Deciphering core microbiomes and community assembly of table grapes

doi:10.21203/rs.3.rs-3237349/v1

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Deciphering core microbiomes and community assembly of table grapes

https://doi.org/10.21203/rs.3.rs-3237349/v1

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Aims

Understanding the assemblage of microbial communities is important for the health maintenance and post-harvest quality of fruit crops. However, systematic studies on the core microbiomes of table grapes and microbial community assembly of soil-plant continuum are still rare.

Methods

We collected samples from different compartments (bulk soil, rhizosphere soil of new roots and old roots, endosphere of new and old roots, and the endosphere of leaves and fruits) of five table grape varieties of Victoria, Balado Black, Fujimino, Jingya and Kyoho at the swelling stage and harvest stage. Microbial communities were analyzed using 16S rRNA and ITS rRNA high-throughput sequencing.

Results

The compartment was the major factor attributable to the variations in both bacterial and fungal communities. The alpha-diversity of both bacterial and fungal community decreased significantly along the compartment continuum from soil to fruit endosphere, but did not differ among the five varieties across all samples. We used the occupancy-abundance distribution to define core microbiomes for rhizosphere soil and endosphere. Functional annotations of the rhizospheric core bacteria were mainly associated with the redox process, while endophytic bacteria were mainly fermentative and symbiotic. Rhizospheric core fungi were saprophytic and the endophytic fungi were putatively pathogens. The null models indicated that the relative contribution of deterministic processes especially homogeneous selection gradually increased along the soil-plant continuum.

Conclusion

Our findings highlight niche-specific microbial communities are observed in different grape varieties. The deterministic processes contribute more to the assembly of microbial communities in the aboveground than in the belowground.

Compartment

Table grape variety

Core microbiomes

Microbial community assembly

Acting as the second-genome of plants, plant-associated microbiome plays an important role in promoting plant growth, supporting plant health and the adaption of plants to the changing environment (Rosenberg and Zilber-Rosenberg 2016). Understanding the diversity, composition and community assembly process of plant-associated microbial community has been the long-standing research hotspots of microbial ecology. Plant-associated microbiome includes a collection of microorganisms, differing greatly in root, rhizosphere, stem, leaf, flower and fruit (Lindow and Brandl 2003). The microbials are active participants in promoting plant growth, releasing active molecules, establishing the bacteria/mycorrhizal fungus/plant network (Bonfante and Anca 2009), affecting plant performance and potential growth–defense relationships (Geisen et al. 2022). Plant-associated microbial community is shown to be affected by groundcover managements (Vukicevich et al. 2018), host genotypes (Wagner et al. 2016) and rootstocks (Marasco et al. 2018). However, microbial diversity, structure in table grapes remain largely under-explored, despite the fact that monitoring the dynamics of microbials is an important component in the maintenance of healthy plants.

Plants exert a strong role in filtering and selecting microbiome from the environment. Notably, microbiota in different organs exhibits distinct characteristics and compositions (Cregger et al. 2018; Hamonts et al. 2018). Core microbiomes which are the relatively abundant and ubiquitous taxa in the soil are important for plant health (Delgado-Baquerizo et al. 2018; Shade and Stopnisek 2019). Microbial species with higher relative abundance and longer survival time might have greater ecological functions (Shade and Handelsman 2012). The enriched microbes in the rhizosphere were associated with transformation of organic compounds, nitrogen fixation and denitrification, while microbes involved in nitrification are strongly reduced (Ling et al. 2022). Besides, the selection of specific bacteria in angiosperm reproductive organs was related to the regulation of fruit and seed production (Massoni et al. 2021). Using source tracking it was found that crop-associated microbiota was mainly derived from soils and gradually filtered by different plant compartments in maize (Zea mays)-wheat (Triticum aestivum)/barley (Hordeum vulgare) rotation system (Xiong et al. 2021). Identifying the core microbiomes in different compartments across different table grape varieties may provide important clues for the development of proper management towards healthy plants and high-quality fruits.

