Evidence for saponin diversity-mycobiome links and conservatism of plant-fungi interaction patterns across Holarctic disjunct Panax species

Soil fungal networks exhibit sparser interactions than bacterial networks in diseased banana plantations

Soil microorganisms play a crucial role in suppressing soil-borne diseases. Although the composition of microbial communities in healthy versus diseased soils is somewhat understood, the interplay between microbial interactions and disease incidence remains unclear. This study used 16S rRNA and fungal internal transcribed spacer (ITS) sequencing to investigate the bacterial and fungal community composition in three soil types: forest soil (Z), soil from healthy banana plantations (H), and soil from diseased banana plantations (D). Principal coordinate analysis revealed significant differences among the bacterial and fungal community structures of the three soil types. Compared with those in forest soil, bacterial and fungal diversities significantly decreased in diseased banana soil. Key microorganisms, including the bacteria Chloroflexi and Pseudonocardia and the fungi Mortierellomycota and Moesziomyces, were significantly increased in soil from diseased banana plantations. Redundancy analysis revealed that total nitrogen and available phosphorus were the primary drivers of the soil microbial community structure. The neutral community model posited that the bacterial community assembly in banana plantations is predominantly governed by stochastic processes, whereas the fungal community assembly in banana plantations is primarily driven by deterministic processes. Furthermore, co-occurrence network analysis revealed that the proportion of positive edges in the fungal network of soil from diseased banana plantations was 5.92 times lower than that in soil from healthy banana plantations, and its fungal network structure was sparse and simple. In conclusion, reduced interactions within the fungal network were significantly linked to the epidemiology of Fusarium wilt. These findings underscore the critical role of soil fungal communities in modulating pathogens.

IMPORTANCE

Soil microorganisms are pivotal in mitigating soil-borne diseases. The intricate mechanisms underlying the interactions among microbes and their impact on disease occurrence remain enigmatic. This study underscores that a reduction in fungal network interactions correlates with the incidence of soil-borne Fusarium wilt.

Understanding the influence of plant genetic factors on rhizosphere microbiome assembly in Panax notoginseng

Introduction

Functional rhizosphere microbiomes (FRM) are critical for plant health and yield. However, the ecological succession of FRM and their links to plant genetic factors across the life cycle of perennial plants remain poorly understood.

Methods

This study profiled FRM, including plant-beneficial bacteria (PBB) and fungal plant pathogens (FPP), across different developmental stages of Panax notoginseng.

Results

The biodiversity of both PBB and FPP were significantly higher in rhizosphere compared with farmland soil, and exhibited different succession patterns with plant growth. The relative abundance of PBB, but not FPP, decreased after plant cultivation. There were significantly negative correlations between FPP and PBB, particularly the biocontrol subgroup (ρ = -0.56, p < 0.001). The antagonistic effects of biocontrol bacteria against fungal pathogens were further validated by in vitro assays. The fitting of neutral community model indicated that the deterministic assembly of PBB, especially the biocontrol subgroup, was the strongest at the 3rd-year root growth stage of P. notoginseng. Plant genes involved in protein export, biosynthesis of alkaloids and amino acids were identified as drivers of the deterministic assembly of biocontrol subcommunity by RNA-Seq analysis. Additionally, a total of 13 transcription factors potentially regulating the expression of these biosynthesis genes were identified through co-expression network. In summary, this study unveils the succession patterns of FRM throughout the life cycle of P. notoginseng and the underlying plant genetic mechanisms, providing valuable insights for developing new plant disease management strategies by manipulating microbes.

Stochasticity-dominated rare fungal endophytes contribute to coexistence stability and saponin accumulation in Panax species

Fungal communities inhabiting plant tissues are complex systems of inter-species interactions, consisting of both the "abundant biosphere" and "rare biosphere". However, the composition, assembly, and stability of these subcommunities, as well as their contributions to productivity remain unclear. In this study, the taxonomic and functional composition, co-occurrence, and ecological assembly of abundant and rare fungal subcommunities in different tissues of three Panax species were investigated. Abundant subcommunities were dominated by potential plant pathogens belonging to Microbotryomycetes, while saprotrophic fungi like Agaricomycetes and Mortierellomycetes were more prevalent in rare subcommunities. The rare taxa played a central role in upholding the stability of the fungal networks as driven by Dothideomycetes and Sordariomycetes. Homogeneous selection played a larger role in the assembly of abundant fungal subcommunities compared to the rare counterparts, which was more dominated by stochastically ecological drift in all plant species. Rare biospheres played a larger role in the accumulation of saponin compared to their abundant counterparts, especially in the leaf endosphere, which was mainly affected by environmental factors (Mg, pH, OC, and etc.). Furthermore, we found that rare species belonging to unidentified saprotrophs were associated with saponin formation. This study provides hypotheses for future experiments to understand mechanisms accounting for the variations in the composition and function of rare fungal subcommunities across different Panax species.

