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Culture-Independent Analysis of Bacterial Fuel Contamination Provides Insight into the Level of Concordance with the Standard Industry Practice of Aerobic Cultivation

机译:与文化无关的细菌燃料污染分析可深入了解与有氧栽培标准行业惯例的一致程度

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摘要

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.
机译:尚未使用与栽培无关的方法来系统地研究受污染燃料中的细菌多样性。燃料工业依靠基于表型培养的污染物识别,这种识别可能缺乏准确性,而忽视了难以培养的分类单元。通过采用行业有氧培养,16S rRNA基因测序和菌株基因分型,从54个燃料样品中收集了152个独特的污染物分离物,并在假单胞菌(21%),伯克霍尔德氏菌(7%)和芽孢杆菌中占主导地位(7%)被证明。 15个样品的变性梯度凝胶电泳(DGGE)表明,Proteobacteria和Firmicutes是最丰富的门。当对四个选定的燃料样品(以“ JW”表示)进行16S rRNA V6基因焦磷酸测序时,β变形杆菌(42.8%)和γ变形杆菌(30.6%)形成了最大的读取比例。最丰富的属是Marinobacter(15.4%; JW57),Achromobacter(41.6%; JW63),Burkholderia(80.7%; JW76)和Halomonas(66.2%; JW78),所有这些都由DGGE观察到。但是,通过DGGE或好氧培养未观察到焦磷酸测序法鉴定的梭菌(38.5%)和变形杆菌(11.1%)。基因分型揭示了三个发现相同菌株的情况:(i)假单胞菌属。从同一工厂的两个不同的柴油燃料箱中回收的菌株; (ii)红树菌从一个炼油厂的三个生物柴油储罐中分离出的菌株; (iii)在两个不相关的汽车柴油样品中存在的伯克霍尔德菌 vietnamiensis 菌株。总体而言,有氧培养回收的燃料污染物分离物广泛代表了目前存在的门和类别,但由于某些类别的成员(如 Pseudomonas )的过分代表而缺乏准确性。

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