ISME Communications

Myxococcota are globally distributed bacteria renowned for their remarkable ecological and biotechnological significance due to their complex lifestyles, social behaviour, and secondary metabolite production. Despite their ubiquity in diverse environments, including soil, marine, and extreme habitats, their diversity and ecological roles remain underexplored. Here, we utilized the Microflora Danica dataset, encompassing >10,000 metagenomes and >400 rRNA gene datasets from various environments in Denmark, to investigate the distribution, diversity, and metabolic potential of Myxococcota. We show that Myxococcota are ubiquitous but strongly structured by environment, with soil-associated lineages enriched in predatory and multicellular development traits, whereas aquatic-associated taxa exhibit alternative lifestyles, including anaerobic metabolism and phototrophy. Comparative genomic analysis reveals widespread potential for secondary metabolite production, hydrocarbon degradation, and organohalide transformation, alongside diverse contribution to carbon and nutrient cycling. Together, these findings redefine Myxococcota as a functionally diverse and ecologically differentiated phylum, extending beyond canonical predation and multicellularity, and underscore their promise as large reservoir of unexplored functional potential for biotechnological applications in drug discovery and environmental remediation.

Chytrids are unicellular fungi that infect and degrade phytoplankton as parasites or saprotrophs. They impact not only food availability and quality in surface waters but also carbon cycling and sequestration. So far, their ecological significance has mostly been investigated for freshwater environments, whereas observations for marine environments are scarce -- even though chytrids can be highly abundant there, too (as shown for the Arctic Ocean). To test the chytrids' potential to control phytoplankton dynamics in the Arctic Ocean, we analysed metabarcoding and photosynthetic pigment data from two expeditions, Tara Polar Circle and MOSAiC; the latter providing a dense sampling transect across one year from the under-ice water column and sea ice samples. The phytoplankton communities of both environments were dominated by diatoms, with strong seasonal effects indicating blooms in the water column. Chytrids dominated fungal communities in both environments and revealed a strong cryo-pelagic coupling. They were especially abundant during the sea ice melt in water samples and in ice-associated (sympagic) samples, where they represented >2% and up to 61%, respectively, of all combined reads assigned to chytrids or phytoplankton. Co-occurrences of the two most abundant chytrid taxa with some of the most abundant diatom taxa and niche differentiation from other potential diatom parasites are consistent with the chytrids' critical role in controlling diatom blooms, especially in sympagic habitats.

Nitrous oxide (N2O) is a potent greenhouse gas and is largely produced by incomplete denitrification. Although we know many of the microbial species that denitrify, we are still unable to reliably predict N2O production from soils. Recent work in microbial ecology has shown that when key microbes are considered as members of functional ensembles rather than isolated, the predictive power linking their activity to emergent properties increases dramatically. We hypothesized that the active microbial community during high N2O production would be taxonomically distinct from the inactive portion and increases in N2O production rates would correlate more strongly with increased abundance across multiple active taxa than with dominance by a single active species. We conducted a microcosm experiment where agricultural soil was incubated in anaerobic vials for up to 15 hours while tracking N2O production. Using bioorthogonal non-canonical amino acid tagging paired with fluorescence-activated cell sorting and 16S rRNA amplicon sequencing (BONCAT-FACS-Seq), we probed the active subset of the microbial community throughout the incubation period. Analysis of 16S rRNA gene amplicons revealed that the active and inactive fractions contained distinct taxa, and the taxonomic composition of the active fraction shifted over time. We found that less than 1% of the microbial community was responsible for N2O flux rates as high as 3.84 {micro}g N2O-N g dry soil-1 hr-1. The level of activity (median fluorescent intensity of active cells) correlated well with N2O production rates. The Ensemble Quotient Optimization for Microbiomes (mEQO) tool was used to identify an ensemble of eight organisms whose combined abundance best correlated with N2O fluxes. Overall, our results reveal that N2O fluxes are driven not by changes in a single taxon but by shifting ensembles of active microorganisms whose combined functional potential supports consistent emissions. This study applied a novel conceptual and methodological framework with a distinct focus on the active microbial community, rather than the entire community; if our observation that N2O flux rates are correlated with an ensemble of organisms is broadly confirmed, then framing denitrification as a community trait may increase predictability of this key process.

