Adipose tissue inflammation is present in insulin-resistant conditions. We recently proposed a network of microRNAs (miRNAs) and transcription factors (TFs) regulating the production of the proinflammatory chemokine (C-C motif) ligand-2 (CCL2) in adipose tissue. We presently extended and further validated this network and investigated if the circuits controlling CCL2 can interact in human adipocytes and macrophages. The updated subnetwork predicted that miR-126/-193b/-92a control CCL2 production by several TFs, including v-ets erythroblastosis virus E26 oncogene homolog 1 (avian) (ETS1), MYC-associated factor X (MAX), and specificity protein 12 (SP1). This was confirmed in human adipocytes by the observation that gene silencing of ETS1, MAX, or SP1 attenuated CCL2 production. Combined gene silencing of ETS1 and MAX resulted in an additive reduction in CCL2 production. Moreover, overexpression of miR-126/-193b/-92a in different pairwise combinations reduced CCL2 secretion more efficiently than either miRNA alone. However, although effects on CCL2 secretion by co-overexpression of miR-92a/-193b and miR-92a/-126 were additive in adipocytes, the combination of miR-126/-193b was primarily additive in macrophages. Signals for miR-92a and -193b converged on the nuclear factor-κB pathway. In conclusion, TF and miRNA-mediated regulation of CCL2 production is additive and partly relayed by cell-specific networks in human adipose tissue that may be important for the development of insulin resistance/type 2 diabetes.
White adipose tissue (WAT) function plays an important role in the development of insulin resistance/type 2 diabetes. Fat cells present in WAT secrete a number of molecules, collectively termed adipokines, which affect insulin sensitivity by autocrine and/or paracrine mechanisms (1,2). In insulin-resistant obese subjects, WAT displays a chronic low-grade inflammation, which is proposed to alter insulin signaling by increased fatty acid release and altered adipokine production (3).
Chemokine (C-C motif) ligand-2 (CCL2), also referred as monocyte chemoattractant protein-1, is an early proinflammatory signal in WAT that acts by promoting adipose infiltration of macrophages (4,5). After diet-induced obesity, Ccl2-/- mice are less insulin-resistant and display a less pronounced inflammatory reaction in WAT (6). Adipocytes and macrophages both contribute significantly to CCL2 secretion from WAT.
Little is known about the mechanisms regulating WAT inflammation. Results in recent years have demonstrated that microRNAs (miRNAs) play important roles in controlling inflammation in other conditions and nonadipose tissues, as reviewed (7). In mammals, miRNAs act by inhibiting the expression of target genes after binding to defined complementary sites in target 3′-untranslated regions (UTRs) (8).
Cellular function is controlled by transcriptional (transcription factors [TFs]) and posttranscriptional mechanisms (miRNAs). Using global expression profiling data and mathematical models, the transcriptome can be mapped into transcriptional regulatory networks (TRNs), with regulatory elements (e.g., TFs and miRNAs) as nodes and their interactions as edges (9,10). We recently described and partly experimentally verified a miRNA-TF network in the subcutaneous WAT of insulin-resistant obese women that controls the expression of CCL2 (11). This TRN suggests that several miRNAs and TFs interact in different combinations to regulate CCL2 production. Although the reason for this complex regulation and redundancy is not entirely clear, it may allow for more exact fine-tuning of gene expression and/or signal enhancement in response to specific environmental cues. In line with this, recent studies in cancer cells have proposed that partly overlapping regulatory circuits allow signal amplification in an additive or synergistic manner (12,13). To the best of our knowledge, it is not known whether these types of mechanisms are present in WAT or whether they differ between specific cell types within the tissue.
Through combinatorial gain-of-function/loss-of-function studies focusing on TFs and miRNAs, we investigated how transcriptional regulators (TFs and miRNAs) can integrate effects on the expression of inflammatory factors in WAT. First, we extended and further validated the proposed TRN (11). We subsequently silenced potentially important TFs in the network, alone or in combination, and investigated how this altered CCL2 production in human adipocytes. Finally, we determined whether concomitant overexpression of miRNAs in human adipocytes or macrophages resulted in increased effects when compared with overexpressing each miRNA alone.
