Fast and Sensitive Genome-Hashing Software and its Application in Using NGS as a Detection Agent for Bacterial Presence in Oral Metagenomic Samples

Next generation sequencing has increased the throughput of sequenced DNA into the range of billions of nucleotides sequenced per day. With the increased speed of DNA sequencing and the short length of reads produced by next generation sequencers, a significant challenge has been created in quickly and accurately assembling the hundreds of millions of short reads created by modern sequencing instruments into their full genomic sequences. With the increase in throughput in next generation sequencing and the decrease in time and cost to perform DNA sequencing, novel applications for DNA sequencing are being considered. Among them is a methodology by which DNA sequencing can be used as a diagnostic or detection tool for bacterial infection or presence. Here, the implementation, characteristics, and deployment of a novel, genome-hashing alignment algorithm for quickly performing reference-based alignment is described. This algorithm, SRmapper, is shown to be between two-fold to eight-fold faster than a current and popular alignment algorithm, BWA, while retaining a similar fraction of reads aligned to human reference genome. SRmapper demonstrates a capability to align approximately 150 billion nucleotides per processor day on an Intel Xeon 2.8GHz processor to the human genome while using approximately 2.5GB of RAM. SRmapper is demonstrated to be able to perform both single-end and pair-end alignment and tolerates a higher number of discrepancies between reads and the reference sequence than BWA. Using SRmapper as an alignment tool, a method to detect Mycobacterium tuberculosis (TB) in metagenomic samples containing many different bacteria is described. This method utilizes the construction of a novel uniqueness genome for TB containing only the regions of the TB genome not similar to any other bacterial species in the oral metagenome. Alignment of simulated and real metagenomic samples demonstrate the effectiveness of the uniqueness genome in the detection of TB and discover TB contamination in samples from the 1000 genomes project. Finally, the uniqueness genomes methodology is expanded to all genomes within the oral metagenome, and preliminary evidence is provided demonstrating that next generation sequencing can detect the presence of multiple simultaneously via alignment using SRmapper