Label-free proteomic analysis of intestinal mucosa proteins in common carp (Cyprinus carpio) infected with Aeromonas hydrophila

Accepted Manuscript Label-free proteomic analysis of intestinal mucosa proteins in common carp (Cyprinus carpio) infected with Aeromonas hydrophila Guilan Di, Hui Li, Chao Zhang, Yanjing Zhao, Chuanjiang Zhou, Sajid Naeem, Li Li, Xianghui Kong PII:

S1050-4648(17)30231-0

DOI:

10.1016/j.fsi.2017.04.025

Reference:

YFSIM 4550

To appear in:

Fish and Shellfish Immunology

Received Date: 13 October 2016 Revised Date:

27 April 2017

Accepted Date: 30 April 2017

Please cite this article as: Di G, Li H, Zhang C, Zhao Y, Zhou C, Naeem S, Li L, Kong X, Label-free proteomic analysis of intestinal mucosa proteins in common carp (Cyprinus carpio) infected with Aeromonas hydrophila, Fish and Shellfish Immunology (2017), doi: 10.1016/j.fsi.2017.04.025. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT

Label-free proteomic analysis of intestinal mucosa proteins in

2

common carp (Cyprinus carpio) infected with Aeromonas

3

hydrophila

4

Guilan Dia, Hui Lia, Chao Zhanga, Yanjing Zhaoa, Chuanjiang Zhoua, Sajid Naeemb, Li Lia

5

Xianghui Konga,*

6

a

College of Fisheries, Henan Normal University, Xinxiang, 453007, China

7

b

School of Life Sciences, Lanzhou University, Lanzhou, 730000, China

8

*

9

453007, China, Tel: ＋86 373 3328507; E-mail: [email protected]

SC

RI PT

1

M AN U

Corresponding author: Xianghui Kong, College of Fisheries, Henan Normal University, Xinxiang,

10 11

15 16 17 18 19

EP

14

AC C

13

TE D

12

20 21 22

1

ACCEPTED MANUSCRIPT 23

Abstract: Outbreaks of infectious diseases in common carp Cyprinus carpio, a major cultured fish in

25

northern regions of China, constantly result in significant economic losses. Until now, information

26

proteomic on immune defence remains limited. In the present study, a profile of intestinal mucosa

27

immune response in Cyprinus carpio was investigated after 0, 12, 36 and 84 h after challenging

28

tissues with Aeromonas hydrophila at a concentration of 1.4 × 108 CFU/mL. Proteomic profiles in

29

different samples were compared using label-free quantitative proteomic approach. Based on

30

MASCOT database search, 1149 proteins were identified in samples after normalisation of

31

proteins. Treated groups 1 (T1) and 2 (T2) were first clustered together and then clustered with

32

control (C group). The distance between C and treated group 3 (T3) represented the maxima

33

according to hierarchical cluster analysis. Therefore, comparative analysis between C and T3 was

34

selected in the following analysis. A total of 115 proteins with differential abundance were

35

detected to show conspicuous expressing variances. A total of 52 up-regulated proteins and 63

36

down-regulated proteins were detected in T3. Gene ontology analysis showed that identified up-

37

regulated differentially expressed proteins in T3 were mainly localised in the hemoglobin complex,

38

and down-regulated proteins in T3 were mainly localised in the major histocompatibility complex

39

II protein complex. Forty-six proteins of differential abundance (40% of 115) were involved in

40

immune response, with 17 up-regulated and 29 down-regulated proteins detected in T3. This study

41

is the first to report proteome response of carp intestinal mucosa against A. hydrophila infection;

42

information obtained contribute to understanding defence mechanisms of carp intestinal mucosa.

43 44

AC C

EP

TE D

M AN U

SC

RI PT

24

Keywords: Cyprinus carpio; Aeromonas hydrophila; intestinal mucosa; label-free proteomics; immune response 2

ACCEPTED MANUSCRIPT 45

1. Introduction The common carp, Cyprinus carpio, is an important economical fresh water fish that is

47

cultivated on a large scale in China. Recently, the infectious disease caused by Aeromonas

48

hydrophila in Cyprinus carpio resulted in significant economic loss and reached alarming levels.

49

Molecular mechanisms of such disease and immune response to this pathogenic bacterium in

50

common carp are still unclear.

RI PT

46

As a ubiquitous pathogen in water, and as it can infect a wide range of hosts, A. hydrophila

52

attracted increasing attention of researchers in recent years. Losses in aquaculture are estimated to

53

reach millions of dollars per annum due to diseases caused by A. hydrophila [1]. Symptoms of

54

disease caused by A. hydrophila infection include tissue swelling, dropsy, red sores, necrosis,

55

ulceration and haemorrhagic septicaemia [2]. A. hydrophila infect a variety of fish species,

56

including the common carp Cyprinus carpio [2], cat fish Clarias gariepinus [3], tilapia

57

Oreochromis niloticus [4], eel Anguilla anguilla [5] and goldfish Carassius auratus [6].

58

Identifying effective pharmaceutical and immunological methods is therefore necessary to prevent

59

and cure diseases caused by A. hydrophila.

EP

TE D

M AN U

SC

51

Fish intestine absorbs nutrition and defends against harmful materials [7]. Mucus is formed

61

by hydration and glycosylation of mucin and covers epithelial cell surface to form intestinal

62

mucus barrier, which provides mechanical protection from invasion of external microbes [7].

63

AC C

60

Differential proteomics provides multiplex quantitative comparison of thousands of proteins

64

between cases and control in search of disease biomarkers. This field mainly aims to study

65

differential proteins induced by special stimuli between two or more groups [8]. Differential

66

proteomics was recently applied to study stress responses of aquatic animals. Isotope and 3

ACCEPTED MANUSCRIPT 67

fluorescent labelling techniques are widely used in quantitative proteomics research. However,

68

recently, an increasing number of researchers turned to label-free proteomics techniques for faster,

69

cleaner and simpler results [9]. Whole genomes of zebrafish, puffer fish Fugu rubripes [10] and stickleback medaka

71

(Oryzias latipes) [11] were sequenced and assembled. Recently, whole genome sequencing of

72

Cyprinus carpio was also completed [12], providing a rich resource for identification of immune-

73

relevant genes and investigation of molecular mechanism of fish immunity. Meanwhile,

74

significant economic interest focused on EST (Expressed Sequence Tag) resources of these model

75

fish and other fish, such as Japanese flounder (Paralichthys olivaceus), Atlantic salmon (Salmo

76

salar), channel catfish (Ictalurus punctatus), rainbow trout (Oncorhynchus mykiss), crucian carp

77

(Carassius auratus L.) and large yellow croaker (Pseudosciaena crocea), and rapidly increasing

78

research centred on characterisation of immune-relevant genes in bony fish [13–18]. Alternatively,

79

with the help of genomic information, functional proteomic techniques became a powerful tool for

80

identification of proteins differentially responding to microorganisms or immune stimuli in fish

81

[19–21]. This approach can provide functional proteomes for understanding host immunity.

82

Therefore, proteomics will certainly contribute to understanding functions of immune-related

83

molecules in animals with unsequenced whole genomes.

SC

M AN U

TE D

EP

AC C

84

RI PT

70

With the aim of clarifying mechanisms of immune response of intestinal mucosa against

85

bacterial pathogen in common carp, the present study used label-free proteomics to analyse

86

characterisations of molecules responding to A. hydrophila challenge in Cyprinus carpio.

87

2. Materials and methods

88

2.1. Fish and bacterial strain 4

ACCEPTED MANUSCRIPT Common carp (Cyprinus carpio) weighing 90 g to 100 g were obtained from a breeding farm

90

in Wuzhi County, Henan, China. Fish were reared at 20 ±1°C for two weeks in a cylindrical tank

91

measuring 75 cm in diameter. Water depth was maintained at 70 cm, and approximately 25% of

92

water was replaced daily. Fish were randomly divided into groups of 60 fish, and experiments

93

were conducted in triplicate. All subsequent experiments were carried out in an isolated space.

94

Fish were kept in aquaria with recirculating, filtered and ultraviolet-sterilised water in the

95

Research Institute for Fisheries, Xinxiang, China. Fish were fed daily with dry commercial pellets

96

weighing 1% of their body weight. A. hydrophila was obtained from our lab. Strain of motile

97

Aeromonads was isolated from diseased commercially farmed carp with naturally developed

98

bacterial enteritis and obtained from Xinxiang, China. Healthy fish were experimentally infected

99

with isolated bacteria. Then, bacteria were re-isolated from a single symptomatic fish. Standard

SC

M AN U

biochemical diagnostic methods identified this bacteria as A. hydrophila.

TE D

100

RI PT

89

Preliminary experimental inoculation of A. hydrophila on Cyprinus carpio: Strain of A.

