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ABSTRACT:
PROVIDER: PRJNA476054 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:In order to identify metabolites descriptive of alterations of the working themperature during the process of anaerobic digestion, we performed untargeted metabolomics on samples of sewage sludge collected from two reactors working in parallel but with different temperature settings.
2021-11-26 | ST002004 | MetabolomicsWorkbench
Project description:Population dynamics of methanogenic genera was investigated in pilot anaerobic digesters. Cattle manure and two-phase olive mill wastes were codigested at a 3:1 ratio in two reactors operated at 37 ï¾°C and 55 ï¾°C. Other two reactors were run with either residue at 37 ï¾°C. Sludge DNA extracted from samples taken from all four reactors on days 4, 14 and 28 of digestion was used for hybridisation with the AnaeroChip, an oligonucleotide microarray targeting those groups of methanogenic archaea that are commonly found under mesophilic and thermophilic conditions (Franke-Whittle et al. 2009, in press, doi:10.1016/j.mimet.2009.09.017).
2010-11-10 | E-MEXP-2453 | biostudies-arrayexpress
Project description:Anaerobic co-digestion of sewage sludge and food waste Metagenome
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Project description:Anaerobic digestion sludge Metagenome
| PRJNA703818 | ENA
Project description:Anaerobic digestion sludge Metagenome
| PRJNA231891 | ENA
Project description:Two parallel anaerobic digestion lines were designed to match a "bovid-like" digestive structure. Each of the lines consisted of two Continuous Stirred Tank Reactors placed in series and separated by an acidic treatment step. The first line was inoculated with industrial inocula whereas the second was seeded with cow digestive tract contents. After three month of continuous sewage sludge feeding, samples were recovered for shotgun metaproteomic and DNA-based analysis. Strikingly, protein inferred and 16S rDNA tags based taxonomic community profiles were not fully consistent. Principal Component analysis however revealed a similar clustering pattern of the samples, suggesting that reproducible methodological and/or biological factors underlie this observation. The performances of the two digestion lines did not differ significantly and the cow derived inocula did not establish in the reactors. A low throughput metagenomic dataset (3.4x106 reads, 1.1 Gb) was also generated for one of the samples. It allowed a substantial increase of the analysis depth (increase of the spectral identification rate). For the first time, a high level of proteins expressed by members of the "Candidatus Competibacter" group is reported in an anaerobic digester, a key microbial player in environmental bioprocess communities.
2015-08-12 | PXD002420 | Pride
Project description:The anaerobic digestion microbiomes has been puzzling us since the dawn of molecular methods for mixed microbial community analysis. Monitoring of the anaerobic digestion microbiome can either take place via a holistic evaluation of the microbial community through fingerprinting or by targeted monitoring of selected taxa. Here, we compared four different microbial community fingerprinting methods, i.e., amplicon sequencing, metaproteomics, metabolomics and phenotypics, in their ability to reflect the full-scale anaerobic digestion microbiome. The phenotypic fingerprinting reflects a, for anaerobic digestion, novel, single cell-based approach of direct microbial community fingerprinting. Three different digester types, i.e., sludge digesters, digesters treating agro-industrial waste and dry anaerobic digesters reflected different operational parameters. The α-diversity analysis yielded inconsistent results, especially for richness, across the different methods. In contrast, β-diversity analysis resulted in comparable profiles, even when translated into phyla or functions, with clear separation of the three digester types. In-depth analysis of each method's features i.e., operational taxonomic units, metaproteins, metabolites, and phenotypic traits, yielded certain similar features yet, also some clear differences between the different methods, which was related to the complexity of the anaerobic digestion process. In conclusion, phenotypic fingerprinting is a reliable, fast method for holistic monitoring of the anaerobic digestion microbiome, and the complementary identification of key features through other methods could give rise to a direct interpretation of anaerobic digestion process performance.
2021-05-26 | PXD024788 | Pride