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Identification of differentially expressed proteins in liver in response to subacute ruminal acidosis (SARA) induced by high-concentrate diet.

INTRODUCTION

In intensive ruminant livestock systems, rapidly fermentable (high grain) diets are commonly utilized to increase energy intake or simply due to a lack of forages at times in China. When ruminants are fed high-grain diets, short chain fatty acid (SCFA) production can exceed absorption and ruminal pH becomes depressed which can cause ruminal acidosis (Bergman, 1990; DeVries et al., 2009). Subacute ruminal acidosis (SARA), which is diagnosed when ruminal pH falls below 5.6 for more than 3 h per day, is common in practical dairy production (Gozho et al., 2005; AlZahal et al., 2007). As a common digestive disorder occurring in ruminants, the consequences of SARA include feed intake depression, reduced fiber digestion, milk fat depression, diarrhea, laminitis (Nocek, 1997; Stone, 2004), liver abscesses, rumen mucosal damage (Kleen et al., 2003), increased production of bacterial endotoxin and inflammation characterized by increases in acute phase proteins (AlZahal et al., 2007).

Liver is the largest and complex digestive gland in ruminant animals, which is involved in the digestion, absorption, excretion, detoxification, material transportation, energy metabolism and immunity. Nutrients absorbed from digestive tract in dairy cows must pass through liver, and then enter into circulatory system, arrive at mammary gland; therefore, liver plays an important role in nutrient composition of peripheral blood and metabolic integration regulation. Although the physiopathology of SARA has been comprehensively studied (Nocek, 1997; Kleen et al., 2003), there are few reports describing the hepatic metabolic adaption when SARA occurs. Two-dimensional gel electrophoresis (2-DE) is a holistic protein characterization method that might help to decipher proteomic changes in the goat liver. Therefore, the first objective of this study was to develop and characterize a nutritional model for inducing SARA. The second objective was to determine global protein expression changes in the liver in response to SARA.

MATERIALS AND METHODS

Materials

Immobilized pH gradient (IPG) strips (pH 3.0 to 10.0 non-linear (NL); 17 cm), urea, thiourea, dithiothreitol (DTT), 3-([3-cholamidopropyl] dimethyl-ammonio)-1-propane sulfonate (CHAPS), ampharmalyte pH 3 to 10, phenylmethane sulfonyl fluoride (PMSF), iodoacetamide (IAM) were purchased from Bio-Rad (Richmond, CA, USA). Coomassie brilliant blue G-250 was purchased from AMRESCO (Solon, OH, USA). All chemicals for sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) were of electrophoresis grade.

Animals and liver sampling

Sixteen mid-lactating Boer crossbred goats (obtained from Zhejiang, China) with rumen fistula, weighed 46.90[+ or -]3.14 kg, were randomly divided into 2 groups. The experiment periods were 3 weeks in duration following a 14-day adaptation. The animals were fed either a high-forage (HF) diet or a high-concentrate (HC) diet. Goats were fed and milked twice daily (8:00 and 18:00). The HC diet composition was selected to induce SARA (Brossard et al., 2003). Composition and nutrient levels of experimental diets are given in Table 1. All goats were housed in individual stalls and had free access to drinking water. The animal care and use protocol was approved by the Institutional Animal Care and Use Committee of Nanjing Agricultural University.

Ruminal liquid samples (10 mL) were taken from the ventral sac of the rumen before morning feeding and at 1, 2, 4, 6, and 10 h after feeding of the last 2 days. The pH of the rumen fluid was immediately determined by means of a portable pH meter (HI8424, Hana Instruments, Milan, Italy). When rumen pH was depressed for prolonged periods each day, e.g. below 5.6 for over 3 h/d, SARA was induced successfully. After ensuring the occurrence of SARA, liver samples were collected at the 3rd day. Samples were collected directly after goats were sacrificed and stored at -80[degrees]C.

