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At least 19 recordsLinked to original sources
PubMed2026

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↗
PubMed2026

Parental niche construction buffers microbial and competitive challenges and drives offspring dependence in burying beetles.

Parents across diverse taxa modify the biotic or abiotic environments of their offspring. Such modifications may constitute ecological inheritance and are central to developmental niche construction, whereby organisms shape developmental conditions and selective pressures experienced by the next generation. Despite its theoretical importance, parental niche construction is often studied under simplified conditions or by focusing on single components of care, limiting our understanding of how multiple parental modifications interact in ecologically relevant contexts, whether they buffer environmental heterogeneity, and how this shapes offspring development and evolutionary trajectories. Using the burying beetle Nicrophorus vespilloides, we investigated how parents jointly modify chemical and microbial properties of vertebrate carcasses, a highly contested resource on which offspring develop. We show that under natural microbial and competitive conditions, prehatch care enhances larval survival and growth, alters cadaveric volatile emissions, and reduces carcass attractiveness to competitors. While soil type shapes carcass-associated microbial communities, parental care buffers these environmental effects, creating a more consistent microbiome and reducing environmentally induced larval mortality. Larvae of the related species Ptomascopus morio, which lacks prehatch carcass preparation, survived equally well on prepared and unmodified carcasses, whereas N. vespilloides larvae showed reduced survival on unmodified carcasses. This contrast is consistent with the hypothesis that N. vespilloides larvae have evolved a reliance on a parentally constructed developmental environment. Together, these findings show that parental care can constitute an integrated form of niche construction that reshapes developmental environments, enhances offspring performance, and may promote evolutionary feedback leading to increased offspring dependence on parental care.

Animals↗
PubMed2026

From sequence space to ecological function: microbiome-derived antimicrobial peptides as community effectors and therapeutic leads.

Antimicrobial peptide research has long centred on host defence molecules, yet microbiomes themselves encode a diverse and increasingly important repertoire of peptide-based antimicrobials. These microbiome-derived antimicrobial peptides include bacteriocins, ribosomally synthesised and post-translationally modified peptides, cryptic short open reading frame-encoded peptides, embedded antimicrobial regions within larger proteins, and selected peptide antibiotics recovered from human, animal, plant and environmental microbiomes. Recent advances in genome mining, metagenomics, and machine learning have greatly expanded the scale of discovery, moving the field from a handful of landmark exemplars to large candidate catalogues spanning the global microbiome. In the clearest cases, these molecules are not only anti-infective leads but ecological effectors: they mediate microbial competition, enforce colonisation resistance, and influence community structure within densely occupied niches. The present review synthesises the field across discovery classes, microbiome sources, ecological roles, and translational bottlenecks, emphasizing a central limitation of the field: candidate catalogues are expanding at extraordinary scale, while evidence for native expression, producer assignment, ecological function, and in vivo relevance remains limited for the vast majority of predicted molecules. Progress will depend on workflows that connect sequence level prediction to biological context through expression support, producer assignment, community level validation, and perturbation-based approaches that distinguish ecological association from causal function. Microbiome-derived antimicrobial peptides are best understood not only as promising therapeutic leads, but also as molecular mediators of microbial social life whose ecological origins are central to their interpretation and future application.

Microbiota↗
PubMed2026

ZILA-SRM: a probabilistic framework with zero-inflated latent models for robust strain reconstruction from metagenomes.

