Herpes simplex virus 2 (HSV-2) evolves faster in cell culture than HSV-1 by generating greater genetic diversity

Embracing Complexity: What Novel Sequencing Methods Are Teaching Us About Herpesvirus Genomic Diversity

The arrival of novel sequencing technologies throughout the past two decades has led to a paradigm shift in our understanding of herpesvirus genomic diversity. Previously, herpesviruses were seen as a family of DNA viruses with low genomic diversity. However, a growing body of evidence now suggests that herpesviruses exist as dynamic populations that possess standing variation and evolve at much faster rates than previously assumed. In this review, we explore how strategies such as deep sequencing, long-read sequencing, and haplotype reconstruction are allowing scientists to dissect the genomic composition of herpesvirus populations. We also discuss the challenges that need to be addressed before a detailed picture of herpesvirus diversity can emerge.

Sequence analysis of isolated strains of herpes zoster virus among patients with shingles

Background and Objectives

Herpes zoster, or shingles, is caused by the varicella-zoster virus (VZV), which initially presents as chickenpox in children. VZV is a global health concern, especially in winter and spring, affecting 10-20% of adults over 50 and posing a 30% risk for the general population. This study used PCR to detect VZV, confirming results with duplicated DNA samples and identifying 234 bp fragments by targeting the gpB gene.

Materials and Methods

This study examined 50 herpes zoster cases from October 2020 to April 2021, involving 30 males and 20 females aged 10 to 90, diagnosed by dermatologists. Data were collected via a questionnaire. PCR detected VZV by amplifying the gpB and MCP genes from skin lesion samples. Six positive 234-bp PCR products were sequenced at Macrogen Inc. in Seoul, South Korea.

Results

Six DNA samples with 234 bp amplicons were sequenced, showing 99-100% similarity to human alpha herpesvirus sequences in the gpB gene. NCBI BLAST matched these sequences to a reference (GenBank acc. MT370830.1), assigning accession numbers LC642111, LC642112, and LC642113. Eight nucleic acid substitutions caused amino acid changes in the gpB protein: isoleucine to threonine, serine to isoleucine, and threonine to Proline. These variants were deposited in NCBI GenBank as gpB3 samples.

Conclusion

The study found high sequence similarity to known VZV sequences, identifying six nucleic acid variations and eight SNPs. Notable amino acid changes in the gpB protein were deposited in NCBI GenBank as the gpB3 sample.

Evolutionary Dynamics of Accelerated Antiviral Resistance Development in Hypermutator Herpesvirus

Antiviral therapy is constantly challenged by the emergence of resistant pathogens. At the same time, experimental approaches to understand and predict resistance are limited by long periods required for evolutionary processes. Here, we present a herpes simplex virus 1 mutant with impaired proofreading capacity and consequently elevated mutation rates. Comparing this hypermutator to parental wild type virus, we study the evolution of antiviral drug resistance in vitro. We model resistance development and elucidate underlying genetic changes against three antiviral substances. Our analyzes reveal no principle difference in the evolutionary behavior of both viruses, adaptive processes are overall similar, however significantly accelerated for the hypermutator. We conclude that hypermutator viruses are useful for modeling adaptation to antiviral therapy. They offer the benefit of expedited adaptation without introducing apparent bias and can therefore serve as an accelerator to predict natural evolution.

The utility of SARS-CoV-2 genomic data for informative clustering under different epidemiological scenarios and sampling

OBJECTIVES

Clustering pathogen sequence data is a common practice in epidemiology to gain insights into the genetic diversity and evolutionary relationships among pathogens. We can find groups of cases with a shared transmission history and common origin, as well as identifying transmission hotspots. Motivated by the experience of clustering SARS-CoV-2 cases using whole genome sequence data during the COVID-19 pandemic to aid with public health investigation, we investigated how differences in epidemiology and sampling can influence the composition of clusters that are identified.

METHODS

We performed genomic clustering on simulated SARS-CoV-2 outbreaks produced with different transmission rates and levels of genomic diversity, along with varying the proportion of cases sampled.

RESULTS

In single outbreaks with a low transmission rate, decreasing the sampling fraction resulted in multiple, separate clusters being identified where intermediate cases in transmission chains are missed. Outbreaks simulated with a high transmission rate were more robust to changes in the sampling fraction and largely resulted in a single cluster that included all sampled outbreak cases. When considering multiple outbreaks in a sampled jurisdiction seeded by different introductions, low genomic diversity between introduced cases caused outbreaks to be merged into large clusters. If the transmission and sampling fraction, and diversity between introductions was low, a combination of the spurious break-up of outbreaks and the linking of closely related cases in different outbreaks resulted in clusters that may appear informative, but these did not reflect the true underlying population structure. Conversely, genomic clusters matched the true population structure when there was relatively high diversity between introductions and a high transmission rate.

CONCLUSION

Differences in epidemiology and sampling can impact our ability to identify genomic clusters that describe the underlying population structure. These findings can help to guide recommendations for the use of pathogen clustering in public health investigations.

High-throughput engineering of cytoplasmic- and nuclear-replicating large dsDNA viruses by CRISPR/Cas9

The application of CRISPR/Cas9 to improve genome engineering efficiency for large dsDNA viruses has been extensively described, but a robust and versatile method for high-throughput generation of marker-free recombinants for a desired locus has not yet been reported. Cytoplasmic-replicating viruses use their own repair enzymes for homologous recombination, while nuclear-replicating viruses use the host repair machinery. This is translated into a wide range of Cas9-induced homologous recombination efficiencies, depending on the virus replication compartment and viral/host repair machinery characteristics and accessibility. However, the use of Cas9 as a selection agent to target parental virus genomes robustly improves the selection of desired recombinants across large dsDNA viruses. We used ectromelia virus (ECTV) and herpes simplex virus (HSV) type 1 and 2 to optimize a CRISPR/Cas9 method that can be used versatilely for efficient genome editing and selection of both cytoplasmic- and nuclear-replicating viruses. We performed a genome-wide genetic variant analysis of mutations located at predicted off-target sequences for 20 different recombinants, showing off-target-free accuracy by deep sequencing. Our results support this optimized method as an efficient, accurate and versatile approach to enhance the two critical factors of high-throughput viral genome engineering: generation and colour-based selection of recombinants. This application of CRISPR/Cas9 reduces the time and labour for screening of desired recombinants, allowing for high-throughput generation of large collections of mutant dsDNA viruses for a desired locus, optimally in less than 2 weeks.