A microfluidic system for studying ageing and dynamic single-cell responses in budding yeast

Recognition of the importance of cell-to-cell variability in cellular decision-making and a growing interest in stochastic modeling of cellular processes has led to an increased demand for high density, reproducible, single-cell measurements in time-varying surroundings. We present ALCATRAS (A Long-term Culturing And TRApping System), a microfluidic device that can quantitatively monitor up to 1000 cells of budding yeast in a well-defined and controlled environment. Daughter cells are removed by fluid flow to avoid crowding allowing experiments to run for over 60 hours, and the extracellular media may be changed repeatedly and in seconds. We illustrate use of the device by measuring ageing through replicative life span curves, following the dynamics of the cell cycle, and examining history-dependent behaviour in the general stress response

Affinity binding of inclusion bodies on supermacroporous monolithic cryogels using labeling with specific antibodies

A new chromatographic method based on affinity supermacroporous monolithic cryogels is developed for binding and analyzing inclusion bodies during fermentation. The work demonstrated that it is possible to bind specific IgG and IgY antibodies to the 15 and 17 amino acids at the terminus ends of a 33 kDa target protein aggregated as inclusion bodies. The antibody treated inclusion bodies from lysed fermentation broth can be specifically retained in protein A and pseudo-biospecific ligand sulfamethazine modified supermacroporous cryogels. The degree of binding of IgG and IgY treated inclusion bodies to the Protein A and sulfamethazine gels are investigated, as well as the influence of pH on the sulfamethazine ligand. Optimum binding of 78 and 72% was observed on both protein A and sulfamethazine modified cryogel columns, respectively, using IgG labeling of the inclusion bodies. The antibody treated inclusion bodies pass through unretained in the sulfamethazine supermacroporous gel at pH that does not favour the binding between the ligand on the gel and the antibodies on the surface of inclusion bodies. Also the unlabeled inclusion bodies went through the gel unretained, showing no non-specific binding or trapping within the gel. These findings may very well be the foundation for the building of a powerful analytical tool during fermentation of inclusion bodies as well as a convenient way to purify them from fermentation broth. These results also support our earlier findings [Kumar, A., Plieva, F.M., Galaev, I.Yu., Mattiasson, B.. 2003. Affinity fractionation of lymphocytes using a monolithic cyogel. J. Immunol. Methods 283, 185-194] with mammalian cells that were surface labeled with specific antibodies and recognized on protein A supermacroporous gels. A general binding and separation system can be established on antibody binding cryogel affinity matrices

Bioreactor hydrodynamic effect on Escherichia coli physiology: experimental results and stochastic simulations.

A microorganism circulating in a bioreactor can be submitted to hydrodynamic conditions inducing a significant effect on its physiology. The mixing time exhibited by the stirred bioreactor and the circulation of microorganisms are both involved in this reacting system. The mixing component determines the intensity of the concentration gradient and the circulation component determines the way in which the microorganism is exposed to this gradient. These two components linked to the experimental evaluation of microbial physiology can be analysed by a structured stochastic model in the case of a partitioned or "scale-down" reactor (SDR). A stochastic model indeed enables to simulate the mixing process as well as the circulation of microorganisms in SDRs. The superimposition of mixing and circulation processes determines the concentration profile experienced by a microorganism in the reactor. In the present case, the glucose concentration experienced by Escherichia coli has been modelled during a fed-batch culture. In this context, the use of a stochastic hydrodynamic model has permitted to point out an interesting feed pulse retardant effect in the SDRs. Nevertheless, the metabolic response of E. coli is not easy to interpret because of the possible simultaneous developments of overflow metabolism and mixed acid fermentation induced by the strong glucose concentration in the reactor