Search bioRxiv⌕ Search

Biology subjects

Lustig, G.

Publications and source records attributed to Lustig, G..

6 recordsLinked to original sources

Aggregated Mycobacterium tuberculosis enhances the inflammatory response

Mycobacterium tuberculosis (Mtb) readily aggregates in culture and Mtb aggregates in the lung were observed in experimental Mtb infection. However, the physiological consequences of Mtb aggregation are incompletely understood. Here we examined the human macrophage transcriptional response to aggregated Mtb relative to infection with non-aggregated single or multiple bacilli per host cell. Infection with aggregated Mtb led to an early upregulation of pro-inflammatory associated genes and enhanced TNF signaling via the NF{kappa}B pathway. Both these pathways were significantly upregulated relative to infection with single bacilli, and TNF signaling was also significantly elevated relative to infection with multiple non-aggregated Mtb. Secretion of TNF and downstream cytokines were also enhanced. On a longer timescale, aggregate infection led to overall increased acidification per macrophage and a high proportion of death in these cells after aggregate phagocytosis. Host cell death did not occur when Mtb aggregates were heat killed despite such clumps being readily picked up. To validate that Mtb aggregates do occur in the human lung, we document Mtb aggregates surrounding a cavity in a human TB lesion. Aggregates may therefore be present in some lesions and elicit a stronger inflammatory response resulting in recruitment of additional phagocytes and their subsequent death, potentially leading to necrosis and transmission.

microbiology↗

HIV cell-to-cell spread slows evolution of drug resistance

Many enveloped viruses such as HIV have evolved to transmit by two infection modes: cell-free infection and cell-to-cell spread. Cell-to-cell spread is highly efficient as it involves directed viral transmission from the infected to the uninfected cell. In contrast, cell-free infection relies on chance encounters between the virion and cell. Despite the higher efficiency of cell-to-cell spread, there is substantial transmission by cell-free infection in conjunction with cell-to-cell spread. A possible reason is that cell-free infection offers a selective advantage by increasing sensitivity to factors interfering with infection, hence accelerating evolution of resistance relative to cell-to-cell spread alone. Here we investigated whether a combination of cell-free infection and cell-to-cell spread confers a selective advantage in experimental evolution to an antiretroviral drug. We maintained HIV infection using coculture of infected with uninfected cells in the face of moderate inhibition by the reverse transcriptase inhibitor efavirenz. We tested the effect on the rate of drug resistance evolution of replacing one coculture infection cycle with an infection cycle involving cell-free infection only, and observed earlier evolution of drug resistance mutations to efavirenz. When we increased selective pressure by adding a second reverse transcriptase inhibitor, emtricitabine, infection with the cell-free step consistently evolved multidrug resistance to both drugs and was able to replicate. In contrast, infection without a cell-free step mostly failed to evolve multidrug resistance. Therefore, HIV cell-to-cell spread decreases the ability of HIV to rapidly evolve resistance to inhibitors, which is conferred by cell-free infection. Author summaryCell-to-cell spread of HIV differs from cell-free, diffusion-based HIV infection in that viral transmission is directed from the infected to the uninfected cell through cellular interactions. Cell-to-cell spread has been recognized as a highly efficient infection mode that is able to surmount inhibition by antibodies and antiretroviral drugs. However, the effect of HIV cell-to-cell spread on the rate of evolution of viral resistance to infection inhibitors has not been studied. Here we used experimental evolution to investigate the effect of cell-to-cell spread versus cell-free infection on the emergence of drug resistance mutations to one or a combination of antiretroviral drugs. We found that replacing one infection cycle in experimental evolution with cell-free infection, where the filtered supernatant from infected cells, but not the cellular fraction, is used as the viral source, results in more rapid evolution of resistance. The consequences are that multidrug resistance consistently evolves with a cell-free viral cycle, but not when infection is solely by coculture of infected and uninfected cells. A possible consequence is that in environments where HIV cell-to-cell spread may predominate and some residual viral replication occurs in the face of ART, the emergence of drug resistance mutations would be delayed.

