Serum antioxidant activity and non-specific immunity
As shown in Fig. 1, with the increasing dietary AMP supplemental level, the activities of T-SOD, GSH-Px and lipid LZM in A240 were the highest, which were 0.95 U/mL and 621 µmol mL− 1 and 6.02 µg mL− 1, respectively, which were significantly higher than the CT (P<0.05). CAT and ACP activity in A240 and A480 were significantly higher than those in CT (P<0.05); With the increase of AMP supplemental level, MDA content decreased significantly, and MDA content in A240 and A480 were significantly lower than that in CT (P<0.05).
Characteristics of the High-Throughput Sequencing Data
According to the above serum antioxidant activity and non-specific immune analysis, the A2 group had the most significant effect. Therefore, in this study, we selected the CT and A2 groups for microbial diversity analysis. The sequencing produced 311,872 and 306,857 original sequences were acquired from the AMP and CT, respectively (Table S1). After excluding low quality data, a total of 306,626 clean reads were obtained in the control group, and 311,660 clean reads were obtained in the AMP group. The average effective reads per sample was 93.84% (Table S1), indicating that the gut microbes had high coverage.
A total of 2,478 and 2,499 were identified based on 97% nucleotide sequence similarity the AMP and CT, respectively (Table S1). The OTU of each sample was combined and analyzed for its common and unique OTUs. As shown in Fig. 2, there were 576 OTUs in intestinal flora of each sample, including 484 OTUs unique to CT group and 455 OTUs unique to AMP group (Fig. 2). In addition, there was no statistical difference between the groups (P > 0.05). The rarefaction curve shows that the sequencing amount has basically covered all samples, and the sequencing amount tends to be saturated (Fig. 3a). The number of sequences that met the sequencing conditions reached 80,000, indicating that the depth and quantity of sequencing met the needs of sequencing analysis and covered most of the diversity. In addition, rank–abundance curve was smooth, indicating the uniformity of species distribution in the samples (Fig. 3b).
At phylum level, a total of 28 flora were identified in all samples. However, there are only 7 (Firmicutes, Proteobacteria, Bacteroidetes, Cyanobacteria, Actinobacteria, Verrucomicrobia and Epsilonbacteraeota) phyla in taxa with an abundance of effective tags greater than 1%, and the proportion of other phyla in all tags is usually less than 0.5% (Table S2). Among them, Firmicutes, Proteobacteria and Bacteroidetes were the dominant bacteria (Fig. 4a). Compared with the control group, the abundance of Proteobacteria, Cyanobacteria, Actinobacteria and Verrucomicrobia increased in the AMP group, but the differences were not significant (P > 0.05).
At the genus level, a total of 379 taxa of intestinal flora were identified. The first 10 genera were Arthromitus, Lactobacillus, Romboutsia, Lactococcus, Ruminococcus, Terrisporobacter, CHKCI001, Acinetobacter, Bacillus, and Lachnoclostridium (Fig. 4b). Compared with the control group, the abundance of Halomonas in the AMP groups significantly decreased (P < 0.05) (Fig. 4c).
Alpha-diversity and beta-diversity of gut bacterial communities in tsinling lenok trout
Alpha diversity reflected the species richness and diversity of species in a particular ecosystem. In this study, we used Chao index to estimate intestinal microbial richness, and found that the Chao index, Ace index, Shannon index and Simpson index showed no significant difference between CT group and AMP group compared with the control group, but it showed an upward trend in AMP group (Fig. 5a-5d). The Alpha diversity index can only judge whether there is a significant difference in the overall microbial community structure between two different taxa. However, microbial species is responsible for this difference, requiring analysis of between-group differences. Therefore, to find species with significant differences between groups, we searched for biomarkers by analyzing linear discriminant analysis effect size (LEfSe).
In this study, analysis with LefSe noted several indicator bacteria species associated with each group (Fig. 6). including 23 taxa in the CT (e.g., Prevotellaceae, Bacteroides, Micrococcaceae and Aeromonadales ), 26 taxa in the AMP (e.g., Akkermansia, Akkermansiaceae, Verrucomicrobiales and Actinobacteriia).
Functional analysis
In functional analysis, the abundance of KEGG pathways in the intestinal compartment of the control and AMP groups showed that Systemic lupus erythematosus and Chloroalkane and chloroalkene degradation were significantly increased in the AMP group (Fig. 7).