Original Article

Obesity

OBESITY BIOLOGY AND INTEGRATED PHYSIOLOGY

Toll-like Receptor 5 in Obesity: The Role of Gut Microbiota and Adipose Tissue Inflammation Satu Pekkala1,2*, Eveliina Munukka1,2*, Lingjia Kong3, Eija P€ oll€ anen1, Reija Autio3,4, Christophe Roos3, Petri Wiklund1, 5 5 6 Pamela Fischer-Posovszky , Martin Wabitsch , Markku Alen , Pentti Huovinen2,7, and Sulin Cheng1

Objective: This study aimed at establishing bacterial flagellin-recognizing toll-like receptor 5 (TLR5) as a novel link between gut microbiota composition, adipose tissue inflammation, and obesity. Methods: An adipose tissue microarray database was used to compare women having the highest (n 5 4, H-TLR) and lowest (n 5 4, L-TLR) expression levels of TLR5-signaling pathway genes. Gut microbiota composition was profiled using flow cytometry and FISH. Standard laboratory techniques were used to determine anthropometric and clinical variables. In vivo results were verified using cultured human adipocytes. Results: The H-TLR group had higher flagellated Clostridium cluster XIV abundance and Firmicutes-toBacteroides ratio. H-TLR subjects had obese phenotype characterized by greater waist circumference, fat %, and blood pressure (P < 0.05 for all). They also had higher leptin and lower adiponectin levels (P < 0.05 for both). Six hundred and sixty-eight metabolism- and inflammation-related adipose tissue genes were differentially expressed between the groups. In vitro studies confirmed that flagellin activated TLR5 inflammatory pathways, decreased insulin signaling, and increased glycerol secretion. Conclusions: The in vivo findings suggest that flagellated Clostridium cluster XIV bacteria contribute to the development of obesity through distorted adipose tissue metabolism and inflammation. The in vitro studies in adipocytes show that the underlying mechanisms of the human findings may be due to flagellin-activated TLR5 signaling. Obesity (2015) 00, 00–00. doi:10.1002/oby.20993

Introduction Obesity and related metabolic disorders are characterized by increased adipocity, impaired glucose and lipid metabolism, insulin resistance (IR), and inflammation (1,2). Over the past decade several studies have highlighted the possible role of gut microbiota in the development of obesity and related disorders (3). Various infections and gut dysbiosis have been proposed to link the inflammation to obesity and metabolic complications though the mechanisms are not well understood (4). Consequently, it is thought that inflammation

has an important role in the development of obesity-associated IR (5). Toll-like receptors (TLR) are pattern-recognition receptors that sense the pathogens and have been proposed to act as a link between inflammation and metabolism. However, among the TLR family members, only the most studied TLR2 and TLR4 have been associated with obesity and IR (6). TLR4 is activated by lipolysaccharides (LPS) from Gram-negative bacteria. TLR2, which forms a receptor complex with TLR1 or TLR6 recognizes peptidoglycans and

1

Department of Health Sciences, University of Jyv€askyl€a, Jyv€askyl€a, Finland. Correspondence: Satu Pekkala ([email protected]) 2 Department of Medical Microbiology and Immunology, University of Turku, Turku, Finland 3 Department of Signal Processing, Tampere University of Technology, Tampere, Finland 4 School of Health Sciences, University of Tampere, Tampere, Finland 5 Division of Pediatric Endocrinology and Diabetes, University Medical Center Ulm, Ulm, Germany 6 Department of Medical Rehabilitation, Oulu University Hospital, Oulu, Finland 7 Division of Health Protection, National Institute of Health and Welfare, Turku, Finland.

Funding agencies: This study was financially supported by the Finnish Academy SKIDI-KID program, by the Finnish Academy postdoctoral research fellow for Dr. Satu Pekkala (267719), and by the Finnish Diabetes Research Foundation. Disclosure: The authors declared no conflict of interest Author contributions: S.P. and S.C. designed the experiments. S.P., E.M., and E.P. performed the laboratory experiments and analyses and P.K.W. and E.P. the statistical analyses. S.P., L.K., R.A., and C.R. were responsible for the microarray data analysis. M.A. was the study physician. S.P., E.M., E.P., P.F-P., M.W., and P.H. were involved in the interpretation of the results and revised the article. S.P. and E.M. wrote the article. P.K.W., M.A., L.K., R.A., C.R., and S.C. revised the article. All authors approved the final version of the manuscript. *Satu Pekkala and Eveliina Munukka contributed equally to this work. Christophe Roos’s present address is Euformatics Oy, Espoo, Finland. Additional Supporting Information may be found in the online version of this article. Received: 26 August 2014; Accepted: 3 November 2014; Published online 00 Month 2015. doi:10.1002/oby.20993

