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    The EU needs a nutrient directive

    Sutton, M. A. et al. The European Nitrogen Assessment: Sources, Effects and Policy Perspectives (Cambridge Univ. Press, 2011).Withers, P. J. A. & Haygarth, P. M. Agriculture, phosphorus and eutrophication: A European perspective. Soil Use Manag. 23, 1–4 (2007).Article 

    Google Scholar 
    Heffer, P. Assessment of Fertilizer Use by Crop at the Global Level (IFA, 2008).Wassen, M. J., Schrader, J., van Dijk, J. & Eppinga, M. B. Phosphorus fertilization is eradicating the niche of northern Eurasia’s threatened plant species. Nat. Ecol. Evol. 5, 67–73 (2021).Article 

    Google Scholar 
    Penuelas, J., Janssens, I. A., Ciais, P., Obersteiner, M. & Sardans, J. Anthropogenic global shifts in biospheric N and P concentrations and ratios and their impacts on biodiversity, ecosystem productivity, food security, and human health. Glob. Change Biol. 26, 1962–1985 (2020).Article 

    Google Scholar 
    Stokstad, E. Nitrogen crisis threatens Dutch environment — and economy. Science 366, 1180–1181 (2019).Article 

    Google Scholar 
    Dentener, F. et al. Nitrogen and sulfur deposition on regional and global scales: A multimodel evaluation. Global Biogeochem. Cycles 20, GB4003 (2006).Article 

    Google Scholar 
    Garske, B., Stubenrauch, J. & Ekardt, F. Sustainable phosphorus management in European agricultural and environmental law. RECIEL 29, 107–117 (2020).Article 

    Google Scholar 
    A Farm to Fork Strategy for a Fair, Healthy and Environmentally-friendly Food System (COM(2020) 381 final: European Commission, 2020); https://knowledge4policy.ec.europa.eu/publication/communication-com2020381-farm-fork-strategy-fair-healthy-environmentally-friendly-food_en More

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    Wastewater effluent affects behaviour and metabolomic endpoints in damselfly larvae

    Ternes, T. A. Occurrence of drugs in German sewage treatment plants and rivers. Water Res. 32, 3245–3260 (1998).CAS 
    Article 

    Google Scholar 
    Heberer, T. Occurrence, fate, and removal of pharmaceutical residues in the aquatic environment: A review of recent research data. Toxicol. Lett. 131, 5–17 (2002).CAS 
    PubMed 
    Article 

    Google Scholar 
    Luo, Y. et al. A review on the occurrence of micropollutants in the aquatic environment and their fate and removal during wastewater treatment. Sci. Total Environ. 473–474, 619–641 (2014).ADS 
    PubMed 
    Article 
    CAS 

    Google Scholar 
    Ternes, T., Joss, A. & Oehlmann, J. Occurrence, fate, removal and assessment of emerging contaminants in water in the water cycle (from wastewater to drinking water). Water Res. 72, 1–2 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Zorita, S., Mårtensson, L. & Mathiasson, L. Occurrence and removal of pharmaceuticals in a municipal sewage treatment system in the south of Sweden. Sci. Total Environ. 407, 2760–2770 (2009).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Yang, Y., Ok, Y. S., Kim, K.-H., Kwon, E. E. & Tsang, Y. F. Occurrences and removal of pharmaceuticals and personal care products (PPCPs) in drinking water and water/sewage treatment plants: A review. Sci. Total Environ. 596–597, 303–320 (2017).ADS 
    PubMed 
    Article 
    CAS 

    Google Scholar 
    Eggen, R. I. L., Hollender, J., Joss, A., Schärer, M. & Stamm, C. Reducing the discharge of micropollutants in the aquatic environment: The benefits of upgrading wastewater treatment plants. Environ. Sci. Technol. 48, 7683–7689 (2014).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Kümmerer, K., Dionysiou, D. D., Olsson, O. & Fatta-Kassinos, D. Reducing aquatic micropollutants: Increasing the focus on input prevention and integrated emission management. Sci. Total Environ. 652, 836–850 (2019).ADS 
    PubMed 
    Article 
    CAS 

    Google Scholar 
    Love, A. C., Crooks, N. & Ford, A. T. The effects of wastewater effluent on multiple behaviours in the amphipod. Gammarus pulex. Environ. Pollut. 267, 115386 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Rodrigues, C., Guimarães, L. & Vieira, N. Combining biomarker and community approaches using benthic macroinvertebrates can improve the assessment of the ecological status of rivers. Hydrobiolgia 839, 1–24 (2019).CAS 
    Article 

    Google Scholar 
    Previšić, A. et al. Aquatic macroinvertebrates under stress: Bioaccumulation of emerging contaminants and metabolomics implications. Sci. Total Environ. 704, 135333 (2020).ADS 
    PubMed 
    Article 
    CAS 

    Google Scholar 
    De Castro-Català, N., Muñoz, I., Riera, J. L. & Ford, A. T. Evidence of low dose effects of the antidepressant fluoxetine and the fungicide prochloraz on the behavior of the keystone freshwater invertebrate Gammarus pulex. Environ. Pollut. 231, 406–414 (2017).PubMed 
    Article 
    CAS 

    Google Scholar 
    Pisa, L. W. et al. Effects of neonicotinoids and fipronil on non-target invertebrates. Environ. Sci. Pollut. Res. 22, 68–102 (2015).CAS 
    Article 

    Google Scholar 
    Jonsson, M., Fick, J., Klaminder, J. & Brodin, T. Antihistamines and aquatic insects: Bioconcentration and impacts on behavior in damselfly larvae (Zygoptera). Sci. Total Environ. 472, 108–111 (2014).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Stoks, R. & Córdoba-Aguilar, A. Evolutionary ecology of odonata: A complex life cycle perspective. Annu. Rev. Entomol. 57, 249–265 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    Janssens, L. & Stoks, R. Stronger effects of Roundup than its active ingredient glyphosate in damselfly larvae. Aquat. Toxicol. 193, 210–216 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Brodin, T. & Johansson, F. Conflicting selection pressures on the growth/predation-risk trade-off in a damselfly. Ecology 85, 2927–2932 (2004).Article 

    Google Scholar 
    Smith, B. R. & Blumstein, D. T. Fitness consequences of personality: A meta-analysis. Behav. Ecol. 19, 448–455 (2008).Article 

    Google Scholar 
    Monserrat, J. M. et al. Pollution biomarkers in estuarine animals: Critical review and new perspectives. Comp. Biochem. Physiol. Part C 146, 221–234 (2007).
    Google Scholar 
    Ågerstrand, M. et al. Emerging investigator series: Use of behavioural endpoints in the regulation of chemicals. Environ. Sci. Process. Impacts 22, 49–65 (2020).PubMed 
    Article 

    Google Scholar 
    Sardo, A. M. & Soares, A. M. V. M. Assessment of the effects of the pesticide imidacloprid on the behaviour of the aquatic oligochaete Lumbriculus variegatus. Arch. Environ. Contam. Toxicol. 58, 648–656 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    Bossus, M. C., Guler, Y. Z., Short, S. J., Morrison, E. R. & Ford, A. T. Behavioural and transcriptional changes in the amphipod Echinogammarus marinus exposed to two antidepressants, fluoxetine and sertraline. Aquat. Toxicol. 151, 46–56 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    Rodrigues, A. C. M. et al. Behavioural responses of freshwater planarians after short-term exposure to the insecticide chlorantraniliprole. Aquat. Toxicol. 170, 371–376 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Nielsen, M. E. & Roslev, P. Behavioral responses and starvation survival of Daphnia magna exposed to fluoxetine and propranolol. Chemosphere 211, 978–985 (2018).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Al-Badran, A. A., Fujiwara, M. & Mora, M. A. Effects of insecticides, fipronil and imidacloprid, on the growth, survival, and behavior of brown shrimp Farfantepenaeus aztecus. PLoS ONE 14, e0223641 (2019).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Leonard, J. A., Cope, W. G., Barnhart, M. C. & Bringolf, R. B. Metabolomic, behavioral, and reproductive effects of the synthetic estrogen 17 α-ethinylestradiol on the unionid mussel Lampsilis fasciola. Aquat. Toxicol. 150, 103–116 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    Robert Michaud, M. et al. Metabolomics reveals unique and shared metabolic changes in response to heat shock, freezing and desiccation in the Antarctic midge, Belgica antarctica. J. Insect Physiol. 54, 645–655 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    Chou, H., Pathmasiri, W., Deese-Spruill, J., Sumner, S. & Buchwalter, D. B. Metabolomics reveal physiological changes in mayfly larvae (Neocloeon triangulifer) at ecological upper thermal limits. J. Insect Physiol. 101, 107–112 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hidalgo, K., Beaugeard, E., Renault, D., Dedeine, F. & Lécureuil, C. Physiological and biochemical responses to thermal stress vary among genotypes in the parasitic wasp Nasonia vitripennis. J. Insect Physiol. 117, 103909 (2019).PubMed 
    Article 
    CAS 

    Google Scholar 
    Hines, A., Oladiran, G. S., Bignell, J. P., Stentiford, G. D. & Viant, M. R. Direct sampling of organisms from the field and knowledge of their phenotype: Key recommendations for environmental metabolomics. Environ. Sci. Technol. 41, 3375–3381 (2007).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Agbo, S. O. et al. Changes in Lumbriculus variegatus metabolites under hypoxic exposure to benzo(a)pyrene, chlorpyrifos and pentachlorophenol: Consequences on biotransformation. Chemosphere 93, 302–310 (2013).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Venter, L. et al. Uncovering the metabolic response of abalone (Haliotis midae) to environmental hypoxia through metabolomics. Metabolomics 14, 49 (2018).PubMed 
    Article 
    CAS 

    Google Scholar 
    Melvin, S. D. Short-term exposure to municipal wastewater influences energy, growth, and swimming performance in juvenile Empire Gudgeons (Hypseleotris compressa). Aquat. Toxicol. Amst. Neth. 170, 271–278 (2016).CAS 
    Article 

    Google Scholar 
    Du, S. N. N. et al. Metabolic costs of exposure to wastewater effluent lead to compensatory adjustments in respiratory physiology in bluegill sunfish. Environ. Sci. Technol. 52, 801–811 (2018).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Mehdi, H., Dickson, F. H., Bragg, L. M., Servos, M. R. & Craig, P. M. Impacts of wastewater treatment plant effluent on energetics and stress response of rainbow darter (Etheostoma caeruleum) in the Grand River watershed. Comp. Biochem. Physiol. B 224, 270–279 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Simmons, D. B. D. et al. Altered expression of metabolites and proteins in wild and caged fish exposed to wastewater effluents in situ. Sci. Rep. 7, 17000 (2017).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    McCallum, E. S. et al. Exposure to wastewater effluent affects fish behaviour and tissue-specific uptake of pharmaceuticals. Sci. Total Environ. 605–606, 578–588 (2017).ADS 
    PubMed 
    Article 
    CAS 

    Google Scholar 
    Simmons, D. B. D. et al. Reduced anxiety is associated with the accumulation of six serotonin reuptake inhibitors in wastewater treatment effluent exposed goldfish Carassius auratus. Sci. Rep. 7, 17001 (2017).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Gauthier, P. T. & Vijayan, M. M. Municipal wastewater effluent exposure disrupts early development, larval behavior, and stress response in zebrafish. Environ. Pollut. 259, 113757 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Finotello, S., Feckler, A., Bundschuh, M. & Johansson, F. Repeated pulse exposures to lambda-cyhalothrin affect the behavior, physiology, and survival of the damselfly larvae Ischnura graellsii (Insecta; Odonata). Ecotoxicol. Environ. Saf. 144, 107–114 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Späth, J. et al. Novel metabolomic method to assess the effect-based removal efficiency of advanced wastewater treatment techniques. Environ. Chem. https://doi.org/10.1071/EN19270 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Späth, J. et al. Oxylipins at intermediate larval stages of damselfly Coenagrion hastulatum as biochemical biomarkers for anthropogenic pollution. Environ. Sci. Pollut. Res. https://doi.org/10.1007/s11356-021-12503-x (2021).Article 

    Google Scholar 
    Späth, J. et al. Metabolomics reveals changes in metabolite profiles due to growth and metamorphosis during the on. J. Insect Physiol. 136, 104341 (2022).PubMed 
    Article 
    CAS 

    Google Scholar 
    Rodriguez, A. et al. ToxTrac: A fast and robust software for tracking organisms. Methods Ecol. Evol. 9, 460–464 (2018).Article 

    Google Scholar 
    Treit, D. & Fundytus, M. Thigmotaxis as a test for anxiolytic activity in rats. Pharmacol. Biochem. Behav. 31, 959–962 (1988).CAS 
    PubMed 
    Article 

    Google Scholar 
    Brodin, T. Behavioral syndrome over the boundaries of life—carryovers from larvae to adult damselfly. Behav. Ecol. 20, 30–37 (2009).Article 

    Google Scholar 
    Jonsson, M. et al. High-speed imaging reveals how antihistamine exposure affects escape behaviours in aquatic insect prey. Sci. Total Environ. 648, 1257–1262 (2019).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Gullberg, J., Jonsson, P., Nordström, A., Sjöström, M. & Moritz, T. Design of experiments: An efficient strategy to identify factors influencing extraction and derivatization of Arabidopsis thaliana samples in metabolomic studies with gas chromatography/mass spectrometry. Anal. Biochem. 331, 283–295 (2004).CAS 
    PubMed 
    Article 

    Google Scholar 
    Teixeira, P. F. et al. A multi-step peptidolytic cascade for amino acid recovery in chloroplasts. Nat. Chem. Biol. 13, 15–17 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Rohart, F., Gautier, B., Singh, A. & Cao, K.-A.L. mixOmics: An R package for ‘omics feature selection and multiple data integration. PLOS Comput. Biol. 13, e1005752 (2017).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Gorrochategui, E., Jaumot, J., Lacorte, S. & Tauler, R. Data analysis strategies for targeted and untargeted LC-MS metabolomic studies: Overview and workflow. TrAC Trends Anal. Chem. 82, 425–442 (2016).CAS 
    Article 

    Google Scholar 
    Chong, J., Wishart, D. S. & Xia, J. Using MetaboAnalyst 40 for comprehensive and integrative metabolomics data analysis. Curr. Protoc. Bioinform. 68, e86 (2019).Article 

    Google Scholar 
    Van Gossum, H. et al. Behaviour of damselfly larvae (Enallagma cyathigerum) (Insecta, Odonata) after long-term exposure to PFOS. Environ. Pollut. 157, 1332–1336 (2009).PubMed 
    Article 
    CAS 

    Google Scholar 
    Bownik, A., Ślaska, B., Bochra, J., Gumieniak, K. & Gałek, K. Procaine penicillin alters swimming behaviour and physiological parameters of Daphnia magna. Environ. Sci. Pollut. Res. 26, 18662–18673 (2019).CAS 
    Article 

    Google Scholar 
    Di Cicco, M. et al. Effects of diclofenac on the swimming behavior and antioxidant enzyme activities of the freshwater interstitial crustacean Bryocamptus pygmaeus (Crustacea, Harpacticoida). Sci. Total Environ. 799, 149461 (2021).ADS 
    PubMed 
    Article 
    CAS 

    Google Scholar 
    Di Nica, V., González, A. B. M., Lencioni, V. & Villa, S. Behavioural and biochemical alterations by chlorpyrifos in aquatic insects: An emerging environmental concern for pristine Alpine habitats. Environ. Sci. Pollut. Res. 27, 30918–30926 (2020).Article 
    CAS 

    Google Scholar 
    Cappello, T. et al. Sex steroids and metabolic responses in mussels Mytilus galloprovincialis exposed to drospirenone. Ecotoxicol. Environ. Saf. 143, 166–172 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Rodrigues, A. C. M. et al. Energetic costs and biochemical biomarkers associated with esfenvalerate exposure in Sericostoma vittatum. Chemosphere 189, 445–453 (2017).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Ji, C. et al. Proteomic and metabolomic analysis of earthworm Eisenia fetida exposed to different concentrations of 2,2′,4,4′-tetrabromodiphenyl ether. J. Proteom. 91, 405–416 (2013).CAS 
    Article 

