|KOLMOGOROV, MIKHAIL - University Of California|
|TSENG, ELIZABETH - Pacific Biosciences Inc|
|PORTIK, DANIEL - Pacific Biosciences Inc|
|KOROBEYNIKOV, ANTON - St Petersburg State University|
|TOLSTOGANOV, IVAN - St Petersburg State University|
|URITSKIY, GHERMAN - Phase Genomics, Inc|
|LIACHKO, IVAN - Phase Genomics, Inc|
|SULLIVAN, SHAWN - Phase Genomics, Inc|
|ZOREA, ALVAH - Ben Gurion University Of Negev|
|ANDREU, VICTORIA PASCAL - University Of Wageningen|
|MEDEMA, MARNIX - Wageningen University|
|MIZRAHI, ITZIK - Ben Gurion University Of Negev|
|PEVZNER, PAVEL - University Of California, San Diego|
|Smith, Timothy - Tim|
Submitted to: Nature Biotechnology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/13/2021
Publication Date: 1/3/2022
Citation: Bickhart, D.M., Kolmogorov, M., Tseng, E., Portik, D., Korobeynikov, A., Tolstoganov, I., Uritskiy, G., Liachko, I., Sullivan, S.T., Shin, S.B., Zorea, A., Andreu, V., Panke-Buisse, K., Medema, M., Mizrahi, I., Pevzner, P., Smith, T.P. 2022. Generating lineage-resolved, complete metagenome-assembled genomes from complex microbial communities. Nature Biotechnology. 40:711-719. https://doi.org/10.1038/s41587-021-01130-z.
Interpretive Summary: Metagenomics is a field of study that looks at the genomes of microscopic organisms. It is very difficult to capture individual microorganisms in the environment, so we often must identify them through remnants of their DNA. Until now, this has been very complicated due to limits in DNA sequencing technologies. We have developed a new method using state of the art sequencing technologies that makes this process incredibly easy. Using our method, it is possible for clinicians, microbiologists and other researchers to start analyzing this data immediately and without need for expert curation.
Technical Abstract: Microbial communities might include distinct lineages of closely related organisms that complicate metagenomic assembly and prevent the generation of complete metagenome-assembled genomes (MAGs). Here we show that deep sequencing using long (HiFi) reads combined with Hi-C binning can address this challenge even for complex microbial communities. Using existing methods, we sequenced the sheep fecal metagenome and identified 428 MAGs with more than 90% completeness, including 44 MAGs in single circular contigs. To resolve closely related strains (lineages), we developed MAGPhase, which separates lineages of related organisms by discriminating variant haplotypes across hundreds of kilobases of genomic sequence. MAGPhase identified 220 lineage-resolved MAGs in our dataset. The ability to resolve closely related microbes in complex microbial communities improves the identification of biosynthetic gene clusters and the precision of assigning mobile genetic elements to host genomes. We identified 1,400 complete and 350 partial biosynthetic gene clusters, most of which are novel, as well as 424 (298) potential host–viral (host–plasmid) associations using Hi-C data.