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lipoproteins from Gram-positive bacteria. These bacterial compounds have been shown to increasingly translocate from the gut to adipose tissue in response to high-fat feeding and further affect metabolism in peripheral tissues (3). While the roles of TLR2 and TLR4 in metabolic disorders have been explored, the other TLR family members by far have been left without ample attention. Mouse studies have shown that TLR1, TLR5, TLR8, TLR9, and TLR12 are overexpressed in visceral adipose tissue of diet-induced obese and genetically obese ob/ob mice (7). However, the role of TLR5 in obesity and metabolism is unknown. Therefore, the aims of this study were to clinically characterize women overexpressing TLR5 signaling pathway genes in the adipose tissue, and identify potential TLR5 activators, such as flagellated members of gut microbiota to find a possible link to obesity and inflammation. The underlying mechanisms for TLR5-mediated changes in humans were verified using flagellin and cultured human adipocytes.

Gut Microbiota, TLR5, Inflammation, and Obesity Pekkala et al.

lar Probes, Eugene, OR) and flow cytometry were used to analyze the fecal microbiota composition as described previously (9,10). The R DNA-stain (Molecular Probes, bacteria were stained with SYTOXV Eugen, Oregon) and analyzed with BD FACSCaliburTM flow cytometer (Becton Dickinson, San Jose, CA). Data were analyzed using CellQuestTM software (Becton Dickinson).

Adipose tissue biopsies, RNA isolation, and microarray experiments The subcutaneous adipose tissue biopsies were taken under sterile conditions between 7 and 9 am after overnight fasting. Biopsies were frozen in liquid nitrogen and stored at 280 C until used. Total RNA was isolated using FastPrep systems (MP Biomedicals, France) and RNeasy Lipid Tissue Mini Kit (Qiagen, Valencia, CA), amplified and processed using the GeneChip 30 IVT Express Kit (Affymetrix, Santa Clara, CA) and hybridized on Affymetrix Human Genome U219 Array Plates as described previously (10). The analysis and validation of transcriptomics data is described in Supporting Information methods.

Methods Human study subjects Participants were recruited from a larger study (the AMB-study, The Finnish Academy SKID-KID program), conducted at the University of Jyv€askyl€a in accordance with the Helsinki Declaration and approved by the ethical committee of the Central Finland Health Care district. Informed consent was given by all subjects prior to the assessments. Exclusion criteria were major current/chronic diseases (cancer, psychiatric, neurological, cardiovascular and rheumatic musculoskeletal conditions and type 1 diabetes), Crohn’s disease, celiac disease and eating disorders. For group comparisons we selected from our microarray database (Kong et al., in preparation) female subjects who had the highest (H-TLR group, n 5 4) and lowest (L-TLR group, n 5 4) expression levels of several genes (TLR5, CD86, CCL4, MyD88, Jun, Ly96) of the TLR-signaling pathway (KEGG ID hsa04620). The samples of this study have been submitted to ArrayExpress.

Background information, anthropometrical, and body composition assessments Medical history and current health status were collected via selfadministered questionnaire and checked by a physician. Body composition and anthropometrical variables were determined as described previously (8).

Blood and biochemical measurements Blood samples were drawn in the morning (7-9 am) after overnight fasting. Plasma glucose, serum triglycerides, total cholesterol and high-density lipoprotein (HDL), serum insulin, adiponectin, and leptin, as well as HOMA-IR, were determined as described previously (8).

Cells and reagents SGBS preadipocytes (11) were maintained in DMEM/F12 supplemented with 10% FBS (Invitrogen, Carlsbad, CA), 0.33 lM biotin (Sigma-Aldrich, St Louis, USA) plus 0.17 lM panthotenat (P/B, Sigma-Aldrich) and penicillin/streptomycin solution (Invitrogen). To differentiate the preadipocytes into mature adipocytes the cells were incubated for 4 days in DMEM/F12 supplemented with P/B, 0.01 mg ml21 transferrin, 20 nM insulin, 100 nM cortisol, 0.2 nM triiodothyronine, 25 nM dexamethasone, 250 lM IBMX and 2 lM rosiglitazone (all from Sigma-Aldrich). Afterward the mature adipocytes were incubated in DMEM/F12 supplemented with P/B, 0.01 mg ml21 transferrin, 20 nM insulin, 100 nM cortisol and 0.2 nM triiodothyronine either for 1 or 10 days. LPS and recombinant flagellin (Salmonella typhimurium) were from Sigma Aldrich and Invivogen (San Diego, CA), respectively. When exposing the cultured adipocytes LPS was used at a concentration of 100 ng ml21 and flagellin at 10 ng ml21. Determination of optimal concentrations is described in Supporting Information Results.

