Novel SWATHTM technology for follicular fluid metabolomics in patients with endometriosis

was adequate for detecting the unknown samples. The chromatography residue was also assessed using the internal stan- dard peak area in the blank sample, following the follicular fluid sample. The internal standard peak was not detected in the blank sample, which indicates that there was no chromatography residue. These results indicate that the analytical method was adequate for use in the metabolomics study. 2.3. Comparison of EMT group and control group The EMT group could be separated completely from the control group, as shown in Fig.  1 (PCA score plot) and Fig.  2 (loading plot), which indicated significant differences between them. The contribution list of metabolites was produced based on p-values below 0.05. The metabolites were validated based on accurate mass, isotope patterns, and mass spectrometric fragmentation patterns, and the results are shown in Table 3. Fig.1: Score plots obtained from non-targeted UPLC-TOF MS analysis. Fig. 2: Loading plot obtained from non-targeted UPLC-TOF MS analysis. Table 3: Characterization of the biomarkers between endometriosis group and control group in follicular fluid by UPLC-Q-TOF MS Compound T R (min) m/z Molecular Formula Identity (Endometriosis group vs Control group) Error (mDa) Fold change (E/C) T-test (p) M1 4.78 318.3007 C 18H39NO3 Phytosphingosine -0.1 0.15 <0.05 M2 5.38 520.3396 C 26H50NO7P LysoPC(18:2(9Z,12Z)) -0.7 10.2 <0.01 M3 7.22 524.3722 C 26H54NO7P LysoPC(18:0) 0.6 3.6 <0.01 The differential metabolite M1 showed the [M+H] + ion at m/z 318.3007. The elution time of M1 was 4.78 min in the UPLC chromatogram. Its molecular formula was inferred as C 18H39NO3, according to its accurate mass and isotope patterns. A series of characteristic product ions were observed at m/z 300.2893, 256.2648, 212.2387, 102.0948, and 88.0780 by successive loss of H 2O, C 2H6O2, C 4H10O2, C 13H28O2 and C 14H30O2. The structure of M1 was inferred as phytosphingosine, based on the MS and MS2 information (Fig. 3). The differential metabolite M2 showed the ORIGINAL ARTICLES Pharmazie 73 (2018)320 [M+H]+ ion at m/z 520.3396. The elution time of M2 was 5.38 min in the UPLC chromatogram. Its molecular formula was inferred as C 26H50NO7P, based on its accurate mass and isotope patterns. A series of characteristic product ions were observed at m/z 502.3277, 461.2522, 184.0731, 104.1076 and 86.0974 by successive loss of H 2O, C 3H9N, C 21H36O3, C 21H37O6P and C 21H39O7P. The structure of M2 was inferred as LysoPC (18:2(9Z, 12Z)), based on the MS and MS2 information (Fig. 4). Differential metabolite M3 showed the [M+H] + ion at m/z 524.3729. The elution time of M3 was 7.22 min in the UPLC chromatogram. Its molecular formula was inferred as C 26H54NO7P, according to its accurate mass and isotope patterns. A series of characteristic product ions were observed at m/z 506.3614, 341.3062, 184.0735, 104.1085 and 86.0955, by successive loss of H 2O, C5H14NO4P, C21H40O3 and C21H43O7P. The structure of M3 was inferred as LysoPC (18:0), based on the MS and MS2 information (Fig. 5). The complete results are listed in Table  3. As seen in Fig.  6, differences in the three metabolites between the EMT group and the control group were displayed with Graph Pad Prism. The names of the metabolites are shown in the box plot. When accounting for outliers, the whiskers extended to a maximum of 1.5 times the inter-quartile range. 3. Discussion SW ATHTM is a new on-line data acquisition method, used for the assessment of independent parameters of compounds. The SW ATH TM method enables the detection of all peaks and the corre- sponding MS/MS spectra. Some small indicators such as lactate, insulin, glucose, leucine and proline were identified in previous studies (Bancsi et  al. 2003; Santonastaso et  al. 2017; Nicholson et al. 1999). In our study, new differential metabolites between two groups were obtained by the SW ATH TM method. Oocyte quality directly reflects the intrinsic developmental potential and is responsible for normal fertilization/embryonic development during IVF (Harlow et al. 1996). The rate of fertil- ization was reduced during IVF/ICSI cycles in mice with endo- Fig. 3: The product ion spectra and structure of M1 Fig. 4: The product ion spectra and structure of M2 Fig. 5: The product ion spectra and structure of M3 Fig. 6: Metabolite profiles of the 3 candidate biomarkers obtained from the quantitative analysis of the subjects (p < 0.05). ORIGINAL ARTICLES Pharmazie 73 (2018) 321 metriosis, in a previous study (Mansour et al. 2010). Poor oocyte quality could be the main factor in adverse pregnancy outcomes during IVF/intracytoplasmic sperm injection (ICSI) cycles in women with endometriosis. The proliferation of uterine endome- trial cells outside the uterine cavity significantly increases the demand of biosynthesis and biological energy. Fatty acids are