Isobaric Tags for Relative and Absolute Quantification (iTRAQ)-Based

Subscriber access provided by Universitaetsbibliothek | Johann Christian Senckenberg

Article

iTRAQ-based untargeted quantitative proteomic approach to identify change of the plasma proteins by salbutamol abuse in beef cattle Kai Zhang, Chaohua Tang, Xiaowei Liang, Qingyu Zhao, and Junmin Zhang J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b04397 • Publication Date (Web): 14 Dec 2017 Downloaded from http://pubs.acs.org on December 15, 2017

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Journal of Agricultural and Food Chemistry is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 34

Journal of Agricultural and Food Chemistry

iTRAQ-based untargeted quantitative proteomic approach to identify change of the plasma proteins by salbutamol abuse in beef cattle Kai Zhang,†,‡ Chaohua Tang,†,‡ Xiaowei Liang,†,‡ Qingyu Zhao,†,‡ Junmin Zhang†,‡,* †

State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese

Academy of Agricultural Sciences, Beijing 100193, China ‡

Scientific Observing and Experiment Station of Animal Genetic Resources and

Nutrition in North China, Ministry of Agriculture, Beijing 100125, China *

Corresponding author, E-mail: [email protected]; Fax: 86-10-62815537; Tel:

86-10-62815852.

1

ACS Paragon Plus Environment


1

ABSTRACT

2

Salbutamol, a selective β2-agonist, endangers the safety of animal products because of

3

illegal use in food animals. In this study, an iTRAQ-based untargeted quantitative

4

proteomic approach was applied to screen potential protein biomarkers in plasma of

5

cattle before and after treatment with salbutamol for 21 days. A total of 62 plasma

6

proteins were significantly affected by salbutamol treatment, which can be used as

7

potential biomarkers to screen for the illegal use of salbutamol in beef cattle.

8

Enzyme-linked immunosorbent assay measurements of five selected proteins

9

demonstrated the reliability of iTRAQ-based proteomics in screening of candidate

10

biomarkers among the plasma proteins. The plasma samples collected before and after

11

salbutamol treatment were well separated by principal complement analysis (PCA)

12

using the differentially expressed proteins. These results suggested that an

13

iTRAQ-based untargeted quantitative proteomic strategy combined with PCA pattern

14

recognition methods can discriminate differences in plasma protein profiles collected

15

before and after salbutamol treatment.

16

KEYWORDS: salbutamol, cattle, plasma, iTRAQ proteome, biomarkers, PCA

2


Page 2 of 34

Page 3 of 34


17

INTRODUCTION

18

β2-Agonists, are traditionally used for therapeutic purposes in humans and as well as

19

bronchodilator and tocolytic agents in veterinary medicine,1,2 but are also illegally used

20

for anabolic purposes to improve animal growth and feed efficiency by reducing fat

21

deposition and increasing protein synthesis and carcass leanness.3,4 Because the residues

22

of these compounds in animal tissues could pose potential hazards to human health,5–7

23

China,8 the European Union,9 and most other countries have prohibited the use of

24

β2-agonists as growth promoters in animal husbandry. However, β2-agonists, like

25

salbutamol, are repeatedly discovered during routine control by national authorities.10

26

To ensure the safety of animal products and monitor illegal usage, many rapid and

27

sensitive analytical methods have been developed for analysis of β2-agonist residues in

28

various food matrices. These methods, such as enzyme immunoassays and gas or liquid

29

chromatography (LC) coupled to mass spectrometry (MS),11–14 are all based on existing

30

drugs for the detection of residues in animal tissues. To escape from residue detection

31

during routine control, β2-agonists like salbutamol are eliminated rapidly and usually

32

below the limit of detection within several days.15 Several unknown β2-agonist

33

analogues used illicitly as growth promoters in animal production have been

34

discovered.16–18 In addition, the use of low dose “cocktails” that exert a synergetic effect

35

and exhibit similar growth promotion characteristics has been reported in food

36

animals.19 The use of both unknown β2-agonists and low dose “cocktails” render routine

37

screening approaches difficult to implement. In this context, strategies based on the

38

detection of physiological actions of anabolic practices are promising approaches to 3



39

screen for the illegal use of β2-agonist.20 Over the past few years, omics-based

40

technologies, such as transcriptomics, proteomics, and metabolomics, have emerged as

41

untargeted global strategies to highlight candidate-biomarkers to tackle illegal practices.

