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    Risk assessment for the native anurans from an alien invasive species, American bullfrogs (Lithobates catesbeianus), in South Korea

    Pimentel, D. Economic and environmental impacts of invasive species and their management. Pesticides 21, 10–11 (2001).
    Google Scholar 
    Beck, K. G. et al. Invasive species defined in a policy context: Recommendations from the Federal Invasive Species Advisory Committee. Invasive. Plant. Sci. Manag. 1, 414–421. https://doi.org/10.1614/IPSM-08-089.1 (2008).Article 

    Google Scholar 
    Arya, A. K., Joshi, K. K., Bachheti, A. & Rawat, R. Status and impact of invasive and alien species on environment, and human welfare: an overview. Uttar Pradesh J. Zool. 42, 49–58 (2021).
    Google Scholar 
    Boone, M. D., Little, E. E. & Semlitsch, R. D. Overwintered bullfrog tadpoles negatively affect salamanders and anurans in native amphibian communities. Copeia 2004, 683–690. https://doi.org/10.1643/CE-03-229R1 (2004).Article 

    Google Scholar 
    Borzée, A., Kosch, T. A., Kim, M. & Jang, Y. Introduced bullfrogs are associated with increased Batrachochytrium dendrobatidis prevalence and reduced occurrence of Korean treefrogs. PLoS ONE 12, e0177860. https://doi.org/10.1371/journal.pone.0177860 (2017).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Yap, T. A., Koo, M. S., Ambrose, R. F. & Vredenburg, V. T. Introduced bullfrog facilitates pathogen invasion in the western United States. PLoS ONE 13, e0188384. https://doi.org/10.1371/journal.pone.0188384 (2018).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gobel, N., Laufer, G. & Cortizas, S. Changes in aquatic communities recently invaded by a top predator: Evidence of American bullfrogs in Aceguá, Uruguay. Aquat. Sci. 81, 1–11. https://doi.org/10.1007/s00027-018-0604-1 (2019).Article 

    Google Scholar 
    Li, Y., Ke, Z., Wang, Y. & Blackburn, T. M. Frog community responses to recent American bullfrog invasions. Curr. Zool. 57, 83–92. https://doi.org/10.1093/czoolo/57.1.83 (2011).Article 

    Google Scholar 
    Vitousek, P. M., D’antonio, C. M., Loope, L. L., Rejmanek, M. & Westbrooks, R. Introduced species: a significant component of human-caused global change. N. Z. J. Ecol. 21, 1–16 (1997).
    Google Scholar 
    Ficetola, G. F. et al. Pattern of distribution of the American bullfrog Rana catesbeiana in Europe. Biol. Invasions. 9, 767–772. https://doi.org/10.1007/s10530-006-9080-y (2007).Article 

    Google Scholar 
    Lorvelec, O., & Détaint, M. Lithobates catesbeianus (Shaw), American bullfrog (Ranidae, Amphibia). Handbook of alien species in Europe. DAISIE (ed.). (Springer, 2009).Koo, K. S., Park, H. R., Choi, J. H. & Sung, H. C. Present status of non-native amphibians and reptiles traded in Korean online pet shops. J. Ecol. Environ. 3, 106–114. https://doi.org/10.13047/KJEE.2020.34.2.106 (2020).Article 

    Google Scholar 
    Lowe, S., Browne, M., Boudjelas, S., & De Poorter, M. 100 of the world’s worst invasive alien species: A selection from the global invasive species database (Vol. 12) (Auckland: Invasive Species Specialist Group, 2000).Ficetola, G. F., Thuiller, W. & Miaud, C. Prediction and validation of the potential global distribution of a problematic alien invasive species—The American bullfrog. Divers. Distrib. 13, 476–485. https://doi.org/10.1111/j.1472-4642.2007.00377.x (2007).Article 

    Google Scholar 
    Orchard, S. A. Removal of the American bullfrog, Rana (Lithobates) catesbeiana, from a pond and a lake on Vancouver Island, British Columbia, Canada Island invasives: Eradication and management. IUCN (Gland, Switzerland). 2011, 1–542 (2011).
    Google Scholar 
    Oh, H. S. & Hong, C. E. Current conditions of habitat for Rana catesbeiana and Trachemys scripta elegans imported to Jeju-do, including proposed management plans. J. Ecol. Environ. 21, 311–317 (2007).
    Google Scholar 
    Park, D. et al. Conservation of amphibians in South Korea. Das, M. Wilkinson, and H. Heatwole (eds.). (2014).Groffen, J., Kong, S., Jang, Y. & Borzee, A. The invasive American bullfrog (Lithobates catesbeianus) in the Republic of Korea: history and recommendations for population control. Manag. Biol. Invasions. 10, 517. https://doi.org/10.3391/mbi.2019.10.3.08 (2019).Article 

    Google Scholar 
    Jang, H. J. & Suh, J. H. Distribution of amphibian species in South Korea. Korean J. Herpetol. 2, 45–51 (2010).
    Google Scholar 
    Kim, J. B. Taxonomic list and distribution of Korean amphibians. Korean J. Herpetol. 1, 1–13. https://doi.org/10.5145/KJCM.2010.13.3.144 (2010).CAS 
    Article 

    Google Scholar 
    Liu, X., McGarrity, M. E. & Li, Y. The influence of traditional Buddhist wildlife release on biological invasions. Conserv. Lett. 5, 107–114. https://doi.org/10.1111/j.1755-263X.2011.00215.x (2012).Article 

    Google Scholar 
    Snow, N. P. & Witmer, G. American bullfrogs as invasive species: a review of the introduction, subsequent problems, management options, and future directions. Proc. Vertebrate Pest Conf. 24, 86–89. https://doi.org/10.5070/V424110490 (2010).Article 

    Google Scholar 
    Lee, J. H., & Park, D. The encyclopedia of Korean amphibians. (Nature and Ecology, 2016).Park, C. D., Lee, C. W., Lim, J. C., Yang, B. G. & Lee, J. H. A study on the diet items of American Bullfrog (Lithobates catesbeianus) in Ga-hang Wetland Korea. J. Ecol. Environ. 32, 55–65. https://doi.org/10.13047/KJEE.2018.32.1.55 (2018).Article 

    Google Scholar 
    Kim, H. W., Adhikari, P., Chang, M. H. & Seo, C. Potential distribution of amphibians with different habitat characteristics in response to climate change in South Korea. Animals 11, 2185. https://doi.org/10.3390/ani11082185 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Adhikari, P., Kim, B. J., Hong, S. H. & Lee, D. H. Climate change induced habitat expansion of nutria (Myocastor coypus) in South Korea. Sci. Rep. 12, 1–12. https://doi.org/10.1038/s41598-022-07347-5 (2022).CAS 
    Article 

    Google Scholar 
    Shim, J. H. et al. A study to determine factors affecting bullfrog decline in Korea. Gwacheon, Republic of Korea. 38. (2005).Ra, N. Y. et al. Habitat requirements of the Gold-spotted pond frog (Rana chosenica): Implications for conservation and management plans. In 63th Annual Meeting of the Korean Association of Biological Sciences. (2008).Ministry of Environment. Act on the conservation and use of biological diversity. (2020).Bellard, C., Genovesi, P. & Jeschke, J. M. Global patterns in threats to vertebrates by biological invasions. Proc. R. Soc. B: Biol. Sci. 283, 20152454. https://doi.org/10.1098/rspb.2015.2454 (2016).Article 

    Google Scholar 
    Blackburn, T. M., Bellard, C. & Ricciardi, A. Alien versus native species as drivers of recent extinctions. Front. Ecol. Environ. 17, 203–207. https://doi.org/10.1002/fee.2020 (2019).Article 

    Google Scholar 
    Marino, C., Leclerc, C. & Bellard, C. Profiling insular vertebrates prone to biological invasions: What makes them vulnerable?. Glob. Change Biol. 28, 1077–1090. https://doi.org/10.1111/gcb.15941 (2022).CAS 
    Article 

    Google Scholar 
    Pearl, C. A., Adams, M. J., Bury, R. B. & McCreary, B. Asymmetrical effects of introduced bullfrogs (Rana catesbeiana) on native ranid frogs in Oregon. Copeia 2004, 11–20. https://doi.org/10.1643/CE-03-010R2 (2004).Article 

    Google Scholar 
    Wu, Z., Li, Y., Wang, Y. & Adams, M. J. Diet of introduced Bullfrogs (Rana catesbeiana): predation on and diet overlap with native frogs on Daishan Island, China. J. Herpetol. 39, 668–674. https://doi.org/10.1670/78-05N.1 (2005).Article 

    Google Scholar 
    Liu, X. et al. Diet and prey selection of the Invasive American bullfrog (Lithobates catesbeianus) in southwestern China. Asian Herpetol. Res. 6, 34–44. https://doi.org/10.16373/j.cnki.ahr.140044 (2015).Article 

    Google Scholar 
    Wang, Y., Wang, Y., Lu, P., Zhang, F. & Li, Y. Diet composition of post-metamorphic bullfrogs (Rana catesbeiana) in the Zhoushan archipelago, Zhejiang Province, China. Front. Biol. China. 3, 219–226. https://doi.org/10.1007/s11515-008-0036-8 (2008).CAS 
    Article 

    Google Scholar 
    Da Silva, E. T., Dos Reis, E. P., Feio, R. N. & Ribeiro Filho, O. P. Diet of the invasive frog Lithobates catesbeianus (Shaw, 1802) (Anura: Ranidae) in Viçosa, Minas Gerais State, Brazil. S. Am. J. Herpetol. 4, 286–294. https://doi.org/10.2994/057.004.031 (2009).Article 

    Google Scholar 
    Ortíz-Serrato, L., Ruiz-Campos, G. & Valdez-Villavicencio, J. H. Diet of the exotic American bullfrog, Lithobates catesbeianus, in a stream of northwestern Baja California, Mexico. West. N. Am. Nat. 74, 116–122. https://doi.org/10.3398/064.074.0112 (2014).Article 

    Google Scholar 
    Ryan, M. J. The reproductive behavior of the bullfrog (Rana catesbeiana). Copeia 1, 108–114 (1980).Article 

    Google Scholar 
    Gahl, M. K., Calhoun, A. J. & Graves, R. Facultative use of seasonal pools by American bullfrogs (Rana catesbeiana). Wetlands 29, 697–703. https://doi.org/10.1672/08-56.1 (2009).Article 

    Google Scholar 
    Louette, G., Devisscher, S. & Adriaens, T. Control of invasive American bullfrog Lithobates catesbeianus in small shallow water bodies. Eur. J. Wildl. Res. 59, 105–114 (2013).Article 

    Google Scholar 
    Descamps, S. & De Vocht, A. Movements and habitat use of the invasive species Lithobates catesbeianus in the valley of the Grote Nete (Belgium). Belg. J. Zool. 146, 90–100. https://doi.org/10.26496/bjz.2016.44 (2016).Article 

    Google Scholar 
    Willis, Y. L., Moyle, D. L. & Baskett, T. S. Emergence, breeding, hibernation, movements and transformation of the bullfrog, Rana catesbeiana in Missouri. Copeia 1956, 30–41 (1956).Article 

    Google Scholar 
    Cooper, M. C. Movement, Habitat, and Home Range of Introduced Bullfrogs (Lithobates Catesbeianus) on Mad River Gravel Ponds (Humboldt Co., CA, USA), With Implications for Hydro-Modification as a Method of Management. Dissertation, Humboldt State University. https://digitalcommons.humboldt.edu/etd/40 (2017).Updated guidelines for reporting animal research. Percie du Sert, N. et al. The ARRIVE guidelines 2.0. J. Cereb. Blood Flow Metab. 40, 1769–1777. https://doi.org/10.1177/0271678X20943823 (2020).Article 

    Google Scholar 
    Stebbins, R. C. A Field Guide to Western Reptiles and Amphibians (Houghton Mifflin, 2003).
    Google Scholar 
    Howard, R. D. Alternative mating behaviors of young male bullfrogs. Am. Zool. 24, 397–406. https://doi.org/10.1093/icb/24.2.397 (1984).Article 

    Google Scholar 
    Lee, J. H., Jang, H. J., & Suh, J. H. Ecological Guide Book of Herpetofauna in Korea. 56–142 (National Institute of Environmental Research, 2011).Schmidt, K. & Schwarzkopf, L. Visible implant elastomer tagging and toe-clipping: Effects of marking on locomotor performance of frogs and skinks. Herpetol. J. 20, 99–105 (2010).
    Google Scholar 
    Heyer, R., Donnelly, M. A., Foster, M., & Mcdiarmid, R. Measuring and Monitoring Biological Diversity: Standard Methods for Amphibians. (Smithsonian Institution, 2014).Muths, E. A radio transmitter belt for small ranid frogs. Herpetol. Rev. 34, 345–347 (2003).
    Google Scholar 
    McGarrity, M. E. & Johnson, S. A. A radio telemetry study of invasive Cuban treefrogs. Florida Sci. 73, 225–235 (2010).
    Google Scholar 
    Stinner, J., Zarlinga, N. & Orcutt, S. Overwintering behavior of adult bullfrogs, Rana catesbeiana, in northeastern Ohio. Ohio. J. Sci. 94, 8–13 (1994).
    Google Scholar 
    Wassens, S., Watts, R. J., Jansen, A. & Roshier, D. Movement patterns of southern bell frogs (Litoria raniformis) in response to flooding. Wildl. Res. 35, 50–58. https://doi.org/10.1071/WR07095 (2008).Article 

    Google Scholar 
    Bury, R. B., & Whelan, J. A. Ecology and management of the bullfrog (Vol. 155) (US Department of the Interior, Fish and Wildlife Service, 1985).Sepulveda, A. J. & Layhee, M. Description of fall and winter movements of the introduced American Bullfrog (Lithobates catesbeianus) in a Montana, USA, pond. Herpetol. Conserv. Biol. 10, 978–984 (2015).
    Google Scholar 
    Ingram, W. M. & Raney, E. C. Additional studies on the movement of tagged bullfrogs, Rana catesbeiana Shaw. Am. Midl. Nat. 29, 239–241 (1943).Article 

    Google Scholar 
    Wang, Y. & Li, Y. Habitat selection by the introduced American bullfrog (Lithobates catesbeianus) on Daishan Island, China. J. Herpetol. 43, 205–211. https://doi.org/10.1670/0022-1511-43.2.205 (2009).Article 

    Google Scholar 
    Werner, E. E., Wellborn, G. A. & McPeek, M. A. Diet composition in postmetamorphic bullfrogs and green frogs: implications for interspecific predation and competition. J. Herpetol. 29, 600–607 (1995).Article 

    Google Scholar 
    Yoo, M. S., Ra, C. H., Kwon, H. B., Kim, J. Y. & Kang, S. G. Reproductive cycle and maturation induction of oocytes in Rana rugosa. Korean J. Zool. 38, 96–105 (1995).
    Google Scholar 
    Chung, H. H. A Study on the Ecological Characteristics, Capture and Use of Bullfrog. Dissertation, Chosun University. (2002).Hirai, T. Diet composition of introduced bullfrog, Rana catesbeiana, in the Mizorogaike Pond of Kyoto, Japan. Ecol. Res. 19, 375–380. https://doi.org/10.1111/j.1440-1703.2004.00647.x (2004).Article 

    Google Scholar 
    Quagliata, S., Delfino, G., Giachi, F. & Malentacchi, C. Chemical skin defence in the Eastern fire-bellied toad Bombina orientalis: an ultrastructural approach to the mechanism of poison gland rehabilitation after discharge. Acta. Herpetol. https://doi.org/10.1400/181560 (2008).Article 

    Google Scholar 
    Lee, J. H. & Park, D. Effects of body size, operational sex ratio, and age on pairing by the Asian toad, Bufo stejnegeri. Zool. Stud. 48, 334–332 (2009).
    Google Scholar 
    Kim, I. H., Ham, C. H., Jang, S. W., Kim, E. Y. & Kim, J. B. Determination of breeding season, and daily pattern of calling behavior of the endangered Suweon-tree frog (Hyla suweonensis). Korean J. Herpetol. 4, 23–29 (2012).
    Google Scholar 
    Jancowski, K. & Orchard, S. Stomach contents from invasive American bullfrogs Rana catesbeiana (= Lithobates catesbeianus) on southern Vancouver Island, British Columbia, Canada. NeoBiota. 16, 17–37. https://doi.org/10.3897/neobiota.16.3806 (2013).Article 

    Google Scholar 
    An, D. & Waldman, B. Enhanced call effort in Japanese tree frogs infected by amphibian chytrid fungus. Biol. Lett. 12, 20160018. https://doi.org/10.1098/rsbl.2016.0018 (2016).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Borzée, A. et al. Temporal and spatial differentiation in microhabitat use: Implications for reproductive isolation and ecological niche specification. Integr. Zool. 11, 375–387. https://doi.org/10.1111/1749-4877.12200 (2016).Article 
    PubMed 

    Google Scholar 
    Borzee, A. et al. Yellow sea mediated segregation between North East Asian Dryophytes species. PLoS ONE 15, e0234299. https://doi.org/10.1371/journal.pone.0234299 (2020).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Park, J. K., Kim, J. B. & Do, Y. Examination of physiological and morphological differences between farm-bred and wild black-spotted pond frogs (Pelophylax nigromaculatus). Life. 11, 1089. https://doi.org/10.3390/life11101089 (2021).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Peterson, A. C., Richgels, K. L., Johnson, P. T. & McKenzie, V. J. Investigating the dispersal routes used by an invasive amphibian, Lithobates catesbeianus, in human-dominated landscapes. Biol. Invasions. 15, 2179–2191. https://doi.org/10.1007/s10530-013-0442-y (2013).Article 

