The Rootstock-Scion Combination Drives Microorganisms' Selection

The Rootstock-Scion Combination Drives Microorganisms’ Selection

and Recruitment in Grapevine Rhizosphere

Thesis by Hend Alturkey

In Partial Fulfillment of the Requirements For the Degree of Master of Science

King Abdullah University of Science and Technology Thuwal, Kingdom of Saudi Arabia

July 2020

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EXAMINATION COMMITTEE PAGE

The thesis of Hend Alturkey is approved by the examination committee.

Committee Chairperson: Daniele Daffonchio Committee Members: Peiying Hong, Arnab Pain

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© July, 2020 Hend Alturkey All Rights Reserved

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ABSTRACT

The Rootstock-Scion Combination Drives Microorganisms’ Selection and Recruitment in Grapevine Rhizosphere

Hend Alturkey

In the last decade, several studies demonstrated that plants have developed a tight partnership with the edaphic microbial communities, mainly bacteria, fungi, and archaea. Such microbiome accomplishes essential functions and ecological services complementary to the functions encoded by the host plant, conferring adaptive advantages to the plant, particularly during stressful conditions. The interaction between microbial communities and their host plants in the natural ecosystem are complex and the mechanisms regulating these mutualistic associations are not fully elucidated. Several biotic and abiotic factors have been shown to be important during this process, including the plant properties (species, age, stage, etc.), the soil type and agronomic practices, the geo-climate conditions, and the biotic interaction. In this context, the vineyard ecosystems represent a unique biogeography model to study and disentangle microbial biodiversity patterns (compositional diversity and potential functionality) across plants cultivated in different geographical regions. Here, I used the rhizosphere and bulk soil of seven different rootstock-scion combinations (Vitis spp.) to dissect the main factors driving the microbial communities’ recruitment in ten different vineyards in Tuscany (Italy), distributed in the Pomino and Nipozzano estates of Frescobaldi company. Among the factors investigated, I focused my attention on the geographical area, soil type and rootstock-scion combination. By using high-throughput sequencing of bacterial 16S rRNA gene and fungal ITS region, I show how both bacterial and fungal communities associated with grapevine rhizosphere and bulk soils are mainly affected by the geographical area and the soil. Nonetheless, I also revealed that the rootstock-scion combination is an important driver in shaping the microbial community, explaining a higher percentage of variability in comparison with the factors rootstock and scion taken alone. Overall, the results obtained in my thesis offer a new perspective of 5 research that aim to develop a deep understanding about the contribution of scion- rootstock combinations in the microbial community ecology of the plant holobiont.

Keywords: Plant-microbe interactions, edaphic microorganisms, Microbial ecology, Plant Growth Promoting Bacteria, Rootstock-scion, Grapevine.

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ACKNOWLEDGEMENTS

I would like to express my sincere gratitude to my advisor professor Daniele Daffonchio for giving me the opportunity to work in his lab and for his guidance, immense knowledge, encouragement, and support throughout the course of this research. Besides my advisor, I would like to thank my thesis committee: prof. Peiying Hong and prof. Arnab Pain for their insightful comments, and support. Thanks to Michele Brandi, Andrea Bellucci and the Frescobaldi s.p.a. (Nipozzano and Pomino Frescobaldi estates) for their collaboration in this project and their assistance during sampling procedures. I would like to express my deepest thanks to my mentor Dr. Ramona Marasco who personally supervised, supported, and motivated me all through this project. She has trained me on how to be a scientist and showing me that it can be done and how to do it. I am truly thankful for her efforts, patience, and immense expertise that were a key motivations throughout my master research journey. Thank you for always keeping me on track, I honestly cannot think of a better mentor to have. Thanks to Kholoud Seferji for her support whenever I ran into a problem or had question about laboratory work and for being very friendly and always helpful. Thanks to my family and friends for supporting me in many ways along the way, I am forever grateful. This thesis stands as a testament to your unconditional love and encouragement. Special thanks to my mom for her kind words, encouragement, baked goods, and love, which without I would be lost. Finally, I must express my thanks to my fellow labmates for providing me with continuous support and encouragement throughout my research project. Thanks to all of you whom provided a great cheerful environment that makes it easy to work and share the laboratory with you. Thanks to the lab manager Taskeen Begum for everything she does in the lab. It has been an honor to be a member of Extreme Systems Microbiology Lab, a group whose passion for science is truly inspirational. 7

TABLE OF CONTENTS

EXAMINATION COMMITTEE PAGE 2 COPYRIGHT PAGE 3 ABSTRACT 4 ACKNOWLEDGEMENTS 6 TABLE OF CONTENTS 7 LIST OF ABBREVIATIONS 9 LIST OF ILLUSTRATIONS 10 LIST OF TABLES 12 AIM OF THE STUDY 13 Chapter 1. Understanding the plant holobiont: the interdependence of plants and 17 their microbiome 1.1 Introduction 17 1.2 Soil microbiome: ecological services and biodiversity reservoir 19 1.3 Microbial selection and recruitment by the plant host 21 1.3.1 Two-step selection model for root-system microbial community 21 differentiation 1.3.2 Compartmentalization of plant microbiome 24 1.4 Ecological factors driving the plant-microbiome assembly and interactions 27 1.5 Functional services of plant-associated microbiomes: biopromotion and 30 bioprotection mechanisms exerted by beneficial microorganisms 1.6 Conclusion 34 Bibliography 35 Chapter 2. Grapevine associated microbiome: understanding the factors affecting the rhizosphere microbial community structure and composition in rootstock-scion 44 combinations Abstract 44 2.1 Introduction 45 8

2.2 Methods and Materials 48 2.2.1 Sample collection 48 2.2.2 Physico-chemical analysis of vineyards’ soil 48 2.2.3 Total DNA extraction 49 2.2.4 Amplification, sequencing and meta-phylogenomic analysis 49 2.2.5 Bacterial and fungal diversity, taxonomy distribution and statistical analysis 50 2.3 Results and Discussion 51 2.3.1 Geoclimatic and physico-chemical characterization of Pomino and Nipozzano 51 areas 2.3.2 Distribution and use of grape rootstocks in Tuscan vineyards 55 2.3.3 Diversity estimation of microbial communities associated to the rhizosphere 56 of different grapevine rootstocks 2.3.4 Relative abundance of bacterial taxa associated to the grape rootstocks’ 63 rhizosphere and surrounding bulk soil 2.3.5 Taxonomy of the mycobiota associated with the rootstocks’ rhizosphere and 67 the surrounding bulk soil 2.3.6 Shared microbiome and rootstock-scion specific microbial assemblages 71 2.4 Conclusion 76 Bibliography 77 Supplementary Materials 86 THESIS CONCLUSION 91

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LIST OF ABBREVIATIONS

C Carbon Ca Calcium K Potassium N Nitrogen P Phosphorus Mg Magnesium Na Sodium CEC Cation Exchange Capacity PGP Plant Growth Promoting OTU Operational Taxonomic Unit PCoA Principal Coordinate Analysis PERMANOVA Permutational Multivariate Analysis of Variance

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LIST OF ILLUSTRATIONS

Figure 1.1. Description of plant microbiome 19 Figure 1.2. The recruitment and enrichment of microbes by the plant root system 23 Figure 1.3. The relative abundance of grapevine microbial community 26 Figure 1.4. Rhizosphere Microbiome Drivers in natural and agricultural ecosystems 28 Figure 1.5. Schematic representation of the microbial activities involved in the 32 alleviation of abiotic stress in plants Figure 2.1. Satellite images of the studied vineyards in Tuscany 52 Figure 2.2. Chemical-physical analysis of vineyards’ soil 53 Figure 2.3. Microbial recruitment process in grape rhizosphere 59 Figure 2.4. Beta-diversity of microbial communities associated with grapevine 61 rootstocks’ rhizosphere and bulk soils in Tuscan vineyards Figure 2.5. Taxonomic diversity of bacterial communities associated with 64 grapevine rhizosphere and vineyard bulk soils Figure 2.6. Distribution of the main bacterial taxa across the rhizosphere of the 66 grafted grapes Figure 2.7. Taxonomic diversity of fungal communities associated with grapevine 68 rhizosphere and vineyards bulk soils Figure 2.8. Distribution of the main fungal taxa across the rhizosphere of the 70 grafted grapes Figure 2.9. Distribution of the core microbial taxa across the rhizosphere of 72 grapevine plants with different graft combinations Figure 2.10. Relative abundance of the rootstock-scion specific microbial taxa 75 across grapevine rhizospheres

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LIST OF TABLES

Table 2.1. List of vineyards with location and of the sampled rootstock-scion 49 combinations Table 2.2. Physical-chemical parameters measured in the ten selected vineyards 54 Table 2.3. Results of distance-based linear model (DistLM) marginal and sequential 55 step-wise tests Table 2.4. Rootstock name, genetic origin and main adaptation to environment are 56 reported Table 2.5. Alpha diversity estimates of the microbial communities 57 Table 2.6. Multivariate analysis of variance for each factor tested 60 Table 2.7. Bacterial and fungal reads assigned to taxonomic ranks 63 Table 2.8. Shared and specific bacterial and fungal OTUs detected across rhizosphere microbial communities associated with the seven rootstock-scion 71 combinations

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AIM OF THE STUDY

Complex organisms like plants and animals have been recently re-defined as the association between the eukaryote host and the associated microorganisms (symbionts: bacteria, fungi, archaea and viruses), which interact throughout complex metabolic and physiological networks. As all the other complex eukaryotes, plants can be regarded as “metaorganisms/holobionts” which act as single entities and as units of selection in evolution (Sánchez-Cañizares et al., 2017; Hassani et al., 2018; Rosenberg and Zilber- Rosenberg., 2016; Zilber-Rosenberg and Rosenberg., 2008), hosting microbial communities in both the belowground and aboveground compartments (Bulgarelli et al., 2013). Despite several plant pathogenic microorganisms (‘the bad’) live in the soil, a much higher number of beneficial microorganisms (‘the good’) live in soil, which are successfully selected by the plant to establish positive interactions. Beneficial microorganisms provide ecological services to the entire plant metaorganism and favor both fitness, resilience and adaptability to a wide range of conditions including stressful conditions (growth promotion and protection; Mendes et al., 2013; Compant et al., 2019; Berlanas et al., 2019; Glick., 2012). Such microorganisms are actively attracted from the surrounding soil (microbial reservoir; Busby et al., 2017) to the plant root systems by the release of nutrients in the form of root exudates (e.g., organic acids, fatty acids, sugars, vitamins; Zhalnina et al., 2018; Doornbos et al., 2012). Such a soil-nutrient enrichment process creates the so called “rhizosphere” (Jones et al., 2009), a thin layer of soil surrounding the roots (few millimeters) rich in nutrients that represent a ‘hot spot’ for microbial diversity and activity (Berlanas et al., 2019). This portion of soil–significantly reconditioned by the plant (Gopal and Gupta., 2016)–represents the first step/barrier in the process of microbial selection and recruitment mediated by the plant (Van der Heijden and Schlaeppi., 2015). In fact, as revealed by several researches, only a portion of the soil microbial diversity is attracted and enriched in the rhizosphere and a further subset of this is able to enter and colonize the internal tissues of the plant roots (Van der Heijden and Schlaeppi., 2015), thus becoming plant endophytes (Gopal and Gupta., 2016). 13

The interaction between microbial communities and their host plants in the natural ecosystem are complex and the mechanisms regulating these mutualistic associations are not fully elucidated. Several factors have been shown to be important during this process, including biotic and abiotic factors such as the plant itself (species, age, stage, etc.), the soil type and the agronomic practices, the geo-climatic conditions, and the biotic interaction (Philippot et al., 2013). In order to elucidate the ecological patterns that the constituents of a microbial community follow in the plant root colonization, reductionist approaches have been extensively used. However, the cultivation of each individual endophyte is virtually impossible and next generation sequencing technologies with molecular microbial ecology approaches have allowed fingerprinting and quantify these microbes independently from cultivation. The identification and quantification of microorganisms associated with plants grown under distinct environmental conditions (i.e., different soils, geographical areas, etc.) may facilitate the understanding of the processes of selection and recruitment of the plant-associated microbiomes, and as well as their ecological role. In this context, vineyard ecosystems represent a unique biogeographic model to study and disentangle the compositional and functional patterns which establish in the root systems across different geographical regions, in order to answer questions regarding the selection, recruitment and community maintenance in plant root system. Recent studies conducted on the microbiome associated with grapevine showed the importance of macroecological factors such as soil type, rootstock type and geographical location in the plant microbiome assembly (Zarraonaindia et al., 2015; Nallanchakravarthula et al., 2014; Schreiter et al., 2014). Notably, such factors were investigated singularly (one by one). Thus, my thesis work aims at characterizing diversity of the belowground prokaryotic communities (bacteria and fungi) associated with grapevine cultivated in different environmental settings and soils in Tuscany (Italy), considering different combinations of plant rootstocks and scions, in order to estimate the importance of these factors in the microbial selection and recruitment. In particular, the specific objectives of this study are i) to assess the effect of soil types and geographical location on the recruitment and 14 selection processes driven by grapevine plants; ii) to evaluate the role of rootstock-scion combinations in the microbiome recruitment and selection in different soils; iii) to evaluate the influence of the scion type in the rootstocks’ recruitment of the rhizosphere microorganisms. To achieve these goals, a total of 66 plants and related bulk soil (not affected by grapevine roots) have been collected from 11 vineyards (with a biological replication of 6 plants per vineyard). I selected four different rootstock types and three scion types for a total of seven rootstock-scion combinations. I extracted DNA from the 132 samples (66 bulk and 66 rhizospheric soils) and performed high-throughput metaphylogenomic sequencing of both bacterial and fungal communities, respectively targeting the bacterial 16S rRNA gene and the fungal ITS as molecular markers. The use of culture-independent approach allowed me to obtain a large amount of sequences to assess the structure and the composition of the microbial communities associated with the root system of grapevine. Then, I correlate the microbial biodiversity data with the scion/rootstock combination of the plants and the soil type and geographical location of the vineyards, in order to define how these factors determine microbial community assembly in the vineyard agroecosystem.

BIBLIOGRAPHY

Berlanas C, Berbegal M, Elena G, et al. The fungal and bacterial rhizosphere microbiome associated with grapevine rootstock genotypes in mature and young vineyards. Front Microbiol. 2019, 10:1142. DOI:10.3389/fmicb.2019.01142 Bulgarelli D, Schlaeppi K, Spaepen S, Ver Loren van Themaat E, Schulze-Lefert P. Structure and functions of the bacterial microbiota of plants. Annu Rev Plant Biol. 2013, 64:807‐ 838. DOI:10.1146/annurev-arplant-050312-120106 Busby, P. E., Soman, C., Wagner, M. R., Friesen, M. L., Kremer, J., Bennett, A., Morsy, M., Eisen, J. A., Leach, J. E., & Dangl, J. L. Research priorities for harnessing plant microbiomes in sustainable agriculture. PLoS biology. 2017, 15(3). DOI:org/10.1371/journal.pbio.2001793 15

Compant, S., Samad, A., Faist, H., & Sessitsch, A. A review on the plant microbiome: Ecology, functions, and emerging trends in microbial application. Journal of Advanced Research. 2019, 19, 29-37. DOI: doi.org/10.1016/j.jare.2019.03.004 Doornbos, R.F., van Loon, L.C. & Bakker, P.A.H.M. Impact of root exudates and plant defense signaling on bacterial communities in the rhizosphere. A review. Agron. Sustain. Dev. 2012, 32, 227–243. DOI:org/10.1007/s13593-011-0028-y Glick BR. Plant growth-promoting bacteria: mechanisms and applications. Scientifica (Cairo). 2012, 2012:963401. DOI:10.6064/2012/963401 Gopal, M., & Gupta, A. Microbiome selection could spur next-generation plant breeding strategies. Frontiers in microbiology. 2016, 7, 1971. DOI:org/10.3389/fmicb.2016.01971 Hassani, M.A., Durán, P. & Hacquard, S. Microbial interactions within the plant holobiont. Microbiome. 2018, 6, 58. DOI:org/10.1186/s40168-018-0445-0 Jones, D. L., Nguyen, C., & Finlay, R. D. Carbon flow in the rhizosphere: carbon trading at the soil-root interface. Plant and Soil. 2009, 321(1-2), 5-33. DOI:org/10.1007/s11104- 009-9925-0 Mendes R, Garbeva P, Raaijmakers JM. The rhizosphere microbiome: significance of plant beneficial, plant pathogenic, and human pathogenic microorganisms. FEMS Microbiol Rev. 2013, 37(5):634‐663. DOI:10.1111/1574-6976.12028 Nallanchakravarthula S, Mahmood S, Alström S, Finlay RD. Influence of soil type, cultivar and Verticillium dahliae on the structure of the root and rhizosphere soil fungal microbiome of strawberry. Plos One. 2014, 9(10). DOI:10.1371/journal.pone.0111455 Philippot, L., Raaijmakers, J. M., Lemanceau, P., & Van Der Putten, W. H. Going back to the roots: the microbial ecology of the rhizosphere. Nature Reviews Microbiology. 2013, 11(11), 789-799. DOI:org/10.1038/nrmicro3109 Rosenberg E, Zilber-Rosenberg I. Microbes drive evolution of animals and plants: the hologenome concept. mBio. 2016, 7(2). DOI:10.1128/mBio.01395-15 16

Sánchez-Cañizares C, Jorrín B, Poole PS, Tkacz A. Understanding the holobiont: the interdependence of plants and their microbiome. Curr Opin Microbiol. 2017, 38:188‐ 196. DOI:10.1016/j.mib.2017.07.001 Schreiter S, Ding GC, Heuer H, et al. Effect of the soil type on the microbiome in the rhizosphere of field-grown lettuce. Front Microbiol. 2014, 5:144. DOI:10.3389/fmicb.2014.00144 Van der Heijden MG, Schlaeppi K. Root surface as a frontier for plant microbiome research. Proc Natl Acad Sci U S A. 2015;112(8):2299-2300. DOI:10.1073/pnas.1500709112 Zarraonaindia I, Owens SM, Weisenhorn P, et al. The soil microbiome influences grapevine-associated microbiota. mBio. 2015, 6(2). DOI:10.1128/mBio.02527-14 Zhalnina, K., Louie, K.B., Hao, Z. et al. Dynamic root exudate chemistry and microbial substrate preferences drive patterns in rhizosphere microbial community assembly. Nat Microbiol 3. 2018, 470–480. DOI:org/10.1038/s41564-018-0129-3 Zilber-Rosenberg I, Rosenberg E. Role of microorganisms in the evolution of animals and plants: the hologenome theory of evolution. FEMS Microbiol Rev. 2008, 32(5):723‐ 735. DOI:10.1111/j.1574-6976.2008.00123.x

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Chapter 1. Understanding the plant holobiont: the interdependence of plants and their microbiome.