Research Design and Methods
Cohort 1 comprised 30 obese (BMI >30 kg/m2) and 26 nonobese (BMI <30 kg/m2) women who had no chronic disease and were free of continuous medication. This cohort has been described in detail previously (11). The subjects came to the laboratory in the morning after an overnight fast. Height, weight, and waist circumference were determined. An abdominal subcutaneous WAT biopsy specimen (∼1.0–1.5 g) was obtained by needle aspiration as described (14). One part (300 mg) of the tissue was used for measurement of CCL2 release and expressed per number of fat cells as described (15). Another part of the tissue (at least 500 mg) was subjected to collagenase treatment, and mean adipocyte volume and weight were determined as described (16). Packed fat cells (200 µL) and intact WAT (400 mg) were frozen at −70°C for future mRNA and miRNA measurements as described (11). The Karolinska University Hospital Ethical Committee (Stockholm, Sweden) approved this study. All subjects were informed in detail about the studies, and written informed consent was obtained.
For in vitro studies, subcutaneous WAT was obtained from healthy men and women undergoing cosmetic liposuction. This experimental group was not selected for age, sex, or BMI. Isolation of human adipocyte progenitor cells from subcutaneous WAT was performed as described (17). The progenitor cells obtained from separate individuals were not mixed.
Affymetrix GeneChip Human Gene 1.0 ST and miRNA Array Protocols
Data obtained from gene and miRNA arrays from human subcutaneous WAT (Gene Expression Omnibus number GSE25402) and the protocols have been described (11).
Culture and in vitro differentiation of human adipocyte progenitor cells were performed as described (17). 3T3-L1 and THP1 cells were handled as recommended in the protocols from American Type Culture Collection (Manassas, VA). For the induction of monocyte–macrophage differentiation, THP1 cells were stimulated with 50 ng/mL phorbol 12-myristate 13-acetate (PMA).
miRNA and Small Interfering RNA Transfection
In vitro differentiated adipocytes (day 10–12 postinduction) were treated for 24–48 h with various concentrations (5–40 nmol/L) of miRIDIAN miRNA mimics for overexpression of miRNA activity or 60 nmol/L of miRIDIAN miRNA Hairpin Inhibitors for native miRNA inhibition (Thermo Fisher Scientific, Lafayette, CO) and HiPerFect Transfection Reagent (Qiagen, Hilden, Germany), according to the manufacturers’ protocols. Optimal transfection conditions were determined in separate titration experiments. Transfection efficiency was assessed with real-time quantitative PCR (qPCR) using miRNA probes/assays (Applied Biosystems, Foster City, CA; and Qiagen, respectively). To rule out unspecific effects, control cells were transfected with miRIDIAN miRNA Mimic or Hairpin Inhibitor Non-Targeting Negative Controls (Thermo Fisher Scientific).
In some experiments, in vitro differentiated adipocytes were cotransfected with miScript Target Protector for the miR-92a binding site on specificity protein 12 (SP1; 500 nmol/L; Qiagen) and miR-92a mimics (40 nmol/L) or appropriate control reagents (miScript Target Protector Negative Control; Qiagen) and miRIDIAN miRNA Mimic Non-Targeting Negative Control (Thermo Fisher Scientific). THP1 cells were transfected with miRNA mimics, as described above, for adipocytes 48 h after incubation with PMA.
For RNA interference experiments, adipocytes were treated with various concentrations (10–40 nmol/L), as described above, using ON-TARGETplus SMARTpool small interfering RNA (siRNA) for v-ets erythroblastosis virus E26 oncogene homolog 1 (avian) (ETS1), SP1, or MYC-associated factor X (MAX) and appropriate concentrations of siRNA Non-Targeting Negative Control (Thermo Fisher Scientific) instead of miRNA reagents.
