Self-organization at the origin of life

The concept of an (M,R) system with organizational invariance allows one to understand how a system may be able to maintain itself indefinitely if it is coupled to an external source of energy and materials. However, although this constitutes an important step towards understanding the difference between a living and a non-living system, it is not clear that an (M,R) system with organizational invariance is sufficient to define a living system. To take a further step towards defining what it means to be alive it is necessary to add to a simple (M,R) system some property that represents its identity, and which can be maintained and modified in subsequent generations.     

Modeling species-specific diacylglycerol dynamics in the RAW 264.7 macrophage

A mathematical model of the G protein signaling pathway in RAW 264.7 macrophages downstream of P2Y₆ receptors activated by the ubiquitous signaling nucleotide uridine 5’-diphosphate is developed. The model, which is based on time-course measurements of inositol trisphosphate, cytosolic calcium, and diacylglycerol, focuses particularly on differential dynamics of multiple chemical species of diacylglycerol. When using the canonical pathway representation, the model predicted that key interactions were missing from the current network structure. Indeed, the model suggested that accurate depiction of experimental observations required an additional branch to the signaling pathway. An intracellular pool of diacylglycerol is immediately phosphorylated upon stimulation of an extracellular receptor for uridine 5’-diphosphate and subsequently used to aid replenishment of phosphatidylinositol. As a result of sensitivity analysis of the model parameters, key predictions can be made regarding which of these parameters are the most sensitive to perturbations and are therefore most responsible for output uncertainty.     

The role of low avidity T cells in the protection against type 1 diabetes: a modeling investigation

Cytotoxic T lymphocytes (CTLs) play a dominant role in the pathogenesis of autoimmune diabetes, commonly denoted Type 1 Diabetes (T1D). These CTLs (notably CD8⁺ T cells) recognize and kill insulin-secreting pancreatic β cells, reducing their number by ∼90%. The resulting reduction of insulin secretion causes the defective regulation of glucose metabolism, leading to the characteristic symptoms of diabetes. Recognition of β cells as targets by CTLs depends on the interactions between MHC-peptide complexes on the surface of β cells and receptors (TCRs) on T cells. Those CTLs with high affinity TCRs (also called high avidity T cells) cause most of the harm, while those with low affinity TCRs (also called low avidity T cells) play a more mysterious role. Recent experimental evidence suggests that low avidity T cells accumulate as memory T cells during the disease and may be protective in NOD mice (a strain prone to developing T1D), delaying disease progression. It has been hypothesized that such low avidity T cells afford disease protection either by crowding the islets of Langerhans, where β cells reside, or by killing antigen presenting cells (APCs).In this paper, we explore the hypothesized mechanisms for this protective effect in the context of a series of models for (1) the interactions of low and high avidity T cells, (2) the effect of APCs and (3) the feedback from β cell killing to autoantigen-induced T cell proliferation. We analyze properties of these models, noting consistency of predictions with observed behaviour. We then use the models to examine the influence of various treatment strategies on the progression of the disease. The model reveals that progressive accumulation of memory low avidity autoreactive T cells during disease progression makes treatments aimed at expanding these protective T cell types more effective close to, or at the onset of clinical disease. It also provides evidence for the hypothesis that low avidity T cells kill APCs (rather than the alternate hypothesis that they crowd the islets).     

Perturbation avalanches and criticality in gene regulatory networks

Boolean networks are simplified models of gene regulatory networks. We derive an approximation of the size distribution of perturbation avalanches in Boolean networks based on known results in the theory of branching processes. We show numerically that the approximation works well for different kinds of Boolean networks. It has been suggested that gene regulatory networks may be dynamically critical. To study this, as an application of the presented theory we present a novel method for estimating an order parameter from microarray data. According to the available data and our method, we find that gene regulatory networks appear to be stable and reside near the phase transition between order and chaos.     

