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Mushroom Emergence Detected by Combining Spore Trapping with Molecular Techniques.

ABSTRACT: 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.IMPORTANCE 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.

SUBMITTER: Castano C

PROVIDER: S-EPMC5478987 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Mushroom Emergence Detected by Combining Spore Trapping with Molecular Techniques.

Castaño Carles C Oliva Jonàs J Martínez de Aragón Juan J Alday Josu G JG Parladé Javier J Pera Joan J Bonet José Antonio JA

Applied and environmental microbiology 20170616 13

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 ...[more]

PMID: 28432095

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Project description:BackgroundDental plaque microbes play a key role in the development of periodontal disease. Numerous high-throughput sequencing studies have generated understanding of the bacterial species associated with both canine periodontal health and disease. Opportunities therefore exist to utilise these bacterial biomarkers to improve disease diagnosis in conscious-based veterinary oral health checks. Here, we demonstrate that molecular techniques, specifically quantitative polymerase chain reaction (qPCR) can be utilised for the detection of microbial biomarkers associated with canine periodontal health and disease.ResultsOver 40 qPCR assays targeting single microbial species associated with canine periodontal health, gingivitis and early periodontitis were developed and validated. These were used to quantify levels of the respective taxa in canine subgingival plaque samples collected across periodontal health (PD0), gingivitis (PD1) and early periodontitis (PD2). When qPCR outputs were compared to the corresponding high-throughput sequencing data there were strong correlations, including a periodontal health associated taxa, Capnocytophaga sp. COT-339 (rs =0.805), and two periodontal disease associated taxa, Peptostreptococcaceae XI [G-4] sp. COT-019 (rs=0.902) and Clostridiales sp. COT-028 (rs=0.802). The best performing models, from five machine learning approaches applied to the qPCR data for these taxa, estimated 85.7% sensitivity and 27.5% specificity for Capnocytophaga sp. COT-339, 74.3% sensitivity and 67.5% specificity for Peptostreptococcaceae XI [G-4] sp. COT-019, and 60.0% sensitivity and 80.0% specificity for Clostridiales sp. COT-028.ConclusionsA qPCR-based approach is an accurate, sensitive, and cost-effective method for detection of microbial biomarkers associated with periodontal health and disease. Taken together, the correlation between qPCR and high-throughput sequencing outputs, and early accuracy insights, indicate the strategy offers a prospective route to the development of diagnostic tools for canine periodontal disease.

Project description:The button mushroom Agaricus bisporus is represented mainly by two varieties, a secondarily homothallic variety with predominantly two heterokaryotic spores per basidia and a heterothallic variety with predominantly four homokaryotic spored basidium. Both varieties also differ in their recombination landscape with the former showing crossovers (CO) predominantly at chromosome ends whereas the latter has a more evenly distribution of CO over the chromosomes. The two varieties are compatible, and this has been used to study segregation of the basidial spore number (BSN) and the genomic positions of recombination, i.e., the CO landscape, in order to find the underlying genetic determinants. Knowledge on genes controlling CO positions might facilitate either the conservation of favorable allele combinations or the disruption of unwanted allele combinations to reduce linkage drag. For BSN, in total seven QTL were found with the major QTL on chromosome 1 explaining ca. 55% of the phenotypic variation. It appeared, however, difficult to map the recombination landscape. This phenotype can only be assessed in the meiotic offspring of an intervarietal hybrid which is a laborious and difficult task. Nevertheless, this was done, and we were able to map three QTLs for this trait, two on chromosome 1 and one on chromosome 2 not overlapping with the QTL for BSN. The hurdles encountered are discussed and a new strategy is proposed that can solves these. We propose to use two genetically unrelated mapping populations both offspring of a cross between a var. bisporus and a var. burnettii homokaryon and thus segregating both for CO and BSN. Homokaryotic offspring of both populations can be intercrossed without limitation of mating incompatibility and marker homozygosity and the hybrid mushrooms directly used to map BSN. Homokaryotic offspring of these hybrid mushrooms can be genotypes to assess CO positions using next generation sequencing technologies that will solve marker problems encountered, especially for genotyping chromosome ends. This new approach can be a useful strategy for a more efficient breeding strategy for mushrooms in general.

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Mushroom Emergence Detected by Combining Spore Trapping with Molecular Techniques.

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Mushroom Emergence Detected by Combining Spore Trapping with Molecular Techniques.

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