Expanding the Toolbox for Functional Genomics in Fonsecaea pedrosoi : The Use of Split-Marker and Biolistic Transformation for Inactivation of Tryptophan Synthase ( trpB ) Gene.
Luísa Dan FavillaTatiana Sobianski HermanCamila da Silva GoerschRosangela Vieira de AndradeMaria Sueli Soares FelipeAnamélia Lorenzetti BoccaLarissa FernandesPublished in: Journal of fungi (Basel, Switzerland) (2023)
Chromoblastomycosis (CBM) is a disease caused by several dematiaceous fungi from different genera, and Fonsecaea is the most common which has been clinically isolated. Genetic transformation methods have recently been described; however, molecular tools for the functional study of genes have been scarcely reported for those fungi. In this work, we demonstrated that gene deletion and generation of the null mutant by homologous recombination are achievable for Fonsecaea pedrosoi by the use of two approaches: use of double-joint PCR for cassette construction, followed by delivery of the split-marker by biolistic transformation. Through in silico analyses, we identified that F. pedrosoi presents the complete enzymatic apparatus required for tryptophan (trp) biosynthesis. The gene encoding a tryptophan synthase trpB -which converts chorismate to trp-was disrupted. The Δ trpB auxotrophic mutant can grow with external trp supply, but germination, viability of conidia, and radial growth are defective compared to the wild-type and reconstituted strains. The use of 5-FAA for selection of trp - phenotypes and for counter-selection of strains carrying the trp gene was also demonstrated. The molecular tools for the functional study of genes, allied to the genetic information from genomic databases, significantly boost our understanding of the biology and pathogenicity of CBM causative agents.
Keyphrases
- genome wide
- copy number
- genome wide identification
- wild type
- dna methylation
- genome wide analysis
- dna damage
- transcription factor
- dna repair
- gene expression
- hydrogen peroxide
- molecular docking
- nitric oxide
- cystic fibrosis
- social media
- health information
- oxidative stress
- single cell
- deep learning
- big data
- high density
- artificial intelligence