) module. The resultant images of control and mastitic whey
   proteomes were compared by calculation of fold changes in differential
   abundance and statistically evaluated with the DeCyder BVA module. A
   false discovery rate (FDR) of 1% was applied to minimize the number of
   false-positive results.

   Protein spots were characterized as differentially abundant between
   control and mastitic groups if showing a difference in fold change of
   ≥2-fold, with a statistically significant variation (p ≤ 0.05). Using
   preparative 2-D gels, the differentially abundant proteins were
   separated and matched with the analytical gels. For optimal matching,
   50 µg of proteins were labeled with Cy5 as described above and then
   mixed with 550 µg of non-labeled proteins on 24-cm IPG strips with a pH
   non-linear gradient of 3–10 (GE Healthcare, Montreal, QC, Canada). All
   strips were rehydrated, focused, and subjected to second dimension
   electrophoresis as described above. After electrophoresis, all gels
   were fixed in 10% methanol-7% acetic acid for 40–60 min and
   post-stained overnight in SYPRO Ruby stain (Lonza Bioscience,
   Walkersville, MD, USA). Gels were destained in 10% methanol–7% acetic
   acid for 40 min at room temperature and then imaged on a Typhoon
   scanner. Matching between 2D DIGE and 2D gels was performed using
   Decyder analysis software and differential in-gel analysis (DIA)
   modules and a spot-picking list was generated and exported to an Ettan
   Spot Picker (GE Healthcare, Montreal, QC, Canada). The gel plugs were
   excised and placed into wells of 96-well plates.

2.4. In-Gel Digestion and Liquid Chromatography–Tandem Mass Spectrometry
(LC–MS/MS) Analysis

   Gel plugs excised from the 2D gels were subjected to tryptic digestion.
   Briefly, gel plugs were destained at room temperature for 1 h in 25 mM
   ammonium bicarbonate–50% acetonitrile. Gel plugs were dehydrated in
   100% acetonitrile for 5 min at room temperature and then dried to
   completeness in a vacuum centrifuge for 20 min at 22 °C. Plugs were
   rehydrated in 15 μg/mL of trypsin (Sigma-Aldrich, St. Louis, MO, USA)
   in 25 mM ammonium bicarbonate and allowed to digest for 16 h at 37 °C.
   After digestion, peptides were extracted with 50% acetonitrile-5%
   trifluoroacetic acid at room temperature for 1 h. Peptides were
   concentrated in a vacuum centrifuge for 20 min at 22 °C. Samples were
   then analyzed on a linear ion trap-Orbitrap hybrid analyzer (LTQ
   Orbitrap, ThermoFisher Scientific, Ottawa, ON, Canada) outfitted with a
   nanospray source and EASY-nLC split-free nano-LC system (ThermoFisher
   Scientific, Ottawa, ON, Canada). Lyophilized peptide mixtures were
   dissolved in 0.1% formic acid and loaded onto a 75 μm × 15 cm PepMax
   RSLC EASY-Spray column filled with 2 μM C18 beads (ThermoFisher
   Scientific, Ottawa, ON, Canada) at a pressure of 800 BAR. Peptides were
   eluted over 60 min at a rate of 250 nl/min using a 0 to 35%
   acetonitrile gradient in 0.1% formic acid. Peptides were introduced by
   nano electrospray into an LTQ-Orbitrap hybrid mass spectrometer
   (ThermoFisher Scientific, Ottawa, ON, Canada). The instrument method
   consisted of one full MS scan (400–1400 m/z) in the Orbitrap mass
   analyzer with an automatic gain control target of 500,000 with a
   maximum ion injection of 100 ms followed by one microscan, and a
   resolution of 100,000. Ten data-dependent MS/MS scans were performed in
   the linear ion trap using the ten most intense ions at 35% normalized
   collision energy. The MS and MS/MS scans were obtained in a parallel
   fashion. In MS/MS mode automatic gain control targets were 10,000 with
   a maximum ion injection time of 50 ms. Minimum ion intensity of 10,000
   was required to trigger an MS/MS spectrum. The dynamic exclusion was
   applied using a maximum exclusion list of 500 with one repeat count
   with a repeat duration of 30 s and exclusion duration of 20 s.

