You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


Introduction
============

The liver is a key organ that regulates glucose homeostasis by balancing the storage of glucose and the output of glucose ([@B1], [@B2]). Pre-diabetes describes a condition affecting increasing numbers of the population who have abnormal glucose homeostasis but not diabetes mellitus and who suffer impaired glucose tolerance or fasting glucose ([@B3]). Glucose intolerance is common in patients with liver cirrhosis of various etiologies, and ∼20% of cirrhotic patients have overt diabetes ([@B4]). Recent observational studies have provided consistent evidence on associations of diabetes with increased risk of cancers of the liver ([@B5]). In Korea, both elevated fasting serum glucose levels and a diagnosis of diabetes are regarded as independent risk factors for several major cancers, including stomach, pancreatic, lung, and liver cancers, and the risks of these conditions increase with an increased level of fasting serum glucose ([@B6]). HBV[^4^](#FN4){ref-type="fn"} infection is also strongly associated with type 2 diabetes among Asian, Asian Americans, Pacific Islanders, and Italians ([@B7]--[@B10]). Diabetic hyperglycemia is associated with serum alanine aminotransferase activity in patients with hepatitis B infection ([@B11]). However, the mechanisms by which HBV leads to glucose metabolism are not elucidated at all.

HBV is a hepatotrophic virus that causes acute and chronic hepatocellular injury. HBV X protein (*HBx*), one of four open reading frames in the HBV genome, has been implicated in regulating apoptosis, inflammation, and tumorigenesis ([@B12], [@B13]) by acting as a coactivator of transcription factors, including nuclear factor κB (NF-κB) ([@B14]), cAMP-response element-binding protein (CREB) ([@B15]), and mitogen-activated protein kinases (MAPKs) ([@B16]). Our previous studies demonstrated that HBx causes hepatic steatosis through the transcriptional activation of sterol regulatory element-binding protein 1 (SREBP1) and peroxisome proliferator-activated receptor (PPARγ) transcripts ([@B17]), suggesting the involvement of HBx in the transcriptional regulation of glucose metabolism-related genes.

Inflammation is an important pathogenic factor of metabolic liver diseases, including non-alcoholic steatohepatitis ([@B18]) and hepatogenous diabetes ([@B19]). Inflammatory mediators, such as nitric oxide and TNF-α, have been shown to impair the metabolic action of insulin in the liver, which ultimately results in hepatic dysfunction causing insulin resistance. Indeed, expression of inducible nitric oxide synthase (iNOS) was elevated in the liver of chronic HBV-infected patients ([@B20]). During acute or chronic HBV infection, HBx plays a pivotal role in the induction of hepatic inflammatory responses, as evidenced by the fact that HBx transactivates the promoter of the *iNOS* gene through the proximal NF-κB-binding site ([@B21]). Moreover, TNF-α synthesis induced by HBV is transcriptionally up-regulated by HBx in hepatocytes ([@B22]). These results imply that HBx may act as a key component connecting a link between hepatic glucose metabolism and inflammation.

In the current study, we investigated the role of HBx in glucose metabolism by studying transgenic mice that carry the *HBx* gene *in vivo* and cultured hepatic cell lines *in vitro*, with particular emphasis on transcriptional regulation of gluconeogenic enzymes and whole body glucose homeostasis. We also sought to determine whether activation of iNOS is required for HBx-mediated metabolic dysregulation. Here we show that increased HBx expression is sufficient to cause hyperglycemia and impaired glucose tolerance by enhancing gene expression of hepatic gluconeogenic enzymes and hepatic glucose production. These effects are thought to be regulated through nitric oxide (NO)/JNK signaling. Our data establish a novel function of HBx in the regulation of hepatic glucose homeostasis in chronic hepatitis-related metabolic diseases.

EXPERIMENTAL PROCEDURES
=======================

Detailed methods can be found in the [supplemental material](http://www.jbc.org/cgi/content/full/M111.259978/DC1).

### 

#### Animal Model

The generation of *HBx* homozygous transgenic (*HBx*Tg) mice that have one copy of *HBx* transgene in chromosome 2 has been described previously ([@B13]); the strain of *HBx*Tg mice was fixed to C57BL/6 by backcrossing with the C57BL/6 strain for more than 20 generations. The *iNOS*-deficient (C57BL/6-NOS2^tm/Lau^) mice were obtained from the Jackson Laboratory. Double mutant (*HBx*Tg/*iNOS*^−/−^) mice were produced by crossing *HBx*Tg mice with *iNOS*^−/−^ mice. The mice were housed in a pathogen-free animal facility under a standard 12-h light/dark cycle. All animal procedures were conducted in accordance with the guidelines of the Institutional Animal Care and Use Committee, Korea Research Institute of Bioscience and Biotechnology (KRIBB, Daejeon, Korea).

