Visualization and quantitation of the expression of microRNAs and their target genes in neuroblastoma single cells using imaging cytometry

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are regulatory molecules that play an important role in many physiological processes, including cell growth, differentiation, and apoptosis. In addition to modulating normal cellular functions, it has also been reported that miRNAs are involved in the development of many pathologies, including cardiovascular diseases, cancer, inflammation, and neurodegeneration. Methods for the sensitive detection and measurement of specific miRNAs and their cellular targets are essential for both basic research endeavours, as well as diagnostic efforts aimed at understanding the role of miRNAs in disease processes.</p> <p>Findings</p> <p>In this study, we describe a novel, imaging cytometry-based protocol that allows for simultaneous visualisation and quantification of miRNAs and their putative targets. We validated this methodology in a neuronal cell line by examining the relationship of the miRNA miR-124 and its known target, cyclin dependent kinase 6 (CDK6). We found that ectopic overexpression of miR-124 resulted in the downregulation of CDK6, decreased cellular proliferation, and induced cellular morphological changes.</p> <p>Conclusions</p> <p>This method is suitable for analysing the expression and cellular localisation of miRNAs and target proteins in small cell subsets within a heterogeneous cell suspension. We believe that our cytometry-based methodology will be easily adaptable to miRNA studies in many areas of biomedical research including neuroscience, stem cell biology, immunology, and oncology.</p

Evolution of response dynamics underlying bacterial chemotaxis

© 2011 Soyer and Goldstein; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: The ability to predict the function and structure of complex molecular mechanisms underlying cellular behaviour is one of the main aims of systems biology. To achieve it, we need to understand the evolutionary routes leading to a specific response dynamics that can underlie a given function and how biophysical and environmental factors affect which route is taken. Here, we apply such an evolutionary approach to the bacterial chemotaxis pathway, which is documented to display considerable complexity and diversity.Results: We construct evolutionarily accessible response dynamics starting from a linear response to absolute levels of attractant, to those observed in current-day Escherichia coli. We explicitly consider bacterial movement as a two-state process composed of non-instantaneous tumbling and swimming modes. We find that a linear response to attractant results in significant chemotaxis when sensitivity to attractant is low and when time spent tumbling is large. More importantly, such linear response is optimal in a regime where signalling has low sensitivity. As sensitivity increases, an adaptive response as seen in Escherichia coli becomes optimal and leads to 'perfect' chemotaxis with a low tumbling time. We find that as tumbling time decreases and sensitivity increases, there exist a parameter regime where the chemotaxis performance of the linear and adaptive responses overlap, suggesting that evolution of chemotaxis responses might provide an example for the principle of functional change in structural continuity.Conclusions: Our findings explain several results from diverse bacteria and lead to testable predictions regarding chemotaxis responses evolved in bacteria living under different biophysical constraints and with specific motility machinery. Further, they shed light on the potential evolutionary paths for the evolution of complex behaviours from simpler ones in incremental fashion

A cell-based computational model of early embryogenesis coupling mechanical behaviour and gene regulation

The study of multicellular development is grounded in two complementary domains: cell biomechanics, which examines how physical forces shape the embryo, and genetic regulation and molecular signalling, which concern how cells determine their states and behaviours. Integrating both sides into a unified framework is crucial to fully understand the self-organized dynamics of morphogenesis. Here we introduce MecaGen, an integrative modelling platform enabling the hypothesis-driven simulation of these dual processes via the coupling between mechanical and chemical variables. Our approach relies upon a minimal ‘cell behaviour ontology’ comprising mesenchymal and epithelial cells and their associated behaviours. MecaGen enables the specification and control of complex collective movements in 3D space through a biologically relevant gene regulatory network and parameter space exploration. Three case studies investigating pattern formation, epithelial differentiation and tissue tectonics in zebrafish early embryogenesis, the latter with quantitative comparison to live imaging data, demonstrate the validity and usefulness of our framework