evolutionary biology↗

Complementation can maintain a quasispecies of drug sensitive and resistant HIV

HIV exists as multiple genotypes in a single infected individual referred to as a quasispecies. Here we reproduced a quasispecies by moderate selective pressure using an HIV reverse transcriptase inhibitor. The drug resistant genotype never completely supplanted the drug sensitive genotype, which stabilized at about 20 percent of viral sequences. Single-cell sequencing showed that resistant genotype frequency plateaued when cells were co-infected with sensitive and resistant genotypes, suggesting a sharing of viral proteins in co-infected cells (complementation) which masks genotypic differences. To test if complementation can confer phenotypic drug resistance, we co-transfected fluorescently labelled molecular clones of sensitive and resistant HIV and observed that genotypically sensitive virus from co-transfected cells was drug resistant. Resistant virus preferentially infected cells in tandem with drug sensitive HIV, explaining how co-infections of sensitive and resistant genotypes were initiated. Modelling this effect, we observed that a stable quasispecies could form at the experimental multiplicities of infection for the drug resistant and drug sensitive virus, showing that complementation can lead to a quasispecies in an HIV evolution experiment.

evolutionary biology↗

The CNS in the face of ART contains T cell origin HIV which can lead to drug resistance

HIV persists despite antiretroviral therapy (ART) in cellular reservoirs thought to occur in distinct anatomical compartments. Therapy failure may occur because of incomplete ART adherence and possibly viral replication at some reservoir sites. The CNS may serve as a reservoir site due to lowered ART penetration and virus production from long-lived tissue resident macrophages. Compelling evidence for the CNS as a reservoir is the existence of individuals where HIV is suppressed below limit of detection in blood but detectable in the cerebrospinal fluid (CSF), termed CSF Escape. Here, we asked whether HIV in CSF Escape individuals is derived from macrophages or persists due to lowered ART. We used cell surface markers on the HIV envelope to determine the cellular source of HIV. We verified detection using in vitro derived virus from infected macrophages and T cells and tested CSF from CSF Escape individuals. We observed host surface markers consistent with T cell origin. We also measured ART concentrations in the CSF and plasma. We found a dramatic decrease in CSF ART concentrations described previously, but no significant difference between CSF Escape versus fully suppressed individuals. To examine the effect of the observed CSF ART concentrations on HIV replication, we used long-term infection with ART in cell culture. CSF Escape ART levels led to either HIV suppression or evolution of drug resistance, but not replication of drug sensitive HIV. These observations argue that persistent CNS viremia despite ART can be T cell generated and may result in drug resistance and therapy failure.

microbiology↗

Interference with HIV infection of the first cell is essential for viral clearance in a pre-exposure prophylaxis model

Pre-exposure prophylaxis (PrEP) uses relatively weak HIV inhibition to reduce transmission between individuals. Why this approach is successful is unclear. Here we derive and experimentally validate a mathematical model for predicting infection clearance with PrEP based on the measured effect of a drug on the HIV replication ratio and number of initial infected cells. We tested the model by inhibiting low dose HIV infection with tenofovir, which reduces infection frequency per cell, and atazanavir, which reduces the cellular burst size of viable virions. Both drugs were at concentrations which allowed similar HIV replication. Reducing infection frequency dramatically increased infection clearance, while reducing burst size did not. This indicates that initial infection is vulnerable to inhibition before it infects the first cell, but not thereafter. Our model explains why PrEP is potent at drug concentrations which are ineffective against established infection, and provides a framework to test drug effectiveness for PrEP.

bioinformatics↗

Incomplete inhibition of HIV infection results in more HIV infected lymph node cells by reducing cell death

HIV has been reported to be cytotoxic in vitro and in lymph node infection models. Using a computational approach, we found that partial inhibition of transmission which involves multiple virions per cell could lead to increased numbers of live infected cells if the number of viral DNA copies remains above one after inhibition, as eliminating the surplus viral copies reduces cell death. Using a cell line, we observed increased numbers of live infected cells when infection was partially inhibited with the antiretroviral efavirenz or neutralizing antibody. We then used efavirenz at concentrations reported in lymph nodes to inhibit lymph node infection by partially resistant HIV mutants. We observed more live infected lymph node cells, but with fewer HIV DNA copies per cell, relative to no drug. Hence, counterintuitively, limited attenuation of HIV transmission per cell may increase live infected cell numbers in environments where the force of infection is high.

bioinformatics↗