{"paper_id":"fbe9f47b-76c2-499d-8ee9-6e57ae311584","body_text":"ORIGINAL ARTICLES\nPharmazie 73 (2018)318\nReproductive and Genetic Center of Integrated Traditional and Western Medicine1, the Affiliated Hospital of Shandong \nUniversity of Traditional Chinese Medicine, Jinan, China; Department of Gynecology and Obstetrics of Traditional Chinese \nMedicine\n2, the First Clinical College, Shandong University of Traditional Chinese Medicine, Jinan, China; School of \nBioscience & Bioengineering3, South China University of Technology, Guangzhou, China\nNovel SWATHTM technology for follicular fluid metabolomics in patients \nwith endometriosis\nZHENGAO SUN1,*, JINGYAN SONG2, XINGXING ZHANG2, AIJUAN WANG2, YING GUO1, YI YANG2, XIAOMING WANG2, KAIYUE XU2, JIFENG DENG3\nReceived November 21, 2017, accepted February 17, 2018\n*Corresponding author: Zhengao Sun, Integrative Medicine Research Centre of Reproduction and Heredity,The \nAffiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan City, 250011, Shandong  Province, \nChina\nsunzhengao77@126.com\nPharmazie 73: 318–323 (2018) doi: 10.1691/ph.2018.7193\nAim of the study: Sequential window acquisition of all theoretical fragment-ion spectra (SWATH TM), a powerful \nhigh-resolution mass spectrometric data independent acquisition technique, was used to identify differences \nthat relate certain metabolites to endometriosis (EMT) in follicular fluid collected from EMT patients and a control \ngroup. Methods: A case-control study was conducted to analyze the EMT -related metabolites and the IVF clinical \ndata of 33 subjects. Subjects were divided between the observation group (17 cases, infertility due to EMT) and \nthe control group (16 cases, infertility due to male factor, such as obstructive azoospermia). Results: Analysis \nrevealed three metabolites including phytosphingosine, LysoPC(18:2(9Z,12Z)) and LysoPC(18:0), which were \nclosely related to infertility associated withEMT. In the EMT group, LysoPC(18:2(9Z,12Z)) and LysoPC(18:0) were \nupregulated, while phytosphingosine was downregulated. Conclusions: This study employed, for the first time, \nthe SWATH\nTM data acquisition mode for the metabolomics study of human follicular fluid in patients with EMT. \nThe differential metabolite profiles of follicular fluid were identified and mapped. These differential metabolites \nare involved in cell proliferation and apoptosis, energy metabolism, inflammatory responses and angiogenesis. \nThe differential metabolite profile may be a new tool for early noninvasive assessment of the developmental \npotential of oocytes in patients with EMT.\n1. Introduction\nEndometriosis is a disorder of the female human reproductive \nsystem in which the endometrium grows outside the uterus, which \noften occurs on the ovaries and peritoneum, and causes premen-\nstrual pain and dysmenorrhea (Damewood 1989; Ozkan et  al. \n2008; Rock and Markham 1992). Endometriosis is one of the \nmost common reasons of infertility, being diagnosed in 25-40% \nof infertile women (Ozkan et al. 2008). Dysfunction of a fallopian \ntube (Bergendal et al. 1998), subtle impairments of the oocytes and \nembryo development potential (Carrido et al. 2000; Lyons et al. \n2002), immunological defects (Mansour et al. 2010), and anatom-\nical dysfunctions of an ovary have been postulated to explain \ninfertility associated with endometriosis. In addition, estrogen and \ninflammation have also been associated with the development of \nendometriosis (Bulun 2009). Even mild stage endometriosis might \nhave a direct negative effect on oocyte quality and the potential \nfor embryonic development and implantation (Arici et  al. 1997; \nBarnhart et  al. 2002). Oocyte quality is widely accepted as a \npotential major factor in infertility in those patients (Broekmans \net al. 2006; Garrido et al. 2003). Cahill et al. (1997) and Xu et al. \n(2015) showed that ovulatory dysfunction and the associated \npain of patients lead to reduced fertilization rates in women with \nminor endometriosis. Pauli et al. (2013) found that trans-retinoic \nacid plays a fundamental role in oocyte development and quality, \nand that reduced trans-retinoic acid synthesis may contribute to \ndecreased fecundity in patients with endometriosis.