A transcriptome approach evaluating the effects of Atractylenolide Ⅰ on the secretion of estradiol and progesterone in feline ovarian granulosa cell

A transcriptome approach evaluating the effects of Atractylenolide Ⅰ on the secretion of estradiol and progesterone in feline ovarian granulosa cell | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A transcriptome approach evaluating the effects of Atractylenolide Ⅰ on the secretion of estradiol and progesterone in feline ovarian granulosa cell yuli guo, Junping Liu, Shuangyi Zhang, Di Sun, Zhiying Dong, Jinshan Cao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3080498/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Atractylodes macrocephala Koidz (AMK) as eartraditional oriental medicine has been used in the treatment of threatened abortion. Atractylenolide I (AT-I) is one of the major bioactive components of AMK. This study aimed to investigate the effect of AT-I on the secretion of estradiol (E 2 ) and progesterone (P 4 ) of feline ovarian granulosa cells (FOGCs) which is necessary for pregnancy. At first, the prolifeation of FOGCs after AT-I treatment was measured by CCK-8. Then, the synthesis of E 2 and P 4 were measured by ELISA. Lastly, transcriptome sequencing was used to detect the DEGs in the FOGCs, and RNA-Seq results were verified by RT-qPCR and biochemical verification. It was found that AT-I could promote proliferation and the secretion of E 2 and P 4 in FOGCs; after AT-I treatment, 137 significantly DEGs were observed, out of which 49 were up-regulated and 88 down-regulated. The DEGs revealed significant enrichment of 52 GO terms throughout the differentiation process ( P < 0.05) as deciphered by Gene Ontology enrichment analysis. Kyoto Encyclopedia of Genes and Genomes analysis manifested that the DEGs were successfully annotated as members of 155 pathways, with 23 significantly enriched ( P < 0.05). A relatively high number of genes were enriched for the cholesterol metabolism, ovarian steroidogenesis, and biosynthesis of unsaturated fatty acids. Furthermore, the contents of the total cholesterol and low-density lipoprotein cholesterol were decreased by AT-I treatment in the cell culture supernatant. The results indicated that AT-I could increase the ability of FOGCs to secrete E 2 and P 4 , which might be achieved by activation of cholesterol metabolism. ovarian granulosa cell Atractylenolide-I estradiol progesterone cholesterol metabolism Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction Atractylodes macrocephala Koidz (AMK) has been commonly used in the clinical prescription for preserving fetuses, and their fetal safety effects have been confirmed by thousands of years of medical practice in traditional Chinese medicine (Zhu et al., 2018 ). As one of the major bioactive components in AMK, Atractylenolide I (AT-I) is a naturally occurring sesquiterpene lactone has been found to display a wide range of pharmacological and biological activities such as anti-atherosclerotic and the treatment of various inflammatory illness, etc (G. Ji, 2014 ; Li et al., 2017 ; Long et al., 2017 ; Song et al., 2017 ). The Progesterone (P4) has a variety of physiological functions, such as promoting endometrial decidualization,establishing maternal-fetal immune tolerance,inhibiting inflammatory response, and improving uterine-placental circulation, which are prerequisites for the maintenance of pregnancy (Mesen and Young, 2015 ; Nardo and Sallam, 2006 ). Insufficient secretion of P 4 affects endometrial secretion, thereby affecting embryo implantation and development. In early embryonic development, P 4 mainly comes from luteal granulosa cells, so the activity of granulosa cells plays a very important role in corpus luteum (CL) development and early pregnancy maintenance (Niswender et al., 2000 ). Maintaining a certain concentration of estradiol (E 2 ) can increase the uterine placental blood flow and increase the sensitivity of the uterus to P 4 (Braun et al., 2012 ).E 2 plays a role in the endometrium mainly through its homologous nuclear receptors ESR1 and ESR2, and participates in the decidualization process of the endometrium through the ERK/MAPK pathway (Braun et al., 2012 ). Studies have shown that if the E 2 content is too low, it would lead to embryo implantation failure (Vannuccini et al., 2016 ). Therefore, determining the effect of AT-I on the secretion of E 2 and P 4 in feline ovarian granulosa cells (FOGCs) might contribute to our understanding of the protection of AMK in early pregnancy. In recent years, the high-throughput RNA sequencing technique (RNA-seq) has emerged as a powerful tool for transcriptome analysis (Guo-Liang Zhang, 2017). By using this method, it might help to assess the changes of the transcriptome in FOGCs upon treatment with AT-I at the whole genome scale, contributing to explain the mechanism of how AT-I regulates the changes of FOGCs. 2. Materials and methods 2.1 AT-I structure AT-I (CAS No. 73069-13-with purity ≥ 98%) used in this study were purchased from Dalian Meilune Biotechnology Co. Ltd. (Liaoning, China). The chemical structure of the AT-I has been depicted in Fig. 1 . 2.2 Culture of primary feline ovarian granulosa cells FOGCs were obtained from fresh ovarian tissues of healthy and diestrus period felines between six months and two years old, which were under sterilization operation in the animal hospital of Inner Mongolia Agricultural University. The feline ovarian tissues were maintained in a vacuum thermos flask containing sterile physiological saline and transported to the laboratory within 2 h. The ovarian tissues were washed several times with 37 ℃ DPBS solution (Gibco, MA, USA), contained 3% penicillin and streptomycin (Gibco, MA, USA,) until the tissues completely clean. The tissues were then transferred to a 300 mm diameter plate with 0.5 mL of 12% fetal calf serum-supplemented Ham’s F-12 nutrient mixture (DMEM/F12, Gibco, MA, USA). Thereafter, the follicular fluid and cumulus-oocyte complexes (COCs) from primary follicles between 1 and 1.5 mm in diameter were aspirated by using a 2.5 mL aseptic syringe. Collected cells were transferred to a 1mL centrifuge tube and centrifuged at 1500 rpm for 3 min, then sediment was harvested and washed with DPBS solution. This process was repeated three times. Afterward, the isolated FOGCs were transferred in DMEM/F12 medium containing 12% fetal bovine serum (Excell Biology, Shanghai, China), 1% streptomycin and penicillin, and cultivated in a 5% CO 2 incubator at 37°C. Cell growth and morphological characteristics were observed with inverted microscope (Philips, Tokyo, Japan). After 72 h, the oocytes were washed out with DPBS, and the granulosa cells were isolated. Then, the medium was renewed routinely every other day until the cell density reached 75–80%, then digested with 0.25% trypsin-EDTA (Gibco, MA, USA) of 1mL for 2 min, and the digestion was terminated with the DMEM/F12 culture medium containing 12% serum. After fully mixing, inoculated at a split ratio of 1:2 for subsequent cultivation. 2.3 Morphological observations The FOGCs at the logarithmic growth phase were seeded 100 µL at a density of 1 × 10 5 cells/mL on the autoclaved slides, thereafter the slides were stored in an autoclaved wet box that was placed in a 37°C, 5% CO 2 incubator for 24 h. After reaching 70% confluence, washed three times with DPBS and the cells were fixed for 20 min with cold acetone. The processed slides were then stained with two different staining methods: hematoxylin-eosin (HE) and Wright-Giemsa, photographed and analyzed by using a light microscope (ECLIPSE TS100-F. Nikon, Tokyo, Japan). 2.4 Immunofluorescence identification To analyze the identity and purity of isolated FOGCs, immunofluorescence staining for a specific marker of ovarian granulosa cells was performed by FSHR (follicle stimulating hormone receptor). Seeded the logarithmic growth phase FOGCs 0.5 mL at a density of 1 × 10 5 cells/mL into 35 mm glass-bottom dishes (Shengyou Biotechnology, Hangzhou, China). After the cells reached 80% confluence, washed three times with aseptic DPBS solution, fixed for 30 min with 4% paraformaldehyde (Solarbio, Beijing, China) at room temperature, and washed three times with DPBS. After fixation, the FOGCs were incubated with 1mL 0.25% Triton X-100 (PH=7.40, Sigma-Aldrich, MO, USA) for 20 min, then washed three times with DPBS. After blocking for non-specific binding sites, the cells were stained with primary antibody to FSHR (1:200, Rabbit Anti-FSH receptor antibody; BS-0895R; Bioss; Beijing, China) overnight at 4°C. The granulosa cells were washed three times in DPBS and incubated with a secondary antibody (Alx647; donkey-anti-rabbit IgG; Jackson, Pennsylvania, USA) for 2 h at room temperature in the dark. After incubation, the cells were washed three times for 10 min with DPBS in the dark. Then with DAPI stained the nuclei, washed on the decolorizing shaker 4 times for 10 min. Observed glass-bottom dishes under an LSM 800 (Zeiss, Jena, Germany) laser confocal system. 2.5 Cell viability assay The cell viability was assessed using Cell Counting Kit-8 assays (CCK-8; BS350B; Biosharp; Shanghai, China). The second-generation feline ovary granule cells were used, washed with DPBS, and 1mL of 0.25% trypsin–EDTA was added to digest them for 2 min. Thereafter, DMEM/F12 medium containing 12% fetal bovine serum (Excell Biology, Shanghai, China) was added to stop the digestion. The pipetting was repeated to ensure that the cells are away from the wall and uniformly distributed. After digestion, the cell suspension concentration was adjusted to 2×10 6 cells/mL. Thereafter, a 96-well cell culture plate was taken, 100 µL of culture medium with cells was added to each well, and the plate was incubated for 12 h. Thereafter, 100 µL DPBS was added to the remaining wells to reduce evaporation. The cells in the plate were purified for 6 h (with the serum-free medium), the cell supernatant was purged after purification, and 100 µL medium (containing 12% serum) was added. The plate was cultivated for 6 h, 12 h, 24 h, 36 h, and 48 h, then CCK-8 was added for 4 h. After then, the absorbance value (OD value) of each well was measured with a microplate reader at a wavelength of 450 nm. 2.6 Cytotoxicity of AT-Ⅰ against primary feline ovarian granulosa cells After the FOGCs purified as described above, 100 µL medium (containing 12% serum) with different AT-I concentrations (0 µmol/L, 1 µmol/L, 3 µmol/L, 10 µmol/L, 30 µmol/L, 100 µmol/L, 300 µmol/L) was added to the plate and incubated at 37℃ for 0 h,12 h, 24 h, 36 h and 48 h, CCK-8 was added for 4 h and the absorbance value of each well was measured with a microplate reader at a wavelength of 450 nm to measure the cytotoxicity. 2.7 Determination of estradiol (E 2 ) and progesterone (P 4 ) concentration FOGCs were seeded at a density of 2×10 6 cells/mL in 6-well cell culture plates and cultivated at 5% CO 2 and 37°C until 70% of the cells were fused. The cell culture supernatant was then removed and 2 mL of fresh DMEM/F12 medium containing 10 µmol/L AT-I was added to the FOGCs monolayer for co-culturing at 37°C with 5% CO 2 . After incubation for 0 h, 12 h, 24 h, 36 h and 48 h respectively, the supernatant was aspirated and used for subsequent experiments. The control cells were treated with DMEM/F12 medium with the same time condition. Three different biological replicates were designed for both the treatment and control experiments. The concentrations of E 2 in the culture medium were measured by enzyme-linked immunosorbent assay (Wuhan Xinqidi Biological Technology; Wuhan, China) according to the manufacturer’s instructions. The estradiol standard curve ranged from 0 to 1000 pg/mL. The samples were analyzed in triplicates. The assay sensitivity, range, and intra-assay coefficient of variation were 5 pg/mL, 15.6–1000 pg/mL, and ≤ 8%, respectively. The concentrations of P 4 in the culture medium were measured by enzyme-linked immunosorbent assay (Wuhan Xinqidi Biological Technology; Wuhan, China) according to the manufacturer’s instructions. The progesterone standard curve ranged from 0 to 100 ng/mL. The samples were analyzed in triplicates. The assay sensitivity, range, and intra-assay coefficient of variation were 0.5 ng/mL, 1.56–100 ng/mL, and ≤ 8%, respectively. 2.8 AT-I treatment According to the above experiments, we selected the 10 µmol/L AT-I and incubated it for 36 h for the next study. FOGCs were seeded at a density of 2 × 10 6 cells/mL in 6-well cell culture plates and cultivated at 37°C and 5% CO 2 until they reached 70% confluence. The cell culture supernatant was thereafter removed and 2 mL of fresh DMEM/F12 medium containing 10 µmol/L AT-I was added to the FOGCs monolayer and the plate was incubated for 36 h at 37°C and 5% CO 2 . After AT-I treatment, FOGCs were photographed and analyzed for potential morphological changes using an inverted microscope (Philips, Tokyo, Japan). The supernatant was aspirated and used for subsequent experiments. Thereafter, FOGCs were gently washed three times with DPBS to remove the remaining drug, collected the cells for transcription analysis. The control cells were treated with DMEM/F12 medium only. Three biological replicates were tested for the treatment and control experiments. 