Eight complete Salinivibrio genomes from Pearse Lakes are generated using Oxford Nanopore long-read sequencing and seven putative depolymerases that form a single accessory cluster in 15% of strains are identified, showing that annotation-dependent approaches can overlook genomic diversity and divergent enzyme families in non-model organisms.
Abstract
Abstract Current understanding of genomic diversity within the halophilic genus Salinivibrio relies predominantly on draft genomes, with only seven complete genomes among the 62 publicly available. Previous pangenome analysis suggested a closed genomic structure while concluding that Salinivibrio lacks polyhydroxyalkanoate (PHA) degradation capacity despite possessing biosynthesis genes. Here, we present eight complete Salinivibrio genomes from Pearse Lakes (Rottnest Island, Western Australia) generated using Oxford Nanopore long-read sequencing, alongside re-analysis of 38 high-quality public genomes (≥90% completeness and ≤5% contamination cut-off). Pangenome analysis revealed a more open structure than previously reported, with a core genome comprising 25% of total gene clusters and an accessory genome accounting for 71%. Panstripe analysis demonstrated significant temporal signal in gene gain and loss events associated with phylogenetic branch length (core: P=1.72×10⁻⁴; tip: P=2.64×10⁻¹⁴). All 46 genomes contained complete PHA biosynthesis operons (phaB-phaA-phaP-phaC) with high sequence conservation under strong purifying selection (Z=30.30, P<0.001). In a genome that readily gains and loses genes, this conservation indicates that PHA synthesis is a maintained pathway, which is difficult to reconcile with a previous report that Salinivibrio lacks PHA degradation capacity. We therefore searched the genomes by Hidden Markov Model-based homology rather than standard annotation and identified seven putative depolymerases that form a single accessory cluster in 15% of strains, all previously annotated as 3-oxoadipate enol-lactonase-2. These candidates retained all catalytic residues characteristic of active depolymerases but are divergent from reference PHA depolymerases which could explain why annotation missed them. They remain putative and require biochemical confirmation. Both the expanded pangenome and these candidates emerged from standardized homology-based re-analysis, showing that annotation-dependent approaches can overlook genomic diversity and divergent enzyme families in non-model organisms. Together, these results establish Salinivibrio as a genomically dynamic genus with potential for halophilic bioplastic production.
A genomic framework for understanding the high glycosphingolipid-producing capacity of NKG400013 is established and insights into the evolutionary diversification of sphingolipid metabolism in green algae are provided.
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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.
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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).
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