RNA Isolation, cDNA Synthesis, and Real-Time PCR
Total RNA was extracted from in vitro differentiated adipocytes, 3T3-L1 cells, and THP1 macrophages, and purity control was performed as described (11). Synthesis of coding-gene cDNA and real-time qPCR using Taqman probes (Applied Biosystems) was performed as described (11). Synthesis of miRNA cDNA and following real-time qPCR was performed using Applied Biosystems reagents as described (11) or using the miScript II RT Kit and miScript Primer Assays (Qiagen) according to the manufacturer’s instructions. Relative gene expression was calculated using the comparative Ct method (i.e., 2ΔCt-target gene/2ΔCt-reference gene) with 18S as the internal control. Expression of miRNA was normalized to a reference gene RNU48 or SNORD68. Levels of 18S, RNU48, and SNORD68 did not differ between groups.
Cells were lysed in radioimmunoprecipitation assay buffer as described (18). SDS-PAGE was used to separate 15–20 µg total protein, and Western blot was performed according to standard protocols. The membranes were blocked in 3% enhanced chemiluminescence Advance Blocking Agent (GE Healthcare, Buckinghamshire, U.K.). Primary antibodies against ETS1 were from Novocastra Leica Biosystems AB (Wetzlar, Germany) and against SP1 were from Santa Cruz Biotechnology (Santa Cruz, CA). β-Actin (Sigma-Aldrich, St. Louis, MO) was used as a loading control. Secondary antibodies mouse/rabbit IgG-horseradish peroxidase were from Sigma-Aldrich. All tested primary antibodies detecting MAX were unspecific and results therefore could not be demonstrated. Antibody-antigen complexes were detected by chemiluminescence using ECL Select Western Blotting Detection Kit (GE Healthcare).
CCL2 levels in conditioned media from in vitro differentiated adipocytes and macrophages were analyzed using an ELISA assay from R&D Systems (Minneapolis, MN).
Luciferase Reporter Assay
Empty luciferase reporter vector and vector containing a part of 3′UTR of SP1 (enclosing predicted binding site for hsa-miR-92a) were obtained from GeneCopoeia (Rockville, MD). The luciferase reporter assay in 3T3-L1 cells was performed as described (11).
Global Gene Expression Analysis, Motif Activity Response Analysis, and Network Construction
Motif activity response analysis and construction of the adipocyte CCL2 TRN used in this study has been described in detail (11,19). Predicted targets of miRNAs were updated according to the latest release of TargetScan (March 2013).
Data presented are mean ± SEM. When appropriate, the data were log-transformed to become normally distributed. Results were analyzed with unpaired t test, linear regression (simple and multiple), or ANOVA (repeated-measures).
Strategy for Investigating Additive Effects of TFs and miRNAs
To dissect the regulation of adipocyte CCL2 production by miRNAs and TFs, we extended and further validated a recently described TRN present in human fat cells and perturbed in obese insulin-resistant subjects (11). In brief, this in silico–generated TRN links for several miRNAs (miR-92a/-126/-193b/-652 and let-7a), directly or indirectly, through one or two intermediate TF steps, to CCL2 production. For the current study, we focused on a subpart of the TRN comprising two partly validated circuits, from miR-126 and -193b to CCL2, and a third possible candidate, miR-92a, which was not fully characterized in our previous study (Fig. 1A).
miR-92a Regulates CCL2 Production by SP1 in Adipocytes
Because the regulatory edges linking miR-92a to CCL2 have not been explored in detail, we first tested if miR-92a affected its predicted target genes SP1 and ETS1 in human adipocytes. We overexpressed or inhibited miR-92a using miRNA mimics/inhibitors and evaluated expression of SP1 as well as mRNA expression of ETS1. Modulation of miR-92a expression levels affected the mRNA and protein of SP1, whereas ETS1 expression remained unaltered (Fig. 1B–D and Table 1), suggesting that SP1, but not ETS1, is a direct target of miR-92a. The levels of CCL2 in conditioned media mirrored the changes in SP1 mRNA/protein expression (Fig. 1B and D). Luciferase reporter assays confirmed that miR-92a interacted directly with the 3′UTR region of SP1 (Fig. 1E).