Abstract. Plants and their associated microorganisms are not standalone entities, but a collective and unique ecological unit known as a holobiont that act synergistically to favor the fitness and phenotypic plasticity of the holobiont. Plants attract and sustain microbes mainly from the surrounding soil by depositing carbon into the rhizosphere via root exudation and rhizodeposition. In a stepwise process, the root system recruits and enriches microorganisms within the rhizosphere, while the root surface further selects those that can enter the root tissues as endophytes. These associated microorganisms can influence in several ways the fitness of the host, favoring nutrients availability and uptake, controlling pathogens, stimulating plant growth, and improving resistance to abiotic stresses (e.g., drought and high salinity). A variety of biotic and abiotic factors shape these microbial communities associated with root systems, including plant species, soil type, biogeographical location, plant community diversity and agricultural practices. In this chapter, I provide an overview of the microbial (i.e., bacteria and fungi) communities associated with plants, discussing the recruiting process, composition and structure, and functionality of such plant-associated microorganisms.

Keywords. Plant metaorganisms, Holobiont, Microbiome, Rhizosphere, Plant-microbe interactions

1.1 Introduction

Plants do not live alone. Indeed, a vast diversity of microorganisms colonize all their organs (i.e., root, shoot, leaf and fruit), making up their microbiome (Sánchez-Cañizares et al., 2017). In nature, plants cohabit and interact with a complex microbial community composed by bacteria, fungi, and archaea (i.e., plant microbiota, Figure 1.1a). Although plants have evolved their own adaptations to alleviate most biotic and abiotic stresses, 18 they also rely on microbial partners to survive and defend themselves against microbial invaders, nutrient limitation and other abiotic stresses (“the good” in Figure 1.1b; see details in paragraph “Functional services of plant-associated microbiomes”). Interactions between plants and their associated microbiome are not unidirectional: while microorganisms often protect and promote plant growth (PGP, plant growth promoting bacteria), the host plant also provides novel metabolites to the microorganisms associated, leading to the adaptation of niche-specialized inhabitants that can either have positive (mutualism), neutral (commensalism), or deleterious (pathogenic) impact on plant fitness (Mendes et al., 2013). Such relationship usually starts in the rhizosphere as, in most cases, the initial reservoir of microbial diversity is the soil (Figure 1.1a; Gopal and Gupta., 2016). A mix of compounds rich in carbon and nutrients is released by the root (i.e., root exudates and mucilage) in the surrounding soil, creating the so-called rhizosphere (Hartmann et al., 2008). In this narrow portion of soil (i.e., few millimeters) starts and occurs all the processes aimed at the selection, enrichment and recruitment of edaphic microorganisms that will constitute the plant microbiome (see paragraph “Microbial selection and recruitment by plant root system”).

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Figure 1.1. (a) The plant microbiome includes the whole microbial communities that are associated with all plant organs. The majority of microbial communities inhabit the rhizosphere, endosphere, and phyllosphere. The soil represents a microorganisms’ reservoir from which plant selects and recruits the associated microorganisms. The plant genotype, root exudation, and soil type are main factors affecting the 19

recruitment and composition of plant-associated microbiomes (reproduced from Gopal and Gupta., 2016). (b) Schematic overview of the functions and impact of plant beneficial (‘the good’), plant pathogenic (‘the bad’), and human pathogenic microorganisms (‘the ugly’) on the host plant (reproduced from Mendes et al., 2013).

Microorganisms colonizing the plant tissues can be as well vertically inherited by seeds and further transmitted from one plant generation to the next, as the culmination of a complex process of microbial interactions mediated by plant throughout its life cycle that start in the belowground root-system (Berg and Raaijmakers., 2018). This partnership between the host and its associated community is also driven and affected by many factors (see paragraph "Ecological factors driving the plant-microbiome assembly and interactions”). In this context, understanding the association of plants and microorganisms may improve efforts to comprehend the overall ecological processes taking place at the interface between soil and the plant root system (i.e., the rhizosphere and root tissue). Thus, here I assess the available knowledge on the composition, structure, functionality, and biotechnological potential of the microbial communities associated with plants (natural and cultivated).

1.2 Soil microbiome: ecological services and biodiversity reservoir

Microbial communities associated with plant are generally a subset of the microbial pool available in the surrounding soil (Van der Heijden and Schlaeppi, 2015). Thus, such soil is an important factor originating and strongly influencing the diversity of the plant microbiome (Lundberg et al., 2012). It consists of a great biodiversity; for instance, it has been reported that one gram of soil harbor approximately 10 billion of cells and several thousands of different microorganisms (Torsvik and Øvreås., 2002). Among these, bacteria represent the most abundant, reaching up to 2.2x1010 cells per gram of soil (dry weight of heathland and forest soil samples; Torsvik et al., 1980), followed by fungi that in fertile soil may get to 106 fungal “propagules” (e.g. spores) per gram of dry soil with their hyphae which may arrive as high as 66,900 meter in length (Bridge and Spooner., 20

2001). Soil bacterial communities are mainly composed by Proteobacteria, Actinobacteria, Acidobacteria, while the fungal ones by Ascomycota, Basidiomycota and Mucoromycota are abundant in soil (Delgado-Baquerizo et al., 2020). These microorganisms form complex and diverse microbial communities involved in essential ecosystem functions (Carbonetto et al., 2014; Delgado-Baquerizo, et al., 2020). In fact, edaphic microorganisms play a wide range of functions leading to soil fertility and nutrients cycles, such as nitrogen fixation, denitrification, nitrification, and organic carbon degradation (Aislabie et al., 2013; Delgado-Baquerizo et al. 2020; Carbonetto et al., 2014; Toju et al., 2018). The composition of microorganisms in soil is mainly influenced by agricultural practices and by the soil physico-chemical properties. For instance, taxonomic analyses of microbial communities associated with cultivated and non-cultivated soils revealed a different composition of the bacterial communities: the non-cultivated soils were more heterogeneous and mainly composed by Verrucomicrobia, Planctomycetes, Actinobacteria and Chloroflexi, while the cultivated soils were dominated by members of Gemmatimonadetes and Nitrospirae, showing an overall reduced biodiversity (Delgado- Baquerizo, et al., 2020). As expected, crop rotation, frequent use of fertilizers and pesticides significantly change nutrients available and the soil properties of cultivated soil and consequently the soil microbiome composition (Carbonetto et al., 2014; Campisano et al., 2014). Such changes affect the soil-biome functionality and soil fertility which is sustained by the diversity of the community itself (for instance exploiting the functional redundancy principle; Delgado-Baquerizo, et al., 2020). As demonstrated by Hartmann et al., (2015), long-term conventional farming can have serious impact on soil microbial diversity, affecting the quality and fertility of the soil, while the use of organic farming favors the enhancement of microbial biodiversity in the soil. Such effect is more evident, especially when the practices applied in the field modify the organic matter content of the soil; its increment results in the enhancement of fungal abundance, microbial biomass and activity (García-Orenes et al., 2013). From the literature, it is clear that the interactions between soil microorganisms and biotic and abiotic factors is complex. Understanding such interaction-complexity could 21 certainly contribute to develop sustainable soil management and improve ecosystem functionality.

1.3 Microbial selection and recruitment by the plant host

1.3.1 Two-step selection model for root-system microbial community differentiation. The interaction between microorganisms and plants first takes place in the belowground soil. While both plants and microorganisms obtain their nutrients from soil, plants are also able to actively attract and sustain the surrounding edaphic microorganisms through a process known as rhizodeposition, in which carbon sources (sugars, amino acids, organic acids, plant growth regulators, vitamins, and sterols) are exudated and released by the roots into the rhizospheric-soil layer (Jones et al., 2009; Hirsch & Mauchline, 2012; Jacoby et al., 2017). Such layer of soil, consistently enriched in nutrients by such continuous release of root exudates, is a ‘hot spot’ of microbial diversity and activity (Figure 1.2a; Hartmann et al., 2008). According to Santoyo et al. (2016) the rhizosphere is a highly competitive zone for microorganisms to obtain nutrients. Thus, plant associated microorganisms, regardless of their potential beneficial nature or pathogenicity are highly prone to colonize such rich-nutrient region compared to bulk soil (Figure 1.2b; Bulgarelli et al., 2013). Such process determines a dramatic enrichment of microbial cells. For instance, a gram of rhizosphere soil might contain up to 109 microbial cells (range, 106 to 109) and 106 distinct taxa (Torsvik and Øvreås., 2002; Curtis and Sloan., 2005), compared with the lower microbial cell abundance (105-107) in the bulk soil (Beneduzi et al., 2012; Bulgarelli et al., 2013). In addition to the ‘hot spot’ role, the rhizosphere and the molecular components of the released root exudates act as selectors of the surrounding microorganisms (Van der Heijden and Schlaeppi., 2015). Analysis of the bacterial composition based on sequencing of the bacterial 16S rRNA gene revealed a reduction of richness (i.e., numbers of different species) in the rhizosphere (Bulgarelli et al., 2013), indicating that only a pool of the edaphic microorganisms is able to became rhizospheric. Studies of the microbiome 22 associated with different plants species, from herbaceous to arboreal (e.g., Arabidopsis, soybean, grapevine, apple), confirm that the recruitment process mediated by the plant root is a conserved mechanism aimed to select and enrich (in term of number) only a subset of the soil microbes (Figure 1.2b), possible involved in favoring the overall holobiont fitness (i.e., “the good” microbes in Figure 1.1b; see details in paragraph “Functional services of plant-associated microbiomes”). For example, benzoxazinoids (BXs), a class of secondary metabolites released by maize roots, significantly affect the assembly and composition of the rhizospheric microbial community. BXs are known to mediate the colonization of plant growth promoting bacteria such as Pseudomonas putida, while inhibit the activation of virulence gene transfer T-DNA mediated by the pathogenic bacterium Agrobacterium tumefaciens (Hu et al., 2018). On the contrary, other compounds, such as malic acid (a tricarboxylic acid cycle intermediate) favors the recruitment by Arabidopsis thaliana of beneficial rhizobacteria of the Bacillus genus (B. subtilis FB17; Rudrappa et al., 2008).

a b

Figure 1.2. The recruitment and enrichment of microbes by the plant root system. (a) Microbial differentiation in soil at the levels of rhizosphere, rhizoplane, and endosphere. The rhizodeposits by the root system influence soil microbial community biodiversity and activity. Root wounds and lateral root emergence provide a passage for microbes to enter the root interior and colonize the plant tissues. Reproduced from Toju et al., 2018. (b) Plant-recruitment process starts from the selection and acquisition of microorganisms from the surrounding bulk soil with further selection taking place in rhizosphere layer via root exudate release by the plant. Once microbes reach root surface (rhizoplane), they can firmly attach 23

to occupy the high-nutrients root sites such as root hair zone and become endophytes; reproduced from Van der Heijden and Schlaeppi, 2015.

Despite plant evolution evolved mechanisms aimed to recognize beneficial (or neutral to the host fitness) microorganisms (Faure et al., 2009; Finkel et al., 2017), the rhizospheric nutrient-rich environment can also attract pathogenic microorganisms (Mendes et al., 2013; Berendsen et al., 2012). In this case, plants may be able to recognize the pathogen associated molecular patterns (PAMPs), such as peptidoglycan and lipopolysaccharides (LPS) through special receptors known as the pattern recognition receptors (PRRs), resulting in an efficient “exclusion” mechanism in the majority of the cases (Faure et al., 2009; Kogel et al., 2006). However, some microorganisms developed effector proteins able to hijack the plant immune response PAMP-triggered immunity (PTI) and allow the invasion of plant tissues (Turner et al., 2013; Faure et al., 2009). On the other hand, also the microbe-microbe interactions have an important role in the plant microbiome assembly (Müller et al., 2016). Notably, antimicrobial compounds and secondary metabolites (i.e., toxins, antibiotics, siderophores, and lytic enzymes) released by edaphic microorganisms have a wide range of functions in the soil (e.g., signaling; Doornbos et al., 2012; Philippot et al., 2013; Bulgarelli et al., 2013), driving competitive niche exclusion. Production and release of antibiotics and siderophores are facilitated by the presence of large gene clusters described in several rhizospheric bacteria, such as Pseudomonas and Bacillus spp. (Selosse et al., 2004). For example, P. chlororaphis produce phenazine, an antibiotic used against the fungal phytopathogen Fusarium oxysporum (Lareen et al., 2016). In addition, microorganisms can cooperate to meliorate the soil physical and nutritional conditions, by cycling important elements (C, N, and P), decomposing organic matter, and releasing compounds that favor soil particles aggregation and water retention (e.g., fungal hypha; Frąc et al., 2018). All these activities significantly contribute to meliorate the substrate where plant lives, as well as favoring plant growth and development (Toju et al., 2018; Singh et al., 2020). All these findings indicate that plants largely rely on their associated microbiomes for growth, development, fitness maintenance and resilience from stresses. 24

These multitrophic interactions between plant and edaphic microbial community starting in the rhizosphere are shaped by multiple factors (see paragraph "Ecological factors driving the plant-microbiome assembly and interactions”). A better understanding of these factors and their effect on plant microbiome assembly will help to develop useful methods to utilize specific microbes for crop production and pest management.

1.3.2 Compartmentalization of plant microbiome. The root system not only plays an important role in the recruitment and selection of the rhizospheric microbial community, but it defines the overall microbial recruitment process: a subset of the microbial communities of the soil microbial pool are enriched in the rhizosphere and further selected by interaction with the rhizoplane, which acts as a physical barrier allowing only certain types of microorganisms to colonize the internal tissues of the plant (Van der Heijden and Schlaeppi, 2015; Barea et al., 2005). Each plant compartment acts as an “ecological niche” in which specific microbial communities are hosted (Coleman-Derr et al., 2016; Beckers et al., 2017). To start an endophytic life, the edaphic microorganisms colonizing the rhizosphere, have to over the barrier constituted by the root rhizoplane (Figure 1.2b). This can happen in different ways: they can invade plant tissues in ‘passive way’, through root cracks, emergence points of lateral roots and wounds that provide an easy entrance and at the same time an attractive nutritious-spot (i.e., leakage of plant metabolites; Santoyo et al., 2016). The plant root system provides distinctive ecological niche(s) to the rhizospheric microorganisms, including external rhizoplane and the different root tissues (Van der Heijden and Schlaeppi., 2015). Root endophytic microbial community is generally horizontally transferred from the rhizosphere, passing form the rhizoplane surface (Friesen et al., 2011). Various microbes have gained access to root tissues; they belong to different phyla, including Acidobacteria, Actinobacteria, Bacteroidetes, Planctomycetes, Proteobacteria, Firmicutes, Proteobacteria and Verrucomicrobia. For example, while in the endosphere of cultivated rice (Oryza sativa) a high abundance of Firmicutes and Proteobacteria members has been observed, the rhizosphere was dominated by 25

Actinobacteria (Bulgarelli et al., 2013). Once colonized the root tissues, the endophytes can translocate through xylem to the aboveground portion of the plant, which can either be flowers, fruits, leaves, or stem vegetative compartments (Nair and Padmavathy., 2014; Frank et al., 2017; Hardoim et al., 2015). Notably, the endophytic communities analyzed from different plants and portion of plants revealed unique composition and structure. Among the taxa found, Pseudomonas and Bacillus species were consistently found in almond, apple, grapefruit, pumpkin (Aleklett et al., 2014), as well as in seeds (Lareen et al., 2016). A recent study examined the bacterial and archaeal communities in the rhizosphere, phyllosphere, leaf and root endosphere of agaves plants (i.e., wild and cultivated) through Illumina amplicon sequencing of 16S rRNA marker gene (Coleman- Derr et al., 2016). The results clearly showed that the composition of prokaryotic communities was primarily determined by the plant compartments: plant-associated samples (episphere and endosphere) were enriched in Proteobacteria and Actinobacteria and depleted for Acidobacteria compared to the surrounding soils, as previously observed in other plants (Bulgarelli et al., 2013; Lundberg et al., 2012; Shakya et al., 2013; Desgarennes et al., 2014), determining a substantial difference between the prokaryotic composition of the rhizosphere, the root endosphere, and the phyllosphere such as in the leaf endosphere (Coleman-Derr et al., 2016). Similar results were obtained by Deyett and Rolshausen (2020) after analyzing grapevine microbiome compartmentalization (i.e., bacterial and fungal communities). Distinct clustering between above and belowground microbiomes with a significant segregation of the two habitats were detected, and the plant sap (i.e., the fluid transported in xylem tubes or phloem cells of plant) microbiome clustered in between the two habitats. Notably, Proteobacteria ranged from 80% of the relative abundance in the above compartments of the plant to less than 40% in the sap and soil that were enriched in Firmicutes and Actinobacteria, respectively (Figure 1.3), confirming the previous observation of Zarraonaindia et al., (2015), Marasco et al., (2018), and Martinez-Diz et al., (2019). In the case of fungi, Ascomycota dominated the endophytic community (above 26 and below ground), followed by Basidiomycota mainly enriched in the rhizosphere and bulk soil.

Figure 1.3. Resume of met phylogenomic analysis of microbiome (bacteria and fungi) associated with grapevine across a continuum of six grapevine compartments. Grapevine plants were collected from California vineyards. Relative abundance of bacterial and fungal taxa at phylum level within the grapevine compartments (i.e., bulk soil, rhizosphere, root, cordon, cane and sap; reproduced from Deyett and Rolshausen (2020).

