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 {#s1}
============

Vagal afferent neurons innervate the gastrointestinal (GI) tract, pancreas, liver, and portal vein and link peripheral levels of GI nutrients as well as circulating and stored fuels ([@bib3]). Peripheral sensory mechanisms play a crucial role in the regulation of satiation ([@bib23]; [@bib2]; [@bib15]), but mechanisms underlying vagal sensing itself are still unknown. Recently, we identified an enrichment of 'lipid sensing' nuclear receptors (NRs), including liver X receptor alpha and beta (LXRα/β) in the nodose ganglia (NG) of the vagus nerve ([@bib19]). Notably, these neurons and their processes reside outside the blood--brain barrier, enabling the potential for direct sensing of molecules released by adipose tissue or liver. LXRs are oxysterol-sensitive NRs that direct cholesterol uptake, transport, and excretion in various tissues. LXRα and LXRβ are encoded by the *Nr1h3* and *Nr1h2* genes, respectively (NR subfamily 1, group H, member 3 and 2). LXRs regulate target genes encoding for ATP-binding cassette proteins, and apolipoproteins ([@bib21a] [@bib28]; [@bib6]; [@bib4]; [@bib16]). Ligand activation of LXRs also stimulates de novo lipogenesis of triglycerides in liver via sterol regulatory element-binding protein 1c ([@bib21b] [@bib32]). Hepatic LXRα/β regulate whole lipid and glucose homeostasis, and LXRα/β in macrophages regulate inflammation ([@bib6]; [@bib22]; [@bib1]; [@bib31]). In the central nervous system, they regulate local inflammation, differentiation, and neuron survival by orchestrating cholesterol uptake and efflux ([@bib29]).

Further studies in LXR null mice revealed the rather surprising finding that these mice were resistant to obesity when challenged with a diet containing both high fat and cholesterol ([@bib17]). This study showed that the LXR^−/−^ response was due to abnormal energy dissipation resulting in part from ectopic expression of uncoupling proteins in white adipose. Here, we show that Western diet (WD)-fed mice that lack LXRα/β in sensory neurons of the NG have altered neuronal cholesterol content and increased white adipose tissue browning, leading to changes in energy expenditure and body weight. This unexpected function of LXRs in vagal sensory neurons provides a plausible mechanism that may in part explain the role LXRs on metabolism in response to a diet containing fat and cholesterol.

Results {#s2}
=======

The absence of LXRs in NAV1.8 expressing neurons disrupts *Abca1* regulation and increases NG neuronal cholesterol content {#s2-1}
--------------------------------------------------------------------------------------------------------------------------

We first assessed the effects on LXR-target gene expression following pharmacological administration of LXR agonists. Canonical LXR target genes, including ATP binding cassette protein A1 (*Abca1*) and SREBP-1c (*Srebf1*), were up-regulated in the NG of mice treated with LXR agonists ([Figure 1A](#fig1){ref-type="fig"}). These results agree with reports of expression of *Abca1* in the central nervous system (CNS) and its up-regulation in cultured neurons and sciatic nerves following LXR agonist treatment ([@bib11]; [@bib5]). Previous data have also shown SREBP-1c to be expressed in Schwann cells and CNS neurons, and LXR agonist stimulated *Srebp1f* expression has also been reported in various tissues ([@bib5]). Carbohydrate-responsive element-binding protein (*Chrebp*) expression remained unchanged in response to LXR agonist ([Figure 1A](#fig1){ref-type="fig"}).10.7554/eLife.06667.003Figure 1.LXRs signaling regulates cholesterol metabolism in nodose ganglia neurons.(**A**) Regulation of selected target genes in nodose ganglia (NG) following liver X receptor (LXR) agonist treatment in vivo (left panel) n = 5--8 per group. \*\*p \< 0.005. (**B**) NG organotypic slices were prepared from LXRs^Nav^ or LXRs^fl/fl^ treated with GW3965 (5 μM) or vehicle for 4 hr. Quantitative PCR (qPCR) data are expressed as average fold-change relative to vehicle ± S.E.M., n = 3 independent experiments. \# and \*indicates p \< 0.5, \*\*p \< 0.005. (**C**) Quantification of total cholesterol. Values were expressed as ng of cholesterol per NG, n = 6. \#\# and \*\*p \< 0.001. (right panel). Neurons isolated from LXRs^Nav^ or control mice NG were subjected to Filipin staining (representative images of staining from 3 individual mice).**DOI:** [http://dx.doi.org/10.7554/eLife.06667.003](10.7554/eLife.06667.003)10.7554/eLife.06667.004Figure 1---figure supplement 1.Ablation of LXR in the NAV1.8 positive neurons.qPCR analysis detecting the expression of truncated isoforms of *Nr1h3* (**A**) and Nr1h2 (**B**) in NG, liver, white adipose, brown adipose tissues (BATs), and muscle. Error bars show S.E.M. \*\*indicates p \< 0.01.**DOI:** [http://dx.doi.org/10.7554/eLife.06667.004](10.7554/eLife.06667.004)