To verify that SP1 could regulate CCL2 production in human adipocytes independently of miR-92a, the expression of SP1 was silenced using siRNA at two different concentrations (10 and 20 nmol/L). SP1 gene knockdown significantly attenuated CCL2 secretion (Fig. 2A) and reduced SP1 mRNA/protein levels (Fig. 2B and C). In addition, SP1 silencing affected mRNA expression of two predicted direct targets in the TRN: CCL2 and v-rel reticuloendotheliosis viral oncogene homolog [avian] (REL), a part of the nuclear factor (NF)-κB network (Table 1). To further investigate the role of miR-92a in CCL2 production by SP1, we concomitantly inhibited expression of miR-92a and SP1. The combination of miR-92a inhibition and silencing of SP1 abolished their individual effects on CCL2 production (Fig. 2D). Attenuation of miR-92a levels increased CCL2 secretion to the same extent as previously shown in Fig. 1D. Moreover, simultaneous transfection of miR-92a mimics and a target protector (corresponding to the miR-92a target sequence on SP1 3′UTR) abolished the effect of miR-92a on CCL2 production (Fig. 2E).
Previous validations of the interactions in the CCL2 TRN identified that miR-126 targeted CCL2 directly, whereas miR-193b affected its production indirectly through several TFs, including ETS1 and MAX (11). In the current study, we identified two additional TFs as possible targets for miR-126 and miR-193b, REL and SP1, respectively (Fig. 1A). However, overexpression of miR-126 or miR-193b did not alter REL and SP1 mRNA levels, suggesting that they are not true targets for these miRNAs in human adipocytes (Table 1).
ETS1 and MAX Regulate CCL2 Production in Human Adipocytes by TRN in an Additive Fashion
According to Fig. 1A, ETS1 and MAX are entry TFs for miR-193b; moreover, they have a predicted interaction and have been validated as direct targets of miR-193b (11). To determine whether ETS1 and MAX could affect CCL2 secretion independently of miR-193b, we knocked down ETS1 and MAX in adipocytes using various concentrations of siRNAs, followed by measurements of mRNA levels of their first predicted neighbors in the TRN (Fig. 1A). We could confirm that silencing of the ETS1 gene decreased the mRNA levels of MAX, signal transducer and activator of transcription 6, interleukin-4 induced (STAT6), nuclear factor of k light polypeptide gene enhancer in B-cells 1 (NFKB1), and CCL2, whereas silencing of MAX decreased the mRNA levels of v-rel reticuloendotheliosis viral oncogene homolog B (RELB) (Table 1).
Silencing of ETS1 and MAX with 10 nmol/L of siRNA had modest effects on CCL2 secretion, but higher concentrations (i.e., 20 nmol/L) resulted in significantly decreased CCL2 production (Fig. 3A). Because CCL2 protein levels were affected by both TFs, and MAX mRNA expression was affected by silencing of ETS1, we assessed whether ETS1 and MAX could interact with each other in controlling CCL2 secretion. Indeed, concomitant silencing of ETS1 and MAX using low concentrations (10 nmol/L) of siRNA resulted in a more pronounced reduction of CCL2 secretion (10+10 nmol/L of each siRNA) compared with single knockdown of either TF (Fig. 3A). Expression of CCL2 mRNA followed the same trend as CCL2 secretion (Supplementary Fig. 1A).
Knockdown efficiency was determined by quantifying ETS1 and MAX mRNA levels (Fig. 3B and C). There was a marked decrease in mRNA levels of ETS1 and MAX when silenced alone at 10/20 nmol/L or in combination (10+10 nmol/L). ETS1-siRNA treatment reduced protein levels of ETS1 (Fig. 3D). Owing to the poor specificity of tested MAX antibodies, we were not able to determine protein levels of this TF.
