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The growth of the Rhodococcus sp. on diesel fuel under the effect of heavy metals and different concentrations of zinc

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Advances in Polar Science 2020年第2期31卷 132-136页

作者： Eg Xiang KAI wan lutfi wan johari Syahir HABIB Nur Adeela YASID Siti Aqlima AHMAD Mohd Yunus SHUKOR Department of Environment Faculty of Forestry and EnvironmentUniversiti Putra Malaysia43400 UPM SerdangSelangorMalaysia Department of Biochemistry Faculty of Biotechnology and Biomolecular SciencesUniversiti Putra Malaysia43400 UPM SerdangSelangorMalaysia

Co-contamination of diesel fuel and heavy metals can be challenging for microbial remediation due to the complex composition of the fuel and the inhibitory effect of heavy *** is an urgent need to study this interaction to improve the pollutant removal efficiency in the Polar *** growth of an Antarctic bacterium,Rhodococcus *** studied by comparing the growth at the logarithmic phase under the effect of selected heavy metals(Pb,Cr,As,Cd,Cu,Zn,Ni,Hg and Co).The selected heavy metals inhibited the growth of the Rhodococcus *** diesel fuel in an order from highest to lowest of:Hg>Zn>Cd>Cu>Co>Ni>As>Pb>*** on diesel fuel co-contaminated with Hg and Zn were 2.95%and 5.71%,respectively compared to the no-metal control.A further experiment with various Zn concentrations was *** specific growth rate of Rhodococcus ***-contaminated with different concentrations of Zn showed a correlation coefficient(r)of 0.916,and was modelled with an exponential decay *** investigation is needed to determine the effect of low concentration of Zn on hydrocarbon *** is important to understand the relationships between microbes,hydrocarbons and heavy metals,especially in the Polar Regions because this interaction might be promising in treating hydrocarbon-polluted sites containing heavy *** data and results also provide baseline tools of bioremediation processes at low temperatures and the knowledge of the ecological roles of Rhodococcus *** Antarctica.

关键词： co-conamination diesel heavy metals Rhodococcus sp. exponential decline model

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