Proteomics, Genomics, and Pathway Analyses of Escherichia coli and Staphylococcus aureus Infected Milk Whey Reveal Molecular Pathways and Networks Involved in Mastitis Eveline M. Ibeagha-Awemu,† Aloysius E. Ibeagha,† Serge Messier,‡ and Xin Zhao*,† Department of Animal Science, McGill University, 21111 Lakeshore Road, Ste-Anne-De-Bellevue, Quebec H9S 3 V9, Canada, and Department of Pathology and Microbiology, Faculty of Veterinary Medicine, University of Montreal, 1500 venue des Ve´te´rinaires, St-Hyacinthe, Que´bec J2S 6N9, Canada Received April 13, 2010
Gram-negative and -positive bacteria elicit different response patterns by the host. The proteomic profiles of milk whey samples from cows naturally infected with Escherichia coli or Staphyloccocus aureus as compared to whey from healthy cows were determined by one-dimensional, liquid chromatographytandem mass spectrometry (LC-MS/MS), bioinformatics processing, and pathway analyses. Since mammary epithelial cells contribute to immune responses in mammary glands, the genes of selected proteins were measured in MAC-T cells by real time quantitative PCR (qPCR) after stimulation with heat inactivated E. coli strain P4 and S. aureus strain Smith CP bacteria. A total of 173 proteins were identified including 73 proteins differentially expressed among normal, E. coli, and S. aureus treatment groups. E. coli was more effective at significantly altering the concentration of the affected proteins. The mRNA of 23 proteins out of 24 measured by qPCR was significantly altered in MAC-T cells. Pathway analyses identified top canonical pathways significantly enriched in our samples, the most significant being the acute phase response signaling pathway. Also, top networks of genes with significant associations to identified proteins were identified. Our study has demonstrated a wider proteome profile of E. coli and S. aureus mastitic milk whey, identified more low abundant defense proteins than reported before, and has linked for the first time identified proteins to several network functions and Biocarta pathways. Keywords: Escherichia coli • Staphyloccocus aureus • defense proteins • binding proteins • molecular pathways • acute phase response signaling • milk whey • mastitis • cow
Introduction Mastitis, a disease of the mammary gland, most commonly results from bacterial infection and remains one of the most important infectious diseases of dairy cattle with grievous consequences to the dairy industry.1 Gram-positive Staphyloccucus aureus (S. aureus) and Gram-negative Escherichia coli (E. coli) bacteria are among the most prevalent mastitis bacteria. Pathogenic ligands from Gram-negative and positive bacteria elicit different response patterns in the host often leading to different degrees of mastitis development, either clinical or subclinical. The innate immune system represents the primary host determinant for dictating the outcome of intramammary infection. Using proteomic techniques, several authors have identified the presence of low abundance proteins, including defense proteins and differential expression of the major milk proteins in milk from cows with experimentally challenged or naturally occurring mastitis2-6 and in healthy milk.4,7 Also, the gene * To whom correspondence should be addressed. E-mail: xin.zhao@ mcgill.ca; tel: +1 514 398 7975; fax: +1 514 398 7964. † McGill University. ‡ University of Montreal.
4604 Journal of Proteome Research 2010, 9, 4604–4619 Published on Web 07/27/2010
expression of factors related to the immune response that occur in response to released toxins from E. coli and S. aureus bacteria, and other mastitis causing bacteria have been characterized by the use of nonproteomic techniques (such as PCR, microarray, real time quantitative PCR, and ELISA).6,8-13 The role of the mammary epithelial cells in mounting an immune response to the presence of bacterial pathogens has also been examined.12,14-18 However, more work is still needed to elucidate the network of proteins expressed in milk during mastitis for a better understanding of the biological events that occur during this period. Furthermore, the list of genes or proteins generated from proteomics or transcriptone studies do not explain much unless they are connected to known biological functions, pathways, and networks. Such connections may shed more light on the nature of relationships among expressed genes during mastitis and may open-up new strategies of control. Bovine milk contains about 3.3% protein, of which caseins constitute about 80% and the remaining 20% are the major whey proteins, beta-lactoglobulin (LGB), alpha-lactalbumin (LALBA), albumin (ALB), and other low abundant proteins. The whey fraction of milk is generally regarded as a functional food with potential health benefits due to the bioactive properties 10.1021/pr100336e
2010 American Chemical Society
research articles of the proteins and the presence of proteins with defense properties.19 However, the presence of highly abundant proteins generally hampers a clearer elucidation of the less abundant proteins,4 requiring further processing like fractionation or immuno-depletion of the major proteins.7 As a result, relatively little is known about the occurrence and expression of less abundant milk whey proteins as affected by the presence of mastitis pathogens. With application of recent advances in proteomics, a clearer picture of milk whey proteome under the conditions of naturally occurring E. coli and S. aureus mastitis may identify new protein targets or biomarkers, involved pathways, and regulated networks of functions that may pave the way for the development of new monitoring and control measures. The aims of this study were (1) to determine the protein expression profiles of milk whey of cows with naturally occurring mastitis caused by E. coli and S. aureus, (2) to determine the contribution of mammary epithelial cells to the expression of selected proteins detected in the proteomics analyses, and (3) to determine biological functions, canonical pathways, and networks significantly enriched during E. coli or S. aureus mastitis.
Figure 1. One dimensional (1D) SDS gel electrophoresis of normal (control) and mastitic (E. coli and S. aureus) milk whey in 7-15% polyacrylamide gels showing differential protein profiles (band pattern and intensities). Only one sample from each category is shown. All bands, marked 1-15, were excised for mass spectrometry analysis.
Experimental Procedures Mastitic Milk Samples. Milk samples from dairy cows with naturally occurring mastitis were submitted for bacteriological analysis to the Faculte´ de Me´decine Ve´te´rinaire, Universite´ de Montre´al. All cows came from dairy farms in the province of Que´bec, Canada, and were part of the national cohort of dairy farms of the Canadian Bovine Mastitis Research Network. Cows were in their first to fourth parities. From each sample, 10 µL aliquots were streaked on Columbia base agar supplemented with 5% sheep blood (CBAB) (PML Microbiologicals, Mississauga, ON, Canada) or McConkey agar (MAC) (PML Microbiologicals). The CBAB and MAC plates were incubated at 35 °C under aerobic conditions and examined after 24 and 48 h of incubation. Bacteria were identified based on the macroscopic appearance of the colonies (size, color, hemolysis on CBAB), the microscopic morphology after Gram staining, and results of biochemical tests.20 After pathogen identification, six milk samples infected with E. coli and six infected with S. aureus were randomly selected for use in the proteomics study. As a control, five samples from healthy cows at the Howard Webster Centre-Macdonald Teaching Farm, McGill University, without mammary gland infections were used. Milk Whey. Milk whey was obtained by centrifugation of whole milk at 13000g for 30 min at 4 °C. After centrifugation, the middle clear portion (whey) was removed and subjected to a second round of centrifugation (13000g for 30 min at 4 °C). The middle clear portion was again removed and stored at -80 °C until used. This process removes fat and cell debris and partially depletes caseins. One Dimensional (1D) SDS-PAGE and Automated Band Excision. The protein concentration of whey samples was determined with a 2D Quant protein assay (GE Healthcare, Baie d’Urfe, Quebec, Canada) and 30 µg of protein of each sample was resolved on 2.4 cm 1D SDS-PAGE with 7-15% acrylamide gradient. The gels were then stained with Coomassie Brilliant blue G (Sigma, Oakville, Ontario, Canada). Each lane (total of 17 lanes representing 17 samples) was subjected to automated band excision, to generate 15 bands per lane (Figure 1). The Protein Picking Workstation, ProXCISION (Perkin-Elmer, Walth-
am, Massachusetts, USA) was set to excise 5-7 pieces per band (about 1275-1785 gel pieces in total), depending on the width of the lane. In-Gel Tryptic Digestion, Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) Analysis and Bioinformatics Data Processing. Gel pieces containing proteins were destained, reduced, cysteine-alkylated, and in-gel digested by automation in a MassPrep Workstation (Micromass, Manchester, UK) as previously described.21 Extracted peptides were then subjected to mass spectrometry analysis by injecting onto a Zorbax 300SB-C18 precolumn (5 × 0.0 mm, 5 µm) linked to an HPLC system (Agilent 1100 Series, Agilent Technologies, SantaClara, CA, USA). Prior to injection, the precolumn was conditioned with water containing acetonitrile (3%) and formic acid (0.1%) supplied by an Isocratic pump (Agilent 1100 series) set at a flow rate of 15 µL/min. A volume of 20 µL of the tryptic digest solution was injected on the precolumn at 15 µL/min and the sample was washed for 5 min, and subsequently the valve holding the precolumn was flushed to the 75 µm i.d. PicoFrit column (New Objective, Woburn, MA) (filled with 10 cm of BioBasic C18 packing, 5 µm, 300 Å) by the acetonitrile gradient (supplied by the Agilent series 1100 Nanopump) at 200 nL/min. The linear gradient was started after the washing step and after 5 min, solvent B (acetonitrile/water (95:5) containing formic acid 0.1%) was at 10.5%. It was further set to reach 42% at 45 min, 73.5% at 53 min, and 100% at 65 min and was then kept at 100% for 5 min and brought back to 10.5% in 2 min. Eluted peptides were analyzed in a QTOF Micro (Waters Micromass, Manchester, UK) equipped with a Nanosource modified with a nanospray adapter (New Objective, Woburn, MA) to hold the PicoFrit column tip near the sampling cone. The capillary voltage was adjusted to get the best spraying plume at 35% B. MS survey scan was set to 1 s (0.1 s interscan) and recorded from 350 to 1600 m/z. In a given MS Survey scan (1 MSMS precursor per scan), all doubly and triply charged ions with intensity higher that 25 counts were considered candidates to undergo MS/MS fragmentation. From these, the strongest one was selected. MS/MS acquisition was stopped as soon as the total ion current reached 2800 counts/s or after a maximum time of 4 s. MS/MS scan was acquired from 50 to 1990 Journal of Proteome Research • Vol. 9, No. 9, 2010 4605
research articles m/z, scan time was 1.35 s, interscan was 0.15 s, and a maximum of three scans were summed per precursor selected. Also, a second precursor ion was selected from the following MS Survey scan, while the previous ion selected in MSMS was excluded for 90 s (data dependent analysis). The doubly and triply charged selected ions were fragmented with collision energies calculated using a linear curve from reference collision energies. MS/MS raw data were transferred from the QTOF Micro computer to a 50 terabytes server and automatically manipulated for generation of peaklists by employing Distiller version 2.1.0 (http://www.matrixscience.com/distiller.htmls) software with peak picking parameters set at 30 for Signal Noise Ration (SNR) and at 0.6 for Correlation Threshold (CT). The peaklisted data were searched against a copy of the Universal Protein Resource (UniProt) database (accessed on May 21, 2009) by employing Mascot version 2.1.04 (http://www.matrixscience. com) and X!Tandem version 2007.01.01.1 (http://www.thegpm. org), and restricting the search to up to 1 missed (trypsin) cleavage, fixed carbamidomethyl alkylation of cysteines, variable oxidation of methionine, 0.5 Da mass unit tolerance on parent and fragment ions, and monoisotopic. The search was limited to three taxonomies, Mammalia (Taxonomy ID: 40674), Escherichia coli (Taxonomy ID: 562), and Staphylococcus aureus (Taxonomy ID: 1280) (359 148 sequences; 122 994 690 residues). The Mascot/X!Tandem search results (based on spectra assigned to tryptic peptide sequences at the 95% confidence level) were loaded into Scaffold version 2.2 (Proteome Software Inc., Portland, OR) as .dat files. Peptide identifications were accepted at greater than 95% probability. Protein identification was also accepted at greater than 95% probability and contained at least two identified peptides. The results were parsed and grouped based on the peptide and protein prophet algorithms to create a protein report satisfying the principles of parsimony.22,23 A statistical analysis comparing protein abundance between sample groups was done using Scaffold program and t test P-values < 0.05 were considered significant. Even though considerable variations exist between the samples since the control and infected samples did not come from the same individuals, a statistical analysis was considered to give an idea of the global occurrences during natural infection. Cell Culture Conditions. To validate identified proteins and investigate the contribution of mammary epithelial cells to protein profiles identified in the proteomics analysis, 24 proteins out of 73 proteins significantly altered by the presence of one or both pathogens (Table 1) were randomly selected to measure the expression of their mRNAs in MAC-T cells (a bovine mammary epithelial cell line)24 by quantitative real time PCR (qPCR) after stimulation with heat inactivated E. coli and S. aureus bacteria. An equal number of cells, about 500 000, were seeded in each well of a six-well cell culture cluster plate (Corning Incorporated, Corning, NY, USA) and grown in a medium containing DMEM (Sigma) and RPMI 1640 (Invitrogen, Burlington, Ontario, Canada) at a concentration of 1:1, 10% fetal bovine serum (FBS) (Invitrogen), 10 µL/mL ITS (insulin-transferrin-selenium solution) (Invitrogen), and 1% antibiotic antimycotic solution (100×) (Invitrogen) at 37 °C in 5% CO2 humidified incubator. At about 90% confluent growth, the medium was refreshed with another medium of the same composition except that no FBS 4606
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Ibeagha-Awemu et al. was added and cells were grown for 24 h and then treated with bacterial pathogens. Treatment of MAC-T Cells with E. coli and S. aureus Pathogens. The bacterial pathogens used were E. coli strain P4 and S. aureus strain Smith CP. S. aureus or E. coli was initially stripped on tryptic soy agar Petri dishes or Luria-Bertani agar Petri dishes respectively and cultivated overnight (16-18 h). On the following day, one colony each of S. aureus and E. coli was incubated overnight in 500 mL conical flasks each containing 10 mL of tryptic soy broth (S. aureus) or Luria-Bertani (E. coli) medium at 37 °C and diluted 1:1000 with the respective medium on the next day. Before infecting cells, one well of cells was harvested by trypsination and counted, and cells were infected with bacteria at an infection rate of 1:10. Bacteria were heat inactivated just before use in infecting cells by boiling at 63 °C for 30 min to prevent overgrowth during the period of cell challenge. Cells were harvested at 0 h (non-infected), 6, 12, 24, or 48 h (infected) for total RNA isolation. Three different samples were used for each time point for each pathogen. Harvesting was done by aseptically aspirating cell culture medium and adding 1 mL of tryzol reagent (Invitrogen) to cells. Total RNA Isolation and Reverse Transcription. Total RNA was isolated by using Tryzol reagent and PureLink RNA Mini Kit (Invitrogen) following manufacturer’s protocol. To completely exclude the presence of residual DNA, the RNA was treated with PureLink DNase (Invitrogen). The concentration and purity of the isolated RNA was checked by measurements on a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies Inc., Wilmington, DE, USA). The OD260/OD280 ratio of samples ranged from 2.10 to 2.18. The quality of RNA was further checked by agarose gel electrophoresis through staining with Safe View (Applied Biological Materials Inc., Richmond, BC, Canada) and visualization under UV light. The major 28S and 18S RNA bands were distinctly resolved. The samples were stored at -80 °C until being used. About 1.5 µg of total RNA was then reversed transcribed into cDNA with SuperScript III First-Strand Synthesis SuperMix for qRT-PCR (Invitrogen). The 30 µL RT reaction mixture contained 3 × RT reaction mix [including oligo(dT)20 (2.5 µM), random hexamers (2.5 ng/µL), 10 mM MgCl2, and dNTPs], 3 µL of Enzyme Mix (including SuperScript III RT and RNaseOUT), 1.5 µg of total RNA and DEPC treated RNase and DNase free water. The reaction mix was incubated at 25 °C for 10 min and the temperature was increased to 50 °C for 30 min. The reaction was terminated at 85 °C for 5 min and immediately chilled on ice. Three units of E. coli RNase H was added to the RT mixture and incubated at 37 °C for 20 min. cDNA was further diluted with DEPC treated water (ratio of 1:10) and stored at -80 °C until being used. Real Time PCR Quantification of Genes and Statistical Analysis. Primer sequences of 24 genes of selected proteins and two housekeeping genes are shown in Table S1, Supporting Information. The primers which in most cases span exon boundaries were synthesized by Invitrogen. The Fast SYBR Green Master Mix (Applied Biosystems, Foster City, CA, USA) and the ABI 7500 Fast Real-Time PCR System (Applied Biosystems) were used in the qPCR analysis. The qPCR mix was in a final volume of 10 µL and contained 2× Fast SYBR Green Master Mix, 200 nM each primer, 40% diluted cDNA and DEPC treated DNase and RNase free water. The thermal profile included an initial denaturation at 95 °C for 20 s followed by 50 circles of denaturation at 95 °C for 3 s and annealing/extension at 60 or 62 °C (see Table S1, Supporting Information) for 30 s.
