Toxic effect of silica nanoparticles on endothelial cells through DNA damage response via Chk1-dependent G2/M checkpoint.
Toxic Effect of Silica Nanoparticles on Endothelial Cells through DNA Damage Response via Chk1-Dependent G2/M Checkpoint Junchao Duan1, Yongbo Yu1, Yang Li2, Yang Yu1, Yanbo Li1, Xianqing Zhou1, Peili Huang1, Zhiwei Sun1,2* 1 School of Public Health, Capital Medical University, Beijing, P.R. China, 2 School of Public Health, Jilin University, Changchun, Jilin, P.R. China Abstract Silica nanoparticles have become promising carriers for drug delivery or gene therapy. Endothelial cells could be directly exposed to silica nanoparticles by intravenous administration. However, the underlying toxic effect mechanisms of silica nanoparticles on endothelial cells are still poorly understood. In order to clarify the cytotoxicity of endothelial cells induced by silica nanoparticles and its mechanisms, cellular morphology, cell viability and lactate dehydrogenase (LDH) release were observed in human umbilical vein endothelial cells (HUVECs) as assessing cytotoxicity, resulted in a dose- and timedependent manner. Silica nanoparticles-induced reactive oxygen species (ROS) generation caused oxidative damage followed by the production of malondialdehyde (MDA) as well as the inhibition of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px). Both necrosis and apoptosis were increased significantly after 24 h exposure. The mitochondrial membrane potential (MMP) decreased obviously in a dose-dependent manner. The degree of DNA damage including the percentage of tail DNA, tail length and Olive tail moment (OTM) were markedly aggravated. Silica nanoparticles also induced G2/M arrest through the upregulation of Chk1 and the downregulation of Cdc25C, cyclin B1/ Cdc2. In summary, our data indicated that the toxic effect mechanisms of silica nanoparticles on endothelial cells was through DNA damage response (DDR) via Chk1-dependent G2/M checkpoint signaling pathway, suggesting that exposure to silica nanoparticles could be a potential hazards for the development of cardiovascular diseases. Citation: Duan J, Yu Y, Li Y, Yu Y, Li Y, et al. (2013) Toxic Effect of Silica Nanoparticles on Endothelial Cells through DNA Damage Response via Chk1-Dependent G2/M Checkpoint. PLoS ONE 8(4): e62087. doi:10.1371/journal.pone.0062087 Editor: Yanchang Wang, Florida State University, United States of America Received January 14, 2013; Accepted March 17, 2013; Published April 19, 2013 Copyright: ß 2013 Duan, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was supported by National Natural Science Foundation of China (number 81230065, number 81172704), Funding Project for Academic Human Resources Development of Beijing Education Committee (PHR201006110) and Innovative Team Project of Beijing Education Committee (PHR201107116). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: firstname.lastname@example.org The human umbilical vein endothelial cells (HUVECs) line isolated from the umbilical cord by collagenase digestion has been used for in vitro studies of endothelial cells function . Unfortunately, most previous studies focused on the cytotoxicity induced by silica nanoparticles using a wide range of different cells lines rather than endothelial cell line [13,14,15]. Although recently reports have shown that HUVECs exposure to silica nanoparticles could induce reactive oxygen species (ROS), inflammatory cytokines and von Willebrand factor (VWF) [16,17,18], information about the toxic effect and its mechanisms of silica nanoparticles on endothelial cells is still limited. Our previous study confirmed that silica nanoparticles caused oxidative DNA damage and cell cycle arrest in human hepatoma (HepG2) cells . However, as far as we know, whether the silica nanoparticles could also induce endothelial cells toxic effect through oxidative DNA damage or cell cycle arrest has not been reported. Mammalian cells are frequently at risk of DNA damage from a variety of endogenous and exogenous sources, including reactive oxygen species, ultraviolet light, background radiation and environmental factors . To protect their genomes from this assault, cells have evolved complex mechanisms known as DNA damage response (DDR) that act to rectify damage and minimize the probability of lethal or permanent genetic damage . DDR encompass multiple repair mechanisms and signal transduction Introduction Silica nanoparticles have been found extensive applications in biomedical and biotechnological fields , such as medical diagnostics, drug delivery, gene therapy, biomolecules detection, photodynamic therapy and bioimaging [2,3,4]. This adds to the increasing industrial exposure to silica nanoparticles during production, transportation, storage, and consumer use by which human exposure and environmental burden were obviously increased. Epidemiological evidences link air pollution with fine particles in which silica is inorganic components to increase the morbidity and mortality of cardiovascular diseases [5,6,7]. In addition, several studies have shown translocation of ultrafine particles from the lungs to extrapulmonary organs via the systemic circulation [8,9,10]. Thus, endothelial cells could be directly exposed to ultrafine particles. Moreover, silica nanoparticles as carriers of drug delivery or gene therapy are generally injected into the body intravenously and directly contacted with endothelial cells. The single layer of endothelial cells that lines the lumen of all blood vessels is recognized to be not only a barrier between circulating blood and the vessel wall, but also a critical factor for the maintenance of vascular function and homeostasis . Therefore, it is important to understand the interaction between silica nanoparticles and endothelial cells. PLOS ONE | www.plosone.org 1 April 2013 | Volume 8 | Issue 4 | e62087 Toxic Effect of Nano-SiO2 on Endothelial Cells ments, each group had five replicate wells. Data are expressed as means 6 S.D. from three independent experiments (*p,0.05). pathways that effect cell cycle checkpoint arrest and/or apoptosis . These regulatory mechanisms involving an intricate network of protein kinase signaling pathways are central to the maintenance of genomic integrity and basic viability of the cells . Intact DDR pathways are very critical for preventing the replication of damaged DNA templates and transmission of mutations to daughter cells. Whereas defects in DDR will result in accumulation of genetic mutations, gene amplification, and chromosomal alterations, which in turn contribute to malignant transformation and tumorigenesis . Therefore, it is necessary to clarify the basic molecular mechanism of silica nanoparticlesinduced DDR pathways in endothelial cells. To our best knowledge, this is the first study to illustrate the biological interaction mechanisms between DDR pathways and endothelial cells toxic effect triggered by silica nanoparticles. Prior to undertaking in vitro toxicity experiments, the characterization of silica nanoparticles, which is essential for nanotoxicity studies, was performed by transmission electron microscope (TEM) and dynamic light scattering (DLS) measurements. To investigate the toxic effect mechanisms of endothelial cells induced by silica nanoparticles, we conducted a sequence of assessments including cellular uptake and morphology, cell viability, membrane integrity, intracellular ROS generation, oxidative damage, DNA damage, cell cycle arrest, apoptosis and necrosis after HUVECs exposure to silica nanoparticles for 24 h. We also measured the protein levels of Chk1, Cdc25c, cyclin B1/Cdc2 to analyze whether silica nanoparticles-induced endothelial cells toxic effect was through DDR via Chk1-dependent G2/M checkpoint signaling pathway. Detection of silica nanoparticles uptake LSCM detection: HUVECs were seeded at 16104 cells in 35 mm-diameter glass bottom cell culture dish and were cultured in DMEM as above. After 24 h of cell attachment, the cells were treated with Ruthenium (II) hydrate (Ru(phen)32+) interior-labeled silica nanoparticles (50 mg/mL) for 24 h at 37uC in serum-free medium. These red fluorescent silica nanoparticles were prepared by a modified Stöber method and characterized as described before . Cells were then washed several times with phosphatebuffered saline (PBS) and fixed with 4% paraformaldehyde at room temperature for 10 min. Cells were then washed 3 times with phosphate-buffered saline (PBS) and fixed with 4% paraformaldehyde at room temperature for 10 min. The cells were washed with 0.1% Triton X-100 three times and incubated with Phalloidin-FITC Actin-Tracker Green (Jiancheng, China) at room temperature for 30 min. The Actin-Tracker was dissolved in the mixture of 0.1% Triton X-100 and 3% bovine serum albumin (BSA) (Sigma, USA) for