Infectio: a Generic Framework for Computational Simulation of Virus Transmission between Cells

ABSTRACT Viruses spread between cells, tissues, and organisms by cell-free and cell-cell mechanisms, depending on the cell type, the nature of the virus, or the phase of the infection cycle. The mode of viral transmission has a large impact on disease development, the outcome of antiviral therapies...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Artur Yakimovich, Yauhen Yakimovich, Michael Schmid, Jason Mercer, Ivo F. Sbalzarini, Urs F. Greber
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2016
Materias:	infection spread numerical simulation hybrid modeling multiscale modeling cellular automata particle strength exchange Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/aa29ccee14f4490e9ff61a192b92ce14
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:aa29ccee14f4490e9ff61a192b92ce14
record_format	dspace
spelling	oai:doaj.org-article:aa29ccee14f4490e9ff61a192b92ce142021-11-15T15:21:38ZInfectio: a Generic Framework for Computational Simulation of Virus Transmission between Cells10.1128/mSphere.00078-152379-5042https://doaj.org/article/aa29ccee14f4490e9ff61a192b92ce142016-02-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSphere.00078-15https://doaj.org/toc/2379-5042ABSTRACT Viruses spread between cells, tissues, and organisms by cell-free and cell-cell mechanisms, depending on the cell type, the nature of the virus, or the phase of the infection cycle. The mode of viral transmission has a large impact on disease development, the outcome of antiviral therapies or the efficacy of gene therapy protocols. The transmission mode of viruses can be addressed in tissue culture systems using live-cell imaging. Yet even in relatively simple cell cultures, the mechanisms of viral transmission are difficult to distinguish. Here we present a cross-platform software framework called “Infectio,” which is capable of simulating transmission phenotypes in tissue culture of virtually any virus. Infectio can estimate interdependent biological parameters, for example for vaccinia virus infection, and differentiate between cell-cell and cell-free virus spreading. Infectio assists in elucidating virus transmission mechanisms, a feature useful for designing strategies of perturbing or enhancing viral transmission. The complexity of the Infectio software is low compared to that of other software commonly used to quantitate features of cell biological images, which yields stable and relatively error-free output from Infectio. The software is open source (GPLv3 license), and operates on the major platforms (Windows, Mac, and Linux). The complete source code can be downloaded from http://infectio.github.io/index.html . IMPORTANCE Infectio presents a generalized platform to analyze virus infection spread between cells. It allows the simulation of plaque phenotypes from image-based assays. Viral plaques are the result of virus spreading from primary infected cells to neighboring cells. This is a complex process and involves neighborhood effects at cell-cell contact sites or fluid dynamics in the extracellular medium. Infectio differentiates between two major modes of virus transmission between cells, allowing in silico testing of hypotheses about spreading mechanisms of any virus which can be grown in cell cultures, based on experimentally measured parameters, such as infection intensity or cell killing. The results of these tests can be compared with experimental data and allow interpretations with regard to biophysical mechanisms. Infectio also facilitates characterizations of the mode of action of therapeutic agents, such as oncolytic viruses or other infectious or cytotoxic agents.Artur YakimovichYauhen YakimovichMichael SchmidJason MercerIvo F. SbalzariniUrs F. GreberAmerican Society for Microbiologyarticleinfection spreadnumerical simulationhybrid modelingmultiscale modelingcellular automataparticle strength exchangeMicrobiologyQR1-502ENmSphere, Vol 1, Iss 1 (2016)
institution	DOAJ
collection	DOAJ
language	EN
topic	infection spread numerical simulation hybrid modeling multiscale modeling cellular automata particle strength exchange Microbiology QR1-502
spellingShingle	infection spread numerical simulation hybrid modeling multiscale modeling cellular automata particle strength exchange Microbiology QR1-502 Artur Yakimovich Yauhen Yakimovich Michael Schmid Jason Mercer Ivo F. Sbalzarini Urs F. Greber Infectio: a Generic Framework for Computational Simulation of Virus Transmission between Cells
