Cross-linking reconsidered: binding and cross-linking fields and the cellular response

Next-generation bNAbs for HIV-1 cure strategies

Despite the ability to suppress viral replication using anti-retroviral therapy (ART), HIV-1 remains a global public health problem. Curative strategies for HIV-1 have to target and eradicate latently infected cells across the body, i.e. the viral reservoir. Broadly neutralizing antibodies (bNAbs) targeting the HIV-1 envelope glycoprotein (Env) have the capacity to neutralize virions and bind to infected cells to initiate elimination of these cells. To improve the efficacy of bNAbs in terms of viral suppression and viral reservoir eradication, next generation antibodies (Abs) are being developed that address the current limitations of Ab treatment efficacy; (1) low antigen (Env) density on (reactivated) HIV-1 infected cells, (2) high viral genetic diversity, (3) exhaustion of immune cells and (4) short half-life of Abs. In this review we summarize and discuss preclinical and clinical studies in which anti-HIV-1 Abs demonstrated potent viral control, and describe the development of engineered Abs that could address the limitations described above. Next generation Abs with optimized effector function, avidity, effector cell recruitment and immune cell activation have the potential to contribute to an HIV-1 cure or durable control.

Dynamic trafficking and turnover of JAM-C is essential for endothelial cell migration

Junctional complexes between endothelial cells form a dynamic barrier that hinders passive diffusion of blood constituents into interstitial tissues. Remodelling of junctions is an essential process during leukocyte trafficking, vascular permeability, and angiogenesis. However, for many junctional proteins, the mechanisms of junctional remodelling have yet to be determined. Here, we used receptor mutagenesis, horseradish peroxidase (HRP), and ascorbate peroxidase 2 (APEX-2) proximity labelling, alongside light and electron microscopy (EM), to map the intracellular trafficking routes of junctional adhesion molecule-C (JAM-C). We found that JAM-C cotraffics with receptors associated with changes in permeability such as vascular endothelial cadherin (VE-Cadherin) and neuropilin (NRP)-1 and 2, but not with junctional proteins associated with the transmigration of leukocytes. Dynamic JAM-C trafficking and degradation are necessary for junctional remodelling during cell migration and angiogenesis. By identifying new potential trafficking machinery, we show that a key point of regulation is the ubiquitylation of JAM-C by the E3 ligase Casitas B-lineage lymphoma (CBL), which controls the rate of trafficking versus lysosomal degradation.

Targeting Siglecs with a sialic acid-decorated nanoparticle abrogates inflammation

Sepsis is the most frequent cause of death in hospitalized patients, and severe sepsis is a leading contributory factor to acute respiratory distress syndrome (ARDS). At present, there is no effective treatment for these conditions, and care is primarily supportive. Murine sialic acid-binding immunoglobulin-like lectin-E (Siglec-E) and its human orthologs Siglec-7 and Siglec-9 are immunomodulatory receptors found predominantly on hematopoietic cells. These receptors are important negative regulators of acute inflammatory responses and are potential targets for the treatment of sepsis and ARDS. We describe a Siglec-targeting platform consisting of poly(lactic-co-glycolic acid) nanoparticles decorated with a natural Siglec ligand, di(α2→8) N-acetylneuraminic acid (α2,8 NANA-NP). This nanoparticle induced enhanced oligomerization of the murine Siglec-E receptor on the surface of macrophages, unlike the free α2,8 NANA ligand. Furthermore, treatment of murine macrophages with these nanoparticles blocked the production of lipopolysaccharide-induced inflammatory cytokines in a Siglec-E-dependent manner. The nanoparticles were also therapeutically beneficial in vivo in both systemic and pulmonary murine models replicating inflammatory features of sepsis and ARDS. Moreover, we confirmed the anti-inflammatory effect of these nanoparticles on human monocytes and macrophages in vitro and in a human ex vivo lung perfusion (EVLP) model of lung injury. We also established that interleukin-10 (IL-10) induced Siglec-E expression and α2,8 NANA-NP further augmented the expression of IL-10. Indeed, the effectiveness of the nanoparticle depended on IL-10. Collectively, these results demonstrated a therapeutic effect of targeting Siglec receptors with a nanoparticle-based platform under inflammatory conditions.

Mathematical models of the VEGF receptor and its role in cancer therapy

We present an analysis of a stochastic model of the vascular endothelial growth factor (VEGF) receptor. This analysis addresses the contribution of ligand-binding-induced oligomerization, activation of src-homology 2 domain-carrying kinases and receptor internalization in the overall behaviour of the VEGF/VEGF receptor (VEGFR) system. The analysis is based upon a generalization of a Wentzel-Kramers-Brillouin (WKB) approximation of the solution of the corresponding master equation. We predict that tumour-mediated overexpression of VEGFRs in the endothelial cells (ECs) of tumour-engulfed vessels leads to an increased sensitivity of the ECs to low concentrations of VEGF, thus endowing the tumour with increased resistance to anti-angiogenic treatment.

The evolution of mathematical immunology

The types of mathematical models used in immunology and their scope have changed drastically in the past 10 years. Classical models were based on ordinary differential equations (ODEs), difference equations, and cellular automata. These models focused on the 'simple' dynamics obtained between a small number of reagent types (e.g. one type of receptor and one type of antigen or two T-cell populations). With the advent of high-throughput methods, genomic data, and unlimited computing power, immunological modeling shifted toward the informatics side. Many current applications of mathematical models in immunology are now focused around the concepts of high-throughput measurements and system immunology (immunomics), as well as the bioinformatics analysis of molecular immunology. The types of models have shifted from mainly ODEs of simple systems to the extensive use of Monte Carlo simulations. The transition to a more molecular and more computer-based attitude is similar to the one occurring over all the fields of complex systems analysis. An interesting additional aspect in theoretical immunology is the transition from an extreme focus on the adaptive immune system (that was considered more interesting from a theoretical point of view) to a more balanced focus taking into account the innate immune system also. We here review the origin and evolution of mathematical modeling in immunology and the contribution of such models to many important immunological concepts.

Stochastic models of receptor oligomerization by bivalent ligand

In this paper, we develop stochastic models of receptor binding by a bivalent ligand. A detailed kinetic study allows us to analyse the role of cross-linking in cell activation by receptor oligomerization. We show how oligomer formation could act to buffer intracellular signalling against stochastic fluctuations. In addition, we put forward the hypothesis that formation of long linear oligomers increases the range of ligand concentration to which the cell is responsive, whereas formation of closed oligomers increases ligand concentration specificity. Thus, different physiological functions requiring different degrees of specificity to ligand concentration would favour formation of oligomers with different lengths and geometries. Furthermore, provided that ligand concentration specificity is taken as a design principle, our model enables us to estimate parameters, such as the minimum proportion of receptors, that must engage in oligomer formation in order to trigger a cellular response.

A new bell-shaped function for idiotypic interactions based on cross-linking

Most recent models of the immune network are based upon a phenomenological log bell-shaped interaction function. This function depends on a single parameter, the "field," which is the sum of all ligand concentrations weighted by their respective affinities. The typical behavior of these models is dominated by percolation, a phenomenon in which a local stimulus spreads globally throughout the network. The usual reason for employing a log bell-shaped interaction function is that B cells are activated by cross-linking of their surface immunoglobulin receptors. Here we formally derive a new phenomenological log bell-shaped function from the chemistry of receptor cross-linking by bivalent ligand. Specifying how this new function depends on the ligand concentrations requires two fields: a binding field and a cross-linking field. When we compare the activation functions for ligand-receptor pairs with different affinities, the one-field and the two-field functions differ markedly. In the case of the one-field activation function, its graph is shifted to increasingly higher concentration as the affinity decreases but keeps its width and height. In the case of the two-field activation function, the graph of a low-affinity interaction is nested within the graphs of all higher-affinity interactions. We show that this difference in the relations among activation functions for different affinities radically changes the network behavior. In models that described B cell proliferation using the one-field activation function, network behavior was dominated by low-affinity interactions. Conversely, in our new model, the high-affinity interactions are the most significant. As a consequence, percolation is no longer the only typical network behavior.