Refining Salinivibrio pangenome dynamics and biotechnological potential through comparative analysis

Genome analysis of the glycosphingolipid-producing green alga Tetraselmis sp. NKG400013.

Microalgae are gaining attention as sustainable resources for the production of valuable compounds, including biofuels, pigments, and bioactive metabolites. To support metabolic engineering and genome editing approaches aimed at enhancing these traits, high-quality genome assemblies are essential; however, genomic information remains limited for many microalgal lineages. Tetraselmis sp. NKG400013 is a green alga known for high glycosphingolipid accumulation with distinctive structural features. Here, we report a draft genome assembly of this strain generated using PacBio HiFi sequencing and transcriptome-supported annotation. The assembled genome spans 423.7 Mbp, with 74.5% repetitive sequences and 15,322 predicted protein-coding genes. Comparative analyses across 11 green algal species revealed a positive correlation between genome sizes and repeat contents, indicating that transposable element expansion, particularly long terminal repeat retrotransposons, has substantially contributed to genome enlargement in Tetraselmis. Genome-wide functional annotation and ortholog inference identified core enzymes required for glycosylceramide biosynthesis. Both sphingolipid Δ4 and Δ8 desaturases were identified in Tetraselmis. and their coexistence suggests an expanded capacity for long-chain base modification that may underlie its distinctive glycosphingolipid profile. These results establish a genomic framework for understanding the high glycosphingolipid-producing capacity of NKG400013 and provide insights into the evolutionary diversification of sphingolipid metabolism in green algae.

Pangenome Dynamics and Functional Diversification in the Marine Genus Pseudoalteromonas: Association to Colony Pigmentation

Pseudoalteromonas species are ecologically versatile marine bacteria widely recognized for their capacity to synthesize diverse bioactive metabolites and psychrophilic enzymes with biotechnological relevance. Here, we present a comprehensive comparative genomic analysis of 53 reference genomes to elucidate the dynamics, functional diversity, and biosynthetic potential of this genus. Reference genomes representing each deposited species were selected in order to avoid bias associated with unequal numbers of genomes per species. Pangenome reconstruction revealed an open structure comprising a small core genome (1,350 gene families) and a large proportion of accessory and strain-specific genes, reflecting extensive genomic plasticity. Functional annotation indicated that accessory regions are enriched for genes involved in secondary metabolism, stress adaptation, and environmental resilience. Notably, biosynthetic gene cluster (BGC) mining uncovered a rich repertoire of potentially novel RiPPs and other secondary metabolite clusters, underscoring Pseudoalteromonas as a promising source of unexplored bioactive compounds. Statistical analyses revealed that pigmented strains harbor significantly higher numbers of BGCs compared to non-pigmented strains, while only a weak and non-significant correlation was observed between BGC abundance and carbohydrate-active enzyme (CAZyme) content. No significant effect of the isolation source was detected on either BGC or CAZyme distributions. Together, these findings provide new insights into the genomic basis of ecological adaptation and metabolic diversification in Pseudoalteromonas, supporting the role of pigmentation as a proxy for enhanced biosynthetic potential, while carbohydrate utilization capabilities evolve more independently and offering a framework for targeted bioprospecting of marine-derived metabolites with industrial and environmental applications.

Genomic exploration of Serratia rubidaea MJ24 uncovers diverse biosynthetic capacity and agricultural relevance

