Valorization of Wheat Bran by Co-Cultivation of Fungi with Integrated Hydrolysis to Provide Sugars and Animal Feed.

The enzymatic hydrolysis of agricultural residues like wheat bran enables the valorization of otherwise unused carbon sources for biotechnological processes. The co-culture of Aspergillus niger and Trichoderma reesei with wheat bran particles as substrate produces an enzyme set consisting of xylanases, amylases, and cellulases that is suitable to degrade lignocellulosic biomass to sugar monomers (D-glucose, D-xylose, and L-arabinose). An integrated one-pot process for enzyme production followed by hydrolysis in stirred tank bioreactors resulted in hydrolysates with overall sugar concentrations of 32.3 g L-1 and 24.4 g L-1 at a 25 L and a 1000 L scale, respectively, within 86 h. Furthermore, the residual solid biomass consisting of fermented wheat bran with protein-rich fungal mycelium displays improved nutritional properties for usage as animal feed due to its increased content of sugars, protein, and fat.

Spectroscopic insights into multi-phase protein crystallization in complex lysate using Raman spectroscopy and a particle-free bypass.

Protein crystallization as opposed to well-established chromatography processes has the benefits to reduce production costs while reaching a comparable high purity. However, monitoring crystallization processes remains a challenge as the produced crystals may interfere with analytical measurements. Especially for capturing proteins from complex feedstock containing various impurities, establishing reliable process analytical technology (PAT) to monitor protein crystallization processes can be complicated. In heterogeneous mixtures, important product characteristics can be found by multivariate analysis and chemometrics, thus contributing to the development of a thorough process understanding. In this project, an analytical set-up is established combining offline analytics, on-line ultraviolet visible light (UV/Vis) spectroscopy, and in-line Raman spectroscopy to monitor a stirred-batch crystallization process with multiple phases and species being present. As an example process, the enzyme Lactobacillus kefir alcohol dehydrogenase (LkADH) was crystallized from clarified Escherichia coli (E. coli) lysate on a 300 mL scale in five distinct experiments, with the experimental conditions changing in terms of the initial lysate solution preparation method and precipitant concentration. Since UV/Vis spectroscopy is sensitive to particles, a cross-flow filtration (cross-flow filtration)-based bypass enabled the on-line analysis of the liquid phase providing information on the lysate composition regarding the nucleic acid to protein ratio. A principal component analysis (PCA) of in situ Raman spectra supported the identification of spectra and wavenumber ranges associated with productspecific information and revealed that the experiments followed a comparable, spectral trend when crystals were present. Based on preprocessed Raman spectra, a partial least squares (PLS) regression model was optimized to monitor the target molecule concentration in real-time. The off-line sample analysis provided information on the crystal number and crystal geometry by automated image analysis as well as the concentration of LkADH and host cell proteins (HCPs) In spite of a complex lysate suspension containing scattering crystals and various impurities, it was possible to monitor the target molecule concentration in a heterogeneous, multi-phase process using spectroscopic methods. With the presented analytical set-up of off-line, particle-sensitive on-line, and in-line analyzers, a crystallization capture process can be characterized better in terms of the geometry, yield, and purity of the crystals.

3D bioprinting of microorganisms: principles and applications.

In recent years, the ability to create intricate, live tissues and organs has been made possible thanks to three-dimensional (3D) bioprinting. Although tissue engineering has received a lot of attention, there is growing interest in the use of 3D bioprinting for microorganisms. Microorganisms like bacteria, fungi, and algae, are essential to many industrial bioprocesses, such as bioremediation as well as the manufacture of chemicals, biomaterials, and pharmaceuticals. This review covers current developments in 3D bioprinting methods for microorganisms. We go over the bioink compositions designed to promote microbial viability and growth, taking into account factors like nutrient delivery, oxygen supply, and waste elimination. Additionally, we investigate the most important bioprinting techniques, including extrusion-based, inkjet, and laser-assisted approaches, as well as their suitability with various kinds of microorganisms. We also investigate the possible applications of 3D bioprinted microbes. These range from constructing synthetic microbial consortia for improved metabolic pathway combinations to designing spatially patterned microbial communities for enhanced bioremediation and bioprocessing. We also look at the potential for 3D bioprinting to advance microbial research, including the creation of defined microenvironments to observe microbial behavior. In conclusion, the 3D bioprinting of microorganisms marks a paradigm leap in microbial bioprocess engineering and has the potential to transform many application areas. The ability to design the spatial arrangement of various microorganisms in functional structures offers unprecedented possibilities and ultimately will drive innovation.

Challenges and Advances in the Bioproduction of L-Cysteine.

L-cysteine is a proteogenic amino acid with many applications in the pharmaceutical, food, animal feed, and cosmetic industries. Due to safety and environmental issues in extracting L-cysteine from animal hair and feathers, the fermentative production of L-cysteine offers an attractive alternative using renewable feedstocks. Strategies to improve microbial production hosts like Pantoea ananatis, Corynebacterium glutamicum, Pseudomonas sp., and Escherichia coli are summarized. Concerning the metabolic engineering strategies, the overexpression of feedback inhibition-insensitive L-serine O-acetyltransferase and weakening the degradation of L-cysteine through the removal of L-cysteine desulfhydrases are crucial adjustments. The overexpression of L-cysteine exporters is vital to overcome the toxicity caused by intracellular accumulating L-cysteine. In addition, we compiled the process engineering aspects for the bioproduction of L-cysteine. Utilizing the energy-efficient sulfur assimilation pathway via thiosulfate, fermenting cheap carbon sources, designing scalable, fed-batch processes with individual feedings of carbon and sulfur sources, and implementing efficient purification techniques are essential for the fermentative production of L-cysteine on an industrial scale.

Metabolic control analysis enabled the improvement of the L-cysteine production process with Escherichia coli.

L-cysteine is an amino acid with relevance to the pharmaceutical, food, feed, and cosmetic industry. The environmental and societal impact of its chemical production has led to the development of more sustainable fermentative L-cysteine production processes with engineered E. coli based on glucose and thiosulfate as sulphur source. Still, most of the published processes show low yields. For the identification of further metabolic engineering targets, engineered E. coli cells were withdrawn from a fed-batch production process, followed by in vivo metabolic control analysis (MCA) based on the data of short-term perturbation experiments, metabolomics (LC-MS), and thermodynamic flux analysis (TFA). In vivo MCA indicated that the activities of the L-cysteine synthases of the cells withdrawn from the production process might be limiting, and we hypothesised that the L-cysteine precursor O-acetylserine (OAS) might be exported from the cells faster than it took to transform OAS into L-cysteine. By increasing the expression of the L-cysteine synthases, either sulfocysteine synthase or L-cysteine synthase, which transform OAS into L-cysteine, an improvement of up to 70% in specific L-cysteine productivity and up to 47% in the final L-cysteine concentration was achieved in standardised fed-batch processes thereby increasing the yield on glucose by more than 85 to 9.2% (w/w). KEY POINTS: • Metabolic control analysis was applied to analyse L-cysteine production with E. coli • OAS export was faster than its transformation to L-cysteine • Overexpression of L-cysteine synthases improved L-cysteine productivity and yield.

Impact of mixing insufficiencies on L-phenylalanine production with an Escherichia coli reporter strain in a novel two-compartment bioreactor.

