Dataset Information

Identification of human plasma proteins associated with the cell wall of the pathogenic fungus Paracoccidioides brasiliensis.

ABSTRACT: Paracoccidioides brasiliensis and Paracoccidioides lutzii are thermodimorphic species that cause paracoccidioidomycosis. The cell wall is the outermost fungal organelle to form an interface with the host. A number of host effector compounds, including immunologically active molecules, circulate in the plasma. In the present work, we extracted cell-wall-associated proteins from the yeast pathogenic phase of P. brasiliensis, isolate Pb3, grown in the presence of human plasma and analyzed bound plasma proteins by liquid chromatography-tandem mass spectrometry. Transport, complement activation/regulation, and coagulation pathway were the most abundant functional groups identified. Proteins related to iron/copper acquisition, immunoglobulins, and protease inhibitors were also detected. Several human plasma proteins described here have not been previously reported as interacting with fungal components, specifically, clusterin, hemopexin, transthyretin, ceruloplasmin, alpha-1-antitrypsin, apolipoprotein A-I, and apolipoprotein B-100. Additionally, we observed increased phagocytosis by J774.16 macrophages of Pb3 grown in plasma, suggesting that plasma proteins interacting with P. brasiliensis cell wall might be interfering in the fungal relationship with the host.

SUBMITTER: Longo LV

PROVIDER: S-EPMC3619194 | biostudies-other | 2013 Apr

REPOSITORIES: biostudies-other

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Identification of human plasma proteins associated with the cell wall of the pathogenic fungus Paracoccidioides brasiliensis.

Longo Larissa V G LV Nakayasu Ernesto S ES Matsuo Alisson L AL Peres da Silva Roberta R Sobreira Tiago J P TJ Vallejo Milene C MC Ganiko Luciane L Almeida Igor C IC Puccia Rosana R

FEMS microbiology letters 20130401 2

Paracoccidioides brasiliensis and Paracoccidioides lutzii are thermodimorphic species that cause paracoccidioidomycosis. The cell wall is the outermost fungal organelle to form an interface with the host. A number of host effector compounds, including immunologically active molecules, circulate in the plasma. In the present work, we extracted cell-wall-associated proteins from the yeast pathogenic phase of P. brasiliensis, isolate Pb3, grown in the presence of human plasma and analyzed bound pla ...[more]

PMID: 23398536

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Project description:BackgroundTranscriptome sequences provide a complement to structural genomic information and provide snapshots of an organism's transcriptional profile. Such sequences also represent an alternative method for characterizing neglected species that are not expected to undergo whole-genome sequencing. One difficulty for transcriptome sequencing of these organisms is the low quality of reads and incomplete coverage of transcripts, both of which compromise further bioinformatics analyses. Another complicating factor is the lack of known protein homologs, which frustrates searches against established protein databases. This lack of homologs may be caused by divergence from well-characterized and over-represented model organisms. Another explanation is that non-coding RNAs (ncRNAs) may be caught during sequencing. NcRNAs are RNA sequences that, unlike messenger RNAs, do not code for protein products and instead perform unique functions by folding into higher order structural conformations. There is ncRNA screening software available that is specific for transcriptome sequences, but their analyses are optimized for those transcriptomes that are well represented in protein databases, and also assume that input ESTs are full-length and high quality.ResultsWe propose an algorithm called PORTRAIT, which is suitable for ncRNA analysis of transcriptomes from poorly characterized species. Sequences are translated by software that is resistant to sequencing errors, and the predicted putative proteins, along with their source transcripts, are evaluated for coding potential by a support vector machine (SVM). Either of two SVM models may be employed: if a putative protein is found, a protein-dependent SVM model is used; if it is not found, a protein-independent SVM model is used instead. Only ab initio features are extracted, so that no homology information is needed. We illustrate the use of PORTRAIT by predicting ncRNAs from the transcriptome of the pathogenic fungus Paracoccidoides brasiliensis and five other related fungi.ConclusionPORTRAIT can be integrated into pipelines, and provides a low computational cost solution for ncRNA detection in transcriptome sequencing projects.

Dataset Information

Identification of human plasma proteins associated with the cell wall of the pathogenic fungus Paracoccidioides brasiliensis.

Publications

Identification of human plasma proteins associated with the cell wall of the pathogenic fungus Paracoccidioides brasiliensis.

Similar Datasets

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