102

hydrophila was cultured in Luria broth (LB) at 28 °C for 24 h prior to infectivity testing. A single

103

colony was inoculated into LB and grown for 16 h at 28 °C. A. hydrophila were harvested by

104

centrifugation at 3500 rpm for 5 min and washed in physiological saline solution (PSS). Bacterial

105

concentration was determined using colony forming unit (CFU) per mL by plating 10 µL of

106

tenfold serial dilutions onto LB agar plates. Different bacterial concentrations of 2.7×104, 2.7×105,

107

2.7×106, 2.7×107, 2.7×108 and 2.7×109 CFU/mL were achieved by serial dilution with PSS.

108

Bacteria were introduced into different groups of Cyprinus carpio, with each group containing 60

109

fish (three parallel groups, each containing 20 individuals). Viability of infected fish was checked,

110

and some gross features were observed at different time intervals after A. hydrophila challenge;

AC C

EP

101

5

ACCEPTED MANUSCRIPT these parameters included swimming movement, body surface bleeding, anal inflammation,

112

abdominal dropsy and intestinal mucosal lesions. Evident indicator of disease in injected fish was

113

the inflamed area around enlarged anal opening (see Supplementary Figure 1). After re-isolation

114

of injected bacteria from internal organs of fish, bacteria were identified as A. hydrophila. Under

115

experimental conditions, half-lethal concentration of A. hydrophila (LC50 96h) on Cyprinus

116

carpio reached 7.2 ×107 CFU. Considering the above observations, challenge dose of 1.4× 108

117

CFU was selected.

118

2.2. Experimental infection and preparation of fish intestinal mucosa sample

M AN U

SC

RI PT

111

A. hydrophila was cultured in LB at 28 °C and washed by centrifugation with PSS. Cells

120

were then suspended in PSS to a final concentration of 1.4×108 CFU/mL. Live A. hydrophila was

121

injected intraperitoneally into experimental fish at 0.1 mL per fish, and control group was injected

122

with PSS using the same volume. Fish were sampled at 0, 12, 36 and 84 h. Sampled time points

123

were determined based on symptoms and activities of fish injected with A. hydrophila in a

124

preliminary study (at 12 h, mild inflammation was observed around anal regions; at 36 h, the

125

inflamed area around anal opening enlarged; at 84 h, fish died, resulting in 55% mortality rates).

126

Time point of 0 h indicates condition before injection, and it was used as control (C). Treated

127

groups T1, T2 and T3 respectively represented groups at 12, 36 and 84 h after infection with A.

128

hydrophila.

129

2.3 Sample preparation from paraffin-embedded tissues and assessment of stained sections

AC C

EP

TE D

119

130

Intestines, gills and livers of C and T3 groups were dissected out and fixed in Bouin’s fluid

131

for histological studies. Tissues were dehydrated through an ascending series of ethanol

132

concentrations and embedded in paraffin wax. Paraffin masses were cut at 4 µm thickness using a 6

ACCEPTED MANUSCRIPT Leica rotary microtome. Sections were mounted on glass slides and dried at 40 °C. Afterward,

134

sections were dewaxed in xylene and then hydrated through a descending series of ethanol

135

concentrations. Sections were then stained with Ehrlich’s haematoxylin and eosin using a Leica

136

automatic dyeing instrument and routine protocol for study of general tissues. Tissues were

137

microscopically observed. Histochemical procedures were performed on tissue sections from six

138

samples from each fish group.

139

2.4 Intestinal mucosa protein extraction for proteomics

SC

RI PT

133

Fish were not fed during infection experiment, but other conditions were kept the same as the

141

acclimation period. Fish were slit open immediately, and intestines were removed and placed on

142

ice. Intestines were cleaned to remove fat and bacteria and rinsed with cold (2 °C to 4 °C)

143

Ringer’s solution (prepared for ectothermic animals: 110 mM NaCl, 1.9 mM KCl, 13 mM CaCl2,

144

pH 7.4). Mucosa of medial part of intestine was removed with a plastic spatula. Samples were

145

homogenised using a glass homogeniser with addition of cold (2 °C to 4°C) Ringer’s solution

146

(same as above) in a 1:9 volume. Subsequently, homogenate was diluted with Ringer’s solution 2–

147

10 times. Intestinal mucosa proteins were extracted from each of the 18 fish in three independent

148

samples, each of which contained intestinal mucosa from six fish. Three technical replicates were

149

obtained for each sample to ensure reproducibility.

TE D

EP

AC C

150

M AN U

140

Pooled intestinal mucosa consisted of six fish, with 0.2 g sample obtained from each fish.

151

Pooled intestinal mucosa was mixed with four times the volume of cold acetone for 3 h at 20 °C.

152

Precipitated protein pellet was dissolved in lysis buffer (9.0 M urea, 4% b-mercaptoethanol, Tris

153

40 mM, 0.125% sodium dodecyl sulfate, 1% ampholine) for further analysis. Protein

154

concentrations were calculated by Bradford assay (BioRad, Hertfordshire, UK) using bovine 7

ACCEPTED MANUSCRIPT 155

serum albumin as standard.

156

2.5 Filter-aided sample preparation protein digestion Protein pellet was dissolved in a solution comprising 6 M urea and 2 M thiourea. Proteins

158

were reduced with dithiotreitol (1 mM) for 28 min at room temperature. Then, alkylation was

159

performed with iodoacetamide (55 mM) for 28 min in the dark. Incubation with trypsin (1 g/50 g

160

protein) (Promega, Madison, WI) was performed overnight at 37 °C. Digestion was stopped by

161

adding 5% formic acid. Peptide mixture was desalted using reversed phase C18 Stage Tips

162

(Thermo Fisher Scientific) then washed thrice with 50% acetonitrile (ACN) and 0.1%

163

trifluoroacetic acid. Peptides were eluted using each Stage Tip with 40% ACN and 0.1% formic

164

acid. Peptide concentration was measured with a Nano Drop spectrophotometer. Finally, peptides

165

were frozen at −70 °C.

166

2.6 Label-free liquid chromatography−tandem mass spectrometry (LC−MS/MS) Q Exactive

167

quantification

TE D

M AN U

SC

RI PT

157

Reversed-phase LC column featured a 5 µm particle size and a 200 Å pore size C18 resin

169

(Thermo Fisher Scientific, Bremen, Germany). The column was washed for 5.5 min with 90%

170

mobile phase A (0.1% formic acid in water) and 10% mobile phase B (0.1% formic acid in ACN)

171

after sample injection. Peptides were eluted using a linear gradient of 10% to 50% mobile phase B

172

for 25 min and then 50% to 80% mobile phase B for 6.5 min. Flow rate measured 300 nL/min,

173

column temperature was 30 °C and injection volume reached 10 µL. At least 5 µg sample of each

174

digest was used, and each sample was analysed thrice.

AC C

EP

168

175

Results of data-dependent label-free analysis were measured using Q Exactive mass

176

spectrometer (Thermo Scientific) at a flow rate of 300 nL/min. Data acquisition consisted of a 8

ACCEPTED MANUSCRIPT 70,000-resolution full-scan MS scan (automatic gain control (AGC) set to 106 ions with a

178

maximum fill time of 200 ms). Then, the 10 most abundant peaks were selected for MS/MS using

179

a 17,500-resolution scan (AGC set to 1×104 ions with a maximum fill time of 200 ms) with ion

180

selection window of 1.6 m/z and a normalised collision energy of 30. The program used a 40 s

181

dynamic exclusion window to avoid repeated selection of peptides for MS/MS. Thermo Scientific

182

Orbitrap RAW files were processed to peak lists, RAW spectra were changed to MASCOT-

183

generated files (mgf) using Proteome Discoverer software (Thermo Scientific) and analysed by

184

SIEVE software, which quantified all detected peaks and peaks exhibiting expression change

185

(>1.5-fold) were analysed using one-way ANOVA; false positive results in multiple tests were

186

estimated using q value [22].

187

2.7 Mass spectrometric data analysis

M AN U

SC

RI PT

177

Data files against protein database for identifications were analysed using Mascot. Peptides

189

identified with 95% confidence are considered “significant sequences” by Mascot Server. MS/MS

190

searches were conducted against non-redundant National Center for Biotechnology Information

191

database. Search parameters were as follows: enzyme was trypsin; allowance of one missed

192

cleavage site; fixed modification with carbamidomethyl (cysteine); variable modification was

193

oxidation of Met; monoisotopic mass values; unrestricted protein mass, with ±100 ppm as peptide

194

mass tolerance and ±1 Da as fragment mass tolerance.

