Steven Robinette - Academia.edu (original) (raw)

Papers by Steven Robinette

Research paper thumbnail of Nephrocalcinosis (Enamel Renal Syndrome) Caused by Autosomal Recessive FAM20A Mutations

Nephron Physiology, 2012

Calcium homeostasis requires regulated cellular and interstitial systems interacting to modulate ... more Calcium homeostasis requires regulated cellular and interstitial systems interacting to modulate the activity and movement of this ion. Disruption of these systems in the kidney results in nephrocalcinosis and nephrolithiasis, important medical problems whose pathogenesis is incompletely understood. We investigated 25 patients from 16 families with unexplained nephrocalcinosis and characteristic dental defects (amelogenesis imperfecta, gingival hyperplasia, impaired tooth eruption). To identify the causative gene, we performed genome-wide linkage analysis, exome capture, next-generation sequencing, and Sanger sequencing. All patients had bi-allelic FAM20A mutations segregating with the disease; 20 different mutations were identified. This autosomal recessive disorder, also known as enamel renal syndrome, of FAM20A causes nephrocalcinosis and amelogenesis imperfecta. We speculate that all individuals with biallelic FAM20A mutations will eventually show nephrocalcinosis.

Research paper thumbnail of Cluster Analysis Statistical Spectroscopy Using Nuclear Magnetic Resonance Generated Metabolic Data Sets from Perturbed Biological Systems

Analytical Chemistry, 2009

| Supporting Info • Full Text HTML • Hi-Res PDF[4779K] • PDF w/ Links[358K] Abstract • Full Text ... more | Supporting Info • Full Text HTML • Hi-Res PDF[4779K] • PDF w/ Links[358K] Abstract • Full Text HTML • Hi-Res PDF[4325K] Abstract • Full Text HTML • Hi-Res PDF[1067K] Abstract Stay Current Get your research ASAP. e-Alerts | RSS Feeds Advertisements Abstract • Full Text HTML • Hi-Res PDF[2869K] Abstract • Full Text HTML • Hi-Res PDF[1299K] • PDF w/ Links[230K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[658K] • PDF w/ Links[194K] Abstract • Full Text HTML • Hi-Res PDF[1360K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[574K] • PDF w/ Links[263K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[4623K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[1081K] • PDF w/ Links[213K] Abstract • Full Text HTML • Hi-Res PDF[8941K] Abstract • Full Text HTML • Hi-Res PDF[3868K] • PDF w/ Links[431K] Abstract • Full Text HTML • Hi-Res PDF[360K] • PDF w/ Links[223K] Abstract • Full Text HTML • Hi-Res PDF[680K] Abstract • Full Text HTML • Hi-Res PDF[618K] Abstract • Full Text HTML • Hi-Res PDF[578K] Abstract • Full Text HTML • Hi-Res PDF[1280K] Abstract • Full Text HTML • Hi-Res PDF[386K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[280K] Abstract • Full Text HTML • Hi-Res PDF[934K] Abstract • Full Text HTML Abstract • Full Text HTML • Hi-Res PDF[484K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[1091K] Abstract • Full Text HTML • Hi-Res PDF[208K] Abstract • Full Text HTML Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[522K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[3418K] • PDF w/ Links[369K] Sponsored Access Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[3609K] • PDF w/ Links[481K] Abstract | Supporting Info Abstract • Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[2923K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[1528K] Abstract • Full Text HTML • Hi-Res PDF[1441K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[1932K] • PDF w/ Links[363K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[3971K] Abstract • Full Text HTML • Hi-Res PDF[503K] • PDF w/ Links[170K] Abstract • Full Text HTML •

Research paper thumbnail of MetaboNetworks, an interactive Matlab-based toolbox for creating, customizing and exploring sub-networks from KEGG

Bioinformatics, 2014

MetaboNetworks is a tool to create custom sub-networks in Matlab using main reaction pairs as def... more MetaboNetworks is a tool to create custom sub-networks in Matlab using main reaction pairs as defined by the Kyoto Encyclopaedia of Genes and Genomes and can be used to explore transgenomic interactions, for example mammalian and bacterial associations. It calculates the shortest path between a set of metabolites (e.g. biomarkers from a metabonomic study) and plots the connectivity between metabolites as links in a network graph. The resulting graph can be edited and explored interactively. Furthermore, nodes and edges in the graph are linked to the Kyoto Encyclopaedia of Genes and Genomes compound and reaction pair web pages. Availability and implementation: MetaboNetworks is available from

Research paper thumbnail of Metabonomics of Newborn Screening Dried Blood Spot Samples: A Novel Approach in the Screening and Diagnostics of Inborn Errors of Metabolism

Analytical Chemistry, 2012

A novel, single stage high resolution mass spectrometry-based method is presented for the populat... more A novel, single stage high resolution mass spectrometry-based method is presented for the population level screening of inborn errors of metabolism. The approach proposed here extends traditional electrospray tandem mass spectrometry screening by introducing nanospray ionization and high resolution mass spectrometry, allowing the selective detection of more than 400 individual metabolic constituents of blood including acylcarnitines, amino acids, organic acids, fatty acids, carbohydrates, bile acids, and complex lipids. Dried blood spots were extracted using a methanolic solution of isotope labeled internal standards, and filtered extracts were electrosprayed using a fully automated chip-based nanospray ion source in both positive and negative ion mode. Ions were analyzed using an Orbitrap Fourier transformation mass spectrometer at nominal mass resolution of 100,000. Individual metabolic constituents were quantified using standard isotope dilution methods. Concentration threshold (cutoff) level-based analysis allows the identification of newborns with metabolic diseases, similarly to the traditional electrospray tandem mass spectrometry (ESI-MS/MS) method; however, the detection of additional known biomarkers (e.g., organic acids) results in improved sensitivity and selectivity. The broad range of detected analytes allowed the untargeted multivariate statistical analysis of spectra and identification of additional diseased states, therapeutic artifacts, and damaged samples, besides the metabolic disease panel.

