Mycorrhizal colonization of dryland tree establishment depends on soil microbial cooperation

Domain: biology
Published: 2025-12-29
Editorial outcome: minor_revision

Abstract
Mycorrhizal fungi serve as fundamental agents in forest establishment and progression, underpinning critical ecosystem functions through symbiotic root associations. Drylands, which cover nearly half of Earth’s land, have limited forest establishment, and factors influencing mycorrhization in these stressful environments remain unclear. Here, we integrate large-scale field surveys along aridity gradients with greenhouse experiments and over 33,000 microscopic mycorrhizal observations, revealing that aridity significantly enhances mycorrhization. Mycorrhizal fungi undergo niche modification, whereby facilitative microbial interactions promote mycorrhization under aridity stress. We identify a core synthetic microbial community linked to mycorrhization and provide mechanistic evidence that this community facilitates mycorrhization through physical attachment to fungal hyphae and by alleviating soil metabolite inhibition that otherwise suppresses mycorrhization under arid conditions. In this work, our findings highlight the role of microbial interkingdom interactions in driving tree mycorrhizal colonization in arid regions, offering critical insights for guiding tree planting and restoration efforts in drylands.

Introduction
Forest plantations provide significant ecological and economic benefits, including soil conservation, carbon sequestration, and timber production1–3. As a core strategy for landscape restoration, they are integral to the implementation of the United Nations Decade on Ecosystem Restoration (2021–2030)3. Similarly, forest plantations are fundamental for food production in agroecosystems. Unfortunately, the establishment and success of forest plantations is constrained by water scarcity across 41 percent of the global land area; i.e., in drylands4. This challenge is particularly significant in arid and hyper-arid zones, where aridity thresholds critically limit forest ecosystem functions and have led to widespread plantations failures5. Global climate change further intensifies aridification processes, further threatening plantations viability4,6,7. Ectomycorrhizal (ECM) fungi are a key functional microbial community that enhances tree adaptability to aridity by optimizing root water absorption and physiological responses8,9. However, the mechanisms behind the ectomycorrhization of trees in drylands remain virtually unknown10–13, hampering our ability to design adaptive forest management strategies to mitigate aridity threats. Here, we considered two contrasting scenarios. (1) The prevalent harsh conditions in drylands, such as water scarcity, nutrient depletion, and carbon limitation in host trees, directly inhibit mycorrhizal symbiosis establishment14,15. (2) Tree establishment is likely more dependent on mycorrhizal fungi under highly arid and environmentally challenging conditions. In such settings, the soil microbiome can supportively maintain mycorrhizal colonization within these extreme ecosystems.

Advancing our understanding of how to support the establishment and success of forest plantations in drylands is urgently needed. The current lack of knowledge about the mechanisms behind the colonization of roots by mycorrhizal fungi in drylands exists for three main reasons. First, we do not know if mycorrhizal colonization follows an aridity-threshold driven distribution similar to that previously reported for biodiversity and soil function14. Revealing these aridity-shaped patterns and their mechanistic impacts requires comprehensive, cross-scale studies combining field surveys with microcosm experiments. Second, the contribution of the soil microbiome to support mycorrhizal establishment is poorly understood, yet soil microbes are known to undergo critical changes as aridity increases16,17. Mutualistic interactions within the microbiome represent a key ecological process mitigating aridity-induced suppression of mycorrhization18,19 (Fig. 1). Specifically, ECM fungal hyphae provide ecological niches for the soil microbiome, which in turn enhances ECMF hyphal growth and mycorrhization, thereby expanding tree resource acquisition capacity in drylands20,21. Nevertheless, the complexity of microbial interactions and their dynamic interplay with environmental factors constrain our mechanistic understanding of ectomycorrhization in drylands and pose significant challenges for constructing predictive models of mycorrhization22. Finally, we lack an ecological theory capable of explaining the role of the soil microbiome to support mycorrhizal establishment. Notably, the stress gradient hypothesis posits that facilitative microbial associations increase in frequency under stressful conditions23–26. We therefore hypothesize that aridity-shaped facilitative microbial interactions critically determine ectomycorrhization success.

In this work, we combined large-scale field surveys with greenhouse experiments and microscopic observations to evaluate mycorrhizal tree colonization across a wide aridity gradient. To evaluate the changes in ECM colonization with aridity, we conducted a regional survey across 11 poplar cultivation regions in China spanning 1400 km. This transect encompassed a natural aridity gradient (1-Aridity Index), ranging from 0.41 (dry subhumid) to 0.88 (arid; Supplementary Table 1, Fig. S1b). We performed over 33,000 microscopic examinations on 110 root samples, conducting at least 300 examinations per sample until no new ECM morphotypes were observed. We used Populus as our tree model. This tree species is fundamental in natural ecosystems, providing a niche for biodiversity while supporting multiple ecosystem services such as carbon sequestration. Populus is also one of the most commonly planted trees worldwide in restoration processes and in agrosystems to support timber production, playing a fundamental role in local and regional economies. Our sampling encompassed three planted Populus sections in China (Tacamahaca, Leuce, and Aigeiros) to evaluate species-independent aridity effect on ECM colonization. Subsequently, along the soil-ectomycorrhiza continuum, we profiled ECM fungal and bacterial community composition across the aridity gradient, revealing that cross-kingdom associations between ECM fungal and bacterial communities are primary drivers of ectomycorrhization along aridity gradients. We focused on three compartments: (i) bulk soil (reservoir of microbial diversity), (ii) ectomycorrhizosphere (hotspot for fungal-bacterial interactions), and (iii) ectomycorrhiza (functional interface for nutrient exchange), to dissect how aridity shapes microbial interaction in driving ECM colonization. We further generated a synthetic microbial community (SynM) comprising nine key bacteria isolated from the ectomycorrhizosphere as promoters of ectomycorrhization. Finally, using integrated multi-omics and cultivation-dependent approaches27, we elucidated a dual mechanism for SynM-enhanced ectomycorrhization: (i) upregulation of genes involved in butanoate metabolism and DNA replication within ECM fungus, (ii) mitigation of the inhibitory effects of soil metabolites, specifically L-tyrosine and L-phenylalanine, on ECM fungus.

Results
Aridity enhances ectomycorrhizal fungal colonization and diversity
Our analyses revealed that aridity significantly increased ECM colonization. ECM colonization in arid zones (57.01%) was more than double those observed in dry subhumid zones (27.88%) (P<0.05; Tukey-Kramer test; Fig. 2a). This strong aridity response supports the scenario that tree establishment in highly arid environments is more dependent on mycorrhizal fungi and underscore the importance of ECM symbiosis as a key functional trait for tree adaptation to water stress8. Further analysis indicated a nonlinear relationship between colonization and increasing aridity: colonization increased linearly across habitats with aridity values from 0.41 to 0.78 (P<0.01) but plateaued under more severe aridity (P>0.05; Fig. 2b). This aridity threshold (~0.78) aligns closely with previously reported thresholds (~0.8) associated with ecosystem breakdown and minimal plant photosynthesis14,28. Therefore, the stability of ECM colonization beyond this threshold suggests compensatory ecological processes (e.g., microbial interactions) may sustain mycorrhization within the observed aridity range.

Aridity also significantly elevated ECM fungal alpha diversity, measured both within the ectomycorrhizosphere and on the ECM root tips themselves (ectomycorrhiza) (P<0.01; Fig. 2c). In the ectomycorrhizosphere, diversity increased by 242.12% in arid zones and 40.43% in semi-arid zones relative to dry subhumid zones (Tukey-Kramer, P<0.05; Fig. S3a). A similar aridity-driven diversity increase was observed in the ectomycorrhiza (P<0.01; Fig. S3a). These findings are consistent with our microscopic examinations, which found more ectomycorrhiza and greater diversity in arid zones. Furthermore, ECM fungal alpha diversity in bulk soil also increased significantly with aridity (P<0.01), indicating their synergistic adaptation across the soil-ectomycorrhiza continuum to environmental stress gradients25. Bulk soil likely acts as a persistent reservoir of ECM fungal propagules (e.g., spores, hyphal fragments)29,30, potentially hosting a greater diversity of aridity-adaptive fungal strategies available for symbiosis.

Mycorrhizosphere microbiome determines mycorrhization under intensified aridity
We further demonstrated that the soil microbiome critically regulated mycorrhization in drylands. Our results showed that aridity significantly restructured ECM fungal and bacterial communities, though compartment-specific variation characterized these shifts (bulk soil, ectomycorrhizosphere, ectomycorrhiza; Fig. S4a, c). Notably, the bacterial community in the ectomycorrhizosphere displayed pronounced sensitivity to aridity, evidenced by its strongest correlation with aridity for alpha diversity (R²=0.40, P<0.01; Fig. 2c, d) and community similarity (Mantel r = −0.39, P<0.01; Fig. 2e, f) relative to other compartments. This aridity-driven differentiation further amplified dissimilarity between ectomycorrhizosphere and bulk soil bacterial communities, peaking above an aridity value of 0.7 (Fig. S5). Collectively, our findings demonstrate progressive niche contraction for bacteria under increasing aridity, wherein the ectomycorrhizosphere constitutes a critical interface of available plant habitat, thereby fostering a bacterial community distinct from bulk soil31.

