{"title":"从低生物量环境样品中扩增16S rRNA基因的数字聚合酶链反应验证。","authors":"Veronika V Koziaeva, Katja Engel, Josh D Neufeld","doi":"10.1093/ismeco/ycaf115","DOIUrl":null,"url":null,"abstract":"<p><p>Digital polymerase chain reaction (dPCR) is a DNA quantification technology that offers absolute quantification of DNA templates. In this study, we optimized and validated a chip-based dPCR EvaGreen assay with commonly used 16S rRNA gene primer pairs and compared its performance to quantitative real-time PCR (qPCR). We compared measurements of low amounts of template DNA using a newly designed synthetic DNA standard to assess precision, accuracy, and sensitivity. Optimization approaches were tested to minimize partitions with intermediate fluorescence levels between true positive and true negative partitions (so-called \"rain\") for dPCR. Both dPCR and qPCR demonstrated similar quantification performance, with variability in accuracy increasing for samples containing fewer than 30 copies μl<sup>-1</sup> template concentrations. Both tested 16S rRNA gene primer sets amplified non-target template contaminants within both qPCR and dPCR mixtures, which could not be eliminated by ultraviolet light or DNAse treatment and negatively affected the apparent sensitivity of both PCR assays. Digital PCR was less susceptible to common PCR inhibitors, such as ethanol and humic acids, but was more susceptible to tannic acid inhibition than qPCR. These findings demonstrate the suitability of dPCR for 16S rRNA gene quantification of low biomass environmental samples.</p>","PeriodicalId":73516,"journal":{"name":"ISME communications","volume":"5 1","pages":"ycaf115"},"PeriodicalIF":6.1000,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12342375/pdf/","citationCount":"0","resultStr":"{\"title\":\"Validating digital polymerase chain reaction for 16S rRNA gene amplification from low biomass environmental samples.\",\"authors\":\"Veronika V Koziaeva, Katja Engel, Josh D Neufeld\",\"doi\":\"10.1093/ismeco/ycaf115\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Digital polymerase chain reaction (dPCR) is a DNA quantification technology that offers absolute quantification of DNA templates. In this study, we optimized and validated a chip-based dPCR EvaGreen assay with commonly used 16S rRNA gene primer pairs and compared its performance to quantitative real-time PCR (qPCR). We compared measurements of low amounts of template DNA using a newly designed synthetic DNA standard to assess precision, accuracy, and sensitivity. Optimization approaches were tested to minimize partitions with intermediate fluorescence levels between true positive and true negative partitions (so-called \\\"rain\\\") for dPCR. Both dPCR and qPCR demonstrated similar quantification performance, with variability in accuracy increasing for samples containing fewer than 30 copies μl<sup>-1</sup> template concentrations. Both tested 16S rRNA gene primer sets amplified non-target template contaminants within both qPCR and dPCR mixtures, which could not be eliminated by ultraviolet light or DNAse treatment and negatively affected the apparent sensitivity of both PCR assays. Digital PCR was less susceptible to common PCR inhibitors, such as ethanol and humic acids, but was more susceptible to tannic acid inhibition than qPCR. These findings demonstrate the suitability of dPCR for 16S rRNA gene quantification of low biomass environmental samples.</p>\",\"PeriodicalId\":73516,\"journal\":{\"name\":\"ISME communications\",\"volume\":\"5 1\",\"pages\":\"ycaf115\"},\"PeriodicalIF\":6.1000,\"publicationDate\":\"2025-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12342375/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ISME communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/ismeco/ycaf115\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"ECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISME communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/ismeco/ycaf115","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"ECOLOGY","Score":null,"Total":0}
Validating digital polymerase chain reaction for 16S rRNA gene amplification from low biomass environmental samples.
Digital polymerase chain reaction (dPCR) is a DNA quantification technology that offers absolute quantification of DNA templates. In this study, we optimized and validated a chip-based dPCR EvaGreen assay with commonly used 16S rRNA gene primer pairs and compared its performance to quantitative real-time PCR (qPCR). We compared measurements of low amounts of template DNA using a newly designed synthetic DNA standard to assess precision, accuracy, and sensitivity. Optimization approaches were tested to minimize partitions with intermediate fluorescence levels between true positive and true negative partitions (so-called "rain") for dPCR. Both dPCR and qPCR demonstrated similar quantification performance, with variability in accuracy increasing for samples containing fewer than 30 copies μl-1 template concentrations. Both tested 16S rRNA gene primer sets amplified non-target template contaminants within both qPCR and dPCR mixtures, which could not be eliminated by ultraviolet light or DNAse treatment and negatively affected the apparent sensitivity of both PCR assays. Digital PCR was less susceptible to common PCR inhibitors, such as ethanol and humic acids, but was more susceptible to tannic acid inhibition than qPCR. These findings demonstrate the suitability of dPCR for 16S rRNA gene quantification of low biomass environmental samples.