Research paper thumbnail of Mistargeting of Peroxisomal EHHADH and Inherited Renal Fanconi's Syndrome

New England Journal of Medicine, 2014

In renal Fanconi&... more In renal Fanconi's syndrome, dysfunction in proximal tubular cells leads to renal losses of water, electrolytes, and low-molecular-weight nutrients. For most types of isolated Fanconi's syndrome, the genetic cause and underlying defect remain unknown. We clinically and genetically characterized members of a five-generation black family with isolated autosomal dominant Fanconi's syndrome. We performed genomewide linkage analysis, gene sequencing, biochemical and cell-biologic investigations of renal proximal tubular cells, studies in knockout mice, and functional evaluations of mitochondria. Urine was studied with the use of proton nuclear magnetic resonance ((1)H-NMR) spectroscopy. We linked the phenotype of this family's Fanconi's syndrome to a single locus on chromosome 3q27, where a heterozygous missense mutation in EHHADH segregated with the disease. The p.E3K mutation created a new mitochondrial targeting motif in the N-terminal portion of EHHADH, an enzyme that is involved in peroxisomal oxidation of fatty acids and is expressed in the proximal tubule. Immunocytofluorescence studies showed mistargeting of the mutant EHHADH to mitochondria. Studies of proximal tubular cells revealed impaired mitochondrial oxidative phosphorylation and defects in the transport of fluids and a glucose analogue across the epithelium. (1)H-NMR spectroscopy showed elevated levels of mitochondrial metabolites in urine from affected family members. Ehhadh knockout mice showed no abnormalities in renal tubular cells, a finding that indicates a dominant negative nature of the mutation rather than haploinsufficiency. Mistargeting of peroxisomal EHHADH disrupts mitochondrial metabolism and leads to renal Fanconi's syndrome; this indicates a central role of mitochondria in proximal tubular function. The dominant negative effect of the mistargeted protein adds to the spectrum of monogenic mechanisms of Fanconi's syndrome. (Funded by the European Commission Seventh Framework Programme and others.).

Research paper thumbnail of Optimized Preprocessing of Ultra-Performance Liquid Chromatography/Mass Spectrometry Urinary Metabolic Profiles for Improved Information Recovery

Analytical Chemistry, 2011

Ultra-performance liquid chromatography coupled to mass spectrometry (UPLC/MS) has been used incr... more Ultra-performance liquid chromatography coupled to mass spectrometry (UPLC/MS) has been used increasingly for measuring changes of low molecular weight metabolites in biofluids/tissues in response to biological challenges such as drug toxicity and disease processes. Typically samples show high variability in concentration, and the derived metabolic profiles have a heteroscedastic noise structure characterized by increasing variance as a function of increased signal intensity. These sources of experimental and instrumental noise substantially complicate information recovery when statistical tools are used. We apply and compare several preprocessing procedures and introduce a statistical error model to account for these bioanalytical complexities. In particular, the use of total intensity, median fold change, locally weighted scatter plot smoothing, and quantile normalizations to reduce extraneous variance induced by sample dilution were compared. We demonstrate that the UPLC/MS peak intensities of urine samples should respond linearly to variable sample dilution across the intensity range. While all four studied normalization methods performed reasonably well in reducing dilution-induced variation of urine samples in the absence of biological variation, the median fold change normalization is least compromised by the biologically relevant changes in mixture components and is thus preferable. Additionally, the application of a subsequent log-based transformation was successful in stabilizing the variance with respect to peak intensity, confirming the predominant influence of multiplicative noise in peak intensities from UPLC/MS-derived metabolic profile data sets. We demonstrate that variance-stabilizing transformation and normalization are critical preprocessing steps that can benefit greatly metabolic information recovery from such data sets when widely applied chemometric methods are used.

Research paper thumbnail of NMR in Metabolomics and Natural Products Research: Two Sides of the Same Coin

Accounts of Chemical Research, 2012

S mall molecules are central to biology, mediating critical phenomena such as metabolism, signal ... more S mall molecules are central to biology, mediating critical phenomena such as metabolism, signal transduction, mating attraction, and chemical defense. The traditional categories that define small molecules, such as metabolite, secondary metabolite, pheromone, hormone, and so forth, often overlap, and a single compound can appear under more than one functional heading. Therefore, we favor a unifying term, biogenic small molecules (BSMs), to describe any small molecule from a biological source.

Research paper thumbnail of Web Server Based Complex Mixture Analysis by NMR

Analytical Chemistry, 2008

Comprehensive metabolite identification and quantification of complex biological mixtures are cen... more Comprehensive metabolite identification and quantification of complex biological mixtures are central aspects of metabolomics. NMR shows excellent promise for these tasks. An automated fingerprinting strategy is presented, termed COLMAR query, which screens NMR chemical shift lists or raw 1D NMR cross sections taken from covariance total correlation spectroscopy (TOCSY) spectra or other multidimensional NMR spectra against an NMR spectral database. Cross peaks are selected using local clustering to avoid ambiguities between chemical shifts and scalar J-coupling effects. With the use of three different algorithms, the corresponding chemical shift list is then screened against chemical shift lists extracted from 1D spectra of a NMR database. The resulting query scores produced by forward assignment, reverse assignment, and bipartite weighted-matching algorithms are combined into a consensus score, which provides a robust means for identifying the correct compound. The approach is demonstrated for a metabolite model mixture that is screened against the metabolomics BioMagResDatabank (BMRB). This NMR-based compound identification approach has been implemented in a public Web server that allows the efficient analysis of a wide range of metabolite mixtures.

Research paper thumbnail of Statistical Spectroscopic Tools for Biomarker Discovery and Systems Medicine

Analytical Chemistry, 2013

Metabolic profiling based on comparative, statistical analysis of NMR spectroscopic and mass spec... more Metabolic profiling based on comparative, statistical analysis of NMR spectroscopic and mass spectrometric data from complex biological samples has contributed to increased understanding of the role of small molecules in affecting and indicating biological processes. To enable this research, the development of statistical spectroscopy has been marked by early beginnings in applying pattern recognition to nuclear magnetic resonance data and the introduction of statistical total correlation spectroscopy (STOCSY) as a tool for biomarker identification in the past decade. Extensions of statistical spectroscopy now compose a family of related tools used for compound identification, data preprocessing, and metabolic pathway analysis. In this Perspective, we review the theory and current state of research in statistical spectroscopy and discuss the growing applications of these tools to medicine and systems biology. We also provide perspectives on how recent institutional initiatives are providing new platforms for the development and application of statistical spectroscopy tools and driving the development of integrated "systems medicine" approaches in which clinical decision making is supported by statistical and computational analysis of metabolic, phenotypic, and physiological data.

Research paper thumbnail of Web server suite for complex mixture analysis by covariance NMR

Magnetic Resonance in Chemistry, 2009

Elucidation of the chemical composition of biological samples is a main focus of systems biology ... more Elucidation of the chemical composition of biological samples is a main focus of systems biology and metabolomics. Their comprehensive study requires reliable, efficient, and automatable methods to identify and quantify the underlying metabolites. Because nuclear magnetic resonance (NMR) spectroscopy is a rich source of molecular information, it has a unique potential for this task. Here we present a suite of public web servers (http://spinportal.magnet.fsu.edu), termed COLMAR, which facilitates complex mixture analysis by NMR. The COLMAR web portal presently consists of three servers: COLMAR covariance calculates the covariance NMR spectrum from an NMR input dataset, such as a TOCSY spectrum; COLMAR DemixC method decomposes the 2D covariance TOCSY spectrum into a reduced set of nonredundant 1D cross sections or traces, which belong to individual mixture components; and COLMAR query screens the traces against a NMR spectral database to identify individual compounds. Examples are presented that illustrate the utility of this web server suite for complex mixture analysis.

Research paper thumbnail of Hierarchical Alignment and Full Resolution Pattern Recognition of 2D NMR Spectra: Application to Nematode Chemical Ecology

Analytical Chemistry, 2011

Nuclear magnetic resonance (NMR) is the most widely used nondestructive technique in analytical c... more Nuclear magnetic resonance (NMR) is the most widely used nondestructive technique in analytical chemistry. In recent years, it has been applied to metabolic profiling due to its high reproducibility, capacity for relative and absolute quantification, atomic resolution, and ability to detect a broad range of compounds in an untargeted manner. While one-dimensional (1D) 1 H NMR experiments are popular in metabolic profiling due to their simplicity and fast acquisition times, two-dimensional (2D) NMR spectra offer increased spectral resolution as well as atomic correlations, which aid in the assignment of known small molecules and the structural elucidation of novel compounds. Given the small number of statistical analysis methods for 2D NMR spectra, we developed a new approach for the analysis, information recovery, and display of 2D NMR spectral data. We present a native 2D peak alignment algorithm we term HATS, for hierarchical alignment of two-dimensional spectra, enabling pattern recognition (PR) using full-resolution spectra. Principle component analysis (PCA) and partial least squares (PLS) regression of full resolution total correlation spectroscopy (TOCSY) spectra greatly aid the assignment and interpretation of statistical pattern recognition results by producing back-scaled loading plots that look like traditional TOCSY spectra but incorporate qualitative and quantitative biological information of the resonances. The HATS-PR methodology is demonstrated here using multiple 2D TOCSY spectra of the exudates from two nematode species: Pristionchus pacificus and Panagrellus redivivus. We show the utility of this integrated approach with the rapid, semiautomated assignment of small molecules differentiating the two species and the identification of spectral regions suggesting the presence of species-specific compounds. These results demonstrate that the combination of 2D NMR spectra with full-resolution statistical analysis provides a platform for chemical and biological studies in cellular biochemistry, metabolomics, and chemical ecology. N uclear magnetic resonance (NMR) is a powerful and almost universal detector due to its ability to analyze essentially all types of molecules at atomic resolution. Recently, it has been applied extensively to metabolic profiling in studies of human and animal biofluids, 1,2 cellular biochemistry, 3,4 and nonmammalian chemical ecology. 5-8 While one-dimensional (1D) 1 H NMR spectra have been used in the majority of NMR-based metabolic profiling studies, resonance overlap and lack of structural correlations can limit the utility of the 1D approach. In contrast, powerful multidimensional NMR methods are routinely used in structural biology and natural products studies 9 but have been used much less frequently for metabolomics. Two dimensional (2D) homonuclear (such as total correlation spectroscopy (TOCSY) and correlation spectroscopy (COSY)) and heteronuclear (such as heteronuclear single quantum coherence (HSQC) and heteronuclear multiple-bond correlation (HMBC)) spectra offer increased dispersion of signals in two dimensions that can overcome the problem of signal overlap, which often limits the use of 1D 1 H NMR spectra. Additionally, the information provided by these 2D experiments through specific atomic correlations can assist in the identification and assignment of known molecules and the structural elucidation of unknown small molecules that may be significant to the underlying biology. The presence of novel, uncharacterized small molecules in complex biological mixtures is a frequent occurrence, especially in nonmammalian metabolomics where a priori knowledge of the metabolome is often incomplete. Even when complex biological mixtures are composed mainly of known metabolites, the assignment of a large number of spectral peaks is a significant complication for metabolic profiling. The use of 2D correlation

Research paper thumbnail of Non-negative matrix factorization of two-dimensional NMR spectra: Application to complex mixture analysis

The Journal of Chemical Physics, 2008

A central problem in the emerging field of metabolomics is how to identify the compounds comprisi... more A central problem in the emerging field of metabolomics is how to identify the compounds comprising a chemical mixture of biological origin. NMR spectroscopy can greatly assist in this identification process, by means of multi-dimensional correlation spectroscopy, particularly total correlation spectroscopy (TOCSY). This Communication demonstrates how non-negative matrix factorization (NMF) provides an efficient means of data reduction and clustering of TOCSY spectra for the identification of unique traces representing the NMR spectra of individual compounds. The method is applied to a metabolic mixture whose compounds could be unambiguously identified by peak matching of NMF components against the BMRB metabolomics database.

Research paper thumbnail of Genetic determinants of metabolism in health and disease: from biochemical genetics to genome-wide associations

Genome Medicine, 2012

consequences in functional genomics, microbial metagenomics and disease modeling, the early resul... more consequences in functional genomics, microbial metagenomics and disease modeling, the early results and implications of which are reviewed.

