Biology subjects

Gavriilidou, A.

Publications and source records attributed to Gavriilidou, A..

7 recordsLinked to original sources

bioRxiv2026

Distinct taxonomic groups of sponge symbionts have the biosynthetic capacity for the production of ether lipids

The marine sponge holobiont, composed of the sponge host and its microbial symbionts, is a known source of abundant and diverse ether lipids (ELs). Apart from their structural role in the cytoplasmic membrane of archaea and some bacteria, ELs have often been linked to signaling functions and defense against pathogens. Despite the relevance of ELs, their biosynthesis, as well as the identity of their producers, remain elusive. Here, we report the analysis of potential ether lipid producing genes and gene clusters, detected in marine sponge metagenomes as well as public sponge genomes. We show that the sponge holobiont has the capacity to synthesize ELs via several pathways, and suggest the ability of the sponge holobiont to synthesize ELs under different O2 levels. Finally, targeted lipidome analysis confirmed that ELs are present in the lipid profiles of all of the studied sponge holobiont samples, and indicates that the biosynthesis of the plasmalogens detected is likely restricted to the sponge host itself, based on the detected hydrocarbon chain lengths. This work provides a basis for the challenging quest to decipher intricate EL biosynthesis in marine sponges and their associated microbes.

microbiology↗

bioRxiv2025

PanBGC: A Pangenome-inspired framework for comparative analysis of biosynthetic gene clusters

AO_SCPLOWBSTRACTC_SCPLOWBacterial secondary metabolites are a major source of therapeutics and play key roles in microbial ecology. These compounds are encoded by biosynthetic gene clusters (BGCs), which show extensive genetic diversity across microbial genomes. While recent advances have enabled clustering of BGCs into gene cluster families (GCFs), there is still a lack of frameworks for systematically analysing their internal diversity at a population scale. Here, we introduce PanBGC, a pangenome-inspired framework that treats each GCF as a population of related BGCs. This enables classification of biosynthetic genes into core, accessory, and unique categories and provides openness metrics to quantify compositional diversity. Applied to over 250 000 BGCs from more than 35 000 genomes, PanBGC maps biosynthetic diversity of more than 80 000 GCFs. To facilitate exploration, we present PanBGC-DB (https://panbgc-db.cs.uni-tuebingen.de), an interactive web platform for comparative BGC analysis. PanBGC-DB offers gene- and domain-level visualizations, phylogenetic tools, openness metrics, and custom query integration. Together, PanBGC and PanBGC-DB provide a scalable framework for exploring biosynthetic gene clusters at population resolution and for contextualizing newly discovered BGCs within the global landscape of secondary metabolism.

microbiology↗

bioRxiv2024

Antiviral Mechanisms and Preclinical Evaluation of Amantadine Analogs that Continue to Inhibit Influenza A Viruses with M2 S31N-Based Drug Resistance

To better manage seasonal and pandemic influenza infections, new drugs are needed with enhanced activity against contemporary amantadine- and rimantadine-resistant influenza A virus (IAV) strains containing the S31N variant of the viral M2 ion channel (M2S31N). Here we tested 36 amantadine analogs against a panel of viruses containing either M2S31N or the parental, M2 S31 wild-type variant (M2WT). We found that several analogs, primarily those with sizeable lipophilic adducts, inhibited up to three M2S31N-containing viruses with activities at least 5-fold lower than rimantadine, without inhibiting M2S31N proton currents or modulating endosomal pH. While M2WT viruses in passaging studies rapidly gained resistance to these analogs through the established M2 mutations V27A and/or A30T, resistance development was markedly slower for M2S31N viruses and did not associate with additional M2 mutations. Instead, a subset of analogs, exemplified by 2-propyl-2-adamantanamine (38), but not 2-(1-adamantyl)piperidine (26), spiro[adamantane-2,2-pyrrolidine] (49), or spiro[adamantane-2,2-piperidine] (60), inhibited cellular entry of infectious IAV following pre-treatment and/or H1N1 pseudovirus entry. Conversely, an overlapping subset of the most lipophilic analogs including compounds 26, 49, 60, and others, disrupted viral M2-M1 protein colocalization required for intracellular viral assembly and budding. Finally, a pilot toxicity study in mice demonstrated that 38 and 49 were tolerated at doses approaching those of amantadine. Together, these results indicate that amantadine analogs act on multiple, complementary mechanisms to inhibit replication of M2S31N viruses. Highlights- Current IAVs have M2 mutations that confer resistance to amantadine and rimantadine - Several amantadine analogs inhibit these viruses without acting on M2 proton currents - Alternative antiviral targets include IAV entry and M2-M1 protein colocalization - Amantadine analogs are also tolerated in mice - Future amantadine antivirals could simultaneously act on multiple IAV mechanisms

microbiology↗

bioRxiv2024

Goldfinder: Unraveling Networks of Gene Co-occurrence and Avoidance in Bacterial Pangenomes

