Krinitsina Anastasia A, Omelchenko Denis O, Kasianov Artem S, Karaseva Vera S, Selezneva Yulia M, Chesnokova Olga V, Shirobokov Vitaly A, Polevova Svetlana V, Severova Elena E
Department of Higher Plants, Faculty of Biology, Lomonosov Moscow State University, 119991 Moscow, Russia.
Laboratory of Plant Genomics, Institute for Information Transmission Problems, 127051 Moscow, Russia.
Plants (Basel). 2023 Jun 17;12(12):2351. doi: 10.3390/plants12122351.
Grass pollen is one of the leading causes of pollinosis, affecting 10-30% of the world's population. The allergenicity of pollen from different Poaceae species is not the same and is estimated from moderate to high. Aerobiological monitoring is a standard method that allows one to track and predict the dynamics of allergen concentration in the air. Poaceae is a stenopalynous family, and thus grass pollen can usually be identified only at the family level with optical microscopy. Molecular methods, in particular the DNA barcoding technique, can be used to conduct a more accurate analysis of aerobiological samples containing the DNA of various plant species. This study aimed to test the possibility of using the ITS1 and ITS2 nuclear loci for determining the presence of grass pollen from air samples via metabarcoding and to compare the analysis results with the results of phenological observations. Based on the high-throughput sequencing data, we analyzed the changes in the composition of aerobiological samples taken in the Moscow and Ryazan regions for three years during the period of active flowering of grasses. Ten genera of the Poaceae family were detected in airborne pollen samples. The representation for most of them for ITS1 and ITS2 barcodes was similar. At the same time, in some samples, the presence of specific genera was characterized by only one sequence: either ITS1 or ITS2. Based on the analysis of the abundance of both barcode reads in the samples, the following order could describe the change with time in the dominant species in the air: , , and in early mid-June, , , , and in mid-late June, , in late June to early July, and in early mid-July. In most samples, the number of taxa found via metabarcoding analysis was higher compared to that in the phenological observations. The semi-quantitative analysis of high-throughput sequencing data well reflects the abundance of only major grass species at the flowering stage.
草花粉是花粉症的主要病因之一,影响着全球10%-30%的人口。不同禾本科物种的花粉致敏性不尽相同,估计为中度到高度。空气生物学监测是一种标准方法,可用于追踪和预测空气中过敏原浓度的动态变化。禾本科是一个花粉类型单一的科,因此通常只能通过光学显微镜在科的层面鉴定草花粉。分子方法,特别是DNA条形码技术,可用于对包含各种植物物种DNA的空气生物学样本进行更准确的分析。本研究旨在测试使用ITS1和ITS2核基因座通过元条形码技术确定空气样本中草花粉存在的可能性,并将分析结果与物候观测结果进行比较。基于高通量测序数据,我们分析了莫斯科和梁赞地区在禾本科植物花期活跃的三年期间采集的空气生物学样本组成的变化。在空气中的花粉样本中检测到了禾本科的十个属。它们中大多数的ITS1和ITS2条形码表现相似。同时,在一些样本中,特定属的存在仅由一个序列表征:要么是ITS1,要么是ITS2。基于对样本中两个条形码读数丰度的分析,以下顺序可以描述空气中优势物种随时间的变化:6月上旬至中旬为[具体物种1]、[具体物种2]、[具体物种3],6月中旬至下旬为[具体物种4]、[具体物种5]、[具体物种6]、[具体物种7],6月下旬至7月上旬为[具体物种8]、[具体物种9],7月上旬至中旬为[具体物种10]。在大多数样本中,通过元条形码分析发现的分类单元数量高于物候观测中的数量。高通量测序数据的半定量分析很好地反映了开花期仅主要草种的丰度。