Metabolomics/Analytical Methods/Mass Spectrometry/GC-MS
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TagFinder
[edit | edit source]GC-MS-based metabolite profiling experiments typically comprise of hundreds of chromatogram files. Each of these files may contain up to 1000 mass spectral tags (MSTs). MSTs are the individual patterns of approximately 25 – 250 fragment ions and respective isotopomers. The patterns are generated from gas chromatography (GC) by electron impact ionization (EI) of separated chemical molecules. The fragment ions are detected by time-of-flight (TOF) mass spectrometry (MS). Experimentally profiled MSTs are usually reported as a list of ions that are characterized by their mass, chromatographic retention index (RI) or retention time (RT), and arbitrary abundance. Mass and RI characterization is used to identify and quantify analyzed chemical compounds. The employment of pre-processing tools provides numerical data matrices that contain all aligned MSTs and samples of an experiment. Errors in this process are likely to result from imprecision in RI or RT alignment of MSTs and/or highly complex biological samples. Biological complexity may lead to impure MSTs via compound co-elution. Therefore, this potential simultaneous elution mandates technology capable of quantitative and qualitative analysis of co-eluting compounds. TagFinder, a developing software tool, is expected to be capable of validating data matrices prior to statistical analyses.
“TagFinder facilitates the analysis of all fragment ions, which are observed in GC-(EI-TOF)-MS profiling experiments.” Compound discovery is also facilitated by a non-targeted approach. Furthermore, TagFinder processing maintains mass isotopomer resolution, which is a necessary feature during metabolic flux analyses, and can be especially useful for metabolite profiling. TagFinder also prioritizes the standardization of chemical means. Specifically, the software will make use of internal reference compounds for retention time calibration or quantitative standardization. Maintenance of external standardization of compound identification and calibration is also featured. TagFinder functionality is ordered as follows: 1)import of fragment ion data, including mass, time, and arbitrary abundance, 2)annotating sample information and the grouping of samples into classes, 3)calculating the RI, 4)binning observed fragment ions of equal mass from different chromatograms into RI windows, 5)combining the bins and mass tags into time groups of co-eluting fragment ions, 6)testing of time groups for intensity correlated mass tags, 7)data matrix generation, and 8)compound identification supported extraction of selective mass tags. In synopsis, TagFinder maintains and is compatible with non-targeted fingerprinting analysis as well as metabolite targeted profiling.
TagFinder has proven to be an exceedingly useful tool for aligning large GC-MS-based metabolite profiling experiments into data matrices. TagFinder is also capable of automatically extracting quantitative data enhanced by mass spectral matching to reference mass spectra from provided RI windows. Inclusive quantitative data might comprise of mass fragments, time groups of mass fragments or clusters of intensity-correlated mass fragments. In addition, generating data matrices provides user intervention featured for automatic parameter optimization. TagFinder has also proven to be especially applicable to non-biased metabolomics fingerprinting, footprinting and profiling, as well as quantitative and qualitative metabolite analyses.
References
[edit | edit source]Websites
[edit | edit source]Bioinformatics
[edit | edit source]http://bioinformatics.oxfordjournals.org/cgi/content/full/22/11/1391
This website is actually an article that provides a brief introduction about what metabolomics. There are two approaches that are associated with metabolomics: metabolic fingerprinting and metabolic profiling. However, metobolomic studies tend to use gas chromatography mass spectrometry (GS-MS), liquid chromatography mass spectrometry (LC-MS), capillary electrophoresis mass spectrometry (CE-MS), direct infusion electrospray ionization mass spectrometry (ESI-MS), and NMR. These analytical techniques produce signals that consist of informative peaks embedded in a continuum of background noise. However, the researcher’s goal was to explore the idea of peak clustering for the consolidation of signal lists using a two-step hierarchical clustering of peak signals. First it will be used within each set of replicate experiments then between the sets of replicate experiments. Researchers will test this method using GC-MS metabolic studies of Leishmania mexicana.
Terms
- Liquid chromatography mass spectrometry (LC-MS)
- analytical chemistry chemical technique that combines the physical separation capabilities of liquid chromatography (i.e. HPLC) with the mass analysis capabilities of mass spectrometry.
