MicroRNA-181b suppresses TAG via target IRS2 and regulating multiple genes in the Hippo pathway

MicroRNA-181b suppresses TAG via target IRS2 and regulating multiple genes in the Hippo pathway

Author’s Accepted Manuscript MicroRNA-181b Suppresses TAG via target IRS2 and regulating multiple genes in the Hippo pathway Zhi Chen, HuaiPing Shi, S...

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Author’s Accepted Manuscript MicroRNA-181b Suppresses TAG via target IRS2 and regulating multiple genes in the Hippo pathway Zhi Chen, HuaiPing Shi, Shuang Sun, HuiFen Xu, DuoYao Cao, Jun Luo www.elsevier.com/locate/yexcr

PII: DOI: Reference:

S0014-4827(16)30278-6 http://dx.doi.org/10.1016/j.yexcr.2016.09.004 YEXCR10333

To appear in: Experimental Cell Research Received date: 4 June 2016 Revised date: 24 August 2016 Accepted date: 7 September 2016 Cite this article as: Zhi Chen, HuaiPing Shi, Shuang Sun, HuiFen Xu, DuoYao Cao and Jun Luo, MicroRNA-181b Suppresses TAG via target IRS2 and regulating multiple genes in the Hippo pathway, Experimental Cell Research, http://dx.doi.org/10.1016/j.yexcr.2016.09.004 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

MicroRNA-181b Suppresses TAG via target IRS2 and regulating multiple genes in the Hippo pathway Zhi Chen , HuaiPing Shi, Shuang Sun, HuiFen Xu, DuoYao Cao, Jun Luo*

Shanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, PR China

*Corresponding Author: Jun Luo, Tel:+86-029-87082891, [email protected]

ABSTRACT Milk fat metabolism is a complex procedure controlled by several factors. MiRNAs (microRNAs) regulate expression of genes and influence a series of biological procedures, such as fatty acid metabolism. Here we screened expression of goat mammary gland's miRNA during peak-lactation and late-lactation, and found that miR-181b expresses remarkably. Moreover, we illustrated that the over-expression of miR-181b impaired fat metabolism while the knockdown of miR-181b promoted fat metabolism in GMEC. These findings extend the discovery of miR-181b functioning in mediating adipocyte differentiation, by suggesting its role in impairing fat metabolism, which develops our cognition on the importance of miRNAs in milk fat metabolism and synthesis. In this study, we find that over expressed miR-181b impaired adipogenesis and inhibited miR-181b promoted adipogenesis in GMEC. Using Luciferase reporter assay and Western Blot, IRS2 was illustrated to be a miR-181b's potential target gene. What is interesting is that miR-181b regulates multiple key components in the Hippo pathway, such as LATS1 and YAP1 in GMECs. In conclusion, our findings indicated that miR-181b suppress fat metabolism by means of regulating multiple genes in the Hippo pathway and target IRS2, which promotes further study on the function of miRNAs in milk fat metabolism and synthesis. Key Words: miR-181b, fat metabolism, Hippo pathway, IRS2

INTRODUCTION Comparing with the cow milk, goat milk (milk of Capra hircus) includes a higher level of unsaturated fatty acids, along with total fat, vitamins, calcium, carbohydrates, and proteins.

Recently, scholars make great contributions to raising the nutrition of milk to satisfy the increasing demands of people. Nowadays, raising the milk's nutritional value is mainly altering their diet (Han et al., 2004, Hinrichs, 2004, Luna et al., 2008). Thus, investigating goat milk fat metabolism has received substantial attention (Chilliard et al., 2003, Marquart et al., 2010). For instance, there have been several researches on the molecular mechanism. These researches focused on a single gene's function, rather than a more comprehensive research for the molecular regulation of synthesis (Wilfred et al., 2007, Fabian et al., 2010, Shirasaki et al., 2013). MiRNAs are a series of single-stranded non-coding RNAs which have 22 nts (nucleotides) in length. MiRNAs regulate gene expression in a post-transcriptional level transcribed by RNA polymeraseⅡ (Avery-Kiejda et al., 2014, Humphries et al., 2014, Wang et al., 2014). Generally, miRNAs bind to the 3’-UTR (untranslated region) of target mRNAs to regulate target genes negatively (Lee et al., 2003, Denli et al., 2004). Currently, hundreds of miRNAs have been uncovered in the body of human, and bioinformatics prediction indicates that they could regulate the expression of approximately thirty percent of genes in the genome(Calvano Filho et al., 2014, Gasparini et al., 2014, Sharma et al., 2014). Previous researches indicated that over sixty percent of protein-coding genes have more than one conserved site for miRNAs (Gregory et al., 2004, Han et al., 2004). Various reports illustrated that miRNA are expressed in a spatio-temporal specific manner, and influence a variety of procedures such as immune regulation, fat metabolism, cell apoptosis, cell proliferation, and cell differentiation among others. Despite the vast amount of work on miRNA in non-ruminant species, there are few studies focused on the function and mechanisms whereby miRNA synergistically regulate the process of milk fat metabolism (Gu et al., 2007, Lee et al., 2011, Yin et al., 2013).

miR-181b together with miR-181a, miR-181c, and miR-181d is a member of the miR-181 family (Xia and Gao, 2014). MiR-181 family has a close relation with fat metabolism. For example, miR-181a regulates lipid metabolism via isocitrate dehydrogenase 1 (IDH1), decreases the expression of genes involving in lipid synthesis, and increases the expression of genes involving in β-oxidation, thereafter inhibiting lipid accumulation(Chu et al., 2015). Although previous studies have indicated that miR-181 influences adipocyte differentiation and regeneration (Chu et al., 2015, Sun et al., 2016), the functional role of miR-181b in GMEC is unknown. Thereby, the main purpose of this work was to investigate the function of

miR-181b in controlling of mammary cell lipid metabolism

2 Material and methods 2.1 Ethics Statement Animals use and care protocol was approved by Animals Use and Care Committee in the Northwest Agricultural and Forestry University, Yang Ling, China.

