Turning antagonists into allies: Bacterial-fungal interactions enhance the efficacy of controlling 
The utilization of beneficial bacterial and fungal species in the plant rhizosphere has gradually gained popularity, emerging as a crucial alternative to agrochemicals in controlling soil-borne diseases . In soil ecosystems, bacteria and fungi frequently share microhabitats where they aggregate into dynamic, coevolved communities that play a crucial role in orchestrating the complexities of plant growth and health . Recent studies indicate that the composition and function of these bacterial and fungal communities are influenced not only by the host and environmental cues but also by their interactions within the host niche . These interactions are key drivers of ecosystem functions and are crucial for plant health outcomes . However, the underlying molecular mechanisms, especially bacterial-fungal interactions (BFIs) and their importance for plant health remain poorly understood. BFIs are intricate and dynamic, giving rise to myriad interactions ranging from antagonism to cooperation that can affect the functional ecology of bacteria and fungi regarding growth, reproduction, stress resistance, and pathogenicity . Both bacteria and fungi react differentially depending on the interacting partners and often evolve strategies to use secreted metabolites and overcome the defense mechanisms of competitors . Moreover, the competition for nutrients and niches between bacteria and fungi has led to the development of a vast array of chemical weapons (i.e., antibiotics and volatile compounds) over the millions of years of interactions . On the other hand, the occurrence of antibiotic-resistant genes and the evolution of resistance through mutation or horizontal gene transfer are commonly reported in microbes . Besides, the intra- and intermicrobial interactions can induce the resistance of individual species or communities to antagonistic compounds even in the absence of antibiotic-resistance genes . Both the production of antibiotics and the development of counter-resistance strategies lead to fitness costs in microbes, which reduce their growth and ecosystem functions . This makes plant growth–promoting biocontrol bacterial and fungal strains spend much energy for their survival in highly competitive soil environments rather than developing mutualistic interactions with each other and plants, ultimately causing the failure of their biocontrol capabilities . The energy-consuming antagonistic microbial interactions are so robust that they can shift mutualistic interactions to antagonistic interactions in the human gut microbiome . This mechanism could also be important in soils for the success of plant growth–promoting microbes, especially for bacteria-fungi consortia . As antibiotic resistance evolution due to selection pressure, adaptation, or horizontal gene transfer is commonly found in natural ecosystems , it would be interesting to evaluate whether the reduction or elimination of antagonistic interactions can reverse the process from antagonism to mutualism. Several studies have elucidated transitions from antagonism to mutualism in plant-herbivore interactions . Similarly, the development of cooperative behavior has been reported for seed-borne bacterium, Burkholderia glumae and airborne fungi Fusarium graminearum . Plant antagonist bacterium Pseudomonas protegens evolved into mutualists in the rhizosphere by improved nutrient competitiveness and enhanced tolerance to plant-secreted antimicrobials . However, limited evidence is available regarding the occurrence of interaction changes among soil microbes and their consequences on plant growth and health. Bacillus spp. and Trichoderma spp. are the most widely distributed beneficial microbes in the plant rhizosphere, capable of effectively improving plant growth and preventing disease incidence . Here, we selected these representative strains to investigate the impact of BFIs on plant health. Preliminary results suggested that the synthetic consortium of Bacillus sp. and Trichoderma sp. did not improve Fusarium wilt disease (FWD) control efficiency compared to the application of individual strains. We hypothesized that this lack of difference might be attributed to antagonistic interactions between Bacillus and Trichoderma , and a change in their interaction could potentially affect the ability of consortium to control FWD. To address this hypothesis, we used forward mutagenesis and molecular biology techniques and manipulated Trichoderma ’s resistance to critical antibiotics produced by Bacillus through gene editing. The subsequent improvement in resistance strategy in Trichoderma reduced antibiotic production by Bacillus . It shifted their interactions from antagonism to coexistence, which saved fitness costs and increased the biomass of the individual strains but also led to dynamic changes in the functional dynamics of the rhizosphere microbial community. This shift resulted in forming a more effective barrier against pathogen invasion and achieved higher control efficiency of FWD with the combined application of Bacillus and Trichoderma .   Changes in the antagonistic effect between bacteria and fungi affect the FWD control efficacy The initial in vitro plate assay showed a strong antagonistic effect of Bacillus velezensis ( Bv ) on the growth of wild-type Trichoderma guizhouense ( Tg -WT; fig. S1). To investigate the effect of BFIs change on plant health, we use x-ray radiation to generate distinct Tg mutants, which demonstrated divergent behavior in interactions with Bv compared to Tg -WT . The subsequent evaluation of the mutant’s interaction with Bv revealed that two Tg mutants, Tg -M19 and Tg -M23, displayed higher antagonistic responses to Bv compared to Tg -WT, primarily manifested by a significant increase in the area of inhibition zones. In contrast, the cocultivation of mutants Tg -M15, Tg -M33, Tg -M50, and Tg -M93 with Bv resulted in a significant decrease in the area of inhibition zones, exhibiting a reduced antagonistic effect compared to Tg -WT ( and fig. S1). Tg -M33 was selected to evaluate the impact of reduced antagonistic interaction between Bv and Tg on the control of FWD caused by Fusarium oxysporum f. sp. lycopersici ( FOL ) in a pot experiment. For the in planta assay, six treatments were designed to assess the FWD control efficacy: control without microbes (CK), Bv strain only, Tg -WT strain only, mutant Tg -M33 only, Tg -WT and Bv ( Tg -WT+ Bv ), and a combination of Tg -M33 and Bv ( Tg -M33+ Bv ) . Compared to CK, the application of individual Bv and Tg -WT strains effectively reduced FWD ( P < 0.05, Duncan’s), whereas the control efficacy of Tg -WT+ Bv did not significantly differ from the individual Bv and Tg -WT strains. Notably, the highest FWD control efficiency was determined with Tg -M33+ Bv . Similarly, the abundance of FOL was significantly lower in the Tg -M33+ Bv ( P < 0.05, Duncan’s) compared to Tg -WT+ Bv , individual Bv and Tg strains, and CK . In contrast, the abundance of Bv and Tg -WT in the Tg -M33+ Bv significantly increased ( P < 0.05, Duncan’s) compared to other treatments . These findings implied that BFIs could potentially affect the efficacy of FWD control by influencing the number of beneficial microbes colonizing the rhizosphere. Bacilysin is the major antifungal compound produced by Bv To further elucidate the interaction mechanisms between Bv and Tg , we conducted cocultivation of Bv with both Tg -WT and Tg -M33 and isolated the Bv and Tg strains from the agar plates for transcription analysis (fig. S2A). Transcriptomic profiling of Bv indicated a pronounced enrichment in the biosynthesis of various secondary metabolites pathway when cocultured with Tg -WT and Tg -M33 (fig. S2B). These results suggested that Bv notably modulated the secretion of secondary metabolites during confrontations with different Tg strains, playing a pivotal role in the interaction dynamics. To validate, we introduced the secondary metabolites from the liquid culture broth of Bv into the potato dextrose agar (PDA) medium and evaluated their effect on Tg growth. As anticipated, the growth of Tg was markedly inhibited by the secondary metabolites secreted by Bv , whereas the secondary metabolites produced by Tg showed no notable inhibitory effects on the growth of Bv (fig. S3). Previous studies have highlighted the ability of Bv to synthesize a variety of antifungal metabolites . Leveraging this knowledge, we performed a transcriptomic analysis on the secondary metabolite synthesis genes of Bv during its cocultivation with both Tg -WT and Tg -M33. The results showed significant down-regulation of most genes within the gene cluster responsible for bacilysin synthesis and transport in the Tg -M33+ Bv compared to Tg -WT+ Bv (fold change ≥ 2.0, P < 0.05), whereas no significant differences were noted in the expression of genes related to the synthesis of other antifungal metabolites ( , fig. S4A, and table S1). This suggested that inhibiting bacilysin secretion might potentially reduce the inhibitory effect of Bv on Tg growth, promoting a symbiotic relationship. To further investigate the specific inhibitory role of bacilysin, we evaluated the interactions between Bv mutants and Tg by generating knockout mutants targeting various secondary metabolite gene clusters. Consistent with our initial findings, mutants deficient in the production of bacillomycin (Δ bmy ), surfactin (Δ srf ), fengycin (Δ fen ), difficidin (Δ dfn ), macrolactin (Δ mln ), bacillaene (Δ bae ), and bacillibactin (Δ dhb ) retained their antagonistic effects against Tg -WT. This indicated that these compounds were not the primary contributors to the antagonistic activity against Tg -WT. However, the bacilysin-deficient mutant (Δ bac ) showed a notably reduced antagonistic effect against Tg -WT, further confirming bacilysin as the principal antifungal compound mediating Bv ’s antagonistic activity against Tg -WT . This raised a question: How does Tg -M33 overcome the antagonistic effects of bacilysin to establish a symbiotic interaction with Bv ? Transmembrane transport protein is critical for bacilysin sensitivity in Tg To thoroughly understand the inhibitory effects of bacilysin on Tg growth, we initiated a transcriptomic analysis under confrontational cultivation conditions. The Gene Ontology (GO) annotation results indicated that 16.97% of differentially expressed genes (DEGs; P < 0.001) were enriched in molecular functions related to transmembrane transporter activity and general transporter activity. In the biological process classification, 44.44% of DEGs ( P < 0.001) were found to be involved in transmembrane transport and transport processes. Notably, in the cellular component classification, 100% of DEGs ( P < 0.001) were associated with components such as the intrinsic component of the membrane, integral component of the membrane, and membrane itself (fig. S4B). This suggested that changes in the expression levels of key transmembrane transporter genes in Tg -M33 might modulate its tolerance to bacilysin, thus influencing its interaction with Bv . Subsequently, a comparative analysis was conducted on the expression levels of all identified transmembrane transporter genes between Tg -WT+ Bv and Tg -M33+ Bv , revealing significant expression differences (|fold change| ≥ 1.50, P < 0.05) for nine genes across both treatments. These genes mainly encode multidrug resistance (MDR)–type ABC transporter, major facilitator superfamily (MFS) multidrug transporter, ATP binding cassette (ABC) multidrug transporter, and multidrug