Transcriptomics and iTRAQ-proteomics Analyses of Bovine Mammary

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Transcriptomics and iTRAQ-proteomics Analyses of Bovine Mammary Tissue with Streptococcus agalactiae-induced Mastitis Huimin Zhang, Hongrui Jiang, Yongliang Fan, Zhi Chen, Mingxun Li, Yongjiang Mao, Niel A. Karrow, Juan J. Loor, Stephen Moore, and Zhangping Yang J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b02386 • Publication Date (Web): 10 Aug 2018 Downloaded from http://pubs.acs.org on August 11, 2018

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Journal of Agricultural and Food Chemistry

85x47mm (300 x 300 DPI)

ACS Paragon Plus Environment


and

iTRAQ-proteomics

Analyses

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1

Transcriptomics

of

Bovine

2

Mammary Tissue with Streptococcus agalactiae-induced Mastitis

3

Huimin Zhang1,2, Hongrui Jiang1,2, Yongliang Fan1,2, Zhi Chen1,2, Mingxun Li1,2, ,

4

Yongjiang Mao1,2, Niel A. Karrow3, Juan J. Loor4, Stephen Moore5, Zhangping

5

Yang1,2*

6

1

7

of Jiangsu Province, College of Animal Science and Technology, Yangzhou University,

8

Yangzhou, Jiangsu 225009, China

9

2

Key Laboratory for Animal Genetics, Breeding, Reproduction and Molecular Design

Joint International Research Laboratory of Agriculture & Agri-Product Safety,

10

Ministry of Education, Yangzhou University, Yangzhou, Jiangsu 225009, China

11

3

12

Canada

13

4

14

Illinois, Urbana, IL 61801, USA

15

5

16

Australia

17

*Corresponding

18

+86-514-8735 -0440

Department of Animal Biosciences, University of Guelph, Guelph, N1G 2W1,

Department of Animal Sciences & Division of Nutritional Sciences, University of

Centre for Animal Science, University of Queensland, St Luci QLD 4072a,

author:

[email protected];

Tel.:

19


+86-514-8797-9307;

Fax:

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Mastitis is a highly prevalent disease in dairy cows that causes large

20

Abstract:

21

economic losses. Streptococcus agalactiae is a common contagious pathogen, and a

22

major cause of bovine mastitis. The immune response to intramammary infection with

23

S. agalactiae in dairy cows is a very complex biological process. In order to

24

understand the host immune response to S. agalactiae-induced mastitis, mammary

25

gland of lactating Chinese Holstein cows was challenged with S. agalactiae via nipple

26

tube perfusion. Visual inspection, analysis of milk somatic cell counts, histopathology

27

and transmission electron microscopy of mammary tissue was performed to confirm S.

28

agalactiae-induced mastitis. Microarray and isobaric tags for relative and absolute

29

quantitation (iTRAQ) were used to compare the transcriptomes and proteomes of

30

healthy and mastitic mammary tissue. Compared with healthy tissue, a total of 129

31

differentially expressed genes (DEGs, fold change > 2, p < 0.05) and 144

32

differentially expressed proteins (DEPs, fold change > 1.2, p < 0.05) were identified

33

in mammary tissue from S. agalactiae-challenged cows. Among the concordant 18

34

DEGs/DEPs, immunoglobulin M precursor, cathelicidin-7 precursor, integrin alpha-5

35

and complement C4-A-like isoform X1 were associated with mastitis. Intramammary

36

infection with S. agalactiae triggered a complex host innate immune response that

37

involves complement and coagulation cascades, ECM-receptor interaction, focal

38

adhesion, phagosome and bacterial invasion of epithelial cells pathways. These results

39

provide candidate genes or proteins for further studies in the context of prevention

40

and targeted treatment of bovine mastitis.



41

Keywords: bovine mastitis, Streptococcus agalactiae, transcriptome, iTRAQ proteome,

42

innate immune response


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INTRODUCTION

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Mastitis is the most frequent disease afflicting dairy cows and has

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well-recognized detrimental effects on animal wellbeing and dairy farm profitability,

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including decreased milk production and quality, increased discarded milk, cow

47

mortality and cull rate.1,2 Previous studies have shown that contagious pathogens such

48

as Streptococcus agalactiae and Staphylococcus aureus are major causes of mastitis

49

around the world.3 Analysis of pathogens causing mastitis in Chinese dairy cows has

50

revealed that S. agalactiae was the most frequently isolated pathogen in cows with

51

subclinical mastitis, and it was detected in 2.8% of 3,288 clinical mastitis samples.4,5

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Subclinical mastitis is difficult to detect visually, and it may involve transient

53

cases of inflammation and abnormal milk, while clinical mastitis is an inflammatory

54

disease causing visibly abnormal milk.6 Intramammary infection (IMI) with S.

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agalactiae triggers a complex host immune response that involves immune,

56

endothelial and epithelial cells as well as humoral proteins.7 Understanding the

57

mechanisms of the host immune response to S. agalactiae infection is important for

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the development of innovative strategies for mastitis prevention or treatment.

