More stories

  • in

    Terrestrial and marine influence on atmospheric bacterial diversity over the north Atlantic and Pacific Oceans

    Regional distribution of airborne and surface water bacterial phyla in the Pacific and Atlantic oceansThe two open ocean sailing transects examined in this study included the western Pacific path, sampled in May 2017 from Keelung, Taiwan, towards Fiji (Fig. 1a and Supplementary Data 1), and the Atlantic crossing, sampled in June 2016 from Lorient, France, to Miami, USA (Fig. 1b and Supplementary Data 1). In the water, we found a higher homogeneity in phyla distribution within each transect (significantly lower Euclidean distances between centered log-ratio (CLR)-converted phyla counts (betadispar): Atlantic: 0.3212 compared to 0.4229 in the air, ANOVA (with Tukey’s post hoc), p  More

  • in

    Consuming fresh macroalgae induces specific catabolic pathways, stress reactions and Type IX secretion in marine flavobacterial pioneer degraders

    Duarte C, Middelburg JJ, Caraco N. Major role of marine vegetation on the oceanic carbon cycle. Biogeosciences. 2005;2:1–8.CAS 
    Article 

    Google Scholar 
    Kloareg B, Quatrano RS. Structure of the cell walls of marine algae and ecophysiological functions of the matrix polysaccharides. Ocean Mar Biol Annu Rev. 1988;26:259–315.
    Google Scholar 
    Fletcher HR, Biller P, Ross AB, Adams JMM. The seasonal variation of fucoidan within three species of brown macroalgae. Algal Res. 2017;22:79–86.Article 

    Google Scholar 
    Deniaud-Bouët E, Hardouin K, Potin P, Kloareg B, Hervé C. A review about brown algal cell walls and fucose-containing sulfated polysaccharides: Cell wall context, biomedical properties and key research challenges. Carbohydr Polym. 2017;175:395–408.PubMed 
    Article 
    CAS 

    Google Scholar 
    Haug A, Larsen B, Smidsrød O. Uronic acid sequence in alginate from different sources. Carbohydr Res. 1974;32:217–225.CAS 
    Article 

    Google Scholar 
    Bruhn A, Janicek T, Manns D, Nielsen MM, Balsby TJS, Meyer AS, et al. Crude fucoidan content in two North Atlantic kelp species, Saccharina latissima and Laminaria digitata—seasonal variation and impact of environmental factors. J Appl Phycol. 2017;29:3121–3137.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Ponce NMA, Stortz CA. A comprehensive and comparative analysis of the fucoidan compositional data across the Phaeophyceae. Front Plant Sci. 2020;11:556312.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Fleurence J. The enzymatic degradation of algal cell walls: A useful approach for improving protein accessibility? J Appl Phycol. 1999;11:313–314.CAS 
    Article 

    Google Scholar 
    Verhaeghe EF, Fraysse A, Guerquin-Kern JL, Wu TD, Devès G, Mioskowski C, et al. Microchemical imaging of iodine distribution in the brown alga Laminaria digitata suggests a new mechanism for its accumulation. J Biol Inorg Chem. 2008;13:257–269.CAS 
    PubMed 
    Article 

    Google Scholar 
    Schiener P, Black KD, Stanley MS, Green DH. The seasonal variation in the chemical composition of the kelp species Laminaria digitata, Laminaria hyperborea, Saccharina latissima and Alaria esculenta. J Appl Phycol. 2015;27:363–373.CAS 
    Article 

    Google Scholar 
    Deniaud-Bouët E, Kervarec N, Michel G, Tonon T, Kloareg B, Hervé C. Chemical and enzymatic fractionation of cell walls from Fucales: Insights into the structure of the extracellular matrix of brown algae. Ann Bot. 2014;114:1203–1216.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Michel G, Tonon T, Scornet D, Cock JM, Kloareg B. Central and storage carbon metabolism of the brown alga Ectocarpus siliculosus: Insights into the origin and evolution of storage carbohydrates in Eukaryotes. N. Phytol. 2010;188:67–81.CAS 
    Article 

    Google Scholar 
    Mann K. Ecology of coastal waters—A systems approach, Berkeley: University of California Press; 1982.Egan S, Harder T, Burke C, Steinberg P, Kjelleberg S, Thomas T. The seaweed holobiont: Understanding seaweed-bacteria interactions. FEMS Microbiol Rev. 2013;37:462–476.CAS 
    PubMed 
    Article 

    Google Scholar 
    Kirchman DL. The ecology of Cytophaga-Flavobacteria in aquatic environments. FEMS Microbiol Ecol. 2002;39:91–100.CAS 
    PubMed 

    Google Scholar 
    Thomas F, Hehemann JH, Rebuffet E, Czjzek M, Michel G. Environmental and gut Bacteroidetes: The food connection. Front Microbiol. 2011;2:93.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Teeling H, Fuchs BM, Becher D, Klockow C, Gardebrecht A, Bennke CM, et al. Substrate-controlled succession of marine bacterioplankton populations induced by a phytoplankton bloom. Science. 2012;336:608–611.CAS 
    PubMed 
    Article 

    Google Scholar 
    Wietz M, Wemheuer B, Simon H, Giebel HA, Seibt MA, Daniel R, et al. Bacterial community dynamics during polysaccharide degradation at contrasting sites in the Southern and Atlantic Oceans. Environ Microbiol. 2015;17:3822–3831.CAS 
    PubMed 
    Article 

    Google Scholar 
    Arnosti C, Wietz M, Brinkhoff T, Hehemann J-H, Probant D, Zeugner L, et al. The biogeochemistry of marine polysaccharides: sources, inventories, and bacterial drivers of the carbohydrate cycle. Ann Rev Mar Sci. 2020;13:9.1–9.28.
    Google Scholar 
    Lombard V, Golaconda Ramulu H, Drula E, Coutinho PM, Henrissat B. The carbohydrate-active enzymes database (CAZy) in 2013. Nucleic Acids Res. 2014;42:490–495.Article 
    CAS 

    Google Scholar 
    Barbeyron T, Brillet-Guéguen L, Carré W, Carrière C, Caron C, Czjzek M, et al. Matching the diversity of sulfated biomolecules: Creation of a classification database for sulfatases reflecting their substrate specificity. PLoS One. 2016;11:1–33.Article 
    CAS 

    Google Scholar 
    Tang K, Lin Y, Han Y, Jiao N. Characterization of potential polysaccharide utilization systems in the marine Bacteroidetes Gramella flava JLT2011 using a multi-omics approach. Front Microbiol. 2017;8:220.PubMed 
    PubMed Central 

    Google Scholar 
    Zhu Y, Chen P, Bao Y, Men Y, Zeng Y, Yang J, et al. Complete genome sequence and transcriptomic analysis of a novel marine strain Bacillus weihaiensis reveals the mechanism of brown algae degradation. Sci Rep. 2016;6:38248.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Thomas F, Bordron P, Eveillard D, Michel G. Gene expression analysis of Zobellia galactanivorans during the degradation of algal polysaccharides reveals both substrate-specific and shared transcriptome-wide responses. Front Microbiol. 2017;8:1808.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Ficko-Blean E, Préchoux A, Thomas F, Rochat T, Larocque R, Zhu Y, et al. Carrageenan catabolism is encoded by a complex regulon in marine heterotrophic bacteria. Nat Commun. 2017;8:1685.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Koch H, Dürwald A, Schweder T, Noriega-Ortega B, Vidal-Melgosa S, Hehemann JH, et al. Biphasic cellular adaptations and ecological implications of Alteromonas macleodii degrading a mixture of algal polysaccharides. ISME J. 2019;13:92–103.CAS 
    PubMed 
    Article 

    Google Scholar 
    Bunse C, Koch H, Breider S, Simon M, Wietz M. Sweet spheres: succession and CAZyme expression of marine bacterial communities colonizing a mix of alginate and pectin particles. Environ Microbiol. 2021;23:3130–3148.CAS 
    PubMed 
    Article 

    Google Scholar 
    Hehemann JH, Arevalo P, Datta MS, Yu X, Corzett CH, Henschel A, et al. Adaptive radiation by waves of gene transfer leads to fine-scale resource partitioning in marine microbes. Nat Commun. 2016;7:12860.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Gralka M, Szabo R, Stocker R, Cordero OX. Trophic interactions and the drivers of microbial community assembly. Curr Biol. 2020;30:R1176–R1188.CAS 
    PubMed 
    Article 

    Google Scholar 
    Jiménez DJ, Dini-Andreote F, DeAngelis KM, Singer SW, Salles JF, van Elsas JD. Ecological insights into the dynamics of plant biomass-degrading microbial consortia. Trends Microbiol. 2017;25:788–796.PubMed 
    Article 
    CAS 

    Google Scholar 
    Kang S, Kim JK. Reuse of red seaweed waste by a novel bacterium, Bacillus sp. SYR4 isolated from a sandbar. World J Microbiol Biotechnol. 2015;31:209–217.PubMed 
    Article 

    Google Scholar 
    Jonnadula R, Verma P, Shouche YS, Ghadi SC. Characterization of Microbulbifer strain CMC-5, a new biochemical variant of Microbulbifer elongatus type strain DSM6810T isolated from decomposing seaweeds. Curr Microbiol. 2009;59:600–607.CAS 
    PubMed 
    Article 

    Google Scholar 
    Martin M, Barbeyron T, Martin R, Portetelle D, Michel G, Vandenbol M. The cultivable surface microbiota of the brown alga Ascophyllum nodosum is enriched in macroalgal-polysaccharide-degrading bacteria. Front Microbiol. 2015;6:1487.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Dogs M, Wemheuer B, Wolter L, Bergen N, Daniel R, Simon M, et al. Rhodobacteraceae on the marine brown alga Fucus spiralis are abundant and show physiological adaptation to an epiphytic lifestyle. Syst Appl Microbiol. 2017;40:370–382.CAS 
    PubMed 
    Article 

    Google Scholar 
    Brunet M, le Duff N, Fuchs B, Amann R, Barbeyron T, Thomas F. Specific detection and quantification of the marine flavobacterial genus Zobellia on macroalgae using novel qPCR and CARD-FISH assays. Syst Appl Microbiol. 2021;44:126269.CAS 
    PubMed 
    Article 

    Google Scholar 
    Barbeyron T, L’Haridon S, Corre E, Kloareg B, Potin P. Zobellia galactanovorans gen. nov., sp. nov., a marine species of Flavobacteriaceae isolated from a red alga, and classification of [Cytophaga] uliginosa (ZoBell and Upham 1944) Reichenbach 1989 as Zobellia uliginosa gen. nov., comb. nov. Int J Syst Evol Microbiol. 2001;51:985–997.CAS 
    PubMed 
    Article 

    Google Scholar 
    Barbeyron T, Thiébaud M, Le Duff N, Martin M, Corre E, Tanguy G, et al. Zobellia roscoffensis sp. nov. and Zobellia nedashkovskayae sp. nov., two flavobacteria from the epiphytic microbiota of the brown alga Ascophyllum nodosum, and emended description of the genus Zobellia. Int J Syst Evol Microbiol. 2021;71:004913.Nedashkovskaya OI, Suzuki M, Vancanneyt M, Cleenwerck I, Lysenko AM, Mikhailov VV, et al. Zobellia amurskyensis sp. nov., Zobellia laminariae sp. nov. and Zobellia russellii sp. nov., novel marine bacteria of the family Flavobacteriaceae. Int J Syst Evol Microbiol. 2004;54:1643–1648.CAS 
    PubMed 
    Article 

    Google Scholar 
    Nedashkovskaya O, Otstavnykh N, Zhukova N, Guzev K, Chausova V, Tekutyeva L, et al. Zobellia barbeyronii sp. nov., a new member of the family Flavobacteriaceae, isolated from seaweed, and emended description of the species Z. amurskyensis, Z. laminariae, Z. russellii and Z. uliginosa. Diversity. 2021;13:520.CAS 
    Article 

    Google Scholar 
    Chernysheva N, Bystritskaya E, Stenkova A, Golovkin I. Comparative genomics and CAZyme genome repertoires of marine Zobellia amurskyensis KMM 3526T and Zobellia laminariae KMM 3676T. Mar Drugs. 2019;17:661.CAS 
    PubMed Central 
    Article 

    Google Scholar 
    Chernysheva N, Bystritskaya E, Likhatskaya G, Nedashkovskaya O, Isaeva M. Genome-wide analysis of PL7 alginate lyases in the genus Zobellia. Molecules. 2021;26:2387.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Barbeyron T, Thomas F, Barbe V, Teeling H, Schenowitz C, Dossat C, et al. Habitat and taxon as driving forces of carbohydrate catabolism in marine heterotrophic bacteria: Example of the model algae-associated bacterium Zobellia galactanivorans DsijT. Environ Microbiol. 2016;18:4610–4627.CAS 
    PubMed 
    Article 

    Google Scholar 
    Potin P, Sanseau A, Le Gall Y, Rochas C, Kloareg B. Purification and characterization of a new k‐carrageenase from a marine Cytophaga‐like bacterium. Eur J Biochem. 1991;201:241–247.CAS 
    PubMed 
    Article 

    Google Scholar 
    Lami R, Grimaud R, Sanchez-Brosseau S, Six C, Thomas F, West NJ, et al. Marine bacterial models for experimental biology. In: Boutet A, Schierwater B, editors. Handbook of Marine Model Organisms in Experimental Biology. London: Taylor & Francis Ltd; 2021.Dudek M, Dieudonné A, Jouanneau D, Rochat T, Michel G, Sarels B, et al. Regulation of alginate catabolism involves a GntR family repressor in the marine flavobacterium Zobellia galactanivorans DsijT. Nucleic Acids Res. 2020;48:7786–7800.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Thomas F, Lundqvist LCE, Jam M, Jeudy A, Barbeyron T, Sandström C, et al. Comparative characterization of two marine alginate lyases from Zobellia galactanivorans reveals distinct modes of action and exquisite adaptation to their natural substrate. J Biol Chem. 2013;288:23021–23037.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Thomas F, Barbeyron T, Tonon T, Génicot S, Czjzek M, Michel G. Characterization of the first alginolytic operons in a marine bacterium: from their emergence in marine Flavobacteriia to their independent transfers to marine Proteobacteria and human gut Bacteroides. Environ Microbiol. 2012;14:2379–94.CAS 
    PubMed 
    Article 