Microbial communities occur in all habitats, yet how individual growth on available nutrients scales to community assembly remains poorly understood. This gap stems largely from the unknown effects of species interactions. These interactions arise because individual populations both consume and transform primary substrates into metabolites exploitable by others, and because parasitic and predatory mechanisms can release cellular building blocks that enable nutrient reuse. Here, we present a mathematical framework that predicts community growth and compositional succession from monoculture growth kinetics, resource availability, and species interaction parameters. To parametrize species interactions, we use a simulated-annealing optimization algorithm to search parameter space for sets that minimize the difference between modeled community growth and experimental time series from soil microcosms inoculated with defined communities of 20 or 21 soil isolates, with or without an opportunistic bacteriovorous member. The optimized interaction parameter sets were then used to predict growth dynamics in an independent 21-member community and in species drop-out communities. We find that community development is biphasic: an initial phase dominated by competition for primary resources driven by inherent strain growth kinetics, followed by a phase governed by cross-feeding and biomass formation on released byproducts. Paired metatranscriptomic analysis corroborated predicted shifts in individual growth states and revealed metabolic repurposing associated with the sudden renewed availability of metabolites and cellular building blocks. Model simulations that excluded species interactions reproduced only one-fifth of the observed community biomass, highlighting the importance of cross-feeding for soil community growth. Overall, models that integrate monoculture growth kinetics with inferred species interactions can predict the dynamics of medium-complexity communities from starting inocula even when environmental nutrient composition is largely unknown.

In marine ecosystems, phytoplankton growth is frequently limited by iron, a micronutrient, due to its poor solubility from major sources such as atmospheric dust. Many phytoplankton cannot access dust-bound iron independently, and processes that solubilize this iron remain poorly understood. Here, we investigated whether bacterial partners can enhance phytoplankton growth under iron-limited conditions by facilitating utilization of dust-bound iron. Our study focused on Phaeodactylum tricornutum, a model diatom that is adapted to low iron growth conditions, grown in co-culture with bacteria isolated from its phycosphere. In iron-limited experiments using mineral dust as the sole iron source, the addition of Marinobacter significantly enhanced diatom growth compared to axenic controls, whereas Stappia significantly suppressed it. However, under iron-replete conditions, neither bacterium affected growth. These results indicated that under low-iron conditions, Marinobacter actively alleviates iron deficiency. Co-cultured bacterial cell abundances remained at least an order of magnitude lower than diatom cells. Marinobacter also enhanced algal growth within days of dust addition to established Fe-limited co-cultures, indicating its beneficial effect on P. tricornutum was not unique to a system in which it was newly introduced. Exometabolomic profiling comparing the axenic diatom and co-cultures revealed a suite of condensed aromatic organosulfur and peptide-like compounds associated with bacterial presence, as well as compounds that appeared to be unique to each co-culture, hinting at a molecular underpinning of each strains impact. Our findings demonstrate that low-abundance members of the phycosphere community can have a significant impact on host growth by modulating the accessibility of dust-bound Fe.