staining the actin filamentous skeleton. After that, the nucleus was stained with 5 mg/mL 4,6-diamidino-2phenylindole (DAPI) (Sigma, USA) in PBS for 5 min. Cellular uptake were observed by a laser scanning confocal microscopy (LSCM) (Leica TCS SP5, Germany). TEM detection: After HUVECs incubated for 24 h with silica nanoparticles (50 mg/mL), the cells were washed with PBS and then centrifuged at 2000 r/min for 10 min. The supernatants were removed. The cell pellets were fixed in a 0.1 M PBS solution containing 2.5% glutaraldehyde and 4% paraformaldehyde for 3 h. They were then washed with 0.1 M PBS, embedded in 2% agarosegel, postfixed in 4% osmium tetroxide solution for 1 h, washed with distilled water, stained with 0.5% uranyl acetate for 1 h, dehydrated in a graded series of ethanol (30%, 60%, 70%, 90%, and 100%), and embedded in epoxy resin. The resin was polymerized at 60uC for 48 h. Ultrathin sections obtained with a ultramicrotome were stained with 5% aqueous uranyl acetate and 2% aqueous lead citrate, air dried, and imaged under a transmission electron microscope (TEM) (JEOL JEM2100, Japan). Materials and Methods Silica nanoparticles preparation and characterization Silica nanoparticles were prepared using the Stöber method . Briefly, 2.5 mL of tetraethylorthosilicate (TEOS) (Sigma, USA) was added to premixed ethanol solution (50 mL) containing ammonia (2 mL) and water (1 mL). The reaction mixture was kept at 40uC for 12 h with continuous stirring (150 r/min). The resulting particles were isolated by centrifugation (12,000 r/min, 15 min) and washed three times with deionized water and then dispersed in 50 mL of deionized water. The size and distribution of silica nanoparticles were performed by transmission electron microscope (TEM) (JEOL JEM2100, Japan) and ImageJ software. The hydrodynamic sizes and zeta potential of silica nanoparticles were examined by Zetasizer (Malvern Nano-ZS90, Britain). Suspensions of silica nanoparticles were dispersed by sonicator (160 W, 20 kHz, 5 min) (Bioruptor UDC-200, Belgium) before addition to culture medium in order to minimize their aggregation. Assessment of cytotoxicity Cultured HUVECs were treated with various concentrations (25, 50, 75, and 100 mg/mL) of silica nanoparticles for 24 h. Cell morphology was observed by optical microscope (Olympus IX81, Japan). The cell viability was measured using the 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) reduction assay. MTT assay is the most common employed for the detection of cytotoxicity or cell viability following exposure to toxic substances. MTT is a water soluble tetrazolium salt, which is converted to an insoluble purple formazan by cleavage of the tetrazolium ring by succinate dehydrogenase within the mitochondria. The formazan product is impermeable to the cell membranes and therefore it accumulates in healthy cells. The absorbance of formazan was measured at 492 nm using a microplate reader (Themo Multiscan MK3, USA). The lactate dehydrogenase leakage assay (LDH), which is based on the measurement of lactate dehydrogenase activity in the extracellular medium, was determined using a commercial LDH Kit (Jiancheng, China) according to the manufacturer’s protocols. The loss of intracellular LDH and its release into the culture medium is an indicator of irreversible cell death due to cell membrane damage. After HUVECs treated with different concentrations (25, 50, 75, and 100 mg/mL) of silica nanoparticles Cell culture and exposure to silica nanoparticles The primary human umbilical vein endothelial cells (HUVECs) line was purchased from the Cell Resource Center, Shanghai Institutes for Biological Sciences (SIBS, China). The cells were maintained in Dulbecco’s Modified Eagle’s Medium (DMEM) (Gibco, USA) supplemented with 10% fetal bovine serum (Gibco, USA), 100 U/mL penicillin and 100 mg/mL streptomycin, and cultured at 37uC in 5% CO2 humidified environment. For experiments, the cells were seeded in 6-well plates (except MTT assay using 96-well plates) at a density of 16105 cells/mL and allowed to attach for 24 h, then treated with silica nanoparticles suspended in DMEM of certain concentrations for another 24 h. Before use, the stock suspensions of silica nanoparticles were sonicated for 5 min. Controls were supplied with an equivalent volume of DMEM without silica nanoparticles. For all experiPLOS ONE | www.plosone.org 2 April 2013 | Volume 8 | Issue 4 | e62087 Toxic Effect of Nano-SiO2 on Endothelial Cells for 24 h, the supernatants were collected for LDH measurement. 