Optimization and evaluation of viral metagenomic amplification and sequencing procedures toward a genome-level resolution of the human fecal DNA virome

Viruses in the human gut have been linked to health and disease. Deciphering the gut virome is dependent on metagenomic sequencing of the virus-like particles (VLPs) purified from the fecal specimens. A major limitation of conventional viral metagenomic sequencing is the low recoverability of viral genomes from the metagenomic dataset. To develop an optimal method for viral amplification and metagenomic sequencing for maximizing the recovery of viral genomes. We performed parallel virus enrichment and DNA extraction to generate ∼ 30 viral DNA samples from each of 5 fresh fecal specimens and conducted the experiments including 1) optimizing the cycle number for high-fidelity enzyme-based PCR amplification, 2) evaluating the reproducibility of the optimally whole viral metagenomic experimental process, 3) evaluating the reliability of multiple displacement amplification (MDA), 4) testing the capability of long-read sequencing for improving viral metagenomic assembly, and 5) comparing the differences between viral metagenomic and bulk metagenomic approaches. Our results revealed that the optimal cycle number for PCR amplification is 15. We verified the reliability of MDA and the effectiveness of long-read sequencing. Based on our optimized results, we generated 151 high-quality viruses using the dataset combined from short-read and long-read sequencing. Genomic analysis of these viruses found that most (60.3%) of them were previously unknown and showed a remarkable diversity of viral functions, especially the existence of 206 viral auxiliary metabolic genes. Finally, we uncovered significant differences in the efficiency and coverage of viral identification between viral metagenomic and bulk metagenomic approaches. Our study demonstrates the potential of optimized experiment and sequencing strategies in uncovering viral genomes from fecal specimens, which will facilitate future research about the genome-level characterization of complex viral communities.