- Open Access
Proteomic Study of Hepatic Nuclear Extracts in an Adaptive Acetaminophen Tolerance Model
© Humana Press 2009
Received: 10 September 2008
Accepted: 13 January 2009
Published: 3 February 2009
Variability in response to acetaminophen (APAP)-induced aseptic inflammation and tolerance to the impending hepatic damage has been described. To understand the mechanism of adaptive tolerance, we investigated the proteomic profiles of crude nuclear lysates in a mouse model. We hypothesized that pretreatment with low doses of APAP prior to a toxic dose results in differential protein expression.
Materials and Methods
Mice (BALB/C) were separated into three groups: the pretreated (PT) group received incremental doses of APAP while the last dose only (LD) and naïve groups were given saline vehicle. A toxic dose of APAP was administered on the seventh day to the PT and LD animals only and all groups were euthanized 3 h postdose. Total protein from crude hepatic nuclear lysates were applied to protein arrays and analyzed by immunoaffinity mass spectrometry.
Results and Discussion
Comparative data analyses of protein peaks revealed a protein that was significantly increased at m/z of 60,030 (p60) in the LD animals vs the other two groups. The closest match for the preliminary identification of the p60 protein based on a Swiss-Prot/TagIdent database search using the approximate isoelectric point and molecular weight information was Ccr4–Not complex subunit-2. This protein is a subunit of a multiprotein complex and serves as a transcriptional suppressor involved in controlling mRNA synthesis and degradation. Preliminary identification was also supported by Western blot analysis using anti-CNOT2 antibody.
Considering the APAP tolerance model, we conclude that toxicogenomic approaches such as nuclear profiling are useful tools in assessing differential expression of transcriptional factors involved in inflammatory response and adaptive tolerance to toxins.
Acetaminophen (N-acetyl-para-aminophenol or APAP) is a commonly available over-the-counter medication. At therapeutic doses, it is an effective analgesic and antipyretic; however, when consumed in large quantities due to accidental or deliberate overdose, APAP is the leading cause of drug-induced acute liver failure . As reviewed by Gelotte et al. , approximately 90% of APAP is metabolized by two rate-limiting factors. The metabolism of both glucuronidation via uridine 5′-diphospho-glucuronosyltransferase (isoform UGT1A6) and sulfotransferase isoforms (SULT1A1 and 1A3) are based upon the availability of their respective inorganic forms and enzymatic transferase activities. Roughly 8–10% of APAP is metabolized by cytochrome P450 (CYP), a superfamily of hemoproteins involved in the metabolism of steroid hormones, drugs, and xenobiotic substances, and the remaining fraction is excreted unchanged by the kidneys. The primary cytochrome involved in APAP metabolism, CYP2E1, results in the formation of a highly reactive and toxic intermediate N-acetyl-p-benzo-quinone imine (NAPQI) that is subsequently metabolized to glutathione by glutathione-S-transferases. Thiol metabolites of glutathione production include cysteine, mercapturate, methylthioacetaminophen, and methyanesulfinylacetaminophen  which are excreted thru the bile or urinary system. In conditions of APAP overdose and oxidative stress, the primary metabolic pathway becomes saturated. The reduced glutathione stores are rapidly depleted and thereby NAPQI accumulates at the site of metabolism, the liver. As a reactive intermediate, NAPQI is then free to covalently bind to various intracellular targets, ultimately resulting in hepatocellular injury and necrosis.