These results suggest that *Abca1* and *Srepb1f* are targets of LXR in the NG. To confirm these findings, we established NG organotypic cultures from mice lacking LXRα and LXRβ in vagal sensory neurons expressing the sodium ion channel NAV1.8 encoded by the *Scn10a* gene. The resulting LXRs^Nav^ mice were generated by breeding double floxed *Nr1h3* and *Nr1h2* mice (LXRs^fl/fl^ mice) with the Nav1.8::Cre mice, which selectively expresses Cre-recombinase in peripheral sensory neurons ([@bib26]; [@bib13]). As expected, LXRα/β were deleted in the majority of NG neurons in LXRs^Nav^ mice compared to LXRs^fl/fl^ littermate controls ([Figure 1---figure supplement 1](#fig1s1){ref-type="fig"}). No difference in LXRs expression was observed in liver, white adipose tissue, brown adipose tissues (BATs), and muscle ([Figure 1---figure supplement 1](#fig1s1){ref-type="fig"}).

In LXRs^fl/fl^ controls, *Abca1* and *Srebp1f* mRNA levels increased significantly after agonist treatment. This stimulation was fully (*Abca1*) or partially (*Srebp1f*) blunted in NG from LXRs^Nav^ littermates ([Figure 1B](#fig1){ref-type="fig"}). Collectively, these results suggest that in the NG, the regulation by LXRs of *Abca1* is restricted to sensory neurons, but that its action on *Srebp1f* likely occurs in multiple cell types.

Interestingly, cholesterol assays on whole NG taken from WD (42% fat, 0.2% cholesterol)-fed LXRs^Nav^ knockout mice showed a 60% increase in total cholesterol compared to littermate controls ([Figure 1C](#fig1){ref-type="fig"}). An increase of intracellular cholesterol level was also observed in LXRs^Nav^ dispersed neurons ([Figure 1C](#fig1){ref-type="fig"}).

Collectively, our results suggest that in a WD setting, LXRs regulate NG sensory neuron cholesterol levels though ABCA1-dependent signaling. A role for ABCA1 in cholesterol, lipid distribution has previously been extensively observed in the brain ([@bib27]; [@bib30]; [@bib18]). In addition, LXR agonist or ABCA1 over-expression has been shown to alter cholesterol content in degenerating neurons or cancer cells ([@bib24]). Our results demonstrate that in sensory neurons, NG cholesterol metabolism is also regulated via LXR.

Resistance to diet induced obesity in mice lacking *LXRα/β* in *Nav1.8*-expressing neurons {#s2-2}
------------------------------------------------------------------------------------------

To measure the physiological impact of LXRs loss in peripheral sensory neurons expressing Nav1.8, LXRs^fl/fl^, LXRs^Nav^, Nav1.8::Cre were maintained for 16 weeks on a standard rodent chow diet (normal chow, NC, 4% fat) or WD. All mice had similar body weights at weaning. However, LXRs^Nav^ mice weighed significantly less than controls after 11 weeks of NC ([Figure 2A](#fig2){ref-type="fig"}). Similarly, LXRs^Nav^ mice fed WD were resistant to diet-induced obesity. NMR analysis revealed that LXRs^fl/fl^ mice had twofold more body fat after 10 weeks of WD than LXRs^Nav^ mice ([Figure 2B](#fig2){ref-type="fig"}). However, the differences in body fat do not completely reflect the body weight difference, despite no difference in lean mass ([Figure 2B](#fig2){ref-type="fig"}). WD-fed LXRs^Nav^ mice had higher energy expenditure than littermate controls ([Figure 2C,D](#fig2){ref-type="fig"}). However, no differences in food intake were noted in metabolic chambers. Furthermore, no important changes were found in plasma glucose, serum cholesterol, free fatty acids and liver triglycerides or cholesterol ([Figure 2---figure supplement 1A-F](#fig2s1){ref-type="fig"}). A decrease in adiposity in the setting of nutrient excess is sometimes due to ectopic lipid deposition in liver. However, histological examination using Hematoxylin and Eosin staining (H&E staining) showed that when fed WD, both LXRs^fl^ and LXRs^Nav^ mice developed hepatosteatosis and increase in hepatic lipid droplets ([Figure 2---figure supplement 1G](#fig2s1){ref-type="fig"}). Our results suggest that LXRs^Nav^ mice have an exacerbated response to the WD with increased diet-induced thermogenesis. This suggests that LXRs may regulate the whole-body energy expenditure according to the amount of fat or cholesterol present in the diet.10.7554/eLife.06667.005Figure 2.Ablation of LXRs from NAV1.8 expressing neurons exacerbates high-fat diet induced thermogenesis.(**A**) Body weight of LXRs^Nav^ mice and littermate controls on chow and Western Diet (WD) as followed over time (n = 12 per genotype) \* for WD, \# for normal chow (NC). (**B**) Adipose tissue as a percentage of total body weight in mice fed WD for 9 weeks, measured by NMR (n = 6). (**C**,**D**) Energy expenditure in weight-matched mice. (**C**) Calorimetry trace before and after a switch from NC to WD. (**D**) Energy expenditure during light and dark cycles before and after a switch from NC to WD. Error bars show S.E.M. \*indicates p \< 0.05.**DOI:** [http://dx.doi.org/10.7554/eLife.06667.005](10.7554/eLife.06667.005)10.7554/eLife.06667.006Figure 2---figure supplement 1.Blood chemistry and lipid levels of LXRs^Nav^ mice.Metabolite levels as measured by the UTSW metabolic core from LXRs^Nav^ and LXRs^fl/fl^ mice fed 16 weeks with NC or WD. (**A**) Glucose. (**B**) Serum cholesterol. (**C**) Fatty acid (FFA). (**D**) Serum triglycerides. (**E**) Liver triglycerides. (**F**) Liver cholesterol.**DOI:** [http://dx.doi.org/10.7554/eLife.06667.006](10.7554/eLife.06667.006)

The loss of LXRα/β in NAV1.8 positive neurons attenuates lipid accumulation in BAT, promotes browning in subcutaneous fat, and enhances mitochondrial respiration in skeletal muscle {#s2-3}
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Expectedly, we found that WD-fed control mice accumulated large lipid droplets in their BAT. Notably, this accumulation was considerably attenuated in LXRs^Nav^ mice ([Figure 3A](#fig3){ref-type="fig"}). To evaluate the BAT activity, markers for mitochondrial metabolism and thermogenesis regulation in adipose tissue were assessed by Western blot or real-time PCR. Uncoupling protein 1 (*Ucp1*) and peroxisome proliferator-activated receptor gamma coactivator 1-alpha (*Pgc1α*) were higher in LXRs^Nav^ mice BAT ([Figure 3B,C](#fig3){ref-type="fig"}). A more striking threefold UCP1 increase was observed in LXRs^Nav^ mice subcutaneous fat as assessed by immunohistochemistry (IHC) and whole fat pad Western blot ([Figure 3D,E](#fig3){ref-type="fig"}). These results suggest LXRs in sensory neurons may be important for BAT activity regulation and subcutaneous white fat conversion to a 'beige' phenotype in response to WD.10.7554/eLife.06667.007Figure 3.Adipose tissue and muscle reprogramming in LXRs^Nav^ mice vs control mice.(**A**) Immunohistochemistry for UCP1 in BAT. (**B**) UCP1 Western blot on whole BAT pads (upper panel, n = 4) UCP1 molecular weight (MW) is 33 kDa, Actin served as the loading control, MW 42 kDa, the graph represents blot quantification. (**C**) mRNA levels in the BAT of LXR ablated mice vs control mice (lower panel, n = 4). *\**indicates p \< 0.05. (**D**) UCP1 staining and (**E**) Western-blot analysis of UCP1 protein levels in whole, individual dorsal subcutaneous fat pads. Actin served as the loading control. The signal is quantified in the graph below (n = 4) Scale bar = 100 μm. (**F**,**G**) Oxygen-consumption rates were determined using the XF24 Extracellular Flux Analyzer following the manufacturers\' protocols (n = 3). *\**indicates p \< 0.01.**DOI:** [http://dx.doi.org/10.7554/eLife.06667.007](10.7554/eLife.06667.007)10.7554/eLife.06667.008Figure 3---figure supplement 1.Electron-flow experiments.Isolated skeletal muscle mitochondria were seeded at 10 μg of protein per well in XF24 V7 cell-culture microplates and analyzed with the XF24 Extracellular Flux Analyzer (n = 3).**DOI:** [http://dx.doi.org/10.7554/eLife.06667.008](10.7554/eLife.06667.008)