#### Patients

The paired peritumoral and tumoral hepatocellular carcinoma (HCC) tissues of HBV patients were collected from the hospital of Chonbuk National University. The HBV patients only reacted to antibodies of HBV. All patients participating in this study gave informed consent before surgery.

#### Hyperinsulinemic-Euglycemic Clamp Study

Seven days prior to the hyperinsulinemic-euglycemic clamp studies, indwelling catheters were placed into the right internal jugular vein. After an overnight fast, \[3-^3^H\]glucose (HPLC-purified; PerkinElmer Life Sciences) was infused at a rate of 0.05 μCi/min for 2 h to assess the basal hepatic glucose production. Following the basal period, hyperinsulinemic-euglycemic clamp was conducted for 140 min with a primed/continuous infusion of human insulin (126 pmol/kg of prime, 18 pmol/kg/min of infusion) (Novo Nordisk). Blood samples (10 μl) were collected at 10--20-min intervals, plasma glucose was immediately analyzed during the clamps by a glucose oxidase method (GM9 Analyzer; Analox Instruments), and 20% dextrose was infused at variable rates to maintain plasma glucose at basal concentrations (∼6.7 m[m]{.smallcaps}). To estimate insulin-stimulated whole body glucose fluxes, \[3-^3^H\]glucose was infused at a rate of 0.1 μCi/min throughout the clamps, and 2-deoxy-[d]{.smallcaps}-\[1-^14^C\]glucose (PerkinElmer Life Sciences) was injected as a bolus at the 85th min of the clamp to estimate the rate of insulin-stimulated tissue glucose uptake, as described previously ([@B23]). Blood samples (10 μl) for the measurement of plasma ^3^H and ^14^C activities were taken at the end of the basal period and during the last 45 min of the clamp. Rates of basal and insulin-stimulated whole body glucose fluxes and tissue glucose uptake were determined as described previously ([@B23]).

#### Statistical Analysis

Data were analyzed using the SigmaStat 3.1 software. Quantitative data are presented as the mean ± the S.E. from at least three independent experiments. Comparisons between groups were analyzed by the unpaired two-tailed Student\'s *t* test or one-way or two-way analysis of variance with post hoc analyses, when appropriate, as indicated.

RESULTS
=======

### 

#### HBx Regulates the Expression of Gluconeogenic Genes

We investigated the effect of HBx on hepatic glucose metabolism by assessing gene expression of the key gluconeogenic enzymes in HepG2-*HBx* cells. Overexpression of HBx caused a significant increase in gene expression of gluconeogenic molecules (*G6Pase*, *PEPCK*, and *PGC1*α) and of *FOXO1* and its target genes, such as insulin-like growth factor-binding protein-1 (*IGFBP1*) ([@B24]) and insulin receptor substrate 2 (*IRS2*) ([@B25]) in HepG2 cells ([Fig. 1](#F1){ref-type="fig"}*A*). However, the glucose transporter 2 (*GLUT2*), insulin receptor (*INSR*), carnitine palmitoyltransferase 1*a* (*CPT1a*), and pyruvate carboxylase (*PC*) were unaltered by HBx overexpression ([Fig. 1](#F1){ref-type="fig"}*A*). Conversely, shRNA-mediated suppression of *HBx* mRNA decreased gene expression of the key gluconeogenic enzymes in HepG2 cells ([Fig. 1](#F1){ref-type="fig"}*B*). We also investigated gene expression of the key gluconeogenic enzymes in non-tumor liver tissues of HBV patients with high or low levels of *HBx* gene expression. The difference with *HBx* mRNA was ∼90-fold. Transcript levels of gluconeogenic genes in patients with high levels of *HBx* gene expression were significantly increased when compared with patients with low levels. However, there was no difference in expression of *PCNA* mRNA between groups, indicating that liver tissues are non-tumor ([Fig. 1](#F1){ref-type="fig"}*C*). These data suggest that HBx plays a key role in regulating the expression of gluconeogenic genes in HepG2-*HBx* cells as well as in HBV patients.