2.5. Protein Identification

   The following database searching parameters were applied. All MS/MS
   samples were analyzed using Sequest (ThermoFisher Scientific, Ottawa,
   ON, Canada; version 1.4.0.288) and X! Tandem (The GPM, thegpm.org;
   version CYCLONE) (2010.12.01.1). Sequest was set up to search
   Uniprot_Bos_Taurus_Feb232015.fasta assuming the digestion enzyme
   trypsin. X! Tandem was set up to search the
   Uniprot_Bos_Taurus_Feb232015 database also assuming trypsin. Sequest
   and X! Tandem were searched with a fragment ion mass tolerance of 0.60
   Da and a parent ion tolerance of 10.0 PPM. Deamidation of asparagine
   and glutamine, oxidation of methionine and carbamidomethylation of
   cysteine were specified in Sequest as variable modifications. Scaffold
   (version Scaffold_4.4.1.1, Proteome Software Inc., Portland, OR, USA)
   was used to validate MS/MS-based peptide and protein identifications.
   Peptide identifications were accepted if they could be established at
   greater than 95.0% probability. Peptide probabilities from Sequest were
   assigned by the Scaffold Local FDR algorithm. Peptide probabilities
   from X! Tandem were assigned by the Peptide Prophet algorithm with
   Scaffold delta-mass correction. Protein identifications were accepted
   if they could be established at greater than 99.0% probability and
   contained at least 2 identified peptides. Protein probabilities were
   assigned by the Protein Prophet algorithm. Proteins that contained
   similar peptides, and could not be differentiated based on MS/MS
   analysis alone, were grouped to satisfy the principles of parsimony.
   Proteins sharing significant peptide evidence were grouped into
   clusters.

2.6. Gene Ontology (GO) and Pathway Enrichment Analyses

   To investigate the biological and clinical value of the identified
   differentially abundant proteins in the mastitic group through 2D-DIGE
   and mass spectrometry methods, in silico functional analyses were
   performed. Enrichment analyses for Gene Ontology (GO) terms were
   performed. The proteins were categorized based on their biological
   processes (BP), cellular components (CC) and molecular function (MF)
   using the Database for Annotation, Visualization and Integrated
   Discovery (DAVID) v6.8 software ([45]http://david.abcc.ncifcrf.gov/)
   [[46]12]. Pathway enrichment analysis was performed using the Kyoto
   Encyclopedia of Genes and Genomes (KEGG) [[47]13] to investigate the
   interaction between the differentially abundant proteins.

3. Results

   Proteomic analysis of whey fractions from normal and S. aureus mastitic
   bovine milk samples was performed using combined 2D-DIGE and MS
   procedures. Milk sample grouping was undertaken based on specific
   microbiological culture and somatic cell counting. Typical
   morphological and biochemical properties of S. aureus were identified
   including large, creamy hemolytic colonies on CBA, positive coagulase
   production within 18 h and sugar–alcohol fermentation.

   In order to identify protein signatures of each experimental group, the
   analysis was undertaken on 6 biological replicates in each group for a
   total of 6 gels. Only protein spots accurately detected and matched in
   all gels run on samples collected from all the biological replicates
   were considered for further identification. Analysis of the 2-D DIGE
   images with DeCyder software (GE Healthcare) through the Biological
   Variation Analysis (BVA) module allowed gel-to-gel matching and
   statistical analysis of protein abundance changes between samples
   (control and mastitic) across the 6 different gels by comparison with
   the pooled internal standard.

