Searching for glyphosate-degrading flavoenzymes in Ambargasta Salt Flat through metagenomics and protein modeling

ZERDA MOREIRA, ANDREA; LÓPEZ, MARÍA BELEN; GONZALEZ, JAVIER MARCELO

Rosario

Congreso; L Reunión Anual de la Sociedad Argentina de Biofísica; 2022

Ambargasta salt flat (ASF) located in the southwest of Santiago del Estero, Argentina, with an area of 4,200 Km2, is part of the Cuenca Saliniana, considered one of the largest salt flats in the world. Its geological and extreme climatical conditions, along with the possible accumulation of xenobiotics (pesticides, herbicides, fertilizers, etc) from irrigation of crops from surrounding areas, make ASF an interesting environment to explore its halophile- adapted microbial community. The aim of this study was to investigate the occurrence of microorganisms in ASF harboring natural variants of FAD-dependent oxidase enzymes, capable of degrading the widely used and controversial herbicide glyphosate. The search for putative glyphosate oxidase enzymes (GLO enzymes) was conducted by metagenomic sequencing of environmental DNA extracted from two samples from different areas in ASF. Metagenomic DNA sequences were assembled using metaSPAdes and the obtained contigs were processed using PROKKA and further annotated through BlastKOALA. All proteins belonging to the D-amino oxidases family (DAO) in the metagenome were identified by hmmsearch using profile hidden Markov models (HMMs). Members of the DAO family were analyzed through sequence similarity network calculation and neighborhood connectivity analysis (SSN-NC). Sequences similar to target GLO enzymes were selected and their structures were modeled using ColabFold. The interaction between predicted proteins structures with glyphosate was analyzed through ligand docking with DockThor. Amino acid residues involved in glyphosate binding and recognition were identified and analyzed in the context of multiple sequence alignments. Our research enables a better understanding of the biodegradation process of glyphosate in soils; and the evolution of GLO enzymes, which acquired specificity for this herbicide. In addition, the comprehension of these mechanisms could help in the advancement of biotechnological solutions for the detection of glyphosate in contaminated environments, such as the development of biosensors based on immobilized GLO enzymes.