Twenty male Wistar rats (five weeks old, 90-110 g) were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd, Beijing, China. All rats were housed in single cages. The temperature of the animal room was kept at 22±1°C, the relative humidity was 60%, the illumination period was 12 h, and light and dark periods were alternated. After 7 days of adaptive feeding, the 20 rats were randomly divided into two groups. The normal calcium diet group (NCG, 10rats) was fed with a normal calcium diet (0.50% (w/w) calcium), and the low-calcium diet group (LCG) was fed with a low-calcium diet (0.15% (w/w) calcium) for 12 weeks. The animal diets were modified based on the standard AIN-93G diet from Beijing KeAoLiXie Animal Food Co.,Ltd., Beijing, China. The rats were given free access to water, and their food intake was recorded regularly. At the end of the experiment, all rats were anesthetized by intraperitoneal injection of sodium pentobarbital (40 mg/kg body weight) (Tianjin Guangfu Fine Chemical Research Institute) after fasting for 12 hours and were then sacrificed by exsanguination. Blood samples from the abdominal aorta was collected and centrifuged at 3000 rpm (835 g) for 15 min. The serum was separated and stored in a refrigerator at -80 °C. The serum calcium and phosphorus levels of all rats were measured by anautomatic biochemical analyzer (Hitachi 7100 Automatic Biochemistry Analyzer (Hitachi High Technologies, International Trading, Shanghai, China), and PTH levels was detected by an Elisa kit (SUMMUS, Harbin). The left femur of each rat was isolated by dissection. The femur BMDs of rats were measured using dual energy X-ray absorptiometry (Norland XR-36DEXA System; Cooper Surgical, Trumball, CT, USA) in the Second Affiliated Hospital of Harbin Medical University. The study was approved by the Harbin Medical University Institutional Animal Care Committee and performed in accordance with the Harbin Medical University guidelines for the care and use of laboratory animals.
Serum metabolomics by UPLC/Q-TOF MS/MS
Serum metabolomics was performed following a slightly modified protocol described inreference[21,22].
Pretreatment of serum samples
All serum samples were thawed at room temperature and then vortexed for 1min. Then, 1050 μL methanol (HPLC, Thermo Fisher) was added to 350 mL serum to precipitate protein. After vortexing for 1min, all serum samples were centrifuged at12000 r/min for 10 min, and the supernatants were transferred into 2mL tube. After drying with nitrogen, the residue in the 2mL tube was dissolved by 350 μL of a mixed solution of water: acetonitrile (2:1). After centrifugation at 12000 r/min for 10 min, the supernatants were transferred to a sample bottle for testing.
UPLC analysis conditions
Chromatographic separation was performed on a 1.8 μm BEH C18 column (ACQUITY (HSS); Waters Corp., Milford, MA, USA; 2.1 mm × 100 mm) used with an ACQUITY UPLC system (Waters Corp., Milford, MA, USA). Mobile phase A was ultrapure water (containing 0.1% formic acid, Tianjin Comeio); mobile phase B was chromatographically pure acetonitrile (HPLC, Thermo Fisher); and the flow rate was 0.35 mL/min. The metabolites in serum were separated by using the gradient elution method in positive and negative ion mode (Table 2). Each injection was 2 μL, the column temperature was 35°C, and the autosampler temperature was 4°C. Acetonitrile was run every fifth sample as a blank solution, and the serum samples were injected alternately as five NCG and five LCG samples.
Mass spectrometry conditions
Q-TOF MS/MS was performed with Micromass Q-TOF mass spectrometer (Waters Corp., Manchester, UK) using an electrospray ionization (ESI) interface. The MS data were collected in Centroid mode both in positive and negative ion mode. The analytical parameters of Q-TOF mass spectrometry were as follows: capillary voltage 3.0kV (ESI+) / 2.8kV (ESI-); cone voltage 35V; extraction cone voltage 3V; ion source temperature 125°C; desolvation gas temperature 320°C; desolvation gas (N2)flow rate,700L/hr; cone gas (nitrogen) flow, 50 L/h; collision gas, argon; MCP detector voltage, 2350 V; collision energy, 6V; scanning time, 0.4s; and scanning time interval, 0.1 s. To ensure the accuracy and repeatability of the mass-to-charge ratio, a concentration of 200pg/mL leucine-cerebral peptide solution (Waters) was used as the Lock-Spray calibration solution, and the exact mass-to-charge ratios in positive and negative ion modes were respectively [M+H]+=556.2771 and [M+H]- =554.2615. The lock spray frequency was set at 10 seconds, and the lock mass data were averaged over 10 scans for correction. The data acquisition range was m/z 50~1000, and the acquisition time was 0~16 min.
After the data acquisition by the liquid chromatography-mass spectrometer was completed, MakerLynx software (incorporated into the MassLynx software; version 4.1; SCN 714; Waters Corp., USA)was used for peak matching, alignment, and other pretreatment. The ApexTrack peak parameters were set as follows: peak width at 5% height, 1 s; and peak-to-peak baseline noise as calculated automatically. The collection parameters were set as follows: mass window, 0.05 Da; retention time window, 0.2 min; minimum intensity, 80; noise elimination level, 6.0; deisotope data, “Yes”. Data were used for the period of 0.4 to 10.5 mins. After recognition and alignment, the intensity of each ion was normalized to the summed total ion intensity of each chromatogram. The data-reduction process was handled in accordance with the “80% rule”. Multivariate statistical analysis such as principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) was performed using EZ-info software (version 188.8.131.52; June 5, 2008; Waters Corp., USA) to obtain the classification trends of the two groups. SIMCA-P software (version 11.5; Umetrics AB, Umeå, Sweden) was used in across-validation procedure with 200 random permutations for avoiding the overfitting of supervised PLS-DA models. Biomarkers were screened by orthogonal partial least squares (OPLS-DA).
Identification of biomarkers
The accurate mass and MSMS spectrum of the markers were determined by quadrupole/time-of-flight mass spectrometry. Compound databases such as the Human Metabolome Database (HMDB) (http://www.hmdb.ca) and Metlin (http://metlin.scripps.edu/) and ChemSpider (http://www.chemspider.com) were searched by molecular formula or molecular mass to obtain possible compound structures. The chemical structures of the markers were identified from standard compounds based on both retention times and MS/MS spectra.
The serum biochemical indicators and BMD of two groups are expressed as x±SD. The statistical difference between the two groups was analyzed by an independent sample t test. A two-tailed threshold of p<0.05 was considered statistically different between the two groups. The ROC analysis and other statistical analysis were implemented using the R language. Pathway analysis of differential metabolites was performed using the online servers MetaboAnalyst. All analyses including the error bars of three unique metabolites were performed using SPSS software (version 16.0; SPSS Inc., Chicago, IL, USA).