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PXD003526

PXD003526 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleProteotyping of microbial communities reveals the correlations between the microorganisms and the process parameters
DescriptionBackground: Methane yield and biogas productivity of biogas plants depend on microbial community structure and functionality, substrate supply, and general process parameters. Little is known, however, about the correlations between microbial community function and the process parameters. To close this knowledge gap the microbial community of 40 industrial biogas plants was evaluated by a metaproteomics approach in this study. Results: Liquid chromatography coupled to tandem mass spectrometry (Elite Hybrid Ion Trap Orbitrap) enabled the identification of 3138 metaproteins belonging to 162 biological processes and 75 different taxonomic orders. Therefore, database searches were performed against UniProtKB/Swiss-Prot and several metagenome databases. Subsequent clustering and principal component analysis of these data allowed to identify four main clusters associated to mesophilic and thermophilic process conditions, upflow anaerobic sludge blanket reactors and sewage sludge as substrate. Observations confirm a previous phylogenetic study of the same biogas plant samples that was based on 16S-rRNA gene by De Vrieze et al. (2015) (De Vrieze, Saunders et al. 2015). Both studies described similar microbial key players of the biogas process, namely Bacillales, Enterobacteriales, Bacteriodales, Clostridiales, Rhizobiales and Thermoanaerobacteriales as well as Methanobacteriales, Methanosarcinales and Methanococcales. In addition, a correlation study and a Gephi graph network based on the correlations between the taxonomic orders and process parameters suggested the presence of various trophic interactions, e.g. syntrophic hydrogen transfer between Thermoanaerobacteriales and Methanomicrobiales. For the elucidation of the main biomass degradation pathways the most abundant 1% of metaproteins were assigned to the KEGG map 1200 representing the central carbon metabolism. Additionally, the effect of the process parameters (i) temperature, (ii) organic loading rate (OLR), (iii) total ammonia nitrogen (TAN) and (iv) sludge retention time (SRT) on these pathways was investigated. For example high TAN correlated with hydrogenotrophic methanogens and bacterial one-carbon metabolism, indicating syntrophic acetate oxidation. Conclusion: This study shows the benefit of large-scale proteotyping of biogas plants, enabling the identification of general correlations between the process parameters and the microbial community structure and function. Changes in the level of microbial key functions or even in the microbial community type represent a valuable hint for process problems and disturbances.
HostingRepositoryPRIDE
AnnounceDate2016-08-03
AnnouncementXMLSubmission_2016-08-03_04:00:38.xml
DigitalObjectIdentifier
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportUnsupported dataset by repository
PrimarySubmitterRobert Heyer
SpeciesList scientific name: Acyrthosiphon pisum (Pea aphid); NCBI TaxID: 7029;
ModificationListiodoacetamide derivatized residue
InstrumentLTQ Orbitrap Elite
Dataset History
RevisionDatetimeStatusChangeLog Entry
02016-01-26 03:59:43ID requested
12016-04-19 09:16:53announced
22016-08-03 04:00:40announcedUpdated publication reference for PubMed record(s): 27462366.
Publication List
Heyer R, Benndorf D, Kohrs F, De Vrieze J, Boon N, Hoffmann M, Rapp E, Schl, ΓΌ, ter A, Sczyrba A, Reichl U, Proteotyping of biogas plant microbiomes separates biogas plants according to process temperature and reactor type. Biotechnol Biofuels, 9():155(2016) [pubmed]
Keyword List
curator keyword: Biological
submitter keyword: Biogas, Biogas Plant, Anaerobic Digestion, Complex Microbial Community
Contact List
Dirk Benndorf
contact affiliationOtto von Guericke University Magdeburg
contact emailbenndorf@mpi-magdeburg.mpg.de
lab head
Robert Heyer
contact affiliationOvGU
contact emailheyer@mpi-magdeburg.mpg.de
dataset submitter
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Dataset FTP location
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