PLOS Biology

Despite longstanding recognition of sex as a biological variable, its integration into biomedical research remains inconsistent. Numerous publishers have introduced policies to improve reporting and inclusion of sex and gender, including Nature, which requires authors to complete a Life Science Reporting Summary documenting sex inclusion. Here, we evaluated the effectiveness of these policies by examining sex inclusion and reporting practices in all original research articles involving humans, vertebrates, or cell lines published in Nature in 2025 (N=513). Nearly two-thirds of articles included both sexes (62.7%); however, inclusion was often nominal. Of these articles reporting inclusion of both sexes, 33% did not maintain inclusion across experiments, used markedly unbalanced sex ratios ([≥]2:1), or alternated between male- and female-only experiments. Another 45.5% of these articles reporting inclusion of both sexes did not report sample size by sex, so it cannot be ascertained whether sex inclusion was maintained across experiments or balanced by sex. Single-sex studies accounted for approximately one-fifth of articles. While male-only and female-only studies occurred at similar overall rates, male-only studies were more than four times more likely to address conditions affecting both sexes while female-only studies were more likely to address sex-specific conditions (e.g., ovarian cancer). Only 7% of articles explicitly analyzed sex as a discovery variable for at least some analyses. These findings suggest that transparency-focused reporting summaries alone are insufficient to ensure sex inclusion and/or meaningful analytical integration of sex. As a leading biomedical journal, Nature plays a central role in shaping research norms; without stronger editorial expectations, reporting requirements risk reinforcing male-default assumptions rather than advancing rigor and generalizability.

Detecting causal language in scientific literature is critical for understanding how research fields frame evidence and inform interventions and policies, yet existing approaches commonly rely on manual annotation. The objective of this study was to evaluate four classifiers for detecting causal language and to apply the best-performing model to assess trends in microbiome research. Microbiome research, with its rapidly expanding observational literature, provides a relevant case study. We extracted Term Frequency-Inverse Document Frequency (TF-IDF) features from the last three sentences of available publication abstracts and trained four classifiers (L1- and L2-regularized logistic regression, Random Forest, and eXtreme Gradient Boosting) to detect causal language. A total of 475 sentences, as determined pragmatically based on annotation feasibility and observed stabilization of model performance, were manually labeled as causal or non-causal following established guidelines for systematic evaluation of causal language in observational health research. Of these, 75% of sentences were used for training and 25% for testing. L1-regularized logistic regression achieved the highest performance (accuracy 76%, F1 72%, prevalence detection accuracy 95%, sensitivity 72%, and specificity 80%) and was applied to 20,022 human gut microbiome abstracts published between 2015 and 2025 grouped into 20 thematic topics using structural topic modeling. Predicted causal language prevalence declined from 52% to 44% between 2015 and 2018, then rose to 51% by 2025, with notable variation across topics (range: 43.1-53.3%). Temporal trends differed across subfields, with increases in Metabolic disorders, Fecal microbiota transplantation, and decreases in Biomarkers and prediction, Antibiotic resistance, and In vitro fermentation. Analysis of influential words confirmed that causal meaning is primarily driven by verbs and modifiers lexically signaling change or intervention. The proposed approach for identifying causal claims in scientific abstracts enables systematic and automated, scalable assessment of how evidence is framed. Its application to the microbiome field highlighted heterogeneity in the reporting of causal relationships and informing the interpretation of microbiome findings for clinical and public health decision-making.

The (semi-)automated screening of publications for diverse quality and transparency criteria is at the core of systematic literature assessment. Typically, the assessment process involves two initial reviewers and one additional reviewer for cases that require reconciliation. Here, we explore to what extent this process can be assisted by Large Language Models (LLMs). Specifically, whether LLMs are capable of assessing responsible research practices (RRPs) in scientific papers in a robust way. We employed proprietary LLMs to assess an initial set of 37 papers across ten RRPs. The same papers were also reviewed by three human reviewers. We iteratively redesigned prompts to increase model accuracy compared to human ratings which we treated as the gold standard. The resulting pipeline was validated on an additional set of 15 papers. We show that LLM accuracy is comparable to single human reviewer performance (90% for LLM vs 86% for a single human reviewer). However, performance strongly depended on the specific RRPs with accuracy ranging from 40% to 100%. LLMs exhibited an affirmative bias, making more errors when practices were not reported in the papers. Overall, we show how such an approach potentially replaces one human reviewer, enabling AI-assisted assessment of research papers. We discuss how dataset imbalances, validation procedures, and implementation time limit the broad applicability of such approaches. Through this, we develop initial guidance on the utility of proprietary LLMs in evidence synthesis.