   Results of statistical analysis indicated significant differential
   abundance for numerous protein spots in the S. aureus-positive group
   compared to the control group as shown in the representative overlay
   2-D DIGE image ([48]Figure 1). In total, 22 differentially abundant
   spots that were significantly altered two-fold or greater (p < 0.05)
   were selected and picked from the preparatory gel and then further
   identified using LC–MS/MS analysis. Twenty-eight proteins were
   identified, 9 of which have a host defense-associated biological
   function. All the statistically significant spots were highly abundant
   in the mastitic whey samples and no low-abundant proteins were
   detected. The identified spots and their corresponding proteins that
   were modulated or high-abundant in association with S. aureus infection
   are summarized in Some spots were visible on the analytical 2D-DIGE gel
   images; however, they were undetected in the preparative gel possibly
   due to the relative lower protein concentration in the preparative gel,
   which may have resulted in difficulty in spot picking. Multiple spots
   were often identified representing isoforms of the same protein which
   might reflect possible post-translational modifications.

Figure 1.

   [49]Figure 1
   [50]Open in a new tab

   Proteomic analysis of milk whey proteins from healthy cows and cows
   with with S. aureus subclinical mastitis. Two-dimensional differential
   gel electrophoresis (2D-DIGE) composite image shows
   differentially-represented proteins in mastitic milk (red spots)
   compared to milk from healthy controls (green spots). Proteins with
   similar levels in both groups are represented by white spots. Gel spot
   numbers correspond to those indicated in [51]Table 1.

   In addition to the identification of host proteins in mastitic whey, we
   also detected proteins of bacterial origin when the results of LC–MS/MS
   analysis were screened against a S. aureus reference proteome database
   [[52]14] ([53]Table 2). The identified proteins were detected in four
   spots on the 2D-DIGE gels from mastitic whey. These spots are labelled
   A, B, C and D and they are not indicated in [54]Figure 1. Because the
   fold change and total spectral counts of these proteins were less than
   the bovine proteins, no further analysis was performed to quantify the
   identified bacterial proteins.

Table 2.

   List of proteins identified by searching a S. aureus reference proteome
   database.
   Spot Number Protein Name Protein Accession Numbers Unique Peptide Count
   Sequence Coverage
   A 50S ribosomal protein L19 RL19_STAA1 2 17.20%
   A Orotate phosphoribosyltransferase PYRE_STAAC,PYRE_STAAS 2 10.80%
   A Immunoglobulin G-binding protein A SPA_STAA8 8 23.10%
   B ATP-dependent Clp protease ATP-binding subunit ClpL CLPL_STAAR 5
   16.00%
   B DNA topoisomerase 4 subunit B PARE_STAEQ 5 13.30%
   B Hyaluronate lyase HYSA_STAA8 7 13.40%
   B Putative hemin import ATP-binding protein HrtA HRTA_STAAR 5 24.40%
   B Septation ring formation regulator EzrA EZRA_STAEQ 5 12.60%
   B Protein draper DRPR_DROME 6 16.10%
   C DNA-directed RNA polymerase subunit beta (Fragment) RPOC_STAAU 5
   12.10%
   C 60 kDa chaperonin CH60_STAAU 5 20.40%
   D Immunoglobulin G-binding protein A SPA_STAA8 10 26.60%
   D Staphopain B SSPB_STAAS 2 10.90%
   D Transcription termination/antitermination protein NusG NUSG_STAA8 2
   14.30%
   D Lactose phosphotransferase system repressor LACR_STAA8, LACR_STAAR 2
   18.30%
   D Acetylglutamate kinase ARGB_STAAR 2 22.70%
   [55]Open in a new tab

   Database name: Uniprot_Staphylococcus-aureus_Feb192017.fasta. Peptide
   thresholds: 95.0% minimum, Protein thresholds: 99.9% minimum and 2
   minimum unique peptides.

   To further investigate the biological and clinical value of the
   differentially abundant proteins identified in the mastitic group, GO
   functional annotations and enrichment analysis were performed and the
   proteins were categorized based on their biological processes (BP),
   cellular components (CC) and molecular function (MF) using DAVID
   analysis Differentially abundant proteins that were significantly
   enriched at a p-value <0.05 for each category are presented in
   [56]Table 3.

Table 3.

   Gene Ontology (GO) terms over-represented in significantly abundant
   whey proteins due to S. aureus mastitis.
   Categories Biological Processes Count ^1 p-Value ^2
   Cellular form GO:0044085~cellular component biogenesis 5 0.009
   GO:0065003~macromolecular complex assembly 4 0.017
   GO:0016043~cellular component organization 8 0.002
   GO:0022607~cellular component assembly 5 0.005
   GO:0009653~anatomical structure morphogenesis 5 0.008
   GO:0043933~macromolecular complex subunit organization 4 0.02
   GO:0051270~regulation of cell motion 3 0.008
   GO:0048856~anatomical structure development 6 0.021
   GO:0048646~anatomical structure formation involved in morphogenesis 3
   0.033
   GO:0051651~maintenance of location in cell 2 0.028
   GO:0051235~maintenance of location 3 0.001
   Regulation of cellular process GO:0032879~regulation of localization 4
   0.008
   GO:0051179~localization 9 0.011
   GO:0048523~negative regulation of cellular process 5 0.021
   GO:0048519~negative regulation of biological process 5 0.03
   GO:0065008~regulation of biological quality 5 0.029
   GO:0051049~regulation of transport 3 0.037
   GO:0001649~osteoblast differentiation 2 0.038
   Cell Death GO:0042981~regulation of apoptosis 4 0.017
   GO:0043065~positive regulation of apoptosis 3 0.022
   GO:0043068~positive regulation of programmed cell death 3 0.022
   GO:0010942~positive regulation of cell death 3 0.022
   GO:0043067~regulation of programmed cell death 4 0.018
   GO:0010941~regulation of cell death 4 0.018
   Response to stimulus GO:0009605~response to external stimulus 4 0.019
   GO:0050896~response to stimulus 8 0.005
   GO:0006950~response to stress 6 0.006
   GO:0009611~response to wounding 3 0.043
   Angiogenesis GO:0001944~vasculature development 3 0.022
   GO:0001568~blood vessel development 3 0.021
   [57]Open in a new tab

   Count ^1 = the number of proteins enriched in the GO term using DAVID
   (Database for Annotation, Visualization and Integrated Discovery)
   software. p-value ^2 = Absolute p-value where significantly (p ≤ 0.05)
   annotated proteins were considered.

   There were 30 GO terms identified for the BP category of which the top
   five were maintenance of location, cellular component organization,
   cellular component assembly, response to stimulus and response to
   stress. There were only five GO terms for the CC category which were
   extracellular region, extracellular space, macromolecular complex and
   protein complex. There were also only five GO terms for the MF category
   which included protein binding, oxygen binding, lipid binding and
   cytoskeletal protein binding.

   Pathway enrichment analysis performed using the KEGG pathway to
   investigate the interaction between the differentially abundant
   proteins indicated the following: S. aureus infection pathway
   (bta05150) was enriched with complement C3 and fibrinogen gamma-B chain
   (FGG); Antigen processing and presentation pathway (bta04612) was
   enriched with Cathepsin B (CTSB) and MHC class I antigen (BOLA-NC1);
   Complement and coagulation cascades pathway (bta04610) was enriched
   with FGG and C3 and ECM–receptor interaction pathway (bta04512) was
   enriched with COL1A1 and DAG1.

