Endocrine Disruption in Freshwater Cladocerans: Transcriptomic-Network Perspectives on TBOEP and PFECHS Impacts in Daphnia magna

Endocrine Disruption in Freshwater Cladocerans: Transcriptomic-Network Perspectives on TBOEP and PFECHS Impacts in Daphnia magna | 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 Endocrine Disruption in Freshwater Cladocerans: Transcriptomic-Network Perspectives on TBOEP and PFECHS Impacts in Daphnia magna Hyun Woo Kim, Seok-Gyu Yun, Ju Yeon Park, Jun Lee, Dong Yeop Shin, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7224759/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Freshwater cladocerans such as Daphnia magna are keystone grazers whose hormone‑regulated life‑history traits make them sensitive sentinels of endocrine‑disrupting chemicals (EDCs). The organophosphate flame‑retardant tris(2‑butoxyethyl) phosphate (TBOEP) and perfluoroethylcyclohexane sulfonate (PFECHS) now co‑occur at ng L⁻¹–µg L⁻¹ in surface waters, yet their chronic sub‑lethal impacts on invertebrate endocrine networks remain unclear. We analysed two publicly available 21‑day microarray datasets (TBOEP: GSE55132; PFECHS: GSE75607) using Gene Ontology enrichment, STRING protein‑interaction networks, Drosophila phenotype mapping and KEGG(Kyoto Encyclopedia of Genes and Genomes) ‑anchored frameworks to build putative adverse outcome pathways (AOPs) for D. magna. Differentially expressed genes were clustered into functional modules and hub nodes ranked by degree and betweenness. TBOEP suppressed molting and growth, altering 1 157 genes enriched for metabolism and membrane processes; hubs VRK1, MIB2 and adenylosuccinate synthetase formed a muscle anatomical development sub‑network. PFECHS down‑regulated vitellogenin and shifted 879 genes dominated by oxidative‑stress and glutathione‑metabolism signatures; central nodes UBC9, eIF4A‑III, Tra‑2α and HDAC1 linked meiotic‑cycle, oogenesis and cyclic‑compound binding. Despite chemical dissimilarity, both compounds converged on Wnt‑signalling nodes—TBOEP via presenilin‑1, PFECHS via CK1ε/CK2—thereby reducing TCF/LEF‑dependent transcription. Predicted outcomes include impaired oocyte maturation, reduced fecundity and stunted body size, consistent with observed decreases in length and vitellogenin protein. Our network analysis indicates that environmentally relevant concentrations of TBOEP and PFECHS destabilise endocrine, developmental and metabolic pathways in D. magna without overt lethality, foreshadowing population‑level repercussions for freshwater plankton dynamics. Hub genes and Wnt‑mediated key events emerge as sensitive biomarkers for monitoring mixed EDC exposure. Daphnia magna endocrine disruption TBOEP PFECHS transcriptomic analysis adverse outcome pathway (AOP) Figures Figure 1 Figure 2 Introduction Endocrine‑disrupting chemicals (EDCs) are exogenous substances that alter hormone synthesis, metabolism, transport, or receptor signaling, thereby impairing growth, development, and reproduction in exposed organisms (Diamanti‑Kandarakis 2009). Notably, freshwater ecosystems receive a continuous influx of industrial effluent, agricultural runoff, and municipal wastewater, exposing aquatic species to complex EDC mixtures (Schwarzenbach 2010; Li 2020). Although early research focused on vertebrates, classic field observations, such as tributyltin‑induced imposex in marine gastropods, have demonstrated that invertebrate taxa are equally vulnerable and that endocrine disruption can drive population‑level changes (Gibbs and Bryan 1986 ). Daphnia magna (D.magna) is a widely used sentinel for detecting endocrine disruption. The lifecycle of D. magna is exquisitely hormone‑dependent, with juvenile hormones regulating the transition from clonal to sexual reproduction, while ecdysteroids control molting and somatic growth. Consequently, shifts in sex ratio, fecundity, or molting frequency provide sensitive read‑outs of endocrine perturbation (Olmstead and LeBlanc 2002 ; De Fraine 2019). Owing to its well‑characterized life history, short generation time, and extensive genomic resources, D. magna is routinely used to screen chemicals that target invertebrate hormonal pathways. Among the many contaminants detected in surface waters, two compounds warrant scrutiny: tris(2‑butoxyethyl) phosphate (TBOEP), a high‑production‑volume organophosphate flame retardant that is now ubiquitously identified at microgram‑per‑liter levels (Ballesteros‑Gómez 2014). Chronic exposure of D. magna to environmentally relevant TBOEP concentrations (≈ 10 µg L⁻¹) dysregulates transcripts in juvenile‑hormone and ecdysteroid pathways, lowers molting frequency, and retards growth without causing acute lethality (Giraudo 2017). Studies in zebrafish have revealed altered hypothalamic–pituitary–gonadal gene expression, elevated male estradiol levels, and reduced fecundity, underscoring the cross‑phylum endocrine activity of TBOEP (Wang 2019). Perfluoroethylcyclohexane sulfonate (PFECHS), used in aviation hydraulic fluids, also persists in remote waters at nanogram‑per‑liter concentrations (Gomis 2018). A 12‑day exposure of D. magna to sub‑milligram levels markedly suppressed vitellogenin mRNA and protein while up‑regulating cuticle‑synthesis genes, indicating sub‑lethal endocrine interference without immediate effects on survival or reproduction (Houde 2018). Adverse outcome pathway (AOP) frameworks provide a structured means to link a molecularinitiating event through successive key events to apical outcomes that are ecologically relevant and regulatoryready (Ankley 2010; Yang SW 2017). Integrating highcontent transcriptomics with AOP thinking allows early mechanistic signals—such as Wnt/βcatenin perturbation (Nusse & Clevers 2017 )—to be traced to reproductive endpoints in cladocerans. The pervasive occurrence of TBOEP and the extreme persistence of PFECHS suggest that D. magna populations experience chronic, low‑level exposure capable of disrupting endocrine homeostasis and, by extension, freshwater ecosystem function. Even at low ambient concentrations, evidence exists of endocrine‑mediated effects at higher doses, raising concern about cumulative or mixture‑driven impacts. Since D. magna influences water‑column clarity and serves as prey for higher trophic levels, any impairment of its reproduction or development could cascade through planktonic communities. Therefore, clarifying the molecular mechanisms, effects, and consequences of TBOEP and PFECHS exposure is critical for robust ecological risk assessment and informed chemical management. The present study integrates public transcriptomic datasets, Gene Ontology enrichment, interaction network analysis, and adverse‑outcome‑pathway construction to elucidate how chronic exposure to these two EDCs reshapes endocrine‑regulated processes in D. magna. Materials and Methods Transcriptomic datasets and preprocessing Wholeanimal microarray data for D.magna chronically exposed to TBOEP or PFECHS were retrieved from the NCBI Gene Expression Omnibus (GEO). The TBOEP study corresponds to series GSE55132, profiling animals after a 21day exposure to 1 470 µg L⁻¹ on the Agilent 4 × 44 K platform (GPL16592). The PFECHS study corresponds to series GSE75607, generated under identical platform conditions following a 21day exposure to 6 mg L⁻¹. Raw files were imported into R v4.3.1. Background correction and withinarray normalisation were performed with the limma package. Where multiple probes targeted the same transcript, signals collapsed to the median intensity. Differential expression was assessed using an empirical Bayesmoderated t statistic; transcripts with |log₂fold change| ≥ 1.0 and a Benjamini–Hochberg falsediscovery rate (FDR) < 0.05 were retained as differentially expressed genes (DEGs). Functional enrichment analysis Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) term enrichment was performed in clusterProfiler v4.8.1 with the D. magna background (taxon 35525). GO terms (biological process, cellular component, molecular function) with FDR 0.4; “ D. magna ” organism filter). Resulting interaction tables were imported into Cytoscape v3.10.3. Network topologies were analysed with node degree and betweennesscentrality scores were calculated, and the top-10 ranked genes were defined as hub genes. Adverse outcome pathway (AOP) inference Putative molecular key events (MKEs) were anchored to KEGG pathway ko04310 (Wnt signalling). Candidate stressor/MKE, MKE/MKE and MKE/adverseoutcome links were extracted with AOPhelpFinder v3.0 (query terms: “TBOEP” or “PFECHS” AND “ Daphnia OR invertebrate”). Literature cooccurrence scores ≥ 2 were accepted. Final AOP schematics were rendered in Cytoscape v3.10.3. Results and Discussion TBOEP Toxicity and Transcriptomic Insights TBOEP is detected in surface waters worldwide, and its chronic presence is recognised as an ecological concern (BallesterosGómez 2014). Multigenerational 21-day assays with Daphnia magna report unchanged survival and brood production but significant reductions in body length and molting frequency, accompanied by persistent transcriptional shifts in ecdysteroid and juvenile hormone pathways that control growth and reproduction (Giraudo 2017). Complementary vertebrate data strengthen the endocrinedisruption signal: adult zebrafish maintained for 21-days at 5–500 µg L⁻¹ produce fewer eggs, their progeny hatch and survive less often, and histology shows arrested oocyte maturation and delayed spermiation, coincident with elevated 17βestradiol, altered testosterone and broad disruption of hypothalamic–pituitary–gonadal transcripts (Wang et al. 2019 ). Embryos exposed to 2–200 µg L⁻¹ develop oedema and skeletal deformities, while hormonesynthesis genes are suppressed and receptor genes induced across thyroid, gonadal axes—confirming endocrine dysregulation during development (Han 2014). Beyond endocrine effects, oxidativestress responses have also been recorded: in D. magna , catalase activity drops in the F₁ generation after 28-days at 20 µg L⁻¹, glutathione Stransferase and heatshockprotein transcripts fall at low doses, and ABCtransporter genes rise only at milligramperlitre levels (Giraudo 2017). Additional mechanistic insight is provided by analysis of the public microarray dataset GSE55132, which profiles wholebody RNA from D. magna exposed to 1 470 mg L⁻¹ TBOEP for 21-days. DEGs were extracted, followed by geneontology enrichment, interactionnetwork synthesis and formulation of a putative adverseoutcome pathway. The resulting GO terms, DEGcentred protein network and AOP framework together outline how chronic TBOEP exposure perturbs metabolic processes, membrane integrity and hormoneregulated development, thereby linking transcriptomic disturbances to the observed impairments in growth and reproduction. GO Enrichment in TBOEP Exposure The top 10 activated and suppressed biological processes (BPs), cellular components (CCs), and molecular functions (MFs) were discovered, with falsediscovery rate (FDR) < 0.05, respectively. The top 10 activated and six suppressed BPs were observed, with the ontology cellular process occurring in both lists. Activated BPs were predominantly associated with metabolicprocessrelated GO terms, whereas in the suppressed BPs positive regulation of transport was identified. In many animals there is an association between metabolism and reproduction. In C. elegans , lipid metabolism is regulated by signals from the reproductive system (Hansen 2013). Additionally, in humans, successful reproduction is associated with regulated energy metabolism (Seli 2014). Therefore, it can be inferred indirectly that abnormalities in metabolism due to chronic exposure to TBOEP affect the reproductive capacity of Daphnia magna . Among 10 activated and five suppressed statistically significant CCs, ontologies including cellular anatomical entity , cytoplasm , intercellular anatomical structure , and intracellular organelle were concurrently identified. In the activated CCs, GO terms related to anatomical entities and membranes were observed (Table 1 ). Similarly, in the suppressed CCs, identified ontologies were related to anatomical entities and membranes. Both activated and suppressed CCs indicate abnormalities within cell components and cell membranes. Considering that damaged cells are replaced by new cells through apoptosis, chronic exposure to TBOEP can affect the developmental stages of D. magna offspring. Statistically significant MFs were identified, with five activated and one suppressed. The activated MFs primarily include catalyticactivity and bindingrelated ontologies, while the suppressed MF is associated with binding. From the perspective of