Projects

Modem molecular biology techniques, particularly environmental DNA (eDNA) analysis, have great potential to revolutionize biodiversity and microbial community monitoring by overcoming the limitations of traditional, invasive monitoring methods. While eDNA has been widely used to assess a broad ange of organisms in diverse matrices, the potential of using spider webs as eDNA passive samplers, and particularly for studying vi ral diversity, emains largely unexplored. Acting as natural air filters, spider webs capture genetic material from their environment, positioning them as a promising ool for ecological surveillance. As key predators, spiders and their webs interact with a diverse array of viruses through their preys and environmental exposure. Few viruses have been detected in some spider species, however, viral diversity present in spider webs remains completely unexplored. 

To fill this gap, we have chosen Linyphia triangularis as a model organism due to its high population density across various locations in Slovenia. As this s a pioneering study on the virome of spider webs, we will first optimize the methodologies for virome research of spiders and their webs. Next, we will xamine the contributions of both, spider and environmental factors to the virome of spider webs by analyzing spider webs collected in the field with pider webs produced by same spiders in the laboratory. Finally, we will assess viral diversity across selected diverse ecosystems using spider webs as io-samplers to gain insights into the environmental impact on viral diversity within specific ecosystems. 

We hypothesize that spider webs, by passively capturing diverse environmental material, can serve as an efficient sampler for viral monitoring, complementing traditional surveillance methods. By applying high-throughput sequencing (HTS) based-metagenomic techniques, this research will expand our understanding of viral biodiversity in ecosystems, establish spider webs as a valuable tool for environmental virus monitoring, and improve the detection of both known and novel viral pathogens. Ultimately, this approach has the potential to enhance ecosystem health monitoring and enable arly detection of emerging viral threats. 

SICRIS