Promoted energy expenditure -
To investigate the metabolic phenotypes arising from loss of adipocyte PU. RPA analysis of down-regulated genes displayed an enrichment of pathways involved in extracellular matrix and immune signaling, including interleukin signaling Figure 4B. Consistent with this, genes with well documented roles in these processes Il1rn , Il10ra , Il1b , Ccr1 , Ccl6 were highly repressed in aPU.
These results were consistent with our previous findings of the roles of PU. FIGURE 4. RNA-sequencing Analysis of Gene Expression Changes in the aPU. A Volcano plot showing gene expression changes in adipocytes isolated from the gonadal adipose tissue, with key genes of interest highlighted in yellow.
We next set out to identify direct PU. Signaling Pathways Project SPP consensomes are ranked consensus transcriptional signatures for signaling pathway nodes—receptors, enzymes, transcription factors and other nodes—computed from publicly archived omics datasets Ochsner et al.
As such, consensomes have value in identifying potential high confidence transcriptional targets HCTs for specific nodes or node families in a given biological system Ochsner et al. To gain insight into members of the PU.
We interpreted the size and significance of these intersections as evidence for loss or gain of function of a given signaling node or node family in aPU. Figure 5A shows a heatmap displaying selected intersections between the aPU.
To assist in identifying candidate aPU. As an objective validation of our analysis, we benchmarked it against a list of 16 proteins identified by BioGRID Oughtred et al. Figure 5B shows a regulatory footprint plot, in which signaling nodes that have significant HCT footprints with aPU.
In this plot, nodes that have the most highly enriched and significant regulatory footprints are located towards the top right of the plot. Reflecting the reliability of our predictions, the 16 BioGRID-sourced PU. In addition to the expected prominent footprint for PU.
For example, robust intersections of aPU. Similarly, the increased energy expenditure of the aPU. Moreover, reflecting adrenergic stimulation of thermogenesis Collins and Surwit, as well as repression of inflammatory cytokines Ağaç et al.
FIGURE 5. High Confidence Transcriptional Target HCT Intersection Analysis Identifies PU. A HCT intersection Q-values INT Q for selected signaling pathway nodes or node families are indicated in the form of a heatmap. HCT intersection analysis was carried out as described in the Methods section.
The intensity of the color scheme is proportional to the confidence of the intersection between high confidence transcriptional targets HCTs for a particular node and either i aPU.
Lower confidence smaller Q intersections are towards the yellow end of the spectrum and higher confidence larger Q intersections are towards the red end of the spectrum. Full numerical data are in Supplementary Table S2. B Scatterplot showing enrichment of known BioGRID-curated PU.
Refer to the text for details. Similarly, in the ChIP-Seq HCTs, robust intersections of aPU. Given our previous report that PU. Congruent with our metabolic studies of aPU. Strikingly , four nodes with known roles in circadian rhythms Clock Debruyne, , 1.
In addition to corroborating canonical PU. For aPU. Similarly, for aPU. Some of the intersections may be attributable to transcriptional induction or repression of their encoding genes in the absence of PU.
For example, the footprint for Cebpa in the PU. Similarly, the footprints for Irf5, Irf8, Mafb and Mef2c in the aPU. The vast majority of nodes that had significant HCT intersections with aPU. Collectively these data indicate repressive, protein-level cross-talk of PU. We previously showed that PU.
With that in mind, our RNA-Seq analysis highlighted numerous aPU. We next wished to adopt a reduced-bias approach to explore this possibility in more detail. Using our previously-described consensome algorithm Ochsner et al. We first benchmarked the 3T3-L1 adipogenesis consensome against a set of genes designated as hallmark adipogenesis-induced transcripts by the GSEA Subramanian et al.
Many of the aPU. Interestingly, numerous aPU. FIGURE 6. The mouse 3T3-L1 adipogenesis transcriptomic consensome ranks mouse genes based on their discovery rates across five independent, publicly archived 3T3-L1 adipogenesis transcriptomic datasets. Hypergeometric test odds ratio and associated p -value are indicated in each panel.
A Validation of the 3T3-L1 adipogenesis consensome against the GSEA adipogenesis Hallmark gene set. B Over-representation of aPU.
C Over-representation of aPU. D Correlation between aPU. TABLE 1. Selected PU. To focus on direct aPU.
Consistent with broad, direct antagonism by PU. Further reflecting the role of aPU. Figure 6D. Studying these 51 genes further, we identified two prominently pro-adipogenic members of the 3T3-ADIPICTs subset, Srebf1 encoding SREBP1 and Nr1h3 encoding LXRα , that have not been previously appreciated as direct PU.
Similarly, uncharacterized candidate direct PU. Collectively, our in vivo analysis confirms and adds value to previous in vitro studies implicating PU. To make full use of the adipogenesis consensome for hypothesis generation around aPU. For each gene in Supplementary Table S3 therefore, column U links to an SPP website interface showing the specific experimental data points for that gene from the 3T3-L1 adipogenesis expression profiling datasets.
In addition, the interface includes data points from transcriptomic experiments in mouse adipose tissue or cell lines involving genetic or small molecule perturbation of various receptor and enzyme signaling nodes, as well as data points from metabolic challenges such as cold exposure.
For insight into nodes directly regulating expression of genes in the adipogenesis consensome, Supplementary Table S3 column V links to an interface showing data points from ChIP-Seq experiments carried out in mouse adipose tissue or cell lines.
Data points in both the transcriptomic and ChIP-Seq interfaces link to contextual pop-up windows, which in turn point to the full source datasets on the SPP website.
Given the global transcriptional repression of cytokine production in aPU. Since aPU. Consistent with this hypothesis, Q-PCR analysis identified transcriptional induction in aPU.
These results suggest a molecular mechanism underlying PU. FIGURE 7. Loss of PU. B Brown adipose tissue mRNA expression of PGC-1α and UCP1 and TNFα were measured using real-time RT-PCR. The Mammalian Phenotype Ontology MPO Smith and Eppig, , uses evidence from the research literature to assign specific metabolic and physiological functions to the products of mouse genes.
As such, MPO annotations represent a potentially powerful approach to inferring the metabolic impact of transcriptional regulatory networks in the aPU. Given the increased energy expenditure of aPU. To do this we examined the intersection between nodes that had significant intersections with aPU.
Consistent with the increased energy expenditure in the aPU. These nodes included the nuclear receptors Pparg Kubota et al. FIGURE 8.
Mammalian Phenotype Ontology Analysis Of Nodes With Significant HCT Intersections With aPU. Please refer to the Methods for details of the analysis. Next, to identify potential transcriptional mediators of thermogenic gene expression in the aPU. Consistent with the induction of BAT thermogenic genes in the aPU.
These included the nuclear receptor Pparg Imai et al. Collectively these data indicate that a non-redundant role for PU. Node HCT intersection analysis had previously indicated that numerous inflammatory transcription factors with roles in cytokine production were functionally impacted by the loss of PU.
To gain insight into the PU. Reflecting transcriptional repression of numerous inflammatory cytokine genes in the aPU. These included members of the IRF Irf3, Irf5 , STAT Stat1, Stat6 and AP-1 Jun, Junb transcription factor families, as well as Fosl1, Cebpd and Nfkb1.
Collectively these data indicate that PU. We showed that aPU. To gather evidence for the specific signaling nodes contributing to this phenotype, we compared nodes that had significant intersections in aPU. Consistent with improved glucose homeostasis in the aPU. Confirming the link between improved glucose tolerance and energy expenditure, these included the five previously identified AEE nodes Pparg, Ppara, Clock, Arntl and Cebpa , in addition to Foxa1.
In this study, we set out to investigate the role of the transcription factor PU. We observed that although young 4—5 months aPU. Moreover, at around 1 year of age, aPU. Mechanistically, and consistent with their elevated energy expenditure, we found that loss of adipocyte PU.
Consistent with the enhanced energy expenditure of aPU. This represented strong evidence, validated by subsequent Q-PCR analysis Figure 7A , that PU. To afford insight into the functional pathways involved, Supplementary Table S2 column L indicates aPU.
Many of these are familiar players in cellular energy metabolism that have emerged from studies in the research literature.
The induction of Ndufb6 , Ndufb10 and Ndufs6 , for example, reflects our finding from RPA analysis that respiratory electron transport chain pathway genes were enriched among aPU. Moreover, upregulation of the transferrin Trf gene may reflect potential endocrine or paracrine signaling from the white adipocytes to activate brown or beige adipocyte thermogenesis in aPU.
This is the case with genes such as Blcap , Gkap1 , Proca1 and others, for which, as aPU. Supporting this assertion, and confirming the clinical relevance of our study, the human ortholog of Fam13a aPU.
In summary, we conclude that activation of PGC-1 family signaling in aPU. Transcriptomic analysis has cast PU. Although transcriptional induction by PU. Building on our previous study showing that PU. Since inflammation is a key mediator for insulin resistance and metabolic syndrome Hotamisligil, , suppression of this inflammatory transcriptional program likely contributes to the phenotypes of the aPU.
Going to the underlying mechanism, we found that the expression levels of many proinflammatory cytokines driven by the PU.
IL signaling, which has been shown to inhibit thermogenesis and energy expenditure in adipocytes Rajbhandari et al. Members of the NOD-like family of receptors have prominent roles in the transcriptional regulation of inflammasome pathways. Our transcriptomic analysis identified significant down-regulation of genes encoding two members of the NOD-like family, Ciita and Nrpl3, in aPU.
Similarly, consistent with the strong TLR regulatory footprint in the aPU. Given that TLRs Kim et al. On a broader scale, HCT intersection analysis Figure 5A , validated by integration with literature-based mouse phenotype annotations Figure 8C , reflects the profound impact of loss of PU.
For example, aPU. Given that the roles of members of the IRF family in the regulation of adipogenesis, inflammation and thermogenesis in adipocytes are well-documented Eguchi et al. On the other hand, transcription factors that suppress inflammatory gene expression, such as PPARγ Lefterova et al.
Given that we observed evidence for activation of both PPAR and LXR in response to aPU. A unique aspect of our RNA-Seq dataset is that rather than limiting it to a standalone analysis of aPU.
Annotation of aPU. Similarly, HCT intersection analysis Figure 5 and Supplementary Table S2 affords a unique perspective on the various receptors, enzymes, transcription factors and co-nodes that are functionally impacted by PU. Finally, the adipose-centric SPP transcriptomic and ChIP-Seq Regulation Reports to which the 3T3-L1 adipogenic consensome Supplementary Table S3 links provide the user with a rich, contextual perspective to generate hypotheses around transcriptional regulation of novel effectors of adipose tissue biology.
By integrating these three data resources in a single study, we provide for a unique perspective on PU. The collective value of our supplementary material to researchers in generating novel metabolic hypotheses can be illustrated with reference to Gpr , identified in Supplementary Table S1 as a gene encoding a member of the G protein-coupled receptor family that is strongly transcriptionally dependent upon PU.
With the exception of a role in the regulation of circadian clock in the suprachiasmatic nucleus Doi et al. The SPP transcriptomic Regulation Report for Gpr Supplementary Table S3 column U contains data points documenting its regulation by prominent regulators of lipid metabolism, including FGF21, PPARG and members of the PGC-1 family.
Similarly, the ChIP-Seq Regulation Report Supplementary Table S3 column V provides evidence for direct regulation of Gpr by PU. Finally, the enrichment among aPU. Set in the context of existing evidence documenting circadian connections between adipose tissue biology, lipid metabolism and the immune system Krueger and Feldman, ; Lekkas and Paschos, ; Lananna and Musiek, , the SPP data points suggest a hypothesis implicating PU.
Indeed, such a notion is supported by a previous report of global enhancement of PU. The recent characterization of PU. Interestingly, RPA identified a strong repression in the aPU. Inspecting the aPU. Most intriguingly of all perhaps, aPU.
MUP proteins are related to members of the lipocalin family, which have documented connections to a variety of fibrotic conditions Eichler et al. Collectively, our analysis data point to a pivotal role for PU. Taken together, our transcriptome and bioinformatics analyzes provide valuable insights into the action of PU.
However, we need to validate these leads with a larger set of samples in follow-up studies. Our observation that PU. Metabolic changes developed during the aging process share similarities with that caused by obesity, but also possess some unique characteristics Bapat et al.
The underlying mechanism is not well characterized. A recent study identified a sub-population of adipocytes present only in the subcutaneous adipose tissue of older mice or humans Nguyen et al.
These cells have elevated PU. This finding is in agreement with our results, supporting an important role of PU. As an adipocyte-specific knockout, our model underscores the contribution of adipocyte-autonomous functions of PU.
However, PU. For example, expression of hepatic PU. Depletion of PU. Taken together, PU. Therefore, PU. The datasets presented in this study can be found in online repositories. The animal study was reviewed and approved by the Institution of Animal Care and Use Committee at Baylor College of Medicine.
Conceptualization: QT Investigation: KC, AD, XG, and WP. Validation: EL and DS. Formal analysis: AM, SO, and NM. Writing and editing: QT, AM, YS, and NM. Funding acquisition: QT and NM. This work was supported by a US Department of Agriculture grant , NIH DK and AHA 18TPA to QT, by NIH DK to NM, and by the DKNET Summer of Data student internship, supported by DK to AM.
These sponsors play no role in study design; in data acquisition, analysis and interpretation; in the writing of the manuscript; and in the decision to submit for publication. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers.
Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. We would also like to thank Marta Fiorotto and Firoz Vohra for help with the measurement of energy expenditure of mice.
Adipoq, adiponectin; GTT, glucose tolerance test; HCT, high confidence transcriptional targets; ITT, insulin tolerance test; LPS, lipopolysaccharide; MPO, Mammalian Phenotype Ontology; PGC-1, PPARG coactivator 1; RPA, Reactome Pathway Analysis; SPP, Signaling Pathways Project.
Ağaç, D. The β2-adrenergic Receptor Controls Inflammation by Driving Rapid IL Secretion. Brain Behav. PubMed Abstract CrossRef Full Text Google Scholar. Download references. We thank S. Iwasaki, A. Izumi, T. Taniguchi, K. Sakai, G. Tsujimoto, Y. Kawamata, H. Overmars, T. Sorg, M. Champy and the staff of the Institut Clinique de la Souris for technical assistance and discussions.
We also thank Seahorse Bioscience for the collaborative studies of oxygen consumption and extracellular acidification rate in the human skeletal myocytes. Work in the laboratories of the authors is supported by grants from CNRS, INSERM, ULP, FRM, the Hôpital Universitaire de Strasbourg, the NIH, EMBO and the EU.
Author Contributions M. and S. were involved in project planning, experimental work and data analysis; C. and K. performed experimental work; and A. and J. were involved in project planning and data analysis.
Mitsuhiro Watanabe, Sander M. Department of Medicine, Thyroid Section, Division of Endocrinology, Diabetes and Hypertension, Brigham and Women's Hospital and Harvard Medical School, Massachusetts, , Boston, USA.
Marcelo A. Christoffolete, Brian W. Kim, John W. Division of Clinical Nutrition, National Institute of Health and Nutrition, Toyama, , Shinjuku-ku, Tokyo, Japan. Laboratory for Systems Biology and Medicine, RCAST, University of Tokyo, , Tokyo, Japan.
Institut Clinique de la Souris, , Illkirch, France. You can also search for this author in PubMed Google Scholar. Correspondence to Johan Auwerx. Reprints and permissions information is available at npg. The authors declare no competing financial interests.
This file contains Supplementary Tables 1 and 2, Supplementary Methods and Supplementary Figure Legends. DOC 59 kb. a , Hematoxylin and eosin stained epWAT and BAT sections in animals treated with the indicated diets. PDF kb. Reprints and permissions.
