Analysis of global control of Escherichia coli carbohydrate uptake

<p>Abstract</p> <p>Background</p> <p>Global control influences the regulation of many individual subsystems by superimposed regulator proteins. A prominent example is the control of carbohydrate uptake systems by the transcription factor Crp in <it>Escherichia coli</it>. A detailed understanding of the coordination of the control of individual transporters offers possibilities to explore the potential of microorganisms e.g. in biotechnology.</p> <p>Results</p> <p>An o.d.e. based mathematical model is presented that maps a physiological parameter – the specific growth rate – to the sensor of the signal transduction unit, here a component of the bacterial phosphotransferase system (PTS), namely EIIA^<it>Crr</it>. The model describes the relation between the growth rate and the degree of phosphorylation of EIIA ^{<it>crr </it>}for a number of carbohydrates by a distinctive response curve, that differentiates between PTS transported carbohydrates and non-PTS carbohydrates. With only a small number of kinetic parameters, the model is able to describe a broad range of experimental steady-state and dynamical conditions.</p> <p>Conclusion</p> <p>The steady-state characteristic presented shows a relationship between the growth rate and the output of the sensor system PTS. The glycolytic flux that is measured by this sensor is a good indicator to represent the nutritional status of the cell.</p

Robust control of a catalytic fixed bed reactor

Catalytic fixed bed reactors exhibit interesting control problems due to their nonlinear behaviour and their sensitivity to load changes and other disturbances. Because detailed nonlinear models of such reactors are too complex for use in controller design, a linear model description is identified here along with an appropriate structured uncertainty description. The controller is designed based on the &#956;-paradigm to guarantee robust stability and robust performance. A comparison with an H&#8734;-optimal controller is also given. For the H&#8734;-design the structured uncertainties are converted into a single multivariable unstructured uncertainty. As expected the H&#8734;-controller can only achieve a much less demanding performance because of the conservatism of the unstructured uncertainty description. Experimental results involving a real reactor are given

Metabolic engineering of Halomonas elongata: Ectoine secretion is increased by demand and supply driven approaches

The application of naturally-derived biomolecules in everyday products, replacing conventional synthetic manufacturing, is an ever-increasing market. An example of this is the compatible solute ectoine, which is contained in a plethora of treatment formulations for medicinal products and cosmetics. As of today, ectoine is produced in a scale of tons each year by the natural producer Halomonas elongata. In this work, we explore two complementary approaches to obtain genetically improved producer strains for ectoine production. We explore the effect of increased precursor supply (oxaloacetate) on ectoine production, as well as an implementation of increased ectoine demand through the overexpression of a transporter. Both approaches were implemented on an already genetically modified ectoine-excreting strain H. elongata KB2.13 (ΔteaABC ΔdoeA) and both led to new strains with higher ectoine excretion. The supply driven approach led to a 45% increase in ectoine titers in two different strains. This increase was attributed to the removal of phosphoenolpyruvate carboxykinase (PEPCK), which allowed the conversion of 17.9% of the glucose substrate to ectoine. For the demand driven approach, we investigated the potential of the TeaBC transmembrane proteins from the ectoine-specific Tripartite ATP-Independent Periplasmic (TRAP) transporter as export channels to improve ectoine excretion. In the absence of the substrate-binding protein TeaA, an overexpression of both subunits TeaBC facilitated a three-fold increased excretion rate of ectoine. Individually, the large subunit TeaC showed an approximately five times higher extracellular ectoine concentration per dry weight compared to TeaBC shortly after its expression was induced. However, the detrimental effect on growth and ectoine titer at the end of the process hints toward a negative impact of TeaC overexpression on membrane integrity and possibly leads to cell lysis. By using either strategy, the ectoine synthesis and excretion in H. elongata could be boosted drastically. The inherent complementary nature of these approaches point at a coordinated implementation of both as a promising strategy for future projects in Metabolic Engineering. Moreover, a wide variation of intracelllular ectoine levels was observed between the strains, which points at a major disruption of mechanisms responsible for ectoine regulation in strain KB2.13.This work has been funded by the German Federal Ministry of Education and Research (BMBF) through project HOBBIT (031B03)

Adaptation to Varying Salinity in Halomonas elongata: Much More Than Ectoine Accumulation