research articles Table 1. Proteins Significantly Up-Regulated or Down-Regulated (-) by the Presence of Mastitis Pathogens As Compared to the Control Samplesa expression (fold change)b protein name
protein accession no.
gene accession no.
control
E. coli
S. aureus
A1BG AZGP1 AHSG APOA1 BTN1A1 CATHL1 CATHL2 CATHL4 C3 CFB CFH CORO1A FGB HSPCA HP ITIH4 LPO LTF PGLYRP1 PLG PTGDS ALB SAA3
1a 1a 1a 1a 1a 1a 0a 0a 1a 1a 1a 0a 0a 0a 0a 0a 1a 1a 1a 0a 1ab 1a 0a
17.500b -3.257b 3.167b 3.750b -11.099b 18.333b 1.833b 3.333b 1.497b 6.500b 20.833b 3.000b 5.833b 4.000b 10.667b 9.000b -2.325b 1.436ab 29.167b 2.167b -3.599a 1.77b 2.167b
6.667ab -2.682b 1a 2.760b -2.114b 12.917ab 1.167ab 2.333b 1.423b 3.167a 6.667ab 1.602a 7.333b 1.500ab 9.833b 6.833ab -1.583b 1.680b 18.333ab 0.167a 2.500b 1.00ab 1.167b
ACTN1 ACTN4 A2M LGB CP CHI3L1 CFL1 ENO1 FABP3 ALDOA GSN GAPDH GPI HPX MFGE8 LDHB LDHA LCP1 NPC2 NUCB1 PRDX5 CD36 PIGR S100A9 S100A8 ARHGDIB S100A12 SDS TF SERPINA1
0a 0a 0a 1a 1a 0a 0a 0a 1a 0a 0a 0a 0a 0a 1a 0a 0a 0a 1a 1a 0a 1a 1a 0a 0a 0a 0a 0a 1a 1a
1.167b 5.833b 30.667b -1.342b 30.00b 2.167ab 3.000b 3.312b -7.199b 3.500b 3.333b 3.333b 1.862b 2.833b -3.391b 3.833b 0.333b 4.000b -6.600b -0.000b 0.983b -2.55b -4.588b 3.833b 1.776b 2.667b 1b 4.000b 9.760b 1.923b
1.333ab 5.000ab 20.500b -1.085a 18.333ab 3.000b 1.500ab 5.115ab -2.618b 2.667ab 1.333a 1.167ab 1.211ab 2.000ab -1.814ab 2.000ab 0.167ab 2.667b 1.000a -2.300b 0.816ab -1.7a -1.238ac 1.833ab 0.833ab 1.833ab 0.667ab 2.833ab 2.020c 1.538ab
TTR YWHAZ
1a 0a
15.000b 2.833b
9.167b 2.000ab
GC XDH
1a 1a
2.396b -2.886b
1.042a -1.154ab
c
alpha-1-B glycoprotein alpha-2-glycoprotein 1, zinc-binding alpha-2-HS-glycoprotein apolipoprotein A-I butyrophilin subfamily 1 member A1 cathelicidin-1 cathelicidin-2 cathelicidin-4 complement component 3 complement factor B complement factor H coronin, actin binding protein, 1A fibrinogen beta chain heat shock 90 kDa protein 1, alpha haptoglobin interalpha (globin) inhibitor H4 lactoperoxidase lactotransferrin peptidoglycan recognition protein plasminogen prostaglandin D2 synthase 21 kDa serum albumin serum amyloid A 3
Immune Process/Response Q2KJF1 Q3ZCH5 B0JYN6 P15497 P18892 P22226 P19660 P33046 Q2UVX4 P81187 Q28085 Q92176 P02676 Q76LV2 Q2TBU0 Q3T052 P80025 P24627 Q8SPP7 P06868 B1H0W7 P02769 Q32PB7
Binding Activities alpha-actinin-1 Q3B7N2 alpha-actinin-4 A5D7D1 alpha-2-macroglobulin A8E647 beta-lactoglobulin P02754 ceruloplasmin Q32P72 chitinase-3-like protein 1 P30922 cofilin 1 (nonmuscle) B0JYL8 enolase 1 (alpha) Q9XSJ4 fatty acid-binding protein 3 P10790 fructose-bisphosphate aldolase A A6QLL8 gelsolin Q3SX14 glyceraldehyde-3-phosphate dehydrogenase P10096 glucose phosphate isomerase Q3ZBD7 hemopexin Q3SZV7 lactadherin (milk fat globule EGF factor 8 protein) Q95114 L-lactate dehydrogenase B0JYN3 L-lactate dehydrogenase A P19858 lymphocyte cytosolic protein 1 (L-plastin) Q3ZC00 Niemann-Pick disease, type C2 (epididymal secretory protein E1) P79345 nucleobindin-1 Q0P569 peroxiredoxin 5 Q9BGI1 platelet glycoprotein P26201 polymeric immunoglobulin receptor P81265 protein S100-A9 P28783 protein S100-A8 P28782 rho GDP-dissociation inhibitor (GDI) beta Q9TU03 S100 calcium binding protein A12 (calgranulin C) P79105 serine dehydratase Q0VCW4 serotransferrin Q29443 serpin peptidase inhibitor, clade A, member 1 (alpha-1 P34955 antiproteinase, antitrypsin) transthyretin O46375 trosine 3-monooxygenase/tryptophan 5-monooxygenase P63103 activation protein, zeta polypeptide vitamin D-binding protein Q3MHN5 xanthine dehydrogenase P80457
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Table 1. Continued expression (fold change)b protein name
protein accession no.
