Skip to main content

The Arabidopsis holobiont: a (re)source of insights to understand the amazing world of plant–microbe interactions

Abstract

As holobiont, a plant is intrinsically connected to its microbiomes. However, some characteristics of these microbiomes, such as their taxonomic composition, biological and evolutionary role, and especially the drivers that shape them, are not entirely elucidated. Reports on the microbiota of Arabidopsis thaliana first appeared more than ten years ago. However, there is still a lack of a comprehensive understanding of the vast amount of information that has been generated using this holobiont. The main goal of this review was to perform an in-depth, exhaustive, and systematic analysis of the literature regarding the Arabidopsis–microbiome interaction. A core microbiota was identified as composed of a few bacterial and non-bacterial taxa. The soil (and, to a lesser degree, air) were detected as primary microorganism sources. From the plant perspective, the species, ecotype, circadian cycle, developmental stage, environmental responses, and the exudation of metabolites were crucial factors shaping the plant–microbe interaction. From the microbial perspective, the microbe-microbe interactions, the type of microorganisms belonging to the microbiota (i.e., beneficial or detrimental), and the microbial metabolic responses were also key drivers. The underlying mechanisms are just beginning to be unveiled, but relevant future research needs were identified. Thus, this review provides valuable information and novel analyses that will shed light to deepen our understanding of this plant holobiont and its interaction with the environment.

Introduction

The realization that all animal and plant species harbor complex associated microbial communities (the microbiota) in their surfaces as well as and inner parts is relatively recent in Biology [17]. Furthermore, the holistic view of the holobiont represented by the conjunction of a macro-organism and its microbiome (the associated microorganisms and their collective genomes) is even newer [26]. For decades, our understanding of these inter-kingdom interactions increased thanks to studies of plant or animal models interacting with single microbial species, such as pathogens and, to a lesser degree, beneficial microorganisms. However, the characteristics of the microbiome in experimental model species regarding their taxonomic composition, biological role, and especially the drivers that shape those microbiomes are far from being completely understood. Plants are holobiont harboring microorganisms in their internal and external tissues [43, 65, 72, 192] (Fig. 1A). Therefore, plant fitness, environmental responses, adaptation, and evolution should be addressed, considering plants as complex dynamic entities controlled by the hologenome: the host genome plus all the genomes of the microbiome.

Fig. 1
figure 1

Features and connections in the Arabidopsis microbiota. A The distribution of the main microbial taxa among different plant compartments is represented by symbols explained in the boxes at the bottom of the figure; light blue for bacterial phyla and light orange for fungal phyla, while relative abundances of the major phyla are represented next to each compartment [20, 22, 23, 30, 60, 85, 191]. B Connections among the microbiota of compartments and their different sources (inputs) of inoculation. The arrow width represents the relative contributions of the sources based on the percentage of each source input with respect to the total input. Dashed lines represent minor influences. Roots comprise endorhizosphere plus rhizoplane. Leaves comprise the endophyllosphere plus the epiphyllosphere. Names of the taxa are Pseudomonadota, Actinomycetota, Bacillota, Bacteroidota, Acidobacteriota, Chloroflexota, Cyanobacteriota, Planctomycetota, Basidiomycota, Ascomycota, Zygomycota, and Mucoromycota, formerly Proteobacteria, Actinobacteria, Firmicutes, Bacteroidetes, Acidobacteria, Chloroflexi, Cyanobacteria, Planctomycetes, Basidiomycetes, Ascomycetes, Zygomycetes, and Mucoromycetes, respectively

After rice (Oryza sativa), Arabidopsis thaliana is the second most studied plant species and has proven to be a valuable model in plant sciences [37, 144, 185], specifically to get insights into plant development and responses to the environment [92, 144]. As with other well-studied biological models, a few studies targeting A. thaliana interactions with bacterial populations were available at the beginning of this century, mainly using culture-dependent molecular approaches (e.g., [63, 91]. Since then, a great deal of information has been obtained with culture-independent molecular techniques and, more recently, with omics approaches. Massive sequencing allows statistically significant comparisons among plant compartments using Operational Taxonomic Units (OTUs) or a more accurate manually supervised clustering of Operational Phylogenetic Units [135]. More than 170 original reports have covered several aspects of this holobiont, such as the composition and structure of the microbial communities; comparisons between different compartments of the plant; abiotic and biotic factors controlling the shape of these communities, and, more recently, they have started the incipient elucidation of the underlying molecular mechanisms (Fig. 1A-B; Fig. 2A-B). Nevertheless, there is still a lack of a comprehensive understanding of the large amount of information generated using this holobiont (Fig. 2C). In this article, a thorough and systematic revision of the existing literature was performed, extracting common patterns, identifying some methodological or operative aspects, and proposing future research needs. Some of the aspects that are discussed are the composition of the core microbiome and its variation according to changes in the environment or plant compartments and traits; how the endophyte core community in Arabidopsis has similarities with those found in other plant species (confirming the valuable role of this species as a model for plant holobiont); the sometimes-controversial issue about the presence of microorganisms in plant seeds; and the multiple layers affecting microbe-microbe and plant-microbiota interactions (Fig. 2). This comprehensive and systematic analysis of the bulk of information already available in the well-studied Arabidopsis model will highlight critical aspects of plant-microbiome interactions, providing valuable guidelines for studying other plant hosts and their microbial communities.

Fig. 2
figure 2

The Arabidopsis-microbiota interaction as a complex system: Multiple drivers that shape the outcomes of this plant–microbe interaction. A Drivers from the macro-organism plant perspective (from top to bottom): circadian and seasonal effects; ecotype; soil; plant developmental stage; biomolecules released by plants (i.e., root exudates); responses to the environment (i.e., biotic/abiotic stress responses) B Drivers from the microbial perspective: microbe-microbe interactions; microbial responses to biotic and abiotic stresses; biomolecules released by microorganisms and type of microorganisms (i.e., plant growth-promoting/protecting bacteria). C Future research needs

Among these outcomes, the concept of core microbiota has been stablished for Arabidopsis, showing that it harbors community members that are essentially constant [30, 115, 169], while others are variably affected by the soil type, ecotype, developmental stage [115], season [3, 15, 30], generation [183], and other factors playing minor contributions (Fig. 2A). The root endophyte core community in Arabidopsis has the same most abundant phyla reported for many plant endophyte communities [70], confirming the valuable role of this species as a model for plant holobiont.

In addition, several reports provide clear evidence that the soil (both abiotic and biotic components) is the main factor explaining the root microbiota composition in Arabidopsis, and other plants [30, 47, 65, 115, 169, 183, 184, 194].

Nevertheless, there still needs to be a comprehensive understanding of the large amount of information generated using this holobiont (Fig. 2C). For example, the microbiome-root-shoot axis has been conceptualized and addressed (e.g., [80, 179]. The ways in which these compartments are connected are not sufficiently studied. One way is the external connection between microbes associated with the rhizosphere that are transferred (by proximity, early development contact, wind moving, insects, among others) to the surface of the leaves (Fig. 1B). The reverse way, always external, is through raindrops falling off from leaves to the rhizosphere and then to the root compartment (Fig. 1B). An alternative mechanism is through inner connections between the endorhizospheric- and endophyllospheric compartments.

In this article, a thorough and systematic revision of the existing literature was performed, extracting common patterns, identifying some methodological or operative aspects, and proposing future research needs. This comprehensive and systematic analysis of the bulk of information already available in the well-studied Arabidopsis model will highlight critical aspects of plant-microbiome interactions, providing valuable guidelines for studying other plant hosts and their microbial communities.

Literature review methodology

PubMed and Google Scholar were browsed for eligible published articles up to December 2022, using the keywords: Arabidopsis, A. thaliana, microbiota, and microbiome. A few BioRxiv preprint files were included, as also milestone reviews on A. thaliana holobiont [31, 59, 62, 72, 136, 166]. Overall, nearly 220 research articles were analyzed to prepare the review and construct Additional file 1: Table SI. For taxonomy, the recently approved rules on phyla valid names are used [141]. Metabolic, functional, and ecological features linked to the plant biology of families or genera mentioned in the text are indicated in Table 1.

Table 1 Main metabolic, functional, and ecological features reported for microbial families and genera found associated with the Arabidopsis holobiont

Microbial taxonomy in the different plant organs and compartments

Root microbiota

Bacterial communities in the plant roots

Concerning root microbiota, Bulgarelli et al. [30] and Lundberg et al. [115] contributed by carefully defining the following root compartments: the endorhizosphere (the microbial. community found inside root tissues); the root-associated (the microbial community in close contact with the outer part of the roots), and the rhizosphere (the microbial community found in the proximity to roots), allowing finer distinctions among root microbial communities, and clearly distinguished them from bulk soil (not influenced by plants). However, procedures to obtain samples from these compartments are not strictly comparable in these and other studies (see subSect. "Experimental design, methods, and data analysis."), potentially explaining differences in microbial compositions of compartments.

Bulgarelli et al. [30] compared the bacterial communities in close contact with the roots of Arabidopsis. Using a slightly different operational definition of the plant-associated microbial community (endorhizospheric compartment), Lundberg et al. [115] found the same trend for plant or soil-associated communities, i.e., plants recruit a different subset of the surrounding soil microbiota. The main conclusion of these landmark studies is that A. thaliana root microbiota is composed of a core microbiome (for an in-depth analysis of this concept, see [172] of relatively few bacterial groups, mostly belonging to Actinomycetota, and the α, β, and γ Pseudomonadota classes (Fig. 1A), independently of the soil where the plants were collected from, the ecotype, or other factors. Bacillota, Bacteroidota, and a few other phyla were also found in these two and other reports (Table 2). Phylum relative abundances were different among these reports (Table 2), which is also observed at the family level in other studies (e.g., [101]. Just as representative cases (Table 2): α Pseudomonadota families Caulobacteraceae and Rhizobiaceae appear ranked in the top 3 of relative abundances, whereas Sphingobacteraceae shows different relative abundance positions; in β Pseudomonadota families, Comamonadaceae and Oxalobacteraceae are commonly found abundant, while Burkholderiaceae exhibits a variable ranking. Despite the expected differences in the bacterial community composition due to biological factors that may explain differences between these two studies (and several others), methodological factors also contribute to explaining such differences (sub-Sect. "Experimental design, methods, and data analysis.").

Table 2 Top relative abundances of bacterial endophyte's main phyla (A), and Pseudomonadota classes (B), determined by massive amplicon sequencing, reported in selected publications

Non-bacterial communities in the plant roots

Bacterial communities are far more abundant (10–1000 times) than archaeal, fungal, and microeukaryotic communities in plant roots [50, 180]. However, these non-bacterial communities [72] play relevant roles in Arabidopsis performance (Fig. 1A). Bressan et al. [28] provided early evidence for the presence of archaeal species in this plant, and a low proportion of this domain was also observed in later studies [30, 115]. Furthermore, members of the Thaumarchaeota phylum have been described as relatively abundant, surpassing bacterial phyla such as Nitrospirota or Bacillota [184]. This becomes more relevant, considering that the PCR primer sets used in most studies are not primarily defined to detect archaeal species.

It should be kept in mind that Arabidopsis, like other Brassicaceae, does not harbor arbuscular mycorrhiza fungi (AMF) as most plant species, which means that its fungal community should have unique features. Members of the fungal phyla Basidiomycota, Ascomycota, and Mucoromycota or Chytriomycota can be found in significant numbers as part of the Arabidopsis root microbiota, but with variable predominance, based on relative abundances [180, 184, 191]. Urbina et al. [191] found Archaeorhizomycetes enriched in the rhizosphere and Leotiomycetes in the endosphere, both Ascomycota groups. Later, Fabiańska et al. [58] reported that eleven fungal orders were enriched in the rhizosphere, whereas four others were increased in the endosphere. Another study established that Hypocreales, Pleorosporales, and Agaricales were more abundant in roots compared to soils [60]. Leotiomycetes and Sordariomycetes have also been reported as abundant in seeds [50]. Interestingly, characteristic Glomeromycota mycorrhizal members were found in soils but not enriched in the plant compartments [58], which is consistent with the lack of mycorrhizal symbiosis in Arabidopsis. The basis for fungal endophytism in Arabidopsis has recently started to build up, with the finding that fungal functions like the secretion of cell wall-degrading enzymes and effector proteins are part of the repertoire of endophytic root mycobiota members [131].

A few recent studies provide helpful information regarding the presence of eukaryotic microorganisms other than fungi [72]. Using PCR primers targeting Oomycota and Cercozoa, Sapp et al. [165] found that Oomycota were not significantly different in soils compared to roots but discovered many diverse groups of Cercozoa, and some of them were preferentially found in roots. Durán et al. [50] described that Pythium, an Oomycota genus, was abundant in roots. Tkacz et al. [184] reported a scarcely described group, the microeukaryotes, finding that several metazoans are part of the root microbiota of the Arabidopsis holobiont. To help further studies with protists, a collection of nearly 80 Cercozoa isolates have been recently obtained from A. thaliana and is now available for future research for gnotobiotic studies [49], including the possibility of preparing Synthetic Communities (SynComs), i.e., simpler communities that mimic entire, complex communities ([109, 125, 199]). Concerning non-microbial groups closely interacting with microbial ones, Sikder et al. [174] have reported a vital nematode community in roots of Arabidopsis grown in soil, finding OTUs belonging to 75 species, from 32 families.

Phyllosphere (leaf) microbiota

The microbiota of different compartments has been analyzed in the phyllosphere. For instance, the surface of the leaves, including epiphytes in the adaxial (upper surface) and abaxial (lower surface)] and the inner tissues (endophyllosphere). On the other hand, as Arabidopsis adult plants are small, shoot tissues are comparatively less relevant than leaves, so with a few exceptions (e.g., [60], the studies usually do no track shoot compartments (except for some targeting interactions among plant compartments, see Sect. "Microbial connections among plant compartments and their surroundings"), or they include them along with the leaves.

Bacterial communities in the phyllosphere

Phyllosphere microbiota has received less attention than root microbiota [31, 198]. Kniskern et al. [91] reported the presence of more than twenty different taxa in the culturable bacteria of endo- and the epiphyllosphere, including some well-known phytopathogens, presumably in an inactive state. Using Denaturing Gradient Gel Electrophoresis (DGGE) and clonal library approaches, a phylum bacterial composition, like the one reported for roots, was reported in the epiphyllosphere, including Actinomycetota, Pseudomonadota, and Bacteroidota [45]. Among Pseudomonadota, Sphingomonas were significantly abundant, whereas other families were found in detectable levels: Rhizobiaceae, Oxalobacteraceae, Comamonadaceae, and Pseudomonadaceae [45, 78]. Delmotte et al. [45] also applied a culture-independent metaproteomic approach, which showed the presence of a significant active population of other genera, mainly Methylobacterium -which use methanol coming from pectins-, along with several differences in relative abundances of different taxa. The relatively high abundance of the genus Methylobacterium in the epiphyllosphere of Arabidopsis was also reported using a ribosomal intergenic spacer analysis (RISA) and cultivation, defining M. extorquens as a key species [89, 90]. Key, or keystones, or hub species, play a fundamental role in the structure and functioning of the microbiota community [13, 72]. Interestingly, a relatively diverse bacterial community of anoxygenic photoautotrophs was detected in the phyllosphere, which might use sulfide provided by plants as a reductant [6]. This is consistent with the reported release of volatile sulfide compounds, mainly hydrogen sulfide, as a mediator of plant immunity and defense against microbial colonization in leaves (Vojtovic et al. 2020), thus providing a metabolic niche for anoxygenic photoautotrophy.

The leaf core community [23, 156], possesses as the main abundant phyla Pseudomonadota, followed by Actinomycetota, Bacteroidota, and then Bacillota (Fig. 1A, Table 2, [78]. As in roots, Arabidopsis leaf endophyte core community comprises the same significant phyla reported for most plant endophyte communities [70]. The main phyla found in a total phyllosphere bacterial community show a clear predominance of Pseudomonadota (> 90%) [10, 40]. Using fluorescence targeting, Remus-Enserman et al. [157]) found a heterogeneous distribution, with a significantly higher surface covered by bacteria on the abaxial side than on the adaxial one and concentrated in the borders of the stomata. Interestingly, essential levels of autofluorescence were found (Remus-Enserman et al., [157]), which may be explained by the presence of the abovementioned anoxygenic phototrophs [6]. An exometabolomic approach allowed finding a heterogeneous distribution of different organic compounds on the leaf surface which might explain the unequal distribution of phyllosphere bacterial community members [162]. Such distribution is probably due to differential amounts of sugars, nucleotides, and other molecules in the leaf source. Compared to the leaf surface, two to three orders of magnitude lower bacterial abundances (but with higher diversity) have been described in the endophyllosphere [40, 146]. These differences are explained mainly by the Pseudomonadota groups such as Pseudomonas, Burkholderia, and the Actinomycetota group Kineosporia [23].

Other microbial communities in the phyllosphere

As with roots, non-bacterial phyllosphere communities have received less attention [198]. Fungal members of Ascomycota and Basidiomycota are predominant in leaves (Fig. 1A, [20, 78]. The microeukaryotic community of the Arabidopsis phyllosphere has also been addressed, compared with other closely related plant species, but not much detail was provided, with the presence of some bacterivores and potential pathogens [148, 184]. No reports on archaeal members in the phyllosphere community have been published so far, except in Regalado et al. [155], where a tiny proportion of archaeal sequences was found.