1.4 Ecological factors driving the plant-microbiome assembly and interactions

Over the past decade, many studies have been focused on the plant associated microorganisms. Progresses in molecular methods have enhanced our understanding of the microbial function, composition, and the ecological factors of plant associated microbial assemblages in particular for the rhizosphere. As previously discussed, the rhizosphere is soil fraction strongly adhering to the plant root which influenced by root exudates and, consequently, its chemical-metabolic composition significantly depends on plant genotype, developmental stage and environmental conditions (Philippot et al., 27

2013). It has been shown that root exudation, along with root morphology, is a main factor driving the microbial assembly in plants (Figure 1.4), significantly influencing and affecting the structure, composition and abundance of rhizosphere bacterial communities (Zhang et al., 2014). Recently, it has been demonstrated that plant genotypes can also influence the rhizosphere associated microorganisms (Haney et al., 2015; Marasco et al., 2018) mainly due to the fact that different plant species (and cultivars) release different pools of molecules during their root exudations (Zhalnina et al., 2018; Hu et al., 2018). As well, roots architecture and functionalities vary among species and cultivar (e.g., water and nutrient uptakes; Saleem et al., 2018; Mercado-Blanco and Prieto., 2012). For instance, different genotypes of Arabidopsis thaliana inhibited colonization of certain Pseudomonadaceae species (P. brassicacearum, P. fluorescens and P. syringae) without disturbing most of the remaining taxa in the microbiome. Notably, also the different rootstocks used to nest the same scion species can significantly affect the microbial composition, as it was recently demonstrated by Marasco and colleagues (2018) in grapevine growing in the same vineyard and soil. Grapevine rootstocks–resulting from the combination of different species in the plant genus Vitis–recruited different bacterial communities that carried similar ecological services to the plants (Marasco et al., 2018). This result revealed for the first time that the selection of rootstock not only affect the plant performance (i.e., growth, productivity, resilience, and adaptability; Wallis et al., 2013; Warschefsky et al., 2016; Gonçalves et al., 2006), but also influence the selection and recruitment of plant microbiota and consequently the holobiont fitness properties and potential. After this study several others confirmed the effects of rootstock on the selection of the plant-associated microbes, both in case of arboreal and horticultural plant species used for agriculture (D’Amico et al., 2018; Sivritepe et al., 2010; Corso and Bonghi., 2014), thus contributing to elucidate a novel manipulable factor (the rootstock type) to determine and steer microbiome selection and microbial dynamics. However, the role of the above portion of grafted plants (i.e., the scion) and its combination with the rootstock type on the selection and recruitment of the plant associated microbiome is still unexplored both under experimental settings and in real field conditions. 28

Figure 1.4. Rhizosphere Microbiome Drivers in natural and agricultural ecosystems. Factors driving the recruitment and composition of plant microbes are different in natural and agricultural soils. In natural system, the plant type and the biotic interactions are the main factors determining the microbial community composition, while in managed agricultural soils the soil type and crop management are the most important determinants of microbial community assemblage (reproduced from Philippot et al., 2013).

Despite plant genotype is crucial in selecting the plant associated microorganisms, it is important to underline that plants recruit their microbiomes from the surrounding soil, which remains a very important factor for the assembly of the plant microbial community (Berg and Smalla., 2009; Philippote et al., 2013). Many studies report that plant species and soil type go hand in hand in shaping the plant-associated microbiome, in which the bacterial community in the rhizosphere is assembled as the result of complex interaction between plant species and soil type. As previously discussed, different soil types have distinct microbial communities and each plant species selects and harbors unique microbial communities by mean of specific enrichment mediated by specific root exudates. For instance, Kuramae et al. (2012) showed that the composition of bacterial communities harbored by different soils were affected by the physical-chemical condition of the soil, such as pH, C, P and N content, water availability (Chiarini et al., 1998; Steenwerth et al., 2008). Indeed, soil condition can directly affect the presence of specific 29 bacterial groups and consequently the pool of microbial diversity available for plant (Winston et al., 2014; Nallanchakravarthula et al., 2014; Schreiter et al., 2014; Yeoh et al., 2017); for example, while Gammaproteobacteria and Actinobacteria are more abundant is low-pH soils, similar trend also observed in fungi, for example, the fungal member Fusarium moniliforme was detected in low-pH soils (Jain and Sharma, 2009). Notably, investigations of the evolutionary conservation of root microbiomes associated with the same plant species in different soils, revealed that the type of soil is a stronger factor in shaping plant-associated microbiome than the plant species (Nallanchakravarthula et al., 2014; Kuramae et al., 2012) as it was confirmed by several studies (Winston et al., 2014; Schreiter et al., 2014). The physico-chemical conditions of a soils–especially in the case of agricultural soils–are strongly influenced by soil management and agricultural practices (e.g., chemical fertilization, use of oat straw and herbicides; soil tillage, etc.; García-Orenes et al., 2013; Manici et al., 2017; Zhang et al., 2013; Vimal et al., 2017). In agricultural system, the conventional soil management and the use of fertilizers and pesticides can have a severe impact on the edaphic microbial community, interfering with both plant-microbe and microbe-microbe interactions that occur in soil. For example, the application of organic farming methods that limit the use of chemical fertilizers, pesticides, and herbicides promoted higher biodiversity and improve soil properties, favoring as well a more biodiverse and functional microbial community (Hartmann et al., 2015). On the contrary, in natural ecosystem–where plants are growing in their natural habitats without human interferences–the assembly of microbial communities is not governed by soil conditions, but by plant species, biodiversity and biotic interactions (Figure 1.4). One example of the difference between microbiome associated with cultivated and natural plants was showed by Coleman-Derr et al. (2016) using three Agave species as model (Agave tequilana, A. salmiana, and A. deserti). As expected, the microbial diversity of cultivated agave was lower compared to native ones, indicating that agriculture practices determined a significantly reduction of microbial diversity possibly affecting specific microorganisms. 30

Along with the factors already analyzed, also geographical location (Delgado-Baquerizo et al., 2018; Corneo et al., 2013), abiotic (Simmons et al., 2020) and biotic (Compant et al., 2019) stresses can strongly influence the plant associated microbiome. Root system- associated microbial communities can locally change in response to drought (Simmons et al., 2020). In millet species (n=4) the degree of drought has been correlated with levels of Actinobacteria enrichment, resulting in an overall shift in drought-treated root microbiome structure; notably, such response was localized to portions of the root experiencing drought. There are many factors that influence plant-associated microbiome structure and composition, as well as microbial interactions; thus, understanding the aspects regulating the ecological process driving plant-microbes recruitment and interaction will allow us to possibly re-direct the plant microbiome to our advantage promoting plant health and productivity (Sheth et al., 2016).

1.5 Functional services of plant-associated microbiomes: biopromotion and bioprotection mechanisms exerted by beneficial microorganisms

Biological, environmental, and geo-climatic factors are crucial in shaping the diversity and functionality of plant-associated microbial communities, ultimately determining the stability and functioning of the ecosystem (Toju et al., 2018). The interactions between the host and associated microorganisms include several types, mutualism, commensalism, and parasitism (Newton et al., 2010). As demonstrated in the last decades, despite the presence of phytopathogens (‘the bads’; Figure 1.1b) plants, and in particular their root systems, act as a reservoir of microorganisms potentially able to confer to the host plant beneficial services, contributing to its fitness and resilience (Barea et al., 2005; Compant et al., 2019). Under stressful conditions (e.g., pathogens attack, high salt, and drought), plants rely on their ability to adjust their physiology to secure survival and mitigate the effects of environmental changes. At the same time, the beneficial microbial community (Plant Growth Promoting, PGP microorganisms) naturally 31 associated to plants extend host’s metabolic repertoire, improving plant’s fitness in terms of environmental adaptation (Figure 1.5a). PGP microorganisms can influence several plant responses, especially during abiotic stresses such as salt and drought, inducing morphological, physiological and biochemical changes (Lugtenberg and Kamilova., 2009; Compant et al., 2010). They can serve as biofertilizers, biostimulators and bioprotectors through several direct and indirect mechanisms that can act synergically to mediate plant tolerance to stress, including among others (i) production of exopolysaccharides to increase water uptake; (ii) accumulation of osmolytes to reduce cell dehydration; (iii) enzymatic and non-enzymatic mechanisms to alleviate oxidative stress; and (iv) synthesis of hormone-like substances to modify the root system traits (Figure 1.5b; Jacoby et al., 2017; Barea et al., 2005; Newsham et al., 1995). As a result of their activity, PGP microbes influence several physiological responses in plant, inducing morphological, physiological and biochemical changes that can confer adaptive advantages to the entire meta- organism under both normal and stressful conditions (Daffonchio et al., 2015). As several studies suggested, adaptive plant response to abiotic stress is strongly linked to the rapid response of belowground microbial communities interacting with the plant that can change to communities metabolically and physiologically more adapted to abiotic stresses (Martin Heil., 2011). Such changes in the microbiome components of the holobiont can be relatively rapid thus providing a significant role in the host adaptation to sudden abiotic stresses (Rolli et al., 2015; Ullah et al., 2019). In comparison to the plant, microbes possess a larger set of diverse metabolic pathways, which can synthesize biologically-active metabolites that can contribute to modulate the physiology of plant host (Aislabie et al., 2013; Lakshmanan et al., 2012). Friesen et al. (2011) showed that all plants hormones currently known can be produced by microbes. Such ability makes it possible for microorganisms to alter–either positively (Figure 1.5b) or negatively–plant physiological pathways by producing or manipulating phytohormones (Faure et al., 2009). One of the most studied aspects of PGP microorganisms is their ability to produce phytohormone-like molecules. Patten and Glick, (1996) estimated that 80% of bacteria 32 isolated from the rhizosphere display such activities. Analysis of root architecture demonstrated that plants inoculated with Azospirillum present a potentiated root apparatus able to improve water, minerals and microelements uptake (Sánchez-Cañizares et al., 2017). These changes were related to the bacterial production of hormone-like substances, such as auxins (indoleacetic acid, IAA), giberellines (GAs) and cytokinins (CK) (Finkel et al., 2017). A. brasilense was demonstrated to be able to modify the morphology of bean root system in water-stressed potted plants, increasing the root length involved in water uptake respect to non-inoculated controls (German et al., 2000). Similarly, studies performed with an auxin-producing Pseudomonas and Bacillus PGP strains exhibited a significant improvement of plant biomass, along with changes in the root architecture of several model plants during normal and stressful condition (i.e., drought; Cherif et al., 2015; Vigani et al., 2018).

a b

Figure 1.5. Schematic representation of the microbial activities involved in the alleviation of abiotic stress in plants. (a) In agricultural and natural ecosystems, plant-associated microorganisms (e.g., nitrogen-fixing bacteria and mycorrhizal fungi) supply nutrients, such as nitrogen (N) and phosphorus (P) to host plants, thereby allowing us to reduce chemical fertilizer input into agroecosystems. Others PGP symbionts are also known to enhance host plants’ resistance to drought and salinity stresses, and suppress populations of air- borne or soil-borne pathogens and pests. Reproduced from Toju et al., 2018. (b) PGP microbes mediate plant drought alleviation through (i) the synthesis of hormone-like substances, volatile compounds, and enzymes influencing plant hormone homeostasis, (ii) enzymatic and non-enzymatic mechanisms to alleviate oxidative stress, (iii) the production of osmolytes to reduce cell dehydration; and (iv) the production of exopolysaccharides that protect roots from the mechanical stress exerted by dry soils. The same or similar mechanisms work for salt stress (panel b credit, Ramona Marasco). 33

PGP microorganisms can also affect the plant through regulation of its phytohormones levels. Glick et al., (1998) firstly proposed that many PGP bacteria could promote plant growth by lowering the levels of ethylene in plants under abiotic stress. This ability was attributed to the activity of the enzyme 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase (ACCd), which hydrolyzes ACC, the biosynthetic precursor of ethylene in plants (Santoyo et al., 2016). The resulting decrease in ACC concentration induces the proliferation of secondary roots and root hairs: the larger root apparatus increases water uptake in the deep layers of dry soils, contributing to maintaining shoot water content, growth and yield (Vigani et al., 2018). In addition to plant growth stimulation, PGP microorganisms are able to favor the nutrient uptake. For instance, under nutrient-limiting conditions, symbiotic nitrogen-fixing rhizobacteria such as Azospirillum irakense or Rhizobiaceae (Khammas et al., 1989) and arbuscular mycorrhizal fungi (AMF; Metarhizium) are able to fix the atmospheric nitrogen (in the case of AMF, N fixation is mediated by the intracellular bacterial symbionts which such fungi may host) that can be used by the plants (Frąc et al., 2018; Berdeni et al., 2018). Other nutrients not available for the plants (e.g., insoluble forms of phosphate, such as

AlPO4, FePO4) can be solubilized and mobilized by rhizospheric bacteria, such as Pseudomonas, Rhizobium, and Bacillus, while fungi such as Aspergillus and Penicillium also play a role in solubilization of nutrients for plants (Khan et al., 2007; Song et al., 2008). Along with biopromotion (studied for instance during abiotic stress; Rolli et al., 2015) and biofertilizer activities, plant associated microorganism can improve plant resistance against biotic stresses (e.g., phytopathogens). It has been observed that plant protection can be mediated by microbial compounds with antagonistic activity against a wide range of phytopathogens, such as fungi (Bridge and Spooner., 2001). For example, plant associated microorganisms produce lytic enzymes, antibiotics, and antimicrobial compounds that can suppress pathogen growth (Innerebner et al., 2011). One interesting example is brought by fungi of the genus Trichoderma–a mycoparasite affecting many phytopathogenic fungi (Frąc et al., 2018); Trichoderma spp. protect plants by secreting 34 extracellular enzymes for the degradation of the chitinous phytopathogen cell wall (Gao et al., 2010; Selosse et al., 2004). Along with the production/secretion of antimicrobial molecules, microorganisms’ competition for available resource and niches is also an important strategy to indirectly exclude and contrast pathogens (Innerebner et al., 2011). For example, PGP Pseudomonas sp. strains are able to compete for iron (Fe) by the production of chelating siderophores, resulting in an active and efficient antagonistic activity to limit pathogens spread and development (Selosse et al., 2004). Undoubtedly, PGP microorganisms exhibit a great potential under diverse ecosystems and climatic conditions. While several mechanisms used by PGP microorganisms have been characterized, further research is needed to improve their exploitation as useful bio- resources in agriculture.

1.6 Conclusions

Plant microbiome interactions are very complex and there are a number of factors shaping the recruitment and assembly of plant-associated microbial communities. It is evident that the assemblage and the function of plant-associated microbial communities is driven by different ecological factors, including the type of plant and its growing conditions, the soil type, land history, cultivar variety, abiotic stresses and geo-climatic factors among others. Despite the recognized importance of the microbial components in the plant holobiont, we are still far from clearly understanding the relative weight of each factor in the establishment of the plant meta-organism. This indicates how such kind of research have to continue to deeply explore the complex and highly diverse microbiome interactions occurring in both natural and agricultural ecosystems, especially looking to a possible implementation of the use of plant microbiome to improve plant growth, health and production in agriculture.

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Chapter 2. Grapevine associated microbiome: understanding the factors affecting the rhizosphere microbial community structure and composition in rootstock-scion combinations

Abstract. Beneficial interactions between plants and microbes present a crucial role in sustaining plant fitness, promoting growth and controlling diseases. While it has been extensively documented that the recruitment of plant associated microorganisms (i.e., bacteria and fungi) is influenced by many factors, among others soil type, fertilization, and developmental stage, few studies have been conducted on the selective pressure imposed by the rootstock and the related scion-rootstock combinations. In many countries, to overcome biotic and abiotic stress constraints, and enhance vegetative growth and fruit yield, crops–both arboreal and non-arboreal–are extensively cultivated in the form of grafted plant, in which a productive plant species (for instance grapevine, Vitis vinifera) is grafted onto resistant rootstocks (for instance, other species of the genus Vitis, but no V. vinifera). Since it has been shown that the plant species and in particular the plant root system play a key role in the recruitment of microorganisms from the soil on and in the root, it is expected that different rootstocks, as well as different scion- rootstock combinations, select different microbes from the surrounding soil. Here, the rhizosphere of seven combinations of grafted grapevine (rootstock-scion) cultivated in ten vineyards has been selected in two geographical areas of Tuscany, in order to evaluate the contribution of the rootstock type, the scion type, their combinations and the soil type on the rhizosphere microbial community enrollment. A total of 66 rhizospheric soils, along with their related bulk soils, have been sampled. High-throughput sequencing of bacterial 16S rRNA gene and fungal ITS were performed and the structure and composition communities examined. Results showed that the assembly of grape rhizospheric microbial communities is mainly influenced by the geographical area, as well as by the soil type. Despite a strong effect of the edaphic nature, the rhizospheric microbial communities were also significantly affected by the rootstock-scion combinations. Notably, all grapes were consistently associated with a core microbiome, 45 composed by known plant growth promoting microorganisms, as well as with specific taxa related to each rootstock-scion combination. Keywords: Grapevine microbiome, Vitis vinifera, Microbial community, Bacteria, Fungi, Rootstock-scion combination

2.1 Introduction

The plant-associated microbiota is an essential component of plant holobiont (Sánchez- Cañizares et al., 2017); Such microbial communities (i.e., bacteria, fungi, protists, and viruses; Turner et al., 2013) add an external second metagenome to that of the plant, which supplies key ecological functionalities enhancing plant fitness (Rosenberg and Zilber-Rosenberg., 2016). As recent literature unveiled, the plant-associated microbiome plays an important role in prmoting plant health, growth, and adaptation to environmental challenges (Berendsen et al., 2012). Thus, understanding and characterizing the dynamics and factors driving the recruitment and assembly of plant microbiome is key in view of a possible manipulations of the ecological processes driving the plant-microbiome assembly and, indirectly, plant fitness, growth and productivity for a sustainable agriculture (Hartman et al., 2018). Plants actively recruit and select microorganisms from the surrounding bulk soil by means of the rhizosphere (i.e., transition zone between root and soil influenced by root exudates; Zhalnina et al., 2018), before they cross the rhizoplane barrier to become endophytes (Santoyo et al., 2016). Thus, the interaction among the root system (where the plant species has e specificity role), the edaphic microorganism, and the soil are extremely important to understand the complex process involved in plant-microbe association. The majority of studies were conducted on conventional plant species (e.g., cultivated and wild), with low attention to ‘chimeric plant’, i.e., individual plants constituted by two or multiple species. Examples are grafted plants widely used in agriculture, in which two plants are physically joined to create a single individual (Gaion et al., 2018); the typical grafted plant presents genetically different compartments, the 46 root system of one plant (rootstock) and the shoot (scion) from another variety or even species. This technique is mainly used with trees and shrubs, to combine the best characteristics of the two plants (typically, the rusticity and resistance of rootstocks and the quality and productivity of scion). Today, most fruit trees (e.g., grapevine, apple, avocado, citrus, peach, rose; Melnyk and Meyerowitz, 2015; Goldschmidt, 2014) and horticulture plants (e.g., 20-40% of tomatoes, 75% of cucumbers, 20-40% of eggplant, 5- 10% of peppers, and 90% of watermelon plants; Lee et al., 2010; Lee et al., 1994) are grafted onto rootstocks. Among these, grapevine is the most iconic and spread grafted crop, covering up to 7.5 million hectares worldwide (OIV, 2017). In Europe, since the 19th century, Vitis vinifera varieties are cultivated as scion grafted onto a rootstock of other Vitis species to prevent vineyard collapse by the aphid-like hemipteran Phylloxera spp. (Granett et al., 2001; Berlanas et al., 2019). Grafting the susceptible species V. vinifera on to rootstocks of American vine species (e.g., V. rupestri, V. berlandieri, and V ruparia) that co-evolved with Phylloxera represents the only effective solution to protect grapevine plants and viticulture worldwide (Battey and Simmond, 2005). So far, the rootstock- mediated treatment was also adopted as a general practice and the development of new genotypes became an important issue in modern viticulture (Whiting, 2004). The rootstock can affect the grapevine development by influencing the reproductive performance, the vigor of the scion, biomass accumulation and distribution in the plant, quality yield and phenology (Corso et al., 2016). Moreover, it can influence the plant resistance to several soil-borne pests and diseases (e.g., nematodes, powdery mildew, black rot; Ferris et al., 2012; Reisch et al., 2012; Wallis et al., 2013), as well as improve plant resistance against climate or adverse soil conditions, such as drought (Berdeja et al., 2015), salinity, (Henderson et al., 2014), lime content (Bert et al., 2013) and poor mineral nutrition (Habran et al., 2016). Studies on the spatial and temporal variations of the bacterial assemblages associated with different grapevine organs, including leaves, flowers, grapes, and roots show a jeopardized composition and structure, revealing that myriad of factors can influence their dynamics of assembly, including specific biogeographic factors and vineyard 47 management (Zarraonaindia et al., 2015; Martins et al., 2013; Pinto et al., 2014; Compant et al., 2011; Marasco et al., 2013; D’Amico et al., 2018; Novello et al., 2017; Samad et al., 2017; Zhang et al., 2017; Vitulo et al., 2019 Deyett and Rolshausen., 2020; Niem et al., 2020; Gamalero et al., 2020). It has been demonstrated that the majority of the microbial taxa associated to above-ground grapevine tissues originate from the soil microbime, indicating that the roots act as the primary reservoir of bacteria and fungi in the colonization of the entire grapevine plant (Deyett and Rolshausen., 2020; Pancher et al., 2012; Zarraonaindia et al., 2015). Soil heterogeneity and vineyard agricultural practices seem to represent the main factors that can affect the diversity of beneficial taxa recruited by the grapevine in the root system (Gamalero et al., 2020; Martínez-Diz et al., 2019; Berlanas et al., 2019; Manici et al., 2017; Campisano et al., 2014; Vega-Avila et al., 2015; Zarraonaindia et al., 2015). Nevertheless, despite obvious differences in terms of taxonomical composition, three vineyards from different pedoclimatic and geographical sets share a similar plant growth promoting potential hosted by the associated microbiota, indicating a requirement of closely-related beneficial traits supported by the associate bacteria to maintain grapevine functional homeostasis across an aridity gradient (Marasco et al., 2013). Although it is widely known that the rootstock genotype, as well as the grape associated microbiota, can deeply affect grapevine physiology (Düring 1994; Ezzahouani and Williams., 1995; Soar et al., 2006; Padget-Johnson et al., 2000; Southey and Archer, 1988), studies specifically addressing the relationship between a given graft combination (rootstock-scion) and the associated microbial assemblages are limited, and mainly focused only to the rootstock portion of plants growing in the same soil. Marasco et al., (2018) demonstrated that different rootstocks exerted a strong selection pressure able to recruit a specific bacterial community in grape cultivated in the same vineyard and soil. Notably, despite the selection of taxonomically different bacterial communities, the microbiome associated to grape root-systems conserved their ecological services (PGP traits). The role of rootstock in the recruitment of the grape microbiome was also confirmed by other researches: Lambrusco cultivars grafted on 1103P and Kober 5BB 48 rootstocks in D’Amico et al., (2018), Cabernet, Sauvignon, and Chardonnay cultivars grafted on 13 different rootstocks in Wallis et al., (2013), and Tempranillo cultivars grafted on five different rootstocks in Berlanas et al., (2019). All these studies confirmed that the rootstock genotype plays a critical role in the process of microbes’ recruitment and selection. However, the works published until know focused on nested plant with same scion without exploring the possible influence on the root microbiome recruitment of the above portion of the plant, as well as of the rootstock-scion combinations. Moreover, the fact that such studies were focused on grapes grown in the same soil, only partially addressed the role of the rootstock in the recruitment and selection of plant microbiome. To contribute in addressing this question, I selected seven different rootstock-scion combinations of grafted grapevine cultivated in ten vineyards located in two geographical area of Tuscany. Among these combinations, a total of four rootstocks (i.e., SO4, 420A, 110R and 3309C) and three scions (i.e., Chardonnay, Sangiovese and Merlot) were selected and rhizosphere (n=66) and bulk soil (n=66) were sampled. In this study, I used a high-throughput sequencing of bacterial 16S rRNA gene and fungal ITS to evaluate the effects of the rootstock type, the scion type, their combination and the soil type on the structure and diversity of the associated rhizospheric microbiome.

2.2 Methods and Materials

2.2.1 Sample collection. The root system (i.e., root tissue and rhizospheric soil) of four rootstocks (420A, SO4, 110R, and 3309C) were collected at the end of October, 2016 in the vineyards (n=10) of Nipozzano and Pomino areas (north-east of Tuscany, Italy; Figure 2.1), owned by Frescobaldi farm; location of vineyards and details on samples collected are reported in Table 2.1. The selected rootstocks were grafted on Chardonnay, Merlot, and Sangiovese grape cultivars, obtaining a total of seven rootstock-scion combinations (Table 2.1). A total of six plants (6 biological replicates) were selected in each vineyard; grapevine roots portions (n=66) were collected at 30-50 cm depth where the root system was denser. Six samples of bulk soil (fractions of soil not influenced by the root system) 49

from each location were also collected. All samples were collected under sterile conditions using sterile tools. Recovered samples were stored at -20°C for molecular analysis. The sampling was authorized by the private owners of each location and no specific permissions were required for this activity.

2.2.2 Physico-chemical analysis of vineyards’ soil. The chemical and physical properties of the bulk soil were characterized by Frescobaldi, the vineyards’ owner. Samples of bulk soil were collected from each vineyard, pooled and homogenized before to evaluate soil texture and analyze physico-chemical parameters, such as pH, cation exchange capacity

(CEC), total and active limestone content (CaCO3), organic matter, total carbon, total nitrogen, C/N ratio and available elements/nutrients (calcium, magnesium, potassium, and phosphorus), basic saturation, and overall acidity. Physico-chemical data were analyzed by performing a principal coordinate analysis (PCoA) and permutational multivariate analysis of variance (PERMANOVA) on the Euclidean distance matrix in Primer v.6.1 (Anderson et al., 2008); sample categories (2 levels: i.e., Pomino and Nipozzano) were used as explanatory variables.

Table 2.1. List of vineyards with location and of the sampled rootstock-scion combinations. A total of 6 plants (i.e., root system) per vineyard (6 biological replicates were collected, along with 6 samples of bulk soil.

Area Vineyard Coordinates Rootstock Scion Pomino Rena 43°49'23.02"N 11°32'32.61"E SO4 Chardonnay Rena 43°49'26.59"N 11°32'28.63"E 110R Chardonnay Fonte 43°48'26.36"N 11°33'10.41"E 420A Merlot Colle 43°48'45.75"N 11°33'39.41“E 420A Chardonnay Torta 43°49'0.70"N 11°32'17.81"E 420A Sangiovese Nipozzano Castelvecchio 43°47'23.89"N 11°29'15.01"E 420A Sangiovese Scopetino 43°47'41.71"N 11°30'14.16"E 3309C Chardonnay Sodi 43°47'5.90"N 11°29'13.74"E 420A Merlot Sodi Remole 43°47'17.35"N 11°24'36.36"E 420A Chardonnay Montesodi 43°47'2.25"N 11°28'56.27"E 110R Sangiovese Cartellone 43°46'22.89"N 11°28'35.75"E 420A Merlot

2.2.3 Total DNA extraction. The sampled roots with attached soil particles were placed in a sterile tube and 9 mL of physiological solution (9 g/L NaCl) were added. The tubes were 50 vortexed for 5 min to detach soil particles tightly attached, then centrifuged at 4000 rpm for 5 min; the roots were removed and the supernatant was discarded in order to collect the remaining soil and use it as rhizospheric soil. The obtained rhizospheric soils (n=66) and the collected bulk soils (n=66) were homogenized and 0.5±0.1 g were used to extract the total DNA using the PowerSoil® DNA Isolation Kit (MoBio Inc., CA, USA); the manufacturer’s instructions were followed. Eluted DNA (5 μl) was visualized on 0.8% agarose gel using electrophoresis to evaluate its quality; quantification of DNA was performed using Qubit 3.0 Fluorometer and dsDNA BR Assay kit. All Extracted DNA samples were stored at -20°C.

2.2.4 Amplification, sequencing and meta-phylogenomic analysis. Illumina tag screening of the V3-V4 hypervariable regions of the bacterial 16S rRNA gene was applied on DNA and performed at KAUST (Bioscience Core Lab) using the primers 341f and 785r (Klindworth et al., 2013), following the protocol described in (Mapelli et al., 2017). In case of fungi, the fungal ITS2 gene was amplified using ITS3F and ITS4R primers, following the protocol described in (Marasco et al., 2018). The sequencing libraries were constructed using 96 Nextera® XT Index kit (Illumina, Inc.); products of amplification were cleaned using SequalPrepTM Normalization Plate (96) kit. All libraries were sequenced on the Illumina MiSeq platform at Bioscience Core Lab, King Abdullah University of Science and Technology. The raw data obtained from Illumina sequencing were analyzed using a combination of the QIIME pipeline version 1.9 (Caporaso et al., 2010) and UPARSE version 8 (Edgar., 2013) as described in (Mapelli et al., 2017). After paired-end merging and quality filtering, only high-quality reads were kept for the further steps of the analysis. Reads were clustered as OTUs considering at 97% sequence distance similarity and taxonomy was assigned using QIIME’s uclust against SILVA 132 and UNITE databases for bacteria and fungi, respectively. All OTUs non-assigned to bacteria and fungi were removed. Number of sequences and OTUs obtained were reported in Supplementary Table 2.1; Good’s coverage values were calculated and reported in Supplementary Table 2.2. 51

2.2.5 Bacterial and fungal diversity, taxonomy distribution and statistical analysis. OTUs were filtered in order to keep only those presenting a relative abundance (%) higher than 0.01% and 0.001% for bacteria and fungi, respectively. Bray-Curtis distance matrices were used to perform a Principal Coordinates Analysis (PCoA), Canonical Analysis of Principal coordinates (CAP), and to conduct permutational multivariate analysis of variance (PERMANOVA) in PRIMER 6 (Anderson et al., 2008). Two fixed and orthogonal explanatory variables were considered: fraction (2 levels: rhizosphere and bulk soil), followed by geographical area (2 levels, Pomino and Nipozzano), vineyards (10 levels), rootstock-scion combination (7 levels), rootstock (4 levels) and scion (3 levels). Multivariate analysis of variance for each factor tested and the relative weight on the variance explained (R2) has been performed using adonis function within the package vegan of R. Alpha diversity indices (richness and Shannon diversity) were calculated using the PAST software (Horstemeyer and Wang, 2003). The shared and specific microbial OTUs among fractions (rhizosphere and bulk soil) and the rootstock-scion combinations have been defined by Venn-diagram analysis in R.

2.3 Results and Discussion

2.3.1 Geoclimatic and physico-chemical characterization of Pomino and Nipozzano areas. Pomino and Nipozzano estates of Frescobaldi are located in the north-east area of Tuscany (Italy), in the piedmont region in proximity of the Apennines (Figure 2.1a and b). They are mainly characterized by two different micro-climate conditions due to their different exposure to sun/light. Pomino estate occurs in the valley created by the small mountain river “Rufina” and cover a total surface of 1.458 hectares, of which 108 cultivated with vineyards within an altitude that range from 400 and 750 meters above the sea level (Figure 2.1a). Pomino agronomic area was established more than 500 years ago and the area has been managed for viticulture since then. Although the higher latitude, the exposure to south creates a 52 unique environmental condition for viticulture in Tuscany, where the specific geology (mainly characterized by sandstone and marl; Figure 2.2a and b), ecological and climatic microcosm makes possible the perfect balance between vineyards, fir forests, chestnut groves and olive groves (Figure 2.1b). This peculiarity shows an integrated management that support a high biodiversity in the area. On the contrary, Nipozzano (located 30 km north-east of Florence) extends over a total area of 626 hectares at an altitude of between 300 and 400 meters above sea level between the valley formed by river Arno and river Sieve, among the most important rivers in the region (Figure 2.1b). Nipozzano has 300 hectares of vineyards entangled with extensive patches of olive groves. Compared to Pomino, the estate of Nipozzano has less diverse environments (Figure 2.1). The geology of the site is characterized by a mix of sandstone and limestone bedrock that create a clayey and calcareous soil matrix (Figure 2.2a and b) that, along with dry and warm climate, results particularly suitable for grape cultivation. Both estates use the rootstocks 110R, 3309C, SO4, and 420A–obtained by the cross of different Vitis species (i.e., V. berlandieri, V. riparia, and V. rupestris; see details in the “Distribution and use of grape rootstocks in Tuscan vineyards”)–mainly grafted with Chardonnay, Merlot, and Sangiovese. There is no use of ungrafted plant. The agronomic techniques used are mainly two: the ‘traditional’ one with the use of common fertilizer and the ‘biological’ one that foresees the use of plant like wild-broad bean for the nourishment of the soil. Both estates did not experience fungal pest epidemic events in the last thirty years and the normal treatment for pest control are applied by using copper and sulfur treatments.

A- Pomino area Colle Fonte

Rena

Colle

Torta

Fonte Rena Torta

53

B – Nipozzano area Scopetino Scopetino Castelvecchio Montesodi

Sodi Remole Sodi

Castelvecchio Cartellone

Montesodi Cartellone Sodi Sodi Remole

Figure 2.1. Satellite images of the studied vineyards in Tuscany. (a) Pomino area and specific image of each of the studied vineyards (4 vineyards, 5 sampling sites). (b) Nipozzano rural area showing the six sampled vineyards. Blue and red tags indicate the locations in which samplings were conducted; coordinates are specified in the materials and methods. Satellite images were obtained from Google Earth.

As expected, the two geographical areas investigated (i.e., Nipozzano and Pomino) were characterized by different soil textures (PERMANOVA, F1,8=5.99; p=0.023; Figure 2.2a and b), mainly determined by the different content in sand (t1,8=2.707, p=0.027) and clay

(t1,8=4.52, p=0.002); silt content did not differ across the two areas (t1,8=0.8, p=0.4;). While in the Nipozzano vineyards (Figure 2.1b) the heterogeneous soil texture (i.e., Montesodi and Castelvecchio were richer in sand) determined distinct vineyards clusters (Figure 2.2b), in Pomino dominance of sand across all vineyards (range, 57-75%) determined more similar soil texture conditions (i.e., all samples cluster in the left-low corner of the ternary plot; Figure 2.2b). 54

a b SSiltilt c 0 20 40 60 80 100

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20 40 60 80 100 Nipozzano Pomino SandSand ClClaayy PCO1 (40.9% of total variation)

Figure 2.2. Chemical-physical analysis of vineyards’ soil. (a) Heat map showing the texture of the 10 vineyards selected; sand, silt and clay contents are expressed in percentage. (b) Ternary plot showing the soil texture; dots indicate the selected vineyards (red, Nipozzano and blue, Pomino); position of dots in the triangle indicates their relative content in sand, silt and clay. (c) Principal coordinates analysis (PCoA) of physico-chemical parameters reported in Table 2.2.

Soil texture and geometry properties (i.e., soil pore size) are important factors having direct effects on water and oxygen availability, thus on root system development (Chapman et al., 2012). In general, the presence of larger pore size (6-30 μm) observed in soils with high percentage of sand and sandstone, compared to the ones in clayish soils (<0.2-1.2 μm), determines a quick drainage of water (Hassink et al., 1993; Franzluebbers, 1999; Baldock and Skjemstad, 2000; Hassink et al., 1997), possibly favoring better agronomic performance of Pomino vineyards in rainy years than in drought periods because incapable to retain sufficient moisture (Bhardwaj et al., 2007). Physical chemical properties of the vineyards soil, such as pH, soil organic carbon, and nutrients content, summarized in Table 2.2, are usually considered as indicators of soil quality (i.e., fertility; Riches et al., 2013). Analysis of such data (i.e., excluding collinear variables; see Material and Methods section) further confirmed that there are considerable differences between the two areas. The Principal Coordinates Analysis (PCoA) of physico-chemical soil analysis showed the presence of different groups, mainly depicted as Pomino and Nipozzano areas

(PERMANOVA, F2,19 =7.03; p=0.0001 Figure 2.2c).

55

Table 2.2. Physical-chemical parameters measured in the ten selected vineyards.

Nipozzano Pomino

Physical-chemical

parameters

Castelvecchio Scopetino RemoleSodi Sodi Montesodi Cartellone Rena Fonte Colle Torta pH 7.7 8 8.1 8.1 7.66 8.02 6.46 7.98 7.5 7.34 Total limestone 100 7.8 14.7 16.6 66 277 58 38 1 17 Limestone active 96 2.8 3 7.9 55 145 3 18 0.1 6 Total N 2 0.98 0.89 0.93 1.8 1.9 0.7 0.9 0.75 1 Organic substance 30.1 36.86 10.43 10.78 28.5 21.6 13.6 13.1 5.19 3.4 C/N ratio 8.9 21.8 6.7 9.4 6.5 10.9 8.9 4 2 Equivalent P 71 2 1 2 21 17 14 20 13 10 Exc. K 433 264 247 159 569 491 160 108 164 75 Exc. Mg 218 300 92 178 213 166.6 482.5 157.6 994 786 Exc. Ca 3479 5538 7441 5912 3969 3840.2 2064.2 2918 2901 2606 Exc. Na 1 19 21 20 1 2.7 0.1 0.1 17 72 CEC 20.2 30.9 38.6 31.5 23 21.8 14.7 16.1 23.4 20

Notably, despite the absence of replicates hinder to apply a proper statistical analysis, it is possible to observe that within each area-group the vineyards that cluster together (i.e., close to each other’s in the PCoA ordination space) were geographically distant; for instance, Scopetino and Sodi Remole were in the opposite side within the Nipozano area (Figure 2.1b), possibly indicating that other additional factors–not driven by geography– may explain such results. For instance, while all the vineyards’ soils were neutral-slightly alkaline, with pH from 6.5 to 8 in Pomino and from 7.7 to 8.1 in Nipozzano, several other parameters influence soil diversity, such as organic carbon, limestone and exchangeable ions contents and cation exchange capacity (Table 2.3). Among these, the total nitrogen followed by exchangeable calcium were the main physio-chemical variables that influence the soil of the selected vineyards (sequential test and AIC model in Table 2.3).