and toxic compound extrusion (MATE) family efflux transporter . The transporter genes and their relationship with bacilysin sensitivity were investigated by isolating and purifying bacilysin from the liquid culture broth of Bv , which was subsequently identified using High-performance liquid chromatography–mass spectrometry (HPLC-MS) (fig. S5). Next, deletion mutants of nine genes were generated in Tg -WT through homologous recombination, and all nine mutants displayed normal growth under nutrient conditions (fig. S6A). In the cultures supplemented with bacilysin, Δ Tgmfs4 (the strain lacking the Tgmfs4 gene) showed a notable increase in growth compared to Tg -WT, whereas the complemented strain (Δ Tgmfs4C ) did not exhibit any difference ( and fig. S6, B and C). Besides, upon the addition of bacilysin, the growth rate and biomass of Δ Tgmfs4 exhibited a significant increase compared to Tg -WT ( P < 0.001; fig. S7, A and B). Transmission electron microscopy (TEM) was used to assess cellular morphology under liquid culture conditions with and without bacilysin to further explore the potential mechanisms underlying Tg growth inhibition by bacilysin. The cell wall architecture was found to be well preserved in all three strains under normal conditions. However, Tg -WT and Δ Tgmfs4C exhibited cell wall rupture and leakage of cellular contents upon bacilysin addition, whereas the negative impact on Δ Tgmfs4 was notably reduced . Previous studies have shown that bacilysin competitively inhibits the aminotransferase activity of glucosamine-6-phosphate synthase (Glms), a key enzyme that uses glutamine as its substrate . This inhibitory interaction directly hinders the biosynthesis of glucosamine-6-phosphate, which is essential for fungal cellular biosynthesis . In this study, Glms activity assays revealed that the inhibitory effect of bacilysin on the Glms activity of Δ Tgmfs4 was significantly reduced compared to Tg -WT ( P < 0.001; fig. S7C). These findings indicated that bacilysin exerted growth-inhibitory effects on Tg by disrupting cell wall synthesis through the targeted inhibition of Glms activity, whereas Δ Tgmfs4 showed higher Glms activity and reduced susceptibility to bacilysin. Tg MFS4 mediates the transport of bacilysin into Tg cells The MFS proteins have been shown to be localized on the membrane . To ascertain the subcellular localization of Tg MFS4, the fluorescence of Tg MFS4–green fluorescent protein (GFP) and immunostaining with a cell membrane fluorescent probe (DiI) were observed in Tg hyphae using confocal microscopy. The colocalization of Tg MFS4-GFP and the probe at the cell membrane was clearly observed (fig. S7, D to F). Considering the subcellular localization of Tg MFS4 and the down-regulation of Tgmfs 4 in Tg -M33, we hypothesized its involvement in facilitating transmembrane transport of bacilysin. Initially, the transport capability of Tg MFS4 for bacilysin was evaluated using molecular docking. Previous studies have shown that both the N and C termini of MFS proteins are intracellularly oriented on the same side of the cell membrane , which was consistent with our findings . The molecular docking analysis suggested that bacilysin could potentially bind to the extracellular domain of Tg MFS4, forming electrostatic interactions with Tyr 445 and Gln 208 [Glide extra precision GScore (XP GScore): −5.69 kcal mol −1 ; molecular mechanics/generalized Born surface area (MM/GBSA): −27.54 kcal mol −1 )]. In addition, the central region of Tg MFS4 displayed hydrogen bonding with bacilysin at Val 535 and Val 538 , and electrostatic interaction with Tyr 316 (XP GScore: −4.50 kcal mol −1 ; MM/GBSA: −22.08 kcal mol −1 ). However, bacilysin failed to effectively dock the cellular interior region near Tg MFS4, indicating dissociation from the protein . These results indicated that Tg MFS4 might facilitate the translocation of bacilysin from the extracellular space into the cell. Next, the Xenopus laevis oocyte system was used to evaluate the bacilysin transport capacity of Tg MFS4. Bacilysin labeled with nitrogen-15 ( 15 N-bacilysin) was obtained and purified from the Bv liquid culture broth and identified by HPLC-MS (fig. S8). Bathed with 0.2 mM 15 N-bacilysin, Tg MFS4 capped mRNA (cRNA)–injected oocytes exhibited a significant increase in 15 N uptake in comparison to the water-injected control ( P < 0.05), whereas no significant uptake difference was detected in 2.0 mM 15 N-bacilysin . The Michaelis constant ( K m ) of Tg MFS4 for bacilysin uptake was calculated from the net bacilysin accumulation in oocytes incubated at various concentrations of 15 N-bacilysin, estimated as 0.27 ± 0.07 mM . These results demonstrated that Tg MFS4 functioned as a high-affinity bacilysin transporter. Trade-off between bacilysin production and growth of Bv when cocultured with Δ Tgmfs4 Staphylococcus aureus was used as an indicator strain to quantify bacilysin levels in the coculture liquid culture broth and Tg hyphae. The bacilysin content in the Δ Tgmfs4 + Bv treatment steadily increased over liquid culture time, significantly higher than in Tg -WT+ Bv and Δ Tgmfs4C + Bv treatments (fig. S9, A and B). Conversely, bacilysin content in Δ Tgmfs4 hyphae was significantly lower than in the other treatments (fig. S9, C and D). These findings indicated that the absence of Tgmfs4 impaired the transport of bacilysin from the coculture liquid culture broth into Tg cells, further substantiating the role of Tg MFS4 in mediating the transmembrane transport of bacilysin. Subsequently, we explored the impact of Tgmfs4 deficiency on bacilysin production by Bv and its accumulation in the coculture environment. Over the course of 4-day cultivation, a notable repression in the expression of genes involved in bacilysin synthesis and transport was observed in Δ Tgmfs4 + Bv compared to Tg -WT+ Bv (fig. S10, A to G). Furthermore, it was observed that the biomass of Bv significantly increased when cocultivated with the Δ Tgmfs4 , in comparison to Tg -WT+ Bv and Δ Tgmfs4C + Bv treatments (fig. S10H). This increase in biomass might be attributed to the reduction in antibiotic production, leading to notable savings in fitness costs and subsequently promoting the growth rate . Therefore, the increased resistance of Δ Tgmfs4 led to an accumulation of bacilysin in the coculture environment, which, in turn, balanced the growth and bacilysin production in Bv (fig. S10I). BFI changes triggered by Tgmfs4 affect FWD control efficacy through influencing the microbial community function We hypothesized that the change in BFI mediated by Tgmfs4 played a pivotal role in effectively controlling FWD. To test this hypothesis, we conducted additional pot experiments (fig. S11). As expected, the consortium formed by Bv and Δ Tgmfs4 (Δ Tgmfs4 + Bv ) was more effective in preventing FWD than both the Tg -WT+ Bv treatment and CK, with no significant differences observed between Tg -WT and Δ Tgmfs4 . Moreover, the Δ Tgmfs4 + Bv treatment showed a significantly higher abundance of both Bv and Tg in the rhizosphere soil compared to Tg -WT+ Bv and CK, whereas the abundance of FOL was significantly reduced . These results suggested that the increase in beneficial microbial biomass due to changes in BFIs could be a critical factor in reducing the incidence of FWD. On the other hand, whether this alteration in BFIs solely affected the control of FWD by improving the colonization numbers of beneficial microbes remained to be determined. Consequently, we initially hypothesized that preinfection changes in BFIs might modulate the overall microbial community function, thereby inducing a strengthened microbial barrier in the tomato rhizosphere and enhancing its resistance to FOL . Subsequently, we performed another pot experiment and used metagenomics to delineate the impact of BFI change on the functional spectra of the tomato rhizosphere microbial community (fig. S12). The genes derived from the metagenomic dataset were initially annotated using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Principal coordinates analysis (PCoA) revealed significant differences among the treatments, with robust statistical support ( R = 0.68, P = 0.01, Adonis). The ordination plot indicated that the first two principal components accounted for 56.50 and 34.65% of the total variance, respectively (fig. S13A). Furthermore, 36 pathways showed significant differences across the three treatments ( P < 0.05, Kruskal-Wallis test) . Notably, 15 pathways were enriched in the Δ Tgmfs4 + Bv treatment, mainly including tryptophan metabolism, protein digestion and absorption, RNA degradation, the citrate cycle [tricarboxylic acid (TCA) cycle], and glycolysis/gluconeogenesis. The Tg -WT+ Bv treatment showed enrichment in pathways such as staurosporine biosynthesis, nonribosomal peptide structures, and biosynthesis of acarbose and validamycin, suggesting that there might be more production of antifungal compounds . This was seemingly paradoxical given that the Δ Tgmfs4 + Bv treatment exhibited stronger resistance to FOL than the Tg -WT+ Bv treatment . It was plausible to hypothesize that the Δ Tgmfs4 + Bv treatment might contain additional enriched community functionalities that resist FOL invasion. Accordingly, we annotated the functionalities of carbohydrate-active enzymes (CAZymes) across different treatments to clarify the differences in the expression abundance of critical genes. PCoA revealed significant differences among the treatments ( R = 0.82, P = 0.002, Adonis), with the first and second principal components accounting for 67.42 and 19.99% of the total variance, respectively (fig. S13B). Besides, the gene abundance of five CAZyme families was significantly higher in the Δ Tgmfs4 + Bv treatment compared to CK, with minimal variation observed in the Tg -WT+ Bv treatment . To elucidate the role of CAZymes in the potential control against FOL , we initially evaluated the induced systemic resistance (ISR) in tomato plants under different treatments, by assessing the expression levels of salicylic acid (SA)–induced disease-related protein 1 acid gene ( PR1 α) and jasmonic acid (JA)–induced defensin gene ( PD F1). The results showed that both the Δ Tgmfs4 + Bv and Tg -WT+ Bv treatments significantly increased the expression of the PR1 α gene in tomato plants compared to CK ( P < 0.05, Duncan’s). Notably, the Δ Tgmfs4 + Bv treatment induced the highest level of PR1 α expression, whereas there was no significant effect on the expression of the PDF1 gene across the three treatments . Moreover, univariate linear regression analysis demonstrated a significant positive correlation between the expression level of PR1 α and the abundance of Glycoside hydrolases (GH) ( R 2 = 0.72, P = 0.004), Carbohydrate-binding modules (CBM) ( R 2 = 0.58, P = 0.017), Carbohydrate esterases (CE) ( R 2 = 0.77, P = 0.002), and Glycosyltransferases (GT) ( R 2 = 0.79, P = 0.001) gene families. In contrast, a significant negative correlation was observed with the abundance of the Polysaccharide lyases (PL) gene family ( R 2 = −0.69, P = 0.006) across the treatments (fig. S14). These findings suggested that the differential expression of CAZymes notably influenced the activation of ISR, potentially affecting tomato resistance to FOL . On the other hand, considering the cell wall of pathogenic fungi as their primary obstacle to biological degradation, the abundant presence of CAZymes in the plant rhizosphere would play a crucial role in impeding the reproductive and proliferative phase of FOL . This indicated that changes in the consortium relationships might systematically influence the metabolic functions of carbon compounds in the entire rhizosphere community. Therefore, prior to FOL invasion, compared to the application of the Tg -WT+ Bv consortium, the application of the Δ Tgmfs4 + Bv consortium notably altered the functional profile of the tomato rhizosphere microbiome, particularly by enhancing the expression of CAZyme family genes, which not only stimulated tomato immune resistance but also established an effective barrier potentially inhibiting FOL proliferation, thereby rendering tomatoes more resistant to FOL . In summary, the BFI change not only enhanced the colonization of both beneficial strains within the tomato root system but also profoundly affected the functional profile of the entire microbial community to reduce the occurrence of FWD .   