42

Several reports have described the use of non-targeted metabolomics approaches to

43

screen for the abuse of β2-agonists, like salbutamol, in food animals and athletes.21–24

44

Some papers have described the use of comparative two-dimensional gel electrophoresis

45

(2DE) proteomics to identify plasma proteins as markers of growth promoter abuse in

46

cattle.25,26 However, to the author’s knowledge, the use of proteomics-based strategies to

47

screen for the abuse of β2-agonists, such as salbutamol, in food animal has not been

48

extensively reported except for clenbuterol.27 Isobaric tags for relative and absolute

49

quantification (iTRAQ) is a common labeling strategy in proteomics that has been

50

increasing used in the past few years. iTRAQ-based proteomic technologies have been

51

proposed as more accurate and reliable methods for the quantitation of proteins than

52

traditional 2DE proteomic analysis.28

53

Therefore, an iTRAQ-based untargeted quantitative proteomics approach was applied

54

to plasma samples collected from cattle before and after salbutamol treatment for 21

55

consecutive days to identify differently expressed proteins as potential biomarkers to

56

screen for the abuse of salbutamol in beef cattle.

57

MATERIALS AND METHODS

58

Chemicals and Reagents

59

Salbutamol hydrochloride (95% purity) was provided by the Institute of Quality

60

Standard and Testing Technology for Agro-Products, Chinese Academy of Agricultural 4


Page 4 of 34

Page 5 of 34


61

Sciences (Beijing, China). ProteoMiner Protein Enrichment Kits and Bradford protein

62

assays were purchased from Bio-Rad Laboratories, Inc. (Hercules, CA, USA). The

63

iTRAQ reagent-8 plex one assay kit was purchased from AB Sciex Pte. Ltd. (Foster

64

City, CA, USA). Dithiothreitol and iodoacetamide were obtained from Promega Co.,

65

Ltd. (Madison, WI, USA). Acetone, tetraethylammonium bromide (TEAB), sodium

66

dodecyl sulfate (SDS), trypsin, monobasic potassium phosphate (KH2PO4), phosphoric

67

acid (H2PO4), potassium chloride (KCL), and isopropanol were purchased from

68

Sigma-Aldrich (Schnelldorf, Switzerland). Formic acid and acetonitrile were obtained

69

from Fisher Scientific (Loughborough, UK). All solvents used in this study were

70

analytical grade or higher.

71

Experimental Animals

72

In this experiment, four seven-month-old male Chinese Simmental beef cattle weighting

73

281.11 ± 29.36 kg (mean ± standard error) were housed in a single stall barn for

74

tie-down feeding with ad libitum access to feed and water. The cattle were orally

75

administrated salbutamol at a dose of 0.15 mg/kg body weight/d for 21 consecutive

76

days. Blood samples were collected before and after treatment for 21 days from the

77

jugular vein into heparinized tubes, centrifuged at 1450 × g for 10 min to obtain plasma

78

samples, which were then stored at −80 °C. The study protocol was approved by the

79

Animal Welfare Committee of the Institutes of Animal Science, Chinese Academy of

80

Agricultural Sciences.

81

Sample Preparation

82

Plasma samples were defrosted and centrifuged at 10000 × g for 10 min. Then, 5



83

ProteoMiner™ Protein Enrichment kits (Bio-Rad Laboratories, Inc.) were used to

84

simultaneously dilute high-abundance proteins and concentrate low-abundance proteins,

85

as described by the manufacturer’s instructions, and subsequently, reduced using 10

86

mM dithiothreitol, in a 56 °C water bath for 1 h. Then, iodoacetamide was quickly

87

added to a final concentration of 55 mM, under darkness for 1 h. Afterward, 4 × volume

88

of cold acetone was added and the samples, which were stored at −20 °C for 3 h and

89

then centrifuged at 20000 × g (4 °C) for 20 min. The precipitants were collected, mixed

90

with 300 µL of buffer (50% TEAB and 0.1% SDS), and then sonicated for 3 min.

