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PubMed2024

Soil keystone viruses are regulators of ecosystem multifunctionality.

Ecosystem multifunctionality reflects the capacity of ecosystems to simultaneously maintain multiple functions which are essential bases for human sustainable development. Whereas viruses are a major component of the soil microbiome that drive ecosystem functions across biomes, the relationships between soil viral diversity and ecosystem multifunctionality remain under-studied. To address this critical knowledge gap, we employed a combination of amplicon and metagenomic sequencing to assess prokaryotic, fungal and viral diversity, and to link viruses to putative hosts. We described the features of viruses and their potential hosts in 154 soil samples from 29 farmlands and 25 forests distributed across China. Although 4,460 and 5,207 viral populations (vOTUs) were found in the farmlands and forests respectively, the diversity of specific vOTUs rather than overall soil viral diversity was positively correlated with ecosystem multifunctionality in both ecosystem types. Furthermore, the diversity of these keystone vOTUs, despite being 10-100 times lower than prokaryotic or fungal diversity, was a better predictor of ecosystem multifunctionality and more strongly associated with the relative abundances of prokaryotic genes related to soil nutrient cycling. Gemmatimonadota and Actinobacteria dominated the host community of soil keystone viruses in the farmlands and forests respectively, but were either absent or showed a significantly lower relative abundance in that of soil non-keystone viruses. These findings provide novel insights into the regulators of ecosystem multifunctionality and have important implications for the management of ecosystem functioning.

Soil Microbiology↗

PubMed2026

Orchard netting impacts on biodiversity leading to cascading effects at the ecosystem level.

Agriculture must ensure food production without further compromising the ecosystem functions upon which it depends. Agricultural practices should therefore avoid harming farmland biodiversity, especially of taxa that supply the key ecosystem services (e.g. pollination, pest control and nutrient uptake) that ultimately support crop production. Orchards are among the largest permanent plantations worldwide and are increasingly characterised by the spread of plastic nets used to protect fruits/nuts from either abiotic (anti-hail, anti-rain, shade nets) or biotic (exclusion nets) hazards. Despite having received little attention to date, these nets may impact natural communities, acting both as physical barriers and as drivers of habitat changes to which biota must respond. Species-level responses to netting depend on the organism's ability to enter the netted environment and successfully exploit available resources. Net-mediated ecological filtering and plastic behavioural responses may alter species interactions, leading to cascading ecological impacts that may create species-poorer 'netted communities' with simplified ecological networks. Such changes may erode biological control potential, other ecosystem functions, and overall system stability. We conducted a systematic review on the effects of protection nets on biota, and reported novel empirical evidence on anti-hail nets' impacts on communities of orchard-dwelling birds, flower-visiting insects, and rodents. In total, we identified 48 studies from the literature, however this literature was strongly biased towards apple orchards, western countries, and pest taxa. Net deployment was highly effective in deterring target pest species, in some cases regardless of their original function, as even weather-protection nets limited pest populations. Side effects on non-target taxa were also often reported, such as decreases in pollinators and natural enemies, and/or increases in secondary pests or microbial diseases. However, most assessments largely disregarded non-pest taxa and the broader ecological consequences of netting. The few studies that addressed the effects of nets at the guild/community level, including our empirical study, confirmed that orchard netting resulted in species-poor assemblages, with possible ecosystem-level consequences. We propose that future assessments should pay more attention to the indirect effects of netting on non-target taxa, and on the supply of crop-supporting ecosystem services mediated by wild species occurring in agroecosystems. Due to the trade-offs between these services and net-mediated crop protection, integrated alternatives should be tested to improve the environmental sustainability of food production and biodiversity conservation in farmed landscapes.

