Visual exploration of isotope labeling networks in 3D

(13)C Tracers for Glucose Degrading Pathway Discrimination in Gluconobacter oxydans 621H

Gluconobacter oxydans 621H is used as an industrial production organism due to its exceptional ability to incompletely oxidize a great variety of carbohydrates in the periplasm. With glucose as the carbon source, up to 90% of the initial concentration is oxidized periplasmatically to gluconate and ketogluconates. Growth on glucose is biphasic and intracellular sugar catabolism proceeds via the Entner-Doudoroff pathway (EDP) and the pentose phosphate pathway (PPP). Here we studied the in vivo contributions of the two pathways to glucose catabolism on a microtiter scale. In our approach we applied specifically (13)C labeled glucose, whereby a labeling pattern in alanine was generated intracellularly. This method revealed a dynamic growth phase-dependent pathway activity with increased activity of EDP in the first and PPP in the second growth phase, respectively. Evidence for a growth phase-independent decarboxylation-carboxylation cycle around the pyruvate node was obtained from (13)C fragmentation patterns of alanine. For the first time, down-scaled microtiter plate cultivation together with (13)C-labeled substrate was applied for G. oxydans to elucidate pathway operation, exhibiting reasonable labeling costs and allowing for sufficient replicate experiments.

High-throughput data pipelines for metabolic flux analysis in plants

In this chapter we illustrate the methodology for high-throughput metabolic flux analysis. Central to this is developing an end to end data pipeline, crucial for integrating the wet lab experiments and analytics, combining hardware and software automation, and standardizing data representation providing importers and exporters to support third party tools. The use of existing software at the start, data extraction from the chromatogram, and the end, MFA analysis, allows for the most flexibility in this workflow. Developing iMS2Flux provided a standard, extensible, platform independent tool to act as the "glue" between these end points. Most importantly this tool can be easily adapted to support different data formats, data verification and data correction steps allowing it to be central to managing the data necessary for high-throughput MFA. An additional tool was needed to automate the MFA software and in particular to take advantage of the course grained parallel nature of high-throughput analysis and available high performance computing facilities.In combination these methods show the development of high-throughput pipelines that allow metabolic flux analysis to join as a full member of the omics family.

Mass spectrometry-based metabolomics, analysis of metabolite-protein interactions, and imaging

Our understanding of biology has been greatly improved through recent developments in mass spectrometry, which is providing detailed information on protein and metabolite composition as well as protein-metabolite interactions. The high sensitivity and resolution of mass spectrometry achieved with liquid or gas chromatography allows for detection and quantification of hundreds to thousands of molecules in a single measurement. Where homogenization-based sample preparation and extraction methods result in a loss of spatial information, mass spectrometry imaging technologies provide the in situ distribution profiles of metabolites and proteins within tissues. Mass spectrometry-based analysis of metabolite abundance, protein-metabolite interactions, and spatial distribution of compounds facilitates the high-throughput screening of biochemical reactions, the reconstruction of metabolic networks, biomarker discovery, determination of tissue compositions, and functional annotation of both proteins and metabolites.

Metabolomic analysis and visualization engine for LC-MS data

Metabolomic analysis by liquid chromatography-high-resolution mass spectrometry results in data sets with thousands of features arising from metabolites, fragments, isotopes, and adducts. Here we describe a software package, Metabolomic Analysis and Visualization ENgine (MAVEN), designed for efficient interactive analysis of LC-MS data, including in the presence of isotope labeling. The software contains tools for all aspects of the data analysis process, from feature extraction to pathway-based graphical data display. To facilitate data validation, a machine learning algorithm automatically assesses peak quality. Users interact with raw data primarily in the form of extracted ion chromatograms, which are displayed with overlaid circles indicating peak quality, and bar graphs of peak intensities for both unlabeled and isotope-labeled metabolite forms. Click-based navigation leads to additional information, such as raw data for specific isotopic forms or for metabolites changing significantly between conditions. Fast data processing algorithms result in nearly delay-free browsing. Drop-down menus provide tools for the overlay of data onto pathway maps. These tools enable animating series of pathway graphs, e.g., to show propagation of labeled forms through a metabolic network. MAVEN is released under an open source license at http://maven.princeton.edu.

Hyperpolarized (13)C spectroscopy and an NMR-compatible bioreactor system for the investigation of real-time cellular metabolism

The purpose of this study was to combine a three-dimensional NMR-compatible bioreactor with hyperpolarized (13)C NMR spectroscopy in order to probe cellular metabolism in real time. JM1 (immortalized rat hepatoma) cells were cultured in a three-dimensional NMR-compatible fluidized bioreactor. (31)P spectra were acquired before and after each injection of hyperpolarized [1-(13)C] pyruvate and subsequent (13)C spectroscopy at 11.7 T. (1)H and two-dimensional (1)H-(1)H-total correlation spectroscopy spectra were acquired from extracts of cells grown in uniformly labeled (13)C-glucose, on a 16.4 T, to determine (13)C fractional enrichment and distribution of (13)C label. JM1 cells were found to have a high rate of aerobic glycolysis in both two-dimensional culture and in the bioreactor, with 85% of the (13)C label from uniformly labeled (13)C-glucose being present as either lactate or alanine after 23 h. Flux measurements of pyruvate through lactate dehydrogenase and alanine aminotransferase in the bioreactor system were 12.18 +/- 0.49 nmols/sec/10(8) cells and 2.39 +/- 0.30 nmols/sec/10(8) cells, respectively, were reproducible in the same bioreactor, and were not significantly different over the course of 2 days. Although this preliminary study involved immortalized cells, this combination of technologies can be extended to the real-time metabolic exploration of primary benign and cancerous cells and tissues prior to and after therapy.