    Google Scholar 
    Felten, V. et al. Physiological and behavioural responses of Gammarus pulex (Crustacea: Amphipoda) exposed to cadmium. Aquat. Toxicol. 86, 413–425 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    De Lange, H. J., Peeters, E. T. H. M. & Lürling, M. Changes in ventilation and locomotion of Gammarus pulex (Crustacea, Amphipoda) in response to low concentrations of pharmaceuticals. Hum. Ecol. Risk Assess. Int. J. 15, 111–120 (2009).Article 
    CAS 

    Google Scholar 
    Ashauer, R., Caravatti, I., Hintermeister, A. & Escher, B. I. Bioaccumulation kinetics of organic xenobiotic pollutants in the freshwater invertebrate Gammarus pulex modeled with prediction intervals. Environ. Toxicol. Chem. 29, 1625–1636 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    Schroeder-Spain, K., Fisher, L. L. & Smee, D. L. Uncoordinated: Effects of sublethal malathion and carbaryl exposures on juvenile and adult blue crabs (Callinectes sapidus). J. Exp. Mar. Biol. Ecol. 504, 1–9 (2018).CAS 
    Article 

    Google Scholar 
    Janssens, L. & Stoks, R. Synergistic effects between pesticide stress and predator cues: Conflicting results from life history and physiology in the damselfly Enallagma cyathigerum. Aquat. Toxicol. 132–133, 92–99 (2013).PubMed 
    Article 
    CAS 

    Google Scholar 
    Ernest, S. K. M. Homeostasis. In Encyclopedia of Ecology (eds Jørgensen, S. E. & Fath, B. D.) 1879–1884 (Academic Press, 2008).Chapter 

    Google Scholar 
    Karanova, M. V. & Andreev, A. A. Free amino acids and reducing sugars in the freshwater shrimp Gammarus lacustris (Crustacea, Amphipoda) at the initial stage of preparation to winter season. J. Evol. Biochem. Physiol. 46, 335–340 (2010).CAS 
    Article 

    Google Scholar 
    Maity, S. et al. Starvation causes disturbance in amino acid and fatty acid metabolism in Diporeia. Comp. Biochem. Physiol. B 161, 348–355 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    Cappello, T. et al. Impact of environmental pollution on caged mussels Mytilus galloprovincialis using NMR-based metabolomics. Mar. Pollut. Bull. 77, 132–139 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Jiang, Y., Jiao, H., Sun, P., Yin, F. & Tang, B. Metabolic response of Scapharca subcrenata to heat stress using GC/MS-based metabolomics. PeerJ 8, e8445 (2020).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Roznere, I., Watters, G. T., Wolfe, B. A. & Daly, M. Effects of relocation on metabolic profiles of freshwater mussels: Metabolomics as a tool for improving conservation techniques. Aquat. Conserv. Mar. Freshw. Ecosyst. 27, 919–926 (2017).Article 

    Google Scholar 
    Cappello, T., Maisano, M., Mauceri, A. & Fasulo, S. 1H NMR-based metabolomics investigation on the effects of petrochemical contamination in posterior adductor muscles of caged mussel Mytilus galloprovincialis. Ecotoxicol. Environ. Saf. 142, 417–422 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Cao, C. & Wang, W.-X. Chronic effects of copper in oysters Crassostrea hongkongensis under different exposure regimes as shown by NMR-based metabolomics. Environ. Toxicol. Chem. 36, 2428–2435 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Aru, V., Sarais, G., Savorani, F., Engelsen, S. B. & Cesare Marincola, F. Metabolic responses of clams, Ruditapes decussatus and Ruditapes philippinarum, to short-term exposure to lead and zinc. Mar. Pollut. Bull. 107, 292–299 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Tufi, S., Stel, J. M., de Boer, J., Lamoree, M. H. & Leonards, P. E. G. Metabolomics to explore imidacloprid-induced toxicity in the central nervous system of the freshwater snail Lymnaea stagnalis. Environ. Sci. Technol. 49, 14529–14536 (2015).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Tanguy, A., Boutet, I. & Moraga, D. Molecular characterization of the glutamine synthetase gene in the Pacific oyster Crassostrea gigas: Expression study in response to xenobiotic exposure and developmental stage. Biochim. Biophys. Acta BBA 1681, 116–125 (2005).CAS 
    PubMed 
    Article 

    Google Scholar 
    Chen, X., Shi, X., Gan, F., Huang, D. & Huang, K. Glutamine starvation enhances PCV2 replication via the phosphorylation of p38 MAPK, as promoted by reducing glutathione levels. Vet. Res. 46, 32 (2015).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Leroy, D., Haubruge, E., De Pauw, E., Thomé, J. P. & Francis, F. Development of ecotoxicoproteomics on the freshwater amphipod Gammarus pulex: Identification of PCB biomarkers in glycolysis and glutamate pathways. Ecotoxicol. Environ. Saf. 73, 343–352 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    Ch, R., Singh, A. K., Pandey, P., Saxena, P. N. & Mudiam, M. K. R. Identifying the metabolic perturbations in earthworm induced by cypermethrin using gas chromatography-mass spectrometry based metabolomics. Sci. Rep. 5, 15674 (2015).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Simpson, J. W., Allen, K. & Awapara, J. Free amino acids in some aquatic invertebrates. Biol. Bull. 117, 371–381 (1959).CAS 
    Article 

    Google Scholar 
    Fu, Q., Scheidegger, A., Laczko, E. & Hollender, J. Metabolomic profiling and toxicokinetics modeling to assess the effects of the pharmaceutical diclofenac in the aquatic invertebrate Hyalella azteca. Environ. Sci. Technol. 55, 7920–7929 (2021).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Tikunov, A. P., Johnson, C. B., Lee, H., Stoskopf, M. K. & Macdonald, J. M. Metabolomic investigations of american oysters using 1H-NMR spectroscopy. Mar. Drugs 8, 2578–2596 (2010).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Gülçin, İ. Antioxidant and antiradical activities of l-carnitine. Life Sci. 78, 803–811 (2006).PubMed 
    Article 
    CAS 

    Google Scholar 
    Yuan, D. et al. Ancestral genetic complexity of arachidonic acid metabolism in Metazoa. Biochim. Biophys. Acta 1841, 1272–1284 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    Garreta-Lara, E. et al. Effect of psychiatric drugs on Daphnia magna oxylipin profiles. Sci. Total Environ. 644, 1101–1109 (2018).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Dwyer, G. K., Stoffels, R. J., Rees, G. N., Shackleton, M. E. & Silvester, E. A predicted change in the amino acid landscapes available to freshwater carnivores. Freshw. Sci. 37, 108–120 (2017).Article 

    Google Scholar  More

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    Mammal extinction facilitated biome shift and human population change during the last glacial termination in East-Central Europe

    Vörös, I. Large mammal remains from the Upper Palaeolithic site at Esztergom-Gyurgyalag. Acta Archaeol. Hung. 43, 261–263 (1991).
    Google Scholar 
    Jánossy, D. Pleistocene Vertebrate Faunas of Hungary. Journal of Chemical Information and Modeling (Akadémiai Kiadó, 1986).
    Google Scholar 
    Kordos, L. A sketch of the vertebrata biostratigraphy of the Hungarian Holocene. Földrajzi Közlemények 101, 144–160 (1978).
    Google Scholar 
    Sümegi, P., Rudner, E. & Törőcsik, T. Environmental and chronological reconstruction problems during the Pleistocene/Holocene transition in Hungary (Magyarország pleisztocén végi és kora holocén környezeti változások kronológiai, tér és időbeli rekonstrukciós problémái). In Őskoros Kutatók IV. Összejövetelének Konferenciakötete (ed. Kolozsi, B.) 279–298 (Hajdú-Bihar Megyei Múzeumok Igazgatósága, 2012).
    Google Scholar 
    Bösken, J. et al. Investigating the last glacial Gravettian site ‘Ságvár Lyukas Hill’ (Hungary) and its paleoenvironmental and geochronological context using a multi-proxy approach. Palaeogeogr. Palaeoclimatol. Palaeoecol. 509, 77–90 (2018).Article 

    Google Scholar 
    Wilczyński, J. et al. Mammoth hunting strategies during the Late Gravettian in Central Europe as determined from case studies of Milovice I (Czech Republic) and Kraków Spadzista (Poland). Quat. Sci. Rev. 223, 105919 (2019).Article 

    Google Scholar 
    Lengyel, G. Reassessing the middle and late upper palaeolithic in Hungary. Acta Archaeol. Carpathica 51, 47–66 (2016).
    Google Scholar 
    Béres, S. et al. Zöld cave and the late epigravettian in eastern central Europe. Quat. Int. 587–588, 158–171 (2021).Article 

    Google Scholar 
    Feurdean, A. et al. Trends in biomass burning in the Carpathian region over the last 15,000 years. Quat. Sci. Rev. 45, 111–125 (2012).Article 
    ADS 

    Google Scholar 
    Kuneš, P. et al. Interpretation of the last-glacial vegetation of eastern-central Europe using modern analogues from southern Siberia. J. Biogeogr. 35, 2223–2236 (2008).Article 

    Google Scholar 
    Pazonyi, P. Mammalian ecosystem dynamics in the Carpathian Basin during the last 27,000 years. Palaeogeogr. Palaeoclimatol. Palaeoecol. 212, 295–314 (2004).Article 

    Google Scholar 
    Sümegi, P. et al. Climatic fluctuations inferred for the middle and late pleniglacial (MIS 2) based on high-resolution (∼ca. 20 y) preliminary environmental magnetic investigation of the loess section of the Madaras brickyard (Hungary). Cent. Eur. Geol. 55, 329–345 (2012).Article 

    Google Scholar 
    Magyari, E. K. et al. Vegetation and environmental responses to climate forcing during the last glacial maximum and deglaciation in the East Carpathians: attenuated response to maximum cooling and increased biomass burning. Quat. Sci. Rev. 106, 278–298 (2014).Article 
    ADS 

    Google Scholar 
    Feurdean, A. et al. Climate variability and associated vegetation response throughout central and eastern Europe (CEE) between 60 and 8 ka. Quat. Sci. Rev. 106, 206–224 (2014).Article 
    ADS 

    Google Scholar 
    Mann, D. H. et al. Life and extinction of megafauna in the ice-age Arctic. Proc. Natl. Acad. Sci. U. S. A. 112, 14301–14306 (2015).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    Magyari, E. K. et al. Rapid vegetation response to Lateglacial and early Holocene climatic fluctuation in the South Carpathian Mountains (Romania). Quat. Sci. Rev. 35, 116–130 (2012).Article 
    ADS 

    Google Scholar 
    Magyari, E. K. et al. Late Pleniglacial vegetation in eastern-central Europe: are there modern analogues in Siberia?. Quat. Sci. Rev. 95, 60–79 (2014).Article 
    ADS 

    Google Scholar 
    Magyari, E. K. et al. Warm Younger Dryas summers and early late glacial spread of temperate deciduous trees in the Pannonian Basin during the last glacial termination (20–9 kyr cal BP). Quat. Sci. Rev. 225, 105980 (2019).Article 

    Google Scholar 
    Sümegi, P., Magyari, E., Dániel, P., Molnár, M. & Törocsik, T. Responses of terrestrial ecosystems to Dansgaard-Oeshger cycles and Heinrich-events: a 28,000-year record of environmental changes from SE Hungary. Quat. Int. 293, 34–50 (2013).Article 

    Google Scholar 
    Hillebrand, J. Paleolithic History (Az őskőkor Története) (Magyar Szemle Társaság, 1934).
    Google Scholar 
    Vértes, L., Kretzoi, M. & Herrmann, M. Neuere Forschungen in der Jankovich-Höhle. Folia Archaeol. 9, 3–23 (1957).
    Google Scholar 
    Jánossy, D. Preliminary results of the paleontological investigations of a yet unknown rock shelter in the Bükk Mountains (A Bükk-hegység eddig ismeretlen kőfülkéjében végzett őslénytani ásatás előzetes eredménye, Répáshuta, Rejtek). Karszt- és Barlkut. Tájékoztató 72 (1963).Jánossy, D. & Kordos, L. Pleistocene-Holocene Mollusc and Vertebrate Fauna of two caves in Hungary. Ann. Hist. Musei Natl. Hungarici 68, 5–29 (1976).
    Google Scholar 
    Vértes, L. Paleolithic and Mesolithic Remains in Hungary (Az Őskőkor és az Átmeneti Kőkor Emlékei Magyarországon) (Akadémiai Kiadó, 1965).
    Google Scholar 
    Stieber, J. Oberpleistozäne Vegetationsgeschichte Ungarns im Spiegel anthrakotomischer Ergebnisse (bis 1957) (A magyarországi felsőpleisztocén vegetáció-története az anthrakotómiai eredmények (1957-ig) tükrében). Földtani Közlöny 97, 305–317 (1967).
    Google Scholar 
    Jánossy, D. Vorläufige Ergebnisse der Ausgrabungen in der Felsnische Rejtek I. (Bükkgebirge, Gem. Répáshuta). Karszt- és Barlangkutatás 3, 49–58 (1961).
    Google Scholar 
    Kovács, J. Radiocarbon chronology of late Pleistocene large mammal faunas from the Pannonian basin (Hungary). Bull. Geosci. 87, 13–19 (2012).Article 

    Google Scholar 
    Willis, K. J., Braun, M., Sümegi, P. & Tóth, A. Does soil change cause vegetation change or vice versa? A temporal perspective from Hungary. Ecology 78, 740–750 (1997).Article 

    Google Scholar 
    Magyari, E. Holocene biogeography of Fagus sylvatica L. and Carpinus betulus L. in the Carpathian-Alpine Region. Folia Hist. Musei Matra. 26, 15–35 (2002).
    Google Scholar 
    Magri, D. Persistence of tree taxa in Europe and quaternary climate changes. Quat. Int. 219, 145–151 (2010).Article 

    Google Scholar 
    Füköh, L. Biostratigraphical investigation of the mollusc fauna of Rejtek I. rock-niche and Petényi Cave: Bükk Mountains, Hungary (Rejtek kőfülke és a Petényi-barlang (Bükk-hegység) Mollusca faunájának malakosztratigráfiai vizsgálata). Folia Hist. Musei Matra. 12, 9–13 (1987).
    Google Scholar 
    Ramsey, C. B. & Lee, S. Recent and planned developments of the program OxCal. Radiocarbon 55, 720–730 (2013).CAS 
    Article 

    Google Scholar 
    Bradshaw, C. J. A., Cooper, A., Turney, C. S. M. & Brook, B. W. Robust estimates of extinction time in the geological record. Quat. Sci. Rev. 33, 14–19 (2012).Article 
    ADS 

    Google Scholar 
    Rasmussen, S. O. et al. A stratigraphic framework for abrupt climatic changes during the last glacial period based on three synchronized Greenland ice-core records: refining and extending the INTIMATE event stratigraphy. Quat. Sci. Rev. 106, 14–28 (2014).Article 
    ADS 

    Google Scholar 
    Reimer, P. J. et al. The IntCal20 Northern Hemisphere radiocarbon age calibration curve (0–55 cal kBP). Radiocarbon 62, 725–757 (2020).CAS 
    Article 

    Google Scholar 
    Katona, L., Kovács, J., Kordos, L., Szappanos, B. & Linkai, I. The Csajág mammoths (Mammuthus primigenius): late Pleniglacial finds from Hungary and their chronological significance. Quat. Int. 255, 130–138 (2012).Article 

    Google Scholar 
    Buczkó, K. et al. Responses of diatoms to the Younger Dryas climatic reversal in a South Carpathian mountain lake (Romania). J. Paleolimnol. 48, 417–431 (2012).Article 
    ADS 

    Google Scholar 
    Tóth, M. et al. A chironomid-based reconstruction of late glacial summer temperatures in the southern Carpathians (Romania). Quat. Res. 77, 122–131 (2012).Article 
    CAS 

