Croft, M. T., Lawrence, A. D., Raux-Deery, E., Warren, M. J. & Smith, A. G. Algae acquire vitamin B12 through a symbiotic relationship with bacteria. Nature https://doi.org/10.1038/nature04056 (2005).
Google Scholar
Kazamia, E. et al. Mutualistic interactions between vitamin B12-dependent algae and heterotrophic bacteria exhibit regulation. Environ. Microbiol. https://doi.org/10.1111/j.1462-2920.2012.02733.x (2012).
Google Scholar
Bunbury, F. et al. Exploring the onset of B12-based mutualisms using a recently evolved Chlamydomonas auxotroph and B12-producing bacteria. Environ. Microbiol. 24, 3134–3147 (2022).
Google Scholar
Butler, A. Acquisition and utilization of transition metal ions by marine organisms. Science https://doi.org/10.1126/science.281.5374.207 (1998).
Google Scholar
Amin, S. A. et al. Photolysis of iron-siderophore chelates promotes bacterial-algal mutualism. Proc. Natl. Acad. Sci. U. S. A. https://doi.org/10.1073/pnas.0905512106 (2009).
Google Scholar
Amin, S. A. et al. Interaction and signalling between a cosmopolitan phytoplankton and associated bacteria. Nature https://doi.org/10.1038/nature14488 (2015).
Google Scholar
Mayali, X. & Azam, F. Algicidal bacteria in the sea and their impact on algal blooms. J. Eukaryot. Microbiol. https://doi.org/10.1111/j.1550-7408.2004.tb00538.x (2004).
Google Scholar
Bagwell, C. E. et al. Discovery of bioactive metabolites in biofuel microalgae that offer protection against predatory bacteria. Front. Microbiol. https://doi.org/10.3389/fmicb.2016.00516 (2016).
Google Scholar
Hoeger, A. L., Jehmlich, N., Kipping, L., Griehl, C. & Noll, M. Associated bacterial microbiome responds opportunistic once algal host Scenedesmus vacuolatus is attacked by endoparasite Amoeboaphelidium protococcarum. Sci. Rep. https://doi.org/10.1038/s41598-022-17114-1 (2022).
Google Scholar
Mars Brisbin, M., Mitarai, S., Saito, M. A. & Alexander, H. Microbiomes of bloom-forming Phaeocystis algae are stable and consistently recruited, with both symbiotic and opportunistic modes. ISME J. https://doi.org/10.1038/s41396-022-01263-2 (2022).
Google Scholar
Milici, M. et al. Co-occurrence analysis of microbial taxa in the Atlantic ocean reveals high connectivity in the free-living bacterioplankton. Front. Microbiol. 7, 1–20 (2016).
Google Scholar
Barberán, A., Bates, S. T., Casamayor, E. O. & Fierer, N. Using network analysis to explore co-occurrence patterns in soil microbial communities. ISME J. 6, 343–351 (2012).
Google Scholar
Tucker, A. E. & Brown, S. P. Sampling a gradient of red snow algae bloom density reveals novel connections between microbial communities and environmental features. Sci. Rep. 12, 1–15 (2022).
Google Scholar
Faust, K. & Raes, J. Microbial interactions: From networks to models. Nat. Rev. Microbiol. 10, 538–550 (2012).
Google Scholar
Chun, S. J. et al. Network analysis reveals succession of microcystis genotypes accompanying distinctive microbial modules with recurrent patterns. Water Res. https://doi.org/10.1016/j.watres.2019.115326 (2020).
Google Scholar
Huang, S. Back to the biology in systems biology: What can we learn from biomolecular networks?. Briefings Funct. Genom. Proteom. https://doi.org/10.1093/bfgp/2.4.279 (2004).
Google Scholar
Ma’ayan, A. Introduction to network analysis in systems biology. Sci. Signal. https://doi.org/10.1126/scisignal.2001965 (2011).
Google Scholar
Williams, R. J., Howe, A. & Hofmockel, K. S. Demonstrating microbial co-occurrence pattern analyses within and between ecosystems. Front. Microbiol. 5, 1–10 (2014).
Google Scholar
Fuhrman, J. A., Cram, J. A. & Needham, D. M. Marine microbial community dynamics and their ecological interpretation. Nat. Rev. Microbiol. https://doi.org/10.1038/nrmicro3417 (2015).
Google Scholar
Chafee, M. et al. Recurrent patterns of microdiversity in a temperate coastal marine environment. ISME J. 12, 237–252 (2018).
Google Scholar
Zamkovaya, T., Foster, J. S., de Crécy-Lagard, V. & Conesa, A. A network approach to elucidate and prioritize microbial dark matter in microbial communities. ISME J. 15, 228–244 (2021).
Google Scholar
Lima-Mendez, G. et al. Determinants of community structure in the global plankton interactome. Science https://doi.org/10.1126/science.1262073 (2015).
Google Scholar
Bennke, C. M. et al. The distribution of phytoplankton in the Baltic Sea assessed by a prokaryotic 16S rRNA gene primer system. J. Plankton Res. 40, 244–254 (2018).
Google Scholar
Berry, D. & Widder, S. Deciphering microbial interactions and detecting keystone species with co-occurrence networks. Front. Microbiol. https://doi.org/10.3389/fmicb.2014.00219 (2014).
Google Scholar
Needham, D. M. & Fuhrman, J. A. Pronounced daily succession of phytoplankton, archaea and bacteria following a spring bloom. Nat. Microbiol. https://doi.org/10.1038/nmicrobiol.2016.5 (2016).
Google Scholar
Thompson, L. R. et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature https://doi.org/10.1038/nature24621 (2017).
Google Scholar
Gonzalez, A. et al. Qiita: Rapid, web-enabled microbiome meta-analysis. Nat. Methods https://doi.org/10.1038/s41592-018-0141-9 (2018).
Google Scholar
Caporaso, J. G. et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl. Acad. Sci. U. S. A. https://doi.org/10.1073/pnas.1000080107 (2011).
Google Scholar
Caporaso, J. G. et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. https://doi.org/10.1038/ismej.2012.8 (2012).
Google Scholar
Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. https://doi.org/10.1038/s41587-019-0209-9 (2019).
Google Scholar
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet. J. https://doi.org/10.14806/ej.17.1.200 (2011).
Google Scholar
Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods https://doi.org/10.1038/nmeth.3869 (2016).
Google Scholar
Bokulich, N. A. et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome https://doi.org/10.1186/s40168-018-0470-z (2018).
Google Scholar
Decelle, J. et al. PhytoREF: A reference database of the plastidial 16S rRNA gene of photosynthetic eukaryotes with curated taxonomy. Mol. Ecol. Resour. 15, 1435–1445 (2015).
Google Scholar
Major oceanic 16S/18S databases in qiime2 format. https://github.com/ndu-invitae/Oceanic_database/tree/master/PhytoRef.
Hemprich-Bennett, D. R., Oliveira, H. F. M., Le Comber, S. C., Rossiter, S. J. & Clare, E. L. Assessing the impact of taxon resolution on network structure. Ecology https://doi.org/10.1002/ecy.3256 (2021).
Google Scholar
Watts, S. C., Ritchie, S. C., Inouye, M. & Holt, K. E. FastSpar: Rapid and scalable correlation estimation for compositional data. Bioinformatics https://doi.org/10.1093/bioinformatics/bty734 (2019).
Google Scholar
Friedman, J. & Alm, E. J. Inferring correlation networks from genomic survey data. PLoS Comput. Biol. https://doi.org/10.1371/journal.pcbi.1002687 (2012).
Google Scholar
Csardi, G., & Nepusz, T. The igraph software package for complex network research. InterJournal, Complex Systems. igraph Softw. Packag. (2006).
Shannon, P. et al. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. https://doi.org/10.1101/gr.1239303 (2003).
