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Principles Governing Establishment versus Collapse of HIV-1 Cellular Spread

Cite this dataset

Hataye, Jason et al. (2019). Principles Governing Establishment versus Collapse of HIV-1 Cellular Spread [Dataset]. Dryad.


A population at low census might go extinct, or instead transition into exponential growth to become firmly established. Whether this pivotal event occurs for a within-host pathogen can be the difference between health and illness. Here we define the principles governing whether HIV-1 spread among cells fails or becomes established, by coupling stochastic modeling with laboratory experiments. Following ex vivo activation of latently-infected CD4 T cells without de novo infection, stochastic cell division and death contributes to high variability in the magnitude of initial virus release. Transition to exponential HIV-1 spread often fails due to release of an insufficient amount of replication-competent virus. Establishment of exponential growth occurs when virus produced from multiple infected cells exceeds a critical population size. We quantitatively define the crucial transition to exponential viral spread. Thwarting this process would prevent HIV transmission or rebound from the latent reservoir.


The file "" contains two experimental data tables and script code in R, details are in the file "README.txt".

These files were generated for this research publication:

Principles Governing Establishment versus Collapse of HIV-1 Cellular Spread

Hataye JM et al. Cell Host & Microbe, 2019

See this publication for details. It has an extensive methods section. The HIV env sequencing for this study was deposited at Genbank ( with accession numbers MN515491-MN516420.

There are two experimental data files in the directory /expData

HIVrna1.txt, HIV RNA detection data (RT-PCR) from ex vivo culture supernatants using CD4+ T cells isolated from the peripheral blood of human donors with HIV-1 infection on combination antiretroviral therapy (ART). These data are organized into a table with columns with the following headings:

well: culture well index 

set: experiment set index

pid: patient ID (anonymized)

cd4: clinical CD4+ T cell count on day of donation

vl: clinical HIV viral load on day of donation

outg: If TRUE then cultures had exogenous target cells plus IL-2 added for outgrowth conditions

efv: If TRUE then cultures had efavirenz (reverse-transcriptase inhibitor) added for viral inhibition conditions

tcab: If TRUE then cultures had T cell activation beads (containing anti-CD3, anti-CD2, anti-CD28) added

days: days of culture

cells: number of CD4+ T cells added to culture on day 0 (day of sorting)

rcas: fraction of RCAS retroviral RNA recovered (range 0-1).

dna: HIV DNA copies detected from entire culture supernatant following DNAse treatment

rna: HIV RNA copies in entire culture supernatant (based on gag RT-PCR reaction, dilution factors and RCAS recovery)

rnac: HIV RNA copies in entire culture supernatant, corrected for residual HIV DNA if present


HIVrna2.txt, HIV RNA detection data (RT-PCR) from secondary (virus transfer from primary culture) and tertiary HIV culture supernatants.

The remaining directories contain simulation results or R code to perform data analysis, plotting, fitting of ordinary differential equation models, stochastic simulation, and Bayesian inference in Stan.

Usage notes

To verify the integrity (verify intact download) of the “” file, one can check the SHA-256 hash of this file. On Mac OS X, this can be done by opening a terminal, typing “cd Desktop” to change to the Desktop directory (if you put the file there), and typing “shasum -a 256”. Note that you may need to first unzip the direct download from Dryad to do the SHA-256 for "".

The SHA-256 for "" is 




National Institute of Allergy and Infectious Diseases

National Institutes of Health, Award: R01-AI028433

Department of Energy (USA), Award: Contract 89233218CNA000001

National Cancer Institute, Award: Contract HHSN261200800001E

National Institutes of Health, Award: R01-OD011095

National Institutes of Health, Award: R01-OD011095

National Institutes of Health, Award: P01-AI131365