: The construction of efficient enzyme complexes for multienzymatic biosynthesis is of increasing interest in order to achieve maximum yield and to minimize the interference due to shortcomings that are typical for straightforward one-pot multienzyme catalysis. These include product or intermediate feedback inhibition, degeneration, and diffusive losses of reaction intermediates, consumption of co-factors, and others. The main mechanisms in nature to tackle these effects in transient or stable protein associations are the formation of metabolic channeling and microcompartments, processes that are desirable also for multienzymatic biosynthesis in vitro. This chapter provides an overview over two main aspects. First, numerous recent strategies for establishing compartmentalized multienzyme associations and constructed synthetic enzyme complexes are reviewed. Second, the computational methods at hand to investigate and optimize such associations systematically, especially with focus on large multienzyme complexes and metabolic channeling, are discussed. Perspectives on future studies of multienzymatic biosynthesis concerning compartmentalization and metabolic channeling are presented.

The understanding of cell-cycle-dependent population heterogeneities in mammalian cell culture and their influence on production rates is still limited. Furthermore, metabolic regulations arising from self-expressed signaling factors (autocrine/autoinhibitory factors) have been postulated in the past, but no determination of such effects have been made so far for fast-growing production Chinese hamster ovary (CHO) cells in chemically defined media. In this study, a novel approach combining near-physiological treatment of cells (including synchronization), population resolved mechanistic modeling and statistical analysis was developed to identify population inhomogeneities. Cell-cycle-dependent population dynamics and metabolic regulations due to a putative autocrine factor were examined and their impact on the metabolic rates and antibody production of near-physiologically synchronized CHO DP-12 cell cultures was determined. To achieve this, a population resolved model was extended to describe putative autocrine-dependentt and cell-cycle-related metabolic rates for glucose, glutamine, lactate, ammonia, and antibody production. The model parameters were estimated based on data of two repeated batch cultivations (three batches each), with main substrates in excess and potentially inhibiting waste products (lactate and ammonium) controlled within narrow ranges. Significant changes, due to a putative autocrine factor, were identified for lactate and ammonia formation and antibody production. The cell growth and the uptake of glucose and glutamine were only partially affected by the putative autocrine under the given conditions. The results indicate the presence of a self-expressed autocrine factor and its strong impact on the metabolism of CHO DP-12 cells. Furthermore, glucose and glutamine uptake, as well as the formation of ammonium and antibody were found to be significantly cell-cycle-dependent. The combined approach has a strong potential to improve the understanding of the interplay of population heterogeneities and signal factors in mammalian cell culture.

The consideration of inherent population inhomogeneities of mammalian cell cultures becomes increasingly important for systems biology study and for developing more stable and efficient processes. However, variations of cellular properties belonging to different sub-populations and their potential effects on cellular physiology and kinetics of culture productivity under bioproduction conditions have not yet been much in the focus of research. Culture heterogeneity is strongly determined by the advance of the cell cycle. The assignment of cell-cycle specific cellular variations to large-scale process conditions can be optimally determined based on the combination of (partially) synchronized cultivation under otherwise physiological conditions and subsequent population-resolved model adaptation. The first step has been achieved using the physical selection method of countercurrent flow centrifugal elutriation, recently established in our group for different mammalian cell lines which is presented in Part I of this paper series. In this second part, we demonstrate the successful adaptation and application of a cell-cycle dependent population balance ensemble model to describe and understand synchronized bioreactor cultivations performed with two model mammalian cell lines, AGE1.HNAAT and CHO-K1. Numerical adaptation of the model to experimental data allows for detection of phase-specific parameters and for determination of significant variations between different phases and different cell lines. It shows that special care must be taken with regard to the sampling frequency in such oscillation cultures to minimize phase shift (jitter) artifacts. Based on predictions of long-term oscillation behavior of a culture depending on its start conditions, optimal elutriation setup trade-offs between high cell yields and high synchronization efficiency are proposed.

A quantitative and mechanistic understanding of intracellular transport processes in eukaryotic cells during transient transfection is an important prerequisite for the systematic and specific optimization of transient gene expression procedures for pharmaceutic and industrial protein production. There is evidence that intracellular transport processes during gene delivery and their regulation may have significant influence on the transfection efficiency. This contribution describes a compartmented, spatiotemporally resolved and stochastic modeling approach that describes intracellular transport processes responsible for gene delivery during transient transfection. It enables a detailed prediction and analysis and identification of potential bottlenecks. This model is currently being adapted to a model cell line, HEK293s. The simulated results are compared with experimental quantitative polymerase chain reaction (qPCR) data and confocal imaging data obtained with transfected and stained HEK293 cells. Global parameter estimation is performed to qPCR data based on two different novel plasmid constructs in order to identify candidates for plasmid-specific transport parameter variations. The influence of the specific property of HEK293 cells to grow in clusters is investigated and the impact of active microtubule transport depending on cell morphology and clustering is examined. A general sensitivity analysis allows for the identification of the sensitive parameters.