Immunofluorescence For confocal microscopy imaging and staining differentiated SGBS cells were fixed for 15 min with 4% PFA-PBS, permeabilized with 0.5% Triton-X for 5 min, blocked 1 h with 5% donkey serum and thereafter incubated with primary antibody over night at 4 C. Immunolabeling was performed using rabbit polyclonal antibodiy against TLR5 (Pierce, Appleton, WI, 1:50 in 1% donkey serum) and donkey anti-rabbit Alexa Fluor 555 as secondary antibody (Invitrogen). The labeled cells were imaged using an inverted wide-field microscope (Carl Zeiss) with a confocal unit and 403 oil/1.4 NA objective (Carl Zeiss).

Fecal samples

Protein extraction from SGBS adipocytes and Western blot analysis

Fecal samples (from the above-mentioned eight subjects) were collected and stored at -70 C until processing. After separating the bacterial cells, the 16S rRNA-targeted oligonucleotide probes labeled at the 50 -end with Cy5 indocarbocyanin (Ex/Em 646/662 nm; Molecu-

Proteins from the 5-days differentiated SGBS adipocytes were extracted at 14 C using an ice-cold lysis buffer (10 mM Tris-HCl, 150 mM NaCl2, 2 mM EDTA, 1% Triton X-100, 10% glycerol and 1 mM DTT), supplemented with protease and phosphatase inhibitors

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inhibitors (Sigma Aldrich). About 15-20 lg of protein extracts were separated by SDS-Page using 4-20% Criterion gradient gels (BioRad Laboratories, Richmond, CA) and transferred to nitrocellulose membranes. After blocking, the membranes were probed overnight at 4 C with primary antibodies purchased from Cell Signaling Technology (Danvers, MA) (except anti-GAPDH, which was from Sigma-Aldrich). As a secondary antibody Odyssey anti-rabbit IRDye 800 (LI-COR Biosciences, Lincoln, NE) was used. Finally, the blots were scanned and quantified by using Odyssey CLX Infrared Imager of Li-COR and manufacturer’s software. When re-probing was needed, the membranes were incubated in 0.2 M NaOH for 10 min at RT, washed with TBS and re-probed with appropriate antibodies. All samples and results were normalized to GAPDH.

RNA extraction and real-time quantitative PCR from SGBS adipocytes The 5-days differentiated adipocytes were homogenized in Trizol reagent (Invitrogen) and the total RNA was extracted according to the supplier’s protocol. Total RNA was reverse transcribed according to the manufacturer’s instructions using High Capacity cDNA Synthesis Kit (Applied Biosystems, Foster City, CA). Real-time PCR analysis was performed using in-house designed primers, iQ SYBR Supermix and CFX96TM Real-time PCR Detection System (Bio-Rad Laboratories, Richmond, CA). The primer sequences were as follows; TLR4: Fwd50 AAGCCGAAAGGTGATTGTTG0 3 and Rev50 CTGAGCAGGGTCTTCTCCAC0 3; TLR5: Fwd50 TCAAACCC CTTCAGAGAATCCC0 3 and Rev50 TTGGAGTTGAGGCTTAGTC CCC0 3; MMP9: Fwd50 GAGTGGCAGGGGGAAGATGC0 3 and Rev 50 CCTCAGGGCACTGCAGGATG0 3; SCD1: Fwd50 TGCAGGACGA TATCTCTAGC0 3 and Rev50 ACGATGAGCTCCTGCTGTTA0 3; FASN: Fwd50 TATGCTTCTTCGTGCAGCAGTT0 3 and Rev50 GCT GCCACACGCTCCTCTAG0 3; Citrate synthase: Fwd50 GAGCAG GGTAAAGCCAAGAAT0 3 and Rev50 CCCAAACAGGACCG TGTAGT0 3; COXIV: Fwd50 CGAGCAATTTCCACCTCTGT0 3 and Rev50 GGTCACGCCGATCCATATAA0 3; GAPDH: Fwd50 CCACCC ATGGCAAATTCC0 3 and Rev50 TGGGATTTCCATTGATGACA A0 3; NF-jB: Fwd50 ATGGCTTCTATGAGGCTGAG0 3 and Rev50 CA CAGCATTCAGGTCGTAGT0 3. Relative expression levels for each gene were calculated with the DDCt method and normalized to the expression of GAPDH.

Reactive oxygen species and glycerol measurement from cell culture media For glycerol measurement 14-days differentiated SGBS adipocytes were treated with flagellin or LPS for 1 and 4 h. Afterward the cell culture media was collected and centrifuged for 5 min at 300g. Glycerol was measured using the KONELAB 20XTi analyzer (Thermo Fischer Scientific). For reactive oxygen species (ROS) measurement the cells were treated with flagellin or LPS for 4 and 24 h. ROS were detected using a cell-based ROS-GloTM H2O2 Assay and Glomax Multidetection System (Promega, Madison, WI).

