Bacteria

Extracellular vesicles, encompassing eukaryotic exosomes and bacterial outer membrane vesicles (OMVs), play multifaceted roles in mediating host–pathogen interactions. These nanoscale structures act as critical mediators of intercellular communication, transporting diverse bioactive cargo such as miRNAs, cytokines, proteins, and bacterial components. Exosomes contribute to host immunity by delivering antimicrobial agents and modulating inflammatory responses, but they can also be hijacked by pathogens to suppress defenses and promote persistent infection. OMVs, on the other hand, enable bacteria to disseminate virulence factors, deliver toxins directly into host cells, and modulate immune signaling. For example, exosomes from infected macrophages can stimulate dendritic cell activation and T-cell priming, whereas bacterial OMVs have been shown to suppress host immunity or trigger excessive inflammation depending on their molecular cargo. Importantly, OMVs facilitate horizontal gene transfer and nutrient exchange within microbial communities, thereby influencing microbiome composition and adaptation. Together, these complex dynamics position both exosomes and OMVs as central players in immunity and pathogenesis. This review synthesizes recent insights into how host- and pathogen-derived vesicles modulate infection biology and immune responses, while also exploring their potential as diagnostic biomarkers and therapeutic carriers, and discussing current limitations in their clinical translation.

Toxin–antitoxin (TA) modules represent sophisticated regulatory networks that have evolved from simple plasmid maintenance factors into multifunctional genetic modules orchestrating bacterial stress responses, pathogenesis, and ecological adaptation. This review highlights a compelling correlation between the abundance of toxin–antitoxin (TA) modules and bacterial pathogenicity, as exemplified by Mycobacterium tuberculosis (M.tb), which encodes 118 TA loci—significantly more than the fewer than 10 found in closely related saprophytic species. The clinical significance of TA modules extends beyond traditional stress response roles to encompass antimicrobial persistence, where systems like VapBC and MazEF facilitate dormant subpopulations that survive antibiotic therapy while maintaining chronic infections. Recent discoveries have revealed TA modules as sophisticated bacterial defense mechanisms against bacteriophage infection, with DarTG and ToxIN systems representing novel antiviral immunity components that complement CRISPR-Cas and restriction–modification systems. The immunomodulatory capacity of TA modules demonstrates their role in host–pathogen interactions, where systems such as VapC12 in M.tb promote macrophage polarization toward permissive M2 phenotypes while inducing anti-inflammatory cytokine production. Large-scale genomic analyses reveal that TA modules function as drivers of horizontal gene transfer networks, with their signatures enabling accurate prediction of plasmid community membership and serving as determinants of microbial community structure. The biotechnological applications of TA modules have expanded to include genetic circuit stabilization, biocontainment device construction, and multi-species microbial community engineering, while therapeutic strategies focus on developing multi-target inhibitors against conserved TA protein families as promising approaches for combating drug-resistant bacterial infections. The evolutionary conservation of TA modules across diverse bacterial lineages underscores their fundamental importance as central organizing principles in bacterial adaptation strategies, where their multifunctional nature reflects complex selective pressures operating across environmental niches and host-associated ecosystems. This review provides an integrated perspective on TA modules as dynamic regulatory elements that support bacterial persistence, immune evasion, and ecological versatility, establishing them as genetic elements with truly “many faces and functions” in prokaryotic biology.

Escherichia coli LS5218 is an attractive host for producing polyhydroxybutyrate. The strain, however, strongly requires heterologous gene expressions like phaC for efficient production. For enhancing the production, the whole gene expressions relating to end product-producing flow should be optimized so that not only heterologous induced-genes but also other relating genes are comprehensively analyzed on the transcription levels, resulting in normally time-consuming mutant-creation. Additionally, the explanation for each transcriptional relationship is likely to follow the relationships on known metabolic pathway map to limit the consideration. This study aimed to infer gene regulatory networks within glycolysis, a central metabolic pathway in LS5218, using machine learning-based causal discovery methods. To construct a directed acyclic graph representing the gene regulatory network, we employed the NOTEARS algorithm (Non-combinatorial Optimization via Trace Exponential and Augmented lagRangian for Structure learning). Using transcription data of 264 time-resolved sampling points, we inferred the gene regulatory network and identified several distal regulatory relationships. Notably, gapA, a key enzyme controlling the transition between the preparatory and rewarding phases in glycolysis, was found to influence pgi, the enzyme at the pathway’s entry point. These findings suggest that inferring such nonlocal regulatory interactions can provide valuable insights for guiding genetic engineering strategies.