Enhancing soil citrulline degrading function to mitigate soil-borne Fusarium wilt

Ding, Zhexu; Wen, Tao; Teng, Xinyang; Yang, Wenyi; Yuan, Xiaohang; Liu, Xiaoyu; Xie, Penghao; Zhao, Xiangyang; Shen, Qirong; Yuan, Jun

doi:10.1038/s41467-026-68606-x

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Published: 20 January 2026

Enhancing soil citrulline degrading function to mitigate soil-borne Fusarium wilt

Nature Communications volume 17, Article number: 1868 (2026) Cite this article

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Abstract

Continuous cropping often exacerbates soil-borne diseases, particularly Fusarium wilt, yet the intricate rhizosphere relationships among phyto-derived metabolites, pathogens, and particular microbial functions remain poorly understood. Here, we observe that citrulline accumulation during continuous cropping is positively correlated with Fusarium wilt severity by enhancing fusaric acid production in Fusarium oxysporum. Metagenomic analyses reveal that citrulline turnover-related functions, represented by functional modules including M00978, are significantly enriched in healthy rhizosphere soils but are notably reduced in Fusarium-conducive soils. The functional genes, arcB and argH, are identified in Pseudomonas putida YDTA3, with arcB being essential for citrulline-degradation via knockout experiments. The inoculation of an arcB-expressing indigenous Escherichia consortium (EO-arcB) in three independent continuous cropping systems of cucurbit crops demonstrates that enhancing and maintaining the soil citrulline-degrading function mitigates soil-borne Fusarium wilt. In summary, this study advances our understanding of rhizosphere interactions underlying Fusarium wilt disease occurrence and offers a promising biocontrol strategy.

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Introduction

Soil-borne diseases lead to severe crop losses and substantial economic repercussions^1,2,3,4. Typically, continuous cropping obstacles result from the complex interactions among host plants, pathogens and rhizosphere elements, such as plant autotoxins, soil microbial function, and other factors^5,6,7,8. These obstacles lead to the accumulation of root exudates and microbial metabolites in the rhizosphere^9,10, which in turn influence soil microbial communities and contribute to disease development. Rhizosphere metabolites comprise root exudates and microbial metabolites, among which substances detectable by instruments generally linger in the soil for a certain period of time¹¹. This implies that the turnover of these rhizosphere metabolites continuously exerts an influence on the root microbiome. A previous study has identified that five metabolites, including citrulline, drove the deterministic assembly of diseased rhizosphere microbiome, leading to a high incidence of Fusarium wilt in watermelon¹².

The rhizosphere—a thin soil layer immediately adjacent to plant roots—acts as a bustling epicenter of microbial activity and is integral for maintaining plant health¹³. The composition and function of the rhizosphere microbiome not only influence plant resistance to pathogens but also offer opportunities for disease management^14,15. For instance, Sphingomonas and Rhizobium species can activate jasmonic acid and salicylic acid signaling pathways to combat infection by wheat yellow mosaic virus¹⁶. Additionally, construction of synthetic communities composed of rhizosphere bacteria with functions, such as nitrogen fixation, phosphate solubilization, and auxin production, could enhance crop yield¹⁷. Most research focuses on identifying functional microorganisms and elucidating their interaction mechanisms¹⁸. Nevertheless, efforts aimed at discovering and applying key functional genes remain limited. Investigating key functional genes present in the rhizosphere microbiome, particularly those involved in the turnover of specific root metabolites, could expand the functional scope and metabolic capabilities conferred to the soil by the microbial community. In recent years, increasing attention has been directed toward understanding how specific rhizosphere metabolites shape the rhizosphere microbiome and contribute to disease suppression or facilitation. For example, metabolites from pathogens¹⁹, or a large group of organic acids from root exudates²⁰, and possibly secondary metabolites from beneficial bacteria²¹, are all potential factors in this context. Among these, citrulline has not only emerged as a major root exudate in cucurbitaceous crops, but also a metabolite of soil microorganisms. Studies suggest that citrulline, as one of the amino acids, can influence microbial community dynamics across multiple species^12,22,23,24, however, its precise role in shaping rhizosphere functions related to disease progression remains unclear. Understanding the metabolic pathways and functional genes associated with citrulline turnover in the rhizosphere could offer novel insights into soil-borne disease management.

Fusarium wilt, caused by Fusarium oxysporum, is particularly devastating in cucurbitaceous crops due to continuous cropping^8,25,26. Fusaric acid (FA), a key virulence factor produced by F. oxysporum, has been linked to citrulline metabolism^27,28. Experimental evidence shows that citrulline not only promotes FA production in statically cultured fungal hyphae but may also serve as a precursor for FA synthesis, as indicated by isotope tracing experiments^29,30. Additionally, citrulline has been reported to play a broader regulatory role in pathogenic Fusarium species, exemplified by its involvement in the induction of deoxynivalenol in F. graminearum and fumonisins in F. proliferatum^31,32. As an organic nitrogen compound, citrulline’s role may also be intertwined with nitrogen availability. Indeed, nitrogen sources have been shown to considerably influence FA production^33,34, with high nitrogen conditions enhancing the expression of Fub genes, leading to increased FA synthesis²⁸. Notably, citrulline is abundantly present in Cucurbitaceae phloem and has long been recognized as an organic nitrogen carrier, raising the possibility of its involvement in host-pathogen interactions^35,36,37. Nevertheless, the relationship between rhizosphere-derived citrulline, FA production by F. oxysporum, and disease incidence in continuous cropped watermelon remains poorly understood. Supporting its broader role in plant–pathogen interactions, citrulline has also been implicated in the infection process of Phytophthora cactorum in leaf tissues³⁸. Together, these findings highlight citrulline as a potentially important factor in host-pathogen dynamics, yet its interactions with soil-borne pathogens and their implications for pathogenicity remain inadequately understood.

In this work, given the critical role of citrulline in FA production by F. oxysporum and its potential to accumulate under continuous cropping and reshape rhizosphere microbial functions, we aim to identify the key microbial functions impaired during this process as a means to disrupt this pathogenic mechanism. Here, we demonstrate that (1) citrulline accumulation in the rhizosphere could enhance the Fusarium oxysporum f. sp. niveum (FON) virulence via FA generation; (2) citrulline turnover-related functional pathways are weakened in the rhizosphere of cucurbitaceous crops under continuous cropping; and (3) uncovering and expanding the application of these microbial functions in the soil can effectively control Fusarium wilt.

Results

Citrulline facilitates the Fusarium wilt under continuous cropping conditions by enhancing the FA production

To investigate the relationship between citrulline and the occurrence of Fusarium wilt under continuous cropping conditions, we first collected rhizosphere soil samples associated with watermelon from various regions. These included uncultivated soil, healthy soil, disease-suppressive, initial Fusarium-infested soil, and Fusarium-conducive soil (Supplementary Table 1). Content analysis revealed that the citrulline levels in initial Fusarium-infested soil and Fusarium-conducive soil were significantly higher than those in uncultivated soil, healthy soil and disease-suppressive soil (Fig. 1a, Kruskal-Wallis, P < 0.001). To assess the impact of citrulline content on watermelon Fusarium wilt, a pot experiment was conducted by adding citrulline to the previously collected soils. A significant increase in disease incidence was observed in both healthy and disease-associated soils due to citrulline addition (Fig. 1b, one-way ANOVA, P < 0.001). Meanwhile, watermelons grown in soils incubated with different concentrations of citrulline (1 μM, 100 μM, and 10 mM) exhibited a fast disease progression and high incidence of Fusarium wilt (Fig. 1c). An ordinary least squares (OLS) regression revealed a significant positive correlation (Fig. 1d, adjusted R² = 0.936, P < 0.001) between citrulline concentration and Fusarium wilt incidence in diseased soil samples. In contrast, no significant correlations were observed in healthy soil (R² = 0.010, P = 0.848), uncultivated soil (R² = 0.031, P = 0.651), and disease-suppressive soil samples (R² = 0.024, P = 0.772) (Supplementary Fig. 1).

**Fig. 1: Citrulline facilitates Fusarium wilt under continuous cropping conditions by enhancing FA production.**

To further investigate the mechanism underlying the disease-promoting effect of citrulline, an in vitro experiment was conducted by culturing the Fusarium oxysporum f. sp. niveum (FON) with citrulline. All citrulline concentrations significantly enhanced the FA production by FON (Fig. 1e, Kruskal-Wallis, P < 0.01). Simultaneously, the expression of the gene cluster (Fub1 - Fub4) encoding FA biosynthesis in FON significantly increased with citrulline utilization (Fig. 1f, Supplementary Fig. 2, Supplementary Table 2, Kruskal-Wallis P < 0.001). When citrulline was nearly depleted, the gene expression approached the initial level (Fig. 1f, Supplementary Fig. 2). There was a sharp increase in gene expression after citrulline resupply for 30 min (Fig. 1f, Supplementary Fig. 2). Additionally, the relative expression of the Fub5 gene encoding the biosynthesis of a more toxic FA metabolite—FA methyl ester, exhibited the same trend (Supplementary Fig. 2, Supplementary Table 2).

