The role of microRNAs in adipocyte differentiation

Abstract

Adipocytes differentiate from mesenchymal stem cells (MSCs) in a process known as adipogenesis. The programme of adipogenesis is regulated by the sequential activation of transcription factors and several signaling pathways. There is growing evidence indicating that a class of small non-coding single-stranded RNAs known as “microRNAs (miRNAs)” also are involved in this process. In this review, we summarize the biology and functional mechanisms of miRNAs in adipocyte differentiation. In addition, we further discuss the miRNAs profiling, the miRNAs function and miRNAs target prediction in the adipogenesis.

Keywords

microRNA / adipocyte / differentiation / adipogenesis

Introduction

Adipocytes, the cells which provide retrievable fat and energy depots in animal species, differentiate from mesenchymal stem cells (MSCs) [1] in a process known as adipogenesis. Adipogenesis can be divided into two main phases: commitment of mesenchymal stem cells to a preadipocyte fate and terminal differentiation [2]. Adipocyte differentiation is an ordered multistep process requiring the sequential activation of several groups of transcription factors [3-5], including CCAAT/enhancer binding protein (C/EBP) gene family, peroxisome proliferatoractivated receptor-γ (PPARγ), Krüppel-like factors (KLFs) and sterol regulatory element-binding protein (SREBP). Hormones and growth factors that affect adipocyte differentiation, such as insulin [6] and insulin-like growth factor [7], transfer external growth and differentiation signals to differentiating adipocytes. While it is accepted that this complex process is tightly controlled by a combination of multiple transcription factors and extracellular hormones, little is known about the precise mechanisms of adipogenesis. Moreover, miRNAs have been reported in proliferation and differentiation in several pathways including the development timing, hematopoiesis, organogenesis, apoptosis, cell proliferation and tumorigenesis [8]. Recent computational and experimental studies indicate miRNAs play a role in regulating adipocyte differentiation.

Obesity and the associated metabolic syndrome represent a major public health issue, and present a formidable therapeutic challenge [9]. Thus, investigation of miRNAs and their genetic targets may potentially identify new pathways involved in adipocyte differentiation, and may influence future approaches to the treatment of obesity.

This review will discuss the role of miRNAs in the adipocyte differentiation and the dominant miRNA research techniques available and consider future perspective of miRNAs as a promising therapeutic target.

miRNAs: definition, biogenesis, and function

MicroRNAs (miRNAs) are an abundant class of small (approximately 22 nucleotides) noncoding single-stranded RNAs. In mammals, hundreds of miRNAs have now been identified, some of which are expressed in a tissue-specific and developmental stage-specific manner [10]. For the few miRNAs of which function have been uncovered, they are important regulators of various aspects of developmental control in both plants and animals, including cell fate determination and differentiation (Fig. 1), cell proliferation, cell death, fat metabolism, neuronal patterning, hematopoietic differentiation, immunity, and control of leaf and flower development [11-13].

miRNAs can be derived from individual miRNAs genes, introns of protein-coding genes, or from polycistronic transcripts that often encode multiple, closely related miRNAs. In animals, miRNAs are synthesized from primary miRNAs (pri-miRNAs) in two stages. The first step is the nuclear cleavage of the pri-miRNA, which liberates 60-70nt stem loop intermediate, known as the miRNA precursor, or the pre-miRNA [14,15]. This processing is performed by the Drosha RNase III endonuclease, which cleaves both strands of the stem at sites near the base of the primary stem loop [16]. This pre-miRNA is actively transported from the nucleus to the cytoplasm by Ran-GTP and the export receptor exportin-5 [17,18]. The nuclear cut by Drosha defines one end of the mature miRNA. The other end is processed in the cytoplasm by the enzyme Dicer, also an RNase III endonuclease [16]. These form a transient, double-stranded miRNA of 22 nucleotides in length. The miRNA duplex is then incorporated into a multicomponent protein complex known as RNA-induced silencing complex (RISC), which contains the Argonuate (AGO) protein [19,20]. During the functional process, one strand is rapidly removed and degraded, the other strand of the miRNA duplex is selected as a mature miRNA. The mature miRNA negatively regulate gene expression through translational repression or mRNA cleavage, which depend on the extent of complementarity between the miRNA and its target. If the target mRNA has perfect complementarity to the miRNA-armed RISC, the mRNA will be cleaved and degraded, or it will repress productive translation if the mRNA does not have sufficient complementarity to be cleaved but does have a suitable constellation of miRNA complementary sites [15,21,22].

