利用数字 PCR 从核糖体 RNA 基因拷贝数预测纤毛虫的丰度

IF 4.3 2区 生物学 Q2 MICROBIOLOGY
Megan Gross, Micah Dunthorn, Quentin Mauvisseau, Thorsten Stoeck
{"title":"利用数字 PCR 从核糖体 RNA 基因拷贝数预测纤毛虫的丰度","authors":"Megan Gross,&nbsp;Micah Dunthorn,&nbsp;Quentin Mauvisseau,&nbsp;Thorsten Stoeck","doi":"10.1111/1462-2920.16619","DOIUrl":null,"url":null,"abstract":"<p>Ciliates play a key role in most ecosystems. Their abundance in natural samples is crucial for answering many ecological questions. Traditional methods of quantifying individual species, which rely on microscopy, are often labour-intensive, time-consuming and can be highly biassed. As a result, we investigated the potential of digital polymerase chain reaction (dPCR) for quantifying ciliates. A significant challenge in this process is the high variation in the copy number of the taxonomic marker gene (ribosomal RNA [rRNA]). We first quantified the rRNA gene copy numbers (GCN) of the model ciliate, <i>Paramecium tetraurelia</i>, during different stages of the cell cycle and growth phases. The per-cell rRNA GCN varied between approximately 11,000 and 130,000, averaging around 50,000 copies per cell. Despite these variations in per-cell rRNA GCN, we found a highly significant correlation between GCN and cell numbers. This is likely due to the coexistence of different cellular stages in an uncontrolled (environmental) ciliate population. Thanks to the high sensitivity of dPCR, we were able to detect the target gene in a sample that contained only a single cell. The dPCR approach presented here is a valuable addition to the molecular toolbox in protistan ecology. It may guide future studies in quantifying and monitoring the abundance of targeted (even rare) ciliates in natural samples.</p>","PeriodicalId":11898,"journal":{"name":"Environmental microbiology","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1462-2920.16619","citationCount":"0","resultStr":"{\"title\":\"Using digital PCR to predict ciliate abundance from ribosomal RNA gene copy numbers\",\"authors\":\"Megan Gross,&nbsp;Micah Dunthorn,&nbsp;Quentin Mauvisseau,&nbsp;Thorsten Stoeck\",\"doi\":\"10.1111/1462-2920.16619\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Ciliates play a key role in most ecosystems. Their abundance in natural samples is crucial for answering many ecological questions. Traditional methods of quantifying individual species, which rely on microscopy, are often labour-intensive, time-consuming and can be highly biassed. As a result, we investigated the potential of digital polymerase chain reaction (dPCR) for quantifying ciliates. A significant challenge in this process is the high variation in the copy number of the taxonomic marker gene (ribosomal RNA [rRNA]). We first quantified the rRNA gene copy numbers (GCN) of the model ciliate, <i>Paramecium tetraurelia</i>, during different stages of the cell cycle and growth phases. The per-cell rRNA GCN varied between approximately 11,000 and 130,000, averaging around 50,000 copies per cell. Despite these variations in per-cell rRNA GCN, we found a highly significant correlation between GCN and cell numbers. This is likely due to the coexistence of different cellular stages in an uncontrolled (environmental) ciliate population. Thanks to the high sensitivity of dPCR, we were able to detect the target gene in a sample that contained only a single cell. The dPCR approach presented here is a valuable addition to the molecular toolbox in protistan ecology. It may guide future studies in quantifying and monitoring the abundance of targeted (even rare) ciliates in natural samples.</p>\",\"PeriodicalId\":11898,\"journal\":{\"name\":\"Environmental microbiology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-04-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1462-2920.16619\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental microbiology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/1462-2920.16619\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental microbiology","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/1462-2920.16619","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

纤毛虫在大多数生态系统中都扮演着重要角色。它们在自然样本中的数量对于回答许多生态问题至关重要。传统的单个物种定量方法依赖显微镜,往往需要大量人力、时间,而且可能存在很大偏差。因此,我们研究了数字聚合酶链反应(dPCR)量化纤毛虫的潜力。这一过程中的一个重大挑战是分类标记基因(核糖体 RNA [rRNA])的拷贝数差异很大。我们首先量化了模式纤毛虫四膜虫在细胞周期不同阶段和生长阶段的 rRNA 基因拷贝数(GCN)。每个细胞的 rRNA GCN 在大约 11,000 到 130,000 之间变化,平均每个细胞大约有 50,000 个拷贝。尽管每细胞 rRNA GCN 存在这些差异,但我们发现 GCN 与细胞数量之间存在非常显著的相关性。这可能是由于在不受控制的(环境)纤毛虫种群中,不同细胞阶段同时存在。得益于 dPCR 的高灵敏度,我们能够在仅含有单个细胞的样本中检测到目标基因。本文介绍的 dPCR 方法是对原生动物生态学分子工具箱的宝贵补充。它可以指导未来的研究,量化和监测自然样本中目标(甚至稀有)纤毛虫的数量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Using digital PCR to predict ciliate abundance from ribosomal RNA gene copy numbers

Using digital PCR to predict ciliate abundance from ribosomal RNA gene copy numbers

Ciliates play a key role in most ecosystems. Their abundance in natural samples is crucial for answering many ecological questions. Traditional methods of quantifying individual species, which rely on microscopy, are often labour-intensive, time-consuming and can be highly biassed. As a result, we investigated the potential of digital polymerase chain reaction (dPCR) for quantifying ciliates. A significant challenge in this process is the high variation in the copy number of the taxonomic marker gene (ribosomal RNA [rRNA]). We first quantified the rRNA gene copy numbers (GCN) of the model ciliate, Paramecium tetraurelia, during different stages of the cell cycle and growth phases. The per-cell rRNA GCN varied between approximately 11,000 and 130,000, averaging around 50,000 copies per cell. Despite these variations in per-cell rRNA GCN, we found a highly significant correlation between GCN and cell numbers. This is likely due to the coexistence of different cellular stages in an uncontrolled (environmental) ciliate population. Thanks to the high sensitivity of dPCR, we were able to detect the target gene in a sample that contained only a single cell. The dPCR approach presented here is a valuable addition to the molecular toolbox in protistan ecology. It may guide future studies in quantifying and monitoring the abundance of targeted (even rare) ciliates in natural samples.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Environmental microbiology
Environmental microbiology 环境科学-微生物学
CiteScore
9.90
自引率
3.90%
发文量
427
审稿时长
2.3 months
期刊介绍: Environmental Microbiology provides a high profile vehicle for publication of the most innovative, original and rigorous research in the field. The scope of the Journal encompasses the diversity of current research on microbial processes in the environment, microbial communities, interactions and evolution and includes, but is not limited to, the following: the structure, activities and communal behaviour of microbial communities microbial community genetics and evolutionary processes microbial symbioses, microbial interactions and interactions with plants, animals and abiotic factors microbes in the tree of life, microbial diversification and evolution population biology and clonal structure microbial metabolic and structural diversity microbial physiology, growth and survival microbes and surfaces, adhesion and biofouling responses to environmental signals and stress factors modelling and theory development pollution microbiology extremophiles and life in extreme and unusual little-explored habitats element cycles and biogeochemical processes, primary and secondary production microbes in a changing world, microbially-influenced global changes evolution and diversity of archaeal and bacterial viruses new technological developments in microbial ecology and evolution, in particular for the study of activities of microbial communities, non-culturable microorganisms and emerging pathogens
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信