Table 2.3. Results of distance-based linear model (DistLM) marginal and sequential step-wise tests, showing the influence of the different physical-chemical parameters on the vineyard soils; model selection using the AIC (Akaike information) criterion is also reported. Significance contribution of variable to soil difference, p-values <0.05. CEC: Cation Exchange capacity.

Marginal test Variable F Prop. P pH 2.0202 0.20162 0.063 56

Organic substance 3.2565 0.2893 0.008 Total N 4.4706 0.35849 0.004 C/N ratio 1.4273 0.1514 0.207 Total limestone 3.1121 0.28006 0.002 Limestone active 4.3824 0.35392 0.001 CEC 2.4657 0.2356 0.032 Equivalent P 2.344 0.22661 0.011 Exchangeable Ca 2.6127 0.24619 0.024 Exchangeable K 4.0758 0.33752 0.002 Exchangeable Mg 2.5523 0.24187 0.023 Sequential test Total N 4.4706 0.35849 0.001 Exchangeable Ca 4.3731 0.24667 0.002 Overall best solution AIC 24.503; R2=0.6 Sequential test, 2 variables

2.3.2 Distribution and use of grape rootstocks in Tuscan vineyards. Rootstocks affect scion vigor, yield, fruit size, fruit quality, and pest tolerance (Pavlousek., 2011; Lambert et al., 2008). However, plant growth and productivity strongly depend also on climate, soil type, and other factors, often producing contradictory reports on rootstock performance in different areas (Leeuwen et al., 2019). Thus, choosing the right rootstock for soil type and vineyard location is critical. As previously described (Figure 2.1 and 2.2), each vineyard has unique combination of conditions, strongly dictated by the soil physico- chemical characteristics and geoclimatic factors. In Italy, most of the grapevine plants are now grafted on the SO4 rootstock (selection oppenheim, V. berlandieri ⨉ V. riparia; Boso et al., 2008). It offers the advantage of adaptability and good productivity, representing the first choice for several Italian viticulturists. Subsequently, based on soil conditions, the most commonly used rootstocks are those that push plant vigor, such as 110 Richter (110R, V. berlandieri ⨉ V. rupestris); it is perfectly suited to tough and dry hillside slopes and it is an excellent rootstock for warm climates encompassing drought events (Yıldırıma et al., 2018; Leeuwen et al., 2019), representing a possible suitable alternative to cope with the climate change condition that Europe experienced in the last decade (Duchêne and Schneider., 2005). On the contrary, 3309 Couderc (3309C, V. riparia ⨉ V. rupestris) had low to moderate tolerance to chlorosis and it only resists up to 20 and 11% of total and active limestone, respectively (Lambert et al., 2008). Notably, it was planted in Scopetino vineyard (Nipozzano), in which total and active limestone had low values (Table 57

2.2). Moreover, it is sensitive to water stress, particularly when it occurs suddenly during the growing cycle, thus it is not wide spread in the Frescobaldi vineyards. Finally, 420A rootstock (Millardet et de. Grasset 420A, V. berlandieri ⨉ V. riparia) confers low vigor to plants, limiting the yields, particularly during the first years of production (Cousins., 2005). Thus, it is the less popular rootstock, also if in the last years it can be found in several Italian vineyards; its requirements cover a wide range of soil type (i.e., deep, fine texture, alkaline soils), representing a possible compromise for vineyards with heterogeneous soils, such as the case of Pomino and Nipozzano vineyards.

Table 2.4. Rootstock name, genetic origin and main adaptation to environment are reported. Notably, all the rootstock selected have low resistance to nematodes and high resistance to Phylloxera.

Rootstock Parentage Vigor Drought Salinity Wetness

420A V. berlandieri ⨉ V. riparia Low Moderate Low Low-moderate

SO4 V. berlandieri ⨉ V. riparia Very high Moderate Low Moderate

110R V. berlandieri ⨉ V. rupestris High Very high Moderate Low-moderate

3309C V. riparia ⨉ V. rupestris High Moderate Low Moderate

2.3.3 Diversity estimation of microbial communities associated to the rhizosphere of different grapevine rootstocks. Next generation sequencing technology was adopted to explore the biodiversity of microbiomes (i.e., bacterial and fungal components) associated to the plant rhizosphere of seven rootstocks-scion combinations (i.e., from 4 rootstocks and 3 scions; Table 2.1) in Tuscan vineyards, and related bulk soils not influenced by grapevine root systems. After quality trimming, exclusion of non-target co- amplicons (e.g., chloroplast and mitochondria) and unclassified reads, a total of 4,901,970 and 7,895,828 paired-end reads have been recovered; these sequences were clustered into 5,399 and 1,479 unique operational taxonomic units (OTUs; 97% nucleotide identity) for bacteria and fungi, respectively (Supplementary Table 2.1).

Table 2.5. Alpha diversity estimates of the microbial communities. OTUs richness (number of observed OTUs) and Shannon were calculated for bacterial and fungal communities. Values are reported as average 58

± standard deviation. Dollar ($) indicates that only rhizospheric communities were considered; hash (#) indicates that in the case of fraction, cultivation area and vineyards, low coverage of bulk soil samples could affect the alpha-diversity indices (all data presenting this issue are reported in grey). ANOVA is performed for each factor and p-values reported: non-significant, p>0.05; *, p<0.05; **, p<0.01; ***; p<0.001, ****, p<0.0001

Bacteria Fungi Factor Richness Shannon Richness# Shannon# Fraction **** **** **** **** Rhizosphere 1992 ± 484 5.3 ± 0.9 414 ± 96 3.9 ± 0.4 Bulk 2576 ± 427 6.3 ± 0.2 212 ± 67 3.3 ± 0.5 Cultivation area **** ** * p>0.5 Pomino 2039 ± 580 5.6 ± 1.1 341 ± 155 3.62 ± 0.56 Nipozzano 2488 ± 409 6.0 ± 0.6 290 ± 101 3.60 ± 0.48 Vineyard *** p>0.5 p>0.5 p>0.5 Rena 2045 ± 610 5.4 ± 1.3 341 ± 168 3.4 ± 0.7 Fonte 2259 ± 777 5.4 ± 1.3 375 ± 160 3.7 ± 0.5 Colle 1928 ± 276 5.8 ± 0.5 273 ± 104 3.7 ± 0.5 Torta 1917 ± 515 5.7 ± 0.7 375 ± 162 3.9 ± 0.2 Castelvecchio 2436 ± 564 5.8 ± 0.9 298 ± 91 3.5 ± 0.6 Scopetino 2472 ± 337 6.3 ± 0.3 301 ± 93 3.8 ± 0.3 Sodi 2496 ± 372 6.1 ± 0.4 224 ± 69 3.6 ± 0.6 Sodi Remole 2631 ± 539 6.1 ± 0.4 331 ± 94 3.7 ± 0.3 Montesodi 2380 ± 238 5.9 ± 0.5 290 ± 149 3.5 ± 0.5 Cartellone 2513 ± 351 6.0 ± 0.6 295 ± 84 3.5 ± 0.5 Rootstock$ ** * **** p>0.5 SO4 1658 ± 465 5.0 ± 1.0 516 ± 49 3.8 ± 0.2 420A 2105 ± 441 5.4 ± 0.9 376 ± 97 3.9 ± 0.2 3090C 1832 ± 517 4.9 ± 1.0 379 ± 52 3.7 ± 0.8 110R 2297 ± 296 6.1 ± 0.4 441 ± 60 4.0 ± 0.3 Scion-rootstock combination$ *** *** *** p>0.5 SO4-Chardonnay 1770 ± 510 4.6 ± 0.9 517 ± 49 3.8 ± 0.1 420A-Chardonnay 2020 ± 331 5.6 ± 0.4 381 ± 65 4.0 ± 0.2 420A-Merlot 2191 ± 519 5.3 ± 1.1 375 ± 124 3.9 ± 0.2 420A-Sangiovese 2019 ± 386 5.3 ± 1.1 373 ± 65 4.0 ± 0.3 110R-Chardonnay 1384 ± 297 4.0 ± 0.6 467 ± 59 4.0 ± 0.2 110R-Sangiovese 2279 ± 143 5.7 ± 0.5 416 ± 54 4.1 ± 0.1 3309C-Chardonnay 2297 ± 296 6.1 ± 0.4 379 ± 52 4.1 ± 0.3

Rarefaction curves evaluating the OTUs richness per sample generally approached saturation, except in the case of fungal community of bulk soils (Supplementary Figure 2.1). The microbial diversity within each sample (alpha-diversity) was analyzed, considering taxa richness (number of OTUs) and Shannon diversity index as main indicators (Table 2.5). 59

As expected, bulk soil bacterial communities were more diverse than rhizospheric ones with a higher number of species (higher richness) evenly distributed (higher Shannon), confirming previous data obtained in several vineyards in which the selective pressure exerted by the plant root system is the main factor that drive the structure of the bacterial community associated to the rhizosphere (D’Amico et al., 2018; Berlanas et al., 2019; Marasco et al., 2018). Unfortunately, this comparison cannot be properly run for the fungal communities, due to the low rarefaction presented by diversity in the bulk soil (Supplementary Figure 2.1). However, analysis of fungal community performed in cordon- pruned conventional vineyard (Temecula, California) showed that also in the case of fungi, the bulk soil had significantly higher number of taxa evenly distributed than the rhizosphere (Deyett and Rolshausen., 2020). Since the published observation on the fungal communities in other vineyards (Martínez-Diz et al., 2019) and agricultural fields (Varanda et al., 2016) and the consistent trend observed for bacteria in the studied vineyards (i.e., bulk soil as bacterial reservoir; Zarraonaindia et al., 2015; Garbeva et al., 2014), it is reasonable to suppose that a similar situation occurred also for fungi in my samples. Further sequencing will be performed to confirm this speculation. Despite the general trends observed in the two compartments, a complex scenario has been depicted for the microbiomes associated to the different cultivation areas, vineyards, and rootstocks, with a marked difference across rhizosphere of different rootstocks and rootstock-scion combinations (Table 2.5). Notably, while microbial richness was consistently affected by such parameters, they influence the distribution of taxa (i.e., Shannon index) only in bacteria. To confirm the selective process mediated by the rhizodeposition and root exudate release, in which the rhizosphere recruits and enriches its communities from the microbial-pools present in the surrounding soil (Zhalnina et al., 2018; Hu et al., 2018; Doornbos et al., 2012; Zarraonaindia et al., 2015), microbial taxa in common between rhizosphere and bulk soil were visualized using Venn diagram (Figure 2.3): in both Pomino and Nipozzano only a limited number of OTUs was detected as fraction specific (i.e., rhizosphere and bulk soil), with up to 94 and 75% of bacterial and fungal OTUs, 60 respectively, ubiquitously detected in rhizosphere and surrounding bulk soil. These represented almost the totality of reads analyzed (Pomino: 99 and 94% bacterial and fungal reads; Nipozzano: 99 and 96% bacterial and fungal reads, respectively). Such high percentage of microbial OTUs shared between bulk soil and rhizosphere confirmed the bulk soil as reservoir from which root system can recruit microorganisms (Zarraonaindia et al., 2015; Gamalero et al., 2020; Berlanas et al., 2019; Novello et al., 2017). Specialist OTUs–only present in one of the two fractions–where also detected; as expected, due to the selection of edaphic microorganism from the bulk soil, the grape root systems (i.e., rootstocks rhizosphere) had a lower percentage of unique OTUs compared to bulk soil (Novello et al., 2017). Due to limited number of fungal reads recovered for bulk soil samples, this trend could be confirmed only for the bacterial community; new sequencing efforts will be necessary to enrich good sequencing depth and understand if the recruitment process for the fungal members of the communities follows the same mechanisms of bacteria.

Figure 2.3. Microbial recruitment process in grape rhizosphere. Venn diagram detecting bacterial and fungal specialists (only present in one fraction) and generalists (shared among the two fractions) OTUs in rhizospheres and bulk soils of Pomino and Nipozzano vineyards. The numbers not included in the circles (i.e., rhizosphere and bulk soil) represent OTUs not detected in Pomino or Nipozzano.

61

Notably, the two studied geographical areas shared the majority of bacterial and fungal OTUs, with a limited portion of OTUs not detected in Pomino (5 and 7% of bacterial and fungal OTUs) and in Nipozzano (6 and 12% of bacterial and fungal OTUs). Principal Component Analysis (PCoA) revealed a strong clustering of edaphic microorganisms according to the different fractions sampled (rhizospheric and bulk soil) at the OTUs level in both bacteria and fungi (PERMANOVA, bacteria: F1,130=18.35, p=0.001 and fungi: F1,130=38.03, p=0.001; Figure 2.4). Despite root-system (i.e., rhizosphere) exerted a strong selective pressure in the recruitment of microorganisms, the geographical area of samples’ origin (i.e., soil type and geoclimatic conditions of Nipozzano and Pomino; Figure 2.2) significantly contributed to shape the edaphic microbial communities, clearly determining two main clusters, Nipozzano and Pomino

(bacteria: F1,130=44.84, p= 0.001 and fungi: F1,130=16.09, p= 0.001; Figure 2.4a and b), in which rhizosphere and bulk soil communities were consistently different (Pomino - bacteria: t=4.51, p=0.001 and fungi: t=5.53, p=0.001; Nipozzano - bacteria: t=3.79, p=0.001 and fungi: t=4.80, p=0.001). In addition, the micro-ecosystem defined by each vineyard also had a significant role in shaping the diversity of edaphic microbial communities (Figure 2.4c and d), as clearly showed by the soil-chemical analysis (details in Figure 2.2 and Table 2.2).

Table 2.6. Multivariate analysis of variance for each factor tested and is relative weight on the variance explanation (R2 provided in the table).

Rhizosphere Bulk soil Kingdom Factor Df F P R2 F P R2 Bacteria Vineyard 9,56 7.56 0.001 0.55 10.71 0.001 0.63 Area 1,64 30.88 0.001 0.32 34.92 0.001 0.35 Rootstock-scion combination 6,56 4.63 0.001 0.29 4.49 0.001 0.31 Rootstock 3,62 2.44 0.005 0.11 3.09 0.002 0.13 Scion 2,63 2.63 0.007 0.08 2.89 0.005 0.08 Fungi Vineyard 9,56 9.01 0.001 0.59 4.18 0.001 0.40 Rootstock-scion combination 7,58 4.55 0.001 0.32 2.75 0.001 0.22 Area 1,64 21.12 0.001 0.25 9.34 0.001 0.13 Rootstock 3,62 3.18 0.001 0.13 2.51 0.001 0.11 Scion 2,63 3.22 0.001 0.09 2.13 0.001 0.06

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The vineyards soil conditions explained up to 63 and 40% of the diversity ordination in the bulk soil of the bacterial and fungal communities, respectively, and 55 and 59% in the rhizosphere, resulting the most important factor shaping the overall microbial communities studied (Table 2.6). Geographical area (a general parameter including climatic conditions and altitude among others) also contributed to shape data ordination, resulting the second factor explaining diversity of the bacterial community (32-35% of variability), and the third for fungal communities (13-25%; Table 2.6).

a Fraction and Area c Fraction and Vineyard e Rootstock-scion combination

a

i

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Figure 2.4. Beta-diversity of microbial communities associated with grapevine rootstocks’ rhizosphere and bulk soils in Tuscan vineyards. Principle coordinate analysis (PCoA) of (a,c,e) bacterial and (b,d,f) fungal communities based on Bray-Curtis similarity matrices. (a and b) Separation of (a) bacterial and (b) fungal microbial communities considering both fraction (bulk soils and rhizosphere) and areas (Pomino and Nipozzano). (c and d) Bacterial and fungal communities, respectively, associated with bulk soil (triangle) and rhizosphere (circles) in the different vineyards; Pomino vineyards are indicated by blue shades and 63

Nipozzano by red shades. (e and f) Samples of bulk soil (triangle) and rhizosphere (circles) are colored based on rootstock-scion combinations.

The importance of environmental factors, such as the soil condition and its physio- chemical characteristics (e.g., soil structure and element content) have been often reported as the major factor regulating the recruitment and selection of rhizosphere microbiome in grapevine (Costa et al., 2006; Schreiter et al., 2014; Fernández-Calviño et al., 2010; Corneo et al., 2014; Zarraonaindia et al., 2015; Holland et al., 2016). However, among the factors affecting the rhizosphere microbiome, the rootstock-scion combination and rootstock itself had also a significant role in mediating the recruitment of specific bacterial and fungal microbial communities (Table 2.6). The rootstock-scion combination consistently explained higher percentage of the observed variability compared to the rootstock itself, while scion alone did not have strong influence (Table 2.6). The importance of these factors in the microbial communities’ assembly was further corroborated by cross-validation (canonical analysis of principal coordinates, CAP): low percentage of misclassification was observed for the rhizospheric communities when vineyards (4.5 and 2% in bacteria and fungi, respectively), rootstock (6 and 3%) and rootstock scion combination (7.6 and 3%) are considered as factors, confirming the consistent role of all these factors in plant-microbiome assembly. These results confirmed the general trend of the microbial community selection in agriculture ecosystem (Philippot et al., 2013), and specifically in grapevine (Zarraonaindia et al., 2015; Marasco et al., 2018; D'Amico et al., 2018; Berlanas et al., 2019). I have highlighted for the first time, the role of rootstock-scion combination in the assembly of the rhizosphere microbiome in grapevine. As reported in Table 2.6, this factor explained up to 39% of the observed microbial diversity in the rhizosphere, representing the second in term of importance among those analyzed. In this work–in which different soils and rootstock-scion combinations were taken into account (Table 2.1)–the factor rootstock alone resulted less important than the rootstock-scion combination, indicating that the above-ground portion of the plant (scion) is involved in the communication with the below ground rootstock, not only to maintain the appropriate physiology and metabolism 64

(i.e., nutrient exchange, growth signal, etc.; Sivritepe et al., 2010; Tandonnet et al., 2010), but also to mediate the microbiome recruitment in the rootstock. In another study, Liu et al. (2018) revealed that the beta-diversity of fungal endophytes is significantly different among scions grafted on same rootstocks. The rootstock-scion interactions mediate many aspects of the plant physiology such as, for instance and among others, plant hormonal signaling (Aloni et al., 2010; Gonçalves et al., 2006). Sorce et al. (2002) reported that in grafted plants the levels of auxin and cytokinin are different compared to ungrafted plants. Thus, the scion genotype may impact the ecological process related to the selection and recruitment of root associated microbial communities.

2.3.4 Relative abundance of bacterial taxa associated to the grape rootstocks’ rhizosphere and surrounding bulk soil. The taxonomic affiliation of OTUs revealed that the grapevine rhizosphere hosted 28 bacterial phyla, 79 classes, 154 orders, 229 families and 427 genera (Table 2.7). Both rhizospheric and bulk soil bacterial communities were dominated (on average) by Proteobacteria (44%; classes: 21.6% Gammaproteobacteria, 18.7% Alphaproteobacteria, and 3.8% Deltaproteobacteria), Acidobacteria (16%; 9.4% Blastocatellia, 4% Subgroup 6, 1.9% Acidobacteriia, and 1.4% Acidimicrobiia), Actinobacteria (14%; 9.2% Actinobacteria and 3% Thermoleophilia), Bacteroidetes (7%; Bacteroidia, 6.6%), Chloroflexi (6%; 1.3% Chloroflexia and 1.6% Anaerolineae), Verrucomicrobia (4%; 3.7% Verrucomicrobiae), Gemmatimonadetes and Planctomycetes (2% each; Gemmatimonadetes and Phycisphaerae, respectively), along with several low abundance members (n=20), accounting for a total of 3% of the relative abundance.

Table 2.7. Bacterial and fungal reads assigned to taxonomic ranks (phylum, class, order, family and genus). Values are expressed as total number of reads in the overall datasets and percentage. Number of different taxa detected at each taxonomic rank was also reported (N., number of different taxa).

Bacteria Fungi Reads Percentage N. Reads Percentage N. Phylum 4901970 100 28 7833210 99.2 10 Class 4877141 99.5 79 7452497 94.4 32 Order 4392673 89.6 154 5933355 75.1 92 Family 3910464 79.8 229 4630949 58.7 179 65

Genus 2594375 52.9 427 4177726 52.9 352

Total 4901970 7895828

Specifically, an increment in the relative abundance of Proteobacteria (mainly Gammaproteobacteria and Alphaproteobacteria classes) was observed in the rhizosphere of both geographical areas (Nipozzano: 51% in rhizosphere and 32% in bulk soil; Pomino: 69% in rhizosphere and 28% in bulk soil), while Actinobacteria (Actinobacteria class) were enriched only in the rhizosphere of plants cultivated in the Nipozzano vineyards (Nipozzano: 19% in rhizosphere and 12% in bulk soil; Pomino: 10% in rhizosphere and 16% in bulk soil; Figure 2.5a).

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Figure 2.5. Taxonomic diversity of bacterial communities associated with grapevine rhizosphere and vineyard bulk soils. (a) Comparison of bacterial communities in samples from root-system compartments (i.e., rhizospheres) and surrounding bulk soil, in Nipozzano and Pomino vineyards. Relative abundance of different bacterial phyla in the rhizospheres and bulk soil is shown. (b) Relative abundance of different bacterial phyla is also visualized in the rhizosphere and bulk soil fraction across the ten vineyards selected (6 in Nipozzano and 4 in Pomino). (c) Visualization of phyla relative abundance using as variable the seven rootstock-scion combinations (2 in Nipozzano, 2 in Pomino and 3 shared among the two areas). Phyla representing less than 1% of the total reads are grouped in ‘Others’.

All the other phyla (Acidobacteria, Verrumicrobia, Chloroflexi, Plantomycetes, and Gemmanotimonadetes) reduced their relative abundance moving from the bulk soil to the rhizosphere and showed a consistent pattern of recruitment in the two geographical areas (Figure 2.5a). As shown by similarity percentage analysis (SIMPER), the main phyla that contributed to differentiate the rhizosphere from the surrounding soil were Acidobacteria, Proteobacteria, Actinobacteria, Chloroflexi and Bacteroidetes in Nipozzano (explained dissimilarity, 86%), along with the contribute of Verrucromicrobia in Pomino (explained dissimilarity, 88%). The major phyla detected in Tuscan vineyards do not differ from those found in previous studies examining the bacterial microbiomes of grapevines in other geographical locations, suggesting that part of the bacterial microbiome associated with grapevine root system (i.e., rhizosphere) is conserved (Berlanas et al., 2019). For instance, dominance of Proteobacteria (Gamma and Alpha) in grapevine rhizosphere was consistently observed in grafted (D’Amico et al., 2018; Berlanas et al., 2019; Novello et al., 2017; Vega-Avila et al., 2015; Pinto et al., 2014; Zarraonaindia et al., 2015) and ungrafted (Marasco et al. 2018) grape plants. Proteobacteria and Actinobacteria are widely known for their functional role in soil, including their activities in carbon and nutrients cycling, production of secondary metabolites, degradation of organic matter, phosphorus solubilization, and nitrogen fixation (Hedrich et al., 2011; Aislabie et al., 2013; Eilers et al., 2010; Goldfarb et al., 2011). Proteobacteria classes, Alpha and Gamma, are mainly characterized by r-strategy of growth with high affinity for simple carbon molecules like the sugars released by the roots, confirming their abundance in rich nutrient environments, such as the one present 67 in the rhizosphere (Kersters et al., 2006). On the contrary, Actinobacteria are oligotrophic k-strategists with slow growth rate and high affinity for complex carbon molecules; this and their low nutritional requirement give them the advantage to outcompete with the fast-grower (Jenkins et al., 2009). Also, members of Gemmatimonadetes were often reported in association with vineyard soils and they are considered to be among the top nine common bacterial groups found in soil, representing 2% of soil bacteria diversity (DeBruyn et al., 2011; Janssen., 2006). A complex picture–defining the variation of taxa distribution in vineyards edaphic communities–was depicted by considering the vineyards (Figure 2.5b) and rootstock- scion combinations as variables (Figure 2.5c). For instance, the distribution of phyla in the rhizosphere and bulk soil was significantly influenced by the vineyards’ soils

(PERMANOVAVineyard(Fraction), Nipozzano: F10,60=4.15, p=0.001 and Pomino: F6,52=4.45, p=0.001; pair-wise comparison in Supplementary Table 2.3). For instance, SIMPER revealed that also in this case, the main responsible of the differences observed among vineyards edaphic communities were, first and foremost, Proteobacteria, followed by Acidobacteria and Actinobacteria; these three phyla consistently explain up to 79% of the differences across vineyards edaphic bacterial communities. A similar trend was observed by considering as a variable the rootstock-scion combinations (PERMANOVARootstock- scion(Fraction), Nipozzano: F8,62=4.12, p=0.001 and Pomino: F8,50=4.64, p=0.001; Figure 2.5c; pair-wise comparison in Supplementary Table 2.4). As expected, due to their distribution across vineyards and the dominance of Proteobacteria, Acidobacteria and Actinobacteria in the edaphic communities (both rhizosphere and bulk soil), such phyla were also the main players in determining differences among rootstock-scion groups (Figure 2.6). In particular, Gammaproteobacteria were the main components of 110R-Chardonnay and SO4- Chardonnay, while a lower presence of these bacteria was detected in 110R-Sangiovese and 3309C-Chardonnay. In grapes grafted on the 420A rootstock (i.e., Chardonnay, Merlot and Sangiovese), Gammaproteobacteria shared equally the community relative abundance with Alphaproteobacteria and Actinobacteria. 68

420A-Sangiovese Relative abundance (%) 420A-Chardonnay 60 420A-Merlot 40

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110R-Chardonnay 0 110R-Sangiovese 3309C-Chardonnay

a 6 a a a e li a 4 6 a a a s e a a a e ) ii i l i e i li b p ri ri ri a ci id p -9 xi ri ri t ra ri d i ia % u e e e e u 4 le e e e e e a h b .5 ct ct ct lin Ba ro f ct ct d a ct n p cro ro a a a e ro ro a a a h a o cro g b b b ro ct g KD o b b n b mo le (<0 imi b o o o e b xi l o o sp ri mi d d in e a e h e e ro rs Su t Ba Su fl C t t imo yci b a rmo co e ro An ro ro t u e h Aci a Aci Act p lia ro p p R t ri a l o a Ph cch h rru O e h te l lt T e ct p h e mma Sa V a ca C mma e b Al o D a G o st G d a Aci Bl Figure 2.6. Distribution of the main bacterial taxa across the rhizosphere of the grafted grapes. Heat map with the relative abundance of major bacterial classes (>1% relative abundance) across the rhizosphere of 0 20 40 60 the seven studied rootstock-scion combination. Classes accounting for less than 1% of relative abundance are merged and represented as others.

2.3.5 Taxonomy of the mycobiota associated with the rootstocks’ rhizosphere and the surrounding bulk soil. In the selected Tuscan vineyards, the edaphic fungal communities harbored by rhizosphere and bulk soils comprised ten phyla (Ascomycota, Basidiomycota, Calcarisporiellomycota, Chytridiomycota, Entomophthoromycota, Glomeromycota, Mortierellomycota, Mucoromycota, Olpidiomycota, and Rozellomycota), 32 classes, 92 orders, 179 families and 352 genera (percentage of reads assigned to the different taxonomic ranks in Table 2.7). Ascomycota is the dominant phylum and it was mainly represented by Sordariomycetes (46%), Dothideomycetes (13%), Eurotiomycetes (8%), Leotiomycetes (4%), Pezizomycetes (4%), and unidentified Ascomycota (4%). An overall depletion of this phylum was observed in the rhizosphere of both Nipozzano and Pomino areas (average, 73 and 84% in the rhizosphere and bulk soil, respectively; Figure 2.7a). However, this trend was ascribable only to certain members of Ascomycota, in the classes Sordariomycetes, Dothideomycetes, and Pezizomycetes; only minor classes of Ascomycota (i.e., Eurotiomycetes and Leotiomycetes) were enriched in the rhizosphere, resulting in the observed trend. Notably, all the other main phyla, including Basidiomycota (Agaricomycetes), Mortierellomycota (Mortierellomycetes), and Mucoromycota (Mucoromycetes), along 69 with the others low abundance phyla (<1% of relative abundance, six phyla and unclassified fungi) showed higher relative abundance in the rhizosphere. Interestingly, SIMPER analysis depicted Ascomycota, Basidiomycota and Mortierellomycota as the phyla responsible of 98% of the differences among rhizosphere and bulk soil fungal communities. The dominance of Ascomycota and Basidiomycota in soil is expected (Lim et al., 2010; Anderson et al., 2003; O'Brien et al., 2005). Fungal members of these two phyla are the main responsible of organic matter decomposition, particularly in agricultural soil (Ma et al., 2013; Frąc et al., 2018). Both Ascomycota and Basidiomycota secrete a wide variety of complex extracellular enzymes which aid in the organic matter decomposition process (Osono and Takeda., 2006; Eichlerová et al., 2015). Among these, Basidiomycota are particularly suited to degrade the aromatic lignin polymers present in the litter of woody plants, making them the fastest decomposing fungi (Osono and Takeda., 2006; Manici et al., 2017). These fungi are not only involved in organic matter decomposition, but also in the solubilization of minerals and the release of polysaccharides, possibly supporting the plant for water storage in the rhizosphere (Jin et al., 2019). They also present antioxidant and antimicrobial capacities, presumably involved in regulating the microbial communities’ activity and dynamics in soil (Osińska-Jaroszuk et al., 2015). 70

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Figure 2.7. Taxonomic diversity of fungal communities associated with grapevine rhizosphere and vineyards bulk soils. (a) Comparison of fungal communities associated with rhizosphere and surrounding bulk soil in Nipozzano and Pomino vineyards. Relative abundance of different fungal phyla is reported in percentage. Relative abundance of different fungal phyla is also visualized in the rhizosphere and bulk soil fraction across (b) the ten vineyards selected (6 in Nipozzano and 4 in Pomino) and (c) the seven rootstock- scion combinations (2 in Nipozzano, 2 in Pomino and 3 shared among the two areas). Phyla representing less than 1% of the total reads are denoted as ‘Others’.

Soil physicochemical properties, local bio-geographical factors and vineyard management procedures do not only affect the composition bacterial community associated with grape rhizosphere (Table 2.6 and Figure 2.5), but also influence the assembly of the community 71

fungal component along the lifespan of grapevine plants (Berlanas et al., 2019; Varanda et al., 2016; Steenwerth et al., 2008; Martínez-Diz et al., 2019; Corneo et al., 2013; Pancher et al., 2012; Deyett and Rolshausen, 2020). In my study, the analysis of the edaphic mycobiota associated with the rhizosphere and bulk soil along the different vineyards confirmed the role of soil in shaping the community structure and composition

(PERMANOVAVineyard(Fraction), Nipozzano: F10,60=2.51, p=0.003 and Pomino: F6,52=2.27, p=0.043). In particular, data showed that bulk soils harbored different fungal communities only in few cases (pair-wise comparison in Supplementary Table 2.5), showing a more homogeneous pattern of fungal phyla distribution, while in the rhizosphere–where root system exerts strong selective pressure–the fungal distribution appeared more heterogenous with specific fungal association in both Pomino (F5,30=4.15, p=0.001) and Nipozzano (F5,30=4.52, p=0.001; Figure 2.7b; Supplementary Table 2.5). Also in this case, the dissimilarity among vineyards fungal communities (both from rhizosphere and bulks oil) was mainly ascribable to Ascomycota, Basidiomycota and Mortierellomycota (contribution to dissimilarity, 95-98%). Among the main drivers in shaping root system associated fungi, also plant genotype plays a key role (Jiang et al., 2017). Plant genotype affects root metabolism, immune system functioning and root exudate composition, which in turn influence the activity and structure of the root microbiome. Even small changes in host genotype have an effect on the microbiome structure, with possible impacts on plant health (Haney et al., 2015). Despite the effect of host genotype on the composition of plant microbial communities was smaller than the one of soil type (Table 2.6), it still resulted an important driver of microbial community in vineyards (e.g., Marasco et al., 2018) and other agricultural systems (Philippot et al., 2013). The results proposed here reveal a host-genotype- dependent assembly of the rhizosphere mycobiota according to the grape rootstock and rootstock-scion combination, accounting 13 and 32%, respectively, of the total observed variance (Table 2.6 and Figure 2.4). There is a variety of possible rootstock-scion combinations that are supposed to affect grape quality and productivity (Habran et al., 2016; Table 2.4), as well as the recruitment of the plant associated fungal community. 72

While bulk soils were not affected by this factor (Nipozzano: F4,31=1.87, p=0.051 and

Pomino: F4,25=1.55, p=0.146), the rhizosphere were significantly and strongly impacted by rootstock-scion combination (Nipozzano: F4,31=3.81, p=0.001 and Pomino: F4,25=3.85, p=0.001; pair-wise comparison in Supplementary Table 2.6), with 60 and 70% of pair-wise comparisons with significant p-values (p<0.05) in both Pomino and Nipozzano (rhizosphere in Supplementary Table 2.6). The most evident difference was the enrichment of Mucoromycota (Mucoromycetes; up to 12%) in the 110R-Chardonnay grape grown in the Rena vineyard of Pomino (Figure 2.7c). The presence of this phylum has been only reported in few others studies on vineyards; for example, in the soil and air of vineyards located in Italy (Berruti et al., 2017; Abdelfattah et al., 2019). Members of Mucoromycota are evolutionary very ancient fungi known for their association, both as ephyfites and endophytes; their hyphae build complex underground networks that may interact among plants of the same species and with a wide variety of other plants (Berruti et al., 2017; Spatafora et al., 2006). Along with Mucoromycota, also Sordariomycetes, Dothideomycetes and Eurotiomycetes within Ascomycota, Tremellomycetes and Agaricomycetes within Basidiomycota, and Mortierellomycetes within Mortierellomycota, presented a variable distribution (i.e., relative abundance) across rootstock-scion combinations (Figure 2.8). All these fungi are involved in organic matter decomposition, soil aggregation and nutrient availability (Lehmann et al., 2020).

420A-Sangiovese Relative abundance (%) 420A-Chardonnay 50 420A-Merlot 30 SO4-Chardonnay 10 110R-Chardonnay 110R-Sangiovese 3309C-Chardonnay

i s s s s s s s s s g te te te te te te te te te n % e e e e e e e e e u 1 c c c c c c c c c F < y y y y y y y y y . rs m m m m m m m m m c e o o o o o o o o o n h c e ti ti ll r z ri ll U t ri d o o e o i a e O a i r e r c z d g th u L ie u e r m A o E rt M P o re D o S T M

Figure 2.8. Distribution of the main fungal taxa across the rhizospheres of the grafted grapes. Heat map with the relative abundance of major fungal classes (>1% relative abundance) across the rhizospheres of 73

the seven studied rootstock-scion combinations. Classes accounting for less than 1% of relative abundance are merged and denoted as ‘others’.

2.3.6 Shared microbiome and rootstock-scion specific microbial assemblages. As described by Bulgarelli and colleagues (2013), the microbiota diversification process begins in the rhizosphere, where root exudates drive the recruitment of microorganisms that inhabit the surrounding bulk soil, recently defined as reservoir of microbial diversity for the recruitment by plant root system (Gopal and Gupta., 2016). In this study, the rhizosphere of grafted grapevine plants actively recruited microorganisms from the surrounding soil to establish a complex microbiome largely composed of bacteria of the Proteobacteria, Actinobacteria, Acidobacteria, Bacteroidetes and Cloroflexi, (Figure 2.5) and fungi of the Ascomycota, Basidiomycota, Mortierellomycota and Mucoromycota phyla (Figure 2.7). As previously discussed, the host genotype is an important factor in determining the profile of a subset of bacterial and fungal members that are distributed in the rhizosphere of the different rootstocks-scion combinations (i.e., explaining 29 and 32% of total variance in bacterial and fungal rhizospheric communities, respectively; Table 2.6). Such repartition of OTUs among the microbial communities associated with the seven rootstocks-scion combinations was evident for both bacteria and fungi: the rhizosphere microbial communities showed (i) specific OTUs, typical of each rootstock- scion combination, and (ii) a cluster of shared OTUs, which were always present (Table

2.8). Table 2.8. Shared and specific bacterial and fungal OTUs detected across rhizosphere microbial communities associated with the seven rootstock-scion combinations.