The experimental use of antibodies that have not been validated for context-specific use frequently misdirects biomedical research. Experimental results that derive from the use of inadequately validated antibodies are estimated to waste over $1 billion annually in the United States alone and to consume millions of animal and human biological samples in experiments whose conclusions may be unreliable. Community validation frameworks, reporting standards, and independent characterisation initiatives have made important progress, and multi-stakeholder coordination efforts are emerging. However, the research community lacks a formally developed, consensus-based action plan that specifies what each stakeholder group should do, by when, and with what priority. We conducted a modified Delphi study with international experts representing academic researchers, scientific publishers, research funders, antibody manufacturers, and institutional research leaders to develop actionable recommendations for improving antibody validation, selection, and reporting practices. Thirty-two participants rated 33 proposed actions on effectiveness and feasibility using 9-point scales, with consensus assessed using the RAND/UCLA Appropriateness Method. Over two rounds, the panel achieved consensus on 15 items as both effective and feasible for implementation by 2030. These spanned institutional actions (training in antibody validation, integration into research integrity frameworks, support for local expertise networks), funder actions (dedicated validation budgets, grant application requirements, endorsement of community reporting standards), publisher actions (complete antibody reporting packages, clear validation standards), manufacturer actions (assignment of unique identifiers at source), and cross-stakeholder coordination (a shared roadmap for improvement). An additional 15 items were rated as effective but with uncertain feasibility, reflecting a consistent pattern in which the panel agreed on the value of proposed interventions but expressed reservations about realistic implementation timelines. One item was rejected by the panel with concerns around effectiveness and feasibility. Participants described four interconnected barriers to progress: diffuse ownership of the problem across stakeholders; market dynamics that inadequately reward antibody quality; difficulty justifying investment when returns are distributed across the research system; and coordination challenges among actors with different incentive structures. These barriers are addressable through coordinated action, and the findings complement existing technical and data-sharing initiatives by providing the structured, stakeholder-endorsed policy framework needed to translate awareness of the problem into concrete practice and policy changes.

The interleukin-17 (IL-17) family of cytokines comprises structurally distinct ligands and receptors which mediate immune responses at mucosal surfaces. The growing understanding of its regulatory functions beyond immunity, together with extensive genetic variation in protein-coding genes, raises the possibility that IL-17 cytokines participate in an even wider network of biologic processes. Despite successes of experimental approaches to chart IL-17 functions, inherent signaling complexities and crosstalk with multiple physiologic pathways obscure a full appreciation of the biological potential of IL-17. Here, we integrated comparative genomics, evolutionary rate covariation (ERC), and signatures of natural selection to resolve phylogenetic relationships between IL-17 ligands and receptors and discovered evidence for hidden signaling interactions. ERC analysis revealed putative ligand-receptor interactions for IL-17D and IL-17RC and suggested uncharacterized potential signaling mediator for the receptor IL-17REL, such as IL-17B. Signals of covariation extended beyond the IL-17 family to other genes encoding neurodevelopmental effectors and growth factors, emphasizing recurrent co-evolutionary patterns that delineate the immune and neuromodulatory roles of IL-17. These connections are underlined by signatures of positive selection in the disordered N-terminal domain of IL-17E and its cognate receptor, IL-17RB, key modulators of both type 2 immune response and neuronal function, suggesting functional consequences of this understudied domain. Together, our findings suggest that IL-17 biology is repeatedly impacted by lineage-specific selective pressures that dictate both immune and non-immune functions. By anchoring the expanding IL-17 field in an evolutionary framework, we propose a model for understanding the diversification and functional expansion of this and other cytokine families.

Circular RNAs (circRNAs) originate from backsplicing of numerous genes in animals, but the functions of most circRNAs remain elusive. We previously demonstrated that circZNF827 forms a complex with hnRNPL/K and its host gene-encoded protein ZNF827 that acts in the nucleus to transcriptionally repress the nerve growth factor receptor (NGFR/p75NTR) gene during neuronal differentiation (Hollensen, 2020) [1]. To explore the mechanism of action, and to assess a potential role of the circZNF827-hnRNP complex on additional loci, we scrutinized the genome-wide consequences of circZNF827 and/or hnRNPL knockdown at the transcriptomic and epigenetic level. RNA-sequencing and CUT&RUN confirmed that NGFR and additional loci are transcriptionally repressed by the circZNF827-protein complex, and that these are primarily enriched for H3K27me3 signatures. Only a fraction of the massive transcriptomic changes could be ascribed to a direct circZNF827 transcription-regulated phenotype, suggesting that initial key regulatory events elicited by the circZNF827-hnRNP complex likely lead to a secondary response, which further augments neuronal differentiation.