The halophilic γ-proteobacterium Halomonas elongata DSM 2581 T thrives at salt concentrations well above 10 % NaCl (1.7 M NaCl). A well-known osmoregulatory mechanism is the accumulation of the compatible solute ectoine within the cell in response to osmotic stress. While ectoine accumulation is central to osmoregulation and promotes resistance to high salinity in halophilic bacteria, ectoine has this effect only to a much lesser extent in non-halophiles. We carried out transcriptome analysis of H. elongata grown on two different carbon sources (acetate or glucose), and low (0.17 M NaCl), medium (1 M), and high salinity (2 M) to identify additional mechanisms for adaptation to high saline environments. To avoid a methodological bias, the transcripts were evaluated by applying two methods, DESeq2 and Transcripts Per Million (TPM). The differentially transcribed genes in response to the available carbon sources and salt stress were then compared to the transcriptome profile of Chromohalobacter salexigens, a closely related moderate halophilic bacterium. Transcriptome profiling supports the notion that glucose is degraded via the cytoplasmic Entner-Doudoroff pathway, whereas the Embden-Meyerhoff-Parnas pathway is employed for gluconeogenesis. The machinery of oxidative phosphorylation in H. elongata and C. salexigens differs greatly from that of non-halophilic organisms, and electron flow can occur from quinone to oxygen along four alternative routes. Two of these pathways via cytochrome bo' and cytochrome bd quinol oxidases seem to be upregulated in salt stressed cells. Among the most highly regulated genes in H. elongata and C. salexigens are those encoding chemotaxis and motility proteins, with genes for chemotaxis and flagellar assembly severely downregulated at low salt concentrations. We also compared transcripts at low and high-salt stress (low growth rate) with transcripts at optimal salt concentration and found that the majority of regulated genes were down-regulated in stressed cells, including many genes involved in carbohydrate metabolism, while ribosome synthesis was up-regulated, which is in contrast to what is known from non-halophiles at slow growth. Finally, comparing the acidity of the cytoplasmic proteomes of non-halophiles, extreme halophiles and moderate halophiles suggests adaptation to an increased cytoplasmic ion concentration of H. elongata. Taken together, these results lead us to propose a model for salt tolerance in H. elongata where ion accumulation plays a greater role in salt tolerance than previously assumed

SYSTEMORIENTIERTE BIOPROZESSTECHNIK: INTERDISZIPLINÄRE FORSCHUNG IN BIOLOGIE, SYSTEM- UND COMPUTERWISSENSCHAFTEN

Die aktuelle Forschung in der molekularen Genetik und die Erfolge bei der Analyse von Genexpression und Proteinfunktion führen zu einer bisher unerreichten Fülle von Informationen über biologische Phänomene. Damit ergeben sich neben der medizinischen Anwendung auch neue Möglichkeiten und Aufgaben in der biotechnologischen Produktion von Wirkstoffen. Um dieses biologische Potenzial voll ausschöpfen zu können, bedarf es jedoch verstärkt interdisziplinärer Forschung in Biologie, System- und Computerwissenschaften. Der hier skizzierte Forschungsansatz soll langfristig zum Aufbau eines „Virtuellen Biologischen Labors“ führen, in dem Experimente am Rechner analog zu Experimenten im Labor durchgeführt werden können. Damit steht in Forschung und Lehre ein Werkzeug zur Vermittlung quantitativer und qualitativer Aspekte von zellulären Stoffwechsel- und Regulationsvorgängen zur Verfügung

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Strukturierung zellulärer Funktionseinheiten - ein signalorientierter Modellierungsansatz für zelluläre Systeme am Beispiel von Escherichia coli

The understanding of the growth and production behaviour of microorganisms requires a detailed knowledge in microbiology and genetics. To use the high potential of biological systems, e.g. in biotechnology, the knowledge has to be structured and collected in an apparent form. This will be a basis for setting up mathematical models. The thesis starts with a presentation of the research field, followed by an introduction in the modeling concept. In the thesis, a systematic approach to develop a detailed metabolic model is introduced. The approach is based on the definition of modeling objects (submodels) with defined in- and outputs. To guarantee a high biological transparency the modeling objects can be assigned directly to cellular units, e.g. a single enzymatic reaction step or e.g. complete pathways for transport and degradation of carbohydrates. Elementary modeling objects represent modeling objects with the highest resolution, i.e. substance storages, substance transformers and signal transformers. Substance storages represent metabolites, substance transformers stand for enzymatic reaction steps or polymerization steps while signal transformers describe processes of signal transduction and processing. A mathematical description is realized by assigning equations to the modeling objects. The following chapter describes the aggregation of elementary modeling objects to ’functional units’,i.e. units with higher complexity. Three criteria are given to demarcate functional units. The most important one describes the organization according signal transduction and processing. Special characteristics of functional units are (i) a hierarchical structure and (ii) signal processing in local as well as global signal transduction elements. An important point discussed in the chapter is signal processing in hierarchical structured units. For the initiation of transcription, in general, activators or inhibitors interact with the RNA polymerase to modify the initiation frequency. However, the influence of these effectors is limited to a small number of binding sites, e.g. the lactose repressor LacI has only one binding site on the whole E. coli genome. Hence, the repressor will clearly influence the initiation frequency of the lac-operon, but it will not influence the overall distribution of the RNA polymerase inside the cell. This fact is used in a new method to describe signal processing. Every protein involved in transcription of a gene is assigned to one level in hierarchy. Signals are transduced from top level to the lower level, but not vice versa. A computer tool is necessary to set up models with a large number of equations. The software package CellMod is based on C++ and supports the modeler by generating the required equations automatically. A number of elementary and aggregated modeling objects are implemented. Central in this tool is a model library for enzyme catalysed reactions, including about 42 entrys, starting from a simple Michaels-Menten equation up to complex models for 4 reaction partners. The modeling concept is applied to carbohydrate uptake in Escherichiacoli. The phenomenon of “glucose catabolite repression” means the repression of uptake of carbon sources if glucose is present in the medium. Only if glucose has run out, transport systems of other available carbohydrates are synthesised. This is due to a complex signal transduction pathway starting from the main glucose uptake system. The mathematical model developed in this thesis describes the main glucose uptake system and further elements in the signal transduction pathway. They represent the highest level of control in a functional unit called crp-modulon, named after the final target of the signal transduction pathway, the protein Crp. Besides the description of the signal transduction pathway, the metabolic pathways for lactose uptake and degradation and for the glycolysis are also included in the model. Finally the simulation results are compared to data published in the literature. The comparision of simulation results and experimental data of a wild type strain and of strains which are genetically modified are in good agreement

