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Vincent A A Jansen

Publications and source records attributed to Vincent A A Jansen.

18 recordsLinked to original sources
PubMed2006

Altruism through beard chromodynamics.

The evolution of altruism, a behaviour that benefits others at one's own fitness expense, poses a darwinian paradox. The paradox is resolved if many interactions are with related individuals so that the benefits of altruism are reaped by copies of the altruistic gene in other individuals, a mechanism called kin selection. However, recognition of altruists could provide an alternative route towards the evolution of altruism. Arguably the simplest recognition system is a conspicuous, heritable tag, such as a green beard. Despite the fact that such genes have been reported, the 'green beard effect' has often been dismissed because it is unlikely that a single gene can code for altruism and a recognizable tag. Here we model the green beard effect and find that if recognition and altruism are always inherited together, the dynamics are highly unstable, leading to the loss of altruism. In contrast, if the effect is caused by loosely coupled separate genes, altruism is facilitated through beard chromodynamics in which many beard colours co-occur. This allows altruism to persist even in weakly structured populations and implies that the green beard effect, in the form of a fluid association of altruistic traits with a recognition tag, can be much more prevalent than hitherto assumed.

Altruism↗
PubMed2005

Phage variation: understanding the behaviour of an accidental pathogen.

Understanding why carriers of meningococci occasionally develop invasive disease is a major challenge. Individual strains of meningococci are extremely variable and undergo dynamic changes in DNA content and organization. This heterogeneity of meningococcal populations might enhance the fitness of this human-restricted bacterium. The recent discovery of a meningococcal bacteriophage and its associations to disease is an intriguing example of this variability and could contribute to a better understanding of microbial commensal and virulence behaviour.

Bacteriophages↗
PubMed2005

The evolution of stability in a competitive system.

The characteristics governing the dynamics of populations can evolve and this evolution can either be towards stability or chaos. Yet it is not obvious how or why such population characteristics can evolve through selection on individuals. In this paper we construct a mathematical model, inspired by experimental results, illustrating the dynamics of a population of competing Drosophila. We demonstrate how selection of life history characteristics and stability influence one another as a population interacts with its environment. We generalize this result and show that population stability can evolve as a consequence of selection on individuals.

Animals↗
PubMed2005

Statistics of infections with diversity in the pathogenicity.

The statistics of outbreaks in a model for the propagation of meningococcal disease is analyzed, taking into account the possibility that the population is fragmented into weakly connected patches. It is shown that, depending on the size of the sample studied, the ration between the variance and the average of infected cases can vary from unity (Poisson statistics) to epsilon(-1), where epsilon is the normalized infection rate.

Disease Outbreaks↗
PubMed2004

Contrasting B cell- and T cell-based protective vaccines.

A substantial research effort is devoted to the development of vaccines based on T cells. Such a vaccine would provide a means to protect against infection with HIV and stop the current pandemic. Here we investigate the possibility to develop a protective T cell-based vaccine. We do this by means of a mathematical model which describes the dynamics of a pathogen and the immune system in the early stages of infection. We compare an immune response that is near immediate--as is the case for a humoral response--with that of a response in which the effector cells have to be formed from precursor cells--as occurs in T cell responses. The latter applies to a T cell-based vaccine. A near immediate response is associated with a threshold number of effector cells above which an infection cannot take hold. For a T cell-based vaccine this threshold increases with the amount of antigen the immune system is exposed to. For small initial doses, as one would naturally expect to occur, this gives rise to impractically large thresholds. Thus, although a T cell vaccine might work against a high dose exposure, it might fail when exposed against to a low-dose exposure. This limits, we argue, the efficacy of T cell-based vaccines.

AIDS Vaccines↗
PubMed2004

Spatial models of virus-immune dynamics.

To date, the majority of theoretical models describing the dynamics of infectious diseases in vivo are based on the assumption of well-mixed virus and cell populations. Because many infections take place in solid tissues, spatially structured models represent an important step forward in understanding what happens when the assumption of well-mixed populations is relaxed. Here, we explore models of virus and virus-immune dynamics where dispersal of virus and immune effector cells was constrained to occur locally. The stability properties of our spatial virus-immune dynamics models remained robust under almost all biologically plausible dispersal schemes, regardless of their complexity. The various spatial dynamics were compared to the basic non-spatial dynamics and important differences were identified: When space was assumed to be homogeneous, the dynamics generated by non-spatial and spatially structured models differed substantially at the peak of the infection. Thus, non-spatial models may lead to systematic errors in the estimates of parameters underlying acute infection dynamics. When space was assumed to be heterogeneous, spatial coupling not only changed the equilibrium properties of the uncoupled populations but also equalized the dynamics and thereby reduced the likelihood of dynamic elimination of the infection. In line with experimental and clinical observations, long-lasting oscillation periods were virtually absent. When source-sink dynamics were considered, the long-term outcome of the infection depended critically on the degree of spatial coupling. The infection collapsed when emigration from source sites became too large. Finally, we discuss the implications of spatially structured models on medical treatment of infectious diseases, and note that a huge gap exists in data accurately describing infection dynamics in solid tissues.

