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Effect of synaptic transmission on viral fitness in HIV infection.

ABSTRACT: HIV can spread through its target cell population either via cell-free transmission, or by cell-to-cell transmission, presumably through virological synapses. Synaptic transmission entails the transfer of tens to hundreds of viruses per synapse, a fraction of which successfully integrate into the target cell genome. It is currently not understood how synaptic transmission affects viral fitness. Using a mathematical model, we investigate how different synaptic transmission strategies, defined by the number of viruses passed per synapse, influence the basic reproductive ratio of the virus, R(0), and virus load. In the most basic scenario, the model suggests that R(0) is maximized if a single virus particle is transferred per synapse. R(0) decreases and the infection eventually cannot be maintained for larger numbers of transferred viruses, because multiple infection of the same cell wastes viruses that could otherwise enter uninfected cells. To explain the relatively large number of HIV copies transferred per synapse, we consider additional biological assumptions under which an intermediate number of viruses transferred per synapse could maximize R(0). These include an increased burst size in multiply infected cells, the saturation of anti-viral factors upon infection of cells, and rate limiting steps during the process of synapse formation.

SUBMITTER: Komarova NL

PROVIDER: S-EPMC3499495 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Effect of synaptic transmission on viral fitness in HIV infection.

Komarova Natalia L NL Levy David N DN Wodarz Dominik D

PloS one 20121115 11

HIV can spread through its target cell population either via cell-free transmission, or by cell-to-cell transmission, presumably through virological synapses. Synaptic transmission entails the transfer of tens to hundreds of viruses per synapse, a fraction of which successfully integrate into the target cell genome. It is currently not understood how synaptic transmission affects viral fitness. Using a mathematical model, we investigate how different synaptic transmission strategies, defined by ...[more]

PMID: 23166585

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Project description:BackgroundA single viral variant is transmitted in the majority of HIV infections. However, about 20% of heterosexually transmitted HIV infections are caused by multiple viral variants. Detection of transmitted HIV variants is not trivial, as it involves analysis of multiple viral sequences representing intra-host HIV-1 quasispecies.MethodologyWe distinguish two types of multiple virus transmission in HIV infection: (1) HIV transmission from the same source, and (2) transmission from different sources. Viral sequences representing intra-host quasispecies in a longitudinally sampled cohort of 42 individuals with primary HIV-1C infection in Botswana were generated by single-genome amplification and sequencing and spanned the V1C5 region of HIV-1C env gp120. The Maximum Likelihood phylogeny and distribution of pairwise raw distances were assessed at each sampling time point (n = 217; 42 patients; median 5 (IQR: 4-6) time points per patient, range 2-12 time points per patient).ResultsTransmission of multiple viral variants from the same source (likely from the partner with established HIV infection) was found in 9 out of 42 individuals (21%; 95 CI 10-37%). HIV super-infection was identified in 2 patients (5%; 95% CI 1-17%) with an estimated rate of 3.9 per 100 person-years. Transmission of multiple viruses combined with HIV super-infection at a later time point was observed in one individual.ConclusionsMultiple HIV lineages transmitted from the same source produce a monophyletic clade in the inferred phylogenetic tree. Such a clade has transiently distinct sub-clusters in the early stage of HIV infection, and follows a predictable evolutionary pathway. Over time, the gap between initially distinct viral lineages fills in and initially distinct sub-clusters converge. Identification of cases with transmission of multiple viral lineages from the same source needs to be taken into account in cross-sectional estimation of HIV recency in epidemiological and population studies.

Project description:We used Affymetrix U133A 2.0 chips to better understand transcriptional changes associated with HIV-1 infection and perinatal transmission in human PBMCS obtained from young adult mothers with infants in Botswana in vivo. HIV seropositive and drug naÃ¯ve samples:; GSM94333, GSM94334, GSM94335, GSM94336, GSM94337, GSM94338, GSM94340, GSM94342, GSM94343, GSM94345, GSM94351, GSM94353, GSM94354, GSM94355, GSM94357, GSM94358, GSM94360, GSM94361, GSM94362, GSM94364, GSM94365, GSM94367, GSM94369, GSM94370, GSM94378; HIV seronegative samples:; GSM92590, GSM92788, GSM92789, GSM92790, GSM92791, GSM92792, GSM92793, GSM92794, GSM92795, GSM92796, GSM92797, GSM92798, GSM92799, GSM92800, GSM92801, GSM92802, GSM92803, GSM92804, GSM92805, GSM92806; HIV seropositive transmitter mothers:; GSM94333, GSM94334, GSM94335, GSM94336, GSM94337, GSM94338, GSM94340, GSM94342, GSM94343, GSM94345, GSM94378; HIV seropositive nontransmitter mothers:; GSM94351, GSM94353, GSM94354, GSM94355, GSM94357, GSM94358, GSM94360, GSM94361, GSM94362, GSM94364, GSM94365, GSM94367, GSM94369, GSM94370 Experiment Overall Design: Total RNA was extracted from peripheral blood and processed for microarray hybridizations that were conducted using U133A 2.0 chips (Affymetrix, Santa Clara, CA). The 22,777 gene-probes were filtered based on presence/absence, resulting in data for 11,705 gene-probes. The array data sets were then analyzed for differential expression based on HIV status (seronegative, seropositive) and transmitter status (transmitter: TR, nontransmitter: NTR) using BADGE version 1.0, a computer program implementing a Bayesian approach to identify differentially expressed genes (Sebastiani et al, Nat.Gen, 2005). Once differentially expressed genes were identified by BADGE, the biologically enriched categories were identified, as recently described (Montano et al, Int Immunol, 2006), by implementing a stand-alone version of the EASE statistical software (Hosack et al, Genome Biol., 2003). Selected genes were validated using realtime reverse transcription PCR.

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Effect of synaptic transmission on viral fitness in HIV infection.

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Effect of synaptic transmission on viral fitness in HIV infection.

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