The offensive role of the Bacillus extracellular matrix in driving metabolite-mediated dialogue and adaptive strategies with pathogenic fungi

The offensive role of the Bacillus extracellular matrix in driving metabolite-mediated dialogue and adaptive strategies with pathogenic fungi | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results The offensive role of the Bacillus extracellular matrix in driving metabolite-mediated dialogue and adaptive strategies with pathogenic fungi View ORCID Profile Alicia I. Pérez-Lorente , View ORCID Profile Carlos Molina-Santiago , View ORCID Profile David Vela-Corcía , View ORCID Profile Paolo Stincone , View ORCID Profile Jesús Hierrezuelo , Montserrat Grifé , Abzer K. Pakkir Shah , Antonio de Vicente , View ORCID Profile Daniel Petras , View ORCID Profile Diego Romero doi: https://doi.org/10.1101/2025.02.06.636830 Alicia I. Pérez-Lorente 1 Instituto de Hortofruticultura Subtropical y Mediterránea ‘‘La Mayora’’, Universidad de Málaga-Consejo Superior de Investigaciones Científicas (IHSM-UMA-CSIC) 2 Departamento de Microbiología, Universidad de Málaga, Bulevar Louis Pasteur 31 (Campus Universitario de Teatinos) , Málaga, 29071, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Alicia I. Pérez-Lorente Carlos Molina-Santiago 1 Instituto de Hortofruticultura Subtropical y Mediterránea ‘‘La Mayora’’, Universidad de Málaga-Consejo Superior de Investigaciones Científicas (IHSM-UMA-CSIC) 2 Departamento de Microbiología, Universidad de Málaga, Bulevar Louis Pasteur 31 (Campus Universitario de Teatinos) , Málaga, 29071, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Carlos Molina-Santiago David Vela-Corcía 1 Instituto de Hortofruticultura Subtropical y Mediterránea ‘‘La Mayora’’, Universidad de Málaga-Consejo Superior de Investigaciones Científicas (IHSM-UMA-CSIC) 2 Departamento de Microbiología, Universidad de Málaga, Bulevar Louis Pasteur 31 (Campus Universitario de Teatinos) , Málaga, 29071, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for David Vela-Corcía Paolo Stincone 3 University of Tuebingen, CMFI Cluster of Excellence, Interfaculty Institute of Microbiology and Infection Medicine , Tuebingen, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Paolo Stincone Jesús Hierrezuelo 1 Instituto de Hortofruticultura Subtropical y Mediterránea ‘‘La Mayora’’, Universidad de Málaga-Consejo Superior de Investigaciones Científicas (IHSM-UMA-CSIC) 2 Departamento de Microbiología, Universidad de Málaga, Bulevar Louis Pasteur 31 (Campus Universitario de Teatinos) , Málaga, 29071, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Jesús Hierrezuelo Montserrat Grifé 1 Instituto de Hortofruticultura Subtropical y Mediterránea ‘‘La Mayora’’, Universidad de Málaga-Consejo Superior de Investigaciones Científicas (IHSM-UMA-CSIC) 2 Departamento de Microbiología, Universidad de Málaga, Bulevar Louis Pasteur 31 (Campus Universitario de Teatinos) , Málaga, 29071, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abzer K. Pakkir Shah 3 University of Tuebingen, CMFI Cluster of Excellence, Interfaculty Institute of Microbiology and Infection Medicine , Tuebingen, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Antonio de Vicente 2 Departamento de Microbiología, Universidad de Málaga, Bulevar Louis Pasteur 31 (Campus Universitario de Teatinos) , Málaga, 29071, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Daniel Petras 3 University of Tuebingen, CMFI Cluster of Excellence, Interfaculty Institute of Microbiology and Infection Medicine , Tuebingen, Germany 4 University of California Riverside, Department of Biochemistry , Riverside, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Daniel Petras For correspondence: diego_romero{at}uma.es dpetras{at}ucr.edu Diego Romero 1 Instituto de Hortofruticultura Subtropical y Mediterránea ‘‘La Mayora’’, Universidad de Málaga-Consejo Superior de Investigaciones Científicas (IHSM-UMA-CSIC) 2 Departamento de Microbiología, Universidad de Málaga, Bulevar Louis Pasteur 31 (Campus Universitario de Teatinos) , Málaga, 29071, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Diego Romero For correspondence: diego_romero{at}uma.es dpetras{at}ucr.edu Abstract Full Text Info/History Metrics Preview PDF Abstract Bacterial□fungal interactions have traditionally been attributed to secondary metabolites, but the role of the bacterial extracellular matrix (ECM) in shaping these relationships has remained unclear. Here, we demonstrate that the ECM protein TasA is a key mediator in the antagonistic interaction between Bacillus subtilis and Botrytis cinerea . TasA enables Bacillus to tightly adhere to fungal hyphae, disrupts the β-glucan layer, and compromises fungal cytoskeletal integrity synergistically with fengycin, which causes cytological damage. Additionally, TasA acts as a carrier for bacillaene, amplifying its fungistatic activity. In response, B. cinerea mounts a multifaceted defense, enzymatically degrading fengycin, producing antibacterial oxylipins, and activating adaptive programs such as hyphal branching and chlamydospore formation. Our findings reveal the previously unrecognized role of ECM components in fungal suppression and the modulation of fungal adaptive responses. This study reveals the complex interplay between microbial aggression and defense, providing new insights into the ecological dynamics of microbial competition and coexistence. Introduction Microbial interactions shape microbial community dynamics and impact ecosystems, particularly within the plant microbiome 1 – 3 . These interactions range from cooperative to competitive and are often mediated by secondary metabolites, signaling molecules, and biofilms that influence plant health 4 . Beneficial microbes support nutrient acquisition, plant defense, and stress tolerance but compete for limited resources 5 , 6 with detrimental pathogens, including fungal species such as Botrytis cinerea 7 – 10 . Bacillus subtilis is a gram-positive bacterium known for its ability to promote plant growth and effectively antagonize fungal pathogens such as B. cinerea , the causative agent of gray mold disease, which significantly impacts crops and leads to economic losses 7 – 10 . The antagonistic activity of B. subtilis stems from its production of antifungal lipopeptides, such as fengycin and surfactin, and apparently robust biofilm formation capacity 11 . The extracellular matrix (ECM) of B. subtilis comprises mainly but not exclusively exopolysaccharides (EPSs), TasA, TapA, and BslA 12 , 13 , 14 , which provide structural integrity and participate in interactions with plants; bacteria such as Pseudomonas species 15 , 16 ; and fungal species such as Aspergillus niger 17 , 18 or Rhizophagus irregularis 19 . However, the exact role of the ECM in interactions with phytopathogenic fungi remains poorly understood. Traditionally, the B. subtilis–B. cinerea interaction has been viewed as being statically antagonistic. However, microbial interactions are dynamic, with both organisms undergoing metabolic and transcriptomic changes 20 . While B. subtilis suppresses B. cinerea growth, a portion of the fungal population adapts and survives 21 – 23 . This study demonstrates the multifaceted involvement of the ECM, beyond adhesion, in this interkingdom chemical crosstalk and in antagonistic interactions, with TasA and fengycin as key components driving fungal modulation and ecological balance within microbial ecosystems. Results The Bacillus ECM mediates adhesion and bidirectional damage in the interaction with Botrytis Microbial interactions are inherently dynamic and are shaped by evolving exchanges between organisms and their environment. This ecological fluidity is especially pronounced in antagonistic or competitive relationships within microbial communities, where organisms constantly adapt to maintain ecological balance or eliminate competitors 24 – 27 . Historically, the interaction between B. subtilis and B. cinerea has been described as unidirectionally antagonistic, driven by the ability of B. subtilis to suppress fungal growth through the secretion of antifungal compounds, including plipastatins and surfactins 28 – 30 . However, our observations revealed a more complex and dynamic interaction over time. In the short term, Bacillus inhibited Botrytis growth; however, some of the fungal population survived after one week and even one month of interaction ( Fig. 1A ), an observation that suggests the existence of a defense mechanism activated by Botryti s to persist in a chemically hostile environment. Moreover, rather than simply being the attacker, the Bacillus population also experiences significant mortality during this interaction, particularly the bacterial cells that are in close contact with fungal hyphae ( Fig. 1B ). These findings, indicative of bidirectional antagonism, challenge the conventional view of this interaction as strictly unidirectional and point toward a more balanced relationship wherein both organisms may employ adaptive defense mechanisms. Indeed, in the long term (one week), the total Bacillus population was comparatively larger than that in Bacillus monoculture ( Fig. 1C ), despite the higher percent mortality of Bacillus cells attached to Botrytis hyphae. This result indicates that individual bacterial cells are more likely to die when they are in close contact with Botrytis , although the overall Bacillus population increases during the interaction, possibly due to a beneficial environmental niche or nutrient availability created by the presence of the fungus. Download figure Open in new tab Figure 1. Bidirectional damage and adaptive responses in the interaction between B. subtilis and B. cinerea . A) Representative confocal microscopy images of B. cinerea after coculture with wild-type B. subtilis for one week. B) Left : confocal microscopy images showing B. subtilis mortality near B. cinerea hyphae after 24 h, visualized using live/dead staining, highlighting significant bacterial cell death near fungal structures, indicative of bidirectional aggression. Right: transmission electron microscopy images showing B. cinerea cell leakage and B. subtilis ghost cells surrounding fungal hyphae. C) Quantification of the total B. subtilis population in coculture after one week, demonstrating an overall increase compared with that of the monoculture. D) Representative images showing impaired adhesion of B. subtilis mutants lacking tapA or tasA to B. cinerea hyphae. E) Quantification of ROS levels in B. cinerea during coculture with wild-type B. subtilis (Bsub), mutants lacking structural and nonstructural ECM components (Δpps, ΔtasA, ΔtapA, Δeps, and ΔbslA) and double mutants (Δpps Δeps and ΔppsΔtasA). F) Fungal growth of B. cinerea during coculture ON assays. G) Quantification of the percentage of B. subtilis cell death in monoculture and during coculture with B. cinerea , including comparisons with the ΔtasAΔpps mutant strain, showing the influence of these ECM components on fungus-induced bacterial mortality. Scale bars for confocal microscopy represent 20 µm, and scale bars for TEM images represent 2 µm. The whisker plot shows all the measurements (pink dots), medians (black line), and minimum and maximum values (whisker ends). Statistical analyses were performed on at least three biological replicates. Statistical significance was assessed using a t test, with two asterisks indicating significant differences at P < 0.01. To investigate the mechanism underlying the dynamic interaction between Bacillus and Botrytis , we initially examined the transcriptomic profiles of both organisms after six hours of coculture. Dual RNA-seq analyses revealed deregulation of key pathways involved in glutathione metabolism, secondary metabolite biosynthesis, or phospholipid metabolism in Botrytis ( Extended Data Fig. 1A ). Specifically, we observed the overexpression of Botrytis genes related to the fungal matrix, microbody lumen, cell wall, peroxisomes, plasma membrane, and peroxisomal matrix ( Extended Data Fig. 1B). These results suggest the activation of a defensive strategy to preserve structural integrity and manage putative cellular damage associated with oxidative stress. Moreover, we observed notable downregulation of genes associated with the cytoskeleton, further indicating potential reorganization or damage of the internal structures of Botrytis due to the interaction with Bacillus ( Extended Data Fig. 1C ). In the interaction, genes involved in secondary metabolite production ( Extended Data Fig. 2 ) and genes related to Bacillus ECM biosynthesis (TasA, TapA, EPSs, and BslA) were upregulated in the Bacillus population. These