2.9 RNA library construction and sequencing Total RNA from untreated and AT-I treated FOGCs was extracted according to the instructions of the Axygen-RNA extraction kit (AxyGen, CA, USA), and there were three biological repeats in each group. Bioanalyzer 2100 and RNA 6000 Nano LabChip Kit (Agilent, CA, USA) were thereafter used to analyze the quantity and purity of total RNA, yielding RIN scores>8.0, in accordance with the testing standard. Magnetic beads connected with Oligo were used to enrich and purify eukaryotic mRNA with poly-A tail. The extracted eukaryotic mRNA was randomly broken into short fragments by the fragmentation reagent (Fragmentation Buffer). Using the fragmented mRNA as the template, one-strand cDNA was synthesized by a six-base random primer (Random hexamers), and then the buffer, dNTPs, RNaseH, and DNA Polymerase I was added to synthesize the two-strand cDNA. The cDNA double-stranded product was purified by AMPureXP beads. The viscous end of DNA was repaired to a flat end by T4 DNA polymerase and Klenow DNA polymerase, and the 3 'end was selected by adding base An and splice, AMPureXP beads. Finally, the final sequencing library was obtained by PCR amplification. After passing the quality inspection of the library, the library was sequenced with Illumina Hiseq 4000 to produce 150 bp double-terminal data. The cDNA library was sequenced on an Illumina HiSeq 4000 sequencing platform (Illumina, San Diego, USA) provided by Majorbio Bio-pharm Technology Co., Ltd (Shanghai, China). 2.10 Statistical analysis of transcription data The raw RNA-seq data was then filtered to remove various adaptor contamination, low-quality bases, and undetermined bases utilizing Cutadapt software (Maher et al., 2009 ). The sequencing quality was verified using FASTQC software including the Q20, Q30, and GC content of the clean data. All downstream analysis was based on clean as well as high-quality data. The filtered reads were aligned and mapped to the reference genome using Hisat 2.0. The aligned read files were processed by Cufflinks (Martin M, 2011 ), which uses the normalized RNA-seq fragment counts to measure the relative abundances of the different transcripts. The unit of measurement is fragments per kilobases of exon per million fragments mapped (FPKM). The DEGs were screened using R package edger (Love M I, 2014) with fold change (FC) ≥ 1.5 and P-adjust <0.05, which were considered significantly different expressed (Anders and Huber, 2010 ). The DEGs underwent enrichment analysis using GO and KEGG. P values were calculated using the Benjamini-corrected modified Fisher exact test, and P <0.05 was deemed statistically significant. 2.11 Validation by quantitative reverse transcription PCR Quantitative reverse transcription PCR (RT-qPCR) was utilized to validate the DEGs identified by RNA-seq. The total RNA concentration of all samples was adjusted to 300 ng/µL at the same time, and cDNA was used as starting material for real-time PCR with FastStart Universal SYBR Green Master (Roche, Mannheim, Germany) on an iQ5 multicolor real-time PCR detection system (Bio-Rad, CA, USA). Eight DEGs were chosen based on changes in their expression levels in the treated cells as compared with the control cells. Eight DEGs were selected with cDNA as template and the glyceraldehyde 3-phosphate dehydrogenase ( GAPDH ) gene was used as the internal control. The sequence of primers is shown in Table 3 . The RT-qPCR reaction conditions are as follows: 5 min pre-incubation at 95°C; 40 cycles of amplification for 5 s at 95°C for denaturation, 34 s at 60°C for annealing, and 20 s at 72°C for elongation. Negative controls (without cDNA) were run in the same reaction set. The relative mRNA expression of DEGs in each group was calculated by the 2 −ΔΔCt formula (Kanehisa et al., 2008 ). 2.12 Biochemical verification After 10 µmol/L AT-I treatment for 36 h, the supernatant was collected for biochemical testing (lnc.BS-180vet blood biochemical analyzer; Abaxis, USA). Three biological replicates were used for the treatment and control experiments. The contents of total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) in the supernatant were detected to explore the possible effect of AT-I on lipid metabolism. 2.13 Statistical analysis The experimental data were expressed as mean ± SD. The difference between the two groups was analyzed using the T-test and One-way ANOVA. P < 0.05 was considered significant with *, P < 0.05 and **, P < 0.01. 3. Results 3.1 Identification of cultured feline ovarian granulosa cells The cells nearby the oocytes begun to display an elongated or fibroblastic property within the first 36 h ( Fig. 2 A ) . The cells were then distinguished by the presence of a triangle cone or irregular star-shaped morphology. After 3 days of culture, large number of cells was observed around oocytes in clusters. The cells confluence reached 75 to 80% on day 7. The sub-cultured cells began to adhere after 4 h, the cell could reached to 80% confluence on day 3. The similar phenomenon happed on passages 3 and 4 with classic irregular star-shaped morphology. By HE staining, the structure of cells was confirmed to be contact by which the edge was clear and a triangle cone or irregular star shape. The cytoplasm was pink, and the nuclei were dyed in blue ( Fig. 2 C ) . By Giemsa staining, the structure of cells also presented contact by which the edge was clear and a triangle cone or irregular star shape. The cytoplasm was blue-violet and the nuclei were pink ( Fig. 2 D ) . The FSHR was expressed in the cytoplasm of triangle cone-like cells by immunofluorescence staining, while FSHR was not observed in control group (without primary antibody) ( Fig. 2 E ) , confirming that FOGCs were cultivated successfully and the purity could reach 90%. 3.2 Cell viability assay The cell growth curve detected by CCK-8 assay ( Fig. 2 B ) showed that cell proliferation significantly happened after 12 h until 48 h ( P < 0.05), indicating that the way of cultivated FGOCs growth consist with that in normal cell growth. 3.3 Cytotoxicity of AT- Ⅰ on the primary FOGCs AT-I treatment in a concentration range (0 µmol/L-300 µmol/L) showed that 1, 3, 10 and 30 µmol/L could effectively promote FOGCs proliferation from 12 h to 48 h ( Fig. 3 A ) . 100 µmol/L significantly increased FOGCs proliferation after 36 h and the increased effect of 300 µmol/L happened at 48 h ( P < 0.05) ( Fig. 3 A ) . In addition, under the microscope, the increased density of granulosa cells by 10 µmol/L AT-I treatment for 36 h was clearly observed as well ( Fig. 3 B ) . These results indicated that the 10 µmol/L AT-I could enhance the viability at 36 h most obviously among selected concentration and time points indicating 10 µmol/L could be used as the experimental concentration for following experiment. 3.4 The effect of AT-I on the synthesis of E 2 and P 4 in FOGCs 10 µmol/L AT-I could significantly promote the E 2 secretion in FOGCs at 24 h and 36 h, while the increased tendency weakened at 48 h ( Fig. 4 A ) . The P 4 concentration significantly increased by AT-I treatment from 12 h to 48 h ( Fig. 4 B ) . Although the secretion of E 2 and P 4 was both increased, the ratio of P 4 /E 2 indicated that the E 2 secretion was more obviously than P 4 secretion in FOGCs within 36 h after AT-I treatment. However, the secretion pattern of E 2 and P 4 changed at 48 h, in which the FOGCs secret P 4 more obviously than that E 2 secretion ( Fig. 4 C ) . 3.5 Classification of transcriptional sequencing data To evaluate the transcriptional response of the FOGCs to AT-Ⅰ exposure and decipher the various host factors, which may be involved in the luteinization, the Illumina HiSeq 4000 platform with cDNA libraries of FOGCs treated with AT-Ⅰ were used. The sequencing quality data are shown in Table 1 , the two libraries produced 58,841,865 and 52,950,059 original sequences (Raw Data), respectively, from both the treated and control FOGC groups. After filtering, the effective date of 58,189,124 and 52,340,848 was obtained. The proportion of data quality Q20 (sequencing base mass) of the two databases is more than 98%, which meets the needs of follow-up test analysis. All the valid reads were aligned to the feline genome using Hisat 2.0. Furthermore, 56,730,426 and 51,014,192 Map Reads were obtained from the different groups of treated and control FOGCs, in which the number of Reads with unique alignment position in the genome and meeting the needs of subsequent experimental analysis were 53,563,083 and 48,058,826 respectively, and the ratio of alignment to genome sequence was 92.06% and 91.82%, respectively. The results show that the sequencing data are of high quality and meet the needs of further analysis. The sequencing data have been saved in the NCBI gene expression comprehensive database ( http://www.ncbi.nlm.nih.gov/geo/info/linking.html ) and can be obtained by GEO Series accession number GSE155784. 3.6 Analysis of differentially expressed genes FOGCs treated with the AT-Ⅰ showed a relative degree of differential expression. A total of 137 DEGs were obtained (≥ 1.5-Fold Change, P-adjust < 0.05), of which 49 DEGs were significantly up-regulated and 88 DEGs were significantly down-regulated. The overall distribution of DEGs can be understood by drawing a volcanic map. ( Fig. 5 ) . 3.7 Functional enrichment analysis of differentially expressed gene The RNA-seq analysis revealed a total of 17 265 genes, of which 137 genes were significant differences in expression. To assess the biological functions of the 137 DEGs, enrichment analysis of GO classification ( http://www.geneontology.org/ ) and the KEGG pathway ( http://www.genome.jp/kegg ) was systematically performed. The annotated results of the GO database in the sequencing are shown in Fig. 6 . The histogram of GO enrichment analysis is mainly reflected in biological processes, cellular components, and molecular functions. In biological processes, 644 DEGs are assigned to the regulation of biological processes, such as cellular processes, single-organism process, biological regulation, regulation of biological process development, and metabolic processes. In the cell component field, 308 DEGs belong to the the cell, the cell part, and membrane. In the molecular functional class, 93 DEGs resins can be used for binding and catalytic activity. KEGG analysis showed that the DEGs were mainly involved in the regulation of the various signal transduction pathways, signaling molecules and their possible interactions, membrane transport, lipid metabolism, endocrine system, as well as digestive system ( Fig. 7 ) . The DEGs successfully annotated 155 signal pathways, and 23 signal pathways were significantly different ( P < 0.05). Relatively high numbers of different genes were involved in the regulation of cholesterol metabolism, ovarian steroidogenesis, rheumatoid arthritis, biosynthesis of unsaturated fatty acids, steroid hormone biosynthesis, AMPK signaling pathway, ABC transporters, and other signaling pathways ( Fig. 8 ) . DEGs were analyzed with KEGG to predict and study the signal pathways that are mainly involved and most interested, and to obtain those pathways that may be related to the luteinizing effect of AT-I. In the various pathways associated with the response of the FOGCs treated with AT-I, 9 DEGs were found to be significantly affected ( Table 2 ) . Among the DEGs, three genes ( ABCA1 , LDLR , and SREBF1 ) were found to be upregulated and involved in the regulation of the cholesterol metabolism, cholesterol metabolism is a complex biological process and most of the other DEGs identified were also found to actively participate in this process. Three genes ( StAR, LDLR and CYP1A1 ) have been implicated in the regulation of ovarian steroidogenesis. Two genes ( SCD , and FADS2 ) were upregulated and were found to be involved in the biosynthesis of unsaturated fatty acids. Two genes ( ABCG1 , and ABCA1 ) were upregulated and participated in ABC transporters, and the two DEGs ( SREBF1 , and SCD ) were observed to be upregulated and could participate in the regulation of the AMPK signaling pathway. 3.8 Validation of the selected Genes by quantitative reverse transcription PCR and Biochemical analysis To validate the results of RNA-seq analysis, RT-qPCR was used to examine the various DEGs. All DEGs have the same trend of changes with RNA-seq data. Thereby suggesting that the RNA-seq data reliably reflected the changes in the trends of gene expression ( Fig. 9 A ) . To verify whether AT-I can promote the metabolism of cholesterol, the biochemical analysis of the supernatants of granulosa cells treated with AT-I was carried out. It was found that the contents of the total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) in the treated group with AT-I were significantly lower than those in the control group ( Fig. 9 B ) . 