Reciprocal influence of soil, phyllosphere and aphid microbiomes

doi:10.21203/rs.3.rs-2651152/v1

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Reciprocal influence of soil, phyllosphere and aphid microbiomes

https://doi.org/10.21203/rs.3.rs-2651152/v1

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published 21 Jul, 2023

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Background

The effect of soil on the plant microbiome is well-studied. However, less is known about the impact of soil microbiome in multitrophic systems. Here we examined the effect of soil on plant and aphid microbiomes, and the reciprocal effect of aphid herbivory on the plant and soil microbiomes. We designed microcosms, which separate below and aboveground compartments, to grow oak seedlings with and without aphid herbivory in soils with three different microbiomes. We used amplicon sequencing and qPCR to characterize the bacterial and fungal communities in soils, phyllospheres, and aphids.

Results

Soil microbiomes significantly affected the microbial communities of phyllospheres and, to a lesser extent, aphid microbiome, indicating plant-mediated assembly processes from soil to aphids via the plant endosphere. While aphid herbivory significantly decreased microbial diversity in phyllospheres independent of soil microbiomes, the effect of aphid herbivory on the community composition in soil varied among the three soils.

Conclusions

This study provides experimental evidence for reciprocal influence of soil, plant and aphid microbiomes, with potential for the development of new microbiome-based pest management strategies.

plant-insect-microbe

multitrophic interaction

herbivory

microcosm

Quercus robur (pedunculate oak)

Tuberculatus annulatus (common oak aphid)

Soil microbiomes influence the microbiome associated with plants, which are known to have major implications for plant resilience, growth and vigor (Hardoim et al., 2015; Vandenkoornhuyse et al., 2015; Berg et al., 2017). Plants further interact with various invertebrate animals during their lifespan, for instance soil-inhabiting, pollinating or herbivorous arthropods. Insect herbivores often depend on their associated microbiome including microbial symbionts, providing pivotal nutrients, or for detoxifying secondary plant metabolites (Baumann, 2005). Interaction between multicellular organisms like plants and aphids consequently lead to a concurrence and interaction of two host-associated microbiomes as well (van der Heijden & Hartmann, 2016; Brinker et al., 2019). While we know from literature that soil microbiome influences phyllosphere (Bergna et al., 2018; Grady et al., 2019; Malacrinò et al., 2021a) and aphid microbiomes (Malacrinò et al., 2021a), it is yet unclear whether these effects are direct or plant-mediated, or whether reciprocal effects of aphid herbivory to phyllospheres and soil microbiomes are direct or plant-mediated. Investigating only plant-mediated interactions between soil, plant and aphid microbiomes would indicate to what extent plants themselves are able to modulate and shape soil- and aphid-associated microbiota in their environment. This would have major implications for future pest biocontrol options and our general understanding of plant microbiome assembly under biotic stress.

Phyllosphere microbiome assembly starts during seed germination through microbial inheritance (Bergna et al., 2018; Wolfgang et al., 2020; Abdelfattah et al., 2021b; Fort et al., 2021). During seed germination, a specific set of microorganisms migrate from seed to phyllosphere (Abdelfattah et al., 2021). Subsequent phyllosphere colonizers are then recruited from the surrounding environment, especially from soil, through horizontal acquisition (Bergna et al., 2018; Grady et al., 2019; Dastogeer et al., 2020; Trivedi et al., 2020; Malacrinò et al., 2021a; Massoni et al., 2021), but also dust, air, and water (Berg et al., 2014; Trivedi et al., 2020). It is yet unclear whether the observed effect of soil on the plant, especially the phyllosphere, microbiome is due to a direct transmission of microorganisms from the environment, or mediated through the plant. Soil physicochemical properties have a substantial effect of on the soil microbiome, which can subsequently influence phyllosphere microbiomes (Thapa et al., 2018; Mittelstrass et al., 2021). Therefore, understanding direct and plant-mediated effects on plant microbiomes will reveal to what extent plants use present soil microbial diversity for microbiome assembly, and to what extent plant anatomy and physiology are able to influence the respective plant microbiome.

The aphid microbiome can be divided into primary endosymbionts such as Buchnera aphidicola, secondary symbionts, and transient bacteria (Zytynska et al., 2021). While the presence of primary symbionts is guaranteed by vertical transmission (Baumann, 2005; Bennett & Moran, 2015), the mechanism by which the remaining members of the aphid microbiome are assembled or maintained is yet not fully known (Zytynska & Weisser, 2016). At the current state of knowledge, factors including aphid species identity, plant host species identity, geographical location, aphid predator and aphid parasitoid frequency are known to influence the composition of the aphid microbiome (Zytynska & Weisser, 2016). Although soil microbial diversity was shown to influence aphid bacterial community (Malacrinò et al., 2021a), aphid fungal communities were not investigated using culture-independent methods so far. Furthermore, it is difficult to determine whether in vivo observed effects of soil microbiome on aphid microbiomes are due to plant-mediated mechanism (plant assembly of soil microbiome and subsequent transmission to aphids) or due to environmental contamination, particularly from soil. The effect of soil microbes on aphids, with plants connecting below- and above-ground microbiomes, may have important consequences for understanding effects on herbivore performance as well as biocontrol approaches.

Information regarding the effect of aphid infestation on phyllosphere microbiomes is limited, but often attributed to the production and deposition of honeydew to phyllosphere surfaces. Honeydew is known to favor sooty mold species (Dhami et al., 2013) and aphids were found to increase abundance of culturable epiphytic fungi and bacteria on leaves and shoots of several forest tree species (Stadler & Müller, 1996, 2000; Mühlenberg & Stadler, 2005). Moreover, aphids are known to deposit associated microbes in and on leaves and induce stress responses in plants (De Vos & Jander, 2009; Chaudhary et al., 2014; Furch et al., 2015; Whitfield et al., 2015; Luna et al., 2018). Plant stress responses affect phyllosphere microbiomes as well (Liu et al., 2020a). For instance, woolly beech aphid (Phyllaphis fagi) infestation leads to a bacterial community shift in beech (Fagus sylvatica, L.)(Potthast et al., 2022). However, to what extent phyllosphere microbiome response upon aphid herbivory depends on the soil microbiome remains elusive.

Reports on the effect of aphid herbivory on the soil microbiome are relatively scarce and partially contradictory. Some studies have shown that aphid herbivory can change the composition of the microbial communities in the rhizosphere (Liu et al., 2020b; Malacrinò et al., 2021b), while others reported no observable effects (O’Brien et al., 2018). In nature, soil microbiome shifts upon aphid herbivory may be caused either by throughfall of honeydew, influencing carbon and nitrogen fluxes (Michalzik & Stadler, 2005; Potthast et al., 2022), or by changes in root exudation patterns, known to shape soil microbiomes (Liu et al., 2020a). While honeydew throughfall promotes microbial activity in soil (Seeger & Filser, 2008), the effect of changed root exudates are less clear and probably depend on the biotic or abiotic soil characteristics.