- Metabolic profiling
- purpose is to resolve, identify and quantitate individual analytes
- Metabolic fingerprinting
- refers to the analysis of patterns in the molecular response profiles without an attempt to resolve individual analytes
- gas chromatography mass spectrometry (GS-MS)
- separates the components of a mixture and mass spectroscopy characterizes each of the components individually
- Capillary electrophoresis mass spectrometry (CE-MS)
- increases the utility of a CE separation. The mass spectrometer (MS) allows unambiguous information on a solute's molecular weight and also provides structural information helping with the identification of unknowns
Connection No specific correlation to coursework. Just a general overview of various analytical methods and it also explains how GC-MS works.
This website is actually a book about plant metabolomics. It states that GC-MS is one of the most common technology platforms used in metabolomics studies. It is used for metabalome profiling analysis. In order to use GC-MS for metabolomic profiling, there must be clear distinction between metabolite and analyte because metabolites can be chemically transformed before quantification. It also provides information about the metabolite profiles. Other information includes the pros and cons of using GC-MS for metabolomics.
Terms
- analyte
- term used to address the chemical structure and compound that is submitted to GC-MS to be detected and quantified
- mass special tag
- a mass spectrum that is characterized by a specific chromatographic retention and repeated occurrence in a single or multiple types of biological samples
- alkoxyamination
- conducted with reagents such as methoxyamine to stabilize carbonyl moieties in native metabolic structures; however it forms E and Z-isomers of the –N=C< double bond substituents
- metabolite
- compound which is internalized, chemically converted, or secreted by an organism but is not yet synthesized by DNA replication, transcription, translation
- ion current
- The electric current resulting from motion of ions
Connection: This article also describes how radioactive labeled techniques are used to identify certain metabolites. We have talked about radioactive labeled Carbon when we were trying to figure out where does the carbon from CO2 fit in the rubisco mechanism.
BBSRC
[edit | edit source]This website provided background information on metabolomics. It also lists various techniques that are used in metabolomics. Metabolic analysis is divided into four groups: target compound analysis, metabolic profiling, metabolomics, and metabolic profiling. The way the GC-MS works in this specific field is that helps detect a specific class of metabolites. If the sample is too volatile, then it has to be converted to something less polar before it can be applied to the GC column.
Terms:
- target compound analysis
- focuses on the quantification of specific metabolites
- transcriptomics
- the study of the transcriptome, the complete set of RNA transcripts produced by the genome at any one time
- proteomics
- the qualitative and quantitative comparison of proteomes under different conditions to further unravel biological processes
- National Centre for Plant and Microbial Metabolomics
- leading UK facility for research and service activity in plant and microbial metabolomics; goal is to provide a focus of research activities to overcome this hurdle and allow post-genomic science to truly focus on fully integrative aspects of organism 'phenotype'
- Genomics
- the study of an organism's entire genome; includes intensive efforts to determine the entire DNA sequence of organisms and fine-scale genetic mapping effort
Connection: There is no connection to coursework. It just provides an overview of the development of metabolomics and the analytical methods used including GC-MS.
Articles
[edit | edit source]This article focuses on the cis-trans isomerization of unsaturated fatty acids found in the cells of Pseudomonas putida. This group of bacteria has a high tolerance for aromatic solvents. The reason why this group of bacteria can grow in the presence of membrane-disrupting compounds is due to the isomerization of cis to trans unsaturated fatty acids. The isomrase activity does not utilize ATP or other cofactors such as NAD(P)H. The fact that it is independent of ATP corresponds with the negative free energy of the cis-trans isomerization. The fatty acid methyl esters were examined and analyzed using GC-MS. The fatty acids that become unsaturated were also identified by GC-MS.
Terms:
- Fatty acid methyl ester (FAME)
- can be created by an alkali catalyzed reaction between fats or fatty acids and methanol. The molecules in biodiesel are primarily FAMEs, usually obtained from vegetable oils by transesterification.
- Isomerization
- the transformation of a molecule into a different isomer. It also converts an aldose to a ketose or a ketose to an aldose.
