439000 Searching Therapeutic Candidates Against the Yeast Malassezia Sp. By a Metabolic Reconstruction, Feasibility Analysis and Proteomics Validation

Wednesday, September 16, 2015
Crowne Plaza Heidelberg City Centre
Sergio Heli Triana Sierra, Chemical Engineering, Grupo de Diseño de Productos y Procesos Universidad de los Andes, (GDPP), Bogota, Colombia, John Mario Gonzalez Escobar, Medicine, Grupo de Ciencias Básicas Médicas, Universidad de los Andes, Bogota, Colombia, Silvia Restrepo Restrepo, Biological Sciences, Mycology and Plant Disease Laboratory, Universidad de los Andes, Bogota, Colombia, Hans de Cock, Microbiology, University of Utrecht, Utrcht, Netherlands, Adriana Marcela Celis Ramirez, Biological Sciences, Universidad de los Andes, Bogota, Colombia and Andrés Fernando González Barrios, Chemical Engineering, Grupo de Diseño de Productos y Procesos (GDPP) Universidad de los Andes, Bogotá, Colombia

Malassezia species, are lipophilic and lipid dependent, belonging to the human and animal microbiota. Usually, they are isolated from regions rich in sebaceous glands, also in some individuals they have been associated with different dermatological diseases such as seborrheic dermatitis, tinea versicolor, atopic dermatitis and folliculitis. Their lipid dependence has been recently confirmed by the genome sequencing of Malassezia globosa and M. sympodialis, which showed the absence of genes related to the synthesis of fatty acids. Due to the fact that the diseases caused by Malassezia sp. are chronic, the treatments must be administered frequently and for long periods of time, due to poor response of patients to the treatment. Reconstruction of metabolic networks, based on genome data and its further modeling with flux balance analysis (FBA) is an approach that can be applied to search for therapeutic candidates and design new antimicrobial molecules. Consequently, the objective of this work is to find therapeutic candidates against Malassezia spp. by building a yeast´s metabolism’s computer model with emphasis on the lipid synthesis pathway of five Malassezia species. In addition a feasibility analysis of the network with different knockouts in silico will be done. Three new draft genomes were assembled from a shotgun Illumina HiSeq 2000-Paired data set using CLC-assembler to a total of 2084 scaffolds (N50 = 23 kb) corresponding to a nuclear genome of 14.9 Mbp in M .furfur, 3577 scaffolds (N50 = 42 kb), corresponding to a nuclear genome of 10.3 Mbp in Atypical M .furfur and a total of 44 scaffolds (N50 = 23 kb), corresponding to a nuclear genome of 8.14 Mbp in M . pachydermatis, We predicted a total of 10203 protein-coding genes in M. furfur, 12131 in atypical M. furfur and 4284 in M. pachydermatis,  twelve categories were used to discriminate the distribution of the metabolic pathways. Reactions from the five Malassezia species (including M. globosa and M. sympdialis previously sequenced) were used to retrieve pathways from KEEG database. Furthermore lipid metabolism was analyzed deeper with sixteen sub categories. A group contribution approached showed between 20-23% irreversible reactions and 77-80% of reversible reactions. Compartmentalization analysis showed the same distribution of reactions within the samples. However, the difference between M. furfur and other species corresponded to cytoplasmic and mitochondrial reactions. Furthermore a metabolic curation of the metabolic network curation was done with Gapfind and GapFill algorithms implemented in GAMS, the amount of problem metabolites was reduced as much as possible, Metabolic reconstruction analysis with FBA predicts an interesting degeneracy on the objective function, reflecting several mechanism for the yeast survival as we identified a relatively low number of genes related to lipid biosynthesis but several genes encoding lipid-hydrolyzing enzymes. These enzymes that could have a role in the pathogenesis of the yeast and could be used as therapeutic candidates.

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