The assembly of microbial communities is explained by the niche-based theory or neutral-based theory. According to the niche-based theory, microbial community is shaped by deterministic process affected by abiotic and biotic factors, which is attributable to habitat preferences and adaptability of microorganisms (Chesson 2000). By contrast, the neutral-based theory assumes that microorganisms present a random balance between the loss and return (Chave 2004). The random processes such as birth, death, migration, species formation and limited diffusion shape the microbial community structure. For example, environmental selection affected the assembly of bacterial communities in the rhizosphere and rhizoplane in wheat and faba bean (Attia et al. 2022), whilst the deterministic process dominated in soybean rhizosphere and endorhizosphere (Luo et al. 2022). Here we aimed to understand whether the stochastic or the deterministic process shaped the structure of microbial community of table grapes.

Globally table grapes are widely planted. A wealth of studies has shown that bacteria and fungi play a key role in determining fruit quality such as grape size, shape, color, flavor, yield and fruit (Bokulich et al. 2014; Burns et al. 2015; Gilbert et al. 2014). By contrast, few studies have systematically investigated microbial diversity, microbial community structure and core microbiomes in table grapes. Here we conducted a systematic study on five table grape varieties and collected samples across soil-plant continuum to explore the change of bacterial and fungal communities on the soil-fruit continuum, reveal taxonomic composition and functional annotations of core microbiomes. We also quantified the relative importance of deterministic and stochastic processes in microbial community assembly of different compartments. We hypothesized that both variety and compartment had significant effects on the structure of microbial community; The community of bacteria and fungi were sensitive to the changes of soil physicochemical properties and leaf nutrient contents; and the assembly of bacterial and fungal communities in different compartments was shaped primarily by deterministic process.

Experimental design and sample collection

The experiment was conducted in Qianya village, Quzhou County, Hebei Province, China (36°40′35.82″N, 114°57′34.73″E). Five commonly cultivated table grape varieties were selected: Victoria, Balado Black, Fujimino, Jingya and Kyoho. The tree ages of Victoria, Balado Black, Fujimino, Jingya and Kyoho were approximately 13, 4, 9, 4 and 22 years respectively. Kyoho, Fujimino and Jingya belong to European and American hybrid grapes, while Victoria and Balado Black belong to Eurasian grapes. The grapes were planted in the same field, and the field was evenly divided into 4 plots of 200 square meters. The planting density was 6000 plants ha^− 1 with a row spacing of 160 cm and plant spacing of 80 cm. The management practices were the same for all grape varieties.

Soil and plant samples were collected at the swelling stage (June 20, 2019) and at harvest (July 25, 2019). At each stage, bulk soil and rhizosphere soil, and different plant organs (old roots, new roots, leaves and fruits) were sampled. In each sampling plot, three grape trees were randomly selected, and the samples were thoroughly mixed into one composite. Soil samples were collected from 0–20 cm. Soil loosely attached to plant roots were defined as bulk soil, and soils tightly attached to plant roots were rhizosphere soils (Zarraonaindia et al. 2015). The root samples were divided into old roots and new roots, with 2–3 mm in diameter. Old roots and new roots were distinguished by the color, and the former was brown and the latter was white. Totally 30 mature and young leaves from three grape trees (10 leaves of each tree) were collected near the fruit clusters which was 70–80 cm above the ground in each plot (Barata et al. 2012). Five to ten mature leaves were collected from each plot. 30 ~ 50 grape berries (10 ~ 20 grape berries of each tree) from the three grape trees were collected at the same location as the leaves. All soil and plant samples were packed in ziplocked bags, marked, and transferred to the laboratory within 24 hours for further processing. All the samples of bulk soil, leaves and fruits were divided into two parts. One part was marked and stored at -80 ℃ to determine the microbial community structure. The other part was washed with distilled water, then sterilized at 105 ℃ for 2 hours, dried at 75 ℃ for 24 hours, and then crushed to determine the nutrient content of bulk soil, leaves and fruits.

DNA extraction and high-throughput sequencing

Total DNA from bulk soil, rhizosphere soil of old roots and new roots, endosphere of old roots and new roots, endosphere of leaves and fruits were extracted using MoBio PowerSoil DNA Isolation Kit (MoBi Laboratories, Carlsbad, CA, USA). Each sample was extracted in two parallel. The quantity and quality of DNA samples were assayed using a NanoDrop ND-1000 UV-visible light spectrophotometer (NanoDrop Technologies, Wilmington, DE, United States). After DNA extraction samples were stored at -20◦C for high-throughput sequencing analysis.

