Ten years ago, a group of researchers, led by Francisco Varela, were proposing an alternative vision of the immune system main behavior and function. I was part of this group. This new vision saw the immune system not as behaving distinctively with self and non-self or according to any dichotomy imposed a priori and from outside (the self-recognition vision), but rather as behaving in a unique way. From this indifferent behavior, any external impact would progressively been treated in two different ways, reactive and tolerant, but now, consequently and from inside the system (the self-assertion view). This paper will recall, through a very artificial simulation, the difference existing between these two visions. Also at that time, we believed that, from an engineering perspective, this new vision, emphasizing more the adaptability and the need for endogenous constraints than the recognition and the defensive ability, although less obvious to accept than the classical defensive one, should be more beneficial. These last ten years proved that we haven’t been convincing enough, and in this paper I resume the crusade.
Biology gives us numerous examples of self-assertional systems whose essence does not precede their existence but is rather revealed through it. Immune system is one of them. The fact of behaving in order not only to satisfy external constraints as a pre-fixed set of possible environments and objectives, but also to satisfy internal “viability” constraints justifies a sharper focus. Adaptability, creativity and memory are certainly interesting “side-effects” of such a tendency for self-consistency. However in this paper, we adopted a largely pragmatic attitude attempting to find the best hybridizing between the biological lessons and the engineering needs. The great difficulty, also shared by neural net and GA users, remains the precise localisation of the frontier where the biological reality must give way to a directed design.
The following basic question is studied here: In the relatively stable molecular environment of a vertebrate body, can a dynamic idiotypic immune network develop a natural tolerance to endogenous components? The approach is based on stability analyses and computer simulation using a model that takes into account the dynamics of two agents of the immune system, namely B-lymphocytes and antibodies. The study investigates the behavior of simple immune networks in interaction with an antigen whose concentration is held constant as a function of the symmetry properties of the connectivity matrix of the network. Current idiotypic network models typically become unstable in the presence of this type of antigen. It is shown that idiotypic networks of a particular connectivity show tolerance towards auto-antigen without the need for ad hoc mechanisms that prevent an immune response. These tolerant network structures are characterized by aperiodic behavior in the absence of auto-antigen. When coupled to an auto-antigen, the chaotic attractor degenerates into one of several periodic ones, and at least one of them is stable. The connectivity structure needed for this behavior allows the system to adopt particular dynamic concentration patterns which do not lead to an unbounded immune response. Possible implications for the understanding of autoimmune disease and its treatment are discussed.
This article investigates the following basic question: in the relatively stable molecular environment of a vertebrate body, can a dynamic idiotypic immune network develop a natural tolerance to endogenous components? Our approach is based on stability analysis and computer simulation using a model that takes into account the dynamics of two agents of the immune system, namely, B-lymphocytes and antibodies. We investigate the behavior of simple immune networks in interaction with an Ag whose concentration is being held constant as a function of the connectivity matrix of the network. The latter is characterized by the total number of clones, N, and the number of clones, C, with which each clone interacts. The idiotypic network models typically become unstable in the presence of this type of Ag. We show that idiotypic networks that can be found in particular connected regions of NC-space show tolerance towards auto-Ag without the need for ad hoc mechanisms that prevent an immune response. These tolerant network structures provide dynamical regimes in which the clone which interacts with the auto-Ag is suppressed instead of being excited such that an unbounded immune response does not occur. Possible implications for the future treatment of auto-immune disease such as IvIg-treatment are discussed in the light of these results. Moreover, we propose an experimental approach to verify the results of the present theoretical study.
Based upon the shape-space formalism, a model of an idiotypic network including both bound and free immunoglobulins is simulated. Our point of interest is the network development in the context of self antigens. The investigations are organized around simulations initiated by various spatial configurations of antigens; the behavior of the system with respect to antigens is analyzed in terms of morphogenetic processes occurring in the shape space. For certain values of the parameters, the network expands by traveling waves. The resulting spatial pattern is a partition of the shape space into zones where introduction of an antigen entails an infinite growth of the clones binding to it, and into zones where, on the contrary, the anti-antigen idiotypes decrease. Among the parameter combinations tested, some produce a partition that remains static whereas others produce a partition that changes in time. For other values of the parameters, the patterns generated do not partition shape space into zones; in these cases, it is observed that the system systematically explodes when an antigen is present.