![**HBx regulates the gene expression of glucose metabolism-related molecules in hepatocytes.** *A*, expression profiles of metabolic genes in HepG2 cells. *B*, expression profiles of metabolic genes of HepG2-*HBx* cells infected with lentiviruses expressing HBx shRNA. mRNA levels were analyzed by qRT-PCR. *C*, increased expression of gluconeogenic genes in HBV-infected patient livers. mRNA was purified from the non-tumor regions of patient livers with HBx expression and cancer (*n* = 15--22). Data are presented as the mean ± S.E. \*, *p* \< 0.05; \*\*, *p* \< 0.01; \*\*\*, *p* \< 0.001 *versus* control.](zbc0381174600001){#F1}

#### HBx Expression Causes Impaired Glucose Tolerance in Mice

We next examined the physiological role of HBx in the regulation of glucose homeostasis and insulin sensitivity *in vivo. HBx*Tg mice had normal body weight until 6 months of age; thereafter they did not gain weight when compared with wild-type (WT) mice ([Fig. 2](#F2){ref-type="fig"}*A*). Liver weight in *HBx*Tg mice was increased ∼25% when compared with WT mice, whereas adipose tissue mass decreased significantly (∼70%) ([Fig. 2](#F2){ref-type="fig"}*B*). Furthermore, *HBx*Tg mice showed several hepatic histopathological changes, including fatty changes, inflammation and dysplasia ([supplemental Table 1](http://www.jbc.org/cgi/content/full/M111.259978/DC1)), and an increase of serum parameters, such as triglyceride, cholesterol, and free fatty acid ([Table 1](#T1){ref-type="table"}). These observations indicate possible involvement of HBx in complicated liver metabolic diseases. Notably, *HBx*Tg mice had a high risk for glucose intolerance, as evidenced by higher glucose levels in fasted and fed states ([Fig. 2](#F2){ref-type="fig"}*C*). As expected, blood glucose levels at all times during the glucose tolerance tests were also markedly higher than controls ([Fig. 2](#F2){ref-type="fig"}*D*). However, *HBx*Tg mice showed insulin tolerance ([Fig. 2](#F2){ref-type="fig"}*E*). After injection of insulin, blood glucose levels dropped to a similar rate in *HBx*Tg mice and WT. Except at the starting point, blood glucose levels were virtually identical in the WT and *HBx*Tg mice at various time points after insulin injection. However, unexpectedly serum insulin level was significantly lowered in *HBx*Tg mice when compared with WT mice, regardless of feeding states, whereas serum glucagon level was greatly elevated in *HBx*Tg mice ([Table 1](#T1){ref-type="table"}). Consistent with the results, hepatic glycogen level was significantly reduced in *HBx*Tg livers in concert with an increase in hepatic glucose production ([Fig. 2](#F2){ref-type="fig"}, *F* and *G*). These results suggest that the impaired glucose metabolism in *HBx*Tg livers may be associated with the changes in hormones regulating serum glucose level.

![**HBx expression causes impaired hepatic glucose metabolism in mice.** *A*, growth curves were constructed by plotting mean ± S.E. body weight of WT and *HBx*Tg mice (*n* = 11--16). *B*, comparison of liver and epididymal fat weight/body weight between WT (*n* = 7) and *HBx*Tg (*n* = 8) mice at 6 months of age. *C*, glucose concentration in blood derived from mouse tail vein in 12-h fasted and *ad libitum*-fed mice at 6 months of age. *D* and *E*, insulin sensitivity was examined by a glucose tolerance test (*D*) and insulin tolerance test (*E*). Mice were 6 months of age (*n* = 10--13). *F*, glycogen content was measured in liver of 12-h fasted and *ad libitum*-fed mice (*n* = 6). Periodic acid-Schiff stained paraffin-embedded liver sections of *HBx*Tg mice at 6 months of age. The *scale bar* represents 100 μm. *G*, glucose amount secreted in media from cultured primary hepatocytes of WT and *HBx*Tg mice. Data are presented as the mean ± S.E. (\*, *p* \< 0.05; \*\*, *p* \< 0.01; \*\*\*, *p* \< 0.001).](zbc0381174600002){#F2}

###### 

**Serum parameters measured in 6-month-old mice fasted overnight**

FFA, free fatty acid; ALT, alanine transaminase; AST, aspartate aminotransferase; LDL, low density lipoprotein; HDL, high density lipoprotein; ND, not determined. *n* = 8--11 mice per group. \*, *p* \< 0.05; \*\*, *p* \< 0.01; \*\*\*, *p* \< 0.001 for WT versus *HBx*Tg mice. \#, *p* \< 0.05; \#\#, *p* \< 0.01; \#\#\#, *p* \< 0.001 for *HBx*Tg versus *HBx*Tg/*iNOS*^−/−^ mice. Data are expressed as means ± S.E.

