Proteome Science

, 16:8 | Cite as

ITRAQ-based quantitative proteomic analysis of processed Euphorbia lathyris L. for reducing the intestinal toxicity

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Research
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Abstract

Background

Euphorbia lathyris L., a Traditional Chinese medicine (TCM), is commonly used for the treatment of hydropsy, ascites, constipation, amenorrhea, and scabies. Semen Euphorbiae Pulveratum, which is another type of Euphorbia lathyris that is commonly used in TCM practice and is obtained by removing the oil from the seed that is called paozhi, has been known to ease diarrhea. Whereas, the mechanisms of reducing intestinal toxicity have not been clearly investigated yet.

Methods

In this study, the isobaric tags for relative and absolute quantitation (iTRAQ) in combination with the liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomic method was applied to investigate the effects of Euphorbia lathyris L. on the protein expression involved in intestinal metabolism, in order to illustrate the potential attenuated mechanism of Euphorbia lathyris L. processing. Differentially expressed proteins (DEPs) in the intestine after treated with Semen Euphorbiae (SE), Semen Euphorbiae Pulveratum (SEP) and Euphorbiae Factor 1 (EFL1) were identified. The bioinformatics analysis including GO analysis, pathway analysis, and network analysis were done to analyze the key metabolic pathways underlying the attenuation mechanism through protein network in diarrhea. Western blot were performed to validate selected protein and the related pathways.

Results

A number of differentially expressed proteins that may be associated with intestinal inflammation were identified. They mainly constituted by part of the cell. The expression sites of them located within cells and organelles. G protein and Eph/Ephrin signal pathway were controlled jointly by SEP and SE. After processing, the extraction of SEP were mainly reflected in the process of cytoskeleton, glycolysis and gluconeogenesis.

Conclusions

These findings suggest that SE induced an inflammatory response, and activated the Interleukin signaling pathway, such as the Ang/Tie 2 and JAK2/ STAT signaling pathways, which may eventually contribute to injury result from intestinal inflammatory, while SEP could alleviate this injury by down-regulating STAT1 and activating Ang-4 that might reduce the inflammatory response. Our results demonstrated the importance of Ang-4 and STAT1 expression, which are the target proteins in the attenuated of SE after processing based on proteomic investigation. Thus iTRAQ might be a novel candidate method to study scientific connotation of hypothesis that the attenuated of SE after processing expressed lower toxicity from cellular levels.

Keywords

Euphorbia lathyris Proteomics iTRAQ Bio-pathway 

Abbreviations

2D-LC-MS/MS

Two-dimensional liquid chromatography-tandem mass spectrometry

ACN

Acetonitrile

Ang

Angiopoietin

CIITA

TypeIItranscription activator

DEPs

Differentially expressed proteins

DTT

Dithiothreitol

EFL1

Euphorbiae Factor 1

EGF

Epidermal growth factor

Eph/Ephrin

Erythropoientin-producing hepatocyte kinases/Eph receptor interacting proteins

GO

Gene ontology

IFN

Interferon

IgG

Immunoglobulin G

IL-6

Interleukin-6

iTRAQ

Isobaric tags for relative and absolute quantitation

JAK2

Janus Kinase 2

LC

Liquid chromatography

NF-κB

Nuclear factor kappa B

PDGF

Platelet-derived growth factor

PSMs

Peptide-spectrum matches

PVDF

Polyvinylidene fluoride

SDS-PAGE

Sodium dodecyl sulfate polyacrylamide gel electrophoresis

SE

Semen Euphorbiae

SEP

Semen Euphorbiae Pulveratum

STAT1

Signal transducers and activators of transcription one

TCM

Traditional Chinese medicine

TNF

Tumor necrosis factor

Background

Euphorbia lathyris L. is an effective but toxic traditional Chinese medicine (TCM) derived from the family of euphorbiaceae. It can expel water retention with drastic purgative effects, namely, breaking up the static blood and eliminating masses and is often used for the treatment of hydropsy, ascites, anuresis and constipation, amenorrhea, scabies [1, 2]. It shows several side effects such as irritation and inflammation intense on the skin, mouth and gastrointestinal tract irritation, carcinogenic, and so on. The gastrointestinal mucosa irritation mainly manifested as serious diarrhea. Traditionally, Semen Euphorbiae Pulveratum (SEP), which is another type of Euphorbia lathyris L., is commonly used in TCM practice and is obtained by removing the oil from the seed which is called paozhi. After processing, the toxicity and the capacity of diarrhea was decreased obviously [3]. Interestingly, considerable research efforts have been devoted to the studies on the effect of SEP and SE on diarrhea. Whereas, the intestine protein changes related to intestinal toxicity and the main mechanisms of reducing toxicity by processing of SE remain poorly understood.

With the improvement of two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and mass spectrometry [4], considerable research efforts have been devoted to the application of proteomics to find possible involved signals in toxic injure induced by some toxins or to determine the modes of action and mechanisms involved in drug- or chemical-induced toxicity [5, 6]. The isobaric tags for relative and absolute quantitation (iTRAQ) technique is one of the most widely used, innovative and common quantitative proteomics approaches that measure the qualitative and quantitative changes in protein content of a cell or tissue in response to treatment or disease and determine protein-protein and protein-ligand interactions [7]. It can simultaneously analyze 4–8 different specimens, thus increasing throughput while reducing experimental error [8, 9]. iTRAQ labeling coupled with LC-MS/MS is sensitive, automated, and multidimensional and can detect large molecules (> 20 kDa) [10]. ITRAQ is suitable for exploratory studies of the processing mechanisms.

In our study, we applied iTRAQ approach to processing for Euphorbia lathyris-induced intestinal toxicity and to identify candidate biomarkers for main mechanisms underlying processing of SE. Bioinformatics analysis including GO analysis, pathway analysis, and network analysis were done to find possible differential pathways. Additionally, the investigation suggested that Euphorbiae factor 1(EFL1), isolated from Euphorbia lathyris, is the main and active diterpenoids which might mediate diarrhea [11]. We also demonstrated EFL1 group to further compare the DEPs induced by SE and SEP. Finally, western blot analysis was applied further to identify candidate biomarkers, and to confirm and validate significance of the proteomic findings. These results provided a first insight into scientific connotation of hypothesis that the attenuated of SE after processing expressed lower toxicity from cellular levels in mice model and described an efficient method for mechanisms of toxic TCM processing.

Methods

Samples

Experimental animals

KM mice (SPF grade, 18–22 g) were purchased from Sibeifu Co., Ltd. (Beijing, China). All experiments were approved by the Animal Care Committee. Mice were kept at room temperature (23 ± 1 °C) and 55 ± 5% humidity. All experiments were conducted in accordance with the Guiding Principles for the Care and Use of Laboratory Animal, as adopted by the Committee on Animal Research at Beijing University of Chinese Medicine.

Extracts preparations of semen euphorbiae and semen euphorbiae Pulveratum

Pieces of Euphorbiae Semen (batch number, 1203070692; origin, Jiangxi province, China) were purchased from Anhui Bozhou HuQiao Chinese Herbal Pieces plant. Petroleum ether extract of Semen Euphorbiae, petroleum ether extract of Semen Euphorbiae Pulveratum was provided by Shandong University of Traditional Chinese Medicine. The extraction and isolation methods of Semen Euphorbiae had been published in these articles [12, 13]. Euphorbiae factor 1 was isolated from the petroleum ether extracts of semen Euphorbia by our team [13, 14].

Proteomics extraction procedures

Protein preparation

After 12 h of fasting, KM mice were randomly divided into 4 groups (n = 10 for each group): the group 1 was served as a control, and received only blank 1% sodium carboxymethyl cellulose solution; meanwhile group 2 was the extracts of SE and group 3 was the extraction of SEP, in which the mice were orally administered at the dose of 1.5 ml/20 g and 1.0 ml/20 g, respectively, with the same amount of crude drug. In order to validate the results induced by SE and SEP, group 4 was administered 20 mg/20 g Euphorbiae factor 1(EFL1) to further verify the protein networks. Mice then received standard diet and water ad libitum. 6 h later, mice were sacrificed, from which the colon were obtained and frozen in liquid nitrogen immediately until they were used for analysis.

Protein isolation

The colon tissue samples were ground into powder in liquid nitrogen, extracted with Lysis buffer (7 M urea (Bio-Rad, 161–0731), 2 M Thiourea (Sigma-Aldrich, T7875), 4% CHAPS (Bio-Rad, 161–0460)) containing complete protease inhibitor Cocktai (Roche, 04693116001). The cell was lysed by sonication at 200 W for 60s and then extracted 30 min at room temperature, centrifuged at 4 °C, 15000 g for 20 min. Before the protein processing, each 5 individual protein samples were mixed equally into 1 specimen. As a result of the strategy, each group contained 2 sample pools, and these sample pools were enrolled to be conducted in subsequent experiments.

Bradford analysis

Total protein concentration of the samples was determined using a Bradford Assay [15]. Standards of BSA were prepared and all samples and standards were analyzed in duplicate. Protein concentrations and standards of BSA were determined at 595 nm on an Multiskan MK3 UV–vis spectrophotometer (Thermo, U.S.) with 10 μL sample reacted with 300 μL Thermo Scientific Pierce Coomassie Plus Bradford Assay (Part No. 23238) 20 min.

