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 "code-data-HatayeJ.zip" 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 

https://doi.org/10.1016/j.chom.2019.10.006

See this publication for details. It has an extensive methods section. The HIV env sequencing for this study was deposited at Genbank (https://www.ncbi.nlm.nih.gov/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.

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