As mentioned above, we observed that 20 nmol/L siRNA (ETS1 or MAX) caused a more pronounced decrease in CCL2 production than 10 nmol/L. Unfortunately, we did not detect significant quantitative differences in the mRNA levels of ETS1 and MAX between 10 and 20 nmol/L of siRNA at a given time point. To control for off-target effects, we treated in vitro adipocytes with transfection agent alone or transfected with various concentrations of siRNA nontargeting negative control, followed by mRNA measurements. Indeed, basal expression levels of CCL2, ETS1, or MAX remained stable (Supplementary Fig. 2).
miRNA-193b, -126, and -92a Cooperatively Affect CCL2 Production in Human Adipocytes
Because our data presented above indicate that TFs are able to additively control CCL2 secretion, we assessed if this mode of action is also present when combining miRNAs. We have previously shown that single overexpression of miR-193b, -126, or -92a at high concentrations (i.e., 40 nmol/L) downregulate CCL2 production to a substantial degree (30–50%) (11). Here we assessed how co-overexpression of miRNAs affected CCL2 secretion. A caveat is that overexpression of multiple miRNA mimics, particularly at high concentrations, increases the risk for off-target effects. Therefore, lower concentrations of miRNA mimics were used in the combined transfections. At 5 nmol/L, single overexpression of miR-193b, -126, and -92a had significantly weaker effects on CCL2 secretion compared with concomitant overexpression of miR-92a with miR-193b or -126 (Fig. 4A). However, combining miR-193b and -126 did not cause a more pronounced effect than miR-126 alone. The effects on CCL2 secretion were paralleled by similar changes in mRNA expression (Supplementary Fig. 1B).
To rule out the possibility that the additive effects on CCL2 production by combined overexpression of miRNAs were not due to alterations in transfection efficiency, we quantified miRNA levels after transfection. Indeed, there were no differences in miRNA abundance irrespective of whether they were overexpressed alone or in pairs (Supplementary Fig. 3).
As suggested in Fig. 1A, the signaling circuits for miR-193b and -92a converge on TFs in the NF-κB pathway. We therefore quantified mRNA levels of NFKB1 and RELB in the miRNA co-overexpression experiments. Although no changes occurred in the expression levels of NFKB1 (Fig. 4B), RELB mRNA expression was attenuated by the combined overexpression of miR-92a with miR-193b or miR-126 (Fig. 4C).
Cooperative Effects of miRNA 193b, -126, and -92a on CCL2 Production in Human Macrophages
That CCL2 is secreted by several other cell types present within WAT, among which macrophages are probably the most important (20), is well known. Therefore, we assessed the effects of miR-193b, -126, and -92a on CCL2 secretion in the THP1 human monocyte/macrophage cell line. We previously used high concentrations of mimic reagents (40 nmol/L) to show that miR-193b and -126 affected CCL2 production in these cells (40 nmol/L) (11). To observe possible additive effects of miRNAs on CCL2 production, we overexpressed miRNAs at lower concentrations (10 nmol/L). In this experimental setting, overexpression of miR-92a alone significantly decreased CCL2 secretion, whereas overexpressing miR-193b caused somewhat increased (albeit not statistically significant) CCL2 secretion. In contrast to the results obtained in adipocytes, co-overexpression miR-193b and -126 decreased the secretion of CCL2 significantly, whereas the combinations of miR-193b/-92a and miR-126/-92a showed less prominent effects (Fig. 4D).
Similar to the experiments in adipocytes, we quantified the expression of miRNAs after transfection in THP1 macrophages. There were no differences in the abundance of miR-126 or -92a irrespective of whether they were overexpressed alone or in pairs (Supplementary Fig. 4). Owing technical problems of tested probes for miR-193b, we were not able to determine levels of this miRNA in THP1 cells.
Association Between Expression of Adipose Tissue miR-193b, -126, and -92a and CCL2 Secretion
The possible in vivo relevance was assessed by correlating expression levels of miRNAs (miR-193b, -126, and -92a) with CCL2 secretion in adipose tissue of cohort 1 (results in Table 2). In simple regression, only miR-193b correlated significantly (and negatively) with CCL2 secretion. However, when miRNA levels were combined in a stepwise regression, miR-193b/-92a and miR-193b/-126 interacted significantly in the negative correlation with CCL2. The combinations explained 21–24% of the interindividual variations in CCL2 secretion (adjusted r2). There was no significant correlation with CCL2 release when miR-92a and -126 were combined as regressors (values not shown). miRNA-193b always entered as the first step in the models.
