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Use of the local false discovery rate for identification of metabolic biomarkers in rat urine following Genkwa Flos-induced hepatotoxicity.
PUBLISHED: 01-01-2013
Metabolomics is concerned with characterizing the large number of metabolites present in a biological system using nuclear magnetic resonance (NMR) and HPLC/MS (high-performance liquid chromatography with mass spectrometry). Multivariate analysis is one of the most important tools for metabolic biomarker identification in metabolomic studies. However, analyzing the large-scale data sets acquired during metabolic fingerprinting is a major challenge. As a posterior probability that the features of interest are not affected, the local false discovery rate (LFDR) is a good interpretable measure. However, it is rarely used to when interrogating metabolic data to identify biomarkers. In this study, we employed the LFDR method to analyze HPLC/MS data acquired from a metabolomic study of metabolic changes in rat urine during hepatotoxicity induced by Genkwa flos (GF) treatment. The LFDR approach was successfully used to identify important rat urine metabolites altered by GF-stimulated hepatotoxicity. Compared with principle component analysis (PCA), LFDR is an interpretable measure and discovers more important metabolites in an HPLC/MS-based metabolomic study.
Authors: Charmion Cruickshank-Quinn, Kevin D. Quinn, Roger Powell, Yanhui Yang, Michael Armstrong, Spencer Mahaffey, Richard Reisdorph, Nichole Reisdorph.
Published: 07-11-2014
Metabolomics is an emerging field which enables profiling of samples from living organisms in order to obtain insight into biological processes. A vital aspect of metabolomics is sample preparation whereby inconsistent techniques generate unreliable results. This technique encompasses protein precipitation, liquid-liquid extraction, and solid-phase extraction as a means of fractionating metabolites into four distinct classes. Improved enrichment of low abundance molecules with a resulting increase in sensitivity is obtained, and ultimately results in more confident identification of molecules. This technique has been applied to plasma, bronchoalveolar lavage fluid, and cerebrospinal fluid samples with volumes as low as 50 µl.  Samples can be used for multiple downstream applications; for example, the pellet resulting from protein precipitation can be stored for later analysis. The supernatant from that step undergoes liquid-liquid extraction using water and strong organic solvent to separate the hydrophilic and hydrophobic compounds. Once fractionated, the hydrophilic layer can be processed for later analysis or discarded if not needed. The hydrophobic fraction is further treated with a series of solvents during three solid-phase extraction steps to separate it into fatty acids, neutral lipids, and phospholipids. This allows the technician the flexibility to choose which class of compounds is preferred for analysis. It also aids in more reliable metabolite identification since some knowledge of chemical class exists.
22 Related JoVE Articles!
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Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics
Authors: Takayuki Tohge, Alisdair R. Fernie.
Institutions: Max-Planck-Institut.
Given the ever expanding number of model plant species for which complete genome sequences are available and the abundance of bio-resources such as knockout mutants, wild accessions and advanced breeding populations, there is a rising burden for gene functional annotation. In this protocol, annotation of plant gene function using combined co-expression gene analysis, metabolomics and informatics is provided (Figure 1). This approach is based on the theory of using target genes of known function to allow the identification of non-annotated genes likely to be involved in a certain metabolic process, with the identification of target compounds via metabolomics. Strategies are put forward for applying this information on populations generated by both forward and reverse genetics approaches in spite of none of these are effortless. By corollary this approach can also be used as an approach to characterise unknown peaks representing new or specific secondary metabolites in the limited tissues, plant species or stress treatment, which is currently the important trial to understanding plant metabolism.
Plant Biology, Issue 64, Genetics, Bioinformatics, Metabolomics, Plant metabolism, Transcriptome analysis, Functional annotation, Computational biology, Plant biology, Theoretical biology, Spectroscopy and structural analysis
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Hydrogel Nanoparticle Harvesting of Plasma or Urine for Detecting Low Abundance Proteins
Authors: Ruben Magni, Benjamin H. Espina, Lance A. Liotta, Alessandra Luchini, Virginia Espina.
Institutions: George Mason University, Ceres Nanosciences.
Novel biomarker discovery plays a crucial role in providing more sensitive and specific disease detection. Unfortunately many low-abundance biomarkers that exist in biological fluids cannot be easily detected with mass spectrometry or immunoassays because they are present in very low concentration, are labile, and are often masked by high-abundance proteins such as albumin or immunoglobulin. Bait containing poly(N-isopropylacrylamide) (NIPAm) based nanoparticles are able to overcome these physiological barriers. In one step they are able to capture, concentrate and preserve biomarkers from body fluids. Low-molecular weight analytes enter the core of the nanoparticle and are captured by different organic chemical dyes, which act as high affinity protein baits. The nanoparticles are able to concentrate the proteins of interest by several orders of magnitude. This concentration factor is sufficient to increase the protein level such that the proteins are within the detection limit of current mass spectrometers, western blotting, and immunoassays. Nanoparticles can be incubated with a plethora of biological fluids and they are able to greatly enrich the concentration of low-molecular weight proteins and peptides while excluding albumin and other high-molecular weight proteins. Our data show that a 10,000 fold amplification in the concentration of a particular analyte can be achieved, enabling mass spectrometry and immunoassays to detect previously undetectable biomarkers.
Bioengineering, Issue 90, biomarker, hydrogel, low abundance, mass spectrometry, nanoparticle, plasma, protein, urine
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Barnes Maze Testing Strategies with Small and Large Rodent Models
Authors: Cheryl S. Rosenfeld, Sherry A. Ferguson.
Institutions: University of Missouri, Food and Drug Administration.