\nFollicular fluid comes from follicles, and contains numerous \nmetabolites that play an important role in follicle development and \noocyte maturation. Endometriosis might cause alterations in the \nmicroenvironment formed by follicular fluid for oocyte develop-\nment and, therefore, negatively impact fertility. At present, there \nare few clear small molecular indicators (lactate, insulin, glucose, \nleucine, proline, etc.) of poor oocyte quality due to endometriosis \n(Bancsi et  al. 2003; Nicholson et  al. 1999; Santonastaso et  al. \n2017).\nMetabolomics, which is the identification and quantification of a \nset of metabolites in biological systems, can be used to find poten-\ntial biomarkers for studying the relative biochemical pathways in \nfollicular fluid. A better understanding of this complex disorder \nand the identification of potential biomarkers of endometriosis \nmay mean a significant advance for evaluating changes in oocytes \ncaused by endometriosis.\nAlthough high-resolution mass spectrometry (HRMS) such as time \nof flight (TOF) has become a conventional tool for metabolomics \nstudy (Qiang et  al. 2016; Yao et  al. 2016), the identification of \nlow-level differential endogenous metabolites is still very diffi-\ncult. The m/z of the precursor and product ions was recorded in \nMS and MS/MS spectra to provide crucial information for the \nelemental composition analysis and structure elucidation. The \nhit rates of the MS/MS spectrum played a decisive role in the \nidentification of differential endogenous metabolites. Compared \nto the information-dependent acquisition (IDA) method (Lin \net al. 2014; Sun et al. 2015), sequential window acquisition of all \ntheoretical fragment-ion spectra (SW ATH\nTM) (Hopfgartner et  al. \n2012) significantly improved the hit rate of low-level endogenous \nmetabolites, as it can sequentially obtain all MS/MS spectra of all \nmass windows across the specified mass range (Xie et al. 2017). \nMoreover, the MS\nALL technique does not require the selection of \nprecursor ions to trigger the acquisition of fragment ion spectra \n(Bilbao et al. 2015). The novel SW ATH technique presents various \nadvantages in the field of absolute quantification (Bonner and \nHopfgartner 2016; Wrona et al. 2005). For example, an advantage \n\nORIGINAL ARTICLES\nPharmazie 73 (2018) 319\nof SW ATHTM acquisition resides in the possibility of reprocessing \nthe same data set to obtain previously unidentified features without \nreacquiring the sample (Gillet et al. 2012).\nIn our study, the SW ATH technique was used, for the first time, \nto assess the differences between the metabolomics profile of \nfollicular fluid collected from EMT patients and a control group. \nMetabolomics based on the SW ATH approach could be used for \nproviding comprehensive information about follicular fluid for the \ndiagnosis and prognosis of endometriosis-related infertility.\n2. Investigations and results\n2.1. Clinical background of subjects\nThe results of basal FSH and E2 in blood are shown in Table 1. \nNo significant changes were observed in the EMT group. Clini-\ncally, no statistical differences in the number of oocytes were seen. \n2PN cleavage rate, high-grade embryo rate, cumulative pregnancy \nrate and live birth rate were identified between these two groups \n(Table  2). However, participants in the EMT group had signifi-\ncantly lower MII rates and fertility rates than those in the control \ngroup (Table 2).