UNLABELLED: Resolving bacterial strain diversity from shotgun metagenomic data is fundamental to understanding intra-host evolution, transmission dynamics, and phenotypic heterogeneity. However, current probabilistic approaches face a severe "identifiability limit" when disentangling highly similar genomes. Under high-noise conditions, sequencing errors, coverage overdispersion, and collinearity confound standard expectation-maximization algorithms, resulting in overfitting and spurious "ghost" strains. Here, we introduce zero-inflated latent allocation for strain reconstruction from metagenomes with adaptive sparsity regularization (ZILA-SRM) to overcome this barrier through three innovations. First, we integrate a zero-inflated Poisson mixture model to decouple "structural zeros" (true strain absence) from "sampling zeros" (stochastic dropout), addressing overdispersion in standard Poisson-based tools. Second, we impose a convex adaptive sparsity regularization penalty that leverages biological sparsity priors to shrink noise artifacts dynamically. Third, we implement a graph-theoretic refinement step using maximal clique enumeration to resolve haplotype collinearity. Benchmarking against StrainFinder and MixtureS on 702 synthetic data sets shows that ZILA-SRM achieves a 20% improvement in precision in high-complexity scenarios while maintaining over 80% recall for minor variants at 0.5% abundance. Re-analysis of deep-sequencing data from 195 Mycobacterium tuberculosis clinical samples reveals cryptic low-abundance drug-resistant variants in 12% of patients, including a minor clone carrying the rpoB S450L mutation. Furthermore, application to skin microbiome data sets further reveals a strong negative correlation between dominant Staphylococcus aureus and Staphylococcus epidermidis strains, providing genomic evidence for competitive exclusion. These findings establish ZILA-SRM as a robust tool for resolving strain-level diversity in complex metagenomes. IMPORTANCE: Understanding microbial communities at the strain level is critical because closely related strains can differ dramatically in traits such as drug resistance, virulence, and ecological interactions. However, resolving individual strains from metagenomic sequencing data remains difficult, especially when strains are highly similar or present at low abundance. As a result, biologically meaningful diversity is often obscured or misinterpreted as noise. In this study, we introduce a new framework that improves the reliability of strain reconstruction from complex metagenomic data. By reducing false-positive strain detection while preserving sensitivity to rare variants, our approach enables more accurate characterization of microbial populations. This improved resolution reveals previously hidden subpopulations in clinical and microbiome datasets, providing clearer insights into microbial evolution, competition, and the emergence of clinically relevant traits such as antibiotic resistance.

Metagenomics↗
PubMed2025

The Gfr Uptake System Provides a Context-Dependent Fitness Advantage to Salmonella Typhimurium SL1344 During the Initial Gut Colonization Phase.

Salmonella enterica serovar Typhimurium (S. Tm) is a major cause of foodborne diarrhea. However, in healthy individuals, the microbiota typically restricts the growth of incoming pathogens, a protective mechanism termed colonization resistance (CR). To circumvent CR, Salmonella strains can utilize private nutrients that remain untapped by the resident microbiota. However, the metabolic pathways and environmental niches promoting pathogen growth are still not completely understood. Here, we investigate the significance of the gfr operon in gut colonization of S. Tm, which is essential for the utilization of fructoselysine (FL) and glucoselysine (GL). These Amadori compounds are present in heated foods with high protein and carbohydrate contents. We detected FL in both mouse chow and the intestinal tract of mice and showed that gfr mutants are attenuated during the initial phase of colonization in the murine model. Experiments in gnotobiotic mice and competition experiments with Escherichia coli suggest that gfr-dependent fitness advantage is context-dependent. We conclude that dietary Amadori products like FL can support S. Tm gut colonization, depending on the metabolic capacities of the microbiota.

Salmonella typhimurium↗
PubMed2026

Computational mass spectrometry and genome mining guided discovery of metallophores produced by Microbulbifer.

Iron is an essential component of cellular biology. Thus, iron's low bioavailability is a key evolutionary pressure guiding microbial dynamics in the marine environment. Among marine bacteria, Microbulbifer is a chemically underexplored and functionally versatile bacterial genus, which is commonly associated with sponges, algae, corals, and sediments. Previously, genome analyses have revealed that Microbulbifer spp. can degrade polymers and synthesize natural products. Despite their recognized potential to produce secondary metabolites, siderophores are yet to be identified in Microbulbifer, and their iron acquisition strategies remain largely unknown. Here, we developed a comprehensive mass spectrometry-based query language code to determine siderophore production by Microbulbifer spp. in mono- and mixed cultures. Using this workflow, we discovered a new metallophore, which we named bulbichelin, as well as a suite of previously unreported petrobactins containing an unprecedented longer chain length acylation on the central spermidine moiety. We applied genome mining methods to describe the biosynthesis of these compounds. Using metal infusion mass spectrometry, we show that bulbichelins bind a variety of metals. Notably, neither of these compounds were produced in a co-culture of Microbulbifer with coral-derived pathogen Vibrio coralliilyticus Cn52-H1. Understanding how siderophores shape interspecies interactions between Microbulbifer spp. and other marine organisms will aid in unraveling the chemical and catalytic versatility of this genus and adaptation in nutrient deplete marine environment.