Chronic Disease↗
PubMed2004

Life history trade-offs assemble ecological guilds.

Ecological theory predicts that competition for a limiting resource will lead to the exclusion of species unless the within-species effects outweigh the between-species effects. Understanding how multiple competitors might coexist on a single resource has focused on the prescriptive formalism of a necessary niche width and limiting similarity. Here, we show how continuously varying life histories and trade-offs in these characteristics can allow multiple competitors to coexist, and we reveal how limiting similarity emerges and is shaped by the ecological and evolutionary characteristics of competitors. In this way, we illustrate how the interplay of ecological and evolutionary processes acts to shape ecological communities in a unique way. This leads us to argue that evolutionary processes (life-history trait trade-offs) are fundamental to the understanding of the structure of ecological communities.

Animals↗
PubMed2004

Diversity in pathogenicity can cause outbreaks of meningococcal disease.

Neisseria meningitidis, the meningococcus, is a major cause of bacterial meningitis and septicemia worldwide. Infection in most cases leads to asymptomatic carriage and only rarely to disease. Meningococcal disease often occurs in outbreaks, which are both sporadic and highly unpredictable. The occurrence of disease outbreaks in a host population in which the etiological agent is widely carried is not well understood. A potential explanation lies in the fact that meningococci are diverse with respect to disease-causing potential. We formulated a stochastic mathematical model to investigate whether diversity of the bacterial population is related to outbreaks of meningococcal disease. In the model, strains that occasionally cause the disease appear repeatedly in a population dominated by a nonpathogenic strain. When the pathogenicity, i.e., the disease-causing potential, of the pathogenic lineage was low, the model shows distinct outbreaks, the size distribution of the outbreaks follows a power law, and the ratio of the variance to the mean number of cases is high. Analysis of notification data of meningococcal disease showed that the ratio of the variance to the mean was significantly higher for meningococcal diseases than for other bacterial invasive diseases. This result lends support to the hypothesis that outbreaks of meningococcal disease are caused by diversity in the pathogenicity of meningococcal strains.

Disease Outbreaks↗
PubMed2004

Prion kinetics.

Explore the source record for details and available documents.

Algorithms↗
PubMed2003

Meningitis, pathogenicity near criticality: the epidemiology of meningococcal disease as a model for accidental pathogens.

We formulate and analyse a model for infectious diseases transmitted by asymptomatic carriers finding, that if harmless and pathogenic strains of the infected agent compete, frequent outbreaks of the pathogenic strains can occur. A counterintuitively high number of clustered outbreaks at low pathogenicity in our model compares well with observations in diseases with severe and often fatal results for the host, as for example in meningitis. These clustered outbreaks can be described by the typical scaling behaviour around criticality. The epidemic model is a susceptible-infected-recovered system (SIR) for the harmless infective agent, acting as a background to a mutant strain Y which occasionally creates severely affected hosts X. The full system of SIRYX is described in the master equation framework, confirming limiting assumptions about a reduced YX-system with the SIR-system in stationarity. In this limiting case we can analytically show convergence to power law scaling typical for critical states, as well as the divergence of the variance of outbreaks near criticality. These large fluctuations of outbreaks of accidental pathogens as mutants of otherwise harmless commensal organisms is the challenging new feature of our model for future epidemiology of diseases like meningococcal disease.

Carrier State↗
PubMed2003

A dynamical perspective of CTL cross-priming and regulation: implications for cancer immunology.

Cytotoxic T lymphocytes (CTL) responses are required to fight many diseases such as viral infections and tumors. At the same time, they can cause disease when induced inappropriately. Which factors regulate CTL and decide whether they should remain silent or react is open to debate. The phenomenon called cross-priming has received attention in this respect. That is, CTL expansion occurs if antigen is recognized on the surface of professional antigen presenting cells (APCs). This is in contrast to direct presentation where antigen is seen on the surface of the target cells (e.g. infected cells or tumor cells). Here we introduce a mathematical model, which takes the phenomenon of cross-priming into account. We propose a new mechanism of regulation which is implicit in the dynamics of the CTL: According to the model, the ability of a CTL response to become established depends on the ratio of cross-presentation to direct presentation of the antigen. If this ratio is relatively high, CTL responses are likely to become established. If this ratio is relatively low, tolerance is the likely outcome. The behavior of the model includes a parameter region where the outcome depends on the initial conditions. We discuss our results with respect to the idea of self/non-self discrimination and the danger signal hypothesis. We apply the model to study the role of CTL in cancer initiation, cancer evolution/progression, and therapeutic vaccination against cancers.