We choosed 799F (5’-AACMGGATTAGATACCCKG-3’) and 1392R (5’-ACGGGCGGTGTGTRC-3’) as the first round PCR primer for bacterial 16S rDNA amplification, and choosed 799F (5’-AACMGGATTAGATACCCKG-3’) and 1193R (5’-ACGTCATCCCCACCTTCC-3’) as the PCR primer of the second round (Bai et al. 2015). Fungi were amplified by primers ITS9F (5’-GAACGCAGRAAIIGYGA-3’) and ITS4R (5’-TCCTCGCTTATTGATGC-3’) (de Souza et al. 2016). The PCR was carried out with 10 ng template DNA, 0.8 µl of each primer both at 5 µM, 4 µl 5 × FastPfu Buffer, 2 µl 2.5 mM dNTPs, 0.4 µl FastPfuPolymerase (TransGen Biotech, Beijing, China), and made up to a final volume of 20 µl with ddH2O, and the thermal conditions were 95◦C for 3 min, 27 cycles of 95◦C for 30 s, 55◦C for 30 s and 72◦C for 45 s of extension, followed by 72◦C for 10 min. The PCR products were then purified and mixed in equimolar ratios to obtain quantitative sample DNA library that was used for sequencing. Finally, the purified PCR products were sequenced by a MiSeq platform (Illumina, San Diego, CA).

Bioinformatic Analysis

We used a computer server to handle the raw data returned by the sequencing company in Linux system. The raw sequences were demultiplexed and quality-filtered using the Ultra-fast sequence analysis (USEARCH) software according to the UPARSE pipeline (Edgar 2013). The primer sequences were removed, and the low-quality sequences with a quality score (Q) below 20 were eliminated. The paired terminal sequences were combined into a single sequence with length, 16S sequence was 400 bp and ITS sequence was 340 bp, then the resultant sequences were quality-filtered and singletons were removed. We clustered all qualified sequences into 97% identity operational taxonomic units (OTUs), and chimeras were removed by comparing with the platform Ribosomal Database Project (RDP) (Wang et al. 2007). The representative sequences of 16S and ITS rRNA gene were annotated and taxonomically identified by RDP classifier database with a confidence threshold of 80% (Wang et al. 2007). Those OTUs annotated as “Mitochondria” and “Chloroplasts” were removed. According to the minimum sequencing amount in bacterial samples and fungal samples in original OTU table, we got the rarefied OTU table for next step analysis. A total of 2,744,556 high-quality bacterial sequences and a total of 5,445,195 high-quality fungal sequences were obtained and clustered into bacterial and fungal OTUs at 97% sequence similarity. After rarefying to 2053 sequences per bacterial sample and 7720 sequences per fungal sample, 3518 bacterial OTUs and 2155 fungal OTUs were retained. Bacterial alpha-diversity and fungal alpha-diversity were calculated in R based on the “vegan” package.

Statistical Analysis

All statistical analyses were performed in R (version 4.2.0) unless otherwise noted. The multiple comparisons of soil nutrient contents, nutrient contents of leaves and quality parameters were calculated by analysis of variance (ANOVA) and Duncan's tests using the “agricolae” package. The alpha-diversity (observed OTUs number, phylogenetic diversity index) was calculated after rarefying using the “vegan” package. A nonparametric statistical test (Kruskal-Wallis test) was used to evaluate the difference in the alpha-diversity and beta-diversity among different grape varieties and among different compartments (bulk soil, rhizosphere soil of new roots and old roots, endosphere of new and old roots, leaves, fruits). The beta-diversity of bacteria and fungi were assessed by computing weighted Bray-Curtis distances matrices and then ordinated using Constrained principal coordinate analysis (CPCoA) (Zgadzaj et al. 2016), the results were visualized through the “ggplot2” package. The significance of three factors on community dissimilarity was tested with PERMANOVA using the “adonis” function of the “vegan” package based on weighted Bray-Curtis distance with 999 permutations. Functional annotation of prokaryotic taxa (FAPROTAX) was used to the functional annotation of bacterial community (Louca et al. 2016). The functional annotation of fungal community was predicted using the FUNGuild database (Nguyen et al. 2016). The abundance-occupancy analysis was used to define core microbiome (Shade and Stopnisek 2019). More specifically, we defined core microbiome from rhizosphere soil as those OTUs which shared by all rhizospheric samples, those OTUs which shared by all treatments and exists in at least one repeat in a treatment were defined as core microbiome from all endospheric compartments. The phylogenetic-bin-based null model analysis (iCAMP) was used to determine the relative importance of stochastic and deterministic processes to the assembly of microbial communities (Ning et al. 2020).

