Automated strain separation in low-complexity metagenomes using long reads
About Riccardo Vicedomini
Riccardo Vicedomini is a postdoctoral researcher in the Sequence Bioinformatics group at Institut Pasteur. He earned his Ph.D. in computer science at the University of Udine, where he worked on genome assembly and contributed to the Spruce Genome Project. After his Ph.D. studies, he worked on protein domain annotation and functional classification in the Laboratory of Computational and Quantitative Biology at Sorbonne University. He is currently interested in methods for strain-level metagenome assembly.
Recent methodological and technological advances enabled the reconstruction of bacterial genomes from complex microbial communities and, to a certain degree, a strain-level characterization. Nevertheless, at present, methods aiming to characterize metagenomes at the strain level are based on either short-read data or hybrid approaches. This motivated us to develop Strainberry, an assembly-based method that separates individual strains in low-complexity metagenomes using uniquely long reads. We benchmarked Strainberry on mock communities and real nanopore datasets. It provided high-quality strain-resolved assemblies in low-complexity metagenomes, but was also able to unravel a more fine-grained microbial diversity in samples of higher complexity.