570 Biowissenschaften; Biologie
Refine
Has Fulltext
- yes (3)
Document Type
- Postprint (3) (remove)
Language
- English (3)
Is part of the Bibliography
- yes (3)
Keywords
- Escherichia-coli (1)
- actin polymerization (1)
- activator–inhibitor models (1)
- algorithms (1)
- amp (1)
- bifurcation theory (1)
- chemoattractant (1)
- chemotaxis (1)
- cluster-analysis (1)
- cyclic-gmp (1)
Institute
- Institut für Physik und Astronomie (3) (remove)
Intracellular photoactivation of caged cGMP induces myosin II and actin responses in motile cells
(2013)
Cyclic GMP (cGMP) is a ubiquitous second messenger in eukaryotic cells. It is assumed to regulate the association of myosin II with the cytoskeleton of motile cells. When cells of the social amoeba Dictyostelium discoideum are exposed to chemoattractants or to increased osmotic stress, intracellular cGMP levels rise, preceding the accumulation of myosin II in the cell cortex. To directly investigate the impact of intracellular cGMP on cytoskeletal dynamics in a living cell, we released cGMP inside the cell by laser-induced photo-cleavage of a caged precursor. With this approach, we could directly show in a live cell experiment that an increase in intracellular cGMP indeed induces myosin II to accumulate in the cortex. Unexpectedly, we observed for the first time that also the amount of filamentous actin in the cell cortex increases upon a rise in the cGMP concentration, independently of cAMP receptor activation and signaling. We discuss our results in the light of recent work on the cGMP signaling pathway and suggest possible links between cGMP signaling and the actin system.
Background: Inferring regulatory interactions between genes from transcriptomics time-resolved data, yielding reverse engineered gene regulatory networks, is of paramount importance to systems biology and bioinformatics studies. Accurate methods to address this problem can ultimately provide a deeper insight into the complexity, behavior, and functions of the underlying biological systems. However, the large number of interacting genes coupled with short and often noisy time-resolved read-outs of the system renders the reverse engineering a challenging task. Therefore, the development and assessment of methods which are computationally efficient, robust against noise, applicable to short time series data, and preferably capable of reconstructing the directionality of the regulatory interactions remains a pressing research problem with valuable applications.
Results: Here we perform the largest systematic analysis of a set of similarity measures and scoring schemes within the scope of the relevance network approach which are commonly used for gene regulatory network reconstruction from time series data. In addition, we define and analyze several novel measures and schemes which are particularly suitable for short transcriptomics time series. We also compare the considered 21 measures and 6 scoring schemes according to their ability to correctly reconstruct such networks from short time series data by calculating summary statistics based on the corresponding specificity and sensitivity. Our results demonstrate that rank and symbol based measures have the highest performance in inferring regulatory interactions. In addition, the proposed scoring scheme by asymmetric weighting has shown to be valuable in reducing the number of false positive interactions. On the other hand, Granger causality as well as information-theoretic measures, frequently used in inference of regulatory networks, show low performance on the short time series analyzed in this study.
Conclusions: Our study is intended to serve as a guide for choosing a particular combination of similarity measures and scoring schemes suitable for reconstruction of gene regulatory networks from short time series data. We show that further improvement of algorithms for reverse engineering can be obtained if one considers measures that are rooted in the study of symbolic dynamics or ranks, in contrast to the application of common similarity measures which do not consider the temporal character of the employed data. Moreover, we establish that the asymmetric weighting scoring scheme together with symbol based measures (for low noise level) and rank based measures (for high noise level) are the most suitable choices.
During the last decade, intracellular actin waves have attracted much attention due to their essential role in various cellular functions, ranging from motility to cytokinesis. Experimental methods have advanced significantly and can capture the dynamics of actin waves over a large range of spatio-temporal scales. However, the corresponding coarse-grained theory mostly avoids the full complexity of this multi-scale phenomenon. In this perspective, we focus on a minimal continuum model of activator–inhibitor type and highlight the qualitative role of mass conservation, which is typically overlooked. Specifically, our interest is to connect between the mathematical mechanisms of pattern formation in the presence of a large-scale mode, due to mass conservation, and distinct behaviors of actin waves.