共找到 20 条结果
[This corrects the article DOI: 10.1093/ismeco/ycaf171.].
The Rickettsiales are an alphaproteobacterial lineage engaging in ancient associations with a variety of eukaryotic hosts and with a wide spectrum of effects. They include vector-borne pathogens, as well as Wolbachia, which ranges from a reproductive manipulator to a mutualist in arthropods and nematodes. The majority of Rickettsiales are associated with aquatic protists, but these interactions are poorly understood. Here, we explored by dual RNA-Seq the effect of the host-generalist Rickettsiales bacterium Megaera polyxenophila on the protist Paramecium primaurelia. Megaera induces substantial changes in host gene expression, in particular, increased expression levels of certain cell replication-related functions, consistent with the higher growth observed in previous experiments. Conversely, the co-occurring reduction of catabolism and energy metabolism can be explained by the capability of the bacterium to efficiently exert the same pathways also for the host's benefit. Therefore, Megaera likely behaves as a facultative mutualist, consistent with its predicted ability to provide the host with Adenosine triphosphate (ATP) and biotin, the latter synthesized, thanks to a recently horizontally acquired operon. At the same time, this bacterium expresses several genes involved in host cell invasion and possibly toxicity. Accordingly, it is envisioned that the overall effect of Megaera on its host is rather plastic, being the fine-tuned sum of supportive and parasitic actions, likely resulting in flexibility according to host and symbiont genotypes and environmental conditions, and subjected to evolutionary changes. Such flexibility may also explain the broad host range of Megaera and, from a more general perspective, hints for shared traits and analogies among other protist-associated Rickettsiales.
In this work, we describe an engineering approach that leverages ecological drift to generate minimal microbiomes; microbial consortia that are relatively simple, cohesive, and functionally complete. This process can be applied to any microbial ecosystem, provided that the target microbiome can be experimentally mimicked. Empirical support for this approach has emerged from multiple independent studies. We use simulations across diverse scenarios, significantly varying niche structures and biotic interactions, to explore the experimental conditions and source microbiome characteristics that favor successful outcomes, within a computational framework that also enables the study of microbial community assembly. Our results indicate that the effectiveness of this approach is constrained by several factors, and that perfect outcomes should not be routinely expected. Nevertheless, despite its drawbacks, this strategy remains a powerful tool for simplifying microbiomes and isolating key co-adapted populations, enabling the construction of low-diversity consortia that retain community function and present ecological cohesion.
The Type VI secretion system (T6SS) is a major determinant of bacterial competition, yet its dissemination across lineages remains unclear. By analyzing 43 213 plasmids and 29 161 chromosomes, we reveal plasmids as an underestimated reservoir and vehicle for T6SS diversification. We identified 405 complete plasmid-encoded T6SSs and 929 orphan islands containing hcp, vgrG, and/or PAAR genes, often independent of full systems. Plasmid-encoded T6SSs are biased toward large replicons, frequently megaplasmids, with distinct stability and mobility traits: orphan island plasmids are enriched in conjugation modules, whereas complete systems are associated with partition and toxin-antitoxin maintenance systems. Phylogenomic analyses show that some plasmid lineages stably integrate T6SSs as core traits, while others undergo recurrent acquisition and diversification. Comparative and ancestral analyses indicate pervasive bidirectional transfers between plasmids and chromosomes, with insertion sequences frequently detected in their vicinity. The presence of near-identical homologs across compartments underscores the capacity of plasmids to transcend phylogenetic barriers and propagate these nanoweapons. Together, our results identify plasmids as dual evolutionary actors in T6SS ecology, functioning as short-term vectors for rapid horizontal spread and as long-term reservoirs that foster stabilization and adaptive diversification.
Antimicrobial resistance (AMR) is a global health threat requiring a One Health approach across human, animal, and environmental sectors. Bacterial extracellular vesicles (BEVs), membrane-bound particles secreted by bacteria, have emerged as potential vectors of antibiotic resistance and mediators of horizontal gene transfer. Found across clinical, agricultural, and natural environments, BEVs carry resistance genes, mobile genetic elements, and virulence factors. They protect genetic cargo, function without direct cell contact, and can cross ecological boundaries more easily than whole bacteria. This review synthesises current knowledge on BEVs in AMR transmission, highlights their cross-sector potential, and identifies key research gaps. Recognising their role is essential for improving AMR surveillance and informing future mitigation strategies.
