4.0 Article

Isolation, Identification and Optimization of Phenanthrene Degrading Bacteria From the Coastal Sediments of Nayband Bay

Journal

JUNDISHAPUR JOURNAL OF MICROBIOLOGY
Volume 6, Issue 9, Pages -

Publisher

KOWSAR PUBL
DOI: 10.5812/jjm.13816

Keywords

RSM; PAHs; Biodegradation

Categories

Funding

  1. Shahid Beheshti University
  2. G.C.
  3. POGC

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Background: Biodegradation of polycyclic aromatic hydrocarbons (PAHs) contaminated sediments is an effective remediation technique and its success depends on the optimal condition of PAH-degrading isolates. Objectives: The present study was conducted to isolate the PAHs-degrading bacteria from Nayband bay mangrove sediments and to investigate the effect of different variables on phenanthrene (Phe) biodegrading efficiency of the most effective isolated strains, by using response surface methodology (RSM). Materials and Methods: Phe degrading bacteria were isolated from surface sediments. Isolated strains were then identified by biochemical and molecular (16S rDNA gene sequence) analysis. RSM was employed to evaluate the optimum biodegradation of Phe by the most effective isolated strain. The investigated parameters included the temperature, inoculum sizes, pH, NH4Cl concentration, and salinity. Results: One Gram-negative bacterium strain (SBU1) was isolated from enrichment consortium SBU. SBU1 have been identified by 16S rDNA sequence analysis and revealed 96% homology with Roseovarius sp., the biodegradation activity of the SBU1 was properly interpreted using a second-order polynomial regression model. Maximum biodegradation efficiency was predicted at pH = 8.2, temperature approximate to 35 degrees C, salinity = 30 ppt, NH4Cl concentration = 0.13 g/L and inoculum size = 0.2 OD600nm. Under these conditions the aerobic biodegradation rate reached up to 28.4%. Conclusions: Indigenous bacteria from mangrove surface sediments of Nayband bay were found to be able to degrade Phe. The similarity of the predicted and observed results confirmed the validity and applicability of RSM in optimization processes.

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