Viral-Host Metabolic Interactions

A special issue of Life (ISSN 2075-1729). This special issue belongs to the section "Microbiology".

Deadline for manuscript submissions: closed (20 October 2021) | Viewed by 2993

Special Issue Editors


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Guest Editor
Duke-NUS Medical School, Singapore 169857, Singapore
Interests: innate immunity; monocytes; host response; immunometabolism; systems biology; antibody; viral pathogenesis
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E-Mail Website
Guest Editor
Programme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore 169857, Singapore
Interests: functional genomics; virus-host interactions; vector borne RNA viruses; host-directed therapeutics
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
1. Singapore-MIT Alliance for Research and Technology, 1 CREATE Way, Singapore 138602, Singapore
2. OBGYN-Academic Clinical Program, Duke-NUS Medical School, Singapore 169857, Singapore
Interests: metabolomics; lipidomics; host- virus metabolism; biomarkers; adventitious agent metabolism and detection
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Viral Research and Experimental Medicine Centre @ SingHealth Duke-NUS (ViREMiCS); Programme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore 169857, Singapore
Interests: therapeutic antibodies; clinical development of vaccines and therapeutics for infectious diseases; molecular endpoints for monitoring clinical trial outcomes
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Viruses are obligate intracellular pathogens that depend on the host cell machinery and metabolism for replication. To thrive within the host, viruses leverage their small genome to synthesize viral proteins to evade host detection. Moreover, emerging studies now support that viruses can exploit host metabolism to synthesize macromolecules and ATP for viral propagation. Examples include the induction glycolysis to promote ATP production, elevating mitochondrial metabolism to increase oxidative phosphorylation, altering mitochondrial dynamics to enhance respiratory activity, and increased lipid synthesis to facilitate viral entry, replication, and assembly. Therefore, a detailed understanding of these virus–metabolic interactions could facilitate the development of specific antiviral therapeutics against viral diseases. In addition to their role in the viral life cycle, virus–metabolic interactions are increasingly known to be involved in disease pathogenesis. Indeed, individuals with disrupted metabolism caused by aging, obesity, and diabetes are more susceptible to severe outcomes after viral infection. Viruses can also trigger oxidative stress response, maladaptive unfolded protein response (UPR), and dysregulated host metabolism that leads to increased inflammation and cell death—both of which potentiate viral pathogenesis.

This Special Issue will highlight the various aspects of how viruses interact with host metabolism to promote viral infection and disease pathogenesis. We seek to showcase how viruses can alter host cell metabolism and their consequent impact on the viral life cycle and disease pathogenesis. We are also interested in manuscripts that interrogate how baseline variations in host metabolism, caused by genetic, dietary, environment or chronic diseases, can impact the outcome of virus infection and host responses to viruses, especially in the context of disease pathogenesis. Finally, we also welcome studies on therapeutic interventions that can modulate host metabolism, and their consequent effects on viral infection and disease pathogenesis.

You may choose our Joint Special Issue in Tropical Medicine and Infectious Disease.

Dr. Kuan Rong Chan
Dr. Yaw Shin Ooi
Dr. Yie Hou Lee
Dr. Eugenia Ong Ziying
Guest Editor

Manuscript Submission Information

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Keywords

  • Viruses
  • Cell metabolism
  • Virus–host metabolic interactions
  • Host metabolic responses
  • Metabolic therapeutics
  • Baseline between-individual differences

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Published Papers (1 paper)

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Research

9 pages, 982 KiB  
Communication
An Unsupervised Algorithm for Host Identification in Flaviviruses
by Phuoc Truong Nguyen, Santiago Garcia-Vallvé and Pere Puigbò
Life 2021, 11(5), 442; https://doi.org/10.3390/life11050442 - 14 May 2021
Cited by 2 | Viewed by 2094
Abstract
Early characterization of emerging viruses is essential to control their spread, such as the Zika Virus outbreak in 2014. Among other non-viral factors, host information is essential for the surveillance and control of virus spread. Flaviviruses (genus Flavivirus), akin to other viruses, [...] Read more.
Early characterization of emerging viruses is essential to control their spread, such as the Zika Virus outbreak in 2014. Among other non-viral factors, host information is essential for the surveillance and control of virus spread. Flaviviruses (genus Flavivirus), akin to other viruses, are modulated by high mutation rates and selective forces to adapt their codon usage to that of their hosts. However, a major challenge is the identification of potential hosts for novel viruses. Usually, potential hosts of emerging zoonotic viruses are identified after several confirmed cases. This is inefficient for deterring future outbreaks. In this paper, we introduce an algorithm to identify the host range of a virus from its raw genome sequences. The proposed strategy relies on comparing codon usage frequencies across viruses and hosts, by means of a normalized Codon Adaptation Index (CAI). We have tested our algorithm on 94 flaviviruses and 16 potential hosts. This novel method is able to distinguish between arthropod and vertebrate hosts for several flaviviruses with high values of accuracy (virus group 91.9% and host type 86.1%) and specificity (virus group 94.9% and host type 79.6%), in comparison to empirical observations. Overall, this algorithm may be useful as a complementary tool to current phylogenetic methods in monitoring current and future viral outbreaks by understanding host–virus relationships. Full article
(This article belongs to the Special Issue Viral-Host Metabolic Interactions)
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