Edited by: Emanuela Ricciotti, University of Pennsylvania, United States
Reviewed by: Helena Idborg, Karolinska Institute (KI), Sweden; Georgios Paschos, University of Pennsylvania, United States
This article was submitted to Inflammation Pharmacology, a section of the journal Frontiers in Pharmacology
†These authors have contributed equally to this work.
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Cervicitis is an exceedingly common gynecological disorder that puts women at high risk of sexually transmitted infections and induces a series of reproductive system diseases. This condition also has a significant impact on quality of life and is commonly misdiagnosed in clinical practice due to its complicated pathogenesis. In the present study, we performed non-targeted plasma metabolomics analysis of cervicitis in both plasma samples obtained from human patients and plasma samples from a phenol mucilage induced rat model of cervicitis, using ultra-performance liquid chromatography coupled to quadrupole time-of-flight tandem mass spectrometry. In addition to differences in histopathology, we identified differences in the metabolic profile between the cervicitis and control groups using unsupervised principal component analysis and orthogonal projections to latent structures discriminant analysis. These results demonstrated changes in plasma metabolites, with 27 and 22 potential endogenous markers identified in rat and human samples, respectively. The metabolic pathway analysis showed that linoleic acid, arachidonic acid, ether lipid, and glycerophospholipid metabolism are key metabolic pathways involved in cervicitis. This study showed the rat model was successfully created and applied to understand the pathogenesis of cervicitis.
Cervicitis is an extremely common gynecological disorder in women aged 20–40 years, which puts women at high risk of sexually transmitted infections and can induce a series of reproductive system disorders, such as endometritis, salpingitis, pelvic inflammatory disease, chorioamnionitis, and other complications during pregnancy (Jayakumar,
In recent years, the diagnosis of cervicitis is commonly inaccurate, and women with the disorder may not receive effective treatment. Metabolomics has attracted increasing attention among researchers and become an effective and accurate tool for identifying biomarkers of many diseases, including cancers, metabolic disorders, and infectious diseases (Huang et al.,
In general, metabolomics studies depend on various high-throughput techniques, such as liquid chromatography tandem mass spectrometry (LC-MS/MS), nuclear magnetic resonance spectroscopy (NMR), and gas chromatography-mass spectrometry (GC-MS) (Lee et al.,
In fact, to investigate mechanism of action of the drugs or pro-drugs in clinical, it could be time-consuming, laborious, and difficult to recruit patients. Researchers often apply animal models to study related diseases in the early stage. A rat model could be easier and more repeatable to operate with relevant experiments. Some tests are not ethical to perform on human and therefore a rat model is good. To compare similarities between human patients and a rat model may be indicative for capturing the metabolic pathway in organism and specific biomarkers. Based on the similarities, a further clinical research could be more ambitious and targeted. To investigate the detailed metabolomics profile of cervicitis and identify potential biomarkers, a plasma metabolomics was applied using UPLC-QTOF-MS/MS with high resolution. In our study, we compared the metabolomics profiles of cervicitis in both human patients and a rat model of cervicitis induced by phenol mucilage.
Methanol and acetonitrile (analytical gradient grade) for lipid chromatography were purchased from Merck (Darmstadt, Germany). Deionized water was produced using a Mill-Q ultrapure water system (Millipore, USA). HPLC grade formic acid was obtained from Tianjin Kermel Chemical Reagent Company (Tianjin, China). 2-Chloro-L-phenylalanine for use as an internal standard (IS) was provided by Shanghai Macklin Biochemical Company (Shanghai, China). Standard eicosapentaenoic acid, palmitoleic acid, glycocholic acid, gamma-Linolenic acid, arachidonic acid, thymidine, linoleic acid, L-Phenylalanine, L-Tryptophan, and taurocholic acid were purchased from Shanghai Yuanye Biotechnology Co., Ltd.
This study was carried out in accordance with the recommendations of guidelines of the experimental animal ethics committee of Jiangxi University of traditional Chinese Medicine. The protocol was approved by the experimental animal ethics committee of Jiangxi University of traditional Chinese Medicine. Specific pathogen free (SPF) Sprague–Dawley rats (female, 180–220 g) were obtained from the Laboratory Animal Center of Wuhan University (Wuhan, China). Prior to the experiment, all rats were acclimated for 1 week under standard laboratory conditions. Subsequently, 40 rats were randomly divided into cervicitis model and control groups. In the rat model, cervicitis was induced by phenol mucilage according to a previously described method (Ma et al.,
Cervical tissue samples were collected from rats on day 7 after establishing the cervicitis model. The tissues were processed and embedded in paraffin blocks. Sections (Thickness, 5 μm) sections were prepared and mounted on slides, deparaffinized in xylene, and dehydrated in alcohol before staining with hematoxylin and eosin (HE). Histopathological analysis of the tissues from control and cervicitis model rats was performed by examination under Olympus CX31 microscope (Olympus Corporation, Japan).
Eye orbital venous blood samples were collected into eppendorf tube (EP tube) which is coated with heparin sodium from the rats on day 7 after establishing the cervicitis model. Plasma was obtained after 20 min by centrifugation at 4,500 r/min for 10 min at 4°C. All plasma samples were stored at −80°C prior to sample preparation.
A working IS solution of 2-chloro-L-phenylalanine (5.31 μg/mL) was prepared in methanol. Plasma samples (50 μL) were added to 200 μL of the working IS solution. A total of 780 μL rat plasma sample (20 μL of each rat plasma sample, one from model group died in the experimental progress) were added to 3,120 μL of the working IS solution to generate a quality control (QC) sample for validating the reproducibility of the method and UPLC-QTOF-MS/MS stability. Pretreated samples were vortexed for 3 min, and then centrifuged (15,000 r/min, 4°C) for 10 min. The supernatant was transferred into a sample bottle and stored at 4°C for MS analysis of cervicitis rat metabolomics.
This study was carried out in accordance with the recommendations of guidelines of the Ethics Committee of the Affiliated Hospital of Jiangxi Institute of Traditional Chinese Medicine, with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the Ethics Committee of the Affiliated Hospital of Jiangxi Institute of Traditional Chinese Medicine. Plasma sample collection of patients was conducted in Affiliated Hospital of Jiangxi Institute of Traditional Chinese Medicine from March 1, 2016 to February 28, 2017. A total of 193 patients with the following inclusion and exclusion criteria were enrolled.
Human plasma sample (50 μL) were added to 200 μL of the working IS solution. 20 μL of each human plasma sample were added to 3,200 μL of the working IS solution to obtain a QC sample. Pretreated samples were vortexed for 3 min, and then centrifuged (15,000 r/min, 4°C) for 10 min. The supernatant was transferred into a sample bottle and stored at 4°C for MS analysis of human cervicitis metabolomics.
The UPLC analysis was carried out on an ACQUITY H-CLASS instrument (Waters Corp., Milford, MA, USA) equipped with an automatic degasser, a quaternary pump, and an autosampler. An ACQUITY UPLC™ HSS T3 column (100 × 2.1 mm, 1.7 μm; Waters Corp.) was applied for chromatographic separation. The mobile phases consisted of 0.1% formic acid/water (A) and acetonitrile (B). The mobile phase gradient was as follows: 0–3 min, 5–20% B; 3–5 min, 20–40% B; 5–9 min, 40–60% B; 9–16 min, 60–65% B; 16–18 min, 65–80% B; 18–21 min, 80–95% B; 21–23 min, 95–5% B; and 23–25 min, 5% B. The flow rate was set to 0.35 mL/min, with an injection volume set to 5 μL, and the column oven set at 30°C.
MS/MS detection was conducted on a Triple TOF™ 5,600+ system (equipped with a Duo Spray source) for ions in both positive and negative modes with high resolution (AB SCIEX, Foster City, CA, USA). In the positive mode, the electrospray ionization was applied with the following parameters: ion spray voltage, 4,500 V; ion source temperature, 500°C; curtain gas, 25 psi; nebulizer gas (GS 1), 50 psi; heater gas (GS 2), 50 psi; and declustering potential (DP), 80 V. In the information dependent acquisition (IDA) experiment, the collision energy (CE) was set at 35 eV, and the collision energy spread (CES) was (±) 10 eV. In the negative mode, the electrospray ionization was applied with the following parameters: ion spray voltage, −4,500 V; ion source temperature, 500°C; curtain gas, 25 psi; GS 1, 50 psi; GS 2, 50 psi; and DP, −100 V. In the IDA, CE was set at −30 eV, CES was (±) 10 eV. In both the positive and negative ion modes, the mass ranges were set at m/z 50–1,250 Da for TOF-MS scans and TOF MS/MS scans. The MS/MS fragmentation was selected from the eight most intense ions for each TOF-MS scan. Dynamic background subtraction (DBS) was applied to match the IDA tests for UPLC-QTOF-MS/MS.
