Transition from hexagons to optical turbulence

4 pages, 3 figures.-- PACS nrs.: 42.65.Sf, 47.20.Ky, 47.54.+r, 89.75.Kd.We characterize the different dynamical regimes and bifurcations in the transition from a stationary hexagonal pattern to optical turbulence. In order to characterize the bifurcations we perform linear stability analysis of stationary hexagonal patterns and Floquet analysis of oscillating hexagons. The interplay between space and time leads to a series of bifurcations showing spatial-period multiplying and quasiperiodicity.The authors acknowledge financial support from the MCyT (Spain, Project Nos. PB97-0141-C02-02, BFM2000-1108, and BFM2001-0341-C02-02).Peer reviewe

A census of cell types and paracrine interactions in colorectal cancer

In colorectal cancer, oncogenic mutations transform a hierarchically organized and homeostatic epithelium into invasive cancer tissue. To define differences in cellular composition between the normal colon and colorectal cancer, and to map potential cellular interactions between tumor cells and their microenvironment, we profiled transcriptomes of >50,000 single cells from tumors and matched normal tissues of eight colorectal cancer patients. We find that tumor formation is accompanied by changes in epithelial, immune and stromal cell compartments in all patients. In the epithelium, we identify a continuum of five tumor-specific stem cell and progenitor-like populations, and persistent multilineage differentiation. We find multiple stromal and immune cell types to be consistently expanded in tumor compared to the normal colon, including cancer-associated fibroblasts, pericytes, monocytes, macrophages and a subset of T cells. We identify epithelial tumor cells and cancer-associated fibroblasts as relevant for assigning colorectal cancer consensus molecular subtypes. Our survey of growth factors in the tumor microenvironment identifies cell types responsible for increased paracrine EGFR, MET and TGF-β signaling in tumor tissue compared to the normal colon. We show that matched colorectal cancer organoids retain cell type heterogeneity, allowing to define a distinct differentiation trajectory encompassing stem and progenitor-like tumor cells. In summary, our single-cell analyses provide insights into cell types and signals shaping colorectal cancer cell plasticity

Signal integration by the CYP1A1 promoter - a quantitative study

Genes involved in detoxification of foreign compounds exhibit complex spatiotemporal expression patterns in liver. Cytochrome P450 1A1 (CYP1A1), for example, is restricted to the pericentral region of liver lobules in response to the interplay between aryl hydrocarbon receptor (AhR) and Wnt/β-catenin signaling pathways. However, the mechanisms by which the two pathways orchestrate gene expression are still poorly understood. With the help of 29 mutant constructs of the human CYP1A1 promoter and a mathematical model that combines Wnt/β-catenin and AhR signaling with the statistical mechanics of the promoter, we systematically quantified the regulatory influence of different transcription factor binding sites on gene induction within the promoter. The model unveils how different binding sites cooperate and how they establish the promoter logic; it quantitatively predicts two-dimensional stimulus-response curves. Furthermore, it shows that crosstalk between Wnt/β-catenin and AhR signaling is crucial to understand the complex zonated expression patterns found in liver lobules. This study exemplifies how statistical mechanical modeling together with combinatorial reporter assays has the capacity to disentangle the promoter logic that establishes physiological gene expression patterns.Pharmacolog

Computer-assisted curation of a human regulatory core network from the biological literature

Motivation: A highly interlinked network of transcription factors (TFs) orchestrates the context-dependent expression of human genes. ChIP-chip experiments that interrogate the binding of particular TFs to genomic regions are used to reconstruct gene regulatory networks at genome-scale, but are plagued by high false-positive rates. Meanwhile, a large body of knowledge on high-quality regulatory interactions remains largely unexplored, as it is available only in natural language descriptions scattered over millions of scientific publications. Such data are hard to extract and regulatory data currently contain together only 503 regulatory relations between human TFs. Results: We developed a text-mining-assisted workflow to systematically extract knowledge about regulatory interactions between human TFs from the biological literature. We applied this workflow to the entire Medline, which helped us to identify more than 45 000 sentences potentially describing such relationships. We ranked these sentences by a machine-learning approach. The top-2500 sentences contained ∼900 sentences that encompass relations already known in databases. By manually curating the remaining 1625 top-ranking sentences, we obtained more than 300 validated regulatory relationships that were not present in a regulatory database before. Full-text curation allowed us to obtain detailed information on the strength of experimental evidences supporting a relationship. Conclusions: We were able to increase curated information about the human core transcriptional network by >60% compared with the current content of regulatory databases. We observed improved performance when using the network for disease gene prioritization compared with the state-of-the-art. Availability and implementation: Web-service is freely accessible athttp://fastforward.sys-bio.net/.FWN – Publicaties zonder aanstelling Universiteit Leide

Mathematical and Statistical Techniques for Systems Medicine: The Wnt Signaling Pathway as a Case Study

The last decade has seen an explosion in models that describe phenomena in systems medicine. Such models are especially useful for studying signaling pathways, such as the Wnt pathway. In this chapter we use the Wnt pathway to showcase current mathematical and statistical techniques that enable modelers to gain insight into (models of) gene regulation, and generate testable predictions. We introduce a range of modeling frameworks, but focus on ordinary differential equation (ODE) models since they remain the most widely used approach in systems biology and medicine and continue to offer great potential. We present methods for the analysis of a single model, comprising applications of standard dynamical systems approaches such as nondimensionalization, steady state, asymptotic and sensitivity analysis, and more recent statistical and algebraic approaches to compare models with data. We present parameter estimation and model comparison techniques, focusing on Bayesian analysis and coplanarity via algebraic geometry. Our intention is that this (non exhaustive) review may serve as a useful starting point for the analysis of models in systems medicine.Comment: Submitted to 'Systems Medicine' as a book chapte

Tree Resin Composition, Collection Behavior and Selective Filters Shape Chemical Profiles of Tropical Bees (Apidae: Meliponini)

The diversity of species is striking, but can be far exceeded by the chemical diversity of compounds collected, produced or used by them. Here, we relate the specificity of plant-consumer interactions to chemical diversity applying a comparative network analysis to both levels. Chemical diversity was explored for interactions between tropical stingless bees and plant resins, which bees collect for nest construction and to deter predators and microbes. Resins also function as an environmental source for terpenes that serve as appeasement allomones and protection against predators when accumulated on the bees' body surfaces. To unravel the origin of the bees' complex chemical profiles, we investigated resin collection and the processing of resin-derived terpenes. We therefore analyzed chemical networks of tree resins, foraging networks of resin collecting bees, and their acquired chemical networks. We revealed that 113 terpenes in nests of six bee species and 83 on their body surfaces comprised a subset of the 1,117 compounds found in resins from seven tree species. Sesquiterpenes were the most variable class of terpenes. Albeit widely present in tree resins, they were only found on the body surface of some species, but entirely lacking in others. Moreover, whereas the nest profile of Tetragonula melanocephala contained sesquiterpenes, its surface profile did not. Stingless bees showed a generalized collecting behavior among resin sources, and only a hitherto undescribed species-specific “filtering” of resin-derived terpenes can explain the variation in chemical profiles of nests and body surfaces from different species. The tight relationship between bees and tree resins of a large variety of species elucidates why the bees' surfaces contain a much higher chemodiversity than other hymenopterans

Identification of Y-Box Binding Protein 1 As a Core Regulator of MEK/ERK Pathway-Dependent Gene Signatures in Colorectal Cancer Cells

Transcriptional signatures are an indispensible source of correlative information on disease-related molecular alterations on a genome-wide level. Numerous candidate genes involved in disease and in factors of predictive, as well as of prognostic, value have been deduced from such molecular portraits, e.g. in cancer. However, mechanistic insights into the regulatory principles governing global transcriptional changes are lagging behind extensive compilations of deregulated genes. To identify regulators of transcriptome alterations, we used an integrated approach combining transcriptional profiling of colorectal cancer cell lines treated with inhibitors targeting the receptor tyrosine kinase (RTK)/RAS/mitogen-activated protein kinase pathway, computational prediction of regulatory elements in promoters of co-regulated genes, chromatin-based and functional cellular assays. We identified commonly co-regulated, proliferation-associated target genes that respond to the MAPK pathway. We recognized E2F and NFY transcription factor binding sites as prevalent motifs in those pathway-responsive genes and confirmed the predicted regulatory role of Y-box binding protein 1 (YBX1) by reporter gene, gel shift, and chromatin immunoprecipitation assays. We also validated the MAPK-dependent gene signature in colorectal cancers and provided evidence for the association of YBX1 with poor prognosis in colorectal cancer patients. This suggests that MEK/ERK-dependent, YBX1-regulated target genes are involved in executing malignant properties

Temporal scale‐dependence of plant–pollinator networks

The study of mutualistic interaction networks has led to valuable insights into ecological and evolutionary processes. However, our understanding of network structure may depend upon the temporal scale at which we sample and analyze network data. To date, we lack a comprehensive assessment of the temporal scale-dependence of network structure across a wide range of temporal scales and geographic locations. If network structure is temporally scale-dependent, networks constructed over different temporal scales may provide very different perspectives on the structure and composition of species interactions. Furthermore, it remains unclear how various factors – including species richness, species turnover, link rewiring and sampling effort – act in concert to shape network structure across different temporal scales. To address these issues, we used a large database of temporally-resolved plant–pollinator networks to investigate how temporal aggregation from the scale of one day to multiple years influences network structure. In addition, we used structural equation modeling to explore the direct and indirect effects of temporal scale, species richness, species turnover, link rewiring and sampling effort on network structural properties. We find that plant–pollinator network structure is strongly temporally-scale dependent. This general pattern arises because the temporal scale determines the degree to which temporal dynamics (i.e. phenological turnover of species and links) are included in the network, in addition to how much sampling effort is put into constructing the network. Ultimately, the temporal scale-dependence of our plant–pollinator networks appears to be mostly driven by species richness, which increases with sampling effort, and species turnover, which increases with temporal extent. In other words, after accounting for variation in species richness, network structure is increasingly shaped by its underlying temporal dynamics. Our results suggest that considering multiple temporal scales may be necessary to fully appreciate the causes and consequences of interaction network structure.Fil: Schwarz, Benjamin. Albert Ludwigs University of Freiburg; AlemaniaFil: Vazquez, Diego P.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Provincia de Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Universidad Nacional de Cuyo. Instituto Argentino de Investigaciones de las Zonas Áridas; ArgentinaFil: Cara Donna, Paul J.. Chicago Botanic Garden; Estados UnidosFil: Knight, Tiffany M.. German Centre for Integrative Biodiversity Research; AlemaniaFil: Benadi, Gita. Albert Ludwigs University of Freiburg; AlemaniaFil: Dormann, Carsten F.. Albert Ludwigs University of Freiburg; AlemaniaFil: Gauzens, Benoit. German Centre for Integrative Biodiversity Research; AlemaniaFil: Motivans, Elena. German Centre for Integrative Biodiversity Research; AlemaniaFil: Resasco, Julian. University of Colorado; Estados UnidosFil: Blüthgen, Nico. Universitat Technische Darmstadt; AlemaniaFil: Burkle, Laura A.. Montana State University; AlemaniaFil: Fang, Qiang. Henan University of Science and Technology; ChinaFil: Kaiser Bunbury, Christopher N.. University of Exeter; Reino UnidoFil: Alarcón, Ruben. California State University; Estados UnidosFil: Bain, Justin A.. Chicago Botanic Garden; Estados UnidosFil: Chacoff, Natacha Paola. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Huang, Shuang Quan. Central China Normal University; ChinaFil: LeBuhn, Gretchen. San Francisco State University; Estados UnidosFil: MacLeod, Molly. Rutgers University; Estados UnidosFil: Petanidou, Theodora. Univversity of the Aegean; Estados UnidosFil: Rasmussen, Claus. University Aarhus; DinamarcaFil: Simanonok, Michael P.. Montana State University; Estados UnidosFil: Thompson, Amibeth H.. German Centre for Integrative Biodiversity Research; AlemaniaFil: Fründ, Jochen. Albert Ludwigs University of Freiburg; Alemani

The Missing Part of Seed Dispersal Networks: Structure and Robustness of Bat-Fruit Interactions

Mutualistic networks are crucial to the maintenance of ecosystem services. Unfortunately, what we know about seed dispersal networks is based only on bird-fruit interactions. Therefore, we aimed at filling part of this gap by investigating bat-fruit networks. It is known from population studies that: (i) some bat species depend more on fruits than others, and (ii) that some specialized frugivorous bats prefer particular plant genera. We tested whether those preferences affected the structure and robustness of the whole network and the functional roles of species. Nine bat-fruit datasets from the literature were analyzed and all networks showed lower complementary specialization (H2' = 0.37±0.10, mean ± SD) and similar nestedness (NODF = 0.56±0.12) than pollination networks. All networks were modular (M = 0.32±0.07), and had on average four cohesive subgroups (modules) of tightly connected bats and plants. The composition of those modules followed the genus-genus associations observed at population level (Artibeus-Ficus, Carollia-Piper, and Sturnira-Solanum), although a few of those plant genera were dispersed also by other bats. Bat-fruit networks showed high robustness to simulated cumulative removals of both bats (R = 0.55±0.10) and plants (R = 0.68±0.09). Primary frugivores interacted with a larger proportion of the plants available and also occupied more central positions; furthermore, their extinction caused larger changes in network structure. We conclude that bat-fruit networks are highly cohesive and robust mutualistic systems, in which redundancy is high within modules, although modules are complementary to each other. Dietary specialization seems to be an important structuring factor that affects the topology, the guild structure and functional roles in bat-fruit networks