Biosurfactant-mediated degradation of petroleum hydrocarbons by indigenous bacteria from contaminated soil in Hyderabad, India 

Petroleum is a global primary raw material and energy resource. Despite its high economic value and energy density, its usage and extraction cause significant environmental pollution and climate change. Biosurfactants, primarily produced by microorganisms, facilitate the degradation of petroleum hydrocarbons by improving their bioavailability and solubility in the environment. Hence, they are considered as eco-friendly and biodegradable substitutes for bioremediation applications. In the current study, five novel bacterial strains, Rhodococcus sp. strain SARSHI1, Pseudomonas sp. strain SARSHI2, Pseudomonas sp. strain SARSHI3, Acinetobacter sp. strain SARSHI4, and Rhodococcus sp. strain SARSHI5, were isolated, identified, and functionally characterized to evaluate their biosurfactant-producing and hydrocarbon-degrading efficiency. The strains were systematically screened to assess their cell-surface hydrophobicity, biosurfactant activity, emulsification activity, and hydrocarbon-degrading efficiency, etc. Among all the strains, SARSHI1 governed the highest quantitative results by achieving the highest biosurfactant-producing capacity (2.54 g/L), lowest reduced-surface tension (26.87 ± 0.05 mN/m) and CMC (67 mg/L), highest adhesive bioactivity (70.6 ± 2.1%), highest emulsification index (E 24 − 81 ± 0.45%), and highest hydrocarbon degradation profile (82% under glycerol supplemented condition). Media optimization analysis revealed the factors for improving the biosurfactant yield at pH 7.0, temperature (30–50 °C), 4% yeast extract, and 4% crude oil concentration. The molecular and taxonomical assessment was conducted by 16S rRNA sequencing, with partial sequences submitted to the GenBank database with unique accession numbers: ‘PV034287’, ‘OP597529’, ‘OP584476’, ‘OQ711779’, and ‘OQ711775’ for SARSHI1–SARSHI5, respectively. Lastly, the secondary structure of the 16S rRNA sequences was determined using the UNAFold algorithm. Therefore, the findings of this study present a robust preliminary functional framework for advanced microbial studies and highlight the potential of native bacterial strains for developing economical bioremediation applications to combating petroleum pollution.