Exploring operational boundaries for acoustic concentration of cell suspensions.

The development of a standardized, generic method for concentrating suspensions in continuous flow is challenging. In this study, we developed and tested a device capable of concentrating suspensions with an already high cell concentration to meet diverse industrial requirements. To address typical multitasking needs, we concentrated suspensions with high solid content under a variety of conditions. Cells from Saccharomyces cerevisiae, Escherichia coli, and Chinese hamster ovary cells were effectively focused in the center of the main channel of a microfluidic device using acoustophoresis. The main channel bifurcates into three outlets, allowing cells to exit through the central outlet, while the liquid evenly exits through all outlets. Consequently, the treatment separates cells from two-thirds of the surrounding liquid. We investigated the complex interactions between parameters. Increasing the channel depth results in a decrease in process efficiency, attributed to a decline in acoustic energy density. The study also revealed that different cell strains exhibit distinct acoustic contrast factors, originating from differences in dimensions, compressibility, and density values. Finally, a combination of high solid content and flow rate leads to an increase in diffusion through a phenomenon known as shear-induced diffusion. KEY POINTS: • Acoustic focusing in a microchannel was used to concentrate cell suspensions • The parameters influencing focusing at high concentrations were studied • Three different cell strains were successfully concentrated.

Giving the cells what they need when they need it: Biosensor-based feeding control.

"Giving the cells exactly what they need, when they need it" is the core idea behind the proposed bioprocess control strategy: operating bioprocess based on the physiological behavior of the microbial population rather than exclusive monitoring of environmental parameters. We are envisioning to achieve this through the use of genetically encoded biosensors combined with online flow cytometry (FCM) to obtain a time-dependent "physiological fingerprint" of the population. We developed a biosensor based on the glnA promoter (glnAp) and applied it for monitoring the nitrogen-related nutritional state of Escherichia coli. The functionality of the biosensor was demonstrated through multiple cultivation runs performed at various scales-from microplate to 20 L bioreactor. We also developed a fully automated bioreactor-FCM interface for on-line monitoring of the microbial population. Finally, we validated the proposed strategy by performing a fed-batch experiment where the biosensor signal is used as the actuator for a nitrogen feeding feedback control. This new generation of process control, -based on the specific needs of the cells, -opens the possibility of improving process development on a short timescale and therewith, the robustness and performance of fermentation processes.

Towards a widespread adoption of metabolic modeling tools in biopharmaceutical industry: a process systems biology engineering perspective.

In biotechnology, the emergence of high-throughput technologies challenges the interpretation of large datasets. One way to identify meaningful outcomes impacting process and product attributes from large datasets is using systems biology tools such as metabolic models. However, these tools are still not fully exploited for this purpose in industrial context due to gaps in our knowledge and technical limitations. In this paper, key aspects restraining the routine implementation of these tools are highlighted in three research fields: monitoring, network science and hybrid modeling. Advances in these fields could expand the current state of systems biology applications in biopharmaceutical industry to address existing challenges in bioprocess development and improvement.

Phenotypic variability in bioprocessing conditions can be tracked on the basis of on-line flow cytometry and fits to a scaling law.

Noise in gene and protein expression is a major cause for bioprocess deviation. However, this phenomenon has been only scarcely considered in real bioprocessing conditions. In this work, a scaling-law derived from genome-scale studies based on GFP reporter systems has been calibrated to an on-line flow cytometry device, allowing thus to get an insight at the level of promoter activity and associated noise during a whole microbial culture carried out in bioreactor. We show that most of the GFP reporter systems investigated and thus corresponding genes could be included inside the area covered by the scaling-law. The experimental results suggest that this scaling-law could be used to predict the dynamics of promoter activity, as well as the associated noise, in bioprocessing conditions. The knowledge acquired throughout this work could be used for the design of more robust expression systems.