description	ABSTRACT Viruses spread between cells, tissues, and organisms by cell-free and cell-cell mechanisms, depending on the cell type, the nature of the virus, or the phase of the infection cycle. The mode of viral transmission has a large impact on disease development, the outcome of antiviral therapies or the efficacy of gene therapy protocols. The transmission mode of viruses can be addressed in tissue culture systems using live-cell imaging. Yet even in relatively simple cell cultures, the mechanisms of viral transmission are difficult to distinguish. Here we present a cross-platform software framework called “Infectio,” which is capable of simulating transmission phenotypes in tissue culture of virtually any virus. Infectio can estimate interdependent biological parameters, for example for vaccinia virus infection, and differentiate between cell-cell and cell-free virus spreading. Infectio assists in elucidating virus transmission mechanisms, a feature useful for designing strategies of perturbing or enhancing viral transmission. The complexity of the Infectio software is low compared to that of other software commonly used to quantitate features of cell biological images, which yields stable and relatively error-free output from Infectio. The software is open source (GPLv3 license), and operates on the major platforms (Windows, Mac, and Linux). The complete source code can be downloaded from http://infectio.github.io/index.html . IMPORTANCE Infectio presents a generalized platform to analyze virus infection spread between cells. It allows the simulation of plaque phenotypes from image-based assays. Viral plaques are the result of virus spreading from primary infected cells to neighboring cells. This is a complex process and involves neighborhood effects at cell-cell contact sites or fluid dynamics in the extracellular medium. Infectio differentiates between two major modes of virus transmission between cells, allowing in silico testing of hypotheses about spreading mechanisms of any virus which can be grown in cell cultures, based on experimentally measured parameters, such as infection intensity or cell killing. The results of these tests can be compared with experimental data and allow interpretations with regard to biophysical mechanisms. Infectio also facilitates characterizations of the mode of action of therapeutic agents, such as oncolytic viruses or other infectious or cytotoxic agents.
format	article
author	Artur Yakimovich Yauhen Yakimovich Michael Schmid Jason Mercer Ivo F. Sbalzarini Urs F. Greber
author_facet	Artur Yakimovich Yauhen Yakimovich Michael Schmid Jason Mercer Ivo F. Sbalzarini Urs F. Greber
author_sort	Artur Yakimovich
title	Infectio: a Generic Framework for Computational Simulation of Virus Transmission between Cells
title_short	Infectio: a Generic Framework for Computational Simulation of Virus Transmission between Cells
title_full	Infectio: a Generic Framework for Computational Simulation of Virus Transmission between Cells
title_fullStr	Infectio: a Generic Framework for Computational Simulation of Virus Transmission between Cells
title_full_unstemmed	Infectio: a Generic Framework for Computational Simulation of Virus Transmission between Cells
title_sort	infectio: a generic framework for computational simulation of virus transmission between cells
publisher	American Society for Microbiology
publishDate	2016
url	https://doaj.org/article/aa29ccee14f4490e9ff61a192b92ce14
work_keys_str_mv	AT arturyakimovich infectioagenericframeworkforcomputationalsimulationofvirustransmissionbetweencells AT yauhenyakimovich infectioagenericframeworkforcomputationalsimulationofvirustransmissionbetweencells AT michaelschmid infectioagenericframeworkforcomputationalsimulationofvirustransmissionbetweencells AT jasonmercer infectioagenericframeworkforcomputationalsimulationofvirustransmissionbetweencells AT ivofsbalzarini infectioagenericframeworkforcomputationalsimulationofvirustransmissionbetweencells AT ursfgreber infectioagenericframeworkforcomputationalsimulationofvirustransmissionbetweencells
_version_	1718428150323478528

Infectio: a Generic Framework for Computational Simulation of Virus Transmission between Cells

Ejemplares similares