It is common practice in the development of bioprocesses to genetically modify a microorganism and study a large number of resulting mutants in order to select the ones that perform best for use at the industrial scale. At industrial scale, strict nutrient-controlled growth conditions are imposed to control the metabolic activity and growth rate of the microorganism, thereby enhancing the expression of the product of interest. Although it is known that microorganisms that perform best under these strictly controlled conditions are not the same as the ones that perform best under uncontrolled batch conditions, screening, and selection is predominantly performed under batch conditions. Tools that afford high throughput on the one hand and dynamic control over cultivation conditions on the other hand are not yet available. Microbioreactors offer the potential to address this problem, resolving the gap between bioprocess development and industrial scale use. In this review, we highlight the current state-of-the-art of microbioreactors that offer the potential to screen microorganisms under dynamically controlled conditions. We classify them into: (i) microtiter plate-based platforms, (ii) microfluidic chamber-based platforms, and (iii) microfluidic droplet-based platforms. We conclude this review by discussing the opportunities of nutrient-fed microbioreactors in the field of biotechnology.

In large scale fermentors the cultivated cells are exposed to dynamic changes in the nutrient concentrations due to imperfect mixing. Based on the characterization of these nutrient gradients in space and time, a rational scale down design can be obtained. This study focuses on the combined gradients of dissolved sugar and oxygen concentrations. Based on a recent computational fluid dynamics (CFD) study, firstly a scale-down design was developed. From intracellular metabolite measurements during these scale-down experiments, the metabolic behavior of the cells under highly dynamic conditions was revealed. Under the combined influence of oscillating glucose and oxygen concentrations, the penicillin production declined to 50 % of the value under steady state conditions. This decline was similar as observed during glucose oscillations alone. The influence of oxygen oscillations on the levels of the majority of the intracellular metabolites analyzed was negligible, although these metabolites were strongly affected by the varying oxygen levels under solely oxygen oscillations. Additionally, a metabolic structured kinetic model was developed and validated with data from glucose and oxygen oscillation experiments. This model can be coupled to CFD simulations to obtain an accurate prediction of the performance of industrial strains in space and time in large industrial scale bioreactors.

Product yield on carbohydrate feedstocks is a key performance indicator for industrial ethanol production with the yeast Saccharomyces cerevisiae. This paper reviews pathway engineering strategies for improving ethanol yield on glucose and/or sucrose in anaerobic cultures of this yeast by altering the ratio of ethanol production, yeast growth and glycerol formation. Particular attention is paid to strategies aimed at altering energy coupling of alcoholic fermentation and to strategies for altering redox-cofactor coupling in carbon and nitrogen metabolism that aim to reduce or eliminate the role of glycerol formation in anaerobic redox metabolism. In addition to providing an overview of scientific advances we discuss context dependency, theoretical impact and potential for industrial application of different proposed and developed strategies.

Understanding of thermal adaptation mechanisms in yeast is crucial to develop better-adapted strains to industrial processes, providing more economical and sustainable products. We have analyzed the transcriptomic responses of three Saccharomyces cerevisiae strains, a commercial wine strain, ADY5, a laboratory strain, CEN.PK113-7D and a commercial bioethanol strain, Ethanol Red, grown at non-optimal temperatures under anaerobic chemostat conditions. Transcriptomic analysis of the three strains revealed a huge complexity of cellular mechanisms and responses. Overall, cold exerted a stronger transcriptional response in the three strains comparing with heat conditions, with a higher number of down-regulating genes than of up-regulating genes regardless the strain analyzed. The comparison of the transcriptome at both sub- and supra-optimal temperatures showed the presence of common genes up- or down-regulated in both conditions, but also the presence of common genes up- or down-regulated in the three studied strains. More specifically, we have identified and validated three up-regulated genes at sub-optimal temperature in the three strains, OPI3, EFM6 and YOL014W. Finally, the comparison of the transcriptomic data with a previous proteomic study with the same strains revealed a good correlation between gene activity and protein abundance, mainly at low temperature. Our work provides a global insight into the specific mechanisms involved in temperature adaptation regarding both transcriptome and proteome, which can be a step forward in the comprehension and improvement of yeast thermotolerance.

