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在多种胁迫条件下,河流表生生物膜中微生物群落结构特征的两种不同方法:开发分子指标。

Two different approaches of microbial community structure characterization in riverine epilithic biofilms under multiple stressors conditions: Developing molecular indicators.

机构信息

Norsk Institutt for Vannforskning (NIVA), Oslo, Norway.

Section for Aquatic Biology and Toxicology, Department of Biosciences, Centre for Biogeochemistry in the Anthropocene, University of Oslo, Norway.

出版信息

Mol Ecol Resour. 2021 May;21(4):1200-1215. doi: 10.1111/1755-0998.13341. Epub 2021 Feb 22.

Abstract

Microbial communities are major players in the biogeochemical processes and ecosystem functioning of river networks. Despite their importance in the ecosystem, biomonitoring tools relying on prokaryotes are still lacking. Only a few studies have employed both metabarcoding and quantitative techniques such as catalysed reported deposition fluorescence in situ hybridization (CARD-FISH) to analyse prokaryotic communities of epilithic biofilms in river ecosystems. We intended to investigate the efficacy of both techniques in detecting changes in microbial community structure associated with environmental drivers. We report a significant correlation between the prokaryotic community composition and pH in rivers from two different geographical areas in Norway. Both CARD-FISH and metabarcoding data were following the pattern of the environmental variables, but the main feature distinguishing the community composition was the regional difference itself. Beta-dispersion analyses on both CARD-FISH abundance and metabarcoding data revealed higher accuracy of metabarcoding to differentiate regions and river systems. The CARD-FISH results showed high variability, even for samples within the same river, probably due to some unmeasured microscale ecological variability which we could not resolve. We also present a statistical method, which uses variation coefficient and overall prevalence of taxonomic groups, to detect possible biological indicators among prokaryotes using metabarcoding data. The development of new prokaryotic bioindicators would benefit from both techniques used in this study, but metabarcoding seems to be faster and more reliable than CARD-FISH for large scale bio-assessment.

摘要

微生物群落是河流网络中生物地球化学过程和生态系统功能的主要参与者。尽管它们在生态系统中很重要,但仍缺乏依赖原核生物的生物监测工具。只有少数研究同时使用了代谢组学和定量技术,如催化报告沉积荧光原位杂交(CARD-FISH)来分析河流生态系统中附生生物膜的原核生物群落。我们旨在研究这两种技术在检测与环境驱动因素相关的微生物群落结构变化方面的效果。我们报告了来自挪威两个不同地理区域的河流中原核生物群落组成与 pH 值之间的显著相关性。CARD-FISH 和代谢组学数据都遵循环境变量的模式,但区分群落组成的主要特征是区域差异本身。CARD-FISH 丰度和代谢组学数据的 Beta 分散分析表明,代谢组学在区分区域和河流系统方面具有更高的准确性。CARD-FISH 结果显示出很高的变异性,即使是在同一河流内的样本也是如此,这可能是由于一些我们无法解决的未测量的微观生态变异性所致。我们还提出了一种统计方法,该方法使用变异系数和分类群的总体流行率,利用代谢组学数据来检测原核生物中的可能生物指标。新的原核生物生物指标的开发将受益于本研究中使用的两种技术,但代谢组学似乎比 CARD-FISH 更适合大规模生物评估,因为它更快且更可靠。

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