Statistical analysis Descriptive results are given as means and 95% confidence interval (CI). Non-parametric Mann-Whitney U was used for the statistical comparison of blood biomarkers, anthropometric variables and microbiota parameters between the groups. For cell culture experiments the

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Kruskall-Wallis or one-way ANOVA followed with Tukey HSD post hoc test were used to locate the differences between groups.

Results Increased adipose tissue expression of TLR5 pathway genes associated in humans with obesity, metabolic changes, and dysbiotic gut microbiota composition To study which clinical manifestations were associated with TLR5 signaling in humans, we compared women who had the highest (HTLR group, n 5 4) and lowest (L-TLR group, n 5 4) expression levels of several genes (TLR5, CD86, CCL4, MyD88, Jun, Ly96) belonging to the TLR5 signaling pathway (KEGG ID hsa04620) in the subcutaneous adipose tissue. The respective fold differences between the groups were: TLR5 1.9, CD86 1.9, CCL4 4.5, Ly96 2.8, MyD88 1.2 and Jun 2. The groups did not differ on the expression levels of other TLRs. We found that the subjects in the H-TLR group were heavier and had higher BMI (P50.043 for both, Table 1). They also had significantly greater waist circumference, fat % and systolic blood pressure (P < 0.05 for all, Table 1). Their metabolism seemed to be distorted as shown by a higher blood levels of leptin accompanied with lower levels of adiponectin (P < 0.05 for both, Table 1). In addition, subjects in the H-TLR group tended to have higher low-density lipoprotein (LDL) (P 5 0.146) and triglycerides (P 5 0.083). Determination of the gut microbiota composition revealed a significant dysbiosis in the H-TLR group (Figure 1). The H-TLR group had more flagellated Clostridium cluster XIV as compared to the L-TLR group (P 5 0.029). They also tended to have higher Firmicutes-toBacteroides ratio (P 5 0.057). Because of the limited number of subjects and relatively high inter-individual variation in bacterial groups, no other significant differences were found. H-TLR group, however, had 20% less Bifidobacterium than L-TLR group. The group comparison of the adipose tissue microarray data showed that there were 419 up-regulated and 249 down-regulated genes in the H-TLR group (adjusted P < 0.05, Supporting Information Table S1) compared to L-TLR group. Clustering analysis of the data of differentially expressed genes (DEGs) showed that the samples clustered into the expected groups, i.e., L-TLR and H-TLR, as presented in the clustering result with the heat map in Supporting Information Figure S1. According to gene set enrichment analysis on KEGG pathways and Gene Ontology terms, the DEGs encompassed 20 cellular pathways and 376 biological processes, respectively (Table 2 and Supporting Information Table S2). The enriched pathways were related to metabolism and inflammation, specifically in the defense against pathogenic E. coli infections, B cell signaling and leukocyte transendothelial migration (Table 2). The finding that TLR5 expression was higher in obese than lean subjects was validated by using Gene Expression Omnibus (GEO) and the GDS3679 dataset (12). In addition, by utilizing GEO2R tool we compared subjects with highest (n 5 3) and lowest (n 5 3) TLR5 expression, and found that 80% of the DEGs that were part of the enriched in KEGG pathways (Table 2), were up- and downregulated similarly to our data. However, the genes of E. coli infections were not found similarly expressed (data not shown).

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TABLE 1 Clinical and anthropometric characterization of the human study subjects

Variable Age (years) Weight (kg) Waistline (cm) Fat (%) BMI BP systolic (mmHg) BP diastolic (mmHg) Glucose (mmol l21) Insulin (uIU ml21) HOMA-IR Trigly (mmol l21) Chol (mmol l21) HDL (mmol l21) LDL (mmol l21) Adiponectin (ng ml21) Leptin (ng ml21)

H-TLR mean (95% CI), n54

L-TLR mean (95% CI), n54

P value

29 (22-61) 85.6 (57.7-124.4) 103.9 (80.6-128.6) 44.2 (35.8-52.6) 30.6 (20.2-43.4) 138 (126-149) 85 (65-104) 5.59 (4.17-7.00) 12.03 (6.91-17.15) 2.77 (1.77-3.76) 1.64 (0.93-2.34) 5.80 (5.30-6.30) 1.41 (0.46-2.35) 2.88 (2.74-4.61) 7.06 (4.32-9.79) 67.00 (19.58-114.41)

26 (2-51) 55.0 (39.6-70.5) 70.9 (61.1-80.6) 27.1 (18.8-35.4) 20.7 (16.3-25.1) 109 (100-118) 66 (50-81) 4.62 (4.20-5.03) 4.34 (1.71-6.95) 0.90 (0.31-1.49) 1.07 (0.42-1.72) 5.13 (3.00-7.25) 1.78 (1.24-2.31) 3.68 (1.33-4.42) 19.64 (7.11-32.17) 21.55 (214.17-57.26)

1.000 0.043 0.021 0.021 0.043 0.020 0.043 0.386 1.000 0.564 0.083 0.468 0.248 0.146 0.021 0.043

L-TLR, low TLR expression group; H-TLR, high TLR expression group; BP, blood pressure; Trigly, triglycerides; Chol, total cholesterol.

