A penetratin-derived peptide reduces the membrane permeabilization and cell toxicity of α-synuclein oligomers

Parkinson's disease is a neurodegenerative movement disorder associated with the intracellular aggregation of α-synuclein (α-syn). Cytotoxicity is mainly associated with the oligomeric species (αSOs) formed at early stages in α-syn aggregation. Consequently, there is an intense focus on the discovery of novel inhibitors such as peptides to inhibit oligomer formation and toxicity. Here, using peptide arrays, we identified nine peptides with high specificity and affinity for αSOs. Of these, peptides p194, p235, and p249 diverted α-syn aggregation from fibrils to amorphous aggregates with reduced β-structures and increased random coil content. However, they did not reduce αSO cytotoxicity and permeabilization of large anionic unilamellar vesicles. In parallel, we identified a non-self-aggregating peptide (p216), derived from the cell-penetrating peptide penetratin, which showed 12-fold higher binding affinity to αSOs than to α-syn monomers (K_d^app 2.7 and 31.2 μM, respectively). p216 reduced αSOs-induced large anionic unilamellar vesicle membrane permeability at 10^-1 to 10^-3 mg/ml by almost 100%, was not toxic to SH-SY5Y cells, and reduced αSOs cytotoxicity by about 20%. We conclude that p216 is a promising starting point from which to develop peptides targeting toxic αSOs in Parkinson's disease.

Quantitating denaturation by formic acid: imperfect repeats are essential to the stability of the functional amyloid protein FapC

Bacterial functional amyloids are evolutionarily optimized to aggregate, so much so that the extreme robustness of functional amyloid makes it very difficult to examine their structure-function relationships in a detailed manner. Previous work has shown that functional amyloids are resistant to conventional chemical denaturants, but they dissolve in formic acid (FA) at high concentrations. However, systematic investigation requires a quantitative analysis of FA's ability to denature proteins. Amyloid formed by Pseudomonas sp. protein FapC provides an excellent model to investigate FA denaturation. It contains three imperfect repeats, and stepwise removal of these repeats slows fibrillation and increases fragmentation during aggregation. However, the link to stability is unclear. We first calibrated FA denaturation using three small, globular, and acid-resistant proteins. This revealed a linear relationship between the concentration of FA and the free energy of unfolding with a slope of mFA+pH (the combined contribution of FA and FA-induced lowering of pH), as well as a robust correlation between protein size and mFA+pH We then measured the solubilization of fibrils formed from different FapC variants with varying numbers of repeats as a function of the concentration of FA. This revealed a decline in the number of residues driving amyloid formation upon deleting at least two repeats. The midpoint of denaturation declined with the removal of repeats. Complete removal of all repeats led to fibrils that were solubilized at FA concentrations 2-3 orders of magnitude lower than the repeat-containing variants, showing that at least one repeat is required for the stability of functional amyloid.

The interactome of stabilized α-synuclein oligomers and neuronal proteins

While it is generally accepted that α-synuclein oligomers (αSOs) play an important role in neurodegeneration in Parkinson's disease, the basis for their cytotoxicity remains unclear. We have previously shown that docosahexaenoic acid (DHA) stabilizes αSOs against dissociation without compromising their ability to colocalize with glutamatergic synapses of primary hippocampal neurons, suggesting that they bind to synaptic proteins. Here, we develop a proteomic screen for putative αSO binding partners in rat primary neurons using DHA-stabilized human αSOs as a bait protein. The protocol involved co-immunoprecipitation in combination with a photoactivatable heterobifunctional sulfo-LC-SDA crosslinker which did not compromise neuronal binding and preserved the interaction between the αSOs-binding partners. We identify in total 29 proteins associated with DHA-αSO of which eleven are membrane proteins, including synaptobrevin-2B (VAMP-2B), the sodium-potassium pump (Na⁺ /K⁺ ATPase), the V-type ATPase, the voltage-dependent anion channel and calcium-/calmodulin-dependent protein kinase type II subunit gamma; only these five hits were also found in previous studies which used unmodified αSOs as bait. We also identified Rab-3A as a target with likely disease relevance. Three out of four selected hits were subsequently validated with dot-blot binding assays. In addition, likely binding sites on these ligands were identified by computational analysis, highlighting a diversity of possible interactions between αSOs and target proteins. These results constitute an important step in the search for disease-modifying treatments targeting toxic αSOs.

The development of a new computer adaptive test to evaluate chorea in Huntington disease: HDQLIFE Chorea

PURPOSE

Huntington's disease (HD) is an autosomal dominant neurodegenerative disease associated with motor, behavioral, and cognitive deficits. The hallmark symptom of HD, chorea, is often the focus of HD clinical trials. Unfortunately, there are no self-reported measures of chorea. To address this shortcoming, we developed a new measure of chorea for use in HD, HDQLIFE Chorea.

METHODS

Qualitative data and literature reviews were conducted to develop an initial item pool of 141 chorea items. An iterative process, including cognitive interviews, expert review, translatability review, and literacy review, was used to refine this item pool to 64 items. These 64 items were field tested in 507 individuals with prodromal and/or manifest HD. Exploratory and confirmatory factor analyses (EFA and CFA, respectively) were conducted to identify a unidimensional set of items. Then, an item response theory graded response model (GRM) and differential item functioning analyses were conducted to select the final items for inclusion in this measure.

RESULTS

EFA and CFA supported the retention of 34 chorea items. GRM and DIF supported the retention of all of these items in the final measure. GRM calibration data were used to inform the selection of a 6-item, static short form and to program the HDQLIFE Chorea computer adaptive test (CAT). CAT simulation analyses indicated a 0.99 correlation between the CAT scores and the full item bank.

CONCLUSIONS

The new HDQLIFE Chorea CAT and corresponding 6-item short form were developed using established rigorous measurement development standards; this is the first self-reported measure developed to evaluate the impact of chorea on HRQOL in HD. This development work indicates that these measures have strong psychometric properties; future work is needed to establish test-retest reliability and responsiveness to change.