195

2.8 Bioinformatics analysis

AC C

EP

TE D

188

196

Gene Ontology (GO) project is a major bioinformatics initiative that aims to standardize

197

representation of genes and gene product attributes across species and databases. The project

198

provides structured, controlled vocabularies and classifications that cover several domains of 9

ACCEPTED MANUSCRIPT molecular and cellular biology and are freely available online with annotation of genes, gene

200

products, and sequences. GO database integrates vocabularies and contributed annotations and

201

provides full access to these information in several formats. GO and subcellular localisation

202

prediction were analysed in www.geneontology.org and http://www.uniprot.org/uniprot/,

203

respectively. We used UniProt Knowledgebase (UniProtKB) for function analysis. UniProtKB is

204

the central hub for collection of functional information on proteins with accurate, consistent and

205

rich annotation. Proteins are classified into distinct categories according to their functions. The

206

function tool contains molecular function and biological processes with a subcellular location tool.

207

Currently, UniProtKB consists of more than 78,037,000 terms. The web site is

208

http://www.uniprot.org/uniprot/.

209

3. Result

210

3.1 Histological changes in intestinal mucosa, gill and liver tissues of healthy fish and fish

211

infected with A. hydrophila

TE D

M AN U

SC

RI PT

199

Microscopic examination of intestinal sections of normal fish revealed their characteristic

213

layers showing normal architecture of villi, crypts and enterocytes (Figure 1A and 1B). A: a

214

section of intestinal mucosa of control fish and its characteristic layers: mucosa, submucosa,

215

stratum compactum, muscular layer and serosa. B: normal architecture of intestinal villi. Figure

216

1C–1G: Investigation of bacteria-infected sections showed gross abnormalities of intestinal villi;

217

abnormalities included stratum compactum damage (Figure 1C–1D arrows); intestinal wall

218

thickened because of inflammatory oedema (Figure 1C–1D); many mucus-secreting goblet cells

219

were observed, and goblet cells were mainly localised in mucosal folds (Figure 1E–1G);

220

disorganisation of submucosal layer, ulceration of villi, vacuolation, sloughing of intestine,

221

desquamation especially at the tip of villi (Figure 1G), necrosis of mucous epithelium,

222

haemorrhagic septicaemia and intravascular haemolysis of blood vessels (Figure 1E). Diffuse

223

infiltration with inflammatory cells was noted in lamina propria and muscularis mucosa.

AC C

EP

212

10

ACCEPTED MANUSCRIPT Figure 2A shows a histological section of gills of normal Cyprinus carpio. Figure 2B presents

225

histological section of gills of Cyprinus carpio during A. hydrophila infection; the figure exhibits

226

fusion of gill filaments and necrosis of gill lamella. Control fish manifested normal structure and

227

systematic arrangement of hepatocytes (Figure 2C); hepatic parenchyma and blood vessels

228

showed normal structure and arrangement. A. hydrophila-infected fishes showed ruptured blood

229

vessel, mild necrosis and vacuolation in severely infected fish (Figure 2D)

230

3.2 Series protein expression data analysis by the Short Time-series Expression Miner

231

(STEM)

SC

RI PT

224

STEM is a tool for analysis of short time-series gene expression data [23]. Data from fish

233

sampled at four time points (0, 12, 36 and 84 h) were filtered to contain only 115 differential

234

proteins, which exhibited 1.5-fold increase or decrease in at least one time point. These proteins

235

were classified into 37 types. Along the top of each window are statistics on the number of

236

proteins assigned to profiles and enrichment p value. The number at the top left-hand corner of a

237

profile box represents profile ID number. Coloured profiles feature a statistically significant

238

number of assigned proteins. Non-white profiles of the same colour represent profiles grouped

239

into a single cluster (Figure 3A).

EP

TE D

M AN U

232

Figure 3B displays profiles that were reordered based on actual size and p value enrichment

241

for proteins annotated under a GO category. Each profile type number is assigned and presented in

242

the upper-left corner of each small square, and enrichment p value is found at the lower-left

243

(Figure 3B) corner. Figures 3C–3D present screenshots of detailed model profile windows.

244

Differentially expressed proteins in profiles 6 and 3 were significant and clustered on the left.

AC C

240

245

The tables present lists of genes from GO category enrichment analysis; profile 6 was

246

assigned to Table 1, and profile 3 was assigned to Table 2. The first two columns in tables

247

represent GO category ID and name. 11

ACCEPTED MANUSCRIPT For profile 6 (Figure 3C), proteins with differential expression included Rhesus-blood-group-

249

associated glycoprotein C, fast skeletal myosin light chain 1b, fast skeletal myosin light chain 3,

250

tumour necrosis factor (TNF)-α4, TNF-α1, odorant receptor 5, tyrosine protein kinase Janus

251

tyrosine kinase (JAK) 1, vitellogenin B1, major histocompatibility complex (MHC) class II alpha

252

chain and glutathione-S-transferase. For profile 3 (Figure 3D), differentially expressed proteins

253

included cluster of differentiation (CD) 8 alpha 2, sox10 protein, D4A dopamine receptor, MHC

254

class II beta chain, myosin heavy chain, nucleolin and RNA-dependent RNA polymerase.

255

3.3 Distances of four experimental groups

M AN U

SC

RI PT

248

In this study, hierarchical clustering analysis technique was used to visualise large data sets.

257

Briefly, this method calculates dissimilarity, usually called the distance, between samples with one

258

sample corresponding to one column of data matrix. Protein abundant hierarchical clustering was

259

used to identify main classes of protein abundance. Distances were determined for the four groups

260

(C, T1, T2 and T3). Together, hierarchical clustering with a TMEV heatmap determined protein

261

intensities in all technical replicates. Distances between groups were calculated based on protein

262

intensities. In this study, 1149 proteins were detected, and a dendrogram was constructed based on

263

volume values of 115 differential proteins in four fish groups using HemI 1.0 statistical software.

264

We selected a mean value (% vol)-based approach that also served as data normalisation step and

265

then proceeded with analysis. Individual proteins constantly varied among separate groups.

266

Results showed that T1 and T2 clustered in one clade, followed by clustering with C and final

267

clustering with T3. According to hierarchical cluster analysis, two formed clusters indicated clear

268

separation of T3 from C, T1 and T2 groups. C and T3 presented maximum distance (Figure 4).

269

Therefore, in this study, comparative analysis between groups T3 and C was used as primary

AC C

EP

TE D

256

12

ACCEPTED MANUSCRIPT 270

analysis.

271

3.4 Subcellular localisation prediction of differentially expressed proteins Identification of subcellular compartment of a protein can help in assessment of its function.

273

We predicted identified proteins using predictive methods (http://psort.hgc.jp/form2.html). Figure

274

5 summarises subcellular locations of differentially expressed proteins. In T3, differentially

275

expressed proteins were identified and analysed. Up-regulated proteins mainly localised in the

276

hemoglobin complex (10 proteins), membrane (8), MHC class II protein complex (8), extracellular

277

regions (5) and myosin complex (5), whereas down-regulated proteins were mainly localised in

278

the MHC class II protein complex (14 proteins), membrane (10), nucleus (9), myosin complex (6),

279

hemoglobin complex (5) and secreted molecules (5).

280

3.5 Label-Free Proteomic Analysis

M AN U

SC

RI PT

272

Identified proteins were matched to specific processes or functions by searching the GO

282

database (http://www.uniprot.org/uniprot/). Using a label-free quantitative proteomic approach,

283

1149 proteins were identified from samples, and 115 differentially abundant proteins (>1.5 fold)

284

were detected.

EP

TE D

281

Among these proteins, 52 up-regulated proteins and 63 down-regulated proteins were found

286

in T3 (Supplementary Table 1). Most up-regulated proteins were involved in oxygen transport (10

287

proteins, including beta globin, hemoglobin alpha and alpha globin), muscle proteins (nine

288

proteins including myosin heavy-chain embryonic type 3, actin-cytoplasmic 1, myosin heavy-

289

chain embryonic type 1, myosin heavy-chain embryonic type 2, skeletal muscle alpha-actin, actin-

290

alpha skeletal muscle and skeletal muscle actin mutant), antigen processing and presentation

291

(immune response) (eight proteins identified as MHC class II antigen beta chains), immune

AC C

285

13

ACCEPTED MANUSCRIPT response (four proteins, including interferon (IFN) gamma 2a, interleukin (IL)-1 beta and CD8

293

alpha2-2), endocytosis (three proteins, including growth hormone receptor type 2a and growth

294

hormone receptor type 2b) (Figure 6). Most of down-regulated proteins were involved in antigen

295

processing and presentation, immune response (14 proteins, including MHC class II antigen beta

296

chain, MHC class II alpha chain and Rhesus-blood-group-associated glycoprotein C), muscle

297

protein (eight proteins, including fast skeletal myosin light chain 1a, fast skeletal myosin light

298

chain 1b, fast skeletal myosin light chain 3, myosin heavy-chain and skeletal muscle actin),

299

immune response (five proteins, including CD8 alpha 2, TANK-binding kinase 1 (TBK1), IL-1

300

beta, TNF-α4 and TNF-α1), oxygen transport (five proteins, including hemoglobin alpha, alpha-

301

globin and beta-globin), transcription (four proteins, including oestrogen receptor, Irx3a2,

302

mineralocorticoid receptor and upstream binding transcription factor 1), complement pathway,

303

fatty acid metabolism and immunity (three proteins, including complement C3-Q1 and

304

complement C3-H1). As shown in Figure 6, protein abundance profiles differed significantly from

305

C to T3 (Figure 6).

