Mitochondrial Respiratory Chain Alternative Components Activity During Different Growth Phases in Yarrowia Lipolytica

Additional file 4. Spreadsheet file containing BioLector raw data set with backscatter and DO readings for twenty-four cultivations of C. glutamicum strains, used for calculation of growth rates in the application example

Monitoreo descriptivo de parásitos de origen fecal hallados en hortalizas de hojas

p.271-276El objetivo de este trabajo fue contabilizar la presencia de protozoos, huevos y larvas de helmintos en muestras de hortalizas de hoja para consumo fresco, que se comercializan en el Mercado Central de Buenos Aires. Las especies analizadas fueron: lechuga, radicheta, berro y perejil. Las muestras se procesaron por los métodos de Baerman y Flotación. Los resultados obtenidos indican que: 1- Existe contaminación parasitaria: sobre un total de 98 muestras analizadas durante 12 meses, el 27,5por ciento estaban contaminadas. 2- La especie más contaminada fue berro (66,7por ciento), luego radicheta (31,8por ciento), lechuga (21,4por ciento) y, finalmente, perejil (13,6por ciento). 3- El parásito más frecuente fue Entamoeba coli (44,4por ciento) y en segundo término E.hystolitica (22,4por ciento). 4- El sur y sudoeste del conurbano bonaerense fue la zona de mayor contaminación (66,6por ciento). La presencia de los contaminantes en las hortalizas estudiadas demuestra el desconocimiento de los riesgos potenciales que ciertas prácticas agrícolas pueden acarrear a los consumidores

Metabolomanalyse zur Untersuchung der Dynamik im Aromatenbiosyntheseweg in L–Phenylalanin Produzenten von <i>Escherichia coli</i>

Die Metabolomanalyse gewinnt zunehmend an Bedeutung für die Untersuchung der Eigenschaften, Funktion und Kinetik von Stoffwechselsystemen auf intrazellulärem Niveau. Am Beispiel der Aromatenbiosynthese in Escherichia coli (E. coli) wurde das Prinzip des „Metabolic Profiling“, d.h. der quantitativen Messung von intrazellulären Stoffwechselmetaboliten, für die Untersuchung von rekombinanten L-Phenylalanin Produktionsstämmen von E. coli angewendet. Die Fermentationsexperimente wurden unter dynamischen Bedingungen durchgeführt, d.h. unter substratlimitierten (glukoselimitierten) Bedingungen wurde schlagartig ein Glukosepuls zugesetzt. Um die schnelle intrazelluläre Antwort der Zellen auf die Substratzugabe aufzuzeichnen wurde eine automatisierte Technik zur schnellen Probenahme im subsekunden-Bereich eingesetzt. Durch parallele Abkühlung der Probe auf -20°C wurde gleichzeitig der Metabolismus der Zellen gestoppt. Nach der Aufarbeitung der Proben wurde der dynamische Verlauf der intrazellulären Metabolitkonzentrationen im Verlauf des Pulsexperimentes in den Zellextraktproben mittels einer neu entwickelten LC–MS/MS Methode gemessen. In der Arbeit wurden sowohl ein LC-MS mit Ionenfallentechnik für die Strukturaufklärung von Metaboliten, als auch ein LC-MS mit Triple-Quadrupol-Technik für die Quantifizierung der Metaboliten eingesetzt. Für eine exakte Quantifizierung der LC-MS Messungen wurde die Standard-Additions-Methode eingesetzt, wobei die nicht kommerziell verfügbaren Metaboliten aus dem Aromatenbiosyntheseweg chemisch bzw. mikrobiell durch Fermentation gentechnisch geblockter E. coli Mutanten dargestellt wurden. Die Fermentationsexperimente mit Glukosepuls wurden im Fed–Batch Verfahren unter produktionsrelevanten Bedingungen durchgeführt, so dass die Ergebnisse Rückschlüsse auf den Produktionsprozess zulassen konnten. Die Stimulation des Stoffwechsels durch den Glukosepuls konnte dabei nicht nur im katabolen Stoffwechsel (Glykolyse, Pentose-Phosphat-Weg), sondern auch in Metaboliten der Aromatenbiosynthese auf dem Weg zum L–Phenylalanin nachgewiesen werden. Die gemessenen intrazellulären Konzentrations-Zeit-Verläufe der Metaboliten wurden mit einfachen statistischen Methoden ausgewertet. Die Daten identifizierten die 3-Dehydroquinat-Synthase (aroB), die Shikimat-Kinasen (aroK, aroL) und die EPSP-Synthase (aroA) als Biosyntheseschritte mit hoher Flusskontrolle durch den Aromatenbiosyntheseweg.Metabolome analysis for the investigation of dynamic in the aromatic biosynthesis pathway in a L-phenylalanine Escherichia coli production strain Metabolome analysis is gaining interest for the investigation of the properties, function and kinetics of metabolic systems at intracellular level. Using the aromatic biosynthesis in Escherichia coli (E. coli) the principle of “metabolic profiling”, meaning the quantitative measurement of intracellular metabolites was applied for the investigation of recombinant L-phenylalanine production strains of E. coli. Fermentation experiments were conducted under dynamic conditions, meaning the rapid addition of a glucose pulse to the glucose limited fermentation culture. To monitor the fast intracellular metabolism response of the cells an automated rapid sampling technique was used allowing sampling on a subsecond time scale. Parallel cooling of the samples to -20°C simultaneously stopped metabolism activity. After sample preparation the dynamic response of the intracellular metabolite concentrations during the glucose pulse experiment were measured with a newly developed LC-MS/MS method. Two different LC-MS systems were used in this work. Structure analysis of metabolites was performed with a LC-MS with ion-trap technique and metabolite quantification was done with a LC-MS with triple-quadrupole technique. To correct for matrix effects during quantification, the standard-addition-method was used. Commercially non-available metabolites from the aromatic biosynthesis were prepared chemically or fermentatively with the aid of genetically blocked E. coli mutant strains. The fermentation experiments with glucose pulse were conducted in fed-batch mode under conditions relevant to the L-phenylalanine production process. The glucose pulse induced metabolism stimulation was detected in the catabolic metabolism (glycolysis, pentose-phosphate-pathway) and in the metabolite pools of the aromatic biosynthesis leading to L-phenylalanine. The measured intracellular concentration-time-courses of the metabolites were interpreted with simple statistical methods. The data identified 3-dehydroquinate synthase (aroB), shikimate kinases (aroK/aroL) and EPSP-synthase (aroA) to be of high flux control in the aromatic biosynthesis pathway

