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The Multiple Roles of Genetics on Freshwater Macrophyte Functional Traits in the Interplay With the Environment: A Review.

The study of functional trait variation is increasingly used to understand macrophyte adaptation, as traits reflect organismal performance under different ecosystem conditions. Phenotypic expression results from the interplay of genetic and environmental factors: genetics provides the molecular basis for heritable traits and constrains potential phenotypes, while the environment acts as a selective and modulatory force. However, the genetic insight into traits has rarely been addressed in freshwater macrophyte studies. This review examines the different ways in which the DNA of macrophytes interplays with the environment and contributes to the variation in their functional traits, outlining main approaches, gaps, and future challenges. Only 21 studies explicitly combined genetics with functional traits and environment in the last fifteen years. The most common approach was the use of common garden experiments to explore acclimation and adaptation in a few model species. Current studies mainly focus on morphological and growth traits that best describe macrophytes' economic strategies, with limited attention to other trait categories, while the genetic and DNA traits studied are more variable. Across studies, environmental factors generally explained a larger proportion of functional trait variation, highlighting the dominant role of phenotypic plasticity for macrophyte acclimatation, whereas genetic contribution increased under experimentally manipulated conditions. Genome size and epigenetic variation influenced phenotypic plasticity; however, the effect was different and inconsistent on traits and depended on phylogenetic relationships and geographical environment variation. In field studies of natural populations, life history traits and hydrology had a strong effect on the geographic distribution of genetic diversity and the response to selection, as well as on our ability to distinguish selection from genetic drift. Future research should enhance molecular analyses, adopt multifactorial and long-term experimental designs, develop conceptual frameworks to address the relationships between genomics, environment and functional traits and integrate emerging tools to capture macrophyte adaptation better.

adaptation

Revealing Functional Traits of Insect Pest Suppressive Rhizobacterial Strains Through Comparative Genomics.

Root inoculation with rhizobacteria is an emerging strategy to enhance plant resistance to aphid herbivory, yet the microbial functional traits underpinning these responses remain poorly characterised. Here, we present a comparative genomic analysis of five rhizobacteria (Acidovorax radicis N35, Bacillus subtilis B171, Bacillus velezensis FZB42, Rhizobium radiobacter F4 and Pseudomonas simiae WCS417r) that suppress aphids when inoculated onto barley. As expected, functional variation largely reflected phylogenetic relatedness; however, candidate traits implicated in modulation of plant immune defences were conserved across all strains, including biosynthesis of 2,3-butanediol, riboflavin and salicylic acid. Additional shared functions, linked to plant defence signalling, included phytoene and squalene biosynthesis (absent in P. simiae) and N-acyl homoserine lactone quorum sensing (absent in Bacillus spp.). Strain-specific traits were also identified, including surfactin production in Bacillus spp. and hydrogen cyanide biosynthesis in A. radicis and P. simiae. Comparison with a broader collection of rhizobacteria revealed that many putative plant-beneficial functions identified were widely conserved, including among closely related phytopathogens. This extensive functional overlap suggests aphid suppression cannot be explained solely by presence or absence of broad functional traits, but rather by specific trait combinations, regulatory differences, or context-dependent expression. This highlights the need for genome-informed approaches for bioinoculant discovery.

Animals

Enrichment of root-associated Streptomyces strains in response to drought is driven by diverse functional traits and does not predict beneficial effects on plant growth.

The genus Streptomyces has consistently been found enriched in drought-stressed plant root microbiomes, yet the ecological basis and functional variation underlying this enrichment at the strain and isolate level remain unclear. Using two 16S rRNA sequencing methods with different levels of taxonomic resolution, we confirmed drought-associated enrichment (DE) of Streptomyces in field-grown sorghum roots and identified five closely related but distinct amplicon sequence variants (ASVs) belonging to the genus with variable drought enrichment patterns. From a culture collection of sorghum root endophytes, we selected 12 Streptomyces isolates representing these ASVs for phenotypic and genomic characterization. Whole-genome sequencing revealed substantial variation in gene content, even among closely related isolates, and exometabolomic profiling showed distinct metabolic responses to media supplemented with drought- versus well-watered root tissue. Traits linked to drought survival, including osmotic stress tolerance, siderophore production, and carbon utilization, varied widely among isolates and were not phylogenetically conserved. Using a broader panel of 48 Streptomyces, we demonstrate that DE scores, determined through mono-association experiments in gnotobiotic sorghum systems, showed high variability and lacked correlation with plant growth promotion. Pangenome-wide association identified orthogroups involved in osmolyte transport (e.g., proP) and membrane biosynthesis (e.g., fabG) as positively associated with DE, though most associations lacked phylogenetic signal. Collectively, these results demonstrate that Streptomyces DE is not a conserved genus-level trait but is instead strain-specific and functionally heterogeneous. Furthermore, DE in the root microbiome was shown not to predict beneficial effects on plant growth. This work underscores the need to resolve functional traits at the strain level and highlights the complexity of microbe-host-environment interactions under abiotic stress.

