Mass spectrometry and database search in the analysis of proteins from the fungus Pleurotus ostreatus

Transcriptome and proteome exploration to provide a resource for the study of Agrocybe aegerita

BACKGROUND

Agrocybe aegerita, the black poplar mushroom, has been highly valued as a functional food for its medicinal and nutritional benefits. Several bioactive extracts from A. aegerita have been found to exhibit antitumor and antioxidant activities. However, limited genetic resources for A. aegerita have hindered exploration of this species.

METHODOLOGY/PRINCIPAL FINDINGS

To facilitate the research on A. aegerita, we established a deep survey of the transcriptome and proteome of this mushroom. We applied high-throughput sequencing technology (Illumina) to sequence A. aegerita transcriptomes from mycelium and fruiting body. The raw clean reads were de novo assembled into a total of 36,134 expressed sequences tags (ESTs) with an average length of 663 bp. These ESTs were annotated and classified according to Gene Ontology (GO), Clusters of Orthologous Groups (COG), and Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways. Gene expression profile analysis showed that 18,474 ESTs were differentially expressed, with 10,131 up-regulated in mycelium and 8,343 up-regulated in fruiting body. Putative genes involved in polysaccharide and steroid biosynthesis were identified from A. aegerita transcriptome, and these genes were differentially expressed at the two stages of A. aegerita. Based on one-dimensional gel electrophoresis (1-DGE) coupled with electrospray ionization liquid chromatography tandem MS (LC-ESI-MS/MS), we identified a total of 309 non-redundant proteins. And many metabolic enzymes involved in glycolysis were identified in the protein database.

CONCLUSIONS/SIGNIFICANCE

This is the first study on transcriptome and proteome analyses of A. aegerita. The data in this study serve as a resource of A. aegerita transcripts and proteins, and offer clues to the applications of this mushroom in nutrition, pharmacy and industry.

Proteome characterization of the unsequenced psychrophile Pedobacter cryoconitis using 15N metabolic labeling, tandem mass spectrometry, and a new bioinformatic workflow

Organisms without a sequenced genome and lacking a complete protein database encounter an added level of complexity to protein identification and quantitation. De novo sequencing, new bioinformatics tools, and mass spectrometry (MS) techniques allow for advances in this area. Here, the proteomic characterization of an unsequenced psychrophilic bacterium, Pedobacter cryoconitis, is presented employing a novel workflow based on (15) N metabolic labelling, 2DE, MS/MS, and bioinformatics tools. Two bioinformatics pipelines, based on nitrogen constraint (N-constraint), ortholog searching, and de novo peptide sequencing with N-constraint similarity database search, are compared based on proteome coverage and throughput. Results demonstrate the effect of different growth temperatures (1°C, 20°C) and different carbon sources (glucose, maltose) on the proteome. Seventy-six and 69 proteins were identified and validated from the glucose- and maltose-grown bacterium, respectively, from which 21 and 22 were differentially expressed at different growth temperatures. Differentially expressed proteins are involved in stress response and carbohydrate metabolism, with higher expression at 20°C than at 1°C, while antioxidants were upregulated at 1°C. This study provides an alternative workflow to identify, validate, and quantify proteins from unsequenced organisms distantly related to other species in the protein database. Furthermore, it provides further understanding on bacterial adaptation mechanisms to cold environments, and a comparative proteomic analyses with other psychrophilic microorganisms.

Post-genomic approaches to understanding interactions between fungi and their environment

Fungi inhabit every natural and anthropogenic environment on Earth. They have highly varied life-styles including saprobes (using only dead biomass as a nutrient source), pathogens (feeding on living biomass), and symbionts (co-existing with other organisms). These distinctions are not absolute as many species employ several life styles (e.g. saprobe and opportunistic pathogen, saprobe and mycorrhiza). To efficiently survive in these different and often changing environments, fungi need to be able to modify their physiology and in some cases will even modify their local environment. Understanding the interaction between fungi and their environments has been a topic of study for many decades. However, recently these studies have reached a new dimension. The availability of fungal genomes and development of post-genomic technologies for fungi, such as transcriptomics, proteomics and metabolomics, have enabled more detailed studies into this topic resulting in new insights. Based on a Special Interest Group session held during IMC9, this paper provides examples of the recent advances in using (post-)genomic approaches to better understand fungal interactions with their environments.

