Kristin Sott

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° between each nanotube. Formation of branching nanotube networks appears to follow a minimum-bending energy algorithm that solves for pathway minimization. It is also demonstrated that materials can be injected into specific containers within a network by nanotube-mediated transport of satellite vesicles having defined contents. Using a combination of microelectrofusion, spontaneous nanotube pattern formation, and satellite-vesicle injection, complex networks of containers and nanotubes can be produced for a range of applications in, for example, nanofluidics and artificial cell design. In addition, this electrofusion method allows integration of biological cells into lipid nanotube-vesicle networks.

Adsorption behavior and enzymatically or chemically induced cross‐linking of a mussel adhesive protein

The adsorption behavior of the mussel adhesive protein Mytilus edulis foot protein‐1 (Mefp‐1) has been investigated on a negatively charged polar SiO2 surface and an electrically inert non‐polar CH3‐terminated thiolated gold surface. How the structure of adsorbed Mefp‐1 is changed upon chemically and enzymatically induced cross‐linking using sodium periodate (NaIO4) and catechol oxidase, both of which transform DOPA residues in Mefp‐1 into highly reactive o‐quinones, was also investigated. The results are compared with those resulting from addition of Cu2+ to adsorbed Mefp‐1, which forms complexes with and catalyses oxidation of DOPA residues, previously suggested to participate in the cohesive and adhesive properties of the byssus thread of M. edulis. By combining surface plasmon resonance (SPR) and quartz crystal microbalance/dissipation (QCM‐D) measurements, the effects of these agents were investigated with respect to changes in the amount of coupled water, the viscoelastic properties (rigidity) and the hydrodynamic thickness of the protein adlayers. The layer of Mefp‐1 formed on the bare CH3‐terminated surface was elongated, flexible and coupled hydrodynamically a substantial amount of water, whereas Mefp‐1 formed a rigidly attached adlayer on the SiO2 surface. Upon enzymatically and chemically induced cross‐linking of Mefp‐1 formed on the CH3 surface, the rigidity of the adlayer(s) increased significantly. A similar increase in the rigidity was observed also upon addition of Cu2+, suggesting that the high level of metal ions present in the byssus thread might be essential for the cohesive and adhesive properties of this protein. For the mass‐uptake kinetics of enzymatically induced cross‐linking, three different phases were observed and are interpreted as competition between binding of protein and release of coupled water. For the reaction with NaIO4 and Cu2+, only release of water affected the coupled mass. The importance of this type of information for an improved understanding of the strong adhesion and cohesive properties in marine environments is discussed.

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. Objective: This review highlights the use of optical manipulation, microfluidics and advanced fluorescence imaging techniques for the acquisition of single cell data. Conclusion: By implementation of these three techniques, it is possible to achieve a deeper insight into the principles underlying cellular functioning and a more thorough understanding of the phenomena often observed in cell populations, thus facilitating research in drug discovery.

CellStress - open source image analysis program for single-cell analysis

This work describes our image-analysis software, CellStress, which has been developed in Matlab and is issued under a GPL license. CellStress was developed in order to analyze migration of fluorescent proteins inside single cells during changing environmental conditions. CellStress can also be used to score information regarding protein aggregation in single cells over time, which is especially useful when monitoring cell signaling pathways involved in e.g. Alzheimers or Huntingtons disease. Parallel single-cell analysis of large numbers of cells is an important part of the research conducted in systems biology and quantitative biology in order to mathematically describe cellular processes. To quantify properties for single cells, large amounts of data acquired during extended time periods are needed. Manual analyses of such data involve huge efforts and could also include a bias, which complicates the use and comparison of data for further simulations or modeling. Therefore, it is necessary to have an automated and unbiased image analysis procedure, which is the aim of CellStress. CellStress utilizes cell contours detected by CellStat (developed at Fraunhofer-Chalmers Centre), which identifies cell boundaries using bright field images, and thus reduces the fluorescent labeling needed.

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. The experimental flow results show good agreement with predictions from the Lattice-Boltzmann modelling. These simulations were performed in geometries constructed from 3D CLSM images of the actual PDMS structures. Given these results, mass transport behaviour may be predicted for even more complex structures, like gels or composite material in, e.g., food or biomaterials. This is a step in the direction towards predictive science with regards to tailoring soft biomaterials for specific mass transport properties.