The objective of this study was to examine the effect of the soil microbiome on the assembly of oak phyllosphere and aphid microbiomes, as well as the effects of aphid herbivory on phyllosphere and soil microbiomes. We used the pedunculate oak (Quercus robur L.), the common oak aphid (Tuberculatus annulatus, HARTIG) and three soil microbial communities with the same physicochemical background as test system to answer the following questions:

Do different microbial soil communities lead to differences in phyllosphere communities? (Fig. 1a: Q1)
Do different microbial soil communities lead to differences in aphid communities? (Fig. 1a: Q2)
Does aphid feeding alter the phyllosphere microbial communities? (Fig. 1a: Q3)
Does aphid feeding alter soil microbial communities? (Fig. 1a: Q4)

By investigating these questions in a controlled setting, we aim to reveal which formerly observed effects on microbiomes in a plant-herbivore system are truly plant-mediated, and which effects are potentially influenced or influenceable by the soil microbiota in a given soil.

Raw material

Three different types of soil were collected on March 29, 2019 including a loamy sandy soil from Stockholm University campus (henceforth called ’mixed’ soil), a sandy soil and a clayey soil from Tovetorp Zoological Research Center, situated 60 km southwest of Stockholm. Each soil type was divided into two parts. The first part, was autoclaved twice at 120 °C for 20 min with 24 hours interval at room temperature. The second part, was used later as inoculum. To minimize the effects of soil physicochemical properties, 1.25 l of all soil types were mixed in same proportions (v/v) across treatments, together with 7.5 l of commercial sterilized potting soil (Så och pluggjord, SW Horto, Hammenhög, Sweden) (Supporting Information Table S1). All soil types were sterile except the soil of interest, which acted as inoculum for the otherwise identical soil mixture (Fig. 1b). These soil mixtures are further denoted according to their corresponding non-autoclaved inoculum (‘clayey’, ’mixed’, and ’sandy’). Two liters of sterilized MilliQ water was added to each soil mix.

Pedunculate oak (Quercus robur) acorns were collected from a single oak tree located on Stockholm University campus (Tree # 000369) to minimize the effect of genotype. Acorns were surface-sterilized to minimize contamination with environment-derived microbes using 5% NaOCl for 30 minutes, followed by three rinses in sterile MilliQ water each for 10 minutes. Surface-sterilized acorns were stored in sterile sand at 4 C until use. Before the start of the experiment, acorns were surface sterilized again for 5 min in 5% NaOCl and rinsed as previously mentioned. Common oak aphid (Tuberculatus annulatus) was originally collected from natural populations in Stockholm (2018) and reared on oak saplings in a climate chamber (10 h light at 20°C light, 14 h dark at 18°C) for several generations prior to the experiment.

Experimental Setup and sample collection

To capture solely plant-mediated microbiome assembly processes, we used microcosms that physically separate above- and belowground plant compartments to grow seedlings under aseptic conditions (Abdelfattah, 2021; Abdelfattah et al., 2021b). Microcosms included openings with filters in the upper compartments to allow gas exchange, but prevent microbial contaminants from the surrounding (Fig. 1b). To separate microbiome shifts in soil due to experimental settings and general plant-mediated effects (e.g. normal root exudation) from herbivory-mediated effects, ten soil samples per soil type, each consisting of 500mg collected before planting acorns from microcosms with and without aphids. These samples are further denoted as “inoculum”, despite being the readily prepared soil mixtures at the beginning of the experiment (Fig. 1b). A total of 45 microcosms per soil type were prepared, making a total of 135 microcosms. The lower compartment of the microcosms was filled with 250 ml of soil and left for 10 days in a growth chamber at 20°C for acclimatization. One surface-sterilized acorn per microcosm was planted under aseptic conditions. Once germinated, a seal was applied to encapsulate the acorn, limiting cross-contamination between below- and above-ground plant parts, preventing neither aphid nor honeydew to come in direct contact with soil, or soil to come in direct contact with neither seedling phyllospheres nor aphids. Seedlings were kept in growth chambers (10 h light at 20°C, 14 h dark at 18°C, light intensity 110 µmol m^-2 s^-1, air humidity 65%) until they reached the three- to four-leaf stage. For 35 randomly selected seedlings per soil type, twenty aphids were added to the uppermost leaves using a sterile needle. Ten seedlings per soil type were grown without aphids, acting as a control group (Fig. 1b). Microcosms were randomly divided into 4 sampling groups in the course of processing. After seven days, soil, leaves without petiole which were thoroughly checked for aphid remains, and living aphids were collected for DNA extraction. Microcosms containing plants that showed symptoms of wilting or disease were removed from further analyses (Fig. 1b). For soil samples, 500mg was collected at the center of each microcosm. All samples were stored at -20°C until further processing. Leaves were lyophilized using ScanVac CoolSafe™ (LaboGene), and grounded using TissueLyser II (Qiagen). Leaf samples are further denoted as “phyllosphere

DNA extraction and library preparation

Inoculum and soil samples were extracted using DNEasy PowerSoil pro Kit (Qiagen, Hilden, Germany) according to the manufacturer instructions. For phyllosphere samples, 200mg of the lyophilized phyllosphere powder was extracted using DNEasy PowerSoil pro Kit (Qiagen, Hilden, Germany). Aphids were extracted using a modified protocol of the DNeasy® Blood&Tissue (QIAGEN GmbH, Hilden, Germany) standard procedure for insects (Supporting Information Methods S1). One extraction control sample was added per extraction procedure, which was further treated like additional samples to remove potential contaminants in silico.

Amplification of 16SrRNA and ITS sequences was performed using the primer pairs 515f/806r (Caporaso et al., 2011) and ITS1f/ITS2r (White et al., 1990) for bacteria and fungi, respectively. Primers included sample-specific barcodes and Illumina adaptors. For phyllosphere and soil samples, peptide nucleic acid (PNA) PCR clamps were added to block the amplification of plant plastid and mitochondrial DNA (Lundberg et al., 2013). PCR was performed in 30μl reactions, with 2µl template for soil and phyllosphere, and 5µl template for aphid samples (Supporting Information Methods S2). To identify and remove potential contaminants in silico, technical control samples (no-template PCR control samples and extraction control samples for aphid extraction) were also sequenced. In total, 333 and 311 samples for bacteria and fungi were successfully amplified, respectively. PCR products were purified using the Wizard SV Gel and PCR Clean-Up System (Promega, Madison, WI, USA). Final DNA concentrations were estimated using Nanodrop 2000 (Thermo Scientific, Wilmington, DE, USA). Since the source of phyllosphere- and aphid-associated microorganisms is one of the main questions of this study, soil, bacterial phyllosphere, fungal phyllosphere, bacterial aphid and fungal aphid samples were separately pooled to equimolar concentrations to avoid index hopping (Costello et al., 2017; Ros-Freixedes et al., 2018). Amplicon sequencing was performed by Eurofins Genomics (Konstanz, Germany) on a MiSeq V3 (600-cycle) platform.