Animals↗
PubMed2003

Common language or Tower of Babel? On the evolutionary dynamics of signals and their meanings.

We investigate how the evolution of communication strategies affects signal credibility when there is common interest as well as a conflict between communicating individuals. Taking alarm calls as an example, we show that if the temptation to cheat is low, a single signal is used in the population. If the temptation increases cheaters will erode the credibility of a signal, and an honest mutant using a different signal ('a private code') will be very successful until this, in turn, is cracked by cheaters. In such a system, signal use fluctuates in time and space and hence the meaning of a given signal is not constant. When the temptation to cheat is too large, no honest communication can maintain itself in a Tower of Babel of many signals. We discuss our analysis in the light of the Green Beard mechanism for the evolution of altruism.

Altruism↗
PubMed2003

Pharmacokinetic principles of bacteriophage therapy.

Use of bacteriophage to control bacterial infections, including antibiotic-resistant infections, shows increasing therapeutic promise. Effective bacteriophage therapy requires awareness of various novel kinetic phenomena not known in conventional drug treatments. Kinetic theory predicts that timing of treatment could be critical, with the strange possibility that inoculations given too early could be less effective or fail completely. Another paradoxical result is that adjuvant use of an antibiotic can sometimes diminish the efficacy of phage therapy. For a simple kinetic model, mathematical formulae predict the values of critical density thresholds and critical time points, given as functions of independently measurable biological parameters. Understanding such formulae is important for interpreting data and guiding experimental design. Tailoring pharmacokinetic models for specific systems needs to become standard practice in future studies.

Animals↗
PubMed2002

Herpes viruses hedge their bets.

Static latency is the hallmark of all herpes viruses. The varicella zoster virus, for instance, causes varicella (chickenpox), and after a latent phase of between 5 and 40 years, it can give rise to herpes zoster (shingles). This latency and the subsequent reactivation has intrigued and puzzled virologists. Although several factors have been suggested, it is unknown what triggers reactivation. However, latency can be explained with a simple evolutionary model. Here, we demonstrate that a simple, yet efficient, bet-hedging strategy might have evolved in a number of viruses, especially those belonging to the herpes virus family and most importantly in varicella zoster virus. We show that the evolution of latency can be explained by the population dynamics of infectious diseases in fluctuating host populations.

Chickenpox↗
PubMed2002

Red queen dynamics of protein translation.

We explore adaptive theories for the diversity of translational binding based on the genetic code viewed as a primitive mechanism of resistance. Modifying the set of codons bound by tRNA anticodon molecules or changing the specificity of binding, reduces the replication rate of translational parasites such as viruses. Increased translational efficiency of the parasite requires a high degree of specificity of host tRNAs for the parasite codons. This suggests that the genetic code might serve as the first line of defense against infection. We construct a red queen theory for translational diversity: a theory in which host-translational strategies- as defined by the degree of redundancy (a single anticodon binding many codons for a single amino acid) or degeneracy (many anticodons binding many codons for a single amino acid)-are constantly shifting through time to evade parasitism but where neither parasite nor host gain a systematic advantage.

Animals↗
PubMedDate not supplied

Spatiotemporal dynamics of epidemics: synchrony in metapopulation models.

Multi-patch models - also known as metapopulation models - provide a simple framework within which the role of spatial processes in disease transmission can be examined. An n-patch model which distinguishes between k different classes of individuals is considered. The linear stability of spatially homogeneous solutions of such models is studied using an extension of an analysis technique previously described for a population setting in which individuals migrate between patches according to a simple linear term. The technique considerably simplifies the analysis as it decouples the nk dimensional linearized system into n distinct k-dimensional systems. An important feature of the spatial epidemiological model is that the spatial coupling may involve non-linear terms. As an example of the use of this technique, the dynamical behavior in the vicinity of the endemic equilibrium of a symmetric SIR model is decomposed into spatial modes. For parameter values appropriate for childhood diseases, expressions for the eigenvalues corresponding to in-phase and out-of-phase modes are obtained, and it is shown that the dominant mode of the system is an in-phase mode. Furthermore, the out-of-phase modes are shown to decay much more rapidly than the in-phase mode for a broad range of coupling strengths.

Communicable Diseases↗