PGPg_finder: A comprehensive and user-friendly pipeline for identifying plant growth-promoting genes in genomic and metagenomic data

Abstract

Identifying and comparing plant growth-promoting traits (PGPT) within whole-genome and metagenomic sequencing data can significantly advance agricultural research and promote sustainable crop production. This study introduces PGPg_finder, a comprehensive pipeline designed to annotate and compare PGPT from both whole-genome and metagenome sequencing datasets. This pipeline utilizes direct sequence annotation alongside de novo assembly methods to accurately detect PGPT. By cross-referencing sequences from the PLaBAse database, it identifies and quantifies the presence of these genes within the original datasets, facilitating an intuitive comparison of the abundance and distribution of PGPT across various samples. We evaluated the performance of PGPg_finder by analyzing genomes from five rhizobacterial strains: Paenibacillus vini, Paenibacillus polymyxa, Fictibacillus sp., Brevibacillus agri, and Bacillus cereus, and also metagenomic samples from bulk soils subjected to forest-to-pasture conversion in the Amazon rainforest. The genomic workflow revealed several genes associated with substrate utilization, abiotic stress neutralization, phosphate solubilization, and iron acquisition. It also identified genes unique to specific lineages, including those associated with colonization and plant-derived substrate usage in P. polymyxa, quorum sensing response and biofilm formation in P. vini, heavy metal detoxification and nitrogen acquisition in B. agri, and spore production and neutralizing biotic stress in B. cereus. The strain Fictibacillus sp. presented several unique genes related to surface attachment, stress response, xenobiotic degradation, phosphate solubilization, and phytohormone production. The use of PGPg_finder highlights its potential to uncover novel inoculants and strains. The metagenomic workflow distinguished plant-growth promotion gene profiles between soils from the Amazon rainforest and pasture, with the latter showing a profile more aligned with simple carbohydrate consumption, abiotic stress tolerance, motility and chemotaxis, and phosphorus mineralization. Native forests exhibited a profile associated with the degradation of complex organic matter, oxidative stress tolerance, xenobiotic degradation, bactericidal activity, iron acquisition, and volatile pathways. These findings underscore the effectiveness and sensitivity of PGPg_finder in accurately identifying and comparing PGPT genes, highlighting both commonalities and variations across samples. The application of this pipeline has the potential to significantly facilitate the identification of plant growth-promoting microbes.