2.2 Animals and RNA extraction of sampling The elite herds of Xinong Sanen dairy goats used in this research were from the experimental farm of Northwest Agricultural and Forestry University of China. Three goats (three years old) of similar weight were used at the following stages of lactation: no-pregnant, early-lactation (15 days after parturition), peak-lactation (60 days after parturition), late-lactation(150 days after parturition), and non- lactating (“dry” period). Spleen, stomach, heart, liver, sebum, mammary gland tissue, muscle, lung and kidney were collected after slaughter. Three biological samples per tissue were snap-frozen in liquid nitrogen as soon as possible. Using Trizol reagent (Invitrogen, USA), total RNA was extracted in accordance with the instructions. The quality and quantity of RNA were detected by a ND-1000 spectrophotometer (NanoDrop, USA) and the RNA was stored in -80℃ before experiment.

2.3 Cells culture and transfection As for GMEC separation, we collected mammary glands of milk goats in peak-lactation period. Then, we used 3xPBS to rinse them and put them into 3x double anti-d-Hanks solution. Next, we kept them in a lower temperature and took them back to the laboratory, thereafter quickly placing them in 3xPBS, cutting acinar, removing connective tissues, and cutting into pieces conserving in a small dish with 37 degrees Celsius for 30min. Finally, we fetched these tissues and added 1ml F12 medium into them, changing the medium after 2 days. The GMECs were cultured in DMEM/F12 medium (Invitrogen Corp., USA) containing10% FBS, 10 ng/ml EGF-1 (epidermal growth factor 1, Gibco), 5 mg/ml insulin, 50 U/ml penicillin/ml streptomycin and 0.25 mmol/l hydrocortisone in 37℃ in a humidified atmosphere with 5% CO2. The GMECs were cultured and fractionated in accordance with a previous research (Shi et al., 2013).To induce lactogenesis, GMECs were cultured in a lactogenic medium for 48h prior to initial experiments (Peterson et al.,

2004, Kadegowda et al., 2009). Cells were cultured and transfected with either miR-181b mimic (60nM) or miR-181b inhibitor (60nM) (Invitrogen, USA) using LipofectamineTM RNAiMAX (Invitrogen, USA) on the basis of manufacturer’s instructions. Cells were harvested after 48h after transfection. The sequences of mimic, inhibitor and siRNA were listed in S1 and S3.

2.4 Staining of oil red O Oil red O staining was used as mentioned in the previous research with modifications (Zhu et al., 2015). In brief, epithelial cells were transfected with miR-181b mimic or miR-181b inhibitor, were cleaned several times in PBS (phosphate buffer solution), and were fixed in 10% paraformal dehyde for 30 mins. Afterwards, cells were stained using 10% oil red O in isopropanol for 10 mins, were cleaned by PBS, and were detected microscopically.

2.5 Assay of cellular TAG content The GMECs were transfected with either miR-181b mimic or miR-181b inhibitor. Cells were obstained with lysis buffer (1% Triton X-100, pH 7.4, 150 mmol/NaCl, 50mmol/l Tris-HCL) after 48h of incubation. TAG was measured using a commercial kit on the basis of instructions (Loogen, China) on an XD 811G Biochemistry Analyzer (Odin Science &Technology Company, Shanghai China). The values acquired were normalized to the content of total protein with the BCA protein assay kit (Thermo crop, Prod#23227).

2.6 Assay of cellular cholesterol content The GMECs were transfected with either miR-181b mimic or inhibitor and siRNA (20ng). Cells were obstained with lysis buffer (1% Triton X-100, pH 7.4, 150 mmol/NaCl, 50mmol/l Tris-HCL) after 48h of incubation. Cholesterol was measured using a serum cholesterol kit on the basis of the instructions (Loogen, China) on an XD 811G Biochemistry Analyzer (Odin Science &Technology Company, Shanghai China). The values obtained were normalized to the content of total protein.

2.7 RT-qPCR and Western blot MiRBase(http://www.mirbase.org)was the source of profiling miRNA of Bostaurus and Capra hircus. Among them, Bos Taurus has 793 miRNA while Capra hircus has 267. As Capra hircus and Bos taurus share high sequence homology with each other, some raw data or referenced data are overlapping. These overlapping data have been marked out, and details could be found in the additional materials (Table S1). The expression of 18s rRNA was used as a normalization control.

The expression levels of miRNAs were determined by the S-Poly(T) (Kang et al., 2012).The S1 primer was used as specific reverse primer. In brief, reverse transcription was performed as follows: 2.5 µl of 4×reaction buffer, a 10 µl reaction including 0.2 µg total RNA, 1µl of 0.5 µM RT primer, 1 µl of polyA/RT enzyme mix. The reaction was performed in 37 ℃ for 25 mins, followed by 42 ℃ for 25 mins, and 72 ℃ for 10 mins. The products of RT were amplified and detected by 20 µl PCR reaction containing 0.3 µl of RT products, a universal Taqman○ R probe, 0.5 unit of Go Taq○ R Start Polymerase (Promega, USA), universal reverse primer, 4 µl of 5×qPCR probe Mix, 0.5µM forward primer and 0.2 mM universal Taqman probe. The PCR reaction was performed at 95 ℃ for 3min, followed by 42 cycles of 93 ℃ for 10s and 62 ℃ for 30s. For the R mRNA expression level, 0.3 µg of total RNA were synthesized into cDNA using the PrimeScript○

RT Reagent Kit (Perfect Real time, Takara, Japan). (Bionaz and Loor, 2007, Kadegowda et al., 2009, Bonnet et al., 2013). The expression was normalized to UXT. The sequence of primers are listed in S2. All the real-time reactions, including controls with no templates, were carried out on a Bio-Rad CFX96 real-time PCR detection system (Bio-Rad, USA) in triplicate. Relative expression was measured by the 2-△△Ct method (Lin et al., 2013b, Lin et al., 2013c, Lin et al., 2013d, Shi et al., 2013). As to western blot research analyses, cells were obtained and lysed in RIPA buffer (Solarbio, China). Proteins extracted from cells were separated by SDS-PAGE, transferred to nitrocellulose membrane (Millipore, USA) and probed with the primary monoclonal rabbit anti- IRS-2 (Cell Signaling Technology Kit #3089), monoclonal rabbit anti-YAP and anti-LATS1 (Cell Signaling Technology Kit #8579), rabbit anti-Casein beta (Biorbyt, orb0184) and monoclonal mouse anti-β-actin (Proteintech Gronup, 66009-1-IG, China), respectively. Polyclonal goat anti-rabbit HRP-conjugated IgG (Tiangen, China) was used as secondary antibody. All antibodies were used on the basis of the instructions. Signals were detected by the chemiluminescent ECL Western blot system (Pierce, USA).