Virus-like particles (VLPs) are an abundant component of microbiomes with critical ecological roles such as population control through viral predation and horizontal gene transfer. Studying the collection of viruses in microbiomes (the virome) through metagenomics has provided important insights into the composition and functions of VLPs in different environments. However, the current gold-standard method for VLP purification, CsCl density gradient ultracentrifugation (CsCl), is low throughput, time consuming and suffers from biases which limits the ability to study viromes in larger sample sets and can interfere with data interpretation. Here we present an anion exchange (AEX) chromatography-based approach for the purification of VLPs from microbiome samples that allows for significant increases in throughput and reproducibility while achieving VLP purity levels similar to or higher than CsCl. We used microbiome samples of known composition to first establish and evaluate the AEX approaches and compare them to CsCl. We implemented the AEX approach both for fast performance liquid chromatography (FPLC) and in multi-well plates. We compared the VLPs purified with CsCl and AEX using shotgun metagenomic sequencing and found that AEX performs similarly to or better than CsCl for purification of VLPs. AEX purified VLP-fractions captured significantly more viral DNA compared to CsCl. We also found that both AEX and CsCl were capable of capturing viruses present at extremely low relative abundances (<0.001%). Additionally, we found that DNase digestion and CsCl may bias against filamentous phage morphologies. Finally, we purified VLPs from conventional murine feces using AEX and CsCl. AEX purified murine fecal VLPs had a much higher viral DNA content (85%) than CsCl (41%). While there were some differences in viral contigs assembled from AEX and CsCl VLP metagenomes, these method unique viral contigs made up only small proportions (<8%) of the relative abundance in the VLP metagenomes. AEX, particularly in the multi-well format, enables the ultrapurification of VLPs from tens to hundreds of samples in a single day thus facilitating virome studies with the large sample numbers needed for translational and clinical research.

Bacterial bloomers,populations that experience rapid and significant increases in abundance in response to environmental triggers, briefly dominate marine microbial communities, potentially impacting the ecosystem by channeling large amounts of nutrients and affecting carbon fluxes. Due to their ephemeral nature, bacterial bloomers are challenging to capture, and it remains unknown whether they are restricted to specific taxonomic groups or whether they exhibit recurrent patterns. We analyzed a decade-long time series from the Blanes Bay Microbial Observatory (BBMO, NW Mediterranean Sea) to investigate bacterial bloomers in two size fractions (free-living (0.2-3 um) and particle-attached (3-20 um) communities. We identified 57 Amplicon Sequence Variants (ASVs), less than 1% of the total bacterial richness, exhibiting recurrent or chaotic blooming-like behavior. Bloomers spanned diverse phyla, though some taxonomic coherence appeared within families containing multiple blooming taxa. Monthly sampling detected bloom events on average 4.6 +- 1.9 times per year across both size fractions. Once seasonality was accounted for, blooms showed weak associations with biological and physicochemical variables, likely a consequence of monthly sampling resolution. Nonetheless, a marked shift in the blooming community within the particle-attached size fraction coincided with ecosystem disturbances from the nearby harbour restoration, suggesting that bloomers may act as disturbance sentinels. Metagenomic data showed that blooms led to marked shifts in the community functional potential. Overall, our findings underscore the importance of investigating bloom dynamics to understand microbial contributions to biogeochemical cycles and stress the need for higher-frequency sampling to accurately capture these transient but ecologically relevant events.

Nitrification inhibitors are applied to reduce nitrogen losses and greenhouse gas emissions from fertilized agricultural ecosystems. However, their characterization is typically focused on determining effective inhibitor concentrations from growth or substrate conversion assays that are time-intensive and provide limited mechanistic resolution. Here, we present a microrespirometry (MR)-based workflow for rapid mechanistic characterization of nitrification inhibitors using oxygen consumption as a real-time readout for metabolic activity. The workflow enables the simultaneous assessment of inhibitor efficacy, competitiveness, and enzyme specificity within a single experimental setup, as sequential substrate and inhibitor additions enable direct discrimination between competitive and non-competitive inhibition and between ammonia monooxygenase-specific and broader respiratory inhibition. As a proof of concept, we evaluated three known nitrification inhibitors phenylacetylene (PA), nitrapyrin (NP), and dicyandiamide (DCD) using the ammonia-oxidizing bacteria Nitrosomonas europaea and Nitrosospira multiformis, the complete ammonia oxidizer Nitrospira inopinata, and the nitrite oxidizer Nitrospira moscoviensis. We also compared the results from the MR-based inhibition workflow with those from a conventional growth-based approach and observed a poor correlation between results for inhibitors that are not fully enzyme specific. In conclusion, this work establishes MR as a rapid and versatile platform for the mechanistic screening of novel potential nitrification inhibitors. MR assays reproduce known inhibitory responses while substantially reducing experimental time and increasing mechanistic resolution compared to other assays types. Additionally, we provide the first pure-culture characterization of PA, NP, and DCD efficacy and inhibition mechanisms in a complete ammonia oxidizer, N. inopinata.