Enzyme Activities endopin-1 Q9TTE1 SERPINA3-5 A2I7N1 serpin peptidase inhibitor, clade B (ovalbumin), member 1 Q1JPB0 (leukocyte elastase inhibitor) serpin peptidase inhibitor, clade B, member 4 A6QPZ4 serpin peptidase inhibitor, clade G (C1 inhibitor), member 4 P50448 alpha-lactalbumin quiescin Q6 sulfhydryl oxidase 1 (MGC152578 protein) transketolase triosephosphate isomerase 1 profilin-1
Metabolic Process P00711 A6QQA8 A5PJ79 Q5E956 Biological Adhesion P02584
Unknown Function glycoprotein 2 (zymogen granule membrane) Q0IIA4 glycosylation-dependent cell adhesion molecule 1 P80195 hibernation-associated plasma protein HP-20-like (hypothetical Q2KIT0 protein LOC616715) immunoglobulin lambda light chain, lambda gene cluster Q3T101 immunoglobulin lambda light chain variable region Q2KIF5 Ig kappa chain or IGK protein B0JYP6
gene accession no.
control
E. coli
SERPINA3 SERPINA3-5 SERPINB1
1a 0a 0a
SERPINB4 SERPING1
0a 1ab
8.333b -2.159b
6.833b -1.200b
LALBA QSOX1 TKT TPI1
1a 0a 0a 0a
-1.94b 3.333b 2.500b 1.500b
-1.614c 1.000ab 2.333ab 1.167ab
PFN1
0a
4.500b
3.000ab
GP2 GLYCAM1 MGC137014
1a 1a 1a
-4.800b -1.482b 6.250b
-2.667ab -1.326ab 2.500a
IGL@ VI1a IGK
1a 1a 1a
1.488b 2.000b 4.583b
1.25ab 1.333ab 3.333ab
2.244b 1.833b 5.667b
S. aureus
2.628ab 2.000ab 6.167b
a For each protein, row values with different superscripts differ significantly (P < 0.05). b Peptide mass of proteins are expressed as fold change relative to control values arbitrarily set to 1. Where a control sample peptide mass is zero (protein not present or below detection limit), the corresponding actual values are recorded under E. coli and S. aureus. c Most of the identified proteins are involved in multiple functions.
During the qPCR run, each sample was replicated three times and the relative quantification method and the ABI 7500 System SDS Sequence Detection Software version 1.4.0 (Applied Biosystems) were used in mRNA quantification. The Relative Expression Software Tool, REST 2008 version 2.0.725 (http:// www.corbettlifescience.com) was used in calculating relative expression levels and pairwise significance in mRNA abundance of treatments (different time points) vs zero time point. REST uses randomization and bootstrapping in calculations. Two housekeeping genes, polyubiquitin and ribosomal protein, large, P0 (RPLO), were used in normalization. An efficiency correction ratio for each target was used in calculating pairwise significance. Pathway Analysis. To determine the biological processes, functions, pathways, and molecular networks that were significantly enriched by the proteins that emerged during response to the presence of E. coli or S. aureus pathogens, the Ingenuity Pathway Analysis (IPA) program (http://www. ingenuity.com) was used. During the analysis, both up- and down-regulated proteins were defined as value parameters for the analysis. All identifier types and data sources were selected for our analysis to take advantage of all available information on our protein set, and both direct and indirect relationships between proteins were considered. Networks generated during the analysis were ordered by a score that takes into account the number of focus proteins and the size of the networks, indicating the likelihood of the focus proteins in a network being found together by chance. A higher score value indicates a lower probability of finding the eligible protein in a given network by chance. Using a 99% confidence level, scores g3 were considered significant. The networks, pathways, and biological functional classification were formed by connecting proteins based on known relationships available in the IPA knowledge base. IPA also tests significance of canonical 4608
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pathways and biological functions by Fisher Exact test p-value. IPA is a manually curated database based on the published literature in humans and rodents.
Results Identified Proteins. The result of 1D gel electrophoresis showed clear visual differences between normal and mastitic milks (Figure 1). After subjection of all gel bands, numbered 1-15 to MS/MS, a total of 1603 peptides were observed. Out of this number, 131 peptides were unique to control samples, 171 to S. aureus samples and 278 to E. coli samples. All proteins identified by one peptide, even if present in all samples, were screened out. After fulfilling all screening criteria, a total of 173 proteins were detected in the studied samples (Table S2, Supporting Information). Of this number, 74 proteins were detected in all groups and 74 in diseased (i.e., both E. coli and S. aureus) samples (Table S3, Supporting Information). Furthermore, nine proteins were unique to E. coli infected milk, four to S. aureus milk, four to control milk, two to control and E. coli milk, and six to control and S. aureus milk (Table S3, Supporting Information). The peculiarity of identified proteins to certain treatment groups, either diseased or control samples, could mean their total absence in other groups or they were below detection threshold in other groups. Global Functional Classification of Identified Proteins. Gene ontology classification (GO is a major bioinformatics initiative to unify the representation of gene and gene product attributes across all species) of identified proteins according to biological process indicated that 20% are involved in cellular processes, 14.8% in metabolic processes, 14.5% in immunity and defense, 13% in biological regulation, 8.2% in localization, 4.8% in multicellular organismal processes, 4.4% in developmental processes, 8.6% in other functions, and 11.7% of unknown
research articles functions. Functional classification according to molecular functions indicated that about 35.2% of identified proteins are involved in molecular processes, 27.5% in binding activities, 12% in catalytic activities, 7.1% in enzyme regulator activities, 3.4% in transport activities, 3.4% in other functions (molecular transducer, antioxidant, structural molecule, and electron carrier activities) and 11.4% are of unknown molecular functions. Effect of Pathogens on Protein Expression. Statistical comparisons indicated differential amounts of about 42% (73) of identified proteins in the samples, either significantly (P < 0.05) up-regulated or down-regulated in E. coli or S. aureus samples or both as compared to normal samples (Table 1). Over 50% of the altered proteins existed only in the mastitic milks and were completely absent in normal milks. A majority of the affected proteins are involved in binding activities followed by proteins in the immune process or response. Other proteins with major function in enzyme activities, metabolic processes, and biological adhesion as well as proteins with unknown functions were also affected. E. coli was more effective at significantly altering the concentration of the affected proteins. For proteins involved in the immune response for example, only apolipoprotein A-1 (APOA1), cathelicidin 4 (CATHL4), complement component 3 (C3), fibrinogen beta chain (FGB), haptoglobin (HP), and serum amyloid A 3 (SAA3) were significantly upregulated by the presence of both E. coli and S. aureus, while alpha-1-B glycoprotein (A1BG), alpha-2-HS-glycoprotein (AHSG), cathelicidin 1 (CATHL1), cathelicidin 2 (CATHL2), complement factor B (CFB), complement factor H (CFH), coronin (CORO1A), heat shock 90 kDa protein 1 alpha (HSPCA), interalpha inhibitor H4 (ITIH4), peptidoglycan recognition protein (PGLYRP1), plasminogen (PLG), and ALB were significantly up-regulated in the presence of E. coli only. Interestingly, the expression of four defense proteins (alpha-2-glycoprotein 1 zinc binding-AZGP1, butyrophilin subfamily 1 member A1BTN1A1, lactoperoxidase-LPO and prostaglandin D2 synthasePTGDS), eight binding proteins (LGB, fatty acid-binding protein 3-FABP3, lactadherin-MFGE8, nucleobindin-1-NUCB1, CD36 antigen-CD36, niemann-pick disease type C2-NPC2, polymeric immunoglobulin receptor-PIGR and xanthine dehydrogenaseXDH), one protein each involved in enzyme activities (SERPING1) and metabolic process (LALBA), and two proteins of unknown functions (glycoprotein 2-GP2 and glycosylationdependent cell adhesion molecule 1-GLYCAM1) were significantly down-regulated by the presence of one or both pathogens. The major whey proteins, LGB and LALBA, were highly affected by the type of pathogen. LGB was significantly downregulated in E. coli samples, and LALBA was significantly downregulated by the presence of both pathogens. The concentrations of ALB and XDH were unaffected by the presence of pathogens, while C3 was significantly up-regulated in the presence of both pathogens. Effect of Pathogens on Gene Expression in MAC-T Cells. Results of qPCR mRNA quantification of selected genes of the proteins up- or down-regulated in the proteomics experiment are shown in Table S4, Supporting Information and Figures 2-4. The qPCR results were generally similar to proteomics results in most cases and were different in other instances. The responses of 10 immune process/response genes, 2 proteins involved in enzyme activities, and 1 protein involved in biological adhesion, all up-regulated in the proteomics study, were up-regulated significantly at some time point during the course of the experiment. For the selected proteins involved in binding activities, mRNA quantification of the corresponding