Functional changes in response to flagellin and LPS treatment in cultured human adipocytes We first determined that TLR5 protein was expressed in both 5- and 14-days differentiated SGBS adipocytes by Western blot and immunofluorescence (Figure 2). For Western blot protein extracts from white blood cells were used as positive control. Confocal microscopy revealed a small part of TLR5 pool was located on the mature adipocyte cell surface and the majority in different intracellular compartments (Figure 2). After verifying the presence of TLR5 in human adipocytes we studied whether flagellin induced functional

Figure 1 The gut microbiota composition of H-TLR (n 5 4) and L-TLR (n 5 4) groups. The gut microbiota composition was profiled from the fecal samples of human subjects using flow cytometry and FISH. The results are shown as percentage proportions of fecal bacterial groups. Data is presented as mean 6 SD. * indicates a statistical significance, P < 0.05. F. prausnitzii, Faecalibacterium prausnitzii; Erec, Clostridium cluster XIV; F/B ratio, Firmicutes-to Bacteroides ratio.

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changes in adipocytes that could explain the in vivo findings. LPS, which is known to affect adipocyte metabolism via TLR4 was used as a control in addition to mock-treated cells. In 5-days differentiated adipocytes flagellin induced a 3.4-fold increase in TLR5 mRNA expression (P 5 0.006, Figure 3). Flagellin did not affect the expression of TLR4 (Figure 3). Instead it increased the expression of the TLR downstream target NF-jB (1.8-fold, P 5 0.026) and lipogenetic SCD1 (1.5-fold, P 5 0.035) at 1 h. In addition, 4-h treatment with flagellin augmented the expression of inflammatory MMP-9, which was also overexpressed in the H-TLR group adipose tissue, by 1.9-fold (P 5 0.001). LPS increased the expression of TLR5 by 2.6-fold (P 5 0.033), NF-jB by 1.7-fold (P 5 0.047) and SCD1 by 1.5-fold (P 5 0.009) compared to the mock treatment at 1 h. After 4 h the expression of TLR4 (1.7-fold, P 5 0.015), MMP-9 (1.5-fold, P 5 0.003), and SCD1 (1.4-fold P 5 0.045) were increased in response to the LPS treatment. Next, we studied whether LPS and flagellin affected the phosphorylation levels of proteins related to insulin signaling and other intracellular, metabolism-related signaling routes. As an indication of decreased insulin signaling in 5-days differentiated adipocytes, we found that both flagellin and LPS increased inhibitory serine phosphorylation of IRS1, and decreased in downstream Akt phosphorylation (Figure 4). Flagellin decreased the phosphorylation of Akt (P < 0.001) and increased the phosphorylation mTOR (P < 0.001) and ERK1/2 (P 5 0.042). LPS decreased the phosphorylation of Akt (P 5 0.004) compared to the mock treatment. The phosphorylation of 4EB-P1 downstream from mTOR and AMPK seemed to increase due to both treatments, but did not reach statistical significance. As an indication of increased lipolysis, in 14-days differentiated adipocytes both flagellin and LPS increased glycerol secretion significantly at 4 h (P < 0.05 for both, Figure 5). Both flagellin and LPS

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TABLE 2 KEGG pathway enrichment of the differentially expressed adipose tissue genes in the H-TLR group

KEGG ID

P value

Count

Size

Term

Gene names in the pathway

280

0.0003

9

46

Valine, leucine, and isoleucine degradation

1032 640 531 4510

0.0005 0.001 0.001 0.003

7 7 5 19

31 35 18 203

603 5130

0.003 0.004

4 8

14 54

Glycosphingolipid biosynthesis globo series Pathogenic Escherichia coli infection (EHEC)

5131

0.004

8

54

Pathogenic Escherichia coli infection (EPEC)

4670

0.004

13

119

4610

0.005

9

69

Complement and coagulation cascades

4662 530 1040 910 4650

0.011 0.013 0.019 0.025 0.027

8 5 4 4 12

65 30 22 24 135

B cell receptor signaling pathway Aminosugars metabolism Biosynthesis of unsaturated fatty acids Nitrogen metabolism Natural killer cell mediated cytotoxicity