Automated Characterization of Catalytically Active Inclusion Body Production in Biotechnological Screening Systems

We here propose an automated pipeline for the microscopy image-based characterization of catalytically active inclusion bodies (CatIBs), which includes a fully automatic experimental high-throughput workflow combined with a hybrid approach for multi-object microbial cell segmentation. For automated microscopy, a CatIB producer strain was cultivated in a microbioreactor from which samples were injected into a flow chamber. The flow chamber was fixed under a microscope and an integrated camera took a series of images per sample. To explore heterogeneity of CatIB development during the cultivation and track the size and quantity of CatIBs over time, a hybrid image processing pipeline approach was developed, which combines an ML-based detection of in-focus cells with model-based segmentation. The experimental setup in combination with an automated image analysis unlocks high-throughput screening of CatIB production, saving time and resources. Biotechnological relevance - CatIBs have wide application in synthetic chemistry and biocatalysis, but also could have future biomedical applications such as therapeutics. The proposed hybrid automatic image processing pipeline can be adjusted to treat comparable biological microorganisms, where fully data-driven ML-based segmentation approaches are not feasible due to the lack of training data. Our work is the first step towards image-based bioprocess control

Germination and Growth Analysis of Streptomyces lividans at the Single-Cell Level Under Varying Medium Compositions

Quantitative single-cell cultivation has provided fundamental contributions to our understanding of heterogeneity among industrially used microorganisms. Filamentous growing Streptomyces species are emerging platform organisms for industrial production processes, but their exploitation is still limited due to often reported high batch-to-batch variations and unexpected growth and production differences. Population heterogeneity is suspected to be one responsible factor, which is so far not systematically investigated at the single-cell level. Novel microfluidic single-cell cultivation devices offer promising solutions to investigate these phenomena. In this study, we investigated the germination and growth behavior of Streptomyces lividans TK24 under varying medium compositions on different complexity levels (i.e., mycelial growth, hyphal growth and tip elongation) on single-cell level. Our analysis reveals a remarkable stability within growth and germination of spores and early mycelium development when exposed to constant and defined environments. We show that spores undergo long metabolic adaptation processes of up to &gt; 30 h to adjust to new medium conditions, rather than using a “persister” strategy as a possibility to cope with rapidly changing environments. Due to this uniform behavior, we conclude that S. lividans can be cultivated quite robustly under constant environmental conditions as provided by microfluidic cultivation approaches. Failure and non-reproducible cultivations are thus most likely to be found in less controllable larger-scale cultivation workflows and as a result of environmental gradients within large-scale cultivations