Biodiversity↗

PubMed2026

Spatially defined microenvironmental niches are associated with clinical outcome and tumor ecosystem diversity in head and neck cancer.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) exhibits substantial biological heterogeneity that is not fully explained by human papillomavirus (HPV) status. The spatial organization of tumor, immune, and stromal cell populations and its relationship to clinical outcome remain incompletely understood. METHODS: We performed single-cell spatial transcriptomic and proteomic profiling of 44 primary HNSCC tumors, generating a spatial atlas of 19,471,501 cells across whole-slide tissue sections. Spatial niches and ecosystem states were identified through integrated computational analyses and evaluated for associations with tumor programs, clinicopathologic features, and patient outcomes. FINDINGS: HPV-negative tumors were enriched for fibroblast-rich, immune-poor niches associated with epithelial-mesenchymal transition and hypometabolic tumor programs, whereas HPV-positive tumors displayed more diverse immune, stromal, and vascular niche combinations and were enriched for immunogenic ecosystem states. Approximately 20% of HPV-positive tumors exhibited fibroblast-rich ecosystem architectures resembling HPV-negative disease and were associated with less favorable outcomes than other HPV-positive tumors of similar stage. In patient-derived co-culture models, extracellular matrix-associated fibroblasts were associated with epithelial-mesenchymal transition (EMT)-like tumor states, CD8+ T cell dysfunction, and chemotherapy resistance-associated phenotypes. CONCLUSIONS: Spatial ecosystem architecture is associated with clinically relevant heterogeneity beyond conventional HPV-based classification. Fibroblast-rich, immune-poor ecosystem states characterize a high-risk subset of HPV-positive tumors and may provide a framework for improved biological classification and risk stratification in HNSCC. FUNDING: This work was supported by the National Institutes of Health (R01CA291607 and R21CA267527-01) and the Feldstein Medical Foundation.

Humans↗

PubMed2026

Multicellular ecosystems: Linking cellular diversity to tissue function and disease.

Tissue function emerges from coordinated interactions among diverse cell populations, whereas disruption of these interactions can lead to dysfunction. Recent advances in single-cell and spatial genomics have not only cataloged cellular diversity but also revealed how tissues are organized as dynamic multicellular ecosystems. Moving beyond descriptive cell atlases toward functional, system-level representations represents a major frontier in tissue biology. In this review, we outline conceptual and methodological frameworks for dissecting multicellular coordination, highlight recurrent multicellular ecosystems across physiological and pathological contexts, and explore translational opportunities such as patient stratification, therapeutic reprogramming, and regenerative strategies. Viewing tissues through an ecosystem lens provides a unifying framework that links cellular diversity to emergent tissue function and informs strategies for disease intervention.

Humans↗

PubMed2026

The Baltic Sea: A Unique and Sensitive Ecosystem.

The Baltic Sea is a young, semi-enclosed brackish ecosystem shaped by postglacial history; restricted exchange with the North Sea; and strong gradients in salinity, temperature, and oxygen. These conditions have produced a species-poor but highly productive and ecologically important system. This review synthesizes evidence that Baltic populations persist not only through phenotypic plasticity but also through rapid evolutionary change, local adaptation, hybridization, and demographic history. Population genomic studies reveal sharp genetic differentiation between Baltic and Atlantic populations in many taxa, often across the Danish Straits, and fine-scale structuring within the Baltic itself. Case studies of eelgrass, bladderwrack, blue mussels, Baltic clam, cod, flounder, and herring illustrate how clonality, hybrid swarm formation, reproductive isolation, and habitat-specific selection shape resilience and vulnerability. Rapid warming, hypoxia, eutrophication, overfishing, and low functional redundancy increase ecosystem sensitivity. Long-term resilience will depend on protecting locally adapted populations and integrating genomic knowledge into ecosystem-based management and conservation.

Journal Article↗

PubMed2026

SCMO: a deep learning model integrating the single-cell resolution TME ecosystem and multi-omics for survival prediction in CRC patients.

BACKGROUND: Colorectal cancer (CRC) remains a leading cause of global cancer mortality, highlighting the need for precise survival prediction to guide clinical decisions. Although tissue-level multi-omics is widely utilized for survival prediction, its limited resolution cannot capture tumor heterogeneity. Single-cell RNA sequencing (scRNA-seq) enables dissection of the tumor microenvironment (TME) at cellular resolution, supporting personalized prognostic assessment. METHODS: We collected 213 CRC scRNA-seq samples and established a CRC-specific TME atlas comprising 339,060 cells. Using this atlas as a reference, we deconvolved bulk RNA-seq data from TCGA-CRC cohort with the EcoTyper algorithm to reconstruct TME features. Clinical, genomic, and transcriptomic data were obtained from the Xena platform; microbial data were sourced from the BIC database. We integrated TME and multi-omics features through a self-normalizing neural network to construct a deep learning model (single-cell resolution TME ecosystem with multi-omics data [SCMO]) for survival prediction. To enhance interpretability, we utilized the Integrated Gradients algorithm and spatial transcriptomic data to analyze multi-omics and TME features. We performed anticancer drug screening with tumor necrosis factor receptor-associated protein 1 (TRAP1), a critical feature according to the Integrated Gradients algorithm, as a potential target. RESULTS: We identified 13 survival-related TME features from the CRC-specific atlas: 12 cell states and one multi-cellular ecosystem. SCMO, which combined TME and multi-omics features, improved survival prediction and outperformed existing methods, achieving a concordance index of 0.762. The SCMO demonstrated robust performance for long-term predictions, achieving areas under the curve (AUCs) of 0.752, 0.772, and 0.869 for 1-, 3-, and 5-year predictions in the training set, with corresponding test set AUCs of 0.639, 0.756, and 0.772. TME features from the SCMO model revealed that ecosystem density increased with CRC malignancy. Multi-omics features included TRAP1 as a potential drug target. Drug screening identified saikosaponin A as a novel TRAP1 inhibitor, and its anticancer activity was validated in vitro. We developed SCMO-Lite, a simplified model incorporating 12 high-attribution-weight multi-omics features, which demonstrated robust risk stratification. CONCLUSIONS: SCMO combines analytical precision with biological interpretability, offering novel insights for oncology survival prediction.

Humans↗

PubMed2026

Sedimentary Ancient DNA Tracks Multi-Kingdom Ecosystem Reorganizations Following Sequential Human Land Use at Crawford Lake.

Crawford Lake has an exceptional stratigraphic record that began recording biannual (varved) sedimentation in the lake basin ~750 years ago, preserving evidence of shifting cultural zones and agricultural practices, from Late Woodland Period Indigenous agriculturalists to the impacts of industrialization during the late 19th century. It was selected as the candidate site for the proposed 'Anthropocene' epoch in 2023-a proposal ultimately rejected in 2024-but the lake's significance extends beyond a formal stratigraphic boundary. Its sediments preserve a long record of human-ecosystem entanglement that captures the cumulative, reverberating nature of local human impacts and global change. While many proxies have been studied at the site, the lake's sedimentary ancient DNA (sedaDNA) record has yet to be investigated. Here, we report on sedaDNA preserved at Crawford Lake over the last ~1300 years. Sedentism and agriculture clearly impacted the entire lake ecosystem, with corresponding shifts observable in the sedaDNA of plants, animals, algae, fungi and bacteria. Canada goose (Branta canadensis) roosting on the lake-likely drawn by foraging opportunities in fields cleared for Three/Four Sisters agriculture and sedentism-contributed to repeated eutrophications and algal blooms that permanently shifted the lake's ecological structure. Subsequent impacts during the Euro-Canadian zone furthered anthropogenic succession, although local impacts have been minimal since closure of the sawmill in 1900 ce, allowing for sensitivity to global change. Beyond the molecular ecological history of the lake, we also evaluate the effectiveness of an Arctic/Subarctic bait-set for palaeoecological reconstructions of the Eastern Woodlands, and the preservation of lake sedaDNA.

Lakes↗

PubMed2026

Beyond antibiotics: artificial intelligence-enabled anti-infective ecosystems for next-generation precision therapeutics against antimicrobial resistance.