BACKGROUND: The omnipresence of population heterogeneity in industrial bioprocesses originates from prevailing dynamic bioprocess conditions, which promote differences in the expression of cellular characteristics. Despite the awareness, the concrete consequences of this phenomenon remain poorly understood. RESULTS: Therefore, for the first time, a L-phenylalanine overproducing Escherichia coli quadruple reporter strain was established for monitoring of general stress response, growth behavior, oxygen limitation and product formation of single cells based on mTagBFP2, mEmerald, CyOFP1, and mCardinal2 expression measured by flow cytometry. This strain was applied for the fed-batch production of L-phenylalanine from glycerol and ammonia in a stirred-tank bioreactor at homogeneous conditions compared to the same process in a novel two-compartment bioreactor. This two-compartment bioreactor consists of a stirred-tank bioreactor with an initial volume of 0.9 L (homogeneous zone) with a coiled flow inverter with a fixed working volume of 0.45 L as a bypass (limitation zone) operated at a mean hydraulic residence time of 102 s. The product formation was similar in both bioreactor setups with maximum L-phenylalanine concentrations of 21.1 ± 0.6 g L-1 demonstrating the consistency of this study's microbial L-phenylalanine production. However, cell growth was vulnerable to repetitive exposure to the dynamically changing conditions in the two-compartment bioreactor with maximum biomass yields reduced by 21%. The functionality of reporter molecules was approved in the stirred-tank bioreactor cultivation, in which expressed fluorescence levels of all four markers were in accordance with respective process state variables. Additional evaluation of the distributions on single-cell level revealed the presence of population heterogeneity in both bioprocesses. Especially for the marker of the general stress response and the product formation, the corresponding histograms were characterized by bimodal shapes and broad distributions. These phenomena were pronounced particularly at the beginning and the end of the fed-batch process. CONCLUSIONS: The here shown findings confirm multiple reporter strains to be a noninvasive tool for monitoring cellular characteristics and identifying potential subpopulations in bioprocesses. In combination with experiments in scale-down setups, these can be utilized for a better physiological understanding of bioprocesses and support future scale-up procedures.

Continuous Production of Ethanol, 1-Butanol and 1-Hexanol from CO with a Synthetic Co-Culture of Clostridia Applying a Cascade of Stirred-Tank Bioreactors.

Syngas fermentation with clostridial co-cultures is promising for the conversion of CO to alcohols. A CO sensitivity study with Clostridium kluyveri monocultures in batch operated stirred-tank bioreactors revealed total growth inhibition of C. kluyveri already at 100 mbar CO, but stable biomass concentrations and ongoing chain elongation at 800 mbar CO. On/off-gassing with CO indicated a reversible inhibition of C. kluyveri. A continuous supply of sulfide led to increased autotrophic growth and ethanol formation by Clostridium carboxidivorans even at unfavorable low CO concentrations. Based on these results, a continuously operated cascade of two stirred-tank reactors was established with a synthetic co-culture of both Clostridia. An amount of 100 mbar CO and additional sulfide supply enabled growth and chain elongation in the first bioreactor, whereas 800 mbar CO resulted in an efficient reduction of organic acids and de-novo synthesis of C2-C6 alcohols in the second reactor. High alcohol/acid ratios of 4.5-9.1 (w/w) were achieved in the steady state of the cascade process, and the space-time yields of the alcohols produced were improved by factors of 1.9-5.3 compared to a batch process. Further improvement of continuous production of medium chain alcohols from CO may be possible by applying less CO-sensitive chain-elongating bacteria in co-cultures.

Bioproduction and applications of aldobionic acids with a focus on maltobionic and cellobionic acid.

Aldobionic acids are sugar acids which consist of a disaccharide with an anomeric acid group. The most famous is lactobionic acid (LBA). LBA is used in many applications such as food and beverages, pharmaceuticals and medicine, cosmetics or chemical processes. During the last decade, all these industries are observing a shift of consumer preferences towards plant-based options. Thus, the biotechnological industry is trying to replace the animal-derived LBA. Maltobionic acid (MBA) and cellobionic acid (CBA) are two stereoisomers of LBA which have emerged as vegan alternatives. However, MBA and CBA face different obstacles related to their industrial production. While traditionally used electrochemical or chemical catalysis often rely on cost intensive and/or hazardous catalysts, novel production methods with microorganisms are still poorly studied. In the first part, this paper discusses both alternatives in terms of their characteristics and applications. In the second part, it reviews the long-studied chemical production and the novel bioproduction methods, which are based on enzymatic and microbial systems. This review concludes with a discussion of future work needed to bring their production to the industrial scale.

Accelerated Adaptive Laboratory Evolution by Automated Repeated Batch Processes in Parallelized Bioreactors.

