Modulation of antimicrobial metabolites production by the fungus Aspergillus parasiticus

Abstract

Biosynthesis of active secondary metabolites by fungi occurs as a specific response to the different growing environments. Changes in this environment alter the chemical and biological profiles leading to metabolites diversification and consequently to novel pharmacological applications. In this work, it was studied the influence of three parameters (fermentation length, medium composition and aeration) in the biosyntheses of antimicrobial metabolites by the fungus Aspergillus parasiticus in 10 distinct fermentation periods. Metabolism modulation in two culturing media, CYA and YES was evaluated by a 22 full factorial planning (ANOVA) and on a 23 factorial planning, role of aeration, medium composition and carbohydrate concentration were also evaluated. In overall, 120 different extracts were prepared, their HPLC profiles were obtained and the antimicrobial activity against A. flavus, C. albicans, E. coli and S. aureus of all extracts was evaluated by microdilution bioassay. Yield of kojic acid, a fine chemical produced by the fungus A. parasiticus was determined in all extracts. Statistical analyses pointed thirteen conditions able to modulate the production of bioactive metabolites by A. parasiticus. Effect of carbon source in metabolites diversification was significant as shown by the changes in the HPLC profiles of the extracts. Most of the extracts presented inhibition rates higher than that of kojic acid as for the extract obtained after 6 days of fermentation in YES medium under stirring. Kojic acid was not the only metabolite responsible for the activity since some highly active extracts showed to possess low amounts of this compound, as determined by HPLC.

Production of bioherbicide by Phoma sp. in a stirred-tank bioreactor

“…The difference in T3 and T4 was the stirring rate (40 and 60 rpm, respectively) both at 3 vvm. Modification of process variables as stirring rate may affect the excretion of different compounds in the media, because biosynthesis of active secondary metabolites by fungi occurs as a specific response to the different growing environments (Bracarense and Takahashi, 2014). This is corroborated by comparing the chemical composition of T3 and T4 experiments (Tables 2, 3, respectively), where the profile and the concentration (expressed as normalized peak area) were different.…”

“…One possibility is the production of bioherbicide by submerged fermentation, which is a process well established industrially. However, it is necessary to evaluate the influence of process variables such as stirring rate and agitation on metabolite production, because biosynthesis of active secondary metabolites by fungi occurs as a specific response to the different growing environments (Bracarense and Takahashi 2014). It is well documented that stirring rate affects severally the growth of microorganism due to shear stress (Serrano-Carreón et al 2015; Garcia-Ochoa et al 2013; Maldonado et al 2012).…”

Metabolômica De Plantas: Métodos E Desafios

“…No geral, modelos baseados em planejamentos fatoriais completos ou fracionários são os mais utilizados para esse fim, uma vez que o número de experimentos é relativamente reduzido. [54][55][56][57] Nos casos em que as variáveis dominantes são conhecidas, é possível aplicar um modelo de otimização das variáveis. Dentre os modelos mais utilizados, o planejamento composto central arranja as variáveis dentro de um espaço amostral com cinco diferentes níveis (5 variações).…”

Development and Evaluation of Antimicrobial and Modulatory Activity of Inclusion Complex of Euterpe oleracea Mart Oil and β-Cyclodextrin or HP-β-Cyclodextrin

“…There is a growing number of studies on the discovery of new antimicrobial drugs as well as the improvement of existing formulations [44][45][46][47]. Drug-modulating activity subsidizes a combination therapy that does not always improve clinical outcomes but is able to decrease the chances of bacterial resistance to multiple drugs, which is a growing problem [48].…”