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Agrociencia

On-line version ISSN 2521-9766Print version ISSN 1405-3195

Abstract

MONTESINOS-MATIAS, Roberto et al. Virulence and growth phenotypes variation in mutant strains of Beauveria bassiana (Bals.) Vuill. resistant to 2-deoxy-D-glucose. Agrociencia [online]. 2011, vol.45, n.8, pp.929-942. ISSN 2521-9766.

In the breeding processes of fungal strains of entomopathogenic, it is necessary to know which ones they are and how the most important variables have influence on the most virulent strains. In this study an evaluation was made of a series of growth and virulence variables of a parental strain of Beauveria bassiana (Bals.) Vuill. (Hyocreales: Cordycipitaceae) (88) and derived mutants resistant to the toxic compound 2-doxy-D-glucose (2DG). 2DG is a toxic analogue of glucose, and has frequently been used to isolate a variety deregulated mutants in the metabolism of carbon in some microorganisms. Of the variables evaluated, prior to the bioassay of virulence on larvae of Tenebrio molitor (Coleoptera: Tenebrionidae), the percentage of germination of conidia (G) was best correlated with the parameters of virulence such as time of onset of death (t0) (r=-0.879; p<0.05), lethal time 50 (LT50) (r=-0.869; p<0.05) and maximum mortality M (r=0.589; p=0.1). The other variables evaluated showed a lower correlation with virulence. There is a high correlation of t0 with the LT50 (r=0.967; p<0.05), a variable determined in the early stage of infection of B. bassiana in larvae of T. molitor. The mutant strains 881.2, 882.5 and 885.5 resistant to 2DG showed improved characteristics in virulence compared with the parental strain (88). The above was confirmed through simple regression coefficients and Principal Components Analysis (PCA), used to examine the relationship among the variables of study. The analysis of the results shows the physiological characteristics with highest influence to select more virulent strains of entomopathogenic fungi.

Keywords : biological control; virulence; germination; Tenebrio molitor; Principal Components Analysis.

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