genes indicated up-regulation or down-regulation, which was similar to observations at the protein level. However, there was a lack of change in mRNA expression of fructose-bisphosphate aldolase A (ALDOA) even though this protein was clearly increased in mastitic milk. The mRNA expression of APOA1, CATHL4, CFH, gelsolin (GSN), HP, lymphocyte cytosolic protein 1 (LCP1), and protein S100-A9 (S100A9) were very similar to proteomics data by showing a stronger expression in E. coli samples than in S. aureus samples (Figure 2). For example, mRNA expression of HP increased steadily and significantly from 2 h time point at 5.08-fold expression and reached a high fold expression of 28.73 at 48 h in E. coli treated cells. In S. aureus treated cells, significant mRNA expression was achieved from the 6 h time point (2.00-fold) through to the 48 h time point (15.02-fold change). The data at the protein level indicated a 10.67-fold increase in E. coli samples as compared to a 9.83-fold increase in S. aureus samples (Figure 2). Data with opposing trends in the two sources are recorded for A1BG, CATHL1, CFB, cofilin 1 (CFL1), profiling-1 (PFN1), and SERPINB4 showing stronger mRNA expression in S. aureus samples as compared to E. coli samples and a stronger protein expression in E. coli samples as compared to S. aureus samples (Figure 3). For Chitinase-3-like protein 1 (CHI3L1), the mRNA expression was stronger in E. coli samples, while its protein was of a higher concentration in S. aureus samples (Figure 3). The expression of CFB was very high at the mRNA level in response to both types of pathogens (Figure 3). Similarly, the expression of alpha-actinin-4 (ACTN4), enolase 1 (ENO1), FGB, and SERPINB1 were stronger at the protein level than at mRNA level (Figure 4). The mRNA and protein expressions of NUCB1 were similarly down-regulated in both treatments (Figure 4). While there was no change in the expression of hemopexin (HPX) protein between control and S. aureus samples, there was a down-regulation (significantly at the 48 h) in mRNA expression (Figure 4). Pathway Analysis Identifies Molecular Networks Enriched during E. coli and S. aureus Mastitis. The molecular networks have been established with data on human and mouse studies (IPA Program). From our data set of 173 proteins, IPA successfully mapped 161 proteins out of which 109 or 103 were eligible for network analysis in E. coli and S. aureus respectively and 105 or 99 for functions and pathway analysis. IPA identified seven significant networks in E. coli and five in S. aureus samples (Table 2). The most significant networks, with scores of 47 (E. coli) and 46 (S. aureus), are associated with carbohydrate metabolism/small molecule biochemistry/lipid metabolism and lipid metabolism/molecular transport/small molecule biochemistry, respectively. The relationships, both direct and indirect, between the focus molecules in these networks are shown in Figures S1 and S2, Supporting Information. Figure S1 shows the relationship of the 24 focus molecules in this network, 19 were up-regulated (10 significantly) and five were down-regulated (CD36 and LALBA significantly). Similarly in Figure S2 and out of 23 focus molecules, 14 were up-regulated (alpha-2-macroglobulin-A2M, APOA1 and FGB significantly) and 8 were down-regulated (LALBA significantly). In both figures, the majority of the molecules have relationships, either direct or indirect, to the nuclear factor (NF)-κB complex. Similarly, APOA1, high density lipoprotein (HDL), and fibrinogen also showed high interconnections with molecules in the networks. Detailed relationships between molecules enriched in networks with top disease functions like cancer/reproductive system disease/neurological disease (score ) 40) is shown in Journal of Proteome Research • Vol. 9, No. 9, 2010 4609
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Figure 2. Similar trends in mRNA expression of seven genes in MAC-T cells treated with heat inactivated E. coli strain P4 and S. aureus strain Smith CP and protein profiles of the same genes in mastitic and control milks. Figures show similar expression patterns at protein and mRNA levels with a stronger expression in E. coli samples than in S. aureus samples. Fold change values are as compared to the control for proteins or 0 time points for mRNA. For E. coli: *P < 0.05, **P < 0.01; for S. aureus: ‡P < 0.05, ‡‡P < 0.01.
Supplementary Figure S3 for E. coli and for S. aureus like hematological disease/immunological disease/respiratory disease (score ) 45) is shown in Figure S4. Both up- and downregulated proteins in our data showed relationship types that are crucial in effectively responding to the presence of pathogens. When only proteins that were significantly altered by the presence of either of the pathogens (73 genes in all, 66 were mapped and 59 were network eligible for E. coli and 56 for S. aureus) were subjected to network analysis, four significant networks were obtained for E. coli samples and three for S. aureus samples (Table 2). The relationships between the focus molecules in the most significant network for both pathogens are shown in Figure 5a (E. coli) and 5b (S. aureus). Figure 5a (score ) 51) and b (score ) 56) shows the network of genes with top functions in neurological disease/genetic disorder/ ophthalmic disease. Direct and indirect interactions between focus molecules and the NF-κB complex, interleukin 1 (IL1), and low density lipoprotein (LDL) were again evident in the 4610
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two figures. Also, molecules involved in immune response are highly represented in the figures. Out of the 20 proteins that were up-regulated in Figure 5a (E. coli), the concentrations of 19 of them were significantly increased. In Figure 5b (S. aureus), 18 proteins were up-regulated and only seven of them (A2M, APOA1, C3, FGB, HP, lactotransferrin-LTF, and transthyretinTTR) were significantly increased. More proteins were downregulated in Figure 5 panel b than in panel a. Canonical Pathways Enriched during E. coli and S. aureus Mastitis. Canonical pathways have been established with data from human and mouse studies (IPA Program). Proteins in our protein sets were represented in over 100 canonical pathways and the four most significant for each category is shown in Table 3. The acute phase response signaling pathway is the most significantly enriched in both pathogens and the involvement of proteins in our protein sets in these pathways is shown in Figure 6, panel a (E. coli) and b (S. aureus). Proteins whose concentrations are expected to
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Figure 3. Opposing trends in mRNA expression of seven genes in MAC-T cells treated with heat inactivated E. coli strain P4 and S. aureus strain Smith CP and protein profiles of the same genes in mastitic and control milks. Figures show a stronger mRNA expression in S. aureus samples as compared to E. coli samples and a stronger protein expression in E. coli samples as compared to S. aureus samples. For E. coli: *P < 0.05, **P < 0.01; for S. aureus: ‡P < 0.05, ‡‡P < 0.01.
increase during the acute phase response such as FGB, SERPINA3, CP, ITIH4, PLG, SERPINA1, hemopexin-HPX, and HP were significantly increased in E. coli samples (Figure 6a). Most of these proteins were also increased in S. aureus samples but not significantly (Figure 6b). Further eight acute phase response proteins (A2M, C3, CFB, SAA3, AHSG, APOA1, serotransferrinTF, TTR) were significantly increased in E. coli samples (Figure 6a) and lesser increases (most cases not significant, only A2M, APOA1, C3, FGB, HP, TF, and TTR were significant) in S. aureus samples (Figure 6b). The other most significant pathways like coagulation system, complement system, and pentose phosphate pathway (Table 3) all involve processes of response to the presence of pathogens. Top Biological Functions Associated to E. coli and S. aureus Mastitis. Biological functions have been established with data on human and mouse studies (IPA Program). The top biological functions associated with our data sets are shown in Table 4. For both E. coli and S. aureus data sets, the four diseases and disorders associated with the most identified proteins were cancer (74 or 67 proteins for E. coli and S. aureus,
respectively), respiratory disease (38 or 34 proteins), gastrointestinal disease (26 or 20 proteins), and inflammatory disease/response (55 proteins each). These and other diseases are listed in Table 4. The top molecular and cellular functions that our protein sets are associated with are cellular movement, antigen presentation, cell death, cell-to-cell signaling and interaction, lipid metabolism, and molecular transport (Table 4). Similarly, the most proteins were associated with hematological system development and dysfunction, 51 proteins for E. coli and 46 for S. aureus. Other physiological system development and function categories include immune cell trafficking, cell-mediated immune response, and humoral immune response (Table 4).