Estuarine ecosystems are jointly regulated by freshwater plumes and seawater intrusion, yet their impact mechanisms on community dynamics remain insufficiently understood. Here, we investigated the response of ciliate community to freshwater plume-seawater intrusion disturbance in a large subtropical estuary in China. Ciliate distribution exhibited clear turnover along environmental gradients in both community composition and abundance. In summer, community composition showed gradual horizontal and vertical shifts that corresponded with broad environmental gradients generated by strong freshwater plumes. In contrast, in winter, community variation was most pronounced between the inner and middle estuary, reflecting the upstream compression of environmental gradients driven by strong seawater intrusion. These patterns were corroborated by our determinants analyses. Variation partitioning analysis revealed that physical factors explained a substantial proportion of community variation in both seasons, and structural equation modelling further demonstrated that physical factors exerted the strongest total effects on community structure. In addition, species abundances closely followed a log-normal distribution in both seasons, which is consistent with predictions of niche-based community theory. Niche differentiation along environmental gradients shaped by freshwater plumes and seawater intrusion may contribute to this pattern. Overall, our findings reveal a clear linkage between ciliate distribution and freshwater plume-seawater intrusion dynamics, suggesting that ciliate communities can sensitively reflect the spatial-temporal variability of these physical processes.
Prokaryotes play a central role in marine biogeochemical cycles, yet quantifying their activity requires sensitive methods, particularly in the deep ocean where their biomass and metabolic rates are low. One widely used method to determine single-cell activity of prokaryotes is bioorthogonal non-canonical amino acid tagging (BONCAT), which offers a non-radioactive approach to measure protein synthesis. However, direct comparisons between BONCAT and radioisotope-based techniques across ocean depth gradients remain limited, particularly for low-activity prokaryotic communities. To address this knowledge gap, we applied BONCAT to quantify single-cell heterotrophic activity in prokaryotic communities from surface to bathypelagic depths (1000-4000 m) in the Southern Ocean near the Kerguelen Islands. Employing picolyl azide-based copper-catalysed click chemistry, we compared BONCAT (L-homopropargylglycine [HPG] incorporation) with microautoradiography (3H-methionine uptake). BONCAT consistently detected active cells throughout the water column, with HPG-derived total fluorescence intensity closely correlating with both microautoradiography (R2 = 0.91, P < .001) and bulk methionine incorporation (R2 = 0.94, P < .001). This strong relationship between BONCAT and microautoradiography was maintained into the upper bathypelagic depths, where detecting single-cell activity becomes challenging. Our results demonstrate that BONCAT provides estimates of single-cell heterotrophic activity consistent with microautoradiography in deep-ocean samples, supporting its application as a non-radioactive alternative in low-activity environments.
Flavonifractor plautii, a prevalent gut commensal, uniquely combines flavonoid degradation with the capacity to produce health-promoting short-chain fatty acids (SCFAs), notably butyrate and propionate. However, its metabolic pathways, ecological roles, and health impacts remain poorly characterized. To explore its probiotic potential and ecological functions, we developed a genome-scale metabolic model, iFP655, using automated reconstruction, deep-learning-based gap-filling, thermodynamic constraints, and transcriptomics. The iFP655 model substantially improved the predictions of growth rates and SCFA profiles compared to previous models. Simulations identified acetyl-CoA pathways as the preferred route for butyrate production, whereas the energetically costly lysine pathway remained inactive despite robust gene expression. Propionate synthesis occurred primarily via the methylmalonyl-CoA pathway. Community metabolic modeling with representative species of a Western minimal gut microbiota highlighted F. plautii's contributions to enhanced SCFA production, especially butyrate, amino acid metabolism, and syntrophic interactions driven by dietary substrates. Our findings indicate that diet-driven syntrophy significantly shapes microbial community structure and function, underscoring the ecological importance of F. plautii in gut microbial interactions and highlighting its potential as a probiotic candidate to beneficially modulate gut microbiota through dietary interventions.
