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Algorithm-based design of novel synthetic media for Metarhizium anisopliae simulating its nutritional conditions in the environment.
Hutwimmer, S; Wagner, S; Affenzeller, M; Burgstaller, W; Strasser, H.
Affiliation
  • Hutwimmer S; Institute of Microbiology, University of Innsbruck, Innsbruck, Austria. Stefan.hutwimmer@uibk.ac.at
J Appl Microbiol ; 105(2): 459-68, 2008 Aug.
Article in En | MEDLINE | ID: mdl-18298524
ABSTRACT

AIMS:

The objective of this study was to develop a novel synthetic growth medium for increased conidium production of the entompathogenic fungus Metarhizium anisopliae. The medium should simulate natural nutritional conditions. METHODS AND

RESULTS:

Macro- and micronutrients were selected in concentrations found in insects or from sources which are believed to be advantageous for virulence. Medium development was guided by a problem-oriented genetic algorithm (GA) implemented with 'mutation' and 'recombination' operators specific for this optimization problem. Following five optimization steps and a total of 181 medium variations, 19 synthetic media led to increased conidium production as compared with the standard Sabouraud dextrose agar medium increases in conidia yields of up to 120% and a 17-fold higher conidium production per square centimetre of mycelium were achieved. Rapid germination of conidia, conidial C N ratio, as well as spore-bound Pr1 protease production were monitored as proposed quality control markers for a virulent inoculum.

CONCLUSIONS:

It was demonstrated that our problem-oriented GA is a powerful tool for the design of chemically defined cultivation media with special/enhanced properties for anamorphic fungi. SIGNIFICANCE AND IMPACT OF THE STUDY This is the first study, which demonstrates the advantage of the use of a GA for the rapid design of solid synthetic media for maximum production of virulent conidia.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Soil Microbiology / Algorithms / Metarhizium / Models, Genetic / Mycology Type of study: Prognostic_studies Language: En Journal: J Appl Microbiol Journal subject: MICROBIOLOGIA Year: 2008 Document type: Article Affiliation country: Austria

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Soil Microbiology / Algorithms / Metarhizium / Models, Genetic / Mycology Type of study: Prognostic_studies Language: En Journal: J Appl Microbiol Journal subject: MICROBIOLOGIA Year: 2008 Document type: Article Affiliation country: Austria