Research paper thumbnail of Cluster Analysis Statistical Spectroscopy Using Nuclear Magnetic Resonance Generated Metabolic Data Sets from Perturbed Biological Systems

Analytical Chemistry, 2009

| Supporting Info • Full Text HTML • Hi-Res PDF[4779K] • PDF w/ Links[358K] Abstract • Full Text ... more | Supporting Info • Full Text HTML • Hi-Res PDF[4779K] • PDF w/ Links[358K] Abstract • Full Text HTML • Hi-Res PDF[4325K] Abstract • Full Text HTML • Hi-Res PDF[1067K] Abstract Stay Current Get your research ASAP. e-Alerts | RSS Feeds Advertisements Abstract • Full Text HTML • Hi-Res PDF[2869K] Abstract • Full Text HTML • Hi-Res PDF[1299K] • PDF w/ Links[230K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[658K] • PDF w/ Links[194K] Abstract • Full Text HTML • Hi-Res PDF[1360K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[574K] • PDF w/ Links[263K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[4623K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[1081K] • PDF w/ Links[213K] Abstract • Full Text HTML • Hi-Res PDF[8941K] Abstract • Full Text HTML • Hi-Res PDF[3868K] • PDF w/ Links[431K] Abstract • Full Text HTML • Hi-Res PDF[360K] • PDF w/ Links[223K] Abstract • Full Text HTML • Hi-Res PDF[680K] Abstract • Full Text HTML • Hi-Res PDF[618K] Abstract • Full Text HTML • Hi-Res PDF[578K] Abstract • Full Text HTML • Hi-Res PDF[1280K] Abstract • Full Text HTML • Hi-Res PDF[386K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[280K] Abstract • Full Text HTML • Hi-Res PDF[934K] Abstract • Full Text HTML Abstract • Full Text HTML • Hi-Res PDF[484K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[1091K] Abstract • Full Text HTML • Hi-Res PDF[208K] Abstract • Full Text HTML Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[522K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[3418K] • PDF w/ Links[369K] Sponsored Access Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[3609K] • PDF w/ Links[481K] Abstract | Supporting Info Abstract • Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[2923K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[1528K] Abstract • Full Text HTML • Hi-Res PDF[1441K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[1932K] • PDF w/ Links[363K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[3971K] Abstract • Full Text HTML • Hi-Res PDF[503K] • PDF w/ Links[170K] Abstract • Full Text HTML •

Research paper thumbnail of Self-Consistent Metabolic Mixture Analysis by Heteronuclear NMR. Application to a Human Cancer Cell Line

Analytical Chemistry, 2008

Elucidation of the chemical composition of biological samples is a main focus of systems biology ... more Elucidation of the chemical composition of biological samples is a main focus of systems biology and metabolomics. In order to comprehensively study these complex mixtures, reliable, efficient, and automatable methods are needed to identify and quantify the underlying metabolites and natural products. Because of its rich information content, nuclear magnetic resonance (NMR) spectroscopy has a unique potential for this task. Here we present a generalization of the recently introduced homonuclear TOCSY-based DemixC method to heteronuclear HSQC-TOCSY NMR spectroscopy. The approach takes advantage of the high resolution afforded along the (13)C dimension due to the narrow (13)C line widths for the identification of spin systems and compounds. The method combines information from both 1D (13)C and (1)H traces by querying them against an NMR spectral database using our COLMAR query web server. The complementarity of (13)C and (1)H spectral information improves the robustness of compound identification. The method is demonstrated for a metabolic model mixture and is then applied to an extract from DU145 human prostate cancer cells.

Research paper thumbnail of Bacterial Attraction and Quorum Sensing Inhibition in Caenorhabditis elegans Exudates

Journal of Chemical Ecology, 2009

Caenorhabditis elegans, a bacterivorous nematode, lives in complex rotting fruit, soil, and compo... more Caenorhabditis elegans, a bacterivorous nematode, lives in complex rotting fruit, soil, and compost environments, and chemical interactions are required for mating, monitoring population density, recognition of food, avoidance of pathogenic microbes, and other essential ecological functions. Despite being one of the best-studied model organisms in biology, relatively little is known about the signals that C. elegans uses to interact chemically with its environment or as defense. C. elegans exudates were analyzed by using several analytical methods and found to Author contributions Fatma Kaplan and Dayakar V. Badri contributed equally and led the study; Fatma Kaplan, Aaron T. Dossey, Ramadan Ajredini, Hans Alborn and Michael Stadler intellectually contributed to the worm exudate protocol which was developed in the ASE laboratory; Fatma Kaplan, Ramadan Ajredini, and Rathika Nimalendran collected exudates; Dayakar V. Badri conducted bacterial bioassays; Hans Alborn collected LC-MS data; Fatma Kaplan and Cherian Zachariah collected NMR data; Fengli Zhang, Steven L. Robinette and Rafael Brüschweiler did COLMAR analysis; Fatma Kaplan, Cherian Zachariah, Michael Stadler, and Aaron T. Dossey manually analyzed NMR data. Sanja Roje and Francisco Sandoval analyzed amino acids by HPLC; Lanfang H. Levine analyzed young adult exudates by GC-MS; Wei Zhao did principle component analysis; Fatma Kaplan, Dayakar V. Badri, Arthur S. Edison and Jorge M. Vivanco analyzed the data and wrote the paper with help from the entire team.

Research paper thumbnail of 2D NMR-Based Metabolomics Uncovers Interactions between Conserved Biochemical Pathways in the Model Organism Caenorhabditis elegans

ACS Chemical Biology, 2013

Ascarosides are small-molecule signals that play a central role in C. elegans biology, including ... more Ascarosides are small-molecule signals that play a central role in C. elegans biology, including dauer formation, aging, and social behaviors, but many aspects of their biosynthesis remain unknown. Using automated 2D NMRbased comparative metabolomics, we identified ascaroside ethanolamides as shunt metabolites in C. elegans mutants of daf-22, a gene with homology to mammalian 3-ketoacyl-CoA thiolases predicted to function in conserved peroxisomal lipid βoxidation. Two groups of ethanolamides feature β-keto functionalization confirming the predicted role of daf-22 in ascaroside biosynthesis, whereas α-methyl substitution points to unexpected inclusion of methylmalonate at a late stage in the biosynthesis of long-chain fatty acids in C. elegans. We show that ascaroside ethanolamide formation in response to defects in daf-22 and other peroxisomal genes is associated with severe depletion of endocannabinoid pools. These results indicate unexpected interaction between peroxisomal lipid β-oxidation and the biosynthesis of endocannabinoids, which are major regulators of lifespan in C. elegans. Our study demonstrates the utility of unbiased comparative metabolomics for investigating biochemical networks in metazoans.