MassQL↗
PubMed2026

Cross-Kingdom Siderophores: Biosynthesis, Ecology, and Biotechnological Applications.

Microbial siderophores are high-affinity iron-binding compounds which are produced by bacteria, fungi, and actinomycetes to obtain iron and survive and interact with different species in an iron-deficient environment. While the conventional research on siderophore systems deals mainly with the study within the same taxa, modern researchers have increased their inclination toward cross-kingdom integration of siderophore behavior and their impact on host-associated environments. This can be largely attributed to differences in biosynthetic gene clusters, receptor systems, and regulatory networks, which produce distinct genotype-to-phenotype results determining microbial cooperation and competition. Current advancements in genomic research, together with omics studies like transcriptomics, proteomics, and metabolomics, have created newer insights into how siderophores function. However, the present literature evidences multiple major gaps in multi-omics data because the link between genomes and metabolomes remains weak due to inconsistent regulatory data sets and failure in identifying producer-consumer relationships in polymicrobial systems. Additionally, major constraints like molecular instability, delivery system limitations, host toxicity, limitations in upscaling, and regulatory issues delimit the use of siderophores in medical treatment, agricultural practices, and environmental biotechnology. This review aims to bridge the existing knowledge about siderophore biochemistry, biosynthesis, ecological functions, and genetic regulation across kingdoms while integrating multi-omics outlook with translational considerations. Thus, by connecting molecular mechanisms with evolutionary cross-talk, this study aims to provide a system-level framework in the world of siderophore-mediated iron uptake and therefore shapes future directions in emerging fields of microbial engineering, precision therapies, and sustainable biotechnology.

Fur regulation↗
PubMed2025

Type VI secretion system activity at lethal antibiotic concentrations leads to overestimation of weapon potency.

Competition assays are a mainstay of modern microbiology, offering a simple and cost-effective means to quantify microbe-microbe interactions in vitro. Here, we demonstrate a key weakness of this method that arises when competing microbes interact via toxins, such as those secreted via the type VI secretion system (T6SS). Time-lapse microscopy reveals that T6SS-armed Acinetobacter baylyi bacteria can maintain lethal T6SS activity against E. coli target cells, even under selective conditions intended to eliminate A. baylyi. Further, this residual killing creates a density- and T6SS-dependent bias in the apparent recovery of E. coli, leading to a misreporting of competition outcomes where target survival is low. We also show that incubating A. baylyi/E. coli co-cultures in liquid antibiotic prior to selective plating can substantially correct this bias. Our findings demonstrate the need for caution when using selective plating as part of T6SS competition assays, or assays involving other toxin-producing bacteria.

Type VI Secretion Systems↗
PubMed2026

Implications of proteome allocation constraints for understanding interbacterial antagonism.

Bacteria live in dense communities where competition influences the composition and, therefore, the function of these communities. Beyond competing for resources, bacteria engage in antagonism by deploying a range of molecular weapon systems to inhibit and kill other bacteria. Investing in antagonism is expected to incur a fitness trade-off, but the nature of this trade-off at the level of molecular physiology remains underexplained. Applying recent advances about the physiological constraints faced by bacterial cells may help us better understand existing studies and design new investigations into interbacterial antagonism. Bacterial cells face two important constraints: a finite amount of protein and a maximum translation speed for ribosomes. As a result, the only way for a cell to grow faster is to allocate more of its finite proteome to synthesizing ribosomes. A cell choosing to attack competitors must therefore allocate some of its limited proteome budget to antagonistic proteins instead of other functions. Conversely, being attacked and resisting the effects of such attacks also require an investment of proteomic resources. The extent to which proteome allocation constraints influence bacterial physiology is not fully understood; consequently, how these constraints influence interbacterial antagonism has not been investigated. Here, I will discuss how proteome allocation constraints can re-contextualize our existing understanding of the costs of both deploying and resisting attacks and how investigation of these constraints may further our understanding of interbacterial antagonism.