Microbial communities are structured through complex interactions that are difficult to observe directly. Co-occurrence networks offer a way to infer community structure, revealing (not exclusively) potential biotic interactions. Such networks have been inferred for diverse biomes and repeatedly found to be modular, yet the ecological significance of this modularity remains underexplored. We tested whether clusters within co-occurrence networks ("cohorts"), are universal and ecologically meaningful units by assessing their ubiquity, stability, and environmental specificity across diverse ecosystems. Our meta-analysis spans 25 previously published 16S rRNA gene amplicon sequencing datasets (14 160 samples) and covers high environmental variability ranging from aquatic, terrestrial to anthropogenic environments. Microbial co-occurrence networks consistently exhibited high modularity across biomes. Inferred cohorts were ubiquitous and represented up to 90% of the community composition. Our findings demonstrate that modularity is a fundamental and generalizable feature of microbial community organization, indicating the existence of stable subcommunities. Highly similar cohorts were inferred even across different, unconnected environments and datasets, and showed consistent responses to environmental gradients, indicating that their composition is to a large degree deterministic and predictable. The overall cohort structure and environmental preferences were independent of the sample size and the inference algorithm, underlining the robustness and applicability of the results. Recognizing these microbial cohorts as a meaningful level of microbial organization will refine microbial community ecology, cultivation strategies, and predictive modelling of microbial dynamics.
Phytoplankton undertake daily vertical migration through the water column to optimize light and nutrient access while avoiding predators. However, diel vertical migration (DVM) patterns remain poorly characterized for many taxa due to limitations of labor-intensive traditional microscopy. Here, we employed high-throughput in situ imaging flow cytometry to investigate DVM. An Imaging FlowCytobot (IFCB) was deployed to continuously profile the vertical water column for ~10 weeks (August-October 2016) at a location in the Skagerrak, eastern North Sea. This revealed significant DVM for several morpho-taxonomic groups, including taxa belonging to ciliates, dinoflagellates, and diatoms, shifting median depth by 2-6 m between night and day. The analysis also revealed that DVM can be inferred from diel pulses in surface water biomass, which we leveraged to study DVM in an extensive IFCB time-series dataset from the central Baltic Sea (June-October in 2020 and 2021). Migratory taxa accounted for 77% and 79% of total phytoplankton biomass (size range <10-150 μm) in the Skagerrak and Baltic Sea, respectively, underscoring the ecological significance of DVM. Most populations peaked near the surface at midday, although other patterns were also observed. While many taxa displayed consistent migration behaviors across both regions, others differed-likely due to population-specific traits or local environmental conditions. Seasonal changes in migration patterns suggest a role for community turnover and shifting environmental conditions. This study highlights the prevalence of DVM in phytoplankton and showcases the power of automated, high-throughput imaging technologies to advance our understanding of plankton ecology.
Laboratory models provide tractable, reproducible systems that have long served as foundational tools in microbiology. However, the extent to which these models accurately mimic the biological environments they represent remains poorly understood. A quantitative framework was recently introduced to assess how well laboratory models capture microbial physiology in situ. However, applications of this framework have been limited to characterizing the physiology of a single species in human infections, leaving a gap in our understanding of overall microbial community physiology in polymicrobial contexts. Here, we extended this framework to evaluate the accuracy of laboratory model systems in capturing community-level functions in polymicrobial infection. As a proof of concept, we applied the extended framework to a polymicrobial model of human chronic wound (CW) infection. CWs harbor metabolically diverse bacterial species that engage in a range of microbe-microbe interactions, ultimately impacting community dynamics and disease progression. However, studies on the mechanistic drivers of chronic wound infection have relied on single species or pairwise approaches. Here, we demonstrate that our adapted framework can be used to develop accurate polymicrobial models. Further, we demonstrate that this extended framework can evaluate the occurrence of known microbe-microbe interactions. Building on our prior work in large-scale metagenomic and metatranscriptomic analysis, we propose a highly accurate 6-member synthetic bacterial community model i.e. representative of the taxonomic and functional complexity of human CW infections. This approach will support the development of ecologically relevant polymicrobial models and better treatment strategies.