Rootstock-scion combination Bacteria Fungi in Tuscan vineyards Rel. abundance (%) OTUs (%) Rel. abundance (%) OTUs (%) 420A-Sangiovese 0.0033 0.32 0.145 2.10 420A-Chardonnay 0.0250 0.56 0.099 1.90 420A-Merlot 0.0092 0.60 0.099 1.42 SO4-Chardonnay 0.0003 0.09 0.004 0.20 110R-Chardonnay 0.0002 0.04 0.001 0.07 110R-Sangiovese 0.0001 0.04 0 0.00 3309C-Chardonnay 0.0005 0.13 0.006 0.20 Shared among all 85.8 31.5 78.2 20.5 Partially shared 14.1 66.7 21.5 73.6 Total numbers in rhizosphere 1,845,758 5338 7,439,960 1475.00 74

For instance, 31.5% and 20.5% of bacterial and fungal OTUs (counting 85.8% and 78.2% of the relative abundance), respectively, were shared among all the rootstock-scion combinations Table 2.8. As expected, these OTUs belong to the main detected phyla, including Proteobacteria (36% Gammaproteobacteria, 25% Alphaproteobacteria, and 3% Deltaproteobacteria), Actinobacteria (16%), Acidobacteria (7.5%), Bacteroidetes (5%), Chloroflexi (3.5%), and Verrucomicrobia (2%). Despite these OTUs were always present, their distribution varied in the rhizospheres influenced by the different rootstock-scion combinations. As showed by the analysis of the rootstock-scion core microbiome (Figure 2.9a), the dominant genera Pseudomonas (21.5%), Spingomonas (7.5%), Enterobacter/Serratia (3.5%), Rhizobium and Streptomyces (1.5% each) had a peculiar distribution in term of abundance across the different rootstock-scion combinations, confirming the diversity among the recruitment process exerted by the plants with different graft combinations. 75

y y y y y a y y y a se a a a n se se a a a n se n n n n n n n n ve n n n o ve ve n n n o ve io o t o o rd io io o t o o rd io g rd o rd rd a g g rd o rd rd a g n a rl a a h n b n a rl a a h n a h h h h h -C h -C -C C -Sa -C C -Sa A-Sa A-C A-Me -C R 9 R A-Sa A-C A-Me -C R 9 R 0 0 0 4 0 0 0 0 0 0 4 0 0 0 2 2 2 1 3 1 2 2 2 3 4 4 4 SO 1 3 1 4 4 4 SO 11 3 11

Pseudomonas Mortierellaceae Sphingomonas Nectriaceae RB41 Enterobacter Mucoraceae Rhizobium Piskurozymaceae Serratia Pleosporaceae Streptomyces Nocardioides Chaetomiaceae Steroidobacter Aspergillaceae Flavobacterium Bionectriaceae e Bradyrhizobium Ceratobasidiaceae Skermanella e m Mycobacterium Herpotrichiellaceae

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C Acidibacter Lentitheciaceae Terrimonas Sporormiaceae Lysobacter Reyranella Bartaliniaceae Niastella Psathyrellaceae Pedobacter Rhynchogastremataceae Variovorax Bryobacter Bulleribasidiaceae Comamonas Stachybotryaceae Nordella Botryosphaeriaceae Lechevalieria Gaiella Lycoperdaceae Microvirga Clavicipitaceae Candidatus Xiphinematobacter Hyaloscyphaceae Candidatus Udaeobacter Sebacinaceae Actinoplanes Others (av. <0.1%, 184 genera) Others (<0.1%, 31 Families) Unclussified Genera Unclassified Genera Relative abundance-log Relative abundance-log transformed transformed 0 0.5 1.0 1.5 0 0.5 1.0 1.5

Figure 2.9. Distribution of the core microbial taxa across the rhizosphere of grapevine plants with different graft combinations. Heat map showing the relative abundance of bacterial and fungal genera shared among the rhizosphere of the different rootstock-scion combinations. Values are expressed as log- transformed data of relative abundance. Taxa with average relative abundance <0.1% are cluster together under the group ‘Others’. 76

Similarly, dominant fungi, such as Ascomycota (46.7% Sordariomycetes, Dothideomycetes 12%, Eurotiomycetes 6.5%, Leotiomycetes 3%), Basidiomycota (Agaricomycetes 4% and Tremellomycetes 5.5%), Mortierellomycota (Mortierellomycetes 13%), and Mucoromycota (Mucoromycetes 3%), were the components of the core microbiome. As expected, also in the case of fungi, a differential distribution of core members across rootstock-scion combinations was detected, confirming the complexity of the rhizosphere communities and their assembly. As reported in Figure 2.9b, the most abundant families in the fungal core microbiome were Mortierellaceae, Nectriaceae, Mucoraceae, Piskurozymaceae, Pleosporaceae, Chaetomiaceae, Aspergillaceae, and Bionectriaceae that all together represent 40% of the relative abundance. The analysis was performed at the family level because more detailed taxonomic information was available compared to the genus level (Table 2.7); notably, 42% of the rhizosphere reads were not classified at family level. A similar trend with higher values was found by computing the rootstock- scion core microbiome separately for the two geographical areas (relative abundance of shared OTUs in rhizosphere: Pomino, 94% of bacteria and 82% of fungi, and Nipozzano, 96% of bacteria and 85% of fungi), indicating that the microbial communities selected by the different rootstock-scion combinations differed mainly for the relative distribution of the taxa within the community (i.e., structure) than for their composition (taxa present). Similar observations were obtained by the analysis of fungal and bacterial rhizosphere microbiome associated with five grapevine rootstock genotypes in mature and young plants cultivated in vineyards located in two regions of Spain (Berlanas et al., 2019); many bacterial (82.9%) and fungal (58.7%) species were found in all rootstocks, demonstrating the existence of a “core” grape microbiome that is independent of the rootstock genotype and growing region. Analogously, Marasco et al., (2018) showed that four grafted- rootstocks and ungrafted Barbera grape plants grown in north Italy (Oltrepò Pavese region) had 76 and 74% of root bacterial OTUs in common, respectively in the endosphere and the rhizosphere. Such “core” rootstock microbiomes were dominated by Pseudomonas, Enterobacteriaceae, Actinomycetales and Rhizobiaceae in the root tissues, while Actinomycetales, Sphingomonadales Rhizobiales, Pseudomonas, 77

Enterobacteriaceae and Chloroflexi in the rhizosphere. Notably, both studies reported have been conducted considering as variable the rootstock, all plants exanimated were grafted with the same scion (Tempranillo and Barbera cultivars in Marasco et al., 2018 and Berlanas et al., 2019, respectively). Besides a shared microbiome, grape rootstocks present a rootstock-specific portion of the community (Marasco et al., 2018; Berlanas et al., 2019; D’Amico et al., 2018). It can vary based on the study and the genotype of the rootstocks analyzed. From my datasets, the different rootstock-scion combinations selected specific-OTUs, accounting for 2% and 6% of the bacterial and fungal OTUs, respectively (OTUs with less than 1% of relative abundance in both cases). Looking in detail, it was possible to observe that the rootstock- scion combinations with 420A have more microbial signatures than the others. Taxonomic analysis showed that Acidobacteriia Subgroup 2, Betaproteobacteriales, Elesterales, Gemmatimonadales, and Saccharimodales were the main families defining the bacterial-signatures for 420A-Chardonnay, while Micromonosporales, Bacteroidetes and Candidatus Woesebacteria the ones for 420A-Sangiovese and Bacillales, Chitinophagales and Sphingobacteriales for 420A-Merlot, along with Azospirillales for 110R-Chardonnay and Candidatus Moranbacteria for 110R-Sangiovese (Figure 2.10). Contrary, Chardonnay scions grafted of 3309C and SO4 did not have unique families associated with, but only specific OTUs belonging to Pedosphaerales, Saccharimonadales, Sphingobacteriales and Betaproteobacteriales. Fungal OTUs specific for the different rootstock-scion combinations showed a similar pattern, in which the combinations with the 420A rootstock had more specific signature OTUs (Table 2.8); in certain cases, the specific taxa belong to the same orders, such as Agaricales, Mortierellales, Orbillales, Sordariales, Spizzemycetales, and Tremellaes among the most abundant (Figure 2.10b). As well, combinations with 420A had specific indicators for each scion: Agaricostilbales, Eurotiales and Xylarliales for Chardonnay, Chaetothyriales and Glomerales for Merlot, and Botryosphaeriales, Cantharellales and Diaporthales for Sangiovese. The other three combinations present few specific fungal OTUs; for instance, 110R-Chardonnay has members of Endogonales, and 3309C- 78

Chardonnay-specific taxa belong to Agaricales and Tremellales, while 110R-Sangiovese did not show any specific fungal taxa (Figure 2.10b). Within both bacterial and fungal communities, these specific OTUs were accompanied by a complex pattern of partially- shared OTUs among the different combinations (i.e., not present in all categories) that accounted for the remaining portion of bacterial and fungal OTUs (66.7 and 73.6%, respectively), confirming the complexity and multiple factors that act during the recruitment process in the rhizosphere of grafted grapes.

y y y y y a y y a se a a a n se se a y a n se n n n n n a n n ve n n n o ve ve n n n o ve b o o t o o rd o a n i i o o o o o a i t o rd i g rd rl rd rd h g g rd o rd rd a g n a a a n n a rl a a h n h h h -C h h h -C -C C -Sa -C C -Sa A-Sa A-C A-Me -C R 9 R A-Sa A-C A-Me -C 9 0 0 0 4 0 0 0 0 0 0 4 R 0 R 2 2 2 1 3 1 2 2 2 0 3 0 4 4 4 SO 1 3 1 4 4 4 SO 11 3 11 Agaricales Acidobacteriales Acidobacteriia Subgroup 2 Agaricostilbales

Anaerolineae SBR1031 Auriculariales Ardenticatenales Botryosphaeriales Azospirillales Cantharellales Bacillales Chaetosphaeriales Bacteroidales Betaproteobacteriales Chaetothyriales Blastocatellales Diaporthales e Blastocatellia 11-24 Endogonales

e

m Blastocatellia DS-100 Eurotiales Candidatus Moranbacteria

o m Geoglossales i Candidatus Woesebacteria Glomerales

o b Chitinophagales i Gomphales Chloroflexales o b Helotiales r Clostridiales o Hypocreales

c Corynebacteriales

r i Cytophagales Microascales

c

Elsterales i Mortierellales

m

- Elusimicrobia unc. Orbiliales l Flavobacteriales m - Paraglomerales

a Gammaproteobacteria unc. l i Peltigerales

r Gemmatales a Gemmatimonadales Pezizales

e g

t Ktedonobacterales Pleosporales

n

c Ktedonobacteria C0119 Saccharomycetales

Longimicrobiales u

a

f Sordariales

scion specific bacteria OTUs bacteria specific scion scion specific fungal OTUs fungal specific scion

Micromonosporales -

b Spizellomycetales -

Myxococcales e Thelephorales Pedosphaerales r e Trechisporales

r

Propionibacteriales o Pyrinomonadales Tremellales

o

Rhodobacterales C Umbelopsidales

C Saccharimonadales Umbelopsidomycetes GS23 Solibacterales Xylariales Sphingobacteriales Xylonomycetes GS24 Thermomicrobiales

Xylonomycetes GS34 Rootstock Vampirovibrionales Rootstock Unclussified Order Unclussified Order Relative abundance-log Relative abundance-log transformed transformed 0 1 2 0 2 4

Figure 2.10. Relative abundance of the rootstock-scion specific microbial taxa across grapevine rhizospheres. Heat map showing the relative abundance of (a) bacterial and (b) fungal OTUs specific for the different rootstock-scion combinations grouped at the order level. Values are expressed as log-transformed data of relative abundance. OTUs that did not show classification at the family level were grouped in the ‘Unclassified Order’ group.

The overall data acknowledge specific relationship between rootstock genotype and rhizosphere microbiota which we speculate may be reflected/explained by slight differences in the plant physiology (Marasco et al., 2018; D’Amico et al., 2018; Berlanas 79 et al., 2019), suggesting the importance of the grafted scion in the process mediating rootstock-microbe interactions. A limited understanding is available on how the physical connections across the graft components (i.e., vascular tissue integration, plasmodesmata formation, and organelles exchanging; Gautier et al., 2018) are formed and what is their effect on the microbiome recruitment by the plant. This limited knowledge has left the question open on which genotype, either the rootstock or scion, has the stronger effect on the selection of the microbial types in the rhizosphere and the assembly of the microbial community (Liu et al., 2018). My results does not provide a definitive answer to this question, but contribute to elucidate that a role exists for each component of the scion-rootstock combinations and the combination itself in the assembly of the rhizosphere microbial communities. These results can be also useful in the light of the proposed strategies for a future improvement of grapevine physiology. In particular, it was recently highlighted the possibility to complement the plant microbiome with specific supplementation of probiotic microbes to the soil, as well as to develop designer communities and microbiome-based breeding to improve crop production (Poudel et al., 2019) that, in the light of my data, should take into consideration the type of rootstock-scion combination in grafted plants.

2.4 Conclusions

I sowed that the variability of microbial communities associated to the rhizosphere of grafted grape plants cultivated in Tuscan vineyards is significantly influenced by the soil type and the rootstock-scion combination. The data collected strengthen the strong influence played by plant (i.e., rhizosphere) in the microbial community assembly; moreover, I showed the unique role of the host genotype of both rootstock and scion in the recruitment and selection of the associated microbiome. My results further revealed the presence of a grape core microbiome, as well as a unique sub-community that is affected by the type of rootstock-scion combination, although the entity of shared and 80 specific taxa is influenced by the edaphic factors. Since the most widespread grapevine rootstock (e.g., among others, the ones used in this work: SO4, 420A, 110R and 3309C) have been selected by breeders for their ability to confer agronomic advantages for grape cultivation (e.g., abiotic stress tolerance and resistance to phytopathogen; Pagliarani et al., 2017), the differences in the microbiome structure and composition observed between the different graft combinations can have important repercussion on the overall metaorganism (plant and microbiome) and its fitness. In fact, it is important to underline that many plant-associated microorganisms, in particular those equipped with PGP properties are able to influence their host in many aspects, such as promoting the growth, protecting from stress, and incrementing fruit production. Thus, understanding the relationship between plant bacterial community and its rootstock-scion mediated selection could provide helpful information to be exploited in viticulture and more in general in agriculture.

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Supplementary Materials (Tables and Figures)

Supplementary Table 2.1. Quality metrics of high-throughput sequencing (MiSeq Illumina) analysis for (a) bacterial and (f) fungal components of the microbial communities associated with grape rhizosphere and vineyards’ soil. a) Reads from bacterial 16S rRNA gene amplification

N. Sample Vineyard Rootstock x Scion Used Unclassified Low abundant Archaea Plastid samples Torta SO4 x Sangiovese 6 254254 3058 11057 134 619 Colle 420A x Chardonnay 6 242440 3178 11336 62 952 Fonte 420A x Merlot 6 231562 2939 9672 102 814 Rena SO4 x Chardonnay 6 152805 2611 8588 46 537 Rena 110R x Chardonnay 6 147447 1010 6920 20 858 Bulk Scopetino 3309C x Chardonnay 6 184700 925 5387 13 772 Castelvecchio 420A x Sangiovese 6 271322 1470 7545 36 408 Sodi 420A x Merlot 6 258572 1648 7063 19 397 Cartellone 420A x Merlot 6 293376 1802 7494 53 1747 Montesodi 110R x Sangiovese 6 220570 1901 6508 33 303 Sodi 420A x Chardonnay 6 1083966 4939 24450 141 1807 Torta SO4 x Sangiovese 6 95050 2435 5785 6 492 Colle 420A x Chardonnay 6 166607 475 5282 10 176 Fonte 420A x Merlot 6 127472 1048 2533 9 96 Arena SO4 x Chardonnay 6 174574 1224 3810 5 240 Arena 110R x Chardonnay 6 120868 580 1782 3 106 Rhizosphere Scopetino 3309C x Chardonnay 6 128488 440 3981 7 169 Castelvecchio 420A x Sangiovese 6 168745 744 3481 7 393 Sodi 420A x Merlot 6 301823 855 6961 34 633 Cartellone 420A x Merlot 6 176659 765 4165 14 246 Montesodi 110R x Sangiovese 6 203611 1009 5639 13 595 Sodi 420A x Chardonnay 6 181861 1487 5265 18 522 b) Reads from fungal ITS2 amplification

N. Sample Vineyard Rootstock x Scion Used Plant/Algae Low abundant Unclassified samples Torta SO4 x Sangiovese 6 33714 4811 1213 305 Colle 420A x Chardonnay 6 22003 274 238 288 Fonte 420A x Merlot 6 34837 411 356 269 Rena SO4 x Chardonnay 6 44082 405 377 222 Rena 110R x Chardonnay 6 30475 93 176 100 Bulk Scopetino 3309C x Chardonnay 6 40786 153 441 160 Castelvecchio 420A x Sangiovese 6 56883 373 592 159 Sodi 420A x Merlot 6 42407 433 861 678 Cartellone 420A x Merlot 6 65582 606 685 624 Montesodi 110R x Sangiovese 6 32869 227 308 132 Sodi 420A x Chardonnay 6 52230 704 995 144 Torta SO4 x Sangiovese 6 663409 3188 7216 2732 Colle 420A x Chardonnay 6 723337 3518 4768 1655 Fonte 420A x Merlot 6 608131 3047 3178 2215 Rena SO4 x Chardonnay 6 734393 2498 2497 1795 Rena 110R x Chardonnay 6 600905 846 1767 2006 Rhizosphere Scopetino 3309C x Chardonnay 6 817305 9622 2484 4092 Castelvecchio 420A x Sangiovese 6 667401 4569 2317 1603 Sodi 420A x Merlot 6 744307 35863 1323 1106 Cartellone 420A x Merlot 6 602517 11578 1525 4729 Montesodi 110R x Sangiovese 6 714350 8457 2133 1319 Sodi 420A x Chardonnay 6 563905 11635 2032 1186

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Supplementary Table 2.2. Number of reads and Goods’ coverage values calculated for each sample, considering both bacteria (16S rRNA) and fungi (ITS2) sequencing. Rhizo, rhizosphere; Goods, Goods’ coverage values.