Protein reduction, alkylation, and digestion

Filter-aided sample preparation (FASP) method was used to digest protein based on Jacek R Wis’niewski et al. [16]. The 200 μg calculated protein samples were added to centrifuge tube and 25 mM DTT was added and the samples were incubated at 60 °C for 1 h. Samples were incubated for 10 min in the dark after adding 50 mM IAA at room temperature and then centrifuged at 12,000 rpm for 20 min using Ultrafiltration centrifugal tube(NWCO:10 K). 100 μL Dissolution Buffer(iTRAQ ® Kit Dissolution Buffer, AB Sciex, USA, PN:4381664) was added to the filter and centrifuged at 12,000 rpm for 20 min. This step was repeated three times.50 μL trypsin, totally 4 μg, was added and samples were incubated at 37 °C overnight. After trypsin digestion, samples were centrifuged at 12,000 rpm for 20 min, the digested peptides were collected at the bottom of the tube and mixed with 50 μL Dissolution Buffer. Finally 100 μL samples were obtained.

iTRAQ labeling

Each iTRAQ reagent tube (tags-113-121) had 150 μl isopropanol added and vortexed thoroughly, then centrifuged. 50 μl samples (equal to 100 μg digested peptides) were transferred to new tubs and processed according to the manufacturer’s protocol for 8-plex iTRAQ reagent (AB Sciex, PN:4390812) by incubation at RT for 2 h with gentle shaking. The labeled peptide mixtures were then pooled and dried by vacuum centrifugation. Samples were labeled respectively with different isobaric tags as follow: EFL1 samples labeled 113 and 114, control samples labeled 115 and 116, and extraction of SE samples labeled 117 and 118, extraction of SEP samples labeled 119 and 121. The peptides were labeled with the isobaric tags, incubated at room temperature for 2 h. The labeled peptide mixtures were then pooled and dried by vacuum centrifugation.

iTRAQ-labeled peptide fractionation and proteomic analysis by LC-MS/MS

The iTRAQ-labeled peptide mixtures were re-suspended in buffer A (2% ACN, pH 10) and centrifuged at 14,000 g for 20 min. High pH reversed-phase chromatography was performed to separate the trypsin digestion peptide. The supernatant was loaded onto a 4.6 × 250 mm Durashell-C18 containing 5-μm particles. The peptides were eluted at a flow rate of 0.7 mL/min with a 51-min gradient:0-10 min,5.0% B (Mobile phaseA:2%ACN,98%ddH2O,pH 10;Mobile phaseB:98%ACN,2%ddH2O,pH 10);10–13.4 min,5%-8.%B;13.4–31.7 min,8.5%–20.5%B;31.7-41 min,20.5%–31.0%B; 41-46 min,31%–90%B;46-47 min,90.0–95.0%B;47-48 min, 95%–5%B;48-51 min,5%B. The eluted peptides were obtained 40 fractions and finally pooled into 10 fractions through Peak shape.

Then the fraction was re-suspended in 20 μL buffer A (2% ACN, 0.1% FA)and centrifuged at 12,000 rpm for 10 min and 10 μL supernatant was loaded onto a 12 cm × 75 μm EASY-Spray column (C18,3 μm). The samples were loaded at 300 nL/min with mobile phase A: 100% dd H2O/0.1% Formic acid; mobile phase B: 100% ACN/0.1%FA. The gradient as follows:0-13 min,5–8%B;13-90 min,8030%B;90-100 min,30–50%B;100-105 min,50–95%B;105-115 min,95%B;115-116 min,95–5%B;116-126 min,5%B.

The peptides were subjected to Nano-electrospray ionization followed by mass spectrometry (MS/MS) using a Q-Exactive mass spectrometer (Thermo Scientific) coupled with an online micro flow HPLC system. Key parameter settings for the Thermo Q-Exactive mass spectrometer were as follows:

spray voltage floating (ISVF) 2.3KV, Capillary Temperature:320 °C, Ion source: EASY-Spray source, declustering potential (DP) 100 V.

Full MS:Resolution:70000FWHM;Full Scan AGC target:3e6;Full Scan Max.IT:20 ms;Scan range:300-1800 m/z;

dd-MS2:Resolution:17500 FWHM;AGC target:1e5;Maximum IT:120 ms;Intensity threshold:8.30E + 03;Fragmentation Methods:HCD;NCE:32%;Top N:20.

Bioinformatics analysis

Annotations of identified proteins were done with GO for biological processes, molecular functions and cellular component. The analysis were carried out using the Database for Annotation Visualization and Integrated Discovery. Tagged samples were normalized by comparing median protein ratios for the reference channel. Protein quantitative ratios were calculated from the median of all peptide ratios. The proteins with a relative expression of > 1.32 or < 0.68, and with a P-value < 0.05 selected as statistically significance to ensure up- and downregulation authenticity. The selection parameter was based on the overrepresented GO terms with gene enrichment analysis of p < 0.05. The protein lists were further analyzed by UniProt database (http://www.uniprot.org/uniprot/?query=taxonomy:10090) which gave all canonical pathways, interactions, and network construction with significant enrichment of the input proteins based on data from the UniProt Database, Biocarta, etc. [17]

Western blot analysis

Western blot analysis were performed to confirm the presence of differentially expressed proteins. Colons from mouse were washed with ice-cold saline and triturated under Liquid Nitrogen. 200 mg powder were lysed in 1.5 ml RIPA buffer and incubated on ice for 60 min, sonicated for 60s, followed by centrifugation at 12,000×g for 15 min at 4 °C. The total protein concentration was measured using the BCA protein assay kit (Applygen Technologies Inc. Beijing, China). The supernatant lysates were diluted in 5× SDS sample buffer and boiled for 5–10 min.

Proteins from individual samples were separated on SDS-PAGE gels and transferred electrophoretically onto PVDF membranes (Millipore, Billerica, MA, USA). The membranes were blocked for 2 h at room temperature with 3% non-fat dried milk in Tris-buffered saline (TBST, 20 mM Tris-HCl, 137 mM NaCl, and 0.1% Tween 20, pH 7.6). Then, the membranes were incubated overnight at 4 °C in a primary antibody against Anti-STAT1 antibody(Abcam, USA), Rabbit Anti-Angiopoietin 4(Beijing Biosynthesis Biotechnology Co., Ltd.,China), Rabbit and Mouse Anti-β-actin(ZS-Bio. Co., Ltd. Beijing, China). The membranes were then washed with TTBS three times and incubated with horseradish peroxidase-conjugated secondary antibodies (ZS-Bio. Co., Ltd. Beijing, China), Peroxidase-Conjugated Goat anti-Mouse IgG (H + L) (ZB-2305) and Peroxidase-Conjugated Goat anti-Rabbit IgG (H + L) (ZB-2301).Proteins were detected using an enhanced chemiluminescence (ECL) method (Super ECL plus Detection Reagent, Applygen Technologies Inc.P1010). Protein bands were imaged using a ChemiScope 3300 Mini bio-imaging system (Clinx Science Instruments Co., Ltd. (CSI), Shanghai, China). Bands were normalized with β- actin as an internal control. Protein expressions were quantified by chemi analysis and Ang4 and STAT1 were normalized to the beta-actin of each sample. These experiments were each conducted five times.

Results and discussion

Protein profiling

MS raw data files were converted into MGF files using Proteome Discoverer 1.4 (PD 1.4, Thermo), and the MGF data files were searched by using the Mascot search engine (Matrix Science, London, UK; version 2.3.02) to identify proteins. Each confident protein identification involves at least one unique peptide. For protein quantification, it was required that a protein contained at least two unique spectra. The quantitative protein ratios were weighted and normalized by the median ratio in Mascot. As shown in Fig. 1, a total of 393,357 MS/MS spectra which are the secondary mass spectrums were identified by iTRAQ-coupled 2D LC-MS/MS analysis in mice intestine tissues. Among them, 123,136 peptide spectrum-match (PSM) were found. In addition, the LC-MS/MS analysis employed here resulted in identification of 50,007 total peptides with 6727 identified protein groups.
Fig. 1

Basic information statistics of proteome by iTRAQ. MS/MS spectra are the secondary mass spectrums, and PSMs are the secondary mass spectrums after quality control. Protein is identified by Proteome Discoverer 1.4 software

Identification of differentially expressed proteins using iTRAQ labeling and LC-MS/MS

Through analysis with software, data were processed using the Proteome Discoverer Software 4.0 utilizing the Mascot (Matrix Science,London, U.K.; version 2.3.0) Algorithm. In this algorithm, Parameters set for the searching were iTRAQ eight plex peptide-labeled, trypsin digestion with only two maximum miss cleavage, carboxymate for cysteine residue and oxidation for methionine. The tolerances were specified as ±15 ppm for peptides and ± 20 mmu for MS/MS fragments. The mice protein database was downloaded from UniProt. The false discovery rate (FDR) was controlled at the 1% level. Distributional normality and homogeneity of variance were tested for numerical data. Values were given as mean ± SD. To reduce probability of false peptide identification, only peptides with a fold change cut-off ratio of > 1.32 or < 0.68 and ones with p-values smaller than 0.05 in the analysis (where P-value < 0.05 indicates > 95% confidence of a change in protein concentration irrespective of the magnitude of the change) was selected to designate differentially expressed proteins. The similar experimental design was described in previous study [18, 19, 20]. Among them, proteins that displayed significantly altered expression levels comparing with the control group were considered as up-regulated or down-regulated differentially expressed proteins (DEPs), respectively. With this filter, we identified 103 DEPs in EFL1 group, including 82 up-regulated proteins and 21 down-regulated proteins. Besides, regarding to 70 DEPs from SE-treated group compared to control group, 47 proteins were up-regulated, and 23 proteins were down-regulated. Moreover, there were 96 up-regulated proteins and 26 down-regulated proteins, totaling 122 proteins in the SEP-treated groups were identified relative to control. Further analysis indicated that the three test groups shared 7 DEPs in the colon tissues of mice after intersection, of which, 5 proteins were down-regulated and 2 proteins up-regulated (Table 1). Meanwhile, there were 295 differentially expressed proteins in the colon tissues of mice in union of DEPs of SE and SEP, EFL1, of which, 70 proteins were down-regulated and 225 proteins up-regulated (Table 2). These proteins were subjected to gene-ontology enrichment.
Table 1

