Fusarium cross-infection in medicinal herbs alters rhizosphere microbiomes and disrupts mycorrhizal functions under soil physicochemical imbalances

Fusarium cross-infection in medicinal herbs alters rhizosphere microbiomes and disrupts mycorrhizal functions under soil physicochemical imbalances | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (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],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Fusarium cross-infection in medicinal herbs alters rhizosphere microbiomes and disrupts mycorrhizal functions under soil physicochemical imbalances Andéole Niyongabo Turatsinze, Xiaofan Xie, Ailing Ye, Gaofeng Chen, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5926386/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 08 May, 2025 Read the published version in Plant and Soil → Version 1 posted 5 You are reading this latest preprint version Abstract Background and Aims Fusarium root rot and wilt affect medicinal herbs in Gansu Province, China, despite extended crop rotations. This study investigated the cross-pathogenicity of Fusarium species isolated from Angelica sinensis (Danggui), Codonopsis pilosula (Dangshen), and Astragalus mongholicus (Huangqi). Methods Of 83 fungal isolates recovered, 69.8% were identified as Fusarium spp., through ITS, TEF1-α, and RPB2 sequencing, clustering into Fusarium oxysporum (FOSC, 36.2%), Fusarium solani (FSSC, 31%), and Fusarium tricinctum (FTSC, 22.4%) species complexes. Representative strains ( F. oxysporum DSH27, F. solani HQ123, F. tricinctum DG105) were tested for cross-pathogenicity in greenhouse and field trials. Rhizosphere microbial dynamics, including fungal and bacterial community diversity, functional guilds, and soil physicochemical properties, were analyzed. Results Fusarium strains exhibited varying aggressiveness, highest on original hosts, while cross-infective hosts showed less to moderate severity. Infections disrupted rhizosphere networks, increasing pathotrophic dominance over arbuscular mycorrhizal functions. Sequencing showed reduced fungal and bacterial operational taxonomic units (OTUs), with distinct clustering of infected vs. non-infected rhizospheres. Pathogenic fungal genera Fusarium positively correlated with disease incidence, while beneficial fungal genera Mortierella and bacterial genera RB41 showed negative correlations. Infected soils exhibited significant changes in total carbon, available phosphorus, manganese, and zinc, correlating with microbial dynamics and disease severity. Conclusion This study links Fusarium cross-infection with rhizosphere microbial network disruptions, including the loss of arbuscular mycorrhizal fungi (AMF) functions under altered soil physicochemical conditions in medicinal herbs. These findings uncover the systematic cross-pathogenicity of Fusarium species, highlighting the need for AMF-based strategies and integrated soil management to mitigate its impact. Medicinal herbs Fusarium root rot Fusarium species cross-pathogenicity rhizosphere soil microbiome metagenome sequencing Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 1. Introduction Medicinal herbs have historically been integral to traditional healthcare systems worldwide, rooted in cultural and therapeutic practices. In China, modern medicine significantly relies on cultivating commonly used medicinal herbs, which are widespread across multiple medical systems (Lixin et al., 2009; Shan et al., 2023). The Northwestern region of China exhibits arid and semi-arid conditions, serving as the primary habitat and cultivation area for various medicinal herbs, particularly in mountainous and desert environments (Liu et al., 2017). Traditional Chinese Medicine (TCM) employs medicinal herbs such as Angelica sinensis (Oliv.) Diels, Codonopsis pilosula Franch., and Astragalus membranaceus Bge. var. mongholicus as essential remedies, acknowledged for their preventive and therapeutic functions (Zhang and Chen, 2016; Hao and Liu, 2022). These herbs, mainly cultivated in Gansu Province, are crucial to Traditional Chinese Medicine and serve as significant income sources for local farmers (Liu et al., 2017; Zhou et al., 2024). The extensive cultivation of these perennial medicinal herbs in Dingxi, Gansu Province, underscores their significant contributions to local agriculture and traditional medicine practices (Yang et al., 2019; Zhou et al., 2024). However, the sustainability of these medicinal herbs is increasingly compromised by Fusarium root rot, a prevalent and destructive disease that not only threatens plant health and yield but also alters soil microbial balance and affects long-term cultivation strategies. Fusarium species are well-known soil-borne pathogens capable of infecting diverse plant hosts through the use of cross-pathogenicity mechanisms and by exploiting environmental and host vulnerabilities (Arie, 2019, Summerell, 2019, Okello and Mathew, 2019). In medicinal herb cultivation, their ability to survive in soil and plant residues enables long-term persistence, leading to widespread and systematic infections that cause root and crown rots in plants (Leonce, 2021). Yet, how cross-infection occurs among different herb species remains unclear. Fusarium spp. have been recognized as the pathogens responsible for root rot and wilt among several medicinal perennial herbs in Gansu Province (Liu et al., 2022; Niyongabo et al., 2024; Uwaremwe et al., 2021; Wang et al., 2024; Zhao et al., 2021; Zhou et al., 2024). These species form species complexes with varying levels of aggressiveness and adaptability, complicating disease management (Suga and Hyakumachi, 2004). Their complex interactions, allow them to invade various host plants and cause root rot and wilt diseases among plant species (Coleman, 2016; Habibi et al., 2018). This explain why, despite ongoing efforts to manage Fusarium root rot through crop rotation, disease prevalence remains high, raising critical concerns about unexplored mechanisms driving pathogen persistence. Specifically, cross-infection among rotational medicinal herbs remains poorly understood, with limited studies investigating how Fusarium species adapt to multiple hosts and influence rhizosphere microbiomes and soil conditions. This knowledge gap hinders the development of effective disease control strategies and compromises sustainable medicinal herb cultivation. Moreover, Fusarium spp. not only infect plant roots but also interact with soil microbial communities, altering the microbial composition, diversity, and trophic networks in the rhizosphere while disrupting physicochemical and nutrient availability, thereby enhancing disease severity (Liu et al., 2023; Mendes et al., 2011). Recent studies have shown that pathogen-induced shifts in the rhizosphere microbiome, including changes in fungal trophic functions and reductions in beneficial fungi such as arbuscular mycorrhizal (AM), contribute to increased disease severity and plant stress susceptibility (Barelli et al., 2020; Solis-Garcia et al., 2021). Additionally, altered soil properties, including pH, organic matter, and nutrient availability, are implicated in pathogen proliferation and disease dynamics (Naseri, 2014). However, the extent to which these changes facilitate cross-infection among medicinal herbs and reduce the efficacy of current disease management strategies remains largely unexplored. The colonization mechanisms of Fusarium species and the resulting host disease development are also shaped by their interactions and competition with the rhizosphere microbiome (Karlsson et al., 2021; Ping et al., 2024; Zhu et al., 2022). The composition and diversity of the rhizosphere microbiome affect Fusarium pathogenicity and disease severity, as shifts in microbial diversity and the presence of specific microbial taxa create environments that favor Fusarium species colonization (Luo et al., 2024; Park et al., 2023). Indeed, changes in nutrient composition favoring their establishment, as well as alterations in the rhizosphere fungal community composition along with the predicted functions of bacteria, have been associated with the development and aggressiveness of Fusarium root rot (Solis-Garcia et al., 2021; Uwaremwe et al., 2023). However, despite these insights, little is known about how medicinal herb cultivation practices influence Fusarium -associated microbial shifts and whether these changes contribute to disease recurrence even after crop rotation. Although some microbial communities inhibit the growth of Fusarium species, fungal pathogen invasion is a major driving force shaping the rhizosphere microbiome. The rhizosphere of diseased plants and disease severity have been associated with specific microbes that can either prevent or promote the growth of the pathogens and disease development (Chapelle et al., 2016; Xiong et al., 2017). For instance, some microbial communities inhibit the growth of Fusarium species, while others, such as Pandoraea , Rhizomicrobium , Mortierella , and Fusarium spp., are positively correlated with root rot incidence and severity (Bi et al., 2023; Goodwin, 2022). This dualism highlights the complexity of Fusarium -host-microbiome interactions and suggests that sustainable disease management should rely not only on crop rotation but also on enhancing beneficial microbial communities that suppress Fusarium infections. Moreover, the complex interplay between Fusarium species, soil properties and microbial activity within the rhizosphere profoundly affects plant health and disease incidence. Physicochemical properties of the soil are key determinants of disease outcomes. For example, limited moisture and specific soil temperature and water content interactions have been observed to enhance Fusarium root rot (Cruz et al., 2020; Yan and Nelson, 2022). The pathogenic Fusarium inoculum density has shown positive correlations with total nitrogen and negative correlations with Olsen phosphorus. Disease severity was higher in soil with low organic matter, which has poor nitrate: ammonium ratios, as well as when sand and silt are in specific proportions (Moutassem et al., 2019; Naseri, 2014; Yan and Nelson, 2022). Furthermore, root exudates, as well as Fusarium metabolites such as toxins, phytotoxins, and degrading enzymes, influenced soil chemical composition in favor of pathogen colonization while impeding the growth and activity of beneficial microbes (Liu et al., 2017; Perincherry et al., 2019). These findings underscore the synergistic relationship between soil properties and Fusarium species and the influence of pathogen-induced changes in the soil environment on pathogenicity and persistence of disease. Fusarium root rot and wilts have been frequently reported in A. sinensis , C. pilosula , and A. mongholicus in Gansu province, with disease prevalence reaching up to 90% in A. sinensis during peak infection periods of June and July. F. tricinctum has been identified as the dominant pathogen, causing severe root rot symptoms and plant collapse in A. sinensis (Liu et al., 2022), while C. pilosula exhibits intense internal tissue browning (Zhao et al. 2021), and more than 50% of A. mongholicus yields are lost due to Fusarium -inducing root rots (Li et al., 2021b; Yun et al., 2022; Zhou et al., 2024). Although these three medicinal herbs are usually cultivated under 1-, 2-, and 3-year rotation systems intended to mitigate disease occurrence, However, these crop rotation practices that were designed to alleviate disease occurrence, Fusarium root rot, and wilts persists, raising concerns about cross-infection mechanisms and their interactions with soil and microbial environments. The ability of Fusarium spp to survive in plant residues further enhances their capacity to infect new hosts after decomposition (Arie, 2019; Leonce, 2021), facilitating long-term pathogen persistence in cropping systems. This cross-pathogenicity demonstrates the complexity and challenges in root rot control and the necessity of integrated disease management to control Fusarium infections effectively (Okello and Mathew, 2019). Although Fusarium-induced root rot is well-documented in medicinal herbs, the specific mechanisms of cross-infection, their long-term impacts on rhizosphere microbial networks, and the role of soil physicochemical conditions in disease persistence remain poorly understood. This study addresses these gaps by investigating how Fusarium cross-infection enables pathogen survival across multiple medicinal herb hosts and disrupts beneficial microbial networks, critical for plant resilience. By integrating cross-pathogenicity trials with microbiome and soil physicochemical analyses, we offer a comprehensive perspective on Fusarium-driven ecological shifts in medicinal herb cultivation. These findings contribute to a deeper understanding of Fusarium pathogenicity and emphasize the necessity of AMF-based strategies and integrated soil management to mitigate disease impact. We hypothesized that Fusarium cross-infection alters the structure and function of the rhizosphere microbiome and soil physicochemical conditions, leading to expedited disease development. Our findings aim to elucidate these interactions and provide valuable considerations for integrated management of Fusarium root rot to enhance resilient cultivation systems. 2. Materials and Methods 2.1 Field sampling, isolation, and characterization of culturable fungal species from plants and rhizosphere soils Field surveys and sample collections were conducted for root rot disease investigations in A. sinensis , C. pilosula , and A. mongholicus in Weiyuan County, Dingxi City, Gansu Province, in June 2022. The sampling sites included Dananchuan and Taizi (35°03′′N, 103°98′′E) in Luojiamo Village and Niejiashan (35°14′′N, 104°26′′E) in Niejiashan Village (Fig. 1 a-b). The cultivation of these three medicinal herbs at these locations was characterized by different cropping rotation systems (1-, 2-, and 3-year cycles). Diseased and healthy plants displaying symptoms such as leaf yellowing, wilting, and root decay were collected, with a total of 42 plant samples. Specifically, six diseased and six healthy A. sinensis plants were sampled from fields previously cultivated with A. mongholicus . For C. pilosula , nine diseased and nine healthy plants were sampled from three fields with different crop rotation histories, including sequential rotations of A. sinensis and A. mongholicus . Similarly, six diseased and six healthy A. mongholicus plants were collected from a field previously cultivated with A. sinensis . Plants were carefully uprooted using a shovel to loosen the surrounding soil, forming a wide circle approximately 30cm away from the root zone diameter to minimize root damage. The plants were then gently lifted by holding the base while preserving the rhizosphere soil. Rhizosphere soils were carefully collected by gently shaking the plant to remove loose bulk soil. The soil tightly adhering to the root surface of an approximately 2 mm thick layer was considered rhizosphere soil and was carefully collected to ensure minimal contamination. Samples were preserved in portable plastic boxes with ice packs and transported to the laboratory, followed by immediate preservation under controlled temperatures (4°C and − 80°C for subsequent molecular analyses). Plant tissues (roots, stems, and leaves) from symptomatic and asymptomatic samples of A. sinensis , C. pilosula , and A. mongholicus were surface sterilized using 70% ethanol (30 s) and 3% sodium hypochlorite (5 min), followed by sterile water rinses. For each plant species, three root, three stem, and three leaf samples were selected per condition (symptomatic and asymptomatic), totaling 18 tissue samples per species. After blotting dry, tissues were cut into 0.5 × 0.5 cm pieces using a sterile scalpel under a laminar flow hood to maintain aseptic conditions. The scalpel was flame sterilized before each use to prevent cross-contamination. These tissue sections, including leaf samples, were placed on Rose Bengal Agar (RBA; 36.6 g/L, Qingdao Bio-Technology Co., Ltd., China) plates. Rhizosphere soils were processed by transferring 0.5 g into sterile water, vortexing for 5–10 min, and preparing 10-fold serial dilutions (10⁻¹ to 10⁻⁵). From each dilution, 100 µL was spread onto RBA plates. The plates were incubated in darkness at 25°C for 5–7 days. Emerging fungal mycelia to allow mycelial growth from plant tissues and soil suspensions. Emerging mycelia from plant tissues and soil suspensions were subcultured onto full-strength potato dextrose agar (PDA; 46 g/L, Qingdao Bio-Technology Co., Ltd., China) and subcultured to obtain distinct fungal colonies, which were further purified on fresh PDA for identification. The morphological characterization of isolates was performed based on colony features, including the color, texture and mycelia growth rate on PDA and microscopic observation of conidial structures, including macroconidia, microconidia and chlamydospores on both PDA and Carboxymethylcellulose (CMC) broth. Distinctive traits were used for preliminary identification before molecular analysis. Isolates were preserved in 40% glycerol at − 80°C for future studies. 2.2 Fungal DNA Extractions and Molecular Identification Fungal genomic DNA of all 83 fungal isolates was extracted from 100 mg of ground fungal mycelia using a CTAB-based method. Tissues were lysed with Buffer CPL, mercaptoethanol, and optional RNase, incubated at 65°C. Chloroform and isoamyl alcohol were used for phase separation. DNA was precipitated with ethanol, bound to a HiBind DNA column, and washed twice with SPW Wash Buffer. Residual ethanol was removed by centrifugation, and DNA was eluted using a pre-warmed Elution Buffer. Final eluates were collected for downstream applications (Omega Bio-tek, Inc. 2022. E.Z.N.A. ®HP Fungal DNA kit. Available at www.omegabiotek.com ). DNA concentration and quality were evaluated using a NanoDrop 2000c spectrophotometer (Thermo Fisher Scientific) and agarose gel electrophoresis. Species-level molecular identification of Fusarium isolates was achieved by amplifying the internal transcribed spacer (ITS) region, the translation elongation factor (TEF1-α), and RNA polymerase II second largest subunit (RPB2) gene regions using ITS1/ITS4 primers (ITS1: 5′-TCCGTAGGTGAACCTGCGG-3′; ITS4: 5′-TCCTCCGCTTATTGATATGC-3′; (Schoch et al., 2012; Zarrin et al., 2016)), TEF1F/TEF1R primers (TEF1F: 5′-GTCACTTGATCTACCAGTGC-3′; TEF1R: 5′-TACCAATGACGGTGACATAG-3′ (Uwaremwe et al., 2021)), and 7cr/5f2 (7cr: 5′-GGGGWGAYCAGAAGAAGGC-3′; 5f2: 5′-CCCATRGCTTGYTTRCCCAT-3′; ( O’Donnell et al., 2010)) primers, respectively. PCR products were sequenced at Sangon Biotech and analyzed using BLAST against NCBI GenBank. All sequences have been deposited in NCBI GenBank under accession numbers (Table 1 ). Phylogenetic trees were constructed with concatenated ITS and TEF1-α sequences using the neighbor-joining method in MEGA 7 (Kumar et al., 2016) with 1,000 bootstrap replicates to validate evolutionary relationships, and bootstrap values calculated for 1,000 replicates. Table 1 Detailed information on 58 Fusarium isolates obtained in this study, with their original sequences accession numbers. Isolate IDᵃ Species Host of Originᵇ Isolation Saurce c GeneBank Accessions ITS TEF1-α DSH26 F. oxysporum C. pilosula Diseased Root PQ328624 PQ397570 DSH27 F. oxysporum C. pilosula Diseased Root PQ328625 PQ397571 DSH28 F. oxysporum C. pilosula Diseased Root PQ328626 PQ397572 DSH29 F. oxysporum C. pilosula Diseased soil PQ328627 - DSH30 F. oxysporum C. pilosula Diseased Root PQ328628 PQ397573 DSH31 F. oxysporum C. pilosula Diseased Root PQ328629 PQ397574 DSH32b F. tricinctum C. pilosula Diseased Root PQ328630 PQ397575 DSH62 F. oxysporum C. pilosula Diseased soil PQ328631 - DSH63 F. oxysporum C. pilosula Diseased Root PQ328632 PQ397576 DSH64 F. oxysporum C. pilosula Diseased Root PQ328633 PQ397577 DSH65 F. oxysporum C. pilosula Diseased Root PQ328634 PQ397578 DSH67 F. oxysporum C. pilosula Diseased Root PQ328635 PQ397579 DSH69 F. oxysporum C. pilosula Diseased Stem PQ328636 - DSH34 F. oxysporum C. pilosula Diseased Root PQ328637 PQ397580 DSH37 F. oxysporum C. pilosula Diseased Root PQ328638 PQ397581 DSH38 F. oxysporum C. pilosula Diseased Root PQ328639 PQ397582 DSH39 F. oxysporum C. pilosula Diseased Root PQ328640 PQ397583 DSH40 F. oxysporum C. pilosula Diseased Root PQ328641 PQ397584 DSH71 F. oxysporum C. pilosula Diseased Root PQ328642 PQ397585 DSH73 F. redolens C. pilosula Healthy Root PQ328643 PQ397586 DSH82 F. flocciferum C. pilosula Diseased soil PQ328644 PQ397587 DSH114b F. solani C. pilosula Diseased Root PQ328645 PQ397588 DSH122 F. oxysporum C. pilosula Diseased Root PQ328646 PQ397589 DG14 F. oxysporum A. sinensis Diseased Soil PQ328647 - DG15 F. solani A. sinensis Diseased Root PQ328648 PQ397590 DG16 F. solani A. sinensis Diseased Root PQ328649 PQ397591 DG18 F. acuminatum A. sinensis Diseased Root PQ328650 PQ397592 DG19 F. Avenaceum A. sinensis Diseased Root PQ328651 PQ397593 DG105 F. tricinctum A. sinensis Diseased Root PQ328655 PQ397596 DG4 F. tricinctum A. sinensis Diseased Root PQ328656 PQ397597 DG4a F. tricinctum A. sinensis Diseased Root PQ328657 PQ397598 DG105b F. tricinctum A. sinensis Diseased Root PQ328658 PQ397599 HQ1 F. solani A. mongholicus Diseased Root PQ328659 PQ397600 HQ2 F. solani A. mongholicus Diseased Root PQ328660 PQ397601 HQ5 F. solani A. mongholicus Diseased Root PQ328661 PQ397602 HQ8 F. solani A. mongholicus Diseased Root PQ328662 PQ397603 HQ9 F. solani A. mongholicus Diseased Root PQ328663 PQ397604 HQ10 F. oxysporum A. mongholicus Diseased Soil PQ328664 - HQ11 F. oxysporum A. mongholicus Diseased Soil PQ328665 - HQ12 F. solani A. mongholicus Diseased Root PQ328666 - HQ13 F. solani A. mongholicus Diseased Root PQ328667 PQ397605 HQ51 F. solani A. mongholicus Diseased Soil PQ328668 PQ397606 HQ53 F. acuminatum A. mongholicus Diseased Root PQ328669 PQ397607 HQ54 F. oxysporum A. mongholicus Diseased Root PQ328670 PQ397608 HQ90 F. solani A. mongholicus Diseased Soil PQ328671 - HQ91 F. solani A. mongholicus Diseased Soil PQ328672 PQ397609 HQ99 F. solani A. mongholicus Diseased Soil PQ328673 PQ397610 HQ100 F. solani A. mongholicus Diseased Root PQ328674 - HQ101 F. solani A. mongholicus Diseased Root PQ328675 PQ397611 HQ102 F. solani A. mongholicus Diseased Root PQ328676 PQ397612 HQ103 F. acuminatum A. mongholicus Diseased Root PQ328677 PQ397613 HQ104 F. solani A. mongholicus Diseased Root PQ328678 PQ397614 HQ123 F. solani A. mongholicus Diseased Root PQ328679 PQ397615 HQ124 F. solani A. mongholicus Diseased Stem PQ328680 PQ397616 HQ125 F. avenaceum A. mongholicus Diseased Root PQ328681 PQ397617 ᵃBolded identities are Fusarium isolates used in cross-pathogenicity experiments. ᵇ Fusarium spp. were isolated from different medicinal herb plant species. c Fusarium spp . were isolated from symptomatic and asymptomatic plants and rhizosphere soils. 2.3 Experiment design, inoculum preparation, and cross-pathogenicity evaluation Fungal inoculum was prepared by culturing Fusarium isolates (DSH27, HQ123, DG105) on PDA for 10 days. Conidia suspension was prepared by scraping the mycelium with sterile water and subsequently filtering it through sterile cheesecloth. Fusarium strains were grown on PDA at 25°C in complete darkness for 5 days to enhance conidia production. The actively growing fungal mycelia were excised as agar plugs from culture plates. Then, sterile forceps were used to transfer the plugs into autoclaved carboxymethylcellulose (CMC) broth in a sterilized 500 mL Erlenmeyer flask. A solution of CMC broth was prepared by dissolving 15 g of carboxymethylcellulose, 2 g of NaNO3, 1 g of KH2PO4, 0.5 g of MgSO4⋅7H2O, and 1 g of yeast extract in 1000 ml of sterile water. The culture was shaken for 5 days at 175 rpm in an incubator at 25°C (Zhang et al., 2020). Concentrations of spores were adjusted to 10⁶ conidia/mL using sterile ddH2O and a hemocytometer. Pathogenicity was assessed through three assays, including greenhouse pot tests, field trial, and pathogenicity tests on excised root tissues. Seedlings were planted into pots containing sterilized soil made of peat and vermiculite in a 2:2:1 ratio in the greenhouse. Each fungal isolate was tested on eight plants per species, with two plants per pot and four replicates per isolate. A field experiment was conducted in Longxi County (35°01′′N, 104°51′′E), Gansu Province, from April to October 2023, with plots classified by species and inoculation treatments. Inoculation was performed in June with F. oxysporum (DSH27), F. solani (HQ123), F. tricinctum (DG105), and a water control (CK). Plants were cultivated in rows, with spacing tailored to each species. Inoculation involved applying spore suspension to wounded taproots. For inoculation, taproot wounds (3 mm depth) were created on seedlings of A. sinensis , C. pilosula , and A. mongholicus . A 20 mL spore suspension was applied directly to the wounded part of the main roots and gently into the rhizosphere dripline. Control plants underwent the same wounding procedure but were inoculated with sterile water double distilled (ddH₂O) to distinguish the effects of mechanical damage from Fusarium infection (Pande et al., 2007; Pouralibaba et al. 2016). The field experiment was conducted over a full growing-to-harvest cycle using a randomized complete block design (RCBD), with 3 replicates ensuring reproducibility and minimizing environmental variability across the study area. For excised root tissue assays, sterilized and wounded root tissues were inoculated with agar plugs extracted from the Fusarium colony margins of 10-day-old PDA medium cultures using a 5-mm diameter cork-borer, incubated in petri dishes, and assessed for rot symptoms (Bugingo et al., 2024; Moparthi et al. 2024). The maintained control treatment consisted of root tissue without a fungal plug. (Fig. S1 ). Inoculated Fusarium species were re-isolated from symptomatic tissues and re-cultured for morphological and molecular confirmation through DNA extraction, ITS/TEF1-α PCR amplification, and sequencing. Greenhouse and excised root tissue experiments were repeated twice, and BLAST analysis confirmed pathogen identities, ensuring consistency with the original inoculated Fusarium strains. 