Location: Cell Wall Biology and Utilization Research
Title: Assignment of virus and antimicrobial resistance genes to microbial hosts in a complex microbial community by combined long-read assembly and proximity ligationAuthor
Bickhart, Derek | |
WATSON, MICK - University Of Edinburgh | |
KOREN, SERGEY - National Institutes Of Health (NIH) | |
PRESS, MAXIMILLIAN - Phase Genomics, Inc | |
SULLIVAN, SHAWN - Phase Genomics, Inc | |
LIACHKO, IVAN - Phase Genomics, Inc | |
PHILLIPPY, ADAM - National Institutes Of Health (NIH) | |
Smith, Timothy - Tim |
Submitted to: Meeting Abstract
Publication Type: Abstract Only Publication Acceptance Date: 12/10/2018 Publication Date: N/A Citation: N/A Interpretive Summary: Technical Abstract: The characterization of microbial communities by metagenomic approaches has been enhanced by recent improvements in short-read sequencing efficiency and assembly algorithms. It is now possible to model the genome structure of even complex communities using a combination of proximity ligation, whole-community sequencing, and metagenomic binning approaches. We describe the results of adding long-read sequencing to the mix of technologies used to assemble a highly complex cattle rumen microbial community, and compare the assembly to current short read-based methods applied to the same sample. Contigs in the long-read assembly were 7-fold longer on average, and contained 7-fold more complete open reading frames (ORF), than the short read assembly, despite having three-fold lower sequence depth. The larger number of ORFs included proportionately higher numbers of carbohydrate metabolism and transport-related predicted proteins. The linkages between long-read contigs, provided by proximity ligation data, supported identification of 188 novel viral-host associations in the rumen microbial community that suggest cross-species infectivity of specific viral strains. The improved contiguity of the long-read assembly also identified 94 antimicrobial resistance genes, compared to only seven alleles identified in the short-read assembly. Overall, we demonstrate a combination of experimental and computational methods that work synergistically to improve characterization of biological features in a highly complex rumen microbial community. |