**Impairment of PGC-1 Alpha Up-Regulation Enhances Nitrosative Stress in the Liver during Acute Pancreatitis in Obese Mice**

**Sergio Rius-Pérez 1,**† **, Isabel Torres-Cuevas 2,**† **, María Monsalve <sup>3</sup> , Francisco J. Miranda <sup>1</sup> and Salvador Pérez 1,\***


Received: 31 July 2020; Accepted: 17 September 2020; Published: 19 September 2020

**Abstract:** Acute pancreatitis is an inflammatory process of the pancreatic tissue that often leads to distant organ dysfunction. Although liver injury is uncommon in acute pancreatitis, obesity is a risk factor for the development of hepatic complications. The aim of this work was to evaluate the role of PGC-1α in inflammatory response regulation in the liver and its contribution to the detrimental effect of obesity on the liver during acute pancreatitis. For this purpose, we induced acute pancreatitis by cerulein in not only wild-type (WT) and PGC-1α knockout (KO) mice, but also in lean and obese mice. PGC-1α levels were up-regulated in the mice livers with pancreatitis. The increased PGC-1α levels were bound to p65 to restrain its transcriptional activity toward *Nos2*. Lack of PGC-1α favored the assembly of the p65/phospho-STAT3 complex, which promoted *Nos2* expression during acute pancreatitis. The increased transcript *Nos2* levels and the pro-oxidant liver status caused by the down-regulated expression of the PGC-1α-dependent antioxidant genes enhanced nitrosative stress and decreased energy charge in the livers of the PGC-1α KO mice with pancreatitis. It is noteworthy that the PGC-1α levels lowered in the obese mice livers, which increased the *Nos2* mRNA expression and protein nitration levels and decreased energy charge during pancreatitis. In conclusion, obesity impairs PGC-1α up-regulation in the liver to cause nitrosative stress during acute pancreatitis.

**Keywords:** acute pancreatitis; obesity; nitrosative stress; PGC-1α; liver

### **1. Introduction**

Acute pancreatitis (AP) is an inflammatory disorder of the pancreas that often leads to a systemic inflammatory response and organ failure [1]. Currently, AP is the main cause of hospital admission for gastrointestinal problems in the USA [2], with a mortality rate of around 30% in patients who develop organ failure [3]. Several pieces of evidence suggest that oxidative and nitrosative stresses play an essential role in AP pathogenesis [4]. Oxidative stress amplifies the inflammatory process that leads to oxidative damage and contributes to the progression of extrapancreatic complications [5,6]. Nitrosative stress is a well-known feature of AP, with inducible nitric oxide synthase (NOS2) being the main source of nitric oxide (NO) in the pancreas during the course of this pathology [7–10]. In fact, *Nos2*-deficient mice exhibit a low degree of pancreatic inflammation and tissue damage in the pancreas with AP [10].

Obesity is a chronic inflammatory condition that increases the appearance of local and systemic complications and mortality in patients with AP [11–13]. Numerous factors contribute to systemic injury in obese patients with AP, such as the uncontrolled cytokine response, the release of unsaturated fatty acids and damage-associated molecular patterns [13]. The pulmonary, cardiovascular, and renal systems are more frequently affected in AP via these mediators [14]. On the contrary, liver damage is less common, but interestingly its appearance is used as a prognostic value in human AP and its failure invariably leads to death [15]. Remarkably, obesity only triggers hepatic injury during AP in genetically obese fa/fa Zucker rats compared to lean rats [16]. Furthermore, fatty livers can imply much higher rates for local complications, organ failure and mortality during AP [17].

PPARγ co-activator 1α (PGC-1α) is a transcriptional co-activator that is dysregulated in obesity and is important for maintenance of balance in the production of reactive oxygen species (ROS) during inflammatory processes [18]. Indeed, PGC1α modulates the expression of mitochondrial antioxidant defense genes, including manganese superoxide dismutase (*Sod2*), peroxiredoxin (*Prx*) 3, *Prx5* and catalase [19,20]. PGC-1α overexpression is known to suppress the expression of the pro-inflammatory cytokines triggered by tumor necrosis factor-α (TNF-α) in C2C12 muscle cells [21]. Low PGC-1α levels in inflamed tissues increase ROS production and contribute to increased inflammatory response [22].

In the present work, we address the role of PGC-1α in inflammatory response regulation in the liver during acute pancreatitis. Furthermore, we explore the precise contribution of PGC-1α in the liver to the detrimental effect of obesity on acute pancreatitis.