Related information of differentially expressed protein (DEPs) by iTRAQ analysis after intersection

Acc no. (NCBI)

Prot names

Gene names

Control

SE

SEP

EFL1

Down-regulated proteins

Q3TMQ6

Angiogenin-4

Ang4

1

0.5795

0.6082

0.549

Q62010

Oviduct-specific glycoprotein

Ovgp1

1

0.4252

0.5825

0.451

Q80ZA0

Intelectin-1b (Intelectin-2)

Itln1b

1

0.4847

0.6715

0.498

Q8R1M8

Mucosal pentraxin

Mptx1

1

0.5352

0.5652

0.559

V9GXU2

C2 domain-containing protein 3

C2cd3

1

0.5372

0.636

0.463

Up-regulated proteins

F6R782

IQ domain-containing protein E

Iqce

1

3.496

4.4437

4.691

Q9D1X0

Nucleolar protein 3 (Apoptosis repressor with CARD)

Nol3 Arc

1

1.3665

1.5167

1.345

Acc no Accession number, Prot name Protein name, SE Semen Euphorbiae, SEP Semen Euphorbiae Pulveratum, EFL 1 Euphorbiae Factor 1

Table 2

Summary table showing significantly up-regulated or down-regulated proteins identified by iTRAQ Analysis after combine together

Acc no.(NCBI)

Pro names

Gene names

Control

SE

EFL1

SEP

Up-regulated

Q62010

Oviduct-specific glycoprotein

Ovgp1 Chit5 Ogp

1

0.4252

0.451

0.5825

A2BDX4

Potassium voltage-gated channel subfamily G member 1

Kcng1

1

0.4347

0.856

0.6645

P97816

Protein S100-G

S100 g Calb3 S100d

1

0.4485

0.599

0.653

Q8BV14

Ankyrin repeat domain-containing protein 55

Ankrd55

1

0.4652

0.636

/

Q80ZA0

Intelectin-1b (Intelectin-2)

Itln1b Itln2 Itlnb

1

0.4847

0.498

0.6715

Q8R1M8

Mucosal pentraxin

Mptx1 Mptx

1

0.5352

0.559

0.5652

V9GXU2

C2 domain-containing protein 3

C2cd3

1

0.5372

0.463

0.636

P07146

Anionic trypsin-2

Prss2 Try2

1

0.5465

0.776

0.5967

D6RFD6

Protein RFT1 homolog

Rft1

1

0.5687

0.771

4.6342

Q8VCV1

Alpha/beta hydrolase domain-containing protein 17C

Abhd17c

1

0.5707

1.271

0.7095

Q3TMQ6

Angiogenin-4

Ang4

1

0.5795

0.549

0.6082

Q08189

Protein-glutamine gamma-glutamyltransferase E

Tgm3 Tgase3

1

0.6085

0.728

0.528

Q8CIM3

D-2-hydroxyglutarate dehydrogenase, mitochondrial

D2hgdh

1

0.61

0.704

1.0195

Q9D7Z6

Calcium-activated chloride channel regulator 1

Clca1

1

0.649

0.709

0.637

O88273

Gremlin-2 (Protein related to DAN and cerberus)

Prdc

1

0.6542

0.906

1.7397

D6RFQ5

p53 and DNA damage-regulated protein 1

Pdrg1

1

0.6585

0.683

0.6567

Q8BYF6

Sodium-coupled monocarboxylate transporter 1

Slc5a8 Smct Smct1

1

0.6667

0.972

0.767

H3BLD0

ATP synthase mitochondrial F1 complex assembly factor 1

Atpaf1

1

0.6687

0.841

0.9637

Q8BXQ3

Leucine-rich repeat and transmembrane domain-containing protein 1

Lrtm1

1

0.6702

0.982

0.573

A0A075B5L8

Protein Igkv4–79

Igkv4–79

1

0.6722

0.688

0.8432

Q3V341

Protein kinase C zeta type

Prkcz

1

0.6775

0.606

1.052

O88310

Intelectin-1a

Itln1

1

0.6782

0.696

0.7225

Q9D2X6

Colon SVA-like protein

Sval1 mcsp mCG_17084

1

0.6782

0.912

0.5127

Q64339

Ubiquitin-like protein ISG15

Isg15 G1p2 Ucrp

1

0.6887

0.922

0.6737

Q810Q5

Normal mucosa of esophagus-specific gene 1 protein

Nmes1

1

0.693

0.832

0.5877

P21550

Beta-enolase

Eno3 Eno-3

1

0.6965

0.876

0.6672

P56392

Cytochrome c oxidase subunit 7A1, mitochondrial

Cox7a1

1

0.7257

0.755

0.655

P30275

Creatine kinase U-type, mitochondrial

Ckmt1

1

0.7492

0.851

0.6657

Q6T707

Protein Scd4 (Stearoyl-CoA desaturase-4)

Scd4

1

0.768

1.808

1.1152

Q9NYQ2

Hydroxyacid oxidase 2 (HAOX2)

Hao2 Hao3 Haox2

1

0.771

0.721

0.658

P09036

Serine protease inhibitor Kazal-type 3

Spink3

1

0.7765

0.987

0.595

P98086

Complement C1q subcomponent subunit A

C1qa

1

0.785

0.406

0.8317

F8VPP8

Protein Zc3h7b

Zc3h7b

1

0.7887

0.677

0.787

Q5RI75–2

Ras and EF-hand domain-containing protein homolog

Rasef

1

0.7892

0.651

0.6965

A2AGQ3

MAP kinase-activating death domain protein

Madd

1

0.7932

1.327

1.398

E9QNL5

Sulfotransferase

Sult1a1

1

0.796

0.659

0.7287

P00329

Alcohol dehydrogenase 1

Adh1 Adh-1

1

0.7992

1.036

0.5625

Q3UZZ6

Sulfotransferase 1 family member D1

Sult1d1 St1d1

1

0.81

0.632

0.7565

B2RT41

Protein Zfc3h1

Zfc3h1 Ccdc131

1

0.831

0.921

0.6362

P57774

Pro-neuropeptide Y [Cleaved into: Neuropeptide Y

Npy

1

0.835

1.436

1.1532

Q3UW68

Calpain-13 (Calcium-activated neutral proteinase 13)

Capn13 Gm943

1

0.838

0.987

0.669

P13634

Carbonic anhydrase 1

Ca1 Car1

1

0.8425

0.622

0.818

Q9WUG6

Insulin-like peptide INSL5 (Insulin-like peptide 5)

Insl5 Rif Rif2 Zins3

1

0.861

1.429

0.6775

F7BQ76

MPN domain-containing protein (Fragment)

Mpnd

1

0.8617

0.603

1.577

P56393

Cytochrome c oxidase subunit 7B, mitochondrial

Cox7b

1

0.8755

1.075

0.6255

Q80WK2

Organic solute transporter subunit beta

Slc51b Ostb

1

0.881

1.373

1.177

A2A6K0

Troponin I, fast skeletal muscle

Tnni2

1

0.886

0.374

0.965

Q7TPR4

Alpha-actinin-1 (Alpha-actinin cytoskeletal isoform)

Actn1

1

0.888

0.857

0.6745

G3X940

Histone acetyltransferase

Kat6a Myst3

1

0.8887

1.618

1.1427

P01796

Ig heavy chain V-III region A4

0

1

0.8935

1.481

1.0095

G3UVW7

Protein Zfp40 (Zinc finger protein 40)

Zfp40 mCG_13522

1

0.9052

1.53

1.0887

Q9EPS2

Peptide YY

Pyy

1

0.9135

1.349

0.974

G3XA21

MCG134445, isoform CRA_a (Protein Mroh1)

Mroh1 Heatr7a

1

0.922

1.114

1.3435

Q9Z179

SHC SH2 domain-binding protein 1

Shcbp1 Pal

1

0.9295

1.107

1.4725

I6L974

TBC1 domain family member 17

Tbc1d17

1

0.9315

1.155

1.3645

P01631

Ig kappa chain V-II region 26–10

0

1

0.9387

1.75

0.821

P01878

Ig alpha chain C region

0

1

0.942

1.332

0.8282

P57776–2

Elongation factor 1-delta (EF-1-delta)

Eef1d

1

0.9477

0.898

0.6252

D3Z6J0

HemK methyltransferase family member 2, isoform CRA_b

N6amt1 Hemk2 mCG_130002

1

0.9562

1.524

1.4077

Q9WUH1

Transmembrane protein 115 (Protein PL6 homolog)

Tmem115 Pl6

1

0.962

1.161

1.4085

Q8R1U2

Cell growth regulator with EF hand domain protein 1

Cgref1 Cgr11

1

0.9635

0.931

1.4472

A0A087WNJ2

Deleted.