To establish whether sensory neuron-specific deletion of LXRs alters skeletal muscle mitochondrial respiration, we examined mitochondrial electron transport chain activity by performing mitochondrial electron-flow (EF) and electron-coupling (EC) experiments to assess oxygen-consumption rates (OCRs). During EF analyses, we observed that skeletal muscle mitochondria derived from LXRs^Nav^ mice exhibit markedly higher OCRs in response to the substrates pyruvate, malate, succinate, and ascorbate ([Figure 3F,G](#fig3){ref-type="fig"}), when compared from control mice skeletal muscle mitochondria. Furthermore, EC experiments to gage mitochondrial coupling and integrity revealed no defects in skeletal muscle mitochondrial function in either genotype ([Figure 3---figure supplement 1](#fig3s1){ref-type="fig"}). Taken together, these data indicate that deletion of LXR specifically in peripheral sensory neurons enhances skeletal muscle mitochondrial oxidative respiration.

The loss of LXRα/β in NAV1.8 expressing neurons modifies NG gene expression {#s2-4}
---------------------------------------------------------------------------

To gain more insights into the signaling downstream of LXR in NG sensory neurons, we surveyed genes important for vagal neuronal function, including: cholecystokinin A and B receptor (*Cckar* and *Cckbr*), which regulate vagal nerve activity and feeding; neuregulin 1 (*Nrg1*), involved in axon/Schwann cell communication and sensory nerve structure ([@bib12]; [@bib25]); and α, β, and γ synuclein (*Syna, Synb, Syng*), which are involved in intraneuronal trafficking/cell--cell communication and known to be LXR targets in the brain ([@bib14]). *Nrg1* and *Syng* were decreased twofold in both chow and WD-fed LXRs^Nav^ mice, interestingly *Syna* was only significantly up-regulated in control mice in response to WD ([Figure 4A](#fig4){ref-type="fig"}). Interestingly, in recent reports, γ synuclein has been linked to metabolism ([@bib21]; [@bib14]; [@bib20]). γ synuclein is a protein that modulates synaptic trafficking in neurons but also lipid droplets generating intracellular fatty acids. Notably, the γ synuclein whole body knockout is protected against diet-induced obesity ([@bib21]; [@bib20]).10.7554/eLife.06667.009Figure 4.NG gene expression in LXRs^Nav^ mice vs control mice.(**A**) Gene expression in NG from LXRs^Nav^ and control mice fed with NC or WD. (**B**) Gene expression in NG from LXRs^Nav^ and control mice fasted 20 hr or fed. All genes show a significant difference between both genotypes. *\**indicates p \< 0.05 (n = 6--10).**DOI:** [http://dx.doi.org/10.7554/eLife.06667.009](10.7554/eLife.06667.009)

Starvation reduces triglyceride levels in serum, but increases circulating fatty acids, which are rapidly taken up by the liver. To study the ability of NG to acutely respond to nutrient changes (including triglycerides and fatty acids), we studied the expression of LXR targets in the NG of fed or fasted mice. We asked whether fasting-induced increases in fatty acid availability modified NG gene expression. *Abca1*, *Srepb1f*, and *Syng* mRNA levels were significantly changed in LXRs^fl/fl^ mice fasted 20 hr ([Figure 4B](#fig4){ref-type="fig"}). Notably, the fasting-induced increase in *Abca1* and *Syng* was blunted in LXRs^Nav^ mice ([Figure 4B](#fig4){ref-type="fig"}). We also exposed NG cultures to serum obtained from mice fed or fasted for 20 hr. These data suggest that NG neurons may sense circulating secreted starvation cues and respond by regulating unique LXR-dependent genes. Despite its well-documented role in regulating the transcription of genes crucial for lipid synthesis and storage upon cholesterol sensing, little is known about how LXRs function in peripheral neurons and further investigation is necessary to completely understand the role of these NRs in the NG neurons.

Our study suggests that LXRs in vagal sensory neurons potentially regulate vagal synaptic transmission to ultimately affect the gating of information to adipose tissues and muscle. Since WAT, BAT, and muscle receive innervation from sympathetic neurons, we suspect that the increased sympathetic tone (secondary to altered input from the vagal sensory neuron activity) may underlie the increased energy expenditure observed in LXRs^Nav^ mice.

Interestingly, Kalaany et al., also described LXR null mice as resistant to obesity when challenged with a Western-style diet containing high fat and cholesterol. This phenotype was surprisingly independent of SREBP-1c and due to a net increase in the energy utilization in white adipose and muscle ([@bib17]). Our study of LXR function in NG neurons is consistent with this previous report and provides a partial explanation of how LXRs can affect the whole body thermogenesis via sensory neurons.

