Biomedical subjects

Karl-Heinz Ott

Publications and source records attributed to Karl-Heinz Ott.

3 recordsLinked to original sources

PubMed2007

Nuclear magnetic resonance metabonomics: methods for drug discovery and development.

Nuclear magnetic resonance (NMR)-based metabonomics is gaining popularity in drug discovery and development and in academia in a variety of settings, ranging from toxicology, preclinical, and clinical approaches to nutrition research, studies on microorganisms, and research on plants. This chapter focuses on the basic steps in a metabonomics study and emphasizes experience and lessons learned in our lab where we focused on metabonomic analyses of plant extracts, cell lines, and a variety of animal tissues and biofluids. We emphasize that a comprehensive and suitable study design is pivotal for a correct biological interpretation of the results, as well as highly controlled experimental conditions. Sample preparation and NMR protocols are detailed for a wide range of sample types. We discuss alternative data processing strategies and considerations for a general data analysis approach, paying particular attention to the statistical interpretation and validation of the results while also highlighting approaches to avoid possible pitfalls resulting from systematic and random errors. A tutorial written for the R statistical package and other small utilities are available from the authors upon request.

Animals↗

PubMed2006

Metabolomic analysis using optimized NMR and statistical methods.

NMR-based metabolomics requires robust automated methodologies, and the accuracy of NMR-based metabolomics data is greatly influenced by the reproducibility of data acquisition and processing methods. Effective water resonance signal suppression and reproducible spectral phasing and baseline traces across series of related samples are crucial for statistical analysis. We assess robustness, repeatability, sensitivity, selectivity, and practicality of commonly used solvent peak suppression methods in the NMR analysis of biofluids with respect to the automated processing of the NMR spectra and the impact of pulse sequence and data processing methods on the sensitivity of pattern recognition and statistical analysis of the metabolite profiles. We introduce two modifications to the excitation sculpting pulse sequence whereby the excitation solvent suppression pulse cascade is preceded by low-power water resonance presaturation pulses during the relaxation delay. Our analysis indicates that combining water presaturation with excitation sculpting water suppression delivers the most reproducible and information-rich NMR spectra of biofluids.

Animals↗

PubMed2003

Metabonomics classifies pathways affected by bioactive compounds. Artificial neural network classification of NMR spectra of plant extracts.

The biochemical mode-of-action (MOA) for herbicides and other bioactive compounds can be rapidly and simultaneously classified by automated pattern recognition of the metabonome that is embodied in the 1H NMR spectrum of a crude plant extract. The ca. 300 herbicides that are used in agriculture today affect less than 30 different biochemical pathways. In this report, 19 of the most interesting MOAs were automatically classified. Corn (Zea mays) plants were treated with various herbicides such as imazethapyr, glyphosate, sethoxydim, and diuron, which represent various biochemical modes-of-action such as inhibition of specific enzymes (acetohydroxy acid synthase [AHAS], protoporphyrin IX oxidase [PROTOX], 5-enolpyruvylshikimate-3-phosphate synthase [EPSPS], acetyl CoA carboxylase [ACC-ase], etc.), or protein complexes (photosystems I and II), or major biological process such as oxidative phosphorylation, auxin transport, microtubule growth, and mitosis. Crude isolates from the treated plants were subjected to 1H NMR spectroscopy, and the spectra were classified by artificial neural network analysis to discriminate the herbicide modes-of-action. We demonstrate the use and refinement of the method, and present cross-validated assignments for the metabolite NMR profiles of over 400 plant isolates. The MOA screen also recognizes when a new mode-of-action is present, which is considered extremely important for the herbicide discovery process, and can be used to study deviations in the metabolism of compounds from a chemical synthesis program. The combination of NMR metabolite profiling and neural network classification is expected to be similarly relevant to other metabonomic profiling applications, such as in drug discovery.

Herbicides↗