Cardiff School of Biosciences, Cardiff University, Room 0.11E Main Building, Museum Avenue, Cardiff CF10 3AT, United Kingdom.
Appl Environ Microbiol. 2011 Jul;77(13):4527-38. doi: 10.1128/AEM.02317-10. Epub 2011 May 20.
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.
采用基于表型的培养方法对受污染燃料中的细菌多样性进行了系统的研究。燃料行业依赖于基于表型的污染物鉴定方法,这种方法可能不够准确,并且忽略了难以培养的类群。通过使用工业实践中的好氧培养、16S rRNA 基因测序和菌株基因分型,从 54 个燃料样本中收集了 152 个独特的污染物分离株,结果表明,假单胞菌(21%)、伯克霍尔德菌(7%)和芽孢杆菌(7%)占优势。对 15 个样本的变性梯度凝胶电泳(DGGE)分析表明,变形菌门和厚壁菌门是最丰富的门。对四个选定燃料样本(以“JW”表示)的 16S rRNA V6 基因焦磷酸测序显示,β变形菌(42.8%)和γ变形菌(30.6%)是最大的读长比例;最丰富的属是 Marinobacter(15.4%;JW57)、Achromobacter(41.6%;JW63)、Burkholderia(80.7%;JW76)和 Halomonas(66.2%;JW78),这些属在 DGGE 中也有观察到。然而,在 JW57 样本中通过焦磷酸测序鉴定的梭菌(38.5%)和δ变形菌(11.1%)在 DGGE 或好氧培养中未观察到。基因分型显示了三个发现相同菌株的实例:(i)从单个工业现场的两个不同的柴油燃料箱中回收的假单胞菌;(ii)从单个精炼厂现场的 3 个生物柴油箱中分离出的 Mangroveibacter 菌株;(iii)存在于两个不相关的汽车柴油样本中的 Burkholderia vietnamiensis 菌株。总体而言,对燃料污染物的好氧培养恢复了广泛代表存在的门和纲的分离株,但由于过度代表某些群体(如假单胞菌)而缺乏准确性。