INRA-Université de Bourgogne, UMR Microbiologie du Sol et de l'Environnement, CMSE, Dijon, France.
PLoS One. 2011;6(9):e24166. doi: 10.1371/journal.pone.0024166. Epub 2011 Sep 8.
Fungi constitute an important group in soil biological diversity and functioning. However, characterization and knowledge of fungal communities is hampered because few primer sets are available to quantify fungal abundance by real-time quantitative PCR (real-time Q-PCR). The aim in this study was to quantify fungal abundance in soils by incorporating, into a real-time Q-PCR using the SYBRGreen® method, a primer set already used to study the genetic structure of soil fungal communities. To satisfy the real-time Q-PCR requirements to enhance the accuracy and reproducibility of the detection technique, this study focused on the 18S rRNA gene conserved regions. These regions are little affected by length polymorphism and may provide sufficiently small targets, a crucial criterion for enhancing accuracy and reproducibility of the detection technique. An in silico analysis of 33 primer sets targeting the 18S rRNA gene was performed to select the primer set with the best potential for real-time Q-PCR: short amplicon length; good fungal specificity and coverage. The best consensus between specificity, coverage and amplicon length among the 33 sets tested was the primer set FR1/FF390. This in silico analysis of the specificity of FR1/FF390 also provided additional information to the previously published analysis on this primer set. The specificity of the primer set FR1/FF390 for Fungi was validated in vitro by cloning--sequencing the amplicons obtained from a real time Q-PCR assay performed on five independent soil samples. This assay was also used to evaluate the sensitivity and reproducibility of the method. Finally, fungal abundance in samples from 24 soils with contrasting physico-chemical and environmental characteristics was examined and ranked to determine the importance of soil texture, organic carbon content, C∶N ratio and land use in determining fungal abundance in soils.
真菌在土壤生物多样性和功能中构成一个重要的群体。然而，由于缺乏可用于通过实时定量 PCR（real-time Q-PCR）定量真菌丰度的引物集，因此对真菌群落的特征和了解受到阻碍。本研究的目的是通过将已经用于研究土壤真菌群落遗传结构的引物集纳入使用 SYBRGreen®方法的实时 Q-PCR 中，从而定量土壤中的真菌丰度。为了满足实时 Q-PCR 的要求，以提高检测技术的准确性和可重复性，本研究侧重于 18S rRNA 基因保守区。这些区域受长度多态性的影响较小，并且可能提供足够小的靶标，这是提高检测技术准确性和可重复性的关键标准。对靶向 18S rRNA 基因的 33 个引物集进行了计算机分析，以选择最适合实时 Q-PCR 的引物集：短扩增子长度；良好的真菌特异性和覆盖度。在测试的 33 个集合中，特异性、覆盖度和扩增子长度之间的最佳一致性是 FR1/FF390 引物集。对 FR1/FF390 特异性的计算机分析还为该引物集之前的出版物分析提供了额外的信息。通过克隆对 FR1/FF390 引物集的特异性进行了体外验证，对从在五个独立土壤样本上进行的实时 Q-PCR 测定中获得的扩增子进行了测序。该测定还用于评估该方法的灵敏度和可重复性。最后，检查了 24 个具有不同物理化学和环境特征的土壤样本中的真菌丰度，并对其进行了排序，以确定土壤质地、有机碳含量、C∶N 比和土地利用对土壤中真菌丰度的重要性。
