In a 54 m³ large-scale penicillin fermentor, the cells experience substrate gradient cycles at the timescales of global mixing time about 20–40 s. Here, we used an intermittent feeding regime (IFR) and a two-compartment reactor (TCR) to mimic these substrate gradients at laboratory-scale continuous cultures. The IFR was applied to simulate substrate dynamics experienced by the cells at full scale at timescales of tens of seconds to minutes (30 s, 3 min and 6 min), while the TCR was designed to simulate substrate gradients at an applied mean residence time ((Formula presented.)) of 6 min. A biological systems analysis of the response of an industrial high-yielding P. chrysogenum strain has been performed in these continuous cultures. Compared to an undisturbed continuous feeding regime in a single reactor, the penicillin productivity (q_PenG) was reduced in all scale-down simulators. The dynamic metabolomics data indicated that in the IFRs, the cells accumulated high levels of the central metabolites during the feast phase to actively cope with external substrate deprivation during the famine phase. In contrast, in the TCR system, the storage pool (e.g. mannitol and arabitol) constituted a large contribution of carbon supply in the non-feed compartment. Further, transcript analysis revealed that all scale-down simulators gave different expression levels of the glucose/hexose transporter genes and the penicillin gene clusters. The results showed that q_PenG did not correlate well with exposure to the substrate regimes (excess, limitation and starvation), but there was a clear inverse relation between q_PenG and the intracellular glucose level.

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In the present work, by performing chemostat experiments at 400 and 600 RPM, two typical power inputs representative of industrial penicillin fermentation (P/V, 1.00 kW/m³ in more remote zones and 3.83 kW/m³ in the vicinity of the impellers, respectively) were scaled-down to bench-scale bioreactors. It was found that at 400 RPM applied in prolonged glucose-limited chemostat cultures, the previously reported degeneration of penicillin production using an industrial Penicillium chrysogenum strain was virtually absent. To investigate this, the cellular response was studied at flux (stoichiometry), residual glucose, intracellular metabolite and transcript levels. At 600 RPM, 20% more cell lysis was observed and the increased degeneration of penicillin production was accompanied by a 22% larger ATP gap and an unexpected 20-fold decrease in the residual glucose concentration (C_s,out). At the same time, the biomass specific glucose consumption rate (q_s) did not change but the intracellular glucose concentration was about sixfold higher, which indicates a change to a higher affinity glucose transporter at 600 RPM. In addition, power input differences cause differences in the diffusion rates of glucose and the calculated Batchelor diffusion length scale suggests the presence of a glucose diffusion layer at the glucose transporting parts of the hyphae, which was further substantiated by a simple proposed glucose diffusion-uptake model. By analysis of calculated mass action ratios (MARs) and energy consumption, it indicated that at 600 RPM glucose sensing and signal transduction in response to the low C_s,out appear to trigger a gluconeogenic type of metabolic flux rearrangement, a futile cycle through the pentose phosphate pathway (PPP) and a declining redox state of the cytosol. In support of the change in glucose transport and degeneration of penicillin production at 600 RPM, the transcript levels of the putative high-affinity glucose/hexose transporter genes Pc12g02880 and Pc06g01340 increased 3.5- and 3.3-fold, respectively, and those of the pcbC gene encoding isopenicillin N-synthetase (IPNS) were more than twofold lower in the time range of 100–200 hr of the chemostat cultures. Summarizing, changes at power input have unexpected effects on degeneration and glucose transport, and result in significant metabolic rearrangements. These findings are relevant for the industrial production of penicillin, and other fermentations with filamentous microorganisms.

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We assess the effect of substrate heterogeneity on the metabolic response of P. chrysogenum in industrial bioreactors via the coupling of a 9-pool metabolic model with Euler-Lagrange CFD simulations. In this work, we outline how this coupled hydrodynamic-metabolic modeling can be utilized in 5 steps. (1) A model response study with a fixed spatial extra-cellular glucose concentration gradient, which reveals a drop in penicillin production rate q_p of 18–50% for the simulated reactor, depending on model setup. (2) CFD-based scale-down design, where we design a 1-vessel scale down simulator based on the organism lifelines. (3) Scale-down verification, numerically comparing the model response in the proposed scale-down simulator with large-scale CFD response. (4) Reactor design optimization, reducing the drop in penicillin production by a change of feed location. (5) Long-term fed-batch simulation, where we verify model predictions against experimental data, and discuss population heterogeneity. Overall, these steps present a coupled hydrodynamic-metabolic approach towards bioreactor evaluation, scale-down and optimization.

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The objective of this research study is to be able to scale-up and optimize aerobic fermentation processes via computer simulations. As an example the production of penicillin by P. chrysogenum is studied. In vivo kinetics of the cell can be understood by conducting stimulus response and scale down experiments. These experiments provide dynamic information that can be used to estimate parameters of enzyme kinetic models. The transport phenomena inside the bioreactor can by understood by solving hydrodynamic model using computational fluid dynamics (CFD). Thus, with information from intracellular and extracellular environments, an integrated model is solved using CFD. In these simulations, the multiphase flow and transport phenomena taking place inside the bioreactor are simulated, and integrated with the microbial reaction kinetics. The micro-organisms inside the reactor are followed along their trajectories, where they experience a changing environment. The dynamic response of the cells to this environment dictates the productivity and selectivity of the cells. By simulating both the flow in the reactor and the response of the cells, the entire process inside the bioreactor can be assessed and scaled-up and optimization can be done without the need of costly experiments, both in time and financial resources.@en

δ-[L-α-Aminoadipyl]-L-cysteinyl-D-valine (ACV) is a key intermediate in the biosynthesis pathway of penicillins and cephalosporins. Therefore, the accurate quantification of ACV is relevant, e.g. for kinetic studies on the production of these β-lactam antibiotics. However, accurate quantification of ACV is a challenge, because it is an active thiol compound which, upon exposure to air, can easily react with other thiol compounds to form oxidized disulfides. We have found that, during exposure to air, the oxidation of ACV occurs both in aqueous standard solutions as well as in biological samples. Qualitative and quantitative determinations of ACV and the oxidized dimer bis-δ-[L-α-aminoadipyl]-L-cysteinyl-D-valine have been carried out using ion pair reversed-phase ultra high-performance liquid chromatography, hyphenated with tandem mass spectrometry (IP-RP-UPLC-MS/MS) as the analytical platform. We show that by application of tris(2-carboxy-ethyl)phosphine hydrochloride (TCEP) as the reducing reagent, the total amount of ACV can be determined, while using maleimide as derivatizing reagent enables to quantify the free reduced form only.

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