Modellbasierte Bestimmung von Interventionsstrategien zur Optimierung der Produktion von Biokraftstoffen in Cyanobakterien

Otto-von-Guericke-Universität Magdeburg, Fakultät für Verfahrens- und Systemtechnik, Dissertation, 2016von Diplom-Ingenieur Philipp ErdrichLiteraturverzeichnis: Seite 131-15

Derivation of a biomass proxy for dynamic analysis of whole genome metabolic models

A whole genome metabolic model (GEM) is essentially a reconstruction of a network of enzyme-enabled chemical reactions representing the metabolism of an organism, based on information present in its genome. Such models have been designed so that flux balance analysis (FBA) can be applied in order to analyse metabolism under steady state. For this purpose, a biomassfunctionisaddedtothesemodelsasanoverallindicatorofthemodel’s viability. Our objective is to develop dynamic models based on these FBA models in order to observe new and complex behaviours, including transient behaviour. There is however a major challenge in that the biomass function does not operate under dynamic simulation. An appropriate biomass function would enable the estimation under dynamic simulation of the growth of both wildtype and genetically modified bacteria under different, possibly dynamically changing growth conditions. Using data analytics techniques, we have developed a dynamic biomass function which acts as a faithful proxy for the FBA equivalent for a reduced GEM for E. coli. This involved consolidating data for reaction rates and metabolite concentrations generated under dynamic simulation with gold standard target data for biomass obtained by steady state analysis using FBA. It also led to a number of interesting insights regarding biomass fluxes for pairs of conditions. These findings were reproduced in our dynamic proxy function

Emerging ensembles of kinetic parameters to identify experimentally observed phenotypes

Background: Determining the value of kinetic constants for a metabolic system in the exact physiological conditions is an extremely hard task. However, this kind of information is of pivotal relevance to effectively simulate a biological phenomenon as complex as metabolism. Results: To overcome this issue, we propose to investigate emerging properties of ensembles of sets of kinetic constants leading to the biological readout observed in different experimental conditions. To this aim, we exploit information retrievable from constraint-based analyses (i.e. metabolic flux distributions at steady state) with the goal to generate feasible values for kinetic constants exploiting the mass action law. The sets retrieved from the previous step will be used to parametrize a mechanistic model whose simulation will be performed to reconstruct the dynamics of the system (until reaching the metabolic steady state) for each experimental condition. Every parametrization that is in accordance with the expected metabolic phenotype is collected in an ensemble whose features are analyzed to determine the emergence of properties of a phenotype. In this work we apply the proposed approach to identify ensembles of kinetic parameters for five metabolic phenotypes of E. Coli, by analyzing five different experimental conditions associated with the ECC2comp model recently published by Hädicke and collaborators. Conclusions: Our results suggest that the parameter values of just few reactions are responsible for the emergence of a metabolic phenotype. Notably, in contrast with constraint-based approaches such as Flux Balance Analysis, the methodology used in this paper does not require to assume that metabolism is optimizing towards a specific goal

Cyanobacterial biofuels: new insights and strain design strategies revealed by computational modeling

BACKGROUND: Cyanobacteria are increasingly recognized as promising cell factories for the production of renewable biofuels and chemical feedstocks from sunlight, CO2, and water. However, most biotechnological applications of these organisms are still characterized by low yields. Increasing the production performance of cyanobacteria remains therefore a crucial step. RESULTS: In this work we use a stoichiometric network model of Synechocystis sp. PCC 6803 in combination with CASOP and minimal cut set analysis to systematically identify and characterize suitable strain design strategies for biofuel synthesis, specifically for ethanol and isobutanol. As a key result, improving upon other works, we demonstrate that higher-order knockout strategies exist in the model that lead to coupling of growth with high-yield biofuel synthesis under phototrophic conditions. Enumerating all potential knockout strategies (cut sets) reveals a unifying principle behind the identified strain designs, namely to reduce the ratio of ATP to NADPH produced by the photosynthetic electron transport chain. Accordingly, suitable knockout strategies seek to block cyclic and other alternate electron flows, such that ATP and NADPH are exclusively synthesized via the linear electron flow whose ATP/NADPH ratio is below that required for biomass synthesis. The products of interest are then utilized by the cell as sinks for reduction equivalents in excess. Importantly, the calculated intervention strategies do not rely on the assumption of optimal growth and they ensure that maintenance metabolism in the absence of light remains feasible. Our analyses furthermore suggest that a moderately increased ATP turnover, realized, for example, by ATP futile cycles or other ATP wasting mechanisms, represents a promising target to achieve increased biofuel yields. CONCLUSION: Our study reveals key principles of rational metabolic engineering strategies in cyanobacteria towards biofuel production. The results clearly show that achieving obligatory coupling of growth and product synthesis in photosynthetic bacteria requires fundamentally different intervention strategies compared to heterotrophic organisms. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12934-014-0128-x) contains supplementary material, which is available to authorized users

