Next Article in Journal
Micromorphology of Pine Needle Primordia and Young Needles after Bud Dormancy Breaking
Next Article in Special Issue
Changes in Metal-Chelating Metabolites Induced by Drought and a Root Microbiome in Wheat
Previous Article in Journal
Metabolic Profiling Identifies Changes in the Winter Wheat Grains Following Fusarium Treatment at Two Locations in Croatia
Previous Article in Special Issue
Chlamydomonas reinhardtii, a Reference Organism to Study Algal–Microbial Interactions: Why Can’t They Be Friends?
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

Insights into the Methodological, Biotic and Abiotic Factors Influencing the Characterization of Xylem-Inhabiting Microbial Communities of Olive Trees

Department of Crop Protection, Institute for Sustainable Agriculture, Spanish National Research Council (CSIC), 14004 Córdoba, Spain
Author to whom correspondence should be addressed.
Plants 2023, 12(4), 912;
Received: 7 January 2023 / Revised: 8 February 2023 / Accepted: 15 February 2023 / Published: 17 February 2023
(This article belongs to the Special Issue Plant-Microbe Interactions 2022)


Vascular pathogens are the causal agents of some of the most devastating plant diseases in the world, which can cause, under specific conditions, the destruction of entire crops. These plant pathogens activate a range of physiological and immune reactions in the host plant following infection, which may trigger the proliferation of a specific microbiome to combat them by, among others, inhibiting their growth and/or competing for space. Nowadays, it has been demonstrated that the plant microbiome can be modified by transplanting specific members of the microbiome, with exciting results for the control of plant diseases. However, its practical application in agriculture for the control of vascular plant pathogens is hampered by the limited knowledge of the plant endosphere, and, in particular, of the xylem niche. In this review, we present a comprehensive overview of how research on the plant microbiome has evolved during the last decades to unravel the factors and complex interactions that affect the associated microbial communities and their surrounding environment, focusing on the microbial communities inhabiting the xylem vessels of olive trees (Olea europaea subsp. europaea), the most ancient and important woody crop in the Mediterranean Basin. For that purpose, we have highlighted the role of xylem composition and its associated microorganisms in plants by describing the methodological approaches explored to study xylem microbiota, starting from the methods used to extract xylem microbial communities to their assessment by culture-dependent and next-generation sequencing approaches. Additionally, we have categorized some of the key biotic and abiotic factors, such as the host plant niche and genotype, the environment and the infection with vascular pathogens, that can be potential determinants to critically affect olive physiology and health status in a holobiont context (host and its associated organisms). Finally, we have outlined future directions and challenges for xylem microbiome studies based on the recent advances in molecular biology, focusing on metagenomics and culturomics, and bioinformatics network analysis. A better understanding of the xylem olive microbiome will contribute to facilitate the exploration and selection of specific keystone microorganisms that can live in close association with olives under a range of environmental/agronomic conditions. These microorganisms could be ideal targets for the design of microbial consortia that can be applied by endotherapy treatments to prevent or control diseases caused by vascular pathogens or modify the physiology and growth of olive trees.

1. Introduction

Plant microbiome research has been expanding over the last years due to its key determinant role in plant health and crop productivity [1], as is revealed by the increase in the number of scientific publications listed in Web of Science (WoS) and Scopus databases (Figure 1). Nowadays, it is generally accepted that plants live in association with a rich diversity of microorganisms. The sum of these microbial cells formed by multi-kingdom microbial communities (bacteria, fungi, viruses, etc.) that colonize both below- and aboveground plant organs in a particular environment is called plant-associated microbiota and refers to the taxonomy and abundance of microbial community members in a given environment. On the other hand, the totality of genomes of this microbiota is called the plant microbiome and it is often used to define the microbial behaviors or functions determined by a microbiota [2].
A better knowledge of the plant microbiome will result in developing alternatives to solve some of the environmental issues and challenges worldwide caused by excess use of chemicals for pest control by enhancing crop production and soil health [3] and by developing biological control alternatives for managing plant diseases [4,5]. Plant-associated beneficial microbiomes can confer fitness advantages to the host plant because these microorganisms can directly impact plant growth and health by producing phytohormones, improving nutrient acquisition and phosphate solubilization and tolerance to biotic and abiotic stresses. Additionally, they can act indirectly by activating a series of host physiological and immune responses that may trigger the multiplication of a specific microbiome to cope with the pathogen infection. This beneficial elicited microbiome can compete for plant resources and niche space or inhibit the growth of plant pathogens via the production of antibiotics, fungal cell wall-degrading enzymes or siderophores, among others [6,7,8].
In this review, we have explored how research on the plant microbiome has evolved during the last decades to unravel the factors and complex interactions that affect the associated microbial communities and their surrounding environment, focusing on a very specific plant niche, the xylem vessels of the olive tree. We have also discussed the importance of studying the xylem-inhabiting microorganisms and their potential role in protecting plants against vascular pathogens, such as Verticillium dahliae and Xylella fastidiosa, that threaten olive production worldwide, highlighting the current challenges and future perspectives that endophytes represent for the control of these xylem-associated pathogens. Additionally, we reviewed some of the most important biotic and abiotic factors that can modulate and influence xylem microbial communities in different host plants (Table 1).

2. Olive Tree and Its Vascular Pathogens

Olive (Olea europaea susbp. europaea L.) is one of the most relevant tree species within the Mediterranean Basin due to its cultural and economic importance, without underestimating the noteworthy environmental attributes related to its ability to survive in poor, shallow and dry soils, and its contribution to the control of soil erosion and increase in soil nutrient retention [9,10]. In addition, olive orchards are important agroforestry habitats, playing essential roles in maintaining ecosystem diversity [11]. Hence, olive cultivation comprises relevant economic, environmental and socio-cultural values representing an agricultural system that should remain integral to the Mediterranean Basin. However, the health status of olive trees is being threatened by a remarkable increase in diseases caused by xylem-inhabiting pathogens, such as the plant pathogenic bacterium Xylella fastidiosa and the soilborne fungus Verticillium dahliae. Both pathogens are global threats to olive production which can adversely affect olive growth and production, causing substantial economic losses and severe environmental impact [12,13,14,15,16].
The life cycle of V. dahliae, the causal agent of Verticillium wilt, is mainly characterized by its growth confined within the xylem vessels during the pathogenic phase and its ability to survive for many years as dormant microsclerotia in soil or within plant debris [12,17]. Verticillium dahliae infects the olive plants through the root system; then, the pathogen colonizes the xylem vessels and impairs the sap flow through mycelial proliferation, the formation of occlusions and tyloses that ultimately may cause the death of the tree [12,18]. The implementation of an integrated management strategy is the best option for controlling this disease, combining the use of resistant olive cultivars, or tolerant ones grafted onto resistant rootstocks, with adequate irrigation management and agricultural practices that prevent the spread of inoculum of the pathogen [12,19,20,21,22,23].
On the other hand, X. fastidiosa is a quarantine plant pathogenic bacterium in the European Union (EU) and was ranked first on the list of the 20 priority pests within the EU territory (Commission Delegated Regulation (EU) 2019/1702). X. fastidiosa is transmitted by sap-feeding insect vectors and has been described as the causal agent of Olive Quick Decline Syndrome (OQDS). This disease is characterized by rapid dieback of shoots, twigs and branches, followed by the death of the tree [24]. Sap-feeding insect vectors inoculate the pathogen into xylem vessels from infected to healthy trees. Once inside, the aggregation of bacterial cells and biofilm formation block the sap flow in the xylem causing the plant to dry out and die [25]. Xylella fastidiosa is taxonomically divided into three major subspecies (fastidiosa, multiplex and pauca) [26], although two additional subspecies have been proposed (morus and sandyi). Only isolates belonging to the subspecies pauca are currently considered a threat to olive production worldwide. As previously indicated for V. dahliae, currently, there is no efficient control measure for the management of X. fastidiosa once the plant is infected. Consequently, the use of preventive strategies focused on the early detection and eradication of infected host plants, the control of the vectors and restrictions on plant material movements are currently the only available tools for the management of the diseases caused by this harmful bacterium [27,28,29].
The establishment of a pathogen lifestyle in a microorganism depends on its interactions with the host microbiome and the host immune system [30]. The xylem-associated microorganisms are involved in several biotic and abiotic processes within the plant host, including the acquisition of nutrients and increase of plant tolerance to abiotic stresses, without overlooking their role in the defense of the plant against vascular pathogens. In this context, acquiring and maintaining a beneficial xylem-associated microbiota capable of adapting more rapidly to a changing environment could be a selective advantage for the olive tree to fight against vascular pathogens [31,32].

3. The Role of Xylem Composition and Its Associated Microorganisms in Plants

Xylem vessels play a decisive role in plant growth maintenance, providing a main route and refined plumbing system for the circulation of micro- and macronutrients derived from xylem sap. This nutrient flow in the xylem from roots to shoots ensures a controlled exchange of ions and metabolites from the xylem to a required and localized area which is driven by hydrostatic pressure and water potential [33,34]. The xylem is traditionally considered a nutritionally poor environment with highly fluctuating negative pressure and low oxygen and nutrient content compared with other plant ecological niches [35]. Consequently, the characterization of xylem sap composition is crucial to understand the nutrient fluxes and dynamics occurring within this plant niche since it may influence the maintenance or selection of a specific beneficial xylem-associated microbiota [36].
Several studies have shown that xylem sap contains a wide variety of chemical compounds, including a high level of sugars, followed by alcohols, amino acids and organic acids [37,38,39]. Xylem sap metabolome analysis demonstrated the presence of these compounds in different crops, including herbaceous (i.e., tomato [40], soybean [38] and cabbage [37]) and woody plant species (i.e., grapevines [41], peach [42] and plum [43]). In olive xylem sap, several primary (mannitol, ethanol, glutamine and acetic acid) and secondary metabolites (terpenoids, phytohormones, alkaloids, sterols, retinols, tocopherols and carotenoids) [44] have been identified [39], many of which have been shown to play a determinant role in plant growth and resistance or tolerance to different biotic and abiotic stresses [45,46]. Additionally, several studies recently showed that olive xylem sap composition can be influenced by a variety of factors, such as changes in crop management [47], climatic conditions and biotic factors including the olive plant age and genotype [39].
Xylem vessels are considered ideal niches for microbial endophytes characterized by specific abiotic and biotic conditions supporting the colonization by endophytes and providing an effective pathway for its distribution throughout the plant and a continuous source of nutrients from xylem sap [48]. Nevertheless, only a few microbes have adapted to exclusively inhabit the xylem (e.g., X. fastidiosa), while various pathogens may colonize other plant niches without causing symptoms until they reach the xylem vessels (e.g., V. dahliae). Thus, once established in the xylem, these pathogens modulate their physicochemical composition to enhance their growth and virulence [49]. On the other hand, there are microbial endophytes that colonize xylem vessels and plant host tissues internally, evoking a series of critical responses that have beneficial effects on plant growth and may confer protection against vascular plant pathogens [50].
Potential engineering of the plant microbiome is generating exciting results for plant disease control by transplanting specific members of the plant microbiome. However, its practical application in agriculture for the control of vascular plant pathogens is hampered by the limited knowledge of the xylem niche. Knowledge of xylem sap composition may be crucial for improving the isolation and culturability of specific beneficial members of the xylem microbiome to exploit them as biocontrol agents [51,52].