0

1

0.974

0.641

0.7125

E0CYM0

Protein 1700019G17Rik

1700019G17Rik

1

0.9752

1.376

1.0687

D3Z7B5

Protein C330027C09Rik

C330027C09Rik

1

0.978

1.336

1.1042

D3Z652

Testis-expressed sequence 35 protein

Tex35

1

0.9797

0.993

1.3665

F8VQE9

ANK repeat and PH domain-containing protein 3

Agap3

1

0.9855

1.026

1.6535

O88665

Bromodomain-containing protein 7

Brd7 Bp75

1

0.9895

0.928

1.5765

E9Q933

Transmembrane protein 11, mitochondrial

Tmem11

1

0.9942

1.5

1.1595

down-regulated

6NXH9

Keratin, type II cytoskeletal 73

Krt73 Kb36

1

14.265

1.559

1.4102

F6R782

IQ domain-containing protein E

Iqce

1

3.496

4.691

4.4437

A0A075B6A3

Protein Igha

Igha

1

2.7217

1.208

1.9125

P00687

Alpha-amylase 1

Amy1

1

2.5575

4.341

3.1215

Q8C804

Spindle and centriole-associated protein 1

Spice1 Ccdc52

1

2.3742

1.928

1.8472

O88273

Formin-2

Fmn2

1

2.2107

2.234

3.8712

D3Z1G3

Multiple coagulation factor deficiency protein 2 homolog

Mcfd2

1

2.2085

1.694

1.931

A2AHB7

Potassium channel subfamily T member 1

Kcnt1

1

2.181

1.35

5.51

G3UZX8

Probable JmjC domain-containing histone demethylation protein 2C

Jmjd1c

1

2.1745

1.124

3.0692

P35991

Tyrosine-protein kinase BTK

Btk Bpk

1

2.1057

1.302

1.5725

P70213

Friend virus susceptibility protein 1

Fv1

1

1.847

1.207

1.5947

A0A075B664

Protein Iglv2

Iglv2

1

1.8257

3.016

1.2922

E9Q9F6–2

Cation channel sperm-associated protein subunit delta

Catsperd Tmem146

1

1.7907

1.132

0.6605

P57791

CAAX prenyl protease 2

Rce1 Face2 Rce1a

1

1.6772

1.103

1.4677

Q9QZU9

Ubiquitin/ISG15-conjugating enzyme E2 L6

Ube2l6 Ubce8

1

1.648

3.026

2.0062

A2AF82

Activator of 90 kDa heat shock protein ATPase homolog 2

Ahsa2

1

1.6057

1.363

1.5

F8VQM0

Alkaline phosphatase

Akp3

1

1.6022

1.282

2.631

P11034

Mast cell protease 1

Mcpt1

1

1.602

1.704

1.5607

Q6ZWN5

40S ribosomal protein S9

Rps9

1

1.5622

1.053

1.3207

Q9DBB8

Trans-1,2-dihydrobenzene-1,2-diol dehydrogenase

Dhdh

1

1.5585

1.268

1.6725

Q6NZQ2

DEAD/H (Asp-Glu-Ala-Asp/His) box polypeptide 31

Ddx31

1

1.5305

1.169

1.3397

G5E8C3

G protein-coupled receptor, family C, group 5, member A

Gprc5a mCG_22262

1

1.5077

1.168

1.4337

Q91WP6

Serine protease inhibitor A3N

Serpina3n Spi2

1

1.502

0.995

1.2225

A2A3U8

LON peptidase N-terminal domain and RING finger protein 3

Lonrf3

1

1.5017

1.274

1.9312

P07759

Serine protease inhibitor A3K

Spi2

1

1.4825

0.804

1.2742

Q9DCG2–2

CD302 antigen

Cd302 Clec13a

1

1.469

1.116

1.786

P27005

Protein S100-A8 (Calgranulin-A)

S100a8 Caga Mrp8

1

1.4637

1.522

1.154

P04227

H-2 class II histocompatibility antigen, A-Q alpha chain

H2-Aa

1

1.4617

1.382

0.916

Q8C6B9

Active regulator of SIRT1

Rps19bp1 Aros

1

1.4555

1.094

1.78

P70412

CUB and zona pellucida-like domain-containing protein 1

Cuzd1 Itmap1

1

1.4365

1.325

1.5315

Q9D083–3

Kinetochore protein Spc24

Spc24 Spbc24

1

1.4297

1.978

2.0805

P62984

Ubiquitin-60S ribosomal protein L40

Uba52 Ubcep2

1

1.4247

1.336

1.143

P12804

Fibroleukin

Fgl2 Fiblp

1

1.4215

1.407

1.7527

J3QPY0

Protein 1600014C10Rik

1600014C10Rik

1

1.4165

1.485

1.8247

B1AXR3

Perilipin-2

Plin2

1

1.414

0.975

1.3562

Q9ESG9

Membrane-associated tyrosine- and threonine-specific cdc2-inhibitory kinase

Pkmyt1 Myt1

1

1.4137

1.332

1.9545

P07758

Alpha-1-antitrypsin 1–1 (AAT)

Serpina1a Dom1 Spi1–1

1

1.4085

0.908

1.1527

Q8C7E9

Cleavage stimulation factor subunit 2 tau variant

Cstf2t Kiaa0689

1

1.401

1.082

1.014

F6ZQQ3

26S proteasome non-ATPase regulatory subunit 13

Psmd13

1

1.3935

1.417

2.6332

Q91XL1

Leucine-rich HEV glycoprotein (Protein Lrg1)

Lrg1 Lrg lrhg

1

1.3932

0.949

1.327

Q03145

Ephrin type-A receptor 2

Epha2 Eck Myk2

1

1.3932

1.186

1.522

Q9QXA1

Cysteine and histidine-rich protein 1

Cyhr1 Chrp

1

1.3902

1.191

1.0515

Q8BHZ4

Zinc finger protein 592 (Zfp-592)

Znf592 Kiaa0211

1

1.3865

1.338

1.3052

P07724

Serum albumin

Alb Alb-1 Alb1

1

1.3842

0.816

1.2217

V9GX06

Protein Gm11214

Gm11214

1

1.3835

1.098

1.3607

P29699

Alpha-2-HS-glycoprotein (Countertrypin)

Ahsg Fetua

1

1.382

0.774

1.1715

P14148

60S ribosomal protein L7

Rpl7

1

1.3705

0.953

1.1725

P42232

Signal transducer and activator of transcription 5B

Stat5b

1

1.3705

1.627

1.311

P35980

60S ribosomal protein L18

Rpl18

1

1.3695

0.963

1.176

Q9D1X0

Nucleolar protein 3 (Apoptosis repressor with CARD)

Nol3 Arc

1

1.3665

1.345

1.5167

G3X8Z1

Calcium-activated chloride channel regulator 4A

mCG_119588

1

1.366

1.008

1.3725

P01741

Ig heavy chain V region (Anti-arsonate antibody)

0

1

1.3647

3.709

1.06

A0A087WQ94

Protein Tns1

Tns1

1

1.3562

1.117

0.9982

A2AAC0

Chymotrypsin-C

Ctrc

1

1.354

1.062

1.3185

E9Q8K5

Titin

Ttn

1

1.3532

0.744

1.6037

Q3U3Q1–2

Serine/threonine-protein kinase ULK3

Ulk3

1

1.353

1.188

1.574

Q91YU8

Suppressor of SWI4 1 homolog

Ppan Ssf1

1

1.3522

1.167

1.1937

Q6LC96

RXR alpha 2 (RXR alpha 3)

Rxra RXR alpha

1

1.329

0.984

1.2152

Q3UPV6

Voltage-gated potassium channel subunit beta-2

Kcnab2

1

1.328

1.568

1.183

P62301

40S ribosomal protein S13

Rps13

1

1.3275

1.093

1.1617

P22599

Alpha-1-antitrypsin 1–2 (AAT) (Alpha-1 protease inhibitor 2)

Serpina1b Aat2

1

1.326

0.849

1.1235

Q9EP52

Twisted gastrulation protein homolog 1

Twsg1 Tsg

1

1.3242

1.197

0.9917

E9PV04

Protein Gm8994

Gm8994 Gm5576

1

1.3237

1.14

1.2215

P15119

Mast cell protease 2

Mcpt2

1

1.322

1.36

1.0482

Q3ZAR9

Nr2c2 protein (Nuclear receptor subfamily 2 group C member 2)

Nr2c2

1

1.3202

1.395

1.158

Q8BSI6

R3H and coiled-coil domain-containing protein 1

R3hcc1

1

1.319

1.279

1.569

Q32M21–2

Gasdermin-A2

Gsdma2 Gsdm2

1

1.3125

1.482

1.233

Q80TL0

Protein phosphatase 1E

Ppm1e Camkn

1

1.3082

0.645

1.1805

F6RUC3

Ribonucleoside-diphosphate reductase subunit M2 (Fragment)

Rrm2

1

1.3075

1.238

1.4467

A2ALH2

Putative tRNA

Ftsj1

1

1.296

1.3

1.5377

Q8BGS0–2

Protein MAK16 homolog (Protein RBM13)

Mak16 Rbm13

1

1.2927

1.195

1.334

Q8BHY2

Nucleolar complex protein 4 homolog (NOC4 protein homolog)

Noc4l

1

1.2877

1.455

1.5922

Q99J23

GH3 domain-containing protein

Ghdc D11lgp1e

1

1.287

1.231

1.3732

O35640

Annexin A8

Anxa8 Anx8

1

1.277

1.55

1.1167

Q60590

Alpha-1-acid glycoprotein 1

Orm1 Agp1 Orm-1

1

1.263

1.116

1.4175

P35461

Lymphocyte antigen 6G (Ly-6G)