Next, to characterize the driving force of microbiome along the aridity gradient, we employed cohesion metrics to quantify potentially cooperative and competitive interactions between ECM fungi and bacteria. We found that in the ectomycorrhizosphere, aridity specifically enhanced cooperative interactions while suppressing competitive ones (Figs. 3a and S6). In contrast, in bulk soil and ectomycorrhiza, aridity exerted only minor effects on microbial interactions. Specifically, in the ectomycorrhizosphere, positive cohesion in arid zones was 1.37-fold and 2.42-fold higher than in semi-arid and dry subhumid zones, respectively (Fig. 3a). In this compartment, ECM fungal hyphal metabolites provide carbon sources supporting certain microorganisms, mitigating the lethal effect of water limitation under increasing aridity20,21. This aligns with the Stress Gradient Hypothesis, indicating that microbial cooperation is an important strategy for mycorrhizal adaptation to aridity24,32,33. Critically, the ectomycorrhizosphere exhibited the strongest association between positive cohesion and aridity (R²=0.54, P< 0.001) compared with bulk soil (R²=0.08, P< 0.01) and ectomycorrhiza (R²=0.01, P> 0.05; Fig. 3a), confirming its status as the primary interface for aridity-driven microbial cooperation.

We further evaluated the contributions of ECM fungal and bacterial community characteristics and their cross-kingdom interactions to ECM colonization using random forest (RFM) and generalized additive model (GAM). The bacterial community in the ectomycorrhizosphere dominated ECM colonization, with positive ECMF-bacterial cohesion emerging as the most influential factor (% IncMSE=13.55, P<0.05), followed by bacterial community composition (PCoA1) and alpha diversity (P<0.05; Fig. 3b). Partial least squares regression confirmed a significant positive correlation between positive ECMF-bacterial cohesion and colonization in the ectomycorrhizosphere (R²=0.22; Fig. S7a). This direct evidence supports our hypothesis that prolonged aridity drives ECM fungal niche optimization, promoting bacteria-ECMF cooperative assemblies to underpin mycorrhization. This represents a coevolutionary outcome of tripartite (bacteria-ECMF-host tree) systems responding to environmental stress. GAM analysis incorporating the six RFM-significant variables (total R2=0.65) strengthened these findings, with ectomycorrhizosphere bacteria explaining 34% of colonization variance (Fig. S7b). Although the identities of ECMF exhibit variable root colonization capacity34,35, RFM detected no direct contribution from ECM fungal community characteristics (Fig. 3b). This limited explanatory power of ECM fungi underscore the primacy of niche adjustment in driving ECM colonization under intensified aridity. Collectively, these findings suggest that under increasing aridity, tree mycorrhization depends on ectomycorrhizosphere microbiome, specifically on facilitative cross-kingdom interactions as pivotal drivers31. This underscores the necessity of prioritizing the dynamics of microbial interactions in predictive models of plant mycorrhization under conditions of global aridification.

The bacteriome of ectomycorrhizal colonization
We hypothesized that bacteria enriched specifically under high aridity contribute to ECM colonization. We then aimed to further understand the bacterial communities associated with mycorrhizal colonization. To such an end, we identified key ectomycorrhizosphere bacterial taxa for ECM colonization. We first detected 619 bacterial ASVs significantly enriched in the ectomycorrhizosphere compared to bulk soil (Fig. S8a). Subsequently, we employed two complementary analytical methods to identify key bacterial taxa. The first method utilized microbial interaction patterns. Given the importance of positive ECMF-bacterial interactions for ECM colonization (Fig. 3a), we calculated the positive connectedness (defined as the mean of significant positive correlations between each bacterial ASV and the ECMF ASV based on SparCC networks) and assessed the correlation of bacterial ASVs with ECM colonization. This approach identified 145 ASVs (Fig. 3c), indicating their potential to promote ectomycorrhization through positive interactions with ECM fungi. To further validate these candidates under high aridity, we quantified two key ecological metrics—occupancy and specificity (see “method section” for details)—in ectomycorrhizosphere samples with aridity >0.7. This additional screening step identified 36 candidate ASVs (Fig. 3d). Among these, 34 ASVs showed significant positive correlations with both ECMF ASVs and colonization (Fig. 3e), defining them as key bacteria that potentially facilitate ECM colonization. This key group represents four bacterial phyla and 19 genera, including Mesorhizobium (4 ASVs), Leifsonia (2 ASVs), and Flavobacterium (2 ASVs; Fig. S9a), demonstrating taxonomic diversity in bacteria supporting ECM colonization.

To obtain these key bacterial isolates, we first confirmed their predominant enrichment in the BJT, LZ, and GL regions through enrichment analysis (Fig. S8b). Subsequently, we isolated and purified bacteria from the ectomycorrhizosphere soil in these regions. A total of 417 bacterial strains were obtained, and after sequence alignment, 172 strains with sequence similarity of less than 98.65% (this measure is now widely used for species demarcation) were retained. Since promoting ECMF hyphae growth is a primary trait of ectomycorrhiza helper bacteria36, all 172 strains were co-cultured with the dominant ECM fungus Tuber from poplar plantations to assess hyphal growth promotion (Fig. S2c, S9a). Twelve bacterial strains (ASVs) that exhibited a negative association with ECM colonization significantly inhibited Tuber growth in vitro. Among these, seven strains were identified as Pseudomonas, and two strains were classified within the Bacillus (Fig. S10). Notably, these ASVs (e.g., Pseudomonas ASV9, B18) were found to be enriched in dry subhumid regions (Fig. S10). This finding corroborates our results (Fig. 3b), suggesting that competitive interactions inhibit ECM colonization in dry subhumid regions. Most importantly, nine key bacterial strains were identified based on sequence matching (≥98.65% similarity) to enriched ASVs and demonstrable growth-promoting abilities (Fig. 3f). Functionally, six of these nine strains significantly enhanced Tuber hyphal growth. Specifically, strain B1 (Flavobacterium, ASV196) showed the strongest promotion (12.34% increase versus control), while B188 (Sphingopyxis, ASV354) and B127 (Chryseobacterium, ASV727) ranked third (9.79%) and eighth (7.11%), respectively, among all isolates (Fig. S9a). These findings validate the rationality and scientific rigor of our methodology for selecting key bacterial taxa.

Experimental evidence on the contribution of bacteria to ECM colonization
We then seek to provide further experimental evidence that bacteria shape mycorrhizal tree colonization in drylands. To test whether key bacteria promote mycorrhization, we constructed a SynM comprising the nine key bacterial strains through bacterial co-culture. Subsequently, we established a pot experiment with four treatments: sterile control, SynM inoculation alone, Tuber inoculation alone (one of the dominant ECM fungi identified in field surveys), and SynM-Tuber co-inoculation. We observed that SynM significantly enhanced ECM colonization. Specifically, although Tuber inoculation alone achieved 18.83% ECM colonization, SynM-Tuber co-inoculation significantly increased colonization to 33.74% (Fig. 4a). This enhancement corresponded with 12.4% and 18.2% increases in poplar height and aboveground biomass, respectively, relative to the control (Fig. 4b–d). This result demonstrates that key bacterial taxa enriched in the ectomycorrhizosphere of trees under aridity conditions effectively promote mycorrhization. Furthermore, SynM inoculation alone showed no effect on tree growth, indicating that SynM facilitates primarily through direct interactions with ECM fungi rather than indirect tree-mediated pathways in this system.

Previous studies have shown that soils contain ECMF-antagonistic metabolites (e.g., phenolics), which inhibit the growth and extension of ECMF hyphae37–39. Here, we tested whether arid soil extracts (SE) suppress mycorrhization and whether key bacteria mitigate this effect. We separately inoculated Tuber alone and co-inoculated SynM with Tuber in poplar pots amended with SE from arid regions (DX and LW, aridity: 0.74–0.87). Indeed, we found that arid SE inhibited ECM formation. SE addition reduced ECM colonization by 27% (P<0.05; Fig. 4a), and decreased poplar height, shoot biomass, and total biomass by 5.44%, 9.78%, and 7.29% respectively, in Tuber-only treatments (Fig. 4b–d). Notably, SynM co-inoculation alleviated this suppression, maintaining ECM colonization and plant growth at non-extract level (P<0.05; Fig. 4a). Several SynM constituents, such as Sphingomonas, Sphingopyxis, and Flavobacterium, are reported to degrade inhibitory organic acids and aromatic compounds40–42. Collectively, these results demonstrate that key bacteria promote ECM colonization and alleviate environmental suppression43.

Bacteria promote ECM growth via butanoate metabolism and DNA replication
We then aimed to understand the contribution of SynM to in vitro ECM fungal growth, and further investigate the mechanisms behind such relationship. To elucidate the mechanism by which key bacteria enhance ECM colonization, we assessed the effect of SynM on Tuber growth using three in vitro co-culture systems: contact coculture, bacterial supernatant, and non-contact coculture (methods detailed in “Methods”; Figs. 5a and S2c, S9a). These methods enable us to clarify the main interaction modes between bacteria and ECM fungi. We also constructed multiple SynMs in parallel as controls, which contained: SynM1 (three non-promoting strains from original SynM), SynM2 (six growth-promoting strains from original SynM), and SynM3 (nine randomly selected strains; Fig. S9a). Our in vitro co-culture systems revealed that direct physical contact (contact coculture) is important for SynM-mediated Tuber growth promotion. SynM showed the highest growth promotion (18.15%) when it contacts with Tuber hyphae (contact co-culture; Fig. 5b), surpassing other co-culture systems. Scanning electron microscopy confirmed bacterial colonization on Tuber hyphae (Fig. 5c), indicating a structural symbiosis. This contact-dependent interaction mode aligns with documented mechanisms for ECM fungal development facilitated by hyphal-colonizing bacteria27,36. Moreover, the rationally designed SynM outperformed all control communities (SynM1/2/3) and individual strains in Tuber growth promotion (Figs. 5a and S9b), confirming its rational design efficacy. Strikingly, removal of non-promoting strains from original SynM (SynM2) reduced the growth promotion by >50% relative to complete SynM (Fig. 5a), revealing functional synergy essential for SynM activity.