4. Discussion AT-I has been found to be the the major bioactive component from AMK, which is a medicinal plant that has been used as a pharmacological agent for the treatment of threatened miscarriages for a long time (Zhu et al., 2018 ). CL is an essential organ for maintain the early pregnancy, and luteal dysfunction could cause infertility and abortions (Mesen and Young, 2015 ). The CL is mainly composed of large luteum cells (LLC) and little amount of small luteum cells (SLC). LLC, which has the stronger steroidogenic capacity than that in SLC, mainly originates from ovarian granulosa cells (Hryciuk et al., 2019 ). As the major bioactive compent of AMK, the effect of AT-I on the ovarian granulosa cells might contribute to our understanding on how AMK treatment of threatened miscarriages. This study found that AT-I could promote proliferation and the secretion of E 2 and P 4 in FOGCs. And the transcriptome profile of differential gene expression in FOGCs treated with the AT-I was examined in this report. Ovarian granulosa cells as the largest cell group within the follicles, they not only cooperate with theca interstitial cells to regulate the synthesis of female steroid hormones, and also can regulate both the growth and maturation of oocytes (Havelock et al., 2004 ). At present, there is only one method to culture primary FOGCs by slicing ovaries into many pieces (Chiara Perego et al., 2021 ), but the cell identification was not carried out and the fibroblasts, endothelial cells could not effectively removed. In this study, a new method by puncturing small folliclesto to cultivate primary FOGCs and confirmed with FSHR immunofluorescence identification, the FOGCs purity could reach 90% which could be used to perform relative experiment. After ovulation, ovarian granulosa cells proliferation and transformed to LLC that can have the ability to secrete amount of P 4 and maintain early pregnancy (Luigi Devoto, 2009 ) (Richards and Pangas, 2010 ); Amelkina et al. revealed that ovarian granulosa cells could be transformed to LLC that can have the ability to secrete steroids in domestic cat (Amelkina et al., 2015 ). In this study, the FOGCs viability was noticed to increase significantly in a dose and time-dependent within a certain range ( Fig. 3 A and 3 B ) and the secretion of E 2 and P 4 increased significantly ( Fig. 4 ) after AT-I treatment in FOGCs. The increase of E2 and P4 might due to cell proliferation or enhanced single cell secretion or combined effect, which needs further investigation. Recent evidence obtained with a luteal cell line has confirmed that E 2 can positively regulate the transcriptional activity of the SR-BI gene to speed up the occurrence of the luteinization process (Stocco, 2007). In our study, after AT-I-stimulation, E 2 concentration was observed to increase in 36 h, and after AT-I treatment 36 h, FOGCs can produce a substantial amount of P 4 instead of E 2 that they did before and the ratio of P 4 /E 2 indicated that the P 4 secretion was more obviously than E 2 secretion in FOGCs after 36 h indicating that the AT-I might initiate luteinization process, which resulted in the enhanced P 4 secretion in FOGCs . In this study, a total of 137 DEGs were obtained after transcriptome sequencing on the FOGCs group treated with AT-I and these results were confirmed by RT-qPCR. According to the GO classification and KEGG pathway enrichment analysis, it was found that the DEGs were mainly enriched in several important pathways including those regulating cholesterol metabolism, ovarian steroidogenesis, biosynthesis of unsaturated fatty acids and ABC transporter. The unsaturated fatty acids are able to reduce the harmful cholesterol and triglyceride in the blood by esterifying cholesterol and promote cholesterol metabolism effectively control the concentration of blood lipids, and increase the content of high-density lipoprotein (HDL) which is beneficial to the human body (Wiktorowska-Owczarek et al., 2015 ). The DEGs SCD , a central regulator controlling the biosynthesis of unsaturated fatty acids (AM et al., 2017 ) was up-regulated by AT-I which might contribute to the secretion of E 2 and P 4 through regulate the biosynthesis of unsaturated fatty acid. The cholesterol metabolism is critical for the production of the various essential membrane components which is necessary for cell proliferation (Miranda-Jimenez and Murphy, 2007 ). In addition, as a precursor of steroid hormones, cholesterol is pivotal for ovarian follicular maturation (Shimano and Sato, 2017 ). Interestingly, in this study, it was found that the DEGs after AT-I treated mainly related to cholesterol metabolism. A constant supply of cholesterol is needed for the synthesis of steroid hormones in the CL and maternal cholesterol metabolism plays a role in fetal development (Woollett, 2008 ). Circulating plasma lipoproteins are the major source of cholesterol for steroid production in these different cells and cholesterol can be mainly obtained from circulating low-density lipoproteins (LDL) and small part from high-density lipoprotein (HDL) (Li et al., 2019 ; Miranda-Jimenez and Murphy, 2007 ). There are multiple systems involved in the cellular cholesterol delivery for steroidogenesis, mainly through the uptake of lipoprotein-derived cholesterol via LDLR mediated endocytic pathways (Craig et al., 2011 ). According to the RNA-seq analysis and RT-qPCR result, the expression of LDLR was induced by AT-I treatment in FOGCs, indicating the uptake of lipoprotein-derived cholesterol might be activated which could further stimulate the cholesterol biosynthesis.The identified DEGs SREBF1 that responsible for encoding sterol regulatory element-binding protein (SREBP) able to promote the transcription of various lipogenesis involved in the biosynthesis of fatty acids and cholesterols and involved in the regulation of sterol synthesis rates (Richards and Pangas, 2010 ; Wang et al., 2020 ; Woollett, 2008 ). It was reported that SREBP could up-regulated the LDLR expression promote the cholesterol uptake (Lindholm et al., 2009 ; Shimano and Sato, 2017 ) and regulate the luteinization process through enhance the sensitivity of Human Granulosa-Lutein Cells to LH (Li et al., 2019 ). After AT-I treatment, the SREBF1 expression was up-regulated than that in control group, suggesting the SREBF1 signaling pathway might be activated. The activation of SREBF1 signaling pathway by AT-I treatment might contribute to the FOGCs synthesis of steroid hormones.To further confirm the effect of AT-I on cholesterol metabolism, the biochemical test was used to detect the content of cholesterol in the cell supernatant. After AT-I treatment 36 h, the contents of total cholesterol and LDL cholesterol both declined, whereas the synthesis of steroid hormones increased, suggested that AT-I indeed significantly affect cholesterol metabolism and promote the secretion of E 2 and P 4 in FOGCs. Li et al showed that AT-I dose dependently inhibited Ox-LDL induced VSMCs proliferation to treat atherosclerosis (Li et al., 2017 ), which might be the result of increased LDLR expression. The ovaries are responsible for producing sex steroid hormones during reproductive life, which is important for both reproductive and somatic health (Richards and Pangas, 2010 ). After AT-I treatment, the secretion of E 2 and P 4 increased significantly in FOGCs. The CYP1A1 was down-regulated and thereby can reduce the degradation of E 2 to modulate ovarian steroidogenesis (Deok-Soo Son 1999). The identified DEGs LDLR is also a key gene in ovarian steroidogenesis by promote the cholesterol biosynthesis. The DEGs StAR can introduce cholesterol into mitochondria, which is essential for steroid production. Cholesterol is the major raw material for ovarian steroid hormone synthesis. According to this study, the expression of LDLR,StAR and SREBF1 increased were induced by AT-I treatment in FOGCs, and the increased gene might further stimulate the cholesterol biosynthesis which leading ovarian steroidogenesis happened. The ABCA-1 and ABCG-1 expression increased after AT-I treatment might improve the reverse cholesterol transport, and further speed up the metabolic process of cholesterol in FOGCs since ABC transport system can drive intracellular superfluous cholesterol from arterial wall macrophages to the liver, thus allowing its excretion into the bile and feces as to speed up the metabolic process of cholesterol (Iborra, 2011). AT-I can promote the biosynthesis of unsaturated fatty acids to enhance the HDL content in plasma, and dramatically enhance the ability to transport LDL into cells by increased LDLR expression; The intake cholesterol can be used as raw material for ovarian steroidogenesis incloud E 2 and P 4 . At the same time, AT-I can dynamically promote the reverse transport of cholesterol by up-regulating ABCA1 and ABCG-1 gene expression to speed up the metabolic process of cholesterol. Taken together, after AT-I treatment, the differential genes identified were mainly concentrate on cellular cholesterol uptake and efflux. Thus, it was hypothesized that AT-I might affect the secretion of E 2 and P 4 by promoting the cholesterol metabolism in the granulosa cells. 5 Conclusion This study demonstrated that AT-I could promote cholesterol metabolism determined by RNA-seq and biochemical test in FOGCs. The effect of AT-I on cholesterol metabolism might help to explaining the AT-I induced the secretion of E 2 and P 4 in FOGCs. These results together will contribute to our understanding of the mechanism of early pregnancy protection by AMR. Abbreviations AMK Atractylodes macrocephala Koidz AT-I atractylenolide I FOGCs primary feline ovarian granulosa cells RNA-seq transcriptome sequencing CL corpus luteum LLC large luteum cells SLC small luteum cells E 2 estradiol P 4 progesterone ELISA enzyme linked immunosorbent assay DEGs differentially expressed genes GO Gene Ontology KEGG Kyoto Encyclopedia of Genes and Genomes FC fold change FPKM fragmented per kilobases of exon per million fragments mapped RIN RNA integrity number RT-qPCR quantitative reverse transcription PCR DPBS dulbecco’s phosphate-buffered saline DMEM/F12 Ham’s F-12 nutrient mixture COCs cumulus-oocyte complexes HE hematoxylin-eosin FSHR follicle stimulating hormone receptor DAPI 4,6-diamidino-2-phenylindole CCK-8 cell counting kit 8 OD value optical density value TC total cholesterol LDL-C low density lipoprotein cholesterol HDL-C high density lipoprotein cholesterol SD standard deviation Declarations Acknowledgments This work was supported by the National key research and development plan "New technology for diagnosis, treatment, and prevention of pet diseases Research" (Grant 2016YFD0501000). All data included in this study are available upon request by contact with the corresponding author. The authors would like to thank Shanghai Majorbio Bio-pharm Technology Co., Ltd for sequencing services. Author contributions: Y.L Guo carried out the study, analyzed, and interpreted the data and compiled the article. J.P Liu, S.Y Zhang contributed to the design of the study, discussion of the results, and critical revision of the article. Z.Y Dong, Sun contributed to the hormone analysis and critical revision of the article. J.S Cao supervised the study and contributed to its design, discussion of the results, and critical revision of the article. Ethics approval All animal studies were conducted in accordance with the experimental practices and standards approved by the Animal Welfare and Research Ethics Committee at Inner Mongolia Agricultural University (Approval ID: 20160829-1). Declaration of competing interest The authors declare that there is no conflict of interest. 