[@bib7], previously showed induction of LXRs in the hypothalamus in response to high-fat feeding. This finding suggests that LXRs may also regulate energy homeostasis beyond the nodose nucleus neurons.

Based on the aforementioned findings, we postulate that the LXR pathway may mediate certain aspects of lipid sensing in peripheral sensory neurons. Our findings also suggest that the ability to metabolize and sense cholesterol and/or fatty acids in peripheral neurons may be an important requirement for physiological adaptations to high-fat/high-cholesterol (Western) diets, such including thermogenesis leading to changes in key metabolic processes.

Materials and methods {#s3}
=====================

Animals {#s3-1}
-------

All 'Materials and methods' were approved by the Institutional Animal Care and Use Committee at UT Southwestern Medical Center. All mice were housed in a temperature-controlled room with a 12-hr light/dark cycle in the animal facility of University of Texas Southwestern Medical Center.

Mice were fed with either NC (\#2916, Harlan-Teklad, Madison, WI; 4.25% kcal from fat) or WD (\#88137, Harlan Teklad, cholesterol (0.2% total cholesterol), fat (42% kcal from fat), high in saturated fatty acids (\>60% of total fatty acids)). LXRs^fl/fl^ mice (floxed *Nr1h3* and Nr1h2 *genes*) on a mixed C57BL6 and 129SV background were bred and kept as a mixed background in a closed colony in UTSW germ-free facility. LXRs^fl/fl^ mice were then backcrossed to C57BL/6J mice for six generations prior to experiments. Transgenic mice (C57/BL6 background) carrying *Cre* recombinase driven by a Scn10a promoter (called Nav1.8::Cre mice) were bred with backcrossed LXRs^fl/fl^ mice. LXRs^fl/fl^ mice were bred with LXRs^fl/fl^ Nav^+/−^ to generate cohorts of littermate LXRs^Nav^ and LXRs^fl^ that were used and compared in at least three cohorts for each experiment.

We have generated cohort of Nav1.8-Cre/ tdTomato reporter mice to examine the hypothalamus. Our current findings show that tdTomato Nav1.8 expression is absent from the entire hypothalamus (Data not shown).

Body weight and composition {#s3-2}
---------------------------

Body weight was monitored weekly from weaning (at 4 weeks of age) to 28 weeks of age. In the WD studies, mice were maintained on NC until 6 weeks old before being fed WD.

Metabolic cage studies {#s3-3}
----------------------

Food intake, meal patterns, energy expenditure, and physical activity were continuously monitored using a combined indirect calorimetry system (TSE Systems GmbH, Bad Homburg, Germany). Experimental animals (11-week-old) were acclimated in the metabolic chambers for 5 days before data collection. Mice were initially maintained on NC during the acclimation period and the first two days of data collection and then fed WD for the next three days. O~2~ consumption and CO~2~ production were measured to determine the energy expenditure. In addition, physical activity was measured using a multi-dimensional infrared light bean system.

In vivo agonist treatment {#s3-4}
-------------------------

C57Bl/6 males were treated with vehicle (1% methylcellulose) and LXR agonist (10 milligram/kg body weight (mpk) GW3965), by oral gavage at 14 hr and 2 hr prior to sacrifice. NG were rapidly dissected and frozen in liquid nitrogen.

Metabolic cage studies {#s3-5}
----------------------

Metabolic parameters were continuously monitored using a combined indirect calorimetry system (TSE Systems GmbH) as described in the supplemental methods.

Data analysis {#s3-6}
-------------

The data were represented as mean ± S.E.M. Statistical analyses were performed using GraphPad PRISM version 6.0. Single comparisons were made using 1- or 2-tailed *t* tests, as appropriate, and multiple comparisons were performed using 1-way analysis of variance (ANOVA) followed by Dunnett\'s post hoc test. For repeated measures, 2-way repeated-measures ANOVA was performed, with Bonferroni post hoc tests. A p value less than 0.05 was considered significant.

Quantitative PCR {#s3-7}
----------------

Real-time quantitative PCR (qPCR) gene expression analysis was performed using inventoried TaqMan Gene Expression Assays (Applied Biosystems). 18 s was used as normalizer. TaqMan probes used for qPCR include *18 s* (ABI, Hs99999901_s1), *Adrb3* (ABI, Mm02601819_g1), C*ckar* (ABI, Mm00438060_m1), *Cckbr* (ABI, Mm00432329_m1), *Ucp1* (ABI, Mm01244861_m1), *Pgc1a* (01016719_m1), *Nrg1* (Mm01212130_m1), S*yna* (Mm01188700_m1), S*ynb* (Mm00504325_m1), S*ynb* Mm00488345_m1), *Abca1* (Mm00442646_m1), Two Sybr green-based primer sets located in the first exons of the floxed *Nr1h3* and Nr1h2 *genes* were used to specifically detect the truncated form of LXRα and β.