results, along with the relevance of the ECM in Bacillus ecology and communication with other biological entities, led us to investigate the role of structural ECM components in the colonization of fungal hyphae and the antagonism toward Botrytis . Adhesion to hyphae was clearly impaired in mutants lacking tapA or tasA ( Fig. 1D ). Interestingly, the removal of any ECM component, including TasA, TapA or EPSs but not BslA, resulted in a reduction in reactive oxygen species (ROS) levels in Botrytis ( Fig. 1E ). However, no reduction in the mortality rate or fungal biomass of Botrytis during coculture with ΔtapA or ΔtasA strains was detected ( Fig. 1F ), likely because of the higher levels of fengycin production reported for the ΔtasA mutant 31 . The plipastatin produced by B. subtilis is classified in the fengycin family because of its similar structure 32 . Therefore, herein, we will refer to both as fengycin, including when discussing Bacillus- derived compounds. The lack of adhesion observed in the ΔtapA mutant, coupled with reduced ROS levels, was intuitively attributed to the inability of this mutant to efficiently expose TasA on the cell surface 13 , 33 . Compared with Bacillus WT cells, the Δpps mutant, unable to synthesize fengycin, triggered lower levels of ROS production in Botrytis ( Fig. 1E ). The ΔtasAΔpps double mutant strain lost practically all of its antifungal activity, which correlated with levels of ROS comparable to those in untreated Botrytis hyphae ( Fig. 1E , 1F ). Therefore, TasA and fengycin seem to synergistically influence the antagonistic activity of Bacillus cells toward Botrytis . According to our initial observation of mutual aggression, coinoculation of Botrytis with the ΔtasAΔpps double mutant strain completely abolished the mortality of Bacillus induced by Botrytis ( Fig. 1G ), a finding that supported a fungal offensive response activated upon perception of the ECM component TasA or fengycin. Lysophosphatidylcholine and ROS accumulation in Botrytis hyphae is correlated with the presence of TasA Considering the relevance of the ECM in the antagonistic interaction of Bacillus and Botrytis and the differences in Bacillus mortality on the basis of the presence of certain ECM components, we aimed to elucidate potential metabolic changes that might modulate the interaction between these two microorganisms. We conducted a time-course comparative analysis of Bacillus strains (WT and derivative ECM mutants) and Botrytis metabolomes in monocultures and pairwise interactions at 6, 24, and 48 h. Non-targeted metabolomics analysis revealed that multiple metabolites, including glycerophosphocholines, glycerophosphoethanolamines, cyclic lipopeptides, dipeptides, tripeptides, and alkaloids, were differentially accumulated during the interaction ( Extended Data Fig. 3A ). Bacillus notably presented elevated levels of cyclic lipopeptides and glycerophosphoethanolamines, both of which are known for their antagonistic activity and their role in membrane stress responses 7 , 34 , 35 . In contrast, changes in glycerophosphocholine levels in Botrytis indicated active membrane remodeling in response to Bacillus , potentially aiding in adaptation to environmental stresses 36 – 40 . Additionally, the accumulation of dipeptides, tripeptides, and alkaloids, which are typically associated with stress and intercellular signaling, suggested a reorganization of metabolic pathways, potentially influencing the growth and survival of both organisms ( Extended Data Fig. 3A, Extended Data Fig. 3B ). Principal component analysis of the cell fraction after 24 h of interaction revealed distinct clustering patterns between Botrytis treated with the Bacillus WT or single ECM mutants. Consistent with the proposed prominent role of TasA and fengycin in the antagonistic activity, the metabolomes of Botrytis cocultured with the Δpps, ΔtasA, or ΔtapA mutants clustered closely with those of Botrytis grown in monoculture, whereas the Bacillus WT and mutant lacking EPSs formed a separate cluster ( Fig. 2A ). These results suggest that the interaction with Bacillus WT or the Δeps mutant induces substantial shifts in the B. cinerea metabolome. In contrast, the metabolome of Botrytis treated with the ΔtapA, ΔtasA, or Δpps mutant showed minimal changes and closely resembled that observed without treatment, indicating the critical contribution of TasA and fengycin in driving the metabolic modulation of Botrytis during the interaction. Download figure Open in new tab Figure 2. ECM structural components of B. subtilis drive lysophosphatidylcholine accumulation and oxidative stress in B. cinerea . A) PCA 2D score plot of the metabolome of the B. cinerea cell fraction after 24 h of coculture with wild-type B. subtilis or ECM mutants (Δpps, ΔtasA, ΔtapA, and ΔEPS). B. cinerea cocultured with the Δpps, ΔtasA, or ΔtapA mutant clustered closely with the B. cinerea monoculture control, whereas B. cinerea cocultured with wild-type B. subtilis and the Δeps mutant formed distinct clusters. The percentage of variation explained by each principal component is indicated on the axes. B) Molecular family of features differentially abundant in the cell fraction of B . cinerea after 48 h of treatment with wild-type B. subtilis or ECM mutants (Δpps, ΔtasA, ΔtapA, and ΔEPS), annotated as lysophoshphocholines according to NPClassifier. The chemical structures of annotated features and their average masses on the basis of spectral matches to GNPS libraries are also represented for the corresponding molecular families. Pie charts indicate the peak abundance of each metabolite under the corresponding conditions. The node shape indicates the level of identification according to ref. 101 . Lyso-PC accumulation is significantly reduced in interactions with ΔtasA or ΔtapA mutants, suggesting a dependence on ECM structural components. C) ROS levels in B. cinerea cultures treated with 150 µM commercial lyso-PC, confirming its role in triggering oxidative stress. D) Fungal growth of B . cinerea treated with 150 µM commercial lyso-PC and control Botrytis , showing that lyso-PC-induced ROS do not lead to B. cinerea growth inhibition. The whisker plot shows all the measurements (pink dots), medians (black line), and minimum and maximum values (whisker ends). For all experiments, the results of at least three biological replicates are shown. Statistical significance was assessed via a t test. E) Stacked bar plots represent the relative abundance of chemical classes for the top 250 features significantly increased in the B. cinerea cell fraction after 24 h of treatment with TasA, fengycin, or wild-type B. subtilis , compared with untreated B. cinerea . The features were ranked using volcano plots generated in MetaboAnalyst. Metabolite chemical class prediction was performed using SIRIUS, and the metabolites were classified with NPClassifier. Scale bars represent 20 µm. Further analysis of the metabolomes revealed notable accumulation of lysophosphatidylcholine (lyso-PC) in the Botrytis cell fraction after coculture with Bacillus . Lyso-PC is a lipid signaling molecule associated with ROS generation, cellular damage and inflammatory processes in other biological systems 40 – 45 . Interestingly, lyso-PC was practically absent in Botrytis treated with the ΔtasA or ΔtapA mutant, a finding that led us to correlate the accumulation of lyso-PC with the presence of Bacillus ECM components ( Fig. 2B ). We hypothesize that the accumulation of lyso-PC might correlate with the levels of ROS accumulated in Botrytis during the interaction ( Fig. 1E ). Commercial lyso-PC exogenously added to Botrytis cultures triggered significant increases in ROS levels ( Fig. 2C , Extended Data Fig. 3C ), confirming that lyso-PC contributes to the oxidative stress observed during the Bacillus-Botrytis interaction, a physiological response triggered by the presence of the Bacillus ECM structural component TasA. However, the level of ROS produced after the addition of lyso-PC did not appear to lead to fungal death or growth inhibition ( Fig 2D ), suggesting that lyso-PC may function primarily in signaling rather than inhibiting the growth of Botrytis . According to this finding, the external addition of purified TasA to Botrytis reproduced the accumulation of ROS observed in previous coculture experiments and promoted the accumulation of lyso-PC in Botrytis cells. Fengycin also triggered ROS accumulation in Botrytis hyphae; however, the level of lyso-PC accumulation did not increase significantly. To better understand the specific metabolic changes triggered by the most active ECM components, we analyzed the metabolome of B. cinerea treated with purified TasA or fengycin. Chemical class analysis of non-targeted metabolomics data with CANOPUS 46 revealed that during the interaction of Botrytis with Bacillus , glycerophosphocholines, dipeptides, tripeptides, cyclic peptides, and alkaloids accumulated after 24 h, as shown in Extended Data Fig. 3B . Fengycin-treated Botrytis exhibited accumulation of dipeptides, tripeptides and glycerophosphocholines, which is consistent with its membrane-disrupting activity. Similarly, TasA-treated Botrytis presented minor accumulation of dipeptides and tripeptides compared with fengycin-treated Botrytis , as well as pronounced accumulation of alkaloids, particularly piperazine and pyridine alkaloids ( Fig. 2D ). These findings suggest that dipeptides and tripeptides accumulate in the presence of both ECM components. Glycerophosphocholine production is driven by fengycin, and alkaloid production is associated with TasA. This differential response of Botrytis at the metabolic level led us to investigate specific physiological and anatomical damage induced by these molecules produced by Bacillus . TasA modifies the structural integrity of Botrytis hyphae, compromising virulence Botrytis accumulates ROS in response to the presence of Bacillus ECM; however, evident inhibition of fungal growth or accumulation of lyso-PC was observed in the presence of fengycin or TasA, respectively. The addition of purified TasA to Botrytis cultures promoted a curling morphology of hyphae ( Fig. 3A ), a macroscopic phenotype reasonably associated with disorganization of the fungal cell surface. To examine the hypothetical impact of TasA on the biophysical properties of the fungal matrix, we conducted magnetic resonance imaging (MRI) analyses to assess T2 relaxation times across different colony regions, which reflect water content and diffusion. High-resolution images of untreated Botrytis macrocolonies revealed significant heterogeneity, with varying water contents and relatively high T2 relaxation times in the center of the colonies. In contrast, Botrytis treated with TasA presented a homogeneous distribution, with uniformly lower T2 times. This finding suggested the existence of an intact matrix in Botrytis colonies that is able to retain water within the colony and that disruption of matrix integrity in the presence of TasA reduces water retention and thus structural organization ( Fig. 3B ). Download figure Open in new tab Figure 3. TasA and fengycin differentially impact B. cinerea physiology. A) Macroscopic phenotypic analysis showing the curling morphology of B. cinerea hyphae upon treatment with purified TasA, likely due to disorganization of the fungal cell surface. Scale bars represent 20 µm. B) Magnetic resonance imaging-based T2 relaxation time analysis showing that untreated B. cinerea macrocolonies retain water heterogeneously, with higher T2 times at the colony center. In contrast, TasA-treated colonies presented a uniform distribution of water content and relatively low T2 relaxation times, suggesting disruption of fungal matrix integrity and reduced water retention. C) Immunocytochemistry using anti-TasA antibodies demonstrating extensive decoration of fungal hyphae after B. cinerea treatment with 3 µM purified TasA. Scale bars represent 20 µm. D) Transmission electron micrograph of negatively stained thin sections of Botrytis hyphae with immunogold labeling revealing TasA accumulation in the outer and inner layers of the fungal cell wall, which is primarily composed of chitin and chitosan. The scale bar represents 1 μm for the image on the left and 0.2 μm for the zoomed-in image on the right. E) TEM images of untreated hyphae display a sharply defined β-glucan layer outside the cell wall (left), whereas TasA-treated hyphae exhibit disorganized β-glucan structures (right). The scale bar represents 2 μm. F) Tubulin staining of B. cinerea hyphae revealed significantly fewer tubulin foci in TasA-treated samples than in control