Current state and challenges for dynamic metabolic modeling

While the stoichiometry of metabolism is probably the best studied cellular level, the dynamics in metabolism can still not be well described, predicted and, thus, engineered. Unknowns in the metabolic flux behavior arise from kinetic interactions, especially allosteric control mechanisms. While the stoichiometry of enzymes is preserved in vitro, their activity and kinetic behavior differs from the in vivo situation. Next to this challenge, it is infeasible to test the interaction of each enzyme with each intracellular metabolite in vitro exhaustively. As a consequence, the whole interacting metabolome has to be studied in vivo to identify the relevant enzymes properties. In this review we discuss current approaches for in vivo perturbation experiments, that is, stimulus response experiments using different setups and quantitative analytical approaches, including dynamic carbon tracing. Next to reliable and informative data, advanced modeling approaches and computational tools are required to identify kinetic mechanisms and their parameters.The authors EV, AT, KN, IR, MO, DM and AW are part of the ERA-IB funded consortium DYNAMICS (ERA-IB-14-081, NWO 053.80.724)

Modeling metabolic networks in C. glutamicum: a comparison of rate laws in combination with various parameter optimization strategies

<p>Abstract</p> <p>Background</p> <p>To understand the dynamic behavior of cellular systems, mathematical modeling is often necessary and comprises three steps: (1) experimental measurement of participating molecules, (2) assignment of rate laws to each reaction, and (3) parameter calibration with respect to the measurements. In each of these steps the modeler is confronted with a plethora of alternative approaches, e. g., the selection of approximative rate laws in step two as specific equations are often unknown, or the choice of an estimation procedure with its specific settings in step three. This overall process with its numerous choices and the mutual influence between them makes it hard to single out the best modeling approach for a given problem.</p> <p>Results</p> <p>We investigate the modeling process using multiple kinetic equations together with various parameter optimization methods for a well-characterized example network, the biosynthesis of valine and leucine in <it>C. glutamicum</it>. For this purpose, we derive seven dynamic models based on generalized mass action, Michaelis-Menten and convenience kinetics as well as the stochastic Langevin equation. In addition, we introduce two modeling approaches for feedback inhibition to the mass action kinetics. The parameters of each model are estimated using eight optimization strategies. To determine the most promising modeling approaches together with the best optimization algorithms, we carry out a two-step benchmark: (1) coarse-grained comparison of the algorithms on all models and (2) fine-grained tuning of the best optimization algorithms and models. To analyze the space of the best parameters found for each model, we apply clustering, variance, and correlation analysis.</p> <p>Conclusion</p> <p>A mixed model based on the convenience rate law and the Michaelis-Menten equation, in which all reactions are assumed to be reversible, is the most suitable deterministic modeling approach followed by a reversible generalized mass action kinetics model. A Langevin model is advisable to take stochastic effects into account. To estimate the model parameters, three algorithms are particularly useful: For first attempts the settings-free Tribes algorithm yields valuable results. Particle swarm optimization and differential evolution provide significantly better results with appropriate settings.</p

Germination and Growth Analysis of Streptomyces lividans at the Single-Cell Level Under Varying Medium Compositions

Koepff J, Sachs CC, Wiechert W, et al. Germination and Growth Analysis of Streptomyces lividans at the Single-Cell Level Under Varying Medium Compositions. FRONTIERS IN MICROBIOLOGY. 2018;9: 2680.Quantitative single-cell cultivation has provided fundamental contributions to our understanding of heterogeneity among industrially used microorganisms. Filamentous growing Streptomyces species are emerging platform organisms for industrial production processes, but their exploitation is still limited due to often reported high batch-to-batch variations and unexpected growth and production differences. Population heterogeneity is suspected to be one responsible factor, which is so far not systematically investigated at the single-cell level. Novel microfluidic single-cell cultivation devices offer promising solutions to investigate these phenomena. In this study, we investigated the germination and growth behavior of Streptomyces lividans TK24 under varying medium compositions on different complexity levels (i.e., mycelial growth, hyphal growth and tip elongation) on single-cell level. Our analysis reveals a remarkable stability within growth and germination of spores and early mycelium development when exposed to constant and defined environments. We show that spores undergo long metabolic adaptation processes of up to > 30 h to adjust to new medium conditions, rather than using a "persister" strategy as a possibility to cope with rapidly changing environments. Due to this uniform behavior, we conclude that S. lividans can be cultivated quite robustly under constant environmental conditions as provided by microfluidic cultivation approaches. Failure and non-reproducible cultivations are thus most likely to be found in less controllable larger-scale cultivation workflows and as a result of environmental gradients within large-scale cultivations