Diversity of microbial communities

Across all samples, the number of the observed OTUs and the phylogenetic diversity of both bacterial and fungal communities decreased gradually along the compartment continuum from bulk soil to rhizosphere soil to endosphere of roots, leaves and fruits (Fig. 1). In particular, from rhizosphere soil to root endosphere, the alpha diversity of both bacteria and fungi decreased significantly and the former was greater than the latter. By contrast, no significant difference was observed among different grape varieties across all compartments and between the two sampling times (Fig. S1). Furthermore, the alpha-diversity of both bacterial and fungal communities at harvest were higher than those at swelling stage across all the compartments and among the five varieties (Fig. S2). The restricted principal coordinate analysis (CPCoA) and PERMANOVA analysis revealed that the community structure of both bacteria and fungi was significantly affected by compartment, followed by variety and sampling time (Fig. 2).

The effect of variety on bacterial communities was significant in bulk soil, rhizosphere, endosphere of old roots and leaves, and fruits. Its effect on fungal communities was observed in all compartments (Table 1, Table 2). The effect of sampling time on bacterial and fungal communities was significant in bulk soil, rhizosphere, endosphere of new roots. In addition, its effect on fungal communities was also observed in the endosphere of old roots (Table 1, Table 2).

Table 1

Effects of variety, time on bacterial community structure in different compartments based on PERMANOVA.
Compartment	Variety		Time		Variety*Time
Compartment	R²	P	R²	P	R²	P
Bulk soil	0.197	0.001	0.069	0.001	0.111	0.060
Rhizosphere soil of new roots	0.208	0.001	0.148	0.001	0.083	0.068
Rhizosphere soil of old roots	0.250	0.001	0.080	0.001	0.095	0.088
Endosphere of new roots	0.134	0.153	0.110	0.003	0.073	0.471
Endosphere of old roots	0.339	0.001	0.034	0.096	0.107	0.072
Endosphere of leaves	0.227	0.037	0.033	0.235	0.056	0.706
Endosphere of fruits	0.330	0.007	0.021	0.333	0.009	0.992
PERMANOVA using the ‘adonis’ function of the VEGAN package in R, based on weighted Bray-Curtis distances matrices.

Table 2

Effects of variety and time on fungal community structure in different compartments based on PERMANOVA.
Compartment	Variety		Time		Variety*Time
Compartment	R²	P	R²	P	R²	P
Bulk soil	0.194	0.001	0.099	0.001	0.080	0.556
Rhizosphere soil of new roots	0.222	0.001	0.275	0.001	0.076	0.046
Rhizosphere soil of old roots	0.228	0.001	0.155	0.001	0.131	0.001
Endosphere of new roots	0.183	0.007	0.144	0.001	0.092	0.122
Endosphere of old roots	0.263	0.001	0.046	0.048	0.084	0.395
Endosphere of leaves	0.204	0.001	0.020	0.535	0.078	0.689
Endosphere of fruits	0.194	0.017	0.025	0.387	0.036	0.999
PERMANOVA using the ‘adonis’ function of the VEGAN package in R, based on weighted Bray-Curtis distances matrices.

Relationships between microbial communities and environmental variables

The Mantel test showed the relationships between the microbial community structure and environmental variables (Fig. 3). Bacterial community structure in bulk soil was significantly correlated with available magnesium while fungal community structure was not significantly affected by any of the soil physicochemical properties. Bacterial communities in the endosphere of leaf and fruit were not significantly correlated with nutrient contents in leaves and fruits, but fungal communities in those two compartments were affected by iron and total nitrogen content.