    Google Scholar 
    Jam M, Flament D, Allouch J, Potin P, Thion L, Kloareg B, et al. The endo-β-agarases AgaA and AgaB from the marine bacterium Zobellia galactanivorans: Two paralogue enzymes with different molecular organizations and catalytic behaviours. Biochem J. 2005;385:703–713.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hehemann JH, Correc G, Thomas F, Bernard T, Barbeyron T, Jam M, et al. Biochemical and structural characterization of the complex agarolytic enzyme system from the marine bacterium Zobellia galactanivorans. J Biol Chem. 2012;287:30571–30584.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Labourel A, Jam M, Jeudy A, Hehemann JH, Czjzek M, Michel G. The β-glucanase ZgLamA from Zobellia galactanivorans evolved a bent active site adapted for efficient degradation of algal laminarin. J Biol Chem. 2014;289:2027–2042.CAS 
    PubMed 
    Article 

    Google Scholar 
    Labourel A, Jam M, Legentil L, Sylla B, Hehemann JH, Ferrières V, et al. Structural and biochemical characterization of the laminarinase ZgLamCGH16 from Zobellia galactanivorans suggests preferred recognition of branched laminarin. Acta Crystallogr. 2015;D71:173–184.
    Google Scholar 
    Dorival J, Ruppert S, Gunnoo M, Orłowski A, Chapelais-Baron M, Dabin J, et al. The laterally-acquired GH5 ZgEngAGH5_4 from the marine bacterium Zobellia galactanivorans is dedicated to hemicellulose hydrolysis. Biochem J. 2018;475:3609–3628.PubMed 
    Article 

    Google Scholar 
    Groisillier A, Labourel A, Michel G, Tonon T. The mannitol utilization system of the marine bacterium Zobellia galactanivorans. Appl Environ Microbiol. 2015;81:1799–1812.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Fournier JB, Rebuffet E, Delage L, Grijol R, Meslet-Cladière L, Rzonca J, et al. The vanadium iodoperoxidase from the marine Flavobacteriaceae species Zobellia galactanivorans reveals novel molecular and evolutionary features of halide specificity in the vanadium haloperoxidase enzyme family. Appl Environ Microbiol. 2014;80:7561–7573.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Grigorian E, Groisillier A, Thomas F, Leblanc C, Delage L. Functional characterization of a L-2-haloacid dehalogenase from Zobellia galactanivorans DsijT suggests a role in haloacetic acid catabolism and a wide distribution in marine environments. Front Microbiol. 2021;12:725997.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Zhu Y, Thomas F, Larocque R, Li N, Duffieux D, Cladière L, et al. Genetic analyses unravel the crucial role of a horizontally acquired alginate lyase for brown algal biomass degradation by Zobellia galactanivorans. Environ Microbiol. 2017;19:2164–2181.CAS 
    PubMed 
    Article 

    Google Scholar 
    Zablackis E, Perez J. A partially pyruvated carrageenan from hawaiian Grateloupia filicina (Cryptonemiales, Rhodophyta). Bot Mar. 1990;33:273–276.CAS 
    Article 

    Google Scholar 
    Filisetti-Cozzi T, Carpita N. Measurement of uronic acids without interference from neutral sugars. Anal Biochem. 1991;197:15162.Article 

    Google Scholar 
    Blumenkrantz N, Asboe-Hansen G. New method for quantitative determination of uronic acids. Anal Biochem. 1973;54:484–489.CAS 
    PubMed 
    Article 

    Google Scholar 
    Cumashi A, Ushakova NA, Preobrazhenskaya ME, D’Incecco A, Piccoli A, Totani L, et al. A comparative study of the anti-inflammatory, anticoagulant, antiangiogenic, and antiadhesive activities of nine different fucoidans from brown seaweeds. Glycobiology. 2007;17:541–552.CAS 
    PubMed 
    Article 

    Google Scholar 
    Jung SY, Oh TK, Yoon JH. Tenacibaculum aestuarii sp. nov., isolated from a tidal flat sediment in Korea. Int J Syst Evol Microbiol. 2006;56:1577–1581.CAS 
    PubMed 
    Article 

    Google Scholar 
    ZoBell C. Studies on marine bacteria. I. The cultural requirements of heterotrophic aerobes. J Mar Res. 1941;4:75.
    Google Scholar 
    Klindworth A, Pruesse E, Schweer T, Peplies J, Quast C, Horn M, et al. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res. 2013;41:e1.CAS 
    PubMed 
    Article 

    Google Scholar 
    Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C. Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods. 2017;14:417–419.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Vallenet D, Calteau A, Dubois M, Amours P, Bazin A, Beuvin M, et al. MicroScope: An integrated platform for the annotation and exploration of microbial gene functions through genomic, pangenomic and metabolic comparative analysis. Nucleic Acids Res. 2020;48:D579–D589.CAS 
    PubMed 

    Google Scholar 
    Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9:357–359.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25:2078–2079.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Thomas F, Barbeyron T, Michel G. Evaluation of reference genes for real-time quantitative PCR in the marine flavobacterium Zobellia galactanivorans. J Microbiol Methods. 2011;84:61–6.CAS 
    PubMed 
    Article 

    Google Scholar 
    Robinson JT, Thorvaldsdóttir H, Winckler W, Guttman M, Lander ES, Getz G, et al. Integrative genomics viewer. Nat Biotechnol. 2011;29:24–26.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:1–21.Article 
    CAS 

    Google Scholar 
    R Core Team. R: A language and environment for statistical computing. 2018. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.Lex A, Gehlenborg N, Strobelt H. UpSet: Visualization of intersecting sets. IEEE Trans Vis Comput Graph. 2014;20:1983–1992.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Krassowski M. krassowski/complex-upset. 2020. https://doi.org/10.5281/zenodo.3700590.Murtagh F, Legendre P. Ward’s hierarchical clustering method: clustering criterion and agglomerative algorithm. J Classif. 2014;31:274–295.Article 

    Google Scholar 
    Wickham H Use R! ggplot2: Elegant graphics for data analysis. 2nd ed. London: Springer; 2016.Kidby DK, Davidson DJ. Ferricyanide estimation of sugars in the nanomole range. Anal Biochem. 1973;55:321–325.CAS 
    PubMed 
    Article 

    Google Scholar 
    Zhang H, Yohe T, Huang L, Entwistle S, Wu P, Yang Z, et al. DbCAN2: A meta server for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 2018;46:W95–W101.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Chen X, Hu Y, Yang B, Gong X, Zhang N, Niu L, et al. Structure of lpg0406, a carboxymuconolactone decarboxylase family protein possibly involved in antioxidative response from Legionella pneumophila. Protein Sci. 2015;24:2070–2075.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Enke TN, Datta MS, Schwartzman J, Cermak N, Schmitz D, Barrere J, et al. Modular assembly of polysaccharide-degrading marine microbial communities. Curr Biol. 2019;29:1528–1535.e6.CAS 
    PubMed 
    Article 

    Google Scholar 
    Pollak S, Gralka M, Sato Y, Schwartzman J, Lu L, Cordero OX. Public good exploitation in natural bacterioplankton communities. Sci Adv. 2021;7:eabi4717.Pontrelli S, Szabo R, Pollak S, Schwartzman J, Ledezma D, Cordero OX, et al. Metabolic cross-feeding structures the assembly of polysaccharide degrading communities. Sci Adv. 2022;8:eabk3076.Holdt SL, Kraan S. Bioactive compounds in seaweed: Functional food applications and legislation. J Appl Phycol. 2011;23:543–597.CAS 
    Article 

    Google Scholar 
    Kawamura-Konishi Y, Watanabe N, Saito M, Nakajima N, Sakaki T, Katayama T, et al. Isolation of a new phlorotannin, a potent inhibitor of carbohydrate-hydrolyzing enzymes, from the brown alga Sargassum patens. J Agric Food Chem. 2012;60:5565–5570.CAS 
    PubMed 
    Article 

    Google Scholar 
    Garbary DJ, Brown NE, MacDonell HJ, Toxopeux J. Ascophyllum and its symbionts — A complex symbiotic community on North Atlantic shores. Algal and Cyanobacteria Symbioses. 2017:547–572.Pluvinage B, Grondin JM, Amundsen C, Klassen L, Moote PE, Xiao Y, et al. Molecular basis of an agarose metabolic pathway acquired by a human intestinal symbiont. Nat Commun. 2018;9:1043.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Reintjes G, Arnosti C, Fuchs BM, Amann R. An alternative polysaccharide uptake mechanism of marine bacteria. ISME J. 2017;11:1640–1650.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hollants J, Leliaert F, de Clerck O, Willems A. What we can learn from sushi: A review on seaweed-bacterial associations. FEMS Microbiol Ecol. 2013;83:1–16.CAS 
    PubMed 
    Article 

    Google Scholar 
    Thomas F, Le Duff N, Wu TD, Cébron A, Uroz S, Riera P, et al. Isotopic tracing reveals single-cell assimilation of a macroalgal polysaccharide by a few marine Flavobacteria and Gammaproteobacteria. ISME J. 2021;15:3062–3075.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Datta MS, Sliwerska E, Gore J, Polz MF, Cordero OX. Microbial interactions lead to rapid micro-scale successions on model marine particles. Nat Commun. 2016;7:11965.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Enke TN, Leventhal GE, Metzger M, Saavedra JT, Cordero OX. Microscale ecology regulates particulate organic matter turnover in model marine microbial communities. Nat Commun. 2018;9:2743.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Sichert A, Cordero OX. Polysaccharide-bacteria Interactions from the lens of evolutionary ecology. Front Microbiol. 2021;12:705082.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Sichert A, Corzett CH, Schechter M, Unfried F, Markert S, Becher D, et al. Verrucomicrobia use hundreds of enzymes to digest the algal polysaccharide fucoidan. Nat Microbiol. 2020;5:1026–1039.CAS 
    PubMed 
    Article 

    Google Scholar 
    Reisky L, Préchoux A, Zühlke MK, Bäumgen M, Robb CS, Gerlach N, et al. A marine bacterial enzymatic cascade degrades the algal polysaccharide ulvan. Nat Chem Biol. 2019;15:803–812.CAS 
    PubMed 
    Article 

    Google Scholar 
    Mabeau S, Kloareg B, Joseleau J-P. Fractionation and analysis of fucans from brown algae. Phytochemistry. 1990;29:2441–2445.CAS 
    Article 

    Google Scholar 
    Küpper FC, Kloareg B, Guern J, Potin P. Oligoguluronates elicit an oxidative burst in the brown algal kelp Laminaria digitata. Plant Physiol. 2001;125:278–291.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Küpper FC, Müller DG, Peters AF, Kloareg B, Potin P. Oligoalginate recognition and oxidative burst play a key role in natural and induced resistance of sporophytes of Laminariales. J Chem Ecol. 2002;28:2057–2081.PubMed 
    Article 

    Google Scholar 
    Leonard S, Hommais F, Nasser W, Reverchon S. Plant–phytopathogen interactions: bacterial responses to environmental and plant stimuli. Environ Microbiol. 2017;19:1689–1716.PubMed 
    Article 

    Google Scholar 
    Sato K, Naito M, Yukitake H, Hirakawa H, Shoji M, McBride MJ, et al. A protein secretion system linked to bacteroidete gliding motility and pathogenesis. PNAS. 2010;107:276–281.CAS 
    PubMed 
    Article 

    Google Scholar 
    Eckroat TJ, Greguske C, Hunnicutt DW. The type 9 secretion system is required for Flavobacterium johnsoniae biofilm formation. Front Microbiol. 2021;12:660887.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Xie S, Tan Y, Song W, Zhang W, Qi Q, Lu X. N-glycosylation of a cargo protein C-terminal domain recognized by the type IX secretion system in Cytophaga hutchinsonii affects protein secretion and localization. Appl Environ Microbiol. 2022;88:e0160621.PubMed 
    Article 

    Google Scholar  More

  • in

    Insect vector manipulation by a plant virus and simulation modeling of its potential impact on crop infection

    Whitfield, A. E., Falk, B. W. & Rotenberg, D. Insect vector-mediated transmission of plant viruses. Virology 479–480, 278–289. https://doi.org/10.1016/j.virol.2015.03.026 (2015).CAS 
    Article 
    PubMed 

    Google Scholar 
    Nault, L. R. Arthropod transmission of plant viruses: A new synthesis. Ann. Entomol. Soc. Am. 90, 521–541. https://doi.org/10.1093/aesa/90.5.521 (1997).Article 

    Google Scholar 
    Maluta, N., Fereres, A. & Lopes, J. R. S. Plant-mediated indirect effects of two viruses with different transmission modes on Bemisia tabaci feeding behavior and fitness. J. Pest Sci. 92, 405–416. https://doi.org/10.1007/s10340-018-1039-0 (2019).Article 

    Google Scholar 
    Scheirs, J. & De Bruyn, L. Integrating optimal foraging and optimal oviposition theory in plant–insect research. Oikos 96, 187–191. https://doi.org/10.1034/j.1600-0706.2002.960121.x (2002).Article 

    Google Scholar 
    Pyke, G. H. Optimal foraging theory: A critical review. Annu. Rev. Ecol. Syst. 15, 523–575. https://doi.org/10.1146/annurev.es.15.110184.002515 (1984).Article 

    Google Scholar 
    Hurd, H. Manipulation of medically important insect vectors by their parasites. Annu. Rev. Entomol. 48, 141–161. https://doi.org/10.1146/annurev.ento.48.091801.112722 (2003).CAS 
    Article 
    PubMed 

    Google Scholar 
    Moore, J. Parasites and the Behavior of Animals (Oxford University Press, 2002).
    Google Scholar 
    Eigenbrode, S. D., Bosque-Pérez, N. A. & Davis, T. S. Insect-borne plant pathogens and their vectors: Ecology, evolution, and complex interactions. Annu. Rev. Entomol. 63, 169–191. https://doi.org/10.1146/annurev-ento-020117-043119 (2018).CAS 
    Article 
    PubMed 

    Google Scholar 
    Mauck, K., Bosque-Pérez, N. A., Eigenbrode, S. D., De Moraes, C. M. & Mescher, M. C. Transmission mechanisms shape pathogen effects on host–vector interactions: Evidence from plant viruses. Funct. Ecol. 26, 1162–1175. https://doi.org/10.1111/j.1365-2435.2012.02026.x (2012).Article 

    Google Scholar 
    Blanc, S. & Michalakis, Y. Manipulation of hosts and vectors by plant viruses and impact of the environment. Curr. Opin. Insect. Sci. 16, 36–43. https://doi.org/10.1016/j.cois.2016.05.007 (2016).Article 
    PubMed 

