Dataset Information

Vimentin networks at tunable ion-concentration in microfluidic drops.

ABSTRACT: The structure and function of biological systems, for example, cells and proteins, depend strongly on their chemical environment. To investigate such dependence, we design a polydimethylsiloxane-based microfluidic device to encapsulate biological systems in picoliter-sized drops. The content of each individual drop is tuned in a defined manner. As a key feature of our method, the individual chemical composition is determined and related to the drop content. In our case, the drop content is imaged using microscopy methods, while the drops are immobilized to allow for long-time studies. As an application of our device, we study the influence of divalent ions on vimentin intermediate filament networks in a quantitative way by tuning the magnesium concentration from drop to drop. This way we are able to directly image the effect of magnesium on the fluorescently tagged protein in a few hundreds of drops. Our study shows that with increasing magnesium concentration in the drops, the compaction of the networks becomes more pronounced. The degree of compaction is characterized by different morphologies; freely fluctuating networks are observed at comparatively low magnesium concentrations of 5-10 mM, while with increasing magnesium concentration reaching 16 mM they develop into fully aggregated networks. Our approach demonstrates how a systematic study of interactions in biological systems can benefit from the exceptional controllability of microfluidic methods.

SUBMITTER: Dammann C

PROVIDER: S-EPMC3360716 | biostudies-other | 2012 Jun

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:The physiological heterogeneity of cells within a microbial population imparts resilience to stresses such as antimicrobial treatments and nutrient limitation. This resilience is partially due to a subpopulation of cells that can survive such stresses and regenerate the community. Microfluidic approaches now provide a means to study microbial physiology and bacterial heterogeneity at the single cell level, improving our ability to isolate and examine these subpopulations. Drop-based microfluidics provides a high-throughput approach to study individual cell physiology within bacterial populations. Using this approach, single cells are isolated from the population and encapsulated in growth medium dispersed in oil using a 15 ?m diameter drop making microfluidic device. The drops are arranged as a packed monolayer inside a polydimethylsiloxane (PDMS) microfluidic device. Growth of thousands of individual cells in identical microenvironments can then be imaged using confocal laser scanning microscopy (CLSM). A challenge for this approach has been the maintenance of drop stability during extended time-lapse imaging. In particular, the drops do not maintain their volume over time during incubation in PDMS devices, due to fluid transport into the porous PDMS surroundings. Here, we present a strategy for PDMS device preparation that stabilizes drop position and volume within a drop array on a microfluidic chip for over 20 h. The stability of water-in-oil drops is maintained by soaking the device in a reservoir containing both water and oil in thermodynamic equilibrium. This ensures that phase equilibrium of the drop emulsion fluids within the porous PDMS material is maintained during drop incubation and imaging. We demonstrate the utility of this approach, which we label DropSOAC (Drop Stabilization On A Chip), for time-lapse studies of bacterial growth. We characterize growth of Pseudomonas aeruginosa and its ?hpf mutant derivative during resuscitation and growth following starvation. We demonstrate that growth rate and lag time heterogeneity of hundreds of individual bacterial cells can be determined starting from single isolated cells. The results show that the DropSOAC capsule provides a high-throughput approach toward studies of microbial physiology at the single cell level, and can be used to characterize physiological differences of cells from within a larger population.

Dataset Information

Vimentin networks at tunable ion-concentration in microfluidic drops.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure