L-Tyrosine (L-Tyr) and its derivatives are high-value aromatic compounds with broad applications in food, pharmaceutical, and chemical industries. The traditional methods for producing these natural products through natural extraction and chemical synthesis are often limited by sustainability, efficiency, and environmental concerns. Advances in synthetic biology have enabled the construction of microbial cell factories for green and scalable production, with E. coli and yeast emerging as the preferred chassis organisms due to their well-characterized genetics and extensive toolkits. This review systematically summarizes the engineering strategies applied for the biosynthesis of L-Tyr and its derivatives in these hosts at the enzymatic, metabolic, and cellular levels. Focusing on tyrosol, p-coumaric acid, and L-3,4-dihydroxyphenylalanine (L-DOPA) as the key nodes, it highlights the cutting-edge advances primarily within the last five years. Finally, the review critically assesses the persistent challenges and future opportunities, offering a strategic roadmap to accelerate the biomanufacturing of L-Tyr-derived natural products.

The rise of antimicrobial resistance (AMR) constitutes a serious threat to global health. Environmental bacterial communities are a key reservoir of AMR genes (ARGs) that can spread to clinical pathogens. Biocides, which include broad-spectrum herbicides, can co-select for ARGs, posing a potential driver for AMR spread. Glyphosate, the world’s most widely used herbicide with known bactericidal properties, targets the shikimate pathway and may thus exert selective pressure favoring resistant bacteria, potentially elevating clinical AMR risk from a One Health perspective. We assessed glyphosate resistance in multidrug-resistant (MDR) species isolated from nosocomial infections. Furthermore, we investigated the relationship between glyphosate-resistant environmental species and clinically relevant MDR pathogens using whole-genome sequencing of environmental and clinical strains. Multidrug-resistant species from hospital-acquired infections exhibited high levels of glyphosate resistance. We established a link between glyphosate-resistant environmental species and typically MDR species common in nosocomial settings. Genomic analysis revealed that glyphosate resistance is partially independent of mutations in the target enzyme (5-enolpyruvylshikimate-3-phosphate synthase), suggesting the contribution of alternative mechanisms, such as efflux pumps. Our findings indicate that glyphosate exposure could favor the prevalence of bacteria associated with nosocomial infections and the rise of MDR clinical strains. This suggests that intensive glyphosate use may accelerate the dissemination of AMR. Consequently, the AMR dimension should be incorporated into the environmental risk assessment of biocidal products that are not used as antimicrobial agents.

Static metabolic regulation during microbial synthesis of polyphenolic compounds leads to tyrosol accumulation, inducing cellular toxicity and growth inhibition. Dynamic regulation effectively alleviates the imbalance between cell growth and production; yet, a tyrosol-responsive dynamic system for yeast adaptive regulation remains unreported. In this study, endogenous tyrosol-responsive promoters were mined via transcriptomics, and the optimal promoter PYOR153W was identified. Subsequently, a novel tyrosol-responsive biosensor composed of the responsive promoter and CRISPR/dSpCas9-VPR was designed to dynamically regulate green fluorescent protein (GFP) expression and hydroxytyrosol biosynthesis, respectively. This strategy successfully enhanced hydroxytyrosol production by 1.53-fold with negligible tyrosol accumulation. Furthermore, this dynamic system improved strain robustness during longer yeast fermentation periods, and the hydroxytyrosol titer increased to 4.26 g/L in a 5 L bioreactor. Our findings establish the first tyrosol-responsive biosensor in yeast and provide a framework for the efficient biosynthesis of high-value tyrosol derivatives.

Pseudomonas putida strain KT2440 is a crucial model organism for synthetic biology and bioengineering applications, yet there currently exists no comprehensive metabolomics database comparable to those available for other model organisms. This gap hinders the use of untargeted metabolomics for exploratory analyses in this system. We developed the P. putida metabolome reference database (PPMDB v1) to address this limitation by consolidating metabolite information from multiple sources and expanding coverage through computational predictions. The database was constructed by curating metabolites from BioCyc, BiGG, and other literature sources, then computationally expanding this collection using BioTransformer environmental transformation predictions to generate additional predicted metabolites. We enhanced the database's utility for molecular annotation in metabolomics studies by incorporating analytical properties including collision cross-sections, tandem mass spectra, and gas-phase infrared spectra. These analytical properties were gathered from existing measurement data or predicted using computational tools. We further augmented the database through inclusion of reaction information and pathway annotations, facilitating biological interpretation of metabolomics data. This publicly available resource fills a critical gap in P. putida research infrastructure, supporting metabolite annotation and biological interpretation in untargeted metabolomics studies and enabling in-depth exploratory analyses of this important synthetic biology platform at the molecular level.