Simultaneous model discrimination and parameter estimation in dynamic models of cellular systems

14 páginas, 11 figuras, 1 tablaBackground Model development is a key task in systems biology, which typically starts from an initial model candidate and, involving an iterative cycle of hypotheses-driven model modifications, leads to new experimentation and subsequent model identification steps. The final product of this cycle is a satisfactory refined model of the biological phenomena under study. During such iterative model development, researchers frequently propose a set of model candidates from which the best alternative must be selected. Here we consider this problem of model selection and formulate it as a simultaneous model selection and parameter identification problem. More precisely, we consider a general mixed-integer nonlinear programming (MINLP) formulation for model selection and identification, with emphasis on dynamic models consisting of sets of either ODEs (ordinary differential equations) or DAEs (differential algebraic equations). Results We solved the MINLP formulation for model selection and identification using an algorithm based on Scatter Search (SS). We illustrate the capabilities and efficiency of the proposed strategy with a case study considering the KdpD/KdpE system regulating potassium homeostasis in Escherichia coli. The proposed approach resulted in a final model that presents a better fit to the in silico generated experimental data. Conclusions The presented MINLP-based optimization approach for nested-model selection and identification is a powerful methodology for model development in systems biology. This strategy can be used to perform model selection and parameter estimation in one single step, thus greatly reducing the number of experiments and computations of traditional modeling approaches.Authors MRF and JRB acknowledge financial support from the EU ERASysBio programme and the Spanish MICINN and MINECO (SYSMO grant KOSMOBAC, ref. GEN2006-27747-E/SYS and project MultiScales ref. DPI2011-28112-C04-03, both with partial support from the European Regional Development Fund, ERDF). MR was supported by the Max Planck society and the European Erasmus project. AK was funded in part by the BMBF through the Era-Net initiative SysMO. We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI).Peer Reviewe

Den Zur Gnade abgefoderten Benjamin, Wolte, Als Des Hoch-Edelgebohrnen Herrn Rudolph August von Windheims, Hoch-Gräfl. Stolberg-Wernigerödischen wohlbestallten Amtmann zu Beckenstedt und Stapelnburg, Und Der Hoch-Edelgebohrnen Frauen, Frauen Dorothea Regina, gebohrnen Oehlerin, Lieb-gewesenes Jüngstes Söhnlein Julius Christian Friderich, Am 8. Sept. dieses 1735. Jahres ... die Zeit mit der Ewigkeit verwechselte, Und am 10. ejusd. das entseelte Cörperlein der Erden anvertrauet wurde, Aus hertzlichem Mitleiden und Schuldigkeit Vorstellen Johann Heinrich Andreas Kremling, SS. Theol. Stud.

Vorlageform des Erscheinungsvermerks: Wernigeroda, Gedruckt mit Struckischen Schriften

A comparison of deterministic and stochastic modeling approaches for biochemical reaction systems: On fixed points, means, and modes.

In the mathematical modeling of biochemical reactions, a convenient standard approach is to use ordinary differential equations (ODEs) that follow the law of mass action. However, this deterministic ansatz is based on simplifications; in particular, it neglects noise, which is inherent to biological processes. In contrast, the stochasticity of reactions is captured in detail by the discrete chemical master equation (CME). Therefore, the CME is frequently applied to mesoscopic systems, where copy numbers of involved components are small and random fluctuations are thus significant. Here, we compare those two common modeling approaches, aiming at identifying parallels and discrepancies between deterministic variables and possible stochastic counterparts like the mean or modes of the state space probability distribution. To that end, a mathematically flexible reaction scheme of autoregulatory gene expression is translated into the corresponding ODE and CME formulations. We show that in the thermodynamic limit, deterministic stable fixed points usually correspond well to the modes in the stationary probability distribution. However, this connection might be disrupted in small systems. The discrepancies are characterized and systematically traced back to the magnitude of the stoichiometric coefficients and to the presence of nonlinear reactions. These factors are found to synergistically promote large and highly asymmetric fluctuations. As a consequence, bistable but unimodal, and monostable but bimodal systems can emerge. This clearly challenges the role of ODE modeling in the description of cellular signaling and regulation, where some of the involved components usually occur in low copy numbers. Nevertheless, systems whose bimodality originates from deterministic bistability are found to sustain a more robust separation of the two states compared to bimodal, but monostable systems. In regulatory circuits that require precise coordination, ODE modeling is thus still expected to provide relevant indications on the underlying dynamics