Next-Generation Technologies to Understand Mechanisms of Virus Infections
A special issue of Viruses (ISSN 1999-4915). This special issue belongs to the section "General Virology".
Deadline for manuscript submissions: closed (28 February 2022) | Viewed by 52547
Special Issue Editor
Interests: Innate immunity, unfolded protein response; paramyxoviridae; rhinoviridae; next generation sequencing; high resolution proteomics
Special Issue Information
Dear colleagues,
RNA viruses are responsible for the majority of the health burden caused by infectious diseases. Some 200 diverse human-transmissible RNA viruses are known, including respiratory syncytial virus, influenza virus, measles virus, HCV, HIV, dengue, rotavirus, and others that produce substantial disease burdens. This class of viruses exhibits substantial mutability leading to antigenic variation, enhanced virulence, changed cellular tropism and expanded host range. This feature results in RNA viruses representing current emerging zoonotic transmissions to humans including SARS-CoV2, MERS and Ebola. Because of their morbidity and economic impact, RNA viruses are a major focus of therapeutics and vaccine development efforts.
This Special Issue seeks original papers and reviews exploring the complex interactions produced by RNA virus-infecting host organisms. RNA virus replication triggers innate responses, activates unfolded protein responses, and produces metabolic adaptations. Variability in host responses affects dynamics of innate immune response, viral clearance, and establishment of adaptive immunity, resulting in distinct manifestations of disease and/or chronic sequelae. From the virus side, viral sequence variations influence fitness, spread and host innate responses.
The applications of next-generation technologies provide substantial opportunities to advance the understanding of disease mechanisms, improve detection, and advance therapeutics for this important class of infections. Special consideration will be given to papers applying next generation RNA sequencing, proteomics, epigenetics or metabolomics at the single cell level to understand cellular variability or stochastic responses.
Prof. Allan Brasier
Guest Editor
Manuscript Submission Information
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Keywords
- single-cell profiling
- assay for transpoase accessible chromatin (ATAC-Seq)
- variability
- next generation sequencing
- proteomics
- metabolomics
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