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比较含生物膜环境中 16S rRNA 基因扩增子分析的 DNA 分离和测序策略。

Comparing DNA isolation and sequencing strategies for 16S rRNA gene amplicon analysis in biofilm containing environments.

机构信息

Environmental Research Institute, University of the Highlands and Islands, Castle Street, Thurso, Caithness, Scotland KW14 7JD, UK.

Institute for Biodiversity and Freshwater Conservation, University of the Highlands and Islands, 1 Inverness Campus, Inverness, Scotland IV2 5NA, UK.

出版信息

J Microbiol Methods. 2024 May;220:106921. doi: 10.1016/j.mimet.2024.106921. Epub 2024 Mar 16.

Abstract

Bacteria are primarily responsible for biological water treatment processes in constructed wetland systems. Gravel in constructed wetlands serves as an essential substrate onto which complex bacterial biofilms may successfully grow and evolve. To fully understand the bacterial community in these systems it is crucial to properly isolate biofilms and process DNA from such substrates. This study looked at how best to isolate bacterial biofilms from gravel substrates in terms of bacterial richness. It considered factors including the duration of agitation during extraction, extraction temperature, and enzyme usage. Further, the 16S taxonomy data subsequently produced from Illumina MiSeq reads (using the SILVA 132 ribosomal RNA (rRNA) database on the DADA2 pipeline) were compared with the 16S data produced from Oxford Nanopore Technologies (ONT) MinION reads (using the NCBI 16S database on the EPI2ME pipeline). Finally, performance was tested by comparing the taxonomy data generated from the Illumina MiSeq and ONT MinION reads using the same (SILVA 132) database. We found no significant differences in the effective number of species observed when using different bacterial biofilm detachment techniques. However, enzyme treatment enhanced the total concentration of DNA. In terms of wetland community profiles, relative abundance differences within each sample type were clearer at the genus level. For genus-level taxonomic classification, MinION sequencing with the EPI2ME pipeline (NCBI database) produced bacterial abundance information that was poorly correlated with that from the Illumina MiSeq and DADA2 pipelines (SILVA132 database). When using the same database for each sequencing technology (SILVA132), the correlation between relative abundances at genus-level improved from negligible to moderate. This study provides detailed information of value to researchers working on constructed wetlands regarding efficient biofilm detachment techniques for DNA isolation and 16 s metabarcoding platforms for sequencing and data analysis.

摘要

细菌是人工湿地系统中生物水处理过程的主要责任人。砾石在人工湿地中是一种重要的基质,可以成功地生长和进化复杂的细菌生物膜。为了充分了解这些系统中的细菌群落,必须正确分离生物膜并从这些基质中提取 DNA。本研究着眼于从砾石基质中分离细菌生物膜时,从细菌丰富度的角度考虑了最佳的提取方法。它考虑了提取过程中搅拌的持续时间、提取温度和酶的使用等因素。此外,随后使用 DADA2 管道中的 SILVA 132 核糖体 RNA(rRNA) 数据库从 Illumina MiSeq 读取中生成的 16S 分类学数据与使用 EPI2ME 管道中的 NCBI 16S 数据库从 ONT MinION 读取中生成的 16S 数据进行了比较。最后,通过使用相同的 (SILVA 132) 数据库比较从 Illumina MiSeq 和 ONT MinION 读取生成的分类学数据,测试了性能。我们发现,使用不同的细菌生物膜分离技术时,观察到的有效物种数量没有显著差异。然而,酶处理提高了 DNA 的总浓度。就湿地群落图谱而言,每种样本类型内的相对丰度差异在属水平上更为明显。对于属水平的分类学分类,使用 EPI2ME 管道(NCBI 数据库)进行 MinION 测序产生的细菌丰度信息与使用 Illumina MiSeq 和 DADA2 管道(SILVA132 数据库)产生的信息相关性较差。当为每个测序技术使用相同的数据库 (SILVA132) 时,属水平的相对丰度相关性从微不足道提高到中等水平。本研究为从事人工湿地研究的研究人员提供了有关有效生物膜分离技术的详细信息,用于 DNA 分离和 16s 代谢组学平台用于测序和数据分析。

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