Pelagibacterales gMED is the dominant epipelagic genomospecies in the western Mediterranean Sea. We used the O-chain biosynthesis gene clusters, OBCs, as clonal barcodes to analyse strain-level population structure. In total, 385 OBC-defined clonal lineages were tracked across Mediterranean metagenomes spanning 14 years and depths from 5 to 90 m within the photic zone, with between 128 and 336 detected per metagenome. The relative conservation of dominant OBC types across years, seasons, and geographic locations indicated a persistently high and stable clonal diversity.

Natural products are central mediators of microbial interactions. However, once released into the environment, they also become available for neighboring microorganisms capable of degrading and modifying them through biotransformation. These biotransformations may fundamentally reshape metabolomes and influence community behavior, yet our understanding of these processes remains limited. Ribosomally synthesized peptides are particularly compelling in this context because their structural complexity and potent antimicrobial activity coexist with the potential to yield essential nutrients and reduced bioactivity through biotransformation. Identifying the pathways underlying these biotransformations is essential for understanding mechanisms that support microbial coexistence and nutrient recycling in soil microbiomes. Here, we used nisin as a model peptide to investigate biotransformation by soil bacteria. Selective isolation under nisin-rich, carbon-limited conditions yielded two Gram-negative isolates, Burkholderia stabilis and Pseudomonas fragi. Using growth assays and liquid chromatography-mass spectrometry, we found that both isolates grow in the presence of nisin while biotransforming and depleting the peptide. Burkholderia stabilis completely converted nisin through sequential cleavage of the C-terminus, hinge region and lanthionine ring C, whereas Pseudomonas fragi showed more limited processing restricted to the C-terminal region. Although these biotransformations dismantled structural features required for nisins antimicrobial activity, the intrinsic resistance of both isolates suggests a role beyond detoxification. We further detected nisin biosynthetic genes in the source environment, supporting nisins ecological relevance and suggesting that these bacteria may participate in its turnover in soil. Together, these findings reveal extensive microbial processing of nisin and support a role for antimicrobial peptide recycling in soil microbiomes.

Evidence from the Cassini mission confirmed that Saturn's moon Enceladus hosts a subsurface alkaline ocean where rock-water reactions may generate redox disequilibria capable of supporting microbial metabolisms. To investigate potential microbial survival under simulated Enceladus ocean conditions, we used thermodynamic modeling to develop a salt formulation consistent with one possible Enceladus ocean composition and supplemented it with putative microbial energy sources to create a growth medium. The medium was inoculated with samples from diverse ocean world analog environments on Earth to determine which microorganisms could persist under Enceladus-like conditions. The microorganisms persisting in this geochemically bounded medium were heterotrophic, metabolically versatile bacteria with low carbon requirements. Genomic and physiological analyses further showed the presence of multiple stress-response pathways, sodium- based bioenergetic systems, osmoregulation strategies, and other adaptations consistent with survival in alkaline, low-nutrient settings. These results suggest that some stress-tolerant heterotrophic bacteria may serve as useful model organisms for life in Enceladus' subsurface ocean. These findings demonstrate the value of geochemically modeled media as a framework for constraining habitability, identifying relevant biosignatures, and probing potential microbial survival strategies beyond Earth.

