Dataset Information

Tandem mass spectrometry proteotyping of microbial samples isolated from an industrial infrastructure.

ABSTRACT: Tandem mass spectrometry proteotyping of microbial samples isolated from an industrial infrastructure for identifying their species taxonomical rank.

INSTRUMENT(S): LTQ Orbitrap

ORGANISM(S): Cordyceps Confragosa Nevskia Ramosa Ralstonia Pickettii Limnobacter Thiooxidans

SUBMITTER: Jean ARMENGAUD

LAB HEAD: Jean Armengaud

PROVIDER: PXD020976 | Pride | 2021-09-09

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

Items per page:

1 - 5 of 13

Publications

Proteotyping Environmental Microorganisms by Phylopeptidomics: Case Study Screening Water from a Radioactive Material Storage Pool.

Hayoun Karim K Pible Olivier O Petit Pauline P Allain François F Jouffret Virginie V Culotta Karen K Rivasseau Corinne C Armengaud Jean J Alpha-Bazin Béatrice B

Microorganisms 20201004 10

The microbial diversity encompassed by the environmental biosphere is largely unexplored, although it represents an extensive source of new knowledge and potentially of novel enzymatic catalysts for biotechnological applications. To determine the taxonomy of microorganisms, proteotyping by tandem mass spectrometry has proved its efficiency. Its latest extension, phylopeptidomics, adds a biomass quantitation perspective for mixtures of microorganisms. Here, we present an application of phylopepti ...[more]

PMID: 33020444

Similar Datasets

Project description:Background: 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.

			Action	DRS
	F420131.dat	Other
	F420131.mzid.gz	Mzid
	F420132.dat	Other
	F420132.mzid.gz	Mzid
	F420133.dat	Other