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Gene name Gene Description Fold Change P adjust Regulation ABCA1 ATP binding cassette subfamily A member 1 4.554 0.000006 up SCD stearoyl-CoA desaturase 2.48 0.003099 up LDLR low density lipoprotein receptor 1.934 0.025723 up CYP1A1 cytochrome P450 1A1 0.451 0.026415 down FADS2 fatty acid desaturase 2 1.609 0.034371 up ABCG1 ATP binding cassette subfamily G member 1 3.724 0.044671 up SREBF1 sterol regulatory element binding transcription factor 1 1.839 0.040339 up StAR steroidogenic acute regulatory protein 1.48 0.042111 up MYLIP myosin regulatory light chain interacting protein 2.451 0.002304 up Table 3 Primers for RT-qPCR. Gene Name Nucleotide sequence (5’-3’) GAPDH Forward CAAGGCTGTGGGCAAGGTCATC Reverse TTCTCCAGGCGGCAGGTCAG SREBF1 Forward GGCATCGCAAGCAGGCTGAC Reverse GGTGGGAGGTGGGCAGTGG ABCG1 Forward ACATGCTGTTGCCACACCTCAC Reverse TCCTGCCTTCGTCCTTCTCCTG ABCA1 Forward GGCAACGGCACTGAGGAAGATG Reverse TGCGGGAAAGAGGACTGGACTC LDLR Forward GCCAGCAGAGGAGACGAGGAG Reverse CCCGAAGCCCAGGAGGATGAG SCD Forward AAATTCCCTTCGGCCAATGAC Reverse TCTCACCTCCTCTTGCAGCAA CYP1A1 Forward TGGCACCATCAACAAGGCACTG Reverse AAAGACCTCCAAGCGGGCAATG FADS2 Forward GGATATGCGGGCGTAGAAGC Reverse GTGCCGTGCAAATAGGTGGA StAR Forward GTGGAGCACATGGAAGCGATGG Reverse GCAGCCAACTCGTGGGTGATG MYLIP Forward AACGAGGGAGCAGGGTTGAA Reverse ACACTGCCGAGACAGAGGTT Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3080498","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":211458684,"identity":"20b55dd0-9c94-4455-8a64-4e5086e52e70","order_by":0,"name":"yuli guo","email":"","orcid":"","institution":"Inner Mongolia Agricultural University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"yuli","middleName":"","lastName":"guo","suffix":""},{"id":211458686,"identity":"d0ca18f6-77b0-4fd5-8d71-b37919627784","order_by":1,"name":"Junping Liu","email":"","orcid":"","institution":"Inner Mongolia Agricultural University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Junping","middleName":"","lastName":"Liu","suffix":""},{"id":211458687,"identity":"3d8ddb19-69ef-4e56-a752-9bde18e39e05","order_by":2,"name":"Shuangyi Zhang","email":"","orcid":"","institution":"Inner Mongolia Agricultural University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shuangyi","middleName":"","lastName":"Zhang","suffix":""},{"id":211458688,"identity":"15ff2e36-481e-42cd-a3aa-85ee00bd43a6","order_by":3,"name":"Di Sun","email":"","orcid":"","institution":"Inner Mongolia Agricultural University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Di","middleName":"","lastName":"Sun","suffix":""},{"id":211458689,"identity":"a12a4b05-2650-46ab-a41f-d2049185059d","order_by":4,"name":"Zhiying Dong","email":"","orcid":"","institution":"Inner Mongolia Agricultural University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhiying","middleName":"","lastName":"Dong","suffix":""},{"id":211458690,"identity":"aadaa6e5-3fff-4ee6-a42b-d95c8fdd9cc3","order_by":5,"name":"Jinshan Cao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAt0lEQVRIiWNgGAWjYBACfobzz39+MGCTI16LZOMZBmmJCj5j4rUYNJ9hkOA5I5fYQLwWtrMHDCTbzNL7jicwfviYQ4QWc55zCQmFbWm5M888YJacuY0ILZYzDhgckGw7lrvhRgIbMy8xWgzuPzBs4G37n25AvJYDZ4wZeM6wJRCvRbLhWBqzRAWb4cwzD5uJ8ws/w+FjjMColOc7nnzww0ditCDAARKiBqYlgVQdo2AUjIJRMFIAAKs2PGQ4jp6GAAAAAElFTkSuQmCC","orcid":"","institution":"Inner Mongolia Agricultural University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Jinshan","middleName":"","lastName":"Cao","suffix":""}],"badges":[],"createdAt":"2023-06-19 05:14:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3080498/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3080498/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":39123431,"identity":"05b33ef2-e421-4dba-904f-5a267bb868a9","added_by":"auto","created_at":"2023-06-26 21:36:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":34175,"visible":true,"origin":"","legend":"\u003cp\u003eChemical structure of Atractylenolide-I (AT-I).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3080498/v1/eb87a6b41f0d814ff37b108b.png"},{"id":39124286,"identity":"ce62695c-c7d6-4697-8d22-cf62ec84bb3a","added_by":"auto","created_at":"2023-06-26 21:44:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":878283,"visible":true,"origin":"","legend":"\u003cp\u003eMorphological observation and growth curve of the primary FOGCs. (A)The primary FOGCs attach to the substrate around the oocytes and begin to display an elongated or fibroblastic property within the first 24 h of culture. (B) Growth curve of cultivated cells within 48 h. (C) The HE staining of cultivated cells on substrate. (D) The Giemsa staining of cultivated cells on substrate. (E) Immunofluorescence of cultivated cells on substrate: FSHR (green) as the marker expressed in FOGCs, negative-control group and nuclei with DAPI staining (blue). Values are expressed as mean±S.D. (n=4). *,\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05; **,\u003cem\u003eP\u003c/em\u003e \u0026lt;0.01.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3080498/v1/11abf52ea7e9162dc84b7c0d.png"},{"id":39123438,"identity":"145990eb-2f0a-4807-9a85-78a5f8683982","added_by":"auto","created_at":"2023-06-26 21:36:33","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":672897,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of AT-I on the FOGCs. (A) Treatment with AT-I in 1, 3, 10 and 30 µmol/L could effectively promote FOGCs proliferation from 12 h to 48 h ;100 µmol/L significantly increased FOGCs proliferation after 36 h and the increased effect of 300 µmol/L happened at 48 h (P\u0026lt;0.05). (B) After 10umol/L AT-I treated 36 hours, the density of granulosa cells increased, cell viability increased significantly. Values are expressed as mean±S.D. (n=4). *,P \u0026lt; 0.05; **,P \u0026lt;0.01; ns, not statistically significant.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3080498/v1/9bc560cad808c2581d64bfca.png"},{"id":39123435,"identity":"31490ed7-5049-4c9c-b542-50cac73375a6","added_by":"auto","created_at":"2023-06-26 21:36:33","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":55971,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of 10 umol/L AT-I on the synthesis of E\u003csub\u003e2\u003c/sub\u003e and P\u003csub\u003e4\u003c/sub\u003e in FOGCs. (A) AT-I could significantly promote the E\u003csub\u003e2\u003c/sub\u003e secretion in FOGCs at 24 h and 36 h, while the increased tendency weakened at 48 h. (B) The P\u003csub\u003e4\u003c/sub\u003e concentration significantly increased by AT-I treatment from 12 h to 48 h. (C) The ratio of P\u003csub\u003e4\u003c/sub\u003e/E\u003csub\u003e2\u003c/sub\u003e indicated that the E\u003csub\u003e2\u003c/sub\u003e secretion was more obviously than P\u003csub\u003e4\u003c/sub\u003e secretion in FOGCs within 36 h after AT-I treatment. However, the secretion pattern of E\u003csub\u003e2\u003c/sub\u003e and P\u003csub\u003e4\u003c/sub\u003e changed at 48 h, in which the FOGCs secret P\u003csub\u003e4\u003c/sub\u003e more obviously than that E\u003csub\u003e2\u003c/sub\u003e secretion. Values are expressed as mean±S.D. (n=3). *,\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; **,\u003cem\u003eP\u003c/em\u003e \u0026lt;0.01; ns, not statistically significant.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3080498/v1/00a115f3460809fdeece644f.png"},{"id":39124285,"identity":"d2084b8e-3451-4f8a-b6dd-e459d89009ca","added_by":"auto","created_at":"2023-06-26 21:44:33","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":108108,"visible":true,"origin":"","legend":"\u003cp\u003eVolcano graph of 137 differentially expressed genes between two groups. Red represents upregulated DEGs; blue represents downregulated DEGs.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-3080498/v1/05093c7b41cb7342271803aa.png"},{"id":39123432,"identity":"e9a95abb-b43a-4848-ae1f-e188dd955648","added_by":"auto","created_at":"2023-06-26 21:36:33","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":126812,"visible":true,"origin":"","legend":"\u003cp\u003eGO classifications of genes in FOGCs. The abscissa is the GO classification, and the ordinate is the number of genes in each category.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-3080498/v1/d643faced40ed56b90956277.png"},{"id":39123433,"identity":"33a9e50a-b102-49ae-ac9c-f4d5ded4b55b","added_by":"auto","created_at":"2023-06-26 21:36:33","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":176056,"visible":true,"origin":"","legend":"\u003cp\u003eKEGG pathway classification of genes in FOGCs. The abscissa is the name of the KEGG metabolic pathway, and the ordinate is the ratio of the number of genes annotated to the pathway and the number of genes in the annotated genes.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-3080498/v1/ac58110ed3277caa4b09b11c.png"},{"id":39123437,"identity":"93fb21e1-7723-4fe5-aec1-5f3ba123997d","added_by":"auto","created_at":"2023-06-26 21:36:33","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":153947,"visible":true,"origin":"","legend":"\u003cp\u003eThe significantly enriched KEGG pathway of DEGs. Rich factor, number of differentially expressed genes/total number of genes in this KEGG pathway. The larger the value, the greater the enrichment.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-3080498/v1/172bd9512e5e7fee9976e44d.png"},{"id":39124287,"identity":"372cc156-89fc-4bf4-952a-646595f1f59e","added_by":"auto","created_at":"2023-06-26 21:44:34","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":75874,"visible":true,"origin":"","legend":"\u003cp\u003eVerification of transcriptome results (A) Relative quantification of DEGs by RT-qPCR. The expression of each gene was normalized to the average expression of the endogenous reference gene GAPDH. (B) Biochemical verification. After AT-I treatment, the contents of total cholesterol and LDL-cholesterol both declined. The values are expressed as mean±S.D. (n=3). *\u003cem\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/em\u003e \u0026lt; 0.05; **\u003cem\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/em\u003e\u0026lt;0.01; ns, not statistically significant.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-3080498/v1/30857fbbdbdad952e37fd93c.png"},{"id":46972610,"identity":"e03c71ae-94ff-495d-8e5a-d1ac58b6adad","added_by":"auto","created_at":"2023-11-23 12:08:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2723174,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3080498/v1/7f1aef56-4c5d-4b66-a7e5-c8e29f970542.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A transcriptome approach evaluating the effects of Atractylenolide Ⅰ on the secretion of estradiol and progesterone in feline ovarian granulosa cell","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e \u003cem\u003eAtractylodes macrocephala Koidz\u003c/em\u003e (AMK) has been commonly used in the clinical prescription for preserving fetuses, and their fetal safety effects have been confirmed by thousands of years of medical practice in traditional Chinese medicine (Zhu et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). As one of the major bioactive components in AMK, \u003cem\u003eAtractylenolide I\u003c/em\u003e (AT-I) is a naturally occurring sesquiterpene lactone has been found to display a wide range of pharmacological and biological activities such as anti-atherosclerotic and the treatment of various inflammatory illness, etc (G. Ji, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Long et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Song et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Progesterone (P4) has a variety of physiological functions, such as promoting endometrial decidualization,establishing maternal-fetal immune tolerance,inhibiting inflammatory response, and improving uterine-placental circulation, which are prerequisites for the maintenance of pregnancy (Mesen and Young, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Nardo and Sallam, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Insufficient secretion of P\u003csub\u003e4\u003c/sub\u003e affects endometrial secretion, thereby affecting embryo implantation and development. In early embryonic development, P\u003csub\u003e4\u003c/sub\u003e mainly comes from luteal granulosa cells, so the activity of granulosa cells plays a very important role in corpus luteum (CL) development and early pregnancy maintenance (Niswender et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Maintaining a certain concentration of estradiol (E\u003csub\u003e2\u003c/sub\u003e) can increase the uterine placental blood flow and increase the sensitivity of the uterus to P\u003csub\u003e4\u003c/sub\u003e (Braun et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).E\u003csub\u003e2\u003c/sub\u003e plays a role in the endometrium mainly through its homologous nuclear receptors ESR1 and ESR2, and participates in the decidualization process of the endometrium through the ERK/MAPK pathway (Braun et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Studies have shown that if the E\u003csub\u003e2\u003c/sub\u003e content is too low, it would lead to embryo implantation failure (Vannuccini et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Therefore, determining the effect of AT-I on the secretion of E\u003csub\u003e2\u003c/sub\u003e and P\u003csub\u003e4\u003c/sub\u003e in feline ovarian granulosa cells (FOGCs) might contribute to our understanding of the protection of AMK in early pregnancy.\u003c/p\u003e \u003cp\u003eIn recent years, the high-throughput RNA sequencing technique (RNA-seq) has emerged as a powerful tool for transcriptome analysis (Guo-Liang Zhang, 2017). By using this method, it might help to assess the changes of the transcriptome in FOGCs upon treatment with AT-I at the whole genome scale, contributing to explain the mechanism of how AT-I regulates the changes of FOGCs.