Seed and floral microbiota

Using the bacterial markers 16S rRNA and gyrB, and a fungal marker, Barret et al. [14] compared the seed microbiota among 20 Brassicaceae, including A. thaliana. Although bacterial and fungal richness exhibited significant variability, a common core was observed among all tested plant species, with Pseudomonas, Pantoea, Xanthomonas, and Sphingomonas as the main bacterial groups, and Mycosphaerellaceae, Cladosporium, and Alternaria among main fungal groups [14]. A comparison of the internal seed tissues and spermosphere microbiota (see a review of [137] of 17 angiosperm plant species, including Arabidopsis [85, 86], showed a predominance of Pseudomonadota and Ascomycota, with a significant proportion of common (present in more than 60% of plants) bacterial and fungal OTUs (Fig. 1A), with a few core (present in 100% of plants) bacteria (Pantoea, Enterobacter, Pseudomonas, Bacillus, among others), and one fungus, Fusarium.

There is only one report of the Arabidopsis floral microbiota [22], comparing Col-0 and two mutants of CYP706A3 (P450) with decreased volatile terpene levels. They found about 350 OTUs belonging primarily to Pseudomonadota and Actinomycetota, with a few members of Bacteroidota and Bacillota (Fig. 1A) [22]. About 45 members changed their abundance in the cytochrome P450 mutant lines, suggesting a role of terpene volatiles in floral microbiota structure, specifically affecting taxa such as Pseudomonas.

Microbial connections among plant compartments and their surroundings

One of the main factors influencing plant microbial communities is the physical connection, for example, between the surrounding soil and the plant roots, or the air and the leaves, and between compartments of the plant (rhizoplane and inner root parts, endorhizosphere and phyllosphere, etc.). These connections are responsible for the source (inoculum) of microbes that can reach and colonize a particular compartment defining its taxonomic composition and, therefore, playing a significant role in available microbial community functions and their interaction with the plant parts (see a summary on Fig. 1B).

The soil as a microbial source in plants

Plants select their (core) microbiota (resident/transient) recruiting surrounding soil microbes, and, therefore, some microbial taxa are enriched in roots, whereas others are more abundant in the surrounding soil. Thus, the soil (both abiotic and biotic components) is the main factor explaining the root microbiota composition in Arabidopsis, and other plants [30, 47, 65, 115, 169, 183, 184, 194]. Typical phyla that are enriched in roots are Pseudomonadota and Actinomycetota, whereas Acidobacteriota, Gemmatimonadota, and Verrucomicrobiota are enriched in soils (Fig. 1A), with Bacteroidota, and Bacillota depending on the lower rank taxa that are analyzed [16, 30, 34, 36, 47, 60, 68, 101, 115, 186].

Concerning fungal and microeukaryotic members [191], and archaeal communities [180], the differences between surrounding soil and roots are less pronounced than those observed for bacteria. This could be explained because of a higher influence of the soil type and location on the eukaryotic communities compared to the plant factor [50, 159, 165, 184, 186]. Nevertheless, the effect of plants on fungal composition is reported to be significant [58], with increases in fungal diversity in roots [180] and endosphere [191]. Hypocreales, Pleoroporales, and Agaricales are enriched in roots, whereas Filobasidiales and Mortierellales are more abundant in soils than in roots [60].

Some studies differentiate the microbial community of the rhizosphere from the rhizoplane and the endorhizosphere compartments. Depending on the treatment of samples, the endorhizosphere community may be combined with or separated from the rhizoplane community (e.g., [30, 47, 50, 115, 169]. Several reports indicate that the endorhizosphere microbial communities are significantly different from those of the rhizosphere and, of course, those of bulk soils [101, 115, 159, 169]. Endorhizospheric communities are the less diverse, although the prominent members correspond to enriched taxa found both in the rhizosphere and the soil compartments [30, 50, 115]. Thiergart et al. [186] studied the root microbiota from Arabidopsis populations grown in 17 locations in Europe (a latitudinal transect) for three years. They found that bacterial communities were more affected by soil (edaphic factors) than the location (climatic factors), whereas the contrary was observed for fungal and oomycotal communities. The main drivers for endorhizosphere communities (quantity and availability) were reserve and available P, and manganese for bacteria and fungi, respectively [186]. In summary, the surrounding bulk soil is the rhizosphere's primary source of bacterial microbiota. In turn, this compartment is the source for the inner parts of the plant (Fig. 1B, [31].

The air as a microbial source in plants

To address the effect of the “"air” factor (Fig. 1B), Maignien et al. [124] conducted carefully controlled tests under greenhouse conditions. They found that the phyllosphere composition was defined by early succession events driven by a combination of a plant selective (filtering) process that recruits specific taxa from the air present in low abundances, such as Variovorax, Rhodococcus, Methylobacterium, with stochastic effects mainly reflected in the variability of abundances of these taxa, related to the position of plant individuals in the greenhouse.

Microbial connections among plant compartments

Using a SynCom approach, Bai et al. [10] reported the effect of spray inoculation of SynComs from leaves, roots, and soil, in leaves and in soil planted or not with Arabidopsis. They reported that the established phyllosphere community resulted differently when the leaves SynCom was inoculated in the leaves or in the soil, the latter containing not only soil sources but also air and dust. When plants were exposed to the three SynComs, the root compartment was colonized by the root and soil SynComs members, indicating that leaf isolates were less adapted to the root environment. Furthermore, Hou et al. [79, 80], nicely demonstrated a microbiota-roots-shoots bidirectional connection in plant response to suboptimal light conditions. Part of these effects were provoked by ectopic colonization of leaves from root-inoculated bacterial commensals [79].

The contribution of the seed microbiota (inner and external tissues) to other compartments was studied by growing 17 plant species, including Arabidopsis, under sterile conditions and comparing them with those grown on natural soil [85, 86]. They reported significant input of seed microorganisms to root and shoot microbiota in most plants, including Arabidopsis, and to a lower degree in the rhizosphere microbiota (Fig. 1B) [85]. This provides strong evidence for vertical transmission controlling the microbiota of seedlings.

One of the most unexplored connections is that of soil to flowers. Massoni et al. [126] nicely compared the phyllosphere and floral microbiota in plants exposed only to soil microorganisms under closed lab conditions or under open-air garden conditions. They showed that about 25% of the bacterial taxa found in the floral microbiota originated from soil microorganisms and therefore were internally transported (Fig. 1B), irrespective of the growth conditions. These bacteria represented more than 75% of the relative abundances, and 24 out of 28 bacteria that marked floral microbiota belonged to Burkholderiaceae. It is worth mentioning that in most cases, this family is found at low, and more commonly, very low levels in the roots and phyllosphere, which reflects the strong selection followed by the plant, making this finding even more remarkable. A member of this family, Paraburkholderia phytofirmans PsJN, has been proposed as a source of vertical transmission to seeds when applied to flowers of different plants [134], and is able to affect floral transition in Arabidopsis [151].

Methodological issues in plant microbiota studies

Germ-free studies

Germ-free plant models represent abnormal conditions [145]. Currently, the presence of seed microbiota in plants is undoubted [173]. An important part of publications on Arabidopsis microbiota indicates germ-free conditions lacking a proper experimental confirmation. Sterile seeds could be explained by producing seeds for many generations under laboratory conditions with low microbial loads (agar, artificial soil mixtures, etc.). Thus, it is perfectly conceivable, but not systematically addressed yet, that A. thaliana seed batches (and therefore, the derived plantlets and adult individuals) would harbor different (both in composition and structure) microbial communities, depending on the time and conditions of maintenance in the lab. Truyens et al. [190] clearly demonstrated significant losses in the richness and abundance of the bacterial community after several generations of A. thaliana seeds grown in bacteria-poor substrates. Therefore, part of the knowledge of the biology of this plant model is not correctly addressed if this natural microbial source is not considered.

Experimental design, methods, and data analysis

A large variety of experimental choices is observed regarding plant age/development, ecotypes (accessions), sampling procedures (including specific plant microzones), targeted 16S rRNA sequence sites, PCR primer sequences (Table 3), PCR conditions, and DNA sequence amplification technologies. Thirteen different primer pair sequence combinations targeting 16S rRNA have been used, although those targeting V3-V4 (several combinations of), V4, and V5-V7 sequences, represent 23, 20, and 34% of reports, respectively (Table 3). In a few cases, a couple of PCR primer sequences were compared, and significant differences were found (e.g., [115, 186]). For instance, the primer pair targeting the V5-V7 region showed less bias than the primer pair amplifying the V3-V4 sequence [186]. In addition, there are differences in DNA sequence data analysis, data bioinformatics pipelines, statistical packages, and alignment and taxonomical databases. For instance, bioinformatic removal of non-target sequences is not always declared or detailed. Although OTUs are used in more than 85% of reports, amplicon/amplified/actual sequence variants have been increasingly utilized in the last 5-years publications. Statistical procedures such as normalization or rarefaction are dissimilarly stated or detailed. All these differences, some of them noted in previous publications (e.g., [169]) should be considered to compare reports. Proposals and guidelines to improve and correct biases and misinterpretations in sequence data analysis have been published, e.g., Sczyrba et al. [171], and Lucaciu et al. [113].

Table 3 rRNA sequence variations in next generation sequencing data acquisition to study Arabidopsis microbiota

This variety of choices may explain rather gross differences in the relative abundance of higher-rank taxa groups (Table 1, [10, 30, 54, 111, 115, 170, 177, 178, 180, 204, 205], and more evidently, in lower rank taxa groups, and less abundant taxa, e.g., the presence of archaeal taxa [184]. In a few cases, inconsistencies were detected and even corrected, such as the presence of an unexpected abundance of Chloroflexota [30], in other cases, PCR bias was previously known, and caution analyzing results was applied [148, 165, 184], or an internal validation using more than one approach was performed [47, 101, 115]). The hidden effects of experimental and data analysis variability may lead to wrong conclusions, and the need to systematize protocols and bioinformatic and statistics approaches should be addressed by the Arabidopsis research community.

In this context, most reports use 16S rRNA as a molecular marker for bacteria. Few exceptions use gyrB, targeting the β subunit of the bacterial gyrase [14, 15], which allows the identification of the sequences to the species level and does not have a variation of copy number per genome. Although Bartoli et al. [15] also reported Pseudomonadota being the most abundant phylum in the main compartments, the estimated abundance (> 80%) exceeded by far that reported using the 16S rRNA marker. The use of both gyrB, and 16S rRNA, allowed to detect important changes in community composition and relative abundances associated with the developmental stages of plants [14]. Use of PhyloChip also indicated that Pseudomonadota was the predominant phylum in A. thaliana rhizosphere, exceeding by two the relative abundance of Bacillota and Bacteroidota, and by ten those of Cyanobacteriota, Actinomycetota, and Verrucomicrobiota [18], a pattern quite different of that reported using Next Generation Sequences approaches. On the other hand, a comparison of two plant culture systems (pots and rhizoboxes) added another layer of fluctuations as several growth parameters of Arabidopsis plants differed significatively [130]. In this context, Kremer et al. [95] have proposed a plant growth system/protocol for microbiota research.

Regalado et al. [155] compared rRNA gene amplicon analyses with metagenome shotgun sequencing to study Arabidopsis leaf microbiota. Although with the shotgun strategy, they found a similar pattern as reported in other publications, they determined different interactions between the ten main family taxa (positive turned negative or neutral) when both methodologies were compared. The discrepancies are produced because microbial abundances can be related to plant DNA abundances in the shotgun procedure, whereas amplicon analyses are usually based on microbial relative abundances. Microbial absolute abundances should be based on plant material determinations (e.g., [51, 202]. Although primarily designed to avoid/minimize the amplification of Arabidopsis nontarget DNA [2], blocking oligos can also be used to estimate bacterial loads and determine absolute abundances [128]. Blocking oligos has proved to be effective in avoiding the amplification of non-target DNA from plastids, and microeukaryotes, improving the bacterial sequence depth [128]. An improved approach to both better quantification of microbial loads and description of community compositions has been recently reported [116].

Arabidopsis features that shape its microbial communities

The plant holobiont sustains reciprocal regulations between microbes and the plant [192]. This section focuses on the plant as a selective recruiter of microbiota to enhance plant fitness under a suite of environmental conditions (Fig. 2A).

The role of the plant ecotype modulating the plant microbiota

In terms of the ecotype, most of the studies used Col-0 (~ 65%), a lower proportion (~ 25%), more than 15 different accessions, or wild populations (~ 15%), and a few did not mention ecotype. Concerning ecotype effects, early work using Terminal Restriction Fragment Length Polymorphism, RISA, DGGE, and high-performance liquid chromatography to track plant root exudates (PRE) composition differences evidenced that bacterial communities differed among ecotypes [132, 133]; dissimilarities related to the distinct PRE compositions of each ecotype. Then, ecotype effects on a small subset of unique OTUs were reported [30, 115]. Later, Horton et al. [78] tested 196 worldwide accessions and used Genome-Wide Associations Studies; they found that richness was affected by host genetic variation and was associated with loci involved in virus responses, trichome branching, and morphogenesis. Other comparisons of microbial community structures across accessions revealed the main keystone role of Comamonadaceae in bacterial communities and Articulospora in fungal communities [13]. Network analysis of the data from different accession communities showed more positive than negative interactions, with fungal members being relevant in shaping leaves and roots communities [20]. A well-defined effect of nine different accessions has also been demonstrated for SynComs [24], whereas other Arabidopsis accessions impact Pseudomonas fluorescens populations depending on each specific ecotype [68]. Differences among Col-0, Ws-O, and Ksk-1 ecotypes were found for bacterial, fungal, and oomycetal microbiota components [2]. Cold tolerance Arabidopsis accessions also showed changes in their microbiota composition [57]. In addition to host genotype effects on the Arabidopsis microbiota, ploidy levels, which vary in wild and managed populations, also affected microbial communities, as recently reported [129, 149].

Plant circadian cycle effects on the microbiota

Staley et al. [178] demonstrated changes in the bacterial community (at several taxonomic levels) depending on the phase of the day. Hubbard et al. [82] confirmed the role of the circadian cycle in the root bacterial communities, comparing the Ws ecotype with two circadian cycle mutants (short, 20 h and large, 28 h). In a more detailed analysis, Lu et al. [112] studied transcriptomic and metabolomic changes in Col-0 and two other acyclic mutants, finding changes in plant gene expression and PRE components in both mutants comparing the wild-type. Multiple regression analysis performed with data of PRE components and relative abundances showed a strong correlation which agrees with previously reported effects of the circadian clock in PRE composition, partially explaining changes in the bacterial community [178]. Also, mutant plants in LHY (a transcription factor involved in circadian rhythm) displayed rhizosphere microbiota changes, especially in fungal groups involved in plant health [138].

Effects of the developmental stage on the plant microbiota

Chaparro et al. [39] compared bacterial communities at seedling, vegetative, bolting, and flowering stages, and found that the seedling stage community mainly differed from the other three, with relatively few gross changes in composition throughout the life cycle. Such differences were mainly explained by variations in the relative abundances of a few genera: among others, Streptomyces, Solibacter, Flexibacter, and Leptolyngbya, which might be due to changes in PRE composition. A comparison of the phyllosphere microbiota in bolting, flowering, and maturation showed a set of 40 genera that were shared among these three stages; 27 genera belonging to Pseudomonadota, six to Actinomycetota, five to Bacteroidota, and two to Bacillota [106]. Enriched members associated with flowering were, among others, Azospirillum, Methylobacterium, Paracoccus, and Nocardioides.

Host developmental effects on natural bacterial assemblages have been followed in field samples during all the stages of the annual cycle of Arabidopsis [16]. They found that endophyte bacterial community compositions from roots, shoots, and leaves were driven by the same set of commensals that were not especially prevalent but whose relative abundances changed among compartments. Similar conclusions were obtained when young and old leaves were compared [19].

Community composition changes at early seed germination and emergence have been reported for bacteria and fungi from several plants, mostly Brassicaceae, including A. thaliana [14]. Contrasting seeds with germination and emergence (seedlings) microbiota, they found essential changes at the emergence stage, characterized by an apparent decrease in bacterial and fungal richness. However, a note of caution on the interpretation of the developmental stage's effects on microbial communities should be considered, as Dibner et al. [46] reported that elapsed time (and resulting microbial succession) has more potent effects on communities than on the specific stage.

Role of PRE and specific plant metabolites

Among the effects that plants exert on their microbial communities, those played by simple molecules, alone or in complex mixtures as in PRE [11], have received considerable attention [31]. Early work on Arabidopsis fungal communities showed that biomass and phylotype richness, measured by internally transcribed sequences profiling, was significantly affected by in vitro prepared PRE [29]. An ABC-transporter Arabidopsis mutant with an altered PRE composition produced changes (mainly decreases in abundances) in bacterial and fungal communities [8]. Further evidence on the role of PRE in shaping rhizobacterial communities was suggested when PRE effects from eight Arabidopsis ecotypes were compared [133]. In addition, the role of PRE influencing microbial communities has been proposed to explain differences between bacterial communities from the root and the rhizospheric compartment, with specific sub-groups of α and β Pseudomonadota classes being differentially active [67].

Small PRE molecules are classified as amino acids, sugars, organic acids, and phenolics [7]. Considering this, Badri et al. [9] tested different PRE compound mixtures on unplanted soil communities, finding changes in relative abundances at low taxonomical levels rather than in higher ones. It is worth mentioning that the unidentified compounds present in PRE are still a majority fraction and that the assignation of PRE compounds to the phenolics or organic acids category used in some reports is not free of confusion. An inspection of compounds listed as phenolics (aromatic ring compounds with at least one hydroxyl substitution) shows that this category included fatty acids, non-aromatic organic acids, alcohols, aliphatic hydroxy acids, and N-containing compounds, being actual phenolics only one-tenth of compounds listed as such. Recent reports have shown that aromatics are significantly lower than sugars, amino acids, and lipids [77], with a relative abundance of lipids and lipids-like components higher than 40% [112]. It is out of the question that further progress in analytical tools is needed to fully understand PRE composition [139].