5110

0.027

7

62

52 511 4060

0.033 0.038 0.044

4 3 19

26 16 263

4614

0.044

3

17

ACADM, ALDH6A1, AUH, BCKDHB, DBT, HADH, MUT, PCCA, PCCB GBA, GLB1, GNS, GUSB, HEXB, HPSE, MAN2B1 ACACB, ACADM, ACSS3, ALDH6A1, MUT, PCCA, PCCB GLB1, GNS, GUSB, HEXB, HPSE ACTB, ACTG1, BIRC3, COL6A1, COL6A2, COL6A6, FLNA, GRB2, ITGB5, JUN, MYL9, PDGFA, PIK3R5, PPP1CA, RAC2, SPP1, VAV1, VEGFA, ZYX GBGT1, GLA, HEXB, NAGA ACTB, ACTG1, CD14, HCLS1, LY96, TUBA1C, TUBB2A, TUBB2B ACTB, ACTG1, CD14, HCLS1, LY96, TUBA1C, TUBB2A, TUBB2B ACTB, ACTG1, CYBA, GNAI1, ICAM1, ITGB2, MMP9, MSN, MYL9, NCF4, PIK3R5, RAC2, VAV1 C1QA, C1QB, C1QC, C1R, C1S, C3AR1, C6, F13A1, SERPINE1 BLNK, FCGR2B, JUN, PIK3R5, PTPN6, RAC2, SYK, VAV1 CHIT1, HEXB, HK3, NAGK, NPL ACOT7, FADS1, PECR, PTPLB CA2, CA3, CTH, GLUL FCER1G, GRB2, HCST, ICAM1, ITGB2, PIK3R5, PTPN6, RAC2, SYK, TNFSF10, TYROBP, VAV1 ACTB, ACTG1, ATP6V0B, ATP6V1F, KCNQ1, PRKX, TCIRG1 GAA, GLA, GLB1, HK3 GLB1, HEXB, MAN2B1 CCL13, CCL18, CCL19, CCL2, CCL22, CCL3, CCL4, CSF1R, CSF2RB, CXCL16, GHR, IL10RA, PDGFA, TNFRSF12A, TNFRSF1B, TNFSF10, TNFSF13B, TSLP, VEGFA AGTR1, ANPEP, CTSG

Glycan structures degradation Propanoate metabolism Glycosaminoglycan degradation Focal adhesion

Leukocyte transendothelial migration

Vibrio cholerae infection Galactose metabolism N-Glycan degradation Cytokine-cytokine receptor interaction

Renin-angiotensin system

Size is the total amount of genes involved in this pathway. Count is the amount of differentially expressed genes that map in this pathway.

The subjects with higher expression levels of TLR5 signaling pathway genes (H-TLR group) had significantly higher fat mass and several metabolic alterations as well as dysbiotic gut microbiota composition. The results of the present study suggest biochemical and signaling pathways that interconnect the gut microbiota, specifically flagellated Clostridium cluster XIV, with TLR5 signaling, metabolic changes and obesity.

adipose tissue and local hypoxia also drive the development of its vasculature (15). Accordingly, as a result of adipose tissue hypoxia several genes involved in cellular respiration (e.g., IDH, OXA, and UQCR) were found to be down-regulated in the H-TLR group. In addition, H-TLR subjects were characterized by increased expression of several genes related to apoptosis and inflammation-induced cell death (e.g. BAG3, CASP3, TNFRSF12A, and TNFRSF1B), which may be ascribed to adipocyte hypertrophy and local hypoxia since various genes related to vasculogenesis (e.g., EGFL6, VEGFA, MMP9, and MMP19) were over-expressed. Nevertheless, the mechanisms which sustain the constant stimuli for macrophage infiltration into the adipose tissue are unknown.

Generally, in obesity impaired lipid metabolism participates in the development of adipocyte hypertrophy (13), which in turn leads to local hypoxia and subsequent cell death. These changes drive macrophage infiltration into the adipose tissue ensuing extracellular matrix (ECM) remodeling and inflammation (14). The expansion of

Our results suggest several possible underlying causes. First, dysbiotic gut microbiota composition can disrupt the epithelial barrier facilitating bacterial translocation and induction of inflammation in the host (16,17). Decreased amounts of Bifidobacteria have been shown to increase intestinal permeability (18) and an increase in Bifidobacteria

increased inflammatory ROS production (Figure 5). The increase was significant in response to flagellin treatment at 24 h (P 5 0.04).

Discussion

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Gut Microbiota, TLR5, Inflammation, and Obesity Pekkala et al.