TE D

M AN U

SC

RI PT

292

To test direct correlation in corresponding proteins, the correlation between C and T3 was

307

based on estimated concentrations of differentially expressed proteins (Figure 7A). Correlation

308

between C and T3 was positive with a correlation score of 0.87 (Figure 7B). To compare

309

abundance ranking of differential proteins between C and T3, abundances of 115 differentially

310

expressed proteins were identified. Supplementary Table 1 presents correlation results of proteins.

311

Among the top 30 abundant proteins identified (Figure 7C), six differentially expressed proteins

312

increased over three times in T3, for example, MHC class II antigen beta chain (9.29-fold,

313

involved in antigen processing and presentation and immune response), complement component

AC C

EP

306

14

ACCEPTED MANUSCRIPT C5-1 (4.06-fold, involved in complement alternate pathway, inflammatory response and innate

315

immunity), beta globin (3.97-fold, involved in oxygen transport), D4B dopamine receptor (3.47-

316

fold, involved in adenylate-cyclase-inhibiting dopamine receptor signalling pathway) and myosin

317

heavy-chain embryonic type 3 (3.05-fold, involved in muscle protein). Six differentially expressed

318

proteins decreased four times in T3; these proteins included C-reactive protein (CRP)-like 2

319

(>tenfold, involved in acute-phase response), oestrogen receptor (eightfold, involved in

320

transcription and immune response), Irx3a2 (6.29-fold, involved in transcription), MHC class II

321

beta chain (protein No 112, 5.45-fold, involved in antigen processing and presentation and

322

immune response), myogenic factor 6 (4.37-fold, involved in muscle organ development and

323

regulation of transcription) and MHC class II antigen beta chain (protein No 110, 4.04-fold,

324

involved in antigen processing and presentation and immune response).

M AN U

SC

RI PT

314

In our study, differentially expressed proteins are involved in immune response, as described

326

in Figure 8 (Supplementary table 1). A total of 46 differentially abundant proteins (40% of 115

327

differential abundance proteins) were involved in immune response with 17 up-regulated and 29

328

down-regulated proteins in T3 compared with C. Most up-regulated proteins included MHC class

329

II proteins (47.06%) and growth hormone receptors (17.65%). (Figure 8A). Most down-regulated

330

proteins included MHC class II proteins (48.28%) and complement C3 (10.34%). (Figure 8B).

331

Interestingly, a significant portion of up-regulated proteins in T3 were identified as IFN gamma 2a

332

(5.88%) (Figure 8A), down-regulated proteins in T3 corresponded to complement C3 (10.34%),

333

TNF-α4 (3.45%), TNF-α1 (3.45%), TBK1 (3.45%), CRP (3.45%), serum amyloid A (SAA)

334

protein (3.45%), complement C4 (3.45%), glutathione-S-transferase (3.45%) and corticotropin-

335

releasing hormone-binding protein 2 (3.45%) (Figure 8B).

AC C

EP

TE D

325

15

ACCEPTED MANUSCRIPT 336 337

3.6 Predicted interactions of identified differentially proteins involved in immune response Figure

9

shows

predicted

interactions

of

identified

differential

proteins

at

http://string.embl.de/ website. Figure 10 displays the number of interactive network of protein co-

339

expression. Table 3 lists protein abbreviations and their corresponding full names. Identified

340

differentially expressed co-expression proteins mainly included glutathione reduced (glutathione

341

re.), maleylacetoacetic acid (maleylacet.tic.), glutathione transferase zeta 1 isoform 1(zgc:92869),

342

adenosine triphosphate (adenosine trip.), homogentisate 1,2-dioxygenase (hgd), acetoacetic acid

343

(acetoacetate), homogentisic acid (homogentisic a.), fumarylacetoacetate hydrolase (FAH), IL-1

344

(il1b), nuclear factor of kappa light polypeptide gene enhancer in B-cells 2 (nfkb2), v-rel

345

reticuloendotheliosis viral oncogene homolog A (rela) and myeloid differentiation primary

346

response gene 88 (myd88) (Figure 10).

347

4. Discussion

348

4.1 Histopathological studies

TE D

M AN U

SC

RI PT

338

Integrity of gastrointestinal tract acts as protective barrier against bacteria and endotoxins.

350

Histological study of intestine is important in understanding status of structural integrity. This

351

method helps in improving our understanding of the influence of infective pathogens. In this study,

352

A. hydrophila induced deterioration in intestinal mucosa, suggesting that immune ability of

353

intestinal mucosal can be affected.

354

4.2 Data quality assessment with label-free quantitative proteomics using Q Exactive MS

AC C

EP

349

355

Proteomics based on LC-MS is a well-established technology for discovery of disease

356

biomarkers. In the present study, we detected differentially abundant immune proteins against

357

bacterial challenge; our objective was to evaluate the Q Exactive MS with an Orbitrap [24]. This 16

ACCEPTED MANUSCRIPT 358

technology offers more accurate and higher resolution in mass measurements of precursors and

359

their fragments and detects significantly more proteins compared with traditional methods [8]. Label-free quantitation is one of the simplest and least expensive methods [25]. These label-

361

free quantitative approaches provided rigorous, powerful tools for analysing protein changes in

362

large-scale proteomics study [9]. Commercially available data-processing software can

363

automatically detect, match and analyse peptides from hundreds of different LC-MS experiments

364

simultaneously and provide high-throughput technique for disease-related biomarker discovery.

SC

RI PT

360

In the present study, we identified 115 differential proteins. Data analyses of differentially

366

expressed proteins identified with at least 1.5-fold changes between C and T3 are emphatically

367

discussed as follows.

368

4.3 Acute-phase proteins

370

CRP, SAA, and haptoglobin increase in concentration in response to infection; they are

TE D

369

M AN U

365

classified as positive acute-phase proteins (APPs) [26]. CRP: CRPs make up the first barrier for host-invading pathogenic bacteria [27]. CRP and/or

372

antibody-antigen complexes and surfaces of bacteria, viruses or fungi activate the classical

373

pathway [28]. CRP can agglutinate and activate the complement system by classical pathways.

374

Previous studies [29, 30] revealed that bacterial and viral infections in common carp (Cyprinus

375

carpio) invoke acute phase response (APR). For example, serum levels of CRP increased up to

376

sixfold within 40 h of infection with A. hydrophila [31]. In the present study, protein No 115 was

377

identified as CRP. Protein contents reached 1 for C, 9.63 for T1, 0 for T2 and 0 for T3, and CRP

378

increased up to ninefold within 12 h of infection with A. hydrophila.

379

AC C

EP

371

SAA is a vital protein involved in inflammatory reaction and features two basic functions. 17

ACCEPTED MANUSCRIPT The first function involves induction of extracellular matrix-degrading enzymes, such as

381

collagenase, stromelysin and matrix metalloproteinases, which are important for tissue damage

382

repair. The second function is chemoattraction of immune-related cells, such as monocytes,

383

polymorphonuclear leukocytes and mast cells [32]. SAA is released from hepatocytes under

384

inflammatory condition to protect healthy cells from damages caused by pathogens or from self-

385

destructive mechanisms. SAA is a major positive APP, which increases several hundred folds in

386

concentration during acute phase of infection and is regulated by Toll-like receptor (TLR)

387

signalling cascade [33]. In zebrafish, SAA mRNA level enhances rapidly in response to virus,

388

lipopolysaccharide (LPS) and Poly (I: C) and then quickly returns to normal phase. Thus, SAA

389

plays a significant role in innate immune response in zebrafish [34]. In this study, protein No 84

390

was identified as SAA protein, reaching an amount of 7.81 in control and 5.35 in T3; no

391

significant difference was noted between C and T3.

TE D

M AN U

SC

RI PT

380

CRP decreased by tenfold at 84 h of infection with A. hydrophila, and SAA slightly decreased

393

in T3. These results may be related to time of infection. CRP increased up to eightfold at 12 h of

394

infection with A. hydrophila. These results suggested that A. hydrophila injection significantly

395

affected carp CRP at preliminary stages of infection. Compared with SAA, CRP was identified as

396

an APP in carp.