Tuber transcriptomics after contact coculture elucidated underlying mechanisms. SynM significantly altered Tuber gene expression, upregulating 937 genes compared to the control (Fig. S11a). KEGG enrichment analysis identified butanoate metabolism as the most enriched pathway, followed by DNA replication (Fig. 5d). The metabolic pathway and heatmap analysis revealed induced expression of genes encoding acetoacetyl-CoA synthetase (AACS), hydroxy methylglutaryl-CoA lyase (HMGCL), 4-aminobutyrate aminotransferase (puuE) and 3-hydroxybutyryl-CoA dehydrogenase (paaH) (Figs. 5e and S11c, d). These genes collectively enhance acetyl-CoA biosynthesis. AACS converts acetoacetate to acetoacetyl-CoA, HMGCL cleaves hydroxymethylglutaryl-CoA to generate acetoacetate, and paaH facilitates the conversion of 3-hydroxybutyryl-CoA to acetoacetyl-CoA. The accumulated acetoacetyl-CoA is further metabolized to acetyl-CoA, a central intermediate that enters the tricarboxylic acid cycle to produce ATP. This energy supply directly supports fungal hyphal growth and biomass accumulation44,45. Concomitantly, upregulation of DNA replication pathways indicates increased cellular proliferation, which is tightly coupled to enhanced energy availability from butanoate metabolism. Collectively, these results introduce a perspective on bacterial-ECM fungal interactions wherein SynM modulates butanoate metabolism and DNA replication pathways to stimulate ECM fungal growth46.

Bacteria facilitate mycorrhization by eliminating soil metabolic constraints
To better understand the mechanism by which key bacteria facilitate ECM colonization through the elimination of soil constraints, we first assessed the impact of SE from arid regions on Tuber growth. SE significantly inhibited Tuber growth, reducing colony diameter by 23.73% versus the control (Fig. 6a). Crucially, pre-cultivating the SE with SynM (SE+SynM) eliminated this suppression, demonstrating bacteria-mediated microenvironmental improvement supporting ECM fungi (Fig. 6a). Metabolic profiling revealed that SynM specifically reduced two aromatic amino acids in SE: L-tyrosine (20.05-fold reduction) and L-phenylalanine (14.01-fold reduction) (Fig. 6b–f). These metabolites involved in various metabolic pathways (Fig. 6d, e), and their accumulation disrupts metabolic homeostasis of fungi43. We propose that SynM members, notably Sphingomonas and Sphingopyxis, likely eliminate the inhibitory by utilizing these aromatic amino acids as carbon and nitrogen sources, thereby optimizing the microenvironment for ECM fungal growth41,47.

Transcriptomic analysis of Tuber in control, SE, and SE+SynM offered further mechanistic insight. 507 genes exhibiting sequential downregulation in SE and recovery in SE+SynM (Fig. 6g). KEGG enrichment of these genes showed their significant roles for glutathione metabolism and arachidonic acid metabolism pathways (Figs. 6h and S12). This transcriptional response indicates that soil extract compromises antioxidant defenses and disrupts membrane integrity through dysregulated arachidonic acid metabolism48,49. SynM effectively counteracted these detrimental effects at the transcriptional level. Collectively, these findings establish that SynM facilitates ECMF colonization by eliminating inhibitory soil metabolites, specifically removing inhibitory aromatic amino acids, thereby alleviating metabolic stress and restoring essential cellular functions for oxidative defense and membrane integrity in the ECM fungus. This bacteria-mediated soil metabolic change establishes a conducive microenvironment for successful mycorrhization.

Taken together, ECM colonization represents a key adaptive strategy of tree plantation for addressing the intensified aridity stress, characterized by a distinct threshold effect. ECM fungi undergo niche adjustment as aridity intensifies, wherein facilitation of the microbiome supports ECM colonization under aridity stress. Given the ECM fungal diversity, this ecological regulatory strategy exhibits broader applicability for mitigating the negative impacts of global aridity on mycorrhizal systems. Through the construction of a targeted SynM, we mechanistically demonstrated that bacteria facilitate ECM colonization by direct physical attachment to fungal hyphae and by eliminating soil inhibitory metabolites. Our findings elucidate an ecological mechanism sustaining mycorrhization under severe aridity and provide a microbiome-based strategy to enhance plantation resilience against climate change stressors.

Methods
Sitedescriptionandsampling
To investigate how ECM colonization in poplar roots responds to an aridity gradient, we conducted a regional-scale survey spanning 11 poplar cultivation regions (Table S1). These regions were located across a climate gradient from west to east in China, spanning dry subhumid to arid zones, and were distributed along gradients of climatic aridity (ranging from 0.41 [dry subhumid] to 0.88 [arid]; Fig. S1a). Regions were selected based on the five poplar cultivation areas in China, with the westernmost and easternmost sites separated by 1400 km. Geographic coordinates were recorded in the field using handheld GPS receivers (Fig. S1a). Corresponding mean annual temperature (MAT) and mean annual precipitation values (MAP) for each region were obtained from the WorldClim 2 Global Climate Data at a spatial resolution of 30 arc-seconds based on the sampling coordinates. Aridity (1-aridity index) was estimated using the Global Aridity Index dataset (http://www.cgiar-csi.org/data/global-aridity-and-pet-database), higher values denote drier conditions. Further details regarding the 11 regions are provided in Supplementary Table S1.

Sampling was conducted in September 2021 across 11 regions. In each region, 7–13 poplar plantations with minimal recent disturbance were selected as sampling sites, spaced at least 100 m apart to prevent cross-interference between poplar root systems (Table S1). At each sampling site, the sample comprised two to three individual poplar trees, which were pooled to form a single composite sample per site. From each poplar tree, we collected the following compartments in the field: roots and bulk soil. Roots were collected and gently shaken to remove loosely adhering soil. In total, 110 root samples and 110 bulk soil samples were collected from 11 regions. All these samples were placed on ice for transport and processed within 48 h. The 110 bulk soil samples were divided into two subsamples: one was air-dried at room temperature for the determination of soil physicochemical properties; the other was stored at −80°C for subsequent DNA extraction.

Morphotyping and colonization rate measurement
Fine roots (<2 mm diameter) were cut to approximately 2 cm segments (Fig. S2). After carefully removing adhering soil particles that obscured observation using sterile tweezers (flame-sterilized with an alcohol lamp), root tips were examined under a dissecting microscope (10–50× magnification; Nikon SMZ18, Kanagawa, Japan) for the presence of a mantle. Root tips with a mantle were identified as ECM roots. Subsequently, based on morphological distinctions in branching pattern, tip morphology, emanating hyphae, ECM root tips were classified into distinct morphotypes50,51. Per sample, at least ten root tips per ECM morphotype were preserved for molecular analysis; all morphotypes from the same sample were pooled into a single composite sample52, yielding a total of 110 ECM root samples. For rare morphotypes with low abundance, a minimum of two root tips per morphotype was collected in per sample53. No minimum number of root tips per sample was predefined: observations continued until no new morphotypes were detected. Approximately 300~400 root tips were examined per sample, totaling over 33,000 root tips. The number of ECM root tips and total root tips observed per sample was recorded. ECM colonization rate was calculated as: (Number of ECM root tips / Total root tips observed) × 100%. For clarity, the root samples referenced in this manuscript are understood to pertain to ECM samples, unless stated otherwise.

Collection of ectomycorrhizosphere soil samples
Mycorrhizosphere soil was defined as the soil layer adhering to ECM roots with an approximate thickness of ~1 mm54. For its collection, the protocol of He et al55. was followed: ECM roots were transferred to sterile 50-mL centrifuge tubes containing 20 mL of sterile 10 mM phosphate-buffered saline (PBS) and shaken at 120 rpm for 20 min at 4°C56. During shaking, mantle integrity was monitored in real-time, with parameters adjusted if necessary to prevent dislodgement. Subsequently, using sterile tweezers, the ECM root tips were picked out and taken as ectomycorrhiza samples. The remaining suspension was centrifuged (6000×g, 4°C, 20 min) to pellet ectomycorrhizosphere soil. These steps were repeated as needed until sufficient samples were obtained. 110 ectomycorrhizosphere soil samples and 110 ectomycorrhiza samples were collected and stored at −80°C for DNA extraction.

Soil properties
Sieved (<2 mm) soil samples were analyzed for soil properties. Soil pH was measured potentiometrically in a 1:2.5 (w/v) soil-water suspension. Total carbon (TC) and total nitrogen (TN) were quantified by combustion using a vario MICRO cube elemental analyzer (Elementar, Germany). According to China’s Soil Standard protocols for forest regions (LY/T 1232-2015, LY/T 1234-2015, in Chinese), total phosphorus (TP) was determined via alkali fusion-Mo-Sb antispectrophotometric method, and Available phosphorus (AP) was extracted with 0.05 mol·L–1 HCl−0.025 mol·L–1 1/2 H2SO4; Total potassium (K) was determined by flame photometry on a NaOH melt, and available K was measured using 1 mol·L–1 ammonium acetate extraction flame photometry. Nitrate nitrogen (NO₃⁻-N) and ammonium nitrogen (NH₄⁺-N) were measured following the procedures outlined by DeForest (Ohio University, Athens 2009), specific protocol for each assay can be found at https://www.ohio.edu/cas/plant-biology/research/facilities-laboratories/forest-soil-ecology-lab/optimized-lab-protocols. The soil properties for each region are presented in Table S2 (Supplementary material).