TBOEP as an endocrine disruptor, ontologies related to binding can be interpreted as the process of reproductive hormones binding to receptors, and ontologies related to catalytic activity can be seen as the breakdown process of reproductive hormones (Table 2 ). In brief, activated biological processes are primarily related to metabolism, whereas suppressed processes involve transport regulation. Chronic TBOEP exposure may disrupt metabolism, affecting reproductive capacity. Additionally, abnormalities in cellular components and membranes were noted, potentially impacting D. magna offspring development. Molecular functions mainly involve catalytic activity and binding, suggesting effects on reproductivehormone interactions and breakdown. Table 1 Top 10 Gene Ontology terms for up‑regulated DEGs and the top 10 GO terms for down‑regulated DEGs in D. magna subjected to chronic TBOEP exposure. GO term category Activated GO Suppressed GO GO term FDR GO term FDR Biological process Cellular process 0.00018 Biological regulation 2.10E-03 Metabolic process 0.00051 Cellular process 2.10E-03 Organic substance metabolic process 0.00068 Regulation of cellular process 1.13E-02 Primary metabolic process 0.0013 Regulation of biological process 0.0174 Protein metabolic process 0.0017 Positive regulation of transport 0.0335 Organonitrogen compound metabolic process 0.0017 Positive regulation of biological process 0.0483 Macromolecule metabolic process 0.0017 - - Nitrogen compound metabolic process 0.0017 Protein localization 0.0043 Cellular localization 0.0099 Cellular component Cellular anatomical entity 1.8E-13 Cellular anatomical entity 6.44E-08 Intracellular anatomical structure 3.16E-08 Cytoplasm 3.16E-06 Cytoplasm 1.62 E-07 Intracellular anatomical structure 1.29E-05 Endomembrane system 0.0016 Intracellular organelle 0.0056 Membrane-bounded organelle 0.0018 Membrane 0.0072 Intracellular membrane-bounded organelle 0.0018 - - Intracellular organelle 0.0018 Protein-containing complex 0.0053 Dendritic shaft 0.0091 Cytoplasmic vesicle 0.0096 Molecular function Catalytic activity 2.40E-04 Binding 0.00033 Protein binding 5.70E-03 - - Catalytic activity, acting on a protein 3.00E-02 Hydrolase activity 0.03 Binding 0.032 Table 2 Endocrinerelated Gene Ontology categories for upregulated and downregulated DEGs in D. magna following chronic exposure to TBOEP. Network type GO term category GO term FDR Main network Biological process Organic substance biosynthetic process 1.56E-02 Organic substance transport 2.21E-02 Anatomical structure development 3.63E-02 Muscle structure development 4.39E-02 Collagen trimer 4.83E-02 TBOEP Functional network evidence To gain insights into the key DEGs of TBOEP in D.magna , protein–protein interactions (Fig. 1 A) were illustrated from STRING‑DB. These interactions clarify how numerous DEGs inter‑connect at the molecular level. The proteins encoded by DEGs, regardless of their expression patterns, were jointly subjected to GO analysis, which highlighted terms linked to the synthesis and transport of organic substances, developmental processes and collagen trimers (Table 1 ). Within an endocrine context, Organic substance biosynthetic process maps to hormone synthesis, whereas Organic substance transport aligns with hormone trafficking. Two further GO biological‑process (BP) terms related to development were also enriched. For a comprehensive view of TBOEP toxicity, we built a biological network (Fig. 1 B) that integrates protein–protein, protein–cell‑process and protein–orthologous‑phenotype relationships. Five statistically significant (FDR < 0.05) GO terms associated with endocrine disruption were recovered among biological processes; none were significant for cellular components (CCs) or molecular functions (MFs). Organic substance biosynthetic process and organic substance transport relate to reproductive‑hormone metabolism because steroid hormones such as oestrogen and progesterone are organic molecules. Ontologies describing anatomical and muscle‑structure development imply that chronic TBOEP exposure during early life stages disrupts organogenesis—especially of muscle. When D. magna muscles malfunction, animals experience restricted swimming, cardiac‑rhythm abnormalities and impaired movement of the head, eyes and other appendages (Hoffschröer 2024; Watanabe 2024; Chea 2017). To predict phenotypes, DEGs were first matched to Drosophila melanogaster orthologues with BLASTp because phenotype–protein links are sparse for D. magna. The well‑annotated fruit‑fly data set enabled inference of size‑ and reproduction‑related phenotypes via FlyBase. Central genes were mined from the STRING network (Fig. 1 A) using edge degree and betweenness‑centrality scores. Six hubs emerged: LOC116918246 (serine/threonine‑protein kinase VRK1), LOC116935564 (E3 ubiquitin–protein ligase MIB2), LOC116924990 (adenylosuccinate synthetase), LOC116918466 (28S ribosomal protein S2, mitochondrial), LOC116921285 (tyrosine‑tRNA ligase, cytoplasmic) and LOC116917541 (glutamine synthetase). VRK1 is broadly expressed across zebrafish tissues (Xu 2023) and is essential for early embryogenesis in Drosophila (González‑Martínez 2024). MIB2 participates in post‑translational regulation in all major eukaryotic lineages (Mukherjee & Rotin 2013 ) and mediates ubiquitination to activate Notch signalling in zebrafish (Itoh 2006). Adenylosuccinate synthetase fuels ATP synthesis under stress in D. magna (Becker 2019) and influences vertebrate eye development. A condensed network (Fig. 1 C) that links these hubs to cell‑process and orthologous‑phenotype nodes highlights associations with anatomical and muscle‑structure development, reproduction and infertility. TBOEP Putative AOP analysis A putative adverseoutcome pathway (AOP) for TBOEP exposure in D. magna was derived from the KEGG Wntsignalling pathway (Fig. 1 D). Given that genetic based analysis, it is difficult to find molecular initiating event (MIE) about reproductive and developmental toxicity of TBOEP. We constructed a putative AOP if PS-1 changed after the pMIE following chronic exposure to TBOEP. The expression change of PS-1 alters the expression level of β-catenin, thereby impacting TCF/LEF family. These three biological events are regarded as key events (KEs) and adverse outcomes (AO) can be described as abnormal transcription of target genes such as oocyte maturation early development. Through the putative AOP, we present that TBOEP exposure occurs abnormal transcriptions involved in female reproduction and development in D.magna. In summary, we identified DEGs derived from the transcriptome of whole D. magna which had been exposed to TBOEP during 21-days. We suggest that the meaning of DEGs using gene ontology, protein-protein network, orthological phenotype, and putative AOP. At the cellular level, the chronic exposure of TBOEP makes unusual metabolism, abnormal cell anatomical structure, decreasing offspring development, and binding. This suggests that chronic exposure of TBOEP effects reproduction and reproductive hormone metabolism. Through biological network and orthological phenotypes, we achieved a comprehensive understanding of the chronic toxicity of TBOEP through network construction (Fig. 1 B). Through TBOEP chronic toxicity network, it was possible to identify phenotypes associated with size and reproduction related adverse effects. In the condensed network (Fig. 1 D), adverse effects on reproduction related phenotypes and muscle development could be observed. Additionally, it was evident that genes LOC116918246, LOC116935564, and LOC116924990 may play a crucial role in the chronic toxicity mechanism of TBOEP. For intuitive insights of chronic toxic mechanisms, we suggest putative AOP based on KEGG pathway. The putative AOP showed that TBOEP induces changes in the expression of PS-1 potentially leading to the occurrence of abnormal transcription of target genes such as oocyte maturation and early development. PFECHS Toxicity and Transcriptomic Insights PFECHS is a cyclic PFAS used in aviation hydraulic fluids and has been measured in river water at low nanogram‑per‑litre concentrations, (Muñoz 2017) its toxicology is only recently described (Gomis 2018). When D. magna were exposed for 12-days to 0.06–six mg L⁻¹, vitellogenin transcripts and protein content fell sharply while survival, molting, and brood size remained unchanged, signalling an anti‑estrogenic endocrine‑disrupting action likely to impair oocyte provisioning if exposure persists (Houde 2018). Vertebrate evidence is consistent: zebrafish embryos and larvae raised in 500 ng L⁻¹ to two mg L⁻¹ PFECHS developed edema and skeletal malformations at frequencies comparable to those caused by legacy PFOS, although mortality was lower; transcriptomic analysis showed induction of lipid‑metabolism and detoxification genes including pparα and cyp1a1 at concentrations near environmental relevance, indicating metabolic imbalance and activation of chemical‑stress defences (Gomis 2018). These invertebrate and vertebrate data together reveal that PFECHS, much like the compounds it was meant to replace, perturbs endocrine function, development, and energy metabolism even at sub‑lethal doses, underscoring the need for extended and multigenerational studies to gauge its population‑level impact. The GSE75607 dataset shared in the public database consists of gene expression data evaluating reproductive performance in D. magna following chronic exposure to PFECHS. The gene expression data conducted by Houde M et al., following OECD guidelines (OECD 2008 ; Houde 2018), encompass the adverse effects of chronic exposure to 6 mg L⁻¹ of PFECHS for 21-days. From the dataset, we extracted DEGs and interpreted the chronic toxicity effects of PFECHS through gene ontology (GO) enrichment, constructing network, and the presenting putative AOP based on the DEGs. GO Enrichment in PFECHS Exposure To elucidate the cellular significance of DEGs elicited by chronic PFECHS exposure, the gene‑ontology profiles of activated and suppressed transcripts were examined. Activated or suppressed DEGs were assigned to biological processes (BPs), cellular components (CCs) and molecular functions (MFs); ontologies with a false‑discovery rate < 0.05 were retained, and the ten most significant terms per category were collated (Table 3 ). Among the ten activated and suppressed BPs, metabolic-process terms were dominant in both lists. ‘Cellular process’, ‘metabolic process’, ‘organic-substance metabolic process’, ‘nitrogen-compound metabolic process’, and ‘primary metabolic process’ appeared in common. Excluding metabolic terms, activated BPs included ‘response to stimulus’, ‘regulation of biological quality’, ‘glutathione metabolic process’, and ‘response to ethanol’, whereas suppressed BPs uniquely contained ‘biological regulation’, ‘cellular-component organization or biogenesis’, and ‘regulation of biological process’. Notably, the activation of ‘glutathione metabolic process’ indicates a response to oxidative stress, as glutathione-dependent antioxidants such as GPX4 protect gametes and pre-implantation embryos from reactive oxygen species; GPX4 disruption leads to infertility and early embryonic lethality, potentially affecting reproductive functions and early development. Such activation can reduce cell-division fidelity and implantation rates at the earliest embryonic stages. Suppression of ‘organonitrogen compound metabolic process’ may be linked to gametogenesis, because de-novo amino-acid synthesis and nitrogen recycling fuel chromatin remodeling and ATP-intensive meiotic stages. Statistically significant activated or suppressed CCs were identified based on the top 10 ontologies with the lowest FDR (Table 4 ). Among these, ‘cellular anatomical entity’, ‘cytoplasm’, ‘intracellular anatomical structure’, ‘organelle’, and ‘intracellular organelle’ were common. Activated CCs were enriched for fiber, organelle, and extracellular-structure terms; suppressed CCs highlighted protein complexes, organelles, and the extracellular structure. Within activated CCs, fiber-related terms such as ‘sarcomere’, ‘supramolecular fiber’, and ‘Z disc’ suggest adverse effects of PFECHS on myofilament. In suppressed CCs, terms such as ‘protein-containing complex’ and ‘ribonucleoprotein complex’ predominated. The suppression of cell-structure-associated ontologies such as ‘membrane-bounded organelle’ implies impaired redistribution of the endoplasmic reticulum and mitochondria, which coordinate Ca²⁺ signaling and maternal mRNA storage—processes essential for oocyte maturation and embryonic developmental competence. Conversely, the prevalence of myofilament-related