  Parameter                WT              *HBx*Tg               *HBx*Tg*/iNOS*^−/−^
  ------------------------ --------------- --------------------- ---------------------
  Triglyceride (mg/dl)     78 ± 1.1        113 ± 2.6\*\*\*       95 ± 5.6\#\#
  Cholesterol (mg/dl)      120 ± 2.8       196 ± 3.7\*\*\*       161 ± 5.2\#\#\#
  FFA (μmol/liter)         1.156 ± 0.046   1.766 ± 0.043\*\*\*   1.964 ± 0.107
  Serum insulin (ng/ml)                                          
      Fasted               1.101 ± 0.182   0.340 ± 0.070         0.280 ± 0.015
      Fed                  1.842 ± 0.366   1.095 ± 0.235         1.010 ± 0.344
  Serum glucagon (pg/ml)   414 ± 26        535 ± 27\*            458 ± 27
  ALT (unit/liter)         41 ± 3.8        51 ± 2.8\*\*          43 ± 3.6
  AST (unit/liter)         51 ± 5.1        83 ± 7.2\*            73 ± 5.6
  HDL (mg/dl)              74 ± 4          89 ± 7\*\*            ND
  LDL (mg/dl)              7 ± 2           12 ± 3\*              ND
  Adiponectin (μg/ml)      23.3 ± 0.35     15.1 ± 0.23\*         18.9 ± 0.18\#

#### HBxTg Mice Increase Glucose Production

To further determine the role of HBx on fasting hyperglycemia and insulin resistance, we assessed basal hepatic glucose production and insulin-stimulated whole body and tissue-specific glucose fluxes in *HBx*Tg using hyperinsulinemic-euglycemic clamp studies with radioisotope-labeled glucose infusion. The basal hepatic glucose production was significantly increased by 23% in *HBx*Tg mice when compared with the WT mice ([Fig. 3](#F3){ref-type="fig"}*A*). These data clearly indicate that fasting hyperglycemia observed in *HBx*Tg mice was mostly attributed to increased hepatic glucose production because there was no difference in basal glucose clearance ([Fig. 3](#F3){ref-type="fig"}*B*). However, whole body insulin sensitivity did not differ, as reflected by no difference in glucose infusion rate ([Fig. 3](#F3){ref-type="fig"}, *C* and *D*). Moreover, there was no difference in insulin-induced suppression of hepatic glucose production and whole body ([Fig. 3](#F3){ref-type="fig"}*E*) and muscle glucose uptake ([Fig. 3](#F3){ref-type="fig"}*F*). These data suggest that HBx expression results in fasting hyperglycemia by increasing hepatic glucose production *in vivo*.

![**Whole body glucose metabolism during hyperinsulinemic-euglycemic clamp in *HBx*Tg mice.** *A* and *B*, basal and clamp hepatic glucose production (*HGP*) (*A*) and basal glucose clearance (*B*) during the clamp of WT and *HBx*Tg mice. *C* and *D*, plasma glucose concentrations (*C*) and glucose infusion rate (*D*) during the clamps. *E* and *F*, whole body glucose turnover rate, whole body glycolysis rate, whole body glycogen synthesis (*E*), and insulin-stimulated muscle (gastrocnemius) glucose uptake (*F*) were determined. *2DG*, 2-deoxy-[d]{.smallcaps}-\[1-^14^C\]glucose. All data are presented as mean ± S.E. (\*, *p* \< 0.05, *t* test, *n* = 10--11).](zbc0381174600003){#F3}

#### Changes in Glucose Metabolism and Insulin Signaling in HBxTg Mice

Gene expressions involved in glucose metabolism and insulin signaling were examined by qRT-PCR analysis (see [supplemental Table 2](http://www.jbc.org/cgi/content/full/M111.259978/DC1)) using the livers. Consistent with *in vitro* data, gene expressions of glucose metabolism-related molecules, including *PEPCK*, *G6Pase*, *PGC1*α, *FOXO1*, and *IGFBP1*, were significantly increased in the liver of *HBx*Tg mice when compared with WT mice ([Fig. 4](#F4){ref-type="fig"}*A*). These effects are independent of changes in nutritional states. *HBx*Tg mice also had increased protein levels of PEPCK, G6Pase, and PGC1α in the liver ([Fig. 4](#F4){ref-type="fig"}*B*).