Ly6g

1

1.2495

0.915

1.331

P42225

Signal transducer and activator of transcription 1

Stat1

1

1.2437

1.533

0.9722

Q8VEJ4

Notchless protein homolog 1

Nle1

1

1.2432

1.251

1.3997

F6S522

Claspin

Clspn

1

1.2415

1.134

7.6765

Q8BHN5

RNA-binding protein 45

Rbm45 Drb1 Drbp1

1

1.2387

1.232

1.4235

P31725

Protein S100-A9

S100a9

1

1.2345

1.351

1.028

F8WJ43

Merlin

Nf2

1

1.234

1.168

1.441

Q8C3X8

Lipase maturation factor 2

Lmf2 Tmem112b Tmem153

1

1.2307

0.928

1.5145

E9Q8D0

Protein Dnajc21

Dnajc21

1

1.227

1.476

1.1372

Q9QXA1–2

Cysteine and histidine-rich protein 1

Cyhr1 Chrp

1

1.2205

1.374

1.054

Q3UW98

Chloride channel calcium activated 7

Clca4b AI747448

1

1.2187

1.401

1.0597

A0A075B5M8

Protein Igkv12–38

Igkv12–38

1

1.218

1.337

1.2272

Q4QRL3

Coiled-coil domain-containing protein 88B

Ccdc88b Ccdc88

1

1.2172

1.485

1.392

Q3TBT3–3

Stimulator of interferon genes protein (mSTING)

Tmem173 Eris Mita

1

1.2167

1.441

1.1297

P08905

Lysozyme C-2 (EC 3.2.1.17) (1,4-beta-N-acetylmuramidase C) (Lysozyme C type M)

Lyz2 Lyz Lyzs

1

1.2162

1.353

1.0305

Q9DCS1

Transmembrane protein 176A (Gene signature 188) (Kidney-expressed gene 2 protein)

Tmem176a Gs188 Keg2

1

1.2157

1.248

1.5587

P84228

Histone H3.2

Hist1h3b

1

1.214

0.511

1.0842

D3Z408

High affinity cGMP-specific 3′,5′-cyclic phosphodiesterase 9A

Pde9a

1

1.2137

1.307

1.3392

E9Q4G7

Casein kinase I isoform alpha

Csnk1a1

1

1.2105

1.47

1.643

P05533

Lymphocyte antigen 6A-2/6E-1 (Ly-6A.2/Ly-6E.1) (Stem cell antigen 1) (SCA-1) (T-cell-activating protein) (TAP)

Ly6a Ly6

1

1.2085

1.378

1.1695

P01844

Ig lambda-2 chain C region

Iglc2

1

1.2072

2.441

1.087

G3X8S8

MCG14499 (tRNA-splicing endonuclease subunit Sen15)

Tsen15 mCG_14499

1

1.2065

1.143

1.4907

F6QQ13

Selenocysteine insertion sequence-binding protein 2-like (Fragment)

Secisbp2l

1

1.2035

1.149

1.3285

P58501

PAX3- and PAX7-binding protein 1 (PAX3/7BP) (GC-rich sequence DNA-binding factor 1)

Paxbp1 Gcfc Gcfc1

1

1.2035

1.488

1.2637

Q9JLM9

Growth factor receptor-bound protein 14 (GRB14 adapter protein)

Grb14

1

1.1975

0.601

1.1215

P59328–2

WD repeat and HMG-box DNA-binding protein 1 (Acidic nucleoplasmic DNA-binding protein 1) (And-1)

Wdhd1 And1

1

1.1922

1.221

1.4022

A2A5Z6–2

E3 ubiquitin-protein ligase SMURF2 (EC 6.3.2.-) (SMAD ubiquitination regulatory factor 2) (SMAD-specific E3 ubiquitin-protein ligase 2)

Smurf2

1

1.1902

1.098

1.3955

Q8CIA9

Hippocampus abundant transcript-like protein 1

Hiatl1

1

1.1852

1.098

1.3277

H3BKB9

Protein zwilch homolog (Fragment)

Zwilch

1

1.1817

1.114

1.3972

Q5SUA5

Unconventional myosin-Ig

Myo1g

1

1.1747

1.196

1.3717

P03991

H-2 class I histocompatibility antigen, K-W28 alpha chain

H2-K1 H2-K

1

1.1682

1.554

0.966

Q61542

StAR-related lipid transfer protein 3 (Protein ES 64) (Protein MLN 64) (START domain-containing protein 3) (StARD3)

Stard3 Es64 Mln64

1

1.1672

1.663

1.496

A8C756

Thyroid adenoma-associated protein homolog

Thada Kiaa1767

1

1.165

1.299

1.382

Q80ZI6

E3 ubiquitin-protein ligase LRSAM1 (EC 6.3.2.-) (Leucine-rich repeat and sterile alpha motif-containing protein 1) (Tsg101-associated ligase)

Lrsam1

1

1.1627

1.094

1.59

F6RR81

Protein cordon-bleu (Fragment)

Cobl

1

1.1585

1.355

1.1932

Q8R2S8

CD177 antigen (CD antigen CD177)

Cd177

1

1.158

1.426

1.0102

A2ALA0

Surfeit locus protein 6

Surf6

1

1.1567

1.218

1.3962

Q5SUW0

Growth factor receptor-bound protein 10 (Fragment)

Grb10

1

1.1552

1.019

1.3747

Q9CQS2

H/ACA ribonucleoprotein complex subunit 3 (Nucleolar protein 10) (Nucleolar protein family A member 3) (snoRNP protein NOP10)

Nop10 Nola3

1

1.1455

1.37

1.1737

D3YUW8

Pogo transposable element with ZNF domain

Pogz

1

1.1365

1.373

1.3605

Q62293

Interferon-gamma-inducible GTPase Ifggb5 protein

Tgtp

1

1.1357

1.958

1.0067

Q8BX57–3

PX domain-containing protein kinase-like protein (Modulator of Na,K-ATPase) (MONaKA)

Pxk

1

1.1355

0.867

1.3607

E0CYU9

Sjoegren syndrome/scleroderma autoantigen 1 homolog

Sssca1

1

1.135

1.705

1.5802

Q9R0X0–3

Mediator of RNA polymerase II transcription subunit 20 (Mediator complex subunit 20) (TRF-proximal protein homolog)

Med20 Trfp

1

1.1335

1.088

1.3255

P18527

Ig heavy chain V region 914

0

1

1.133

1.071

0.618

A2A6A1

G patch domain-containing protein 8

Gpatch8 Gpatc8 Kiaa0553

1

1.1295

1.861

1.0447

O35242

Protein FAN (Factor associated with neutral sphingomyelinase activation) (Factor associated with N-SMase activation)

Nsmaf Fan

1

1.1275

1.116

1.417

P04184

Thymidine kinase, cytosolic (EC 2.7.1.21)

Tk1 Tk-1

1

1.1222

1.288

1.638

Q80VC9–2

Calmodulin-regulated spectrin-associated protein 3 (Protein Nezha)

Camsap3 Kiaa1543

1

1.1107

1.308

1.492

S4R2K0

Protein Pdf

Pdf

1

1.1082

1.644

1.4732

Q8BZR9

Uncharacterized protein C17orf85 homolog

0

1

1.108

1.132

1.6712

Q8K4Q0–5

Regulatory-associated protein of mTOR (Raptor) (p150 target of rapamycin (TOR)-scaffold protein)

Rptor Raptor

1

1.105

1.153

1.4442

Q6P9L6

Kinesin-like protein KIF15 (Kinesin-like protein 2) (Kinesin-like protein 7)

Kif15 Klp2 Knsl7

1

1.1012

1.367

1.3967

Q9CR76

Transmembrane protein 186

Tmem186

1

1.0997

0.655

1.0117

Q924Z6–2

Exportin-6 (Exp6) (Ran-binding protein 20)

Xpo6 Ranbp20

1

1.0997

1.209

1.5217

Q8BZT5

Leucine-rich repeat-containing protein 19

Lrrc19

1

1.0952

1.379

1.2207

P11247

Myeloperoxidase (MPO) (EC 1.11.2.2) [Cleaved into: Myeloperoxidase light chain; Myeloperoxidase heavy chain]

Mpo

1

1.0945

1.195

1.415

A8DUK4

Beta-globin (Protein Hbb-bs) (Protein Hbb-bt)

Hbbt1 Hbb-bs Hbb-bt Hbbt2

1

1.0942

2.14

0.8445

P01630

Ig kappa chain V-II region 7S34.1

0

1

1.094

1.405

1.2252

Q8CGN5

Perilipin-1 (Lipid droplet-associated protein) (Perilipin A)

Plin1 Peri Plin

1

1.0895

0.885

1.3687

Q9CQT2

RNA-binding protein 7 (RNA-binding motif protein 7)

Rbm7

1

1.0877

1.142

1.333

F7BJK1

Protein Pcdh1 (Fragment)

Pcdh1

1

1.0875

0.927

1.8367

Q80TA6–2

Myotubularin-related protein 12

Mtmr12 Kiaa1682

1

1.0835

1.091

1.5237

P54754

Ephrin type-B receptor 3 (EC 2.7.10.1) (Developmental kinase 5) (mDK-5) (Tyrosine-protein kinase receptor SEK-4)

Ephb3 Etk2 Mdk5 Sek4

1

1.082

1.341

1.1597

D3Z769

Protein lin-37 homolog (Fragment)

Lin37

1

1.0795

1.116

1.5232

A0A075B5X9

Ig heavy chain V region B1–8/186–2 (Fragment)

Ighv1–72

1

1.0795

1.415

1.2

F6TLB0

DNA-directed RNA polymerase, mitochondrial (Fragment)

Polrmt

1

1.077

1.111

1.3495

A0A087WRI5

Adenylate kinase isoenzyme 6

Ak6

1

1.075

1.346

1.1457

Q8BK35

MCG2065, isoform CRA_c (PreS1 binding protein) (Protein Gltscr2)

Gltscr2 mCG_2065

1

1.074

0.953

1.557

Q9CQT0

tRNA(His) guanylyltransferase (EC 2.7.7.79) (tRNA-histidine guanylyltransferase)