    Google Scholar 
    Austin, J. D., Dávila, J. A., Lougheed, S. C. & Boag, P. T. Genetic evidence for female-biased dispersal in the bullfrog, Rana catesbeiana (Ranidae). Mol. Ecol. 12, 3165–3172. https://doi.org/10.1046/j.1365-294X.2003.01948.x (2003).Article 
    PubMed 

    Google Scholar 
    Doubledee, R. A., Muller, E. B. & Nisbet, R. M. Bullfrogs, disturbance regimes, and the persistence of California red-legged frogs. J. Wildl. Manage. 67, 424–438 (2003).Article 

    Google Scholar 
    Hanselmann, R. et al. Presence of an emerging pathogen of amphibians in introduced bullfrogs Rana catesbeiana in Venezuela. Biol. Conserv. 120, 115–119. https://doi.org/10.1016/j.biocon.2004.02.013 (2004).Article 

    Google Scholar 
    Adams, M. J., & Pearl, C. A. Problems and opportunities managing invasive bullfrogs: is there any hope? In Biological Invaders in Inland Waters: Profiles, Distribution, and Threats. 679–693 (Springer, 2007).Fisher, M. C. & Garner, T. W. The relationship between the emergence of Batrachochytrium dendrobatidis, the international trade in amphibians and introduced amphibian species. Fungal. Biol. Rev. 21, 2–9. https://doi.org/10.1016/j.fbr.2007.02.002 (2007).Article 

    Google Scholar 
    IUCN. The IUCN Red List of Threatened Species. Version 2021–3. https://www.iucnredlist.org. Accessed on [10.02.2022].Ministry of Environment. Enforcement decree of the wildlife protection and management act. (2018). More

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    Trawling the ocean virome

    Microbial biodiversity surveys have often been done in a number of generally better-studied regions3, as with the San Pedro Time Series from the San Pedro Channel off the coast of Southern California. Global surveys have also been emerging, such as the Sorcerer II Global Ocean Sampling Expedition from 2004 to 2006 launched by J. Craig Venter. There are also data and samples from the Malaspina circumnavigation, an expedition devoted to data collection on ocean biodiversity and climate change that was led by the Spanish Ministry of Science and Innovation.As microbiome researcher Shinichi Sunagawa of the ETH Zurich and colleagues point out4, sequencing technologies have advanced such that they now enable systematic and quantitative global ocean surveys. These advances, in turn, made it possible to find and assess marine double-stranded DNA virus populations. This latest work on marine RNA viruses, says Sunagawa, in which he was also involved, embeds new phylum-level findings into a “robust taxonomic framework.” In his view, this research ranks in importance with the reconstruction a few years ago of a group of bacterial genomes representing more than 35 phyla that the researchers call “the candidate phyla radiation”5. If one counts viruses in with other taxonomic groups, the finding might be the largest single expansion of established microbial taxonomy, he says. And he especially likes the definition of a new basal Orthornavirae megataxon, the proposed phylum ‘Taraviricota’. This proposed phylum is one of several findings from recently published analyses of sampling data from Tara Oceans1,2, a global expedition supported by the Tara Ocean Foundation, or Fondation Tara Océan, based in France and with many partner organizations and supporters. The foundation is a major source of global data about the ocean and ocean microbes and, as its president Étienne Bourgois says, it’s a “family project.” The family business is the French fashion house agnès b., founded by his mother Agnès Troublé.Because the family cares about the sea, they bought a 36-meter schooner from Lady Pippa Blake, widow of yachtsman and explorer Sir Peter Blake, after pirates killed him during an environmental expedition in the Amazon delta, and turned it into the expedition vessel and floating science laboratory Tara, devoted to understanding and protecting the world’s marine environment. It’s a way to continue what Peter Blake started, to continue the conversation about the ocean and do research as well, says sailor-scientist Romain Troublé, executive director of the foundation and nephew of Agnès Troublé. The boat had been previously owned by explorer Jean-Louis Étienne. The foundation has supported several expeditions with Tara including the Tara Oceans and Tara Oceans Polar Circle expeditions, as well as Tara Mission Microbiomes, which is currently underway. The equilibrium of the planet “depends on the microbiome of the ocean in the same way we depend on our own microbiome,” says Romain Troublé. Viruses are part of the larger picture of how life is supported on the planet. It’s “a great mystery of the century” to decipher the roles, behaviors and functions of the ocean microbiome, including its beneficial effects. Over the last decade, he says, the expeditions have, for example, collected plankton samples from coastal waters, coral reefs and the high seas around the world for scientists to ask questions of. Microplastics in the ocean concentrate chemical pollutants such as pesticides, and microplastics appear to be substrates for distinct microbiomes. Polystyrene and polypropylene, for example, harbor different microbial communities. “We call it the plastisphere,” he says. All sample collection, not just of microplastics, happens with a view to scientific rigor to assure data quality, says Troublé. Many institutes are part of and support the expeditions through the Tara Ocean Foundation, including AtlantECO, the French Ministry of Research, the Swiss National Science Foundation, the US National Science Foundation, the European Molecular Biology Laboratory and the French National Centre for Scientific Research.Tara Oceans was an expedition initiated by EMBL researcher Eric Karsenti, here in the foreground. He is checking a rosette of Niskin bottles that collect water, and ocean microbe samples, at various depths. Sensors capture parameters such as temperature.
    Credit: Fondation Tara OcéanIts expedition Tara Oceans was initiated by cell and marine biologist Eric Karsenti of the European Molecular Biology Laboratory. The expedition ran from 2009 to 2013 and covered 125,000 kilometers of ocean, taking ocean water and samples. It collected nearly 35,000 samples of viruses, algae and plankton and delivered more than 60 terabases of DNA and RNA sequences.The research community strives to follow FAIR data principles, the principles of findability, accessibility, interoperability and reusability, says Sunagawa. Tara Ocean’s data troves can be found, for instance, in the European Nucleotide Archive (ENA), Pangeaea, Cyverse, iVIRUS and on Genoscope. Other data-collection efforts target users with less programming experience and offer various types of data relevant to marine microbial research, he says: for example, the Ocean Gene Atlas, a portal to search for a gene or protein sequence to see, for instance, its abundance on an ocean map. The Ocean Barcode Atlas lets users explore, for example, operational taxonomic units (OTU) data and plankton communities from Tara Oceans and OTUs from Malaspina prokaryote data. Sunagawa also points to the Ocean Microbiomics Database and its high-quality genome-resolved information about the global microbiome, which has sequencing data from 2003 onwards and which includes Tara Oceans data as well as datasets such as the Hawaii Ocean Time-Series (HOT), the Bermuda Atlantic Time-series Study (BATS), with its collection of ocean data dating back to 1988, and BioGeotraces, with hydrographic and marine geochemical data from various expeditions.The recent publications on RNA viruses1,2, in which Sunagawa was also involved, have expanded the known diversity of these viruses, he says. They build on efforts by, for example, the research team that created and applied a cloud-based infrastructure called Serratus6, with which researchers can perform sequence alignment using bowtie2 for nucleotide sequences and DIAMOND2 for protein sequences in ‘ultra-high throughput’ on a petabase scale. Using Serratus, the team identified more than 130,000 previously unknown RNA viruses, both on land and in the oceans. The wealth of resources for microbial and viral data about the oceans is helpful to the research community, but “we could still improve the connectivity between various datasets though,” says Sunagawa. That would help, for example, with searching and finding data products that are derived from primary data, such as identifiers of individual genome assemblies, genes and metagenome assembled genomes, which are all presented in different online locations. But connecting data resources is a project that itself takes resources, and such projects are hard to get funding for.Going forward, it will be challenging, says Sunagawa, to update and keep up to date both past projects and ongoing projects such as the Global Ocean Ship-based Hydrographic Investigations program (GO-SHIP), which is focused on physical oceanography; the Antarctic Circumnavigation Expedition (ACE), on carbon-cycle marine biogeochemistry; Mission Microbiomes; and many more. “And ultimately, we will need to cross boundaries that currently separate biome-focused research to better understand processes at the sea–land–atmosphere interfaces.”Tara Mission Microbiomes has been underway for nearly two years and wraps up in October 2022. At press time, the schooner Tara was off the Angolan Coast. At the end of the expedition, it will have traveled a total of 70,000 km of ocean area around South America, Africa, Europe and Antarctica. Mission Microbiomes is part of the EU-funded AtlantECO and also includes 42 research organizations from 13 countries. The microbiome mission is collecting data on how climate change is affecting the marine microbiome, on how pollution, microplastics pollution in particular, affects the marine environments and on the beneficial impact of the ocean microbiome.Krill are small ocean crustaceans that mainly eat phytoplankton and are a food source for animals such as whales and seals. Krill play a crucial role in biogeochemical cycles.
    Credit: F. Aurat, Fondation Tara OcéanChris Bowler, from the Institut de Biologie de l’École Normale Supérieure, is scientific director of the Tara Oceans consortium, was scientific coordinator of the Tara Oceans expedition and was onboard in Antarctica during the Tara Mission Microbiomes expedition to collect data on the impact of icebergs on the Weddell Sea ecosystem. The project’s scientists in Tara Mission Microbiomes, he says, are studying specific processes, including the Amazon plume, the Malvinas confluence, the impact of tabular icebergs in the Weddell Sea, the Benguela upwelling and more. The data from this expedition will be similar to those from Tara Oceans but, he says, “we will have much more contextual data related to the specific processes we have been studying.” The applied techniques are all ones that have undergone much advancement since Tara Oceans, he says. They include long-read sequencing, Hi-C sequencing to capture chromatin organization on a genome-wide basis and various types of microscopy.Data and results from previous and ongoing expeditions are impressive, says Sunagawa but “we are still data-limited in our field of research.” Geographically, sampling stations are usually still separated by hundreds of kilometers, and often they are even further apart than that. This means that what is missing is both temporal and seasonal resolution, “and we keep detecting new organisms,” he says. Tara Mission Microbiomes will help to fill in some of these gaps. The mission is unlike Tara Oceans, with its focus more on coastal areas and environmental pollutants such as microplastics. Sunagawa and his group are not currently involved with Tara Mission Microbiomes, “but we look forward to seeing the first results coming out soon.”Through photosynthesis, phytoplankton deliver oxygen to the planet. They are food for zooplankton, which are food for other marine organisms. This food web and its associated decomposition are part of the ocean’s carbon pump, in which marine viruses play an important role that scientists have only begun exploring.
    Credit: M. Bardy, Fondation Tara Océan More

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    Why the ocean virome matters

    Kyoto University microbiome researcher Hiroyuki Ogata says that the recent work2,3 further connects RNA viruses and the carbon pump, which affects the Earth’s biogeochemical cycles and thus its climate. And it sheds light on the diversity, evolution and ecology of RNA viruses, which has not previously been possible through applying the techniques of traditional DNA-based metagenomics. The team found many new lineages at the phylum-level by using “highly sensitive” computational approaches.It’s possible to assess the ecosystem impact of viruses by inferring auxiliary metabolic genes (AMGs). AMGs hint at the ways RNA viruses manipulate the physiology of their hosts as they seek to maximize production of more virus through the host. As Jian explains, labs have identified a variety of AMGs that are encoded by DNA viruses and, he says, it’s “well-recognized” that AMGs probably play a role in marine ecosystems. It was unknown if AMGs could be found in RNA viruses, which the recent Science paper2 has now established, he says. Jian sees this work as providing “a very important foundational dataset” for exploring questions connected to AMGs. “In my opinion, if more long-sequence or complete marine RNA virus genomes can be obtained in the future, and they can be further connected with specific hosts, it will greatly promote the understanding of the ecological impact of RNA viruses in the oceans.”To tease out AMGs, the scientists used a variety of tools, such as viral identification software for both DNA and RNA viruses, says Wainaina. The ones for DNA viruses are available on Cyverse, and the protocols for the tools from the Sullivan lab are on protocols.io. One method for RNA viruses is in progress and will be soon available on Cyverse, he says. DNA viral identification tools include VirSorter2, a pipeline for identifying viral sequence from metagenomics data, and the protocol for using this and other tools are also on protocols.io. To identify AMGs from viral sequence that had been identified through VirSorter, the team used use DRAM-v, a software tool from the lab of microbiome researcher Kelly Wrighton at Colorado State University. Her group had created Distilled and Refined Annotation of Metabolism (DRAM), a framework to resolve metabolic information from microbial data. The companion tool DRAM-v is for viruses and can be applied to metagenomic data sets for annotating metagenomics-based assembled genomes, for example through the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database, and to contiguous viral sequences identified by VirSorter.The hunt for AMGs is one instance in which the team needed to determine in each case whether a sequence was likely ‘stolen’ from host cells, says Dominguez-Huerta. RNA viral genomes are less than 40 kilobases long and usually have complicated genomic organization, both in a structural genomics sense related to the physical arrangement of genes along the viral genome and in a functional sense in terms of transcription and translation: there are overlapping genes, frameshifts and more, all of which makes this kind of annotation difficult. And sometimes information in the annotation databases is wrong and indicates that a match is cellular when it is in fact viral. Thus, to find AMGs, “we don’t have a defined clean methodology automated in a pipeline yet,” he says. It remains a time-consuming task. Assigning putative function to the protein sequences encoded by AMGs also involves checking the literature and comparing different annotation sources.Dominguez-Huerta says he and the team were glad they could assemble AMG functionalities to suggest the range of ways in which RNA viruses manipulate the metabolisms of their hosts—from photosynthesis to central carbon metabolism to vacuolar digestion and RNA repair. This overview let them see how some AMGs are repeated across different viruses across the oceans. Finding AMGs in long-read sequence is what he calls a “fire test” for the lab. To avoid ‘false AMGs’ from unreliable matches, they use BLASTP, the Basic Alignment Search Tool that compares a protein query sequence to a protein database.“I am fascinated by the ability of viruses to metabolic reprogram not only their hosts but more importantly at the ecosystem level,” says Wainaina. It is probable that the AMGs the team identified “are a central cog in microbial metabolism networks.” Current and future modeling efforts will hopefully provide insights into the ecosystem roles of viruses—both DNA viruses and RNA viruses—and on a global scale both within the ocean ecosystem and beyond.Host inference is challenging, says Dominguez-Huerta, because, for example, viruses with RNA genomes do not share genetic information with their host genomic DNA the way dsDNA viruses do when they infect bacteria. That means there is no clear signal to be derived from the host genome to help one guess the possible host. But sometimes RNA viruses do integrate into host genomes, and those, likely more accidental, events were sufficient for the scientists to capture some signal to infer hosts. “We also performed statistical co-occurrence analytics using abundances to infer the hosts with certain success,” he says.Unlike dsDNA viruses, RNA viruses infect mostly eukaryotes, from protists and fungi to invertebrates and fish larvae; only a minority infect bacteria. Overall, the team has been able to capture “a picture of dsDNA viruses infecting prokaryotes and RNA viruses infecting eukaryotes in the oceans, complementing each other in their marine hosts,” says Dominguez-Huerta. The fact that the scientists can infer “that RNA viruses can steal genes from the host,” in the form of AMGs, to then reprogram host metabolism matters not only as scientists complete the picture of how viruses directly tune the activity of hosts during infection, but also in regard to how this influences biogeochemical cycles, he says. “We think that these AMGs are incorporated into the RNA virus genomes from cellular mRNA transcripts by non-homologous recombination,” he says. This gives, in his view, a new picture of RNA viruses, which, despite their small genome sizes, can squeeze in protein-coding genes. Such proteins could be sufficient to boost the production of virus particles per infected cell, perhaps increasing viral fitness in the difficult conditions of the oligotrophic open ocean and letting the viruses better propagate in the environment.More generally, says Dominguez-Huerta, capturing RNA from ocean samples is difficult, because RNA is physically fragile and degrades rapidly. When digging into metatranscriptomic data, which include the RNA from plankton and RNA from other organisms, less than 1% of this RNA is likely to be viral RNA, he says. Previously, some labs have first purified RNA from samples, enriched it for replicating RNA viruses and then applied a method called dsRNA-seq to recover dsRNA virus sequence and replicate sequences from single-stranded RNA viruses. For future ocean RNA virus projects, he says that the lab is currently working on a wet-lab method to purify RNA virus particles from seawater to solve the challenges of obtaining viral RNA for analysis. 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    Stochastic models of Mendelian and reverse transcriptional inheritance in state-structured cancer populations

    Pienta, K. J., Hammarlund, E. U., Austin, R. H., Axelrod, R., Brown, J. S. & Amend, S. R. Cancer cells employ an evolutionarily conserved polyploidization program to resist therapy. In Seminars in Cancer Biology, 1–15 (2020).Siegel, R. L., Miller, K. D. & Jemal, A. Cancer statistics, 2020. CA A Cancer J. Clin. 70(1), 7–30 (2020).Article 

    Google Scholar 
    Duesberg, P. & Rasnick, D. Aneuploidy, the somatic mutation that makes cancer a species of its own. Cell Motil. Cytoskelet. 47(2), 81–107 (2000).CAS 
    Article 

    Google Scholar 
    Hanahan, D. & Weinberg, R. A. Leading edge review hallmarks of cancer: The next generation. Cell 144, 646–674 (2011).CAS 
    PubMed 
    Article 

    Google Scholar 
    Amend, S. R. et al. Polyploid giant cancer cells: Unrecognized actuators of tumorigenesis, metastasis, and resistance. Prostate 79(13), 1489–1497 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Pienta, K. J. et al. Convergent evolution, evolving evolvability, and the origins of lethal cancer. Mol. Cancer Res. 18(6), 801–810 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Pienta, K. J., Hammarlund, E. U., Axelrod, R., Brown, J. S. & Amend, S. R. Poly-aneuploid cancer cells promote evolvability, generating lethal cancer. Evol. Appl. 13(7), 1626–1634 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Roychowdhury, S. et al. Personalized oncology through integrative high-throughput sequencing: A pilot study. Sci. Transl. Med. 3(111), 1–12 (2011).Article 
    CAS 