The rapid global expansion of antimicrobial resistance (AMR) threatens to undermine decades of progress in infectious disease management and highlights the limitations of conventional antibiotic-centered therapeutic strategies. Although emerging technologies-including antimicrobial peptides, bacteriophage therapy, CRISPR-based antimicrobials, microbiome therapeutics, anti-virulence approaches, nanotechnology-enabled drug delivery, and artificial intelligence (AI)-have individually demonstrated considerable promise, they are predominantly being developed as independent interventions rather than as coordinated components of an integrated therapeutic strategy. This Perspective proposes the Intelligent Anti-Infective Ecosystem (IAIE) as a conceptual systems-level framework that computationally integrates multimodal diagnostics, pathogen genomics, microbiome profiling, AI-assisted decision support, programmable precision therapeutics, ecological monitoring, and longitudinal clinical feedback within a continuously learning dynamically optimized workflow. Unlike existing paradigms that primarily optimize individual technologies or therapeutic decisions, IAIE emphasizes closed-loop coordination among complementary antimicrobial approaches to support precision-guided infection management while preserving microbiome integrity and mitigating resistance selection pressure. We further outline the core components, operational principles, translational challenges, and technology readiness of the major therapeutic platforms that could contribute to such an ecosystem, while distinguishing clinically established interventions from emerging experimental strategies. Importantly, IAIE should be interpreted as a prospective conceptual architecture rather than an existing clinical platform. Its proposed clinical value remains to be established through sequential computational, preclinical, and prospective clinical investigations using standardized microbiological, ecological, and patient-centered outcome measures. By framing antimicrobial innovation within an responsive systems perspective, IAIE provides a roadmap for future multidisciplinary research aimed at integrating artificial intelligence and systems microbiology to enable sustainable management of antimicrobial resistance.

Humans↗

PubMed2026

Global Patterns of Net Ecosystem Exchange in peatlands: A Systematic Review and Meta-analysis of Drivers Across Land Use and Environmental Gradients.

Peatlands play an essential role in the global carbon cycle, storing approximately one-third of the world's soil carbon despite covering less than 3% of the land surface. Peatland degradation from anthropogenic activities and climate change can convert peatlands from net carbon sinks to sources by altering carbon cycling. Net Ecosystem Exchange (NEE), the balance between CO2 uptake and emission, is a critical indicator for assessing peatland condition and restoration efforts. We conducted a systematic quantitative literature review to investigate global patterns of NEE in peatlands and identify key environmental and anthropogenic drivers of CO2 flux variability. Annual NEE values from 120 globally distributed sites reported in peer-reviewed literature were analyzed in relation to climatic zone, land use, vegetation type, peatland condition, and water table depth. Our synthesis revealed significant geographic gaps, with peatland NEE studies substantially underrepresented in the Tropics, Africa, and Oceania. Agricultural peatlands emitted significantly more CO2 than sites under natural land uses or peat extraction, while degraded peatlands were significantly greater net CO2 sources than intact and restored systems. Restored peatlands remained net CO2 sources on average, emphasizing the importance of long-term monitoring and adaptive management following restoration interventions. Water table depth significantly affected NEE variability, with CO2 emissions increasing approximately 7.2 gCO2-C m-2yr-1 for every centimeter of water table drawdown. A substantial variability in measurement methods, data processing software, and protocols highlighted the critical need for methodological standardization. Our findings provide evidence-based targets for peatland conservation and restoration monitoring as nature-based climate solutions.

Ecosystem↗

PubMed2025

The role of mobile genetic elements in adaptation of the microbiota to the dynamic human gut ecosystem.

The human intestinal microbiota is a dynamic ecosystem shaped by extensive horizontal gene transfer, particularly in individuals from industrialized populations. In this review, we discuss recent advances in our understanding of how mobile genetic elements (MGEs) contribute to microbial ecology and evolution in this diverse community, focusing on MGEs carrying fitness-conferring genes. Bacteroidales species can colonize individuals for decades and serve as major hubs for MGE exchange. Most MGEs are highly variable across individuals and geographies. Occasionally, conserved MGEs can spread across geography and lifestyles. Functional characterizations of MGEs reveal their roles in antibiotic resistance, interbacterial antagonism, biofilm formation, immune evasion, and nutrient acquisition, among others. Substantive progress in our understanding of MGEs in the gut microbiome offers promising avenues for therapeutic microbiome interventions. However, major challenges remain in functional prediction, host-MGE linkage, and experimental characterization.

Humans↗

PubMed2025

Exploring genetic adaptation and microbial dynamics in engineered anaerobic ecosystems via strain-level metagenomics.