    Google Scholar 
    Moreno-Delafuente, A., Garzo, E., Moreno, A. & Fereres, A. A plant virus manipulates the behavior of its whitefly vector to enhance its transmission efficiency and spread. PLoS ONE 8, e61543. https://doi.org/10.1371/journal.pone.0061543 (2013).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ng, J. C. K. & Falk, B. W. Virus-vector interactions mediating nonpersistent and semipersistent transmission of plant viruses. Annu. Rev. Phytopathol. 44, 183–212. https://doi.org/10.1146/annurev.phyto.44.070505.143325 (2006).CAS 
    Article 
    PubMed 

    Google Scholar 
    Stafford, C. A., Walker, G. P. & Ullman, D. E. Infection with a plant virus modifies vector feeding behavior. Proc. Natl. Acad. Sci. 108, 9350–9355. https://doi.org/10.1073/pnas.1100773108 (2011).ADS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rajabaskar, D., Bosque-Pérez, N. A. & Eigenbrode, S. D. Preference by a virus vector for infected plants is reversed after virus acquisition. Virus Res. 186, 32–37. https://doi.org/10.1016/j.virusres.2013.11.005 (2014).CAS 
    Article 
    PubMed 

    Google Scholar 
    Su, Q. et al. Manipulation of host quality and defense by a plant virus improves performance of whitefly vectors. J. Econ. Entomol. 108, 11–19. https://doi.org/10.1093/jee/tou012 (2015).Article 
    PubMed 

    Google Scholar 
    Chen, G. et al. Virus infection of a weed increases vector attraction to and vector fitness on the weed. Sci. Rep. 3, 2253. https://doi.org/10.1038/srep02253 (2013).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wei, J. et al. Vector development and vitellogenin determine the transovarial transmission of begomoviruses. Proc. Natl. Acad. Sci. 114, 6746–6751. https://doi.org/10.1073/pnas.1701720114 (2017).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ogada, P. A., Moualeu, D. P. & Poehling, H.-M. Predictive models for tomato spotted wilt virus spread dynamics, considering Frankliniella occidentalis specific life processes as influenced by the virus. PLoS ONE 11, e0154533. https://doi.org/10.1371/journal.pone.0154533 (2016).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Shoemaker, L. G. et al. Pathogens manipulate the preference of vectors, slowing disease spread in a multi-host system. Ecol. Lett. 22, 1115–1125. https://doi.org/10.1111/ele.13268 (2019).Article 
    PubMed 

    Google Scholar 
    Shelton, A. M. & Badenes-Perez, F. R. Concepts and applications of trap cropping in pest management. Annu. Rev. Entomol. 51, 285–308. https://doi.org/10.1146/annurev.ento.51.110104.150959 (2006).CAS 
    Article 
    PubMed 

    Google Scholar 
    Bennett, C. W. The Curly Top Disease of Sugarbeet and Other Plants (The American Phytopathological Society, 1971).Book 

    Google Scholar 
    Chen, L.-F. & Gilbertson, R. L. Chapter 17: Transmission of curtoviruses (beet curly top virus) by the beet leafhopper (Circulifer tenellus). In Vector-Mediated Transmission of Plant Pathogens (ed. Brown, J. K.) 243–262 (The American Phytopathological Society of America, 2016).Chapter 

    Google Scholar 
    Creamer, R. Chapter 37: Beet curly top virus transmission, epidemiology, and management. In Applied Plant Virology (ed. Awasthi, L. P.) 521–527 (Academic Press, 2020).Chapter 

    Google Scholar 
    Gilbertson, R. L., Melgarejo, T. A., Rojas, M. R., Wintermantel, W. M. & Stanley, J. Beet curly top virus (Geminiviridae). In Encyclopedia of Virology 4th edn (eds Bamford, D. H. & Zuckerman, M.) 200–212 (Academic Press, 2021).Chapter 

    Google Scholar 
    Hudson, A., Richman, D. B., Escobar, I. & Creamer, R. Comparison of the feeding behavior and genetics of beet leafhopper, Circulifer tenellus, populations from California and New Mexico. Southwest. Entomol. 35, 241–250, 210 (2010).Article 

    Google Scholar 
    Soto, M. J. & Gilbertson, R. L. Distribution and rate of movement of the curtovirus Beet mild curly top virus (Family Geminiviridae) in the beet leafhopper. Phytopathology 93, 478–484. https://doi.org/10.1094/phyto.2003.93.4.478 (2003).Article 
    PubMed 

    Google Scholar 
    Prager, S. M., Lewis, O. M., Michels, J. & Nansen, C. The influence of maturity and variety of potato plants on oviposition and probing of Bactericera cockerelli (Hemiptera: Triozidae). Environ. Entomol. 43, 402–409. https://doi.org/10.1603/en13278 (2014).Article 
    PubMed 

    Google Scholar 
    Prager, S. M., Vaughn, K., Lewis, M. & Nansen, C. Oviposition and leaf probing by Bactericera cockerelli (Homoptera: Psyllidae) in response to a limestone particle film or a plant growth regulator applied to potato plants. Crop Prot. 45, 57–62 (2013).CAS 
    Article 

    Google Scholar 
    McBryde, M. C. A method of demonstrating rust hyphae and Haustoria in unsectioned leaf tissue. Am. J. Bot. 23, 686–688 (1936).Article 

    Google Scholar 
    Backus, E. A., Hunter, W. B. & Arne, C. N. Technique for staining leafhopper (Homoptera: Cicadellidae) salivary sheaths and eggs within unsectioned plant tissue. J. Econ. Entomol. 81, 1819–1823. https://doi.org/10.1093/jee/81.6.1819 (1988).Article 

    Google Scholar 
    R Core Team. R: A language and environment for statistical computing (R Foundation for Statistical computing, Vienna, Austria, 2019).Stafford, C. A., Walker, G. P. & Creamer, R. Stylet penetration behavior resulting in inoculation of beet severe curly top virus by beet leafhopper, Circulifer tenellus. Entomol. Exp. Appl. 130, 130–137. https://doi.org/10.1111/j.1570-7458.2008.00813.x (2009).Article 

    Google Scholar 
    Chen, L.-F., Brannigan, K., Clark, R. & Gilbertson, R. L. Characterization of curtoviruses associated with curly top disease of tomato in California and monitoring for these viruses in beet leafhoppers. Plant Dis. 94, 99–108. https://doi.org/10.1094/pdis-94-1-0099 (2010).CAS 
    Article 
    PubMed 

    Google Scholar 
    Rojas, M. R. et al. World management of geminiviruses. Annu. Rev. Phytopathol. 56, 637–677. https://doi.org/10.1146/annurev-phyto-080615-100327 (2018).CAS 
    Article 
    PubMed 

    Google Scholar 
    Schoonhoven, L. M., Van Loon, B., van Loon, J. J. & Dicke, M. Insect-plant biology (Oxford University Press, 2005).
    Google Scholar 
    Mauck, K. E., Kenney, J. & Chesnais, Q. Progress and challenges in identifying molecular mechanisms underlying host and vector manipulation by plant viruses. Curr. Opin. Insect. Sci. 33, 7–18. https://doi.org/10.1016/j.cois.2019.01.001 (2019).Article 
    PubMed 

    Google Scholar 
    Pelosi, P., Iovinella, I., Felicioli, A. & Dani, F. R. Soluble proteins of chemical communication: An overview across arthropods. Front. Physiol 5, 320. https://doi.org/10.3389/fphys.2014.00320 (2014).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pelosi, P., Zhou, J. J., Ban, L. P. & Calvello, M. Soluble proteins in insect chemical communication. Cell. Mol. Life Sci. 63, 1658–1676. https://doi.org/10.1007/s00018-005-5607-0 (2006).CAS 
    Article 
    PubMed 

    Google Scholar 
    Matsuo, T., Sugaya, S., Yasukawa, J., Aigaki, T. & Fuyama, Y. Odorant-binding proteins OBP57d and OBP57e affect taste perception and host-plant preference in Drosophila sechellia. PLoS Biol. 5, e118. https://doi.org/10.1371/journal.pbio.0050118 (2007).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Li, Z. et al. Mouthparts enriched odorant binding protein AfasOBP11 plays a role in the gustatory perception of Adelphocoris fasciaticollis. J. Insect Physiol. 117, 103915. https://doi.org/10.1016/j.jinsphys.2019.103915 (2019).CAS 
    Article 
    PubMed 

    Google Scholar 
    Waris, M. I. et al. Silencing of chemosensory protein gene NlugCSP8 by RNAi induces declining behavioral responses of Nilaparvata lugens. Front. Physiol. 9, 379. https://doi.org/10.3389/fphys.2018.00379 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hu, K. et al. Odorant-binding protein 2 is involved in the preference of Sogatella furcifera (Hemiptera: Delphacidae) for rice plants infected with the Southern rice black-streaked dwarf virus. Fla. Entomol. 102, 353–358. https://doi.org/10.1653/024.102.0210 (2019).CAS 
    Article 

    Google Scholar 
    Brentassi, M. E., Machado-Assefh, C. R. & Alvarez, A. E. The probing behaviour of the planthopper Delphacodes kuscheli (Hemiptera: Delphacidae) on two alternating hosts, maize and oat. Aust. Entomol. 58, 666–674. https://doi.org/10.1111/aen.12383 (2019).Article 

    Google Scholar 
    Milenovic, M., Wosula, E. N., Rapisarda, C. & Legg, J. P. Impact of host plant species and whitefly species on feeding behavior of Bemisia tabaci. Front. Plant Sci. 10, 1. https://doi.org/10.3389/fpls.2019.00001 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Stafford, C. A. & Walker, G. P. Characterization and correlation of DC electrical penetration graph waveforms with feeding behavior of beet leafhopper, Circulifer tenellus. Entomol. Exp. Appl. 130, 113–129. https://doi.org/10.1111/j.1570-7458.2008.00812.x (2009).Article 

    Google Scholar 
    Mauck, K. E., Chesnais, Q. & Shapiro, L. R. Evolutionary determinants of host and vector manipulation by plant viruses. In Advances in Virus Research (ed. Malmstrom, C. M.) 189–250 (Academic Press, 2018).
    Google Scholar 
    Chesnais, Q. et al. Virus effects on plant quality and vector behavior are species specific and do not depend on host physiological phenotype. J. Pest Sci. 92, 791–804 (2019).Article 

    Google Scholar  More

  • in

    Plant beta-diversity across biomes captured by imaging spectroscopy

    Díaz, S. et al. Summary for policymakers of the global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. https://doi.org/10.5281/zenodo.3553579 (2019).Fei, S. et al. Divergence of species responses to climate change. Sci. Adv. 3, e1603055 (2017).ADS 
    Article 

    Google Scholar 
    Jetz, W. et al. Monitoring plant functional diversity from space. Nat. Plants 2, 16024 (2016).Article 

    Google Scholar 
    HyspIRI Mission Concept Team. HyspIRI Final Report. https://hyspiri.jpl.nasa.gov/downloads/reports_whitepapers/HyspIRI_FINAL_Report_1October2018_20181005a.pdf. Jet Propulsion Laboratories, California Institute of Technology, Pasadena, CA, USA (2018).Turner, W. Sensing biodiversity. Science 346, 301–302 (2014).ADS 
    CAS 
    Article 

    Google Scholar 
    Ustin, S. L. & Middleton, E. M. Current and near-term advances in Earth observation for ecological applications. Ecol. Process. 10, 1 (2021).Article 

    Google Scholar 
    Cawse-Nicholson, K. et al. NASA’s surface biology and geology designated observable: a perspective on surface imaging algorithms. Remote Sens. Environ. 257, 112349 (2021).ADS 
    Article 

    Google Scholar 
    Stavros, E. N. et al. ISS Observations Offer Insights Into Plant Function. Nature Ecology and Evolution 1, https://doi.org/10.1038/s41559-017-0194 (2017).Rast, M., Nieke, J., Adams, J., Isola, C. & Gascon, F. Copernicus Hyperspectral Imaging Mission for the Environment (Chime). IEEE International Geoscience and Remote Sensing Symposium IGARSS, 108–111, https://doi.org/10.1109/IGARSS47720.2021.9553319 (2021).Cogliati, S. et al. The PRISMA imaging spectroscopy mission: overview and first performance analysis. Remote Sens. Environ. 262, 112499 (2021).ADS 
    Article 

    Google Scholar 
    Asner, G. P. et al. Airborne laser-guided imaging spectroscopy to map forest trait diversity and guide conservation. Science 355, 385–389 (2017).ADS 
    CAS 
    Article 

    Google Scholar 
    Meireles, J. E. et al. Leaf reflectance spectra capture the evolutionary history of seed plants. N. Phytologist 228, 485–493 (2020).Article 

    Google Scholar 
    Schweiger, A. K. et al. Plant spectral diversity integrates functional and phylogenetic components of biodiversity and predicts ecosystem function. Nat. Ecol. Evolution https://doi.org/10.1038/s41559-018-0551-1 (2018).Article 

    Google Scholar 
    Cavender-Bares, J. et al. Harnessing plant spectra to integrate the biodiversity sciences across biological and spatial scales. Am. J. Bot. 104, 966–969 (2017).Article 

    Google Scholar 
    Laliberté, E., Schweiger, A. K. & Legendre, P. Partitioning plant spectral diversity into alpha and beta components. Ecol. Lett. 23, 370–380 (2020).Article 

    Google Scholar 
    Rocchini, D. et al. Remotely sensed spectral heterogeneity as a proxy of species diversity: recent advances and open challenges. Ecol. Inform. 5, 318–329 (2010).Article 

    Google Scholar 
    Gholizadeh, H. et al. Detecting prairie biodiversity with airborne remote sensing. Remote Sens. Environ. 221, 38–49 (2019).ADS 
    Article 

    Google Scholar 
    Wang, R. et al. Influence of species richness, evenness, and composition on optical diversity: a simulation study. Remote Sens. Environ. 211, 218–228 (2018).ADS 
    Article 

    Google Scholar 
    Féret, J.-B. & Asner, G. P. Mapping tropical forest canopy diversity using high‐fidelity imaging spectroscopy. Ecol. Appl. 24, 1289–1296 (2014).Article 

    Google Scholar 
    Draper, F. C. et al. Imaging spectroscopy predicts variable distance decay across contrasting Amazonian tree communities. J. Ecol. 107, 696–710 (2019).Article 

    Google Scholar 
    Wang, R., Gamon, J. A., Cavender‐Bares, J., Townsend, P. A. & Zygielbaum, A. I. The spatial sensitivity of the spectral diversity–biodiversity relationship: an experimental test in a prairie grassland. Ecol. Appl. 28, 541–556 (2018).Article 