Adaptive laboratory evolution (ALE) is a valuable complementary tool for modern strain development. Insights from ALE experiments enable the improvement of microbial cell factories regarding the growth rate and substrate utilization, among others. Most ALE experiments are conducted by serial passaging, a method that involves large amounts of repetitive manual labor and comes with inherent experimental design flaws. The acquisition of meaningful and reliable process data is a burdensome task and is often undervalued and neglected, but also unfeasible in shake flask experiments due to technical limitations. Some of these limitations are alleviated by emerging automated ALE methods on the µL and mL scale. A novel approach to conducting ALE experiments is described that is faster and more efficient than previously used methods. The conventional shake flask approach was translated to a parallelized, L scale stirred-tank bioreactor system that runs controlled, automated, repeated batch processes. The method was validated with a growth optimization experiment of E. coli K-12 MG1655 grown with glycerol minimal media as a benchmark. Off-gas analysis enables the continuous estimation of the biomass concentration and growth rate using a black-box model based on first principles (soft sensor). The proposed method led to the same stable growth rates of E. coli with the non-native carbon source glycerol 9.4 times faster than the traditional manual approach with serial passaging in uncontrolled shake flasks and 3.6 times faster than an automated approach on the mL scale. Furthermore, it is shown that the cumulative number of cell divisions (CCD) alone is not a suitable timescale for measuring and comparing evolutionary progress.

Novel synthetic co-culture of Acetobacterium woodii and Clostridium drakei using CO2 and in situ generated H2 for the production of caproic acid via lactic acid.

Acetobacterium woodii is known to produce mainly acetate from CO2 and H2, but the production of higher value chemicals is desired for the bioeconomy. Using chain-elongating bacteria, synthetic co-cultures have the potential to produce longer-chained products such as caproic acid. In this study, we present first results for a successful autotrophic co-cultivation of A. woodii mutants and a Clostridium drakei wild-type strain in a stirred-tank bioreactor for the production of caproic acid from CO2 and H2 via the intermediate lactic acid. For autotrophic lactate production, a recombinant A. woodii strain with a deleted Lct-dehydrogenase complex, which is encoded by the lctBCD genes, and an inserted D-lactate dehydrogenase (LdhD) originating from Leuconostoc mesenteroides, was used. Hydrogen for the process was supplied using an All-in-One electrode for in situ water electrolysis. Lactate concentrations as high as 0.5 g L-1 were achieved with the AiO-electrode, whereas 8.1 g L-1 lactate were produced with direct H2 sparging in a stirred-tank bioreactor. Hydrogen limitation was identified in the AiO process. However, with cathode surface area enlargement or numbering-up of the electrode and on-demand hydrogen generation, this process has great potential for a true carbon-negative production of value chemicals from CO2.

Artificial microbial consortia for bioproduction processes.

The application of artificial microbial consortia for biotechnological production processes is an emerging field in research as it offers great potential for the improvement of established as well as the development of novel processes. In this review, we summarize recent highlights in the usage of various microbial consortia for the production of, for example, platform chemicals, biofuels, or pharmaceutical compounds. It aims to demonstrate the great potential of co-cultures by employing different organisms and interaction mechanisms and exploiting their respective advantages. Bacteria and yeasts often offer a broad spectrum of possible products, fungi enable the utilization of complex lignocellulosic substrates via enzyme secretion and hydrolysis, and microalgae can feature their abilities to fixate CO2 through photosynthesis for other organisms as well as to form lipids as potential fuelstocks. However, the complexity of interactions between microbes require methods for observing population dynamics within the process and modern approaches such as modeling or automation for process development. After shortly discussing these interaction mechanisms, we aim to present a broad variety of successfully established co-culture processes to display the potential of artificial microbial consortia for the production of biotechnological products.

Control of parallelized bioreactors I: dynamic scheduling software for efficient bioprocess management in high-throughput systems.

The shift towards high-throughput technologies and automation in research and development in industrial biotechnology is highlighting the need for increased automation competence and specialized software solutions. Within bioprocess development, the trends towards miniaturization and parallelization of bioreactor systems rely on full automation and digital process control. Thus, mL-scale, parallel bioreactor systems require integration into liquid handling stations to perform a range of tasks stretching from substrate addition to automated sampling and sample analysis. To orchestrate these tasks, the authors propose a scheduling software to fully leverage the advantages of a state-of-the-art liquid handling station (LHS) and to enable improved process control and resource allocation. Fixed sequential order execution, the norm in LHS software, results in imperfect timing of essential operations like feeding or Ph control and execution intervals thereof, that are unknown a priori. However, the duration and control of, e.g., the feeding task and their frequency are of great importance for bioprocess control and the design of experiments. Hence, a software solution is presented that allows the orchestration of the respective operations through dynamic scheduling by external LHS control. With the proposed scheduling software, it is possible to define a dynamic process control strategy based on data-driven real-time prioritization and transparent, user-defined constraints. Drivers for a commercial 48 parallel bioreactor system and the related sensor equipment were developed using the SiLA 2 standard greatly simplifying the integration effort. Furthermore, this paper describes the experimental hardware and software setup required for the application use case presented in the second part.