Figure 2 Expression of TLR5 in human SGBS adipocytes. The confocal microscopy images of intracellular localization of TLR5 show that (A) only a minority of the TLR5 pool is located on membrane structures, and (B) the majority of the pool is intracellular in 14-days differentiated SGBS adipocytes. Part of the intracellular TLR5 pool seems to be localized (C, D) in the nuclei and lipid droplet-like structures. (E) Western blot analysis shows the expression of TLR5 (90 kDa) in 5 (5 d) and 14 (14 d) days differentiated adipocytes, as well as in white blood cells (C1), which served as positive control.

and decrease in Clostridium cluster XIV in the gut had beneficial effects on adipose tissue gene expression in obese mice (19). While we and others have associated the abundance of Clostridium cluster XIV with metabolic disorders and obesity (9,20), controversial results of Firmicutes-to-Bacteroides ratio have been reported (9,21). Nevertheless, it may be that the dysbiotic gut microbiota (described by increased fecal Clostridium cluster XIV, possibly Firmicutes-to-Bacteroides ratio, and decreased Bifidobacterium) in the H-TLR group increase intestinal permeability and promote inflammation. Bacteria within Clostridium cluster XIV such as E. rectale are motile i.e., they carry flagella and the corresponding genes in their genome (22). Thus flagellated Clostridium cluster XIV representatives are potential TLR5 activators. It has been shown that representatives of cluster XIV induce colonic Treg (23) and their abundance has been associated to immunodominance in Crohn’s disease, characterized by increased intestinal permeability (24). Therefore, too high abundance of Clostridium cluster XIV could induce inflammation through flagellin and TLR5. Importantly, the S. typhimurium flagellin used in our in vitro experiments shares a similar structure with E. rectale flagellin (25). Clostridium cluster XIV representatives are also active short-chain fatty acids (SCFA) producers. While the host can actually benefit of SCFAs at normal range (26), increased production and decreased catabolism can have lipogenic effects on the host (27). In the adi-

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pose tissue of H-TLR group several SCFA catabolic genes (e.g., AACS, ACSS3, HADH, ACACB, and ACADM) were down-regulated while lipogenic genes were over-expressed. Therefore, increased production of SCFAs by Clostridium cluster XIV and the decreased catabolism may create a vicious circle providing base for the increased lipogenesis and inflammation. Second, during innate immunity to bacteria the classical complement pathway and C1Q are known to be activated [e.g., (28)]. Accordingly, in the H-TLR group adipose tissue C1QA, C1QB, and C1QC were over-expressed. Third, in cells other than adipocytes infectious bacteria are known to attach to ECM integrins. The interaction between the bacterial adhesins and host integrins (29) results in cytoskeleton reorganization of adipocytes and subsequent infiltration of inflammatory cells into the tissue (30). Interestingly, in H-TLR adipose tissue these mechanisms were activated, as shown by the over-expression of KEGG pathway for pathogenic Escherichia coli infection genes (KEGG pathway 5130, Table 2). Involvement of tissue bacteria in diabetes and obesity has been shown also by Amar et al. (31). It could, however, be questioned whether the gut microbes are the cause or the consequence of obesity. While both options may exist, our functional tests in cultured human adipocytes indicate that flagellin could be in part responsible of the metabolic disturbances in obese humans although further studies are needed to confirm the

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Figure 3 mRNA fold changes of selected genes in response to LPS and flagellin treatment of human SGBS adipocytes. SGBS adipocytes were differentiated for 5 days and afterward treated with 100 ng ml21 LPS or 10 ng ml21 flagellin (FLG) for 1 or 4 h. Total RNA was extracted from the cells and reverse transcribed. mRNA fold changes were determined by quantitative PCR and normalized to GAPDH. TLR4, toll-like receptor 4; TLR5, toll-like receptor 5; NF-jB, nuclear factor kappa B; SCD1, stearoyl coenzyme desaturase 1; MMP-9, matrix metalloprotease 9. Quantification was made from three or four independent experiments (mean 6 SD shown). * indicates a statistical significance, P < 0.05.

causal relationship. We confirmed that TLR5 was expressed in mature human adipocytes. The location of TLR5, which has been debated by other researchers, varied inside the cells. In dendritic cells, TLR5 has been found on the cell surface (32), and in breast cancer cell lines on the surface and intracellular compartments (33). Our results with human adipocytes show that a very small part of the TLR5 pool was located on the cell surface and the majority in different intracellular compartments. TLRs induce inflammation through activation of several kinases and the NF-jB pathway (6). Intracellular kinase activation, such as ERK1/2, inhibits insulin signaling by inducing the inhibitory serine phosphorylation of IRS1 (34). In accordance with that, our results showed that flagellin induced NF-jB expression, ERK1/2 phosphorylation and the inhibitory serine phosphorylation of IRS1.