2.8 Assay of luciferase reporter To generate reporter construction for assay of luciferase, a segment containing a miRNA target site in the 3’-UTR of IRS2 was inserted into the psiCHECK-2 vector (Promega, USA) between the NotⅠand Xho sites immediately downstream of the Renilla luciferase gene. The wild-type

segment and mutant type sequence were established by PCR overlap technology. The sequence of primers were listed in S4. All constructions were proven using sequencing. The GMECs were seeded in plates of 384-well at a density of 50,000 cells per well one day before transfection. A total of 0.33g of each reporter construct were transiently transfected using the X-treme GENE HP DNA Transfection Reagent (Roche, Switzerland) on the basis of the protocol. Cells were then transfected either miR-181b mimic or miR-181b inhibitor using LipofectamineTM RNAi MAX on the basis of protocol after a 6h recovery period in medium. At 48h post-transfection,

firefly and Renilla luciferase activities were measured with the Dual-Glo

luciferase assay system on the basis of the manufacturer’s instructions (Promega, USA).

2.9 Statistical analysis Analysis of statistics was calculated by the statistics software package (SPSS 19.0). Research data were presented as mean ± SE (standard error) of three independent experiments. Distinguished differences between the groups were detected, taking *p < 0.05, **p < 0.01 as significant differences.

3 RESULTS 3.1 Screening of miRNAs in periods of peak-lactation and late-lactation Several researches indicated that miRNAs were related to the regulation of fatty acid and milk fat metabolism(Lin et al., 2013b, Lin et al., 2013c, Lin et al., 2013d). To reveal the connection between the physiological process and the miRNA regulation, here we screened the miRNAs expression including peak-lactation and late-lactation, including 793 Bos taurus primary miRNAs and 267 Capra hircus primary miRNAs from miRBase. In the screening, all the miRNAs with p-value under 0.05 and four-fold change were chosen as candidate miRNA (Fig 1.A)(Table.S1). Among these miRNAs, miR-181b are up-regulated (Fig. 1A). Hence, we focused on miR-181b for more detailed studies. For instance, we measured the expression of miR-181b in different tissues of dairy goats (Fig 4A) and mammary gland at different stages of lactation (Fig 4B). MiR-181b is primarily expressed in mammary tissues, supporting the idea that miR-181b plays an significant role in Lactation mechanism.

3.2 miR-181b specifically targets IRS2 in GMEC. When we choose miR-181b as our research object, we must make the regulation relationship clear

between target genes. Based on the 3’-UTR complementary prediction with Target Scan 6.2 and miRNA functional analysis by DAVID (https://david.ncifcrf.gov/summary), it is evident that many genes are potential targets of miR-181b (Fig. 1B; Table 1, Table.S2). We chose IRS2 for functional validation because it is known to be an important regulator for milk fat metabolism processes. Furthermore, IRS-2 is main mediators of insulin action but their relative contributions to the in vivo regulation of carbohydrate and lipid metabolism (Previs et al., 2000). Our results indicated that IRS2 was up-regulated by inhibition of miR-181b, and down-regulated by over-expression of miR-181b (Fig. 2A). Furthermore, as it was shown in Fig. 2C, IRS2 had a binding site for miR-181b in the 3’-UTR. To vertify that miR-181b directly targeted this site, we synthesized a 3’-UTR segment of IRS2 including the miR-181b target site, and cloned it into the psi-CHECK2 vector to construct a 3'-UTR reporter plasmid. The luciferase reporter assay indicated over-expression of miR-181b decreased the relative luciferase activity of the reporter with a wild-type 3’-UTR rather than the one with mutations in the seed sequences (Fig. 2B and Fig. 2C). Furthermore, the expression level of IRS2 protein was consistent with the expression of mRNA data after miR-181b over-expression treatment (Fig. 2D). We also measured the expression of IRS2 in different tissues of dairy goats (Fig. 4C) and mammary gland at different stages of lactation (Fig. 4D). The findings illustrated that miR-181b directly interacted with the target site of the IRS2 mRNA and negatively regulated its expression, which partly explained the function of miR-181b during lactation.

3.3 Functional evaluation of miR-181b and IRS2 in GMECs Expression of miR-181b increases TAG levels and milk fat droplet accumulation in GMECs. After we making it clear that miR-181b can regulate via IRS2, we would like to know what their specific function is in GMECs. The miR-181b expression was 42 times higher in the miR-181b mimic GMECs than the NC (negative control), but expression decreased more than 99% in the miR-181b inhibited group (Fig.S1 S2). Milk fat existed as milk fat droplets which was composed of TAG in GMECs (Hans Otto HANSEN et al., 1984, Bionaz and Loor, 2008). Hence, we detected the fat droplets and TAG content of cellular in GMECs in which miR-181b was over expressed or suppressed. Compared with the negative control, the TAG content decreased (P<0.05)by 0.62 times in miR-181b mimic (Fig.3A). For another, content of TAG increased significantly while miR-181b was suppressed