Citrulline turnover functions are enriched and diagnostically important in healthy rhizosphere soils

To explore the variation in citrulline-related microbial functions in continuous cropping soils, the rhizosphere soil samples collected from continuous cropping watermelon fields at three geographic locations were subjected to metagenomic sequencing analysis (Supplementary Table 3). More than 811.25 million clean reads were generated for the 26 samples, yielding a total of 43,193,998 contigs after assembly. To accurately determine the genes and pathways involved in citrulline metabolism, metagenomic sequences were annotated using the KEGG database, and the identified genes were subsequently mapped to corresponding KEGG Orthology, MODULE and PATHWAY levels. The PCoA with Bray-Curtis distance showed a significant difference among healthy and diseased samples (Fig. 2a, Supplementary Fig. 3a, b, ANOSIM R = 0.82, P < 0.01). KEGG differential analysis at the module level (P < 0.01; fold change > 1.5) revealed that 22 of the top 30 significantly altered modules were related to amino acids metabolism and other organic acids metabolism (Fig. 2b, Supplementary Data 1). Analysis of the PCA loading matrix and PLS-DA VIP scores identified three functional modules that consistently contributed to distinguishing healthy from Fusarium-conducive rhizosphere soils, including M00978 (Fig. 2c, Supplementary Fig. 4). Among these three modules, module M00978, which is directly involved in citrulline anabolism, was more abundant in healthy samples, showing an 11.53% higher relative abundance compared with diseased samples (Fig. 2b, Supplementary Data 1). Further analysis revealed that all the reactions comprising module M00978 were significantly more abundant in healthy samples than in Fusarium-conducive soils (Fig. 2d, Supplementary Data 2,P < 0.05). By constructing a co-occurrence network using reactions as nodes, we found that network modules associated with citrulline degradation were clearly clustered in healthy samples (Fig. 2e, Supplementary Table 4). Subsequently, all genes contained in these network modules were subjected to Gene Set Enrichment Analysis (GSEA), which revealed that these genes belonged to the arg gene cluster and were involved in reactions, such as R01954, R01398, R09107, and R07245 (Fig. 2f).

Fig. 2: Citrulline turnover function was relatively suppressed in Fusarium-conducive soils. — **Fig. 2: Citrulline turnover function was relatively suppressed in *Fusarium*-conducive soils.**

Mining and verifying key microbial citrulline degrading genes

Based on the identification of the primary modules and reactions involved in citrulline turnover, we further determined the taxonomic origins of these potential functional genes in the diseased samples. The flow plots indicated that the majority of functional genes originated from genera, such as Sphingomicrobium, Nitrosospira, Pseudomonas, Mesorhizobium, Lysobacter (Fig. 3a, Supplementary Table 5). In particular, citrulline-amended microcosm incubations conducted for 8 weeks (Supplementary Fig. 5) enriched taxa including Pseudomonas, Lysobacter, and Pseudarthrobacter, confirming citrulline-driven microbial selection (Fig. 3b, Supplementary Table 6). Among these bacteria, Pseudomonas showed the maximum increase in relative abundance (Control: 3.12%, Cit: 7.09%). qPCR-based absolute quantification showed that Pseudomonas 16S rRNA gene copy numbers also increased (Supplementary Fig. 6). Moreover, the treatment and control groups exhibited significant differences in both bacterial diversity and community structure (Supplementary Figs. 7-8, Kruskal-Wallis, P < 0.05). Meanwhile, modular analysis of microbial networks at the genus level revealed that Pseudomonas was present in most hub modules across the soil incubated with citrulline (Fig. 3c).

**Fig. 3: Mining and validating key microbial functional genes for citrulline degradation.**

To further identify potential microbial hosts of functional genes, the top 40 genera from each treatment were ranked by their importance using the random forest model as the classifier. Among them, Pseudomonas scored the highest among all the bacterial genera (Supplementary Fig. 9, Supplementary Table 7). Then, a Pseudomonas strain with the ability to degrade citrulline was isolated by employing a high-throughput screening strategy. In detail, the citrulline degradation ability of the selected strain was preliminarily assessed by adding bromocresol purple to the medium containing citrulline as the sole carbon and nitrogen source. A color change from yellow to purple was observed due to NH₃ production via the arginine deiminase (ADI) pathway (Supplementary Fig. 10).

To mine the functional genes, the strain Pseudomonas putida YDTA3 (hereinafter referred to as P. putida YDTA3) was identified by whole-genome sequencing and average nucleotide identity (ANI) analysis (Fig. 3d, Supplementary Fig. 11). Citrulline metabolism pathways, including the arc and arg gene clusters, were identified through whole-genome functional annotation and homology comparison (Fig. 3e). Among these, arcB and argH genes directly encode enzymes responsible for citrulline metabolism (Supplementary Table 8). Interestingly, arcB and argF (which belongs to the same arg gene cluster as argH) were identified as homologous genes of the key gene K00611 in the metagenome, encoding catabolic ornithine carbamoyltransferase (α-OTC) and anabolic ornithine carbamoyltransferase (β-OTC), respectively (Supplementary Fig. 12). Further in vitro testing of the citrulline degradation ability revealed that this functional gene bearer could degrade more than 95% of the citrulline within a short period (Fig. 3f). Additionally, these two genes were significantly upregulated when the strain was cultured in a medium containing citrulline as a sole carbon and nitrogen source (Supplementary Fig. 13, one-way ANOVA, P < 0.01), thereby confirming the involvement of arcB and argH of P. putida YDTA3 in citrulline metabolism.

By using homologous recombination-based tri-parental conjugation, we knocked out specific functional genes to construct mutant strains ΔarcB and ΔargH (Fig. 3e, Supplementary Figs. 14-15). The expected linker fragments (992 and 1172 bp) of the upstream arm, resistance gene fragments and downstream arm in genomic DNA samples of ΔarcB and ΔargH mutants were confirmed by Polymerase Chain Reaction (PCR) (Supplementary Fig. 16). The ΔarcB and ΔargH mutants exhibited significantly reduced growth rates and citrulline degradation rates in vitro compared to the wild-type strain (Fig. 3g, one-way ANOVA, P < 0.001; Supplementary Fig. 17, Kruskal-Wallis, P < 0.001). Notably, the ΔargH mutant exhibited a slightly higher growth rate and citrulline degradation rate than the ΔarcB mutant when citrulline was used as the sole nitrogen source (Fig. 3g, one-way ANOVA, P < 0.001; Supplementary Fig. 17, Kruskal-Wallis, P < 0.001). In addition, targeted quantification of downstream products following citrulline degradation revealed distinct metabolic shifts among the wild-type and mutant strains (Fig. 3h, Student’s t-test, P < 0.001). In the ΔarcB mutant, arginine accumulation was markedly increased, while ornithine remained at a low level, indicating that arcB is essential for the catabolic conversion of citrulline to ornithine. Conversely, the ΔargH mutant exhibited elevated levels of ornithine but failed to accumulate arginine, suggesting that disruption of argH hampers the anabolic conversion of citrulline to arginine. The wild-type strain showed balanced accumulation of both products over time, reflecting intact functionality of the full metabolic pathway.

Enhancing citrulline degradation ability in soil for the biocontrol of Fusarium wilt

Pot experiments confirmed that application of functional gene bearer — P. putida YDTA3— significantly reduced disease incidence in simulated continuous watermelon cropping systems (Supplementary Fig. 18). Furthermore, subsequent trials with gene knockout strains demonstrated that deletion of arcB resulted in high disease incidence, whereas deletion of argH exhibited a moderate effect (Supplementary Fig. 19). In line with this, application of the ΔarcB strain in pots indeed did not significantly eliminate citrulline accumulation in the rhizosphere (Supplementary Fig. 20). These observations spurred us to further investigate the function of arcB within biocontrol of Fusarium wilt. It is worth highlighting that metagenomic analysis revealed a significantly higher frequency of taxa harboring the K00611 gene (arcB homologous gene) in healthy samples as opposed to diseased ones. This trend was consistent across multiple taxonomic levels—including phylum, class, order, family, and genus (Supplementary Table 9)—with Pseudomonas spp. accounting for a notable proportion. Based on this observation, we initially sought to evaluate the efficacy of P. putida YDTA3 in a realistic pot-based continuous cropping system to test its effect on disease mitigation. Unexpectedly, the disease mitigation effect of P. putida YDTA3 declined progressively across planting generations in the pot experiments (Fig. 4a). This trend became increasingly evident over successive cropping cycles, suggesting that its colonization efficiency in the rhizosphere may have been suboptimal under continuous cropping conditions (Supplementary Fig. 21, one-way ANOVA, P < 0.05). Therefore, we aimed to reconstruct a microbial community containing the functional gene to sustain the reduction of citrulline accumulation in continuous watermelon cropping systems. As part of a function-validation–oriented strategy, we selected Escherichia spp. as the engineered host. Simultaneously, absolute quantities of Escherichia spp. remained statistically invariant across the 1st, 5th, and 8th generations of continuously cropped watermelon (P = 0.914, one-way ANOVA), with a mean value of 5.8 × 10⁷ copies g^-1 soil in rhizosphere samples (Supplementary Fig. 22). Using a selective medium (eosin methylene blue, EMB), we isolated a batch of Escherichia strains (E-consortium) from the rhizosphere soil that exhibited minimal citrulline degradation ability (Supplementary Fig. 23). Next, a simplified electroporation-based method was employed to introduce the arcB gene into the above Escherichia strains (Supplementary Fig. 23). In vitro cultivation experiments showed that the genetically modified E-consortium (EO-arcB) could efficiently degrade up to 95% of citrulline within 60 h (Fig. 4b). SDS-PAGE analysis further revealed that the target enzyme was robustly expressed in EO-arcB as soluble proteins, both intracellularly and extracellularly (Supplementary Fig. 24). Furthermore, in the multi-crop continuous cropping pot trials involving watermelon, pumpkin and cucumber, the application of EO-arcB demonstrated that the disease mitigation effect was more pronounced than that of P. putida YDTA3 (Fig. 4a). This enhanced effect may be attributed to the more stable and efficient rhizosphere colonization capacity of EO-arcB, which sustained functional gene activity over continuous cropping generations (Supplementary Fig. 25, one-way ANOVA, P < 0.001). Moreover, this intervention effectively prolonged the soil’s ability to degrade citrulline (Fig. 4c, as measured by the number of continuous cropping generations). Upon reaching the fifth season of continuous cropping, significant differences in disease incidence and growth conditions became evident among the various treatments (Figs. 4d–f, Supplementary Table 10).