Quantification of fungal and bacterial communities

To quantify the gene copy number of 16S rRNA and ITS rDNA, we used a subset of 4 samples from each treatment for quantitative real time PCR (qPCR). Target genes were amplified using KAPA SYBR® Green 2X MM (KAPA Biosystems, Cape Town, South Africa) in 10 μl reaction mixtures (for details see Supporting Information Methods S2). PNA clamps (Lundberg et al., 2013) were used for soil and phyllosphere samples. Each measurement was performed in three independent runs on a Rotor-Gene 6000 device (Corbett Research, Mortlake, Australia). Mean fragment copy numbers were blank-corrected and extrapolated to copy numbers per g initial sample weight. We still observed mitochondrial, plastid DNA (16SrRNA dataset), unassigned and plant-assigned reads (ITS dataset) in our amplicon sample results. Therefore, the corresponding relative abundance in the amplicon dataset was used to remove non-target reads from qPCR data. Reads were log10-transformed and will be further denoted as “microbial abundance”.

Data preprocessing and Bioinformatic analyses

Preprocessing of amplicon data was performed in QIIME2 v. 2019.10 (Bolyen et al., 2019). Raw amplicon sequences were demultiplexed using cutadapt (Martin, 2011). Sequences were truncated at 150bp and 170bp for bacteria and fungi respectively, and denoised using DADA2 (Callahan et al., 2016). Taxonomy assignment was performed using VSEARCH (Rognes et al., 2016) with SILVA v.132 (Quast et al., 2013) and UNITE v. 7 (Nilsson et al., 2019) as bacterial and fungal reference sequences, respectively. Amplicon sequencing variants (ASVs) table, taxonomy and metadata was imported to R v. 4.1.1 (R Core Team, 2018) and further processed using the ’phyloseq‘ package (McMurdie & Holmes, 2013). For the bacterial dataset, chloroplast, mitochondrial, and reads unassigned at the kingdom level were removed. Due to low remaining ASV read counts in phyllosphere samples, only forward reads were used for diversity analyses. For fungi, plant reads and reads unassigned at the kingdom level were removed. Bacterial and fungal contaminants were identified and removed with the prevalence-based method of the R package ’decontam’ using PCR and extraction control samples (Davis et al., 2018).

Statistical analyses

Statistical analyses were performed in R v. 4.1.1 (R Core Team, 2018). To account for uneven sequencing depth, ASV tables were rarefied to an even depth of 3900 and 4000 for soil, 100 and 4000 for phyllosphere and 1500 and 4000 for aphid samples for bacteria and fungi, respectively. Species richness and Shannon diversity index were estimated using phyloseq package and checked for normal distribution using Shapiro-Wilks test. For community composition analysis, ASV tables were normalized using Cumulative Sum Scaling (CSS) which was used to calculate Bray-Curtis dissimilarities.

To test the effect of soils on phyllosphere (Q1) and aphid (Q2) on microbial community descriptors, we modelled fungal and bacterial richness, Shannon diversity, and abundance as a function of soil type using Kruskal-Wallis test with FDR-correction followed by Wilcoxon signed-rank test for pairwise comparisons. To test the effect of aphid infestation on fungal and bacterial diversity of phyllosphere (Q3) and soils (Q4), we modelled fungal and bacterial richness, Shannon diversity, and evenness as a function of aphid infestation using Wilcoxon signed-rank test for pairwise comparisons.

To investigate the effect of soil type on the microbial community composition of phyllosphere (Q1) and aphids (Q2), we modelled multivariate fungal and bacterial community composition as a function of soil type, using Bray Curtis distances and the adonis function in the vegan package (Oksanen et al., 2020). Pairwise Adonis (Martinez Arbizu, 2017) with subsequent Bonferroni correction was conducted separately for each soil type. To investigate which taxa differed in relative abundance between phyllosphere and aphids grown in different soils, we conducted a Linear discriminant analysis Effect Size (LEfSe) implemented in the ’microbial’ package (Segata et al., 2011; Guo & Gao, 2021). Due to the dominance of aphid primary endosymbiont Buchnera aphidicola while displaying varying relative abundances between samples, the analyses of aphid microbiomes were repeated with a Buchnera-filtered dataset, which was rarefied to 500 reads.

To investigate the effect of aphid infestation on the microbial community composition of phyllosphere (Q3) and soils (Q4), we modelled multivariate fungal and bacterial community composition as a function of aphid infestation, using Bray Curtis distances and the adonis function in the vegan package (Oksanen et al., 2020). Pairwise Adonis (Martinez Arbizu, 2017) with subsequent Bonferroni correction was conducted separately for each combination of soil type and herbivory. To ascertain that potential differences in microbial community composition in soil due to aphid infestation (Q4) do not arise from legacy effects of initial differences in soil communities, we modelled community composition as a function of aphid infestation in inoculum, comparing soil of control plants and soil of plants being later infested with aphids. To investigate which taxa differed in relative abundance between infested and not infested phyllosphere (Q3) and soils (Q4), we conducted a Linear discriminant analysis of effect size (LEfSe) implemented in the ’microbial’ package (Segata et al., 2011; Guo & Gao, 2021). Using the same method, we identified differential abundant taxa in inoculum and soil to discriminate between general trends in soil community composition due to normal root exudation or experimental settings, and effects mediated by aphid infestation.

Amplicon data overview

A total of 6,437,014 bacterial and 13,822,677 fungal reads were retained after quality filtering, decontamination, removal of plastid DNA, contaminants and unassigned sequences. A total of 27,596 ASVs were identified in the bacterial amplicon library, in fungi 8,671. Maximum read count per sample was 180,761 with a mean of 20,765 reads per sample in bacterial amplicon samples. For fungal amplicon samples, maximum read counts of 542,484 with a mean of 47,338 reads per sample were retained. All three soil inocula differed significantly in community composition both in bacteria (PERMANOVA: R² = 0.43; p = 0.001) and fungi (PERMANOVA: R² = 0.19; p = 0.001). All inocula combined, bacterial community was dominated by Proteobacteria, Firmicutes, and Actinobacteria; fungal community was dominated by Basidiomycota (dominant genus: Lyophyllum) and Ascomycota (dominant genus: Rasamsonia) (Supporting Information Notes S1).

