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Biology subjects

Lund, P.

Publications and source records attributed to Lund, P..

2 recordsLinked to original sources

Inter- and intra-domain functional redundancy in the rumen microbiome during plant biomass degradation

BackgroundRuminant livestock is a major source of the potent greenhouse gas methane (CH4), produced by the complex rumen microbiome. Using an integrated approach, combining quantitative metatranscriptomics with gas- and volatile fatty acid (VFA) profiling, we gained fundamental insights into temporal dynamics of the cow rumen microbiome during feed degradation.\n\nResultsThe microbiome composition was highly individual and remarkably stable within each cow, despite similar gas emission and VFA profiles between cows. Gene expression profiles revealed a fast microbial growth response to feeding, reflected by drastic increases in microbial biomass, CH4 emissions and VFA concentrations. Microbiome individuality was accompanied by high inter- and intra-domain functional redundancy among pro- and eukaryotic microbiome members in the key steps of anaerobic feed degradation. Methyl-reducing but not CO2-reducing methanogens were correlated with increased CH4 emissions during plant biomass degradation.\n\nConclusionsThe major response of the rumen microbiome to feed intake was a general growth of the whole community. The high functional redundancy of the cow-individual microbiomes was possibly linked to the robust performance of the anaerobic degradation process. Furthermore, the strong response of methylotrophic methanogens is suggesting that they might play a more important role in ruminant CH4 emissions than previously assumed, making them potential targets for CH4 mitigation strategies.

microbiology

The essential genome of Escherichia coli K-12

Transposon-Directed Insertion-site Sequencing (TraDIS) is a high-throughput method coupling transposon mutagenesis with short-fragment DNA sequencing. It is commonly used to identify essential genes. Single gene deletion libraries are considered the gold standard for identifying essential genes. Currently, the TraDIS method has not been benchmarked against such libraries and therefore it remains unclear whether the two methodologies are comparable. To address this, a high density transposon library was constructed in Escherichia coli K-12. Essential genes predicted from sequencing of this library were compared to existing essential gene databases. To decrease false positive identification of essential gene candidates, statistical data analysis included corrections for both gene length and genome length. Through this analysis new essential genes and genes previously incorrectly designated as essential were identified. We show that manual analysis of TraDIS data reveals novel features that would not have been detected by statistical analysis alone. Examples include short essential regions within genes, orientation-dependent effects and fine resolution identification of genome and protein features. Recognition of these insertion profiles in transposon mutagenesis datasets will assist genome annotation of less well characterized genomes and provides new insights into bacterial physiology and biochemistry.\n\nIMPORTANCEIncentives to define lists of genes that are essential for bacterial survival include the identification of potential targets for antibacterial drug development, genes required for rapid growth for exploitation in biotechnology, and discovery of new biochemical pathways. To identify essential genes in E. coli, we constructed a very high density transposon mutant library. Initial automated analysis of the resulting data revealed many discrepancies when compared to the literature. We now report more extensive statistical analysis supported by both literature searches and detailed inspection of high density TraDIS sequencing data for each putative essential gene for the model laboratory organism, Escherichia coli. This paper is important because it provides a better understanding of the essential genes of E. coli, reveals the limitations of relying on automated analysis alone and a provides new standard for the analysis of TraDIS data.

microbiology