NG organotypic culture {#s3-8}
----------------------

Mouse pups between 8 and 11 day old were decapitated, and the NG were quickly removed and cultured in chilled Gey\'s Balanced Salt Solution (Invitrogen) enriched with glucose (0.5%) and KCl (30 mM). The NG were then placed on Millicell-CM filters (Millipore; pore size 0.4 μm) and then maintained at the air-media interface in minimum essential medium (Invitrogen) supplemented with heat-inactivated horse serum (25%, Invitrogen), glucose (32 mM), and GlutaMAX (2 mM, Invitrogen). Cultures were typically maintained for 10 days in standard medium, which was replaced three times a week. After an overnight incubation in low serum, (1.5%) MEM supplemented with GlutaMAX (2 mM), slices were stimulated with vehicle, 5 μM GW3965 for 4 hr. RNA was harvested using Acturus PicoPure RNA Extraction kit (Applied Biosystems).

Histology {#s3-9}
---------

For IHC, sections were deparaffinized and the wax at the surface was removed with xylenes. After antigen retrieval and blockage of endogenous peroxidase activity, sections were stained with primary antibodies against UCP-1 (Cat\# ab10983, Abcam) followed by biotinylated secondary antibodies (anti-rabbit; Dako, Glostrup, Denmark). Secondary antibodies were detected using a DAB chromogen A kit (Dako) following the manufacturer\'s protocol. The slides were also counterstained with Hematoxylin. Filipin staining for unesterified cholesterol was performed according to manufacturer\'s instructions (FilipinIII cholesterol detection, Abcam).

Glucose tolerance tests {#s3-10}
-----------------------

After measuring the fasting glucose levels, mice were given an i.p. dose of glucose (1.5--2 g/kg body weight). Blood glucose levels were then monitored using an AlphaTrak glucometer (Abbott Laboratories, North Chicago, IL) designed for use in rodents.

Cholesterol quantitative measurement {#s3-11}
------------------------------------

Adult tissue was resuspended in 1× lysis buffer placed on ice 30 min and homogenized in 2 ml tubes, glass bead-containing tubes. Samples were then directly used to quantify total cholesterol. The reaction was performed in 96-well plates by adding Amplex Red reagent, horseradish peroxidase, cholesterol oxidase, and cholesterol esterase (Amplex Red Cholesterol Assay Kit; Life technologies). The reactions were incubated for 30 min at 37°C. Results presented here were obtained from individual mice (n = 6).

Isolation of mitochondria from skeletal muscle tissues {#s3-12}
------------------------------------------------------

To isolate mitochondria, skeletal muscle tissues were homogenized using a motorized Dounce homogenizer in ice-cold MSHE buffer (70 mM sucrose, 210 mM mannitol, 5 mM HEPES, 1 mM EDTA) containing 0.5% FA-free Bovine Serum Albumin (BSA). Homogenates then underwent low centrifugation (800×*g* for 10 min) to remove nuclei and cell debris, followed by high centrifugation (8000×*g* for 10 min) to obtain the mitochondrial pellet, which was washed once in ice-cold MSHE buffer and was resuspended in a minimal amount of MSHE buffer prior to determination of protein concentrations using a BCA assay (Pierce).

Mitochondrial experiments {#s3-13}
-------------------------

OCRs were determined using the XF24 Extracellular Flux Analyzer (Seahorse Bioscience, MA) following the manufacturers\' protocols. For the EF experiments, isolated skeletal muscle mitochondria were seeded at 10 μg of protein per well in XF24 V7 cell-culture microplates (Seahorse Bioscience), then pelleted by centrifugation (2000×*g* for 20 min at 4°C) in 1× MAS buffer (70 mM sucrose, 220 mM mannitol, 10 mM KH~2~PO~4~, 5 mM MgCl~2~, 2 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES), 1 mM ethylene glycol tetraacetic acid (EGTA) in 0.2% FA-free BSA; pH 7.2) supplemented with 10 mM pyruvate, 10 mM malate, and 4 μM carbonyl cyanide 4-(trifluoromethoxy)phenylhydrazone (FCCP) (for EF experiments), with a final volume of 500 μl per well. For EC experiments, 1× MAS buffer was supplemented with 10 mM succinate and 2 μM rotenone. The XF24 plate was then transferred to a temperature-controlled (37°C) Seahorse analyzer and subjected to a 10-min equilibration period and 2 assay cycles to measure the basal rate, comprising a 30-s mix, and a 3-min measure period each; and compounds were added by automatic pneumatic injection followed by a single assay cycle after each; comprising a 30-s mix and 3-min measure period. For EF experiments, OCR measurements were obtained following sequential additions of rotenone (2 μM final concentration), succinate (10 mM), antimycin A (4 μM), and ascorbate (10 mM) (the latter containing 1 mM N,N,N′,N′-tetramethyl-p-phenylenediamine \[TMPD\]). For EC experiments, OCR measurements were obtained post sequential additions of ADP (4 mM), oligomycin (2 μM), FCCP (4 μM), and antimycin-A (2 μM). OCR measurements were recorded at set interval time-points. All compounds and materials above were obtained from Sigma--Aldrich.

