Suspended and sinking particle-associated microbiomes exhibit distinct lifestyles in the Elbe estuary

Abstract

Estuaries are important components of the global carbon cycle; exchanging carbon between aquatic, atmospheric, and terrestrial environments, representing important loci for blue carbon storage and greenhouse gas emissions. Estuarine particles are especially important due to their microbial transformation and vertical/horizontal transport. We used metagenomes and metatranscriptomes to assess changes in microbial community composition and functions across the Elbe estuary over one year, linking changes to dissolved and particulate organic matter. We will be the first to link microbial activity derived from molecular data to particulate and dissolved organic carbon characteristics. There were no microbial species responses to the measured physicochemical and dissolved/particulate organic matter parameters, however Weighted Correlation Network Analyses showed significant spatial microbiome differences linked to the estuarine salinity profile. Meanwhile, suspended and sinking particle fractions did not show any community wide differences, but individual gene analyses revealed clear microbial lifestyle differences. Sinking particle-associated transcripts highly expressed competition and stress-responses genes, while suspended particle-associated transcripts favoured energy acquisition and growth. Transcription patterns further indicate that suspended particles may represent a mitigating influence on methane release via methanotrophy, while both suspended and sinking particles produce methane through the same gene complex. This notion suggests that increased sinking particle abundance, such as under high turbidity conditions, leads to increased methane production. Our findings further imply that urban activities such as dredging may have a high impact on greenhouse gas emissions, and higher suspended-sinking particle ratios may alleviate aquatic-atmospheric methane exchanges. Future studies should explore in detail the underlying mechanisms and controlling variables, in particular when taking predicted global changes into account.