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Programmable enzymes for targeted gene insertion.

Genome editing technologies have advanced from nuclease-based reagents that generate programmed DNA double-strand breaks, which can cause deleterious effects, to next-generation reagents that perform controlled DNA modification through double-strand break-independent mechanisms, such as base editing and prime editing. Although these approaches enable precise small-scale sequence changes, methods for programmable insertion of large DNA cargos have been limited. The ability to write entire genes or large regions into the genome could transform the treatment of genetically heterogeneous disorders, for which numerous pathogenic variants underlie a common disease and mutation-specific editing strategies are impractical. Recent advances in computational genome mining have accelerated the discovery of naturally occurring enzymes with novel biochemical and functional properties, including recombinases and transposases capable of large-scale modifications. Moreover, directed evolution, rational engineering and expanded homologue discovery are enabling the repurposing and optimization of these systems for genome engineering. Here we review recent technology development efforts that harness diverse enzymes for kilobase-scale genome engineering, with a particular focus on CRISPR-associated transposase systems.

Journal Article↗

Accurate serotype identification of Streptococcus pneumoniae using nanopore Cas9-targeted serotype identification (nCATSerotyping).

Streptococcus pneumoniae (pneumococcus) is a leading cause of community-acquired pneumonia and invasive diseases, particularly among children and the elderly. The introduction of pneumococcal conjugate vaccines has significantly reduced invasive pneumococcal disease, but the prevalence of non-vaccine serotypes and newly emerging serotypes is increasing globally. Thus, accurate serotyping is essential for epidemiological surveillance and the development of next-generation multivalent pneumococcal vaccines. Conventional serotyping methods, including multiplex polymerase chain reaction (mPCR), monoclonal antibody (mAb) assays, and Quellung reaction using rabbit antisera, are limited by serotype coverage and cross-reactivity, making the detection of new or emerging serotypes challenging. In this study, we developed a nanopore Cas9-targeted serotyping (nCATSerotyping) platform, which employs Cas9-mediated enrichment of the capsular polysaccharide synthesis locus followed by Oxford Nanopore sequencing. Applying this method to 276 clinical pneumococcal isolates collected in South Korea (2018-2020), we achieved a serotyping success rate of 97.10% (268/276), significantly outperforming conventional methods such as mAb and mPCR, which identified only 76.45% (211/276) of isolates. Whole-genome sequencing of the remaining eight non-typeable isolates revealed them to be non-pneumococcal (oral streptococci), confirming 100% accuracy for S. pneumoniae serotyping. Importantly, our method identified emerging and underrepresented serotypes, including serotype 13 and null capsule clade strains. nCATSerotyping offers a rapid, accurate, and comprehensive solution for pneumococcal serotyping, with significant advantages in identifying novel and non-typeable strains. This scalable platform will be a valuable tool for global serotype surveillance and next-generation multivalent pneumococcal vaccine development.IMPORTANCEAccurate pneumococcal serotyping is critical for vaccine development and epidemiological surveillance, particularly as non-vaccine serotypes emerge following widespread pneumococcal conjugate vaccine implementation. Current serotyping methods face significant limitations in coverage and accuracy, identifying around 76% of pneumococcal isolates and failing to detect emerging serotypes like serotype 13 and null capsule clades. The nanopore Cas9-targeted serotyping platform addresses these critical gaps by achieving 100% serotyping accuracy for confirmed Streptococcus pneumoniae isolates while identifying previously undetectable strains that conventional methods missed. This comprehensive approach is essential for monitoring vaccine effectiveness, understanding serotype replacement patterns, and informing next-generation vaccine development strategies. Furthermore, the identification of misclassified oral streptococci highlights the diagnostic precision needed for accurate pneumococcal surveillance, ensuring that epidemiological data accurately reflect true pneumococcal disease burden and serotype distribution patterns.

Streptococcus pneumoniae↗

An Acetyltransferase Conferring Self-Resistance of the Producer to Lasso Peptide Antibiotic Lariocidin.