Bacteria Fungi Bulk Reads Goods Rhizo Reads Goods Bulk Reads Goods Rhizo Reads Goods A01A 46950 98.6 R01 16197 96.1 B01A 8531 99.4 fR01 84160 99.9 A01B 47274 98.5 R02 16509 96.0 B01B 19713 99.7 fR02 113311 100.0 A02A 55786 99.1 R03 17059 96.8 B02A 1792 95.2 fR03 103311 100.0 A02B 42798 98.9 R04 16873 96.4 B02B 962 94.7 fR04 152006 100.0 A03A 27602 97.8 R05 12772 97.5 B03A 1713 96.8 fR05 91832 100.0 A03B 33844 97.9 R06 15640 96.4 B03B 1003 94.0 fR06 118789 100.0 A04A 57666 99.2 R07 24737 97.7 B04A 1234 96.7 fR07 119985 100.0 A04B 29579 98.5 R08 22840 97.2 B04B 3349 98.5 fR08 110662 100.0 A05A 47558 99.1 R09 13940 96.3 B05A 6320 98.9 fR09 119352 100.0 A05B 41103 98.8 R10 31647 98.4 B05B 2773 98.0 fR10 121138 100.0 A06A 30189 98.1 R11 17885 97.1 B06A 6456 99.2 fR11 118225 100.0 A06B 36345 98.5 R12 55558 99.1 B06B 1871 96.2 fR12 133975 100.0 A07A 56672 98.7 R13 21802 97.0 B07A 12407 99.4 fR13 89320 100.0 A07B 35581 97.7 R14 15333 94.9 B07B 2981 98.0 fR14 102782 100.0 A08A 40495 97.7 R15 14773 94.7 B08A 8468 99.1 fR15 81888 99.9 A08B 31949 97.4 R16 25230 97.5 B08B 3306 98.6 fR16 128918 100.0 A09A 27204 97.2 R17 30196 98.2 B09A 3098 98.4 fR17 107380 100.0 A09B 39661 98.0 R18 20138 96.6 B09B 4577 98.6 fR18 97843 100.0 A10A 27555 97.2 R19 24744 96.8 B10A 2250 98.3 fR19 117486 100.0 A10B 20940 96.5 R20 33046 97.8 B10B 2590 98.0 fR20 113585 100.0 A11A 19204 95.7 R21 30359 98.1 B11A 7260 99.0 fR21 115457 100.0 A11B 23653 96.6 R22 32030 98.7 B11B 2939 97.8 fR22 104528 99.9 A12A 28739 97.2 R23 22643 97.1 B12A 4912 99.0 fR23 123202 100.0 A12B 32714 97.6 R24 31752 97.5 B12B 24131 99.7 fR24 160135 100.0 A13A 48052 98.7 R25 26172 97.5 B13A 13406 99.6 fR25 148996 100.0 A13B 24434 97.2 R26 16999 96.6 B13B 2463 98.3 fR26 93739 100.0 A14A 19000 95.8 R27 18651 96.9 B14A 8790 99.2 fR27 110223 100.0 A14B 18140 95.8 R28 22221 96.5 B14B 1987 97.1 fR28 71387 99.9 A15A 19750 96.6 R29 17969 96.9 B15A 2818 98.6 fR29 80622 100.0 A15B 18071 96.4 R30 18856 97.2 B15B 1011 97.3 fR30 95938 99.9 A16A 27133 96.9 R31 22868 96.4 B16A 5414 99.1 fR31 117971 100.0 A16B 34559 97.7 R32 26553 97.2 B16B 3558 98.4 fR32 108430 100.0 A17A 20983 95.9 R33 12806 94.2 B17A 5215 99.1 fR33 149103 100.0 A17B 30704 97.2 R34 16989 94.9 B17B 4109 99.0 fR34 145812 100.0 A18A 23401 96.8 R35 22849 96.3 B18A 13799 99.6 fR35 136361 100.0 A18B 47920 98.4 R36 26423 96.7 B18B 8691 99.4 fR36 159628 100.0 A19A 71526 99.0 R37 27796 97.5 B19A 12103 99.7 fR37 145739 100.0 A19B 51718 98.5 R38 17029 95.7 B19B 15052 99.6 fR38 126216 100.0 A20A 52887 98.6 R39 26945 97.0 B20A 5954 99.0 fR39 101955 100.0 A20B 32134 97.6 R40 27474 97.2 B20B 6504 99.3 fR40 91994 100.0 A21A 31448 97.4 R41 45278 98.7 B21A 12138 99.4 fR41 109101 100.0 A21B 31609 97.6 R42 24223 97.1 B21B 5132 98.9 fR42 92396 100.0 A22A 33231 98.0 R43 46064 98.5 B22A 8135 99.5 fR43 124686 100.0 A22B 38799 98.3 R44 38693 98.1 B22B 4709 99.2 fR44 98876 100.0 A23A 25200 97.5 R45 40374 98.5 B23A 3040 98.8 fR45 132369 100.0 A23B 28967 97.8 R46 53393 98.9 B23B 4942 99.1 fR46 130730 100.0 A24A 48020 98.6 R47 44680 98.5 B24A 17612 99.6 fR47 109486 100.0 A24B 84355 99.3 R48 78619 99.1 B24B 3969 98.8 fR48 148160 100.0 A25A 60115 99.0 R49 27764 97.2 B25A 5244 99.0 fR49 124004 100.0 A25B 46926 98.5 R50 17868 95.6 B25B 9304 99.2 fR50 123672 100.0 A26A 55878 98.8 R51 34574 97.6 B26A 24108 99.8 fR51 110297 100.0 A26B 59329 98.9 R52 28840 97.1 B26B 7562 99.4 fR52 30014 99.9 A27A 51840 98.7 R53 24574 96.9 B27A 18957 99.6 fR53 115214 100.0 A27B 19288 96.7 R54 43039 98.2 B27B 407 94.6 fR54 99316 100.0 A28A 36636 98.4 R55 29623 97.9 B28A 4783 99.2 fR55 102369 100.0 A28B 34743 98.1 R56 34369 97.6 B28B 4690 99.1 fR56 113761 100.0 A29A 32238 97.8 R57 29631 97.6 B29A 2127 98.2 fR57 129076 100.0 A29B 29401 97.5 R58 38843 98.2 B29B 3565 98.9 fR58 100611 100.0 A30A 30852 97.7 R59 34614 98.1 B30A 12591 99.4 fR59 134460 100.0 A30B 56700 98.7 R60 36531 98.2 B30B 5113 99.3 fR60 134073 100.0 A31A 392393 100.0 R61 32704 97.7 B31A 3821 98.7 fR61 76837 100.0 A31B 162677 99.7 R62 32059 97.7 B31B 9016 99.1 fR62 53320 99.9 A32A 64467 99.0 R63 39641 98.0 B32A 18562 99.7 fR63 118774 100.0 A32B 29486 98.2 R64 23384 97.5 B32B 5244 99.2 fR64 102631 100.0 A33A 61953 99.0 R65 31327 98.0 B33A 11559 99.5 fR65 116972 100.0 A33B 88188 99.5 R66 22746 96.6 B33B 4028 98.6 fR66 95371 100.0

92

Supplementary Table 2.3. Pairwise comparison of bacterial phyla distribution in Nipozzano and Pomino vineyards, considering both bulk soil and rhizosphere fractions.

Bulk soil Rhizosphere Nipozzano vineyards t p t P Scopetino, Castelvecchio 1.3993 0.117 0.97511 0.39 Scopetino, Sodi 1.1289 0.281 2.2571 0.011 Scopetino, Cartellone 1.8539 0.028 1.4143 0.108 Scopetino, Montesori 2.0128 0.007 2.0989 0.007 Scopetino, Sodi Remole 2.71 0.008 2.1703 0.009 Castelvecchio, Sodi 1.4502 0.108 2.3715 0.012 Castelvecchio, Cartellone 1.6254 0.062 1.5422 0.082 Castelvecchio, Montesori 1.8143 0.024 1.5447 0.06 Castelvecchio, Sodi Remole 2.2867 0.021 1.8453 0.021 Sodi, Cartellone 1.4992 0.124 2.1799 0.006 Sodi, Montesori 1.7102 0.051 2.8223 0.001 Sodi, Sodi Remole 2.4379 0.016 3.2265 0.002 Cartellone, Montesori 2.4568 0.007 1.6063 0.031 Cartellone, Sodi Remole 1.9028 0.063 1.5083 0.059 Montesori, Sodi Remole 3.0615 0.007 1.2849 0.155

Bulk soil Rhizosphere Pomino vineyards t p t P Torta, Colle 2.6158 0.001 2.6714 0.005 Torta, Fonte 2.115 0.009 1.2335 0.257 Torta, Rena 3.4326 0.001 1.5151 0.112 Colle, Fonte 1.7203 0.045 2.4083 0.012 Colle, Rena 2.5395 0.002 2.701 0.003 Fonte, Rena 2.4465 0.001 0.9550 0.423

Supplementary Table 2.4. Pairwise comparison of bacterial phyla distribution across the seven rootstock-scion combination in Pomino and Nipozzano, considering both bulk soil and rhizosphere fractions.

Bulk soil Rhizosphere Rootstock-scion in Nipozzano t p t P 3309CChardonnay, 420ASangiovese 1.3993 0.117 0.9751 0.409 3309CChardonnay, 420AMerlot 1.2987 0.158 1.7082 0.03 3309CChardonnay, 110RSangiovese 2.0128 0.007 2.0989 0.005 3309CChardonnay, 420AChardonnay 2.71 0.012 2.1703 0.008 420ASangiovese, 420AMerlot 1.3759 0.105 2.0948 0.011 420ASangiovese, 110RSangiovese 1.8143 0.019 1.5447 0.063 420ASangiovese, 420AChardonnay 2.2867 0.021 1.8453 0.024 420AMerlot, 110RSangiovese 1.9014 0.018 2.0269 0.005 420AMerlot, 420AChardonnay 2.5363 0.006 2.2669 0.004 110RSangiovese, 420AChardonnay 3.0615 0.006 1.2849 0.133

Bulk soil Rhizosphere Rootstock-scion in Nipozzano t p t P 420ASangiovese, 420AChardonnay 2.6158 0.002 2.6714 0.004 420ASangiovese, 420AMerlot 2.115 0.004 1.2335 0.206 420ASangiovese, SO4Chardonnay 3.0504 0.001 1.2161 0.219 420ASangiovese, 110RChardonnay 3.7138 0.001 2.1566 0.017 420AChardonnay, 420AMerlot 1.7203 0.039 2.4083 0.004 420AChardonnay, SO4Chardonnay 2.7497 0.002 1.7735 0.055 420AChardonnay, 110RChardonnay 2.415 0.004 4.2396 0.001 420AMerlot, SO4Chardonnay 1.9545 0.013 0.8590 0.524 420AMerlot, 110RChardonnay 2.7672 0.002 1.688 0.054 SO4Chardonnay, 110RChardonnay 2.1052 0.009 1.8546 0.055 93

Supplementary Table 2.5. Pairwise comparison of fungal phyla distribution in Nipozzano and Pomino vineyards, considering both bulk soil and rhizosphere fractions.

Bulk soil Rhizosphere Nipozzano vineyards t p t P Scopetino, Castelvecchio 1.7883 0.039 1.8498 0.04 Scopetino, Sodi 1.212 0.212 1.4282 0.121 Scopetino, Cartellone 1.3891 0.144 1.5859 0.079 Scopetino, Montesori 1.5031 0.114 1.6806 0.061 Scopetino, Sodi Remole 1.0963 0.301 1.8791 0.026 Castelvecchio, Sodi 1.6617 0.048 2.0966 0.014 Castelvecchio, Cartellone 1.0913 0.352 2.13 0.009 Castelvecchio, Montesori 1.903 0.051 2.3768 0.005 Castelvecchio, Sodi Remole 0.8988 0.519 2.9262 0.002 Sodi, Cartellone 1.57 0.079 2.2899 0.003 Sodi, Montesori 1.3416 0.159 2.0789 0.017 Sodi, Sodi Remole 0.8075 0.508 2.9694 0.003 Cartellone, Montesori 1.7619 0.067 2.0132 0.026 Cartellone, Sodi Remole 0.6756 0.655 2.0705 0.013 Montesori, Sodi Remole 1.5218 0.11 1.7426 0.063

Bulk soil Rhizosphere Pomino vineyards t p t P Torta, Colle 0.6074 0.753 2.6246 0.001 Torta, Fonte 0.8305 0.539 1.9951 0.01 Torta, Rena 1.6262 0.078 2.3955 0.002 Colle, Fonte 0.6329 0.802 1.4627 0.094 Colle, Rena 1.829 0.034 1.6625 0.052 Fonte, Rena 1.7014 0.061 1.4397 0.113

Supplementary Table 2.6. Pairwise comparison of fungal phyla distribution across the seven rootstock-scion combination in Pomino and Nipozzano, considering both bulk soil and rhizosphere fractions.

Bulk soil Rhizosphere Rootstock-scion in Nipozzano t p t P 3309CChardonnay, 420ASangiovese 1.7883 0.035 1.8498 0.028 3309CChardonnay, 420AMerlot 0.9608 0.414 1.0896 0.317 3309CChardonnay, 110RSangiovese 1.5031 0.138 1.6806 0.042 3309CChardonnay, 420AChardonnay 1.0963 0.319 1.8791 0.036 420ASangiovese, 420AMerlot 1.273 0.202 1.8684 0.021 420ASangiovese, 110RSangiovese 1.903 0.05 2.3768 0.016 420ASangiovese, 420AChardonnay 0.8988 0.463 2.9262 0.003 420AMerlot, 110RSangiovese 1.7562 0.05 1.524 0.067 420AMerlot, 420AChardonnay 0.2812 0.979 2.433 0.004 110RSangiovese, 420AChardonnay 1.5218 0.108 1.7426 0.064

Bulk soil Rhizosphere Rootstock-scion in Nipozzano t p t P 420ASangiovese, 420AChardonnay 0.6074 0.778 2.6246 0.004 420ASangiovese, 420AMerlot 0.8305 0.517 1.9951 0.016 420ASangiovese, SO4Chardonnay 1.2671 0.19 1.8836 0.028 420ASangiovese, 110RChardonnay 1.449 0.136 2.3661 0.006 420AChardonnay, 420AMerlot 0.6329 0.809 1.4627 0.081 420AChardonnay, SO4Chardonnay 1.5453 0.083 1.3286 0.17 420AChardonnay, 110RChardonnay 1.7254 0.047 2.1969 0.013 420AMerlot, SO4Chardonnay 1.443 0.157 0.9724 0.441 420AMerlot, 110RChardonnay 1.6675 0.059 2.1168 0.024 SO4Chardonnay, 110RChardonnay 0.5471 0.79 1.4955 0.096 94

Supplementary Figure 2.1. Rarefaction curve of bacteria and fungi. Each line represents a sample; bulk and rhizospheric soil samples are indicated in yellow and green, respectively. Due to sequencing issue, only few reads were obtained for the fungal communities of bulk soil samples; after the re-opening of the BCL in KAUST, a new MiSeq run will be performed to obtain enough reads to better describe the fungal diversity of bulk soils.

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THESIS CONCLUSION

Several reports demonstrated that plants have developed a close relationship with their associated microbiome (Sánchez-Cañizares et al., 2017). Plants are able to attract and sustain the associated microbial communities through a process known as rhizodeposition, in which carbon substrates are released by the roots into the surrounding soil (Jacoby et al., 2017; Müller et al., 2016; Bulgarelli et al., 2013). At the same time, the associated microbes can provide important ecological services to the host favoring its fitness and adaptability in natural conditions (Barea et al., 2005; Compant et al., 2019). While the detailed role of these associated-microbes is not thoroughly understood, a large number of them have been characterized as PGP microorganisms (Lugtenberg and Kamilova, 2009; Santoyo et al., 2016; Compant et al., 2010). These microorganisms can facilitate plant growth acting as biofertilizers, biostimulators and/or biocontrol agents (Compant et al., 2019). Particularly, during abiotic stresses, PGP microorganisms can increase stress tolerance in plants (Ullah et al., 2019; Compant et al., 2010). Among all the microorganisms associated to plant, it has been shown that regardless environmental conditions, the hosts are able to recruit and select a “core microbiome” in their endophytic (i.e., root tissues) and rhizospheric compartments (Singh et al., 2019; Jiang et al., 2017; D’Amico et al., 2018; Lareen et al., 2016). The study published by Lundberg et al., (2012) using Arabidopsis thaliana as model plant showed how this recruitment is strongly influenced by the soil type, rather than other variables such as plant’s developmental stage (Chiarini et al., 1998; Schreiter et al., 2014; Nallanchakravarthula et al., 2014). However, despite the taxonomic commonalities found in the associated microbiome of plants of the same species, there are reports suggesting the influence of other factors in the selection of certain microbes, such as the host genotype (Berg and Smalla, 2019; Winston et al., 2014; Bálint et al., 2013). These observations were also confirmed in wild and agriculture ecosystems (Philippot et al., 2013) on other plant species, including arboreal (Marasco et al., 2018a; Zarraonaindia et al., 2015) herbaceous plants (Vale et al., 2005; Marasco et al., 2018b). The interactions 96 between microbial communities and their host plants in the ecosystem are very complex and the regulating mechanisms are not fully elucidated. In order to improve the understanding of the metabolic and ecological potential of each constituent of a microbial community, reductionist approaches have been extensively used. However, the cultivation of each individual associated to plants it is virtually impossible and next generation sequencing technologies with molecular microbial ecology approaches have allowed accurate characterization of these microbes independently from cultivation. In my thesis, I evaluated the microbial communities (bacteria and fungi) associated with bulk soil and rhizosphere of grapevine plants (scion Vitis vinifera, cultivar Merlot, Chardonnay, and Sangiovese) grafted on different rootstocks genotypes (110R, SO4, 3309C, and 420A, which are hybrids derived from other Vitis species, V. berlandieri, V. riparia and V. rupestris) in ten different vineyards located in the areas of Pomino and Nipozzano in Tuscany, Italy. I investigated which factor (area, vineyards, rootstock, scion and rootstock-scion combination) contributes most to the assembly of the rhizospheric microbial community. The results obtained showed that the diversity of the microbial community was significantly conditioned by the geograpical area, and as expected across vineyards, mainly by the different physico-chemical conditions of their soils. I also found that despite differences in the structure of the grape microbial community were driven by known factors, such soil type and geographical location (Praeg et al., 2019; Corneo et al., 2013; Delgado-Baquerizo et al., 2018), I was able to show that the rootstock-scion combination is also an important driver that influence the microbial community assembly in the grape rhizosphere; the rootstock-scion combination factor, analyzed for the first time here, resulted more important than the rootstock and scion taken alone. The use of grafted plant has the aim to make a more robust plant with improved characteristics such as resistance to soil-borne pathogens and diseases, to promote shoot growth, to increase yield and production and tolerance to abiotic stresses (drought, salinity, and temperature), and to improve fruit quality (Lee et al., 2010; Gautier et al., 2019; Melnyk and Meyerowitz., 2015; Goldschmidt., 2014). Even though little information is available on how the connection between the graft components is formed (i.e., vascular 97 tissue integration, plasmodesmata formation, and organelles exchanging; Gautier et al., 2019), I demonstrated in in this thesis work that such combination plays an important role in determining the plant holobiont-associated microbiome, even though it remains to be elucidated the relative weight of each of the genotypes, either the rootstock or the scion, determining the composition of a microbial community. In this contest, the results obtained in my thesis contributes to feed a new prospective of research aimed at understand and elucidate the role and contribute of the combination scion-rootstock in the microbial ecology of the plant holobiont. This is potentially useful for the future improvement of physiology of grapevine and other grafted crops, especially in the recent prospective to develop designer communities and microbiome-based breeding to improve crop production (Poudel et al., 2019).

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