Streptomyces

Multi-omics reveal microbial functional traits and antifungal metabolites associated with lower Pseudogymnoascus destructans loads in bat cave soils.

White-nose syndrome, caused by Pseudogymnoascus destructans (Pd), is a major fungal disease threatening hibernating bats. Cave soils can serve as environmental reservoirs for Pd, yet the microbial and biochemical mechanisms underlying naturally low Pd burdens in some cave environments remain poorly understood. Here, we integrated soil microbiome profiling, metagenomics, metabolomics, multi-omics network analysis, and in vitro validation to investigate the ecological and functional basis of differential Pd loads in hibernating bat caves in Northeast China. The three caves shared cold, humid, and weakly acidic microenvironments, but differed significantly in electrical conductivity, soil water content, nutrient availability, and extracellular enzyme activities. Soil microbial communities showed significant inter-cave variation in composition, diversity, and niche breadth, with stochastic processes contributing substantially to community assembly. Environmental variables, particularly pH and Pd load, were important predictors of microbial community structure. Functional analyses revealed that the low-Pd Gezi Cave was enriched in genes associated with organic carbon degradation, nitrogen input and retention, and secondary metabolism. Metabolomic profiling further identified cave-specific metabolite signatures, among which Biochanin A, 4-Hydroxybenzaldehyde, Vanillin, and Arachidonic acid were negatively correlated with Pd loads. Integrated pathway and network analyses showed that differential genes and metabolites jointly mapped to secondary metabolite biosynthesis, aminobenzoate degradation, and flavonoid degradation pathways, forming a microbe-metabolite-functional gene coupling network involving key taxa such as Rhodococcus, Pseudorhodoplanes, and Rhodoplanes. In vitro assays confirmed that 4-Hydroxybenzaldehyde, Coumarin, and Vanillin inhibited Pd growth. Structural equation modelling further indicated that environmental heterogeneity was associated with variation in Pd loads through microbial functional attributes and metabolite profiles. These findings suggest that naturally low-Pd cave soils are associated with coordinated environmental filtering, microbial functional specialization, and antifungal metabolite production, providing mechanistic insight into microbial and biochemical constraints on Pd persistence in cave reservoirs.

Animals

Phylogenetic Constraints and Environmental Filtering Jointly Drive Adaptive Evolution in Phragmites australis: From Genetic Structure to Trait Decoupling on the Mongolian Plateau.

The Mongolian Plateau, a typical arid and semi-arid zone in Eurasia, is characterized by highly heterogeneous and fragmented wetland habitats. Phragmites australis, a common wetland species in this region, exhibits remarkable adaptability. Unraveling the coordination between phylogenetic history and local environmental filtering is crucial for elucidating its adaptive mechanisms. Integrating landscape genomics and trait-based phylogenetic analyses, we analyzed transcriptome-wide SNPs, multidimensional functional traits, and environmental variables across 90 individuals from 30 natural P. australis populations. This study aims to reveal the genetic and phenotypic variation patterns underlying population genetic structure and trait variation, specifically distinguishing the roles of geographic isolation, environmental filtering, and phylogenetic history. Results reveal a significant drainage-dependent pattern in genetic structure. Populations in hydrologically connected basins show extensive admixture, whereas those in isolated endorheic basins form distinct lineages. While geographic isolation underpins genetic differentiation, environmental filtering independently explains ~33.84% of the genetic variation, driven primarily by moisture heterogeneity (precipitation seasonality and soil moisture). Crucially, we observed differentiated evolutionary trajectories across functional traits. Structural traits (e.g., plant height, leaf thickness) are phylogenetically conserved; in contrast, physiological traits (e.g., water use efficiency) are decoupled from phylogeny, showing patterns consistent with high plasticity regulated by local environments. This evolutionary decoupling strategy enables P. australis to flexibly adapt to heterogeneous habitats while maintaining structural stability. This study uncovers the synergistic mechanisms by which geographic isolation and environmental filtering jointly shape the genetic patterns of this cosmopolitan species at a regional scale, clarifies that its evolutionary responses may depend heavily on the differentiated plasticity of trait types, and provides valuable regional insights into how widespread wetland species adapt to heterogeneous environments under global change.

