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Distinct Features Based on Partitioning of the Endophytic Fungi of Cereals and Other Grasses - PubMed

  • ️Sun Jan 01 2023

Meta-Analysis

Distinct Features Based on Partitioning of the Endophytic Fungi of Cereals and Other Grasses

Xiang Sun et al. Microbiol Spectr. 2023.

Abstract

Endophytic fungi form a significant part of the plant mycobiome. Defining core members is crucial to understanding the assembly mechanism of fungal endophytic communities (FECs) and identifying functionally important community members. We conducted a meta-analysis of FECs in stems of wheat and five wild cereal species and generated a landscape of the fungal endophytic assemblages in this group of plants. The analysis revealed that several Ascomycota members and basidiomycetous yeasts formed an important compartment of the FECs in these plants. We observed a weak spatial autocorrelation at the regional scale and high intrahost variations in the FECs, suggesting a space-related heterogeneity. Accordingly, we propose that the heterogeneity among subcommunities should be a criterion to define the core endophytic members. Analysis of the subcommunities and meta-communities showed that the core and noncore members had distinct roles in various assembly processes, such as stochasticity, universal dynamics, and network characteristics, within each host. The distinct features identified between the community partitions of endophytes aid in understanding the principles that govern the assembly and function of natural communities. These findings can assist in designing synthetic microbiomes. IMPORTANCE This study proposes a novel method for diagnosing core microbiotas based on prevalence of community members in a meta-community, which could be determined and supported statistically. Using this approach, the study found stratification in community assembly processes within fungal endophyte communities (FECs) in the stems of wheat and cereal-related wild species. The core and noncore partitions of the FECs exhibited certain degrees of determinism from different aspects. Further analysis revealed abundant and consistent interactions between rare taxa, which might contribute to the determinism process in noncore partitions. Despite minor differences in FEC compositions, wheat FECs showed distinct patterns in community assembly processes compared to wild species, suggesting the effects of domestication on FECs. Overall, our study provided a new approach for identifying core microbiota and provides insights into the community assembly processes within FECs in wheat and related wild species.

Keywords: community assembly; core microbiome; endophytic fungi; wheat; wild cereals.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

FIG 1
FIG 1

Community composition of the stem endophytes of wheat and wild cereals. (a) Relative abundances of the 12 most abundant fungal classes or higher taxa in the meta-community. (b) Hellinger-transformed abundance (x axis) of the 20 predominant fungal species or OTUs in the meta-community. Colored squares to the right of species or OTU names indicate the fungal taxa; the color key is shown in panel a. Squares with black frames indicate the basidiomycetous species with a yeast lifestyle. (c) NMDS plot of community composition based on Bray-Curtis dissimilarity (stress = 0.2577) labeled according to host. (d) NMDS plot of community composition based on Bray-Curtis dissimilarity labeled according to site; sites are arranged from north to south. (e) Linear modeling between community dissimilarity and geographic distances. The low R2 values and slopes close to zero indicate that geographic distance had a negligible effect on community composition at the current scale.

FIG 2
FIG 2

Taxon number and abundance in the core sets of real and simulated communities. (a)–(f) indicated results from all six hosts. The x axes indicate thresholds ranging from 0% to 99%. Colored solid lines show numbers of core taxa, and dashed lines represent the sum of the relative abundance of core taxa. Dark colors show values calculated with real communities, and light colors show values calculated with simulated communities. Gray solid lines indicate J between core sets identified with real and simulated communities at certain thresholds. At a J value of 1, actual and simulated communities yielded the same sets of core taxa; these are labeled as tier 1 (T1), etc. Black frames around tier numbers indicate core sets used in the subsequent analysis as core endophytes of a specific plant species.

FIG 3
FIG 3

NCM fit and DOC of core and noncore taxa. (a) NCM fit of each taxon. The plots show the NCM fit of a taxon in each host. Solid blue lines indicate the best fit to the neutral model, and dashed blue lines represent 95% confidence intervals with 1,000 bootstrap replicates. Black dots between dashed blue lines indicate taxa that fit the neutral model with 95% confidence. Taxa that deviate from the model and occur more or less frequently than the predictions are shown in turquoise and red, respectively. R2 indicates the fit to the neutral model. Nm is meta-community size times migration rate. Horizontal dashed lines indicate thresholds for certain tiers of the core set determined in Fig. 2, which divide the plots into core taxa (top; solid circles) and noncore taxa (bottom; open circles). Stacked bars above and below the dashed line indicate taxon proportions for core and noncore partitions; the colors used for the taxa are the same as for the plots. (b) Taxon proportions for core and non-core partitions at different thresholds. Proportions of taxa that fit or deviate from the NCM in the core and noncore sets with an increase in the thresholds of core from 0% to 99% (x axis). (c) DOC of meta-communities in the core and noncore partitions of each host. DOC (red) were calculated for core and noncore sets to detect universality in the dynamics of endophyte communities in different partitions. The overlap distributions of the real and randomized between-subject sample pairs are shown as black curves. The vertical black lines represent the change points.

FIG 4
FIG 4

Combined co-occurrence networks of the six hosts based on the simulated data. One hundred co-occurrence networks were generated from simulated communities with a threshold |rho| of >0.8 and a P value of <0.001; then, the shared edges (associations) presented in multiple simulated networks were combined to generate a single network graph (see the supplemental material for details). (a) Histograms showing the numbers of all edges present among the 100 networks generated from simulated communities with certain frequencies. Only a few edges occurred more than 20 times in 100 networks (to the right of the red line). (b) Combined co-occurrence networks of edges that occurred more than 20 times among 100 simulated subcommunities in each of the six hosts. Vertex size indicates the relative abundance of the taxon; vertex color indicates whether the taxon fits the neutral model (black, fit; turquoise and red, not a fit [as in Fig. 3]). The color of edges indicates the frequency of the edge in 100 stimulated networks from low (light) to high (dark). The taxonomical identities of nodes in the network graphs are listed in Table S2.

FIG 5
FIG 5

Conceptualization of the core microbiome used in present study. a) Core set determined at certain threshold based on real sub-community data. The core’ set in a given sub-community (or local community) is determined with the frequencies of taxon occurrences. Taxa with frequencies above threshold are regarded as members in core’ set of the sub-community, as described in Equation 1. When a taxon is determined as core’ member with higher frequency than threshold among all sub-communities, it is determined as a member in core set, as described in Equation 2. For example, taxon 3, 4, and 5 are diagnosed as core’ member in a sub-community when threshold = 80%. Nevertheless, the epidemic taxon 5 is denied by core set later, as its “core’ pattern” is not adequately prevalent. b) Core set determined at certain threshold based on simulated sub-community data. Replicates from all sub-communities are pooled to meta-community, from which random subsample are proceeded to generate stimulated sub-communities. Then the core set at certain threshold is determined with the same procedures in panel a. c) Core microbiome with statistical support. Serial core sets would be produced by repeating the core set determination at different thresholds (from 0~99%) for real or stimulated community data. Commonly there would be several threshold intervals in which the real and stimulated datasets yield same core sets (Jaccard Index between Corereal and Corestimulated set equals to 1). The core sets determined with thresholds in such intervals were named as Tier 1, 2, 3…… N cores. Researchers could select proper tiers as core criteria in researches due to specific application scenarios. TH, threshold; T, tier; J, Jaccard Index.

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