A proper dose of selenium yeast supplementation ameliorates the depression in laying performance during the late laying period
To explore the effect of selenium yeast supplementation on production performance in aged laying hens, we administered a selenium-deficient diet for 6 weeks to obtain the selenium deficient hens. Immediately following selenium-deficient treatment, the Se content in plasma has dramatically dropped and then remained at a lower status for another 4 weeks (Fig. 1a), suggesting that the Se in aged laying hens has depleted. Then, a total number of 375 selenium-exhausted aged laying hens were fed selenium-deficient (SD), selenium yeast (SY), and sodium selenite (SS) diet for 12 weeks. Resulting in the gradual decline of the laying performance during the supplementation period (Fig. 1b). Within 4 weeks, no significant differences in laying performance were found, while being significantly higher in the SY0.30 group than the SS0.45 group and SY0.15 group after 8-week and 12-week supplementation, respectively (Fig. 1b). These results revealed that 0.30 mg/kg selenium yeast supplementation alleviate the depression in laying performance during the late laying period. We further investigated Se status in ileum after Se supplementation. The Se content in Se supplementation of higher dose had dramatically increased compared to the SD group (Fig. 1c). Meanwhile, the Se content in the SY group was higher than the SS group at the same dose (Fig. 1c). These data highlighted that the Se deposition in ileum is dose-dependent on the dietary Se intake, and compared with inorganic selenium, selenium yeast has a well-absorbed characteristic.
In general, the peaking production of commercial laying hens usually remains at the age of 60 weeks, and after that period the laying rate and egg quality begin to decline . Thus, age may be one of the leading factors causing egg performance reduction. Additionally, we investigated the effect of Se supplementation on ileum aging by testing β-galactosidase activity. There were no significant differences between the SD group and the SY groups (Fig. 1d, e). Interestingly, a significant difference was observed between the SS group and the SY group (Fig. 1f), suggesting that different forms of Se supplementation may have reversed effects on ileum aging.
Transcriptome analysis revealed selenium yeast supplementation may affect metabolic pathways and immune response in the ileum in aged laying hens
To figure out the effects of different doses and forms of Se, we analyzed the gene expression profile of ileum in aged laying hens under Se supplementation using RNA-sEq. Compared with the SD group, 1857(538 upregulated; 1319 downregulated), 627(207 upregulated; 420 downregulated) and 3305(1379 upregulated; 1926 downregulated) differentially expressed genes (DEGs) were obtained in SY0.15 group, SY0.30 group and SY0.45 group, respectively (Fig. 2a and Table S1). Simultaneously, 366 DEGs were shared among three groups. To define the biological functions of all DEGs in the SY groups, GO term and KEGG pathway analysis were carried out. The common enriched pathways in three groups were Glycerophospholipid metabolism, Glycerolipid metabolism and DNA-binding transcription factor activity, suggesting selenium yeast supplementation (discarding dose effect) primarily influenced lipid metabolism (Glycerolipid and Glycerophospholipid metabolism) on ileum in aged laying hens (Fig. 2b, Fig. S1a and Table S2). Due to 0.30 mg/kg selenium yeast alleviating the depression in laying performance, we focus on the unique pathways in SY0.30 group. The ion transmembrane transport, calcium ion transport into cytosol, and MAPK signaling pathway were unique in the SY0.30 group (Fig. 2b and Fig. S1a). These results suggested that 0.30 mg/kg selenium yeast probably regulated both the redox status and cell proliferation, and alleviated the depression in laying performance through MAPK signaling pathway and calcium ion transport.