Topology is the Principal Determinant in the Folding of a Complex All-alpha Greek Key Death Domain from Human FADD

In order to elucidate the relative importance of secondary structure and topology in determining folding mechanism, we have carried out a phi-value analysis of the death domain (DD) from human FADD. FADD DD is a 100 amino acid domain consisting of six anti-parallel alpha helices arranged in a Greek key structure. We asked how does the folding of this domain compare with that of (a) other all-alpha-helical proteins and (b) other Greek key proteins? Is the folding pathway determined mainly by secondary structure or is topology the principal determinant? Our Φ-value analysis reveals a striking resemblance to the all-beta Greek key immunoglobulin-like domains. Both fold via diffuse transition states and, importantly, long-range interactions between the four central elements of secondary structure are established in the transition state. The elements of secondary structure that are less tightly associated with the central core are less well packed in both cases. Topology appears to be the dominant factor in determining the pathway of folding in all Greek key domains.     

Melanoblast proliferation dynamics during mouse embryonic development. Modeling and validation

In this paper, we are looking for mathematical modeling of mouse embryonic melanoblast proliferation dynamics, taking into account, the expression level of β‐catenin. This protein plays an important role into the whole signal pathway process. Different assumptions on some unobservable features lead to different candidate models. From real data measured, from biological experiments and from a priori biological knowledge, it was able to validate or invalidate some of the candidate models. Data assimilation and parameter identification allowed us to derive a mathematical model that is in very good agreement with biological data. As a result, the produced model can give tracks for biologists into their biological investigations and experimental evidence. Another interest is the use of this model for robust hidden parameter identification like double times or number of founder melanoblasts.     

Population differentiation and migration: coalescence times in a two-sex island model for autosomal and X-linked loci

Evolutionists have debated whether population-genetic parameters, such as effective population size and migration rate, differ between males and females. In humans, most analyses of this problem have focused on the Y chromosome and the mitochondrial genome, while the X chromosome has largely been omitted from the discussion. Past studies have compared F_ST values for the Y chromosome and mitochondrion under a model with migration rates that differ between the sexes but with equal male and female population sizes. In this study we investigate rates of coalescence for X-linked and autosomal lineages in an island model with different population sizes and migration rates for males and females, obtaining the mean time to coalescence for pairs of lineages from the same deme and for pairs of lineages from different demes. We apply our results to microsatellite data from the Human Genome Diversity Panel, and we examine the male and female migration rates implied by observed F_ST values.     

Genetic diversity of microsatellite loci in hierarchically structured populations

Microsatellite loci are widely used for investigating patterns of genetic variation within and among populations. Those patterns are in turn determined by population sizes, migration rates, and mutation rates. We provide exact expressions for the first two moments of the allele frequency distribution in a stochastic model appropriate for studying microsatellite evolution with migration, mutation, and drift under the assumption that the range of allele sizes is bounded. Using these results, we study the behavior of several measures related to Wright’s F_ST, including Slatkin’s R_ST. Our analytical approximations for F_ST and R_ST show that familiar relationships between N_em and F_ST or R_ST hold when the migration and mutation rates are small. Using the exact expressions for F_ST and R_ST, our numerical results show that, when the migration and mutation rates are large, these relationships no longer hold. Our numerical results also show that the diversity measures most closely related to F_ST depend on mutation rates, mutational models (stepwise versus two-phase), migration rates, and population sizes. Surprisingly, R_ST is relatively insensitive to the mutation rates and mutational models. The differing behaviors of R_ST and F_ST suggest that properties of the among-population distribution of allele frequencies may allow the roles of mutation and migration in producing patterns of diversity to be distinguished, a topic of continuing investigation.     