    Google Scholar 
    Sümegi, P. et al. Radiocarbon-dated paleoenvironmental changes on a lake and peat sediment sequence from the central Great Hungarian Plain (Central Europe) during the last 25,000 years. Radiocarbon 53, 85–97 (2011).Article 

    Google Scholar 
    Gill, J. L., Williams, J. W., Jackson, S. T., Lininger, K. B. & Robinson, G. S. Pleistocene megafaunal collapse, novel plant communities, and enhanced fire regimes in North America. Science 326, 1100–1103 (2009).CAS 
    PubMed 
    Article 
    ADS 

    Google Scholar 
    Feurdean, A. et al. Fire hazard modulation by long-term dynamics in land cover and dominant forest type in eastern and central Europe. Biogeosciences 17, 1213–1230 (2020).Article 
    ADS 

    Google Scholar 
    Sümegi, P. et al. Radiocarbon dated complex paleoecological and geoarcheological analyses at the Bodrogkeresztúr—Henye Gravettian site (Ne Hungary). Archeometriai Műhely 13, 31–41 (2016).
    Google Scholar 
    Herrmann, M., Jánossy, D., Stieber, J. & Vértes, L. Ausgrabungen in der Petényi- und Pesko-Höhle (Bükk-Gebirge). Folia Archaeol. 8, 3–22 (1956).
    Google Scholar 
    Royer, A. How complex is the evolution of small mammal communities during the Late Glacial in southwest France?. Quat. Int. 414, 23–33 (2016).Article 

    Google Scholar 
    Crégut-Bonnoure, E. et al. The karst of the Vaucluse, an exceptional record for the last glacial maximum (LGM) and the Late-glacial period palaeoenvironment of southeastern France. Quat. Int. 339–340, 41–61 (2014).Article 

    Google Scholar 
    Cuenca-Bescós, G., Straus, L. G., González Morales, M. R. & García Pimienta, J. C. The reconstruction of past environments through small mammals: from the Mousterian to the Bronze Age in El Mirón Cave (Cantabria, Spain). J. Archaeol. Sci. 36, 947–955 (2009).Article 

    Google Scholar 
    Kovalchuk, O. et al. Living in a time of change: late Pleistocene/Holocene transitional vertebrate fauna of Grot Skeliastyi (Crimea, Ukraine). Hist. Biol. https://doi.org/10.1080/08912963.2020.1769094 (2020).Article 

    Google Scholar 
    Puzachenko, A. Y. & Markova, A. K. Evolution of mammal species composition and species richness during the Late Pleistocene—Holocene transition in Europe: a general view at the regional scale. Quat. Int. 530–531, 88–106 (2019).Article 

    Google Scholar 
    Varga, Z. Extra-Mediterranean refugia, post-glacial vegetation history and area dynamics in Eastern Central Europe. In Relict Species: Phylogeography and Conservation Biology (eds Habel, J. C. & Assmann, T.) 57–87 (Springer Berlin Heidelberg, 2010).Chapter 

    Google Scholar 
    Magyari, E. K. et al. Holocene persistence of wooded steppe in the Great Hungarian Plain. J. Biogeogr. 37, 915–935 (2010).Article 

    Google Scholar 
    Sommer, R. S. & Nadachowski, A. Glacial refugia of mammals in Europe: evidence from fossil records. Mamm. Rev. 36, 251–265 (2006).Article 

    Google Scholar 
    Mann, D. H., Groves, P., Gaglioti, B. V. & Shapiro, B. A. Climate-driven ecological stability as a globally shared cause of Late Quaternary megafaunal extinctions: the Plaids and Stripes Hypothesis. Biol. Rev. 94, 328–352 (2019).Article 

    Google Scholar 
    Lister, A. M. & Sher, A. V. Ice cores and mammoth extinction. Nature 378, 23–24 (1995).CAS 
    Article 
    ADS 

    Google Scholar 
    Owen-Smith, N. R. Megaherbivores: The Influence of Very Large Body Size on Ecology (Cambridge University Press, 1988).Book 

    Google Scholar 
    Guthrie, R. D. Frozen Fauna of the Mammoth Steppe: The story of Blue Babe (The University of Chicago Press, 1990).Book 

    Google Scholar 
    Huntley, B. et al. Millennial climatic fluctuations are key to the structure of last glacial ecosystems. PLoS One 8, e61963 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    Vörös, I. Large mammalian faunal changes during the Late Upper Pleistocene and Early Holocene times in the Carpathian Basin. In Pleistocene Environment in Hungary (ed. Pécsi, M.) 81–102 (Geographical Research Institute HAS, 1987).
    Google Scholar 
    Németh, A. et al. Holocene mammal extinctions in the Carpathian Basin: a review. Mamm. Rev. 47, 38–52 (2017).Article 

    Google Scholar 
    Marchant, R., Brewer, S., Webb, T. I. & Turvey, S. T. Holocenedeforestation: a history of human–environmental interactions, climate change, and extinction. In Holocene Extinctions (ed. Turvey, S. T.) 213–234 (Oxford University Press, 2009).Chapter 

    Google Scholar 
    Lorenzen, E. D. et al. Species-specific responses of Late Quaternary megafauna to climate and humans. Nature 479, 359–364 (2011).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    Herre, W. Rangifer tarandus—Ren, Rentier. In Handbuch der Saugetiere Europas 2/II Paarhufer—Artiodactyla (eds Niethammer, J. & Krapp, F.) 198–216 (Aula Publisher, 1986).
    Google Scholar 
    Sommer, R. S., Kalbe, J., Ekström, J., Benecke, N. & Liljegren, R. Range dynamics of the reindeer in Europe during the last 25,000 years. J. Biogeogr. 41, 298–306 (2014).Article 

    Google Scholar 
    Lengyel, G. & Wilczyński, J. (2018) The Gravettian and the Epigravettian chronology in eastern central Europe: a comment on Bösken et al. (2017). Palaeogeogr. Palaeoclimatol. Palaeoecol. 506, 265–269 (2018).Article 

    Google Scholar 
    Sommer, R. S. Late Pleistocene and Holocene history of mammals in Europe. Handb. Mamm. Eur. https://doi.org/10.1007/978-3-319-65038-8_3-1 (2020).Article 

    Google Scholar 
    Palkopoulou, E. et al. Holarctic genetic structure and range dynamics in the woolly mammoth. Proc. R. Soc. B Biol. Sci. 280, 20131910 (2013).Article 

    Google Scholar 
    Spötl, C., Reimer, P. J. & Göhlich, U. B. Mammoths inside the Alps during the last glacial period: radiocarbon constraints from Austria and palaeoenvironmental implications. Quat. Sci. Rev. 190, 11–19 (2018).Article 
    ADS 

    Google Scholar 
    Sümegi, P. Loess and Upper Paleolithic Environment in Hungary: An Introduction to the Environmental History of Hungary (Aurea, 2005).
    Google Scholar 
    Újvári, G. et al. Coupled European and Greenland last glacial dust activity driven by North Atlantic climate. Proc. Natl. Acad. Sci. U. S. A. 114, E10632–E10638 (2017).PubMed 
    PubMed Central 
    Article 
    ADS 
    CAS 

    Google Scholar 
    Haynes, G. Extinctions in North America’s late glacial landscapes. Quat. Int. 285, 89–98 (2013).Article 

    Google Scholar 
    Cooper, A. et al. Abrupt warming events drove Late Pleistocene Holarctic megafaunal turnover. Science 349, 602–606 (2015).CAS 
    PubMed 
    Article 
    ADS 

    Google Scholar 
    Lengyel, G. et al. The Epigravettian chronology and the human population of eastern Central Europe during MIS2. Quat. Sci. Rev. 271, 107187 (2021).Article 

    Google Scholar 
    Sajó, I. E. et al. Core-shell processing of natural pigment: upper Palaeolithic red ochre from Lovas, Hungary. PLoS One 10, 1–18 (2015).Article 
    CAS 

    Google Scholar 
    Horváth, T. & Ilon, G. Mezőlak-Szélmező-peatbog: an unusual prehistoric site (Mezőlak-szélmező-tőzegtelep: egy nem hétköznapi őskori lelőhely). Archeometriai Műhely 14, 143–183 (2017).
    Google Scholar 
    Zalai-Gaál, I. Possibilites of the social-archaeological studies of the Neolithic. Antaeus 27, 449–471 (2004).
    Google Scholar 
    Reade, H. et al. Magdalenian and Epimagdalenian chronology and palaeoenvironments at Kůlna Cave, Moravia, Czech Republic. Archaeol. Anthropol. Sci. https://doi.org/10.1007/s12520-020-01254-4 (2021).Article 
    PubMed 

    Google Scholar 
    Łanczont, M. et al. Late Glacial environment and human settlement of the Central Western Carpathians: a case study of the Nowa Biała 1 open-air site (Podhale Region, southern Poland). Quat. Int. 512, 113–132 (2019).Article 

    Google Scholar 
    Mészáros, G. & Vértes, L. A paint mine from the early Upper Palaeolithic age near Lovas (Hungary, county Veszprém). Acta Archaeol. Acad. Sci. Hung. 5, 5–34 (1955).
    Google Scholar 
    Pathou-Mathis, M. Nouvelle analyse du metérial osseux du site de Lovas. Praehistoria 3, 161–175 (2002).
    Google Scholar 
    Sobkowiak-Tabaka, I. & Diachenko, A. Approaching daily life at Late Palaeolithic camps: the case of Lubrza 10, Western Poland. Prahistorische Z. 95, 311–333 (2020).Article 

    Google Scholar 
    Molnár, M. et al. EnvironMICADAS : a mini 14C AMS with enhanced gas ion source. Radiocarbon 55, 338–344 (2013).Article 

    Google Scholar 
    Major, I. et al. Assessment and development of bone preparation for radiocarbon dating at HEKAL. Radiocarbon 61, 1551–1561 (2019).CAS 
    Article 

    Google Scholar 
    Rinyu, L. et al. Optimization of sealed tube graphitization method for environmental C-14 studies using MICADAS. Nucl. Instrum. Methods Phys. Res. Sect. B Beam Interact. Mater. At. 294, 270–275 (2013).CAS 
    Article 
    ADS 

    Google Scholar 
    Molnár, M. et al. Status report of the new AMS 14 C sample preparation lab of the Hertelendi laboratory of environmental studies (Debrecen, Hungary). Radiocarbon 55, 665–676 (2013).Article 

    Google Scholar 
    Blaauw, M. & Christeny, J. A. Flexible paleoclimate age-depth models using an autoregressive gamma process. Bayesian Anal. 6, 457–474 (2011).MathSciNet 
    MATH 
    Article 

    Google Scholar 
    Kosintsev, P. et al. Evolution and extinction of the giant rhinoceros Elasmotherium sibiricum sheds light on late Quaternary megafaunal extinctions. Nat. Ecol. Evol. 3, 31–38 (2019).PubMed 
    Article 

    Google Scholar 
    Davis, B. A. S. et al. The European modern pollen database (EMPD) project. Veg. Hist. Archaeobot. 22, 521–530 (2013).Article 

    Google Scholar 
    ter Braak, C. J. F. & Juggins, S. Weighted averaging partial least squares regression (WA-PLS): an improved method for reconstructing environmental variables from species assemblages. Hydrobiologia 269–270, 485–502 (1993).Article 

    Google Scholar 
    Birks, H. J. B., Line, J. M., Juggings, S., Stevenson, A. C. & ter Braak, C. J. F. Diatoms and pH reconstruction. Philos. Trans. R. Soc. B 327, 263–278 (1990).ADS 

    Google Scholar 
    Prentice, I. C. Multidimensional scaling as a research tool in quaternary palynology: a review of theory and methods. Rev. Palaeobot. Palynol. 31, 71–104 (1980).Article 

    Google Scholar 
    van der Voet, H. Comparing the predictive accuracy of models using a simple randomization test. Chemom. Intell. Lab. Syst. 25, 313–323 (1994).Article 

    Google Scholar 
    Birks, H. J. B. Quantitative palaeoenvironmental reconstructions from holocene biological data. Glob. Change Holocene https://doi.org/10.4324/9780203785027 (2003).Article 

    Google Scholar 
    Rioja, J. S. Analysis of Quaternary Science Data, R package version (0.8-5). (2012).Telford, R. J. & Birks, H. J. B. A novel method for assessing the statistical significance of quantitative reconstructions inferred from biotic assemblages. Quat. Sci. Rev. 30, 1272–1278 (2011).Article 
    ADS 

    Google Scholar 
    Guiot, J. Methodology of the last climatic cycle reconstruction in France from pollen data. Palaeogeogr. Palaeoclimatol. Palaeoecol. 80, 49–69 (1990).Article 

    Google Scholar 
    Birks, H. J. B. Ecological palaeoecology and conservation biology: controversies, challenges, and compromises. Int. J. Biodivers. Sci. Ecosyst. Serv. Manag. 8, 292–304 (2012).Article 

    Google Scholar 
    Kordos, L. Climatostratigraphy of Upper Pleistocene vertebrates and the conditions of loess formation in Hungary. GeoJournal 15, 163–166 (1987).Article 

    Google Scholar 
    Prentice, I. C., Guiot, J., Huntley, B., Jolly, D. & Cheddadi, R. Reconstructing biomes from palaeoecological data: a general method and its application to European pollen data at 0 and 6 ka. Clim. Dyn. 12, 185–194 (1996).Article 

    Google Scholar 
    Tarasov, P. E. et al. Present-day and mid-Holocene biomes reconstructed from pollen and plant macrofossil data from the former Soviet Union and Mongolia. J. Biogeogr. 25, 1029–1053 (1998).Article 

    Google Scholar 
    Allen, J. R. M., Watts, W. A. & Huntley, B. Weichselian palynostratigraphy, palaeovegetation and palaeoenvironment; the record from Lago Grande di Monticchio, southern Italy. Quat. Int. 73–74, 91–110 (2000).Article 

    Google Scholar  More

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    Pork dinners fuel huge crocodiles’ return from near-extinction

    RESEARCH HIGHLIGHT
    26 April 2022

    Saltwater crocodiles in northern Australia have thrived after adding feral pig to the menu.

    The population of saltwater crocodiles boomed in some parts of Australia after the reptiles began supplementing their usual seafood with feral pig. Credit: Reinhard Dirscherl/Science Photo Library

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    In parts of Australia, the world’s largest living reptile is making a comeback thanks in part to a diet rich in pork, new research suggests1.

