Multi-Stage Regulation, a Key to Reliable Adaptive

ABSTRACT A general “multi-stage ” regulation model, based on linearly connected regulatory units, is formulated to demonstrate how biochemical pathways may achieve high levels of accuracy. The general mechanism, which is robust to changes in biochemical parameters, such as protein concentration and kinetic rate constants, is incorporated into a mathematical model of the bacterial chemotaxis network and provides a new framework for explaining regulation and adaptiveness in this extensively studied system. Although conventional theories suggest that methylation feedback pathways are responsible for chemotactic regulation, the model, which is deduced from known experimental data, indicates that protein interactions downstream of the bacterial receptor complex, such as CheAs and CheZ, may play a crucial and complementary role

Analysis of Influenza and RSV dynamics in the community using a ‘Local Transmission Zone’ approach

Understanding the dynamics of pathogen spread within urban areas is critical for the effective prevention and containment of communicable diseases. At these relatively small geographic scales, short-distance interactions and tightly knit sub-networks dominate the dynamics of pathogen transmission; yet, the effective boundaries of these micro-scale groups are generally not known and often ignored. Using clinical test results from hospital admitted patients we analyze the spatio-temporal distribution of Influenza Like Illness (ILI) in the city of Jerusalem over a period of three winter seasons. We demonstrate that this urban area is not a single, perfectly mixed ecology, but is in fact comprised of a set of more basic, relatively independent pathogen transmission units, which we term here Local Transmission Zones, LTZs. By identifying these LTZs, and using the dynamic pathogen-content information contained within them, we are able to differentiate between disease-causes at the individual patient level often with near-perfect predictive accuracy

Immune response and virus population composition: HIV as a case study

Based on the current understanding of the immune response, we present what we believe to be a new model of intrahost virus dynamics. The model takes into account the relationship between virus replication rate and the level of antigen displayed by infected cells, and shows how the cell-directed immune response controls both virus load and virus replication rate. In contrast to conventional wisdom, it shows that the predominant virus variant does not necessarily have the highest replication rate. A strong immune response produces a selective advantage for latent viruses, whereas a deteriorating immune response invites in viruses of higher replication rates. The model is analysed in light of the well-studied HIV/AIDS disease progression, and shows how a wide range of major, seemingly unrelated issues in the study of HIV may be accounted for in a simple and uni® ed manner

Binding of the Fap2 Protein of Fusobacterium nucleatum to Human Inhibitory Receptor TIGIT Protects Tumors from Immune Cell Attack

Bacteria, such as Fusobacterium nucleatum, are present in the tumor microenvironment. However, the immunological consequences of intra-tumoral bacteria remain unclear. Here, we have shown that natural killer (NK) cell killing of various tumors is inhibited in the presence of various F. nucleatum strains. Our data support that this F. nucleatum- mediated inhibition is mediated by human, but not by mouse TIGIT, an inhibitory receptor present on all human NK cells and on various T cells. Using a library of F. nucleatum mutants, we found that the Fap2 protein of F. nucleatum directly interacted with TIGIT, leading to the inhibition of NK cell cytotoxicity. We have further demonstrated that tumor- infiltrating lymphocytes expressed TIGIT and that T cell activities were also inhibited by F. nucleatum via Fap2. Our results identify a bacterium- dependent, tumorimmune evasion mechanism in which tumors exploit the Fap2 protein of F. nucleatum to inhibit immune cell activity via TIGIT