3K0924 Estimating core designs of signaling networks from live-cell imaging data using a particle filter approach(Cell biology 3,The 49th Annual Meeting of the Biophysical Society of Japan)

Monitoring cellular responses to changes in growth conditions and perturbation of targeted pathways is integral to the investigation of biological processes. However, manipulating cells and their environment during live-cell-imaging experiments still represents a major challenge. While the coupling of microfluidics with microscopy has emerged as a powerful solution to this problem, this approach remains severely underexploited. Indeed, most microdevices rely on the polymer polydimethylsiloxane (PDMS), which strongly absorbs a variety of molecules commonly used in cell biology. This effect of the microsystems on the cellular environment hampers our capacity to accurately modulate the composition of the medium and the concentration of specific compounds within the microchips, with implications for the reliability of these experiments. To overcome this critical issue, we developed new PDMS-free microdevices dedicated to live-cell imaging that show no interference with small molecules. They also integrate a module for maintaining precise sample temperature both above and below ambient as well as for rapid temperature shifts. Importantly, changes in medium composition and temperature can be efficiently achieved within the chips while recording cell behaviour by microscopy. Compatible with different model systems, our platforms provide a versatile solution for the dynamic regulation of the cellular environment during live-cell imaging.

Download Full-text

From imaging to understanding: Frontiers in Live Cell Imaging, Bethesda, MD, April 19–21, 2006

The Journal of Cell Biology ◽

10.1083/jcb.200607097 ◽

2006 ◽

Vol 174 (4) ◽

pp. 481-484 ◽

Cited By ~ 17

Author(s):

Yu-li Wang ◽

Klaus M. Hahn ◽

Robert F. Murphy ◽

Alan F. Horwitz

Keyword(s):

Cell Biology ◽

Live Cell Imaging ◽

Recent Progress ◽

Cell Imaging ◽

Live Cell ◽

The Other ◽

Biological Applications ◽

Research Fields ◽

Recent Meeting ◽

The One

A recent meeting entitled Frontiers in Live Cell Imaging was attended by more than 400 cell biologists, physicists, chemists, mathematicians, and engineers. Unlike typical special topics meetings, which bring together investigators in a defined field primarily to review recent progress, the purpose of this meeting was to promote cross-disciplinary interactions by introducing emerging methods on the one hand and important biological applications on the other. The goal was to turn live cell imaging from a “technique” used in cell biology into a new exploratory science that combines a number of research fields.

Download Full-text

Deconvolution of subcellular protrusion heterogeneity and the underlying actin regulator dynamics from live cell imaging

10.1101/144238 ◽

2017 ◽

Cited By ~ 1

Author(s):

Chuangqi Wang ◽

Hee June Choi ◽

Sung-Jin Kim ◽

Aesha Desai ◽

Namgyu Lee ◽

...

Keyword(s):

Machine Learning ◽

Live Cell Imaging ◽

Cell Imaging ◽

Leading Edge ◽

Live Cell ◽

Imaging Data ◽

Computational Framework ◽

Cell Protrusion ◽

Learning Analysis ◽

Subcellular Level

AbstractCell protrusion is morphodynamically heterogeneous at the subcellular level. However, the mechanistic understanding of protrusion activities is usually based on the ensemble average of actin regulator dynamics at the cellular or population levels. Here, we establish a machine learning-based computational framework called HACKS (deconvolution of Heterogeneous Activity Coordination in cytosKeleton at a Subcellular level) to deconvolve the subcellular heterogeneity of lamellipodial protrusion in migrating cells. HACKS quantitatively identifies distinct subcellular protrusion phenotypes from highly heterogeneous protrusion activities and reveals their underlying actin regulator dynamics at the leading edge. Furthermore, it can identify specific subcellular protrusion phenotypes susceptible to pharmacological perturbation and reveal how actin regulator dynamics are changed by the perturbation. Using our method, we discovered ‘accelerating’ protrusion phenotype in addition to ‘fluctuating’ and ‘periodic’ protrusions. Intriguingly, the accelerating protrusion was driven by the temporally coordinated actions between Arp2/3 and VASP: initiated by Arp2/3-mediated actin nucleation, and then accelerated by VASP-mediated actin elongation. We were able to confirm it by pharmacological perturbations using CK666 and Cytochalasin D, which specifically reduced ‘strong accelerating protrusion’ activities. Taken together, we have demonstrated that HACKS allows us to discover the fine differential coordination of molecular dynamics underlying subcellular protrusion heterogeneity via a machine learning analysis of live cell imaging data.

Download Full-text