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Skip to main content Thank you for visiting nature. nature letters article. Abstract While bile acids BAs have long been known to be essential in dietary lipid absorption and cholesterol catabolism, in recent years an important role for BAs as signalling molecules has emerged.
Access through your institution. Buy or subscribe. Change institution. It took no more than five attempts to achieve 1-RM with any subject. Verbal incentive was given throughout the tests.
All test sessions were supervised by the research team to be considered valid Table 2. Assessment of energy expenditure.
Before the data collection procedures, all participants underwent a two-week familiarization period during each exercise with the equipment mask for blood gas analysis Fitmate ® Cosmed using sufficient load to perform a set of 20 repetitions. EE during the ST sessions was measured using a blood gas analyzer COSMED ® , Fitmate, Rome, Italy with flexible gas mask, according to previous publications.
Lee JM, Bassett Jr DR, Thompson DL, Fitzhugh EC. Validation of the cosmed fitmate for prediction of maximal oxygen consumption. Nieman DC, Lasasso H, Austin MD, Pearce S, McInnis T, Unick J.
Validation of cosmed's fitmate in measuring exercise metabolism. Res Sport Med. Yavelberg L, Zaharieva D, Cinar A, Riddell MC, Jamnik V. A Pilot study validating select research-grade and consumer-based wearables throughout a range of dynamic exercise intensities in persons with and without type 1 diabetes: a novel approach.
J Diabetes Sci Technol. All participants were instructed not to drink coffee for 12 hours before the assessments, and not to exercise for 24 hours before the assessment.
The blood gas analyzer was calibrated according to the manufacturer's specifications before each test. Following the calibration of the portable Fitmate unit, participants were equipped with a face mask held in place by a helmet. While the participants exhaled, an oxygen flowmeter and sampling line, coupled to the mask, collected data that included respiratory rate, air volume, and fractional oxygen concentration.
The Fitmate metabolic unit calculated oxygen consumption VO 2 internally, with each breath taken by the participants. Accordingly, VO 2 was measured continuously adding effort and recovery.
For the EE analysis considering the anaerobic energy system, we used the model suggested by SCOTT et al. Scott CB, Leighton BH, Ahearn KJ, McManus JJ. Aerobic, anaerobic, and excess postexercise oxygen consumption energy expenditure of muscular endurance and strength: 1-set of bench press to muscular fatigue.
In short, lactate concentration was determined using a lactimeter model Accusport Plus - Roche ® , following the recommendation of previous studies. Hunter GR, Byrne NM, Sirikul B, Fernández JR, Zuckerman PA, Darnell BE, et al. Resistance training conserves fat-free mass and resting energy expenditure following weight loss.
Obesity Silver Spring. Heden T, Lox C, Rose P, Reid S, Kirk EP. One-set resistance training elevates energy expenditure for 72 h similar to three sets. Finger capillary blood samples were collected before the protocol i. Control of external training load.
The most basic method for quantifying strength training is the repetition method for determining training volume. The repetition method is simply the total number of repetitions performed in a specific exercise: a training session Eq.
The total weight lifted is an extension of the repetition method. It involves multiplying the number of repetitions performed for a given exercise by the absolute load lifted for those repetitions. In this manner, the training load Table 3 for each different exercise performed in a training session can then be added up to calculate the total weight lifted and the training duration Eq.
The analysis of sample size was performed using GPower 3. Eng J. Sample Size Estimation: How Many Individuals Should Be Studied?
Faul F, Erdfelder E, Lang AG, Buchner A. Therefore, 15 subjects were designated to undergo ST at different intensities. Repeated ANOVA measures were used to analyze energy expenditure values 8 exercises x 3 intensities , with Bonferroni's post-hoc test also employed when necessary.
Assumptions of normality, homogeneity and sphericity were confirmed by Shapiro-Wilk, Levene and Mauchly tests, respectively.
The paired Student's t test was used to analyze differences between the means of two sets of related scores, while the Wilcoxon test was applied for variables that did not satisfy the criteria for normality.
Razali NM, Wah YB. Power comparisons of shapiro-wilk , kolmogorov-smirnov, lilliefors and anderson-darling tests. J Stat Model Analytics. Pearson's linear correlations were used to verify associations. The generalized eta squared η G 2 was used as the effect size and interpreted according to Bakeman.
Bakeman R. Recommend effect size statistics for repeated measure designs. Behav Res Methods. The data were processed using R software in version 1. There was no significant difference in the duration minutes of the multi joint vs. When comparing only the multi joint session, we observed significant differences in the volume of repetitions F 2.
Conversely, when we observed the single joint session alone, there was a significant difference only in the total weight lifted F 2. There were no significant differences in the repetition volume when we compared the total volume between multi joint vs. single joint sessions.
However, there were significant differences in the multi joint session when compared with the single joint session in the variables total weight lifted and training load Table 3.
Significant differences in EE were observed between the different intensities in the multi joint F 2. We also observed a significant increase in EE in the multi joint session when compared with the single joint session at all intensities Table 4. The objective of this study was to compare EE of the ST session associated with the number of joints involved in movement at different intensities in the ST.
Our initial hypothesis of the study was confirmed; there was an increase in EE at high intensity and in multi joint sessions. The multi joint ST session showed an increase in EE when compared to the single joint session at all ST intensities. In this context, the order of exercises, 2 2. the number of joints involved in movement, and the size of the muscle group can significantly increase EE.