4. Methodological Approaches to Study the Xylem Microbiota

4.1. Methods Used to Extract Xylem Microbial Communities

The xylem can be considered a hostile environment when compared to other ecological niches of the plant due to its limited nutritional content and specific abiotic conditions (i.e., low oxygen content, negative pressure, etc.). This could explain why only a limited number of microbes and plant pathogens are able to thrive in this environment [35]. Furthermore, only a few studies have identified the diversity of xylem-inhabiting microorganisms in promoting plant health and crop productivity [52,53,54,55,56]. The lack of comprehensive studies may be due, at least in part, to the technical difficulties involved in the isolation of xylem-inhabiting microorganisms.
Alexou and Peuke (2013) [57] described four different methods for collecting the plant xylem sap: (i) root pressure exudate, (ii) Scholander–Hammel pressure vessel, (iii) the root pressurizing method according to Passioura (1980) [58] and (iv) (hand/battery) vacuum pump. Although each method presented advantages and disadvantages, all bring in common the small amount of xylem sap recovered, which might be a limitation for obtaining a representative sample of the microbial communities inhabiting this plant niche.
These techniques have evolved and the possibility of using an external port (40 to 60 cm long) with the Scholander chamber device and the admission of pressure has allowed the extraction of higher volumes of xylem sap from larger and more representative plant portions [39,52,59,60]. However, the extraction of xylem sap using this device is not always feasible due to its high cost for laboratories, in particular when the sampling sites are located at long distances from laboratory facilities, or a large number of samples need to be assessed in a short period. Consequently, other methods for extracting xylem exudates need to be explored to overcome these limitations.
One of the simplest approaches for collecting xylem exudates is to make a cross-section excision in the stem and harvest the sap oozing out through capillary movement by gravity and root pressure [40,61]. Additionally, a portable simple method has been developed for the rapid extraction of xylem sap from stems and petioles using negative pressure generated from handheld needleless syringes [62]. However, these methods do not work for most woody plants due to their high negative stem water potential [63].
Another method used for xylem sap extraction consists of the use of macerated xylem tissue obtained by scraping the most external layers of debarked woody pieces with a sterile scalpel. This method is the most widely used approach in studies targeting the xylem microbiome, since this technique is less time-consuming and more affordable (no need to use a nitrogen tank) than the use of the Scholander device [5,52,60,64]. However, it has been demonstrated that the Scholander chamber device or the woody chips maceration approach retrieve different microbial communities’ profiles, since they affect the recovery of several microbial taxa, showing the importance of the choice of a proper xylem extraction method for the characterization of the xylem microbiome [52,60]. Differences between these two methods might be explained by the extraction of some microorganisms that may occupy intercellular tissues surrounding the xylem vessels that could not be true inhabitants of the vascular tissues, or by the extraction of microbes forming biofilms and strongly adhered to the xylem vessels, the release of which is favored by the tissue maceration process [5].

4.2. Assessment of Microbial Communities by Culture-Dependent Approaches

One of the most conventional approaches for the study of plant-associated microorganisms is the use of culture-dependent techniques. Although only a minor fraction of individual microbial species out of the whole microbial community is known to be cultivable, this technique offers several advantages due to the establishment of microbial cultures under laboratory conditions and the purification of single strains from a microbial cluster present in particular ecological niches [65]. This approach has led to the recovery and isolation of a wide range of microorganisms from the rhizosphere [66,67], endosphere [52,68,69] and phyllosphere [70,71] plant compartments.
The development of studies focusing on the optimization of the isolation of specific members of the plant microbiome is rising, as there is a need to test hypotheses based on the manipulation of the plant microbiota and to establish synthetic communities for plant microbiome studies. This strategy can be applied to identify key microbial genera associated with particular plant phenotypes (e.g., resistant to vascular plant pathogens [5]) or by transplanting beneficial bacteria from microbiomes of wild plant genotypes to cropped cultivars [72]. Such cultured bacterial consortia can also be ideal targets for the design of effective biofertilizers, biostimulants or biocontrol agents for a wide range of crops [73]. Therefore, the rebirth of microbial culture collections from specific plant ecological niches represents a valuable tool for increasing our understanding of the plant microbiome. In fact, some authors have applied systematic bacterial isolation approaches to establish culture collections of the Arabidopsis thaliana leaf- and root-associated microbiota, being able to capture most of the species found in their respective natural communities (≥0.1% relative abundance) [74].
In line with this, Anguita-Maeso et al. (2020) [52] recovered a bacterial culture collection from the xylem sap of different cultivated and wild olive genotypes, using two of the xylem extraction methods referred to above (Scholander chamber device and woody chips maceration). Results from this study indicated that bacteria from the phyla Actinobacteria, Firmicutes, Bacteroidetes and Proteobacteria clustering into 34 genera could be readily isolated from different olive genotypes. These results agree with the gross taxonomic bacterial distribution of isolates already identified in the olive rhizosphere and phyllosphere [75,76], as well as with the composition of bacterial endophytes identified in other woody plants, such as citrus, grapevine or poplar [77,78,79,80].

4.3. Assessment of Microbial Communities by Next-Generation Sequencing

In recent years, improvements in high-throughput sequencing technologies have vastly shifted our understanding regarding the complexity of plant-associated microbiota and has greatly expanded the catalogue of microorganisms known to inhabit plants and their surrounding environment, increasing the identification of millers of uncultivable microorganisms. The use of NGS technologies has opened new opportunities for high-resolution, cost-affordable studies and represents a holistic approach to deepen into the complex biological systems of plant microbiomes [81].
The era of culture-independent plant microbiome study began with an exploratory phase of the diversity and composition of microbial taxa with amplicon-based community profiling approaches. These studies provided insights into the main environmental and biological factors responsible for shaping plant-associated microbial communities [82]. In NGS analysis, the most frequent practice is the use of metabarcoding amplification libraries obtained by amplification from whole isolated DNA of the ITS for fungal communities [83], whereas the 16S rRNA is used for bacteria [84].
The accurate identification of xylem-inhabiting microorganisms could be a determinant for plant protection against vascular pathogens. This accurate identification involves the avoidance of different bias sources in NGS analysis, ranging from the selection of a convenient DNA extraction kit to the appropriate use of specific PCR primer pairs.
The assessment and optimization of a wide range of commercial and ready-to-use DNA extraction kits should be one of the most important initial steps when developing a protocol for plant microbiota analysis due to its potential influence on the structure and diversity of the recovered community profile [85]. Consequently, the bias associated with different commercial kits for DNA extraction in NGS studies must be considered when analyzing the plant-associated microbiome [86,87,88]. Thus, the quality and concentration of DNA obtained, the short processing time and the kit market price must be factors to consider when selecting a suitable DNA extraction protocol. Thus, it has been demonstrated that the method used for DNA extraction can lead to dramatic differences in microbial output composition [86,88], which makes essential the validation of DNA extraction methods with a mock microbial community to ensure an accurate representation of the microbial communities in the samples under study. In fact, the lack of standardization procedures across plant microbiota studies makes comparing them difficult [89]. Several studies have shown the effects of using different commercial kits for DNA extraction of plant-associated microorganisms in NGS studies [59,90,91]. In olive, the comparison of 12 DNA extraction kits indicated that the most accurate description of a bacterial mock community artificially inoculated on xylem sap samples was generated when using the PowerPlant DNA extraction kit (QIAGEN) [59]. The DNeasy PowerSoil kit (QIAGEN) also showed good characteristics and it could be used to analyse olive microbiota, especially in studies in which other plant niches such as the rhizosphere need to be explored. In fact, these kits are recommended for extracting microbial DNA from environmental samples in the Earth Microbiome and the Human Microbiome Projects, two of the largest microbiome initiatives worldwide [92].
Another procedure that may influence the assessment of microbial communities is the use of appropriate PCR primer pairs to avoid undesired co-amplification of mitochondria and chloroplasts, which may strongly affect the characterization of the microbial community composition of plant-associated material [60,93,94,95,96]. Additionally, the results of bacterial profiling can vary considerably according to the hypervariable region that is amplified within the 16S rRNA, which depends on the choice of primers [60,97]. Multiple primer pairs are available for 16S rRNA analysis; consequently, each pair needs to be carefully selected and tested on specific samples to avoid taxonomy biases in the microbial-community analysis, and to allow for a comparison with different datasets [60,98]. For olive microbiome research, the primer pair 799F-1115R provided a higher depth and taxa coverage, with a low percentage of plant mitochondria sequences co-amplified and with the benefit of not needing an additional purification step (i.e., the excision of the PCR-amplification products from agarose gels) as shown for other primer pairs [60].

5. Biotic and Abiotic Factors That Influence Xylem Microbiota

While there are a huge number of studies that focus on the description of the soil- and root-associated microbiome, only a few publications have focused on identifying the diversity in the xylem microbiome and its role in plant health and productivity [52,53,54,55,59,99,100]. The lack of comprehensive studies on this plant niche may be due, in part, to the technical difficulties that are involved in the isolation of the xylem-inhabiting microorganisms, as stated above, or due to the microbiome complexity itself, which can also be affected by several biotic (plant age and developmental stage and the host genotype) [39,52,60] and abiotic (agronomic factors, climate, seasonality, etc.) factors [5,39,101,102,103].

5.1. Plant-Associated Factors

Several plant-associated factors can modulate and influence microbial diversity in host plants, such as plant niche, plant age or developmental stage, plant genotype and the use of rootstocks (Figure 2). Soil is considered a large reservoir of microorganisms that interact with plants, which are influenced by root exudates and secretions, being crucial for plant growth and health. Interestingly, microorganisms associated with plant roots might help plants access particular chemical pools, such as nitrate, ammonium or amino-acid sources of nitrogen, thereby generating a specificity response in plant–microbe–soil interactions [104]. The belowground fraction of the plant compartment formed by soil, rhizosphere and roots has been widely analyzed over the last years [1,105,106,107,108,109], as well as the aboveground portion composed of stems, fruits and the phyllosphere [110,111,112,113]. Differences in microbial taxa have been found, mainly according to plant niche, which may be explained by the classical definition that each microbial community occupies and colonizes its own plant niche. This niche adaptation may also have a major role in the selective filtering and recruitment of different microorganisms that results in successful colonizers inhabiting the same host niche [8], as reported for various host plants, such as poplar trees [114], agave and cacti species [115,116], Arabidopsis thaliana [117,118] and olive [119].
Additionally, several studies have reported differences in microbiome community composition as a function of plant age or genotype, but mainly in herbaceous species (e.g., mustard, potato, Arabidopsis or soybean) [120,121,122,123], with only a few studies in woody crops (e.g., olive, pine, oak) [39,124,125,126]. In woody crops, the use of rootstocks is the most practical, long-term and economically efficient disease control measure for soilborne plant pathogens that must be also considered as a modulating factor of microbiome assemblages in those crops [127,128,129].
On the other hand, the influence of plant age on the chemical composition of xylem sap has been overlooked, as only a few studies have described this interaction in leaves and roots. Nevertheless, some metabolomic studies have shown the existence of some differentiation of chemical compound dynamics during different plant growth stages in various herbaceous plants [92,130,131,132,133], which may result from different biological activities of the plant host or due to variations in soil properties or environmental conditions [130,131]. Plant age has also been reported to have an undoubted effect on the microbial community structure and assembly. Thus, several studies have indicated differences in the microbial community composition according to plant age, but this has been mainly addressed in herbaceous species (i.e., mustard, potato, Arabidopsis and soybean) [120,121,122,123,134] and much less in woody species [125,126], with only two studies conducted in olive [39,124]. In olive, the metabolomic and ionomic profiles of xylem sap have revealed changes according to plant age, showing significantly higher levels of glucose, fructose, sucrose and mannitol, choline, B and PO43− in adult trees, whereas NO3− and Rb were significantly enriched in olive plantlets [39].
Finally, several studies with domesticated crop species have indicated differences in microbiome community composition between wild accessions and modern cultivated varieties, although, as for other features, mainly for herbaceous species (e.g., barley, bean maize, and rice [135,136,137,138]), and less so in woody crops [99,139,140], but including olive [76,141,142,143]. In the same way, to date, there are few studies addressing how the host genotype influences its microbiome [123,144,145], although some works have shown that microbial community adaptation to host genotypes is stronger at early stages, but the relative importance of host genotype declines with time [144]. Some of the studies focusing on olive have shown the existence of significant differences in population densities and community composition of xylem-limited microorganisms according to the olive genotype [39,52]. However, this should be further explored, including the same olive cultivars growing under different environmental conditions, to be able to differentiate between the effect of the olive genotype and that of the environment [146].