Research paper thumbnail of Nephrocalcinosis (Enamel Renal Syndrome) Caused by Autosomal Recessive FAM20A Mutations

Nephron Physiology, 2012

Calcium homeostasis requires regulated cellular and interstitial systems interacting to modulate ... more Calcium homeostasis requires regulated cellular and interstitial systems interacting to modulate the activity and movement of this ion. Disruption of these systems in the kidney results in nephrocalcinosis and nephrolithiasis, important medical problems whose pathogenesis is incompletely understood. We investigated 25 patients from 16 families with unexplained nephrocalcinosis and characteristic dental defects (amelogenesis imperfecta, gingival hyperplasia, impaired tooth eruption). To identify the causative gene, we performed genome-wide linkage analysis, exome capture, next-generation sequencing, and Sanger sequencing. All patients had bi-allelic FAM20A mutations segregating with the disease; 20 different mutations were identified. This autosomal recessive disorder, also known as enamel renal syndrome, of FAM20A causes nephrocalcinosis and amelogenesis imperfecta. We speculate that all individuals with biallelic FAM20A mutations will eventually show nephrocalcinosis.

Research paper thumbnail of Cluster Analysis Statistical Spectroscopy Using Nuclear Magnetic Resonance Generated Metabolic Data Sets from Perturbed Biological Systems

Analytical Chemistry, 2009

| Supporting Info • Full Text HTML • Hi-Res PDF[4779K] • PDF w/ Links[358K] Abstract • Full Text ... more | Supporting Info • Full Text HTML • Hi-Res PDF[4779K] • PDF w/ Links[358K] Abstract • Full Text HTML • Hi-Res PDF[4325K] Abstract • Full Text HTML • Hi-Res PDF[1067K] Abstract Stay Current Get your research ASAP. e-Alerts | RSS Feeds Advertisements Abstract • Full Text HTML • Hi-Res PDF[2869K] Abstract • Full Text HTML • Hi-Res PDF[1299K] • PDF w/ Links[230K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[658K] • PDF w/ Links[194K] Abstract • Full Text HTML • Hi-Res PDF[1360K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[574K] • PDF w/ Links[263K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[4623K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[1081K] • PDF w/ Links[213K] Abstract • Full Text HTML • Hi-Res PDF[8941K] Abstract • Full Text HTML • Hi-Res PDF[3868K] • PDF w/ Links[431K] Abstract • Full Text HTML • Hi-Res PDF[360K] • PDF w/ Links[223K] Abstract • Full Text HTML • Hi-Res PDF[680K] Abstract • Full Text HTML • Hi-Res PDF[618K] Abstract • Full Text HTML • Hi-Res PDF[578K] Abstract • Full Text HTML • Hi-Res PDF[1280K] Abstract • Full Text HTML • Hi-Res PDF[386K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[280K] Abstract • Full Text HTML • Hi-Res PDF[934K] Abstract • Full Text HTML Abstract • Full Text HTML • Hi-Res PDF[484K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[1091K] Abstract • Full Text HTML • Hi-Res PDF[208K] Abstract • Full Text HTML Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[522K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[3418K] • PDF w/ Links[369K] Sponsored Access Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[3609K] • PDF w/ Links[481K] Abstract | Supporting Info Abstract • Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[2923K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[1528K] Abstract • Full Text HTML • Hi-Res PDF[1441K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[1932K] • PDF w/ Links[363K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[3971K] Abstract • Full Text HTML • Hi-Res PDF[503K] • PDF w/ Links[170K] Abstract • Full Text HTML •

Research paper thumbnail of MetaboNetworks, an interactive Matlab-based toolbox for creating, customizing and exploring sub-networks from KEGG

Bioinformatics, 2014

MetaboNetworks is a tool to create custom sub-networks in Matlab using main reaction pairs as def... more MetaboNetworks is a tool to create custom sub-networks in Matlab using main reaction pairs as defined by the Kyoto Encyclopaedia of Genes and Genomes and can be used to explore transgenomic interactions, for example mammalian and bacterial associations. It calculates the shortest path between a set of metabolites (e.g. biomarkers from a metabonomic study) and plots the connectivity between metabolites as links in a network graph. The resulting graph can be edited and explored interactively. Furthermore, nodes and edges in the graph are linked to the Kyoto Encyclopaedia of Genes and Genomes compound and reaction pair web pages. Availability and implementation: MetaboNetworks is available from

Research paper thumbnail of Metabonomics of Newborn Screening Dried Blood Spot Samples: A Novel Approach in the Screening and Diagnostics of Inborn Errors of Metabolism

Analytical Chemistry, 2012

A novel, single stage high resolution mass spectrometry-based method is presented for the populat... more A novel, single stage high resolution mass spectrometry-based method is presented for the population level screening of inborn errors of metabolism. The approach proposed here extends traditional electrospray tandem mass spectrometry screening by introducing nanospray ionization and high resolution mass spectrometry, allowing the selective detection of more than 400 individual metabolic constituents of blood including acylcarnitines, amino acids, organic acids, fatty acids, carbohydrates, bile acids, and complex lipids. Dried blood spots were extracted using a methanolic solution of isotope labeled internal standards, and filtered extracts were electrosprayed using a fully automated chip-based nanospray ion source in both positive and negative ion mode. Ions were analyzed using an Orbitrap Fourier transformation mass spectrometer at nominal mass resolution of 100,000. Individual metabolic constituents were quantified using standard isotope dilution methods. Concentration threshold (cutoff) level-based analysis allows the identification of newborns with metabolic diseases, similarly to the traditional electrospray tandem mass spectrometry (ESI-MS/MS) method; however, the detection of additional known biomarkers (e.g., organic acids) results in improved sensitivity and selectivity. The broad range of detected analytes allowed the untargeted multivariate statistical analysis of spectra and identification of additional diseased states, therapeutic artifacts, and damaged samples, besides the metabolic disease panel.

