Dataset Information

Metaproteome analysis of two synthetic bacterial consortia

ABSTRACT: Two synthetic bacterial consortia (SC) composed by bacterial strains isolated from a natural phenanthrene-degrading consortium (CON), Sphingobium sp. AM, Klebsiella aerogenes B, Pseudomonas sp. Bc-h and T, Burkholderia sp. Bk and Inquilinus limosus Inq were grown in LMM supplemented with 200 mg/L of phenanthrene (PHN) during 72 hours in triplicate.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Sphingobium Sp. Am Inquilinus Limosus Pseudomonas Sp. Burkholderia Sp. Bk Klebsiella Aerogenes

SUBMITTER: Marianela Macchi

LAB HEAD: Bibiana Marina Coppotelli

PROVIDER: PXD022882 | Pride | 2021-09-09

REPOSITORIES: Pride

ACCESS DATA

Publications

Design and evaluation of synthetic bacterial consortia for optimized phenanthrene degradation through the integration of genomics and shotgun proteomics.

Macchi Marianela M Festa Sabrina S Nieto Esteban E Irazoqui José M JM Vega-Vela Nelson E NE Junca Howard H Valacco María P MP Amadio Ariel F AF Morelli Irma S IS Coppotelli Bibiana M BM

Biotechnology reports (Amsterdam, Netherlands) 20210106

Two synthetic bacterial consortia (SC) composed of bacterial strains Sphingobium sp. (AM), Klebsiella aerogenes (B), Pseudomonas sp. (Bc-h and T), Burkholderia sp. (Bk) and Inquilinus limosus (Inq) isolated from a natural phenanthrene (PHN)-degrading consortium (CON) were developed and evaluated as an alternative approach to PHN biodegradation in bioremediation processes. A metabolic network showing the potential role of strains was reconstructed by in silic ...[more]

PMID: 33489789

Similar Datasets

Project description:Background: Although the clinical fingerprints of the BK virus (BKV) infection in kidney transplant recipients (KTRs) has been well documented, the systemic biological machinery involved in this complication is still poorly recognized. Proteomics analysis of urinary extracellular vesicles (EVs) can allow us to better address this knowledge gap. Methods: Twenty-nine adult KTRs with normal allograft function affected by BKV infection (15 with only viremia, 14 with viruria and viremia) and 15 controls (CTR) were enrolled and randomly divided in a training cohort (12 BKV and 6 CTR) used for the mass spectrometry analysis of the EVs protein content and a testing cohort(17 BKV and 9 CTR) used for the biological validation of the proteomic results by ELISA. Results: Mass spectrometry analysis revealed a large protein enrichment (more than 1500) in urinary EVs of BKV patients and controls. Pathway analysis by GSEA revealed that several biological gene ontologies (including immunity, complement activation, renal fibrosis, tubular diseases, epithelial to mesenchymal transition) were able to discriminate BKV versus CTR. Kinase was the only gene ontology annotation term negatively enriched in BKV (with SLK being the most down-regulated protein in BKV). Statistical analysis, then, identified a core panel of 70 proteins (including DNASE2, F12, AGT, CTSH, C4A, C7, FABP4 and BPNT1) able to discriminate the two study groups. Instead, although a set of proteins were able to differentiate patients with BKV viruria from those with both viremia-viruria, the urinary proteomic profile of these patients resulted quite similar between the two sub-groups. ELISA for SLK and ELISA for BPNT1 and DNASE2 validated proteomics results. Conclusions: Our study demonstrated that BK virus infection is able to significantly modify the urinary EVs proteomic profile of KTRs also in a very early stage of the disease (when patients still have normal allograft function and only BK viruria) suggesting, whether possible, to start an early preventive therapeutic approach to minimize the risk of the disease progression. Moreover, some 3 of our identified proteins could be employed in future as early urinary biomarkers and/or new therapeutic targets.

Dataset Information

Metaproteome analysis of two synthetic bacterial consortia

Publications

Design and evaluation of synthetic bacterial consortia for optimized phenanthrene degradation through the integration of genomics and shotgun proteomics.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure