Castaño Carles, Oliva Jonàs, Martínez de Aragón Juan, Alday Josu G, Parladé Javier, Pera Joan, Bonet José Antonio
Forest Bioengineering Solutions S.A., Solsona, Spain
Departament de Producció Vegetal i Ciència Forestal, Universitat de Lleida-AGROTECNIO, Lleida, Spain.
Appl Environ Microbiol. 2017 Jun 16;83(13). doi: 10.1128/AEM.00600-17. Print 2017 Jul 1.
Obtaining reliable and representative mushroom production data requires time-consuming sampling schemes. In this paper, we assessed a simple methodology to detect mushroom emergence by trapping the fungal spores of the fruiting body community in plots where mushroom production was determined weekly. We compared the performance of filter paper traps with that of funnel traps and combined these spore trapping methods with species-specific quantitative real-time PCR and Illumina MiSeq to determine the spore abundance. Significantly more MiSeq proportional reads were generated for both ectomycorrhizal and saprotrophic fungal species using filter traps than were obtained using funnel traps. The spores of 37 fungal species that produced fruiting bodies in the study plots were identified. Spore community composition changed considerably over time due to the emergence of ephemeral fruiting bodies and rapid spore deposition (lasting from 1 to 2 weeks), which occurred in the absence of rainfall events. For many species, the emergence of epigeous fruiting bodies was followed by a peak in the relative abundance of their airborne spores. There were significant positive relationships between fruiting body yields and spore abundance in time for five of seven fungal species. There was no relationship between fruiting body yields and their spore abundance at plot level, indicating that some of the spores captured in each plot were arriving from the surrounding areas. Differences in fungal detection capacity by spore trapping may indicate different dispersal ability between fungal species. Further research can help to identify the spore rain patterns for most common fungal species. Mushroom monitoring represents a serious challenge in economic and logistical terms because sampling approaches demand extensive field work at both the spatial and temporal scales. In addition, the identification of fungal taxa depends on the expertise of experienced fungal taxonomists. Similarly, the study of fungal dispersal has been constrained by technological limitations, especially because the morphological identification of spores is a challenging and time-consuming task. Here, we demonstrate that spores from ectomycorrhizal and saprotrophic fungal species can be identified using simple spore traps together with either MiSeq fungus-specific amplicon sequencing or species-specific quantitative real-time PCR. In addition, the proposed methodology can be used to characterize the airborne fungal community and to detect mushroom emergence in forest ecosystems.
获取可靠且具代表性的蘑菇产量数据需要耗时的采样方案。在本文中,我们评估了一种简单方法,通过在每周测定蘑菇产量的样地中捕获子实体群落的真菌孢子来检测蘑菇的出菇情况。我们比较了滤纸陷阱和漏斗陷阱的性能,并将这些孢子捕获方法与物种特异性定量实时PCR和Illumina MiSeq相结合,以确定孢子丰度。使用滤纸陷阱比使用漏斗陷阱产生的外生菌根真菌和腐生真菌物种的MiSeq比例读数显著更多。鉴定出了在研究样地中产生子实体的37种真菌的孢子。由于短暂子实体的出现和快速的孢子沉积(持续1至2周),孢子群落组成随时间发生了很大变化,这发生在无降雨事件的情况下。对于许多物种,地上子实体出现后,其空气传播孢子的相对丰度会出现峰值。七种真菌中的五种,其子实体产量与孢子丰度在时间上存在显著正相关。在样地水平上,子实体产量与其孢子丰度之间没有关系,这表明每个样地中捕获的一些孢子是从周边地区飞来的。通过孢子捕获检测真菌的能力差异可能表明真菌物种之间不同的扩散能力。进一步的研究有助于确定大多数常见真菌物种的孢子雨模式。从经济和后勤角度来看,蘑菇监测是一项严峻挑战,因为采样方法在空间和时间尺度上都需要大量的野外工作。此外,真菌分类单元的鉴定依赖于经验丰富的真菌分类学家的专业知识。同样,真菌扩散的研究也受到技术限制,特别是因为孢子的形态鉴定是一项具有挑战性且耗时的任务。在这里,我们证明,使用简单的孢子陷阱以及MiSeq真菌特异性扩增子测序或物种特异性定量实时PCR,可以鉴定外生菌根真菌和腐生真菌物种的孢子。此外,所提出的方法可用于表征森林生态系统中的空气传播真菌群落并检测蘑菇的出菇情况。