RESUMO
Polycyclic aromatic hydrocarbons (PAHs) are chemical compounds that are widespread in the environment, arising from the incomplete combustion of organic material, as well as from human activities involving petrol exploitation, petrochemical industrial waste, gas stations, and environmental disasters. PAHs of high molecular weight, such as pyrene, have carcinogenic and mutagenic effects and are considered pollutants. The microbial degradation of PAHs occurs through the action of multiple dioxygenase genes (nid), which are localized in genomic island denominate region A, and cytochrome P450 monooxygenases genes (cyp) dispersed in the bacterial genome. This study evaluated pyrene degradation by five isolates of Mycolicibacterium austroafricanum using 2,6-dichlorophenol indophenol (DCPIP assay), gas chromatography/mass spectrometry (CG/MS), and genomic analyses. Two isolates (MYC038 and MYC040) exhibited pyrene degradation indexes of 96% and 88%, respectively, over a seven-day incubation period. Interestingly, the genomic analyses showed that the isolates do not have nid genes, which are involved in PAH biodegradation, despite their ability to degrade pyrene, suggesting that degradation may occur due to the presence of cyp150 genes, or even genes that have not yet been described. To the best of our knowledge, this is the first report of isolates without nid genes demonstrating the ability to degrade pyrene.
RESUMO
Genomics research has produced an exponential amount of data. However, the genetic knowledge pertaining to certain phenotypic characteristics is lacking. Also, a considerable part of these genomes have coding sequences (CDSs) with unknown functions, posing additional challenges to researchers. Phylogenetically close microorganisms share much of their CDSs, and certain phenotypes unique to a set of microorganisms may be the result of the genes found exclusively in those microorganisms. This study presents the GTACG framework, an easy-to-use tool for identifying in the subgroups of bacterial genomes whose microorganisms have common phenotypic characteristics, to find data that differentiates them from other associated genomes in a simple and fast way. The GTACG analysis is based on the formation of homologous CDS clusters from local alignments. The front-end is easy to use, and the installation packages have been developed to enable users lacking knowledge of programming languages or bioinformatics analyze high-throughput data using the tool. The validation of the GTACG framework has been carried out based on a case report involving a set of 161 genomes from the Xanthomonadaceae family, in which 19 families of orthologous proteins were found in 90% of the plant-associated genomes, allowing the identification of the proteins potentially associated with adaptation and virulence in plant tissue. The results show the potential use of GTACG in the search for new targets for molecular studies, and GTACG can be used as a research tool by biologists who lack advanced knowledge in the use of computational tools for bacterial comparative genomics.