5.2. Environmental Factors

Plants and their microbial communities are exposed to environmental factors, such as soil physicochemical properties (pH, salinity, texture, structure, moisture, mineral and soil organic matter content, etc.), climatic conditions (temperature, precipitation, seasonality, etc.) and agronomic and farming practices (use of chemical and biofertilizers, cover crops, etc.) [103]. In this context, a strong seasonality effect on the diversity and composition of the xylem microbiome has been reported for grapes [54] and olives [146] and Anguita-Maeso et al., unpublished results. Furthermore, numerous studies using metabarcoding sequencing have proved that soil type is a major factor driving root microbiome structure [147], while soil pH exerts a stronger impact on total community composition, even at very high taxonomic ranks [148]. Additionally, drought is one of the abiotic factors that more strongly affect plant-associated microorganisms and is positioned as a determinant environmental stressor in agriculture that can alter the composition of root microbiomes by modifying the abundance of certain microbial taxa [106,149]. On the other hand, some common agricultural practices, such as crop rotation, application of chemicals (e.g., ammonium sulphate, ammonium phosphate and urea) and natural fertilizers (e.g., seaweed products and manure) currently used by farmers to improve yield and quality of their products could have a positive, neutral or negative impact on the diversity and structure of plant-associated microbial communities [150].

5.3. Infection by Vascular Pathogens

Plants have evolved their own adaptations to alleviate most biotic and abiotic stresses in nature, and they rely on microbial partners to survive and defend themselves against harmful microbial invaders and pathogens [151]. Pathogenic organisms require recognition and communication with a host to suppress their immune response, allowing the pathogen to enter the host tissue and infect it [152].
Table 1. Summary of main methodological, abiotic and biotic factors that influence the characterization of the xylem-associated microbiome.
Table 1. Summary of main methodological, abiotic and biotic factors that influence the characterization of the xylem-associated microbiome.
Methods for Extracting the Xylem MicrobiomeReference
Root pressure exudate method
Scholander–Hammel pressure vessel method
Root pressurizing method according to Passioura
Vacuum pump
Scholander chamber with external port
Cross-section excision and capillary movement
Negative pressure with handheld needleless syringes
Macerated xylem tissue
Methods for isolation and identification of microbiome
Culture-dependent approaches
Culture-independent approaches (NGS)
Biotic and abiotic factors
Plant-associated factors:
   Ecological niche[114,115,116,117,118,119]
   Plant age [39,120,121,122,123,124,125,126]
   Plant genotype[39,52,123,144,145]
Environmental factors:
   Soil type[147]
   Soil pH[148]
   Agricultural practices[150]
Infection by vascular pathogens:
   Verticillium dahliae[15,153]
   Xylella fastidiosa[64,154,155,156,157]
Several studies have described differences in plant microbiota when comparing infected and healthy plants, reporting changes in plant host microbiota by direct inhibition or/and by indirectly shifting the microbiome composition in infected plants [5,64,158,159]. In this context, some authors have studied the effect of some vascular pathogens, including X. fastidiosa [154,155,156,157] and V. dahliae [15,153] in the metabolomic and ionomic profiles of olive trees. Thus, specific chemical compounds detected in stems, leaves and fruits have been indicated to potentially be involved in the defense mechanisms of the host plant against those pathogens. In parallel, some differences in xylem sap microbial composition have been associated with the differential disease reaction observed in certain olive genotypes to those vascular pathogens [102,160]. A recent study described the changes in the diversity and structural profile of the microbial communities associated with the infection of almond trees by X. fastidiosa [64], showing that X. fastidiosa infection reshapes the xylem-associated microbiome. Finally, some studies have indicated that a modification of the microbial communities inhabiting the xylem vessels, or a reduction of their diversity, can induce changes in the resistance response of the host plant [5]. Moreover, modification of microbial composition during olive propagation, which is conducted in vitro under aseptic conditions, can induce changes and alter the composition of the xylem microbiome by excluding some beneficial endophytes which were determinant in the breakdown of resistance in a wild olive genotype to the vascular plant pathogen V. dahliae when grown in infested soil [5].

6. Future Perspectives for Xylem Microbiome Analysis

Bioinformatics analyses represent a valuable tool for characterizing the diversity of plant-colonizing microorganisms and their functions and interactions in a particular plant niche and will lead to a better understanding of the plant microbiome for its exploitation in agriculture to improve plant growth, health and crop productivity [119]. Microbial network analysis is a novel exploratory data analysis technique that can be used to derive hypotheses from the microbial composition of thousands of samples sequenced by NGS. Network analysis represents an approach for exploring and identifying patterns in large, complex datasets that are difficult to detect using the standard alpha/beta diversity metrics widely used in microbial ecology and may help to investigate potential associations among microbial taxa across spatial or temporal gradients [161]. Exploring co-occurrence patterns between microorganisms can help to identify potential environmental factors (biotic and abiotic interactions), habitat affinities linked to a variety of inter-dependent factors or shared physiologies among community members that could guide more focused studies or experimental perspectives.
Several authors have described the importance and ecological interpretations of the cross-kingdom co-occurrence networks in the plant microbiome [162,163]. Network analyses have identified the existence of interactions among the myriad of endophytes present in natural communities and other potential higher-order interactions [164]. Thus, this analysis has contributed to the discovery of hub or keystone microbial taxa in the plant microbiome. In fact, leaves of Arabidopsis thaliana, a fungal species, Dioszegia sp., and an oomycete, Albugo sp., were detected as hubs in the networks and experimentally validated as keystone species [165]; whereas in the wild rice seed microbiome, two fungal species were identified to be hub species in the cross-kingdom network [166]. This data analysis tool can be used to determine the existence of aggregation or exclusion interactions in xylem-associated microbiomes and reveal keystone microbial players in the xylem of olive trees to fight against vascular pathogens to contribute to the production of olive plants that are more resilient to these pathogens.
Amplicon profiling approaches have provided insights into community structure and phylogenetic diversity of plant-associated microbes over last decades. However, there is a need to move forward from the era of describing the taxonomic profile of plant niches in order to unravel the microbial activities encoded within the plant holobiont. This step is critical to understanding how microbial communities can execute plant growth and plant protection actions, in order to exploit them as a potential tool to increase plant fitness and health [2]. In this regard, metagenomics, as a cutting-edge technique, is the most recent technology that has emerged to address these questions. The plant-associated metagenomes are defined as the set of genes encoded by any particular microbiota that can provide the host plant with critical nutrients, protection from plant pathogens, production of functional plant hormones and tolerance to abiotic stresses, etc. Metagenomics will also contribute to improving our understanding of species composition, genetic diversity, inter-species interactions and species evolution in the context of different ecological niches [164]. However, to the best of our knowledge, to date, only one study has analyzed the olive xylem microbiome by metagenomic analysis, and was conducted by Giampetruzzi et al. (2020) [102]. These authors studied the dynamics of X. fastidiosa infections and its associated endophytic microbiome in susceptible ‘Kalamata’ and resistant ‘FS17’ olive cultivars at two different stages of pathogen infection, concluding that the bacterial and fungal communities present in the xylem of olive trees appeared to be more tightly structured by season and X. fastidiosa abundance than by host cultivar, probably due to the high pathogen inoculum pressure in the orchard where olive trees were sampled [102].
The next generation of cultured-based methods, commonly known as culturomics, has been declared the new implement on the block of ‘omics’ approaches. Microbial culturomics has emerged as a successful tool to isolate high numbers of microbes and identify new species that will complement molecular techniques, providing another approach for determining the composition of microbial populations living in diverse environments [167]. This strategy overbears the importance of isolating single cells of environmental microbiomes and bringing them into cultivation. It needs to be accomplished based on the diversification and multiple combinations of various artificial growth media, incubation conditions simulating environmental conditions of the niche of study and the duration of incubation time to favor rare or slow-growing microorganisms. Consequently, there is still a long way to go before standardizing culturomics, which is essential to complement the data obtained from culture-independent NGS analyses [168].
Improving microbial culturability is also essential for a better understanding of plant–microbiota interactions and their functions in the complex ecological niches of the plant holobiont. Culturomics has been designed, optimized and largely applied in human microbiology, but has not yet been fully exploited in plant microbiology [169]. In fact, only a few studies have focused on the design of new media and approaches to improve the culturability of novel bacterial taxa from the uncultured fraction of plant-associated bacterial communities [170,171]. Most of the known microbial phyla (ca. 120 bacterial and 20 archaeal phyla) contain only a few cultivable representatives [172]. Nowadays, no culture media are described for axenic growth of xylem microbiota, which is crucial to understand the ecological interactions of xylem-inhabiting microorganisms with vascular pathogens. For that reason, the characterization of different broth culture media mimicking xylem sap composition for their ability to sustain growth of olive xylem-inhabiting microorganisms is needed to decipher the ecological interactions of xylem-inhabiting pathogens with the indigenous plant endophytic microorganisms. In this regard, we have evaluated four solid media [52] and six broth culture media mimicking the olive xylem sap composition [173] (Anguita-Maeso et al. unpublished results) to support the growth of olive xylem-inhabiting microorganisms. A total of 66 genera of olive xylem-inhabiting bacteria were identified that could be cultured in any of the culture media tested, from which, about 42% were previously described as bacterial endophytes of the plant stem in other studies, and the remaining ones are novel cultivable bacteria associated with the plant endosphere. These results can be relevant for future studies aimed at culturing xylem-inhabiting microorganisms potentially involved in host tolerance and/or plant defense against xylem-inhabiting pathogens, or may help to select synthetic microbial communities that are easy to culture and that can be tested in planta through endotherapy treatment to determine their ability to suppress vascular diseases.
Thus, the application of xylem microbial consortia is an emerging approach to promote plant growth and biocontrol of vascular plant pathogens. The application of microbial consortia into the xylem vessels by endotherapy can be a powerful tool for modifying the native xylem microbiome of a woody plant to control diseases caused by xylem-inhabiting pathogens or the plant physiology and growth. These microbial consortia can be designed or obtained by two approaches: (1) by extracting the natural xylem microbiome from a different genotype (e.g., a resistant variety) and transplanting it into the desired plant genotype; or (2) it can be produced by in vitro culturing of selected microorganisms independently or as a consortium.
In regard to the first approach, a pilot experiment of a xylem endotherapy treatment was conducted in our laboratory and focused on the modification of the xylem microbiome composition of plantlets of two cultivated olive cultivars (‘Picual’ and ‘Arbequina’) by transplanting an external xylem microbiome obtained from a wild olive genotype, ‘Acebuche’, which showed a fairly different microbial community composition compared to that of the cultivated genotypes. Then, we evaluated the changes in the xylem microbial composition of the challenged plants over time. Results indicated that treated ‘Picual’ and ‘Arbequina’ olive genotypes showed new bacterial species in the first months after the endotherapy treatment. Additionally, although there were no clear differences in the beta-diversity according to the endotherapy treatment, some trends were observed across the different sampling times in each olive genotype that were mainly associated with the plant growth stage, rather than the endotherapy treatment. These results indicate that the xylem microbiome of olive plants is somehow resilient to drastic changes from invading microorganisms [174] (Anguita-Maeso et al., unpublished results).
For the second approach, endotherapy treatments with microorganisms artificially cultured prior to inoculation have already been explored to control some plant pathogens of woody trees, including beech [175] and elm [176]. Currently, we are evaluating the possibility of modifying the xylem microbiome composition of olive by transplanting a microbiome artificially cultured in liquid media mimicking the xylem sap composition and monitoring the stability of the challenged microbial community composition over time. When optimized, this technique can settle the basis to inoculate ad hoc selected microbial consortia or synthetic communities (SynCom) to control diseases caused by xylem-inhabiting pathogens, such as V. dahliae or X. fastidiosa, and/or to modify olive plant physiology and growth.
Finally, the plant-associated microbiome is not only composed of prokaryotic organisms (e.g., bacteria and archaea), but also of other less studied biota members, including unicellular (e.g., protozoa) and multicellular (e.g., fungi) eukaryotes and viruses, which all may play important roles in plant growth and should not be overlooked in future studies [177]. Therefore, additional research into the dynamic interactions between or among these less represented biota communities within the plant microbiome are necessary to better guide the harnessing of the plant microbiome to increase crop yield and quality, as well as to increase its resilience against vascular pathogens. One approach to directly explore the whole plant microbiome is based on an amplification-free NGS approach, defined as shotgun whole genome sequencing. This approach can be technically employed for general plant microbiome identification, but can also be used specifically for the detection of vascular pathogens, paving the way for novel sequencing opportunities as an effective surveillance tool for the detection of plant pathogens [178].

Author Contributions

M.A.-M. and B.B.L. conceived review and wrote the manuscript; J.A.N.-C. contributed to reviewing the manuscript. All authors have read and agreed to the published version of the manuscript.


