bioRxiv Science⌕ Search

bioRxiv · 10.64898/2026.02.09.704904

Dual transcriptomics reveal commensal interactions between microalgae and phycosphere bacteria

Abstract

The interactions between microalgae and the bacteria living in the phycosphere are pivotal to the role they play in aquatic ecosystems. This study examines how two representatives of common phycosphere bacteria, Yoonia sp. TsM2_T14_4 (Rhodobacteraceae) and Maribacter sp. IgM3_T14_3 (Flavobacteriaceae), interact with three microalgal hosts: Isochrysis galbana, Tetraselmis suecica, and Conticribra weissflogii (formerly Thalassiosira weissflogii) using dual transcriptomic analyses of both bacteria and microalgae. Bacterial transcriptomes differed significantly depending on microalgal host, with notable changes in carbohydrate metabolism among other COG categories. Yoonia sp. expressed genes involved in anoxygenic photosynthesis in co-culture with I. galbana, presumably due to its inability to utilize carbohydrates from this algal host, whereas Maribacter sp. expressed polysaccharide degradation genes in co-culture with C. weissflogii along with T9SS genes, which can be employed to secrete these hydrolytic enzymes. Specifically, a putative glucan endo-1,3-beta-D-glucosidase was highly expressed, an enzyme that can hydrolyze laminarin and curdlan. Maribacter sp. IgM3_T14_3 could utilize laminarin as a sole carbon source in laboratory settings, a polysaccharide commonly found in marine environments and produced by C. weissflogii. Surprisingly, microalgal transcriptomes remained largely unaltered in the presence of either of the bacteria compared to transcriptomes of axenic algal cultures. These findings highlight the adaptability of phycosphere bacteria to different microalgal hosts. Furthermore, it also indicates a commensalism between microalgae, Yoonia sp. and Maribacter sp., in which the bacteria adapt to and benefit from microalgal host exudates, whereas under the conditions employed here the microalgae are unaffected by the presence of these bacterial symbionts. ImportanceMicroalgae are the key players in marine ecosystems, capturing carbon dioxide through photosynthesis and releasing carbohydrates into their immediate environment, the so-called phycosphere. Certain bacterial taxa are consistently found within the phycosphere, where they interact with their microalgal host in a variety of ways. However, the impact of these bacteria on the microalgae is not fully understood despite their ecological relevance. This study uses a dual transcriptomic approach to investigate the impact of such core phycosphere bacteria on microalgal hosts and vice versa to uncover the reason behind their success in the phycosphere and possible roles in marine ecosystems.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Roager, L., Schostag, M., Garritano, A., Gram, L., Egan, S.. 2026-02-09. Dual transcriptomics reveal commensal interactions between microalgae and phycosphere bacteria. https://doi.org/10.64898/2026.02.09.704904

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

A population-scale landscape of the subgingival microbiome reveals divergent routes to periodontal dysbiosis

Periodontitis is an archetypical mucosal inflammatory disease in which microbiome dysbiosis at the tooth-epithelial interface interacts with host genetic and behavioral risk factors to drive immune-mediated tissue destruction. Although subgingival microbiome compositional shifts are thought to parallel disease severity, microbiome variation at the population-level and its relationship to periodontal clinical phenotypes and disease-modifying factors remain poorly defined. Here, we use unsupervised manifold learning to map the compositional landscape of the subgingival microbiome in 1,355 adults spanning periodontal health to severe periodontitis. We identified eight latent microbiome states organized along a branching continuum from eubiosis to dysbiosis. An intermediate microbial configuration marked ecological destabilization and bifurcation into two distinct periodontitis-associated dysbiotic trajectories, distinguished by links to gingival inflammation and smoking. Although the microbiome trajectories broadly tracked periodontal destruction, a minority of individuals showed discordant microbiome-clinical phenotypes, with some individuals with periodontitis retaining otherwise eubiotic microbiomes enriched for low-abundance pathobionts, while some cases of health or mild disease had highly dysbiotic communities, suggesting distinct host susceptibility. Together, these findings define a population-scale ecological landscape of the subgingival microbiome, reveal divergent trajectories to periodontal dysbiosis, and highlight heterogeneity in the relationship between microbial community structure and clinical disease expression.

microbiology↗

Rapid and largely reversible shifts in the canine fecal metabolome during dietary change