**Fig. 4: Enhancing citrulline degradation ability within soil for the biocontrol of Fusarium wilt.**

To specifically investigate the disease-suppressive mechanisms of EO-arcB, microbial consortia were randomly assembled based on different phylogenetic branches of individual colonies isolated from the EO-arcB (Supplementary Fig. 26), which were designated as EO-3, EO-5, EO-7, and EO-9 (detailed group information in Supplementary Data 3). After the application of these four consortia in the simulated continuously cropped watermelon system, it was found that the greater the number of soil microorganisms performing this function, the lower the severity of Fusarium wilt in cucurbit crops under continuous cropping obstacles (Supplementary Fig. 27, Kruskal–Wallis, P < 0.001). Moreover, the estimated half-life of the arcB gene in these soils further supported this effect (Supplementary Fig. 28).

Discussion

Continuous cropping, a common agricultural practice, often exacerbates the prevalence and severity of soil-borne diseases. The accumulation of pathogens in the rhizosphere has long been considered a primary factor contributing to the increased incidence of plant diseases under continuous cropping systems. The underlying mechanisms driving this phenomenon have been a subject of intensive research, with pathogen accumulation being a primary suspect. However, recent evidence suggests that the complexity of continuous cropping systems extends beyond mere pathogen buildup³⁹.

The escalating disease severity in continuous cropping systems may involve additional underlying factors that remain to be fully elucidated. Our preliminary research revealed that citrulline is a key component in shaping the community structure of rhizosphere soil samples obtained from several diseased crops affected by continuous cropping⁴⁰. Based on this, we focused on watermelon—a crop with well-documented citrulline research^41,42,43,44—to conduct an in-depth examination of the influential role of citrulline in the rhizosphere, particularly under conditions where Fusarium wilt is prevalent in cucurbit crops under continuous cropping systems. The increased levels of citrulline observed in disease-associated soils suggest a possible correlation between citrulline accumulation and the prevalence of Fusarium wilt. This hypothesis was further supported by our pot experiments, which confirmed a positive correlation. During infection, plant pathogens utilize virulence factors to subvert plant immunity and establish infection⁴⁵. However, the interplay between these virulence factors and root metabolites in the context of continuous cropping has been largely unexplored territory, prompting us to investigate the relationship between plant-secreted citrulline and pathogens.

Previous studies indicated that citrulline acts as a precursor in the biosynthesis of FA³⁰, a critical virulence factor produced by Fusarium oxysporum, which is instrumental in the severity of wilt diseases across a spectrum of crops⁴⁶. Additionally, Stipanovic et al. demonstrated a novel mechanism involving the incorporation of amino acids (or derivatives) in FA biosynthesis⁴⁷, which was more pronounced under nitrogen-sufficient conditions²⁸. Consistent with this research perspective, our in vitro experiments revealed that citrulline enhanced FA production by upregulating the expression of the Fub gene cluster. Notably, citrulline considerably promoted the expression of Fub5, which encodes the enzyme responsible for FA methyl ester synthesis—a more toxic downstream product of FA²⁷. It is well established that citrulline is metabolized to arginine, which can be further processed into ornithine and other compounds that feed into secondary metabolite pathways⁴⁸. This metabolic link could explain why citrulline application promotes FA production. The restoration of pathogenicity in the ARG1 mutant strain of F. oxysporum f. sp. melonis by arginine supplementation also indicates the importance of this metabolic link for the production of FA⁴⁹. These collective findings suggest that citrulline accumulation in soil intensifies FA production, thereby aggravating the impact of Fusarium wilt in continuous cropping systems.

The differential citrulline accumulation in healthy and diseased samples prompted a further exploration of the associated microbial functions. Given the specific research focus on citrulline-related functions, functional annotation was directly performed at the module level using the KEGG MODULE database. Module M00978 (ornithine-ammonia cycle), an extension of the urea cycle, plays a role in ammonia detoxification⁵⁰. This functional cycle was highly enriched in the rhizosphere of healthy crops and ranked among the top in importance for distinguishing between healthy and diseased states. This finding is consistent with previous reports that various identified pathways involved in the degradation of autotoxic compounds were enriched in the rhizosphere microbiota under healthy conditions¹². Notably, module M00978 participates in energy regulation as a bypass to the top-ranking module M00173 (reductive citrate cycle)⁵¹. Previous studies have shown that under stress conditions, amino acids can be converted into substrates of the citric acid cycle to generate energy⁵¹. Additionally, the arginine deiminase pathway (ADI, arginine-citrulline-ornithine), which is unique to microorganisms affiliated with module M00978, does not consume energy. This allows the generated ATP to be fully utilized for other energy-demanding processes⁵². This adaptation is considered an evolutionary advantage for microbial communities in facilitating hosts adapt to complex and changing environments⁵². GSEA and random forest models of related genes in an interaction network indicated that homologous genes responsible for key reactions in modules M00978, M00844, and M00845, such as K00611 (R01398) and K01438 (R09107), play important roles in shaping the functional profile of the rhizosphere microbiome in healthy soils. Importantly, these genes were found to be homologous to the arg gene cluster in most microbial genomes⁵³. Taken together, analyses from modules to reactions and then to genes consistently reflected that citrulline turnover functions were relatively suppressed in diseased samples.

The hypothesis of removing harmful rhizosphere exudates or metabolites to maintain crop health has been proposed in previous studies^54,55. However, citrulline cannot be simply classified as a harmful exudate, given its role in alleviating oxidative stress in plants⁵⁶. Considering the positive relationship between citrulline accumulation and increased soil-borne disease incidence, as well as the critical role of citrulline turnover functions in healthy samples (Figs. 1,2), we hypothesized that enhancing the soil’s citrulline degradation ability could mitigate soil-borne diseases. First, the functional gene bearer P. putida YDTA3 was isolated through substrate induction by citrulline in soil. The core module of OTUs in the microbial symbiotic network further underscored the importance of this functional gene bearer. Consistent with previous studies, the ADI pathway, involving the arcB gene, has been reported in Saccharomyces cerevisiae, Lactobacillus sakei, and Enterococcus faecium^52,57. Another pathway involving the argH gene has been observed in Escherichia coli and Corynebacterium glutamicum^58,59. The coexistence of both pathways in the functional gene bearer indicated that it is highly adaptable to variations in citrulline levels. Furthermore, the construction of two gene knockout mutants and in vitro experiments demonstrated the functional gene bearer’s strong citrulline degradation capacity (Fig. 3).

Second, the effectiveness of this function was confirmed by its application to mitigate soil-borne diseases. However, the colonization efficiency of the functional gene bearer P. putida YDTA3 declined with increasing continuous cropping generations. Inspired by previous studies employing Escherichia as a functional chassis in soil systems^60,61, we constructed an indigenous Escherichia consortium (EO-arcB). The relative abundance of Escherichia remained stable over multiple cropping generations, suggesting the presence of a resilient microbial community amenable to bio-augmentation strategies⁶². Unlike previous strategies that involved designing synthetic microbial consortia for biocontrol purposes^63,64, EO-arcB was used solely in controlled pot experiments as a tool for functional validation, specifically to assess the impact of enhanced citrulline degradation on disease progression. Although the exact number of microbial taxa involved remains undetermined, EO-arcB showed superior persistence in citrulline removal and enhanced disease control under continuous cropping conditions (Fig. 4). This highlights the importance of stability and longevity of introduced traits for successful bio-augmentation. Nonetheless, we acknowledge the concerns regarding the use of genetically modified organisms (GMOs) in agriculture, as they may pose ecological risks or unintended impacts on human health⁶⁵. Therefore, for future practical applications, alternative approaches should be considered, such as (1) activating native rhizosphere microbes with citrulline-degrading functionality using specific inducing agents; or (2) formulating bio-organic fertilizers containing diverse microbial communities with this functional potential, thereby enhancing the functional biodiversity of soil ecosystems.

In conclusion, our study identified a pathogenic mechanism in continuous cropping systems: citrulline accumulation in the rhizosphere facilitates toxin production by Fusarium oxysporum, coupled with the relative suppression of citrulline turnover functions in Fusarium-conducive soils (Fig. 5). We further proposed a strategy to mitigate soil-borne Fusarium wilt by enhancing and sustaining soil citrulline-degrading function through the use of indigenous microbial communities. This capacity was identified from the functional gene bearer P. putida YDTA3. The elucidation of molecular mechanisms and the application of the indigenous Escherichia consortium (EO-arcB), which expresses the key functional arcB gene, in a multi-cucurbit crop continuous cropping system confirmed our hypothesis. These findings highlight the potential of utilizing ubiquitous indigenous engineered microbial communities to neutralize pathogen-derived toxins, offering a promising strategy for integration into sustainable agricultural practices.