91

Finally, the total protein concentrations were determined using the Bradford method,

92

according to the manufacturer’s instructions (Bio-Rad Laboratories, Inc.).

93

Digestion and iTRAQ Labeling

94

One hundred micrograms of protein from each plasma sample (consistent volume

95

containing 0.1% SDS of TEAB) were combined with 3.3 µg of trypsin (1 µg/µL) in a

96

37 °C water bath for 24 h. Afterward, 1 µg of trypsin was added to the sample, which

97

was then incubated in a 37 °C water bath for 12 h, freeze-dried in digestion fluid and

98

redissolved in 30 µL of TEAB (water:TEAB, 1:1, by volume). The iTRAQ reagents

99

were allowed to adjust to room temperature, then added to 70 µL of isopropanol and

100

vortexed for 1 min. The resulting peptides were labeled using with iTRAQ reagents for

101

2 h at room temperature. Then, the eight labeled peptides were pooled together. The four

102

plasma samples collected before treatment were labeled with iTRAQ reagents 113, 114,

103

115, and 116, while the four treatment plasma samples were labeled with iTRAQ tags

104

117, 118, 119, and 121, respectively. 6


Page 6 of 34

Page 7 of 34


105

Strong Cationic-Exchange Chromatography Separation

106

The combined peptide mixtures were dried in a Speedvac vacuum concentrator and

107

dissolved in 1 µL of buffer A (10 mM KH2PO4 in 25% acetonitrile). After adjusting the

108

pH to 3.0 with H2PO4, the sample was subjected to strong cationic-exchange

109

chromatography (SCX) using a silica-based column (250 × 4.6 mm, Phenomenex, Inc.,

110

Torrance, CA, USA). A total of 16 fractions were collected with a gradients of buffer B

111

(10 mM KH2PO4 and 2 M KCL in 25% acetonitrile, pH 3.0) as follows: 0% B for 45

112

min, 0–5% B for 1 min, 5%–30% B for 20 min, 30%–50% B for 5 min, 50% B for 5

113

min, 50%–100% B for 5 min, and 100% B for 5 min. The fractions were desalted with a

114

strata-X C18 column (Phenomenex, Inc.).

115

LC-MS/MS Analysis and Protein Quantification

116

For chromatographic separation, a Dionex ultimate 3000 NanoLC system (Dionex,

117

Sunnyvale, CA, USA) was used. Separation was carried out on a reversed phase C18

118

column (100 × 75 mm, 5 µm, 300 Å, Agent Technologies, Santa Clara, CA, USA).

119

Solvent A was composed of 0.1% formic acid in water and solvent B was composed of

120

0.1% formic acid in acetonitrile. Peptides were eluted at a flow rate of 400 nL/min with

121

the flowing gradient conditions: 5% B for 10 min, 5%–30% B for 30 min, 30%–60% B

122

for 5 min, 60%–80% B for 3 min, 80% B for 7 min, 80%–5% B for 3 min, and 5% B for

123

7 min. The elutants were directly subjected to Q-Exactive MS (Thermo Fisher Scientific,

124

Waltham, MA, USA), setting in positive ion mode and data-dependent manner with full

125

MS scan range from 350 to 2000 Da, full scan resolution of 70000, MS/MS scan

126

resolution of 17500, capillary temperature of 320 °C, ion source voltage of 1800 V, 7



127

MS/MS scan with minimum signal threshold of IE+5, and an isolation width of 2 Da.

128

To evaluate the performance of this MS on the iTRAQ-labeled samples, two MS/MS

129

acquisition models, and higher collision energy dissociation were employed.