Prior to the plasma analysis, the precision of the instrument and the method repeatability were validated by duplicate analysis of six injections QC samples prepared as described previously. To investigate plasma stability, the QC sample was detected at 0, 6, 12, 18, 24, and 48 h, after preparation. In addition, QC samples were analyzed every 10 injections during plasma sample analysis in both the positive and negative modes. The retention time and intensity of each peak were determined using PeakView software 1.2.0 with XIC manager (AB SCIEX) and statistical analysis of relative standard deviations (RSD) was performed to validate the analytical method (Table
All the plasma samples were analyzed by UPLC-QTOF-MS/MS and the raw data were processed by MarkerView v1.2.1 software (AB SCIEX). The data processing involved retention time correction and sample normalization using the IS 2-chloro-L-phenylalanine. The processed data were exported from MarkerView v1.2.1 software, and then imported into the SIMCA-P 14.1 (Umetrics, Sweden) to perform multivariate statistical data analysis. All the data was scaled using the pareto scaling algorithm and autofitted for multivariate analysis. First, unsupervised principal component analysis (PCA) was performed to create an overview, and a DModX was applied to remove outliers. Supervised orthogonal partial least squares-discriminant analysis (OPLS-DA) was then applied to distinguish the contribution of the detected variables to the discrimination between the groups (Li et al.,
Following screening with two-tailed independent Student's
As shown in Figure
Representative H&E stain of cervix sections from control group rat and cervicitis group rat on 7th day: the lowercase letter a-e means pathological features in model group.
Prior to plasma sample detection, the QC samples of rat and human were detected to validate the reproducibility of the method and the stability of UPLC-QTOF-MS/MS system, respectively. During the detection, the QC samples were inserted between every 10 experimental samples to monitor the batches. The plasma samples of rat and human were detected separately. The total ion chromatograms (TICs) of QC sample injections are shown in the supplementary material (see Figure
Figures
Overview of the rat plasma samples:
The OPLS-DA model was built to distinguish the metabolites that contributed to discrimination of the rat sample profile. Differential metabolites (VIP > 1) were then screened as contributive variables for apparent discrimination. Those filtered metabolites were subjected to independent
Identification of potential biomarkers of rat plasma samples between control group and cervicitis module group.
1 | 3-Methyl-5-propyl-2-furanundecanoic acid | 18.63 | C19H32O3 | −1.1 | [M+H]+ | 1.02 | 1.19E-06 | 0.904 |
2 | Acetylcarnitine |
1.11 | C9H17NO4 | −2.6 | [M+H]+ | 1.15 | 1.49E-03 | 0.786 |
3 | Etiocholanolone |
16.71 | C19H30O2 | −0.5 | [M+NH4]+ | 2.87 | 3.29E-10 | 0.991 |
