Metaproteomics of activated sludge from a wastewater treatment plant – A pilot study. Issue 20 (20th August 2015)

• Record Type: Journal Article
• Authors: Püttker, Sebastian; Kohrs, Fabian; Benndorf, Dirk; Heyer, Robert; Rapp, Erdmann; Reichl, Udo; Jagtap, Pratik; Griffin, Tim; Armengaud, Jean
• Is Part Of: Proteomics. Volume 15:Issue 20(2015:Oct.)
• Page Start: 3596
• Page End: 3601
• Publication Date: 2015-08-20
• Subjects: Proteins -- Separation -- Periodicals; Bioinformatics -- Periodicals; Proteomics -- Periodicals; Genomes -- Periodicals; Molecular genetics -- Periodicals; 572.605
• DOI: 10.1002/pmic.201400559
• Languages: English
• ISSNs: 1615-9853

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>In this study, the impact of protein fractionation techniques prior to LC/MS analysis was investigated on activated sludge samples derived at winter and summer condition from a full‐scale wastewater treatment plant (WWTP). For reduction of the sample complexity, different fractionation techniques including RP‐LC (1D‐approach), SDS‐PAGE and RP‐LC (2D‐approach) as well as RP‐LC, SDS‐PAGE and liquid IEF (3D‐approach) were carried out before subsequent ion trap MS analysis. The derived spectra were identified by MASCOT search using a combination of the public UniProtKB/Swiss‐Prot protein database and metagenome data from a WWTP. The results showed a significant increase of identified spectra, enabled by applying IEF and SDS‐PAGE to the proteomic workflow. Based on meta‐proteins, a core metaproteome and a corresponding taxonomic profile of the wastewater activated sludge were described. Functional aspects were analyzed using the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway library by plotting KEGG Orthology identifiers (KO numbers) of protein hits into pathway maps of the central carbon (map01200) and nitrogen metabolism (map00910). Using the 3D‐approach, most proteins involved in glycolysis and citrate cycle and nearly all proteins of the nitrogen removal were identified, qualifying this approach as most promising for future studies. All MS data have been deposited in the ProteomeXchange with identifier PXD001547 (<ext-link ext-link-type="uri" xlink:href="http://proteomecentral.proteomexchange.org/dataset/PXD001547" xlink:type="simple" xmlns:xlink="http://www.w3.org/1999/xlink">http://proteomecentral.proteomexchange.org/dataset/PXD001547</ext-link>).</p> </abstract>