miRNAs profiling

Several methods are currently available to determine the presence and abundance of miRNAs. However, in contrast to mRNA profiling technologies, miRNAs present several unique challenges that make them more difficult to analyze. miRNA profiling must take into account the difference between mature miRNAs and their precursors which also contain the RNA sequence of the mature miRNA species, and also should distinguish between miRNAs within a family that differ by as little as a single nucleotide [23]. Moreover, it has been shown that mature miRNAs display unequal melting temperature (T_m), owing to their short length, creating miRNA-specific biases. Mature miRNAs lack a common sequence feature, such as a poly(A) tail which helps facilitate their selective purification. Despite these challenges, the three most commonly used technologies are microarray, quantitative real-time PCR (qPCR), and RNA-seq.

Microarrays are among the first methods to be used for miRNA profiling as they are able to screen large numbers of miRNAs simultaneously. However, they are limited by the probes that are available for any given technology and the binding affinity of each miRNA to its probe may vary when relatively quantifying the different miRNAs[24]. One effective strategy is the incorporation of locked nucleic acids (LNAs) into capture probe in place of conventional DNA probes [25]. LNAs are commercially available nucleic acid analogs in which the 2′ oxygen and the 4′ carbon positions in the ribose ring are connected or “locked”. By modifying the LNA contents in the probe, the thermostability of each miRNA-LNA duplex can be increased as well as making it possible to eliminate the diversity of T_m values for individual, which results in more-accurate profiling. The increased binding affinity of LNA probes not only increases in sensitivity compared with unmodified DNA probes, but also improves hybridization discrimination among closely related miRNAs [25,26].

Quantitative real-time PCR-based approaches are becoming increasingly popular due to the unparalleled specificity and sensitivity. Recently, a second generation of TaqMan miRNA assay has been developed for mature miRNAs and discriminates among related miRNAs that differ by as little as one nucleotide. This assay is a novel miRNA quantification method using stem-loop reverse-transcription (RT) followed by TaqMan PCR analysis. qPCR is also used to validate observations determined by genome-wide profiling of miRNA expression. The successful outcome of qPCR analysis depends upon a number of interconnected steps that require individual optimization. Considerations are needed when undertaking qPCR quantitation of miRNA including the cDNA synthesis method, the chemistry used to detect the specific miRNA, the primer design and the selection of appropriate endogenous control transcripts which is used to normalize the data[27].

RNA-seq takes advantages of recent advances in high-throughput sequencing technologies [28]. The major advantage is detection of both novel and known miRNAs, as it allows the sequencing and direct quantification of all the small RNA molecules, independent of any a priori information. It is also able to resolve different members of miRNA families with only single-nucleotide differences. However, it has been noted that the method of library preparation used may bias against the detection of some small RNA molecules, which means this technique is probably best used for relative quantification of miRNAs between samples rather than for absolute quantification [29].

Attempts to catalog miRNA expression during adipogenesis have been carried out using different profiling platforms. Using Northern blot analyses, Kajimoto et al. profiled ~100 miRNAs in mouse preadipocyte 3T3-L1 cells before and after differentiation and found that the expression of 21 miRNAs was modulated in fully differentiated adipocytes [30]. The result also showed mild downmodulations of these upregulated miRNAs did not appear to affect 3T3-L1 pre-adipocyte differentiation. In addition, Xie et al. profiled the expression of>370 miRNAs during adipogenesis of preadipocyte 3T3-L1 cells using miRNA microarrays [31]. The result showed that during differentiation 8 miRNAs were significantly upregulated and 4 miRNAs were downregulated, which was validated by quantitative RT-PCR assays. They compared the expression of these 12 miRNAs by RT-PCR in enriched mouse primary preadipocytes and adipocytes. The results suggested that similar changes in miRNA expression occurred during in vivo adipogenesis. This study also functionally characterized two adipocyte-enriched miRNAs, miR-103 and miR-143, and further provided the first experimental evidence for miR-103 function in adipose biology.