100 mL cell medium was used for LDH activity analysis and the absorbance at 440 nm was measured by a UV-visible spectrophotometer (Beckman DU-640B, USA). Detection of mitochondrial membrane potential (MMP) MMP was detected by using 5,59,6,69-tetrachloro-1,19,3,39tetraethylbenzimi dazo-lylcarbocyanide iodine (JC-1) (Sigma, USA). This probe can selectively enter into mitochondria and reversibly change color from red to green as the membrane potential decreased. The ratio of green to red expresses the change of MMP. Cells were treated with silica nanoparticles (25, 50, 75, and 100 mg/mL) for 24 h. After washing with PBS, the cells were incubated with 10 mg/mL working solution of JC-1 for 20 min. Then the cells were washed with PBS twice and analyzed by flow cytometry (Becton-Dickison, USA). The green fluorescence intensity was determined at an excitation wavelength of 488 nm and an emission wavelength of 525 nm, whereas the red fluorescence intensity determined at an excitation wavelength of 488 nm and an emission wavelength of 590 nm. For each sample, at least at least 16104 cells were collected. Apoptosis and necrosis Apoptosis in endothelial cells was measured using the Annexin V-propidium iodide (PI) apoptosis detection kit (KeyGen, China). The kit contains Annexin V conjugated to the flurochrome FITC. This complex displays a high affinity to the membrane phospholipid phosphatidylserine, which undergoes externalization in the earlier stages of apoptosis. To distinguish early apoptotic cells from dead cells resulted from late apoptosis or necrosis, the vital dye PI was used. In this way, FITC negative and PI negative were designated as live cells in the lower left quadrant; FITC positive and PI negative as apoptotic cells in the upper left quadrant; FITC positive and PI positive as necrotic cells in the upper right quadrant; and FITC negative and PI positive as large nuclear fragments in the lower right quadrant . HUVECs were exposed to silica nanoparticles for 24 h, washed with PBS three times and trypsinized. After centrifugation at 1000 rpm, the cell pellet was washed with PBS once and incubated with 5 mL Annexin V-FITC for 15 min, which was followed by staining with 5 mL PI. Then, the samples were diluted with 500 mL binding buffer and analyzed with a flow cytometer (Becton Dickinson, USA), and at least 16104 cells were counted for each sample. Comet assay Comet assay, also known as single cell gel electrophoresis (SCGE), is a visual and sensitive technique for measuring DNA breakage in individual mammalian cells. The DNA damage induced by silica nanparticles was performed by Single cell gel electrophoresis kit (Biolab, China). HUVECs were collected and resuspended in PBS. 20 mL of the cells suspension and 80 mL of low melting agarose were mixed and 80 mL of the suspension pipetted onto a comet-slide. The slides were placed flat in dark at 4u C for 10 min for the mixture to solidify. Then the slides were placed in pre-chilled lysing solution at 4u C for 2 h. Slides were removed from lysing solution, tapped on a paper towel to remove any excess lysis solution and immersed in alkaline solution for 45 min in dark at room temperature. The slides were washed twice for 5 min. Then the slides were electrophoresed at low voltage (300 mA, 25 V) for 30 min. Slides were removed from the electrophoresis unit after the designated time, tapped to remove excess buffer at room temperature. Subsequently, the air-dried slides were stained with DNA-binding dye propidium iodide (PI) and evaluated under a fluorescence microscope (Olympus IX81, Japan). To prevent additional DNA damage, all the steps described above were conducted under dimmed light or in the dark. The data were analyzed by CASP software based on 100 randomly selected cells per sample. The percentage of tail DNA, tail length and Olive tail moment (OTM) were selected as indicators of DNA damage. Intracellular ROS measurement The cytotoxicity effects might occur through the induction of oxidative stress and apoptosis with possible involvement of overproduction of reactive oxygen species (ROS). In this regard, the production of intracellular ROS was measured by flow cytometry using the 29, 79-dichlorofluorescein equilibrium value of MeCpG steps (,+14 deg.) [31,44]. In