Genetic heterogeneity exists within all microbial populations, with sympatric cells of the same species often exhibiting single-nucleotide variations that influence phenotypic traits, including metabolic efficiency. However, the evolutionary dynamics of these strain-level differences in response to environmental stress remain poorly understood. Here, we present a first-of-its-kind study tracking the adaptive evolution of an anaerobic, carbon-fixing microbiota under a controlled engineered ecosystem focused on carbon dioxide bioconversion into methane. Leveraging strain-resolved metagenomics with an ad hoc variant calling and phasing approach, we mapped mutation trajectories and observed that the two dominant Methanothermobacter species maintained distinct sweeping haplotypes over time, most likely due to niche-specific metabolic roles. By combining population genetic statistics and peptide reconstruction, mer and mcrB genes emerged as potential drivers of archaeal strain-level competition. These findings pave the way for targeted engineering of microbial communities to enhance bioconversion efficiency, with significant implications for sustainable energy and carbon management in anaerobic systems.

Metagenomics↗

PubMed2025

Giotto Suite: a multiscale and technology-agnostic spatial multiomics analysis ecosystem.

Emerging spatial multiomics technologies provide an increasingly large amount of information content at multiple scales. However, it remains challenging to efficiently represent and harmonize diverse spatial datasets. Here we present Giotto Suite, a suite of modular packages that provides scalable and extensible end-to-end solutions for multiscale and multiomic data analysis, integration and visualization. At its core, Giotto Suite is centered around an innovative data framework, allowing the representation and integration of spatial omics data in a technology-agnostic manner. Giotto Suite integrates molecular, morphology, spatial and annotated feature information to create a responsive and flexible workflow, as demonstrated by applications to several state-of-the-art spatial technologies. Furthermore, Giotto Suite builds upon interoperable interfaces and data structures that bridge the established fields of genomics and spatial data science in R, thereby enabling independent developers to create custom-engineered pipelines. As such, Giotto Suite creates an immersive and multiscale ecosystem for spatial multiomic data analysis.

Genomics↗

PubMed2026

Motile and non-motile Listeria species adopt distinct ecological and evolutionary strategies to achieve broad geographic ranges across soil ecosystems.

Broad geographic ranges often reflect ecological versatility and are associated with lower extinction risk. Motility is a key physiological and ecological trait in bacteria. However, how some motile and non-motile bacteria achieve broad geographic ranges remains poorly understood. Here, we analyzed the genomes of 141 Listeria welshimeri and 90 Listeria booriae isolates systematically obtained from soils, representing widespread motile and non-motile species, respectively. We show that L. welshimeri lacks clear phylogeographic structure, suggesting minimal geographic barriers to dispersal. Its wide distribution is likely associated with enhanced motility and effective host colonization that facilitate wildlife-driven dispersal, particularly by regional-terrestrial birds. This pattern is supported by positive selection on flagellar and chemotaxis genes, strong associations with wildlife movement patterns, and close genomic relatedness between soil and wild bird isolates. In contrast, L. booriae displays clade endemism and a strong distance-decay relationship, suggesting dispersal limitation. Despite lacking a dispersal advantage, L. booriae's wide distribution appears to be linked to genomic flexibility and metabolic versatility that support adaptation to diverse environmental conditions, especially those shaped by iron concentration and precipitation. This is evidenced by its large, open pangenome characterized by abundant and diverse metabolic pathways and broad substrates utilization capacity; pronounced positive selection on genes involved in inorganic ion, amino acid, and coenzyme transport and metabolism; and strong associations between gene richness and abiotic factors as well as bacterial community composition. These findings suggest distinct genomic foundations and ecological and evolutionary mechanisms underlying the success of motile and non-motile cosmopolitan bacteria in soil ecosystems.

Soil Microbiology↗

PubMed2026

Institutional data commons: a federated Data Use Certification-aware architecture for secure and scalable data use in biomedical data ecosystems.

BACKGROUND: Modern biomedical data ecosystems increasingly rely on global cloud platforms to coordinate access to large-scale genomic and clinical datasets. However, operational governance remains largely investigator-centric, shifting the responsibility for complex security, compliance, and infrastructure management to individual laboratories. As data volumes and regulatory requirements expand, this approach fails to scale across the research enterprise. This disjointed approach creates a substantial governance burden and can slow down scientific progress. In centralized cloud environments, investigators face siloed identity management and high costs, leading to inefficient data use and increased risk when integrating local and global datasets. MATERIALS AND METHODS: We examine limitations in the current infrastructure and propose reframing institutional data commons as governance-aware intermediaries to ensure secure, efficient and sustainable use of controlled-access biomedical data. RESULTS: This federated architecture decouples storage from authorization, enabling dynamic access linked to active certifications, whether data are analyzed in situ on global platforms or in local governance-aware institutional access environments. DISCUSSION: Shifting governance from investigators to institutional infrastructure ensures that biomedical research remains both secure and economically sustainable.

biomedical data ecosystems↗

PubMed2024

Spatiotemporal and genomic analysis of carbapenem resistance elements in Enterobacterales from hospital inpatients and natural water ecosystems of an Irish city.