(Fig. 3A). Compared with the negative control, the cholesterol content decreased (P<0.05) by 0.82 times in miR-181b mimic (Fig. 3B). Furthermore, fat droplet formation and beta casein were decreased in the miR-181b (Fig. 3C, 3D, 3E). Our research revealed miR-181b played an important role in TAG synthesis and promoted milk fat metabolism in GMECs. Several genes work in a coordinated fashion to control mammary lipid and protein metabolism in ruminants (Hans Otto HANSEN et al., 1984, Bionaz and Loor, 2008, 2011). To study the role of miR-181b in lipid metabolism gene expression we detected the mRNA level of various genes. The results showed that ectopic over expression of miR-181b up-regulated the expression of ACSL1,HSL and ACOX1 (Fig. 4E, Table S2). In contrast, miR-181b performed remarkable down-regulation of series of genes related to fat metabolism, including CD36 and DGAT1 (Fig. 4E, Table S2) indicating that miR-181b plays an important role in their regulation. Expression of IRS2 increases TAG levels and milk fat droplet accumulation in GMEC. Both IRS2 siRNA was used to explore their functional role in GMEC obtained from individual lactation goats. Compared with the negative control, the level of IRS2 was decreased by 75% in GMEC with the transfected IRS2 siRNA (Fig. S1 S2). As depicted in Fig.5A, compared with the negative control, the TAG content decreased (P<0.05)by 0.53 times in GMECs by IRS2 siRNA. The cholesterol content decreased (P<0.05) by 0.66 times in IRS2 siRNA transfected cells (Fig. 5B). In addition,

we

uncovered

that

IRS2

siRNA

impaired

expression

of

milk fat metabolic marker genes including miRNA and protein(Fig. 5C, D). Our research indicated that IRS2 influenced in TAG synthesis and promotes fat metabolism in GMECs. siRNA- IRS2 rescue partly abolishes(rescue) the decrease in TAG level induced by inhibition of miR-181b. We proved that the miR-181b suppress the synthesis of triglycerides. In contrast, the target genes of miR-181b (IRS2) are decreased triglyceride synthesis. Weused a “rescue” experiment to demon strate that miR-181b exert their functions via IRS2. The siRNA-IRS2 rescue increased TAG in GMEC (Figure 5E) in response to ectopic expression of inhibitor-miR-181b. The increase in TAG was partly alleviated by the siRNA- IRS2 rescue (TAG assay, P < 0.05, Figure 5E). The invasion inhibitory effects of inhibitor- miR-181b were partially diminished by SiRNA- IRS2 rescue.

3.4 Multiple components of a Hippo path way are regulated by miR-181b The Hippo pathway has an significant role in controlling organ size in mammals(Lin et al., 2013a)

(Liu et al., 2010). We knock out the LATS1 by SiRNA, detect YAP1 expression, and find that LATS1 can inhibit the expression of YAP1(Fig. 6C, 6D, Fig.S1 S2). When the mimic and inhibitor of miR-181b have been treated as GMECs at the same time, we found that it is much stronger than their individual functions. We find out miR-181b not only can regulate LATS1 (Fig. 6A, 6B), but can regulate YAP1 expression (Fig. 6E, 6F). Interestingly, IRS2 is the target gene of miR-181b, and can reduce YAP1 expression in GMECs by using siRNA and can lead to decreasing YAP mRNA and protein levels (Fig. 6G, 6H). These results suggested miR-181b is a factor whose expression is driven by Hippo pathway in GMECs.

DISCUSSION miRNA expression screen in peak-lactation and Late-lactation Some researches illustrated that miRNA played an important role in mammary development and lactation (Bu et al., 2015, Peng et al., 2015, Zhu et al., 2015). For instance, Avril-Sassen screened and compared the expression of 102 miRNAs in different stages of lactation and speculated that differentially miRNAs expressed were related to activity of fat metabolism (Avril-Sassen et al., 2009). A more recent study using Wendeng goats compared miRNA expression profiles between pregnancy and early lactation and uncovered several differentially expressed miRNAs associated with development and lactation. (Ji et al., 2012). Lin et al. (2013c) detected that miR-27 suppresses TAG accumulation in GMEC. To investigate the connection between the miRNA

regulation and this physiological process in a more comprehensive way, here we profiled the differential miRNAs expression between peak-lactation and late-lactation in goat mammary gland with S-Poly (T) real method, including 267 Capra hircus primary miRNAs and 793 Bos taurus primary miRNAs from miRBase (http://www.mirbase.org/). As Capra hircus and Bos taurus share high sequence homology with each other, some raw data or referenced data are overlapping. We have marked out the overlapping data, and details can be found in the additional materials (Table S1). All the miRNAs with four-fold change and p-value smaller than 0.05 were chose as candidates. In conclusion, we detected 54 differentially expressed miRNAs in peak-lactation and late-lactation stages with 30 up-regulated and 24 down-regulated. In this research, we established a miRNA library which included 793 Bos taurus primary miRNAs

and 267 Capra hircus primary miRNAs from miRBase, with which we screened a several potential miRNAs involved in regulation of milk fat metabolism. Overall, we found 54 miRNAs expression changed between peak-lactation and late-lactation, among which the miR-148a, miR-15a and miR-130b have been reported to involve in the milk fat metabolism process. Among these miRNAs, miR-181b was one of the up-regulated (Fig. 1A). Therefore we could focused on the miR-181b in subsequent studies.

miR-181b target IRS2 3’-UTR directly MiRNAs were showed to be significant regulators of gene expression at the post-transcriptional level. Many nuclear receptor cofactors exist, hence, providing additional control of gene expression(Yu and Reddy, 2007). Insulin mediates multiple metabolic responses in skeletal muscle, including glucose and fatty-acid uptake and metabolism, as well as gene-regulatory responses. Insulin receptor activation results in phosphorylation of insulin receptor substrates (IRSs), which in turn relay positive and negative signals along complex networks of intracellular circuitry that is only beginning to be unraveled(Bouzakri et al., 2006). Previs et al showed important tissue-specific roles for IRS in mediating the effect of insulin on carbohydrate and lipid metabolism in mice (Previs et al., 2000). To confirm that IRS2 was a direct target of miR-181b, we first cloned the 3'-UTR of IRS2 for miR-181b into a luciferase reporter plasmid to detect whether miR-181b had an suppressing effect on this gene. Our findings indicated that miR-181b significantly inhibited the luciferase activity, suggesting that miR-181b functioned through the 3′-UTR of IRS2 to inhibit the reporter gene expression. Furthermore, we made a mutation of the potential binding site for miR-181b in the 3'-UTR, and this mutation abrogated the suppressive effect of miR-181b a on the 3′-UTR of IRS2 . The rescue experiments dealing with siRNA-IRS2 partly abolished the decrease in TAG level induced by inhibitor-miR-181b. Thus, the rescue experiments illustrated that miR-181b via IRS2, respectively. These data provide the basis for additional research on IRS2 to determine the synergistic mechanism regulating fat oxidation in mammary epithelial cells.