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Currently, high-throughput profiling of the transcriptome and proteome are

60

powerful tools for exploring immunoregulatory mechanisms involved in the host

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response to IMI. For instance, microarray analysis was previously used to compare

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the transcriptomes of mammary glands infected with Escherichia coli and

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Staphylococcus aureus, and 187 differentially expressed genes (DEGs) were

64

identified, some of which were closely associated with cellular responses.8 In another



65

study, a combination of microarray and real-time PCR identified 14 genes (AATK,

66

CCL2, CCL20, CD40, CSF2, GRO-α, IL-12, IL-17, IL-1β, INHBA, NOS2A, TGF-β1,

67

TLR-2 e TLR-4) that were related to the immune responses of zebu dairy cows during

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IMI with S. agalactiae.9 Differentially expressed proteins (DEPs) in whey samples

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from cows with E.coli IMI have also been identified using 2-dimensional gel

70

electrophoresis coupled with MALDI-TOF MS; these included antimicrobial peptides

71

(cathelicidin, indolicidin, bactenecin 5 and 7), and various other proteins

72

(β-fibrinogen, α-2-HS-glycoprotein, S100-Al2, and α-1-antiproteinase).2 Isobaric tags

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for relative and absolute quantitation (iTRAQ) protein quantitative analysis

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technology has also been used to screen potential proteins associated with mastitis

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caused by natural Staphylococci aureus infection, leading to identification of the

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up-regulation of COL1A1 and ITIH4. These proteins are associated with tissue

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damage and repair during late-stages of infection.10 Different pathogens appear to

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give rise to different host immune-related gene and protein signatures, these

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signatures have been well-studied in the context of S.aureus and E.coli infections,8,11

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however, there is little information pertaining to S. agalactiae-induced mastitis at the

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mRNA and protein levels.

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Integration of transcriptome and proteome analyses, along with bioinformatics, is

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essential for generating a complete inventory of gene networks, because of

84

post-translational turnover and alternative translation efficiency.12 In the present study,

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microarray and iTRAQ analyses of mammary glands from Chinese Holstein cows

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infected with S. agalactiae were investigated. This integrated analysis of


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transcriptome and proteome will substantially improve our global view of molecular

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mechanisms involved in S. agalactiae-induced mastitis, and will guide further studies

89

designed to investigate the pathogenesis of S. agalactiae-induced mastitis as well as

90

the development of new prevention and treatment strategies.

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MATERIALS AND METHODS

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Animals

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Primiparous Chinese Holstein cows (n = 3) in mid-lactation were selected from

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Yangzhou University dairy farm. Somatic cell count (SCC) of the milk samples

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determined by flow cytometry (Fossmatic 5000, Foss Electric, Denmark) indicated

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the cows had levels lower than 100 000 cells/ml. Bacteriological testing of milk

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samples confirmed that all mammary quarters in the cows were free of pathogens.

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Induction of S. agalactiae Mastitis

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Three Chinese Holstein cows were selected for research in this study. Two rear

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mammary quarters of each cow were injected with a 5 mL suspension of 106 CFU/mL

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S. agalactiae ATCC13813 (left quarter), or 5 mL sterile PBS solution (right quarter).

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After 6, 12, 18, and 24 h of treatment, milk SCC and visual inspection of the

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mammary gland were used to confirm S. agalactiae-induced mastitis.

105

Collection of Mammary Tissue

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After 24 h of IMI, mammary tissue was collected by biopsy as described

107

previously.13 Any visible drops of milk, blood and connective tissue were removed by

108

blotting on sterile gauze or tweezers. Subsequently, 2×3×0.5 cm of tissue sample was



109

transferred to 10% formalin, and 1×1×1 cm of tissue sample was transferred to 2.5%

110

glutaraldehyde. A 2 g mammary tissue block was immediately frozen in liquid

111

nitrogen and stored at -80°C until RNA and protein extraction.

112

Histopathological Examination

113

After fixing mammary tissues in 10% formalin, tissues were washed with water,

114

and dehydrated using a series of alcohol gradients, then embedded in paraffin wax.

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The paraffin-fixed tissue blocks were sliced using a microtome, and tissues stained

116

with hematoxylin and eosin (HE), then visualized with a microscope (Nikon, Tokyo,

117

Japan).

118

Transmission Electron Microscopy (TEM)

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After fixing in 2.5% glutaraldehyde, mammary tissues were washed with 0.1 M

120

PBS, fixed in OsO4, then dehydrated using a series of alcohol gradients. The samples

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were transferred to 100% acetone, and embedded in epoxy resin 618. The resin-fixed

122

blocks were then sectioned into slices (50 - 60 nm in thickness) using a microtome

123

(EM UC7, Leica, Germany). Last, the tissues were stained with 2% uranyl acetate for

124

TEM analysis (Tecnai 12, Philips, Netherlands).