    Google Scholar 
    Kuczler, M. D., Olseen, A. M., Pienta, K. J. & Amend, S. R. ROS-induced cell cycle arrest as a mechanism of resistance in polyaneuploid cancer cells (PACCs). Prog. Biophys. Mol. Biol. 165, 3–7 (2021).CAS 
    PubMed 
    Article 

    Google Scholar 

    Brown, R. L. What evolvability really is. Br. J. Philos. Sci.65(3), 549–572 (2014).MathSciNet 
    Article 

    Google Scholar 
    Crother, B. I. & Murray, C. M. Early usage and meaning of evolvability. Ecol. Evol. 9(7), 3784–3793 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Payne, J. L. & Wagner, A. The causes of evolvability and their evolution. Nat. Rev. Genet. 20, 24–38 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Pigliucci, M. Is evolvability evolvable?. Genetics 9, 75–82 (2008).CAS 
    PubMed 

    Google Scholar 
    Sniegowski, P. D. & Murphy, H. A. Evolvability. Curr. Biol. 16, R831–R834 (2006).CAS 
    PubMed 
    Article 

    Google Scholar 
    Kostecka, L. G., Pienta, K. J. & Amend, S. R. Polyaneuploid cancer cell dormancy: Lessons from evolutionary phyla. Front. Ecol. Evol. 9, 439 (2021).Article 

    Google Scholar 
    Rajaraman, R., Rajaraman, M. M., Rajaraman, S. R. & Guernsey, D. L. Neosis–a paradigm of self-renewal in cancer. Cell Biol. Int. 29(12), 1084–1097 (2005).CAS 
    PubMed 
    Article 

    Google Scholar 
    Rajaraman, R., Guernsey, D. L., Rajaraman, M. M. & Rajaraman, S. R. Neosis–A parasexual somatic reduction division in cancer. Int. J. Hum. Genet. 7(1), 29–48 (2007).CAS 
    Article 

    Google Scholar 
    Sundaram, M., Guernsey, D. L., Rajaraman, M. M. & Rajaraman, R. Neosis: A novel type of cell division in cancer. Cancer Biol. Ther. 3(2), 207–218 (2004).CAS 
    PubMed 
    Article 

    Google Scholar 
    Gatenby, R. A., Cunningham, J. J. & Brown, J. S. Evolutionary triage governs fitness in driver and passenger mutations and suggests targeting never mutations. Nat. Commun. 5(1), 1–9 (2014).Article 

    Google Scholar 
    Bukkuri, A. & Brown, J. S. Evolutionary game theory: Darwinian dynamics and the G function approach. MDPI Games 12(4), 1–19 (2021).MathSciNet 
    MATH 

    Google Scholar 
    Lopez-Sánchez, L. M. et al. CoCl2, a mimic of hypoxia, induces formation of polyploid giant cells with stem characteristics in colon cancer. PLoS ONE 9(6), e99143 (2014).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Mittal, K. et al. Multinucleated polyploidy drives resistance to Docetaxel chemotherapy in prostate cancer. Br. J. Cancer 116(9), 1186–1194 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Niu, N., Mercado-Uribe, I. & Liu, J. Dedifferentiation into blastomere-like cancer stem cells via formation of polyploid giant cancer cells. Oncogene 36(34), 4887–4900 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Ogden, A., Rida, P. C. G., Knudsen, B. S., Kucuk, O. & Aneja, R. Docetaxel-induced polyploidization may underlie chemoresistance and disease relapse. Cancer Lett. 367, 89–92 (2015).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Puig, P. E. et al. Tumor cells can escape DNA-damaging cisplatin through DNA endoreduplication and reversible polyploidy. Cell Biol. Int. 32(9), 1031–1043 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    Zhang, S. et al. Generation of cancer stem-like cells through the formation of polyploid giant cancer cells. Oncogene 33(1), 116–128 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    Lin, K. C. et al. The role of heterogeneous environment and docetaxel gradient in the emergence of polyploid, mesenchymal and resistant prostate cancer cells. Clin. Exp. Metastasis 36(2), 97–108 (2019).PubMed 
    Article 

    Google Scholar 
    Lin, K.-C. et al. Epithelial and mesenchymal prostate cancer cell population dynamics on a complex drug landscape. Converg. Sci. Phys. Oncol. 3(4), 045001 (2017).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Boe, L. Mechanism for induction of adaptive mutations in Escherichia coli. Mol. Microbiol. 4(4), 597–601 (1990).CAS 
    PubMed 
    Article 

    Google Scholar 
    Cairns, J. Mutation and cancer: The antecedents to our studies of adaptive mutation. Genetics 148(4), 1433–1440 (1998).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hall, B. G. Adaptive mutagenesis: A process that generates almost exclusively beneficial mutations. Genetica 102, 109 (1998).PubMed 
    Article 

    Google Scholar 
    Waddington, C. H. Genetic assimilation of an acquired character. Evolution 7(2), 118–126 (1953).Article 

    Google Scholar 
    Waddington, C. H. Genetic assimilation. Adv. Genet. 10, 257–293 (1961).CAS 
    PubMed 
    Article 

    Google Scholar 
    Jablonka, E. V. A. & Raz, G. A. L. Transgenerational epigenetic inheritance: Prevalence, mechanisms, and implications for the study of heredity and evolution. Q. Rev. Biol. 84(2), 131–176 (2009).PubMed 
    Article 

    Google Scholar 
    Steele, E. J. & Pollard, J. W. Hypothesis: Somatic hypermutation by gene conversion via the error prone DNA(longrightarrow )RNA(longrightarrow )DNA information loop. Mol. Immunol. 24(6), 667–673 (1987).CAS 
    PubMed 
    Article 

    Google Scholar 
    Steele, E. J. Somatic hypermutation in immunity and cancer: Critical analysis of strand-biased and codon-context mutation signatures. DNA Repair 45, 1–24 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Steele, E. J. Somatic Selection and Adaptive Evolution (Springer, US, 1979).
    Google Scholar 
    Steele, E. J., Lindley, R. A. & Blanden, R. V. Lamarck’s Signature (Perseus Books, 1998).
    Google Scholar 
    Foster, P. L. Adaptive mutation: Implications for evolution. Bioessays 22, 1067–1074 (2000).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    McCutcheon, J. P. & Moran, N. A. Extreme genome reduction in symbiotic bacteria. Nat. Rev. Microbiol. 10(1), 13–26 (2012).CAS 
    Article 

    Google Scholar 
    Badyaev, A. V. Stress-induced variation in evolution: From behavioural plasticity to genetic assimilation. Proc. R. Soc. B Biol. Sci. 272, 877–886 (2005).Article 

    Google Scholar 
    Bateman, K. G. The genetic assimilation of four venation phenocopies. J. Genet. 56(3), 443–474 (1959).Article 

    Google Scholar 
    Milkman, R. D. The genetic basis of natural variation. VI. Selection of a crossveinless strain of Drosophila by phenocopying at high temperature. Genetics 51(1), 87 (1965).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Waddington, C. H. Genetic assimilation of the bithorax phenotype. Evolution 10(1), 1–13 (1956).Article 

    Google Scholar 
    Godoy, O., Saldaña, A., Fuentes, N., Valladares, F. & Gianoli, E. Forests are not immune to plant invasions: Phenotypic plasticity and local adaptation allow Prunella vulgaris to colonize a temperate evergreen rainforest. Biol. Invasions 13(7), 1615–1625 (2011).Article 

    Google Scholar 
    Schlichting, C. D. & Wund, M. A. Phenotypic plasticity and epigenetic marking: An assessment of evidence for genetic accommodation. Evolution 68(3), 656–672 (2014).PubMed 
    Article 

    Google Scholar 
    Otaki, J. M., Hiyama, A., Iwata, M. & Kudo, T. Phenotypic plasticity in the range-margin population of the lycaenid butterfly Zizeeria maha. BMC Evol. Biol. 10(1), 1–13 (2010).Article 

    Google Scholar 
    Aubret, F. & Shine, R. Genetic assimilation and the postcolonization erosion of phenotypic plasticity in island tiger snakes. Curr. Biol. 19(22), 1932–1936 (2009).CAS 
    PubMed 
    Article 

    Google Scholar 
    Losos, J. B., Irschick, D. J. & Schoener, T. W. Adaptation and constraint in the evolution of specialization of Bahamian Anolis lizards. Evolution 48(6), 1786–1798 (1994).PubMed 
    Article 

    Google Scholar 
    Losos, J. B. et al. Evolutionary implications of phenotypic plasticity in the hindlimb of the lizard Anolis sagrei. Evolution 54(1), 301–305 (2000).CAS 
    PubMed 

    Google Scholar 
    Sword, G. A. Density-dependent warning coloration. Nature 397(6716), 217 (1999).ADS 
    CAS 
    Article 

    Google Scholar 
    Sword, G. A. A role for phenotypic plasticity in the evolution of aposematism. Proc. R. Soc. B Biol. Sci. 269(1501), 1639–1644 (2002).Article 

    Google Scholar 
    Clausen, J. & Hiesey, W. M. The balance between coherence and variation in evolution. Proc. Natl. Acad. Sci. 46(4), 494–506 (1960).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Gurevitch, J. Variation in leaf dissection and leaf energy budgets among populations of Achillea from an altitudinal gradient. Am. J. Bot. 75(9), 1298–1306 (1988).Article 

    Google Scholar 
    Gurevitch, J. & Schuepp, P. H. Boundary layer properties of highly dissected leaves: An investigation using an electrochemical fluid tunnel. Plant Cell Environ. 13(8), 783–792 (1990).Article 

    Google Scholar 
    Gurevitch, J. Sources of variation in leaf shape among two populations of Achillea lanulosa. Genetics 130(2), 385–394 (1992).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Foster, P. L. Stress-induced mutagenesis in bacteria. Crit. Rev. Biochem. Mol. Biol. 42(5), 373–397 (2007).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Soppa, J. Polyploidy in archaea and bacteria: About desiccation resistance, giant cell size, long-term survival, enforcement by a eukaryotic host and additional aspects. Microb. Physiol. 24, 409–419 (2014).ADS 
    CAS 
    Article 

    Google Scholar 
    Bastide, A. & David, A. The ribosome, (slow) beating heart of cancer (stem) cell. Oncogenesis 7(4), 1–13 (2018).CAS 
    Article 

    Google Scholar 
    Cairns, J., Overbaugh, J. & Miller, S. The origin of mutants. Nature 335, 142–145 (1988).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Foster, P. L. Adaptive mutation: The uses of adversity. Annu. Rev. Microbiol. 47, 467–504. https://doi.org/10.1146/annurev.mi.47.100193.002343 (2003).Article 

    Google Scholar 
    Lenski, R. E. & Mittler, J. E. The directed mutation controversy and neo-Darwinism. Science 259(5092), 188–194 (1993).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Lenski, R. E. & Sniegowski, P. D. “Adaptive mutation’’: The debate goes on. Science 269, 285–288 (1995).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Noller, H. F., Hoffarth, V. & Zimniak, L. Unusual resistance of peptidyl transferase to protein extraction procedures. Science 256(5062), 1416–1419 (1992).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Pribis, J. P. et al. Gamblers: An antibiotic-induced evolvable cell subpopulation differentiated by reactive-oxygen-induced general stress response. Mol. Cell 74(4), 785–800 (2019).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Silvera, D., Formenti, S. C. & Schneider, R. J. Translational control in cancer. Nat. Rev. Cancer 10(4), 254–266 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    Shcherbakov, D. et al. Ribosomal mistranslation leads to silencing of the unfolded protein response and increased mitochondrial biogenesis. Commun. Biol. 2(1), 1–16 (2019).CAS 
    Article 

    Google Scholar 
    Truitt, M. L. & Ruggero, D. New frontiers in translational control of the cancer genome. Nat. Rev. Cancer 16(5), 288–304 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Alphey, L. S., Crisanti, A., Randazzo, F. & Akbari, O. S. Opinion: Standardizing the definition of gene drive. Proc. Natl. Acad. Sci. USA 117(49), 30864 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Champer, J., Buchman, A. & Akbari, O. S. Cheating evolution: Engineering gene drives to manipulate the fate of wild populations. Nat. Rev. Genet. 17, 146–159 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Champer, S. E. et al. Modeling CRISPR gene drives for suppression of invasive rodents using a supervised machine learning framework. PLOS Comput. Biol. 17(12), e1009660 (2021).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Deredec, A., Burt, A. & Godfray, H. C. J. The population genetics of using homing endonuclease genes in vector and pest management. Genetics 179(4), 2013–2026 (2008).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Heffel, M. G. & Finnigan, G. C. Mathematical modeling of self-contained CRISPR gene drive reversal systems. Sci. Rep. 9(1), 1–10 (2019).Article 
    CAS 

    Google Scholar 
    Leftwich, P. T. et al. Recent advances in threshold-dependent gene drives for mosquitoes. Biochem. Soc. Trans. 46, 1203–1212 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Nijhout, H. F., Kudla, A. M. & Hazelwood, C. C. Genetic assimilation and accommodation: Models and mechanisms. Curr. Top. Dev. Biol. 141, 337–369 (2021).PubMed 
    Article 

    Google Scholar 
    Noble, C., Adlam, B., Church, G. M., Esvelt, K. M. & Nowak, M. A. Current CRISPR gene drive systems are likely to be highly invasive in wild populations. eLife 7, e33423 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Novozhilov, A. S., Karev, G. P. & Koonin, E. V. Mathematical modeling of evolution of horizontally transferred genes. Mol. Biol. Evol. 22(8), 1721–1732 (2005).CAS 
    PubMed 
    Article 

    Google Scholar 
    Pigliucci, M. & Murren, C. J. Perspective: Genetic assimilation and a possible evolutionary paradox: Can macroevolution sometimes be so fast as to pass us by?. Evolution 57, 1455–1464 (2003).PubMed 
    Article 

    Google Scholar 
    Hammerstein, P. Darwinian adaptation, population genetics and the streetcar theory of evolution. J. Math. Biol. 34(5–6), 511–532 (1996).CAS 
    PubMed 
    MATH 
    Article 

    Google Scholar 
    Dieckmann, U. Coevolutionary Dynamics of Stochastic Replicator Systems (Central Library of the Research Center Jülich, 1994).
    Google Scholar 
    Dieckmann, U., Marrow, P. & Law, R. Evolutionary cycling in predator-prey interactions: population dynamics and the red queen. J. Theor. Biol. 176(1), 91–102 (1995).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Dieckmann, U. & Law, R. The dynamical theory of coevolution: a derivation from stochastic ecological processes. J. Math. Biol. 34, 579–612 (1996).MathSciNet 
    CAS 
    PubMed 
    MATH 
    Article 

    Google Scholar 
    Metz, J. A. J., Nisbet, R. M. & Geritz, S. A. H. How should we define ‘fitness’ for general ecological scenarios?. Trends Ecol. Evol. 7(6), 198–202 (1992).CAS 
    PubMed 
    Article 

    Google Scholar 
    Goldschmidt, R. Some aspects of evolution. Science 78(2033), 539–547 (1933).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Vincent, T. L., Cohen, Y. & Brown, J. S. Evolution via strategy dynamics. Theor. Popul. Biol. 44(2), 149–176 (1993).MATH 
    Article 

    Google Scholar 
    Bell, G. Evolutionary rescue. Annu. Rev. Ecol. Evol. Syst. 48, 605–627 (2017).Article 

    Google Scholar  More

  • in

    Combining multi-marker metabarcoding and digital holography to describe eukaryotic plankton across the Newfoundland Shelf

    Lombard, F. et al. Consistent quantitative observations of planktonic ecosystems. Front. Mar. Sci. 6, 196. https://doi.org/10.3389/fmars.2019.00196 (2019).Article 

    Google Scholar 
    Sieracki, M. E., et al. Optical plankton imaging and analysis systems for ocean observation. Proceedings of OceanObs’09: Sustained Ocean Observations and Information for Society, 878–885 (2010). https://doi.org/10.5270/OceanObs09.cwp.81.Irisson, J.-O., Ayata, S.-D., Lindsay, D. J., Karp-Boss, L. & Stemmann, L. Machine learning for the study of plankton and marine snow from images. Ann. Rev. Mar. Sci. 14(1), 277. https://doi.org/10.1146/annurev-marine-041921-013023 (2022).Article 
    PubMed 

    Google Scholar 
    Mars Brisbin, M., Brunner, O. D., Grossmann, M. M. & Mitarai, S. Paired high-throughput, in situ imaging and high-throughput sequencing illuminate acantharian abundance and vertical distribution. Limnol. Oceanogr. 65(12), 2953–2965. https://doi.org/10.1002/lno.11567 (2020).ADS 
    CAS 
    Article 

    Google Scholar 
    Benfield, M. et al. RAPID: Research on automated plankton identification. Oceanography 20(2), 172–187. https://doi.org/10.5670/oceanog.2007.63 (2007).Article 

    Google Scholar 
    Colin, S. et al. Quantitative 3D-imaging for cell biology and ecology of environmental microbial eukaryotes. Elife 6, e26066. https://doi.org/10.7554/eLife.26066 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kim, M. K. Principles and techniques of digital holographic microscopy. J. Photonics Energy. 1, 018005. https://doi.org/10.1117/6.0000006 (2010).Article 

    Google Scholar 
    Tahara, T., Quan, X., Otani, R., Takaki, Y. & Matoba, O. Digital holography and its multidimensional imaging applications: A review. Microscopy 67(2), 55–67. https://doi.org/10.1093/jmicro/dfy007 (2018).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jericho, S. K., Garcia-Sucerquia, J. F. W., Jericho, M. H. & Kreuzer, H. J. Submersible digital in-line holographic microscope. Rev. Sci. Instrum. 77(4), 043706. https://doi.org/10.1063/1.2193827 (2006).ADS 
    CAS 
    Article 