The shared reward dilemma

One of the most direct human mechanisms of promoting cooperation is rewarding it. We study the effect of sharing a reward among cooperators in the most stringent form of social dilemma, namely the prisoner's dilemma (PD). Specifically, for a group of players that collect payoffs by playing a pairwise PD game with their partners, we consider an external entity that distributes a fixed reward equally among all cooperators. Thus, individuals confront a new dilemma: on the one hand, they may be inclined to choose the shared reward despite the possibility of being exploited by defectors; on the other hand, if too many players do that, cooperators will obtain a poor reward and defectors will outperform them. By appropriately tuning the amount to be shared a vast variety of scenarios arises, including the traditional ones in the study of cooperation as well as more complex situations where unexpected behavior can occur. We provide a complete classification of the equilibria of the n-player game as well as of its evolutionary dynamics.     

Transmission dynamics of Toxoplasma gondii along an urban-rural gradient

Recently, several authors have proposed that the availability of intermediate hosts (IHs) for definitive hosts (DHs) may contribute to determining the dynamics and evolutionary ecology of parasites with facultative complex life cycles. The protozoa Toxoplasma gondii may be transmitted to DHs either via predation of infected IHs through a complex life cycle (CLC) or directly from a contaminated environment through a simple life cycle (SLC). This parasite is also present in contrasting host density environments. We tested the hypothesis that the relative contributions of the CLC and SLC along an urban-rural gradient depend on the IH supply. We built and analysed a deterministic model of the T. gondii transmission cycle. The SLC relative contribution is important only in urban-type environments, i.e., with low predation rate on IHs. In contrast, the parasite is predominantly transmitted through a CLC in suburban and rural environments. The association of the two cycles enables the parasite to spread in situations of low IH availability and low DH population size for which each cycle alone is insufficient.     

Generalized population models and the nature of genetic drift

The Wright–Fisher model of allele dynamics forms the basis for most theoretical and applied research in population genetics. Our understanding of genetic drift, and its role in suppressing the deterministic forces of Darwinian selection has relied on the specific form of sampling inherent to the Wright–Fisher model and its diffusion limit. Here we introduce and analyze a broad class of forward-time population models that share the same mean and variance as the Wright–Fisher model, but may otherwise differ. The proposed class unifies and further generalizes a number of population-genetic processes of recent interest, including the Λ and Cannings processes. Even though these models all have the same variance effective population size, they encode a rich diversity of alternative forms of genetic drift, with significant consequences for allele dynamics. We characterize in detail the behavior of standard population-genetic quantities across this family of generalized models. Some quantities, such as heterozygosity, remain unchanged; but others, such as neutral absorption times and fixation probabilities under selection, deviate by orders of magnitude from the Wright–Fisher model. We show that generalized population models can produce startling phenomena that differ qualitatively from classical behavior — such as assured fixation of a new mutant despite the presence of genetic drift. We derive the forward-time continuum limits of the generalized processes, analogous to Kimura’s diffusion limit of the Wright–Fisher process, and we discuss their relationships to the Kingman and non-Kingman coalescents. Finally, we demonstrate that some non-diffusive, generalized models are more likely, in certain respects, than the Wright–Fisher model itself, given empirical data from Drosophila populations.     

The evolution of n-player cooperation-threshold games and ESS bifurcations

An evolutionary game of individuals cooperating to obtain a collective benefit is here modelled as an n-player Prisoner's Dilemma game. With reference to biological situations, such as group foraging, we introduce a threshold condition in the number of cooperators required to obtain the collective benefit. In the simplest version, a three-player game, complex behaviour appears as the replicator dynamics exhibits a catastrophic event separating a parameter region allowing for coexistence of cooperators and defectors and a region of pure defection. Cooperation emerges through an ESS bifurcation, and cooperators only thrive beyond a critical point in cost-benefit space. Moreover, a repelling fixed point of the dynamics acts as a barrier to the introduction of cooperation in defecting populations. The results illustrate the qualitative difference between two-player games and multiple player games and thus the limitations to the generality of conclusions from two-player games. We present a procedure to find the evolutionarily stable strategies in any n-player game with cost and benefit depending on the number of cooperators. This was previously done by Motro [1991. Co-operation and defection: playing the field and the ESS. J. Theor. Biol. 151, 145-154] in the special cases of convex and concave benefit functions and constant cost.     