Generative models versus underlying symmetries to explain biological pattern

Mathematical models play an increasingly important role in the interpretation of biological experiments. Studies often present a model that generates the observations, connecting hypothesized process to an observed pattern. Such generative models confirm the plausibility of an explanation and make testable hypotheses for further experiments. However, studies rarely consider the broad family of alternative models that match the same observed pattern. The symmetries that define the broad class of matching models are in fact the only aspects of information truly revealed by observed pattern. Commonly observed patterns derive from simple underlying symmetries. This article illustrates the problem by showing the symmetry associated with the observed rate of increase in fitness in a constant environment. That underlying symmetry reveals how each particular generative model defines a single example within the broad class of matching models. Further progress on the relation between pattern and process requires deeper consideration of the underlying symmetries.

Natural selection. VII. History and interpretation of kin selection theory

Kin selection theory is a kind of causal analysis. The initial form of kin selection ascribed cause to costs, benefits and genetic relatedness. The theory then slowly developed a deeper and more sophisticated approach to partitioning the causes of social evolution. Controversy followed because causal analysis inevitably attracts opposing views. It is always possible to separate total effects into different component causes. Alternative causal schemes emphasize different aspects of a problem, reflecting the distinct goals, interests and biases of different perspectives. For example, group selection is a particular causal scheme with certain advantages and significant limitations. Ultimately, to use kin selection theory to analyse natural patterns and to understand the history of debates over different approaches, one must follow the underlying history of causal analysis. This article describes the history of kin selection theory, with emphasis on how the causal perspective improved through the study of key patterns of natural history, such as dispersal and sex ratio, and through a unified approach to demographic and social processes. Independent historical developments in the multivariate analysis of quantitative traits merged with the causal analysis of social evolution by kin selection.

Natural selection. V. How to read the fundamental equations of evolutionary change in terms of information theory

The equations of evolutionary change by natural selection are commonly expressed in statistical terms. Fisher's fundamental theorem emphasizes the variance in fitness. Quantitative genetics expresses selection with covariances and regressions. Population genetic equations depend on genetic variances. How can we read those statistical expressions with respect to the meaning of natural selection? One possibility is to relate the statistical expressions to the amount of information that populations accumulate by selection. However, the connection between selection and information theory has never been compelling. Here, I show the correct relations between statistical expressions for selection and information theory expressions for selection. Those relations link selection to the fundamental concepts of entropy and information in the theories of physics, statistics and communication. We can now read the equations of selection in terms of their natural meaning. Selection causes populations to accumulate information about the environment.

Fisher's fundamental theorem of natural selection

Fisher's Fundamental Theorem of natural selection is one of the most widely cited theories in evolutionary biology. Yet it has been argued that the standard interpretation of the theorem is very different from what Fisher meant to say. What Fisher really meant can be illustrated by looking in a new way at a recent model for the evolution of clutch size. Why Fisher was misunderstood depends, in part, on the contrasting views of evolution promoted by Fisher and Wright.

Natural selection. IV. The Price equation

The Price equation partitions total evolutionary change into two components. The first component provides an abstract expression of natural selection. The second component subsumes all other evolutionary processes, including changes during transmission. The natural selection component is often used in applications. Those applications attract widespread interest for their simplicity of expression and ease of interpretation. Those same applications attract widespread criticism by dropping the second component of evolutionary change and by leaving unspecified the detailed assumptions needed for a complete study of dynamics. Controversies over approximation and dynamics have nothing to do with the Price equation itself, which is simply a mathematical equivalence relation for total evolutionary change expressed in an alternative form. Disagreements about approach have to do with the tension between the relative valuation of abstract versus concrete analyses. The Price equation's greatest value has been on the abstract side, particularly the invariance relations that illuminate the understanding of natural selection. Those abstract insights lay the foundation for applications in terms of kin selection, information theory interpretations of natural selection and partitions of causes by path analysis. I discuss recent critiques of the Price equation by Nowak and van Veelen.

Natural selection. III. Selection versus transmission and the levels of selection

George Williams defined an evolutionary unit as hereditary information for which the selection bias between competing units dominates the informational decay caused by imperfect transmission. In this article, I extend Williams' approach to show that the ratio of selection bias to transmission bias provides a unifying framework for diverse biological problems. Specific examples include Haldane and Lande's mutation-selection balance, Eigen's error threshold and quasispecies, Van Valen's clade selection, Price's multilevel formulation of group selection, Szathmáry and Demeter's evolutionary origin of primitive cells, Levin and Bull's short-sighted evolution of HIV virulence, Frank's timescale analysis of microbial metabolism and Maynard Smith and Szathmáry's major transitions in evolution. The insights from these diverse applications lead to a deeper understanding of kin selection, group selection, multilevel evolutionary analysis and the philosophical problems of evolutionary units and individuality.

Natural selection. II. Developmental variability and evolutionary rate

In classical evolutionary theory, genetic variation provides the source of heritable phenotypic variation on which natural selection acts. Against this classical view, several theories have emphasized that developmental variability and learning enhance nonheritable phenotypic variation, which in turn can accelerate evolutionary response. In this paper, I show how developmental variability alters evolutionary dynamics by smoothing the landscape that relates genotype to fitness. In a fitness landscape with multiple peaks and valleys, developmental variability can smooth the landscape to provide a directly increasing path of fitness to the highest peak. Developmental variability also allows initial survival of a genotype in response to novel or extreme environmental challenge, providing an opportunity for subsequent adaptation. This initial survival advantage arises from the way in which developmental variability smooths and broadens the fitness landscape. Ultimately, the synergism between developmental processes and genetic variation sets evolutionary rate.