4 | LysoPC(18:2) | 10.48 | C26H50NO7P | −3.1 | [M+H]+ | 10.22 | 4.41E-04 | 0.801 |
5 | LysoPC(18:3) |
11.25 | C26H48NO7P | −4.2 | [M+H]+ | 2.48 | 1.71E-09 | 0.971 |
6 | LysoPC(20:4) | 10.55 | C28H50NO7P | −4.7 | [M+H]+ | 10.75 | 8.20E-05 | 0.813 |
7 | LysoPC(20:5) | 10.47 | C28H48NO7P | −3.6 | [M+H]+ | 2.14 | 8.73E-11 | 0.976 |
8 | LysoPC(22:6) | 10.51 | C30H50NO7P | −4.4 | [M+H]+ | 4.22 | 7.30E-03 | 0.742 |
9 | PC(O-18:1/2:0) | 15.77 | C28H56NO7P | −3.5 | [M+H]+ | 1.32 | 8.81E-04 | 0.809 |
10 | SM(d18:0/16:1) | 20.19 | C39H79N2O6P | −1.2 | [M+H]+ | 7.74 | 2.92E-03 | 0.803 |
11 | Stearoylcarnitine | 15.11 | C25H49NO4 | −1.9 | [M+H]+ | 1.21 | 7.00E-10 | 0.976 |
12 | Tetracosahexaenoic acid | 9.96 | C24H36O2 | −2.6 | [M+H]+ | 1.95 | 1.35E-02 | 0.684 |
13 | Tryptophan | 2.7 | C11H12N2O2 | −1.7 | [M+H]+ | 1.25 | 4.48E-02 | 0.692 |
14 | Pregnenolone | 9.44 | C21H32O2 | −2.8 | [M+H]+ | 2.34 | 9.94E-03 | 0.691 |
15 | Tetradecanoylcarnitine | 9.7 | C21H41NO4 | −3.1 | [M+H]+ | 1.08 | 3.40E-02 | 0.655 |
16 | 20-Hydroxyeicosatetraenoic acid | 13.18 | C20H32O3 | −0.4 | [M-H]- | 1.45 | 4.55E-02 | 0.629 |
17 | 3b,7a-Dihydroxy-5b-cholanoic acid | 9.93 | C24H40O4 | −0.9 | [M-H]– | 2.01 | 1.85E-02 | 0.675 |
18 | 9,10-Epoxyoctadecenoic acid | 11.95 | C18H32O3 | −3.4 | [M-H]– | 3.86 | 3.55E-04 | 0.997 |
19 | Arachidonic acid | 8.38 | C20H32O2 | −1.4 | [M-H]– | 1.35 | 4.47E-02 | 0.622 |
20 | Eicosapentaenoic acid | 18.62 | C20H30O2 | −2.1 | [M-H]– | 1.70 | 2.55E-02 | 0.705 |
21 | Glycocholic acid | 6.74 | C26H43NO6 | −1.8 | [M-H]– | 1.26 | 1.24E-02 | 0.734 |
22 | LysoPE(0:0/20:0) | 14.72 | C25H52NO7P | −1.6 | [M-H]– | 1.55 | 1.47E-02 | 0.718 |
23 | PI(20:4/0:0) | 11.12 | C29H49O12P | −1 | [M-H]– | 7.49 | 3.93E-09 | 0.958 |
24 | S-(PGA2)-glutathione | 14.63 | C30H47N3O10S | 0.3 | [M-H]– | 1.15 | 2.10E-04 | 0.803 |
25 | Taurocholic acid | 6.1 | C26H45NO7S | −1.8 | [M-H]– | 2.68 | 2.20E-03 | 0.845 |
26 | Thymidine | 1.83 | C10H14N2O5 | −0.3 | [M-H]– | 1.40 | 1.96E-05 | 0.904 |
27 | 3-Carboxy-4-methyl-5-propyl-2-furanpropionic acid | 5.81 | C12H16O5 | −3.6 | [M-H]– | 2.24 | 3.55E-03 | 0.553 |
Changes for rat potential biomarkers between control group and cervicitis group (RN, control group; RC, cervicitis group).
ROC analysis of rat potential biomarkers (
All the 27 potential biomarkers were subjected to perform metabolic pathway analysis (MetPA) using the Kyoto Encyclopedia of Genes and Genomes (KEGG) online database and MetaboAnalyst 3.0 (Xia and Wishart,
Overview of metabolic pathway analysis:
As shown in Figure
Overview of the human plasma samples:
Based on OPLS-DA models for both the positive and negative ion modes, significant differentially expressed metabolites were identified in the human sample profile. In total, 22 metabolites that adhered to the parameters of VIP > 1 and
Identification of potential biomarkers of human plasma samples between healthy women and cervicitis patients.