As shown in Fig. 1A, miR-193b targets two TFs in the TRN: ETS1 and MAX. We applied regression analysis to further investigate if the activity of these TFs covaried in their relationship with adipose CCL2 secretion (Table 2). In simple regression, the motif activity of either TF was significantly and positively correlated with adipose CCL2 secretion (Table 2). In a stepwise regression, their motif activities acted together in a significant manner with regard to their correlation with CCL2 secretion. Together they explained 40% of the CCL2 variation (i.e., adjusted r2). ETS1 entered as the first step in the relationship. We also investigated by regression analysis if the activity of SP1 (target of miR-92a) covaried with adipose CCL2 secretion. A simple regression showed the SP1 motif activity was significantly and positively correlated with adipose CCL2 secretion (r = 0.42, P = 0.003).
In this study, we tested whether combined silencing of TFs (ETS1 and MAX) and overexpression of miRNAs (miR-193b/-126/-92a) resulted in augmented effects in CCL2 production. Our main conclusion is that the three investigated miRNAs (miR-193b, -126, and -92a) regulated CCL2 production by distinct pathways involving specific TFs. Concomitant overexpression of miRNA pairs or paired silencing of their cognate target TFs (ETS1 and MAX) resulted in additive effects on CCL2 production. The enhanced effects of miRNAs pairs were qualitatively different in human adipocytes compared with human macrophages. This suggests that TRNs regulating CCL2 production are cell-specific and that the combined effects of miRNAs influence cellular phenotypes.
Several biological processes, including diseases such as cancer, have been causatively associated with disturbances in the interplay between miRNAs and TF in vitro and in vivo, as reviewed (21). MiRNAs and TFs are transactivating factors that interact with cis-regulatory elements, potentially generating complex combinatorial effects. Here, we extensively characterized the first downstream targets of miR-193b and -92a in the proposed CCL2 TRN. By knocking down ETS1, MAX, and SP1, we demonstrate that these TFs downregulate CCL2 production in fat cells independently of the targeting miRNAs. This suggests that these three TFs are upstream regulators of CCL2 in human adipose tissue. The results with ETS1 and SP1 are in accordance with findings in nonadipose tissue demonstrating that both TFs control CCL2 (22,23). Although the MYC/MAX/MAD family are well-established regulators of key processes in basic cell physiology, including cell metabolism (24), their involvement in the regulation of CCL2 has not been described before. Our study therefore suggests a novel role for MAX in the regulation of adipose inflammation. Because ETS1 and MAX were both direct targets for miR-193b, we explored the effects on CCL2 production of combined knockdown of these two genes. This resulted in more pronounced inhibition of CCL2 production compared with single knockdown of either TF. Thus, miR-193b may amplify its signal to CCL2 through interactions within the TF network.
To study the combined effects of miRNAs in human adipocytes, we overexpressed miR-193b/-126/-92a individually and in pairs. In fat cells, the combination of miR-92a with miR-193b or -126 caused a more marked downregulation of CCL2 production compared with either miRNA alone. This demonstrates two types of signal amplifications, which are summarized in Fig. 5. For miR-92a and -193b, there are interactions through the TF network that in an additive manner amplify the effects on CCL2 secretion (interaction A1 and A3). For miR-92a and -126, the effects are most probably obtained due to a combination of the TF network (miR-92a acts through SP1) and the direct interaction of miR-126 with CCL2 (interaction A2).
We also investigated if combinations of miRNAs could alter signaling further downstream in the TF network. Co-overexpression of miR-92a with miR-193b or miR-126 downregulated RELB mRNA expression. This suggests that in adipocytes, an additive effect of miRNAs on CCL2 production may be due to signals converging onto the NF-κB/REL pathway. These results are in concordance with previously published data on other cell types demonstrating that NF-κB/REL are downstream of SP1, ETS1, and MYC (an interaction partner with MAX) (25–27).
