CHARACTERIZATION AND STATISTICAL OPTIMIZATION OF BIOSURFACTANT PRODUCTION USING BACILLUS SUBTILIS ISOLATED FROM AUTOMOTIVE OIL-CONTAMINATED SOIL IN YOLA, NIGERIA
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Ja’afaru, Mohammed Inuwa
Abbas, Tema
Ajunwa, Obinna Markraphael
Olaifa, Kayode
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Scientific African
Abstract
The need for cost effective and ecofriendly means of producing compounds of environ- mental, industrial, and other biotechnological applications cannot be overemphasized. Bio- surfactant from microbial sources have been identified to have the potential to substitute chemical types. This has led to the continuous bioprospecting for biosurfactant-producing microorganisms and optimization of processes for high yield biosurfactant production. De- spite the widespread, high levels of oil-induced soil pollution in Yola, Nigeria and its en- virons, there is dearth of information on the potential application of indigenous bacteria for biosurfactant production. In this study, a Bacillus subtilis B3 strain was isolated from an automotive oil-contaminated soil in Yola, and was further used for production, char- acterization, and optimization of biosurfactant activity. The partially purified biosurfactant had a structural elucidation of a lipopeptide and exhibited surface tension reduction of distilled water from 72 to 29.30 mN/m. It also forms stable emulsions between pH 6-8 and temperature 60-80 °C, and a critical micelle concentration of 0.65 %. The dry weight of the purified biosurfactant was 0.25 g/L representing a 1.6-fold increase in comparison with one obtained from conventional medium with 0.16 g/L biosurfactant yield. This find- ing suggests that the bacterial strain isolated in this study has the potential to meet the demand for bioremediation and other industrial exploitations.
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Ja’afaru, M. I., Abbas, T., Ajunwa, O. M., & Olaifa, K. (2022). Characterization and statistical optimization of biosurfactant production using Bacillus subtilis isolated from automotive oil-contaminated soil in Yola, Nigeria. Scientific African, 17, e01357. https://doi.org/10.1016/j.sciaf.2022.e01357
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