Funding Information
===================

This paper was supported by the following grants:

-   http://dx.doi.org/10.13039/100000002National Institutes of Health (NIH) R01DK088423 to Joel K Elmquist.

-   http://dx.doi.org/10.13039/100000002National Institutes of Health (NIH) R37DK053301 to Joel K Elmquist.

-   http://dx.doi.org/10.13039/100000002National Institutes of Health (NIH) R01DK55758 to Philipp E Scherer.

-   http://dx.doi.org/10.13039/100000002National Institutes of Health (NIH) U19DK062434 to David J Mangelsdorf.

-   http://dx.doi.org/10.13039/100000011Howard Hughes Medical Institute (HHMI) to David J Mangelsdorf.

-   http://dx.doi.org/10.13039/100000002National Institutes of Health (NIH) R01DK099110 to Philipp E Scherer.

We thank the UTSW Mouse Metabolic Phenotyping Core (NIH PL1 DK081182, UL1 RR024923). This work was supported by NIH grants R01DK088423 and R37DK053301 (to JKE), R01DK55758 and R01DK099110 (to PES), P01DK088761 (to PES and JKE), NURSA grant U19DK062434 (to JKE and DJM), GM007062 (to ALB); the Robert A. Welch Foundation (grant I-1275 to DJM); and the Howard Hughes Medical Institute (DJM).

Additional information {#s4}
======================

JKE: Reviewing editor, *eLife*.

The other authors declare that no competing interests exist.

VM-A, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article.

LG, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article.

SL, Conception and design, Analysis and interpretation of data, Drafting or revising the article.

DJM, Conception and design, Analysis and interpretation of data, Drafting or revising the article.

JKE, Conception and design, Analysis and interpretation of data, Drafting or revising the article.

ALB, Conception and design, Acquisition of data, Analysis and interpretation of data.

KS, Conception and design, Acquisition of data, Analysis and interpretation of data.

YZ, Conception and design, Acquisition of data, Analysis and interpretation of data.

CMK, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article, Contributed unpublished essential data or reagents.

PES, Conception and design, Drafting or revising the article.

Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols (2012-0206) of UTSW. The protocol was approved by the Committee on the Ethics of Animal Experiments of UTSW. Every effort was made to minimize suffering.

10.7554/eLife.06667.010

Decision letter

Tontonoz

Peter

Reviewing editor

Howard Hughes Medical Institute, University of California, Los Angeles

,

United States

eLife posts the editorial decision letter and author response on a selection of the published articles (subject to the approval of the authors). An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent (see [review process](http://elifesciences.org/review-process)). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.

Thank you for sending your work entitled "Loss of LXRα/β in Peripheral Sensory Neurons Modifies Energy Expenditure" for consideration at *eLif*e. Your article has been favorably evaluated by a Senior editor and three reviewers, one of whom is a member of our Board of Reviewing Editors.

The Reviewing editor and the other reviewers discussed their comments before we reached this decision, and the Reviewing editor has assembled the following comments to help you prepare a revised submission.

The reviewers were in agreement that the work was novel and potentially of interest to the readers of *eLife*. All of the reviewers felt that the delineation of a role for sensory nerve metabolism in control of systemic physiology was exciting.

At the same time, the review process identified a few opportunities to strengthen the work.

1\) Some of the reviewers felt that the observed effect on browning was modest and that it would be important to consider the potential contribution of muscle to the energy expenditure phenotype. Is there evidence of increased fatty acid uptake and oxidation?

2\) The suggestion that LXRs sense changes in fatty acid levels is provocative, but not currently supported by data. The authors could address whether LXR target gene expression in sensory neurons change during fasting/refeeding. Additional discussion of how this might be accomplished would also be useful.

Minor comments:

1\) Please confirm that the knockout mice employed have been appropriately backcrossed to a common genetic background. Genetic background and degree of backcrossing should be indicated clearly in Methods.