Mongolia Plateau

Genome-wide association studies of plant traits and functional analysis of leaf development-related genes in citrus.

Labor-saving and high-light-efficiency tree architecture is a key breeding objective for woody fruit trees like citrus. However, population genetics information on these traits remains limited. In this study, tree architecture, thorn, and leaf traits were evaluated in 353 F2 progeny derived from a cross between Clementine mandarin and precocious trifoliate orange-an early-flowering variety. A random subset of 300 offspring was sequenced for a genome-wide association study (GWAS), which detected 10 216 significantly associated SNPs and defined several major quantitative trait loci (QTLs) for the target traits. Subsequent bulked segregant analysis (BSA) and GWAS on individuals with extreme compound leaf phenotypes mapped the causal gene(s) to a 0.8 Mb region (22.15-22.95 Mb) on chromosome 4. Genetic analysis across multiple hybrid combinations confirmed that the compound leaf trait in trifoliate orange is dominantly inherited and follows Mendelian segregation. Transcriptome profiling of parental leaves at different developmental stages identified a KNOX gene, CiKNAT6, as a candidate. Further validation using CAPS markers and Hi-Tom sequencing demonstrated tight linkage between an InDel polymorphism in CiKNAT6 and leaf shape across diverse citrus species and the F2 population, with co-segregation observed for the compound leaf trait. Due to alternative splicing producing seven splice variants, the CiKNAT6 DNA sequence was selected for genetic transformation experiments. Functional analysis revealed that the Clementine mandarin allele of CiKNAT6 is non-functional owing to an InDel, whereas ectopic expression of the trifoliate orange allele in tobacco and lemon induced leaf curling and reduced leaf size. CRISPR-Cas9 knockout of CiKNAT6 in trifoliate orange resulted in increased leaf area. These findings provide valuable genetic resources and insights for future studies on tree architecture and leaf morphology.

Plant Leaves

Genome-Resolved Metagenomics Revealed the Functional Potential of Core Novel and Known Genera Key to Processes in Full-Scale Aerobic Granular Sludge Plants.

Microbial communities are critical for nutrient removal in aerobic granular sludge (AGS) wastewater treatment plants (WWTPs). Despite the stable long-term operation of full-scale AGS WWTPs, the microbial populations and functional traits sustaining stable long-term performance remain poorly resolved. To address this gap, the recovered MAG catalog from nine full-scale AGS WWTPs across five countries was analyzed. From this catalog, 74 high-quality core MAGs were identified and used for downstream taxonomic characterization and functional analyses. These high-quality core MAGs spanned 48 established and 7 novel genera, representing 31 known and 43 novel species. Functional analysis linked core MAGs to key WWTP processes: polyphosphate accumulation (9), glycogen accumulation (12), denitrification (62), and nitrification (1). These included four novel MAGs with glycogen-accumulating (3) and polyphosphate-accumulating (1) potential and 11 capable of nitrous oxide reduction, critical for mitigating greenhouse gas emissions. Ca. Phosphoribacter was the most abundant genus, highlighting its underestimated role caused by misclassification as Tetrasphaera in 16S rRNA surveys. Specifically, Ca. P. hodrii was the dominant species, exhibiting enhanced sugar uptake and amino acid synthesis as likely drivers of its enrichment in the AGS WWTPs. Overall, this study resolves for the first time the taxa and functional traits consistently enriched in full-scale AGS systems, enabling a shift from an empirical performance assessment toward biologically informed process interpretation.

