Mass spectrometry data of diabetic rat sperm proteome treated with Gynura procumbens aqueous extract

Ethical statement

This research has obtained ethical approval from the Animal Ethics Committee of Faculty of Medicine, Universiti Kebangsaan Malaysia (FST/2013/MAHANEM/31-JAN./492-FEB.-2013-FEB.-2015). All efforts were made to ameliorate harm to animals, achieved by inducing to imitate diabetes conditions with streptozotocin (STZ) intravenously at a dose of 50 mg/kg bodyweight (BW) in all groups except the control normal group, which was left uninduced.

Source and husbandry of animals

A total of 28 male Sprague Dawley rats aged eight weeks (120–200 g) were used in this study. All rats were proven fertile and provided by the Animal House of Universiti Kebangsaan Malaysia. All animals were acclimatized for seven days, wherein their food pellet (Rat Chow, Barastoc, Ridley, Australia) and drink intakes were given ad libitum. The rats were kept in PVC cages at controlled room temperature with a 12-hour light/12-hour dark cycle.

Experimental design

G. procumbens were harvested from Universiti Kebangsaan Malaysia glass house (2.9300°N, 101.7774°E). The G. procumbens aqueous extract was prepared as described previously³. Briefly, the leaves part of G. procumbens were harvested and dried in the oven for 72 hours at 48°C. The dried leaves then were ground to dust and extracted for three hours at 60°C. The extract produced was in liquid form, later sent for freeze-drying and kept in 4°C for freshness.

Experimental methods and procedures were detailed as previously⁷. Briefly, male Sprague-Dawley rats were used in this study, which were randomly hand-picked and divided into four groups, with seven rats in each group. Randomization was performed in choosing the rats to avoid bias in the experiment. One group served as a normal untreated group (N), while the three other groups were induced with 50 mg/kg BW STZ intravenously for type 1 diabetes induction. The blood glucose level of each rats was measured after 72 hours of STZ induction. Rats with blood glucose level at 13 mmol/L and more were considered as diabetic and used in this study. These diabetic rats served as (i) diabetic-untreated (negative control), (ii) diabetic-metformin treated (positive control) (500 mg/kg BW) and (iii) diabetic-GPAE treated (450 mg/kg BW) groups. Treatment was given via oral gavage for 14 consecutive days after seven days of STZ induction at the Animal House, Universiti Kebangsaan Malaysia. On the 15^th day, all rats were euthanized by inhalation of diethyl ether for sperm protein analysis.

Sample collection and preparation

Sperm protein extraction was performed as described previously⁸. Briefly, sperm samples from each rat were collected separately from the caudal epididymis and minced in Biggers-Whitten-Whittingham medium (91.06 mM Sodium chloride, 4.78 mM Potassium chloride, 2.0 mM Calcium chloride, 1.17 mM potassium phosphate, 2.44 mM Magnesium sulphate, Sodium hydrogen carbonate, 0.25 mM Sodium pyruvate, 21.55 mM Sodium lactate, 5.55 mM glucose, and bovine serum albumin)⁹. Briefly, the samples were incubated in a 5% CO₂ incubator for 30 minutes at 37°C, to allow the sperm to swim up. Sperm samples were then centrifuged at 4000 rpm for 15 minutes and the supernatant was removed. The pellet was mixed with lysis buffer (7 M Urea, 2 M Thiourea, 4% 3-[(3-Cholamidopropyl)-dimethyl-ammonio]-1-propanesulfonate (CHAPS), 0.8% Immobilized pH Gradient (IPG) buffer, 1 mM phenylmethane sulfonyl fluoride (PMSF)). The samples were then centrifuged at 15,000 rpm for 20 minutes at 4°C. The supernatant was collected, added to 60 mM dithiothreitol (DTT) and kept at ­80°C until used. The concentration of sperm proteins was determined using the Bradford assay¹⁰.

SDS-PAGE

A total of 100 µg of the sperm protein samples from each group were used for one-dimensional SDS-PAGE. Protein samples were loaded onto 12.5% SDS-PAGE gels and run for eight minutes or until all the proteins stacked up in the resolving gel. The gel was then cut for trypsin digestion using the in-gel trypsin digestion method¹¹. For this purpose, excised protein bands were treated with DTT for one hour at 57 °C to reduce the disulphide bridges, followed by Iodoacetamide for another hour at room temperature in the dark for alkylation purposes, as previously described¹¹. Gels were rehydrated with 50 mM ammonium bicarbonate and dehydrated with acetonitrile for three times, respectively. Enzymatic digestion was performed by incubating samples with trypsin for 30 minutes at 4 °C in a 1: 50 (w/w) ratio. The digestion products were then incubated with 50 mM ammonium bicarbonate for overnight at 37 °C. Digested peptides were sent for liquid chromatography with tandem mass spectrometry (LC-MS/MS) for protein identification and quantification.

LC-MS/MS analysis

LC-MS/MS analysis was performed as described in Kamaruzaman et al.⁷. Briefly, the peptide samples were analysed using a liquid chromatography (LC) system (UltiMate 3000 RSLCnano, Dionex) coupled to a Linear Trap Quadropole (LTQ) Orbitrap Fusion mass spectrometer (Thermo Fisher, Bremen, Germany). A total of 1.0 µL of digested samples from each group were injected into a reverse phase column (15 cm × 75 µm internal diameter, particle size of 2 µm, 100 Å, C18 PepMap column) and eluted at a flow rate of 300 nL/min. The elution mobile phase composition was 0.1% formic acid in water (solvent A) and 0.1% formic acid in acetonitrile (solvent B). The eluted peptides were separated in 5–40% solvent B for 91 minutes, 95% solvent B for 2 minutes, 95% solvent B for 6 minutes and back to 5% solvent B for 2 minutes. Data were acquired in data dependent mode. Full scan spectra in the range of 310–1800 m/z were acquired. The automatic gain control (AGC) was targeted at 4.0 × 10⁵ with a maximum injection time of 50 ms and 3 seconds in top speed mode, where precursors were selected with a maximum cycle time of 3 seconds. Precursors with an assigned monoisotopic m/z and a charge between 2 and 7 were further analysed. All precursors were filtered using a 20 second dynamic exclusion window with an intensity threshold of 5000. The MS/MS spectra analyses were performed using rapid scan rate and collision-induced dissociation (CID), with normalized collision energy (NCE) set to 30% and high energy collision-induced dissociation (HCD) at 28%, a 1.6 m/z isolation window, AGC targeted at 1.0 × 10² and a maximum injection time of 250 ms.

Protein identification and quantification

Data processing was conducted according to previous studies^12,13. Raw files for each biological replicate were analysed together using the MaxQuant software (version 1.5.3.30)¹⁴. The derived peak list was searched using the Andromeda search algorithm embedded in the MaxQuant workflow. The protein sequence database used for protein identification analysis was the Rattus norvegicus database, obtained from Uniprot database (proteome ID: UP000002494, accessed on February 2016). The MaxQuant parameters were set as enzyme trypsin and allowed up to two miss cleavages. The peptide length was set minimally up to seven amino acids. The spectra search included carbamidomethylation of cysteine as a fixed modification and oxidation of methionine was set as a variable modification. Since no labelling was performed, multiplicity was set to one. Peptide spectrum match (PSM) and protein identification were filtered using a target-decoy approach with a false discovery rate (FDR) of 1 %. The second peptide feature was enabled. The label-free quantification (LFQ) of protein was done using the MaxLFQ algorithm integrated in MaxQuant. Other MaxQuant settings were set as default. All resulting information was reported in the “proteinGroups” output file (proteinGroups.txt in the combined file), containing the full list of identified and quantified proteins. This file has been deposited to the ProteomeXchange Consortium¹⁵ via the PRIDE partner repository with the dataset identifier PXD011373.

The data were further analysed for protein quantification using Perseus software (version 1.5.4.1)¹⁶. The hits to the reverse database, contaminants and proteins identified with modified peptides were eliminated. Then, the LFQ intensity ratios were transformed by log₂. Missing values were imputed by drawing random numbers from a normal distribution to stimulate signals from low abundance proteins, using the default parameters described previously¹². The value of log2 (LFQ ratios) for each sample were averaged and statistically analysed as per Kamaruzaman et al.⁷. In short, data were displayed as mean ± standard error of mean. The statistical analysis for protein LFQ intensities were compared using Perseus software (version 1.5.4.1) (one-way ANOVA, p < 0.05).

Underlying data

Dataset on ProteomeXchange, Accession number PXD01133: https://identifiers.org/px/PXD011373

Rattus norvegicus reference proteome was obtained from Uniprot, Proteome ID UP000002494: https://www.uniprot.org/proteomes/UP000002494.