This research was funded by projects AGL2016-75606-R, PID2020-114917RB-I00 (Programa Estatal de I + D Orientado a los Retos de la Sociedad from Spanish Government, the Spanish State Research Agency and FEDER-EU); TED2021-130110B-C41 (Proyectos Orientados a la Transición Ecológica y a la Transición Digital-Plan de Recuperación, Transformación y Resiliencia from Spanish Government, the Spanish State Research Agency) and XF-ACTORS (Xylella fastidiosa Active Containment Through a Multidisciplinary Oriented Research Strategy; grant 727987 from the European Union’s Horizon 2020 Framework Research Programme). MA-M acknowledges the research fellowship BES-2017-082361 from the Spanish Ministry of Economy and Competitiveness.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.


  1. Berendsen, R.L.; Pieterse, C.M.J.; Bakker, P.A.H.M. The rhizosphere microbiome and plant health. Trends Plant Sci. 2012, 17, 478–486. [Google Scholar] [CrossRef] [PubMed]
  2. Schlaeppi, K.; Bulgarelli, D. The Plant Microbiome at Work. Mol. Plant Microbe Interact. 2015, 28, 212–217. [Google Scholar] [CrossRef] [PubMed][Green Version]
  3. Chaparro, J.M.; Sheflin, A.M.; Manter, D.K.; Vivanco, J.M. Manipulating the soil microbiome to increase soil health and plant fertility. Biol. Fertil. Soils 2012, 48, 489–499. [Google Scholar] [CrossRef]
  4. Weller, D.M.; Raaijmakers, J.M.; Gardener, B.B.M.; Thomashow, L.S. Microbial populations responsible for specific soil suppressiveness to plant pathogens. Annu. Rev. Phytopathol. 2002, 40, 309–348. [Google Scholar] [CrossRef][Green Version]
  5. Anguita-Maeso, M.; Trapero-Casas, J.L.; Olivares-García, C.; Ruano-Rosa, D.; Palomo-Ríos, E.; Jiménez-Díaz, R.M.; Navas-Cortés, J.A.; Landa, B.B. Verticillium dahliae inoculation and in vitro propagation modify the xylem microbiome and disease reaction to Verticillium wilt in a wild olive genotype. Front. Plant Sci. 2021, 12, 250. [Google Scholar] [CrossRef] [PubMed]
  6. Carrión, V.J.; Perez-Jaramillo, J.; Cordovez, V.; Tracanna, V.; de Hollander, M.; Ruiz-Buck, D.; Mendes, L.W.; van Ijcken, W.F.J.; Gomez-Exposito, R.; Elsayed, S.S.; et al. Pathogen-induced activation of disease-suppressive functions in the endophytic root microbiome. Science (80) 2019, 366, 606–612. [Google Scholar] [CrossRef]
  7. Song, C.; Zhu, F.; Carrión, V.J.; Cordovez, V. Beyond Plant Microbiome Composition: Exploiting Microbial Functions and Plant Traits via Integrated Approaches. Front. Bioeng. Biotechnol. 2020, 8, 896. [Google Scholar] [CrossRef]
  8. Trivedi, P.; Leach, J.E.; Tringe, S.G.; Sa, T.; Singh, B.K. Plant–microbiome interactions: From community assembly to plant health. Nat. Rev. Microbiol. 2020, 18, 607–621. [Google Scholar] [CrossRef]
  9. Allen, H.D.; Randall, R.E.; Amable, G.S.; Devereux, B.J. The impact of changing olive cultivation practices on the ground flora of olive groves in the Messara and Psiloritis regions, Crete, Greece. Land Degrad. Dev. 2006, 17, 249–273. [Google Scholar] [CrossRef]
  10. Gómez, J.A.; Infante-Amate, J.; De Molina, G.M.; Vanwalleghem, T.; Taguas, V.E.; Lorite, I. Olive Cultivation, its Impact on Soil Erosion and its Progression into Yield Impacts in Southern Spain in the Past as a Key to a Future of Increasing Climate Uncertainty. Agriculture 2014, 4, 170–198. [Google Scholar] [CrossRef][Green Version]
  11. Tscheulin, T.; Neokosmidis, L.; Petanidou, T.; Settele, J. Influence of landscape context on the abundance and diversity of bees in Mediterranean olive groves. Bull. Entomol. Res. 2011, 101, 557–564. [Google Scholar] [CrossRef] [PubMed][Green Version]
  12. Jiménez-Díaz, R.M.; Cirulli, M.; Bubici, G.; del Mar Jiménez-Gasco, M.; Antoniou, P.P.; Tjamos, E.C. Verticillium Wilt, a major threat to olive production: Current status and future prospects for its management. Plant Dis. 2011, 96, 304–329. [Google Scholar] [CrossRef] [PubMed][Green Version]
  13. Saponari, M.; Giampetruzzi, A.; Loconsole, G.; Boscia, D.; Saldarelli, P. Xylella fastidiosa in olive in Apulia: Where we stand. Phytopathology 2018, 109, 175–186. [Google Scholar] [CrossRef] [PubMed][Green Version]
  14. Almeida, R.P.P.; De La Fuente, L.; Koebnik, R.; Lopes, J.R.S.; Parnell, S.; Scherm, H. Addressing the New Global Threat of Xylella fastidiosa. Phytopathology 2019, 109, 172–174. [Google Scholar] [CrossRef][Green Version]
  15. Landa, B.B.; Pérez, A.G.; Luaces, P.; Montes-Borrego, M.; Navas-Cortés, J.A.; Sanz, C. Insights into the effect of Verticillium dahliae defoliating-pathotype infection on the content of phenolic and volatile compounds related to the sensory properties of virgin olive oil. Front. Plant Sci. 2019, 10, 232. [Google Scholar] [CrossRef] [PubMed][Green Version]
  16. Schneider, K.; van der Werf, W.; Cendoya, M.; Mourits, M.; Navas-Cortés, J.A.; Vicent, A.; Oude Lansink, A. Impact of Xylella fastidiosa subspecies pauca in European olives. Proc. Natl. Acad. Sci. USA 2020, 117, 9250–9259. [Google Scholar] [CrossRef][Green Version]
  17. Berlanger, I.; Powelson, M.L. Verticillium wilt. Plant Health Instr. 2000, 151, 109–110. [Google Scholar] [CrossRef]
  18. Báidez, A.G.; Gómez, P.; Del Río, J.A.; Ortuño, A. Dysfunctionality of the xylem in Olea europaea L. Plants associated with the infection process by Verticillium dahliae Kleb. Role of phenolic compounds in plant defense mechanism. J. Agric. Food Chem. 2007, 55, 3373–3377. [Google Scholar] [CrossRef]
  19. López-Escudero, F.J.; Mercado-Blanco, J.; Roca, J.M.; Valverde-Corredor, A.; Blanco-López, M.Á. Verticillium wilt of olive in the Guadalquivir Valley (southern Spain): Relations with some agronomical factors and spread of Verticillium dahliae. Phytopathol. Mediterr. 2010, 49, 370–380. [Google Scholar] [CrossRef]
  20. Bubici, G.; Cirulli, M. Control of Verticillium wilt of olive by resistant rootstocks. Plant Soil 2012, 352, 363–376. [Google Scholar] [CrossRef]
  21. Jiménez-Fernández, D.; Trapero-Casas, J.L.; Landa, B.B.; Navas-Cortés, J.A.; Bubici, G.; Cirulli, M.; Jiménez-Díaz, R.M. Characterization of resistance against the olive-defoliating Verticillium dahliae pathotype in selected clones of wild olive. Plant Pathol. 2016, 65, 1279–1291. [Google Scholar] [CrossRef][Green Version]
  22. Montes-Osuna, N.; Mercado-Blanco, J. Verticillium Wilt of Olive and Its Control: What Did We Learn during the Last Decade? Plants 2020, 9, 735. [Google Scholar] [CrossRef] [PubMed]
  23. Ostos, E.; Garcia-Lopez, M.T.; Porras, R.; Lopez-Escudero, F.J.; Trapero-Casas, A.; Michailides, T.J.; Moral, J. Effect of cultivar resistance and soil management on spatial–temporal development of Verticillium wilt of olive: A long-term study. Front. Plant Sci. 2020, 11, 1595. [Google Scholar] [CrossRef]
  24. Saponari, M.; Boscia, D.; Altamura, G.; Loconsole, G.; Zicca, S.; D’Attoma, G.; Morelli, M.; Palmisano, F.; Saponari, A.; Tavano, D.; et al. Isolation and pathogenicity of Xylella fastidiosa associated to the olive quick decline syndrome in southern Italy. Sci. Rep. 2017, 7, 17723. [Google Scholar] [CrossRef] [PubMed][Green Version]
  25. Bucci, E.M. Xylella fastidiosa, a new plant pathogen that threatens global farming: Ecology, molecular biology, search for remedies. Biochem. Biophys. Res. Commun. 2018, 502, 173–182. [Google Scholar] [CrossRef] [PubMed]
  26. Schaad, N.W.; Postnikova, E.; Lacy, G.; Fatmi, M.; Chang, C.-J. Xylella fastidiosa subspecies: X. fastidiosa subsp piercei, subsp. nov., X. fastidiosa subsp. multiplex subsp. nov., and X. fastidiosa subsp. pauca subsp. nov. Syst. Appl. Microbiol. 2004, 27, 763. [Google Scholar] [CrossRef]
  27. EFSA. Effectiveness of in planta control measures for Xylella fastidiosa. EFSA J. 2019, 17, e05666. [Google Scholar] [CrossRef]
  28. Di Serio, F.; Bodino, N.; Cavalieri, V.; Demichelis, S.; Di Carolo, M.; Dongiovanni, C.; Fumarola, G.; Gilioli, G.; Guerrieri, E.; Picciotti, U.; et al. Collection of data and information on biology and control of vectors of Xylella fastidiosa. EFSA Support. Publ. 2019, 16, 1628E. [Google Scholar] [CrossRef]
  29. Morelli, M.; García-Madero, J.M.; Jos, Á.; Saldarelli, P.; Dongiovanni, C.; Kovacova, M.; Saponari, M.; Baños Arjona, A.; Hackl, E.; Webb, S.; et al. Xylella fastidiosa in Olive: A Review of Control Attempts and Current Management. Microorganisms 2021, 9, 1771. [Google Scholar] [CrossRef]
  30. Landa, B.B.; Saponari, M.; Feitosa-Junior, O.R.; Giampetruzzi, A.; Vieira, F.J.D.; Mor, E.; Robatzek, S. Xylella fastidiosa’s relationships: The bacterium, the host plants and the plant microbiome. New Phytol. 2022, 234, 1598–1605. [Google Scholar] [CrossRef]
  31. Doty, S.L. Functional importance of the plant microbiome: Implications for agriculture, forestry and bioenergy. Funct. Importance Plant Microbiome. Implic. Agric. For. Bioenergy 2017, 178, 1–111. [Google Scholar] [CrossRef]
  32. Rabiey, M.; Hailey, L.E.; Roy, S.R.; Grenz, K.; Al-Zadjali, M.A.S.; Barrett, G.A.; Jackson, R.W. Endophytes vs tree pathogens and pests: Can they be used as biological control agents to improve tree health? Eur. J. Plant Pathol. 2019, 155, 711–729. [Google Scholar] [CrossRef][Green Version]
  33. De Boer, A.H.; Volkov, V. Logistics of water and salt transport through the plant: Structure and functioning of the xylem. Plant Cell Environ. 2003, 26, 87–101. [Google Scholar] [CrossRef][Green Version]
  34. White, P.J. Chapter 3—Long-Distance Transport in the Xylem and Phloem, 3rd ed.; Marschner’s Mineral Nutrition of Higher Plants; Academic Press: San Diego, CA, USA, 2012; pp. 49–70. ISBN 978-0-12-384905-2. [Google Scholar]
  35. Yadeta, K.; Thomma, B. The xylem as battleground for plant hosts and vascular wilt pathogens. Front. Plant Sci. 2013, 4, 97. [Google Scholar] [CrossRef] [PubMed][Green Version]