Environmental resistome comprises diverse antibiotic resistance genes (ARGs) that can play critical roles in "One Health", facilitating the evolution, persistence, and dissemination of microbial resistances. Yet, knowledge gaps exist in resistome structures and ecological connectivity across various ecosystems at a national scale. Here, we combined nationwide extensive short- and long-read sequencing efforts for soils, sediments, waters and wastewater treatment plants across Denmark to resolve resistome composition, habitat specificity and connectivity. From over 7,000 sequenced environmental samples (24 Tb of metagenomic data) that were classified into 21 distinct habitat classifications, resistomes exhibited habitat-specific patterns. We identified core ARGs for establishing environmental baseline of ARGs, and habitat-associated indicator ARGs facilitating source tracking. Using 110 deep long-read metagenomes (9 Tb data), we showed that only a subset of cross-habitat commonly-abundant ARGs showed elevated associations with MGEs and broad host range, suggesting unequal resistome connectivity across ecosystems among environmental ARGs. Additionally, although natural habitats had much lower resistome relative abundance and transferability than human-associated habitats, some mobile environmental ARGs exhibited links to those in human pathogens. These findings establish an ecological framework for interpreting environmental resistomes and prioritizing ARGs for environmental surveillance in the One Health framework.

The marine sponge holobiont, composed of the sponge host and its microbial symbionts, is a known source of abundant and diverse ether lipids (ELs). Apart from their structural role in the cytoplasmic membrane of archaea and some bacteria, ELs have often been linked to signaling functions and defense against pathogens. Despite the relevance of ELs, their biosynthesis, as well as the identity of their producers, remain elusive. Here, we report the analysis of potential ether lipid producing genes and gene clusters, detected in marine sponge metagenomes as well as public sponge genomes. We show that the sponge holobiont has the capacity to synthesize ELs via several pathways, and suggest the ability of the sponge holobiont to synthesize ELs under different O2 levels. Finally, targeted lipidome analysis confirmed that ELs are present in the lipid profiles of all of the studied sponge holobiont samples, and indicates that the biosynthesis of the plasmalogens detected is likely restricted to the sponge host itself, based on the detected hydrocarbon chain lengths. This work provides a basis for the challenging quest to decipher intricate EL biosynthesis in marine sponges and their associated microbes.

Microbial eukaryotes are prevalent members of host-associated and free-living microbial communities, but are routinely excluded from studies of these communities. Existing methods for eukaryote detection from whole metagenome sequencing are limited by contamination of eukaryotic reference genomes and incomplete taxonomic coverage. Our previously published tool EukDetect addressed these challenges using a curated database of universal BUSCO marker genes, but lacked validated quantitative abundance metrics and was built from a limited number of genomes. Here we present EukDetect2, incorporating a database containing 6,948 microbial eukaryotic genomes representing 6,594 unique species, 2,339 of which are newly added since EukDetect version 1, alongside quantitative metrics for estimating absolute and relative abundance of microbial eukaryotes. Using simulated data, we demonstrate accurate abundance estimation, no false positives from bacterial or host-derived reads, and equivalent or greater sensitivity and specificity than alternative taxonomic profiling tools across a range of microbial abundances and community compositions. Applying EukDetect2 across globally distributed human gut microbiome cohorts, we find that Blastocystis spp. and Dientamoeba fragilis are the most prevalent gut eukaryotes across cohorts, while host-associated fungi are consistently less prevalent than commensal protists. Blastocystis abundance is positively associated with a gut microbial community enriched for fiber-fermenting microbes and depleted for pro-inflammatory and industrialization-associated taxa. EukDetect2 provides sensitive, accurate, and quantitative metrics for investigating microbial eukaryotes from metagenomic samples.

With the rapid expansion of global food demand, aquaculture has become a critical pillar for future food security. However, aquaculture systems remain highly vulnerable to pathogenic bacteria, and rapid identification of antagonistic microbes is essential for sustainable disease control. Conventional evaluation approaches rely on fluorescence labeling or post-culture assays, limiting the ability to quantify dynamic interactions in mixed microbial populations in a real-time and label-free manner. Here, we propose a computational framework for classifying the mixing ratio of Vibrio harveyi and environmental bacteria using time-series motion features extracted from microscopy videos. We defined 24 interpretable motility descriptors and employed a Temporal Convolutional Network (TCN) to learn their temporal structure. The proposed method achieved a classification accuracy of 93.3%, outperforming conventional static statistical approaches and alternative machine learning models. These findings indicate that mixture discrimination in microbial communities is governed not by absolute motility magnitude, but by collective alignment and its temporal stability. Our study establishes a time-resolved computational framework for quantifying dynamic collective order in mixed microbial populations and highlights its potential for label-free automated screening and robotic microbiological applications.