The soil microbiome, a reservoir of antibiotic-producing bacteria, also harbors resistance determinants encoded within antibiotic biosynthetic gene clusters (BGCs). Studying self-resistance mechanisms, which have evolved in producers to protect against their own toxic metabolites, provides critical insights into the evolution of resistance and the potential vulnerabilities of new antibiotics and can facilitate the production of natural products in heterologous hosts. Here, we describe the self-resistance mechanism to lariocidin (LAR), a recently discovered lasso peptide antibiotic that inhibits the ribosomal machinery and exhibits antibacterial activity against key pathogens. We identified and characterized an N-acetyltransferase enzyme (LrcE) encoded within the LAR BGC that mediates self-resistance in LAR-producing Paenibacillus sp. M2. LrcE is a member of the GCN5-related N-acetyltransferase (GNAT) superfamily and performs site-specific acetylation of LAR at a critical lysine residue. This modification disrupts ribosomal binding, thereby reducing LAR's antibacterial activity. Using in silico modeling, we predicted a conserved acetyl-CoA-binding motif and an LAR-binding region on LrcE. Bioinformatic analysis revealed LrcE homologues in environmental but not clinically relevant pathogens, suggesting a limited risk of horizontal gene transfer and, therefore, supporting the further development of LAR as a next-generation antibiotic.

Anti-Bacterial Agents↗

Molecular biology and integrated strategies for activating cryptic biosynthetic gene clusters toward next-generation antibiotic discovery.

Antimicrobial resistance (AMR) has been identified as one of the 21st century's severest global public health crises. AMR led to an estimated 4.95 million deaths in 2019 and will claim 10 million lives a year by 2050 in the absence of targeted interventions. During the same period, the number of novel antibiotics discovered has decreased drastically as many researchers are rediscovering known antibiotics, non-model microorganisms are poorly understood or difficult to culture and antibiotic research and development investment has declined drastically. However, high-throughput whole genome sequencing and the subsequent application of bioinformatics in bacterial and fungal genomes have shown that a numerous of cryptic or silent biosynthetic gene clusters (BGCs) remain latent at ambient laboratory conditions since their genes are transcriptionally inactive. Cryptic BGCs represent a vast source of unique secondary metabolites, many of which may yield novel antibacterial, antifungal, anti-cancer and other potentially valuable natural products. This review discusses the biological relevance of cryptic BGCs, the major limiting factors that restricts their activation and novel strategies that have been employed to activate them and exploit their potential to produce novel natural products. The review focuses on biological approaches including CRISPR-Cas mediation for the activation of cryptic BGCs, promoter engineering, pathway refactoring, and heterologous expression; biochemical strategies such as Osman, OsMAC, Precursor Feeding, Chemical Elicitation, Epigenetic Regulation and Co-cultivation and technology-based strategies such as Genome mining, Microfluidic Cultivation systems, High-Throughput Screening, Metabolomics, Molecular Networking and Artificial Intelligence and Machine Learning based prediction of BGCs and their metabolites. The use of multi-omics technologies combined with synthetic biology to achieve better discovery, characterization and large-scale production of novel natural products is also discussed herein. Finally, we will talk about the ecological significance and evolutionary advantage of cryptic BGCs' role in interactions between microorganisms, such as competition, communication, symbiosis and environmental adaptability, so as to provide a useful background for accelerating next-generation antibiotics.

CRISPR-Cas activation↗

Endogenous CRISPR-Based Removal of Tetracycline Resistance in Bifidobacterium animalis subsp. lactis Through a Safe-by-Design Approach.

Bifidobacterium animalis subsp. lactis is widely used as a probiotic; however, the presence of the tetracycline resistance gene tetW raises safety and regulatory concerns due to its potential mobility within the gut microbiome. Here, we applied a Safe-by-Design strategy using the endogenous CRISPR-Cas system of B. animalis subsp. lactis BLC01 to inactivate tetW through the introduction of premature stop codons. Whole-genome sequencing confirmed the intended editing and excluded relevant off-target effects. tetW inactivation markedly reduced the tetracycline minimum inhibitory concentration, restoring susceptibility below the tetracycline cut-off value for bifidobacteria (8 μg/mL). Comparative phenotypic analyses demonstrated that the edited strain (BLC01-2F3G10) retained key probiotic traits, including tolerance to acid, bile, and osmotic stress, exopolysaccharide production, aggregation capacity, survival during simulated gastrointestinal digestion and adhesion to intestinal epithelial cells. Importantly, no reversion to tetracycline resistance was observed after prolonged exposure to sub-inhibitory minimal selective antimicrobial concentration, indicating genetic stability of the edited phenotype. Collectively, these findings demonstrate that endogenous CRISPR-based genome editing can be leveraged to selectively remove antimicrobial resistance determinants from probiotic strains while preserving functionality, supporting the development of next-generation probiotics with an improved safety profile and reduced potential for antimicrobial resistance dissemination in the human gut.