Sewage

SLB-msSIM: A Spectral Library-Based Multiplex Segmented SIM Platform for Single-Cell Proteomic Analysis.

Mass spectrometry (MS)-based single-cell proteomics, while highly challenging, offers unique potential for a wide range of applications to interrogate cellular heterogeneity, trajectories, and phenotypes at a functional level. We report here the development of the spectral library-based multiplex segmented selected ion monitoring (SLB-msSIM) method, a conceptually unique approach with significantly enhanced sensitivity and robustness for single-cell analysis. The single-cell MS data is acquired by a multiplex segmented selected ion monitoring (msSIM) technique, which sequentially applies multiple isolation cycles with the quadrupole using a wide isolation window in each cycle to accumulate and store precursor ions in the C-trap for a single scan in the Orbitrap. Proteomic identification is achieved through spectral matching using a well-defined spectral library. We applied the SLB-msSIM method to interrogate cellular heterogeneity in various pancreatic cancer cell lines, revealing common and distinct functional traits among PANC-1, MIA-PaCa2, AsPc-1, HPAF, and normal HPDE cells. Furthermore, for the first time, our novel data revealed the diverse cell trajectories of individual PANC-1 cells during the induction and reversal of epithelial-mesenchymal transition (EMT). Collectively, our results demonstrate that SLB-msSIM is a highly sensitive and robust platform, applicable to a wide range of instruments for single-cell proteomic studies. SUMMARY: We present the SLB-msSIM method, a conceptually unique approach in mass spectrometry-based single-cell proteomics that significantly enhances sensitivity and robustness. This innovative platform enables detailed analysis of the proteome landscape, capturing cellular heterogeneity, trajectories, and phenotypes at a single-cell resolution. Utilizing the SLB-msSIM technique, we identified both common and distinct functional traits among various pancreatic cancer cell lines and normal cells. Moreover, our study unveiled new insights into the diverse cell trajectories of individual cancer cells during the induction and reversal of epithelial-mesenchymal transition (EMT). In summary, the SLB-msSIM method offers a highly sensitive and robust platform for single-cell proteomic studies, with broad applicability across different instruments.

Single-Cell Analysis

Ecological Filtering by Tuber Compartments Shapes Stable Core Microbiomes That Underpin Potato Plant Growth Across Environments.

Harnessing plant microbiomes for sustainable agriculture requires understanding not only whether they can boost crop performance, but also how ecological processes govern their assembly, stability, and functional contributions across environments. While we previously showed that seed tuber microbiomes can predict potato vigour using machine learning, it remained unclear how ecological processes shape tuber microbiome stability and functionality across host genotypes, tuber compartments, soil types, and years. Here, we analyzed the national-scale dataset of 240 field-collected potato seedlots, spanning six genotypes, two soil types, and two growing years, with a focus on the spatially distinct heel and eye compartments of the potato tuber. By profiling over 1200 bacterial and fungal communities and linking microbiome composition to plant performance, we show that plant genotype and tuber compartment are the strongest determinants of microbial diversity and composition. Compartment-specific enrichment of functional traits revealed spatial partitioning of microbial functions, with organic compound conversion and nitrogen cycling dominant in the heel, and energy metabolism enriched in the eye. Applying a macroecological abundance-occupancy framework, we identified a stable core microbiome of bacterial and fungal taxa that persisted across all environments and years. These core members were more strongly associated with plant growth-related traits than non-core taxa, and core taxa in different tuber compartments showed distinct correlations with taxa of potential pathogenic relevance. Together, our findings demonstrate that tuber compartments act as ecological filters that structure persistent, functionally specialised microbiomes linked to plant growth-related traits across environments. By providing an ecological and functional framework for compartment-resolved, stable core microbiomes, this study advances mechanistic understanding of plant-microbe interactions and identifies stable microbial partners as promising targets for improving potato resilience and productivity.

Journal Article

Heterogeneous trait responses of Páramo plant species and community to experimental warming.