Although the exact mechanism by which APAP exerts toxicity is not known, it is clear that liver susceptibility to APAP toxicity is multifactorial. Furthermore, it is yet to be determined how some individuals tolerate extreme doses of APAP without exhibiting hepatic toxicity. One such case was reported by Shayiq and colleagues  involving a patient with an estimated daily ingestion of 65 g of APAP. While this massive ingestion was thought to have exhibited extensive hepatic necrosis, permanent liver injury did not occur. This lack of toxicity may be attributed in part to inherent variations in CYP2E1 expression [4, 5]. Animal models have been useful in the studies of complex cellular responses and networks involved in toxicity. Using these approaches, induction of tolerance to poisoning brought about by incremental exposure to multiple sublethal doses (prior to a lethal dose) have been investigated. To elucidate the hepatoprotective nature of this exposure, Shayiq et al.  developed a mouse model in which animals were either pretreated with saline vehicle or administered incremental sublethal doses of APAP prior to the administration of a lethal dose. Induced tolerance to APAP was measured in terms of the median lethal dose (LD-50) or the dose of a toxic agent necessary to kill 50% of the study population in a defined time interval. In this study, the LD-50 of the APAP pretreatment group increased by 400%, suggesting that pre-exposure afforded hepatoprotection. We have reproduced this model of adaptive tolerance in our laboratory and have confirmed tolerance of the pretreated animals by demonstrating a lack in increased serum alanine transaminase (ALT) concentrations in the pretreated animals under APAP dosing conditions that lead to fivefold increased serum ALT in naïve animals .
Proposals for hepatocyte autoprotection (i.e., induced or adaptive tolerance) include the role of oxidative stress [7–9], inflammatory chemokines and cytokines [10–12], and the resultant equilibrium shift in the balance between proinflammatory and anti-inflammatory cytokines [8, 9]. The investigation of covalent bonding of APAP intermediates to enzymes and proteins has lead to the examination of glutathione expression  and hepatocyte regeneration [10, 11, 14].
A variety of standard techniques have been utilized to assess potential molecular mechanisms of adaptive tolerance, including immunohistochemistry [8, 9], RNA, and protein analyses [14, 15]. Recent technological advancements in proteomic profiling and bioinformatics have allowed for a dramatic increase in the analyses of biomarkers in complex biological fluids including: serum and plasma [16–19], urine [20–23], cellular subfractions [24–26], ligand binding [27–29], and cerebral spinal fluid [30, 31]. Although these applications have systematic limitations [32–34], a variety of platforms are being used for the separation and identification of novel proteins involved in various cellular processes.
In an effort to understand and characterize the mechanism of adaptive tolerance, we have utilized proteomic analyses to evaluate protein expression in crude nuclear lysates by bioaffinity mass spectrometry. Using a mouse model of APAP toxicity established in our laboratory , we hypothesized that animals pretreated with low doses of this drug prior to a final toxic dose differentially express proteins compared to naïve animals and, as such, these proteins may contribute to the observed hepatoprotection in our model system. Understanding the mechanisms for adaptive tolerance to drugs may provide insights into better diagnoses and treatments for drug toxicities.
Materials and Methods
The saline solution was drained from minced tissue and the remaining tissue fragments were homogenized in 0.25 M sucrose buffered with 50 mM potassium phosphate buffer (pH 7.4). Homogenates were centrifuged at 1,000 rpm in 50 mL polycarbonate tubes to sediment cellular debris. The supernatant was then resedimented at 12,000 rpm for 20 min. Crude nuclear pellets were then aliquoted and stored frozen at −80°C.
Frozen pellets (approximately 700 μL) were thawed on ice and combined with approximately 300 μL of autoclaved, double-distilled ice-cold H2O containing protease inhibitors (Complete Protease Inhibitors; Roche #1836153; 1:7 dilution, tablet to H2O). The resultant volume was vortexed briefly and the nuclear suspension (approximately 200 μL) was removed and transferred to 300 μL of U9 buffer (9 M urea, 2% 3-[(3-cholamidopropyl) dimethylammonio]propanesulfonic acid, 50 mM Tris–HCl, pH 9.0). Samples were then vortexed approximately 10 min at room temperature and then centrifuged at 20,000×g at 4°C for 30 min. The supernatants were collected, aliquoted on ice, and immediately stored at −80°C .