The Spearman correlation analysis was conducted between the phyla at higher relative abundance with the environmental variables such as soil physicochemical properties, leaf nutrients content and fruit nutrients content (Fig. 4). In bulk soil and endosphere of leaves and fruits, there were significant correlations between microbial taxa at different phylum and soil physicochemical properties, as well as nutrient contents of leaves. In bulk soil, The phylum of Proteobacteria, Firmicutes, Chloroflexi, Actinobacteriota, Bacteroidota, Bdellovibrionota, Gemmatimonadota, Myxococcota and Dependentiae was significantly correlated with soil physicochemical properties. Among them, the relative abundance of Bdellovibrionota was positively correlated with soil pH, available P, available Mg and Fe, total carbon and C/N ratio while the relative abundance of Gemmatimonadota was negatively correlated with soil pH, available magnesium, available zinc, total carbon and C/N ratio. Eight fungal phyla were affected by soil physicochemical properties. The relative abundance of Aphelidiomycota was negatively correlated with available P and SOM while the relative abundance of GS01 was positively correlated with SOM, available zinc and total carbon. However, compared to that in bulk soil, the relative abundance of bacteria and fungi in leaf and fruit endosphere was less susceptible to plant and soil variables. In leaf and fruit endosphere, two bacterial phyla and 2 fungal phyla were significantly affected by nutrient contents of leaves and fruits. The relative abundance of Firmicutes was positively correlated with available Ca, Mg, Mn, and that of the Bacteroidota was positively correlated with total carbon and negatively with total P. The relative abundance of Basidiomycota was affected by nearly all the variables.

Core microbiomes and functional annotations

To define core microbiomes in rhizosphere soil, we first selected those OTUs shared by all samples of each variety, then we used Venn diagrams to find those OTUs which were common to five varieties (Fig. 5). Then the relative abundance of core bacterial taxa or core fungal taxa must be more than 1% in whole bacterial or fungal dataset, respectively. Subsequently, 97 OTUs were regarded as core and 29 OTUs were as core fungi. Taken together, 5 bacterial OTUs and 172 fungal OTUs were defined as core microbiomes of endosphere.

The taxonomic analysis showed that the core bacteria in rhizosphere soil belonged to 9 phyla, 40 families and 43 generas (Supplementary file1). Subsequently, core bacteria (relative abundance > 1%) in rhizosphere soil mainly belonged to Proteobacteria, Actinobacteriota, and Firmicutes (Fig. 6A). Taken together, the relative abundance of core bacteria belonging to Enterobacteriaceae, Rhizobiaceae, Comamonadaceae, Sphingomonadaceae, Streptomycetaceae, Steroidobacteraceae, Bacillaceae, Methylophilaceae, Xanthomonadaceae, Paenibacillaceae, Microbacteriaceae, Nocardioidaceae were all more than 1%. Core fungi in rhizosphere soil belonged to 5 phyla, 15 families and 20 generas, and mainly belonged to Ascomycota, Basidiomycota, Mortierellomycota with relative abundance > 1% (Fig. 6C). The core fungi mainly belong to Ceratobasidiaceae, Lasiosphaeriaceae, Nectriaceae, Mortierellaceae, Stachybotryaceae, Bionectriaceae, Morosphaeriaceae and Chaetomiaceae.

Endophytic core bacteria all belonged to Proteobacteria (Fig. 6B). The endophytic core bacteria belong to Burkholderiaceae, Enterobacteriaceae and Mitochondria, respectively. Endophytic core fungi were belonged to Ascomycota, Rozellomycota, Basidiomycota, Mortierellomycota, Monoblepharomycota and others (Fig. 6D). Chaetomiaceae, Nectriaceae, Ascobolaceae, Phaeosphaeriaceae, Lasiosphaeriaceae, Onygenales fam Incertae sedis, Gymnoascaceae, Aspergillaceae and Metschnikowiaceae were main families of endophytic core fungi (relative abundance > 1%).

To gain further insights into the potential functioning of core microbiomes, the functional annotations according to FunGuild database were also displayed (Supplementary file2). There were 78 functional annotations for bacteria in rhizosphere soil and 8 annotations in endosphere (Supplementary file2). The predicted functions in rhizosphere soil were mainly associated with methanol oxidation, methylotrophy, chitinolysis, nitrogen fixation, aerobic chemoheterotrophy, aromatic compound degradation, nitrate reduction, predatory, ureolysis and chemoheterotrophy. The functions for endophytic core bacteria were mainly associated with fermentation, forming symbionts with plants, nitrate reduction, intracellular parasites, chemoheterotrophy. Furthermore, the major trophic modes of core fungi in rhizosphere soil were saprotroph, followed by pathotroph and symbiotroph. Core fungi in endosphere were mainly putative pathotroph, followed by saprotroph and symbiotroph.