Proteomics of plant pathogenic fungi

Plant pathogenic fungi cause important yield losses in crops. In order to develop efficient and environmental friendly crop protection strategies, molecular studies of the fungal biological cycle, virulence factors, and interaction with its host are necessary. For that reason, several approaches have been performed using both classical genetic, cell biology, and biochemistry and the modern, holistic, and high-throughput, omic techniques. This work briefly overviews the tools available for studying Plant Pathogenic Fungi and is amply focused on MS-based Proteomics analysis, based on original papers published up to December 2009. At a methodological level, different steps in a proteomic workflow experiment are discussed. Separate sections are devoted to fungal descriptive (intracellular, subcellular, extracellular) and differential expression proteomics and interactomics. From the work published we can conclude that Proteomics, in combination with other techniques, constitutes a powerful tool for providing important information about pathogenicity and virulence factors, thus opening up new possibilities for crop disease diagnosis and crop protection.

Crucial role of antioxidant proteins and hydrolytic enzymes in pathogenicity of Penicillium expansum: analysis based on proteomics approach

Penicillium expansum, a widespread filamentous fungus, is a major causative agent of fruit decay and may lead to the production of mycotoxin that causes harmful effects on human health. In this study, we compared the cellular and extracellular proteomes of P. expansum in the absence and presence of borate, which affects the virulence of the fungal pathogen. The differentially expressed proteins were identified using ESI-Q-TOF-MS/MS. Several proteins related to stress response (glutathione S-transferase, catalase, and heat shock protein 60) and basic metabolism (glyceraldehyde-3-phosphate dehydrogenase, dihydroxy-acid dehydratase, and arginase) were identified in the cellular proteome. Catalase and glutathione S-transferase, the two antioxidant enzymes, exhibited reduced levels of expression upon exposure to borate. Because catalase and glutathione S-transferase are related to oxidative stress response, we further investigated the reactive oxygen species (ROS) levels and oxidative protein carbonylation (damaged proteins) in P. expansum. Higher amounts of ROS and carbonylated proteins were observed after borate treatment, indicating that catalase and glutathione S-transferase are important in scavenging ROS and protecting cellular proteins from oxidative damage. Additionally to find secretory proteins that contribute to the virulence, we studied the extracellular proteome of P. expansum under stress condition with reduced virulence. The expression of three protein spots were repressed in the presence of borate and identified as the same hydrolytic enzyme, polygalacturonase.

Functional Proteome Analysis of the Banana Plant (Musa spp.) Using de Novo Sequence Analysis of Derivatized Peptides

We report the use of chemical derivatization with MALDI-MS/MS analysis for de novo sequence analysis. Using three frequently used homology-based search algorithms, we were able to identify more than 40 proteins from banana, a nonmodel plant with unsequenced genome. Furthermore, this approach allowed the identification of different isoforms. We also observed that the identification score obtained varied according to the position of the peptide sequences in the query using the MS-Blast algorithm.

Laccases of Pleurotus sapidus: characterization and cloning

Peanut shells, a major waste stream of food processing, served as a renewable substrate for inducing the production of laccases by basidiomycetes. Of 46 surface cultures examined, 29 showed laccase activity under the experimental conditions. The edible fungus Pleurotus sapidus was selected as the most active producer, immobilized on the shells, and cultivated in the fed-batch mode. A continuous rise in laccase activity was found, indicating the inducibility of laccase secretion by the peanut shells and the reusability of the mycelium. Two laccase isoenzymes were purified by decoupled 2-D electrophoresis, and amino acid sequence information was obtained by electrospray ionization tandem mass spectrometry. cDNAs of the corresponding gene and another laccase were cloned and sequenced using a PCR-based screening of a synthesized P. sapidus cDNA library. Data bank searches against public databases returned laccases of P. ostreatus and P. sajor-caju as the best hits. The potential use of laccases by the food industry is discussed.

Global Analysis of the Hortaea werneckii Proteome: Studying Steroid Response in Yeast

The response of the halophilic black yeast Hortaea werneckii to the steroid hormone progesterone has been studied at the protein level using fluorescent two-dimensional differential gel electrophoresis (2D-DIGE) technology in combination with mass spectrometry. Data on protein identification from this study reveal molecular mechanisms of the response to progesterone. In particular, the overexpression of Pck2 and Pac2 in the stimulated cells indicates the interactions of progesterone with the cell growth and reproduction signaling pathways.