  36. Schurr, U. Xylem sap sampling—New approaches to an old topic. Trends Plant Sci. 1998, 3, 293–298. [Google Scholar] [CrossRef]
  37. Fernández-García, N.; Hernández, M.; Casado-Vela, J.; Bru, R.; Elortza, F.; Hedden, P.; Olmos, E. Changes to the proteome and targeted metabolites of xylem sap in Brassica oleracea in response to salt stress. Plant Cell Environ. 2011, 34, 821–836. [Google Scholar] [CrossRef]
  38. Krishnan, H.B.; Natarajan, S.S.; Bennett, J.O.; Sicher, R.C. Protein and metabolite composition of xylem sap from field-grown soybeans (Glycine max). Planta 2011, 233, 921–931. [Google Scholar] [CrossRef]
  39. Anguita-Maeso, M.; Haro, C.; Montes-Borrego, M.; De La Fuente, L.; Navas-Cortés, J.A.; Landa, B.B. Metabolomic, ionomic and microbial characterization of olive xylem sap reveals differences according to plant age and genotype. Agronomy 2021, 11, 6. [Google Scholar] [CrossRef]
  40. Lowe-Power, T.M.; Hendrich, C.G.; von Roepenack-Lahaye, E.; Li, B.; Wu, D.; Mitra, R.; Dalsing, B.L.; Ricca, P.; Naidoo, J.; Cook, D.; et al. Metabolomics of tomato xylem sap during bacterial wilt reveals Ralstonia solanacearum produces abundant putrescine, a metabolite that accelerates wilt disease. Environ. Microbiol. 2018, 20, 1330–1349. [Google Scholar] [CrossRef]
  41. Wallis, C.M.; Chen, J. Grapevine phenolic compounds in xylem sap and tissues are significantly altered during infection by Xylella fastidiosa. Phytopathology 2012, 102, 816–826. [Google Scholar] [CrossRef][Green Version]
  42. Rellán-Álvarez, R.; El-Jendoubi, H.; Wohlgemuth, G.; Abadía, A.; Fiehn, O.; Abadía, J.; Alvarez-Fernández, A. Metabolite profile changes in xylem sap and leaf extracts of strategy I plants in response to iron deficiency and resupply. Front. Plant Sci. 2011, 2, 66. [Google Scholar] [CrossRef][Green Version]
  43. Gallinger, J.; Gross, J. Unraveling the Host Plant Alternation of Cacopsylla pruni—Adults but Not Nymphs Can Survive on Conifers Due to Phloem/Xylem Composition. Front. Plant Sci. 2018, 9, 484. [Google Scholar] [CrossRef] [PubMed]
  44. Sofo, A.; Fausto, C.; Mininni, A.N.; Dichio, B.; Lucini, L. Soil management type differentially modulates the metabolomic profile of olive xylem sap. Plant Physiol. Biochem. 2019, 139, 707–714. [Google Scholar] [CrossRef] [PubMed]
  45. Boutaj, H.; Chakhchar, A.; Meddich, A.; Wahbi, S.; El Alaoui-Talibi, Z.; Douira, A.; Filali-Maltouf, A.; El Modafar, C. Mycorrhizal autochthonous consortium induced defense-related mechanisms of olive trees against Verticillium dahliae. J. Plant Dis. Prot. 2021, 128, 225–237. [Google Scholar] [CrossRef]
  46. Novelli, S.; Gismondi, A.; Di Marco, G.; Canuti, L.; Nanni, V.; Canini, A. Plant defense factors involved in Olea europaea resistance against Xylella fastidiosa infection. J. Plant Res. 2019, 132, 439–455. [Google Scholar] [CrossRef] [PubMed]
  47. Fausto, C.; Araniti, F.; Mininni, A.N.; Crecchio, C.; Scagliola, M.; Bleve, G.; Dichio, B.; Sofo, A. Differential olive grove management regulates the levels of primary metabolites in xylem sap. Plant Soil 2021, 460, 281–296. [Google Scholar] [CrossRef]
  48. McCully, M.E. Niches for bacterial endophytes in crop plants: A plant biologist’s view. Funct. Plant Biol. 2001, 28, 983–990. [Google Scholar] [CrossRef]
  49. De La Fuente, L.; Merfa, M.V.; Cobine, P.A.; Coleman, J.J. Pathogen Adaptation to the Xylem Environment. Annu. Rev. Phytopathol. 2022, 60, 163–186. [Google Scholar] [CrossRef]
  50. Reinhold-Hurek, B.; Hurek, T. Living inside plants: Bacterial endophytes. Curr. Opin. Plant Biol. 2011, 14, 435–443. [Google Scholar] [CrossRef]
  51. Berg, G.; Grube, M.; Schloter, M.; Smalla, K. Unraveling the plant microbiome: Looking back and future perspectives. Front. Microbiol. 2014, 5, 148. [Google Scholar] [CrossRef][Green Version]
  52. Anguita-Maeso, M.; Olivares-García, C.; Haro, C.; Imperial, J.; Navas-Cortés, J.A.; Landa, B.B. Culture-dependent and culture-independent characterization of the olive xylem microbiota: Effect of sap extraction methods. Front. Plant Sci. 2020, 10, 1708. [Google Scholar] [CrossRef][Green Version]
  53. Martín, J.A.; Witzell, J.; Blumenstein, K.; Rozpedowska, E.; Helander, M.; Sieber, T.N.; Gil, L. Resistance to Dutch Elm Disease Reduces Presence of Xylem Endophytic Fungi in Elms (Ulmus spp.). PLoS ONE 2013, 8, e56987. [Google Scholar] [CrossRef] [PubMed][Green Version]
  54. Deyett, E.; Rolshausen, P.E. Temporal dynamics of the sap microbiome of grapevine under high Pierce’s Disease pressure. Front. Plant Sci. 2019, 10, 1246. [Google Scholar] [CrossRef] [PubMed]
  55. Sofo, A.; Mininni, A.N.; Fausto, C.; Scagliola, M.; Crecchio, C.; Xiloyannis, C.; Dichio, B. Evaluation of the possible persistence of potential human pathogenic bacteria in olive orchards irrigated with treated urban wastewater. Sci. Total Environ. 2019, 658, 763–767. [Google Scholar] [CrossRef] [PubMed]
  56. Vergine, M.; Meyer, J.B.; Cardinale, M.; Sabella, E.; Hartmann, M.; Cherubini, P.; De Bellis, L.; Luvisi, A. The Xylella fastidiosa-resistant olive cultivar “Leccino” has stable endophytic microbiota during the olive quick decline syndrome (OQDS). Pathogens 2020, 9, 35. [Google Scholar] [CrossRef] [PubMed][Green Version]
  57. Alexou, M.; Peuke, A. Methods for Xylem Sap Collection. Methods Mol. Biol. 2013, 953, 195–207. [Google Scholar] [CrossRef] [PubMed]
  58. Passioura, J.B. The Transport of Water from Soil to Shoot in Wheat Seedlings. J. Exp. Bot. 1980, 31, 333–345. [Google Scholar] [CrossRef]
  59. Haro, C.; Anguita-Maeso, M.; Metsis, M.; Navas-Cortés, J.A.; Landa, B.B. Evaluation of established methods for DNA extraction and primer pairs targeting 16S rRNA gene for bacterial microbiota profiling of olive xylem sap. Front. Plant Sci. 2021, 12, 296. [Google Scholar] [CrossRef]
  60. Anguita-Maeso, M.; Haro, C.; Navas-Cortés, J.A.; Landa, B.B. Primer Choice and Xylem-Microbiome-Extraction Method Are Important Determinants in Assessing Xylem Bacterial Community in Olive Trees. Plants 2022, 11, 1320. [Google Scholar] [CrossRef]
  61. Buhtz, A.; Kolasa, A.; Arlt, K.; Walz, C.; Kehr, J. Xylem sap protein composition is conserved among different plant species. Planta 2004, 219, 610–618. [Google Scholar] [CrossRef]
  62. Longchar, B.; Phukan, T.; Yadav, S.; Senthil-Kumar, M. An efficient low-cost xylem sap isolation method for bacterial wilt assays in tomato. Appl. Plant Sci. 2020, 8, e11335. [Google Scholar] [CrossRef] [PubMed]
  63. García-Tejera, O.; López-Bernal, Á.; Orgaz, F.; Testi, L.; Villalobos, F.J. The pitfalls of water potential for irrigation scheduling. Agric. Water Manag. 2021, 243, 106522. [Google Scholar] [CrossRef]
  64. Anguita-Maeso, M.; Ares-Yebra, A.; Haro, C.; Román-Écija, M.; Olivares-García, C.; Costa, J.; Marco-Noales, E.; Ferrer, A.; Navas-Cortés, J.A.; Landa, B.B. Xylella fastidiosa infection reshapes microbial composition and network associations in the xylem of almond trees. Front. Microbiol. 2022, 13, 866085. [Google Scholar] [CrossRef] [PubMed]
  65. Gupta, R.; Anand, G.; Gaur, R.; Yadav, D. Plant-microbiome interactions for sustainable agriculture: A review. Physiol. Mol. Biol. Plants 2021, 27, 165–179. [Google Scholar] [CrossRef]
  66. Lee, S.A.; Park, J.; Chu, B.; Kim, J.M.; Joa, J.-H.; Sang, M.K.; Song, J.; Weon, H.-Y. Comparative analysis of bacterial diversity in the rhizosphere of tomato by culture-dependent and -independent approaches. J. Microbiol. 2016, 54, 823–831. [Google Scholar] [CrossRef]
  67. Armanhi, J.S.L.; De Souza, R.S.C.; Damasceno, N.D.B.; de Araújo, L.M.; Imperial, J.; Arruda, P. A Community-Based Culture Collection for Targeting Novel Plant Growth-Promoting Bacteria from the Sugarcane Microbiome. Front. Plant Sci. 2018, 8, 2191. [Google Scholar] [CrossRef][Green Version]
  68. Miller, K.I.; Qing, C.; Sze, D.M.-Y.; Roufogalis, B.D.; Neilan, B.A. Culturable Endophytes of Medicinal Plants and the Genetic Basis for Their Bioactivity. Microb. Ecol. 2012, 64, 431–449. [Google Scholar] [CrossRef]
  69. Shen, S.Y.; Fulthorpe, R. Seasonal variation of bacterial endophytes in urban trees. Front. Microbiol. 2015, 6, 427. [Google Scholar] [CrossRef]
  70. Yashiro, E.; Spear, R.N.; McManus, P.S. Culture-dependent and culture-independent assessment of bacteria in the apple phyllosphere. J. Appl. Microbiol. 2011, 110, 1284–1296. [Google Scholar] [CrossRef]
  71. Abadi, V.A.J.M.; Sepehri, M.; Rahmani, H.A.; Dolatabad, H.K.; Shamshiripour, M.; Khatabi, B. Diversity and abundance of culturable nitrogen-fixing bacteria in the phyllosphere of maize. J. Appl. Microbiol. 2021, 131, 898–912. [Google Scholar] [CrossRef]
  72. Raaijmakers, J.M.; Kiers, E.T. Rewilding plant microbiomes. Science (80) 2022, 378, 599–600. [Google Scholar] [CrossRef] [PubMed]
  73. Li, J.; Wang, J.; Liu, H.; Macdonald, C.A.; Singh, B.K. Application of microbial inoculants significantly enhances crop productivity: A meta-analysis of studies from 2010 to 2020. J. Sustain. Agric. Environ. 2022, 1, 216–225. [Google Scholar] [CrossRef]
  74. Bai, Y.; Müller, D.B.; Srinivas, G.; Garrido-Oter, R.; Potthoff, E.; Rott, M.; Dombrowski, N.; Münch, P.C.; Spaepen, S.; Remus-Emsermann, M.; et al. Functional overlap of the Arabidopsis leaf and root microbiota. Nature 2015, 528, 364–369. [Google Scholar] [CrossRef] [PubMed]
  75. Ercolani, G.L. Distribution of epiphytic bacteria on olive leaves and the influence of leaf age and sampling time. Microb. Ecol. 1991, 21, 35–48. [Google Scholar] [CrossRef]
  76. Aranda, S.; Montes-Borrego, M.; Jiménez-Díaz, R.M.; Landa, B.B. Microbial communities associated with the root system of wild olives (Olea europaea L. subsp. europaea var. sylvestris) are good reservoirs of bacteria with antagonistic potential against Verticillium dahliae. Plant Soil 2011, 343, 329–345. [Google Scholar] [CrossRef][Green Version]