\nTable 1: Clinical background of endometriosis group and control \ngroup\nClinical parameter Control group EMT group T-test (P)\nAge (years) 34.8±3.4 36.1±3.0 0.239\nInfertility duration (years) 2.79±1.90 3.89±2.68 0.083\nBody mass index (kg/m2) 23.79±4.21 23.70±3.24 0.930\nBasal FSH (mIU/mL) 9.89±7.30 7.17±3.86 0.091\nBasal E2 (pg/mL) 35.46±14.50 43.37±18.78 0.086\nBasal AFC (N) 10.18±5.75 12.70±8.20 0.191\nDuration of Gn used (days) 11.18±2.84 11.37±3.27 0.817\nDosage of Gn used (mg) 2946.7±1152.0 2802.3±1194.3 0.650\nTable 2: Comparison of in vitro fertilization between EMT group and \ncontrol group\nClinical parameter Control group EMT group T-test (P)\nOocytes retrieved (N) 7.82±4.92 7.78±4.30 0.972\nMII oocyte maturation rate (%) 89.4% 81.0% 0.015*\nFertility rate (%) 73.5% 54.3% 0.008**\n2PN cleavage rate (%) 97.9% 97.4% 0.772\nHigh-grade embryo rate (%) 55.7% 49.5% 0.331\nCumulative pregnancy rate (%) 37.0% 32.0% 0.703\nLive birth rate (%) 29.6% 28.0% 0.897\n* (p<0.05), ** (p<0.01)\n2.2. Reproducibility of the LC-MS system\nIn total, six quality control (QC) samples (one QC after each four \nfollicular fluid samples) were prepared by mixing equal volumes \nof different individual follicular fluid samples. These were used to \nassess the reproducibility and reliability of the UPLC-MS system. \nThe QC samples were tightly clustered together (Fig. 1). The repro-\nducibility of the main background ions and the internal standard \nions, such as midazolam (m/z 326.0860), was assessed using the \nrelative standard deviation (RSD). The RSD of these background \nions and the internal standard ions for all QC samples was less than \n13.5%. This indicates good reproducibility and reliability of the \nUPLC-MS system. The internal standard ion (m/z 326.0860) was \ndetected at m/z 326.0866, and was less than 1 mDa by comparison \nwith the theoretical mass. This shows that the accuracy of the \nmethod was adequate for detecting the unknown samples. The \nchromatography residue was also assessed using the internal stan-\ndard peak area in the blank sample, following the follicular fluid \nsample. The internal standard peak was not detected in the blank \nsample, which indicates that there was no chromatography residue. \nThese results indicate that the analytical method was adequate for \nuse in the metabolomics study.\n2.3. Comparison of EMT group and control group\nThe EMT group could be separated completely from the control \ngroup, as shown in Fig.  1 (PCA score plot) and Fig.  2 (loading \nplot), which indicated significant differences between them. The \ncontribution list of metabolites was produced based on p-values \nbelow 0.05. The metabolites were validated based on accurate \nmass, isotope patterns, and mass spectrometric fragmentation \npatterns, and the results are shown in Table 3.\nFig.1: Score plots obtained from non-targeted UPLC-TOF MS analysis.\nFig. 2: Loading plot obtained from non-targeted UPLC-TOF MS analysis.\nTable 3: Characterization of the biomarkers between endometriosis \ngroup and control group in follicular fluid by UPLC-Q-TOF MS\nCompound T R\n(min)\nm/z Molecular \nFormula\nIdentity\n(Endometriosis group vs \nControl group)\nError \n(mDa)\nFold \nchange\n(E/C)\nT-test\n(p)\nM1 4.78 318.3007 C 18H39NO3 Phytosphingosine -0.1 0.15 <0.05\nM2 5.38 520.3396 C 26H50NO7P LysoPC(18:2(9Z,12Z)) -0.7 10.2 <0.01\nM3 7.22 524.3722 C 26H54NO7P LysoPC(18:0) 0.6 3.6 <0.01\nThe differential metabolite M1 showed the [M+H] + ion at m/z \n318.3007. The elution time of M1 was 4.78 min in the UPLC \nchromatogram. Its molecular formula was inferred as C\n18H39NO3, \naccording to its accurate mass and isotope patterns. A series of \ncharacteristic product ions were observed at m/z 300.2893, \n256.2648, 212.2387, 102.0948, and 88.0780 by successive loss of \nH\n2O, C 2H6O2, C 4H10O2, C 13H28O2 and C 14H30O2. The structure of \nM1 was inferred as phytosphingosine, based on the MS and MS2 \ninformation (Fig. 3). The differential metabolite M2 showed the \n\nORIGINAL ARTICLES\nPharmazie 73 (2018)320\n[M+H]+ ion at m/z 520.3396. The elution time of M2 was 5.38 min \nin the UPLC chromatogram. Its molecular formula was inferred \nas C\n26H50NO7P, based on its accurate mass and isotope patterns. A \nseries of characteristic product ions were observed at m/z 502.3277, \n461.2522, 184.0731, 104.1076 and 86.0974 by successive loss of \nH\n2O, C 3H9N, C 21H36O3, C 21H37O6P and C 21H39O7P. The structure \nof M2 was inferred as LysoPC (18:2(9Z, 12Z)), based on the MS \nand MS2 information (Fig. 4). Differential metabolite M3 showed \nthe [M+H]\n+ ion at m/z 524.3729. The elution time of M3 was \n7.22 min in the UPLC chromatogram. Its molecular formula was \ninferred as C\n26H54NO7P, according to its accurate mass and isotope \npatterns. A series of characteristic product ions were observed at \nm/z 506.3614, 341.3062, 184.0735, 104.1085 and 86.0955, by \nsuccessive loss of H\n2O, C5H14NO4P, C21H40O3 and C21H43O7P. The \nstructure of M3 was inferred as LysoPC (18:0), based on the MS \nand MS2 information (Fig. 5). The complete results are listed in \nTable  3. As seen in Fig.  6, differences in the three metabolites \nbetween the EMT group and the control group were displayed with \nGraph Pad Prism. The names of the metabolites are shown in the \nbox plot. When accounting for outliers, the whiskers extended to a \nmaximum of 1.5 times the inter-quartile range.\n3. Discussion\nSW ATHTM is a new on-line data acquisition method, used for \nthe assessment of independent parameters of compounds. The \nSW ATH\nTM method enables the detection of all peaks and the corre-\nsponding MS/MS spectra. Some small indicators such as lactate, \ninsulin, glucose, leucine and proline were identified in previous \nstudies (Bancsi et  al. 2003; Santonastaso et  al. 2017; Nicholson \net al. 1999). In our study, new differential metabolites between two \ngroups were obtained by the SW ATH\nTM method.\nOocyte quality directly reflects the intrinsic developmental \npotential and is responsible for normal fertilization/embryonic \ndevelopment during IVF (Harlow et al. 1996). The rate of fertil-\nization was reduced during IVF/ICSI cycles in mice with endo-\nFig. 3: The product ion spectra and structure of M1\nFig. 4: The product ion spectra and structure of M2\nFig. 5: The product ion spectra and structure of M3\nFig. 6: Metabolite profiles of the 3 candidate biomarkers obtained from the quantitative analysis of the subjects (p < 0.05).\n\nORIGINAL ARTICLES\nPharmazie 73 (2018) 321\nmetriosis, in a previous study (Mansour et al. 2010). Poor oocyte \nquality could be the main factor in adverse pregnancy outcomes \nduring IVF/intracytoplasmic sperm injection (ICSI) cycles in \nwomen with endometriosis. The proliferation of uterine endome-\ntrial cells outside the uterine cavity significantly increases the \ndemand of biosynthesis and biological energy. Fatty acids are \nesterified to phospholipids as the sources of signaling molecules \nand energy supply, to support the rapid proliferation of ectopic \ne n d o m e tri al  c e ll s  (M ar e i  e t  al .  2 0 1 0 ) .  F urth e rm o r e ,  e n d o m e tri -\nosis may be associated with altered endogenous lipid metab-\nolism (Toya and Hiroi 2000). Vouk et al. (2012) and Lee et al. \n(2014) indicated that the signaling pathway of endogenous lipids \nrelated to sphingolipids, ethers and lysophospholipids is influ-\nenced in the endometrial tissues of EMT patients. In our study, \nlysoPC(18:0) and lysoPC(18:2(9Z,12Z)) showed higher levels \nin the EMT group compared to the control group. LysoPC can \ninduce the acrosome reacti on ( AR ) of spermatozoa in diff erent \nspecies, including humans, enhancing fertility (De Lamirande \net al. 1998; Ohzu and Yanagimachi 1982). Dutta et al. (2012) also \nidentified three differential metabolites such as monoacylglyc-\nerol (MAG), lysophosphatidylcholine (lysoPC) and phytosphin-\ngosine (PHS). Their results indicated that lysoPC and PHS are \nsecreted by cumulus cells during in vitro  fertilization, and can \nparticipate in the induced AR process. However, the capacita-\ntion of the sperm may be affected by the high concentration of \nLysoPC. Acrosomal loss was also caused by high concentration \nof LysoPC, which may affect the combination of egg cells and \nsperm (Byrd and Wolf 1986). Therefore, a higher level of lysoPC \nin follicular fluid may be one of the reasons for low conception \nrate in endometriosis patients. Our study also found that the level \nof phytosphingosine in the EMT group was significantly lower \nthan that in the control group. Phytosphingosine was involved in \nthe pathway of sphingolipid metabolism (Fig. 7), which indicates \nthat sphingolipid metabolism was abnormal in the patients with \nEMT. Sphingolipids are bioactive molecules that participate in \ndiverse functions, controlling fundamental cellular processes \nsuch as ce ll di vis i on, diff eren tiati on, and ce ll death (Rao et al.  \n2013). Furthermore, the decreased level of phytosphingosine in \npatients with EMT could increase the risk of type 2 diabetes \nmellitus (Floegel et al. 2013).\n4. Experimental\n4.1. Chemicals and reagents\nGemfibrozil (purity: > 98.5%) and isotope-labeled d3-palmitic acid (purity: > 99%), \nas internal standard, were purchased from Sigma (St. Louis, MO, USA). Chromato-\ngraphic grade acetonitrile and formic acid were obtained from Merck & Co., INC \n(Darmstadt, Germany).\n4.2. Subjects\nAll subjects were recruited from the Integrative Medicine Research Centre of Repro-\nduction and Heredity, of the Affiliated Hospital of Shandong University of Traditional \nChinese Medicine, from January to December 2015. The study was approved by the \nHealth Authorities and Ethics Committees of the Affiliated Hospital of Shandong \nUniversity of Traditional Chinese Medicine. All study participants signed an informed \nconsent form before the start of the study. The diagnosis of endometriosis was done \nvia laparoscopy and requires the presence of one or more typical bluish or black \nlesions, according to guidelines for diagnosis and treatment of endometriosis (Depart-\nment of Endometriosis of the Chinese Medical Association 2015). We recruited 17 \nendometriosis patients and 16 age- and BMI-matched unaffected women as controls, \nand participant information was listed in Table 1. All controls had a normal menstrual \ncycle, and none had clinical and/or biochemical hyperandrogenism. The age of the \nsubjects was between 31 and 40 years. Exclusion criteria for both groups included \n(1) having received hormonal therapy in the last three months; (2) inability to support \npregnancy due to severe diseases; (3) suffering from severe mental diseases, acute \nurogenital system inflammation or sexually transmitted diseases; (4) being affected by \nhereditary diseases that prohibit having a baby; harmful addictions, including drugs \nFig. 7: The pathway of sphingolipid metabolism\n\n\nORIGINAL ARTICLES\nPharmazie 73 (2018)322\nand alcohol; being exposed to radiation, toxins and/or drugs within the action period \nthat could cause malformations in the fetus.\n4.3. Study design\nPrior to entering the trial, 33 women signed informed consents. On the basis of estab-\nlished protocols, all patients underwent controlled ovarian hyperstimulation (COH). \nWhen the mean diameter of at least three leading follicles reached more than 18 mm, \n10,000 IU human chorionic gonadotropin (hCG) (Choriomon, IBSA, Switzerland) \nwas administered intramuscularly, 34-38 h after hCG injection under ultrasound \nguidance. The follicles (the maximum size < 20 mm) were aspirated using a 17-gauge \nCook needle. Subsequently, oocytes were retrieved. After oocyte isolation, follicular \nfluid from three mature follicles was pooled and centrifuged at 14,000× g for 20 min, \nto remove cells and insoluble particles. The supernatant was transferred to sterile \ncryovials and stored at -80 °C for further study. Specimens with blood contamination \nwere discarded. Blood samples were also acquired during the early follicular phase \n(days 3-5), from all subjects. The concentrations of follicle stimulating hormone in \nblood were detected using the enzyme-linked immunosorbent assay (ELISA) (Lucas \net al. 1995; Li and Li 2000; Mickova et al. 2003).\n4.4. Sample preparation\nFollicular fluid samples of 100 μL were mixed with 300 μL of methanol containing \n4 μM of gemfibrozil and isotope-labeled d3-palmitic acid. The mixture was vortexed \nfor 5 min and then centrifuged at 14000× g for 30 min, at 4 °C. The supernatant was \nthen transferred to an autosampler plate for analysis.