Culture-independent analysis of bacterial fuel contamination provides insight into the level of concordance with the standard industry practice of aerobic cultivation

Appl Environ Microbiol. 2011 Jul;77(13):4527-38. doi: 10.1128/AEM.02317-10. Epub 2011 May 20.

Abstract

Bacterial diversity in contaminated fuels has not been systematically investigated using cultivation-independent methods. The fuel industry relies on phenotypic cultivation-based contaminant identification, which may lack accuracy and neglect difficult-to-culture taxa. By the use of industry practice aerobic cultivation, 16S rRNA gene sequencing, and strain genotyping, a collection of 152 unique contaminant isolates from 54 fuel samples was assembled, and a dominance of Pseudomonas (21%), Burkholderia (7%), and Bacillus (7%) was demonstrated. Denaturing gradient gel electrophoresis (DGGE) of 15 samples revealed Proteobacteria and Firmicutes to be the most abundant phyla. When 16S rRNA V6 gene pyrosequencing of four selected fuel samples (indicated by "JW") was performed, Betaproteobacteria (42.8%) and Gammaproteobacteria (30.6%) formed the largest proportion of reads; the most abundant genera were Marinobacter (15.4%; JW57), Achromobacter (41.6%; JW63), Burkholderia (80.7%; JW76), and Halomonas (66.2%; JW78), all of which were also observed by DGGE. However, the Clostridia (38.5%) and Deltaproteobacteria (11.1%) identified by pyrosequencing in sample JW57 were not observed by DGGE or aerobic culture. Genotyping revealed three instances where identical strains were found: (i) a Pseudomonas sp. strain recovered from 2 different diesel fuel tanks at a single industrial site; (ii) a Mangroveibacter sp. strain isolated from 3 biodiesel tanks at a single refinery site; and (iii) a Burkholderia vietnamiensis strain present in two unrelated automotive diesel samples. Overall, aerobic cultivation of fuel contaminants recovered isolates broadly representative of the phyla and classes present but lacked accuracy by overrepresenting members of certain groups such as Pseudomonas.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bacteria / classification*
  • Bacteria / genetics
  • Bacteria / isolation & purification*
  • Bacteriological Techniques / methods*
  • Biodiversity*
  • Cluster Analysis
  • DNA, Bacterial / chemistry
  • DNA, Bacterial / genetics
  • DNA, Ribosomal / chemistry
  • DNA, Ribosomal / genetics
  • Fossil Fuels / microbiology*
  • Molecular Sequence Data
  • Phylogeny
  • RNA, Ribosomal, 16S / genetics
  • Sequence Analysis, DNA

Substances

  • DNA, Bacterial
  • DNA, Ribosomal
  • Fossil Fuels
  • RNA, Ribosomal, 16S

Associated data

  • GENBANK/FN556561
  • GENBANK/FN556562
  • GENBANK/FN556563
  • GENBANK/FN556564
  • GENBANK/FN556565
  • GENBANK/FN556566
  • GENBANK/FN556567
  • GENBANK/FN556568
  • GENBANK/FN556569
  • GENBANK/FN556570
  • GENBANK/FN556571
  • GENBANK/FN556572
  • GENBANK/FN556573
  • GENBANK/FN556574
  • GENBANK/FN556575
  • GENBANK/FN556576
  • GENBANK/FN556577
  • GENBANK/FN556578