miR-181b regulates multiple components of Hippo pathway and control TAG Lipid metabolism plays an important role in cellular energy homeostasis. It has suggested that miR-181a is a potential therapeutic target for lipid metabolism disorders such as hyperlipidemia and obesity(Chu et al., 2015). Thus, the role of miR-181b in lipid metabolism synthesis was

further clarified in the current research. Because miR-181b has different functions in different tissues, we speculate that miR-181b can regulate TAG metabolism in ruminant mammary cells. When mimic and inhibitor of miR-181b were simultaneously transfected in GMEC, we detected a much stronger response than individually. YAP protein (Yes associated protein), a downstream proteins of Hippo signaling pathway, play a crucial role(Kang et al., 2015). Eunjeong Seo illustrate YAP1 induction by SOX2 is restrained in adipogenesis, and both YAP1 over-expression and depletion inhibit the process (Seo et al., 2013). Interestingly, miR-181b can regulate LATS1 which is components of Hippo pathway, and LATS 1 can also reduce YAP1 expression in GMECs by using miRNA detection and protein levels. We also verified the IRS2, as miR-181b target genes, can regulate YAP1 by RT-qPCR and western bl otting. Interestingly, when we knock out the miR-181b and detect YAP1 expression, it is surprisin g to find that miR-181b can promote the expression YAP1. In conclusion, our findings indicate th at miR-181b can regulate multiple components of Hippo pathway during fat metabolism in GMEC s (Fig. 7).

CONCLUSIONS In conclusion, our results have revealed that miR-181b plays an important role in TAG synthesis in GMECs. In addition, miR-181b regulate TAG by IRS2 and multiple components of Hippo pathway in GMEC. In the long-term, these findings might be helpful in developing practical means to improve the quality of ruminant milk.

CONFLICT OF INTEREST The authors declare no conflict of interest.

ACKNOWLEDGEMENTS This research was jointly supported by the National Natural Science Foundation of China (No. 31372281), the Special Fund for Agro-scientific Research in the Public Interest (201103038), and the Transgenic New Species Breeding Program of China (2014ZX08009-051B).

Reference Avery-Kiejda, K. A., S. G. Braye, A. Mathe, J. F. Forbes, and R. J. Scott. 2014. Decreased expression of key tumour suppressor microRNAs is associated with lymph node metastases in triple negative breast cancer. BMC cancer 14:51. Avril-Sassen, S., L. D. Goldstein, J. Stingl, C. Blenkiron, J. Le Quesne, I. Spiteri, K. Karagavriilidou, C. J. Watson, S. Tavare, E. A. Miska, and C. Caldas. 2009. Characterisation of microRNA expression in post-natal mouse mammary gland development. BMC genomics 10:548. Bionaz, M. and J. J. Loor. 2007. Identification of reference genes for quantitative real-time PCR in the bovine mammary gland during the lactation cycle. Physiol Genomics 29(3):312-319 Bionaz, M. and J. J. Loor. 2008. Gene networks driving bovine milk fat synthesis during the lactation cycle. BMC genomics 9(1):366. Bionaz, M. and J. J. Loor. 2011. Gene Networks Driving Bovine Mammary Protein Synthesis During the Lactation Cycle. Bioinformatics and Biology Insights:83. Bonnet, M., L. Bernard, S. Bes, and C. Leroux. 2013. Selection of reference genes for quantitative real-time PCR normalisation in adipose tissue, muscle, liver and mammary gland from ruminants. animal 7(08):1344-1353. Bouzakri, K., A. Zachrisson, L. Al-Khalili, B. B. Zhang, H. A. Koistinen, A. Krook, and J. R. Zierath. 2006. siRNA-based gene silencing reveals specialized roles of IRS-1/Akt2 and IRS-2/Akt1 in glucose and lipid metabolism in human skeletal muscle. Cell metabolism 4(1):89-96. Bu, D. P., X. M. Nan, F. Wang, J. J. Loor, and J. Q. Wang. 2015. Identification and characterization of microRNA sequences from bovine mammary epithelial cells. Journal of dairy science 98(3):1696-1705. Calvano Filho, C. M., D. C. Calvano-Mendes, K. C. Carvalho, G. A. Maciel, M. D. Ricci, A. P. Torres, J. R. Filassi, and E. C. Baracat. 2014. Triple-negative and luminal A breast tumors: differential expression of miR-18a-5p, miR-17-5p, and miR-20a-5p. Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine 35(8):7733-7741. Chilliard, Y., A. Ferlay, J. Rouel, and G. Lamberet. 2003. A review of nutritional and physiological factors affecting goat milk lipid synthesis and lipolysis. Journal of dairy science 86(5):1751-1770. Chu, B., T. Wu, L. Miao, Y. Mei, and M. Wu. 2015. MiR-181a regulates lipid metabolism via IDH1. Scientific reports 5:8801. Denli, A. M., B. B. Tops, R. H. Plasterk, R. F. Ketting, and G. J. Hannon. 2004. Processing of primary microRNAs by the Microprocessor complex. Nature 432(7014):231-235. Fabian, M. R., N. Sonenberg, and W. Filipowicz. 2010. Regulation of mRNA translation and stability by microRNAs. Annual review of biochemistry 79:351-379. Gasparini, P., L. Cascione, M. Fassan, F. Lovat, G. Guler, S. Balci, C. Irkkan, C. Morrison, C. M. Croce, C. L. Shapiro, and K. Huebner. 2014. microRNA expression profiling identifies a four microRNA signature as a novel diagnostic and prognostic biomarker in triple negative breast cancers. Oncotarget 5(5):1174-1184. Gregory, R. I., K. P. Yan, G. Amuthan, T. Chendrimada, B. Doratotaj, N. Cooch, and R. Shiekhattar. 2004. The Microprocessor complex mediates the genesis of microRNAs. Nature 432(7014):235-240. Gu, Z., S. Eleswarapu, and H. Jiang. 2007. Identification and characterization of microRNAs from the bovine adipose tissue and mammary gland. FEBS letters 581(5):981-988. Han, J., Y. Lee, K. H. Yeom, Y. K. Kim, H. Jin, and V. N. Kim. 2004. The Drosha-DGCR8 complex in primary microRNA processing. Genes & development 18(24):3016-3027.