Immunoaffinity mass spectrometry products were obtained from Bio-Rad Laboratories (Hercules, CA, USA) including: chip arrays, bioprocessors (with disposable reservoirs and gaskets), sinapinic acid (50% acetonitrile, 0.5% trifluoroacetic acid [SPA]) as the energy absorbing molecules (EAM), PBS-II reader (time of flight mass spectrometer [TOF-MS]), and the Biomarker Wizard (BW) software. The performance of the mass spectrometer was monitored weekly by assessing its calibration according to the manufacturer’s instructions.
Multiple chip arrays were utilized to capture proteins based upon their innate biochemical properties, including IMAC30 (metal binding), SAX2 (strong cation exchange), and H4 (hydrophobic) surfaces. Chips were processed in 96-well formatted bioprocessors. The IMAC30 chip surface required activation by the addition of 100 mM CuS04; the addition of 100 mM of sodium bicarbonate (pH 4.0) facilitated the removal of any remaining unbound copper molecules. All chip types were equilibrated with their respective binding/washing buffers according to the manufacturer’s instructions. Binding/washing buffers for IMAC30 (100 mM NaH2PO4 [pH 7.0], 0.5 M NaCl, 0.1% polyethylene glycol p-(1,1,3,3-tetramethylbutyl)-phenyl ether [Triton X-100]), SAX2 (10 mM Tris Base [pH 8.0], 0.1% Triton X-100) and H4 (50 mM 1 mM N-(2-hydroxyethyl)-piperazine-N′-2-ethanesulfonic acid [HEPES buffer, pH 7.0], 0.1% Triton X-100) surfaces were applied to the chip surface prior to protein application.
Protein concentration was determined using the Bradford Assay (Bio-Rad Laboratories, Hercules, CA, USA) using albumin as the standard (Sigma-Aldrich [purity of 96% by electrophoresis]). Crude nuclear lysates (15 μg in 2:3 [v/v] of deionized water/U9 buffer) were incubated on chip surfaces for 30 min followed by repeated washes with each chip’s respective buffer. All chips were washed with 1 mM HEPES buffer (pH 7.0) prior to bioprocessor disassembly. Excess volume was drained from each chip spot and arrays were air-dried. The EAM for each chip type was SPA and was applied in two successive 1-μL aliquots. Experimental groups were analyzed concurrently to minimize chip to chip variation using the Bio-Rad Laboratories PBS-II protein chip reader. Samples were randomized on each chip and run in triplicate.
Initially, all spectra were visually inspected. If the matrix peaks were missing or depressed below 30% the log-normalized value, the spectra were eliminated from final data analysis. Peaks were detected with first and second pass signal to noise ratio of 5 and 2 using the BW software. All spectra were normalized according to manufacturer’s instructions. Calculated p values using the BW software were utilized in selecting proteins which yielded the greatest mass difference amongst groups. The mass of relevant peaks were further analyzed using the ExPASy molecular biology server (http://ca.expasy.org/tools/tagident.html; accessed on March 2005) to ascertain potential protein candidates. Input variables included a percentage range about the molecular weight (MW), isoelectric point (pI), range of the protein (as estimated by the pH of the binding and wash buffer solutions for each chip type), organism classification (i.e., mouse), and keyword (restricted based on UniProtKB list of keywords).
Mouse liver crude nuclear lysates (15 μg per lane) were loaded onto 4–20% gels (Bio-Rad Laboratories, Hercules, CA, USA) prior to sodium dodecyl sulfate polyacrylamide gel electrophoresis. Gels were transferred to nitrocellulose membrane using the Semi-Dry Trans-Blot Apparatus (Bio-Rad Laboratories, Hercules, CA, USA) according to manufacturer’s instructions. Following an initial block (5% dried milk in 1X phosphate buffered saline, 137 mM NaCl, 10 mM phosphate, 2.7 mM KCl, pH 7.4) and multiple washes (1X phosphate buffered saline plus 0.005% Tween-20), membranes were hybridized with a rabbit antihuman IgG polyclonal antibody to CNOT2 using a 1:500 dilution in blocking buffer (affinity purified recombinant protein, confirmed by immunohistochemistry and Western blotting [ProteinTech Group, Chicago, IL, USA]) . Membranes were then washed with agitation for 30 min and subsequently hybridized with a goat antirabbit IgG-labeled HRP antibody diluted 1:2,000 in blocking buffer (Abcam, Cambridge, MA, USA). Chemiluminescent signal was detected by Enhanced Chemiluminescent Plus reagents according to the manufacturer’s recommendations (Amersham Biosciences, Piscataway, NJ, USA) and exposed to chemiluminescence film.