samples, indicating cytoskeletal disorganization. G) Confocal microscopy images of ROS levels in 3 μM TasA-treated B. cinerea hyphae, obtained using double staining with FM4-64 to stain the membrane, and TEM images showing ultrastructural damage, including autophagosome formation, in TasA-treated Botrytis . Scale bars: 20 μm for confocal microscopy images and 2 μm for TEM images. H) In planta experiments showing reduced lesion size and fungal colonization in plants treated with TasA compared with those in untreated controls. The whisker plot shows all the measurements (pink dots), medians (black line), and minimum and maximum values (whisker ends). For all experiments, the results from at least three biological replicates are shown. Statistical significance was assessed via a t test, with quadruple asterisks indicating significant differences at P < 0.0001. I) Brightfield microscopy of B. cinerea hyphae demonstrating extensive chlamydospore formation upon fengycin treatment (lower panel) compared with the control treated with methanol (upper panel). Scale bars equal 20 µm. J) Volcano plot of DEGs identified by RNA-seq in B. cinerea treated with fengycin for 6 hours and untreated hyphae. P values were calculated on the basis of the Fisher method using nominal P values provided by edgeR and DEseq2. The dashed lines represent the thresholds defined for P (horizontal) and the fold change (vertical) for a gene to be considered a DEG. Genes related to virulence and detoxification pathways are labelled as follows: MFS (major facilitator superfamily), gstII (glutathione S-transferase), Bcprd11 (peroxidase, involved in the response to oxidative stress), Bcprm1 (serine peptidase, involved in fungal survival), Bcnqo1 (oxidoreductase) and Bcbot1 (botrydial biosynthesis gene, involved in secondary metabolism). The relevance of TasA for the cellular attachment of Bacillus cells to Botrytis hyphae led us to initially evaluate the role of this protein in the disorganization of the fungal cell wall. Immunocytochemistry analysis using anti-TasA antibodies revealed that the fungal hyphae were extensively decorated with the fluorescent signal associated with TasA ( Fig. 3C ). Transmission electron microscopy (TEM) analysis of thin sections of Botrytis hyphae and immunogold labeling confirmed the accumulation of TasA-related signals in the outer and inner fungal cell wall layers, which contained mainly chitin and chitosan, the two major components of the fungal cell wall ( Fig. 3D ). TEM control images of B. cinerea are shown in Extended Data Fig. 4A . The affinity of TasA for both chitin and chitosan was biochemically demonstrated via polysaccharide affinity assays ( Extended Data Fig. 4B ). In the TEM analysis, however, any alteration in the chitin-chitosan layer was disregarded, and noticeable disorganization of the β-glucan layer of the fungal cell wall was observed following treatment with TasA, which, in untreated hyphae, appeared as a sharply defined electrodense line outside the less electrodense chitin-chitosan layer ( Fig. 3E ). Fungal shape and structural integrity are largely regulated by the cytoskeletal element actin filaments and microtubules 47 , and disruption of the cytoskeleton may induce a curling morphology. Therefore, we reasoned that disorganization of the β-glucan layer induced by TasA might cause cytoskeleton dysfunction, weakening the structural integrity of the fungal cell wall and compromising the ability of Botrytis to maintain its typical hyphal architecture and function. Diverse lines of experimental evidence support this hypothesis: i) downregulation of genes related to cytoskeletal organization in transcriptomic analysis of TasA-treated Botrytis hyphae ( Extended Data Fig. 4C ), ii) a significant decrease in tubulin foci of hyphae of Botrytis treated with TasA upon specific staining of the cytoskeleton with a tubulin tracker ( Fig. 3F , Extended Data Fig. 4D ), and iii) cytoplasmic damage characterized by autophagosome formation observed via TEM analysis of thin sections of Botrytis hyphae ( Fig. 3G ). Collectively, these findings demonstrate that in addition to facilitating the physical contact of Bacillus cells with Botrytis hyphae, TasA disrupts the physical and molecular architecture of Botrytis cells. These results confirm the active participation of TasA in the arsenal of molecules secreted by Bacillus to efficiently antagonize Botrytis. The failure of EPSs to induce significant changes at the ultrastructural level ( Extended Data Fig. 5A ) is likely related to the limited access of this bacterial polymer to the fungal cell wall or membrane. However, the increase in ROS levels suggested that Botrytis can sense the presence of EPS, most likely triggering a differential response to TasA ( Extended Data Fig. 5B ). We further demonstrated in an in vivo plant model (melon) that the structural disorganization and morphological changes triggered by TasA translated into a reduced ability of Botrytis to induce symptoms in leaves ( Fig. 3H ). Fengycin is known to target fungal membranes, and consistent with this, the cytoplasmic disorganization of Botrytis hyphae was more pronounced than that induced by TasA. The most noticeable cytological alterations were autophagosome formation ( Fig. 3G ), plasmolysis, and extensive formation of chlamydospores ( Fig. 3I ), which are differentiated fungal cells associated with resistance to external aggressions 48 – 50 . Consistent with these cellular reorganizations, transcriptomic analysis of Botrytis treated with fengycin after 6 h revealed upregulation of virulence-related genes and detoxification pathways, particularly those associated with glutathione, oxidoreductases, and major facilitator superfamily (MFS) transporters, indicating the activation of a chemical defense mechanism oriented toward mitigating the oxidative stress and cytological damage inflicted by fengycin ( Fig. 3J ). All the ROS quantifications for B. cinerea with purified ECM components are provided in Extended Data Fig. 4D . Antibacterial oxylipins are differentially produced by Botrytis in response to TasA or fengycin We determined how Botrytis hyphae (cell fraction, Extended Data Fig. 2E ) respond differentially metabolically and anatomically to TasA or fengycin, two active Bacillus ECM components involved in the interaction. However, the factors delivered by B. cinerea that are lethality to B. subtilis cells ( Fig. 1B ) remain elusive. To illuminate the change in metabolite production associated with hyphal damage in B. cinerea , we performed non-targeted metabolomics analyses of the Botrytis supernatant at different time points (6, 24, and 48 h) after treatment with purified TasA or commercial fengycin. Consistent with the morphological changes ( Fig. 3G ), our data revealed that TasA and fengycin differentially impacted Botrytis physiology, the metabolome, and most likely the fungal lifestyle. Fengycin treatment led to substantial secretion of metabolites by Botrytis into the media, particularly after 24 h, and TasA-treated Botrytis reduced the overall accumulation of metabolites ( Extended Data Fig. 6 ). The pool of accumulated metabolites in the fungal supernatant fraction under both treatments included oxygenated fatty acids or oxylipins, especially after treatment with fengycin ( Fig. 4A ). Oxylipins are derived from linoleic and linolenic acids and are known as developmental regulators or mediators of interspecies communication across various biological systems, including mammals, bacteria, fungi, and plants 51 – 53 . In filamentous fungi, oxylipins constitute an essential defensive mechanism for fungal adaptation to the environment 54 – 56 . The linolenic-derived oxylipins detected included stearidonic acid (SDA), 9-OxoOTrE, trans-EKODE, 13-OxoODE and 9S-HOTrE, and the linoleic-derived epoxides detected included 12,13-EpOME and 9(10)-EpOME ( Extended Data Fig. 7 ). One of the most abundant oxylipins, SDA, exhibited potent antibacterial effects, significantly contributing to B. subtilis mortality at concentrations as low as 6 µg/mL. This finding endorses SDA as a potential key factor in the defensive arsenal of Botrytis activated upon the differential cellular aggression inflicted by the Bacillus ECM molecule fengycin and, to a lesser extent, TasA. Download figure Open in new tab Figure 4. Counteracting B. subtilis aggression: oxylipin production and fengycin enzymatic degradation. A) Molecular families of features differentially abundant in the supernatant fraction of B. cinerea after 24 h of treatment with 10 μM fengycin or no treatment. The chemical structures of annotated features and their average masses on the basis of spectral matches to GNPS libraries are also represented for the corresponding molecular families. Pie charts indicate the peak abundance of each metabolite under the corresponding conditions. The node shape indicates the level of identification according to ref. 101 . The node border color indicates the compound name according to the GNPS library. B) Representative confocal microscopy images of untreated B. cinerea (left) or B. cinerea treated with 1 µg/mL commercial SDA (right), triggering hyperbranching. Scale bars equal 10 µm. C) Molecular family analysis of fengycin and its structural variants in B. cinerea supernatants after the addition of 10 µM fengycin, which were sampled at 6, 24, and 48 h. Pie charts represent the mean peak abundance of metabolites at each time point, with node shapes indicating the level of metabolite identification. The arrows indicate the chemical directionality of the modifications observed, with arrow sizes corresponding to ChemProp scores. The labels above the arrows reflect the mass differences between related metabolites. D) Floating bar plots showing the peak abundances of four selected putative degradation products of fengycin in B. subtilis cultures growing alone and in coculture with B. cinerea at 6, 24, and 48 h. E) Left: Quantification of ROS levels in B. cinerea after treatment with fengycin preincubated in PDB medium for 24 h versus fengycin preincubated with Botrytis for the same amount of time. Lower ROS levels were detected in B. cinerea treated with fengycin preincubated with B. cinerea , suggesting neutralization of fengycin activity. The whisker plot shows all the measurements (pink dots), medians (black line), and minimum and maximum values (whisker ends). For all experiments, the results from at least three biological replicates are shown. Statistical significance was assessed via a t test, with quadruple asterisks indicating significant differences at P < 0.0001. Right: Confocal microscopy images showing cytological damage and chlamydospore formation in B. cinerea treated with fengycin preincubated with PDB as a control, whereas B. cinerea treated with fengycin preincubated with B. cinerea presented no apparent cytological damage. Scale bars equal 20 µm. In addition to their antibacterial activity, fungus-derived oxylipins seem to mediate intrapopulation communication within fungi. Accordingly, SDA exogenously added to Botrytis culture induced hyphal hyperbranching ( Fig. 4B ). Hyperbranching in filamentous fungi is perceived as an ecological strategy that enhances the ability of fungi to explore and capture nutrients, as well as provides protection against threats. This behavior is part of an interference competition strategy that increases the likelihood of survival and fitness in resource-limited environments 57 . Therefore, the production of these oxylipins by Botrytis seems to exemplify a dual function: damaging competing microbes such as Bacillus while promoting alternative adaptive growth strategies. Botrytis enzymatically degrades fengycin, neutralizing its antifungal activity Two alternative strategies could explain the long-term resistance of Botrytis to the physicochemical effects of Bacillus : i) antagonism toward Bacillus cells ( Fig. 1B ) and ii) neutralization of the toxicity of the antifungal molecules produced by Bacillus . We have proposed oxylipins as one type of antibacterial agents secreted by Botrytis in response to the action of fengycin, with a deleterious effect on Bacillus cells ( Fig. 4A ); thus, we focused on demonstrating the implications of the second strategy. Considering the relevance of fengycin in the antifungal activity of B. subtilis , we analyzed the degradation of this lipopeptide during the interaction. By leveraging non-targeted metabolomics data from serial incubation with fengycin, we analyzed proportionality changes (anticorrelation behavior) in chemically related metabolites through molecular networking and the ChemProp2 computational tool 58 . This analysis revealed a significant reduction in fengycin levels in the cell-free supernatant 24 to 48 h after the addition of commercial fengycin to Botrytis cultures. This reduction in the original fengycin level was accompanied by the accumulation of specific structural variants of fengycin with m/z values of 762.9354, 755.9276, 762.4341 and 755.4263, likely representing degradation products ( Fig. 4C ). Similar dynamics were observed for native fengycin produced by Bacillus upon interaction with Botrytis , indicating the ability of Botrytis to chemically modify fengycin ( Fig. 4D ). To evaluate the biological implications of this degradation, Botrytis was incubated with commercial fengycin for 24 h, after which the supernatant was added to fresh Botrytis cells. Fengycin exposed to Botrytis lost its antifungal activity, as demonstrated by the absence of fungal growth inhibition, lack of cellular damage, and lack of increase in ROS levels, compared with that of control fengycin incubated in PDB simultaneously ( Fig. 4E ). Two complementary observations supported the active enzymatic degradation of fengycin carried out by Botrytis during the interaction: i) the fact that the pH of the culture did not change significantly and ii) the specific fengycin degradation products with known enzymatic degradation profiles reported in the literature 59 . To identify putative enzymes involved in the chemical transformation of fengycin, we analyzed the genes that were upregulated in Botrytis following fengycin treatment or upon interaction with wild-type Bacillus via a previously described workflow involving RNA-Seq data 60 . We focused on proteins predicted to be extracellular and conducted a search for conserved protein domains to uncover key functional motifs involved in their activity, identifying putative enzymes involved in fengycin degradation ( Suppl. Table 1 ). This is a notable observation since the degradation of lipopeptides is reported to occur during competition with other bacteria 61 , 62 but not fungi. This finding indicates that there could be an additional defensive mechanism used by Botrytis and probably other filamentous fungi to neutralize antifungal molecules produced by Bacillus . Degradation of fengycin coincides with the secretion of fungistatic bacillaene by Bacillus Following the degradation of Bacillus primary antifungal compounds with activity against Botrytis , metabolomic analyses revealed an increase in the production and accumulation of bacillaene, another secondary metabolite from the Bacillus chemical arsenal 63 , 64 . Specifically, bacillaene accumulated at significantly greater levels in the supernatants of Bacillus cells cocultured with Botrytis than in those of Bacillus cells grown in monoculture after 24 h ( Fig. 5A ). Non-targeted metabolomic analysis of the interaction of Botrytis with the Δpps mutant (unable to produce fengycin) revealed elevated accumulation of bacillaene compared with the levels accumulated during the interaction with wild-type Bacillus , indicating compensatory regulation between fengycin and bacillaene ( Extended Data Fig. 8 ). This finding indicates a flexible defensive strategy adopted by Bacillus that involves the use of bacillaene in response to the fengycin-neutralizing activity of Botrytis . Download figure Open in new tab Figure 5. Interaction with B. cinerea triggers bacillaene production, revealing its fungistatic effects. A) Left: Molecular family analysis of bacillaene in B. cinerea supernatant after interaction with B. subtilis compared with that in the B. subtilis monoculture at 24 h. Pie charts represent the mean peak abundance of metabolites in the supernatant, with node shapes indicating the level of metabolite identification according to GNPS libraries. Right: Floating bar plots showing the peak abundance of bacillaene (precursor m/z 581.3581) in B. subtilis supernatants from monoculture and coculture with B. cinerea at 6, 24, and 48 h, highlighting bacillaene accumulation during interactions at 24 h. B) Confocal microscopy images of B. cinerea treated with 60 µg/mL purified bacillaene for 24 h, showing cytoplasmic vacuolization and hyphal tip splitting. Scale bars represent 20 µm. C) Quantification of the fungal mass after 24 h and one week demonstrated halted fungal growth upon bacillaene treatment, confirming its fungistatic activity. The whisker plot shows all the measurements (pink dots), medians (black line), and minimum and maximum values (whisker ends). For all experiments, the results from at least three biological replicates are shown. Statistical significance was assessed via a t test, with quadruple asterisks indicating significant differences at P < 0.0001. D) Molecular docking analysis predicted a putative binding site between bacillaene and the cytoplasmic elongation factor Bchbs1, as well as between bacillaene and the mitochondrial elongation factor Bcmef1, in Botrytis cinerea . E) Molecular docking analysis predicted a strong binding interaction between bacillaene B (precursor m/z 743.4) and TasA. F) Top: Overview of the native metabolomics workflow. Bottom: Analyses of native metabolomics assays between purified TasA and the crude extract of metabolites. Left: Mass spectrum of TasA alone. Right: Mass spectrum of TasA in the presence of the crude metabolite extract from the Bacillus-Botrytis coculture, revealing a distinct mass shift corresponding to the formation of the TasA-bacillaene complex when bacillaene passed through the column. This shift indicates the binding of bacillaene A, an isoform of bacillaene functionalized with a hexose group. To test whether this highly unstable metabolite 65 , 66 affects fungal growth, Botrytis cultures were treated with purified bacillaene at a concentration of 60 µg/mL. Hyphal tip splitting and massive cytoplasmic vacuolization were the most notable fungal morphological changes ( Fig. 5B ). Furthermore, the external addition of purified bacillaene halted Botrytis growth, whereas the untreated Botrytis continued to grow, confirming the fungistatic role of bacillaene ( Fig. 5C ). Bacillaene has been reported to be bacteriostatic and able to disrupt bacterial protein synthesis by targeting the prokaryotic elongation factor FusA 28 , 67 – 71 . To explore whether a similar mechanism might occur in fungi, we conducted a BLAST search between FusA and the genome of Botrytis , which revealed 50% and 30% homology between the bacterial elongation factor and two B. cinerea elongation factors: the mitochondrial elongation factor encoded by Bcmef1 and the cytoplasmic elongation factor encoded by Bchbs1 , respectively. Docking studies predicted a potential ligand□protein binding interaction between bacillaene and both elongation factors, suggesting their possible role as targets of bacillaene ( Fig. 5D ). Additionally, in a previous study, we reported that B. cinerea treated with bacillaene developed mutations in the elongation factor gene 71 . To investigate this further, B. cinerea cultures were treated with bacillaene for both short (24 h) and long (1 week) durations. Whole-genome sequencing of B. cinerea subjected to long-term treatment revealed several mutations likely impacting the cytoplasmic elongation factor Bchbs1 , as well as mutations in adjacent genes within the same transcript ( Suppl. Table 2 ). These results suggest that Bchbs1 is a likely target of bacillaene and demonstrate the capacity of B. cinerea to adapt to its presence, potentially as part of an adaptive response to mitigate the effects of bacillaene and maintain its viability. Bacillaene is a highly unstable molecule that is particularly sensitive to light and oxygen 65 , 66 , which raises the question of the mechanism that preserves the functionality of this ecologically significant molecule. Bacillus ECM is known to retain secondary metabolites 72 , and we have shown that ECM components are upregulated during the interaction with Botrytis , two observations that led us to propose an ECM with a bacillaene-stabilizing role. TasA is capable of disorganizing the β-glycan layer and reaching the chitin-chitosan layer of the fungal cell wall, which further supports the hypothesis that TasA is a molecular vehicle for the stabilization and efficient delivery of bacillaene to the Botrytis hyphal surface. Molecular docking studies using the resolved crystal structure of TasA and bacillaene predicted the highly likely interaction of bacillaene with TasA ( Fig. 5E ). We performed native metabolomics experiments 73 to explore the interaction between TasA and the crude extract containing metabolites from Bacillus-Botrytis cocultures. Native metabolomics, performed by combining non-targeted metabolomics and native mass spectrometry, showed that the fold and function of TasA were preserved 73 . The crude metabolite extract was first separated via microflow UHPLC, and subsequently (postcolumn), a make-up buffer neutralized the mobile phase, and purified TasA was infused via a T-splitter before mass spectrometry (MS) analysis ( Fig. 5F , top ). Upon bacillaene passage through the system, the interaction with TasA was monitored via MS, which revealed a molecular mass shift corresponding to the formation of the TasA-bacillaene complex ( Fig. 5F , bottom ). This molecular mass shift, along with a distinct retention time, indicated the binding of bacillaene A, a version of bacillaene functionalized with a sugar residue in its structure, to TasA. We hypothesize that binding to TasA protects bacillaene A from degradation while ensuring the stability of this metabolite and its effective delivery to the fungal target. These findings revealed an interconnection among the ECM and secondary metabolites, more specifically, TasA, as a carrier and stabilizer of structurally unstable bioactive molecules during microbial interactions. B. subtilis feeds on B. cinerea chitosan to maintain fengycin production The switch from fungicidal activity mediated by fengycin to fungistatic activity driven by bacillaene suggests a shift in the strategy adopted by Bacillus during its interaction with Botrytis . This change likely leads to long-term nutritional benefits, probably in oligotrophic environments, where maintaining a balance between microbial competition and coexistence could be advantageous for B. subtilis . In this context, the B. subtilis population density increased in coculture, mostly as vegetative cells and not spores, compared with monoculture ( Fig. 1C ). One explanation for these population dynamics is associated with the ability of B. subtilis cells to feed on B. cinerea hyphal structural components as nutrients. We hypothesized that chitosan is the preferred carbon source used by B. subtilis , which is supported by two complementary observations: first, the accessibility of B. subtilis cells to chitosan is mediated by the chemical affinity of TasA ( Fig. 3D and Extended Data Fig. 4A ), and second, the existence of a B. subtilis chitosanase encoded by the gene csn , an enzyme that hydrolyses the β-1,4-glycosidic bonds of chitosan molecules 74 – 76 . The dynamic growth of bacteria in minimal MSGG medium with chitosan as the sole carbon source revealed the ability of the B. subtilis WT strain to grow; however, a Δcsn mutant strain lacking functional chitosanase was not able to grow ( Fig. 6A ). Further in situ degradation of fungal chitosan by Bacillus during the interaction with Botrytis was confirmed via the use of the chitosan dye eosin Y 77 and fluorescence microscopy ( Fig. 6B ). Furthermore, the addition of purified chitosanase to B. cinerea culture produced a similar reduction in the fluorescence signal of fungal hyphae, indicative of chitosan loss, underscoring its role in fungal cell wall breakdown ( Fig. 6B ). Metabolomic analysis further highlighted the role of chitosanase in the interaction between B. subtilis and B. cinerea . After 24 h of coculture, we observed lower accumulation of fengycin in the supernatant of cocultures with the Δ csn mutant than in that of cocultures with wild-type B. subtilis ( Fig. 6C ). This result suggests a link between chitosanase activity, or the degradation of chitosan, and fengycin production. Flow cytometry analysis further supported this connection, revealing heightened fengycin promoter activity in the presence of chitosan after one week, which indicates that B. cinerea cell wall components sustain expression over time ( Fig. 6D ) and explains why, in the interaction, without accessible chitosan, fengycin accumulation is reduced. This result also suggested the possibility of a synergistic effect between Csn and fengycin against Botrytis . Compared with single treatments, the application of purified Csn and fengycin at the same time to B. cinerea significantly increased ROS production ( Fig. 6E ). These findings suggest that B. subtilis employs a dual strategy, nutrient acquisition and metabolic modulation, through both physical and chemical means to keep B. cinerea in a slowed growth state, ensuring the sustained availability of a carbon source in long-term balanced antagonistic coexistence. Download figure Open in new tab Figure 6. Chitosan degradation and the synergistic effects of chitosanase and fengycin contribute to B. subtilis growth. A) Growth curve of the wild-type and Δcsn B. subtilis strains in minimal MSGG medium supplemented with chitosan as the sole carbon source, showing no growth of the Δcsn mutant, highlighting the role of Csn in enabling B. subtilis to utilize chitosan. B) Confocal microscopy images of B. cinerea hyphae stained with eosin Y to visualize chitosan. The fluorescence signal was absent in hyphae treated with wild-type B. subtilis or 0.2 mg/mL purified Csn, demonstrating chitosan degradation. The scale bar equals 20 µm. C) Floating bar plot showing the peak abundances of four fengycin structural variants in the supernatant of B. cinerea after 24 h of interaction with wild-type B. subtilis or interaction with the Δcsn mutant. D) Flow cytometry analysis of B. subtilis expressing YFP under the fengycin promoter (Bsub Pfen-yfp) in the presence of control conditions, 0.06 mg/mL chitosan, or 0.125 mg/mL chitosan, demonstrating chitosan-induced maintenance of the fengycin promoter over time. E) Quantification of ROS intensity in B. cinerea treated with 10 µM fengycin, 0.2 mg/mL purified chitosanase, or a combination of both, demonstrating a synergistic effect between chitosanase and fengycin in inducing ROS accumulation. The whisker plot shows all the measurements (pink dots), medians (black line), and minimum and maximum values (whisker ends). In all experiments, at least three biological replicates are shown. Statistical significance was assessed via a t test, with double and quadruple asterisks indicating significant differences at P < 0.01 and P < 0.0001. Download figure Open in new tab Figure 7. Overview of the dynamic interaction and counterdefense between B. subtilis and B. cinerea . The interaction between Bacillus and Botrytis is a highly dynamic process characterized by mutual adaptation. Bacillus ECM components, specifically TasA and fengycin, induce stress in B. cinerea , which responds by forming chlamydospores, secreting oxylipins, and neutralizing fengycin. In turn, Bacillus has shifted its strategy, producing bacillaene to target fungal mitochondria. Additionally, Bacillus utilizes chitosan from the fungal cell wall, resulting in ecological competition between the two organisms. Discussion In this study, we demonstrated that the B. subtilis ECM, in addition to playing a structural role in the communication with other bacteria and plants 78 , 79 , is essential for fungal hyphal colonization and antagonism against pathogenic fungi. Our observations indicate that the ECM can play an offensive or defensive role in interspecies interactions, depending on the competitor. In interactions with Pseudomonas , defense seems to be the prevalent function 78 ; however, in interactions with B. cinerea, the role of ECM is more offensive. We show that the ECM components TasA and fengycin are crucial for antagonizing B. cinerea , acting synergistically while playing complementary roles, with each modifying B. cinerea physiology differently and triggering distinct metabolic changes. Our data revealed that the ECM, specifically TasA, not only facilitates physical attachment but also orchestrates metabolite-driven antagonistic mechanisms, positioning the B. subtilis ECM as an active mediator of microbial competition. We specifically propose that the ECM component TasA has two unprecedented functions: one in altering the physiology of B. cinerea hyphae and the other as a stabilizer and carrier of the bioactive and highly sensitive molecule bacillaene. TasA alone directly disrupts Botrytis physiology by disorganizing its β-glucan layer, resulting in cellular and morphological damage. Moreover, our results highlight the specificity of fungal defenses against B. subtilis lipopeptides. For example, surfactin has a lethal effect on Aspergillus , inducing chlamydospore formation; however, it does not trigger this response in B. cinerea 18 . Conversely, fengycin has no apparent effect on the lifestyle of Aspergillus but does induce chlamydospore formation in B. cinerea . These findings suggest that the effectiveness of B. subtilis lipopeptides may be highly dependent on the unique membrane composition of different fungal species. Furthermore, our results illustrate the complexity of the Bacillus .J Botrytis interaction, which involves bidirectional damage and dynamic chemical interplay, challenging the notion of purely antagonistic interkingdom bacteria□fungi interactions. Although B. subtilis initially suppresses fungal growth, the B. cinerea population initiates a chemical defense response by producing oxylipins that target B. subtilis and restructuring its cell morphology through hyperbranching and chlamydospore formation to increase survival. Some oxylipins, such as SDA, have been previously identified as mediators of survival strategies produced by the eukaryote C. elegans coexisting with Pseudomonas 80 , suggesting a conserved resilience mechanism among eukaryotes. The accumulation of Lyso-PC and ROS in Botrytis in response to TasA further indicates the complex biochemical interaction and metabolomic modulation of B. cinerea by B. subtilis ECM. Lyso-PC is implicated in oxidative stress in various organisms, and its accumulation in B. cinerea , alongside ROS, suggests the existence of a defense mechanism activated by the fungal cell in response to B. cinerea ECM. As part of this defense, B. cinerea partially neutralizes B. subtilis action by degrading fengycin, as previously reported for bacteria□bacteria interactions 81 , 82 but not for interactions with fungi. Following the degradation of fengycin by B. cinerea to neutralize B. subtilis primary antifungal compounds, the production of another secondary metabolite from the Bacillus arsenal, bacillaene, increases. The role of bacillaene, which functions fungistatically rather than as a fungicide, exemplifies this adaptive strategy. Known to mediate microbe□microbe interactions 83 and plant interactions, increased bacillaene production in response to fungal degradation of fengycin reflects the adaptability of Bacillus chemical weapons in response to B. cinerea counterattack. Additionally, we demonstrated that TasA binds to and stabilizes bacillaene, likely ensuring the fungistatic functionality. A previous study demonstrated the ability of bacillaene to bind the E. coli curli protein components CsgA and CsgB 84 , but in this case, it disrupted the assembly of amyloid fibers and thus biofilm formation, a strategy that confers B. subtilis with a competitive advantage in microbial interactions. In the sequence of events leading to this interkingdom interaction, it may be predicted that following attachment to B. cinerea via TasA, Bacillus employs chitosanase to degrade chitosan from the B. cinerea cell wall and gain access to an extra carbon source. This ability to exploit B. cinerea for carbon is demonstrated by increased B. subtilis growth in coculture. Our results show that chitosanase acts synergistically with fengycin, increasing cell wall susceptibility to further fungal stress. Flow cytometry indicated that the presence of chitosan extends fengycin promoter activity, potentially stabilizing the antifungal arsenal of B. subtilis . Thus, the ECM, by supporting metabolite delivery and nutrient extraction, exemplifies an adaptive strategy in which B. subtilis can maintain B. cinerea in a state of fungistatic control without immediate eradication. In short-term interactions, these adaptive responses may reflect a shift toward a stable antagonistic coexistence, consistent with ecological theories on microbial competition, suggesting that in some antagonistic interactions, competitors may reach a nonlethal equilibrium where metabolic adjustments allow for prolonged coculture 6 , 27 . This adaptability may represent a broader fungal strategy, wherein B. cinerea perceives specific ECM components from B. subtilis , thereby modulating its physiological defenses and enhancing survival. Competition upon initial contact can often evolve into a form of stable coexistence, where both B. subtilis and B. cinerea adapt and survive despite ongoing antagonism. Such coexistence may lead to spatial or resource partitioning, ultimately enabling both organisms to persist within a shared niche. In conclusion, our data expand the understanding of microbial interactions by revealing the role of the bacterial ECM in mediating physical attachment and extracellular matrix-driven antagonism, with implications for microbial competition and survival strategies in resource-limited environments. Through such interactions, the B. subtilis ECM has emerged as a central element in microbial antagonism, shaping microbial interplay and sustaining B. subtilis survival under competitive conditions. Materials and Methods Strains, media and culture conditions A complete list of the bacterial strains used in this study is shown in Suppl. Table 3 . Bacterial cultures were grown in liquid lysogeny broth/Luria–Bertani (LB; 1% tryptone, 0.5% yeast extract and 0.5% NaCl) medium at 30°C ( Bacillus ) or 37°C ( E. coli ) with shaking on an orbital platform. The pH was adjusted to 7 prior to sterilization. When necessary, antibiotics were added to the media at appropriate concentrations. Isolate B05.10 of the necrotrophic fungus B. cinerea was cultured on potato dextrose agar (PDA, Oxoid) at 20°C under illumination with fluorescent light at a photofluency rate of 12□μmol□m -2 □s -1 and a 12/12 h photoperiod. Conidia were harvested from the light-grown culture in sterile distilled water and filtered through a 40-μm cell strainer to remove the remaining hyphae. Escherichia coli DH5α was used for cloning and plasmid replication. E. coli BL21(DE3) and BL21(AI) were used for protein purification. B. subtilis mutants B. subtilis mutants were generated using the SPP1 phage transduction method as previously described 85 . To generate double mutant strains, phage lysates were prepared from the ΔtasA and Δeps single mutant strains and subsequently transferred to a Δpps mutant. The mutants were verified through PCR and antibiotic resistance assays. Construction of fluorescence-labeled strains The fluorescence labeling plasmid pKM008V was constructed for Bacillus subtilis strains. In brief, a 300 bp fragment of the Pveg promoter was extracted from pBS1C3 using restriction enzymes EcoRI and HindIII. The Pveg promoter was selected because of its role as a constitutive promoter in B. subtilis. After purification, the fragment was inserted into the pKM003 (YFP) or pDR183 (CFP) plasmid, which had been digested with the same enzymes. The plasmid was introduced into B. subtilis 168 by natural competence. Transformants were selected by plating on LB agar supplemented with antibiotics. To fluorescently label the extracellular matrix mutants, YFP or CFP was transferred from B. subtilis 168 using SPP1 phage transduction as previously described 85 . Bacterial lJfungal competition assay B. cinerea was precultured by growing a germinated conidial suspension in potato dextrose broth (PDB, Oxoid) at 28°C for 24 h at 150 rpm. B. subtilis strains were grown on LB plates overnight at 28°C, and the resulting colonies were grown overnight in 5 mL of LB at 28°C on an orbital platform. Then, 10-15 germinated hyphae (microcolonies) were mixed with 200 µL of bacterial culture grown in 6-well plates with PDB at 28°C overnight at 150 rpm. Evaluation of Bacillus adhesion To analyze the adhesion of different Bacillus ECM mutants to Botrytis hyphae, Botrytis was mixed with precultures of the different Bacillus strains constitutively labeled with YFP or CFP. After overnight incubation at 28°C in PDB, the Botrytis clumps were washed three times with water to remove unattached Bacillus cells. The washed hyphae were subsequently placed onto agarose-coated slides. For the Bacillus strains labeled with CFP, excitation and emission detection were performed at the corresponding wavelengths (excitation at 405 nm and emission detection between 450 and 550 nm), and likewise for YFP-labeled strains (excitation at 512 nm and emission detection between 520 and 600 nm). Images were obtained using a Leica Stellaris 8 confocal microscope with a 63x NA 1.3 Plan APO oil-immersion objective. For each experiment, the laser settings, scan speed, PMT or HyD detector gain, and pinhole aperture were kept constant across all acquired images. To count CFUs adhered to the fungus with each ECM mutant, the fungal mass was separated from the liquid bacterial culture by filtering with a 40 µm nylon filter to retain the fungus. The fungal mass was then washed once with Milli□Q (MQ) water to remove the free bacterial cells that were not attached to the fungi. The washed fungal mass was collected in a microtube and weighed to normalize the results to the mass of fungus. A pestle was then used to break the fungal structures and release the bacteria adhering to the fungus. The content was resuspended, and serial dilutions were performed. Finally, CFUs were counted and normalized to the fungal mass. Transmission electron microscopy B. cinerea samples were fixed in 2.5% (v/v) glutaraldehyde and 4% (v/v) paraformaldehyde overnight at 4°C. After three washes in fixation mix, the samples were postfixed with 1% osmium tetroxide solution for 90 min at room temperature, followed by two washes and 15 min of stepwise dehydration in an ethanol series (30%, 50%, 70%, 90%, and 100% twice). Between the 50% and 70% steps, the samples were incubated en bloc in 2% uranyl acetate solution in 50% ethanol at 4°C overnight. Following dehydration, the samples were gradually embedded in low-viscosity Spurr’s resin as follows: resin:ethanol, 1:1, 4 h; resin:ethanol, 3:1, 4 h; and pure resin, overnight. The sample blocks were embedded in capsule molds containing pure resin for 72 h at 70°C. The samples were left to dry and visualized under an FEI TALOS F200X. Confocal laser scanning microscopy Bacterial cell death within the colonies was assessed utilizing the LIVE/DEAD BacLight Bacterial Viability Kit (Invitrogen). The kit components were combined in equal proportions, and 2 μl of this mixture was used to stain 1 ml of the corresponding bacterial suspension. To visualize live or dead bacteria in the samples, sequential acquisitions were performed. Live bacteria were imaged using excitation at 488 nm, and emission was recorded between 499 and 554 nm, whereas dead bacteria were imaged through a subsequent acquisition via excitation at 561 nm and emission recorded between 592 and 688 nm. Intracellular ROS levels were detected by staining with dihydrorhodamine 123 (DHR123; Sigma). Following incubation, DHR123 was added to the cell suspension to obtain a final concentration of 2 μg/mL, and the suspension was subsequently incubated for 5 min at room temperature. The cells were counterstained with the lipophilic dye FM4-64 (Thermo Fisher) to stain the plasma membrane. Images were obtained using a Leica Stellaris 8 confocal microscope with a 63x NA 1.3 Plan APO oil-immersion objective, with excitation at 488□nm and emission detection between 510 and 580 nm (for DHR123 fluorescence emission) and between 670 and 850 nm (for FM4-64 fluorescence emission). Image processing was performed using FIJI/ImageJ software 86 . For each experiment, the laser settings, scan speed, PMT or HyD detector gain, and pinhole aperture were kept constant across all acquired images. Protein purification Recombinant His6-tagged TasA was purified as previously reported 87 . In brief, BL21 (DE3) E. coli was transformed with the pET22b-tasA plasmid. The resulting colonies were grown in 5 mL of LB medium at 37°C overnight at 150 rpm, reinoculated at a ratio of 1:100 in fresh LB medium and incubated at 37°C with shaking until an OD 600 of 0.7–0.8 was reached. At that point, protein expression was induced with 1 mM isopropyl β-D-1-thiogalactopyranoside (IPTG), and the mixture was incubated overnight at 28°C with shaking to induce inclusion body formation. The next day, the cells were harvested via centrifugation (7000 × g, 30 min, 4°C) and stored at -80°C until purification. After thawing, the pellet was resuspended in buffer A (Tris 50 mM, 150 mM NaCl; pH 8) supplemented with 0.2 mg/mL lysozyme, 1 mM PMSF, and 10x Cell Lysis Reagent (Sigma) and incubated for 1 h at 37°C. Then, 6 M GuHCl was added until saturation, and the mixture was incubated at 60°C overnight until complete solubilization occurred. The lysate was sonicated on ice (3 × 60 s, 60% amplitude) and centrifuged (110,000 × g, 1 h, 16°C). The resulting supernatant was passed through a 0.45-μm filter prior to affinity chromatography. The protein was purified using an AKTA Start FPLC system (GE Healthcare). The suspension was loaded into a HisTrap HP 5 mL column (GE Healthcare) previously equilibrated with binding buffer (50 mM Tris, 0.5 M NaCl, 20 mM imidazole, and 8 M urea; pH 8). Next, the protein was eluted from the column with elution buffer (50 mM Tris, 0.5 M NaCl, 500 mM imidazole, and 8 M urea; pH 8). Afterward, the purified protein was loaded into a HiPrep 26/10 desalting column (GE Healthcare), and the buffer was exchanged with 20 mM Tris or 50 mM NaCl to perform the corresponding experiments. To purify chitosanase, recombinant His6-tagged chitosanase (Csn) was purified following a modified protocol for recombinant protein expression. Briefly, E. coli cultures carrying the Csn expression plasmid were grown in 250 mL of LB medium supplemented with ampicillin and incubated with shaking until an OD 600 of 0.7 was reached. Expression was induced with IPTG, and the cultures were incubated for the optimal expression time before the cells were harvested by centrifugation (10,000 × g, 5 min). The cell pellets were lysed in washing buffer containing 50 mM Na 3 PO 4 (pH 8), 500 mM NaCl, 10 mM imidazole, 1 mM PMSF, 0.2 mg/mL lysozyme, and 10x CelLytic® (Sigma□Aldrich) and incubated with shaking at room temperature for 30 min. The cells were then disrupted by sonication on ice (3 × 60 s pulses), and the lysates were clarified by centrifugation and filtered. The lysate was loaded onto a HisTrap HP column (GE Healthcare) on an AKTA Start FPLC system equilibrated with washing buffer. The protein was eluted via elution buffer (20 mM Na 3 PO4, 500 mM NaCl, and 500 mM imidazole; pH 8). The purified Csn protein was dialyzed against 50 mM Tris-HCl and 50 mM NaCl (pH 7.4) using a HiPrep™ 26/10 Desalting column (GE Healthcare) and stored at -80°C until further use. EPS extraction and purification The B. subtilis strain lacking tasA was used for EPS production using an overnight preculture of Ty liquid medium, and one milliliter was inoculated into 200 mL of Ty liquid medium for static culture in a 24-well microplate and left at 30°C for 5 days. The cells were harvested by centrifugation at 8000 × g for 10 min and washed with distilled water. After centrifugation, the cell pellets were resuspended in PBS and mildly sonicated to separate EPSs from the cells. The soluble fractions were stirred on ice, and a 100% TCA solution was added to precipitate proteins from the EPS extract. The mixture was left at 4°C overnight, and the proteins were removed by centrifugation at 10000 × g for 20 min. EPSs from the supernatant were precipitated by adding 5 volumes of chilled ethanol under continuous stirring and incubating at 4°C overnight. The crude EPS mixture was collected by centrifugation (10,000 × g, 20 min). The pellets were dialyzed against distilled water overnight (Spectra/Por ® dialysis membrane with a molecular weight cutoff of 3.5 kDa), and the resulting solution was filtered and applied to a size exclusion chromatography column (Hiprep TM 16/60 Sephacryl TM S-300HR), eluting with MQ water. Aliquots of each fraction were analyzed by the phenol sulfuric acid method, and the absorption at 490 nm was monitored in a multiplate reader (FLUOstar Omega reader, BMG LabTech). Fractions containing carbohydrates were pooled and lyophilized for further analysis. Immunolocalization of TasA by CLSM To assess the binding of purified tagged TasA to Botrytis hyphae, we added 3 μM purified TasA and incubated it overnight. Next, the samples were applied to well slides treated with 0.1% poly-L-lysine (Sigma□Aldrich) and incubated for 2 h. After the samples were removed, they were fixed with fixation buffer (3% paraformaldehyde and 0.1% glutaraldehyde diluted in PBS) for 10 min. The wells were subsequently rinsed twice with PBS and incubated for 1 h in blocking buffer (3% w/v bovine serum albumin (BSA) and 0.2% v/v Triton X-100 in PBS). Following removal of the buffer, the wells were treated with the primary antibody (anti-His) at a concentration of 1:100 diluted in blocking buffer and incubated for 3 h. The wells were then washed three times with washing buffer (0.2% w/v BSA and 0.05% v/v Triton X-100 in PBS), with each incubation lasting for 5 min. The wells were subsequently incubated for 2 h with the secondary antibody goat anti-rabbit IgG-Atto488 at a dilution of 1:200 in blocking buffer. The samples were washed once with washing buffer and twice with PBS, with each incubation lasting for 5 min. The immunostained samples were fixed for 5 min with fixation buffer, followed by rinsing with PBS three times. As a negative control, immunostaining was performed without incubation with the primary antibody. Visualization of immunostaining was carried out using confocal laser scanning microscopy. For Atto-488 fluorescence, an excitation wavelength of 488 nm and emission wavelengths between 497 and 572 nm were employed. The Alexa Fluor 647 signal was visualized with an excitation wavelength of 561 nm, and emission was detected between 576 and 686 nm. TasA immunolabeling assay by TEM To identify the specific localization of TasA on the cell wall of Botrytis , we first added 3 μM purified TasA to a Botrytis culture and incubated it overnight. Next, the cells were fixed and embedded as described in the TEM section. For immunolabeling assays, carbon-coated copper grids were deposited over the samples of Botrytis . After 2 h of incubation, the grids were washed in PBS for 5 min and blocked with Pierce protein-free (TBS) blocking buffer (Thermo Fisher) for 30 min. An anti-TasA primary antibody was used at a 1:150 dilution in blocking buffer, and the grids were deposited over the drops of antibody solution and incubated for 1 h at room temperature. The samples were washed three times with TBS-T (50 mM Tris-HCl, 150 mM NaCl, pH 7.5, and 0.1% Tween 20) for 5 min and then exposed to a 10-nm-diameter immunogold-conjugated secondary antibody (10 nm goat anti-rabbit conjugate, BBI solutions) for 1 h at a 1:50 dilution. The samples were then washed twice with TBS-T and once with water for 5 min each time. Finally, the grids were treated with 2% glutaraldehyde for 10 min, washed in water for 5 min, negatively stained with 1% uranyl acetate for 15 s and washed once with water for 15 s. The samples were left to dry, and images were acquired via a JEOL JEM-1400 transmission electron microscope at an accelerating voltage of 80 kV. MRI assays B. cinerea cells (treated with purified TasA or protein buffer) were incubated for 24 h in PDB. Following incubation, all samples were embedded in 1.5% agar in Falcon tubes to ensure stable positioning for imaging. MRI experiments were conducted using a 9.4 T Bruker Biospec system equipped with 400 mT/m gradients and an Avance III console (Bruker BioSpin, Ettlingen, Germany). High-resolution T2-weighted images were acquired using a turbo-RARE sequence with the following parameters: TE = 33 ms, TR = 500 ms, 2 averages, a field of view (FOV) of 3.2 cm, a matrix size of 384 × 384, an in-plane resolution of 78 μm, and a slice thickness of 1 mm. These settings enabled detailed visualization of structural and texture variations in the Botrytis samples in response to TasA treatment. Plant infection assays Assays of B. cinerea infection were carried out in 5–6-week-old plants. Fungal conidia were collected from cultures grown under illumination in sterile distilled water and filtered through a 40 μm cell strainer to remove the remaining hyphae. For inoculation, the conidial suspension was adjusted to 10 5 conidia/mL in grape juice (100% pure organic). Each leaf was inoculated with 5 μL droplets of conidial suspension. The pots were covered with a plastic dome and placed in a growth chamber. After 24 h, the plastic dome was temporarily removed to apply the treatment (TasA) or buffer to the control plants. The leaves were imaged 72 h after inoculation, and the size of the lesions was determined using ImageJ software. RNA isolation and sequencing RNA from B. cinerea was extracted from clumps disrupted with liquid nitrogen. After disruption, the suspensions