Natural selection. I. Variable environments and uncertain returns on investment

Many studies have analysed how variability in reproductive success affects fitness. However, each study tends to focus on a particular problem, leaving unclear the overall structure of variability in populations. This fractured conceptual framework often causes particular applications to be incomplete or improperly analysed. In this article, I present a concise introduction to the two key aspects of the theory. First, all measures of fitness ultimately arise from the relative comparison of the reproductive success of individuals or genotypes with the average reproductive success in the population. That relative measure creates a diminishing relation between reproductive success and fitness. Diminishing returns reduce fitness in proportion to variability in reproductive success. The relative measurement of success also induces a frequency dependence that favours rare types. Second, variability in populations has a hierarchical structure. Variable success in different traits of an individual affects that individual's variation in reproduction. Correlation between different individuals' reproduction affects variation in the aggregate success of particular alleles across the population. One must consider the hierarchical structure of variability in relation to different consequences of temporal, spatial and developmental variability. Although a complete analysis of variability has many separate parts, this simple framework allows one to see the structure of the whole and to place particular problems in their proper relation to the general theory. The biological understanding of relative success and the hierarchical structure of variability in populations may also contribute to a deeper economic theory of returns under uncertainty.

Measurement scale in maximum entropy models of species abundance

The consistency of the species abundance distribution across diverse communities has attracted widespread attention. In this paper, I argue that the consistency of pattern arises because diverse ecological mechanisms share a common symmetry with regard to measurement scale. By symmetry, I mean that different ecological processes preserve the same measure of information and lose all other information in the aggregation of various perturbations. I frame these explanations of symmetry, measurement, and aggregation in terms of a recently developed extension to the theory of maximum entropy. I show that the natural measurement scale for the species abundance distribution is log-linear: the information in observations at small population sizes scales logarithmically and, as population size increases, the scaling of information grades from logarithmic to linear. Such log-linear scaling leads naturally to a gamma distribution for species abundance, which matches well with the observed patterns. Much of the variation between samples can be explained by the magnitude at which the measurement scale grades from logarithmic to linear. This measurement approach can be applied to the similar problem of allelic diversity in population genetics and to a wide variety of other patterns in biology.

A simple derivation and classification of common probability distributions based on information symmetry and measurement scale

Commonly observed patterns typically follow a few distinct families of probability distributions. Over one hundred years ago, Karl Pearson provided a systematic derivation and classification of the common continuous distributions. His approach was phenomenological: a differential equation that generated common distributions without any underlying conceptual basis for why common distributions have particular forms and what explains the familial relations. Pearson's system and its descendants remain the most popular systematic classification of probability distributions. Here, we unify the disparate forms of common distributions into a single system based on two meaningful and justifiable propositions. First, distributions follow maximum entropy subject to constraints, where maximum entropy is equivalent to minimum information. Second, different problems associate magnitude to information in different ways, an association we describe in terms of the relation between information invariance and measurement scale. Our framework relates the different continuous probability distributions through the variations in measurement scale that change each family of maximum entropy distributions into a distinct family. From our framework, future work in biology can consider the genesis of common patterns in a new and more general way. Particular biological processes set the relation between the information in observations and magnitude, the basis for information invariance, symmetry and measurement scale. The measurement scale, in turn, determines the most likely probability distributions and observed patterns associated with particular processes. This view presents a fundamentally derived alternative to the largely unproductive debates about neutrality in ecology and evolution.

Demography and the tragedy of the commons

Individual success in group-structured populations has two components. First, an individual gains by outcompeting its neighbours for local resources. Second, an individual's share of group success must be weighted by the total productivity of the group. The essence of sociality arises from the tension between selfish gains against neighbours and the associated loss that selfishness imposes by degrading the efficiency of the group. Without some force to modulate selfishness, the natural tendencies of self interest typically degrade group performance to the detriment of all. This is the tragedy of the commons. Kin selection provides the most widely discussed way in which the tragedy is overcome in biology. Kin selection arises from behavioural associations within groups caused either by genetical kinship or by other processes that correlate the behaviours of group members. Here, I emphasize demography as a second factor that may also modulate the tragedy of the commons and favour cooperative integration of groups. Each act of selfishness or cooperation in a group often influences group survival and fecundity over many subsequent generations. For example, a cooperative act early in the growth cycle of a colony may enhance the future size and survival of the colony. This time-dependent benefit can greatly increase the degree of cooperation favoured by natural selection, providing another way in which to overcome the tragedy of the commons and enhance the integration of group behaviour. I conclude that analyses of sociality must account for both the behavioural associations of kin selection theory and the demographic consequences of life history theory.

The common patterns of nature

We typically observe large-scale outcomes that arise from the interactions of many hidden, small-scale processes. Examples include age of disease onset, rates of amino acid substitutions and composition of ecological communities. The macroscopic patterns in each problem often vary around a characteristic shape that can be generated by neutral processes. A neutral generative model assumes that each microscopic process follows unbiased or random stochastic fluctuations: random connections of network nodes; amino acid substitutions with no effect on fitness; species that arise or disappear from communities randomly. These neutral generative models often match common patterns of nature. In this paper, I present the theoretical background by which we can understand why these neutral generative models are so successful. I show where the classic patterns come from, such as the Poisson pattern, the normal or Gaussian pattern and many others. Each classic pattern was often discovered by a simple neutral generative model. The neutral patterns share a special characteristic: they describe the patterns of nature that follow from simple constraints on information. For example, any aggregation of processes that preserves information only about the mean and variance attracts to the Gaussian pattern; any aggregation that preserves information only about the mean attracts to the exponential pattern; any aggregation that preserves information only about the geometric mean attracts to the power law pattern. I present a simple and consistent informational framework of the common patterns of nature based on the method of maximum entropy. This framework shows that each neutral generative model is a special case that helps to discover a particular set of informational constraints; those informational constraints define a much wider domain of non-neutral generative processes that attract to the same neutral pattern.