Hans Otto HANSEN, I. GRUNNET, and J. KNUDSEN. 1984. Triacylglycerol synthesis in goat mammary gland. The effect of ATP, Mg2+ and glycerol 3-phosphate on the esterification of fatty acids synthesized de novo. Biochem. J 220:513-519. Hinrichs, J. 2004. Mediterranean milk and milk products. European journal of nutrition 43 Suppl 1:I/12-17. Humphries, B., Z. Wang, A. L. Oom, T. Fisher, D. Tan, Y. Cui, Y. Jiang, and C. Yang. 2014. MicroRNA-200b targets protein kinase Calpha and suppresses triple-negative breast cancer metastasis. Carcinogenesis 35(10):2254-2263. Ji, Z., G. Wang, Z. Xie, C. Zhang, and J. Wang. 2012. Identification and characterization of microRNA in the dairy goat (Capra hircus) mammary gland by Solexa deep-sequencing technology. Molecular biology reports 39(10):9361-9371. Kadegowda, A. K. G., M. Bionaz, L. S. Piperova, R. A. Erdman, and J. J. Loor. 2009. Peroxisome proliferator-activated receptor-γ activation and long-chain fatty acids alter lipogenic gene networks in bovine mammary epithelial cells to various extents. Journal of dairy science 92(9):4276-4289. Kang, K., X. Zhang, H. Liu, Z. Wang, J. Zhong, Z. Huang, X. Peng, Y. Zeng, Y. Wang, Y. Yang, J. Luo, and D. Gou. 2012. A novel real-time PCR assay of microRNAs using S-Poly(T), a specific oligo(dT) reverse transcription primer with excellent sensitivity and specificity. PloS one 7(11):e48536. Kang, W., J. H. Tong, R. W. Lung, Y. Dong, J. Zhao, Q. Liang, L. Zhang, Y. Pan, W. Yang, J. C. Pang, A. S. Cheng, J. Yu, and K. F. To. 2015. Targeting of YAP1 by microRNA-15a and microRNA-16-1 exerts tumor suppressor function in gastric adenocarcinoma. Molecular cancer 14:52. Lee, E. K., M. J. Lee, K. Abdelmohsen, W. Kim, M. M. Kim, S. Srikantan, J. L. Martindale, E. R. Hutchison, H. H. Kim, B. S. Marasa, R. Selimyan, J. M. Egan, S. R. Smith, S. K. Fried, and M. Gorospe. 2011. miR-130 suppresses adipogenesis by inhibiting peroxisome proliferator-activated receptor gamma expression. Mol Cell Biol 31(4):626-638. Lee, Y., C. Ahn, J. Han, H. Choi, J. Kim, J. Yim, J. Lee, P. Provost, O. Radmark, S. Kim, and V. N. Kim. 2003. The nuclear RNase III Drosha initiates microRNA processing. Nature 425(6956):415-419. Lin, C. W., Y. L. Chang, Y. C. Chang, J. C. Lin, C. C. Chen, S. H. Pan, C. T. Wu, H. Y. Chen, S. C. Yang, T. M. Hong, and P. C. Yang. 2013a. MicroRNA-135b promotes lung cancer metastasis by regulating multiple targets in the Hippo pathway and LZTS1. Nature communications 4:1877. Lin, X., J. Luo, L. Zhang, W. Wang, and D. Gou. 2013b. MiR-103 controls milk fat accumulation in goat (Capra hircus) mammary gland during lactation. PLoS One 8(11):e79258. Lin, X., J. Luo, L. Zhang, and J. Zhu. 2013c. MicroRNAs synergistically regulate milk fat synthesis in mammary gland epithelial cells of dairy goats. Gene expression 16(1):1-13. Lin, X. Z., J. Luo, L. P. Zhang, W. Wang, H. B. Shi, and J. J. Zhu. 2013d. MiR-27a suppresses triglyceride accumulation and affects gene mRNA expression associated with fat metabolism in dairy goat mammary gland epithelial cells. Gene 521(1):15-23. Liu, Q., X. Gu, Y. Zhao, J. Zhang, Y. Zhao, Q. Meng, G. Xu, X. Hu, and N. Li. 2010. Pig large tumor suppressor 2 (Lats2), a novel gene that may regulate the fat reduction in adipocyte. BMB reports 43(2):97-102. Luna, P., A. Bach, M. Juarez, and M. A. de la Fuente. 2008. Effect of a diet enriched in whole linseed and sunflower oil on goat milk fatty acid composition and conjugated linoleic acid isomer profile. Journal of dairy science 91(1):20-28. Marquart, T. J., R. M. Allen, D. S. Ory, and A. Baldan. 2010. miR-33 links SREBP-2 induction to repression of sterol transporters. Proceedings of the National Academy of Sciences of the United