The initial in vitro plate assay showed a strong antagonistic effect of Bacillus velezensis ( Bv ) on the growth of wild-type Trichoderma guizhouense ( Tg -WT; fig. S1). To investigate the effect of BFIs change on plant health, we use x-ray radiation to generate distinct Tg mutants, which demonstrated divergent behavior in interactions with Bv compared to Tg -WT . The subsequent evaluation of the mutant’s interaction with Bv revealed that two Tg mutants, Tg -M19 and Tg -M23, displayed higher antagonistic responses to Bv compared to Tg -WT, primarily manifested by a significant increase in the area of inhibition zones. In contrast, the cocultivation of mutants Tg -M15, Tg -M33, Tg -M50, and Tg -M93 with Bv resulted in a significant decrease in the area of inhibition zones, exhibiting a reduced antagonistic effect compared to Tg -WT ( and fig. S1). Tg -M33 was selected to evaluate the impact of reduced antagonistic interaction between Bv and Tg on the control of FWD caused by Fusarium oxysporum f. sp. lycopersici ( FOL ) in a pot experiment. For the in planta assay, six treatments were designed to assess the FWD control efficacy: control without microbes (CK), Bv strain only, Tg -WT strain only, mutant Tg -M33 only, Tg -WT and Bv ( Tg -WT+ Bv ), and a combination of Tg -M33 and Bv ( Tg -M33+ Bv ) . Compared to CK, the application of individual Bv and Tg -WT strains effectively reduced FWD ( P < 0.05, Duncan’s), whereas the control efficacy of Tg -WT+ Bv did not significantly differ from the individual Bv and Tg -WT strains. Notably, the highest FWD control efficiency was determined with Tg -M33+ Bv . Similarly, the abundance of FOL was significantly lower in the Tg -M33+ Bv ( P < 0.05, Duncan’s) compared to Tg -WT+ Bv , individual Bv and Tg strains, and CK . In contrast, the abundance of Bv and Tg -WT in the Tg -M33+ Bv significantly increased ( P < 0.05, Duncan’s) compared to other treatments . These findings implied that BFIs could potentially affect the efficacy of FWD control by influencing the number of beneficial microbes colonizing the rhizosphere.   Bv To further elucidate the interaction mechanisms between Bv and Tg , we conducted cocultivation of Bv with both Tg -WT and Tg -M33 and isolated the Bv and Tg strains from the agar plates for transcription analysis (fig. S2A). Transcriptomic profiling of Bv indicated a pronounced enrichment in the biosynthesis of various secondary metabolites pathway when cocultured with Tg -WT and Tg -M33 (fig. S2B). These results suggested that Bv notably modulated the secretion of secondary metabolites during confrontations with different Tg strains, playing a pivotal role in the interaction dynamics. To validate, we introduced the secondary metabolites from the liquid culture broth of Bv into the potato dextrose agar (PDA) medium and evaluated their effect on Tg growth. As anticipated, the growth of Tg was markedly inhibited by the secondary metabolites secreted by Bv , whereas the secondary metabolites produced by Tg showed no notable inhibitory effects on the growth of Bv (fig. S3). Previous studies have highlighted the ability of Bv to synthesize a variety of antifungal metabolites . Leveraging this knowledge, we performed a transcriptomic analysis on the secondary metabolite synthesis genes of Bv during its cocultivation with both Tg -WT and Tg -M33. The results showed significant down-regulation of most genes within the gene cluster responsible for bacilysin synthesis and transport in the Tg -M33+ Bv compared to Tg -WT+ Bv (fold change ≥ 2.0, P < 0.05), whereas no significant differences were noted in the expression of genes related to the synthesis of other antifungal metabolites ( , fig. S4A, and table S1). This suggested that inhibiting bacilysin secretion might potentially reduce the inhibitory effect of Bv on Tg growth, promoting a symbiotic relationship. To further investigate the specific inhibitory role of bacilysin, we evaluated the interactions between Bv mutants and Tg by generating knockout mutants targeting various secondary metabolite gene clusters. Consistent with our initial findings, mutants deficient in the production of bacillomycin (Δ bmy ), surfactin (Δ srf ), fengycin (Δ fen ), difficidin (Δ dfn ), macrolactin (Δ mln ), bacillaene (Δ bae ), and bacillibactin (Δ dhb ) retained their antagonistic effects against Tg -WT. This indicated that these compounds were not the primary contributors to the antagonistic activity against Tg -WT. However, the bacilysin-deficient mutant (Δ bac ) showed a notably reduced antagonistic effect against Tg -WT, further confirming bacilysin as the principal antifungal compound mediating Bv ’s antagonistic activity against Tg -WT . This raised a question: How does Tg -M33 overcome the antagonistic effects of bacilysin to establish a symbiotic interaction with Bv ?   Tg To thoroughly understand the inhibitory effects of bacilysin on Tg growth, we initiated a transcriptomic analysis under confrontational cultivation conditions. The Gene Ontology (GO) annotation results indicated that 16.97% of differentially expressed genes (DEGs; P < 0.001) were enriched in molecular functions related to transmembrane transporter activity and general transporter activity. In the biological process classification, 44.44% of DEGs ( P < 0.001) were found to be involved in transmembrane transport and transport processes. Notably, in the cellular component classification, 100% of DEGs ( P < 0.001) were associated with components such as the intrinsic component of the membrane, integral component of the membrane, and membrane itself (fig. S4B). This suggested that changes in the expression levels of key transmembrane transporter genes in Tg -M33 might modulate its tolerance to bacilysin, thus influencing its interaction with Bv . Subsequently, a comparative analysis was conducted on the expression levels of all identified transmembrane transporter genes between Tg -WT+ Bv and Tg -M33+ Bv , revealing significant expression differences (|fold change| ≥ 1.50, P < 0.05) for nine genes across both treatments. These genes mainly encode multidrug resistance (MDR)–type ABC transporter, major facilitator superfamily (MFS) multidrug transporter, ATP binding cassette (ABC) multidrug transporter, and multidrug and toxic compound extrusion (MATE) family efflux transporter . The transporter genes and their relationship with bacilysin sensitivity were investigated by isolating and purifying bacilysin from the liquid culture broth of Bv , which was subsequently identified using High-performance liquid chromatography–mass spectrometry (HPLC-MS) (fig. S5). Next, deletion mutants of nine genes were generated in Tg -WT through homologous recombination, and all nine mutants displayed normal growth under nutrient conditions (fig. S6A). In the cultures supplemented with bacilysin, Δ Tgmfs4 (the strain lacking the Tgmfs4 gene) showed a notable increase in growth compared to Tg -WT, whereas the complemented strain (Δ Tgmfs4C ) did not exhibit any difference ( and fig. S6, B and C). Besides, upon the addition of bacilysin, the growth rate and biomass of Δ Tgmfs4 exhibited a significant increase compared to Tg -WT ( P < 0.001; fig. S7, A and B). Transmission electron microscopy (TEM) was used to assess cellular morphology under liquid culture conditions with and without bacilysin to further explore the potential mechanisms underlying Tg growth inhibition by bacilysin. The cell wall architecture was found to be well preserved in all three strains under normal conditions. However, Tg -WT and Δ Tgmfs4C exhibited cell wall rupture and leakage of cellular contents upon bacilysin addition, whereas the negative impact on Δ Tgmfs4 was notably reduced . Previous studies have shown that bacilysin competitively inhibits the aminotransferase activity of glucosamine-6-phosphate synthase (Glms), a key enzyme that uses glutamine as its substrate . This inhibitory interaction directly hinders the biosynthesis of glucosamine-6-phosphate, which is essential for fungal cellular biosynthesis . In this study, Glms activity assays revealed that the inhibitory effect of bacilysin on the Glms activity of Δ Tgmfs4 was significantly reduced compared to Tg -WT ( P < 0.001; fig. S7C). These findings indicated that bacilysin exerted growth-inhibitory effects on Tg by disrupting cell wall synthesis through the targeted inhibition of Glms activity, whereas Δ Tgmfs4 showed higher Glms activity and reduced susceptibility to bacilysin.   MFS4 mediates the transport of bacilysin into Tg cells The MFS proteins have been shown to be localized on the membrane . To ascertain the subcellular localization of Tg MFS4, the fluorescence of Tg MFS4–green fluorescent protein (GFP) and immunostaining with a cell membrane fluorescent probe (DiI) were observed in Tg hyphae using confocal microscopy. The colocalization of Tg MFS4-GFP and the probe at the cell membrane was clearly observed (fig. S7, D to F). Considering the subcellular localization of Tg MFS4 and the down-regulation of Tgmfs 4 in Tg -M33, we hypothesized its involvement in facilitating transmembrane transport of bacilysin. Initially, the transport capability of Tg MFS4 for bacilysin was evaluated using molecular docking. Previous studies have shown that both the N and C termini of MFS proteins are intracellularly oriented on the same side of the cell membrane , which was consistent with our findings . The molecular docking analysis suggested that bacilysin could potentially bind to the extracellular domain of Tg MFS4, forming electrostatic interactions with Tyr 445 and Gln 208 [Glide extra precision GScore (XP GScore): −5.69 kcal mol −1 ; molecular mechanics/generalized Born surface area (MM/GBSA): −27.54 kcal mol −1 )]. In addition, the central region of Tg MFS4 displayed hydrogen bonding with bacilysin at Val 535 and Val 538 , and electrostatic interaction with Tyr 316 (XP GScore: −4.50 kcal mol −1 ; MM/GBSA: −22.08 kcal mol −1 ). However, bacilysin failed to effectively dock the cellular interior region near Tg MFS4, indicating dissociation from the protein . These results indicated that Tg MFS4 might facilitate the translocation of bacilysin from the extracellular space into the cell. Next, the Xenopus laevis oocyte system was used to evaluate the bacilysin transport capacity of Tg MFS4. Bacilysin labeled with nitrogen-15 ( 15 N-bacilysin) was obtained and purified from the Bv liquid culture broth and identified by HPLC-MS (fig. S8). Bathed with 0.2 mM 15 N-bacilysin, Tg MFS4 capped mRNA (cRNA)–injected oocytes exhibited a significant increase in 15 N uptake in comparison to the water-injected control ( P < 0.05), whereas no significant uptake difference was detected in 2.0 mM 15 N-bacilysin . The Michaelis constant ( K m ) of Tg MFS4 for bacilysin uptake was calculated from the net bacilysin accumulation in oocytes incubated at various concentrations of 15 N-bacilysin, estimated as 0.27 ± 0.07 mM . These results demonstrated that Tg MFS4 functioned as a high-affinity bacilysin transporter.   