Dataset Information

Temporal dynamics of fibrolytic and methanogenic rumen microorganisms during in situ incubation of switchgrass determined by 16S rRNA gene profiling.

ABSTRACT: The rumen microbial ecosystem is known for its biomass-degrading and methane-producing phenotype. Fermentation of recalcitrant plant material, comprised of a multitude of interwoven fibers, necessitates the synergistic activity of diverse microbial taxonomic groups that inhabit the anaerobic rumen ecosystem. Although interspecies hydrogen (H2) transfer, a process during which bacterially generated H2 is transferred to methanogenic Archaea, has obtained significant attention over the last decades, the temporal variation of the different taxa involved in in situ biomass-degradation, H2 transfer and the methanogenesis process remains to be established. Here we investigated the temporal succession of microbial taxa and its effect on fiber composition during rumen incubation using 16S rRNA amplicon sequencing. Switchgrass filled nylon bags were placed in the rumen of a cannulated cow and collected at nine time points for DNA extraction and 16S pyrotag profiling. The microbial community colonizing the air-dried and non-incubated (0 h) switchgrass was dominated by members of the Bacilli (recruiting 63% of the pyrotag reads). During in situ incubation of the switchgrass, two major shifts in the community composition were observed: Bacilli were replaced within 30 min by members belonging to the Bacteroidia and Clostridia, which recruited 34 and 25% of the 16S rRNA reads generated, respectively. A second significant shift was observed after 16 h of rumen incubation, when members of the Spirochaetes and Fibrobacteria classes became more abundant in the fiber-adherent community. During the first 30 min of rumen incubation ~13% of the switchgrass dry matter was degraded, whereas little biomass degradation appeared to have occurred between 30 min and 4 h after the switchgrass was placed in the rumen. Interestingly, methanogenic members of the Euryarchaeota (i.e., Methanobacteria) increased up to 3-fold during this period of reduced biomass-degradation, with peak abundance just before rates of dry matter degradation increased again. We hypothesize that during this period microbial-mediated fibrolysis was temporarily inhibited until H2 was metabolized into CH4 by methanogens. Collectively, our results demonstrate the importance of inter-species interactions for the biomass-degrading and methane-producing phenotype of the rumen microbiome-both microbially facilitated processes with global significance.

SUBMITTER: Piao H

PROVIDER: S-EPMC4106096 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Temporal dynamics of fibrolytic and methanogenic rumen microorganisms during in situ incubation of switchgrass determined by 16S rRNA gene profiling.

Piao Hailan H Lachman Medora M Malfatti Stephanie S Sczyrba Alexander A Knierim Bernhard B Auer Manfred M Tringe Susannah G SG Mackie Roderick I RI Yeoman Carl J CJ Hess Matthias M

Frontiers in microbiology 20140722

The rumen microbial ecosystem is known for its biomass-degrading and methane-producing phenotype. Fermentation of recalcitrant plant material, comprised of a multitude of interwoven fibers, necessitates the synergistic activity of diverse microbial taxonomic groups that inhabit the anaerobic rumen ecosystem. Although interspecies hydrogen (H2) transfer, a process during which bacterially generated H2 is transferred to methanogenic Archaea, has obtained significant attention over the last decades ...[more]

PMID: 25101058

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Project description:Subacute rumen acidotic (SARA) conditions are a consequence of high grain feeding. Recent work has shown that the pattern of grain feeding can significantly impact the rumen epimural microbiota. In a continuation of these works, the objective of this study was to determine the role of grain feeding patterns on the colonization and associated changes in predicted functional properties of the fiber-adherent microbial community over a 48 h period. Eight rumen-cannulated Holstein cows were randomly assigned to interrupted or continuous 60%-grain challenge model (n = 4 per model) to induce SARA conditions. Cows in the continuous model were challenged for 4 weeks, whereas cows of interrupted model had a 1-wk break in between challenges. To determine dynamics of rumen fiber-adherent microbial community we incubated the same hay from the diet samples for 24 and 48 h in situ during the baseline (no grain fed), week 1 and 4 of the continuous grain feeding model as well as during the week 1 following the break in the interrupted model. Microbial DNA was extracted and 16SrRNA amplicon (V3-V5 region) sequencing was done with the Illumina MiSeq platform. A significant decrease (P < 0.001) in fiber-adherent rumen bacterial species richness and diversity was observed at the end of a 4 week continuous SARA challenge in comparison to the baseline. A total of 159 operational taxonominc units (OTUs) were identified from the microbial population representing > 0.1% relative abundance in the rumen, 18 of which were significantly impacted by the feeding challenge model. Correlation analysis of the significant OTUs to rumen pH as an indicator of SARA showed genus Succiniclasticum had a positive correlation to SARA conditions regardless of treatment. Predictive analysis of functional microbial properties suggested that the glyoxylate/dicarboxylate pathway was increased in response to SARA conditions, decreased between 24h to 48h of incubation, negatively correlated with propanoate metabolism and positively correlated to members of the Veillonellaceae family including Succiniclasticum spp. This may indicate an adaptive response in bacterial metabolism under SARA conditions. This research clearly indicates that changes to the colonizing fiber-adherent rumen microbial population and their predicted functional genes occur in both the short (48 h) and long term (4 wk) under both continuous and interrupted SARA challenge models.