Investigating the association between the symptoms of women with fibromyalgia, digestive function, and markers of the microbiota of the gastrointestinal tract (The FIDGIT Study) : study protocol

Background: Fibromyalgia a common idiopathic condition affecting around 1.4% of adults globally. Its signature symptom is chronic widespread pain, with a constellation of somatic and psychological symptoms. Fibromyalgia is associated with significant reductions in quality of life, yet to date there is no biochemical marker for its diagnosis. Previous studies have indicated a strong association with gastrointestinal dysfunction, and more recently, alterations to the gut microbiome. No studies have examined the inter-relationship between fibromyalgia, gastrointestinal dysfunction, and the microbiome. This prospective observational case-controlled study will gather data on gastrointestinal function, dietary intake, fermentation patterns of ingested carbohydrates, and symptoms commonly associated with fibromyalgia. These will be evaluated alongside human gene expression and metatranscriptomic analysis of the oral and faecal microbiome. Methods: Adult women aged ≥18 years diagnosed with fibromyalgia and/or meeting ACR 2016 criteria, and healthy family or age-matched controls will be recruited from the community. From consenting participants, we will collect detailed survey information and samples of blood, urine, stool, saliva, and breath. Discussion: This is the first prospective study examining interactions between digestive function, human gene expression, and the gut microbiome together with general, and fibromyalgia-specific, symptoms experienced by New Zealand women. This exploration will allow an in-depth understanding of clinically relevant factors that are associated with fibromyalgia and will guide further research and contribute to improved management of this poorly understood condition. Trial Registration: The study was approved by the New Zealand Health and Disability Committee (HDEC) (ref: 20/CEN/197) and registered with the Australia and New Zealand Clinical Trials Registry (ANZCTR), registration number ACTRN12620001337965. Written consent will be obtained after providing participants with detailed information about the procedures. Access to data will be restricted to the immediate research team, and all samples and survey data will be deidentified and coded before analysis

Hydrogen–methane breath testing results influenced by oral hygiene

Abstract The measurement of hydrogen–methane breath gases is widely used in gastroenterology to evaluate malabsorption syndromes and bacterial overgrowth. Laboratories offering breath testing provide variable guidance regarding oral hygiene practices prior to testing. Given that oral dysbiosis has the potential to cause changes in breath gases, it raises concerns that oral hygiene is not a standard inclusion in current breath testing guidelines. The aim of this study was to determine how a pre-test mouthwash may impact hydrogen–methane breath test results. Participants presenting for breath testing who had elevated baseline gases were given a chlorhexidine mouthwash. If a substantial reduction in expired hydrogen or methane occurred after the mouthwash, breath samples were collected before and after a mouthwash at all breath sample collection points for the duration of testing. Data were evaluated to determine how the mouthwash might influence test results and diagnostic status. In 388 consecutive hydrogen–methane breath tests, modifiable elevations occurred in 24.7%. Administration of a chlorhexidine mouthwash resulted in significantly (p ≤ 0.05) reduced breath hydrogen in 67% and/or methane gas in 93% of those consenting to inclusion. In some cases, this modified the diagnosis. Mean total gas concentrations pre- and post-mouthwash were 221.0 ppm and 152.1 ppm (p < 0.0001) for hydrogen, and 368.9 ppm and 249.8 ppm (p < 0.0001) for methane. Data suggest that a single mouthwash at baseline has a high probability of returning a false positive diagnosis. Variations in gas production due to oral hygiene practices has significant impacts on test interpretation and the subsequent diagnosis. The role of oral dysbiosis in causing gastrointestinal symptoms also demands exploration as it may be an underlying factor in the presenting condition that was the basis for the referral