    Google Scholar 
    Bochdansky, A. B., Jericho, M. H. & Herndl, G. J. Development and deployment of a point-source digital inline holographic microscope for the study of plankton and particlesto a depth of 6000 m. Limnol. Oceanogr: Methods 11, 28–40 (2013).Article 

    Google Scholar 
    Yourassowsky, C. & Dubois, F. High throughput holographic imaging-in-flow for the analysis of a wide plankton size range. Opt. Express 22(6), 6661. https://doi.org/10.1364/OE.22.006661 (2014).ADS 
    Article 
    PubMed 

    Google Scholar 
    Jericho, M. H. & Kreuzer, H. J. Point source digital in-line holographic microscopy. In Coherent Light Microscopy (eds Ferraro, P. et al.) 3–30 (Springer, 2011).Chapter 

    Google Scholar 
    Kanka, M., Riesenberg, R. & Kreuzer, H. J. Reconstruction of high-resolution holographic microscopic images. Opt. Lett. 34(8), 1162. https://doi.org/10.1364/OL.34.001162 (2009).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    Jericho, M. H., Kreuzer, H. J., Kanka, M. & Riesenberg, R. Quantitative phase and refractive index measurements with point-source digital in-line holographic microscopy. Appl. Opt. 51(10), 1503. https://doi.org/10.1364/AO.51.001503 (2012).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    Wu, Y. & Ozcan, A. Lensless digital holographic microscopy and its applications in biomedicine and environmental monitoring. Methods 136, 4–16 (2018).CAS 
    Article 

    Google Scholar 
    Sun, H. et al. digital holography for studies of marine plankton. Philos. Trans. R. Soc. A. 366, 1789–1806 (2008).ADS 
    CAS 
    Article 

    Google Scholar 
    Bianco, V. et al. microplastic identification via holographic imaging and machine learning. Adv. Intell. Syst. 2(2), 1900153. https://doi.org/10.1002/aisy.201900153 (2020).Article 

    Google Scholar 
    Guo, B. et al. Automated plankton classification from holographic imagery with deep convolutional neural networks. Limnol. Oceanogr. 19(1), 21–36. https://doi.org/10.1002/lom3.10402 (2021).Article 

    Google Scholar 
    Nayak, A. R., Malkiel, E., McFarland, M. N., Twardowski, M. S. & Sullivan, J. M. A Review of holography in the aquatic sciences: In situ characterization of particles, plankton, and small scale biophysical interactions. Front. Mar. Sci. 7, 572147. https://doi.org/10.3389/fmars.2020.572147 (2021).Article 

    Google Scholar 
    Di Bella, J. M., Bao, Y., Gloor, G. B., Burton, J. P. & Reid, G. High throughput sequencing methods and analysis for microbiome research. J. Microbiol. Methods 95(3), 401–414. https://doi.org/10.1016/j.mimet.2013.08.011 (2013).CAS 
    Article 
    PubMed 

    Google Scholar 
    Stoeck, T. et al. Multiple marker parallel tag environmental DNA sequencing reveals a highly complex eukaryotic community in marine anoxic water. Mol. Ecol. 19, 21–31. https://doi.org/10.1111/j.1365-294X.2009.04480.x (2010).CAS 
    Article 
    PubMed 

    Google Scholar 
    de Vargas, C. et al. Eukaryotic plankton diversity in the sunlit ocean. Science 348(6237), 1261605–1261605. https://doi.org/10.1126/science.1261605 (2015).CAS 
    Article 
    PubMed 

    Google Scholar 
    Lima-Mendez, G. et al. Determinants of community structure in the global plankton interactome. Science 348(6237), 1262073–1262073. https://doi.org/10.1126/science.1262073 (2015).CAS 
    Article 
    PubMed 

    Google Scholar 
    Santoferrara, L. et al. Perspectives from ten years of protist studies by high-throughput metabarcoding. J. Eukaryot. Microbiol. 67(5), 612–622. https://doi.org/10.1111/jeu.12813 (2020).Article 
    PubMed 

    Google Scholar 
    Eickbush, T. H. & Eickbush, D. G. Finely orchestrated movements: evolution of the ribosomal RNA genes. Genetics 175(2), 477–485. https://doi.org/10.1534/genetics.107.071399 (2007).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kirkham, A. R. et al. Basin-scale distribution patterns of photosynthetic picoeukaryotes along an Atlantic Meridional Transect: Marine photosynthetic picoeukaryote community structure. Environ. Microbiol. 13(4), 975–990. https://doi.org/10.1111/j.1462-2920.2010.02403.x (2011).CAS 
    Article 
    PubMed 

    Google Scholar 
    Decelle, J. et al. PhytoREF: A reference database of the plastidial 16S rRNA gene of photosynthetic eukaryotes with curated taxonomy. Mol. Ecol. Resour. 15(6), 1435–1445. https://doi.org/10.1111/1755-0998.12401 (2015).CAS 
    Article 
    PubMed 

    Google Scholar 
    Leray, M. & Knowlton, N. Censusing marine eukaryotic diversity in the twenty-first century. Phil. Trans. R. Soc. B. 371(1702), 20150331. https://doi.org/10.1098/rstb.2015.0331 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Cowart, D. A. et al. Metabarcoding is powerful yet still blind: A comparative analysis of morphological and molecular surveys of seagrass communities. PLoS ONE 10(2), e0117562. https://doi.org/10.1371/journal.pone.0117562 (2015).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Stefanni, S. et al. Multi-marker metabarcoding approach to study mesozooplankton at basin scale. Sci. Rep. 8(1), 12085. https://doi.org/10.1038/s41598-018-30157-7 (2018).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pappalardo, P. et al. The role of taxonomic expertise in interpretation of metabarcoding studies. ICES J. Mar. Sci. https://doi.org/10.1093/icesjms/fsab082 (2021).Article 

    Google Scholar 
    Gloor, G. B., Macklaim, J. M., Pawlowsky-Glahn, V. & Egozcue, J. J. Microbiome datasets are compositional: And this is not optional. Front. Microbiol. 8, 2224. https://doi.org/10.3389/fmicb.2017.02224 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Zhu, F., Massana, R., Not, F., Marie, D. & Vaulot, D. Mapping of picoeucaryotes in marine ecosystems with quantitative PCR of the 18S rRNA gene. FEMS Microbiol. Ecol. 52(1), 79–92. https://doi.org/10.1016/j.femsec.2004.10.006 (2005).CAS 
    Article 
    PubMed 

    Google Scholar 
    Sargent, E. C. et al. Evidence for polyploidy in the globally important diazotroph Trichodesmium. FEMS Microbiol. Lett. 363(21), 244. https://doi.org/10.1093/femsle/fnw244 (2016).CAS 
    Article 

    Google Scholar 
    Gong, W. & Marchetti, A. Estimation of 18S gene copy number in marine eukaryotic plankton using a next-generation sequencing approach. Front. Mar. Sci. 6, 219. https://doi.org/10.3389/fmars.2019.00219 (2019).Article 

    Google Scholar 
    Biard, T. et al. Biogeography and diversity of collodaria (radiolaria) in the global ocean. ISME J. 11, 1331–1344 (2017).Article 

    Google Scholar 
    Callahan, B. J., McMurdie, P. J. & Holmes, S. P. Exact sequence variants should replace operational taxonomic units in marker-gene data analysis. ISME J. 11(12), 2639–2643. https://doi.org/10.1038/ismej.2017.119 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Behrenfeld, M. J. et al. The North Atlantic aerosol and marine ecosystem study (NAAMES): Science motive and mission overview. Front. Mar. Sci. 6, 122. https://doi.org/10.3389/fmars.2019.00122 (2019).Article 

    Google Scholar 
    Bolaños, L. M. et al. Seasonality of the microbial community composition in the North Atlantic. Front. Mar. Sci. 8, 624164. https://doi.org/10.3389/fmars.2021.624164 (2021).Article 

    Google Scholar 
    Aitchison, J. The statistical analysis of compositional data. J. R. Stat. Soc. B 44(2), 139–160. https://doi.org/10.1111/j.2517-6161.1982.tb01195.x (1982).MathSciNet 
    Article 
    MATH 

    Google Scholar 
    Decelle, J. & Not, F. Acantharia. ELS, 1–10 (2015). https://doi.org/10.1002/9780470015902.a0002102.pub2.Yu, L., An, Y. & Cai, L. Numerical reconstruction of digital holograms with variable viewing angles. Opt. Express 10(22), 1250. https://doi.org/10.1364/OE.10.001250 (2002).ADS 
    Article 
    PubMed 

    Google Scholar 
    Della Penna, A. & Gaube, P. Overview of (sub)mesoscale Ocean dynamics for the NAAMES field program. Front. Mar. Sci. 6, 384. https://doi.org/10.3389/fmars.2019.00384 (2019).Article 

    Google Scholar 
    Sverdrup, H. U. Oceanography for Meteorologists (Prentice Hall, 1942).Book 

    Google Scholar 
    Mahadevan, A. The impact of submesoscale physics on primary productivity of plankton. Annu. Rev. Mar. Sci. 8(1), 161–184. https://doi.org/10.1146/annurev-marine-010814-015912 (2016).ADS 
    Article 

    Google Scholar 
    Fratantoni, P. S. & Pickart, R. S. The Western North Atlantic shelfbreak current system in summer. J. Phys. Oceanogr. 37(10), 2509–2533. https://doi.org/10.1175/JPO3123.1 (2007).ADS 
    Article 

    Google Scholar 
    Bolaños, L. M. et al. Small phytoplankton dominate western North Atlantic biomass. ISME J. 14(7), 1663–1674. https://doi.org/10.1038/s41396-020-0636-0 (2020).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kramer, S. J., Siegel, D. A. & Graff, J. R. Phytoplankton community composition determined from co-variability among phytoplankton pigments from the NAAMES field campaign. Front. Mar. Sci. 7, 215. https://doi.org/10.3389/fmars.2020.00215 (2020).Article 

    Google Scholar 
    Faure, E. et al. Mixotrophic protists display contrasted biogeographies in the global ocean. ISME J. 13(4), 1072–1083. https://doi.org/10.1038/s41396-018-0340-5 (2019).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Fratantoni, P. S. & McCartney, M. S. Freshwater export from the labrador current to the North Atlantic Current at the tail of the grand banks of Newfoundland. Deep Sea Res. I. 57(2), 258–283. https://doi.org/10.1016/j.dsr.2009.11.006 (2010).Article 

    Google Scholar 
    Torti, A., Lever, M. A. & Jørgensen, B. B. Origin, dynamics, and implications of extracellular DNA pools in marine sediments. Mar. Genom. 24, 185–196. https://doi.org/10.1016/j.margen.2015.08.007 (2015).Article 

    Google Scholar 
    Jian, C., Salonen, A. & Korpela, K. Commentary: How to count our microbes? The effect of different quantitative microbiome profiling approaches. Front. Cell. Infect. Microbiol. 11, 627910. https://doi.org/10.3389/fcimb.2021.627910 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Djurhuus, A. et al. Evaluation of marine zooplankton community structure through environmental DNA metabarcoding: Metabarcoding zooplankton from eDNA. Limnol. Oceanogr. Methods 16(4), 209–221. https://doi.org/10.1002/lom3.10237 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    del Campo, J. et al. The others: Our biased perspective of eukaryotic genomes. Trends Ecol. Evol. 29(5), 252–259. https://doi.org/10.1016/j.tree.2014.03.006 (2014).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Karst, S. M. et al. Retrieval of a million high-quality, full-length microbial 16S and 18S rRNA gene sequences without primer bias. Nat. Biotech. 36(2), 190–195. https://doi.org/10.1038/nbt.4045 (2018).CAS 
    Article 

    Google Scholar 
    Johnson, J. S. et al. Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis. Nat. Commun. 10(1), 5029. https://doi.org/10.1038/s41467-019-13036-1 (2019).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Callahan, B. J. et al. High-throughput amplicon sequencing of the full-length 16S rRNA gene with single-nucleotide resolution. Nucleic Acids Res. 47(18), e103–e103. https://doi.org/10.1093/nar/gkz569 (2019).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lin, Y., Gifford, S., Ducklow, H., Schofield, O. & Cassar, N. Towards quantitative microbiome community profiling using internal standards. Appl. Environ. Microbiol. 85(5), 18. https://doi.org/10.1128/AEM.02634-18 (2019).Article 

    Google Scholar 
    Vogt, M. et al. Global marine plankton functional type biomass distributions: Phaeocystis spp. Earth Syst. Sci. Data 5, 405–443. https://doi.org/10.5194/essdd-5-405-2012 (2012).ADS 
    Article 

    Google Scholar 
    MacNeil, L., Missan, S., Luo, J., Trappenberg, T. & LaRoche, J. Plankton classification with high-throughput submersible holographic microscopy and transfer learning. BMC Ecol. Evol. 21(1), 123. https://doi.org/10.1186/s12862-021-01839-0 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pan, J., del Campo, J. & Keeling, P. J. Reference tree and environmental sequence diversity of labyrinthulomycetes. J. Eukary. Microbiol. 64(1), 88–96. https://doi.org/10.1111/jeu.12342 (2017).Article 

    Google Scholar 
    Bochdansky, A. B., Clouse, M. A. & Herndl, G. J. Eukaryotic microbes, principally fungi and labyrinthulomycetes, dominate biomass on bathypelagic marine snow. ISME J. 11(2), 362–373. https://doi.org/10.1038/ismej.2016.113 (2017).Article 
    PubMed 

    Google Scholar 
    Xie, N., Hunt, D. E., Johnson, Z. I., He, Y. & Wang, G. Annual partitioning patterns of Labyrinthulomycetes protists reveal their multifaceted role in marine microbial food webs. Appl. Environ. Microbiol. https://doi.org/10.1128/AEM.01652-20 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Walcutt, N. L. et al. Assessment of holographic microscopy for quantifying marine particle size and concentration. Limnol. Oceanogr. Methods 3, 10379. https://doi.org/10.1002/lom3.10379 (2020).Article 

    Google Scholar 
    Axler, K. et al. Fine-scale larval fish distributions and predator-prey dynamics in a coastal river-dominated ecosystem. Mar. Ecol. Prog. Ser. 650, 37–61. https://doi.org/10.3354/meps13397 (2020).ADS 
    Article 

    Google Scholar 
    Trudnowska, E. et al. Marine snow morphology illuminates the evolution of phytoplankton blooms and determines their subsequent vertical export. Nat. Commun. 12(1), 2816. https://doi.org/10.1038/s41467-021-22994-4 (2021).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    González, P. et al. Automatic plankton quantification using deep features. J. Plankton Res. 41(4), 449–463. https://doi.org/10.1093/plankt/fbz023 (2019).Article 

    Google Scholar 
    Briseño-Avena, C. et al. Three-dimensional cross-shelf zooplankton distributions off the Central Oregon Coast during anomalous oceanographic conditions. Prog. Oceanogr. 188, 102436. https://doi.org/10.1016/j.pocean.2020.102436 (2020).Article 

    Google Scholar 
    Biard, T. et al. In situ imaging reveals the biomass of giant protists in the global ocean. Nature 532, 504–507 (2016).ADS 
    CAS 
    Article 

    Google Scholar 
    Orenstein, E. C. et al. The scripps plankton camera system: A framework and platform for in situ microscopy. Limnol. Oceanogr. Methods 18(11), 681–695. https://doi.org/10.1002/lom3.10394 (2020).Article 

    Google Scholar 
    Fowler, B. L. et al. Dynamics and functional diversity of the smallest phytoplankton on the Northeast US Shelf. PNAS 117(22), 12215–12221. https://doi.org/10.1073/pnas.1918439117 (2020).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Tréguer, P. et al. Influence of diatom diversity on the ocean biological carbon pump. Nat. Geosci. 11(1), 27–37. https://doi.org/10.1038/s41561-017-0028-x (2018).ADS 
    CAS 
    Article 

    Google Scholar 
    Ryabov, A. et al. Shape matters: The relationship between cell geometry and diversity in phytoplankton. Ecol. Lett. 24(4), 847–861. https://doi.org/10.1111/ele.13680 (2021).MathSciNet 
    Article 
    PubMed 

    Google Scholar 
    Keeling, P. J. & del Campo, J. marine protists are not just big bacteria. Curr. Biol. 27(11), R541–R549. https://doi.org/10.1016/j.cub.2017.03.075 (2017).CAS 
    Article 
    PubMed 

    Google Scholar 
    Sgubin, G., Swingedouw, D., Drijfhout, S., Mary, Y. & Bennabi, A. Abrupt cooling over the North Atlantic in modern climate models. Nat. Commun. 8(1), 14375. https://doi.org/10.1038/ncomms14375 (2017).CAS 
    Article 
    PubMed Central 

    Google Scholar 
    Desbruyères, D., Chafik, L. & Maze, G. A shift in the ocean circulation has warmed the subpolar North Atlantic Ocean since 2016. Commun. Earth Environ. 2(1), 48. https://doi.org/10.1038/s43247-021-00120-y (2021).ADS 
    Article 

    Google Scholar 
    Mitchell, M. R. et al. Atlantic zone monitoring program protocol. Can. Tech. Rep. Hydrogr. Ocean Sci. 223, 1–23 (2002).
    Google Scholar 
    Li, W. K. W., Glen Harrison, W. & Head, E. J. H. Coherent assembly of phytoplankton communities in diverse temperate ocean ecosystems. Proc. R. Soc. B. 273(1596), 1953–1960. https://doi.org/10.1098/rspb.2006.3529 (2006).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Richardson, P. L. Florida current, gulf stream, and labrador current. In Encyclopedia of Ocean Sciences (ed. Steele, J. H.) 1054–1064 (Academic Press, 2001). https://doi.org/10.1006/rwos.2001.0357.Chapter 

    Google Scholar 
    Henson, S. A., Dunne, J. P. & Sarmiento, J. L. Decadal variability in North Atlantic phytoplankton blooms. J. Geophys. Res. 114(C4), C04013. https://doi.org/10.1029/2008JC005139 (2009).ADS 
    CAS 
    Article 

    Google Scholar 
    Han, G., Lu, Z., Wang, Z., Helbig, J. & Chen, N. Seasonal variability of the labrador current and shelf circulation off Newfoundland. J. Geophys. Res. 113, 10. https://doi.org/10.1029/2007JC004376 (2008).Article 

    Google Scholar 
    Pante, E. & Simon-Bouhet, B. marmap: A package for importing, plotting and analyzing bathymetric and topographic data in R. PLoS ONE 8(9), e73051. https://doi.org/10.1371/journal.pone.0073051 (2013).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kelley, D. “The Oce Package” In Oceanographic Analysis with R 91–101 (Springer, 2018).Book 

    Google Scholar 
    Oksanen, J., et al. vegan: Community Ecology Package. R package version 2.5-7 (2020). https://CRAN.R-project.org/package=vegan.Tomas, C. R. Identifying Marine Phytoplankton (Academic Press Inc, 1997).
    Google Scholar 
    Comeau, A. M., Li, W. K. W., Tremblay, J. -É., Carmack, E. C. & Lovejoy, C. Arctic ocean microbial community structure before and after the 2007 record sea ice minimum. PLoS ONE 6(11), e27492. https://doi.org/10.1371/journal.pone.0027492 (2011).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Parada, A. E., Needham, D. M. & Fuhrman, J. A. Every base matters: Assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples: Primers for marine microbiome studies. Environ. Microbiol. 18(5), 1403–1414. https://doi.org/10.1111/1462-2920.13023 (2016).CAS 
    Article 
    PubMed 

    Google Scholar 
    Walters, W. et al. Improved bacterial 16S rRNA gene (V4 and V4–5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. MSystems https://doi.org/10.1128/mSystems.00009-15 (2016).Article 
    PubMed 

    Google Scholar 
    Comeau, A. M., Douglas, G. M. & Langille, M. G. I. Microbiome helper: A custom and streamlined workflow for microbiome research. MSystems 2(1), e00127-e216. https://doi.org/10.1128/mSystems.00127-16 (2017).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotech. 37(8), 852–857. https://doi.org/10.1038/s41587-019-0209-9 (2019).CAS 
    Article 

    Google Scholar 
    Amir, A. et al. Deblur rapidly resolves single-nucleotide community sequence patterns. MSystems 2(2), e00191-e216. https://doi.org/10.1128/mSystems.00191-16 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Guillou, L. et al. The protist ribosomal reference database (PR2): A catalog of unicellular eukaryote small sub-unit rRNA sequences with curated taxonomy. Nucleic Acids Res. 41(D1), D597–D604. https://doi.org/10.1093/nar/gks1160 (2013).CAS 
    Article 
    PubMed 

    Google Scholar 
    Mohsen, A., Park, J., Chen, Y.-A., Kawashima, H. & Mizuguchi, K. Impact of quality trimming on the efficiency of reads joining and diversity analysis of Illumina paired-end reads in the context of QIIME1 and QIIME2 microbiome analysis frameworks. BMC Bioinform. 20(1), 581. https://doi.org/10.1186/s12859-019-3187-5 (2019).Article 

    Google Scholar 
    Bokulich, N. A. et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6(1), 90. https://doi.org/10.1186/s40168-018-0470-z (2018).MathSciNet 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Quast, C. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 41(D1), D590–D596. https://doi.org/10.1093/nar/gks1219 (2012).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2021). https://www.R-project.org/.McMurdie, P. J. & Holmes, S. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8(4), e61217. https://doi.org/10.1371/journal.pone.0061217 (2013).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Willis, A. & Bunge, J. Estimating diversity via frequency ratios: estimating diversity via ratios. Biometrics 71(4), 1042–1049. https://doi.org/10.1111/biom.12332 (2015).MathSciNet 
    Article 
    PubMed 
    MATH 

    Google Scholar 
    Willis, A. D. Rarefaction, alpha diversity, and statistics. Front. Microbiol. 10, 2407. https://doi.org/10.3389/fmicb.2019.02407 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Quinn, T. P. et al. A field guide for the compositional analysis of any-omics data. GigaScience 8(9), 107. https://doi.org/10.1093/gigascience/giz107 (2019).CAS 
    Article 

    Google Scholar 
    Silverman, J. D., Roche, K., Mukherjee, S. & David, L. A. Naught all zeros in sequence count data are the same. Comput. Struct. Biotech. J. 18, 2789–2798. https://doi.org/10.1016/j.csbj.2020.09.014 (2020).CAS 
    Article 

    Google Scholar 
    Anderson, M. J. A new method for non-parametric multivariate analysis of variance. Austral. Ecol. 26, 32–46 (2001).
    Google Scholar  More

  • in

    Microbiota succession throughout life from the cradle to the grave

    Chu, D. M. et al. Maturation of the infant microbiome community structure and function across multiple body sites and in relation to mode of delivery. Nat. Med. 23, 314–326 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Ward, T. L. et al. Development of the human mycobiome over the first month of life and across body sites. mSystems 3, e00140–17 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Oh, J. et al. Biogeography and individuality shape function in the human skin metagenome. Nature 514, 59–64 (2014).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Abeles, S. R. et al. Human oral viruses are personal, persistent and gender-consistent. ISME J. 8, 1753–1767 (2014).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Grice, E. A. & Segre, J. A. The human microbiome: our second genome. Annu. Rev. Genomics Hum. Genet. 13, 151–170 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Lauber, C. L., Hamady, M., Knight, R. & Fierer, N. Pyrosequencing-based assessment of soil pH as a predictor of soil bacterial community structure at the continental scale. Appl. Environ. Microbiol. 75, 5111–5120 (2009).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Zengler, K. & Zaramela, L. S. The social network of microorganisms – how auxotrophies shape complex communities. Nat. Rev. Microbiol. 16, 383–390 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Smits, S. A. et al. Seasonal cycling in the gut microbiome of the Hadza hunter-gatherers of Tanzania. Science 357, 802–806 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Rasko, D. A. Changes in microbiome during and after travellers’ diarrhea: what we know and what we do not. J. Travel. Med. 24, S52–S56 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Zheng, D., Liwinski, T. & Elinav, E. Interaction between microbiota and immunity in health and disease. Cell Res. 30, 492–506 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Zaneveld, J. R., McMinds, R. & Vega Thurber, R. Stress and stability: applying the Anna Karenina principle to animal microbiomes. Nat. Microbiol. 2, 17121 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Dini-Andreote, F., Stegen, J. C., van Elsas, J. D. & Salles, J. F. Disentangling mechanisms that mediate the balance between stochastic and deterministic processes in microbial succession. Proc. Natl Acad. Sci. USA 112, E1326–E1332 (2015).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Dominguez-Bello, M. G. et al. Delivery mode shapes the acquisition and structure of the initial microbiota across multiple body habitats in newborns. Proc. Natl Acad. Sci. USA 107, 11971–11975 (2010).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Yassour, M. et al. Natural history of the infant gut microbiome and impact of antibiotic treatment on bacterial strain diversity and stability. Sci. Transl. Med. 8, 343ra81 (2016).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Bokulich, N. A. et al. Antibiotics, birth mode, and diet shape microbiome maturation during early life. Sci. Transl. Med. 8, 343ra82 (2016).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    David, L. A. et al. Host lifestyle affects human microbiota on daily timescales. Genome Biol. 15, R89 (2014).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Vangay, P. et al. US immigration westernizes the human gut microbiome. Cell 175, 962–972.e10 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Yatsunenko, T. et al. Human gut microbiome viewed across age and geography. Nature 486, 222–227 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Gregory, A. C. et al. The gut virome database reveals age-dependent patterns of virome diversity in the human gut. Cell Host Microbe 28, 724–740.e8 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Faith, J. J. et al. The long-term stability of the human gut microbiota. Science 341, 1237439 (2013).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Thaiss, C. A. et al. Microbiota diurnal rhythmicity programs host transcriptome oscillations. Cell 167, 1495–1510.e12 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Zaura, E. et al. Same exposure but two radically different responses to antibiotics: resilience of the salivary microbiome versus long-term microbial shifts in feces. mBio 6, e01693–15 (2015).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Dethlefsen, L. & Relman, D. A. Incomplete recovery and individualized responses of the human distal gut microbiota to repeated antibiotic perturbation. Proc. Natl Acad. Sci. USA 108 (Suppl. 1), 4554–4561 (2011).CAS 
    PubMed 
    Article 

    Google Scholar 
    Hsiao, A. et al. Members of the human gut microbiota involved in recovery from Vibrio cholerae infection. Nature 515, 423–426 (2014).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Chng, K. R. et al. Metagenome-wide association analysis identifies microbial determinants of post-antibiotic ecological recovery in the gut. Nat. Ecol. Evol. 4, 1256–1267 (2020).PubMed 
    Article 

    Google Scholar 
    Gibbons, S. M. Keystone taxa indispensable for microbiome recovery. Nat. Microbiol. 5, 1067–1068 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Rizzatti, G., Lopetuso, L. R., Gibiino, G., Binda, C. & Gasbarrini, A. Proteobacteria: a common factor in human diseases. Biomed. Res. Int. 2017, 9351507 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Biagi, E. et al. Gut microbiota and extreme longevity. Curr. Biol. 26, 1480–1485 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Lim, A. I. et al. Prenatal maternal infection promotes tissue-specific immunity and inflammation in offspring. Science 373, eabf3002 (2021).CAS 
    PubMed 
    Article 

    Google Scholar 
    Al Nabhani, Z. & Eberl, G. Imprinting of the immune system by the microbiota early in life. Mucosal Immunol. 13, 183–189 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Lynn, M. A. et al. Early-life antibiotic-driven dysbiosis leads to dysregulated vaccine immune responses in mice. Cell Host Microbe 23, 653–660.e5 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Blaser, M. J. The theory of disappearing microbiota and the epidemics of chronic diseases. Nat. Rev. Immunol. 17, 461–463 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Thorburn, A. N. et al. Evidence that asthma is a developmental origin disease influenced by maternal diet and bacterial metabolites. Nat. Commun. 6, 7320 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Gomez de Agüero, M. et al. The maternal microbiota drives early postnatal innate immune development. Science 351, 1296–1302 (2016).PubMed 
    Article 
    CAS 

    Google Scholar 
    Macpherson, A. J., de Agüero, M. G. & Ganal-Vonarburg, S. C. How nutrition and the maternal microbiota shape the neonatal immune system. Nat. Rev. Immunol. 17, 508–517 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Nakajima, A. et al. Maternal high fiber diet during pregnancy and lactation influences regulatory T cell differentiation in offspring in mice. J. Immunol. 199, 3516–3524 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Jamalkandi, S. A. et al. Oral and nasal probiotic administration for the prevention and alleviation of allergic diseases, asthma and chronic obstructive pulmonary disease. Nutr. Res. Rev. 34, 1–16 (2021).CAS 
    PubMed 
    Article 

    Google Scholar 
    Örtqvist, A. K., Lundholm, C., Halfvarson, J., Ludvigsson, J. F. & Almqvist, C. Fetal and early life antibiotics exposure and very early onset inflammatory bowel disease: a population-based study. Gut 68, 218–225 (2019).PubMed 
    Article 
    CAS 

    Google Scholar 
    Munyaka, P. M., Eissa, N., Bernstein, C. N., Khafipour, E. & Ghia, J.-E. Antepartum antibiotic treatment increases offspring susceptibility to experimental colitis: a role of the gut microbiota. PLoS ONE 10, e0142536 (2015).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Kiss, E. A. et al. Natural aryl hydrocarbon receptor ligands control organogenesis of intestinal lymphoid follicles. Science 334, 1561–1565 (2011).CAS 
    PubMed 
    Article 

    Google Scholar 
    Lee, J. S. et al. AHR drives the development of gut ILC22 cells and postnatal lymphoid tissues via pathways dependent on and independent of Notch. Nat. Immunol. 13, 144–151 (2011).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Qiu, J. et al. The aryl hydrocarbon receptor regulates gut immunity through modulation of innate lymphoid cells. Immunity 36, 92–104 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    Schulfer, A. F. et al. Intergenerational transfer of antibiotic-perturbed microbiota enhances colitis in susceptible mice. Nat. Microbiol. 3, 234–242 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Ma, J. et al. High-fat maternal diet during pregnancy persistently alters the offspring microbiome in a primate model. Nat. Commun. 5, 3889 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    Torres, J. et al. Infants born to mothers with IBD present with altered gut microbiome that transfers abnormalities of the adaptive immune system to germ-free mice. Gut 69, 42–51 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Milliken, S., Allen, R. M. & Lamont, R. F. The role of antimicrobial treatment during pregnancy on the neonatal gut microbiome and the development of atopy, asthma, allergy and obesity in childhood. Expert. Opin. Drug. Saf. 18, 173–185 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Santacruz, A. et al. Gut microbiota composition is associated with body weight, weight gain and biochemical parameters in pregnant women. Br. J. Nutr. 104, 83–92 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    Trevisanuto, D. et al. Fetal placental inflammation is associated with poor neonatal growth of preterm infants: a case-control study. J. Matern. Fetal Neonatal Med. 26, 1484–1490 (2013).PubMed 
    Article 

    Google Scholar 
    Song, S. J. et al. Naturalization of the microbiota developmental trajectory of Cesarean-born neonates after vaginal seeding. Med 2, 951–964.e5 (2021).CAS 
    PubMed 
    Article 

    Google Scholar 
    Abu-Raya, B., Michalski, C., Sadarangani, M. & Lavoie, P. M. Maternal immunological adaptation during normal pregnancy. Front. Immunol. 11, 575197 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hanson, L. A. et al. The transfer of immunity from mother to child. Ann. NY. Acad. Sci. 987, 199–206 (2003).CAS 
    PubMed 
    Article 

    Google Scholar 
    Dominguez-Bello, M. G. et al. Partial restoration of the microbiota of cesarean-born infants via vaginal microbial transfer. Nat. Med. 22, 250–253 (2016). This study demonstrates that ‘seeding’ infants born by caesarean delivery with the vaginal microbiota of the mother at birth partially naturalizes development of the microbial community.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Ferretti, P. et al. Mother-to-infant microbial transmission from different body sites shapes the developing infant gut microbiome. Cell Host Microbe 24, 133–145.e5 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Helve, O. et al. 2843. Maternal fecal transplantation to infants born by cesarean section: safety and feasibility. Open. Forum Infect. Dis. 6, S68 (2019).PubMed Central 
    Article 

    Google Scholar 
    Subramanian, S. et al. Persistent gut microbiota immaturity in malnourished Bangladeshi children. Nature 510, 417–421 (2014). This study shows that severe acute malnutrition leads to immature microbial development and introduces a metric for the measure of microbiota maturity.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Palmer, C., Bik, E. M., DiGiulio, D. B., Relman, D. A. & Brown, P. O. Development of the human infant intestinal microbiota. PLoS Biol. 5, e177 (2007).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Groer, M. W. et al. Development of the preterm infant gut microbiome: a research priority. Microbiome 2, 38 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Henrick, B. M. et al. Bifidobacteria-mediated immune system imprinting early in life. Cell 184, 3884–3898.e11 (2021). This report describes the immune development driven by microbial interactions and the negative impact of lack of HMO-utilizing microorganisms on the immune system.CAS 
    PubMed 
    Article 

    Google Scholar 
    Sela, D. A. & Mills, D. A. Nursing our microbiota: molecular linkages between bifidobacteria and milk oligosaccharides. Trends Microbiol. 18, 298–307 (2010).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Seppo, A. E. et al. Infant gut microbiome is enriched with Bifidobacterium longum ssp. infantis in old order mennonites with traditional farming lifestyle. Allergy 76, 3489–3503 (2021).CAS 
    PubMed 
    Article 

    Google Scholar 
    Triantis, V., Bode, L. & van Neerven, R. J. J. Immunological effects of human milk oligosaccharides. Front. Pediatr. 6, 190 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Yu, Z.-T., Chen, C. & Newburg, D. S. Utilization of major fucosylated and sialylated human milk oligosaccharides by isolated human gut microbes. Glycobiology 23, 1281–1292 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012).Article 
    CAS 

    Google Scholar 
    McDonald, D. et al. American gut: an open platform for citizen science microbiome research. mSystems 3, e00031–18 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Odamaki, T. et al. Age-related changes in gut microbiota composition from newborn to centenarian: a cross-sectional study. BMC Microbiol. 16, 90 (2016).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Schei, K. et al. Early gut mycobiota and mother-offspring transfer. Microbiome 5, 107 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Alonso, R., Pisa, D., Fernández-Fernández, A. M. & Carrasco, L. Infection of fungi and bacteria in brain tissue from elderly persons and patients with Alzheimer’s disease. Front. Aging Neurosci. 10, 159 (2018).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Nagpal, R. et al. Gut mycobiome and its interaction with diet, gut bacteria and Alzheimer’s disease markers in subjects with mild cognitive impairment: a pilot study. EBioMedicine 59, 102950 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Ahmad, H. F. et al. Gut mycobiome dysbiosis is linked to hypertriglyceridemia among home dwelling elderly Danes. Preprint at bioRxiv https://doi.org/10.1101/2020.04.16.044693 (2020).Article 