Discussion Our results of 1D gel separation of proteins according to molecular weight and microsequencing of all protein bands enabled a much wider elucidation of the whey proteome of normal and mastitic milk whey than previously reported.2,4,7 Journal of Proteome Research • Vol. 9, No. 9, 2010 4611
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Figure 4. Differential expression profiles for mRNA expression of six genes in MAC-T cells treated with heat-inactivated E. coli strain P4 and S. aureus strain Smith CP and protein expression of molecules of the same genes in mastitic and control milks. Figures show a stronger expression at the protein level than at the mRNA level for ACTN4, ENO1, FGB, HPX, and SERPINB1. NUCB1 was downregulated both at the protein and mRNA levels. For E. coli: *P < 0.05, **P < 0.01; for S. aureus: ‡P < 0.05, ‡‡P < 0.01.
Although protein molecules are generally more effectively separated in 2D than in 1D electrophoresis, the former method involves a large amount of sample handling, less reproducibility, difficulty to separate low abundance proteins, acidic and basic proteins, very large and very small proteins and hydrophobic proteins.26 All these may explain why many low abundant proteins reported in this study were missed in previous reports. Our proteomics data have demonstrated that the mastitis pathogens E. coli and S. aureus altered significantly, and to different degrees, the proteomic profiles of bovine milk whey. Our qPCR analysis confirms that most of the altered protein profiles detected in this work were due to the presence of E. coli and S. aureus bacteria and also provided evidence that mammary epithelial cells at least partially contributed to such profile changes. In this study, up to 87 proteins were identified 4612
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in mastitic milk only, while the expression of a further 36 proteins, identified in all samples, were either up- or downregulated by the presence of pathogens. These results demonstrate that the response of cows to the presence of E. coli and S. aureus bacteria is more extensive than demonstrated by previous reports. In addition, the response of cows to E. coli is stronger than that to S. aureus. This may explain why E. coli mastitis is often acute and is normally cleared by the immune system within days. On the other hand, the smaller nonsignificant increases in the identified proteins during S. aureus mastitis may explain the usually chronic condition that may persist throughout the life of the animal. Pathogen-dependent differences in the expression of immune factors have also been highlighted by several authors.9,13,27 Moreover, pathway analysis demonstrated the involvement of proteins significantly altered by the presence of pathogens in many Biocarta path-
research articles Table 2. Top Networks of Proteins with Significant Associations Detected in E. coli and S. aureus Samples Escherichia coli ID
Associated network function
Staphylococcus aureus score
Focusmolecules
Associated network function
score
Focusmolecules
Aa 1
2 3
4
5 6 7
carbohydrate metabolism, small molecule biochemistry, lipid metabolism cancer, reproductive system disease, neurological disease cellular assembly and organization, cellular compromise, free radical scavenging skeletal and muscular disorders, cell death, neurological disease cancer, tumor morphology, cell-mediated immune response inflammatory response, lipid metabolism, molecular transport lipid metabolism, molecular transport, small molecule biochemisrty
47
24
lipid metabolism, molecular transport, small molecule biochemistry
46
23
40
21
45
22
39
20
hematological disease, immunological disease, respiratory disease cancer, reproductive system disease, inflammatory disease
42
23
25
14
32
18
20
12
18
11
20
13
10
7
56
24
40
18
26
13
inflammatory response, lipid metabolism, small molecule biochemistry cellular assembly and organization, drug metabolism, genetic disorder
Bb 1 2
3 4
neurological disease, genetic disorder, ophthalmic disease cellular movement, hematological system development and function, immune cell trafficking lipid metabolism, small molecule biochemistry, cell death cell-to-cell signaling and interaction, antigen presentation, cell-mediated immune response
51
23
42
19
19
11
12
7
neurological disease, genetic disorder, ophthalmic disease infectious disease, respiratory disease, hematological disease cell death, hematological disease, immunological disease
a A: All proteins identified (173) were subjected to analysis and for E. coli 109 proteins were eligible for network analysis and for S. aureus 103 proteins were eligible. b B: Only proteins that were significantly altered (73) in E. coli or S. aureus samples or both were subjected to analysis (59 proteins were eligible for network analysis for E. coli samples and 56 for S. aureus samples).
ways, biological functions, and networks which may widen the focus and also provide new targets for the search of effective therapy against mastitis. Although IPA used published information on human and rodents in establishing these relationships, it provides valuable information on the probable functions or involvements of these proteins during bovine mastitis. Because most of the proteins identified in this study have not been studied in the context of E. coli or S. aureus mastitis, this data set therefore provides baseline information that can be used for future studies. Generally, the increase in the concentration of the defense proteins and proteins of varied functions as shown in this study and in previous studies may be partly as a result of the influx of neutrophils and plasma proteins into the mammary gland in response to infection. Also, because the control and disease samples did not come from the same animals, which is indicative of large intercow variations, may have influenced the type and expression levels of the identified proteins. However, the qPCR data lend support to the fact that the majority of the observed protein changes were partly due to the presence of studied pathogens. Identified proteins in this study were also interrogated against the bacterial database, but no specific proteins of bacterial origin were found. This may not necessarily indicate an absence of bacterial proteins but a situation whereby they were below detection limits. In addition to influx proteins, the bovine mammary epithelium itself also plays an active role in host-defense by synthesizing a number of innate immune factors. In our study, increased mRNA expression was demonstrated for many immune response proteins and pro-
teins involved in binding activities, enzyme activities and biological adhesion. In addition to the influx of neutrophils and plasma proteins, milk fat globules that are secreted by mammary epithelia cells contain many peptides, proteins, and lipids that are involved in host-defense,5,28 including XDH identified in this study. These varied sources of proteins during inflammation of the mammary gland may explain the differences observed in the protein expression between the diseased and control samples and possibly the mRNA expression of studied genes. Our data further confirm the ability of the mammary gland to mount a robust innate immune response to the presence of E. coli and S. aureus mastitis pathogens and thus supports earlier reports.12-15,17,18,27 Disease is one of the factors that are known to influence the protein composition of milk.4 The possible involvement of altered proteins in many biological functions (including disease conditions, molecular and cellular functions, and physiological system development and function), canonical pathways, and network of molecules involved in many related functions was demonstrated in this study. The most significantly enriched canonical pathway in our study, acute phase response signaling, showed the involvement of many acute phase or immune response proteins that were significantly increased during E. coli (stronger increase) or S. aureus mastitis. While the direct role of most of these proteins in modulating mastitis pathogens is not yet clear, our findings confirm the reports by several authors of up-regulation of some of these proteins.2,9 The acute phase response is central to the action of the innate immune system in its response to infection. As shown in the network Journal of Proteome Research • Vol. 9, No. 9, 2010 4613
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Figure 5. IPA generated most significant network of molecules with top functions in neurological disease, genetic disorder, and opthalmic disease in E. coli (score ) 51) when only significantly altered proteins (in one pathogen or both pathogens) were used in network analysis. The networks have been established with data from human and mouse studies (IPA Program). (a) Figure shows the degree of relationships between 23 focus molecules and the extent of expression in E. coli. (b) Figure shows the degree of relationships between 24 focus molecules and the extent of expression in S. aureus. Table 3. Top Canonical Pathways Detected in E. coli and S. aureus Samplesa Escherichia coli
Staphylococcus aureus
name
P-value
ratio
name
acute phase response signaling coagulation system complement system glycolysis/gluconeogenesis pentose phosphate pathway
5.67 × 10-26 1.06 × 10-10 5.21 × 10-9 2.73 × 10-6 2.74 × 10-6
25/177 (0.141) 8/37 (0.216) 7/36 (0.194) 7/144 (0.049) 5/90 (0.056)
acute phase response signaling LXR/RXR activation complement system pentose phosphate pathway coagulation system
P-value
8.26 × 10-21 2.58 × 10-8 1.28 × 10-7 2.05 × 10-6 4.53 × 10-6
ratio
21/177 (0.119) 8/86 (0.093) 6/36 (0.167) 5/90 (0.056) 5/37 (0.135)
a All proteins identified (173) were subjected to analysis and 105 proteins were eligible for pathway analysis in E. coli samples and 99 in S. aureus samples.
