Reconstruction of an industry related biofilm into a proxy model community – Challenges around Field and lab based microbial growth analysis

Biofilms Pub Date : 2020-07-01 DOI:10.5194/biofilms9-52
Damon C. Brown, R. Turner
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Abstract

In the oil and gas industry, internal corrosion represents one of the major threats to asset lifetime and integrity. Of the types of internal corrosion, microbiologically influenced corrosion (MIC) is the most difficult to predict and monitor due to the unpredictable nature of microbial growth and the minimal metal loss resulting in through wall failure (pitting). MIC results from biofilm communities interacting directly and indirectly with the metal. Due to the structure and nature of these pipelines, directly monitoring sessile growth is impossible. As a result, most MIC monitoring is done through planktonic cells retrieved from fluid samples as a proxy for sessile populations.

Growth curves are one of the most fundamental methods of quantitatively assessing microbial growth. In the lab, pure cultures are measured using optical densities, biomass staining, direct microscopic counting and counting colony forming units (CFU) on specialized media while more advanced techniques involve quantitative PCR (qPCR) of key genes. While PCR technologies are more easily transferred from the field to the lab, CFU counts are impossible in the field. Alternatives to the CFU are colorimetric activity assays such as “bug bottles” or biological activity reaction test (BART) bottles but aren’t sensitive and require long incubation times. More sensitive assays such as ATP measurements are also used but can be misleading as high metabolically active samples will give higher cell count equivalents than a metabolically slow community of an identical size.

To systematically evaluate a best practice, we conducted growth curves in a lab scenario using six pure cultures and techniques predominantly used in the field to determine how these techniques compare and accurately measure microbial growth. The six species used are Acetobacterium woodii, Bacillus subtilis, Desulfovibrio vulgaris, Geoalkalibacter subterraneus, Pseudomonas putida and Thauera aromatica. The techniques used are optical density at 600 nm, ATP activity measurements using a luciferase-based assay, DNA concentration and 16S rRNA copy numbers.

It was found that most lines of data follow the expected sigmoidal growth curve to varying degrees for all species. OD600 readings follow the expected sigmoidal curves, exhibiting a lag phase, log growth phase and a stationary phase. ATP peaks during mid log phase and quickly declines, never showing a distinct stationary phase, while DNA concentrations closely follow the OD600 readings but decline to death phase more rapidly. qPCR of the 16S rRNA genes revealed this data followed the same trends but was less susceptible to fluctuations.

Assessing microbial biofilms in the environment and on anthropogenic industrial infrastructure is extremely challenging given sampling, storage and transportation to the lab.  This work begins to establish best practices for growth of environmental communities to be followed.  Cumulatively, this work shows that each approach supports the expected growth curve. Considerations should be made if all field data is of a single type, e.g. ATP, as it measures activity and not total cell count. Collecting even two lines of evidence in the field will greatly improve the quality of assessment and strengthen any conclusions regarding assessment of microbial growth.

将工业相关的生物膜重建为代理模型群落-围绕现场和实验室微生物生长分析的挑战
在油气行业中,内部腐蚀是影响资产使用寿命和完整性的主要威胁之一。在各种类型的内部腐蚀中,微生物影响腐蚀(MIC)是最难预测和监测的,因为微生物生长的不可预测性和导致穿壁破坏(点蚀)的最小金属损失。MIC是生物膜群落直接或间接与金属相互作用的结果。由于这些管道的结构和性质,直接监测无根生长是不可能的。因此,大多数MIC监测是通过从流体样品中提取浮游细胞作为无根细胞群的代表来完成的。生长曲线是定量评价微生物生长的最基本方法之一。在实验室中,纯培养物是使用光学密度、生物量染色、直接显微镜计数和在专门培养基上计数菌落形成单位(CFU)来测量的,而更先进的技术涉及关键基因的定量PCR (qPCR)。虽然PCR技术更容易从现场转移到实验室,但CFU计数在现场是不可能的。CFU的替代品是比色活度测定法,如“或生物活性反应试验(BART)瓶,但不敏感,需要较长的孵育时间。更敏感的测定,如ATP测量也被使用,但可能会产生误导,因为高代谢活跃的样品将比相同大小的代谢缓慢的社区给出更高的细胞计数当量。为了系统地评估最佳实践,我们在实验室场景中使用六种纯培养物和在现场主要使用的技术进行生长曲线,以确定这些技术如何比较和准确测量微生物生长。所使用的6种是伍氏醋酸杆菌、枯草芽孢杆菌、普通脱硫弧菌、地下土碱杆菌、恶臭假单胞菌和芳香Thauera。使用的技术是600 nm的光密度、基于荧光素酶的ATP活性测量、DNA浓度和16S rRNA拷贝数。结果发现,所有物种的大多数数据线都不同程度地遵循预期的s型生长曲线。OD600读数遵循预期的s型曲线,显示滞后阶段,对数增长阶段和平稳阶段。ATP在log期中期达到峰值并迅速下降,从未显示出明显的稳定期,而DNA浓度与OD600读数密切相关,但下降到死亡期的速度更快。16S rRNA基因的qPCR显示,这些数据遵循相同的趋势,但不太容易受到波动的影响。在给定采样、储存和运输到实验室的情况下,评估环境和人为工业基础设施中的微生物生物膜极具挑战性。 这项工作开始确立环境社区发展的最佳做法。 累积起来,这项工作表明,每种方法都支持预期的增长曲线。如果所有的现场数据都是单一类型,例如ATP,则应考虑,因为它测量的是活性而不是总细胞计数。即使在实地收集两种证据,也将大大提高评估的质量,并加强有关微生物生长评估的任何结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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