Minimal two-sphere model of the generation of fluid flow at low Reynolds numbers

Locomotion and generation of flow at low Reynolds number are subject to severe limitations due to the irrelevance of inertia: the "scallop theorem" requires that the system have at least two degrees of freedom, which move in non-reciprocal fashion, i.e. breaking time-reversal symmetry. We show here that a minimal model consisting of just two spheres driven by harmonic potentials is capable of generating flow. In this pump system the two degrees of freedom are the mean and relative positions of the two spheres. We have performed and compared analytical predictions, numerical simulation and experiments, showing that a time-reversible drive is sufficient to induce flow.Comment: 5 pages, 3 figures, revised version, corrected typo

Influence of homology and node-age on the growth of protein-protein interaction networks

Proteins participating in a protein-protein interaction network can be grouped into homology classes following their common ancestry. Proteins added to the network correspond to genes added to the classes, so that the dynamics of the two objects are intrinsically linked. Here, we first introduce a statistical model describing the joint growth of the network and the partitioning of nodes into classes, which is studied through a combined mean-field and simulation approach. We then employ this unified framework to address the specific issue of the age dependence of protein interactions, through the definition of three different node wiring/divergence schemes. Comparison with empirical data indicates that an age-dependent divergence move is necessary in order to reproduce the basic topological observables together with the age correlation between interacting nodes visible in empirical data. We also discuss the possibility of nontrivial joint partition/topology observables.Comment: 14 pages, 7 figures [accepted for publication in PRE

Universal Features in the Genome-level Evolution of Protein Domains

Protein domains are found on genomes with notable statistical distributions, which bear a high degree of similarity. Previous work has shown how these distributions can be accounted for by simple models, where the main ingredients are probabilities of duplication, innovation, and loss of domains. However, no one so far has addressed the issue that these distributions follow definite trends depending on protein-coding genome size only. We present a stochastic duplication/innovation model, falling in the class of so-called Chinese Restaurant Processes, able to explain this feature of the data. Using only two universal parameters, related to a minimal number of domains and to the relative weight of innovation to duplication, the model reproduces two important aspects: (a) the populations of domain classes (the sets, related to homology classes, containing realizations of the same domain in different proteins) follow common power-laws whose cutoff is dictated by genome size, and (b) the number of domain families is universal and markedly sublinear in genome size. An important ingredient of the model is that the innovation probability decreases with genome size. We propose the possibility to interpret this as a global constraint given by the cost of expanding an increasingly complex interactome. Finally, we introduce a variant of the model where the choice of a new domain relates to its occurrence in genomic data, and thus accounts for fold specificity. Both models have general quantitative agreement with data from hundreds of genomes, which indicates the coexistence of the well-known specificity of proteomes with robust self-organizing phenomena related to the basic evolutionary ``moves'' of duplication and innovation

Evolution of the Protein Universe. Time Scales and Selection

The availability of many genome sequences gives us abundant information, which is, however, very difficult to decode. As a consequence, in order to advance our understanding of biological processes at the whole-cell scale, it becomes very important to develop higher-level, synthetic descriptions of the contents of a genome. At the protein level, an effective scale of description is provided by protein domains. Domains are independent unit-shapes (or "folds") forming proteins. They are structurally stable and have thermodynamic origin. A domain determines a set of potential functions and interactions for the protein that carries it, for example DNA- or protein-binding capability or catalytic sites. Protein domains are found on genomes with notable statistical distributions, which bear a high degree of similarity. A stochastic growth model with two universal parameters, related to a minimal number of domains and to the relative time-scale of innovation to duplication reproduces two important features of these distributions: (i) the populations of domain classes (the sets, related to homology classes, containing realizations of the same domain in different proteins) follow common power-laws whose diversity is related to genome size measured by the total number of proteins or protein domains and (ii) the number of domain families is sublinear in genome size. In this evolutionary process, selective pressure can enter both as a global constraint on the innovation time-scale, and as a regulator of the population of specific domain classes, related to their modularity: some shapes are common to all genomes, some are contextual. These two features are sufficient to obtain general quantitative agreement with data from hundreds of genomes, and show that robust self-organizing phenomena encase specific selective pressures during evolution

Ordered structure of the transcription network inherited from the yeast whole-genome duplication

<p>Abstract</p> <p>Background</p> <p>Gene duplication, a major evolutionary path to genomic innovation, can occur at the scale of an entire genome. One such "whole-genome duplication" (WGD) event among the Ascomycota fungi gave rise to genes with distinct biological properties compared to small-scale duplications.</p> <p>Results</p> <p>We studied the evolution of transcriptional interactions of whole-genome duplicates, to understand how they are wired into the yeast regulatory system. Our work combines network analysis and modeling of the large-scale structure of the interactions stemming from the WGD.</p> <p>Conclusions</p> <p>The results uncover the WGD as a major source for the evolution of a complex interconnected block of transcriptional pathways. The inheritance of interactions among WGD duplicates follows elementary "duplication subgraphs", relating ancestral interactions with newly formed ones. Duplication subgraphs are correlated with their neighbours and give rise to higher order circuits with two elementary properties: newly formed transcriptional pathways remain connected (paths are not broken), and are preferentially cross-connected with ancestral ones. The result is a coherent and connected "WGD-network", where duplication subgraphs are arranged in an astonishingly ordered configuration.</p

DnaA and the timing of chromosome replication in Escherichia coli as a function of growth rate.

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.BACKGROUND: In Escherichia coli, overlapping rounds of DNA replication allow the bacteria to double in faster times than the time required to copy the genome. The precise timing of initiation of DNA replication is determined by a regulatory circuit that depends on the binding of a critical number of ATP-bound DnaA proteins at the origin of replication, resulting in the melting of the DNA and the assembly of the replication complex. The synthesis of DnaA in the cell is controlled by a growth-rate dependent, negatively autoregulated gene found near the origin of replication. Both the regulatory and initiation activity of DnaA depend on its nucleotide bound state and its availability. RESULTS: In order to investigate the contributions of the different regulatory processes to the timing of initiation of DNA replication at varying growth rates, we formulate a minimal quantitative model of the initiator circuit that includes the key ingredients known to regulate the activity of the DnaA protein. This model describes the average-cell oscillations in DnaA-ATP/DNA during the cell cycle, for varying growth rates. We evaluate the conditions under which this ratio attains the same threshold value at the time of initiation, independently of the growth rate. CONCLUSIONS: We find that a quantitative description of replication initiation by DnaA must rely on the dependency of the basic parameters on growth rate, in order to account for the timing of initiation of DNA replication at different cell doubling times. We isolate two main possible scenarios for this, depending on the roles of DnaA autoregulation and DnaA ATP-hydrolysis regulatory process. One possibility is that the basal rate of regulatory inactivation by ATP hydrolysis must vary with growth rate. Alternatively, some parameters defining promoter activity need to be a function of the growth rate. In either case, the basal rate of gene expression needs to increase with the growth rate, in accordance with the known characteristics of the dnaA promoter. Furthermore, both inactivation and autorepression reduce the amplitude of the cell-cycle oscillations of DnaA-ATP/DNA.Peer Reviewe

Statistical Mechanics of the Chinese Restaurant Process: lack of self-averaging, anomalous finite-size effects and condensation

The Pitman-Yor, or Chinese Restaurant Process, is a stochastic process that generates distributions following a power-law with exponents lower than two, as found in a numerous physical, biological, technological and social systems. We discuss its rich behavior with the tools and viewpoint of statistical mechanics. We show that this process invariably gives rise to a condensation, i.e. a distribution dominated by a finite number of classes. We also evaluate thoroughly the finite-size effects, finding that the lack of stationary state and self-averaging of the process creates realization-dependent cutoffs and behavior of the distributions with no equivalent in other statistical mechanical models.Comment: (5pages, 1 figure

VEGF overexpression induces post-ischaemic neuroprotection, but facilitates haemodynamic steal phenomena

Therapeutic angiogenesis with vascular endothelial growth factor (VEGF) is a clinically promising strategy in ischaemic disease. The pathophysiological consequences of enhanced vessel formation, however, are poorly understood. We established mice overexpressing human VEGF165 under a neuron-specific promoter, which exhibited an increased density of brain vessels under physiological conditions and enhanced angiogenesis after brain ischaemia. Following transient intraluminal middle cerebral artery (MCA) occlusions, VEGF overexpression significantly alleviated neurological deficits and infarct volume, and reduced disseminated neuronal injury and caspase-3 activity, confirming earlier observations that VEGF has neuroprotective properties. Brain swelling was not influenced in VEGF-overexpressing animals, while sodium fluorescein extravasation was moderately increased, suggesting that VEGF induces a mild blood-brain barrier leakage. To elucidate whether enhanced angiogenesis improves regional cerebral blood flow in the ischaemic brain, [14C]iodoantipyrine autoradiography was performed. Autoradiographies revealed that VEGF induces haemodynamic steal phenomena with reduced blood flow in ischaemic areas and increased flow values only outside the MCA territory. Our data demonstrate that VEGF protects neurons from ischaemic cell death by a direct action rather than by promoting angiogenesis, and suggest that strategies aiming at increasing vascular density in the whole brain, e.g. by VEGF overexpression, may worsen rather than improve cerebral haemodynamics after strok