10.7554/eLife.06667.011

Author response

*1) Some of the reviewers felt that the observed effect on browning was modest and that it would be important to consider the potential contribution of muscle to the energy expenditure phenotype. Is there evidence of increased fatty acid uptake and oxidation*?

First, as suggested we changed the title to "Loss of the Liver X Receptor LXRα/β in Peripheral Sensory Neurons Modifies Energy Expenditure''.

The reviewers suggested that we study the potential contribution of muscle to the energy expenditure phenotype. To establish whether peripheral sensory neuron-specific deletion of LXRs alters skeletal muscle energy expenditure, we examined mitochondrial electron transport chain activity by performing mitochondrial electron-flow and electron-coupling experiments to assess oxygen- consumption rates (OCRs), a previously validated method used to quantify mitochondrial oxidative capacity and integrity (Kusminski CM NatMed 2012; Rogers GW PLoS ONE 2011). Interestingly, during the electron-flow analyses, we observed that skeletal muscle mitochondria derived from knockout (LXRs^Nav^) mice exhibit markedly higher oxygen-consumption rates (OCRs) in response to the substrates pyruvate, malate, succinate and ascorbate (revised version [Figure 3F-G](#fig3){ref-type="fig"}). Furthermore, electron-coupling experiments to gage mitochondrial coupling and integrity revealed no defects in skeletal muscle mitochondrial function in either genotype (revised [Figure 3--figure supplement 1](#fig3s1){ref-type="fig"}). We thank the reviewers for this excellent suggestion. The data described in the revised article (Results section) indicate that deletion of LXR specifically in neuronal nodose ganglion enhances skeletal muscle mitochondrial oxidative respiration.

*2) The suggestion that LXRs sense changes in fatty acid levels is provocative, but not currently supported by data. The authors could address whether LXR target gene expression in sensory neurons change during fasting/refeeding. Additional discussion of how this might be accomplished would also be useful*.

The reviewers also inquired whether LXR target gene expression in sensory neurons change during fasting/refeeding. As suggested, we used a new cohort of littermate mice to study whether fasting-induced increases in fatty acid availability potentially modified nodose ganglia gene expression. We found that *Abca1*, *Srepb1c* and Synuclein mRNA levels were significantly changed in LXRs^fl/fl^ mice that were fasted for 20 hours (see revised [Figure 4B](#fig4){ref-type="fig"}). Notably, this increase in fasted *Abca1* and Synuclein was blunted in LXRs^Nav^ mice (revised [Figure 4B](#fig4){ref-type="fig"}). These in vivo data suggest that nodose ganglia neurons may sense circulated or secreted cues during starvation and respond by regulating unique LXR-dependent genes.

Despite its well-documented role in regulating the transcription of genes crucial for lipid synthesis and storage upon cholesterol sensing, little is known about how LXRs function in peripheral neurons and further investigations will be necessary to completely understand the role of these NRs in the nodose ganglia neurons. Our study suggests that LXRs in vagal sensory neurons potentially regulate vagal synaptic transmission, ultimately affecting the gating of information to adipose tissues and muscle. Since WAT, BAT and muscle receive innervation from sympathetic neurons, we suspect that the increased sympathetic tone---that is secondary to altered input from the parasympathetic vagal sensory neuron activity---may underlie the increased energy expenditure observed in LXRs^Nav^ mice. These results and discussion were added to the revised manuscript (please see the subsection "The loss of LXRα/β in Nav1.8 expressing neurons attenuates lipid accumulation in brown adipose tissue, promotes browning in subcutaneous fat and modifies NG gene expression"). We also added a section detailing the mitochondrial studies to the Methods and made legend modifications.

*Minor comments*:

*1) Please confirm that the knockout mice employed have been appropriately backcrossed to a common genetic background. Genetic background and degree of backcrossing should be indicated clearly in Methods*.

As asked, we have detailed the genetic background of the mice in the Methods section. LXR^fl/fl^ mice (on a mixed C57BL6 and 129SV background) were bred and kept as a mixed background in a closed colony in the UTSW germ-free rodent facility. LXRs^fl/fl^ mice were then backcrossed to C57BL/6J mice for six generations prior to experiments. Transgenic mice (C57/BL6 background) carrying *Cre*-recombinase driven by a Nav1.8 promoter (Nav1.8::Cre) were bred with backcrossed to the LXRs^fl/fl^ mice. LXRs^fl/fl^ mice were then bred with LXRs^fl/fl^ Nav^+/-^ mice to generate at least 3 cohorts of littermate LXRs^Nav^ and LXRs^fl^ mice that were used and compared in each of the respective experiments.