Carbapenemase-producing Enterobacterales (CPE) is a diverse group of often multidrug-resistant organisms. Surveillance and control of infections are complicated due to the inter-species spread of carbapenemase-encoding genes (CEGs) on mobile genetic elements (MGEs), including plasmids and transposons. Due to wastewater discharges, urban water ecosystems represent a known reservoir of CPE. However, the dynamics of carbapenemase-bearing MGE dissemination between Enterobacterales in humans and environmental waters are poorly understood. We carried out whole-genome sequencing, combining short- and long-sequencing reads to enable complete characterization of CPE isolated from patients, wastewaters, and natural waters between 2018 and 2020 in Galway, Ireland. Isolates were selected based on their carriage of Class A blaKPC-2 (n = 6), Class B blaNDM-5 (n = 12), and Class D blaOXA-48 (n = 21) CEGs. CEGs were plasmid-borne in all but two isolates. OXA-48 dissemination was associated with a 64 kb IncL plasmid (62%), in a broad range of Enterobacterales isolates from both niches. Conversely, blaKPC-2 and blaNDM-5 genes were usually carried on larger and more variable multireplicon IncF plasmids in Klebsiella pneumoniae and Escherichia coli, respectively. In every isolate, each CEG was surrounded by a gene-specific common genetic environment which constituted part, or all, of a transposable element that was present in both plasmids and the bacterial chromosome. Transposons Tn1999 and Tn4401 were associated with blaOXA-48 and blaKPC-2, respectively, while blaNDM-5 was associated with variable IS26 bound composite transposons, usually containing a class 1 integron.IMPORTANCESince 2018, the Irish National Carbapenemase-Producing Enterobacterales (CPE) Reference Laboratory Service at University Hospital Galway has performed whole-genome sequencing on suspected and confirmed CPE from clinical specimens as well as patient and environmental screening isolates. Understanding the dynamics of CPE and carbapenemase-encoding gene encoding mobile genetic element (MGE) flux between human and environmental reservoirs is important for One Health surveillance of these priority organisms. We employed hybrid assembly approaches for improved resolution of CPE genomic surveillance, typing, and plasmid characterization. We analyzed a diverse collection of human (n = 17) and environmental isolates (n = 22) and found common MGE across multiple species and in different ecological niches. The conjugation ability and frequency of a subset of these plasmids were demonstrated to be affected by the presence or absence of necessary conjugation genes and by plasmid size. We characterize several MGE at play in the local dissemination of carbapenemase genes. This may facilitate their future detection in the clinical laboratory.

Humans↗

PubMed2026

Metabolic niche differentiation and napA evolution stabilize partial denitrification in wastewater ecosystems.

Although partial denitrification (PD) is increasingly applied as a nitrite-supplying strategy for anammox-based nitrogen removal, the ecological distribution, metabolic specialization, and genomic determinants of stable nitrite accumulation remain poorly understood at the ecosystem scale. Here, we reconstructed 516 high-quality metagenome-assembled genomes (MAGs) using high-depth metagenomic sequencing of 107 wastewater treatment plants and classified denitrifiers according to their nitrite production or consumption capacities. Of these genomes, 23% (120 MAGs) were classified as partial denitrifiers, 41% (211 MAGs) as complete denitrifiers, and 36% (185 MAGs) as nitrite-reducing denitrifiers, revealing pronounced functional partitioning rather than dominance by complete denitrification pathways. Comparative genomics showed that partial denitrifiers possess metabolic architectures favoring rapid carbon oxidation and NADH generation while exhibiting constrained NADPH production and biosynthetic investment, thereby promoting nitrate-to-nitrite conversion but limiting subsequent nitrite reduction. Nitrite accumulation does not result from incomplete denitrification pathways but from metabolic niche differentiation. These metabolic trade-offs were further associated with the evolutionary divergence of the periplasmic nitrate reductase gene, napA, which displayed distinct sequence characteristics and genomic contexts between partial and complete denitrifiers. Integration of carbohydrate-active enzyme repertoires further revealed metabolic complementarity between partial denitrifiers and anammox bacteria, supporting efficient carbon handoff without direct substrate competition. From an engineering perspective, operating conditions that impose moderate electron limitation, such as low or fluctuating C/N ratios and intermittent carbon feeding, may selectively enrich partial denitrifiers and enhance a stable nitrite supply for PD-anammox systems. Together, these findings identify PD as a predictable ecological state shaped by genome-encoded metabolic specialization and provide a mechanistic basis for designing robust, low-carbon nitrogen-removal processes.