Host-pathogen interactions evolve rapidly within species, providing natural genetic resources for the identification of specific ecological interaction factors. We previously identified RNA viruses that infect the nematodes C. elegans and C. briggsae in a species-specific manner. Wild strains of both host species demonstrate ample variation in viral sensitivity. Specifically, the wild C. elegans strain MY10, despite carrying a deletion in a key immunity factor, was among the most resistant strains. Here we use recombinant inbred lines and pool-sequencing approaches to genetically map the major MY10 resistance locus, narrowing down its position by CRISPR/Cas9 mediated recombination and testing candidates by genome editing. A rare non-synonymous polymorphism in the gtnt-1 gene, encoding a putative glycosyltransferase of the GT92 family, causes resistance to viral infection in MY10. We find that viral resistance through gtnt-1 mutation occurred repeatedly in C. elegans, with diverse resistance alleles each remaining at low frequency (<1%). Furthermore, leveraging closely related C. briggsae strains differing in viral susceptibility, we demonstrate that repeated reduction-of-function alleles of the Cbr-gtnt-1 ortholog similarly impair viral infection and enhance host fitness upon infection. In conclusion, we found recurrent evolution in two host species of reduction-of-function alleles of the gtnt-1 orthologs, which repeatedly lead to viral resistance yet remain at low frequency. These repeated events provide a case of transient ecological adaptation to a pathogen through recurrent mutation of the same gene in two species. The low population frequencies of the resistant alleles point to a changing eco-evolutionary context that prevents their spread in populations, resulting in high allelic heterogeneity.

Notch-mediated lateral inhibition is a conserved patterning process that controls alternative cell fate decisions and produces regular cell fate patterns. Prevailing models posit that lateral inhibition singles-out cells from fields of initially equipotent cells by amplifying stochastic fluctuations of Notch or pre-existing fate biases. Here, we revisited the role of Notch in early Drosophila neurogenesis, studying the dynamics of Neuroblast specification by live imaging the transcription of two proneural genes, scute and lethal of scute. We found that proneural gene expression is biased spatially along the dorsal-ventral axis prior to germ band extension and that early proneural expression predicts Neuroblast fate acquisition. This indicated that Neuroblast specification is pre-patterned by positional cues. Additionally, positional cues appeared to instruct individual cells to delaminate in a correct stereotyped pattern in proneural mutant embryos. Finally, contrary to current models, Notch signaling, measured by E(spl)m8 expression, was not detectable within proneural clusters until after Neuroblasts had initiated delamination. This indicated that Notch functions to stabilize rather than initiate fate decisions. We therefore propose that positional cues, not Notch, single-out Neuroblasts during early Drosophila neurogenesis, challenging long-held assumptions about the role of Notch in Neuroblast selection.

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Recent large-scale bibliometric analyses suggest that individual AI use can increase productivity while reducing downstream engagement and topic diversity. Here we ask whether collective AI deployment is associated with shared engagement. Using an Audience Response Engagement (ARE) system at NGS Expo 2025 (N=110 biomedical researchers), we captured real-time consensus and generated updated visualizations within minutes. Our data reveal a substantial gap between adoption and transparency: 93.6% of researchers use AI at least weekly, yet only 5.5% consistently disclose this usage--a 17-fold disparity. This pattern is consistent with systemic policy uncertainty (39.1% report unclear guidelines). Behavioral clustering identifies a "High-Concern" group (31%) as a candidate for targeted interventions: highest productivity yet lowest disclosure. These findings suggest that collective AI deployment in physical settings is associated with shared engagement.