1 | 1-Acetoxy-2-hydroxy-16-heptadecyn-4-one | 11.25 | C19H32O4 | 0.3 | [M+H]+ | 3.62 | 5.86E-13 | 0.993 |
2 | 9-Decenoylcarnitine | 6.33 | C17H31NO4 | 2.5 | [M+H]+ | 1.99 | 1.27E-02 | 0.805 |
3 | Acetylcarnitine |
0.9 | C9H17NO4 | 0.9 | [M+H]+ | 1.87 | 5.63E-04 | 0.775 |
4 | Cortisol | 5.92 | C21H30O5 | 1.5 | [M+H]+ | 1.11 | 3.41E-02 | 0.692 |
5 | Etiocholanolone |
16.9 | C19H30O2 | 1 | [M+NH4]+ | 2.05 | 5.55E-08 | 0.983 |
6 | Linoelaidyl carnitine | 10.44 | C25H45NO4 | 2.1 | [M+H]+ | 2.27 | 9.78E-04 | 0.795 |
7 | L-Phenylalanine | 1.9 | C9H11NO2 | −0.2 | [M+H]+ | 1.01 | 8.81E-03 | 0.771 |
8 | L-Valine | 0.78 | C5H11NO2 | 0.2 | [M+H]+ | 1.48 | 1.96E-06 | 0.910 |
9 | LysoPC(18:3) | 11.34 | C26H48NO7P | −0.9 | [M+H]+ | 1.16 | 3.73E-03 | 0.801 |
10 | LysoPC(P-18:0) | 12.83 | C26H54NO6P | −0.3 | [M+H]+ | 1.25 | 4.04E-02 | 0.701 |
11 | PC(O-18:1/2:0) | 15.99 | C28H56NO7P | −0.5 | [M+H]+ | 1.61 | 6.38E-03 | 0.780 |
12 | Phytosphingosine | 7.46 | C18H39NO3 | 3.5 | [M+H]+ | 3.36 | 6.16E-05 | 0.894 |
13 | Vaccenyl carnitine | 11.83 | C25H47NO4 | 0.8 | [M+H]+ | 2.44 | 6.37E-04 | 0.822 |
14 | 12,13-Dihydroxy-9-octadecenoic acid | 19.24 | C18H34O4 | 1.2 | [M-H]– | 1.46 | 1.61E-02 | 0.675 |
15 | 9-Hydroxy-10,12-octadecadienoic acid | 12 | C18H32O3 | 2.6 | [M-H]– | 1.58 | 7.37E-03 | 0.735 |
16 | 3-Oxoandrostan-17-yl hydrogen sulfate | 7.12 | C19H30O5S | 1.9 | [M-H]– | 2.28 | 3.98E-04 | 0.787 |
17 | gamma-Linolenic acid | 18.79 | C18H30O2 | −1.3 | [M-H]– | 1.66 | 2.01E-02 | 0.777 |
18 | Linoleic acid | 20.17 | C18H32O2 | 0.1 | [M-H]– | 1.27 | 3.71E-02 | 0.677 |
19 | LysoPE(18:1/0:0) | 11.93 | C23H46NO7P | 0 | [M-H]– | 2.08 | 6.06E-04 | 0.814 |
20 | LysoPE(18:2/0:0) | 10.39 | C23H44NO7P | 3.4 | [M-H]– | 1.12 | 1.25E-02 | 0.713 |
21 | Palmitoleic acid | 19.51 | C16H30O2 | 1.2 | [M-H]– | 1.60 | 3.66E-02 | 0.724 |
22 | PI(20:4/0:0) |
11.31 | C29H49O12P | −0.7 | [M-H]– | 3.68 | 3.32E-07 | 0.782 |
Changes for human potential biomarkers between health group and cervicitis group (HN, health human group, HC, cervicitis human group).
ROC analysis of human potential biomarkers (
The 22 identified potential biomarkers were imported into MetaboAnalyst 3.0 for pathway analysis. For the human plasma samples, metabolic pathways were identified as linoleic acid metabolism, steroid hormone biosynthesis, ether lipid metabolism, alpha-linolenic acid metabolism, glycerophospholipid metabolism, and phenylalanine metabolism. An overview of the pathway analysis is shown in Figure
In current, diagnostic tests for
The results has displayed that there were some overlaps between the metabolic analysis of the human and rat cervicitis, namely, glycerophospholipid metabolism, ether lipid metabolism, steroid hormone biosynthesis. In addition, arachidonic acid metabolism and linoleic acid metabolism were interacted closely. Based on the metabolomics profiling and pathway analysis, a metabolite pathway map was constructed (Figure
The metabolic pathway networks of potential biomarkers in response to cervicitis, The word in green means enzyme according to KEGG (
As it is shown, there are some differences between metabolite pathways of the human and rat cervicitis to some extent. The metabolomics profiling has clarified that rat cervicitis refers to primary bile acid biosynthesis, tryptophan metabolism, pyrimidine metabolism, and purine metabolism. On the other hand, human cervicitis was revealed to be related with alpha-linolenic acid metabolism, and phenylalanine metabolism. This study also revealed some potential biomarkers in rat cervicitis or human cervicitis such as tryptophan, glycocholic acid, L-Valine, L-Phenylalanine, etc.