terms among suppressed CCs suggests interference with sarcomere assembly; for example, loss of the sarcomere-assembly factor Smyd1b disrupts early muscle formation and subsequently lowers developmental and hatching success. In both activated and suppressed MFs, ‘catalytic activity’, ion binding’, ‘binding’, and ‘protein binding’ were common. Unique activated MFs were detoxification-related—e.g., ‘oxidoreductase activity’, ‘glutathione transferase activity’, and other transferase activities—whereas unique suppressed MFs were largely binding-related (cyclic-compound-binding and nucleic-acid-binding terms). Activated MFs related to binding non-protein substances, hormones, or other molecules critical for reproduction. Suppressed MFs showed oxidative-stress-related terms such as ‘Oxidoreductase activity’ and ‘Glutathione transferase activity’, indicating altered ROS-detoxification pathways vital for reproductive health. Table 3 Top 10 Gene Ontology terms for up‑regulated DEGs and the top 10 GO terms for down‑regulated DEGs in D. magna subjected to chronic PFECHS exposure. GO term category Activated GO Suppressed GO GO term FDR GO term FDR Biological process Cellular process 9.71E-17 Cellular process 1.98E-88 Metabolic process 4.73E-11 Organic substance metabolic process 1.95E-51 Organic substance metabolic process 9.28E-10 Metabolic process 2.07E-51 Organonitrogen compound metabolic process 1.26E-08 Primary metabolic process 1.23E-50 Response to stimulus 4.84E-08 Nitrogen compound metabolic process 5.18E-50 Primary metabolic process 1.23E-06 Macromolecule metabolic process 3.06E-48 Nitrogen compound metabolic process 1.40E-05 Cellular metabolic process 5.02E-45 Regulation of biological quality 3.83E-05 Biological regulation 4.19E-43 Glutathione metabolic process 6.61E-05 Cellular component organization or biogenesis 8.24E-42 Response to ethanol 1.10E-04 Regulation of biological process 2.60E-38 Cellular component Cellular anatomical entity 3.54E-23 Intracellular anatomical structure 2.37E-105 Cytoplasm 6.45E-08 Cellular anatomical entity 1.45E-96 Sarcomere 4.75E-06 Intracellular organelle 1.35E-71 Intracellular anatomical structure 5.18E-06 Organelle 4.54E-71 Extracellular region 6.61E-06 Intracellular membrane-bounded organelle 1.83E-59 Supramolecular fiber 1.10E-04 Protein-containing complex 3.80E-57 Membrane 1.10E-04 Membrane-bounded organelle 3.80E-57 Z disc 2.30E-03 Nucleus 3.64E-52 Organelle 2.90E-03 Cytoplasm 6.12E-50 Intracellular organelle 7.60E-03 Ribonucleoprotein complex 1.14E-35 Molecular function Catalytic activity 5.48E-12 Binding 2.38E-65 Ion binding 1.93E-07 Organic cyclic compound binding 6.34E-49 Binding 5.32E-07 Heterocyclic compound binding 2.18E-48 Cation binding 5.22E-05 Nucleic acid binding 1.03E-28 Oxidoreductase activity 2.10E-04 RNA binding 5.49E-27 Glutathione transferase activity 2.50E-04 Protein binding 3.23E-26 Metal ion binding 3.00E-04 Ion binding 7.42E-22 Transferase activity 6.70E-04 Catalytic activity 1.38E-20 Catalytic activity, acting on a protein 2.50E-03 Small molecule binding 4.93E-20 Protein binding 2.80E-03 Carbohydrate derivative binding 6.75E-20 Table 4 Endocrinerelated Gene Ontology categories for upregulated and downregulated DEGs in D. magna following chronic exposure to PFECHS. Network type GO term category GO term FDR Main network Biological process Organic substance biosynthetic process 5.44E-09 Developmental process 2.60E-04 Cellular process involved in reproduction in Multicellular organism 4.60E-04 Anatomical structure development 5.10E-04 Reproductive process 5.60E-04 Female gamete generation 2.50E-03 Organic substance transport 7.50E-03 Developmental process involved in reproduction 9.40E-03 Multicellular organism development 1.63E-02 Meiotic cell cycle process 1.79E-02 Germ cell development 3.46E-02 Meiotic nuclear division 3.88E-02 Oogenesis 4.01E-02 Female meiotic nuclear division 4.15E-02 Cellular component Meiotic spindle 1.05E-02 Molecular function Organic cyclic compound binding 1.41E-43 PFECHS Functional network evidence For comprehensive understanding of the toxic mechanisms of PFECHS in D. magna, biological network was constructed using protein‑protein interactions, cell processes, orthological diseases. Protein‑protein interactions were collected from STRING‑DB within D. magna. A network based on the protein‑protein interaction was constructed for comprehensive understanding reproductive toxicity of PFECHS (Fig. 2 A). The biological network consists of protein‑protein interactions, protein‑cell process relationships and protein‑orthological phenotype relationships (Fig. 2 B). The proteins constituting the biological network are encoded by DEGs, with their expression changes mirroring those of DEGs. To elucidate the biological functions of this network at cellular level, gene ontologies were identified among DEGs encoding proteins, regardless of its expression pattern. After confirming statistically significant (FDR < 0.05) gene ontologies associated with reproduction, a total of 14 ontologies were identified in biological processes (BPs), while one each was found in cellular component (CC) and molecular function (MF). Among the BPs, development, reproduction, and organic substances metabolism related ontologies were identified, whereas ontologies associated with cell division were identified in CC and organic compound binding in MF. To find putative phenotypes based DEGs in D. magna, transcribed proteins of DEGs were converted to proteins of Drosophila melanogaster (D. melanogaster), one of fruit flies, using NCBI BLASTp. Because the limited information on the relationships among phenotype‑related proteins in D. magna is attributed to the lack of studies on phenotype. Conversely, for evolutionary proximate species like fruit flies, extensive research on phenotype has resulted in abundant information (Altschul 1990; Gramates 2022). We identified phenotypes associated with reproduction and development in D. melanogaster from FlyBase (proteins of DEGs). We obtained orthological phenotypes, including abnormal developmental rate, abnormal size, fertile, abnormal oxidative stress response. To identify central genes in the reproductive and developmental toxicity network of PFECHS, each gene in the protein‑protein interaction network (Fig. 2 A) was assessed based on two parameters: edge degree and betweenness centrality. LOC116919267 (SUMO‑conjugating enzyme UBC9), LOC116919853 (eukaryotic initiation factor 4A‑III), LOC116919548 (transformer‑2 protein homolog α), and LOC116923253 (histone deacetylase 1) displayed high significance in the network. Based on these central proteins, condensed network (Fig. 2 C) was constructed using interactions between central proteins and interactions of central protein‑cellular process and central protein‑orthologous phenotype. These genes are in critical reproductive and developmental functions, from specific cellular processes in multicellular organisms to the development of anatomical structures (Li 2012; Palacios 2004; Amrein 1994; Ma & Schultz 2008 ). They are particularly significant in the generation and development of gametes, such as in oogenesis and the meiotic cycle. Furthermore, the meiotic spindle in chromosome separation and the binding of DEGs to organic cyclic compounds, which may influence hormone function, the altered regulation of reproduction‑related VTG1 and YLK suggest that the interaction with the signaling hormones could alter reproduction in D. magna as these proteins are essential to the feeding reserve of developing embryos (Tufail & Takeda 2008 ). This suggests a network of genes that are crucial for regulating reproductive health and development, providing insights into the genetic interactions that support these biological functions. In the condensed network, reproductive‑related phenotypes such as fertility and reproductive‑related cellular processes, particularly 'female gamete generation' and 'female meiotic nuclear division,' were observed (Schwenk et al. 2001 ). This suggests that the four central genes could be involved in the reproductive toxicity mechanism of PFECHS in D. magna, which reproduces parthenogenesis. PFECHS Putative AOP analysis The putative AOP of PFECHS exposure to D. magna (Fig. 2 D) was outlined from the KEGG Wnt‑signalling pathway. Because a definitive molecular‑initiating event (MIE) could not be resolved from the available transcriptomic evidence, the model postulates an initial perturbation of CK1ε and CK2 expression (pMIE). Altered CK1ε/CK2 levels are predicted to remodel the Dishevelled (DVL) scaffold and, in turn, attenuate TCF/LEF transcriptional activity. These sequential changes constitute three key events (KEs), after which transcription of targets governing oocyte maturation and early development is impaired. Downstream DEGs include vtg1, yolkless and multiple cyclins, indicating disrupted yolk‑protein uptake, nutrient provision and cell‑cycle progression in developing oocytes. At the organismal level, such molecular defects are consistent with the observed suppression of vitellogenin protein and the lack of overt lethality despite impaired reproductive output. Integrating these findings with oxidative‑stress signatures—e.g. up‑regulation of glutathione‑metabolism genes—suggests that PFECHS imposes combined endocrine and redox pressure, which may compound over successive generations. The pathway therefore links CK1ε/CK2‑mediated Wnt disruption to transcriptional dysregulation of female reproductive processes and provides a mechanistic framework for evaluating sub‑lethal PFAS impacts in freshwater cladocerans. Conclusion EDCs threaten aquatic ecosystems by disturbing hormone-controlled growth and reproduction. Among them, the flame retardant TBOEP and PFECHS now occur from surface waters and persist in wastewater discharge. Chronic exposure of D. magna to environmentally TBOEP levels reduced body length and molting while shifting juvenile-hormone and ecdysteroid transcripts. PFECHS exposure suppressed vitellogenin, altered cuticle-synthesis genes, and activated detoxification pathways without acute lethality. Gene-expression profiling (GSE55132, GSE75607) confirmed broad changes in metabolism, cellular processes, and reproduction. Both datasets pointed to Wnt-signal interference and highlighted central hubs UBC9 (LOC116919267) and eIF4A-III (LOC116919853) that bridge oxidative stress and meiotic control. Functional-enrichment and network analyses allowed construction of putative adverse-outcome pathways (AOPs) linking CK1ε/CK2-mediated Wnt disruption to impaired oogenesis and embryonic development. These molecular events explain how low-level, long-term exposure can erode D. magna fitness and, by extension, alter plankton dynamics essential for water-column clarity and food-web stability. Understanding such mechanisms is critical for ecological risk assessment and chemical management. Further studies that time-resolved transcriptomics are needed to gauge mixture effects and to refine water-quality criteria that safeguard freshwater biodiversity and human communities reliant on these ecosystems. Declarations Funding: This work was supported by the Korea Environment Industry & Technology Institute (KEITI) through the Core Technology Development Project for Environmental Diseases Prevention and Management Program, funded by South Korea’s Ministry of Environment (MOE) (grant number 2022003310012) Competing Interests: The authors have no relevant financial or non‑financial interests to disclose. Author Contributions : Young Rok Seo and Eun-Min Cho designed the research study. Hyun Woo Kim, Seok-Gyu Yun performed an overall analysis procedure and wrote the manuscript. Hyun Woo Kim wrote the manuscript with Seok-Gyu Yun. Dong Yeop Shin and Jong Hun Lee composed the figures with Hyun Woo Kim. Ju Yeon Park and Seok-Gyu Yun investigated information. All authors have read and agreed to the published version of the manuscript. Conflicts of Interest : The authors declare no conflict of interest. The funders had no role in the design of the study, in the collection, analyses, or interpretation of data. Ethics approval: This article does not contain any studies of human participants or animals performed by any of the authors. Consent to participate: Not applicable. Consent to publish: Not applicable. Supplementary Materials: There is no supplementary data in this article. Data Availability: No new data were created or analyzed in this study. Data sharing is not applicable to this article. References Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local alignment search tool. 