Busca avançada
Ano de início
Entree
(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

A new approach for identifying antagonism among fungi species and antifungal activity

Texto completo
Autor(es):
Silva, Airton Damasceno [1] ; Pepe Ambrozin, Alessandra Regina [2] ; Carneiro, Renato Lajarim [1] ; Vieira, Paulo Cezar [1, 3]
Número total de Autores: 4
Afiliação do(s) autor(es):
[1] Fed Univ Sao Carlos UFSCar, Dept Chem, Sao Carlos, SP - Brazil
[2] Fed Univ Alfenas Unifal MG, Inst Sci & Technol, Pocos De Caldas, MG - Brazil
[3] Univ Sao Paulo, Sch Pharmaceut Sci Ribeirao Preto, Dept Phys & Chem, Ribeirao Preto, SP - Brazil
Número total de Afiliações: 3
Tipo de documento: Artigo Científico
Fonte: Journal of Pharmaceutical and Biomedical Analysis; v. 179, FEB 3 2020.
Citações Web of Science: 0
Resumo

New antifungals are increasingly needed due to the emergence of resistant fungal strains. Traditional antifungal assays are laborious and require significant amounts of samples. The present work presents a new proposal to evaluate antifungal activity and antagonism among fungal species, based on experiments of fungal culture and co-culture, H-1 NMR profile of fungal culture extracts and chemometrics. In order to develop the work, six axenic cultures of fungi that infested fruits (Fusarium guttiforme, Pestalotiopsis diospyri, Phoma caricae-papayae, Colletotrichum horii, Phytophthora palmivora, and C. gloeosporioides), and co-cultures of all possible combination among them were performed (totalizing 63 experiments). All fungal extracts were evaluated by H-1 NMR followed by Principal Component Analyses (PCA) in order to determine spectral dissimilarity among the extracts. Results showed that H-1 NMR data evaluated by PCA were capable to predict both antagonism and antifungal activity. Traditional antifungal in vitro assays of active and inactive extracts were also performed in order to prove the prediction made by PCA. The obtained data showed that the approach is an outstanding tool to simultaneously obtain and evaluate bioactive compounds because: it was able to predict the activity of five different extracts in a collection of sixty-three, which would be much more difficult and time consuming if applied randomly; most important antifungal extracts are indicated by PCA; hundreds of traditional in vitro assays are avoid; and, the method is very time and money saving. (C) 2019 Elsevier B.V. All rights reserved. (AU)

Processo FAPESP: 13/07600-3 - CIBFar - Centro de Inovação em Biodiversidade e Fármacos
Beneficiário:Glaucius Oliva
Linha de fomento: Auxílio à Pesquisa - Centros de Pesquisa, Inovação e Difusão - CEPIDs