comparison, methylation has a significantly lower stability cost when happening at major groove positions, such as 211 and 21 base pair from dyad (mutations 9 and 12), where the roll of the nucleosome bound conformation (+10 deg.) is more compatible with the equilibrium geometry of MeCpG steps. The nucleosome destabilizing effect of cytosine methylation increases with the number of methylated cytosines, following the same position dependence as the single methylations. The multiple-methylation case reveals that each major groove meth- PLOS Computational Biology | www.ploscompbiol.org 3 November 2013 | Volume 9 | Issue 11 | e1003354 DNA Methylation and Nucleosome Positioning ylation destabilizes the nucleosome by around 1 kJ/mol (close to the average estimate of 2 kJ/mol obtained for from individual methylation studies), while each minor groove methylation destabilizes it by up to 5 kJ/mol (average free energy as single mutation is around 6 kJ/mol). This energetic position-dependence is the reverse of what was observed in a recent FRET/SAXS study . The differences can be attributed to the use of different ionic conditions and different sequences: a modified Widom-601 sequence of 157 bp, which already contains multiple CpG steps in mixed orientations, and which could assume different positioning due to the introduction of new CpG steps and by effect of the methylation. The analysis of our trajectories reveals a larger root mean square deviation (RMSD) and fluctuation (RMSF; see Figures S2– S3 in Text S1) for the methylated nucleosomes, but failed to detect any systematic change in DNA geometry or in intermolecular DNA-histone energy related to methylation (Fig. S1B, S1C, S4–S6 in Text S1). The hydrophobic effect should favor orientation of the methyl group out from the solvent but this effect alone is not likely to justify the positional dependent stability changes in Figure 2, as the differential solvation of the methyl groups in the bound and unbound states is only in the order of a fraction of a water molecule (Figure S5 in Text S1). We find however, a reasonable correlation between methylation-induced changes in hydrogen bond and stacking interactions of the bases and the change in nucleosome stability (see Figure S6 in Text S1). This finding suggests that methylation-induced nucleosome destabilization is related to the poorer ability of methylated DNA to fit into the required conformation for DNA in a nucleosome. Changes in the elastic deformation energy between methylated and un-methylated DNA correlate with nucleosomal differential binding free energies To further analyze the idea that methylation-induced nucleosome destabilization is connected to a worse fit of methylated DNA into the required nucleosome-bound conformation, we computed the elastic energy of the nucleosomal DNA using a harmonic deformation method [36,37,44]. This method provides a rough estimate of the energy required to deform a DNA fiber to adopt the super helical conformation in the nucleosome (full details in Suppl. Information Text S1). As shown in Figure 2, there is an evident correlation between the increase that methylation produces in the elastic deformation energy (DDE def.) and the free energy variation (DDG bind.) computed from MD/TI calculations. Clearly, methylation increases the stiffness of the CpG step , raising the energy cost required to wrap DNA around the histone octamers. This extra energy cost will be smaller in regions of high positive roll (naked DNA MeCpG steps have a higher roll than CpG steps ) than in regions of high negative roll. Thus, simple elastic considerations explain why methylation is better tolerated when the DNA faces the histones through the major groove (where positive roll is required) that when it faces histones through the minor groove (where negative roll is required). Nucleosome methylation can give rise to nucleosome repositioning We have established that methylation affects the wrapping of DNA in nucleosomes, but how does this translate into chromatin structure? As noted above, accumulation of minor groove methylations strongly destabilizes the nucleosome, and could trigger nucleosome unfolding, or notable changes in positioning or phasing of DNA around the histone core. While accumulation of methylations might be well tolerated if placed in favorable positions, accumulation in unfavorable positions would destabilize the