Biomedical subjects
S A Kauffman
Publications and source records attributed to S A Kauffman.
Coevolution to the edge of chaos: coupled fitness landscapes, poised states, and coevolutionary avalanches.
We introduce a broadened framework to study aspects of coevolution based on the NK class of statistical models of rugged fitness landscapes. In these models the fitness contribution of each of N genes in a genotype depends epistatically on K other genes. Increasing epistatic interactions increases the rugged multipeaked character of the fitness landscape. Coevolution is thought of, at the lowest level, as a coupling of landscapes such that adaptive moves by one player deform the landscapes of its immediate partners. In these models we are able to tune the ruggedness of landscapes, how richly intercoupled any two landscapes are, and how many other players interact with each player. All these properties profoundly alter the character of the coevolutionary dynamics. In particular, these parameters govern how readily coevolving ecosystems achieve Nash equilibria, how stable to perturbations such equilibria are, and the sustained mean fitness of coevolving partners. In turn, this raises the possibility that an evolutionary metadynamics due to natural selection may sculpt landscapes and their couplings to achieve coevolutionary systems able to coadapt well. The results suggest that sustained fitness is optimized when landscape ruggedness relative to couplings between landscapes is tuned such that Nash equilibria just tenuously form across the ecosystem. In this poised state, coevolutionary avalanches appear to propagate on all length scales in a power law distribution. Such avalanches may be related to the distribution of small and large extinction events in the record.
Antichaos and adaptation.
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Drosophila segmentation: supercomputer simulation of prepattern hierarchy.
Spontaneous prepattern formation in a two level hierarchy of reaction-diffusion systems is simulated in three space co-ordinates and time, mimicking gap gene and primary pair-rule gene expression. The model rests on the idea of Turing systems of the second kind, in which one prepattern generates position dependent rate constants for a subsequent reaction-diffusion system. Maternal genes are assumed responsible for setting up gradients from the anterior and posterior ends, one of which is needed to stabilize a double period prepattern suggested to underly the read out of the gap genes. The resulting double period pattern in turn stabilizes the next prepattern in the hierarchy, which has a short wavelength with many characteristics of the stripes seen in actual primary pair-rule gene expression. Without such hierarchical stabilization, reaction-diffusion mechanisms yield highly patchy short wave length patterns, and thus unreliable stripes. The model yields seven stable stripes located in the middle of the embryo, with the potential for additional expression near the poles, as observed experimentally. The model does not rely on specific chemical reaction kinetics, rather the effect is general to many such kinetic schemes. This makes it robust to parameter changes, and it has good potential for adapting to size and shape changes as well. The study thus suggests that the crucial organizing principle in early Drosophila embryogenesis is based on global field mechanisms, not on particular local interactions.
Spatial harmonics and pattern specification in early Drosophila development. Part I. Bifurcation sequences and gene expression.
Molecular probes have now provided an unprecedented wealth of detail revealing the changing spatial patterns of gene products in early Drosophila development. This is examined for dynamic properties which might provide insights into the underlying behaviour of the patterning process. What emerges is that transcripts and protein products of members of the major categories of zygotically active genes involved in segmentation pass through transient spatial patterns that are suggestive of harmonic sequences arising from spatial frequency-doubling bifurcations. That is to say, these patterns are typically periodic in space and show a doubling in the number of domains of spatial expression as development proceeds. One of these patterns reflects the primary functional role of the gene in the establishment of the spatial pattern. The different categories of segmentation gene pass through these transients at different rates, those with the longest functional wavelength progressing most slowly. Each gene in a category has its own unique phase relationship to other members, as well as particular variations on the harmonic sequence theme. The result is that the developing embryo experiences a spatial hierarchy of phase-shifted patterning influences that span the range from the whole embryo to single segments, providing progressively more spatial resolution in the patterning process. The characteristic transients and the dynamic relationships between genes of the different categories suggest that gene products expressed in longer-wavelength patterns act as bifurcation parameters on the dynamic system generating the next shorter wavelength category. Such parametric influences are known to result in frequency-doubling bifurcations in Turing reaction-diffusion systems. A general model is proposed of a hierarchically-nested set of quasi-autonomous dynamic systems involving gene activities that can generate the progressively finer spatial order that emerges during embryogenesis. This model has implications for the general stability properties of evolving epigenetic systems.
Spatial harmonics and pattern specification in early Drosophila development. Part II. The four colour wheels model.
We review the evidence presented in Part I showing that transcripts and protein products of maternal, gap, pair-rule, and segment polarity genes exhibit increasingly complex, multipeaked longitudinal waveforms in the early Drosophila embryo. The central problem we address in Part II is the use the embryo makes of these wave forms to specify longitudinal pattern. Based on the fact that mutants of many of these genes generate deletions and mirror symmetrical duplications of pattern elements on length scales ranging from about half the egg to within segments, we propose that position is specified by measuring a "phase angle" by use of the ratios of two or more variables. Pictorially, such a phase angle can be thought of as a colour on a colour wheel. Any such model contains a phaseless singularity where all or many phases, or colours, come together. We suppose as well that positional values sufficiently close to the singularity are meaningless, hence a "dead zone". Duplications and deletions are accounted for by deformation of the cycle of morphogen values occurring along the antero-posterior axis. If the cycle of values surrounds the singularity and lies outside the dead zone, pattern is normal. If the curve transects the dead zone, pattern elements are deleted. If the curve lies entirely on one side of the singularity, pattern elements are deleted and others are duplicated with mirror symmetry. The existence of different wavelength transcript patterns in maternal, gap, pair-rule, and segment polarity genes and the roles of those same genes in generating deletions and mirror symmetrical duplications on a variety of length scales lead us to propose that position is measured simultaneously on at least four colour wheels, which cycle different numbers of times along the anterior-posterior axis. These yield progressively finer grained positional information. Normal pattern specification requires a unique angle, outside of the dead zone, from each of the four wheels. Deformations of the cycle of gene product concentrations yield the deletions and mirror symmetric duplications observed in the mutants discussed. The alternative familiar hypothesis that longitudinal position is specified in an "on" "off" combinatorial code does not readily account for the duplication deletion phenomena.