Bv when cocultured with Δ Tgmfs4 Staphylococcus aureus was used as an indicator strain to quantify bacilysin levels in the coculture liquid culture broth and Tg hyphae. The bacilysin content in the Δ Tgmfs4 + Bv treatment steadily increased over liquid culture time, significantly higher than in Tg -WT+ Bv and Δ Tgmfs4C + Bv treatments (fig. S9, A and B). Conversely, bacilysin content in Δ Tgmfs4 hyphae was significantly lower than in the other treatments (fig. S9, C and D). These findings indicated that the absence of Tgmfs4 impaired the transport of bacilysin from the coculture liquid culture broth into Tg cells, further substantiating the role of Tg MFS4 in mediating the transmembrane transport of bacilysin. Subsequently, we explored the impact of Tgmfs4 deficiency on bacilysin production by Bv and its accumulation in the coculture environment. Over the course of 4-day cultivation, a notable repression in the expression of genes involved in bacilysin synthesis and transport was observed in Δ Tgmfs4 + Bv compared to Tg -WT+ Bv (fig. S10, A to G). Furthermore, it was observed that the biomass of Bv significantly increased when cocultivated with the Δ Tgmfs4 , in comparison to Tg -WT+ Bv and Δ Tgmfs4C + Bv treatments (fig. S10H). This increase in biomass might be attributed to the reduction in antibiotic production, leading to notable savings in fitness costs and subsequently promoting the growth rate . Therefore, the increased resistance of Δ Tgmfs4 led to an accumulation of bacilysin in the coculture environment, which, in turn, balanced the growth and bacilysin production in Bv (fig. S10I).   Tgmfs4 affect FWD control efficacy through influencing the microbial community function We hypothesized that the change in BFI mediated by Tgmfs4 played a pivotal role in effectively controlling FWD. To test this hypothesis, we conducted additional pot experiments (fig. S11). As expected, the consortium formed by Bv and Δ Tgmfs4 (Δ Tgmfs4 + Bv ) was more effective in preventing FWD than both the Tg -WT+ Bv treatment and CK, with no significant differences observed between Tg -WT and Δ Tgmfs4 . Moreover, the Δ Tgmfs4 + Bv treatment showed a significantly higher abundance of both Bv and Tg in the rhizosphere soil compared to Tg -WT+ Bv and CK, whereas the abundance of FOL was significantly reduced . These results suggested that the increase in beneficial microbial biomass due to changes in BFIs could be a critical factor in reducing the incidence of FWD. On the other hand, whether this alteration in BFIs solely affected the control of FWD by improving the colonization numbers of beneficial microbes remained to be determined. Consequently, we initially hypothesized that preinfection changes in BFIs might modulate the overall microbial community function, thereby inducing a strengthened microbial barrier in the tomato rhizosphere and enhancing its resistance to FOL . Subsequently, we performed another pot experiment and used metagenomics to delineate the impact of BFI change on the functional spectra of the tomato rhizosphere microbial community (fig. S12). The genes derived from the metagenomic dataset were initially annotated using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Principal coordinates analysis (PCoA) revealed significant differences among the treatments, with robust statistical support ( R = 0.68, P = 0.01, Adonis). The ordination plot indicated that the first two principal components accounted for 56.50 and 34.65% of the total variance, respectively (fig. S13A). Furthermore, 36 pathways showed significant differences across the three treatments ( P < 0.05, Kruskal-Wallis test) . Notably, 15 pathways were enriched in the Δ Tgmfs4 + Bv treatment, mainly including tryptophan metabolism, protein digestion and absorption, RNA degradation, the citrate cycle [tricarboxylic acid (TCA) cycle], and glycolysis/gluconeogenesis. The Tg -WT+ Bv treatment showed enrichment in pathways such as staurosporine biosynthesis, nonribosomal peptide structures, and biosynthesis of acarbose and validamycin, suggesting that there might be more production of antifungal compounds . This was seemingly paradoxical given that the Δ Tgmfs4 + Bv treatment exhibited stronger resistance to FOL than the Tg -WT+ Bv treatment . It was plausible to hypothesize that the Δ Tgmfs4 + Bv treatment might contain additional enriched community functionalities that resist FOL invasion. Accordingly, we annotated the functionalities of carbohydrate-active enzymes (CAZymes) across different treatments to clarify the differences in the expression abundance of critical genes. PCoA revealed significant differences among the treatments ( R = 0.82, P = 0.002, Adonis), with the first and second principal components accounting for 67.42 and 19.99% of the total variance, respectively (fig. S13B). Besides, the gene abundance of five CAZyme families was significantly higher in the Δ Tgmfs4 + Bv treatment compared to CK, with minimal variation observed in the Tg -WT+ Bv treatment . To elucidate the role of CAZymes in the potential control against FOL , we initially evaluated the induced systemic resistance (ISR) in tomato plants under different treatments, by assessing the expression levels of salicylic acid (SA)–induced disease-related protein 1 acid gene ( PR1 α) and jasmonic acid (JA)–induced defensin gene ( PD F1). The results showed that both the Δ Tgmfs4 + Bv and Tg -WT+ Bv treatments significantly increased the expression of the PR1 α gene in tomato plants compared to CK ( P < 0.05, Duncan’s). Notably, the Δ Tgmfs4 + Bv treatment induced the highest level of PR1 α expression, whereas there was no significant effect on the expression of the PDF1 gene across the three treatments . Moreover, univariate linear regression analysis demonstrated a significant positive correlation between the expression level of PR1 α and the abundance of Glycoside hydrolases (GH) ( R 2 = 0.72, P = 0.004), Carbohydrate-binding modules (CBM) ( R 2 = 0.58, P = 0.017), Carbohydrate esterases (CE) ( R 2 = 0.77, P = 0.002), and Glycosyltransferases (GT) ( R 2 = 0.79, P = 0.001) gene families. In contrast, a significant negative correlation was observed with the abundance of the Polysaccharide lyases (PL) gene family ( R 2 = −0.69, P = 0.006) across the treatments (fig. S14). These findings suggested that the differential expression of CAZymes notably influenced the activation of ISR, potentially affecting tomato resistance to FOL . On the other hand, considering the cell wall of pathogenic fungi as their primary obstacle to biological degradation, the abundant presence of CAZymes in the plant rhizosphere would play a crucial role in impeding the reproductive and proliferative phase of FOL . This indicated that changes in the consortium relationships might systematically influence the metabolic functions of carbon compounds in the entire rhizosphere community. Therefore, prior to FOL invasion, compared to the application of the Tg -WT+ Bv consortium, the application of the Δ Tgmfs4 + Bv consortium notably altered the functional profile of the tomato rhizosphere microbiome, particularly by enhancing the expression of CAZyme family genes, which not only stimulated tomato immune resistance but also established an effective barrier potentially inhibiting FOL proliferation, thereby rendering tomatoes more resistant to FOL . In summary, the BFI change not only enhanced the colonization of both beneficial strains within the tomato root system but also profoundly affected the functional profile of the entire microbial community to reduce the occurrence of FWD .   Plant roots host a diverse microbiota, including symbiotic consortia of bacteria and fungi, known to protect plants by warding off microbial pathogens, modulating host immune responses, and improving nutrient uptake . Despite their significance, the complex dynamics of BFIs and its influence on plant health still need to be fully understood. Previous research has demonstrated that ABC transporters are capable of transporting not only endogenous metabolites but also a variety of xenobiotic substances, including antifungal compounds. This versatility makes certain ABC transporters key contributors to antifungal drug resistance . Typically, efflux pump proteins encoded by the MFS family proteins are closely associated with antibiotic resistance due to their ability to extrude a wide range of antibiotics from the cell . In this study, we delineated the impact of the inward-facing transport of antibiotics by MFS family proteins on the change in BFIs. Tg MFS4 showed a notable enhancement in transport efficiency in solutions with low bacilysin concentrations, indicating a high affinity for bacilysin. It is important to note that, in the natural environment, such as the plant rhizosphere, the concentration of most antimicrobial peptides produced by Bacillus may be deficient . Therefore, the observed high-affinity transport is consistent with natural conditions. An analogous mode of action has been identified in bacterial-bacterial interactions. For example, the ompC gene disruption in Escherichia coli , when cocultivated with Pseudomonas aeruginosa , reduces the inhibitory effect of P. aeruginosa on E. coli . This was attributed to the potential entry of pyocyanin into E. coli cells through the OmpC porin protein . Other evidence also suggests that the expression levels of membrane transporter proteins are associated with the ecological adaptability of soil microbes. The MDR pump enhanced the ecological adaptability of Shewanella oneidensis in aquifer sediments by extruding other compounds present in the ecosystems, such as humic acids . The constitutive overexpression of MDR pumps has also been shown to shift the behavior of P. aeruginosa from virulent to nonvirulent in response to certain bioactive compounds . Thus, a similar mechanism of action for Tg MFS4 may be common in nature, and a deficiency in its function could also represent an ecological adaptation strategy in the ongoing natural evolution process. The co-occurrence of bacteria and fungi, especially in the host’s niche, indicates that cross-kingdom interactions are key selective forces driving the diversity, variability, and stability of microbial communities . Furthermore, interspecies communication between bacteria and fungi may promote differentiation, diversity, and stability within microbial consortia . Our study further corroborated this notion, showing that the Tg MFS4-mediated change in BFIs not only affected the colonization density of the two beneficial microbial strains in the rhizosphere but also potentially influenced plant health by altering the functional capabilities of the microbial community. In the field of microbial biocontrol for fungal plant diseases, various mechanisms have been identified, such as the production of antifungal metabolites, secretion of hydrolytic enzymes like chitinases and glucanases, and induction of systemic resistance in plants . Our findings revealed that the BFI change changed the paradigm for maintaining plant health. The incorporation of the Δ Tgmfs4 + Bv consortium notably enhanced the expression of CAZyme family genes compared to Tg -WT+ Bv consortium, which might play a direct or indirect role in resisting the invasion of FOL by the following three aspects: (i) the potential stimulation of plant immune responses , (ii) the facilitation of beneficial strains to acquire carbon substrates for proliferation , and (iii) the degradation of pathogen cell walls to erect a barricade that impedes their invasive progress . This supports previous reports that bacteria and fungi have a range of interactions, from antagonism to coexistence, affecting the growth, reproduction, stress resistance, and pathogenicity of the associated partners in various ways . Concurrently, these interactions occur within the microbiota of plants or animals, affecting host health in many ways . BFIs are extensively applied within agricultural systems, encompassing the exploration of constructing synthetic communities to safeguard plant health . Most biocontrol research now available focuses on a limited number of single microbial strains . However, microbes naturally exist in complex communities, influenced by their host, the surrounding environment, and other community members. In theory, applying beneficial microbes in combination for disease control should enhance the efficacy of biocontrol. However, in practice, combining multiple microbes is sometimes less effective than using a single microbe . This is primarily because the selection of beneficial strains focuses on their disease-control effects, often overlooking the interactions and compatibility among microbes . This study provides more effective insights for future efforts in constructing synthetic microbial communities. This approach can be improved by leveraging existing beneficial microbes and strategically modifying their interactions, thus avoiding the complexities of laborious strain selection and the limitations of functional microbial cultivation. Microbes reside within ecosystems not in solitude but in perpetual proximity to other life forms, engaging in the exchange and communion of chemical signals, including secondary metabolites . These secondary metabolites are often considered weapons for their competition with other microbes, aiding in acquiring a survival advantage . Research has indicated that fungi have evolved various strategies to enhance their drug resistance, including alterations in drug targets, augmentation of drug efflux, and the induction of cellular stress response pathways . A suite of adaptive mechanisms emerges during the direct dialogue between fungi and bacteria. Researchers have discovered that fungi can modulate interactions with different bacteria by differentially generating ROS (reactive oxygen species), thereby selectively symbiotic with certain bacteria . In addition to the involvement of fungal genes encoding the HOG (high-osmolarity glycerol) MAPK (mitogen-activated protein kinase) signaling pathway and lipid metabolism in regulating BFIs , a hallmark of symbiotic interactions is the transcriptional up-regulation of genes in the cAMP (cyclic adenosine 3′,5′-monophosphate) signaling pathway and the rearrangement of the cytoskeleton . Moreover, fungi can alter the ratio of 1,3-β-glucans to chitin in their cell walls in response to cell wall–antagonistic drugs, such as chitin synthase or glucan synthase inhibitors . In addition to these defensive strategies, fungi can also modulate their interactions with host microbiota, including bacteria, by secreting specific effector proteins to facilitate their colonization . Even so, the ecological impact of the processes by which fungi acquire adaptive advantages is seldom reported. This study uncovered the capacity of fungi to mitigate the uptake of bacterial toxins by modulating the expression of transmembrane proteins, and this perturbation in the symbiotic dynamic subsequently exerted an influence on the well-being of plants. This study provides a framework for future systematic research on BFIs, particularly the ecological impact of fungal adaptive changes during the coevolutionary process between bacteria and fungi.   Strains and culture conditions T. guizhouense NJAU4742 ( Tg ) [Jiangsu Provincial Key Lab for Organic Solid Waste Utilization, National Center for Biotechnology Information (NCBI) accession no. LVVK00000000.1] and its derived mutants were cultured on the PDA medium at 28°C, and spores were preserved . B. velezensis SQR9 ( Bv ) [CGMCC accession no. 5808, China General Microbiology Culture Collection Center (CGMCC), NCBI accession no. CP006890], and the derived strains were cultivated at 37°C on an LB medium (5 g liter −1 yeast extract, 5 g liter −1 NaCl, and 10 g liter −1 peptone) solidified with 2% agar . F. oxysporum f. sp. lycopersici strain Fol4287 ( FOL ) (Jiangsu Provincial Key Lab for Organic Solid Waste Utilization, NCBI accession no. QESU00000000.1) was used in this study and cultured on the PDA medium at 28°C, and the conidia were obtained as described previously . Screening of Tg -induced mutants Fresh spore suspension of Tg -WT was adjusted to 1 × 10 7 spores ml −1 , mixed with acetic acid–sodium acetate buffer (1:1), and placed in a biological x-ray irradiator (RS 2000 Pro, RADSOURCE, USA) for irradiation. The total irradiation dose was set to 250 grays. After obtaining the irradiated spores, well-growing induced mutants were selected and transferred to the PDA medium for further cultivation until sporulation. Subsequently, bacterial antagonistic activities toward induced strains of Tg were tested by the dual-culture assay on a Warkingsman’s agar (WA) medium, which supported the vegetative growth of both bacteria and fungi . Briefly, all spore suspensions of induced strains were inoculated at the center of the WA medium and incubated for 24 hours at 28°C. Next, Bv was inoculated ~4.50 cm away from the plate center of the Tg mutants, and the plates were further incubated for 36 hours at 28°C, with the confrontation interactions observed and recorded. The area of the inhibition zones was measured using the Fiji/ImageJ software. Pot experiments The soil used in the pot experiments was obtained from the Baima experimental base, located in Lishui District, Nanjing, China, affiliated with Nanjing Agricultural University. The plot had been cultivated with tomatoes for two consecutive seasons without exhibiting any signs of disease. Soil was distributed into polypropylene pots, with each pot containing 200 g of soil and transplanted with one tomato seedling ( Solanum lycopersicum . cv. Micro-Tom). The pots were then cultivated in a plant growth chamber under controlled conditions (daytime: 16 hours at 30°C, nighttime: 8 hours at 28°C, with an average humidity of 75% throughout the day). In this study, a total of three pot experiments were conducted. Initial pot experiment was conducted to assess the impact of incorporating strains on the control efficacy of FWD, which comprised six treatments: T1 functioned as the control (CK) with no addition of any microbial agent and was instead replaced by an equal volume of sterile water; T2-4, individually supplemented with Bv , Tg -WT, and Tg -M33 strain, respectively; and T5-6 were supplemented with Tg -WT+ Bv and Tg -M33+ Bv consortia, respectively. In each treatment, the fungal spore suspension of Tg was inoculated at a ratio of 1 × 10 6 spores g −1 of soil, and the bacterial suspension of Bv was added at a ratio of 1 × 10 6 colony-forming units (CFU) g −1 of soil. One week following the application of microbial treatment, each group was inoculated with a spore suspension of FOL specialized for tomato plants, at a concentration of 1 × 10 6 spores g −1 of soil. To evaluate the impact of Tgmfs4 -mediated changes in BFIs on the efficacy of FWD control, another pot experiment was conducted. The setup was as described in the previous section except few changes in strains. The specific treatment classifications are outlined in fig. S11. To investigate the effect of BFI changes on microbial community function, another batch of pot experiment was performed. Our hypothesis was that, prior to pathogen invasion, the introduction of diverse beneficial microbial communities had already established distinct biological barriers. Only three treatments were included: CK, Tg -WT+ Bv , and Δ Tgmfs4 + Bv . In addition, the cultivation period was concluded 7 days after the application of the strains, followed by the collection of soil samples from tomato rhizosphere and plant samples (fig. S12). The timing was selected based on the previous two batches of experiments, where FOL was introduced at this specific time point. All pot experiments included three replicates per treatment, with eight seedlings in each replicate. The disease severity index of tomato plants was assessed based on the scoring range established by Zhou et al.  and calculated using the following formula: Disease index  = ∑ (Number of diseased plants × Severity score)/(Total number of plants surveyed × Maximum severity score) × 100%. Soil sampling and DNA extraction Soil samples from the rhizosphere were collected following the method described by Deng et al. . In brief, the soil surrounding each tomato root was vigorously shaken to remove excess soil. Subsequently, sterile phosphate-buffered saline (PBS) was used to collect the soil adhering to the roots (rhizosphere soil). Rhizosphere soil samples were centrifuged at 10,000 g for 10 min and stored at −80°C. For each replicate, rhizosphere soil from eight tomato plants was combined to form a subsample. Three subsamples collected from each treatment were used as three replicates for subsequent experiments. Soil samples (0.5 g) were used for DNA extraction using the PowerSoil DNA Isolation Kit (MoBio Laboratories, Carlsbad, CA, USA) following the manufacturer’s instructions. The concentration and quality of DNA were determined using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). Quantitative PCR analysis The abundance of FOL , Bv , and Tg in the rhizosphere of tomatoes was determined using species-specific primers SIX1 -F/ SIX1 -R , SQR9 -F/ SQR9 -R , and T-7 -F/ T-7 -R , respectively. Quantitative polymerase chain reaction (PCR) amplification of DNA samples was performed with the ChamQ Universal SYBR qPCR Master Mix (Q711-02/03, Vazyme Biotech) on a 7500 Real-Time PCR System (Applied Biosystems, Pleasanton, CA, USA) following the manufacturer’s instructions. Gene copies were represented as log 10 , and the primers involved in the quantitative PCR were shown in table S2. Establishing liquid coculture treatments of Tg and Bv : (i) Tg -WT+ Bv ; (ii) Δ Tgmfs4 + Bv ; and (iii) Δ Tgmfs4C + Bv . Tg (500 μl, 1 × 10 7 spores ml −1 ) and Bv [500 μl, optical density at 600 nm (OD 600 ) = 0.8] were inoculated in the WA liquid medium and incubated at 30°C with shaking at 170 rpm for 4 days. To determine the expression level of bacilysin production–related gene, the liquid culture broth from the entire coculture system was filtered daily to remove the Tg mycelium. Subsequently, Bv cells were collected by centrifugation at 12,000 rpm for 10 min. Total RNA was extracted from the Bv cells using a bacterial RNA kit (OMEGA, Biotek), and the RNA was then reverse transcribed into cDNA using the PrimeScript RT reagent kit (TaKaRa, Dalian, China). Relative quantification of genes related to bacilysin production was performed using the SYBR Premix Ex Taq II (Takara, Dalian, China) and a 7500 Real-Time PCR System (Applied Biosystems, Pleasanton, CA, USA). The primer sequences of the SA-inducible gene PR1 α, the JA-inducible plant defensin gene PDF 1, and the reference gene β-actin were used for gene expression analysis . Ten-day-old whole plant seedlings were collected and promptly cryopreserved in liquid nitrogen (fig. S12). Total RNA extraction was performed using the RNeasy Plant Mini Kit (Qiagen, Germany), and cDNA synthesis was completed using the PrimeScript RT Reagent Kit (RR036A, Takara, Dalian, China). The