Robustifying Experimental Tracer Design for13C-Metabolic Flux Analysis

13C metabolic flux analysis (MFA) has become an indispensable tool to measure metabolic reaction rates (fluxes) in living organisms, having an increasingly diverse range of applications. Here, the choice of the13C labeled tracer composition makes the difference between an information-rich experiment and an experiment with only limited insights. To improve the chances for an informative labeling experiment, optimal experimental design approaches have been devised for13C-MFA, all relying on some a priori knowledge about the actual fluxes. If such prior knowledge is unavailable, e.g., for research organisms and producer strains, existing methods are left with a chicken-and-egg problem. In this work, we present a general computational method, termed robustified experimental design (R-ED), to guide the decision making about suitable tracer choices when prior knowledge about the fluxes is lacking. Instead of focusing on one mixture, optimal for specific flux values, we pursue a sampling based approach and introduce a new design criterion, which characterizes the extent to which mixtures are informative in view of all possible flux values. The R-ED workflow enables the exploration of suitable tracer mixtures and provides full flexibility to trade off information and cost metrics. The potential of the R-ED workflow is showcased by applying the approach to the industrially relevant antibiotic producer Streptomyces clavuligerus, where we suggest informative, yet economic labeling strategies

The Design of FluxML: A Universal Modeling Language for 13C Metabolic Flux Analysis

13C metabolic flux analysis (MFA) is the method of choice when a detailed inference of intracellular metabolic fluxes in living organisms under metabolic quasi-steady state conditions is desired. Being continuously developed since two decades, the technology made major contributions to the quantitative characterization of organisms in all fields of biotechnology and health-related research. 13C MFA, however, stands out from other “-omics sciences,” in that it requires not only experimental-analytical data, but also mathematical models and a computational toolset to infer the quantities of interest, i.e., the metabolic fluxes. At present, these models cannot be conveniently exchanged between different labs. Here, we present the implementation-independent model description language FluxML for specifying 13C MFA models. The core of FluxML captures the metabolic reaction network together with atom mappings, constraints on the model parameters, and the wealth of data configurations. In particular, we describe the governing design processes that shaped the FluxML language. We demonstrate the utility of FluxML to represent many contemporary experimental-analytical requirements in the field of 13C MFA. The major aim of FluxML is to offer a sound, open, and future-proof language to unambiguously express and conserve all the necessary information for model re-use, exchange, and comparison. Along with FluxML, several powerful computational tools are supplied for easy handling, but also to maintain a maximum of flexibility. Altogether, the FluxML collection is an “all-around carefree package” for 13C MFA modelers. We believe that FluxML improves scientific productivity as well as transparency and therewith contributes to the efficiency and reproducibility of computational modeling efforts in the field of 13C MFA

A SAT Approach to Clique-Width

Clique-width is a graph invariant that has been widely studied in combinatorics and computer science. However, computing the clique-width of a graph is an intricate problem, the exact clique-width is not known even for very small graphs. We present a new method for computing the clique-width of graphs based on an encoding to propositional satisfiability (SAT) which is then evaluated by a SAT solver. Our encoding is based on a reformulation of clique-width in terms of partitions that utilizes an efficient encoding of cardinality constraints. Our SAT-based method is the first to discover the exact clique-width of various small graphs, including famous graphs from the literature as well as random graphs of various density. With our method we determined the smallest graphs that require a small pre-described clique-width.Comment: proofs in section 3 updated, results remain unchange

Spin decoherence and off-resonance behavior of radiofrequency-driven spin rotations in storage rings

Radiofrequency-driven resonant spin rotators are routinely used as standard instruments in polarization experiments in particle and nuclear physics. Maintaining the continuous exact parametric spin-resonance condition of the equality of the spin rotator and the spin precession frequency during operation constitutes one of the challenges. We present a detailed analytic description of the impact of detuning the exact spin resonance on the vertical and the in-plane precessing components of the polarization. An important part of the formalism presented here is the consideration of experimentally relevant spin-decoherence effects. We discuss applications of the developed formalism to the interpretation of the experimental data on the novel pilot bunch approach to control the spin-resonance condition during the operation of the radiofrequency-driven Wien filter that is used as a spin rotator in the first direct deuteron electric dipole moment measurement at COSY. We emphasize the potential importance of the hitherto unexplored phase of the envelope of the horizontal polarization as an indicator of the stability of the radiofrequency-driven spin rotations in storage rings. The work presented here serves as a satellite publication to the work published concurrently on the proof of principle experiment about the so-called pilot bunch approach that was developed to provide co-magnetometry for the deuteron electric dipole moment experiment at COSY.Comment: 31 pages, 10 figures, 5 table