DNA extraction, PCR amplification and sequencing
DNA from bulk soil, rhizosphere and ECM root samples was isolated using the FastDNA spin kit for soil (MP Biomedicals, Santa Ana, CA, USA) according to the manufacturer’s instructions. Quality and quantity of the DNA were checked by NanoDrop 5000 spectrophotometer (Thermo Scientific, Wilmington, USA) and gel electrophoresis (BggdsAUTO130). The extracted DNA was amplified using primers targeted to the V5-V7 region of the bacterial 16S rRNA gene (799F-AACMGGATTAGATACCCKG57, 1193R-ACGTCATCCCCACCTTCC58). The fungal internal transcribed spacer region 1 (ITS1 region) of ribosomal RNA was amplified using ITS1F (CTTGGTCATTTAGAGGAAGTAA)59 and ITS2 (GCTGCGTTCTTCATCGATGC) primers60. All PCR reactions were carried out in 25 µL reactions: 5× reaction buffer (5 µL), 5× GC buffer (5 µL), dNTP (2.5 mM, 2 µL), Forward primer (10 μM, 1 µL), Reverse primer (10 μM, 1 µL), DNA Template (2 µL), ddH2O (8.75 µL), DNA Polymerase (Q5, 0.25 µL). The PCR amplification program was as follows: 94°C for 2 min; 30 cycles of 98°C for 15 s, 55°C for 30 s, 72°C for 30 s; and 72°C for 5 min. Following purification with Vazyme VAHTS TM DNA clean beads (Vazyme, Nanjing, China), the PCR products were sequenced on an Illumina MiSeq platform at Shanghai Personal Biotechnology Co., Ltd (Shanghai, China).

Bioinformatic analysis
After sequencing, QIIME2 (open-source, http://qiime2.org) was used to trim (16S rRNA sequences were trimmed to 300 bp length (240 bp for fungi)) and denoise raw data into amplicon sequencing variants (ASVs) via the DADA2 plugin (q2-dada2). ITSx 1.0.11 was used to remove the flanking small ribosomal subunit (SSU) and 5.8S genes, leaving the ITS1 region for further analyses. Taxonomy was assigned using the SILVA database (v138.1) for 16S rRNA gene amplicons and the UNITE database (v9-16.10.2022 release) for ITS amplicons. To reduce bias from variation in sample read numbers, samples were rarefied (the " rrarefy function in the R “vegan” package v2.6-4) to the sample with the lowest read count (15,637 counts for the 16S rRNA gene dataset and 30,712 counts for the ITS dataset). Then, in order to reduce the influence of sparse features and eliminate possible error ASVs, ASVs that exist in only a single sample and have fewer than 10 sequences have been removed.

FungalTraits database61, which includes ECM fungal groups identified later than the publication of FUNGuild, was used to extract the ECM fungal ASVs (EASVs) from fungal ASVs according to “primary lifestyle”, based on genus-level identification, with > 90% sequence similarity. Subsequent analyses of alpha and beta diversities of ECM fungal community were based on the EASVs.

Isolation and identification of ectomycorrhizosphere bacteria
From the ectomycorrhizosphere soil samples (Baijitan, Lanzhou, and Gulang), 417 isolates were successfully cultured. Briefly, 1 g of each fresh ectomycorrhizosphere soil was suspended in 9 mL sterile saline solution (0.9% [w/v] NaCl in ddH2O), and vortexed vigorously for 3 min followed by shaking at 200 rpm for 30 min at 30°C. Three gradient dilutions (10–3, 10–4, 10–5) of soil suspensions were plated on Luria-Bertani agar (LB), Nutrient agar (NA), Tryptic soy agar (TSA) and Reasoner’s 2A agar (R2A) media, then incubated at 30°C in the dark for 2–7 days. Colony development was monitored daily. Distinct colonies were selected based on morphological characteristics and purified through three successive subcultures on NA. All isolates were identified by Sanger sequencing of 16S rRNA genes amplified with the 27F (5’-AGAGTTTGATCCTGGCTCAG-3’) and 1492R (5’-GGTTACCTTGTTACGACTT-3’) primers. The 16S sequences were submitted to NCBI databases for taxonomic identification and homologous sequence similarity. Taxonomic identification employed a 98.65% similarity threshold with > 95% coverage for homologous sequences62. Among all isolates, 172 exhibited sequence similarity below this threshold and were retained for subsequent experiments. Pure cultures were preserved in 30% (v/v) glycerol at −80°C.

Effect of bacteria on ECM fungal growth in vitro
To assess bacterial effects on ECM fungal growth in vitro, 172 isolated strains were co-cultured with Tuber, one of dominant genus identified in the field investigation, according to the methods of Deveau et al63. and Zhao et al64. Bacterial cultures were grown in nutrient broth at 30°C with 180 rpm shaking for 48 h, harvested by centrifugation (5000×g, 5 min), washed thrice with sterile water, and resuspended to OD600 = 1. Tuber cultures were pre-grown on modified Melin-Norkrans agar (MMN, 1:5 dilution) for 72 h. Mycelial plugs (4×4 mm) were transferred to fresh 1/5 MMN plates and inoculated with 25 μL bacterial suspension (treatment) or sterile water (control). Then, parafilm-sealed plates were incubated at 25°C in darkness. Fungal radial growth was measured daily in two perpendicular directions for 4 days. Four biological replicates were performed. To test the significance of growth promotion or inhibition, fungal radial growth between treatment and control groups was determined by exact Wilcoxon rank sum tests (two-sided, P<0.05). Growth-promoting and growth-inhibiting strains were defined as those showing significant stimulation or suppression relative to controls. Percentage growth change was calculated as [(Rtreatment - Rcontrol)/Rcontrol]×100%, where R represents mean radial growth65.

The construction of synthetic microbial communities
To obtain bacterial isolates corresponding to key ectomycorrhizosphere taxa, 16S rRNA gene sequences of 172 isolates were aligned against ASVs identified as the key bacterial isolates using a 97% similarity threshold. Nine strains that best matched nine bacterial ASVs were selected to construct a SynM. We also constructed multiple SynMs in parallel as controls, which contained: SynM1 (Three strains from the original nine with neutral effects on Tuber growth), SynM2 (Six strains from the original nine exhibiting Tuber growth promotion), and SynM3 (Nine randomly selected strains corresponding to ectomycorrhizosphere-enriched ASVs; Fig. S9a). Selected strains were activated on NA for 48 h followed by subculture in liquid NA with a total culture period of 72 h at 30°C. Bacterial suspensions were prepared by centrifuging cultures at 5000×g for 5 min and resuspending pellets in sterile water to OD600 = 1. We mixed equal volumes of suspensions of each single strain to construct a total of above four different SynMs.

Effect of synthetic microbial community on ECM colonization in a pot experiment
To assess SynM effects on ECM formation, a pot experiment was conducted using hybrid poplar (Populus alba × P. glandulosa ‘84K’). Five treatments were applied: T1) Tuber inoculation alone; T2) SynM inoculation alone; T3) co-inoculation with SynM and Tuber; T4) individual inoculation with Tuber after adding soil extract to the substrate; T5) co-inoculation with SynM and Tuber after adding soil extract to the substrate. Each treatment comprised four replicates with three poplars per replicate. The steps are as follows: a tissue-cultured poplar tree was performed in Murashige and Skoog (MS) medium as described in our previous work66, then transplanted into a plastic pot containing autoclaved substrate (profile porous ceramic: vermiculite: peat = 3:1:1 v/v). In treatments T4 and T5, substrates were given 30 mL of pre-prepared soil extract. After five days of acclimation, microbial inoculations were performed. SynM suspensions (10 mL, OD600 = 1) were injected into pots. For Tuber inoculants, we first cultured them in 1/5 MMN liquid medium for 72 h (25°C, 180 r/min) and their hyphae were chopped and blended using a sterile stirrer in a new conical flask. 10 mL of Tuber inoculant was inoculated into the pot using a sterile syringe. Pots were randomized in a greenhouse under 16-h light/8-h dark cycles at 25/20°C day/night temperatures, with sterile water replenishment every 72 h.

After six months, the plant height of each poplar was recorded, and the root and aboveground parts of each poplar were collected for physiological index determination. Firstly, the ECMF colonization rate of the poplar was observed according to our previous method66. In short, the fine roots of poplar trees were carefully washed with sterile water, cut into 2 cm segments, and examined under a microscope. ECM root tips displaying fungal mantles with emanating hyphae were counted across ≥ 100 segments per plant. ECM colonization rates were calculated as described previously. Roots and shoots were oven-dried (80°C, 72 h) for biomass determination.

