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Posters

Title & Abstract Author & Venue

Shotgun Lipidomics of Prostate Cancer Cells Using ESI-MS Shimadzu 8050 and Simplified Data Analysis by SimLipid Software

Lipidomics is a relatively recent omics field of research which includes complex lipidome analysis. It is an emerging field in biomedical research as lipids play an important role in cell, tissue and organ physiology and have potential as biomarkers of disease or treatment success. Shotgun lipidomics1 involves identification and quantification of lipids by direct infusion of complex lipid samples into the mass spectrometer without any chromatographic separation. In 2017 prostate cancer is the most commonly diagnosed cancer in Australia among males. It is estimated that the risk of a male being diagnosed with prostate cancer by his 85th birthday will be 1 in 7.

Gupta, R., Sadowski, M., Meitei, N. S., Blanksby, S. J.

13th Annual Conference of the Metabolomic Society (2017), Brisbane, Australia

Utilisation of SimLipid for the Characterisation of Metabolic Syndrome Related Lipids Acquired Using a Novel Scanning Quadrupole DIA Acquisition Method

Lipidomics has become a rapidly increasing area of research over recent years with a focus on its use and application for disease processes including metabolic syndrome disorders, cancer and cardiovascular disease for example. Obesity, a metabolic disorder risk factor, is known to initiate inflammation, which in turn can lead to type 2 diabetes. The exact mechanism as to how this occurs is not understood.

In the method, a low-resolution quadrupole mass filter is scanned repetitively and both precursor and MS/MS data acquired at spectral rates approaching 2000 spectra/s. The method produces a high duty-cycle, highly specific and unbiased two-dimensional data that can be viewed and processed using readily available informatics.

Gethings, L.A., Meitei, N.S., Vissers, J.P.C., Heywood, D., Castro-Perez, J., Langridge, J.I.

13th Annual Conference of the Metabolomic Society (2017), Brisbane, Australia & 65th ASMS Conference on Mass Spectrometry and Allied Topics (2017), Indianapolis, IN

Development of an Integrated Workflow for Profiling and Semi-Quantitative Analysis of Lipids

The lipidome covers a range of lipids from non-polar to polar. Profiling experiments often need two or more chromatography separation schemes to cove the range of polarities: a Normal phase method and a reverse phase method. Quantitation of the annotated lipids requires additional investigation using a more targeted approach.

Mohsin, S.B., Williams, K., Renu, D., Meitei, N.S., Kalakoti, S., Madden, S., Kitagawa, N.

65th ASMS Conference on Mass Spectrometry and Allied Topics (2017), Indianapolis, IN

Automated Lipid Profiling of a Plasma Sample Using Ultra-High Resolution Qq-Time-Of-Flight Impact II™ Mass Spectrometer with SimLipid Software

The field of lipidomics is fueled by analytical technology advances, particularly mass spectrometry and chromatography. The challenges with mass spectrometry based lipidomics lie in the complexity associated with identification of lipids that requires sophisticated software since automated interpretation of lipid MS/MS spectra is more challenging when compared to other biopolymers such as DNA, carbohydrates or peptides, since lipids show much less standardized fragment mass spectra. Each lipid class has its own fragmentation patterns as well as ionization efficiency.

Meitei, N.S., Gupta, H., Apte, A., Barsch, A., Alving, A., Henao, J.J.A., Stark, K.D.

65th ASMS Conference on Mass Spectrometry and Allied Topics (2017), Indianapolis, IN

Automated Lipid Profiling of Malaria Samples Using Orbitrap Velos Pro Mass Spectrometer with LipidSearch and SimLipid Software

Liquid chromatography—Mass spectrometry (LC-MS) provides one of the most popular platforms for lipidomic analysis. Comparative studies of the complex lipid mixtures found in cells and tissues could potentially reveal lipid biomarkers. We have developed a lipidomics analysis method – LC coupled with high resolution Orbitrap Velos Pro MS instrument methods; lipid identification using database search of MS/MS data from both the positive, and negative modes; and multivariate statistical analysis – to identify the significant lipid species that are responsible for classifying multiple biological groups of malaria samples.

Meitei, N.S., Arun Apte, Rahlouni, F., Sullivan, D. J., Shulaev, V.