Mechanisms of pathogenesis and the evolution of parasite virulence

When studying how much a parasite harms its host, evolutionary biologists turn to the evolutionary theory of virulence. That theory has been successful in predicting how parasite virulence evolves in response to changes in epidemiological conditions of parasite transmission or to perturbations induced by drug treatments. The evolutionary theory of virulence is, however, nearly silent about the expected differences in virulence between different species of parasite. Why, for example, is anthrax so virulent, whereas closely related bacterial species cause little harm? The evolutionary theory might address such comparisons by analysing differences in tradeoffs between parasite fitness components: transmission as a measure of parasite fecundity, clearance as a measure of parasite lifespan and virulence as another measure that delimits parasite survival within a host. However, even crude quantitative estimates of such tradeoffs remain beyond reach in all but the most controlled of experimental conditions. Here, we argue that the great recent advances in the molecular study of pathogenesis provide a way forward. In light of those mechanistic studies, we analyse the relative sensitivity of tradeoffs between components of parasite fitness. We argue that pathogenic mechanisms that manipulate host immunity or escape from host defences have particularly high sensitivity to parasite fitness and thus dominate as causes of parasite virulence. The high sensitivity of immunomodulation and immune escape arise because those mechanisms affect parasite survival within the host, the most sensitive of fitness components. In our view, relating the sensitivity of pathogenic mechanisms to fitness components will provide a way to build a much richer and more general theory of parasite virulence.

Genetic variation of polygenic characters and the evolution of genetic degeneracy

The classical model of mutation-selection balance for quantitative characters sums the effects of individual sites to determine overall character value. I develop an alternative version of this classical model in which character value depends on the averaging of the effects of the individual sites. In this new averaging model, the equilibrium patterns of variance in allelic effects and character values change with the number of sites that affect a character in a different way from the classical model of summing effects. Besides changing the patterns of variance, the averaging model favours the addition of loci to the control of character values, perhaps explaining in part the recent observation of widespread genetic degeneracy.

Programmed cell death and hybrid incompatibility

We propose a new theory to explain developmental aberrations in plant hybrids. In our theory, hybrid incompatibilities arise from imbalances in the mechanisms that cause male sterility in hermaphroditic plants. Mitochondria often cause male sterility by killing the tapetal tissue that nurtures pollen mother cells. Recent evidence suggests that mitochondria destroy the tapetum by triggering standard pathways of programmed cell death. Some nuclear genotypes repress mitochondrial male sterility and restore pollen fertility. Normal regulation of tapetal development therefore arises from a delicate balance between the disruptive effects of mitochondria and the defensive countermeasures of the nuclear genes. In hybrids, incompatibilities between male-sterile mitochondria and nuclear restorers may frequently upset the regulatory control of programmed cell death, causing tapetal abnormalities and male sterility. We propose that hybrid misregulation of programmed cell death may also spill over into other tissues, explaining various developmental aberrations observed in hybrids.

Multiplicity of infection and the evolution of hybrid incompatibility in segmented viruses

Some viral genomes are divided into segments. When multiple viruses infect a single cell, progeny form by reassorted mixtures of genomic segments. Hybrid incompatibilities arise when a progeny virus has incompatible segments from different parental viruses. Hybrid incompatibility has been observed in influenza and in the multiparticle plant virus Dianthovirus. Hybrid incompatibility provides an opportunity to study rates of viral evolution, divergence and speciation, and the extent of epistatic interactions among components of the viral genome. This paper presents mathematical and computer simulation models to study hybrid incompatibility between diverging strains. The models identify multiplicity of infection as a key factor. When many viral particles infect each host cell, the effective ploidy of the genetic system is high. High ploidy dilutes the contribution of each locus to the phenotype, weakening the selective intensity on each locus. Weaker selection on variant alleles allows the population to maintain greater genetic diversity and to be more easily perturbed by stochastic fluctuations. Greater diversity and stochastic fluctuations explore more widely the space of epistatic interactions, causing more frequent shifts among favoured combinations of alleles. Variable ploidy of viral genetics differs from standard Mendelian genetics.

Gene discovery and gene function assignment in filamentous fungi

Filamentous fungi are a large group of diverse and economically important microorganisms. Large-scale gene disruption strategies developed in budding yeast are not applicable to these organisms because of their larger genomes and lower rate of targeted integration (TI) during transformation. We developed transposon-arrayed gene knockouts (TAGKO) to discover genes and simultaneously create gene disruption cassettes for subsequent transformation and mutant analysis. Transposons carrying a bacterial and fungal drug resistance marker are used to mutagenize individual cosmids or entire libraries in vitro. Cosmids are annotated by DNA sequence analysis at the transposon insertion sites, and cosmid inserts are liberated to direct insertional mutagenesis events in the genome. Based on saturation analysis of a cosmid insert and insertions in a fungal cosmid library, we show that TAGKO can be used to rapidly identify and mutate genes. We further show that insertions can create alterations in gene expression, and we have used this approach to investigate an amino acid oxidation pathway in two important fungal phytopathogens.

Recent advances in large-scale transposon mutagenesis

Transposons were identified as mobile genetic elements over fifty years ago and subsequently became powerful tools for molecular-genetic studies. Recently, transposon-mutagenesis strategies have been developed to identify essential and pathogenicity-related genes in pathogenic microorganisms. Also, a number of in vitro transposition systems have been used to facilitate genome sequence analysis. Finally, transposon mutagenesis of yeast and complex eukaryotes has provided valuable functional genomic information to complement genome-sequencing projects.

The probability of severe disease in zoonotic and commensal infections

Cross-species transfers of pathogens (zoonoses) cause some of the most virulent diseases, including anthrax, hantavirus and Q fever. Zoonotic infections occur when a pathogen moves from its reservoir host species into a secondary host species. Similarly, commensal infections often have a primary reservoir location within their hosts' bodies from which they rarely cause disease symptoms, but commensals such as Neisseria meningitidis cause severe disease when they cross into a different body compartment from their normal location. Both zoonotic and commensal infections cause either mild symptoms or severe disease, but rarely intermediate symptoms. We develop a mathematical model for studying three factors that affect the probability of severe disease: the size of the inoculum, the route of inoculation and the frequency of naturally occurring infections that do not cause symptoms but do induce protective immunity (vaccinating inoculations). With a single route of infection, increasing pathogen density causes inoculations to develop more often into disease rather than asymptomatic vaccinations that provide protective immunity. With two routes of infection, it may happen that a lower density of a pathogen or of a particular antigenic variant leads to a relatively higher frequency of disease-inducing versus vaccinating inoculations. This reversal occurs when one route of infection tends to vaccinate against relatively common pathogens but less often vaccinates against relatively rare pathogens, whereas the other route of infection is susceptible to disease-inducing inoculation even at relatively low pathogen density.

Within-host spatial dynamics of viruses and defective interfering particles

Defective-interfering (DI) viruses arise spontaneously by deletion mutations. The shortened genomes of the DI particles cannot replicate unless they coinfect a cell with a wild-type virus. Upon coinfection, the DI genome replicates more quickly and outcompetes the wild type. The coinfected cell produces mostly DI viruses. At the population level, the abundances of DI and wild-type viruses fluctuate dramatically under some conditions. In other cases, the DI viruses appear to mediate persistent infections with relatively low levels of host cell death. This moderation of viral damage has led some to suggest DI particles as therapeutic agents. Previous mathematical models have shown that either fluctuation or persistence can occur for plausible parameter values. I develop new mathematical models for the population dynamics of DI and wild-type viruses. My work extends the theory by developing specific predictions that can be tested in the laboratory. These predictions, if borne out by experiment, will explain the key processes that control the diversity of observed outcomes. The most interesting prediction concerns the rate at which killed host cells are replaced. A low rate of replacement causes powerful epidemics followed by a crash in viral abundance. As the rate of replacement increases, the frequency of oscillations increases in DI and wild-type viral abundances, but the severity (amplitude) of the fluctuations declines. At higher replacement rates for host cells, nearly all cells become infected by DI particles and a low level of fluctuating, wild-type viremia persists.

Use of thallium(I) ethoxide in Suzuki cross coupling reactions

[reaction: see text]Thallium(I) ethoxide promotes Suzuki cross couplings for a range of vinyl- and arylboronic acids with vinyl and aryl halide partners in good to excellent yields. This reagent offers distinct advantages over thallium(I) hydroxide in terms of commercial availability, stability, and ease of use.

Specific and non-specific defense against parasitic attack

Specific defense protects against some parasite genotypes but not others, whereas non-specific defense is effective against all genotypes of a parasite. Some empirical studies observe hosts with variability only in non-specific defense, other studies find only specific defense. I analyse a model with combined specific and non-specific defense to determine the conditions that favor detectable variation in each form of defense. High variation in non-specific defense is often maintained when resistance increases in an accelerating way with investment, whereas low variation tends to occur when resistance increases at a decelerating rate with investment. Variation in specific defense rises as the parasite pays a higher cost to attack a broad host range (high cost of virulence), as the number of alternative specificities declines, and as the average level of non-specific defense increases. The last condition occurs because greater non-specific protection tends to stabilize the gene frequency dynamics of specific defense. Selection favors a negative association between costly components of specific and non-specific defense-hosts defended by one component are favored if they have reduced allocation to other costly components. A negative association confounds the measurement of costs of resistance. Individuals with specific defense may have reduced investment in costly non-specific defense. This leads to an apparent advantage of specifically defended hosts in the absence of parasites and a measured cost of resistance that is negative.

A model for the sequential dominance of antigenic variants in African trypanosome infections

Trypanosoma brucei infects various domestic and wild mammals in equatorial Africa. The parasite's genome contains several hundred alternative and highly diverged surface antigens, of which only a single one is expressed in any cell. Individual cells occasionally change expression of their surface antigen, allowing them to escape immune surveillance. These switches appear to occur in a partly random way, creating a diverse set of antigenic variants. In spite of this diversity, the parasitaemia develops as a series of outbreaks, each outbreak dominated by relatively few antigenic types. Host-specific immunity eventually clears the dominant antigenic types and a new outbreak follows from antigenic types that have apparently been present all along at low frequency. This pattern of sequential dominance by different antigenic types remains unexplained. I use a mathematical model of parasitaemia and host immunity to show that small variations in the rate at which each type switches to other types can explain the observations. My model shows that randomly chosen switch rates do not provide sufficiently ordered parasitaemias to match the observations. Instead, minor modifications of switch rates by natural selection are required to develop a sequence of ordered parasitaemias.

Population and quantitative genetics of regulatory networks

I evolved boolean regulatory networks in a computer simulation. I varied mutation, recombination, the size of the network, and the number of connections per node. I measured the performance of networks and the heritability and epistasis of genetic effects. Networks of intermediate connectivity performed best. The distinction between metabolic and quantitative genetic additivity explained some of the variation in performance. Metabolic additivity describes the interaction between changes in a single network, whereas quantitative genetic additivity measures the consistency of phenotypic effect caused by gene substitution in randomly chosen members of the population. I analysed metabolic additivity by the distribution of epistatic effects of pairs of mutations in individual networks. I measured quantitative genetic additivity by heritability. Highly connected networks had greater metabolic additivity for perturbations to individual networks, but had lower additivity when measured by the average effect of a gene substitution (heritability). The lower heritability of highly connected nets appeared to reduce the effectiveness of recombination in searching evolutionary space.

Inducible defence and the social evolution of herd immunity

Many organisms vary their level of investment in defensive characters. Protective traits may be induced upon exposure to predators or parasites. In a similar way, humans vaccinate in response to threatening epidemics. When most group members defend themselves, epidemics die out quickly because parasites cannot spread. A high level of group (herd) immunity is therefore beneficial to the group. There is, however, a well-known divergence between the optimum degree of induction for selfish individuals and the level of induction that maximizes group benefit. I develop two optimality models for the frequency of induction. The first model shows that higher relatedness favours more induction and a smaller difference between selfish and cooperative optima. The second model assumes variation in the vigour of individuals and therefore differences in the relative cost for induction. The model predicts that strong individuals induce more easily than weak individuals. Small differences in vigour cause a large divergence in the optimal levels of induction for strong and weak individuals. The concept of genetic relatedness in an evolutionary model is analogous to correlated interests and correlated strategies in an economic model of human behaviour. The evolutionary models presented here therefore provide a basis for further study of human vaccination.