Phytohormone changes in plant physiology produce alterations in PRE composition and, therefore, in microbial communities, as reported for jasmonic acid (JA) [33, 34]. Furthermore, using a triple mutant in Dicer-like genes involved in small RNAs biogenesis, Kaushal et al. [87] found an altered PRE composition, which can partially explain the observed modifications in the root microbial community.

The nutrient status also produces changes in PRE. Herrera Paredes et al. [77] used the SynCom approach to test plants exposed to different available P levels and found that the ability of some SynCom members to grow on PRE components was not necessarily a good proxy of their performance on plant growth tests. On the contrary, binary plant-bacteria interactions (positive, neutral, negative) were better predictors of SynCom’s effects on plants. Using the 13C DNA Stable Isotope Probing technique, Worsley et al. [203] demonstrated that several Pseudomonadota genera incorporated 13C from PRE components when Arabidopsis is grown on compost.

The role of specific groups of plant-derived compounds on microbial communities has been addressed [84, 181]. Early work using DGGE and 13CO2 labeling reported that glucosinolates, typical Brassicaceae secondary metabolites that are precursors of biocidal compounds protecting plants from pathogens, produced significant changes in the Arabidopsis fungal and the α Pseudomonadota class (Rhizobiaceae) communities [28]. The use of nine glucosinolate plant mutants confirmed extensive effects on root microbiota, with several bacterial and fungal taxa being enriched in the mutants compared with the wild type [98].

The role of a PRE component, scopoletin (a coumarin siderophore and antimicrobial compound), in shaping Arabidopsis microbiota has been demonstrated by comparing the microbial communities from the wild type, and a scopoletin synthesis mutant [180]. The effect of coumarins has been further explored using several plant biosynthetic mutants and the addition of specific coumarins, using SynComs and gnotobiotic cultivation, for better elucidation of direct from indirect effects [196]. Fraxetin, another coumarin synthesized directly from scopoletin, that has antimicrobial effects and affects iron availability, also modified the Arabidopsis root microbiota, differentially affecting relative abundances of lower-rank taxa such as Burkholderiaceae, Rhizobiaceae, and Streptomycetaceae [69]. Recently, flavonoids were also related to changes in the microbiota diversity in Arabidopsis [74].

The role of PRE macromolecules [11], has received no attention in Arabidopsis. It should be noted that released mucilage can harbor protein and DNA, as well as small carbon source molecules that would contribute to shaping rhizosphere microbiota [166].

Effects of plant responses to abiotic stress on the plant microbiota

The effects on the microbiota of Arabidopsis exposed to abiotic stress have started to be studied. Reports on heavy metal pollutants (cadmium, [188], cold [57], drought [117], and nutrient limitations: iron [69, 180, 196] and phosphate [58, 60, 77, 159] are now available.

Although there are several reports on the effects in Arabidopsis of both inorganic and organic pollutants (e.g., [42, 102], to date, only a few reports address the effects of contaminants on Arabidopsis microbiota [108, 188, 190, 207]. Truyens et al. [188] used a culture-dependent approach and found shifts in seed endophyte composition when plants were exposed to Cd for several generations. More recently, the effects of glyphosate on Arabidopsis growth and its phyllosphere microbial community [154] were mainly detected when this herbicide was applied in carbon nanotubes [88]. Effects on microbiota (rhizosphere diversity, community composition, and interspecies interaction) of Arabidopsis and Nicotiana benthamiana of per- and polyfluoroalkyl pollutants have been recently reported [110].

The effect of low temperatures on Arabidopsis phyllosphere microbiota was analyzed in different accessions during cold acclimation [57]. Although the main phyllosphere phyla (Pseudomonadota, Actinomycetota, Bacillota, and Bacteroidota) did not show alterations between cold-acclimated and non-acclimated accessions, differences were found at lower taxonomical ranks. This might be explained by different plant gene expression patterns and plant biomolecule synthesis upon cold acclimation [57].

The connection between microbiota and the impact of drought conditions was initially addressed by Zolla et al. [208], determining that 41 genera were enriched in the Arabidopsis soil slurry,  a significant part of these genera belonging to the Arabidopsis core microbiota [30, 115]. In this context, it has also been reported that bacterial communities significantly changed under drought [117], observing a decrease in the diversities of the the rhizoplane and rhizosphere communities [204]. Using a four-member consortium that protected Arabidopsis from drought conditions, Yang et al. [204] showed significant re-shaping of the microbial assembly in water-stressed plants in such a way that inoculated plants exhibited a bacterial community resembling that of plants grown under watered conditions. Regarding salt stress, chronic exposure to salt produced changes in the bacterial leaf community, with altered relative abundances in members of Actinomycetota, Bacillota, and Pseudomonadota [19]. They reported that community assembly resulted from three interacting factors: the leaf age, the abscisic acid (ABA) phytohormone biosynthesis (as part of the abiotic stress response), and the function of PBS3, a signaling component of the defense phytohormone SA. PBS3 plays a crucial role in regulating the trade-off between biotic and abiotic stresses.

The effect of the responses of plants to suboptimal light conditions was recently addressed using a three-kingdom SynCom, composed of 183 bacteria, 24 fungi, and seven oomycetes, and several combinations of them [79]. Suboptimal light produced significant changes in the composition of the root bacterial (but not the fungal and oomycetal) community.

The effects of iron and phosphorous (phosphate) availability on Arabidopsis microbiota have received consideration. Applying a β diversity comparison, iron depletion was the second factor differentiating Arabidopsis microbial community after the bulk soil versus the rhizosphere soil factor [180]. Relative abundances of 21 genera changed (mostly belonging to Pseudomonadota and Bacillota) at different iron levels. Additionally, under full iron conditions, no changes in microbial composition were observed, but under iron-limiting conditions, the presence of iron mobilizing coumarin (see [181]) drastically reduced Pseudomonadaceae, among other taxa [196]. Bodenhausen et al. [25] reported that OTUs belonging to Burkholderiales, Bdellovibrionales, and Rhodocyclales showed increased relative abundances at low P levels. Diverse microbial communities are also found in the wild-type and phosphate starvation response (PSR) Arabidopsis mutants at low taxonomic rank levels [36, 77]. Finkel et al. [60] reported changes in roots and shoots fungal and bacterial communities regarding P availability and PSR mutations. Further evidence of the effects of PSR genotype and P levels on the fungal community has been reported by Fabiańska et al. [58], identifying, for example, that full-P conditions increase the relative abundance of Microascales and Olpidiales and the decrease of Helotiales and Xylariales. However, the link among the phosphorous levels, microbiota (fungal communities), and plant responses, is more complex and is not completely understood yet (Macía-Vicente et al. 2022).

Effects of plant responses to biotic stress on the plant microbiota

Plants face several biotic stresses, with the effect of phytopathogens the more frequently addressed. The inoculation on leaves with the biotrophic fungal pathogen Hyaloperonospora arabidopsidis produced detectable changes in A. thaliana rhizosphere, these changes were not produced by the necrotrophic pathogen Botrytis cinerea or salicylic acid (SA) and methyl jasmonic acid applications [18]. A soil-mediated effect of this biotrophic pathogen led to protecting newly planted Arabidopsis, which may be due to changes in the rhizosphere microbiota [18]. Another fungal pathogen, Golovinomyces orontii, causing the foliar disease powdery mildew, produced changes in the leaf (but not roots) fungal and bacterial communities [51].

It has been reported that inoculation of leaves with the phytopathogen Pseudomonas syringae pv. tomato in Arabidopsis grown in successive transfers to the same soil produced changes in both bulk and rhizospheric soil microbiota [205]. These changes were partially associated with an increase in the relative abundance of a few initially low-abundance taxa: Fictibacillus and Roseiflexus, and a decrease in the relative abundance of Sphingomonas [18]. Arabidopsis plants infected with this phytopathogen showed disease suppression by soil legacy in a phenomenon probably related to the relative abundance of some PRE components [205]. Recently, a synergistic effect between a fungal endophyte and the resident bacteria microbiota against a fungal hemibiotrophic pathogen was reported (Madhli et al. 2022).

The role of different hormones related to Induced Systemic Resistance (ISR) and Systemic Acquired Resistance (SAR) in shaping plant microbiomes has also been studied [33, 48, 75, 91] and [101]. Kudjordjie et al. [98] reported the effects on root microbial community assembly of seven Arabidopsis mutants in defense signaling molecules: SA, ethylene (ET), JA, ABA, and fatty acid desaturase linked to the regulation of SA and JA pathways. The microbiota of these mutants showed changes, in different degrees, in richness, α and β diversity, of both bacterial and fungal taxa, supporting the role played by plant defense in shaping the wild-type microbial community. Strigolactones, plant hormones involved in plant development and chemical communication during biotic interactions (as those involved in plant—AMF relations), affected the fungal but not the bacterial diversity when the microbiota of the Arabidopsis wild type and a mutant with impaired strigolactones synthesis were compared [35]. Impaired lines of Arabidopsis in JA, SA, ET, and strigolactones synthesis showed changes in nematode taxa abundances, they produced changes in the fungal and bacterial community when the plant was grown in natural soil conditions [174, 175]. Resistance and susceptibility to the pathogen Fusarium oxysporum f.sp mathioli resulted from a combination of plant ecotype and metabolome and robustness of the microbial assembly [99].

The effects of other plant protection processes have also been tested. The role of the cuticle, the first mechanical barrier to colonizing the phyllosphere, was studied using plant mutants possessing different cuticle wax compositions. Reisberg et al. [156] found a role in shaping core, resident, and transient bacterial phyllosphere communities, the latter the more numerous. Similarly, changes in the phyllosphere microbiota were reported in two cuticle A. thaliana mutants resistant to the phytopathogen B. cinerea [158].

As indicated above, changes in the leaf metabolome composition have been reported when pathogenic and non-pathogenic species colonize plants [162]. The protective role of specific compounds, in this case, triterpenes involved in immunity and antibiosis, has also been explored in roots [81]. Several triterpene biosynthetic mutants exhibited different microbial communities.

A quadruple mutant in the innate immune and vesicle trafficking pathways showed a severe alteration in leaf endophytes (but not in the total leaf community) associated with chlorosis and necrotic effects [40]. Using endophyte SynComs from the mutant and wild-type plants, the authors showed that when the mutant SynCom was infiltrated in wild-type leaves, the plant developed chlorosis and necrotic effects, otherwise, when a wild type SynCom was inoculated in the mutant plant, the damaged leaf tissue effects diminished. Therefore, the dysbiosis caused by these mutations increases the abundance of bacteria producing leaf damage that is, in turn, were constrained by the microbiota of the healthy plant. Changes in the endophyllosphere have also been reported in several immune system mutants using gnotobiotic growth systems and SynComs [146]. Such changes allowed increased colonization of opportunist pathogens, especially a Xanthomonas sp. strain, that produce disease and affect plant growth. The role of commensal pseudomonas strains protecting against pathogens, promoting host response has been recently reported [176, 200].

The role of the leaf microbiota on protection against P. syringae pv. tomato DC3000 has been studied in individual isolates of the SynCom At-LSPHERE, and in selected ten-and three- members combinations [195]. Direct microbe-to-microbe interactions and indirect plant-mediated processes are possible mechanisms behind phytopathogen protection [195]. When selected commensals of this At-LSPHERE were tested in mono associations with Arabidopsis, a defined small set of plant genes was up-regulated [123]. The authors defined this set of genes as part of a general non-self-response, helping to distinguish pathogenic from non-pathogenic bacteria. This non-self-response was differentially triggered by these commensals, with variable intensities across close or distantly related strains [56, 123, 182]. This non-self-response is involved in the interaction between the immune system and microbiota, with the former shaping the host-microbial community and the latter influencing the immune response and defense mechanisms. For further details on the interaction of innate immunity and microbiota, see the review of Hacquard et al. [66]. Interestingly, the role of epigenetic regulation in shaping plant microbial communities has started to be addressed. For instance, a dysfunction in the histone demethylase IBM1 produced strong effects in the assembly of root microbiota through the regulation of SA-genes regulating plant immunity [118].

Reciprocal influence of plants and their microbiota

The focus of this section is to consider the microbiota as a facilitator, i.e., providing additional genes to the host to adjust to local environmental conditions [192] (Fig. 2B). The taxonomical composition of communities should reflect the functions they provide to the plant. Those abundant phyla would represent a broader range of tasks than those less abundant. Such seems to be in Arabidopsis, where the predominant Pseudomonadota is far more functionally diverse than the other less abundant phyla [10]. In this context, Lau and Lennon (2012), correction in 2021) performed a multigeneration selection experiment that manipulated the soil-moisture environment of replicated plant populations and their associated microbial communities. They found a strong effect of the microbe's evolutionary history on plant fitness responses to this abiotic stress.

Notably, soil microbiota control plant functions such as flowering time [142, 143]. This phenomenon was further studied with selected Col-0 microbiota from early and late flowering times plants, transferred to other Arabidopsis ecotypes, and the crucifer Brassica rapa [142]. Early or late flowering root microbiota accelerates or delays the flowering of inoculated plants. Few low-abundance families were dissimilarly present in early (Xhantomonadaceae and Pseudomonadaceae) or late (Iamiaceae, Alcaligenaceae, and Corynebacteriaceae) flowering microbial communities. The relative abundance of the main phyla reported associated with the Arabidopsis core microbiota (see subSect. "Root microbiota"., Table 1, and [143] were found altered in early flowering microbiota with Bacillota (31%) being more abundant than Actinomycetota (22%), Pseudomonadota (17%), and Bacteroidota (16%). In a later work, delayed flowering in the wild type and early flowering in a photosynthetic A. thaliana mutant (pgr5) was observed in plants grown on a sterile growth medium inoculated with a slurry containing Arabidopsis root microbiota obtained from previous growth rounds [111].

A survey for bacterial genes that are involved in adaptation to plants has been reported searching genomes from isolates of two Arabidopsis ecotypes (including Col-0), maize and poplar, and a comparison with nearly 3500 other genomes from soil isolates and isolates non-adapted to plants, to define plant-associated genes [104]. Plant-associated genomes possess more “Carbon and Transport” genes and fewer “Mobile Elements” genes than non-plant-associated genomes, with an essential overlap in genes from plant-associated and root-associated and between non-plant-associated and soil genome isolates [105]. Interestingly, plant-associated genomes harbor bacterial protein domains mimicking plant domains that are shared with fungi and oomycetes associated with plants [104], which may help microorganisms camouflage.

In another proof of the reciprocal influence between the plant and its microbiota, Salas-González et al. [163] reported that alterations in genes controlling diffusion barriers, involved in mineral nutrient balance in the root endodermis, produce changes in roots and shoots microbiota assembly. Root microbiota controls endodermic differentiation (mainly suberin deposition) through repression of ABA transcriptional response. Microbial effects were observed in plants grown on agar and soil, with a 41-members SynCom, and in binary tests as well [163]. Significantly, changes in suberin deposition produced by microorganisms when plants were exposed to nutrient stress led to systemic effects in the ionomes of the plants. Impact on the rhizosphere microbial community in mutants in components of a signaling pathway of endodermal root organization (ERK1 and TIC) and lignin and suberin deposition have also been reported using 206-members AtRSPHERE-based SynCom [54]. In another layer of interaction among plant immune response and plant microbiota, root commensals that suppress the root growth inhibition response also significantly affect the expression of subsets of Arabidopsis genes, increasing the expression of genes related to root development, nutrient transport and decreasing some genes related to immune response and detoxification [119]. Such differences in gene expression are not observed when plants are inoculated with non-suppressive commensals.

Microbial interactions in the plant microbiota

Interactions among different microbial groups of the Arabidopsis microbiota are crucial to understanding its dynamics and the effects on the host [72] (Fig. 2B). Seminal work shed some light on the role of protozoa in the bacterial community [96, 97, 161]. The Arabidopsis growth promotion, as observed in other species, takes place by the inoculation of the protozoon Acanthamoeba castellanii. In other words, plant growth promotion is increased when bacteria and protozoan are both present [96]. The effects of A. castellanii on the Arabidopsis bacterial community were selective as β Pseudomonadota class and Bacillota decreased their relative abundance. In contrast, Actinomycetota, Nitrospirota, Verrucomicrobiota, and Planctomycetota increased their relative abundance, measured by DGGE clone library and sequencing [161].

A three-kingdom component (bacteria, fungi, and oomycetes) interaction has been investigated in the Arabidopsis phyllosphere, exploring different ecotypes and abiotic conditions [2]. Using network analysis, the authors identified microbial hubs, key species [13, 27, 193], whose presence/absence severely affects microbial community structure. They further studied some of these microbial hubs showing that the biotroph pathogen oomycete Albugo affected the colonization of both bacterial epiphytes and endophytes (decreasing α diversity); the Basidiomycota yeast Dioszegia interacted negatively with phyllosphere bacteria, and that a bacterial hub Comamonadaceae genus positively interacted with other bacterial groups [2]. Mainly inhibitory interactions between phyllosphere bacterial taxa have been reported, which are explained by the antimicrobial effects of different biosynthetic gene clusters detected in the phyllosphere microbiota members [76]. Relatively less abundant Bacillales and Pseudomonadales microbiota members caused the most inhibitory effects on bacterial target groups, which rarely include closely related bacterial taxa [76]. Actinomycetota species involved in negative interactions in the phyllosphere microbiota have been recently identified using SynCom [168].

Based on reported data [20], He et al. [73] performed network analyses [193] of microbe-to-microbe (bacteria and fungi) interactions (mutualism, antagonism, aggression, and altruism) in the root microbiota from 179 Arabidopsis accessions. They found that bacteria have more connections in mutualism and altruism interactions, whereas fungi were more critical in antagonism and aggression. They, as performed in Agler et al. [2], searched for microbial hubs, reporting 59, mostly belonging to Pseudomonadota (21), Actinomycetota (12), and Ascomycota (20), with antagonism (26) and altruism (24) having far more hubs than mutualism (6) and aggression (3).

