A computational technique to estimate within-host productively infected cell lifetimes in emerging viral infections

University of Oxford, Oxford, Oxfordshire, United Kingdom
DOI
10.7287/peerj.preprints.2621v2
Subject Areas
Bioinformatics, Computational Biology
Keywords
computational biology, emerging diseases, replicon, west nile virus, lifetime of infected cells
Copyright
© 2017 Banerjee
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Banerjee S. (2017) A computational technique to estimate within-host productively infected cell lifetimes in emerging viral infections. PeerJ Preprints 5:e2621v2

Abstract

Emerging viruses cause a lot of fatalities as they jump to humans from other species. Here we develop a novel technique to computationally estimate an important parameter of within-host viral infection: the lifespan of infected cells. Our approach is general and can be applied to a large class of viruses and leverages experimental data from replicon studies. Current techniques have difficulties reliably estimating infected cell lifetimes due to issues of parameter identifiability and correlation of parameters. The infected cell lifetime is an important parameter that gives an estimate of the how fast virus levels will decline. Our method would also help determine if some infected cells are short-lived or have longer lifespans with the consequence that longer lived cells could be reservoirs of infection. This would give a mechanistic understanding of why particular cell types are reservoirs of infection. We apply our technique to West Nile virus (WNV), an emerging disease of public health relevance related to Zika virus. Our analysis suggests that the most abundant infectible cells are short-lived and could motivate therapy that targets these particular cells. Our approach is very general and can be combined with more traditional methods of using differential equation models to simulate viremia in hosts: the combination of these two techniques will likely yield results that may not be achievable using the models in isolation. This will be of great interest especially in modelling emerging diseases.

Author Comment

We have added a new figure, conducted new statistical analysis and added text in the Discussion.