Microbial community assembly

As the compartment had the highest explanations for the overall variation of microbial communities, we investigated microbial assembly in all the compartments across all varieties and two sampling times. The phylogenetic-bin-based null model analysis (iCAMP) was used to quantify the relative importance of deterministic and stochastic processes of the microbial community assembly in each compartment. When all the data was pooled, deterministic processes e.g. homogeneous selection (45%) and stochastic processes e.g drift (41%) were dominant in shaping bacterial communities, whereas the dispersal limitation (67%) was mainly attributable for the fungal community. In bulk soil, leaf and fruit endosphere, the bacterial community were more influenced by homogeneous selection, while in rhizosphere soil of new roots and old roots and in endosphere of new roots and old roots, bacterial community was more affected by drift. In endosphere of leaves and fruits, homogeneous selection contributed more to fungal community compared to other ecological processes.

Our resultes showed that across all samples, the alpha diversity of both bacterial and fungal communities decreased gradually along the soil-plant continuum (Fig .1). The host immune system and plant secretions in the inner sphere caused strong selection pressure, so only relatively few bacteria could colonize (Guttman et al. 2014; Kembel et al. 2014). In line with studies including wine grapes (Marasco et al. 2018) and other crop species (Luo et al. 2022; Xiong et al. 2021), compartments had the strongest effects on the diversity and community structure of microbial communities (Fig. 2), followed by variety and timing. This study further corroborated that microbial community is niche specific and target management is neccessary. The effect of variety on bacterial communities was significant in specific compartments, such as bulk and rhizosphere soil, endosphere of old roots and leaves of leaves, and fruits. The effect was significant in all compartments for fungal communities (Tables 1 and 2). Similary, host genotype (rootstock type) was reported for bacterial community in the roots of grape plants (Marasco et al. 2018). It was also reported that the recruitment of plant root microbiome was driven by groundcover management, genetics and root exudates (Kawasaki et al. 2021; Vukicevich et al. 2018; Zancarini et al. 2021). The minor differences in microbial communities among five varieties might be associated with the disease management practices. The five grapes were grown within one field and were exposed to the same pesticide applications, and this may override the genotypic effects. This was contrast to previous studies (Wu et al. 2021). The alpha-diversity of both bacterial and fungal community at harvest were higher than those at swelling stage in all the seven compartments and cross five varieties (Fig. S2). Similarly, phenological changes lead to the fluctuation of the microbiota in grapevine (Hamaoka et al. 2022). Modifications in the nutrient composition of exudates and pH cause the changes of bacterial abundance and microbial community during the ripening process of wine grapes (Martins et al. 2012).

In the present study, bacterial and fungal community structure were associated with some physicochemical properties of soils, in particular the nutrient availability of macro- and mineral elements. For instance, soil bacterial community structure was significantly correlated with soil available Mg, and fungal communities of leaf endosphere and fruit endosphere were affected by available iron and total nitrogen content (Fig. 3). Previous study also showed that soil pH, soil organic matter, C/N ratio, and total P were the main factors that explained the composition of soil bacterial communities for wine grapes, while SOM was the major factor for fungal communities (Liang et al. 2019). Additionally, it was proposed that environmental factors such as SOM, pH, total phosphorus, inorganic nitrogen, the stoichiometric ratio of C:N:P were all significantly correlated with soil bacterial alpha diversities in alpine ecosystems (Cui et al. 2019). Soil fungal community could also be affected by soil P and Zn (Wu et al. 2022). In the present study, all table grapes were grown in the same field, and hence the microbial communities were mostly related to the capability of each varieties to take up and translocate nutrients. Differences in the growth pattern and nutrient allocation are thus needed in future studies. In addition, we found that those phyla with higher relative abundance were significantly associated with environmental variables (Fig. 4). Genera Lactococcus and Pseudomonas exhibited negative correlations with SOC contents, while Tetracladium was positively associated with SOC contents and amylase activity (Liang et al. 2019).