2.4 Measurement of Disease Incidence and Severity Disease incidence (DI) and disease severity (DS) were evaluated to determine the impact of Fusarium isolates on A. sinensis , C. pilosula , and A. mongholicus . For aboveground symptoms, DI and DS were assessed at 3-, 6-, and 9-weeks post-inoculation. Visible symptoms such as wilting and leaf or stem yellowing were recorded. Belowground symptoms were evaluated 9 weeks after inoculation by examining harvested roots. Roots were washed under low-pressure water, placed on sterilized filter paper, and cut longitudinally to assess key root rot characteristics, including epidermal decay, vascular darkening, and root rot. DI was calculated as the percentage of infected plants relative to the total number of plants in each treatment group (Sharma & Kolte, 1994). DS was evaluated on a 0–5 scale, where 0 represented no symptoms, 1 = 1–9% affected, 2 = 10–29%, 3 = 30–69%; 4 = 70–89%, and 5 = 90–100% affected area (Moparthi et al., 2021; Shikur Gebremariam et al., 2018; Wildermuth & McNamara, 1994). The belowground root rot DI and DS were evaluated 9 weeks post-inoculation during harvest. Roots were cleaned, placed on sterilized filter paper, and longitudinally cut to observe key symptoms such as epidermal decay and vascular discoloration. Here, the DS was scored on a 0–5 scale (Grünwald et al., 2003), where 0 = no symptoms; 1 = slight hypocotyl lesions; 2 = lesions consolidating on epicotyls and hypocotyls; 3 = lesions spreading into root systems; 4 = extensive infection of roots and hypocotyls; 5 = complete root system decay (Fig. 3 g-l). Similarly, field assessments employed a five-point interval sampling method in 1 m square areas within experimental plots. Fifteen plants from Fusarium -inoculated and control groups were evaluated per plot. For excised root tissue assays, DI and DS were determined by observing root rot browning and decay from epidermal lesions to complete root tissue disease severity was assessed by evaluating browning and decay levels, following standard belowground root rot severity scaling methods as shown by Sharma and Kolte (1994). 2.5 Rhizosphere and Bulk Soil DNA Extractions, and Illumina Novaseq Sequencing Total soil DNA was extracted from 0.5 g of bulk and rhizosphere soil samples using the TGuide S96 Magnetic Bead-based Soil Genomic DNA Extraction Kit (Tiangen Biochemical Technology, Beijing, China), following the manufacturer's protocol. DNA concentration and quality were assessed using a microplate (Synergy HTX Gene Company Limited, Bomei Fuxin Technology, Beijing, China). PCR amplification was performed to target conserved regions of ribosomal RNA, including the fungal ITS (internal transcribed spacer) region and bacterial 16S rDNA, using primers ITS1F 5'-CTTGGTCATTTAGAGGAAGTAA-3' and ITS2 5'-GCTGCGTTCTTCATCGATGC-3'; 338F 5'- ACTCCTACGGGAGGCAGCA-3' and 806R 5'- GGACTACHVGGGTWTCTAAT-3', respectively (Liu et al., 2021; White, 1990). Sample-specific PacBio barcode sequences were added to both forward and reverse primers to enable multiplex sequencing, as described by Buermans et al. (2017). PCR reactions included 25 µL of ddH2O, 2.5 µL of each primer, 12.5 µL of Phusion Hot Start Flex 2×Master Mix (Thermo Fisher Scientific, Oregon, USA), and 50 ng of template DNA. Thermal cycling conditions consisted of initial denaturation at 95°C for 5 min, followed by 25 cycles of denaturation (95°C for 30 s), annealing (50°C for 30 s), extension (72°C for 40 s), and a final extension at 72°C for 7 min. Amplified PCR products were purified using Agencourt AMPure XP Beads and quantified with a Qubit 4.0 Fluorometer and Qubit dsDNA HS Assay Kit (Thermo Fisher Scientific Oregon, USA) (Shao et al., 2023). Qualified libraries were prepared and sequenced using the Illumina Novaseq 6000 platform. All sequencing data were deposited in the NCBI Sequence Read Archive (SRA) under accession numbers PRJNA1201923 and PRJNA1202069 for Fungi and bacteria, respectively. 2.6 Bioinformatic Analyses Bioinformatic analyses were performed using the BMK Cloud platform (Biomarker Technologies Co., Ltd., Beijing, China). Illumina high-throughput sequencing data were processed using Trimmomatic v0.33 to filter low-quality reads with a 50 bp sliding window, and sequences were trimmed when the average quality within the window fell below a Phred score of 20 (Bolger et al., 2014). Primer sequences were identified and trimmed using Cutadapt v1.8.3 (Martin, 2011) with a maximum mismatch rate of 20% and a minimum overlap of 15 bp. Sequences were length-filtered based on region-specific thresholds (e.g., 350–490 bp for 16S V3-V4 amplicons). Chimeric sequences were identified and removed using the UCHIME algorithm v8.1 (Edgar et al., 2011). Reads were assigned to samples based on barcode sequences and clustered into operational taxonomic units (OTUs) at 97% similarity using USEARCH v10 (Edgar, 2013). Low-abundance features were filtered, and taxonomic assignment of OTUs was conducted using the DADA2 algorithm (Callahan et al., 2016) in QIIME2 version 2020.6 (Bolyen et al., 2019), with a confidence threshold of 70%. Alpha diversity indices and beta diversity comparisons were calculated using QIIME2 and R software (R Core Team, 2024). Functional annotation of fungal sequences was performed using FUNGuild (Nguyen et al., 2016), classifying taxa into functional guilds based on ecological roles and nutritional strategies. 2.7 Statistical analysis The statistical analysis was conducted using the SPSS software (v27.0, IBM, Armonk, NY, USA). Considering the quantification of disease incidence and severity on an ordinal scale ranging from 0 to 5, statistical non-parametric tests were transformed to evaluate the treatment effects. Mean ranks ( \(\:\stackrel{-}{R}ij\) ), Median disease rate (MDR), and relative treatment effects ( \(\:\widehat{p}ij\) ) with 95% confidence intervals (CIs) were measured. Mean ranks derived from these non-parametric ordinal data and relative treatment effects with CIs were determined, as described in Shah and Madden (2004). Rarefaction curves were generated in QIIME2 to evaluate sequencing depth adequacy, with alpha diversity indices (Shannon, Simpson, ACE, and Chao1) calculated as described by Bokulich et al. (2013). Beta diversity was analyzed using partial least squares discriminant analysis (PLS-DA) to differentiate between groups and identify influential variables (Adamberg et al., 2015). Disease severity rankings were standardized across all plant species to ensure comparability, and Partial Least Squares Discriminant Analysis (PLS-DA) was employed to differentiate between treatment groups, maximizing inter-group variance and identifying key influential microbial variables linked to Fusarium infection. Species diversity, distribution, and function analyses were performed using the BMKCloud platform ( www.biocloud.net ). Network analysis was conducted using Gephi (Bastian et al., 2009), complementing statistical analyses performed in R software (R Core Team, 2024) to identify key interaction patterns and microbial network structures. Metastats analysis (White et al., 2009) was employed to identify significant differences in microbial abundance and functions between control and inoculated groups, with significance set at p < 0.05. The maximum variance to determine the linear combinations and relationships between microbial communities, soil physicochemical properties, and disease metrics was performed using the principal component analysis (PCA) in Canoco 5 software (Šmilauer and Lepš, 2014). 3. Results 3.1 Isolation, morphological characterization, and phylogenetic diversity analysis of Fusarium isolates. The isolation of culturable fungi from diseased and healthy rhizosphere samples of A. sinensis , C. pilosula , and A. mongholicus yielded 83 fungal isolates, of which 69.87% (58 isolates) were identified as Fusarium spp. based on ITS region analysis (Fig. 1 D). The isolation and phylogenetic analysis revealed distinct host associations among the three Fusarium species complexes, with Fusarium oxysporum species complex (FOSC, 36.2%), primarily from C. pilosula ; Fusarium solani species complex (FSSC, 31%) predominantly from A. mongholicus ; and Fusarium tricinctum species complex (FTSC, 22.4%) mainly from A. sinensis , as shown in Table 1 and Fig. 2 . Morphological assessment revealed distinct conidial features among these complexes, with similarities in spore formation patterns and cell structures, exhibiting fast-growing mycelium structures on PDA media and shared pigmentation patterns ranging from whitish to pink or purple. These Fusarium species complexes displayed closely related conidial curvature, dense conidial masses, and comparable conidiogenesis processes (Fig. 2 a–w). Further species-level identification using TEF1-α and RBP2 gene sequencing confirmed the clustering of isolates within their respective complexes. Representative strains F. oxysporum strain DSH27 ( C. pilosula ), F. solani strain HQ123 ( A. mongholicus ), and F. tricinctum strain DG105 ( A. sinensis ) (Fig. 2 Y) were selected for cross-pathogenicity assays. Sequences for these strains were deposited in GenBank (ITS: PQ328624, PQ328672, PQ328653; TEF1-α: PQ397570, PQ397615, PQ397596 and RPB2: PV358060, PV358062, PV358061) for DSH27, HQ123 and DG105, respectively. Other accession numbers are provided in Table 1 3.2 Cross-inoculation and pathogenicity evaluation: Disease incidence and severity The cross-infection and pathogenicity investigation using three Fusarium isolates (DSH27, HQ123, DG105) representing each species complex (FOSC, FSSC, FTSC) from A. sinensis , C. pilosula , and A. mongholicus revealed variability in aggressiveness across plant species. Both greenhouse and field trials, which followed the same experimental design, showed significant differences in disease severity between Fusarium -inoculated and non-inoculated control plants (P ≤ 0.05). Homogeneity of variance tests indicated no significant differences between trials (P ≤ 0.05), allowing data to be pooled for analysis. Fusarium isolates were categorized into four aggressiveness groups based on disease severity ranks: highly aggressive (˃385.1), moderately aggressive (304.5–385.1), less aggressive (223.8–304.4), and weakly aggressive (˂223.7). Across trials, isolates showed the greatest aggressiveness on their original host plants. F. tricinctum (DG105) was highly aggressive on A. sinensis , moderately aggressive on C. pilosula , and less aggressive on A. mongholicus . F. oxysporum (DSH27) displayed high aggressiveness on C. pilosula , moderate aggressiveness on A. sinensis , and weak aggressiveness on A. mongholicus . F. solani (HQ123) was highly aggressive on A. mongholicus , moderate on A. sinensis , and weak on C. pilosula (Table 2 ). Notably, on excised root tissues, disease incidence reached 100% across all plant species for their original Fusarium isolates, with severity averaging 85%, while in cross-infections, both incidence and severity were approximately 80%. ( Fig. S1 d). Intriguingly, F. solani exhibited the highest cross-infection severity, exceeding the disease severity caused by original isolates in A. sinensis ( Fig. S1 a, d). Disease severity correlated with time post-inoculation, with symptoms progressing from yellowing and wilting to stunting and plant death (Fig. 3 a–f). These findings highlight host-specific interactions and variability in cross-pathogenicity, emphasizing that Fusarium isolates exhibit differing levels of aggressiveness based on plant species. Table 2 Evaluation of mean ranks of disease severity ratings across three medicinal herbs ( A. sinensis , C. pilosula , A. mongholicus ) following cross-inoculation with the three Fusarium strains (DSH27, HQ123, and DG105) tested in this study. Isolates Fusarium spp. Host species MDR 95% CI for Relative Effect Aggressiveness \(\:\stackrel{-}{\varvec{R}}\varvec{i}\varvec{j}\text{ᵃ}\) \(\:\widehat{\varvec{p}}\varvec{i}\varvec{j}\) ᵇ Lower Upper DSH27 F. oxysporum A. sinensis 1 288.05 0.52 0.45 0.59 Less HQ123 F. solani A. sinensis 1 295.82 0.53 0.47 0.6 Less DG105 F. tricinctum A. sinensis 3 399.04 0.72 0.66 0.79 High CK Control A. sinensis 0 174.65 0.31 0.25 0.38 Nonpathogenic DSH27 F. oxysporum C. pilosula 2 370.56 0.67 0.6 0.74 Moderate HQ123 F. solani C. pilosula 1 287.77 0.52 0.45 0.58 Less DG105 F. tricinctum C. pilosula 1 321.45 0.58 0.51 0.65 Moderate CK Control C. pilosula 0 158.82 0.28 0.22 0.35 Nonpathogenic DSH27 F. oxysporum A. mongholicus 0.5 248.49 0.45 0.38 0.51 Less HQ123 F. solani A. mongholicus 2 349.45 0.63 0.56 0.69 Moderate DG105 F. tricinctum A. mongholicus 1 276.91 0.5 0.43 0.56 Less CK Control A. mongholicus 0 146.96 0.26 0.19 0.33 Nonpathogenic ᵃMean rank ( \(\:\stackrel{-}{R}ij\) ), median rate (MDR), and relative effect ( \(\:\widehat{P}ij\) ) for root rot severity ratings of Fusarium isolate were determined following the method outlined by Shah and Madden (2004). Higher ranks indicate more aggressive isolate, causing increased root rot severity. Isolate with mean rank ˃223.7, weakly aggressive; 223.8–304.4, Less aggressive; 304.5–385.1, moderately aggressive; and ˃385.1, highly aggressive. 3.3 Infection and root-rot symptomatological observations on root tissue staining Symptomatological observations on A. sinensis , C. pilosula , and A. mongholicus seedlings inoculated with F. oxysporum (DSH27), F. solani (HQ123), and F. tricinctum (DG105), along with controls, were conducted six weeks post-inoculation. Healthy root tissues (CK) exhibited intact cell walls, a continuous hypodermis, and densely packed cells (Fig. 4 ; Fig. S2 ). Infected tissues showed significant variation in aggressiveness depending on Fusarium spp. and plant species. Severe infections in A. sinensis (by F. tricinctum DG105), C. pilosula (by F. oxysporum DSH27), and A. mongholicus (by F. solani HQ123) were characterized by extensive tissue degradation, necrosis, reddish-brown vascular discoloration in A. sinensis , and dark brown to black discoloration in the other two species. Fusarium infections on their original host plants induced increased lignification, accumulation of pathogen hyphae, and high levels of necrosis in A. sinensis (Fig. 4 a; Fig. S2 a), C. pilosula (Fig. 4 b; Fig. S2 b), and A. mongholicus (Fig. 4 c; Fig. S2 c), indicating high aggressiveness (Fig. 5 a-b; Table 2 ). However, cross-infections demonstrated partial tissue degradation and localized damage. F. tricinctum and F. solani caused moderate staining and localized cell disintegration in C. pilosula (Fig. 4 b; Fig. S2 b), indicating moderate aggressiveness (Fig. 5 a-b; Table 2 ). Conversely, F. tricinctum and F. oxysporum caused minimal damage in A. mongholicus , with faint staining, limited cell disruption, and pathogen presence largely confined to epidermal and cortical cells, suggesting weak infections (Fig. 4 c; Fig. S2 c), indicating less aggressiveness (Fig. 5 a-b; Table 2 ). 3.4. Sequencing data and fungal and bacterial community networks in bulk and rhizosphere soils under Fusarium inoculation Sequencing infected and non-infected samples yielded 1,919,988, 1,919,839, and 1,919,839 raw fungal reads, and 1,920,440, 1,918,895, and 1,919,587 raw bacterial reads for A. sinensis , C. pilosula , and A. mongholicus , respectively. After quality filtering, the average high-quality fungal reads per sample ranged from 56,348 to 67,841, while bacterial reads ranged from 40,928 to 62,891. These reads were clustered into 245, 225, and 219 fungal OTUs and 1,705, 1,561, and 1,641 bacterial OTUs for A. sinensis , C. pilosula , and A. mongholicus , respectively, based on 97% sequence similarity. Fusarium -inoculated rhizosphere soils showed more OTUs than healthy non-inoculated rhizospheres. Unique OTUs varied between Fusarium -infected soils (DSH27, HQ123, DG105), non-infected controls (CK), and bulk soils (BF), with rhizosphere soils displaying higher diversity than bulk soils (Fig. 6 a-j). Fungal and bacterial Alpha diversity indices (Shannon, Simpson, Chao1, Ace) revealed no significant differences in fungal diversity between infected and non-infected rhizosphere soils (Fig. 6 c-k). However, the Shannon index for bacterial diversity was significantly lower in F. oxysporum DSH27-inoculated treatments in A. sinensis compared to CK (p < 0.01) (Fig. 6 d-l). Although no significant differences were detected between treatments, species richness (Chao1 and Ace indices) was higher in CK than in DSH27 and HQ123 treatments ( Table S1 ). Beta diversity analysis revealed distinct clustering of microbial communities between infected and non-infected rhizospheres using partial least squares discriminant analysis (PLS-DA). Although the ANOSIM analyses mainly indicated no significant differences in the overall fungal and bacterial community structure between healthy and diseased groups, the non-infected formed separate clusters with Fusarium -infected rhizospheres (Fig. 7 a-c). Here, fungal beta diversity was significantly different in F. tricinctum DG105-infected rhizospheres and bulk soils in A. sinensis (R² = 0.217, p = 0.03) (Fig. 7 a-c), while bacterial beta diversities between bulk and rhizosphere soils showed no significant differences ( p > 0.05) (Fig. 7 d-f). 3.5. The impact of Fusarium infection and cross-infection on rhizosphere fungal and bacterial communities and functional dynamics Shifts in fungal and bacterial community composition and functions following Fusarium inoculation (DSH27, HQ123, and DG105) compared to the water control (CK) revealed significant changes in Fusarium -infected compared to non-infected rhizosphere soils. Fusarium inoculation significantly altered fungal phyla, increasing the abundance of Chytridiomycota in A. sinensis (Fig. 8 a) and Rozellomycota in C. pilosula (Fig. 8 c). Similarly, Olpidiomycota and Mucoromycota were significantly increased in C. pilosula (Fig. 8 c), while Ascomycota and Aphelidiomycota were increased dramatically in A. mongholicus (Fig. 8 e). At the genus level, Fusarium abundance significantly increased in infected C. pilosula (p < 0.01) (Fig. 8 d). Genera such as Lectera, Stagonosporopsis, and Cumuliphoma decreased considerably in DG105-infected A. mongholicus , while Mortierella abundance was significantly reduced in DSH27-infected A. sinensis (Fig. 8 f). Bacterial communities were also influenced, particularly in DG105-infected soils of A. sinensis and C. pilosula , where significant changes in Verrucomicrobiota and Acidobacteriota phyla were observed in A. mongholicus . At the genus level, RB41 and unclassified_Microcellaceae significantly declined under Fusarium treatment ( Fig. S3 ). Interestingly, fungal trophic functions demonstrated a shift toward pathogenicity in all Fusarium -infected rhizosphere soils, with increased plant pathotrophic functions and reduced symbiotrophic and saprotrophic roles (Fig. 9 a-c). Notably, beneficial arbuscular mycorrhizal fungi (AMF) were significantly reduced in HQ123-infected A. sinensis (p = 0.014) (Fig. 9 d). Specifically, comparisons of AMF abundances revealed significant differences in A. sinensis . Although the difference was not statistically significant in A. mongholicus and C. pilosula , there was a clear trend of decreased AMF abundance under infected rhizospheres compared to healthy, non-infected rhizospheres (Fig. 9 d). In contrast, plant pathotrophic fungal abundance displayed an inverse pattern, increasing pathogenic fungi in infected rhizospheres across all tested plant species. For bacterial functions, KEGG pathway analysis revealed significant effects on transcription, translation, and metabolism-related pathways in DG105-infected A. sinensis . In C. pilosula , functions related to the immune system and environmental adaptation were significantly affected ( Fig. S4 ). 3.6. The interconnections between rhizosphere microbial communities, soil physicochemical properties, and the incidence and severity of root rot disease Microbial network analysis revealed Fusarium -driven alterations in taxa connectivity within rhizosphere communities. Fusarium infection decreased network modularity classes by either increasing or decreasing modularity and altering the degree of centrality of specific fungal taxa. Fungal genera predominantly pathogenic or containing numerous pathogenic taxa include Fusarium , Alternaria , Stagonosporopsis , and Plectosphaerella , exhibited either increased weighted degree of centrality or betweenness centrality under F. tricinctum DG105 and F. oxysporum DSH27 infected A. sinensis (Fig. 10 a-d), F. oxysporum DSH27 infected C. pilosula (Fig. 10 e-h), and F. solani HQ123 infected A. mongholicus (Fig. 10 i-l). The dominant genus Mycothermus and some other genera considered to have the most beneficial taxa gained an increased degree of centrality due to the increased negative correlation with Fusarium and other pathogenic genera under F. tricinctum DG105 and F. solani HQ123 infected soils. In C. pilosula , higher degree and betweenness centralities were observed under F. oxysporum DSH27-infected rhizospheres. However, in A. mongholicus , except under its original pathogen isolate F. solani HQ123, beneficial considered genera such as Mycothermus, Trichoderma , and Penicillium gained degree and betweenness increased centralities under F. oxysporum DSH27 and F. tricinctum DG105 which might be attributed to their less aggressiveness in A. mongholicus (Fig. 10 i-l). Soil physicochemical properties and rhizosphere microbial communities were associated with root rot incidence (DI) and severity (DS) in A. sinensis, C. pilosula , and A. mongholicus . In A. sinensis , TC and AVP were significantly higher in Fusarium -infected soils (DSH27 and DG105) compared to healthy soils (p < 0.05). Microbial biomass nitrogen (MBN) showed an increasing trend in DG105- and HQ123-infected soils but was not statistically significant. In contrast, microbial biomass carbon (MBC) and phosphorus (MBP) significantly decreased under F. oxysporum (DSH27) in C. pilosula soils ( Table S2 and S3). The fungal genus Mycothermus was negatively correlated with DI and DS. In contrast, Plectosphaerella and unclassified_Ascomycota positively correlated with DI, DS, and MBC in A. sinensis (Fig. 10 m). DI and DS were negatively correlated with Mortierella and positively with unclassified_Basidiomycota , as well as soil pH, Mn, and Zn (Fig. 10 m). The bacterial genus Micrococcaceae was positively linked to DI, DS, and AVP. In contrast, RB41 and Vicinamibacteraceae negatively correlated with DI and DS ( Fig. S5 a). In C. pilosula , healthy soils had significantly higher TN, SOM, TC, and Fe compared to infected soils (p < 0.05) (Fig. 10 n). The bacterial genus RB41 negatively correlated with DI and DS in HQ123- and DSH27-infected rhizospheres, while positively associated with AVP and total phosphorus (TP) ( Fig. S5 b). In A. mongholicus , DI and DS negatively correlated with TN and Fe, while Plectosphaerella and Fusarium positively correlated with disease severity (Fig. 10 o). Micrococcaceae negatively correlated with DI and DS (p < 0.05) and was positively linked to higher Ca and Mn in DSH27-infected rhizospheres. Across all plant species, higher Zn levels correlated positively with unclassified_Ascomycota and pathogenic Fusarium . Bacterial genera like RB41 , Vicinamibacteraceae , and MDN1 were negatively associated with DI and DS in A. sinensis and C. pilosula rhizospheres ( Fig. S5 ). Micrococcaceae negatively correlated with DI and DS (p < 0.05) and was positively linked to higher Ca and Mn in DSH27-infected A. mongholicus rhizospheres. 4. Discussion Crop rotation significantly influences the dynamics of rhizosphere and plant microbiomes by altering soil conditions, improving microbial diversity, and disrupting the life cycles of soil-borne pathogens (Gahagan et al., 2023; Maarastawi et al., 2018). However, it can also facilitate cross-infection through plant residues, creating similarities in rhizosphere microbiome composition across cropping systems (Kerdraon et al., 2019). This study reveals the successful cross-infection and pathogenicity of Fusarium species among A. sinensis , C. pilosula , and A. mongholicus , demonstrating host-specific aggressiveness. Additionally, Fusarium infection altered rhizosphere microbial networks, decreased AMF abundance, and disrupted soil physicochemical properties, collectively exacerbating disease severity across these medicinal herbs. These Fusarium species were prevalent across plant species, with Fusarium oxysporum species complex (FOSC) primarily associated with C. pilosula , Fusarium solani species complex (FSSC) with A. mongholicus , and Fusarium tricinctum species complex (FTSC) with A. sinensis , underscoring their host specificity and adaptability to different rhizosphere environments. The morphological and phylogenetic similarities among Fusarium isolates highlight their evolutionary adaptability, facilitating survival in soil and plant debris during off-seasons (Leslie and Summerell, 2006). Their shared conidial curvature, dense conidial masses, and rapid mycelial growth enhance persistence and cross-infective potential. Fusarium species endure unfavorable conditions such as chlamydospores or dormant mycelia, which later infect successive crops (Gordon & Martyn, 1997; Summerell, 2019). This adaptability aligns with findings that biochemical changes in the rhizosphere soil due to crop rotations influence pathogen survival and infection dynamics (Peralta et al., 2018; Yan et al., 2023), underscoring their role in cross-pathogenicity in medicinal herb systems. The study revealed that Fusarium species complexes exhibited significant variances in aggressiveness toward distinct medicinal herb hosts during pathogenesis. F. tricinctum was the most aggressive towards A. sinensis , exhibiting moderate aggressiveness on C. pilosula and less aggressiveness on A. mongholicus . According to its diverse host range and involvement in root rot, crown rot, and blight diseases in temperate crops and medicinal herb plants, F. tricinctum ability to infect many host plants indicates its flexibility and the difficulty in managing this pathogen in intercropped situations. (Liu et al., 2022; Uwaremwe et al., 2021; Wang et al., 2022). Similarly, F. solani was highly aggressive to A. mongholicus , moderately aggressive to A. sinensis , and less aggressive to C. pilosula , confirming its pathogenicity in severe A. mongholicus root rots, as well as cross-pathogenicity on other medicinal herbs (Wang et al., 2022) and its cross-pathogenic effects on several different medicinal herbs (Xu et al., 2021). The observed difference in aggressiveness is consistent with earlier research revealing that F. solani exploits harsh host environmental conditions to generate systemic infections with serious economic repercussions (Xi et al., 2023). Furthermore, F. oxysporum was highly aggressive towards C. pilosula but less hostile towards the other two hosts. This discovery is consistent with its documented potential to induce root rot and wilt symptoms in C. pilosula and a variety of medicinal crops in Gansu Province (Liu et al., 2024; Zhao et al., 2021). Soil and plant residues are frequent habitats for Fusarium species, which might serve as a pathway for cross-infection among plants cultivated consecutively (Yan et al., 2023). These findings illustrate the intricate ecological and evolutionary interactions between Fusarium species and their plant hosts, demonstrating that variations in aggressiveness reflect not only host adaptations but also environmental and management factors. Variability in the pathogenicity of Fusarium species among hosts highlights the dual nature as both host-specific and cross-infective, aligning with Moparthi et al. (2020) and (2021), whose greenhouse study in Montana demonstrated that shared Fusarium inocula led to cross-pathogenicity among pulse and cereal crops. Our study showed that F. tricinctum exhibited the highest level of aggressiveness towards its primary host, A. sinensis , with a subsequent reduction in impact observed on C. pilosula and A. mongholicus . Similarly, F. oxysporum and F. solani exhibited higher aggressiveness on their native hosts compared to cross-inoculated plants. Interestingly, on the excised root tissues cross-pathogenicity test, the highest cross-infection severity of F. solani HQ123 observed in A. sinensis aligns with previous reports on its strong pathogenic adaptability across diverse hosts (Nie et al., 2020; Zhang et al., 2021). The observed patterns indicate that although Fusarium spp. preferentially infect their native hosts, they exhibit adaptability that allows them to infect other plant species, which may pose challenges for disease management in intercropping systems. The symptomatology observed in stained tissues provided clear indicators for distinguishing host-pathogen interactions, characterized by significant degradation, necrosis, and vascular discoloration in primary hosts aligned with the observed higher aggressiveness of their original Fusarium isolates. In contrast, cross-infections resulted in localized damage and restricted pathogen penetration, suggesting a degree of host resistance, aligning with earlier findings suggesting that increased lignification and diminished pathogen spread represent a common reaction in non-primary hosts (Jian et al., 2024; Olivain et al., 2006). These observations highlight the presence of fungal hyphae and intermediate levels of necrosis in cross-infected plants, further indicating the potential for Fusarium spp. to persist in alternate hosts, facilitating inoculum buildup and disease persistence in diverse cropping systems. These results emphasize the ecological implications of cross-pathogenicity, where even weak infections can serve as reservoirs for inoculum and drive pathogen evolution. The sequencing analysis of fungal and bacterial communities across Fusarium -infected and non-infected rhizosphere and bulk soils in A. sinensis , C. pilosula , and A. mongholicus revealed significant shifts in microbial diversity and community structure. While non-infected rhizospheres exhibited higher raw reads and OTU counts, fungal alpha diversity indices (Shannon, Simpson, Chao1, ACE) showed no significant differences between infected and non-infected rhizospheres, consistent with findings of Solis-Garcia et al. (2021), where pathogen presence did not universally alter alpha diversity but influenced microbial dynamics. Conversely, Zhou et al. (2019) observed higher fungal and bacterial richness and diversity in diseased soils compared to healthy soils. However, a significant reduction was explicitly observed in the bacterial community in F. oxysporum DSH27-infected A. sinensis , suggesting that pathogen presence can induce modifications in the rhizosphere bacterial communities and reduce overall microbial diversity. On the contrary, beta diversity analyses indicated apparent community clustering in Fusarium -infected plants, highlighting pathogen-induced shifts in rhizosphere ecology, particularly pronounced in A. sinensis . These observations align with studies showing that pathogen colonization reshapes rhizosphere microbial communities and their functional potential (Mendes et al., 2011; Séguin et al., 2014). Beta-diversity, reflecting variations across environmental contexts, emerges as a more sensitive indicator of community structure changes compared to alpha-diversity, which may remain stable despite fluctuations in beta-diversity (Turatsinze et al., 2021; Walters and Martiny, 2020). Our findings highlight the importance of beta diversity in capturing the broader ecological impacts of microbial community shifts induced by pathogen activity. Pathogen-driven community restructuring was evident in the increased abundance of fungal phyla like Chytridiomycota in A. sinensis and Rozellomycota in C. pilosula . Pathogenic genera such as Fusarium , Plectosphaerella , and Alternari a, and beneficial taxa, including Mortierella , gained betweenness centrality in A. sinensis infected soils microbial networks compared to other plant species signifying affected roles under Fusarium infection. These plant species-dependent network changes, coupled with the increased inter-community links observed under Fusarium -infected rhizospheres, aligns with the findings by (Mendes et al., 2023), who reported cultivar-dependent impaired modularity between under disease-suppressive and Fusarium -infection, resulting in reduced functional compartmentalization, resilience and stability of the rhizosphere microbial network (Tang et al., 2020), which is crucial for plant health and soil ecosystem services. Notably, the rhizosphere microbiota, a complex ecosystem of fungi and bacteria, plays a pivotal role in shaping plant-pathogen interactions and mediating plant health (Berendsen et al., 2012). In this study, Fusarium infection significantly altered the rhizosphere microbial composition and functional dynamics across A. sinensis , C. pilosula , and A. mongholicus , increasing the abundance of pathotrophic fungal genera such as Fusarium and Plectosphaerella , particularly in F. solani -infected A. sinensis . These shifts were positively associated with an increase in disease severity, which is consistent with previous studies linking pathogen-induced perturbations in rhizosphere communities to disease development (Mendes et al., 2013). Fusarium infection led to a decline in beneficial symbiotrophic and saprotrophic fungi, notably arbuscular mycorrhizal fungi (AMF). Under F. solani infection, A. sinensis showed significant decreases. The decreased abundance of AMF under pathogen stress emphasizes its crucial role in nutrient uptake and disease suppression (Spagnoletti et al., 2021; Xiong et al., 2017). In this study, root rot was aggravated by a functional imbalance that promoted pathogen multiplication, as demonstrated by decreased AMF functional profiles and increased pathotrophic dominance. These findings are consistent with studies indicating competition with pathogenic fungi (Compant et al., 2005), shifts in root exudates (Jin et al., 2024), and toxins accumulation (Deveau et al., 2018) as potential drivers of microbial community shifts. Under Fusarium infection, bacterial communities underwent considerable alterations, including a decline in the abundance of beneficial taxa such as RB41 and Vicinamibacteraceae , These species, which are favorably associated with soil health indicators like total phosphorus (TP) and nitrogen (TN) but negatively correlated with disease severity, are expected to help with pathogen suppression. Similar to Lee et al. (2021), the disruption of bacterial phyla such as Actinobacteria and Verrucomicrobiota emphasizes the disruptive impact of Fusarium species infection on microbial networks that are critical for rhizosphere resilience. Intriguingly, Fusarium infection significantly altered the microbial networks within the rhizosphere, leading to an increase in the centrality and abundance of pathogenic genera such as Fusarium, Alternaria, and Plectosphaerella while concurrently reducing the populations of beneficial taxa such as Trichoderma and arbuscular mycorrhizal fungi (AMF). In A. sinensis infected with F. solani (HQ123), AMF populations exhibited a notable decrease, highlighting the capacity of Fusarium species to interfere with vital symbiotic and saprotrophic functions that are essential for plant resilience. The observed disruptions coincide with the findings of Fusarium -induced imbalances in microbial communities within the rhizosphere (Kudjordjie et al., 2022) and the pathotrophic dominance identified in diseased soils (Byers et al., 2020). These results indicate a restructuring within the soil ecosystem that promotes the prevalence of pathogens, simultaneously diminishing microbial diversity and functional stability. Consistent with the findings of Liu et al. (2024), these changes suggest a shift from symbiotrophy and saprotrophy to pathotrophy, adversely impacting nutrient cycling and the capacity of plants to withstand stress. Centrality shifts suggest that beneficial taxa, even with their negative correlation to pathogens, may assume compensatory roles, as evidenced by Trichoderma and Penicillium. Moreover, changes in KEGG pathways underscore their impact on metabolism, transcription, and immune responses, reinforcing the conclusions of Wang et al. (2024) about the influence of microbial interactions on ecosystem functions. These results emphasize the significant role of Fusarium spp. in reshaping microbial networks, with critical implications for plant health and the functioning of the rhizosphere ecosystem. Thus highlighting the importance of effective management of fungal pathogens to maintain the rhizosphere resilience and stability. The association between microbial community dynamics and soil physicochemical properties in the context of Fusarium infection is multifaceted, impacting both root rot disease severity and the overall health of rhizosphere ecosystems. In this study, Fusarium infections disrupted the equilibrium of soil properties in A. sinensis , leading to significant increases in total carbon (TC) and available phosphorus (AVP) levels. This elevation in AVP may indicate pathogen-induced organic phosphorus mineralization, which tends to suppress phosphorus-immobilizing microbes as seen in soil systems affected by pathogen stress, supporting findings in specific Fusarium studies (Yan et al., 2023). Additionally, the increased TC levels could be attributed to altered root exudation patterns and the accumulation of metabolites triggered by pathogen interactions, consistent with findings that demonstrate changes in carbon cycling due to Fusarium invasion (Yu et al., 2015; Du et al., 2019). Microbial biomass carbon (MBC), a key indicator of microbial activity and soil health, declined significantly in F. oxysporum -infected C. pilosula soils, suggesting that pathogen invasion may suppress beneficial microbial populations while favoring disease-promoting taxa. This aligns with studies showing that root disease reduces microbial biomass and alters community structures, favoring pathogenic over beneficial microbes (Guo et al., 2024; Ye et al., 2023). The decline in microbial biomass carbon (MBC) and phosphorus (MBP) in F. tricinctum DG105-infected C . pilosula rhizosphere soils suggests a disruption in microbial equilibrium, leading to reduced nutrient cycling and microbial diversity, which weakens disease suppression and soil quality (Tian et al., 2021; Xiong et al., 2017; Guo et al., 2023). In contrast, the increase in microbial biomass nitrogen (MBN) may indicate a shift in microbial composition, where nitrogen-retaining microbes persist despite pathogen stress, potentially due to altered root exudation patterns or microbial competition dynamics (Zhao et al., 2018; Zhou et al., 2019). These shifts highlight the complex interactions between Fusarium infection and microbial resilience, emphasizing the cascading effects of pathogen-induced stress on soil health and nutrient dynamics (Tang et al., 2023). The imbalance suggested by these microbial biomass shifts indicates that while Fusarium infection disrupts carbon and phosphorus cycling, it may inadvertently create conditions favoring nitrogen-retaining microbes. Conversely, the healthy rhizospheres in C. pilosula and A. sinensis showcased greater total nitrogen (TN) and soil organic matter (SOM) concentrations, reinforcing research that correlates pathogen activity with diminutions in nitrogen-fixing and SOM-enhancing microbes (Lilai et al., 2021). The observations from A. mongholicus indicated a complex response post-Fusarium infection, where TN and SOM levels increased, likely driven by root exudates that enhance microbial turnover, paralleling findings that highlight the role of microbial dynamics in nutrient cycling (Zhang et al., 2017). Notably, reduced levels of trace elements such as iron (Fe) and manganese (Mn) are critical for plant defense mechanisms and were observed in the infected rhizospheres of C. pilosula and A. mongholicus , aligning with studies that link pathogen action to the modification of nutrient availability through microbial interactions (Zhong et al., 2024). The relationship between potassium (K) levels and disease severity observed in A. mongholicus further reflects the nuanced role of soil nutrients, where potassium can exhibit both protective and detrimental qualities (Xiao et al., 2016). Moreover, the positive correlations detected between soil pH and disease severity in F. tricinctum DG105-infected C. pilosula underscore the influence of soil chemistry on pathogen dynamics, where alkaline conditions might reduce micronutrient solubility, thus potentially compromising plant immunological responses against pathogens (Calvo et al., 2022). Collectively, these findings elucidate the intricate interplays among soil properties, microbial communities, and root rot disease progression, suggesting that maintaining soil health is paramount in mitigating the adversities posed by pathogenic agents like Fusarium species. Overall, our study identified F. tricinctum as the primary pathogen affecting A. sinensis , F. oxysporum in C. pilosula , and F. solani in A. mongholicus . Each of the three Fusarium pathogens demonstrated successful cross-infection and pathogenicity, contributing to the onset of root rots and wilts across these medicinal herbs with varied levels of aggressiveness. The observed differences in disease severity, where A. sinensis and C. pilosula exhibited the highest susceptibility and A. mongholicus the lowest, suggest that plant-specific physiological traits, such as differential lignification, root architecture, root exudate composition, and immune response efficiency, play a crucial role in determining resistance levels against Fusarium spp. infection. The finer, moisture-retaining roots of A. sinensis and C. pilosula may facilitate pathogen colonization, whereas the thicker, more lignified taproots of A. mongholicus likely provide a structural barrier to infection (Bai et al., 2022; Liao et al., 2019). Changes in microbial networks within the rhizosphere caused by Fusarium infection were characterized by an increase in pathotrophic fungal activities and a disruption of symbiotic fungi like AMF, which are crucial for nutrient cycling and disease management. The findings underscore the complex characteristics of Fusarium cross-pathogenicity, which involves not only the direct interactions between hosts and pathogens but also significant impacts from rhizosphere dynamics and environmental factors (Li et al., 2021; Mendes et al., 2013; Solis-Garcia et al., 2021). Notably, rhizosphere microbial community shifts, particularly reductions in arbuscular mycorrhizal fungi (AMF) abundance, were negatively correlated with Fusarium infection, highlighting AMF's critical role in disease suppression and rhizosphere stability. These changes align with shifts in soil physicochemical properties, such as elevated TC and AVP in infected soils, which likely result from pathogen activity and altered root exudation. The interplay between reduced trace elements like Fe and Mn and increased TK and pH highlights the multifaceted impacts of Fusarium infection on plant defense mechanisms. These findings underscore the importance of AMF-based strategies and integrated soil management practices in sustaining rhizosphere resilience and reducing Fusarium -induced disease progression. However, despite these insights, root exudates are pivotal in shaping rhizosphere microbial communities and influencing pathogen behavior (Bertin et al., 2003; Dhungana et al., 2023), yet their compositional and functional variability across plant species and environmental conditions remains underexplored. Our study leaves open questions regarding the role of root exudates in Fusarium infection dynamics and cross-pathogenicity. Future research should explore root exudate profiles to unravel their role in shaping microbial interactions and pathogen behavior, providing insights into effective disease management strategies in medicinal and agricultural systems. 5. Conclusions Our cross-inoculation and pathogenicity evaluations confirmed the ability of root-recovered Fusarium species to cause root rot among rotational medicinal herbs and influence soil microbiome structure and function in relation to disease severity. Specifically, F. oxysporum , F. solani , and F. tricinctum exhibited varying levels of host-specific aggressiveness and cross-pathogenicity in A. sinensis , C. pilosula , and A. mongholicus . These infections increased root rot severity and disrupted soil microbial balance, reducing beneficial symbiotrophic microbes, such as arbuscular mycorrhizal fungi (AMF), while favoring pathotrophic fungi, indicating the importance of beneficial microbes, particularly AMF, in mitigating Fusarium -induced root rot. Furthermore, key soil properties, including total nitrogen, organic matter, total carbon, available phosphorus, and essential nutrients (iron, zinc, and manganese), were linked to disease incidence and severity, underscoring their role in pathogen-host interactions. Our findings demonstrated that crop rotation alone is insufficient for managing pathogenic Fusarium spp., necessitating complementary strategies to prevent pathogen spread via infected seedlings and promote beneficial microbes like AMF. For growers, integrating AMF-based biocontrol approaches to optimize soil nutrient management is a crucial step. Given the potential impact of Fusarium spp. on regional crops such as potatoes and maize, adopting integrated soil microbiome management practices is essential for sustainable agricultural productivity. Declarations Authorship contribution statement ANT: Investigation, Conceptualization, Methodology, Data curation, Visualization, Validation, Formal analysis, Writing original draft, Writing, review & editing. AY : Methodology, Data curation, Investigation, Visualization. XX: Investigation, Visualization, Formal analysis. GC: Conceptualization, Investigation, Methodology, Visualization. YW: Investigation, Conceptualization, Visualization, Formal analysis. LY: Investigation, Methodology, Visualization. QZ: Investigation, Methodology, Visualization. LW: Visualization, Formal analysis. MZ: Investigation, Visualization. ZZ: Methodology, Data curation, Visualization, Formal analysis. JZ: Methodology, Data curation, Visualization. YS: Investigation, Visualization. YZ: Visualization, Validation. RW: Conceptualization, Methodology, Validation, Formal analysis, Resources, Supervision, Writing – Review & editing, Funding acquisition. Declaration of competing interests The authors have confirmed that there are no financial or personal interests to be declared. Funding This work was supported by the Project of the International Partnership Program of the Chinese Academy of Sciences (grant number 315GJHZ2024123GC), Key Research and Development Projects of Ningxia Hui Autonomous Region (grant number 2022BBF02031), and the Science and Technology Planning Project of Gansu Province (grant number 23JRRA575, 25JRRA524). Data availability Data will be made available on request. References Adamberg K, Tomson K, Talve T, Pudova K, Puurand M, Visnapuu T, Alamäe T, Adamberg S (2015) Levan enhances associated growth of Bacteroides, Escherichia, Streptococcus and Faecalibacterium in fecal microbiota. 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Toxins 9:100. https://doi.org/10.3390/toxins9030100 Zhou Q, Wang Y, Yue L, Ye A, Xie X, Zhang M, Tian Y, Liu Y, Turatsinze AN, Constantine U, Zhao X, Zhang Y, Wang R (2024) Impacts of continuous cropping on the rhizospheric and endospheric microbial communities and root exudates of Astragalus mongholicus. BMC Plant Biol 24:340. https://doi.org/10.1186/s12870-024-05024-5 Zhu F, Fang Y, Wang Z, Wang P, Yang K, Xiao L, Wang R (2022) Salicylic acid remodeling of the rhizosphere microbiome induces watermelon root resistance against Fusarium oxysporum f. sp. niveum infection. Front Microbiol 13. https://doi.org/10.3389/fmicb.2022.1015038 Supplementary Files Fig.S1.tif Fig. S1 Root rot symptoms in excised plant tissues inoculated with Fusarium isolates. Representative symptoms of root rot in excised plant root tissues of A. sinensis (a), C. pilosula (b), and A. mongholicus (c) inoculated with Fusarium isolates. Panels (i) illustrate control (non-inoculated) tissues. (ii) represent tissues inoculated with F. oxysporum DSH27.(iii) and (iv) shows symptoms from inoculations with F. solani and F. tricinctum , respectively. Letters show statistical significance where different letters indicate significant differences. Disease incidence and severity scores are demonstrated in (d), and table (e) presents the analysis of disease severity mean ranks ( ) of each Fusarium isolate tested and their relative treatment ( ). Fig.S2.tif Fig. S2 Toluidine blue staining showing Fusarium infection and colonization within root tissues of A. sinensis (a), C. pilosula (b), and A. mongolicus (c). CK panels display cross-sections of healthy control roots, while other panels depict roots infected by F. solani (HQ123), F. tricinctum (DG105), and F. oxysporum (DSH27), highlighting the epidermis (ep), cortical region (co), hypodermis (hy), and vascular tissue (va). (d) Magnified red-boxed areas in A. sinensis (DG105), A. mongolicus (HQ123), and C. pilosula (DSH27), respectively. The magnification highlights peripheral cells infected by the pathogen, characterized by intense staining and showing fungal mycelium and hyphal penetration of intercellular spaces and colonization of the cell wall. Red arrows indicate mycelium penetration, destructed cells and plasmolysis. Fig.S3.tiff Fig. S3Relative abundance of the top 10 bacterial phyla (a-e) and 10 bacterial genera (b-f) in rhizosphere soil of A. sinensis (a-b), C. pilosula , and (c-d) A. mongholicus (e-f), under different Fusarium species cross-infection treatments. The fungal treatments include F. tricinctum isolate DG105, F. oxysporum isolate DSH27, and F. solani isolate HQ123. CK represents water control, and BF represents bulk soil. Significance tests were conducted to measure differences between the water control (CK) and the Fusarium inoculated treatment. Groups marked *, **, and *** indicate significant differences at p <.05, <.01, and <.001, respectively, compared to the corresponding fungal taxa. Fig.S4.tif Fig. S4Differential analysis of KEGG metabolic pathways at the second level, illustrating rhizosphere soil bacterial community functions in (A ) A. sinensis , (B) C. pilosula , and (C) A. mongholicus under different Fusarium species inoculated treatments. Sub-figures compare the control treatment (CK) to the corresponding Fusarium -infected treatments. Different colors represent different sample groups inoculated with Fusarium species: F. oxysporum isolate DSH27, F. solani isolate HQ123, and F. tricinctum isolate DG105. CK denotes water control treatments. Each sub-figure displays the abundance ratio of different functions (Left), the difference ratio of function abundance within a 95% confidence interval (Middle), and the p-values (Right). FigS5.tif Fig. S5Principal component analysis (PCA) plots depict the distribution relationships between keystone bacterial genera, soil physicochemical properties and disease incidence (DI) and severity (DS) across rhizospheres of healthy controls and samples infected by F. oxysporum (DSH27), F. solani (HQ123), and F. tricinctum (DG105) for A. sinensis (a), C. pilosula (b), and A. mongholicus (c). Soil properties include pH, soil organic matter (SOM), total carbon (TC), total nitrogen (TN), total potassium (TK), total phosphorus (TP), available phosphorus (AVP), moisture content (MC), microbial biomass carbon (MBC), microbial biomass phosphorus (MBP), and trace elements (Zn, Fe, Mn, and Ca). Color-coded points represent samples from infected rhizosphere soils (DSH27, HQ123, and DG105), and the water control (CK). ManuscriptMainTextWithTrackChanges.docx TableS1.docx Table S1 Fungal and bacterial community α-diversity indices across three medicinal herb species ( A. sinensis , C. pilosula , and A. mongholicus under different Fusarium spp. inoculation treatments. TableS2.docx Table S2Nonparametric multivariate statistical analysis of the impact of Fusarium inoculants on soil physicochemical properties across different medicinal herb species ( A. sinensis , C. pilosula and A. mongholicus ). TableS3.docx Table S3Soil physicochemical properties under healthy and Fusarium-inoculated treatments across the three medicinal herbs evaluated. Cite Share Download PDF Status: Published Journal Publication published 08 May, 2025 Read the published version in Plant and Soil → Version 1 posted Editorial decision: Accept 23 Apr, 2025 Reviewers agreed at journal 02 Apr, 2025 Reviewers invited by journal 02 Apr, 2025 Editor assigned by journal 27 Mar, 2025 First submitted to journal 26 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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Niejiashan) within Weiyuan County, and the experimental site (Longxi), (\u003cstrong\u003ec\u003c/strong\u003e) Comparative images of healthy and diseased plants: (\u003cstrong\u003ei–iii\u003c/strong\u003e) Healthy and (\u003cstrong\u003eiv–vi\u003c/strong\u003e) diseased \u003cem\u003eA. sinensis\u003c/em\u003e cultivated in fields previously used for \u003cem\u003eA. mongholicus\u003c/em\u003e; (\u003cstrong\u003evii–ix\u003c/strong\u003e) Healthy and (\u003cstrong\u003ex–xii\u003c/strong\u003e) diseased \u003cem\u003eC. pilosula\u003c/em\u003e from fields previously used for \u003cem\u003eA. mongholicus\u003c/em\u003e; (\u003cstrong\u003exiii–xv\u003c/strong\u003e) Healthy and (\u003cstrong\u003exv–xvii\u003c/strong\u003e) diseased \u003cem\u003eA. mongholicus\u003c/em\u003e from fields previously used for \u003cem\u003eA. sinensis\u003c/em\u003e. Infected plants exhibit symptoms such as leaf yellowing, wilting, necrosis, and plant death, with roots displaying brown to black internal lesions.\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/f133181d30e5c6f553939b63.png"},{"id":79848943,"identity":"0af4b2e5-a6eb-4362-a63d-4e294e1c64d3","added_by":"auto","created_at":"2025-04-03 14:19:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3195731,"visible":true,"origin":"","legend":"\u003cp\u003eMorphological characterization and identification of three \u003cem\u003eFusarium\u003c/em\u003e strains (\u003cstrong\u003eDSH27\u003c/strong\u003e, \u003cstrong\u003eHQ123\u003c/strong\u003e, and \u003cstrong\u003eDG105\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eused in cross-pathogenicity tests and maximum likelihood phylogenetic analysis of 48 \u003cem\u003eFusarium\u003c/em\u003e isolates from three plant species in this study. (\u003cstrong\u003eA\u003c/strong\u003e, \u003cstrong\u003eJ\u003c/strong\u003e,\u003cstrong\u003e \u003c/strong\u003eand\u003cstrong\u003e R\u003c/strong\u003e) Top and (\u003cstrong\u003eB\u003c/strong\u003e,\u003cstrong\u003e K\u003c/strong\u003e, and \u003cstrong\u003eS\u003c/strong\u003e) bottom views colony morphology at 10 days post-culturing on PDA. (\u003cstrong\u003eC\u003c/strong\u003e, \u003cstrong\u003eD\u003c/strong\u003e, \u003cstrong\u003eL\u003c/strong\u003e, \u003cstrong\u003eT\u003c/strong\u003e, and \u003cstrong\u003eU\u003c/strong\u003e) Macroconidia, (\u003cstrong\u003eE\u003c/strong\u003e, \u003cstrong\u003eF\u003c/strong\u003e, \u003cstrong\u003eM\u003c/strong\u003e, \u003cstrong\u003eN\u003c/strong\u003e, \u003cstrong\u003eV\u003c/strong\u003e, and \u003cstrong\u003eW\u003c/strong\u003e) microconidia, and (\u003cstrong\u003eG\u003c/strong\u003e, \u003cstrong\u003eH\u003c/strong\u003e, \u003cstrong\u003eI\u003c/strong\u003e, \u003cstrong\u003eO\u003c/strong\u003e, \u003cstrong\u003eP\u003c/strong\u003e, \u003cstrong\u003eQ\u003c/strong\u003e, and \u003cstrong\u003eX\u003c/strong\u003e) in situ microconidia cultured in carboxymethylcellulose (CMC) broth for five days. (\u003cstrong\u003eY\u003c/strong\u003e) The phylogenetic tree was constructed using concatenated ITS and \u003cem\u003eTEF1-α\u003c/em\u003e sequences from their best-matching references in the NCBI GenBank database. Sequences were aligned and analyzed with MEGA 7 software, and the phylogeny was tested using the bootstrap method (1,000 replications), with bootstrap values (%) shown at branch nodes. \u003cem\u003eFusarium\u003c/em\u003eisolates from \u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003eare highlighted in orange, blue, and purple, respectively. The analysis of phylogeny revealed three main clades corresponding to the \u003cem\u003eF. oxysporum\u003c/em\u003especies complex (\u003cstrong\u003eFOSC\u003c/strong\u003e), \u003cem\u003eF. solani\u003c/em\u003e species complex (\u003cstrong\u003eFSSC\u003c/strong\u003e), and \u003cem\u003eF. tricinctum\u003c/em\u003e species complex (\u003cstrong\u003eFTSC\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/34eadc23839b1b9663e83a60.png"},{"id":79848949,"identity":"b9237b27-cfd5-4765-9123-15bb08aba3ee","added_by":"auto","created_at":"2025-04-03 14:19:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3551473,"visible":true,"origin":"","legend":"\u003cp\u003eCharacteristic symptoms of above-ground and below-ground parts of \u003cem\u003eA. sinensis\u003c/em\u003e\u003cstrong\u003e (a-b), \u003c/strong\u003e\u003cem\u003eC. pilosula \u003c/em\u003e\u003cstrong\u003e(c-d)\u003c/strong\u003e, and \u003cem\u003eA. mongholicus \u003c/em\u003e\u003cstrong\u003e(e-f)\u003c/strong\u003e, before and after pathogen cross-inoculations. Panels \u003cstrong\u003eA\u003c/strong\u003e to \u003cstrong\u003eP \u003c/strong\u003edisplay above-ground parts before inoculation (\u003cstrong\u003eA-M\u003c/strong\u003e) and at 3 weeks (\u003cstrong\u003eB-N\u003c/strong\u003e), 6 weeks (\u003cstrong\u003eC-O\u003c/strong\u003e), and 9 weeks (\u003cstrong\u003eD-P\u003c/strong\u003e) post-inoculation with \u003cem\u003eF. oxysporum \u003c/em\u003eisolate DSH27 (\u003cstrong\u003eE-H\u003c/strong\u003e), \u003cem\u003eF. solani \u003c/em\u003eisolate HQ123 (\u003cstrong\u003eI to L\u003c/strong\u003e),\u003cem\u003e F. tricinctum \u003c/em\u003eisolate DG105 (\u003cstrong\u003eM to P\u003c/strong\u003e), and water control (\u003cstrong\u003eA to D\u003c/strong\u003e). Roman numerals (\u003cstrong\u003ei to iv\u003c/strong\u003e), illustrate belowground cross-sections at harvest (9 weeks post-inoculation) with \u003cem\u003eF. oxysporum \u003c/em\u003eisolate DSH27 (\u003cstrong\u003eii\u003c/strong\u003e), \u003cem\u003eF. solani \u003c/em\u003eisolate (\u003cstrong\u003eiii\u003c/strong\u003e),\u003cem\u003e F. tricinctum \u003c/em\u003eisolate DG105 (\u003cstrong\u003eiv\u003c/strong\u003e), and water control (\u003cstrong\u003ei\u003c/strong\u003e) for \u003cem\u003eA. sinensis\u003c/em\u003e\u003cstrong\u003e (g-h), \u003c/strong\u003e\u003cem\u003eC. pilosula \u003c/em\u003e\u003cstrong\u003e(i-j)\u003c/strong\u003e, and \u003cem\u003eA. mongholicus \u003c/em\u003e\u003cstrong\u003e(k-l)\u003c/strong\u003e. The cross-section observation showed root rot disease symptoms across the cross-inoculated plants with varying levels (\u003cstrong\u003e1 \u003c/strong\u003eto \u003cstrong\u003e5\u003c/strong\u003e) of severity.\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/b4ac3f5b767b3ca900df3d1d.png"},{"id":79850312,"identity":"451f8805-5297-4852-9326-f865d90c08ec","added_by":"auto","created_at":"2025-04-03 14:27:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":12008908,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eCross-sections of root tissues from \u003cem\u003eA. sinensis\u003c/em\u003e(\u003cstrong\u003ea\u003c/strong\u003e), \u003cem\u003eC. pilosula\u003c/em\u003e (\u003cstrong\u003eb\u003c/strong\u003e), and \u003cem\u003eA. mongolicus\u003c/em\u003e (\u003cstrong\u003ec\u003c/strong\u003e), stained with safranin and fast green after paraffin sectioning. \u003cstrong\u003eCK \u003c/strong\u003epanels represent cross-sections of healthy control roots, while other panels show roots infected by \u003cem\u003eF. solani\u003c/em\u003e (\u003cstrong\u003eHQ123\u003c/strong\u003e), \u003cem\u003eF. tricinctum\u003c/em\u003e (\u003cstrong\u003eDG105\u003c/strong\u003e), and \u003cem\u003eF. oxysporum\u003c/em\u003e (\u003cstrong\u003eDSH27\u003c/strong\u003e), showing the epidermis (\u003cstrong\u003eep\u003c/strong\u003e), cortical region (\u003cstrong\u003eco\u003c/strong\u003e), hypodermis (\u003cstrong\u003ehy\u003c/strong\u003e), and vascular tissue (\u003cstrong\u003eva\u003c/strong\u003e). (\u003cstrong\u003ed\u003c/strong\u003e) Magnified red-boxed areas in \u003cem\u003eA\u003c/em\u003e. \u003cem\u003esinensis\u003c/em\u003e (\u003cstrong\u003eDG105\u003c/strong\u003e), \u003cem\u003eA. mongolicus\u003c/em\u003e (\u003cstrong\u003eHQ123\u003c/strong\u003e), and \u003cem\u003eC\u003c/em\u003e. \u003cem\u003epilosula\u003c/em\u003e (\u003cstrong\u003eDSH27\u003c/strong\u003e), respectively. Red arrows illustrate severe root cell damage, characterized by extensive tissue degradation, intense staining, and widespread structural destruction and vascular occlusion.\u003c/p\u003e","description":"","filename":"Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/62ff1bd5ff1dcd8f60d519ea.png"},{"id":79848954,"identity":"e8165523-a0b8-42d3-ad18-4fa536187938","added_by":"auto","created_at":"2025-04-03 14:19:15","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":469846,"visible":true,"origin":"","legend":"\u003cp\u003eDisease incidence and severity indices for aboveground (\u003cstrong\u003ea\u003c/strong\u003e) and belowground (\u003cstrong\u003eb\u003c/strong\u003e) symptoms were recorded on three medicinal plants (\u003cem\u003eA\u003c/em\u003e. \u003cem\u003esinensis\u003c/em\u003e, \u003cem\u003eC\u003c/em\u003e. \u003cem\u003epilosula\u003c/em\u003e, and \u003cem\u003eA\u003c/em\u003e. \u003cem\u003emongholicus \u003c/em\u003efollowing cross-inoculations with \u003cem\u003eF\u003c/em\u003e. \u003cem\u003etricinctum \u003c/em\u003e\u003cstrong\u003eDG105\u003c/strong\u003e (isolated from \u003cem\u003eA\u003c/em\u003e. \u003cem\u003esinensis\u003c/em\u003e), \u003cem\u003eF\u003c/em\u003e. \u003cem\u003eoxysporum \u003c/em\u003e\u003cstrong\u003eDSH-27\u003c/strong\u003e (isolated from \u003cem\u003eC\u003c/em\u003e. \u003cem\u003epilosula\u003c/em\u003e), and \u003cem\u003eF\u003c/em\u003e. \u003cem\u003esolani\u003c/em\u003e \u003cstrong\u003eHQ123\u003c/strong\u003e (isolated from \u003cem\u003eA\u003c/em\u003e. \u003cem\u003emongholicus\u003c/em\u003e), and a water control (\u003cstrong\u003eCK\u003c/strong\u003e) at 3-, 6-, and 9-weeks post-inoculation. Error bars represent the standard error of the mean. According to Tukey’s HSD test, treatments marked with the same lowercase letters do not differ significantly at p˂0.05.\u003c/p\u003e","description":"","filename":"Fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/cc6483c119b85f5aa35144b3.png"},{"id":79848965,"identity":"16cac58a-6f9b-4057-adac-90e681a8ce02","added_by":"auto","created_at":"2025-04-03 14:19:16","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1692361,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of unique and shared operational taxonomic units (OTUs) and Shannon index microbial α-diversity in rhizosphere soils of \u003cem\u003eA. sinensis\u003c/em\u003e (\u003cstrong\u003ea-d\u003c/strong\u003e), \u003cem\u003eC. pilosula \u003c/em\u003e(\u003cstrong\u003ee-h\u003c/strong\u003e), and \u003cem\u003eA. mongholicus\u003c/em\u003e (\u003cstrong\u003ei-l\u003c/strong\u003e) under different Fusarium inoculation treatments. Venn diagrams illustrate shared and unique fungal (\u003cstrong\u003ea-i\u003c/strong\u003e) and bacterial (\u003cstrong\u003eb-j\u003c/strong\u003e) OTUs across three \u003cem\u003eFusarium\u003c/em\u003e-infected groups, bulk soil (\u003cstrong\u003eBF\u003c/strong\u003e), and non-infected controls (\u003cstrong\u003eCK\u003c/strong\u003e). The Shannon index analysis illustrates microbial α-diversity differences for fungi (\u003cstrong\u003ec-k\u003c/strong\u003e) and bacteria (\u003cstrong\u003ed-l\u003c/strong\u003e) in rhizosphere soils treated with \u003cem\u003eF. tricinctum\u003c/em\u003e (\u003cstrong\u003eDG105\u003c/strong\u003e), \u003cem\u003eF. oxysporum\u003c/em\u003e (\u003cstrong\u003eDSH27\u003c/strong\u003e), and \u003cem\u003eF. solani\u003c/em\u003e (\u003cstrong\u003eHQ123\u003c/strong\u003e), with statistical significance denoted by \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 (\u003cstrong\u003e*\u003c/strong\u003e) and \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01 (\u003cstrong\u003e**\u003c/strong\u003e).\"Statistical significance is denoted by \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 (\u003cstrong\u003e*\u003c/strong\u003e) and \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01 (\u003cstrong\u003e**\u003c/strong\u003e).\u003c/p\u003e","description":"","filename":"Fig.6.png","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/8a9ad5e0be4f679eb12c3691.png"},{"id":79848947,"identity":"649911c2-d173-4508-958c-05bcb649cb5e","added_by":"auto","created_at":"2025-04-03 14:19:15","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":388087,"visible":true,"origin":"","legend":"\u003cp\u003ePartial Least Squares Discriminant Analysis (PLS-DA) plots illustrating fungal \u003cstrong\u003e(a-c) \u003c/strong\u003eand bacterial \u003cstrong\u003e(d-f) \u003c/strong\u003ebeta diversities in the rhizosphere soil of \u003cem\u003eAngelica sinensis \u003c/em\u003e\u003cstrong\u003e(a-d) \u003c/strong\u003e\u003cem\u003eCodonopsis pilosula \u003c/em\u003eand \u003cstrong\u003e(b-e) \u003c/strong\u003e\u003cem\u003eAstragalus mongholicus \u003c/em\u003e\u003cstrong\u003e(c-f)\u003c/strong\u003e, treated with different pathogenic Fungi: \u003cem\u003eFusarium tricinctum \u003c/em\u003eisolate \u003cstrong\u003eDG105\u003c/strong\u003e, \u003cem\u003eFusarium oxysporum \u003c/em\u003eisolate\u003cem\u003e \u003c/em\u003e\u003cstrong\u003eDSH27\u003c/strong\u003e,\u003cstrong\u003e \u003c/strong\u003eand \u003cem\u003eFusarium solani \u003c/em\u003eisolate \u003cstrong\u003eHQ123. CK \u003c/strong\u003eand\u003cstrong\u003e BF \u003c/strong\u003erepresent the control and bulk soil, respectively.\u003c/p\u003e","description":"","filename":"Fig.7.png","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/6cea1687a8328e4ef442fc03.png"},{"id":79848959,"identity":"ec22d37c-7684-46ce-b92b-71d0e7a5af83","added_by":"auto","created_at":"2025-04-03 14:19:16","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":930280,"visible":true,"origin":"","legend":"\u003cp\u003eRelative abundance of the top 10 fungal phyla \u003cstrong\u003e(a-e) \u003c/strong\u003eand 10 fungal genera \u003cstrong\u003e(b-f) \u003c/strong\u003ein rhizosphere soil of \u003cem\u003eA. sinensis \u003c/em\u003e\u003cstrong\u003e(a-b) \u003c/strong\u003e\u003cem\u003eC. pilosula \u003c/em\u003eand \u003cstrong\u003e(c-d) \u003c/strong\u003e\u003cem\u003eA. mongholicus \u003c/em\u003e\u003cstrong\u003e(e-f)\u003c/strong\u003e, under different \u003cem\u003eFusarium\u003c/em\u003e species cross-infection treatments. The fungal treatments include \u003cem\u003eF. tricinctum \u003c/em\u003eisolate \u003cstrong\u003eDG105\u003c/strong\u003e, \u003cem\u003eF. oxysporum \u003c/em\u003eisolate\u003cem\u003e \u003c/em\u003e\u003cstrong\u003eDSH27\u003c/strong\u003e,\u003cstrong\u003e \u003c/strong\u003eand \u003cem\u003eF. solani \u003c/em\u003eisolate \u003cstrong\u003eHQ123. CK \u003c/strong\u003erepresents water control, and \u003cstrong\u003eBF\u003c/strong\u003e represents bulk. Samples t-tests comparison were conducted to measure differences between the non-infected water control (\u003cstrong\u003eCK\u003c/strong\u003e) and the \u003cem\u003eFusarium\u003c/em\u003e-infected treatments. Groups marked *, **, and *** indicate significant differences at \u003cem\u003ep\u003c/em\u003e \u0026lt;.05, \u0026lt;.01, and \u0026lt;.001, respectively, compared to the corresponding fungal taxa.\u003c/p\u003e","description":"","filename":"Fig.8.png","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/5efa794467655ebd19c2bcc3.png"},{"id":79850315,"identity":"42b625b7-cc36-4642-98d5-bae438b99c2a","added_by":"auto","created_at":"2025-04-03 14:27:16","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":2785737,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of rhizosphere soil fungal community functions in \u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003eunder different \u003cem\u003eFusarium\u003c/em\u003e species inoculated treatments. Stacked bar charts illustrate the trophic functional taxonomic composition differences among \u003cem\u003eA. sinensis\u003c/em\u003e (\u003cstrong\u003ea\u003c/strong\u003e), \u003cem\u003eC. pilosula\u003c/em\u003e (\u003cstrong\u003eb\u003c/strong\u003e) and \u003cem\u003eA. mongholicus\u003c/em\u003e (\u003cstrong\u003ec\u003c/strong\u003e), inoculated with different \u003cem\u003eFusarium\u003c/em\u003e spp., including \u003cem\u003eF. oxysporum\u003c/em\u003e isolate \u003cstrong\u003eDSH27\u003c/strong\u003e, \u003cem\u003eF. solani\u003c/em\u003e isolate \u003cstrong\u003eHQ123\u003c/strong\u003e, and \u003cem\u003eF. tricinctum\u003c/em\u003e isolate \u003cstrong\u003eDG105\u003c/strong\u003e. CK and BF represent water control and bulk soil, respectively. (\u003cstrong\u003ed\u003c/strong\u003e) Treatment differences in arbuscular mycorrhizal function after filtering the relative abundance of Guild mode \"Arbuscular mycorrhizal\". Error bar plots compare water controls, and \u003cem\u003eFusarium\u003c/em\u003e inoculated treatments, illustrating FUNGuild differential analysis based on microbial guilds in functional categories with their corrected significance p-values at 95%confidence intervals (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"Fig.9.png","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/c46e6d65129ae76354fc506e.png"},{"id":79848981,"identity":"d1694402-6a67-42d6-a36f-7178e0bdfd84","added_by":"auto","created_at":"2025-04-03 14:19:16","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":5765749,"visible":true,"origin":"","legend":"\u003cp\u003eNetwork analysis for the top 30 abundant fungal genera in the rhizosphere of \u003cem\u003eA. sinensis \u003c/em\u003e(\u003cstrong\u003ea-d\u003c/strong\u003e), \u003cem\u003eC. pilosula \u003c/em\u003e(\u003cstrong\u003ee-h\u003c/strong\u003e), and \u003cem\u003eA. mongholicus \u003c/em\u003e(\u003cstrong\u003ei-l\u003c/strong\u003e), comparing non-infected healthy controls (\u003cstrong\u003eCK\u003c/strong\u003e) with soils inoculated with \u003cem\u003eF. oxysporum \u003c/em\u003e(\u003cstrong\u003eDSH27\u003c/strong\u003e), \u003cem\u003eF. solani \u003c/em\u003e(\u003cstrong\u003eHQ123\u003c/strong\u003e), and \u003cem\u003eF. tricinctum \u003c/em\u003e(\u003cstrong\u003eDG105\u003c/strong\u003e). Nodes, labeled at the genus level and colored by modularity class, indicate taxa, with size representing connectivity degree. Edges represent correlations (positive: blue; negative: red), and thickness reflects correlation strength. Principal component analysis (PCA) plots depict the distribution and clustering of the keystone fungal communities in relation to soil parameters (pH, SOM, TC, TN, TK, TP, AVP, MC, MBC, MBP, Zn, Fe, Mn, and Ca) and disease incidence (\u003cstrong\u003eDI\u003c/strong\u003e) and severity (\u003cstrong\u003eDS\u003c/strong\u003e) in \u003cem\u003eA. sinensis\u003c/em\u003e (\u003cstrong\u003em\u003c/strong\u003e), \u003cem\u003eC. pilosula\u003c/em\u003e (\u003cstrong\u003en)\u003c/strong\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003e (\u003cstrong\u003eo\u003c/strong\u003e). Color-coded points represent samples from infected rhizosphere soils (DSH27, HQ123, and DG105) and the water control (CK).\u003c/p\u003e","description":"","filename":"Fig.10.png","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/530725ac7984a4f3dc0490c6.png"},{"id":82537640,"identity":"37ffe98d-5812-4220-a500-0164a1bfc1d4","added_by":"auto","created_at":"2025-05-12 16:09:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":34872942,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/f58ce7be-664b-4c0d-9d34-1996f13c54ba.pdf"},{"id":79850307,"identity":"f6267164-c7ba-4db3-823b-a76c78725c45","added_by":"auto","created_at":"2025-04-03 14:27:15","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1177358,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig. S1 \u003c/strong\u003eRoot rot symptoms in excised plant tissues inoculated with \u003cem\u003eFusarium\u003c/em\u003e isolates. Representative symptoms of root rot in excised plant root tissues of \u003cem\u003eA. sinensis\u003c/em\u003e (\u003cstrong\u003ea\u003c/strong\u003e), \u003cem\u003eC. pilosula\u003c/em\u003e (\u003cstrong\u003eb\u003c/strong\u003e), and \u003cem\u003eA. mongholicus\u003c/em\u003e(\u003cstrong\u003ec\u003c/strong\u003e) inoculated with \u003cem\u003eFusarium\u003c/em\u003e isolates. Panels (\u003cstrong\u003ei\u003c/strong\u003e) illustrate control (non-inoculated) tissues. (\u003cstrong\u003eii\u003c/strong\u003e) represent tissues inoculated with \u003cem\u003eF. oxysporum \u003c/em\u003eDSH27.(\u003cstrong\u003eiii\u003c/strong\u003e) and (\u003cstrong\u003eiv\u003c/strong\u003e) shows symptoms from inoculations with \u003cem\u003eF. solani\u003c/em\u003e and \u003cem\u003eF. tricinctum\u003c/em\u003e, respectively. Letters show statistical significance where different letters indicate significant differences. Disease incidence and severity scores are demonstrated in (\u003cstrong\u003ed\u003c/strong\u003e), and table (\u003cstrong\u003ee\u003c/strong\u003e) presents the analysis of disease severity mean ranks ( \u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;) of each Fusarium isolate tested and their relative treatment ( \u0026nbsp;).\u003c/p\u003e","description":"","filename":"Fig.S1.tif","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/4e172914dd0463824978b73e.tif"},{"id":79850655,"identity":"c1744749-b616-4395-8c75-dceb3edc64f8","added_by":"auto","created_at":"2025-04-03 14:35:16","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":2422390,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig. S2\u003c/strong\u003e Toluidine blue staining showing Fusarium infection and colonization within root tissues of \u003cem\u003eA. sinensis\u003c/em\u003e (\u003cstrong\u003ea\u003c/strong\u003e), \u003cem\u003eC. pilosula\u003c/em\u003e (\u003cstrong\u003eb\u003c/strong\u003e), and \u003cem\u003eA. mongolicus\u003c/em\u003e (\u003cstrong\u003ec\u003c/strong\u003e). CK panels display cross-sections of healthy control roots, while other panels depict roots infected by \u003cem\u003eF. solani\u003c/em\u003e (HQ123), \u003cem\u003eF. tricinctum\u003c/em\u003e (DG105), and \u003cem\u003eF. oxysporum\u003c/em\u003e (DSH27), highlighting the epidermis (ep), cortical region (co), hypodermis (hy), and vascular tissue (va). (\u003cstrong\u003ed\u003c/strong\u003e) Magnified red-boxed areas in A. sinensis (DG105), \u003cem\u003eA. mongolicus\u003c/em\u003e (HQ123), and \u003cem\u003eC. pilosula\u003c/em\u003e (DSH27), respectively. The magnification highlights peripheral cells infected by the pathogen, characterized by intense staining and showing fungal mycelium and hyphal penetration of intercellular spaces and colonization of the cell wall. Red arrows indicate mycelium penetration, destructed cells and plasmolysis.\u003c/p\u003e","description":"","filename":"Fig.S2.tif","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/d25ef6d482eb7ba793dae771.tif"},{"id":79849001,"identity":"7e71a432-e04e-4473-895c-7a7c9103e6d0","added_by":"auto","created_at":"2025-04-03 14:19:17","extension":"tiff","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":31670322,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig. S3\u003c/strong\u003eRelative abundance of the top 10 bacterial phyla (\u003cstrong\u003ea-e\u003c/strong\u003e) and 10 bacterial genera (\u003cstrong\u003eb-f\u003c/strong\u003e) in rhizosphere soil of \u003cstrong\u003eA. sinensis \u003c/strong\u003e(\u003cstrong\u003ea-b\u003c/strong\u003e), \u003cem\u003eC. pilosula\u003c/em\u003e, and (\u003cstrong\u003ec-d\u003c/strong\u003e) \u003cem\u003eA. mongholicus\u003c/em\u003e (\u003cstrong\u003ee-f\u003c/strong\u003e), under different \u003cem\u003eFusarium \u003c/em\u003especies cross-infection treatments. The fungal treatments include \u003cem\u003eF. tricinctum\u003c/em\u003e isolate DG105, \u003cem\u003eF. oxysporum\u003c/em\u003eisolate DSH27, and \u003cem\u003eF. solani\u003c/em\u003e isolate HQ123. CK represents water control, and BF represents bulk soil. Significance tests were conducted to measure differences between the water control (CK) and the Fusarium inoculated treatment. Groups marked *, **, and *** indicate significant differences at p \u0026lt;.05, \u0026lt;.01, and \u0026lt;.001, respectively, compared to the corresponding fungal taxa.\u003c/p\u003e","description":"","filename":"Fig.S3.tiff","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/c3f47b1b312482f689b721cd.tiff"},{"id":79850322,"identity":"e3d29ebd-7c40-493b-b3be-c00859169a71","added_by":"auto","created_at":"2025-04-03 14:27:17","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":1100410,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig. S4\u003c/strong\u003eDifferential analysis of KEGG metabolic pathways at the second level, illustrating rhizosphere soil bacterial community functions in (\u003cstrong\u003eA\u003c/strong\u003e\u003cem\u003e) A. sinensis\u003c/em\u003e, (\u003cstrong\u003eB\u003c/strong\u003e) \u003cem\u003eC. pilosula\u003c/em\u003e, and (\u003cstrong\u003eC\u003c/strong\u003e) \u003cem\u003eA. mongholicus\u003c/em\u003eunder different \u003cem\u003eFusarium\u003c/em\u003e species inoculated treatments. Sub-figures compare the control treatment (CK) to the corresponding \u003cem\u003eFusarium\u003c/em\u003e-infected treatments. Different colors represent different sample groups inoculated with \u003cem\u003eFusarium\u003c/em\u003especies: \u003cem\u003eF. oxysporum\u003c/em\u003e isolate DSH27, \u003cem\u003eF. solani\u003c/em\u003e isolate HQ123, and \u003cem\u003eF. tricinctum\u003c/em\u003e isolate DG105. CK denotes water control treatments. Each sub-figure displays the abundance ratio of different functions (Left), the difference ratio of function abundance within a 95% confidence interval (Middle), and the p-values (Right).\u003c/p\u003e","description":"","filename":"Fig.S4.tif","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/083e199c8dd0742aec490852.tif"},{"id":79850308,"identity":"4f32c983-8ef9-4566-aa9c-620c2af030d6","added_by":"auto","created_at":"2025-04-03 14:27:15","extension":"tif","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":304010,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig. S5\u003c/strong\u003ePrincipal component analysis (PCA) plots depict the distribution relationships between keystone bacterial genera, soil physicochemical properties and disease incidence (DI) and severity (DS) across rhizospheres of healthy controls and samples infected by \u003cem\u003eF. oxysporum\u003c/em\u003e (DSH27), \u003cem\u003eF. solani\u003c/em\u003e (HQ123), and \u003cem\u003eF. tricinctum\u003c/em\u003e (DG105) for \u003cem\u003eA. sinensis\u003c/em\u003e (\u003cstrong\u003ea\u003c/strong\u003e), \u003cem\u003eC. pilosula\u003c/em\u003e (\u003cstrong\u003eb\u003c/strong\u003e), and \u003cem\u003eA. mongholicus\u003c/em\u003e (\u003cstrong\u003ec\u003c/strong\u003e). Soil properties include pH, soil organic matter (SOM), total carbon (TC), total nitrogen (TN), total potassium (TK), total phosphorus (TP), available phosphorus (AVP), moisture content (MC), microbial biomass carbon (MBC), microbial biomass phosphorus (MBP), and trace elements (Zn, Fe, Mn, and Ca). Color-coded points represent samples from infected rhizosphere soils (DSH27, HQ123, and DG105), and the water control (CK).\u003c/p\u003e","description":"","filename":"FigS5.tif","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/91d0d074838330cbafc0d490.tif"},{"id":79849004,"identity":"015595d1-a0c1-4f08-807a-2d26cf4b2ea1","added_by":"auto","created_at":"2025-04-03 14:19:19","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":199065033,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptMainTextWithTrackChanges.docx","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/1531d04265a36829f728dff0.docx"},{"id":79848951,"identity":"557ac4dc-512d-4753-a546-61c0c9ea1a2c","added_by":"auto","created_at":"2025-04-03 14:19:15","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":25258,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable S1 \u003c/strong\u003eFungal and bacterial community α-diversity indices across three medicinal herb species (\u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003e under different Fusarium spp. inoculation treatments.\u003c/p\u003e","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/8d2768371ac4b1cce2be7af0.docx"},{"id":79848944,"identity":"986c8081-778a-4923-a45e-e4142fce8dd3","added_by":"auto","created_at":"2025-04-03 14:19:14","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":22336,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable S2\u003c/strong\u003eNonparametric multivariate statistical analysis of the impact of \u003cem\u003eFusarium\u003c/em\u003einoculants on soil physicochemical properties across different medicinal herb species (\u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e and \u003cem\u003eA. mongholicus\u003c/em\u003e).\u003c/p\u003e","description":"","filename":"TableS2.docx","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/c5d7c7a5cf5a0ac53285d5d2.docx"},{"id":79848971,"identity":"090917c3-95c0-4901-9487-11fb7a1ec359","added_by":"auto","created_at":"2025-04-03 14:19:16","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":27331,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable S3\u003c/strong\u003eSoil physicochemical properties under healthy and Fusarium-inoculated treatments across the three medicinal herbs evaluated.\u003c/p\u003e","description":"","filename":"TableS3.docx","url":"https://assets-eu.researchsquare.com/files/rs-5926386/v1/601581b292d9e5816636ccbd.docx"}],"financialInterests":"","formattedTitle":"Fusarium cross-infection in medicinal herbs alters rhizosphere microbiomes and disrupts mycorrhizal functions under soil physicochemical imbalances","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eMedicinal herbs have historically been integral to traditional healthcare systems worldwide, rooted in cultural and therapeutic practices. In China, modern medicine significantly relies on cultivating commonly used medicinal herbs, which are widespread across multiple medical systems (Lixin et al., 2009; Shan et al., 2023). The Northwestern region of China exhibits arid and semi-arid conditions, serving as the primary habitat and cultivation area for various medicinal herbs, particularly in mountainous and desert environments (Liu et al., 2017). Traditional Chinese Medicine (TCM) employs medicinal herbs such as \u003cem\u003eAngelica sinensis\u003c/em\u003e (Oliv.) Diels, \u003cem\u003eCodonopsis pilosula\u003c/em\u003e Franch., and \u003cem\u003eAstragalus membranaceus\u003c/em\u003e Bge. var. \u003cem\u003emongholicus\u003c/em\u003e as essential remedies, acknowledged for their preventive and therapeutic functions (Zhang and Chen, 2016; Hao and Liu, 2022). These herbs, mainly cultivated in Gansu Province, are crucial to Traditional Chinese Medicine and serve as significant income sources for local farmers (Liu et al., 2017; Zhou et al., 2024). The extensive cultivation of these perennial medicinal herbs in Dingxi, Gansu Province, underscores their significant contributions to local agriculture and traditional medicine practices (Yang et al., 2019; Zhou et al., 2024). However, the sustainability of these medicinal herbs is increasingly compromised by \u003cem\u003eFusarium\u003c/em\u003e root rot, a prevalent and destructive disease that not only threatens plant health and yield but also alters soil microbial balance and affects long-term cultivation strategies.\u003c/p\u003e \u003cp\u003e \u003cem\u003eFusarium\u003c/em\u003e species are well-known soil-borne pathogens capable of infecting diverse plant hosts through the use of cross-pathogenicity mechanisms and by exploiting environmental and host vulnerabilities (Arie, 2019, Summerell, 2019, Okello and Mathew, 2019). In medicinal herb cultivation, their ability to survive in soil and plant residues enables long-term persistence, leading to widespread and systematic infections that cause root and crown rots in plants (Leonce, 2021). Yet, how cross-infection occurs among different herb species remains unclear. \u003cem\u003eFusarium\u003c/em\u003e spp. have been recognized as the pathogens responsible for root rot and wilt among several medicinal perennial herbs in Gansu Province (Liu et al., 2022; Niyongabo et al., 2024; Uwaremwe et al., 2021; Wang et al., 2024; Zhao et al., 2021; Zhou et al., 2024). These species form species complexes with varying levels of aggressiveness and adaptability, complicating disease management (Suga and Hyakumachi, 2004). Their complex interactions, allow them to invade various host plants and cause root rot and wilt diseases among plant species (Coleman, 2016; Habibi et al., 2018). This explain why, despite ongoing efforts to manage Fusarium root rot through crop rotation, disease prevalence remains high, raising critical concerns about unexplored mechanisms driving pathogen persistence. Specifically, cross-infection among rotational medicinal herbs remains poorly understood, with limited studies investigating how \u003cem\u003eFusarium\u003c/em\u003e species adapt to multiple hosts and influence rhizosphere microbiomes and soil conditions. This knowledge gap hinders the development of effective disease control strategies and compromises sustainable medicinal herb cultivation.\u003c/p\u003e \u003cp\u003eMoreover, \u003cem\u003eFusarium\u003c/em\u003e spp. not only infect plant roots but also interact with soil microbial communities, altering the microbial composition, diversity, and trophic networks in the rhizosphere while disrupting physicochemical and nutrient availability, thereby enhancing disease severity (Liu et al., 2023; Mendes et al., 2011). Recent studies have shown that pathogen-induced shifts in the rhizosphere microbiome, including changes in fungal trophic functions and reductions in beneficial fungi such as arbuscular mycorrhizal (AM), contribute to increased disease severity and plant stress susceptibility (Barelli et al., 2020; Solis-Garcia et al., 2021). Additionally, altered soil properties, including pH, organic matter, and nutrient availability, are implicated in pathogen proliferation and disease dynamics (Naseri, 2014). However, the extent to which these changes facilitate cross-infection among medicinal herbs and reduce the efficacy of current disease management strategies remains largely unexplored. The colonization mechanisms of \u003cem\u003eFusarium\u003c/em\u003e species and the resulting host disease development are also shaped by their interactions and competition with the rhizosphere microbiome (Karlsson et al., 2021; Ping et al., 2024; Zhu et al., 2022). The composition and diversity of the rhizosphere microbiome affect \u003cem\u003eFusarium\u003c/em\u003e pathogenicity and disease severity, as shifts in microbial diversity and the presence of specific microbial taxa create environments that favor \u003cem\u003eFusarium\u003c/em\u003e species colonization (Luo et al., 2024; Park et al., 2023). Indeed, changes in nutrient composition favoring their establishment, as well as alterations in the rhizosphere fungal community composition along with the predicted functions of bacteria, have been associated with the development and aggressiveness of \u003cem\u003eFusarium\u003c/em\u003e root rot (Solis-Garcia et al., 2021; Uwaremwe et al., 2023). However, despite these insights, little is known about how medicinal herb cultivation practices influence \u003cem\u003eFusarium\u003c/em\u003e-associated microbial shifts and whether these changes contribute to disease recurrence even after crop rotation.\u003c/p\u003e \u003cp\u003eAlthough some microbial communities inhibit the growth of \u003cem\u003eFusarium\u003c/em\u003e species, fungal pathogen invasion is a major driving force shaping the rhizosphere microbiome. The rhizosphere of diseased plants and disease severity have been associated with specific microbes that can either prevent or promote the growth of the pathogens and disease development (Chapelle et al., 2016; Xiong et al., 2017). For instance, some microbial communities inhibit the growth of \u003cem\u003eFusarium\u003c/em\u003e species, while others, such as \u003cem\u003ePandoraea\u003c/em\u003e, \u003cem\u003eRhizomicrobium\u003c/em\u003e, \u003cem\u003eMortierella\u003c/em\u003e, and \u003cem\u003eFusarium\u003c/em\u003e spp., are positively correlated with root rot incidence and severity (Bi et al., 2023; Goodwin, 2022). This dualism highlights the complexity of \u003cem\u003eFusarium\u003c/em\u003e-host-microbiome interactions and suggests that sustainable disease management should rely not only on crop rotation but also on enhancing beneficial microbial communities that suppress Fusarium infections. Moreover, the complex interplay between \u003cem\u003eFusarium\u003c/em\u003e species, soil properties and microbial activity within the rhizosphere profoundly affects plant health and disease incidence. Physicochemical properties of the soil are key determinants of disease outcomes. For example, limited moisture and specific soil temperature and water content interactions have been observed to enhance \u003cem\u003eFusarium\u003c/em\u003e root rot (Cruz et al., 2020; Yan and Nelson, 2022). The pathogenic \u003cem\u003eFusarium\u003c/em\u003e inoculum density has shown positive correlations with total nitrogen and negative correlations with Olsen phosphorus. Disease severity was higher in soil with low organic matter, which has poor nitrate: ammonium ratios, as well as when sand and silt are in specific proportions (Moutassem et al., 2019; Naseri, 2014; Yan and Nelson, 2022). Furthermore, root exudates, as well as \u003cem\u003eFusarium\u003c/em\u003e metabolites such as toxins, phytotoxins, and degrading enzymes, influenced soil chemical composition in favor of pathogen colonization while impeding the growth and activity of beneficial microbes (Liu et al., 2017; Perincherry et al., 2019). These findings underscore the synergistic relationship between soil properties and \u003cem\u003eFusarium\u003c/em\u003e species and the influence of pathogen-induced changes in the soil environment on pathogenicity and persistence of disease.\u003c/p\u003e \u003cp\u003e \u003cem\u003eFusarium\u003c/em\u003e root rot and wilts have been frequently reported in \u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003e in Gansu province, with disease prevalence reaching up to 90% in \u003cem\u003eA. sinensis\u003c/em\u003e during peak infection periods of June and July. \u003cem\u003eF. tricinctum\u003c/em\u003e has been identified as the dominant pathogen, causing severe root rot symptoms and plant collapse in \u003cem\u003eA. sinensis\u003c/em\u003e (Liu et al., 2022), while \u003cem\u003eC. pilosula\u003c/em\u003e exhibits intense internal tissue browning (Zhao et al. 2021), and more than 50% of \u003cem\u003eA. mongholicus\u003c/em\u003e yields are lost due to \u003cem\u003eFusarium\u003c/em\u003e-inducing root rots (Li et al., 2021b; Yun et al., 2022; Zhou et al., 2024). Although these three medicinal herbs are usually cultivated under 1-, 2-, and 3-year rotation systems intended to mitigate disease occurrence, However, these crop rotation practices that were designed to alleviate disease occurrence, \u003cem\u003eFusarium\u003c/em\u003e root rot, and wilts persists, raising concerns about cross-infection mechanisms and their interactions with soil and microbial environments. The ability of \u003cem\u003eFusarium\u003c/em\u003e spp to survive in plant residues further enhances their capacity to infect new hosts after decomposition (Arie, 2019; Leonce, 2021), facilitating long-term pathogen persistence in cropping systems. This cross-pathogenicity demonstrates the complexity and challenges in root rot control and the necessity of integrated disease management to control Fusarium infections effectively (Okello and Mathew, 2019).\u003c/p\u003e \u003cp\u003eAlthough Fusarium-induced root rot is well-documented in medicinal herbs, the specific mechanisms of cross-infection, their long-term impacts on rhizosphere microbial networks, and the role of soil physicochemical conditions in disease persistence remain poorly understood. This study addresses these gaps by investigating how Fusarium cross-infection enables pathogen survival across multiple medicinal herb hosts and disrupts beneficial microbial networks, critical for plant resilience. By integrating cross-pathogenicity trials with microbiome and soil physicochemical analyses, we offer a comprehensive perspective on Fusarium-driven ecological shifts in medicinal herb cultivation. These findings contribute to a deeper understanding of Fusarium pathogenicity and emphasize the necessity of AMF-based strategies and integrated soil management to mitigate disease impact. We hypothesized that \u003cem\u003eFusarium\u003c/em\u003e cross-infection alters the structure and function of the rhizosphere microbiome and soil physicochemical conditions, leading to expedited disease development. Our findings aim to elucidate these interactions and provide valuable considerations for integrated management of \u003cem\u003eFusarium\u003c/em\u003e root rot to enhance resilient cultivation systems.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Field sampling, isolation, and characterization of culturable fungal species from plants and rhizosphere soils\u003c/h2\u003e\n \u003cp\u003eField surveys and sample collections were conducted for root rot disease investigations in \u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003e in Weiyuan County, Dingxi City, Gansu Province, in June 2022. The sampling sites included Dananchuan and Taizi (35\u0026deg;03\u0026prime;\u0026prime;N, 103\u0026deg;98\u0026prime;\u0026prime;E) in Luojiamo Village and Niejiashan (35\u0026deg;14\u0026prime;\u0026prime;N, 104\u0026deg;26\u0026prime;\u0026prime;E) in Niejiashan Village (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea-b). The cultivation of these three medicinal herbs at these locations was characterized by different cropping rotation systems (1-, 2-, and 3-year cycles). Diseased and healthy plants displaying symptoms such as leaf yellowing, wilting, and root decay were collected, with a total of 42 plant samples. Specifically, six diseased and six healthy \u003cem\u003eA. sinensis\u003c/em\u003e plants were sampled from fields previously cultivated with \u003cem\u003eA. mongholicus\u003c/em\u003e. For \u003cem\u003eC. pilosula\u003c/em\u003e, nine diseased and nine healthy plants were sampled from three fields with different crop rotation histories, including sequential rotations of \u003cem\u003eA. sinensis\u003c/em\u003e and \u003cem\u003eA. mongholicus\u003c/em\u003e. Similarly, six diseased and six healthy \u003cem\u003eA. mongholicus\u003c/em\u003e plants were collected from a field previously cultivated with \u003cem\u003eA. sinensis\u003c/em\u003e. Plants were carefully uprooted using a shovel to loosen the surrounding soil, forming a wide circle approximately 30cm away from the root zone diameter to minimize root damage. The plants were then gently lifted by holding the base while preserving the rhizosphere soil. Rhizosphere soils were carefully collected by gently shaking the plant to remove loose bulk soil. The soil tightly adhering to the root surface of an approximately 2 mm thick layer was considered rhizosphere soil and was carefully collected to ensure minimal contamination. Samples were preserved in portable plastic boxes with ice packs and transported to the laboratory, followed by immediate preservation under controlled temperatures (4\u0026deg;C and \u0026minus;\u0026thinsp;80\u0026deg;C for subsequent molecular analyses).\u003c/p\u003e\n \u003cp\u003ePlant tissues (roots, stems, and leaves) from symptomatic and asymptomatic samples of \u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003e were surface sterilized using 70% ethanol (30 s) and 3% sodium hypochlorite (5 min), followed by sterile water rinses. For each plant species, three root, three stem, and three leaf samples were selected per condition (symptomatic and asymptomatic), totaling 18 tissue samples per species. After blotting dry, tissues were cut into 0.5 \u0026times; 0.5 cm pieces using a sterile scalpel under a laminar flow hood to maintain aseptic conditions. The scalpel was flame sterilized before each use to prevent cross-contamination. These tissue sections, including leaf samples, were placed on Rose Bengal Agar (RBA; 36.6 g/L, Qingdao Bio-Technology Co., Ltd., China) plates. Rhizosphere soils were processed by transferring 0.5 g into sterile water, vortexing for 5\u0026ndash;10 min, and preparing 10-fold serial dilutions (10⁻\u0026sup1; to 10⁻⁵). From each dilution, 100 \u0026micro;L was spread onto RBA plates. The plates were incubated in darkness at 25\u0026deg;C for 5\u0026ndash;7 days. Emerging fungal mycelia to allow mycelial growth from plant tissues and soil suspensions. Emerging mycelia from plant tissues and soil suspensions were subcultured onto full-strength potato dextrose agar (PDA; 46 g/L, Qingdao Bio-Technology Co., Ltd., China) and subcultured to obtain distinct fungal colonies, which were further purified on fresh PDA for identification. The morphological characterization of isolates was performed based on colony features, including the color, texture and mycelia growth rate on PDA and microscopic observation of conidial structures, including macroconidia, microconidia and chlamydospores on both PDA and Carboxymethylcellulose (CMC) broth. Distinctive traits were used for preliminary identification before molecular analysis. Isolates were preserved in 40% glycerol at \u0026minus;\u0026thinsp;80\u0026deg;C for future studies.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Fungal DNA Extractions and Molecular Identification\u003c/h2\u003e\n \u003cp\u003eFungal genomic DNA of all 83 fungal isolates was extracted from 100 mg of ground fungal mycelia using a CTAB-based method. Tissues were lysed with Buffer CPL, mercaptoethanol, and optional RNase, incubated at 65\u0026deg;C. Chloroform and isoamyl alcohol were used for phase separation. DNA was precipitated with ethanol, bound to a HiBind DNA column, and washed twice with SPW Wash Buffer. Residual ethanol was removed by centrifugation, and DNA was eluted using a pre-warmed Elution Buffer. Final eluates were collected for downstream applications (Omega Bio-tek, Inc. 2022. E.Z.N.A. \u0026reg;HP Fungal DNA kit. Available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.omegabiotek.com\u003c/span\u003e\u003c/span\u003e). DNA concentration and quality were evaluated using a NanoDrop 2000c spectrophotometer (Thermo Fisher Scientific) and agarose gel electrophoresis. Species-level molecular identification of \u003cem\u003eFusarium\u003c/em\u003e isolates was achieved by amplifying the internal transcribed spacer (ITS) region, the translation elongation factor (TEF1-\u0026alpha;), and RNA polymerase II second largest subunit (RPB2) gene regions using ITS1/ITS4 primers (ITS1: 5\u0026prime;-TCCGTAGGTGAACCTGCGG-3\u0026prime;; ITS4: 5\u0026prime;-TCCTCCGCTTATTGATATGC-3\u0026prime;; (Schoch et al., 2012; Zarrin et al., 2016)), TEF1F/TEF1R primers (TEF1F: 5\u0026prime;-GTCACTTGATCTACCAGTGC-3\u0026prime;; TEF1R: 5\u0026prime;-TACCAATGACGGTGACATAG-3\u0026prime; (Uwaremwe et al., 2021)), and 7cr/5f2 (7cr: 5\u0026prime;-GGGGWGAYCAGAAGAAGGC-3\u0026prime;; 5f2: 5\u0026prime;-CCCATRGCTTGYTTRCCCAT-3\u0026prime;; ( O\u0026rsquo;Donnell et al., 2010)) primers, respectively. PCR products were sequenced at Sangon Biotech and analyzed using BLAST against NCBI GenBank. All sequences have been deposited in NCBI GenBank under accession numbers (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Phylogenetic trees were constructed with concatenated ITS and TEF1-\u0026alpha; sequences using the neighbor-joining method in MEGA 7 (Kumar et al., 2016) with 1,000 bootstrap replicates to validate evolutionary relationships, and bootstrap values calculated for 1,000 replicates.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDetailed information on 58 \u003cem\u003eFusarium\u003c/em\u003e isolates obtained in this study, with their original sequences accession numbers.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eIsolate IDᵃ\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSpecies\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eHost of Originᵇ\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eIsolation Saurce\u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eGeneBank Accessions\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eITS\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTEF1-\u0026alpha;\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397570\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDSH27\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eF. oxysporum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eC. pilosula\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiseased Root\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePQ328625\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePQ397571\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328626\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397572\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased soil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397573\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328629\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397574\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH32b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. tricinctum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328630\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397575\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased soil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397576\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397577\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328634\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397578\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328635\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397579\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Stem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328637\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397580\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397581\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397582\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328640\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397583\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397584\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328642\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397585\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. redolens\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHealthy Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397586\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. flocciferum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased soil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397587\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH114b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328645\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397588\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328646\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397589\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDG14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. sinensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Soil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDG15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. sinensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328648\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397590\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDG16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. sinensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328649\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397591\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDG18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. acuminatum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. sinensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397592\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDG19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. Avenaceum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. sinensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328651\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397593\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDG105\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eF. tricinctum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eA. sinensis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiseased Root\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePQ328655\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePQ397596\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDG4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. tricinctum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. sinensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397597\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDG4a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. tricinctum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. sinensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397598\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDG105b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. tricinctum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. sinensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328658\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397599\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328659\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397600\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328660\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397601\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328661\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397602\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397603\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328663\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397604\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Soil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328664\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Soil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328665\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328666\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397605\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Soil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328668\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397606\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. acuminatum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328669\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397607\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328670\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397608\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Soil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328671\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Soil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397609\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Soil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328673\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397610\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328674\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328675\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397611\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397612\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. acuminatum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328677\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397613\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328678\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397614\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHQ123\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eF. solani\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eA. mongholicus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiseased Root\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePQ328679\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePQ397615\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Stem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328680\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397616\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. avenaceum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiseased Root\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ328681\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePQ397617\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eᵃBolded identities are \u003cem\u003eFusarium\u003c/em\u003e isolates used in cross-pathogenicity experiments.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eᵇ\u003c/strong\u003e\u003cem\u003eFusarium\u003c/em\u003e spp. were isolated from different medicinal herb plant species.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e\u003cstrong\u003ec\u003c/strong\u003e\u003c/sup\u003e\u003cem\u003eFusarium spp\u003c/em\u003e. were isolated from symptomatic and asymptomatic plants and rhizosphere soils.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Experiment design, inoculum preparation, and cross-pathogenicity evaluation\u003c/h2\u003e\n \u003cp\u003eFungal inoculum was prepared by culturing \u003cem\u003eFusarium\u003c/em\u003e isolates (DSH27, HQ123, DG105) on PDA for 10 days. Conidia suspension was prepared by scraping the mycelium with sterile water and subsequently filtering it through sterile cheesecloth. \u003cem\u003eFusarium\u003c/em\u003e strains were grown on PDA at 25\u0026deg;C in complete darkness for 5 days to enhance conidia production. The actively growing fungal mycelia were excised as agar plugs from culture plates. Then, sterile forceps were used to transfer the plugs into autoclaved carboxymethylcellulose (CMC) broth in a sterilized 500 mL Erlenmeyer flask. A solution of CMC broth was prepared by dissolving 15 g of carboxymethylcellulose, 2 g of NaNO3, 1 g of KH2PO4, 0.5 g of MgSO4\u0026sdot;7H2O, and 1 g of yeast extract in 1000 ml of sterile water. The culture was shaken for 5 days at 175 rpm in an incubator at 25\u0026deg;C (Zhang et al., 2020). Concentrations of spores were adjusted to 10⁶ conidia/mL using sterile ddH2O and a hemocytometer.\u003c/p\u003e\n \u003cp\u003ePathogenicity was assessed through three assays, including greenhouse pot tests, field trial, and pathogenicity tests on excised root tissues. Seedlings were planted into pots containing sterilized soil made of peat and vermiculite in a 2:2:1 ratio in the greenhouse. Each fungal isolate was tested on eight plants per species, with two plants per pot and four replicates per isolate. A field experiment was conducted in Longxi County (35\u0026deg;01\u0026prime;\u0026prime;N, 104\u0026deg;51\u0026prime;\u0026prime;E), Gansu Province, from April to October 2023, with plots classified by species and inoculation treatments. Inoculation was performed in June with \u003cem\u003eF. oxysporum\u003c/em\u003e (DSH27), \u003cem\u003eF. solani\u003c/em\u003e (HQ123), \u003cem\u003eF. tricinctum\u003c/em\u003e (DG105), and a water control (CK). Plants were cultivated in rows, with spacing tailored to each species. Inoculation involved applying spore suspension to wounded taproots. For inoculation, taproot wounds (3 mm depth) were created on seedlings of \u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003e. A 20 mL spore suspension was applied directly to the wounded part of the main roots and gently into the rhizosphere dripline. Control plants underwent the same wounding procedure but were inoculated with sterile water double distilled (ddH₂O) to distinguish the effects of mechanical damage from Fusarium infection (Pande et al., 2007; Pouralibaba et al. 2016). The field experiment was conducted over a full growing-to-harvest cycle using a randomized complete block design (RCBD), with 3 replicates ensuring reproducibility and minimizing environmental variability across the study area. For excised root tissue assays, sterilized and wounded root tissues were inoculated with agar plugs extracted from the \u003cem\u003eFusarium\u003c/em\u003e colony margins of 10-day-old PDA medium cultures using a 5-mm diameter cork-borer, incubated in petri dishes, and assessed for rot symptoms (Bugingo et al., 2024; Moparthi et al. 2024). The maintained control treatment consisted of root tissue without a fungal plug. (Fig. \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e). Inoculated \u003cem\u003eFusarium\u003c/em\u003e species were re-isolated from symptomatic tissues and re-cultured for morphological and molecular confirmation through DNA extraction, ITS/TEF1-\u0026alpha; PCR amplification, and sequencing. Greenhouse and excised root tissue experiments were repeated twice, and BLAST analysis confirmed pathogen identities, ensuring consistency with the original inoculated \u003cem\u003eFusarium\u003c/em\u003e strains.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Measurement of Disease Incidence and Severity\u003c/h2\u003e\n \u003cp\u003eDisease incidence (DI) and disease severity (DS) were evaluated to determine the impact of Fusarium isolates on \u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003e. For aboveground symptoms, DI and DS were assessed at 3-, 6-, and 9-weeks post-inoculation. Visible symptoms such as wilting and leaf or stem yellowing were recorded. Belowground symptoms were evaluated 9 weeks after inoculation by examining harvested roots. Roots were washed under low-pressure water, placed on sterilized filter paper, and cut longitudinally to assess key root rot characteristics, including epidermal decay, vascular darkening, and root rot. DI was calculated as the percentage of infected plants relative to the total number of plants in each treatment group (Sharma \u0026amp; Kolte, 1994). DS was evaluated on a 0\u0026ndash;5 scale, where 0 represented no symptoms, 1\u0026thinsp;=\u0026thinsp;1\u0026ndash;9% affected, 2\u0026thinsp;=\u0026thinsp;10\u0026ndash;29%, 3\u0026thinsp;=\u0026thinsp;30\u0026ndash;69%; 4\u0026thinsp;=\u0026thinsp;70\u0026ndash;89%, and 5\u0026thinsp;=\u0026thinsp;90\u0026ndash;100% affected area (Moparthi et al., 2021; Shikur Gebremariam et al., 2018; Wildermuth \u0026amp; McNamara, 1994). The belowground root rot DI and DS were evaluated 9 weeks post-inoculation during harvest. Roots were cleaned, placed on sterilized filter paper, and longitudinally cut to observe key symptoms such as epidermal decay and vascular discoloration. Here, the DS was scored on a 0\u0026ndash;5 scale (Gr\u0026uuml;nwald et al., 2003), where 0\u0026thinsp;=\u0026thinsp;no symptoms; 1\u0026thinsp;=\u0026thinsp;slight hypocotyl lesions; 2\u0026thinsp;=\u0026thinsp;lesions consolidating on epicotyls and hypocotyls; 3\u0026thinsp;=\u0026thinsp;lesions spreading into root systems; 4\u0026thinsp;=\u0026thinsp;extensive infection of roots and hypocotyls; 5\u0026thinsp;=\u0026thinsp;complete root system decay (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eg-l). Similarly, field assessments employed a five-point interval sampling method in 1 m square areas within experimental plots. Fifteen plants from \u003cem\u003eFusarium\u003c/em\u003e-inoculated and control groups were evaluated per plot. For excised root tissue assays, DI and DS were determined by observing root rot browning and decay from epidermal lesions to complete root tissue disease severity was assessed by evaluating browning and decay levels, following standard belowground root rot severity scaling methods as shown by Sharma and Kolte (1994).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e2.5 Rhizosphere and Bulk Soil DNA Extractions, and Illumina Novaseq Sequencing\u003c/h2\u003e\n \u003cp\u003eTotal soil DNA was extracted from 0.5 g of bulk and rhizosphere soil samples using the TGuide S96 Magnetic Bead-based Soil Genomic DNA Extraction Kit (Tiangen Biochemical Technology, Beijing, China), following the manufacturer\u0026apos;s protocol. DNA concentration and quality were assessed using a microplate (Synergy HTX Gene Company Limited, Bomei Fuxin Technology, Beijing, China). PCR amplification was performed to target conserved regions of ribosomal RNA, including the fungal ITS (internal transcribed spacer) region and bacterial 16S rDNA, using primers ITS1F 5\u0026apos;-CTTGGTCATTTAGAGGAAGTAA-3\u0026apos; and ITS2 5\u0026apos;-GCTGCGTTCTTCATCGATGC-3\u0026apos;; 338F 5\u0026apos;- ACTCCTACGGGAGGCAGCA-3\u0026apos; and 806R 5\u0026apos;- GGACTACHVGGGTWTCTAAT-3\u0026apos;, respectively (Liu et al., 2021; White, 1990). Sample-specific PacBio barcode sequences were added to both forward and reverse primers to enable multiplex sequencing, as described by Buermans et al. (2017). PCR reactions included 25 \u0026micro;L of ddH2O, 2.5 \u0026micro;L of each primer, 12.5 \u0026micro;L of Phusion Hot Start Flex 2\u0026times;Master Mix (Thermo Fisher Scientific, Oregon, USA), and 50 ng of template DNA. Thermal cycling conditions consisted of initial denaturation at 95\u0026deg;C for 5 min, followed by 25 cycles of denaturation (95\u0026deg;C for 30 s), annealing (50\u0026deg;C for 30 s), extension (72\u0026deg;C for 40 s), and a final extension at 72\u0026deg;C for 7 min. Amplified PCR products were purified using Agencourt AMPure XP Beads and quantified with a Qubit 4.0 Fluorometer and Qubit dsDNA HS Assay Kit (Thermo Fisher Scientific Oregon, USA) (Shao et al., 2023). Qualified libraries were prepared and sequenced using the Illumina Novaseq 6000 platform. All sequencing data were deposited in the NCBI Sequence Read Archive (SRA) under accession numbers PRJNA1201923 and PRJNA1202069 for Fungi and bacteria, respectively.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e2.6 Bioinformatic Analyses\u003c/h2\u003e\n \u003cp\u003eBioinformatic analyses were performed using the BMK Cloud platform (Biomarker Technologies Co., Ltd., Beijing, China). Illumina high-throughput sequencing data were processed using Trimmomatic v0.33 to filter low-quality reads with a 50 bp sliding window, and sequences were trimmed when the average quality within the window fell below a Phred score of 20 (Bolger et al., 2014). Primer sequences were identified and trimmed using Cutadapt v1.8.3 (Martin, 2011) with a maximum mismatch rate of 20% and a minimum overlap of 15 bp. Sequences were length-filtered based on region-specific thresholds (e.g., 350\u0026ndash;490 bp for 16S V3-V4 amplicons). Chimeric sequences were identified and removed using the UCHIME algorithm v8.1 (Edgar et al., 2011). Reads were assigned to samples based on barcode sequences and clustered into operational taxonomic units (OTUs) at 97% similarity using USEARCH v10 (Edgar, 2013). Low-abundance features were filtered, and taxonomic assignment of OTUs was conducted using the DADA2 algorithm (Callahan et al., 2016) in QIIME2 version 2020.6 (Bolyen et al., 2019), with a confidence threshold of 70%. Alpha diversity indices and beta diversity comparisons were calculated using QIIME2 and R software (R Core Team, 2024). Functional annotation of fungal sequences was performed using FUNGuild (Nguyen et al., 2016), classifying taxa into functional guilds based on ecological roles and nutritional strategies.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e2.7 Statistical analysis\u003c/h2\u003e\n \u003cp\u003eThe statistical analysis was conducted using the SPSS software (v27.0, IBM, Armonk, NY, USA). Considering the quantification of disease incidence and severity on an ordinal scale ranging from 0 to 5, statistical non-parametric tests were transformed to evaluate the treatment effects. Mean ranks (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{R}ij\\)\u003c/span\u003e\u003c/span\u003e), Median disease rate (MDR), and relative treatment effects (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\widehat{p}ij\\)\u003c/span\u003e\u003c/span\u003e) with 95% confidence intervals (CIs) were measured. Mean ranks derived from these non-parametric ordinal data and relative treatment effects with CIs were determined, as described in Shah and Madden (2004). Rarefaction curves were generated in QIIME2 to evaluate sequencing depth adequacy, with alpha diversity indices (Shannon, Simpson, ACE, and Chao1) calculated as described by Bokulich et al. (2013). Beta diversity was analyzed using partial least squares discriminant analysis (PLS-DA) to differentiate between groups and identify influential variables (Adamberg et al., 2015). Disease severity rankings were standardized across all plant species to ensure comparability, and Partial Least Squares Discriminant Analysis (PLS-DA) was employed to differentiate between treatment groups, maximizing inter-group variance and identifying key influential microbial variables linked to Fusarium infection. Species diversity, distribution, and function analyses were performed using the BMKCloud platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.biocloud.net\u003c/span\u003e\u003c/span\u003e). Network analysis was conducted using Gephi (Bastian et al., 2009), complementing statistical analyses performed in R software (R Core Team, 2024) to identify key interaction patterns and microbial network structures. Metastats analysis (White et al., 2009) was employed to identify significant differences in microbial abundance and functions between control and inoculated groups, with significance set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The maximum variance to determine the linear combinations and relationships between microbial communities, soil physicochemical properties, and disease metrics was performed using the principal component analysis (PCA) in Canoco 5 software (\u0026Scaron;milauer and Lep\u0026scaron;, 2014).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Isolation, morphological characterization, and phylogenetic diversity analysis of Fusarium isolates.\u003c/h2\u003e\n \u003cp\u003eThe isolation of culturable fungi from diseased and healthy rhizosphere samples of \u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003e yielded 83 fungal isolates, of which 69.87% (58 isolates) were identified as \u003cem\u003eFusarium\u003c/em\u003e spp. based on ITS region analysis (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eD). The isolation and phylogenetic analysis revealed distinct host associations among the three \u003cem\u003eFusarium\u003c/em\u003e species complexes, with \u003cem\u003eFusarium oxysporum\u003c/em\u003e species complex (FOSC, 36.2%), primarily from \u003cem\u003eC. pilosula\u003c/em\u003e; \u003cem\u003eFusarium solani\u003c/em\u003e species complex (FSSC, 31%) predominantly from \u003cem\u003eA. mongholicus\u003c/em\u003e; and \u003cem\u003eFusarium tricinctum\u003c/em\u003e species complex (FTSC, 22.4%) mainly from \u003cem\u003eA. sinensis\u003c/em\u003e, as shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. Morphological assessment revealed distinct conidial features among these complexes, with similarities in spore formation patterns and cell structures, exhibiting fast-growing mycelium structures on PDA media and shared pigmentation patterns ranging from whitish to pink or purple. These \u003cem\u003eFusarium\u003c/em\u003e species complexes displayed closely related conidial curvature, dense conidial masses, and comparable conidiogenesis processes (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea–w). Further species-level identification using \u003cem\u003eTEF1-α\u003c/em\u003e and RBP2 gene sequencing confirmed the clustering of isolates within their respective complexes. Representative strains \u003cem\u003eF. oxysporum\u003c/em\u003e strain DSH27 (\u003cem\u003eC. pilosula\u003c/em\u003e), \u003cem\u003eF. solani\u003c/em\u003e strain HQ123 (\u003cem\u003eA. mongholicus\u003c/em\u003e), and \u003cem\u003eF. tricinctum\u003c/em\u003e strain DG105 (\u003cem\u003eA. sinensis\u003c/em\u003e) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eY) were selected for cross-pathogenicity assays. Sequences for these strains were deposited in GenBank (ITS: PQ328624, PQ328672, PQ328653; TEF1-α: PQ397570, PQ397615, PQ397596 and RPB2: PV358060, PV358062, PV358061) for DSH27, HQ123 and DG105, respectively. Other accession numbers are provided in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Cross-inoculation and pathogenicity evaluation: Disease incidence and severity\u003c/h2\u003e\n \u003cp\u003eThe cross-infection and pathogenicity investigation using three \u003cem\u003eFusarium\u003c/em\u003e isolates (DSH27, HQ123, DG105) representing each species complex (FOSC, FSSC, FTSC) from \u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003e revealed variability in aggressiveness across plant species. Both greenhouse and field trials, which followed the same experimental design, showed significant differences in disease severity between \u003cem\u003eFusarium\u003c/em\u003e-inoculated and non-inoculated control plants (P ≤ 0.05). Homogeneity of variance tests indicated no significant differences between trials (P ≤ 0.05), allowing data to be pooled for analysis. \u003cem\u003eFusarium\u003c/em\u003e isolates were categorized into four aggressiveness groups based on disease severity ranks: highly aggressive (˃385.1), moderately aggressive (304.5–385.1), less aggressive (223.8–304.4), and weakly aggressive (˂223.7). Across trials, isolates showed the greatest aggressiveness on their original host plants. \u003cem\u003eF. tricinctum\u003c/em\u003e (DG105) was highly aggressive on \u003cem\u003eA. sinensis\u003c/em\u003e, moderately aggressive on \u003cem\u003eC. pilosula\u003c/em\u003e, and less aggressive on \u003cem\u003eA. mongholicus\u003c/em\u003e. \u003cem\u003eF. oxysporum\u003c/em\u003e (DSH27) displayed high aggressiveness on \u003cem\u003eC. pilosula\u003c/em\u003e, moderate aggressiveness on \u003cem\u003eA. sinensis\u003c/em\u003e, and weak aggressiveness on \u003cem\u003eA. mongholicus\u003c/em\u003e. \u003cem\u003eF. solani\u003c/em\u003e (HQ123) was highly aggressive on \u003cem\u003eA. mongholicus\u003c/em\u003e, moderate on \u003cem\u003eA. sinensis\u003c/em\u003e, and weak on \u003cem\u003eC. pilosula\u003c/em\u003e (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Notably, on excised root tissues, disease incidence reached 100% across all plant species for their original \u003cem\u003eFusarium\u003c/em\u003e isolates, with severity averaging 85%, while in cross-infections, both incidence and severity were approximately 80%. ( Fig. \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003ed). Intriguingly, \u003cem\u003eF. solani\u003c/em\u003e exhibited the highest cross-infection severity, exceeding the disease severity caused by original isolates in \u003cem\u003eA. sinensis\u003c/em\u003e ( Fig. \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003ea, d). Disease severity correlated with time post-inoculation, with symptoms progressing from yellowing and wilting to stunting and plant death (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea–f). These findings highlight host-specific interactions and variability in cross-pathogenicity, emphasizing that\u0026nbsp;\u003cem\u003eFusarium\u003c/em\u003e isolates exhibit differing levels of aggressiveness based on plant species.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eEvaluation of mean ranks of disease severity ratings across three medicinal herbs (\u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e, \u003cem\u003eA. mongholicus\u003c/em\u003e) following cross-inoculation with the three \u003cem\u003eFusarium\u003c/em\u003e strains (DSH27, HQ123, and DG105) tested in this study.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eIsolates\u003c/p\u003e\n \u003c/th\u003e\u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eFusarium spp.\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eHost species\u003c/p\u003e\n \u003c/th\u003e\u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eMDR\u003c/p\u003e\n \u003c/th\u003e\u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e95% CI for Relative Effect\u003c/p\u003e\n \u003c/th\u003e\u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAggressiveness\u003c/p\u003e\n \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{\\varvec{R}}\\varvec{i}\\varvec{j}\\text{ᵃ}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\widehat{\\varvec{p}}\\varvec{i}\\varvec{j}\\)\u003c/span\u003e\u003c/span\u003e\u003cstrong\u003eᵇ\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLower\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eUpper\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH27\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. sinensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e288.05\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eLess\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ123\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. sinensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e295.82\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eLess\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eDG105\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. tricinctum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. sinensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e399.04\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eCK\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eControl\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. sinensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e174.65\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eNonpathogenic\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH27\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e370.56\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ123\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e287.77\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eLess\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eDG105\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. tricinctum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e321.45\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eCK\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eControl\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC. pilosula\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e158.82\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eNonpathogenic\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eDSH27\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e248.49\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eLess\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eHQ123\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. solani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e349.45\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eDG105\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eF. tricinctum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e276.91\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eLess\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eCK\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eControl\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA. mongholicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e146.96\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\u003ctd align=\"left\"\u003e\n \u003cp\u003eNonpathogenic\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003eᵃMean rank (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{R}ij\\)\u003c/span\u003e\u003c/span\u003e), median rate (MDR), and relative effect (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\widehat{P}ij\\)\u003c/span\u003e\u003c/span\u003e) for root rot severity ratings of \u003cem\u003eFusarium\u003c/em\u003e isolate were determined following the method outlined by Shah and Madden (2004). Higher ranks indicate more aggressive isolate, causing increased root rot severity. Isolate with mean rank ˃223.7, weakly aggressive; 223.8–304.4, Less aggressive; 304.5–385.1, moderately aggressive; and ˃385.1, highly aggressive.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Infection and root-rot symptomatological observations on root tissue staining\u003c/h2\u003e\n \u003cp\u003eSymptomatological observations on \u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003e seedlings inoculated with \u003cem\u003eF. oxysporum\u003c/em\u003e (DSH27), \u003cem\u003eF. solani\u003c/em\u003e (HQ123), and \u003cem\u003eF. tricinctum\u003c/em\u003e (DG105), along with controls, were conducted six weeks post-inoculation. Healthy root tissues (CK) exhibited intact cell walls, a continuous hypodermis, and densely packed cells (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e; Fig. \u003cspan class=\"InternalRef\"\u003eS2\u003c/span\u003e). Infected tissues showed significant variation in aggressiveness depending on \u003cem\u003eFusarium\u003c/em\u003e spp. and plant species. Severe infections in \u003cem\u003eA. sinensis\u003c/em\u003e (by \u003cem\u003eF. tricinctum\u003c/em\u003e DG105), \u003cem\u003eC. pilosula\u003c/em\u003e (by \u003cem\u003eF. oxysporum\u003c/em\u003e DSH27), and \u003cem\u003eA. mongholicus\u003c/em\u003e (by \u003cem\u003eF. solani\u003c/em\u003e HQ123) were characterized by extensive tissue degradation, necrosis, reddish-brown vascular discoloration in \u003cem\u003eA. sinensis\u003c/em\u003e, and dark brown to black discoloration in the other two species. \u003cem\u003eFusarium\u003c/em\u003e infections on their original host plants induced increased lignification, accumulation of pathogen hyphae, and high levels of necrosis in \u003cem\u003eA. sinensis\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea; Fig. \u003cspan class=\"InternalRef\"\u003eS2\u003c/span\u003ea), \u003cem\u003eC. pilosula\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb; Fig. \u003cspan class=\"InternalRef\"\u003eS2\u003c/span\u003eb), and \u003cem\u003eA. mongholicus\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ec; Fig. \u003cspan class=\"InternalRef\"\u003eS2\u003c/span\u003ec), indicating high aggressiveness (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ea-b; Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). However, cross-infections demonstrated partial tissue degradation and localized damage. \u003cem\u003eF. tricinctum\u003c/em\u003e and \u003cem\u003eF. solani\u003c/em\u003e caused moderate staining and localized cell disintegration in \u003cem\u003eC. pilosula\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb; Fig. \u003cspan class=\"InternalRef\"\u003eS2\u003c/span\u003eb), indicating moderate aggressiveness (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ea-b; Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Conversely, \u003cem\u003eF. tricinctum\u003c/em\u003e and \u003cem\u003eF. oxysporum\u003c/em\u003e caused minimal damage in \u003cem\u003eA. mongholicus\u003c/em\u003e, with faint staining, limited cell disruption, and pathogen presence largely confined to epidermal and cortical cells, suggesting weak infections (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ec; Fig. \u003cspan class=\"InternalRef\"\u003eS2\u003c/span\u003ec), indicating less aggressiveness (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ea-b; Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.4. Sequencing data and fungal and bacterial community networks in bulk and rhizosphere soils under Fusarium inoculation\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eSequencing infected and non-infected samples yielded 1,919,988, 1,919,839, and 1,919,839 raw fungal reads, and 1,920,440, 1,918,895, and 1,919,587 raw bacterial reads for \u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003e, respectively. After quality filtering, the average high-quality fungal reads per sample ranged from 56,348 to 67,841, while bacterial reads ranged from 40,928 to 62,891. These reads were clustered into 245, 225, and 219 fungal OTUs and 1,705, 1,561, and 1,641 bacterial OTUs for \u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003e, respectively, based on 97% sequence similarity. \u003cem\u003eFusarium\u003c/em\u003e-inoculated rhizosphere soils showed more OTUs than healthy non-inoculated rhizospheres. Unique OTUs varied between \u003cem\u003eFusarium\u003c/em\u003e-infected soils (DSH27, HQ123, DG105), non-infected controls (CK), and bulk soils (BF), with rhizosphere soils displaying higher diversity than bulk soils (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003ea-j). Fungal and bacterial Alpha diversity indices (Shannon, Simpson, Chao1, Ace) revealed no significant differences in fungal diversity between infected and non-infected rhizosphere soils (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003ec-k). However, the Shannon index for bacterial diversity was significantly lower in \u003cem\u003eF. oxysporum\u003c/em\u003e DSH27-inoculated treatments in \u003cem\u003eA. sinensis\u003c/em\u003e compared to CK (p \u0026lt; 0.01) (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003ed-l). Although no significant differences were detected between treatments, species richness (Chao1 and Ace indices) was higher in CK than in DSH27 and HQ123 treatments ( Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eBeta diversity analysis revealed distinct clustering of microbial communities between infected and non-infected rhizospheres using partial least squares discriminant analysis (PLS-DA). Although the ANOSIM analyses mainly indicated no significant differences in the overall fungal and bacterial community structure between healthy and diseased groups, the non-infected formed separate clusters with \u003cem\u003eFusarium\u003c/em\u003e-infected rhizospheres (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003ea-c). Here, fungal beta diversity was significantly different in \u003cem\u003eF. tricinctum\u003c/em\u003e DG105-infected rhizospheres and bulk soils in \u003cem\u003eA. sinensis\u003c/em\u003e (R² = 0.217, \u003cem\u003ep\u003c/em\u003e = 0.03) (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003ea-c), while bacterial beta diversities between bulk and rhizosphere soils showed no significant differences (\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05) (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003ed-f).\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.5. The impact of Fusarium infection and cross-infection on rhizosphere fungal and bacterial communities and functional dynamics\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eShifts in fungal and bacterial community composition and functions following \u003cem\u003eFusarium\u003c/em\u003e inoculation (DSH27, HQ123, and DG105) compared to the water control (CK) revealed significant changes in \u003cem\u003eFusarium\u003c/em\u003e-infected compared to non-infected rhizosphere soils. \u003cem\u003eFusarium\u003c/em\u003e inoculation significantly altered fungal phyla, increasing the abundance of Chytridiomycota in \u003cem\u003eA. sinensis\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003ea) and Rozellomycota in \u003cem\u003eC. pilosula\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003ec). Similarly, Olpidiomycota and Mucoromycota were significantly increased in \u003cem\u003eC. pilosula\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003ec), while Ascomycota and Aphelidiomycota were increased dramatically in \u003cem\u003eA. mongholicus\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003ee). At the genus level, \u003cem\u003eFusarium\u003c/em\u003e abundance significantly increased in infected \u003cem\u003eC. pilosula\u003c/em\u003e (p \u0026lt; 0.01) (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003ed). Genera such as Lectera, Stagonosporopsis, and \u003cem\u003eCumuliphoma\u003c/em\u003e decreased considerably in DG105-infected \u003cem\u003eA. mongholicus\u003c/em\u003e, while \u003cem\u003eMortierella\u003c/em\u003e abundance was significantly reduced in DSH27-infected \u003cem\u003eA. sinensis\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003ef). Bacterial communities were also influenced, particularly in DG105-infected soils of \u003cem\u003eA. sinensis\u003c/em\u003e and \u003cem\u003eC. pilosula\u003c/em\u003e, where significant changes in \u003cem\u003eVerrucomicrobiota\u003c/em\u003e and Acidobacteriota phyla were observed in \u003cem\u003eA. mongholicus\u003c/em\u003e. At the genus level, \u003cem\u003eRB41\u003c/em\u003e and unclassified_Microcellaceae significantly declined under \u003cem\u003eFusarium\u003c/em\u003e treatment ( Fig. \u003cspan class=\"InternalRef\"\u003eS3\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eInterestingly, fungal trophic functions demonstrated a shift toward pathogenicity in all \u003cem\u003eFusarium\u003c/em\u003e-infected rhizosphere soils, with increased plant pathotrophic functions and reduced symbiotrophic and saprotrophic roles (Fig. \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003ea-c). Notably, beneficial arbuscular mycorrhizal fungi (AMF) were significantly reduced in HQ123-infected \u003cem\u003eA. sinensis\u003c/em\u003e (p = 0.014) (Fig. \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003ed). Specifically, comparisons of AMF abundances revealed significant differences in \u003cem\u003eA. sinensis\u003c/em\u003e. Although the difference was not statistically significant in \u003cem\u003eA. mongholicus\u003c/em\u003e and \u003cem\u003eC. pilosula\u003c/em\u003e, there was a clear trend of decreased AMF abundance under infected rhizospheres compared to healthy, non-infected rhizospheres (Fig. \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003ed). In contrast, plant pathotrophic fungal abundance displayed an inverse pattern, increasing pathogenic fungi in infected rhizospheres across all tested plant species. For bacterial functions, KEGG pathway analysis revealed significant effects on transcription, translation, and metabolism-related pathways in DG105-infected \u003cem\u003eA. sinensis\u003c/em\u003e. In \u003cem\u003eC. pilosula\u003c/em\u003e, functions related to the immune system and environmental adaptation were significantly affected ( Fig. \u003cspan class=\"InternalRef\"\u003eS4\u003c/span\u003e).\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.6. The interconnections between rhizosphere microbial communities, soil physicochemical properties, and the incidence and severity of root rot disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eMicrobial network analysis revealed \u003cem\u003eFusarium\u003c/em\u003e-driven alterations in taxa connectivity within rhizosphere communities. \u003cem\u003eFusarium\u003c/em\u003e infection decreased network modularity classes by either increasing or decreasing modularity and altering the degree of centrality of specific fungal taxa. Fungal genera predominantly pathogenic or containing numerous pathogenic taxa include \u003cem\u003eFusarium\u003c/em\u003e, \u003cem\u003eAlternaria\u003c/em\u003e, \u003cem\u003eStagonosporopsis\u003c/em\u003e, and \u003cem\u003ePlectosphaerella\u003c/em\u003e, exhibited either increased weighted degree of centrality or betweenness centrality under \u003cem\u003eF. tricinctum\u003c/em\u003e DG105 and \u003cem\u003eF. oxysporum\u003c/em\u003e DSH27 infected \u003cem\u003eA. sinensis\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003ea-d), \u003cem\u003eF. oxysporum\u003c/em\u003e DSH27 infected \u003cem\u003eC. pilosula\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003ee-h), and \u003cem\u003eF. solani\u003c/em\u003e HQ123 infected \u003cem\u003eA. mongholicus\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003ei-l). The dominant genus \u003cem\u003eMycothermus\u003c/em\u003e and some other genera considered to have the most beneficial taxa gained an increased degree of centrality due to the increased negative correlation with Fusarium and other pathogenic genera under \u003cem\u003eF. tricinctum\u003c/em\u003e DG105 and \u003cem\u003eF. solani\u003c/em\u003e HQ123 infected soils. In \u003cem\u003eC. pilosula\u003c/em\u003e, higher degree and betweenness centralities were observed under \u003cem\u003eF. oxysporum\u003c/em\u003e DSH27-infected rhizospheres. However, in \u003cem\u003eA. mongholicus\u003c/em\u003e, except under its original pathogen isolate \u003cem\u003eF. solani\u003c/em\u003e HQ123, beneficial considered genera such as \u003cem\u003eMycothermus, Trichoderma\u003c/em\u003e, and \u003cem\u003ePenicillium\u003c/em\u003e gained degree and betweenness increased centralities under \u003cem\u003eF. oxysporum\u003c/em\u003e DSH27 and \u003cem\u003eF. tricinctum\u003c/em\u003e DG105 which might be attributed to their less aggressiveness in \u003cem\u003eA. mongholicus\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003ei-l).\u003c/p\u003e\n \u003cp\u003eSoil physicochemical properties and rhizosphere microbial communities were associated with root rot incidence (DI) and severity (DS) in \u003cem\u003eA. sinensis, C. pilosula\u003c/em\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003e. In \u003cem\u003eA. sinensis\u003c/em\u003e, TC and AVP were significantly higher in \u003cem\u003eFusarium\u003c/em\u003e-infected soils (DSH27 and DG105) compared to healthy soils (p \u0026lt; 0.05). Microbial biomass nitrogen (MBN) showed an increasing trend in DG105- and HQ123-infected soils but was not statistically significant. In contrast, microbial biomass carbon (MBC) and phosphorus (MBP) significantly decreased under \u003cem\u003eF. oxysporum\u003c/em\u003e (DSH27) in \u003cem\u003eC. pilosula\u003c/em\u003e soils ( Table \u003cspan class=\"InternalRef\"\u003eS2\u003c/span\u003e and S3). The fungal genus \u003cem\u003eMycothermus\u003c/em\u003e was negatively correlated with DI and DS. In contrast, \u003cem\u003ePlectosphaerella\u003c/em\u003e and \u003cem\u003eunclassified_Ascomycota\u003c/em\u003e positively correlated with DI, DS, and MBC in \u003cem\u003eA. sinensis\u003c/em\u003e (Fig. \u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003em). DI and DS were negatively correlated with Mortierella and positively with \u003cem\u003eunclassified_Basidiomycota\u003c/em\u003e, as well as soil pH, Mn, and Zn (Fig. \u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003em). The bacterial genus \u003cem\u003eMicrococcaceae\u003c/em\u003e was positively linked to DI, DS, and AVP. In contrast, RB41 and \u003cem\u003eVicinamibacteraceae\u003c/em\u003e negatively correlated with DI and DS ( Fig. \u003cspan class=\"InternalRef\"\u003eS5\u003c/span\u003ea).\u003c/p\u003e\n \u003cp\u003eIn \u003cem\u003eC. pilosula\u003c/em\u003e, healthy soils had significantly higher TN, SOM, TC, and Fe compared to infected soils (p \u0026lt; 0.05) (Fig. \u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003en). The bacterial genus RB41 negatively correlated with DI and DS in HQ123- and DSH27-infected rhizospheres, while positively associated with AVP and total phosphorus (TP) ( Fig. \u003cspan class=\"InternalRef\"\u003eS5\u003c/span\u003eb). In \u003cem\u003eA. mongholicus\u003c/em\u003e, DI and DS negatively correlated with TN and Fe, while \u003cem\u003ePlectosphaerella\u003c/em\u003e and \u003cem\u003eFusarium\u003c/em\u003e positively correlated with disease severity (Fig. \u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003eo). \u003cem\u003eMicrococcaceae\u003c/em\u003e negatively correlated with DI and DS (p \u0026lt; 0.05) and was positively linked to higher Ca and Mn in DSH27-infected rhizospheres. Across all plant species, higher Zn levels correlated positively with \u003cem\u003eunclassified_Ascomycota\u003c/em\u003e and pathogenic \u003cem\u003eFusarium\u003c/em\u003e. Bacterial genera like \u003cem\u003eRB41\u003c/em\u003e, \u003cem\u003eVicinamibacteraceae\u003c/em\u003e, and \u003cem\u003eMDN1\u003c/em\u003e were negatively associated with DI and DS in \u003cem\u003eA. sinensis and C. pilosula\u003c/em\u003e rhizospheres ( Fig. \u003cspan class=\"InternalRef\"\u003eS5\u003c/span\u003e). \u003cem\u003eMicrococcaceae\u003c/em\u003e negatively correlated with DI and DS (p \u0026lt; 0.05) and was positively linked to higher Ca and Mn in DSH27-infected \u003cem\u003eA. mongholicus\u003c/em\u003e rhizospheres.\u003c/p\u003e\n \n \n \n \n \n \n \n \n \n \n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eCrop rotation significantly influences the dynamics of rhizosphere and plant microbiomes by altering soil conditions, improving microbial diversity, and disrupting the life cycles of soil-borne pathogens (Gahagan et al., 2023; Maarastawi et al., 2018). However, it can also facilitate cross-infection through plant residues, creating similarities in rhizosphere microbiome composition across cropping systems (Kerdraon et al., 2019). This study reveals the successful cross-infection and pathogenicity of \u003cem\u003eFusarium\u003c/em\u003e species among \u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003e, demonstrating host-specific aggressiveness. Additionally, Fusarium infection altered rhizosphere microbial networks, decreased AMF abundance, and disrupted soil physicochemical properties, collectively exacerbating disease severity across these medicinal herbs. These \u003cem\u003eFusarium\u003c/em\u003e species were prevalent across plant species, with \u003cem\u003eFusarium oxysporum\u003c/em\u003e species complex (FOSC) primarily associated with \u003cem\u003eC. pilosula\u003c/em\u003e, \u003cem\u003eFusarium solani\u003c/em\u003e species complex (FSSC) with \u003cem\u003eA. mongholicus\u003c/em\u003e, and \u003cem\u003eFusarium tricinctum\u003c/em\u003e species complex (FTSC) with \u003cem\u003eA. sinensis\u003c/em\u003e, underscoring their host specificity and adaptability to different rhizosphere environments. The morphological and phylogenetic similarities among \u003cem\u003eFusarium\u003c/em\u003e isolates highlight their evolutionary adaptability, facilitating survival in soil and plant debris during off-seasons (Leslie and Summerell, 2006). Their shared conidial curvature, dense conidial masses, and rapid mycelial growth enhance persistence and cross-infective potential. \u003cem\u003eFusarium\u003c/em\u003e species endure unfavorable conditions such as chlamydospores or dormant mycelia, which later infect successive crops (Gordon \u0026amp; Martyn, 1997; Summerell, 2019). This adaptability aligns with findings that biochemical changes in the rhizosphere soil due to crop rotations influence pathogen survival and infection dynamics (Peralta et al., 2018; Yan et al., 2023), underscoring their role in cross-pathogenicity in medicinal herb systems.\u003c/p\u003e\u003cp\u003eThe study revealed that \u003cem\u003eFusarium\u003c/em\u003e species complexes exhibited significant variances in aggressiveness toward distinct medicinal herb hosts during pathogenesis. \u003cem\u003eF. tricinctum\u003c/em\u003e was the most aggressive towards \u003cem\u003eA. sinensis\u003c/em\u003e, exhibiting moderate aggressiveness on \u003cem\u003eC. pilosula\u003c/em\u003e and less aggressiveness on \u003cem\u003eA. mongholicus\u003c/em\u003e. According to its diverse host range and involvement in root rot, crown rot, and blight diseases in temperate crops and medicinal herb plants, \u003cem\u003eF. tricinctum\u003c/em\u003e ability to infect many host plants indicates its flexibility and the difficulty in managing this pathogen in intercropped situations. (Liu et al., 2022; Uwaremwe et al., 2021; Wang et al., 2022). Similarly, \u003cem\u003eF. solani\u003c/em\u003e was highly aggressive to \u003cem\u003eA. mongholicus\u003c/em\u003e, moderately aggressive to \u003cem\u003eA. sinensis\u003c/em\u003e, and less aggressive to \u003cem\u003eC. pilosula\u003c/em\u003e, confirming its pathogenicity in severe \u003cem\u003eA. mongholicus\u003c/em\u003e root rots, as well as cross-pathogenicity on other medicinal herbs (Wang et al., 2022) and its cross-pathogenic effects on several different medicinal herbs (Xu et al., 2021). The observed difference in aggressiveness is consistent with earlier research revealing that \u003cem\u003eF. solani\u003c/em\u003e exploits harsh host environmental conditions to generate systemic infections with serious economic repercussions (Xi et al., 2023). Furthermore, \u003cem\u003eF. oxysporum\u003c/em\u003e was highly aggressive towards \u003cem\u003eC. pilosula\u003c/em\u003e but less hostile towards the other two hosts. This discovery is consistent with its documented potential to induce root rot and wilt symptoms in \u003cem\u003eC. pilosula\u003c/em\u003e and a variety of medicinal crops in Gansu Province (Liu et al., 2024; Zhao et al., 2021). Soil and plant residues are frequent habitats for \u003cem\u003eFusarium\u003c/em\u003e species, which might serve as a pathway for cross-infection among plants cultivated consecutively (Yan et al., 2023). These findings illustrate the intricate ecological and evolutionary interactions between \u003cem\u003eFusarium\u003c/em\u003e species and their plant hosts, demonstrating that variations in aggressiveness reflect not only host adaptations but also environmental and management factors.\u003c/p\u003e\u003cp\u003eVariability in the pathogenicity of \u003cem\u003eFusarium\u003c/em\u003e species among hosts highlights the dual nature as both host-specific and cross-infective, aligning with Moparthi et al. (2020) and (2021), whose greenhouse study in Montana demonstrated that shared \u003cem\u003eFusarium\u003c/em\u003e inocula led to cross-pathogenicity among pulse and cereal crops. Our study showed that \u003cem\u003eF. tricinctum\u003c/em\u003e exhibited the highest level of aggressiveness towards its primary host, \u003cem\u003eA. sinensis\u003c/em\u003e, with a subsequent reduction in impact observed on \u003cem\u003eC. pilosula\u003c/em\u003e and \u003cem\u003eA. mongholicus\u003c/em\u003e. Similarly, \u003cem\u003eF. oxysporum\u003c/em\u003e and \u003cem\u003eF. solani\u003c/em\u003e exhibited higher aggressiveness on their native hosts compared to cross-inoculated plants. Interestingly, on the excised root tissues cross-pathogenicity test, the highest cross-infection severity of \u003cem\u003eF. solani\u003c/em\u003e HQ123 observed in \u003cem\u003eA. sinensis\u003c/em\u003e aligns with previous reports on its strong pathogenic adaptability across diverse hosts (Nie et al., 2020; Zhang et al., 2021). The observed patterns indicate that although \u003cem\u003eFusarium\u003c/em\u003e spp. preferentially infect their native hosts, they exhibit adaptability that allows them to infect other plant species, which may pose challenges for disease management in intercropping systems. The symptomatology observed in stained tissues provided clear indicators for distinguishing host-pathogen interactions, characterized by significant degradation, necrosis, and vascular discoloration in primary hosts aligned with the observed higher aggressiveness of their original \u003cem\u003eFusarium\u003c/em\u003e isolates. In contrast, cross-infections resulted in localized damage and restricted pathogen penetration, suggesting a degree of host resistance, aligning with earlier findings suggesting that increased lignification and diminished pathogen spread represent a common reaction in non-primary hosts (Jian et al., 2024; Olivain et al., 2006). These observations highlight the presence of fungal hyphae and intermediate levels of necrosis in cross-infected plants, further indicating the potential for \u003cem\u003eFusarium\u003c/em\u003e spp. to persist in alternate hosts, facilitating inoculum buildup and disease persistence in diverse cropping systems. These results emphasize the ecological implications of cross-pathogenicity, where even weak infections can serve as reservoirs for inoculum and drive pathogen evolution.