4. Discussion

   This study highlights the differential abundance of the proteomic
   signatures of S. aureus-positive whey fractions compared to the
   non-infected fractions and provides an insight into understanding the
   role of milk proteins in host-pathogen interaction during S. aureus
   intramammary infection. During intramammary infection, damage to the
   milk-secreting tissues occurs which results in a reduction of the
   synthetic capacity of the mammary epithelial tissues that becomes
   manifested clinically by decreased milk production. In the early stages
   of infection, the damage is minimal and reversible. The outcome of
   bacterial invasion of the mammary gland, whether it is clearance or
   establishment and persistence of the infection, is mainly dependent
   upon the effectiveness of the host defense response that occurs
   immediately after initial infection.

   Bovine milk contains a high concentration of proteins with wide-ranging
   functions. Although dominated by the six major milk proteins
   (α[S1]-casein, α[S2]-casein, β-casein, κ-casein, β-lactoglobulin, and
   α-lactalbumin), accumulated evidence has shown that milk also contains
   a range of low-abundance proteins which are associated with host
   defense functions that form a significant first line of defense against
   the invading pathogens. The detection and profiling of the
   low-abundance proteins is challenging due to the biological complexity
   and high dynamic range of the constituents of bovine milk. However,
   advances in proteomic technologies, improvement of bovine protein
   sequence databases and increased efforts to identify protein biomarkers
   for early detection of intramammary infections have been able to
   overcome many of these challenges. This is reflected in several studies
   investigating the host defense response to different environmental and
   contagious pathogens such as E. coli, Streptococcus uberis and S.
   aureus that cause clinical or subclinical mastitis in different animal
   species [[58]8,[59]9,[60]15,[61]16,[62]17,[63]18,[64]19]. While many
   studies have investigated the host defense response at the
   transcriptomic level of mammary epithelial cells during intramammary
   infection, few have focused on proteomic changes in milk in dairy cows
   with S. aureus mastitis [[65]9,[66]15]. To the best of our knowledge,
   this is the first study profiling the modulation of the bovine milk
   whey proteome during natural infection with S. aureus utilizing 2D-DIGE
   coupled with LC–MS/MS analysis.

   The 2D-DIGE technique is a robust quantitative method that allows
   direct comparison of spots between mastitic and healthy samples on the
   same gel, thus eliminating inter-gel variability. The DIGE workflow
   also provides a platform for relative quantitation of intact proteins
   that are differentially labeled with fluorescent dyes that improves the
   sensitivity of detection and statistical reliability of proteins that
   are differentially abundant.

   Identification of serotransferrin and serum albumin in mastitic whey
   suggests that changes in vascular permeability results in a compromised
   barrier between milk and blood leading to exudation of serum proteins
   into the milk [[67]20,[68]21]. Previous proteomic studies reported that
   serotransferrin and serum albumin were elevated in response to other
   bacterial infections resulting in mastitis
   [[69]8,[70]22,[71]23,[72]24].

   Some of the proteins which were differentially abundant in mastitic
   whey such as fibrinogen gamma-B chain and complement (C3) indicate the
   involvement of the complement and coagulation cascades. A recent study
   involving iTRAQ-proteomic analysis of mammary tissue from cows
   naturally infected with S. aureus suggested that clinical and
   subclinical mastitis might cause disturbances in coagulation due to
   fibrin accumulation and subsequent clot formation [[73]17]. Previously,
   complement C3 was identified in normal whey only [[74]25], however, in
   the present study it was identified in both mastitic and normal whey
   but with higher abundance in mastitic samples. This is in agreement
   with other studies that reported the essential biological role of the
   complement cascade in innate immunity by eliciting chemoattraction and
   activation of leukocytes, opsonization and killing of pathogens
   [[75]8,[76]22,[77]26,[78]27].