Assembly from soil to phyllosphere

Soil microbiome had a significant effect on the bacterial species richness (Fig. 2a) and Shannon diversity (Fig. 2b) in the phyllosphere. Among the different soil types, phyllosphere of plants grown in sandy soil microbiome displayed the highest bacterial richness and Shannon diversity. Whereas phyllosphere of plants grown in mixed soil microbiome exhibited the lowest bacterial richness and Shannon diversity. Bacterial abundance in phyllosphere did not differ significantly according to soil microbiome (Fig. 2c), but bacterial community composition differed significantly (Fig. 2d). Fungal phyllosphere species richness (Fig. 2e) and Shannon diversity (Fig. 2f) were not affected by the soil microbiome, yet fungal abundance was significantly higher in phyllosphere grown in clayey than in mixed soil microbiome (Fig. 2g). Fungal phyllosphere community composition significantly differed among the three soil types (Fig. 2h) microbiomes. Pairwise PERMANOVA revealed phyllospheres grown in the three soil microbiomes to significantly differ from each other (Supporting information Table S2). Differential abundance analysis showed that Burkholderia s. lat is a biomarker for the phyllosphere grown in clayey, Pseudomonas for the phyllosphere in mixed, and Streptomyces, Sphingomonas, Erwinia and Acinetobacter for the phyllosphere microbiota. High microbial species richness, Shannon diversity and abundance in soil was rarely correlated to high species richness, Shannon diversity and abundance in phyllosphere (Table 1).

Assembly from soil to aphid

Soil did not have an effect on bacterial species richness (Fig. 3a), diversity (Fig. 3b), or abundance (Fig. 3c) in bacterial aphid communities, but on community composition (Fig. 3d) in aphids. The same pattern was observed in fungal aphid community (Fig. 3e-h). The variance explained (R²) by the factor soil in community composition was higher in fungal (Fig. 3h), than in bacterial aphid microbiomes (Fig. 3d). Pairwise PERMANOVA showed a significant difference between aphid’s bacterial and fungal communities, except for the bacterial community of aphid from clayey and sandy soil microbiomes (Supporting Information Table S3). Aphid microbiomes were dominated by Burkholderia s. lat., and Pseudomonas, while fungal microbiomes were dominated by Cladosporium and Penicillium (Supporting Information Notes S2). Differential abundance analyses using LefSE only showed Micromonosporaceae to be significantly higher in aphids reared on sandy soil microbiome (Supporting Information Table S4). In the fungal dataset, Mortierella spp. and Parasola spp. were higher abundant in aphids reared on clayey soil microbiome, while Cladosporium spp. was higher in aphids reared on mixed soil microbiome, yet not significant (Supporting Information Table S5). High microbial species richness, Shannon diversity and abundance in soil was rarely correlated to high species richness, Shannon diversity and abundance in aphids, but bacterial abundance and fungal Shannon diversity in aphids showed similar patterns when compared to bacterial abundance and fungal Shannon diversity in phyllosphere (Table 1).

Table 1: Dynamics in alpha diversity during soil microbe assembly. Comparison of bacterial and fungal species richness, Shannon diversity, and abundance between different soil microbiomes relative to each other for the three tested compartments soil, phyllosphere, and aphids. Abundance based on log10 transformed qPCR reads of 16S rRNA (bacteria) and ITS (fungi) gene read counts. Rank position (1 = high, 2 = medium, 3 = low) of richness, Shannon diversity and abundance values compared between corresponding compartments (rows). Compartments where phyllosphere and aphid samples show similar patterns are highlighted in bold.

			Bacteria			Fungi
		Soil microbiome type	Clayey	Mixed	Sandy	Clayey	Mixed	Sandy
Species richness	⇓	Soil (rank)	581.6 (3)	742.8 (1)	644 (2)	33.5 (3)	78.7 (1)	72.9 (2)
		Leaf (rank)	5.83 (3)	6.25 (2)	8.79 (1)	23.26 (1)	22.53 (2)	18.03 (3)
		Aphids (rank)	159.78 (2)	158.00 (3)	226.39 (1)	69.92 (2)	78.06 (1)	45.29 (3)

Shannon diversity	⇓	Soil (rank)	5.62 (2)	5.95 (1)	5.41 (3)	0.97 (3)	1.77 (1)	1.42 (2)
		Leaf (rank)	1.17 (2)	1.07 (3)	1.50 (1)	1.70 (1)	1.63 (2)	1.58 (3)
		Aphids (rank)	1.29 (1)	1.15 (3)	1.15 (2)	2.06 (1)	1.80 (2)	1.71 (3)

Abundance	⇓	soil (rank)	8.06 (2)	8.17 (1)	8.05 (3)	5.49 (2)	5.69 (1)	5.18 (3)
		Leaf (rank)	4.18 (2)	4.17 (3)	4.30 (1)	8.15 (1)	7.74 (3)	8.07 (2)
		Aphids (rank)	4.11 (2)	3.87 (3)	4.66 (1)	3.23 (3)	3.52 (2)	4.92 (1)

The effect of aphid herbivory on phyllosphere microbiota

Aphid herbivory had a significant decreasing effect on the phyllosphere bacterial species richness (Fig. 4a) and Shannon diversity (Fig. 4b). Bacterial abundance (Fig. 4c) and community composition (Fig. 4d) did not differ significantly. In fungal phyllosphere species richness (Fig. 4e), Shannon diversity (Fig. 4f) and abundance (Fig. 4g), microbiome response showed the same pattern than in bacteria, but community composition (Fig. 4h) significantly differed between infested and control phyllosphere. Pairwise comparisons of fungal community composition showed that aphid herbivory to was significantly affected in clayey (R² = 0.045, p = 0.018) and sandy soil microbiome (R² = 0.060, p = 0.013), but not in mixed soil. Lefse analysis showed that 72 fungal taxa were more abundant in the phyllosphere of non-infested compared to infested plants. Among those taxa Russula and Preussia were amongst the most affected taxa (Supporting Information Table S6). On the other hand, the phylum Ascomycota was significantly higher relative abundant in aphid-infested phyllosphere.

The effect of aphid herbivory on soil microbiota

Aphid herbivory did not have an effect on microbial soil species richness, diversity, abundance, and community composition (Supporting information Fig. S1), except for bacterial species community composition in sandy soil (Supporting information Fig. S2d). According to LefSe analyses results, effect of aphid infestation on relative abundance of sandy soil microbiota was not significant after p-value correction. Strongest decrease was observed in Rhodanobacter and -amongst others- Bacillaceae, while relative abundance of Rhizobiaceae (Rhizobium s. lat., Mesorhizobium) and Xanthobacteraceae was increased in sandy soil of aphid-infested plants. However, (Supporting information Table S7). Differential abundance of these taxa did not refer to general abundance shifts from inoculum to soil (data not shown), although a soil type-dependent community development was observed when comparing inoculum and soil microbiomes (Supporting information Fig. S2-S4). No specific fungal taxa showed significantly different relative abundances in soil microbiomes of aphid-infested plant.