397

4.4 Cytokines

AC C

398

EP

392

In general, cytokines are produced at entry sites of pathogens and drive inflammatory signals

399

that regulate capacity of residents and newly arrived phagocytes to destroy invading pathogens.

400

These molecules also regulate antigen presentation function in dendritic cells and their migration

401

to lymph nodes to initiate adaptive immune response in mammals [35]. This study identified 18

ACCEPTED MANUSCRIPT 402

cytokines including IFN gamma 2a, IL-1 beta and TNF-α4. As potent biologically active cytokines, IFNs are key effectors of antiviral activity in

404

vertebrates. IFNs also regulate immune system in mammals [36]. Protein No 13 was identified as

405

IFN gamma 2a, and its amount reached 6.19 for C. With a total of 13.52, this protein also

406

exhibited up-regulation in T3,

RI PT

403

As a group of cytokines that play major regulatory roles in the immune system, ILs are

408

produced by and target a wide variety of cells; they are also involved in complex cell signalling

409

systems in the immune system [37]. In this study, protein No 102 was identified as IL-1 beta, and

410

its protein amount reached 30.82 for C and 14.47 for T3, indicating down-regulation.

M AN U

SC

407

TNFα induces innate immune response and enhances activation of macrophages, respiratory

412

activity, production of phagocytosis and nitric oxide in rainbow trout, turbot, sea bream, goldfish

413

and catfish [38–40]. In this study, protein No 106 was identified as TNF-α4, and its amount was

414

calculated as 3.56 for C and down-regulated in T3 at a value of 1.48.

TE D

411

Cytokine IFN gamma 2a exhibited up-regulation in T3. However, IL-1β and TNFα1 were

416

down-regulated in T3. It was suggested that the defense ability generally reduced in intestinal

417

mucosa in response to A. hydrophila infection at 84 h. Previous studies showed that IL-6 and

418

TNFα induce CRP. In this study, IL-1β, TNFα1 and CRP were down-regulated in T3, suggesting

419

that IL-1β and TNFα1 may induce CRP in carp intestinal mucosa as a response to A. hydrophila

420

infection.

421

4.5 Other intestinal mucosa proteins associated with immune response in common carp

422

infected with A. hydrophila

423

AC C

EP

415

Highly polymorphic classical MHC class II molecules can present exogenous antigenic 19

ACCEPTED MANUSCRIPT peptides, including those derived from proteins of many pathogens to CD4+ T lymphocytes in

425

acquired immune systems [41]. T-cell coreceptor CD8 and CD4 bind to MHC class I and II

426

molecules, respectively [42]. In this study, two proteins were identified as MHC class II (protein

427

No 1 and 17) molecules and were up-regulated in T3, whereas three proteins (protein No 108, 110

428

and 112) were down-regulated in T3. Protein No 93 was identified as CD8 alpha 2, with amounts

429

of 58 for C and down-regulated amount of 37.37 for T3.

RI PT

424

The complement system plays a significant role in early pathogen defence [43]. CRP can

431

agglutinate and activate the complement system through classical methods. Complement gene

432

activation is mediated by several regulatory proteins that provide balanced complement

433

concentrations in proportion to activation signal strength [44]. Binding of activated C3 and C4

434

proteins to pathogenic surfaces enhances phagocytosis of coated microbes. Complement activity

435

significantly increases in common carp orally stimulated with β-glucan and challenged by A.

436

salmonicida [29] or by Cyprinid herpesvirus 3 [45]. In this study, protein No 107 was identified as

437

complement C3, and its amount reached 7.63 for C and 3.09 for T3, indicating down-regulation.

438

Two proteins (protein Nos 2 and 35) were identified as complement component C5. Contents of

439

protein No 2 was 0.8 for C and 3.25 for T3, whereas that of protein No 35 measured 0.01 for C

440

and 0.02 for T3. Both proteins were up-regulated in T3. Complement C5 is the central component

441

in terminal stage of three complement activation pathways; it plays a key role in inflammatory

442

response and complement-mediated cytolysis. RNA expression level of C5 was significantly

443

increased by stimulation of carp with LPS [46]. Published results indicated that expressions of

444

complement molecules in common carp (Cyprinus carpio) were significantly stimulated by the

445

parasite Ichthyophthirius multifiliis [47]. In the present study, C5 were up-regulated in T3, and

AC C

EP

TE D

M AN U

SC

430

20

ACCEPTED MANUSCRIPT 446

results agree with those of previous studies.

447

4.6 Cell signalling pathways This study identified few proteins, such as IFN, TNFα and TBK1, that are associated with

449

cell signalling pathways. Cellular responses to IFN are mediated via cell-specific receptors and

450

depend on activation of signal pathways. The major signal pathways activated by IFNs involve

451

sequential phosphorylation of tyrosine residues of the JAK/signal transducers and activators of

452

transcription proteins [48–50]. In this study, protein No 13 was identified as IFN gamma 2a and

453

was up-regulated in T3. TNFα (protein No 67 and 106) showed down-regulation in T3 and

454

possibly regulated the signal pathways JNK, ERK, IKK, and Wnt.

M AN U

SC

RI PT

448

TBK1 functions as a key node protein in several cell signalling pathways, including innate

456

immune response [51]. To date, most TBK1 studies focus on role of kinase in innate immune

457

pathway that leads to type 1 IFN response, such as TLR (e.g. TLR3 and TLR4) and cytosolic viral

458

DNA/RNA receptor (e.g. RIG-I and MDA5) signalling [52–55]. As mentioned above, various

459

studies also defined the role of TBK1 in degradation of invasive bacteria via ubiquitin-mediated

460

clearance mechanism [56–59]. As this latter pathway also falls under cellular response to pathogen

461

detection, it ultimately engages autophagy machinery to eliminate cytosolic bacteria (xenophagy)

462

as opposed to inducing transcriptional up-regulation of IFNs and inflammation to combat infection.

463

In this study, protein No 101 was identified as TBK1, and its amount reached 66.92 for C and

464

34.72 for T3. Down-regulation of TBK1 suggested that A. hydrophila infection features a more

465

significant effect on intestinal mucosal immunity in carp.

AC C

EP

TE D

455

466

In this study, some proteins, including CRP, IFNγ, IL-1β, TNFα, MHC II, CD8 α2, C3, C5,

467

and TBK1, showed differential expressions in intestinal mucosa of carps infected by A. hydrophila. 21

ACCEPTED MANUSCRIPT Among these proteins, IFNγ and C5 were up-regulated in T3. Further studies are needed to define

469

mechanisms by which proteins associate with stress response and other host factors and to gain

470

new insights into intestinal mucosa immunity and new therapeutic strategies for inflammatory and

471

infectious diseases of the bowel [7].

472

5. Conclusions

RI PT

468

The present study investigated effects of A. hydrophila on carp intestinal mucosa based on

474

label-free quantitative proteomics. Detected differentially expressed proteins are involved in stress

475

and immune responses of local defence mechanism of intestinal mucosa. This study is the first to

476

report proteome of carp intestinal mucosa against A. hydrophila infection, and results may

477

contribute to understanding defence mechanisms of carp intestinal mucosa and associated

478

molecular mechanisms. However, further studies are needed to determine functions of the

479

described proteins and their specific roles in immune response against bacteria.

480

Acknowledgements

TE D

M AN U

SC

473

It was supported by the fund of the National Natural Science Foundation of China (NSFC)

482

(No. 31640085), Henan Basic and Advanced Research Program (No. 152300410206), this work

483

was also supported by Henan Science and Technology Program (No. 14B240003), the PhD Start-

484

up Fund of Henan Normal University (No.qd13053). The joint Fund of Natural Science

485

Foundation of China and Henan Province (U1604104), the Program for Innovative Research Team

486

(in Science and Technology) in University of Henan Province (15IRTSTHN018), Innovation

487

Scientists and Technicians Troop Construction Projects of Henan Province (CXTD2016043).

488

References

AC C

EP

481

22

ACCEPTED MANUSCRIPT 489 490

[1] Fang HM, Ge R, Sin YM. Cloning, characterisation and expression of Aeromonas hydrophila major adhesin. Fish Shellfish Immunol 2004; 16:645–58.

[2] Karunasagar I, Rosalind GM, Karunasagar I, Gopal Rao K. Aeromonas hydrophila septicaemia

492

of Indian major carps in some commercial fish farms of West Godavari District, Andhra

493

Pradesh. Curr Sci 1989; 58:1044–5.

496 497

SC

495

[3] Llobrera AT, Gacutan RQ. Aeromonas hydrophila associated with ulcerative disease epizootic in Laguna de Bay, Philippines. Aquaculture 1987;67:273–8.

[4] Yambot AV. Isolation of Aeromonas hydrophila from Oreochromis niloticus during fish

M AN U

494

RI PT

491

disease outbreaks in the Philippines. Asian Fish Sci 1998;10:347–54.

[5] Esteve C, Biosca EG,AmaroC. Virulence of Aeromonas hydrophila andsomeother bacteria

499

isolated from European eels Anguilla anguilla reared in fresh water. Dis Aquat Org

500

1993;16:15–20.

TE D

498

[6] Maji S, Mali P, Joardar SN. Immunoreactive antigens of the outer membrane protein of

502

Aeromonas hydrophila, isolated from goldfish, Carassius auratus (Linn.).Fish Shellfish

503

Immunol 2006;20:462–73.

AC C

EP

501

504

[7] Golovanova IL, Golovanov VK, Smirnov AK, Pavlov DD. Effect of ambient temperature

505

increase on intestinal mucosa amylolytic activity in freshwater fish. Fish Physiol Biochem

506

2013; 39:1497–1504

507

[8] Jones KA, Kim PD, Patel BB, Kelsen SG, Braverman A, Swinton DJ, et al. Immunodepletion

508

plasma proteomics by triple TOF 5600 and Orbitrap elite/LTQ-Orbitrap Velos/Q exactive

509

mass spectrometers. J Proteome Res 2013; 12(10):4351-65. 23

ACCEPTED MANUSCRIPT

513

514 515

516 517

[10] Aparicio S, Chapman J, Stupka E, Putnam N, Chia JM, Dehal P, et al. Whole genome shotgun assembly and analysis of the genome of Fugu rubripes. Science 2002; 297:1301-10.

RI PT

512

Biomed Biotechnol 2010; Article ID 840518, 6 pages

[11] Kasahara M, Naruse K, Sasaki S, Nakatani Y, Qu W, Ahsan B, et al. The medaka draft genome and insights into vertebrate genome evolution. Nature 2007; 447: 714-9.

SC

511

[9] Zhu W, Smith JW, Huang CM. Mass spectrometry-based label-free quantitative proteomics. J

[12] Xu P, Zhang X, Wang X, Li J, Liu G, Kuang Y, et al. Genome sequence and genetic diversity of the common carp, Cyprinus carpio. Nature Genetics 2014; 46(11):1212-9.

M AN U

510

[13] Nam BH, Hirono I, Aoki T. Bulk isolation of immune response-related genes by expressed

519

sequenced tags of Japanese flounder Paralichthys olivaceus leucocytes stimulated with Con

520

A/PMA. Fish Shellfish Immunol 2003; 14: 467-76.

522

[14] Davey GC, Caplice NC, Martin SA, Powell R. A survey of genes in the Atlantic salmon (Salmo salar) as identified by expressed sequence tags. Gene 2001; 263:121-30.

EP

521

TE D

518

[15] Ju Z, Karsi A, Kocabas A, Patterson A, Li P, Cao D, et al. Transcriptome analysis of channel

524

catfish (Ictalurus punctatus): genes and expression profile from the brain. Gene 2000;

525

526

AC C

523

261:373-82

[16] Goetz FW, Iliev DB, McCauley LA, Liarte CQ, Tort LB, Planas JV, et al. Analysis of genes

527

isolated

528

macrophages. Mol Immunol 2004; 41:1199-210.

529 530

from

lipopolysaccharide-stimulated

rainbow

trout

(Oncorhynchus mykiss)

[17] Zhang YB, Zhang QY, Xu DQ, Hu CY, Gui JF. Identification of antiviral-relevant genes in the cultured fish cells induced by inactivated virus. Chin Sci Bull 2003; 48:581-8. 24

ACCEPTED MANUSCRIPT 531

[18] Zheng WB, Liu GZ, Ao JQ, Chen XH. Expression analysis of immune-relevant genes in the

532

spleen of large yellow croaker Pseudosciaena crocea, stimulated by polyI: C. Fish Shellfish

533

Immunol 2006; 21:414-30.

[19] Booth NJ, Bilodeau-Bourgeois AL. Proteomic analysis of head kidney tissue from high and

535

low susceptibility families of channel catfish following challenge with Edwardsiella ictaluri.

536

Fish Shellfish Immunol 2009; 26: 193-6.

SC

538

[20] Peng XX, Wu YJ, Wang SY. Acute phase response (APR)-related proteome of loach skin to injury. Proteomics 2004; 4: 3989-97.

M AN U

537

RI PT

534

[21] Martin SA, Mohanty BP, Cash P, Houlihan DF, Secombes CJ. Proteome analysis of the

540

Atlantic salmon (Salmo salar) cell line SHK-1 following recombinant IFN-gamma

541

stimulation. Proteomics 2007; 7: 2275-86.

TE D

539

[22] Mcdonagh B, Sakellariou GK, Smith NT, Brownridge P, Jackson MJ. Differential Cysteine

543

Labelingand Global Label-Free Proteomics Reveals an Altered Metabolic State in Skeletal

544

Muscle Aging. J Proteome Res 2014; 13(11):5008-21.

546

[23] Ernst J, Bar-Joseph Z. Stem: a tool for the analysis of short time series gene expression

AC C

545

EP

542

data. Bmc Bioinformatics 2006; 7(3), 1-11.

547

[24] Michalski A, Damoc E, Hauschild JP, Lange O, Wieghaus A, Makarov A, et al. Mass

548

spectrometry-based proteomics using Q Exactive, a high-performance benchtop quadrupole

549

Orbitrap mass spectrometer. Mol Cell Proteomics 2011; 10: M111.011015.

25

ACCEPTED MANUSCRIPT 550

[25] Aoshima K, Takahashi K, Ikawa M, Kimura T, Fukuda M, Tanaka S, et al. A simple peak

551

detection and label-free quantitation algorithm for chromatography-mass spectrometry. BMC

552

Bioinformatics 2014; 15(1):376-376.

555 556

RI PT

554

[26] Heinrich PC, Castell JV, Andus T. Interleukin-6 and the acute phaseresponse. Biochem J 1990; 265: 621-636.

[27] Ansar W, Ghosh S. C-reactive protein and the biology of disease. Immunol Res 2013;56: 131~142.

SC

553

[28] Ebenbichler CF, Thielens NM, Vornhagen R, Marschang P, Arlaud GJ, Dierich MP. Human

558

immunodeficiency virus type 1 activates the classical pathway of complement by direct C1

559

binding through specific sites in the transmembrane glycoprotein gp41. J Exp Med 1991;

560

174:1417-24.

M AN U

557

[29] Pionnier N, Falco A, Miest J, Frost P, Irnazarow I, Shrive A, et al. Dietary bglucan stimulate

562

complement and C-reactive protein acute phase responses in common carp (Cyprinus carpio)

563

during an Aeromonas salmonicida infection. Fish Shellfish Immunol 2013; 34(3):819-31.

564

[30] MacCarthy EM, Burns I, Irnazarow I, Polwart A, Greenhough TJ, Shrive AK, et al. Serum

565

CRP-like protein profile in common carp Cyprinus carpio challenged with Aeromonas

567

EP

AC C

566

TE D

561

hydrophila and Escherichia coli lipopolysaccharide. Dev Comp Immunol 2008; 32(11):12819.

568

[31] Jorgensen JB, Lunde H, Jensen L, Whitehead AS, Robertsen B. Serum amyloid A

569

transcription in Atlantic salmon (Salmo salar L.) hepatocytes is enhanced by stimulation with

570

macrophage factors, recombinant human IL beta, IL-6 and TNF alpha or bacterial

571

lipopolysaccharide. Dev Comp Immunol 2000; 24:553-63. 26

ACCEPTED MANUSCRIPT [32] Strissel KJ, Girard MT, West-Mays JA, Rinehart WB, Cook JR, Brinckerhoff CE, et al. Role

573

of serum amyloid A as an intermediate in the IL-1 and PMA-stimulated signaling pathways

574

regulating expression of rabbit fibroblast collagenase. Exp Cell Res 1997; 237: 275-287.

575

[33] Wei J, Guo, M Ji, Qin H, Molecular cloning Q. characterization of one key molecule of

576

teleost innate immunity from orange-spotted grouper (Epinephelus coioides): serum amyloid

577

A. Fish Shellfish Immunol 2013; 34: 296-304.

SC

579

[34] Lin QI, Feng X, Xiang Z, Zhang T. The Expression Pattern of SAA Responding to Virus Infection in Zebrafish. Journal of Henan University 2013; 43(5):540-544.