    Google Scholar 
    Wampach, L. et al. Colonization and succession within the human gut microbiome by archaea, bacteria, and microeukaryotes during the first year of life. Front. Microbiol. 8, 738 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Breitbart, M. et al. Metagenomic analyses of an uncultured viral community from human feces. J. Bacteriol. 185, 6220–6223 (2003).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Liang, G. et al. The stepwise assembly of the neonatal virome is modulated by breastfeeding. Nature 581, 470–474 (2020). This study describes the assembly of the human virome during development.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Lim, E. S. et al. Early life dynamics of the human gut virome and bacterial microbiome in infants. Nat. Med. 21, 1228–1234 (2015).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Liang, G. et al. Dynamics of the stool virome in very early-onset inflammatory bowel disease. J. Crohns. Colitis 14, 1600–1610 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Koren, O. & Rautava, S. The Human Microbiome in Early Life: Implications to Health and Disease (Academic, 2020).Reyes, A. et al. Gut DNA viromes of Malawian twins discordant for severe acute malnutrition. Proc. Natl Acad. Sci. USA 112, 11941–11946 (2015).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Liang, G. & Bushman, F. D. The human virome: assembly, composition and host interactions. Nat. Rev. Microbiol. 19, 514–527 (2021).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Oude Munnink, B. B. & van der Hoek, L. Viruses causing gastroenteritis: the known, the new and those beyond. Viruses 8, 42 (2016).PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Woolhouse, M., Scott, F., Hudson, Z., Howey, R. & Chase-Topping, M. Human viruses: discovery and emergence. Phil. Trans. R. Soc. B 367, 2864–2871 (2012).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Rascovan, N., Duraisamy, R. & Desnues, C. Metagenomics and the human virome in asymptomatic individuals. Annu. Rev. Microbiol. 70, 125–141 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Mason, M. R., Chambers, S., Dabdoub, S. M., Thikkurissy, S. & Kumar, P. S. Characterizing oral microbial communities across dentition states and colonization niches. Microbiome 6, 67 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Dzidic, M. et al. Oral microbiome development during childhood: an ecological succession influenced by postnatal factors and associated with tooth decay. ISME J. 12, 2292–2306 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Merglova, V. & Polenik, P. Early colonization of the oral cavity in 6- and 12-month-old infants by cariogenic and periodontal pathogens: a case-control study. Folia Microbiol. 61, 423–429 (2016).CAS 
    Article 

    Google Scholar 
    Gomez, A. & Nelson, K. E. The oral microbiome of children: development, disease, and implications beyond oral health. Microb. Ecol. 73, 492–503 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Cephas, K. D. et al. Comparative analysis of salivary bacterial microbiome diversity in edentulous infants and their mothers or primary care givers using pyrosequencing. PLoS ONE 6, e23503 (2011).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Crielaard, W. et al. Exploring the oral microbiota of children at various developmental stages of their dentition in the relation to their oral health. BMC Med. Genomics 4, 22 (2011).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Darwazeh, A. M. & al-Bashir, A. Oral candidal flora in healthy infants. J. Oral. Pathol. Med. 24, 361–364 (1995).CAS 
    PubMed 
    Article 

    Google Scholar 
    Stecksén-Blicks, C., Granström, E., Silfverdal, S. A. & West, C. E. Prevalence of oral Candida in the first year of life. Mycoses 58, 550–556 (2015).PubMed 
    Article 
    CAS 

    Google Scholar 
    Ghannoum, M. A. et al. Characterization of the oral fungal microbiome (mycobiome) in healthy individuals. PLoS Pathog. 6, e1000713 (2010).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Brusa, T., Conca, R., Ferrara, A., Ferrari, A. & Pecchioni, A. The presence of methanobacteria in human subgingival plaque. J. Clin. Periodontol. 14, 470–471 (1987).CAS 
    PubMed 
    Article 

    Google Scholar 
    Ferrari, A., Brusa, T., Rutili, A., Canzi, E. & Biavati, B. Isolation and characterization ofMethanobrevibacter oralis sp. nov. Curr. Microbiol. 29, 7–12 (1994).CAS 
    Article 

    Google Scholar 
    Nguyen-Hieu, T., Khelaifia, S., Aboudharam, G. & Drancourt, M. Methanogenic archaea in subgingival sites: a review. APMIS 121, 467–477 (2013).PubMed 
    Article 

    Google Scholar 
    Abeles, S. R., Ly, M., Santiago-Rodriguez, T. M. & Pride, D. T. Effects of long term antibiotic therapy on human oral and fecal viromes. PLoS ONE 10, e0134941 (2015).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Pérez-Brocal, V. & Moya, A. The analysis of the oral DNA virome reveals which viruses are widespread and rare among healthy young adults in Valencia (Spain). PLoS ONE 13, e0191867 (2018).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Dye, B. A., Li, X. & Thornton-Evans, G. Oral health disparities as determined by selected healthy people 2020 oral health objectives for the United States, 2009–2010. NCHS Data Brief. 104, 1–8 (2012).
    Google Scholar 
    Baker, J. L., Bor, B., Agnello, M., Shi, W. & He, X. Ecology of the oral microbiome: beyond bacteria. Trends Microbiol. 25, 362–374 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Gaitanis, G. et al. Variation of cultured skin microbiota in mothers and their infants during the first year postpartum. Pediatr. Dermatol. 36, 460–465 (2019).PubMed 

    Google Scholar 
    Lee, Y. W., Yim, S. M., Lim, S. H., Choe, Y. B. & Ahn, K. J. Quantitative investigation on the distribution of Malassezia species on healthy human skin in Korea. Mycoses 49, 405–410 (2006).CAS 
    PubMed 
    Article 

    Google Scholar 
    Byrd, A. L., Belkaid, Y. & Segre, J. A. The human skin microbiome. Nat. Rev. Microbiol. 16, 143–155 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Sugita, T. et al. Quantitative analysis of the cutaneous Malassezia microbiota in 770 healthy Japanese by age and gender using a real-time PCR assay. Med. Mycol. 48, 229–233 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    Probst, A. J., Auerbach, A. K. & Moissl-Eichinger, C. Archaea on human skin. PLoS ONE 8, e65388 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hulcr, J. et al. A jungle in there: bacteria in belly buttons are highly diverse, but predictable. PLoS ONE 7, e47712 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Caporaso, J. G. et al. Moving pictures of the human microbiome. Genome Biol. 12, R50 (2011).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Moya, A. & Brocal, V. P. The Human Virome: Methods and Protocols (Springer, 2018).Foulongne, V. et al. Human skin microbiota: high diversity of DNA viruses identified on the human skin by high throughput sequencing. PLoS ONE 7, e38499 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Turnbaugh, P. J. et al. Organismal, genetic, and transcriptional variation in the deeply sequenced gut microbiomes of identical twins. Proc. Natl Acad. Sci. USA 107, 7503–7508 (2010). This study shows that cohabitating identical twins result in different microbial communities, highlighting the many unknown processes that lead to the unique human microbiota.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Shao, Y. et al. Stunted microbiota and opportunistic pathogen colonization in caesarean-section birth. Nature 574, 117–121 (2019).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Stewart, C. J. et al. Temporal development of the gut microbiome in early childhood from the TEDDY study. Nature 562, 583–588 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Ainonen, S. et al. Antibiotics at birth and later antibiotic courses: effects on gut microbiota. Pediatr. Res. 91, 154–162 (2022).CAS 
    PubMed 
    Article 

    Google Scholar 
    Chen, X., Lu, Y., Chen, T. & Li, R. The female vaginal microbiome in health and bacterial vaginosis. Front. Cell. Infect. Microbiol. 11, 631972 (2021).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Wells, J. S., Chandler, R., Dunn, A. & Brewster, G. The vaginal microbiome in U.S. black women: a systematic review. J. Womens Health 29, 362–375 (2020).Article 

    Google Scholar 
    Martino, C. et al. Context-aware dimensionality reduction deconvolutes gut microbial community dynamics. Nat. Biotechnol. 39, 165–168 (2021).CAS 
    PubMed 
    Article 

    Google Scholar 
    Furman, O. et al. Stochasticity constrained by deterministic effects of diet and age drive rumen microbiome assembly dynamics. Nat. Commun. 11, 1904 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Henderickx, J. G. E., Zwittink, R. D., van Lingen, R. A., Knol, J. & Belzer, C. The preterm gut microbiota: an inconspicuous challenge in nutritional neonatal care. Front. Cell. Infect. Microbiol. 9, 85 (2019).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Malamitsi-Puchner, A. et al. The influence of the mode of delivery on circulating cytokine concentrations in the perinatal period. Early Hum. Dev. 81, 387–392 (2005).CAS 
    PubMed 
    Article 

    Google Scholar 
    Stokholm, J. et al. Maturation of the gut microbiome and risk of asthma in childhood. Nat. Commun. 9, 141 (2018).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Andersen, V., Möller, S., Jensen, P. B., Møller, F. T. & Green, A. Caesarean delivery and risk of chronic inflammatory diseases (inflammatory bowel disease, rheumatoid arthritis, coeliac disease, and diabetes mellitus): a population based registry study of 2,699,479 births in Denmark during 1973–2016. Clin. Epidemiol. 12, 287–293 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Blustein, J. et al. Association of caesarean delivery with child adiposity from age 6 weeks to 15 years. Int. J. Obes. 37, 900–906 (2013).CAS 
    Article 

    Google Scholar 
    Ardic, C., Usta, O., Omar, E., Yıldız, C. & Memis, E. Caesarean delivery increases the risk of overweight or obesity in 2-year-old children. J. Obstet. Gynaecol. 41, 374–379 (2021).PubMed 
    Article 

    Google Scholar 
    Cox, L. M. et al. Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences. Cell 158, 705–721 (2014).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Martinez, K. A. 2nd et al. Increased weight gain by C-section: functional significance of the primordial microbiome. Sci. Adv. 3, eaao1874 (2017).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Olszak, T. et al. Microbial exposure during early life has persistent effects on natural killer T cell function. Science 336, 489–493 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Livanos, A. E. et al. Antibiotic-mediated gut microbiome perturbation accelerates development of type 1 diabetes in mice. Nat. Microbiol. 1, 16140 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Moya-Pérez, A. et al. Intervention strategies for cesarean section–induced alterations in the microbiota-gut-brain axis. Nutr. Rev. 75, 225–240 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Braniste, V. et al. The gut microbiota influences blood-brain barrier permeability in mice. Sci. Transl. Med. 6, 263ra158 (2014).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Forbes, J. D. et al. Association of exposure to formula in the hospital and subsequent infant feeding practices with gut microbiota and risk of overweight in the first year of life. JAMA Pediatr. 172, e181161 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Shenhav, L. & Azad, M. B. Using community ecology theory and computational microbiome methods to study human milk as a biological system. mSystems 7, e01132–21 (2022).PubMed Central 
    Article 

    Google Scholar 
    Kaetzel, C. S. Cooperativity among secretory IgA, the polymeric immunoglobulin receptor, and the gut microbiota promotes host-microbial mutualism. Immunol. Lett. 162, 10–21 (2014).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Munblit, D., Verhasselt, V. & Warner, J. O. Human Milk Composition and Health Outcomes in Children (Frontiers Media, 2019).Mastromarino, P. et al. Correlation between lactoferrin and beneficial microbiota in breast milk and infant’s feces. Biometals 27, 1077–1086 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    Agus, A., Planchais, J. & Sokol, H. Gut microbiota regulation of tryptophan metabolism in health and disease. Cell Host Microbe 23, 716–724 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Coats, S. R., Pham, T.-T. T., Bainbridge, B. W., Reife, R. A. & Darveau, R. P. MD-2 mediates the ability of tetra-acylated and penta-acylated lipopolysaccharides to antagonize Escherichia coli lipopolysaccharide at the TLR4 signaling complex. J. Immunol. 175, 4490–4498 (2005).CAS 
    PubMed 
    Article 

    Google Scholar 
    Denou, E. et al. Defective NOD 2 peptidoglycan sensing promotes diet‐induced inflammation, dysbiosis, and insulin resistance. EMBO Mol. Med. 7, 259–274 (2015).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Quinn, R. A. et al. Global chemical effects of the microbiome include new bile-acid conjugations. Nature 579, 123–129 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Rooks, M. G. & Garrett, W. S. Gut microbiota, metabolites and host immunity. Nat. Rev. Immunol. 16, 341–352 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Vatanen, T. et al. Variation in microbiome LPS immunogenicity contributes to autoimmunity in humans. Cell 165, 1551 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Fan, Y. & Pedersen, O. Gut microbiota in human metabolic health and disease. Nat. Rev. Microbiol. 19, 55–71 (2021).CAS 
    PubMed 
    Article 

    Google Scholar 
    Xiao, J., Fiscella, K. A. & Gill, S. R. Oral microbiome: possible harbinger for children’s health. Int. J. Oral. Sci. 12, 12 (2020).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Zhao, S. et al. Adaptive evolution within gut microbiomes of healthy people. Cell Host Microbe 25, 656–667.e8 (2019).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Zhang, R., Lahens, N. F., Ballance, H. I., Hughes, M. E. & Hogenesch, J. B. A circadian gene expression atlas in mammals: implications for biology and medicine. Proc. Natl Acad. Sci. USA 111, 16219–16224 (2014).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Allaband, C. et al. Intermittent hypoxia and hypercapnia alter diurnal rhythms of luminal gut microbiome and metabolome. mSystems 6, e00116–e00121 (2021).CAS 
    PubMed Central 
    Article 

    Google Scholar 
    Marotz, C. et al. Quantifying live microbial load in human saliva samples over time reveals stable composition and dynamic load. mSystems 6, e01182–20 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bouslimani, A. et al. The impact of skin care products on skin chemistry and microbiome dynamics. BMC Biol. 17, 47 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Costello, E. K. et al. Bacterial community variation in human body habitats across space and time. Science 326, 1694–1697 (2009). This study demonstrates the important variability between body habitats and between individuals across the same body habitat.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Kolodziejczyk, A. A., Zheng, D. & Elinav, E. Diet–microbiota interactions and personalized nutrition. Nat. Rev. Microbiol. 17, 742–753 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Zaramela, L. S. et al. Gut bacteria responding to dietary change encode sialidases that exhibit preference for red meat-associated carbohydrates. Nat. Microbiol. 4, 2082–2089 (2019).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Zmora, N., Suez, J. & Elinav, E. You are what you eat: diet, health and the gut microbiota. Nat. Rev. Gastroenterol. Hepatol. 16, 35–56 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Etemadi, A. et al. Mortality from different causes associated with meat, heme iron, nitrates, and nitrites in the NIH-AARP Diet and Health Study: population based cohort study. BMJ 357, j1957 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Koeth, R. A. et al. Intestinal microbiota metabolism of L-carnitine, a nutrient in red meat, promotes atherosclerosis. Nat. Med. 19, 576–585 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Gilbert, J. A. et al. Current understanding of the human microbiome. Nat. Med. 24, 392–400 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Durack, J. & Lynch, S. V. The gut microbiome: relationships with disease and opportunities for therapy. J. Exp. Med. 216, 20–40 (2019).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Lai, Y. et al. Commensal bacteria regulate Toll-like receptor 3–dependent inflammation after skin injury. Nat. Med. 15, 1377–1382 (2009).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Chng, K. R. et al. Whole metagenome profiling reveals skin microbiome-dependent susceptibility to atopic dermatitis flare. Nat. Microbiol. 1, 16106 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Li, H. et al. Skin commensal Malassezia globosa secreted protease attenuates Staphylococcus aureus biofilm formation. J. Invest. Dermatol. 138, 1137–1145 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Shirtliff, M. E., Peters, B. M. & Jabra-Rizk, M. A. Cross-kingdom interactions: Candida albicans and bacteria. FEMS Microbiol. Lett. 299, 1–8 (2009).CAS 
    PubMed 
    Article 

    Google Scholar 
    Santus, W., Devlin, J. R. & Behnsen, J. Crossing kingdoms: how the mycobiota and fungal-bacterial interactions impact host health and disease. Infect. Immun. 89, e00648–20 (2021).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Taur, Y. et al. Reconstitution of the gut microbiota of antibiotic-treated patients by autologous fecal microbiota transplant. Sci. Transl. Med. 10, eaap9489 (2018). This study shows that autologous faecal microbiota transplantation helps to restore the microbiota of patients who underwent antibiotic treatment.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    van Nood, E., Dijkgraaf, M. G. W. & Keller, J. J. Duodenal infusion of feces for recurrent Clostridium difficile. N. Engl. J. Med. 368, 2145 (2013).PubMed 
    Article 
    CAS 

    Google Scholar 
    Tariq, R., Pardi, D. S., Bartlett, M. G. & Khanna, S. Low cure rates in controlled trials of fecal microbiota transplantation for recurrent Clostridium difficile infection: a systematic review and meta-analysis. Clin. Infect. Dis. 68, 1351–1358 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Panigrahi, P. et al. Corrigendum: a randomized synbiotic trial to prevent sepsis among infants in rural India. Nature 553, 238 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Halkjær, S. I. et al. Faecal microbiota transplantation alters gut microbiota in patients with irritable bowel syndrome: results from a randomised, double-blind placebo-controlled study. Gut 67, 2107–2115 (2018).PubMed 
    Article 
    CAS 

    Google Scholar 
    Korpela, K. et al. Maternal fecal microbiota transplantation in cesarean-born infants rapidly restores normal gut microbial development: a proof-of-concept study. Cell 183, 324–334.e5 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Morton, J. T. et al. Learning representations of microbe–metabolite interactions. Nat. Methods 16, 1306–1314 (2019).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Kehe, J. et al. Positive interactions are common among culturable bacteria. Sci. Adv. 7, eabi7159 (2021).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Strandwitz, P. et al. GABA-modulating bacteria of the human gut microbiota. Nat. Microbiol. 4, 396–403 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Rubin, B. E. et al. Species- and site-specific genome editing in complex bacterial communities. Nat. Microbiol. 7, 34–47 (2022).CAS 
    PubMed 
    Article 