   The identification of polymeric immunoglobulin receptor-like protein
   (PIgR) with higher abundance in mastitic whey is particularly
   intriguing. PIgR is a transmembrane glycoprotein which is expressed in
   many mucosal epithelium cell types including mammary epithelial cells
   (MECs) [[79]28,[80]29]. Recently, several studies showed that PIgR is
   one of the pattern recognition receptors (PRRs) which are expressed and
   activated through the MECs to respond to bacterial infection and
   so-called pathogen-associated molecular patterns (PAMP). PIgR plays an
   active role in transporting IgG into the lactating mammary glands and
   facilitates the translocation of IgA across the MECs. Once at the
   apical side of MECs, PIgR is cleaved to release IgA into the alveolar
   lumen which suggests that this receptor may contribute to bridging the
   innate and the adaptive immune response in MECs [[81]28,[82]30,[83]31].

   Beta-2-microglobulin is a component of MHC class I molecules and is
   associated with transport of serum IgG into the mammary gland of cattle
   and is responsible for the transfer of IgG into colostrum [[84]32].
   Proteomic 2DE analysis of whey samples from cows and sheep with
   mastitis including subclinical mastitis have revealed elevated levels
   of beta-2-microglobulin [[85]18,[86]21,[87]33,[88]34].

   The abundance of cathepsin B in mastitic whey is consistent with
   previous studies which reported its increase in milk quarters infused
   with lipoteichoic acid (LTA) from S. aureus, in whey from cows with
   subclinical mastitis naturally infected with S. aureus or infected with
   Streptococcus uberis [[89]9,[90]20,[91]35]. Intracellular granules of
   polymorphonuclear neutrophils (PMNs) contain several neutral and acidic
   proteases such as elastase and cathepsins B and G that have the ability
   to kill different pathogens that cause mastitis [[92]30]. Additionally,
   these proteases contribute to the elevated SCC and the increased
   proteolysis of caseins during infection [[93]35,[94]36].

   The roles of apolipoproteins (APO) in lipid transport and as a
   component of high-density lipoproteins (HDL) have been well
   characterized [[95]37]. Recently, several investigations revealed other
   roles, such as anti-inflammatory functions, for apolipoproteins
   particularly APO A-I (APOA1). This includes inhibition of neutrophil
   activation and suppression of inflammatory cytokine release following
   E.coli intramammary infection suggesting a role in immune response
   modulation during mastitis [[96]38,[97]39]. The immune-modulatory
   functions of APOA1 were also reported during S. uberis and S. aureus
   mastitis but to a lesser extent [[98]18,[99]26]. In the current study,
   we observed that apolipoprotein-E (APO-E) was highly abundant in
   mastitic milk. Others have detected a high-abundance of APO-E in the
   cerebral spinal fluid of cows showing signs of BSE [[100]40]. However,
   the specific role of APO-E in inflammation, particularly during
   mastitis, requires further investigation.

   The relatively high abundance of different forms of casein (αS1-casein,
   αS2-casein, β-casein, κ-casein) in the whey of mastitic animals was
   unexpected in this study in view of our efforts to partially deplete
   caseins to enrich low abundant whey proteins. As reported previously
   [[101]8,[102]41], the concentration of caseins decreases during
   mastitis while the whey proteins (β-lactoglobulin, and α-lactalbumin)
   may increase or decrease if the epithelial cells lose their synthetic
   functions due to tissue damage. The increase of caseins in the current
   analysis may reflect proteolysis due to activation of plasmin during
   infection rather than a higher level of production of caseins
   [[103]20,[104]39].

   Several protein spots were characterized as bovine serum albumin (BSA)
   in the mastitic whey in the current study. The multiple isoforms of the
   BSA which were detected on 2D gels have the same molecular weight (69
   kD), however, they have different pI values which is similar to results
   demonstrated in a previous study [[105]42]. In contrast, others have
   reported shifts in both molecular weight and pI of BSA isoforms in
   mastitic whey due to E. coli infection [[106]22]. A possible
   explanation for the abundance of multiple forms of BSA is proteolysis
   as a result of trypsin digestion during sample preparation for MS
   analysis.

