Peptaibols are linear fungal peptides featuring α,α-dialkylated amino acids (e.g., α-aminoisobutyric acid (Aib), isovaline (Iva)) and characteristic C-terminal alcohol groups. Despite their promising antibacterial and antiplasmodial activities, detailed biosynthetic studies remain limited. A genome-guided study of the fungus Trichodema sp. SK1-7, isolated from decaying wood, revealed the production of previously described trichorozin IV (1), along with novel SF4-type peptaibol 2 (trichorozin V). The structures of these compounds were elucidated through MS analysis, NMR study and advanced Marfey’s method. The genome of Trichoderma sp. SK1-7 harbors two PKS-NRPS hybrid gene clusters containing 14 and 18 adenylation domains. Analysis of the modular architecture suggested that trichorozins are synthesized by a 14-module protein via a module skipping mechanism. Genome mining revealed several types of short peptaibol synthase architectures (10–14 adenylation domains) across various Trichoderma species, accompanied by similar long peptaibol synthases. Furthermore, putative Aib/Iva biosynthesis machinery in Trichoderma was identified, showing specific architectures potentially involved in regulating peptaibol biosynthesis. Feeding experiments demonstrated that peptaibol production depends on the ratio of Iva/Aib. The isolated compounds exhibited moderate antibacterial and cytotoxic activities along with a synergistic effect when combined with membrane-targeting antibiotics. Our findings suggest that genome-guided approaches hold promise for further development of peptabiotics with a wide range of applications, including antibiotic adjuvants.

The Oxford Nanopore platform and nanopore sequencing are gaining increasing popularity in modern metagenomic research. However, there is a limited set of dedicated tools for analyzing this type of data. The tools used for nanopore amplicon sequencing data analysis often provide only taxonomy annotation without OTU sequence assembly. Conversely, tools that facilitate OTU assembly are constrained in their analysis to long reads, such as the V1–V9 regions of 16S rRNA for bacterial community studies or the full-length ITS cluster (ITS1–5.8S–ITS2) for fungal community studies. In other cases, researchers propose their own solutions without dedicated tools. In this paper, we present Pike, a novel tool for analyzing Oxford Nanopore amplicon sequencing data. Pike allows analysis without amplicon size limitations and allows de novo assembly of OTU sequences. In our research, we created mock communities of fungi and bacteria, which we then used to demonstrate the efficiency of our algorithm. Furthermore, we validated the algorithm using externally available data. We also compared our approach with similar ones to show its applicability.

Background: Periodontitis is a chronic inflammatory disease mostly associated with Porphyromonas gingivalis infection and characterized by progressive destruction of the supporting structures of the tooth, including the gingiva, periodontal ligament and alveolar bone. However, the impact of other members of the periodontal microbiome on stage of the severity of the periodontitis remains largely uncharacterized. Methods: This exploratory study employs whole-genome shotgun (WGS) metagenomics to characterize the periodontal microbiome in patients suffering from mild and severe periodontitis, aiming to identify microbial signatures linked to disease severity via analysis of taxonomic composition, predicted metabolic pathways and metagenome-assembled genomes (MAGs). After initial selection, 28 adult patients with a computer tomography (CT)-confirmed diagnosis of mild and severe stage of periodontitis from 2 clinics were included in the research project. Results: Taxonomic analysis confirms the presence of various commensal and pathogenic bacteria detectable at the species level, especially belonging to so-called “red, orange and green periodontal complexes”—P. gingivalis, T. forsythia, C. rectus, and Capnocytophaga spp. that may contribute to disease heterogeneity. The conducted investigation suggests that non-microbial factors such as cardiovascular diseases and antibiotic usage in the last 6 months prior to the hospital admission could explain variance of disease progression and impact on severity. Analysis of microbial functional composition revealed metabolic traits showing positive correlations with severe stage of periodontitis. Robust network analysis suggested interactions between pathogenic bacteria of the red complex and other members of the periodontal microbiome. Conclusions: These findings underscore the multifactorial nature of periodontitis pathogenesis, highlighting the need for integrated approaches combining microbial, host, and environmental data to unravel drivers of disease progression. The study provides a foundation for future large-scale investigations into personalized diagnostic or therapeutic strategies.

Pseudomonas aeruginosa is a model organism for biofilm formation research, as it forms biofilms under diverse environmental conditions. At the same time, numerous studies have reported impaired‐biofilm formation in clinical isolates; however, the genetic basis of these impairments remains unexplored. In this study, we assessed the ability of P. aeruginosa clinical isolates from a laboratory collection to form biofilms. Among these isolates, three demonstrated biofilm formation impairment. A comparative genomic analysis revealed genetic determinants associated with biofilm formation impairment, including mutations in the pelA and fleQ genes, and psl operon deletion. Interestingly, the identified loss‐of‐function mutations in regulatory genes involved in biofilm formation did not appear to affect the ability to form biofilms.

Histone H2A is capable of delivering transgenic DNA into mammalian cells in vitro. Its ability to deliver DNA in vivo is unknown as yet, but the factors that affect the efficiency of in vivo delivery...