Effect of synthetic microbial community on ECM fungal growth in vitro
We then tested the effect of synthetic bacteria on the growth of Tuber by three coculture systems: contact coculture (physical contact-dependent interactions), bacterial supernatant (metabolite-mediated interactions), and noncontact coculture (volatile organic compound-mediated interactions; Fig. S2c). These methods enable us to clarify the main interaction modes between bacteria and ECM fungi27. In the contact coculture system, 25 μL SynM suspension was injected concentrically around a 4-mm Tuber mycelial plug on 1/5 MMN agar. In the bacterial supernatant system, sterile supernatant (0.22-μm filtered after centrifugation at 5000×g for 5 min) from 72-h SynM cultures was applied similarly. In the noncontact coculture system: SynM spread on NA (200 μL, 72 h, 25°C); Tuber transferred to fresh 1/5 MMN agar; fungal plate inverted over bacterial plate and sealed with Parafilm67. In this way, Tuber and SynM grow separately in the same space without contact, allowing us to evaluate the impact of volatile organic compounds from SynM on fungal growth. Control groups received equivalent volumes of sterile water to replace SynM (or supernatant). Radial growth of Tuber was measured after incubation for 72 h at 25°C. Experiments were done in triplicate.

Transcriptome sequencing of ECM fungi
To elucidate the molecular mechanisms underlying SynM-mediated promotion of Tuber growth, transcriptome analysis was performed on the control group and the SynM-treated group from the contact coculture system. Three biological replicates were selected per treatment group, yielding a total of six samples. First, Tuber hyphae corresponding to each treatment were collected from the culture medium for RNA extraction. Total RNA was extracted using the Trizol method following grinding in liquid nitrogen. After digestion with DNase I to remove genomic DNA contamination, RNA integrity and purity were assessed by agarose gel electrophoresis and Nanodrop spectrophotometry.

Libraries were constructed using the Illumina Truseq™ RNA Sample Prep Kit. Eukaryotic mRNA containing poly A tails was enriched using magnetic beads coated with oligo (dT). The enriched mRNA was then fragmented by ultrasonication. Using the fragmented mRNA as a template and random oligonucleotides as primers, the first strand of cDNA was synthesized in an M-MuLV Reverse Transcriptase system. Subsequently, the RNA strand was degraded with RNase H, and the second strand of cDNA was synthesized using DNA polymerase I with dNTPs. The purified double-stranded cDNA underwent end repair, A-tailing, and adapter ligation. cDNA fragments approximately 200 bp in size were selected using AMPure XP beads, amplified by PCR, and the PCR products were purified again using AMPure XP beads to obtain the final libraries.

Sequencing was performed on the Illumina platform using the TruSeq SBS Kit (300 cycles). Raw reads were processed with Trimmomatic (http://www.usadellab.org/cms/index.php?page= trimmomatic) to remove low-quality sequences: reads containing >10% ambiguous bases (N), bases at the ends with quality scores <20, adapter sequences, and reads shorter than 75 bp after trimming. Following quality control, high-quality reads were mapped to the previously assembled transcriptome using Trinity (http://trinityrnaseq.sourceforge.net/), which de novo assembled all sequencing fragments into contigs and singletons. The assembled sequences were functionally annotated by aligning them against the NR, Swiss-Prot, eggNOG, KEGG, GO, and CAZy databases. Differentially expressed genes (DEGs) were identified based on the criteria of |log2 (fold change)| ≥ 1 and false discovery rate (FDR) < 0.05. Functional enrichment analysis of DEGs was conducted using the GO and KEGG databases.

In vitro assessment of SynM-mediated soil metabolite modification on ECM fungal growth
To assess the effect of soil metabolites on Tuber growth, soil samples from Dingxi and Lingwu (aridity: 0.74–0.87) were selected for extract preparation. Briefly, 30 g of soil was combined with 90 mL of 80% methanol and agitated at 180 rpm for 3 h. The supernatant was then collected and subjected to rotary evaporation to remove methanol. The precipitate was re-dissolved with 1 mL of methanol under ultrasonic conditions. A 10 mL soil extract solution was prepared by diluting this concentrate with 9 mL sterile water, followed by filtration through a 0.2 μm membrane to remove microorganisms. This procedure was repeated in subsequent experiments. This procedure was repeated for subsequent experiments.

Next, we established three treatments to investigate how SynM modifies soil metabolic components to facilitate the ECMF growth. (1) Soil extract control: 5 mL of soil extract was combined with 15 mL of 1/5 MMN and inoculated with Tuber. (2) soil extract + SynM supernatant: Soil extract was mixed with an equal volume of sterile SynM supernatant. Subsequently, 5 mL of this mixture was combined with 15 mL of 1/5 MMN and inoculated with Tuber. (3) soil extract + SynM: The SynM was inoculated into 20 mL soil extract and incubated at 28°C for 72 h. Following incubation, the culture was centrifuged, and the supernatant was passed through a 0.2 μm filter to remove the bacteria. Then, 5 mL of this treated SE was combined with 15 mL of 1/5 MMN and inoculated with Tuber. In the control group, an equal volume of sterile water was substituted for the soil extract. Radial growth of Tuber was measured after 72 h of incubation in darkness at 25°C.

Transcriptome sequencing of Tuber from Control, Soil extract control, and Soil extract + SynM treatments provided molecular-level insights, following the sampling and sequencing protocols described above in the section titled “Transcriptome sequencing of ECM fungi”.

LC-MS metabolomic analysis of modified soil extracts
To characterize changes in soil metabolite composition induced by the SynM, LC-MS was used to profile metabolites in both original SE and SynM-treated SE. For metabolite extraction, 100 μL of each sample was vortex-mixed with 400 μL of 80% methanol-water solution, incubated on ice for 5 min, and centrifuged at 15,000×g for 20 min at 4°C. A defined volume of the supernatant was diluted to 53% methanol using spectrometry-grade water. This dilution was transferred to a new centrifuge tube and re-centrifuged at 15000×g for 20 min at 4°C. The final supernatant was loaded onto the LC-MS system for analysis (Vanquish UHPLC and Orbitrap Q ExactiveTM HF; Thermo Fisher Scientific, Germany). Chromatographic separation was achieved using a Hypersil Gold column (100×2.1 mm, 1.9 μM) with a flow rate of 0.2 mL/min and a 17-min linear gradient. For the positive ionization mode, mobile phase A consisted of water containing 0.1% formic acid (FA), and mobile phase B was methanol. For negative ionization mode, mobile phase A was 5 mM ammonium acetate (pH 9.0), and mobile phase B was methanol. The solvent gradient program was set as follows: 2% B, 1.5 min; 2-100% B, 12.0 min; 100% B, 14.0 min; 100–2% B, 14.1 min; 2% B, 17 min. The Q ExactiveTM HF mass spectrometer was operated in both positive and negative ionization modes with spray voltage of 3.2 kV, capillary temperature of 320°C, sheath gas flow rate of 40 arbitrary units (arb) and auxiliary gas flow rate of 10 arb.

Statistical analyses
Statistical analyses and data visualization were performed conducted in Origin Pro 2023, R software (v4.0.2; https://www.R-project.org/). Residual normality and variance homogeneity were verified using the Shapiro-Wilk and Levene tests, respectively. Differences in ECM colonization rates were assessed by one-way ANOVA followed by Tukey-Kramer post hoc tests. Alpha diversity indices and beta diversity (weighted UniFrac-based) for bacterial and ECMF communities were calculated with the “vegan” R package (v2.5-2; https://cran.rproject.org/package=vegan). Two-way ANOVA with Tukey-Kramer post hoc testing evaluated alpha diversity variations across compartments and aridity zones. Beta diversity patterns were visualized via principal coordinate analysis (PCoA) and statistically tested using permutational multivariate analysis of variance (PERMANOVA) with the adonis function (vegan). Linear and quadratic relationships of ECMF colonization and microbial diversity along aridity gradients were examined. Model fit was evaluated via Akaike Information Criterion (AIC; lower values indicating better fit68; Table S3). Thresholds were detected when the quadratic regressions fit the data better. We fit segmented regressions using the “segmented” package of R to identify the tipping point where the values abruptly changed along the aridity gradient69, with the tipping point detected as the aridity threshold, as many previous studies28,70. Geographic distances (Km) between sampling sites were calculated from coordinates using the “geosphere” package. Distance-decay relationships for community similarity (1-weighted UniFrac distance) were fitted with ordinary least squares regression, with correlations assessed via Mantel tests.

Microbial cohesion between ECM fungi and bacteria was quantified per sample based on SparCC-constructed interkingdom networks (SparCC |r| > 0.4, P< 0.05)71,72. Positive cohesion (reflecting the strength of positive interkingdom connections) and negative cohesion (indicating negative connectivity) were derived72. Compartmental differences in cohesion were tested with two-way ANOVA and Tukey-Kramer tests. We then employed a linear mixed model (LMM) to assess ECMF-bacterial interaction changes along aridity gradients. RFM identified key predictors of ECMF colonization, with model significance evaluated via “RfUtilities” R package and predictor importance via “RfPermute” R package. A GAM incorporated the six RFM-selected predictors, and compartmental contributions to ECM colonization were quantified by decomposing GAM-adjusted R².