\u003c/p\u003e\u003cp\u003eThe sequencing analysis of fungal and bacterial communities across \u003cem\u003eFusarium\u003c/em\u003e-infected and non-infected rhizosphere and bulk soils in \u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003e revealed significant shifts in microbial diversity and community structure. While non-infected rhizospheres exhibited higher raw reads and OTU counts, fungal alpha diversity indices (Shannon, Simpson, Chao1, ACE) showed no significant differences between infected and non-infected rhizospheres, consistent with findings of Solis-Garcia et al. (2021), where pathogen presence did not universally alter alpha diversity but influenced microbial dynamics. Conversely, Zhou et al. (2019) observed higher fungal and bacterial richness and diversity in diseased soils compared to healthy soils. However, a significant reduction was explicitly observed in the bacterial community in \u003cem\u003eF. oxysporum\u003c/em\u003e DSH27-infected \u003cem\u003eA. sinensis\u003c/em\u003e, suggesting that pathogen presence can induce modifications in the rhizosphere bacterial communities and reduce overall microbial diversity. On the contrary, beta diversity analyses indicated apparent community clustering in \u003cem\u003eFusarium\u003c/em\u003e-infected plants, highlighting pathogen-induced shifts in rhizosphere ecology, particularly pronounced in \u003cem\u003eA. sinensis\u003c/em\u003e. These observations align with studies showing that pathogen colonization reshapes rhizosphere microbial communities and their functional potential (Mendes et al., 2011; Séguin et al., 2014). Beta-diversity, reflecting variations across environmental contexts, emerges as a more sensitive indicator of community structure changes compared to alpha-diversity, which may remain stable despite fluctuations in beta-diversity (Turatsinze et al., 2021; Walters and Martiny, 2020). Our findings highlight the importance of beta diversity in capturing the broader ecological impacts of microbial community shifts induced by pathogen activity. Pathogen-driven community restructuring was evident in the increased abundance of fungal phyla like Chytridiomycota in \u003cem\u003eA. sinensis\u003c/em\u003e and Rozellomycota in \u003cem\u003eC. pilosula\u003c/em\u003e. Pathogenic genera such as \u003cem\u003eFusarium\u003c/em\u003e, \u003cem\u003ePlectosphaerella\u003c/em\u003e, and \u003cem\u003eAlternari\u003c/em\u003ea, and beneficial taxa, including \u003cem\u003eMortierella\u003c/em\u003e, gained betweenness centrality in \u003cem\u003eA. sinensis\u003c/em\u003e infected soils microbial networks compared to other plant species signifying affected roles under \u003cem\u003eFusarium\u003c/em\u003e infection. These plant species-dependent network changes, coupled with the increased inter-community links observed under \u003cem\u003eFusarium\u003c/em\u003e-infected rhizospheres, aligns with the findings by (Mendes et al., 2023), who reported cultivar-dependent impaired modularity between under disease-suppressive and \u003cem\u003eFusarium\u003c/em\u003e-infection, resulting in reduced functional compartmentalization, resilience and stability of the rhizosphere microbial network (Tang et al., 2020), which is crucial for plant health and soil ecosystem services.\u003c/p\u003e\u003cp\u003eNotably, the rhizosphere microbiota, a complex ecosystem of fungi and bacteria, plays a pivotal role in shaping plant-pathogen interactions and mediating plant health (Berendsen et al., 2012). In this study, \u003cem\u003eFusarium\u003c/em\u003e infection significantly altered the rhizosphere microbial composition and functional dynamics across \u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003e, increasing the abundance of pathotrophic fungal genera such as \u003cem\u003eFusarium\u003c/em\u003e and \u003cem\u003ePlectosphaerella\u003c/em\u003e, particularly in \u003cem\u003eF. solani\u003c/em\u003e-infected \u003cem\u003eA. sinensis\u003c/em\u003e. These shifts were positively associated with an increase in disease severity, which is consistent with previous studies linking pathogen-induced perturbations in rhizosphere communities to disease development (Mendes et al., 2013). \u003cem\u003eFusarium\u003c/em\u003e infection led to a decline in beneficial symbiotrophic and saprotrophic fungi, notably arbuscular mycorrhizal fungi (AMF). Under \u003cem\u003eF. solani\u003c/em\u003e infection, \u003cem\u003eA. sinensis\u003c/em\u003e showed significant decreases. The decreased abundance of AMF under pathogen stress emphasizes its crucial role in nutrient uptake and disease suppression (Spagnoletti et al., 2021; Xiong et al., 2017). In this study, root rot was aggravated by a functional imbalance that promoted pathogen multiplication, as demonstrated by decreased AMF functional profiles and increased pathotrophic dominance. These findings are consistent with studies indicating competition with pathogenic fungi (Compant et al., 2005), shifts in root exudates (Jin et al., 2024), and toxins accumulation (Deveau et al., 2018) as potential drivers of microbial community shifts. Under \u003cem\u003eFusarium\u003c/em\u003e infection, bacterial communities underwent considerable alterations, including a decline in the abundance of beneficial taxa such as \u003cem\u003eRB41\u003c/em\u003e and \u003cem\u003eVicinamibacteraceae\u003c/em\u003e, These species, which are favorably associated with soil health indicators like total phosphorus (TP) and nitrogen (TN) but negatively correlated with disease severity, are expected to help with pathogen suppression. Similar to Lee et al. (2021), the disruption of bacterial phyla such as Actinobacteria and Verrucomicrobiota emphasizes the disruptive impact of \u003cem\u003eFusarium\u003c/em\u003e species infection on microbial networks that are critical for rhizosphere resilience.\u003c/p\u003e\u003cp\u003eIntriguingly, \u003cem\u003eFusarium\u003c/em\u003e infection significantly altered the microbial networks within the rhizosphere, leading to an increase in the centrality and abundance of pathogenic genera such as Fusarium, Alternaria, and \u003cem\u003ePlectosphaerella\u003c/em\u003e while concurrently reducing the populations of beneficial taxa such as Trichoderma and arbuscular mycorrhizal fungi (AMF). In \u003cem\u003eA. sinensis\u003c/em\u003e infected with \u003cem\u003eF. solani\u003c/em\u003e (HQ123), AMF populations exhibited a notable decrease, highlighting the capacity of \u003cem\u003eFusarium\u003c/em\u003e species to interfere with vital symbiotic and saprotrophic functions that are essential for plant resilience. The observed disruptions coincide with the findings of \u003cem\u003eFusarium\u003c/em\u003e-induced imbalances in microbial communities within the rhizosphere (Kudjordjie et al., 2022) and the pathotrophic dominance identified in diseased soils (Byers et al., 2020). These results indicate a restructuring within the soil ecosystem that promotes the prevalence of pathogens, simultaneously diminishing microbial diversity and functional stability. Consistent with the findings of Liu et al. (2024), these changes suggest a shift from symbiotrophy and saprotrophy to pathotrophy, adversely impacting nutrient cycling and the capacity of plants to withstand stress. Centrality shifts suggest that beneficial taxa, even with their negative correlation to pathogens, may assume compensatory roles, as evidenced by Trichoderma and Penicillium. Moreover, changes in KEGG pathways underscore their impact on metabolism, transcription, and immune responses, reinforcing the conclusions of Wang et al. (2024) about the influence of microbial interactions on ecosystem functions. These results emphasize the significant role of \u003cem\u003eFusarium\u003c/em\u003e spp. in reshaping microbial networks, with critical implications for plant health and the functioning of the rhizosphere ecosystem. Thus highlighting the importance of effective management of fungal pathogens to maintain the rhizosphere resilience and stability.\u003c/p\u003e\u003cp\u003eThe association between microbial community dynamics and soil physicochemical properties in the context of Fusarium infection is multifaceted, impacting both root rot disease severity and the overall health of rhizosphere ecosystems. In this study, Fusarium infections disrupted the equilibrium of soil properties in \u003cem\u003eA. sinensis\u003c/em\u003e, leading to significant increases in total carbon (TC) and available phosphorus (AVP) levels. This elevation in AVP may indicate pathogen-induced organic phosphorus mineralization, which tends to suppress phosphorus-immobilizing microbes as seen in soil systems affected by pathogen stress, supporting findings in specific Fusarium studies (Yan et al., 2023). Additionally, the increased TC levels could be attributed to altered root exudation patterns and the accumulation of metabolites triggered by pathogen interactions, consistent with findings that demonstrate changes in carbon cycling due to Fusarium invasion (Yu et al., 2015; Du et al., 2019). Microbial biomass carbon (MBC), a key indicator of microbial activity and soil health, declined significantly in \u003cem\u003eF. oxysporum\u003c/em\u003e-infected \u003cem\u003eC. pilosula\u003c/em\u003e soils, suggesting that pathogen invasion may suppress beneficial microbial populations while favoring disease-promoting taxa. This aligns with studies showing that root disease reduces microbial biomass and alters community structures, favoring pathogenic over beneficial microbes (Guo et al., 2024; Ye et al., 2023). The decline in microbial biomass carbon (MBC) and phosphorus (MBP) in \u003cem\u003eF. tricinctum\u003c/em\u003e DG105-infected \u003cem\u003eC\u003c/em\u003e. \u003cem\u003epilosula\u003c/em\u003e rhizosphere soils suggests a disruption in microbial equilibrium, leading to reduced nutrient cycling and microbial diversity, which weakens disease suppression and soil quality (Tian et al., 2021; Xiong et al., 2017; Guo et al., 2023). In contrast, the increase in microbial biomass nitrogen (MBN) may indicate a shift in microbial composition, where nitrogen-retaining microbes persist despite pathogen stress, potentially due to altered root exudation patterns or microbial competition dynamics (Zhao et al., 2018; Zhou et al., 2019). These shifts highlight the complex interactions between Fusarium infection and microbial resilience, emphasizing the cascading effects of pathogen-induced stress on soil health and nutrient dynamics (Tang et al., 2023). The imbalance suggested by these microbial biomass shifts indicates that while Fusarium infection disrupts carbon and phosphorus cycling, it may inadvertently create conditions favoring nitrogen-retaining microbes.\u003c/p\u003e\u003cp\u003eConversely, the healthy rhizospheres in \u003cem\u003eC. pilosula\u003c/em\u003e and \u003cem\u003eA. sinensis\u003c/em\u003e showcased greater total nitrogen (TN) and soil organic matter (SOM) concentrations, reinforcing research that correlates pathogen activity with diminutions in nitrogen-fixing and SOM-enhancing microbes (Lilai et al., 2021). The observations from \u003cem\u003eA. mongholicus\u003c/em\u003e indicated a complex response post-Fusarium infection, where TN and SOM levels increased, likely driven by root exudates that enhance microbial turnover, paralleling findings that highlight the role of microbial dynamics in nutrient cycling (Zhang et al., 2017). Notably, reduced levels of trace elements such as iron (Fe) and manganese (Mn) are critical for plant defense mechanisms and were observed in the infected rhizospheres of \u003cem\u003eC. pilosula\u003c/em\u003e and \u003cem\u003eA. mongholicus\u003c/em\u003e, aligning with studies that link pathogen action to the modification of nutrient availability through microbial interactions (Zhong et al., 2024). The relationship between potassium (K) levels and disease severity observed in \u003cem\u003eA. mongholicus\u003c/em\u003e further reflects the nuanced role of soil nutrients, where potassium can exhibit both protective and detrimental qualities (Xiao et al., 2016). Moreover, the positive correlations detected between soil pH and disease severity in \u003cem\u003eF. tricinctum\u003c/em\u003e DG105-infected \u003cem\u003eC. pilosula\u003c/em\u003e underscore the influence of soil chemistry on pathogen dynamics, where alkaline conditions might reduce micronutrient solubility, thus potentially compromising plant immunological responses against pathogens (Calvo et al., 2022). Collectively, these findings elucidate the intricate interplays among soil properties, microbial communities, and root rot disease progression, suggesting that maintaining soil health is paramount in mitigating the adversities posed by pathogenic agents like \u003cem\u003eFusarium\u003c/em\u003e species.\u003c/p\u003e\u003cp\u003eOverall, our study identified \u003cem\u003eF. tricinctum\u003c/em\u003e as the primary pathogen affecting \u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eF. oxysporum\u003c/em\u003e in \u003cem\u003eC. pilosula\u003c/em\u003e, and \u003cem\u003eF. solani\u003c/em\u003e in \u003cem\u003eA. mongholicus\u003c/em\u003e. Each of the three \u003cem\u003eFusarium\u003c/em\u003e pathogens demonstrated successful cross-infection and pathogenicity, contributing to the onset of root rots and wilts across these medicinal herbs with varied levels of aggressiveness. The observed differences in disease severity, where \u003cem\u003eA. sinensis\u003c/em\u003e and \u003cem\u003eC. pilosula\u003c/em\u003e exhibited the highest susceptibility and \u003cem\u003eA. mongholicus\u003c/em\u003e the lowest, suggest that plant-specific physiological traits, such as differential lignification, root architecture, root exudate composition, and immune response efficiency, play a crucial role in determining resistance levels against \u003cem\u003eFusarium\u003c/em\u003e spp. infection. The finer, moisture-retaining roots of \u003cem\u003eA. sinensis\u003c/em\u003e and \u003cem\u003eC. pilosula\u003c/em\u003e may facilitate pathogen colonization, whereas the thicker, more lignified taproots of \u003cem\u003eA. mongholicus\u003c/em\u003e likely provide a structural barrier to infection (Bai et al., 2022; Liao et al., 2019). Changes in microbial networks within the rhizosphere caused by \u003cem\u003eFusarium\u003c/em\u003e infection were characterized by an increase in pathotrophic fungal activities and a disruption of symbiotic fungi like AMF, which are crucial for nutrient cycling and disease management. The findings underscore the complex characteristics of \u003cem\u003eFusarium\u003c/em\u003e cross-pathogenicity, which involves not only the direct interactions between hosts and pathogens but also significant impacts from rhizosphere dynamics and environmental factors (Li et al., 2021; Mendes et al., 2013; Solis-Garcia et al., 2021). Notably, rhizosphere microbial community shifts, particularly reductions in arbuscular mycorrhizal fungi (AMF) abundance, were negatively correlated with \u003cem\u003eFusarium\u003c/em\u003e infection, highlighting AMF's critical role in disease suppression and rhizosphere stability. These changes align with shifts in soil physicochemical properties, such as elevated TC and AVP in infected soils, which likely result from pathogen activity and altered root exudation. The interplay between reduced trace elements like Fe and Mn and increased TK and pH highlights the multifaceted impacts of \u003cem\u003eFusarium\u003c/em\u003e infection on plant defense mechanisms. These findings underscore the importance of AMF-based strategies and integrated soil management practices in sustaining rhizosphere resilience and reducing \u003cem\u003eFusarium\u003c/em\u003e-induced disease progression. However, despite these insights, root exudates are pivotal in shaping rhizosphere microbial communities and influencing pathogen behavior (Bertin et al., 2003; Dhungana et al., 2023), yet their compositional and functional variability across plant species and environmental conditions remains underexplored. Our study leaves open questions regarding the role of root exudates in \u003cem\u003eFusarium\u003c/em\u003e infection dynamics and cross-pathogenicity. Future research should explore root exudate profiles to unravel their role in shaping microbial interactions and pathogen behavior, providing insights into effective disease management strategies in medicinal and agricultural systems.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eOur cross-inoculation and pathogenicity evaluations confirmed the ability of root-recovered \u003cem\u003eFusarium\u003c/em\u003e species to cause root rot among rotational medicinal herbs and influence soil microbiome structure and function in relation to disease severity. Specifically, \u003cem\u003eF. oxysporum\u003c/em\u003e, \u003cem\u003eF. solani\u003c/em\u003e, and \u003cem\u003eF. tricinctum\u003c/em\u003e exhibited varying levels of host-specific aggressiveness and cross-pathogenicity in \u003cem\u003eA. sinensis\u003c/em\u003e, \u003cem\u003eC. pilosula\u003c/em\u003e, and \u003cem\u003eA. mongholicus\u003c/em\u003e. These infections increased root rot severity and disrupted soil microbial balance, reducing beneficial symbiotrophic microbes, such as arbuscular mycorrhizal fungi (AMF), while favoring pathotrophic fungi, indicating the importance of beneficial microbes, particularly AMF, in mitigating \u003cem\u003eFusarium\u003c/em\u003e-induced root rot. Furthermore, key soil properties, including total nitrogen, organic matter, total carbon, available phosphorus, and essential nutrients (iron, zinc, and manganese), were linked to disease incidence and severity, underscoring their role in pathogen-host interactions. Our findings demonstrated that crop rotation alone is insufficient for managing pathogenic \u003cem\u003eFusarium\u003c/em\u003e spp., necessitating complementary strategies to prevent pathogen spread via infected seedlings and promote beneficial microbes like AMF. For growers, integrating AMF-based biocontrol approaches to optimize soil nutrient management is a crucial step. Given the potential impact of \u003cem\u003eFusarium\u003c/em\u003e spp. on regional crops such as potatoes and maize, adopting integrated soil microbiome management practices is essential for sustainable agricultural productivity.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eANT:\u003c/strong\u003e Investigation, Conceptualization, Methodology, Data curation, Visualization, Validation, Formal analysis, Writing original draft, Writing, review \u0026amp; editing. \u003cstrong\u003eAY\u003c/strong\u003e: Methodology, Data curation, Investigation, Visualization. \u003cstrong\u003eXX:\u003c/strong\u003e Investigation, Visualization, Formal analysis. \u003cstrong\u003eGC:\u003c/strong\u003e Conceptualization, Investigation, Methodology, Visualization. \u003cstrong\u003eYW:\u003c/strong\u003e Investigation, Conceptualization, Visualization, Formal analysis. \u003cstrong\u003eLY:\u003c/strong\u003e Investigation, Methodology, Visualization. \u003cstrong\u003eQZ:\u003c/strong\u003e Investigation, Methodology, Visualization. \u003cstrong\u003eLW:\u003c/strong\u003e Visualization, Formal analysis. \u003cstrong\u003eMZ:\u003c/strong\u003e Investigation, Visualization.\u003cstrong\u003e\u0026nbsp;ZZ:\u003c/strong\u003e Methodology, Data curation, Visualization, Formal analysis. \u003cstrong\u003eJZ:\u003c/strong\u003e Methodology, Data curation, Visualization. \u003cstrong\u003eYS:\u0026nbsp;\u003c/strong\u003eInvestigation, Visualization.\u003cstrong\u003e\u0026nbsp;YZ:\u003c/strong\u003e Visualization, Validation. \u003cstrong\u003eRW:\u003c/strong\u003e Conceptualization, Methodology, Validation, Formal analysis, Resources, Supervision, Writing – Review \u0026amp; editing, Funding acquisition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have confirmed that there are no financial or personal interests to be declared.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Project of the International Partnership Program of the Chinese Academy of Sciences (grant number 315GJHZ2024123GC), Key Research and Development Projects of Ningxia Hui Autonomous Region (grant number 2022BBF02031), and the Science and Technology Planning Project of Gansu Province (grant number 23JRRA575, 25JRRA524).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available on request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdamberg K, Tomson K, Talve T, Pudova K, Puurand M, Visnapuu T, Alam\u0026auml;e T, Adamberg S (2015) Levan enhances associated growth of Bacteroides, Escherichia, Streptococcus and Faecalibacterium in fecal microbiota. 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Front Microbiol 13. https://doi.org/10.3389/fmicb.2022.1015038\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"plant-and-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plso","sideBox":"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)","snPcode":"11104","submissionUrl":"https://submission.nature.com/new-submission/11104/3","title":"Plant and Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Medicinal herbs, Fusarium root rot, Fusarium species, cross-pathogenicity, rhizosphere soil microbiome, metagenome sequencing","lastPublishedDoi":"10.21203/rs.3.rs-5926386/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5926386/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eBackground and Aims\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFusarium root rot and wilt affect medicinal herbs in Gansu Province, China, despite extended crop rotations. This study investigated the cross-pathogenicity of \u003cem\u003eFusarium\u003c/em\u003especies isolated from \u003cem\u003eAngelica sinensis \u003c/em\u003e(Danggui), \u003cem\u003eCodonopsis pilosula \u003c/em\u003e(Dangshen), and \u003cem\u003eAstragalus mongholicus\u003c/em\u003e (Huangqi).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOf 83 fungal isolates recovered, 69.8% were identified as \u003cem\u003eFusarium\u003c/em\u003e spp., through ITS, TEF1-α, and RPB2 sequencing, clustering into \u003cem\u003eFusarium oxysporum\u003c/em\u003e (FOSC, 36.2%), \u003cem\u003eFusarium solani\u003c/em\u003e (FSSC, 31%), and \u003cem\u003eFusarium tricinctum\u003c/em\u003e (FTSC, 22.4%) species complexes. Representative strains (\u003cem\u003eF. oxysporum\u003c/em\u003e DSH27, \u003cem\u003eF. solani\u003c/em\u003eHQ123, \u003cem\u003eF. tricinctum\u003c/em\u003e DG105) were tested for cross-pathogenicity in greenhouse and field trials. Rhizosphere microbial dynamics, including fungal and bacterial community diversity, functional guilds, and soil physicochemical properties, were analyzed.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFusarium\u003c/em\u003estrains exhibited varying aggressiveness, highest on original hosts, while cross-infective hosts showed less to moderate severity. Infections disrupted rhizosphere networks, increasing pathotrophic dominance over arbuscular mycorrhizal functions. Sequencing showed reduced fungal and bacterial operational taxonomic units (OTUs), with distinct clustering of infected vs. non-infected rhizospheres. Pathogenic fungal genera \u003cem\u003eFusarium\u003c/em\u003e positively correlated with disease incidence, while beneficial fungal genera \u003cem\u003eMortierella\u003c/em\u003e and bacterial genera \u003cem\u003eRB41\u003c/em\u003e showed negative correlations. Infected soils exhibited significant changes in total carbon, available phosphorus, manganese, and zinc, correlating with microbial dynamics and disease severity.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study links Fusarium cross-infection with rhizosphere microbial network disruptions, including the loss of arbuscular mycorrhizal fungi (AMF) functions under altered soil physicochemical conditions in medicinal herbs. These findings uncover the systematic cross-pathogenicity of \u003cem\u003eFusarium\u003c/em\u003e species, highlighting the need for AMF-based strategies and integrated soil management to mitigate its impact.\u003c/p\u003e","manuscriptTitle":"Fusarium cross-infection in medicinal herbs alters rhizosphere microbiomes and disrupts mycorrhizal functions under soil physicochemical imbalances","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-03 14:19:09","doi":"10.21203/rs.3.rs-5926386/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accept","date":"2025-04-23T04:48:17+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-04-02T13:48:38+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-02T08:16:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-27T06:05:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"Plant and Soil","date":"2025-03-26T13:52:47+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"plant-and-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plso","sideBox":"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)","snPcode":"11104","submissionUrl":"https://submission.nature.com/new-submission/11104/3","title":"Plant and Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"82ec97c7-07a1-45b7-8012-35cba44865d5","owner":[],"postedDate":"April 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-12T16:05:47+00:00","versionOfRecord":{"articleIdentity":"rs-5926386","link":"https://doi.org/10.1007/s11104-025-07504-5","journal":{"identity":"plant-and-soil","isVorOnly":false,"title":"Plant and Soil"},"publishedOn":"2025-05-08 15:56:59","publishedOnDateReadable":"May 8th, 2025"},"versionCreatedAt":"2025-04-03 14:19:09","video":"","vorDoi":"10.1007/s11104-025-07504-5","vorDoiUrl":"https://doi.org/10.1007/s11104-025-07504-5","workflowStages":[]},"version":"v1","identity":"rs-5926386","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5926386","identity":"rs-5926386","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}