The preprint ecosystem has expanded rapidly over the past decade, fundamentally altering science communication. Yet, the scholarly communitys attitudes toward this shift remain underexplored. Through a large-scale survey of US and Canadian biomedical scholars, we provide a comprehensive analysis of preprint utilization, perceived impact, and integration into academic credit systems. We find robust engagement across reading, citing, and submitting preprints; however, this activity is driven primarily by a desire for rapid dissemination rather than a foundational commitment to open science. Furthermore, while preprints are valued as networking assets, perceived career penalties during formal academic evaluations stifle broader cultural adoption. Crucially, to navigate the absence of formal peer review, scholars report a heavy reliance on author reputation as a primary heuristic to evaluate a preprints credibility and guide their reading and citation decisions. Notably, despite acknowledging preprints role in accelerating knowledge sharing, scholars express significant concerns regarding fraud and misinformation, particularly amid declining public trust in science and emerging threats to scientific integrity from artificial intelligence. To resolve these tensions, the preprint ecosystem must evolve beyond prioritizing speed to foster genuine academic dialogue. Simultaneously, evaluation frameworks must adapt to the realities of preprinting, and innovative quality-control mechanisms are urgently needed to balance rapid dissemination with rigorous scientific integrity.

HighlightsO_LIWe introduce the TMS-RAT, a reporting (assessment) tool for TMS studies C_LIO_LIDeveloped within a community-informed, iterative process rating 333 TMS studies C_LIO_LIEmpirically evaluated for usability, inter-rater, and test-retest reliability C_LIO_LIA validated subset enables reliable retrospective assessment of reporting C_LIO_LIThe modular structure enables use across a wide range of TMS study designs C_LI BackgroundA standardised tool for comprehensive reporting can improve transparency, support consistent documentation, and enable comparison across transcranial magnetic stimulation (TMS) studies. The most used reporting checklist lacks clear definitions of full reporting and was not initially evaluated for usability or inter-rater reliability. A scoping review of studies using this checklist shows that its items are reported only 50% of the time, suggesting that method descriptions are often incomplete. MethodsWe developed the TMS Reporting Assessment Tool (TMS-RAT), a comprehensive reporting framework that provides clear definitions and examples for its items, covering a wide range of TMS protocols. We tested the usability and reliability of the TMS-RAT by rating all studies published between 1991 and 2025 using afferent conditioning (n = 333), a protocol encompassing many reporting categories identified during tool development. Seventeen independent raters contributed across three development phases, a validation phase, and a retest phase, with naive raters introduced in each phase. Iterative refinements of the tool were informed by inter-rater reliability, qualitative rater feedback, and consultation with external TMS experts. ResultsWe present two versions of the tool: the 72-item TMS-RAT v1.0, designed to guide comprehensive reporting, and the TMS-RAT v1.1, a subset of 50 items with the highest inter-rater (overall AC1 = 0.78, range = [0.60-0.99]) and test-retest reliability (overall AC1 = 0.82, range = [0.65-1.0]), intended for retrospective evaluation of reporting in systematic reviews, meta-analyses. ConclusionThe TMS-RAT is a comprehensive, reliable tool that seeks to improve transparency and reproducibility in TMS research.

The California serogroup (CSG) of orthobunyaviruses includes neuroinvasive viruses with varying pathogenicity. La Crosse virus (LACV) is a leading cause of pediatric arboviral encephalitis in the USA, while Inkoo virus (INKV) is widespread in Northern Europe but rarely causes disease. The reassortment potential of CSG viruses raises concerns about emerging virulent strains and highlights the need to develop therapies that are broadly effective against multiple CSG viruses. To identify host factors mediating viral neurotoxicity, we performed genome-wide CRISPR-Cas9 knockout screens in human neuroblastoma cells infected with LACV or INKV. Analysis revealed largely overlapping host dependency factors for both viruses. Unexpectedly, the screens identified mitochondrial energy production as a major pathway required for both LACV- and INKV-induced cell death. Reducing host cell energy production with mild hypothermia or sugar source substitution prolonged cell survival during viral infection with additive effects mediated by different mechanisms. Both manipulations also protected neuroblastoma cells from the Bunyamwera virus (BUNV), a non-CSG orthobunyavirus; and mild hypothermia protected mature human neurons from LACV. These results highlight host energy metabolism as a key modulator of CSG virus cytotoxicity and suggest novel avenues for general non-invasive therapeutic intervention against current and future strains of these and other orthobunyaviruses.

