ArticleScientific reports2023
Unravelling microalgal-bacterial interactions in aquatic ecosystems through 16S rRNA gene-based co-occurrence networks.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed, 56 citations in OpenAlex.
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- Environmental gradients and habitat specificity structure benthic microbial assemblages in a temperate seagrass ecosystem.bioRxiv : the preprint server for biology · 2026Article
- Phycosphere microbiome contributes to ecological dominance of diatoms: a comparative study ofISME communications · 2026Article
- A hybrid framework for disease biomarker discovery in microbiome research combining Bayesian networks, machine learning, and network-based methods.Biology methods & protocols · 2026Article
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- Identification of microbial groups and functional genes associated with greenhouse gas emissions in prawn farms.Scientific reports · 2025Article
- Unraveling the assembly mechanisms and differentiated ecological functions of protist cell-associated and free-living bacterial communities during twoMicrobiology spectrum · 2025Article
- Diversity and Vertical Distribution of Planctomycetota in the Water Column of the Remote North Pacific.Environmental microbiology reports · 2025Article
- Importance, structure, cultivability, and resilience of the bacterial microbiota during infection of laboratory-grown Haematococcus spp. by the blastocladialean pathogen Paraphysoderma sedebokerense: evidence for a domesticated microbiota and its potential for biocontrol.FEMS microbiology ecology · 2025Article
- Characterization, Bio-Prospection, and Comparative Metagenomics of Bacterial Communities Revealing the Predictive Functionalities in Wild and Cultured Samples of Industrially Important Red Seaweed Gracilaria dura.Current microbiology · 2025Article
- Drift, dispersal limitation, and homogeneous selection as key processes shaping prokaryotic community assembly in marine sediments.ISME communications · 2025Article
- The dynamic history of prokaryotic phyla: discovery, diversity and division.International journal of systematic and evolutionary microbiology · 2024Review
- Impact of host species on assembly, composition, and functional profiles of phycosphere microbiomes.mSystems · 2024Article
- Microbiomes of three coral species in the Mexican Caribbean and their shifts associated with the Stony Coral Tissue Loss Disease.PloS one · 2024Article
- Seasonal and anthropogenic influences on bacterioplankton communities: ecological impacts in the coastal waters of Qinhuangdao, Northern China.Frontiers in microbiology · 2024Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Interactions between microalgae and bacteria can directly influence the global biogeochemical cycles but the majority of such interactions remain unknown. 16S rRNA gene-based co-occurrence networks have potential to help identify microalgal-bacterial interactions. Here, we used data from 10 Earth microbiome projects to identify potential microalgal-bacterial associations in aquatic ecosystems. A high degree of clustering was observed in microalgal-bacterial modules, indicating densely connected neighbourhoods. Proteobacteria and Bacteroidetes predominantly co-occurred with microalgae and represented hubs of most modules. Our results also indicated that species-specificity may be a global characteristic of microalgal associated microbiomes. Several previously known associations were recovered from our network modules, validating that biologically meaningful results can be inferred using this approach. A range of previously unknown associations were recognised such as co-occurrences of Bacillariophyta with uncultured Planctomycetes OM190 and Deltaproteobacteria order NB1-j. Planctomycetes and Verrucomicrobia were identified as key associates of microalgae due to their frequent co-occurrences with several microalgal taxa. Despite no clear taxonomic pattern, bacterial associates appeared functionally similar across different environments. To summarise, we demonstrated the potential of 16S rRNA gene-based co-occurrence networks as a hypothesis-generating framework to guide more focused research on microalgal-bacterial associations.
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