  77. Bell, C.R.; Dickie, G.A.; Harvey, W.L.G.; Chan, J.W.Y.F. Endophytic bacteria in grapevine. Can. J. Microbiol. 1995, 41, 46–53. [Google Scholar] [CrossRef]
  78. Compant, S.; Mitter, B.; Colli-Mull, J.G.; Gangl, H.; Sessitsch, A. Endophytes of Grapevine Flowers, Berries, and Seeds: Identification of Cultivable Bacteria, Comparison with Other Plant Parts, and Visualization of Niches of Colonization. Microb. Ecol. 2011, 62, 188–197. [Google Scholar] [CrossRef]
  79. Azevedo, J.; Araújo, W.L.; Lacava, P.T. The diversity of citrus endophytic bacteria and their interactions with Xylella fastidiosa and host plants. Genet. Mol. Biol. 2016, 39, 476–491. [Google Scholar] [CrossRef][Green Version]
  80. Durand, A.; Maillard, F.; Alvarez-Lopez, V.; Guinchard, S.; Bertheau, C.; Valot, B.; Blaudez, D.; Chalot, M. Bacterial diversity associated with poplar trees grown on a Hg-contaminated site: Community characterization and isolation of Hg-resistant plant growth-promoting bacteria. Sci. Total Environ. 2018, 622–623, 1165–1177. [Google Scholar] [CrossRef][Green Version]
  81. López-Mondéjar, R.; Kostovčík, M.; Lladó, S.; Carro, L.; García-Fraile, P. Exploring the Plant Microbiome Through Multi-Omics Approaches BT—Probiotics in Agroecosystem; Kumar, V., Kumar, M., Sharma, S., Prasad, R., Eds.; Springer: Singapore, 2017; pp. 233–268. ISBN 978-981-10-4059-7. [Google Scholar]
  82. Bulgarelli, D.; Schlaeppi, K.; Spaepen, S.; van Themaat, E.V.L.; Schulze-Lefert, P. Structure and Functions of the Bacterial Microbiota of Plants. Annu. Rev. Plant Biol. 2013, 64, 807–838. [Google Scholar] [CrossRef][Green Version]
  83. Schoch, C.L.; Seifert, K.A.; Huhndorf, S.; Robert, V.; Spouge, J.L.; Levesque, C.A.; Chen, W.; Consortium, F.B. Nuclear ribosomal internal transcribed spacer (ITS) region as a universal DNA barcode marker for Fungi. Proc. Natl. Acad. Sci. USA 2012, 109, 6241–6246. [Google Scholar] [CrossRef] [PubMed][Green Version]
  84. Case, R.; Boucher, Y.; Dahllöf, I.; Holmström, C.; Doolittle, W.F.; Kjelleberg, S. Use of 16S rRNA and rpoB Genes as Molecular Markers for Microbial Ecology Studies. Appl. Environ. Microbiol. 2007, 73, 278–288. [Google Scholar] [CrossRef] [PubMed][Green Version]
  85. Rubin, B.E.R.; Sanders, J.G.; Hampton-Marcell, J.; Owens, S.M.; Gilbert, J.A.; Moreau, C.S. DNA extraction protocols cause differences in 16S rRNA amplicon sequencing efficiency but not in community profile composition or structure. Microbiologyopen 2014, 3, 910–921. [Google Scholar] [CrossRef][Green Version]
  86. Henderson, G.; Cox, F.; Kittelmann, S.; Miri, V.H.; Zethof, M.; Noel, S.J.; Waghorn, G.C.; Janssen, P.H. Effect of DNA extraction methods and sampling techniques on the apparent structure of cow and sheep rumen microbial communities. PLoS ONE 2013, 8, e74787. [Google Scholar] [CrossRef] [PubMed][Green Version]
  87. Kennedy, N.A.; Walker, A.W.; Berry, S.H.; Duncan, S.H.; Farquarson, F.M.; Louis, P.; Thomson, J.M.; Satsangi, J.; Flint, H.J.; Parkhill, J.; et al. The impact of different DNA extraction kits and laboratories upon the assessment of human gut microbiota composition by 16S rRNA gene sequencing. PLoS ONE 2014, 9, e88982. [Google Scholar] [CrossRef]
  88. Brooks, J.P.; Edwards, D.J.; Harwich, M.D.; Rivera, M.C.; Fettweis, J.M.; Serrano, M.G.; Reris, R.A.; Sheth, N.U.; Huang, B.; Girerd, P.; et al. The truth about metagenomics: Quantifying and counteracting bias in 16S rRNA studies. BMC Microbiol. 2015, 15, 66. [Google Scholar] [CrossRef] [PubMed][Green Version]
  89. Stulberg, E.; Fravel, D.; Proctor, L.M.; Murray, D.M.; LoTempio, J.; Chrisey, L.; Garland, J.; Goodwin, K.; Graber, J.; Harris, M.C.; et al. An assessment of US microbiome research. Nat. Microbiol. 2016, 1, 15015. [Google Scholar] [CrossRef] [PubMed]
  90. Fadiji, A.E.; Babalola, O.O. Metagenomics methods for the study of plant-associated microbial communities: A review. J. Microbiol. Methods 2020, 170, 105860. [Google Scholar] [CrossRef]
  91. Giangacomo, C.; Mohseni, M.; Kovar, L.; Wallace, J.G. Comparing DNA Extraction and 16S rRNA Gene Amplification Methods for Plant-Associated Bacterial Communities. Phytobiomes J. 2020, 5, 190–201. [Google Scholar] [CrossRef]
  92. Thompson, L.R.; Sanders, J.G.; McDonald, D.; Amir, A.; Ladau, J.; Locey, K.J.; Prill, R.J.; Tripathi, A.; Gibbons, S.M.; Ackermann, G.; et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature 2017, 551, 457–463. [Google Scholar] [CrossRef][Green Version]
  93. Beckers, B.; Op De Beeck, M.; Thijs, S.; Truyens, S.; Weyens, N.; Boerjan, W.; Vangronsveld, J. Performance of 16s rDNA primer pairs in the study of rhizosphere and endosphere bacterial microbiomes in metabarcoding studies. Front. Microbiol. 2016, 7, 650. [Google Scholar] [CrossRef] [PubMed][Green Version]
  94. Comeau, A.M.; Li, W.K.W.; Tremblay, J.-É.; Carmack, E.C.; Lovejoy, C. Arctic Ocean Microbial Community Structure before and after the 2007 Record Sea Ice Minimum. PLoS ONE 2011, 6, e27492. [Google Scholar] [CrossRef] [PubMed]
  95. Dyall, S.D.; Brown, M.T.; Johnson, P.J. Ancient invasions: From endosymbionts to organelles. Science 2004, 304, 253–257. [Google Scholar] [CrossRef] [PubMed][Green Version]
  96. Thijs, S.; Op De Beeck, M.; Beckers, B.; Truyens, S.; Stevens, V.; Van Hamme, J.D.; Weyens, N.; Vangronsveld, J. Comparative Evaluation of Four Bacteria-Specific Primer Pairs for 16S rRNA Gene Surveys. Front. Microbiol. 2017, 8, 494. [Google Scholar] [CrossRef] [PubMed][Green Version]
  97. Tremblay, J.; Singh, K.; Fern, A.; Kirton, E.; He, S.; Woyke, T.; Lee, J.; Chen, F.; Dangl, J.; Tringe, S. Primer and platform effects on 16S rRNA tag sequencing. Front. Microbiol. 2015, 6, 771. [Google Scholar] [CrossRef] [PubMed][Green Version]
  98. Klindworth, A.; Pruesse, E.; Schweer, T.; Peplies, J.; Quast, C.; Horn, M.; Glöckner, F.O. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res. 2012, 41, e1. [Google Scholar] [CrossRef] [PubMed]
  99. Deyett, E.; Roper, M.C.; Ruegger, P.; Yang, J.-I.; Borneman, J.; Rolshausen, P.E. Microbial Landscape of the Grapevine Endosphere in the Context of Pierce’s Disease. Phytobiomes J. 2017, 1, 138–149. [Google Scholar] [CrossRef][Green Version]
  100. Fausto, C.; Mininni, A.N.; Sofo, A.; Crecchio, C.; Scagliola, M.; Dichio, B.; Xiloyannis, C. Olive orchard microbiome: Characterisation of bacterial communities in soil-plant compartments and their comparison between sustainable and conventional soil management systems. Plant Ecol. Divers. 2018, 11, 597–610. [Google Scholar] [CrossRef]
  101. Turner, T.R.; James, E.K.; Poole, P.S. The plant microbiome. Genome Biol. 2013, 14, 209. [Google Scholar] [CrossRef][Green Version]
  102. Giampetruzzi, A.; Baptista, P.; Morelli, M.; Cameirão, C.; Lino Neto, T.; Costa, D.; D’Attoma, G.; Abou Kubaa, R.; Altamura, G.; Saponari, M.; et al. Differences in the endophytic microbiome of olive cultivars infected by Xylella fastidiosa across seasons. Pathogens 2020, 9, 723. [Google Scholar] [CrossRef]
  103. Dastogeer, K.M.G.; Tumpa, F.H.; Sultana, A.; Akter, M.A.; Chakraborty, A. Plant microbiome–an account of the factors that shape community composition and diversity. Curr. Plant Biol. 2020, 23, 100161. [Google Scholar] [CrossRef]
  104. Reynolds, H.L.; Packer, A.; Bever, J.D.; Clay, K. Grassroots Ecology: Plant-Microbe-Soil Interactions as Drivers of Plant Community Structure and Dynamics. Ecology 2003, 84, 2281–2291. [Google Scholar] [CrossRef][Green Version]
  105. Fierer, N. Embracing the unknown: Disentangling the complexities of the soil microbiome. Nat. Rev. Microbiol. 2017, 15, 579–590. [Google Scholar] [CrossRef]
  106. Fitzpatrick, C.R.; Copeland, J.; Wang, P.W.; Guttman, D.S.; Kotanen, P.M.; Johnson, M.T.J. Assembly and ecological function of the root microbiome across angiosperm plant species. Proc. Natl. Acad. Sci. USA 2018, 115, E1157–E1165. [Google Scholar] [CrossRef][Green Version]
  107. Bergelson, J.; Mittelstrass, J.; Horton, M.W. Characterizing both bacteria and fungi improves understanding of the Arabidopsis root microbiome. Sci. Rep. 2019, 9, 24. [Google Scholar] [CrossRef] [PubMed][Green Version]
  108. Delgado-Baquerizo, M.; Eldridge, D.J. Cross-Biome Drivers of Soil Bacterial Alpha Diversity on a Worldwide Scale. Ecosystems 2019, 22, 1220–1231. [Google Scholar] [CrossRef][Green Version]
  109. Brunel, C.; Pouteau, R.; Dawson, W.; Pester, M.; Ramirez, K.S.; van Kleunen, M. Towards Unraveling Macroecological Patterns in Rhizosphere Microbiomes. Trends Plant Sci. 2020, 25, 1017–1029. [Google Scholar] [CrossRef] [PubMed]
  110. Droby, S.; Wisniewski, M. The fruit microbiome: A new frontier for postharvest biocontrol and postharvest biology. Postharvest Biol. Technol. 2018, 140, 107–112. [Google Scholar] [CrossRef]
  111. Leveau, J.H.J. A brief from the leaf: Latest research to inform our understanding of the phyllosphere microbiome. Curr. Opin. Microbiol. 2019, 49, 41–49. [Google Scholar] [CrossRef]
  112. Liu, H.; Brettell, L.E.; Singh, B. Linking the Phyllosphere Microbiome to Plant Health. Trends Plant Sci. 2020, 25, 841–844. [Google Scholar] [CrossRef]
  113. Zhang, H.; Serwah Boateng, N.A.; Ngolong Ngea, G.L.; Shi, Y.; Lin, H.; Yang, Q.; Wang, K.; Zhang, X.; Zhao, L.; Droby, S. Unravelling the fruit microbiome: The key for developing effective biological control strategies for postharvest diseases. Compr. Rev. Food Sci. Food Saf. 2021, 20, 4906–4930. [Google Scholar] [CrossRef] [PubMed]
  114. Beckers, B.; Op De Beeck, M.; Weyens, N.; Boerjan, W.; Vangronsveld, J. Structural variability and niche differentiation in the rhizosphere and endosphere bacterial microbiome of field-grown poplar trees. Microbiome 2017, 5, 25. [Google Scholar] [CrossRef] [PubMed][Green Version]