Disentangling the assembly process of plant-associated microbial community provide important information for understanding the interactions among host plants, soil and microbes. The results of null modelling showed that stochastic process played an important role in affecting the structure of grape-associated bacterial community and fungal community along the soil-plant continuum, especially for fungal community (Fig. 7). Similarly, neutral-based models were used to described bacterial community assemblages of various compartments in soil-plant continuum compartments of different cropping systems (Chen et al. 2022). In the present study, bacterial community assembly in bulk soil was mainly affected by deterministic processes but stochastic processes dominated fungal community assembly (Fig. 7). The microbial assembly in rhizosphere soil and endosphere of new roots and old roots were all dominated by the stochastic processes. Our results were similar to a previous study (Zhang et al. 2022). However, for endosphere of leaves and fruits, homogeneous selection were relatively more important compared to other ecological processes. Previously the flower involved host–symbiont feedback, the selection of specific bacteria by the reproductive organs of angiosperms was relevant for the modulation of fruit and seed production (Massoni et al. 2021). Host selection played an important role in the assembly of endophytic bacterial communities while bacterial communities in both bulk and rhizosphere soils were significantly positively correlated with the relative contribution of deterministic processes (Zhang et al. 2022).

Understanding the core microbiomes of crops was important for understanding the stable, consistent components across complex microbial assemblages (Shade and Handelsman 2012). We identified core microbiomes of rhizosphere soil and endosphere (Fig. 5). 97 bacterial OTUs and 29 fungal OTUs were defined as the core microbiomes of rhizosphere soil while 5 bacterial OTUs and 172 fungal OTUs were defined as the core microbiomes of endosphere. In the present study, functional annotations of the rhizospheric core bacteria were mainly associated with redox process, while endophytic bacteria were mainly fermentative and symbiotic. Rhizospheric core fungi were saprophytic and the endophytic fungi were putative pathogens. Previously core fungi of wine grapes was mainly associated with fermentative yeasts (Saccharomyces, Candida), yeast-like fungi (Aureobasidium), and filamentous fungi (Cladosporium, Alternaria, Fusarium, Penicillium) while the core bacteria were Proteobacteria, Firmicutes, Actinobacteria, and Verrucomicrobia (Wei et al. 2022). Core bacterial microbiomes composed of Gammaproteobacteria, Alphaproteobacteria, Betaproteobacteria, Sphingobacteria, Bacilli, and Actinobacteria, and fungal microbiomes included Dothideomycetes, Leotiomycetes, and Tremellomycetes were regarded to be important components and also a gene reservoir of secondary metabolism in Salvia miltiorrhiza (Chen et al. 2018a; Chen et al. 2018b).

Collectively, the compartment was the major factor attributable to the variations in both bacterial and fungal community. The taxonomic diversity and phylogenetic diversity of bacterial and fungal community showed a sharp decreasing trend from bulk soil, rhizosphere soil, root endosphere to aboveground. Soil bacterial community structure was significantly correlated with soil available magnesium. Bacterial communities from endosphere of leaves and fruits were not affected by nutrients content in leaves and fruits while fungal communities of those two compartments were affected by iron and total nitrogen content. We identified 97 bacterial OTUs and 29 fungal OTUs as core microbiomes for rhizosphere soil, and 5 bacterial OTUs and 172 fungal OTUs were core microbiomes of endosphere. Those core bacteria in rhizosphere soil were mainly associated with redox process, while endophytic core bacteria mainly performed functions such as fermentation and symbiosis with table grapes. The main nutritional mode of rhizospheric core fungi were saprophytic fungi but the endophytic core fungi were dominated by pathogens. From rhizosphere soil to aboveground organs, the relative contribution of deterministic processes especially homogeneous selection gradually increased for both bacterial and fungal community assembly.

OTUs Operational Taxonomic Units

ANOVA Analysis of variance

PERMANOVA Permutational multivariate ANOVA

PCoA Principal co-ordinates analysis

CPCoA Constrained principal co-ordinates analysis

Competing Interests

The authors declare that they have no conflicts of interest.

Authors’ contribution

Jiangzhou Zhang and Junling Zhang designed this study; Jiangzhou Zhang sampled samples from field; Jiangzhou Zhang and Jiyu Jia performed laboratory work; Muxi Xie analyzed and interpreted the data; Muxi Xie, Jiangzhou Zhang and Junling Zhang wrote the manuscript.

Acknowledgements

This work was supported by the National Key R&D Program of China (2022YFD1901301).

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Deciphering core microbiomes and community assembly of table grapes

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Abstract

Aims

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Introduction

Materials and methods

Experimental design and sample collection

DNA extraction and high-throughput sequencing

Bioinformatic Analysis

Statistical Analysis

Results

Diversity of microbial communities

Relationships between microbial communities and environmental variables

Core microbiomes and functional annotations

Microbial community assembly

Discussion

Conclusion

Abbreviations

Declarations

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