Bartoli et al. [15] addressed the interaction between the microbiota, essentially non-pathogenic, with the pathobiota fraction. They tested 163 native A. thaliana bacterial populations from different ecologically contrasting habitats in France and found that at low or high α diversity microbiota levels, the pathobiota α diversity levels were low, with higher pathobiota α diversity levels found at intermediate levels of microbiota diversity (the invasion paradox). Tracking of the microbiota species that lead to the pathobiota changes determined a dozen OTUs, unclassified, with a few exceptions, among the latter Pseudomonas moraviensis [15].

Interactions between prokaryotic and eukaryotic members help maintain Arabidopsis health, as judged by several SynCom inter-kingdom combinations [50, 202], being positive interactions predominant between bacterial groups, whereas adverse effects dominate fungal/oomycetal interactions with bacteria. SynCom with fungal/oomycetal members negatively affected plant health, while bacterial SynCom positively acted on Arabidopsis health. Variovorax and Acidovorax, were the best to rescue the plant from the adverse effects of eukaryotic members [50].

An exciting phenomenon revealing multilevel interactions among root bacteria was reported in Arabidopsis [61]. A 185-member SynCom produced severe root growth inhibition. All the Variovorax genus strains from this SynCom could suppress the root growth inhibition exerted by the whole SynCom, subsets, and unique strains. Stimulatingly, the mechanism underlying this phenomenon is related with an interference in the signaling of auxin [44].

Carlström et al. [32] studied the effect of bacterial groups’ arrival times from the same taxa or individual strains in structuring the bacterial community. They used a 62-phyllosphere members SynCom and found that assembly is historically contingent (time of arrival), subjected to priority, and resistant to late arrivals. Through single strain drop-out tests (a single strain is initially absent in the community but added later) and causal network analysis, they detected keystone strains (Microbacterium and Rhodococcus, and Sphingomonas and Rhizobium) and the predominance of negative (competition) direct or indirect interactions [32]. Priority effects in root community assembly have also been reported, as non-native species were less abundant when introduced after an initial inoculation of commensals [201]. This phenomenon needs a living root and some components of PRE, does not depend on immune response functions, and correlates with the strength of commensal invasiveness [119].

Plant growth promoting rhizobacteria effects on Arabidopsis microbiota

Plant Growth Promoting Rhizobacteria (PGPR) has a tremendous potential to increase crop productivity through the improvement of plant nutrition as well as plant protection [59]. Despite the more than 250 articles on PGPR and Arabidopsis, relatively few of them study the effects of PGPR in the Arabidopsis microbiota. Haney et al. [68] tested the impact on the whole microbiota of the inoculation of one PGPR P. fluorescens strain, finding relatively few changes, with some enrichments in Bacillota and losses in Bacteroidota. This observation raises an interesting point, largely unexplored in this kind of report, about the actual promotion or protection being a direct effect of inoculated PGPR or a consequence of the activation or depletion of pre-existing populations in the microbiota.

Using combinations of N-fixing, non-N-fixing, symbiotic and non-symbiotic species isolated from other plants and soils, Garrido-Oter et al. [64] reported plant gene expression associated explicitly with an interfered immune system response. It should be noted that such decreased immune response is found when some Rhizobiales establish an N-fixing, nodule-forming symbiosis [94], which is not a possibility in Arabidopsis. However, Arabidopsis-endophyte Ensifer meliloti interaction provides N to the plant [5]. Therefore, it is possible to think that Rhizobiales are normal inhabitants in Arabidopsis that may modulate the immune response. Evidence for a role as a PGPR for some Rhizobiales is also reported [64], whose colonization process may be benefited by this immune system interference. Root immune system interference has also been shown for bacterial commensals [182]. They found that about one-third of 35 members Syncoms [36] suppressed microbe-associated molecular patterns triggered immunity. Arabidopsis growth promotion by a bacterial/fungal/oomycetal SynCom is also observed but abolished in immunocompromised plants [202]. The fungal component (dysbiosis due to fungal load) of this SynCom is responsible for altered plant growth promotion in the immune response mutants.

In a different context, hydroponic culture tests of the effects of 96 Arabidopsis root isolates in the maintenance of a Bacillus subtilis PGPR indicated that a relatively small fraction of them, not phylogenetically related, helped this PGPR to survive in binary co-cultures [55]. Among the helpers, a Variovorax isolate better performed with B. subtilis and the other two B. amyloquefaciens PGPR. A recent report explores the effects of another PGPR, Sphingomonas sp. Cra2 [117], finding that the inoculant increased the relative abundances of members Burkholderiales and Pseudomonadales, to whom several PGPR species have been reported [103, 114, 147, 152, 167, 187, 206, 209], Orellana et al. 2022). This suggests that benefic effects may be produced by changes in the root microbiota that are part of the promotion effects of the added strain stimulating PGPR species present in the root system [117]. A drought-protecting four members consortium that re-shapes Arabidopsis microbiota also has plant growth promotion effects [204]. In addition, the presence of the siderophore scopoletin strongly affects the Arabidopsis microbial community with the enhanced presence of genera having PGPR and metal or N uptake properties [180].

Arabidopsis microbiota in comparison with other plant species

Several studies compare the Arabidopsis microbiota with other plant species. A first report compared Arabidopsis phyllosphere with those of soybean, rice, and clover [45, 198]. Using DGGE, the authors found that α diversity was higher in Arabidopsis and that each plant species has a particular and stable in-time bacterial profile, although sharing about 70% of species with similar relative abundances. One of the main taxa found in Arabidopsis phyllosphere, Methylobacterium, was further explored by comparing this community to that found in several other plant species, including M. truncatula. The authors found that this community primarily depended on the site, but also on the plant species [90]. Anoxygenic phototrophs found in the phyllosphere of Arabidopsis have also been found in clover, rice, and soybean [6].

An in-depth comparison of the microbiota from root/rhizosphere compartments among Arabidopsis, Arabidopsis species (A. halleri and A. lyrata), and the Brassicaceae relative Cardamine hirsuta, showed similar bacterial communities, being the main groups Actinomycetotales, Burkholderiales, Flavobacteriales, Rhizobiales, and Sphingomonadales, with the differences attributable to specific taxa [169]. They also found that about one-half of the diversity is shared among plants, with the other half explaining adaptative differences such as resistance to metals (A. halleri), or being perennial (A. halleri, and A. lyrata). A similar degree of sharing among high-rank taxa was reported between Arabidopsis and the legume L. japonicus, with the shared taxa showing different abundances [201]. These authors also showed that a clear host preference for root commensals was observed in A. thaliana and A. lyrata.

Similarities among microbial communities of closely related Brassicaceae species (Draba verna, C. hirsuta, and C. pratensis) are not always found. Poch et al. (2017) used PCR primers to detect Cercozoa in the phyllosphere. They found that shared groups were only one-fifth of the sequences and that A. thaliana was the more distant species. However, a common group of bacterial and fungal species has been reported in seeds from 20 Brassicaceae, including A. thaliana, and several non-Brassicaceae species [14]. In a meta-analysis, Hacquard et al. [65] compared the composition of the root bacterial community of Arabidopsis and its relatives [169], with that of other plants such as soybean, wheat, and cucumber. This work found that root plant communities were more similar among them than with those of human gut and other animals, where Bacteroidota and Bacillota dominate, but closer to the fish gut where Pseudomonadota were abundant, as in plants.

A comparison among A. thaliana (Col-0), A. alpina, and C. hirsuta showed that the factor species only explain 7–10% of the variability among bacterial communities, indicating microbiota closeness which includes nearly 20 shared families [47]. Interestingly, shared core microbiota members can also be found when not-so-close plant species (poplar, maize, and Brassicaceae) are considered [105]. In another context, a minor fraction of the shared Arabidopsis taxa with rice and wheat was affected in Arabidopsis triterpene biosynthesis mutants, indicating that triterpene effects are species-specific and contribute to the recruitment of Arabidopsis microbiota from soil [81].

The comparison of bacterial community successions after three generations in model plants (A. thaliana as a non-legume, M. truncatula as a legume, and Brachypodium distachyon as a monocot cereal) and crops (B. rappa, Pisum sativum, and Triticum aestivum), allowed to determine that the plant factor is, after soil source, the more important factor shaping these communities [183]. This critical role of the plant species was more significant with bacterial communities than with fungal communities, and with evident differences found in Arabidopsis, including more archaeal groups than in the other three species. The shared OTUs taxa belonged to relatively rare groups (Verrucomicrobiota > Chloroflexota > Thaumarchaeota >  > Actinomycetota = Acidobacteriota), with the scarce presence of Pseudomonadota OTUs [184]. Bacterial and fungal community comparisons among Arabidopsis with eight other phylogenetically diverse plant species thriving in the same semi-natural grassland habitat, showed that endorhizosphere bacterial communities were substantially shared [170]. In contrast, fungal communities, especially that of the rhizosphere compartment were more variable among these plants, with Arabidopsis sharing only around 10% of fungal OTUs, as has been also reported by Bergelson et al. [20]. Among the nine plants, Arabidopsis rhizosphere bacterial community was the one which have less OTUs that change their relative abundance with respect to the bulk soil, indicating a comparatively lower rhizosphere effect [170], as reported also by Tkacz et al. (2015, 2020).

Comparison of the bacterial community from duckweed, a phylogenetically distant monocot aquatic plant, with the microbiota of Arabidopsis phyllosphere indicated a similar assemblage, with Pseudomonadota, Bacteroidota, Bacillota, and Actinomycetota as main phyla, although the latter being significantly less abundant in duckweed [1]. A general similar root-associated bacterial community was reported in a comparative study between Arabidopsis and Petunia, a plant that establishes interactions with AMF, with β- and γ Pseudomonadota, and Bacteroidota as more abundant taxa, and with Petunia exhibiting higher richness and diversity than Arabidopsis [25]. This overall similitude was not reflected when plants were exposed to different P levels, as changes in relative abundances were found for different bacterial groups in both plants. Going forward, Durán et al. [52] contrasted the microbial community of Arabidopsis with that of a taxonomically distant photosynthetic organism, the subaerial green model alga Chlamydomonas reinhardtii. The authors reported taxonomically similar communities, a core microbiota, with relatively abundant phyla, as indicated in Table 2, between the phycosphere and the plant roots, with larger abundances in Bacillota and lower in Actinomycetota, in the alga compared to the plant.

In a different approach, Bieker et al. [21] compared the leaf microbiota of Arabidopsis with that of the annual weed Ambrosia artemisiifolia and contrasted the metagenomic profiles of ancient samples (collected up to 180 years ago and available in herbariums). The authors reported different leaf metagenomic profiles, and variations between ancient and modern samples for both species, with the differential presence of specific fungal sequences in ancient samples attributable to contamination during preparation and storage. Ancient samples of Arabidopsis showed sequences reported in modern leaf samples such as Pseudomonas putida and Albugo spp.

Concluding remarks and future research needs

Several aspects of the Arabidopsis microbiota were discussed in detail in the previous sections, revealing how intertwined each of the factors that modulate these complex biological relationships are (Fig. 2B). Despite that, Arabidopsis allows us to unveil the intricacies of the mechanisms behind host-microbe interactions and their effects on plant holobiont fitness. Arabidopsis provides grounds to answer most, if not all, questions on molecular plant–microbe interactions posed in a recent survey [71]. The depth, critical and exhaustive analysis provided here is, so far, the most comprehensive review of the Arabidopsis microbiota, and brings light to the understanding of such fundamental biological interactions. There are some limitations in this model as it does not establish AMF symbiotic relations nor is a nodulating plant [4, 166], which, in turn, is a useful tool as a non-symbiotic plant control. Interestingly, it is not clear, yet which evolutionary and genetic limitations constrain these symbiotic interactions to specific taxa.

Then, there is a need to move forward (Fig. 2C) and consider the Arabidopsis microbiota/microbiome as a complex system, where the outputs are not the sum of the parts, and multifactorial approaches should be addressed. For instance, the plant-life history traits, epigenome, evolutionary, ecological, and climate (as recently addressed by [53] aspects, and concomitant multiple layers of the abiotic and biotic aspects of the environment should be included in future research. Networking mapping analysis [107] and multi-genome metabolic modeling [127] are some of the ways to move forward in this issue. This will foster our ability to predict the effects of a particular plant-microbiota interaction and to engineer the use of microbiomes for more sustainable agriculture. More specifically, what is clear is the lack of omics approaches to understand Arabidopsis–microbe interactions, other than metagenomics analysis based only on the 16S sequence marker, i.e., taxonomy-based analysis. There are, comparatively, only a few reports so far, addressing functional metagenomics (metatranscriptomics, metaproteomics, metametabolomics) in Arabidopsis [104]. They are clearly required as early proposed by Bakker et al. [12]. A recent approach for metaproteomic analyses of rhizosphere microorganisms has been reported [164]. It is quite possible that technical problems based on low biomass, which are not observed in bigger plant species such as cucumber, soybean, and wheat [65], explain this Arabidopsis drawback, which should be surpassed soon as more sensitive/resolutive methods and technologies come available. Gnotobiotic plant systems may help in this direction as allow analysis of microbiota functions under easily controlled experimental conditions [120].

An effort of the Arabidopsis research community [144] to set the basis to make Arabidopsis (and other plants) microbiota studies more systematically comparable [31] is clearly required to provide a strong basis for analysis between different reports for a single species and comparisons among diverse species. Such a systematic methodological approach will be required to perform finer studies like comparisons of microbiota at different root lengths/sites (root tip, intermediate and mature roots, and secondary growth roots) and their connection with PRE rhizodeposition components [31]. Lateral position/border cells studies on rhizosphere microbiota effects are also enlightened by Sasse et al. [166], which in turn is linked to the role of macromolecular components of PRE, mucilage, and other components derived from sloughed cells [31].

Other studies that would benefit from having a systematic experimental approach will be comparisons of the adaxial and abaxial sides of leaf microbiota, microbial loads of seeds, and those addressing the rare and semi-rare bacterial community [180]. Also, consensus operational procedures would be helpful in dealing with poorly studied issues such as the circadian cycle [178] and seasonal effects [15, 31]. In addition, seed microbiota functions should be considered: i.e. ecology, developmental stages, shaping of the core microbiota, vertical transmission [41, 137, 189], and seed-to-seed cycle [15]. Finally, an unexpected lack of reports on the effects of Arabidopsis microbiota/microbiome in issues such as nitrogen limitation [94], or plant–insect (nematode)-microbe interactions, is clearly a call for new studies. In addition, there is a complete lack of reports on Arabidopsis virome. Even though it is suggested that viruses, not only those that cause diseases, also have commensal and mutualistic interactions, helping plants to overcome abiotic stresses [150], and shaping plant ecology and evolution [160]. In turn, bacteriophages and temperate phages can also contribute to modify the ecology and evolution of plant-associated microbial communities and should be considered in some analyses [93, 153]. Then, Arabidopsis may also be a helpful plant model for studying plant virome in-depth (Fig. 2C).

Availability of data and materials

Not applicable.

References

  1. Acosta K, Xu J, Gilbert S, Denison E, Brinkman T, Lebeis S, Lam E. Duckweed hosts a taxonomically similar bacterial assemblage as the terrestrial leaf microbiome. PLoS ONE. 2020;15:e0228560. https://doi.org/10.1371/journal.pone.0228560.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Agler MT, Ruhe J, Kroll S, Morhenn C, Kim S-T, Weigel D, Kemen EM. Microbial hub taxa link host and abiotic factors to plant microbiome variation. PLoS Biol. 2016;14:e1002352. https://doi.org/10.1371/journal.pbio.1002352.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Almario J, Mahmudi M, Kroll S, Agler M, Placzek A, Mari A, Kemen E. The leaf microbiota of Arabidopsis displays reproducible dynamics and patterns throughout the growing season. mbio. 2022;13:e02825-21. https://doi.org/10.1128/mbio.02825-21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Almario J, Fabiańska I, Saridis G, Bucher M. Unearthing the plant-microbe quid pro quo in root associations with beneficial fungi. New Phytol. 2022;234:1967–76. https://doi.org/10.1111/nph.18061.

    Article  PubMed  Google Scholar 

  5. Armijo, G., Kraiser, T., Medina, M.P., Gras, D.E., Zuñiga, A., González, B., and Gutiérrez, R.A. (2020). Arabidopsis thaliana interaction with Ensifer meliloti can support plant growth under N-deficiency. bioRxiv preprint. https://doi.org/10.1101/2020.07.25.221283.

  6. Atamna-Ismaeel N, Finkel O, Glaser F, von Mering C, Vorholt JA, Koblížek M, Belkin S, Béjà O. Bacterial anoxygenic photosynthesis on plant leaf surfaces. Environ Microbiol Rep. 2012;4:209–16. https://doi.org/10.1111/j.1758-2229.2011.00323.x.

    Article  CAS  PubMed  Google Scholar 

  7. Badri DV, Vivanco JM. Regulation and function of root exudates. Plant Cell Environ. 2009;32:666–81. https://doi.org/10.1111/j.1365-3040.2009.01926.x.