#### **2. Materials and Methods**

#### *2.1. Animals*

C57BL/6 J PGC-1α <sup>−</sup>/<sup>−</sup> mice were originally provided by Dr. Bruce Spiegelman (Dana–Farber Cancer Institute, Harvard Medical School, Boston, MA, USA). Subsequently, a colony was established at the Institute of Biomedical Research "Alberto Sols" (Madrid, Spain) animal facility. The generation and phenotype of PGC-1α knockout (KO) mice have been described previously [23].

Male C57BL/6 J PGC-1α +/+ (22.4 <sup>±</sup> 1.5 g; *n* = 12) and C57BL/6 J PGC-1<sup>α</sup> <sup>−</sup>/<sup>−</sup> (21.9 <sup>±</sup> 1.7 g; *n* = 12) mice were used and fed a standard diet. The male C57BL/6 J mice purchased from Jackson Laboratory (Bar Harbor, ME, USA) were used, and fed either standard chow (TD.08485, Envigo, Barcelona, Spain) (lean: 22.9 ± 1.0 g; *n* = 10) or a high-fat diet with 40% calories from fat (TD.88137, Envigo, Barcelona, Spain) (obese: 29.7 ± 1.8 g; *n* = 10) for 12 weeks.

All the animals were housed under standard environmental conditions (20–22 ◦C, 50 ± 10% humidity, 12 h light–dark cycle) with food and water ad libitum. Experiments were conducted in compliance with legislation on the protection of animals used for scientific purposes in Spain (RD 53/2013) and with EU (Directive 2010/63/EU). Protocols were approved by the Ethics Committee of Animal Experimentation and Welfare of the University of Valencia (Ethical Protocol Code A1529666350463, Valencia, Spain). This was approved by the Regional Ministry of Agriculture, Environment, Climate Change and Rural Development of Generalitat Valenciana with Code 2018/VSC/PEA/0190 type 2.

#### *2.2. Experimental Model of Acute Pancreatitis*

Acute pancreatitis was induced in 12-week-old mice by seven intraperitoneal cerulein injections (Sigma-Aldrich, St. Louis, MO, USA) (50 µg/kg body weight) at 1-h intervals [24]. Physiological saline (0.9% NaCl) was administered to the control group (sham mice). Animals were sacrificed 1 h after the seventh cerulein injection. Mice were sacrificed by euthanization under anesthesia with isoflurane 3–5% and were then exsanguinated. The pancreas and liver were immediately removed. Sacrifice was confirmed by cervical dislocation.

#### *2.3. RNA Extraction and RT-qPCR Analysis of Gene Expression*

Total RNA was isolated using TRIzol reagent (Sigma-Aldrich, St. Louis, MO, USA) following the manufacturer's instructions. The RNA concentration was measured in a NanoDrop Lite spectrophotometer (Thermo Scientific, Waltham, MA, USA), and purity was determined by the optical density (OD) 260/280 ratio. RNA was reverse transcribed to cDNA with the PrimeScript RT Reagent Kit (Perfect Real Time) (Takara Bio Inc., Kusatsu, Japan) following the manufacturer's instructions. The RNA levels of the genes were performed in a thermal cycler (I-Cycler + IQ Multicolor Real-Time OCR Detection System, Biorad, Hercules, CA, USA) by using the SYBR Green PCR Master Mix (Takara Bio Inc., Kusatsu, Japan). The employed specific primers are shown in Table 1.


**Table 1.** The oligonucleotides used for RT-qPCR.

RT-qPCR was performed by running TaqMan gene expression assays and the TaqMans PCR Master Mix (Applied Biosystems, Life Technologies Corporation, Carlsbad, CA, USA). A list of the analyzed genes and TaqMan probes is presented in Table 2.


**Table 2.** The TaqMan® probe used for RT-qPCR.

The results were normalized using the TATA binding protein (*Tbp*) as housekeeping. The threshold cycle (CT) was determined and the relative gene expression was expressed as follows: fold change = 2–∆(∆CT), where ∆CT = CT target − CT housekeeping, and ∆(∆CT) = ∆CT treated − ∆CT control.

#### *2.4. Western Blot Analysis*

The liver and pancreas tissue samples were frozen at −80 ◦C until homogenization (Politron Generator FSH-G 5/085 from Thermo Fisher Scientific, Waltham, MA, USA,) in extraction buffer (100 mg/mL) on ice. Lysis buffer (20 mm Tris–HCl, pH 7.5, 1 mM EDTA, 150 mM NaCl, 0.1% SDS, 1% Igepal, 30 mM sodium pyrophosphate, 50 mM sodium fluoride, 1 mM sodium orthovanadate) and a protease inhibitor cocktail (Sigma-Aldrich) at a concentration of 4 µL/mL were employed. Homogenates were centrifuged for 15 min at 15,000 rpm and 4 ◦C. The concentration of the proteins in each homogenate was measured by the bicinchoninic acid (BCA) protein assay (Thermo Fisher

Scientific, Waltham, MA, USA). Blots were visualized using a chemiluminescence (ECL) detection kit Western blotting substrate (Fisher Scientific, Madrid, Spain). Signals were captured by the ChemiDoc XRS and Imaging System (Bio-rad, Richmond, CA, USA). The density of bands was measured by version 2.0.1 of the Image Lab Software (Bio-rad, Richmond, CA, USA).