Tetracycline Resistance↗

Tracking the shifting landscape of SARS-CoV-2 variants in Lebanon among healthcare workers and hospitalized patients.

UNLABELLED: Genomic surveillance of SARS-CoV-2 is critical for tracking viral evolution and informing public health responses. This study characterized variants circulating among healthcare workers (HCWs) and hospitalized patients in Lebanon between January 2022 and September 2024. A total of 530 SARS-CoV-2-positive nasopharyngeal swabs were collected from five Lebanese governorates and subjected to whole-genome sequencing. Correlations between variant circulation and a number of demographic and clinical variables were assessed. Most HCWs were female (64%), young adults (20-30 years, 39%), and had no comorbidities (97%). In contrast, hospitalized patients were mostly older adults (>60 years, 55.6%) with underlying conditions (77%). Early 2022 was marked by BA.1- and BA.2-like Omicron variants, followed by the predominance of BA.5-like lineages. In 2023, recombinant XBB sublineages became widespread. By 2024, these were largely replaced by next-generation variants, including JN.1 and KP.3.1.1. Despite differences in demographics and exposure risk, both groups showed parallel variant evolution. These findings reflect global and regional patterns and highlight the dynamic nature of SARS-CoV-2 circulation in Lebanon. IMPORTANCE: This study provides a comprehensive snapshot of SARS-CoV-2 variant evolution in Lebanon between 2022 and 2024, focusing on healthcare workers and hospitalized patients. By combining genomic and clinical data, it reveals how successive Omicron subvariants emerged and spread within key population groups. The detection of diverse and evolving lineages, including XBB recombinants and next-generation variants such as JN.1, underscores the ongoing antigenic drift of SARS-CoV-2. These insights reinforce the value of continued genomic surveillance for pandemic preparedness, especially in regions where data remain limited. Understanding local variant dynamics can guide targeted vaccination strategies and health policy decisions.

Humans↗

Next-generation phylogeography reveals unanticipated population history and climate and human impacts on the endangered floodplain bitterling (Acheilognathus longipinnis).

BACKGROUND: Floodplains harbor highly biodiverse ecosystems, which have been strongly affected by both past climate change and by recent human activities, resulting in a high prevalence of many endangered species in these habitats. Understanding the history of floodplain species over a wide range of timescales can contribute to effective conservation planning. We reconstructed the population formation history of the Itasenpara bitterling Acheilognathus longipinnis, an endangered floodplain fish species in Japan, over a broad timescale based on phylogenetic analysis, demographic modeling, and historical demographic analysis using mitogenome and whole-genome sequences. A genome sequence was newly assembled as a reference for the resequencing analysis. This bitterling is distributed in three plains separated by high mountain ranges and exhibits ecological characteristics well adapted to floodplain environments. RESULTS: Our analyses revealed an unexpected population branching pattern, gene flow, and timing of the differentiation that occurred within a few hundred thousand years, i.e., long after the mountain uplift that was assumed to be the primary geological cause of the population differentiation. The analyses also showed that all local populations experienced a severe decline during the last glacial and post-glacial periods. CONCLUSIONS: Our results suggest that the floodplain bitterling was able to disperse through unknown routes after mountain uplift and that its populations were strongly influenced by climatic and geographic changes in glacial-interglacial cycles and subsequent human activities, probably related to its floodplain-dependent ecology. The genomic data highlight the unanticipated distribution process of this species and the magnitude of the impact of human activities, with important implications for its conservation.

Endangered Species↗

Developing low-carbon metered-dose inhalers: effects of propellant HFA-152a on mucociliary clearance and bronchoconstriction in two Phase 1 randomised trials.