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    Africans and Europeans differ in their facial perception of dominance and sex-typicality: a multidimensional Bayesian approach

    de Waal-Andrews, W., Gregg, A. P. & Lammers, J. When status is grabbed and when status is granted: Getting ahead in dominance and prestige hierarchies. Br. J. Soc. Psychol. 54, 445–464 (2015).PubMed 

    Google Scholar 
    Mileva, V. R., Cowan, M. L., Cobey, K. D., Knowles, K. K. & Little, A. C. In the face of dominance: Self-perceived and other-perceived dominance are positively associated with facial-width-to-height ratio in men. Pers. Individ. Dif. 69, 115–118 (2014).
    Google Scholar 
    Quist, M. C., Watkins, C. D., Smith, F. G., DeBruine, L. M. & Jones, B. C. Facial masculinity is a cue to women’s dominance. Pers. Individ. Dif. 50, 1089–1093 (2011).
    Google Scholar 
    Gallup, A. C., O’Brien, D. T., White, D. D. & Wilson, D. S. Handgrip strength and socially dominant behavior in male adolescents. Evol. Psychol. 8, 229–243 (2010).PubMed 

    Google Scholar 
    Toscano, H., Schubert, T. W. & Sell, A. N. Judgments of dominance from the face track physical strength. Evol. Psychol. 12, 1–18 (2014).PubMed 

    Google Scholar 
    Toscano, H., Schubert, T. W., Dotsch, R., Falvello, V. & Todorov, A. Physical strength as a cue to dominance: A data-driven approach. Personal. Soc. Psychol. Bull. 42, 1603–1616 (2016).
    Google Scholar 
    Kordsmeyer, T. L., Freund, D., van Vugt, M. & Penke, L. Honest signals of status: Facial and bodily dominance are related to success in physical but not nonphysical competition. Evol. Psychol. 17, 147470491986316 (2019).
    Google Scholar 
    Han, C. et al. Interrelationships among men’s threat potential, facial dominance, and vocal dominance. Evol. Psychol. 15, 1–4 (2017).
    Google Scholar 
    Sell, A. et al. Human adaptations for the visual assessment of strength and fighting ability from the body and face. Proc. R. Soc. B Biol. Sci. 276, 575–584 (2009).
    Google Scholar 
    Kleisner, K., Kočnar, T., Rubešová, A. & Flegr, J. Eye color predicts but does not directly influence perceived dominance in men. Pers. Individ. Dif. 49, 59–64 (2010).
    Google Scholar 
    Windhager, S., Schaefer, K. & Fink, B. Geometric morphometrics of male facial shape in relation to physical strength and perceived attractiveness, dominance, and masculinity. Am. J. Hum. Biol. 23, 805–814 (2011).PubMed 

    Google Scholar 
    Albert, G., Wells, E., Arnocky, S., Liu, C. H. & Hodges-Simeon, C. R. Observers use facial masculinity to make physical dominance assessments following 100-ms exposure. Aggress. Behav. https://doi.org/10.1002/ab.21941 (2020).Article 
    PubMed 

    Google Scholar 
    Batres, C., Re, D. E. & Perrett, D. I. Influence of perceived height, masculinity, and age on each other and on perceptions of dominance in male faces. Perception 44, 1293–1309 (2015).PubMed 

    Google Scholar 
    Boothroyd, L. G., Jones, B. C., Burt, D. M. & Perrett, D. I. Partner characteristics associated with masculinity, health and maturity in male faces. Pers. Individ. Dif. 43, 1161–1173 (2007).
    Google Scholar 
    Main, J. C., Jones, B. C., DeBruine, L. M. & Little, A. C. Integrating gaze direction and sexual dimorphism of face shape when perceiving the dominance of others. Perception 38, 1275–1283 (2009).PubMed 

    Google Scholar 
    Van Dongen, S. & Sprengers, E. Hand grip strength in relation to morphological measures of masculinity, fluctuating asymmetry and sexual behaviour in males and females. Sex Horm. https://doi.org/10.5772/25880 (2012).Article 

    Google Scholar 
    Fink, B., Neave, N. & Seydel, H. Male facial appearance signals physical strength to women. Am. J. Hum. Biol. 19, 82–87 (2007).PubMed 

    Google Scholar 
    Little, A. C., Třebický, V., Havlíček, J., Roberts, S. C. & Kleisner, K. Human perception of fighting ability: Facial cues predict winners and losers in mixed martial arts fights. Behav. Ecol. 26, 1470–1475 (2015).
    Google Scholar 
    Law, S. M. J. et al. Facial appearance is a cue to oestrogen levels in women. Proc. Biol. Sci. 273, 135–140 (2006).
    Google Scholar 
    Probst, F., Bobst, C. & Lobmaier, J. S. Testosterone-to-estradiol ratio is associated with female facial attractiveness. Q. J. Exp. Psychol. 69, 89–99 (2016).
    Google Scholar 
    Marečková, K. et al. Testosterone-mediated sex differences in the face shape during adolescence: Subjective impressions and objective features. Horm. Behav. 60, 681–690 (2011).PubMed 

    Google Scholar 
    Whitehouse, A. J. O. et al. Prenatal testosterone exposure is related to sexually dimorphic facial morphology in adulthood. Proc. R. Soc. B Biol. Sci. 282, 78–94 (2015).
    Google Scholar 
    Kordsmeyer, T. L., Freund, D., Pita, S. R., Jünger, J. & Penke, L. Further evidence that facial width-to-height ratio and global facial masculinity are not positively associated with testosterone levels. Adapt. Hum. Behav. Physiol. 5, 117–130 (2019).
    Google Scholar 
    Chiu, H. T., Shih, M. T. & Chen, W. L. Examining the association between grip strength and testosterone. Aging Male 3, 1–8 (2019).
    Google Scholar 
    Hirschberg, A. L. et al. Effects of moderately increased testosterone concentration on physical performance in young women: A double blind, randomised, placebo controlled study. Br. J. Sports Med. 3, 1–7. https://doi.org/10.1136/bjsports-2018-100525 (2019).Article 

    Google Scholar 
    Finkelstein, J. S. et al. Gonadal steroids and body composition, strength, and sexual function in men. N. Engl. J. Med. 369, 1011–1022 (2013).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    van Bokhoven, I. et al. Salivary testosterone and aggression, delinquency, and social dominance in a population-based longitudinal study of adolescent males. Horm. Behav. 50, 118–125 (2006).PubMed 

    Google Scholar 
    Carré, J. M. & Olmstead, N. A. Social neuroendocrinology of human aggression: Examining the role of competition-induced testosterone dynamics. Neuroscience 286, 171–186 (2015).PubMed 

    Google Scholar 
    Lefevre, C. E., Etchells, P. J., Howell, E. C., Clark, A. P. & Penton-Voak, I. S. Facial width-to-height ratio predicts self-reported dominance and aggression in males and females, but a measure of masculinity does not. Biol. Lett. 10, 20140729 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    Alrajih, S. & Ward, J. Increased facial width-to-height ratio and perceived dominance in the faces of the UK’s leading business leaders. Br. J. Psychol. 105, 153–161 (2014).PubMed 

    Google Scholar 
    Watkins, C. D., Jones, B. C. & DeBruine, L. M. Individual differences in dominance perception: Dominant men are less sensitive to facial cues of male dominance. Pers. Individ. Dif. 49, 967–971 (2010).
    Google Scholar 
    Wang, X., Guinote, A. & Krumhuber, E. G. Dominance biases in the perception and memory for the faces of powerholders, with consequences for social inferences. J. Exp. Soc. Psychol. 78, 23–33 (2018).
    Google Scholar 
    de Carrito, M. L. et al. The role of sexually dimorphic skin colour and shape in attractiveness of male faces. Evol. Hum. Behav. 37, 125–133 (2016).
    Google Scholar 
    Stephen, I. D., Oldham, F. H., Perrett, D. I. & Barton, R. A. Redness enhances perceived aggression, dominance and attractiveness in men’s faces. Evol. Psychol. 10, 562–572 (2012).PubMed 

    Google Scholar 
    Stephen, I. D. & Perrett, D. I. Color and face perception. in Handbook of Color Psychology (eds. Elliot, A. J., Fairchild, M. D. & Franklin, A.) 585–602 (Cambridge University Press, 2016). https://doi.org/10.1017/cbo9781107337930.029.Carrito, M. L. & Semin, G. R. When we don’t know what we know–Sex and skin color. Cognition 191, 103972 (2019).PubMed 

    Google Scholar 
    Said, C. P. & Todorov, A. A statistical model of facial attractiveness. Psychol. Sci. 22, 1183–1190 (2011).PubMed 

    Google Scholar 
    Mitteroecker, P., Windhager, S., Møller, G. B. & Schaefer, K. The morphometrics of ‘masculinity’ in human faces. PLoS One 10, e0118374 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    Sanchez-Pages, S., Rodriguez-Ruiz, C. & Turiegano, E. Facial masculinity: How the choice of measurement method enables to detect its influence on behaviour. PLoS One 9, 10078 (2014).
    Google Scholar 
    Scott, I. M. L., Pound, N., Stephen, I. D., Clark, A. P. & Penton-Voak, I. S. Does masculinity matter? The contribution of masculine face shape to male attractiveness in humans. PLoS One 5, e13585 (2010).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rennels, J. L., Bronstad, P. M. & Langlois, J. H. Are attractive men’s faces masculine or feminine ? The importance of type of facial stimuli. J. Exp. Psychol. Hum. Percept. Perform. 34, 884–893 (2008).PubMed 

    Google Scholar 
    Swaddle, J. P. & Reierson, G. W. Testosterone increases perceived dominance but not attractiveness in human males. Proc. R. Soc. B Biol. Sci. 269, 2285–2289 (2002).CAS 

    Google Scholar 
    Hester, N., Jones, B. C. & Hehman, E. Perceived femininity and masculinity contribute independently to facial impressions. J. Exp. Psychol. Gen. https://doi.org/10.1037/xge0000989 (2020).Article 
    PubMed 

    Google Scholar 
    Howansky, K., Albuja, A. & Cole, S. Seeing Gender: Perceptual Representations of Transgender Individuals. Soc. Psychol. Personal. Sci. 11, 474–482 (2020).
    Google Scholar 
    Kleisner, K. et al. How and why patterns of sexual dimorphism in human faces vary across the world. Sci. Rep. 7, 10048 (2021).
    Google Scholar 
    Kleisner, K. et al. African and European perception of African female attractiveness. Evol. Hum. Behav. 38, 744–755 (2017).
    Google Scholar 
    Strom, M. A., Zebrowitz, L. A., Zhang, S., Bronstad, P. M. & Lee, H. K. Skin and bones: The contribution of skin tone and facial structure to racial prototypicality ratings. PLoS One 7, e41193 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Coetzee, V., Greeff, J. M., Stephen, I. D. & Perrett, D. I. Cross-cultural agreement in facial attractiveness preferences: The role of ethnicity and gender. PLoS One 9, 1700 (2014).
    Google Scholar 
    Henrich, J., Heine, S. J. & Norenzayan, A. Most people are not WEIRD. Nature 466, 29–29 (2010).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Třebický, V., Fialová, J., Kleisner, K. & Havlíček, J. Focal length affects depicted shape and perception of facial images. PLoS One 11, e0149313 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Nábělková, M. Closely-related languages in contact: Czech, Slovak, “Czechoslovak”. Int. J. Soc. Lang. 183, 53–73 (2007).
    Google Scholar 
    Dixson, B. J. Facial width to height ratio and dominance. Encycl. Evol. Psychol. Sci. https://doi.org/10.1007/978-3-319-16999-6 (2017).Article 

    Google Scholar 
    Geniole, S. N. & McCormick, C. M. Facing our ancestors: Judgements of aggression are consistent and related to the facial width-to-height ratio in men irrespective of beards. Evol. Hum. Behav. 36, 279–285 (2015).
    Google Scholar 
    Třebický, V. et al. Further evidence for links between facial width-to-height ratio and fighting success: Commentary on Zilioli et al. (2014). Aggress. Behav. 41, 331–334 (2015).PubMed 

    Google Scholar 
    McLaren, K. The development of the CIE 1976 (L*a*b*) uniform colour space and colour-difference formula. J. Soc. Dye. Colour. 92, 338–341 (1976).
    Google Scholar 
    Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Coetzee, V. et al. African perceptions of female attractiveness. PLoS ONE 7, 3–8 (2012).
    Google Scholar 
    Webster, M. & Sheets, H. D. A practical introduction to landmark-based geometric morphometrics. Paleontol. Soc. Pap. 16, 163–188 (2010).Kleisner, K., Pokorný, Š & Saribay, S. A. Toward a new approach to cross-cultural distinctiveness and typicality of human faces: The cross-group typicality/ distinctiveness metric. Front. Psychol. 10, 124 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Bookstein, F. L. Biometrics, biomathematics and the morphometric synthesis. Bull. Math. Biol. 58, 313–365 (1996).CAS 
    PubMed 
    MATH 

    Google Scholar 
    Rohlf, F. J. The tps series of software. Hystrix 26, 1–4 (2015).
    Google Scholar 
    Adams, D. C. & Otárola-Castillo, E. Geomorph: An r package for the collection and analysis of geometric morphometric shape data. Methods Ecol. Evol. 4, 393–399 (2013).
    Google Scholar 
    R Core Team. R: A language and environment for statistical computing. (2021).Revelle, W. psych: Procedures for Personality and Psychological Research. (2018).Shrout, P. E. & Fleiss, J. L. Intraclass correlations: uses in assessing rater reliability. Psychol. Bull. 86, 420–428 (1979).CAS 
    PubMed 

    Google Scholar 
    McElreath, R. rethinking: Statistical Rethinking book package. R package version 2.13. (2020).Stan Development Team. RStan: The R interface to Stan. R package version 2.21.2. (2020).Rhodes, G. The evolutionary psychology of facial beauty. Annu. Rev. Psychol. 57, 199–226 (2006).PubMed 

    Google Scholar 
    Voegeli, R. et al. Cross-cultural perception of female facial appearance: A multi-ethnic and multi-centre study. PLoS ONE 16, 8–12 (2021).
    Google Scholar 
    Kočnar, T., Adil Saribay, S. & Kleisner, K. Perceived attractiveness of Czech faces across 10 cultures: Associations with sexual shape dimorphism, averageness, fluctuating asymmetry, and eye color. PLoS One 14, e0225549 (2019).Pavlovič, O., Fiala, V. & Kleisner, K. Environmental convergence in facial preferences: A cross-group comparison of Asian Vietnamese, Czech Vietnamese, and Czechs. Sci. Rep. 11, 1–10 (2021).
    Google Scholar 
    Gonzalez-Santoyo, I. et al. The face of female dominance: Women with dominant faces have lower cortisol. Horm. Behav. 71, 16–21 (2015).CAS 
    PubMed 

    Google Scholar 
    Perrett, D. I. et al. Effects of sexual dimorphism on facial attractiveness. Nature 394, 884–887 (1998).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Saribay, S. A. et al. The Bogazici face database: Standardized photographs of Turkish faces with supporting materials. PLoS One 13, 10058 (2018).
    Google Scholar 
    Alharbi, S. A. H., Holzleitner, I. J., Lee, A. J., Saribay, S. A. & Jones, B. C. Women’s preferences for sexual dimorphism in faces: Data from a sample of arab women. Evol. Psychol. Sci. 6, 328–334 (2020).
    Google Scholar 
    Jones, B. C. et al. To which world regions does the valence–dominance model of social perception apply?. Nat. Hum. Behav. 5, 159–169 (2021).PubMed 

    Google Scholar 
    Sutherland, C. A. M. et al. Facial first impressions across culture: Data-driven modeling of Chinese and British perceivers’ unconstrained facial impressions. Personal. Soc. Psychol. Bull. 44, 521–537 (2017).
    Google Scholar 
    Marcinkowska, U. M. et al. Cross-cultural variation in men’s preference for sexual dimorphism in women’s faces. Biol. Lett. 10, 4–7 (2014).
    Google Scholar 
    Marcinkowska, U. M. et al. Women’s preferences for men’s facial masculinity are strongest under favorable ecological conditions. Sci. Rep. 9, 1–10 (2019).CAS 

    Google Scholar 
    Todorov, A., Olivola, C. Y., Dotsch, R. & Mende-Siedlecki, P. Social attributions from faces: Determinants, consequences, accuracy, and functional significance. Annu. Rev. Psychol. 66, 519–545 (2015).PubMed 

    Google Scholar 
    Little, A. C., Jones, B. C. & Debruine, L. M. Facial attractiveness: Evolutionary based research. Philos. Trans. R. Soc. B Biol. Sci. 366, 1638–1659 (2011).Foo, Y. Z., Simmons, L. W. & Rhodes, G. Predictors of facial attractiveness and health in humans. Sci. Rep. 7, 39731 (2017).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Dion, K., Berscheid, E. & Walster, E. What is beautiful is good. J. Pers. Soc. Psychol. 24, 285–290 (1972).CAS 
    PubMed 

    Google Scholar 
    Cheng, J. T., Tracy, J. L., Foulsham, T., Kingstone, A. & Henrich, J. Two ways to the top: Evidence that dominance and prestige are distinct yet viable avenues to social rank and influence. J. Pers. Soc. Psychol. 104, 103–125 (2013).PubMed 