Metagenomic exploration of the rhizosphere soil microbial community and their significance in facilitating the development of wild-simulated ginseng

Panax ginseng, a prized medicinal herb, has faced increasingly challenging field production due to soil degradation and fungal diseases in Northeast China. Wild-simulated cultivation has prevailed because of its sustainable soil management and low disease incidence. Despite the recognized benefits of rhizosphere microorganisms in ginseng cultivation, their genomic and functional diversity remain largely unexplored. In this work, we utilized shotgun metagenomic analysis to reveal that Pseudomonadota, Actinomycetota, and Acidobacteriota were dominant in the ginseng rhizobiome and recovered 14 reliable metagenome-assembled genomes. Functional analysis indicated an enrichment of denitrification-associated genes, potentially contributing to the observed decline in soil fertility, while genes associated with aromatic carbon degradation may be linked to allelochemical degradation. Further analysis demonstrated enrichment of Actinomycetota in 9-year-old wild-simulated ginseng (WSG), suggesting the need for targeted isolation of Actinomycetota bacteria. Among these, at least three different actinomycete strains were found to play a crucial role in fungal disease resistance, with Streptomyces spp. WY144 standing out for its production of actinomycin natural products active against the pathogenic fungus Ilyonectria robusta. These findings not only enhance our understanding of the rhizobiome of WSG but also present promising avenues for combating detrimental fungal pathogens, underscoring the importance of ginseng in both medicinal and agricultural contexts.IMPORTANCEWild-simulated ginseng, growing naturally without human interference, is influenced by its soil microbiome. Using shotgun metagenomics, we analyzed the rhizospheric soil microbiome of 7- and 9-year-old wild-simulated ginseng. The study aimed to reveal its composition and functions, exploring the microbiome's key roles in ginseng growth. Enrichment analysis identified Streptomycetes in ginseng soil, with three strains inhibiting plant pathogenic fungi. Notably, one strain produced actinomycins, suppressing the ginseng pathogenic fungus Ilyonectria robusta. This research accelerates microbiome application in wild-simulated ginseng cultivation, offering insights into pathogen protection and supporting microbiome utilization in agriculture.

A core root bacteria contribute to plant growth and anisodine accumulation of Anisodus tanguticus

BACKGROUND

Although it is well recognized that core root microorganisms contribute to plant health and productivity, little is known about their role to the accumulation of secondary metabolites. The roots of Anisodus tanguticus, a traditional herbal medication utilized by Tibetan medicine, are rich in tropane alkaloids. We collected wild A. tanguticus populations throughout a 1500 km transect on the Qinghai-Tibetan Plateau.

RESULTS

Our results showed that despite sampling at a distance of 1500 km, the root of A. tanguticus selectively recruits core root bacteria. We obtained 102 root bacterial core OTUs, and although their number only accounted for 2.99% of the total, their relative abundance accounted for 73% of the total. Spearman correlation and random forest analyses revealed that the composition of core root microbiomes was related to anisodine contents, aboveground biomass and nitrogen contents of Anisodus tanguticus. Among them, the main role is played by Rhizobacter, Variovorax, Polaromonas, and Mycobacterium genus that are significantly enriched in roots. Functional prediction by FAPROTAX showed that nitrogen-cycling microorganisms and pathogenic bacteria are strongly associated with anisodine contents, aboveground biomass and nitrogen contents of Anisodus tanguticus.

CONCLUSIONS

Our findings show that the root selectively recruits core root bacteria and revealed that the core microbiomes and microbial functions potentially contributed to the anisodine contents, aboveground biomass and nitrogen contents of the plant. This work may increase our understanding of the interactions between microorganisms and plants and improve our ability to manage root microbiota to promote sustainable production of herbal medicines.