    Google Scholar 
    Zmora, N. et al. Personalized gut mucosal colonization resistance to empiric probiotics is associated with unique host and microbiome features. Cell 174, 1388–1405.e21 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Zeevi, D. et al. Personalized nutrition by prediction of glycemic responses. Cell 163, 1079–1094 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Schooley, R. T. et al. Development and use of personalized bacteriophage-based therapeutic cocktails to treat a patient with a disseminated resistant Acinetobacter baumannii infection. Antimicrob. Agents Chemother. 61, e00954–17 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Mu, A. et al. Effects on the microbiome during treatment of a staphylococcal device infection. Preprint at Research Square https://doi.org/10.21203/rs.3.rs-969336/v1 (2021).Article 

    Google Scholar 
    Claesson, M. J. et al. Gut microbiota composition correlates with diet and health in the elderly. Nature 488, 178–184 (2012). This study reports microbial community alterations between older individuals (aged 65 years and older) dependent on whether they live in the company of others or alone, the latter of which was correlated to worse outcomes (that is, frailty and co-morbidity).CAS 
    PubMed 
    Article 

    Google Scholar 
    Wu, L. et al. A cross-sectional study of compositional and functional profiles of gut microbiota in Sardinian centenarians. mSystems 4, e00325–19 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Kong, F. et al. Gut microbiota signatures of longevity. Curr. Biol. 26, R832–R833 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Claesson, M. J. et al. Composition, variability, and temporal stability of the intestinal microbiota of the elderly. Proc. Natl Acad. Sci. USA 108 (Suppl. 1), 4586–4591 (2011).CAS 
    PubMed 
    Article 

    Google Scholar 
    O’Toole, P. W. & Jeffery, I. B. Gut microbiota and aging. Science 350, 1214–1215 (2015).PubMed 
    Article 
    CAS 

    Google Scholar 
    Shibagaki, N. et al. Aging-related changes in the diversity of women’s skin microbiomes associated with oral bacteria. Sci. Rep. 7, 10567 (2017).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Liu, S., Wang, Y., Zhao, L., Sun, X. & Feng, Q. Microbiome succession with increasing age in three oral sites. Aging 12, 7874–7907 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Schwartz, J. L. et al. Old age and other factors associated with salivary microbiome variation. BMC Oral. Health 21, 490 (2021).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Strati, F. et al. Age and gender affect the composition of fungal population of the human gastrointestinal tract. Front. Microbiol. 7, 01227 (2016).Article 

    Google Scholar 
    Wu, L. et al. Age-related variation of bacterial and fungal communities in different body habitats across the young, elderly, and centenarians in Sardinia. mSphere 5, e00558–19 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Nagpal, R. et al. Gut microbiome and aging: physiological and mechanistic insights. Nutr. Healthy Aging 4, 267–285 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Wilmanski, T. et al. Gut microbiome pattern reflects healthy ageing and predicts survival in humans. Nat. Metab. 3, 274–286 (2021).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Sato, Y. et al. Novel bile acid biosynthetic pathways are enriched in the microbiome of centenarians. Nature 599, 458–464 (2021). This study finds that centenarians often had high abundances of microorganisms that produced unique secondary bile acids, namely various isoforms of lithocholic acid.CAS 
    PubMed 
    Article 

    Google Scholar 
    Gill-King, H. in Forensic Taphonomy: the Postmortem Fate of Human Remains 93–108 (CRC, 1997).Janaway, R. C., Percival, S. L. & Wilson, A. S. in Microbiology and Aging (ed. Percival, S. L) 313–334 (Humana, 2009).Forbes, S. L., Perrault, K. A. & Comstock, J. L. in Taphonomy of Human Remains: Forensic Analysis of the Dead and the Depositional Environment (eds Schotsmans, E. M. J., Márquez-Grant, N. & Forbes, S. L.) 26–38 (Wiley, 2017).Heimesaat, M. M. et al. Comprehensive postmortem analyses of intestinal microbiota changes and bacterial translocation in human flora associated mice. PLoS ONE 7, e40758 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Parkinson, R. A. et al. in Criminal and Environmental Soil Forensics (eds Ritz, K., Dawson, L. & Miller, D.) 379–394 (Springer, 2009).Metcalf, J. L. et al. Microbial community assembly and metabolic function during mammalian corpse decomposition. Science 351, 158–162 (2016). This study finds that the time since death was predictable through the microbial community composition independent of the soil type and season.CAS 
    PubMed 
    Article 

    Google Scholar 
    DeBruyn, J. M. & Hauther, K. A. Postmortem succession of gut microbial communities in deceased human subjects. PeerJ 5, e3437 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Pechal, J. L., Schmidt, C. J., Jordan, H. R. & Benbow, M. E. A large-scale survey of the postmortem human microbiome, and its potential to provide insight into the living health condition. Sci. Rep. 8, 5724 (2018).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Kodama, W. A. et al. Trace evidence potential in postmortem skin microbiomes: from death scene to morgue. J. Forensic Sci. 64, 791–798 (2019).PubMed 
    Article 

    Google Scholar 
    Hauther, K. A., Cobaugh, K. L., Jantz, L. M., Sparer, T. E. & DeBruyn, J. M. Estimating time since death from postmortem human gut microbial communities. J. Forensic Sci. 60, 1234–1240 (2015).PubMed 
    Article 

    Google Scholar 
    Burcham, Z. M. et al. Fluorescently labeled bacteria provide insight on post-mortem microbial transmigration. Forensic Sci. Int. 264, 63–69 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Burcham, Z. M. et al. Bacterial community succession, transmigration, and differential gene transcription in a controlled vertebrate decomposition model. Front. Microbiol. 10, 745 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Balzan, S., de Almeida Quadros, C., de Cleva, R., Zilberstein, B. & Cecconello, I. Bacterial translocation: overview of mechanisms and clinical impact. J. Gastroenterol. Hepatol. 22, 464–471 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    Metcalf, J. L. et al. A microbial clock provides an accurate estimate of the postmortem interval in a mouse model system. eLife 2, e01104 (2013).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Hyde, E. R., Haarmann, D. P., Petrosino, J. F., Lynne, A. M. & Bucheli, S. R. Initial insights into bacterial succession during human decomposition. Int. J. Leg. Med. 129, 661–671 (2015).Article 

    Google Scholar 
    Javan, G. T., Finley, S. J., Smith, T., Miller, J. & Wilkinson, J. E. Cadaver thanatomicrobiome signatures: the ubiquitous nature of Clostridium species in human decomposition. Front. Microbiol. 8, 2096 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Johnson, H. R. et al. A machine learning approach for using the postmortem skin microbiome to estimate the postmortem interval. PLoS ONE 11, e0167370 (2016).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Belk, A. et al. Microbiome data accurately predicts the postmortem interval using random forest regression models. Genes 9, 104 (2018).PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Metcalf, J. L. Estimating the postmortem interval using microbes: knowledge gaps and a path to technology adoption. Forensic Sci. Int. Genet. 38, 211–218 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Deel, H. et al. A pilot study of microbial succession in human rib skeletal remains during terrestrial decomposition. mSphere 6, e0045521 (2021).PubMed 
    Article 

    Google Scholar 
    Metcalf, J. L. et al. Microbiome tools for forensic science. Trends Biotechnol. 35, 814–823 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Nguyen, T. T., Hathaway, H., Kosciolek, T., Knight, R. & Jeste, D. V. Gut microbiome in serious mental illnesses: a systematic review and critical evaluation. Schizophr. Res. 234, 24–40 (2021).PubMed 
    Article 

    Google Scholar 
    Jeste, D. V., Koh, S. & Pender, V. B. Perspective: social determinants of mental health for the new decade of healthy aging. Am. J. Geriatr. Psychiatry 30, 733–736 (2022).PubMed 
    Article 

    Google Scholar 
    Matijašić, M. et al. Gut microbiota beyond bacteria-mycobiome, virome, archaeome, and eukaryotic parasites in IBD. Int. J. Mol. Sci. 21, 2668 (2020).PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Morton, J. T. et al. Establishing microbial composition measurement standards with reference frames. Nat. Commun. 10, 2719 (2019).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Gerber, G. K. The dynamic microbiome. FEBS Lett. 588, 4131–4139 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    Zarrinpar, A., Chaix, A., Yooseph, S. & Panda, S. Diet and feeding pattern affect the diurnal dynamics of the gut microbiome. Cell Metab. 20, 1006–1017 (2014).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Vázquez-Baeza, Y. et al. Guiding longitudinal sampling in IBD cohorts. Gut 67, 1743–1745 (2018).PubMed 
    Article 

    Google Scholar 
    Kane, P. B., Bittlinger, M. & Kimmelman, J. Individualized therapy trials: navigating patient care, research goals and ethics. Nat. Med. 27, 1679–1686 (2021).CAS 
    PubMed 
    Article 

    Google Scholar 
    Huang, S. et al. Human skin, oral, and gut microbiomes predict chronological age. mSystems 5, e00630–19 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Thompson, L. R. et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature 551, 457–463 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Franzosa, E. A. et al. Identifying personal microbiomes using metagenomic codes. Proc. Nat. Acad. Sci. USA 112, E2930–E2938 (2015).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Vangay, P. et al. Microbiome metadata standards: report of the national microbiome data collaborative’s workshop and follow-on activities. mSystems 6, e01194–20 (2021).PubMed 
    PubMed Central 

    Google Scholar  More

  • in

    Biogeographic implication of temperature-induced plant cell wall lignification

    Körner, C. The cold range limit of trees. Trends Ecol. Evo. 36, 979–989 (2021).Article 

    Google Scholar 
    Körner, C. Alpine Treelines (Springer, 2012).Miehe, G., Miehe, S., Vogel, J., Co, S. & Duo, L. Highest treeline in the northern hemisphere found in southern Tibet. Mt. Res. Dev. 27, 169–173 (2007).Article 

    Google Scholar 
    Hoch, G. & Körner, C. Growth, demography and carbon relations of Polylepis trees at the world’s highest treeline. Funct. Ecol. 19, 941–951 (2005).Article 

    Google Scholar 
    von Humboldt, A. & Bonpland, A. Ideen zu einer Geographie der Pflanzen nebst einem Naturgemälde der Tropenländer: auf Beobachtungen und Messungen gegründet, welche vom 10ten Grade nördlicher bis zum 10ten Grade südlicher Breite, in den Jahren 1799, 1800, 1801, 1802 und 1803 angestellt worden sind. Tübingen, Bey F.G. Cotta (1807).Körner, C. Climatic treelines: conventions, global patterns, causes. Erdkunde 61, 315–324 (2007).Article 

    Google Scholar 
    Piermattei, A., Crivellaro, A., Carrer, M. & Urbinati, C. The “blue ring”: anatomy and formation hypothesis of a new tree-ring anomaly in conifers. Trees Struct. Funct. 29, 613–620 (2015).CAS 
    Article 

    Google Scholar 
    Körner, C. et al. Life at 0 °C: the biology of the alpine snowbed plant Soldanella pulsatilla. Alp. Bot. 129, 63–80 (2019).Article 

    Google Scholar 
    Crivellaro, A. & Büntgen, U. New evidence of thermally-constraint plant cell wall lignification. Trends Plant Sci. 24, 322–324 (2020).Article 
    CAS 

    Google Scholar 
    Büntgen, U. et al. Temperature-induced recruitment pulses of Arctic dwarf shrub communities. J. Ecol. 103, 489–501 (2015).Article 

    Google Scholar 
    Dolezal, J. et al. Vegetation dynamics at the upper elevational limit of vascular plants in Himalaya. Sci. Rep. 6, 24881 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Ryan, M. G. & Yoder, B. J. Hydraulic limits to tree height and tree growth. Biosci 47, 235–242 (1997).Article 

    Google Scholar 
    Koch, G. W., Sillett, S. C., Jennings, G. M. & Davis, S. D. The limits to tree height. Nature 428, 851–854 (2004).CAS 
    PubMed 
    Article 

    Google Scholar 
    Körner, C. Alpine Plant Life: Functional Plant Ecology of High Mountain Ecosystems (Springer, 2003).Scherrer, D. & Körner, C. Infra-red thermometry of alpine landscapes challenges climatic warming projections. Glob. Change Biol. 16, 2602–2613 (2010).
    Google Scholar 
    Begum, S., Nakaba, S., Yamagishi, Y., Oribe, Y. & Funada, R. Regulation of cambial activity in relation to environmental conditions: understanding the role of temperature in wood formation of trees. Physiol. Planta 147, 46–54 (2013).CAS 
    Article 

    Google Scholar 
    Plomion, C., Leprovost, G. & Stokes, A. Wood formation in trees. Plant Physiol. 127, 1513–1523 (2001).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Rossi, S., Deslauriers, A., Anfodillo, T. & Carraro, V. Evidence of threshold temperatures for xylogenesis in conifers at high altitudes. Oecologia 152, 1–12 (2007).PubMed 
    Article 

    Google Scholar 
    Moura, J. C. M. S., Bonine, C. A. V., Viana, J. O. F., Dornelas, M. C. & Mazzafera, P. Abiotic and biotic stresses and changes in the lignin content and composition in plants. J. Integr. Plant Biol. 52, 360–376 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    Weng, J. K. & Chapple, C. The origin and evolution of lignin biosynthesis. N. Phytol. 187, 273–285 (2010).CAS 
    Article 

    Google Scholar 
    Niklas, K. J., Cobb, E. D. & Matas, A. J. The evolution of hydrophobic cell wall biopolymers: from algae to angiosperms. J. Exp. 68, 5261–5269 (2017).CAS 

    Google Scholar 
    Popper, Z. A. et al. Evolution and diversity of plant cell walls: from algae to flowering plants. Annu. Rev. Plant Biol. 62, 567–590 (2011).CAS 
    PubMed 
    Article 

    Google Scholar 
    Piquemal, J. et al. Down regulation of cinnamoyl CoA reductase induces significant changes of lignin profiles in transgenic tobacco plants. Plant J. 13, 71–83 (1998).CAS 
    Article 

    Google Scholar 
    Renault, H., Werck-Reichhart, D. & Weng, J.-K. Harnessing lignin evolution for biotechnological applications. Curr. Opin. Biotechnol. 56, 105–111 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Schenk, H. J., Espino, S., Rich-Cavazos, S. M. & Jansen, S. From the sap’s perspective: The nature of vessel surfaces in angiosperm xylem. Am. J. Bot. 105, 172–185 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Polo, C. C. et al. Correlations between lignin content and structural robustness in plants revealed by X-ray ptychography. Sci. Rep. 10, 6023 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Meents, M. J., Watanabe, Y. & Samuels, A. L. The cell biology of secondary cell wall biosynthesis. Ann. Bot. 121, 1107–1125 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Campbell, M. M. & Sederoff, R. R. Variation in lignin content and composition (mechanisms of control and implications for the genetic improvement of plants). Plant Physiol. 110, 3–13 (1996).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Schweingruber, F. H. & Büntgen, U. What is ‘wood’ – An anatomical re-definition. Dendrochronologia 31, 187–191 (2013).Article 

    Google Scholar 
    Ellenberg, H. & Mueller-Dombois, D. A key to Raunkiaer plant life forms with revised subdivisions. Ber. Geobot. Inst. ETH Z.ürich. 37, 56–73 (1967).
    Google Scholar 
    Kim, W. J., Campbell, A. G. & Koch, P. Chemical variation in Lodgepole pine with latitude, elevation, and diameter class. Prod. J. 39, 7–12 (1989).CAS 

    Google Scholar 
    Gindl, W., Grabner, M. & Wimmer, R. The influence of temperature on latewood lignin content in treeline Norway spruce compared with maximum density and ring width. Trees, Struct. Funct. 14, 409–414 (2000).Article 

    Google Scholar 
    Schenker, G., Lens, A., Körner, C. & Hoch, G. Physiological minimum temperatures for root growth in seven common European broad-leaved tree species. Tree Physiol. 34, 302–313 (2014).PubMed 
    Article 

    Google Scholar 
    Nagelmüller, S., Hiltbrunner, E. & Körner, C. Low temperature limits for root growth in alpine species are set by cell differentiation. AoB Plants 9, plx054 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Ji, H. et al. The Arabidopsis RCC1 family protein TCF1 regulates freezing tolerance and cold acclimation through modulating lignin biosynthesis. PLoS Gen. 11, e1005471 (2015).Article 
    CAS 

    Google Scholar 
    Büntgen, U. Re-thinking the boundaries of dendrochronology. Dendrochronologia 53, 1–4 (2019).Article 

    Google Scholar 
    Piermattei, A. et al. A millennium-long ‘Blue-Ring’ chronology from the Spanish Pyrenees reveals sever ephemeral summer cooling after volcanic eruptions. Environ. Res. Lett. 15, 124016 (2020).Article 

    Google Scholar 
    Montwé, D., Isaac-Rentin, M., Hamman, A. & Spiecker, H. Cold adaptation recorded in tree rings highlights risks associated with climate change and assisted migration. Nat. Comm. 9, 1574 (2018).Article 
    CAS 

    Google Scholar 
    Barros, J., Serk, H., Granlund, I. & Pesquet, E. The cell biology of lignification in higher plants. Ann. Bot. 115, 1053–1074 (2015).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hao, Z. & Mohnen, D. A review of xylan and lignin biosynthesis: Foundation for studying Arabidopsis irregular xylem mutants with pleiotropic phenotypes. Cri. Rev. Biochem. Mol. Biol. 49, 212–241 (2014).CAS 
    Article 