The integration of bottom-up and top-down signals is crucial for perception and behavior. Neocortical layer 1 (L1) is a key target for top-down inputs and contains various GABAergic interneurons. Here, we investigated whether GABA can presynaptically regulate neurotransmitter release at top-down synapses targeting L1 of primary somatosensory cortex (S1). Our findings show that presynaptic GABAB receptor activation suppresses corticocortical inputs from primary motor (M1) and secondary somatosensory cortices (S2) more than those from the posterior medial nucleus of the thalamus (POm). This effect varied by target cell type, with GABAergic interneurons being less affected. Finally, we demonstrate that L1 neuron-derived neurotrophic factor (NDNF)-expressing interneurons inhibit top-down synapses more effectively than somatostatin-expressing interneurons, and that POm drives L1 neurogliaform cells, a subtype of NDNF interneuron that elicits unitary GABAB responses. These results reveal a novel circuit in which higher-order thalamus influences top-down corticocortical communication via L1 neurogliaform cells.

Numerous experimental evolution studies have suggested that adaptation rate of microbial populations evolving in stable environments decline over time. Despite the generality of this phenomenon across different domains of life, the timing and magnitude of decline in adaptation can vary greatly based on the idiosyncrasies of the biological system. To investigate the characteristics of adaptation deceleration in a fast-evolving virus, we propagated HIV-1 in two human T-cell lines (MT-2 and MT-4) for approximately 4.8 years and tracked its genome evolution through next-generation sequencing. The curated sequencing data covering the whole-genome can be accessed and explored via LTEEviz, an interactive web application. Time-resolved sequencing data uncovered that despite constant fixation rate of 0.085 (MT-2) and 0.042 (MT-4) mutations per generation, the fixation kinetics of adaptive mutations changed considerably over time. The rate of fixation of adaptive parallel mutations decreased by 44% per 300 generations, while their conferred fitness gain decreased by 27% (MT-2) and 18% (MT-4) per every added adaptive mutation in their genetic background. The early and substantial deceleration of adaptation in our HIV-1 populations can, at least in part, be explained by diminishing gains of adaptive mutations. Furthermore, we identified genomic patterns consistent with a hard selective sweep that occurred in one population later in the experiment. Together, our results confirm that HIV-1 genomic evolution is characterized by a swift and substantial deceleration of adaptation, while also revealing that episodes of positive selection can occur beyond the initial adaptive phase.

De novo gene emergence from non-coding sequences is increasingly recognized as an important evolutionary mechanism, yet the functional potential of random sequences remains debated. Previous experiments suggested that expression of random sequence clones in Escherichia coli can enhance growth of the cells bearing them, i.e. they provide a fitness advantage. However, these findings have been questioned, regarding potential confounding effects of the clone mixtures and a possibly negatively acting peptide expressed from the cloning vector. Here we performed controlled competitive growth assays using a defined subset of 64 random sequence clones representing a spectrum of fitness effects. Experiments across multiple conditions, including two different growth cycle durations, induction states, and replicate sets, showed high technical reproducibility and consistent clone-specific growth trajectories for the majority of the clones, but for some also influences of genomic background and experimental conditions. While vector-derived constructs that inhibit the vector-coded peptide expression showed the same fitness improvements relative to the parental vector that were previously shown, several random sequence clones exhibited higher positive selection coefficients under conditions of exponential growth. These effects persisted even when negative clones were excluded, indicating that they are not driven by competition dynamics with negative clones. Our results demonstrate that positive growth effects of random sequence clones cannot be explained by clone mixture and vector artifacts alone. Instead, a subset of random sequences confers genuine fitness advantages comparable to beneficial mutations observed in experimental evolution studies. These findings provide strong experimental support for the capacity of random sequences to generate adaptive functions and underscore their role in de novo gene evolution. Significance statementThis study provides robust experimental evidence that a subset of random DNA sequences can confer genuine fitness advantages in Escherichia coli, independent of previously proposed artifacts such as vector effects or clone competition. Based on controlled competitive assays across multiple conditions, the results show that these adaptive effects are reproducible and comparable to beneficial mutations observed in experimental evolution. These findings strengthen the case that random sequences can serve as a meaningful source of functional innovation, supporting their role in de novo gene evolution.