Spatial learning and memory of laboratory rodents is often assessed via navigational ability in mazes, most popular of which are the water and dry-land (Barnes) mazes. Improved performance over sessions or trials is thought to reflect learning and memory of the escape cage/platform location. Considered less stressful than water mazes, the Barnes maze is a relatively simple design of a circular platform top with several holes equally spaced around the perimeter edge. All but one of the holes are false-bottomed or blind-ending, while one leads to an escape cage. Mildly aversive stimuli (e.g. bright overhead lights) provide motivation to locate the escape cage. Latency to locate the escape cage can be measured during the session; however, additional endpoints typically require video recording. From those video recordings, use of automated tracking software can generate a variety of endpoints that are similar to those produced in water mazes (e.g. distance traveled, velocity/speed, time spent in the correct quadrant, time spent moving/resting, and confirmation of latency). Type of search strategy (i.e. random, serial, or direct) can be categorized as well. Barnes maze construction and testing methodologies can differ for small rodents, such as mice, and large rodents, such as rats. For example, while extra-maze cues are effective for rats, smaller wild rodents may require intra-maze cues with a visual barrier around the maze. Appropriate stimuli must be identified which motivate the rodent to locate the escape cage. Both Barnes and water mazes can be time consuming as 4-7 test trials are typically required to detect improved learning and memory performance (e.g. shorter latencies or path lengths to locate the escape platform or cage) and/or differences between experimental groups. Even so, the Barnes maze is a widely employed behavioral assessment measuring spatial navigational abilities and their potential disruption by genetic, neurobehavioral manipulations, or drug/ toxicant exposure.
Behavior, Issue 84, spatial navigation, rats, Peromyscus, mice, intra- and extra-maze cues, learning, memory, latency, search strategy, escape motivation
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Analysis of Tubular Membrane Networks in Cardiac Myocytes from Atria and Ventricles
Authors: Eva Wagner, Sören Brandenburg, Tobias Kohl, Stephan E. Lehnart.
Institutions: Heart Research Center Goettingen, University Medical Center Goettingen, German Center for Cardiovascular Research (DZHK) partner site Goettingen, University of Maryland School of Medicine.
In cardiac myocytes a complex network of membrane tubules - the transverse-axial tubule system (TATS) - controls deep intracellular signaling functions. While the outer surface membrane and associated TATS membrane components appear to be continuous, there are substantial differences in lipid and protein content. In ventricular myocytes (VMs), certain TATS components are highly abundant contributing to rectilinear tubule networks and regular branching 3D architectures. It is thought that peripheral TATS components propagate action potentials from the cell surface to thousands of remote intracellular sarcoendoplasmic reticulum (SER) membrane contact domains, thereby activating intracellular Ca2+ release units (CRUs). In contrast to VMs, the organization and functional role of TATS membranes in atrial myocytes (AMs) is significantly different and much less understood. Taken together, quantitative structural characterization of TATS membrane networks in healthy and diseased myocytes is an essential prerequisite towards better understanding of functional plasticity and pathophysiological reorganization. Here, we present a strategic combination of protocols for direct quantitative analysis of TATS membrane networks in living VMs and AMs. For this, we accompany primary cell isolations of mouse VMs and/or AMs with critical quality control steps and direct membrane staining protocols for fluorescence imaging of TATS membranes. Using an optimized workflow for confocal or superresolution TATS image processing, binarized and skeletonized data are generated for quantitative analysis of the TATS network and its components. Unlike previously published indirect regional aggregate image analysis strategies, our protocols enable direct characterization of specific components and derive complex physiological properties of TATS membrane networks in living myocytes with high throughput and open access software tools. In summary, the combined protocol strategy can be readily applied for quantitative TATS network studies during physiological myocyte adaptation or disease changes, comparison of different cardiac or skeletal muscle cell types, phenotyping of transgenic models, and pharmacological or therapeutic interventions.
Bioengineering, Issue 92, cardiac myocyte, atria, ventricle, heart, primary cell isolation, fluorescence microscopy, membrane tubule, transverse-axial tubule system, image analysis, image processing, T-tubule, collagenase
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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Authors: Hans-Peter Müller, Jan Kassubek.
Institutions: University of Ulm.
Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls. DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels. In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.
Medicine, Issue 77, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Anatomy, Physiology, Neurodegenerative Diseases, nuclear magnetic resonance, NMR, MR, MRI, diffusion tensor imaging, fiber tracking, group level comparison, neurodegenerative diseases, brain, imaging, clinical techniques
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Biomarkers in an Animal Model for Revealing Neural, Hematologic, and Behavioral Correlates of PTSD
Authors: Min Jia, Fei Meng, Stanley E. Smerin, Guoqiang Xing, Lei Zhang, David M. Su, David Benedek, Robert Ursano, Yan A. Su, He Li.
Institutions: Uniformed Services University of the Health Sciences, Bethesda, Maryland, GenProMarkers, Inc..
