Modelling of peripheral lymphocyte migration: system identification approach

COMPUTATIONAL MODEL OF RECIRCULATING LYMPHOCYTES

Lymphocyte recirculation plays an important role in controlling the spread of both pathogenic infections and tumor-producing cancer cells in the human body. We present a mathematical and computational framework that allows investigation of recirculating lymphocytes and estimation of model parameters using a genetic algorithm. The framework allows estimating parameters using data obtained from experiments performed in laboratory studies of rats as well as clinical studies of human subjects. Our computational model allows improved understanding of these data. Mathematical models enable investigators to obtain a quantitative picture of immune system kinetics and diversity in human health and disease outcomes. Our data-driven systems biology and immunological modeling approach contributes to a growing understanding of the dynamics of lymphocyte recirculation.

Random migration and signal integration promote rapid and robust T cell recruitment

To fight infections, rare T cells must quickly home to appropriate lymph nodes (LNs), and reliably localize the antigen (Ag) within them. The first challenge calls for rapid trafficking between LNs, whereas the second may require extensive search within each LN. Here we combine simulations and experimental data to investigate which features of random T cell migration within and between LNs allow meeting these two conflicting demands. Our model indicates that integrating signals from multiple random encounters with Ag-presenting cells permits reliable detection of even low-dose Ag, and predicts a kinetic feature of cognate T cell arrest in LNs that we confirm using intravital two-photon data. Furthermore, we obtain the most reliable retention if T cells transit through LNs stochastically, which may explain the long and widely distributed LN dwell times observed in vivo. Finally, we demonstrate that random migration, both between and within LNs, allows recruiting the majority of cognate precursors within a few days for various realistic infection scenarios. Thus, the combination of two-scale stochastic migration and signal integration is an efficient and robust strategy for T cell immune surveillance.

Directional migration of recirculating lymphocytes through lymph nodes via random walks

Naive T lymphocytes exhibit extensive antigen-independent recirculation between blood and lymph nodes, where they may encounter dendritic cells carrying cognate antigen. We examine how long different T cells may spend in an individual lymph node by examining data from long term cannulation of blood and efferent lymphatics of a single lymph node in the sheep. We determine empirically the distribution of transit times of migrating T cells by applying the Least Absolute Shrinkage & Selection Operator (LASSO) or regularised S-LASSO to fit experimental data describing the proportion of labelled infused cells in blood and efferent lymphatics over time. The optimal inferred solution reveals a distribution with high variance and strong skew. The mode transit time is typically between 10 and 20 hours, but a significant number of cells spend more than 70 hours before exiting. We complement the empirical machine learning based approach by modelling lymphocyte passage through the lymph node insilico. On the basis of previous two photon analysis of lymphocyte movement, we optimised distributions which describe the transit times (first passage times) of discrete one dimensional and continuous (Brownian) three dimensional random walks with drift. The optimal fit is obtained when drift is small, i.e. the ratio of probabilities of migrating forward and backward within the node is close to one. These distributions are qualitatively similar to the inferred empirical distribution, with high variance and strong skew. In contrast, an optimised normal distribution of transit times (symmetrical around mean) fitted the data poorly. The results demonstrate that the rapid recirculation of lymphocytes observed at a macro level is compatible with predominantly randomised movement within lymph nodes, and significant probabilities of long transit times. We discuss how this pattern of migration may contribute to facilitating interactions between low frequency T cells and antigen presenting cells carrying cognate antigen.

T-lymphocyte perturbation following large-scale apheresis and hematopoietic stem cell transplantation in HIV-infected individuals

Analysis and mathematical modeling of T-lymphocyte perturbation following administration of granulocyte colony stimulating factor (G-CSF) and two large-scale aphereses are reported. 74 HIV-1 positive antiretroviral-treated individuals were infused with gene- or sham-transduced CD34+ hematopoietic stem cells (HSC) in a Phase II clinical trial. T cell numbers were examined in four phases: 1) during steady state; 2) increases in peripheral blood (PB) following G-CSF administration; 3) depletion post-aphereses and 4) reconstitution post HSC infusion. The present analysis provides the first direct estimate of CD4+ T cell distribution and trafficking in HIV-infected individuals on stable HAART, indicating that CD4+ T lymphocytes in PB represent 5.5% of the pool of CD4+ T lymphocytes that traffic to PB.

LIGHT regulates inflamed draining lymph node hypertrophy

Lymph node (LN) hypertrophy, the increased cellularity of LNs, is the major indication of the initiation and expansion of the immune response against infection, vaccination, cancer, or autoimmunity. The mechanisms underlying LN hypertrophy remain poorly defined. In this article, we demonstrate that LIGHT (homologous to lymphotoxins, exhibits inducible expression, and competes with HSV glycoprotein D for HVEM, a receptor expressed by lymphocytes) (TNFSF14) is a novel factor essential for LN hypertrophy after CFA immunization. Mechanistically, LIGHT is required for the influx of lymphocytes into but not egress out of LNs. In addition, LIGHT is required for dendritic cell migration from the skin to draining LNs. Compared with wild type mice, LIGHT(-)(/)(-) mice express lower levels of chemokines in skin and addressins in LN vascular endothelial cells after CFA immunization. We unexpectedly observed that LIGHT from radioresistant rather than radiosensitive cells, likely Langerhans cells, is required for LN hypertrophy. Importantly, Ag-specific T cell responses were impaired in draining LNs of LIGHT(-)(/)(-) mice, suggesting the importance of LIGHT regulation of LN hypertrophy in the generation of an adaptive immune response. Collectively, our data reveal a novel cellular and molecular mechanism for the regulation of LN hypertrophy and its potential impact on the generation of an optimal adaptive immune response.

Modelling the dynamics of LCMV infection in mice: II. Compartmental structure and immunopathology

In this study, we develop a mathematical model for analysis of the compartmental aspects and immunopathology of lymphocytic choriomeningitis virus (LCMV) infection in mice. We used sets of original and published data on systemic (extrasplenic) virus distribution to estimate the parameters of virus growth and elimination for spleen and other anatomical compartments, such as the liver, kidney, thymus and lung as well as transfer rates between blood and the above organs. A mathematical model quantitatively integrating the virus distribution kinetics in the host, the specific cytotoxic T lymphocyte (CTL) response in spleen and the re-circulation of effector CTL between spleen, blood and liver is advanced to describe the CTL-mediated immunopathology (hepatitis) in mice infected with LCMV. For intravenous and "peripheral" routes of infection we examine the severity of the liver disease, as a function of the virus dose and the host's immune status characterized by the numbers of precursor and/or cytolytic effector CTL. The model is used to predict the efficacy of protection against virus persistence and disease in a localized viral infection as a function of the composition of CTL population. The modelling analysis suggests quantitative demands to CTL memory for maximal protection against a wide range of doses of infection with a primarily peripheral site of virus replication without the risk of favoring immunopathology. It specifies objectives for CTL vaccination to ensure virus elimination with minimal immunopathology vs. vaccination for disease.

Computational immunology: The coming of age

The explosive growth in biotechnology combined with major advances in information technology has the potential to radically transform immunology in the postgenomics era. Not only do we now have ready access to vast quantities of existing data, but new data with relevance to immunology are being accumulated at an exponential rate. Resources for computational immunology include biological databases and methods for data extraction, comparison, analysis and interpretation. Publicly accessible biological databases of relevance to immunologists number in the hundreds and are growing daily. The ability to efficiently extract and analyse information from these databases is vital for efficient immunology research. Most importantly, a new generation of computational immunology tools enables modelling of peptide transport by the transporter associated with antigen processing (TAP), modelling of antibody binding sites, identification of allergenic motifs and modelling of T-cell receptor serial triggering.