qRT-PCR was performed using the SYBR Premix Ex Taq II (Takara, Dalian, China) and a 7500 Real-Time PCR System (Applied Biosystems, Pleasanton, CA, USA). The primers involved in the quantitative PCR are shown in table S2. RNA sequencing and transcriptome analysis The cocultivation of Bv and Tg strains was performed to elucidate the mechanism underlying their interaction, and samples were collected for transcriptional analysis of each strain. Briefly, 1-μl spore suspensions (1 × 10 7 spores ml −1 ) of Tg -WT and Tg -M33 were separately inoculated onto the center of the WA medium and incubated at 28°C for 1 day. Subsequently, Bv was inoculated at 2.5 cm away from the center of the medium, and 10 μl of Bv (1 × 10 6 CFU ml −1 ) was simultaneously inoculated on both sides. After incubation at 28°C for 5 days, the mycelia of Tg and bacterial cells of Bv were collected, flash frozen in liquid nitrogen, and stored at −80°C. The RNA from Tg mycelia samples was extracted using the RNeasy Plant Mini Kit (Qiagen, Germany), and the RNA from Bv cells was extracted using the bacterial RNA kit (OMEGA, Biotek). Subsequently, RNA integrity and contamination were assessed by 1% agarose gel electrophoresis. Qualified RNA samples were sequenced using the Illumina Novaseq6000 platform (LC-Bio Technology Co. Ltd., Hangzhou, China), and high-quality clean reads were filtered using Cutadapt (version 1.9). Next, the filtered reads were aligned to their respective reference genomes ( Tg : assembly accession GCA_002022785.1; Bv : assembly accession GCA_000685725.1) using the upgraded HISAT2 software, a successor to TopHat2. RNA sequencing data were normalized as FPKM (fragments per kilobase of exon model per million mapped reads). Generation of different targeted gene mutants in Tg and Bv Gene deletion and reverse complementation mutants of Tg were obtained via a gene replacement strategy using the polyethylene glycol (PEG)–mediated protoplast transformation procedure as described by Li et al. . For the generation of strain Tgmfs4 - gfp , the DNA fraction of Tgmfs 4 was amplified with Tg DNA as a template, and the GFP fragment was amplified using plasmid pEGFP-N1 as a template (Clontech, USA). The DNA fragment of Tgmfs4 was ligated with the GFP fragment using the overlapping PCR technique based on the instructions of CloneAmp HiFi PCR Premix (Clontech, USA). Mutant of Tgmfs4 - gfp was constructed using the PEG-mediated protoplast transformation with hygromycin resistance cassette ( Hyg B) as the biomarker. Besides, mutants of Bv deficient in bacillomycin (Δ bmy ), surfactin (Δ srf ), fengycin (Δ fen ), difficidin (Δ dfn ), macrolactin (Δ mln ), bacillaene (Δ bae ), bacillibactin (Δ dhb ), and bacilysin (Δ bac ) were constructed with a marker-free strategy as described previously . Preparation and assay of bacilysin The extraction and detection of bacilysin were carried out as previously described with some modifications . Briefly, Bv was inoculated into the Perry and Abraham (PA) medium and incubated at 30°C for 48 hours. The culture was then centrifuged at 12,000 rpm for 10 min to remove bacterial cells. Ethanol (four times the volume of the supernatant) was added to precipitate impurities. After concentrating the supernatant 50-fold, it was passed through XAD1600 resin (particle size: 350 to 450 μm, Shanghai Yuanye Bio-Technology Co. Ltd.). The eluate was further processed using SP207 resin (Sepabeads; Mitsubishi Chemical Corporation, Japan), washed with 3 bed volumes (BV) of water, and then eluted with 3 BV of a 10% ethanol solution. The resulting eluate was freeze dried into a powder and stored at −80°C. For HPLC-MS analysis, freeze-dried samples were reconstituted in purified water and filtered through a 0.22-μm filter (Merck Millipore, German). HPLC was conducted using a Waters E2695 system with an XBridge C18 column (5 μm, 4.6 by 250 mm). The solvent system consisted of 40% acetonitrile in distilled water with 0.1% acetic acid (v/v). The flow rate was set at 0.6 ml min −1 , with a gradient program of 30 min: starting from 0% acetonitrile, increasing to 100% in 20 min, maintained for 5 min, and then decreasing to 5% in the final 5 min. The absorbance at 230 and 205 nm was monitored, and compounds with a retention time of 5.26 min were collected. The collected bacilysin was further identified using an HPLC-MS system (Agilent 1200-6410B), with mobile phase conditions identical to those used in HPLC and a molecular weight detection range of 100 to 400 Da. In the preparation of 15 N-bacilysin, Bv was cultured using ( 15 NH 4 ) 2 SO 4 as the sole nitrogen source instead of sodium glutamate in the PA medium. The culture conditions, isolation methods, and detection techniques were previously detailed. An HPLC system (Agilent 1260 Infinity II) was used to isolate 15 N-bacilysin at a flow rate of 1 ml min −1 . The elution peak at 4.45 min was collected and validated using an HPLC-MS system (Agilent 1200-6410B). Assay of mycelium growth rate, biomass, and Glms activity of Tg To investigate the sensitivity of different strains to bacilysin, 1-μl spore suspension (1 × 10 7 spores ml −1 ) of Tg -WT and its mutants were inoculated into the PDA medium supplemented with bacilysin, resulting in a final concentration of 100 μg ml −1 . After 3 days, the colony diameters were measured. Simultaneously, the fresh mycelia were harvested from PDA plates covered with cellophane and quantified by weighing as a measure of biomass. In addition, the collected mycelia were assessed for the aminotransferase activity of Glms using the Glms detection kit (G0558F, Suzhou Grace Biotechnology Co. Ltd.). The entire process involved a control group in which bacilysin was not added the formula for calculating the relative inhibition rate of Tg was as follows: relative inhibition rate  = (mean diameter of control colonies − mean diameter of experimental colonies)/(mean diameter of control colonies − diameter of mycelial mass at inoculation) × 100%. TEM and confocal imaging analysis The fresh spore suspension of Tg -WT, Δ Tgmfs4 , and Δ Tgmfs4C were inoculated on the potato dextrose broth medium supplemented with bacilysin (100 μg ml −1 ) and incubated at 28°C for 3 days. Upon completion of the incubation, the mycelia were subsequently fixed overnight at 4°C in a solution containing 3% glutaraldehyde and 1% paraformaldehyde. Following fixation, the samples underwent dehydration using a graded series of ethanol and were then embedded in a mixture of embedding resin and acetone. Ultrathin sections were prepared using a Reichert ultramicrotome and examined using a transmission electron microscope (Hitachi HT7800). The GFP-labeled mutant ( Tgmfs4 - gfp ) was cultured on the PDA medium for 3 days, and the fresh mycelia were collected and stained with Cell Plasma Membrane Staining Kit (C1991S, Beyotime) according to the manufacturer’s instructions. Subsequently, the mycelia were washed three times with PBS buffer (pH 7.4) and imaged using a confocal fluorescence microscope (TCS SP8, Leica, Germany) using a 60x oil immersion objective. The channel of GFP was excited at 488 nm and emitted at 510 nm, whereas the red fluorescent probe was excited at 549 nm and emitted at 565 nm. Image processing was performed using the Fiji/ImageJ software. Molecular docking The sequence of Tg MFS4 (OPB38031) was collected from the NCBI online site. Whereupon, the initial three-dimensional structure of Tg MFS4 was constructed using the AlphaFold2 . The structures of receptors and ligands were processed by using Schrödinger . The ligand amitraz was prepared by using the LigPrep module with OPLS3e force field . The sitemap tool was used to predict the binding sites for bacilysin , and the parameters of the grid box were determined based on the results generated by the sitemap. Docking was performed using the Glide program in extra precision mode . The optimal binding poses of various Tg MFS4 conformations with bacilysin were retained. The 15 N-bacilysin uptake assay in X. laevis oocytes The CDS of Tg MFS4 was amplified and cloned into the X. laevis oocyte expression vector pT7Ts between the restriction sites Bgl II and Spe I and then linearized with Xba I. cRNA was synthesized in vitro using the Ambion mMessage mMachine kit (Ambion, AM1340). Oocytes were injected with Tg MFS4 cRNA (50 ng) or RNase-free water (50 nl) and incubated in an ND96 solution for 2 days. Subsequently, they were divided into seven groups and transferred to a series of solutions containing 15 N-bacilysin at concentrations of 0, 0.2, 0.5, 0.8, 1.2, 1.5, and 2.0 mM (dissolved in an ND96 solution). The experiment was conducted in triplicate, with each replicate comprising a minimum of three oocytes. After incubating at 18°C for 6 hours, the oocytes were washed with a nitrogen-free ND96 solution and subsequently desiccated at 75°C until reaching a constant weight. The dried oocytes were weighed, and the 15 N content was determined using a MAT253 isotope ratio mass spectrometer (Flash 2000 HT, Thermo Fisher Scientific, Germany). Absorption kinetics curves were plotted using the GraphPad Prism software (version 9.1.1), and the K m values were also calculated. Assay of bacilysin content and biomass of Bv Establishing liquid coculture treatments of Tg and Bv : (i) Tg -WT+ Bv ; (ii) Δ Tgmfs4 + Bv ; and (iii) Δ Tgmfs4C + Bv . Tg (500 μl, 1 × 10 7 spores ml −1 ) and Bv (500 μl, OD 600 = 0.8) were inoculated in the WA liquid medium and incubated at 30°C with shaking at 170 rpm for 4 days. Samples were obtained from the coculture system to determine the relative levels of bacilysin in both the mycelium and liquid culture broth. Specifically, mycelium from the coculture liquid culture broth was washed thrice with PBS buffer (pH 7.4), blotted to remove excess moisture, and weighed. The mycelium was then thoroughly ground in liquid nitrogen and dissolved in PBS buffer (pH 7.4). The mixture was centrifuged, and the supernatant was collected for further analysis. In addition, an equal volume of the liquid culture broth was collected daily from the coculture system. The broth was centrifuged to remove the Tg mycelium and Bv cells, and the supernatant was collected. The supernatants obtained from both methods were filtered through a 0.22-μm filter (Merck Millipore, German). S. aureus ATCC9144 was used as the indicator strain for detecting bacilysin via the paper disc agar diffusion method, and the bacilysin level was estimated as described previously . The biomass of Bv was determined by collecting a uniform sample from the coculture system daily, and then the sample was diluted and plated on an LB agar medium at 30°C for 18 hours. The plates were incubated, and the biomass was quantified by enumerating the CFU. Metagenome analysis The rhizosphere soil collected from the third batch of pot experiments was subjected to shotgun metagenomic sequencing, yielding an average of 10 giga–base pairs per sample. The extraction and quality control of rhizosphere soil DNA were performed in accordance with the methods described above. Library preparation was carried out according to the standard Illumina protocol. Briefly, DNA was isolated using ultrasonication, and a pooled library containing equimolar amounts of barcoded fragments ranging from 350 to 500 base pairs (bp) was prepared. This library was then sequenced using the Illumina NovaSeq 6000 platform, targeting 150-bp paired-end reads. The raw sequence data underwent trimming, filtering, and assembly using MEGAHIT, whereas contigs longer than 300 bp were further subjected to gene prediction and annotation. The assembled contig sequences were subjected to open reading frame (ORF) prediction using Prodigal. Translations were performed for predicted ORFs longer than 100 bp, and a nonredundant gene catalog was constructed based on sequence identity of 95% and coverage of 90%. Gene abundance in each sample was normalized using RPKM (reads per kilobase million). Representative sequences from the nonredundant gene set were aligned with the NCBI NR database using the Diamond blastp program, selecting annotations with e values < 1 × 10 −5 . For functional annotation, sequences were annotated against the KEGG and the Carbohydrate-Active Enzymes Database (CAZy) with an e value cutoff of 1 × 10 −5 . Statistical analyses All statistical analyses were performed using IBM SPSS 22 (IBM Corporation, New York, USA) and R software (version 3.5.0). The significance of differences among multiple groups, excluding the sequencing data, was determined by one-way analysis of variance (ANOVA) (with Duncan’s multiple range test). The significance between the two groups was evaluated using a two-sided Student’s t test, and the resulting P value was adjusted for multiple comparisons using the FDR (false discovery rate) correction. In metagenomic data analysis, the Wilcoxon rank sum test (for two groups) or Kruskal-Wallis test (for three groups) was used to perform hypothesis testing on functional abundance data to obtain P values. In this study, a P value of <0.05 indicated a statistically significant difference. The permutational multivariate analysis of variance (PERMANOVA) (Adonis, with Bray-Curtis transformed data, permutation = 999) was used to determine whether there were significant differences in gene functions annotated through the KEGG or CAZy databases among different treatments. PCoA plots based on the Bray-Curtis similarity matrix were generated using the “ggplot2” and “vegan” packages. In addition, linear regression was performed using R, and the “ggpmisc” package was used to report R 2 and P values to determine the relationship between the expression of the CAZyme family genes and the activation of the SA signaling pathway.   T. guizhouense NJAU4742 ( Tg ) [Jiangsu Provincial Key Lab for Organic Solid Waste Utilization, National Center for Biotechnology Information (NCBI) accession no. LVVK00000000.1] and its derived mutants were cultured on the PDA medium at 28°C, and spores were preserved . B. velezensis SQR9 ( Bv ) [CGMCC accession no. 5808, China General Microbiology Culture Collection Center (CGMCC), NCBI accession no. CP006890], and the derived strains were cultivated at 37°C on an LB medium (5 g liter −1 yeast extract, 5 g liter −1 NaCl, and 10 g liter −1 peptone) solidified with 2% agar . F. oxysporum f. sp. lycopersici strain Fol4287 ( FOL ) (Jiangsu Provincial Key Lab for Organic Solid Waste Utilization, NCBI accession no. QESU00000000.1) was used in this study and cultured on the PDA medium at 28°C, and the conidia were obtained as described previously .   Tg -induced mutants Fresh spore suspension of Tg -WT was adjusted to 1 × 10 7 spores ml −1 , mixed with acetic acid–sodium acetate buffer (1:1), and placed in a biological x-ray irradiator (RS 2000 Pro, RADSOURCE, USA) for irradiation. The total irradiation dose was set to 250 grays. After obtaining the irradiated spores, well-growing induced mutants were selected and transferred to the PDA medium for further cultivation until sporulation. Subsequently, bacterial antagonistic activities toward induced strains of Tg were tested by the dual-culture assay on a Warkingsman’s agar (WA) medium, which supported the vegetative growth of both bacteria and fungi . Briefly, all spore suspensions of induced strains were inoculated at the center of the WA medium and incubated for 24 hours at 28°C. Next, Bv was inoculated ~4.50 cm away from the plate center of the Tg mutants, and the plates were further incubated for 36 hours at 28°C, with the confrontation interactions observed and recorded. The area of the inhibition zones was measured using the Fiji/ImageJ software.   The soil used in the pot experiments was obtained from the Baima experimental base, located in Lishui District, Nanjing, China, affiliated with Nanjing Agricultural University. The plot had been cultivated with tomatoes for two consecutive seasons without exhibiting any signs of disease. Soil was distributed into polypropylene pots, with each pot containing 200 g of soil and transplanted with one tomato seedling ( Solanum lycopersicum . cv. Micro-Tom). The pots were then cultivated in a plant growth chamber under controlled conditions (daytime: 16 hours at 30°C, nighttime: 8 hours at 28°C, with an average humidity of 75% throughout the day). In this study, a total of three pot experiments were conducted. Initial pot experiment was conducted to assess the impact of incorporating strains on the control efficacy of FWD, which comprised six treatments: T1 functioned as the control (CK) with no addition of any microbial agent and was instead replaced by an equal volume of sterile water; T2-4, individually supplemented with Bv , Tg -WT, and Tg -M33 strain, respectively; and T5-6 were supplemented with Tg -WT+ Bv and Tg -M33+ Bv consortia, respectively. In each treatment, the fungal spore suspension of Tg was inoculated at a ratio of 1 × 10 6 spores g −1 of soil, and the bacterial suspension of Bv was added at a ratio of 1 × 10 6 colony-forming units (CFU) g −1 of soil. One week following the application of microbial treatment, each group was inoculated with a spore suspension of FOL specialized for tomato plants, at a concentration of 1 × 10 6 spores g −1 of soil. To evaluate the impact of Tgmfs4 -mediated changes in BFIs on the efficacy of FWD control, another pot experiment was conducted. The setup was as described in the previous section except few changes in strains. The specific treatment classifications are outlined in fig. S11. To investigate the effect of BFI changes on microbial community function, another batch of pot experiment was performed. Our hypothesis was that, prior to pathogen invasion, the introduction of diverse beneficial microbial communities had already established distinct biological barriers. Only three treatments were included: CK, Tg -WT+ Bv , and Δ Tgmfs4 + Bv . In addition, the cultivation period was concluded 7 days after the application of the strains, followed by the collection of soil samples from tomato rhizosphere and plant samples (fig. S12). The timing was selected based on the previous two batches of experiments, where FOL was introduced at this specific time point. All pot experiments included three replicates per treatment, with eight seedlings in each replicate. The disease severity index of tomato plants was assessed based on the scoring range established by Zhou et al.  and calculated using the following formula: Disease index  = ∑ (Number of diseased plants × Severity score)/(Total number of plants surveyed × Maximum severity score) × 100%.   Soil samples from the rhizosphere were collected following the method described by Deng et al. . In brief, the soil surrounding each tomato root was vigorously shaken to remove excess soil. Subsequently, sterile phosphate-buffered saline (PBS) was used to collect the soil adhering to the roots (rhizosphere soil). Rhizosphere soil samples were centrifuged at 10,000 g for 10 min and stored at −80°C. For each replicate, rhizosphere soil from eight tomato plants was combined to form a subsample. Three subsamples collected from each treatment were used as three replicates for subsequent experiments. Soil samples (0.5 g) were used for DNA extraction using the PowerSoil DNA Isolation Kit (MoBio Laboratories, Carlsbad, CA, USA) following the manufacturer’s instructions. The concentration and quality of DNA were determined using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA).   The abundance of FOL , Bv , and Tg in the rhizosphere of tomatoes was determined using species-specific primers SIX1 -F/ SIX1 -R , SQR9 -F/ SQR9 -R , and T-7 -F/ T-7 -R , respectively. Quantitative polymerase chain reaction (PCR) amplification of DNA samples was performed with the ChamQ Universal SYBR qPCR Master Mix (Q711-02/03, Vazyme Biotech) on a 7500 Real-Time PCR System (Applied Biosystems, Pleasanton, CA, USA) following the manufacturer’s instructions. Gene copies were represented as log 10 , and the primers involved in the quantitative PCR were shown in table S2. Establishing liquid coculture treatments of Tg and Bv : (i) Tg -WT+ Bv ; (ii) Δ Tgmfs4 + Bv ; and (iii) Δ Tgmfs4C + Bv . Tg (500 μl, 1 × 10 7 spores ml −1 ) and Bv [500 μl, optical density at 600 nm (OD 600 ) = 0.8] were inoculated in the WA liquid medium and incubated at 30°C with shaking at 170 rpm for 4 days. To determine the expression level of bacilysin production–related gene, the liquid culture broth from the entire coculture system was filtered daily to remove the Tg mycelium. Subsequently, Bv cells were collected by centrifugation at 12,000 rpm for 10 min. Total RNA was extracted from the Bv cells using a bacterial RNA kit (OMEGA, Biotek), and the RNA was then reverse transcribed into cDNA using the PrimeScript RT reagent kit (TaKaRa, Dalian, China). Relative quantification of genes related to bacilysin production was performed using the SYBR Premix Ex Taq II (Takara, Dalian, China) and a 7500 Real-Time PCR System (Applied Biosystems, Pleasanton, CA, USA). The primer sequences of the SA-inducible gene PR1 α, the JA-inducible plant defensin gene PDF 1, and the reference gene β-actin were used for gene expression analysis . Ten-day-old whole plant seedlings were collected and promptly cryopreserved in liquid nitrogen (fig. S12). Total RNA extraction was performed using the RNeasy Plant Mini Kit (Qiagen, Germany), and cDNA synthesis was completed using the PrimeScript RT Reagent Kit (RR036A, Takara, Dalian, China). The qRT-PCR was performed using the SYBR Premix Ex Taq II (Takara, Dalian, China) and a 7500 Real-Time PCR System (Applied Biosystems, Pleasanton, CA, USA). The primers involved in the quantitative PCR are shown in table S2.   The cocultivation of Bv and Tg strains was performed to elucidate the mechanism underlying their interaction, and samples were collected for transcriptional analysis of each strain. Briefly, 1-μl spore suspensions (1 × 10 7 spores ml −1 ) of Tg -WT and Tg -M33 were separately inoculated onto the center of the WA medium and incubated at 28°C for 1 day. Subsequently, Bv was inoculated at 2.5 cm away from the center of the medium, and 10 μl of Bv (1 × 10 6 CFU ml −1 ) was simultaneously inoculated on both sides. After incubation at 28°C for 5 days, the mycelia of Tg and bacterial cells of Bv were collected, flash frozen in liquid nitrogen, and stored at −80°C. The RNA from Tg mycelia samples was extracted using the RNeasy Plant Mini Kit (Qiagen, Germany), and the RNA from Bv cells was extracted using the bacterial RNA kit (OMEGA, Biotek). Subsequently, RNA integrity and contamination were assessed by 1% agarose gel electrophoresis. Qualified RNA samples were sequenced using the Illumina Novaseq6000 platform (LC-Bio Technology Co. Ltd., Hangzhou, China), and high-quality clean reads were filtered using Cutadapt (version 1.9). Next, the filtered reads were aligned to their respective reference genomes ( Tg : assembly accession GCA_002022785.1; Bv : assembly accession GCA_000685725.1) using the upgraded HISAT2 software, a successor to TopHat2. RNA sequencing data were normalized as FPKM (fragments per kilobase of exon model per million mapped reads).   