Animals, diets and experiment design
NCG was produced by Beijing Animore Sci. & Tech. Co., Ltd. (Beijing, China). Forty-eight Holstein dairy cows with similar days in milk (154.37 ± 13.56 d), parity (1–3), and body condition score (BCS) were provided by Hong Da dairy farm (Baoding, Hebei). The cows were randomly separated into 4 groups (n = 12 per group) as: control (TMR diet), low dose NCG (LNCG, TMR with NCG 15 g/day per cow), medium dose NCG (MNCG, TMR with NCG 20 g/day per cow) and high dose NCG (HNCG, TMR with NCG 25 g/day per cow). Experimental design was shown in Fig. 1. The detail composition and nutrient level of the basal diet were given in Table S1. The NCG treatment lasted for 60 days. THI was employed as an index of the HS status of the dairy cows. In this study, the THI of cowsheds ranged from 72 to 87.7 (Figure S1), indicating the dairy cows were clearly exposed to HS over the course of the experiment.
Sample Collection And Measurements
Samples of the TMR diets and orts were collected three times every week throughout the experiment period. Feed samples were dried (65 °C, 48 h) and ground for the analyses of DMI, crude protein (CP), ether extract (EE), neutral detergent fiber (NDF), acid detergent fiber (ADF) [17], and contents of calcium (Ca) and phosphorus (P). The measurement methods were accorded to the AOAC [18]. In addition, NDF and ADF were measured by the using of ANKOM-A2000i fiber analyzer (Ankom Technology, Macedon, NY).
Mile yield of each cow was recorded electronically three times every day. Milk samples were collected at the time points of 15, 30, 45 and 60 d through milking at 0600, 1400, and 2000 h in the experiment, and the samples were collected into the aliquot of 50 mL at the proportion of 4:3:3. Milk compositions including fat percentage (MFP), protein percentage (MPP), lactose percentage (LP), somatic cell count (SCC) and urea nitrogen (MUN) were analyzed at the DHI Central of Hebei Animal Husbandry Varieties Workstation (Shijiazhuang, China).
Blood samples (10 mL) were collected from the coccygeal vain into vacuum tubes with or without heparin before morning feeding at the middle (30 day) and end of the experiment (60 day), and then centrifuged (2000 g, 4 °C and 15 min) to obtain the serum and plasma, respectively. The plasma and serum samples were stored at -80 °C until analysis. Serum was used to measure blood biochemistry indexes including glucose (GLU), urea nitrogen (BUN), total protein (TP), albumin (ALB), creatinine (CRE), aspartate aminotransferase (AST), alanine aminotransferase (ALT) and ammonia (BA) by the using of biochemistry analyzer Microlab-300. In addition, antioxidant and immune indexes and heat stress indicators were measured by the corresponding colorimetric methods or ELISA kits provided by Nanjing Jiancheng Biology Engineering Institute (Nanjing, China). Heat stress indicators were composed of triiodothyronine (T3), thyroxine (T4), growth hormone (GH), prolactin (PRL), heat shock protein-70 (HSP-70), cortisol and ascorbic acid. Antioxidant indexes were consisted of total antioxidant capacity (T-AOC), glutathione peroxidase (GSH-Px), malondialdehyde (MDA) and superoxide dismutase (SOD). Immunoglobulins (Ig) including IgG, IgM and IgA were also examined.
Sample Preparation For Metabonomics
Plasma samples were thawed at room temperature prior to analysis. 200 µL of plasma was placed into PE tubes, and then 400 µL of methanol/water (4:1, v/v) was added. Next, the tubes were vortex-mixed and incubated for 1 h at -20 °C, and then centrifuged at 14,000 g for 20 min at 4 °C. The supernatant was collected and dried. Lyophilized powder samples were reconstituted by dissolving in 100 µL of 60% methanol. The samples were vortexed (1 min) and centrifuged (14,000 g, 15 min, 4 °C) to collect the supernatant for metabonomic analysis. Quality control (QC) samples prepared from the pooled supernatant were placed in the analysis sequence.
Metabonomic Data Analysis
Chromatographic separation of plasma was performed with Vanquish ultra high performance liquid chromatograph (UHPLC) system (Thermo, USA). An Accucore HILIC column (2.1 × 150 mm, 2.6 µm) was used in the study. The column was maintained at 40 °C, and the flow rate was 0.3 mL/min. The mobile phase for the positive ion mode was consisted of A (0.1% formic acid, 95% acetonitrile, 10 mM ammonium acetate) and B (0.1% formic acid, 50% acetonitrile, 10 mM ammonium acetate); the negative ion mode was consisted of A (95% acetonitrile, 10 mM ammonium acetate) and B (50% acetonitrile, 10 mM ammonium acetate). The process of linear gradient elution was shown as follows: 0–1 min, 98% A; 1–17 min, 98 − 50% A; 17-17.5 min, 50% A; 17.5–18 min, 50–98% A; 18–20 min, 98% A.
Mass spectrometer used in this study was Q Exactive™ HF-X (Thermo, USA) equipped with an electrospray ionization source (ESI) operating in positive (ESI+) and negative ion modes (ESI-). The MS main properties were set as follows: spray voltage, 3.2 KV; sheath gas flow rate, 35 arb; aux gas flow rate, 10 arb; scan range, m/z of 100–1500; capillary temperature, 320 °C. MS/MS data was acquired in data dependent acquisition (DDA) mode.
Metabonomic data processing and metabolites identification
The MS data was processed by Compound Discovery 2.0 (Thermo, USA) for nonlinear alignment, automatic integration and extraction of the peak intensities. Then, the obtained dataset was imported into SIMCA-P (Umetrics AB, Sweden) for multivariate statistical analysis. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed. Cumulative R2 and Q2 of the PCA and OPLS-DA models were used to evaluate the fitness and predictive capability of the model. Variable importance in projection (VIP) score in the OPLS-DA model was constructed, and the P-value of the candidate metabolite was analyzed by Student’s t-test. Metabolite with VIP > 1 and P < 0.05 was considered to be statistically significant.
According to the exact molecular weight and MS/MS fragmentation pattern data, metabolite identification was carried out through the database search including HMDB (http://www.hmdb.ca/), METILN (https://metlin.scripps.edu), mzCloud (https://www.mzcloud.org/), and Chemspider (http://www.chemspider.com/). KEGG (https://www.kegg.jp/) and HMDB search was conducted to identify the metabolic pathways and biochemical reactions of the metabolites. Pathway analysis was performed by MetaboAnalyst 4.0 (http://www.metaboanalyst.ca/) for further biological interpretation.
Statistical analysis
All the data were analyzed using the MIXED procedure in the SAS software version 9.4 (SAS Institute Inc., Cary, NC). In MIXED model, NCG supplementations were fixed effects and cows were random effects. The PDIFF option adjusted by the Tukey method was included in the LSMEANS statement to account for multiple comparisons among treatments. The linear and quadratic responses to increasing NCG supplementation doses were determined by using specific preplanned contrasts. Data were presented as mean and mean standard error (SEM).Treatment effects were declared significant at P ≤ 0.05, and trends were discussed at 0.05 < P ≤ 0.10.