Research paper thumbnail of Mistargeting of Peroxisomal EHHADH and Inherited Renal Fanconi's Syndrome

New England Journal of Medicine, 2014

In renal Fanconi&... more In renal Fanconi's syndrome, dysfunction in proximal tubular cells leads to renal losses of water, electrolytes, and low-molecular-weight nutrients. For most types of isolated Fanconi's syndrome, the genetic cause and underlying defect remain unknown. We clinically and genetically characterized members of a five-generation black family with isolated autosomal dominant Fanconi's syndrome. We performed genomewide linkage analysis, gene sequencing, biochemical and cell-biologic investigations of renal proximal tubular cells, studies in knockout mice, and functional evaluations of mitochondria. Urine was studied with the use of proton nuclear magnetic resonance ((1)H-NMR) spectroscopy. We linked the phenotype of this family's Fanconi's syndrome to a single locus on chromosome 3q27, where a heterozygous missense mutation in EHHADH segregated with the disease. The p.E3K mutation created a new mitochondrial targeting motif in the N-terminal portion of EHHADH, an enzyme that is involved in peroxisomal oxidation of fatty acids and is expressed in the proximal tubule. Immunocytofluorescence studies showed mistargeting of the mutant EHHADH to mitochondria. Studies of proximal tubular cells revealed impaired mitochondrial oxidative phosphorylation and defects in the transport of fluids and a glucose analogue across the epithelium. (1)H-NMR spectroscopy showed elevated levels of mitochondrial metabolites in urine from affected family members. Ehhadh knockout mice showed no abnormalities in renal tubular cells, a finding that indicates a dominant negative nature of the mutation rather than haploinsufficiency. Mistargeting of peroxisomal EHHADH disrupts mitochondrial metabolism and leads to renal Fanconi's syndrome; this indicates a central role of mitochondria in proximal tubular function. The dominant negative effect of the mistargeted protein adds to the spectrum of monogenic mechanisms of Fanconi's syndrome. (Funded by the European Commission Seventh Framework Programme and others.).

Research paper thumbnail of Optimized Preprocessing of Ultra-Performance Liquid Chromatography/Mass Spectrometry Urinary Metabolic Profiles for Improved Information Recovery

Analytical Chemistry, 2011

Ultra-performance liquid chromatography coupled to mass spectrometry (UPLC/MS) has been used incr... more Ultra-performance liquid chromatography coupled to mass spectrometry (UPLC/MS) has been used increasingly for measuring changes of low molecular weight metabolites in biofluids/tissues in response to biological challenges such as drug toxicity and disease processes. Typically samples show high variability in concentration, and the derived metabolic profiles have a heteroscedastic noise structure characterized by increasing variance as a function of increased signal intensity. These sources of experimental and instrumental noise substantially complicate information recovery when statistical tools are used. We apply and compare several preprocessing procedures and introduce a statistical error model to account for these bioanalytical complexities. In particular, the use of total intensity, median fold change, locally weighted scatter plot smoothing, and quantile normalizations to reduce extraneous variance induced by sample dilution were compared. We demonstrate that the UPLC/MS peak intensities of urine samples should respond linearly to variable sample dilution across the intensity range. While all four studied normalization methods performed reasonably well in reducing dilution-induced variation of urine samples in the absence of biological variation, the median fold change normalization is least compromised by the biologically relevant changes in mixture components and is thus preferable. Additionally, the application of a subsequent log-based transformation was successful in stabilizing the variance with respect to peak intensity, confirming the predominant influence of multiplicative noise in peak intensities from UPLC/MS-derived metabolic profile data sets. We demonstrate that variance-stabilizing transformation and normalization are critical preprocessing steps that can benefit greatly metabolic information recovery from such data sets when widely applied chemometric methods are used.

Research paper thumbnail of NMR in Metabolomics and Natural Products Research: Two Sides of the Same Coin

Accounts of Chemical Research, 2012

S mall molecules are central to biology, mediating critical phenomena such as metabolism, signal ... more S mall molecules are central to biology, mediating critical phenomena such as metabolism, signal transduction, mating attraction, and chemical defense. The traditional categories that define small molecules, such as metabolite, secondary metabolite, pheromone, hormone, and so forth, often overlap, and a single compound can appear under more than one functional heading. Therefore, we favor a unifying term, biogenic small molecules (BSMs), to describe any small molecule from a biological source.

Research paper thumbnail of Web Server Based Complex Mixture Analysis by NMR

Analytical Chemistry, 2008

Comprehensive metabolite identification and quantification of complex biological mixtures are cen... more Comprehensive metabolite identification and quantification of complex biological mixtures are central aspects of metabolomics. NMR shows excellent promise for these tasks. An automated fingerprinting strategy is presented, termed COLMAR query, which screens NMR chemical shift lists or raw 1D NMR cross sections taken from covariance total correlation spectroscopy (TOCSY) spectra or other multidimensional NMR spectra against an NMR spectral database. Cross peaks are selected using local clustering to avoid ambiguities between chemical shifts and scalar J-coupling effects. With the use of three different algorithms, the corresponding chemical shift list is then screened against chemical shift lists extracted from 1D spectra of a NMR database. The resulting query scores produced by forward assignment, reverse assignment, and bipartite weighted-matching algorithms are combined into a consensus score, which provides a robust means for identifying the correct compound. The approach is demonstrated for a metabolite model mixture that is screened against the metabolomics BioMagResDatabank (BMRB). This NMR-based compound identification approach has been implemented in a public Web server that allows the efficient analysis of a wide range of metabolite mixtures.

Research paper thumbnail of Statistical Spectroscopic Tools for Biomarker Discovery and Systems Medicine

Analytical Chemistry, 2013

Metabolic profiling based on comparative, statistical analysis of NMR spectroscopic and mass spec... more Metabolic profiling based on comparative, statistical analysis of NMR spectroscopic and mass spectrometric data from complex biological samples has contributed to increased understanding of the role of small molecules in affecting and indicating biological processes. To enable this research, the development of statistical spectroscopy has been marked by early beginnings in applying pattern recognition to nuclear magnetic resonance data and the introduction of statistical total correlation spectroscopy (STOCSY) as a tool for biomarker identification in the past decade. Extensions of statistical spectroscopy now compose a family of related tools used for compound identification, data preprocessing, and metabolic pathway analysis. In this Perspective, we review the theory and current state of research in statistical spectroscopy and discuss the growing applications of these tools to medicine and systems biology. We also provide perspectives on how recent institutional initiatives are providing new platforms for the development and application of statistical spectroscopy tools and driving the development of integrated "systems medicine" approaches in which clinical decision making is supported by statistical and computational analysis of metabolic, phenotypic, and physiological data.