In the current study, we showed that manipulating soil microbiome changed the plant phyllosphere, and subsequently the aphid microbiome. We found aphid infestation to have significant effects on phyllosphere microbiomes and soil microbiome-plant interactions, interfering with plant-mediated assembly. The implications of aphid infestation for plant-associated microbiomes depend on microbial communities in soil. In this way, this study provides experimental evidence for reciprocal influence of soil, plant and aphid microbiomes.

Soil microbiome affected plant-mediated phyllosphere microbiome assembly. Microbial assembly in plants is regarded as a non-random process governed by selective pressures within the host plant itself (Grady et al., 2019; Xiong et al., 2021), and the fact that soil microbiome shapes phyllosphere microbiomes was observed before in other plant species (e.g., Bai et al., 2015a; Wagner et al., 2016; Grady et al., 2019; Tkacz et al., 2020; Malacrinò et al., 2021a). By investigating the effect of different microbial communities in soil of same physicochemical properties, we could show that phyllosphere microbiome assembly is plant-mediated and thus at least partially driven by biotic factors. Still, selective pressures on microbial endophytes in oak appeared to be generally high, since microbial phyllosphere diversity was low in comparison to other tree species (Laforest-Lapointe et al., 2016; Beckers et al., 2017) which was observed in oaks grown in microcosms (Abdelfattah et al., 2021b) and under field conditions (Faticov et al., 2021). The effect of soil microbiomes on phyllosphere microbiomes was most evident for plants grown in sandy soil microbiomes. This soil, was dominated by Proteobacteria which are known to be the most common phylum of the plant microbiomes (Levy et al., 2018; Trivedi et al., 2020). Thus, experiments conducted in Proteobacteria-rich soils may result in more apparent effects on above-ground microbiomes. Although we found taxa dominating endophytic acorn communities as dominant taxa in phyllosphere, namely Pseudomonas, Burkholderia, Erwinia, Cladosporium or Penicillium (Abdelfattah et al., 2021a), we further identified bacterial biomarkers arising from soil communities in phyllospheres (e.g., Streptomyces, Acinetobacter). This experimentally confirms soil microbiomes to shape oak phyllosphere microbiomes via plant-mediated assembly processes and indirectly by modulating endophytic communities even without any direct physical contact between soil and phyllosphere.

We found that the soil microbiome had an effect on aphid microbiome assembly, even without any direct physical contact. Several studies reported effects of soil microbiome on aphid performance before (Hol et al., 2010; Blubaugh et al., 2018; Brock et al., 2018), and these effects were discussed to arise from indirect effects on plant defense systems (e.g. Pineda et al., 2012). A similar experiment in potato and potato aphids (Macrosiphum euphorbiae Thomas) revealed soil diversity to affect bacterial aphid microbiomes (Malacrinò et al., 2021a), reporting a higher effect size of soil on aphid microbiomes compared to our study. Here, soil microbiome more evidently affected fungal communities in aphids in this experiment, although soil microbiome effect on phyllosphere was more evident for bacteria. To our knowledge, this is the first culture-independent study investigating aphid-associated fungal communities, and we found generalistic fungal taxa common to phyllosphere surfaces in aphids. Therefore, we hypothesize aphid-associated fungi to arise from direct exchanges between epifoliar and epicuticular fungi. Epifoliar fungi are considered to be generalists (Arnold, 2007), and such fungi may be enhanced by aphid honeydew deposition, increasing chances to re-associate with aphids. Interestingly, bacterial species richness is around elevenfold higher in aphids (X̄ = 180.4 ± 112.7) than in phyllosphere (X̄ = 7.3 ± 3.7). Due to the limited diversity in oak phyllospheres and additional selective pressures in the digestive tract of aphids, direct uptake of soil microbes via plant sap may only have minor effects on the autochthonous aphid microbiome.

We observed that aphid herbivory decreased the microbial diversity in phyllosphere, yet abundance was not affected. The statement that soil communities impair phyllosphere microbiomes more than aphid herbivory (Malacrinò et al., 2021a) could be confirmed in this pathosystem. Herbivore-associated microbiomes are known to interfere with plant metabolism and plant defense responses, thus acting as a hidden driving force of plant–herbivore coevolution (Zhu et al., 2014). For instance, bacteria in the saliva of Colorado potato beetle (Leptinotarsa decemlineata SAY) act as plant immunological decoy by triggering antimicrobial (SA-regulated) rather than antiherbivore (JA and ethylene-regulated) plant defenses (Chung et al., 2013). An increase in SA and decrease in JA response-related gene expression was also observed and discussed for bacteria in aphid honeydew (Schwartzberg & Tumlinson, 2014). Interestingly, we found an example of such a potentially “misled” plant immune response in phyllosphere grown in mixed soil microbiomes. Abundance of the entomopathogenic fungus Metarhizium brunneum PETCH, only found in mixed soil microbiomes and corresponding phyllospheres, was reduced in aphid-infested phyllospheres, despite being potentially beneficial to the plant by infecting and killing aphids (Reingold et al., 2021). These results indicate an untargeted, general decrease of several fungal taxa upon aphid herbivory, either arising directly via plant stress responses or indirectly by affecting soil microbiome assembly processes in the plant. The deposition of honeydew may further favor microbial generalists, masking the loss in abundance. Therefore, we hypothesize phyllosphere microbiome shifts upon aphid herbivory to be the consequence of an untargeted antifungal plant defense response, as well as honeydew deposition by the aphid.

