Auto Tag: Sample input

There are many sequencing-based approaches to understanding complex metagenomic communities spanning targeted amplification to whole-sample shotgun sequencing. While targeted approaches provide valuable data at low sequencing depth, they are limited by primer design and PCR. Whole-sample shotgun experiments generally use short-read sequencing, which results in data processing difficulties. For example, reads less than 500bp in length will rarely cover a complete gene or region of interest, and will require assembly. This not only introduces the possibility of incorrectly combining sequence from different community members, it requires a high depth of coverage. As such, rare community members may not be represented in the resulting assembly. Circular-consensus, single molecule, real-time (SMRT®) Sequencing reads in the 1-3kb range, with >99% accuracy can be efficiently generated for low amounts of input DNA. 10 ng of input DNA sequenced in 4 SMRT Cells on the PacBio RS II would generate >100,000 such reads. While throughput is lower compared to short-read sequencing methods, the reads are a true random sampling of the underlying community since SMRT Sequencing has been shown to have very low sequence-context bias. With reads >1 kb at >99% accuracy it is reasonable to expect a high percentage of reads include gene fragments useful for analysis without the need for de novo assembly. Here we present the results of circular consensus sequencing for an individual’s microbiome, before and after undergoing fecal microbiota transplantation (FMT) in order to treat a chronic Clostridium difficile infection. We show that even with relatively low sequencing depth, the long-read, assembly-free, random sampling allows us to profile low abundance community members at the species level. We also show that using shotgun sampling with long reads allows a level of functional insight not possible with classic targeted 16S, or short read sequencing, due to entire genes being covered in single reads.