- Unsaturated fatty acids
- is a fat or fatty acid in which there are one or more double bonds in the fatty acid chain
- Cis-trans isomers
- sterioisomeric olefins or cycloalkanes which differ in the positions of atoms relative to a reference plane; in the cis-isomer atoms are on the same side and in the trans-isomer atoms are on opposite sides
- Oleic acid
- fatty acid found in animal and vegetable oils. It is called a mono-unsaturated fatty acid because of the single double bond between the carbons. Its physical properties are determined by the number, geometry, and position of this double bond and the degree of unsaturation.
Connection: We have talked about ATP and NAD(P)H in many pathways. For example, glycolysis produces and uses ATP as a source of energy. NADPH is reductive; it acts as an electron donor in the biosynthesis of fatty acids as well as in oxidative reduction.
This article focuses on determination of fluxes in the metabolites within a cell. The determination of fluxes provides a clear description of metabolism before and after engineering interventions. Researcher’s show how a strain of E. coli was used engineered to produce amorphadiene. Amorphadiene is a precursor to the antimalarial drug artemisinin. Cells were grown in continuous cultures of glucose containing 20% 20% [U-13C] glucose. Twenty percent [U-13C] glucose was measured out using GC-MS conducted on 13 amino acids taken from the cells. Researches use a mathematical approach to determine the number of fluxes.
Terms:
- Atom Mapping Matrices (AMM)
- describe the transfer of carbon atoms from the reactants to products
- Isotopomer mapping matrices (IMMs)
- indicate the possible product isotopomers that can be created from each reactant isotopomer
- Terpenoids
- class of isoprenoids often isolated from plants, and are currently used for a variety of applications including anticancer and antimicrobial drugs
- Flux
- change in the metabolic pathway in terms of energy
- Mevalonate
- salt of mevalonic acid; also plays an important role in the synthesis of cholesterol
Connection: This article mentions the Pentose Phosphate Pathway, glycolysis, and the tricarboxylic acid cycle. It also discusses the anaplerotic reactions and amino acid biosynthesis and the degradation pathways. We also have learned throughout the course of metabolism that the cofactors such as ATP, NADH, and NADPH are balanced. In the article this balance was shown by reactions for energy generation via substrate-level, oxidative phosphorylation, and tranhydrogenase activity.
This article uses comparative metabolic profiling of cancerous cells and non-cancerous cells to help understand the crucial elements of tumorigenesis as well as find new ways of drugs. Even though there has been progress in metabolomics technology, research has sort of been hindered due to technical challenges. Problems such as incomplete reference data, limited availability of biological material, insufficient sensitivity and resolution of existing protocols, and the lack of established computational modeling framework are common in this field. To overcome these problems, researchers have combined [U -13C]-glucose two dimensional NMR and GC-MS techniques to test the metabolite pools and fluxes associated with some of the interrelated metabolic pathways in humans. The reason for using comparative analysis of breast cancer cells and non-cancerous breast cells for this approach was because it is the central backbone of metabolism providing energy, cofactor regeneration, and building blocks for cell synthesis. Cancer cells have also been identified to display different roles in some of the above pathways.
Terms:
- Non-essential amino acids
amino acids that are not produced by humans and they are not essential.
- NMR
- nuclear magnetic resonance; a physical phenomenon based upon the quantum mechanical magnetic properties of an atom's nucleus
- Tumorigenesis
- s the formation of tumors in the body, often caused by the mutation of oncogenes. These tumors are the result of uncontrollable reproduction (cell division) due to alterations in the cell's genes, creating lesions in the tissue where they reside
- Anaplerotic flux
- replenishing of the intermediates of a given pathway such as the citric acid cycle
- Isotopomer
isomers having the same number of each isotopic atom but differing in their positions
Connection: We have extensively explored the citric acid cycle and its key components. In this article, these points are also revisited. Also, the article talks about the fluctuations associated with this cycle.
This article states that amino acid labelings possess significant information for the calculation of metabolic fluxes. As opposed to proteins, intracellular amino acids are permanently synthesized and consumed. Since intracellular amino acids have a low concentration in the millimolar range GCMS was used to analyze the data since it is an excellent tool for fast, accurate and sensitive labeling analysis. Overall, the experiment conducted was on intracellular amino acids derived from S. cerevisiae. The amino acids were identified by comparing their mass spectra obtained in scan mode and their retention times with pure TBDMS amino acids.