Tg and Bv Gene deletion and reverse complementation mutants of Tg were obtained via a gene replacement strategy using the polyethylene glycol (PEG)–mediated protoplast transformation procedure as described by Li et al. . For the generation of strain Tgmfs4 - gfp , the DNA fraction of Tgmfs 4 was amplified with Tg DNA as a template, and the GFP fragment was amplified using plasmid pEGFP-N1 as a template (Clontech, USA). The DNA fragment of Tgmfs4 was ligated with the GFP fragment using the overlapping PCR technique based on the instructions of CloneAmp HiFi PCR Premix (Clontech, USA). Mutant of Tgmfs4 - gfp was constructed using the PEG-mediated protoplast transformation with hygromycin resistance cassette ( Hyg B) as the biomarker. Besides, mutants of Bv deficient in bacillomycin (Δ bmy ), surfactin (Δ srf ), fengycin (Δ fen ), difficidin (Δ dfn ), macrolactin (Δ mln ), bacillaene (Δ bae ), bacillibactin (Δ dhb ), and bacilysin (Δ bac ) were constructed with a marker-free strategy as described previously .   The extraction and detection of bacilysin were carried out as previously described with some modifications . Briefly, Bv was inoculated into the Perry and Abraham (PA) medium and incubated at 30°C for 48 hours. The culture was then centrifuged at 12,000 rpm for 10 min to remove bacterial cells. Ethanol (four times the volume of the supernatant) was added to precipitate impurities. After concentrating the supernatant 50-fold, it was passed through XAD1600 resin (particle size: 350 to 450 μm, Shanghai Yuanye Bio-Technology Co. Ltd.). The eluate was further processed using SP207 resin (Sepabeads; Mitsubishi Chemical Corporation, Japan), washed with 3 bed volumes (BV) of water, and then eluted with 3 BV of a 10% ethanol solution. The resulting eluate was freeze dried into a powder and stored at −80°C. For HPLC-MS analysis, freeze-dried samples were reconstituted in purified water and filtered through a 0.22-μm filter (Merck Millipore, German). HPLC was conducted using a Waters E2695 system with an XBridge C18 column (5 μm, 4.6 by 250 mm). The solvent system consisted of 40% acetonitrile in distilled water with 0.1% acetic acid (v/v). The flow rate was set at 0.6 ml min −1 , with a gradient program of 30 min: starting from 0% acetonitrile, increasing to 100% in 20 min, maintained for 5 min, and then decreasing to 5% in the final 5 min. The absorbance at 230 and 205 nm was monitored, and compounds with a retention time of 5.26 min were collected. The collected bacilysin was further identified using an HPLC-MS system (Agilent 1200-6410B), with mobile phase conditions identical to those used in HPLC and a molecular weight detection range of 100 to 400 Da. In the preparation of 15 N-bacilysin, Bv was cultured using ( 15 NH 4 ) 2 SO 4 as the sole nitrogen source instead of sodium glutamate in the PA medium. The culture conditions, isolation methods, and detection techniques were previously detailed. An HPLC system (Agilent 1260 Infinity II) was used to isolate 15 N-bacilysin at a flow rate of 1 ml min −1 . The elution peak at 4.45 min was collected and validated using an HPLC-MS system (Agilent 1200-6410B).   Tg To investigate the sensitivity of different strains to bacilysin, 1-μl spore suspension (1 × 10 7 spores ml −1 ) of Tg -WT and its mutants were inoculated into the PDA medium supplemented with bacilysin, resulting in a final concentration of 100 μg ml −1 . After 3 days, the colony diameters were measured. Simultaneously, the fresh mycelia were harvested from PDA plates covered with cellophane and quantified by weighing as a measure of biomass. In addition, the collected mycelia were assessed for the aminotransferase activity of Glms using the Glms detection kit (G0558F, Suzhou Grace Biotechnology Co. Ltd.). The entire process involved a control group in which bacilysin was not added the formula for calculating the relative inhibition rate of Tg was as follows: relative inhibition rate  = (mean diameter of control colonies − mean diameter of experimental colonies)/(mean diameter of control colonies − diameter of mycelial mass at inoculation) × 100%.   The fresh spore suspension of Tg -WT, Δ Tgmfs4 , and Δ Tgmfs4C were inoculated on the potato dextrose broth medium supplemented with bacilysin (100 μg ml −1 ) and incubated at 28°C for 3 days. Upon completion of the incubation, the mycelia were subsequently fixed overnight at 4°C in a solution containing 3% glutaraldehyde and 1% paraformaldehyde. Following fixation, the samples underwent dehydration using a graded series of ethanol and were then embedded in a mixture of embedding resin and acetone. Ultrathin sections were prepared using a Reichert ultramicrotome and examined using a transmission electron microscope (Hitachi HT7800). The GFP-labeled mutant ( Tgmfs4 - gfp ) was cultured on the PDA medium for 3 days, and the fresh mycelia were collected and stained with Cell Plasma Membrane Staining Kit (C1991S, Beyotime) according to the manufacturer’s instructions. Subsequently, the mycelia were washed three times with PBS buffer (pH 7.4) and imaged using a confocal fluorescence microscope (TCS SP8, Leica, Germany) using a 60x oil immersion objective. The channel of GFP was excited at 488 nm and emitted at 510 nm, whereas the red fluorescent probe was excited at 549 nm and emitted at 565 nm. Image processing was performed using the Fiji/ImageJ software.   The sequence of Tg MFS4 (OPB38031) was collected from the NCBI online site. Whereupon, the initial three-dimensional structure of Tg MFS4 was constructed using the AlphaFold2 . The structures of receptors and ligands were processed by using Schrödinger . The ligand amitraz was prepared by using the LigPrep module with OPLS3e force field . The sitemap tool was used to predict the binding sites for bacilysin , and the parameters of the grid box were determined based on the results generated by the sitemap. Docking was performed using the Glide program in extra precision mode . The optimal binding poses of various Tg MFS4 conformations with bacilysin were retained.   15 N-bacilysin uptake assay in X. laevis oocytes The CDS of Tg MFS4 was amplified and cloned into the X. laevis oocyte expression vector pT7Ts between the restriction sites Bgl II and Spe I and then linearized with Xba I. cRNA was synthesized in vitro using the Ambion mMessage mMachine kit (Ambion, AM1340). Oocytes were injected with Tg MFS4 cRNA (50 ng) or RNase-free water (50 nl) and incubated in an ND96 solution for 2 days. Subsequently, they were divided into seven groups and transferred to a series of solutions containing 15 N-bacilysin at concentrations of 0, 0.2, 0.5, 0.8, 1.2, 1.5, and 2.0 mM (dissolved in an ND96 solution). The experiment was conducted in triplicate, with each replicate comprising a minimum of three oocytes. After incubating at 18°C for 6 hours, the oocytes were washed with a nitrogen-free ND96 solution and subsequently desiccated at 75°C until reaching a constant weight. The dried oocytes were weighed, and the 15 N content was determined using a MAT253 isotope ratio mass spectrometer (Flash 2000 HT, Thermo Fisher Scientific, Germany). Absorption kinetics curves were plotted using the GraphPad Prism software (version 9.1.1), and the K m values were also calculated.   Bv Establishing liquid coculture treatments of Tg and Bv : (i) Tg -WT+ Bv ; (ii) Δ Tgmfs4 + Bv ; and (iii) Δ Tgmfs4C + Bv . Tg (500 μl, 1 × 10 7 spores ml −1 ) and Bv (500 μl, OD 600 = 0.8) were inoculated in the WA liquid medium and incubated at 30°C with shaking at 170 rpm for 4 days. Samples were obtained from the coculture system to determine the relative levels of bacilysin in both the mycelium and liquid culture broth. Specifically, mycelium from the coculture liquid culture broth was washed thrice with PBS buffer (pH 7.4), blotted to remove excess moisture, and weighed. The mycelium was then thoroughly ground in liquid nitrogen and dissolved in PBS buffer (pH 7.4). The mixture was centrifuged, and the supernatant was collected for further analysis. In addition, an equal volume of the liquid culture broth was collected daily from the coculture system. The broth was centrifuged to remove the Tg mycelium and Bv cells, and the supernatant was collected. The supernatants obtained from both methods were filtered through a 0.22-μm filter (Merck Millipore, German). S. aureus ATCC9144 was used as the indicator strain for detecting bacilysin via the paper disc agar diffusion method, and the bacilysin level was estimated as described previously . The biomass of Bv was determined by collecting a uniform sample from the coculture system daily, and then the sample was diluted and plated on an LB agar medium at 30°C for 18 hours. The plates were incubated, and the biomass was quantified by enumerating the CFU.   The rhizosphere soil collected from the third batch of pot experiments was subjected to shotgun metagenomic sequencing, yielding an average of 10 giga–base pairs per sample. The extraction and quality control of rhizosphere soil DNA were performed in accordance with the methods described above. Library preparation was carried out according to the standard Illumina protocol. Briefly, DNA was isolated using ultrasonication, and a pooled library containing equimolar amounts of barcoded fragments ranging from 350 to 500 base pairs (bp) was prepared. This library was then sequenced using the Illumina NovaSeq 6000 platform, targeting 150-bp paired-end reads. The raw sequence data underwent trimming, filtering, and assembly using MEGAHIT, whereas contigs longer than 300 bp were further subjected to gene prediction and annotation. The assembled contig sequences were subjected to open reading frame (ORF) prediction using Prodigal. Translations were performed for predicted ORFs longer than 100 bp, and a nonredundant gene catalog was constructed based on sequence identity of 95% and coverage of 90%. Gene abundance in each sample was normalized using RPKM (reads per kilobase million). Representative sequences from the nonredundant gene set were aligned with the NCBI NR database using the Diamond blastp program, selecting annotations with e values < 1 × 10 −5 . For functional annotation, sequences were annotated against the KEGG and the Carbohydrate-Active Enzymes Database (CAZy) with an e value cutoff of 1 × 10 −5 .   All statistical analyses were performed using IBM SPSS 22 (IBM Corporation, New York, USA) and R software (version 3.5.0). The significance of differences among multiple groups, excluding the sequencing data, was determined by one-way analysis of variance (ANOVA) (with Duncan’s multiple range test). The significance between the two groups was evaluated using a two-sided Student’s t test, and the resulting P value was adjusted for multiple comparisons using the FDR (false discovery rate) correction. In metagenomic data analysis, the Wilcoxon rank sum test (for two groups) or Kruskal-Wallis test (for three groups) was used to perform hypothesis testing on functional abundance data to obtain P values. In this study, a P value of <0.05 indicated a statistically significant difference. The permutational multivariate analysis of variance (PERMANOVA) (Adonis, with Bray-Curtis transformed data, permutation = 999) was used to determine whether there were significant differences in gene functions annotated through the KEGG or CAZy databases among different treatments. PCoA plots based on the Bray-Curtis similarity matrix were generated using the “ggplot2” and “vegan” packages. In addition, linear regression was performed using R, and the “ggpmisc” package was used to report R 2 and P values to determine the relationship between the expression of the CAZyme family genes and the activation of the SA signaling pathway.   