Metabolic control analysis enables rational improvement of E. coli L-tryptophan producers but methylglyoxal formation limits glycerol-based production.

BACKGROUND: Although efficient L-tryptophan production using engineered Escherichia coli is established from glucose, the use of alternative carbon sources is still very limited. Through the application of glycerol as an alternate, a more sustainable substrate (by-product of biodiesel preparation), the well-studied intracellular glycolytic pathways are rerouted, resulting in the activity of different intracellular control sites and regulations, which are not fully understood in detail. Metabolic analysis was applied to well-known engineered E. coli cells with 10 genetic modifications. Cells were withdrawn from a fed-batch production process with glycerol as a carbon source, followed by metabolic control analysis (MCA). This resulted in the identification of several additional enzymes controlling the carbon flux to L-tryptophan. RESULTS: These controlling enzyme activities were addressed stepwise by the targeted overexpression of 4 additional enzymes (trpC, trpB, serB, aroB). Their efficacy regarding L-tryptophan productivity was evaluated under consistent fed-batch cultivation conditions. Although process comparability was impeded by process variances related to a temporal, unpredictable break-off in L-tryptophan production, process improvements of up to 28% with respect to the L-tryptophan produced were observed using the new producer strains. The intracellular effects of these targeted genetic modifications were revealed by metabolic analysis in combination with MCA and expression analysis. Furthermore, it was discovered that the E. coli cells produced the highly toxic metabolite methylglyoxal (MGO) during the fed-batch process. A closer look at the MGO production and detoxification on the metabolome, fluxome, and transcriptome level of the engineered E. coli indicated that the highly toxic metabolite plays a critical role in the production of aromatic amino acids with glycerol as a carbon source. CONCLUSIONS: A detailed process analysis of a new L-tryptophan producer strain revealed that several of the 4 targeted genetic modifications of the E. coli L-tryptophan producer strain proved to be effective, and, for others, new engineering approaches could be derived from the results. As a starting point for further strain and process optimization, the up-regulation of MGO detoxifying enzymes and a lowering of the feeding rate during the last third of the cultivation seems reasonable.

Control of parallelized bioreactors II: probabilistic quantification of carboxylic acid reductase activity for bioprocess optimization.

Autonomously operated parallelized mL-scale bioreactors are considered the key to reduce bioprocess development cost and time. However, their application is often limited to products with very simple analytics. In this study, we investigated enhanced protein expression conditions of a carboxyl reductase from Nocardia otitidiscaviarum in E. coli. Cells were produced with exponential feeding in a L-scale bioreactor. After the desired cell density for protein expression was reached, the cells were automatically transferred to 48 mL-scale bioreactors operated by a liquid handling station where protein expression studies were conducted. During protein expression, the feed rate and the inducer concentration was varied. At the end of the protein expression phase, the enzymatic activity was estimated by performing automated whole-cell biotransformations in a deep-well-plate. The results were analyzed with hierarchical Bayesian modelling methods to account for the biomass growth during the biotransformation, biomass interference on the subsequent product assay, and to predict absolute and specific enzyme activities at optimal expression conditions. Lower feed rates seemed to be beneficial for high specific and absolute activities. At the optimal investigated expression conditions an activity of [Formula: see text] was estimated with a [Formula: see text] credible interval of [Formula: see text]. This is about 40-fold higher than the highest published data for the enzyme under investigation. With the proposed setup, 192 protein expression conditions were studied during four experimental runs with minimal manual workload, showing the reliability and potential of automated and digitalized bioreactor systems.

Phage-free production of artificial ssDNA with Escherichia coli.

Artificial single-stranded DNA (ssDNA) with user-defined sequences and lengths up to the kilobase range is increasingly needed in mass quantities to realize the potential of emerging technologies such as genome editing and DNA origami. However, currently available biotechnological approaches for mass-producing ssDNA require dedicated, and thus costly, fermentation infrastructure, because of the risk of cross-contaminating manufacturer plants with self-replicating phages. Here we overcome this problem with an efficient, scalable, and cross-contamination-free method for the phage-free biotechnological production of artificial ssDNA with Escherichia coli. Our system utilizes a designed phagemid and an optimized helper plasmid. The phagemid encodes one gene of the M13 phage genome and a freely chosen custom target sequence, while the helper plasmid encodes the other genes of the M13 phage. The phagemid particles produced with this method are not capable of self-replication in the absence of the helper plasmid. This enables cross-contamination-free biotechnological production of ssDNA at any contract manufacturer. Furthermore, we optimized the process parameters to reduce by-products and increased the maximal product concentration up to 83 mg L-1 of ssDNA in a stirred-tank bioreactor, thus realizing up to a 40-fold increase in maximal product concentration over previous scalable phage-free ssDNA production methods.

Machine learning-based protein crystal detection for monitoring of crystallization processes enabled with large-scale synthetic data sets of photorealistic images.

Since preparative chromatography is a sustainability challenge due to large amounts of consumables used in downstream processing of biomolecules, protein crystallization offers a promising alternative as a purification method. While the limited crystallizability of proteins often restricts a broad application of crystallization as a purification method, advances in molecular biology, as well as computational methods are pushing the applicability towards integration in biotechnological downstream processes. However, in industrial and academic settings, monitoring protein crystallization processes non-invasively by microscopic photography and automated image evaluation remains a challenging problem. Recently, the identification of single crystal objects using deep learning has been the subject of increased attention for various model systems. However, the advancement of crystal detection using deep learning for biotechnological applications is limited: robust models obtained through supervised machine learning tasks require large-scale and high-quality data sets usually obtained in large projects through extensive manual labeling, an approach that is highly error-prone for dense systems of transparent crystals. For the first time, recent trends involving the use of synthetic data sets for supervised learning are transferred, thus generating photorealistic images of virtual protein crystals in suspension (PCS) through the use of ray tracing algorithms, accompanied by specialized data augmentations modelling experimental noise. Further, it is demonstrated that state-of-the-art models trained with the large-scale synthetic PCS data set outperform similar fine-tuned models based on the average precision metric on a validation data set, followed by experimental validation using high-resolution photomicrographs from stirred tank protein crystallization processes.

Efficient Green Light Acclimation of the Green Algae Picochlorum sp. Triggering Geranylgeranylated Chlorophylls.

In analogy to higher plants, eukaryotic microalgae are thought to be incapable of utilizing green light for growth, due to the "green gap" in the absorbance profiles of their photosynthetic pigments. This study demonstrates, that the marine chlorophyte Picochlorum sp. is able to grow efficiently under green light emitting diode (LED) illumination. Picochlorum sp. growth and pigment profiles under blue, red, green and white LED illumination (light intensity: 50-200 µmol m-2 s-1) in bottom-lightened shake flask cultures were evaluated. Green light-treated cultures showed a prolonged initial growth lag phase of one to 2 days, which was subsequently compensated to obtain comparable biomass yields to red and white light controls (approx. 0.8 gDW L-1). Interestingly, growth and final biomass yields of the green light-treated sample were higher than under blue light with equivalent illumination energies. Further, pigment analysis indicated, that during green light illumination, Picochlorum sp. formed unknown pigments (X1-X4). Pigment concentrations increased with illumination intensity and were most abundant during the exponential growth phase. Mass spectrometry and nuclear magnetic resonance data indicated, that pigments X1-X2 and X3-X4 are derivatives of chlorophyll b and a, which harbor C=C bonds in the phytol side chain similar to geranylgeranylated chlorophylls. Thus, for the first time, the natural accumulation of large pools (approx. 12 mg gDW -1) of chlorophyll intermediates with incomplete hydrogenation of their phytyl chains is demonstrated for algae under monochromatic green light (Peak λ 510 nm, full width at half maximum 91 nm). The ability to utilize green light offers competitive advantages for enhancing biomass production, particularly under conditions of dense cultures, long light pathways and high light intensity. Green light acclimation for an eukaryotic microalgae in conjunction with the formation of new aberrant geranylgeranylated chlorophylls and high efficiency of growth rates are novel for eukaryotic microalgae. Illumination with green light could enhance productivity in industrial processes and trigger the formation of new metabolites-thus, underlying mechanisms require further investigation.

