The Genealogical Population Dynamics of HIV-1 in a Large Transmission Chain:Bridging within and among Host Evolutionary Rates

Transmission lies at the interface of human immunodeficiency virus type 1 (HIV-1) evolution within and among hosts and separates distinct selective pressures that impose differences in both the mode of diversification and the tempo of evolution. In the absence of comprehensive direct comparative analyses of the evolutionary processes at different biological scales, our understanding of how fast within-host HIV-1 evolutionary rates translate to lower rates at the between host level remains incomplete. Here, we address this by analyzing pol and env data from a large HIV-1 subtype C transmission chain for which both the timing and the direction is known for most transmission events. To this purpose, we develop a new transmission model in a Bayesian genealogical inference framework and demonstrate how to constrain the viral evolutionary history to be compatible with the transmission history while simultaneously inferring the within-host evolutionary and population dynamics. We show that accommodating a transmission bottleneck affords the best fit our data, but the sparse within-host HIV-1 sampling prevents accurate quantification of the concomitant loss in genetic diversity. We draw inference under the transmission model to estimate HIV-1 evolutionary rates among epidemiologically-related patients and demonstrate that they lie in between fast intra-host rates and lower rates among epidemiologically unrelated individuals infected with HIV subtype C. Using a new molecular clock approach, we quantify and find support for a lower evolutionary rate along branches that accommodate a transmission event or branches that represent the entire backbone of transmitted lineages in our transmission history. Finally, we recover the rate differences at the different biological scales for both synonymous and non-synonymous substitution rates, which is only compatible with the 'store and retrieve' hypothesis positing that viruses stored early in latently infected cells preferentially transmit or establish new infections upon reactivation.status: publishe

Organisation et variabilite genetique des retrovirus HIV

SIGLECNRS T Bordereau / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

ROLE DES GLYCOPROTEINES D'ENVELOPPE DES VIRUS DE L'IMMUNODEFICIENCE HUMAINE DE TYPE 1 DANS L'ENTREE VIRALE (ETUDE DU MECANISME D'ACTION DE DEUX ANTIVIRAUX)

PARIS-BIUSJ-Physique recherche (751052113) / SudocCentre Technique Livre Ens. Sup. (774682301) / SudocSudocFranceF

Rôle de l'ectodomaine des glycoprotéines d'enveloppe transmembranaires virales dans les étapes tardives de la fusion membranaire

PARIS7-Bibliothèque centrale (751132105) / SudocSudocFranceF

Role of the Ectodomain of the gp41 Transmembrane Envelope Protein of Human Immunodeficiency Virus Type 1 in Late Steps of the Membrane Fusion Process

The membrane fusion process mediated by the gp41 transmembrane envelope glycoprotein of the human immunodeficiency virus type 1 (HIV-1) was addressed by a flow cytometry assay detecting exchanges of fluorescent membrane probes (DiI and DiO) between cells expressing the HIV-1 envelope proteins (Env) and target cells. Double-fluorescent cells were detected when target cells expressed the type of chemokine receptor, CXCR4 or CCR5, matching the type of gp120 surface envelope protein, X4 or R5, respectively. Background levels of double-fluorescent cells were observed when the gp120-receptor interaction was blocked by AMD3100, a CXCR4 antagonist. The L568A mutation in the N-terminal heptad repeat (HR1) of gp41 resulted in parallel inhibition of the formation of syncytia and double-fluorescent cells, indicating that gp41 had a direct role in the exchange of fluorescent probes. In contrast, three mutations in the loop region of the gp41 ectodomain, located on either side of the Cys-(X)(5)-Cys motif (W596 M and W610A) or at the distal end of HR1 (D589L), had limited or no apparent effect on membrane lipid mixing between Env(+) and target cells, while they blocked formation of syncytia and markedly reduced the exchanges of cytoplasmic fluorescent probes. The loop region could therefore have a direct or indirect role in events occurring after the merging of membranes, such as the formation or dilation of fusion pores. Two types of inhibitors of HIV-1 entry, the gp41-derived peptide T20 and the betulinic acid derivative RPR103611, had limited effects on membrane exchanges at concentrations blocking or markedly reducing syncytium formation. This finding confirmed that T20 can inhibit the late steps of membrane fusion (post-lipid mixing) and brought forth an indirect argument for the role of the gp41 loop region in these steps, as mutations conferring resistance to RPR103611V were mapped in this region (I595S or L602H)

Étude de l'oligomérisation du récepteur de chimiokines CCR5 (implication dans l'entrée du virus de l'immunodéficience humaine)

PARIS-BIUSJ-Thèses (751052125) / SudocPARIS-BIUSJ-Physique recherche (751052113) / SudocSudocFranceF

Predicting COVID-19 incidence in French hospitals using human contact network analytics

International audienceBackground COVID-19 was first detected in Wuhan, China, in 2019 and spread worldwide within a few weeks. The COVID-19 epidemic started to gain traction in France in March 2020. Subnational hospital admissions and deaths were then recorded daily and served as the main policy indicators. Concurrently, mobile phone positioning data have been curated to determine the frequency of users being colocalized within a given distance. Contrarily to individual tracking data, these can be a proxy for human contact networks between subnational administrative units. Methods Motivated by numerous studies correlating human mobility data and disease incidence, we developed predictive time series models of hospital incidence between July 2020 and April 2021. We added human contact network analytics, such as clustering coefficients, contact network strength, null links or curvature, as regressors. Findings We found that predictions can be improved substantially (by more than 50%) at both the national level and the subnational level for up to 2 weeks. Our subnational analysis also revealed the importance of spatial structure, as incidence in colocalized administrative units improved predictions. This original application of network analytics from colocalization data to epidemic spread opens new perspectives for epidemic forecasting and public health