Next, the relationship between Se content and gene expression profile in ileum was analyzed by the weighted gene co-expression network analysis (WGCNA). WGCNA analysis showed that all the expressed genes were segmented into 17 modules and the correlation of each mcodule with Se content was estimated (Fig. 2c, Fig. S1b and Table S3). The expression of genes in the MEbrown and MEdarkgrey module was positively correlated with the Se content of ileum, while it was negatively correlated in MEgreen, MEblue, MEturquoise, and MEdarkred. To understand the features of the correlative gene expression module, we performed GSEA analysis. Co-expressed host genes in the MEbrown module were enriched in functions related to fatty acid metabolism, metabolism of steroids, bile acid metabolic process, and glycerolipid catabolic process, while those in the MEgreen module were related to organs or tissues specific immune response and regulation of T/B cell proliferation (Fig. 2d). Meanwhile, co-expressed host genes in the MEblue module were involved in the carbohydrate transmembrane transporter activity and the activation of matrix metalloproteinases (Fig. 2d). To screen the core genes affected by selenium yeast treatment, we constructed the network structure of genes within modules and assessed the connectivity of host genes to identify hub genes. A total of 68, 5, 634, and 164 candidate hub genes exhibited high intramodular connectivity and significant correlation with Se deposition in ileum were identified from the brown, green, blue, and turquoise module, respectively (Fig. 2e and Fig. S1c). Based on the GO annotation and genes closely related to the metabolism pathway, we further selected the candidate hub genes, such as TXNRD1 (enriched in Selenocompound metabolism pathway), DLD (enriched in Citrate cycle/TCA cycle pathway, and Pyruvate metabolism pathway), ILK and LZTS2 (enriched in regulation of canonical Wnt signaling pathway (Fig. S1d, e). Overall, these data demonstrated that the genes modulated by dietary selenium yeast intake were mainly involved in fatty acid metabolism, immune response, and carbohydrate transmembrane transporter activity, which influenced deeply intestinal digestion and metabolism.
Furthermore, to investigate the alterations of these DEGs patterns with different dose selenium yeast treatment, trend analysis was carried out. The total DEGs were clustered into 10 profiles on the basis of the colored block significant enrichment (P༜0.05) and the same color block with similarity greater than 0.88 (Fig. 2f). The clusters strongly associated with selenium yeast treatment further investigated the biological functions by GSEA. The expression of 199 genes (cluster 3) displayed a decrease at 0.15 mg/kg selenium yeast and an increase at 0.30 mg/kg selenium yeast and then again a decrease at 0.45 mg/kg selenium yeast, which were mainly enriched in the metabolic process (including carbohydrate metabolic process, fatty acid metabolic process, triglyceride metabolic process, and cellular ketone metabolic process), inflammatory response, reactive oxygen species biosynthetic process and developmental cell growth (Fig. 2g and Table S4). The expression of 74 genes (cluster 8) increased during low dose, peaked at 0.15 mg/kg and subsequently decreased at 0.45 mg/kg, returning to the pre-supplementation levels (basal lines). The GSEA results showed that cluster 8 was major enriched in regulation of digestive system process, aging and inflammatory response (Fig. 2f, g). The expression of 44 genes (cluster 9) had a decrease at a dose of 0.15 mg/kg and 0.30 mg/kg and was restored at 0.45 mg/kg, which were predominantly enriched in innate immune response and Wnt signaling pathway (Fig. 2f, g). Additionally, the expression of 89 genes (cluster 10) exhibited an opposite trend compared with the cluster 9, which was majorly enriched in intestinal absorption and digestion, metabolic process (including lipid metabolic process, glycerolipid metabolic process, glycerophospholipid metabolic process, sterol and steroid metabolic process), oxidative stress response and inflammatory response (Fig. 2f, g). These results indicated that the dose of selenium yeast supplementation affected various biological functions.
Generally, selenium yeast is a high-quality organic Se source for animals which is incorporated into proteins structures to improve bioavailability compared with inorganic sources, such as sodium selenite . Differences in the sources of Se may have diverse effects on gene expression of hosts. Thus, we investigated the effect of different Se sources under the adequate Se status in aged laying hens. 586 DEGs were obtained in the SY0.45 group relative to the SS0.45 group (Fig. S1f and Table S1). GO enrichment analysis indicated that the differences between selenium yeast and sodium selenite supplementation were enriched in fatty acid metabolic process, cellular lipid metabolic process, and oxidoreductase activity (Fig. S1g and Table S2). Meanwhile, KEGG analysis suggested that the major differences were in Glycerophospholipid metabolism, Glycerolipid metabolism, PPAR signaling pathway, Arachidonic acid metabolism, mTOR signaling pathway, and Fatty acid degradation in aged laying hens (Fig. S1h and Table S2).
