Evaluation and Optimization of Sample Processing and Bioinformatics Analysis for Long-Read Metagenomic Sequencing

摘要

Next-generation sequencing (NGS) has been instrumental to the advancement of metagenomic analysis for complex microbial communities. As techniques and metagenome databases improve, shotgun metagenomic analysis is becoming more common. However, several factors including genomic sequence repeats, translocations, and duplications can be difficult for NGS short reads to resolve. Long-read sequencing, on the other hand, has the potential to overcome the limitations of short-read sequencing, enabling better resolution of structural variants, sequencing repetitive regions, phasing of alleles, and distinguishing highly homologous genomic regions. With NGS revolutionizing our ability to characterize diverse and complex microbial communities such as stool, there is an increased need for high-quality, long high-molecular weight (HMW) genomic DNA (gDNA) and therefore efficient and effective long HMW gDNA extraction methods, especially from metagenomic samples. Many factors affect the quality and length of microbial DNA when extracting from stool, including microbial blooms and evanescence during collection and storage, nuclease activity during processing, and inefficient lysis of recalcitrant bacteria, yeast, and archaea during DNA purification. Furthermore, the choice of bioinformatics tools can alter read alignment efficiency and relative abundance analysis. Here we present evaluations of stool sample preservation, pre-treatment, and long HMW gDNA extraction. Additionally, we utilized long-read sequencing and a defined mock microbial community standard comprised of 8 bacteria and 2 yeasts to compare metagenomic long-read data using individual alignment tools. These data and observations contribute to the improvement of our ability to utilize long-read sequencing for routine metagenomic analysis.