Protein sample preparation and 2-D gel electrophoresis

Two-dimensional gel electrophoresis (2-DE) was performed on both HF and HC groups with the method as previously described by Chen et al. (2010). Tissues were homogenized in lysis buffer consisting of 7 M urea, 2 M thiourea, 2% (w/v) CHAPS, 50 mM DTT, 0.8% (w/v) ampharmalyte pH 3 to 10 and 1 mM PMSF using a glass homogenization vessel in ice bath. The resulting homogenates were swirled for 30 min followed by a 30 min centrifugation at 15,000 g at 4[degrees]C. Supernatants were collected and fractionated in aliquots. Protein concentrations of the final supernatants were measured using bovine serum albumin (BSA) as standard by the Bradford assay (Bradford, 1976).

To ensure reproducibility, the goat liver extract was pooled and run under the same conditions to overcome inter-individual changes in animals. All 2-DE gels were run three times. In brief, protein concentration of the lysate was adjusted to 850 [micro]g/320 [micro]L volume of rehydration buffer and the lysate was applied onto IPG strips (pH 3.0 to 10.0 NL; 17 cm) in the protean system (Bio-Rad, Hercules, CA, USA). After 13 h of passive rehydration in the tray, isoelectric focusing was performed with the following programmed voltage parameters: 250 V for 1 h, 500 V for 1 h, 2,000 V for 1 h, 8,000 V for 3 h, and then holding at 8,000 V until a total of at least 60,000 V-h was reached. Then strips were equilibrated with DTT and iodoacetamide. The second dimension was run on a 12.5% polyacrylamide SDS gel (26 x 20 cm) at 16[degrees]C using Multiphor system (15 W/gel) (Amersham Biosciences, Uppsala, Sweden) until the bromophenol blue dye had reached the bottom of the gel. Then Neuhoff's colloidal Coomassie blue G-250 stain was carried out according to the method described by Candiano et al. (2004).

Stained gels were scanned with a high precision scanner (Versa Doc 3000, Bio-Rad, Hercules, CA, USA) and analyzed using PDQuest8.1.0 software (Bio-Rad, Hercules, CA, USA). After alignment, spots between gels were automatically matched first. The matched spots were reexamined manually to ensure accuracy. Generally, only those spots of more than 3-fold difference in both dietary modes were chosen for further analysis. Spot quantity normalization was conducted in the 'total quantity valid spots' mode.

Matrix-assisted laser desorption ionization/time of flight analysis

The differentially expressed protein spots were excised from gels and conserved in Ependoff tubes, followed by matrix-assisted laser desorption ionization/time of flight analysis which was carried out by BoYuan Biological Technology Company in Shanghai, China. Protein digested by trypsin was used to calibrate the mass instrument using the internal calibration mode. Parent mass peaks had a mass range of 800-3,500 Da. Protein data searches were performed by search engine of Mascot.

RESULTS

Dynamic change of ruminal pH

The pH data were expressed as mean[+ or -] standard deviation, and differences were considered significant when p<0.05, which were tested by one-way analysis of variance (ANOVA) followed by a multiple range test using SPSS16.0 software (SPSS, Chicago, IL, USA). As expected, goats fed the HF diet displayed steady ruminal pH traces with no hours below pH 5.6 (Figure 1). In contrast, SARA was diagnosed in the HC group as ruminal pH was depressed below 5.6 for about 4 h (Figure 1).

Comparison of proteomic patterns

We performed comparative visual and software-guided analysis of representative 2-DE proteome profiles of the 2 groups. There was good separation of protein spots seen in the 2-D gel electrophoresis except in the base area (Figure 2). After auto-matching and manual quality check of the detected spots, 495[+ or -]23 valid spots were identified in this experiment series.

In general, the protein profiles of the 2 feeding conditions detected by 2-DE were similar to each other, suggesting that few proteins were differentially expressed in the two groups. A total of 15 protein spots, however, showed up to a 3-fold difference in volume when comparing the 2 groups (Figure 3). Positive identifications were obtained for these 15 spots, including 10 up-regulated and 5 down-regulated in SARA group, and protein identities of the 15 spots are listed in Table 2.