Research paper thumbnail of Web server suite for complex mixture analysis by covariance NMR

Magnetic Resonance in Chemistry, 2009

Elucidation of the chemical composition of biological samples is a main focus of systems biology ... more Elucidation of the chemical composition of biological samples is a main focus of systems biology and metabolomics. Their comprehensive study requires reliable, efficient, and automatable methods to identify and quantify the underlying metabolites. Because nuclear magnetic resonance (NMR) spectroscopy is a rich source of molecular information, it has a unique potential for this task. Here we present a suite of public web servers (http://spinportal.magnet.fsu.edu), termed COLMAR, which facilitates complex mixture analysis by NMR. The COLMAR web portal presently consists of three servers: COLMAR covariance calculates the covariance NMR spectrum from an NMR input dataset, such as a TOCSY spectrum; COLMAR DemixC method decomposes the 2D covariance TOCSY spectrum into a reduced set of nonredundant 1D cross sections or traces, which belong to individual mixture components; and COLMAR query screens the traces against a NMR spectral database to identify individual compounds. Examples are presented that illustrate the utility of this web server suite for complex mixture analysis.

Research paper thumbnail of Hierarchical Alignment and Full Resolution Pattern Recognition of 2D NMR Spectra: Application to Nematode Chemical Ecology

Analytical Chemistry, 2011

Nuclear magnetic resonance (NMR) is the most widely used nondestructive technique in analytical c... more Nuclear magnetic resonance (NMR) is the most widely used nondestructive technique in analytical chemistry. In recent years, it has been applied to metabolic profiling due to its high reproducibility, capacity for relative and absolute quantification, atomic resolution, and ability to detect a broad range of compounds in an untargeted manner. While one-dimensional (1D) 1 H NMR experiments are popular in metabolic profiling due to their simplicity and fast acquisition times, two-dimensional (2D) NMR spectra offer increased spectral resolution as well as atomic correlations, which aid in the assignment of known small molecules and the structural elucidation of novel compounds. Given the small number of statistical analysis methods for 2D NMR spectra, we developed a new approach for the analysis, information recovery, and display of 2D NMR spectral data. We present a native 2D peak alignment algorithm we term HATS, for hierarchical alignment of two-dimensional spectra, enabling pattern recognition (PR) using full-resolution spectra. Principle component analysis (PCA) and partial least squares (PLS) regression of full resolution total correlation spectroscopy (TOCSY) spectra greatly aid the assignment and interpretation of statistical pattern recognition results by producing back-scaled loading plots that look like traditional TOCSY spectra but incorporate qualitative and quantitative biological information of the resonances. The HATS-PR methodology is demonstrated here using multiple 2D TOCSY spectra of the exudates from two nematode species: Pristionchus pacificus and Panagrellus redivivus. We show the utility of this integrated approach with the rapid, semiautomated assignment of small molecules differentiating the two species and the identification of spectral regions suggesting the presence of species-specific compounds. These results demonstrate that the combination of 2D NMR spectra with full-resolution statistical analysis provides a platform for chemical and biological studies in cellular biochemistry, metabolomics, and chemical ecology. N uclear magnetic resonance (NMR) is a powerful and almost universal detector due to its ability to analyze essentially all types of molecules at atomic resolution. Recently, it has been applied extensively to metabolic profiling in studies of human and animal biofluids, 1,2 cellular biochemistry, 3,4 and nonmammalian chemical ecology. 5-8 While one-dimensional (1D) 1 H NMR spectra have been used in the majority of NMR-based metabolic profiling studies, resonance overlap and lack of structural correlations can limit the utility of the 1D approach. In contrast, powerful multidimensional NMR methods are routinely used in structural biology and natural products studies 9 but have been used much less frequently for metabolomics. Two dimensional (2D) homonuclear (such as total correlation spectroscopy (TOCSY) and correlation spectroscopy (COSY)) and heteronuclear (such as heteronuclear single quantum coherence (HSQC) and heteronuclear multiple-bond correlation (HMBC)) spectra offer increased dispersion of signals in two dimensions that can overcome the problem of signal overlap, which often limits the use of 1D 1 H NMR spectra. Additionally, the information provided by these 2D experiments through specific atomic correlations can assist in the identification and assignment of known molecules and the structural elucidation of unknown small molecules that may be significant to the underlying biology. The presence of novel, uncharacterized small molecules in complex biological mixtures is a frequent occurrence, especially in nonmammalian metabolomics where a priori knowledge of the metabolome is often incomplete. Even when complex biological mixtures are composed mainly of known metabolites, the assignment of a large number of spectral peaks is a significant complication for metabolic profiling. The use of 2D correlation

Research paper thumbnail of Non-negative matrix factorization of two-dimensional NMR spectra: Application to complex mixture analysis

The Journal of Chemical Physics, 2008

A central problem in the emerging field of metabolomics is how to identify the compounds comprisi... more A central problem in the emerging field of metabolomics is how to identify the compounds comprising a chemical mixture of biological origin. NMR spectroscopy can greatly assist in this identification process, by means of multi-dimensional correlation spectroscopy, particularly total correlation spectroscopy (TOCSY). This Communication demonstrates how non-negative matrix factorization (NMF) provides an efficient means of data reduction and clustering of TOCSY spectra for the identification of unique traces representing the NMR spectra of individual compounds. The method is applied to a metabolic mixture whose compounds could be unambiguously identified by peak matching of NMF components against the BMRB metabolomics database.

Research paper thumbnail of Genetic determinants of metabolism in health and disease: from biochemical genetics to genome-wide associations

Genome Medicine, 2012

consequences in functional genomics, microbial metagenomics and disease modeling, the early resul... more consequences in functional genomics, microbial metagenomics and disease modeling, the early results and implications of which are reviewed.