Quorum sensing is a communication process bacteria use to orchestrate collective behaviors. Some temperate phages monitor bacterial quorum-sensing cues to track the abundance of vicinal host cells. Quorum-sensing-responsive phages can preferentially undertake lytic replication at high cell density, presumably maximizing transmission. If nearby host cells are lysogens, infections initiated by released virions could be nonproductive due to homoimmunity or superinfection exclusion, posing a conundrum for temperate phages. We define host and phage components influencing transmission of the quorum-sensing-responsive phage VP882 in Vibrio parahaemolyticus populations. Phage VP882 uses the K-antigen of serotype O3:K6 as its receptor. Host cells prevent phage attachment via quorum-sensing-controlled export of polysaccharides that shield the K-antigen from the phage at high cell density. Phage VP882 can superinfect and superlysogenize V. parahaemolyticus, overcoming the challenge of detecting whether or not potential hosts are lysogens. Following superlysogenization, recombination of phage genomes can occur possibly promoting genome diversification. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=144 SRC="FIGDIR/small/712183v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@19c151dorg.highwire.dtl.DTLVardef@2e3a4forg.highwire.dtl.DTLVardef@f64ae4org.highwire.dtl.DTLVardef@1aee428_HPS_FORMAT_FIGEXP M_FIG C_FIG

The emergence of centralized nervous systems reflects a major inflection point in evolution, enabling animals to integrate diverse inputs and coordinate complex behaviors. Neural centralization is typically associated with Bilateria, whereas their sister group, Cnidaria (jellyfish, anemones, and corals), has long been thought to rely on diffuse nerve nets mediating simple reflexes. This view, reinforced by limited anatomical and molecular data, has left unresolved whether cnidarians can form localized centers for neural processing, a question sharpened by the growing recognition of their diverse behavioral repertoires. Here we show that the sea anemone Nematostella vectensis possesses an oral nerve ring composed of ganglion-like condensations, a hallmark of centralized organization. These neurons are enriched for excitatory, inhibitory, and modulatory receptors but lack sensory or ciliary markers, yielding a molecular profile most consistent with bilaterian interneurons. Genetic disruption of a conserved inhibitory receptor subunit predominantly expressed in the oral nerve ring delayed the initiation of swallowing in a novel feeding paradigm, demonstrating a potential role in behavioral regulation. Together, these findings provide converging anatomical, molecular, and functional evidence that cnidarians can assemble localized integrative centers, suggesting that key elements of neural centralization predated the cnidarian-bilaterian split.

Lack of antibody validation by researchers frequently misdirects biomedical research, yet the ethical consequences -- particularly avoidable use of animal and human biological materials -- remain unquantified. Using focus groups (n=12), surveys (n=107), and systematic analysis of 785 publications, we examined how researchers select and validate antibodies, and quantified the downstream ethical costs. Antibody selection is substantially influenced by social factors such as previous laboratory use and peer recommendations, while systematic evaluation of performance characteristics remains limited. From a dataset of 614 antibodies subjected to rigorous characterisation using knockout controls, 97 (15.8%) failed across all tested applications; we systematically searched for publications linked to these antibodies. Within the 760 publications (those where validation status could be confirmed), only 120 (15.8%) presented any validation evidence -- despite 72.0% of surveyed researchers reporting having used at least one recommended validation method. The remaining 640 papers consumed a minimum of 8,064 animal samples and 4,424 human tissue samples using antibodies with demonstrated poor performance, without any evidence confirming fitness for the specific experimental purpose used. Conservative extrapolation suggests millions of animal and human tissue samples have been consumed globally in experiments using antibodies that would fail independent testing. Researchers identified time, cost, and lack of supervisor support as primary barriers, whilst strongly supporting open data sharing, dedicated validation funding, and publisher requirements as solutions. These findings quantify for the first time the ethical costs of inadequate antibody validation and highlight the need for coordinated stakeholder interventions to reduce avoidable biological sample waste in biomedical research.

Root-knot nematodes are obligate plant parasites that cause substantial agricultural losses worldwide. They induce highly specialized, metabolically hyperactive feeding sites within host roots, which serve as their sole source of nutrients throughout their life cycle. The formation and maintenance of these feeding sites depend on the manipulation of host developmental pathways by nematode-derived secretions. Phytosulfokines (PSKs) are small plant peptide hormones that regulate cell division, tissue expansion, and growth responses, processes essential for feeding site development. Here, we identify root-knot nematode genes predicted to encode peptides with a conserved PSK functional motif. These genes are predominantly expressed during the early stages of infection and localize to secretory glands, suggesting a role in early parasitism. Moreover, silencing PSK-like gene expression reduces root gall formation and nematode reproduction. Together, these findings reveal that root-knot nematodes deploy PSK-like peptides as virulence factors to promote successful parasitism, providing the first report of PSK peptide mimicry in any plant pathogen.