Structural and Phylogenetic Analysis of Laccases from Trichoderma: A Bioinformatic Approach

37Citations
Citations of this article
140Readers
Mendeley users who have this article in their library.

Abstract

The genus Trichoderma includes species of great biotechnological value, both for their mycoparasitic activities and for their ability to produce extracellular hydrolytic enzymes. Although activity of extracellular laccase has previously been reported in Trichoderma spp., the possible number of isoenzymes is still unknown, as are the structural and functional characteristics of both the genes and the putative proteins. In this study, the system of laccases sensu stricto in the Trichoderma species, the genomes of which are publicly available, were analyzed using bioinformatic tools. The intron/exon structure of the genes and the identification of specific motifs in the sequence of amino acids of the proteins generated in silico allow for clear differentiation between extracellular and intracellular enzymes. Phylogenetic analysis suggests that the common ancestor of the genus possessed a functional gene for each one of these enzymes, which is a characteristic preserved in T. atroviride and T. virens. This analysis also reveals that T. harzianum and T. reesei only retained the intracellular activity, whereas T. asperellum added an extracellular isoenzyme acquired through horizontal gene transfer during the mycoparasitic process. The evolutionary analysis shows that in general, extracellular laccases are subjected to purifying selection, and intracellular laccases show neutral evolution. The data provided by the present study will enable the generation of experimental approximations to better understand the physiological role of laccases in the genus Trichoderma and to increase their biotechnological potential. © 2013 Cázares-García et al.

Cite

CITATION STYLE

APA

Cázares-García, S. V., Vázquez-Garcidueñas, M. S., & Vázquez-Marrufo, G. (2013). Structural and Phylogenetic Analysis of Laccases from Trichoderma: A Bioinformatic Approach. PLoS ONE, 8(1). https://doi.org/10.1371/journal.pone.0055295

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free