Obtaining meaningful snapshots of the metabolome of microorganisms requires rapid sampling and immediate quenching of all metabolic activity, to prevent any changes in metabolite levels after sampling. Furthermore, a suitable extraction method is required ensuring complete extraction of metabolites from the cells and inactivation of enzymatic activity, with minimal degradation of labile compounds. Finally, a sensitive, high-throughput analysis platform is needed to quantify a large number of metabolites in a small amount of sample. An issue which has often been overlooked in microbial metabolomics is the fact that many intracellular metabolites are also present in significant amounts outside the cells and may interfere with the quantification of the endo metabolome. Attempts to remove the extracellular metabolites with dedicated quenching methods often induce release of intracellular metabolites into the quenching solution. For eukaryotic microorganisms, this release can be minimized by adaptation of the quenching method. For prokaryotic cells, this has not yet been accomplished, so the application of a differential method whereby metabolites are measured in the culture supernatant as well as in total broth samples, to calculate the intracellular levels by subtraction, seems to be the most suitable approach. Here we present an overview of different sampling, quenching, and extraction methods developed for microbial metabolomics, described in the literature. Detailed protocols are provided for rapid sampling, quenching, and extraction, for measurement of metabolites in total broth samples, washed cell samples, and supernatant, to be applied for quantitative metabolomics of both eukaryotic and prokaryotic microorganisms.

In large-scale bioreactors, there is often insufficient mixing and as a consequence, cells experience uneven substrate and oxygen levels that influence product formation. In this study, the influence of dissolved oxygen (DO) gradients on the primary and secondary metabolism of a high producing industrial strain of Penicillium chrysogenum was investigated. Within a wide range of DO concentrations, obtained under chemostat conditions, we observed different responses from P. chrysogenum: (i) no influence on growth or penicillin production (>0.025 mmol L⁻¹); (ii) reduced penicillin production, but no growth limitation (0.013–0.025 mmol L⁻¹); and (iii) growth and penicillin production limitations (<0.013 mmol L⁻¹). In addition, scale down experiments were performed by oscillating the DO concentration in the bioreactor. We found that during DO oscillation, the penicillin production rate decreased below the value observed when a constant DO equal to the average oscillating DO value was used. To understand and predict the influence of oxygen levels on primary metabolism and penicillin production, we developed a black box model that was linked to a detailed kinetic model of the penicillin pathway. The model simulations represented the experimental data during the step experiments; however, during the oscillation experiments the predictions deviated, indicating the involvement of the central metabolism in penicillin production.

Carbon limitation is a common feeding strategy in bioprocesses to enable an efficient microbiological conversion of a substrate to a product. However, industrial settings inherently promote mixing insufficiencies, creating zones of famine conditions. Cells frequently traveling through such regions repeatedly experience substrate shortages and respond individually but often with a deteriorated production performance. A priori knowledge of the expected strain performance would enable targeted strain, process, and bioreactor engineering for minimizing performance loss. Today, computational fluid dynamics (CFD) coupled to data-driven kinetic models are a promising route for the in silico investigation of the impact of the dynamic environment in the large-scale bioreactor on microbial performance. However, profound wet-lab datasets are needed to cover relevant perturbations on realistic time scales. As a pioneering study, we quantified intracellular metabolome dynamics of Saccharomyces cerevisiae following an industrially relevant famine perturbation. Stimulus-response experiments were operated as chemostats with an intermittent feed and high-frequency sampling. Our results reveal that even mild glucose gradients in the range of 100 µmol·L⁻¹ impose significant perturbations in adapted and non-adapted yeast cells, altering energy and redox homeostasis. Apparently, yeast sacrifices catabolic reduction charges for the sake of anabolic persistence under acute carbon starvation conditions. After repeated exposure to famine conditions, adapted cells show 2.7% increased maintenance demands.