Glycerophospholipid metabolism, which is widely found in many species, was identified as an important pathway in both of human and rat cervicitis in this study. Our results revealed the involvement of a series of lysophosphatidylcholines (LysoPCs), including LysoPC (18:2), LysoPC (18:3), LysoPC (20:4), LysoPC 20:5), LysoPC (22:6). Lysophosphatidylcholine is a monoglycerophospholipid in which a phosphorylcholine moiety occupies a glycerol substitution site and is generated by the degradation of glycerophosphocholines by phospholipase A(2)[PLA(2)]. There are significant amounts of lysophosphatidylcholine in plasma and several studies have indicated that it may be a proinflammatory mediator, causing inflammatory responses through disrupting endothelial barrier function (Huang et al.,
Both the human and rat cervicitis were involved with the metabolic pathway of ether lipid metabolism. As is shown in Tables
Both the human and rat cervicitis were involved with the metabolic pathway of steroid hormone biosynthesis. It is acutely regulated by pituitary trophic hormones and other steroidogenic stimuli (Stocco,
As shown in Figures
As a form of gynecological inflammation, the pathogenesis of cervicitis is related to arachidonic acid (AA) metabolism. The polyunsaturated, essential fatty acid AA and its metabolites play a central role in regulating inflammatory signaling pathways (Ma et al.,
Sometimes, it would be extremely difficult to comprehensively understand the clinical pathogenesis of the disease. The progress of sample collection and selection is also time-consuming and arduous. And it is especially complex to research the mechanism of action of pro-drugs or active constituents in holism. Without any targets, it could be even more difficult. Therefore, researching a clinical disease by building a corresponding animal model can put through an abecedarian exploration and thus provide a reliable foundation for subsequent clinical study. In this study, the metabolic pathway of rat cervicitis model, to some extent, is in accordance with those of human cervicitis, which could provide a novel perspective for searching effective mechanism for cervicitis of drugs or active constituents in clinical.
In this study, plasma metabolomics profiling of both cervicitis patients and a rat model of the disease was successfully established based on UPLC-QTOF-MS/MS as an appropriate technique for the identification of potential biomarkers of cervicitis. Furthermore, the metabolomics profile of the rat model of cervicitis provided some important information for the investigation of human cervicitis. Our results suggest that the metabolic pathways involved in cervicitis include AA, ether lipid, glycerophospholipid, and linoleic acid metabolism. In addition, AA, linoleic acid, lysophosphatidylcholine, PI (20:4/0:0) were implicated as potential biomarkers of cervicitis for use in clinical practice. In addition, this study showed the rat model was successfully created and applied to understand the pathogenesis of cervicitis. However, the role of these biomarkers in the pathogenesis of cervicitis requires confirmation in further proteomics and transcriptomics studies.
XZ wrote this main manuscript text and performed the data analysis. The animal experiment including histopathological analysis was conducted by XZ and JL, together. And the human plasma sample was collected by BX and BW. In addition, SL gave the contribution to plasma sample detection. As for data process, it is conducted by YY and MH. HO contributed significantly to analysis and manuscript preparation. WX designed the work that led to the submission, acquired data, and played an important role in interpreting the results. YF revised the manuscript and approved the final version. And SY contributed to the conception of the study.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer GP and handling Editor declared their shared affiliation.
The Supplementary Material for this article can be found online at:
Total ion chromatogram (TIC) of 16 QC sample injections:
Total ion chromatogram (TIC):
MS/MS spectrometry of standard and metabolite.
Retention time and intensity of eight typical peaks extracted from 16 QC sample injections.