C146-E095 Metabolite Profiling of NSAID Effects In Vitro ... · Metabolite Profiling of NSAID...
1
Introduction Methods Atmospheric pressure ionization source Quadrupole array to focus ions into the octopole Ion trap There are 2 functions of the ion trap 1 – Pulsed Argon gas eliminates CID energy mass dependence and achieve high CID efficiency. 2 – Pulse ions into the TOF mass analyser at a precise start time. Heated capillary inlet The octopole acts as an ion gate, holding and controlling ions before release into the ion trap itself. Name Drug Dose Name Drug Dose ASA - HD ASA - LD Cel - LD Cel - LD DMSO ASA (aspirin) ASA Celebrex Celebrex none (solvent) high - 3mM low - 1mM high - 100µM low - 10µM none Indo - HD Indo - LD Viox - LD Viox - LD Indomethacin Indomethacin Vioxx Vioxx high - 800µM low - 100µM high - 200µM low - 20µM In total, 27 drug-treated HT29 cancer cell line samples were analyzed on the LCMS-IT-TOF system using a positive ion ESI with a scan range of 150 to 1000 m/z. All unique MS/retention time pairs represent sample-specific metabolites, and metabolite fragments are visualized in a metabolite array (Figure 2). Purple represents metabolites with the greater intensity and followed by dark blue, and light blue represents undetected metabolites. Each column of the array represents one sample, and each row represents a single MS/retention time pair. The array can then be analyzed, and key metabolites identified, using numerous statistical (unsupervised analysis) and Boolean search(supervised analysis) tools incorporated in the Phenomenome Profiler™ software. As displayed in Figure 2, the array has been clustered hierarchically by sample and metabolite, as indicated by the dendrogram at the top and left of the array. As you can see clearly by the array, drug-related metabolites are clustered together. Results Metabolite array of drug-treated HT29 human cancer cell line samples. Figure 2. Molecular Formula Finder assigns the molecular formulae based on accurate MS. Figure 5b. Extracted accurate MS ion chromatogram at m/z of 289.269. Figure 4. Variable subtraction of extracted averaged accurate MS spectrum of indomethacin (minus DMSO) at retention time of 15.68 min.. Figure 5a. > 350 unique MS/retention time pairs 27 separate samples Indo-HD ASA-HD Cel-HD DMSO Viox-LD ASA-LD Indo-LD Cel-LD Viox-HD Indo minus DMSO DMSO Indo Indo-HD ASA-HD ASA-LD DMSO Viox-LD Cel-HD Indo-LD Viox-HD Cel-LD Discussion and Conclusions For the comprehensive metabolite analysis, we employed a Shimadzu LCMS-IT-TOF (Figure 1), a new hybrid MS spectrometer combining an ion trap with time-of-flight. This instrument enables the acquisition of MS and MS n spectral data featuring high resolution, high mass accuracy, and high sensitivity. These valuable attributes are due to the following features of the LCMS-IT- TOF: compressed ion introduction methods, improvements to Dual Stage Reflection, ion cooling using argon gas, and a temperature- controlled time of flight mass analyser. Phenomenome Profiler™’s new profile-matching tool uses the same concepts as other cluster analysis tools used in multivariate statistical analyses. By simply selecting the metabolite of interest from the array, this tool will extract all other metabolites with the same expression profile. As pictured in Figure 3a, by selecting the indomethacin-high dose (indo-HD) effect, the program indicates any indo-HD-related down- regulated endogenous metabolites. Phenomenome Profiler™ will also display the expression pattern of those selected metabolites, as shown in Figure 3b. Real-time interaction exists between the array tables and the underlying raw chromatogram and MS spectrum data. Figure 4 shows the extracted accurate MS ion chromatogram (EIC) of the indicated row from Figure 3a. In this figure, the assigned variables are grouped together and displayed as an EIC overlay. Some of the metabolites of interest were related to indomethacin metabolism in vitro; these were extracted from the array (Figure 2), and are displayed in Figure 5a as a variable subtraction of the extracted MS spectrum. According to the accurate mass information, we can easily assign the putative molecular formula—one of the remarkable features of Profiler™ software—as shown in Figure 5b. In this example, the detected metabolite was indomethacin itself. The Molecular Formula Finder also identifies carbon- 13 metabolites in the same array. Human cancer cell lines are invaluable tools for many aspects of basic cancer research, ranging from purely investigational studies to drug efficacy and toxicity studies. The ability to measure endogenous and excreted metabolites over the course of such studies creates an opportunity to quantify the resulting phenotypes. Metabolites found to correlate with specific biological events are highly informative, and can be utilized as biomarkers for numerous applications, including disease