    Google Scholar 
    Rossi, C. et al. Spatial resolution, spectral metrics and biomass are key aspects in estimating plant species richness from spectral diversity in species-rich grasslands. Remote Sens. Ecol. Conserv. https://doi.org/10.1002/rse2.244 (2021).Article 

    Google Scholar 
    Finderup Nielsen, T., Sand-Jensen, K., Dornelas, M. & Bruun, H. H. More is less: net gain in species richness, but biotic homogenization over 140 years. Ecol. Lett. 22, 1650–1657 (2019).Article 

    Google Scholar 
    McKinney, M. L. & Lockwood, J. L. Biotic homogenization: a few winners replacing many losers in the next mass extinction. Trends Ecol. Evolution 14, 450–453 (1999).CAS 
    Article 

    Google Scholar 
    Anderson, M. J. et al. Navigating the multiple meanings of β diversity: a roadmap for the practicing ecologist. Ecol. Lett. 14, 19–28 (2011).ADS 
    Article 

    Google Scholar 
    Rocchini, D. et al. Measuring β‐diversity by remote sensing: a challenge for biodiversity monitoring. Methods Ecol. Evolution 9, 1787–1798 (2018).Article 

    Google Scholar 
    Chadwick, K. D. & Asner, G. P. Landscape evolution and nutrient rejuvenation reflected in Amazon forest canopy chemistry. Ecol. Lett. 21, 978–988 (2018).Article 

    Google Scholar 
    Felsenstein, J. Phylogenies and the comparative method. American Naturalist, 1-15, https://doi.org/10.1086/284325 (1985).Wang, R. & Gamon, J. A. Remote sensing of terrestrial plant biodiversity. Remote Sens. Environ. 231, 111218 (2019).ADS 
    Article 

    Google Scholar 
    Schimel, D. S., Asner, G. P. & Moorcroft, P. Observing changing ecological diversity in the Anthropocene. Front. Ecol. Environ. 11, 129–137 (2013).Article 

    Google Scholar 
    NEON (National Ecological Observatory Network). Spectrometer orthorectified surface directional reflectance—mosaic, RELEASE-2021 (DP3.30006.001). https://doi.org/10.48443/qeae-3×15. Dataset accessed from https://data.neonscience.org on March (2021).Richter, R. & Schläpfer, D. Geo-atmospheric processing of airborne imaging spectrometry data. Part 2: Atmospheric/topographic correction. Int. J. Remote Sens. 23, 2631–2649 (2002).Article 

    Google Scholar 
    Asner, G. P. & Martin, R. E. Airborne spectranomics: mapping canopy chemical and taxonomic diversity in tropical forests. Front. Ecol. Environ. 7, 269–276 (2009).Article 

    Google Scholar 
    Rüfenacht, D., Fredembach, C. & Süsstrunk, S. Automatic and accurate shadow detection using near-infrared information. IEEE Trans. pattern Anal. Mach. Intell. 36, 1672–1678 (2013).Article 

    Google Scholar 
    NEON (National Ecological Observatory Network). High-resolution orthorectified camera imagery mosaic, RELEASE-2021 (DP3.30010.001). https://doi.org/10.48443/4e85-cr14. Dataset accessed from https://data.neonscience.org on March 3 (2021).Feilhauer, H., Asner, G. P., Martin, R. E. & Schmidtlein, S. Brightness-normalized partial least squares regression for hyperspectral data. J. Quant. Spectrosc. Radiat. Transf. 111, 1947–1957 (2010).ADS 
    CAS 
    Article 

    Google Scholar 
    NEON (National Ecological Observatory Network). Plant presence and percent cover, RELEASE-2021 (DP1.10058.001). https://doi.org/10.48443/abge-r811. Dataset accessed from https://data.neonscience.org on March 3 (2021).NEON (National Ecological Observatory Network). Woody plant vegetation structure, RELEASE-2021 (DP1.10098.001). https://doi.org/10.48443/e3qn-xw47. Dataset accessed from https://data.neonscience.org on March 3 (2021).Schweiger, A. K. NEON_crown_area (1.0.0). https://doi.org/10.5281/zenodo.6383923 (2022).R Foundation for Statistical Computing. R: A language and environment for statistical computing (R Foundation for Statistical Computing, 2019).Oksanen, J. et al. vegan: Community Ecology Package. R package version 2.5-7 (2020).Jin, Y. & Qian, H. V. PhyloMaker: an R package that can generate very large phylogenies for vascular plants. Ecography 42, 1353–1359 (2019).Article 

    Google Scholar 
    Smith, S. A. & Brown, J. W. Constructing a broadly inclusive seed plant phylogeny. Am. J. Bot. 105, 302–314 (2018).Article 

    Google Scholar 
    Kembel, S. W. et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26, 1463–1464 (2010).CAS 
    Article 

    Google Scholar 
    NEON (National Ecological Observatory Network). Plant foliar traits, RELEASE-2021 (DP1.10026.001). https://doi.org/10.48443/za0d-wn97. Dataset accessed from https://data.neonscience.org on March 3 (2021).Legendre, P. & De Cáceres, M. Beta diversity as the variance of community data: dissimilarity coefficients and partitioning. Ecol. Lett. 16, 951–963 (2013).Article 

    Google Scholar 
    Dray, S. & Dufour, A.-B. The ade4 package: implementing the duality diagram for ecologists. J. Stat. Softw. 22, 1–20 (2007).Article 

    Google Scholar 
    Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. & Team, R. C. nlme: Linear and nonlinear mixed effects models. R package version 3.1-152 (2021).NEON (National Ecological Observatory Network). LAI—spectrometer—mosaic, RELEASE-2021 (DP3.30012.001). https://doi.org/10.48443/h2rb-pj34. Dataset accessed from https://data.neonscience.org on March 3 (2021). More

  • in

    Behavioural and electrophysiological responses of Philaenus spumarius to odours from conspecifics

    Saponari, M., Boscia, D., Nigro, F. & Martelli, G. P. Identification of DNA sequences related to Xylella fastidiosa in oleander, almond and olive trees exhibiting leaf scorch symptoms in Apulia (Southern Italy). J. Plant Pathol. 95, 668 (2013).
    Google Scholar 
    Janse, J. D. & Obradovic, A. Xylella fastidiosa: Its biology, diagnosis, control and risks. J. Plant Pathol. 92, 35–48 (2010).
    Google Scholar 
    EPPO EPPO Global Database (available online). https://gd.eppo.int (2022)Article 

    Google Scholar 
    Bragard, C. et al. Update of the scientific opinion on the risks to plant health posed by Xylella fastidiosa in the EU territory. EFSA J. 17, 5665 (2019).
    Google Scholar 
    Nunney, L., Ortiz, B., Russell, S. A., Sánchez, R. R. & Stouthamer, R. The complex biogeography of the plant pathogen Xylella fastidiosa: Genetic evidence of introductions and subspecific introgression in central America. PLoS ONE 9, e112463 (2014).PubMed 
    PubMed Central 
    Article 
    ADS 
    CAS 

    Google Scholar 
    Sicard, A. et al. Introduction and adaptation of an emerging pathogen to olive trees in Italy. Microb. Genom. 7, 000735 (2021).CAS 
    PubMed Central 

    Google Scholar 
    Cornara, D. et al. Transmission of Xylella fastidiosa by naturally infected Philaenus spumarius (Hemiptera, Aphrophoridae) to different host plants. J. Appl. Entomol. 141, 80–87 (2017).Article 

    Google Scholar 
    Cornara, D. et al. Spittlebugs as vectors of Xylella fastidiosa in olive orchards in Italy. J. Pest Sci. 2004, 521–530 (2017).Article 

    Google Scholar 
    Bodino, N. et al. Phenology, seasonal abundance and stage-structure of spittlebug (Hemiptera: Aphrophoridae) populations in olive groves in Italy. Sci. Rep. 9, 17725 (2019).PubMed 
    PubMed Central 
    Article 
    ADS 
    CAS 

    Google Scholar 
    Di Serio, F. et al. Collection of data and information on biology and control of vectors of Xylella fastidiosa. EFSA Support. Publ. 16, 2 (2019).
    Google Scholar 
    Bayram, A., Salerno, G., Onofri, A. & Conti, E. Lethal and sublethal effects of preimaginal treatments with two pyrethroids on the life history of the egg parasitoid Telenomus busseolae. Biocontrol 55, 697–710 (2010).CAS 
    Article 

    Google Scholar 
    Saponari, M., Giampetruzzi, A., Loconsole, G., Boscia, D. & Saldarelli, P. Xylella fastidiosa in olive in Apulia: Where we stand. Phytopathology 109, 175–186 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Virant-Doberlet, M. & Cokl, A. Vibrational communication in insects. Neotrop. Entomol. 33, 121–134 (2004).Article 

    Google Scholar 
    Avosani, S. et al. Vibrational communication and mating behavior of the meadow spittlebug Philaenus spumarius. Entomol. Gen. 40, 307–321 (2020).Article 

    Google Scholar 
    Polajnar, J., Eriksson, A., Virant-Doberlet, M. & Mazzoni, V. Mating disruption of a grapevine pest using mechanical vibrations: From laboratory to the field. J. Pest Sci. 2004(89), 909–921 (2016).Article 

    Google Scholar 
    Boullis, A. & Verheggen, F. J. Chemical ecology of aphids (Hemiptera: Aphididae). In Biology and Ecology of Aphids (ed. Vilcinskas, A.) 181–208 (CRC Press, 2016). https://doi.org/10.1201/b19967-11.Chapter 

    Google Scholar 
    Ganassi, S. et al. Evidence of a female-produced sex pheromone in the European pear psylla Cacopsylla pyri. Bull. Insectol. 71, 57–64 (2018).
    Google Scholar 
    Tabata, J. & Ichiki, R. T. Sex pheromone of the cotton mealybug, Phenacoccus solenopsis, with an unusual cyclobutane structure. J. Chem. Ecol. 42, 1193–1200 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Millar, J. G. Pheromones of true bugs. Top. Curr. Chem. 240, 37–84 (2000).Article 
    CAS 

    Google Scholar 
    Khrimian, A. et al. Discovery of the aggregation pheromone of the brown marmorated stink bug (Halyomorpha halys) through the creation of stereoisomeric libraries of 1-Bisabolen-3-ols. J. Nat. Prod. 77, 1708–1717 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    Borges, M., Blassioli-Moraes, M. C., Laumann, R. A. & Čokl, A. Suggestions for neotropic stink bug pest status and control. In Stink Bugs: Biorational Control Based on Communication Processes (eds Cokl, A. & Borges, M.) 246–254 (CRC Press, 2017). https://doi.org/10.1201/9781315120713.Chapter 

    Google Scholar 
    Ranieri, E., Ruschioni, S., Riolo, P., Isidoro, N. & Romani, R. Fine structure of antennal sensilla of the spittlebug Philaenus spumarius L. (Insecta: Hemiptera: Aphrophoridae). I. Chemoreceptors and thermo-/hygroreceptors. Arthropod Struct. Dev. 45, 432–439 (2016).PubMed 
    Article 

    Google Scholar 
    Germinara, G. S. et al. Antennal olfactory responses of adult meadow spittlebug, Philaenus spumarius, to volatile organic compounds (VOCs). PLoS ONE 12, e0190454 (2017).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Ganassi, S. et al. Electrophysiological and behavioural response of Philaenus spumarius to essential oils and aromatic plants. Sci. Rep. 10, 3114 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    Nault, L. R., Wood, T. K. & Goff, A. M. Treehopper (Membracidae) alarm pheromones. Nature 249, 387–388 (1974).CAS 
    PubMed 
    Article 
    ADS 

    Google Scholar 
    Chen, X. & Liang, A. P. Identification of a self-regulatory pheromone system that controls nymph aggregation behavior of rice spittlebug Callitettix versicolor. Front. Zool. 12, 10 (2015).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Liang, A. P. A new structure on the frons of male adults of the Asian rice spittlebug Callitettix versicolor (Hemiptera: Auchenorrhyncha: Cercopidae). Zootaxa 4801, 591–599 (2020).Article 

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

    Google Scholar 
    Mazzoni, V. et al. Mating disruption by vibrational signals: state of the field and perspectives. In Biotremology: Studying Vibrational Behavior (eds Hill, P. S. M. et al.) 331–354 (Springer, Cham, 2019). https://doi.org/10.1007/978-3-030-22293-2_17.Chapter 

    Google Scholar 
    Bachmann, G. E. et al. Male sexual behavior and pheromone emission is enhanced by exposure to guava fruit volatiles in Anastrepha fraterculus. PLoS ONE 10, e0124250 (2015).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Frati, F., Salerno, G., Conti, E. & Bin, F. Role of the plant–conspecific complex in host location and intra-specific communication of Lygus rugulipennis. Physiol. Entomol. 33, 129–137 (2008).Article 

    Google Scholar 
    Frati, F. et al. Vicia faba–Lygus rugulipennis interactions: Induced plant volatiles and sex pheromone enhancement. J. Chem. Ecol. 35, 201–208 (2009).CAS 
    PubMed 
    Article 

    Google Scholar 
    Lubanga, U. K., Guédot, C., Percy, D. M. & Steinbauer, M. J. Semiochemical and vibrational cues and signals mediating mate finding and courtship in Psylloidea (Hemiptera): A synthesis. Insects 5, 577–595 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Borges, M. & Blassioli-Moraes, M. C. The semiochemistry of Pentatomidae. In Stink Bugs: Biorational Control Based on Communication Processes 95–124 (CRC Press, 2017). https://doi.org/10.1201/9781315120713.Chapter 

    Google Scholar 
    Yin, L. & Maschwitz, U. Sexual pheromone in the green house whitefly Trialeurodes vaporariorum Westw. Zeitschrift für Angew. Entomol. 95, 439–446 (1983).Article 

    Google Scholar 
    Dawson, G. W. et al. Identification of an aphid sex pheromone. Nature 325, 614–616 (1987).CAS 
    Article 
    ADS 

    Google Scholar 
    Zanardi, O. Z. et al. Putative sex pheromone of the Asian citrus psyllid, Diaphorina citri, breaks down into an attractant. Sci. Rep. 8, 455 (2018).PubMed 
    PubMed Central 
    Article 
    ADS 
    CAS 

    Google Scholar 
    Sevarika, M., di Giulio, A., Rondoni, G., Conti, E. & Romani, R. Morpho-functional analysis of the head glands in three Auchenorrhynca species and their possible biological significance. bioRxiv 03.03.482260 (2022).Mazzoni, V. et al. Use of substrate-borne vibrational signals to attract the brown marmorated stink bug Halyomorpha halys. J. Pest Sci. 2004, 1219–1229 (2017).Article 

    Google Scholar 
    Avosani, S., Franceschi, P., Ciolli, M., Verrastro, V. & Mazzoni, V. Vibrational playbacks and microscopy to study the signalling behaviour and female physiology of Philaenus spumarius. J. Appl. Entomol. https://doi.org/10.1111/jen.12874 (2021).Article 

    Google Scholar 
    Stewart, A. J. A. & Lees, D. R. Genetic control of colour polymorphism in spittlebugs (Philaenus spumarius) differs between isolated populations. Heredity (Edinb). 59, 445–448 (1987).Article 

    Google Scholar 
    Stewart, A. J. A. The colour/pattern polymorphism of Philaenus spumarius (L.) (Homoptera: Cercopidae) in England and Wales. Philos. Trans. R. Soc. B Biol. Sci. 351, 69–89 (1996).Article 
    ADS 

    Google Scholar 
    Moyal, P. et al. Origin and taxonomic status of the Palearctic population of the stem borer Sesamia nonagrioides (Lefèbvre) (Lepidoptera: Noctuidae). Biol. J. Linn. Soc. 103, 904–922 (2011).Article 

    Google Scholar 
    Glaser, N. et al. Differential expression of the chemosensory transcriptome in two populations of the stemborer Sesamia nonagrioides. Insect Biochem. Mol. Biol. 65, 28–34 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Bodino, N. et al. Spittlebugs of mediterranean olive groves: host-plant exploitation throughout the year. Insects 11, 130 (2020).PubMed Central 
    Article 

    Google Scholar 
    Cook, S. M., Khan, Z. R. & Pickett, J. A. The use of push-pull strategies in integrated pest management. Annu. Rev. Entomol. 52, 375–400 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    Molinatto, G. et al. Biology and prevalence in Northern Italy of Verrallia aucta (Diptera, Pipunculidae), a parasitoid of Philaenus spumarius (Hemiptera, Aphrophoridae), the main vector of Xylella fastidiosa in Europe. Insects 11, 607 (2020).PubMed Central 
    Article 

    Google Scholar 
    Mesmin, X. et al. Ooctonus vulgatus (Hymenoptera, Mymaridae), a potential biocontrol agent to reduce populations of Philaenus spumarius (Hemiptera, Aphrophoridae) the main vector of Xylella fastidiosa in Europe. PeerJ 2020, e8591 (2020).Article 

    Google Scholar 
    Conti, E., Jones, W. A., Bin, F. & Vinson, S. B. Physical and chemical factors involved in host recognition behavior of Anaphes iole Girault, an egg parasitoid of Lygus hesperus knight (Hymenoptera: Mymaridae; Heteroptera: Miridae). Biol. Control 7, 10–16 (1996).Article 

    Google Scholar 
    Conti, E., Jones, W. A., Bin, F. & Vinson, S. B. Oviposition behavior of Anaphes iole, an egg parasitoid of Lygus hesperus (Hymenoptera: Mymaridae; Heteroptera: Miridae). Ann. Entomol. Soc. Am. 90, 91–101 (1997).Article 

    Google Scholar 
    Chiappini, E. et al. Role of volatile semiochemicals in host location by the egg parasitoid Anagrus breviphragma. Entomol. Exp. Appl. 144, 311–316 (2012).CAS 
    Article 

    Google Scholar 
    Conti, E. et al. Biological control of invasive stink bugs: review of global state and future prospects. Entomol. Exp. Appl. 169, 28–51 (2021).Article 

    Google Scholar 
    Rondoni, G. et al. Native egg parasitoids recorded from the invasive Halyomorpha halys successfully exploit volatiles emitted by the plant–herbivore complex. J. Pest Sci. 2004, 1087–1095 (2017).Article 

    Google Scholar 
    Rondoni, G., Ielo, F., Ricci, C. & Conti, E. Behavioural and physiological responses to prey-related cues reflect higher competitiveness of invasive vs native ladybirds. Sci. Rep. 7, 3716 (2017).PubMed 
    PubMed Central 
    Article 
    ADS 
    CAS 

    Google Scholar 
    Colazza, S. et al. Xbug, a video tracking and motion analysis system for LINUX. in XII International Entomophagous Insects Workshop. Pacific Grove, California (1999).De Cristofaro, A. et al. Electrophysiological responses of Cydia pomonella to codlemone and pear ester ethyl (E, Z)-2,4-decadienoate: Peripheral interactions in their perception and evidences for cells responding to both compounds. Bull. Insectol. 57, 137–144 (2004).
    Google Scholar 
    Raguso, R. A. & Light, D. M. Electroantennogram responses of male Sphinx perelegans hawkmoths to floral and ‘green-leaf volatiles’. Entomol. Exp. Appl. 86, 287–293 (1998).CAS 
    Article 

    Google Scholar 
    Pinheiro, J. C. & Bates, D. M. Mixed-Effects Models in S and S-PLUS (Springer, 2000). https://doi.org/10.1007/b98882.Book 
    MATH 

    Google Scholar 
    Rondoni, G., Onofri, A. & Ricci, C. Differential susceptibility in a specialised aphidophagous ladybird, Platynaspis luteorubra (Coleoptera: Coccinellidae), facing intraguild predation by exotic and native generalist predators. Biocontrol Sci. Technol. 22, 1334–1350 (2012).Article 

    Google Scholar 
    Zuur, A. F., Ieno, E. N., Walker, N. J., Saveliev, A. A. & Smith, G. M. Mixed Effects Models and Extensions in Ecology with R (Springer Verlag, 2009). https://doi.org/10.18637/jss.v032.b01.Book 
    MATH 

    Google Scholar 
    Bertoldi, V., Rondoni, G., Brodeur, J. & Conti, E. An egg parasitoid efficiently exploits cues from a coevolved host but not those from a novel host. Front. Physiol. 10, 746 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Suh, E., Choe, D.-H., Saveer, A. M. & Zwiebel, L. J. Suboptimal larval habitats modulate oviposition of the malaria vector mosquito Anopheles coluzzii. PLoS ONE 11, e0149800 (2016).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org (2020).Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D., R Core Team. nlme: Linear and Nonlinear Mixed Effects Models (2020). R package version 3.1–148, https://CRAN.R-project.org/package=nlme.Venables, W. N. & Ripley, B. D. Modern Applied Statistics with S 4th edn. (Springer, 2002). https://doi.org/10.1007/978-0-387-21706-2.Book 
    MATH 

    Google Scholar 
    Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, 2016).MATH 
    Book 

    Google Scholar 
    Lenth, R. emmeans: Estimated Marginal Means, aka Least-Squares Means (2019). R package version 1.3.2. Available online at: https://CRAN.R-project.org/package=emmeans. More

  • in

    Neuro-molecular characterization of fish cleaning interactions

    Oliveira, R. F. Social plasticity in fish: Integrating mechanisms and function. J. Fish Biol. 81, 2127–2150 (2012).CAS 
    PubMed 

    Google Scholar 
    Oliveira, R. F. Mind the fish: Zebrafish as a model in cognitive social neuroscience. Front. Neural Circuits 7, 1–15 (2013).
    Google Scholar 
    Hofmann, H. A. et al. An evolutionary framework for studying mechanisms of social behavior. Trends Ecol. Evol. 29, 581–589 (2014).PubMed 

    Google Scholar 
    Maruska, K., Soares, M., Lima-Maximino, M., de Siqueira-Silva, D. H. & Maximino, C. Social plasticity in the fish brain: Neuroscientific and ethological aspects. Brain Res. 1711, 156–172 (2019).CAS 
    PubMed 

    Google Scholar 
    O’Connell, L. A. & Hofmann, H. A. The Vertebrate mesolimbic reward system and social behavior network: A comparative synthesis. J. Comp. Neurol. 519, 3599–3639 (2011).PubMed 

    Google Scholar 
    Teles, M. C., Almeida, O., Lopes, J. S. & Oliveira, R. F. Social interactions elicit rapid shifts in functional connectivity in the social decision-making network of zebrafish. Proc. R. Soc. B Biol. Sci. 282, 20151099 (2015).
    Google Scholar 
    Rittschof, C. C. et al. Neuromolecular responses to social challenge: Common mechanisms across mouse, stickleback fish, and honey bee. Proc. Natl. Acad. Sci. U.S.A. 111, 17929–17934 (2014).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kasper, C., Colombo, M., Aubin-horth, N. & Taborsky, B. Physiology & behavior brain activation patterns following a cooperation opportunity in a highly social cichlid fish. Physiol. Behav. 195, 37–47 (2018).CAS 
    PubMed 

    Google Scholar 
    Filby, A. L., Paull, G. C., Bartlett, E. J., Van Look, K. J. W. & Tyler, C. R. Physiological and health consequences of social status in zebrafish (Danio rerio). Physiol. Behav. 101, 576–587 (2010).CAS 
    PubMed 

    Google Scholar 
    Munchrath, L. A. & Hofmann, H. A. Distribution of sex steroid hormone receptors in the brain of an African cichlid fish, Astatotilapia burtoni. J. Comp. Neurol. 518, 3302–3326 (2010).CAS 
    PubMed 

    Google Scholar 
    Robinson, G. E., Fernald, R. D. & Clayton, D. F. Genes and social behavior. Science 322, 896–900 (2008).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Barron, A. B. & Robinson, G. E. The utility of behavioral models and modules in molecular analyses of social behavior. Genes Brain Behav. 7, 257–265 (2008).PubMed 

    Google Scholar 
    Qiu, Y.-Q. KEGG pathway database. In Encyclopedia of Systems Biology (ed. Dubitzky, W.) 1068–1069 (Springer, 2013).
    Google Scholar 
    Bloch, G. & Grozinger, C. M. Social molecular pathways and the evolution of bee societies. Philos. Trans. R. Soc. B Biol. Sci. 366, 2155–2170 (2011).
    Google Scholar 
    Waldie, P. A., Blomberg, S. P., Cheney, K. L., Goldizen, A. W. & Grutter, A. S. Long-term effects of the cleaner fish Labroides dimidiatus on coral reef fish communities. PLoS ONE 6, e21201 (2011).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Grutter, A. S. Cleaner fish really do clean. Nature. 398, 672–673. https://doi.org/10.1038/19443 (1999).CAS 
    Article 

    Google Scholar 
    Soares, M., Oliveira, R. F., Ros, A. F. H., Grutter, A. S. & Bshary, R. Tactile stimulation lowers stress in fish. Nat. Commun. 2, 534–535 (2011).PubMed 

    Google Scholar 
    Soares, M., Gerlai, R. & Maximino, C. The integration of sociality, monoamines and stress neuroendocrinology in fish models: Applications in the neurosciences. J. Fish Biol. 93, 170–191 (2018).PubMed 

    Google Scholar 
    Grutter, A. Parasite removal rates by the cleaner wrasse Labroides dimidiatus. Mar. Ecol. Prog. Ser. 130, 61–70 (1996).
    Google Scholar 
    Grutter, A. S. Effect of the removal of cleaner fish on the abundance and species composition of reef fish. Oecologia 111, 137–143 (1997).PubMed 

    Google Scholar 
    Tebbich, S., Bshary, R. & Grutter, A. Cleaner fish Labroides dimidiatus recognise familiar clients. Anim. Cogn. 5, 139–145 (2002).CAS 
    PubMed 

    Google Scholar 
    Pinto, A., Oates, J., Grutter, A. & Bshary, R. Cleaner wrasses Labroides dimidiatus are more cooperative in the presence of an audience. Curr. Biol. 21, 1140–1144 (2011).CAS 
    PubMed 

    Google Scholar 
    Soares, M. The neurobiology of mutualistic behavior: The cleanerfish swims into the spotlight. Front. Behav. Neurosci. 11, 1–12 (2017).
    Google Scholar 
    Soares, M. C., Bshary, R., Mendonça, R., Grutter, A. S. & Oliveira, R. F. Arginine vasotocin regulation of interspecific cooperative behaviour in a cleaner fish. PLoS ONE 7, 39583 (2012).
    Google Scholar 
    Paula, J. R., Messias, J., Grutter, A., Bshary, R. & Soares, M. The role of serotonin in the modulation of cooperative behavior. Behav. Ecol. 26, 1005–1012 (2015).
    Google Scholar 
    Schunter, C., Jarrold, M. D., Munday, P. L. & Ravasi, T. Diel CO2 fluctuations alter the molecular response of coral reef fishes to ocean acidification conditions. Mol. Ecol. 30, 5150–5118 (2021).
    Google Scholar 
    Soares, M. C., Santos, T. P. & Messias, J. P. M. Dopamine disruption increases cleanerfish cooperative investment in novel client partners. R. Soc. Open Sci. 4, 1–7 (2017).
    Google Scholar 
    Paula, J. R. et al. Neurobiological and behavioural responses of cleaning mutualisms to ocean warming and acidification. Sci. Rep. 9, 1–10 (2019).
    Google Scholar 
    Cardoso, S. C. et al. Arginine vasotocin modulates associative learning in a mutualistic cleaner fish. Behav. Ecol. Sociobiol. 69, 1173–1181 (2015).
    Google Scholar 
    Cardoso, S. C. et al. Forebrain neuropeptide regulation of pair association and behavior in cooperating cleaner fish. Physiol. Behav. 145, 1–7 (2015).CAS 
    PubMed 

    Google Scholar 
    O’Connell, L. A., Fontenot, M. R. & Hofmann, H. A. Characterization of the dopaminergic system in the brain of an African cichlid fish, Astatotilapia burtoni. J. Comp. Neurol. 519, 75–92 (2011).PubMed 

    Google Scholar 
    Vernier, P. The Brains of Teleost Fishes. Evolution of Nervous Systems 2nd edn, 1–4 (Elsevier, 2016).
    Google Scholar 
    Weitekamp, C. A. & Hofmann, H. A. Neuromolecular correlates of cooperation and conflict during territory defense in a cichlid fish. Horm. Behav. 89, 145–156 (2017).CAS 
    PubMed 

    Google Scholar 
    Messias, J., Santos, T. P., Pinto, M. & Soares, M. C. Stimulation of dopamine D1 receptor improves learning capacity in cooperating cleaner fish. Proc. R. Soc. B Biol. Sci. 283, 20152272 (2016).
    Google Scholar 
    Bshary, R. & Grutter, A. S. Punishment and partner switching cause cooperative behaviour in a cleaning mutualism. Biol. Lett. 1, 396–399 (2005).PubMed 
    PubMed Central 