esterified to phospholipids as the sources of signaling molecules and energy supply, to support the rapid proliferation of ectopic e 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 - osis may be associated with altered endogenous lipid metab- olism (Toya and Hiroi 2000). Vouk et al. (2012) and Lee et al. (2014) indicated that the signaling pathway of endogenous lipids related to sphingolipids, ethers and lysophospholipids is influ- enced in the endometrial tissues of EMT patients. In our study, lysoPC(18:0) and lysoPC(18:2(9Z,12Z)) showed higher levels in the EMT group compared to the control group. LysoPC can induce the acrosome reacti on ( AR ) of spermatozoa in diff erent species, including humans, enhancing fertility (De Lamirande et al. 1998; Ohzu and Yanagimachi 1982). Dutta et al. (2012) also identified three differential metabolites such as monoacylglyc- erol (MAG), lysophosphatidylcholine (lysoPC) and phytosphin- gosine (PHS). Their results indicated that lysoPC and PHS are secreted by cumulus cells during in vitro fertilization, and can participate in the induced AR process. However, the capacita- tion of the sperm may be affected by the high concentration of LysoPC. Acrosomal loss was also caused by high concentration of LysoPC, which may affect the combination of egg cells and sperm (Byrd and Wolf 1986). Therefore, a higher level of lysoPC in follicular fluid may be one of the reasons for low conception rate in endometriosis patients. Our study also found that the level of phytosphingosine in the EMT group was significantly lower than that in the control group. Phytosphingosine was involved in the pathway of sphingolipid metabolism (Fig. 7), which indicates that sphingolipid metabolism was abnormal in the patients with EMT. Sphingolipids are bioactive molecules that participate in diverse functions, controlling fundamental cellular processes such as ce ll di vis i on, diff eren tiati on, and ce ll death (Rao et al. 2013). Furthermore, the decreased level of phytosphingosine in patients with EMT could increase the risk of type 2 diabetes mellitus (Floegel et al. 2013). 4. Experimental 4.1. Chemicals and reagents Gemfibrozil (purity: > 98.5%) and isotope-labeled d3-palmitic acid (purity: > 99%), as internal standard, were purchased from Sigma (St. Louis, MO, USA). Chromato- graphic grade acetonitrile and formic acid were obtained from Merck & Co., INC (Darmstadt, Germany). 4.2. Subjects All subjects were recruited from the Integrative Medicine Research Centre of Repro- duction and Heredity, of the Affiliated Hospital of Shandong University of Traditional Chinese Medicine, from January to December 2015. The study was approved by the Health Authorities and Ethics Committees of the Affiliated Hospital of Shandong University of Traditional Chinese Medicine. All study participants signed an informed consent form before the start of the study. The diagnosis of endometriosis was done via laparoscopy and requires the presence of one or more typical bluish or black lesions, according to guidelines for diagnosis and treatment of endometriosis (Depart- ment of Endometriosis of the Chinese Medical Association 2015). We recruited 17 endometriosis patients and 16 age- and BMI-matched unaffected women as controls, and participant information was listed in Table 1. All controls had a normal menstrual cycle, and none had clinical and/or biochemical hyperandrogenism. The age of the subjects was between 31 and 40 years. Exclusion criteria for both groups included (1) having received hormonal therapy in the last three months; (2) inability to support pregnancy due to severe diseases; (3) suffering from severe mental diseases, acute urogenital system inflammation or sexually transmitted diseases; (4) being affected by hereditary diseases that prohibit having a baby; harmful addictions, including drugs Fig. 7: The pathway of sphingolipid metabolism ORIGINAL ARTICLES Pharmazie 73 (2018)322 and alcohol; being exposed to radiation, toxins and/or drugs within the action period that could cause malformations in the fetus. 4.3. Study design Prior to entering the trial, 33 women signed informed consents. On the basis of estab- lished protocols, all patients underwent controlled ovarian hyperstimulation (COH). When the mean diameter of at least three leading follicles reached more than 18 mm, 10,000 IU human chorionic gonadotropin (hCG) (Choriomon, IBSA, Switzerland) was administered intramuscularly, 34-38 h after hCG injection under ultrasound guidance. The follicles (the maximum size < 20 mm) were aspirated using a 17-gauge Cook needle. Subsequently, oocytes were retrieved. After oocyte isolation, follicular fluid from three mature follicles was pooled and centrifuged at 14,000× g for 20 min, to remove cells and insoluble particles. The supernatant was transferred to sterile cryovials and stored at -80 °C for further study. Specimens with blood contamination were discarded. Blood samples were also acquired during the early follicular phase (days 3-5), from all subjects. The concentrations of follicle stimulating hormone in blood were detected using the enzyme-linked immunosorbent assay (ELISA) (Lucas et al. 1995; Li and Li 2000; Mickova et al. 2003). 