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. 2023 Feb 27:13:1088850.
doi: 10.3389/fimmu.2022.1088850. eCollection 2022.

Transcriptomics and metabolomics analysis reveal the anti-oxidation and immune boosting effects of mulberry leaves in growing mutton sheep

Xiaopeng Cui  1 , Yuxin Yang  1 , Minjuan Zhang  1 , Shuang Liu  1 , Hexin Wang  1 , Feng Jiao  1 , Lijun Bao  1 , Ziwei Lin  1 , Xinlan Wei  1 , Wei Qian  1 , Xiang Shi  1 , Chao Su  1 , Yonghua Qian  1
Affiliations

Transcriptomics and metabolomics analysis reveal the anti-oxidation and immune boosting effects of mulberry leaves in growing mutton sheep

Xiaopeng Cui et al. Front Immunol. .

Abstract

Introduction: Currently, the anti-oxidation of active ingredients in mulberry leaves (MLs) and their forage utilization is receiving increasing attention. Here, we propose that MLs supplementation improves oxidative resistance and immunity.

Methods: We conducted a trial including three groups of growing mutton sheep, each receiving fermented mulberry leaves (FMLs) feeding, dried mulberry leaves (DMLs) feeding or normal control feeding without MLs.

Results: Transcriptomic and metabolomic analyses revealed that promoting anti-oxidation and enhancing disease resistance of MLs is attributed to improved tryptophan metabolic pathways and reduced peroxidation of polyunsaturated fatty acids (PUFAs). Furthermore, immunity was markedly increased after FMLs treatment by regulating glycolysis and mannose-6-phosphate pathways. Additionally, there was better average daily gain in the MLs treatment groups.

Conclusion: These findings provide new insights for understanding the beneficial effects of MLs in animal husbandry and provide a theoretical support for extensive application of MLs in improving nutrition and health care values.

Keywords: anti-oxidation; glycolysis; immunity; mulberry leaves; peroxidation of polyunsaturated fatty acids; tryptophan metabolism.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
DEMs from Con vs. TR1. Upregulated, downregulated and total numbers of DEMs from Con vs. TR1 (A), the 20 leading DEMs from Con vs. TR1 (B), a correlation heat map between the 20 leading DEMs from Con vs. TR1 and their indexes of antioxidant performance (C).
Figure 2
Figure 2
DEMs from Con vs. TR2. Upregulated, downregulated and total numbers of DEMs from Con vs. TR2 (A), the 20 leading DEMs from Con vs. TR2 (B), a correlation heat map between the 20 leading DEMs from Con vs. TR2 and their indexes of antioxidant performance (C).
Figure 3
Figure 3
Peroxidation of PUFAs and tryptophan metabolism. Elevated metabolites are highlighted in red, reduced metabolites are shown in blue; the contents of painted green or red metabolites from top 20 DEMs and antioxidant biochemical indexes are displayed in heat map (*p<0.05, **p<0.01, * and ** are TR1 or TR2 compared to Con). (MLs, mulberry leaves; FMLs, fermented mulberry leaves; DMLs, dried mulberry leaves; LP, Lactobacillus plantarum; LAB, lactic acid bacteria; PUFA, polyunsaturated fatty acids; ALA, α linolenic acid; ARA, arachidonic Acid; CPT1/CPT2, carnitine palmitoyltransferase 1/2; NFA, medium-chain fatty acid; 5-HTP, 5-hydroxytryptophan; 5-HT, serotonin; AAAD, aromatic amino acid decarboxylase; TPH1/2, tryptophan hydroxylase 1/2).
Figure 4
Figure 4
DEGs related with peroxidation of PUFAs. Module analysis of DEMs related with PUFAs metabolism and all filtered genes (Underlined modules in red represent selective modules; A, carnitine C8:1; B, 8-iso-prostaglandin F2α; C, 11β-prostaglandin F2α; D, 8-iso-prostaglandin F2β; E, (±) 8-HETE; F, 13-HOTrE) (A), network map analysis of selective twelve DEGs and DEMs related with PUFAs metabolism (circle size represents absolute log2FC (Con vs TR1) value; blue, red and green divisions in every circle are on behalf of contents of some DEGs or DEMs in Con, TR1,TR2 in turn; The thickness of the connecting wire represents the degree of connectivity) (B) and the relative expression levels of selective twelve target DEGs in three groups (*represents p<0.05, ** represents p<0.01, ns represents no differences) (C).
Figure 5
Figure 5
Indexes of immune properties and DEGs related to immune response. Immune indexes of serum (A) a transition from IgM to IgG in immune B cells over the course of immune response (Heat maps show the relative amounts of substances in group Con, TR1 and TR2 from left to right; * represent p<0.05, indicative of the significant difference by comparing TR1 or TR2 to Con) (B), kegg enrichment analysis of all DEGs from TR1 vs. Con (C), Circular correlation analysis of six selective DEGs from top 4 kegg pathway and immune indexes of serum (D), Relative expression levels of six selective DEGs related to immune response (E) (* represents p<0.05, ** represents p<0.01, ns represents no differences in histograms).
Figure 6
Figure 6
Glycolysis and the mannose-6-P pathway in immune function. Heat maps show the relative amounts of substances in group Con, TR1 and TR2 from left to right; * represent p<0.05, indicative of the significant difference by comparing TR1 or TR2 to Con; M1, type 1 macrophages; M2, type 2 macrophages; Treg, regulatory T cells; P, phosphatase.
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