Rapid expansion of viral sequence data demands classifiers that scale, track ICTV updates, and provide interpretable evidence. We present VPF-Class 2.0, an updated successor to VPF-Class, centred on the taxonomic classification, that retains marker-driven protein domain detection but replaces rule-based voting with a lightweight supervised model on per-genome marker-composition features. In controlled benchmarks, VPF-Class 2.0 achieves near-perfect family-level performance and strong genus-level accuracy while increasing confident annotation coverage. Under a practical confidence threshold (0.3), performance improves and matches or exceeds representative tools within shared taxonomic scopes. We further introduce an interpretability study that relates errors to the genus specificity of activated markers. Finally, we demonstrate applicability on large real-world viromes with consistent labels and substantial agreement with graph-based classifications. The implementation of VPF-Class 2.0 can be downloaded from https://github.com/luisvidalj/VPFClass2.git.

Plant growth is influenced by the composition of its associated microbiome. The inherent complexity and functional redundancy of natural plant microbiomes presents a formidable barrier to understanding the myriad biological interactions therein. Efforts have been made to develop synthetic microbial communities (SynComs) that can provide a rigorous and generalizable framework for the rational design of next-generation microbial products for sustainable agriculture. We test multiple strategies for stable, plant growth promoting SynCom design and evaluate the phenotypic and molecular impacts of a successful plant-SynCom interaction. We designed 4 distinct, reduced-complexity variants of SynCom SRC1 and assessed their capacities for colonization, stability, and plant growth promotion. To understand the impact on plant performance of our highest performing SynCom variant, we characterized the host's longitudinal transcriptional response to SynCom inoculation and corroborated the results with metabolomics analysis. The top performing SynCom stably colonized sorghum roots and rhizospheres, elicited plant growth promotion, and induced dynamic spatiotemporal gene transcription in sorghum roots and shoots defined by modulation of growth-defense tradeoff machinery and enhanced flavonoid production. The resultant reduced-complexity SynCom is a highly stable, soil-independent, plant growth promoting, and demonstrates the utility of colonization-based selection criteria, integrated with longitudinal transcriptomic and metabolomic characterization.

Understanding the social structure and evolutionary dynamics of microbial communities requires the identification and characterization of relevant mutant subpopulations. While Pseudomonas aeruginosa employs quorum sensing (QS) to coordinate population-wide behaviors, the social traits of many QS mutants remain poorly defined. In this study, we developed an iterative “targeted gene duplication followed by mutant screening” (TGD-MS) approach to systematically identify noncanonical QS cheater mutants. We discovered that a single-nucleotide mutation in rpoA, which encodes the α subunit of RNA polymerase (RNAP), produces a QS-deficient phenotype resembling QS-null mutants. This RpoA variant mutant exhibits characteristic features of social cheating, including a competitive growth advantage in mixed populations, impaired QS-dependent virulence factor production, and attenuated pathogenicity. Structural and biochemical analyses revealed that the RpoA variant impairs RNAP binding to the promoters of core QS genes (lasI and lasR), leading to diminished QS activity. Further examination of natural RpoA variants uncovered a spectrum of QS-related phenotypes, suggesting that RpoA has a dual regulatory role in QS control. Within the C-terminal domain (α-CTD) of RpoA, we identified two distinct functional determinants that, through adaptive mutations, can acquire opposing regulatory effects on QS. This enables an environmentally dependent phenotypic switch between cooperation and cheating. Our discovery of noncanonical RpoA-mediated QS cheaters expands the framework of bacterial social evolution, demonstrating that mutations outside the canonical QS circuitry can disrupt cooperative behaviors. These findings underscore how core transcriptional machinery can be evolutionarily co-opted to modulate complex social interactions in dynamic environments.

Phosphorus (P) is an essential nutrient for plant growth but the global supply is limited, and over-reliance on chemical phosphate fertilizers can lead to soil pollution and ecological imbalance. Phosphate-solubilizing bacteria (PSB) can convert insoluble P in the soil into plant-available forms and enhance the P utilization efficiency of crops. The application of PSB can also improve the soil ecological environment and contribute to the sustainable development of agriculture. This review systematically summarizes the diversity and distribution of PSB. It comprehensively investigates the mechanisms through which PSB enhance soil P utilization efficiency, focusing on the following aspects: the acid-mediated solubilization of inorganic P, the enzymatic hydrolysis of organic P, the interactions between PSB and plant roots, and the interactions between PSB and rhizosphere microorganisms. Furthermore, recent advances in the development and application of PSB-based biofertilizers are also reviewed. Potential future research directions and the anticipated challenges within this field are also discussed, to develop innovative strategies for alleviating P deficiency in agricultural soils.

Throughout their life cycle, animal protein production processes generate 15–24% of global greenhouse gas emissions and consume 29% of the total water footprint of the agricultural sector worldwide. While it has been acknowledged that alternative proteins (plant, microbial, and insect proteins) can lessen the damage that animal proteins cause to the environment, the possible sustainability-related risks associated with the alternative protein processing technologies currently are still obvious, which could be eliminated through low-carbon technological innovations. Here, we examine the recent technological developments and future directions for accelerating the green transition that aim to address these issues in a cradle-to-grave fashion, with particular attention on whole-component utilization and waste-to-protein conversion pathways, while focusing on sustainability challenges and solutions within a circular bioeconomy framework. Their impacts on the Sustainable Development Goals in the United Nations Agenda 2030 were further discussed, particularly with regard to natural resources, energy, and environmental impacts.