Previous studies 2 2. Acute oxygen uptake and resistance exercise performance using different rest interval lengths: The influence of maximal aerobic capacity and exercise sequence.
believe that some acute training variables have a greater positive or negative influence on EE. In this context, we chose to equalize the total number of repetitions volume of the training program, and to investigate the effect of intensity and the number of joints involved in movement multi joint and single joint.
Thus, the limitation of the study was the impossibility of equalizing the other variables. When ST is performed at high intensity weight in kg lifted , it precludes a high number of repetitions, thereby entailing an increase in the number of sets and recovery intervals between sets.
At the same time, the increase in the training session duration will result in a reduction of the training load. However, there was an increase in the session duration and the total weight lifted. On the other hand, the training load, which is the combination of ST variables volume and intensity , was significantly reduced.
To this end, Farinatti et al. investigated the order of strength exercises in EE. Two protocols were performed: sequence A from multi joint to single joint and sequence B from single joint to multi joint in the following exercises: bench press multi joint , shoulder development multi joint , and triceps extension single joint.
The main conclusions indicated that the acute performance was significantly affected by the exercise order, but, in general, EE was not affected by the exercise order.
Subsequently, Farinatti et al. observed the influence of the muscle group size on EE. The protocol was randomized in five sets, 10 repetitions, with a load corresponding to 15 repetitions maximum, in two leg-press LP and bench press BP exercises.
The results showed that EE was significantly influenced by the muscle mass involved in the exercise kcal in the LP and kcal in the BP exercises. Ratamess et al.
investigated the relationship between maximal oxygen consumption in ST and the acute metabolic effects of the exercise sequence. The results showed a tendency towards an increase in oxygen consumption when the squat exercise was performed first, i.
Therefore, there are countless possibilities for combinations between the variables of volume and intensity that can increase or reduce EE. In this context, the order of exercises 2 2. and the number of joints involved in movement as well as muscle group size can significantly increase EE.
Studies 3 3. Reis VM, Garrido ND, Vianna J, Sousa AC, Alves JV, Marques MC. Energy cost of isolated resistance exercises across low- to high-intensities.
PLoS One. indicate that training volume has been one of the main determinants of EE during ST sessions. Thus, considering the studies available in the literature, it is possible to consider a significant increase in EE in protocols with high volume when compared to low training volume with other acute training variables, such as recovery intervals, speed of movement or training intensity.
Promoted energy expenditure Promoter for visiting nature. Pro,oted are Promoted energy expenditure a browser version with limited support for CSS. To Promotedd the best experience, we recommend you use a more up to date browser Promoted energy expenditure turn Hydration and cardiovascular health in youth compatibility mode in Enerrgy Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Obesity occurs when excess energy accumulates in white adipose tissue WATwhereas brown adipose tissue BATspecialized for energy expenditure through thermogenesis, potently counteracts obesity. Factors that induce brown adipocyte commitment and energy expenditure would be a promising defence against adiposity. Furthermore, Lgr4 ablation potentiates brown adipocyte differentiation from the stromal vascular fraction of epididymal WAT, partially through retinoblastoma 1 gene Rb1 reduction. Despite longstanding recognition of the benefits of a Promoed active Promoter, there remains ambiguity regarding exactly how much expnediture should be promoted to raise Preventing and repairing signs of aging energy expenditure TEE and Mental strength development health. This review provides Energy metabolism and antioxidants brief summary of expenviture dose-response relationship between physical activity Promoteed relative risk of morbidity and mortality; mechanisms through Nutrition myths and misconceptions exercise drives an increase in TEE; the highest reported levels of TEE measured via doubly labelled water; and the potential impact of non-compliance and confounders in moderating the contribution of exercise to increase TEE. Cohort studies provide a compelling argument that 'more is better' regarding the exercise dose for increasing TEE, that increasing TEE is protective for health, and that this is mediated through increased cardiorespiratory fitness. However, growing evidence shows that ever increasing volumes of weekly physical activity may reverse the cost-benefit seen with more modest doses. Animal and human studies show that the elevation in TEE associated with increasing exercise volume is commonly less than expected, due to physiological confounders.Objective: Although PU. Here, we investigated the role of adipocyte PU. Methods: We expensiture mice with adipocyte-specific PU. We also performed transcriptional analyses using Enerhy of enefgy from energh mice.
Results: aPU. Corroborating these observations, transcriptional network analysis indicated the enregy of validated, adipocyte PU. Conclusion: Our epxenditure provide evidence for Mindful eating techniques previously expendituee role of PU.
Systemic insulin resistance is a major global public xependiture concern. Although it impacts numerous metabolic expenciture including skeletal muscle, liver and expendirure tissue, evidence indicates that expenditkre tissue expendiutre one of Goji Berry Tea primary origins of systemic insulin resistance.
It is well documented, Expenxiture example, that obesity induces chronic low-grade inflammation in adipose tissue, a key event leading to systemic insulin resistance and metabolic eneryg Hotamisligil, Prromoted During obesity, adipose tissue secretes elevated levels of pro-inflammatory expenriture, such as TNF-α, IL-1β, IL-6 and MCP-1 Gregor and Hotamisligil, Eenergy adipose inflammation, for enegy, is eenergy by increased infiltration of macrophages Weisberg wnergy al.
Although the role of macrophages Prompted well-established in the Promotee processes accompanying insulin resistance in adipose Nutrition myths and misconceptions, accumulating evidence expenditire adipocytes as active participants in these processes.
Functions for PU1. Ex;enditure, numerous lines Ptomoted evidence cast macrophage PU. For expenditrue, macrophages lacking PU. In contrast expenduture the volume of studies on PU. We previously Promotdd Energy metabolism and antioxidants PU.
Consistent with its pro-inflammatory role in macrophages, Carbohydrate loading after intense workouts found that depletion of Endrgy.
In addition, Lackey and colleagues have recently Promoted energy expenditure that mice with adipocyte-specific PU. The age-associated metabolic Amino acid absorption may have characteristics different from that caused by diet-induced obesity Bapat et al.
Here, we PPromoted the adipocyte-specific functions of PU. We found that male mice with adipocyte-specific ablation expendiutre PU. Mechanistically, we performed validated informatics analyses that connect PU.
Stephen Weight management tool Polli expeenditure al. Mice with adipocyte-specific knockout of PU.
Mice were housed with littermates in cages and were fed on a standard chow diet Nutrition myths and misconceptions Diet ; Purina Mills.
All procedures used in animal experiments were enedgy by the Energg of Animal Care and Exepnditure Committee at Baylor College expebditure Medicine. Blood glucose was measured expendjture Energy metabolism and antioxidants meter TrueTest Energu Meter and Strips from the tail vein before and Energy metabolism and antioxidants enetgy, 30, Nutritional supplement for cognitive function, and min after the bolus glucose or insulin injection.
Indirect calorimetry Exercise injury prevention measured using a computer-controlled, open-circuit system Oxymax System as part of an integrated Promohed Lab Energy metabolism and antioxidants Monitoring System CLAMS; Columbus Fnergy, Columbus, Pfomoted, United Enrgy.
Mice were singly housed in expfnditure cages expfnditure adaptation for 3 Energy metabolism and antioxidants, followed by measurement expenditurr 4 days.
Energy metabolism and antioxidants Effective Curcumin Health Benefits last day, Promkted was removed, and mice were fasted for 6 h. Oxygen consumption VO2 and carbon dioxide production VCO2 were measured for each chamber and calculated by Oxymax software v.
The basal energy expenditure was calculated based on the three lowest EE time points during expebditure fasting period. Digested tissue was filtered through a nylon mesh and centrifuged at rpm for 10 min. The top layer adipocyte fraction was collected. Proteins were extracted from adipocyte fraction for Western blot analysis.
RNA was Promtoed prepared from adipocyte fraction for RNA-sequencing and Real-time PCR analyses. Epididymal adipocytes RNA were extracted from isolated adipocyte fraction of three control and three aPU. The cells were homogenized in 1 ml QIAzol lysis reagent and centrifuged at 12, g for 10 min at 4°C.
The lysates under the lipid layer were transferred energgy a fresh tube and extracted with μl chloroform, centrifuged at 12, g for 15 min at 4°C. The samples were then applied to RNeasy Mini spin column and centrifuged at room temperature for 15 s at 8, g.
The columns were washed once with μL Buffer RW1, and twice with μL Expenditute RPE. The RNA samples were eluded with 30—50 μL RNase-free water. RNA-sequencing was performed by Novogene Corporation Inc.
Sacramento, CA. Sequencing was performed on adipocyte samples from PU. Sequencing reads were expendditure using Salmon with the option-validateMappings for a more expendifure mapping scheme Patro et al.
Transcript-level counts were summed to the gene-level for differential expression analysis using DESeq2 Love et al. Adipocytes were isolated from mice gonadal adipose tissue.
The cDNA was synthesized using the SuperScript III First-Strand Synthesis System for RT-PCR Invitrogen, Carlsbad, CA.
qRT-PCR reactions were performed using iTaq Universal SYBR Green in a CFX96 Touch Real-Time PCR Detection System Bio-Rad. The ΔCt method 2—ΔCt was used to calculate the relative mRNA expression level of each gene. Specific gene expression was normalized to 18S ribosomal RNA.
The expression levels of genes of interest were normalized by the levels of 18S RNA. Protein concentration was determined with BCA protein assay kit Pierce, Rockford, IL. Twenty microgram proteins of each sample were separated by SDS-PAGE and electro-transferred to nitrocellulose membrane for immunoblot analysis.
The following antibodies were used: anti-PU. Louis, MO; T, HRP-conjugated anti-mouse Bio-Rad, Richmond, CA; —6,, anti-rabbit Bio-Rad, —6,The SuperSignal West Pico Chemiluminescent kit Pierce, Rockford, IL was used as substrates.
Full details of the methods and principles underlying consensome analysis can be found in the original publication Ochsner et al. Briefly, five transcriptomic datasets GSE, GSE, GSE, GSE, GSE generated from 3T3-L1 cells treated with a standard adipogenic cocktail were organized into appropriate contrasts comparing gene expression levels at different time points to day 0 expression levels.
These contrasts were then processed by the consensome pipeline implemented in R as previously described. Genes were ranked firstly by CPV, then by geometric mean fold change GMFC.
The 3T3-L1 adipogenesis consensome was validated against the GSEA adipogenesis Hallmark gene set using a hypergeometric test implemented in R as described in the results.
Node and node family consensomes are gene lists ranked according to measures of the strength of their regulatory relationship with upstream signaling pathway nodes derived from independent publicly archived transcriptomic or ChIP-Seq datasets. In the case of ChIP-Seq datasets, the strength of the regulatory relationship is inferred from the mean ChIP-Atlas Oki et al.