![**Hepatic expression of metabolic genes in *HBx*Tg mice.** *A*, mRNA levels were quantified by qRT-PCR in 6-month-old mice on *ad libitum*-fed (*Ad lib*) and 12-h fasted states. Each PCR was carried out in triplicate. *B* and *C*, immunoblot analysis of total liver lysates obtained from *ad libitum*-fed mice. *pAkt*, phosphorylated Akt; *pJNK*, phosphorylated JNK; *pFOXO1*, phosphorylated FOXO1. *D*, IRS-1 and IRS-2-associated PI 3-kinase activity in the liver from 12-h fasted state. Tissues were collected 6 min after intravenous saline or insulin (10 units/kg (body weight)) injection. *E*, insulin signaling in liver of WT and *HBx*Tg mice. Liver lysates were subjected to SDS-PAGE and immunoblot with antibodies as indicated. *pIR*, phospho-insulin receptor; *IR*, insulin receptor. \*, *p* \< 0.05; \*\*, *p* \< 0.01; \*\*\*, *p* \< 0.001 *versus* control. \#\#, *p* \< 0.01 *versus* WT. The *bars* represent the S.E. (*n* = 4--7).](zbc0381174600004){#F4}

Basal Akt and FOXO1 phosphorylation was significantly reduced in the liver of *HBx*Tg mice, whereas basal JNK phosphorylation was increased ([Fig. 4](#F4){ref-type="fig"}*C*). The ability of insulin to increase PI3K (phosphatidylinositol 3-kinase) activity associated with IRS-1 but not IRS-2 was impaired in *HBx*Tg mice when compared with WT mice ([Fig. 4](#F4){ref-type="fig"}, *D* and *E*) without change in insulin receptor phosphorylation. Interestingly, insulin-stimulated Akt phosphorylation was normal, suggesting that maximal stimulation of Akt may not require the full activation of PI3K activity. Collectively, these data demonstrate that liver dysfunction induced by HBx may be associated with impaired PI3K activation.

#### Reciprocal Regulation in Expression between HBx and iNOS in Induction of Gluconeogenesis

Studies revealed that HBx leads to hepatic inflammation by activating *iNOS*, which can produce NO ([@B26]). It is thus important to investigate whether increased levels of NO are sufficient to increase gene expression involved in gluconeogenic pathways in the presence of HBx. Our data demonstrated that *iNOS* mRNA was significantly increased in the liver of *HBx*Tg mice when compared with WT mice, and its expression pattern was greatly similar to that of the *HBx* gene in nutritional states ([Fig. 5](#F5){ref-type="fig"}, *A* and *B*). It is therefore likely that *HBx* and *iNOS* expression is mutually regulated under a certain condition and that hyperactivation of *iNOS* may contribute to the pathogenesis of HBx-induced hepatic gluconeogenesis. Furthermore, increased *HBx* mRNA levels were seen in HepG2-*HBx* cells treated with sodium nitroprusside (SNP), an NO donor, indicating NO-mediated expression of *HBx*. In control cells, gene expression of *FOXO1* did not increase in response to SNP, whereas gene expression of *G6Pase*, *PEPCK*, and *PGC1*α was up-regulated. However, treatment of HepG2-*HBx* cells with SNP further increased the gene expression of *G6Pase*, *PEPCK*, *PGC1*α, and *FOXO1* when compared with those of control HepG2 cells ([Fig. 5](#F5){ref-type="fig"}*C*). Thus, our data suggest that gluconeogenesis genes were significantly up-regulated in *HBx*Tg mice and HepG2-*HBx* cells, indicating that NO could induce gluconeogenesis through activation of *HBx* transcription.

![**Reciprocal activation between HBx and iNOS in HepG2 cells and *HBx*Tg mice.** *A* and *B*, relative levels of *HBx* (*A*) and *iNOS* (*B*) mRNAs in *HBx*Tg mice (*n* = 6--8) in *ad libitum*-fed (*Ad lib*), 12-h fasted, and refed states. *C*, expression of *HBx* and gluconeogenic genes mRNA in cells treated with SNP (50 μ[m]{.smallcaps}) at the indicated times. All the data were the mean of three independent experiments and are indicated as mean ± S.E. (\*, *p* \< 0.05; \*\*\*, *p* \< 0.001 *versus* control. \#, *p* \< 0.05; \#\#\#, *p* \< 0.001 *versus* Mock).](zbc0381174600005){#F5}

#### Involvement of JNK1 in Induction of Gluconeogenic Genes by NO in HBx-overexpressing HepG2 Cells

To investigate whether HBx/NO-mediated JNK activation leads to increased expression of gluconeogenic genes, we measured JNK1 expression and activity after NO treatment. Our experiment showed that *JNK1* gene expression and phosphorylation were elevated by treatment of HepG2-*HBx* cells with SNP ([Fig. 6](#F6){ref-type="fig"}, *A* and *B*). The results led us to hypothesize that activation of JNK is necessary for the transcriptional regulation of gluconeogenic molecules in hepatocytes overexpressing HBx. Consistent with this hypothesis, inhibition of JNK1 signaling significantly decreased HBx-induced mRNA levels of hepatic gluconeogenic genes ([Fig. 6](#F6){ref-type="fig"}*C*). In addition, these effects were unaltered by treating HepG2-*HBx* cells transfected with *JNK1* siRNA with SNP, confirming that JNK1 is a downstream mediator of NO signaling ([Fig. 6](#F6){ref-type="fig"}*D*). Taken together, these data suggest that HBx/NO-mediated JNK activation may contribute to the up-regulation of hepatic gluconeogenic genes.