   The results of bioinformatics analysis reveal differential expression
   of proteins that reflect the biological processes and cellular
   activities occurring in the mammary gland during S. aureus infection,
   specifically the host defense biological functions. The categories
   generated by GO functional annotations and enrichment analysis signify
   responses of mammary tissues to the stresses initiated by the presence
   of the bacteria notably maintaining and regulating cell form and
   function, responding to stressful external stimuli and wounding,
   regulating cell death, and facilitating wound healing by promoting
   angiogenesis. While similar GO categories were identified in our
   previous assessment of these samples by shotgun proteomic analysis
   [[107]9], more specific GO categories were identified in that analysis
   reflecting the host response including antimicrobial responses, the
   acute phase response, cytokine production and pathogen recognition
   functions.

   When bacteria gain access to mammary tissues, a typical first line of
   host defense is activation of the innate immune response either by
   recognition of pathogen molecules or by upregulation of the local
   resident immune components in order to combat an invading pathogen. In
   the present study, several host defense proteins including PIgR,
   complement C3, fibrinogen gamma-B chain, APO-E and cathepsin B were
   differentially expressed. To the best of our knowledge, this is the
   first time that high abundances of complement C3, PIgR and APO-E have
   been identified in mastitic milk. While differential expression of the
   antimicrobial peptide Cathepsin B was also detected in our previous
   shotgun proteomic analysis of these samples [[108]9], other host
   defense proteins were identified including those with roles in
   antimicrobial activity (i.e., cathelicidin-4 peptidoglycan recognition
   protein, lactoperoxidase and lactotransferrin), the acute phase
   response (i.e., haptoglobin) and pathogen-recognition (i.e.,
   lipopolysaccharide-binding protein, monocyte differentiation antigen
   and chitinase-3-like protein 1). Changes in the expression levels of
   innate immune mediators, acute phase proteins and antimicrobial
   peptides could represent biomarkers of the host defense response that
   predict early intramammary infection with specific pathogens. It is
   likely that a panel of biomarkers will be necessary to enable the
   detection of subclinical stages of S. aureus mastitis with high
   sensitivity and specificity.

   In conclusion, increased knowledge of the host immune response to
   different mastitis pathogens is an essential prerequisite for the
   detection and diagnosis of subclinical mastitis. The results of the
   current study present, for the first time, 2D-DIGE analysis that
   elucidates the proteomic changes that occur in bovine milk naturally
   infected with S. aureus. There were inherent limitations in the
   gel-based approach used in this study that resulted in the low number
   of proteins identified in our proteomic analysis compared to our
   previous study in which LC–MS/MS and label-free proteomic analyses were
   used [[109]9]. Possible reasons include insufficient separation of
   low-abundance proteins and acidic and basic proteins from
   high-abundance, high molecular weight proteins likely due to the high
   complexity and the high dynamic range of proteins present in bovine
   milk. Moreover, the limited sensitivity of SYPRO Ruby staining of
   preparatory gels made it difficult to pick all differentially abundant
   proteins identified on analytical 2D-DIGE gels. Nonetheless, the
   majority of high-abundance proteins such as complement C3,
   serotransferrin, polymeric immunoglobulin receptor, cathepsin B and
   fibrinogen gamma-B chain have relevant biological functions related to
   host defense and acute phase responses. These data provide information
   about biomarkers that could be validated and subsequently used in
   future studies for the detection of intramammary infection at
   subclinical stages.

Table 1.