Identification of biomarkers representing the evolution of the pathophysiology of Post Traumatic Stress Disorder (PTSD) is vitally important, not only for objective diagnosis but also for the evaluation of therapeutic efficacy and resilience to trauma. Ongoing research is directed at identifying molecular biomarkers for PTSD, including traumatic stress induced proteins, transcriptomes, genomic variances and genetic modulators, using biologic samples from subjects' blood, saliva, urine, and postmortem brain tissues. However, the correlation of these biomarker molecules in peripheral or postmortem samples to altered brain functions associated with psychiatric symptoms in PTSD remains unresolved. Here, we present an animal model of PTSD in which both peripheral blood and central brain biomarkers, as well as behavioral phenotype, can be collected and measured, thus providing the needed correlation of the central biomarkers of PTSD, which are mechanistic and pathognomonic but cannot be collected from people, with the peripheral biomarkers and behavioral phenotypes, which can. Our animal model of PTSD employs restraint and tail shocks repeated for three continuous days - the inescapable tail-shock model (ITS) in rats. This ITS model mimics the pathophysiology of PTSD 17, 7, 4, 10. We and others have verified that the ITS model induces behavioral and neurobiological alterations similar to those found in PTSD subjects 17, 7, 10, 9. Specifically, these stressed rats exhibit (1) a delayed and exaggerated startle response appearing several days after stressor cessation, which given the compressed time scale of the rat's life compared to a humans, corresponds to the one to three months delay of symptoms in PTSD patients (DSM-IV-TR PTSD Criterian D/E 13), (2) enhanced plasma corticosterone (CORT) for several days, indicating compromise of the hypothalamopituitary axis (HPA), and (3) retarded body weight gain after stressor cessation, indicating dysfunction of metabolic regulation. The experimental paradigms employed for this model are: (1) a learned helplessness paradigm in the rat assayed by measurement of acoustic startle response (ASR) and a charting of body mass; (2) microdissection of the rat brain into regions and nuclei; (3) enzyme-linked immunosorbent assay (ELISA) for blood levels of CORT; (4) a gene expression microarray plus related bioinformatics tools 18. This microarray, dubbed rMNChip, focuses on mitochondrial and mitochondria-related nuclear genes in the rat so as to specifically address the neuronal bioenergetics hypothesized to be involved in PTSD.
Medicine, Issue 68, Genetics, Physiology, Neuroscience, Immunology, PTSD, biomarker, stress, fear, startle, corticosterone, animal model, RNA, RT-PCR, gene chip, cDNA microarray, oligonucleotide microarray, amygdala, prefrontal cortex, hippocampus, cingulate cortex, hypothalamus, white blood cell
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Chemically-blocked Antibody Microarray for Multiplexed High-throughput Profiling of Specific Protein Glycosylation in Complex Samples
Authors: Chen Lu, Joshua L. Wonsidler, Jianwei Li, Yanming Du, Timothy Block, Brian Haab, Songming Chen.
Institutions: Institute for Hepatitis and Virus Research, Thomas Jefferson University , Drexel University College of Medicine, Van Andel Research Institute, Serome Biosciences Inc..
In this study, we describe an effective protocol for use in a multiplexed high-throughput antibody microarray with glycan binding protein detection that allows for the glycosylation profiling of specific proteins. Glycosylation of proteins is the most prevalent post-translational modification found on proteins, and leads diversified modifications of the physical, chemical, and biological properties of proteins. Because the glycosylation machinery is particularly susceptible to disease progression and malignant transformation, aberrant glycosylation has been recognized as early detection biomarkers for cancer and other diseases. However, current methods to study protein glycosylation typically are too complicated or expensive for use in most normal laboratory or clinical settings and a more practical method to study protein glycosylation is needed. The new protocol described in this study makes use of a chemically blocked antibody microarray with glycan-binding protein (GBP) detection and significantly reduces the time, cost, and lab equipment requirements needed to study protein glycosylation. In this method, multiple immobilized glycoprotein-specific antibodies are printed directly onto the microarray slides and the N-glycans on the antibodies are blocked. The blocked, immobilized glycoprotein-specific antibodies are able to capture and isolate glycoproteins from a complex sample that is applied directly onto the microarray slides. Glycan detection then can be performed by the application of biotinylated lectins and other GBPs to the microarray slide, while binding levels can be determined using Dylight 549-Streptavidin. Through the use of an antibody panel and probing with multiple biotinylated lectins, this method allows for an effective glycosylation profile of the different proteins found in a given human or animal sample to be developed. Introduction Glycosylation of protein, which is the most ubiquitous post-translational modification on proteins, modifies the physical, chemical, and biological properties of a protein, and plays a fundamental role in various biological processes1-6. Because the glycosylation machinery is particularly susceptible to disease progression and malignant transformation, aberrant glycosylation has been recognized as early detection biomarkers for cancer and other diseases 7-12. In fact, most current cancer biomarkers, such as the L3 fraction of α-1 fetoprotein (AFP) for hepatocellular carcinoma 13-15, and CA199 for pancreatic cancer 16, 17 are all aberrant glycan moieties on glycoproteins. However, methods to study protein glycosylation have been complicated, and not suitable for routine laboratory and clinical settings. Chen et al. has recently invented a chemically blocked antibody microarray with a glycan-binding protein (GBP) detection method for high-throughput and multiplexed profile glycosylation of native glycoproteins in a complex sample 18. In this affinity based microarray method, multiple immobilized glycoprotein-specific antibodies capture and isolate glycoproteins from the complex mixture directly on the microarray slide, and the glycans on each individual captured protein are measured by GBPs. Because all normal antibodies contain N-glycans which could be recognized by most GBPs, the critical step of this method is to chemically block the glycans on the antibodies from binding to GBP. In the procedure, the cis-diol groups of the glycans on the antibodies were first oxidized to aldehyde groups by using NaIO4 in sodium acetate buffer avoiding light. The aldehyde groups were then conjugated to the hydrazide group of a cross-linker, 4-(4-N-MaleimidoPhenyl)butyric acid Hydrazide HCl (MPBH), followed by the conjugation of a dipeptide, Cys-Gly, to the maleimide group of the MPBH. Thus, the cis-diol groups on glycans of antibodies were converted into bulky none hydroxyl groups, which hindered the lectins and other GBPs bindings to the capture antibodies. This blocking procedure makes the GBPs and lectins bind only to the glycans of captured proteins. After this chemically blocking, serum samples were incubated with the antibody microarray, followed by the glycans detection by using different biotinylated lectins and GBPs, and visualized with Cy3-streptavidin. The parallel use of an antibody panel and multiple lectin probing provides discrete glycosylation profiles of multiple proteins in a given sample 18-20. This method has been used successfully in multiple different labs 1, 7, 13, 19-31. However, stability of MPBH and Cys-Gly, complicated and extended procedure in this method affect the reproducibility, effectiveness and efficiency of the method. In this new protocol, we replaced both MPBH and Cys-Gly with one much more stable reagent glutamic acid hydrazide (Glu-hydrazide), which significantly improved the reproducibility of the method, simplified and shorten the whole procedure so that the it can be completed within one working day. In this new protocol, we describe the detailed procedure of the protocol which can be readily adopted by normal labs for routine protein glycosylation study and techniques which are necessary to obtain reproducible and repeatable results.