States of America 107(27):12228-12232. Peng, J., J. S. Zhao, Y. F. Shen, H. G. Mao, and N. Y. Xu. 2015. MicroRNA expression profiling of lactating mammary gland in divergent phenotype swine breeds. International journal of molecular sciences 16(1):1448-1465. Peterson, D. G., E. A. Matitashvili, and D. E. Bauman. 2004. The Inhibitory Effect of trans-10, cis-12 CLA on Lipid Synthesis in Bovine Mammary Epithelial Cells Involves Reduced Proteolytic Activation of the Transcription Factor SREBP-1. The Journal of nutrition 134(10):2523-2527. Previs, S. F., D. J. Withers, J. M. Ren, M. F. White, and G. I. Shulman. 2000. Contrasting effects of IRS-1 versus IRS-2 gene disruption on carbohydrate and lipid metabolism in vivo. The Journal of biological chemistry 275(50):38990-38994. Seo, E., U. Basu-Roy, P. H. Gunaratne, C. Coarfa, D. S. Lim, C. Basilico, and A. Mansukhani. 2013. SOX2 regulates YAP1 to maintain stemness and determine cell fate in the osteo-adipo lineage. Cell reports 3(6):2075-2087. Sharma, S. B., C. C. Lin, M. K. Farrugia, S. L. McLaughlin, E. J. Ellis, K. M. Brundage, M. A. Salkeni, and J. M. Ruppert. 2014. MicroRNAs 206 and 21 cooperate to promote RAS-extracellular signal-regulated kinase signaling by suppressing the translation of RASA1 and SPRED1. Molecular and cellular biology 34(22):4143-4164. Shi, H., J. Luo, J. Zhu, J. Li, Y. Sun, X. Lin, L. Zhang, D. Yao, and H. Shi. 2013. PPAR gamma Regulates Genes Involved in Triacylglycerol Synthesis and Secretion in Mammary Gland Epithelial Cells of Dairy Goats. PPAR research 2013:310948. Shirasaki, T., M. Honda, T. Shimakami, R. Horii, T. Yamashita, Y. Sakai, A. Sakai, H. Okada, R. Watanabe, S. Murakami, M. Yi, S. M. Lemon, and S. Kaneko. 2013. MicroRNA-27a regulates lipid metabolism and inhibits hepatitis C virus replication in human hepatoma cells. Journal of virology 87(9):5270-5286. Sun, X., J. Lin, Y. Zhang, S. Kang, N. Belkin, A. K. Wara, B. Icli, N. M. Hamburg, D. Li, and M. W. Feinberg. 2016. MicroRNA-181b Improves Glucose Homeostasis and Insulin Sensitivity by Regulating Endothelial Function in White Adipose Tissue. Circulation research 118(5):810-821. Wang, J., E. Tsouko, P. Jonsson, J. Bergh, J. Hartman, E. Aydogdu, and C. Williams. 2014. miR-206 inhibits cell migration through direct targeting of the actin-binding protein coronin 1C in triple-negative breast cancer. Molecular oncology 8(8):1690-1702. Wilfred, B. R., W. X. Wang, and P. T. Nelson. 2007. Energizing miRNA research: a review of the role of miRNAs in lipid metabolism, with a prediction that miR-103/107 regulates human metabolic pathways. Molecular genetics and metabolism 91(3):209-217. Xia, Y. and Y. Gao. 2014. MicroRNA-181b promotes ovarian cancer cell growth and invasion by targeting LATS2. Biochemical and biophysical research communications 447(3):446-451. Yin, H., A. Pasut, V. D. Soleimani, C. F. Bentzinger, G. Antoun, S. Thorn, P. Seale, P. Fernando, W. van Ijcken, F. Grosveld, R. A. Dekemp, R. Boushel, M. E. Harper, and M. A. Rudnicki. 2013. MicroRNA-133 controls brown adipose determination in skeletal muscle satellite cells by targeting Prdm16. Cell metabolism 17(2):210-224. Yu, S. and J. K. Reddy. 2007. Transcription coactivators for peroxisome proliferator-activated receptors. Biochimica et biophysica acta 1771(8):936-951. Zhu, J., Y. Sun, J. Luo, M. Wu, J. Li, and Y. Cao. 2015. Specificity protein 1 regulates gene expression related to fatty acid metabolism in goat mammary epithelial cells. International journal of molecular sciences 16(1):1806-1820.

Table 1 Predicted miR-181b target genes are associated with fat metabolism DO term

Number of target genes

p-value

lipid localization lipid transporter activity lipid biosynthetic process lipid-binding Regulation of lipid metabolic process Regulation of fatty acid metabolic process lipid metabolism

12 4 16 9 8 3 7

8.9E-1 9.9E-1 1.0E0 1.0E-1 4.5E-1 7.7E-1 8.1E-1

The p-value is calculated using Fisher's exact test.

Figure1.A: Screening for miRNAs involves in the peak-lactation and late-lactation. The samples are mixture of three goats (at the same period) in peak-lactation and late-lactation, respectively. The expression of 18s rRNA is used as a normalization control. B: Predicted miR-181b target genes are associated with fat metabolism. All experiments are duplicated and repeated three times. Values are presented as means ± standard errors, *, P<0.05; **, P<0.01. Figure2. A: GMECs are transfected with miR-181b mimic or inhibitor for 48h, IRS2 expression level is quantified by RT-qPCR (n=6). White bars represent negative control; black bars represent miR-181b mimic or inhibitor. B and C: Target site of miR-181b in IRS2 3′-UTR and the construction of the luciferase (Luc) expression vector fuses with the IRS2 3′-UTR. WT represents Luc reporter vector with the WT IRS2 3′-UTR (1601 to 1608); MU represents Luc reporter vector with the mutation at miR-181b site in IRS2 3′-UTR. D: Western blot analysis of IRS2 expression in the miR-181b mimic and NC treatment experiments. The effect of miR-181b mimics and Inhibitor on IRS2 protein expression is evaluated by western blot analysis in GMECs. Total protein is harvested 48 h post-transfection, respectively. Figure3. A: Triglyceride levels in cells transfect with miR-181b mimic (60nM) or inhibitor (60nM); triglyceride levels are compared with that of control (n=6). White bars represent negative control; black bars represent miR-181b mimic or inhibitor. B: Cholesterol levels in cells transfect with miR-181b mimic (60nM) or inhibitor (60nM); cholesterol levels are compared with that of control (n=6). White