    Article  CAS  PubMed  Google Scholar 

  8. Badri DV, Quintana N, El Kassis EG, Kim HK, Choi YH, Sugiyama A, Verpoorte R, Martinoia E, Manter DK, Vivanco JM. An ABC transporter mutation alters root exudation of phytochemicals that provoke an overhaul of natural soil microbiota. Plant Physiol. 2009;151:2006–17. https://doi.org/10.1104/pp.109.147462.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Badri DV, Chaparro JM, Zhang R, Shen Q, Vivanco JM. Application of natural blends of phytochemicals derived from the root exudates of Arabidopsis to the soil reveal that phenolic-related compounds predominantly modulate the soil microbiome. J Biol Chem. 2013;288:4502–12. https://doi.org/10.1074/jbc.M112.433300.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Bai Y, Müller DB, Srinivas G, Garrido-Oter R, Potthoff E, Rott M, Dombrowski N, Münch PC, Spaepen S, Remus-Emsermann M, Hüttel B, McHardy AC, Vorholt JA, Schulze-Lefert P. Functional overlap of the Arabidopsis leaf and root microbiota. Nature. 2015;528:364–9. https://doi.org/10.1038/nature16192.

    Article  CAS  PubMed  Google Scholar 

  11. Bais HP, Weir TL, Perry LG, Gilroy S, Vivanco JM. The role of root exudates in rhizosphere interactions with plants and other organisms. Annu Rev Plant Biol. 2006;57:233–66. https://doi.org/10.1146/annurev.arplant.57.032905.105159.

    Article  CAS  PubMed  Google Scholar 

  12. Bakker PAHM, Berendsen RL, Doornbos RF, Wintermans PCA, Pieterse CMJ. The rhizosphere revisited: root microbiomics. Front Plant Sci. 2013;4:165. https://doi.org/10.3389/fpls.2013.00165.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Banerjee S, Schlaeppi K, van der Heijden MGA. Keystone taxa as drivers of microbiome structure and functioning. Nat Rev Microbiol. 2018;16:567–76. https://doi.org/10.1038/s41579-018-0024-1.

    Article  CAS  PubMed  Google Scholar 

  14. Barret M, Briand M, Bonneau S, Préveux A, Valière S, Bouchez O, Hunault G, Simoneau P, Jacques M-A. Emergence shapes the structure of the seed microbiota. Appl Environ Microbiol. 2015;81:1257–66. https://doi.org/10.1128/AEM.03722-14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Bartoli C, Frachon L, Barret M, Rigal M, Huard-Chauveau C, Mayjonade B, Zanchetta C, Bouchez O, Roby D, Carrère S, Roux F. In situ relationships between microbiota and potential pathobiota in Arabidopsis thaliana. ISME J. 2018;12:2024–38. https://doi.org/10.1038/s41396-018-0152-7.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Beilsmith K, Perisin M, Bergelson J. Natural bacterial assemblages in Arabidopsis thaliana become more distinguishable and diverse during host development. mBio. 2021;12:e02723-20. https://doi.org/10.1128/mBio.02723-20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Berendsen RL, Pieterse CM, Bakker PAHM. The rhizosphere microbiome and plant health. Trends Plant Sci. 2012;17:478–86. https://doi.org/10.1016/j.tplants.2012.04.001.

    Article  CAS  PubMed  Google Scholar 

  18. Berendsen RL, Vismans G, Yu K, Song Y, de Jonge R, Burgman WP, Burmølle M, Herschend J, Bakker PAHM, Pieterse CMJ. Disease-induced assemblage of a plant-beneficial bacterial consortium. ISME J. 2018;12:1496–507. https://doi.org/10.1038/s41396-018-0093-1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Berens ML, Wolinska KW, Spaepen S, Ziegler J, Nobori T, Nair A, Krüler V, Winkelmüller TM, Wanf Y, Mine A, Becker D, Garrido-Oter R, Schulze-Lefert P, Tsuda K. Balancing trade-offs between biotic and abiotic stress responses through leaf age-dependent variation in stress hormone cross-talk. Proc Natl Acad Sci. 2019;116:2364–73. https://doi.org/10.1073/pnas.1817233116.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Bergelson J, Mittelstrass JM, Horton MW. Characterizing both bacteria and fungi improves understanding of the Arabidopsis root microbiome. Sci Rep. 2019;9:24. https://doi.org/10.1038/s41598-018-37208-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Bieker VC, Sánchez Barreiro F, Rasmussen JA, Brunier M, Wales N, Martin MD. Metagenomic analysis of historical herbarium specimens reveals a postmortem microbial community. Mol Ecol Resour. 2020;20:1206–19. https://doi.org/10.1111/1755-0998.13174.

    Article  CAS  PubMed  Google Scholar 

  22. Boachon B, Burdloff Y, Ruan J-K, Rojo R, Junker RR, Vincent B, Nicolè F, Bringel F, Lesot A, Henry L, Bassrad J-E, Mathieu S, Allouche L, Kaplan I, Dudareva N, Vuilleumier S, Miesch L, André F, Navrot N, Chen X-Y, Werck-Reichhart D. A promiscuous CYP706A3 reduces terpene volatile emission fron Arabidopsis flowers, affecting florivores and the floral microbiome. Plant Cell. 2019;31:2947–72. https://doi.org/10.1105/tpc.19.00320.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Bodenhausen N, Horton MW, Bergelson J. Bacterial communities associated with the leaves and roots of Arabidopsis thaliana. PLoS ONE. 2013;8(2):e56329. https://doi.org/10.1371/journal.pone.0056329.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Bodenhausen N, Bortfeld-Miller M, Ackermann M, Vorholt JA. A synthetic community approach reveals plant genotypes affecting the phyllosphere microbiota. PLoS Genet. 2014;10(4):e1004283. https://doi.org/10.1371/journal.pgen.1004283.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Bodenhausen N, Somerville V, Desirò A, Walser J-C, Broghi L, van der Heijden MGA, Schlaeppi K. Petunia-and Arabidopsis-specific root microbiota responses to phosphate supplementation. Pythobiomes J. 2019;3:112–24. https://doi.org/10.1094/PBIOMES-12-18-0057-R.

    Article  Google Scholar 

  26. Bordenstein SR, Theis KR. Host biology in light of the microbiome: Ten principles of holobionts and hologenomes. PLoS Biol. 2015;13:e1002226. https://doi.org/10.1371/journal.pbio.1002226.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Brachi B, Filiault D, Whitehurst H, Darme P, Le Gars P, Le Mentec M, Morton TC, Kerdaffrec E, Rabanal F, Anastasio A, Box MS, Duncan S, Huang F, Leff R, Novikova P, Perisin M, Tsuchimatsu T, Woolley R, Dean C, Nordborg M, Holm S, Bergelson J. Plant genetic effects on microbial hubs impact fitness across field trials. Proc Natl Acad Sci. 2022;119:e2201285119. https://doi.org/10.1073/pnas.2201285119.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Bressan M, Roncato M-A, Bellvert F, Comte G, Haichar FZ, Achouak W, Berge O. Exogenous glucosinolate produced by Arabidopsis thaliana has an impact on microbes in the rhizosphere and plant roots. ISME J. 2009;3:1243–57. https://doi.org/10.1038/ismej.2009.68.

    Article  CAS  PubMed  Google Scholar 

  29. Broeckling CD, Broz AK, Bergelson J, Manter DK, Vivanco JM. Root exudates regulate soil fungal community composition and diversity. Appl Environ Microbiol. 2008;71:738–44. https://doi.org/10.1128/AEM.02188-07.

    Article  CAS  Google Scholar 

  30. Bulgarelli D, Rott M, Schlaeppi K, Loren V, van Themaat E, Ahmadinejad N, Assenza F, Rauf P, Huettel B, Reinhardt R, Schmelzer E, Peplies J, Gloeckner FO, Amann R, Eickhorst T, Schulze-Lefert P. Revealing structure and assembly cues for Arabidopsis root-inhabiting bacterial microbiota. Nature. 2012;488:91–5. https://doi.org/10.1038/nature11336.

    Article  CAS  PubMed  Google Scholar 

  31. Bulgarelli D, Schlaeppi K, Spaepen S, van Themaat EVL, Schulze-Lefert P. Structure and functions of the bacterial microbiota of plants. Annu Rev Plant Biol. 2013;64:807–38. https://doi.org/10.1146/annurev-arplant-050312-120106.

    Article  CAS  PubMed  Google Scholar 

  32. Carlström CI, Field CM, Bortfeld-Miller M, Müller B, Sunagawa S, Vorholt J. Synthetic microbiota reveal priority effects and keystone strains in the Arabidopsis phyllosphere. Nat Ecol Evol. 2019;3:1445–54. https://doi.org/10.1038/s41559-019-0994-z.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Carvalhais LC, Dennis PG, Badri DV, Tyson GW, Vivanco JM, Schenk PM. Activation of the jasmonic acid plant defence pathway alters the composition of rhizosphere bacterial communities. PloS ONE. 2013;8:e56457. https://doi.org/10.1371/journal.pone.0056457.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Carvalhais LC, Dennis PG, Badri DV, Kidd BN, Vivanco JM, Schenk PM. Linking jasmonic acid signaling, root exudates, and rhizosphere microbiomes. Mol Plant Microbe Interact. 2015;28:1049–58. https://doi.org/10.1094/MPMI-01-15-0016-R.

    Article  CAS  PubMed  Google Scholar 

  35. Carvalhais LC, Rincon-Florez VA, Brewer PB, Beveridge CA, Dennis PG, Schenk PM. The ability of plants to produce strigolactones affects rhizosphere community composition of fungi but not bacteria. Rhizosphere. 2019;9:18–26. https://doi.org/10.1016/j.rhisph.2018.10.002.

    Article  Google Scholar 

  36. Castrillo G, Lima Teixeira PJP, Herrera Paredes S, Law TF, de Lorenzo L, Feltcher ME, Finkel OM, Breakfield NW, Mieczkowski P, Jones CD, Paz-Ares J, Dangl JL. Root microbiota drive direct integration of phosphate stress and immunity. Nature. 2017;543:513–8. https://doi.org/10.1038/nature21417.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Chang C, Bowman JL, Meyerowitz EM. Field guide to plant model systems. Cell. 2016;167:325–39. https://doi.org/10.1016/j.cell.2016.08.031.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Chaparro JM, Badri DV, Bakker MG, Sugiyama A, Manter DK, Vivanco JM. Root exudation of phytochemicals in Arabidopsis follows specific patterns that are developmentally programmed and correlate with soil microbial functions. PloS ONE. 2013;8:e55731. https://doi.org/10.1371/journal.pone.0055731.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Chaparro JM, Badri DV, Vivanco JM. Rhizosphere microbiome assemblage is affected by plant development. ISME J. 2014;8:790–803. https://doi.org/10.1038/ismej.2013.196.

    Article  CAS  PubMed  Google Scholar 

  40. Chen T, Nomura K, Wang X, Sohrabi R, Xu J, Yao L, Paasch BC, Ma Li, Kremer J, Cheng Y, Zhang L, Wang N, Wang E, Xin X-F, He SY. A plant genetic network for preventing dysbiosis in the phyllosphere. Nature. 2020;580:653–7. https://doi.org/10.1038/s41586-020-2185-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Chesneau G, Laroche B, Préveaux A, Marais C, Briand M, Marolleau B, Simonin M, Barret M. Single seed microbiota: assembly and transmission from parent plant to seedling. MBio. 2022;13(6):1–17. https://doi.org/10.1128/mbio.01648-22.

    Article  CAS  Google Scholar 

  42. Claveró-León C, Ruiz D, Cillero J, Orlando J, González B. The multi metal-resistant bacterium Cupriavidus metallidurans CH34 affects growth and metal mobilization in Arabidopsis thaliana plants exposed to copper. PeerJ. 2021;9:e11373. https://doi.org/10.7717/peerj.11373/supp-3.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Compant S, Cambon MC, Vacher C, Mitter B, Samad A, Sessitsch A. The plant endosphere world–bacterial life within plants. Environ Microbiol. 2021;23:1812–29. https://doi.org/10.1111/1462-2920.15240.

    Article  PubMed  Google Scholar 

  44. Conway JM, Walton WG, Salas-González I, Law TF, Lindberg CA, Crook LE, Kosina SM, Fitzpatrick CR, Lietzan AD, Northen TR, Jones CD, Finkel OM, Redinbo MR, Dangl JL. Diverse MarR bacterial regulators of auxin catabolism in the plant microbiome. Nat Microbiol. 2022;7:1817–33. https://doi.org/10.1038/s41564-022-01244-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Delmotte N, Knief C, Chaffron S, Innerebner G, Roschitzki B, Schlapbach R, von Mering C, Vorholt JA. Community proteogenomics reveal into the physiology of phyllosphere bacteria. Proc Natl Acad Sci. 2009;106:16428–33. https://doi.org/10.1073/pnas.0905240106.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Dibner RR, Weaver AM, Brock MT, Custer GF, Morrison HG, Maignien L, Weinig C. Time outweighs the effect of host development stage on microbial community composition. FEMS Microb Ecol. 2021;97:fiab102. https://doi.org/10.1093/femsec/fiab102.

    Article  CAS  Google Scholar 

  47. Dombrowski N, Schlaeppi K, Agler MT, Hacquard S, Kemen E, Garrido-Oter R, Wunder J, Coupland G, Schulze-Lefert P. Root microbiota dynamics of perennial Arabis alpina are dependent on soil residence time but independent of flowering time. ISME J. 2017;11:43–55. https://doi.org/10.1038/ismej.2016.109.

    Article  CAS  PubMed  Google Scholar 

  48. Doornbos RF, Geraats BPJ, Kuramae EE, Van Loon LC, Bakker PAHM. Effects of jasmonic acid, ethylene, and salicylic acid signaling on the rhizosphere bacterial community of Arabidopsis thaliana. Mol Plant Microbe Interact. 2011;24:395–407. https://doi.org/10.1094/MPMI-05-10-0115.

    Article  CAS  PubMed  Google Scholar 

  49. Dumack K, Sapp M, von Steimker T, Mänz AT, Rose LE, Bonkowski M. A call for research: a resource of core microbial symbionts of the Arabidopsis thaliana microbiome ready and awaiting experimental exploration. Phytobiomes J. 2021;5:362–6. https://doi.org/10.1094/PBIOMES-11-20-0080-A.

    Article  Google Scholar 

  50. Durán P, Thiergart T, Garrido-Oter R, Agler M, Kemen E, Schulze-Lefert P, Hacquard S. Microbial interkingdom interactions in roots promote Arabidopsis survival. Cell. 2018;175:973–83. https://doi.org/10.1016/j.cell.2018.10.020.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Durán P, Reinstädler A, Rajakrut AL, Hashimoto M, Garrido-Oter R, Schulze-Lefert P, Panstruga R. A fungal powdery mildew pathogen induces extensive and marginal systemic changes in the Arabidopsis thaliana microbiota. Environ Microbiol. 2021;23:6292–308. https://doi.org/10.1111/1462-2920.15768.

    Article  CAS  PubMed  Google Scholar 

  52. Durán P, Flores-Uribe J, Wippel K, Zhang P, Guan R, Melkonian B, Melkonian M, Garrido-Oter R. Shared features and reciprocal complementation of the Chlamydomonas and Arabidopsis microbiota. Nat Commun. 2022;13:403. https://doi.org/10.1038/s41467-022-28055-8.

    Article  CAS  Google Scholar 

  53. Durán P, Ellis TJ, Thiergart T, Ågren J, Hacquard S. Climate drives rhizosphere microbiome variation and divergent selection between geographically distant Arabidopsis populations. New Phytol. 2022;236:608–21. https://doi.org/10.1111/nph.18357.

    Article  CAS  PubMed  Google Scholar 

  54. Durr J, Reyt G, Spaepen S, Hilton S, Meehan C, Qi W, Kamiya T, Fis P, Dickingson HG, Feher A, Shivshankar U, Pavgadhi S, Swarup S, Salt D, Bending GD, Gutierrez-Marcos J. A novel signaling pathway required for Arabidopsis endodermal root organization shapes the rhizosphere microbiome. Plant Cell Physiol. 2021;62:248–61. https://doi.org/10.1093/pcp/pcaa170.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Eckshtain-Levi N, Harris SL, Roscios RQ, Shank EA. Bacterial community members increase Bacillus subtilis maintenance on the roots of Arabidopsis thaliana. Phytobiomes J. 2020;4:303–13. https://doi.org/10.1094/PBIOMES-02-20-0019-R.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Emonet A, Zhou F, Vacheron J, Heiman CM, Dénervaud Tendon V, Ma K-W, Schulze-Lefert P, Keel C, Geldner N. Spatially restricted immune responses are required for maintaining root meristematic activity upon detection of bacteria. Curr Biol. 2021;31:1012–28. https://doi.org/10.1016/j.cub.2020.12.048.

    Article  CAS  PubMed  Google Scholar 

  57. Etemadi M, Zuther E, Müller H, Hincha DK, Berg G. Ecotype-dependent response of bacterial communities associated with Arabidopsis to cold acclimation. Phytobiomes J. 2018;2:3–13. https://doi.org/10.1094/PBIOMES-04-17-0015-R.

    Article  Google Scholar 

  58. Fabiańska I, Gerlach N, Almario J, Bucher M. Plant-mediated effects of soil phosphorus on the root-associated fungal microbiota in Arabidopsis thaliana. New Phytol. 2019;221:2123–37. https://doi.org/10.1111/nph.15538.

    Article  CAS  PubMed  Google Scholar 

  59. Finkel OM, Castrillo G, Herrera Paredes S, Salas González I, Dangl JL. Understanding and exploiting plant beneficial microbes. Curr Opin Plant Biol. 2017;38:155–63. https://doi.org/10.1016/j.pbi.2017.04.018.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Finkel OM, Salas-González I, Castrillo G, Spaepen S, Law TF, Teixeira PJPL, Jones D, Dangl JL. The effects of soil phosphorous content on plant microbiota are driven by the plant phosphate starvation response. PLoS Biol. 2019;17(11):e3000534. https://doi.org/10.1371/journal.pbio.3000534.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Finkel OM, Salas-González I, Castrillo G, Conway JM, Law TF, Teixeira PJPL, Wilson ED, Fitzpatrick CR, Jones CD, Dangl JL. A single bacterial genus maintains root growth in a complex microbiome. Nature. 2020;587:103–8. https://doi.org/10.1038/s41586-020-2778-7.