    Google Scholar 
    Bajaffer, A., Mineta, K. & Gojobori, T. Evolution of memory system-related genes. FEBS Open Bio 11, 3201–3210 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    Soares, M., Cardoso, S. C., Grutter, A. S., Oliveira, R. F. & Bshary, R. Cortisol mediates cleaner wrasse switch from cooperation to cheating and tactical deception. Horm. Behav. 66, 346–350 (2014).CAS 
    PubMed 

    Google Scholar 
    de Abreu, M. S., Messias, J., Thörnqvist, P. O., Winberg, S. & Soares, M. C. The variable monoaminergic outcomes of cleaner fish brains when facing different social and mutualistic contexts. PeerJ 2018, 1–17 (2018).
    Google Scholar 
    Terry, W. S. Classical conditioning. In Learning and Memory (ed. Terry, W. S.) 76–112 (Psychology Press, 2021).
    Google Scholar 
    Dunn, A. R. et al. Synaptic vesicle glycoprotein 2C (SV2C) modulates dopamine release and is disrupted in Parkinson disease. Proc. Natl. Acad. Sci. U.S.A. 114, E2253–E2262 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Studzinski, A. L. M., Barros, D. M. & Marins, L. F. Growth hormone (GH) increases cognition and expression of ionotropic glutamate receptors (AMPA and NMDA) in transgenic zebrafish (Danio rerio). Behav. Brain Res. 294, 36–42 (2015).CAS 
    PubMed 

    Google Scholar 
    von Trotha, J. W., Vernier, P. & Bally-Cuif, L. Emotions and motivated behavior converge on an amygdala-like structure in the zebrafish. Eur. J. Neurosci. 40, 3302–3315 (2014).
    Google Scholar 
    Hoppmann, V., Wu, J. J., Søviknes, A. M., Helvik, J. V. & Becker, T. S. Expression of the eight AMPA receptor subunit genes in the developing central nervous system and sensory organs of zebrafish. Dev. Dyn. 237, 788–799 (2008).CAS 
    PubMed 

    Google Scholar 
    Weld, M. M., Kar, S., Maler, L. & Quirion, R. The distribution of excitatory amino acid binding sites in the brain of an electric fish, Apteronotus leptorhynchus. J. Chem. Neuroanat. 4, 39–61 (1991).
    Google Scholar 
    Zoicas, I. & Kornhuber, J. The role of metabotropic glutamate receptors in social behavior in Rodents. Int. J. Mol. Sci. 20, 1412 (2019).CAS 
    PubMed Central 

    Google Scholar 
    Borroni, A. M., Fichtenholtz, H., Woodside, B. L. & Teyler, T. J. Role of voltage-dependent calcium channel long-term potentiation (LTP) and NMDA LTP in spatial memory. J. Neurosci. 20, 9272–9276 (2000).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Oliveira, R. F. Social plasticity in fish: Integrating mechanisms. J. Fish Biol. 81, 2127–2150 (2012).CAS 
    PubMed 

    Google Scholar 
    O’Connell, L. A., Ding, J. H. & Hofmann, H. A. Sex differences and similarities in the neuroendocrine regulation of social behavior in an African cichlid fish. Horm. Behav. 64, 468–476 (2013).PubMed 

    Google Scholar 
    Soares, M., Bshary, R., Cardoso, S. C. & Côté, I. M. The meaning of jolts by fish clients of cleaning gobies. Ethology 114, 209–214 (2008).
    Google Scholar 
    Grutter, A. S. & Bshary, R. Cleaner wrasse prefer client mucus: Support for partner control mechanisms in cleaning interactions. Proc. R. Soc. B Biol. Sci. 270, S242–S244. https://doi.org/10.1098/rsbl.2003.0077 (2003).Article 

    Google Scholar 
    Soares, M. et al. Hormonal mechanisms of cooperative behaviour. Philos. Trans. R. Soc. B Biol. Sci. 365, 2737–2750 (2010).
    Google Scholar 
    Alberini, C. M. Transcription factors in long-term memory and synaptic plasticity. Physiol. Rev. 89, 121–145 (2009).CAS 
    PubMed 

    Google Scholar 
    Dou, Y. et al. Memory function in feeding habit transformation of mandarin fish (Siniperca chuatsi). Int. J. Mol. Sci. 19, 1254 (2018).PubMed Central 

    Google Scholar 
    Blanton, M. L. & Specker, J. L. The hypothalamic-pituitary-thyroid (HPT) axis in fish and its role in fish development and reproduction. Crit. Rev. Toxicol. 37, 97–115 (2007).CAS 
    PubMed 

    Google Scholar 
    Kawauchi, H., Sower, S. A. & Moriyama, S. Chapter 5. The neuroendocrine regulation of prolactin and somatolactin secretion in fish. In Fish Physiology Vol. 28 (eds Kawauchi, H. et al.) 197–234 (Elsevier Inc., 2009).
    Google Scholar 
    Helmreich, D. L., Parfitt, D. B., Lu, X. Y., Akil, H. & Watson, S. J. Relation between the hypothalamic-pituitary-thyroid (HPT) axis and the hypothalamic-pituitary-adrenal (HPA) axis during repeated stress. Neuroendocrinology 81, 183–192 (2005).CAS 
    PubMed 

    Google Scholar 
    Jönsson, E. & Björnsson, B. Physiological functions of growth hormone in fish with special reference to its influence on behaviour. Fish. Sci. 68, 742–748 (2002).
    Google Scholar 
    Zoeller, R. T., Tan, S. W. & Tyl, R. W. General background on the hypothalamic-pituitary-thyroid (HPT) axis. Crit. Rev. Toxicol. 37, 11–53 (2007).CAS 
    PubMed 

    Google Scholar 
    Björnsson, B. et al. Growth hormone endocrinology of salmonids: Regulatory mechanisms and mode of action. Fish Physiol. Biochem. 27, 227–242 (2002).
    Google Scholar 
    Trainor, B. C. & Hofmann, H. A. Somatostatin regulates aggressive behavior in an African cichlid fish. Endocrinology 147, 5119–5125 (2006).CAS 
    PubMed 

    Google Scholar 
    Doyon, C., Gilmour, K. M., Trudeau, V. L. & Moon, T. W. Corticotropin-releasing factor and neuropeptide Y mRNA levels are elevated in the preoptic area of socially subordinate rainbow trout. Gen. Comp. Endocrinol. 133, 260–271 (2003).CAS 
    PubMed 

    Google Scholar 
    du Sert, N. P. et al. Reporting animal research: Explanation and elaboration for the ARRIVE guidelines 2.0. PLoS Biol. 18, e3000411 (2020).
    Google Scholar 
    Triki, Z. & Bshary, R. Sex differences in the cognitive abilities of a sex-changing fish species Labroides dimidiatus. R. Soc. Open Sci. 8, 210239 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    Grutter, A. S. Cleaner fish use tactile dancing behavior as a preconflict management strategy. Curr. Biol. 14, 1080–1083 (2004).CAS 
    PubMed 

    Google Scholar 
    Friard, O. & Gamba, M. BORIS: A free, versatile open-source event-logging software for video/audio coding and live observations. Methods Ecol. Evol. 7, 1325–1330 (2016).
    Google Scholar 
    Andrews, S. Babraham Bioinformatics—FastQC: A Quality Control Tool for High Throughput Sequence Data. https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (2010).Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Haas, B. J. et al. De novo transcript sequence reconstruction from RNA-seq using the trinity platform for reference generation and analysis. Nat. Protoc. 8, 1494–1512 (2013).CAS 
    PubMed 

    Google Scholar 
    Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Waterhouse, R. M. et al. BUSCO applications from quality assessments to gene prediction and phylogenomics. Mol. Biol. Evol. 35, 543–548 (2018).CAS 
    PubMed 

    Google Scholar 
    Götz, S. et al. High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic Acids Res. 36, 3420–3435 (2008).PubMed 
    PubMed Central 

    Google Scholar 
    Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing https://www.R-project.org/ (R Foundation for Statistical Computing, 2021). More

  • in

    Genetic identification and diversity of stocks of the African bonytongue, Heterotis niloticus (Osteoglossiformes: Arapaiminae), in Nigeria, West Africa

    Béné, C. & Heck, S. Fish and food security in Africa. NAGA WorldFish Center Q. 28, 8–13 (2005).
    Google Scholar 
    Funge-Smith, S. J. Review of the state of world fishery resources: inland fisheries. FAO Fisheries and Aquaculture Circular (2018).Funge-Smith, S. & Bennett, A. A fresh look at inland fisheries and their role in food security and livelihoods. Fish Fish. (Oxf.) 20, 1176–1195 (2019).Article 

    Google Scholar 
    De Graaf, G. & Garibaldi, L. The value of African fisheries. FAO fisheries and aquaculture circular, I (2015).FAO. FAO yearbook. Fishery and Aquaculture Statistics 2018/FAO annuaire. Statistiques des pêches et de l’aquaculture 2018/FAO anuario. Estadísticas de pesca y acuicultura 2018 (2020).Olaosebikan, B. D. & Bankole, N. O. An analysis of Nigerian freshwater fishes: those under threat and conservation options, In Proceedings of the 19th annual conference of the fisheries society of Nigeria (FISON), 29 Nov – 03 Dec 2004. 754–762.Marshall, B. E. Inland fisheries of tropical Africa. In Freshwater Fisheries Ecology (ed. Graig, J. F.) 349 (Wiley, Chichester, 2016).
    Google Scholar 
    Dudgeon, D. et al. Freshwater biodiversity: importance, threats, status and conservation challenges. Biol. Rev. (Camb.) 81, 163–182 (2006).Article 

    Google Scholar 
    United Nations-Department of Economic and Social Affairs-Population Division. World population prospects 2019: Highlights (st/esa/ser. A/423). (2019).FAO, IFAD, UNICEF, WFP & WHO. The state of food security and nutrition in the world 2019: safeguarding against economic slowdowns and downturns 2019. (Rome, Italy: FAO, http://www.fao.org/3/ca5162en/ca5162en.pdf 2019).Carvalho, G. R. & Hauser, L. Molecular genetics and the stock concept in fisheries. In Molecular Genetics in Fisheries (eds Carvalho, G. R. & Pitcher, T. J.) 55–79 (Springer, Berlin, 1995).Chapter 

    Google Scholar 
    Abban, E. K. Considerations for the conservation of African fish genetic resources for their sustainable exploitation. In Towards Policies for Conservation and Sustainable Use of Aquatic Genetic Resources. ICLARM Conf. Proc. 59, 277p. (eds R.S.V. Pullin, D.M. Bartley, & J. Kooiman) 95–100 (International Center for Living Aquatic Resources Management (ICLARM) and FAO).FAO. Fishery Statistical Collections: Global Capture Production 1950–2018. http://www.fao.org/fishery/statistics/global-capture-production/query/en (2020).Chan, C. Y. et al. Prospects and challenges of fish for food security in Africa. Glob. Food Sec. 20, 17–25 (2019).Article 

    Google Scholar 
    Olopade, O. A., Taiwo, I. O. & Dienye, H. E. Management of Overfishing in the Inland Capture Fisheries in Nigeria. LimnoFish 3, 189–194 (2017).Article 

    Google Scholar 
    Gbaguidi, A. S. & Pfeiffer, V. Stastistiques des peches continentals, Annees 1987–1995. Cotonou, Benin: GTZ-GmbH, Benin Direction des Pêches (1996).Monentcham, S.-E., Kouam, J., Pouomogne, V. & Kestemont, P. Biology and prospect for aquaculture of African bonytongue, Heterotis niloticus (Cuvier, 1829): A review. Aquaculture 289, 191–198 (2009).Article 

    Google Scholar 
    FAO. The State of the World’s Aquatic Genetic Resources for Food and Agriculture. (Rome, 2019).Mustapha, M. K. Heterotis niloticus (Cuvier, 1829) a threatened fish species in Oyun reservoir, Offa, Nigeria; the need for its conservation. Asian J. Exp. Biol. Sci. 1, 1–7 (2010).
    Google Scholar 
    Hurtado, L. A., Carrera, E., Adite, A. & Winemiller, K. O. Genetic differentiation of a primitive teleost, the African bonytongue Heterotis niloticus, among river basins and within a floodplain river system in Benin, West Africa. J. Fish Biol. 83, 682–690 (2013).CAS 
    Article 

    Google Scholar 
    Hauber, M. E., Bierbach, D. & Linsenmair, K. E. A description of teleost fish diversity in floodplain pools (‘Whedos’) and the Middle-Niger at Malanville (north-eastern Benin). J. Appl. Ichthyol. 27, 1095–1099 (2011).Article 

    Google Scholar 
    Carrera, E., Renshaw, M. A., Winemiller, K. O. & Hurtado, L. A. Isolation and characterization of nuclear-encoded microsatellite DNA primers for the African bonytongue, Heterotis niloticus. Conserv. Genet. Resour. 3, 537–539 (2011).Article 

    Google Scholar 
    Lischer, H. E. L. & Excoffier, L. PGDSpider: an automated data conversion tool for connecting population genetics and genomics programs. Bioinformatics 28, 298–299 (2012).CAS 
    Article 

    Google Scholar 
    Raymond, M. & Rousset, F. GENEPOP (version-1.2)—Population genetics software for exact tests and ecumenicism. J. Hered. 86, 248–249 (1995).Article 

    Google Scholar 
    Rousset, F. Genepop’007: A complete re-implementation of the genepop software for Windows and Linux. Mol. Ecol. Resour. 8, 103–106 (2008).Article 

    Google Scholar 
    Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate—A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B. Stat. Methodol. 57, 289–300 (1995).MathSciNet 
    MATH 

    Google Scholar 
    Peakall, R. & Smouse, P. E. GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol. Ecol. Notes 6, 288–295. https://doi.org/10.1111/j.1471-8286.2005.01155.x (2006).Article 

    Google Scholar 
    Peakall, R. & Smouse, P. E. GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics 28, 2537–2539 (2012).CAS 
    Article 

    Google Scholar 
    Van Oosterhout, C., Hutchinson, W. F., Wills, D. P. M. & Shipley, P. MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Mol. Ecol. Notes 4, 535–538 (2004).Article 

    Google Scholar 
    Chapuis, M. P. & Estoup, A. Microsatellite null alleles and estimation of population differentiation. Mol. Biol. Evol. 24, 621–631 (2007).CAS 
    Article 

    Google Scholar 
    Excoffier, L. & Lischer, H. E. L. Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol. Ecol. Resour. 10, 564–567. https://doi.org/10.1111/j.1755-0998.2010.02847.x (2010).Article 
    PubMed 

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

    Google Scholar 
    Jombart, T. & Ahmed, I. adegenet 1.3–1: New tools for the analysis of genome-wide SNP data. Bioinformatics 27, 3070–3071 (2011).CAS 
    Article 

    Google Scholar 
    Jombart, T., Devillard, S. & Balloux, F. Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genet. 11, 94 (2010).Article 

    Google Scholar 
    Miller, J. M., Cullingham, C. I. & Peery, R. M. The influence of a priori grouping on inference of genetic clusters: simulation study and literature review of the DAPC method. Heredity https://doi.org/10.1038/s41437-020-0348-2 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pritchard, J. K., Stephens, M. & Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 155, 945–959 (2000).CAS 
    Article 

    Google Scholar 
    Mantel, N. The detection of disease clustering and a Generalized Regression Approach. Cancer Res. 27, 209–220 (1967).CAS 
    PubMed 

    Google Scholar 
    Allendorf, F. W., Ryman, N. & Utter, F. M. Genetics and fishery management: Past, present, and future. In Population Genetics and Fishery Management (eds Ryman, N. & Utter, F.) 1–19 (Washington Sea Grant Publications/University of Washington Press, 1987).
    Google Scholar 
    Otobo, F. O. The commercial fishery of the middle River Niger, Nigeria. In Symposium on River and Floodplain Fisheries in Africa, Bujumbura, Burundi, 21–23 November 1977, Review and Experience Papers Vol. CIFA TECHNICAL PAPER No. 5 (ed R. L. Welcomme) (Committe for Inland Fisheries of Africa, FAO, 1978).Lelek, A. & El-Zarka, A. Ecological comparison of the preimpoundment and postimpoundment fish faunas of the River Niger and Kainji Lake, Nigeria. Geophys. Monogr. Ser. 17, 655–660 (1973).ADS 

    Google Scholar 
    Morin, P. A., Manaster, C., Mesnick, S. L. & Holland, R. Normalization and binning of historical and multi-source microsatellite data: Overcoming the problems of allele size shift with allelogram. Mol. Ecol. Resour. 9, 1451–1455 (2009).Article 

    Google Scholar 
    Pruett, C. L. & Winker, K. The effects of sample size on population genetic diversity estimates in song sparrows Melospiza melodia. J. Avian Biol. 39, 252–256. https://doi.org/10.1111/j.2008.0908-8857.0409 (2008).Article 

    Google Scholar 
    Hale, M. L., Burg, T. M. & Steeves, T. E. Sampling for microsatellite-based population genetic studies: 25 to 30 individuals per population is enough to accurately estimate allele frequencies. PLoS ONE 7, e45170 (2012).ADS 
    CAS 
    Article 

    Google Scholar 
    Macedo, D. et al. Population genetics and historical demographic inferences of the blue crab Callinectes sapidus in the US based on microsatellites. PeerJ 7, e7780 (2019).Article 

    Google Scholar 
    Latch, E. K., Dharmarajan, G., Glaubitz, J. C. & Rhodes, O. E. Relative performance of Bayesian clustering software for inferring population substructure and individual assignment at low levels of population differentiation. Conserv. Genet. 7, 295–302 (2006).Article 

    Google Scholar 
    Lind, C. E. et al. Genetic diversity of Nile tilapia (Oreochromis niloticus) throughout West Africa. Sci. Rep. 9, 1–12 (2019).ADS 

    Google Scholar 
    Araripe, J., do Rêgo, P. S., Queiroz, H., Sampaio, I. & Schneider, H. Dispersal capacity and genetic structure of Arapaima gigas on different geographic scales using microsatellite markers. PLoS ONE 8, e54470 (2013).ADS 
    CAS 
    Article 

    Google Scholar 
    Hilton, E. J. & Lavoué, S. A review of the systematic biology of fossil and living bony-tongue fishes, Osteoglossomorpha (Actinopterygii: Teleostei). Neotrop. Ichthyol. 16 (2018).DeWoody, J. A. & Avise, J. C. Microsatellite variation in marine, freshwater and anadromous fishes compared with other animals. J. Fish Biol. 56, 461–473 (2000).CAS 
    Article 

    Google Scholar 
    Abiodun, J. A. Fisheries Statistical Bulletin Kainji Lake, Nigeria, 2001. 25p (2002).Yem, I. Y., Sani, A. O., Bankole, N. O., Onimisi, H. U. & Musa, Y. M. Over fishing as a factor responsible for declined in fish species diversity of Kainji, Nigeria. In 21st Annual Conference of the Fisheries Society of Nigeria (FISON). 79–85.Mshelia, M. B. et al. Responsible fisheries enhancing poverty alleviation of fishing communities of Lake Kainji. In 19th Annual Conference of the Fisheries Society of Nigeria (FISON) 597–604.Adelakun, K. M. & Kehinde, A. S. Heavy metals bioaccumulations in Chrysichthys nigrodigitatus (Silver catfish) from River Oli, Kainji Lake National Park, Nigeria. Egypt. J. Aquat. Biol. Fish. 23, 253–259 (2019).Article 

    Google Scholar 
    Ikomi, R. B. & Arimoro, F. O. Effects of recreational activities on the littoral macroinvertebrates of Ethiope River, Niger Delta, Nigeria. J. Aquat. Sci. 29, 155–170 (2014).
    Google Scholar 
    Ushurhe, O., Origho, T. & Ewhuwhe-Ezo, J. Determinant of water quality and suitability of River Ethiope for fish survival in Southern Nigeria. Can. J. Agr. Crop. 1, 11–18 (2016).
    Google Scholar 
    Arojojoye, O. A., Oyagbemi, A. A. & Afolabi, J. M. Toxicological assessment of heavy metal bioaccumulation and oxidative stress biomarkers in Clarias gariepinus from Igbokoda River of South Western Nigeria. Bull. Environ. Contam. Toxicol. 100, 765–771 (2018).CAS 
    Article 

    Google Scholar 
    Arojojoye, O. A. et al. Assessment of water quality of selected rivers in the Niger Delta region of Nigeria using biomarkers in Clarias gariepinus. Environ. Sci. Pollut. Res. 28, 22936–22943 (2021).CAS 
    Article 

    Google Scholar 
    Soyinka, O. O. & Ebigbo, C. H. Species diversity and growth pattern of the fish fauna of Epe Lagoon, Nigeria. J. Fish. Aquat. Sci. 7, 392–401 (2012).
    Google Scholar 
    Akinsanya, B., Ayanda, I. O., Fadipe, A. O., Onwuka, B. & Saliu, J. K. Heavy metals, parasitologic and oxidative stress biomarker investigations in Heterotis niloticus from Lekki Lagoon, Lagos, Nigeria. Toxicol. Rep. 7, 1075–1082 (2020).CAS 
    Article 

    Google Scholar 
    Akinsanya, B., Ayanda, I. O., Onwuka, B. & Saliu, J. K. Bioaccumulation of BTEX and PAHs in Heterotis niloticus (Actinopterygii) from the Epe Lagoon, Lagos, Nigeria. Heliyon 6, e03272. https://doi.org/10.1016/j.heliyon.2020.e03272 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar  More

  • in

    Metagenomic, (bio)chemical, and microscopic analyses reveal the potential for the cycling of sulfated EPS in Shark Bay pustular mats

    Hoffman P. Stromatolite morphogenesis in Shark Bay, Western Australia. In: Developments in sedimentology. Elsevier; 1976.261–71.Golubic S, Hofmann HJ. Comparison of Holocene and Mid-Precambrian Entophysalidaceae (Cyanophyta) in stromatolitic algal mats: Cell division and degradation. J Paleontol. 1976;50:1074–82.
    Google Scholar 
    Mlewski EC, Pisapia C, Gomez F, Lecourt L, Rueda ES, Benzerara K, et al. Characterization of pustular mats and related Rivularia-rich laminations in oncoids from the Laguna Negra lake (Argentina). Front Microbiol. 2018;9:1–23.Article 

    Google Scholar 
    St Kendall C, Skipwith A. Recent algal mats of a Persian Gulf lagoon. SEPM J Sediment Res. 1968;38:1040–58.
    Google Scholar 
    Golubic S, Abed R. Entophysalis mats as environmental regulators. In: Microbial mats, modern and ancient microorganisms in stratified systems. Dordrecht: Springer; 2010.237–51.Logan BW, Hoffman P, Gebelien CD. Algal mats, cryptalgal fabrics, and structures, Hamelin Pool, Western Australia. Am Assoc Pet Geol. 1974;22:140–94.
    Google Scholar 
    Jahnert RJ, Collins LB. Controls on microbial activity and tidal flat evolution in Shark Bay, Western Australia. Sedimentology. 2013;60:1071–99.Article 

    Google Scholar 
    Moore KR, Pajusalu M, Gong J, Sojo V, Matreux T, Braun D, et al. Biologically mediated silicification of marine cyanobacteria and implications for the Proterozoic fossil record. Geology. 2020;48:862–6.CAS 
    Article 

    Google Scholar 
    Decho AW, Visscher PT, Reid RP. Production and cycling of natural microbial exopolymers (EPS) within a marine stromatolite. Geobiology: objectives, concepts, perspectives. 2005;71–86.Visscher PT, Dupont CL, Braissant O, Gallagher KL, Glunk C, Casillas L, et al. Biogeochemistry of carbon cycling in hypersaline mats: Linking the present to the past through biosignatures. In: Microbial mats, modern and ancient microorganisms in stratified systems. Dordrecht: Springer; 2010.443–68.Ruvindy R, White RA, Neilan BA, Burns BP. Unravelling core microbial metabolisms in the hypersaline microbial mats of Shark Bay using high-throughput metagenomics. ISME J. 2016;10:183–96.CAS 
    PubMed 
    Article 

    Google Scholar 
    Stuart RK, Mayali X, Lee JZ, Craig Everroad R, Hwang M, Bebout BM, et al. Cyanobacterial reuse of extracellular organic carbon in microbial mats. ISME J. 2016;10:1240–51.CAS 
    PubMed 
    Article 

    Google Scholar 
    Wong HL, White RA, Visscher PT, Charlesworth JC, Vázquez-Campos X, Burns BP. Disentangling the drivers of functional complexity at the metagenomic level in Shark Bay microbial mat microbiomes. ISME J. 2018;12:2619–39.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Campbell MA, Coolen MJL, Visscher PT, Morris T, Grice K. Structure and function of Shark Bay microbial communities following tropical cyclone Olwyn: a metatranscriptomic and organic geochemical perspective. Geobiology. 2021;19:642–64.CAS 
    PubMed 
    Article 

    Google Scholar 
    Braissant O, Decho AW, Przekop KM, Gallagher KL, Glunk C, Dupraz C, et al. Characteristics and turnover of exopolymeric substances in a hypersaline microbial mat. FEMS Microbiol Ecol. 2009;67:293–307.CAS 
    PubMed 
    Article 

    Google Scholar 
    Cutts EM, Baldes MJ, Skoog EJ, Hall J, Gong J, Moore KR, et al. Using molecular tools to understand microbial carbonates. Geosciences 2022;12:185.Moore KR, Gong J, Pajusalu M, Skoog EJ, Xu M, Soto Feliz T, et al. A new model for silicification of cyanobacteria in Proterozoic tidal flats. Geobiology. 2021;19:438–49.CAS 
    PubMed 
    Article 

    Google Scholar 
    Pereira S, Zille A, Micheletti E, Moradas-Ferreira P, De Philippis R, Tamagnini P. Complexity of cyanobacterial exopolysaccharides: composition, structures, inducing factors and putative genes involved in their biosynthesis and assembly. FEMS Microbiol Rev. 2009;33:917–41.CAS 
    PubMed 
    Article 

    Google Scholar 
    Wingender J, Neu TR, Flemming H-C. Microbial extracellular polymeric substances. In: Microbial extracellular polymeric substances. Berlin, Heidelberg: Springer; 1999.1–19.Sheng GP, Yu HQ, Li XY. Extracellular polymeric substances (EPS) of microbial aggregates in biological wastewater treatment systems: a review. Biotechnol Adv. 2010;28:882–94.CAS 
    PubMed 
    Article 

    Google Scholar 
    Bar-Or Y, Shilo M. Characterization of macromolecular flocculants produced by Phormidium sp. Strain J-1 and by Anabaenopsis circularis PCC 6720. Appl Environ Microbiol. 1987;53:2226–30.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Sudo H, Burgess JG, Takemasa H, Nakamura N, Matsunaga T. Sulfated exopolysaccharide production by the halophilic cyanobacterium Aphanocapsa halophytia. Curr Microbiol. 1995;30:219–22.CAS 
    Article 

    Google Scholar 
    Witvrouw M, De Clercq E. Sulfated polysaccharides extracted from sea algae as potential antiviral drugs. Gen Pharmacol: The Vasc Syst. 1997;29:497–511.CAS 
    Article 

    Google Scholar 
    De Philippis R, Vincenzini M. Exocellular polysaccharides from cyanobacteria and their possible applications. FEMS Microbiol Rev. 1998;22:151–75.Article 

    Google Scholar 
    Chen L, Li T, Guan L, Zhou Y, Li P. Flocculating activities of polysaccharides released from the marine mat-forming cyanobacteria Microcoleus and Lyngbya. Aquat Biol. 2011;11:243–8.CAS 
    Article 

    Google Scholar 
    Wang L, Wang X, Wu H, Liu R. Overview on biological activities and molecular characteristics of sulfated polysaccharides from marine green algae in recent years. Marine Drugs. 2014;12:4984–5020.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hans N, Malik A, Naik S. Antiviral activity of sulfated polysaccharides from marine algae and its application in combating COVID-19: Mini review. Bioresour Technol Rep. 2021;13:100623.2020.PubMed 
    Article 

    Google Scholar 
    Braissant O, Decho AW, Dupraz C, Glunk C, Przekop KM, Visscher PT. Exopolymeric substances of sulfate-reducing bacteria: Interactions with calcium at alkaline pH and implication for formation of carbonate minerals. Geobiology. 2007;5:401–11.CAS 
    Article 

    Google Scholar 
    Barbeyron T, Brillet-Guéguen L, Carré W, Carrière C, Caron C, Czjzek M, et al. Matching the diversity of sulfated biomolecules: Creation of a classification database for sulfatases reflecting their substrate specificity. PLoS ONE. 2016;11:1–33.Article 

