Eukaryotic cells like fibroblasts can be grown adherently in cell culture flasks. They bind to the substrate (which is the cell culture vessel in this case) by transmembrane adhesion proteins. When treated with the protein-capping enzyme trypsin, cells detach from the substratum and form a suspension of globular cells in medium. Subsequent to a wash-out of the trypsin, cells are able to attach to substrates again. When the substrates are coated with extracellular matrix proteins such as fibronectin, adhesion of the cells triggers signaling cascades that lead to an active spreading on the substrate. During the process of cell spreading the cells deform their cell body by protrusion of the so-called lamellipodium by forces generated by polymerization of actin. Cell spreading experiments therefore allow insights into the motility machinery of motile cells ranging from molecular signaling cascades to bio-mechanical aspects such as the interplay of membrane tension, adhesion energy gain and dissipative energy losses.
The interested reader will find helpful information searching the internet for the following keywords:
- Cell membrane
- Fibroblast cells
- Extracellular matrix
A network is a set of nodes connected by links. As an abstract concept, networks can be used to describe various systems. For example in a social network a node will represent a person while a link might describe a friendship or any sort of relationship between two persons. In this example, a link is just a representation, while in a transportation network like the power grid or a road map a link is a physical connection forcing the network into a defined geometry. We are interested in the development of spatial transportation networks. Our model organism Physarum polycephalum spans such networks as a foraging strategy connecting food sources and distributing nutrients. We characterize such a network's growth from disconnected pieces using mostly the distribution pk of the node degrees k. The node degree is a property of every individual node representing the number of links attached to said node. The distribution pk gives us the probability that by picking a random node from the network we get a node of degree k. From those quantities we may gather information on the network state. A mostly unconnected network which is mostly made up of fragments will have high values for p0, p1while for a strongly connected network higher node degrees dominate. Note that for a planar transportation network note degrees will remain relatively small even though the network is fully connected while a social network, for example, may have nodes with comparably higher degrees.
Diploid cells (indicated by 2n) have two sets of homologous chromosomes. In the human body, every cell contains two pairs of chromosomes. One copy originates from the egg cell of the mother, one from the sperm cell of the father. Most higher organisms are diploid.
Giant Unilamellar Vesicles (GUVs) can be synthetically produced by exploitation of the self assembly mechanisms of phospholipids into closed bilayer shapes. The energies for shape deformations of GUVs are very small, and thus the thermal energy of their surrounding is enough to cause membrane fluctuations that can be seen clearly in a light microscope. The radial representation of vesicle shapes can be decomposed into Fourier modes. Each of these modes corresponds to one degree of freedom. According to the equipartition theorem of statistical physics, the thermal energy is equally shared between these modes. This allows us to measure material properties like the bending rigidity of lipid bilayers based on time lapse sequences of fluctuating vesicle shapes.
A haploid cell (indicated by 1n) contains only one copy of each chromosome. In most organisms, only the gametes are haploid.
Light microscopy plays a fundamental role in our research. We especially employ phase contrast microscopy, differential interference contrast microscopy, fluorescence microscopy, reflection interference contrast microscopy, and total internal reflection fluorescence contrast microscopy. There are very good introductions available online that explain these techniques in detail. We recommend the following three links to the manufacturers Nikon, Zeiss, and Olympus.
A single cell containing many nuclei.
Plural: nuclei. The biggest compartment in a cell, enclosed by a membrane. This is where the DNA is stored.
When thinking of phase transitions, the first thing that likely comes to our minds is the transition between the states of matter, be it the common transitions like melting or evaporation or maybe the more exotic (re-)sublimation, the transition between solid and gaseous phase. To create a so-called phase diagram we define quantities which allow us to shift between states of the system by simply changing their values. In the case of the aforementioned states of matter, temperature and pressure are suitable. Mapping the system state as a function of those quantities gives us a diagram whichs dimension depends on the number of quantites chosen.
Phase transitions can be classified into first and second order transitions, dependen on whether or not the order parameter is continous at the transition. Cooling Water below 0°C does not instantly lead to a liquid → solid transition. Additional energy is required, usually brought by motion, allowing to classify this transition as first order.
In biological systems, phase transitions can be used to describe various phenomena, such as transitions between behavioral modes, like the different phases of cell motion in cell spreading. Within our network research, we define a percolation transition as the transition between an unconnected network and a network, in which most nodes are contained within a largest component. For large network size this transition happens abruptly, while for finite size the point of the transition is not clearly defined.
The dominant phase in the life cycle of Physarum polycephalum is a giant, diploid macroplasmodium (1) which can reach sizes of several cm2 and is capable of amoeboid movement. The organism forages in the damp, dark soil and feeds on dead organic matter. It forms a transportation network of veins in which a vigorous shuttle streaming of cytoplasm can be observed.
When exposed to light and lack of food, the macroplasmodium differentiates into fruiting bodies (sporangia, 2) in which innumerable haploid spores are formed.
The spores are globular, with a diameter of about 8 to 11 µm, displaying tiny spikes on the surface. Within each spore there is a single, uninucleate myxamoeba which hatches in the presence of water (3).
Myxamoeba of different mating types can fuse and form a cell with two nuclei in a process called plasmogamy. The two haploid nuclei are now together within the same cell. These two nuclei will then fuse, creating a diploid zygote with one diploid nucleus. The zygote grows while the nucleus undergoes multiple mitotic divisions.
A specific feature of acellular slime molds is that the nuclei divide many times, but the cell does not divide. The result is a multinucleate cell of considerable size with amoeboid characteristics. From this zygote (4), the young plasmodium originates and grows into a large macroplasmodium.
Possessing only one nucleus.
Studying slime mold networks we were able to learn about various properties shared by transportation networks. We learned that a single parameter is able to drive the system between a disconnected and a fully connected, percolated state. This knowledge might prove invaluable when looking for a gauge for cancer therapy targetting a tumors blood supply by not allowing it to create a fully developed network of blood vessels.
Tumors may derive their blood vessels by various mechanisms. Some initiate existing blood vessels to grow into the tumor by sprouting. This is usually referred to as a mechanism of angiogenesis. Other tumors, like embryos, derive their blood vessels by vasculogenesis, meaning the differentiation of pluripotent cells into angioblast and endothelial cells which aggregate in blood islands. Those islands may fuse in a percolation transition to form a connected network. This can be modeled in an artificial experiment using endothelial cells (see figure, Serini et al 2003, modified.)