![**Involvement of JNK1 in induction of gluconeogenic genes by NO in *HBx*-expressed cells.** *A*, relative *JNK1* transcript levels of cells treated with the indicated concentrations of SNP for 48 h (\#, *p* \< 0.05 *versus* 0 μ[m]{.smallcaps}). *B*, immunoblot analysis of phosphorylated JNK (*pJNK*) in cells treated with SNP (50 μ[m]{.smallcaps}). *C*, expression profiles of metabolic genes in cells treated with *JNK1* siRNA. Levels of *JNK1* mRNA 48 h after transfection with siRNAs were evaluated by qRT-PCR and immunoblotting assays. *Scr*, scrambled. *D*, HepG2 cells were transfected with *JNK1* siRNA at 24 h before treatment with SNP (50 μ[m]{.smallcaps}) for 48 h, and the transcript levels of JNK1 and gluconeogenic genes were analyzed by qRT-PCR. \*, *p* \< 0.05; \*\*, *p* \< 0.01; \*\*\*, *p* \< 0.001. Each PCR was carried out in triplicate.](zbc0381174600006){#F6}

#### Deficiency of iNOS Normalizes HBx-induced Impaired Glucose Tolerance in Mice

We further determined whether blockade of *iNOS* signaling could prevent the ability of HBx to induce hyperglycemia and impaired glucose tolerance in mice. Toward this end, we generated *HBx*Tg mice that lacked *iNOS* gene expression by breeding *HBx*Tg mice with *iNOS*^−/−^ mice ([Fig. 7](#F7){ref-type="fig"}*A*). Elevated glucose levels in *HBx*Tg mice were normalized to the level of WT mice by a deficiency of *iNOS* in *HBx*Tg/*iNOS*^−/−^ mice ([Fig. 7](#F7){ref-type="fig"}*B*). Aligned with these findings, *iNOS* deficiency completely rescued hyperglycemia and impaired glucose tolerances that were seen in *HBx*Tg mice ([Fig. 7](#F7){ref-type="fig"}, *C* and *D*). However, plasma insulin levels in *HBx*Tg mice were unaltered by loss of *iNOS*, suggesting the specificity of iNOS action, and serum glucagon levels were lowered in *HBx*Tg/*iNOS*^−/−^ mice in the fasted state when compared with *HBx*Tg mice ([Table 1](#T1){ref-type="table"}). Moreover, hepatic glycogen levels and serum levels of triglyceride and cholesterol in *HBx*Tg/*iNOS*^−/−^ mice were restored to those of WT mice ([Fig. 7](#F7){ref-type="fig"}*E* and [Table 1](#T1){ref-type="table"}). These data strongly suggest that iNOS signaling is required for HBx-induced hepatic impaired glucose tolerance in mice.

![**Effect of iNOS on glycemic control in *HBx*Tg mice.** *A*, PCR analysis of genomic DNA from mouse tails (*HBx*Tg, 355 bp; *iNOS* wild allele, 108 bp; *iNOS* mutant allele, 275 bp). *B*, blood glucose levels in 12-h fasted and *ad libitum*-fed mice. *C* and *D*, insulin sensitivity was examined by a glucose tolerance test (*C*) and an insulin tolerance test (*D*). Mice were 6 months of age (*n* = 6--10). *E*, liver glycogen contents measured in the liver lysates of 12-h fasted and *ad libitum*-fed mice (*n* = 6). Periodic acid-Schiff stained paraffin-embedded liver sections at 6 months of age. \*, *p* \< 0.05; \*\*, *p* \< 0.01; \*\*\*, *p* \< 0.001 for *HBx*Tg *versus HBx*Tg/*iNOS*^−/−^ mice.](zbc0381174600007){#F7}

#### Reduced Expression of Metabolic Genes in HBxTg/iNOS^−/−^ Mice

The fact that deficiency of iNOS normalizes impaired glucose tolerance in *HBx*Tg mice promptly led us to investigate gene expression of glucose metabolism-related molecules in the liver of *HBx*Tg/*iNOS*^−/−^ mice. Hepatic *HBx* mRNA levels were significantly decreased in the fasted state in *HBx*Tg/*iNOS*^−/−^ mice when compared with *HBx*Tg mice ([Fig. 8](#F8){ref-type="fig"}*A*), indicating NO-dependent HBx up-regulation. Deficiency of iNOS led to a significant decrease in gene expression levels of glucose metabolism-related molecules, including *PEPCK*, *G6Pase*, *PGC1*α, *FOXO1*, *IRS1*, and *IRS2*, all of which were elevated in the liver of *HBx*Tg mice ([Fig. 8](#F8){ref-type="fig"}*B*). In addition, hepatic *JNK1* mRNA levels were significantly decreased when iNOS was deleted in *HBx*Tg mice ([Fig. 8](#F8){ref-type="fig"}*C*). Collectively, these results suggest that iNOS plays an essential role in regulating HBx-induced expression of hepatic gluconeogenic key enzymes, which could contribute to the pathogenesis of hepatic metabolic dysfunction.

![**Normalization of the expression of genes related to glucose metabolism by deficiency of iNOS in *HBx*Tg mice.** *A*, *HBx* mRNA levels were quantified by qRT-PCR in *ad libitum*-fed (*Ad lib*) and 12-h fasted states in *HBx*Tg (*n* = 6) and *HBx*Tg/*iNOS*^−/−^ (*n* = 8) mice. *B*, metabolic gene expression of 6-month-old mice in *ad libitum*-fed and 12-h fasted states. *C*, relative levels of hepatic *JNK1* gene expression in mice (*n* = 5--6). \*, *p* \< 0.05; \*\* *p* \< 0.01; \*\*\*, *p* \< 0.001 for *HBx*Tg *versus HBx*Tg/*iNOS*^−/−^ mice. \#, *p* \< 0.05 *versus* WT.](zbc0381174600008){#F8}

DISCUSSION
==========

The current study investigated the role of HBx in the regulation of hepatic glucose metabolism, specifically the impact of gluconeogenesis. Hepatic glucose production was greatly increased in *HBx*Tg liver, which is most likely due to the increased expression of gluconeogenic genes (*PEPCK*, *PGC1*α, and *G6Pase*). Ultimately, the enhanced gluconeogenesis further caused hyperglycemia in *HBx*Tg mice with age. Interestingly, nitric oxide-induced JNK activation is closely associated with the disturbed hepatic glucose metabolism. Thus, our data provide compelling evidences that HBx is an important player in regulating hepatic glucose homeostasis during the progression of chronic hepatitis-related metabolic diseases.

Inflammation has been implicated as an important etiological factor in the development of both hyperglycemia and type 2 diabetes. HBx induces the intrahepatic inflammatory process during acute and chronic hepatitis progression and HCC developments ([@B22]). Recently, we notified that HBx transactivates the *iNOS* gene promoter through the proximal NF-κB-binding site ([@B21]). Here we showed that the level of iNOS transcript was significantly increased in the liver of *HBx*Tg mice. Interestingly, *HBx* expression was also increased by treatment of HepG2-*HBx* cells with a NO donor. Moreover, the NO donor triggers induction of gluconeogenic genes in these cells. Based on these results, we suggest that the impairment in regulation of gluconeogenesis may be accelerated by the synergistic action between *HBx* and *iNOS*.

Gluconeogenesis is strongly stimulated during fasting and is aberrantly activated in type 2 diabetes. The transcriptional coactivator PGC1α was strongly induced in the liver in fasting mice and in mouse models of insulin action deficiency ([@B27]). Likewise, *PGC1*α mRNA in *HBx*Tg mice was significantly increased in the fasting state when compared with the *ad libitum*-fed state. It is interesting that *PGC1*α mRNA was more highly increased in *HBx*Tg mice than in control animals even in the state of *ad libitum*, suggesting that *HBx* modulates *PGC1*α transcription in mice.

Akt signaling has been implicated in the regulation of hepatic glucose metabolism ([@B28]). HBx-induced inflammatory stress is associated with impairment in Akt phosphorylation, which was partially mediated by the JNK pathway in hepatocytes ([@B29]). JNK is known to induce serine phosphorylation of IRS-1 and thereby reduce the activity of IRS-1 and also its downstream target, Akt. Similarly, the current study has shown that in *HBx*Tg liver, decreased Akt phosphorylation and increased JNK1 phosphorylation were observed, whereas JNK1 phosphorylation was alleviated by null mutation of iNOS. In addition, it is known that FOXO1 is mainly determined by Akt phosphorylation status ([@B30]). In general, the function of FOXO1 is closely associated with hepatic glucose homeostasis as a transcription factor governing the expression of gluconeogenic genes. Thus, impairment in regulation of FOXO1 signaling may ultimately cause imbalance of hepatic glucose metabolism. Consistent with this, FOXO1 phosphorylation was greatly reduced in *HBx*Tg liver when compared with WT mice ([Fig. 4](#F4){ref-type="fig"}*C*). Based on these observations, we suggest that HBx-driven impairment in hepatic glucose metabolism may be dependent on the cross-talk between the IRS-1/Akt/FOXO1 and JNK1 signaling pathways.

