The hindgut microbiome contributes to host oxidative stress in postpartum dairy cows by affecting glutathione synthesis process

Abstract

Background: Dairy cows are susceptible to postpartum systemic oxidative stress (OS), which leads to significant production loss and metabolic disorders. The gut microbiota has been linked to host health and stress levels. However, to what extent the gut microbiota is associated with postpartum OS remains unknown. In this study, the contribution of the fecal microbiota to postpartum systemic OS and its underlying mechanisms were investigated by integrating 16S rRNA gene sequencing, metagenomics, and metabolomics in postpartum dairy cattle and by transplanting fecal microbiota from cattle to mice.

Results: A strong link was found between fecal microbial composition and postpartum OS, with an explainability of 43.1%. A total of 17 significantly differential bacterial genera and 19 species were identified between cows with high (HOS) and low OS (LOS). Among them, 9 genera and 16 species showed significant negative correlations with OS, and Marasmitruncus and Ruminococcus_sp._CAG:724 had the strongest correlations. The microbial functional analysis showed that the fecal microbial metabolism of glutamine, glutamate, glycine, and cysteine involved in glutathione synthesis was lower in HOS cows. Moreover, 58 significantly different metabolites were identified between HOS and LOS cows, and of these metabolites, 19 were produced from microbiota or cometabolism of microbiota and host. Furthermore, these microbial metabolites were enriched in the metabolism of glutamine, glutamate, glycine, and cysteine. The mice gavaged with HOS fecal microbiota had significantly higher OS and lower plasma glutathione peroxidase and glutathione content than those orally administered saline or LOS fecal microbiota.

Conclusions: Integrated results suggest that the fecal microbiota is responsible for OS and that lower glutathione production plays a causative role in HOS. These findings provide novel insights into the mechanisms of postpartum OS and potential regulatory strategies to alleviate OS in dairy cows. Video Abstract.

Keywords: Dairy cows; Fecal microbiota transplantation; Glutathione synthesis; Multiomics; Oxidative stress; Transition period.

Fig. 1

The overview of the oxidative stress and fecal microbial composition of postpartum dairy cows. A Study and sampling design of the cow trial. B The oxidative stress index profile of dairy cows at 7 days postpartum. C Taxonomic and phylogenetic trees of the gut microbiome by 16S rRNA gene sequencing. D Study design diagram of the fecal transplantation experiment. E Plasma oxidative stress parameters of mice in the four groups. LOS, cows with lower oxidative stress; HOS, cows with higher oxidative stress; CON, mice orally gavaged with saline; FLOS, mice orally gavaged with fecal microbial suspension from LOS cows; FHOS, mice orally gavaged with fecal microbial suspension from HOS cows. The P value < 0.10 were presented

Fig. 2

The difference in the fecal microbiome between cows with how (HOS) and low oxidative stress (LOS) according to the 16S rRNA gene sequencing data. A Changes in alpha diversity at the genus level. B Changes in beta diversity at the genus level. The p value was tested with ANOSIM. C Community biplot analysis at the family level. D Community biplot analysis at the genus level. E Genus co-occurrence network between LOS and HOS based on Spearman correlation analysis. Each node represents a bacterial genus; node size shows the relative abundance of each genus per group. The line refers to the Spearman coefficient. Red and green lines represent positive and negative interactions between nodes, respectively. Correlations with |rho|> 0.7 are presented

Fig. 3

Gut microbiota divergence between cows with high (HOS) and low oxidative stress (LOS) at the species level based on metagenome sequencing data. A Abundance of significantly different bacterial genera between HOS and LOS. Significant differences were tested by linear discriminant analysis effect size analysis, with linear discriminant analysis (LDA) scores > 2 and a P value < 0.05. B Abundance of significantly different bacterial genera between HOS and LOS. Significant differences were tested by linear discriminant analysis effect size analysis, with linear discriminant analysis (LDA) scores > 2 and a P value < 0.05. C The network of the Spearman correlations between significantly different genera and species and plasma OSI between HOS and LOS cows. Interactions with a P value < 0.05 are presented

Fig. 4

Differential KEGG functions of fecal microbiota between cows with high (HOS) and low oxidative stress (LOS). A Significantly different KEGG pathways of fecal microbiota between HOS and LOS; average transcripts per million of each pathway in HOS and LOS are presented. B Partial least squares-discriminant analysis of the fecal metabolome between HOS and LOS cows. C Volcano map of metabolites identified by the fecal metabolome. D Number of metabolites from different sources. E Metabolic pathway enrichment analysis according to different categories of metabolites belonging to the host, bacteria, or both

Fig. 5

The integration analysis of the significantly differential microbes, microbial function, and metabolites. A The Spearman correlations between the significantly differential microbiota and the enriched metabolic pathways. The genera and species were selected from the significantly differential microbiota that were significantly correlated with oxidative stress status, and the pathways were enriched in the gut microbial functional analysis. *Represents the correlation P value < 0.05, **P value < 0.01, and ***P value < 0.001. B Integration of significantly different metabolic pathways involved in glutathione synthesis between HOS and LOS cows. KEGG Orthology (KO) entries with red and green words represent what was significantly increased and decreased in HOS compared with LOS, respectively, and black words indicate no significant difference observed between the two groups. The metabolites with red words represent the identified metabolites from microbiota or cometabolism by metabolome analysis and increased in the HOS cows. The names of the significant KO entries are as follows: K02591: nitrogenase molybdenum-iron protein beta chain [EC:1.18.6.1], K00266: glutamate synthase (NADPH) small chain [EC:1.4.1.13], K01776: glutamate racemase [EC:5.1.1.3], K01777: proline racemase [EC:5.1.1.4], K07250: 4-aminobutyrate aminotransferase/(S)-3-amino-2-methylpropionate transaminase/5-aminovalerate transaminase [EC:2.6.1.19 2.6.1.22 2.6.1.48], K01620: threonine aldolase [EC:4.1.2.48], K00600: glycine hydroxymethyltransferase [EC:2.1.2.1], K00812: aspartate aminotransferase [EC:2.6.1.1], and K00824: D-alanine transaminase [EC:2.6.1.21], K01919: glutamate–cysteine ligase [EC:6.3.2.2], K01920: glutathione synthase [EC:6.3.2.3], and K11358: aspartate aminotransferase [EC:2.6.1.1]