This study explores the relation between biomass-specific succinic acid (SA) production rate and specific growth rate of an engineered industrial strain of Saccharomyces cerevisiae, with the aim to investigate the extent to which growth and product formation can be uncoupled. Ammonium-limited aerobic chemostat and retentostat cultures were grown at different specific growth rates under industrially relevant conditions, that is, at a culture pH of 3 and with sparging of a 1:1 CO₂–air mixture. Biomass-specific SA production rates decreased asymptotically with decreasing growth rate. At near-zero growth rates, the engineered strain maintained a stable biomass-specific SA production rate for over 500 h, with a SA yield on glucose of 0.61 mol mol⁻¹. These results demonstrate that uncoupling of growth and SA production could indeed be achieved. A linear relation between the biomass-specific SA production rate and glucose consumption rate indicated the coupling of SA production rate and the flux through primary metabolism. The low culture pH resulted in an increased death rate, which was lowest at near-zero growth rates. Nevertheless, a significant amount of non-viable biomass accumulated in the retentostat cultures, thus underlining the importance of improving low-pH tolerance in further strain development for industrial SA production with S. cerevisiae.

A key bottleneck in bioprocess development is that state-of-the-art tools used for screening of cells and optimization of cultivation conditions do not represent the conditions enforced at industrial scale. At industrial scale, cell growth is strictly controlled (“fed-batch”) to optimize the metabolites produced by the cells. In contrast, cell growth is uncontrolled (“batch”) in microwells commonly used for bioprocess development due to the difficulty to continuously supply minute amounts of nutrients to the cells in these wells over the course of the cultivation experiment. This work addresses this bottleneck through the development of a droplet-based fed-batch nanobioreactor. A key challenge addressed in this work is the implementation of the required non-steady droplet operations on chip to establish a semi-continuous nutrient supply, while keeping the chip and its operation as simple as possible. The ability to study micro-organisms under nutrient-controlled fed-batch conditions is demonstrated using the yeast Cyberlindnera (Pichia) jadinii, with the cell growth rate controlled through the glucose concentration. Given the relative ease of operation and the potential to extend its features, the presented nanobioreactor provides a solid platform technology for further development and use in the field of bioprocess development and beyond.

Co-fermentation of mixed sugars to produce butanol is an attractive route in sucrochemical production chains. Herein, high-level mixed sugars from sugarcane bagasse hemicellulosic hydrolysate (HH) and molasses (SCM) were investigated as potential substrates for acetone-butanol-ethanol (ABE) production in batch fermentation by Clostridium saccharoperbutylacetonicum DSM 14923. HH produced after hydrothermal pretreatment was concentrated 5-fold and was called concentrated hemicellulosic hydrolysate (CHH). The fermentation media that were investigated consisted solely of CHH and SCM and three CHH-to-SCM ratios were used to provide 30 g/L initial sugar concentrations and furan derivatives lower than 0.1 g/L. For CHH50/SCM50 and CHH75/SCM25, diluting CHH to concentrations of 15 g/L sugars and 22.5 g/L sugars, respectively, which were supplemented with SCM and nutrients, suffered growth inhibition as a function of the concentration of undissociated acid in the medium. The best-performing medium, CHH25/SCM75 (7.5 g/L and 22.5 g/L sugars from CHH and SCM, respectively and about 0.017 g/L furan derivatives), showed 97 % sugar consumption, and in the pH range of 5.5–6.5, undissociated acetic acid was not an inhibitory molecular form to C. saccharoperbutylacetonicum. After 30 h of fermentation, 7.8 and 9.8 g/L butanol and ABE were produced, respectively, which yielded 0.28 and 0.36 g/g. Based on our findings, C. saccharoperbutylacetonicum exhibits its potential and effective application for renewable butanol production by co-fermenting mixed sugars.

Intracellular metabolites were evaluated during the continuous growth of Trichoderma harzianum P49P11 under carbon-limited conditions. Four different conditions in duplicate were investigated (10 and 20 g/L of glucose, 5.26/5.26 g/L of fructose/glucose and 10 g/L of sucrose in the feed). Differences in the values of some specific concentrations of intracellular metabolites were observed at steady-state for the duplicates. The presence of extracellular polysaccharide was confirmed in the supernatant of all conditions based on FT-IR and proton NMR. Fragments of polysaccharides from the cell wall could be released due to the shear stress and since the cells can consume them under carbon-limited conditions, this could create an unpredictable carbon flow rate into the cells. According to the values of the metabolite concentrations, it was considered that the consumption of those fragments was interfering with the analysis.