Annotation of glycoside hydrolases in unassembled metagenomes using CAZyOGH

Abstract Motivation Functional characterization of microbiomes often relies on the sequencing of metagenomic DNA extracted from environmental samples, with current approaches using metagenome-assembled genomes (MAGs). Although glycoside hydrolases (GHs) are central to carbon cycling, accurate annotation of GHs in metagenomic datasets remains challenging due to the multidomain architecture of carbohydrate-active enzymes and the prevalence of unassembled short reads due to limitations in the MAG-generation process. Results Here, we present CAZyOGH (CAZymes Open-source GH annotation), a curated reference database for the domain-specific identification of 135 protein domains spanning 99 GH families with well-defined catalytic domain signatures. CAZyOGH focuses on individual GH domains, enabling robust annotation of both assembled and unassembled metagenomic data. We validated CAZyOGH by reanalyzing genomes listed in CAZy db, where predicted GH profiles closely matched reported values. Next, we used CAZyOGH to analyze 12 human gut metagenomes and 12 newly sequenced soil microbiomes to reveal environment-specific GH repertoires. By accurately detecting catalytic domains independent of the genomic context, CAZyOGH improves sensitivity and specificity in short-read metagenomic annotation. This framework provides a scalable and reproducible approach to investigate carbohydrate-active enzymes across ecosystems, advancing our capacity to characterize microbial functional potential in global carbon cycling. Availability and implementation CAZyOGH data is available on figshare (https://figshare.com/projects/CAZyO_GH/267770).

Decoding the genome of the basidiomycetous yeast Vishniacozyma victoriae D19: a promising fungal model for biotechnology.

BACKGROUND Vishniacozyma victoriae is a ubiquitous yeast isolated from various regions across the globe, especially in extreme environments. It can produce several interesting extracellular compounds, including carotenoids and cold-active hydrolytic enzymes, that confer high potential for industrial production and biotechnological applications. However, insufficient knowledge in its biology, genetics and genomics are the primary obstacle of its development as a new chassis. The aim of this study was to provide a high-quality genome assembly and an in-depth genome analysis of V. victoriae strain D19. RESULTS We isolated V. victoriae D19 (CBS 19383) from Trondheimfjordens, Norway. Here we present its high-quality genome assembly, along with comprehensive structural and functional annotation of the genome. The assembly consists of 10 nuclear scaffolds with a cumulative size of 18.1 Mb, an N50 value of 1.7 Mb (L50 = 3) and a complete circular mitochondrial genome. A total of 7,853 protein-coding genes were predicted. Intron structure and other features, such as rRNA, tRNA, transposable elements, telomeric repeats were also analyzed to contribute to a deeper understanding of the V. victoriae genome architecture. Functional gene annotation, performed using the go-FAnnoT and BlastKOALA tools, enabled the reconstruction of key metabolic pathways, providing potential functions for 6,434 and 3,626 proteins, respectively. Moreover, the analysis of protein targeting and in silico secretome analysis, followed by CAZymes identification, helped us to understand the metabolic potential of this yeast. CONCLUSION These genomic resources establish a valuable foundation for future functional studies and provide keys for developing a new chassis for potential industrial applications.

Defining the ESKAPE pathogen prophage repertoire with PHORAGER

Prophages are major drivers of bacterial evolution, mediating horizontal gene transfer and lysogenic conversion to alter host phenotypes. Nevertheless, identifying prophages within bacterial genomes remains challenging due to their heterogeneity and similarity to other mobile genetic elements. Here we present PHORAGER (Prophage Hunting, vOtu Retrieval, Annotation and Genomic ExploRation), a scalable Nextflow pipeline for the standardised identification and quality assessment of prophages from bacterial genomes. PHORAGER incorporates bacterial genome pre-processing, consolidation of predictions from multiple mining tools, annotation-based filtering to reduce false positives, and generation of ready-to-analyse summary tables. We validated PHORAGER using 30,824 publicly available ESKAPE pathogen genomes. PHORAGER recovered more high-quality prophages than individual mining tools alone, and through extensive quality assessments removed a substantial number of false-positive predictions. In total 23,132 putative prophages were identified, the majority belonging to the class Caudoviricetes, and exhibiting a high degree of host-specificity. Putative antimicrobial resistance genes were detected in 0.48% of prophages, whereas virulence factors were most abundant in S. aureus prophages. ESKAPE prophages also frequently encoded anti-phage defence systems. PHORAGER is freely available as open-source software and the ESKAPE prophage collection generated in this study provides a reusable resource for further investigations. GRAPHICAL ABTRACT