Understanding the impact of climate change on the functional trait composition (and hence ecosystem functioning) of tropical alpine regions is critical for predicting biodiversity responses. We tested the effects of a decade of warming on the morphological, chemical and genomic traits of Páramo species using open-top chambers (OTCs). We conducted vegetation surveys and collected samples from individuals inside and outside the OTC plots to estimate differences between treatments (warming versus control). Vegetation cover decreased over time in both treatments suggesting a potential decline in soil moisture in our study area. Warming led to a reorganization of the trait space and trait network structure. Species showed a wide range of responses to warming, with significant changes across different trait combinations. Nevertheless, we did not find significant differences in trait values or the direction of change between species whose percentage vegetation cover increased in OTC (or decreased less) over time, compared with control. Community-weighted mean values of plant height, leaf area, leaf dry matter content, genome size, leaf C and P, significantly increased over time only in OTC plots (i.e. traits associated with carbon storage and decomposition). While warming and reduced soil moisture lead to heterogeneous species responses without a clear winning trait strategy, changes at the community level may have important implications for Páramo ecosystem functioning.

Climate Change

Decoding microbial metabolic complementarity from individual traits to community structuring.

A fundamental challenge in microbiome research lies in elucidating the functional capacity of microbial communities through community membership and genomic data. As community structuring and emergent functional traits are determined by bacterial community metabolic networks, it is important to gain insights into the principles that govern bacteria-bacteria interactions. Here, we applied an integrative framework linking individual strain-level traits to community structuring in a simplified synthetic bacterial community (SSC8) that promotes the growth of ungrafted watermelon. By combining mono- and coculture assays with genome-scale metabolic modeling and metabolomic profiling of spent media, we characterized directional interactions and resource dependencies among community members. Our findings show that positive interactions dominated the community network, accounting for 55% of all pairwise combinations, indicating a high prevalence of growth-promoting effects among strains. Genome-scale metabolic modeling showed that functional divergence among strains enhanced the potential for metabolic complementarity as phylogenetic distance increased. Integrating metabolic modeling with metabolomics further suggested that Pseudomonas azotifigens Q6 not only benefited from all other community members, but also exhibited mutualistic interactions with the other three strains, with metabolite exchange involving compounds such as L-lysine and L-cysteine. Pseudomonas azotifigens Q6 acted as an important driver of community composition by affecting the abundance of several other consortium members in vitro. These findings highlight the role of metabolic complementarity in driving community structuring by promoting selective persistence of specific strains. Our work provides mechanistic insights into microbial interaction networks in vitro and offers a conceptual foundation for the rational design of functionally robust and plant-beneficial microbiomes.

Bacteria

Peptide YY (PYY) gene polymorphisms in the 3'-untranslated and proximal promoter regions regulate cellular gene expression and PYY secretion and metabolic syndrome traits in vivo.

RATIONALE: Obesity is a heritable trait that contributes to hypertension and subsequent cardiorenal disease risk; thus, the investigation of genetic variation that predisposes individuals to obesity is an important goal. Circulating peptide YY (PYY) is known for its appetite and energy expenditure-regulating properties; linkage and association studies have suggested that PYY genetic variation contributes to susceptibility for obesity, rendering PYY an attractive candidate for study of disease risk. DESIGN: To explore whether common genetic variation at the human PYY locus influences plasma PYY or metabolic traits, we systematically resequenced the gene for polymorphism discovery and then genotyped common single-nucleotide polymorphisms across the locus in an extensively phenotyped twin sample to determine associations. Finally, we experimentally validated the marker-on-trait associations using PYY 3'-untranslated region (UTR)/reporter and promoter/reporter analyses in neuroendocrine cells. RESULTS: Four common genetic variants were discovered across the locus, and three were typed in phenotyped twins. Plasma PYY was highly heritable (P < 0.0001), and genetic pleiotropy was noted between plasma PYY and body mass index (BMI) (P = 0.03). A PYY haplotype extending from the proximal promoter (A-23G, rs2070592) to the 3'-UTR (C+1134A, rs162431) predicted not only plasma PYY (P = 0.009) but also other metabolic syndrome traits. Functional studies with transfected luciferase reporters confirmed regulatory roles in altering gene expression for both 3'-UTR C+1134A (P < 0.001) and promoter A-23G (P = 0.0016). CONCLUSIONS: Functional genetic variation at the PYY locus influences multiple heritable metabolic syndrome traits, likely conferring susceptibility to obesity and subsequent cardiorenal disease.