Action of miRNAs on adipocyte differerntiation

Adipocytes derive from multipotent mesenchymal stem cells [32]. Adipogenesis can be divided into two main phases. The first phase, known as determination, involves the commitment of mesenchymal stem cells to a preadipocyte fate, which cannot be distinguished morphologically from its precursor cell but has lost the potential to differentiate into other cell types. In the second phase, which is known as terminal differentiation, the pre-adipocyte takes on the characteristics of the mature adipocyte, which acquires the machinery that is necessary for lipid transport and synthesis, insulin sensitivity and the secretion of adipocyte-specific proteins. Many of these changes occur at the level of gene expression through a series of molecular events involving several transcription factor families [3,4,33,34]. Among these transcription factors, the nuclear receptor PPARγ [35,36] and members of the C/EBP family [37,38] are crucial and well-studied. In addition, several signaling pathways, including Wnt signaling [39-41], TGFβ superfamily signaling [42], IGF-1 and insulin [6,7], have been reported to mediate adipogenesis in vivo and in vitro. Besides, studies have showed that the composition and stiffness of the ECM can regulate adipogenesis [43,44].

Recent studies have discovered multiple microRNAs as potential regulators of adipocyte differentiation. The first study to discover the involvement of an mRNA in the regulation of adipogenesis and fat metabolism was performed in Drosophila. It was observed that animals with miR-14 deleted had increased levels of triacylglycerol and diacylglycerol, and increasing miR-14 had the opposite effect [45]. In mammalian cells, studies have identified several candidate miRNAs which can enhance or inhibit adipocyte differentiation (Table 1). miR-143 has been shown to increase during human and murine pre-adipocyte differentiation [30,31,46]. Ectopic expression of miR-143 in preadipocytes accelerated adipogenesis, as measured both by the upregulation of many adipogenesis markers and by an increase in triglyceride accumulation at an early stage of adipogenesis [31]. Inhibition of miR-143 inhibited differentiation in cultured human preadipocytes [30]. miR-143 seems to inhibit the expression of the gene ERK5 (extracellular-signal-regulated kinase 5), which does not have a defined role in adipogenesis [46]. The miR-17-92 cluster, which comprises miR-17-5p, miR-17-3p, miR-18, miR-19a, miR-20, miR-19b and miR-92-1, can promote proliferation in cancers [47]. It is upregulated during the mitotic clonal expansion of adipogenesis and ectopic expression accelerates differentiation and increases triglyceride accumulation [48]. MiR-17-92 was demonstrated to target Rb2/p130, which is an important regulator of pre-adipocyte clonal expansion in the early differentiation process [49,50]. miR-103 has also been reported to be upregulated during adipocyte development in 3T3-L1 cells and downregulated in obese mice [31]. The ectopic expression of this miRNA increases the rate of triglyceride accumulation in adipocytes [31]. miR-21 has been demonstrated to enhance adipogenesis of human adipose tissue-derived stromal cells (hASCs) through the modulation of endogenous TGFβ signaling pathway [51]. It was also observed that overexpression of miR-21 decreased cell proliferation of hASCs by targeting STAT3 [52]. Another study showed that miR-519d was overexpressed in human obesity and it also showed that miR-519d suppressed translation of the PPARα protein, another member of the PPAR family. The treatment of primary human visceral pre-adipocytes with miR-519d or anti-miR-519d respectively resulted in an increase and decrease in adipogenesis [53]. Previous research has shown that Wnt signaling represses adipocyte differentiation by blocking the expression of C/EBPa and PPARγ, two transcription factors indispensable for adipogenesis [54]. Recently, Kennell et al. identified that the miR-200 family, homologs of Drosophila miR-8 in mammals, promoted adipogenesis by inhibiting the Wnt signaling [55]. Another finding suggested that miR-210 could promote adipogenesis by repressing Wnt signaling through targeting Tcf7l2, which is a key transcription factor modulating components of Wnt signaling. Overexpression of miR-210 in 3T3-L1 cells is reported to stimulate adipocyte hypertrophy and lipid droplet formation [56]. The miR-30 family acted as a positive regulator of adipocyte differentiation in a human adipose tissue-derived stem cell model [57]. It has been demonstrated that miR-30a and miR-30d target RUNX2, a major regulator of osteogenesis and a potent inhibitor of the expression of the master gene for adipogenesis, PPARγ. Huang et al. demonstrated that miR-204 and miR-211, which were upregulated during adipogenesis of human bone marrow stem cells, also target RUNX2 [58]. miR-375 has been shown to enhance adipogenesis in 3T3-L1 cells, with inhibition of miR-375 having the converse effect [59].