BACKGROUND: To reduce the impact of respiratory care on climate change, metered-dose inhalers (MDIs) are being reformulated with low-global warming potential (GWP) propellants. Next-generation propellant hydrofluoroalkane (HFA)-152a has >90% lower GWP than HFA-134a. As part of the safety evaluation for HFA-152a, mucociliary clearance (MCC), bronchoconstriction and safety were compared with HFA-134a. METHODS: Two Phase 1, randomised, two-way crossover studies (NCT06506266/NCT06702462) were conducted. MCC study: healthy participants inhaled HFA-152a and HFA-134a in two 7-day sequences. MCC was quantified as area under radiolabelled particle retention time curve over 4 h (AUC0-4h) after nebulised 99mTc sulphur colloid, following each propellant. Bronchoconstriction study: patients with mild asthma inhaled single doses of HFA-152a and HFA-134a. Non-inferiority of HFA-152a versus HFA-134a was defined as percent change in FEV1 (litres), 15 min post dose (95% confidence intervals [CI]: lower limit >-10%, upper limit >0%). Both studies assessed safety. RESULTS: In 22 healthy participants, the impact on MCC did not differ between HFA-134a and HFA-152a (AUC0-4h geometric mean ratio [90% CI]: 1.00 [0.99, 1.01]). In 19 patients with mild asthma, neither HFA-152a nor HFA-134a induced bronchoconstriction (percent change in FEV1 at 15 min: -0.37% [HFA-152a] vs -0.60% [HFA-134a]); HFA-152a was non-inferior to HFA-134a (mean difference [95% CI]: 0.23% [-3.61, 4.07]). Adverse event (AE) rates were low and similar for both propellants in both studies; all AEs were mild, with no serious AEs or deaths. CONCLUSION: HFA-152a and HFA-134a had almost identical effects on MCC, neither induced bronchoconstriction, supporting MDI reformulation with the low-GWP propellant HFA-152a.

Humans↗

Unlocking the unexplored AMPSphere in marine rare species.

BACKGROUND: Antimicrobial peptides (AMPs) have advantages over traditional antibiotics in fighting against drug-resistant bacterial infections. Natural microbial communities are considered as the priority targets for next-generation AMP bioprospecting initiatives. While progress has been made in characterizing AMPs from the dominant microbial taxa in natural ecosystems, current research largely overlooks the biosynthetic potential of rare species. Given their distinct evolutionary pressures, rare species likely produce AMPs with novel structures and unconventional mechanisms of action. RESULTS: In this study, enrichment cultivation of a marine biofilm was conducted in 138 carbon source- and oxygen level-based conditions, followed by metagenomic sequencing using both Illumina and Nanopore platforms. Analysis of 435 high-quality genomes derived from the metagenomes suggests that these bacterial strains are significantly underrepresented (<&#x2009;0.01%) in global marine biofilm communities. Through multi-model prediction, we identified 3,054,472 candidate AMPs from the genomes, including 1048 high-confidence ones, thereby significantly expanding the previously known AMPSphere. Furthermore, AMPs derived from the rare bacterial species exhibit unique sequence characteristics, structural diversity, remarkable stability under diverse pH conditions and pepsin exposure, and strong therapeutic potential in animal models, reflecting their specialized adaptive and defensive strategies developed within ecological systems. CONCLUSIONS: The features of the underexplored AMPs from low-abundance bacteria in marine biofilms provide valuable resources and theoretical foundations for the development of highly effective antimicrobial agents. Video Abstract.

Biofilms↗

A novel allele of Sh1 facilitates the development of waxy-sweet corn from waxy corn.

Waxy corn and sweet corn represent 2 major classes of fresh-eating corn, each with distinct sensory attributes and nutritional compositions. Developing a new variety that combines both waxy and sweet traits would address rising consumer demand and expand new market potential. From a fast neutron-mutagenized population of the waxy corn inbred line HB522, we isolated a novel mutant, designated as wx-sweet, whose kernels simultaneously exhibit waxy and sweet characteristics at the milk-filling stage. Through bulked segregant analysis combined with fine mapping, we mapped the causal locus to SHRUNKEN1 (Sh1) on chromosome 9, which was confirmed by an allelism test with a characterized Mu-insertion allele of Sh1. A 7,227-bp Copia-type long terminal repeat retrotransposon insertion was identified in exon 2 of Sh1 in the wx-sweet mutant by long-read sequencing. Consistently, the novel sh1 allele significantly reduced sucrose synthase activity. Genetic and physiological analyses demonstrate that sh1 and wx1 act synergistically to fine-tune carbohydrate metabolism in the endosperm. Integrated transcriptomic and metabolomic profiling uncover extensive transcriptional reprogramming and redirected metabolic flux, leading to substantial accumulation of sucrose and a range of oligosaccharides. These metabolic shifts underlie the unique simultaneous dual waxy-sweet texture in fresh-eating wx-sweet kernels. In summary, our work not only provides valuable genetic resources for breeding next-generation fresh-eating corn but also, for the first time, elucidates the molecular mechanism by which the sh1 and wx1 mutations cooperatively shape the waxy-sweet endosperm phenotype.

