Screening And Characterization of Lipopeptide Biosurfactant Producing Paenibacilus Dendritiformis And Its Applicability for Enhanced Oil Recovery
Abstract The bio-surfactants produced by microorganisms have high demand from microbial-enhanced oil recovery (MEOR) and they have focused on a chemical surfactant for the past few decades for degrading petro-based pollutants and oil spills due to its non-toxicity and increasing bioavailability. These microorganisms can survive over the different oil species and contaminants that lead to their degradation with carbon dioxide and water as the remnants. The study aims to identify and screen potential lipopeptide biosurfactant produced by Paenibacillus species employing a design experiment based on response surface methodology (RSM). The bacterial culture was isolated from India's most significant brackish water, Chilika Lake. It screened using various protocols, including oil spread assay, BATH, drop collapse assay, hydrocarbon overlay agar method, E24, etc. The acid precipitation performed to extract the biosurfactant produced by isolate succeeding solvent recovery. 0.426g of biosurfactant per 100ml medium was obtained from the isolated novel Paenibacillus dendritiformis strain (C50H87N7O13), having a molecular weight of 999.300g/mol. The highest yield is attained at emulsification activity (E24 = 73.37%), having optimized environmental parameters (pH- 7, temp- 30°C and 4% salinity) using crude oil as the sole carbon source. The isolated novel strain owing an advantage in improving bioremediation of PAH (polycyclic aromatic hydrocarbons) and efficiently impact the environmental contaminants due to its high lipopeptide concentration up to a threshold level. Based on the Box-Behnken experimental design, the E24 values were varied from 24.6% to 73.3%, and the highest E24 was observed for pH 7, temperature 30°C and 4% salinity. The data generated from the biosurfactant stability experiments were used to fit a regression model using the parameters such as ph, temp and salinity to predict the E24 index. R-squared value 0.91 obtained from the annova model explains that the regression model was significant, and the model p-value obtained was < 0.05 and was also statistically significant. Therefore the statistical regression model obtained in the present investigation can predict the E24 index by using any combination of ph, temp and salinity parameters. Molecular characterization of the isolate was carried out by 16S rRNA gene sequencing using Sanger dideoxy sequencing followed by a phylogenetic assessment. The isolate was found to be a novel strain of Paenibacillus dendritiformis, further named Paenibacillus dendritiformis ANSKLAB02. The novel isolates obtained in this research was deposited in GenBank with accession number KU518891. The present study contributes to the list of such microbial factories by introducing a new strain of Paenibacillus dendritiformis. The growth of this species under controlled conditions has a high potential to help in environmental clean-up and is suitable for use in MEOR applications.