The miR-27 gene family has been suggested as negative regulators of adipogenesis. miR-27 is found to be downregulated during adipogenesis and ectopic expression reduces adipogenesis in 3T3-L1 cells [60,61] and hASCs [62]. It has been confirmed that miR27a inhibits adipogenesis in 3T3-L1 cells by directly targeting the 3′UTR of PPARγ mRNA [62]. Another family member, miR-27b, also functions as repressor of human adipogenesis by directly targeting PPARγ. miR-130 is also found to inhibit adipogenesis by targeting PPARγ mRNA. It is suggested that miR-130 may be related to human obesity as adipose tissue from obese women has higher expression of miR-130 with lower expression of PPARγ mRNA than non-obese women [63]. The expression of miRNA let-7 was shown to inhibit the clonal expansion and terminal differentiation of 3T3-L1 cells by targeting HMGA2 mRNA and protein expression, which is a high mobility group (HMG) protein [64]. Mice lacking HMGA2 resist diet-induced obesity due to a reduced number of adipocytes, implicating it in proliferative expansion of pre-adipocytes [65]. miR-448 also inhibits adipocyte differentiation by targeting and repressing the KLF5 mRNA [66], which is another important transcription factor participating in adipogenesis.

MicroRNAs target prediction and validation in adipocyte differentiation

It is important to determine the targets of miRNAs for understanding their function. However, effective prediction of miRNA-mRNA interactions in animal systems remains challenging due to the interaction complexity and a limited knowledge of rules governing these processes. Thus, many different algorithms have been developed for prediction of miRNA-mRNA interactions [67-70]. Among them, TargetScanS [71], PicTar [70], and miRanda [68] are the most common target prediction programs. Each is based on a different set of rules to identify and evaluate the efficacy of a miRNA target using a unique scoring system. The prediction of miRNA targets by computational approaches is based mainly on three steps. The first step in the prediction procedure is the identification of potential miRNA-binding sites in the mRNA 3′UTR according to specific base-pairing rules, especially strong Watson-Crick base-pairing of the seed region (6 or 7-nt at the 5′ end) of the miRNA to a complementary site in the 3′UTR of the mRNA. TargetScanS requires perfect complementarity with a miRNA seed [71], whereas PicTar allows for targets with imperfect seed matches given that they pass a heuristically defined binding-energy threshold [70]. miRanda uses a modified dynamic programming approach that recognizes the importance of seed binding, but does not require perfect seed complementarity [68]. The second step involves the implementation of cross-species conservation requirements. TargetScanS and PicTar both require conservation between at least five species for the portion of the target site that binds to the miRNA seed, but they define conservation slightly differently. The third step requires a local miRNA-mRNA interaction with a positive balance of minimum free energy (MFE).