\n4.5. Method condition\nAliquots of 2 μL supernatant were injected into the ultra-performance liquid chroma-\ntography tandem Triple TOF 5600 system (AB SCIEX, CA, USA) in random order, \nto avoid complications caused by artifacts related to injection order and occasional \nchanges in instrumental efficiency. The liquid chromatography system consisted of \na reverse-phase 2.1*100 mm ACQUITY UPLC® BEH C18 1.7 μm column (Waters \nCorp., USA), with a gradient mobile phase composed of 0.1% formic acid solution \n(A) and acetonitrile containing 0.1% formic acid solution (B). The gradient was kept \nat 95% A for 1 min, increased to 100% B over the next 6 min, and then returned to \n95% A from 9 min to 9.2 min. The total run time was 12 min. The optimized mass \nparameters were as follows: nebulizing gas (GAS1): 60 psi; TIS gas (GAS2): 60 psi; \nsource temperature: 550 °C; ion spray voltage: 5500 V with 30 psi curtain gas in \npositive mode and -4500 V with 30 psi curtain gas in negative mode. The declustering \npotential and collision energy were set at 60 eV and 25 V in positive mode (-60 eV and \n-25 V in negative mode), respectively. The SW ATH method analysis with 15 variable \nisolation windows was performed in full-scan mode and in product ion scan mode at \nm/z 100 – 1200 using the Analyst TF 1.7.1 software. Data processing was performed \nusing MarkerView 2.0.\n4.6. Data analysis\nIn total, 33 follicular fluid samples were analyzed in replicates using the SW ATHTM \ntechnique on UPLC-TOF MS. Data was processed using the PeakView software (AB \nSCIEX, CA, USA) for qualitative analyses and the MarkerView software (AB SCIEX, \nCA, USA) for multi-variate analysis (MV A). In large-scale non-targeted LC-MS \nmetabolomic measurements, the reproducibility of the analysis may be influenced \nby source contamination or the maintenance and cleaning of the mass-spectrometer. \nNormalization is a common preprocessing method to decrease systematic change. \nHowever, normalization of the data may cause nonsystematic, compound-dependent \nvariability (Gika et al. 2007). In this study, internal standards were used to calibrate the \nresponse of metabolite ions. Gemfibrozil was used to calibrate the metabolites in posi-\ntive ion mode. Isotope-labeled d3-palmitic acid was used only for negative ion mode. \nBy mixing equal volumes of follicular fluid from different subjects, 6 QC samples \nin replicates were prepared to evaluate the reproducibility of the metabolite analysis. \nAll ion features were extracted and aligned using the MarkerView software (Applied \nBiosystems/MDS Sciex, Canada), to generate a data matrix consisting of peak areas \ncorresponding to a unique m/z and retention time. After aligning peaks from the EMT \nand control groups, the zero-values were removed using the modified 80% rule. The \nscore plot and loading scatter plot were obtained via principal component analysis \n(PCA) in the MarkerView software. The differences between groups can be seen from \nthe score plot. Loading plots were used to identify metabolites that exerted a major \ninfluence on the group membership. Each point represented an ion that contributed \nto the sample separation between groups. These ions were listed according to their \ncorrelation and their abundance rank (peak area) following the primary screening. \nPrecursor ions of metabolites were quantified by their peak areas. The Student’s t-test \nwas used for statistical comparisons. The data were presented as the mean±standard \ndeviation. The contributing list of metabolites was determined by p-values below \n0.05. The contributory list presents candidate biomarkers in the EMT group compared \nwith the control group. The predictability of the model was determined by internal \nvalidation with 7-fold cross-validation and response permutation testing.\nMetabolites with high contribution score were identified by accurate mass, isotope \npatterns and mass spectrometric fragmentation patterns, which were used to search \ndatabases, including KEGG, PubChem compound, METLIN, the Madison Metabolo-\nmics Consortium Database and the Human Database.\nAcknowledgments: This work was supported by the National Natural Science Fund \nproject (No. 81373676; No.81674018) and the Science and Technology Development \nProject of Shandong Province (2014GSF119021).\nConflicts of interest: None declared.\nReferences\nArici A, Oral E, Attar E, Tazuke SI, Olive DL (1997) Monocyte chemotactic protein-1 \nconcentration in peritoneal fluid of women with endometriosis and its modulation \nof expression in mesothelial cells. 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