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Environ Chem 7:336–342. https://doi.org/10.1071/EN09124 Houde M, Muñoz G, Giraudo M, et al (2018) Transcriptomic responses of Daphnia magna to perfluoroethylcyclohexane sulfonate (PFECHS). Environ Toxicol Chem 37:2801–2810. https://doi.org/10.1002/etc.4247 Itoh M, Kim CH, Palardy G, et al (2006) Mind bomb 2 is required for lateral inhibition and cell‑fate specification regulated by Notch signalling in zebrafish. Development 133:2045–2055. https://doi.org/10.1242/dev.02342 Li Y, Huang W, Zhang X, Fang C, Tang J, Yu Y (2020) Environmental fate and risk of organophosphate flame retardants in wastewater treatment plants: a review. J Clean Prod 263:121475. https://doi.org/10.1016/j.jclepro.2020.121475 Li Y, Zhang H, Choi SC, et al (2012) Ubc9 is essential for early embryonic development and contributes to histone H3K4 methylation in mice. Biochem Biophys Res Commun 419:666–671. https://doi.org/10.1016/j.bbrc.2012.02.058 Ma P, Schultz RM (2008) Histone deacetylase 1 regulates meiotic progression in mouse oocytes. Development 135:199–208. https://doi.org/10.1242/dev.012138 Mukherjee A, Rotin D (2013) Regulation of Notch signalling by the ubiquitin ligase Mind bomb 2. J Biol Chem 288:14724–14734. https://doi.org/10.1074/jbc.M113.453241 Muñoz G, Giraudo M, Houde M, et al (2017) Perfluoroethylcyclohexane sulfonate (PFECHS) in Canadian surface waters: occurrence and distribution. Environ Sci Technol 51:13697–13705. https://doi.org/10.1021/acs.est.7b01929 Nusse R, Clevers H (2017) Wnt/β‑catenin signaling, disease, and emerging therapeutic modalities. Cell 169:985–999. https://doi.org/10.1016/j.cell.2017.05.016 OECD (2008) Test No. 211: Daphnia magna Reproduction Test. OECD Guidelines for the Testing of Chemicals, Section 2. OECD Publishing, Paris. Olmstead AW, LeBlanc GA (2002) Juvenoid hormone methyl farnesoate is a sex determinant in the crustacean Daphnia magna . J Exp Zool 293:736–739. https://doi.org/10.1002/jez.10162 Palacios IM, St Johnston D, Kiebler MA (2004) eIF4AIII couples translation to mRNA localisation in Drosophila oocytes. Nature 427:753–757. https://doi.org/10.1038/nature02351 Schwarzenbach RP, Egli T, Hofstetter TB, et al (2010) Global water pollution and human health. Annu Rev Environ Resour 35:109–136. https://doi.org/10.1146/annurev‑environ‑100809‑125342 Schwenk K, Spaak P, Hochkirch A (2001) Parthenogenesis in Daphnia : patterns and consequences. Hydrobiologia 442:291–303. https://doi.org/10.1023/A:1017519331775 Seli E, Babayev E, Collins SC, et al (2014) Metabolism of female reproduction: regulatory mechanisms and clinical implications. Mol Endocrinol 28:790–804. https://doi.org/10.1210/me.2013‑1413 Tufail M, Takeda M (2008) Molecular characteristics of insect vitellogenins. J Insect Physiol 54:1447–1458. https://doi.org/10.1016/j.jinsphys.2008.08.007 Wang Q, Lam JCW, Man YB, et al (2019) Tris(2‑butoxyethyl) phosphate disrupts reproduction in zebrafish ( Danio rerio ). Environ Sci Technol 53:8187–8196. https://doi.org/10.1021/acs.est.9b01218 Watanabe K, Pintado P, Yoshida M, Zeis B (2024) The neurogenesis patterns underlying behavioural flexibility in Daphnia magna . J Exp Biol 227:jeb246132. https://doi.org/10.1242/jeb.246132 Xu JF, Kim JH, Lee S (2023) Tissue‑specific expression atlas and developmental functions of VRK family kinases in zebrafish. Dev Dyn 252:1550–1565. https://doi.org/10.1002/dvdy.609 Yang SW, Kim HJ, Choi JY, Rhee JS (2017) Cadmium‑induced biomarkers and adverse‑outcome‑pathway prediction in Daphnia magna revealed by transcriptome network analysis. Mol Cell Toxicol 13:389–400. https://doi.org/10.1007/s13273‑017‑0036‑3 Additional Declarations No competing interests reported. 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(b) Integrated biological network derived from DEGs after long‑term TBOEP exposure, highlighting the tight coupling between developmental and reproductive adverse effects. (c) Endocrine‑centred sub‑network extracted from the same DEG set, underscoring strong links to female reproductive processes and ontogeny. Red nodes denote up‑regulated genes, blue nodes down‑regulated genes. Yellow rectangles mark associated cellular‑process terms; purple rectangles indicate phenotype annotations. Solid blue edges represent gene–gene associations; solid grey edges connect genes to phenotypes, and dashed grey edges connect genes to cellular processes. (d) Proposed adverse‑outcome pathway (AOP) describing the sequence of key events triggered by chronic TBOEP exposure.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7224759/v1/039679140a4ac9e9b45930f5.png"},{"id":89802701,"identity":"25c77533-e662-4f15-a4ed-0f78f4efd8cd","added_by":"auto","created_at":"2025-08-25 08:33:19","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":284824,"visible":true,"origin":"","legend":"\u003cp\u003eBiological‑network and AOP overview of chronic PFECHS toxicity in Daphnia magna.\u003c/p\u003e\n\u003cp\u003e(a) Protein–protein interaction graph of all differentially expressed genes (DEGs); each edge connects the protein products of two DEGs. (b) Integrated biological network derived from DEGs after long‑term PFECHS exposure, showing the close inter‑relationship between developmental and reproductive adverse effects. (c) Endocrine‑focused sub‑network extracted from the same DEG set, emphasizing strong links to female reproductive processes and ontogeny. Red nodes indicate up‑regulated genes; blue nodes indicate down‑regulated genes. Yellow rectangles denote associated cellular‑process terms, and purple rectangles denote phenotype annotations. Solid blue lines represent gene–gene associations; solid grey lines link genes to phenotypes, while dashed grey lines link genes to cellular processes. (d) Proposed adverse‑outcome pathway (AOP) illustrating the sequence of key events triggered by chronic PFECHS exposure.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7224759/v1/96a7b2a592fdd4ae2673da77.png"},{"id":92813514,"identity":"69c37451-61bd-4cb2-a851-4fb0d083d062","added_by":"auto","created_at":"2025-10-05 17:46:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1406099,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7224759/v1/0fe4338b-2590-40af-9c6a-f36ec4574271.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Endocrine Disruption in Freshwater Cladocerans: Transcriptomic-Network Perspectives on TBOEP and PFECHS Impacts in Daphnia magna","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEndocrine‑disrupting chemicals (EDCs) are exogenous substances that alter hormone synthesis, metabolism, transport, or receptor signaling, thereby impairing growth, development, and reproduction in exposed organisms (Diamanti‑Kandarakis 2009). Notably, freshwater ecosystems receive a continuous influx of industrial effluent, agricultural runoff, and municipal wastewater, exposing aquatic species to complex EDC mixtures (Schwarzenbach 2010; Li 2020). Although early research focused on vertebrates, classic field observations, such as tributyltin‑induced imposex in marine gastropods, have demonstrated that invertebrate taxa are equally vulnerable and that endocrine disruption can drive population‑level changes (Gibbs and Bryan \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1986\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cem\u003eDaphnia magna (D.magna)\u003c/em\u003e is a widely used sentinel for detecting endocrine disruption. The lifecycle of D. magna is exquisitely hormone‑dependent, with juvenile hormones regulating the transition from clonal to sexual reproduction, while ecdysteroids control molting and somatic growth. Consequently, shifts in sex ratio, fecundity, or molting frequency provide sensitive read‑outs of endocrine perturbation (Olmstead and LeBlanc \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; De Fraine 2019). Owing to its well‑characterized life history, short generation time, and extensive genomic resources, D. magna is routinely used to screen chemicals that target invertebrate hormonal pathways.\u003c/p\u003e\u003cp\u003eAmong the many contaminants detected in surface waters, two compounds warrant scrutiny: tris(2‑butoxyethyl) phosphate (TBOEP), a high‑production‑volume organophosphate flame retardant that is now ubiquitously identified at microgram‑per‑liter levels (Ballesteros‑G\u0026oacute;mez 2014). Chronic exposure of D. magna to environmentally relevant TBOEP concentrations (\u0026asymp;\u0026thinsp;10 \u0026micro;g L⁻\u0026sup1;) dysregulates transcripts in juvenile‑hormone and ecdysteroid pathways, lowers molting frequency, and retards growth without causing acute lethality (Giraudo 2017). Studies in zebrafish have revealed altered hypothalamic\u0026ndash;pituitary\u0026ndash;gonadal gene expression, elevated male estradiol levels, and reduced fecundity, underscoring the cross‑phylum endocrine activity of TBOEP (Wang 2019).\u003c/p\u003e\u003cp\u003ePerfluoroethylcyclohexane sulfonate (PFECHS), used in aviation hydraulic fluids, also persists in remote waters at nanogram‑per‑liter concentrations (Gomis 2018). A 12‑day exposure of D. magna to sub‑milligram levels markedly suppressed vitellogenin mRNA and protein while up‑regulating cuticle‑synthesis genes, indicating sub‑lethal endocrine interference without immediate effects on survival or reproduction (Houde 2018).\u003c/p\u003e\u003cp\u003eAdverse outcome pathway (AOP) frameworks provide a structured means to link a molecularinitiating event through successive key events to apical outcomes that are ecologically relevant and regulatoryready (Ankley 2010; Yang SW 2017). Integrating highcontent transcriptomics with AOP thinking allows early mechanistic signals\u0026mdash;such as Wnt/βcatenin perturbation (Nusse \u0026amp; Clevers \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u0026mdash;to be traced to reproductive endpoints in cladocerans.\u003c/p\u003e\u003cp\u003eThe pervasive occurrence of TBOEP and the extreme persistence of PFECHS suggest that D. magna populations experience chronic, low‑level exposure capable of disrupting endocrine homeostasis and, by extension, freshwater ecosystem function. Even at low ambient concentrations, evidence exists of endocrine‑mediated effects at higher doses, raising concern about cumulative or mixture‑driven impacts. Since D. magna influences water‑column clarity and serves as prey for higher trophic levels, any impairment of its reproduction or development could cascade through planktonic communities. Therefore, clarifying the molecular mechanisms, effects, and consequences of TBOEP and PFECHS exposure is critical for robust ecological risk assessment and informed chemical management. The present study integrates public transcriptomic datasets, Gene Ontology enrichment, interaction network analysis, and adverse‑outcome‑pathway construction to elucidate how chronic exposure to these two EDCs reshapes endocrine‑regulated processes in D. magna.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cb\u003eTranscriptomic datasets and preprocessing\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWholeanimal microarray data for \u003cem\u003eD.magna\u003c/em\u003e chronically exposed to TBOEP or PFECHS were retrieved from the NCBI Gene Expression Omnibus (GEO). The TBOEP study corresponds to series GSE55132, profiling animals after a 21day exposure to 1 470 \u0026micro;g L⁻\u0026sup1; on the Agilent 4 \u0026times; 44 K platform (GPL16592). The PFECHS study corresponds to series GSE75607, generated under identical platform conditions following a 21day exposure to 6 mg L⁻\u0026sup1;.\u003c/p\u003e\u003cp\u003eRaw files were imported into R v4.3.1. Background correction and withinarray normalisation were performed with the limma package. Where multiple probes targeted the same transcript, signals collapsed to the median intensity. Differential expression was assessed using an empirical Bayesmoderated \u003cem\u003et\u003c/em\u003estatistic; transcripts with |log₂fold change| \u0026ge; 1.0 and a Benjamini\u0026ndash;Hochberg falsediscovery rate (FDR)\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were retained as differentially expressed genes (DEGs).\u003c/p\u003e\u003cp\u003e\u003cb\u003eFunctional enrichment analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) term enrichment was performed in clusterProfiler v4.8.1 with the \u003cem\u003eD. magna\u003c/em\u003e background (taxon 35525). GO terms (biological process, cellular component, molecular function) with FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were retained.