  115. Fonseca-García, C.; Coleman-Derr, D.; Garrido, E.; Visel, A.; Tringe, S.G.; Partida-Martínez, L.P. The Cacti Microbiome: Interplay between Habitat-Filtering and Host-Specificity. Front. Microbiol. 2016, 7, 150. [Google Scholar] [CrossRef] [PubMed][Green Version]
  116. Coleman-Derr, D.; Desgarennes, D.; Fonseca-Garcia, C.; Gross, S.; Clingenpeel, S.; Woyke, T.; North, G.; Visel, A.; Partida-Martinez, L.P.; Tringe, S.G. Plant compartment and biogeography affect microbiome composition in cultivated and native Agave species. New Phytol. 2016, 209, 798–811. [Google Scholar] [CrossRef][Green Version]
  117. Lundberg, D.S.; Lebeis, S.L.; Paredes, S.H.; Yourstone, S.; Gehring, J.; Malfatti, S.; Tremblay, J.; Engelbrektson, A.; Kunin, V.; del Rio, T.G.; et al. Defining the core Arabidopsis thaliana root microbiome. Nature 2012, 488, 86–90. [Google Scholar] [CrossRef][Green Version]
  118. Bulgarelli, D.; Rott, M.; Schlaeppi, K.; Ver Loren van Themaat, E.; Ahmadinejad, N.; Assenza, F.; Rauf, P.; Huettel, B.; Reinhardt, R.; Schmelzer, E.; et al. Revealing structure and assembly cues for Arabidopsis root-inhabiting bacterial microbiota. Nature 2012, 488, 91–95. [Google Scholar] [CrossRef]
  119. Anguita-Maeso, M.; Arias-Giraldo, L.F.; Navas-Cortés, J.A.; de Menezes, A.; Landa, B.B. Bioinformatic pipelines are determinant in the analysis of microbial communities from different ecological niches in cultivated olive trees. In Proceedings of the 4th Annual Conference of the EuroXanth COST Action Integrating Science on Xanthomonadaceae for Integrated Plant Disease Management in Europe, Virtual Conference, 28–30 June 2021; p. 51. Available online: (accessed on 10 January 2023).
  120. Micallef, S.A.; Channer, S.; Shiaris, M.P.; Colon-Carmona, A. Plant age and genotype impact the progression of bacterial community succession in the Arabidopsis rhizosphere. Plant Signal. Behav. 2009, 4, 777–780. [Google Scholar] [CrossRef][Green Version]
  121. Xu, Y.; Wang, G.; Jin, J.; Liu, J.; Zhang, Q.; Liu, X. Bacterial communities in soybean rhizosphere in response to soil type, soybean genotype, and their growth stage. Soil Biol. Biochem. 2009, 41, 919–925. [Google Scholar] [CrossRef]
  122. Marques, J.M.; da Silva, T.F.; Vollu, R.E.; Blank, A.F.; Ding, G.-C.; Seldin, L.; Smalla, K. Plant age and genotype affect the bacterial community composition in the tuber rhizosphere of field-grown sweet potato plants. FEMS Microbiol. Ecol. 2014, 88, 424–435. [Google Scholar] [CrossRef]
  123. Wagner, M.R.; Lundberg, D.S.; del Rio, T.G.; Tringe, S.G.; Dangl, J.L.; Mitchell-Olds, T. Host genotype and age shape the leaf and root microbiomes of a wild perennial plant. Nat. Commun. 2016, 7, 12151. [Google Scholar] [CrossRef][Green Version]
  124. Caliz, J.; Montes-Borrego, M.; Triadó-Margarit, X.; Metsis, M.; Landa, B.B.; Casamayor, E.O. Influence of edaphic, climatic, and agronomic factors on the composition and abundance of nitrifying microorganisms in the rhizosphere of commercial olive crops. PLoS ONE 2015, 10, e0125787. [Google Scholar] [CrossRef] [PubMed][Green Version]
  125. Meaden, S.; Metcalf, C.J.E.; Koskella, B. The effects of host age and spatial location on bacterial community composition in the English Oak tree (Quercus robur). Environ. Microbiol. Rep. 2016, 8, 649–658. [Google Scholar] [CrossRef] [PubMed][Green Version]
  126. Carper, D.L.; Carrell, A.A.; Kueppers, L.M.; Frank, A.C. Bacterial endophyte communities in Pinus flexilis are structured by host age, tissue type, and environmental factors. Plant Soil 2018, 428, 335–352. [Google Scholar] [CrossRef][Green Version]
  127. Marasco, R.; Rolli, E.; Fusi, M.; Michoud, G.; Daffonchio, D. Grapevine rootstocks shape underground bacterial microbiome and networking but not potential functionality. Microbiome 2018, 6, 3. [Google Scholar] [CrossRef][Green Version]
  128. Toju, H.; Okayasu, K.; Notaguchi, M. Leaf-associated microbiomes of grafted tomato plants. Sci. Rep. 2019, 9, 1787. [Google Scholar] [CrossRef][Green Version]
  129. Montes-Borrego, M.; Jiménez-Díaz, R.M.; Trapero-Casas, J.L.; Navas-Cotés, J.A.; Haro, C.; Rivas, J.C.; De La Fuente, L.; Landa, B.B. Metabolomic characterization of xylem sap of different olive cultivars growing in Spain. In Proceedings of the European Conference on Xylella fastidiosa: Finding Answers to a Global Problem, Palma de Mallorca, Spain, 13–15 November 2017; p. 40. [Google Scholar] [CrossRef]
  130. Puzanskiy, R.K.; Yemelyanov, V.V.; Shavarda, A.L.; Gavrilenko, T.A.; Shishova, M.F. Age- and Organ-Specific Differences of Potato (Solanum phureja) Plants Metabolome. Russ. J. Plant Physiol. 2018, 65, 813–823. [Google Scholar] [CrossRef]
  131. Yun, D.-Y.; Kang, Y.-G.; Kim, E.-H.; Kim, M.; Park, N.-H.; Choi, H.-T.; Go, G.H.; Lee, J.H.; Park, J.S.; Hong, Y.-S. Metabolomics approach for understanding geographical dependence of soybean leaf metabolome. Food Res. Int. 2018, 106, 842–852. [Google Scholar] [CrossRef]
  132. Lawal, U.; Mediani, A.; Maulidiani, M.; Shaari, K.; Ismail, I.S.; Khatib, A.; Abas, F. Metabolite profiling of Ipomoea aquatica at different growth stages in correlation to the antioxidant and α-glucosidase inhibitory activities elucidated by 1H NMR-based metabolomics. Sci. Hortic. 2015, 192, 400–408. [Google Scholar] [CrossRef]
  133. Zheng, L.; Wang, M.; Ibarra-Estrada, E.; Wu, C.; Wilson, E.; Verpoorte, R.; Klinkhamer, P.; Choi, Y. Investigation of Chemomarkers of Astragali Radix of Different Ages and Geographical Origin by NMR Profiling. Molecules 2015, 20, 3389–3405. [Google Scholar] [CrossRef][Green Version]
  134. Walters, W.A.; Jin, Z.; Youngblut, N.; Wallace, J.G.; Sutter, J.; Zhang, W.; González-Peña, A.; Peiffer, J.; Koren, O.; Shi, Q.; et al. Large-scale replicated field study of maize rhizosphere identifies heritable microbes. Proc. Natl. Acad. Sci. USA 2018, 115, 7368–7373. [Google Scholar] [CrossRef][Green Version]
  135. Peiffer, J.A.; Spor, A.; Koren, O.; Jin, Z.; Tringe, S.G.; Dangl, J.L.; Buckler, E.S.; Ley, R.E. Diversity and heritability of the maize rhizosphere microbiome under field conditions. Proc. Natl. Acad. Sci. USA 2013, 110, 6548–6553. [Google Scholar] [CrossRef] [PubMed][Green Version]
  136. Bulgarelli, D.; Garrido-Oter, R.; Münch, P.C.; Weiman, A.; Dröge, J.; Pan, Y.; McHardy, A.C.; Schulze-Lefert, P. Structure and Function of the Bacterial Root Microbiota in Wild and Domesticated Barley. Cell Host Microbe 2015, 17, 392–403. [Google Scholar] [CrossRef] [PubMed][Green Version]
  137. Pérez-Jaramillo, J.E.; Carrión, V.J.; Bosse, M.; Ferrão, L.F.V.; de Hollander, M.; Garcia, A.A.F.; Ramírez, C.A.; Mendes, R.; Raaijmakers, J.M. Linking rhizosphere microbiome composition of wild and domesticated Phaseolus vulgaris to genotypic and root phenotypic traits. ISME J. 2017, 11, 2244–2257. [Google Scholar] [CrossRef] [PubMed][Green Version]
  138. Edwards, J.; Johnson, C.; Santos-Medellín, C.; Lurie, E.; Podishetty, N.K.; Bhatnagar, S.; Eisen, J.A.; Sundaresan, V. Structure, variation, and assembly of the root-associated microbiomes of rice. Proc. Natl. Acad. Sci. USA 2015, 112, E911–E920. [Google Scholar] [CrossRef] [PubMed][Green Version]
  139. Bullington, L.S.; Larkin, B.G. Using direct amplification and next-generation sequencing technology to explore foliar endophyte communities in experimentally inoculated western white pines. Fungal Ecol. 2015, 17, 170–178. [Google Scholar] [CrossRef]
  140. Yang, R.; Liu, P.; Ye, W. Illumina-based analysis of endophytic bacterial diversity of tree peony (Paeonia Sect. Moutan) roots and leaves. Braz. J. Microbiol. 2017, 48, 695–705. [Google Scholar] [CrossRef]
  141. Montes-Borrego, M.; Navas-Cortés, J.A.; Landa, B.B. Linking microbial functional diversity of olive rhizosphere soil to management systems in commercial orchards in southern Spain. Agric. Ecosyst. Environ. 2013, 181, 169–178. [Google Scholar] [CrossRef][Green Version]
  142. Montes-Borrego, M.; Metsis, M.; Landa, B.B. Arbuscular mycorhizal fungi associated with the olive crop across the Andalusian landscape: Factors driving community differentiation. PLoS ONE 2014, 9, e96397. [Google Scholar] [CrossRef][Green Version]
  143. Müller, H.; Berg, C.; Landa, B.B.; Auerbach, A.; Moissl-Eichinger, C.; Berg, G. Plant genotype-specific archaeal and bacterial endophytes but similar Bacillus antagonists colonize Mediterranean olive trees. Front. Microbiol. 2015, 6, 138. [Google Scholar] [CrossRef][Green Version]
  144. Morella, N.M.; Weng, F.C.-H.; Joubert, P.M.; Metcalf, C.J.E.; Lindow, S.; Koskella, B. Successive passaging of a plant-associated microbiome reveals robust habitat and host genotype-dependent selection. Proc. Natl. Acad. Sci. USA 2020, 117, 1148–1159. [Google Scholar] [CrossRef]
  145. Leopold, D.R.; Busby, P.E. Host Genotype and Colonist Arrival Order Jointly Govern Plant Microbiome Composition and Function. Curr. Biol. 2020, 30, 3260–3266. [Google Scholar] [CrossRef] [PubMed]
  146. Anguita-Maeso, M.; Rivas, J.C.; León, G.; Estudillo, C.; Navas-Cortés, J.A.; Landa, B.B. Soil physicochemical properties, seasonality, plant niche and plant genotype affect bacterial and fungal communities in olive orchard soils. In Proceedings of the Global Symposium on Soil Biodiversity, Virtual Conference, 19–22 April 2021; Available online: (accessed on 20 December 2022).
  147. Schlaeppi, K.; Dombrowski, N.; Oter, R.G.; Ver Loren van Themaat, E.; Schulze-Lefert, P. Quantitative divergence of the bacterial root microbiota in Arabidopsis thaliana relatives. Proc. Natl. Acad. Sci. USA 2014, 111, 585–592. [Google Scholar] [CrossRef] [PubMed][Green Version]
