1. Transcriptome characterization of the dimorphic and pathogenic fungus Paracoccidioides brasiliensis by EST analysis.
- Author
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Felipe MS, Andrade RV, Petrofeza SS, Maranhão AQ, Torres FA, Albuquerque P, Arraes FB, Arruda M, Azevedo MO, Baptista AJ, Bataus LA, Borges CL, Campos EG, Cruz MR, Daher BS, Dantas A, Ferreira MA, Ghil GV, Jesuino RS, Kyaw CM, Leitão L, Martins CR, Moraes LM, Neves EO, Nicola AM, Alves ES, Parente JA, Pereira M, Poças-Fonseca MJ, Resende R, Ribeiro BM, Saldanha RR, Santos SC, Silva-Pereira I, Silva MA, Silveira E, Simões IC, Soares RB, Souza DP, De-Souza MT, Andrade EV, Xavier MA, Veiga HP, Venancio EJ, Carvalho MJ, Oliveira AG, Inoue MK, Almeida NF, Walter ME, Soares CM, and Brígido MM
- Subjects
- Base Sequence, Brazil, Cluster Analysis, DNA, Fungal chemistry, DNA, Fungal genetics, Humans, Molecular Sequence Data, Polymerase Chain Reaction, Sequence Analysis, DNA, Transcription, Genetic, Expressed Sequence Tags, Genome, Fungal, Paracoccidioides genetics
- Abstract
Paracoccidioides brasiliensis is a pathogenic fungus that undergoes a temperature-dependent cell morphology change from mycelium (22 degrees C) to yeast (36 degrees C). It is assumed that this morphological transition correlates with the infection of the human host. Our goal was to identify genes expressed in the mycelium (M) and yeast (Y) forms by EST sequencing in order to generate a partial map of the fungus transcriptome. Individual EST sequences were clustered by the CAP3 program and annotated using Blastx similarity analysis and InterPro Scan. Three different databases, GenBank nr, COG (clusters of orthologous groups) and GO (gene ontology) were used for annotation. A total of 3,938 (Y = 1,654 and M = 2,274) ESTs were sequenced and clustered into 597 contigs and 1,563 singlets, making up a total of 2,160 genes, which possibly represent one-quarter of the complete gene repertoire in P. brasiliensis. From this total, 1,040 were successfully annotated and 894 could be classified in 18 functional COG categories as follows: cellular metabolism (44%); information storage and processing (25%); cellular processes-cell division, posttranslational modifications, among others (19%); and genes of unknown functions (12%). Computer analysis enabled us to identify some genes potentially involved in the dimorphic transition and drug resistance. Furthermore, computer subtraction analysis revealed several genes possibly expressed in stage-specific forms of P. brasiliensis. Further analysis of these genes may provide new insights into the pathology and differentiation of P. brasiliensis., (Copyright 2003 John Wiley & Sons, Ltd.)
- Published
- 2003
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