    Google Scholar 
    Liu, Q., Luo, L. & Zheng, L. Lignins: biosynthesis and biological functions in plants. Int. J. Mol. Sci. 19, 335 (2018).PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Kumar, M., Campbell, L. & Turner, S. Secondary cell walls: biosynthesis and manipulation. J. Exp. Bot. 67, 515–531 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Mellerowicz, E. J., Baucher, M., Sundberg, B. & Boerjan, W. Unravelling cell wall formation in the woody dicot stem. Plant Mol. Biol. 47, 239–274 (2001).CAS 
    PubMed 
    Article 

    Google Scholar 
    Petit, G., Anfodillo, T., Carraro, V., Grani, F. & Carrer, M. Hydraulic constraints limit height growth in trees at high altitude. N. Phytol. 189, 241–252 (2010).Article 

    Google Scholar 
    Li, L. et al. Combinatorial modification of multiple lignin traits in trees through multigene co-transformation. Proc. Natl Acad. Sci. USA 100, 4939–4944 (2003).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Baldacci-Cresp, F. et al. A rapid and quantitative safranin-based fluorescent microscopy method to evaluate cell wall lignification. Plant J. 102, 1074–1089 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Körner, C. A re-assessment of high elevation treeline positions and their explanation. Oecologia 115, 445–459 (1998).PubMed 
    Article 

    Google Scholar 
    Landolt, E. et al. Flora indicativa: Okologische Zeigerwerte und biologische Kennzeichen zur Flora der Schweiz und der Alpen (Haupt, 2010).Büntgen, U., Psomas, A. & Schweingruber, F. H. Introducing wood anatomical and dendrochronological aspects of herbaceous plants: applications of the Xylem Database to vegetation science. J. Veg. Sci. 25, 967–977 (2014).Article 

    Google Scholar 
    Körner, C. Coldest places on earth with angiosperm plant life. Alp. Bot. 121, 11–22 (2011).Article 

    Google Scholar 
    GBIF.org. GBIF Occurrence Download. https://doi.org/10.15468/dl.ms4hjt (2018).Chamberlain, S., Ram, K. & Hart, T. Spocc: Interface to Specie Occurrence Data Sources, R package v.0.9.0. http://CRAN.R-project.org/package=spocc (2018).Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high-resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005).Article 

    Google Scholar 
    Hijmans, R. J. Raster: geographic data analysis and modelling, R package v.2.2-12. http://CRAN.R-project.org/package=raster (2014).Gärtner, H. et al. A technical perspective in modern tree-ring research – How to overcome dendroecological and wood anatomical challenges. J. Vis. Exp. 97, e52337 (2015).
    Google Scholar 
    Gärtner, H. & Schweingruber, F. H. Microscopic Preparation Techniques for Plant Stem Analysis (Verlag Kessel, 2013).Ghislan, B., Engel, J. & Clair, B. Diversity of anatomical structure of tension wood among 242 tropical tree species. IAWA J. 40, 1–20 (2019).Article 

    Google Scholar 
    Schweingruber, F. H., Börner, A. & Schulze, E. D. Atlas of Stem Anatomy in Herbs, Shrubs and Trees Vol. 1 (Springer, 2011).Schweingruber, F. H., Börner, A. & Schulze, E. D. Atlas of Stem Anatomy in Herbs, Shrubs and Trees Vol. 2 (Springer, 2013).Dolezal, J., Dvorsky, M., Börner, A., Wild, J. & Schweingruber, F. H. Anatomy, Age and Ecology of High Mountain Plants in Ladakh, the Western Himalaya (Springer International Publishing, 2018).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 
    Article 

    Google Scholar 
    Ter Braak, C. J. F. & Šmilauer, P. Canoco Reference Manual and User’s Guide: Software 559 for Ordination, Version 5.0 (Cambridge Univ. Press, 2012).Šmilauer, P. & Lepš, J. Multivariate Analysis of Ecological Data Using Canoco 5 (Cambridge Univ. Press, 2014). More

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    Acoustic characteristics of sound produced by males of Bactrocera oleae change in the presence of conspecifics

    Benelli, G. et al. Sexual communication and related behaviours in Tephritidae: Current knowledge and potential applications for Integrated Pest Management. J. Pest Sci. 87, 385–405 (2014).Article 

    Google Scholar 
    Kuba, H. & Sokei, Y. The production of pheromone clouds by spraying in the melon fly, Dacus cucurbitae coquillett (Diptera: Tephritidae). J. Ethol. 6, 105–110 (1988).Article 

    Google Scholar 
    Fletcher, B. S. The structure and function of the sex pheromone glands of the male Queensland fruit fly, Dacus tryoni.. J. Insect Physiol. 15, 1309–1322 (1969).Article 

    Google Scholar 
    Nation, J. L. Courtship behavior and evidence for a sex attractant in the male Caribbean fruit fly, Anastrepha suspensa. Ann. Entomol. Soc. Am. 65, 1364–1367 (1972).Article 

    Google Scholar 
    Arita, L. H. & Kaneshiro, K. Y. Sexual selection and lek behavior in the Mediterranean fruit fly, Ceratitis capitata (Diptera: Tephritidae). Pacific Sci. (EUA) 43, 135–143 (1989).
    Google Scholar 
    Briceño, R.D. & Eberhard, W.G. Male wing positions during courtship by Mediterranean fruit flies (Ceratitis capitata) (Diptera: Tephritidae). J. Kansas Entomol. Soc. 143–47 (2000).Benelli, G. et al. Male wing vibration in the mating behavior of the Olive fruit fly Bactrocera oleae (Rossi) (Diptera: Tephritidae). J. Insect Behav. 25, 590–603 (2012).Article 

    Google Scholar 
    Feron, M. L’appel sonore du mâle dans le comportement sexuel de Dacus oleae Gmel [Dipt Trypetidae]. Bull. Soc. Entomol. Fr. 65, 139–143 (1960).Article 

    Google Scholar 
    Feron, M. & Andrieu, A. J. Etude des signaux acoustiques du male dans le comportement sexuel de Dacus Oleae Gmel (Dipt. Trypetidae). Ann. Epiphyt. 13, 269–276 (1962).
    Google Scholar 
    Rolli, K. Die akustischen Sexualsignale von Ceratitis capitata Wied. Und Dacus oleae Gmel. Z. Angew. Entomol. 81, 219–223 (1976).Article 

    Google Scholar 
    Webb, J. C., Calkins, C. O., Chambers, D. L., Schwienbacher, W. & Russ, K. Acoustical aspects of behavior of Mediterranean fruit fly, Ceratitis capitata: Analysis and identification of courtship sounds. Entomol. Exp. Appl. 33, 1–8 (1983).Article 

    Google Scholar 
    Mankin, R. W., Lemon, M., Harmer, A. M. T., Evans, C. S. & Taylor, P. W. Time pattern and frequency analyses of sounds produced by irradiated and untreated male Bactrocera tryoni (Diptera: Tephritidae) during mating behavior. Ann. Entomol. Soc. Am. 101, 664–674 (2008).Article 

    Google Scholar 
    Miyatake, T. & Kanmiya, K. Male courtship song in circadian rhythm mutants of Bactrocera cucurbitae (Tephritidae: Diptera). J. Insect Physiol. 50, 85–91 (2004).CAS 
    PubMed 
    Article 

    Google Scholar 
    Sivinski, J., Burk, T. & Webb, J. Acoustic courtship signals in the Caribbean fruit fly, Anastrepha suspensa (Loew). Anim. Behav. 32, 1011–1016 (1984).Article 

    Google Scholar 
    Mankin, R. W. et al. Broadcasts of wing-fanning vibrations recorded from calling male Ceratitis capitata (Diptera: Tephritidae) increase captures of females in traps. J. Econ. Entomol. 97, 1299–1309 (2004).CAS 
    PubMed 
    Article 

    Google Scholar 
    Mankin, R. W., Petersson, E., Epsky, N. D., Heath, R. R. & Sivinski, J. Exposure to male pheromones enhances Anastrepha suspensa (Diptera: Tephritidae) female response to male calling song. Fla. Entomol. 83, 411 (2000).CAS 
    Article 

    Google Scholar 
    Sivinski, J. & Webb, J. C. Changes in a Caribbean fruit fly acoustic signal with social situation (Diptera: Tephritidae)1. Ann. Entomol. Soc. Am. 79, 146–149 (1986).Article 

    Google Scholar 
    Canale, A. et al. The courtship song of fanning males in the fruit fly parasitoid Psyttalia concolor (Szépligeti) (Hymenoptera: Braconidae). Bull. Entomol. Res. 103, 303–309 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Wicker-Thomas, C. Pheromonal communication involved in courtship behavior in Diptera. J. Insect. Physiol. 53, 1089–1100 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    Tan, K.H., Nishida, R., Jang, E.B. & Shelly, T.E. Pheromones, male lures, and trapping of tephritid fruit flies. In: Trapping and the Detection, Control, and Regulation of Tephritid Fruit Flies: Lures, Area-Wide Programs, And Trade Implications 15–74 (Springer, 2014).Poramarcom, R. Sexual communication in the Oriental fruit fly, Dacus dorsalis Hendel (Diptera: Tephritidae). Doctoral dissertation. (University of Hawaii at Manoa, 1988).Ekanayake, D. The mating system and courtship behaviour of the Queensland fruit fly, Bactrocera tryoni (Froggatt) (Diptera: Tephritidae). Doctoral dissertation. (Queensland University of Technology, 2017).Suzuki, Y. & Koyama, J. Courtship behavior of the melon fly, Dacus cucurbitae Coquillett (Diptera: Tephritidae). Appl. Entomol. Zool. 16, 164–166 (1981).Article 

    Google Scholar 
    Scolari, F., Valerio, F., Benelli, G., Papadopoulos, N. T. & Vaníčková, L. Tephritid fruit fly semiochemicals: Current knowledge and future perspectives. Insects 12, 408 (2021).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Nieri, R., Anfora, G., Mazzoni, V. & Rossi Stacconi, M. V. Semiochemicals, semiophysicals and their integration for the development of innovative multi-modal systems for agricultural pests’ monitoring and control. Entomol. Gen. 42, 167–183 (2022).Article 

    Google Scholar 
    Cocroft, R. B. & Rodríguez, R. L. The behavioral ecology of insect vibrational communication. Bioscience 55, 323–334 (2005).Article 

    Google Scholar 
    Daane, K. M. & Johnson, M. W. Olive fruit fly: Managing an ancient pest in modern times. Annu. Rev. Entomol. 55, 151–169 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    Rice, R. E., Phillips, P. A., Stewart-Leslie, J. & Sibbett, G. S. Olive fruit fly populations measured in Central and Southern California. Calif. Agric. 57, 122–127 (2003).Article 

    Google Scholar 
    Wang, X. et al. Exploration for olive fruit fly parasitoids across Africa reveals regional distributions and dominance of closely associated parasitoids. Sci. Rep. 11, 1–14 (2021).Article 
    CAS 

    Google Scholar 
    Loher, W. & Zervas, G. The mating rhythm of the olive fruitfly, Dacus oleae Gmelin. Z. Angew. Entomol. 88, 425–435 (1979).Article 

    Google Scholar 
    Benelli, G. Aggression in Tephritidae flies: Where, when, why? Future directions for research in integrated pest management. Insects 6, 38–53 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Benelli, G. Aggressive behavior and territoriality in the olive fruit fly, Bactrocera oleae (Rossi) (Diptera: Tephritidae): Role of residence and time of day. J. Insect. Behav. 27, 145–161 (2014).Article 

    Google Scholar 
    Shelly, T. E. Aggression between wild and laboratory-reared sterile males of the mediterranean fruit fly in a natural habitat (Diptera: Tephritidae). Fla. Entomol. 83, 105–108 (2000).Article 

    Google Scholar 
    Ekanayake, W. M., Clarke, A. R. & Schutze, M. K. Close-distance courtship of laboratory reared Bactrocera tryoni (Diptera: Tephritidae). Austral. Entomol. 58, 578–588 (2019).Article 

    Google Scholar 
    Ant, T. et al. Control of the olive fruit fly using genetics-enhanced sterile insect technique. BMC Biol. 10, 1–8 (2012).Article 

    Google Scholar 
    Estes, A. M. et al. A basis for the renewal of sterile insect technique for the olive fly, Bactrocera oleae (Rossi). J. Appl. Entomol. 136, 1–16 (2012).Article 

    Google Scholar 
    Zanini, D., Geurten, B., Spalthoff, C. & Göpfert, M. C. Sound communication in Drosophila. In Insect Hearing and Acoustic Communication Animal Signals and Communication, Vol. 1 (ed. Hedwig, B.) (Springer, 2014).
    Google Scholar 
    Windmill, J. F. C. & Jackson, J. C. Mechanical specializations of insect ears. In Insect Hearing. Springer Handbook of Auditory Research, Vol. 55 (eds Pollack, G. et al.) (Springer, 2016).
    Google Scholar 
    Talyn, B. C. & Dowse, H. B. The role of courtship song in sexual selection and species recognition by female Drosophila melanogaster. Anim. Behav. 68, 1165–1180 (2004).Article 

    Google Scholar 
    Kanmiya, K. Acoustic studies on the mechanism of sound production in the mating songs of the melon fly, Dacus cucurbitae Coquillett (Diptera: Tephritidae). J. Ethol. 6, 143–151 (1988).Article 

    Google Scholar 
    Benelli, G. et al. Wing-fanning frequency as a releaser boosting male mating success—High-speed video analysis of courtship behavior in Campoplex capitator, a parasitoid of Lobesia botrana. Insect Sci. 27, 1298–1310 (2020).PubMed 
    Article 

    Google Scholar 
    Ge, J. et al. Pea leafminer Liriomyza huidobrensis (Diptera: Agromyzidae) uses vibrational duets for efficient sexual communication. Insect Sci. 26, 510–522 (2019).PubMed 
    Article 

    Google Scholar 
    Mazzoni, V., Anfora, G. & Virant-Doberlet, M. Substrate vibrations during courtship in three drosophila species. PLoS ONE 8, e80708 (2013).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    McKelvey, E. G. Z. et al. Drosophila females receive male substrate-borne signals through specific leg neurons during courtship. Curr. Biol. 31, 3894–3904 (2021).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Strauß, J., Stritih-Peljhan, N., Nieri, R., Virant-Doberlet, M., & Mazzoni, V. Communication by substrate-borne mechanical waves in insects: From basic to applied biotremology. In: Advances in Insect Physiology, vol. 61, 189–307 (Academic Press, 2021).Mazomenos, B. E. Effect of age and mating on pheromone production in the female olive fruit fly, Dacus oleae (Gmel.). J. Insect Physiol. 30, 765–769 (1984).CAS 
    Article 

    Google Scholar 
    Carpita, A. et al. (Z)-9-tricosene identified in rectal gland extracts of Bactrocera oleae males: First evidence of a male-produced female attractant in in olive fruit fly. Naturwissenschaften 99, 77–81 (2012).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Canale, A. et al. Behavioural and electrophysiological responses of the olive fruit fly, Bactrocera oleae (Rossi) (Diptera: Tephritidae), to male- and female-borne sex attractants. Chemoecology 23, 155–164 (2013).CAS 
    Article 

    Google Scholar 
    Mcdonald, P. T. Intragroup stimulation of pheromone release by male mediterranean fruit flies (Diptera: Tephritidae). Ann. Entomol. Soc. Am. 80, 17–20 (1987).CAS 
    Article 

    Google Scholar 
    Iwahashi, O. & Majima, T. Lek formation and male–male competition in the melon fly, Dacus cucurbitae Coquillett: Diptera: Tephritidae. Appl. Entomol. Zool. 21, 70–75 (1986).Article 

    Google Scholar 
    Keiser, I., Kobayashi, R. M., Chambers, D. L. & Schneider, E. L. Relation of sexual dimorphism in the wings, potential stridulation, and illumination to mating of oriental fruit flies, melon flies, and Mediterranean fruit flies in Hawaii. Ann. Ent. Soc. Am. 66, 937–941 (1973).Article 

    Google Scholar 
    Benelli, G. & Canale, A. Aggressive behavior in olive fruit fly females: Oviposition site guarding against parasitic wasps. J. Insect Behav. 29, 680–688 (2016).Article 

    Google Scholar 
    Rohde, B. B. et al. An acoustic trap to survey and capture two neoscapteriscus species. Fla. Entomol. 102, 654–657 (2019).Article 

    Google Scholar 
    Shelly, T. E. Lek size and female visitation in two species of tephritid fruit flies. Anim. Behav. 62, 33–40 (2001).Article 

    Google Scholar 
    Niyazi, N., Shuker, D. M. & Wood, R. J. Male position and calling effort together influence male attractiveness in leks of the medfly, Ceratitis capitata (Diptera: Tephritidae): Male attractiveness in leks of Ceratitis capitata. Biol. J. Linn. Soc. Lond. 95, 479–487 (2008).Article 

    Google Scholar 
    Greenfield, M. D. Signal interactions and interference in insect choruses: Singing and listening in the social environment. J. Comp. Physiol. A 201, 143–154 (2015).Article 

    Google Scholar 
    Kouloussis, N. A. et al. Age related assessment of sugar and protein intake of Ceratitis capitata in ad libitum conditions and modeling its relation to reproduction. Front. Physiol. 8, 1–13 (2017).Article 

    Google Scholar 
    Boersma, P. & Van Heuven, V. Speak and unSpeak with PRAAT. Glot Int. 5, 341–347 (2001).
    Google Scholar 
    Joyce, A. L. et al. Effect of continuous rearing on courtship acoustics of five braconid parasitoids, candidates for augmentative biological control of Anastrepha species. Biocontrol 55, 573–582 (2010).Article 

    Google Scholar 
    Sall, J. et al. JMP Start Statistics: A Guide to Statistics and Data Analysis Using JMP (Sas Institute, 2017).
    Google Scholar  More