Proteome↗
PubMed2025

Archaea produce peptidoglycan hydrolases that kill bacteria.

The social life of archaea is poorly understood. In particular, even though competition and conflict are common themes in microbial communities, there is scant evidence documenting antagonistic interactions between archaea and their abundant prokaryotic brethren: bacteria. Do archaea specifically target bacteria for destruction? If so, what molecular weaponry do they use? Here, we present an approach to infer antagonistic interactions between archaea and bacteria from genome sequence. We show that a large and diverse set of archaea encode peptidoglycan hydrolases, enzymes that recognize and cleave a structure-peptidoglycan-that is a ubiquitous component of bacterial cell walls but absent from archaea. We predict the bacterial targets of archaeal peptidoglycan hydrolases using a structural homology approach and demonstrate that the predicted target bacteria tend to inhabit a similar niche to the archaeal producer, indicative of ecologically relevant interactions. Using a heterologous expression system, we demonstrate that two peptidoglycan hydrolases from the halophilic archaeaon Halogranum salarium B-1 kill the halophilic bacterium Halalkalibacterium halodurans, a predicted target, and do so in a manner consistent with peptidoglycan hydrolase activity. Our results suggest that, even though the tools and rules of engagement remain largely unknown, archaeal-bacterial conflicts are likely common, and we present a roadmap for the discovery of additional antagonistic interactions between these two domains of life. Our work has implications for understanding mixed microbial communities that include archaea and suggests that archaea might represent a large untapped reservoir of novel antibacterials.

N-Acetylmuramoyl-L-alanine Amidase↗
PubMed2026

ALPAR: automated learning pipeline for antimicrobial resistance.

SUMMARY: The field of machine learning in antimicrobial resistance (AMR) research has experienced rapid growth, fueled by advancements in high-throughput genome sequencing and the growing capacity of computational resources. However, the complexity and lack of standardized data preparation and bioinformatic analyses present significant challenges, especially for newcomers to the domain. In response to these challenges, we introduce ALPAR (Automated Learning Pipeline for Antimicrobial Resistance), a comprehensive AMR data analysis tool covering the entire process from processing of raw genomic data to training machine learning models to interpretation of results. Our method relies on a reproducible pipeline that integrates widely used bioinformatics tools, presenting a simplified, automatic workflow specifically tailored for single-reference AMR analysis. Accepting genomic data in the form of FASTA files as input, ALPAR facilitates the generation of machine learning-ready data tables and both the training of machine learning and the execution of genome-wide association studies (GWAS) experiments. Additionally, our tool offers supplementary functionalities such as phylogeny-based analysis of the distribution of mutations, enhancing its utility for researchers. The tool has also proven its performance in competitive benchmarks, winning the 2024 CAMDA Anti-Microbial Resistance Prediction Challenge and placing third in the 2025 edition. AVAILABILITY AND IMPLEMENTATION: ALPAR is open-source and freely accessible via GitHub (https://github.com/kalininalab/ALPAR). The pipeline is fully reproducible and can be easily installed as a Conda package (https://anaconda.org/kalininalab/ALPAR).

Machine Learning↗
PubMed2026

The metabolic and anatomical complexity of root microhabitats modulate their interaction with the microbiota.

Plant roots constantly communicate with their microbiota, adapting their anatomy to facilitate microbial colonisation under abiotic stresses. Microbes, in turn, can reshape root anatomy once they establish. However, the mechanisms that coordinate this interplay remain largely unknown. Working with the aquatic plant family Lemnaceae, we reveal that the inherent complexity of root anatomy determines root plasticity in response to microbial colonisation. This microbiota-driven anatomical plasticity enhances plant survival in nutrient-competitive environments. By combining synthetic root models with real roots, we also find that anatomical plasticity is associated with metabolic reprogramming during microbial establishment. Moreover, we identify a plant metabolite, N6,N6,N6-Trimethyl-L-lysine, that regulates anatomical plasticity in response to microbial colonisation. Our work generalizes the importance of microhabitat complexity for microbiome recruitment under challenging environmental conditions.

Plant Roots↗
PubMed2025

Health-associated key gut microbiota drives the variation in community metabolic interactions in non-human primates.

