Biomedical subjects

Elizabeth J Want

Publications and source records attributed to Elizabeth J Want.

6 recordsLinked to original sources

PubMed2006

Solvent-dependent metabolite distribution, clustering, and protein extraction for serum profiling with mass spectrometry.

The aim of metabolite profiling is to monitor all metabolites within a biological sample for applications in basic biochemical research as well as pharmacokinetic studies and biomarker discovery. Here, novel data analysis software, XCMS, was used to monitor all metabolite features detected from an array of serum extraction methods, with application to metabolite profiling using electrospray liquid chromatography/mass spectrometry (ESI-LC/MS). The XCMS software enabled the comparison of methods with regard to reproducibility, the number and type of metabolite features detected, and the similarity of these features between different extraction methods. Extraction efficiency with regard to metabolite feature hydrophobicity was examined through the generation of unique feature density distribution plots, displaying feature distribution along chromatographic time. Hierarchical clustering was performed to highlight similarities in the metabolite features observed between the extraction methods. Protein extraction efficiency was determined using the Bradford assay, and the residual proteins were identified using nano-LC/MS/MS. Additionally, the identification of four of the most intensely ionized serum metabolites using FTMS and tandem mass spectrometry was reported. The extraction methods, ranging from organic solvents and acids to heat denaturation, varied widely in both protein removal efficiency and the number of mass spectral features detected. Methanol protein precipitation followed by centrifugation was found to be the most effective, straightforward, and reproducible approach, resulting in serum extracts containing over 2000 detected metabolite features and less than 2% residual protein. Interestingly, the combination of all approaches produced over 10,000 unique metabolite features, a number that is indicative of the complexity of the human metabolome and the potential of metabolomics in biomarker discovery.

Blood Proteins↗

PubMed2006

XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification.

Metabolite profiling in biomarker discovery, enzyme substrate assignment, drug activity/specificity determination, and basic metabolic research requires new data preprocessing approaches to correlate specific metabolites to their biological origin. Here we introduce an LC/MS-based data analysis approach, XCMS, which incorporates novel nonlinear retention time alignment, matched filtration, peak detection, and peak matching. Without using internal standards, the method dynamically identifies hundreds of endogenous metabolites for use as standards, calculating a nonlinear retention time correction profile for each sample. Following retention time correction, the relative metabolite ion intensities are directly compared to identify changes in specific endogenous metabolites, such as potential biomarkers. The software is demonstrated using data sets from a previously reported enzyme knockout study and a large-scale study of plasma samples. XCMS is freely available under an open-source license at http://metlin.scripps.edu/download/.

Algorithms↗

PubMed2006

Sepsis plasma protein profiling with immunodepletion, three-dimensional liquid chromatography tandem mass spectrometry, and spectrum counting.

Sepsis is a systemic, often fatal inflammatory response whose biochemical pathways are not fully understood and with no single biomarker capable of its reliable prediction. Increased interest in protein profiling to reveal fundamental biochemical events as well as disease diagnosis has grown considerably, largely due to advances in mass spectrometry and related front-end technologies. In this study, patients with sepsis and systemic inflammatory response syndrome (SIRS) were examined using plasma protein profiling following immunodepletion treatment to remove the most abundant proteins, serum albumin, transferrin, haptoglobin, anti-trypsin, IgG, and IgA. These proteins cause significant signal suppression, and their removal allows for lower abundance proteins to be examined through improved ion signal. Analyses after immunodepletion were performed using 3-dimensional reverse phase/strong cation exchange/reverse phase liquid chromatography with electrospray ion trap mass spectrometry (3D LC-MS/MS) and spectrum counting for comparative quantitation. The results revealed a major theme in immune system activity, including activation of the complement and coagulation pathways. Additionally, lipid transport may prove to be important in distinguishing sepsis from SIRS. Specifically, significant multi-fold changes were observed in 10 proteins and are now being investigated for the early diagnosis of sepsis.

Biomarkers↗

PubMed2005

The expanding role of mass spectrometry in metabolite profiling and characterization.

Mass spectrometry has a strong history in drug-metabolite analysis and has recently emerged as the foremost technology in endogenous metabolite research. The advantages of mass spectrometry include a wide dynamic range, the ability to observe a diverse number of molecular species, and reproducible quantitative analysis. These attributes are important in addressing the issue of metabolite profiling, as the dynamic range easily exceeds nine orders of magnitude in biofluids, and the diversity of species ranges from simple amino acids to lipids to complex carbohydrates. The goals of the application of mass spectrometry range from basic biochemistry to clinical biomarker discovery with challenges in generating a comprehensive profile, data analysis, and structurally characterizing physiologically important metabolites. The precedent for this work has already been set in neonatal screening, as blood samples from millions of neonates are tested routinely by mass spectrometry as a diagnostic tool for inborn errors of metabolism. In this review, we will discuss the background from which contemporary metabolite research emerged, the techniques involved in this exciting area, and the current and future applications of this field.

Biomarkers↗

PubMed2005

METLIN: a metabolite mass spectral database.

Endogenous metabolites have gained increasing interest over the past 5 years largely for their implications in diagnostic and pharmaceutical biomarker discovery. METLIN (http://metlin.scripps.edu), a freely accessible web-based data repository, has been developed to assist in a broad array of metabolite research and to facilitate metabolite identification through mass analysis. METLINincludes an annotated list of known metabolite structural information that is easily cross-correlated with its catalogue of high-resolution Fourier transform mass spectrometry (FTMS) spectra, tandem mass spectrometry (MS/MS) spectra, and LC/MS data.

Biomarkers↗

PubMed2004

Assignment of endogenous substrates to enzymes by global metabolite profiling.

Enzymes regulate biological processes through the conversion of specific substrates to products. Therefore, of fundamental interest for every enzyme is the elucidation of its natural substrates. Here, we describe a general strategy for identifying endogenous substrates of enzymes by untargeted liquid chromatography-mass spectrometry (LC-MS) analysis of tissue metabolomes from wild-type and enzyme-inactivated organisms. We use this method to discover several brain lipids regulated by the mammalian enzyme fatty acid amide hydrolase (FAAH) in vivo, including known signaling molecules (e.g., the endogenous cannabinoid anandamide) and a novel family of nervous system-enriched natural products, the taurine-conjugated fatty acids. Remarkably, the relative hydrolytic activity that FAAH exhibited for lipid metabolites in vitro was not predictive of the identity of specific FAAH substrates in vivo. Thus, global metabolite profiling establishes unanticipated connections between the proteome and metabolome that enable assignment of an enzyme's unique biochemical functions in vivo.

Amidohydrolases↗