Pilot bunch and co-magnetometry of polarized particles stored in a ring

In polarization experiments at storage rings, one of the challenges is to maintain the spin-resonance condition of a radio-frequency spin rotator with the spin-precessions of the orbiting particles. Time-dependent variations of the magnetic fields of ring elements lead to unwanted variations of the spin precession frequency. We report here on a solution to this problem by shielding (or masking) one of the bunches stored in the ring from the high-frequency fields of the spin rotator, so that the masked pilot bunch acts as a co-magnetometer for the other signal bunch, tracking fluctuations in the ring on a time scale of about one second. While the new method was developed primarily for searches of electric dipole moments of charged particles, it may have far-reaching implications for future spin physics facilities, such as the EIC and NICA.Comment: 5 pages, 3 figures + references + supplemental material (6 pages, 2 figures, 6 tables + references

A Pareto approach to resolve the conflict between information gain and experimental costs: Multiple-criteria design of carbon labeling experiments

Science revolves around the best way of conducting an experiment to obtain insightful results. Experiments with maximal information content can be found by computational experimental design (ED) strategies that identify optimal conditions under which to perform the experiment. Several criteria have been proposed to measure the information content, each emphasizing different aspects of the design goal, i.e., reduction of uncertainty. Where experiments are complex or expensive, second sight is at the budget governing the achievable amount of information. In this context, the design objectives cost and information gain are often incommensurable, though dependent. By casting the ED task into a multiple-criteria optimization problem, a set of trade-off designs is derived that approximates the Pareto-frontier which is instrumental for exploring preferable designs. In this work, we present a computational methodology for multiple-criteria ED of information-rich experiments that accounts for virtually any set of design criteria. The methodology is implemented for the case of 13C metabolic flux analysis (MFA), which is arguably the most expensive type among the ‘omics’ technologies, featuring dozens of design parameters (tracer composition, analytical platform, measurement selection etc.). Supported by an innovative visualization scheme, we demonstrate with two realistic showcases that the use of multiple criteria reveals deep insights into the conflicting interplay between information carriers and cost factors that are not amendable to single-objective ED. For instance, tandem mass spectrometry turns out as best-in-class with respect to information gain, while it delivers this information quality cheaper than the other, routinely applied analytical technologies. Therewith, our Pareto approach to ED offers the investigator great flexibilities in the conception phase of a study to balance costs and benefits

Oxide Formation during Transpassive Material Removal of Martensitic 42CrMo4 Steel by Electrochemical Machining

The efficiency of material removal by electrochemical machining (ECM) and rim zone modifications is highly dependent on material composition, the chemical surface condition at the break through potential, the electrolyte, the machining parameters and the resulting current densities and local current density distribution at the surfaces. The ECM process is mechanistically determined by transpassive anodic metal dissolution and layer formation at high voltages and specific electrolytic compositions. The mechanisms of transpassive anodic metal dissolution and oxide formation are not fully understood yet for steels such as 42CrMo4. Therefore, martensitic 42CrMo4 was subjected to ECM in sodium nitrate solution with two different current densities and compared to the native oxide of ground 42CrMo4. The material removal rate as well as anodic dissolution and transpassive oxide formation were investigated by mass spectroscopic analysis (ICP-MS) and (angle-resolved) X-ray photoelectron spectroscopy ((AR)XPS) after ECM. The results revealed the formation of a Fe3−xO4 mixed oxide and a change of the oxidation state for iron, chromium and molybdenum, e.g., 25% Fe (II) was present in the oxide at 20.6 A/cm2 and was substituted by Fe (III) at 34.0 A/cm2 to an amount of 10% Fe (II). Furthermore, ECM processing of 42CrMo4 in sodium nitrate solution was strongly determined by a stationary process with two parallel running steps: 1. Transpassive Fe3−xO4 mixed oxide formation/repassivation; as well as 2. dissolution of the transpassive oxide at the metal surface

A pathogen-specific isotope tracing approach reveals metabolic activities and fluxes of intracellular Salmonella.

Pathogenic bacteria proliferating inside mammalian host cells need to rapidly adapt to the intracellular environment. How they achieve this and scavenge essential nutrients from the host has been an open question due to the difficulties in distinguishing between bacterial and host metabolites in situ. Here, we capitalized on the inability of mammalian cells to metabolize mannitol to develop a stable isotopic labeling approach to track Salmonella enterica metabolites during intracellular proliferation in host macrophage and epithelial cells. By measuring label incorporation into Salmonella metabolites with liquid chromatography-mass spectrometry (LC-MS), and combining it with metabolic modeling, we identify relevant carbon sources used by Salmonella, uncover routes of their metabolization, and quantify relative reaction rates in central carbon metabolism. Our results underline the importance of the Entner-Doudoroff pathway (EDP) and the phosphoenolpyruvate carboxylase for intracellularly proliferating Salmonella. More broadly, our metabolic labeling strategy opens novel avenues for understanding the metabolism of pathogens inside host cells