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 AT-I structure\u003c/h2\u003e \u003cp\u003eAT-I (CAS No. 73069-13-with purity\u0026thinsp;\u0026ge;\u0026thinsp;98%) used in this study were purchased from Dalian Meilune Biotechnology Co. Ltd. (Liaoning, China). The chemical structure of the AT-I has been depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Culture of primary feline ovarian granulosa cells\u003c/h2\u003e \u003cp\u003eFOGCs were obtained from fresh ovarian tissues of healthy and diestrus period felines between six months and two years old, which were under sterilization operation in the animal hospital of Inner Mongolia Agricultural University. The feline ovarian tissues were maintained in a vacuum thermos flask containing sterile physiological saline and transported to the laboratory within 2 h. The ovarian tissues were washed several times with 37 ℃ DPBS solution (Gibco, MA, USA), contained 3% penicillin and streptomycin (Gibco, MA, USA,) until the tissues completely clean. The tissues were then transferred to a 300 mm diameter plate with 0.5 mL of 12% fetal calf serum-supplemented Ham\u0026rsquo;s F-12 nutrient mixture (DMEM/F12, Gibco, MA, USA). Thereafter, the follicular fluid and cumulus-oocyte complexes (COCs) from primary follicles between 1 and 1.5 mm in diameter were aspirated by using a 2.5 mL aseptic syringe. Collected cells were transferred to a 1mL centrifuge tube and centrifuged at 1500 rpm for 3 min, then sediment was harvested and washed with DPBS solution. This process was repeated three times. Afterward, the isolated FOGCs were transferred in DMEM/F12 medium containing 12% fetal bovine serum (Excell Biology, Shanghai, China), 1% streptomycin and penicillin, and cultivated in a 5% CO\u003csub\u003e2\u003c/sub\u003e incubator at 37\u0026deg;C. Cell growth and morphological characteristics were observed with inverted microscope (Philips, Tokyo, Japan). After 72 h, the oocytes were washed out with DPBS, and the granulosa cells were isolated. Then, the medium was renewed routinely every other day until the cell density reached 75\u0026ndash;80%, then digested with 0.25% trypsin-EDTA (Gibco, MA, USA) of 1mL for 2 min, and the digestion was terminated with the DMEM/F12 culture medium containing 12% serum. After fully mixing, inoculated at a split ratio of 1:2 for subsequent cultivation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Morphological observations\u003c/h2\u003e \u003cp\u003eThe FOGCs at the logarithmic growth phase were seeded 100 \u0026micro;L at a density of 1 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells/mL on the autoclaved slides, thereafter the slides were stored in an autoclaved wet box that was placed in a 37\u0026deg;C, 5% CO\u003csub\u003e2\u003c/sub\u003e incubator for 24 h. After reaching 70% confluence, washed three times with DPBS and the cells were fixed for 20 min with cold acetone. The processed slides were then stained with two different staining methods: hematoxylin-eosin (HE) and Wright-Giemsa, photographed and analyzed by using a light microscope (ECLIPSE TS100-F. Nikon, Tokyo, Japan).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Immunofluorescence identification\u003c/h2\u003e \u003cp\u003eTo analyze the identity and purity of isolated FOGCs, immunofluorescence staining for a specific marker of ovarian granulosa cells was performed by FSHR (follicle stimulating hormone receptor). Seeded the logarithmic growth phase FOGCs 0.5 mL at a density of 1 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells/mL into 35 mm glass-bottom dishes (Shengyou Biotechnology, Hangzhou, China). After the cells reached 80% confluence, washed three times with aseptic DPBS solution, fixed for 30 min with 4% paraformaldehyde (Solarbio, Beijing, China) at room temperature, and washed three times with DPBS. After fixation, the FOGCs were incubated with 1mL 0.25% Triton X-100 (PH=7.40, Sigma-Aldrich, MO, USA) for 20 min, then washed three times with DPBS. After blocking for non-specific binding sites, the cells were stained with primary antibody to FSHR (1:200, Rabbit Anti-FSH receptor antibody; BS-0895R; Bioss; Beijing, China) overnight at 4\u0026deg;C. The granulosa cells were washed three times in DPBS and incubated with a secondary antibody (Alx647; donkey-anti-rabbit IgG; Jackson, Pennsylvania, USA) for 2 h at room temperature in the dark. After incubation, the cells were washed three times for 10 min with DPBS in the dark. Then with DAPI stained the nuclei, washed on the decolorizing shaker 4 times for 10 min. Observed glass-bottom dishes under an LSM 800 (Zeiss, Jena, Germany) laser confocal system.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Cell viability assay\u003c/h2\u003e \u003cp\u003eThe cell viability was assessed using Cell Counting Kit-8 assays (CCK-8; BS350B; Biosharp; Shanghai, China). The second-generation feline ovary granule cells were used, washed with DPBS, and 1mL of 0.25% trypsin\u0026ndash;EDTA was added to digest them for 2 min. Thereafter, DMEM/F12 medium containing 12% fetal bovine serum (Excell Biology, Shanghai, China) was added to stop the digestion. The pipetting was repeated to ensure that the cells are away from the wall and uniformly distributed. After digestion, the cell suspension concentration was adjusted to 2\u0026times;10\u003csup\u003e6\u003c/sup\u003e cells/mL. Thereafter, a 96-well cell culture plate was taken, 100 \u0026micro;L of culture medium with cells was added to each well, and the plate was incubated for 12 h. Thereafter, 100 \u0026micro;L DPBS was added to the remaining wells to reduce evaporation. The cells in the plate were purified for 6 h (with the serum-free medium), the cell supernatant was purged after purification, and 100 \u0026micro;L medium (containing 12% serum) was added. The plate was cultivated for 6 h, 12 h, 24 h, 36 h, and 48 h, then CCK-8 was added for 4 h. After then, the absorbance value (OD value) of each well was measured with a microplate reader at a wavelength of 450 nm.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Cytotoxicity of AT-Ⅰ against primary feline ovarian granulosa cells\u003c/h2\u003e \u003cp\u003eAfter the FOGCs purified as described above, 100 \u0026micro;L medium (containing 12% serum) with different AT-I concentrations (0 \u0026micro;mol/L, 1 \u0026micro;mol/L, 3 \u0026micro;mol/L, 10 \u0026micro;mol/L, 30 \u0026micro;mol/L, 100 \u0026micro;mol/L, 300 \u0026micro;mol/L) was added to the plate and incubated at 37℃ for 0 h,12 h, 24 h, 36 h and 48 h, CCK-8 was added for 4 h and the absorbance value of each well was measured with a microplate reader at a wavelength of 450 nm to measure the cytotoxicity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Determination of estradiol (E\u003csub\u003e2\u003c/sub\u003e) and progesterone (P\u003csub\u003e4\u003c/sub\u003e) concentration\u003c/h2\u003e \u003cp\u003eFOGCs were seeded at a density of 2\u0026times;10\u003csup\u003e6\u003c/sup\u003e cells/mL in 6-well cell culture plates and cultivated at 5% CO\u003csub\u003e2\u003c/sub\u003e and 37\u0026deg;C until 70% of the cells were fused. The cell culture supernatant was then removed and 2 mL of fresh DMEM/F12 medium containing 10 \u0026micro;mol/L AT-I was added to the FOGCs monolayer for co-culturing at 37\u0026deg;C with 5% CO\u003csub\u003e2\u003c/sub\u003e. After incubation for 0 h, 12 h, 24 h, 36 h and 48 h respectively, the supernatant was aspirated and used for subsequent experiments. The control cells were treated with DMEM/F12 medium with the same time condition. Three different biological replicates were designed for both the treatment and control experiments.\u003c/p\u003e \u003cp\u003eThe concentrations of E\u003csub\u003e2\u003c/sub\u003e in the culture medium were measured by enzyme-linked immunosorbent assay (Wuhan Xinqidi Biological Technology; Wuhan, China) according to the manufacturer\u0026rsquo;s instructions. The estradiol standard curve ranged from 0 to 1000 pg/mL. The samples were analyzed in triplicates. The assay sensitivity, range, and intra-assay coefficient of variation were 5 pg/mL, 15.6\u0026ndash;1000 pg/mL, and \u0026le;\u0026thinsp;8%, respectively. The concentrations of P\u003csub\u003e4\u003c/sub\u003e in the culture medium were measured by enzyme-linked immunosorbent assay (Wuhan Xinqidi Biological Technology; Wuhan, China) according to the manufacturer\u0026rsquo;s instructions. The progesterone standard curve ranged from 0 to 100 ng/mL. The samples were analyzed in triplicates. The assay sensitivity, range, and intra-assay coefficient of variation were 0.5 ng/mL, 1.56\u0026ndash;100 ng/mL, and \u0026le;\u0026thinsp;8%, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 AT-I treatment\u003c/h2\u003e \u003cp\u003eAccording to the above experiments, we selected the 10 \u0026micro;mol/L AT-I and incubated it for 36 h for the next study. FOGCs were seeded at a density of 2 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells/mL in 6-well cell culture plates and cultivated at 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e until they reached 70% confluence. The cell culture supernatant was thereafter removed and 2 mL of fresh DMEM/F12 medium containing 10 \u0026micro;mol/L AT-I was added to the FOGCs monolayer and the plate was incubated for 36 h at 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e. After AT-I treatment, FOGCs were photographed and analyzed for potential morphological changes using an inverted microscope (Philips, Tokyo, Japan). The supernatant was aspirated and used for subsequent experiments. Thereafter, FOGCs were gently washed three times with DPBS to remove the remaining drug, collected the cells for transcription analysis. The control cells were treated with DMEM/F12 medium only. Three biological replicates were tested for the treatment and control experiments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9 RNA library construction and sequencing\u003c/h2\u003e \u003cp\u003eTotal RNA from untreated and AT-I treated FOGCs was extracted according to the instructions of the Axygen-RNA extraction kit (AxyGen, CA, USA), and there were three biological repeats in each group. Bioanalyzer 2100 and RNA 6000 Nano LabChip Kit (Agilent, CA, USA) were thereafter used to analyze the quantity and purity of total RNA, yielding RIN scores\u003e8.0, in accordance with the testing standard. Magnetic beads connected with Oligo were used to enrich and purify eukaryotic mRNA with poly-A tail. The extracted eukaryotic mRNA was randomly broken into short fragments by the fragmentation reagent (Fragmentation Buffer). Using the fragmented mRNA as the template, one-strand cDNA was synthesized by a six-base random primer (Random hexamers), and then the buffer, dNTPs, RNaseH, and DNA Polymerase I was added to synthesize the two-strand cDNA. The cDNA double-stranded product was purified by AMPureXP beads. The viscous end of DNA was repaired to a flat end by T4 DNA polymerase and Klenow DNA polymerase, and the 3 'end was selected by adding base An and splice, AMPureXP beads. Finally, the final sequencing library was obtained by PCR amplification. After passing the quality inspection of the library, the library was sequenced with Illumina Hiseq 4000 to produce 150 bp double-terminal data. The cDNA library was sequenced on an Illumina HiSeq 4000 sequencing platform (Illumina, San Diego, USA) provided by Majorbio Bio-pharm Technology Co., Ltd (Shanghai, China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.10 Statistical analysis of transcription data\u003c/h2\u003e \u003cp\u003eThe raw RNA-seq data was then filtered to remove various adaptor contamination, low-quality bases, and undetermined bases utilizing Cutadapt software (Maher et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The sequencing quality was verified using FASTQC software including the Q20, Q30, and GC content of the clean data. All downstream analysis was based on clean as well as high-quality data. The filtered reads were aligned and mapped to the reference genome using Hisat 2.0. The aligned read files were processed by Cufflinks (Martin M, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), which uses the normalized RNA-seq fragment counts to measure the relative abundances of the different transcripts. The unit of measurement is fragments per kilobases of exon per million fragments mapped (FPKM). The DEGs were screened using R package edger (Love M I, 2014) with fold change (FC)\u0026thinsp;\u0026ge;\u0026thinsp;1.5 and \u003cem\u003eP-adjust\u003c/em\u003e\u003c0.05, which were considered significantly different expressed (Anders and Huber, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The DEGs underwent enrichment analysis using GO and KEGG. \u003cem\u003eP\u003c/em\u003e values were calculated using the Benjamini-corrected modified Fisher exact test, and \u003cem\u003eP\u003c/em\u003e\u003c0.05 was deemed statistically significant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.11 Validation by quantitative reverse transcription PCR\u003c/h2\u003e \u003cp\u003eQuantitative reverse transcription PCR (RT-qPCR) was utilized to validate the DEGs identified by RNA-seq.