    Article  CAS  PubMed  Google Scholar 

  62. Fitzpatrick CR, Salas-González I, Conway JM, Finkel OM, Gilbert S, Russ D, Teixeira PJPL, Dangl JL. The plant microbiome: from ecology to reductionism and beyond. Annu Rev Microbiol. 2020;74:81–100. https://doi.org/10.1146/annurev-micro-022620-014327.

    Article  CAS  PubMed  Google Scholar 

  63. Fromin N, Achouak W, Thiéry JM, Heulin T. The genotypic diversity of Pseudomonas brassicacearum populations isolated from roots of Arabidopsis thaliana: influence of plant genotype. FEMS Microbiol Ecol. 2001;37:21–9. https://doi.org/10.1111/j.1574-6941.2001.tb00849.x.

    Article  CAS  Google Scholar 

  64. Garrido-Oter R, Nakano RT, Dombrowski N, Ma K-W, McHardy AC, Schulze-Lefert P, The AgBiome Team. Modular traits of the rhizobiales root microbiota and their evolutionary relationship with symbiotic rhizobia. Cell Host Microbe. 2018;24:155–67. https://doi.org/10.1016/j.chom.2018.06.006.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Hacquard S, Garrido-Oter R, González A, Spaepen S, Ackermann G, Lebeis S, McHardy AC, Dangl JL, Knight R, Ley R, Schulze-Lefert P. Microbiota and host nutrition across plant and animal kingdoms. Cell Host Microbe. 2015;17:603–16. https://doi.org/10.1016/j.chom.2015.04.009.

    Article  CAS  PubMed  Google Scholar 

  66. Hacquard S, Spaepen S, Garrido-Oter R, Schulze-Lefert P. Interplay between innate immunity and the plant microbiota. Annu Rev Phytopathol. 2017;55:565–89. https://doi.org/10.1146/annurev-phyto-080516-035623.

    Article  CAS  PubMed  Google Scholar 

  67. Haichar FZ, Roncato MA, Achouak W. Stable isotope probing of bacterial community structure and gene expression in the rhizosphere of Arabidopsis thaliana. FEMS Microbiol Ecol. 2012;81:291–302. https://doi.org/10.1111/j.1574-6941.2012.01345.x.

    Article  CAS  PubMed  Google Scholar 

  68. Haney CH, Samuel BS, Bush J, Ausubel FM. Associations with rhizosphere bacteria can confer an adaptive advantage to plants. Nat Plants. 2015;1:15051. https://doi.org/10.1038/nplants.2015.51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Harbort CJ, Hashimoto M, Inoue H, Niu Y, Guan R, Rombolà AD, Kopriva S, Voges MJEEE, Sattely ES, Garrido-Oter R, Schulze-Lefert P. Root-secreted coumarins and the microbiota interact to improve iron nutrition in Arabidopsis. Cell Host Microbe. 2020;28:825–37. https://doi.org/10.1016/j.chom.2020.09.006.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Hardoim PR, van Overbeek LS, Berg G, Pirttilä AM, Compant S, Campisano A, Döring M, Sessitsch A. The hidden world within plants: ecological and evolutionary considerations for defining functioning of microbial endophytes. Microbiol Mol Biol Rev. 2015;79:293–320. https://doi.org/10.1128/MMBR.00050-14.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Harris JM, Balint-Kurti P, Bede JC, Day B, Gold S, Goss EM, Grenville-Briggs LJ, Jones KM, Wang A, Wang Y, Mitra RM, Sohn KH, Alvarez MA. What are the top 10 unanswered questions in molecular plant-microbe interactions? Mol Plant Microbe Interact. 2020;33:1354–65. https://doi.org/10.1094/MPMI-08-20-0229-CR.

    Article  CAS  PubMed  Google Scholar 

  72. Hassani MA, Duran P, Hacquard S. Microbial interactions within the plant holobiont. Microbiome. 2018;6:58. https://doi.org/10.1186/s40168-018-0445-0.

    Article  PubMed  PubMed Central  Google Scholar 

  73. He X, Zhang Q, Li B, Jin Y, Jiang L, Wu R. Network mapping of root-microbe interactions in Arabidopsis thaliana. npj Biofilms Microbiomes. 2021;7:72. https://doi.org/10.1038/s41522-021-00241-4.

    Article  PubMed  PubMed Central  Google Scholar 

  74. He D, Singh SK, Peng L, Kaushal R, Vílchez JI, Shao C, Wu X, Zheng S, Morcillo RJL, Paré PW, Zhang H. Flavonoid-attracted Aeromonas sp. from the Arabidopsis root microbiome enhances plant dehydration resistance. ISME J. 2022;16:2622–32. https://doi.org/10.1038/s41396-022-01288-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Hein JW, Wolfe GV, Blee KA. Comparison of rhizosphere bacterial communities in Arabidopsis thaliana mutants for systemic acquired resistance. Microb Ecol. 2008;55:333–43. https://doi.org/10.1007/s00248-007-9279-1.

    Article  CAS  PubMed  Google Scholar 

  76. Helfrich EJN, Vogel CM, Ueoka R, Schäfer M, Ryffel F, Müller DB, Probst S, Kreuzer M, Piel J, Vorholt JA. Bipartite interactions, antibiotic production, and biosynthetic potential of the Arabidopsis leaf microbiome. Nat Microbiol. 2018;3:909–19. https://doi.org/10.1038/s41564-018-0200-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Herrera Paredes S, Gao T, Law TF, Finkel OM, Mucyn T, Teixeira PJPL, Salas González I, Feltcher ME, Powers MJ, Shank EA, Jones CD, Jojic V, Dangl JL, Castrillo G. Design of synthetic bacterial communities for predictable plant phenotypes. PLoS Biol. 2018;16(2):e2003962. https://doi.org/10.1371/journal.pbio.2003962.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Horton MW, Bodenhausen N, Beilsmith K, Meng D, Muegge BD, Subramanian S, Madlen Vetter M, Vilhjálmsson BJ, Nordborg M, Gordon JI, Bergelson J. Genome-wide association study of Arabidopsis thaliana leaf microbial community. Nat Commun. 2014;5:5320. https://doi.org/10.1038/ncomms6320.

    Article  PubMed  Google Scholar 

  79. Hou S, Thiergart T, Vannier N, Mesny F, Ziegler J, Pickel B, Hacquard S. A microbiota-root-shoot circuit favours Arabidopsis growth over defence under suboptimal light. Nat Plants. 2021;7:1078–92. https://doi.org/10.1038/s41477-021-00956-4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Hou S, Wolinska KW, Hacquard S. Microbiota-root-shoot-environment axis and stress tolerance in plants. Curr Opin Plant Biol. 2021;62:102028. https://doi.org/10.1016/j.pbi.2021.102028.

    Article  CAS  PubMed  Google Scholar 

  81. Huang AC, Jiang T, Liu Y-X, Bai Y-C, Reed J, Qu B, Goossens A, Nützmann H-W, Bai Y, Ossbourn A. A specialized metabolic network selectively modulates Arabidopsis root microbiota. Science. 2019;364:eaau6389. https://doi.org/10.1126/science.aau6389.

    Article  CAS  PubMed  Google Scholar 

  82. Hubbard CJ, Brock MT, van Diepen LTA, Maignien L, Ewers BE, Weining C. The plant circadian clock influences rhizosphere community structure and function. ISME J. 2018;12:400–10. https://doi.org/10.1038/ismej.2017.172.

    Article  PubMed  Google Scholar 

  83. Hubbard CJ, McMinn R, Weinig C. Rhizosphere microbes influence host circadian clock function. Phytobiomes J. 2021;5:368–72. https://doi.org/10.1094/PBIOMES-01-21-0005-SC.

    Article  Google Scholar 

  84. Jacoby RP, Koprivova A, Kopriva S. Pinpointing secondary metabolites that shape the composition and function of the plant microbiome. J Exp Bot. 2021;72:57–69. https://doi.org/10.1093/jxb/eraa424.

    Article  CAS  PubMed  Google Scholar 

  85. Johnston-Monje D, Gutiérrez JP, Becerra López-Lavalle LA. Seed-transmitted bacteria and fungi dominate juvenile plant microbiomes. Front Microbiol. 2021;12:737616. https://doi.org/10.3389/fmicb.2021.737616.

    Article  PubMed  PubMed Central  Google Scholar 

  86. Johnston-Monje D, Gutiérrez JP, Becerra López-Lavalle LA. Stochastic inoculum, biotic filtering and species-specific seed transmission shape the rare microbiome of plants. Life. 2022;12:1372. https://doi.org/10.3390/life12091372.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Kaushal R, Peng L, Singh SK, Zhang M, Zhang X, Vílchez JI, Wang Z, He D, Yang Y, Lv S, Xu Z, Morcillo RJL, Wang W, Huang W, Paré PW, Song C-P, Zhu J-K, Liu R, Zhong W, Ma P, Zhang H. Dicer-like proteins influence Arabidopsis root microbiota independent of RNA-directed DNA methylation. Microbiome. 2021;9:57. https://doi.org/10.1186/s40168-020-00966-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Ke M, Ye Y, Li Y, Zhou Z, Xu N, Feng L, Zhang J, Lu T, Cai Z, Qian H. Leaf metabolic influence of glyphosate and nanotubes on the Arabidopsis thaliana phyllosphere. J Environ Sci. 2021;106:66–75. https://doi.org/10.1016/j.jes.2021.01.002.

    Article  CAS  Google Scholar 

  89. Knief C, Frances L, Vorholt JA. Competitiveness of diverse Methylobacterium strains in the phyllosphere of Arabidopsis thaliana and identification of representative models, including M. extorquens PA1. Microb Ecol. 2010;60:440–52. https://doi.org/10.1007/s00248-010-9725-3.

    Article  PubMed  Google Scholar 

  90. Knief C, Ramette A, Frances L, Alonso-Blanco C, Vorholt JA. Site and plant species are important determinants of the Methylobacterium community composition in the plant phyllosphere. ISME J. 2010;4:719–28. https://doi.org/10.1038/ismej.2010.9.

    Article  CAS  PubMed  Google Scholar 

  91. Kniskern JM, Traw MB, Bergelson J. Salicylic acid and jasmonic acid signaling defense pathways reduce natural bacterial diversity on Arabidopsis thaliana. Mol Plant Microbe Interact. 2007;20:1512–22. https://doi.org/10.1094/MPMI-20-12-1512.

    Article  CAS  PubMed  Google Scholar 

  92. Koornneef M, Meinke D. The development of Arabidopsis as a model plant. Plant J. 2010;61:909–21. https://doi.org/10.1111/j.1365-313X.2009.04086.x.

    Article  CAS  PubMed  Google Scholar 

  93. Koskella B, Taylor TB. Multifaceted impacts of bacteriophages in the plant microbiome. Annu Rev Phytopathol. 2018;56:361–80. https://doi.org/10.1146/annurev-phyto-080417-045858.

    Article  CAS  PubMed  Google Scholar 

  94. Kraiser T, Gras DE, Gutiérrez AG, González B, Gutiérrez RA. A holistic view of nitrogen acquisition in plants. J Exp Bot. 2011;62:1455–66. https://doi.org/10.1093/jxb/erq425.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Kremer JM, Sohrabi R, Paasch BC, Rhodes D, Thireault C, Schulze-Lefert P, Tiedje JM, He SY. Peat-based gnotobiotic plant growth systems for Arabidopsis microbiota research. Nature Prot. 2021;16:2450–70. https://doi.org/10.1038/s41596-021-00504-6.

    Article  CAS  Google Scholar 

  96. Krome K, Rosenberg K, Bonkowski M, Scheu S. Grazing of protozoa on rhizosphere bacteria alters growth and reproduction of Arabidopsis thaliana. Soil Biol Biochem. 2009;41:1866–73. https://doi.org/10.1016/j.soilbio.2009.06.008.

    Article  CAS  Google Scholar 

  97. Krome K, Rosenberg K, Dickler C, Kreuzer K, Ludwig-Müller J, Ullrich-Eberius C, Scheu S, Bonkowski M. Soil bacteria and protozoa affect root branching via effects on the auxin and cytokinin balance in plants. Plant Soil. 2010;328:191–201. https://doi.org/10.1007/s11104-009-0101-3.

    Article  CAS  Google Scholar 

  98. Kudjordjie EN, Sapkota R, Nicolaisen M. Arabidopsis assemble distinct root-associated microbiomes through the synthesis of an array of defense metabolites. PLoS ONE. 2021;16:e0259171. https://doi.org/10.1371/journalpone.0259171.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Kudjordjie EN, Hooshmand K, Sapkota R, Darbani B, Fomsgaard IS, Nicolaisen M. Fusarium oxysporum disrupts microbiome-metabolome networks in Arabidopsis thaliana roots. Microbiol Spectr. 2022;10(4):1–20. https://doi.org/10.1128/spectrum.01226-22.

    Article  CAS  Google Scholar 

  100. Lau JA, Lennon JT. Rapid responses of soil microorganisms improve plant fitness in novel environments. Proc Natl Acad Sci. 2012;109:14058–62. https://doi.org/10.1073/pnas.2118690118.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Lebeis SL, Herrera Paredes S, Lundberg DS, Breakfield N, Gehring J, McDonald M, Malfatti S, Glavina del Rio T, Jones CD, Tringe SG, Dangl JL. Salicylic acid modulates colonization of the root microbiome by specific bacterial taxa. Science. 2015;349:860–4. https://doi.org/10.1126/science.aaa8764.

    Article  CAS  PubMed  Google Scholar 

  102. Ledger T, Zúñiga A, Kraiser T, Dasencich P, Donoso R, Pérez-Pantoja D, González B. Aromatic compounds degradation plays a role in colonization of Arabidopsis thaliana and Acacia caven by Cupriavidus pinatubonensis JMP134. Antonie van Leeuwenhoek. 2012;101:713–23. https://doi.org/10.1007/s10482-011-9685-8.

    Article  CAS  PubMed  Google Scholar 

  103. Ledger T, Rojas S, Timmermann T, Pinedo I, Poupin MJ, Garrido T, Richter P, Tamayo J, Donoso R. Volatile-mediated effects predominate in Paraburkholderia phytofirmans growth promotion and salt stress tolerance of Arabidopsis thaliana. Front Microbiol. 2016;7:1838. https://doi.org/10.3389/fmicb.2016.01838.

    Article  PubMed  PubMed Central  Google Scholar 

  104. Levy A, Conway JM, Dangl JL, Woyke T. Elucidating bacterial gene functions in the plant microbiome. Cell Host Microbe. 2018;24:475–85. https://doi.org/10.1016/j.chom.2018.09.005.

    Article  CAS  PubMed  Google Scholar 

  105. Levy A, Salas González I, Mittelviefhaus M, Clingenpeel S, Herrera Paredes S, Miao J, Wang K, Devescovi G, Stillman K, Monteiro F, Rangel Alvarez B, Lundberg DS, Lu T-Y, Lebeis S, Jin Z, McDonald M, Klein AP, Feltcher ME, Glavina Rio T, Grant SR, Doty SL, Ley RE, Zhao B, Venturi V, Pelletier DA, Vorholt JA, Tringe SG, Woyke T, Dangl JL. Genomic features of bacterial adaptation to plants. Nat Genet. 2018;50:138–50. https://doi.org/10.1038/s41588-017-0012-9.

    Article  CAS  Google Scholar 

  106. Li Y, Zhang Z, Liu W, Ke M, Qu Q, Zhou Z, Lu T, Qian H. Phyllosphere bacterial assemblage is affected by plant genotypes and growth stages. Microbiol Res. 2021;248:126743. https://doi.org/10.1016/j.micres.2021.126743.

    Article  CAS  PubMed  Google Scholar 

  107. Li K, Cheng K, Wang H, Zhang Q, Yang Y, Jin Y, He X, Wu R. Disentangling leaf-microbiome interactions in Arabidopsis thaliana by network mapping. Front Plant Sci. 2022;13:996121. https://doi.org/10.3389/fpls.2022.996121.

    Article  PubMed  PubMed Central  Google Scholar 

  108. Liu W, Ke M, Zhang Z, Lu T, Zhu Y, Li Y, Pan X, Qian H. Effects of imazethapyr spraying on plant growth and leaf surface microbial communities in Arabidopsis thaliana. J Env Sci. 2019;85:35–45. https://doi.org/10.1016/j.jes.2019.04.020.

    Article  CAS  Google Scholar 

  109. Liu Y-X, Qin Y, Bai Y. Reductionist synthetic community approaches in root microbiome research. Curr Opin Microbiol. 2019;49:97–102. https://doi.org/10.1016/j.mib.2019.10.010.

    Article  CAS  PubMed  Google Scholar 

  110. Liu H, Hu W, Li X, Hu F, Liu Y, Xie T, Liu B, Xi Y, Su Z, Zhang C. Effects of perfluoroalkyl substances on root and rhizosphere bacteria: phytotoxicity, phyto-microbial remediation, risk assessment. Chemosphere. 2022;289:133137. https://doi.org/10.1016/j.chemosphere.2021.133137.

    Article  CAS  PubMed  Google Scholar 

  111. Lu T, Ke M, Lavoie M, Jin Y, Fan X, Zhang Z, Fu Z, Sun L, Gillings M, Peñuelas J, Qian H, Zhu Y-G. Rhizosphere microorganisms can influence the timing of plant flowering. Microbiome. 2018;6:231. https://doi.org/10.1186/s40168-018-0615-0.