How a single gram of soil harbors billions of microorganisms, each with distinct genomic variants that collectively maintain coherent ecological function(s), is one of microbiology's grand unsolved problems. A key obstacle is determining which variants contribute to individual- and community-level fitness, in which contexts, and how co-occurring ecotypes interact to divide niche space. Here, using nitrate (NO3-)-contaminated subsurface sediment as inoculum, we have performed high throughput enrichments in laboratory media of defined carbon source compositions across ecologically relevant gradients of pH and NO3-. Long-read metagenomics and link-community decomposition of co-occurrence networks of taxa across these enrichments has revealed context-specific functional interactions among dominant generalist and lower-abundance specialist denitrifier ecotypes that comprise 53 distinct enriched communities (EnComs) across 288 enrichments derived from a single sediment sample. We identified a single enzymatic difference of alternative NO3- reductases (NapAB vs. NarGHI) with differing substrate affinities that provided a mechanistic explanation for competitive niche partitioning between the two dominant taxa, Neorhizobium spp. and Allorhizobium spp., along the NO3- gradient. Genome-wide polymorphism ratios (pN/pS) revealed that selective pressures vary systematically with carbon source availability and gradients of pH and NO3-, which helps explain the natural biodiversity and functional interactions of ecotypes within denitrifying communities in the subsurface sediment. Our findings show that controlled enrichments along ecological gradients can thus uncover eco-evolutionary forces of selection, drift, and diversification that sculpt the biodiversity of microbial populations in the natural environment.

Bacteriophages are abundant and diverse in soils, playing a major role in regulating bacterial communities and consequently affecting biogeochemical cycles. Such host-phage interactions may be influenced by fluctuations in soil moisture, as observed in wetlands soils which constitute a key feature of the ongoing climate change. Here, we investigated the spatial and temporal dynamics of both bacteria and T4-type bacteriophage community structures and diversities in soil of a freshwater wetland. Soil was sampled in three sites across a proximal soil transect presenting an increase moisture content at seven dates over an 18 months period with contrasted flooding periods. DNA was extracted and we applied amplicon sequencing of the bacterial 16S rRNA gene and viral g23 gene. Bacterial community composition varied across the proximal soil transect, with Methylomirabilia and Gammaproteobacteria being significantly enriched in the wettest site and comprising ASVs affiliated to methanotroph and denitrifying bacteria, respectively. We identified a large diversity of T4-type phages, among which a fraction was novel, while others were similar to phages previously sequenced from various biomes. These findings suggest that T4-type phages are capable of successfully colonizing diverse niches in the biosphere, contributing to their ubiquity and diversity. Viral community was however dominated by few vASVs, which were highly represented in one or two of the three studied sites supporting the Bank model. All together our results indicate that T4-type phages have broad host ranges and more likely follow bacterial population dynamics. The present study provides new insights into the role of phages in soil, highlighting their interactions with bacterial hosts involved in carbon and nitrogen cycles, interactions that are likely regulated by fluctuations in soil moisture, as observed in wetlands. HighlightsO_LIBoth bacterial and T4-type phages were structured across proximal sites C_LIO_LIBacterial 16S rRNA gene copy number was inversely correlated to the soil moisture C_LIO_LI26 viral ASVs did not cluster with reference sequences C_LIO_LIviral ASVs seem to be primarily controlled by host availability C_LIO_LISoil bacteria and phage diversities were significantly lower in the wettest site C_LI

