A Combined Metabolomic and Proteomic Study Revealed the Difference in Metabolite and Protein Expression Profiles in Ruminal Tissue From Goats Fed Hay or High-Grain Diets

Abstract

Currently, knowledge about the impact of high-grain (HG) feeding on metabolite and protein expression profiles in ruminal tissue is limited. In this study, a combination of proteomic and metabolomic approaches was applied to evaluate metabolic and proteomic changes of the rumen epithelium in goats fed a hay diet (Hay) or HG diet. At the metabolome level, results from principal component analysis (PCA) and PLS-DA revealed clear differences in the biochemical composition of ruminal tissue of the control (Hay) and the grain-fed groups, demonstrating the evident impact of HG feeding on metabolite profile of ruminal epithelial tissues. As compared with the Hay group, HG feeding increased the levels of eight metabolites and decreased the concentrations of seven metabolites in ruminal epithelial tissues. HG feeding mainly altered starch and sucrose metabolism, purine metabolism, glyoxylate and dicarboxylate metabolism, glycerolipid metabolism, pyruvate metabolism, glycolysis or gluconeogenesis, galactose metabolism, glycine, serine and threonine metabolism, and arginine and proline metabolism in ruminal epithelium. At the proteome level, 35 differentially expressed proteins were found in the rumen epithelium between the Hay and HG groups, with 12 upregulated and 23 downregulated proteins. The downregulated proteins were related to fatty acid metabolism, carbohydrate metabolic processes and nucleoside metabolic processes, while most of upregulated proteins were involved in oxidative stress and detoxification. In general, our findings revealed that HG feeding resulted in differential proteomic and metabolomic profiles in the rumen epithelia of goats, which may contribute to better understanding how rumen epithelium adapt to HG feeding.

Rumen function in goats, an example of adaptive capacity

“…Most of the time, it is the association between different complementary approaches which provides most information. For example, by combining metabolomics and proteomic studies, it is possible to get a better knowledge of the role of the rumen epithelium in goats adapted to grain-rich feeding compared to hay feeding (Guo et al, 2019).The joint and simultaneous use of metabolomics and pyrosequencing studies in goats informs about the metabolic pathways preferentially involved in the response to high-grain diets (Zhang et al, 2019), whilst the links between the ruminal bacterial community and metabolites represent a powerful tool in terms of prediction or monitoring of certain nutritional diseases such as acidosis (Mao et al, 2016;Hua et al, 2017). These approaches also make it possible to investigate more finely and specifically via co-culture the key role of microorganisms such as fungi and methanogens, but also the nature of the metabolites produced (Cheng et al, 2013).…”

Understanding the early ontogenetic stages of Mugil liza (Mugilidae): Morphological traits and digestive/metabolic profile of pre‐juveniles after recruitment

“…The existence of specific digestive enzymes (as a link between digestion and absorption of nutrients) is generally related to the nature of the dietary components potentially used in metabolic processes (Cadiz et al, 2018;Calí et al, 2019;Faulk & Holt, 2009;Guo et al, 2019;Karasov & Douglas, 2013). The digestion of key glycogenic substrates (e.g., starch/glycogen) by amylase and membrane-bound disaccharidases in the intestine is a main source of circulating glucose in fish (Bakker et al, 2011;Gominho-Rosa et al, 2015;Polakof et al, 2011Polakof et al, , 2012Steimberg, 2018).…”

Examining the Impacts of CO2 Concentration and Genetic Compatibility on Perennial Ryegrass—Epichloë festucae var lolii Interactions

“…These differences in host-endophyte response between protein and metabolite production highlight the dynamic and complex regulatory processes underscoring the host and endophyte responses to infection and rising CO 2 conditions. Similar differential profiles between proteomic and metabolomic data sets have been observed in diverse biological systems and may be explained by the different tissues used for the analysis or protein turnover rates [91]. For example, we performed metabolome profiling on blade tissue, whereas we performed the proteome profiling on pseudostem tissue, where fungal genes are more highly expressed [77] and where concentrations of the endophyte are greatest [85,[92][93][94].…”