Interplay between flow and diffusion in capillary alginate hydrogels.

Alginate gels with naturally occurring macroscopic capillaries have been used as a model system to study the interplay between laminar flow and diffusion of nanometer-sized solutes in real time. Calcium alginate gels that contain homogeneously distributed parallel-aligned capillary structures were formed by external addition of crosslinking ions to an alginate sol. The effects of different flow rates (0, 1, 10, 50 and 100 μl min(-1)) and three different probes (fluorescein, 10 kDa and 500 kDa fluorescein isothiocyanate-dextran) on the diffusion rates of the solutes across the capillary wall and in the bulk gel in between the capillaries were investigated using confocal laser scanning microscopy.

μPIV methodology using model systems for flow studies in heterogeneous biopolymer gel microstructures.

A methodology for studying flow in heterogeneous soft microstructures has been developed. The methodology includes: (1) model fractal or random heterogeneous microstructures fabricated in PDMS and characterised using CLSM; (2) μPIV measurements; (3) Lattice-Boltzmann simulations of flow. It has been found that the flow behaviour in these model materials is highly dependent on pore size as well as on the connectivity and occurrence of dead ends.

A mathematical analysis of nuclear intensity dynamics for Mig1-GFP under consideration of bleaching effects and background noise in Saccharomyces cerevisiae.

Fluorescence microscopy is an imaging technique that provides insights into signal transduction pathways through the generation of quantitative data, such as the spatiotemporal distribution of GFP-tagged proteins in signaling pathways. The data acquired are, however, usually a composition of both the GFP-tagged proteins of interest and of an autofluorescent background, which both undergo photobleaching during imaging. We here present a mathematical model based on ordinary differential equations that successfully describes the shuttling of intracellular Mig1-GFP under changing environmental conditions regarding glucose concentration.

A microfluidic device for reversible environmental changes around single cells using optical tweezers for cell selection and positioning.

Cells naturally exist in a dynamic chemical environment, and therefore it is necessary to study cell behaviour under dynamic stimulation conditions in order to understand the signalling transduction pathways regulating the cellular response. However, until recently, experiments looking at the cellular response to chemical stimuli have mainly been performed by adding a stress substance to a population of cells and thus only varying the magnitude of the stress. In this paper we demonstrate an experimental method enabling acquisition of data on the behaviour of single cells upon reversible environmental perturbations, where microfluidics is combined with optical tweezers and fluorescence microscopy.

Optical systems for single cell analyses.

Background: Data extracted from a population of cells represent the average response from all cells within the population. Even when the cells are genetically identical, cell-to-cell variations and genetic noise can make the cells respond in completely different ways. To understand the mechanisms behind the behaviour of a population, the cells must also be analysed on an individual basis.

Controlled initiation of enzymatic reactions in micrometer-sized biomimetic compartments.

We present a technique to initiate chemical reactions involving few reactants inside micrometer-scale biomimetic vesicles (10(-12) to 10(-15) L) integral to three-dimensional surfactant networks. The shape of these networks is under dynamic control, allowing for transfer and mixing of two or several reactants at will. Specifically, two nanotube-connected vesicles were filled with reactants (substrate and enzyme, respectively) by microinjection.

Controlling enzymatic reactions by geometry in a biomimetic nanoscale network.

We demonstrate that a transition from a compact geometry (sphere) to a structured geometry (several spheres connected by nanoconduits) in nanotube-vesicle networks (NVNs) induces an ordinary enzyme-catalyzed reaction to display wavelike properties. The reaction dynamics can be controlled directly by the geometry of the network, and such networks can be used to generate wavelike patterns in product formation. The results have bearing for understanding catalytic reactions in biological systems as well as for designing emerging wet chemical nanotechnological devices.

Nanofluidic networks based on surfactant membrane technology.

We explore possibilities to construct nanoscale analytical devices based on lipid membrane technology. As a step toward this goal, we present nanotube-vesicle networks with fluidic control, where the nanotube segments reside at, or very close (<2 microm) to optically transparent surfaces. These nanofluidic systems allow controlled transport as well as LIF detection of single nanoparticles.

Nanotube-vesicle networks with functionalized membranes and interiors.

We describe nanotube-vesicle networks with reconstituted membrane protein from cells and with interior activity defined by an injection of microparticles or molecular probes. The functionality of a membrane protein after reconstitution was verified by single-channel ion conductance measurements in excised inside-out patches from the vesicle membranes. The distribution of protein, determined by fluorescence detection, in the network membrane was homogeneous and could diffuse via a nanotube connecting two vesicles.

Formation of geometrically complex lipid nanotube-vesicle networks of higher-order topologies.

We present a microelectrofusion method for construction of fluid-state lipid bilayer networks of high geometrical complexity up to fully connected networks with genus = 3 topology. Within networks, self-organizing branching nanotube architectures could be produced where intersections spontaneously arrange themselves into three-way junctions with an angle of 120 degrees between each nanotube. Formation of branching nanotube networks appears to follow a minimum-bending energy algorithm that solves for pathway minimization.