Google Scholar
Assenov, Y., Ramírez, F., Schelhorn, S. E. S. E., Lengauer, T. & Albrecht, M. Computing topological parameters of biological networks. Bioinformatics https://doi.org/10.1093/bioinformatics/btm554 (2008).
Google Scholar
Barabási, A. L. Scale-free networks: A decade and beyond. Science https://doi.org/10.1126/science.1173299 (2009).
Google Scholar
Morris, J. H. et al. ClusterMaker: A multi-algorithm clustering plugin for cytoscape. BMC Bioinform. https://doi.org/10.1186/1471-2105-12-436 (2011).
Google Scholar
Van Dongen, S. & Abreu-Goodger, C. Using MCL to extract clusters from networks. Methods Mol. Biol. https://doi.org/10.1007/978-1-61779-361-5_15 (2012).
Google Scholar
Raivo, K. Pheatmap: Pretty heatmaps. R Pacakage Version (2012).
Albert, R., Jeong, H. & Barabási, A. L. Diameter of the world-wide web. Nature https://doi.org/10.1038/43601 (1999).
Google Scholar
Eisenberg, E. & Levanon, E. Y. Preferential attachment in the protein network evolution. Phys. Rev. Lett. https://doi.org/10.1103/PhysRevLett.91.138701 (2003).
Google Scholar
Ma, B. et al. Earth microbial co-occurrence network reveals interconnection pattern across microbiomes. Microbiome 8, 82 (2020).
Google Scholar
Wang, H. et al. Combined use of network inference tools identifies ecologically meaningful bacterial associations in a paddy soil. Soil Biol. Biochem. 105, 227–235 (2017).
Google Scholar
Goecke, F., Thiel, V., Wiese, J., Labes, A. & Imhoff, J. F. Algae as an important environment for bacteria—Phylogenetic relationships among new bacterial species isolated from algae. Phycologia https://doi.org/10.2216/12-24.1 (2013).
Google Scholar
Krohn-Molt, I. et al. Metagenome survey of a multispecies and alga-associated biofilm revealed key elements of bacterial-algal interactions in photobioreactors. Appl. Environ. Microbiol. https://doi.org/10.1128/AEM.01641-13 (2013).
Google Scholar
Woebken, D. et al. Fosmids of novel marine Planctomycetes from the Namibian and Oregon coast upwelling systems and their cross-comparison with planctomycete genomes. ISME J. https://doi.org/10.1038/ismej.2007.63 (2007).
Google Scholar
Faria, M. et al. Planctomycetes attached to algal surfaces: Insight into their genomes. Genomics https://doi.org/10.1016/j.ygeno.2017.10.007 (2018).
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. https://doi.org/10.1099/00207713-51-3-985 (2001).
Google Scholar
Nedashkovskaya, O. I. et al. Mesonia algae gen. nov., sp. nov., a novel marine bacterium of the family Flavobacteriaceae isolated from the green alga Acrosiphonia sonderi (Kütz) Kornm. Int. J. Syst. Evol. Microbiol. https://doi.org/10.1099/ijs.0.02626-0 (2003).
Google Scholar
Kim, B. H., Ramanan, R., Cho, D. H., Oh, H. M. & Kim, H. S. Role of Rhizobium, a plant growth promoting bacterium, in enhancing algal biomass through mutualistic interaction. Biomass Bioenerg. https://doi.org/10.1016/j.biombioe.2014.07.015 (2014).
Google Scholar
Rivas, M. O., Vargas, P. & Riquelme, C. E. Interactions of Botryococcus braunii cultures with bacterial biofilms. Microb. Ecol. https://doi.org/10.1007/s00248-010-9686-6 (2010).
Google Scholar
Cole, J. J. Interactions between bacteria and algae in aquatic ecosystems. Annu. Rev. Ecol. Syst. https://doi.org/10.1146/annurev.es.13.110182.001451 (1982).
Google Scholar
Fulbright, S. P. et al. Bacterial community changes in an industrial algae production system. Algal Res. https://doi.org/10.1016/j.algal.2017.09.010 (2018).
Google Scholar
Zhou, J. et al. Microbial community structure and associations during a marine dinoflagellate bloom. Front. Microbiol. https://doi.org/10.3389/fmicb.2018.01201 (2018).
Google Scholar
Simon, M., Glöckner, F. O. & Amann, R. Different community structure and temperature optima of heterotrophic picoplankton in various regions of the Southern Ocean. Aquat. Microb. Ecol. https://doi.org/10.3354/ame018275 (1999).
Google Scholar
Brussaard, C. P. D., Mari, X., Van Bleijswijk, J. D. L. & Veldhuis, M. J. W. A mesocosm study of Phaeocystis globosa (Prymnesiophyceae) population dynamics: II. Significance for the microbial community. Harmful Algae https://doi.org/10.1016/j.hal.2004.12.012 (2005).
Google Scholar
Janse, I., Zwart, G., Van der Maarel, M. J. E. C. & Gottschal, J. C. Composition of the bacterial community degrading Phaeocystis mucopolysaccharides in enrichment cultures. Aquat. Microb. Ecol. https://doi.org/10.3354/ame022119 (2000).
Google Scholar
Grossart, H. P., Levold, F., Allgaier, M., Simon, M. & Brinkhoff, T. Marine diatom species harbour distinct bacterial communities. Environ. Microbiol. https://doi.org/10.1111/j.1462-2920.2005.00759.x (2005).
Google Scholar
Sapp, M. et al. Species-specific bacterial communities in the phycosphere of microalgae?. Microb. Ecol. https://doi.org/10.1007/s00248-006-9162-5 (2007).
Google Scholar
Sapp, M., Wichels, A. & Gerdts, G. Impacts of cultivation of marine diatoms on the associated bacterial community. Appl. Environ. Microbiol. https://doi.org/10.1128/AEM.02274-06 (2007).
Google Scholar
Milici, M. et al. Bacterioplankton biogeography of the Atlantic ocean: A case study of the distance-decay relationship. Front. Microbiol. 7, 1–15 (2016).
Google Scholar
Martin, K. et al. The biogeographic differentiation of algal microbiomes in the upper ocean from pole to pole. Nat. Commun. https://doi.org/10.1038/s41467-021-25646-9 (2021).
Google Scholar
Martinez-Garcia, M. et al. Capturing single cell genomes of active polysaccharide degraders: An unexpected contribution of verrucomicrobia. PLoS ONE https://doi.org/10.1371/journal.pone.0035314 (2012).
Google Scholar
Dell’Anno, F. et al. Highly contaminated marine sediments can host rare bacterial taxa potentially useful for bioremediation. Front. Microbiol. https://doi.org/10.3389/fmicb.2021.584850 (2021).
Google Scholar
Newton, R. J. et al. Genome characteristics of a generalist marine bacterial lineage. ISME J. https://doi.org/10.1038/ismej.2009.150 (2010).
Google Scholar
Sañudo-Wilhelmy, S. A., Gómez-Consarnau, L., Suffridge, C. & Webb, E. A. The role of B vitamins in marine biogeochemistry. Ann. Rev. Mar. Sci. https://doi.org/10.1146/annurev-marine-120710-100912 (2014).
Google Scholar
Durham, B. P. et al. Cryptic carbon and sulfur cycling between surface ocean plankton. Proc. Natl. Acad. Sci. U. S. A. https://doi.org/10.1073/pnas.1413137112 (2015).
Google Scholar
Proulx, S. R., Promislow, D. E. L. & Phillips, P. C. Network thinking in ecology and evolution. Trends Ecol. Evol. https://doi.org/10.1016/j.tree.2005.04.004 (2005).
Google Scholar
Coelho, F. J. R. C. et al. Integrated analysis of bacterial and microeukaryotic communities from differentially active mud volcanoes in the Gulf of Cadiz. Sci. Rep. 6, 1–10 (2016).