Thg1l mCG_22296

1

1.0722

1.14

1.4462

A0A075B677

Protein Igkv4–53

Igkv4–53

1

1.0705

1.361

0.986

G3UWZ0

Bromodomain adjacent to zinc finger domain protein 1A

Baz1a

1

1.0702

1.564

1.3232

F6R2G3

Mucin-4 (Fragment)

Muc4

1

1.0695

1.286

1.3432

Q6GU68

Immunoglobulin superfamily containing leucine-rich repeat protein

Islr

1

1.068

1.154

1.3577

E9PWH6

HEAT repeat-containing protein 3

Heatr3

1

1.0605

1.102

1.4625

Q8BLH7

HIRA-interacting protein 3

Hirip3

1

1.0587

1.496

1.4912

Q62264

Thyroid hormone-inducible hepatic protein (Spot 14 protein) (S14) (SPOT14)

Thrsp S14

1

1.0582

0.943

1.4015

Q99M73

Keratin, type II cuticular Hb4 (65 kDa type II keratin) (Keratin-84) (K84) (Type II hair keratin Hb4) (Type-II keratin Kb24)

Krt84 Krt2–16 Krthb4

1

1.0557

1.17

1.3252

Q9D856

Zinc transporter ZIP5 (Solute carrier family 39 member 5) (Zrt- and Irt-like protein 5) (ZIP-5)

Slc39a5 Zip5

1

1.0555

1.484

1.4005

F7BJB9

Protein Morc3

Morc3

1

1.0525

1.375

1.2087

B7ZWM8

Leucine-rich repeat and calponin homology domain-containing protein 3 (Lrch3 protein)

Lrch3

1

1.0505

1.128

1.3452

D3Z6K8

Ras-specific guanine nucleotide-releasing factor 2

Rasgrf2

1

1.0482

1.047

1.3875

Q5FWI3

Transmembrane protein 2

Tmem2 Kiaa1412

1

1.0462

1.163

1.4667

G3UZL2

RCC1 and BTB domain-containing protein 1 (Fragment)

Rcbtb1

1

1.0417

1.433

1.2967

Q61666–4

Protein HIRA (TUP1-like enhancer of split protein 1)

Hira Tuple1

1

1.0405

1.127

1.3862

P53569

CCAAT/enhancer-binding protein zeta (CCAAT-box-binding transcription factor) (CBF) (CCAAT-binding factor)

Cebpz Cbf2 Cebpa-rs1

1

1.0367

1.325

1.7395

Q9JJF3

Bifunctional lysine-specific demethylase and histidyl-hydroxylase NO66 (EC 1.14.11.-) (EC 1.14.11.27) (Histone lysine demethylase NO66)

No66 Mapjd MNCb-7109

1

1.0337

1.68

1.1642

Q9DAA6

Exosome complex component CSL4 (Exosome component 1)

Exosc1 Csl4

1

1.033

1.326

1.2455

A0A087WQR9

NEDD8-conjugating enzyme UBE2F (Fragment)

Ube2f

1

1.0292

1.352

1.2977

Q9Z0E6

Interferon-induced guanylate-binding protein 2 (GTP-binding protein 2) (GBP-2) (mGBP-2) (mGBP2) (Guanine nucleotide-binding protein 2)

Gbp2

1

1.0292

1.432

0.9467

B7ZMP1–2

Probable Xaa-Pro aminopeptidase 3 (X-Pro aminopeptidase 3) (EC 3.4.11.9) (Aminopeptidase P3) (APP3)

Xpnpep3

1

1.0285

0.927

1.4122

D3YWR2

B-cell linker protein

Blnk

1

1.0237

1.595

1.1195

H7BX32

Nuclear envelope pore membrane protein POM 121

Pom121

1

1.0165

1.187

1.3717

Q99N87

28S ribosomal protein S5, mitochondrial (MRP-S5) (S5mt)

Mrps5

1

1.0147

1.41

0.9545

Q8CBC4

Consortin

Cnst

1

1.0092

1.33

1.19

A2AER8

Polyglutamine-binding protein 1

Pqbp1

1

1.0077

1.477

0.9262

A8Y5N4

17-beta-hydroxysteroid dehydrogenase 13

Hsd17b13

1

1.006

0.603

0.7325

Q9D8I1

Marginal zone B- and B1-cell-specific protein

Mzb1 Pacap

1

1.006

1.348

0.9347

P26618

Platelet-derived growth factor receptor alpha

Pdgfra

1

1.0032

1.152

1.4392

P55088–2

Aquaporin-4 (AQP-4)

Aqp4

1

1.0005

1.327

0.8442

Acc no Accession number, Prot name Protein name, SE Semen Euphorbiae, SEP Semen Euphorbiae Pulveratum, EFL 1 Euphorbiae Factor 1

GO ontology analysis

To elucidate the biological significance of these differentially modified proteins, we performed GO analysis and categorized these proteins according to their molecular function and biological process using the GO database. 295 union proteins were selected and separated into 3 categories: biological processes (Fig. 2a), cellular component association (Fig. 2b), and molecular function (Fig. 2c).
Fig. 2

Bioinformatics analysis of the differentially expressed proteins (ratio ≥ 1.32 or ≤ 0.68 fold). a Biological process (b) Cellular component; (c). Molecular function

In the biological process category, the results suggested that most of the DEPs participate in metabolic processes (32.9%), cellular processes (17.10%), biological regulation (12.6%), and response to stimulus (7.70%). In the cellular component analysis, most of the potential biomarkers are concentrated in the cell part (32.80%), organelle (20.90%), extracellular region (19.40%), membrane (11.90%) or macromolecular complex. In the molecular function analysis, the differentially expressed proteins were found to play a role in catalytic activity (34.60%), binding (32.30%), enzymatic activity (9.00%) and structural molecule activity (8.30%),suggesting that their related functions were important in the colon of mice.

On the basis of our findings, it could be concluded that the identified DEPs causing by SE, SEP and EFL1 were mainly associated with the cellular part. The expression sites of them located within cells and organelles. G protein and Eph/Ephrin signal pathway were controlled jointly by SE and SEP. After processing, the extracts of SEP were mainly reflected in the process of cytoskeleton, glycolysis and gluconeogenesis.

Pathway enrichment analysis and interaction network analysis

MetaCore™ (version 6.18) is an integrated software suite for functional analysis of experimental data. Differential pathways among SE, SEP, EFL 1 and control were conducted according to the P Value (P < 0.05). All the differential pathways were shown in Tables 3, 4 and 5.
Table 3

Pathway Enrichment analysis of differentially expressed proteins relative to SE compared with control group

NO

Maps

pValue

1

Immune response_Oncostatin M signaling via JAK-Stat in mouse cells

0.000195

2

Immune response_Oncostatin M signaling via JAK-Stat in human cells

0.000242

3

Development_Thrombopoetin signaling via JAK-STAT pathway

0.000294

4

Immune response_IL-15 signaling via JAK-STAT cascade

0.000322

5

Development_Transcription factors in segregation of hepatocytic lineage

0.000552

6

Immune response_IL-7 signaling in T lymphocytes

0.000887

7

Immune response_IL-7 signaling in B lymphocytes

0.001136

8

Cell adhesion_Ephrin signaling

0.001244

9

Neurophysiological process_Receptor-mediated axon growth repulsion

0.001244

10

Immune response_IL-5 signaling

0.001300

11

Signal transduction_PTMs in IL-12 signaling pathway

0.001415

12

G-protein signaling_Rap1B regulation pathway

0.013047

13

Protein folding_Membrane trafficking and signal transduction of G-alpha (i) heterotrimeric G-protein

0.022438

14

Immune response_IL-12 signaling pathway

0.027103

15

Development_Glucocorticoid receptor signaling

0.028266

Table 4

Pathway Enrichment analysis of differentially expressed proteins relative to SEP compared with control group

NO

Maps

pValue

1

Cytoskeleton remodeling_Role of PDGFs in cell migration

0.002188

2

Glycolysis and gluconeogenesis p.3 / Human version

0.002188

3

Glycolysis and gluconeogenesis p.3

0.002188

4

Development_PDGF signaling via STATs and NF-kB

0.003877

5

Normal and pathological TGF-beta-mediated regulation of cell proliferation

0.004119

6

Cell adhesion_Ephrin signaling

0.007559

7

Neurophysiological process_Receptor-mediated axon growth repulsion

0.007559

8

Development_PDGF signaling via MAPK cascades

0.008224

9

Some pathways of EMT in cancer cells

0.009631

10

Aberrant B-Raf signaling in melanoma progression

0.011137

11

Transport_Macropinocytosis regulation by growth factors

0.014439

12

Glycolysis and gluconeogenesis (short map)

0.015773

13

G-protein signaling_Rap1B regulation pathway

0.031748

14

Cell adhesion_Chemokines and adhesion

0.034254

15

Cytoskeleton remodeling_Cytoskeleton remodeling

0.035519

Table 5

Pathway Enrichment analysis of differentially expressed proteins relative to EFL1 compared with control

NO.

Maps

pValue

1

Development_Angiopoietin - Tie2 signaling

0.000027

2

Immune response_IL-7 signaling in T lymphocytes

0.000035

3

Immune response_IL-7 signaling in B lymphocytes

0.000051

4

Immune response_Antiviral actions of Interferons

0.000090

5

Immune response_Oncostatin M signaling via JAK-Stat in mouse cells

0.000425

6

Immune response_Oncostatin M signaling via JAK-Stat in human cells

0.000526

7

Development_Thrombopoetin signaling via JAK-STAT pathway

0.000639

8

Immune response_IL-15 signaling via JAK-STAT cascade

0.000699

9

Immune response_IL-23 signaling pathway

0.000827

10

Signal transduction_PTMs in IL-23 signaling pathway

0.001274

11

Development_PDGF signaling via STATs and NF-kB

0.001357

12

Immune response_IL-22 signaling pathway

0.001532

13

Development_EPO-induced Jak-STAT pathway

0.001623

14

Development_Growth hormone signaling via STATs and PLC/IP3

0.001623

15

Immune response_IL-9 signaling pathway

0.001717

Comparing with group 1(control), the pathways with higher activity were mainly related to the immune response, and also related to other physiological processes such as development and G protein pathways; the dominant signaling pathways were interleukin signaling pathway, JAK/Stat et al.; the key proteins involved in multiple pathways contain STAT1, SERPINA3, G protein Rap1B and so on. Meanwhile, group 4 (EFL1) showed that the physiological process with high activity was relatively simple, mainly focused on the immune response and development process. Interleukin signaling pathways, Ang/Tie 2 and NF/kB were found to be the main signaling pathways and the key proteins involved were STAT1 and STAT5; compared with control, group 3 induced cytoskeleton remodeling, glycolysis and gluconeogenesis with higher activities, signaling pathways which contain a variety of major B-Raf pathways, epithelial cells to interstitial cell transition(EMT)-related signaling pathways, cell endocytosis, etc. and PDGF receptors, Ephrin receptors,in which STAT 1 was related to the key proteins.

A network was constructed by protein-protein interaction of the 295 significantly DEPs basing on Analyze Network Algorithm using MetaCore in Fig. 3 (A-D). (Tables 6 and 7).
Fig. 3

Biological networks generated by different groups. a Protein interaction networks of DEPs from four groups after taking the intersection; b, c and d: protein interaction networks of DEPs from four groups after taking union (b: Major Histocompatibility Complex class IInetwork; c: Ubiquitination in Mediating the Cellular Stress Response; d: Interferon-γ-mediated signal transduction and response network); e Explanation of various symbols in the network map. The network of significantly differentially expressed proteins (ratio ≥ 1.32 or ≤ 0.68 fold) was analyzed by MetaCoreTM(version 6.18)software

Table 6

Intersection of differentially expressed protein Networks

Network

GO processes

Total nodes

Seed nodes

p-Value

zScore

gScore

Angiopoietin 4, NF-kB, ALDR, TIE2, ATP + PtdIns(4,5)P2 = ADP + PtdIns(3,4,5)P3

response to oxygen-containing compound (70.6%; 1.570e-16), regulation of multicellular organismal process (76.5%; 2.094e-15), response to peptide (47.1%; 1.618e-14), response to stress (82.4%; 2.570e-14), positive regulation of cellular process (88.2%; 3.104e-14)

51

1

0.00245

20.16

22.66

Table 7

Union of differentially expressed protein Networks

Network

GO processes

p-Value

zScore

gScore

Trypsin II, Chymotrypsin C, Trypsin 3, TATI, RAIG1

antigen processing and presentation of peptide or polysaccharide antigen via MHC class II (27.3%; 6.498e-17)

1.010E-21

48.76

48.76

Ubiquitin, Fetuin-A, UBC, RelA (p65 NF-kB subunit), TRAF2

regulation of response to stress (56.5%; 6.254e-19), positive regulation of NF-kappaB transcription factor activity (28.3%; 2.556e-17)

1.140E-05

14.33

44.33

STAT1, TGTP, Mcpt4 (rodent), Sca-1, Thrombomodulin

interferon-gamma-mediated signaling pathway (31.9%; 8.694e-24), response to interferon-gamma (36.2%; 1.175e-23)

2.970E-14

33.37

33.37

Obviously, commonly pathways are mainly interleukin-mediated signaling pathways, including IL-7, IL-15, IL-23 and other inflammatory factors both controlled by EFL1 and SE groups. We supposed that these inflammatory factors activate the interleukin signaling pathway, NF / kB signaling pathway, and then mediate intestinal mucosal barrier injure by up-regulating inflammatory proteins expression which resulting in inflammatory response. While there is no obvious interleukin-mediated inflammatory response in SEP group. Generally speaking, inflammatory response especially interleukin might be closely related to the attenuated mechanism of Semen Euphorbiae.

According to network analysis, four reliable functional networks were found and analyzed. After intersection of four groups, the main protein interaction network was multicellular organism regulation process (only Angiopoietin 4 is the down-regulated differentially expressed protein and NF-κB is a pivotal role which interacts with other proteins in the network most closely, Fig. 3a). DEPs which were taken together mainly participated in the protein interaction networks as shown in Fig. 3b, c and d. MHC II presents endogenous and exogenous antigenic peptides or antigenic polysaccharides (containing 10 differential proteins, the key point is MHC class II in Fig. 3b), stress response (containing 3 up-regulation differential proteins, RelA/P65 and ubiquitin are the central part of network, Fig. 3c), γ- Interferon - mediated signal transduction and response (containing 6 up-regulation,1 down-regulation differential proteins, as shown in Fig. 3d, STAT1 interacted closely with other proteins and play an important role in the networks).

It should be pointed out that Angiopoietin 4 is the only down-regulated differential expressed protein in the interaction network. Subsequently, STAT1 was found to be the key protein shared by the EFL1, SEP and SE tested groups, compared with the control group. A previous study has implied that the transcription factor NF-κB (nuclear factor kappa B) plays a central role in the regulation of immune and inflammatory responses, as well as in control of cell apoptosis. These proteins participate in the regulation of a wide range of genes involved in immune, inflammatory and apoptosis function [21]. Although the relationship between Angiopoietin 4 and NF-κB has not been reported, according to the network, we could make the hypothesis that SE could increase Angiopoietin 4 and then activate NF-κB to make the body produce immune or inflammatory response. In addition, interferons (IFNs) are important cytokines that play essential roles in antiviral, antibacterial, antitumor and immunomodulatory activities. IFNs primarily signals through the JAK-STAT pathway leading to the activation of signal transducer and activator of STAT and subsequent transcription of target genes [22]. Based on the pathway analysis, IFN-γ could activate STATs through JAK-STAT signal pathway to initiate CIITA (typeIItranscription activator) which as MHC IItrans activator, and then the expression of MHC II were up-regulated to produce immune response and immune regulation so that the mice have diarrhea symptoms after treated with SE group. For these reasons and hypothesis, western blot analysis was then conducted to validate the two differentially expressed proteins- STAT1 and Angiopoietin 4.

Validation of differentially expressed proteins identified by proteomics

Two proteins, STAT1 and Angiopoietin 4 identified DEPs with marked differences in expression determined by iTRAQ based quantitative analysis were selected to be verified by western blot analysis (Figs. 4 and 5). As depicted in Figs. 4 and 5 and Table 8, Angiopoietin 4 protein was significantly down-regulated in SEH, SEPH and EFLH groups as compared with control group (p < 0.05), the expression level of Ang4 in SEH was the lowest; and STAT1 was up-regulated in SEH, SEPH and EFLH groups, which levels were all higher than control group (p < 0.05). Moreover, the groups of low dose of SEL, SEPL and EFLL have no significant differences compared with the control. The results which were found by western blot is consistent with the findings in iTRAQ analysis. Both of Ang-4 and STAT1 expression levels in the mice colon tissue may be dose-dependent with the increase dose of SE and SEP.
Fig. 4

Relative expression levels of Ang4 and STAT1were normalized to the β-actin which were quantified by densitometric analysis. These experiments were each conducted five times

Fig. 5

Western blotting showing the changes in Ang4 and STAT1 level in mice intestine treated with different doses of SE, SEP and EFL1 with respect to control-treated mice intestine

Note:Internal reference:β- actin,1.Control, 2.High-dose of SE (SEH, 1.5 ml/20 g), 3.low-dose of SE (SEL, 0.5 ml/20 g), 4. High-dose of SEP (SEPH, 1.0 ml/20 g), 5. Low-dose of SEP (SEPL, 0.33 ml/20 g), 6.High-dose of EFL1 (EFLH, 20 mg/20 g), 7 Low-dose of EFL1 (EFLL, 10 mg/20 g)

Table 8

The relative expression of Ang4 and STAT1 in intestinal tissue of mice (\( \overline{X} \)±S, n = 5)

groups

Ang4

STAT1

Control

0.865 ± 0.027

0.396 ± 0.019

SEH

0.489 ± 0.084*

0.706 ± 0.167*

SEL

0.683 ± 0.218

0.439 ± 0.046

SEPH

0.598 ± 0.142*

0.421 ± 0.076

SEPL

0.803 ± 0.080

0.358 ± 0.086

EFLH

0.582 ± 0.098*

1.326 ± 0.372*

EFLL

0.749 ± 0.111

0.731 ± 0.133

Note: *compared with control (P < 0.05)

It is well established that the angiopoietin (Ang) family of growth factors includes Ang1, Ang2, Ang3 and Ang4, all of which bind to the endothelial receptor tyrosine kinase Tie2. Ang3 (mouse) and Ang4 (human) are interspecies orthologs. Tie2 [23] maintains the vascular integrity of mature vessels by enhancing endothelial barrier function and inhibiting apoptosis of endothelial cells. According to the pathway network analysis, as shown in Fig. 3a, we speculated that Semen Euphorbiae might inhibit the expression of Ang-4, which Tie-2 couldn’t be activated, so that the steady state of endothelial cells was broken and the sensitivity of various inflammatory mediators increased, permeability, and thus promoted the occurrence of inflammatory response. The inhibition of Ang 4 by SEP group after processing was weakened comparing to SE group, resulting in lower diarrhea and inflammatory response.

