Open AccessMETABOLIC SCREENING FOR PKS AND NRPS IN ENDOPHYTIC ACTINOBACTERIA FROMCitrus reticulata
Author(s) -
Pedro Luis Rocha da Cruz,
Leila R. Giarola,
Suellen da Silva Moraes,
Déborah Ellen S. G. da Silva,
Joelma Marcon,
João Lúcio de Azevedo,
Welington Luiz Araújo,
Luciana G. de Oliveira
Publication year - 2015
Publication title -
química nova
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.214
H-Index - 73
eISSN - 1678-7064
pISSN - 0100-4042
DOI - 10.5935/0100-4042.20150010
Subject(s) - polyketide , actinobacteria , biology , gene , polyketide synthase , in silico , computational biology , 16s ribosomal rna , gene cluster , genetics , biochemistry , enzyme , biosynthesis
Polyketides and non-ribosomal peptides are natural products widely found in bacteria, fungi and plants. The biological activities associated with these metabolites have attracted special attention in biopharmaceutical studies. Polyketide synthases act similarly to fatty acids synthetases and the whole multi-enzymatic set coordinating precursor and extending unit selection and reduction levels during chain growth. Acting in a similarly orchestrated model, non-ribosomal peptide synthetases biosynthesize NRPs. PKSs-I and NRPSs enzymatic modules and domains are collinearly organized with the parent gene sequence. This arrangement allows the use of degenerated PCR primers to amplify targeted regions in the genes corresponding to specific enzymatic domains such as ketosynthases and acyltransferases in PKSs and adenilation domains in NRPSs. Careful analysis of these short regions allows the classifying of a set of organisms according to their potential to biosynthesize PKs and NRPs. In this work, the biosynthetic potential of a set of 13 endophytic actinobacteria from Citrus reticulata for producing PKs and NRP metabolites was evaluated. The biosynthetic profile was compared to antimicrobial activity. Based on the inhibition promoted, 4 strains were considered for cluster analysis. A PKS/NRPS phylogeny was generated in order to classify some of the representative sequences throughout comparison with homologous genes. Using this approach, a molecular fingerprint was generated to help guide future studies on the most promising strains