Project description:BackgroundDistribution and evolutionary history of resistance genes in environmental actinobacteria provide information on intensity of antibiosis and evolution of specific secondary metabolic pathways at a given site. To this day, actinobacteria producing biologically active compounds were isolated mostly from soil but only a limited range of soil environments were commonly sampled. Consequently, soil remains an unexplored environment in search for novel producers and related evolutionary questions.ResultsNinety actinobacteria strains isolated at contrasting soil sites were characterized phylogenetically by 16S rRNA gene, for presence of erm and ABC transporter resistance genes and antibiotic production. An analogous analysis was performed in silico with 246 and 31 strains from Integrated Microbial Genomes (JGI_IMG) database selected by the presence of ABC transporter genes and erm genes, respectively. In the isolates, distances of erm gene sequences were significantly correlated to phylogenetic distances based on 16S rRNA genes, while ABC transporter gene distances were not. The phylogenetic distance of isolates was significantly correlated to soil pH and organic matter content of isolation sites. In the analysis of JGI_IMG datasets the correlation between phylogeny of resistance genes and the strain phylogeny based on 16S rRNA genes or five housekeeping genes was observed for both the erm genes and ABC transporter genes in both actinobacteria and streptomycetes. However, in the analysis of sequences from genomes where both resistance genes occurred together the correlation was observed for both ABC transporter and erm genes in actinobacteria but in streptomycetes only in the erm gene.ConclusionsThe type of erm resistance gene sequences was influenced by linkage to 16S rRNA gene sequences and site characteristics. The phylogeny of ABC transporter gene was correlated to 16S rRNA genes mainly above the genus level. The results support the concept of new specific secondary metabolite scaffolds occurring more likely in taxonomically distant producers but suggest that the antibiotic selection of gene pools is also influenced by site conditions.

Project description:BackgroundRecent evidences have suggested that human microorganisms participate in important biological activities in the human body. The dysfunction of host-microbiota interactions could lead to complex human disorders. The knowledge on host-microbiota interactions can provide valuable insights into understanding the pathological mechanism of diseases. However, it is time-consuming and costly to identify the disorder-specific microbes from the biological "haystack" merely by routine wet-lab experiments. With the developments in next-generation sequencing and omics-based trials, it is imperative to develop computational prediction models for predicting microbe-disease associations on a large scale.ResultsBased on the known microbe-disease associations derived from the Human Microbe-Disease Association Database (HMDAD), the proposed model shows reliable performance with high values of the area under ROC curve (AUC) of 0.9456 and 0.8866 in leave-one-out cross validations and five-fold cross validations, respectively. In case studies of colorectal carcinoma, 80% out of the top-20 predicted microbes have been experimentally confirmed via published literatures.ConclusionBased on the assumption that functionally similar microbes tend to share the similar interaction patterns with human diseases, we here propose a group based computational model of Bayesian disease-oriented ranking to prioritize the most potential microbes associating with various human diseases. Based on the sequence information of genes, two computational approaches (BLAST+ and MEGA 7) are leveraged to measure the microbe-microbe similarity from different perspectives. The disease-disease similarity is calculated by capturing the hierarchy information from the Medical Subject Headings (MeSH) data. The experimental results illustrate the accuracy and effectiveness of the proposed model. This work is expected to facilitate the characterization and identification of promising microbial biomarkers.

Dataset Information

Temporal dynamics of fibrolytic and methanogenic rumen microorganisms during in situ incubation of switchgrass determined by 16S rRNA gene profiling.

Publications

Temporal dynamics of fibrolytic and methanogenic rumen microorganisms during in situ incubation of switchgrass determined by 16S rRNA gene profiling.

Similar Datasets

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