Dynamics of Cytoplasmic Incompatability with Multiple Wolbachia Infections

Wolbachia infections occur in many arthropods. These matrilineally inherited bacteria cause cytoplasmic incompatibility, in which a cross produces no offspring when between an infected male and an uninfected female. Some populations harbour multiple Wolbachia strains. Females fail to produce offspring when crossed to a male with a strain that the female lacks. Prior theoretical work showed that a panmictic population cannot maintain polymorphism for different strains when each female carries only a single strain. A few authors suggested that doubly infected females can stabilize multistrain polymorphism, but conditions for invasion and location of stable equilibrium were not analysed in detail. For two strains, I describe the conditions under which a multiply infected class can spread. Spread of the doubly infected type stabilizes polymorphism of the singly infected classes. This analysis also suggests an interesting extension to higher multiplicity of infection. For an arbitrary number of strains, N, a panmictic population cannot maintain different classes with N-1 infections unless the class with N infections is also present. This pyramid of polymorphism may explain the puzzling diversity of incompatibility types observed in some Culex mosquitos. Multiple infection also has interesting consequences for the dynamics of spatial variation and reproductive isolation.Copyright 1998 Academic Press Limited

Multivariate analysis of correlated selection and kin selection, with an ESS maximization method

Kin selection coefficients are used in two distinct ways. First, these coefficients measure phenotypic correlations that affect the marginal costs and benefits of behaviors. For example, the phenotypic correlation in sex ratio produced by two females in an isolated patch influences the favoured sex ratio. Second, kin selection coefficients describe genotypic correlations that measure fidelity of transmission. For example, a female values daughters vs. nieces according to genotypic correlations. It is widely known that kin selection coefficients may be interpreted as phenotypic or genotypic correlations in different contexts. However, these different interpretations have never been fully separated, and their different role have not been clearly explained. I provide proofs of a generic analytical approach. The technique automatically separates phenotypic correlations among social partners from genotypic components of transmission. The result is a general method that can be derived from first principles and applied to multivariate problems in social evolution. I emphasize a simple, practical maximization method that can be used to calculate equilibrium conditions for complex social interactions.

Roles of intensity and duration of nocturnal exercise in causing phase delays of human circadian rhythms

To determine the roles of intensity and duration of nocturnal physical activity in causing rapid phase shifts of human circadian rhythms, eight healthy men were studied three times under constant conditions with no exercise, a 3-h bout of moderate-intensity exercise, or a 1-h bout of high-intensity exercise. Exercise stimulus was centered at 0100. Circadian phase was estimated from the onsets of the nocturnal elevation of plasma thyrotropin (TSH) and melatonin. Mean phase shifts of TSH onsets were -18 +/- 8 (baseline), -78 +/- 10 (low-intensity exercise, P < 0.01), and -95 +/- 19 min (high-intensity exercise, P < 0.01). Mean phase delays of melatonin onsets were -23 +/- 10 (baseline), -63 +/- 8 (low-intensity exercise, P < 0.04), and -55 +/- 15 min (high-intensity exercise, P < 0.12). Taken together with our previous findings, this study indicates that nocturnal physical activity may phase delay human circadian rhythms and demonstrates that phase-shifting effects may be determined with exercise durations and intensities compatible with the demands of a real-life setting.

The design of adaptive systems: optimal parameters for variation and selection in learning and development

Some aspects of learning and development are based on evolutionary change within the organism. In trial and error learning, variant ideas or behaviors are generated and selective filters (learning rules) choose among the population of variants. Development may, in some cases, proceed by selection within a population of variant cellular lineages. This paper analyses abstract properties of selective systems to understand the evolutionary dynamics that occur within organisms. The Price Equation and Fisher's fundamental theorem of natural selection, two of the most powerful concepts in evolutionary genetics, are applied in a general way to internal selective systems in learning and development. This analysis emphasizes generative mechanisms and selective filters as genetically controlled phenotypes of individual organisms. Generative mechanisms create the variation on which selection acts. Selective filters determine the extent to which selection within the organism optimizes organismal performance. The methods of Price and Fisher provide a general way in which to partition evolutionary change into improvements caused by selection and the tendency of high performance variants to deteriorate because of competition or environmental change. This balance between selective improvement, at a rate equal to the variance in fitness, and a matching deterioration in performance, provides general insight into the common properties of adaptive systems in genetics, learning and development. These ideas are applied to a model of honey bee foraging. This example clarifies the relation between genes and phenotypes controlled by internal selective systems.

Developmental selection and self-organization

Developmental selection is the differential survival and proliferation of developmental units, such as cellular lineages. This type of internal selection has been proposed as an explanation for diverse examples of self-organization, from the wiring of brains to the formation of pores on leaf surfaces. A general understanding of developmental selection has been slowed by failure to understand its relationship to familiar forms of genetical selection and evolution. I show the formal analogies between models of developmental selection and genetical selection. The general method I outline for the analysis of selective systems partitions self-organizing selective systems into generative rules that create variation and selective filters that move the population toward a target design. The method also emphasizes aggregate statistical measures of evolving systems, such as the covariance between particular traits and fitness. The identification of useful aggregate measures is a crucial step in the analysis of selective systems. I apply these concepts to a model of self-organization in ant colonies.