**Fig. 5: The pathogenic mechanism of Fusarium wilt under continuous cropping systems and mitigation by enhanced citrulline degradation capacity.**

Methods

Soil samples collection

Rhizosphere soils associated with continuous watermelon cropping were collected from different regions (Supplementary Table 1). Five rhizosphere soil types were sampled: (i) Initial Fusarium-infested soil was collected from plants exhibiting early-stage Fusarium wilt symptoms (e.g., partial leaf yellowing without vascular necrosis, disease index <30%). (ii) Fusarium-conducive soil was collected from plants showing typical wilt symptoms (e.g., vascular necrosis, root decay, and disease index > 65%) in fields under continuous cultivation for at least three years. (iii) Disease-suppressive soil was collected from asymptomatic plants in continuous-cropped fields with confirmed Fusarium oxysporum presence⁴⁰. (iv) Uncultivated soil was collected from the surface layer (0–20 cm) of a field at Baima Teaching and Research Base of Nanjing Agricultural University, Nanjing, China (31°36'50“N, 119°11'02“E) with no history of cucurbit crop cultivation. (v) Healthy soil was collected from well-performing watermelon plants with good yield. The purpose of distinguishing these types of soils is to more clearly characterize differences in citrulline content.

Diseased samples were identified following the method of Wen et al.¹² with minor modifications. The diseased root tissues were ground, diluted, and spread on the Nash-Snyder Fusarium selective growth medium⁶⁶. Plates were incubated at 28 °C for two days, and the appearance of Fusarium colonies confirmed that the samples were diseased. Information on other soils is listed in Supplementary Table 1. Each set of rhizosphere soil samples representing different watermelon health statuses (a total of five sets) consisted of six replicates, with each replicate comprising combined rhizosphere soils from three individual plants. Rhizosphere soil samples were obtained by first gently shaking the roots to dislodge loosely adhering bulk soil. Under sterile conditions, the root tissues were then immersed in 50 mL sterile centrifuge tubes containing 20 mL of phosphate-buffered saline (PBS; 10 mM, pH 7.4) and shaken at 200 r.p.m. for 10 minutes. The resulting root-associated rhizosphere soil suspension was subsequently freeze-dried to obtain solid material (rhizosphere soil), which was stored at −80 °C for subsequent citrulline content testing, DNA extraction, and pot experiments simulating continuous cropping.

Extraction and quantification of citrulline and its converted compounds in soil or solution

Citrulline extraction from soil was performed following the method of Jones et al. with modifications⁶⁷. Briefly, 4 grams of rhizosphere soil were weighed and transferred into 50 mL centrifuge tubes, and 20 mL of 2 M KCl extraction solution was added to each tube. The tubes were placed on a reciprocal shaker at 220 r.p.m. for 1 h and then centrifuged at 16,000 × g for 15 min. The supernatant was filtered through a 0.22 μm microporous membrane and then concentrated 50-fold using a vacuum concentrator (Concentrator Plus, Eppendorf AG, Hamburg, Germany). For liquid bacterial cultures, 2 mL of culture was centrifuged at 5000 × g for 5 min. The supernatant was filtered through a 0.22 μm microporous membrane and then concentrated 5-fold using a vacuum concentrator. All the concentrated samples were subsequently stored at -20 °C until analysis.

Detection of Citrulline and its converted compounds detection was conducted using pre-column derivatization high-performance liquid chromatography (HPLC) with o-Phthaldialdehyde (OPA), following and optimizing the protocols outlined in the Agilent Application Guide⁶⁸. Specifically, 3 μL of borate buffer (0.5 M, pH=8.0, Macklin Inc., Shanghai, China), 1 μL of sample, and 1 μL of OPA derivatization reagent (79760, Sigma-Aldrich, St Louis, MO, USA) were mixed, followed by immediate injection after the pre-column derivatization procedure (Supplementary Table 11). The column temperature was set to 35 °C, and separation was achieved on an Eclipse XDB-C18 column (4.6 × 250 mm, 5 μm), with a post run time of 13 min. Fluorescence detection was performed on an Agilent 1260 Infinity system coupled with a 1260 Infinity Fluorescence Detector (Agilent Technologies, MA, USA). The excitation and emission wavelengths were 340 and 450 nm, respectively.

A binary mobile phase was used for amino acid elution. Mobile phase A consisted of 8 g L^-1 anhydrous sodium acetate and 5 mL L^-1 tetrahydrofuran, adjusted to pH 7.2 with glacial acetic acid. Mobile phase B consisted of anhydrous sodium acetate, water, methanol, and acetonitrile in a ratio of 1:50:100:1000 (m: v: v: v). Both mobile phases were vacuum filtered to remove impurities and degassed using ultrasonication. The elution program is detailed in Supplementary Table 11.

For standard curve preparation, 0.05 g of L-citrulline standard (B21918, HPLC ≥ 98%, Yuanye Biological Co., Ltd., Shanghai, China) was weighed, dissolved in 50% methanol solution, and diluted to a final volume of 100 mL, yielding a stock solution with a concentration of 500 mg L^-1. Serial dilutions were prepared to obtain L-citrulline concentrations of 400, 200, 100, 50, 20, 10, 2, 1, 0.2, and 0.1 mg L^-1. Fluorescence intensity (LU) was plotted against citrulline concentrations (mg L^-1) to construct fluorescence standard curves for citrulline detection by HPLC. The fluorescence standard curve and the detection fluorescence curves are shown in Supplementary Fig. 29.

Pot experiment on simulating continuous cropping conditions (SCCC)

Based on the observed increasing trend in citrulline content during continuous watermelon cropping, we incubated the collected soils (described in the Soil samples collection section) with citrulline to simulate continuous cropping conditions. Specifically, citrulline solution (1 mM unless otherwise specified) was applied at a frequency of twice per week (20 mL each time) until the crops reached the third true-leaf stage.

The pot experiment on SCCC was conducted as follows: the soil matrix was prepared by mixing the collected soils or citrulline-applied soils with vermiculite and humus soil in a volume ratio of 1: 2: 2. Watermelon seeds (Zaojia 8424, Xinjiang Farmer Seed Technology Co., Ltd., China) were surface-disinfected with 75% ethanol for 30 s before germination, followed by 5 min surface disinfection with 2% NaClO. The seeds were then rinsed five times with sterile water, and pre-germinated in a sterile Petri dish at 25 °C for 3 days. Three uniformly germinated seeds were sown in each pot (length × width × height = 10 × 10 × 12 cm) containing 300 g of above the soil matrix, and randomly placed in a growth chamber (28 °C during the day and 26 °C at night, relative humidity 70%, 180 μmol m^-2 s^-1 light). When the watermelon seedlings reached the third true-leaf stage, 20 mL of a FON spore suspension (5 × 10⁴ CFU mL^-1) was applied. The FON strain used in this experiment was stored in our laboratory at -80 °C in glycerol. To obtain the spores, the frozen FON strain was first cultured on potato dextrose agar (PDA) medium at 28 °C for 72 h and then transferred to fresh potato dextrose broth (PDB) and cultured for 1 week at 28 °C. The spore suspension was filtered using eight layers of sterile gauze, followed by centrifugation at 2000 × g for 10 min to remove the fermentation broth. The final concentration was adjusted to 5×10⁴ CFU mL^-1 with sterile water.

A total of eight treatments were set up based on different soil sources: 1. Uncultivated soil; 2. Healthy soil; 3. Disease-suppressive soil (Supplementary Table 1); 4. Healthy soil + citrulline; 5. Initial Fusarium-infested soil; 6. Initial Fusarium-infested soil + citrulline; 7. Fusarium-conducive soil; 8. Fusarium-conducive soil + citrulline. Each treatment included six replicates, with 50 plants per replicate. The disease incidence was counted 28 days after pathogen spore suspension addition.

Pot experiment with citrulline addition at different concentrations

In the pot experiment, the soil matrix was prepared by mixing uncultivated soil, vermiculite, and humus soil at a volume ratio of 1:2:2 (300 g per pot). Prior to planting, the soil matrix was pre-conditioned with sterile citrulline solutions at the indicated concentrations for 2 weeks, while the H₂O group received an equal volume of sterile water. The applied citrulline concentrations (1 μM, 100 μM and 10 mM) correspond to estimated soil concentrations of approximately 0.018, 1.752 and 175.190 μg g⁻¹, respectively, after each application. The preparation of the pot experiments (seed germination, inoculation, and pot cultivation conditions; FON spore suspension and rhizosphere inoculation) was conducted as described above (see section Pot experiments on SCCC). Five treatments were established: (1) Cit-10 mM; (2) Cit-100 μM; (3) Cit-1 μM; (4) H₂O (pathogen-inoculated control) and (5) Control (no pathogen added). Each treatment included six biologically independent replicates, and each replicate consisted of 50 individual pots (one plant per pot). Disease incidence was recorded every two days starting on the 14th day after pathogen inoculation.

Assessing the relationship between citrulline and virulence factors of FON

In vitro culture experiment of FON

To assess the impact of different citrulline concentrations on FA production, FON was cultured in vitro using citrulline (0, 50, 500, 5000 μM). The preparation of the FON spore suspension (1×10⁷ CFU mL^-1) was conducted as described above.

The FA extraction and detection were modified based on the method of Smith et al. ⁶⁹. Briefly, the fungal cultures were centrifuged at 4000 × g for 20 min to pellet mycelia and conidia. The pH of the supernatant was adjusted to 3.0 using 2 M HCl. The acidified supernatant was then extracted three times with dichloromethane. The combined dichloromethane extracts were evaporated to dryness under vacuum at 45 °C using a rotary evaporator. The residue was resuspended in 2 mL methanol and quantified by high-performance liquid chromatography (HPLC) on an Agilent 1260 series HPLC system (Agilent Technologies) equipped with an Agilent Zorbax Eclipse XDB-C18 column (4.6 × 250 mm, 5 µm) with a column temperature of 50 °C. The samples (10 µL) were eluted using a mobile phase of methanol: 0.43% o-phosphoric acid (68%: 32%) for approximately 15 min at a flow rate of 1 mL min^-1. FA detection was performed at 271 nm, and quantification was achieved using a standard curve derived from FA (55952, Sigma-Aldrich, St Louis, MO, USA).

Additionally, for the pathogen cultured in medium containing 5 mM citrulline, 5 mL of the culture medium was collected daily. After centrifugation at 8000 × g for 20 min, the supernatant was used to determine citrulline content. The resulting pellet containing mycelia and spores was immediately snap-frozen in liquid nitrogen and stored at -80 °C for subsequent RNA extraction.

qPCR analysis of FA-encoding genes

RNA was extracted from the above FON culture samples collected at various time points using the Fungal RNA Kit (R6840, Omega Bio-Tek, Norcross, GA, USA) according to the manufacturer’s instructions. The quality and concentration of RNA were assessed using agarose gel electrophoresis and NanoDrop spectrophotometer (ND2000, Thermo Scientific, DE, USA). First-strand cDNA synthesis was performed following the protocol provided with the BeyoRT™ Q cDNA Synthesis Kit (D7190M, Beyotime Biotechnology Co., Ltd., Shanghai, China). Gene-specific primers (listed in Supplementary Table 2) were then used to amplify the genes Fub1-Fub5 via quantitative PCR (qPCR). The qPCR was carried out in a 10 μL reaction mixture containing 1 μL of cDNA and 5 μL of ChamQ SYBR Color qPCR Master Mix (High ROX Premixed, Q441, Vazyme Biotech Co., Ltd., Nanjing, China). The cycling conditions were as follows: initial denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s, and extension at 72 °C for 30 s. These conditions were repeated for 40 cycles on the StepOnePlus™ Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) and analyzed with StepOnePlus V2.3 software. The mRNA expression levels were normalized to the expression levels of the housekeeping gene ACTIN. Fold changes are presented as 2^−ΔΔCt (ΔΔCt = ΔCt_treatment − ΔCt_control).

Isolation and functional analysis of functional gene bearer

Soil microcosm experiment

To identify the soil microorganisms that respond to the persistent presence of citrulline, we incubated uncultivated soil (Supplementary Table 1, described in the Soil samples collection section) under citrulline amendment for two months under four treatment levels: 0 (control), 1 μM, 100 μM, and 10 mM. The cultivation protocol was slightly modified from a previously described method^40,70,71. Prior to cultivation, 50 g of soil was placed in 12 cm diameter Petri dishes and pre-incubated in a growth chamber at 28 °C for two weeks to allow microbial community stabilization. Subsequently, 5 mL of citrulline solution at designated concentrations was added to each soil microcosm dish twice per week, while the control group received an equal volume of sterile water. Based on application frequency and soil mass, the corresponding citrulline concentrations in soil after each addition were estimated at approximately 0, 0.018, 1.75, and 175.19 μg g^-1, respectively. Each treatment included 30 dishes, randomly arranged in the growth chamber during the incubation period. Soil moisture was maintained at 70% of the water holding capacity by weekly weight measurement and adjustment using sterile deionized water. After 8 weeks, soils from each microcosm dish were collected. For each treatment, the 30 dishes were randomly assigned to six groups, and 2 g of soil from each dish within a group was pooled and homogenized to generate six replicates, which were stored at -80 °C for subsequent DNA extraction.

The absolute quantification of Pseudomonas spp. 16S rRNA genes by qPCR

The absolute copy numbers of genus-Pseudomonas-specific 16S rRNA genes in soil samples (control and 10 mM treatment) were quantified by absolute qPCR. Primer sequences⁷² (forward: GACGGGTGAGTAATGCCTA; reverse: CACTGGTGTTCCTTCCTATA) were adopted following the protocols described by Johnsen et al. ⁷³ and Tao et al.⁷⁴, with the corresponding thermal cycling parameters. An external plasmid standard containing the target amplicon was used to generate a 10-fold serial dilution calibration curve, and results are reported as gene copies per gram of dry soil (copies g^-1). For standard-curve generation, the genus-Pseudomonas 16S rRNA amplicon was cloned into a plasmid and serially diluted (10⁰–10⁷ copies per reaction). Amplification efficiency was maintained within 90–110% with R² ≥ 0.99. This qPCR metric reflects the absolute gene copy number of Pseudomonas spp. in soil and is analytically distinct from percentages derived from amplicon sequencing.

In vitro isolation and identification of functional gene bearer

Soil samples incubated with 100 μM citrulline were subjected to dilution plating onto Cetrimide-Fucidin-Cephaloridine (CFC) agar plates to isolate functional gene bearers⁷⁵. Plates were incubated at 28 °C for 6 days. Single colonies with distinct morphologies were selected and streaked onto minimal medium (MM) agar plates⁷⁶ supplemented with citrulline and bromocresol purple. The plates were then incubated overnight at 28 °C. Strains exhibiting a strong purple reaction were selected for further screening⁷⁷.

Single colonies of the selected Pseudomonas strains were inoculated in LB broth containing 5 mM citrulline and incubated for 36 h. Cultures were centrifuged at 5000 × g for 5 min, and the pellet was resuspended in sterile saline to an OD₆₀₀ = 1.0. Subsequently, 100 μL of the bacterial suspension was inoculated into 100 mL of the MM medium with a gradient of citrulline concentrations (50 μM, 500 μM, and 5 mM) as the sole carbon and nitrogen source. Bacterial cultures were incubated at 28 °C in an incubator shaker at 180 r.p.m. for 5 days. Each selected Pseudomonas strain was divided into three treatment groups based on citrulline concentration, with three replicates per treatment. Every 4 h, 2 mL of culture was sampled, centrifuged at 5000 × g for 5 min, and the supernatant was analyzed for citrulline content. The pellet was resuspended in 2 mL of sterile saline, and OD₆₀₀ was measured using a microplate reader (Tecan, Männedorf, Switzerland). The absorbance values were used to fit a Boltzmann model to plot the growth curve of Pseudomonas strains when cultured with a gradient of citrulline concentrations as the sole carbon and nitrogen source. Additionally, every 20 h, 2 mL of culture was centrifuged at 10,000 × g for 1 min at 4 °C. The supernatant was discarded, and the pellet was rapidly frozen in liquid nitrogen and stored at -80 °C for subsequent RNA extraction.

Identification and phylogenetic analysis of the strains was performed following the method described by Li et al.⁷⁸. In detail, genomic DNA was extracted from the final strains using the Ezup Column Bacterial Genomic DNA Extraction Kit (Sangon Biotech, Shanghai, China). The 16S rDNA gene was amplified using primers 27F and 1492R, and Sanger sequencing was performed by Sangon Biotech. PCR amplification was conducted in a 50 μL reaction mixture containing 20 μL ddH₂O, 1 μL template DNA (100 ng μL^-1), 2 μL of each primer (10 μM), and 25 μL of 2× Taq PCR Master Mix. The cycling conditions were as follows: initial denaturation at 94 °C for 4 min, followed by 33 cycles of denaturation at 94 °C for 30 s, annealing at 60 °C for 30 s, and extension at 72 °C for 2 min, with a final extension at 72 °C for 10 min. The PCR fragment (approximately 1.5 kb), detected by electrophoresis on 1% agarose gel, was purified and sequenced. Sequence alignment of 16S rDNA was performed using the BLAST search tool against the nucleotide database (http://www.ncbi.nlm.nih.gov/blast/Blast.cgi). Phylogenetic trees were constructed using the Neighbor-joining method in MEGA X⁷⁹ to analyze the evolutionary relationships among the isolated strains and existing microbial strains in the database. Species-level identification was defined as having >99% sequence similarity in the 16S rRNA sequence.

Whole genome sequencing and ANI analysis

The genomic DNA of the final isolated strains was sequenced using both third-generation Nanopore sequencing technology and second-generation sequencing platforms, achieving a sequencing depth of ≥ 100 × for complete bacterial genome analysis. After filtering for adapters, short fragments, and low-quality reads, the third-generation Nanopore sequencing yielded 1,578,688,861 bp of clean reads for assembly, whereas the second-generation Illumina sequencing produced 1,038,502,880 bp of clean data. The assembled complete genome was 5.793 Mb in size. Raw data from Nanopore sequencing—initially in fast5 format—was converted to fastq format using GUPPY (Version: 5.0.16) for basecalling (https://timkahlke.github.io/LongRead_tutorials/BS_G.html). Subsequent filtering of raw sequencing data to retain high-quality reads (Q ≥ 7) was performed for assembly analysis. The second-generation raw sequencing data were processed using fastp (Version: 0.23.2)⁸⁰ to obtain 1,038,502,880 bp of clean data. Assembly was conducted using Unicycler: initially, high-accuracy Illumina data (Q30 > 85%) were used to construct a high-quality bacterial genome scaffold (contig), followed by linking the high-quality contigs to a complete genome with Nanopore data. Final polishing of the assembled genome was performed using Pilon with the second-generation data to achieve higher accuracy. Gene prediction for the assembled genome was conducted using Prokka (Version: 1.14.6)⁸¹.

Note: The circular genome map consists of the following layers from outermost to innermost: the first ring represents genome sequence information; the second ring shows the GC content curve of the genome sequence, calculated with a 2000 bp sliding window; the dashed line indicates the average GC content of the reference genome; the third ring displays the GC skew curve of the genome sequence, calculated with a 2000 bp sliding window. The dashed line indicates a GC skew of 0 as a reference; the fourth ring illustrates the sequencing depth and coverage information from second-generation sequencing, calculated with a 2000 bp sliding window; the dashed line indicates the average read coverage level; the fifth ring presents sequencing depth and coverage information from third-generation sequencing, calculated with a 2000 bp sliding window. The dashed line indicates the average read coverage level; the sixth ring shows the coding (CDS) and non-coding RNA regions (rRNA, tRNA) of the reference genome, with the outer layer representing the positive strand and the inner layer representing the negative strand.

The Average Nucleotide Identity (ANI) analysis was performed following the method of Li et al.⁸² with modifications. Briefly, whole-genome homology was assessed using the online ANI calculator tool from the EzBioCloud Database service (https://www.ezbiocloud.net/tools/ani)⁸³. The genomes used for ANI analysis include model species and strains of the Pseudomonas genus that are currently being studied more frequently. Information on the genome sequence used is provided in Supplementary Data 4.

The quantification analysis of citrulline metabolic genes in P. putida YDTA3

According to the manufacturer’s instructions, RNA was extracted from the cell pellet samples collected at 40 hours using the Bacterial RNA Kit (R6950, Omega Bio-Tek, Norcross, GA, USA). The quality and concentration of RNA were assessed by agarose gel electrophoresis and NanoDrop spectrophotometer (ND2000, Thermo Scientific, DE, USA). First-strand cDNA synthesis was performed following the protocol provided with the BeyoRT™ Q cDNA Synthesis Kit (D7190M, Beyotime Biotechnology Co., Ltd., Shanghai, China). Gene-specific primers (listed in Supplementary Table 12) were then used to amplify arcB and argH genes via quantitative PCR (qPCR). The qPCR was carried out in a 10 μL reaction mixture containing 1 μL of cDNA and 5 μL of ChamQ SYBR Color qPCR Master Mix (High ROX Premixed, Vazyme Biotech Co., Ltd., Nanjing, China). The cycling conditions were as follows: initial denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s, and extension at 72 °C for 30 s. These conditions were repeated for 40 cycles on StepOnePlus^TM Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) and analyzed with the StepOnePlus V2.3 software. The mRNA expression levels were normalized to the 16S rRNA gene. Fold changes are presented as 2^−ΔΔCt (ΔΔCt = ΔCt_treatment − ΔCt_control).

Construction of the arcB and argH knockout mutant strains

Using the genomic DNA of P. putida YDTA3 as a template, four pairs of gene-specific primers (listed in Supplementary Table 13) were used to amplify the upstream and downstream homologous arms of the target genes arcB and argH, respectively. Using the commercial plasmid pBBR1MCS-5 as a template, a pair of specific primers was used to amplify the gentamicin resistance gene cassette (Gm R). Subsequently, overlap extension PCR was performed using the upstream and downstream homologous arms and the Gm R fragments to obtain fragments of approximately 992 bp and 1,214 bp length, respectively. Using the ClonExpress Ultra One Step Cloning Kit V2 (C116, Vazyme Biotech Co., Ltd., Nanjing, China), the aforementioned fragment was ligated into the linear vector pK18mobSacB, which was digested with BamHI and HindIII (New England Biolabs, Ipswich, MA, USA). The ligation product was transformed into E. coli DH5α and plated onto LB agar containing kanamycin (Kan) and gentamicin (Gm) for selection. After overnight incubation, single colonies were picked and cultured in the LB broth. Plasmid extraction and sequencing verification (Supplementary Table 14) were performed by Sangon Biotech. The correctly sequenced plasmids were designated as the constructed knockout plasmids, namely pK18-ΔarcB+pc-GM and pK18-ΔargH+pc-GM.

The recombinant plasmids were introduced into wild-type P. putida YDTA3 via tri-parental conjugation (helper plasmid is pRK2013). Selection of homologous single crossover events was performed on LB plates containing appropriate concentrations of Gm and Kan antibiotics. A random tri-parental transconjugant was selected for overnight culture, diluted, and plated on LB plates containing 5% sucrose, ampicillin (Amp, to which the wild-type is resistant), and Gm. Gene deletion mutants based on homologous double-crossover were then isolated. Finally, two mutant strains, namely ΔarcB and ΔargH, were obtained.

Endowing soil microbial ability to eliminate citrulline

Pot experiments with P. putida YDTA3 and mutant strains

For the simulated continuous cropping pot experiment with P. putida YDTA3, soil matrix preparation, seed pre-germination, plant growth, and pathogen inoculation were conducted as described in the Pot experiments on SCCC section. Here, 20 mL of citrulline with different concentrations (1 μM, 100 μM, and 10 mM) was added to the watermelon rhizosphere soil to simulate the soil conditions of continuous watermelon cropping. Additionally, the strain P. putida YDTA3 was introduced at the three-leaf stage. Specifically, P. putida YDTA3 was cultured in LB broth for 36 h, centrifuged at 5000 × g for 5 min, and resuspended in sterile saline to an OD₆₀₀ of 1.5. The bacterial suspension (20 mL) was applied to the rhizosphere. There were eight treatment groups (named based on the substances added to the rhizosphere and strains used): 1) 10 mM Cit+FON; 2) 10 mM Cit+P. putida YDTA3 + FON; 3) 100 μM Cit+FON; 4) 100 μM Cit+P. putida YDTA3 + FON; 5) 1 μM Cit+FON; 6) 1 μM Cit+P. putida YDTA3 + FON; 7) P. putida YDTA3; 8) H₂O (control). Each treatment included six replicates with each replicate containing 15 plants. Disease incidence was recorded at 28 days after pathogen inoculation.

For the simulated continuous cropping pot experiment with knockout strains ΔarcB and ΔargH, the procedure (soil preparation, seed pre-germination, knockout strain inoculation, and pathogen inoculation) was identical to that described in the above paragraph, except that it was conducted only in soil containing 1 mM citrulline. There were five treatment groups: 1) FON; 2) ΔargH; 3) ΔarcB; 4) P. putida YDTA3; 5) H₂O. Disease incidence was recorded 28 days after pathogen inoculation.

Soil microbiome analysis and absolute quantification of continuous cropping watermelon

Using the vegan package in R, we calculated the alpha diversity of the microbiome data from rhizosphere soil samples of watermelon grown continuously for eight generations. Absolute quantitative PCR (qPCR) was employed to quantify the loads of bacteria from Enterobacteriaceae and Escherichia in rhizosphere soil DNA samples from the 1st, 5th, and 8th generations. Specific primers are listed in Supplementary Table 15.

For standard curve generation, DNA bands amplified from soil DNA using Enterobacteriaceae-specific primers were purified and ligated into a pUCm-T vector (B522214, Sangon Biotech, Shanghai, China) according to the manufacturer’s instructions, followed by 10-fold serial dilution. Plasmids containing the full-length 16S rRNA gene of Escherichia were similarly diluted. The amplification efficiencies of bacteria from Enterobacteriaceae and Escherichia were 95.4% and 93.7%, respectively.

The qPCR was carried out in a 10 μL reaction mixture containing 1 μL of DNA and 5 μL of ChamQ SYBR Color qPCR Master Mix (High ROX Premixed, Vazyme Biotech Co., Ltd., Nanjing, China). The cycling conditions were as follows: initial denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s, and extension at 72 °C for 30 s. These conditions were repeated for 40 cycles on the StepOnePlus™ Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) and analyzed with StepOnePlus V2.3 software. Each DNA sample was analyzed in triplicate. The specificity of the amplification fragments was confirmed by analyzing the melting curves and agarose gel electrophoresis. The copy number of each target fragment was calculated from the standard curve and expressed as log10 values (copies g^-1 soil).

Isolation of Escherichia consortium

We employed the eosin methylene blue (EMB) selective medium to isolate Escherichia from continuous watermelon cropping soil stored at 4 °C. Briefly, the selected soil samples were serially diluted and plated onto EMB agar plates to isolate Escherichia colonies following the method described by Jett et al.⁷⁵. The plates were incubated upside down overnight in an incubator at 28 °C. Colonies exhibiting a black metallic sheen were selected, whereas non-sheen colonies and surrounding agar (1 mm) were excised. The remaining colonies on the EMB plates were pooled and stored at 4 °C as Escherichia consortium for subsequent genetic manipulation.

Genetic engineering of Escherichia consortium

For genetic engineering transformation of the Escherichia consortium, we first made some modifications to the traditional electroporation method to prepare competent cells to better suit our experimental needs. Specifically, the selection plates with newly formed pinpoint colonies were placed on ice for 30 min (to harden agar medium). The colonies were then repeatedly washed off the plates with sterile ice-cold water to form a bacterial suspension. The suspensions from all plates were transferred into a single 50 mL centrifuge tube and centrifuged at 1500 × g for 10 min at 4 °C. The supernatant was discarded, and the cells were resuspended in ice-cold water and centrifuged again; this washing step was repeated twice. Next, the bacterial pellet was resuspended in 20 mL of sterilized ice-cold 10% glycerol and centrifuged again at low speed to remove the supernatant. Finally, the cells were resuspended in 3 mL of the same glycerol solution and aliquoted into 1.5 mL microcentrifuge tubes in 100 μL portions, followed by rapid freezing in liquid nitrogen. The overexpression plasmid containing the arcB gene was introduced into the freshly thawed competent cells from Escherichia via electroporation. Positive clones were selected by plating on eosin methylene blue agar plates supplemented with kanamycin resistance. All colonies exhibiting the desired colony morphology on the selection plates were pooled together and stored as the engineered Escherichia consortium, namely EO-arcB.

SDS-PAGE analysis

The overexpression plasmid containing arcB was transformed into E. coli BL21. Specifically, the full-length coding sequence (CDS) of arcB was amplified from the P. putida YDTA3 genome using primers arcB-OP-F and arcB-OP-R (primer sequences are listed in Supplementary Table 16). The commercial plasmid pet28a-EGFP was linearized via reverse amplification using the primer pair pet28a-F/pet28a-R (primer sequences are listed in Supplementary Table 16). Using the ClonExpress Ultra One Step Cloning Kit V2 (C116, Vazyme Biotech Co., Ltd., Nanjing, China), arcB was ligated into the linearized pet28a plasmid (complete process is illustrated in Supplementary Fig. 30). The ligation products were sent for sequencing at Sangon Biotech to verify successful plasmid construction. Successfully constructed plasmids were introduced into electrocompetent E. coli BL21 cells via electroporation. The transformation was confirmed by plating the transformed cells on LB agar plates containing kanamycin. Successful transformation was confirmed with colony PCR. The successfully constructed overexpression strain was named E. coli-arcB. For overexpression of arcB, the culture was grown in LB broth to OD₆₀₀ = 0.6. Subsequently, 0.5 mM isopropyl β-D-1-thiogalactopyranoside (IPTG) was added to induce protein expression at 28 °C and 150 r.p.m. for 14 h.

For SDS-PAGE analysis, four treatments were prepared as follows: 1) Supernatant of the induced bacterial culture of E. coli-arcB: The induced bacterial culture of E. coli-arcB was centrifuged at 10,000 × g for 1 min, and the supernatant was collected. 2) Cell pellet of the induced bacterial culture of E. coli-arcB: The induced bacterial culture of E. coli-arcB was centrifuged at 10,000 × g for 1 min to obtain the cell pellet. To the pellet, 1 mL of cell lysis buffer was added, and the mixture was thoroughly resuspended by pipetting. After vigorous shaking for 10 min, the mixture was centrifuged at 10,000 × g for 1 min and the supernatant was collected. 3) Bacterial culture of EO-arcB without centrifugation. 4) Residual cell debris: The residual cell debris remaining after the supernatant was removed from treatment ‘2’.

Each treatment received 500 μL of acetone to denature proteins. The mixtures were then precipitated by incubation on ice for 30 min, followed by centrifugation at 12,000 × g for 10 min. The supernatant was discarded, and the pellets were resuspended in 100 μL of PBS. The resuspended samples were mixed with 25 μL of 5× SDS-PAGE loading buffer (Bio-Rad, CA, USA). The samples were then boiled for 10 min. The SDS-PAGE gels were prepared according to the Bio-Rad protocol, using 1.5 mm thick gel combs. Each well was loaded with 10 μL of the prepared protein samples. Electrophoresis was carried out at 80 V for 30 min followed by 150 V for 30 min. The gels were then scanned for analysis. Bio-Rad recombinant prestained Precision Plus protein standards were run to calculate the apparent molecular weight of protein bands.

Continuous cropping pot experiments with EO-arcB

The preparation of the soil matrix (using soil without a history of watermelon cultivation), seed pre-germination, plant growth, and pathogen inoculation followed the procedures described in the Pot experiments on SCCC section, with the following modifications: EO-arcB or P. putida YDTA3 were added during the three-leaf stage of watermelon, cucumber, and pumpkin. The enrichment and application procedures were consistent with those used in the Pot experiments with P. putida YDTA3 and mutant strains section. Specifically, EO-arcB was first activated in vitro using 0.5 mM IPTG, followed by centrifugation at 5000 × g for 5 minutes. The resulting cell pellet was resuspended in sterile saline to an OD₆₀₀ of 1.5 before root-zone application. At the end of each generation, plant tissues were removed, and a new crop was planted. At the third true-leaf stage, EO-arcB and P. putida YDTA3 were added again. This process was repeated for six generations. There were four treatments set: 1) FON; 2) EO-arcB; 3) P. putida YDTA3; 4) H₂O (control). Each treatment included six replicates, with each replicate containing 15 plants. The final disease incidence was recorded 28 days after pathogen addition. Additionally, 0.5 g of rhizosphere soil was randomly collected from each replicate for DNA extraction after the incidence rate was recorded.

Identification and random combination of EO-arcB strains for pot experiments on SCCC

To prepare the enrichment culture, the EO-arcB strains stored at -80 °C were briefly thawed and directly inoculated in LB broth for 36 h. The bacterial culture was serially diluted in a tenfold dilution series, then uniformly spread onto EMB agar plates and incubated in an inverted position at 35 °C for 24 h. Distinct single colonies differing in morphology, characteristics, and size were selected for purification and submitted to Sangon Biotech for full-length 16S rRNA Sanger sequencing. Sequencing data were aligned using the EzBioCloud database and NCBI BLAST tools. Sequences with high similarity were utilized to construct a phylogenetic tree. Strains from different clades were randomly combined to create mixtures of three, five, seven, and nine strains (designated as EO-3, EO-5, EO-7, and EO-9, respectively; strain details are provided in Supplementary Data 3).

The preparation of soil matrix, seed pre-germination, plant growth, and pathogen inoculation were conducted according to the procedures detailed in the Pot experiments on SCCC section. Six treatments were established: 1) FON; 2) EO-3; 3) EO-5; 4) EO-7; 5) EO-9; and 6) H₂O (control). Each treatment consisted of six replicates, with each replicate containing 15 plants. The final disease incidence was calculated 28 days after pathogen addition. Additionally, 0.5 g of rhizosphere soil was randomly collected from each replicate every 5 days after the FON addition for DNA extraction.

Absolute quantification of the arcB gene

Quantitative PCR (qPCR) was utilized to quantify functional genes in the soil DNA from the aforementioned simulated continuous cropping experiments every five days, as well as in the soil DNA from the 2^nd, 3^rd, 4^th, 5^th, and 6^th cropping generations. The specific primers used for these quantifications are listed in Supplementary Table 12. To generate standard curves, plasmid pet28a-arcB was subjected to 10-fold serial dilutions, achieving an amplification efficiency of 98.4%. The qPCR was carried out in a 10 μL reaction mixture containing 1 μL of DNA and 5 μL of ChamQ SYBR Color qPCR Master Mix (High ROX Premixed). The cycling conditions were as follows: initial denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s, and extension at 72 °C for 30 s. These conditions were repeated for 40 cycles on the StepOnePlus™ Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) and analyzed with StepOnePlus V2.3 software. Each DNA sample was analyzed in triplicate. The specificity of the amplified fragments was confirmed by melt curve analysis and agarose gel electrophoresis. The copy numbers of each target fragment were calculated from the standard curves, and the results were expressed as the ratio of the copy numbers in each generation to the copy numbers in the first generation.

DNA extraction, 16S rRNA gene amplification, amplicon sequencing and analysis

Soil samples incubated with a gradient of citrulline concentrations (CK, 1 μM, 100 μM, and 10 mM) were used for DNA extraction and amplicon sequencing. Total DNA was extracted from 0.5 g of soil using the Power Lyzer Power Soil DNA Isolation Kit (Qiagen, Hilden, Germany) according to the manufacturer’s protocol. The quality and quantity of DNA were assessed using 1% agarose gel electrophoresis and a NanoDrop spectrophotometer (ND2000, Thermo Scientific, DE, USA). For taxonomic analysis, the V4 region of the bacterial 16S rRNA gene was amplified using primers 515F: GTGYCAGCMGCCGCGGTAA and 806R: GGACTACNVGGGTWTCTAAT⁸⁴, resulting in a 292 bp amplicon. The 50 μL PCR reaction mixture contained 25 μL of 2× Premix Taq (Takara Biotechnology, Dalian, China), 1 μL of each primer (10 μM), 3 μL of DNA (20 ng μL⁻¹), and 20 μL of sterilized ultrapure water. PCR amplification was performed using a Thermal Cycler (T100™, Bio-Rad, Hercules, CA, USA) with the following cycling conditions: 95 °C for 5 min, followed by 30 cycles of 94 °C for 30 s, 52 °C for 30 s, and 72 °C for 30 s, with a final extension at 72 °C for 10 min. PCR products were separated on a 1% agarose gel, and the bands between 290 and 310 bp were excised and combined for sequencing. The PCR products were mixed in equimolar ratios using GeneTools analysis software (v.4.03.05.0, SynGene) and purified using the FastPure Gel DNA Extraction Mini Kit (DC301, Vazyme Biotech Co., Ltd., Nanjing, China). Sequencing libraries were prepared using the NEBNext® Ultra™ DNA Library Prep Kit for Illumina® (New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s instructions, with index codes added. Library quality was assessed using a Qubit® 2.0 Fluorometer (Thermo Scientific) and an Agilent Bioanalyzer 2100 system. The 250 bp paired-end library was sequenced on the Illumina NovaSeq6000 platform, and high-quality reads were processed using Usearch⁸⁵, including denoising and OTU generation. Taxonomic classification was performed using the appropriate database, resulting in a number of sequences from samples clustered into OTUs.