Results and Discussion
Analyses of chip types vs treatment groups
LD vs PT
Naїve vs PT
LD vs Naїve
Tentative protein identification via the ExPASy Swiss-Prot/TagIdent database allowed for the incorporation of pI, MW, organism classification, and a set of predefined key words. Since this protein had been discovered using the SAX2 chip type with a binding/washing buffer with a pH of 8.0, the following specifications were used as search criteria: MW of 60.030 ± 600, pI equal to 8.0 ± 1.0, and organism classification defined as mouse. The ExPASy Swiss-Prot database resulted in 39 possible matches. Elimination criteria included proteins not expressed in the nucleus and from tissues other than the liver. The carbon catabolite repressor 4-negative on TATA-less genes (Ccr4–Not transcription complex) subunit-2 was determined to be the best fit and closest partial identification for this protein based on the pI (7.61), MW (59,711), and organism classification (mouse).
The NOT genes were originally isolated in yeast [36, 37] by genetic screening and identified as negative regulatory elements of transcription on TATA-less promoters (HIS3 gene; S. cerevisiae). The CNOT2 gene, a member of the CNOT 2/3/5 family, is located on chromosome 10:115889276–115985621 bp, − strand (GeneID: 72068) in mice (Cnot2) and on 12q15 (GeneID: 4848) in humans (CNOT2). There are two forms of the Ccr4–Not complex (1.0 and 1.9 MDa forms) as determined by mass spectrometry . As reviewed by Denis and Chen , the roles of the Ccr4–Not transcriptional complex include the repression and activation of mRNA initiation, mRNA elongation, deadenylation, and degradation. This complex signaling network can function individually or synergistically to initiate various functions  and is located in both in the nucleus and cytoplasm . Polymorphisms are known to influence transcriptional activity; human CNOT2 has approximately 300 single-nucleotide polymorphisms/variants as identified by Applied Biosystems (Foster City, CA, USA; http://www.genecards.org/cgi-bin/carddisp.pl?gene=CNOT2), while the mouse (Mus musculus) has eight (http://www.ncbi.nlm.nih.gov/SNP/snp_ref.cgi?locusId=72068).
Our preliminary identification of this protein as CNOT2 suggests that its expression may ultimately result in regulatory factors that mediate APAP-induced hepatic inflammation. Inflammation of major organs such as the liver and kidneys is the primary means by which APAP exerts its initial toxic effects [6, 42, 43]. In APAP poisoning cases, it takes 2–3 days on average for hepatic inflammation and damage to appear clinically. The finding that the CNOT2 protein was expressed similarly in the naïve and PT animals implies a potential role for this transcriptional factor in adaptive APAP tolerance. It is clear from the animal model that proinflammatory cytokines play a major role in APAP adaptive tolerance [11, 44–47]. Identification of the p60 protein via proteomic technology has augmented our knowledge of the potential key players in aseptic inflammation. The involvement of a transcriptional factor regulating gene expression in adaptive APAP tolerance is suggestive of transcriptional control as a regulatory mechanism of autoprotection.
The authors would like to thank Dr. Christine Simmons, Mr. Matt Herrnberger, and Dr. Marjorie Bon Homme for their excellent technical assistance. Support for these studies was provided by the following grants: NIH 1P30ES014443-01A1 and NIH 1-RO1-GM065459.
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