Simulated oxygen and glucose gradients as a prerequisite for predicting industrial scale performance a priori.

Transferring bioprocesses from lab to industrial scale without loss of performance is key for the successful implementation of novel production approaches. Because mixing and mass transfer is usually hampered in large scale, cells experience heterogeneities eventually causing deteriorated yields, that is, reduced titers, productivities, and sugar-to-product conversions. Accordingly, reliable and easy-to-implement tools for a priori prediction of large-scale performance based on dry and wet-lab tests are heavily needed. This study makes use of computational fluid dynamic simulations of a multiphase multi-impeller stirred tank in pilot scale. So-called lifelines, records of 120,000 Corynebacterium glutamicum cells experiencing fluctuating environmental conditions, were identified and used to properly design wet-lab scale-down (SD) devices. Physical parameters such as power input, gas hold up, kLa , and mixing time showed good agreement with experimental measurements. Analyzing the late fed-batch cultivation revealed that the complex double gradient of glucose and oxygen can be translated into a wet-lab SD setup with only few compartments. Most remarkably, the comparison of different mesh sizes outlined that even the coarsest approach with a mesh density of 1.12×105#/m3 was sufficient to properly predict physical and biological readouts. Accordingly, the approach offers the potential for the thorough analysis of realistic industrial case scenarios.

Lagrangian Trajectories to Predict the Formation of Population Heterogeneity in Large-Scale Bioreactors.

Successful scale-up of bioprocesses requires that laboratory-scale performance is equally achieved during large-scale production to meet economic constraints. In industry, heuristic approaches are often applied, making use of physical scale-up criteria that do not consider cellular needs or properties. As a consequence, large-scale productivities, conversion yields, or product purities are often deteriorated, which may prevent economic success. The occurrence of population heterogeneity in large-scale production may be the reason for underperformance. In this study, an in silico method to predict the formation of population heterogeneity by combining computational fluid dynamics (CFD) with a cell cycle model of Pseudomonas putida KT2440 was developed. The glucose gradient and flow field of a 54,000 L stirred tank reactor were generated with the Euler approach, and bacterial movement was simulated as Lagrange particles. The latter were statistically evaluated using a cell cycle model. Accordingly, 72% of all cells were found to switch between standard and multifork replication, and 10% were likely to undergo massive, transcriptional adaptations to respond to extracellular starving conditions. At the same time, 56% of all cells replicated very fast, with µ ≥ 0.3 h-1 performing multifork replication. The population showed very strong heterogeneity, as indicated by the observation that 52.9% showed higher than average adenosine triphosphate (ATP) maintenance demands (12.2%, up to 1.5 fold). These results underline the potential of CFD linked to structured cell cycle models for predicting large-scale heterogeneity in silico and ab initio.

Ubiquitin orchestrates proteasome dynamics between proliferation and quiescence in yeast.

Proteasomes are essential for protein degradation in proliferating cells. Little is known about proteasome functions in quiescent cells. In nondividing yeast, a eukaryotic model of quiescence, proteasomes are depleted from the nucleus and accumulate in motile cytosolic granules termed proteasome storage granules (PSGs). PSGs enhance resistance to genotoxic stress and confer fitness during aging. Upon exit from quiescence PSGs dissolve, and proteasomes are rapidly delivered into the nucleus. To identify key players in PSG organization, we performed high-throughput imaging of green fluorescent protein (GFP)-labeled proteasomes in the yeast null-mutant collection. Mutants with reduced levels of ubiquitin are impaired in PSG formation. Colocalization studies of PSGs with proteins of the yeast GFP collection, mass spectrometry, and direct stochastic optical reconstitution microscopy of cross-linked PSGs revealed that PSGs are densely packed with proteasomes and contain ubiquitin but no polyubiquitin chains. Our results provide insight into proteasome dynamics between proliferating and quiescent yeast in response to cellular requirements for ubiquitin-dependent degradation.

Experimentally Validated Model Enables Debottlenecking of in Vitro Protein Synthesis and Identifies a Control Shift under in Vivo Conditions.

Cell-free (in vitro) protein synthesis (CFPS) systems provide a versatile tool that can be used to investigate different aspects of the transcription-translation machinery by reducing cells to the basic functions of protein formation. Recent improvements in reaction stability and lysate preparation offer the potential to expand the scope of in vitro biosynthesis from a research tool to a multifunctional and versatile platform for protein production and synthetic biology. To date, even the best-performing CFPS systems are drastically slower than in vivo references. Major limitations are imposed by ribosomal activities that progress in an order of magnitude slower on the mRNA template. Owing to the complex nature of the ribosomal machinery, conventional "trial and error" experiments only provide little insight into how the desired performance could be improved. By applying a DNA-sequence-oriented mechanistic model, we analyzed the major differences between cell-free in vitro and in vivo protein synthesis. We successfully identified major limiting elements of in vitro translation, namely the supply of ternary complexes consisting of EFTu and tRNA. Additionally, we showed that diluted in vitro systems suffer from reduced ribosome numbers. On the basis of our model, we propose a new experimental design predicting 90% increased translation rates, which were well achieved in experiments. Furthermore, we identified a shifting control in the translation rate, which is characterized by availability of the ternary complex under in vitro conditions and the initiation of translation in a living cell. Accordingly, the model can successfully be applied to sensitivity analyses and experimental design.