In order to assess functional relevance of changes in the differentially expressed proteins, the proteins were classified according to their primary functions. These proteins were mainly related to metabolism and energy transfer. When SARA was induced, acyl-CoA synthetase (ACS) and cytochrome b5 involved in lipid metabolism were up-regulated, phosphoenolpyruvate carboxykinase (PEPCK) involved in glucose metabolism was downregulated, while enolase was up-regulated. At the aspect of protein metabolism, elongation factor Tu (EF-Tu), glutamate dehydrogenase 1 (GLDH), glutathione S-transferase and adenosylhomocysteinase were up-regulated while 26S protease regulatory subunit 7 and serum albumin precursor were down-regulated in HC group. At the same time, glutathione S-transferase and cytochrome b5 were also involved in oxidative stress. These results hinted that SARA had a key effect on substance metabolism in liver.

DISCUSSION

In ruminants, the change of rumen pH is related to prevalent consumption of rapidly fermentable carbohydrates, and authors generally define SARA based on ruminal pH values (DeVries et al., 2009). But the average pH over a day is sometimes considered as a poor indicator of SARA (Sauvant et al., 1999), because it does not reflect the large daily fluctuations in pH (Dijkstra et al., 1993; Dragomir et al., 2008). Several authors have pointed out the necessity of analyzing pH fluctuations (Nocek, 1997; Beauchemin et al., 2001), and the time spent under a pH threshold. We opted to use time below pH 5.6 as the cut-off point for SARA, as in Krause and Oetzel, because it allowed us to detect SARA in goats which were fed with a concentrate: forage ratio of 60:40, in line with previous studies using similar diets (Krause and Oetzel, 2005). The goats ate all the feeds provided, thus keeping concentrate: forage ratios of 60:40 and 40:60. We recorded that the time when pH <5.6 was about 4 h in goats fed with HC diet over 2 successive days. So we determined that SARA was induced successfully by a concentrate: forage ratio of 60:40.

The SARA has a prolonged influence on production performance. It has long been assumed that SARA causes milk fat depression (Nocek, 1997; Kleen et al., 2003; Stone, 2004). Experimentally induced SARA, either by adding grain pellets to the diet or by replacing alfalfa hay with alfalfa pellets, reduced milk fat percentage but increased milk protein percentage (Fairfield et al., 2007). Currently, the research concerning SARA are focused on the physiopathology of SARA (Nocek, 1997; Kleen et al., 2003). Our study applied 2-DE technology to examine liver protein profiles of mid-lactating goats under different dietary patterns and identified 15 differentially expressed proteins by MAIDI-TOF/TOF. The results indicated that glucose, lipid and protein catabolism were enhanced when SARA occurred. Changes of some of the proteins were well correlated with previous findings by different means. For example, alpha enolase (spot 7) is the glycolytic enzyme that catalyzes the production of phosphoenolpyruvate from 2-phosphoglycerate. Phosphoenolpyruvate carboxykinase (spot 15) catalyzes the rate-limiting step in hepatic gluconeogenesis and adipose glyceroneogenesis. The upregulation of alpha enolase and the down-regulation of PEPCK which are involved in glycolysis and gluconeogenesis showed that gluconeogenesis was inhibited and glycolysis was strengthened, namely carbohydrate mainly participated in oxidation and energy supply in liver when SARA occurred.

This study also inferred that lipid catabolism could be enhanced when SARA occurred, as shown by the profiles of spots 1 and 11 (Table 2 and Figure 3). Cytochrome b5 is known to function as an electron transfer component in a number of oxidative pathways, including the anabolic metabolism of fats and steroids. The cytochrome b5 electron-transport system has recently been implicated in fatty acid desaturation reactions in isolated microsomes (Porter, 2002; Schenkman and Jansson, 2003). Acyl-CoA synthetase is a crucial enzyme that facilitates the uptake and permits the metabolism of intracellular lipids. And the enzyme catalyzes the first step of fatty acid metabolism by converting inactive fatty acids into active acyl CoA derivatives (Schoonjans et al., 1995). Thus it was possible that more energy was required and the mobilization of liver fat was enhanced when SARA occurred.

The observation of up-regulation of spots 5, 8, 13 and down-regulation of spots 4 and 6 which participated in protein metabolism in SARA liver was consistent with the previous theories (Lapierre and Lobley, 2001). Elongation factor Tu is a guanosine triphosphate (GTP)-binding protein that is crucial for protein biosynthesis. In the GTP-bound form of the molecule, EF-Tu binds tightly to aminoacyl-tRNA, forming a ternary complex that interacts with the ribosomal acceptor site. During this interaction, GTP is hydrolyzed, and EF-Tu-GDP is released (Kjeldgaard et al., 1993). The catalytic activities of adenosylhomocysteinase have an important effect in controlling the expression of intra-cellular Adohcy as well as regulating transmethylation, transsulfuration and purine metabolism, especially biological methylation. If the activity of adenosylhomocysteinase is decreased or inhibited, the metabolism of protein and nucleic acid will be affected (Palmer and Abeles, 1979). In our experiment, the upregulation of EF-Tu and adenosylhomocysteinase indicated that liver protein synthesis was enhanced when SARA occurred, which was likely to compete for raw materials of lacto protein. Spot 13 was identified as GLDH, which is the key enzyme of amine acid catabolism. The up-regulation of spot 13 in SARA liver enhanced deamination of glutamic acid, namely, amine acid catabolism was accelerated. This would make oxidation and energy supply of amine acid possible, on the other hand, would degrade the content of lutamic acid and increase the consumption of amine acid.

Calreticulin (spot 3) is a major endoplasmic reticulum [Ca.sup.2+] binding chaperone with multiple functions and is involved in a variety of cellular signaling pathways, such as those involved in innate immunity, adipocyte differentiation, apoptosis, and cellular stress responses (Obeid et al., 2007; Yan et al., 2011). Calreticulin also plays a crucial role in regulating [Ca.sup.2+] intracellular homeostasis (Wang et al., 2012). Recent study also showed that the overexpression of regucalcin could suppress cell death and apoptosis induced by stimulation of intracellular signaling-related factors in cloned rat hepatoma H4-II-E cells (Izumi and Yamaguchi, 2004). At the same time, some of the spots were matched to proteins related to oxidative stress, such as GST and cytochrome b5. It inferred that anti-oxidative stress of liver occurred in the activation state to resist the injury of SARA. Further studies would be required to discriminate all these processes.

In summary, this proteomic study indicates an adaptation of protein expression in liver to SARA induced by a HC diet. The results suggested that carbohydrate, lipid and amine acid in the liver mainly participated in oxidation and energy supply when SARA occurred, which possibly consumed excessive precursors involved in milk protein and milk fat synthesis. At the same time, characterization of proteome changes in the liver between HF group and HC group could serve as a model for future studies in elucidating the metabolism pathways of liver when SARA occurred.

http://dx.doi.org/10.5713/ajas.2013.13729

ACKNOWLEDGMENTS

The authors declare that there is no conflict of interest is regarding the publication of this paper. This project was sponsored by grants from the China National Basic Research Program Foundation (Project No. 2011CB100802); Priority Academic Program Development of Jiangsu Higher Education Institutions; and Graduate Students' Innovative Projects of Jiangsu Higher Education Institutions (Project No. CXLX 13-291).

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X. Y. Jiang, Y. D. Ni, S. K. Zhang, Y. S. Zhang *, and X. Z. Shen

College of Veterinary Medicine, Nanjing Agricultural University, Nanjing 210095, China

* Corresponding Author: Y. S. Zhang. Tel: +86-2584396763, E-mail: zhangyuanshu@njau.edu.cn

Submitted Nov. 16, 2013; Revised Jan. 20, 2014; Accepted Mar. 4, 2014

Table 1. Composition and nutrient levels of experimental diets
(%)

Item                    HF         HC

Ingredient (%)
   Hay                  48         32
   Alfalfa              12         8
   Corn                29.2      23.07
   Wheat bran           0         28.3
   Soybean meal        8.43        2
   Rapeseed meal        0         3.7
   Limestone           0.57       1.43
   CaHP[O.sub.4]       0.9        0.6
   Salt                0.4        0.4
   Premix (1)          0.5        0.5
Nutrient level (%)
   ME, KJ/kg          18,012     17,828
   CP                 14.21      15.38
   Fat                 3.47       3.44
   NDF                60.23      50.81
   ADF                23.02      17.29
   Ca                  0.99       1.18
   P                   0.33       0.46

HF, high-forage; HC, high- concentrate; ME, metabolizable energy;
CP, crude protein; NDF, neutral detergent fiber; ADF, acid
detergent fiber.

