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Contributed Talk: Robust spatial organisation and community composition of a phototrophic microbial community predicts metabolic interactions

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UMCW06 - Microbial communities: current approaches and open challenges

Sarah J.N. Duxbury1, Sebastien Raguideau2,4, Mary Coates1, Jerko Rosko1, Kelsey Cremin1, Christopher Quince2,3,4, Orkun S. Soyer1 1School of Life Sciences, University of Warwick, Coventry, CV4 7AL . 2Organisms and Ecosystems, Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ . 3Gut Microbes and Health, Quadram Institute, Norwich NR4 7UQ , UK. 4Warwick Medical School, University of Warwick, Coventry, CV4 7AL . Phototrophic and heterotrophic organisms commonly co-exist in microbial communities in aquatic environments and play an important role in biogeochemical cycling. These communities, often consisting of photosynthetic cyanobacteria, can readily form spatial structures and assemblages including mats and granules. Whilst initial studies have characterised species and some metabolic functions via community DNA sequencing, little is known about specific interaction partners and the spatial and temporal dynamics of these interactions. We have isolated and maintained over laboratory cultures, a naturally-derived phototrophic microbial community and observed dynamic formation of motile filamentous biofilm structures and granules. We have combined both short (Illumina) and long-read (HiFi PacBio) shotgun metagenomic sequencing to resolve bacterial genomes from community cultures. Additionally, we have used dilution plating to isolate and characterise the taxonomy and physiology of different colony morphotypes. Via sequencing, we identified up to sixteen different bacterial species maintained in a spatially-organised community over multiple growth passages. We identified a novel filamentous cyanobacterial species alongside a phylogenetically diverse set of bacteria across the classes Acidimicrobiia, Actinomycetia, Alphaproteobacteria and Gammaproteobacteria. Through bioinformatics analysis of circular genomes, we can predict metabolic functions and potential interactions among community members, with a particular focus on carbon metabolism. We have experimentally isolated species from the Pseudomonas and Allorhizobium genera and have performed growth assays on carbon sources to support metabolic capabilities predicted from sequence data. Overall, we present a stable, structured and medium-complexity microbial community that could provide a representative model system for understanding population dynamics and stability of spatially-structured freshwater communities.

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