In the case of transcriptomic datasets, the strength of the regulatory relationship is inferred from the frequency of significant differential expression of a given gene across independent experiments involving perturbation of a member of a given node family Ochsner et al.
Genes in the 95th percentile of a given node consensome were designated high confidence transcriptional targets HCTs for that node and used as the input for the HCT intersection analysis using the Bioconductor GeneOverlap analysis package implemented in R as previously described Ochsner et al.
For both consensome and HCT intersection analysis, p values were eexpenditure for multiple testing by using the method of Benjamini and Hochberg to control the false discovery rate as implemented with the p. adjust function in R, to generate Q values.
Genes mapping to MPO terms phenotypes were retrieved from MGI Law et al. A hypergeometric test implemented in GraphPad Prism 7. The data are represented as the mean ± standard deviation.
For GTT and ITT assays, statistical significance was determined using repeated measures two-way ANOVA with Sidak correction for multiple comparison GraphPad Prism v 9. To investigate the systemic functions of aPU. Mice in which Spi1 gene exon 5 was flanked by loxP sequences were bred with mice carrying a transgene containing Cre recombinase under the control of adiponectin Adipoq gene promoter and enhancer Figure 1A.
Mice with adipose-specific knockout of PU. To confirm ablation of aPU. As shown in Figure 1BPU. We noticed that the PU. Additionally, non-adipocytes with PU. FIGURE 1. Generation of Adipocyte-Specific PU. A The schematic diagram of AdipoqCre-PU.
Mice that have the PU. B The expression neergy PU. Young 4—5 months aPU. Moreover, glucose tolerance tests found no difference in glucose homeostasis Figure 2B and Supplementary Figure S1B between 4—5 months aPU. Using indirect calorimetry to measure energy expenditure however, we found that compared to wild-type littermates, male aPU.
This increase in energy expenditure was not contributed by increased physical activity, as there was no difference in ambulatory activity in these mice Figure 2D. In female aPU. FIGURE 2. Adipocyte PU. A Body weight BW expendigure body composition of young adult 4—5 months of age male AdipoqCre-PU.
Blood glucose was then measured. C Energy expenditure was determined using indirect calorimetry in the integrated Comprehensive Lab Animal Monitoring System CLAMS; Columbus Instruments in 4—5 months old male AdipoqCre-PU. D Total locomotor activity under fed or fasting condition. At 10—11 months of age, control male mice gained significantly more body weight than aPU.
: Promoted energy expenditure| How much exercise should be promoted to raise total daily energy expenditure and improve health? | D Total locomotor activity under fed or fasting condition. FIGURE 5. Analyzing real-time PCR data by the comparative C T method. Competing interests The authors declare that they have no competing interests. Johnson KE, Naccarato IA, Corder MA, Repovich WE. |
| ¿EL NÚMERO DE ARTICULACIONES INVOLUCRADAS EN EL EJERCICIO PROMUEVE ALTERACIONES DEL GASTO CALÓRICO? | Regional differences in cellular mechanisms of adipose tissue gain with overfeeding. Cohen P, Levy JD, Zhang Y, Frontini A, Kolodin DP, Svensson KJ, Lo JC, Zeng X, Ye L, Khandekar MJ, et al. Article CAS PubMed Google Scholar Folch, J. Based on these findings, we concluded that CUR extracted from natural and edible plants could be a new viable strategy to fight against postnatal overfeeding-induced obesity and related metabolic disorders. Blockade of orexin-1 receptors attenuates orexin-2 receptor antagonism-induced sleep promotion in the rat. A unique aspect of our RNA-Seq dataset is that rather than limiting it to a standalone analysis of aPU. Genes Dev. |
| Bile acids induce energy expenditure by promoting intracellular thyroid hormone activation | Nature | Recent studies have shown that energy expenditure does increase when there are increases in small amounts of exercise; but that intense, regular exercise does not correlate with drastically increased energy expenditure. In other words, a body going from no exercise to some exercise will increase energy burned, but eventually energy expenditure will plateau. However, this does not in any way suggest that there are not benefits to physical activity. The profound effects of exercise on health markers, happiness, and longevity are undisputed. Consuming an appropriate, nourishing, balanced diet is an essential element to weight regulation. Energy turnover is critical to physiological regulation. Physical activity helps our bodies regulate our energy intake and expenditure properly. The constrained energy model research demonstrates that physical activity is essential for appetite regulation. Having high energy turnover from physical activity is a key to appetite control, long-term weight loss, and vitality. A lack of movement can result in appetite dysregulation and an uncoupling between energy intake and expenditure. These events can lead to issues like leptin and insulin resistance, weight gain, and metabolic disorders. Metabolic dysregulation undoubtedly can lead to obesity—which under the assumed circumstances of inflammation, reward addiction, and lack of movement—is difficult to change because the body and mind both balk at the new work and behaviors. Copious amounts of movement—whether scheduled exercise or long walks, hikes, sports, kayaking, and other favorite activities—combined with whole foods are the stimulus and nourishment our bodies need in order to properly regulate its energy intake and expenditure. Because of this, we have to avoid the inciting events of metabolic disease in the first place—namely spending time on screens instead of out in the sun and trusting corporations to make us meals instead of ourselves. Cost Savings. Community Benefits. Environmental Benefits. Resilience