It is widely accepted that the use of siderophores, small molecules that bind and solubilize iron, emerged as a response to the dramatic reduction in bioavailability of this metal in aquatic environments caused by precipitation of iron oxides associated with the Great Oxidation Event (GOE). Here, we report a molecular clock analysis of the time of emergence of siderophore biosynthesis and utilization genes that challenges this view and argues for an emergence of these secondary metabolites that largely predates GOE. The emergence date of Non-ribosomal Peptide Synthase Independent Siderophore synthetases is found to predate by more than 1 Gy the emergence date of ferric siderophore reductases and esterases, which in turn also predate the GOE by approximately 1Gy. This temporal gap is surprising given that these enzymes are essential for microorganisms to obtain iron from siderophores. This timing of events raises questions on the original ecological drivers for the emergence of siderophores. We offer an alternative hypothesis for the origin of siderophores which is their use in ferric mineral dissolution to avoid incrustation of neutrophilic iron oxidizers by metabolically generated ferric iron minerals. The observations and hypothesis reported here highlight the importance of environmental microbe-mineral interactions, beyond nutrient acquisition, as critical selective forces in early Earth, and call for a reassessment of the timing and drivers of siderophore evolution.
Macro-ecosystems, including the human gut, host a vast and diverse set of microbes that indirectly interact with each other through consuming and producing metabolites. Disruptions in this microbial network can affect macro-ecosystem functioning and, in the human gut, contribute to the onset and progression of various disorders, including diabetes, rheumatoid arthritis, and Parkinson's disease. A theoretical foundation for understanding the intricate and dynamic interactions between microbes and metabolites is essential for developing microbiota-targeted interventions to improve macro-ecosystem functioning and health. To this end, a precise mathematical framework is crucial to capture and quantify the complex dynamics of the microbial system. Here, we develop a dynamic network model of coupled ordinary differential equations and present a computational workflow that integrates a generative model with Bayesian inference for model identification. Our approach infers interaction rates, quantifying metabolite consumption and production from simulated time-series data within a Bayesian framework, incorporating prior knowledge and uncertainty quantification. We show that our approach is accurate and reliable in communities of various sizes, sparsity, and with different levels of observational noise. This workflow enables in silico predictions of system behaviour under perturbations and offers a robust method to integrate high-dimensional biological data with dynamic network models. By refining our understanding of microbial dynamics, this framework is capable of assessing microbiota-targeted interventions and their potential to improve the health of the macro-ecosystem.
Soil microbial ecosystems are complex and difficult to replicate in laboratory settings. It is often unclear which pressures most strongly shape microbial survival and evolution in situ, and new methods are needed to intersect the manipulative power of the lab with the reality of field environments. One recent innovation was the "isolation chip," in which many new microbial isolates could be cultured on agar within a buried diffusion chamber while exposed to environmental inputs through fine-pored membranes. Here, we created a modified version of this device containing biologically-cleared soil instead of agar, to trial an in situ reverse ecology experimental evolution approach. Using these "adaptation chips (aChips)" we exposed populations of two different soil-dwelling bacteria (Priestia megaterium and Streptomyces lydicus) to several farm soils in the Northeast US for up to two years, documenting mutations arising in the evolving populations. While evolution was remarkably slow in the field, P. megaterium populations accumulated many mutations pre-burial during aChip construction which seemingly reflected zinc limitation in the aChip carrier soil. Although post-burial mutations were observed in both P. megaterium and S. lydicus populations, they remained at low frequency and did not display parallelism between aChips buried at the same sites, indicating a lack of strong positive selection and/or limited generations of population growth within the aChip. We suggest several improvements to aChip design to facilitate greater evolutionary progression, including a larger within-aChip soil volume and fewer cells initially secured inside the aChip.