Molecular Biology, Issue 63, Glycoproteins, glycan-binding protein, specific protein glycosylation, multiplexed high-throughput glycan blocked antibody microarray
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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Authors: Phoebe Spetsieris, Yilong Ma, Shichun Peng, Ji Hyun Ko, Vijay Dhawan, Chris C. Tang, David Eidelberg.
Institutions: The Feinstein Institute for Medical Research.
The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.
Medicine, Issue 76, Neurobiology, Neuroscience, Anatomy, Physiology, Molecular Biology, Basal Ganglia Diseases, Parkinsonian Disorders, Parkinson Disease, Movement Disorders, Neurodegenerative Diseases, PCA, SSM, PET, imaging biomarkers, functional brain imaging, multivariate spatial covariance analysis, global normalization, differential diagnosis, PD, brain, imaging, clinical techniques
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Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Authors: Philippe Pérot, Valérie Cheynet, Myriam Decaussin-Petrucci, Guy Oriol, Nathalie Mugnier, Claire Rodriguez-Lafrasse, Alain Ruffion, François Mallet.
Institutions: Joint Unit Hospices de Lyon-bioMérieux, BioMérieux, Hospices Civils de Lyon, Lyon 1 University, BioMérieux, Hospices Civils de Lyon, Hospices Civils de Lyon.
The prostate-specific antigen (PSA) is the main diagnostic biomarker for prostate cancer in clinical use, but it lacks specificity and sensitivity, particularly in low dosage values1​​. ‘How to use PSA' remains a current issue, either for diagnosis as a gray zone corresponding to a concentration in serum of 2.5-10 ng/ml which does not allow a clear differentiation to be made between cancer and noncancer2 or for patient follow-up as analysis of post-operative PSA kinetic parameters can pose considerable challenges for their practical application3,4. Alternatively, noncoding RNAs (ncRNAs) are emerging as key molecules in human cancer, with the potential to serve as novel markers of disease, e.g. PCA3 in prostate cancer5,6 and to reveal uncharacterized aspects of tumor biology. Moreover, data from the ENCODE project published in 2012 showed that different RNA types cover about 62% of the genome. It also appears that the amount of transcriptional regulatory motifs is at least 4.5x higher than the one corresponding to protein-coding exons. Thus, long terminal repeats (LTRs) of human endogenous retroviruses (HERVs) constitute a wide range of putative/candidate transcriptional regulatory sequences, as it is their primary function in infectious retroviruses. HERVs, which are spread throughout the human genome, originate from ancestral and independent infections within the germ line, followed by copy-paste propagation processes and leading to multicopy families occupying 8% of the human genome (note that exons span 2% of our genome). Some HERV loci still express proteins that have been associated with several pathologies including cancer7-10. We have designed a high-density microarray, in Affymetrix format, aiming to optimally characterize individual HERV loci expression, in order to better understand whether they can be active, if they drive ncRNA transcription or modulate coding gene expression. This tool has been applied in the prostate cancer field (Figure 1).
Medicine, Issue 81, Cancer Biology, Genetics, Molecular Biology, Prostate, Retroviridae, Biomarkers, Pharmacological, Tumor Markers, Biological, Prostatectomy, Microarray Analysis, Gene Expression, Diagnosis, Human Endogenous Retroviruses, HERV, microarray, Transcriptome, prostate cancer, Affymetrix
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One-step Metabolomics: Carbohydrates, Organic and Amino Acids Quantified in a Single Procedure
Authors: James D. Shoemaker.
Institutions: Saint Louis University School of Medicine.
Every infant born in the US is now screened for up to 42 rare genetic disorders called "inborn errors of metabolism". The screening method is based on tandem mass spectrometry and quantifies acylcarnitines as a screen for organic acidemias and also measures amino acids. All states also perform enzymatic testing for carbohydrate disorders such as galactosemia. Because the results can be non-specific, follow-up testing of positive results is required using a more definitive method. The present report describes the "urease" method of sample preparation for inborn error screening. Crystalline urease enzyme is used to remove urea from body fluids which permits most other water-soluble metabolites to be dehydrated and derivatized for gas chromatography in a single procedure. Dehydration by evaporation in a nitrogen stream is facilitated by adding acetonitrile and methylene chloride. Then, trimethylsilylation takes place in the presence of a unique catalyst, triethylammonium trifluoroacetate. Automated injection and chromatography is followed by macro-driven custom quantification of 192 metabolites and semi-quantification of every major component using specialized libraries of mass spectra of TMS derivatized biological compounds. The analysis may be performed on the widely-used Chemstation platform using the macros and libraries available from the author. In our laboratory, over 16,000 patient samples have been analyzed using the method with a diagnostic yield of about 17%--that is, 17% of the samples results reveal findings that should be acted upon by the ordering physician. Included in these are over 180 confirmed inborn errors, of which about 38% could not have been diagnosed using previous methods.
Biochemistry, Issue 40, metabolomics, gas chromatography/mass spectrometry, GC/MS, inborn errors, vitamin deficiency, BNA analyses, carbohydrate, amino acid, organic acid, urease
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Concentration of Metabolites from Low-density Planktonic Communities for Environmental Metabolomics using Nuclear Magnetic Resonance Spectroscopy
Authors: R. Craig Everroad, Seiji Yoshida, Yuuri Tsuboi, Yasuhiro Date, Jun Kikuchi, Shigeharu Moriya.
