Researchers from the University of Helsinki have developed a bioinformatics pipeline called Lazypipe for identifying viruses in host-associated or environmental samples. Their findings were published in Virus Evolution.
The pipeline was developed in close collaboration between virologists and bioinformaticians. Previously, the Viral Zoonoses Research Unit, led by Olli Vapalahti, had published two examples of novel and potentially zoonotic viral agents that were identified with Lazypipe from wild animals that can serve as vectors. A new ebola virus was identified from feces and organ samples of Mops condylurus bats in Kenya, and a new tick-borne pathogen Alongshan virus from ticks in Northeast Europe.
"These examples demonstrate the efficacy of Lazypipe data analysis for NGS libraries with very different DNA/RNA backgrounds, ranging from mammalian tissues to pooled and crushed arthropods," says lead researcher Teemu Smura.
"The detection of SARS-CoV-2 without reference genome demonstrates the utility of Lazypipe for scenarios in which novel zoonotic viral agents emerge and can be quickly detected by NGS sequencing from clinical samples,” adds researcher Ravi Kant.