Google Scholar
Queiroz, L. L. et al. Bacterial diversity in deep-sea sediments under influence of asphalt seep at the São Paulo Plateau. Antonie van Leeuwenhoek. Int. J. Gen. Mol. Microbiol. 8, 9. https://doi.org/10.1007/s10482-020-01384-8 (2020).
Google Scholar
de Voogd, N. J., Cleary, D. F. R., Polónia, A. R. M. & Gomes, N. C. M. Bacterial community composition and predicted functional ecology of sponges, sediment and seawater from the thousand islands reef complex, West Java, Indonesia. FEMS Microbiol. Ecol. https://doi.org/10.1093/femsec/fiv019 (2015).
Google Scholar
Vigneron, A. et al. Multiple strategies for light-harvesting, photoprotection, and carbon flow in high latitude microbial mats. Front. Microbiol. https://doi.org/10.3389/fmicb.2018.02881 (2018).
Google Scholar
Pushpakumara, B. L. D. U., Tandon, K., Willis, A. & Verbruggen, H. The bacterial microbiome of the coral skeleton algal symbiont Ostreobium shows preferential associations and signatures of phylosymbiosis. bioRxiv https://doi.org/10.1101/2022.12.13.520198 (2022).
Google Scholar
Lage, O. M. & Bondoso, J. Planctomycetes diversity associated with macroalgae. FEMS Microbiol. Ecol. https://doi.org/10.1111/j.1574-6941.2011.01168.x (2011).
Google Scholar
Longford, S. R. et al. Comparisons of diversity of bacterial communities associated with three sessile marine eukaryotes. Aquat. Microb. Ecol. https://doi.org/10.3354/ame048217 (2007).
Google Scholar
Bengtsson, M. M. & Øvreås, L. Planctomycetes dominate biofilms on surfaces of the kelp Laminaria hyperborea. BMC Microbiol. https://doi.org/10.1186/1471-2180-10-261 (2010).
Google Scholar
Ludington, W. B. et al. Assessing biosynthetic potential of agricultural groundwater through metagenomic sequencing: A diverse anammox community dominates nitrate-rich groundwater. PLoS ONE https://doi.org/10.1371/journal.pone.0174930 (2017).
Google Scholar
Vidal-Melgosa, S. et al. Diatom fucan polysaccharide precipitates carbon during algal blooms. Nat. Commun. 12, 1–13 (2021).
Google Scholar
Walker, A. M., Leigh, M. B. & Mincks, S. L. Patterns in benthic microbial community structure across environmental gradients in the beaufort sea shelf and slope. Front. Microbiol. https://doi.org/10.3389/fmicb.2021.581124 (2021).
Google Scholar
Morris, R. M., Longnecker, K. & Giovannoni, S. J. Pirellula and OM43 are among the dominant lineages identified in an Oregon coast diatom bloom. Environ. Microbiol. https://doi.org/10.1111/j.1462-2920.2006.01029.x (2006).
Google Scholar
Sichert, A. et al. Verrucomicrobia use hundreds of enzymes to digest the algal polysaccharide fucoidan. Nat. Microbiol. https://doi.org/10.1038/s41564-020-0720-2 (2020).
Google Scholar
Bohórquez, J. et al. Different types of diatom-derived extracellular polymeric substances drive changes in heterotrophic bacterial communities from intertidal sediments. Front. Microbiol. https://doi.org/10.3389/fmicb.2017.00245 (2017).
Google Scholar
Landa, M. et al. Phylogenetic and structural response of heterotrophic bacteria to dissolved organic matter of different chemical composition in a continuous culture study. Environ. Microbiol. https://doi.org/10.1111/1462-2920.12242 (2014).
Google Scholar
Orsi, W. D. et al. Diverse, uncultivated bacteria and archaea underlying the cycling of dissolved protein in the ocean. ISME J. https://doi.org/10.1038/ismej.2016.20 (2016).
Google Scholar
Source: Ecology - nature.com