4.4. Sample preparation Follicular fluid samples of 100 μL were mixed with 300 μL of methanol containing 4 μM of gemfibrozil and isotope-labeled d3-palmitic acid. The mixture was vortexed for 5 min and then centrifuged at 14000× g for 30 min, at 4 °C. The supernatant was then transferred to an autosampler plate for analysis. 4.5. Method condition Aliquots of 2 μL supernatant were injected into the ultra-performance liquid chroma- tography tandem Triple TOF 5600 system (AB SCIEX, CA, USA) in random order, to avoid complications caused by artifacts related to injection order and occasional changes in instrumental efficiency. The liquid chromatography system consisted of a reverse-phase 2.1*100 mm ACQUITY UPLC® BEH C18 1.7 μm column (Waters Corp., USA), with a gradient mobile phase composed of 0.1% formic acid solution (A) and acetonitrile containing 0.1% formic acid solution (B). The gradient was kept at 95% A for 1 min, increased to 100% B over the next 6 min, and then returned to 95% A from 9 min to 9.2 min. The total run time was 12 min. The optimized mass parameters were as follows: nebulizing gas (GAS1): 60 psi; TIS gas (GAS2): 60 psi; source temperature: 550 °C; ion spray voltage: 5500 V with 30 psi curtain gas in positive mode and -4500 V with 30 psi curtain gas in negative mode. The declustering potential and collision energy were set at 60 eV and 25 V in positive mode (-60 eV and -25 V in negative mode), respectively. The SW ATH method analysis with 15 variable isolation windows was performed in full-scan mode and in product ion scan mode at m/z 100 – 1200 using the Analyst TF 1.7.1 software. Data processing was performed using MarkerView 2.0. 4.6. Data analysis In total, 33 follicular fluid samples were analyzed in replicates using the SW ATHTM technique on UPLC-TOF MS. Data was processed using the PeakView software (AB SCIEX, CA, USA) for qualitative analyses and the MarkerView software (AB SCIEX, CA, USA) for multi-variate analysis (MV A). In large-scale non-targeted LC-MS metabolomic measurements, the reproducibility of the analysis may be influenced by source contamination or the maintenance and cleaning of the mass-spectrometer. Normalization is a common preprocessing method to decrease systematic change. However, normalization of the data may cause nonsystematic, compound-dependent variability (Gika et al. 2007). In this study, internal standards were used to calibrate the response of metabolite ions. Gemfibrozil was used to calibrate the metabolites in posi- tive ion mode. Isotope-labeled d3-palmitic acid was used only for negative ion mode. By mixing equal volumes of follicular fluid from different subjects, 6 QC samples in replicates were prepared to evaluate the reproducibility of the metabolite analysis. All ion features were extracted and aligned using the MarkerView software (Applied Biosystems/MDS Sciex, Canada), to generate a data matrix consisting of peak areas corresponding to a unique m/z and retention time. After aligning peaks from the EMT and control groups, the zero-values were removed using the modified 80% rule. The score plot and loading scatter plot were obtained via principal component analysis (PCA) in the MarkerView software. The differences between groups can be seen from the score plot. Loading plots were used to identify metabolites that exerted a major influence on the group membership. Each point represented an ion that contributed to the sample separation between groups. These ions were listed according to their correlation and their abundance rank (peak area) following the primary screening. Precursor ions of metabolites were quantified by their peak areas. The Student’s t-test was used for statistical comparisons. The data were presented as the mean±standard deviation. The contributing list of metabolites was determined by p-values below 0.05. The contributory list presents candidate biomarkers in the EMT group compared with the control group. The predictability of the model was determined by internal validation with 7-fold cross-validation and response permutation testing. Metabolites with high contribution score were identified by accurate mass, isotope patterns and mass spectrometric fragmentation patterns, which were used to search databases, including KEGG, PubChem compound, METLIN, the Madison Metabolo- mics Consortium Database and the Human Database. Acknowledgments: This work was supported by the National Natural Science Fund project (No. 81373676; No.81674018) and the Science and Technology Development Project of Shandong Province (2014GSF119021). Conflicts of interest: None declared.

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