To identify key ectomycorrhizosphere bacterial taxa influencing ECM colonization, bacterial ASVs significantly enriched in the ectomycorrhizosphere (relative to bulk soil) were first detected using DESeq2 (“DESeq2” R package). Subsequently, two complementary approaches identified key taxa. The first method utilized microbial interaction patterns. Positive connectedness (defined as the mean value of significant SparCC-derived positive correlations between bacterial ASVs and ECMF ASVs) was calculated, and correlations between bacterial ASVs and ECM colonization were assessed. Another strategy targeting environmental filtering utilized the finding that bacterial community divergence between the ectomycorrhizosphere and bulk soil peaked at an aridity level >0.7. Ectomycorrhizosphere bacteria specifically enriched under high aridity were hypothesized as ECM colonization contributors. These taxa were characterized by occupancy (the relative frequency of occurrence of species in the samples of habitat) and specificity (the mean abundance of species in the samples of habitat) with both metrics exceeding 0.7 a threshold referenced from methods for identifying specialist species in environments73,74.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In this manuscript, the authors examine poplar-mycorrhizal fungi interactions across soils with different aridity. Importantly, it\nmoves from field studies into mechanistic greenhouse studies using bacterial synthetic microbiota communities to identify\ninterkingdom interactions. While there is significant data to support the findings in the manuscript, there are a couple of\nsuggestions to improve the current manuscript:\n1) In the description of Figure 3, the provide an explanation for why they focus their analysis on bacterial ASVs that\npositively correlate with ECM colonization, but isn't there also useful information that can be gleaned from those that\nnegatively correlate with ECM colonization. Perhaps these strains inhibit colonization under dry subhumid conditions. Do\nany of the negatively correlated bacterial ASVs match to any of the isolates with ECM growth inhibition in Figure S9? \nCompetitive interactions do contribute to the interactions, particularly in soil, as shown in Figure 3b, so this expansion might\nhelp to support these data futher.\n2) In several figures, \"soil\" is mislabeled as \"siol\".\n3) In the description of Figure 5 on line 238, the authors say that contact is \"essential\", but SynM treated samples have\nincreased colony diameter compared to control in the other 2 methods. This data suggests that contact is important, but not\nnecessary.\n4) Does the Figure Legend for Figure 5 have a sentence in it that should have been omitted in this version? In reference to\npart c, should it just be \"c, a bacterial strain.....\", and omit the next sentence \"Volcano map displaying significant differences\ngenes between co-inoculation with the SynM and inoculation Tuber alone...\" ?", "reviewer_2": "This study provides a comprehensive analysis of how aridity enhances ectomycorrhizal colonization in poplar trees through\nmicrobiome-mediated facilitation. By integrating field surveys across a 1,400-km aridity gradient with controlled experiments,\nsynthetic microbial community (SynM) validation, and multi-omics analyses, the authors demonstrate that drought stress\npromotes—rather than suppresses—ectomycorrhizal colonization by fostering cross-kingdom microbial cooperation. The\nwork reveals a novel dual-mechanism model, showing that SynM stimulates fungal growth both through direct physical\nattachment to hyphae and by alleviating soil metabolite inhibition. Rigorously supported by cross-scale data from ecological\nsurveys to molecular validation, this research offers a fundamental advance in understanding plant–microbe–environment\ninteractions under stress, while providing a tangible microbial strategy to enhance dryland forest restoration.\nAlthough the manuscript presents an innovative and compelling narrative, it would benefit from the clarification of several\nissues, along with supplemented methodological details and optimized figure annotations, to enhance its overall rigor and\nreadability.\nMajor Comments:\n1. The identification of key bacterial taxa and the construction of synthetic microbial communities are methodologically\nsound, supported by complementary analytical approaches and validation experiments. However, to ensure full\nreproducibility, additional methodological details should be provided. For instance, the sentence “These taxa were\ncharacterized by occupancy (sample occurrence frequency) and specificity (the average abundance of a given species\nwithin all samples), with both metrics exceeding 0.7” requires clarification—does this refer to a threshold of 0.7% relative\nabundance or a value of 0.7 (70%)? A citation supporting the use of this threshold would also strengthen the methodological\nrationale.\n2. The study effectively explores microbial cross-kingdom interactions across the soil-ectomycorrhiza continuum. However,\nthe Introduction would benefit from a clearer explanation of the ecological significance of the three compartments studied\n(bulk soil, ectomycorrhizosphere, and ectomycorrhiza) to better frame the research focus.\n3. One proposed mechanism—that key bacteria alleviate soil metabolite inhibition of ECM formation in arid soils—is\nintriguing. Introducing relevant background on metabolite-mediated inhibition in the Introduction or citing supporting studies\nin the Discussion would help contextualize this mechanism.\n4. The Introduction clearly outlines the scientific questions and hypotheses. To improve narrative coherence, the Discussion\ncould more explicitly link the results back to these initial questions. This will improve narrative coherence and readability.\n5. Figure 1 currently does not strongly contribute to the paper’s narrative without summarizing the relative mechanisms or\nkey questions in the Introduction. The authors may consider revising it to visually summarize the core findings and proposed\nmechanisms, possibly placing it later in the manuscript, or removing it if it does not add substantial value.\n6. The English is generally clear but requires polishing. Examples include:\nLine 38: “fungi and bacterial interaction” should be “fungal–bacterial interactions.”\n“Symbiosis resilience” should be replaced with “symbiotic resilience.”\nLine 501: Rephrase as “This procedure was repeated for subsequent experiments.”\nInconsistent singular/plural forms (e.g., Lines 103, 260).\nMinor Comments:\nLines 63–64: The logical connection between microbial niches and tree resource acquisition could be strengthened.\nSpecifically, it should be clarified that by providing ecological niches, the fungal hyphae enable microbial communities to\nperform key functions (e.g., nutrient mobilization) that ultimately expand the tree's resource acquisition capacity.\nLines 71–77: The introduction of these two scenarios feels somewhat abrupt. The preceding text hypothesizes how aridity\nshapes facilitative interactions to enhance colonization, but the subsequent scenarios focus on whether aridity reduces or\npromotes mycorrhizal colonization in general, without clearly linking back to the role of microbial interactions. The logical\nconnection seems misaligned. Alternatively, would it be more appropriate to position this part within the first research\nquestion?\nLine 91: Please confirm whether “ectomycorrhizosphere” is an established term or provide a brief definition.\nLine 103: Replace “were” as “was”.\nLine 136: Please provide a citation for the cohesion metrics threshold (|r| > 0.4, P < 0.05).\nLine 169: Correct the typo “ecotomycorrhizal” to “ectomycorrhizal.”\nLine 198: Use “Tuber hyphal growth.”\nLine 207: sterilized substrate?\nLines 250–253: The discussion of how butanoate metabolism promotes fungal growth is currently preliminary. Elaborating\non the underlying biochemical mechanism would significantly deepen the mechanistic narrative of the study.\nLine 260: Correct “facilitates.”\nLine 266: Ensure the order of results description matches the panel order in the figure.\nLine 306: Use numerals consistently (e.g., “the 11 regions”).\nLine 343: The results of soil property measurements are not presented.\nLine 398: Provide a citation for the 98.65% threshold used for 16S rRNA species demarcation.\nLine 412: Ensure the use of italicized P for p-values.\nLines 466–467: Standardize the acronym “SynCom” to “SynM” for consistency.\nLine 557: Specify the number of trees (ntree) and the mtry parameter used in the random forest modeling.\nThe figures are generally informative but would benefit from the following refinements to improve clarity and consistency.\nFigure Order & Consistency: For consistency with the aridity gradient of other figures, please reorder the bars in Figures 2a\nand 3a from left to right as: dry subhumid, semi-arid, arid.\nStatistical Annotations: In Figures 2a, 3a, and 5a, please state whether error bars represent the standard deviation (SD) or\nstandard error (SEM). Furthermore, \"ns\" (not significant) should be defined in the legends of Figures 2b and 3a.\nAxis Labels and Units: Please specify the units for the x-axis in Figure 2c-f (e.g., 1-Aridity Index). Units should also be\nprovided for both axes in Figure 3d.\nTerminology and Clarity: The label \"%IncMSE\" in Figure 3b should be defined in the figure legend. In Figure 5e, the labels\n\"SynM1–3\" are ambiguous—please clarify whether they denote biological replicates or different synthetic community\ntreatments to avoid confusion. In Figure 5a, they denote treatments. Additionally, correct the typo \"siol extract\" to \"soil\nextract\" in Figure 6h.\nFigure Titles: Figure subheadings could be more descriptive. For example, the title of Figure 6 (\"by altering soil\ncomposition?\") could be rephrased more precisely to reflect the specific finding, such as \"by eliminating soil metabolic\nconstraints.\""}, "author_response": "Point by Point Response to Reviewer’s Comments\nReviewer #1 (Remarks to the Author):\nIn this manuscript, the authors examine poplar-mycorrhizal fungi interactions across soils with\ndifferent aridity. Importantly, it moves from field studies into mechanistic greenhouse studies\nusing bacterial synthetic microbiota communities to identify interkingdom interactions. While\nthere is significant data to support the findings in the manuscript, there are a couple of\nsuggestions to improve the current manuscript:\nResponse: Thank you for your positive comments and insightful evaluation.