M AN U

578

RI PT

572

580

[35] Chabalgoity JA, Baz A, Rial A, Grille S. The relevance of cytokines for development of

581

protective immunity and rational design of vaccines. Cytokine Growth Factor Rev 2007;

582

18:195-207.

[36] Stetson DB, Medzhitov R. Type I interferons in host defense. Immunity 2006; 25:373–381.

584

[37] Pérez-Cordón G, Estensoro I, Benedito-Palos L, Calduch-Giner JA, Sitjà-Bobadilla A, Pérez-

585

Sánchez J. Interleukin gene expression is strongly modulated at the local level in a fish-

586

parasite model. Fish Shellfish Immunol 2014; 37(2):201–208.

588 589

EP

[38]Mulero V, Meseguer J. Functional characterisation of a macrophage-activating factor

AC C

587

TE D

583

produced by leucocytes of gilthead seabream (Sparus aurata L.). Fish Shellfish Immunol

1998; 8: 143–156.

590

[39]Tafalla C, Figueras A, Novoa B. Viral hemorrhagic septicemia virus alters turbot

591

Scophthalmus maximus macrophage nitric oxide production. Dis Aquat Org 2001; 47:101–

592

107.

593

[40] Yin Z, Lam TL, Sin YM. Cytokine-mediated antimicrobial immune response of catfish, 27

ACCEPTED MANUSCRIPT 594

Clarias gariepinus, as a defence against Aeromonas hydrophila. Fish Shellfish Immunol

595

1997; 7: 93–104.

597

[41] Neefjes J, Jongsma MLM, Paul P, Bakke O. Towards a systems understanding of MHC class I and MHC class II antigen presentation. Nature Rev Immunol 2011; 11:823–836.

RI PT

596

[42] Buonocore F, Randelli E, Bird S, Secombes CJ, Costantini S, Facchiano A, et al. The CD8

599

alpha from sea bass (Dicentrarchus labrax L): cloning, expression and 3D modelling. Fish

600

Shellfish Immunol 2006; 20(4): 637–646.

SC

598

[43] Köbis JM, Rebl A, Kühn C, Korytář T, Köllner B, Goldammer T. Comprehensive and

602

comparative transcription analyses of the complement pathway in rainbow trout. Fish

603

Shellfish Immunol 2015; 42(1): 98-107.

605

[44] Volanakis J. Transcriptional regulation of complement genes. Annu Rev Immunol 1995; 13:277-30

TE D

604

M AN U

601

[45] Rakus K, Irnazarow I, Adamek M, Palmeira L, Kawana Y, Hirono I, et al. Gene expression

607

analysis of common carp (Cyprinus carpio L.) lines during Cyprinid herpesvirus 3 infection

608

yields insights into differential immune responses. Dev Comp Immunol 2012;37(1):65-76.

AC C

EP

606

609

[46] Kato Y, Nakao M, Mutsuro J, Zarkadis IK, Yano T. The complement component C5 of the

610

common carp (Cyprinus carpio): cDNA cloning of two distinct iso-types that differ in a

611

functional site. Immunogenetics 2003; 54:807-15.

612

[47] Gonzalez SF, Buchmann K, Nielsen ME. Complement expression in common carp (Cyprinus

613

carpio L.) during infection with Ichthyophthirius multifiliis. Dev Comp Immunol 2007;

614

31:576-86.

28

ACCEPTED MANUSCRIPT

616 617 618 619 620

[48] Platanias LC. Mechanisms of type-I- and type-II-interferon-mediated signalling. Nat Rev Immunol 2005; 5: 375–386. [49] Takaoka A, Yanai H. Interferon signalling network in innate defence. Cell. Microbiol 2006; 8: 907–922.

RI PT

615

[50] Chelbi-Alix MK,Wietzerbin J. Interferon, a growing cytokine family: 50 years of interferon research. Biochimie 2007; 89: 713–718.

[51] Li S, Wang L, Berman M, Kong YY, Dorf ME. Mapping a dynamic innate immunity protein

622

interaction network regulating type I interferon production. Immunity 2011; 35:426–440.

623

[52] Chang CH, Lai LC, Cheng HC, Chen KR, Syue YZ, Lu HC, et al. TBK1-associated protein in

624

endolysosomes (TAPE) is an innate immune regulator modulating the TLR3 and TLR4

625

signaling pathways. J Biol Chem 2011; 86: 7043–7051.

M AN U

SC

621

[53] Castanier C, Zemirli N, Portier A, Garcin D, Bidère N, Vazquez A, et al. MAVS

627

ubiquitination by the E3 ligase TRIM25 and degradation by the proteasome is involved in

628

type I interferon production after activation of the antiviral RIG-I-like receptors. BMC Biol

629

2012;10:1-13.

631 632 633 634

EP

[54] Chattopadhyay S, Yamashita M, Zhang Y. The IRF-3/Baxmediated apoptotic pathway,

AC C

630

TE D

626

activated by viral cytoplasmic RNA and DNA, inhibits virus replication. J Virol 2011; 85:3708-16.

[55] Ferguson BJ, Mansur DS, Peters NE, Ren H, Smith GL. DNA PK is a DNA sensor for IRF-3dependent innate immunity 2012; 1: e00047- e00047.

635

[56] Thurston TL, Ryzhakov M, Bloor G, Muhlinen von SN. Randow F. The TBK1 adaptor and

636

autophagy receptor NDP52 restricts the proliferation of ubiquitin-coated bacteria. Nat 29

ACCEPTED MANUSCRIPT 637

Immunol 2009; 10: 1215–1221. [57] Gleason CE, Ordureau A, Gourlay R, Arthur JSC, Cohen P. Polyubiquitin binding to

639

optineurin is required for optimal activation of TANK-binding kinase 1 and production of

640

interferon b. J Biol Chem 2011; 286: 35663–35674.

643 644

the autophagy receptor optineurin restricts salmonella growth. Science 2011; 333: 228–233. [59] Randow F. How cells deploy ubiquitin and autophagy to defend their cytosol from bacterial invasion. Autophagy 2011; 7: 304–309.

645

646

651

652

653

EP

650

AC C

649

TE D

647

648

SC

642

[58] Wild P, Farhan H, Mcewan DG, Wagner S, Rogov VV, Brady NR, et al. Phosphorylation of

M AN U

641

RI PT

638

654

655

656 30

ACCEPTED MANUSCRIPT Titles and legends of figures

657

Figure 1. Histological changes in intestinal mucosa tissues of healthy fish and fish infected with A.

659

hydrophila

660

Figures 1A–1B: Intestinal sections of normal fish A: Cells were arranged in a regular pattern and

661

showed characteristic layers; B: Normal architecture of villi. Figures 1C–1G: Bacterial infection

662

showed gross abnormalities in intestinal sections. Figures 1C–1D: Stratum compactum damage

663

(arrows) and vacuolation. Figures 1E–1G: Many goblet cells were mainly localised in the mucosal

664

folds; disorganisation of submucosal layer, vacuolation and desquamation especially at the tip of

665

villi (Figure 1G, arrow) and intravascular haemolysis (Figure 1E). HE—Haemorrhage; SC—

666

Stratum compactum; SE—Serosa; L—Lumen; SE—Serosa; V—Villi; VL—Vacuole; G—goblet

667

cells.

668

Figure 2. A: Gill section of Cyprinus carpio (control); B: Gill section of Cyprinus carpio exposed

669

to A. hydrophila; C: Image of cross section of liver in control; D: Liver section of Cyprinus carpio

670

exposed to A. hydrophila. GL—Gill lamella; NC—Necrosis; CV—Central Venule; P—

671

Parenchyma; VL—Vacuole.

672

Figure 3. Reordered interface for model profiles by STEM. Data were drawn from an experiment

673

measuring responses of Cyprinus carpio intestinal mucosa infected with A. hydrophila strain.

674

Data were obtained from four groups (C, T1, T2 and T3). Dataset contained 115 differential

675

proteins. (A) Clusters ordered based on the number of proteins and profiles arranged by

676

significance. The number in the top left-hand corner refers to profile ID number. Coloured profiles

677

show statistically significant numbers; (B) Reordered interface of model profiles. Profiles were

678

arranged based on p value of number of proteins assigned versus expected value. Each profile type

AC C

EP

TE D

M AN U

SC

RI PT

658

31

ACCEPTED MANUSCRIPT number presented in the upper-left and enrichment p value appear in the lower-left of each small

680

square; C–D Detailed information on two model profiles. Images are screenshots of two detailed

681

model profiles for data of Figures 2A–2B. Two significant profiles. (C) Detailed information

682

windows for model profile 6; (D) Detailed information windows for model profile 3.

