![]() To circumvent these two daunting barriers (i.e., taxonomic structure and software), we customized the curated Papilloma Virus Episteme (PaVE) database for use in a user-friendly, GUI-based, commercial software for sequence analysis. Furthermore, the 15-rank format is inconsistent with that of open-source Quantitative Insights into Microbial Ecology (QIIME) popularly used for bacterial and fungal taxonomic analysis. ![]() In 2019, the ICTV taxonomic structure was revised from a 5-rank (1991–2017) to a 15-rank structure which imposes retooling of existing software and restructuring of reference database(s) for viral metagenomic analysis. Second, viral taxonomies based on the International Committee on Taxonomy of Viruses (ICTV) are subject to new revisions. This is compounded by disparate, open-source tools which are often command-line based and require advanced computational or coding skills. First, the enormous amounts of complex data generated from each sample is non-trivial. However, bioinformatics analysis remains a bottleneck. The wet lab portion of genomics research has become more streamlined, simpler, and accessible to the researcher. Since the commercialization of high-throughput sequencing (HTS) instruments in 2005, the variety and choices of sequencing technologies, chemistries, platforms, capacities, and kits have expanded exponentially. Recent advancements in next-generation sequencing (NGS) have actualized HPV virome profiling. Therefore, anatomical virome characterization is crucial to our understanding of niche-specific, virus-host adaptive evolution foundational to pathogenesis. Site-specific genotypes and virome composition may be further shaped by the host’s immune response. Recent phylogenetic analysis also suggested that anatomical site predilection and tissue tropism by distinct HPV genotypes may be a result of viral niche adaptation to host ecosystems. The genetic differences in these oncogenes conferred disparate phenotypes and oncogenic potential. The PV genome backbone acquired oncogenes E6 and E7 and later E5 approximately 184 and 55 million years ago, respectively. The papillomavirus (PV) is a small 8000 base pair (bp) double-stranded, circular DNA virus that co-evolved with an ancestral host over 400 million years. The annual global burden of 570,000 new cervical and 120,000 other anogenital and oropharyngeal cancer cases have been attributed to HPV. Nonetheless, HPV is the second most prevalent primary infectious cause of cancer worldwide. The etiological role of HPV in breast and esophageal cancers has been postulated for several decades but remains controversial due to conflicting findings. Since then, the causal role of carcinogenic HPV in anogenital, oropharyngeal, and dermatological cancers (in patients with epidermodysplasia verruciformis) has been established and classified by the International Agency for Research on Cancer (IARC). Two thousand years elapsed before zur Hausen and his “papillomavirus crew” made the breakthrough discovery of identifying human papillomavirus (HPV)-16 in cervical, vulvar, and penile cancers in 1983. Hippocrates was the first to describe cervical cancer and its destructive nature around 400 BCE. The entire process named “HPV DeepSeq” provides a simple, accurate and practical means of NGS data analysis for a broad range of applications in viral research. Integrating clinically relevant, taxonomized HPV reference genomes within automated workflows proved to be an ultra-fast method of virome profiling. Biodiversity analysis between low- (LSIL) and high-grade squamous intraepithelial lesions (HSIL) revealed loss of species richness and gain of dominance by HPV-16 in HSIL. Tabular output conversion to visualizations entailed 1–2 keystrokes. ![]() Low-grade ( n = 95) and high-grade ( n = 60) Pap smears were tested with ensuing collective runtimes: Taxonomic Analysis (36 min) Alpha/Beta Diversities (5 s) Map Reads (45 min). HPV genomes from Papilloma Virus Episteme were customized and incorporated into CLC “ready-to-use” workflows for stepwise data processing to include: (1) Taxonomic Analysis, (2) Estimate Alpha/Beta Diversities, and (3) Map Reads to Reference. To address this, we developed and tested automated workflows for HPV taxonomic profiling and visualization using a customized papillomavirus database in the CLC Microbial Genomics Module. However, viral computational analysis remains a bottleneck due to semantic discrepancies between computational tools and curated reference genomes. Next-generation sequencing (NGS) has actualized the human papillomavirus (HPV) virome profiling for in-depth investigation of viral evolution and pathogenesis.
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