(1) Premix group was divided into: FeS[O.sub.4] * 7[H.sub.2]O
170 g/kg; CuS[O.sub.4] * 5[H.sub.2]O 70 g/kg; MnS[O.sub.4] *
5[H.sub.2]O 290 g/kg; ZnS[O.sub.4] * 7[H.sub.2]O 240 g/kg;
[Co.sub.2]Cl * 6[H.sub.2]O 510 mg/kg; KI 200 mg/kg;
NaSe[O.sub.3] 130 mg/kg; vit A 1,620,000 IU/kg; vit [D.sub.3]
324,000 IU/kg; vit E 540 IU/kg; vit [K.sub.3] 150 mg/kg; vit
[B.sub.12] 0.9 mg/kg; vit [B.sub.5] 450 mg/kg; calcium
pantothenate 750 mg/kg; folic acid 15 mg/kg.

Table 2. MAIDI-TOF/TOF identification of differentially expressed
proteins in liver in response to SARA

No. (1) Protein name              Accession      pI    Molecular
                                  number (2)            weight

Glucose metabolism

  7     Alpha enolase            AAD33073       6.44    47,589

  15    Phosphoenolpyruvate      NP_083270      7.88    74,226
        carboxykinase [GTP],
        mitochondrial

Lipid metabolism

  1     Cytochrome b5            1106188A       5.15    11,044

  11    Acyl-coenzyme A          NP_777107      7.84    65,706
        synthetase ACSM1,
        mitochondrial

Protein metabolism

  4     Serum albumin            NP_001009376   5.80    71,139
        precursor

  5     Adenosylhomocysteinase   NP_001029487   5.88    48,120

  6     26S protease             NP_150239      5.59    48,943
        regulatory
        subunit 7

  8     Elongation factor        NP_776632      6.72    49,709
        Tu, mitochondrial
        precursor

  13    Glutamate                XP_001925088   8.03    61,668
        dehydrogenase 1,
        mitochondrial

Electron transfer

  1     Cytochrome b5            1106188A       5.15    11,044

  9     Retinal                  NP_001009778   6.37    55,417
        dehydrogenase 1

  14    Electron transfer        NP_001069290   8.77    35,282
        flavoprotein subunit
        alpha, mitochondrial
        precursor

Others

  2     PREDICTED:               XP_001250503   5.81    21,007
        glyoxalase I-like

  3     Regucalcin               NP_776382      5.54    33,857

  10    PREDICTED: aldo-keto     XP_001250576   6.60    37,644
        reductase family 1,
        member C1

  12    Glutathione              NP_787019      6.90    25,789
        S-transferase Mu 1

No. (1) Matched peptide sequences (m/z) (3)        Up or
                                                  down (4)

Glucose metabolism

  7     VVIGMDVAASEFYR (1571.7654)                   Up
        AAVPSGASTGIYEALELR (1803.9366)
        LAMQEFMILPVGAENFR (1996.9750)
        AGYSDKVVIGMDVAASEFYR (2193.0412)
        DATNVGDEGGFAPNILENKEALELLK (2756.3868)

  15    IFHVNWFR (1117.5821)                        Down
        FLWPGFGENAR (1292.6302)
        EVLAELEALEGR (1327.6983)
        GVPLVYEAFNWR (1449.7405)

Lipid metabolism

  1     STWLILHYK (1159.6390)                        Up
        YYTLEEIQK (1185.5917)
        TFIIGELHPDDR (1411.7096)
        FLEEHPGGEEVLR (1510.7416)
        EQAGGDATENFEDVGHSTDAR (2204.9207)

