Impact of external flow on the dynamics of swimming microorganisms near surfaces.

Swimming microorganisms have been previously observed to accumulate along walls in confined systems both experimentally and in computer simulations. Here, we use computer simulations of dilute populations for a simplified model of an organism to calculate the dynamics of swimmers between two walls with an external fluid flow. Simulations with and without hydrodynamic interactions (HIs) are used to quantify their influence on surface accumulation. We found that the accumulation of organisms at the wall is larger when HIs are included. An external fluid flow orients the organisms parallel to the fluid flow, which reduces the accumulation at the walls. The effect of the flow on the orientations is quantified and compared to previous work on upstream swimming of organisms and alignment of passive rods in flow. In pressure-driven flow, the zero shear rate at the channel center leads to a dip in the concentration of organisms in the center. The curvature of this dip is quantified as a function of the flow rate. The fluid flow also affects the transport of organisms across the channel from one wall to the other.

The network of receptors characterize B cell receptor micro- and macroclustering in a Monte Carlo model.

During the recognition of soluble antigens, B cell receptors (BCR) are known to form signaling clusters that can crucially modulate intracellular activation pathways and B cell response. Little is known about the precise nature of receptor cluster and its formation mechanism for the case of soluble antigens. Initial experiments have shown that B cell receptors first microcluster upon ligation with soluble antigens, and then coarsen into a macroscopic cap structure at one pole of a B cell. Such a mutual receptor-receptor attraction can arise locally due to cross-linking by soluble antigens among other possibilities. We develop an energy based Monte Carlo model to investigate the mechanism of B-cell receptor clustering upon ligation with soluble antigens. Our results show that mutual attraction between nearest neighbor receptor pairs can lead to microclustering of B cell receptors, but it is not sufficient for receptor macroclustering. A simple model of biased diffusion where BCR molecules experience a biased directed motion toward the largest cluster is then applied, which results in a single macrocluster of receptor molecules. The various types of receptor clusters are analyzed using the developed network-based metrics such as the average distance between any pairs of receptors.