Apollo: a comprehensive GPU-powered within-host simulator for viral evolution and infection dynamics across population, tissue, and cell

Abstract Modern sequencing instruments bring unprecedented opportunity to study within-host viral evolution in conjunction with viral transmissions between hosts. However, no computational simulators are available to assist the characterization of within-host dynamics. This limits our ability to int...

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Main Authors: Deshan Perera, Evan Li, Paul MK Gordon, Frank van der Meer, Tarah Lynch, John Gill, Deirdre L. Church, A. P. Jason de Koning, Christian D. Huber, Guido van Marle, Alexander Platt, Quan Long
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-025-60988-8
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author Deshan Perera
Evan Li
Paul MK Gordon
Frank van der Meer
Tarah Lynch
John Gill
Deirdre L. Church
A. P. Jason de Koning
Christian D. Huber
Guido van Marle
Alexander Platt
Quan Long
author_facet Deshan Perera
Evan Li
Paul MK Gordon
Frank van der Meer
Tarah Lynch
John Gill
Deirdre L. Church
A. P. Jason de Koning
Christian D. Huber
Guido van Marle
Alexander Platt
Quan Long
author_sort Deshan Perera
collection DOAJ
description Abstract Modern sequencing instruments bring unprecedented opportunity to study within-host viral evolution in conjunction with viral transmissions between hosts. However, no computational simulators are available to assist the characterization of within-host dynamics. This limits our ability to interpret epidemiological predictions incorporating within-host evolution and to validate computational inference tools. To fill this need we developed Apollo, a GPU-accelerated, out-of-core tool for within-host simulation of viral evolution and infection dynamics across population, tissue, and cellular levels. Apollo is scalable to hundreds of millions of viral genomes and can handle complex demographic and population genetic models. Apollo can replicate real within-host viral evolution; accurately recapturing observed viral sequences from HIV and SARS-CoV-2 cohorts derived from initial population-genetic configurations. For practical applications, using Apollo-simulated viral genomes and transmission networks, we validated and uncovered the limitations of a widely used viral transmission inference tool.
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institution Kabale University
issn 2041-1723
language English
publishDate 2025-07-01
publisher Nature Portfolio
record_format Article
series Nature Communications
spelling doaj-art-b2c3f7d856644f219fabe48fe7a599862025-08-20T03:37:38ZengNature PortfolioNature Communications2041-17232025-07-0116111710.1038/s41467-025-60988-8Apollo: a comprehensive GPU-powered within-host simulator for viral evolution and infection dynamics across population, tissue, and cellDeshan Perera0Evan Li1Paul MK Gordon2Frank van der Meer3Tarah Lynch4John Gill5Deirdre L. Church6A. P. Jason de Koning7Christian D. Huber8Guido van Marle9Alexander Platt10Quan Long11Department of Biochemistry & Molecular Biology, Cumming School of Medicine, University of CalgaryDepartment of Biochemistry & Molecular Biology, Cumming School of Medicine, University of CalgaryAlberta Children’s Hospital Research Institute, University of CalgaryFaculty of Veterinary Medicine, University of CalgaryProvincial Public Health Laboratory SouthDepartment of Medicine, University of CalgaryDepartment of Medicine, University of CalgaryDepartment of Biochemistry & Molecular Biology, Cumming School of Medicine, University of CalgaryDepartment of Biology, The Pennsylvania State UniversityDepartment of Microbiology, Immunology and Infectious Diseases, University of CalgaryDepartment of Genetics, Perelman School of Medicine at the University of PennsylvaniaDepartment of Biochemistry & Molecular Biology, Cumming School of Medicine, University of CalgaryAbstract Modern sequencing instruments bring unprecedented opportunity to study within-host viral evolution in conjunction with viral transmissions between hosts. However, no computational simulators are available to assist the characterization of within-host dynamics. This limits our ability to interpret epidemiological predictions incorporating within-host evolution and to validate computational inference tools. To fill this need we developed Apollo, a GPU-accelerated, out-of-core tool for within-host simulation of viral evolution and infection dynamics across population, tissue, and cellular levels. Apollo is scalable to hundreds of millions of viral genomes and can handle complex demographic and population genetic models. Apollo can replicate real within-host viral evolution; accurately recapturing observed viral sequences from HIV and SARS-CoV-2 cohorts derived from initial population-genetic configurations. For practical applications, using Apollo-simulated viral genomes and transmission networks, we validated and uncovered the limitations of a widely used viral transmission inference tool.https://doi.org/10.1038/s41467-025-60988-8
spellingShingle Deshan Perera
Evan Li
Paul MK Gordon
Frank van der Meer
Tarah Lynch
John Gill
Deirdre L. Church
A. P. Jason de Koning
Christian D. Huber
Guido van Marle
Alexander Platt
Quan Long
Apollo: a comprehensive GPU-powered within-host simulator for viral evolution and infection dynamics across population, tissue, and cell
Nature Communications
title Apollo: a comprehensive GPU-powered within-host simulator for viral evolution and infection dynamics across population, tissue, and cell
title_full Apollo: a comprehensive GPU-powered within-host simulator for viral evolution and infection dynamics across population, tissue, and cell
title_fullStr Apollo: a comprehensive GPU-powered within-host simulator for viral evolution and infection dynamics across population, tissue, and cell
title_full_unstemmed Apollo: a comprehensive GPU-powered within-host simulator for viral evolution and infection dynamics across population, tissue, and cell
title_short Apollo: a comprehensive GPU-powered within-host simulator for viral evolution and infection dynamics across population, tissue, and cell
title_sort apollo a comprehensive gpu powered within host simulator for viral evolution and infection dynamics across population tissue and cell
url https://doi.org/10.1038/s41467-025-60988-8
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