  148. Lauber, C.L.; Hamady, M.; Knight, R.; Fierer, N. Pyrosequencing-Based Assessment of Soil pH as a Predictor of Soil Bacterial Community Structure at the Continental Scale. Appl. Environ. Microbiol. 2009, 75, 5111–5120. [Google Scholar] [CrossRef] [PubMed][Green Version]
  149. Santos-Medellín, C.; Edwards, J.; Liechty, Z.; Nguyen, B.; Sundaresan, V.; Frederick, M.A. Drought Stress Results in a Compartment-Specific Restructuring of the Rice Root-Associated Microbiomes. mBio 2017, 8, e00764-17. [Google Scholar] [CrossRef] [PubMed][Green Version]
  150. Singh, B.K.; Millard, P.; Whiteley, A.S.; Murrell, J.C. Unravelling rhizosphere–microbial interactions: Opportunities and limitations. Trends Microbiol. 2004, 12, 386–393. [Google Scholar] [CrossRef]
  151. Hassani, M.A.; Durán, P.; Hacquard, S. Microbial interactions within the plant holobiont. Microbiome 2018, 6, 58. [Google Scholar] [CrossRef][Green Version]
  152. Rodriguez, P.A.; Rothballer, M.; Chowdhury, S.P.; Nussbaumer, T.; Gutjahr, C.; Falter-Braun, P. Systems Biology of Plant-Microbiome Interactions. Mol. Plant 2019, 12, 804–821. [Google Scholar] [CrossRef][Green Version]
  153. Markakis, E.A.; Tjamos, S.E.; Antoniou, P.P.; Roussos, P.A.; Paplomatas, E.J.; Tjamos, E.C. Phenolic responses of resistant and susceptible olive cultivars induced by defoliating and nondefoliating Verticillium dahliae pathotypes. Plant Dis. 2010, 94, 1156–1162. [Google Scholar] [CrossRef][Green Version]
  154. D’Attoma, G.; Morelli, M.; Saldarelli, P.; Saponari, M.; Giampetruzzi, A.; Boscia, D.; Savino, V.N.; De La Fuente, L.; Cobine, P.A. Ionomic differences between susceptible and resistant olive cultivars infected by Xylella fastidiosa in the outbreak area of Salento, Italy. Pathogens 2019, 8, 272. [Google Scholar] [CrossRef][Green Version]
  155. Luvisi, A.; Aprile, A.; Sabella, E.; Vergine, M.; Nicolì, F.; Nutricati, E.; Miceli, A.; Negro, C.; de Bellis, L. Xylella fastidiosa subsp. pauca (CoDiRO strain) infection in four olive (Olea europaea L.) cultivars: Profile of phenolic compounds in leaves and progression of leaf scorch symptoms. Phytopathol. Mediterr. 2017, 56, 259–273. [Google Scholar] [CrossRef]
  156. Girelli, C.R.; Del Coco, L.; Scortichini, M.; Petriccione, M.; Zampella, L.; Mastrobuoni, F.; Cesari, G.; Bertaccini, A.; D’Amico, G.; Contaldo, N.; et al. Xylella fastidiosa and olive quick decline syndrome (CoDiRO) in Salento (southern Italy): A chemometric 1H NMR-based preliminary study on Ogliarola salentina and Cellina di Nardò cultivars. Chem. Biol. Technol. Agric. 2017, 4, 25. [Google Scholar] [CrossRef][Green Version]
  157. Girelli, C.R.; Angilè, F.; Del Coco, L.; Migoni, D.; Zampella, L.; Marcelletti, S.; Cristella, N.; Marangi, P.; Scortichini, M.; Fanizzi, F.P. 1H-NMR Metabolite Fingerprinting Analysis Reveals a Disease Biomarker and a Field Treatment Response in Xylella fastidiosa subsp. pauca-Infected Olive Trees. Plants 2019, 8, 115. [Google Scholar] [CrossRef][Green Version]
  158. Gu, Y.; Wei, Z.; Wang, X.; Friman, V.-P.; Huang, J.; Wang, X.; Mei, X.; Xu, Y.; Shen, Q.; Jousset, A. Pathogen invasion indirectly changes the composition of soil microbiome via shifts in root exudation profile. Biol. Fertil. Soils 2016, 52, 997–1005. [Google Scholar] [CrossRef][Green Version]
  159. Hannula, S.E.; Ma, H.; Pérez-Jaramillo, J.E.; Pineda, A.; Bezemer, T.M. Structure and ecological function of the soil microbiome affecting plant–soil feedbacks in the presence of a soil-borne pathogen. Environ. Microbiol. 2020, 22, 660–676. [Google Scholar] [CrossRef] [PubMed][Green Version]
  160. Sabella, E.; Aprile, A.; Genga, A.; Siciliano, T.; Nutricati, E.; Nicolì, F.; Vergine, M.; Negro, C.; De Bellis, L.; Luvisi, A. Xylem cavitation susceptibility and refilling mechanisms in olive trees infected by Xylella fastidiosa. Sci. Rep. 2019, 9, 9602. [Google Scholar] [CrossRef] [PubMed][Green Version]
  161. Barberán, A.; Bates, S.T.; Casamayor, E.O.; Fierer, N. Using network analysis to explore co-occurrence patterns in soil microbial communities. ISME J. 2012, 6, 343–351. [Google Scholar] [CrossRef] [PubMed][Green Version]
  162. Van der Heijden, M.G.A.; Hartmann, M. Networking in the Plant Microbiome. PLoS Biol. 2016, 14, e1002378. [Google Scholar] [CrossRef][Green Version]
  163. Lee, K.K.; Kim, H.; Lee, Y.-H. Cross-kingdom co-occurrence networks in the plant microbiome: Importance and ecological interpretations. Front. Microbiol. 2022, 13, 953300. [Google Scholar] [CrossRef]
  164. Enespa; Chandra, P. Tool and techniques study to plant microbiome current understanding and future needs: An overview. Commun. Integr. Biol. 2022, 15, 209–225. [Google Scholar] [CrossRef]
  165. Agler, M.T.; Ruhe, J.; Kroll, S.; Morhenn, C.; Kim, S.-T.; Weigel, D.; Kemen, E.M. Microbial Hub Taxa Link Host and Abiotic Factors to Plant Microbiome Variation. PLoS Biol. 2016, 14, e1002352. [Google Scholar] [CrossRef] [PubMed][Green Version]
  166. Kim, H.; Lee, K.K.; Jeon, J.; Harris, W.A.; Lee, Y.-H. Domestication of Oryza species eco-evolutionarily shapes bacterial and fungal communities in rice seed. Microbiome 2020, 8, 20. [Google Scholar] [CrossRef][Green Version]
  167. Nowrotek, M.; Jałowiecki, Ł.; Harnisz, M.; Płaza, G.A. Culturomics and metagenomics: In understanding of environmental resistome. Front. Environ. Sci. Eng. 2019, 13, 40. [Google Scholar] [CrossRef][Green Version]
  168. Lagier, J.-C.; Dubourg, G.; Million, M.; Cadoret, F.; Bilen, M.; Fenollar, F.; Levasseur, A.; Rolain, J.-M.; Fournier, P.-E.; Raoult, D. Culturing the human microbiota and culturomics. Nat. Rev. Microbiol. 2018, 16, 540–550. [Google Scholar] [CrossRef][Green Version]
  169. Mapelli, F.; Mengoni, A.; Riva, V.; Borin, S. Bacterial culturing is crucial to boost sustainable agriculture. Trends Microbiol. 2022, 31, 1–4. [Google Scholar] [CrossRef]
  170. Stanley, C.E.; Grossmann, G.; i Solvas, X.C.; deMello, A.J. Soil-on-a-Chip: Microfluidic platforms for environmental organismal studies. Lab Chip 2016, 16, 228–241. [Google Scholar] [CrossRef] [PubMed]
  171. Overmann, J.; Abt, B.; Sikorski, J. Present and Future of Culturing Bacteria. Annu. Rev. Microbiol. 2017, 71, 711–730. [Google Scholar] [CrossRef] [PubMed]
  172. Sarhan, M.S.; Hamza, M.A.; Youssef, H.H.; Patz, S.; Becker, M.; ElSawey, H.; Nemr, R.; Daanaa, H.-S.A.; Mourad, E.F.; Morsi, A.T.; et al. Culturomics of the plant prokaryotic microbiome and the dawn of plant-based culture media—A review. J. Adv. Res. 2019, 19, 15–27. [Google Scholar] [CrossRef] [PubMed]
  173. Anguita-Maeso, M.; Olivares-García, C.; Rivas, J.C.; Navas-Cortés, J.A.; Landa, B.B. Broth media cultivation of xylem microbiome from cultivated olive trees. In Proceedings of the III European Conference on Xylella fastidiosa, Virtual Conference, 26–30 April 2021. [Google Scholar] [CrossRef]
  174. Anguita-Maeso, M.; León-Ropero, G.; Trapero-Casas, J.L.; Navas-Cortés, J.A.; Landa, B.B. Plant endotherapy treatments enable the modification of xylem microbiome composition in olive trees. In Proceedings of the 9th IOBC-WPRS Meeting on Integrated Protection of Olive Crops, 26–29 October 2021; p. 59. Available online: (accessed on 12 January 2023).
  175. Berger, G.; Czarnocka, K.; Cochard, B.; Oszako, T.; Lefort, F. Biocontrol endotherapy with Trichoderma spp. and Bacillus amyloliquefaciens against Phytophthora spp.: A comparative study with phosphite treatment on Quercus robur and Fagus sylvatica. J. Agric. Sci. Technol. 2015, 5, 428–439. [Google Scholar] [CrossRef][Green Version]
  176. Postma, J.; Goossen-van de Geijn, H. Twenty-four years of Dutch Trig® application to control Dutch elm disease. BioControl 2016, 61, 305–312. [Google Scholar] [CrossRef][Green Version]
  177. Zhang, J.; Cook, J.; Nearing, J.T.; Zhang, J.; Raudonis, R.; Glick, B.R.; Langille, M.G.I.; Cheng, Z. Harnessing the plant microbiome to promote the growth of agricultural crops. Microbiol. Res. 2021, 245, 126690. [Google Scholar] [CrossRef]
  178. Faino, L.; Scala, V.; Albanese, A.; Modesti, V.; Grottoli, A.; Pucci, N.; Doddi, A.; L’Aurora, A.; Tatulli, G.; Reverberi, M.; et al. Nanopore sequencing for the detection and identification of Xylella fastidiosa subspecies and sequence types from naturally infected plant material. Plant Pathol. 2021, 70, 1860–1870. [Google Scholar] [CrossRef]
Figure 1. Number of publications including “plant microbiome” in the title and/or as keywords in Web of Science (WoS) and Scopus databases. Review was performed in January 2023.
Figure 1. Number of publications including “plant microbiome” in the title and/or as keywords in Web of Science (WoS) and Scopus databases. Review was performed in January 2023.
Plants 12 00912 g001
Figure 2. Main methodological, abiotic and biotic factors that influence the characterization of the xylem-associated microbiome and its interactions in olive.
Figure 2. Main methodological, abiotic and biotic factors that influence the characterization of the xylem-associated microbiome and its interactions in olive.
Plants 12 00912 g002
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Anguita-Maeso, M.; Navas-Cortés, J.A.; Landa, B.B. Insights into the Methodological, Biotic and Abiotic Factors Influencing the Characterization of Xylem-Inhabiting Microbial Communities of Olive Trees. Plants 2023, 12, 912.

AMA Style

Anguita-Maeso M, Navas-Cortés JA, Landa BB. Insights into the Methodological, Biotic and Abiotic Factors Influencing the Characterization of Xylem-Inhabiting Microbial Communities of Olive Trees. Plants. 2023; 12(4):912.

Chicago/Turabian Style

Anguita-Maeso, Manuel, Juan A. Navas-Cortés, and Blanca B. Landa. 2023. "Insights into the Methodological, Biotic and Abiotic Factors Influencing the Characterization of Xylem-Inhabiting Microbial Communities of Olive Trees" Plants 12, no. 4: 912.

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop