Spatial heterogeneity and peptide availability determine CTL killing efficiency in vivo

The rate at which a cytotoxic T lymphocyte (CTL) can survey for infected cells is a key ingredient of models of vertebrate immune responses to intracellular pathogens. Estimates have been obtained using in vivo cytotoxicity assays in which peptide-pulsed splenocytes are killed by CTL in the spleens of immunised mice. However the spleen is a heterogeneous environment and splenocytes comprise multiple cell types. Are some cell types intrinsically more susceptible to lysis than others? Quantitatively, what impacts are made by the spatial distribution of targets and effectors, and the level of peptide-MHC on the target cell surface? To address these questions we revisited the splenocyte killing assay, using CTL specific for an epitope of influenza virus. We found that at the cell population level T cell targets were killed more rapidly than B cells. Using modeling, quantitative imaging and in vitro killing assays we conclude that this difference in vivo likely reflects different migratory patterns of targets within the spleen and a heterogeneous distribution of CTL, with no detectable difference in the intrinsic susceptibilities of the two populations to lysis. Modeling of the stages involved in the detection and killing of peptide-pulsed targets in vitro revealed that peptide dose influenced the ability of CTL to form conjugates with targets but had no detectable effect on the probability that conjugation resulted in lysis, and that T cell targets took longer to lyse than B cells. We also infer that incomplete killing in vivo of cells pulsed with low doses of peptide may be due to a combination of heterogeneity in peptide uptake and the dissociation, but not internalisation, of peptide-MHC complexes. Our analyses demonstrate how population-averaged parameters in models of immune responses can be dissected to account for both spatial and cellular heterogeneity

Revisiting Estimates of CTL Killing Rates In Vivo

Recent experimental advances have allowed the estimation of the in vivo rates of killing of infected target cells by cytotoxic T lymphocytes (CTL). We present several refinements to a method applied previously to quantify killing of targets in the spleen using a dynamical model. We reanalyse data previously used to estimate killing rates of CTL specific for two epitopes of lymphocytic choriomeningitis virus (LCMV) in mice and show that, contrary to previous estimates the “killing rate” of effector CTL is approximately twice that of memory CTL. Further, our method allows the fits to be visualized, and reveals one potentially interesting discrepancy between fits and data. We discuss extensions to the basic CTL killing model to explain this discrepancy and propose experimental tests to distinguish between them

Serial Killing of Tumor Cells by Human Natural Killer Cells – Enhancement by Therapeutic Antibodies

BACKGROUND: Natural killer cells are an important component of the innate immune system. Anti-cancer therapies utilizing monoclonal antibodies also rely on the cytotoxicity of NK cells for their effectiveness. Here, we study the dynamics of NK cell cytotoxicity. METHODOLOGY/PRINCIPAL FINDINGS: We observe that IL-2 activated human NK cells can serially hit multiple targets. Using functional assays, we demonstrate that on an average, a single IL-2 activated NK cell can kill four target cells. Data using live video microscopy suggest that an individual NK cell can make serial contacts with multiple targets and majority of contacts lead to lysis of target cells. Serial killing is associated with a loss of Perforin and Granzyme B content. A large majority of NK cells survive serial killing, and IL-2 can replenish their granular stock and restore the diminished cytotoxicity of ‘exhausted’ NK cells. IL-2 and IL-15 are equally effective in enhancing the killing frequency of resting NK cells. Significantly, Rituximab, a therapeutic monoclonal antibody increases the killing frequency of both resting and IL-2 activated NK cells. CONCLUSION/SIGNIFICANCE: Our data suggest that NK cell-based therapies for overcoming tumors rely on their serial killing ability. Therefore, strategies augmenting the killing ability of NK cells can boost the immune system and enhance the effectiveness of monoclonal antibody-based therapies

Current Estimates for HIV-1 Production Imply Rapid Viral Clearance in Lymphoid Tissues

It has recently been estimated that a single HIV-1 infected cell produces between and more than viral particles over its life span. Since body-wide estimates of the ratio of free virus to productively infected cells are smaller than and much smaller than , individual virions must be cleared rapidly. This seems difficult to reconcile with the fact that most of the total body virus is trapped on follicular dendritic cells where it can survive for many months. It has also been difficult to reconcile the vast difference in the rates at which the virus is cleared from the blood in rhesus macaques and in chronically infected patients. Here we attempt to reconcile these seemingly contradictory observations by considering the virion clearance rate in various organs and the virion exchange rates between them. The main results are that the per capita clearance rate of free virus in lymphoid tissue should be fast, the virion exchange rate between lymphoid tissue and the blood should be slow, and the comparatively slow previous estimates for the virion clearance rate from the blood correspond to the rate of virion efflux from the blood to other organs where the virus is ultimately cleared

Fractional modeling dynamics of HIV and CD4+ T-cells during primary infection

In this paper, we introduce fractional-order into a model of HIV-1 infection of CD4+ T cells. We study the effect of the changing the average number of viral particles N with different sets of initial conditions on the dynamics of the presented model. Generalized Euler method (GEM) will be used to find a numerical solution of the HIV-1 infection fractional order model

Systems medicine and infection

By using a systems based approach, mathematical and computational techniques can be used to develop models that describe the important mechanisms involved in infectious diseases. An iterative approach to model development allows new discoveries to continually improve the model, and ultimately increase the accuracy of predictions. SIR models are used to describe epi demics, predicting the extent and spread of disease. Genome-wide genotyping and sequencing technologies can be used to identify the biological mechanisms behind diseases. These tools help to build strategies for disease prevention and treatment, an example being the recent outbreak of Ebola in West Africa where these techniques were deployed. HIV is a complex disease where much is still to be learnt about the virus and the best effective treatment. With basic mathematical modelling techniques, significant discoveries have been made over the last 20 years. With recent technological advances, the computation al resources now available and interdisciplinary cooperation, further breakthroughs are inevitable. In TB, modelling has traditionally been empirical in nature, with clinical data providing the fuel for this top-down approach. Recently, projects have begun to use data derived from laboratory experiments and clinical trials to create mathematical models that describe the mechanisms responsible for the disease. A systems medicine approach to infection modelling helps identify important biological questions that then direct future experiments , the results of which improve the model in an iterative cycle . This means that data from several model systems can be integrated and synthesised to explore complex biological systems .Postprin

Simian-Human Immunodeficiency Infection – Is the Course Set in the Acute Phase?

Identifying early predictors of infection outcome is important for the clinical management of HIV infection, and both viral load and CD4+ T cell level have been found to be useful predictors of subsequent disease progression. Very high viral load or extensively depleted CD4+ T cells in the acute phase often result in failure of immune control, and a fast progression to AIDS. It is usually assumed that extensive loss of CD4+ T cells in the acute phase of HIV infection prevents the establishment of robust T cell help required for virus control in the chronic phase. We tested this hypothesis using viral load and CD4+ T cell number of SHIV-infected rhesus macaques. In acute infection, the lowest level of CD4+ T cells was a good predictor of later survival; animals having less than 3.3% of baseline CD4+ T cells progressed to severe disease, while animals with more than 3.3% of baseline CD4+ T cells experienced CD4+ T cell recovery. However, it is unclear if the disease progression was caused by early depletion, or was simply a result of a higher susceptibility of an animal to infection. We derived a simple relationship between the expected number of CD4+ T cells in the acute and chronic phases for a constant level of host susceptibility or resistance. We found that in most cases, the depletion of CD4+ T cells in chronic infection was consistent with the prediction from the acute CD4+ T cell loss. However, the animals with less than 3.3% of baseline CD4 T cells in the acute phase were approximately 20% more depleted late in the infection than expected based on constant level of virus control. This suggests that severe acute CD4 depletion indeed impairs the immune response

Elucidation of Hepatitis C Virus Transmission and Early Diversification by Single Genome Sequencing

A precise molecular identification of transmitted hepatitis C virus (HCV) genomes could illuminate key aspects of transmission biology, immunopathogenesis and natural history. We used single genome sequencing of 2,922 half or quarter genomes from plasma viral RNA to identify transmitted/founder (T/F) viruses in 17 subjects with acute community-acquired HCV infection. Sequences from 13 of 17 acute subjects, but none of 14 chronic controls, exhibited one or more discrete low diversity viral lineages. Sequences within each lineage generally revealed a star-like phylogeny of mutations that coalesced to unambiguous T/F viral genomes. Numbers of transmitted viruses leading to productive clinical infection were estimated to range from 1 to 37 or more (median = 4). Four acutely infected subjects showed a distinctly different pattern of virus diversity that deviated from a star-like phylogeny. In these cases, empirical analysis and mathematical modeling suggested high multiplicity virus transmission from individuals who themselves were acutely infected or had experienced a virus population bottleneck due to antiviral drug therapy. These results provide new quantitative and qualitative insights into HCV transmission, revealing for the first time virus-host interactions that successful vaccines or treatment interventions will need to overcome. Our findings further suggest a novel experimental strategy for identifying full-length T/F genomes for proteome-wide analyses of HCV biology and adaptation to antiviral drug or immune pressures