Effect of Dietary Forage to Concentrate Ratios on Dynamic Profile Changes and Interactions of Ruminal Microbiota and Metabolites in Holstein Heifers

Abstract

A better understanding of global ruminal microbiota and metabolites under extensive feeding conditions is a prerequisite for optimizing rumen function and improving ruminant feed efficiency. Furthermore, the gap between the information on the ruminal microbiota and metabolites needs to be bridged. The aim of this study was to investigate the effects of a wide range of forage to concentrate ratios (F:C) on changes and interactions of ruminal microbiota and metabolites. Four diets with different F:C (80:20, 60:40, 40:60, and 20:80) were limit-fed to 24 Holstein heifers, and Illumina MiSeq sequencing and gas chromatography time-of-flight/mass spectrometry were used to investigate the profile changes of the ruminal microbes and metabolites, and the interaction between them. The predominant bacterial phyla in the rumen were Bacteroidetes (57.2 ± 2.6%) and Firmicutes (26.8 ± 1.6%), and the predominant anaerobic fungi were Neocallimastigomycota (64.3 ± 3.8%) and Ascomycota (22.6 ± 2.4%). In total, 44, 9, 25, and 2 genera, respectively, were identified as the core rumen bacteria, ciliate protozoa, anaerobic fungi, and archaea communities across all samples. An increased concentrate level linearly decreased the relative abundance of cellulolytic bacteria and ciliates, namely Fibrobacter, Succinimonas, Polyplastron, and Ostracodinium (q < 0.05), and linearly increased the relative abundance of Entodinium (q = 0.04), which is a non-fibrous carbohydrate degrader. Dietary F:C had no effect on the communities of anaerobic fungi and archaea. Rumen metabolomics analysis revealed that ruminal amino acids, lipids, organic acids, and carbohydrates were altered significantly by altering the dietary F:C. With increasing dietary concentrate levels, the proportions of propionate and butyrate linearly increased in the rumen (P ≤ 0.01). Correlation analysis revealed that there was some utilization relationship or productive association between candidate metabolites and affected microbe groups. This study provides a better understanding of ruminal microbiota and metabolites under a wide range of dietary F:C, which could further reveal integrative information of rumen function and lead to an improvement in ruminant production.

Metatranscriptomic analyses reveal ruminal pH regulates fiber degradation and fermentation by shifting the microbial community and gene expression of carbohydrate-active enzymes

“…In the current study, Entodinium was the predominate protozoa genus in the rumen, which was consistent with previous studies [6,77,78]. Entodinium has been characterized as a starch feeder.…”

“…Ruminal pH was monitored every 4 hours, and the acid infusion rate was varied by animal to achieve a ruminal pH between 6.0 and 6.1. When ruminal pH dropped below 6.0, the infusion rate was decreased by 10 ml/h, and the ruminal pH was rechecked in 30 to 60 minutes. The infusion rate was adjusted upwards if ruminal pH was above 6.1.…”

“…High-concentrate diets can stimulate rumen fermentation by resident microorganisms, producing more volatile fatty acids (VFA) including acetate, propionate, and butyrate and sometimes lactic acid [1,2]. When VFA or lactic acid accumulate in the rumen, ruminal pH will rapidly drop which is associated with altered microbial ecology and metabolic disorders such as clinical or subclinical rumen acidosis [3][4][5][6]. Studies have indicated that the activity or numbers of cellulolytic microbes are inhibited if ruminal pH is less than 6.0, primarily due to the regulation of intracellular pH, resulting in inhibition of cellobiose transport activity [7,8].…”

In vitro study on the effects of condensed tannins of different molecular weights on bovine rumen fungal population and diversity

“…The fungal species diversity (Shannon) and richness (Chao 1) of bovine rumens (control, without CTs) were 0.245 and 152.2, respectively (Table 2): these value are lower than previous reports (Tuckwell et al 2005;Lee et al 2012;Zhang et al 2017) and are likely a consequences of the breeds of animals and feed that affect fungal population dynamics as well as effects of samplings and analytical procedures. Quantitative methods of evaluating the a-diversity (richness and species diversity) of rumen fungi communities indicated that inclusion of different MWs CT fraction showed significant interactions between treatments: higher-MW CT fractions, such as fractions F1 and F2 exhibited lower Chao1 index and Shannon index compared with lower-MW CT fractions (fractions F3, F4 and F5).…”

Untargeted metabolomics analysis of Mucor racemosus Douchi fermentation process by gas chromatography with time‐of‐flight mass spectrometry

“…Among the technologies in metabolomics, gas chromatography with time-of-flight mass spectrometry (GC-TOF/MS) has been widely used due to the advantages of high resolution and sensitivity (Adebo et al, 2018;Ding et al, 2009;Salvatore, Gyong, Tobias, Cataldi, & Oliver, 2010;Sun et al, 2015;Tobias et al, 2009). With the help of the effective method, comprehensive and quantitative analysis of metabolites can be achieved, which can be used to characterize metabolic mechanism at molecular level (Zhang et al, 2017). However, the comprehensive research and optimization of the Douchi fermentation with GC-TOF/MS technology are rarely reported so far.…”