The pangenome is the set of all genes present in a prokaryotic species. Most pangenomes contain many accessory genes that are present in only some of the species members. Genes need to function together, and it has been suggested that selection for certain gene combinations affects the structure of prokaryotic pangenomes. Nevertheless, genes might also co-occur simply due to being linked on the genome, and efficient tools are needed to distinguish linkage from co-selection. Here we present Goldfinder, an approach to infer co-occurrence and co-avoidance between gene pairs by taking the phylogenetic relationships of the species into account. The approach is implemented in an efficient Python script available at https://github.com/fbaumdicker/goldfinder. We also provide scripts for clustering co-occurring genes and for visualizing the resulting co-occurrence and co-avoidance networks in Cytoscape. In comparison to the co-occurrence inference tool Coinfinder, Goldfinder finds fewer co-occurring pairs in a real species pangenome, suggesting that fewer spurious associations due to phylogenetic dependencies are detected. We conclude that Goldfinder is a fast and accurate tool to infer gene co-occurrence and co-avoidance, which will enable large-scale analyses to infer co-selected genes across bacterial pangenomes.

bioinformatics↗

bioRxiv2023

Phylogenetic distance and structural diversity directing a reclassification of glycopeptide antibiotics

Glycopeptide antibiotics (GPAs) are key agents against multidrug-resistant Gram-positive pathogens, yet both the term "glycopeptide" and the current GPA type I-V classification framework have become increasingly strained as structurally and mechanistically divergent members continue to be discovered. In particular, compounds historically grouped as "type V GPAs" differ from classical GPAs in features such as glycosylation, peptide length, and reported mode of action, raising the question of whether they belong to the same natural product class. Here, a curated dataset of GPA-associated biosynthetic gene clusters (BGCs) is analysed by combining fingerprint similarity of the products with phylogenetic analysis of the BGCs. Fingerprint-based structural similarity networks and BGC similarity comparisons reveal a pronounced separation between classical lipid II-binding GPAs (types I-IV) and type V GPAs. Multi-locus phylogenetic analyses of conserved biosynthetic components further support two deeply divergent evolutionary subclasses, consistent with subclass-specific biosynthetic signatures. Together, these results motivate a revised, unambiguous framework in which the broader class is termed xyclopeptides, comprising the subclasses dalabactins (legacy GPA types I-IV) and murobactins (legacy type V).

genetics↗

bioRxiv2022

Comparative metagenomic analysis of biosynthetic diversity across sponge microbiomes highlights metabolic novelty, conservation and diversification

Marine sponges and their microbial symbiotic communities are rich sources of diverse natural products (NPs) that often display biological activity, yet little is known about their global distribution landscape and the symbionts that produce them. As the majority of sponge symbionts remain uncultured, it is a challenge to characterize their NP biosynthetic pathways, assess their prevalence within the holobiont and measure their diversity across sponge taxa and environments. Here, we explore the microbial biosynthetic landscapes of three sponge species from the Atlantic Ocean and the Mediterranean Sea. This dataset reveals striking novelty in its encoded biosynthetic potential, with less than 1% of the recovered gene cluster families (GCF) showing similarity to any characterized biosynthetic gene cluster (BGC). When zooming in on the microbial communities of each sponge, we observed higher variability of both secondary metabolic and taxonomic profiles between sponge species than within species. Nonetheless, we also identified conservation of GCFs, with 20% of sponge GCFs being shared between at least two sponge species, and a true GCF core comprised of 6% of GCFs shared across all species. Within this functional core, we identified a set of widespread and diverse GCFs encoding nonribosomal peptide synthetases (NRPS) that are potentially involved in the production of diversified ether lipids, as well as GCFs putatively encoding the production of highly modified proteusins. The present work contributes to the small, yet growing body of data characterizing NP landscapes of marine sponge symbionts, and to the cryptic biosynthetic potential contained in this environmental niche.

microbiology↗

bioRxiv2021

A global survey of specialized metabolic diversity encoded in bacterial genomes

Bacterial specialized metabolites are a proven source of antibiotics and cancer therapies, but whether we have sampled all the secondary metabolite chemical diversity of cultivated bacteria is not known. We analysed ~ 170,000 bacterial genomes and ~ 47,000 metagenome assembled genomes (MAGs) using a modified BiG-SLiCE and the new clust-o-matic algorithm. We found that only 3% of the natural products potentially encoded in bacterial genomes have been experimentally characterized. We show that the variation of secondary metabolite biosynthetic diversity drops significantly at the genus level, identifying it as an appropriate taxonomic rank for comparison. Equal comparison of genera based on Relative Evolutionary Distance revealed that Streptomyces bacteria encode the largest biosynthetic diversity by far, with Amycolatopsis, Kutzneria and Micromonospora also encoding substantial diversity. Finally we find that several less-well-studied taxa, such as Weeksellaceae (Bacteroidota), Myxococcaceae (Myxococcota), Pleurocapsa and Nostocaceae (Cyanobacteria), have potential to produce highly diverse sets of secondary metabolites that warrant further investigation.

genomics↗