Diet can rapidly change the fecal metabolome, but less is known about recovery after the original diet is restored. We used untargeted UPLC-MS metabolomics to analyze 72 fecal samples from nine Pumi dogs during an owner-managed switch from dry food to raw food and back to dry food. Diet phase accounted for a large proportion of variation in both ionization modes. More than 13,000 LC-MS features changed at the first sampling point after the switch to raw food, with a similarly large response after return to dry food. Among features significant in both comparisons, more than 99% changed in opposite directions. At the final sampling point, no positive-mode (ESI+) features and only 13 negative-mode (ESI-) features differed from the second dry-food baseline under the same threshold. BARF-associated patterns persisted in analyses excluding individual dogs and in pedigree-adjusted candidate models, although individual feature effects depended on normalization. Putative metabolites from several biochemical classes differed in their response and recovery. The fecal metabolome therefore changed rapidly and returned largely toward baseline, with differences among dogs.

microbiology↗

Taxonomic and functional concordance between full-length ONT 16S and ONT shotgun metagenomics in the canine gut microbiome

Background: Full-length Oxford Nanopore Technologies (ONT) 16S rRNA sequencing provides a scalable view of microbial community composition and can support phylogeny-based functional prediction, but it is not equivalent to shotgun metagenomics. We asked which biological conclusions are preserved when the same canine fecal specimens are profiled by full-length ONT 16S and ONT whole-genome shotgun (WGS) sequencing, and how their agreement depends on analytical scale, reference representation and classifier. Methods: Ninety-seven fecal specimens from 51 dogs were profiled with both assays from the same DNA extract. Functional profiles predicted from NanoASV/NanoPredict with PICRUSt2 were compared with WGS-supported KEGG Ortholog (KO) profiles generated by Kadath. Taxonomy was benchmarked in a source-genome-matched RefSeq universe and in a host-specific DogMAG universe using minitax and Kraken2. Agreement was evaluated at whole-profile, feature-abundance, detection, between-sample structure and biological-inference scales. Age-associated transfer was assessed with dog-aware continuous mixed models, grouped signed-score analyses and paired/dog-blocked PERMANOVA. Results: Functional whole-profile concordance was high: median within-sample CLR Spearman correlations ranged from 0.781 to 0.860 across developmental strata, while between-sample functional structure remained significant by Mantel (rho=0.543) and Procrustes (r=0.693; both p=0.001). Feature-wise transfer was substantially weaker (median KO-wise CLR Spearman=0.318). Continuous age-associated KO slopes showed substantial cross-assay concordance (Spearman=0.727; signed-score Spearman=0.753; direction agreement=77.9%), although 1,290/5,258 eligible KOs retained significant assay-by-age interactions. Taxonomically, exact genus/species abundance agreement was much lower than agreement in between-sample ecological structure. Host-specific DogMAG improved species-level median Spearman from 0.261 to 0.656 for minitax SpeciesEstimate and from 0.181 to 0.512 for Kraken2. The classifier effect was independent of reference choice: under both RefSeq and DogMAG, minitax yielded stronger 16S-WGS concordance than Kraken2, with all eight prespecified RefSeq paired genus/species endpoints and all 10 DogMAG primary paired endpoints significant after BH correction. The same ordering extended to developmental inference, with DogMAG genus/species age-slope concordance of 0.795/0.799 for SpeciesEstimate versus 0.693/0.702 for Kraken2. Taxonomic Aitchison PERMANOVA detected age-associated structure in every assay/reference/classifier/rank combination, whereas age-by-assay interactions were consistently significant but small (R2 approximately 1.1 to 2.2%). Stricter NanoASV identity thresholds removed substantial 16S abundance without improving species-level agreement. Conclusions: The extent of cross-assay agreement depends on the level of analysis. Full-length ONT 16S preserves broad functional organization, ecological structure and much of the direction of age-associated change, but exact fine-rank composition, individual-feature abundance and effect magnitude remain assay dependent. Host-specific reference representation substantially narrows the taxonomic gap, and classifier choice exerts an additional independent effect: within the same matched reference set, minitax consistently yields stronger 16S-WGS concordance than Kraken2 across abundance, detection, ecological-distance and developmental-inference endpoints. Full-length ONT 16S is therefore well suited to broad ecological screening and hypothesis generation, whereas WGS remains preferable when conclusions depend on quantitative fine-rank composition, directly supported gene content or precise feature-level effect estimates.

microbiology↗