Research paper thumbnail of Cluster Analysis Statistical Spectroscopy Using Nuclear Magnetic Resonance Generated Metabolic Data Sets from Perturbed Biological Systems

Analytical Chemistry, 2009

| Supporting Info • Full Text HTML • Hi-Res PDF[4779K] • PDF w/ Links[358K] Abstract • Full Text ... more | Supporting Info • Full Text HTML • Hi-Res PDF[4779K] • PDF w/ Links[358K] Abstract • Full Text HTML • Hi-Res PDF[4325K] Abstract • Full Text HTML • Hi-Res PDF[1067K] Abstract Stay Current Get your research ASAP. e-Alerts | RSS Feeds Advertisements Abstract • Full Text HTML • Hi-Res PDF[2869K] Abstract • Full Text HTML • Hi-Res PDF[1299K] • PDF w/ Links[230K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[658K] • PDF w/ Links[194K] Abstract • Full Text HTML • Hi-Res PDF[1360K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[574K] • PDF w/ Links[263K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[4623K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[1081K] • PDF w/ Links[213K] Abstract • Full Text HTML • Hi-Res PDF[8941K] Abstract • Full Text HTML • Hi-Res PDF[3868K] • PDF w/ Links[431K] Abstract • Full Text HTML • Hi-Res PDF[360K] • PDF w/ Links[223K] Abstract • Full Text HTML • Hi-Res PDF[680K] Abstract • Full Text HTML • Hi-Res PDF[618K] Abstract • Full Text HTML • Hi-Res PDF[578K] Abstract • Full Text HTML • Hi-Res PDF[1280K] Abstract • Full Text HTML • Hi-Res PDF[386K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[280K] Abstract • Full Text HTML • Hi-Res PDF[934K] Abstract • Full Text HTML Abstract • Full Text HTML • Hi-Res PDF[484K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[1091K] Abstract • Full Text HTML • Hi-Res PDF[208K] Abstract • Full Text HTML Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[522K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[3418K] • PDF w/ Links[369K] Sponsored Access Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[3609K] • PDF w/ Links[481K] Abstract | Supporting Info Abstract • Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[2923K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[1528K] Abstract • Full Text HTML • Hi-Res PDF[1441K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[1932K] • PDF w/ Links[363K] Abstract | Supporting Info • Full Text HTML • Hi-Res PDF[3971K] Abstract • Full Text HTML • Hi-Res PDF[503K] • PDF w/ Links[170K] Abstract • Full Text HTML •

Research paper thumbnail of Self-Consistent Metabolic Mixture Analysis by Heteronuclear NMR. Application to a Human Cancer Cell Line

Analytical Chemistry, 2008

Elucidation of the chemical composition of biological samples is a main focus of systems biology ... more Elucidation of the chemical composition of biological samples is a main focus of systems biology and metabolomics. In order to comprehensively study these complex mixtures, reliable, efficient, and automatable methods are needed to identify and quantify the underlying metabolites and natural products. Because of its rich information content, nuclear magnetic resonance (NMR) spectroscopy has a unique potential for this task. Here we present a generalization of the recently introduced homonuclear TOCSY-based DemixC method to heteronuclear HSQC-TOCSY NMR spectroscopy. The approach takes advantage of the high resolution afforded along the (13)C dimension due to the narrow (13)C line widths for the identification of spin systems and compounds. The method combines information from both 1D (13)C and (1)H traces by querying them against an NMR spectral database using our COLMAR query web server. The complementarity of (13)C and (1)H spectral information improves the robustness of compound identification. The method is demonstrated for a metabolic model mixture and is then applied to an extract from DU145 human prostate cancer cells.

Research paper thumbnail of Bacterial Attraction and Quorum Sensing Inhibition in Caenorhabditis elegans Exudates

Journal of Chemical Ecology, 2009

Caenorhabditis elegans, a bacterivorous nematode, lives in complex rotting fruit, soil, and compo... more Caenorhabditis elegans, a bacterivorous nematode, lives in complex rotting fruit, soil, and compost environments, and chemical interactions are required for mating, monitoring population density, recognition of food, avoidance of pathogenic microbes, and other essential ecological functions. Despite being one of the best-studied model organisms in biology, relatively little is known about the signals that C. elegans uses to interact chemically with its environment or as defense. C. elegans exudates were analyzed by using several analytical methods and found to Author contributions Fatma Kaplan and Dayakar V. Badri contributed equally and led the study; Fatma Kaplan, Aaron T. Dossey, Ramadan Ajredini, Hans Alborn and Michael Stadler intellectually contributed to the worm exudate protocol which was developed in the ASE laboratory; Fatma Kaplan, Ramadan Ajredini, and Rathika Nimalendran collected exudates; Dayakar V. Badri conducted bacterial bioassays; Hans Alborn collected LC-MS data; Fatma Kaplan and Cherian Zachariah collected NMR data; Fengli Zhang, Steven L. Robinette and Rafael Brüschweiler did COLMAR analysis; Fatma Kaplan, Cherian Zachariah, Michael Stadler, and Aaron T. Dossey manually analyzed NMR data. Sanja Roje and Francisco Sandoval analyzed amino acids by HPLC; Lanfang H. Levine analyzed young adult exudates by GC-MS; Wei Zhao did principle component analysis; Fatma Kaplan, Dayakar V. Badri, Arthur S. Edison and Jorge M. Vivanco analyzed the data and wrote the paper with help from the entire team.

Research paper thumbnail of 2D NMR-Based Metabolomics Uncovers Interactions between Conserved Biochemical Pathways in the Model Organism Caenorhabditis elegans

ACS Chemical Biology, 2013

Ascarosides are small-molecule signals that play a central role in C. elegans biology, including ... more Ascarosides are small-molecule signals that play a central role in C. elegans biology, including dauer formation, aging, and social behaviors, but many aspects of their biosynthesis remain unknown. Using automated 2D NMRbased comparative metabolomics, we identified ascaroside ethanolamides as shunt metabolites in C. elegans mutants of daf-22, a gene with homology to mammalian 3-ketoacyl-CoA thiolases predicted to function in conserved peroxisomal lipid βoxidation. Two groups of ethanolamides feature β-keto functionalization confirming the predicted role of daf-22 in ascaroside biosynthesis, whereas α-methyl substitution points to unexpected inclusion of methylmalonate at a late stage in the biosynthesis of long-chain fatty acids in C. elegans. We show that ascaroside ethanolamide formation in response to defects in daf-22 and other peroxisomal genes is associated with severe depletion of endocannabinoid pools. These results indicate unexpected interaction between peroxisomal lipid β-oxidation and the biosynthesis of endocannabinoids, which are major regulators of lifespan in C. elegans. Our study demonstrates the utility of unbiased comparative metabolomics for investigating biochemical networks in metazoans.