High throughput inclusion body sizing: Nano particle tracking analysis.

The expression of pharmaceutical relevant proteins in Escherichia coli frequently triggers inclusion body (IB) formation caused by protein aggregation. In the scientific literature, substantial effort has been devoted to the quantification of IB size. However, particle-based methods used up to this point to analyze the physical properties of representative numbers of IBs lack sensitivity and/or orthogonal verification. Using high pressure freezing and automated freeze substitution for transmission electron microscopy (TEM) the cytosolic inclusion body structure was preserved within the cells. TEM imaging in combination with manual grey scale image segmentation allowed the quantification of relative areas covered by the inclusion body within the cytosol. As a high throughput method nano particle tracking analysis (NTA) enables one to derive the diameter of inclusion bodies in cell homogenate based on a measurement of the Brownian motion. The NTA analysis of fixated (glutaraldehyde) and non-fixated IBs suggests that high pressure homogenization annihilates the native physiological shape of IBs. Nevertheless, the ratio of particle counts of non-fixated and fixated samples could potentially serve as factor for particle stickiness. In this contribution, we establish image segmentation of TEM pictures as an orthogonal method to size biologic particles in the cytosol of cells. More importantly, NTA has been established as a particle-based, fast and high throughput method (1000-3000 particles), thus constituting a much more accurate and representative analysis than currently available methods.

Physiological capacities decline during induced bioprocesses leading to substrate accumulation.

During the cultivation of E. coli for recombinant protein production, substrate accumulation is often observed in induction phase. Uncontrolled substrate accumulation leads to difficulties in transferring or scaling processes and even to failed batches. The phenomenon of metabolite/substrate accumulation occurs as a result of exceeding the physiological capacity to metabolize substrate (qScrit ). In contrast to the common understanding of qScrit as "static" value, we hypothesize that qScrit essentially has a dynamic nature. Following the state of the art approach of physio logical strain characterization, substrate pulse experiments were used to quantify qScrit in induction phase. The qScrit was found to be temperature and time dependent. Subsequently, qScrit was expressed through a linear equation, to serve as boundary for physiologically controlled experiments. Nevertheless, accumulation was observed within a physiologically controlled verification experiment, although the qScrit boundary was not exceeded. A second set of experiments was conducted, by oscillating the qS set point between discrete plateaus during physiologically controlled experiments. From the results, we deduced a significant interrelation between the metabolic activity and the timely decline of qScrit. This finding highlights the necessity of a comprehensive but laborious physiological characterization for each strain or alternatively, to use physio logical feedback control to facilitate real time monitoring of qScrit , in order to effectively avoid substrate accumulation.

Bioprocess development workflow: Transferable physiological knowledge instead of technological correlations.

Microbial bioprocesses need to be designed to be transferable from lab scale to production scale as well as between setups. Although substantial effort is invested to control technological parameters, usually the only true constant parameter is the actual producer of the product: the cell. Hence, instead of solely controlling technological process parameters, the focus should be increasingly laid on physiological parameters. This contribution aims at illustrating a workflow of data life cycle management with special focus on physiology. Information processing condenses the data into physiological variables, while information mining condenses the variables further into physiological descriptors. This basis facilitates data analysis for a physiological explanation for observed phenomena in productivity. Targeting transferability, we demonstrate this workflow using an industrially relevant Escherichia coli process for recombinant protein production and substantiate the following three points: (1) The postinduction phase is independent in terms of productivity and physiology from the preinduction variables specific growth rate and biomass at induction. (2) The specific substrate uptake rate during induction phase was found to significantly impact the maximum specific product titer. (3) The time point of maximum specific titer can be predicted by an easy accessible physiological variable: while the maximum specific titers were reached at different time points (19.8 ± 7.6 h), those maxima were reached all within a very narrow window of cumulatively consumed substrate dSn (3.1 ± 0.3 g/g). Concluding, this contribution provides a workflow on how to gain a physiological view on the process and illustrates potential benefits. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 33:261-270, 2017.

Bioprocess monitoring: minimizing sample matrix effects for total protein quantification with bicinchoninic acid assay.

Determining total protein content is a routine operation in many laboratories. Despite substantial work on assay optimization interferences, the widely used bicinchoninic acid (BCA) assay remains widely recognized for its robustness. Especially in the field of bioprocess engineering the inaccuracy caused by interfering substances remains hardly predictable and not well understood. Since the introduction of the assay, sample pre-treatment by trichloroacetic acid (TCA) precipitation has been indicated as necessary and sufficient to minimize interferences. However, the sample matrix in cultivation media is not only highly complex but also dynamically changing over process time in terms of qualitative and quantitative composition. A significant misestimation of the total protein concentration of bioprocess samples is often observed when following standard work-up schemes such as TCA precipitation, indicating that this step alone is not an adequate means to avoid measurement bias. Here, we propose a modification of the BCA assay, which is less influenced by sample complexity. The dynamically changing sample matrix composition of bioprocessing samples impairs the conventional approach of compensating for interfering substances via a static offset. Hence, we evaluated the use of a correction factor based on an internal spike measurement for the respective samples. Using protein spikes, the accuracy of the BCA protein quantification could be improved fivefold, taking the BCA protein quantification to a level of accuracy comparable to other, more expensive methods. This will allow reducing expensive iterations in bioprocess development to due inaccurate total protein analytics.

Nucleocytosolic depletion of the energy metabolite acetyl-coenzyme a stimulates autophagy and prolongs lifespan.

Healthy aging depends on removal of damaged cellular material that is in part mediated by autophagy. The nutritional status of cells affects both aging and autophagy through as-yet-elusive metabolic circuitries. Here, we show that nucleocytosolic acetyl-coenzyme A (AcCoA) production is a metabolic repressor of autophagy during aging in yeast. Blocking the mitochondrial route to AcCoA by deletion of the CoA-transferase ACH1 caused cytosolic accumulation of the AcCoA precursor acetate. This led to hyperactivation of nucleocytosolic AcCoA-synthetase Acs2p, triggering histone acetylation, repression of autophagy genes, and an age-dependent defect in autophagic flux, culminating in a reduced lifespan. Inhibition of nutrient signaling failed to restore, while simultaneous knockdown of ACS2 reinstated, autophagy and survival of ach1 mutant. Brain-specific knockdown of Drosophila AcCoA synthetase was sufficient to enhance autophagic protein clearance and prolong lifespan. Since AcCoA integrates various nutrition pathways, our findings may explain diet-dependent lifespan and autophagy regulation.