Soil microbial community composition determines whether soil microbiome shifts upon above-ground herbivory. This explains, why effects of sap-sucking insects on soil microbiomes were reported before (Yang et al., 2011; Kong et al., 2016; Malacrinò et al., 2021b), while some studies observed no effect (O’Brien et al., 2018). Similar to our results, soil microbiome-dependent responses upon aphid infestation was reported in a wild tomato (Solanum pimpinellifolium) -potato aphid (Macrosiphum euphorbiae) pathosystem (French et al., 2021). In contrast to our results, Bacillaceae were discussed as positive responders to aphid herbivory in soil. In our experiment, Bacillaceae responded negatively, while Xanthobacteraceae and Rhizobiaceae (ad Proteobacteria) responded positively in soil upon aphid herbivory. Soils used by French and colleagues (2021) did not significantly differ in relative abundance of Proteobacteria, therefore the exact cause for responsiveness of soil microbiomes to herbivory remains a matter of debate. However, responses are most likely driven by plant root exudation. Oak root exudate composition is known to shift towards a higher concentration of secondary metabolites under abiotic stress (Gargallo-Garriga et al., 2018). Given that exudate composition changes accordingly under biotic stress, soil microbiome responses upon herbivory may be indirectly driven by susceptibility of soil microbes towards such root exudates. For sandy soil microbiomes, the ’cry-for-help’ hypothesis (Rolfe et al., 2019) cannot be excluded, but observations can be also explained with decreased amounts of metabolizable root exudates (Hoysted et al., 2018). Firstly, taxa increased in aphid-infested sandy soil are not known for antiherbivore or plant growth-promoting effects. Secondly, genera known for nitrogen fixation (Rhizobium, Mesorhizobium) are increased, indicating a more nutrient-depleted environment compared to control plants. Thirdly, bacterial species richness is higher in aphid-infested sandy soil, indicating lower selection pressure. Fourthly, bacterial abundance is generally lower in infested plant soil. Lastly, when combining all soil data, we do not find significantly responding biomarker taxa in differential abundance analyses. Altogether, this indicates a weaker selective force of root exudates on microbes in the root periphery of aphid-infested plants compared to control plants.

Soil, plant and aphid microbiomes are in a dynamic tripartite interaction, in which the strength of effects depends on the represented microbial communities and not the physicochemical properties of soil. While directly shaping phyllosphere and aphid microbiome using soil is possible to some extent, the effect size of soil microbiome gradually decreases from phyllosphere to aphids. Still, soil microbes being transmitted to aphids via the plant are of interest for biocontrol of pests, since soil or seed treatments are easier to handle, and have less mechanical impact on agricultural plants than spray applications (McQuilken et al., 1998). Herbivory has implications for phyllosphere and partially soil microbiomes, although the specific responses depend on yet unidentified soil microbiome specifics. To fully disentangle the role of soil microbiome from soil physiochemical properties in tritrophic systems, future studies could investigate the response of plant microbiomes on synthetic or otherwise defined microbial soil communities under different physicochemical soil conditions and stressors.

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Availability of data and materials

The dataset supporting the conclusions of this article is available in the European Nucleotide Archive (ENA) repository, accession number PRJEB50358. The code used in this study will be made available on zenodo upon acceptance of the manuscript.

Competing interest

The authors declare that they have no competing interests.

Funding

For AW, this work was performed as part of the ‘BIOINSECTICIDES’ research project (internal project number F42422) at Graz University of Technology. For AA, this work was funded by the European Union's Horizon2020 under ‘Nurturing excellence by means of cross-border and cross-sector mobility’ program for MSCA-IF-2018-Individual Fellowships, grant agreement 844114.

Author Contributions

AA and AT conceptualized the experiments; AA performed the microcosm experiment and sampling; AW prepared amplicon libraries, performed bioinformatics analyses, and wrote the first draft of the manuscript. GB contributed to the interpretation of the results. All authors approved and contributed to the final version of the manuscript.

Acknowledgement

The authors would like to thank Daniela Amhofer (TU Graz), Anaís Carpelan and Laura van Dijk (Stockholm University), for assisting with the laboratory work and providing the aphid population. Expedito Olimi, Wisnu Wicaksono, and Peter Kusstatscher (TU Graz) for their support in bioinformatic analyses.

Abdelfattah A. 2021. Device for germ-free and microbiome controlled growth of plants. Swedish patent database # SE 1950987-6
Abdelfattah A, Wisniewski M, Schena L, Tack AJM. 2021a. Experimental evidence of microbial inheritance in plants and transmission routes from seed to phyllosphere and root. Environmental Microbiology 23: 2199–2214.
Abdelfattah A, Wisniewski M, Schena L, Tack AJM. 2021b. Experimental evidence of microbial inheritance in plants and transmission routes from seed to phyllosphere and root. Environmental Microbiology 23: 2199–2214.
Arnold AE. 2007. Understanding the diversity of foliar endophytic fungi: progress, challenges, and frontiers. Fungal Biology Reviews 21: 51–66.
Bai Y, Müller DB, Srinivas G, Garrido-Oter R, Potthoff E, Rott M, Dombrowski N, Münch PC, Spaepen S, Remus-Emsermann M, et al. 2015. Functional overlap of the Arabidopsis leaf and root microbiota. Nature 528: 364–369.
Baumann P. 2005. Biology of bacteriocyte-associated endosymbionts of plant sap-sucking insects. Annual Review of Microbiology 59: 155–189.
Beckers B, De Beeck MO, Weyens N, Boerjan W, Vangronsveld J. 2017. Structural variability and niche differentiation in the rhizosphere and endosphere bacterial microbiome of field-grown poplar trees. Microbiome 5: 1–17.
Bennett GM, Moran NA. 2015. Heritable symbiosis: The advantages and perils of an evolutionary rabbit hole. Proceedings of the National Academy of Sciences of the United States of America 112: 10169–10176.
Berg G, Grube M, Schloter M, Smalla K. 2014. Unraveling the plant microbiome: Looking back and future perspectives. Frontiers in Microbiology 5: 1–7.
Berg G, Köberl M, Rybakova D, Müller H, Grosch R, Smalla K. 2017. Plant microbial diversity is suggested as the key to future biocontrol and health trends. FEMS Microbiology Ecology 93: 1–9.
Bergna A, Cernava T, Rändler M, Grosch R, Zachow C, Berg G. 2018. Tomato seeds preferably transmit plant beneficial endophytes. Phytobiomes 2:183-193.
Blubaugh CK, Carpenter-Boggs L, Reganold JP, Schaeffer RN, Snyder WE. 2018. Bacteria and competing herbivores weaken top–down and bottom–up aphid suppression. Frontiers in Plant Science 9: 1–10.
Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, Alexander H, Alm EJ, Arumugam M, Asnicar F, et al. 2019. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nature Biotechnology 37: 852–857.
Brinker P, Fontaine MC, Beukeboom LW, Falcao Salles J. 2019. Host, Symbionts, and the Microbiome: The Missing Tripartite Interaction. Trends in Microbiology 27: 480–488.
Brock AK, Berger B, Schreiner M, Ruppel S, Mewis I. 2018. Plant growth-promoting bacteria Kosakonia radicincitans mediate anti-herbivore defense in Arabidopsis thaliana. Planta 248: 1383–1392.
Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. 2016. DADA2: High-resolution sample inference from Illumina amplicon data. Nature Methods 13: 581.
Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Lozupone CA, Turnbaugh PJ, Fierer N, Knight R. 2011. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proceedings of the National Academy of Sciences 108: 4516 LP – 4522.
Chaudhary R, Atamian HS, Shen Z, Briggs SP, Kaloshian I. 2014. GroEL from the endosymbiont Buchnera aphidicola betrays the aphid by triggering plant defense. Proceedings of the National Academy of Sciences of the United States of America 111: 8919–8924.
Chung SH, Rosa C, Scully ED, Peiffer M, Tooker JF, Hoover K, Luthe DS, Felton GW. 2013. Herbivore exploits orally secreted bacteria to suppress plant defenses. Proceedings of the National Academy of Sciences of the United States of America 110: 15728–15733.
Costello M, Fleharty M, Abreu J, Farjoun Y, Ferriera S, Holmes L, Howd T, Mason T, Vicente G, Dasilva M, et al. 2017. Characterization and remediation of sample index swaps by non-redundant dual indexing on massively parallel sequencing platforms. bioRxiv: 1–10.
Dastogeer KMG, Tumpa FH, Sultana A, Akter MA, Chakraborty A. 2020. Plant microbiome–an account of the factors that shape community composition and diversity. Current Plant Biology 23.
Davis NM, Proctor DiM, Holmes SP, Relman DA, Callahan BJ. 2018. Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. Microbiome 6: 1–15.
Dhami MK, Weir BS, Taylor MW, Beggs JR. 2013. Diverse Honeydew-Consuming Fungal Communities Associated with Scale Insects. PLoS ONE 8: 1–12.
Faticov M, Abdelfattah A, Roslin T, Vacher C, Hambäck P, Blanchet FG, Lindahl BD, Tack AJM. 2021. Climate warming dominates over plant genotype in shaping the seasonal trajectory of foliar fungal communities on oak. New Phytologist 231: 1770–1783.
Fort T, Pauvert C, Zanne AE, Ovaskainen O, Caignard T, Barret M, Compant S, Hampe A, Delzon S, Vacher C. 2021. Maternal effects shape the seed mycobiome in Quercus petraea. New Phytologist 230: 1594–1608.
French E, Kaplan I, Enders L. 2021. Foliar Aphid Herbivory Alters the Tomato Rhizosphere Microbiome, but Initial Soil Community Determines the Legacy Effects. Frontiers in Sustainable Food Systems 5: 1–16.
Furch ACU, Van Bel AJE, Will T. 2015. Aphid salivary proteases are capable of degrading sieve-tube proteins. Journal of Experimental Botany 66: 533–539.
Gargallo-Garriga A, Preece C, Sardans J, Oravec M, Urban O, Peñuelas J. 2018. Root exudate metabolomes change under drought and show limited capacity for recovery. Scientific Reports 8: 1-15.
Grady KL, Sorensen JW, Stopnisek N, Guittar J, Shade A. 2019. Assembly and seasonality of core phyllosphere microbiota on perennial biofuel crops. Nature Communications 10: 1–10.
Guo K, Gao P. 2021. microbial: Do 16s Data Analysis and Generate Figures.
Hardoim PR, van Overbeek LS, Berg G, Pirttilä AM, Compant S, Campisano A, Döring M, Sessitsch A. 2015. The Hidden World within Plants: Ecological and Evolutionary Considerations for Defining Functioning of Microbial Endophytes. Microbiology and Molecular Biology Reviews 79: 293–320.
van der Heijden MGA, Hartmann M. 2016. Networking in the Plant Microbiome. PLoS Biology 14: 1–9.
Hol WHG, de Boer W, Termorshuizen AJ, Meyer KM, Schneider JHM, van Dam NM, van Veen JA, van der Putten WH. 2010. Reduction of rare soil microbes modifies plant-herbivore interactions. Ecology Letters 13: 292–301.
Hoysted GA, Bell CA, Lilley CJ, Urwin PE. 2018. Aphid colonization affects potato root exudate composition and the hatching of a soil borne pathogen. Frontiers in Plant Science 9: 1–10.
Kong HG, Kim BK, Song GC, Lee S, Ryu CM. 2016. Aboveground whitefly infestation-mediated reshaping of the root microbiota. Frontiers in Microbiology 7: 1–10.
Laforest-Lapointe I, Messier C, Kembel SW. 2016. Host species identity, site and time drive temperate tree phyllosphere bacterial community structure. Microbiome 4: 1–10.
Levy A, Conway JM, Dangl JL, Woyke T. 2018. Elucidating Bacterial Gene Functions in the Plant Microbiome. Cell Host and Microbe 24: 475–485.
Liu H, Brettell LE, Qiu Z, Singh BK. 2020a. Microbiome-Mediated Stress Resistance in Plants. Trends in Plant Science 25: 733–743.
Liu Q, Li S, Ding W. 2020b. Aphid-induced tobacco resistance against Ralstonia solanacearum is associated with changes in the salicylic acid level and rhizospheric microbial community. European Journal of Plant Pathology 157: 465–483.
Luna E, Van Eck L, Campillo T, Weinroth M, Metcalf J, Perez-Quintero AL, Botha AM, Thannhauser TW, Pappin D, Tisserat NA, et al. 2018. Bacteria associated with Russian wheat aphid (Diuraphis noxia) enhance aphid virulence to wheat. Phytobiomes Journal 2: 151–164.
