Proteomics

Dataset Information

0

20160330_Lentinus crinitus Secretome


ABSTRACT: The analysis of fungi secreted proteins has been increasingly employed as a powerful strategy in the prospecting of new catalysts with potential biotechnological application. Since enzyme production is strongly modulated by several factors such as pH, available nutrients, water content, oxygen levels and temperature, the evaluation of growth conditions is of utmost importance to achieve optimal enzyme production. Here, a non-sequenced wood-rotting fungus, L. crinitus, was selected as a model organism for secretome analysis by means of in vitro enzymatic assays and in-depth characterization via proteomics. For enzyme production, the fungus was cultured with several types and concentrations of carbon and nitrogen sources and variable water content. Five different carbon substrates (glucose, maltose, starch, sucrose, carboxymethylcellulose (CMC), glycerol and fructose) and three nitrogen containing compounds (urea, sodium nitrate and ammonium chloride) were used as substitutes of the original carbon and nitrogen sources in culture media. Interestingly, the biomass yield as well as the array of secreted proteins differed drastically under different growing conditions. A mixture of soluble secreted extracts derived from different culture conditions was analyzed both by shotgun mass spectrometry and through protein separation by two-dimensional gel electrophoresis (2DE) prior to identification via LC-MS/MS. Proteins were identified by sequence homology searches using mass spectrometry (MS)-driven BLAST. The spectrum of secreted enzymes comprised various types of CAZymes (carbohydrate-active enzymes), oxidase/reductases, proteases, lipase/esterases, proteins with non-related functions thereby classified as miscellany proteins and hypothetical or unknown predicted proteins. Although pre-separation by 2DE improved the number of identifications (protein map of 150 spots corresponding to 171 identifications) compared to the shotgun approach (98 identifications) both strategies revealed similar distribution of proteins within the functional categories described above. Culture media with reduced water content stimulated the expression of oxidases/reductases such as Lac, MnP, GMC oxidoreductases and glyoxal oxidase while hydrolases were induced during submerged fermentation. The diversity of proteins observed within both the CAZyme and oxidoreductase groups revealed in this fungus a powerful arsenal of enzymes dedicated to the breakdown and consumption of lignocellulose. Moreover, further secretome characterization after sequencing and analysis of the L. crinitus genome can potentially lead to the discovery of novel enzymes of industrial and biotechnological interest. Importantly, information on sequencing data could also reveal novel enzymes which production is strongly stimulated only in specific growing conditions.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Lentinus Crinitus

SUBMITTER: Mirta Sousa  

LAB HEAD: Jaime Paba

PROVIDER: PXD003901 | Pride | 2016-12-23

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
RAW.zip Other
SEARCH_ProteomeDiscoverer.zip Other
uniprot-Polyporales.fasta Fasta
Items per page:
1 - 3 of 3
altmetric image

Publications

Analysis of the Biotechnological Potential of a Lentinus crinitus Isolate in the Light of Its Secretome.

Cambri Geison G   de Sousa Mirta Mittelstedt Leal MM   Fonseca Davi de Miranda DM   Marchini Fabricio F   da Silveira Joana Lea Meira JL   Paba Jaime J  

Journal of proteome research 20161116 12


Analysis of fungal secretomes is a prospection tool for the discovery of new catalysts with biotechnological applications. Since enzyme secretion is strongly modulated by environmental factors, evaluation of growth conditions is of utmost importance to achieve optimal enzyme production. In this work, a nonsequenced wood-rotting fungus, Lentinus crinitus, was used for secretome analysis by enzymatic assays and a proteomics approach. Enzyme production was assessed after the fungus was cultured in  ...[more]

Similar Datasets

2013-04-30 | GSE45303 | GEO
2013-04-30 | E-GEOD-45303 | biostudies-arrayexpress
2023-12-06 | GSE222372 | GEO
2018-03-19 | GSE95798 | GEO
2011-10-30 | GSE30384 | GEO
2020-12-05 | GSE162657 | GEO
2022-01-29 | GSE168384 | GEO
2005-06-21 | E-GEOD-2830 | biostudies-arrayexpress
| PRJNA32777 | ENA
2012-02-12 | E-GEOD-22566 | biostudies-arrayexpress