nucleosome, which might trigger changes in chromatin structure. Chromatin could in fact react in two different ways in response to significant levels of methylation in unfavorable positions: i) the DNA could either detach from the histone core, leading to nucleosome eviction or nucleosome repositioning, or ii) the DNA could rotate around the histone core, changing its phase to place MeCpG steps in favorable positions. Both effects are anticipated to alter DNA accessibility and impact gene expression regulation. The sub-microsecond time scale of our MD trajectories of methylated DNAs bound to nucleosomes is not large enough to capture these effects, but clear trends are visible in cases of multiple mutations occurring in unfavorable positions, where unmethylated and methylated DNA sequences are out of phase by around 28 degrees (Figure S7 in Text S1). Due to this repositioning, large or small, DNA could move and the nucleosome structure could assume a more compact and distorted conformation, as detected by Lee and Lee , or a slightly open conformation as found in Jimenez-Useche et al. . Using the harmonic deformation method, we additionally predicted the change in stability induced by cytosine methylation for millions of different nucleosomal DNA sequences. Consistently with our calculations, we used two extreme scenarios to prepare our DNA sequences (see Fig. 3): i) all positions where the minor grooves contact the histone core are occupied by CpG steps, and ii) all positions where the major grooves contact the histone core are occupied by CpG steps. We then computed the elastic energy required to wrap the DNA around the histone proteins in unmethylated and methylated states, and, as expected, observed that methylation disfavors DNA wrapping (Figure 3A). We have rescaled the elastic energy differences with a factor of 0.23 to match the DDG prediction in figure 2B. In agreement with the rest of our results, our analysis confirms that the effect of methylation is position-dependent. In fact, the overall difference between the two extreme methylation scenarios (all-in-minor vs all-in-major) is larger than 60 kJ/mol, the average difference being around 15 kJ/ mol. We have also computed the elastic energy differences for a million sequences with CpG/MeCpG steps positioned at all possible intermediate locations with respect to the position (figure 3B). The large differences between the extreme cases can induce rotations of DNA around the histone core, shifting its phase to allow the placement of the methylated CpG steps facing the histones through the major groove. It is illustrative to compare the magnitude of CpG methylation penalty with sequence dependent differences. Since there are roughly 1.5e88 possible 147 base pairs long sequence combinations (i.e., (4n+4(n/2))/2, n = 147), it is unfeasible to calculate all the possible sequence effects. However, using our elastic model we can provide a range of values based on a reasonably large number of samples. If we consider all possible nucleosomal sequences in the yeast genome (around 12 Mbp), the energy difference between the best and the worst sequence that could form a nucleosome is 0.7 kj/mol per base (a minimum of 1 kJ/mol and maximum of around 1.7 kJ/mol per base, the first best and the last worst sequences are displayed in Table S3 in Text S1). We repeated the same calculation for one million random sequences and we obtained equivalent results. Placing one CpG step every helical turn gives an average energetic difference between minor groove and major groove methylation of 15 kJ/ mol, which translates into ,0.5 kJ/mol per methyl group, 2 kJ/ mol per base for the largest effects. Considering that not all nucleosome base pair steps are likely to be CpG steps, we can conclude that the balance between the destabilization due to CpG methylation and sequence repositioning will depend on the PLOS Computational Biology | www.ploscompbiol.org 4 November 2013 | Volume 9 | Issue 11 | e1003354 DNA Methylation and Nucleosome Positioning Figure 3. Methylated and non-methylated DNA elastic deformation energies. (A) Distribution of deformation energies for 147 bplong random DNA sequences with CpG steps positioned every 10 base steps (one helical turn) in minor (red and dark red) and major (light and dark blue) grooves respectively. The energy values were rescaled by the slope of a best-fit straight line of figure 2, which is 0.23, to source of circulating FGF-21. The lack of association between circulating and muscle-expressed FGF-21 also suggests that muscle FGF-21 primarily works in a local manner regulating glucose metabolism in the muscle and/or signals to the adipose tissue in close contact to the muscle. Our study has some limitations. The number of subjects is small and some correlations could have been significant with greater statistical power. Another aspect is that protein levels of FGF-21 were not determined in the muscles extracts, consequently we cannot be sure the increase in FGF-21 mRNA is followed by increased protein expression. In conclusion, we show that FGF-21 mRNA is increased in skeletal muscle in HIV patients and that FGF-21 mRNA in muscle correlates to whole-body (primarily reflecting muscle) insulin resistance. These findings add to the evidence that FGF-21 is a myokine and that muscle FGF-21 might primarily work in an autocrine manner. Acknowledgments We thank the subjects for their participation in this study. Ruth Rousing, Hanne Willumsen, Carsten Nielsen and Flemming Jessen are thanked for excellent technical help. The Danish HIV-Cohort is thanked for providing us HIV-related data. PLOS ONE | www.plosone.org 6 March 2013 | Volume 8 | Issue 3 | e55632 Muscle FGF-21,Insulin Resistance and Lipodystrophy Author Contributions Conceived and designed the experiments: BL BKP JG. Performed the experiments: BL TH TG CF PH. Analyzed the data: BL CF PH. Contributed reagents/materials/analysis tools: BL. Wrote the paper: BL. References 1. Kharitonenkov A, Shiyanova TL, Koester A, Ford AM, Micanovic R, et al. (2005) FGF-21 as a novel metabolic regulator. J Clin Invest 115: 1627–1635. 2. Coskun T, Bina HA, Schneider MA, Dunbar JD, Hu CC, et al. (2008) Fibroblast growth factor 21 corrects obesity in mice. Endocrinology 149: 6018– 6027. 3. Xu J, Lloyd DJ, Hale C, Stanislaus S, Chen M, et al. (2009) Fibroblast growth factor 21 reverses hepatic steatosis, increases energy expenditure, and improves insulin sensitivity in diet-induced obese mice. Diabetes 58: 250–259. 4. Inagaki T, Dutchak P, Zhao G, Ding X, Gautron L, et al. (2007) Endocrine regulation of the fasting response by PPARalpha-mediated induction of fibroblast growth factor 21. Cell Metab 5: 415–425. 5. Potthoff MJ, Inagaki T, Satapati S, Ding X, He T, et al. (2009) FGF21 induces PGC-1alpha and regulates carbohydrate and fatty acid metabolism during the adaptive starvation response. Proc Natl Acad Sci U S A 106: 10853–10858. 6. Badman MK, Pissios P, Kennedy AR, Koukos G, Flier JS, et al. (2007) Hepatic fibroblast growth factor 21 is regulated by PPARalpha and is a key mediator of hepatic lipid metabolism in ketotic states. Cell Metab 5: 426–437. 7. Zhang X, Yeung DC, Karpisek M, Stejskal D, Zhou ZG, et al. (2008) Serum FGF21 levels are increased in obesity and are independently associated with the metabolic syndrome in humans. Diabetes 57: 1246–1253. 8. Chen WW, Li L, Yang GY, Li K, Qi XY, et al. (2008) Circulating FGF-21 levels in normal subjects and in newly diagnose patients with Type 2 diabetes mellitus. Exp Clin Endocrinol Diabetes 116: 65–68. 9. Chavez AO, Molina-Carrion M, Abdul-Ghani MA, Folli F, DeFronzo RA, et al. (2009) Circulating fibroblast growth factor-21 is elevated in impaired glucose tolerance and type 2 diabetes and correlates with muscle and hepatic insulin resistance. Diabetes Care 32: 1542–1546. 10. Hojman P, Pedersen M, Nielsen AR, Krogh-Madsen R, Yfanti C, et al. (2009) Fibroblast growth factor-21 is induced in human skeletal muscles by hyperinsulinemia. Diabetes 58: 2797–2801. 11. Izumiya Y, Bina HA, Ouchi N, Akasaki Y, Kharitonenkov A, et al. (2008) FGF21 is an Akt-regulated myokine. FEBS Lett 582: 3805–3810. 12. Vienberg SG, Brons C, Nilsson E, Astrup A, Vaag A, et al. (2012) Impact of short-term high-fat feeding and insulin-stimulated FGF21 levels in subjects with low birth weight and controls. Eur J Endocrinol 167: 49–57. 13. Carr A, Samaras K, Burton S, Law M, Freund J, et al. (1998) A syndrome of peripheral lipodystrophy, hyperlipidaemia and insulin resistance in patients receiving HIV protease inhibitors. AIDS 12: F51–F58. 14. Haugaard SB, Andersen O, Dela F, Holst JJ, Storgaard H et al. (2005) Defective glucose and lipid metabolism in human immunodeficiency virus-infected patients with lipodystrophy involve liver, muscle tissue and pancreatic betacells. Eur J Endocrinol 152: 103–112. 