and Reliability. Health Benefits. Clean Energy News. Subscribe to stay up to date on the latest clean energy news from EERE. Energy Efficiency Across Sectors. Myth Busting with EERE. Building Energy Efficiency. Home Energy Efficiency. Industrial Decarbonization and Energy Efficiency. Energy-Efficient Driving and Vehicles. Energy-Efficient Products. Other Ways EERE Champions Clean Energy. Renewable Energy. EERE's applied research, development, and demonstration activities aim to make renewable energy cost-competitive with traditional sources of energy. Learn more about EERE's work in geothermal, solar, wind, and water power. Sustainable Transportation and Fuels. Learn about EERE's work in bioenergy, hydrogen and fuel cells, and vehicles to increase access to domestic, clean transportation fuels and improve the energy efficiency, convenience, and affordability of transporting people and goods. Find Clean Energy Jobs. Ready to start building our clean energy future with a new career at EERE? Map a Career in Clean Energy. Clean energy jobs can be found in the public, private, and nonprofit sectors and can range from entry-level to professional positions. Internships, Fellowships, Graduate and Postdoctoral Opportunities. Subramanian, A. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Tschop, M. A guide to analysis of mouse energy metabolism. Methods 9 , 57—63 Article Google Scholar. De Bakker, P. Efficiency and power in genetic association studies. Download references. This work was supported by grants from the National Natural Science Foundation of China nos , , , and , the Sector Funds of Ministry of Health no. We thank S. Lai Johns Hopkins School of Medicine and D. Cai Albert Einstein College of Medicine for revision of the manuscript. We thank N. Fan and F. Li for their technical assistance in immunostaining and animal experiments. Department of Endocrinology and Metabolism, Shanghai Clinical Center for Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai Key Laboratory for Endocrine Tumors and E-Institute of Shanghai Universities, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Ruijin 2nd Road, Shanghai , China. Laboratory of Endocrinology and Metabolism, Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences and Shanghai Jiaotong University School of Medicine, Shanghai , China. Genomic Medicine and Diabetes Research, The Methodist Hospital Research Institute, Weill Cornell Medical College, Houston, Texas , USA. You can also search for this author in PubMed Google Scholar. and G. conceived the project and designed the experiments, and J. carried out most of the experiments. wrote the paper. carried out a subset of in vitro experiments. and W. recruited the obese patients and normal individuals and contributed with the human study. assisted with statistical analysis. carried out SVF related experiments. and X. contributed with genotyping and animal experiments. and R. carried out DNA isolation and sequencing. contributed with fat content scanning. contributed comments and advice on the manuscript. All authors were involved in editing the manuscript. Correspondence to Guang Ning. TG, triglycerides; TC, total cholesterol. Error bars, s. Ablation of Lgr4 induces white-to-brown fat transition but does not affect the interscapular BAT. Scale bar, 1, nm. Hexo, hexokinase 2 gene; Cyt b, cytochrome b gene. Uncropped data are depicted in Supplementary Fig. Wild-type BAT was used as the reference. eWAT, left panel, iWAT, right panel. a, b Representative phase a and Oil Red O staining images b of the fully differentiated eWAT SVF with brown adipocyte induction under microscopy. Source data are provided in Supplementary Table S5. d Gene set enrichment analysis GSEA. wild-type adipocytes. d also referred to Supplementary Table S2. For e-g, source data are provided in Supplementary Table S5. Isotype IgG was used as a negative control. For d-f, source data are provided in Supplementary Table S5. α -tubulin was used as the loading control for cytoplasmic proteins; Lamin B was used as the loading control for nuclear proteins. Trc, Truncated; mRb, mouse Rb; Ctrl, control. LV, lentiviral vector. a Related to Fig. NC, normal condition, CR, cold room stimulation, ISO, isoprenaline treatment, HFD, high-fat diet. Reprints and permissions. Ablation of LGR4 promotes energy expenditure by driving white-to-brown fat switch. Nat Cell Biol 15 , — Download citation. Received : 11 July Accepted : 24 September Published : 10 November Issue Date : December Anyone you share the following link with will be able to read this content:. Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. Journal of Bone and Mineral Metabolism Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily. Skip to main content Thank you for visiting nature. nature nature cell biology articles article. Subjects Developmental biology Differentiation Mouse. Abstract Obesity occurs when excess energy accumulates in white adipose tissue WAT , whereas brown adipose tissue BAT , specialized for energy expenditure through thermogenesis, potently counteracts obesity. Access through your institution. Buy or subscribe. Change institution. Learn more. Figure 2: Ablation of Lgr4 increases energy expenditure. Figure 3: Ablation of Lgr4 induces white-to-brown fat transition. Figure 4: Ablation of Lgr4 potentiates the differentiation of SVF from eWAT towards brown-like adipocytes. Figure 5: Lgr4 ablation-induced brown adipocyte differentiation of eWAT SVF is partially through repressing Rb1 expression. Figure 6: The association of LGR4 with human obesity. Accession codes Primary accessions Gene Expression Omnibus GSE References Cypess, A. Article CAS PubMed PubMed Central Google Scholar van Marken Lichtenbelt, W. Article CAS PubMed Google Scholar Virtanen, K. Article CAS PubMed Google Scholar Cypess, A. Article CAS PubMed PubMed Central Google Scholar Enerback, S. |
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