    Google Scholar 
    van den Berghe, P. L. & Frost, P. Skin color preference, sexual dimorphism and sexual selection: A case of gene culture co-evolution?. Ethn. Racial Stud. 9, 87–113 (1986).
    Google Scholar 
    Fink, B. et al. Colour homogeneity and visual perception of age, health and attractiveness of male facial skin. J. Eur. Acad. Dermatology Venereol. 26, 1486–1492 (2012).CAS 

    Google Scholar 
    Gallagher, N. M. & Bodenhausen, G. V. Gender essentialism and the mental representation of transgender women and men: A multimethod investigation of stereotype content. Cognition 217, 104887 (2021).Fiala, V. et al. Facial attractiveness and preference of sexual dimorphism: A comparison across five populations. Evol. Hum. Sci. 3, e38 (2021). More

  • in

    Short and long-term costs of inbreeding in the lifelong-partnership in a termite

    Shellman-Reeve, J. S. Courting strategies and conflicts in a monogamous, biparental termite. Proc. R. Soc. Lond. Ser. B: Biol. Sci. 266, 137–144 (1999).Article 

    Google Scholar 
    Boomsma, J. J. Beyond promiscuity: mate-choice commitments in social breeding. Philos. Trans. R. Soc. B: Biol. Sci. 368 (2013).Nichols, H. J. The causes and consequences of inbreeding avoidance and tolerance in cooperatively breeding vertebrates. J. Zool. 303, 1–14 (2017).Article 

    Google Scholar 
    Clutton-Brock, T. H. Female transfer and inbreeding avoidance in social mammals. Nature 337, 70–72 (1989).CAS 
    Article 
    PubMed 

    Google Scholar 
    Wolff, J. O. Parents suppress reproduction and stimulate dispersal in opposite-sex juvenile white-footed mice. Nature 359, 409–410 (1992).CAS 
    Article 
    PubMed 

    Google Scholar 
    Abbott, D. In Primate Social Conflict (eds W. A. Mason & S. P. Mendoza) 331–372 (State University of New York Press, 1993).Koenig, W. D., Haydock, J. & Stanback, M. T. Reproductive roles in the cooperatively breeding acorn woodpecker: incest avoidance versus reproductive competition. Am. Nat. 151, 243–255 (1998).CAS 
    Article 
    PubMed 

    Google Scholar 
    Hanby, J. P. & Bygott, J. D. Emigration of subadult lions. Anim. Behav. 35, 161–169 (1987).Article 

    Google Scholar 
    Brooked, M. G., Rowley, I., Adams, M. & Baverstock, P. R. Promiscuity: an inbreeding avoidance mechanism in a socially monogamous species? Behav. Ecol. Sociobiol. 26, 191–199 (1990).Article 

    Google Scholar 
    Amos, B., Schlotterer, C. & Tautz, D. Social structure of pilot whales revealed by analytical DNA proftling. Science 260, 670–672 (1993).CAS 
    Article 
    PubMed 

    Google Scholar 
    Sillero-Zubiri, C., Gottelli, D. & Macdonald, D. W. Male philopatry, extra-pack copulations and inbreeding avoidance in Ethiopian wolves (Canis simensis). Behav. Ecol. Sociobiol. 38, 331–340 (1996).Article 

    Google Scholar 
    Husseneder, C., Simms, D. M. & Ring, D. R. Genetic diversity and genotypic differentiation between the sexes in swarm aggregations decrease inbreeding in the Formosan subterranean termite. Insectes Sociaux 53, 212–219 (2006).Article 

    Google Scholar 
    Blouin, S. F. & Blouin, M. Inbreeding avoidance behaviors. Trends Ecol. Evol. 3, 230–233 (1988).CAS 
    Article 
    PubMed 

    Google Scholar 
    Pusey, A. & Wolf, M. Inbreeding avoidance in animals. Trends Ecol. Evol. 11, 201–206 (1996).CAS 
    Article 
    PubMed 

    Google Scholar 
    Gerlach, G. & Lysiak, N. Kin recognition and inbreeding avoidance in zebrafish, Danio rerio, is based on phenotype matching. Anim. Behav. 71, 1371–1377 (2006).Article 

    Google Scholar 
    Hurst, J. L. et al. Individual recognition in mice mediated by major urinary proteins. Nature 414, 631–634 (2001).CAS 
    Article 
    PubMed 

    Google Scholar 
    Vargo, E. L. & Husseneder, C. In Biology of termites: A modern synthesis (eds D.E. Bignell, Yves Roisin, & Nathan Lo) 133–164 (Springer, 2011).Shellman-Reeve, J. S. Dynamics of biparental care in the dampwood termite, Zootermopsis nevadensis (Hagen): response to nitrogen availability. Behav. Ecol. Sociobiol. 26, 389–397 (1990).Article 

    Google Scholar 
    Cole, E. L., Ilieş, I. & Rosengaus, R. B. Competing physiological demands during incipient colony foundation in a social insect: consequences of pathogenic stress. Front. Ecol. Evol. 6 (2018).Traniello, J. F. A., Rosengaus, R. B. & Savoie, K. The development of immunity in a social insect: evidence for the group facilitation of disease resistance. Proc. Natl Acad. Sci. 99, 6838–6842 (2002).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Cremer, S., Armitage, S. A. O. & Schmid-Hempel, P. Social immunity. Curr. Biol. 17, R693–R702 (2007).CAS 
    Article 
    PubMed 

    Google Scholar 
    Rosengaus, R. B., Traniello, J. F. A. & Bulmer, M. In biology of termites: a modern synthesis (eds D. E. Bignell, Yves Roisin & Nathan Lo) 165–191 (Springer, 2011).Cole, E. L., Bayne, H. & Rosengaus, R. B. Young but not defenceless: antifungal activity during embryonic development of a social insect. R. Soc. Open Sci. 7, 191418–191418 (2020).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rosengaus, R. B. & Traniello, J. F. Disease susceptibility and the adaptive nature of colony demography in the dampwood termite Zootermopsis angusticollis. Behav. Ecol. Sociobiol. 50, 546–556 (2001).Article 

    Google Scholar 
    Cole, E. L. & Rosengaus, R. B. Pathogenic dynamics during colony ontogeny reinforce potential drivers of termite eusociality: mate assistance and biparental care. Front. Ecol. Evol. 7 (2019).Chouvenc, T. The relative importance of queen and king initial weights in termite colony foundation success. Insectes Sociaux 66, 177–184 (2019).Article 

    Google Scholar 
    Matsuura, K. & Kobayashi, N. Termite queens adjust egg size according to colony development. Behav. Ecol. 21, 1018–1023 (2010).Article 

    Google Scholar 
    Calleri, D. V., McGrail Reid, E., Rosengaus, R. B., Vargo, E. L. & Traniello, J. F. A. Inbreeding and disease resistance in a social insect: effects of heterozygosity on immunocompetence in the termite Zootermopsis angusticollis. Proc. R. Soc. B: Biol. Sci. 273, 2633–2640 (2006).Article 

    Google Scholar 
    DeHeer, C. J. & Vargo, E. L. An indirect test of inbreeding depression in the termites Reticulitermes flavipes and Reticulitermes virginicus. Behav. Ecol. Sociobiol. 59, 753–761 (2006).Article 

    Google Scholar 
    Aguero, C. M., Eyer, P.-A., Martin, J. S., Bulmer, M. S. & Vargo, E. L. Natural variation in colony inbreeding does not influence susceptibility to a fungal pathogen in a termite. Ecol. Evol. 11, 3072–3083 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Aguero, C., Eyer, P. A. & Vargo, E. L. Increased genetic diversity from colony merging in termites does not improve survival against a fungal pathogen. Sci. Rep. 10, 4212 (2020).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rosengaus, R. B. & Traniello, J. F. Disease risk as a cost of outbreeding in the termite Zootermopsis angusticollis. Proc. Natl Acad. Sci. 90, 6641–6645 (1993).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Eyer, P.-A. et al. Extensive human-mediated jump dispersal within and across the native and introduced ranges of the invasive termite Reticulitermes flavipes. Mol. Ecol. 30, 3948–3964 (2021).Article 
    PubMed 

    Google Scholar 
    Perdereau, E. et al. Global genetic analysis reveals the putative native source of the invasive termite, Reticulitermes flavipes, in France. Mol. Ecol. 22, 1105–1119 (2013).CAS 
    Article 
    PubMed 

    Google Scholar 
    Sinotte, V. M. et al. Female-biased sex allocation and lack of inbreeding avoidance in Cubitermes termites. Ecol. Evolution 11, 5598–5605 (2021).Article 

    Google Scholar 
    Li, G., Gao, Y., Sun, P., Lei, C. & Huang, Q. Factors affecting mate choice in the subterranean termite Reticulitermes chinensis (Isoptera: Rhinotermitidae). J. Ethol. 31, 159–164 (2013).Article 

    Google Scholar 
    Aguilera-Olivares, D., Flores-Prado, L., Véliz, D. & Niemeyer, H. Mechanisms of inbreeding avoidance in the one-piece drywood termite Neotermes chilensis. Insectes Sociaux 62, 237–245 (2015).Article 

    Google Scholar 
    Miyaguni, Y., Agarie, A., Sugio, K., Tsuji, K. & Kobayashi, K. Caste development and sex ratio of the Ryukyu drywood termite Neotermes sugioi and its potential mechanisms. Sci. Rep. 11, 15037 (2021).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Nutting, W. L. In Biology of Termites (eds Kumar Krishna & Frances M. Weesner) 233–282 (Academic Press, 1969).Fougeyrollas, R. et al. Dispersal and mating strategies in two neotropical soil-feeding termites, Embiratermes neotenicus and Silvestritermes minutus (Termitidae, Syntermitinae). Insectes Sociaux 65, 251–262 (2018).Article 

    Google Scholar 
    Shellman-Reeve, J. S. Genetic relatedness and partner preference in a monogamous, wood-dwelling termite. Anim. Behav. 61, 869–876 (2001).Article 

    Google Scholar 
    Zhang, Z.-Y. et al. Biochemical, molecular, and morphological variations of flight muscles before and after dispersal flight in a eusocial termite, Reticulitermes chinensis. Insect Sci. 28, 77–92 (2021).CAS 
    Article 
    PubMed 

    Google Scholar 
    Mullins, A. J. et al. Dispersal flights of the Formosan subterranean termite (Isoptera: Rhinotermitidae). J. Econ. Entomol. 108, 707–719 (2015).Article 
    PubMed 

    Google Scholar 
    Goodisman, M. A. D. & Crozier, R. H. Population and colony genetic structure of the primitive termite Mastotermes Darwiniensis. Evolution 56, 70–83 (2002).Article 
    PubMed 

    Google Scholar 
    Schmidt, A. M., Jacklyn, P. & Korb, J. Isolated in an ocean of grass: low levels of gene flow between termite subpopulations. Mol. Ecol. 22, 2096–2105 (2013).Article 
    PubMed 

    Google Scholar 
    Thompson, G. J., Lenz, M., Crozier, R. H. & Crespi, B. J. Molecular-genetic analyses of dispersal and breeding behaviour in the Australian termite Coptotermes lacteus: evidence for non-random mating in a swarm-dispersal mating system. Aust. J. Zool. 55, 219–227 (2007).CAS 
    Article 

    Google Scholar 
    Vargo, E. L. Diversity of termite breeding systems. Insects 10, 52 (2019).Article 
    PubMed Central 

    Google Scholar 
    Tranter, C., LeFevre, L., Evison, S. E. F. & Hughes, W. O. H. Threat detection: contextual recognition and response to parasites by ants. Behav. Ecol. 26, 396–405 (2014).Article 

    Google Scholar 
    Hussain, A., Tian, M.-Y., He, Y.-R., Bland, J. M. & Gu, W.-X. Behavioral and electrophysiological responses of Coptotermes formosanus Shiraki towards entomopathogenic fungal volatiles. Biol. Control 55, 166–173 (2010).Article 

    Google Scholar 
    Yanagawa, A., Imai, T., Akino, T., Toh, Y. & Yoshimura, T. Olfactory cues from pathogenic fungus affect the direction of motion of termites, Coptotermes formosanus. J. Chem. Ecol. 41, 1118–1126 (2015).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rosengaus, R. B., James, L.-T., Hartke, T. R. & Brent, C. S. Mate preference and disease risk in Zootermopsis angusticollis (Isoptera: Termopsidae). Environ. Entomol. 40, 1554–1565 (2011).Article 
    PubMed 

    Google Scholar 
    Beani, L. et al. Cuticular hydrocarbons as cues of sex and health condition in Polistes dominula wasps. Insectes Sociaux 66, 543–553 (2019).Article 

    Google Scholar 
    Waser, P. M., Austad, S. N. & Keane, B. When should animals tolerate inbreeding? Am. Nat. 128, 529–537 (1986).Article 

    Google Scholar 
    Bengtsson, B. O. Avoiding inbreeding: at what cost? J. Theor. Biol. 73, 439–444 (1978).CAS 
    Article 
    PubMed 

    Google Scholar 
    Lehmann, L. & Perrin, N. Inbreeding avoidance through kin recognition: Choosy females boost male dispersal. Am. Nat. 162, 638–652 (2003).Article 
    PubMed 

    Google Scholar 
    Basalingappa, S. Environmental hazards to reproductives of Odontotermes assmuthi Holgrem. Indian Zool. 1, 45–50 (1970).
    Google Scholar 
    Darlington, J., Sands, W. & Pomeroy, D. Distribution and post-settlement survival in the field by reproductive pairs of Hodotermes mossambicus hagen (isoptera, hodotermitida). Insectes Sociaux 24, 353–358 (1977).Article 

    Google Scholar 
    Dial, K. P. & Vaughan, T. A. Opportunistic predation on alate termites in Kenya. Biotropica 19, 185–187 (1987).Article 

    Google Scholar 
    Korb, J. & Salewski, V. Predation on swarming termites by birds. Afr. J. Ecol. 38, 173–174 (2000).Article 

    Google Scholar 
    Schwenke, R. A., Lazzaro, B. P. & Wolfner, M. F. ReproduCtion–immunity Trade-offs In Insects. Annu. Rev. Entomol. 61, 239–256 (2016).CAS 
    Article 
    PubMed 

    Google Scholar 
    Calleri, D. II, Rosengaus, R. & Traniello, J. A. Disease and colony foundation in the dampwood termite Zootermopsis angusticollis: The survival advantage of nestmate pairs. Naturwissenschaften 92, 300–304 (2005).CAS 
    Article 
    PubMed 

    Google Scholar 
    Fei, H. X. & Henderson, G. Comparative study of incipient colony development in the Formosan subterranean termite, Coptotermes formosanus Shiraki (Isoptera,Rhinotermitidae). Insectes Sociaux 50, 226–233 (2003).Article 

    Google Scholar 
    Rosengaus, R. B., Cornelisse, T., Guschanski, K. & Traniello, J. F. A. Inducible immune proteins in the dampwood termite Zootermopsis angusticollis. Naturwissenschaften 94, 25–33 (2007).CAS 
    Article 
    PubMed 

    Google Scholar 
    Rosengaus, R. B., Traniello, J. F. A., Chen, T., Brown, J. J. & Karp, R. D. Immunity in a social insect. Naturwissenschaften 86, 588–591 (1999).CAS 
    Article 

    Google Scholar 
    Sun, Q., Haynes, K. F., Hampton, J. D. & Zhou, X. Sex-specific inhibition and stimulation of worker-reproductive transition in a termite. Sci. Nat. 104, 79 (2017).Article 
    CAS 

    Google Scholar 
    Eyer, P.-A. et al. Inbreeding tolerance as a pre-adapted trait for invasion success in the invasive ant Brachyponera chinensis. Mol. Ecol. 27, 4711–4724 (2018).PubMed 

    Google Scholar 
    Barrett, S. C. H. & Charlesworth, D. Effects of a change in the level of inbreeding on the genetic load. Nature 352, 522 (1991).CAS 
    Article 
    PubMed 

    Google Scholar 
    Crnokrak, P. & Spencer, C. H. B. Perspective: purging the genetic load. A review of the experimental evidence. Evolution 56, 2347–2358 (2002).Article 
    PubMed 

