Biology subjects

Marc, A.

Publications and source records attributed to Marc, A..

3 recordsLinked to original sources

bioRxiv2026

A mechanistic basis for CD8+ T cell expansion sensitivity as a predictor of HIV post-treatment control

A key goal in HIV-1 cure research is to understand why some individuals control viral rebound after stopping antiretroviral therapy (ART). Recent human studies have identified responding CD8+ T cells expressing Ki-67 and the transcription factor TCF-1 as correlates of post-treatment control, but the mechanistic basis of this association remains unclear. Using the theoretical framework of Conway and Perelson, we fit mechanistic within-host models to viral load and CD8+ T cell data from 9 individuals in a combination immunotherapy trial following ART interruption. Although Ki-67 and TCF-1 measurements were not used for fitting, the inferred effector cell expansion sensitivity, i.e., the responsiveness of effector expansion to low antigen levels, shows a strong linear relationship with Ki-67 and TCF-1 levels at rebound (Pearsons r {approx} 0.8). Building on this, we show analytically that the post-rebound viral load set point is inversely proportional to the effector cell expansion sensitivity, and thus strongly correlates with cycling (Ki-67+) CD8+ T cells (r {approx} -0.8) at rebound, and a subset that expresses TCF-1 (r {approx} -0.9). In effect, individuals with a larger proportion of CD8+ T cells responding to viral rebound, and a greater representation of TCF-1 expressing cells within the responding subset, achieve markedly lower viral set points through a higher effector cell expansion sensitivity. This mechanism is consistent with prior modeling in a non-intervention ATI setting, suggesting it may generalize across more rebound contexts. Our results provide a mechanistic explanation why both Ki-67+ responding CD8+ T cells and their TCF-1-expressing subset predict post-treatment control, linking clinical correlation to its underlying cause and highlighting Ki-67 and TCF-1 as potential early biomarkers of HIV immunotherapy success.

immunology↗

bioRxiv2022

Impact of variants of concern on SARS-CoV-2 viral dynamics in non-human primates.

The impact of variants of concern (VoC) on SARS-CoV-2 viral dynamics remains poorly understood and essentially relies on observational studies subject to various sorts of biases. In contrast, experimental models of infection constitute a powerful model to perform controlled comparisons of the viral dynamics observed with VoC and better quantify how VoC escape from the immune response. Here we used molecular and infectious viral load of 78 cynomolgus macaques to characterize in detail the effects of VoC on viral dynamics. We first developed a mathematical model that recapitulate the observed dynamics, and we found that the best model describing the data assumed a rapid antigen-dependent stimulation of the immune response leading to a rapid reduction of viral infectivity. When compared with the historical variant, all VoC except beta were associated with an escape from this immune response, and this effect was particularly sensitive for delta and omicron variant (p<10-6 for both). Interestingly, delta variant was associated with a 1.8-fold increased viral production rate (p=0.046), while conversely omicron variant was associated with a 14-fold reduction in viral production rate (p<10-6). During a natural infection, our models predict that delta variant is associated with a higher peak viral RNA than omicron variant (7.6 log10 copies/mL 95% CI 6.8 - 8 for delta; 5.6 log10 copies/mL 95% CI 4.8 - 6.3 for omicron) while having similar peak infectious titers (3.7 log10 PFU/mL 95% CI 2.4 - 4.6 for delta; 2.8 log10 PFU/mL 95% CI 1.9 - 3.8 for omicron). These results provide a detailed picture of the effects of VoC on total and infectious viral load and may help understand some differences observed in the patterns of viral transmission of these viruses.

microbiology↗

bioRxiv2020

Vaccination reshapes the virus-specific T cell repertoire in unexposed adults

How baseline T cell characteristics impact human T cell responses to novel pathogens remains unknown. Here, we address this question by studying the CD4+ T cell response in unexposed individuals to live attenuated yellow fever virus (YFV) vaccine. We quantified virus-specific population dynamics over time using class II peptide-MHC tetramers. Our data revealed that, even in the absence of known viral exposure, memory phenotype T cells were found in the majority of virus-specific precursors in healthy adults. Pre-existing memory T cells can be divided into two groups; abundant pre-vaccine populations that underwent limited overall expansion and rare cells that generated naive-like responses and preferentially contributed to the memory repertoire after vaccination. Single cell T cell receptor (TCR) sequencing was used to track the evolution of immune responses to different epitopes and showed an association between preservation of unexpanded TCRs before exposure and the robustness of post-vaccine responses. Instead of a further increase in pre-established TCR clones, vaccination boosted the representation of rare TCRs. Thus, vaccine restructures the abundance and clonal hierarchy of virus-specific T cells. Our results link T cell precursor states to post-exposure responses, identifying peripheral education of virus-specific repertoire as a key component of effective vaccination. {circ}YFV-specific precursors contain abundant memory phenotype cells in healthy adults. {circ}Precursor frequency and phenotype are linked to post-immune response. {circ}Vaccination recruits rare virus-specific populations. {circ}Vaccination overrides pre-established clonal hierarchy

immunology↗