    Google Scholar 
    Allen MA, Goh F, Burns BP, Neilan BA. Bacterial, archaeal and eukaryotic diversity of smooth and pustular microbial mat communities in the hypersaline lagoon of Shark Bay. Geobiology. 2009;7:82–96.CAS 
    PubMed 
    Article 

    Google Scholar 
    Goh F, Allen MA, Leuko S, Kawaguchi T, Decho AW, Burns BP, et al. Determining the specific microbial populations and their spatial distribution within the stromatolite ecosystem of Shark Bay. ISME J. 2009;3:383–96.CAS 
    PubMed 
    Article 

    Google Scholar 
    Brody SS. New excited state of chlorophyll. Science. 1958;128:838–9.CAS 
    PubMed 
    Article 

    Google Scholar 
    Lamb JJ, Røkke G, Hohmann-Marriott MF. Chlorophyll fluorescence emission spectroscopy of oxygenic organisms at 77 K. Photosynthetica. 2018;56:105–24.CAS 
    Article 

    Google Scholar 
    Hahn T, Schulz M, Stadtmüller R, Zayed A, Muffler K, Lang S, et al. Cationic dye for the specific determination of sulfated polysaccharides. Anal Lett. 2016;49:1948–62.CAS 
    Article 

    Google Scholar 
    Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Li D, Liu CM, Luo R, Sadakane K, Lam TW. MEGAHIT: An ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics. 2015;31:1674–6.CAS 
    PubMed 
    Article 

    Google Scholar 
    Li D, Luo R, Liu CM, Leung CM, Ting HF, Sadakane K, et al. MEGAHIT v1.0: a fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods. 2016;102:3–11.CAS 
    PubMed 
    Article 

    Google Scholar 
    Kang DD, Froula J, Egan R, Wang Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ. 2015;3(e1165).Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25:1043–55.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Chaumeil P-A, Mussig AJ, Hugenholtz P, Parks DH. GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics. 2020;36:1925–7.CAS 

    Google Scholar 
    Huntemann M, Ivanova NN, Mavromatis K, James Tripp H, Paez-Espino D, Palaniappan K, et al. The standard operating procedure of the DOE-JGI Microbial Genome Annotation Pipeline (MGAP v.4). Standards in Genomic. Sciences. 2015;10:4–9.
    Google Scholar 
    Markowitz VM, Ivanova NN, Szeto E, Palaniappan K, Chu K, Dalevi D, et al. IMG/M: a data management and analysis system for metagenomes. Nucleic Acids Res. 2007;36:534–8.SUPPL.1Article 

    Google Scholar 
    Eren AM, Esen ÖC, Quince C, Vineis JH, Morrison HG, Sogin ML, et al. Anvi’o: an advanced analysis and visualization platform for ‘omics data. PeerJ. 2015;3:e1319.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Campbell BJ, Yu L, Heidelberg JF, Kirchman DL. Activity of abundant and rare bacteria in a coastal ocean. Proc National Acad Sci USA 2011;108:12776–81.CAS 
    Article 

    Google Scholar 
    Fukuda M, Hiraoka N, Akama TO, Fukuda MN. Carbohydrate-modifying sulfotransferases: Structure, function, and pathophysiology. J Biol Chem. 2001;276:47747–50.CAS 
    PubMed 
    Article 

    Google Scholar 
    Roeser D, Preusser-Kunze A, Schmidt B, Gasow K, Wittmann JG, Dierks T, et al. A general binding mechanism for all human sulfatases by the formylglycine-generating enzyme. Proc Natl Acad Sci USA 2006;103:81–6.CAS 
    PubMed 
    Article 

    Google Scholar 
    Genicot SM, Groisillier A, Rogniaux H, Meslet-Cladière L, Barbeyron T, Helbert W. Discovery of a novel iota carrageenan sulfatase isolated from the marine bacterium Pseudoalteromonas carrageenovora. Front Chem. 2014;2:1–15.CAS 
    Article 

    Google Scholar 
    Almagro Armenteros JJ, Tsirigos KD, Sønderby CK, Petersen TN, Winther O, Brunak S, et al. SignalP 5.0 improves signal peptide predictions using deep neural networks. Nat Biotechnol. 2019;37:420–3.CAS 
    PubMed 
    Article 

    Google Scholar 
    Fernando IPS, Sanjeewa KKA, Samarakoon KW, Lee WW, Kim HS, Kim EA, et al. FTIR characterization and antioxidant activity of water soluble crude polysaccharides of Sri Lankan marine algae. Algae. 2017;32:75–86.CAS 
    Article 

    Google Scholar 
    Papineau D, Walker JJ, Mojzsis SJ, Pace NR. Composition and structure of microbial communities from stromatolites of Hamelin Pool in Shark Bay, Western Australia. Appl Environ Microbiol. 2005;71:4822–32.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Wong HL, Smith DL, Visscher PT, Burns BP. Niche differentiation of bacterial communities at a millimeter scale in Shark Bay microbial mats. Sci Rep. 2015;5:1–17. 15607
    Google Scholar 
    Pereira SB, Mota R, Vieira CP, Vieira J, Tamagnini P. Phylum-wide analysis of genes/proteins related to the last steps of assembly and export of extracellular polymeric substances (EPS) in cyanobacteria. Sci Rep. 2015;5:1–16.CAS 

    Google Scholar 
    Rossi F, De Philippis R. Role of cyanobacterial exopolysaccharides in phototrophic biofilms and in complex microbial mats. Life. 2015;5:1218–38.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    McCandless EL, Craigie JS. Sulfated polysaccharides in red and brown algae. Ann Rev Plant Physiol. 1979;30:41–53.CAS 
    Article 

    Google Scholar 
    Usov AI, Bilan MI. Fucoidans-sulfated polysaccharides of brown algae. Russ Chem Rev. 2009;78:785–99.CAS 
    Article 

    Google Scholar 
    Jiao G, Yu G, Zhang J, Ewart HS. Chemical structures and bioactivities of sulfated polysaccharides from marine algae. Mar Drugs. 2011;9:196–233.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Al Disi ZA, Zouari N, Dittrich M, Jaoua S, Al-Kuwari HAS, Bontognali TRR. Characterization of the extracellular polymeric substances (EPS) of Virgibacillus strains capable of mediating the formation of high Mg-calcite and protodolomite. Mar Chem. 2019;216:103693.CAS 
    Article 

    Google Scholar 
    Diloreto ZA, Garg S, Bontognali TRR, Dittrich M. Modern dolomite formation caused by seasonal cycling of oxygenic phototrophs and anoxygenic phototrophs in a hypersaline sabkha. Sci Rep. 2021;11:1–13.Article 

    Google Scholar 
    Richert L, Golubic S, Le Guédès R, Ratiskol J, Payri C, Guezennec J. Characterization of exopolysaccharides produced by cyanobacteria isolated from Polynesian microbial mats. Curr Microbiol. 2005;51:379–84.CAS 
    PubMed 
    Article 

    Google Scholar 
    Raguénès G, Moppert X, Richert L, Ratiskol J, Payri C, Costa B, et al. A novel exopolymer-producing bacterium, Paracoccus zeaxanthinifaciens subsp. payriae, isolated from a “kopara” mat located in Rangiroa, an atoll of French Polynesia. Curr Microbiol. 2004;49:145–51.PubMed 
    Article 

    Google Scholar 
    Moppert X, Le Costaouec T, Raguenes G, Courtois A, Simon-Colin C, Crassous P, et al. Investigations into the uptake of copper, iron and selenium by a highly sulphated bacterial exopolysaccharide isolated from microbial mats. J Ind Microbiol Biotechnol. 2009;36:599–604.CAS 
    PubMed 
    Article 

    Google Scholar 
    González-Hourcade M, del Campo EM, Braga MR, Salgado A, Casano LM. Disentangling the role of extracellular polysaccharides in desiccation tolerance in lichen-forming microalgae. First evidence of sulfated polysaccharides and ancient sulfotransferase genes. Environ Microbiol. 2020;22:3096–111.PubMed 
    Article 

    Google Scholar 
    De Souza MCR, Marques CT, Dore CMG, Da Silva FRF, Rocha HAO, Leite EL. Antioxidant activities of sulfated polysaccharides from brown and red seaweeds. J Appl Phycol. 2007;19:153–60.Article 

    Google Scholar 
    Jayawardena TU, Wang L, Asanka Sanjeewa KK, In Kang S, Lee JS, Jeon YJ. Antioxidant potential of sulfated polysaccharides from Padina boryana; protective effect against oxidative stress in in vitro and in vivo zebrafish model. Mar Drugs. 2020;18:1–14.
    Google Scholar 
    Baba M, Snoeck R, Pauwels R, De Clercq E. Sulfated polysaccharides are potent and selective inhibitors of various enveloped viruses, including herpes simplex virus, cytomegalovirus, vesicular stomatitis virus, and human immunodeficiency virus. Antimicrob Agents Chemother. 1988;32:1742–5.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Ghosh T, Chattopadhyay K, Marschall M, Karmakar P, Mandal P, Ray B. Focus on antivirally active sulfated polysaccharides: From structure-activity analysis to clinical evaluation. Glycobiology. 2009;19:2–15.CAS 
    PubMed 
    Article 

    Google Scholar 
    Bakunina IY, Nedashkovskaya OI, Alekseeva SA, Ivanova EP, Romanenko LA, Gorshkova NM, et al. Degradation of fucoidan by the marine proteobacterium Pseudoalteromonas citrea. Mikrobiologiya. 2002;71:49–55.
    Google Scholar 
    Descamps V, Colin S, Lahaye M, Jam M, Richard C, Potin P, et al. Isolation and culture of a marine bacterium degrading the sulfated fucans from marine brown algae. Mar Biotechnol. 2006;8:27–39.CAS 
    Article 

    Google Scholar 
    Mann AJ, Hahnke RL, Huang S, Werner J, Xing P, Barbeyron T, et al. The genome of the alga-associated marine flavobacterium Formosa agariphila KMM 3901T reveals a broad potential for degradation of algal polysaccharides. Appl Environ Microbiol. 2013;79:6813–22.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hehemann JH, Boraston AB, Czjzek M. A sweet new wave: Structures and mechanisms of enzymes that digest polysaccharides from marine algae. Curr Opin Struct Biol. 2014;28:77–86.CAS 
    PubMed 
    Article 

    Google Scholar 
    Thomas F, Bordron P, Eveillard D, Michel G. Gene expression analysis of Zobellia galactanivorans during the degradation of algal polysaccharides reveals both substrate-specific and shared transcriptome-wide responses. Front Microbiol. 2017;8:1–14.CAS 
    Article 

    Google Scholar 
    Martinez-Garcia M, Brazel DM, Swan BK, Arnosti C, Chain PSG, Reitenga KG, et al. Capturing single cell genomes of active polysaccharide degraders: an unexpected contribution of verrucomicrobia. PLoS ONE. 2012;7:1–11.
    Google Scholar 
    Sichert A, Corzett CH, Schechter MS, Unfried F, Markert S, Becher D, et al. Verrucomicrobia use hundreds of enzymes to digest the algal polysaccharide fucoidan. Nat Microbiol. 2020;5:1026–39.CAS 
    PubMed 
    Article 

    Google Scholar 
    Bengtsson MM, Øvreås L. Planctomycetes dominate biofilms on surfaces of the kelp Laminaria hyperborea. BMC Microbiol. 2010;10:1–12.Article 

    Google Scholar 
    Kim JW, Brawley SH, Prochnik S, Chovatia M, Grimwood J, Jenkins J, et al. Genome analysis of Planctomycetes inhabiting blades of the red alga Porphyra umbilicalis. PLoS ONE. 2016;11:1–22.
    Google Scholar 
    Glöckner FO, Kube M, Bauer M, Teeling H, Lombardot T, Ludwig W, et al. Complete genome sequence of the marine planctomycete Pirellula sp. strain 1. Proc Natl Acad Sci USA 2003;100:8298–303.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Bayer K, Jahn MT, Slaby BM, Moitinho-Silva L, Hentschel U. Marine sponges as Chloroflexi hot spots: Genomic insights and high-resolution visualization of an abundant and diverse symbiotic clade. mSystems. 2018;3:1–19.Article 

    Google Scholar 
    Robbins SJ, Song W, Engelberts JP, Glasl B, Slaby BM, Boyd J, et al. A genomic view of the microbiome of coral reef demosponges. ISME J. 2021;15:1641–54.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Salyers AA, O’Brien M. Cellular location of enzymes involved in chondroitin sulfate breakdown by Bacteroides thetaiotaomicron. J Bacteriol. 1980;143:772–80.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Campbell MA, Grice K, Visscher PT, Morris T, Wong HL, White RA, et al. Functional gene expression in Shark Bay hypersaline microbial mats: adaptive responses. Front Microbiol. 2020;11:1–16.Article 

    Google Scholar 
    Van Vliet DM, Ayudthaya SPN, Diop S, Villanueva L, Stams AJM, Sánchez-Andrea I. Anaerobic degradation of sulfated polysaccharides by two novel Kiritimatiellales strains isolated from black sea sediment. Front Microbiol. 2019;10:1–16.Article 

    Google Scholar 
    Bäumgen M, Dutschei T, Bornscheuer UT. Marine polysaccharides: occurrence, enzymatic degradation and utilization. ChemBioChem. 2021;22:2247–56.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Helbert W. Marine polysaccharide sulfatases. Front Mar Sci. 2017;4:1–10.Article 

    Google Scholar 
    Ficko-Blean E, Préchoux A, Thomas F, Rochat T, Larocque R, Zhu Y, et al. Carrageenan catabolism is encoded by a complex regulon in marine heterotrophic bacteria. Nat Commun. 2017;8:1–7.CAS 
    Article 

    Google Scholar 
    McLean MW, Williamson FB. Glycosulphatase from Pseudomonas carrageenovora, purification and some properties. Eur J Biochem. 1979;101:497–505.CAS 
    PubMed 
    Article 

    Google Scholar 
    Mclean MW, Williamson FB Neocarratetraose 4-O-Monosulphate B-Hydrolase from Pseudomonas carrageenovora. 1981;456:447–56.Suarez-Gonzalez P, Reitner J. Ooids forming in situ within microbial mats (Kiritimati atoll, central Pacific). PalZ. 2021;95:809–21.Article 

    Google Scholar 
    Arp G, Helms G, Karlinska K, Schumann G, Reimer A, Reitner J, et al. Photosynthesis versus exopolymer degradation in the formation of microbialites on the atoll of Kiritimati, Republic of Kiribati, central Pacific. Geomicrobiol J. 2012;29:29–65.CAS 
    Article 

    Google Scholar  More