Terms:
- Retention time
- the ionic contamination testing of semiconductor leadframes, the time required for a particular ion type to pass from the injection port to the detector. Retention time is characteristically different for each ion type
- HPLC
- High-performance liquid chromatography is a form of column chromatography used frequently in biochemistry and analytical chemistry. It is also sometimes referred to as high-pressure liquid chromatography. HPLC is used to separate components of a mixture by using a variety of chemical interactions between the substance being analyzed (analyte) and the chromatography column.
- Proteinogenic amino acid
- also known as standard, normal, or primary amino acids are those 20 amino acids that are found in proteins and that are coded for in the standard genetic code. Proteinogenic literally means protein building. Proteinogenic amino acids are assembled into a polypeptide (the subunit of a protein) through a process known as translation (the second stage of protein biosynthesis, part of the overall process of gene expression).
- Lyophilized
- freeze dry
- Derivatization
- is a technique used in chemistry which transforms a chemical compound into a product of similar chemical structure, called derivative.
Connection: In class we have been talking about amino acids and where they are derived from in terms of the pathways that we have talked about. In this article an amino acid was reacted with N-methyl-N-t-butyldimethylsilyl trifluoroacetamide to create t-butyldimethylsilyl (TBDMS) derivate. Amino acids that composed a functional group were converted to TBDMS derivatized residues. If you look at the tables associated with the article, you will be able to tell which TBDMS derivates were formed. In class, we learned how aspartate was formed from glucose. This is formed by either pyruvate which goes to oxaaloacetate using a pyruvate carboxylase and biotin or acetyly CoA which goes on to produce citrate through the citric acid cycle.
HOW GC-MS WORKS
[edit | edit source]http://www.scientific.org/tutorials/articles/gcms.html This is a website that explains exactly how GC-MS works.
GC-MS is separated into two parts. The first part is the gas chromatography portion. In this portion, chemical mixtures are separated into pulses of pure chemicals. Chemicals are separated based on their volatility, or ease in which they evaporate into a gas. There are three main components of the GS potion: the injection point-1 microliter of solvent containing the chemical mixture of molecules is injected into the GC. The sample is carried by inert gas through the instrument. The inert gas is usually helium. The inject port is heated to 300° C. This temperature causes the chemicals to become gases; oven- outer part of the GC system. The columns are heated to move the molecules through the columns. Average oven temperatures are between 40°-320° C; column- located inside the oven. They are 30 meter thin tubes with a special polymer coating on the inside. Chemical mixtures are separated based on their votality and are carried through the column by helium. Chemicals with high volatility travel through the column more quickly than chemicals with low votality.
MS is the second portion. This portion is used to identify chemicals based on their structure. There are three parts: ion source- after going the molecules go through the GC portion, they are blasted with electrons to break them into pieces and changed into positively charged particles called ions; filter- electromagnetic field that filters the ions based on mass; detector- counts the number of ions with a specific mass. Information is sent to the computer and a mass spectrum is created.
IMAGES OF GC-MS
[edit | edit source]LINK TO WIKIPEDIA IN TERMS OF GC-MS
http://en.wikipedia.org/wiki/GC-MS
Articles and Web Pages for Review and Inclusion
[edit | edit source]Peer-Reviewed Article #1:
Temporally resolved GC-MS-based metabolic profiling of herbicide treated plants treated reveals that changes in polar primary metabolites alone can distinguish herbicides of differing mode of action
Metabolomics. 2009 September; 5(3): 277–291'"
Main Focus
[edit | edit source]- Identify the main focus of the resource. Possible answers include specific organisms, database design, intergration of information, but there are many more possibilities as well.
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Summary
[edit | edit source]- Enter your article summary here. Please note that the punctuation is critical at the start (and sometimes at the end) of each entry. It should be 300-500 words. What are the main points of the article? What questions were they trying to answer? Did they find a clear answer? If so, what was it? If not, what did they find or what ideas are in tension in their findings?
Relevance to a Traditional Metabolism Course
[edit | edit source]- Enter a 100-150 word description of how the material in this article connects to a traditional metabolism course. Does the article relate to particular pathways (e.g., glycolysis, the citric acid cycle, steroid synthesis, etc.) or to regulatory mechanisms, energetics, location, integration of pathways? Does it talk about new analytical approaches or ideas? Does the article show connections to the human genome project (or other genome projects)?