Selenium yeast supplementation may affect the ileal metabolic process by changing the expression of redox and aging genes
On the basis of the above results, we further investigated the mechanism of regulating ileal metabolism and immune function after selenium yeast supplementation. The gut could turn ‘on’ or ‘off’ collections of the genes via epigenetics and receptor-driven transcription factors in response to the perceived environment . Thus, we aimed to detect the genes switched-on or off under different doses of selenium yeast supplementation. NCAN was switched on in 0.15 mg/kg selenium yeast, while ST8SIA6 and LOC101747588 were switched off. BCAN was switched on in 0.30 mg/kg selenium yeast, while CSRP3 was switched off. CDRT1 was switched on in 0.45 mg/kg selenium yeast, while MTNR1B and SLCO1A2 were switched off (Fig. 3a and Table S5). Furthermore, Protein-Protein Interaction (PPI) analysis showed that switched-on genes including NCAN, BCAN, CSF3 and CDRT1 were associated with carbohydrate metabolism or immune response. Switched-off genes including ST8SIA6, SLCO1A2 were associated with carbohydrate biosynthesis and lipid metabolism, respectively (Fig. 3b). These findings suggested that selenium yeast may affect metabolism and immune system of aged laying hens through switching on or off the expression of specific genes.
Dietary intake of Se affected the hierarchical pattern of organ-specific selenoprotein expression [33–36]. Different doses of selenium yeast supplementation can determine tissue Se deposition. Thus, the patterns of selenoprotein gene expression in ileum were examined. Twenty-one selenoprotein genes were divided into three expression patterns. The genes of pattern 1, including TXNRD1, TXNRD2, TXNRD3, DIO1, SELENOO, and SELENOI, decreased in groups with Se supplementation compared with that in SD group. Six selenoprotein genes, GPX4, MSRB1, SELENOF, SELENOT, SELENOK, SELENOS, in the pattern 2 exhibited the highest expression in the SY0.15 group, and decreased when increasing the dose. the expression of nine selenoproteins in pattern 3, namely DIO2, GPX1, GPX3, GPX7, GPX8, MSRB3, SELENOP2, SELENOM, SELENOW, were increased with dose increasing of Se (Fig. 3c). The GSEA analysis showed that the effects of selenium yeast supplementation were associated with the expression of selenoproteins enriched in adipose tissue development, lipid localization, selenoamino acid metabolism and Glycerophospholipid biosynthesis (Fig. 3d and Table S6).
In general, dietary Se supplementation plays an important role in numerous antioxidative and inflammatory processes . Thus, the expression of genes associated with the redox process had to be evaluated (Table S7). The expression of these genes was classed into three patterns and enriched in intestinal absorption, glycerolipid catabolic process, transport of bile salts and organic acids, and regulatory T cell differentiation (Fig. 3e, f and Table S6). In order to explore the effect of Se intake on aging, we analyzed the expression of genes associated with aging under selenium yeast supplementation of different doses (Fig. 3g and Table S7). The functions of these genes were mainly enriched in intestinal absorption, digestive system process, organ or tissue specific immune response, and gluconeogenesis (Fig. 3h and Table S6). These findings provided the evidence that supplementation of selenium yeast may affect the pattern of ileal selenoprotein expression, including the intestinal absorption, the digestive system process and the immune response, by regulating the genes associated to redox and aging process.
