The immune system uses many strategies to generate its enormous repertoire of diverse antibodies, but their relative importance is not understood. Here we address the contribution of antibody gene libraries to the antibody repertoire. We introduce a general framework, in which we can study many antibody-pathogen matching rules, including the widely-used shape-space model (Perelson and Oster, 1979). We use the genetic algorithm as a model of evolution to investigate the type of antibody repertoires that might evolve in relation to a given pathogenic environment. For the antibody/pathogen matching rules that we studied, the scaling relation between fitness and the size of the evolved antibody library is only a shifted variant of the scaling relation that we obtain with random libraries of the same size. We discuss how our results compare to the antibodies that are expressed in newborns, and we discuss the implications of our results for recent experiments with phage a...

Artificial Immune Systems (AIS) have been shown to be useful, practical and realisable approaches to real-world problems [5]. Most AIS implementations are based around a canonical algorithm such as clonotypic learning [4], which we may think of as individual, lifetime learning. Yet a species also learns. Gene libraries are often thought of as a biological mechanism for generating combinatorial diversity of antibodies. However, they also bias the antibody creation process, so that they can be viewed as a way of guiding the lifetime learning mechanisms. Over time, the gene libraries in a species will evolve to an appropriate bias for the expected environment (based on species memory). Thus gene libraries are a form of meta-learning which could be useful for AIS. Yet they are hardly ever used. In this paper we consider some of the possible benefits and implications of incorporating the evolution of gene libraries into AIS practice. We examine some of the issues that must be considered if the implementation is to be successful and beneficial.

Evidence for somatic hypermutation of immunoglobulin genes has been observed in all the species in which immunoglobulins have been found. Previous studies have suggested that codon usage in Ig V genes is such that the sequence-specificity of somatic hypermutation results in greater mutability in complementarity-determining regions of the gene than in the framework regions. We have developed a new resampling-based methodology to explore genetic plasticity in individual V genes and in V gene families in a statistically meaningful way. We determine what factors contribute to this mutability difference, and characterize the strength of selection for this effect. We nd that although the codon usage in Ig V genes renders them distinct among translationally equivalent sequences with random codon usage, they are nevertheless far from being optimal in this regard. We find that the mutability patterns in a number of species are similar to those we find for human sequences. Interestingly, sheep seque...

The dynamic clonal selection algorithm (dynamiCS) was created to tackle the difficulties of anomaly detection in continuously changing environments (Kim and Bentley, 2002a). This algorithm was extended in a sister paper (Kim and Bentley, 2002b), so that memory detectors that are no longer valid are automatically deleted. Here we describe a further extension to the system: the use of hypermutation on deleted memory detectors to produce, in effect, a "virtual gene library" which seeds the immature detector population.