    Google Scholar 
    Day, S. B., Bryant, E. H. & Meffert, L. M. The influence of variable rates of inbreeding on fitness, environmental responsiveness, and evolutionary potential. Evolution 57, 1314–1324 (2003).Article 
    PubMed 

    Google Scholar 
    Syren, R. M. & Luykx, P. Permanent segmental interchange complex in the termite Incisitermes schwarzi. Nature 266, 167–168 (1977).CAS 
    Article 
    PubMed 

    Google Scholar 
    Fontana, F. Multiple reciprocal chromosomal translocations and their role in the evolution of sociality in termites. Ethol. Ecol. Evolution 3, 15–19 (1991).CAS 
    Article 

    Google Scholar 
    Matsuura, K. A test of the haplodiploid analogy hypothesis in the termite Reticulitermes speratus (Isoptera: Rhinotermitidae). Ann. Entomol. Soc. Am. 95, 646–649 (2002).Article 

    Google Scholar 
    Yashiro, T. et al. Enhanced heterozygosity from male meiotic chromosome chains is superseded by hybrid female asexuality in termites. Proc. Natl. Acad. Sci. 118, e2009533118 (2021).Charlesworth, B. & Wall, J. D. Inbreeding, heterozygote advantage and the evolution of neo-X and neo-Y sex chromosomes. Proc. R. Soc. Lond. Ser. B: Biol. Sci. 266, 51–56 (1999).Article 

    Google Scholar 
    Hellemans, S. et al. Widespread occurrence of asexual reproduction in higher termites of the Termes group (Termitidae: Termitinae). BMC Evol. Biol. 19, 131 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Vargo, E. L., Labadie, P. E. & Matsuura, K. Asexual queen succession in the subterranean termite Reticulitermes virginicus. Proc. R. Soc. B: Biol. Sci. 279, 813–819 (2012).Article 

    Google Scholar 
    Matsuura, K. et al. Queen succession through asexual reproduction in termites. Science 323, 1687–1687 (2009).CAS 
    Article 
    PubMed 

    Google Scholar 
    Cremer, S., Pull, C. D. & Fürst, M. A. Social immunity: emergence and evolution of colony-level disease protection. Annu. Rev. Entomol. 63, 105–123 (2018).CAS 
    Article 
    PubMed 

    Google Scholar 
    Van Meyel, S., Körner, M. & Meunier, J. Social immunity: why we should study its nature, evolution and functions across all social systems. Curr. Opin. Insect Sci. 28, 1–7 (2018).Article 
    PubMed 

    Google Scholar 
    Cotter, S. C. & Kilner, R. M. Personal immunity versus social immunity. Behav. Ecol. 21, 663–668 (2010).Article 

    Google Scholar 
    Liu, L., Zhao, X.-Y., Tang, Q.-B., Lei, C.-L. & Huang, Q.-Y. The mechanisms of social immunity against fungal infections in eusocial insects. Toxins 11, 244 (2019).CAS 
    Article 
    PubMed Central 

    Google Scholar 
    Chouvenc, T. & Su, N. Y. When subterranean termites challenge the rules of fungal epizootics. Plos One 7, e34484 (2012).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Davis, H. E., Meconcelli, S., Radek, R. & McMahon, D. P. Termites shape their collective behavioural response based on stage of infection. Sci. Rep. 8, 14433–14433 (2018).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Cassidy, S. T. et al. Disease defences across levels of biological organization: individual and social immunity in acorn ants. Anim. Behav. 179, 73–81 (2021).Article 

    Google Scholar 
    López-Uribe, M. M., Sconiers, W. B., Frank, S. D., Dunn, R. R. & Tarpy, D. R. Reduced cellular immune response in social insect lineages. Biol. Lett. 12, 20150984 (2016).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    He, S. et al. Evidence for reduced immune gene diversity and activity during the evolution of termites. Proc. R. Soc. B: Biol. Sci. 288, 20203168 (2021).Article 

    Google Scholar 
    Viljakainen, L. et al. Rapid evolution of immune proteins in social insects. Mol. Biol. Evol. 26, 1791–1801 (2009).CAS 
    Article 
    PubMed 

    Google Scholar 
    Meusemann, K., Korb, J., Schughart, M. & Staubach, F. No evidence for single-copy immune-gene specific signals of selection in termites. Front. Ecol. Evol. 8 (2020).Otani, S., Bos, N. & Yek, S. H. Transitional complexity of social insect immunity. Front. Ecol. Evol. 4 (2016).Barribeau, S. M. et al. A depauperate immune repertoire precedes evolution of sociality in bees. Genome Biol. 16, 83 (2015).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    de Boer, R. A., Vega-Trejo, R., Kotrschal, A. & Fitzpatrick, J. L. Meta-analytic evidence that animals rarely avoid inbreeding. Nat. Ecol. Evol. 5, 949–964 (2021).Article 
    PubMed 

    Google Scholar 
    Szulkin, M., Stopher, K. V., Pemberton, J. M. & Reid, J. M. Inbreeding avoidance, tolerance, or preference in animals? Trends Ecol. Evol. 28, 205–211 (2013).Article 
    PubMed 

    Google Scholar 
    Fox, C. W. & Reed, D. H. Inbreeding depression increases with environmental stress: an experimental study and meta-analysis. Evol. 65, 246–258 (2011).Article 

    Google Scholar 
    Kokko, H., Ots, I. & Tregenza, T. When not to avoid inbreeding. Evolution 60, 467–475 (2006).Article 
    PubMed 

    Google Scholar 
    Zayed, A. & Packer, L. Complementary sex determination substantially increases extinction proneness of haplodiploid populations. Proc. Natl Acad. Sci. USA 102, 10742–10746 (2005).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ross, K. G. & Fletcher, D. J. C. Diploid male production — a significant colony mortality factor in the fire ant Solenopsis invicta (Hymenoptera: Formicidae). Behav. Ecol. Sociobiol. 19, 283–291 (1986).Article 

    Google Scholar 
    Eyer, P.-A., Salin, J., Helms, A. M. & Vargo, E. L. Distinct chemical blends produced by different reproductive castes in the subterranean termite Reticulitermes flavipes. Sci. Rep. 11, 4471 (2021).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kearse, M. et al. Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28, 1647–1649 (2012).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Queller, D. C. & Goodnight, K. F. Estimating relatedness using genetic markers. Evolution 43, 258–275 (1989).Article 
    PubMed 

    Google Scholar 
    Wang, J. Coancestry: a program for simulating, estimating and analysing relatedness and inbreeding coefficients. Mol. Ecol. Resour. 11, 141–145 (2011).Article 
    PubMed 

    Google Scholar 
    Jombart, T. adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics 24, 1403–1405 (2008).CAS 
    Article 
    PubMed 

    Google Scholar 
    Rosengaus, R. B., Moustakas, J. E., Calleri, D. V. & Traniello, J. F. A. Nesting ecology and cuticular microbial loads in dampwood (Zootermopsis angusticollis) and drywood termites (Incisitermes minor, I. schwarzi, Cryptotermes cavifrons). J. Insect Sci. 3, 31 (2003).Kozich, J. J., Westcott, S. L., Baxter, N. T., Highlander, S. K. & Schloss, P. D. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl. Environ. Microbiol. 79, 5112–5120 (2013).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    White, T. J., Burns, T., Lee, S. & Taylor, J. in PCR protocols: A guide to methods and applications (eds. M. A. Innis, D. H. Gelfand, J. J. Snisky, & T. J. White) 315–322 (Academic Press, 1990).Aguero, C. M., Eyer, P.-A., Crippen, T. L. & Vargo, E. L. Reduced environmental microbial diversity on the cuticle and in the galleries of a subterranean termite compared to surrounding soil. Microb. Ecol. 81, 1054–1063 (2021).CAS 
    Article 
    PubMed 

    Google Scholar 
    Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857 (2019).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hamady, M., Lozupone, C. & Knight, R. Fast UniFrac: facilitating high-throughput phylogenetic analyses of microbial communities including analysis of pyrosequencing and PhyloChip data. ISME J. 4, 17–27 (2010).CAS 
    Article 
    PubMed 

    Google Scholar 
    Therneau, T. & Grambsch, P. Modeling Survival Data: Extending the Cox Model (Springer, 2000).Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).Article 

    Google Scholar  More

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    Transversal criminality at sea

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    Global analysis of biosynthetic gene clusters reveals conserved and unique natural products in entomopathogenic nematode-symbiotic bacteria

    General experimental proceduresAll chemicals were purchased from Sigma-Aldrich, Acros Organics or Iris BIOTECH. Isotope-labelled chemicals were purchased from Cambridge Isotope Laboratories. Genomic DNA of selected Xenorhabdus and Photorhabdus strains was isolated using the Qiagen Gentra Puregene Yeast/Bact Kit. DNA polymerases (Taq, Phusion and Q5) and restriction enzymes were purchased from New England Biolabs or Thermo Fisher Scientific. DNA primers were purchased from Eurofins MWG Operon. PCR amplifications were carried out on thermocyclers (SensoQuest). Polymerases were used according to the manufacturers’ instructions. DNA purification was performed from 1% Tris-acetate-EDTA (TAE) agarose gel using an Invisorb Spin DNA Extraction Kit (STRATEC Biomedical AG). Plasmids in E. coli were isolated by alkaline lysis. HPLC-UV-MS analysis was conducted on an UltiMate 3000 system (Thermo Fisher) coupled to an AmaZonX mass spectrometer (Bruker) with an ACQUITY UPLC BEH C18 column (130 Å, 2.1 mm × 100 mm, 1.7-μm particle size, Waters) at a flow rate of 0.6 ml min−1 (5–95% acetonitrile/water with 0.1% formic acid, vol/vol, 16 min, UV detection wavelength 190–800 nm). HPLC-UV-HRMS analysis was conducted on an UltiMate 3000 system (Thermo Fisher) coupled to an Impact II qTof mass spectrometer (Bruker) with an ACQUITY UPLC BEH C18 column (130 Å, 2.1 mm × 100 mm, 1.7-μm particle size, Waters) at a flow rate of 0.4 ml min−1 (5–95% acetonitrile/water with 0.1% formic acid, vol/vol, 16 min, UV detection wavelength 190–800 nm). Flash purification was performed on a Biotage SP1 flash purification system (Biotage) by a C18 main column (Interchim, PF50C18HP-F0080, 120 g) with a self-packed pre-column (Interchim, PF-DLE-F0012, Puriflash dry-load empty F0012 Flash column) coupled with a UV detector. HPLC purification was performed on preparative and semipreparative Agilent 1260 systems coupled to a diode array detector (DAD) and a single quadrupole detector with a C18 ZORBAX Eclipse XDB column (9.4 mm × 250 mm, 5 μm, 3 ml min−1; 21.2 mm × 250 mm, 5 μm, 20 ml min−1; 50 mm × 250 mm, 10 μm, 40 ml min−1). Freeze drying was performed using a BUCHI Lyovapor L-300 Continuous system. NMR experiments were carried out on a Bruker AVANCE 500-, 600- or 700-MHz spectrometer equipped with a 5-mm cryoprobe. 2R,3S-IOC (1) and GameXPeptide A (16) were synthesized by WuXi App Tec following the literature (ref. 73 for 2R,3S-1 and ref. 74 for 16).Genome sequencing, assembly and annotationIsolated DNA was sequenced on the Illumina NextSeq 500 platform. DNA libraries were constructed using the Nextera XT DNA preparation kit (Illumina) and whole-genome sequencing was performed using 2× 150-bp paired-end chemistry. A sequencing depth of >50× was targeted for each sample. Adapters and low-quality ends were trimmed with Trimmomatic 0.39 (ref. 75) and the parameters [2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:10 MINLEN:12] using a database of adapter sequences as provided by Illumina. All genomes were assembled using SPAdes v. 3.10.1 (ref. 76) executed with the following parameters: –cov-cutoff auto –careful in paired-end mode plus mate pairs (in cases where accompanying mate-pair libraries were available). Genome annotation was performed using Prokka v. 1.12 (ref. 77) with the following parameters: –usegenus–genus GENUS–addgenes–evalue 0.0001–rfam–kingdom Bacteria–gcode 11–gram –mincontiglen 200. Geneious Prime 2021 was used in genome visualization and analysis.antiSMASH annotations and BiG-FAM preliminary classificationThe antiSMASH 5.0 (ref. 23) web server was employed to mine all the genome sequences for the presence of putative natural-product BGCs. The annotations were conducted using default settings with the extended parameters of ClusterBlast, Cluster Pfam analysis and Pfam-based GO term annotation. The annotated BGCs were summarized for each strain (Supplementary Fig. 1) and visualized in the anvi’o 6.1 (refs. 28,78) layers (Fig. 1 and Supplementary Figs. 3 and 5). We then submitted the antiSMASH job IDs to the biosynthetic gene cluster families database (BiG-FAM 1.0.0)25 for preliminary GCF explorations and classifications of annotated BGCs (Supplementary Table 3), followed by BiG-SCAPE 1.0.0 (ref. 42) refinement with a cutoff of 0.65 (Source Data Fig. 3). The GCFs were double-checked manually via the interactive network (Fig. 3), and corrections were made if necessary. A putative thiopeptide BGC (Xszus_1.region006, Xsze_2.region003, Xsto_4.region001, Xpb_30.3_21.region001, Xmir_10.region001, Xmau_6.region001, Xkoz_3.region001, Xjap_NZ_FOVO01000011.region001, Xish_1.region003, Xhom_ANU1.region005, Xhom_2.region003, Xets_11.region001, XenKK7.region002, XenDL20_c00108_NODE_12.region001, Xekj_19.region001, Xehl_28.region001, Xe30TX1_c0031_NODE_38.region001, Xdo_HBLC131_1.region001, Xdo_FRM16.1.region005, Xbov_NC_013892.1.region004, Ptem_HBLC135_17.region001, Ppb6_4.region001, Plum_TT01_1.region008, Pthr_PT1.1_23.region001, Plau_IT4.1_12.region001, Plum_IL9_35_scf0001.region001, Pbod_HU2.3_20.region001, Plau_HB1.3_105.region001, Plum_EN01_24_scf0009.region001, Pbod_DE6.1_24.region001, Plau_DE2.2_108.region001, Phpb_1.region001, Pbod_LJ_007.region001, Pbod_CN4_25_scf0020.region001, Paeg_BKT4.5_19.region001, P_tem_1.region017 and so on) that exists throughout 45 XP genomes was excluded in the analysis, because it turned out that its annotation by antiSMASH 5.0 is a false positive and early reports suggest that this cluster is responsible for ribosomal methylthiolation79,80. Two BGCs, Xdo_HBLC131_4.region001 encoding the biosynthesis of glidobactins in X. doucetiae HBLC131 and Ptem_HBLC135_2.region002 encoding the biosynthesis of ririwpeptides in P. temperata HBLC135, were artificially integrated into their respective genome by CRAGE39 previously, and thus the two BGCs were also excluded in our analysis.Pangenome analysisBiosynthetic gene cluster boundary definitionThe cluster boundary was defined by antiSMASH with the start nucleotide of the first biosynthetic gene (5′ end) and the stop nucleotide of the last biosynthetic gene (3′ end), and was manually corrected if necessary. Non-structural genes (such as transporters, regulators, transposases and so on) on the outer periphery of an operon were excluded. We compiled a table with contigs of all BGCs encoded by a given genome, BGC start and stop nucleotide positions, BGC classifications by antiSMASH and BiG-SCAPE (see the BiG-SCAPE analysis section), and possible biosynthetic pathways that the BGCs encode (Source Data Fig. 1). These tables would be integrated into the contigs databases of the pangenome for filtering the biosynthetic genes and monitoring distributions of biosynthetic gene homology groups.Interface generationAll genomes were obtained from the National Center for Biotechnology Information (NCBI). Supplementary Table 1 reports their accession numbers. The pangenome analysis herein mainly followed the anvi’o 6.1 pangenomic workflow28,78. After simplifying the header lines of 45 FASTA files for genomes using ‘anvi-script-reformat-fasta’, we converted FASTA files into anvi’o contigs databases by the ‘anvi-gen-contigs-database’ and then decorated the contigs database with hits from HMM models by ‘anvi-run-hmms’. The program ‘anvi-run-ncbi-cogs’ was run to annotate genes in the contigs databases with functions from the NCBI’s Clusters of Orthologous Groups (COGs). Tables of gene caller IDs with start and stop nucleotide positions were exported by ‘anvi-export-table’. By linking the gene caller IDs with BGCs via the start and stop nucleotide positions, genes that fell within a given BGC boundary were considered to be natural product biosynthetic genes (Source Data Fig. 1). Thereafter, the biosynthetic genes were furnished with a classification and a possible compound name, both of which were derived from the BGC that the biosynthetic genes made up. The obtained tables were imported back to contigs databases by ‘anvi-import-functions’. External genome storage was created by ‘anvi-gen-genomes-storage’ to store DNA and amino-acid sequences, as well as functional annotations of each gene. With the genome storage in hand, we used the program ‘anvi-pan-genome’ with the genomes storage database, the flag ‘–use-ncbi-blast’ and the parameter ‘–mcl-inflation 8’. The results were displayed in an interface by ‘anvi-display-pan’. The organization of the pangenome interface as shown in the dendrogram in the centre was represented by ‘presence/absence’ patterns. The core gene bin was characterized by searching the gene homology group (gene homology group represents amino-acid sequences from one or more genomes aligned by muscle81) using filters with ‘Min number of genomes gene homology group occurs, value = 45’. The singleton bin was identified by ‘Max number of genomes gene homology group occurs, value = 1’. The rest of the gene clusters that were neither sorted into the core gene bin nor the singleton bin were appended to the accessory bin. The single-copy-core-gene (scg) bin was found by ‘Min number of genomes gene homology group occurs, value = 45’ and ‘Max number of genes from each genome, value = 1’. The scg bin was refined by ‘Max functional homogeneity index 0.9’ and ‘Min geometric homogeneity index 1’. The resulting protein sequences were exported by ‘anvi-get-sequences-for-gene-clusters’ and aligned using ClustalW 1.2.2, which is incorporated in Geneious Prime 2021. Phylogenetic trees were generated using the Geneious tree builder utilizing the Jukes–Cantor distance model and the unweighted pair group method with arithmetic mean (UPGMA), and subsequently imported back to anvi’o by ‘anvi-import-misc-data’ and visualized by the interface. The statistical data of BGCs obtained from antiSMASH 5.0 (ref. 23) and BiG-SCAPE42 were imported to the layers of the interface by ‘anvi-import-misc-data’ for visualization.Biosynthetic gene and biosynthetic gene cluster filteringThe bin summary (scg, core, accessory and singleton) with BGC classifications was exported by ‘anvi-summarize’ to monitor the distributions of the biosynthetic gene homology group in the pangenomes (Source Data Fig. 1 and Supplementary Data). In the Excel sheets, ‘core’ and ‘scg’ filters were selected from the ‘bin_name’ column, and the ‘(Blank)’ filter from the ‘BGC_classification’ column was unselected. The table was then sorted by ‘genome_name’ and ‘gene_callers_id’ columns in ascending order. This then displayed consecutive core biosynthetic genes that could possibly make up a BGC. The same procedure was used to filter BGCs in the accessory or singleton region.BiG-SCAPE analysisBGCs in all genome sequences obtained from antiSMASH 5.0 (ref. 23) analyses were compared to reference BGCs from MIBiG repository 2.0 (refs. 41,82) using BiG-SCAPE 1.0.0 (ref. 42) with the PFAM database 32.0 (ref. 83). The analysis was conducted using default settings with the mode ‘auto’, mixing all classes and retaining singletons. Networks were computed for raw distance cutoffs of 0.30–0.95 in increments of 0.05. Results were visualized as a network using Cytoscape 3.7.2 (ref. 84) for a cutoff of 0.65 (Fig. 3 and Source Data Fig. 3). Statistical data for the BGCs were analysed and evaluated using Origin 2020b and Excel from Microsoft Office 365.Strain and culture conditionsWild-type strains and the mutants thereof and E. coli (Supplementary Table 14) were cultivated on lysogeny broth (LB) agar plates at 30 °C overnight, and subsequently inoculated into liquid LB culture at 30 °C with shaking at 200 r.p.m. For compound production, the overnight LB culture was transferred into 5 ml of LB, XPP19 or Sf-900 II SFM medium (1:100, vol/vol) with 2% (vol/vol) Amberlite XAD-16 resins, 0.1% l-arabinose as the inducer for mutants with a PBAD promoter, and selective antibiotics such as ampicillin (Am, 100 µg ml−1), kanamycin (Km, 50 µg ml−1) or chloramphenicol (Cm, 34 µg ml−1) at 30 °C, with shaking at 200 r.p.m.Culture extraction and HPLC-UV-MS analysisThe XAD-16 resins were collected after 72 h and extracted with 5 ml of methanol or ethyl acetate. The solvent was dried under rotary evaporators, and the dried extract was resuspended in 500 μl of methanol or acetonitrile/water (1:1 vol/vol for photoxenobactins), of which 5 μl was injected and analysed by HPLC-UV-MS or HPLC-UV-HRMS. Unless otherwise specified, HPLC-UV-MS and HPLC-UV-HRMS chromatograms in the figures are shown on the same scale. Bruker Compass DataAnalysis 4.3 was used for data collection and analysis of chromatography and MS. MetabolicDetec 2.1 was utilized to differentiate MS profiles between induced and non-induced promoter insertion mutants for identifying possible metabolites produced by targeted BGCs.Construction of PBAD promoter insertion mutantsA 500–800-bp section upstream of the target gene (lpcS, pxbF, rdb1A and xvbA) was amplified with a corresponding primer pair as listed in Supplementary Table 15. The resulting fragments were cloned using Hot Fusion85 into a pCEP_kan or pCEP_cm backbone that was amplified by pCEP_Fw and pCEP_Rv. After transformation of a constructed plasmid into E. coli S17-1 λ pir, clones were verified by PCR with primers pCEP-Ve-Fw and pDS132-Ve-Rv. A wild-type strain (X. bovienii SS-2004, X. szentirmaii DSM 16338, X. budapestensis DSM 16342 or X. vietnamensis DSM 22392) or a deletion mutant (X. szentirmaii ∆hfq, X. budapestensis ∆rdb1P or X. budapestensis ∆rdb1P ∆hfq) was used as a recipient strain. The recipient strain was mated with E. coli S17-1 λ pir (donor) carrying a constructed plasmid (Supplementary Table 16). Both strains were grown in the LB medium to an optical density at 600 nm (OD600) of 0.6 to 0.7, and the cells were washed once with fresh LB medium. Subsequently, the donor and recipient strains were mixed on an LB agar plate in ratios of 1:3 and 3:1, and incubated at 37 °C for 3 h followed by incubation at 30 °C for 21 h. After that, the bacterial cell layer was collected with an inoculating loop and resuspended in 2 ml of fresh LB medium. A 200-μl sample of the resuspended culture was spread out on an LB agar plate with Am/Km or Am/Cm and incubated at 30 °C for two days. Individual insertion clones were cultivated and analysed by HPLC-UV-HRMS, and the genotype of all mutants was verified by plasmid- and genome-specific primers.Construction of deletion mutantsA ~1,000-bp upstream and a ~1,000-bp downstream fragment of hfq in X. budapestensis DSM 16342 were amplified using the primer pairs listed in Supplementary Table 15. The amplified fragments were fused using the complementary overhangs introduced by primers and cloned into the pEB17 vector that was linearized with PstI and BglII by Hot Fusion85. Transformation of E. coli S17-1 λ pir with the resulting plasmid (Supplementary Table 16) and conjugation with X. budapestensis DSM 16342, as well as the generation of double crossover mutants via counterselection on LB plates containing 6% sucrose, were carried out as previously described86. The deletion mutant was verified via PCR using the primer pairs listed in Supplementary Table 15, which yielded a ~2,000-bp fragment for mutants genetically equal to the WT strain and a ~1,000-bp fragment for the desired deletion mutant. The same procedure was used to generate Δrdb1P mutants, during which E. coli S17-1 λ pir carrying pEB17 rdb1P was mated with the X. budapestensis DSM 16342 wild-type and X. budapestensis ∆hfq mutant.Labelling experiments for structural elucidation of photoxenobactins C and D by MSThe cultivation of strains for labelling experiments was carried out as described above. For photoxenobactin C (6) labelling experiments, the overnight culture was transferred into LB medium additionally fed with 4-fluorosalicylate-SNAC, l-methionine-(methyl-d3), l-[U-13C,15N]cysteine and l-[U-34S]cysteine at a final concentration of 1 mM. In terms of inverse feeding experiments, cell pellets of the 100-μl overnight culture were washed once with ISOGRO 13C or 13C,15N medium (100 μl) and resuspended in the corresponding isotope labelling medium (100 μl). The feeding culture in the isotope labelling medium (5 ml) was inoculated with a washed overnight culture (50 μl) and additional l-cysteine was added at a final concentration of 1 mM.For photoxenobactin D (7) labelling experiments, the cell pellets of the 100-μl overnight culture were washed once with ISOGRO 13C or 15N medium (100 μl) and then resuspended in the corresponding isotope labelling medium (100 μl). A 5-ml isotope labelling medium was inoculated with a washed overnight culture (50 μl).Isolation and purificationFor photoxenobactin isolation, 10 ml of LB medium was inoculated with a colony of the X. szentirmaii PBAD pxbF ∆hfq mutant from an LB agar plate and cultivated overnight. A 10-ml culture was taken to inoculate 2 × 100 ml of LB medium (OD600 ≈ 0.1). The 2 × 100-ml cultures were incubated overnight and the whole culture volume (200 ml) was used to inoculate a 20-l LB fermenter (Braun) supplemented with 2% XAD-16 and 0.2% arabinose (antifoam was added when required). Fermenter settings were as follows: 30 °C without pH control, three six-blade impellers 150 r.p.m. After 24 h, 10 l of the culture was collected from the fermenter, and the XAD resins were separated from the cells by filtration. (1) The XAD resins were extracted with 2 × 1 l of ethyl acetate with 1% formic acid, and the combined organic phase was dried under reduced pressure. (2) The culture without XAD was centrifuged and the supernatant was extracted with 3 × 5 l of ethyl acetate with 1% formic acid, and the combined organic layers were dried under reduced pressure. (3) The cell pellet was extracted with 2 × 1 l of ethyl acetate with 1% formic acid, and the organic supernatant was dried under reduced pressure. After 48 h, the remaining 10 l of bacterial culture were extracted as described in steps (1) to (3). The combined extracts from 20 l of culture were fractionated by a flash purification system with a C18 column with a gradient elution of acetonitrile/water 20–100% at 20 ml min−1 (every 10% gradient step was performed with five column volumes, except the 60–70% step, which was performed with ten column volumes). Fractions containing photoxenobactins were combined and dried under reduced pressure. Final purification was achieved via preparative and semipreparative HPLCs with a gradient of 30% acetonitrile/water (0–30 min) and 30–100% acetonitrile/water (30–40 min). The fractions were combined in brown flasks and were immediately freeze-dried to afford photoxenobactin A (4, 0.8 mg), photoxenobactin B (5, 0.6 mg), photoxenobactin C (6, 1.2 mg) and photoxenobactin E (8, 2.2 mg).For the isolation and purification of lipocitides A and B, 2% of XAD-16 resins from a 6-l LB culture of the X. bovienii PBAD lpcS mutant induced by l-arabinose were collected after 72 h of incubation at 30 °C with shaking at 120 r.p.m., and were washed with water and extracted with methanol (3 × 1 l) to yield a crude extract (5.3 g after