125

RNA Isolation and Microarray Analysis

126

Total RNA was extracted from the mammary tissues using mirVanaTM RNA

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Isolation Kit (Applied Biosystem p/n AM1556,) according to the manufacturer’s

128

instructions. The RNA was purified by QIAGEN RNeasy® Kit, then the purity and

129

integrity were assessed using an Agilent 2100 Bioanalyzer (Agilent Technologies, CA,

130

USA), only high-quality RNA (RNA integrity number >8.0) was used for further


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analysis. After reverse transcription and Cyanine-3-CTP labeling reaction, the

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fragmented cRNA was hybridized onto a bovine microarray (Bovine (v2) Gene

133

Expression 4*44K Microarray，Design ID:023647, Agilent). After washing, the arrays

134

were scanned using the Agilent Scanner G2505C (Agilent Technologies).

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Microarray Data Analysis

136

Feature Extraction software (version10.7.1.1, Agilent Technologies) was used to

137

analyze array images to obtain raw data. The raw data was normalized with the

138

quantile algorithm of Genespring Software (12.5 Agilent). After t-test analysis, fold

139

change >2 and p < 0.05 were used as the threshold to determine the significance of

140

DEG. These DEGs were subjected to Gene Ontology (GO) analysis and Kyoto

141

Encyclopedia of Genes and Genomes (KEGG) analysis to determine their

142

involvement in various gene pathways.

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Protein Extraction

144

Each 0.5 g tissue sample was ground into powder in liquid nitrogen. Lysis buffer

145

containing 1 mM phenylmethylsulfonyl fluoride and 2mM EDTA was then added to

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the powder and mixed by vortexing for 5 min. Dithiothreitol was then added to the

147

mixture at a final concentration of 10 mM, then ultrasonicated for 5 min on ice. After

148

centrifugation at 30000 g for 15 min (4 ℃), the supernatant was mixed with a 5-fold

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volume of chilled acetone for more than 2 h (-20 ℃) to precipitate proteins. The

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protein pellets were obtained by centrifugation at 25000 g for 20 min (4 ℃), and then

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air dried and dissolved in lysis buffer containing 7M urea, 2 M thiourea, 4% NP40,

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20mM Tris-HCl (pH 8.0-8.5). To reduce protein disulfide bonds in the supernatant,



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dithiothreitol was added at a final concentration of 10 mM and incubated at 56°C for

154

1 h. Subsequently, iodoacetamide was added at a final concentration of 55 mM and

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incubated for 1 h in the dark to block cysteine residues. After centrifugation at 30000

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g for 15 min (4 oC), the supernatant was quantified for protein using a BCA assay Kit

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(Pierce, Thermo, USA).

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iTRAQ Labelling, SCX Fraction and LC-MS/MS Analysis

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Protein samples (100 µg) were digested with trypsin (protein: trypsin = 20:1)

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overnight at 37︒C. The digested peptides were labelled with iTRAQ reagents

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according to the manufacturer’s protocol (Applied Biosystems), the 3 healthy and 3 S.

162

agalactiae samples were labeled with 113, 114, 116 and 115, 116, 118 iTRAQ

163

reagents, respectively.

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After labeling, samples were fractionated by strong cationic exchange (SCX)

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chromatography using a HPLC system (Shimadzu, Japan) equipped with an Ultremex

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SCX column (4.6 × 250 mm, 5-µm, Phenomenex, CA, USA). The eluted peptides

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were pooled into 12 fractions, desalted using a Strata X C18 column (Phenomenex)

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and dried under vacuum. Each fraction was re-suspended in buffer (2% acetonitrile,

169

0.1% formic acid) and loaded into a LC-20AD nanoHPLC (Shimadzu, Kyoto, Japan)

170

for separation, and then subjected to tandem mass spectrometry (MS/MS, Thermo

171

Fisher, MA, USA) coupled online to the nanoHPLC. Data acquisition was performed

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with a TripleTOF 5600 System (AB SCIEX, Concord, ON) as previously described.10

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The MS/MS data were searched against the NCBI Bos-taurus (45106sequences)

174

database for peptide identification, and quantification was carried out using the


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Mascot 2.3.02 software (Matrix Science, London, U.K.; version 2.3.02). DEPs having

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ratio with fold change > 1.2 and p < 0.05 were considered in the analysis, and their

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annotated proteins were subjected to GO and KEGG analysis.

178 179

RESULTS

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Establishment and Verification of Mastitis

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After 24 h of infection, the S. agalactiae mammary quarters (S. agalactiae group)

182

showed clinical signs of mastitis (redness, pyrexia, swelling), and the milk SCC was

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greater than 2,000,000 cells/mL; these clinical signs were not detected in quarters

184

injected with PBS (control group).

185

Staining with HE showed that the mammary structure of the control group was

186

intact, and its mesenchyma was narrow and uniform (Figure 1A). The monolayer of

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mammary epithelial cells was tightly packed and arranged in an orderly fashion.

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Except for a few lymphocytes in the interstitial blood vessels, no inflammation or

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hyperplasia was detectable in the control group. In contrast, the S. agalactiae group

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had a swollen mesenchyme, enlarged lumen, loosely connected epithelial cells, and

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increased intercellular gaps (Figure 1B). Exfoliated mammary epithelial cells and

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many inflammatory cells including macrophages, polymorphonuclear neutrophils and

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lymphocytes were also concentrated in the lumen.

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Compared with the control group, many bacteria were concentrated in the

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mammary tissues of the S. agalactiae group, presented as scattered chains, which is

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typical for S. agalactiae (Figure 2). The diameter of S. agalactiae was approximately



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0.7 µm. Collectively, these data indicate that S. agalactiae-induced mastitis was

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successfully established.

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Identification of DEGs in Mammary Tissue of S. agalactiae-Challenged Cows

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The Box-whisker plot showed that the data symmetries among the 6 samples

201

were appropriate, with low data dispersion indicating that the quality of microarray

202

data was high (Figure S1). After quantile normalization and statistical analysis, 129

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DEGs (p < 0.05, fold change > 2) were identified. When compared with the control

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group, 62 DEGs were up-regulated and 67 DEGs were down-regulated in the S.

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agalactiae group (Figure S2, Table S1). Functional analysis classified these DEGs

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into 107 GO terms. Among these, 33 were significantly enriched GO terms (p< 0.05,

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Figure 3). These were further classified into the following three independent

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subgroups: 22 terms corresponding to biological processes (BP), 5 terms

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corresponding to cellular components (CC) and 6 terms corresponding to molecular

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functions (MF). The GO terms with high numbers of DEGs in BP, CC, MF were

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blood coagulation, proteinaceous extracellular matrix and calcium ion binding,

212

respectively.

213

To gain insight into the metabolic processes that differed between the S.

214

agalactiae and control group, KEGG pathway analysis of the DEGs was performed.

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The DEGs were enriched in a wide variety of physiological and biological functions

216

(Table S2, Figure 4). Among the immune-related functions, the top overrepresented

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pathways (p < 0.05) were related to complement and coagulation cascades (CFH,

218

PROS1, VWF), the NOD-like receptor signaling pathway (GBP4, GBP5, LOC781710,


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LOC783604), inflammatory mediator regulation of TRP channels (CALML5, PTGER2,

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HTR2B), bacterial invasion of epithelial cells (ELMO1, FN1) and chemokine

221

signaling pathway (CCL17, ELMO1, CCL8).

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Quality Evaluation of iTRAQ Data

223

Mass spectrometer analysis was performed using a Triple TOF5600 apparatus

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with high resolution and quality accuracy. The accurate determination of the parent

225

ion mass of peptide segment can significantly reduce the probability of false positive

226

identification. For protein identification, a mass tolerance of 0.05Da (quality accuracy

227

1.2, p < 0.05),

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and included 46 up-regulated and 98 down-regulated (Table S3). In the GO analysis,



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the DEPs were significantly enriched in 603 GO terms with p < 0.05. The top 10 GO

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terms for BP, CC, MF were shown in Figure 5. GO terms with a high number of

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DEPs in BP, CC, MF were regulation of proteolysis, extracellular space and calcium

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ion binding. Pathway analysis classified these DEPs into 140 pathways (Table S4,

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Figure 6). The most significantly enriched pathways among the 46 up-regulated DEPs

246

were proximal tubule bicarbonate reclamation (GLUD1, PTX3, CA2), phagosome

247

(MPO, IGM, CTSS, TUBB6, ITGA5, ACTR2, ACTR3) and gastric acid secretion

248

(PTX3, CA2, ACTR2, ACTR3). Many pathways were also immune-related including

249

bacterial invasion of epithelial cells, pathogenic Escherichia coli infection,

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Salmonella infection, intestinal immune network for IgA production, lysosome, focal

251

adhesion and Staphylococcus aureus infection. The down-regulated DEPs were

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enriched in several disease-related pathways such as Vibrio cholerae infection,

253

amoebiasis, systemic lupus erythematosus, influenza A, Parkinson's disease,

254

Alzheimer's disease and Huntington's disease.

255

Comparative Analysis of Proteome and Transcriptome Data

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Integration of all the proteome and transcriptome data was also conducted. An

257

expression correlation analysis was performed between proteins and their

258

corresponding transcripts, and a Pearson correlation coefficient of 0.111 was obtained,

259

indicating a low positive correlation between the proteome and transcriptome data. A

260

one-by-one search found that 2153 (82%) of the 2617 identified proteins had

261

corresponding transcripts in the transcriptome data. In addition, correlation analysis

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between the 144 DEPs and the DEGs (p < 0.05) showed that 18 DEPs had


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corresponding transcripts (Table 1). Of the DEPs, HSD17B8 and MX1 were

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up-regulated while their mRNA levels were decreased in the S. agalactiae group.

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Expression of GC, CYB5A, ACADS and TWF1 mRNA was up-regulated but their

266

protein levels were not. The IgM and CAMP proteins were up-regulated by over

267

2-fold, while their mRNA levels were up-regulated by about 1.5-fold. Other proteins

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were similarly regulated at their mRNA and protein levels. Interestingly, some DEPs

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were associated with immune and inflammatory responses including immunoglobulin

270

M precursor (IgM), cathelicidin-7 precursor (CAMP), integrin alpha-5 (ITGA5) and

271

complement C4-A-like isoform X1 (C4F).

272

To obtain an overview of the correlation between the transcript and protein levels

273

within KEGG pathways, an analysis of the common pathways between transcriptome

274

and proteome data was performed (Table S5). There were 47 consistent pathways

275

between the transcriptome and proteome data. As shown in Table 2, 7 pathways were

276

significant in the transcriptome analysis, and 9 pathways were significant in the

277

proteome analysis (p < 0.05). Bacterial invasion of epithelial cells was the only

278

common significant pathway in both the transcriptome and proteome data.

279 280

DISCUSSION

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Because of the growing importance of S. agalactiae as a causative agent of

282

bovine subclinical mastitis, it is necessary to study the pathogenesis of this

283

microorganism in vivo. In this study, a S. agalactiae-induced bovine mastitis model

284

was successfully established. Staining of mammary tissue with HE allowed



285

investigating the early pathogenesis induced by S. agalactiae, which displayed many

286

pathological similarities to those induced by E. coli and Staphylococcus aureus, i.e.

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loosely connected epithelial cells and conglomeration of inflammatory infiltrates.11

288

Immune-mediated defense mechanisms include innate and adaptive immune

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responses. In this study, the infection by S. agalactiae only persisted 24h, the host-S.

290

agalactiae interaction was mainly controlled by innate immune responses designed to

291

respond quickly upon pathogen challenge during the early stage of infection. It

292

involves the recruitment of neutrophils into the mammary gland to facilitate bacterial

293

clearance through phagocytosis. If the S. agalactiae survive these innate host defenses,

294

adaptive immune responses mediated by T and B cells are required to clear

295

infection.14

296

Studies have shown that changes to the host transcriptome and proteome

297

following pathogen infection can provide important clues to the mechanisms of

298

pathogenesis.15 Furthermore, they can help identify candidate genes or pathways that

299

may be useful for engineering resistance.16 Given the detriment of S. agalactiae to

300

dairy cows, we used microarray and iTRAQ analyses to investigate changes in bovine

301

mammary gland transcriptome and proteome following IMI with S. agalactiae. Our

302

results showed that S. agalactiae-infection significantly altered the expression of 129

303

genes and 144 proteins within mammary glands. Among the concordant 18

304

DEGs/DEPs, the mRNA levels of HSD17B8, MX1, GC, CYB5A and ACADS were

305

opposite to their protein levels. This may be related in part to the stability of mRNA

306

and protein, post-transcriptional regulation (such as microRNA), or post-translational


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modifications (such as acetylation, phosphorylation).17-19 In other DEGs/DEPs pairs,

308

IgM, CAMP, ITGA5 and C4F were associated with immune and inflammatory

309

responses. Mammary gland IgM participates in pathogen agglutination and

310

opsonization, and activation of the complement system, all of which are important

311

host defense mechanisms against pathogens. Since milk IgM concentration is highly

312

correlated with milk SCC (p1,000,000 cells/ml.23 Cathelicidin-1 has been detected in milk from cows

322

naturally infected with S. agalactiae, but not in normal milk samples,24 and various

323

cathelicidins possess anti-S. agalactiae activity.23 In this study, CAMP was

324

up-regulated in the S. agalactiae group, which supports previous results reported in

325

the literature.23,24

326

Integrins not only mediate cell-to-cell adherence and immune cell migration, but

327

also take part in signal transduction.25 Pasteurella haemolytica infection in bovine

328

revealed that β2-integrins contribute to the induction of pro-inflammatory cytokine



329

genes, especially interferon-gamma (IFN-γ) and tumor necrosis factor-alpha

330

(TNF-α).25 It was reported that the expression of ITGA5 is also increased in many

331

solid primary mammary tumors and it promotes tumor cell growth and survival.26 In

332

this study, ITGA5 was up-regulated in the S. agalactiae group, which implied a

333

possible relationship between the ITGA5 and mastitis in dairy cows.

334

The complement system is a primary line of defense against infection.27 The

335

bovine complement component 4 (C4A) was significantly associated with the

336

susceptibility to intramammary infections by major pathogens.28 Günther et al

337

reported that mastitis could up-regulate the mRNA abundance of the C4A gene in E.

338

coli-infected udders.29 In the present study, the C4F gene and protein were

339

down-regulated in the S. agalactiae group. This result was similar to the iTRAQ

340

analysis of bovine mammary glands naturally infected with Staphylococci aureus,

341

which indicated that C3 protein was numerically down-regulated in the mastitis group

342

(p > 0.05).10

343

Coordination of multiple signaling pathways by the host is essential to protect it

344

against a pathogen. These pathways are triggered by innate immune recognition of a

345

pathogen, and initiate the inflammatory response, which is characterized by an influx

346

of neutrophils, macrophages and lymphocytes to the infection site.9,30 In the present

347

study, we found DEGs and DEPs participated in 12 and 35 pathways (p < 0.05),

348

respectively. Comparison between our data and the literatures on mastitis obtained

349

using other pathogens revealed that many common pathways are significantly


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regulated during mastitis.10,11 These pathways included complement and coagulation

351

cascades, ECM-receptor interaction, focal adhesion and phagosome.

352

The complement and coagulation cascades are critical components of the innate

353

immune defense against pathogens, which is a primary line of defense against

354

infection.31 The ECM-receptor interaction pathway plays an important role in tissue

355

and organ morphogenesis and in the maintenance of cell and tissue structure and

356

function.10 During infection, S. agalactiae produces toxins that are damaging to the

357

tissue. Moreover, many immune cells migrate into the location of infection, leading to

358

destruction of the blood-milk barrier. Many collagen and actin-related protein were

359

enriched in the focal adhesion pathway that serves an important role in the regulation

360

of cell migration, proliferation, and survival.32 The ECM-receptor interaction and

361

focal adhesion pathway events culminate in the reorganization of actin cytoskeleton,

362

which is a prerequisite for cell transformation and migration. Therefore, up-regulating

363

the gene or protein expression in these pathways may be one important way to reduce

364

tissue damage caused by S. agalactiae-induced mastitis.

365

Phagosomes are pivotal for the ability of macrophages to participate in tissue

366

rebuilding, reduce the spread of intracellular pathogens, and eliminate apoptotic

367

cells.33 Many antibacterial peptides, such as lactoferrin, β-lactoglobulin and defensins,

368

are generated during phagocytosis, resulting in the increases of SCC.34 These findings

369

were consistent with previous data supporting the interactions among the three

370

pathways

(ECM-receptor

interaction,

fcal

adhesion


and

phagosome),

and


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371

underscoring that these interactions are necessary for tension-dependent malignant

372

transformation of mammary cells.26

373

Both transcriptome and proteome data suggested that pathway of bacterial

374

invasion

of

epithelial cell

was

activated

in

mammary

glands

with

S.

375

agalactiae-induced mastitis. S. agalactiae invades epithelial cells with a zipper model,

376

in which the proteins on the surface of S. agalactiae interact with cellular receptors,

377

initiating signaling cascades that result in close apposition of the cellular membrane

378

around the entering bacteria.35 In this study, several DEGs (ELMO1, FN1) and DEPs

379

(ARP2, ITGA5, ARP3, ARP10, ARPC5) participate in this pathway. S. agalactiae is

380

able to bind ITGA5 on mammary epithelial cells through FN1, and commandeer

381

ITGA5 as a receptor for their entry into cells.36 The engagement and clustering of

382

ITGA5 then triggers a series of epithelial cell signaling pathways, resulting in the

383

reorganization of the actin cytoskeleton, which is essential for integrin-initiated

384

uptake of S. agalactiae.37 Phagocytosis of S. agalactiae requires the reorganization of

385

actin cytoskeleton, thus, explaining why several actin-related proteins (ARP2, ARP3,

386

ARPC5) were up-regulated in the S. agalactiae group.

387

In summary, microarray and iTRAQ analyses highlighted the role of IgM,

388

CAMP, ITGA5 and C4F in the host innate response to S. agalactiae IMI. Most

389

significantly, the DEGs/DEPs involved in the innate immune responses included

390

pathways associated with complement and coagulation cascades, ECM-receptor

391

interaction, focal adhesion, phagosome and bacterial invasion. These results provide a

392

better understanding of the molecular mechanisms involved during the early phase of


Page 21 of 39


393

S. agalactiae-induced mastitis, and highlight candidate genes or proteins that may be

394

useful for diagnosis and control of mastitis.

395

ABBREVIATIONS

396

S. agalactiae: Streptococcus agalactiae; iTRAQ: isobaric tags for relative and

397

absolute quantitation; DEGs: differentially expressed genes; DEPs: differentially

398

expressed proteins; IMI: Intramammary infection; SCC: somatic cell count; HE:

399

hematoxylin and eosin; TEM: transmission electron microscopy; GO: Gene Ontology;

400

KEGG: Kyoto Encyclopedia of Genes and Genomes; SCX: strong cationic exchange;

401

MS/MS: tandem mass spectrometry; BP: biological processes; MF: molecular

402

functions; CC: cellular components; IgM: immunoglobulin M precursor; CAMP:

403

cathelicidin-7 precursor; ITGA5: integrin alpha-5; C4F: complement C4-A-like

404

isoform X1; IFN-γ: interferon-gamma; TNF-α: tumor necrosis factor-alpha; C4A:

405

complement component 4.