\u0026nbsp;The total RNA concentration of all samples was adjusted to 300 ng/\u0026micro;L at the same time, and cDNA was used as starting material for real-time PCR with FastStart Universal SYBR Green Master (Roche, Mannheim, Germany) on an iQ5 multicolor real-time PCR detection system (Bio-Rad, CA, USA). Eight DEGs were chosen based on changes in their expression levels in the treated cells as compared with the control cells. Eight DEGs were selected with cDNA as template and the glyceraldehyde 3-phosphate dehydrogenase (\u003cem\u003eGAPDH\u003c/em\u003e) gene was used as the internal control. The sequence of primers is shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The RT-qPCR reaction conditions are as follows: 5 min pre-incubation at 95\u0026deg;C; 40 cycles of amplification for 5 s at 95\u0026deg;C for denaturation, 34 s at 60\u0026deg;C for annealing, and 20 s at 72\u0026deg;C for elongation. Negative controls (without cDNA) were run in the same reaction set. The relative mRNA expression of DEGs in each group was calculated by the 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e formula (Kanehisa et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.12 Biochemical verification\u003c/h2\u003e \u003cp\u003eAfter 10 \u0026micro;mol/L AT-I treatment for 36 h, the supernatant was collected for biochemical testing (lnc.BS-180vet blood biochemical analyzer; Abaxis, USA). Three biological replicates were used for the treatment and control experiments. The contents of total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) in the supernatant were detected to explore the possible effect of AT-I on lipid metabolism.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e2.13 Statistical analysis\u003c/h2\u003e \u003cp\u003eThe experimental data were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. The difference between the two groups was analyzed using the T-test and One-way ANOVA. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered significant with *, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and **, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Identification of cultured feline ovarian granulosa cells\u003c/h2\u003e \u003cp\u003eThe cells nearby the oocytes begun to display an elongated or fibroblastic property within the first 36 h \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. The cells were then distinguished by the presence of a triangle cone or irregular star-shaped morphology. After 3 days of culture, large number of cells was observed around oocytes in clusters. The cells confluence reached 75 to 80% on day 7. The sub-cultured cells began to adhere after 4 h, the cell could reached to 80% confluence on day 3. The similar phenomenon happed on passages 3 and 4 with classic irregular star-shaped morphology.\u003c/p\u003e \u003cp\u003eBy HE staining, the structure of cells was confirmed to be contact by which the edge was clear and a triangle cone or irregular star shape. The cytoplasm was pink, and the nuclei were dyed in blue \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. By Giemsa staining, the structure of cells also presented contact by which the edge was clear and a triangle cone or irregular star shape. The cytoplasm was blue-violet and the nuclei were pink \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eThe FSHR was expressed in the cytoplasm of triangle cone-like cells by immunofluorescence staining, while FSHR was not observed in control group (without primary antibody) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE\u003cb\u003e)\u003c/b\u003e, confirming that FOGCs were cultivated successfully and the purity could reach 90%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Cell viability assay\u003c/h2\u003e \u003cp\u003eThe cell growth curve detected by CCK-8 assay \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e showed that cell proliferation significantly happened after 12 h until 48 h (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating that the way of cultivated FGOCs growth consist with that in normal cell growth.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Cytotoxicity of AT- Ⅰ on the primary FOGCs\u003c/h2\u003e \u003cp\u003eAT-I treatment in a concentration range (0 \u0026micro;mol/L-300 \u0026micro;mol/L) showed that 1, 3, 10 and 30 \u0026micro;mol/L could effectively promote FOGCs proliferation from 12 h to 48 h \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. 100 \u0026micro;mol/L significantly increased FOGCs proliferation after 36 h and the increased effect of 300 \u0026micro;mol/L happened at 48 h (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. In addition, under the microscope, the increased density of granulosa cells by 10 \u0026micro;mol/L AT-I treatment for 36 h was clearly observed as well \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. These results indicated that the 10 \u0026micro;mol/L AT-I could enhance the viability at 36 h most obviously among selected concentration and time points indicating 10 \u0026micro;mol/L could be used as the experimental concentration for following experiment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.4 The effect of AT-I on the synthesis of E\u003csub\u003e2\u003c/sub\u003e and P\u003csub\u003e4\u003c/sub\u003e in FOGCs\u003c/h2\u003e \u003cp\u003e10 \u0026micro;mol/L AT-I could significantly promote the E\u003csub\u003e2\u003c/sub\u003e secretion in FOGCs at 24 h and 36 h, while the increased tendency weakened at 48 h \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. The P\u003csub\u003e4\u003c/sub\u003e concentration significantly increased by AT-I treatment from 12 h to 48 h \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. Although the secretion of E\u003csub\u003e2\u003c/sub\u003e and P\u003csub\u003e4\u003c/sub\u003e was both increased, the ratio of P\u003csub\u003e4\u003c/sub\u003e/E\u003csub\u003e2\u003c/sub\u003e indicated that the E\u003csub\u003e2\u003c/sub\u003e secretion was more obviously than P\u003csub\u003e4\u003c/sub\u003e secretion in FOGCs within 36 h after AT-I treatment. However, the secretion pattern of E\u003csub\u003e2\u003c/sub\u003e and P\u003csub\u003e4\u003c/sub\u003e changed at 48 h, in which the FOGCs secret P\u003csub\u003e4\u003c/sub\u003e more obviously than that E\u003csub\u003e2\u003c/sub\u003e secretion\u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Classification of transcriptional sequencing data\u003c/h2\u003e \u003cp\u003eTo evaluate the transcriptional response of the FOGCs to AT-Ⅰ exposure and decipher the various host factors, which may be involved in the luteinization, the Illumina HiSeq 4000 platform with cDNA libraries of FOGCs treated with AT-Ⅰ were used. The sequencing quality data are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the two libraries produced 58,841,865 and 52,950,059 original sequences (Raw Data), respectively, from both the treated and control FOGC groups. After filtering, the effective date of 58,189,124 and 52,340,848 was obtained. The proportion of data quality Q20 (sequencing base mass) of the two databases is more than 98%, which meets the needs of follow-up test analysis. All the valid reads were aligned to the feline genome using Hisat 2.0. Furthermore, 56,730,426 and 51,014,192 Map Reads were obtained from the different groups of treated and control FOGCs, in which the number of Reads with unique alignment position in the genome and meeting the needs of subsequent experimental analysis were 53,563,083 and 48,058,826 respectively, and the ratio of alignment to genome sequence was 92.06% and 91.82%, respectively. The results show that the sequencing data are of high quality and meet the needs of further analysis.\u003c/p\u003e \u003cp\u003eThe sequencing data have been saved in the NCBI gene expression comprehensive database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ncbi.nlm.nih.gov/geo/info/linking.html\u003c/span\u003e\u003cspan address=\"http://www.ncbi.nlm.nih.gov/geo/info/linking.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and can be obtained by GEO Series accession number GSE155784.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Analysis of differentially expressed genes\u003c/h2\u003e \u003cp\u003eFOGCs treated with the AT-Ⅰ showed a relative degree of differential expression. A total of 137 DEGs were obtained (\u0026ge;\u0026thinsp;1.5-Fold Change, \u003cem\u003eP-adjust\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), of which 49 DEGs were significantly up-regulated and 88 DEGs were significantly down-regulated. The overall distribution of DEGs can be understood by drawing a volcanic map. \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e3.7 Functional enrichment analysis of differentially expressed gene\u003c/h2\u003e \u003cp\u003eThe RNA-seq analysis revealed a total of 17 265 genes, of which 137 genes were significant differences in expression. To assess the biological functions of the 137 DEGs, enrichment analysis of GO classification (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.geneontology.org/\u003c/span\u003e\u003cspan address=\"http://www.geneontology.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and the KEGG pathway (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.genome.jp/kegg\u003c/span\u003e\u003cspan address=\"http://www.genome.jp/kegg\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was systematically performed. The annotated results of the GO database in the sequencing are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e6\u003c/span\u003e. The histogram of GO enrichment analysis is mainly reflected in biological processes, cellular components, and molecular functions. In biological processes, 644 DEGs are assigned to the regulation of biological processes, such as cellular processes, single-organism process, biological regulation, regulation of biological process development, and metabolic processes. In the cell component field, 308 DEGs belong to the the cell, the cell part, and membrane. In the molecular functional class, 93 DEGs resins can be used for binding and catalytic activity.\u003c/p\u003e \u003cp\u003eKEGG analysis showed that the DEGs were mainly involved in the regulation of the various signal transduction pathways, signaling molecules and their possible interactions, membrane transport, lipid metabolism, endocrine system, as well as digestive system \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e7\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The DEGs successfully annotated 155 signal pathways, and 23 signal pathways were significantly different (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Relatively high numbers of different genes were involved in the regulation of cholesterol metabolism, ovarian steroidogenesis, rheumatoid arthritis, biosynthesis of unsaturated fatty acids, steroid hormone biosynthesis, AMPK signaling pathway, ABC transporters, and other signaling pathways \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e8\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eDEGs were analyzed with KEGG to predict and study the signal pathways that are mainly involved and most interested, and to obtain those pathways that may be related to the luteinizing effect of AT-I. In the various pathways associated with the response of the FOGCs treated with AT-I, 9 DEGs were found to be significantly affected \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Among the DEGs, three genes (\u003cem\u003eABCA1\u003c/em\u003e, \u003cem\u003eLDLR\u003c/em\u003e, and \u003cem\u003eSREBF1\u003c/em\u003e) were found to be upregulated and involved in the regulation of the cholesterol metabolism, cholesterol metabolism is a complex biological process and most of the other DEGs identified were also found to actively participate in this process. Three genes (\u003cem\u003eStAR, LDLR\u003c/em\u003e and \u003cem\u003eCYP1A1\u003c/em\u003e) have been implicated in the regulation of ovarian steroidogenesis. Two genes (\u003cem\u003eSCD\u003c/em\u003e, and \u003cem\u003eFADS2\u003c/em\u003e) were upregulated and were found to be involved in the biosynthesis of unsaturated fatty acids. Two genes (\u003cem\u003eABCG1\u003c/em\u003e, and \u003cem\u003eABCA1\u003c/em\u003e) were upregulated and participated in ABC transporters, and the two DEGs (\u003cem\u003eSREBF1\u003c/em\u003e, and \u003cem\u003eSCD\u003c/em\u003e) were observed to be upregulated and could participate in the regulation of the AMPK signaling pathway.