Molecular characterization of β1,4-galactosyltransferase 7 genetic mutations linked to the progeroid form of Ehlers-Danlos syndrome (EDS)

β1,4-Galactosyltransferase 7 (β4GalT7) is a key enzyme initiating glycosaminoglycan (GAG) synthesis. Based on in vitro and ex vivo kinetics studies and structure-based modelling, we molecularly characterized β4GalT7 mutants linked to the progeroid form of Ehlers-Danlos syndrome (EDS), a severe connective tissue disorder. Our results revealed that loss of activity upon L206P substitution due to altered protein folding is the primary cause for the GAG synthesis defect in patients carrying the compound A186D and L206P mutations. We showed that R270C substitution strongly reduced β4GalT7 affinity towards xyloside acceptor, thus affecting GAG chains formation. This study establishes the molecular basis for β4GalT7 defects associated with altered GAG synthesis in EDS.     

Computation of threshold conditions for epidemiological models and global stability of the disease-free equilibrium (DFE)

One goal of this paper is to give an algorithm for computing a threshold condition for epidemiological systems arising from compartmental deterministic modeling. We calculate a threshold condition T(0) of the parameters of the system such that if T(0)<1 the disease-free equilibrium (DFE) is locally asymptotically stable (LAS), and if T(0)>1, the DFE is unstable. The second objective, by adding some reasonable assumptions, is to give, depending on the model, necessary and sufficient conditions for global asymptotic stability (GAS) of the DFE. In many cases, we can prove that a necessary and sufficient condition for the global asymptotic stability of the DFE is R(0)< or =1, where R(0) is the basic reproduction number [O. Diekmann, J.A. Heesterbeek, Mathematical Epidemiology of Infectious Diseases: Model Building, Analysis and Interpretation, Wiley, New York, 2000]. To illustrate our results, we apply our techniques to examples taken from the literature. In these examples we improve the results already obtained for the GAS of the DFE. We show that our algorithm is relevant for high dimensional epidemiological models.     

Pressure equilibrium and jump study on unfolding of 23-kDa protein from spinach photosystem II

Pressure-induced unfolding of 23-kDa protein from spinach photosystem II has been systematically investigated at various experimental conditions. Thermodynamic equilibrium studies indicate that the protein is very sensitive to pressure. At 20 degrees C and pH 5.5, 23-kDa protein shows a reversible two-state unfolding transition under pressure with a midpoint near 160 MPa, which is much lower than most natural proteins studied to date. The free energy (DeltaG(u)) and volume change (DeltaV(u)) for the unfolding are 5.9 kcal/mol and -160 ml/mol, respectively. It was found that NaCl and sucrose significantly stabilize the protein from unfolding and the stabilization is associated not only with an increase in DeltaG(u) but also with a decrease in DeltaV(u). The pressure-jump studies of 23-kDa protein reveal a negative activation volume for unfolding (-66.2 ml/mol) and a positive activation volume for refolding (84.1 ml/mol), indicating that, in terms of system volume, the protein transition state lies between the folded and unfolded states. Examination of the temperature effect on the unfolding kinetics indicates that the thermal expansibility of the transition state and the unfolded state of 23-kDa protein are closer to each other and they are larger than that of the native state. The diverse pressure-refolding pathways of 23-kDa protein in some conditions were revealed in pressure-jump kinetics.     

Compressible gas gills of diving insects: Measurements and models

Many diving insects collect a bubble of air from the surface to supply their oxygen requirements while submerged. It has been theorised that these air bubbles may also act as compressible gas gills, as the low oxygen partial pressure (PO₂) within the bubble caused by the insect's respiration creates a gradient capable of driving the diffusion of oxygen from the water into the bubble. Under these conditions nitrogen diffuses in the opposite direction, resulting in a situation where the volume of the bubble is continually shrinking while oxygen is obtained. This study measures changes in volume and PO₂ within the gas gills held by a tethered water bug, Agraptocorixa eurynome. Both gill volume and PO₂ drop rapidly at the beginning of a dive, but eventually the PO₂ reaches an apparently stable level while volume continually declines at a slower rate. Active ventilation of the gill is crucial to maintaining oxygen uptake. These measurements are used to calculate oxygen flux into the gas gill and the oxygen consumption rate of the bug. The effectiveness of a gas gill as a respiratory organ is also demonstrated by determining the critical PO₂ of the water bug and comparing this with measured gas gill PO₂ and calculated .     