bars represent negative control; black bars represent miR-181b mimic or inhibitor. C: GMECs are conducted with miR-181b mimic or inhibitor for 48h, and the expression of β-casein is quantified by RT-qPCR (n=6). D: Western blot analyses the expression ofβ-casein in the miR-181b mimic or inhibitor treatment experiments. The effect of miR-181b mimic or inhibitor on β -casein protein expression is evaluated by western blot analysis in GMECs. Total protein is harvested 48h post-treatment, respectively. E: Changes in the lipid contents of GMECs are conducted with miR-181b mimic or inhibitor for 48h. Cells are stained by oil red. After examined microscopically, the oil red is extracted with 400µl of isopropanol and its absorbance is detected at 510nm. The relative fat droplet content is normalized to control treatment cells including NC mimic treatment(a), miR-181b mimic treatment (b), NC inhibitor treatment (c), miR-181b and (d) inhibitor treatment. All experiments are duplicated and repeated three times. Values are presented as means ± standard errors, *, P<0.05; **, P<0.01. Figure4.A: miR-181b expression in various tissues of milk goats. The miR-181b expression level is detected in heart, liver, spleen, lung, kidney, muscle, mammary gland, stomach and sebum. The expression of 18s rRNA is used as a normalization control. B: miR-181b expression in various period of milk goats. The miR-181b expression level is detected in no-pregnancy, early-lactation (15 days after parturition) and peak-lactation (60 days after parturition), late-lactation(150 days after parturition) and non- lactation. The expression of 18s rRNA is used as a normalization control. C: IRS2 expression in various tissues of milk goats. The IRS2 expression level is detected in heart, liver, spleen, lung, kidney, muscle, mammary gland, stomach and sebum. The expression of UXT is used as a normalization control. D: IRS2 expression in various period of milk goats. The IRS2 expression level is detected in no-pregnancy, early-lactation (15 days after parturition) and peak-lactation (60 days after parturition), late-lactation(150 days after parturition) and nonlactation. The expression of UXT is used as a normalization control. E: Expression of fat metabolism related genes. GMECs are transfected with miR-181b mimic or inhibitor for 48h, and the mRNA expression of ACOX1, ACSL1, HSL, DGAT1 and CD36 is quantified by RT-qPCR (n=6). White bars represent miR-181b mimic; black bars represent miR-181b inhibitor.

Figure5.A: Triglyceride levels in cells transfect with Si-NC (60nM) or SiRNA- IRS2 (60nM); triglyceride levels are compared with that of control (n=6). White bars represent negative control; black bars represent SiRNA- IRS. B: Cholesterol levels in cells transfect with Si-NC (60nM) or

SiRNA- IRS2 (60nM); Cholesterol levels are compared with that of control (n=6). White bars represent negative control; black bars represent SiRNA- IRS2. C: GMECs are conducted with Si-NC (60nM) or SiRNA-IRS2 (60nM), and the expression ofβ-casein is quantified by RT-qPCR (n=6). D: Western blot analyses the expression ofβ-casein in the Si-NC (60nM) or SiRNA- IRS2 (60nM) treatment experiments. The effect of Si-NC (60nM) or SiRNA- IRS2 (60nM) onβ-casein protein expression is evaluated by western blot analysis in GMECs. Total protein is harvested 48h post-treatment, respectively. E:Triglyceride levels in cells transfect with Control inhibitor(50nM)+ Control siRNA(50nM), Inhibitor-miR-181b (50nM)+ Control siRNA(50nM) and Inhibitor-miR-181b (50nM)+ siRNA- IRS2 (50nM); triglyceride levels are compared with that of control (n=6). Values are presented as means ± standard errors, *, P<0.05; **, P<0.01.

Figure6. A: GMECs are transfected with miR-181b mimic or inhibitor for 48h, LATS1 expression level is quantified by RT-qPCR (n=6). White bars, negative control; black bars, miR-181b mimic or inhibitor. B: Western blot analysis of LATS1 expression in the miR-181b mimic and NC treatment experiments. The effect of miR-181b mimics and Inhibitor on LATS1 protein expression is evaluated by western blot analysis in GMECs. Total protein is harvested 48 h post-transfection, respectively. C: GMECs are transfected with Si-NC (60nM) or SiRNA- LATS1 (60nM) for 48h, the mRNA expression of YAP1 is quantified by RT-qPCR (n=6). White bars, negative control; black bars, SiRNA- LATS1. D: Western blot analysis of YAP1 expression in the Si-NC (60nM) or SiRNA- LATS1 (60nM) treatment experiments. The effect of Si-NC (60nM) or SiRNA- LATS1 (60nM) for 48h on YAP1 protein expression is evaluated by western blot analysis in GMECs. Total protein is harvested 48h post-treatment, respectively. E: GMECs are transfected with miR-181b mimic or inhibitor for 48h, YAP1 expression level is quantified by RT-qPCR (n=6). White bars, negative control; black bars, miR-181b mimic or inhibitor. F: Western blot analysis of YAP1 expression in the miR-181b mimic and NC treatment experiments. The effect of miR-181b mimics and Inhibitor on YAP1 protein expression is evaluated by western blot analysis in GMECs. Total protein is harvested 48 h post-transfection, respectively. G: GMECs are transfected with Si-NC (60nM) or SiRNA- IRS2 (60nM) for 48h, the mRNA expression of YAP1 is quantified by RT-qPCR (n=6). White bars, negative control; black bars, SiRNA- LATS1. H: Western blot analysis of YAP1 expression in the Si-NC (60nM) or SiRNA- IRS2 (60nM) treatment experiments. The effect of Si-NC (60nM) or SiRNA- IRS2 (60nM) for 48h on YAP1 protein expression is

evaluated by western blot analysis in GMECs. Total protein is harvested 48h post-treatment, respectively. Figure7. Diagram summarizing our findings: microRNA-181b regulating multiple genes in the Hippo pathway and target IRS2

Highlights 

After screening miRNAs in periods of peak-lactation and late-lactation, we have concluded that miR-181b shows a higher expression.



We established the regulating relation between miR-181b and its target gene IRS2, and conducted the rescue experiment to prove that miR-181b exercises its function indeed via IRS2.



We made a further research and discussion about the function of miR-181b and Wnt signaling pathway in the GMEC.