\u003c/p\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e3.8 Validation of the selected Genes by quantitative reverse transcription PCR and Biochemical analysis\u003c/h2\u003e \u003cp\u003eTo validate the results of RNA-seq analysis, RT-qPCR was used to examine the various DEGs. All DEGs have the same trend of changes with RNA-seq data. Thereby suggesting that the RNA-seq data reliably reflected the changes in the trends of gene expression \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e9\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eTo verify whether AT-I can promote the metabolism of cholesterol, the biochemical analysis of the supernatants of granulosa cells treated with AT-I was carried out. It was found that the contents of the total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) in the treated group with AT-I were significantly lower than those in the control group \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e9\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eAT-I has been found to be the the major bioactive component from AMK, which is a medicinal plant that has been used as a pharmacological agent for the treatment of threatened miscarriages for a long time (Zhu et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). CL is an essential organ for maintain the early pregnancy, and luteal dysfunction could cause infertility and abortions (Mesen and Young, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The CL is mainly composed of large luteum cells (LLC) and little amount of small luteum cells (SLC). LLC, which has the stronger steroidogenic capacity than that in SLC, mainly originates from ovarian granulosa cells (Hryciuk et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). As the major bioactive compent of AMK, the effect of AT-I on the ovarian granulosa cells might contribute to our understanding on how AMK treatment of threatened miscarriages. This study found that AT-I could promote proliferation and the secretion of E\u003csub\u003e2\u003c/sub\u003e and P\u003csub\u003e4\u003c/sub\u003e in FOGCs. And the transcriptome profile of differential gene expression in FOGCs treated with the AT-I was examined in this report.\u003c/p\u003e \u003cp\u003eOvarian granulosa cells as the largest cell group within the follicles, they not only cooperate with theca interstitial cells to regulate the synthesis of female steroid hormones, and also can regulate both the growth and maturation of oocytes (Havelock et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). At present, there is only one method to culture primary FOGCs by slicing ovaries into many pieces (Chiara Perego et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), but the cell identification was not carried out and the fibroblasts, endothelial cells could not effectively removed. In this study, a new method by puncturing small folliclesto to cultivate primary FOGCs and confirmed with FSHR immunofluorescence identification, the FOGCs purity could reach 90% which could be used to perform relative experiment.\u003c/p\u003e \u003cp\u003eAfter ovulation, ovarian granulosa cells proliferation and transformed to LLC that can have the ability to secrete amount of P\u003csub\u003e4\u003c/sub\u003e and maintain early pregnancy (Luigi Devoto, 2009 ) (Richards and Pangas, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e); Amelkina et al. revealed that ovarian granulosa cells could be transformed to LLC that can have the ability to secrete steroids in domestic cat (Amelkina et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In this study, the FOGCs viability was noticed to increase significantly in a dose and time-dependent within a certain range \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e and the secretion of E\u003csub\u003e2\u003c/sub\u003e and P\u003csub\u003e4\u003c/sub\u003e increased significantly \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e after AT-I treatment in FOGCs. The increase of E2 and P4 might due to cell proliferation or enhanced single cell secretion or combined effect, which needs further investigation.\u003c/p\u003e \u003cp\u003eRecent evidence obtained with a luteal cell line has confirmed that E\u003csub\u003e2\u003c/sub\u003e can positively regulate the transcriptional activity of the \u003cem\u003eSR-BI\u003c/em\u003e gene to speed up the occurrence of the luteinization process (Stocco, 2007). In our study, after AT-I-stimulation, E\u003csub\u003e2\u003c/sub\u003e concentration was observed to increase in 36 h, and after AT-I treatment 36 h, FOGCs can produce a substantial amount of P\u003csub\u003e4\u003c/sub\u003e instead of E\u003csub\u003e2\u003c/sub\u003e that they did before and the ratio of P\u003csub\u003e4\u003c/sub\u003e/E\u003csub\u003e2\u003c/sub\u003e indicated that the P\u003csub\u003e4\u003c/sub\u003e secretion was more obviously than E\u003csub\u003e2\u003c/sub\u003e secretion in FOGCs after 36 h indicating that the AT-I might initiate luteinization process, which resulted in the enhanced P\u003csub\u003e4\u003c/sub\u003e secretion in FOGCs .\u003c/p\u003e \u003cp\u003eIn this study, a total of 137 DEGs were obtained after transcriptome sequencing on the FOGCs group treated with AT-I and these results were confirmed by RT-qPCR. According to the GO classification and KEGG pathway enrichment analysis, it was found that the DEGs were mainly enriched in several important pathways including those regulating cholesterol metabolism, ovarian steroidogenesis, biosynthesis of unsaturated fatty acids and ABC transporter.\u003c/p\u003e \u003cp\u003eThe unsaturated fatty acids are able to reduce the harmful cholesterol and triglyceride in the blood by esterifying cholesterol and promote cholesterol metabolism effectively control the concentration of blood lipids, and increase the content of high-density lipoprotein (HDL) which is beneficial to the human body (Wiktorowska-Owczarek et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The DEGs \u003cem\u003eSCD\u003c/em\u003e, a central regulator controlling the biosynthesis of unsaturated fatty acids (AM et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) was up-regulated by AT-I which might contribute to the secretion of E\u003csub\u003e2\u003c/sub\u003e and P\u003csub\u003e4\u003c/sub\u003e through regulate the biosynthesis of unsaturated fatty acid.\u003c/p\u003e \u003cp\u003eThe cholesterol metabolism is critical for the production of the various essential membrane components which is necessary for cell proliferation (Miranda-Jimenez and Murphy, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). In addition, as a precursor of steroid hormones, cholesterol is pivotal for ovarian follicular maturation (Shimano and Sato, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Interestingly, in this study, it was found that the DEGs after AT-I treated mainly related to cholesterol metabolism. A constant supply of cholesterol is needed for the synthesis of steroid hormones in the CL and maternal cholesterol metabolism plays a role in fetal development (Woollett, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Circulating plasma lipoproteins are the major source of cholesterol for steroid production in these different cells and cholesterol can be mainly obtained from circulating low-density lipoproteins (LDL) and small part from high-density lipoprotein (HDL) (Li et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Miranda-Jimenez and Murphy, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). There are multiple systems involved in the cellular cholesterol delivery for steroidogenesis, mainly through the uptake of lipoprotein-derived cholesterol via LDLR mediated endocytic pathways (Craig et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). According to the RNA-seq analysis and RT-qPCR result, the expression of \u003cem\u003eLDLR\u003c/em\u003e was induced by AT-I treatment in FOGCs, indicating the uptake of lipoprotein-derived cholesterol might be activated which could further stimulate the cholesterol biosynthesis.The identified DEGs \u003cem\u003eSREBF1\u003c/em\u003e that responsible for encoding sterol regulatory element-binding protein (SREBP) able to promote the transcription of various lipogenesis involved in the biosynthesis of fatty acids and cholesterols and involved in the regulation of sterol synthesis rates (Richards and Pangas, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Woollett, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). It was reported that SREBP could up-regulated the LDLR expression promote the cholesterol uptake (Lindholm et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Shimano and Sato, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and regulate the luteinization process through enhance the sensitivity of Human Granulosa-Lutein Cells to LH (Li et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). After AT-I treatment, the \u003cem\u003eSREBF1\u003c/em\u003e expression was up-regulated than that in control group, suggesting the SREBF1 signaling pathway might be activated. The activation of SREBF1 signaling pathway by AT-I treatment might contribute to the FOGCs synthesis of steroid hormones.To further confirm the effect of AT-I on cholesterol metabolism, the biochemical test was used to detect the content of cholesterol in the cell supernatant. After AT-I treatment 36 h, the contents of total cholesterol and LDL cholesterol both declined, whereas the synthesis of steroid hormones increased, suggested that AT-I indeed significantly affect cholesterol metabolism and promote the secretion of E\u003csub\u003e2\u003c/sub\u003e and P\u003csub\u003e4\u003c/sub\u003e in FOGCs. Li et al showed that AT-I dose dependently inhibited Ox-LDL induced VSMCs proliferation to treat atherosclerosis (Li et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), which might be the result of increased LDLR expression.\u003c/p\u003e \u003cp\u003eThe ovaries are responsible for producing sex steroid hormones during reproductive life, which is important for both reproductive and somatic health (Richards and Pangas, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). After AT-I treatment, the secretion of E\u003csub\u003e2\u003c/sub\u003e and P\u003csub\u003e4\u003c/sub\u003e increased significantly in FOGCs. The \u003cem\u003eCYP1A1\u003c/em\u003e was down-regulated and thereby can reduce the degradation of E\u003csub\u003e2\u003c/sub\u003e to modulate ovarian steroidogenesis (Deok-Soo Son 1999). The identified DEGs \u003cem\u003eLDLR\u003c/em\u003e is also a key gene in ovarian steroidogenesis by promote the cholesterol biosynthesis. The DEGs \u003cem\u003eStAR\u003c/em\u003e can introduce cholesterol into mitochondria, which is essential for steroid production. Cholesterol is the major raw material for ovarian steroid hormone synthesis. According to this study, the expression of \u003cem\u003eLDLR,StAR\u003c/em\u003e and \u003cem\u003eSREBF1\u003c/em\u003e increased were induced by AT-I treatment in FOGCs, and the increased gene might further stimulate the cholesterol biosynthesis which leading ovarian steroidogenesis happened.\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eABCA-1\u003c/em\u003e and \u003cem\u003eABCG-1\u003c/em\u003e expression increased after AT-I treatment might improve the reverse cholesterol transport, and further speed up the metabolic process of cholesterol in FOGCs since ABC transport system can drive intracellular superfluous cholesterol from arterial wall macrophages to the liver, thus allowing its excretion into the bile and feces as to speed up the metabolic process of cholesterol (Iborra, 2011).\u003c/p\u003e \u003cp\u003eAT-I can promote the biosynthesis of unsaturated fatty acids to enhance the HDL content in plasma, and dramatically enhance the ability to transport LDL into cells by increased \u003cem\u003eLDLR\u003c/em\u003e expression; The intake cholesterol can be used as raw material for ovarian steroidogenesis incloud E\u003csub\u003e2\u003c/sub\u003e and P\u003csub\u003e4\u003c/sub\u003e. At the same time, AT-I can dynamically promote the reverse transport of cholesterol by up-regulating \u003cem\u003eABCA1\u003c/em\u003e and \u003cem\u003eABCG-1\u003c/em\u003e gene expression to speed up the metabolic process of cholesterol. Taken together, after AT-I treatment, the differential genes identified were mainly concentrate on cellular cholesterol uptake and efflux. Thus, it was hypothesized that AT-I might affect the secretion of E\u003csub\u003e2\u003c/sub\u003e and P\u003csub\u003e4\u003c/sub\u003e by promoting the cholesterol metabolism in the granulosa cells.\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThis study demonstrated that AT-I could promote cholesterol metabolism determined by RNA-seq and biochemical test in FOGCs. The effect of AT-I on cholesterol metabolism might help to explaining the AT-I induced the secretion of E\u003csub\u003e2\u003c/sub\u003e and P\u003csub\u003e4\u003c/sub\u003e in FOGCs. These results together will contribute to our understanding of the mechanism of early pregnancy protection by AMR.