To study cell-specific miRNA effects on CCL2 regulation, we performed similar experiments in the human macrophage THP1 cell line. In contrast to fat cells, only the combination of miR-193b and miR-126 had an additive effect on CCL2 production (Fig. 5; interaction M1). Whether the miRNA-TF regulatory circuits established in adipocytes is also acting in macrophages remains to be determined. Nevertheless, our data demonstrate that miRNAs regulate CCL2 differentially in human macrophages compared with fat cells.
Are additive effects of miRNA signaling of clinical relevance? Unfortunately, determining this in vivo is not possible. To shed some light on this relevant issue, we performed extensive correlation analyses between miRNA expression, TF activities, and CCL2 secretion in human subcutaneous adipose tissue. The combined expression of miR-193b/-92a or miR-193b/-126 explained interindividual variations in CCL2 secretion to a larger extent than either miRNA alone. The same was true for the combined expression of MAX and ETS1. This supports the hypothesis that additive effects of miRNA and TFs may be clinically relevant although, admittedly, caution should be taken when extrapolating these statistical correlations into an in vivo situation. It is also important to stress that the TRN constructed using the present approach is not complete and most likely includes other factors not evaluated in the current and previous analysis (11).
Most of the work characterizing miRNAs associated with obesity and/or insulin resistance concerns single miRNAs rather than combinations or clusters of miRNAs. We propose the following model for how miRNAs affect CCL2 production in human adipose tissue, where the signal may be relayed in at least three different ways (Fig. 5): 1) as the combined effects of direct interactions with CCL2 and indirect interactions with specific TFs, 2) as the interaction of several miRNAs in a TF network, and 3) as the interaction of a single miRNA with several TFs. These combined effects are specific for different cell types within adipose tissue (e.g., fat cells and macrophages). In addition, there are probably other signaling pathways that could be important. For example, the expression of other cytochemokines is probably under the control of other TRNs, and other WAT regions besides the subcutaneous fat could be controlled by miRNAs in a different way.
In summary, human adipose CCL2 production is regulated by a local miRNA-TF network that allows diverse signal amplification and is specific for different cell types present in the tissue. This may be an important factor linking adipose tissue inflammation, insulin resistance, and type 2 diabetes.
Acknowledgments. The authors thank Eva Sjölin, Gaby Åström, Elisabeth Dungner, Kerstin Wåhlén, Britt-Marie Leijonhufvud, Katarina Hertel, and Yvonne Widlund (Department of Medicine, Lipid Laboratory, Karolinska Institutet) for excellent technical assistance.
Funding. This work was supported by several grants from the Swedish Research Council, the Swedish Diabetes Foundation, Diabetes Wellness, the Diabetes Program at Karolinska Institutet, the Swedish Society of Medicine, Tore Nilsson Foundation, Foundation for Gamla Tjänarinnor, Åke Wiberg Foundation, European Association for the Study of Diabetes/Lilly program, Novo Nordisk Foundation, and a research grant from the Ministry of Education, Culture, Sports, and Technology in Japan to the RIKEN Center for Life Science Technologies.
Duality of Interest. No potential conflicts of interests relevant to this article were reported.
Author Contributions. A.K. and Y.B. designed the study, performed the functional analyses, and wrote the manuscript. S.L.-C. and C.B. performed the functional analyses and wrote the manuscript. E.A. and C.O.D. conducted microarray data, motif activity response, and network analyses, and wrote the manuscript. P.H. collected tissue and wrote the manuscript. M.R. designed the study, collected tissue, and wrote the manuscript. N.M. designed the study; conducted microarray data, motif activity response, and network analyses; performed the functional analyses; and wrote the manuscript. P.A. designed the study and wrote the manuscript. All authors contributed to data interpretation and reviewed and approved the final manuscript. A.K. and P.A. are the guarantors of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
This article contains Supplementary Data online at http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db13-0702/-/DC1.
- Received May 3, 2013.
- Accepted December 15, 2013.
- © 2014 by the American Diabetes Association.
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