406

Acknowledgments

407

This research was supported by the National Natural Science Foundation of

408

China (31472067, 31702142), Natural Science Foundation of Jiangsu Province of

409

China (BK20160455), Jiangsu Planned Projects for Postdoctoral Research Funds

410

(1501118B), and the Priority Academic Program Development of Jiangsu Higher

411

Education Institutions (PAPD).

412



413

Supporting Information Description

414

Figure S1.

415

contains normalized intensity values. A1, B1, C1 represent the control group; A3, B4,

416

C3 represent the S. agalactiae group.

417

Figure S2.

418

indicates up-regulated genes in S. agalactiae group.

419

Figure S3.

420

the Y-axis represents the mascot ion score.

421

Figure S4.

422

mass (C), and protein sequence coverage (D) determined by iTRAQ analysis.

423

Figure S5.

424

and the Y-axis represents the frequency.

425

Table S1

DEGs in mammary tissues between control group and S. agalactiae group.

426

Table S2

Enriched pathways of the DEGs.

427

Table S3

DEPs in mammary tissues between control group and S. agalactiae group

428

Table S4

Enriched pathways of the DEPs.

429

Table S5 The consistent KEGG pathways between the transcriptome and proteome

430

data.

Box-whisker plot. The X-axis contains sample name and the Y-axis

Volcano plots of DEGs. The blue indicates down-regulated genes, red

Peptide matching error distribution. The X-axis depicts mass delta, and

The distributions of peptide length (A), peptide number (B), protein

Repetitive distribution analysis. The X-axis depicts the level of variation,


Page 22 of 39

Page 23 of 39


431

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432

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milk using iTRAQ-coupled LC-MS/MS. International Journal of Food Sciences and

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Rondeau, C.; Desjardins, M. The phagosome proteome: Insight into phagosome

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functions. Journal of Cell Biology 2001, 152, 165-180.

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mammary gland to bacterial infection. Veterinary Journal 2012, 192, 148-152.

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(35) Mostowy, S.; Cossart, P. Cytoskeleton Rearrangements During Listeria Infection:

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Clathrin and Septins as New Players in the Game. Cell Motility and the Cytoskeleton

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(36) Wang, B.; Li, S.; Dedhar, S.; Cleary, P. P. Paxillin phosphorylation: bifurcation

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Page 29 of 39


557

Figure captions

558

Figure 1.

559

mammary with an integrated structure; (B) S. agalactiae group: exfoliated mammary

560

epithelial cells and large numbers of inflammatory cells concentrated in the lumen.

561

The arrow denotes cell conglomeration.

562

Figure 2.

563

(A) Control group: no bacteria; (B) S. agalactiae group: S. agalactiae concentrated in

564

the mammary tissues. The arrow denotes bacteria.

565

Figure 3.

566

terms, and the Y-axis represents the –log10P-value.

567

Figure 4.

568

–log10p-value, and the Y-axis shows the biological pathways.

569

Figure 5.

570


571

Figure 6.

572

the corresponding pathway enrichment score; the Y-axis represents the name of each

573

pathway. The enrichment score refers to the ratio of the number of DEPs in the

574

pathway and the number of all annotated proteins in the pathway; a higher enrichment

575

score indicates a greater degrees of enrichment, and a higher diameter indicates a

576

higher number of DEPs.

HE staining of mammary tissues (200×). (A) Control group: normal

Ultrastructure of mammary tissues infected with S. agalactiae (bar: 2 µm).

GO functional annotation histogram of DEGs. The X-axis shows the GO

The KEGG pathways of DEGs (p < 0.05). The X-axis represents the

The top 10 GO enrichment terms of DEPs. The X-axis shows the GO

The top 20 KEGG enrichment pathways of DEPs. The X-axis represents

577



578

Table 1

Page 30 of 39

18 DEPs with corresponding DEGs (p < 0.05).

GeneID

Gene Name

Gene Symbol

protein fold change

gene fold change

524810

uncharacterized protein IGM, IgM precursor

IgM

2.34

1.46

317650

cathelicidin-7 precursor

CAMP

2.23

1.50

281873

integrin alpha-5

ITGA5

1.95

1.37

505964

myosin light chain 9

MYL9

1.73

1.33

532422

hydroxysteroid (17-beta) dehydrogenase 8

HSD17B8

1.66

-1.09

280872

interferon-induced GTP-binding protein Mx1

MX1

1.40

-1.29

614345

actin related protein 2/3 complex subunit 5

ARPC5

1.30

1.18

534001

heterogeneous nuclear ribonucleoprotein H2

HNRNPH2

1.29

1.14

281597

ARP3 actin-related protein 3 homolog (yeast)

ACTR3

1.28

1.21

513707

importin 7

IPO7

1.19

1.27

GC

-1.35

1.24

CYB5A

-1.39

1.26

ACADS

-1.42

1.40

530076 281110 511222

group-specific component (vitamin D binding protein) cytochrome b5 type A (microsomal) acyl-CoA dehydrogenase, C-2 to C-3 short chain