Attribution of dispersal limitation can better explain the assembly patterns of plant microbiota

Disentangling community assembly processes is crucial for fully understanding the function of microbiota in agricultural ecosystems. However, numerous plant microbiome surveys have gradually revealed that stochastic processes dominate the assembly of the endophytic root microbiota in conflict with strong host filtering effects, which is an important issue. Resolving such conflicts or inconsistencies will not only help accurately predict the composition and structure of the root endophytic microbiota and its driving mechanisms, but also provide important guidance on the correlation between the relative importance of deterministic and stochastic processes in the assembly of the root endophytic microbiota, and crop productivity and nutritional quality. Here, we propose that the inappropriate division of dispersal limitation may be the main reason for such inconsistency, which can be resolved after the proportion of dispersal limitation is incorporated into the deterministic processes. The rationality of this adjustment under the framework of the formation of a holobiont between the microbiome and the plant host is herein explained, and a potential theoretical framework for dynamic assembly patterns of endophytic microbiota along the soil-plant continuum is proposed. Considering that the assembly of root endophytic microbiota is complicated, we suggest caution and level-by-level verification from deterministic processes to neutral components to stochastic processes when deciding on the attribution of dispersal limitation in the future to promote the expansion and application of microbiome engineering in sustainable agricultural development based on community assembly patterns.

Modules in robust but low-efficiency phyllosphere fungal networks drive saponin accumulation in leaves of different Panax species

BACKGROUND

The phyllosphere mycobiome plays a crucial role in plant fitness and ecosystem functions. The complex microbial ecological networks (MEN) formed by these fungi remain poorly understood, particularly with regard to their organization strategy and their contributions to plant secondary metabolites such as saponin.

RESULTS

In this study, we constructed six MENs from leaf epiphytic and endophytic mycobiomes of three Panax species distributed in the northeast and southwest ends of mainland China. Hub nodes were absent in these MENs, which were significantly more complex, robust, and less efficient compared to random graphs (P < 0.05), indicating a hub-independent high-robustness strategy to maintain structural homeostasis. The important roles of specific MEN modules in shaping leaf saponin profiles of each Panax species were proved by multiple machine learning algorithms. Positive regulation modules (PRMs) of total saponin content were further identified, which exhibited more deterministic ecological assembly and comprised of highly connected nodes as well as higher proportion of plant-associated fungal guilds compared to other network members, indicating their tight links with host plant. The significant and direct effects (P < 0.05) of PRMs on total saponin accumulation were validated by well-fitted structural equation models (χ2 < 0.3, P > 0.5). Taxonomic analysis revealed that Pleosporales and Chaetothyriales were significantly overrepresented by positive regulation taxa (PRT) of total saponin content (FDR < 0.05). Across PRT identified in three Panax species, Epicoccum and Coniothyrium were conservatively present, while species-specific taxa such as Agaricales were also found, indicating the conservatism and specificity of plant-fungi interactions associated with leaf saponin accumulation in Panax genus.

CONCLUSIONS

These findings provide a foundation for understanding mechanisms maintaining the steady state of phyllosphere mycobiome in healthy plant, and offer clues for engineering phyllosphere mycobiome to improve the accumulation of bioactive secondary metabolites on the basis of network modules.

Artificial Intelligence: A Promising Tool in Exploring the Phytomicrobiome in Managing Disease and Promoting Plant Health

There is increasing interest in harnessing the microbiome to improve cropping systems. With the availability of high-throughput and low-cost sequencing technologies, gathering microbiome data is becoming more routine. However, the analysis of microbiome data is challenged by the size and complexity of the data, and the incomplete nature of many microbiome databases. Further, to bring microbiome data value, it often needs to be analyzed in conjunction with other complex data that impact on crop health and disease management, such as plant genotype and environmental factors. Artificial intelligence (AI), boosted through deep learning (DL), has achieved significant breakthroughs and is a powerful tool for managing large complex datasets such as the interplay between the microbiome, crop plants, and their environment. In this review, we aim to provide readers with a brief introduction to AI techniques, and we introduce how AI has been applied to areas of microbiome sequencing taxonomy, the functional annotation for microbiome sequences, associating the microbiome community with host traits, designing synthetic communities, genomic selection, field phenotyping, and disease forecasting. At the end of this review, we proposed further efforts that are required to fully exploit the power of AI in studying phytomicrobiomes.