15. Reeds DN, Yarasheski KE, Fontana L, Cade WT, Laciny E, et al. (2006) Alterations in liver, muscle, and adipose tissue insulin sensitivity in men with HIV infection and dyslipidemia. Am J Physiol Endocrinol Metab 290: E47–E53. 16. Meininger G, Hadigan C, Laposata M, Brown J, Rabe J, et al. (2002) Elevated concentrations of free fatty acids are associated with increased insulin response to standard glucose challenge in human immunodeficiency virus-infected subjects with fat redistribution. Metabolism 51: 260–266. 17. Carr A, Emery S, Law M, Puls R, Lundgren JD, et al. (2003) An objective case definition of lipodystrophy in HIV-infected adults: a case-control study. Lancet 361: 726–735. 18. Lindegaard B, Hansen T, Hvid T, van HG, Plomgaard P, et al. (2008) The effect of strength and endurance training on insulin sensitivity and fat distribution in human immunodeficiency virus-infected patients with lipodystrophy. J Clin Endocrinol Metab 93: 3860–3869. 19. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, et al. (1985) Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28: 412– 419. 20. Lindegaard B, Frosig C, Petersen AM, Plomgaard P, Ditlevsen S, et al. (2007) Inhibition of lipolysis stimulates peripheral glucose uptake but has no effect on endogenous glucose production in HIV lipodystrophy. Diabetes 56: 2070–2077. 21. DeFronzo RA, Tobin JD, Andres R (1979) Glucose clamp technique: a method for quantifying insulin secretion and resistance. Am J Physiol 237: E214–E223. 22. Plomgaard P, Bouzakri K, Krogh-Madsen R, Mittendorfer B, Zierath JR, et al. (2005) Tumor necrosis factor-alpha induces skeletal muscle insulin resistance in healthy human subjects via inhibition of Akt substrate 160 phosphorylation. Diabetes 54: 2939–2945. 23. Thomas JA, Schlender KK, Larner J (1968) A rapid filter paper assay for UDPglucose-glycogen glucosyltransferase, including an improved biosynthesis of UDP-14C-glucose. Anal Biochem 25: 486–499. 24. Haugaard SB, Andersen O, Madsbad S, Frosig C, Iversen J, et al. (2005) Skeletal Muscle Insulin Signaling Defects Downstream of Phosphatidylinositol 3-Kinase at the Level of Akt Are Associated With Impaired Nonoxidative Glucose Disposal in HIV Lipodystrophy. Diabetes 54: 3474–3483. 25. Boden G, Jadali F, White J, Liang Y, Mozzoli M, et al. (1991) Effects of fat on insulin-stimulated carbohydrate metabolism in normal men. J Clin Invest 88: 960–966. 26. Mashili FL, Austin RL, Deshmukh AS, Fritz T, Caidahl K, et al. (2011) Direct effects of FGF21 on glucose uptake in human skeletal muscle: implications for type 2 diabetes and obesity. Diabetes Metab Res Rev 27: 286–297. 27. Torriani M, Thomas BJ, Barlow RB, Librizzi J, Dolan S, et al. (2006) Increased intramyocellular lipid accumulation in HIV-infected women with fat redistribution. J Appl Physiol 100: 609–614. 28. Lee MS, Choi SE, Ha ES, An SY, Kim TH, et al. (2012) Fibroblast growth factor-21 protects human skeletal muscle myotubes from palmitate-induced insulin resistance by inhibiting stress kinase and NF-kappaB. Metabolism . 29. Tyynismaa H, Carroll CJ, Raimundo N, Ahola-Erkkila S, Wenz T, et al. (2010) Mitochondrial myopathy induces a starvation-like response. Hum Mol Genet 19: 3948–3958. 30. Maagaard A, Holberg-Petersen M, Kollberg G, Oldfors A, Sandvik L, et al. (2006) Mitochondrial (mt)DNA changes in tissue may not be reflected by depletion of mtDNA in peripheral blood mononuclear cells in HIV-infected patients. Antivir Ther 11: 601–608. 31. Payne BA, Wilson IJ, Hateley CA, Horvath R, Santibanez-Koref M, et al. (2011) Mitochondrial aging is accelerated by anti-retroviral therapy through the clonal expansion of mtDNA mutations. Nat Genet 43: 806–810. 32. Kliewer SA, Mangelsdorf DJ (2010) Fibroblast growth factor 21: from pharmacology to physiology. Am J Clin Nutr 91: 254S–257S. 33. Gallego-Escuredo JM, Domingo P, Gutierrez MD, Mateo MG, Cabeza MC, et al. (2012) Reduced Levels of Serum FGF19 and Impaired Expression of Receptors for Endocrine FGFs in Adipose Tissue From HIV-Infected Patients. J Acquir Immune Defic Syndr 61: 527–534. 34. Domingo P, Gallego-Escuredo JM, Domingo JC, Gutierrez MM, Mateo MG, et al. (2010) Serum FGF21 levels are elevated in association with lipodystrophy, insulin resistance and biomarkers of liver injury in HIV-1-infected patients. AIDS 24: 2629–2637. PLOS ONE | www.plosone.org 7 March 2013 | Volume 8 | Issue 3 | e55632