Zea mays↗

Imaging-Guided Omics Technologies for Resolving Rare Cancer States and Advancing Nanomedicine.

The ability to resolve rare and transient cellular states is critical for understanding metastasis, immune evasion, and therapy resistance in cancer, yet these dynamic processes often escape detection by conventional sequencing and imaging approaches. Recent advances at the interface of nanotechnology, high-resolution live-cell imaging, and single-cell/spatial multiomics methods have enabled functional profiling of cells with unprecedented precision within their native microenvironment. In this Mini-Review, we highlight emerging nanoscale platforms that couple real-time phenotypic imaging with molecular readouts, such as FUNseq and CIN-seq, to directly link functional heterogeneity to transcriptomic, proteomic, and epigenomic information. By integrating nanoscale optical imaging, microengineered perturbation tools, and AI-driven computational analysis, these technologies open up new avenues for dissecting rare metastatic, therapy-resistant, or immune-evasive subpopulations. We further discuss how these next-generation imaging-guided single-cell and spatial omics platforms not only advance fundamental cancer biology but also create opportunities to accelerate the development of nanomedicine applications.

Humans↗

Virus-induced gene silencing as a tool for functional genomics in weeds: Challenges and future directions.

Virus-induced gene silencing (VIGS) has evolved from a conceptual demonstration of antiviral defense into a pivotal reverse-genetics platform for plant functional genomics. By exploiting engineered DNA- or RNA-based viral vectors, VIGS enables rapid, sequence-specific transcript knockdown through RNA-mediated degradation of target transcripts. Recent refinements in vector design, inoculation strategies, and viral species selection, such as TRV, BSMV, and FoMV, have expanded its application to previously recalcitrant plants, including major crops and emerging weed models. In weeds, functional genomics remains particularly challenging due to high genetic variability, limited genomic resources, and incompatibility with conventional viral vectors and transformation systems. In this context, VIGS provides a tractable approach to investigate genes associated with herbicide resistance, metabolic adaptation, and stress tolerance. Beyond weed biology, its application to studies of immune signaling, hormonal crosstalk, and secondary metabolism highlights VIGS as a versatile biotechnology for elucidating gene function and supporting next-generation strategies in plant improvement and integrated pest management.

Journal Article↗

Multi-Omics and Integrative Analytics in Natural Products Discovery.

Natural products (NPs) have long been an essential source of new bioactive compounds for drug discovery; however, traditional methods for screening and isolating these compounds can be slow and often yield diminishing returns. Fortunately, advanced multi-omics and computational approaches present powerful solutions to these challenges. This review highlights innovative methodologies that integrate metabolomics, genomics, transcriptomics, and proteomics with bioinformatics and analytical chemistry to accelerate NP discovery. For instance, untargeted metabolomics platforms like high-resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS) and Global Natural Products Social (GNPS) molecular networking allow for comprehensive profiling of new compounds, while targeted isotope-labeling strategies enhance this process. Additionally, genome and metagenome mining tools such as antibiotics and secondary metabolite analysis shell (antiSMASH), Deep Biosynthetic Gene Cluster (DeepBGC), and Pipeline for Reconstructing Integrated Syntheses of Metabolites (PRISM) quickly identify biosynthetic gene clusters (BGCs) in both cultured and uncultured organisms, often using heterologous expression to validate products. Transcriptomic analyses, including RNA sequencing (RNA-seq), co-expression networks, and fluxomics, help clarify how pathways are regulated, while quantitative proteomics techniques like tandem mass tags/isobaric tags for relative and absolute quantitation (TMT/iTRAQ) and label-free methods, along with chemoproteomics approaches such as cellular thermal shift assay and thermal proteome profiling (TPP), uncover molecular targets and their mechanisms of action. This review also places significant emphasis on the role of artificial intelligence (AI) and machine learning (ML) in integrating multi-omics data, spanning activities from constructing gene-metabolite correlation networks to leveraging knowledge graphs and graph neural networks for data fusion and functional prediction. Finally, this review concludes by discussing the synergistic benefits of multi-omics for natural-product discovery, addressing current technical challenges, and exploring future directions toward high-throughput, intelligent data integration for next-generation NP research.