The wild type strain Trichoderma harzianum was able to synthesize enzymes that can catalyse the hydrolysis of p-nitrophenyl-β-D-glucopyranoside (PNPGase) in glucose-limited chemostat cultures. Fructose/glucose and sucrose conditions provided low levels of PNPGase activity. To investigate whether under these conditions other enzymes were produced, a shotgun proteomics analysis of their supernatants was performed. The analysis has indicated that the different carbon sources used influenced the amounts of proteins secreted including 1,3-beta-glucanosyltransferase, alpha-1,2-mannosidase, alpha-galactosidase and glucan 1,3-beta-glucosidase. The analysis has also suggested the presence of beta-glucosidase, which could also be represented by PNPGase activity. Intracellular metabolites were quantified during PNPGase production for the condition using 20 g/L of glucose in the feed and differences were observed, indicating that intracellular glucose could be inhibiting PNPGase production. Significance: This work shows that sugars such as glucose, fructose/glucose and sucrose can be used as substrates for the continuous synthesis of different enzymes under carbon-limited conditions by Trichoderma harzianum. As far as we know, this is the first work about the continuous synthesis of enzymes under carbon-limited conditions suggesting that different easily assimilated carbon sources can be used to generate different enzymatic cocktails. Each enzyme or uncharacterized protein suggested by shotgun proteomics has the potential to become a promising product for biotechnological applications.

Carbon-limited chemostat cultures were performed using different carbon sources (glucose, 10 and 20 g/L; sucrose, 10 g/L; fructose/glucose, 5.26/5.26 g/L; carboxymethyl cellulose, 10 g/L; and carboxymethyl cellulose/glucose, 5/5 g/L) to verify the capability of the wild type strain Trichoderma harzianum to produce extracellular enzymes. All chemostat cultures were carried out at a fixed dilution rate of 0.05 h⁻¹. Experiments using glucose, fructose/glucose and sucrose were performed in duplicate. Glucose condition was found to induce the production of enzymes that can catalyse the hydrolysis of p-nitrophenyl-β-D-glucopyranoside (PNPGase). A concentration of 20 g/L of glucose in the feed provided the highest productivity (1048 ± 16 U/mol h). Extracellular polysaccharides were considered the source of inducers. Based on the obtained results, a new PNPGase production process was developed using mainly glucose. This process raises interesting possibilities of synthesizing the inducer substrate and the induced enzymes in a single step using an easily assimilated carbon source under carbon-limited conditions.

Redox metabolism plays an essential role in the central metabolic network of all living cells, connecting, but at the same time separating, catabolic and anabolic pathways. Redox metabolism is inherently linked to the excretion of overflow metabolites. Overflow metabolism allows for higher substrate uptake rates, potentially outcompeting other microorganisms for the same substrate. Within dynamically changing environments, overflow metabolism can act as storage mechanism, as is shown in many recently described processes. However, for complete understanding of these mechanisms, the intracellular state of the metabolism must be elucidated. In recent years, progress has been made in the field of metabolomics to improve the accuracy and precision of measurements of intracellular and intercompartmental metabolites. This article highlights several of these recent advances, with focus on redox cofactor measurements, both fluorescence and mass spectrometry based.

Cellulase production can be divided into two steps: growth stage; followed by an induction stage. To develop a mathematical model for the optimization of this strategy, two sets of experiments were performed in batch mode for parameter estimation. One set of experiments was performed to evaluate the influence of glycerol regarding cell growth (initial concentrations of 5, 10, 15 and 20 g/L). The other set of experiments considered the induction stage using cellulose as the substrate (initial concentrations of 5, 10, 20, 30 and 40 g/L). Two feeding strategies were simulated to maximize cellulase production using glycerol to maintain a high cell concentration. The first simulation used a discrete feed and the second used a continuous feed of cellulose. The mathematical model proposed allows maintaining a high cell concentration and the addition of optimal small amounts of the inducer substrate to prevent inhibition of enzyme production.

A phenotypic screening of 12 industrial yeast strains and the well-studied laboratory strain CEN.PK113-7D at cultivation temperatures between 12 °C and 40 °C revealed significant differences in maximum growth rates and temperature tolerance. From those 12, two strains, one performing best at 12 °C and the other at 40 °C, plus the laboratory strain, were selected for further physiological characterization in well-controlled bioreactors. The strains were grown in anaerobic chemostats, at a fixed specific growth rate of 0.03 h⁻¹ and sequential batch cultures at 12 °C, 30 °C, and 39 °C. We observed significant differences in biomass and ethanol yields on glucose, biomass protein and storage carbohydrate contents, and biomass yields on ATP between strains and cultivation temperatures. Increased temperature tolerance coincided with higher energetic efficiency of cell growth, indicating that temperature intolerance is a result of energy wasting processes, such as increased turnover of cellular components (e.g. proteins) due to temperature induced damage.

