63,283 research outputs found

    Systematic quantitative characterization of cellular responses induced by multiple signals

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    <p>Abstract</p> <p>Background</p> <p>Cells constantly sense many internal and environmental signals and respond through their complex signaling network, leading to particular biological outcomes. However, a systematic characterization and optimization of multi-signal responses remains a pressing challenge to traditional experimental approaches due to the arising complexity associated with the increasing number of signals and their intensities.</p> <p>Results</p> <p>We established and validated a data-driven mathematical approach to systematically characterize signal-response relationships. Our results demonstrate how mathematical learning algorithms can enable systematic characterization of multi-signal induced biological activities. The proposed approach enables identification of input combinations that can result in desired biological responses. In retrospect, the results show that, unlike a single drug, a properly chosen combination of drugs can lead to a significant difference in the responses of different cell types, increasing the differential targeting of certain combinations. The successful validation of identified combinations demonstrates the power of this approach. Moreover, the approach enables examining the efficacy of all lower order mixtures of the tested signals. The approach also enables identification of system-level signaling interactions between the applied signals. Many of the signaling interactions identified were consistent with the literature, and other unknown interactions emerged.</p> <p>Conclusions</p> <p>This approach can facilitate development of systems biology and optimal drug combination therapies for cancer and other diseases and for understanding key interactions within the cellular network upon treatment with multiple signals.</p

    Cellular interactions in the tumor microenvironment: the role of secretome

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    Over the past years, it has become evident that cancer initiation and progression depends on several components of the tumor microenvironment, including inflammatory and immune cells, fibroblasts, endothelial cells, adipocytes, and extracellular matrix. These components of the tumor microenvironment and the neoplastic cells interact with each other providing pro and antitumor signals. The tumor-stroma communication occurs directly between cells or via a variety of molecules secreted, such as growth factors, cytokines, chemokines and microRNAs. This secretome, which derives not only from tumor cells but also from cancer-associated stromal cells, is an important source of key regulators of the tumorigenic process. Their screening and characterization could provide useful biomarkers to improve cancer diagnosis, prognosis, and monitoring of treatment responses.Agência financiadora Fundação de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) FAPESP 10/51168-0 12/06048-2 13/03839-1 National Council for Scientific and Technological Development (CNPq) CNPq 306216/2010-8 Fundacao para a Ciencia e a Tecnologia (FCT) UID/BIM/04773/2013 CBMR 1334info:eu-repo/semantics/publishedVersio

    Pulsed Feedback Defers Cellular Differentiation

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    Environmental signals induce diverse cellular differentiation programs. In certain systems, cells defer differentiation for extended time periods after the signal appears, proliferating through multiple rounds of cell division before committing to a new fate. How can cells set a deferral time much longer than the cell cycle? Here we study Bacillus subtilis cells that respond to sudden nutrient limitation with multiple rounds of growth and division before differentiating into spores. A well-characterized genetic circuit controls the concentration and phosphorylation of the master regulator Spo0A, which rises to a critical concentration to initiate sporulation. However, it remains unclear how this circuit enables cells to defer sporulation for multiple cell cycles. Using quantitative time-lapse fluorescence microscopy of Spo0A dynamics in individual cells, we observed pulses of Spo0A phosphorylation at a characteristic cell cycle phase. Pulse amplitudes grew systematically and cell-autonomously over multiple cell cycles leading up to sporulation. This pulse growth required a key positive feedback loop involving the sporulation kinases, without which the deferral of sporulation became ultrasensitive to kinase expression. Thus, deferral is controlled by a pulsed positive feedback loop in which kinase expression is activated by pulses of Spo0A phosphorylation. This pulsed positive feedback architecture provides a more robust mechanism for setting deferral times than constitutive kinase expression. Finally, using mathematical modeling, we show how pulsing and time delays together enable “polyphasic” positive feedback, in which different parts of a feedback loop are active at different times. Polyphasic feedback can enable more accurate tuning of long deferral times. Together, these results suggest that Bacillus subtilis uses a pulsed positive feedback loop to implement a “timer” that operates over timescales much longer than a cell cycle

    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"

    MicroRNAs in the stressed heart: Sorting the signal from the noise

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    The short noncoding RNAs, known as microRNAs, are of undisputed importance in cellular signaling during differentiation and development, and during adaptive and maladaptive responses of adult tissues, including those that comprise the heart. Cardiac microRNAs are regulated by hemodynamic overload resulting from exercise or hypertension, in the response of surviving myocardium to myocardial infarction, and in response to environmental or systemic disruptions to homeostasis, such as those arising from diabetes. A large body of work has explored microRNA responses in both physiological and pathological contexts but there is still much to learn about their integrated actions on individual mRNAs and signaling pathways. This review will highlight key studies of microRNA regulation in cardiac stress and suggest possible approaches for more precise identification of microRNA targets, with a view to exploiting the resulting data for therapeutic purposes

    Bion-M2 PI 1-Pagers

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    Sexual pheromone modulates the frequency of cytosolic Ca2+ bursts in Saccharomyces cerevisiae

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    Transient and highly regulated elevations of cytosolic Ca2+ control a variety of cellular processes. Bulk measurements using radioactive Ca2+ and the luminescent sensor aequorin have shown that in response to pheromone, budding yeast cells experience a rise of cytosolic Ca2+ that is mediated by two import systems composed by the Mid1-Cch1-Ecm7 protein complex, and the Fig 1 protein. Although this response has been largely studied, there is no report on Ca2+ dynamics at the single cell level. Here, using protein calcium indicators we show that both vegetative and pheromone-treated yeast cells exhibit discrete and asynchronous Ca2+ bursts. Most bursts reach maximal amplitude in 1-10 secs, span between 7 and 30 secs and decay fitting a single exponential model. In vegetative cells bursts are scarce but preferentially occur when cells are transitioning G1 and S phase. Upon pheromone presence Ca2+ burst occurrence increases dramatically, persisting during cell growth polarization. Pheromone concentration modulates burst frequency in a mechanism that depends on Mid1, Fig 1 and a third, still unidentified, import system. We also show that the calcineurin-responsive transcription factor Crz1 experiences nuclear localization bursts during the pheromone response.Fil: Carbo, Natalia. Instituto Pasteur de Montevideo; UruguayFil: Tarkowski, Nahuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; ArgentinaFil: Perez Ipiña, Emiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Ponce Dawson, Silvina Martha. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; ArgentinaFil: Aguilar, Pablo Sebastián. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentin

    Circuitry of nuclear factor κB signaling

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    Over the past few years, the transcription factor nuclear factor (NF)-κB and the proteins that regulate it have emerged as a signaling system of pre-eminent importance in human physiology and in an increasing number of pathologies. While NF-κB is present in all differentiated cell types, its discovery and early characterization were rooted in understanding B-cell biology. Significant research efforts over two decades have yielded a large body of literature devoted to understanding NF-κB's functioning in the immune system. NF-κB has been found to play roles in many different compartments of the immune system during differentiation of immune cells and development of lymphoid organs and during immune activation. NF-κB is the nuclear effector of signaling pathways emanating from many receptors, including those of the inflammatory tumor necrosis factor and Toll-like receptor superfamilies. With this review, we hope to provide historical context and summarize the diverse physiological functions of NF-κB in the immune system before focusing on recent advances in elucidating the molecular mechanisms that mediate cell type-specific and stimulus-specific functions of this pleiotropic signaling system. Understanding the genetic regulatory circuitry of NF-κB functionalities involves system-wide measurements, biophysical studies, and computational modeling
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