\n1) In the description of Figure 3, the provide an explanation for why they focus their analysis on\nbacterial ASVs that positively correlate with ECM colonization, but isn't there also useful\ninformation that can be gleaned from those that negatively correlate with ECM colonization.\nPerhaps these strains inhibit colonization under dry subhumid conditions. Do any of the\nnegatively correlated bacterial ASVs match to any of the isolates with ECM growth inhibition in\nFigure S9? Competitive interactions do contribute to the interactions, particularly in soil, as\nshown in Figure 3b, so this expansion might help to support these data further.\nResponse: Thank you for your insightful suggestion. Based on your comment, we have expanded\nthe analysis of negatively correlated bacterial ASVs, demonstrating a match with ECM-inhibiting\nisolates in Figure S10 and their biogeographic pattern across three aridity zones. This further\nsupport our conclusion that competitive interactions modulate ECM colonization across aridity\ngradients.\nThe added results in the revised manuscript as below: “Twelve bacterial strains (ASVs) that\nexhibited a negative association with ECM colonization significantly inhibited Tuber growth in\nvitro. Among these, seven strains were identified as the Pseudomonas, and two strains were\nclassified within the Bacillus (Fig. S10). Notably, these ASVs (e.g., Pseudomonas ASV9, B18)\nwere found to be enriched in dry subhumid regions (Fig. S10). This finding corroborates our\nresults (Fig. 3b), suggesting that competitive interactions inhibit ECM colonization in dry\nsubhumid regions.” (Lines 232-237)\n2) In several figures, “soil” is mislabeled as “siol”.\nResponse: We are very sorry for these mistakes. As suggested by the reviewer, we have corrected\nthe typo in Figures 3-5. A full manuscript proofread was conducted to ensure accuracy. (Figures\n3-5)\n3) In the description of Figure 5 on line 238, the authors say that contact is \"essential\", but SynM\ntreated samples have increased colony diameter compared to control in the other 2 methods. This\ndata suggests that contact is important, but not necessary.\nResponse: We thank you for your advice and have revised “essential” to “important” based on\nthe results (hyphal growth in SynM-treated groups under non-contact conditions) and have\nsynchronized the relevant statements in the abstract and discussion to avoid over-extrapolation.\n(Line 289)\n4) Does the Figure Legend for Figure 5 have a sentence in it that should have been omitted in this\nversion? In reference to part c, should it just be \"c, a bacterial strain.....\", and omit the next\nsentence \"Volcano map displaying significant differences genes between co-inoculation with the\nSynM and inoculation Tuber alone...\" ?\nResponse: Thank you for your careful review. We have revised “c, a bacterial strain...” and\ndeleted the redundant sentence as per your suggestion. All figure legends were re-checked to\nensure clarity and brevity. (Figure 5, Lines 944-945)\nReviewer #2 (Remarks to the Author):\nThis study provides a comprehensive analysis of how aridity enhances ectomycorrhizal\ncolonization in poplar trees through microbiome-mediated facilitation. By integrating field\nsurveys across a 1,400-km aridity gradient with controlled experiments, synthetic microbial\ncommunity (SynM) validation, and multi-omics analyses, the authors demonstrate that drought\nstress promotes—rather than suppresses—ectomycorrhizal colonization by fostering cross-\nkingdom microbial cooperation. The work reveals a novel dual-mechanism model, showing that\nSynM stimulates fungal growth both through direct physical attachment to hyphae and by\nalleviating soil metabolite inhibition. Rigorously supported by cross-scale data from ecological\nsurveys to molecular validation, this research offers a fundamental advance in understanding\nplant–microbe–environment interactions under stress, while providing a tangible microbial\nstrategy to enhance dryland forest restoration.\nAlthough the manuscript presents an innovative and compelling narrative, it would benefit from\nthe clarification of several issues, along with supplemented methodological details and optimized\nfigure annotations, to enhance its overall rigor and readability.\nResponse: Thank you for your positive comments and insightful evaluation. In the revised\nmanuscript, we have added the details in the method section and optimized figure annotations.\nMajor Comments:\n1. The identification of key bacterial taxa and the construction of synthetic microbial\ncommunities are methodologically sound, supported by complementary analytical approaches and\nvalidation experiments. However, to ensure full reproducibility, additional methodological details\nshould be provided. For instance, the sentence “These taxa were characterized by occupancy\n(sample occurrence frequency) and specificity (the average abundance of a given species within\nall samples), with both metrics exceeding 0.7” requires clarification—does this refer to a\nthreshold of 0.7% relative abundance or a value of 0.7 (70%)? A citation supporting the use of\nthis threshold would also strengthen the methodological rationale.\nResponse: We appreciate the opportunity to clarify this critical methodological detail. Specificity\nis defined as the mean abundance of species in the samples of habitat; and occupancy is defined\nas the relative frequency of occurrence of species in the samples of habitat. The calculation\nformula is as follows:\nNindividual is the mean number of individual OTU S across all samples of habitat H,\nS,H\nwhile Nindividual is the sum of the mean number of individual S over all habitats; Nsites is\nS S,H\nthe number of samples in H where S is present, while Nsites is the total number of samples in H\nH\n1,2. In the results section (Lines 216-217), we simplified the description of these two parameters\nand added a reference to the method section to maintain the conciseness of the results section and\nguid readers for accessing detailed information.\nIn the statistical analysis chapter of the method section (Lines 686-689), we detailed the\ndefinitions of occupancy and specificity and provided literature support for the threshold of 0.7\nwhich refers to the method for identifying specialist species in environments ensuring the\nreproducibility and scientific rigor of the research method.\n[1] Dufrêne M, Legendre P. Species assemblages and indicator species: the need for a flexible asymmetrical approach.\nEcological monographs 67(3): 345-366 (1997).\n[2] Gweon H S, Bowes M J, Moorhouse H L, et al. Contrasting community assembly processes structure lotic bacteria\nmetacommunities along the river continuum. Environmental microbiology 23(1): 484-498 (2021).\n2. The study effectively explores microbial cross-kingdom interactions across the soil-\nectomycorrhiza continuum. However, the Introduction would benefit from a clearer explanation\nof the ecological significance of the three compartments studied (bulk soil, ectomycorrhizosphere,\nand ectomycorrhiza) to better frame the research focus.\nResponse: The ecological significance of the three compartments is now explicitly stated in the\nIntroduction, framing their roles as microbial reservoir, interaction hotspot, and functional\ninterface. This strengthens the rationale for studying the soil-ectomycorrhiza continuum.\nWe added as follow: “We focused on three compartments: (i) bulk soil (reservoir of\nmicrobial diversity), (ii) ectomycorrhizosphere (hotspot for fungal-bacterial interactions), and (iii)\nectomycorrhiza (functional interface for nutrient exchange), to dissect how aridity shapes\nmicrobial interaction driving ECM colonization.” (Lines 107-111)\n3. One proposed mechanism—that key bacteria alleviate soil metabolite inhibition of ECM\nformation in arid soils—is intriguing. Introducing relevant background on metabolite-mediated\ninhibition in the Introduction or citing supporting studies in the Discussion would help\ncontextualize this mechanism.\nResponse: Thank you for your valuable suggestion to contextualize the metabolite-mediated\ninhibition mechanism of ECM formation. We fully agree that adding relevant background\nenhances the clarity of our proposed mechanism, and we have revised the manuscript accordingly:\n“Previous studies have shown that soils contain ECMF-antagonistic metabolites (e.g., phenolics),\nwhich inhibit the growth and extension of ECMF hyphae37, 38, 39, Here, we tested...”. (Lines 264-\n265)\n4. The Introduction clearly outlines the scientific questions and hypotheses. To improve narrative\ncoherence, the Discussion could more explicitly link the results back to these initial questions.\nThis will improve narrative coherence and readability.\nResponse: Thank you for your insightful suggestion to strengthen the link between results and\nthe initial hypotheses outlined in the Introduction. To enhance narrative coherence, we have made\ntwo key revisions to explicitly connect our findings to the theoretical framework:\n1. We have revised the sentence to directly link the observed aridity-driven increase in ECM\ncolonization to the second scenario proposed in the Introduction: “This strong aridity response\nsupports the scenario that tree establishment in highly arid environments is more dependent on\nmycorrhizal fungi and underscores the importance of ECM symbiosis as a key functional trait for\ntree adaptation to water stress.” (Lines 122-125)\n2. We have added one sentence to anchor the mechanistic findings to our hypothesis：“This\ndirect evidence supports our hypothesis that prolonged aridity drives ECM fungal niche\noptimization, promoting bacteria-ECMF cooperative assemblies to underpin mycorrhization.”\n(Lines 186-188)\nThese changes enhance narrative coherence by grounding results in the initial research\nquestions, ensuring a seamless flow from the Introduction’s theoretical framework to the\nDiscussion’s conclusions.\n5. Figure 1 currently does not strongly contribute to the paper’s narrative without summarizing\nthe relative mechanisms or key questions in the Introduction. The authors may consider revising\nit to visually summarize the core findings and proposed mechanisms, possibly placing it later in\nthe manuscript, or removing it if it does not add substantial value.