We developed a microfluidic droplet on-demand (DoD) generator that enables the production of droplets with a volume solely governed by the geometry of the generator for a range of operating conditions. The prime reason to develop this novel type of DoD generator is that its robustness in operation enables scale out and operation under non-steady conditions, which are both essential features for the further advancement of droplet-based assays. We first detail the working principle of the DoD generator and study the sensitivity of the volume of the generated droplets with respect to the used fluids and control parameters. We next compare the performance of our DoD generator when scaled out to 8 parallel generators to the performance of a conventional DoD generator in which the droplet volume is not geometry-controlled, showing its superior performance. Further scale out to 64 parallel DoD generators shows that all generators produce droplets with a volume between 91% and 105% of the predesigned volume. We conclude the paper by presenting a simple droplet-based assay in which the DoD generator enables sequential supply of reagent droplets to a droplet stored in the device, illustrating its potential to be used in droplet-based assays for biochemical studies under non-steady operation conditions.

Elucidation of temperature tolerance mechanisms in yeast is essential for enhancing cellular robustness of strains, providing more economically and sustainable processes. We investigated the differential responses of three distinct Saccharomyces cerevisiae strains, an industrial wine strain, ADY5, a laboratory strain, CEN.PK113-7D and an industrial bioethanol strain, Ethanol Red, grown at sub- and supra-optimal temperatures under chemostat conditions. We employed anaerobic conditions, mimicking the industrial processes. The proteomic profile of these strains in all conditions was performed by sequential window acquisition of all theoretical spectra-mass spectrometry (SWATH-MS), allowing the quantification of 997 proteins, data available via ProteomeXchange (PXD016567). Our analysis demonstrated that temperature responses differ between the strains; however, we also found some common responsive proteins, revealing that the response to temperature involves general stress and specific mechanisms. Overall, sub-optimal temperature conditions involved a higher remodeling of the proteome. The proteomic data evidenced that the cold response involves strong repression of translation-related proteins as well as induction of amino acid metabolism, together with components related to protein folding and degradation while, the high temperature response mainly recruits amino acid metabolism. Our study provides a global and thorough insight into how growth temperature affects the yeast proteome, which can be a step forward in the comprehension and improvement of yeast thermotolerance.

Targeted, quantitative metabolomics can, in principle, provide precise information on intracellular metabolite levels, which can be applied to accurate modeling of intracellular processes required in systems biology and metabolic engineering. However, quantitative metabolite profiling is often hampered by biased mass spectrometry-based analyses caused by matrix effects, the degradation of metabolites and metabolite leakage during sample preparation, and unexpected variation in instrument responses. Isotope Dilution Mass Spectrometry (IDMS) has been proven as the most accurate method for high-throughput detection of intracellular metabolite concentrations, and the key has been the acquisition of the corresponding fully uniformly (U) - ¹³ C-labeled metabolites to be measured. Here, we have prepared U- ¹³ C-labeled cell extracts by cultivating P. chrysogenum in a fed-batch fermentation with fully U- ¹³ C-labeled substrates. Towards this goal, a dynamic fed-batch model describing P. chrysogenum growth and penicillin production was used to simulate the fermentation process and design the fed-batch fermentation media. Further, a case study with extensive intracellular metabolomics data from glucose-limited cultivation of Penicillium chrysogenum under both single and repetitive glucose pulses was illustrated by using the IDMS methods with the prepared U- ¹³ C-labeled cell extracts as internal standards. In conclusion, the IDMS method can be incorporated into well-established fast sampling and quenching protocols to obtain dynamic quantitative in vivo metabolome data at the timescales of (tens of) seconds and elucidate the underlying regulatory architecture. The case study revealed gross differences between single and repeated pulses, which suggests that single pulse studies have limited value for understanding of metabolic responses in large-scale bioreactors. Instead, intermittent feeding should be favored.