Se supplementation modulation of gut microbiota composition and structure in aged laying hens
It is known that dietary Se supplementation can affect the composition of the gut microbiota, while the gut microbiota also influences Se bioavailability and selenoprotein expression in mice [24, 29]. Therefore, in order to assess the relationship between the microbiota and Se supplementation, the 16S rRNA sequencing based on V3-V4 regions was performed. In the comparison between the SD group and SY groups, 1214231 high-quality sequence reads were generated and the length was distributed on 420–440 bp (Figure S2a). The remaining clean tags were clustered into OTUs based on 97% similarity. 217, 237, 212 and 234 OTUs were generated in the SD, SY0.15, SY0.30 as well as SY0.45 group, respectively. 137 OTUs were shared among 4 groups, and 18, 18, 8 and 12 OTUs were unique in the SD, SY0.15, SY0.30 as well as SY0.45 group, respectively (Fig. 4a). Compared with the SD group, supplementation of selenium yeast had no significant effect on the α-diversity of the bacteria community including richness by Chao1 estimation and diversity reflected by the Shannon index (Figure S2b). PLS-DA analysis showed there were significant differences in the composition of the microbiota (Anosim, P = 0.002) after selenium yeast supplementation (Fig. 4b) compared to the SD group, and especially between the latter and SY0.45 group (Anosim, P = 0.013, R = 0.2439), the SY0.15 group and SY0.45 group (Anosim, P = 0.036, R = 0.2221), as well as the SY0.30 group and SY0.45 group (Anosim, P = 0.006, R = 0.3941). Firmicutes at the phylum level was dominated in four groups (Fig. S2c). But compared with the SD group, the decreased level of the phylum Cyanobacteria as well as the increased level of the phylum Proteobacteria and Fusobacteria were observed in each of the SY0.15, SY0.30 and SY0.45 groups (not significant) (Table S8). The relative abundances of the intestinal bacteria at the genus level were further analyzed. The abundances of several bacteria such as Veillonella (P༜0.05) and Campylobacter (P༜0.05) increased in selenium yeast supplementation groups, and selenium yeast supplementation markedly reduced the abundances of both Stenotrophomonas (P༜0.01) and Faecalicoccus (P༜0.05) (Fig. 4c).
Additionally, we examined the effect of inorganic selenium supplementation on composition of the ileum microbiota by 16S rRNA-sEq. The distribution of clean tags length was mainly 420–440 bp (Figure S2d). 155 and 152 OTUs were generated in the SD and SS0.45group, respectively, and 33 and 30 OTUs were both unique in two groups, while 122 OTUs were shared (Fig. 4d). There were no significant differences in the richness and diversity of gut microbiota between the SD group and SS0.45 group (Figure S2e), but microbial community was considerably different (Anosim, P = 0.049, R = 0.2216) (Fig. 4e). Firmicutes was dominated in two groups (Figure S2f). Compared with the SD group, The abundances of Lactobacillus (P༜0.01) and Stenotrophomonas (P༜0.05) were noticeably reduced by sodium selenite supplementation, while Romboutsia (P༜0.01), Turicibacter (P༜0.05), Veillonella (P༜0.05), and Corynebacterium_1 (P༜0.05) were dramatically increased (Fig. 4f). Sodium selenite supplementation also suppressed Actinobacteria phylum and increased Proteobacteria and Cyanobacteria phylum (not significant) (Table S8).
The absorption efficiency of sodium selenite and selenium yeast in the intestine are different. Thus, the effects on intestine microbiota may also be different. As shown in Fig. S2g, the distribution of clean tags length was 420–440 bp. There were 131 shared OTUs between SS0.45 and SY0.45group, while 23 and 36 unique OTUs were gained, respectively (Fig. 4g). Relatively to the SS0.45 group, in the SY0.45 group there was no significant effect on the Chao1, Good coverage, observed species, and PD index of the bacteria community. However, the Shannon and Simpson index were significantly higher in the SS0.45 group (Figure S2h). There were statistical differences in the compositions of gut microbiota between the two groups (Anosim, P = 0.001, R = 0.5296) analyzed by PLS-DA (Fig. 4h). The level of the phylum Cyanobacteria (P༜0.05) has significantly decreased in the SY0.45 group (Table S8). The relative abundances of the intestinal bacteria at the genus level between two groups were further analyzed. The relative abundances of Romboutsia (P༜0.01) and Methylobacterium (P༜0.05) were markedly reduced in the SY0.45 group, while Lactobacillus (P༜0.01) and Escherichia-Shigella (P༜0.05) were dramatically elevated (Fig. 4i). These results suggested that, to some extent, different forms and doses of Se may have distinctive effects on the composition of the respective gut microbiota.