Anammox↗

PubMed2026

Global microbial DNA signatures of temperature and nutrient limitation across ecosystems.

Microbial genomes continuously adapt to environmental conditions, but identifying universal signatures of adaptation remains challenging. Here we show that environmental temperature can be accurately predicted across ecosystems from DNA composition alone (R2 = 0.75), using tetranucleotide frequencies from 1,235 marine and soil metagenomes and a machine learning approach. This predictive signal was also apparent within individual taxa, consistent with a fundamental temperature-associated signature. By contrast, GC content exhibited opposite correlations with temperature in soil (positive) and marine (negative) environments. This phenomenon was probably driven by differences in nutrient availability, as GC content increases with nutrients while nutrients decrease with temperature in marine samples. By integrating these observations, we identified specific tetranucleotides, with 50% GC, that displayed consistent and robust temperature correlations across environments and may have contributed to the stability of predictions. This work highlights metagenome-wide DNA-temperature associations, relevant for understanding microbial community responses to global changes.

Journal Article↗

PubMed2026

Longitudinal development of infant oral ecosystem: salivary metabolomic, bacteriome, and virome dynamics in early infancy.

This prospective cohort study investigated the longitudinal development of the salivary bacteriome, virome, and metabolome during early infancy. We assessed the associations between oral bacteria, viruses, and metabolites from 10 mother-infant dyads, with oral samples collected at 1 and 2 years of age. Forty saliva and plaque samples underwent untargeted metabolomic analysis, and infant saliva samples underwent metagenomic sequencing. Maternal salivary and plaque metabolomic profiles remained largely stable, whereas infant profiles were clearly separated from maternal profiles and changed with age. Notably, infant dental plaque metabolism underwent more substantial changes from year 1 to year 2 than saliva, with age-dependent metabolite shifts mainly involving energy, amino acid, nucleotide, and lipid metabolic pathways. Our findings also revealed significant developmental shifts in salivary bacteriome, virome, and functional pathway profiles during early childhood. The most abundant oral bacteria in early life, comprising over 75% of total abundance, included Veillonella, Streptococcus, Rothia, Prevotella, Neisseria, and Actinomyces species. While human viruses like Roseolovirus were detected, bacteriophages constituted the majority of the virome. Comparing infants at year 1 and year 2, we identified differentially abundant bacteria, viruses, metabolic functional pathways, and specific metabolites. We observed associations between bacteria and viruses, noting that these cross-kingdom relationships attenuated as infants grew. The study results underscore the complex and dynamic development of the oral microbiome, virome, and metabolome during early childhood.IMPORTANCEThe human oral cavity undergoes substantial microbial and metabolic development during early childhood, yet the temporal changes in the infant oral ecosystem remain incompletely understood. In this study, we longitudinally profiled the salivary metabolome, bacteriome, and virome of infants at 1 and 2 years of age. We demonstrated that the infant oral metabolome undergoes substantial developmental shifts, particularly in pathways related to energy, amino acid, and lipid metabolism; whereas maternal metabolic profiles remained stable over the same period. Furthermore, our results revealed the dynamic assembly of infant salivary virome and bacteriome and their associations with the functional pathways and metabolites. These findings provide new insights into the complex and dynamic development of the oral microbiome, virome, and metabolome in early infancy.

bacteriome↗