Ecological mechanisms of microbial assembly in clonal plant Glechoma longituba: from soil to endosphere

Abstract

Climate change presents significant challenges to plant growth and reproduction. Clonal plants, with low genetic diversity, are particularly vulnerable due to their limited adaptive capacity. Plant-associated microbiomes can play a crucial role in enhancing clonal plant survival and adaptability, yet the mechanisms governing microbial community assembly along the soil-episphere-endosphere continuum remain unclear. In this study, we investigated microbial community assembly patterns in the clonal plant Glechoma longituba. Our findings demonstrate that the assembly of microbial communities is primarily driven by host-related factors rather than external environmental filtering. First, host selection reduced α-diversity and network complexity while increasing β-diversity and community stability. Second, the mechanisms of microbial assembly transitioned from stochastic dominance in bulk soil and epiphytic compartments to deterministic processes within endophytic niches. Third, the taxonomic structure exhibited significant turnover along the soil-episphere-endosphere continuum, accompanied by functional redundancy to maintain ecosystem functions. The results support the hypothesis that host selection optimizes the functional composition of microbial communities by reducing diversity and network complexity while ensuring the stability of key functional microorganisms. The study emphasizes the critical role of host-microbe interactions in sustaining the adaptive and functional advantages of clonal plants, offering insights into managing sustainable plant communities under climate change.IMPORTANCEThis study highlights the vital role of plant-associated microbiomes in helping clonal plants, which have low genetic diversity, adapt to climate change. By examining the clonal plant Glechoma longituba, the research reveals that the plant itself plays a key role in shaping its microbial communities, rather than external environmental factors. Host selection simplifies microbial diversity and network complexity but enhances community stability and functional efficiency. These findings suggest that clonal plants can optimize their microbiomes to maintain critical functions. This work provides valuable insights into how plants and microbes interact to improve resilience, offering potential strategies for managing plant communities in a changing climate. By understanding these mechanisms, we can better support sustainable ecosystems and agricultural practices in the face of global environmental challenges.

Keywords: clonal plant; community assembly; host selection; soil-episphere-endosphere continuum.

Fig 1

α-Diversity of the associated microbiomes in clonal plant Glechoma longituba. (a and b) Phylogenetic diversity of the microbiota of five microhabitats from four sites. (c and d) Phylogenetic diversity of the microbiota of five microhabitats aggregated from four sites. (e and f) Shannon index of the microbiota of five microhabitats from four sites. (g and h) Shannon index of the microbiota of five microhabitats aggregated from four sites. Statistical significance was determined using the Kruskal-Wallis test or ANOVA analysis. The indices (F or H and P-value) are displayed at the bottom of each graph. Means with the same letters are not statistically different based on the Nemenyi test or Tukey's HSD as post hoc analysis (P < 0.05). ns indicates no statistically significant difference between groups.

Fig 2

β-Diversity patterns of the associated microbiomes of clonal plant Glechoma longituba. (a) Bray-Curtis dissimilarity of the bacterial microbiota of five microhabitats aggregated from four sites. Means with the same letters are not statistically different based on the Nemenyi test or Tukey's HSD (P < 0.05). (b) Principal coordinates analysis (PCoA) using Bray-Curtis distances for bacterial microbiota. (c) The contribution of site, microhabitat, and their interaction to the changes in bacterial assemblages. (d) Bray-Curtis dissimilarity of the fungal microbiota of five microhabitats aggregated from four sites. (e) PCoA using Bray-Curtis distances for fungal microbiota. (f) The contribution of site, microhabitat, and their interaction to the changes in bacterial assemblages and fungal assemblages. Asterisk's indication of statistical significance: ***P < 0.001, **P < 0.01, and *P < 0.05.

Fig 3

Taxonomic composition of the associated microbiomes of clonal plant Glechoma longituba in each microhabitat. (a and b) Bacterial community composition at the class level. (c and d) Fungal community composition at the class level. Compartments include bulk soil, rhizosphere (Rhizo), phyllosphere (Phyllo), shoot endosphere (Shoots), and root endosphere (Roots). Sampling sites include four: S1–S4.

Fig 4

Dynamics of microbial networks. (a through e) Bacterial-fungal co-occurrence networks in each microhabitat. Each node represents a single ASV. (f through j) Comparison of key bacterial-fungal co-occurrence network topological properties. Means with the same letters are not statistically different based on the Nemenyi test or Tukey's HSD (P < 0.05).

Fig 5

Stability of bacterial and fungal communities (1−AVD index) across plant-associated habitats and its correlation with diversity indices. (a and d) Stability of bacterial and fungal communities measured by average variation degree (AVD) index, shown as (1–AVD) in box plots. (b and c) Relationships between Shannon index and phylogenetic diversity with AVD index in the bacterial community. (e and f) Relationships between Shannon index and phylogenetic diversity with AVD index in fungal community. Means with the same letters are not statistically different based on the Nemenyi test or Tukey's HSD (P < 0.05).

Fig 6

Ecological processes shaping the associated microbiomes of clonal plant Glechoma longituba in different microhabitats. (a through e) Neutral community model (NCM) for the stochastic assembly processes of the bacterial community in each microhabitat. (f through j) Neutral community model (NCM) for the stochastic assembly processes of the bacterial community in each microhabitat. R² represents the fit to the neutral model, and m indicates the immigration rate of the metacommunity. The gray line indicates the NCM prediction with 95% confidence intervals represented in dashed lines. The points falling above and below the 95% CI are colored green and light green, respectively, and those within the interval are dark green. (k and l) The relative importance of deterministic and stochastic processes quantified by modified stochasticity ratio (NST). (m and n)Comparisons of mean Levins habitat niche breadth for bacterial and fungal communities in different microhabitats. Means with the same letters are not statistically different based on the Nemenyi test or Tukey's HSD (P < 0.05).

Fig 7

Source contributions and shared taxonomical taxa and functional groups across different compartments. (a and b) Source contributions of bacterial and fungal communities across compartments, with percentages indicating microbial transfers among bulk soil, rhizosphere, phyllosphere, roots endosphere, and shoots endosphere. (c and d) The upset diagram shows the total ASVs for each group, the number of unique in each group, and the number of ASVs shared between groups. (e and f) The upset diagram shows the total bacterial KOs and fungal guilds for each group, the number of KOs and guilds unique in each group, and the number of KOs and guilds shared between groups. The bar heights indicate the number of bacterial taxa shared among compartments, and the dots below represent specific combinations of compartments involved in the intersection.