To further understand the function of the altered gut microbiota by Se supplementation in aged laying hens, we carried out PICRUSt analysis based on the microbiota composition. Some enriched pathways, including nitrogen metabolism, MAPK signaling pathway-yeastas well as translation proteins of gut microbiota, were activated by both selenium yeast and sodium selenite supplementation, while the Pentose phosphate pathway was suppressed, compared to the SD group (Fig. 4j, k and Fig. S3). In addition, selenium yeast supplementation may restrain Steroid biosynthesis and metabolism of bothterpenoids and polyketides (Carotenoid biosynthesis), while sodium selenite supplementation may significantly suppress the carbohydrate metabolism (including Glycolysis / Gluconeogenesis, Citrate cycle and Carbohydrate digestion and absorption), lipid metabolism (including Biosynthesis of unsaturated fatty acids, Glycerophospholipid metabolism and Glycerolipid metabolism) as well as metabolism of other amino acids (Selenocompound metabolism and Glutathione metabolism), it also may increase energy metabolism (Oxidative phosphorylation), amino acid metabolism (Cysteine and methionine metabolism) and bacterial movement (Bacterial motility proteins and Bacterial chemotaxis) (Fig. 4j, k and Fig. S3). Moreover, the differences of effect between selenium yeast and sodium selenite were majorly enriched in carbohydrate metabolism (Carbohydrate digestion and absorption, Inositol phosphate metabolism, and Starch and sucrose metabolism), lipid metabolism (Glycerophospholipid metabolism, Glycerolipid metabolism, Sphingolipid metabolism, Biosynthesis of unsaturated fatty acids, and Fatty acid biosynthesis), nucleotide metabolism (Purine metabolism), amino acid metabolism (Glycine, serine and threonine metabolism), other amino acids metabolism (Glutathione metabolism and Selenocompound metabolism), cell cycle (Apoptosis, Cell cycle-Caulobacter, and DNA replication) as well as other biological processes (ABC transporters, Phosphatidylinositol signaling system, and Peroxisome)( Fig. 4l and Fig. S4). These results indicated that Se supplementation may suppress the carbohydrate metabolism (Pentose phosphate pathway) of gut microbiota and increase energy metabolism (Nitrogen metabolism), and that the different forms of Se have distinctive effects on gut microbiota in carbohydrate metabolism, lipid metabolism, energy metabolism, amino acid metabolism, Glutathione metabolism and Selenocompound metabolism.
Correlation of transcriptome and microbiota reveals the effects of selenium yeast supplementation on laying rate and Se deposition in the ileum
To investigate the effect of the interaction between transcriptome and microbiota on the laying rate and ileum Se content of aged laying hens after selenium yeast supplementation, we evaluated the relationship among the ileal transcriptomes, the laying rate, the Se content of ileum and the microbiota. Pearson correlation tests showed there were significant associations between various microbial species and Se content, as well as between some microbial species and the laying rate. The Eubacterium_hallii_group, Mesorhizobium, and Anaerobacillus were positively correlated with Se content in the ileum, while Brevibacterium, Aquabacterium, Faecalicoccus, and Stenotrophomonas were negatively correlated with Se content (Fig. 5a). Moreover, there was a negative correlation between the laying rate and the abundance of Romboutsia, Intestinibacter, Turicibacter, Fusobacyerium, Aeromonas, and Alteromonas, respectively, whilea positive correlation was found between the laying rate and the abundance of Lactobacillus, Anaerovorax, Maritalea, Alteromonas and Geobacter (Fig. 5b). These data indicated that the changes of certain species of microbial in ileum were actually associated to selenium yeast intake and egg production in the aged laying hens.