3' Untranslated Regions

Predictions of rhizosphere microbiome dynamics with a genome-informed and trait-based energy budget model.

Soil microbiomes are highly diverse, and to improve their representation in biogeochemical models, microbial genome data can be leveraged to infer key functional traits. By integrating genome-inferred traits into a theory-based hierarchical framework, emergent behaviour arising from interactions of individual traits can be predicted. Here we combine theory-driven predictions of substrate uptake kinetics with a genome-informed trait-based dynamic energy budget model to predict emergent life-history traits and trade-offs in soil bacteria. When applied to a plant microbiome system, the model accurately predicted distinct substrate-acquisition strategies that aligned with observations, uncovering resource-dependent trade-offs between microbial growth rate and efficiency. For instance, inherently slower-growing microorganisms, favoured by organic acid exudation at later plant growth stages, exhibited enhanced carbon use efficiency (yield) without sacrificing growth rate (power). This insight has implications for retaining plant root-derived carbon in soils and highlights the power of data-driven, trait-based approaches for improving microbial representation in biogeochemical models.

Rhizosphere

Common gardens reveal genomic susceptibility and vulnerability to climate change in Eucalyptus.

Accelerated global climate change and increased species introduction across international scales have raised concerns about the potential for trees to experience maladaptation or lagging adaptation in response to these environmental shifts. However, our knowledge regarding the relationship between the genomic metrics used to predict maladaptation and actual fitness proxies in trees remains limited. Here, we present a population genomic analysis of 295 families from 28 provenances of Eucalyptus pellita, a widely cultivated fast-growing tree species, and conducted two common garden experiments. Genomic susceptibility encompassing individual heterozygosity (H), genomic inbreeding (FROH), and genomic load (inferred from deleterious mutations) exhibited distinct geographic patterns, shedding light on the origin and evolutionary history of E. pellita. The genetic basis of local adaptation was elucidated through genotype-environment associations and genome-wide association studies, including 198 loci associated with climate and 2388 loci regulating different traits. Furthermore, Australian provenances have higher genomic vulnerability under prospective climate alterations than Papua New Guinea and Indonesia provenances. By integrating phenotypic data across two common gardens, the relationship between leaf functional traits and predicted metrics of maladaptation was closer than growth attributes. Notably, pronounced natural selection signals linked to leaf morphogenesis have been identified by comparing two lineages spanning the oceans. This study underscores the immense potential of leveraging genomic susceptibility and genomic vulnerability to decipher the local (mal)adaptation of forest trees.

Eucalyptus

Environmental Stresses Constrain Soil Microbial Community Functions by Regulating Deterministic Assembly and Niche Width.

Increasing evidence indicates that the loss of soil microbial &#x3b1;-diversity triggered by environmental stress negatively impacts microbial functions; however, the effects of microbial &#x3b1;-diversity on community functions under environmental stress are poorly understood. Here, we investigated the changes in bacterial and fungal &#x3b1;- diversity along gradients of five natural stressors (temperature, precipitation, plant diversity, soil organic C and pH) across 45 grasslands in China and evaluated their connection with microbial functional traits. By quantifying the five environmental stresses into an integrated stress index, we found that the bacterial and fungal &#x3b1;-diversity declined under high environmental stress across three soil layers (0-20&#x2009;cm, 20-40&#x2009;cm and 40-60&#x2009;cm). Metagenomic-based analyses showed that the diversity of functional genes decreased along the stress gradients. High stress enhanced the abundance of genes associated with broad functional categories (e.g., glycolysis/gluconeogenesis, TCA cycle, DNA replication/repair and cell growth/death) but reduced the abundance of genes linked to specialised functional categories (e.g., C, N, S and methane metabolism). Phylogenetic null models and niche analyses indicated that stochastic assembly processes predominated in high-diversity communities, in which bacterial and fungal taxa had a narrow ecological niche. However, in low-diversity communities, deterministic assembly processes were dominant, and taxa had wide niches, correlating with the reduction in gene abundance observed for broad and specialised functional categories. Given the essential role of the microbiome in regulating ecosystem functions, our findings suggest that low-diversity-induced deterministic community assembly processes and a wide niche under high environmental stress may regulate microbial functions. These findings emphasise the ecological mechanisms through which microbial biodiversity regulates terrestrial ecosystem functioning.