The NK model of rugged fitness landscapes and its application to maturation of the immune response.
Adaptive evolution is, to a large extent, a complex combinatorial optimization process. Such processes can be characterized as "uphill walks on rugged fitness landscapes". Concrete examples of fitness landscapes include the distribution of any specific functional property such as the capacity to catalyze a specific reaction, or bind a specific ligand, in "protein space". In particular, the property might be the affinity of all possible antibody molecules for a specific antigenic determinant. That affinity landscape presumably plays a critical role in maturation of the immune response. In this process, hypermutation and clonal selection act to select antibody V region mutant variants with successively higher affinity for the immunizing antigen. The actual statistical structure of affinity landscapes, although knowable, is currently unknown. Here, we analyze a class of mathematical models we call NK models. We show that these models capture significant features of the maturation of the immune response, which is currently thought to share features with general protein evolution. The NK models have the important property that, as the parameter K increases, the "ruggedness" of the NK landscape varies from a single peaked "Fujiyama" landscape to a multi-peaked "badlands" landscape. Walks to local optima on such landscapes become shorter as K increases. This fact allows us to choose a value of K that corresponds to the experimentally observed number of mutational "steps", 6-8, taken as an antibody sequence matures. If the mature antibody is taken to correspond to a local optimum in the model, tuning the model requires that K be about 40, implying that the functional contribution of each amino acid in the V region is affected by about 40 others. Given this value of K, the model then predicts several features of "antibody space" that are in qualitative agreement with experiment: (1) The fraction of fitter variants of an initial "roughed in" germ line antibody amplified by clonal selection is about 1-2%. (2) Mutations at some sites of the mature antibody hardly affect antibody function at all, but mutations at other sites dramatically decrease function. (3) The same "roughed in" antibody sequence can "walk" to many mature antibody sequences. (4) Many adaptive walks can end on the same local optimum. (5) Comparison of different mature sequences derived from the same initial V region shows evolutionary hot spots and parallel mutations. All these predictions are open to detailed testing by obtaining monoclonal antibodies early in the immune response and carrying out in vitro mutagenesis and adaptive hill climbing with respect to affinity for the immunizing antigen.
Modeling adaptive biological systems.
During the evolution of many systems found in nature, both the system composition and the interactions between components will vary. Equating the dimension with the number of different components, a system which adds or deletes components belongs to a class of dynamical systems with a finite dimensional phase space of variable dimension. We present two models of biochemical systems with a variable phase space, a model of autocatalytic reaction networks in the prebiotic soup and a model of the idiotypic network of the immune system. Each model contains characteristic meta-dynamical rules for constructing equations of motion from component properties. The simulation of each model occurs on two levels. On one level, the equations of motion are integrated to determine the state of each component. On a second level, algorithms which approximate physical processes in the real system are employed to change the equations of motion. Models with meta-dynamical rules possess several advantages for the study of evolving systems. First, there are no explicit fitness functions to determine how the components of the model rank in terms of survivability. The success of any component is a function of its relationship to the rest of the system. A second advantage is that since the phase space representation of the system is always finite but continually changing, we can explore a potentially infinite phase space which would otherwise be inaccessible with finite computer resources. Third, the enlarged capacity of systems with meta-dynamics for variation allows us to conduct true evolution experiments. The modeling methods presented here can be applied to many real biological systems. In the two studies we present, we are investigating two apparent properties of adaptive networks. With the simulation of the prebiotic soup, we are most interested in how a chemical reaction network might emerge from an initial state of relative disorder. With the study of the immune system, we study the self-regulation of the network including its ability to distinguish between species which are part of the network and those which are not.
Control of sequential compartment formation in Drosophila.
During development of Drosophila melanogaster, sequential commitment to alternative development programs occurs in neighboring groups of cells. These commitments appear to be reflected by lines of clonal restriction, called compartmental boundaries, which progressively subdivide the early embryo, and later the imaginal discs, which give rise to different adult appendages. We propose that a reaction-diffusion system acts throughout development and generates a sequence of differently shaped chemical patterns. These patterns account for the sequence and geometries of compartmental boundaries, and predict that each terminal compartment is specifiied by a unique combination of binary choices made during its formation. This binary "code" interprets coherently the patterned metaplasia seen in transdetermination and homeotic mutations.
Novel behaviour of the mitotic clock in Physarum.
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Premature replication of late S period DNA regions in early S nuclei transferred to late S cytoplasm by fusion in Physarum polycephalum.
Fusion of a late S period plasmodium of Physarum polycephalum to an early S period plasmodium causes premature replication of late S replicating regions in the nuclei of the early S plasmodium. The extent of ahead-of-schedule replication of late S replicating regions in early S period nuclei increases to a plateau of 16-20% for fusions with 40-70 min of phase difference, then declines for larger phase differences. The stimulatory factors for late S replicative units are present only in late S plasmodia and appear to act only on late S regions. Once replicated, early S replicating regions are not stimulated to replicate again by fusion to a plasmodium entering the S period. Our data do not discriminate between anti-termination of replication by factors of stop sites on long replicons, and a sequential initiation of replication on new, possibly non-adjacent regions, but does provide evidence that the stimulatory factors are distinct from one another and specific for certain target replicative units.