Dissimilatory nitrate reduction to ammonium (DNRA) is a key biological nitrogen retention pathway, yet the evolutionary mechanisms remain poorly understood. Here, we combined phylogenomic analysis, codon usage bias assessment, horizontal gene transfer (HGT) detection, and gene tree--species tree reconciliation to investigate the evolutionary history of nrfA. Analysis of 103 DNRA-capable taxa and 45 curated nrfA sequences revealed that DNRA capability evolved polyphyletically. Reconciliation analysis identified six discrete HGT events, establishing {delta}-Proteobacteria as the primary donor reservoir. Extreme GC3 differentiation between {delta}- and {varepsilon}-Proteobacteria and uniformly negative {Delta}ENC values indicated strong lineage-specific translational selection. We identified inter-phylum HGT to Planctomycetes and Bacteroidetes, one inter-domain transfer (Archaea [-&gt;] {delta}-Proteobacteria), and provided direct molecular evidence for IS-element-mediated transfer. To validate the generalizability, we expanded the analysis to 180 nrfA sequences, identifying 112 cross-phylum phylogenetic clusters that further support HGT as a widespread dissemination. These findings established a predictive framework linking molecular evolutionary signatures to DNRA capability, with implications for understanding nitrogen cycling.

Streptomyces are abundant soil inhabitants with extensive secondary metabolism and antibiotic resistance traits. Yet, their ecological role in shaping soil antibiotic resistome dynamics remains understudied. Here, we investigated how two different bio-based fertilizers harbouring Streptomyces shaped soil resistome and mobilome by combining genome analysis of eight Streptomyces isolates to metagenomic profiling of soils before fertilization, within 48 hours after fertilizer application, and six weeks after. Streptomyces genomes showed linkages among antibiotic resistance genes, carbohydrate-active enzymes, and antibiotic-production-associated biosynthetic gene clusters, connecting resistance and biosynthesis to broader metabolic strategies. Relationships between carbon degradation and biosynthesis associated with specific enzyme families, indicating that carbon availability shapes secondary metabolism. We confirmed experimentally that antibacterial potential varied with carbon source, suggesting that microbial activity during manufacturing of the bio-based fertilizers may create localized selection pressures before fertilizers enter the soil. Fertilization with the studied materials induced modest but consistent shifts in resistome and mobilome without major changes in dominant taxa or overall bacterial abundances, indicating functional reorganization within soil communities. Diversity of antibiotic resistance genes and mobile genetic elements increased, whereas abundance changes were small. Mobile genetic element composition showed stronger responses that were associated with fertilizer inputs, Streptomyces abundance, and taxa linked to faecal and resistance sources. Together, our results show that bio-based fertilizers shape soil resistome primarily through ecological restructuring of resident soil communities, while carbon-dependent microbial activity within fertilizers may enrich resistance. These factors should be considered in manufacturing of bio-based fertilizer as well as in designing agricultural practices.

Mangrove forests are major blue carbon ecosystems but are often characterized by low surface methane (CH4) emissions. Such low emissions, however, do not necessarily indicate weak methanogenesis, because CH4 production may be offset by internal CH4 consumption before reaching the atmosphere. Although previous community, genomic, and transcriptomic studies have implicated methylotrophic methanogenesis in mangrove sediments, direct taxon-resolved evidence linking methylated carbon assimilation to potentially active methanogens remains limited. Here, we combined methanogenic activity assays, DNA stable isotope probing (DNA-SIP), mcrA and 16S rRNA gene analyses, and phylogenetic comparisons to identify potentially active methanogens across saline-influenced mangrove soils. The results showed that CH4 production potentials were consistently dominated by methylotrophic pathways (1.86-2.78 g CH4 g-1 soil hr-1) across all sites. DNA-SIP, together with consistent community patterns in fresh soils, indicated the potential activity of methylotrophic and mixotrophic methanogens under saline conditions. Methanolobus-affiliated methanogens were associated with salinity, Na+, Cl-, and NH4+, whereas Methanosarcina and unclassified Methanosarcinaceae were linked to soil soluble organic carbon availability and water content, indicating niche differentiation among active methanogenic groups. Phylogenetic analyses incorporating reference sequences from diverse environments further showed that potentially active mangrove methanogens were dominated by saline-associated lineages. Together with our previous methanotrophic evidence from the same sites, these findings suggest that low CH4 emissions from mangrove blue carbon ecosystems can mask substantial internal CH4 cycling sustained by active methanogenesis and CH4 consumption.