Article
An analysis of the Candida albicans genome database for soluble secreted proteins using computer-based prediction algorithms.
Infectious Diseases Section, Department of Medicine, Yale University School of Medicine, New Haven, CT, USA.
Yeast (impact factor:
1.89).
06/2003;
20(7):595-610.
DOI:10.1002/yea.988
pp.595-610
Source: PubMed
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Citations (0)
- Cited In (3)
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Article: Computational analysis of the interaction between transcription factors and the predicted secreted proteome of the yeast Kluyveromyces lactis.
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ABSTRACT: Protein secretion is a cell translocation process of major biological and technological significance. The secretion and downstream processing of proteins by recombinant cells is of great commercial interest. The yeast Kluyveromyces lactis is considered a promising host for heterologous protein production. Because yeasts naturally do not secrete as many proteins as filamentous fungi, they can produce secreted recombinant proteins with few contaminants in the medium. An ideal system to address the secretion of a desired protein could be exploited among the native proteins in certain physiological conditions. By applying algorithms to the completed K. lactis genome sequence, such a system could be selected. To this end, we predicted protein subcellular locations and correlated the resulting extracellular secretome with the transcription factors that modulate the cellular response to a particular environmental stimulus. To explore the potential Kluyveromyces lactis extracellular secretome, four computational prediction algorithms were applied to 5076 predicted K. lactis proteins from the genome database. SignalP v3 identified 418 proteins with N-terminal signal peptides. From these 418 proteins, the Phobius algorithm predicted that 176 proteins have no transmembrane domains, and the big-PI Predictor identified 150 proteins as having no glycosylphosphatidylinositol (GPI) modification sites. WoLF PSORT predicted that the K. lactis secretome consists of 109 putative proteins, excluding subcellular targeting. The transcription regulators of the putative extracellular proteins were investigated by searching for DNA binding sites in their putative promoters. The conditions to favor expression were obtained by searching Gene Ontology terms and using graph theory. A public database of K. lactis secreted proteins and their transcription factors are presented. It consists of 109 ORFs and 23 transcription factors. A graph created from this database shows 134 nodes and 884 edges, suggesting a vast number of relationships to be validated experimentally. Most of the transcription factors are related to responses to stress such as drug, acid and heat resistance, as well as nitrogen limitation, and may be useful for inducing maximal expression of potential extracellular proteins.BMC Bioinformatics 07/2009; 10:194. · 2.75 Impact Factor -
Article: Identifying secretomes in people, pufferfish and pigs.
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ABSTRACT: The proteins processed by the secretory pathway (secretome) are critical players in the development of multi-cellular eukaryotic organisms but have yet to be comprehensively studied at the genomic level. In this study, we use the Target P algorithm to predict human (13-20% of proteins found in individual datasets) and Fugu (14%) secretomes based on analysis of their nearly complete proteomes. We combine internal processing with prediction software to automate secreted protein identification and overcome one of the major challenges associated with EST data: identification of the minority of clones that encode N-terminally-complete proteins. We discuss the use of these methods to predict secreted proteins in EST-based consensus sequence sets, and we validate these predictions using an assay for cell-free cotranslational translocation. Analysis of TIGR Porcine Gene Index 4.0 as a test dataset resulted in the identification of 352 N-terminally-complete, putative secreted proteins. In functional agreement with our predictions, 34 of 40 (85%) of these cDNAs were verified to be cotranslationally translocated in an in vitro translation system. The methods developed here are specifically designed to accept partial open reading frames and improve secreted protein predictions in eukaryotic transcriptomes, and are valuable for the analysis and annotation of eukaryotic EST databases.Nucleic Acids Research 02/2004; 32(4):1414-21. · 8.03 Impact Factor -
Article: Lipid raft polarization contributes to hyphal growth in Candida albicans.
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ABSTRACT: The polarization of sterol- and sphingolipid-enriched domains (lipid rafts) has been linked to morphogenesis and cell movement in diverse cell types. In the yeast Saccharomyces cerevisiae, a dramatic polarization of sterol-rich domains to the shmoo tip was observed in pheromone-induced cells (M. Bagnat and K. Simons, Proc. Natl. Acad. Sci. USA 99:14183-14188, 2002). We therefore examined whether plasma membrane lipid polarization contributes to the ability of the fungal pathogen Candida albicans to grow in a highly polarized manner to form hyphae. Interestingly, staining with filipin revealed that membrane sterols were highly polarized to the leading edge of growth during all stages of hyphal growth. Budding and pseudohyphal cells did not display polarized staining. Filipin staining was also enriched at septation sites in hyphae, where colocalization with septin proteins was observed, suggesting a role for the septins in forming a boundary domain. Actin appeared to play a role in sterol polarization and hyphal morphogenesis in that both were disrupted by low concentrations of latrunculin A that did not prevent budding. Furthermore, blocking either sphingolipid biosynthesis with myriocin or sterol biosynthesis with ketoconazole resulted in a loss of ergosterol polarization and caused abnormal hyphal morphogenesis, suggesting that lipid rafts are involved. Since hyphal growth is required for the full virulence of C. albicans, these results suggest that membrane polarization may contribute to the pathogenesis of this organism.Eukaryotic Cell 07/2004; 3(3):675-84. · 3.60 Impact Factor
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Keywords
47 C. albicans proteins
495 deduced proteins
C. albicans secretome database
Candida albicans genome database
CandidaDB
certain C. albicans secretory proteins
deduced proteins
encode proteins
entire proteome
extreme N-terminus
final computationally-predicted C. albicans secretome
N-terminal signal peptide
N-terminal signal peptides
non-secreted proteins
potential C. albicans secretome
secreted proteins
SignalP version 2.0
single transmembrane domain
transmembrane domains
utilize genomic database information