  11    EGWLDFR (921.4345)                           Up
        ATIDEEGYFWFLGR (1702.7991)
        TLDPMAIFFTSGTTGFPK (1945.9496)
        IKPTRPIGLFMYYENNPEK (2325.1827)

Protein metabolism

  4     YLYEVAR (912.4705)                          Down
        HPEYAVSVLLR (1282.7034)
        TVMENFVAFVDK (1414.6803)
        HGEYGFQNALIVR (1502.7630)
        DVFLGSFLYEYSR (1594.7668)

  5     IILLAEGR (883.5491)                          Up
        AGIPVYAWK (1003.5491)
        YPQLLSGIR (1045.5920)
        WLNENAVEK (1101.5454)
        VADISLAAWGR (1157.6193)
        EGPFKPDHYRY (1407.6571)
        GISEETTTGVHNLYK (1647.8104)

  6     DIRFELLAR (1131.6400)                       Down
        FDDGAGGDNEVQR (1378.5750)
        KIEFSLPDLEGR (1402.7456)
        LREVVETPLLHPER (1686.9417)

  8     YEEIDNAPEER (1363.5891)                      Up
        QIGVEHVVVYVNK (1482.8195)
        LLDAVDTYIPVPTR (1571.8559)
        DLEKPFLLPVESVYSIPGR (2158.1674)

  13    NLNHVSYGR (1058.5257)                        Up
        DDGSWEVIEGYR (1424.6208)
        HGGTIPIVPTAEFQDR (1736.8846)
        DSNYHLLMSVQESLER (1935.8996)
        ELEDFKLQHGTILGFPK (1971.0466)
        KGFIGPGIDVPAPDMSTGER (2059.0045)
Electron transfer

  1     STWLILHYK (1159.6390)                        Up
        YYTLEEIQK (1185.5917)
        TFIIGELHPDDR (1411.7096)
        FLEEHPGGEEVLR (1510.7416)
        EQAGGDATENFEDVGHSTDAR (2204.9207)

  9     TIPMDGNFFTYTR (1561.7235)                    Up
        IFINNEWHSSVSGK (1616.7947)
        ELGEYGFHEYTEVK (1699.7729)
        LFVEESIYDEFVRR (1800.9046)
        GYFIQPTVFSDVTDDMR (2005.9092)

  14    LDVAPISDIIAIK (1366.8071)                   Down
        ASSTSPVGISEWLDQK (1703.8366)
        GLLPEELTPLILATQK (1735.0131)
        LLYDLADQLHAAVGASR (1811.9530)
        DPEAPIFQVADYGIVADLFK (2207.1150)

Others

  2     VAWVFSR (863.4654)                          Down
        SLDFYTR (900.4341)
        KSLDFYTR (1028.5291)
        GFGHIGIAVPDVHGACK (1733.8672)
        FSLYFLAYEDKNDIPK (1961.9774)

  3     QGSLYSLFPDHHVEK (1755.8580)                  Up
        YFAGTMAEETAPAVLER (1870.8771)

  10    FAIEVGFR (937.5022)                          Up
        QTPALVALR (967.5815)
        REDIFYTSK (1157.5717)
        SHDIVLVAYGALGAQR (1668.8947)
        VWSTFLRPELVRPALEK (2040.1520)
        LNDGHFIPVLGFGTFAPPEVPK (2351.2314)

  12    RPWFAGDK (975.4926)                          Up
        LTQSNAILR (1014.5822)
        LLLEYTDTNYEER (1657.7835)

MAIDI-TOF/TOF, Matrix-assisted laser desorption
ionization/time of flight; SARA, subacute ruminal acidosis.

(1) Number of the protein spots in the gel.

(2) Accession number in National Center for Biotechnology
Information.

(3) The sequences of all the identified peptides with
the corresponding m/z ratio in brackets.

(4) The expression of high-concentrate group compared
with high-forage group.
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Author:Jiang, X.Y.; Ni, Y.D.; Zhang, S.K.; Zhang, Y.S.; Shen, X.Z.
Publication:Asian - Australasian Journal of Animal Sciences
Article Type:Report
Date:Aug 1, 2014
Words:4214
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