Complex interplay between the microalgae and their microbiome in production raceways
Algae-associated microbiomes are underexplored, limiting our understanding of their influence on the large-scale microalgae reactors. Over two 8-month periods, microbial dynamics were monitored three times per week in two microalgae raceways inoculated with Desmodesmus armatus. One reactor received...
| Autores: | , , , , , , , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/452249 |
| Acceso en línea: | https://hdl.handle.net/2117/452249 https://dx.doi.org/10.1016/j.biortech.2025.132650 |
| Access Level: | acceso abierto |
| Palabra clave: | Sewage--Purification Microalgae Marine microbiology Microalgae production Microbiome Metabarcoding Time series Interactomes Aigües residuals--Depuració Microalgues Microbiologia marina Àrees temàtiques de la UPC::Desenvolupament humà i sostenible::Enginyeria ambiental::Tractament de l'aigua Àrees temàtiques de la UPC::Enginyeria civil::Geologia::Oceanografia |
| Sumario: | Algae-associated microbiomes are underexplored, limiting our understanding of their influence on the large-scale microalgae reactors. Over two 8-month periods, microbial dynamics were monitored three times per week in two microalgae raceways inoculated with Desmodesmus armatus. One reactor received wastewater, while the other used clean water and fertilizers. The sampled culture volume was filtered into pico and nano size fractions before DNA extraction. Metabarcoding of the 18S and 16S rRNA genes revealed a high microbial diversity across the two time series and a complex eukaryotic and prokaryotic community growing alongside the microalga. Chlorophyta and Fungi were the dominant eukaryotic groups, while Alphaproteobacteria, Gammaproteobacteria, Actinobacteria, and Bacteroidia dominated the prokaryotic communities. Contrasting Amplicon Sequence Variants (ASVs) were found between healthy (D. armatus abundance > 70 %) and unhealthy (D. armatus abundance 10–20 %) conditions across reactors and time series. Network analysis identified up to 10 potential ecological interactions among D. armatus and its microbiome, predominantly positive. Specific ASVs associated with a healthy condition were positively correlated with D. armatus, while other ASVs linked to an unhealthy condition were negatively correlated. Potentially pathogenic bacteria included Mycobacterium and Flavobacterium, whereas potentially beneficial taxa included Geminocystis, Thiocapsa, Ahniella, and Bosea. Several fungal ASVs showed context-specific associations, whereas specific fungi such as Paraphelidium tribonemae, Aphelidium parallelum, Aphelidium desmodesmi, Aphelidiomycota sp., Rozellomycota sp., and Rhizophidium sp, were identified as potentially harmful. This study reveals the striking diversity and complexity of microalgae- associated microbiomes within raceways, providing valuable insights for optimizing industrial production processes, particularly for wastewater treatment and sustainable green biomass generation. |
|---|