Gut microbiota often undergo metabolic cross-feeding and resource competition. However, our understanding of global variations in these interactions and their implications for host health remain elusive. By analyzing a microbial genome catalog from 841 fecal metagenomes across 53 primate species worldwide, we identified key microbiota assigned to two taxa, i.e., Bacillota_A and Pseudomonadota, which well predicted the trade-off of community-level interaction types between metabolic competition and cooperation. Specifically, Bacillota_A species were inherently competitive and amino acid auxotrophic and typically found in anaerobic habitats. In contrast, members of Pseudomonadota were inherently cooperative, siderophore producers, and more abundant in aerobic conditions. Random forest models successfully distinguished unhealthy gut samples from healthy samples through the key competitive and cooperative microbiota, suggesting potential links between community metabolic interactions and host health. Together, this study enhances our mechanistic understanding of microbial interaction dynamism within complex gut ecosystems, offering new targets for understanding host health.

Animals↗
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↗
PubMed2026

Rgg144/SHP144-controlled streptolancidin D mediates intra-species competition in Streptococcus pneumoniae with cumulative effect from other bacteriocins and fratricide.

UNLABELLED: Streptococcus pneumoniae is a major colonizer of the human nasopharynx, where inter- and intra-strain competition plays a critical role in shaping population structure and influencing vaccine outcomes. Bacteriocins are key mediators of intra-species competition, yet many of their functions and regulatory mechanisms remain poorly understood. Here, we identify and characterize streptolancidin D, a previously uncharacterized bacteriocin encoded by the sldA-T locus, and demonstrate its contribution to pneumococcal competition. Using isogenic streptolancidin-producing and non-producing variants of a naturally colonizing strain, we show that sldA-T contributes to the inhibition of competitor strains in in vitro biofilms and during murine co-colonization. Importantly, streptolancidin D also inhibited in vitro a subset of genetically diverse pneumococcal isolates representing multiple serotypes, whereas non-producing variants showed no activity. This indicates that its effect is broad and not restricted to isogenic interactions. Genomic analysis of over 7,500 pneumococcal genomes revealed that sldA-T is present in ~12% of isolates, with lineage-associated distribution patterns, and is consistently encoded downstream of the Rgg144/SHP144 quorum sensing system. We further demonstrate that sldA-T is regulated by this system, with sldA-T promoter activity abolished in a SHP-deficient background and partially restored by exogenous peptide stimulation. Finally, we show that streptolancidin D acts in concert with other bacteriocin systems and competence-mediated fratricide, highlighting a multifactorial antimicrobial strategy that enhances pneumococcal competitiveness. Overall, our findings identify a quorum sensing-regulated bacteriocin that contributes to pneumococcal competition and helps shape population dynamics. IMPORTANCE: Bacteriocins are central to bacterial competition and niche occupation, particularly in structured environments like the human nasopharynx. While several pneumococcal bacteriocins have been characterized, the functions of many remain unknown, limiting our understanding of how these systems shape strain fitness and population dynamics. We characterize streptolancidin D, a bacteriocin that enhances intraspecies competitiveness in vitro and in vivo and contributes to the inhibition of genetically diverse pneumococcal strains. We demonstrate that its expression is tightly regulated by the conserved Rgg144/SHP144 quorum sensing system and that the locus is distributed and shows synteny across multiple pneumococcal lineages. Our findings reveal that streptolancidin D operates within a broader network of bacteriocins and competence-associated mechanisms that collectively shape competitive interactions. By integrating genomic, functional, and regulatory analyses, this work expands the known repertoire of pneumococcal antimicrobial systems and provides new insights into the mechanisms underpinning competition and population structure in S. pneumoniae.

Bacteriocins↗
PubMed2026

Soil erosion and landscape elevation as unnoticed determinants of environmental antibiotic resistance distribution.

