Biotechnology Bulletin ›› 2016, Vol. 32 ›› Issue (8): 184-193.doi: 10.13560/j.cnki.biotech.bull.1985.2016.08.027

• Orignal Article • Previous Articles     Next Articles

Screening of Marine Crude Oil-degrading Bacteria and Construction of Microbial Consortium

WU Bing-qi, LIU Shu-jie, CHEN Fu-ming, ZHOU Chu-ying   

  1. Research Institute of Tsinghua University in Shenzhen,Shenzhen Environmental Microbiology Resources Development and Application Engineering Laboratory,Shenzhen 518057
  • Revised:2015-10-22 Online:2016-08-25 Published:2016-08-25

Abstract: For the purpose of controlling marine oil contamination by biological treatment technology,using crude oil acting as sole carbon source and enrichment and spread plate method,high-performance oil-grading bacteria were isolated from five sampling points in the sea near Shenzhen,and bacterial consortium was constructed by mixing and orthogonal experiments. Physiological and biochemical experiments and 16S rRNA gene sequence analysis were used to identify the strains. Single-factor experiment was employed to optimize the conditions of oil biodegradation by the consortium,and gas chromatography and mass spectrum(GC-MS)were utilized to analyze its biodegradation characteristics. The results showed that 22 strains of high-performance oil-degrading bacteria were isolated,and the degrading rates varied from 34.5% to 52.2%. The degrading rate by microbial consortium SQ1 composed of S1-30,S1-38,and S2-13 strains reached 68.3%. These three strains were identified as Corynebacterium sp.,Dietzia sp. and Labrenzia sp. SQ1 was able to degrade the oil by 73.5% in 11 days under optimized conditions,referring to 30℃,pH7.6,oil concentration 20 g/L. The GC-MS results showed that consortium SQ1 was able to degrade the total alkane by 91.7%,and the more refractory C21-C35 by nearly 100%. The study shows that consortium SQ1 has great application potential of bioremediation for marine oil contamination.

Key words: oil-degrading bacteria, microbial consortium, degradation rate, identification, condition optimization