TY - JOUR

T1 - Temporal dynamics of volatile fatty acids profile, methane production, and prokaryotic community in an in vitro rumen fermentation system fed with maize silage

AU - Dhakal, Rajan

AU - Alves Neves, Andre Luis

AU - Sapkota, Rumakanta

AU - Khanal, Prabhat

AU - Ellegaard-Jensen, Lea

AU - Winding, Anne

AU - Hansen, Hanne Helene

PY - 2024

Y1 - 2024

N2 - Anaerobic in vitro fermentation is widely used to simulate rumen kinetics and study the microbiome and metabolite profiling in a controlled lab environment. However, a better understanding of the interplay between the temporal dynamics of fermentation kinetics, metabolic profiles, and microbial composition in in vitro rumen fermentation batch systems is required. To fill that knowledge gap, we conducted three in vitro rumen fermentations with maize silage as the substrate, monitoring total gas production (TGP), dry matter degradability (dDM), and methane (CH4) concentration at 6, 12, 24, 36, and 48 h in each fermentation. At each time point, we collected rumen fluid samples for microbiome analysis and volatile fatty acid (VFA) analysis. Amplicon sequencing of 16S rRNA genes (V4 region) was used to profile the prokaryotic community structure in the rumen during the fermentation process. As the fermentation time increased, dDM, TGP, VFA concentrations, CH4 concentration, and yield (mL CH4 per g DM at standard temperature and pressure (STP)) significantly increased. For the dependent variables, CH4 concentration and yield, as well as the independent variables TGP and dDM, polynomial equations were fitted. These equations explained over 85% of the data variability (R2 > 0.85) and suggest that TGP and dDM can be used as predictors to estimate CH4 production in rumen fermentation systems. Microbiome analysis revealed a dominance of Bacteroidota, Cyanobacteria, Desulfobacterota, Euryarchaeota, Fibrobacterota, Firmicutes, Patescibacteria, Proteobacteria, Spirochaetota, and Verrucomicrobiota. Significant temporal variations in Bacteroidota, Campylobacterota, Firmicutes, Proteobacteria, and Spirochaetota were detected. Estimates of alpha diversity based on species richness and the Shannon index showed no variation between fermentation time points. This study demonstrated that the in vitro fermentation characteristics of a given feed type (e.g., maize silage) can be predicted from a few parameters (CH4 concentration and yield, tVFA, acetic acid, and propionic acid) without running the actual in vitro trial if the rumen fluid is collected from similar donor cows. Although the dynamics of the rumen prokaryotes changed remarkably over time and in accordance with the fermentation kinetics, more time points between 0 and 24 h are required to provide more details about the microbial temporal dynamics at the onset of the fermentation.

AB - Anaerobic in vitro fermentation is widely used to simulate rumen kinetics and study the microbiome and metabolite profiling in a controlled lab environment. However, a better understanding of the interplay between the temporal dynamics of fermentation kinetics, metabolic profiles, and microbial composition in in vitro rumen fermentation batch systems is required. To fill that knowledge gap, we conducted three in vitro rumen fermentations with maize silage as the substrate, monitoring total gas production (TGP), dry matter degradability (dDM), and methane (CH4) concentration at 6, 12, 24, 36, and 48 h in each fermentation. At each time point, we collected rumen fluid samples for microbiome analysis and volatile fatty acid (VFA) analysis. Amplicon sequencing of 16S rRNA genes (V4 region) was used to profile the prokaryotic community structure in the rumen during the fermentation process. As the fermentation time increased, dDM, TGP, VFA concentrations, CH4 concentration, and yield (mL CH4 per g DM at standard temperature and pressure (STP)) significantly increased. For the dependent variables, CH4 concentration and yield, as well as the independent variables TGP and dDM, polynomial equations were fitted. These equations explained over 85% of the data variability (R2 > 0.85) and suggest that TGP and dDM can be used as predictors to estimate CH4 production in rumen fermentation systems. Microbiome analysis revealed a dominance of Bacteroidota, Cyanobacteria, Desulfobacterota, Euryarchaeota, Fibrobacterota, Firmicutes, Patescibacteria, Proteobacteria, Spirochaetota, and Verrucomicrobiota. Significant temporal variations in Bacteroidota, Campylobacterota, Firmicutes, Proteobacteria, and Spirochaetota were detected. Estimates of alpha diversity based on species richness and the Shannon index showed no variation between fermentation time points. This study demonstrated that the in vitro fermentation characteristics of a given feed type (e.g., maize silage) can be predicted from a few parameters (CH4 concentration and yield, tVFA, acetic acid, and propionic acid) without running the actual in vitro trial if the rumen fluid is collected from similar donor cows. Although the dynamics of the rumen prokaryotes changed remarkably over time and in accordance with the fermentation kinetics, more time points between 0 and 24 h are required to provide more details about the microbial temporal dynamics at the onset of the fermentation.

U2 - https://doi.org/10.3389/fmicb.2024.1271599

DO - https://doi.org/10.3389/fmicb.2024.1271599

M3 - Journal article

JO - Frontiers in Microbiology

JF - Frontiers in Microbiology

SN - 1664-302X

ER -