Institutions: RIKEN Advanced Science Institute, Yokohama City University, RIKEN Plant Science Center, Nagoya University.
Environmental metabolomics is an emerging field that is promoting new understanding in how organisms respond to and interact with the environment and each other at the biochemical level1. Nuclear magnetic resonance (NMR) spectroscopy is one of several technologies, including gas chromatography–mass spectrometry (GC-MS), with considerable promise for such studies. Advantages of NMR are that it is suitable for untargeted analyses, provides structural information and spectra can be queried in quantitative and statistical manners against recently available databases of individual metabolite spectra2,3. In addition, NMR spectral data can be combined with data from other omics levels (e.g. transcriptomics, genomics) to provide a more comprehensive understanding of the physiological responses of taxa to each other and the environment4,5,6. However, NMR is less sensitive than other metabolomic techniques, making it difficult to apply to natural microbial systems where sample populations can be low-density and metabolite concentrations low compared to metabolites from well-defined and readily extractable sources such as whole tissues, biofluids or cell-cultures. Consequently, the few direct environmental metabolomic studies of microbes performed to date have been limited to culture-based or easily defined high-density ecosystems such as host-symbiont systems, constructed co-cultures or manipulations of the gut environment where stable isotope labeling can be additionally used to enhance NMR signals7,8,9,10,11,12. Methods that facilitate the concentration and collection of environmental metabolites at concentrations suitable for NMR are lacking. Since recent attention has been given to the environmental metabolomics of organisms within the aquatic environment, where much of the energy and material flow is mediated by the planktonic community13,14, we have developed a method for the concentration and extraction of whole-community metabolites from planktonic microbial systems by filtration. Commercially available hydrophilic poly-1,1-difluoroethene (PVDF) filters are specially treated to completely remove extractables, which can otherwise appear as contaminants in subsequent analyses. These treated filters are then used to filter environmental or experimental samples of interest. Filters containing the wet sample material are lyophilized and aqueous-soluble metabolites are extracted directly for conventional NMR spectroscopy using a standardized potassium phosphate extraction buffer2. Data derived from these methods can be analyzed statistically to identify meaningful patterns, or integrated with other omics levels for comprehensive understanding of community and ecosystem function.
Molecular Biology, Issue 62, environmental metabolomics, metabolic profiling, microbial ecology, plankton, NMR spectroscopy, PCA
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Assessing Hepatic Metabolic Changes During Progressive Colonization of Germ-free Mouse by 1H NMR Spectroscopy
Authors: Peter Heath, Sandrine Paule Claus.
Institutions: The University of Reading, The University of Reading .
It is well known that gut bacteria contribute significantly to the host homeostasis, providing a range of benefits such as immune protection and vitamin synthesis. They also supply the host with a considerable amount of nutrients, making this ecosystem an essential metabolic organ. In the context of increasing evidence of the link between the gut flora and the metabolic syndrome, understanding the metabolic interaction between the host and its gut microbiota is becoming an important challenge of modern biology.1-4 Colonization (also referred to as normalization process) designates the establishment of micro-organisms in a former germ-free animal. While it is a natural process occurring at birth, it is also used in adult germ-free animals to control the gut floral ecosystem and further determine its impact on the host metabolism. A common procedure to control the colonization process is to use the gavage method with a single or a mixture of micro-organisms. This method results in a very quick colonization and presents the disadvantage of being extremely stressful5. It is therefore useful to minimize the stress and to obtain a slower colonization process to observe gradually the impact of bacterial establishment on the host metabolism. In this manuscript, we describe a procedure to assess the modification of hepatic metabolism during a gradual colonization process using a non-destructive metabolic profiling technique. We propose to monitor gut microbial colonization by assessing the gut microbial metabolic activity reflected by the urinary excretion of microbial co-metabolites by 1H NMR-based metabolic profiling. This allows an appreciation of the stability of gut microbial activity beyond the stable establishment of the gut microbial ecosystem usually assessed by monitoring fecal bacteria by DGGE (denaturing gradient gel electrophoresis).6 The colonization takes place in a conventional open environment and is initiated by a dirty litter soiled by conventional animals, which will serve as controls. Rodents being coprophagous animals, this ensures a homogenous colonization as previously described.7 Hepatic metabolic profiling is measured directly from an intact liver biopsy using 1H High Resolution Magic Angle Spinning NMR spectroscopy. This semi-quantitative technique offers a quick way to assess, without damaging the cell structure, the major metabolites such as triglycerides, glucose and glycogen in order to further estimate the complex interaction between the colonization process and the hepatic metabolism7-10. This method can also be applied to any tissue biopsy11,12.
Immunology, Issue 58, Germ-free animal, colonization, NMR, HR MAS NMR, metabonomics
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Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)
Authors: Corey D. Broeckling, Adam L. Heuberger, Jessica E. Prenni.
Institutions: Colorado State University.
Non-targeted metabolite profiling by ultra performance liquid chromatography coupled with mass spectrometry (UPLC-MS) is a powerful technique to investigate metabolism. The approach offers an unbiased and in-depth analysis that can enable the development of diagnostic tests, novel therapies, and further our understanding of disease processes. The inherent chemical diversity of the metabolome creates significant analytical challenges and there is no single experimental approach that can detect all metabolites. Additionally, the biological variation in individual metabolism and the dependence of metabolism on environmental factors necessitates large sample numbers to achieve the appropriate statistical power required for meaningful biological interpretation. To address these challenges, this tutorial outlines an analytical workflow for large scale non-targeted metabolite profiling of serum by UPLC-MS. The procedure includes guidelines for sample organization and preparation, data acquisition, quality control, and metabolite identification and will enable reliable acquisition of data for large experiments and provide a starting point for laboratories new to non-targeted metabolite profiling by UPLC-MS.