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAMK \u003cem\u003eAtractylodes macrocephala Koidz\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAT-I \u003cem\u003eatractylenolide I\u003c/em\u003e\u003c/p\u003e\u003cp\u003eFOGCs primary feline ovarian granulosa cells\u003c/p\u003e\u003cp\u003eRNA-seq transcriptome sequencing\u003c/p\u003e\u003cp\u003eCL corpus luteum\u003c/p\u003e\u003cp\u003eLLC large luteum cells\u003c/p\u003e\u003cp\u003eSLC small luteum cells\u003c/p\u003e\u003cp\u003eE\u003csub\u003e2\u003c/sub\u003e estradiol\u003c/p\u003e\u003cp\u003eP\u003csub\u003e4\u003c/sub\u003e progesterone\u003c/p\u003e\u003cp\u003eELISA enzyme linked immunosorbent assay\u003c/p\u003e\u003cp\u003eDEGs differentially expressed genes\u003c/p\u003e\u003cp\u003eGO Gene Ontology\u003c/p\u003e\u003cp\u003eKEGG Kyoto Encyclopedia of Genes and Genomes\u003c/p\u003e\u003cp\u003eFC fold change\u003c/p\u003e\u003cp\u003eFPKM fragmented per kilobases of exon per million fragments mapped\u003c/p\u003e\u003cp\u003eRIN RNA integrity number\u003c/p\u003e\u003cp\u003eRT-qPCR quantitative reverse transcription PCR\u003c/p\u003e\u003cp\u003eDPBS dulbecco\u0026rsquo;s phosphate-buffered saline\u003c/p\u003e\u003cp\u003eDMEM/F12 Ham\u0026rsquo;s F-12 nutrient mixture\u003c/p\u003e\u003cp\u003eCOCs cumulus-oocyte complexes\u003c/p\u003e\u003cp\u003eHE hematoxylin-eosin\u003c/p\u003e\u003cp\u003eFSHR follicle stimulating hormone receptor\u003c/p\u003e\u003cp\u003eDAPI 4,6-diamidino-2-phenylindole\u003c/p\u003e\u003cp\u003eCCK-8 cell counting kit 8\u003c/p\u003e\u003cp\u003eOD value optical density value\u003c/p\u003e\u003cp\u003eTC total cholesterol\u003c/p\u003e\u003cp\u003eLDL-C low density lipoprotein cholesterol\u003c/p\u003e\u003cp\u003eHDL-C high density lipoprotein cholesterol\u003c/p\u003e\u003cp\u003eSD standard deviation\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the\u0026nbsp;National key research and development plan \u0026quot;New technology for diagnosis, treatment, and prevention of pet diseases\u0026nbsp;Research\u0026quot; (Grant\u0026nbsp;2016YFD0501000).\u003c/p\u003e\n\u003cp\u003eAll data included in this study are available upon request by contact with the corresponding author.\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank Shanghai Majorbio Bio-pharm Technology Co., Ltd\u0026nbsp;for sequencing services.\u003c/p\u003e\n\u003cp\u003eAuthor contributions: Y.L Guo carried out the study, analyzed, and interpreted the data and compiled the article.\u0026nbsp;J.P Liu,\u0026nbsp;S.Y Zhang\u0026nbsp;contributed to the design of the study, discussion of the results, and critical revision of the article. Z.Y Dong, Sun contributed to the hormone analysis and critical revision of the article. J.S Cao supervised the study and contributed to its design, discussion of the results, and critical revision of the article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll animal studies were conducted in accordance with the\u0026nbsp;experimental practices and standards approved by the Animal Welfare and Research Ethics Committee at Inner Mongolia Agricultural University\u0026nbsp;(Approval ID: 20160829-1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there is no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAM, A.L., Syed, D.N., Ntambi, J.M., 2017. Insights into Stearoyl-CoA Desaturase-1 Regulation of Systemic Metabolism. 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Annales d\\\u0026quot;Endocrinologie, S0003426616300427\u003c/li\u003e\n\u003cli\u003eWang, H., Humbatova, A., Liu, Y., Qin, W., Lee, M., 2020. Mutations in SREBF1, Encoding Sterol Regulatory Element Binding Transcription Factor 1, Cause Autosomal-Dominant IFAP Syndrome. The American Journal of Human Genetics 107(1), 34-45.https://doi.org/10.1016/j.ajhg.2020.05.006\u003c/li\u003e\n\u003cli\u003eWiktorowska-Owczarek, A., Berezinska, M., Nowak, J.Z., 2015. PUFAs: Structures, Metabolism and Functions. Adv Clin Exp Med 24(6), 931-941.https://doi.org/10.17219/acem/31243\u003c/li\u003e\n\u003cli\u003eWoollett, L.A., 2008. Where does fetal and embryonic cholesterol originate and what does it do? Annu Rev Nutr 28, 97-114.https://doi.org/10.1146/annurev.nutr.26.061505.111311\u003c/li\u003e\n\u003cli\u003eZhu, B., Zhang, Q.L., Hua, J.W., Cheng, W.L., Qin, L.P., 2018. The traditional uses, phytochemistry, and pharmacology of Atractylodes macrocephala Koidz.: A review. J Ethnopharmacol 226, 143-167.https://doi.org/10.1016/j.jep.2018.08.023\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistical summary analysis of RNA-seq data sets of treated cells and control cells\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eMeans for raw reads\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMeans for mapping\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo. of raw reads\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo. of valid reads\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQ20 (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo. of map reads\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo. of unique mapped reads\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUniquely mapped ratio (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52,950,059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52,340,848\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e98.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e51,014,192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e48,058,826\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e91.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreated cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58,841,865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58,189,124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e98.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56,730,426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e53,563,083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e92.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \n\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSignificantly upregulated or downregulated genes involved in signaling in FOGCs.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGene Description\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFold Change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e adjust\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRegulation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABCA1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATP binding cassette subfamily A member 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003estearoyl-CoA desaturase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elow density lipoprotein receptor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.025723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCYP1A1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecytochrome P450 1A1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.026415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003edown\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFADS2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efatty acid desaturase 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.034371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABCG1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATP binding cassette subfamily G member 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.724\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.044671\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSREBF1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esterol regulatory element binding transcription factor 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.040339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStAR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esteroidogenic acute regulatory protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.042111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMYLIP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emyosin regulatory light chain interacting protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.002304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eup\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrimers for RT-qPCR.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNucleotide sequence (5\u0026rsquo;-3\u0026rsquo;)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGAPDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward CAAGGCTGTGGGCAAGGTCATC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse TTCTCCAGGCGGCAGGTCAG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSREBF1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward GGCATCGCAAGCAGGCTGAC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse GGTGGGAGGTGGGCAGTGG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABCG1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward ACATGCTGTTGCCACACCTCAC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse TCCTGCCTTCGTCCTTCTCCTG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABCA1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward GGCAACGGCACTGAGGAAGATG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse TGCGGGAAAGAGGACTGGACTC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward GCCAGCAGAGGAGACGAGGAG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse CCCGAAGCCCAGGAGGATGAG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward AAATTCCCTTCGGCCAATGAC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse TCTCACCTCCTCTTGCAGCAA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCYP1A1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward TGGCACCATCAACAAGGCACTG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse AAAGACCTCCAAGCGGGCAATG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFADS2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward GGATATGCGGGCGTAGAAGC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse GTGCCGTGCAAATAGGTGGA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStAR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward GTGGAGCACATGGAAGCGATGG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse GCAGCCAACTCGTGGGTGATG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMYLIP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward AACGAGGGAGCAGGGTTGAA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse ACACTGCCGAGACAGAGGTT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e "}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"ovarian granulosa cell, Atractylenolide-I, estradiol, progesterone, cholesterol metabolism","lastPublishedDoi":"10.21203/rs.3.rs-3080498/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3080498/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cem\u003eAtractylodes macrocephala Koidz\u003c/em\u003e (AMK) as eartraditional oriental medicine has been used in the treatment of threatened abortion. \u003cem\u003eAtractylenolide I\u003c/em\u003e (AT-I) is one of the major bioactive components of AMK. This study aimed to investigate the effect of AT-I on the secretion of estradiol (E\u003csub\u003e2\u003c/sub\u003e) and progesterone (P\u003csub\u003e4\u003c/sub\u003e) of feline ovarian granulosa cells (FOGCs) which is necessary for pregnancy. At first, the prolifeation of FOGCs after AT-I treatment was measured by CCK-8. Then, the synthesis of E\u003csub\u003e2\u003c/sub\u003e and P\u003csub\u003e4\u003c/sub\u003e were measured by ELISA. Lastly, transcriptome sequencing was used to detect the DEGs in the FOGCs, and RNA-Seq results were verified by RT-qPCR and biochemical verification. It was found that AT-I could promote proliferation and the secretion of E\u003csub\u003e2\u003c/sub\u003e and P\u003csub\u003e4\u003c/sub\u003e in FOGCs; after AT-I treatment, 137 significantly DEGs were observed, out of which 49 were up-regulated and 88 down-regulated. The DEGs revealed significant enrichment of 52 GO terms throughout the differentiation process (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) as deciphered by Gene Ontology enrichment analysis. Kyoto Encyclopedia of Genes and Genomes analysis manifested that the DEGs were successfully annotated as members of 155 pathways, with 23 significantly enriched (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). A relatively high number of genes were enriched for the cholesterol metabolism, ovarian steroidogenesis, and biosynthesis of unsaturated fatty acids. Furthermore, the contents of the total cholesterol and low-density lipoprotein cholesterol were decreased by AT-I treatment in the cell culture supernatant. The results indicated that AT-I could increase the ability of FOGCs to secrete E\u003csub\u003e2\u003c/sub\u003e and P\u003csub\u003e4\u003c/sub\u003e, which might be achieved by activation of cholesterol metabolism.\u003c/p\u003e","manuscriptTitle":"A transcriptome approach evaluating the effects of Atractylenolide Ⅰ on the secretion of estradiol and progesterone in feline ovarian granulosa cell","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-06-26 21:36:28","doi":"10.21203/rs.3.rs-3080498/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"79e0e09c-904a-4065-a8af-361098f1d7a4","owner":[],"postedDate":"June 26th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-11-23T12:00:05+00:00","versionOfRecord":[],"versionCreatedAt":"2023-06-26 21:36:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3080498","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3080498","identity":"rs-3080498","version":["v1"]},"buildId":"omnImTCwR2MFx8CMYfrG7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}