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. 2025 Jun 17;20(1):73.
doi: 10.1186/s40793-025-00739-w.

Salinization alters microbial methane cycling in freshwater sediments

Affiliations

Salinization alters microbial methane cycling in freshwater sediments

Lorena Selak et al. Environ Microbiome. .

Abstract

Climate change-induced salinization poses a global threat to freshwater ecosystems and challenges microbial communities driving crucial biogeochemical processes, particularly methane cycling. This study examined the impact of salinization and the accompanying sulfate concentration increases on microbial community dynamics and methane cycling in coastal freshwater lake sediments. We show that sulfate enrichment in sediment profiles enables the proliferation of distinct sulfate-reducing bacteria (SRB) that reshape microbial niches by competing with methanogens and promoting sulfate-dependent anaerobic oxidation of methane (AOM). Freshwater SRB clusters, which compete with some methanogens for substrates but also degrade organic compounds into methanogenesis precursors, are replaced by the SEEP-SRB groups that form syntrophic relationships with ANME-1 in salinized sediments. As seawater intrudes and reshapes microbial communities, a methane pocket forms that escapes both aerobic and anaerobic oxidation. Underneath this methane pocket, SRB play a key role in enabling sulfate-dependent AOM, facilitating methane consumption at higher sediment depths. While all microorganisms demonstrated some physiological adaptability potential to elevated osmotic stress, SRB exhibited the highest resilience to increased salinity. These findings highlight how salinization-induced geochemical shifts, particularly sulfate enrichment, directly affect microbial community assembly and impact methane cycling in coastal freshwater ecosystems.

Keywords: Community shifts; Microbial adaptations; Microbial methane cycle; Salinization; Sulfate reducing bacteria.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
(a) Map of Lake Vrana containing specific lake zones and annotated sampling campaigns with associated sampling stations. (b) Lake salinity measurements in sediment core profile and surface sediments
Fig. 2
Fig. 2
(a) Depth profiles of sulfate and methane concentrations in sediments. The SMTZ is highlighted. (b) Relative abundances of functional gene copy numbers involved in the methane cycle, retrieved from sediment profiles at freshwater and salinization stations, normalized by the 16 S rRNA gene copy numbers. Light grey-SMTZ, dark grey-mcrA and dsrAB peak (c) Relative abundances of methanogens, methanotrophs, and SRB communities in sediment profiles, based on 16 S rRNA gene sequence data derived from metagenomes. ANME peak relative abundance is highlighted in grey
Fig. 3
Fig. 3
(a) Differentially abundant taxa represented by the mean log2 fold change in the freshwater sediment depth profile relative to the salinization profile (padj. < 0.05). Bars indicate taxa depleted (blue) or enriched (red) in freshwater compared to salinized sediments. The number of distinct ASVs affiliated with each taxon is shown in grey. The y-axis shows the lowest assigned taxonomic level for each group. (b) Relative abundance of differentially abundant ASVs (count number > 100, relative abundance > 0.5%) along depth profiles of salinization and freshwater sediment cores. ASV identifiers (sp-N) are labeled alongside their affiliated taxonomy
Fig. 4
Fig. 4
(a) Statistical values of differentially abundant MAGs between freshwater and salinization samples, showing genome size (normalized by genome completeness), number of different osmoregulation strategies, and cumulative number of osmoregulation genes present in genomes. Individual genomes are colored according to the sulfate concentrations in the environment where they are most abundant. Mean values are represented by a line. (b) Co-occurrence network analysis of MAGs (completeness > 50, contamination < 10), calculated with CoNet and SparCC, highlighting microbial genomes involved in the methane cycle. Node color indicates functional group, node size reflects the number of correlations, edge color represents the type of correlation, and edge size is weighted by correlation strength. The assigned taxonomy for each MAG is added to corresponding nodes and modularity clusters of interest are encircled. (c) Differential relative abundance of MAGs in freshwater and salinization sediment profiles, along with their affiliated osmoregulation gene content

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