Temperature−humidity index
Heat stress in rabbits can be divided into four grades: no heat stress at THI < 27.8; moderate heat stress at THI from 27.8 to 28.9; severe heat stress at THI from 28.9 to 30.0; and especially severe heat stress at THI > 30 (18). The average daily THI index of the control group was lower than 27.8 (Figure 1), indicating that the experimental rabbits in this group were in a state of no heat stress throughout the experiment. The average daily THI index of the heat stress group was greater than 28.9, and thus the rabbits were in a state of heat stress.
Growth performance
Heat stress treatment reduced the average daily feed intake and average daily gain of the rabbits (P < 0.05), but no difference in feed–gain ratio was observed (P > 0.05; Table 1).
Slaughter performance
The preslaughter body weight, semi-clean slaughter ratio, full-clean slaughter ratio, and liver weight of the experimental group treated with heat stress were lower than those of the control group (P < 0.05; Table 2). No differences in head weight, heart weight, and kidney weight were observed (P > 0.05).
Blood indices
Heat stress treatment increased the concentrations of leptin, cholesterol, HDL, and LDL in serum (P < 0.05), and decreased the serum total protein and immunoglobulin (IgG, IgM, and IgA) contents of the rabbits (Table 3). No effects on serum insulin, glucagon, and glucose contents were observed (P > 0.05).
Physical characteristics of the LTL meat
Heat stress changed the muscle color and increased muscle yellowness (b*, P < 0.05). However, no differences in pHu value, shear force, drip loss ratio, and cooking loss ratio were observed (P > 0.05; Table 4).
Protein metabolism of skeletal muscle
Data quality control and identification
The mass spectrometry data were searched against the uniprot-oryctolagus-cuniculus-filtered-organism-Oryctolagus-cuniculus protein database. The obtained fasta file contained 23,058 sequences. To improve the quality of the analysis results and reduce the false positive rate, Proteome Discoverer 2.2 software was used to filter the search results. Peptide spectrum matches (PSMs) with more than 99% confidence were trusted PSMs, and proteins containing at least one unique peptide segment were trusted proteins. Only the trusted peptides and proteins were retained, and those with false discovery rate > 1% were removed. The total number of spectra in this study was 324,622, matched spectra was 79,888, identified peptides was 18,941, identified proteins was 2463, and quantifiable proteins was 2460 (Table 5).
Protein function annotation
To explore the functional characteristics of the differential proteins, the identified proteins were annotated based on information in the GO, KEGG, COG, and InterProScan databases. In total, 1147 proteins were annotated from these databases (Figure 2).
Protein quantitative analysis
The coefficient of variation (CV), which is the ratio of the standard deviation to the mean, was used to measure the degree of variation of each observed value of a sample, which reflects the dispersion degree of the data and thus is a measure of repeatability. The smaller the CV value, the better the repeatability (Figure 3).
Differential protein analysis
Applying the criteria fold-change (FC) ≥ 1.20 or ≤ 0.84 and P-value ≤ 0.05, seven up-regulated proteins and 122 down-regulated proteins were screened (Table 6). With FC ≥ 1.30 or ≤ 0.77 and P-value ≤ 0.05, four up-regulated proteins and 64 down-regulated proteins were screened. With FC ≥ 1.50 or ≤ 0.67 and P-value ≤ 0.05, two up-regulated proteins (G1SUJ3, Histone H2A; and B7NZF9, Nucleophosmin 1 isoform 1, predicted) and 19 down-regulated proteins were screened (Table 7). Finally, with FC ≥ 2.00 or ≤ 0.50 and P-value ≤ 0.05, no up-regulated proteins and three down-regulated proteins (P01870, Ig gamma chain C region; A0A1Y1B8B3 and A0A1Y1BG72, IgG heavy chain VDJ region, fragment) were screened. For each protein multiple of difference, the log2-transformed FC and log10-transformed absolute P-value was plotted to generate a volcano map (Figure 4).
Enrichment analysis
The most enriched GO terms among the differential proteins were response to stress, extracellular region, and protein binding in the biological process, cellular component, and molecular function categories, respectively (Figure 5). The target genes were identified in the KEGG database to determine the pathways involving the differential proteins. The most enriched pathway was the PI3K/Akt signalling pathway (Figure 6).