Soil Microbiology

Host life-history strategy is a critical determinant of virulent phage infection propensity.

Bacteriophages shape microbial communities through two major lifestyles: virulent (obligately lytic) and temperate (capable of lysogeny). Prevailing phage ecology frameworks focus on how environmental conditions, host density, and physiological state modulate infection modality. This perspective overlooks how host traits exert selective pressure on the distribution of virulent and temperate lifestyles across bacterial species, which limits understanding of phage ecology. To address this critical knowledge gap, we adopt a host-centric, trait-based perspective and use 5821 complete bacterial genomes to build a host life-history space predominantly defined by genome size, metabolic capacity, and growth rate potential. After mapping phage lifestyle association signals, prophage burden formed a continuous gradient across this space. Also, virulent phage association was positively correlated with prophage burden, revealing a nested structure of lifestyle signals. Functional trait analysis identified enrichment of resource-acquisition modules underlying both temperate and virulent associations. Overall, these findings indicate that phage lifestyle is significantly influenced by host life-history strategies, highlighting fast-growing, metabolically versatile hosts as favorable targets for virulent phage isolation and biocontrol applications.

Bacteriophages

Carbon metabolic homogenization is linked to microbial competition and antimicrobial resistance in soils under forest-to-cropland conversion.

Global agricultural expansion by converting natural forests into croplands often leads to soil functional homogenization and antimicrobial resistance enhancement, threatening ecosystem services. However, the associations between microbial carbon metabolic homogenization and antimicrobial resistance remain largely unknown. Here, we collected 240 paired forest and cropland soil samples from the most intensively farmed Yangtze River Basin in China, and constructed a novel framework based on microbial functional traits to decipher the role of carbon metabolic homogenization on antimicrobial resistance via microbial competition for metabolites. Using genome-scale metabolic models, we found that carbon metabolic homogenization was associated with a shift in microbial interactions from cooperation toward competition, with a 45.6% increase in competitive interactions that coincided with a 35.6% higher antimicrobial resistance gene (ARG) diversity. This shift was accompanied by smaller genome sizes and higher 16S rRNA copy numbers, indicating fast-growing, resource-acquisitive microbial strategies. Metabolic transfer analyses further revealed less cooperation relationships among microbial communities in cropland soils than in forest soils, indicating an intensified battle for communal metabolites and an attenuated exchange for complementary metabolites. Together, these findings provide a new framework to understand the association between carbon metabolic homogenization and soil antimicrobial resistance risks from the perspective of microbial traits and interactions under land use change.

Soil Microbiology

In silico analysis and comparison of the metabolic capabilities of different organisms by reducing metabolic complexity.

BACKGROUND: Understanding how metabolic capabilities diverge across microbial species is essential for deciphering community function, ecological interactions, and the design of synthetic microbiomes. Despite shared core pathways, microbial phenotypes can differ markedly due to evolutionary adaptations and metabolic specialization. Genome-scale metabolic models (GEMs) provide a systems-level framework to explore these differences; however, their complexity hinders direct comparison. RESULTS: We introduce NIS (Neidhardt-Ingraham-Schaechter), a computational workflow that integrates the redGEM, lumpGEM, and redGEMX algorithms to systematically reduce genome-scale models into biologically interpretable modules. This approach enables direct, quantitative comparison of fueling pathways, biomass biosynthetic routes, and environmental exchange processes while retaining essential metabolic information. We first demonstrate the utility of NIS by analyzing Escherichia coli and Saccharomyces cerevisiae, which revealed both conserved and divergent strategies in central metabolism, biosynthetic cost, and substrate utilization. We then applied NIS to the core honeybee gut microbiome, uncovering distinct metabolic traits, functional redundancy, and complementarity that help explain auxotrophy, cross-feeding interactions, and microbial coexistence. CONCLUSIONS: NIS provides an automated, scalable, and reproducible framework for dissecting microbial metabolic networks beyond gene content or taxonomy. By linking metabolism to ecological function, NIS offers new opportunities to interpret microbial community dynamics and to support the rational design of microbiomes in health, agriculture, and environmental applications. Video Abstract.

Metabolic Networks and Pathways