It is known that NO-mediated increase in TNF-α or free fatty acid caused suppression of insulin secretion and insulin resistance ([@B31]) and that low levels of adiponectin were associated with impaired glucose tolerance and the development of type 2 diabetes ([@B32]). Our studies found that serum adiponectin concentrations were significantly decreased in *HBx*Tg mice when compared with WT mice ([Table 1](#T1){ref-type="table"}), whereas TNF-α and free fatty acid were significantly increased (data not shown). Interestingly, deficiency of iNOS normalized the levels of serum adiponectin but not TNF-α and free fatty acid levels in *HBx*Tg mice, suggesting that adiponectin may be involved in the development of HBx-induced glucose intolerance ([Table 1](#T1){ref-type="table"}). However, it is unclear at this time whether an elevated serum insulin level is due to the direct action of HBx on insulin secretion or secondary effects. It must be further studied in the future.

Experimental evidence revealed that NO donor impaired the ability of insulin to stimulate glucose uptake in muscle cell ([@B33]) and glycogen synthesis in hepatocytes ([@B34]), indicating the inhibitory role for iNOS on insulin action. Support for this comes from the findings that NO donor administration caused hyperglycemia in mice ([@B35]). Here we demonstrated that deficiency of iNOS in *HBx*Tg mice selectively normalized serum glucose levels but not insulin levels. These effects are most likely due to the inhibition of gluconeogenesis, as indicated by the fact that increased gene expression of gluconeogenic enzymes was restored to normal levels by deletion of iNOS. Thus, iNOS plays a critical role in regulating glucose homeostasis and functions as a key determinant of HBx-induced hyperglycemia.

Based on our studies, we propose a hypothesis for the involvement of HBx in regulating hepatic glucose metabolism. Increased HBx expression by HBV causes hyperglycemia through the activation of the gluconeogenic signaling pathway. This is thought to be mediated via iNOS signaling ([Fig. 9](#F9){ref-type="fig"}). Thus, HBx functions as an important regulator of hepatic glucose metabolism that is closely associated with inflammation in hepatitis-induced liver diseases. Finally, these findings will be useful for discovery of potential treatment targets for dysregulated metabolism in HBV patients and future anti-HBV therapy.

![**A potential mechanism by which HBx leads to impaired hepatic glucose metabolism.** Induction of HBx and iNOS is mutually activated, and HBx participates in activation of the JNK1/FOXO1 signaling pathway. Coupled with PGC1α activation, FOXO1 participates in up-regulation of gluconeogenic genes, such as G6Pase and PEPCK. Thus, blood glucose level is increased, and the risk of glucose intolerance is enhanced by the impaired hepatic glucose metabolism.](zbc0381174600009){#F9}

Supplementary Material
======================

###### Supplemental Data

This work was supported by the 21st Century Frontier Program in the Functional Human Genome Project (Grant HGM0200934), by the International Collaboration Program of Science and Technology (Grant FGM0600914), by the World Class Institute (WCI) Program of the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology of Korea (MEST), by a grant from the National R&D Program for Cancer Control, Ministry for Health and Welfare (Grant BCM0061011), by the KRIBB Research Initiative Program Grant (Grant KGM3320911), by a grant of the Korea Healthcare technology R&D Project, Ministry for Health, Welfare and Family Affairs, Korea (Grant A084651) (to C. S. C.), and by National Institutes of Health Grant R01DK083567 (to Y. B. K.) and American Diabetes Association Grant 1-09-RA-87) (to Y. B. K.).

The on-line version of this article (available at <http://www.jbc.org>) contains [supplemental methods and Tables 1 and 2](http://www.jbc.org/cgi/content/full/M111.259978/DC1).

The abbreviations used are: HBVhepatitis B virusHBxhepatitis B virus X proteiniNOSinducible nitric oxide synthaseTgtransgenicPEPCKphosphoenolpyruvate carboxykinaseG6Paseglucose-6-phosphatasePGC1αperoxisome proliferator-activated receptor-γ coactivator 1αqRT-PCRquantitative real-time reverse-transcription polymerase chain reaction.

[^1]: These authors contributed equally to this work.