of the pellets were resuspended in TRIzol reagent (Invitrogen). Total RNA extraction was then performed as indicated by the manufacturer. DNA removal was carried out by treatment with Nucleo-Spin RNA Plant (Macherey–Nagel). The integrity and quality of the total RNA were assessed with an Agilent 2100 Bioanalyzer (Agilent Technologies) via electrophoresis. The removal of rRNA was performed using the RiboZero rRNA Removal (Bacteria) Kit from Illumina, and 100-bp single-end read libraries were prepared via the TruSeq Stranded Total RNA Kit (Illumina). The libraries were sequenced using a NextSeq550 sequencer (Illumina). The raw reads were preprocessed with SeqTrimNext 88 using specific next-generation sequencing (NGS) parameters. This preprocessing removed low-quality, ambiguous and low-complexity stretches; linkers; adapters; vector fragments; and contaminated sequences while keeping the longest informative parts of the reads. SeqTrimNext also discarded sequences less than 25□bp in length. The clean reads were subsequently aligned and annotated using the Bsub reference genome with Bowtie2 89 in BAM files, which were then sorted and indexed using SAMtools v1.484 90 . Uniquely localized reads were used to calculate the read number value for each gene via Sam2counts ( https://github.com/vsbuffalo/sam2counts ). Differentially expressed genes (DEGs) were analyzed via DEgenes Hunter, which provides a combined p value calculated (based on Fisher’s method) using the nominal p values provided by edgeR 91 and DEseq2. This combined p value was adjusted via the Benjamini□Hochberg (BH) procedure (false discovery rate approach) and used to rank all the obtained DEGs. For each gene, a combined p value 1 or < −1 were considered the significance thresholds. Metabolite extraction from liquid culture The cultures were subsequently centrifuged to separate the cell and supernatant fractions. For the extraction of metabolites from the cell fraction, 1 mL of 80% methanol was added, and a tissue-lyser was used for 10 min to disrupt the cells. The mixture was then centrifuged at maximum speed, and the supernatant was transferred to a new tube. The methanol was evaporated using a speed vacuum concentrator and stored at -20°C until analysis by LC□MS. For the supernatant fraction, ethyl acetate was added at a 1:1 ratio, by volume, with the supernatant. The mixture was vortexed and rotated for 30 min. Subsequently, 4 mL of the upper phase was transferred to a new tube. The supernatant was evaporated using a speed vacuum concentrator and stored at -20°C until further analysis via LC□MS. Liquid chromatography lJtandem mass spectrometry (LC lJMSlJMSlJMS ) Nontarget metabolomics was performed by liquid chromatography□tandem mass spectrometry (LC□MS□MS) with a UHPLC coupled to a Q Exactive HF mass spectrometer as previously described 92 . In brief, UHPLC separation was performed using a C18 core□shell column (Kinetex, 50 × 1 mm, 1.7 µm particle size, 100 A pore size; Phenomenex, Torrance, USA). The mobile phases used were solvent (A), containing H2O (LC/MS grade, Fisher Scientific) + 0.1% formic acid (FA), and solvent (B), containing acetonitrile (LC/MS grade, Fisher Scientific) + 0.1% FA. After sample injection, a linear gradient of 5 min was used for the elution of small molecules, and the flow rate was set to 150 µl/min (microflow). The following separation conditions were used: 0–4 min from 5% to 50% solvent (B), 4–5 min from 50 to 99% B, followed by a 2 min washout phase at 99% B and a 3 min re-equilibration phase at 5% B. The measurements were conducted in positive mode, and the HESI parameters included a sheath gas flow rate of 30 L/min, an auxiliary gas flow rate of 10 L/min, and a sweep gas flow rate of 2 L/min. The spray voltage was set to 3.50 kV, the inlet capillary temperature was 250°C, the S-lens RF level was 50 V, and the auxiliary gas heater temperature was 200°C. The full MS survey scan acquisition range was set to 120–1,800 m/z with a resolution of 45,000, automatic gain control (AGC) of 1E6, and a maximum injection time of 100 ms with one microscan. DDA MS/MS spectra acquisition was performed in data-dependent acquisition (DDA) mode with TopN set to 5; as a consequence, the five most abundant precursor ions of the survey MS scan were subjected to MS/MS fragmentation. The resolution of the MS/MS spectra was set to 15,000, the AGC target was 5E5, and the maximum injection time was 50 ms. The quadrupole precursor selection width was set to 1 m/z. Normalized collision energy was applied stepwise at 25, 35, and 45°C. MS/MS scans were triggered in apex mode within 2–15 s from their first occurrence in a survey scan. Dynamic precursor exclusion was set to 5 s. Feature-based molecular networking and spectral library search After LC□MS/MS acquisition, the raw spectra were converted to .mzML files using MSconvert (ProteoWizard). MS1 and MS/MS feature extraction was performed with Mzmine3 93 . For MS1 spectra, an intensity threshold of 1E5 was used, and for MS/MS spectra, an intensity threshold of 1E3 was used. For MS1 chromatogram building, a 10-ppm mass accuracy and a minimum peak intensity of 5E5 were set. Extracted ion chromatograms (XICs) were deconvolved using the baseline cutoff algorithm at an intensity of 1E5. After chromatographic deconvolution, the XICs were matched to the MS/MS spectra within 0.02 m/z and 0.2-minute retention time windows. Isotope peaks were grouped, and features from different samples were aligned with 10 ppm mass tolerance and 0.1-minute retention time tolerance. MS1 features without MS2 features assigned were filtered out of the resulting matrix, as were features that did not contain isotope peaks and that did not occur in at least three samples. After filtering, the gaps in the feature matrix were filled with a relaxed retention time tolerance of 0.2 min and a 10 ppm mass tolerance. Finally, the feature table was exported as a .csv file, and the corresponding MS/MS spectra were exported as .mgf files. Contaminant features observed in blank samples were filtered, and only those with a relative abundance ratio of blank to average lower than 30% were considered for further analysis. For feature-based molecular networking and spectrum library matching, the .mgf file was uploaded to GNPS 94 , 95 . For molecular networking, the minimum cosine score was set to 0.7. The precursor ion mass tolerance was set to 0.01 Da, and the fragment ion mass tolerance was set to 0.01 Da. The minimum number of matched fragment peaks was set to 6, the minimum cluster size was set to 1 (MS cluster-off), and the library search minimum number of matched fragment peaks was set to 5. When analog searches were performed, the cosine score threshold was 0.7, and the maximum analog search mass difference was 100 m/z. Molecular networks were visualized with Cytoscape version 3.9.1 96 . To enhance the chemical structural information in the molecular network, the generated .mgf file from MzMine3 was placed into Sirius 4 for chemical class and structure prediction 97 . The input data were automatically compared and classified against databases present in SIRIUS (Bio Database, GNPS, Natural Products, PubChem, PubMed). For molecular formula identification, the MS2 mass accuracy was set to 3 ppm. Chemical class annotations were performed with CSI: FingerID 98 and CANOPUS 99 , 100 . Mirror plots were generated using GNPS and https://metabolomics-usi.ucsd.edu/ , and the mzspec values of the selected features and the metabolites recorded in the MS/MS databases were compared ( Extended Data Fig. 9 ). Annotations were performed according to the guidelines in ref. 101 ( Suppl. Table 4 ). Statistical analysis of the metabolomic datasets was performed via MetaboAnalyst v.5.0 after data were filtered by the interquartile range (IQR) 102 . An automatic workflow for the analysis of the cell and supernatant fractions of B. cinerea and B. subtilis during coculture and B. cinerea treatment with TasA and fengycin at 6, 24 and 48 h (MSV000089552) can be accessed at https://massive.ucsd.edu/ProteoSAFe/dataset.jsp?task=b7579a1d14df42a09d30bd1418852db2 (feature-based molecular networking of the cell fraction: https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=4e4ade42ae60484886df1295747c5c71 ; feature-based molecular networking of the supernatant fraction: https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=c03281452dd342ccaf6962a051debb40 ). Native metabolomics For the native metabolomics experiments, the same chromatographic parameters were used. In addition, 150 μL/min ammonium acetate buffer was infused postcolumn through a makeup pump and a PEEKT splitter, and a 3 μM TasA protein solution was infused with a 2 μL/min flow rate via the integrated syringe pump. The ESI settings were as follows: sheath gas flow, 40 arbitrary units; auxiliary gas flow, 10 arbitrary units; and sweep gas flow, 0 arbitrary units. The auxiliary gas temperature was set to 150°C. The spray voltage was set to 3 kV, and the inlet capillary was heated to 253°C. The S-lens level was set to 30 V. The MS scan range was set to 2500–4000 m/z with a resolution R m/z 200 of 140,000 to 120,000 with 2 microscans. MS acquisition was performed in all-ion fragmentation (AIF) mode with R m/z 200 with 20% HCD collision energy and an isolation window of 2500–4000 m/z. For native LC□MS data analysis, raw ion spectra were analyzed with Xcalibur software (Thermo Scientific) to identify changes in protein mass. Next, when a suspected ligand was found, feature tables from both the intact protein mass and the metabolomics data were matched by their retention time and a m/z offset corresponding to the masses of bacillaene B and dihydrobacillaene B. Minimum inhibitory concentration (MIC) assays MIC assays were conducted in liquid LB medium using the twofold serial dilution method as outlined by the guidelines of the Clinical and Laboratory Standards Institute (2003). The highest concentration tested for the compound SDA was 1000 μg/mL. All experiments were performed in triplicate, and the MIC was determined as the lowest antibiotic concentration that inhibited growth by more than 90%. Polysaccharide affinity assay These assays were conducted following established protocols 103 , 104 , employing 30 µg/mL purified TasA. In brief, TasA monomers were incubated with 3 mg of chitin beads (New England Biolabs), crab shell chitin, chitosan, β-glucan, cellulose (all from Sigma) or xylan (TCI America) in 800 mL of water. Following gentle agitation at 4°C overnight, the insoluble fraction was pelleted by centrifugation (13000 × g for 5 min), and the supernatant was collected. The insoluble fraction was washed three times with water and subsequently boiled in 1% SDS solution. The presence of protein in both the supernatant and pellet fractions was assessed via Tricine SDS□PAGE followed by Coomassie Brilliant Blue staining. Bacillaene extraction and purification The extraction and purification of bacillaene were performed as previously described with some modifications 105 , 106 . In brief, cultures of B. subtilis (or Δpks as a control) were grown in 1 L batches in LB broth and incubated overnight at 28°C with shaking. Following incubation, the cells were removed by centrifugation (9 000 rpm, 10 min, 16°C), and the resulting cell-free supernatant was retained. Next, 250 mL of ethyl acetate was added for bacillaene extraction, and the mixture was incubated with agitation for 2 h and then left for 30 min to allow phase separation. The organic phase containing bacillaene was recovered and evaporated by lyophilization. The residue was dissolved in methanol and filtered through 0.45 µm filters (Econofltr PTFE). The filtered sample was chromatographed using a preparative HPLC column (Eclipse XDB-C18 5 μm, 9.4x250 mm). The mobile phases used were 20 mM NaPi (A) and acetonitrile (B), with the following elution profile: 0–2 min at 35% B, 2–8 min from 35–40% B, 8–10 min at 40% B, 10–12 min from 40–35% B, and 12–15 min at 35% B. The flow rate of the mobile phase was set to 1 mL/min, and the absorbance was monitored at 362 nm using a photodiode array (PDA). The presence of bacillaene was confirmed by comparing the chromatograms of the wild-type extract with those of the Δpks mutant extract, which lacked bacillaene, and by HPLC-MS by the MEDINA Foundation. The samples were analyzed using an Agilent 1200 Rapid Resolution HPLC connected to a Bruker maXis mass spectrometer. For separation, a Zorbax SB-C8 column (2.1 × 30 mm, 3.5 µm particle size) was used. The mobile phase consisted of two solvents: a 90:10 aqueous solution (solvent A) and a 10:90 aqueous solution (solvent B) of 13 mM ammonium formate and 0.01% TFA. The mass spectrometer was set to positive electrospray ionization (ESI) mode, with the following parameters: 4 kV capillary voltage, 11 L/min at 200°C for the drying gas flow, and 2.8 bar pressure in the nebulizer. The instrument was calibrated prior to sample injection via the ion cluster generated by TFA in the presence of Na+ ions. Each injected sample was subsequently recalibrated by infusing the TFA-Na calibrant before the chromatographic front appeared. Each chromatographic run was processed using Bruker’s internal algorithm for component extraction, and the most intense peaks, both by TIC in positive mode and absorbance at 210 nm, were considered for accurate mass interpretation and molecular formula determination. The combination of retention time and exact mass was used as a search criterion in the high-resolution mass spectrometry database of the MEDINA Foundation. Docking Automated tertiary structure modeling of the elongation factor (EF) protein from B. cinerea B05.10 (Acc. no. XP_001560460.1), derived from the Bchbs1 and Bcmef1 genes, were generated via AlphaFold 107 . To identify potential binding sites for bacillaene (PubChem ID: 25144999) on the EF proteins, we utilized the web-based SwissDock program [ www.swissdock.ch/docking ] 108 for automated molecular docking and thermodynamic analysis. SwissDock employs the EADock DSS algorithm 109 to predict molecular interactions between a target protein and a small molecule. Docking was carried out using the “Accurate” setting with default parameters and no predefined region of interest (blind docking). Binding energies were calculated using CHARMM (Chemistry at HARvard Macromolecular Mechanics), integrated within SwissDock software, and the most favorable energies were assessed via fast analytical continuum treatment of solvation (FACTS). The energy results were then scored and ranked on the basis of full fitness (kcal mol−1), with spontaneous binding indicated by the estimated Gibbs free energy ΔG (kcal mol−1). The negative ΔG values suggest that the binding process is highly spontaneous. Visualization of the modeling and docking results was performed using UCSF Chimera v1.8 software. Flow cytometry assays The cells were grown in 24-well plates filled with 1 mL of MSgg at 28□°C. At different time points, the pellicle was carefully removed, and the cells from the spent medium were recovered in 500□μL of PBS after centrifugation (14,000 rpm, 3 min) and resuspended with a 25G needle. The cells were gently sonicated (12 pulses of 5 s and 30% amplitude) to ensure complete resuspension, fixed in 4% paraformaldehyde in PBS and washed three times in PBS. The flow cytometry runs were performed with 200□μl cell suspensions in 800□μl of GTE buffer (50□mM glucose, 10□mM EDTA, 20□mM Tris-HCl; pH 8), and the cells were quantified on a Beckman Coulter Gallios™ flow cytometer using 488□nm excitation. YFP fluorescence was detected with a 525/40 BP filter. The data were collected using Gallios™ Software v1.2 and further analyzed using Flowing Software v2.5.1. Unlabeled cells ( B. subtilis wild type) were used as a negative control for promoter expression analysis. Chitosan level quantification Changes in the chitosan composition were determined via eosin Y labeling. The samples were subsequently resuspended in citrate-phosphate buffer (0.2 M NaH 2 PO 4 , 0.1 M K citrate; pH 6) with 1 μg/ml eosin Y (final concentration). After 10 min of incubation at room temperature, the cells were washed two times with citrate-phosphate buffer and placed on 1% agarose pads. Finally, the stained cells were imaged with an excitation wavelength of 488 nm, and emission was detected between 510 and 640 nm. Images were obtained using a Leica Stellaris 8 confocal microscope with a 63x NA 1.3 Plan APO oil-immersion objective. Processing and signal intensity measurement were performed via FIJI/ImageJ. For each experiment, the laser settings, scan speed, HyD detector gain, and pinhole aperture were kept constant across all acquired images. Data availability All the raw RNA-seq data have been submitted to the Gene Expression Omnibus (GEO) and can be accessed through GEO series accession no. GSE287578 (URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE287578 . All the metabolomics data are deposited at https://massive.ucsd.edu/with the identifier MSV000089552. Competing interests The authors declare that they have no competing interests. Extended Data Figure 1. Enrichment analysis of differentially expressed B. cinerea genes during interaction with B. subtilis. A) KEGG pathway enrichment analysis showing the deregulation of pathways related to glutathione metabolism, secondary metabolite biosynthesis, and phospholipid metabolism after six hours of coculture. B) Gene Ontology (GO) terms enriched in genes upregulated in B. cinerea after six hours of coculture. C) GO terms enriched by genes downregulated in B. cinerea after six hours of coculture. Extended Data Figure 2. Enrichment analysis of differentially expressed B. subtilis genes during interaction with B. cinerea . KEGG pathway enrichment analysis showing the deregulation of pathways related to the biosynthesis of secondary metabolites. Extended Data Figure. 3. Metabolomic analysis revealed differential accumulation of metabolite classes during the Bacillus-Botrytis interaction. A) Top 25 features with the highest median weighted sum of absolute regression coefficient scores determined by PLS-DA, calculated using MetaboAnalyst. These features were identified as key metabolites discriminating cocultures from single cultures of each microbe after 24 h in the cell fraction. The feature IDs are annotated with their chemical classes via Classyfire classification. The left side of the figure indicates the microbial origin of the different accumulated metabolite classes. B) Heatmap of hierarchical clustering of the top 350 features within impacted molecular families during the coculture of B. cinerea and B. subtilis compared with monoculture of each after 24 h in the cell fraction. The color gradient in the heatmap indicates the relative fold change of each metabolite between the groups. The circular graphs show the percentage distribution of metabolite classes with altered accumulation, with the color code inside the donut chart representing each chemical class according to NPClassifier. C) Quantification of ROS levels in B. cinerea after treatment with 150 µM lysoPC or no treatment for 24 h. The whisker plot shows all the measurements (pink dots), medians (black line), and minimum and maximum values (whisker ends). For all experiments, the results from at least three biological replicates are shown. Statistical significance was assessed via a t test, with quadruple asterisks indicating significant differences at P < 0.0001. Extended Data Figure 4. A) Top: Transmission electron micrograph of negatively stained thin sections of untreated B. cinerea hyphae with immunogold labeling. The scale bar represents 1 μm for the image on the left and 0.2 μm for the zoomed-in image on the right. Bottom: Immunocytochemistry of Botrytis hyphae treated with TasA without anti-TasA antibodies but with secondary antibodies as a control. Scale bars represent 20 µm. B) Coomassie gel of polysaccharide affinity assays with purified TasA. C) Enrichment analysis of differentially expressed B. cinerea genes after six hours of treatment with 3 µm purified TasA. GO terms enriched by upregulated (top) and downregulated (bottom) genes of B. cinerea after treatment with TasA. D) Quantification of tubulin accumulation in pear hyphae treated with 3 µm purified TasA or left untreated. The whisker plot shows all the measurements (pink dots), medians (black line), and minimum and maximum values (whisker ends). For all experiments, the results from at least three biological replicates are shown. Statistical significance was assessed via a t test, with quadruple asterisks indicating significant differences at P < 0.0001. Extended Data Figure 5. Differential effects of EPS and fengycin on B. cinerea physiology and stress responses. A) Representative confocal microscopy images showing ROS accumulation and the fungal membrane (stained with FM4-64) in B. cinerea hyphae treated with EPS. Scale bars represent 20 µm. The lower panels show transmission micrographs of B. cinerea treated with 0.5 mg/mL purified EPS, revealing nonpronounced ultrastructural disorganization or autophagosome formation. Scale bars represent 2 μm. B) Quantification of ROS levels in B. cinerea without treatment, with H 2 O 2 as positive control, after treatment with 3 µM TasA, 0.5 mg/mL EPS or 10 µM fengycin for 24 h. Whisker plot shows all measurements (pink dots), medians (black line), and minimum and maximum (whiskers ends). In all experiments, at least three biological replicates are shown. Statistical significance was assessed ANOVA by one-way ANOVA with Dunnett’s multiple comparisons test (each treatment vs BcB05 control), with quadruple asterisk indicating significant differences at P < 0.0001. Extended Data Figure 6. Differentially abundant metabolite accumulation in B. cinerea supernatants after TasA and fengycin treatments. Volcano plots showing metabolites with significantly greater or lower accumulation in the B. cinerea supernatant after 24 h of treatment with TasA (left) or fengycin (right) than in the supernatant of untreated B. cinerea . Analyses were performed using MetaboAnalyst. Extended Data Figure. 7. KEGG pathway-based schematics of oxylipins accumulated in Botrytis cinerea supernatant after treatment with fengycin . Two pathway diagrams representing the accumulation of oxylipins derived from linoleic (top scheme) and linolenic (bottom scheme) acids in the B. cinerea supernatant. The accumulated metabolites are colored according to the same scheme as the border node color in Figure 4A . Extended Data Figure 8. Molecular family analysis of bacillaene in B. cinerea supernatant after interaction with wild-type B. subtilis compared with B. cinerea interacting with Δ pps after 48h . Pie charts represent the mean peak abundance of metabolites in the supernatant, with node shapes indicating the level of metabolite identification according to GNPS libraries. Extended Data Figure 9. Mirror plots comparing spectra from named features throughout the manuscript to standard spectra deposited in GNPS . The upper part of the plot (black lines) represents the MS spectra of the candidate feature, and the lower part (green lines) represents the MS spectra of the standard compound. Mirror plots were generated using https://metabolomics-usi.ucsd.edu/ . Supplementary Table 1. B. cinerea B05.10 putative secreted proteins upregulated upon challenging with Fengycin. Supplementary Table 2. List of mutated genes in Botrytis cinerea treated with bacillaene for one week compared with the Botrytis control Supplementary Table 3. List of strains used in this study. Supplementary Table 4. Named features throughout the manuscript and their parameters for identification within the framework of Sumner et al ., 2007. Acknowledgments We thank Saray Morales for providing technical support. We also thank Alicia Esteban from the IHSM microscopy unit, and David Navas, Cristina Lucena and Adolfo Martínez from the SCAI microscopy until, for their technical support in confocal and electronic microscopy. We also thank Josefa Gómez Maldonado and Luís Díaz from the Ultrasequencing Unit of the SCBI-UMA for RNA sequencing and bioinformatic analysis and Mercedes Martín Rufián and Casimiro Cárdenas García from the Proteomic Unit of the SCAI-UMA for their technical suggestions, protein sequencing, and LC□MS analysis. This work was supported by grants from an ERC Starting Grant (BacBio 637971), Agencia Estatal de Investigación of the Ministerio de Ciencia e Innovación (PID2019-107724GB-I00 and PID2022-141664NB-I00), and Junta de Andalucía (P20_00479). A.I.P.L. is funded by the program FPU (FPU19/00289) and the program Plan Propio de Investigación y Transferencia from Universidad de Málaga. C.M.S. is funded by grants from Consolidación Investigadora (CSN2022-135744) and Proyectos dirigidos por jóvenes investigadores de la Universidad de Málaga (B1-2021_21). D.V.C. is funded by the program Incorporación de Doctores PAIDI from Junta de Andalucía (DOC_00266) and Proyecto Jóvenes Investigadores from the Plan Propio de Universidad de Málaga (B1-2021_34). P.S. was supported by the European Union’s Horizon Europe Research and Innovation Programme through a Marie Skłodowska-Curie fellowship (no. 101108450 MeStaLeM). 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