519982

RAB33B, member RAS oncogene family

RAB33B

-1.42

-1.16

512276

VCP interacting membrane selenoprotein

VIMP

-1.45

-1.13

C4F

-1.46

-1.46

217474

PREDICTED: complement C4-A-like isoform X1

506683

twinfilin actin binding protein 1

TWF1

-1.47

1.14

508853

inner membrane mitochondrial protein

IMMT

-1.70

-1.19

579


Page 31 of 39


Consistent KEGG pathways (p < 0.05) between the transcriptome and

580

Table 2

581

proteome data. ID

Description

p-value

gene/protein

0.001315

CALML5, HTR2B, CACNA1A, RYR1, ADRA1A

0.006728

CFH, PROS1, VWF

0.00764

GBP4, GBP5, LOC781710, LOC783604

0.044826

ELMO1, FN1

0.046679

CCL17, ELMO1, CCL8

0.046838

GK2, SLC27A5

0.049919

VWF, FN1

transcriptome ko04020

ko04610

o0421

ko05100

ko04062

ko03320

ko0451

Calcium

signaling

pathway Complement

and

coagulation cascades NOD-like

receptor

signaling pathway Bacterial invasion of epithelial cells Chemokine signaling pathway PPAR

signaling

pathway ECM-receptor interaction

proteome ko04971

Gastric acid secretion

0.00122

ARP2, ARP3, ARP10, PTX3, CAH2

ko05164

Influenza A

0.011631

ARP2, ARP3, ARP10, HS71A, NTF2, TRI25, MX1

ko0414

Phagosome

0.013675

ko05146

Amoebiasis

0.015476

CO5A2, CO5A1, GOGA5, IGHA2, ILEU, SPB3

0.020981

GIMA7, HXK3, CH3L1, NB5R1

0.023398

ARP2, ITGA5, ARP3, ARP10, ARPC5

0.030882

CO5A2, CO5A1, VWA1

0.042147

DHB8

0.04457

PTX3, CAH2,

Amino ko00520

sugar

nucleotide

ARP2, ITGA5, ARP3, ARP10, TBB6, IGHA2, PERM, CATS

and sugar

metabolism ko05100

ko04974

ko00140 ko04976

Bacterial invasion of epithelial cells Protein digestion and absorption Steroid biosynthesis Bile secretion

hormone

582 583



584

Figure graphics

585

HE staining of mammary tissues (200×). (A) Control group: normal

586

Figure 1.

587

mammary with an integrated structure; (B) S. agalactiae group: exfoliated mammary

588

epithelial cells and large numbers of inflammatory cells concentrated in the lumen.

589

The arrow denotes cell conglomeration.

590


Page 32 of 39

Page 33 of 39


591

Ultrastructure of mammary tissues infected with S. agalactiae (bar: 2 µm).

592

Figure 2.

593

(A) Control group: no bacteria; (B) S. agalactiae group: S. agalactiae concentrated in

594

the mammary tissues. The arrow denotes bacteria.

595



596

GO functional annotation histogram of DEGs. The X-axis shows the GO

597

Figure 3.

598



Page 34 of 39

Page 35 of 39


599

The KEGG pathways of DEGs (p < 0.05). The X-axis represents the

600

Figure 4.

601

–log10p-value, and the Y-axis shows the biological pathways.



602

The top 10 GO enrichment terms of DEPs. The X-axis shows the GO

603

Figure 5.

604


605


Page 36 of 39

Page 37 of 39


606

The top 20 KEGG enrichment pathways of DEPs. The X-axis represents

607

Figure 6.

608

the corresponding pathway enrichment score; the Y-axis represents the name of each

609

pathway. The enrichment score refers to the ratio of the number of DEPs in the

610

pathway and the number of all annotated proteins in the pathway; a higher enrichment

611

score indicates a greater degrees of enrichment, and a higher diameter indicates a

612

higher number of DEPs.

613



Page 38 of 39

614

Supporting information for review only

615

Transcriptomics

616

Mammary Tissue with Streptococcus agalactiae-induced Mastitis

and

iTRAQ-proteomics

Analyses

of

Bovine

617

(1) Streptococcus agalactiae is a common contagious pathogen, and a major

618

cause of bovine mastitis. In order to understand the pathophysiology of S.

619

agalactiae-induced mastitis and host immune response to this pathogen, integration of

620

microarray and iTRAQ analyses of mammary tissue from Chinese Holstein cows

621

infected with S. agalactiae was performed.

622

(2) This integrated analysis of transcriptome and proteome will substantially

623

improve our global view of molecular mechanisms involved in S. agalactiae-induced

624

mastitis.

625

(3) This paper will guide further studies designed to investigate the pathogenesis

626

of S. agalactiae-induced mastitis as well as the development of new prevention and

627

treatment strategies.

628


Page 39 of 39


629

TOC graphic

630


Transcriptomics and iTRAQ-proteomics Analyses of Bovine Mammary

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