\nResponse: Thanks for the advice. In the revised manuscript, we have adjusted Figure 1 to better\nhighlight the corresponding scientific issues in the introduction and help readers understand.\n(Figure 1)\n6. The English is generally clear but requires polishing. Examples include:\nLine 38: “fungi and bacterial interaction” should be “fungal–bacterial interactions.”\n“Symbiosis resilience” should be replaced with “symbiotic resilience.”\nLine 501: Rephrase as “This procedure was repeated for subsequent experiments.”\nInconsistent singular/plural forms (e.g., Lines 103, 260).\nResponse: A native English-speaking colleague has polished the manuscript, corrected\ngrammatical errors and improved clarity. Key revisions include standardized terminology and\nconsistent verb tense. (Lines 43, 121, 278, 603-604)\nMinor Comments:\n1. Lines 63–64: The logical connection between microbial niches and tree resource acquisition\ncould be strengthened. Specifically, it should be clarified that by providing ecological niches, the\nfungal hyphae enable microbial communities to perform key functions (e.g., nutrient mobilization)\nthat ultimately expand the tree's resource acquisition capacity.\nResponse: Thank you for your suggestion to strengthen the logical link between microbial niches\nand tree resource acquisition. To address this and focus on the direct support of soil microbiome\nto ECMF, we have revised the relevant sentence to clarify the core mutualistic interaction:\n“Specifically, ECM fungal hyphae provide ecological niches for soil microbiome, which in turn\nenhances ECMF hyphal growth and mycorrhization, thereby expanding tree resource acquisition\ncapacity in drylands.” (Lines 78–80)\n2. Lines 71–77: The introduction of these two scenarios feels somewhat abrupt. The preceding\ntext hypothesizes how aridity shapes facilitative interactions to enhance colonization, but the\nsubsequent scenarios focus on whether aridity reduces or promotes mycorrhizal colonization in\ngeneral, without clearly linking back to the role of microbial interactions. The logical connection\nseems misaligned. Alternatively, would it be more appropriate to position this part within the first\nresearch question?\nResponse: Thank you for your perceptive comment on the logical alignment of the two scenarios\nin the Introduction. We fully endorse your suggestion that this section is more appropriately\npositioned within the first research question. We have relocated the two scenarios from Lines 71-\n77 about “unknown mechanisms of ectomycorrhization in drylands” in the first paragraph of the\nIntroduction. This integration frames the scenarios as testable hypotheses under the first research\nquestion, which focuses on resolving the knowledge gap of dryland mycorrhization mechanisms.\n(Lines 60-66)\n3. Line 91: Please confirm whether “ectomycorrhizosphere” is an established term or provide a\nbrief definition.\nResponse: This term has been used in prior literature [1-3], and we have provided the definition in\nthe Methods section: “Mycorrhizosphere soil was defined as the soil layer adhering to ECM roots\nwith an approximate thickness of ~1 mm.” (Lines 407-408)\n[1] Genney, D.R., Alexander, I.J., Killham, K. et al. (2004), Degradation of the polycyclic aromatic hydrocarbon (PAH)\nfluorene is retarded in a Scots pine ectomycorrhizosphere. New Phytologist, 163: 641-649.\nhttps://doi.org/10.1111/j.1469-8137.2004.01131.x\n[2] Frey-Klett, P., Chavatte, M., Clausse, M.-L., Courrier, S. et al. (2005), Ectomycorrhizal symbiosis affects functional\ndiversity of rhizosphere fluorescent pseudomonads. New Phytologist, 165: 317-328. https://doi.org/10.1111/j.1469-\n8137.2004.01212.x\n[3] Blanco Nouche, C., Cochet, C., Turpault, MP. et al. (2024), Feedback effect of the size of mineral particles on the\nmolecular mechanisms employed by Caballeronia mineralivorans PML1(12) to weather minerals. npj Mater Degrad, 8,\n129. https://doi.org/10.1038/s41529-024-00544-9.\n4. Line 103: Replace “were” as “was”.\nResponse: The word has been replaced. (Line 121)\n5. Line 136: Please provide a citation for the cohesion metrics threshold (|r| > 0.4, P < 0.05).\nResponse: The calculation of cohesion was described in detail in the Methodology section (Lines\n663-664). The parameters in here actually refer to the SparCC-constructed interkingdom\nnetworks. To avoid potential confusion for readers, we have removed the “(|r| > 0.4, P < 0.05)” in\nthe revised manuscript.\n6. Line 169: Correct the typo “ecotomycorrhizal” to “ectomycorrhizal.”\nResponse: Correct; thank you for spotting the typo. (Line 201)\n7. Line 198: Use “Tuber hyphal growth.”\nResponse: We have checked and corrected this. (Line 241)\n8. Line 207: sterilized substrate?\nResponse: Yes, autoclaved substrate (profile porous ceramic : vermiculite : peat = 3:1:1 v/v).\n(Line 527)\n9. Lines 250–253: The discussion of how butanoate metabolism promotes fungal growth is\ncurrently preliminary. Elaborating on the underlying biochemical mechanism would significantly\ndeepen the mechanistic narrative of the study.\nResponse: Thank you for your valuable suggestion. By dissecting the synergistic effects of AACS,\nHMGCL, and paaH, we clarified how these enzymes enhance acetyl-CoA synthesis to fuel the\ntricarboxylic acid cycle and generate ATP. The added content explicitly links the increased energy\nsupply to hyphal growth and DNA replication, further strengthening the mechanistic narrative of\nmicrobial regulation of fungal metabolism:\n“These genes collectively enhance acetyl-CoA biosynthesis. AACS converts acetoacetate to\nacetoacetyl-CoA, HMGCL cleaves hydroxymethylglutaryl-CoA to generate acetoacetate, and\npaaH facilitates the conversion of 3-hydroxybutyryl-CoA to acetoacetyl-CoA. The accumulated\nacetoacetyl-CoA is further metabolized to acetyl-CoA, a central intermediate that enters the\ntricarboxylic acid cycle to produce ATP. This energy supply directly supports fungal hyphal\ngrowth and biomass accumulation43, 44. Concomitantly, upregulation of DNA replication pathways\nindicates increased cellular proliferation, which is tightly coupled to enhanced energy availability\nfrom butanoate metabolism.” (Line 308-316)\n10. Line 260: Correct “facilitates.”\nResponse: Revised. (Line 320)\n11. Line 266: Ensure the order of results description matches the panel order in the figure.\nResponse: The order in the figure has been modified. (Line 329)\n12. Line 306: Use numerals consistently (e.g., “the 11 regions”).\nResponse: The unified numerical expression is “the 11 regions”. (Line 374)\n13. Line 343: The results of soil property measurements are not presented.\nResponse: Soil properties across the aridity gradient are summarized in Table S2.\n(Supplementary Table 2 Soil properties)\n14. Line 398: Provide a citation for the 98.65% threshold used for 16S rRNA species demarcation.\nResponse: Added the reference Kim et al. (2014) [1] to support the 98.65% threshold used for 16S\nrRNA species demarcation. (Line 483)\n[1] Kim M, Oh HS, Park SC. et al. (2014), Towards a taxonomic coherence between average nucleotide identity and\n16S rRNA gene sequence similarity for species demarcation of prokaryotes. Int J Syst Evol Microbiol. 64(Pt 2):346-351.\ndoi: 10.1099/ijs.0.059774-0.\n15. Line 412: Ensure the use of italicized P for p-values.\nResponse: Changed throughout the text. (Line 500)\n16. Lines 466–467: Standardize the acronym “SynCom” to “SynM” for consistency.\nResponse: We now use “SynM” throughout the text for consistency. (Line 561)\n17. Line 557: Specify the number of trees (ntree) and the mtry parameter used in the random\nforest modeling.\nResponse: We used the default parameters in the R package “randomForest”.\n18. The figures are generally informative but would benefit from the following refinements to\nimprove clarity and consistency.\nFigure Order & Consistency: For consistency with the aridity gradient of other figures, please\nreorder the bars in Figures 2a and 3a from left to right as: dry subhumid, semi-arid, arid.\nResponse: Figures 2a/3a reordered to match aridity gradient consistency. (Figures 2a, 3a)\n19. Statistical Annotations: In Figures 2a, 3a, and 5a, please state whether error bars represent the\nstandard deviation (SD) or standard error (SEM). Furthermore, \"ns\" (not significant) should be\ndefined in the legends of Figures 2b and 3a.\nResponse: Error bars defined as SD and ‘ns’ (not significant) clarified in figure legends. (Figures\n2a, 3a, 5a)\n20. Axis Labels and Units: Please specify the units for the x-axis in Figure 2c-f (e.g., 1-Aridity\nIndex). Units should also be provided for both axes in Figure 3d.\nResponse: For Figures 2c-f: We have added an explicit note in the figure legend stating that the\nx-axis unit is “1-aridity index”. For Figure3d: Both axes represent dimensionless parameters.\n(Figures 2c-f, 3d)\n21. Terminology and Clarity: The label \"%IncMSE\" in Figure 3b should be defined in the figure\nlegend. In Figure 5e, the labels \"SynM1–3\" are ambiguous—please clarify whether they denote\nbiological replicates or different synthetic community treatments to avoid confusion. In Figure 5a,\nthey denote treatments. Additionally, correct the typo \"siol extract\" to \"soil extract\" in Figure 6h.\nResponse: Terminology definition for Figure 3b: we have added the explanation in the legend:\n“%IncMSE refers to Percentage Increase in Mean Squared Error” to clarify its statistical\nmeaning. (Figure 3b)\nLabel clarification for Figure 5e: we have added the note in the legend: “SynM(1–3) denote\nthree biological replicates of the SynM treatment group”—consistent with the notation in\nFigure5a where “SynM represents the treatment group” to avoid confusion. (Figure 5e)\nSpelling correction for Figure6h: Revised the typo “siol extract” to “soil extract” in the\nlegend. (Figure 6h)\nAll revisions have been updated in the figure legends and corresponding sections of the\nmanuscript.\n22. Figure Titles: Figure subheadings could be more descriptive. For example, the title of Figure 6\n(\"by altering soil composition?\") could be rephrased more precisely to reflect the specific finding,\nsuch as \"by eliminating soil metabolic constraints.\"\nResponse: As you suggested, the title of Figure 6 has been modified to: “Synthetic microbiota\nfacilitates Tuber growth by eliminating soil metabolic constraints.” (Figure 6)"}]

Decision letter