Biological Products↗

Plant cis-regulatory grammar: Decoding the multidimensional code of transcriptional regulation for programmable crop engineering.

Cis-regulatory elements (CREs) orchestrate the spatiotemporal precision of gene expression that underlies plant development, adaptation, and domestication. Decoding the cis-regulatory grammar of plant genomes remains a central challenge in modern biology, with profound implications for programmable crop engineering. Here, recent conceptual and technological advances are synthesized to reshape our understanding of plant CREs. This review first argues that CRE function is not only an intrinsic property of DNA sequence alone but also emerges from a multidimensional context, including chromatin accessibility, histone modifications, three-dimensional genome topology, and cell type-specific regulatory landscapes. Furthermore, the convergence of single-cell epigenomics, high-throughput functional assays, and CRISPR-based dissection has begun to unravel this contextual grammar, revealing the computational principles governing transcriptional regulation. Critically, we propose that artificial intelligence (AI) platforms are catalyzing an ongoing transition from descriptive discovery to predictive engineering, wherein these platforms outperform natural evolution in designing synthetic CREs. Finally, a roadmap is outlined toward a plant regulatory grammar foundation model, which will enable truly predictive engineering of gene expression when fine-tuned for specific tasks. Collectively, the integration of single-cell resolution maps, precise genome editing, AI-driven design, and regulatory-compliant delivery systems promises to transform our ability to reprogram plant gene regulation for next-generation agriculture, bridging the gap between foundational regulatory biology and tangible crop improvement.

artificial intelligence↗

Epigenetic Reprogramming and Zygotic Genome Activation in Human Preimplantation Development: Mechanisms, Models, and Translational Prospects.

PURPOSE: Early human embryogenesis unfolds through a tightly coupled sequence of events-clearance of maternal transcripts, remodeling of parental chromatin, zygotic genome activation (ZGA), lineage segregation, implantation, and post-implantation patterning-accompanied by epigenetic reprogramming, including X-chromosome dosage compensation around the time of implantation. This review aims to synthesize recent advances in understanding this developmental program and to consider their implications for reproductive medicine. METHODS: I review recent literature on human early embryogenesis, with particular emphasis on findings enabled by single-cell genomics and stem-cell-based embryo modeling, and integrate these insights to identify human-specific features of early development. RESULTS: These approaches have made previously inaccessible aspects of human early embryogenesis experimentally tractable, revealing molecular and epigenetic features that distinguish human development from that of model organisms, including species-specific dynamics of ZGA, maternal transcript clearance, chromatin reprogramming, and X-chromosome dosage compensation. CONCLUSIONS: Advances in single-cell genomics and embryo modeling are transforming our understanding of human early embryogenesis. Building on these insights, while recognizing their current limitations, I propose a vision for improving reproductive medicine, including the potential for next-generation embryo selection strategies.

Journal Article↗

Marine-Inspired Antimicrobial Peptides Disrupt Gene Expression at the DNA Level.

Genome mining of Streptomyces sp. H-KF8 combined with sequence engineering yielded two serum-stable, noncytotoxic, nonlytic antimicrobial peptides, L3 and L3-K. Initial studies in uropathogenic Escherichia coli suggested membrane effects and nucleoid relaxation, prompting a comprehensive investigation of their mode of action. In this study tandem mass tag (TMT)-based quantitative proteomics revealed extensive proteome remodeling, with 175 and 120 differentially expressed proteins (DEPs) after treatment with L3 and L3-K, respectively. L3 induced predominantly upregulated responses linked to metabolism, RNA processing, transport, and homeostasis, whereas L3-K mainly caused the downregulation of proteins involved in metabolism, transport, and cell structure. Both peptides disrupted ABC transporter-mediated nutrient uptake and elicited stress responses, while L3 specifically perturbed the mal regulon, indicative of broader transcriptional dysregulation. Complementary fluorescent dye displacement and in vitro transcription/translation assays demonstrated nonspecific DNA binding, stronger for L3 than L3-K, and potent inhibition of transcriptional and translational processes. Strikingly, inhibitory concentrations paralleled their minimum inhibitory concentrations, directly linking DNA binding and interference with central information processing to antimicrobial activity. These findings reveal that L3 and L3-K primarily act by targeting DNA and interfering with the transcription-translation machinery. Beyond offering mechanistic insights, this study underscores peptides' potential to act as scaffolds for next-generation antimicrobial peptides with DNA-binding and nonmembrane-lytic activity.