\u003c/p\u003e\u003cp\u003e\u003cb\u003eProteininteraction networks and hubgene mining\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSignificant DEGs were queried against STRING v12.0 (confidence score\u0026thinsp;\u0026gt;\u0026thinsp;0.4; \u0026ldquo;\u003cem\u003eD. magna\u003c/em\u003e\u0026rdquo; organism filter). Resulting interaction tables were imported into Cytoscape v3.10.3. Network topologies were analysed with node degree and betweennesscentrality scores were calculated, and the top-10 ranked genes were defined as hub genes.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAdverse outcome pathway (AOP) inference\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePutative molecular key events (MKEs) were anchored to KEGG pathway ko04310 (Wnt signalling). Candidate stressor/MKE, MKE/MKE and MKE/adverseoutcome links were extracted with AOPhelpFinder v3.0 (query terms: \u0026ldquo;TBOEP\u0026rdquo; or \u0026ldquo;PFECHS\u0026rdquo; AND \u0026ldquo;\u003cem\u003eDaphnia\u003c/em\u003e OR invertebrate\u0026rdquo;). Literature cooccurrence scores\u0026thinsp;\u0026ge;\u0026thinsp;2 were accepted. Final AOP schematics were rendered in Cytoscape v3.10.3.\u003c/p\u003e"},{"header":"Results and Discussion","content":"\u003cp\u003e\u003cb\u003eTBOEP Toxicity and Transcriptomic Insights\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTBOEP is detected in surface waters worldwide, and its chronic presence is recognised as an ecological concern (BallesterosG\u0026oacute;mez 2014). Multigenerational 21-day assays with \u003cem\u003eDaphnia magna\u003c/em\u003e report unchanged survival and brood production but significant reductions in body length and molting frequency, accompanied by persistent transcriptional shifts in ecdysteroid and juvenile hormone pathways that control growth and reproduction (Giraudo 2017). Complementary vertebrate data strengthen the endocrinedisruption signal: adult zebrafish maintained for 21-days at 5\u0026ndash;500 \u0026micro;g L⁻\u0026sup1; produce fewer eggs, their progeny hatch and survive less often, and histology shows arrested oocyte maturation and delayed spermiation, coincident with elevated 17βestradiol, altered testosterone and broad disruption of hypothalamic\u0026ndash;pituitary\u0026ndash;gonadal transcripts (Wang et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Embryos exposed to 2\u0026ndash;200 \u0026micro;g L⁻\u0026sup1; develop oedema and skeletal deformities, while hormonesynthesis genes are suppressed and receptor genes induced across thyroid, gonadal axes\u0026mdash;confirming endocrine dysregulation during development (Han 2014). Beyond endocrine effects, oxidativestress responses have also been recorded: in \u003cem\u003eD. magna\u003c/em\u003e, catalase activity drops in the F₁ generation after 28-days at 20 \u0026micro;g L⁻\u0026sup1;, glutathione Stransferase and heatshockprotein transcripts fall at low doses, and ABCtransporter genes rise only at milligramperlitre levels (Giraudo 2017).\u003c/p\u003e\u003cp\u003eAdditional mechanistic insight is provided by analysis of the public microarray dataset GSE55132, which profiles wholebody RNA from \u003cem\u003eD. magna\u003c/em\u003e exposed to 1 470 mg L⁻\u0026sup1; TBOEP for 21-days. DEGs were extracted, followed by geneontology enrichment, interactionnetwork synthesis and formulation of a putative adverseoutcome pathway. The resulting GO terms, DEGcentred protein network and AOP framework together outline how chronic TBOEP exposure perturbs metabolic processes, membrane integrity and hormoneregulated development, thereby linking transcriptomic disturbances to the observed impairments in growth and reproduction.\u003c/p\u003e\u003cp\u003e\u003cb\u003eGO Enrichment in TBOEP Exposure\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe top 10 activated and suppressed biological processes (BPs), cellular components (CCs), and molecular functions (MFs) were discovered, with falsediscovery rate (FDR)\u0026thinsp;\u0026lt;\u0026thinsp;0.05, respectively. The top 10 activated and six suppressed BPs were observed, with the ontology \u003cem\u003ecellular process\u003c/em\u003e occurring in both lists. Activated BPs were predominantly associated with metabolicprocessrelated GO terms, whereas in the suppressed BPs \u003cem\u003epositive regulation of transport\u003c/em\u003e was identified. In many animals there is an association between metabolism and reproduction. In \u003cem\u003eC. elegans\u003c/em\u003e, lipid metabolism is regulated by signals from the reproductive system (Hansen 2013). Additionally, in humans, successful reproduction is associated with regulated energy metabolism (Seli 2014). Therefore, it can be inferred indirectly that abnormalities in metabolism due to chronic exposure to TBOEP affect the reproductive capacity of \u003cem\u003eDaphnia magna\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eAmong 10 activated and five suppressed statistically significant CCs, ontologies including \u003cem\u003ecellular anatomical entity\u003c/em\u003e, \u003cem\u003ecytoplasm\u003c/em\u003e, \u003cem\u003eintercellular anatomical structure\u003c/em\u003e, and \u003cem\u003eintracellular organelle\u003c/em\u003e were concurrently identified. In the activated CCs, GO terms related to anatomical entities and membranes were observed (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Similarly, in the suppressed CCs, identified ontologies were related to anatomical entities and membranes. Both activated and suppressed CCs indicate abnormalities within cell components and cell membranes. Considering that damaged cells are replaced by new cells through apoptosis, chronic exposure to TBOEP can affect the developmental stages of \u003cem\u003eD. magna\u003c/em\u003e offspring.\u003c/p\u003e\u003cp\u003eStatistically significant MFs were identified, with five activated and one suppressed. The activated MFs primarily include catalyticactivity and bindingrelated ontologies, while the suppressed MF is associated with binding. From the perspective of TBOEP as an endocrine disruptor, ontologies related to binding can be interpreted as the process of reproductive hormones binding to receptors, and ontologies related to catalytic activity can be seen as the breakdown process of reproductive hormones (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn brief, activated biological processes are primarily related to metabolism, whereas suppressed processes involve transport regulation. Chronic TBOEP exposure may disrupt metabolism, affecting reproductive capacity. Additionally, abnormalities in cellular components and membranes were noted, potentially impacting \u003cem\u003eD. magna\u003c/em\u003e offspring development. Molecular functions mainly involve catalytic activity and binding, suggesting effects on reproductivehormone interactions and breakdown.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTop 10 Gene Ontology terms for up‑regulated DEGs and the top 10 GO terms for down‑regulated DEGs in \u003cem\u003eD. magna\u003c/em\u003e subjected to chronic TBOEP exposure.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGO term category\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eActivated GO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eSuppressed GO\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGO term\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFDR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGO term\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFDR\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e\u003cp\u003eBiological process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCellular process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.00018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBiological regulation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.10E-03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMetabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.00051\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCellular process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.10E-03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOrganic substance metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.00068\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRegulation of cellular process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.13E-02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimary metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRegulation of biological process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0174\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProtein metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePositive regulation of transport\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0335\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOrganonitrogen compound metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePositive regulation of biological process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0483\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMacromolecule metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNitrogen compound metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0017\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProtein localization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0043\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCellular localization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0099\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e\u003cp\u003eCellular component\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCellular anatomical entity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.8E-13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCellular anatomical entity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.44E-08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIntracellular anatomical structure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.16E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCytoplasm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.16E-06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCytoplasm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.62 E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIntracellular anatomical structure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.29E-05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEndomembrane system\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIntracellular organelle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0056\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMembrane-bounded organelle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMembrane\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0072\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIntracellular membrane-bounded organelle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIntracellular organelle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0018\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProtein-containing complex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0053\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDendritic shaft\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0091\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCytoplasmic vesicle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0096\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eMolecular function\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCatalytic activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.40E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBinding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.00033\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProtein binding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.70E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCatalytic activity, acting on a protein\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.00E-02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHydrolase activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBinding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.032\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEndocrinerelated Gene Ontology categories for upregulated and downregulated DEGs in \u003cem\u003eD. magna\u003c/em\u003e following chronic exposure to TBOEP.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNetwork type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGO term category\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGO term\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFDR\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eMain network\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eBiological process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOrganic substance biosynthetic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.56E-02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOrganic substance transport\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.21E-02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAnatomical structure development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.63E-02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMuscle structure development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.39E-02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCollagen trimer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.83E-02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eTBOEP Functional network evidence\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo gain insights into the key DEGs of TBOEP in \u003cem\u003eD.magna\u003c/em\u003e, protein\u0026ndash;protein interactions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) were illustrated from STRING‑DB. These interactions clarify how numerous DEGs inter‑connect at the molecular level. The proteins encoded by DEGs, regardless of their expression patterns, were jointly subjected to GO analysis, which highlighted terms linked to the synthesis and transport of organic substances, developmental processes and collagen trimers (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Within an endocrine context, Organic substance biosynthetic process maps to hormone synthesis, whereas Organic substance transport aligns with hormone trafficking. Two further GO biological‑process (BP) terms related to development were also enriched.\u003c/p\u003e\u003cp\u003eFor a comprehensive view of TBOEP toxicity, we built a biological network (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB) that integrates protein\u0026ndash;protein, protein\u0026ndash;cell‑process and protein\u0026ndash;orthologous‑phenotype relationships. Five statistically significant (FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05) GO terms associated with endocrine disruption were recovered among biological processes; none were significant for cellular components (CCs) or molecular functions (MFs). Organic substance biosynthetic process and organic substance transport relate to reproductive‑hormone metabolism because steroid hormones such as oestrogen and progesterone are organic molecules. Ontologies describing anatomical and muscle‑structure development imply that chronic TBOEP exposure during early life stages disrupts organogenesis\u0026mdash;especially of muscle. When D. magna muscles malfunction, animals experience restricted swimming, cardiac‑rhythm abnormalities and impaired movement of the head, eyes and other appendages (Hoffschr\u0026ouml;er 2024; Watanabe 2024; Chea 2017).\u003c/p\u003e\u003cp\u003eTo predict phenotypes, DEGs were first matched to Drosophila melanogaster orthologues with BLASTp because phenotype\u0026ndash;protein links are sparse for D. magna. The well‑annotated fruit‑fly data set enabled inference of size‑ and reproduction‑related phenotypes via FlyBase.\u003c/p\u003e\u003cp\u003eCentral genes were mined from the STRING network (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) using edge degree and betweenness‑centrality scores. Six hubs emerged: LOC116918246 (serine/threonine‑protein kinase VRK1), LOC116935564 (E3 ubiquitin\u0026ndash;protein ligase MIB2), LOC116924990 (adenylosuccinate synthetase), LOC116918466 (28S ribosomal protein S2, mitochondrial), LOC116921285 (tyrosine‑tRNA ligase, cytoplasmic) and LOC116917541 (glutamine synthetase). VRK1 is broadly expressed across zebrafish tissues (Xu 2023) and is essential for early embryogenesis in Drosophila (Gonz\u0026aacute;lez‑Mart\u0026iacute;nez 2024). MIB2 participates in post‑translational regulation in all major eukaryotic lineages (Mukherjee \u0026amp; Rotin \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and mediates ubiquitination to activate Notch signalling in zebrafish (Itoh 2006). Adenylosuccinate synthetase fuels ATP synthesis under stress in D. magna (Becker 2019) and influences vertebrate eye development.\u003c/p\u003e\u003cp\u003eA condensed network (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC) that links these hubs to cell‑process and orthologous‑phenotype nodes highlights associations with anatomical and muscle‑structure development, reproduction and infertility.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTBOEP Putative AOP analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA putative adverseoutcome pathway (AOP) for TBOEP exposure in \u003cem\u003eD. magna\u003c/em\u003e was derived from the KEGG Wntsignalling pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Given that genetic based analysis, it is difficult to find molecular initiating event (MIE) about reproductive and developmental toxicity of TBOEP. We constructed a putative AOP if PS-1 changed after the pMIE following chronic exposure to TBOEP. The expression change of PS-1 alters the expression level of β-catenin, thereby impacting TCF/LEF family. These three biological events are regarded as key events (KEs) and adverse outcomes (AO) can be described as abnormal transcription of target genes such as oocyte maturation early development. Through the putative AOP, we present that TBOEP exposure occurs abnormal transcriptions involved in female reproduction and development in \u003cem\u003eD.magna.\u003c/em\u003e In summary, we identified DEGs derived from the transcriptome of whole \u003cem\u003eD. magna\u003c/em\u003e which had been exposed to TBOEP during 21-days. We suggest that the meaning of DEGs using gene ontology, protein-protein network, orthological phenotype, and putative AOP. At the cellular level, the chronic exposure of TBOEP makes unusual metabolism, abnormal cell anatomical structure, decreasing offspring development, and binding. This suggests that chronic exposure of TBOEP effects reproduction and reproductive hormone metabolism. Through biological network and orthological phenotypes, we achieved a comprehensive understanding of the chronic toxicity of TBOEP through network construction (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Through TBOEP chronic toxicity network, it was possible to identify phenotypes associated with size and reproduction related adverse effects. In the condensed network (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD), adverse effects on reproduction related phenotypes and muscle development could be observed. Additionally, it was evident that genes LOC116918246, LOC116935564, and LOC116924990 may play a crucial role in the chronic toxicity mechanism of TBOEP. For intuitive insights of chronic toxic mechanisms, we suggest putative AOP based on KEGG pathway. The putative AOP showed that TBOEP induces changes in the expression of PS-1 potentially leading to the occurrence of abnormal transcription of target genes such as oocyte maturation and early development.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePFECHS Toxicity and Transcriptomic Insights\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePFECHS is a cyclic PFAS used in aviation hydraulic fluids and has been measured in river water at low nanogram‑per‑litre concentrations, (Mu\u0026ntilde;oz 2017) its toxicology is only recently described (Gomis 2018). When D. magna were exposed for 12-days to 0.06\u0026ndash;six mg L⁻\u0026sup1;, vitellogenin transcripts and protein content fell sharply while survival, molting, and brood size remained unchanged, signalling an anti‑estrogenic endocrine‑disrupting action likely to impair oocyte provisioning if exposure persists (Houde 2018). Vertebrate evidence is consistent: zebrafish embryos and larvae raised in 500 ng L⁻\u0026sup1; to two mg L⁻\u0026sup1; PFECHS developed edema and skeletal malformations at frequencies comparable to those caused by legacy PFOS, although mortality was lower; transcriptomic analysis showed induction of lipid‑metabolism and detoxification genes including pparα and cyp1a1 at concentrations near environmental relevance, indicating metabolic imbalance and activation of chemical‑stress defences (Gomis 2018). These invertebrate and vertebrate data together reveal that PFECHS, much like the compounds it was meant to replace, perturbs endocrine function, development, and energy metabolism even at sub‑lethal doses, underscoring the need for extended and multigenerational studies to gauge its population‑level impact.\u003c/p\u003e\u003cp\u003eThe GSE75607 dataset shared in the public database consists of gene expression data evaluating reproductive performance in D. magna following chronic exposure to PFECHS. The gene expression data conducted by Houde M et al., following OECD guidelines (OECD \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Houde 2018), encompass the adverse effects of chronic exposure to 6 mg L⁻\u0026sup1; of PFECHS for 21-days. From the dataset, we extracted DEGs and interpreted the chronic toxicity effects of PFECHS through gene ontology (GO) enrichment, constructing network, and the presenting putative AOP based on the DEGs.\u003c/p\u003e\u003cp\u003e\u003cb\u003eGO Enrichment in PFECHS Exposure\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo elucidate the cellular significance of DEGs elicited by chronic PFECHS exposure, the gene‑ontology profiles of activated and suppressed transcripts were examined. Activated or suppressed DEGs were assigned to biological processes (BPs), cellular components (CCs) and molecular functions (MFs); ontologies with a false‑discovery rate\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were retained, and the ten most significant terms per category were collated (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAmong the ten activated and suppressed BPs, metabolic-process terms were dominant in both lists. \u0026lsquo;Cellular process\u0026rsquo;, \u0026lsquo;metabolic process\u0026rsquo;, \u0026lsquo;organic-substance metabolic process\u0026rsquo;, \u0026lsquo;nitrogen-compound metabolic process\u0026rsquo;, and \u0026lsquo;primary metabolic process\u0026rsquo; appeared in common. Excluding metabolic terms, activated BPs included \u0026lsquo;response to stimulus\u0026rsquo;, \u0026lsquo;regulation of biological quality\u0026rsquo;, \u0026lsquo;glutathione metabolic process\u0026rsquo;, and \u0026lsquo;response to ethanol\u0026rsquo;, whereas suppressed BPs uniquely contained \u0026lsquo;biological regulation\u0026rsquo;, \u0026lsquo;cellular-component organization or biogenesis\u0026rsquo;, and \u0026lsquo;regulation of biological process\u0026rsquo;. Notably, the activation of \u0026lsquo;glutathione metabolic process\u0026rsquo; indicates a response to oxidative stress, as glutathione-dependent antioxidants such as GPX4 protect gametes and pre-implantation embryos from reactive oxygen species; GPX4 disruption leads to infertility and early embryonic lethality, potentially affecting reproductive functions and early development. Such activation can reduce cell-division fidelity and implantation rates at the earliest embryonic stages. Suppression of \u0026lsquo;organonitrogen compound metabolic process\u0026rsquo; may be linked to gametogenesis, because de-novo amino-acid synthesis and nitrogen recycling fuel chromatin remodeling and ATP-intensive meiotic stages.\u003c/p\u003e\u003cp\u003eStatistically significant activated or suppressed CCs were identified based on the top 10 ontologies with the lowest FDR (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Among these, \u0026lsquo;cellular anatomical entity\u0026rsquo;, \u0026lsquo;cytoplasm\u0026rsquo;, \u0026lsquo;intracellular anatomical structure\u0026rsquo;, \u0026lsquo;organelle\u0026rsquo;, and \u0026lsquo;intracellular organelle\u0026rsquo; were common. Activated CCs were enriched for fiber, organelle, and extracellular-structure terms; suppressed CCs highlighted protein complexes, organelles, and the extracellular structure. Within activated CCs, fiber-related terms such as \u0026lsquo;sarcomere\u0026rsquo;, \u0026lsquo;supramolecular fiber\u0026rsquo;, and \u0026lsquo;Z disc\u0026rsquo; suggest adverse effects of PFECHS on myofilament. In suppressed CCs, terms such as \u0026lsquo;protein-containing complex\u0026rsquo; and \u0026lsquo;ribonucleoprotein complex\u0026rsquo; predominated. The suppression of cell-structure-associated ontologies such as \u0026lsquo;membrane-bounded organelle\u0026rsquo; implies impaired redistribution of the endoplasmic reticulum and mitochondria, which coordinate Ca\u0026sup2;⁺ signaling and maternal mRNA storage\u0026mdash;processes essential for oocyte maturation and embryonic developmental competence.