Makiola Andreas, Dickie Ian A, Holdaway Robert J, Wood Jamie R, Orwin Kate H, Lee Charles K, Glare Travis R
Agroécologie, AgroSup Dijon, INRA, Université Bourgogne, Université Bourgogne Franche-Comté, Dijon, France.
Bio-Protection Research Centre, Lincoln University, Lincoln, New Zealand.
Microbiologyopen. 2019 Jul;8(7):e00780. doi: 10.1002/mbo3.780. Epub 2018 Dec 25.
Plant pathogens such as rust fungi (Pucciniales) are of global economic and ecological importance. This means there is a critical need to reliably and cost-effectively detect, identify, and monitor these fungi at large scales. We investigated and analyzed the causes of differences between next-generation sequencing (NGS) metabarcoding approaches and traditional DNA cloning in the detection and quantification of recognized species of rust fungi from environmental samples. We found significant differences between observed and expected numbers of shared rust fungal operational taxonomic units (OTUs) among different methods. However, there was no significant difference in relative abundance of OTUs that all methods were capable of detecting. Differences among the methods were mainly driven by the method's ability to detect specific OTUs, likely caused by mismatches with the NGS metabarcoding primers to some Puccinia species. Furthermore, detection ability did not seem to be influenced by differences in sequence lengths among methods, the most appropriate bioinformatic pipeline used for each method, or the ability to detect rare species. Our findings are important to future metabarcoding studies, because they highlight the main sources of difference among methods, and rule out several mechanisms that could drive these differences. Furthermore, strong congruity among three fundamentally different and independent methods demonstrates the promising potential of NGS metabarcoding for tracking important taxa such as rust fungi from within larger NGS metabarcoding communities. Our results support the use of NGS metabarcoding for the large-scale detection and quantification of rust fungi, but not for confirming the absence of species.
诸如锈菌（柄锈菌目）之类的植物病原体具有全球经济和生态重要性。这意味着迫切需要以可靠且经济高效的方式在大规模范围内检测、识别和监测这些真菌。我们调查并分析了在从环境样本中检测和定量已识别的锈菌物种时，下一代测序（NGS）宏条形码方法与传统DNA克隆方法之间存在差异的原因。我们发现不同方法之间观察到的和预期的共享锈菌操作分类单元（OTU）数量存在显著差异。然而，所有方法都能够检测到的OTU的相对丰度没有显著差异。方法之间的差异主要由该方法检测特定OTU的能力驱动，这可能是由于与某些柄锈菌物种的NGS宏条形码引物不匹配所致。此外，检测能力似乎不受方法之间序列长度差异、每种方法使用的最合适的生物信息学流程或检测稀有物种能力的影响。我们的研究结果对未来的宏条形码研究很重要，因为它们突出了方法之间差异的主要来源，并排除了几种可能导致这些差异的机制。此外，三种根本不同且独立的方法之间的高度一致性表明了NGS宏条形码在从更大的NGS宏条形码群落中追踪诸如锈菌之类的重要分类群方面具有广阔的潜力。我们的结果支持使用NGS宏条形码对锈菌进行大规模检测和定量，但不支持用于确认物种不存在的情况。
