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- IOC - Artigos de Periódicos [12825]
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TOWARDS A COMPREHENSIVE SEARCH OF PUTATIVE CHITINASES SEQUENCES IN ENVIRONMENTAL METAGENOMIC DATABASES
Autor
Afiliación
Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Computacional e de Sistemas. Rio de Janeiro, RJ, Brasil.
Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Computacional e de Sistemas. Rio de Janeiro, RJ, Brasil.
Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Computacional e de Sistemas. Rio de Janeiro, RJ, Brasil.
Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Polo de Biologia Computacional e Sistemas. Laboratório de Bioquímica de Proteínas e Peptídeos. Rio de Janeiro, RJ, Brasil.
Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Computacional e de Sistemas. Pólo de Biologia Computacional e de Sistemas. Rio de Janeiro, RJ, Brasil.
Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Computacional e de Sistemas. Rio de Janeiro, RJ, Brasil.
Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Computacional e de Sistemas. Rio de Janeiro, RJ, Brasil.
Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Polo de Biologia Computacional e Sistemas. Laboratório de Bioquímica de Proteínas e Peptídeos. Rio de Janeiro, RJ, Brasil.
Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Biologia Computacional e de Sistemas. Pólo de Biologia Computacional e de Sistemas. Rio de Janeiro, RJ, Brasil.
Resumen en ingles
Chitinases catalyze the hydrolysis of chitin, a linear homopolymer of β-(1,4)-linked N-acetylglucosamine.
The broad range of applications of chitinolytic enzymes makes their identification and
study very promising. Metagenomic approaches offer access to functional genes in uncultured
representatives of the microbiota and hold great potential in the discovery of novel enzymes, but
tools to extensively explore these data are still scarce. In this study, we develop a chitinase mining
pipeline to facilitate the comprehensive search of these enzymes in environmental metagenomic
databases and also to explore phylogenetic relationships among the retrieved sequences. In order
to perform the analyses, UniprotKB fungal and bacterial chitinases sequences belonging to the
glycoside hydrolases (GH) family-18, 19 and 20 were used to generate 15 reference datasets,
which were then used to generate high quality seed alignments with the MAFFT program. Profile
Hidden Markov Models (pHMMs) were built from each seed alignment using the hmmbuild program
of HMMER v3.0 package. The best-hit sequences returned by hmmsearch against two environmental
metagenomic databases (Community Cyberinfrastructure for Advanced Microbial Ecology
Research and Analysis—CAMERA and Integrated Microbial Genomes—IMG/M) were retrieved
and further analyzed. The NJ trees generated for each chitinase dataset showed some variability in
the catalytic domain region of the metagenomic sequences and revealed common sequence patterns
among all the trees. The scanning of the retrieved metagenomic sequences for chitinase conserved
domains/signatures using both the InterPro and the RPS-BLAST tools confirmed the efficacy
and sensitivity of our pHMM-based approach in detecting putative chitinases sequences. These analyses provide insight into the potential reservoir of novel molecules in metagenomic
databases while supporting the chitinase mining pipeline developed in this work. By using our
chitinase mining pipeline, a larger number of previously unannotated metagenomic chitinase sequences
can be classified, enabling further studies on these enzymes.
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