How to make a kin selection model

Kin selection arguments, based on Hamilton's (1964) concept of inclusive fitness, provide a powerful heuristic and can therefore give us valuable insights into the different pathways through which natural selection acts. But their formulation can be quite tricky, requiring as they do, a close accounting of all the fitness effects of a particular item of behaviour. Here we propose a "direct fitness" formulation of inclusive fitness which often has a more straightforward derivation. Our method finds ESS trait values by the standard optimization techniques of simple differentiation plus two additional steps. First, slopes of group phenotype on individual genotype arise naturally during differentiation, and these slopes are replaced by coefficients of relatedness. Second, when behaviours influence different classes such as age, sex of recipient, or other life history components of fitness, the fitness effects on each component are weighted by reproductive value. We illustrate this technique first in a homogeneous population, with examples of group competition and partial dispersal behaviour, and then in a class-structured population, with examples of sex allocation and altruism between age classes.

Host-symbiont conflict over the mixing of symbiotic lineages

Host and symbiont often conflict over patterns of symbiont transmission. Symbionts favour dispersal out of the host to avoid competition with close relatives. Migration leads to competition among different symbiotic lineages, with potentially virulent side-effects on the host. The hosts are favoured to restrict symbiont migration and reduce the virulent tendencies of the symbionts. Reduced mixing of symbionts would, in many cases, lower symbiont virulence and increase the mean fitness of the host population. But a host modifier allele that reduced symbiont mixing increases only when directly associated with reduced virulence. The association between modifiers and reduced virulence depends on the particular details of symbiont biology. The importance of this direct association between modifier and virulence was first noted by Hoekstra (1987) when studying the evolution of uniparental inheritance of cytoplasmic elements. I apply Hoekstra's insight to a wide range of host-symbiont life histories, expanding the scope beyond cytoplasmic inheritance and genomic conflict. My comparison of differing symbiont life histories leads to a careful analysis of the conditions under which hosts are favoured to control mixing of their symbionts.

Models of parasite virulence

Several evolutionary processes influence virulence, the amount of damage a parasite causes to its host. For example, parasites are favored to exploit their hosts prudently to prolong infection and avoid killing the host. Parasites also need to use some host resources to reproduce and transmit infections to new hosts. Thus parasites face a tradeoff between prudent exploitation and rapid reproduction-a life history tradeoff between longevity and fecundity. Other tradeoffs among components of parasite fitness also influence virulence. For example, competition among parasite genotypes favors rapid growth to achieve greater relative success within the host. Rapid growth may, however, lower the total productivity of the local group by overexploiting the host, which is a potentially renewable food supply. This is a problem of kin selection and group selection. I summarize models of parasite virulence with the theoretical tools of life history analysis, kin selection, and epidemiology. I then apply the theory to recent empirical studies and models of virulence. These applications, to nematodes, to the extreme virulence of hospital epidemics, and to bacterial meningitis, show the power of simple life history theory to highlight interesting questions and to provide a rich array of hypotheses. These examples also show the kinds of conceptual mistakes that commonly arise when only a few components of parasite fitness are analysed in isolation. The last part of the article connects standard models of parasite virulence to diverse topics, such as the virulence of bacterial plasmids, the evolution of genomes, and the processes that influenced conflict and cooperation among the earliest replicators near the origin of life.

Models of parasite virulence

Several evolutionary processes influence virulence, the amount of damage a parasite causes to its host. For example, parasites are favored to exploit their hosts prudently to prolong infection and avoid killing the host. Parasites also need to use some host resources to reproduce and transmit infections to new hosts. Thus parasites face a tradeoff between prudent exploitation and rapid reproduction-a life history tradeoff between longevity and fecundity. Other tradeoffs among components of parasite fitness also influence virulence. For example, competition among parasite genotypes favors rapid growth to achieve greater relative success within the host. Rapid growth may, however, lower the total productivity of the local group by overexploiting the host, which is a potentially renewable food supply. This is a problem of kin selection and group selection. I summarize models of parasite virulence with the theoretical tools of life history analysis, kin selection, and epidemiology. I then apply the theory to recent empirical studies and models of virulence. These applications, to nematodes, to the extreme virulence of hospital epidemics, and to bacterial meningitis, show the power of simple life history theory to highlight interesting questions and to provide a rich array of hypotheses. These examples also show the kinds of conceptual mistakes that commonly arise when only a few components of parasite fitness are analysed in isolation. The last part of the article connects standard models of parasite virulence to diverse topics, such as the virulence of bacterial plasmids, the evolution of genomes, and the processes that influenced conflict and cooperation among the earliest replicators near the origin of life.

Extending the multimedia patient record across the wide area network

The Dept. of Veterans Affairs is developing and testing a wide area medical network with multimedia capabilities for coordination and consolidation of medical services across locations. The system is composed of multimedia information systems at individual medical centers connected by a high speed wide area network. The DHCP Imaging System, which has been in clinical use for six years, provides storage management and workstation acquisition and display of the multimedia data. Teleconsulting capability using a variety of mechanisms' is being prototyped and tested to meet medical staffing and consultation needs.

Effects of aging on glucose regulation during wakefulness and sleep

Glucose intolerance, reduced sleep efficiency, and disturbed circadian rhythmicity occur in aging. In normal young subjects, glucose regulation is modulated by sleep and circadian rhythmicity. To examine age-related alterations in the temporal pattern of glucose tolerance and insulin secretion, eight modestly overweight healthy older men, eight weight-matched young men, and six young lean men were studied during constant glucose infusion for 53 h. Levels of glucose, insulin, C-peptide, and growth hormone (GH) were measured every 20 min. Rates of insulin and GH secretion were calculated by deconvolution. In older volunteers, sleep ws shallow and more fragmented than in young subjects but was nevertheless associated with robust glucose elevations. However, postsleep increases of insulin secretion were markedly dampened. During wakefulness, the normal morning-to-evening increase in glucose was preserved in the elderly, but insulin secretion failed to increase proportionately. Thus decreased glucose tolerance in aging is associated with insulin resistance and also with a relative insensitivity of the beta-cell to the modulation of glucose regulation by sleep and circadian rhythmicity.

An analysis of the appropriate use of the Caledon ambulance service in the Overberg. A short report

The objective of this study was to determine the possible extent of the inappropriate use of the ambulances of the Caledon station of the Overberg Regional Services Council. The trip sheets of the ambulances for the period 1987-1990 were retrospectively analysed, and the appropriateness of calls prospectively determined over a 7-month period. The results showed that the vast majority of calls (68%) were of a non-emergency nature, and that only 34% of the trips warranted the use of a fully equipped emergency vehicle. Various cost-containment measures are suggested.

Mutual policing and repression of competition in the evolution of cooperative groups

Evolutionary theory has not explained how competition among lower level units is suppressed in the formation of higher-level evolutionary units. For example, the key problem of early evolution is small, individual replicators formed cooperative groups of sufficient complexity to allow accurate copying of the genetic material. The puzzle is why parasites did not subvert the formation of cells by obtaining benefits from the group without contributing to shared traits that enhance reproduction. These parasites would outcompete other replicators within the cell, disrupting reproductive fairness among subunits and destroying the functional coherence of the group. A similar problem arose at a later evolutionary stage with the orderly mendelian segregation of subunits (chromosomes) within cells, and reproductive fairness continued to be a problem in the evolution of insect and human societies. Here I present a simple model to show how reproductive fairness evolves among subunits to create functional coherence and higher-level units. Self-restraint, which evolves according to the kin-selection coefficient of relatedness, is not sufficient: mutual policing and enforcement of reproductive fairness are also required for the evolution of increasing social complexity.

The origin of synergistic symbiosis

A dominant theme in the history of life has been the evolutionary innovations of cooperative symbioses: the first genomes near the origin of life, integrated prokaryotic cells, the complex symbiotic communities that evolved into modern eukaryotic cells, lichens, mycorrhizae, and so on. In this paper, a model of cooperative symbiosis that shows a threshold condition for the evolution of cooperation is analyzed. The threshold is not easily passed, but cooperative evolution proceeds rapidly once a symbiosis overcomes the threshold. In the model presented here, each species has genetic variability for a symbiotic trait. The trait imposes a reproductive cost on its bearer but enhances the reproduction of its partner species. For example, in the origin of genetic systems, the trait may cause biochemical synergism for the rate of replication of primitive RNA strands as in Eigen and Schuster's hypercycle model. Models of growth are contrasted with synergism, which are most appropriate for the evolution of genetic systems and for mutualisms such as lichens, with the strategic and psychological applications of the Prisoner's Dilemma model.

George Price's contributions to evolutionary genetics

George Price studied evolutionary genetics for approximately seven years between 1967 and 1974. During that brief period Price made three lasting contributions to evolutionary theory; these were: (i) the Price Equation, a profound insight into the nature of selection and the basis for the modern theories of kin and group selection; (ii) the theory of games and animal behavior, based on the concept of the evolutionarily stable strategy; and (iii) the modern interpretation of Fisher's fundamental theorem of natural selection, Fisher's theorem being perhaps the most cited and least understood idea in the history of evolutionary genetics. This paper summarizes Price's contributions and briefly outlines why, toward the end of his painful intellectual journey, he chose to focus his deep humanistic feelings and sharp, analytical mind on abstract problems in evolutionary theory.

Recognition and polymorphism in host-parasite genetics

Genetic specificity occurs in many host-parasite systems. Each host can recognize and resist only a subset of parasites; each parasite can grow only on particular hosts. Biochemical recognition systems determine which matching host and parasite genotypes result in resistance or disease. Recognition systems are often associated with widespread genetic polymorphism in the host and parasite populations. I describe four systems with matching host-parasite polymorphisms: plant-pathogen interactions, nuclear-cytoplasmic conflict in plants, restriction enzymes in bacterial defence against viruses, and bacterial plasmids that compete by toxin production and toxin immunity. These systems highlight several inductive problems. For example, the observed patterns of resistance and susceptibility between samples of hosts and parasites are often used to study polymorphism. The detectable polymorphism by this method may be a poor guide to the actual polymorphism and to the underlying biochemistry of host-parasite recognition. The problem of using detectable polymorphism to infer the true nature of recognition and polymorphism is exacerbated by non-equilibrium fluctuations in allele frequencies that commonly occur in host-parasite systems. Another problem is that different matching systems may lead either to low frequencies of host resistance and common parasites, or to common resistance and rare parasites. Thus low levels of host resistance or rare parasites do not imply that parasitism is an unimportant evolutionary force on host diversity. Knowledge of biochemical recognition systems and dynamical analysis of models provide a framework for analysing the widespread polymorphisms in host-parasite genetics.

Kin selection and virulence in the evolution of protocells and parasites

The evolution of parasite virulence and the origin of cooperative genomes in primitive cells are both problems that balance cooperative and competitive interactions among symbionts. I analyse the trade-off among three correlated traits: competitiveness against other genotypes for resources within hosts (protocells), damage to the host (virulence), and rate of horizontal transmission from one host to another. All three life-history components are strongly influenced by kin selection. For example, when genetic relatedness within hosts is high, each genotype is competing for resources with closely related genotypes. This competition among relatives favours increased horizontal transmission to colonize new hosts and compete against non-relatives. My analysis shows that many aspects of parasite and protocell evolution must be studied with the theoretical tools of social evolution. I discuss extensions that are required for a general theory of symbiosis.

Genetics of mutualism: the evolution of altruism between species

Conditions are analyzed under which natural selection favors an individual to help another species at a cost to its own reproduction. Traditional models for the evolution of altruism between species focus on the genetic relatedness between the original donor and the recipients of return benefits from the mutualistic partner species. A more general model is analyzed here that focuses on the synergistic effects between partner species caused by genetic variability. The model shows that the spread of altruism is enhanced by spatial correlations between species in the genetic tendency to give aid to partners. These spatial correlations between species are similar to the kin selection coefficients of relatedness that determine the course of social evolution within species. The model also shows that natural selection and ecological dynamics can create genetic correlations between neighbors of different species, even when the initial spatial distributions of the species are uncorrelated. Genetic correlations between species may play an important role in the origin and maintenance of altruism between species.