Experimental validation of miRNA targets involves measuring changes in predicted target proteins followed by ectopic miRNA expression or miRNA knockdown. Moreover, it is crucial to demonstrate a miRNA can specifically bind to its predicted target gene. Several methods for predicting miRNA-mRNA interactions are currently being used, such as reporter assays [70,72], microarrays [73,74] and proteome analyses [75]. The use of reporter assays, usually luciferase reporter assays, is the most common approach, because miRNA activity on such reporter genes can be easily measured. This method is based on cloning of a 3′ untranslated region mRNA target into a luciferase reporter, which is co-transfected into cells along with a miRNA mimic or inhibitor [69,76]. Simplicity is the main advantage of the method, but it does not allow a high-throughput identification of miRNA targets which is the advantage of microarrays and proteome analyses. Apart from these strategies, other methods have been recently developed. HITS-CLIP [77], namely high-throughput sequencing of RNAs isolated by crosslinking immunoprecipitation, is used to directly identify AGO-bound miRNAs and their targets using antibodies. With deep sequencing, it allowed validating of miRNA-mRNA interactions in a genome-wide manner.

To identify miRNAs which would affect adipocyte differentiation, Kim et al. [61] screened miRNAs which potentially suppress PPARγ and utilized four computational prediction programs for selection of miRNAs: TargetScan, PicTar, miRanda, and miRGen. Among commonly screened miRNAs, miR-27a showed a high score to bind to the 3′-UTR of PPARγ mRNA. To validate whether miR-27a is able to recognize the PPARγ 3′-UTR, they generated a luciferase reporter DNA construct containing the mouse 206 bp PPARγ 3′-UTR with a miR-27a putative binding site. To determine the specificity between miR-27a and PPARγ 3′-UTR target site, luciferase reporter was mutated at the target elements in the PPARγ 3′-UTR which are the “seed” match region. The results showed that luciferase activity was suppressed by ectopic expression of miR-27a and the mutant reporter activity could not be suppressed, which clearly indicated that miR-27a would directly recognize and bind to the PPARγ 3′-UTR and, thereby, suppress PPARγ gene expression.

To study the functional role of miR-519d [53], TargetScan was used as target prediction algorithm. All target genes for miR-519d prediction were combined, and analyzed using the KEGG database to identify the biological processes that involve the target genes of microRNAs. The PPARα was selected and then the 3′-UTR luciferase assay of reporter plasmid validated that miR-519d targeted this factor.

miRNAs used for therapeutic approaches

miRNAs have been shown to control cellular proliferation and differentiation, suggesting that the manipulation of miRNAs levels provides an attractive approach for therapeutic development. Repression of miRNA activity can be performed with antisense miRNA oligonucleotides [78] or miRNA sponge [79]. On the other hand, enhancement of miRNA activity can be accomplished by transfecting synthetic miRNA mimetics or by using plasmids to transcribe miRNAs from endogenous or viral promoters [80].

Antagomirs have been used successfully to manipulate miRNAs in vivo [81]. Antagomirs are anti-sense oligonucleotide sequences conjugated with cholesterol which act as specific and effective silencers of miRNA expression in mice. More recently, locked nucleic acids have been shown to be capable of potently antagonising miRNAs in vivo [82]. Though safe, effective and targeted delivery of RNA therapeutics remains an important challenge, the potential of miRNAs to modulate the metabolic pathways is still promising.

Conclusions

In recent years, emerging evidence suggests that miRNAs play an important role in adipose tissue development and function. Expression profiling studies have revealed some miRNAs involved in adipogenesis. However, information regarding how these miRNAs are working in adipose tissue remains limited. Further investigations into miRNA functions in adipocyte differentiation and possible therapeutic strategies for the treatment of obesity need to be conducted.

Compliance with ethics guidelines

Rong Zhang, Di Wang, Zhuying Xia, Chao Chen, Peng Cheng, Hui Xie, and Xianghang Luo declare that they have no conflict of interest.

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