Modern crop varieties may exert reduced influence on their microbiome compared to their progenitors, as plant-microbe interactions were not targeted during breeding. Moreover, formerly beneficial microbiome functions might no longer be relevant in modern agricultural ecosystems. We hypothesised that such patterns could become particularly evident under drought, since drought-tolerance has not been a primary breeding target. To test this, we grew six maize landraces (released before 1945) and six modern varieties (released from 2010 onwards) in a field under ambient and 60% reduced precipitation. The experiment was repeated over two years, differing in amounts and temporal distributions of precipitation. We assessed the composition of root-associated prokaryotic communities during grain filling by 16S rRNA gene metabarcoding. Intra-variety dispersion in microbiome composition relative to plant biomass-based dispersion was higher in modern varieties, suggesting breeding may have affected plant control over microbiomes. Besides that, shifts in microbiome composition between landraces and modern varieties were driven mainly by the plants' impact on soil water potentials. Consequently, the taxa that increased in relative abundance during soil drying, mainly Actinomycetota, were similar between landraces and modern varieties. Exploring microbiome-mediated alleviation of drought effects, therefore, appears promising also for applications in modern agricultural ecosystems. Specifically, filamentous Streptomyces spp. potentially contributed to soil aggregate stability, which should be further investigated in the context of drought mitigation. The reduced plant control over microbiome composition of modern varieties suggested by dispersion analysis likely has functional implications beyond microbiome adaptation to drought and should be considered in future assessments of breeding.
Deep-sea hydrothermal vent ecosystems are sustained by chemoautotrophic bacteria that symbiotically provide organic matter to their animal hosts through the oxidation of chemical reductants in vent fluids. Hydrothermal vents also support unique viral communities that often exhibit high host-specificity and frequently integrate into host genomes as prophages; however, little is known about the role of viruses in influencing the chemosynthetic symbionts of vent foundation fauna. Here, we present a comprehensive examination of contemporary lysogenic and lytic bacteriophage infections, auxiliary metabolic genes (AMGs), and CRISPR spacers associated with the intracellular bacterial endosymbionts of snails and mussels at hydrothermal vents in the Lau Basin (Tonga). Our investigation of contemporary phage infection among bacterial symbiont species and across distant vent locations indicated that each symbiont species interacts with different phage species across a large geographic range. Surprisingly, prophages were absent from almost all symbiont genomes, suggesting that phage interactions with intracellular symbionts may differ from free-living microbes at vents. Altogether, these findings suggest that chemosynthetic symbionts primarily interact with species-specific phages via lytic infections, which may ultimately be important to the composition and dynamics of symbiont populations.
A device capable of sampling natural gas under aseptic conditions and in complete safety has been deployed along the transmission grid for the first time. Microbial endospores, resilient enough to survive the extreme conditions of gas transmission and storage, have been detected and isolated throughout high-pressure pipelines and underground reservoirs. In four underground gas storage (UGS) facilities, three in deep aquifers and one in a depleted reservoir, endospores of the same hydrogenotrophic bacterial species from the family Peptococcaceae have been identified, sometimes separated by hundreds of kilometers, and at two different points in the pipeline network. Cultural and genomic analyses show these bacteria can perform acetogenesis, biofilm formation, and produce formate. Hidden within pipelines, these microbes survive long journeys and actively participate in biogeochemical cycles in UGS. Several recent studies on dihydrogen injection into deep aquifers have shown the ubiquity of bacteria similar to these, responsible for formate formation through modified acetogenesis. This formate can serve as a carbon source or inhibit sulfate reduction at high concentrations. Understanding their role offers critical insights into microbial life in the deep biosphere and the potential impacts of future dihydrogen injection into natural gas systems. Their ability to thrive in extreme environments makes these microbes key players in the evolving landscape of underground energy storage and transport.