To further assess the relationship between microbiota and transcriptome, Pearson correlation analysis was performed to investigate the correlations between various pathways form GSEA of four clusters and the abundance of microbial species. The abundance of Mesorhizobium and Bacillus was highly correlated with several pathways (regulation of acute inflammatory response, metallopeptidase activity and regulation of protein oligomerization, etc.) in cluster 3. Meanwhile, interferon-gamma response pathway of cluster 8 was highly associated with the abundance of various microbiota, such as Aliivibrio, Anaerobacillus, Shewanella, Moritella, Psychrilyobacter, Roseiflexus, Anaerovorax, Mycobacterium. The abundance of Paucibacter was hugely correlated with the pathways in cluster 9. The abundance of Methylobacterium, Aeriscardovia, Rhodoplanes and Aerococcus was greatly associated with the pathways of cluster 10. Additionally, the abundance of Psychrobacter was extremely correlated with peptidyl lysine trimethylation of cluster 8 and cellular protein complex disassembly of cluster 10, respectively (Fig. 5c).
To elucidate the relationship between bacterial abundance and switch-on or switch-off genes, the Pearson correlation coefficient was calculated (Fig. 5d). The abundance of Stenotrophomonas, Comamonas, Actinomyces, Acinetobacter, Methylobacterium and Psychrobacter was negatively correlated with the expression of ON genes. However, the abundance of Campylobacter, Ruminococcaceae_UCG.014, RB41 and Eubacterium_hallii_group was positively correlated with the expression of ON genes. Furthermore, the abundance of Acinetobacter, Psychrobacter, Delftia, Paucibacter, Stenotrophomonas, Faecalicoccus, Comamonas, Actinomyces and Methylobacterium had positive correlations with the expression of OFF genes. Alternatively, the abundance of Massilia, RB41, Campylobacter, and Eubacterium_hallii_group had negative correlations with the expression of OFF genes. In brief, selenium yeast supplementation directly influenced the biosynthesis of the selenoprotein. To gain further insight into the relationship between selenoprotein expression and microbiota, we conducted the Pearson correlation coefficient analysis (P༜0.01; R༞0.6) (Fig. 5e). SELENOP2 had positive correlations with almost the whole microbiota, but SELENO had negative correlations with the abundance of Mesorhizobium, Blautia, Campylobacte. The expression of GPX3, MSRB3, GPX8, and SELENOW was positively associated with the abundance of Ruminococcaceae_UCG.013. On the other hand, the Campylobacter was negatively correlated with TXNRD3 gene. These findings indicated that, to some extent, there are interactions between the ON/OFF genes as well as the selenoprotein genes and the specified microbiota, respectively.
In order to provide an initial visualization of the relationships among Se content in the ileum, laying rate, transcriptome pathways of interest and microbiota, we generated a biplot using the R package vegan (Fig. 5f). CCA analysis revealed that the content of Se in the ileum was highly positively correlated with the positive regulation of lymphocyte activation (cluster 9), regulation of digestive system progress (cluster 8) as well as the abundance of Anaerobacillus, Alteromonas, and Loktanella. In contrast, aging (cluster 8), fatty acid metabolic process (cluster 3), and the abundance of Streptococcus, Brevibacterium, Aerococcus, and Devosia were inversely correlated with Se content. Moreover, the laying rate had a positive correlation with positive regulation of the lymphocyte activation (cluster 9), the response to carbohydrate (cluster 9), and the abundance of Mesorhizobium and Paracoccus, while having a negative relationship with fatty acid metabolic progress (cluster 3), the abundance of Streptococcus, Devosia, Aerococcus, and Intestinibacter.