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Biomedical subjects

Ricard V Solé

Publications and source records attributed to Ricard V Solé.

At least 19 recordsLinked to original sources

Neutral fitness landscapes in signalling networks.

Biological and technological systems process information by means of cascades of signals. Be they interacting genes, spiking neurons or electronic transistors, information travels across these systems, producing, for each set of external conditions, an appropriate response. In technology, circuits performing specific complex tasks are designed by humans. In biology, however, design has to be ruled out, confronting us with the question of how these systems could have arisen by accumulation of small changes. The key factor is the genotype-phenotype map. With the exception of RNA folding, not much is known about the exact nature of this mapping. Here, we show that structure of the genotype-phenotype map of simple feed-forward circuits is very close to the ones found in RNA; they have a large degree of neutrality, by which a circuit can be completely rewired keeping its input-output function intact, and there is a relatively small neighbourhood of a given circuit containing almost all the phenotypes.

Cell Physiological Phenomena↗

Protocell self-reproduction in a spatially extended metabolism-vesicle system.

Cellular life requires the presence of a set of biochemical mechanisms in order to maintain a predictable process of growth and division. Several attempts have been made towards the building of minimal protocells from a top-down approach, i.e. by using available biomolecules. This type of synthetic approach has so far been only partially successful, and appropriate models of the synthetic protocell cycle might be needed to guide future experiments. In this paper, we present a simple biochemically and physically feasible model of cell replication involving a discrete semi-permeable vesicle with an internal minimal metabolism involving two reactive centers. It is shown that such a system can effectively undergo a whole cell replication cycle. The model can be used as a basic framework to model whole protocell dynamics including more complex sets of reactions. The possible implementation of our design in future synthetic protocells is outlined.

Animals↗

Bifurcations and phase transitions in spatially extended two-member hypercycles.

Mounting theoretical and experimental evidence indicates that the success of molecular replicators is strongly tied to the local nature of their interactions. Local dispersal in a given spatial domain, particularly on surfaces, might strongly enhance the growth and selection of fit molecules and their resistance to parasites. In this work the spatial dynamics of a simple hypercycle model consisting of two molecular species is analysed. In order to characterize it, both mean field models and stochastic, spatially explicit approaches are considered. The mean field approach predicts the presence of a saddle-node bifurcation separating a phase involving stable hypercycles from extinction, consistently with spatially explicit models, where an absorbing first-order phase transition is shown to exist and diffusion is explicitly introduced. The saddle-node bifurcation is shown to leave a ghost in the phase plane. A metapopulation-based model is also developed in order to account for the observed phases when both diffusion and reaction are considered. The role of information and diffusion as well as the relevance of these phases and the underlying spatial structures are discussed, and their potential implications for the evolution of early replicators are outlined.

Animals↗

Ecological networks and their fragility.

Darwin used the metaphor of a 'tangled bank' to describe the complex interactions between species. Those interactions are varied: they can be antagonistic ones involving predation, herbivory and parasitism, or mutualistic ones, such as those involving the pollination of flowers by insects. Moreover, the metaphor hints that the interactions may be complex to the point of being impossible to understand. All interactions can be visualized as ecological networks, in which species are linked together, either directly or indirectly through intermediate species. Ecological networks, although complex, have well defined patterns that both illuminate the ecological mechanisms underlying them and promise a better understanding of the relationship between complexity and ecological stability.

Animals↗

Are network motifs the spandrels of cellular complexity?

Cellular networks display modular organization at different levels, from small sets of genes exchanging signals in morphogenesis to large groups of proteins involved in cell death. At the smallest scale, minute groups of interacting proteins or genes, so-called 'network motifs', have been suggested to be the functional building blocks of network biology. In this context, the relative abundance of a network motif would reflect its adaptive value. However, although the overabundance of motifs is non-random, recent studies by Mazurie et al. and by Kuo et al. show that motif abundance does not reflect their true adaptive value. Just as some architectural components emerge as a byproduct of a prior decision, common motifs might be a side effect of inevitable rules of genome growth and change.

Cells↗

The fittest versus the flattest: experimental confirmation of the quasispecies effect with subviral pathogens.

The "survival of the fittest" is the paradigm of Darwinian evolution in which the best-adapted replicators are favored by natural selection. However, at high mutation rates, the fittest organisms are not necessarily the fastest replicators but rather are those that show the greatest robustness against deleterious mutational effects, even at the cost of a low replication rate. This scenario, dubbed the "survival of the flattest", has so far only been shown to operate in digital organisms. We show that "survival of the flattest" can also occur in biological entities by analyzing the outcome of competition between two viroid species coinfecting the same plant. Under optimal growth conditions, a viroid species characterized by fast population growth and genetic homogeneity outcompeted a viroid species with slow population growth and a high degree of variation. In contrast, the slow-growth species was able to outcompete the fast species when the mutation rate was increased. These experimental results were supported by an in silico model of competing viroid quasispecies.

Chrysanthemum↗

Phenotypic diversity and chaos in a minimal cell model.

Gánti's chemoton model (Gánti, T., 2002. On the early evolution of biological periodicity. Cell. Biol. Int. 26, 729) is considered as an iconic example of a minimal protocell including three key subsystems: membrane, metabolism and information. The three subsystems are connected through stoichiometrical coupling which ensures the existence of a replication cycle for the chemoton. Our detailed exploration of a version of this model indicates that it displays a wide range of complex dynamics, from regularity to chaos. Here, we report the presence of a very rich set of dynamical patterns potentially displayed by a protocell as described by this implementation of a chemoton-like model. The implications for early cellular evolution and synthesis of artificial cells are discussed.

Animals↗

Information catastrophe in RNA viruses through replication thresholds.

RNA viruses are known to replicate at very high mutation rates. These rates are actually known to be close to their so-called error threshold. This threshold is in fact a critical point beyond which genetic information is lost through a so-called error catastrophe. However, the transition from a stable quasispecies to genetic drift and loss of information can also occur by crossing replication thresholds, below some replication rates, the viral population is suddenly unable to survive. Available data from hepatitis C virus population analysis [Mas, A., Ulloa, E., Bruguera, M., Furcić, I., Garriga, D., Fábregas, S., Andreu, D., Saiz, J.C., Díez, J., 2004. Hepatitis C virus population analysis of a single-source nosocomial outbreak reveals an inverse correlation between viral load and quasispecies complexity. J. Gen. Virol. 85, 3619-3626] can be interpreted through this theoretical view, providing evidence for such a replication threshold. Here a simple model is used in order to provide evidence for such a phenomenon, consistent with available data.

Cross Infection↗

Network motifs in computational graphs: a case study in software architecture.

Complex networks in both nature and technology have been shown to display characteristic, small subgraphs (so-called motifs) which appear to be related to their underlying functionality. All these networks share a common trait: they manipulate information at different scales in order to perform some kind of computation. Here we analyze a large set of software class diagrams and show that several highly frequent network motifs appear to be a consequence of network heterogeneity and size, thus suggesting a somewhat less relevant role of functionality. However, by using a simple model of network growth by duplication and rewiring, it is shown the rules of graph evolution seem to be largely responsible for the observed motif distribution.

Journal Article↗

Topology, tinkering and evolution of the human transcription factor network.

Patterns of protein interactions are organized around complex heterogeneous networks. Their architecture has been suggested to be of relevance in understanding the interactome and its functional organization, which pervades cellular robustness. Transcription factors are particularly relevant in this context, given their central role in gene regulation. Here we present the first topological study of the human protein-protein interacting transcription factor network built using the TRANSFAC database. We show that the network exhibits scale-free and small-world properties with a hierarchical and modular structure, which is built around a small number of key proteins. Most of these proteins are associated with proliferative diseases and are typically not linked to each other, thus reducing the propagation of failures through compartmentalization. Network modularity is consistent with common structural and functional features and the features are generated by two distinct evolutionary strategies: amplification and shuffling of interacting domains through tinkering and acquisition of specific interacting regions. The function of the regulatory complexes may have played an active role in choosing one of them.

Algorithms↗

Patterns in syntactic dependency networks.

Many languages are spoken on Earth. Despite their diversity, many robust language universals are known to exist. All languages share syntax, i.e., the ability of combining words for forming sentences. The origin of such traits is an issue of open debate. By using recent developments from the statistical physics of complex networks, we show that different syntactic dependency networks (from Czech, German, and Romanian) share many nontrivial statistical patterns such as the small world phenomenon, scaling in the distribution of degrees, and disassortative mixing. Such previously unreported features of syntax organization are not a trivial consequence of the structure of sentences, but an emergent trait at the global scale.

Czech Republic↗

An error catastrophe in cancer?

A comparison between the evolution of cancer cell populations and RNA viruses reveals a number of remarkable similarities. Both display high levels of plasticity and adaptability as a consequence of high degrees of genetic variation. It has been suggested that, as it occurs with RNA viruses, there is a threshold in the levels of genetic instability affordable by cancer cells in order to be able to overcome selection barriers (Trends Genet. 15 (1999) M57). Here we explore this concept by means of a simple mathematical model. It is shown that an error threshold exists in this model, which investigates both competition between cancer cell populations and its impact on overall tumor growth dynamics. Once the threshold is reached, the highly unstable tumor cell populations, which were sustaining malignant growth, become unable to maintain their genetic information, which in turn triggers a slowed down overall tumor growth regime.