130

Protein Identification and Quantification

131

For protein identification, the raw files were processed using Proteome Discover 1.3

132

software (Thermo Fisher Scientific) and searched with Mascot 2.3.0 (Matrix Science,

133

London, UK) against the bovine genome with an in-house Uniprot database (02-2016,

134

32352 entries). Carbamidomethyl (C) was set as a fixed modification, while oxidation

135

(M), Gln→Pyro-Glu (N-term Q), iTRAQ 8 plex (K), iTRAQ 8 plex (Y), and iTRAQ 8

136

plex (N-term) were set as variable modifications. The peptide tolerance was set to 15

137

ppm, and the MS/MS tolerance was set to 20 mmu. Trypsin was selected as the enzyme

138

and up to one missed cleavage was allowed. All reported data were based on 99%

139

confidence for identification of proteins and peptides as determined by a false discovery

140

rate of ≤ 1%. Each confident protein identification involved at least one unique peptide.

141

The quantitative protein ratios were weighted and normalized by the median ratio in

142

Mascot. Only protein identification that was inferred from the unique peptide

143

identification in all four biological replicates was included for subsequent analysis.

144

Statistical analysis was performed using a one-way analysis of variance. A probability

145

(P) value of < 0.05 and fold change > 1.2 or < 0.83 (as previous study defined)29 were

146

considered to indicate a differentially expressed protein.

147

Enzyme-linked Immunosorbent Assay (ELISA) Validation

148

To confirm the iTRAQ-based proteomic results, concentrations of five selected proteins 8


Page 8 of 34

Page 9 of 34


149

in each cattle plasma sample were measured using a bovine ELISA kit (Nanjing

150

Jiancheng Bioengineering Institute Co., Ltd., Nanjing, China), according to the

151

manufacturer's instruction, respectively. Briefly, 50 µL of a diluted standard or plasma

152

sample was added into the wells of 96-well plates, which were combined with 50 µL of

153

biotinylated working solution and incubated at 37 °C for 60 min. Then, the plates were

154

washed five times with washing solution. Afterward, 50 µL of horseradish peroxidase

155

working solution were added to each well and the plate was incubated at 37 °C for 60

156

min. After repeating the plate-washing procedure, 50 µL of chromogenic solutions A

157

and B were added to each well and then plate was incubated at 37 °C for 10 min away

158

from light. Afterward, 50 µL of stop solution were added to each well and the optical

159

density at a wavelength of 450 nm was measured using the Infinite M200 Microplate

160

Reader (Tecan Group Ltd., Männedorf, Switzerland).

161

Data Analysis

162

Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG)

163

functional analyses of differentially abundant proteins were performed using the

164

DAVID online software tool (https://david.ncifcrf.gov/summary.jsp). The GO project

165

categorized all of the differentially expressed proteins into three groups: cellular

166

components, molecular functions, and biological processes. Significant GO terms and

167

pathways with P < 0.05 are presented. The identified differentially expressed proteins

168

were analyzed using the PCA program included with the SIMCA 13.0 software package

169

(MKS Umetrics AB, Umea, Sweden). Statistical analysis was performed using IBM

170

SPSS Statistics for windows, version 20.0 (IBM-SPSS, Inc., Chicago, IL, USA). The 9



171

Student's t-test was employed to identify significant differences in protein

172

concentrations before and after salbutamol treatment. A P-value < 0.05 was considered

173

statistically significant.

174

RESULTS

175

Identified Proteins and Function Analysis

176

The workflow of the iTRAQ-based proteomic approach for comparison of the cattle

177

plasma proteome before and after salbutamol treatment is shown in Figure 1. In total,

178

472 proteins were identified from Chinese Simmental beef cattle before and after

179

salbutamol treatment for 21 consecutive days (Supporting Information, Table S1). Of

180

these, 441 of the identified proteins were quantified by the iTRAQ-based proteomic

181

approach and each group included four biological replicates (Supporting Information,

182

Table S2). The labelling efficiency based on peptide was 98%. Statistical analysis of the

183

coefficient of variation of the four biological in this work was below 20%. A total of 62

184

significant differentially expressed proteins were detected by the analysis of variance

185

test (P < 0.05) and conformed to a fold change of >1.2 or

Isobaric Tags for Relative and Absolute Quantification (iTRAQ)-Based

Recommend Documents