Developing a molecular tool for evaluating the status of petrochemical-contaminated soils using functional gene ratio strategy.

Petrochemical spills present a global environmental challenge, necessitating effective monitoring and remediation. This study was designed to develop a molecular tool using binary functional gene ratios to assess contamination levels and timelines in petrochemical-contaminated soils. Soils from petrochemical-contaminated sites were collected and hydrocarbon quantification was performed using gas chromatography-mass spectrometry and two-dimensional gas chromatography with flame ionization detection, against specific standards. Metagenomic DNA was extracted, and functional genes associated with hydrocarbon degradation [PAH Ring-hydroxylating dioxygenase (PAH-RHDα) and 6-oxocyclohex-1-ene-1-carbonyl-CoA hydrolase (bamA)] were analysed using quantitative PCR (qPCR). A diagnostic ratio of PAH degradation genes was applied to characterize pollution. In-silico gene mining was used to verify the functional gene ratios. MS revealed distinct contamination profiles correlating with pollution duration and pollutant levels. One set of samples had kerosene concentrations between 154 and 478.64 µg/g of soil, while the other contained <11 µg/g. Functional genes analysis linked higher kerosene concentrations to increased Gram-negative dioxygenase levels and lower kerosene concentrations to Gram-positive dioxygenases. PAH-RHDα-GN: bamA and PAH-RHDα-GP: bamA reflected contamination levels and apparent pollution age. In-silico gene mining validated qPCR findings, confirming the reliability of gene ratios for environmental monitoring. Our findings show that the functional gene ratios serve as a molecular biomarker for spill characterization, offering a novel approach for assessing and monitoring contamination in soils.