The employed antibodies were: anti-β-tubulin (1:1000, ab6046 from Abcam, Cambridge, UK); anti-PGC-1α (1:500, sc-518025 from Santa Cruz Biotechnology, Dallas, TX, USA); anti-p65 (1:1000, #8242 from Cell Signaling Technology, Danvers, MA, USA); anti-phospho-p65 (Ser 536) (1:100, #3033 from Cell Signaling); anti-Nitro-tyrosine (1:1000, #9691 from Cell Signaling); anti-STAT3 (1:1000, #9132 from Cell Signaling); anti-phospho-STAT3 (Tyr705) (1:1000, #9131 from Cell Signaling); anti-GAPDH (1:1000, #2118 from Cell Signaling); anti-NOS2 (1:1000, ab178945 from Abcam); anti-IgG (1:1000, #7076 from Cell Signaling).

#### *2.5. Co-Immunoprecipitation*

Protein–protein interactions were analyzed by co-immunoprecipitation experiments. Whole-cell extracts were prepared and subjected to immunoprecipitation with specific antibodies against PGC-1α (sc-518025, Santa Cruz, Dallas, TX, USA) and p65 (1:1000, #8242 from Cell Signalling) as previously described [25]. The presence of both NF-κB and p-STAT3 in immunoprecipitates was evaluated by a Western blot with their corresponding antibodies (p65 and p-STAT3).

#### *2.6. Redox Pairs and Protein Nitration and Chlorination by UPLC-MS*/*MS Analysis*

Redox pairs, namely, oxidized glutathione (GSSG)/reduced glutathione (GSH), γ-glutamilcystine/ γ-glutamilcysteine and cysteine (Cyss)/cysteine (Cys), were analyzed from the frozen liver samples homogenized in phosphate buffered saline (PBS) with 10 mM N-ethylmaleimide. Then, perchloric acid was added to obtain a 4% concentration and centrifuged at 15,000× *g* for 15 min at 4 ◦C. The concentration of analytes was determined in the supernatants by Ultra Performance Liquid Chromatography—mass spectrometry UPLC-MS/MS. This method was performed following the protocol of Escobar et al. [26]

Protein nitration and chlorination were determined by calculating the ratio 3NO2-Tyrosine/ p-Tyrosine and 3Cl-Tyrosine/p-Tyrosine. The protocol consists of homogenizing frozen liver with lysis buffer (100 mg/mL). Next proteins were precipitated with trichloroacetic acid (TCA) (10%, *v*/*v*), and pellets were resuspended in sodium acetate (50 mmol/L, Ph 7.2) (Sigma-Aldrich, St. Louis, MO, USA). Immediately, the protein digestion from tissue extracts was carried out according to Hensley's method [27]. To finish pronase activity, TCA was used to precipitate it. Then, samples were centrifuged (5000 rpm, 4 ◦C, 5 min) and the supernatant from each sample was injected into the chromatographic system to be quantified by UPLC-MS/MS according to Torres-Cuevas et al. [28].

Data were acquired and processed with the MassLynx 4.1 software and the QuanLynx 4.1 software (Waters), respectively.

#### *2.7. Energy Charge Determined by UPLC-MS*/*MS*

The energy charge (E.C.) is an index relative to ATP, ADP and AMP concentrations as indicated by the formula E.C. = ((ATP) + 0.5(ADP))/((ATP) + (ADP) + (AMP)) [29].

The determination has been performed in the liver tissue by means of ultra-high-resolution liquid chromatography coupled to a mass spectrometry tandem (UPLC-MS/MS). The system used is Acquity UPLC-Xevo TQD from Waters (Milford, MA, USA). The samples were processed from frozen liver samples (−80 ◦C), homogenized in water: methanol (1:3) cold at 4 ◦C (100 mg/mL). In this step, the methanol precipitates the proteins present in the homogenate and, once precipitated, to be eliminated, the samples were centrifuged for 20 min at 15,000 rpm at 4 ◦C. The supernatant obtained was analyzed by UPLC-MS/MS according to Jiang Y et al. with slight modifications [30]. The precipitate was suspended in ammonium acetate buffer pH = 7 to determine the protein concentration in the sample.