Metagenomic sequencing and analysis

For metagenomic sequencing, a total of 26 rhizosphere soil samples were collected across two consecutive years from continuous watermelon cropping fields in China (Supplementary Table 3). In 2024, six samples were obtained from Henan Province, including three healthy soils and three Fusarium-conducive soils (collected from plants showing Fusarium wilt symptoms under continuous cropping conditions). In 2025, twenty additional samples were collected from two independent continuous cropping demonstration sites in Beijing, consisting of five healthy and five Fusarium-conducive soils at each site. All rhizosphere soil samples were collected strictly following the same protocol described in the Soil sample collection section and were immediately stored at –80 °C. These supplementary samples were included to increase replication and thereby strengthen the robustness of the metagenomic analyses. Soil classification was performed according to the Chinese Soil Taxonomy (CST)⁸⁶. The healthy plant field soil-1 was classified as Cambosols, while the diseased plant field soil-1 was identified as Argosols. Both healthy plant field soil-2 and diseased plant field soil-2 were classified as Cambosols, whereas healthy plant field soil-3 and diseased plant field soil-3 were Argosols. To further clarify the soil pedology/classification, the soils were also categorized following the Genetic Soil Classification of China (GSCC)⁸⁷. Accordingly, Healthy plant field soil-1 corresponds to Fluvo-aquic soils (equivalent to Inceptisols in the U.S. Soil Taxonomy)⁸⁸, Diseased plant field soil-1 to Cinnamon soils (equivalent to Alfisols), Healthy plant field soil-2 and Diseased plant field soil-2 to Fluvo-aquic soils (Inceptisols), and Healthy plant field soil-3 and Diseased plant field soil-3 to Cinnamon soils (Alfisols). Detailed information on sampling year, location, soil health status, crop history, associated diseases, chemical properties, crop varieties, sampling stage, and sample IDs used for metagenomic sequencing is provided in Supplementary Table 3. Library preparation was performed according to the Illumina standard protocol. Briefly, DNA was fragmented by ultrasound, pooled libraries containing equimolar amounts of barcoded 350–500 bp fragments were prepared, and 150 bp paired-end fragments were sequenced by Illumina Noveseq 6000 platform. The raw metagenome sequence data (240 Gbp) were trimmed, filtered, assembled by Megahit and contigs longer than 300 bp were used for further gene prediction and annotation. Open reading frames (ORFs) from assembled metagenomes were predicted using MetaGeneMark. The predicted ORFs with lengths longer than 100 bp were translated to construct a nonredundant gene catalog with criteria of 95% sequence identity and 90% coverage, and gene abundance in each sample was normalized into reads per kilobase million counts. For taxonomic annotations, representative sequences in the gene catalog were searched against the nonredundant protein database of NCBI with an e-value cutoff of 1e − 5 using Diamond⁸⁹ and the lowest common ancestor method was applied to estimate the assignment of genes to specific taxa. For functional annotations, the Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation were conducted with an e-value cutoff of 1e − 5. The newly obtained 20 supplementary metagenomic samples were analyzed using exactly the same framework as the six initial metagenomic samples (with identical tools and database versions). After assembly, the nonredundant gene catalog was generated and then merged with that of the previous six samples, followed by redundancy removal to construct a final unique gene set across all samples. Taxonomic and functional annotations, as well as gene quantification, were then re-performed for all samples. Prior to downstream analyses, gene read counts of all samples were rarefied to the same sequencing depth to avoid biases introduced by sequencing depth.

Statistical Analysis

Alpha diversity of soil microbial communities was calculated using the vegan package in R⁹⁰. In detail, soil incubated with citrulline (1 μM, 100 μM, and 10 mM) and their corresponding water-treated control (CK) from the microcosm cultivation experiments were analyzed (n = 6 per treatment). The OTU table was rarefied to 30,000 reads per sample before analysis to minimize sequencing depth bias. Shannon index, Pielou’s evenness, and richness indices were then calculated. Statistical comparisons of α-diversity indices among treatments were performed using the Kruskal–Wallis test, followed by Dunn’s post-hoc test implemented in the EasyStat package (https://github.com/taowenmicro/EasyStat; Version: 0.1.0). The p-values were adjusted for multiple comparisons using the Benjamini-Hochberg FDR procedure, with significance threshold defined as adjusted-p-values < 0.05. Before the calculation of beta diversity, relative abundances were used to standardize the OTU profiles. Bray–Curtis distance matrices were prepared using the vegan R package⁹⁰. Analysis of similarities (ANOSIM, using Bray–Curtis distances, permutation = 999) was used to test if the beta diversity differed among treatments (control and 10 mM treatment) and principal coordinate analysis (PCoA) plots were generated according to Bray–Curtis similarity matrices created using the R package ggplot2⁹¹. The construction of random forests and co-occurrence networks was performed using the ggClusterNet package in R^92,93. Part of the network construction workflow and related analyses were supported by Nanjing Sinong Bioinformatics Co., Ltd., Nanjing, 211899, China.

Other experimental data (including crop wilt incidence, citrulline content, and gene expression level) were first assessed for normality using the Shapiro–Wilk test and for homogeneity of variance using Levene’s test. For multiple group comparisons, one-way ANOVA followed by Duncan’s multiple range test was performed when parametric assumptions were satisfied. Conversely, when assumptions were not met, the Kruskal–Wallis test was used, followed by pairwise Wilcoxon rank-sum tests with p-values adjusted for multiple testing using the Benjamini–Hochberg false discovery rate (FDR) correction. For comparisons between two groups, two-sided Student’s t-tests were used when parametric assumptions were met; otherwise, the Wilcoxon rank-sum test was applied. All statistical tests were two-sided, and a P value < 0.05 was considered statistically significant. Data are presented as means +/- standard errors (s.e.m.) for bar plots, as box-and-whisker plots (showing median, interquartile range, and outliers) for distributions, and with fitted regression lines ± confidence intervals for correlation analyses, unless otherwise stated. Statistical analyses were performed using IBM SPSS Statistics 26.0 and R software. Figures were prepared using R, PowerPoint, Illustrator and Origin 2022.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

The Metagenomic sequencing data generated in this study have been deposited in the NCBI Sequence Read Archive (SRA) database under accession code PRJNA1394199. Source data are provided with this paper as a Source Data file. All other data supporting the findings of this study are available within the Supplementary Information files. Source data are provided with this paper.

Code availability

Code used in this study has been deposited in Figshare; the permanent https://doi.org/10.6084/m9.figshare.30951695.

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Acknowledgements

This study was financially supported by the National Natural Science Foundation of China (42322708, 42090060, 42277297, 42307394), the Fundamental Research Funds for the Central Universities (KJJQ2025017, YDZX2025045), the China Agriculture Research System (CARS-23), and the China Postdoctoral Science Foundation (BX20230160).

Author information

These authors contributed equally: Zhexu Ding, Tao Wen.

Authors and Affiliations

Jiangsu Provincial Key Lab for Organic Solid Waste Utilization, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource-saving fertilizers, Nanjing Agricultural University, Nanjing, China
Zhexu Ding, Tao Wen, Xinyang Teng, Wenyi Yang, Xiaohang Yuan, Xiaoyu Liu, Penghao Xie, Xiangyang Zhao, Qirong Shen & Jun Yuan

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Zhexu Ding
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Tao Wen
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Xinyang Teng
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Wenyi Yang
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Xiaohang Yuan
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Xiaoyu Liu
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Penghao Xie
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Xiangyang Zhao
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Qirong Shen
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Jun Yuan
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Contributions

Z.D. and T.W.: conducted all experiments, conceived the study, and wrote the paper; X.T. and W.Y.: collected sequencing data; X.L., X.Y., P.X., and X.Z.: provided critical comments on the study; J.Y. and Q.S.: conceived the study, and supervised the study.

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Correspondence to Jun Yuan.

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Ding, Z., Wen, T., Teng, X. et al. Enhancing soil citrulline degrading function to mitigate soil-borne Fusarium wilt. Nat Commun 17, 1868 (2026). https://doi.org/10.1038/s41467-026-68606-x

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Received: 02 March 2025
Accepted: 08 January 2026
Published: 20 January 2026
Version of record: 20 February 2026
DOI: https://doi.org/10.1038/s41467-026-68606-x