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Triggering of intracellular kinases has also additional metabolic effects through activation of the mTOR pathway, which can lead to increased endoplasmic reticulum stress and lipogenesis (35). Flagellin treatment enhanced mTOR phosphorylation in SGBS adipocytes. Flagellin further induced other functional changes in adipocytes indicating that TLR5 can be partly responsible of obesity and metabolic changes found in the H-TLR subjects. First, flagellin increased glycerol secretion. In vivo glycerol produced by adipose tissue lipolysis is taken up and used by the liver for lipid synthesis (36). Accordingly, the H-TLR subjects tended to have higher triglycerides indicating higher rate of lipid synthesis. Interestingly, they also had higher levels of leptin, which can up-regulate the expression of several TLRs (37). Thus, some of the effects of TLR5 may be mediated

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Figure 4 Changes in the phosphorylation levels of several intracellular signaling proteins in response to LPS and flagellin treatment of human SGBS adipocytes. SGBS adipocytes were differentiated for 5 days and afterwards treated with 100 ng ml21 LPS or 10 ng ml21 flagellin (FLG) for 1 or 4 h. Cell lysates were then analyzed by Western blotting for phosphor-IRS1 (Insulin receptor substrate 1), phospho-Akt, phospho-mTOR (Mammalian target of rapamycin), phospho-4EB-P1 (eukaryotic initiation factor 4E binding protein), phospho-AMPK (AMP-activated protein kinase), and phospho-ERK1/2 (extracellular signal-regulated kinase). Quantification was made from three or four independent experiments (mean 6 SD shown). * indicates a statistical significance, P < 0.05.

by leptin. In obese individuals increased leptin concentrations induce target cells to become resistant to its actions, which may contribute to obese phenotype and metabolic changes in H-TLR subjects. Finally, an increased inflammation in response to flagellin was reflected in higher ROS production and SCD1 expression in the adipocytes. Accordingly, SCD1-deficient adipocytes have been shown to exhibit reduced inflammatory response to LPS treatment (38).

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While in response to flagellin SCD1 expression increased, Fatty acid synthase did not, indicating that possibly the overall lipogenesis is not enhanced. In metabolic disorders ROS production increases due to intermediary metabolites and growing evidence indicates that TLRs may be involved in this process (39). ROS activate inflammatory pathways including NF-jB, as well as fatty acid desaturation mediated by SCD1 (40), which are in agreement with our results.

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Original Article

Obesity

OBESITY BIOLOGY AND INTEGRATED PHYSIOLOGY

Figure 5 Reactive oxygen species (ROS) production and glycerol secretion in SGBS adipocytes in response to LPS and flagellin treatment. SBGS adipocytes were allowed to differentiate for 14 days. For glycerol measurement, the cells were treated with flagellin or LPS for 1 and 4 h. Afterward glycerol was measured in the cell culture media. For ROS measurement, the cells were treated with flagellin or LPS for 4 and 24 h and ROS detected by luminescence. Quantification was made from four or five independent experiments (mean 6 SD shown). * indicates a statistical significance, P < 0.05.

In conclusion, our study describes, to our best knowledge for the first time, that flagellin through adipose tissue TLR5 signaling may be involved in obesity and related metabolic changes. The gene expression and gut microbiota analysis from human subjects identified possible new underlying factors for the increased TLR5 signaling related to fat mass and metabolic changes. Our results suggest that the dysbiotic gut microbiota composition contribute to inflammation, which involves ECM degradation, actin filament

remodeling and TLR5 signaling (Figure 6). Moreover, flagellated Clostridium cluster XIV species may serve as potential activators of TLR5. Finally, the changes in adipose tissue further contribute to the obese phenotype with unfavorable metabolism. The findings in humans are corroborated by the in vitro results showing that in cultured human adipocytes flagellin decreased insulin signaling and increased inflammatory ROS production and glycerol secretion. O

Figure 6 The underlying mechanisms and consequences of increased toll-like receptor signaling in humans. The dysbiotic gut microbiota composition [high abundance of Clostridium cluster XIV (EREC) and distorted Firmicutes-to-Bacteroides ratio (F/B ratio)] cause leakage of bacteria from the gut, leading to attachment of bacteria or bacterial compounds to adipose tissue integrins that initiate ECM degradation, actin filament remodeling, TLR signaling, and adipose tissue inflammation. The changes in adipose tissue further contribute to obesity and metabolic changes.

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Acknowledgments We thank Tiina Partanen, Kaisa-Leena Tulla, and Risto Puurtinen for the excellent technical assistance and Paavo Rahkila for helping with the confocal microscopy images. We also thank Soile Tuomela, Omid Rasool, and Riitta Lahesmaa (all from the University of Turku, Finland) for the microarray measurements. C 2014 The Obesity Society Copyright V

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