    Article  PubMed  PubMed Central  Google Scholar 

  112. Lu T, Zhang Z, Li Y, Zhang Q, Cui H, Sun L, Peijnenburg WJGM, Peñuelas J, Zhu L, Zhu Y-G, Chen J, Qian H. Does biological rhythm transmit from plants to rhizosphere microbes? Environ Microbiol. 2021;23:6895–906. https://doi.org/10.1111/1462-2920.15820.

    Article  CAS  PubMed  Google Scholar 

  113. Lucaciu R, Pelikan C, Gerner SM, Zioutis C, Köstlbacher S, Marx H, Herbold CW, Schmidt H, Rattei T. A bioinformatics guide to plant microbiome analysis. Front Plant Sci. 2019;10:1313. https://doi.org/10.3389/fpls.2019.01313.

    Article  PubMed  PubMed Central  Google Scholar 

  114. Lugtenberg B, Kamilova F. Plant-growth-promoting rhizobacteria. Annu Rev Microbiol. 2009;63:541–56. https://doi.org/10.1146/annurev.micro.62.081307.162918.

    Article  CAS  PubMed  Google Scholar 

  115. Lundberg DS, Lebeis SL, Herrera Paredes S, Yourstone S, Gehring J, Malfatti S, Tremblay J, Engelbrektson A, Kunin V, Glavina del Rio T, Edgar RC, Eickhorst T, Ley RE, Hugenholtz P, Tringe SG, Dangl JL. Defining the core Arabidopsis thaliana root microbiome. Nature. 2012;488:86–90. https://doi.org/10.1038/nature11237.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Lundberg DS, Ayutthaya PPN, Strauß A, Shirsekar G, Lo W-S, Lahaye T, Weigel D. Host-associated microbe PCR (hamPCR) enables convenient measurement of both microbial load and community composition. eLife. 2021;10:e66186. https://doi.org/10.7554/eLife.66186.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Luo Y, Wang F, Huang Y, Zhou M, Gao J, Yan T, Sheng H, An L. Sphingomonas sp. Cra20 increases plant growth rate and alters rhizosphere microbial community structure of Arabidopsis thaliana under drought stress. Front Microbiol. 2019;10:1221. https://doi.org/10.3389/fmicb.2019.01221.

    Article  PubMed  PubMed Central  Google Scholar 

  118. Lv S, Yang Y, Yu G, Peng L, Zheng S, Singh SK, Vílchez JI, Kaushal R, Zi H, Yi D, Wang Y, Luo S, Wu X, Zuo Z, Huang W, Liu R, Du J, Macho AP, Tang K, Zhang H. Dysfunction of histone demethylase IBM1 in Arabidopsis causes autoimmunity and reshapes the root microbiome. ISME J. 2022;16:2513–24. https://doi.org/10.1038/s41396-022-01297-6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Ma K-W, Niu Y, Jia Y, Ordon J, Copeland C, Emonet A, Geldner N, Guan R, Stolze SC, Nakagami H, Garrido-Oter R, Schulze-Lefert P. Coordination of microbe-host homeostasis by crosstalk with plant innate immunity. Nat Plants. 2021;7:814–25. https://doi.org/10.1038/s41477-021-00920-2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Ma K-W, Ordon J, Schulze-Lefert P. Gnotobiotic plant systems for reconstitution and functional studies of the root microbiota. Curr Protocols. 2022;2:e362. https://doi.org/10.1002/cpz1.362.

    Article  CAS  Google Scholar 

  121. Maciá-Vicente JG, Bai B, Qi R, Ploch S, Breider F, Thines M. Nutrient availability does not affect community assembly in root-associated fungi but determines fungal effects on plant growth. mSystems. 2022;7:1–14. https://doi.org/10.1128/msystems.00304-22.

    Article  CAS  Google Scholar 

  122. Mahdi LK, Miyauchi S, Uhlmann C, Garrido-Oter R, Langen G, Wawra S, Niu Y, Guan R, Robertson-Abertyn S, Bulgarelli D, Parker JE, Zuccaro A. The fungal root endophyte Serendipita vermifera displays inter-kingdom synergistic beneficial effects with the microbiota in Arabidopsis thaliana and barley. ISME J. 2022;16:876–89. https://doi.org/10.1038/s41396-021-01138-y.

    Article  CAS  PubMed  Google Scholar 

  123. Maier BA, Kiefer P, Field CM, Hemmerle L, Bortfeld-Miller M, Emmenegger B, Schäfer M, Pfeilmeier S, Sunagawa S, Vogel CM, Vorholt JA. A general non-self response as part of plant immunity. Nat Plants. 2021;7:696–705. https://doi.org/10.1038/s41477-021-00913-1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Maignien L, DeForce EA, Chafee ME, Eren AM, Simmons SL. Ecological succession and stochastic variation in the assembly of Arabidopsis thaliana phyllosphere communities. MBio. 2014;5(1):e00682-13. https://doi.org/10.1128/mBio.00682-13.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Marín O, González B, Poupin MJ. From microbial dynamics to functionality in the rhizosphere: a systematic review of the opportunities with synthetic microbial communities. Front Plant Sci. 2021;12:650659. https://doi.org/10.3389/fpls.2021.650609.

    Article  Google Scholar 

  126. Massoni J, Bortfeld-Miller M, Widmer A, Vorholt JA. Capacity of soil bacteria to reach the phyllosphere and convergence of floral communities despite soil microbiota variation. Proc Natl Acad Sci. 2021;118:e2100150118. https://doi.org/10.1073/pnas.2100150118.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Mataigne V, Vannier N, Vandenkoornhuyse P, Hacquard S. Multi-genome metabolic modeling predicts functional inter-dependencies in the Arabidopsis root microbiome. Microbiome. 2022;10:217. https://doi.org/10.1186/s40168-022-01383-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  128. Mayer T, Mari A, Almario J, Murillo-Roos M, Abdullah HSM, Dombrowski N, Hacquard S, Kemen AM, Agler M. Obtaining deeper insights into microbiome diversity using a simple method to block host and nontargets in amplicon sequencing. Mol Ecol Resour. 2021;21:1952–65. https://doi.org/10.1111/1755-0998.13408.

    Article  PubMed  Google Scholar 

  129. Mehlferber EC, Song MJ, Pelaez JN, Jaenish J, Coate JE, Koskella B, Rothfels CJ. Polyploidy and microbiome associations mediate similar responses to pathogens in Arabidopsis. Curr Biol. 2022;32:2719–29. https://doi.org/10.1016/j.cub.2022.05.015.

    Article  CAS  PubMed  Google Scholar 

  130. Mercier A, Mignerot L, Hennion N, Gravouil K, Porcheron B, Durand M, Maurousset L, Héchard Y, Bertaux J, Ferreira T, Lauga B, Lemoine R, Pourtau N. Growth of Arabidopsis thaliana in rhizobox culture system evaluated through the lens of root microbiome. Plant Soil. 2020;455:467–87. https://doi.org/10.1007/s11104-020-04650-w.

    Article  CAS  Google Scholar 

  131. Mesny F, Miyauchi S, Thiergart T, Pickel B, Atanasova L, Karlsson M, Hüttel B, Barry KW, Haridas S, Chen C, Bauer D, Andreopoulos W, Pangilinan J, LaButti K, Riley R, Lipzen A, Clum A, Drula E, Henrissat B, Kohler A, Grigoriev IG, Martin FM, Hacquard S. Genetic determinants of endophytism in the Arabidopsis root mycobiome. Nature Commun. 2021;12:7227. https://doi.org/10.1038/s41467-021-27479-y.

    Article  CAS  Google Scholar 

  132. Micallef SA, Channer S, Shiaris MP, Colón-Carmona A. Plant age and genotype impact the progression of bacterial community succession in the Arabidopsis rhizosphere. Plant Signal Behav. 2009;4:777–80. https://doi.org/10.4161/psb.4.8.9229.

    Article  PubMed  PubMed Central  Google Scholar 

  133. Micallef SA, Shiaris MP, Colón-Carmona A. Influence of Arabidopsis thaliana accessions on rhizobacterial communities and natural variation in root exudates. J Exp Botany. 2009;60:1729–42. https://doi.org/10.1093/jxb/erp053.

    Article  CAS  Google Scholar 

  134. Mitter B, Pfaffenbichler N, Flavell R, Compant S, Antonielli L, Petric A, Berninger T, Naveed M, Sheibani-Tezerji R, von Maltzahn G, Sessitsch A. A new approach to modify plant microbiomes and traits by introducing beneficial bacteria at flowering into progeny seeds. Front Microbiol. 2017;8:11. https://doi.org/10.3389/fmicb.2017.00011.

    Article  PubMed  PubMed Central  Google Scholar 

  135. del Mora-Ruiz MR, Alejandre-Colomo C, Ledger T, González B, Orfila A, Rosselló-Móra R. Non-halophilic endophytes associated with the euhalophyte Arthrocnemum macrostachyum and their plant growth promoting activity potential. FEMS Microb Lett. 2018;365:208. https://doi.org/10.1093/femsle/fny208.

    Article  CAS  Google Scholar 

  136. Müller DB, Vogel C, Bai Y, Vorholt JA. The plant microbiota: systems-level insights and perspectives. Annu Rev Genet. 2016;50:211–34. https://doi.org/10.1146/annurev-genet-120215-034952.

    Article  CAS  PubMed  Google Scholar 

  137. Nelson EB. The seed microbiome: origins, interactions, and impacts. Plant Soil. 2018;422:7–34. https://doi.org/10.1007/s11104-017-3289-7.

    Article  CAS  Google Scholar 

  138. Newman A, Picot E, Davies S, Hilton S, Carré IA, Bending GD. Circadian rhythms in the plant host influence rhythmicity of rhizosphere microbiota. BMC Biol. 2022;20:235. https://doi.org/10.1186/s12915-022-01430-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  139. Oburger E, Jones DL. Sampling root exudates–mission impossible? Rhizosphere. 2018;6:116–33. https://doi.org/10.1016/j.rhisph.2018.06.004.

    Article  Google Scholar 

  140. Orellana D, Machuca D, Ibeas MA, Estevez JM, Poupin MJ. Plant-growth promotion by proteobacterial strains depends on the availability of phosphorous and iron in Arabidopsis thaliana plants. Front Microbiol. 2002;13:1083270. https://doi.org/10.3389/fmicb.2022.1083270.

    Article  Google Scholar 

  141. Oren A, Garrity GM. Valid publication of the names of forty-two phyla of prokaryotes. Int J Syst Evol Microbiol. 2021;71:005056. https://doi.org/10.1099/ijsem.0.005056.

    Article  Google Scholar 

  142. Panke-Buisse K, Poole AC, Goodrich JK, Ley RE, Kao-Kniffin J. Selection on soil microbiomes reveals reproducible impacts on plant function. ISME J. 2015;9:980–9. https://doi.org/10.1038/ismej.2014.196.

    Article  CAS  PubMed  Google Scholar 

  143. Panke-Buisse K, Lee S, Kao-Kniffin J. Cultivated sub-populations of soil microbiomes retain early flowering plant trait. Microb Ecol. 2017;73:394–403. https://doi.org/10.1007/s00248-016-0846-1.

    Article  CAS  PubMed  Google Scholar 

  144. Parry G, Provart NJ, Brady SM, Uzilday B, Committee TMAS. Current status of the multinational Arabidopsis community. Plant Direct. 2020;00:1–9. https://doi.org/10.1002/pld3.248.

    Article  CAS  Google Scholar 

  145. Partida-Martínez LP, Heil M. The microbe-free plant: Fact or artifact? Front Plant Sci. 2011;2:100. https://doi.org/10.3389/fpls.2011.00100.

    Article  PubMed  PubMed Central  Google Scholar 

  146. Pfeilmeier S, Petti GC, Bortfeld-Miller M, Daniel B, Field CM, Sunagawa S, Vorholt JA. The plant NADPH oxidase RBOHD is required for microbiota homeostasis in leaves. Nature. 2021;6:852–64. https://doi.org/10.1038/s41564-021-00929-5.

    Article  CAS  Google Scholar 

  147. Pieterse CMJ, Berendsen RL, de Jonge R, Stringlis IA, Van Dijken AJH, Van Pelt JA, Van Wees SCM, Yu K, Zamioudis C, Bakker PAHM. Pseudomonas simiae WCS417: star track of a model beneficial rhizobacterium. Plant Soil. 2021;461:245–63. https://doi.org/10.1007/s11104-020-04786-9.

    Article  CAS  Google Scholar 

  148. Ploch S, Rose LE, Bass D, Bonkowski M. High diversity revealed in leaf-associated protists (Rhizaria: Cercozoa) of Brassicaceae. J Eukaryot Microbiol. 2016;63:635–41. https://doi.org/10.1111/jeu.12314.

    Article  PubMed  PubMed Central  Google Scholar 

  149. Ponsford JCB, Hubbard CJ, Harrison JG, Maignien L, Buerkle CA, Weinig C. Whole-genome duplication and host genotype affect rhizosphere microbial communities. mSystems. 2022;7:e00973-21. https://doi.org/10.1128/msystems.00973-21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  150. Poudel M, Mendes R, Costa LAS, Bueno CG, Meng Y, Folimonova SY, Garrett KA, Martins SJ. The role of plant-associated bacteria, fungi, and viruses in drought stress mitigation. Front Microbiol. 2021;12:7433512. https://doi.org/10.3389/fmicb.2021.743512.

    Article  Google Scholar 

  151. Poupin MJ, Timmermann T, Vega A, Zúñiga A, González B. Effects of the plant growth promoting bacterium Burkholderia phytofirmans PsJN throughout the life cycle of Arabidopsis thaliana. PLoS ONE. 2013;8:e69435. https://doi.org/10.1371/journal.pone.0069435.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  152. Poupin MJ, Greve M, Carmona V, Pinedo I. A complex molecular interplay of auxin and ethylene signaling pathways is involved in Arabidopsis growth promotion by Burkholderia phytofirmans PsJN. Front Plant Sci. 2016;7:492. https://doi.org/10.3389/fpls.2016.00492.

    Article  PubMed  PubMed Central  Google Scholar 

  153. Pratama AA, Terpstra J, Martinez de Oliveria AL, Falcão Salles J. The role of rhizosphere bacteriophages in plant health. Trends Microbiol. 2020;28:709–X. https://doi.org/10.1016/j.tim.2020.04.005.

    Article  CAS  Google Scholar 

  154. Ramirez-Villacis DX, Finkel OM, Salas-González I, Fitzpatrick CR, Dangl JL, Jones CD, Leon-Reyes A. Root microbiome modulates plant growth promotion induced by low doses of glyphosate. mSphere. 2020;5:e00484-20. https://doi.org/10.1128/mSphere.00484-20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  155. Regalado J, Lundberg DS, Deusch O, Kersten S, Karasov T, Poersch K, Shirsekar G, Weigel D. Combining whole-genome shotgun sequencing and rRNA gene amplicon analyses to improve detection of microbe-microbe interaction network in plant leaves. ISME J. 2020;14:2116–30. https://doi.org/10.1038/s41396-020-0665-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  156. Reisberg EE, Hildebrandt U, Riederer M, Hentschel U. Distinct phyllosphere bacterial communities on Arabidopsis wax mutant leaves. PLoS ONE. 2013;8:e78613. https://doi.org/10.1371/journal.pone.0078613.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  157. Remus-Emsermann MNP, Lücker S, Müller DB, Potthoff E, Dalms H, Vorholt JA. Spatial distribution analysis of natural phyllosphere-colonizing bacteria on Arabidopsis thaliana revealed by fluorescence in situ hybridization. Environ Microbiol. 2014;16:2329–40. https://doi.org/10.1111/1462-2920.12482.

    Article  CAS  PubMed  Google Scholar 

  158. Ritpitakphong U, Falquet L, Vimoltust A, Berger A, Métraux J-P, L`Haridon F. The microbiome of the leaf surface of Arabidopsis protects against a fungal pathogen. New Phytol. 2016;210:1033–43. https://doi.org/10.1111/nph.13808.

    Article  CAS  PubMed  Google Scholar 

  159. Robbins C, Thiergart T, Hacquard S, Garrido-Oter R, Gans W, Peiter E, Schulze-Lefert P, Spaepen S. Root-associated bacterial and fungal community profiles of Arabidopsis thaliana are robust across contrasting soil P levels. Phytobiomes J. 2018;2:24–34. https://doi.org/10.1094/PBIOMES-09-17-0042-R.

    Article  Google Scholar 

  160. Roossinck MJ. Plant, viruses, and the environment: ecology and mutualism. Virology. 2015;479–480:271–7. https://doi.org/10.1016/j.virol.2015.03.041.

    Article  CAS  PubMed  Google Scholar 

  161. Rosenberg K, Bertaux J, Krome K, Hartmann A, Scheu S, Bonkowski M. Soil amoebae rapidly change bacterial community composition in the rhizosphere of Arabidopsis thaliana. ISME J. 2009;3:675–84. https://doi.org/10.1038/ismej.2009.11.

    Article  CAS  PubMed  Google Scholar 

  162. Ryffel F, Helfrich EJN, Kiefer P, Peyriga L, Portais J-C, Piel J, Vorholt JA. Metabolic footprint of epiphytic bacteria on Arabidopsis thaliana leaves. ISME J. 2016;10:632–43. https://doi.org/10.1038/ismej.2015.141.

    Article  CAS  PubMed  Google Scholar 

  163. Salas-González I, Reyt G, Flis P, Custódio V, Gopaulchan D, Bakhoum N, Dew TP, Suresh K, Franke RB, Dangl JL, Salt DE, Castrillo G. Coordination between microbiota and root endodermis supports plant mineral nutrient homeostasis. Science. 2021;371:eabd0695. https://doi.org/10.1126/science.abd0695.