\u003c/p\u003e\u003cp\u003eConversely, the prevalence of myofilament-related terms among suppressed CCs suggests interference with sarcomere assembly; for example, loss of the sarcomere-assembly factor Smyd1b disrupts early muscle formation and subsequently lowers developmental and hatching success.\u003c/p\u003e\u003cp\u003eIn both activated and suppressed MFs, \u0026lsquo;catalytic activity\u0026rsquo;, ion binding\u0026rsquo;, \u0026lsquo;binding\u0026rsquo;, and \u0026lsquo;protein binding\u0026rsquo; were common. Unique activated MFs were detoxification-related\u0026mdash;e.g., \u0026lsquo;oxidoreductase activity\u0026rsquo;, \u0026lsquo;glutathione transferase activity\u0026rsquo;, and other transferase activities\u0026mdash;whereas unique suppressed MFs were largely binding-related (cyclic-compound-binding and nucleic-acid-binding terms). Activated MFs related to binding non-protein substances, hormones, or other molecules critical for reproduction. Suppressed MFs showed oxidative-stress-related terms such as \u0026lsquo;Oxidoreductase activity\u0026rsquo; and \u0026lsquo;Glutathione transferase activity\u0026rsquo;, indicating altered ROS-detoxification pathways vital for reproductive health.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTop 10 Gene Ontology terms for up‑regulated DEGs and the top 10 GO terms for down‑regulated DEGs in \u003cem\u003eD. magna\u003c/em\u003e subjected to chronic PFECHS exposure.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGO term category\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eActivated GO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eSuppressed GO\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGO term\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFDR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGO term\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFDR\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e\u003cp\u003eBiological process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCellular process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.71E-17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCellular process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.98E-88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMetabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.73E-11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOrganic substance metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.95E-51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOrganic substance metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.28E-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMetabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.07E-51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOrganonitrogen compound metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.26E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePrimary metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.23E-50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eResponse to stimulus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.84E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNitrogen compound metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.18E-50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimary metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.23E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMacromolecule metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.06E-48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNitrogen compound metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.40E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCellular metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.02E-45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRegulation of biological quality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.83E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBiological regulation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.19E-43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGlutathione metabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.61E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCellular component organization or biogenesis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.24E-42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eResponse to ethanol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.10E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRegulation of biological process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.60E-38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e\u003cp\u003eCellular component\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCellular anatomical entity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.54E-23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIntracellular anatomical structure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.37E-105\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCytoplasm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.45E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCellular anatomical entity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.45E-96\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSarcomere\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.75E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIntracellular organelle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.35E-71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIntracellular anatomical structure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.18E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOrganelle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.54E-71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExtracellular region\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.61E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIntracellular membrane-bounded organelle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.83E-59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSupramolecular fiber\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.10E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eProtein-containing complex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.80E-57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMembrane\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.10E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMembrane-bounded organelle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.80E-57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eZ disc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.30E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNucleus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.64E-52\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOrganelle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.90E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCytoplasm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.12E-50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIntracellular organelle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.60E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRibonucleoprotein complex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.14E-35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e\u003cp\u003eMolecular function\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCatalytic activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.48E-12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBinding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.38E-65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIon binding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.93E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOrganic cyclic compound binding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.34E-49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBinding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.32E-07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHeterocyclic compound binding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.18E-48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCation binding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.22E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNucleic acid binding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.03E-28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOxidoreductase activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.10E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRNA binding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.49E-27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGlutathione transferase activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.50E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eProtein binding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.23E-26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMetal ion binding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.00E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIon binding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.42E-22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTransferase activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.70E-04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCatalytic activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.38E-20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCatalytic activity, acting on a protein\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.50E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSmall molecule binding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.93E-20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProtein binding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.80E-03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCarbohydrate derivative binding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.75E-20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEndocrinerelated Gene Ontology categories for upregulated and downregulated DEGs in \u003cem\u003eD. magna\u003c/em\u003e following chronic exposure to PFECHS.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNetwork type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGO term category\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGO term\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFDR\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"15\" rowspan=\"16\"\u003e\u003cp\u003eMain network\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"13\" rowspan=\"14\"\u003e\u003cp\u003eBiological process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOrganic substance biosynthetic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.44E-09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDevelopmental process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.60E-04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCellular process involved in reproduction in Multicellular organism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.60E-04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAnatomical structure development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.10E-04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReproductive process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.60E-04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFemale gamete generation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.50E-03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOrganic substance transport\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.50E-03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDevelopmental process involved in reproduction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.40E-03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMulticellular organism development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.63E-02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMeiotic cell cycle process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.79E-02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGerm cell development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.46E-02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMeiotic nuclear division\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.88E-02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOogenesis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.01E-02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFemale meiotic nuclear division\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.15E-02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCellular component\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMeiotic spindle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.05E-02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMolecular function\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOrganic cyclic compound binding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.41E-43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003ePFECHS Functional network evidence\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFor comprehensive understanding of the toxic mechanisms of PFECHS in D. magna, biological network was constructed using protein‑protein interactions, cell processes, orthological diseases. Protein‑protein interactions were collected from STRING‑DB within D. magna. A network based on the protein‑protein interaction was constructed for comprehensive understanding reproductive toxicity of PFECHS (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003eThe biological network consists of protein‑protein interactions, protein‑cell process relationships and protein‑orthological phenotype relationships (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). The proteins constituting the biological network are encoded by DEGs, with their expression changes mirroring those of DEGs. To elucidate the biological functions of this network at cellular level, gene ontologies were identified among DEGs encoding proteins, regardless of its expression pattern. After confirming statistically significant (FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05) gene ontologies associated with reproduction, a total of 14 ontologies were identified in biological processes (BPs), while one each was found in cellular component (CC) and molecular function (MF). Among the BPs, development, reproduction, and organic substances metabolism related ontologies were identified, whereas ontologies associated with cell division were identified in CC and organic compound binding in MF.\u003c/p\u003e\u003cp\u003eTo find putative phenotypes based DEGs in D. magna, transcribed proteins of DEGs were converted to proteins of Drosophila melanogaster (D. melanogaster), one of fruit flies, using NCBI BLASTp. Because the limited information on the relationships among phenotype‑related proteins in D. magna is attributed to the lack of studies on phenotype. Conversely, for evolutionary proximate species like fruit flies, extensive research on phenotype has resulted in abundant information (Altschul 1990; Gramates 2022). We identified phenotypes associated with reproduction and development in D. melanogaster from FlyBase (proteins of DEGs). We obtained orthological phenotypes, including abnormal developmental rate, abnormal size, fertile, abnormal oxidative stress response.\u003c/p\u003e\u003cp\u003eTo identify central genes in the reproductive and developmental toxicity network of PFECHS, each gene in the protein‑protein interaction network (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA) was assessed based on two parameters: edge degree and betweenness centrality. LOC116919267 (SUMO‑conjugating enzyme UBC9), LOC116919853 (eukaryotic initiation factor 4A‑III), LOC116919548 (transformer‑2 protein homolog α), and LOC116923253 (histone deacetylase 1) displayed high significance in the network. Based on these central proteins, condensed network (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC) was constructed using interactions between central proteins and interactions of central protein‑cellular process and central protein‑orthologous phenotype. These genes are in critical reproductive and developmental functions, from specific cellular processes in multicellular organisms to the development of anatomical structures (Li 2012; Palacios 2004; Amrein 1994; Ma \u0026amp; Schultz \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). They are particularly significant in the generation and development of gametes, such as in oogenesis and the meiotic cycle. Furthermore, the meiotic spindle in chromosome separation and the binding of DEGs to organic cyclic compounds, which may influence hormone function, the altered regulation of reproduction‑related VTG1 and YLK suggest that the interaction with the signaling hormones could alter reproduction in D. magna as these proteins are essential to the feeding reserve of developing embryos (Tufail \u0026amp; Takeda \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). This suggests a network of genes that are crucial for regulating reproductive health and development, providing insights into the genetic interactions that support these biological functions.\u003c/p\u003e\u003cp\u003eIn the condensed network, reproductive‑related phenotypes such as fertility and reproductive‑related cellular processes, particularly 'female gamete generation' and 'female meiotic nuclear division,' were observed (Schwenk et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). This suggests that the four central genes could be involved in the reproductive toxicity mechanism of PFECHS in D. magna, which reproduces parthenogenesis.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePFECHS Putative AOP analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe putative AOP of PFECHS exposure to D. magna (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD) was outlined from the KEGG Wnt‑signalling pathway. Because a definitive molecular‑initiating event (MIE) could not be resolved from the available transcriptomic evidence, the model postulates an initial perturbation of CK1ε and CK2 expression (pMIE). Altered CK1ε/CK2 levels are predicted to remodel the Dishevelled (DVL) scaffold and, in turn, attenuate TCF/LEF transcriptional activity. These sequential changes constitute three key events (KEs), after which transcription of targets governing oocyte maturation and early development is impaired. Downstream DEGs include vtg1, yolkless and multiple cyclins, indicating disrupted yolk‑protein uptake, nutrient provision and cell‑cycle progression in developing oocytes. At the organismal level, such molecular defects are consistent with the observed suppression of vitellogenin protein and the lack of overt lethality despite impaired reproductive output. Integrating these findings with oxidative‑stress signatures\u0026mdash;e.g. up‑regulation of glutathione‑metabolism genes\u0026mdash;suggests that PFECHS imposes combined endocrine and redox pressure, which may compound over successive generations. The pathway therefore links CK1ε/CK2‑mediated Wnt disruption to transcriptional dysregulation of female reproductive processes and provides a mechanistic framework for evaluating sub‑lethal PFAS impacts in freshwater cladocerans.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eEDCs threaten aquatic ecosystems by disturbing hormone-controlled growth and reproduction. Among them, the flame retardant TBOEP and PFECHS now occur from surface waters and persist in wastewater discharge.\u003c/p\u003e\u003cp\u003eChronic exposure of \u003cem\u003eD. magna\u003c/em\u003e to environmentally TBOEP levels reduced body length and molting while shifting juvenile-hormone and ecdysteroid transcripts. PFECHS exposure suppressed vitellogenin, altered cuticle-synthesis genes, and activated detoxification pathways without acute lethality. Gene-expression profiling (GSE55132, GSE75607) confirmed broad changes in metabolism, cellular processes, and reproduction. Both datasets pointed to Wnt-signal interference and highlighted central hubs UBC9 (LOC116919267) and eIF4A-III (LOC116919853) that bridge oxidative stress and meiotic control.\u003c/p\u003e\u003cp\u003eFunctional-enrichment and network analyses allowed construction of putative adverse-outcome pathways (AOPs) linking CK1ε/CK2-mediated Wnt disruption to impaired oogenesis and embryonic development. These molecular events explain how low-level, long-term exposure can erode D. magna fitness and, by extension, alter plankton dynamics essential for water-column clarity and food-web stability.\u003c/p\u003e\u003cp\u003eUnderstanding such mechanisms is critical for ecological risk assessment and chemical management. Further studies that time-resolved transcriptomics are needed to gauge mixture effects and to refine water-quality criteria that safeguard freshwater biodiversity and human communities reliant on these ecosystems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis work was supported by the Korea Environment Industry \u0026amp; Technology Institute (KEITI) through the Core Technology Development Project for Environmental Diseases Prevention and Management Program, funded by South Korea\u0026rsquo;s Ministry of Environment (MOE) (grant number 2022003310012)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u0026nbsp;\u003c/strong\u003eThe authors have no relevant financial or non‑financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e: Young Rok Seo and Eun-Min Cho designed the research study. Hyun Woo Kim, Seok-Gyu Yun performed an overall analysis procedure and wrote the manuscript. Hyun Woo Kim wrote the manuscript with Seok-Gyu Yun. Dong Yeop Shin and Jong Hun Lee composed the figures with Hyun Woo Kim. Ju Yeon Park and Seok-Gyu Yun investigated information. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e: The authors declare no conflict of interest. The funders had no role in the design of the study, in the collection, analyses, or interpretation of data.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval:\u0026nbsp;\u003c/strong\u003eThis article does not contain any studies of human participants or animals performed by any of the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Materials:\u003c/strong\u003e There is no supplementary data in this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u003c/strong\u003e No new data were created or analyzed in this study. 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The organophosphate flame‑retardant tris(2‑butoxyethyl) phosphate (TBOEP) and perfluoroethylcyclohexane sulfonate (PFECHS) now co‑occur at ng L⁻\u0026sup1;\u0026ndash;\u0026micro;g L⁻\u0026sup1; in surface waters, yet their chronic sub‑lethal impacts on invertebrate endocrine networks remain unclear.\u003c/p\u003e\u003cp\u003eWe analysed two publicly available 21‑day microarray datasets (TBOEP: GSE55132; PFECHS: GSE75607) using Gene Ontology enrichment, STRING protein‑interaction networks, \u003cem\u003eDrosophila\u003c/em\u003e phenotype mapping and KEGG(Kyoto Encyclopedia of Genes and Genomes) ‑anchored frameworks to build putative adverse outcome pathways (AOPs) for D. magna. Differentially expressed genes were clustered into functional modules and hub nodes ranked by degree and betweenness.\u003c/p\u003e\u003cp\u003eTBOEP suppressed molting and growth, altering 1 157 genes enriched for metabolism and membrane processes; hubs VRK1, MIB2 and adenylosuccinate synthetase formed a muscle anatomical development sub‑network. PFECHS down‑regulated vitellogenin and shifted 879 genes dominated by oxidative‑stress and glutathione‑metabolism signatures; central nodes UBC9, eIF4A‑III, Tra‑2α and HDAC1 linked meiotic‑cycle, oogenesis and cyclic‑compound binding. Despite chemical dissimilarity, both compounds converged on Wnt‑signalling nodes\u0026mdash;TBOEP via presenilin‑1, PFECHS via CK1ε/CK2\u0026mdash;thereby reducing TCF/LEF‑dependent transcription. Predicted outcomes include impaired oocyte maturation, reduced fecundity and stunted body size, consistent with observed decreases in length and vitellogenin protein.\u003c/p\u003e\u003cp\u003eOur network analysis indicates that environmentally relevant concentrations of TBOEP and PFECHS destabilise endocrine, developmental and metabolic pathways in D. magna without overt lethality, foreshadowing population‑level repercussions for freshwater plankton dynamics. Hub genes and Wnt‑mediated key events emerge as sensitive biomarkers for monitoring mixed EDC exposure.\u003c/p\u003e","manuscriptTitle":"Endocrine Disruption in Freshwater Cladocerans: Transcriptomic-Network Perspectives on TBOEP and PFECHS Impacts in Daphnia magna","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-25 08:33:14","doi":"10.21203/rs.3.rs-7224759/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5a41482c-48c7-4e11-8116-ce128159dd6d","owner":[],"postedDate":"August 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-05T17:38:33+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-25 08:33:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7224759","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7224759","identity":"rs-7224759","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}