Antimicrobial Peptides↗

Proteome-wide curation of experimentally validated HPV T-cell epitopes identifies key gaps in our understanding of cellular immunity to HPV and informs vaccine design.

BACKGROUND: Human papillomavirus (HPV) drives both malignant and benign tumours. Current prophylactic vaccines are type-restricted, not optimised for T-cell induction, and lack therapeutic efficacy. Although T-cells are critical for both preventing and clearing HPV infection, experimentally validated HPV T-cell epitopes remain fragmented across the literature, limiting systematic evaluation of cellular immune targets. METHODS: We curated experimentally validated HPV T-cell epitopes from the Immune Epitope Database (IEDB). Epitopes were mapped across HPV proteins and genotypes, and analysed for response rate, sequence conservation across 454 representative HPV genomes, and HLA restriction patterns. RESULTS: 485 unique experimentally validated HPV epitopes have been described (133 studies; 1,494 functional assays). Consistent with research focus and viral biology, E6 and E7 proteins account for >60% of known HPV epitopes despite accounting for ~10% of the viral proteome. High-risk HPV types, especially HPV16 and HPV18, were the most studied (p&#xa0;<.001) and were enriched for CD8+ epitopes (p&#xa0;<.001). We identified major knowledge gaps, including: underrepresentation of structural proteins such as L2; limited epitope coverage for low-prevalence HPV genotypes; a bias towards common HLA alleles. In silico analysis indicated greater conservation of epitopes in L1/L2 and across high-risk HPV types. Conserved, commonly detected, and HLA-promiscuous epitopes were highlighted and we provide panels of candidate epitopes for consideration in immune monitoring, broad-spectrum prophylactic vaccines, and high-risk targeted therapeutic vaccines. CONCLUSION: This study provides the first comprehensive atlas of experimentally validated HPV T-cell epitopes and ranked epitope candidates for translational application. We demonstrate that our understanding of HPV T-cell immunity is constrained by biases in antigen, genotype and HLA focus and by incomplete epitope mapping. Addressing these gaps will be essential for a comprehensive assessment of cellular immunity and for utilising T-cells in next-generation vaccines.

Epitopes, T-Lymphocyte↗

Engineering extracellular vesicles for targeted siRNA delivery: Advances, therapeutic applications, and clinical translation.

Small interfering RNA (siRNA) therapeutics have emerged as a transformative approach for sequence-specific gene silencing, offering the potential to treat a broad spectrum of diseases by selectively suppressing disease-associated genes. However, the clinical translation of siRNA remains limited by rapid enzymatic degradation, poor cellular uptake, inadequate endosomal escape, and off-target effects, necessitating the development of efficient delivery systems. Extracellular vesicles (EVs) have gained considerable attention as natural nanocarriers owing to their excellent biocompatibility, low immunogenicity, intrinsic targeting capability, and ability to protect therapeutic cargo while traversing complex biological barriers. This review comprehensively discusses the biological characteristics of EVs, the molecular basis of RNA interference, and the major challenges associated with siRNA delivery [Fig. 1]. Recent advances in EV engineering, including cargo-loading strategies such as electroporation, sonication, extrusion, parent-cell engineering, and microfluidic approaches, together with surface functionalization using peptides, antibodies, aptamers, and hybrid nanoplatforms, are critically evaluated for improving targeting specificity and intracellular delivery. Furthermore, the therapeutic applications of engineered EV-mediated siRNA delivery in cancer, neurological disorders, liver diseases, cardiovascular diseases, inflammatory disorders, and infectious diseases are systematically summarized, highlighting their potential to enhance gene silencing while minimizing systemic toxicity. Current challenges related to large-scale manufacturing, cargo-loading efficiency, standardization, quality control, regulatory approval, and clinical translation are also discussed, together with emerging technologies involving synthetic biology, genome engineering, artificial intelligence, and multifunctional hybrid vesicles. Overall, engineered extracellular vesicles represent a highly versatile and biologically inspired platform for targeted siRNA delivery, providing a promising foundation for the development of next-generation precision RNA therapeutics and accelerating the clinical translation of gene-silencing strategies.

Extracellular vesicle engineering↗