A multilevel approach to cancer growth modeling

Cancer growth models may be divided into macroscopic models, which describe the tumor as a single entity, and microscopic ones, which consider the tumor as a complex system whose behavior emerges from the local dynamics of its basic components, the neoplastic cells. Mesoscopic models (e.g. as based on the Local Interaction Simulation Approach [Delsanto, P.P., Mignogna, R., Scalerandi, M., Schechter, R., 1998. In: Delsanto, P.P. Saenz, A.W. (Eds.), New Perspectives on Problems in Classical and Quantum Physics, vol. 2. Gordon & Breach, New Delhi, p. 5174]), which explicitly consider the behavior of cell clusters and their interactions, may be used instead of the microscopic ones, in order to study the properties of cancer biology that strongly depend on the interactions of small groups of cells at intermediate spatial and temporal scales. All these approaches have been developed independently, which limits their usefulness, since they all include relevant features and information that should be cross-correlated for a deeper understanding of the mechanisms involved. In this contribution we consider multicellular tumor spheroids as biological reference systems and propose an intermediate model to bridge the gap between a macroscopic formulation of tumor growth and a mesoscopic one. Thus we are able to establish, as an important result of our formalism, a direct correspondence between parameters characterizing processes occurring at different scales. In particular, we analyze their dependence on an important limiting factor to tumor growth, i.e. the extra-cellular matrix pressure. Since the macro and meso-models stem from totally different roots (energy conservation and clinical observations vs. cell groups dynamics), their consistency may be used to validate both approaches. It may also be interesting to note that the proposed formalism fits well into a recently proposed conjecture of growth laws universality.     

The xanthophyll cycle and antioxidative defense system are enhanced in the wheat hybrid subjected to high light stress

Although the wheat hybrids have often shown higher grain yields, the physiological basis of the higher yields remains unknown. Previous studies suggest that tolerance to photoinhibition in the hybrid may be one of the physiological bases (Yang et al., 2006, Plant Sci 171:389-97). The objective of this study was to further investigate the possible mechanism responsible for tolerance to photoinhibition in the hybrid. Photosystem II (PSII) photochemistry, the xanthophyll cycle, and antioxidative defense system were compared between the hybrid and its parents subjected to high light stress (1500 μmol m⁻² s⁻¹). The analyses of oxygen-evolving activity, chlorophyll fluorescence, and protein blotting demonstrated that the higher tolerance in the hybrid than in its parents was associated with its higher tolerance of PSII to photoinhibition. High light induced an increase in non-photochemical quenching, and this increase was greater in the hybrid than in its parents. There were no differences in the pool size of the xanthophyll cycle between the hybrid and its parents. The content of violaxanthin decreased significantly, whereas the content of zeaxanthin + antherxanthin increased considerably during high light treatments. However, the decrease in violaxanthin content and the increase in zeaxanthin + antherxanthin content were greater in the hybrid than in its parents. High light resulted in a significant accumulation of H₂O₂, O₂⁻ and catalytic Fe, and this accumulation was less in the hybrid than in its parents. High light induced a significant increase in the activities of superoxide dismutase, catalase, ascorbate peroxidase, glutathione reductase, dehydroascorbate reductase, and monodehydroascorbate reductase, and these increases were greater in the hybrid than its parents. These results suggest that the higher tolerance to photoinhibition in the hybrid may be associated with its higher capacity for antioxidative defense metabolism and the xanthophyll cycle.