of molecules identified in this study as having relationships in certain common functions (Figures 5a, 5b, S1, S2, S3, and S4), key molecules including IL1 and NF-κB interact either directly or indirectly with these proteins to modulate several disease conditions in humans as well as roles in lipid metabolism, molecular transport, and small molecule biochemistry. It has been shown recently that MAC-T cells responded to the presence of lipopolysaccaride (LPS) (E. coli toxin) by up-regulating NF-κB.18 Also, it is well established that the activation of NF-κB leads to induction and expression of proinflammatory cytokines (e.g., 4614
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TNFR, IL-6, IL-12) which are essential in inhibiting bacterial activity.29 The fact that these proteins were up-regulated during the presence of the pathogens in the mammary gland seems to suggest a direct role in modulating mastitis. The acute phase response proteins, PLG and CORO1A, and proteins involved in binding activities such as S100A8 and S100A12 could be of relevance in E. coli mastitis. PLG is the inactive form of plasmin, a proteolytic enzyme in milk. At the start of mastitis infection, there is an influx of serum constituents, including PLG into the mammary gland.30 Also, serine
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Figure 6. (a) The acute phase response signaling pathway was mapped by IPA as the most significantly enriched canonical pathway in our data set. The pathway has been established with data from human and mouse studies (IPA Program). One hundred seventy three proteins were subjected to analysis and 105 were pathway eligible in E. coli samples and 99 in S. aureus samples. (a) This figure shows the extent of representation and degree of expression of molecules in E. coli samples. (b) This figure shows the extent of representation and degree of expression of molecules in S. aureus samples.
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Table 4. Top Biological Functions Associated with Proteins Detected in E. coli and S. aureus Samples Escherichia coli name
Staphylococcus aureus
P-value
# molecules
cancer respiratory disease gastrointestinal disease inflammatory response neurological disease
7.8 × 10-23 to 2.44 × 10-3 3.19 × 10-18 to 1.13 × 10-3 6.56 × 10-16 to 2.35 × 10-3 4.65 × 10-15 to 2.44 × 10-3 2.73 × 10-13 to 1.68 × 10-3
cellular movement antigen presentation cell death cell-to-cell signaling and interaction lipid metabolism
2.69 4.65 7.66 1.75
hematological system development and function immune cell trafficking cell-mediated immune response humoral immune response tissue development
× × × ×
10-19 10-15 10-13 10-11
a
to to to to
2.47 1.15 1.92 2.44
× × × ×
name
Diseases and Disorders 74 cancer 38 respiratory disease 26 gastrointestinal disease 55 inflammatory response 60 neurological disease
Molecular and Cellular Functions 10-3 45 cellular movement 10-3 48 antigen presentation 10-3 54 cell death 10-3 48 lipid metabolism
2.37 × 10-9 to 2.02 × 10-3
33
molecular transport
Physiological System Development and Function 1.13 × 10-16 to 2.47 × 10-3 51 hematological system development and function 1.13 × 10-16 to 2.47 × 10-3 44 immune cell trafficking 4.65 × 10-15 to 1.15 × 10-3 44 cell-mediated immune response 4.65 × 10-15 to 1.61 × 10-3 44 humoral immune response 7.01 × 10-11 to 2.44 × 10-3 38 tissue development
P-value
# molecules
8.70 5.80 1.47 5.61 7.40
× × × × ×
10-19 10-16 10-12 10-12 10-12
10-3 10-3 10-3 10-3 10-3
67 34 20 55 56
1.15 4.97 1.62 1.48
× × × ×
10-16 to 3.72 × 10-3 10-11 to 3.99 × 10-3 10-10 to 4.07 × 10-3 10-9 to 4.32 × 10-3
44 42 47 32
to to to to to
4.32 2.77 3.16 2.77 3.72
× × × × ×
1.48 × 10-9 to 3.72 × 10-3
40
2.27 × 10-13 to 4.23 × 10-3
46
2.27 × 10-13 to 3.72 × 10-3 4.97 × 10-11 to 3.99 × 10-3
40 38
4.97 × 10-11 to 3.99 × 10-3
38
1.49 × 10-8 to 2.42 × 10-3
35
a
All proteins identified (173) were subjected to analysis and 105 proteins were eligible for biological function analysis in E. coli samples and 99 in S. aureus samples.
protease activator concentrations, including those for plasmin and PLG in blood and milk have been shown to increase sharply during mastitis.30 Furthermore, polymorphonuclear neutrophils have a pool of plasmin activators, and several bacteria including E. coli and S. aureus are known to express a PLG receptor on their surfaces which immobilize PLG and enhance its activation into plasmin.31 On the other hand, ENO1, detected only in diseased samples, is believed to play a role as a receptor to human PLG and the ENO1/PLG system is one of the mechanisms facilitating the invasiveness of pathogens.32 S100A8 has been detected in LPS-induced mastitis in a mouse model and was also shown to be expressed in mammary epithelial cells,33 while S100A12 and CORO1A were recently detected during transcriptone profiling of Streptococcus uberisinduced mastitis.13 Recently, Tanigawa et al.34 found that TLR2mediated activation of the innate immune response resulted in suppression of CORO1A expression, which could explain the lack of significant results observed with S. aureus in this study. Also, Strandberg Lutzow et al.6 detected enhanced expression of S100A12 and Pentraxin-3 (PTX3) in mammary tissue after challenge with S. aureus and also increased expression of their proteins in the milks of challenged cows. They also showed a strong correlation between somatic cell count and the level of S100A12 in milk from a herd of dairy cows, and the inhibition of E. coli growth in vitro by recombinant S100A12.6 These proteins (CORO1A, PLG, S100A8, and S100A12) were only detected in the diseased samples and significantly in E. coli samples in our study, thus suggesting profound roles in the modulation of E. coli mastitis. Proteins ALB, TTR, AHSG, and TF, whose concentrations are expected to decrease in plasma during acute phase response signaling, were significantly up-regulated in E. coli samples and TTR and TF in S. aureus only, thus confirming previous studies.2,4,5 The increase in ALB, AHSG, and TF could result 4616
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from the leakage of serum proteins into milk after cytokine production and altered vascular permeability of the mammary epithelium. ALB has also been shown to be synthesized and secreted by the bovine mammary gland and that local expression of ALB in the mammary gland was increased both in mastitic mammary tissue and after exposure to LPS when compared with expression in healthy mammary tissue.35 Also, ALB is known to bind and transport long-chain fatty acids as well as other small molecules (e.g., bradykinin and interferons) and acute phase proteins including SAA3 and AGP.36 In a recent study, Boehmer et al.2 demonstrated possible binding of complement C3 to ALB. Nevertheless, whether ALB plays a role in the transport of needed defense proteins to the mammary gland during mastitis is unknown. The detection of TTR, also shown to have a relationship with ALB in the network of molecules with top functions in neurological disease/genetic disease/ophthalmic disease, confirms earlier reports by Yamada et al.7 and Boehmer et al.2 TTR is produced mainly in the liver and in the choroid plexus of the brain and secreted into plasma and cerebrospinal fluid.37 Our findings may suggest a possible role of TTR during the acute phase response to E. coli and S. aureus pathogens. Other defense proteins such as HPX, ITIH4, A1BG, and A2M, showing different levels of relationships with other molecules in the networks identified in this study or the acute phase response signaling pathway, are less studied in bovine. HPX, a plasma protein with the highest binding affinity to heme, mediates heme-iron recovery in the liver, thus controlling heme-iron availability in peripheral cells. Recent data38 suggest that HPX, by controlling heme-iron availability in lymphocytes, modulates responsiveness to IFN-gamma and, hence, autoimmune responses. On the other hand, Pineiro et al.39 isolated ITIH4 from cattle during experimental bacterial and viral infections and considered it a new positive acute phase protein
