556 research outputs found

    Metaproteomics of complex microbial communities in biogas plants

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    Production of biogas from agricultural biomass or organic wastes is an important source of renewable energy. Although thousands of biogas plants (BGPs) are operating in Germany, there is still a significant potential to improve yields, e.g. from fibrous substrates. In addition, process stability should be optimized. Besides evaluating technical measures, improving our understanding of microbial communities involved into the biogas process is considered as key issue to achieve both goals. Microscopic and genetic approaches to analyse community composition provide valuable experimental data, but fail to detect presence of enzymes and overall metabolic activity of microbial communities. Therefore, metaproteomics can significantly contribute to elucidate critical steps in the conversion of biomass to methane as it delivers combined functional and phylogenetic data. Although metaproteomics analyses are challenged by sample impurities, sample complexity and redundant protein identification, and are still limited by the availability of genome sequences, recent studies have shown promising results. In the following, the workflow and potential pitfalls for metaproteomics of samples from full-scale BGP are discussed. In addition, the value of metaproteomics to contribute to the further advancement of microbial ecology is evaluated. Finally, synergistic effects expected when metaproteomics is combined with advanced imaging techniques, metagenomics, metatranscriptomics and metabolomics are addressed

    From Hubble to Snap Parameters: A Gaussian Process Reconstruction

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    By using recent H(z)H(z) and SNe Ia data, we reconstruct the evolution of kinematic parameters H(z)H(z), q(z)q(z), jerk and snap, using a model-independent, non-parametric method, namely, the Gaussian Processes. Throughout the present analysis, we have allowed for a spatial curvature prior, based on Planck 18 [1] constraints. In the case of SNe Ia, we modify a python package (GaPP) [2] in order to obtain the reconstruction of the fourth derivative of a function, thereby allowing us to obtain the snap from comoving distances. Furthermore, using a method of importance sampling, we combine H(z)H(z) and SNe Ia reconstructions in order to find joint constraints for the kinematic parameters. We find for the current values of the parameters: H0=67.2±6.2H_0 =67.2 \pm 6.2 km/s/Mpc, q0=−0.60−0.18+0.21q_0 = -0.60^{+0.21}_{-0.18}, j0=0.90−0.65+0.75j_0=0.90^{+0.75}_{-0.65}, s0=−0.57−0.31+0.52s_0=-0.57^{+0.52}_{-0.31} at 1σ\sigma c.l. We find that these reconstructions are compatible with the predictions from flat Λ\LambdaCDM model, at least for 2σ\sigma confidence intervals.Comment: 18 pages, 6 figure

    MPA_Pathway_Tool: User-Friendly, Automatic Assignment of Microbial Community Data on Metabolic Pathways

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    Taxonomic and functional characterization of microbial communities from diverse environments such as the human gut or biogas plants by multi-omics methods plays an ever more important role. Researchers assign all identified genes, transcripts, or proteins to biological pathways to better understand the function of single species and microbial communities. However, due to the versality of microbial metabolism and a still-increasing number of newly biological pathways, linkage to standard pathway maps such as the KEGG central carbon metabolism is often problematic. We successfully implemented and validated a new user-friendly, stand-alone web application, the MPA_Pathway_Tool. It consists of two parts, called ‘Pathway-Creator’ and ‘Pathway-Calculator’. The ‘Pathway-Creator’ enables an easy set-up of user-defined pathways with specific taxonomic constraints. The ‘Pathway-Calculator’ automatically maps microbial community data from multiple measurements on selected pathways and visualizes the results. The MPA_Pathway_Tool is implemented in Java and ReactJS

    A Robust and Universal Metaproteomics Workflow for Research Studies and Routine Diagnostics Within 24 h Using Phenol Extraction, FASP Digest, and the MetaProteomeAnalyzer

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    The investigation of microbial proteins by mass spectrometry (metaproteomics) is a key technology for simultaneously assessing the taxonomic composition and the functionality of microbial communities in medical, environmental, and biotechnological applications. We present an improved metaproteomics workflow using an updated sample preparation and a new version of the MetaProteomeAnalyzer software for data analysis. High resolution by multidimensional separation (GeLC, MudPIT) was sacrificed to aim at fast analysis of a broad range of different samples in less than 24 h. The improved workflow generated at least two times as many protein identifications than our previous workflow, and a drastic increase of taxonomic and functional annotations. Improvements of all aspects of the workflow, particularly the speed, are first steps toward potential routine clinical diagnostics (i.e., fecal samples) and analysis of technical and environmental samples. The MetaProteomeAnalyzer is provided to the scientific community as a central remote server solution at www.mpa.ovgu.de.Peer Reviewe

    Structural characterization of a-plane Zn1−xCdxO (0 < x <0.085) thin films grown by metal-organic vapor phase epitaxy.

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    Zn1−xCdxO(11math0) films have been grown on (01math2) sapphire (r–plane) substrates by metal-organic vapor phase epitaxy. A 800-nm-thick ZnO buffer, deposited prior to the alloy growth, helps to prevent the formation of pure CdO. A maximum uniform Cd incorporation of 8.5 at. % has been determined by Rutherford backscattering spectrometry. Higher Cd contents lead to the coexistence of Zn1−xCdxO alloys of different compositions within the same film. The near band-edge photoluminescence emission shifts gradually to lower energies as Cd is incorporated and reaches 2.93 eV for the highest Cd concentration (8.5 at. %). The lattice deformation, due to Cd incorporation, has been described using a new reference frame in which the lattice distortions are directly related to the a-plane surface structure. Cd introduction does not affect the c lattice parameter but expands the lattice along the two perpendicular directions, [11math0] and [math100], resulting in a quadratic volume [email protected] [email protected]
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