evaporation). The extract was dissolved in methanol and was subjected to preparative HPLC with a C18 column using an acetonitrile/water gradient (0.1% formic acid) for 0–32 min, 55–80%, 40 ml min−1 to afford lipocitides A (17, 4.8 mg) and B (18, 9.0 mg).Two percent of XAD-16 resins from a 12-l LB culture of the X. budapestensis PBAD rdb1A ∆rdb1P ∆hfq mutant induced by l-arabinose were collected after 72 h of incubation at 30 °C with shaking at 120 r.p.m. and washed with water and extracted with methanol (3 × 2 l) to yield a crude extract (15.3 g after evaporation). The extract was subject to a Sephadex LH-20 column eluted with methanol. The fraction (2.8 g) containing pre-rhabdobranins was subjected to preparative HPLC with a C18 column using an acetonitrile/water gradient (0.1% formic acid) for 0–20 min, 15–35%, 40 ml min−1 to afford a fraction (206 mg) mainly containing pre-rhabdobranin D, which was further purified by semipreparative HPLC with a C18 column using an acetonitrile/water gradient (0.1% formic acid) for 0–24 min, 5–53%, 3 ml min−1 to afford pre-rhabdobranin D (27, 59.1 mg).Benzobactin A (28) and its methyl ester (29), which were detected in X. vietnamensis PBAD xvbA, were also produced by Pseudomonas chlororaphis subsp. piscium DSM 21509 (unpublished). Owing to the high production level in Pseudomonas chlororaphis subsp. piscium DSM 21509, 28 and 29 were isolated from the Pseudomonas strain. Four percent of XAD-16 resins from a 12-l XPP culture of Pseudomonas chlororaphis subsp. piscium DSM 21509 PBAD pbzA mutant induced by l-arabinose were collected after 72 h of incubation at 30 °C with shaking at 120 r.p.m., and washed with water and extracted with methanol (3 × 2 l) to yield a crude extract (95.4 g after evaporation). The extract was dissolved in methanol and subjected to preparative HPLC with a C18 column using an acetonitrile/water gradient (0.1% formic acid) for 0–18 min, 5–59%, 20 ml min−1 to afford ten fractions. Fractions 2 (95.6 mg) and 3 (50.7 mg) were further purified by semipreparative HPLC with a C18 column using an acetonitrile/water gradient (0.1% formic acid) for 0–35 min, 5–95%, 3 ml min−1 to afford benzobactin A (28, 3.2 mg) and its methyl ester (29, 0.9 mg), respectively.NMR spectroscopyMeasurements were carried out using 1H and 13C NMR, 1H-13C heteronuclear single quantum coherence (HSQC), 1H-13C heteronuclear multiple bond correlation (HMBC), 1H-1H correlation spectroscopy (COSY), 1H-13C heteronuclear multiple quantum correlation/1H-1H correlation spectroscopy (HMQC-COSY) and 1H-13C heteronuclear single quantum coherence/1H-1H total correlation spectroscopy (HSQC-TOCSY). Chemical shifts (δ) were reported in parts per million (ppm) and referenced to the solvent signals. Data are reported as follows: chemical shift, multiplicity (br = broad, s = singlet, d = doublet, t = triplet, dd = doublet of doublet, m = multiplet and ov = overlapped) and coupling constants (in hertz). Bruker TopSpin 4.0 was used for NMR data collection and spectral interpretation.General synthetic proceduresThe Fmoc protecting group was removed with 2 ml of 40% piperidine/dimethylformamide (DMF; 5 min) followed by 2 ml of 20% piperidine/DMF (10 min). Washings between coupling and deprotection steps were performed with DMF (five syringe volumes) and dichloromethane (DCM) (five syringe volumes). Resin loadings were determined by Fmoc cleavage from a weighted resin sample87. The combined filtrates containing Fmoc cleavage products were quantified spectrophotometrically at 301 nm using a UV–vis spectrophotometer with Hellma absorption cuvettes with a path length of 1 cm. Loadings were calculated (in mmol resin) using Lambert–Beer’s law with ɛ = 7,800 M−1 cm−1: loading (mmol) = ({frac{{{rm{Abs}},{({rm{sample}})}}}{{varepsilon l}}} times V), where ɛ is the molar extinction coefficient, V is the sample volume in liter and l is the optical path length in cm. Final cleavage was achieved by shaking the resin in 2 ml of a mixture of TFA/TIPS/H2O (95:2.5:2.5) for 1 h. The filtrate was then collected and the resin washed three times (2 ml each) with DCM, and the combined filtrates were dried under reduced pressure.Syntheses of lipocitide AFmoc-protected Rink Amide resin (192 mg, 0.52 mmol g−1, 0.1 mmol) was placed in a polypropylene 6-ml syringe vessel fitted with polyethylene porous filter disks and swollen in 3 ml of DMF for 10 min. Subsequently, the Fmoc-protected resin was deprotected and then washed as described in the general synthetic procedures. Fmoc-d-Cit-OH (198.0 mg, 0.5 mmol, 5 equiv.), 1-hydroxy-7-azabenzotriazole (HOAT, 0.83 ml, 0.5 mmol, 5 equiv.), hexafluorophosphate azabenzotriazole tetramethyl uronium (HATU, 190.5 mg, 0.5 mmol, 5 equiv.) and N,N-diisopropylethylamine (DIPEA, 170 μl, 1.0 mmol, 10 equiv.) were dissolved in 1.5 ml of dry DMF. After 5 min, the clear solution was added to the resin and shaken at room temperature overnight. The resin was washed and loading was calculated (79.2%) as described in the general synthetic procedures. Acylation of Fmoc-l-Ala-OH (74.1 mg, 0.24 mmol, 3 equiv.), Fmoc-d-Leu-OH (84.8 mg, 0.24 mmol, 3 equiv.) and myristic acid (54.8 mg, 0.24 mmol, 3 equiv.) were carried out using the abovementioned procedure. Final cleavage was performed as described in the general synthetic procedures, and the crude product (70.8 mg) was purified by HPLC to obtain lipocitide A (17, Supplementary Fig. 100; 24.3 mg, 54.0%) as a white solid.Syntheses of lipocitide B2-CTC resin (63 mg, 1.6 mmol g−1, 0.1 mmol) was placed in a polypropylene 6-ml syringe vessel fitted with polyethylene porous filter disks. The resin was incubated with Fmoc-d-Cit-OH (119.0 mg, 0.3 mmol, 3 equiv.) and DIPEA (153 μl, 0.9 mmol, 9 equiv.) in 1.5 ml of dry DCM at room temperature overnight. The resin was washed and loading was calculated (56.7%) as described in the general synthetic procedures. Acylations of Fmoc-l-Ala-OH (52.9 mg, 0.17 mmol, 3 equiv.), Fmoc-d-Leu-OH (60.1 mg, 0.17 mmol, 3 equiv.) and myristic acid (38.9 mg, 0.24 mmol, 3 equiv.) were performed with additional HOAT (0.47 ml, 0.28 mmol, 5 equiv.), HATU (108 mg, 0.28 mmol, 5 equiv.) and DIPEA (96 μl, 0.56 mmol, 10 equiv.). Final cleavage was carried out as described in the general synthetic procedures, and the crude (54.2 mg) was purified by HPLC to obtain lipocitide B (18, Supplementary Fig. 101; 18.6 mg, 57.6%) as a white solid.Synthesis of S-(2-acetamidoethyl)4-fluoro-2-hydroxybenzothioate (4-fluorosalicylate SNAC)To a solution of 4-fluorosalicylic acid (156 mg, 1.0 mmol, 1.0 equiv.) and hydroxybenzotriazole (HOBt, 162 mg, 1.2 mmol, 1.2 equiv.) in 45 ml of THF, N,N′-dicyclohexylcarbodiimide (DCC, 248 mg, 1.2 mmol, 1.2 equiv.) was added, followed by N-acetylcysteamine (112 µl, 1.0 mmol, 1.0 equiv.). After 1 h at room temperature, K2CO3 (138 mg, 1.0 mmol, 1.2 equiv.) was added and the reaction was stirred for an additional 2 h. The reaction mixture was then filtered and concentrated by rotary evaporation. The solid residue was dissolved in ethyl acetate and washed with sat. NaHCO3 (50 ml) and water (50 ml). The organic layer was dried over MgSO4, concentrated, and purified by flash chromatography (1–10% MeOH in CHCl3) to give 26 mg (10%) S-(2-acetamidoethyl)4-fluoro-2-hydroxybenzothioate (Supplementary Fig. 102).IC50 value determination with the purified yeast 20S proteasome core particleYeast 20S proteasome core particle (yCP) from Saccharomyces cerevisiae was purified according to previously described methods88,89. The concentration of purified yCP was determined spectrophotometrically at 280 nm. yCP (final concentration: 0.05 mg ml−1 in 100 mM Tris-HCl, pH 7.5) was mixed with dimethyl sulfoxide (DMSO) as a control or serial dilutions of IOC (1) in DMSO, thereby not surpassing a final concentration of 10% (vol/vol) DMSO. After an incubation time of 45 min at room temperature, fluorogenic substrates Boc-Leu-Arg-Arg-AMC (AMC, 7-amino-4-methylcoumarin), Z-Leu-Leu-Glu-AMC and Suc-Leu-Leu-Val-Tyr-AMC (final concentration of 200 µM) were added to measure the residual activity of caspase-like (C-L, β1 subunit), trypsin-like (T-L, β2 subunit) and chymotrypsin-like (ChT-L, β5 subunit), respectively. The assay mixture was incubated for another 60 min at room temperature, then diluted 1:10 in 20 mM Tris-HCl, pH 7.5. The AMC molecules released by hydrolysis were measured in triplicate with a Varian Cary Eclipse fluorescence spectrophotometer (Agilent Technologies) at λexc = 360 nm and λem = 460 nm. Relative fluorescence units were normalized to the DMSO-treated control. The calculated residual activities were plotted against the logarithm of the applied inhibitor concentration and fitted with GraphPad Prism 9.0.2. IC50 values were deduced from the fitted data. These depend on enzyme concentration and are comparable within the same experimental settings.Crystallization and structure determination of the yCP in complex with IOC (1)Crystals of the yCP were grown in hanging drops at 20 °C, as previously described88,89. The protein concentration used for crystallization was 40 mg ml−1 in Tris/HCl (20 mM, pH 7.5) and EDTA (1 mM). The drops contained 1 μl of protein and 1 μl of the reservoir solution (30 mM magnesium acetate, 100 mM 2-(N-morpholino)ethanesulfonic acid (pH 6.7) and 10% (wt/vol) 2-methyl-2,4-pentanediol). Crystals appeared after two days and were incubated with 1 at a final concentration of 10 mM for at least 24 h. Droplets were then complemented with a cryoprotecting buffer (30% (wt/vol) 2-methyl-2,4-pentanediol, 15 mM magnesium acetate, 100 mM 2-(N-morpholino)ethanesulfonic acid, pH 6.9) and vitrified in liquid nitrogen. The dataset from the yCP:IOC complex was collected using synchrotron radiation (λ = 1.0 Å) at the X06SA-beamline (Swiss Light Source). X-ray intensities and data reduction were evaluated using the XDS program package version 5 February 2021 (Supplementary Table 17)90. Conventional crystallographic rigid body, positional and temperature factor refinements were carried out with REFMAC5 5.0.32 (ref. 91) and the CCP4 Program Suite 7.1.016 (ref. 92) using coordinates of the yCP structure as the starting model (PDB 5CZ4)50. Model building was performed by the programs SYBYL-X and COOT 0.8.7 (ref. 93). The final coordinates yielded excellent residual factors, as well as geometric bond and angle values. Coordinates were confirmed to fulfil the Ramachandran plot and have been deposited in the RCSB (PDB 7O2L).Haemocyte-spreading assaysSpodoptera exigua larvae were collected from Welsh onion (Allium fistulsum L.) fields in Andong, Korea. Insects were reared in the laboratory under the following conditions: 25 ± 2 °C constant temperature, 16:8 h (light/dark) photoperiod and 60 ± 5% relative humidity. Larvae were reared on an artificial diet94 and 10% sucrose solutions were fed to adult insects. Fifth instar larvae were used in all experiments. For analysing haemocyte behaviours in vivo, fifth instar larvae of S. exigua were co-injected with 1 µl of heat-killed (95 °C for 10 min) E. coli TOP10 (2.4 × 104 cells per larva) with the test compound (0–1,000 ng per larva) by using a Hamilton microsyringe (Reno). At 1 h post-injection, 10 µl of haemolymph from each larva was collected on the glass slide and incubated for 5 min inside a dark wet chamber at room temperature. The medium was replaced with 3.7% of formaldehyde dissolved in phosphate buffered saline (PBS) and incubated for 10 min. After washing three times with PBS, cells were permeabilized with 0.2% Triton X-100 in PBS for 2 min at room temperature. After incubation, the slides were washed with PBS three times. Blocking was performed using 5% skimmed milk (Invitrogen) dissolved in PBS, followed by incubation for 10 min. After washing once with PBS, the cells were incubated with fluorescein isothiocyanate (FITC)-tagged phalloidin in PBS for 1 h at room temperature. After washing three times, the cells were incubated with 4′,6-diamidino-2-phenylindole (DAPI, 1 mg ml−1, Thermo Scientific) in PBS for nucleus staining. Finally, after washing twice in PBS, cells were observed under a fluorescence microscope (DM2500, Leica) at ×400 magnification. Haemocyte spreading was determined by the extension of F-actin out of the original cell boundary. For the in vitro assay, ~100 μl of haemolymph was collected into 400 μl of anticoagulation buffer (ACB; 186 mM NaCl, 17 mM Na2EDTA, 41 mM citric acid, pH 4.5). After adding ACB, the medium was incubated for 30 min on ice. After centrifugation at 300g for 5 min, 400 μl of supernatant was discarded. The rest of the suspension was gently mixed with 200 μl of TC100 insect tissue culture medium (Welgene). From this suspension, 10 µl of haemolymph was collected on the glass slide. The slides were co-injected with 1 µl of E. coli TOP10 (2.4 × 104 cells per larva) with the test compound (0–1,000 ng per larva), followed by the procedure described above. Means were compared by a least squared difference (LSD) test of one-way analysis of variance (ANOVA) using POC GLM of the SAS program (SAS Institute, 1989) and discriminated at type I error = 0.05.Nodulation assaysE. coli TOP10 was heat-killed by incubating at 95 °C for 10 min. Fifth-instar larvae of S. exigua were injected with 1 µl of bacteria (2.4 × 104 cells per larva) using a Hamilton microsyringe along with 1 µl of different concentrations (10, 50, 100, 500 and 1,000 ppm) of inhibitors. Control larvae were injected with bacteria and DMSO. At 8 h after bacterial injection, nodules were counted by dissecting larvae under a stereomicroscope (Stemi SV 11, Zeiss) at ×50 magnification.Phenoloxidase activity assaysThe PO activity from plasma was estimated as previously described95. Briefly, DOPA (l-3,4-dihydroxyphenylalanine) was used as a substrate for determining PO activity from treated larvae plasma. For PO activation, each fifth-instar larva of S. exigua was challenged with 2.4 × 104 cells of heat-killed E. coli TOP10. Different inhibitors were co-injected (1 µg per larva) along with E. coli TOP10. After 8 h of bacterial challenge, haemolymph was collected from treated larvae in a 1.5-ml tube containing a few granules of phenylthiocarbamide (Sigma-Aldrich) to prevent melanization. Haemocytes were separated from plasma by centrifuging at 4 °C for 5 min at 300g. A reaction volume of 200 µl consisted of 180 µl of 10 mM DOPA in PBS (pH 7.4) and 20 µl of plasma. Absorbance was measured using a VICTOR multi-label plate reader (PerkinElmer) at 490 nm. PO activity was expressed as ΔABS per min per µl of plasma. Each treatment was replicated three times with independent samples.Measurement of nitric oxideThe NO was indirectly quantified by measuring its oxidized form, nitrate (NO3−), using the Griess reagent of a Nitrate/Nitrite Colorimetric Assay Kit (Cayman Chemical). Fifth-instar larvae were injected with 1 µl of heat-killed E. coli TOP10 (2.4 × 104 cells per larva) using a Hamilton microsyringe along with 1 µl of the test compound. Haemolymph was collected from each sample 1 h post infection. A 150-μl volume of haemolymph from three L5 larvae was collected and homogenized in 350 μl of 100 mM PBS pH 7.4 with a homogenizer (Ultra-Turrax T8, Ika Laboratory). After centrifugation at 14,000g for 20 min at 4 °C, the supernatant was used to measure the nitrate amounts, and the total protein was measured in each sample by a Bradford assay. The samples were analysed in a 200-μl final reaction volume. Briefly, 80 μl of samples were added to the wells, then 10 μl of enzyme cofactor mixture and 10 μl of nitrate reductase mixture were added. After incubation at room temperature for 1 h, 50 μl of Griess reagent R1 and immediately 50 μl of Griess reagent R2 were added to each well. The plate was left at room temperature for 10 min for colour development. For a standard curve to quantify the nitrate concentrations of the samples, nitrates with final concentrations of 0, 5, 10, 15, 20, 25, 30 and 35 μM in a 200-μl reaction volume were used. The absorbance was recorded at 540 nm on a VICTOR multi-label plate reader. Our measurements used three larvae per sample, and we repeated the treatment with three biological samples.Galleria injection assaysPrecultures of X. szentirmaii DSM wild-type strain and the mutants thereof were grown in LB medium and inoculated into fresh cultures at an OD600 of 0.1. Cells were grown to exponential phase (OD600 ≈ 1) and then diluted to an OD600 of 0.00025. A 5-µl volume of the diluted bacterial culture was injected into the last left pro-leg of the larvae (LB medium as a negative control). G. mellonella larvae were kept at 4 °C for 10 min before injection. After infection, the larvae were incubated at 25 °C. Dead Galleria larvae were frozen at −20 °C, then at −80 °C, and freeze-dried for one day. Freeze-dried larvae were ground. Every injection experiment was aliquoted into two portions, one of which was extracted with 25 ml of acetone/ethyl acetate (vol/vol, 1:1) while the other one was extracted with acetone/methanol. Extracts were dried and resuspended in 3 ml of acetonitrile/water (1:1, vol/vol) with a tenfold dilution for HPLC-MS-UV analysis. To compare the survival percentage of G. mellonella larvae infected with the WT strain and mutants and to determine median lethal time (LT50) values, Kaplan–Meier curves were generated by GraphPad PRISM 8.4.3.Cytotoxicity assaysHepG2 cells (hepatoblastoma cell line; ACC 180, DSMZ) were cultured under conditions recommended by the depositor, and cells were propagated in Dulbecco’s modified Eagle medium supplemented with 10% fetal bovine serum. To determine the cytotoxicity of test compounds, cells were seeded at 6 × 103 cells per well of 96-well plates in 120 μl of complete medium. After 2 h of equilibration, compounds were added in serial dilution in 60 µl of complete medium. Compounds as well as the solvent control and doxorubicin as an in-assay positive control (IC50 of 0.06 ± 0.01 µg ml−1) were tested as duplicates in two independent experiments. After 5 days of incubation, 20 μl of 5 mg ml−1 MTT (thiazolyl blue tetrazolium bromide) in PBS was added per well, and the cells were further incubated for 2 h at 37 °C. The medium was then discarded and cells were washed with 100 μl of PBS before adding 100 μl of 2-propanol/10 N HCl (250:1) to dissolve the formazan granules. The absorbance at 570 nm was measured using a microplate reader (Tecan Infinite M200Pro with Tecan iControl 2.0), and cell viability was expressed as a percentage relative to the respective solvent control. IC50 values were determined by sigmoidal curve fitting using GraphPad PRISM 8.4.3.Statistical analysisIn Fig. 5d,e,g,j,k, means were compared using an LSD test of one-way ANOVA using POC GLM of the SAS program (SAS Institute, 1989) for continuous variables and discriminated at type I error = 0.05. The results were plotted using Sigma Plot 12.0.Reporting SummaryFurther information on research design is available in the Nature Research Reporting Summary linked to this Article. More