   List of proteins identified by 2D-DIGE/liquid chromatography–tandem
   mass spectrometry (LC–MS/MS) analysis that are highly abundant in milk
   from cows with subclinical Staphylococcus aureus mastitis.
   Function Protein Name Accession Number Gel Spot No. p-Value Fold Change
   Relative to Controls Mr (kDa) Unique Peptides Sequence Coverage (%)
   Host-Defense Proteins Serotransferrin [110]Q29443|TRFE_BOVIN 1 0.007
   3.3 77.6 3 50
   Polymeric immunoglobulin receptor [111]P81265|PIGR_BOVIN 1 0.007 3.3
   82.4 12 16
   2 0.003 5.3 82.4 13 15
   Fibrinogen gamma-B chain F1MGU7|F1MGU7_BOVIN 3 0.012 3.5 50.2 22 56
   Complement C3 G3X7A5|G3X7A5_BOVIN 4 0.0001 7.5 187.1 29 17.5
   5 0.025 6.2 187.1 43 23.7
   Beta-1,4-galactosyltransferase 1 [112]P08037|B4GT1_BOVIN 4 0.0001 7.5
   44.8 5 13.7
   MHC class I antigen H6V5G4|H6V5G4_BOVIN 4 0.0001 7.5 38.8 6 26.3
   Apolipoprotein E A7YWR0|A7YWR0_BOVIN 4 0.0001 7.5 35.9 4 17.7
   Cathepsin B [113]P07688|CATB_BOVIN 4 0.0001 7.5 36.6 13 34.4
   Beta-2-microglobulin [114]P01888|B2MG_BOVIN 13 0.001 20.3 13.6 5 25.4
   Major Milk Proteins Serum albumin [115]P02769|ALBU_BOVIN 3 0.012 3.5
   69.2 5 8.5
   4 0.0001 7.5 69.2 27 51.6
   5 0.025 6.2 69.2 15 29.8
   6 0.002 11.3 69.2 11 20.8
   11 0.003 13.7 69.2 7 13.7
   Alpha-S1-casein [116]P02662|CASA1_BOVIN 7 0.005 17.1 24.5 4 32.7
   8 0.002 24.7 24.5 7 35
   9 0.002 13.7 24.5 21 48.1
   Alpha-S2-casein [117]P02663|CASA2_BOVIN 6 0.002 11.3 26.0 3 16.2
   Beta-casein [118]P02666|CASB_BOVIN 11 0.003 13.7 25.1 5 21.4
   12 0.009 40.4 25.1 7 25
   13 0.001 20.3 25.1 6 21.9
   Kappa-casein [119]P02668|CASK_BOVIN 4 0.0001 7.5 21.2 5 30
   6 0.002 11.3 21.2 4 25.8
   Structural and Metabolic proteins Collagen alpha-1 (I) chain
   [120]P02453|CO1A1_BOVIN 3 0.012 3.5 138.9 4 3.1
   Actin, cytoplasmic 1 [121]P60712|ACTB_BOVIN 4 0.0001 7.5 41.7 23 60
   5 0.025 6.2 41.7 11 33.3
   6 0.002 11.3 41.7 29 72.8
   7 0.005 17.1 41.7 3 8.5
   Actin, cytoplasmic 1 [122]P60712|ACTB_BOVIN 10 0.002 21.9 41.7 13 41.6
   11 0.003 13.7 41.7 6 24.3
   13 0.001 20.3 41.7 6 17.9
   Dystroglycan F1N7D7|F1N7D7_BOVIN 4 0.0001 7.5 97.3 5 7.26
   N-acetylglucosamine-1-phosphotransferase subunit gamma
   [123]Q58CS8|GNPTG_BOVIN 4 0.0001 7.5 33.7 5 19.3
   Hemoglobin subunit alpha [124]P01966|HBA_BOVIN 10 0.002 21.9 15.1 4
   31.7
   Thymosin beta-4 [125]P62326|TYB4_BOVIN 10 0.002 21.9 5 3 54.5
   Histone H2B F1MUD2|F1MUD2_BOVIN 10 0.002 21.9 13.9 3 38.1
   Histone H1.2 [126]P02253|H12_BOVIN 10 0.002 21.9 21.3 3 11.7
   Unknown Putative uncharacterized protein A5D7Q2|A5D7Q2_BOVIN 4 0.0001
   7.5 51.6 4 9.65
   [127]Open in a new tab

Acknowledgments