Chemistry, Issue 73, Biochemistry, Genetics, Molecular Biology, Physiology, Genomics, Proteins, Proteomics, Metabolomics, Metabolite Profiling, Non-targeted metabolite profiling, mass spectrometry, Ultra Performance Liquid Chromatography, UPLC-MS, serum, spectrometry
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Sample Preparation of Mycobacterium tuberculosis Extracts for Nuclear Magnetic Resonance Metabolomic Studies
Authors: Denise K. Zinniel, Robert J. Fenton, Steven Halouska, Robert Powers, Raul G. Barletta.
Institutions: University of Nebraska-Lincoln, University of Nebraska-Lincoln.
Mycobacterium tuberculosis is a major cause of mortality in human beings on a global scale. The emergence of both multi- (MDR) and extensively-(XDR) drug-resistant strains threatens to derail current disease control efforts. Thus, there is an urgent need to develop drugs and vaccines that are more effective than those currently available. The genome of M. tuberculosis has been known for more than 10 years, yet there are important gaps in our knowledge of gene function and essentiality. Many studies have since used gene expression analysis at both the transcriptomic and proteomic levels to determine the effects of drugs, oxidants, and growth conditions on the global patterns of gene expression. Ultimately, the final response of these changes is reflected in the metabolic composition of the bacterium including a few thousand small molecular weight chemicals. Comparing the metabolic profiles of wild type and mutant strains, either untreated or treated with a particular drug, can effectively allow target identification and may lead to the development of novel inhibitors with anti-tubercular activity. Likewise, the effects of two or more conditions on the metabolome can also be assessed. Nuclear magnetic resonance (NMR) is a powerful technology that is used to identify and quantify metabolic intermediates. In this protocol, procedures for the preparation of M. tuberculosis cell extracts for NMR metabolomic analysis are described. Cell cultures are grown under appropriate conditions and required Biosafety Level 3 containment,1 harvested, and subjected to mechanical lysis while maintaining cold temperatures to maximize preservation of metabolites. Cell lysates are recovered, filtered sterilized, and stored at ultra-low temperatures. Aliquots from these cell extracts are plated on Middlebrook 7H9 agar for colony-forming units to verify absence of viable cells. Upon two months of incubation at 37 °C, if no viable colonies are observed, samples are removed from the containment facility for downstream processing. Extracts are lyophilized, resuspended in deuterated buffer and injected in the NMR instrument, capturing spectroscopic data that is then subjected to statistical analysis. The procedures described can be applied for both one-dimensional (1D) 1H NMR and two-dimensional (2D) 1H-13C NMR analyses. This methodology provides more reliable small molecular weight metabolite identification and more reliable and sensitive quantitative analyses of cell extract metabolic compositions than chromatographic methods. Variations of the procedure described following the cell lysis step can also be adapted for parallel proteomic analysis.
Infection, Issue 67, Mycobacterium tuberculosis, NMR, Metabolomics, homogenizer, lysis, cell extracts, sample preparation
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Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry (UPLC-HRMS)
Authors: Nathaniel W. Snyder, Maya Khezam, Clementina A. Mesaros, Andrew Worth, Ian A. Blair.
Institutions: University of Pennsylvania .
Here we present a workflow to analyze the metabolic profiles for biological samples of interest including; cells, serum, or tissue. The sample is first separated into polar and non-polar fractions by a liquid-liquid phase extraction, and partially purified to facilitate downstream analysis. Both aqueous (polar metabolites) and organic (non-polar metabolites) phases of the initial extraction are processed to survey a broad range of metabolites. Metabolites are separated by different liquid chromatography methods based upon their partition properties. In this method, we present microflow ultra-performance (UP)LC methods, but the protocol is scalable to higher flows and lower pressures. Introduction into the mass spectrometer can be through either general or compound optimized source conditions. Detection of a broad range of ions is carried out in full scan mode in both positive and negative mode over a broad m/z range using high resolution on a recently calibrated instrument. Label-free differential analysis is carried out on bioinformatics platforms. Applications of this approach include metabolic pathway screening, biomarker discovery, and drug development.
Biochemistry, Issue 75, Chemistry, Molecular Biology, Cellular Biology, Physiology, Medicine, Pharmacology, Genetics, Genomics, Mass Spectrometry, MS, Metabolism, Metabolomics, untargeted, extraction, lipids, accurate mass, liquid chromatography, ultraperformance liquid chromatography, UPLC, high resolution mass spectrometry, HRMS, spectrometry
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A Strategy for Sensitive, Large Scale Quantitative Metabolomics
Authors: Xiaojing Liu, Zheng Ser, Ahmad A. Cluntun, Samantha J. Mentch, Jason W. Locasale.
Institutions: Cornell University, Cornell University.
Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. However, current platforms have different limiting factors, such as labor intensive sample preparations, low detection limits, slow scan speeds, intensive method optimization for each metabolite, and the inability to measure both positively and negatively charged ions in single experiments. Therefore, a novel metabolomics protocol could advance metabolomics studies. Amide-based hydrophilic chromatography enables polar metabolite analysis without any chemical derivatization. High resolution MS using the Q-Exactive (QE-MS) has improved ion optics, increased scan speeds (256 msec at resolution 70,000), and has the capability of carrying out positive/negative switching. Using a cold methanol extraction strategy, and coupling an amide column with QE-MS enables robust detection of 168 targeted polar metabolites and thousands of additional features simultaneously.  Data processing is carried out with commercially available software in a highly efficient way, and unknown features extracted from the mass spectra can be queried in databases.
Chemistry, Issue 87, high-resolution mass spectrometry, metabolomics, positive/negative switching, low mass calibration, Orbitrap
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Stable Isotopic Profiling of Intermediary Metabolic Flux in Developing and Adult Stage Caenorhabditis elegans
Authors: Marni J. Falk, Meera Rao, Julian Ostrovsky, Evgueni Daikhin, Ilana Nissim, Marc Yudkoff.
Institutions: The Children's Hospital of Philadelphia, University of Pennsylvania.
Stable isotopic profiling has long permitted sensitive investigations of the metabolic consequences of genetic mutations and/or pharmacologic therapies in cellular and mammalian models. Here, we describe detailed methods to perform stable isotopic profiling of intermediary metabolism and metabolic flux in the nematode, Caenorhabditis elegans. Methods are described for profiling whole worm free amino acids, labeled carbon dioxide, labeled organic acids, and labeled amino acids in animals exposed to stable isotopes either from early development on nematode growth media agar plates or beginning as young adults while exposed to various pharmacologic treatments in liquid culture. Free amino acids are quantified by high performance liquid chromatography (HPLC) in whole worm aliquots extracted in 4% perchloric acid. Universally labeled 13C-glucose or 1,6-13C2-glucose is utilized as the stable isotopic precursor whose labeled carbon is traced by mass spectrometry in carbon dioxide (both atmospheric and dissolved) as well as in metabolites indicative of flux through glycolysis, pyruvate metabolism, and the tricarboxylic acid cycle. Representative results are included to demonstrate effects of isotope exposure time, various bacterial clearing protocols, and alternative worm disruption methods in wild-type nematodes, as well as the relative extent of isotopic incorporation in mitochondrial complex III mutant worms (isp-1(qm150)) relative to wild-type worms. Application of stable isotopic profiling in living nematodes provides a novel capacity to investigate at the whole animal level real-time metabolic alterations that are caused by individual genetic disorders and/or pharmacologic therapies.
Developmental Biology, Issue 48, Stable isotope, amino acid quantitation, organic acid quantitation, nematodes, metabolism
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Metabolomic Analysis of Rat Brain by High Resolution Nuclear Magnetic Resonance Spectroscopy of Tissue Extracts
Authors: Norbert W. Lutz, Evelyne Béraud, Patrick J. Cozzone.
Institutions: Aix-Marseille Université, Aix-Marseille Université.
Studies of gene expression on the RNA and protein levels have long been used to explore biological processes underlying disease. More recently, genomics and proteomics have been complemented by comprehensive quantitative analysis of the metabolite pool present in biological systems. This strategy, termed metabolomics, strives to provide a global characterization of the small-molecule complement involved in metabolism. While the genome and the proteome define the tasks cells can perform, the metabolome is part of the actual phenotype. Among the methods currently used in metabolomics, spectroscopic techniques are of special interest because they allow one to simultaneously analyze a large number of metabolites without prior selection for specific biochemical pathways, thus enabling a broad unbiased approach. Here, an optimized experimental protocol for metabolomic analysis by high-resolution NMR spectroscopy is presented, which is the method of choice for efficient quantification of tissue metabolites. Important strengths of this method are (i) the use of crude extracts, without the need to purify the sample and/or separate metabolites; (ii) the intrinsically quantitative nature of NMR, permitting quantitation of all metabolites represented by an NMR spectrum with one reference compound only; and (iii) the nondestructive nature of NMR enabling repeated use of the same sample for multiple measurements. The dynamic range of metabolite concentrations that can be covered is considerable due to the linear response of NMR signals, although metabolites occurring at extremely low concentrations may be difficult to detect. For the least abundant compounds, the highly sensitive mass spectrometry method may be advantageous although this technique requires more intricate sample preparation and quantification procedures than NMR spectroscopy. We present here an NMR protocol adjusted to rat brain analysis; however, the same protocol can be applied to other tissues with minor modifications.
Neuroscience, Issue 91, metabolomics, brain tissue, rodents, neurochemistry, tissue extracts, NMR spectroscopy, quantitative metabolite analysis, cerebral metabolism, metabolic profile
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Purification of Transcripts and Metabolites from Drosophila Heads
Authors: Kurt Jensen, Jonatan Sanchez-Garcia, Caroline Williams, Swati Khare, Krishanu Mathur, Rita M. Graze, Daniel A. Hahn, Lauren M. McIntyre, Diego E. Rincon-Limas, Pedro Fernandez-Funez.
Institutions: University of Florida , University of Florida , University of Florida , University of Florida .
For the last decade, we have tried to understand the molecular and cellular mechanisms of neuronal degeneration using Drosophila as a model organism. Although fruit flies provide obvious experimental advantages, research on neurodegenerative diseases has mostly relied on traditional techniques, including genetic interaction, histology, immunofluorescence, and protein biochemistry. These techniques are effective for mechanistic, hypothesis-driven studies, which lead to a detailed understanding of the role of single genes in well-defined biological problems. However, neurodegenerative diseases are highly complex and affect multiple cellular organelles and processes over time. The advent of new technologies and the omics age provides a unique opportunity to understand the global cellular perturbations underlying complex diseases. Flexible model organisms such as Drosophila are ideal for adapting these new technologies because of their strong annotation and high tractability. One challenge with these small animals, though, is the purification of enough informational molecules (DNA, mRNA, protein, metabolites) from highly relevant tissues such as fly brains. Other challenges consist of collecting large numbers of flies for experimental replicates (critical for statistical robustness) and developing consistent procedures for the purification of high-quality biological material. Here, we describe the procedures for collecting thousands of fly heads and the extraction of transcripts and metabolites to understand how global changes in gene expression and metabolism contribute to neurodegenerative diseases. These procedures are easily scalable and can be applied to the study of proteomic and epigenomic contributions to disease.
Genetics, Issue 73, Biochemistry, Molecular Biology, Neurobiology, Neuroscience, Bioengineering, Cellular Biology, Anatomy, Neurodegenerative Diseases, Biological Assay, Drosophila, fruit fly, head separation, purification, mRNA, RNA, cDNA, DNA, transcripts, metabolites, replicates, SCA3, neurodegeneration, NMR, gene expression, animal model
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MALDI-Mass Spectrometric Imaging for the Investigation of Metabolites in Medicago truncatula Root Nodules
Authors: Erin Gemperline, Lingjun Li.
Institutions: University of Wisconsin- Madison, University of Wisconsin- Madison.
Most techniques used to study small molecules, such as pharmaceutical drugs or endogenous metabolites, employ tissue extracts which require the homogenization of the tissue of interest that could potentially cause changes in the metabolic pathways being studied1. Mass spectrometric imaging (MSI) is a powerful analytical tool that can provide spatial information of analytes within intact slices of biological tissue samples1-5. This technique has been used extensively to study various types of compounds including proteins, peptides, lipids, and small molecules such as endogenous metabolites. With matrix-assisted laser desorption/ionization (MALDI)-MSI, spatial distributions of multiple metabolites can be simultaneously detected. Herein, a method developed specifically for conducting untargeted metabolomics MSI experiments on legume roots and root nodules is presented which could reveal insights into the biological processes taking place. The method presented here shows a typical MSI workflow, from sample preparation to image acquisition, and focuses on the matrix application step, demonstrating several matrix application techniques that are useful for detecting small molecules. Once the MS images are generated, the analysis and identification of metabolites of interest is discussed and demonstrated. The standard workflow presented here can be easily modified for different tissue types, molecular species, and instrumentation.
Basic Protocol, Issue 85, Mass Spectrometric Imaging, Imaging Mass Spectrometry, MALDI, TOF/TOF, Medicago truncatula, Metabolite, Small Molecule, Sublimation, Automatic Sprayer
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Dithranol as a Matrix for Matrix Assisted Laser Desorption/Ionization Imaging on a Fourier Transform Ion Cyclotron Resonance Mass Spectrometer
Authors: Cuong H. Le, Jun Han, Christoph H. Borchers.
Institutions: University of Victoria, University of Victoria.
Mass spectrometry imaging (MSI) determines the spatial localization and distribution patterns of compounds on the surface of a tissue section, mainly using MALDI (matrix assisted laser desorption/ionization)-based analytical techniques. New matrices for small-molecule MSI, which can improve the analysis of low-molecular weight (MW) compounds, are needed. These matrices should provide increased analyte signals while decreasing MALDI background signals. In addition, the use of ultrahigh-resolution instruments, such as Fourier transform ion cyclotron resonance (FTICR) mass spectrometers, has the ability to resolve analyte signals from matrix signals, and this can partially overcome many problems associated with the background originating from the MALDI matrix. The reduction in the intensities of the metastable matrix clusters by FTICR MS can also help to overcome some of the interferences associated with matrix peaks on other instruments. High-resolution instruments such as the FTICR mass spectrometers are advantageous as they can produce distribution patterns of many compounds simultaneously while still providing confidence in chemical identifications. Dithranol (DT; 1,8-dihydroxy-9,10-dihydroanthracen-9-one) has previously been reported as a MALDI matrix for tissue imaging. In this work, a protocol for the use of DT for MALDI imaging of endogenous lipids from the surfaces of mammalian tissue sections, by positive-ion MALDI-MS, on an ultrahigh-resolution hybrid quadrupole FTICR instrument has been provided.
Basic Protocol, Issue 81, eye, molecular imaging, chemistry technique, analytical, mass spectrometry, matrix assisted laser desorption/ionization (MALDI), tandem mass spectrometry, lipid, tissue imaging, bovine lens, dithranol, matrix, FTICR (Fourier Transform Ion Cyclotron Resonance)
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Bladder Smooth Muscle Strip Contractility as a Method to Evaluate Lower Urinary Tract Pharmacology
Authors: F. Aura Kullmann, Stephanie L. Daugherty, William C. de Groat, Lori A. Birder.
Institutions: University of Pittsburgh School of Medicine, University of Pittsburgh School of Medicine.
We describe an in vitro method to measure bladder smooth muscle contractility, and its use for investigating physiological and pharmacological properties of the smooth muscle as well as changes induced by pathology. This method provides critical information for understanding bladder function while overcoming major methodological difficulties encountered in in vivo experiments, such as surgical and pharmacological manipulations that affect stability and survival of the preparations, the use of human tissue, and/or the use of expensive chemicals. It also provides a way to investigate the properties of each bladder component (i.e. smooth muscle, mucosa, nerves) in healthy and pathological conditions. The urinary bladder is removed from an anesthetized animal, placed in Krebs solution and cut into strips. Strips are placed into a chamber filled with warm Krebs solution. One end is attached to an isometric tension transducer to measure contraction force, the other end is attached to a fixed rod. Tissue is stimulated by directly adding compounds to the bath or by electric field stimulation electrodes that activate nerves, similar to triggering bladder contractions in vivo. We demonstrate the use of this method to evaluate spontaneous smooth muscle contractility during development and after an experimental spinal cord injury, the nature of neurotransmission (transmitters and receptors involved), factors involved in modulation of smooth muscle activity, the role of individual bladder components, and species and organ differences in response to pharmacological agents. Additionally, it could be used for investigating intracellular pathways involved in contraction and/or relaxation of the smooth muscle, drug structure-activity relationships and evaluation of transmitter release. The in vitro smooth muscle contractility method has been used extensively for over 50 years, and has provided data that significantly contributed to our understanding of bladder function as well as to pharmaceutical development of compounds currently used clinically for bladder management.
Medicine, Issue 90, Krebs, species differences, in vitro, smooth muscle contractility, neural stimulation
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