    Article  CAS  PubMed  Google Scholar 

  164. Salvato F, Vintila S, Finkel OM, Dangla JL, Kleiner M. Evaluation of extraction methods for metaproteomic analyses of root-associated microbes. Molec Microb Plant Interact. 2022;35:977–88. https://doi.org/10.1094/MPMI-05-22-0116-TA.

    Article  CAS  Google Scholar 

  165. Sapp M, Ploch S, Fiore-Donno AM, Bonkowski M, Rose LE. Protists are an integral part of the Arabidopsis thaliana microbiome. Environ Microbiol. 2018;20:30–43. https://doi.org/10.1111/1462-2920.13941.

    Article  CAS  PubMed  Google Scholar 

  166. Sasse J, Martinoia E, Northen T. Feed your friends: Do plants exudates shape the root microbiome? Trends Plant Sci. 2018;23:25–41. https://doi.org/10.1016/j.tplants.2017.09.003.

    Article  CAS  PubMed  Google Scholar 

  167. Sawana A, Adeolu M, Gupta RS. Molecular signatures and phylogenomic analysis of the genus Burkholderia: proposal for division of this genus into the emended genus Burkholderia containing pathogenic organisms and a new genus Paraburkholderia gen nov. harboring environmental species. Front Genet. 2014;5:429. https://doi.org/10.3389/fgene.2014.00429.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  168. Schäfer M, Vogel CM, Bortfeld-Miller M, Mittelviefhaus M, Vorholt JA. Mapping phyllosphere microbiota interactions in planta to establish genotype–phenotype relationships. Nat Microbiol. 2022;7:856–67. https://doi.org/10.1038/s41564-022-01132-w.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  169. Schlaeppi K, Dombrowski N, Garrido-Oter R, Loren V, van Themaat E, Schulze-Lefert P. Quantitative divergence of the bacterial root microbiota in Arabidopsis thaliana relatives. Proc Natl Acad Sci. 2014;111:585–92. https://doi.org/10.1073/pnas.1321597111.

    Article  CAS  PubMed  Google Scholar 

  170. Schneijderberg M, Cheng X, Franken C, de Hollander M, van Velzen R, Schmitz L, Heinen R, Geurts R, van der Putten WM, Martijn Bezemer T, Bisseling T. Quantitative comparison between the rhizosphere effect of Arabidopsis thaliana and co-occurring plant species with a longer life story. ISME J. 2020;14:2433–48. https://doi.org/10.1038/s41396-020-0695-2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  171. Sczyrba A, Hofmann P, Belmann P, Koslicki D, Janssen S, Dröge J, Gregor I, Majda S, Fiedler J, Dahms E, Bremges A, Fritz A, Garrido-Oter R, Sparholt Jørgensen T, Shapiro N, Blood PD, Gurevich A, Bai Y, Turaev D, de Maere MZ, Chikhi R, Nagarajan N, Quince MMZ, Egan R, Kang DD, Cook JJ, Deltel C, Beckstette M, Lemaitre C, Peterlongo P, Rizk G, Lavenier D, Wu Y-W, Singer SW, Jain C, Strous M, Klingenberg H, Meinicke P, Barton MD, Lingner T, Lin HH, Liao YC, Silva GGZ, Cuevas DA, Edwards RA, Saha S, Piro VC, Renard BY, Pop M, Klenk HP, Göker M, Kyrpides NC, Woyke T, Vorholt JA, Schulze-Lefert P, Rubin EM, Darling AE, Rattei T, McHardy AC. Critical assessment of metagenome interpretation-a benchmark of metagenomics software. Nat Meth. 2017;14:1063–73. https://doi.org/10.1038/NMETH.4458.

    Article  CAS  Google Scholar 

  172. Shade A, Stopnisek N. Abundance-occupancy distributions to prioritize plant core microbiome membership. Curr Opin Microbiol. 2019;49:50–8. https://doi.org/10.1016/j.mib.2019.09.008.

    Article  PubMed  Google Scholar 

  173. Shade A, Jacques M-A, Barret M. Ecological patterns of seed microbiome diversity, transmission, and assembly. Curr Opin Microbiol. 2017;37:15–22. https://doi.org/10.1016/j.mib.2017.03.010.

    Article  PubMed  Google Scholar 

  174. Sikder MM, Vestergård M, Kyndt T, Kudjordjie EN, Nicolaisen M. Phytohormones selectively affect plant parasitic nematodes associated with Arabidopsis roots. New Phytol. 2021;232:1272–85. https://doi.org/10.1111/nph.17549.

    Article  CAS  PubMed  Google Scholar 

  175. Sikder MM, Vestergård M, Kyndt T, Topalović O, Kudjordjie EN, Nicolaisen M. Genetic disruption of Arabidopsis secondary metabolite synthesis leads to microbiome-mediated modulation of nematode invasion. ISME J. 2022;16:2230–41. https://doi.org/10.1038/s41396-022-01276-x.

    Article  CAS  PubMed  Google Scholar 

  176. Shalev O, Karasov TL, Lundberg DS, Ashkenazy H, Ayutthaya PPN, Weigel D. Commensal Pseudomonas strains facilitate protective response against pathogens in the host plant. Nat Ecol Evol. 2022;6:383–96. https://doi.org/10.1038/s41559-022-01673-7.

    Article  PubMed  PubMed Central  Google Scholar 

  177. Song Y, Wilson AJ, Zhang X-C, Thoms D, Sohrabi R, Song S, Geissmann Q, Liu Y, Walgren L, He S-Y, Haney CH. FERONIA restricts Pseudomonas in the rhizosphere microbiome via regulation of reactive species. Nature Plants. 2021;7:644–54. https://doi.org/10.1038/s41477-021-00914-0.

    Article  CAS  PubMed  Google Scholar 

  178. Staley C, Ferrieri AP, Tfaily MM, Cui Y, Chu RK, Wang P, Shaw JB, Ansong CK, Brewer H, Norbeck AD, Markillie M, de Amaral F, Tuleski T, Pellizzaro T, Agtuca B, Ferrieri R, Tringe SG, Paša-Tolić L, Stacey G, Sadowsky MJ. Diurnal cycling of rhizosphere bacterial communities is associated with shifts in carbon metabolism. Microbiome. 2017;5:65. https://doi.org/10.1186/s40168-017-0287-1.

    Article  PubMed  PubMed Central  Google Scholar 

  179. Stassen MJJ, Hsu S-H, Pieterse CMJ, Stringlis IA. Coumarin communication along the microbiome-root-shoot axis. Trends Plant Sci. 2021;26:169–83. https://doi.org/10.1016/j.tplants.2020.09.008.

    Article  CAS  PubMed  Google Scholar 

  180. Stringlis IA, Yu K, Feussner K, de Jonge R, Van Bentum S, Van Kerk MC, Berendsen RL, Bakker PAHM, Feussner I, Pieterse CMJ. MYB72-dependent coumarin exudation shapes root microbiome assembly to promote plant health. Proc Natl Acad Sci. 2018;115:E5213–22. https://doi.org/10.1073/pnas.1722335115.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  181. Stringlis IA, de Jonge R, Pieterse CM. The age of coumarins in plant-microbe interactions. Plant Cell Physiol. 2019;60:1405–19. https://doi.org/10.1093/pcp/pcz076.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  182. Teixeira PJPL, Colaianni NR, Law TF, Conway JM, Gilbert S, Li H, Salas-González I, Panda D, Del Risco NM, Finkel OM, Castrillo G, Mieczkowski P, Jones CD, Dangl JL. Specific modulation of the root immune system by a community of commensal bacteria. Proc Natl Acad Sci. 2021;118:e2100678118. https://doi.org/10.1073/pnas.2100678118.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  183. Tkacz A, Cheema J, Chandra G, Grant A, Poole PS. Stability and succession of the rhizosphere microbiota depends upon plant type and soil composition. ISME J. 2015;9:2349–59. https://doi.org/10.1038/ismej.2015.41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  184. Tkacz A, Bestion E, Bo Z, Hortala M, Poole PS. Influence of plant fraction, soil, and plant species on microbiota: a multikingdom comparison. mBio. 2020;11:e02785-19. https://doi.org/10.1128/mBio.02785-19.

    Article  PubMed  PubMed Central  Google Scholar 

  185. Tkacz A, Poole P. The plant microbiome: the dark and dirty secrets of plant growth. Plants People Planets. 2021;3:124–9. https://doi.org/10.1002/ppp3.10167.

    Article  Google Scholar 

  186. Thiergart T, Durán P, Ellis T, Vannier N, Garrido-Oter R, Kemen E, Roux F, Alonso-Blanco C, Ågren J, Schulze-Lefert P, Hacquard S. Root microbiota assembly and adaptive differentiation among European Arabidopsis populations. Nat Ecol Evol. 2020;4:122–31. https://doi.org/10.1038/s41559-019-1063-3.

    Article  PubMed  Google Scholar 

  187. Timmermann T, Poupin MJ, Vega A, Urrutia C, Ruz G, González B. Gene networks underlying the early regulation of Paraburkholderia phytofirmans PsJN induced systemic resistance in Arabidopsis. PLoS One. 2019;14:e0221358. https://doi.org/10.1371/journal.pone.0221358.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  188. Truyens S, Weyens N, Cuypers A, Vangronsveld J. Changes in the population of seed bacteria transgenerationally Cd-exposed Arabidopsis thaliana. Plant Biol. 2013;15:971–81. https://doi.org/10.1111/j.1438-8677.2012.00711.x.

    Article  CAS  PubMed  Google Scholar 

  189. Truyens S, Weyens N, Cuypers A, Vangronsveld J. Bacterial seed endophytes: genera, vertical transmission, and interaction with plants. Environ Microbiol Rep. 2015;7:40–50. https://doi.org/10.1111/1758-2229.12181.

    Article  Google Scholar 

  190. Truyens S, Beckers B, Thijs S, Weyens N, Cuypers A, Vangronsveld J. Cadmium-induced and trans-generational changes in the cultivable and total seed endophytic community of Arabidopsis thaliana. Plant Biol. 2016;18:376–81. https://doi.org/10.1111/plb.12415.

    Article  CAS  PubMed  Google Scholar 

  191. Urbina H, Breed MF, Zhao W, Gurrala KL, Andersson SGE, Ågren J, Baldauf S, Rosling A. Specificity in Arabidopsis thaliana recruitment of root fungal communities from soil and rhizosphere. Fungal Biol. 2018;122:231–40. https://doi.org/10.1016/j.funbio.2017.12.013.

    Article  PubMed  Google Scholar 

  192. Vandenkoornhuyse P, Quaiser A, Duhamel M, Le Van A, Dufresne A. The importance of the microbiome of the plant holobiont. New Phytol. 2015;206:1196–206. https://doi.org/10.1111/nph.13312.

    Article  PubMed  Google Scholar 

  193. van der Heijden MGA, Hartmann M. Networking in the plant microbiome. PLoS Biol. 2016;14:e1002378. https://doi.org/10.1371/journal.pbio.1002378.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  194. van der Meij A, Willemse J, Schneijderberg MA, Geurts R, Raaijmakers JM, van Wezel GP. Inter- and intracellular colonization of Arabidopsis roots by endophytic actinobacteria and the impact of plant hormones on their antimicrobial activity. Antonie van Leeuwenhoek. 2018;111:679–90. https://doi.org/10.1007/s10482-018-1014-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  195. Vogel CM, Potthoff DB, Schäfer M, Barandun N, Vorholt JA. Protective role of the Arabidopsis leaf microbiota against a bacterial pathogen. Nature Microbiol. 2021;6:1537–48. https://doi.org/10.1038/s41564-021-00997-7.

    Article  CAS  Google Scholar 

  196. Voges MJEEE, Bai Y, Schulze-Lefert P, Sattely ES. Plant-derived coumarins shape the composition of an Arabidopsis synthetic root microbiome. Proc Natl Acad Sci. 2019;116:12558–65. https://doi.org/10.1073/pnas.1820691116.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  197. Vojtovič D, Luhová L, Petřivalský M. Something smells bad to plant pathogens: production of hydrogen sulfide in plants and its role in plant defence responses. J Adv Res. 2020;27:199–209. https://doi.org/10.1016/j.jare.2020.09.005.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  198. Vorholt JA. Microbial life in the phyllosphere. Nature Rev Microbiol. 2012;10:828–40. https://doi.org/10.1038/nrmicro2910.

    Article  CAS  Google Scholar 

  199. Vorholt JA, Vogel CM, Carlström CI, Müller DB. Establishing causality: opportunities of synthetic communities for plant microbiome research. Cell Host Microbe. 2017;22:142–55. https://doi.org/10.1016/j.chom.2017.07.004.

    Article  CAS  PubMed  Google Scholar 

  200. Wang NR, Wiesmann CL, Melnyk RA, Hossain SS, Chi M-H, Martens K, Craven K, Haney CH. Commensal Pseudomonas fluorescens strains protect Arabidopsis from closely related Pseudomonas pathogens in a colonization-dependent manner. mBio. 2022;13:e02892-21. https://doi.org/10.1128/mbio.02892-21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  201. Wippel K, Tao K, Niu Y, Zgadzaj R, Kiel N, Guan R, Dahms E, Zhang P, Jensen DB, Logemann E, Radutoiu S, Schulze-Lefert P, Garrido-Oter R. Host preference and invasiveness of commensal bacteria in the Lotus and Arabidopsis root microbiota. Nature Microbiol. 2021;6:1150–62. https://doi.org/10.1038/s41564-021-00941-9.

    Article  CAS  Google Scholar 

  202. Wolinska KW, Vannier N, Thiergart T, Pickel B, Gremmen S, Piasecka A, Piślewska-Bednarek M, Nakano RT, Belkhadir Y, Bednarek P, Hacquard S. Tryptophan metabolism and bacterial commensals prevent fungal dysbiosis in Arabidopsis roots. Proc Natl Acad Sci. 2021;118:e211152118. https://doi.org/10.1073/pnas.2111521118.

    Article  CAS  Google Scholar 

  203. Worsley SF, Macey MC, Prudence SMM, Wilkinson B, Murrell JC, Hutchings MI. Investigating the role of root exudates in recruiting Streptomyces bacteria to the Arabidopsis thaliana microbiome. Front Mol Biosci. 2021;8:686110. https://doi.org/10.3389/fmolb.2021.686110.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  204. Yang N, Nesme J, Røder HL, Li X, Zuo Z, Petersen M, Burmølle M, Sørensen SJ. Emergent bacterial community properties induce enhanced drought tolerance in Arabidopsis. npj Biofilms Microbiomes. 2021;7:82. https://doi.org/10.1038/s41522-021-00253-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  205. Yuan J, Zhao J, Wen T, Zhao M, Li R, Goossens P, Huang Q, Bai Y, Vivanco JM, Kowalchuk GA, Berendsen RL, Shen Q. Root exudates drive the soil-borne legacy of aboveground pathogen infection. Microbiome. 2018;6:156. https://doi.org/10.1186/s40168-018-0537-x.

    Article  PubMed  PubMed Central  Google Scholar 

  206. Zamioudis C, Mastranesti P, Dhonukshe P, Blilou I, Pieterse CM. Unraveling root developmental programs initiated by beneficial Pseudomonas spp. bacteria. Plant Physiol. 2013;162:304–18. https://doi.org/10.1104/pp.112.212597.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  207. Zhao Q, Liu W, Li Y, Ke M, Qu Q, Yuan W, Pan X, Qian H. Enantioselective effects of imazethapyr residues on Arabidopsis thaliana metabolic profile and phyllosphere microbial communities. J Env Sci. 2020;93:57–65. https://doi.org/10.1016/j.jes.2020.03.009.

    Article  CAS  Google Scholar 

  208. Zolla G, Badri DV, Bakker MG, Manter DK, Vivanco JM. Soil microbiomes vary in their ability to confer drought tolerance to Arabidopsis. Appl Soil Ecol. 2013;68:1–9. https://doi.org/10.1016/j.apsoil.2013.03.007.

    Article  Google Scholar 

  209. Zúñiga A, Poupin MJ, Donoso RA, Ledger T, Guiliani N, Gutiérrez RA, González B. Quorum sensing and indole-3-acetic acid degradation play a role in colonization and plant growth promotion of Arabidopsis thaliana by Burkholderia phytofirmans PsJN. Molec Plant Microb Interact. 2013;26:546–53. https://doi.org/10.1094/MPMI-10-12-0241-R.

    Article  CAS  Google Scholar 

Download references

Funding

BG, MJP, and TL research funded by ANID PIA/BASAL FB0002, ANID-Millennium Science Initiative Program—NCN2021_010, ANID PIA/ANILLOS ACT210052, and ANID-FONDECYT 1190634. RRM research is supported by the Spanish Ministry of Sciences Innovation and Universities projects PGC2018-096956-B-C41 and RTC-2017–6405-1, both also supported by European Regional Development Fund (FEDER). These funding sources had no role in the review conception, preparation, and final manuscript.

Author information

Authors and Affiliations

Authors

Contributions

B.G conceived the initial idea. B.G., M.J.P, T.L, and R.R-M wrote and reviewed the manuscript. M.J.P and B.G. prepared figures and tables. All authors read and approved the manuscript.

Corresponding author

Correspondence to B. González.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Content for publication

The authors give the consent for publication to the Publisher.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1

. Supplementary List of References (cited in Table 1).

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Poupin, M.J., Ledger, T., Roselló-Móra, R. et al. The Arabidopsis holobiont: a (re)source of insights to understand the amazing world of plant–microbe interactions. Environmental Microbiome 18, 9 (2023). https://doi.org/10.1186/s40793-023-00466-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s40793-023-00466-0

Keywords