Animals↗

Analytic solution of Hubbell's model of local community dynamics.

Recent theoretical approaches to community structure and dynamics reveal that many large-scale features of community structure (such as species-rank distributions and species-area relations) can be explained by a so-called neutral model. Using this approach, species are taken to be equivalent and trophic relations are not taken into account explicitly. Here we provide a general analytic solution to the local community model of Hubbell's neutral theory of biodiversity by recasting it as an urn model, i.e. a Markovian description of states and their transitions. Both stationary and time-dependent distributions are analysed. The stationary distribution-also called the zero-sum multinomial-is given in closed form. An approximate form for the time-dependence is obtained by using an expansion of the master equation. The temporal evolution of the approximate distribution is shown to be a good representation for the true temporal evolution for a large range of parameter values.

Biodiversity↗

Evolving protein interaction networks through gene duplication.

The topology of the proteome map revealed by recent large-scale hybridization methods has shown that the distribution of protein-protein interactions is highly heterogeneous, with many proteins having few edges while a few of them are heavily connected. This particular topology is shared by other cellular networks, such as metabolic pathways, and it has been suggested to be responsible for the high mutational homeostasis displayed by the genome of some organisms. In this paper we explore a recent model of proteome evolution that has been shown to reproduce many of the features displayed by its real counterparts. The model is based on gene duplication plus re-wiring of the newly created genes. The statistical features displayed by the proteome of well-known organisms are reproduced and suggest that the overall topology of the protein maps naturally emerges from the two leading mechanisms considered by the model.

Animals↗

Coinfection and superinfection in RNA virus populations: a selection-mutation model.

In this paper, we present a general selection-mutation model of evolution on a one-dimensional continuous fitness space. The formulation of our model includes both the classical diffusion approach to mutation process as well as an alternative approach based on an integral operator with a mutation kernel. We show that both approaches produce fundamentally equivalent results. To illustrate the suitability of our model, we focus its analytical study into its application to recent experimental studies of in vitro viral evolution. More specifically, these experiments were designed to test previous theoretical predictions regarding the effects of multiple infection dynamics (i.e., coinfection and superinfection) on the virulence of evolving viral populations. The results of these experiments, however, did not match with previous theory. By contrast, the model we present here helps to understand the underlying viral dynamics on these experiments and makes new testable predictions about the role of parameters such the time between successive infections and the growth rates of resident and invading populations.

Evolution, Molecular↗

Adaptive walks in a gene network model of morphogenesis: insights into the Cambrian explosion.

The emergence of complex patterns of organization close to the Cambrian boundary is known to have happened over a (geologically) short period of time. It involved the rapid diversification of body plans and stands as one of the major transitions in evolution. How it took place is a controversial issue. Here we explore this problem by considering a simple model of pattern formation in multicellular organisms. By modeling gene network-based morphogenesis and its evolution through adaptive walks, we explore the question of how combinatorial explosions might have been actually involved in the Cambrian event. Here we show that a small amount of genetic complexity including both gene regulation and cell-cell signaling allows one to generate an extraordinary repertoire of stable spatial patterns of gene expression compatible with observed anteroposterior patterns in early development of metazoans. The consequences for the understanding of the tempo and mode of the Cambrian event are outlined.

Adaptation, Physiological↗

Metapopulation dynamics and spatial heterogeneity in cancer.

With the advent of drugs targeting specific molecular defects in cancerous cells [Gorre, M. E., et al. (2001) Science 293, 876-880], it is important to understand the degree of genetic heterogeneity present in tumor cell populations and the rules that govern microdiversity in human cancer. Here, we first show that populations with different genotypes in genes influencing cell growth and programmed cell death coexist in advanced malignant tumors of the colon, exhibiting microsatellite instability. Detailed, physical mapping of the diverse populations shows them to be arranged in small, intermingling areas, resulting in a variegated pattern of diversity. Using computational modeling of the experimental data, we find that the coexistence between similar competitors is enhanced, instead of deterred, by spatial dynamics [Hanski, I. (1999) Metapopulation Dynamics (Oxford Univ. Press, New York)]. The model suggests a simple and plausible scenario for the generation of spatial heterogeneity during tumor progression. The emergence and persistence of the patterns of diversity encountered in the tumors can be generated without a need to invoke differences in mutation rates, neutrality of interactions, or separated time scales. We posit that the rules that apply to spatial ecology and explain the maintenance of diversity are also at work in tumors and may underlie tumor microheterogeneity.

Adenocarcinoma↗