65th ASMS Conference on Mass Spectrometry and Allied Topics (2017), Indianapolis, IN

SimLipid®: Software platform for automating Shotgun, LC-MS and MALDI-MS based high-throughput lipidomics

A combination of different approaches namely ‘Shotgun lipidomics’, LC-MS, and MALDI-TOF is often necessary to detect the whole lipidome of an organism. Each lipid class has its own fragmentation patterns as well as ionization efficiency [1], thereby making the interpretation of MS/MS lipid spectra a challenging task.

Meitei, N.S., Gupta, H., Apte, A.

64th ASMS Conference on Mass Spectrometry and Allied Topics (2016), San Antonio, Texas

Automatic lipid characterization using SimLipid® from normal phase and reverse phase liquid chromatography -MS, MS/MS data acquired in variable ion modes

LC-MS techniques using electrospray ionization (ESI) and reversed phase chromatography have successfully been used to profile complex lipid samples. Normal phase (NP) LC-MS separates phospholipids into their respective classes based on their respective polar head groups and with little influence from their sn-1 and sn-2 fatty acid substituents.

Meitei, N.S., Biswas, A., Apte, A., Madden, S., Sartain, M.

63rd ASMS Conference on Mass Spectrometry & Allied Topics (2015), St. Louis

Automatic Characterization of Lipids Using Charge Remote Fragmentation Ions and Peaks Characteristic of Fatty Acid Fragmentation From MALDI MS/MS Data

MALDI mass spectrometry has been used for detecting phosphatidylcholines by direct tissue analysis (1-4). Recently, triacylglycerols and phosphatidylcholine in complex mixtures have been identified using MALDI MS/MS (5,6) wherein charge remote fragmentation (CRF) as well as other A-, B-, C-, G and J- ions are the determinants as described recently (7,8,9).

Meitei, N.S., Apte, A., Waidelich, D., Abdi, F., Glueckmann, M.

62nd ASMS Conference on Mass Spectrometry and Allied Topics (2014), Baltimore

Automatic Lipid Characterization Based on Charge Remote and Fatty Acid Fragmentation in MALDI MSMS

MALDI mass spectrometry has been used for detecting phosphatidylcholines by direct tissue analysis (1-4). Recently, triacylglycerols and phosphatidylcholine in complex mixtures have been identified using MALDI MS/MS (5,6) wherein charge remote fragmentation (CRF) as well as other A-, B-, C-, G and J- ions are the determinants as described recently (7,8,9).

Meitei, N.S., Apte, A., Park, J., Waidelich, D., Abdi, F., Glueckmann, M.

Metabolomics 2014, 10th Annual International Conference of the Metabolomics Society (2014), Tsuruoka

Lipid profiling of serum samples from calcific coronary artery disease patients using UPLC/TOF-HDMSE and multivariate data analysis

The separation of glycans by chromatography prior to MS analysis can reduce sample complexity, minimize ion suppression, and increase dynamic range and separation of structural isomers.

Isaac, G., Vorkas, P.A., Want, E.J., McDonald, S., Naslund, U., Holmgren, A., Henein, M.Y., Millar, A., Holmes, E., Shockcor, J.P., Nicholson, J., Langridge, J.

60th ASMS Conference on Mass Spectrometry and Allied Topics (2012), Vancouver

Technical Note

Title & Abstract Author & Publication

Untargeted and Targeted Lipidomics Using Ultra-High Resolution Qq-Time-Of-Flight Impact II™ Mass Spectrometer with SimLipid® Software

Improvements in analytical methods, especially liquid chromatography and mass spectrometry, have driven the recent advances in the development of lipid profiling methods. We have presented a robust workflow for the global lipid profiling of a plasma sample using an LC system coupled to an Impact II™ Ultra-High Resolution Qq-Time-Of-Flight (UHR-QqTOF) mass spectrometer (Bruker Daltonik, Bremen, Germany) with > 50,000 Full-Sensitivity Resolution and SimLipid® informatics software (PREMIER Biosoft, USA).

Meitei N.S., Gupta H., Apte, A., Barsch, A., Alving, A., PREMIER Biosoft & Bruker Daltonik (2016)

PREMIER Biosoft Technical Note No. TSL101

Application Note

Title & