Revealing the nanoscale structural evolution of electrocatalysts under realistic acidic oxygen evolution reaction (OER) conditions remains a major challenge. Here, we report the tracking of the evolution of the same individual iridium (Ir) nanocatalysts during prolonged acidic OER by developing identical-location transmission electron microscopy (IL‑TEM). The Ir nanocatalysts dispersed on a TEM grid serving as a working electrode are examined before and after OER operation. We find that the deposition of Au nanoparticles and the formation of SnO2 nanoclusters occur when a conventional holey carbon-film-supported gold (Au) grid is used at 1.7 V versus the reversible hydrogen electrode (VRHE), which obscure the identification of genuine Ir reconstruction. By coating the Au grid with Pt to form a stabilized working electrode, these artifacts are effectively suppressed for up to 2.5 h, enabling direct visualization of the nanoscale evolution of Ir nanocatalysts. Control measurements further confirm that the electrochemical response of Ir nanocatalysts on Pt-coated grids is dominated by the Ir catalysts rather than the Pt support. This study demonstrates that IL-TEM provides a practical approach for probing catalyst evolution in harsh, prolonged acidic environments by tracking the same nanocatalysts over extended reaction times, complementing in situ and operando TEM techniques.
Marine bacteria alternate between planktonic and surface-attached lifestyles, facing continuous phage predation. However, how these lifestyles shape resistance evolution remains poorly understood. Using a Roseobacter model strain, we demonstrate that surface-attached populations exhibit 26-fold higher survivability than planktonic counterparts during lytic phage infection. This advantage emerges through the evolution of heterogeneous subpopulations exhibiting diverse resistance phenotypes, a pattern absent in planktonic populations. Whole-genome sequencing of 139 heritable phage-resistant mutants revealed fundamentally divergent mutational patterns, with planktonic populations predominantly harboring tandem repeat mutations, whereas surface-attached populations favor non-coding mutations. Despite this, both lifestyles independently converged on mutations in the CtrA phosphorelay system, identifying CtrA as a previously unrecognized evolutionary target of phage-driven selection and triggering planktonic-to-surface-attached switch. Further analyses revealed systematic downregulation of motility genes and enhancement of biofilm formation, mechanistically linking phage resistance to lifestyle transitions. The identified CtrA mutations occur in regions highly conserved across ecologically important marine Alphaproteobacteria (Rhodobacterales) that are known to switch between planktonic and surface-attached states, suggesting lifestyle-dependent evolutionary trajectories may broadly shape phage resistance in marine ecosystems.
Despite the phenotypic diversity of animal species, the basic anatomical features, or body plan, of each animal phylum have been strictly conserved since their initial establishment in the early Cambrian. While this remarkable conservation could be explained by the conservation of the mid-embryonic phase (the developmental hourglass model) when the body plan is established, the underlying evolutionary mechanisms remained largely unclear. In this respect, recent studies have highlighted intrinsic properties in development, such as robustness, stability, and pleiotropic constraints, as potential contributors to its limitation of phenotypic diversifications. These findings suggest a potential mechanism of how phenotypic evolution is intrinsically limited or biased. In this review, potential developmental factors that contributed to the intrinsic limiting effects of animal embryogenesis against phenotypic diversification will be overviewed, with a particular focus on the general relationship between evolution and developmental processes.
Daihai Lake, a typical closed inland lake in the arid and semi-arid region of Inner Mongolia, has been subject to two consecutive years of ecological water replenishment to mitigate its severe ecological degradation. While the lake water level has risen and wetland ecosystems have been gradually restored, existing studies have predominantly focused on changes in lake water quality, leaving a critical research gap regarding the hydrochemical evolution, formation mechanisms, and drinking water safety risks of groundwater in the plain area of the Daihai Lake Basin under the dynamic conditions of ongoing water replenishment. To fill this gap, this study systematically analyzed the hydrochemical characteristics and formation mechanisms of groundwater in the study area, and conducted a comprehensive groundwater quality assessment. A suite of representative groundwater samples were collected from the study area after two years of ecological water replenishment, and analyzed using an integrated set of methods including Self-Organizing Map (SOM) clustering, hydrochemical graphical analysis, ion ratio analysis, multivariate statistical analysis, and the Entropy-weighted Water Quality Index (EWQI) method. The results show that: (1) Groundwater is divided into three clusters via SOM, with distinct ion sources from carbonate/silicate weathering and halite dissolution across clusters; some samples have excess SO₄2- and HCO₃-, requiring additional cations for charge balance. (2) Groundwater evolution is jointly controlled by water-rock interaction and evaporative concentration, with limited influence from atmospheric precipitation. (3) Three high-fluoride enrichment mechanisms are identified: mineral dissolution under weakly alkaline conditions, evaporative concentration-driven F⁻ enrichment, and accelerated dissolution of fluorine-bearing minerals induced by acidic mining wastewater. (4) 89% of Cluster-3 groundwater meets drinking standards (EWQI < 50), while 70% of groundwater samples from Cluster 1 and Cluster 2 are of poor quality, mainly distributed in the southwestern lakeshore. This study systematically elucidates the hydrochemical characteristics and formation mechanisms of groundwater in the Daihai Lake Basin under continuous ecological water replenishment, identifies key risk zones for groundwater quality, and provides a solid scientific basis for the protection and sustainable utilization of regional groundwater resources, as well as the optimization of ecological water replenishment strategies in similar arid and semi-arid inland lake basins.
Representatives of the phylum Methanobacteriota occur in various anoxic environments, but only members of the genera Methanosphaera and Methanobrevibacter exclusively colonize the digestive tract of animals. Recent phylogenomic analyses revealed that the genus Methanobrevibacter, which harbors the majority of the intestinal species, is severely underclassified and represents a family-level taxon, "Methanobrevibacteraceae", that evolved entirely in the digestive tract of animals. Comparative genome analysis of 158 species of Methanobacteriota, including uncultured representatives in the Genome Taxonomy Database (GTDB), demonstrated that the intestinal lineages are clearly separated from the remaining members of the phylum. They differ from the non-intestinal lineages in genome size, GC content, coding density, an increased number of pseudogenes and adhesin-like proteins, and show numerous adaptations to the copiotrophic gut environment. A decreased biosynthetic potential led to a dependence on other community members and limits the dispersal of intestinal species into other habitats, which is reflected in coevolutionary patterns with their major host groups among arthropods, ungulates, and primates. Certain lineages even engaged in symbiotic associations with intestinal protists, presumably benefiting from the H2 produced by the hydrogenosomes of their anaerobic hosts. Our results reveal that the transition of free-living Methanobacteriota to a host-associated lifestyle involves the same genomic changes that were previously recognized in gut bacteria and bacterial endosymbionts of protists, reflecting resemblances between the two prokaryotic domains that are caused by evolutionary convergence in similar environments.
The investigation of neural circuit dynamics faces a fundamental challenge: existing tools cannot simultaneously achieve cellular resolution, millimeter-depth penetration, and compatibility with freely behaving subjects. Electrophysiology offers temporal precision at depth, while advanced microscopy provides superb resolution, but is physically constrained to superficial layers or head-fixed preparations. In this review, we propose that implantable photonic devices are emerging as the critical solution to address this challenge. We first critically examine the evolution of electrophysiology and microscopic imaging, establishing their inherent trade-offs. We then detail how integrated photonic probes, leveraging semiconductor innovations like single-photon avalanche diode (SPAD) arrays and µLEDs, enable optical sensing and manipulation deep within the brain of behaving animals. By establishing frameworks to compare important performance and synthesizing the latest research, we provide analysis of this transformative shift. Finally, we outline the multidisciplinary challenges in scaling, thermal management, data processing, and biocompatibility, which must be overcome to realize the full potential of implantable photonics as a new paradigm for closed-loop neuroscience and clinical translation.
The plastic pollution crisis urges innovative recycling solutions. Promising approaches especially for polyester-containing wastes include enzymatic hydrolysis and microbial upcycling. For efficient enzymatic hydrolysis of polyesters, elevated temperatures (70-80 °C) are required, necessitating thermophilic microbial chassis for consolidated bioprocessing (CBP). In this study, we engineered Geobacillus thermoleovorans through adaptive laboratory evolution (ALE) for robust growth on adipic acid (AA) and 1,4-butanediol (BDO), two relevant monomers for example derived from poly(butylene adipate-co-terephthalate) (PBAT), enabling growth rates of up to 0.10 h-1 on AA and 0.13 h-1 on BDO. Based on a high-quality annotated genome sequence of the wild type, genomic mutations and gene expression levels were characterized in mutants grown on the respective substrates compared to glucose. For BDO, an alcohol dehydrogenase (Gth_001044) and an aldehyde dehydrogenase (Gth_001082) were identified to be likely responsible for its oxidative degradation. AA uptake appears to be mediated by a dicarboxylate transporter (Gth_003270), followed by CoA activation and β-oxidation involving a CoA transferase (Gth_003192) and several upregulated CoA-family dehydrogenases. To demonstrate applicability of these strains in plastic upcycling, they were co-cultivated with PBAT as the sole carbon source in combination with the cutinase HiC for PBAT hydrolysis. This resulted in growth on the released AA and BDO. Given the potential to purify the remaining terephthalate (TA), this approach highlights the feasibility of selective monomer valorization in bioprocesses. Additional ALE enabled co-utilization of AA and BDO by a single strain and improved AA consumption at lower concentrations, underscoring the strains' adaptability and high potential for plastic upcycling applications. KEY POINTS: • G. thermoleovorans evolved for robust growth on adipate and 1,4-butanediol at 60 °C. • Genome and transcriptome analyses revealed underlying pathways and enzymes involved. • Co-cultivation of the evolved strains on PBAT with HiC as the sole carbon source.
Accurate detection and segmentation of moving objects constitute a fundamental challenge in computer vision, particularly for intelligent video surveillance systems operating under variable illumination, dynamic backgrounds, and environmental noise. This paper presents a fully unsupervised dual-phase motion analysis framework that effectively combines statistical independence modeling and geometric contour evolution to achieve high-precision motion detection and segmentation. In the first phase, an enhanced Fast Independent Component Analysis (Fast-ICA) algorithm is employed to perform statistical decomposition of video sequences, exploiting temporal independence to distinguish moving foregrounds from static backgrounds. This process generates an initial motion mask with strong robustness to illumination variation and noise artifacts. In the second phase, a hybrid level set segmentation model integrating the global Chan-Vese formulation and a locally adaptive Yezzi-based energy function refines object boundaries through an adaptive energy minimization process. A stabilization term and a self-regulating convergence criterion are further incorporated to ensure contour smoothness, numerical stability, and resilience to topological changes. Comprehensive experiments conducted on the CDNet-2014 benchmark dataset demonstrate that the proposed method achieves an average recall of 0.9613, precision of 0.9089, and F-measure of 0.9310, outperforming several state-of-the-art supervised, semi-supervised and unsupervised background subtraction algorithms. The proposed Fast-ICA-Level Set fusion framework thus provides a robust, adaptive, and computationally efficient solution for real-world intelligent surveillance and autonomous visual monitoring applications.
暂无摘要（点击查看详情）
The functional properties of protein fibrils are governed by structural transitions and conversion efficiency, highlighting the need to regulate fibrillation. In this study, a combined ultrasound and Zn2+ treatment was developed to promote the formation of pea protein fibrils and enhance their delivery performance. The results showed that this treatment accelerated pea protein hydrolysis during the lag phase, promoted polypeptide chain folding during the growth and plateau phases, and produced short fibrils enriched in β-sheets (38.9%). This effect was associated with greater exposure of hydrophobic groups (H0 = 25,408.3), which made hydrophobic interactions the dominant driving force for fibrillation while suppressing disulfide bond formation. In addition, CO bond transformation and protein backbone reorganization were involved in fibril formation. Fibrils formed under synergistic treatment were found to further enhance the antioxidant capacity, digestive stability, and bio-accessibility of AST (38.19%), whereas the bio-accessibility of free AST was only 9.37%.
Multiple myeloma (MM) is best understood as a dynamically evolving genomic ecosystem shaped by inherited susceptibility, early oncogenic events, and continuous selective pressures. We propose an evolutionary genomics framework integrating germline risk, disease initiation, clonal diversification, and therapeutic adaptation into a unified model of MM biology. Polygenic risk burden, rare predisposing variants, and alterations in DNA repair and telomere pathways create a permissive background that influences precursor states and immune interactions. Primary cytogenetic events, particularly immunoglobulin heavy chain (IgH) translocations and hyperdiploidy, establish biologically distinct founding clones and constrain subsequent evolutionary trajectories. Disease progression is driven by secondary chromosomal alterations, copy number changes, MYC activation, TP53 loss, and structural rearrangements, promoting genomic instability and transcriptional plasticity. Longitudinal studies reveal branching clonal architectures shaped by treatment-driven selection. Integrating germline and somatic landscapes within an evolution-aware precision framework may improve risk stratification, anticipate high-risk trajectories, and support adaptive strategies to achieve more durable disease control. While polygenic risk scores (PRS) provide insight into inherited susceptibility, they are not yet clinically actionable for risk stratification or screening in MM and currently remain research tools. This framework provides a clinically oriented basis for applying genomic biomarkers to risk stratification, treatment selection, and longitudinal monitoring.
Structural variants (SV) are major drivers of evolutionary processes such as adaptation and speciation, yet their complexity and dynamics in wild populations remain largely unexplored. Avian diversity is highest in the Neotropics, primarily due to the suboscine passerine radiation; however, despite this diversity, genomic resources and studies of SVs in suboscines are scarce compared to their sister clade, the oscine passerines ("songbirds"). Here, we used long-read and chromatin conformation capture sequencing to assemble a high-quality scaffolded reference genome and construct a population-scale pangenome from 5 individuals of the Pearly-vented Tody-Tyrant (Hemitriccus margaritaceiventer), a suboscine bird with plumage variation across its distribution in South American dry forests. Our pangenome graph reveals extensive structural variation, with the chromosomal distribution of SVs strongly predicted by simple and low-complexity repeats - highlighting how specific repeat architecture may influence genome evolution. We discovered intraspecific copy number variation in multigene families, with the most complex instance including beta-keratin genes. Lastly, we identified a 306 kb inversion spanning several melanin pigmentation-associated genes (e.g. MREG, MLPH, RAB17), making it a potential candidate SV for known intraspecific plumage variation. Our study establishes a population-scale pangenome resource for a suboscine bird, enabling characterization of the genome-wide abundance, diversity, and distribution of SVs within this species.
Understanding how different C1 carbon sources participate in photocatalytic reduction is essential for clarifying carbon conversion pathways beyond conventional CO2-centric descriptions. Herein, polar chalcohalide photocatalysts SbSI and SbSeI are systematically investigated for the light-driven reduction of representative molecular and inorganic C1 carbon sources, including HCHO, HCOOH, CH3OH, NaHCO3, and CaCO3. Time-resolved product evolution, quantitative yields (μmol·g-1·h-1), and selectivity were determined using GC-TCD/FID and GC-MS. Across all systems, hydrogen evolution dominates the reaction network, methane is the primary carbon-containing product, and C2+ hydrocarbons appear as minor products, while CO and oxygen-containing organics are not detected. Molecular C1 substrates establish hydrogen-rich reaction environments that favor deep reduction and saturated hydrocarbon formation, whereas bicarbonate and carbonate sources exhibit reduced activity but enhanced formation of unsaturated C2+ hydrocarbons. These results establish a unified, experimentally driven framework for carbon-source-dependent photocatalytic reduction pathways over mixed-anion chalcohalide photocatalysts.
Agricultural nitrogen (N) non-point source pollution is one of the major threats to water environmental safety. Although previous studies have shown that appropriate tillage practices can effectively reduce runoff and associated N loss, it remains unclear how N loss from sloping farmland responds to changes in microtopography and hydrological connectivity under different tillage practices. In this study, natural rainfall observations were conducted from August 2024 to August 2025 under three tillage treatments-flat tillage (FT), artificial digging (AD), and contour ridge tillage (RT)-in the red soil region of southern China. By combining high-resolution UAV-SfM topographic reconstruction with the Index of Connectivity (IC), we examined the dynamic evolution of hydrological connectivity under different tillage practices and its regulatory role in N loss. The results showed that conservation tillage treatments (AD and RT) initially disrupted hydrological flow pathways and reduced N export by >50 %; however, this mitigation effect was short-lived. Continued rainfall and the progressive attenuation of microtopography led to different IC evolution trajectories, which in turn increased N loss. Under RT, abrupt ridge failure during extreme rainfall events triggered a sharp increase in IC, causing runoff and N losses to temporarily exceed those under conventional FT. In addition, heavy rain and rainstorm events were the main drivers of system losses, contributing 36.61 %∼54.75 % of total runoff and 26.40 %∼51.34 % of total nitrogen export, respectively. Partial least squares structural equation modeling (PLS-SEM) further confirmed that IC acted as the primary mediating variable regulating N export through changes in runoff and transport intensity. These findings suggest that maintaining ridge structure after extreme rainfall events is critical to preventing abrupt increases in nitrogen loss caused by sudden shifts in structural connectivity. This study provides a theoretical basis for water and nitrogen loss control and tillage optimization on sloping farmland.
Gob-side entry driving is widely applied in deep coal mines, where rapid unloading of surrounding rock on the gob side induces stress redistribution, and the coal pillar is consequently regarded as a key load-bearing structure. The stability of the roadway is governed by the competition between elastic elastic strain energy and dissipated energy within the coal pillar. To address the difficulty of identifying stability state transition points in coal pillar width design under deep burial and weak rock conditions, this study analyzes the surrounding rock response from an energy perspective and establishes an energy analysis framework based on the coupling of elastic elastic strain energy and dissipated energy, with the dissipated energy ratio introduced as an evaluation index. Based on FLAC3D numerical simulations, the spatial distribution and evolution of elastic strain energy, dissipated energy, and dissipated energy ratio under different coal pillar widths are investigated. The results indicate that when the coal pillar width increases from 4 to 6 m, the bearing mechanism gradually shifts from plastic dissipation-dominated behavior to an elastoplastic coordinated state dominated by elastic elastic strain energy, with the dissipated energy ratio decreasing from 1 to approximately 0.67. When the width further increases to 8 ~ 14 m, elastic strain energy rapidly accumulates in the central region of the coal pillar, resulting in the formation of a pronounced energy concentration zone. Compared with traditional indicators based on stress, displacement, and plastic zone distribution, the dissipated energy ratio is more effective in characterizing. Considering energy evolution characteristics, bearing capacity, and engineering economy, a 6 m coal pillar is considered to achieve the most favorable balance under the conditions of the studied mine. Field monitoring results further verify the engineering applicability of the proposed energy-based criterion and coal pillar width optimization scheme.
Novel invasive genotypes can arise through polyploidisation, hybridisation, or gene flow between populations of distinct origins or related species. Solidago gigantea, a notorious European invader, has long been reported exclusively as tetraploid in its invasive range. Recently, mixed-ploidy populations, including tetraploid and pentaploid plants, were discovered; yet the potential role of the novel pentaploid cytotype (and its progeny) in S. gigantea invasions remains poorly understood. This study aims to elucidate the origin of pentaploids and the cytotype and genetic structure of mixed-ploidy populations, characterise the reproductive mode and mating interactions of pentaploid plants, and assess their fitness and potential contribution to invasiveness using relative DNA content screening, ddRADseq population genetics, and reproductive potential and fitness assessments. Molecular analyses revealed that pentaploids constitute a genetically distinct lineage within S. gigantea. Our results rule out both an autopolyploid origin from the common tetraploid cytotype and an allopolyploid origin via hybridisation with co-occurring native or invasive Solidago species. The pentaploid cytotype reproduces exclusively through clonal propagation; its low genetic variability suggests that the two studied populations may belong to a single extensive clonal genet. Pentaploids produce viable gametes but appear to exhibit strict self-incompatibility, preventing the formation of offspring within the same genotype. However, pentaploid S. gigantea engages in bidirectional mating with co-occurring tetraploid plants, yielding well-developed seeds with offspring ploidy ranging from 4x to 5x (predominantly aneuploid). Despite this cytological variability, progeny from mixed-ploidy populations displayed germination rates and early growth comparable to those from pure tetraploid populations. Notably, at least some tetraploid offspring from 4x-5x crosses successfully established, flowered, and backcrossed with pentaploid plants to produce viable seeds of subsequent introgressed generations. The pentaploid cytotype of S. gigantea introduces a new post-invasion dynamic to its invasive populations. Rather than being an evolutionary dead-end, this cytotype may potentially enhance the species' invasiveness through three evolutionary pathways: (1) a highly successful clonal life strategy enabling both local and long-distance spread; (2) genetic enrichment of tetraploid populations via ongoing interploidy crosses; and (3) establishment of novel aneuploid genotypes due to the remarkable tolerance of chromosomal instability observed in S. gigantea.
Excitons play a decisive role in governing light absorption, charge separation, and carrier utilization in low-dimensional photocatalysts. In this work, we present a comprehensive first-principles investigation of excitonic effects and their impact on photocatalytic water splitting in a SnS2/h-BN van der Waals (vdW) heterostructure. Density functional theory (DFT), combined with many-body perturbation theory (MBPT) within the GW approximation and the Bethe-Salpeter equation (BSE), is employed to determine the quasiparticle band edge alignment, exciton binding energies (EBEs), optical absorption, carrier effective masses, and solar-to-hydrogen (STH) conversion efficiency. The SnS2/h-BN heterostructure exhibits a staggered type-II band alignment with quasiparticle band edges straddling the redox potentials, ensuring thermodynamic feasibility for overall water splitting. Beyond band alignment, the heterostructure supports multiple optically active bright interlayer excitons with spatially separated electrons and holes at the interface. These interlayer excitons display reduced electron-hole (e-h) wave function overlap and favorable effective masses, particularly a highly dispersive SnS2-derived conduction band that enables efficient electron transport toward hydrogen evolution reaction sites. Despite their sizable binding energies, efficient exciton dissociation is promoted by strong interfacial electric fields and large conduction band offsets, leading to effective charge separation. Consequently, photogenerated carriers are selectively funneled to distinct catalytic surfaces, enabling spatially separated hydrogen and oxygen evolution. The synergistic enhancement of light absorption, carrier lifetime, and charge transport results in a markedly higher STH efficiency (11.04%) compared to that of pristine SnS2. This work underscores the necessity of explicit excitonic treatment and establishes exciton engineering in vdW heterostructures as a key strategy for the design of efficient photocatalysts for solar water splitting.
