13,424 research outputs found

    From data towards knowledge: Revealing the architecture of signaling systems by unifying knowledge mining and data mining of systematic perturbation data

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    Genetic and pharmacological perturbation experiments, such as deleting a gene and monitoring gene expression responses, are powerful tools for studying cellular signal transduction pathways. However, it remains a challenge to automatically derive knowledge of a cellular signaling system at a conceptual level from systematic perturbation-response data. In this study, we explored a framework that unifies knowledge mining and data mining approaches towards the goal. The framework consists of the following automated processes: 1) applying an ontology-driven knowledge mining approach to identify functional modules among the genes responding to a perturbation in order to reveal potential signals affected by the perturbation; 2) applying a graph-based data mining approach to search for perturbations that affect a common signal with respect to a functional module, and 3) revealing the architecture of a signaling system organize signaling units into a hierarchy based on their relationships. Applying this framework to a compendium of yeast perturbation-response data, we have successfully recovered many well-known signal transduction pathways; in addition, our analysis have led to many hypotheses regarding the yeast signal transduction system; finally, our analysis automatically organized perturbed genes as a graph reflecting the architect of the yeast signaling system. Importantly, this framework transformed molecular findings from a gene level to a conceptual level, which readily can be translated into computable knowledge in the form of rules regarding the yeast signaling system, such as "if genes involved in MAPK signaling are perturbed, genes involved in pheromone responses will be differentially expressed"

    The Regularizing Capacity of Metabolic Networks

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    Despite their topological complexity almost all functional properties of metabolic networks can be derived from steady-state dynamics. Indeed, many theoretical investigations (like flux-balance analysis) rely on extracting function from steady states. This leads to the interesting question, how metabolic networks avoid complex dynamics and maintain a steady-state behavior. Here, we expose metabolic network topologies to binary dynamics generated by simple local rules. We find that the networks' response is highly specific: Complex dynamics are systematically reduced on metabolic networks compared to randomized networks with identical degree sequences. Already small topological modifications substantially enhance the capacity of a network to host complex dynamic behavior and thus reduce its regularizing potential. This exceptionally pronounced regularization of dynamics encoded in the topology may explain, why steady-state behavior is ubiquitous in metabolism.Comment: 6 pages, 4 figure

    High-resolution temporal profiling of transcripts during Arabidopsis leaf senescence reveals a distinct chronology of processes and regulation

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    Leaf senescence is an essential developmental process that impacts dramatically on crop yields and involves altered regulation of thousands of genes and many metabolic and signaling pathways, resulting in major changes in the leaf. The regulation of senescence is complex, and although senescence regulatory genes have been characterized, there is little information on how these function in the global control of the process. We used microarray analysis to obtain a highresolution time-course profile of gene expression during development of a single leaf over a 3-week period to senescence. A complex experimental design approach and a combination of methods were used to extract high-quality replicated data and to identify differentially expressed genes. The multiple time points enable the use of highly informative clustering to reveal distinct time points at which signaling and metabolic pathways change. Analysis of motif enrichment, as well as comparison of transcription factor (TF) families showing altered expression over the time course, identify clear groups of TFs active at different stages of leaf development and senescence. These data enable connection of metabolic processes, signaling pathways, and specific TF activity, which will underpin the development of network models to elucidate the process of senescence

    Gill transcriptome response to changes in environmental calcium in the green spotted puffer fish

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    Abstract Background Calcium ion is tightly regulated in body fluids and for euryhaline fish, which are exposed to rapid changes in environmental [Ca2+], homeostasis is especially challenging. The gill is the main organ of active calcium uptake and therefore plays a crucial role in the maintenance of calcium ion homeostasis. To study the molecular basis of the short-term responses to changing calcium availability, the whole gill transcriptome obtained by Super Serial Analysis of Gene Expression (SuperSAGE) of the euryhaline teleost green spotted puffer fish, Tetraodon nigroviridis, exposed to water with altered [Ca2+] was analysed. Results Transfer of T. nigroviridis from 10 ppt water salinity containing 2.9 mM Ca2+ to high (10 mM Ca2+ ) and low (0.01 mM Ca2+) calcium water of similar salinity for 2-12 h resulted in 1,339 differentially expressed SuperSAGE tags (26-bp transcript identifiers) in gills. Of these 869 tags (65%) were mapped to T. nigroviridis cDNAs or genomic DNA and 497 (57%) were assigned to known proteins. Thirteen percent of the genes matched multiple tags indicating alternative RNA transcripts. The main enriched gene ontology groups belong to Ca2+ signaling/homeostasis but also muscle contraction, cytoskeleton, energy production/homeostasis and tissue remodeling. K-means clustering identified co-expressed transcripts with distinct patterns in response to water [Ca2+] and exposure time. Conclusions The generated transcript expression patterns provide a framework of novel water calcium-responsive genes in the gill during the initial response after transfer to different [Ca2+]. This molecular response entails initial perception of alterations, activation of signaling networks and effectors and suggests active remodeling of cytoskeletal proteins during the initial acclimation process. Genes related to energy production and energy homeostasis are also up-regulated, probably reflecting the increased energetic needs of the acclimation response. This study is the first genome-wide transcriptome analysis of fish gills and is an important resource for future research on the short-term mechanisms involved in the gill acclimation responses to environmental Ca2+ changes and osmoregulation.Peer Reviewe

    Systems analysis of host-parasite interactions.

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    Parasitic diseases caused by protozoan pathogens lead to hundreds of thousands of deaths per year in addition to substantial suffering and socioeconomic decline for millions of people worldwide. The lack of effective vaccines coupled with the widespread emergence of drug-resistant parasites necessitates that the research community take an active role in understanding host-parasite infection biology in order to develop improved therapeutics. Recent advances in next-generation sequencing and the rapid development of publicly accessible genomic databases for many human pathogens have facilitated the application of systems biology to the study of host-parasite interactions. Over the past decade, these technologies have led to the discovery of many important biological processes governing parasitic disease. The integration and interpretation of high-throughput -omic data will undoubtedly generate extraordinary insight into host-parasite interaction networks essential to navigate the intricacies of these complex systems. As systems analysis continues to build the foundation for our understanding of host-parasite biology, this will provide the framework necessary to drive drug discovery research forward and accelerate the development of new antiparasitic therapies
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