Climate change is reshaping the global antibiotic resistance gene (ARG) landscape through geomorphological processes that remain largely overlooked in the One Health framework. This critical review synthesises evidence on how soil erosion and landscape elevation gradients redistribute, select for, and disseminate ARGs across terrestrial and aquatic ecosystems. Erosion physically removes and transports ARG-bearing microbes, depletes nutrients, and co-selects for resistance via heavy metal exposure and horizontal gene transfer, creating source-sink dynamics that connect eroding hillslopes to downstream water bodies and food systems. Elevation gradients impose abiotic stressors-declining temperature, elevated UV radiation, and shifting pH-that drive microbial community reassembly through environmental selection and dispersal limitation, with emerging evidence linking bacterial competition at high altitude to enhanced multidrug efflux and resistome complexity. The review identifies critical knowledge gaps, including unquantified ARG mass fluxes across erosion-deposition gradients, unresolved dispersal-versus-selection mechanisms along elevation transects, and the absence of integrated One Health surveillance linking environmental ARG reservoirs to clinical outcomes. A synthesis of global case studies illustrates how these processes converge across diverse landscapes. The review concludes with a mechanistic research agenda-including reciprocal transplant experiments, landscape connectivity modelling, and cross-sectoral surveillance-needed to translate these emerging drivers into actionable climate-AMR mitigation policy.

Drug Resistance, Microbial↗
PubMed2026

Characterisation of metabolic burden in Pseudomonas putida reveals precursor limitation in heterologous lycopene production.

BACKGROUND: The introduction of heterologous pathways into microbial hosts often imposes a metabolic burden on the cell, arising from three major physiological constraint layers: competition for gene expression resources, limited precursor availability and flux distribution, and insufficient energy and redox supply. Although Pseudomonas putida KT2440 is considered a robust and metabolically versatile production host, it remains unclear which of these constraint layers primarily limits heterologous terpenoid production in this organism. Here, lycopene biosynthesis was used as a model system to systematically dissect these three potential sources of metabolic burden. RESULTS: A capacity-monitoring system revealed no clear reduction in transcriptional or translational capacity across the tested strains and cultivation conditions, indicating that general gene expression capacity was not the primary limiting factor. Instead, lycopene production depended strongly on promoter architecture and plasmid backbone, showing that regulatory design shaped pathway performance. Enhancing precursor supply by introducing a heterologous mevalonate (MVA) pathway substantially increased product titres, identifying precursor availability from the native MEP pathway as the dominant bottleneck. This conclusion was independently supported by exogenous mevalonate supplementation, which further increased lycopene accumulation but also revealed saturation at higher concentrations, suggesting that downstream pathway balance or enzyme capacity became limiting once precursor supply was relieved. Under controlled bioreactor conditions, lycopene titres increased from approximately 1 mg/L to nearly 25 mg/L, indicating that process conditions further modulate production performance, suggesting an additional contribution of process-dependent energy and redox constraints. CONCLUSION: Metabolic burden during heterologous lycopene production in P. putida is governed primarily by precursor availability rather than by limitations in general gene expression capacity. Regulatory properties of the vector system strongly influence pathway performance, while controlled cultivation conditions can further improve production by alleviating additional process-dependent constraints. Together, these findings provide a systematic framework for distinguishing constraint layers and guiding the optimisation of heterologous terpenoid production systems.

Lycopene↗
PubMed2025

Competition and cooperation: The plasticity of bacterial interactions across environments.

Bacteria live in diverse communities, forming complex networks of interacting species. A central question in bacterial ecology is whether species engage in cooperative or competitive interactions. But this question often neglects the role of the environment. Here, we use genome-scale metabolic networks from two different open-access collections (AGORA and CarveMe) to assess pairwise interactions of different microbes in varying environmental conditions (provision of different environmental compounds). By computationally simulating thousands of environments for 10,000 pairs of bacteria from each collection, we found that most pairs were able to both compete and cooperate depending on the availability of environmental resources. This modeling approach allowed us to determine commonalities between environments that could facilitate the potential for cooperation or competition between a pair of species. Namely, cooperative interactions, especially obligate, were most common in less diverse environments. Further, as compounds were removed from the environment, we found interactions tended to degrade towards obligacy. However, we also found that on average at least one compound could be removed from an environment to switch the interaction from competition to facultative cooperation or vice versa. Together our approach indicates a high degree of plasticity in microbial interactions in response to the availability of environmental resources.

Microbial Interactions↗