Environmental Response to Root Secondary Metabolite Accumulation in Paeonia lactiflora: Insights from Rhizosphere Metabolism and Root-Associated Microbial Communities

Paeonia lactiflora is a commercial crop with horticultural and medicinal value. Although interactions between plants and microbes are increasingly evident and considered to be drivers of ecosystem service, the regulatory relationship between microbial communities and the growth and root metabolites of P. lactiflora is less well known. Here, soil metabolomics indicated that carbohydrates and organic acids were enriched in the rhizosphere (RS) with higher diversity. Moreover, the variation of root-associated microbiotas between the bulk soil (BS) and the RS of P. lactiflora was investigated via 16S rRNA and internally transcribed spacer (ITS) amplicon sequencing. The RS displayed a low-diversity community dominated by copiotrophs, whereas the BS showed an oligotroph-dominated, high-diversity community. Hierarchical partitioning showed that cation exchange capacity (CEC) was the main factor affecting microbial community diversity. The null model and the dispersion niche continuum index (DNCI) suggested that stochastic processes (dispersal limitation) dominated the community assembly of both the RS and BS. The bacterial-fungal interkingdom networks illustrated that the RS possessed more complex and stable co-occurrence patterns. Meanwhile, positive link numbers and positive cohesion results revealed more cooperative relationships among microbes in the RS. Additionally, random forest model prediction and two partial least-squares path model (PLS-PM) analyses showed that the P. lactiflora root secondary metabolites were comprehensively impacted by soil water content (SWC), mean annual precipitation (MAP), pH (abiotic), and Alternaria (biotic). Collectively, this study provides a theoretical basis for screening the microbiome associated with the active components of P. lactiflora. IMPORTANCE Determining the taxonomic and functional components of the rhizosphere microbiome, as well as how they differ from those of the bulk soil microbiome, is critical for manipulating them to improve plant growth performance and increase agricultural yields. Soil metabolic profiles can help enhance the understanding of rhizosphere exudates. Here, we explored the regulatory relationship across environmental variables (root-associated microbial communities and soil metabolism) in the accumulation of secondary metabolites of P. lactiflora. Overall, this work improves our knowledge of how the rhizosphere affects soil and microbial communities. These observations improve the understanding of plant-microbiome interactions and introduce new horizons for synthetic community investigations as well as the creation of microbiome technologies for agricultural sustainability.

Comparison of Phytochemical Profiles of Wild and Cultivated American Ginseng Using Metabolomics by Ultra-High Performance Liquid Chromatography-High-Resolution Mass Spectrometry

American ginseng (Panax quinquefolius L.) has been recognized as a valuable herb medicine, and ginsenosides are the most important components responsible for the health-beneficial effects. This study investigated the secondary metabolites responsible for the differentiation of wild and cultivated American ginsengs with ultrahigh-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS)-based metabolomic approach. An in-house ginsenoside library was developed to facilitate data processing and metabolite identification. Data visualization methods, such as heatmaps and volcano plots, were utilized to extract discriminated ion features. The results suggested that the ginsenoside profiles of wild and cultivated ginsengs were significantly different. The octillol (OT)-type ginsenosides were present in greater abundance and diversity in wild American ginsengs; however, a wider distribution of the protopanaxadiol (PPD)-and oleanolic acid (OA)-type ginsenosides were found in cultivated American ginseng. Based on the tentative identification and semi-quantification, the amounts of five ginsenosides (i.e., notoginsenoside H, glucoginsenoside Rf, notoginsenoside R1, pseudoginsenoside RT2, and ginsenoside Rc) were 2.3-54.5 fold greater in wild ginseng in comparison to those in their cultivated counterparts, and the content of six ginsenosides (chicusetsusaponin IVa, malonylginsenoside Rd, pseudoginsenoside Rc1, malonylfloralginsenoside Rd6, Ginsenoside Rd, and malonylginsenoside Rb1) was 2.6-14.4 fold greater in cultivated ginseng compared to wild ginseng. The results suggested that the in-house metabolite library can significantly reduce the complexity of the data processing for ginseng samples, and UHPLC-HRMS is effective and robust for identifying characteristic components (marker compounds) for distinguishing wild and cultivated American ginseng.