research articles in cattle. Our data are consistent with this hypothesis. A1BG was detected in both diseased and normal samples with a significant increase in E. coli samples in this study. Another protein with significant expression in this study, heat shock 90 kDa protein 1alpha (HSPCA), is also suggested to act as a regulator of pathogenic changes that lead to the neurodegenerative phenotype in Alzheimer’s disease.40 These proteins may have a role in the pathophysiology of mastitis. LTF, an iron-binding protein, is synthesized by mammary gland epithelial cells and has a broad spectrum of functions in immune defense.41 LTF was detected in all samples in our study but it was up-regulated in diseased samples and more so in S. aureus samples (about 1.68-fold as compared to the control). LTF concentration has been reported to increase during mastitis,16,42 and a few studies have reported a higher concentration in mastitis milk from cows infected with S. aureus than with E. coli.16,42 Although the exact mechanisms of action of LTF in host defense are not clearly understood, its increase in mastitic milk suggests a pathogen-dependent relationship. Further investigations may establish the exact role of LTF in modulating E. coli and S. aureus mastitis and hence its potential use for therapeutic intervention in mastitis caused by these pathogens. Several members of the serpins (SERine Proteinase Inhibitors) family of proteins were significantly up-regulated in this study (SERPINA1, SERPINA3, SERPINA3-5, SERPINAB1 and SERPINAB4). They were represented in the acute phase response signaling pathway, the coagulation pathway, and the network of molecules with top functions in carbohydrate metabolism, small molecule biochemistry, lipid metabolism, neurological disease, genetic disease and ophthalmic disease. However, their roles in mastitis pathogenesis remain to be investigated. Some defense proteins of the complement family reported here have also been previously identified in mastitic whey.2 Of the complement factors identified in this study, C3, CFB, and CFH were present in all samples but up-regulated significantly in E. coli milk, while C4A and C6 were only detected in mastitic milk. The activation of the complement system is considered an integral component of the innate immune system and its involvement in our study is consistent with this concept. When activated, the complement system catalyzes downstream events resulting in an inflammatory response, direct lysis, and opsonization of microorganisms while the coagulation system maintains the integrity of the circulatory system upon injury. The complement system is known to contribute to the defense of the bovine mammary gland and also to be activated through the alternative pathway.43 Our findings therefore support a role of the complement system in innate immunity of the mammary gland44 and also suggest that this role remains largely uncharacterized. Some members of the cathelicidin family of peptides and apolipoproteins reported here have been previously observed in mastitic milk2,5 and in addition to their potent antimicrobial properties, they are also known to down-regulate the expression of proinflammatory cytokine.45-47 These antimicrobial peptides are part of the defense machinery of neutrophils and are released upon neutrophil degranulation in the mammary gland.48 Proteins with binding activities such glucose phosphate isomerize (GPI) and PFN1 are being reported in mastitic milk whey for the first time. GPI is a glycolytic enzyme recently reported as a member of bovine sperm protein YWHA (also
49
known as 14-3-3) interactome. PFN1 is involved in cell apoptosis and its silencing has been shown to inhibit endothelial cell proliferation, migration and cord morphogenesis.50 Increased mRNA expression of PFN1 in MAC-T cells was evident in this study. Our data suggest a possible role for these proteins in bovine mammary gland inflammatory development. Other proteins, for example, LCP1 or L-plastin detected in diseased samples only, have been previously found in bovine milk samples.5 LCP1 is usually associated with the lymphocyte cytosol and it has been found to be one of the genes significantly up-regulated in pigs during a response to gastrointestinal infection with Salmonella enterica serovars Choleraesuis.51 Further, binding proteins such as CHI3L1 and CFL1 were identified only in diseased samples. CHI3L1 is known to be expressed in nonlactating bovine mammary gland and involved in tissue remodelling.52 Also, it has been shown that LPS is a potent inducer of CHI3L1 secretion in rat chondrocytes indicating that this protein is part of the LPS response repertoire.53 Therefore, CHI3L1 may be part of the TLR4 or TLR2 mediated innate immune response pathway of bovine mammary gland. On the other hand, CFL1 is a critical mediator of eukaryotic actin polymerization and depolymerization and is known to play important roles in cell migration, mitosis, and apoptosis.54 CFL1 has been implicated as an inhibitor of glucocorticoid receptor action in steroid-resistant HeLa cells through a mechanism involving c-Jun55 and has been found to be up-regulated in bronchoalveolar lavage fluid of dexamethasone-treated cattle thus suggesting an integral role in respiratory disease susceptibility,56 and based on our results, a potential role also in mastitis susceptibility. Not only was there an up-regulation of important defense proteins in this study, there was also a surprising downregulation of some proteins with known bactericidal properties such as AZGP1, LPO, CD36, NUCB1, and XDH. LPO for example is known to exert antimicrobial effects, and this takes place in a nonspecific antibacterial defense system, consisting of LPO, H2O2, and thiocyanate, shown to be present in bovine milk.57 However, for the system to function, H2O2 must be present. Sakai et al.58 recently showed that inflammation of the mammary gland caused a decrease in H2O2 production in milk. Therefore, the presence of E. coli and S. aureus possibly inactivated the LPO/H2O2/thiocyanate system in infected milks and caused the down-regulation of LPO. The down-regulation of CD36, which is involved in the uptake and secretion of longchain fatty acids, may be directly related to the down-regulation of FABP3 in this study. The two proteins are involved in cellular growth, differentiation, lipid transport, and metabolism, and it has been demonstrated that bovine milk fat globule membranes contain the complex of CD36 and FABP which is most likely formed as a result of FABP binding to the cytoplasmic segments of CD36.59 The same group further demonstrated that the expression of CD36 and FABP is related to the state of mammary cell differentiation, reaching its maximum during lactation and declining during the involution period. Inflammation of the mammary gland induces cell death in mammary glands60 and may therefore be one condition that may lead to a decrease in the expression of these proteins. In conclusion, our study has presented a wider proteome profile of E. coli and S. aureus mastitic whey and has identified more low abundant and defense proteins than reported before. E. coli was more potent in the activation of immune response proteins than S. aureus. Also, the canonical acute phase response signaling pathway was the most significantly enriched Journal of Proteome Research • Vol. 9, No. 9, 2010 4617
research articles pathway in our study. Furthermore, many significantly upregulated proteins showed direct or indirect relationships with the NF-κB and IL-1 (key molecules in the innate immune response) and in the network of molecules involved in different functions. Finally, our data have shown for the first time the significant enrichment of expressed proteins during E. coli and S. aureus mastitis in different canonical pathways, network of molecules in different functions, and involvement in disease disorders, molecular and cellular functions, and physiological system development and function, which may provide new insights in mastitis pathogenesis and control.
Acknowledgment. We thank the proteomics platform group of McGill University/Genome Quebec Innovation Centre, in particular, Dr. Sylvie LaBoissie`re, Line Roy, and Nathalie Hamel for their useful inputs. This study was supported by funding from a discovery grant from Natural Science and Engineering Research Council of Canada (NSERC) and a grant from Alberta Milk, Dairy Farmers of New Brunswick, Nova Scotia, Ontario, and Prince Edward Island, Novalait Inc., Dairy Farmers of Canada, Canadian Dairy Network, AAFC, PHAC, Technology PEI Inc., Universite de Montreal, and University of Prince Edward Island through the Canadian Mastitis Research Network. Supporting Information Available: Tables S1-S4 and Figures S1-S4. This material is available free of charge via the Internet at http://pubs.acs.org/.
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