To understand the molecularly obscure pre-diagnostic phase of lung cancer, we mapped the temporal evolution of the plasma proteome for new biological insights and improved risk prediction. Leveraging the UK Biobank prospective cohort, we analyzed 2,921 plasma proteins from 37,759 participants, including 342 incident lung cancer cases identified over a median follow-up of 11.7 years. We employed time-stratified Cox models, locally weighted scatterplot smoothing (LOESS) trajectory modeling, and hierarchical clustering to characterize protein dynamics relative to the time of diagnosis. A multi-algorithm machine learning pipeline was used to develop a predictive signature, and two-sample Mendelian randomization was performed to infer causal relationships. We identified 340 risk-associated proteins showing significant temporal heterogeneity. Long-term risk (>5 years pre-diagnosis) was linked to proteins like CEACAM5, indicating early dysregulation of cell adhesion. Imminent risk (<5 years) was marked by a surge in inflammatory proteins like IL6. These dynamics were resolved into four distinct trajectory patterns, creating a molecular timeline of carcinogenesis. A machine learning-derived 28-protein signature, integrated with clinical factors and Polygenic Risk Score (PRS), achieved outstanding predictive performance (AUC = 0.830). Mendelian randomization also suggested a causal role for some proteins of 340 risk-associated proteins in lung cancer development. Our findings establish that lung cancer evolves through a dynamic sequence of protein changes. This provides a new model for understanding pre-diagnostic disease, and our 28-protein signature is a powerful tool for precision screening to identify individuals with active disease progression.
Triple negative breast cancer (TNBC) is a biologically heterogeneous disease that is treated according to stage at diagnosis. Early steps toward treatment personalization used staging for prognostication and later incorporated residual disease burden after neoadjuvant therapy to guide adjuvant treatment decisions. Therapeutic advances, particularly with immunotherapy and poly (ADP-ribose) polymerase inhibitors, have progressed more rapidly than the ability of clinical trials to adapt accordingly, leaving many critical questions regarding treatment combinations and sequencing unanswered. Adapting neoadjuvant and adjuvant strategies according to dynamic changes in the tumor, tumor microenvironment (TME) and novel biomarkers dynamics offers a compelling framework for both treatments escalation and de-escalatation. This review traces the historical evolution of TNBC treatment, examines the challenges of tumor heterogeneity and residual disease after neoadjuvant therapy, and explores the prognostic impact of the TME. We then appraise the latest evidence on poly (ADP-ribose) polymerase inhibitors, antibody-drug conjugates, and immunotherapy in the early setting, outlining a path toward more individualized therapeutic approaches.
Transposable elements (TEs) are significant drivers of genome evolution, influencing the genome dynamics of clonal fungal pathogens such as those in the Fusarium oxysporum species complex (FOSC) that cause Fusarium wilt in over 100 plant hosts. Among these, Tropical Race 4 (TR4), a clonal lineage within the FOSC, poses a severe threat to global banana production. However, the contribution of TEs to genome variation and functional traits in TR4 remains poorly understood. Here, we investigated Helitron-associated structural variations in a TR4 strain from Mozambique (M1). This revealed two large deletions in core chromosomes associated with an active FoHeli1 Helitron transposon. One of these (464 kb) disrupted 151 genes, including the entire fusaric acid (FA) biosynthetic gene cluster, consequently abolishing FA production, altering secondary metabolite profiles, and increasing sensitivity to exogenous FA. Despite these metabolic changes, infection assays using wild-type, mutant, knock-out, and complemented strains demonstrated that FA production is dispensable for TR4 virulence in banana. Our study highlights the role of FoHeli1 in modulating the genetic and metabolic landscape of TR4, underscoring the broader impact of TEs on fungal genome evolution and functional diversification, especially in clonal lineages.