Identification and Removal of Potential Contaminants in 16S rRNA Gene Sequence Data Sets from Low-Microbial-Biomass Samples: an Example from Mosquito Tissues.
Identification and Removal of Potential Contaminants in 16S rRNA Gene Sequence Data Sets from Low-Microbial-Biomass Samples: an Example from Mosquito Tissues.
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DOI：
10.1128/msphere.00506-21
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发表时间：
2021-06-16
期刊：
影响因子：
4.8
通讯作者：
Avila FW
中科院分区：
文献类型：
--
作者：
Díaz S;Escobar JS;Avila FW
蚊子的细菌微生物群影响宿主的许多生理过程。作为低微生物量的生态系统，蚊子组织容易受到实验室环境和通常用于从组织样品中分离DNA的试剂的污染。在这份报告中，我们分析了9个16S rRNA数据集，包括我们获得的新数据，以深入了解潜在污染序列对蚊子组织微生物群落的组成，多样性和结构的影响。使用基于组织样本和阴性对照中扩增子序列变体（ASV）相对丰度的无聚类方法，我们鉴定了候选污染序列，这些序列有时与使用已建立的方法发现的结果不同，但一致。一些推定的污染序列属于先前被鉴定为污染物的细菌分类群，其通常在宏基因组研究中发现，但也被鉴定为蚊子核心微生物群的一部分，与宿主具有推定的生理相关性。使用不同的相对丰度截止值，我们表明污染序列对组织微生物群多样性和结构分析有显着影响。在过去的几年里，对蚊子组织相关微生物群（主要来自肠道）的研究有了显着增长。苔藓组织样本对研究人员来说是一个挑战，因为它们的微生物生物量很低，而且在实验室环境和分子试剂中常见的分类组成相似。使用新的和已发表的数据集，从肠道和生殖道组织（及其各自的阴性对照）中识别出蚊子组织微生物群，我们开发了一种简单的方法来识别污染微生物群。该方法使用初始分类鉴定而不使用操作分类单位（OTU）聚类，并评估对照样品序列的相对丰度，从而允许鉴定和去除从低微生物生物量样品获得的数据集中的据称的污染序列。虽然它以蚊子组织微生物群的分析为例，但它可以扩展到处理类似技术工件的其他数据集。
The bacterial microbiota of the mosquito influences numerous physiological processes of the host. As low-microbial-biomass ecosystems, mosquito tissues are prone to contamination from the laboratory environment and from reagents commonly used to isolate DNA from tissue samples. In this report, we analyzed nine 16S rRNA data sets, including new data obtained by us, to gain insight into the impact of potential contaminating sequences on the composition, diversity, and structure of the mosquito tissue microbial community. Using a clustering-free approach based on the relative abundance of amplicon sequence variants (ASVs) in tissue samples and negative controls, we identified candidate contaminating sequences that sometimes differed from, but were consistent with, results found using established methodologies. Some putative contaminating sequences belong to bacterial taxa previously identified as contaminants that are commonly found in metagenomic studies but that have also been identified as part of the mosquito core microbiota, with putative physiological relevance for the host. Using different relative abundance cutoffs, we show that contaminating sequences have a significant impact on tissue microbiota diversity and structure analysis. IMPORTANCE The study of tissue-associated microbiota from mosquitoes (primarily from the gut) has grown significantly in the last several years. Mosquito tissue samples represent a challenge for researchers given their low microbial biomass and similar taxonomic composition commonly found in the laboratory environment and in molecular reagents. Using new and published data sets that identified mosquito tissue microbiota from gut and reproductive tract tissues (and their respective negative controls), we developed a simple method to identify contamination microbiota. This approach uses an initial taxonomic identification without operational taxonomic unit (OTU) clustering and evaluates the relative abundance of control sample sequences, allowing the identification and removal of purported contaminating sequences in data sets obtained from low-microbial-biomass samples. While it was exemplified with the analysis of tissue microbiota from mosquitos, it can be extended to other data sets dealing with similar technical artifacts.