{"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, Micah Dunthorn, Quentin Mauvisseau, 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, Micah Dunthorn, Quentin Mauvisseau, 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}
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.
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