Comparison of Syngas-Fermenting Clostridia in Stirred-Tank Bioreactors and the Effects of Varying Syngas Impurities.

In recent years, syngas fermentation has emerged as a promising means for the production of fuels and platform chemicals, with a variety of acetogens efficiently converting CO-rich gases to ethanol. However, the feasibility of syngas fermentation processes is related to the occurrence of syngas impurities such as NH3, H2S, and NOX. Therefore, the effects of defined additions of NH4+, H2S, and NO3− were studied in autotrophic batch processes with C. autoethanogenum, C. ljungdahlii, and C. ragsdalei while applying continuously gassed stirred-tank bioreactors. Any initial addition of ammonium and nitrate curbed the cell growth of the Clostridia being studied and reduced the final alcohol concentrations. C. ljungdahlii showed the highest tolerance to ammonium and nitrate, whereas C. ragsdalei was even positively influenced by the presence of 0.1 g L−1 H2S. Quantitative goals for the purification of syngas were identified for each of the acetogens studied in the used experimental setup. Syngas purification should in particular focus on the NOX impurities that caused the highest inhibiting effect and maintain the concentrations of NH3 and H2S within an acceptable range (e.g., NH3 < 4560 ppm and H2S < 108 ppm) in order to avoid inhibition through the accumulation of these impurities in the bioreactor.

Advances in automated real-time flow cytometry for monitoring of bioreactor processes.

Flow cytometry and its technological possibilities have greatly advanced in the past decade as analysis tool for single cell properties and population distributions of different cell types in bioreactors. Along the way, some solutions for automated real-time flow cytometry (ART-FCM) were developed for monitoring of bioreactor processes without operator interference over extended periods with variable sampling frequency. However, there is still great potential for ART-FCM to evolve and possibly become a standard application in bioprocess monitoring and process control. This review first addresses different components of an ART-FCM, including the sampling device, the sample-processing unit, the unit for sample delivery to the flow cytometer and the settings for measurement of pre-processed samples. Also, available algorithms are presented for automated data analysis of multi-parameter fluorescence datasets derived from ART-FCM experiments. Furthermore, challenges are discussed for integration of fluorescence-activated cell sorting into an ART-FCM setup for isolation and separation of interesting subpopulations that can be further characterized by for instance omics-methods. As the application of ART-FCM is especially of interest for bioreactor process monitoring, including investigation of population heterogeneity and automated process control, a summary of already existing setups for these purposes is given. Additionally, the general future potential of ART-FCM is addressed.

Lab-scale photobioreactor systems: principles, applications, and scalability.

Phototrophic microorganisms that convert carbon dioxide are being explored for their capacity to solve different environmental issues and produce bioactive compounds for human therapeutics and as food additives. Full-scale phototrophic cultivation of microalgae and cyanobacteria can be done in open ponds or closed photobioreactor systems, which have a broad range of volumes. This review focuses on laboratory-scale photobioreactors and their different designs. Illuminated microtiter plates and microfluidic devices offer an option for automated high-throughput studies with microalgae. Illuminated shake flasks are used for simple uncontrolled batch studies. The application of illuminated bubble column reactors strongly emphasizes homogenous gas distribution, while illuminated flat plate bioreactors offer high and uniform light input. Illuminated stirred-tank bioreactors facilitate the application of very well-defined reaction conditions. Closed tubular photobioreactors as well as open photobioreactors like small-scale raceway ponds and thin-layer cascades are applied as scale-down models of the respective large-scale bioreactors. A few other less common designs such as illuminated plastic bags or aquarium tanks are also used mainly because of their relatively low cost, but up-scaling of these designs is challenging with additional light-driven issues. Finally, this review covers recommendations on the criteria for photobioreactor selection and operation while up-scaling of phototrophic bioprocesses with microalgae or cyanobacteria.