Soil phosphorus (P) is a limiting factor for vegetation growth in the Amazon rainforest, where plants depend on microorganisms for organic matter cycling and nutrient uptake. While forest-to-agriculture conversion fundamentally reshapes plant-microbe-soil interactions and P cycling, these dynamics are further modulated by the intensity of land management. This study examined the 30-year effects of converting a primary forest into two contrasting systems: a low-intensity agroforest and a high-intensity citrus monoculture. We investigated how microbial and low molecular weight organic compounds (LMWCs) composition interacted with soil physicochemical attributes, acid phosphatase activity, and P fractions (labile, moderately labile, non-labile, and residual). Agroforest soils retained physicochemical and enzymatic attributes similar to the primary forest, while soils of the citrus plantation showed increased P in all fractions due to mineral fertilization and reduced soil organic matter content, mainly in deeper layers. Microbial and LMWC composition patterns reflected land-use, with agroforest representing an intermediate state between primary forest and citrus monoculture. Pseudomonadota and nutrient-rich LMWC were more abundant in the agroforest, whereas Ascomycota and nutrient-poor LMWC predominated the citrus plantation. Genes related to "P acquisition" were more abundant in forest and agroforest soils, while genes related to "P-compound synthesis" were more abundant in the citrus plantation. Labile P was negatively correlated with genes related to microbial metabolism, suggesting that reduced P availability may induce a boost in microbial activity for internal P-cycling. These findings demonstrate that forest-to-agriculture conversion strongly affects microbial functions, with responses aligning with land-use intensity and LMWC resource availability. Nonetheless, microbes adapt by shifting strategies: prioritizing mineralization and solubilization or favoring biosynthesis depending on P availability.
Spatial organization plays a critical role in shaping microbial community structure and function, influencing ecological stability, resource utilization, and evolutionary dynamics. Microbial interactions such as competition and cooperation are key drivers of spatial patterning, yet the environmental factors modulating these interactions remain incompletely understood. Here, we investigated how toxic substrates influence the spatial organization of synthetic microbial communities engaged in metabolic cross-feeding. Using a synthetic Pseudomonas stutzeri consortium consisting of the detoxifier and consumer that cooperatively degrade the toxic compound salicylate, we found that increasing the substrate concentration leads to a distinct shift in spatial organization: the detoxifier increasingly dominates the outer periphery of the expanding colony, forming a "detoxifier-first" succession pattern. Mathematical modeling further revealed that this spatial arrangement emerges from substrate toxicity, which selectively favors the detoxifier. Substrate toxicity inhibits consumer proliferation. However, the detoxifier, capable of degrading the substrate, locally reduces toxicity and creates a protective microenvironment that enables nearby consumer cells to survive and grow. In return, the consumer provides essential final products that support the growth and expansion of the detoxifier. This reciprocal interaction establishes a directional dynamic in which the detoxifier, favored by its detoxification capability, colonizes first, paving the way for subsequent consumer proliferation. Our findings demonstrate that substrate toxicity is a crucial environmental factor shaping spatial organization and diversity in microbial communities. This study highlights the importance of considering both metabolic interactions and substrate properties in understanding microbial ecology.
Marine viruses impact biogeochemical cycles through cell lysis, releasing organic matter and nutrients that fuel ocean productivity. Identifying and quantifying the specific viruses active in these processes remain a priority in the field. Here, we introduce a click-chemistry method to fluorescently label, sort, and sequence the genomes of newly produced viral particles (viral progeny) released from transcriptionally active host microbial cells, alongside the analysis of co-occurring inactive cells and pre-existing viruses in environmental samples. This approach, called viral bioorthogonal noncanonical amino acid tagging (BONCAT)-fluorescence-activated cell sorting (FACS), combines BONCAT with environmental sample incubation, followed by single-virus and single-cell sorting by flow cytometry (FACS). Genomic analysis of translationally active cells and new viral progeny in coastal seawater incubations confirmed BONCAT labeling and successful sorting of diverse marine bacteria, microeukaryotic cells, and virioplankton, with stark differences in the predicted turnover of specific groups of infecting viruses, including pelagiphages, methylophages, a Flavobacteriales-associated novel "Far-T4" clade, noncanonical DNA viruses of Naomiviridae using dU instead of dT, algae-infecting giant NCLDV viruses, and parasitic virophages. Sequenced BONCAT-active cells showed a strong enrichment in viral contigs relative to the inactive cell fraction, suggestive of a large proportion of translationally active virocells. This study illustrates the effectiveness of viral BONCAT-FACS for uncovering genome-resolved virus-host dynamics. By providing a direct approach for tracking active viral infections in natural environments, this method enhances our ability to investigate behavior and interactions of these nanoscale predators, expanding our understanding of their role in ecosystem dynamics.