STAT1 has been implicated as a mediator of biological responses to a variety of growth factors and cytokines, based on ligand-dependent tyrosine phosphorylation and activation. Stat1 is a functional transcription factor even in the absence of inducer-mediated activation, participating in the constitutive expression of some genes [24]. JAK2/ STAT pathway signaling is activated by a wide array of cytokines and growth factors leading to the stimulation of cell proliferation, differentiation, and apoptosis [25]. And it is an important way of signal transduction of inflammatory factors.

In addition to being involved in the main JAK2 / STAT signaling pathway, STAT1 could be activated by JAK2 (non-receptor tyrosine) kinase, but also by inflammatory factors such as interleukin-6 (IL-6), tumor necrosis factor (TNF),growth factors such as interferon (IFN) [26], epidermal growth factor (EGF), platelet-derived growth factor (PDGF) and other signal activation.

As the up-regulated proteins induced by each group, STAT1 was induced by SEP group lower than the SE group so that we suspected that STAT 1 was most likely one of target proteins related to intestinal inflammation which might illustrate the attenuated mechanism of Semen Euphorbiae.

Both Ang-4 and STAT1 were surmised to be one of the target proteins inducing by Semen Euphorbiae.

Conclusions

This study used iTRAQ labeling followed by 2D-LC-MS/MS for the quantitative proteomic analysis of intestine samples from KM mice with different groups and control to discover candidate biomarkers for attenuated mechanism of Semen Euphorbiae processing for the first time. These findings suggest that SE induced an inflammatory response, and activated the Interleukin signaling pathway, such as the Ang/Tie 2 and JAK2/ STAT signaling pathways, which may eventually contribute to injury result from intestinal inflammatory, while SEP could ease this injury by reducing STAT1 and activating Ang-4 which could reduce the inflammatory response. Taken together, these results not only provided a novel insight into attenuated mechanism of Semen Euphorbiae, which was marked by a number of DEPs that might be associated with intestinal inflammation, but also the first experimental evidence that the Angiopoietin 4 and STAT1 proteins might be two major candidate biomarkers in the attenuated of SE after processing based on proteomic investigation. Our findings suggest that this screening method has potential valuable in studying mechanism of processing. Future systematic studies will investigate how Semen Euphorbiae regulate the expression of these key proteins and illustrate the problem from a clinical point of view.

Notes

Acknowledgments

Not applicable.

Funding

This work was sponsored by grants from NSFC projects (No. 81673597).

Availability of data and materials

Please contact author for data requests.

Authors’ contributions

ZY carried out the preparations of Semen Euphorbiae and Semen Euphorbiae Pulveratum, participated in western blot and drafted the manuscript. ZXT carried out Proteomics extraction procedures. LWH and LSX participated in the design of the study and performed the statistical analysis. SZY and NRJ helped to draft the manuscript and perform the statistical analysis. WYZ and LSJ conceived of the study, and participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate

All procedures employed were approved by Animal Ethical and Welfare Committee of Beijing University of Chinese Medicine.

Consent for publication

Not applicable.

Competing interests

All the authors declare that they have no competing interest.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. 1.
    Shi QW, Su XH, Kiyota H. ChemInform abstract: chemical and pharmacological research of the plants in genus Euphorbia. ChemInform. 2008;108(10):4295–327.Google Scholar
  2. 2.
    Wang YS,Song GW,Zhang HW, et al. Analysis of semen euphorbiae frostlike powders by HPLC fingerprint. 2013;25 (17):10011–10014.Google Scholar
  3. 3.
    FUNG. Characterization of semen euphorbiae. Proceedings of the Society for Experimental Biology & Medicine Society for Experimental Biology & Medicine. 2011;128(1):75–80.Google Scholar
  4. 4.
    Wang ZY, Kang H, Ji LL, et al. Proteomic characterization of the possible molecular targets of pyrrolizidine alkaloid isoline-induced hepatotoxicity. Environmental Toxicology & Pharmacology. 2012;34(2):608–17.CrossRefGoogle Scholar
  5. 5.
    Van SA, Renes J, van Delft JH, et al. Proteomics in the search for mechanisms and biomarkers of drug-induced hepatotoxicity. Toxicology in Vitro An International Journal Published in Association with Bibra. 2012;26(3):373–85.CrossRefGoogle Scholar
  6. 6.
    Wei J, Zhang F, Zhang Y, et al. Proteomic investigation of signatures for geniposide-induced hepatotoxicity. J Proteome Res. 2014;13(12):5724–33.CrossRefPubMedGoogle Scholar
  7. 7.
    Witzmann FA, Grant RA. Pharmacoproteomics in drug development. Pharmacogenomics Journal. 2003;3(2):69–76.CrossRefPubMedGoogle Scholar
  8. 8.
    Su L, Cao L, Zhou R, et al. Identification of novel biomarkers for Sepsis prognosis via urinary proteomic analysis using iTRAQ labeling and 2D-LC-MS/MS. PLoS One. 2013;8(1):e54237.CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Ye H, Sun L, Huang X, et al. A proteomic approach for plasma biomarker discovery with 8-plex iTRAQ labeling and SCX-LC-MS/MS. Mol Cell Biochem. 2010;343(1):91–9.CrossRefPubMedGoogle Scholar
  10. 10.
    Caubet C, Lacroix CS, Drube J, et al. Advances in urinary proteome analysis and biomarker discovery in pediatric renal disease. Pediatr Nephrol. 2010;25(1):27–35.CrossRefPubMedGoogle Scholar
  11. 11.
    Adolf W, Hecker E. Further new diterpene esters from the irritant and cocarcinogenic seed oil and latex of the caper spurge ( Euphorbia lathyris L.). Experientia. 1971;27(12):1393–4.CrossRefPubMedGoogle Scholar
  12. 12.
    Zhu JJ, Wang YZ, Zhang C, et al. Determination of olein compositions in the petroleum ether extractant of semen euphorbiae by gas chromatogra phy-mass. Journal of Shandong University of Traditional Chinese Medicine. 2013;37(5):438–41.Google Scholar
  13. 13.
    Zhu J, Zhang C, Wang Y, et al. Study on chemical constituents of petroleum ether Extractant of semen euphorbiae. Journal of Shandong University of Traditional Chinese Medicine. 2014;38(4):381–2,391.Google Scholar
  14. 14.
    Duan FP, Wang YZ, Li CX. Chemical composition and biological activity analysis of semen euphorbiae petroleum ether extracts. Journal of Chemical & Pharmaceutical Research. 2014;6(5):745–9.Google Scholar
  15. 15.
    Bradford M. A rapid method for the quantification of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem. 1976;72(s 1–2):248–54.CrossRefPubMedGoogle Scholar
  16. 16.
    Sacute W, Niewski JR, et al. Universal sample preparation method for proteome analysis. Nat Methods. 2009;6(5):359–62.CrossRefGoogle Scholar
  17. 17.
    Tam JC, Ko CH, Cheng Z, et al. Comprehensive proteomic analysis of a Chinese 2-herb formula (Astragali Radix and Rehmanniae Radix) on mature endothelial cells. Proteomics. 2014;14(17–18):2089–103.CrossRefPubMedGoogle Scholar
  18. 18.
    Zhang K, Pan X, Zheng J, et al. Comparative tissue proteomics analysis of thoracic aortic dissection with hypertension using the iTRAQ technique. European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery. 2015;47(3):431–8.CrossRefGoogle Scholar
  19. 19.
    Ren W, Hou X, Wang Y, et al. Overgrazing induces alterations in the hepatic proteome of sheep (Ovis aries): an iTRAQ-based quantitative proteomic analysis. Proteome Sci. 2016;15(1):2.CrossRefPubMedGoogle Scholar
  20. 20.
    Glen A, Gan CS, Hamdy FC, et al. iTRAQ-facilitated proteomic analysis of human prostate cancer cells identifies proteins associated with progression. J Proteome Res. 2008;7(3):897–907.CrossRefPubMedGoogle Scholar
  21. 21.
    Gong YT, Wang XM. NF-kB and neurodegenerative disorder in central nervous system. Chinese Bulletin of Life Sciences. 2004;16(5):280–4.Google Scholar
  22. 22.
    Schindler C, Plumlee C. Inteferons pen the JAK-STAT pathway. Semin Cell Dev Biol. 2008;19(4):311.CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Fukuhara S, Sako K, Minami T, et al. Differential function of Tie2 at cell|[ndash]|cell contacts and cell|[ndash]|substratum contacts regulated by angiopoietin-1. Nat Cell Biol. 2008;10(5):513–26.CrossRefPubMedGoogle Scholar
  24. 24.
    Ramana CV, Chatterjee-Kishore M, Nguyen H, et al. Complex roles of Stat1 in regulating gene expression. Oncogene. 2000;19(21):2619–27.CrossRefPubMedGoogle Scholar
  25. 25.
    Caldow MK,Cameron-Smith D.JAK/STAT Pathway.2012:495–497.Google Scholar
  26. 26.
    Sikorski K, Czerwoniec A, Bujnicki JM, et al. STAT1 as a novel therapeutical target in pro-atherogenic signal integration of IFNγ, TLR4 and IL-6 in vascular disease. Cytokine Growth Factor Rev. 2011;22(4):211–9.CrossRefPubMedGoogle Scholar

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© The Author(s). 2018

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors and Affiliations

  • Yu Zhang
    • 1
  • Yingzi Wang
    • 1
  • Shaojing Li
    • 2
  • Xiuting Zhang
    • 1
  • Wenhua Li
    • 1
  • Shengxiu Luo
    • 1
  • Zhenyang Sun
    • 1
  • Ruijie Nie
    • 1
  1. 1.College of Traditional Chinese PharmacyBeijing University of Chinese MedicineBeijingPeople’s Republic of China
  2. 2.Institute of Chinese Materia Medica, China Academy of Chinese Medical SciencesBeijingPeople’s Republic of China

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