BackgroundMicrobial cell population heterogeneity is now recognized as a major source of issues in the development and optimization of bioprocesses. Even if single cell technologies are available for the study of microbial population heterogeneity, only a few of these methods are available in order to study the dynamics of segregation directly in bioreactors. In this context, specific interfaces have been developed in order to connect a flow cytometer directly to a bioreactor for automated analyses. In this work, we propose a simplified version of such an interface and demonstrate its usefulness for multiplexed experiments.ResultsA low-cost automated flow cytometer has been used in order to monitor the synthesis of a destabilized Green Fluorescent Protein (GFP) under the regulation of the fis promoter and propidium iodide (PI) uptake. The results obtained showed that the dynamics of GFP synthesis are complex and can be attributed to a complex set of biological parameters, i.e. on the one hand the release of protein into the extracellular medium and its uptake modifying the activity of the fis promoter, and on the other hand the stability of the GFP molecule itself, which can be attributed to the protease content and energy status of the cells. In this respect, multiplexed experiments have shown a correlation between heat shock and ATP content and the stability of the reporter molecule.ConclusionThis work demonstrates that a simplified version of on-line FC can be used at the process level or in a multiplexed version to investigate the dynamics of complex physiological mechanisms. In this respect, the determination of new on-line parameters derived from automated FC is of primary importance in order to fully integrate the power of FC in dedicated feedback control loops.

A track-sprayer combined with a high-speed camera were used to visualize and identify droplet impaction outcomes for three formulations (water, 0.1% LI 700® (lecithin, a mixture of soya oils, propionic acid and surfactants) in water and 0.1% Pulse® (non-ionic surfactant, trisiloxane ethoxylate) in water) on four plant species (bean (Vicia faba L.), avocado (Persea americana L.), barnyard grass (Echinochloa crus-galli L. P. Beauv.) and cabbage (Brassica oleracea L.)) selected to represent a wide range of leaf surface characters. Droplet sizes and velocities were measured by image analysis and a multiple hypothesis tracking algorithm. Impaction outcomes were categorized into adhesion, bounce, or shatter. The probability of each outcome was estimated from logistic regression models related to the dimensionless Weber number. This approach is in contrast to various deterministic threshold criteria for droplet bounce or shatter that have been used to model droplet impaction events on leaves. It also provides a simple visual and numerical presentation of the complexity of impaction processes, and the relative influence of leaf surface character versus formulation for droplets with different impaction energies.

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