diagnosis, drug efficacy and toxicity, as well as basic investigational research. Traditionally, the most common platforms for studying metabolites have included LC-MS, GC-MS and NMR. Recent technological advancements in MS instrumentation, such as the Shimadzu LCMS-IT-TOF system, enable the acquisition of high resolution and high mass accuracy MS data suitable for novel metabolite discovery. Although these instruments have been developed, no complementary software has been designed specifically to interpret resulting metabolomics data. To address these issues, we have developed Phenomenome Profiler™ software to handle MS spectrometry-based analysis of biological samples. Phenomenome Profiler™ also easily performs a number of multivariate statistical functions on the raw data. HT29 human colon cancer cell lines were grown to 80% confluency, and were treated with four drugs using high and low doses (listed below). After 24-hour treatment, media from each triplicate treatment was analyzed randomly. A total of 27 samples were processed via a proprietary extraction method, optimized to separate the metabolites into multiple extracts based on polarity and acid/base chemistry. HPLC was carried out on an LC-10ADVP pump and SIL-10ADVP auto-injector. MS analysis was performed on the LCMS-IT-TOF using an ESI source. All instruments and columns described above were obtained from Shimadzu Corporation (Kyoto, Japan). Indomethacin-related down-regulated endogenous metabolites; Figure 3a. Metabolite coordinate plot. Figure 3b. Yasuyo Yamazaki 1 , Yusuke Inohana 2 , Shinichi Yamaguchi 2 . 1 Phenomenome Discoveries Inc., Saskatoon, SK, Canada, 2 Shimadzu Corporation, Kyoto, Japan C146-E095 Metabolite Profiling of NSAID Effects In Vitro Using Shimadzu LCMS-IT-TOF System With Phenomenome Profiler™ Software 3295-10602-10A-IK Overview Global metabolite profiling software was used to measure and compare the metabolic changes induced by several NSAIDs in HT29 cells and media. This approach can be used as a model system in monitoring drug metabolism in vitro. To help find components of biological significance the Shimadzu LCMS-IT-TOF was used to provide high mass accuracy MS n data integrated with Phenomenome Profiler™ software to integrate chromatography and mass spectrometry data sets together with statistical methods. Phenomenome Profiler™ software is the world’s first universal metabolomics software solution developed specifically for metabolomics research projects. It is an integrated suite of algorithms, statistical methods, and computer applications to support global profiling of complex mixtures using MS. Shimadzu Corporation are a key partner with Phenomenome Informatics, a division of Phenomenome Discoveries
Transcript of C146-E095 Metabolite Profiling of NSAID Effects In Vitro ... · Metabolite Profiling of NSAID...
Introduction
Methods
Atmosphericpressure ionizationsource
Quadrupole array to focusions into the octopole
Ion trapThere are 2 functions of the ion trap1 – Pulsed Argon gas eliminates CID energy massdependence and achieve high CID efficiency.2 – Pulse ions into the TOF mass analyser at a precisestart time.
Heated capillary inlet
The octopole acts as an ion gate, holding andcontrolling ions before release into the ion trap itself.
Name Drug Dose Name Drug Dose
ASA - HD
ASA - LD
Cel - LD
Cel - LD
DMSO
ASA (aspirin)
ASA
Celebrex
Celebrex
none (solvent)
high - 3mM
low - 1mM
high - 100µM
low - 10µM
none
Indo - HD
Indo - LD
Viox - LD
Viox - LD
Indomethacin
Indomethacin
Vioxx
Vioxx
high - 800µM
low - 100µM
high - 200µM
low - 20µM
In total, 27 drug-treated HT29 cancercell line samples were analyzed onthe LCMS-IT-TOF system using apositive ion ESI with a scan range of150 to 1000 m/z. All uniqueMS/retention time pairs representsample-specific metabolites, andmetabolite fragments are visualizedin a metabolite array (Figure 2).
Purple represents metabolites withthe greater intensity and followed bydark blue, and light blue representsundetected metabolites. Eachcolumn of the array represents onesample, and each row represents asingle MS/retention time pair.
The array can then be analyzed, andkey metabolites identified, usingnumerous statistical (unsupervisedanalysis) and Booleansearch(supervised analysis) toolsincorporated in the PhenomenomeProfiler™ software.
As displayed in Figure 2, the arrayhas been clustered hierarchically bysample and metabolite, as indicatedby the dendrogram at the top and leftof the array. As you can see clearlyby the array, drug-relatedmetabolites are clustered together.
Results
Metabolite array of drug-treatedHT29 human cancer cell line samples.
Figure 2. Molecular Formula Finder assigns the molecular formulaebased on accurate MS.
Figure 5b. Extracted accurate MS ionchromatogram at m/z of 289.269.
Figure 4.
Variable subtraction of extracted averaged accurateMS spectrum of indomethacin (minus DMSO) atretention time of 15.68 min..
Figure 5a.
> 350 uniqueMS/retention timepairs
27 separate samples
Indo
-HD
AS
A-H
D
Cel
-HD
DM
SO
Vio
x-LD
AS
A-L
D
Indo
-LD
Cel
-LD
Vio
x-H
D
Indo minusDMSO
DMSO
Indo
Indo-HD
ASA-HD
ASA-LD
DMSO
Viox-LD
Cel-HD
Indo-LD
Viox-HD
Cel-LD
Discussion andConclusionsFor the comprehensive metabolite analysis, weemployed a Shimadzu LCMS-IT-TOF (Figure 1),a new hybrid MS spectrometer combining an iontrap with time-of-flight. This instrument enablesthe acquisition of MS and MSn spectral datafeaturing high resolution, high mass accuracy,and high sensitivity. These valuable attributesare due to the following features of the LCMS-IT-TOF: compressed ion introduction methods,improvements to Dual Stage Reflection, ioncooling using argon gas, and a temperature-controlled time of flight mass analyser.
Phenomenome Profiler™’s new profile-matchingtool uses the same concepts as other clusteranalysis tools used in multivariate statisticalanalyses. By simply selecting the metabolite ofinterest from the array, this tool will extract allother metabolites with the same expressionprofile. As pictured in Figure 3a, by selecting theindomethacin-high dose (indo-HD) effect, theprogram indicates any indo-HD-related down-regulated endogenous metabolites.Phenomenome Profiler™ will also display theexpression pattern of those selectedmetabolites, as shown in Figure 3b.
Real-time interaction exists between the arraytables and the underlying raw chromatogramand MS spectrum data. Figure 4 shows theextracted accurate MS ion chromatogram (EIC)of the indicated row from Figure 3a. In thisfigure, the assigned variables are groupedtogether and displayed as an EIC overlay.
Some of the metabolites of interest were relatedto indomethacin metabolism in vitro; these wereextracted from the array (Figure 2), and aredisplayed in Figure 5a as a variable subtractionof the extracted MS spectrum. According to theaccurate mass information, we can easily assignthe putative molecular formula—one of theremarkable features of Profiler™ software—asshown in Figure 5b. In this example, thedetected metabolite was indomethacin itself. TheMolecular Formula Finder also identifies carbon-13 metabolites in the same array.
Human cancer cell lines are invaluable tools for many aspects of basic cancer research, ranging from purely investigationalstudies to drug efficacy and toxicity studies. The ability to measure endogenous and excreted metabolites over the course ofsuch studies creates an opportunity to quantify the resulting phenotypes. Metabolites found to correlate with specificbiological events are highly informative, and can be utilized as biomarkers for numerous applications, including diseasediagnosis, drug efficacy and toxicity, as well as basic investigational research. Traditionally, the most common platforms forstudying metabolites have included LC-MS, GC-MS and NMR. Recent technological advancements in MS instrumentation,such as the Shimadzu LCMS-IT-TOF system, enable the acquisition of high resolution and high mass accuracy MS datasuitable for novel metabolite discovery. Although these instruments have been developed, no complementary software hasbeen designed specifically to interpret resulting metabolomics data. To address these issues, we have developedPhenomenome Profiler™ software to handle MS spectrometry-based analysis of biological samples. PhenomenomeProfiler™ also easily performs a number of multivariate statistical functions on the raw data.
HT29 human colon cancer cell lines were grown to 80% confluency, and were treated with four drugs using high and lowdoses (listed below). After 24-hour treatment, media from each triplicate treatment was analyzed randomly. A total of 27samples were processed via a proprietary extraction method, optimized to separate the metabolites into multiple extractsbased on polarity and acid/base chemistry. HPLC was carried out on an LC-10ADVP pump and SIL-10ADVP auto-injector. MSanalysis was performed on the LCMS-IT-TOF using an ESI source. All instruments and columns described above wereobtained from Shimadzu Corporation (Kyoto, Japan).
Indomethacin-related down-regulated endogenous metabolites;Figure 3a. Metabolitecoordinate plot.
Figure 3b.
Yasuyo Yamazaki1, Yusuke Inohana2, Shinichi Yamaguchi2.1Phenomenome Discoveries Inc., Saskatoon, SK, Canada, 2Shimadzu Corporation, Kyoto, Japan
C146-E095
Metabolite Profiling of NSAID Effects In Vitro Using Shimadzu LCMS-IT-TOF System With Phenomenome Profiler™ Software
3295-10602-10A-IK
OverviewGlobal metabolite profiling software was used to measure and compare the metabolic changes induced by several NSAIDs in HT29 cells and media. This approach can be used as a model system in monitoring drug metabolism in vitro.
To help find components of biological significance the Shimadzu LCMS-IT-TOF was used to provide high mass accuracy MSn data integrated with Phenomenome Profiler™ software to integrate chromatography and mass spectrometry data sets together with statistical methods.
Phenomenome Profiler™ software is the world’s first universal metabolomics software solution developed specifically for metabolomics research projects.
It is an integrated suite of algorithms, statistical methods, and computer applications to support global profiling of complex mixtures using MS.
Shimadzu Corporation are a key partner withPhenomenome Informatics, a division ofPhenomenome Discoveries