Lundberg DS, Yourstone S, Mieczkowski P, Jones CD, Dangl JL. 2013. Practical innovations for high-throughput amplicon sequencing. Nature Methods 10: 999.
Malacrinò A, Karley A, Schena L, Bennett A. 2021a. Soil microbial diversity impacts plant microbiota more than herbivory. Phytobiomes Journal: 1–10.
Malacrinò A, Wang M, Caul S, Karley AJ, Bennett AE. 2021b. Herbivory shapes the rhizosphere bacterial microbiota in potato plants. Environmental Microbiology Reports 13: 805-811.
Martin M. 2011. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMPnet.journal 17: 10.
Martinez Arbizu P. 2017. pairwiseAdonis: Pairwise multilevel comparison using adonis.
Massoni J, Bortfeld-Miller M, Widmer A, Vorholt JA. 2021. Capacity of soil bacteria to reach the phyllosphere and convergence of floral communities despite soil microbiota variation. Proceedings of the National Academy of Sciences of the United States of America 118. e2100150118
McMurdie PJ, Holmes S. 2013. Phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PLoS ONE 8. e61217
McQuilken MP, Halmer P, Rhodes DJ. 1998. Application of Microorganisms to Seeds BT - Formulation of Microbial Biopesticides: Beneficial microorganisms, nematodes and seed treatments. In: Burges HD, ed. Dordrecht: Springer Netherlands, 255–285.
Michalzik B, Stadler B. 2005. Importance of canopy herbivores to dissolved and particulate organic matter fluxes to the forest floor. Geoderma 127: 227–236.
Mittelstrass J, Sperone FG, Horton MW. 2021. Using transects to disentangle the environmental drivers of plant-microbiome assembly. Plant Cell and Environment 44: 3515–3525.
Mühlenberg E, Stadler B. 2005. Effects of altitude on aphid-mediated processes in the canopy of Norway spruce. Agricultural and Forest Entomology 7: 133–143.
Nilsson RH, Larsson KH, Taylor AFS, Bengtsson-Palme J, Jeppesen TS, Schigel D, Kennedy P, Picard K, Glöckner FO, Tedersoo L, et al. 2019. The UNITE database for molecular identification of fungi: Handling dark taxa and parallel taxonomic classifications. Nucleic Acids Research 47: D259–D264.
O’Brien FJM, Dumont MG, Webb JS, Poppy GM. 2018. Rhizosphere bacterial communities differ according to fertilizer regimes and cabbage (Brassica oleracea var. capitata l.) harvest time, but not aphid herbivory. Frontiers in Microbiology 9: 1–18.
Pineda A, Zheng SJ, van Loon JJA, Dicke M. 2012. Rhizobacteria modify plant-aphid interactions: A case of induced systemic susceptibility. Plant Biology 14: 83–90.
Potthast K, Tischer A, Herrmann M, Weinhold A, Küsel K, van Dam NM, Michalzik B. 2022. Woolly beech aphid infestation reduces soil organic carbon availability and alters phyllosphere and rhizosphere bacterial microbiomes. Plant and Soil 473: 639–657.
Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO. 2013. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Research 41: 590–596.
R Core Team. 2018. R: A language and environment for statistical computing.
Reingold V, Kottakota C, Birnbaum N, Goldenberg M, Lebedev G, Ghanim M, Ment D. 2021. Intraspecies variation of Metarhizium brunneum against the green peach aphid, Myzus persicae, provides insight into the complexity of disease progression. Pest Management Science 77: 2557–2567.
Rognes T, Flouri T, Nichols B, Quince C, Mahé F. 2016. VSEARCH: A versatile open source tool for metagenomics. PeerJ 10: 1–22.
Rolfe SA, Griffiths J, Ton J. 2019. Crying out for help with root exudates: adaptive mechanisms by which stressed plants assemble health-promoting soil microbiomes. Current Opinion in Microbiology 49: 73–82.
Ros-Freixedes R, Battagin M, Johnsson M, Gorjanc G, Mileham AJ, Rounsley SD, Hickey JM. 2018. Impact of index hopping and bias towards the reference allele on accuracy of genotype calls from low-coverage sequencing. Genetics Selection Evolution 50: 1–14.
Schwartzberg EG, Tumlinson JH. 2014. Aphid honeydew alters plant defence responses. Functional Ecology 28: 386–394.
Seeger J, Filser J. 2008. Bottom-up down from the top: Honeydew as a carbon source for soil organisms. European Journal of Soil Biology 44: 483–490.
Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, Huttenhower C. 2011. Metagenomic biomarker discovery and explanation. Genome Biology 12:R60.
Stadler B, Müller T. 1996. Aphid Honeydew and Its Effect on the Phyllosphere Microflora of Picea abies (L.) Karst. Oecologia 108: 771–776.
Stadler B, Müller T. 2000. Effects of aphids and moth caterpillars on epiphytic microorganisms in canopies of forest trees. Canadian Journal of Forest Research 4: 631–638.
Thapa S, Ranjan K, Ramakrishnan B, Velmourougane K, Prasanna R. 2018. Influence of fertilizers and rice cultivation methods on the abundance and diversity of phyllosphere microbiome. Journal of Basic Microbiology 58: 172–186.
Tkacz A, Bestion E, Bo Z, Hortala M, Poole PS. 2020. Influence of plant fraction, soil, and plant species on microbiota: A multikingdom comparison. mBio 11: e02785-19.
Trivedi P, Leach JE, Tringe SG, Sa T, Singh BK. 2020. Plant–microbiome interactions: from community assembly to plant health. Nature Reviews Microbiology 18: 607–621.
Vandenkoornhuyse P, Quaiser A, Duhamel M, Le Van A, Dufresne A. 2015. The importance of the microbiome of the plant holobiont. New Phytologist 206: 1196–1206.
De Vos M, Jander G. 2009. Myzus persicae (green peach aphid) salivary components induce defence responses in Arabidopsis thaliana. Plant, Cell and Environment 32: 1548–1560.
Wagner MR, Lundberg DS, Del Rio TG, Tringe SG, Dangl JL, Mitchell-Olds T. 2016. Host genotype and age shape the leaf and root microbiomes of a wild perennial plant. Nature Communications 7: 12151.
White TJ, Bruns T, Lee S, Taylor JW. 1990. Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. In: Innis MA, Gelfand DH, Sninsky JJ, White TJ, eds. PCR Protocols: A Guide to Methods and Applications. San Diego: Academic Press, 315–322.
Whitfield AE, Falk BW, Rotenberg D. 2015. Insect vector-mediated transmission of plant viruses. Virology 479–480: 278–289.
Wolfgang A, Zachow C, Müller H, Grand A, Temme N, Tilcher R, Berg G. 2020. Understanding the Impact of Cultivar, Seed Origin, and Substrate on Bacterial Diversity of the Sugar Beet Rhizosphere and Suppression of Soil-Borne Pathogens. Frontiers in Plant Science 11: 1–15.
Xiong C, Zhu YG, Wang JT, Singh B, Han LL, Shen JP, Li PP, Wang GB, Wu CF, Ge AH, et al. 2021. Host selection shapes crop microbiome assembly and network complexity. New Phytologist 229: 1091–1104.
Yang JW, Yi HS, Kim H, Lee B, Lee S, Ghim SY, Ryu CM. 2011. Whitefly infestation of pepper plants elicits defence responses against bacterial pathogens in leaves and roots and changes the below-ground microflora. Journal of Ecology 99: 46–56.
Zhu F, Poelman EH, Dicke M. 2014. Insect herbivore-associated organisms affect plant responses to herbivory. New Phytologist 204: 315–321.
Zytynska SE, Tighiouart K, Frago E. 2021. Benefits and costs of hosting facultative symbionts in plant-sucking insects: A meta-analysis. Molecular Ecology 30: 2483–2494.
Zytynska SE, Weisser WW. 2016. The natural occurrence of secondary bacterial symbionts in aphids. Ecological Entomology 41: 13–26.

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Reciprocal influence of soil, phyllosphere and aphid microbiomes

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The effect of aphid herbivory on soil microbiota

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