683

Figure 4. Hierarchy clustering analysis for proteome of immune response of intestinal mucosa to

684

A. hydrophila in Cyprinus carpio. Hierarchical clustering analysis of 115 differentially abundant

685

proteins. Heat map shows clustered data in which each coloured cell represents a protein

686

abundance value according to colour scale on the right of the figure. Colours ranging from blue to

687

red represent protein abundance from the highest level of down-regulation to highest level of up-

688

regulation, respectively. The lower side shows similarities of protein expression patterns

689

represented by distance of branches. Two main clusters were formed. T3 was clearly separated

690

from C, whereas T1 and T2 were grouped in a common cluster.

691

Figure 5. Distribution of differential proteins identified between C and T3 according to their

692

subcellular localisation.

693

Figure 6. GO functional categories of up-regulated or down-regulated differential abundances

694

proteins from C to T3 based on label-free analysis

695

Figure 7. Overlaps in ranks of proteins between C1 and T3. (A) Correlation between C1 and

696

T3 proteins based on concentration of 115 proteins; (B) Abundance of 115 differentially expressed

697

proteins; (C) Rank of top 30 abundant proteins.

698

Figure 8. Pie chart showing differentially expressed proteins involved in immune response

699

between C and T3. (A) Up-regulated proteins in T3; (B) Down-regulated proteins in T3.

700

Figure 9. Predicted interactions of identified differentially expressed proteins.

AC C

EP

TE D

M AN U

SC

RI PT

679

32

ACCEPTED MANUSCRIPT This image is the evident view. Different line colours represent types of evidence for association. Protein

702

abbreviations and corresponding full name are shown: glutathione reduced (glutathione re.), maleylacetoacetic

703

acid (maleylacet.tic), glutathione transferase zeta 1 isoform 1 (zgc:92869), adenosine triphosphate (adenosine trip.),

704

homogentisate 1,2-dioxygenase (hgd), acetoacetic acid (acetoacetate), homogentisic acid (homogentisic a.),

705

fumarylacetoacetate hydrolase (FAH), IL-1 (il1b), nuclear factor of kappa light polypeptide gene enhancer in B-

706

cells 2 (nfkb2), v-rel reticuloendotheliosis viral oncogene homolog A (rela) and myeloid differentiation primary

707

response gene 88 (myd88).

708

Figure 10. Number of interactive network of protein co-expression.

M AN U

SC

RI PT

701

709 710 711

715 716 717 718 719

EP

714

AC C

713

TE D

712

720 721 722

33

ACCEPTED MANUSCRIPT Figure 1.

725 726 727 728

AC C

724

EP

TE D

M AN U

SC

RI PT

723

729 730 731

34

ACCEPTED MANUSCRIPT Figure 2.

M AN U

SC

RI PT

732

736 737 738 739 740

EP

735

AC C

734

TE D

733

741 742 743 744 35

ACCEPTED MANUSCRIPT Figure 3.

M AN U

SC

RI PT

745

749 750 751 752 753

EP

748

AC C

747

TE D

746

754 755 756

36

ACCEPTED MANUSCRIPT Figure 4.

759 760 761

AC C

758

EP

TE D

M AN U

SC

RI PT

757

762 763 764 765 37

ACCEPTED MANUSCRIPT Figure 5.

M AN U

SC

RI PT

766

770 771 772 773 774

EP

769

AC C

768

TE D

767

775 776 777 778 38

ACCEPTED MANUSCRIPT Figure 6.

781 782 783

AC C

780

EP

TE D

M AN U

SC

RI PT

779

784 785 786

39

ACCEPTED MANUSCRIPT Figure 7.

M AN U

SC

RI PT

787

791 792 793 794 795

EP

790

AC C

789

TE D

788

796 797 798 799 40

ACCEPTED MANUSCRIPT Figure 8.

801 802 803

AC C

EP

TE D

M AN U

SC

RI PT

800

804 805 806 807 41

ACCEPTED MANUSCRIPT Figure 9.

811 812 813

EP

810

AC C

809

TE D

M AN U

SC

RI PT

808

814 815 816 817 42

ACCEPTED MANUSCRIPT Figure 10.

M AN U

SC

RI PT

818

819

823 824 825 826 827

EP

822

AC C

821

TE D

820

828 829 830 831 43

ACCEPTED MANUSCRIPT Table 1 GO enrichment analysis table for profile 6

SP://W6IDT6

72

SP://Q90332

73

SP://Q90333

106

SP://J7I2B1

67

SP://Q8AWC9

68 59

SP://Q5KQT3 SP://Q09178

74

SP://A6P7L9

70

SP://A0A059T1 N8 SP://Q1G1Y6

PROTEIN NAME Rhesus blood groupassociated glycoprotein C Fast skeletal myosin light chain 1b Fast skeletal myosin light chain 3 Tumour necrosis factor (TNF)-α4 TNF-α1 Odorant receptor 5 Tyrosine protein kinase JAK1 Vitellogenin B1

840 841

0.00 0.00

9137.90 8630.39

27775.02 −7846.95

0.00

686409.05

−8189559 −213244.4 1 10272.91

−452748.0 4 −478369.3 5 −26045.15

0.00

76943.10

TE D EP

839

54308.01

Glutathione-S -transferase

AC C

838

842 843 844 845 44

−645846.6 5 −20792.83

420.78

886143.25

835

T3 −196467.3 5 −65570.86

−100463.8 8 −4535112 −31589.11

0.00

834

837

0.00

MHC class II alpha chain

833

836

Ratio of relative amount C T1 T2 0.00 −323606.3 28288.66 7 0.00 −116246.3 9030.08 0 0.00 −954917.6 −161864.7 6 8 0.00 −33305.48 829.05

SC

62

PROTEIN ID

RI PT

Protein NO 77

M AN U

832

ACCEPTED MANUSCRIPT Table 2 GO enrichment analysis table for profile 3 PROTEIN ID SP://A8HDP2 SP://M9V119 SP://O42321

88

SP://J7FI95

85

SP://J7FIE7

99

SP://Q789E7

96

SP://Q4AE64

101 98

SP://Q7T049 SP://Q38I40

CD8 alpha 2 Sox10 protein D4A Dopamine receptor MHC class II beta chain MHC class II beta chain Myosin heavy chain Myosin heavy chain Nucleolin RNA_dependent RNA polymerase

847 848 849

854 855 856 857

−11709.70

−6418.55

−14822.40

0.00

−40829.43

−21487.94

−35319.21

0.00

−109668

−69555.22

−141991

0.00

−125400

−35673.76

−103342

0.00 0.00

−319240 −36163.90

EP

853

0.00

AC C

852

T3 −206238 −54822.40 −66186.33

TE D

850 851

Ratio of relative amount C T1 T2 0.00 −212044 −80037.69 0.00 −49370.02 −35049.09 0.00 −83837.85 −45169.68

−127137.02 −12448.24

M AN U

93 103 81

PROTEIN NAME

RI PT

NO

SC

846

858 859 860

45

−321975 −30495.56

ACCEPTED MANUSCRIPT Table 3. Protein abbreviations and corresponding full name

861

Input:

SC

interleukin 1, beta (197 aa) growth hormone releasing hormone receptor (432 aa) ENSDARG00000076692 Novel protein similar to MHC class II alpha chain Fragment (133 aa) zgc:92869 glutathione transferase zeta 1 isoform 1 (216 aa) LOC794635 complement C4-2-like (1717 aa) (Danio rerio) Predicted Functional Partners:

hgd homogentisic a. myd88

863

AC C

862

EP

acetoacetate adenosine trip.

TE D

maleylacet.tic. nfkb2

rela

glutathione reduced fumarylacetoacetate hydrolase (fumarylacetoacetase) (297 aa) homogentisate 1,2-dioxygenase • (443 aa) homogentisic acid myeloid differentiation primary response gene 88 (284 aa) maleylacetoacetic acid nuclear factor of kappa light polypeptide gene enhancer in B-cells 2, (896 aa) v-rel reticuloendotheliosis viral oncogene homolog A (453 aa) Acetoacetic acid adenosine triphosphate

M AN U

glutathione re. FAH

RI PT

il1b ghrhr

46

• •

•

• •

• •

• • • • • • • •

•

• •

•

• • • • • •

0.991 0.988 0.984 0.981 0.976 0.972 0.971

0.970 0.968 0.968

ACCEPTED MANUSCRIPT 1. A total of 1149 proteins were identified in the samples. 2. The distance between C and T3 was the maxima by hierarchical cluster analysis. 3. There were 52 up-regulated proteins, and 63 proteins with down-regulation in T3.

RI PT

4. 46 proteins of differential abundance (40% of 115) were involved in immunity.

AC C

EP

TE D

M AN U

SC

5. In 46 proteins, 17 up-regulated and 29 down-regulated proteins were detected in T3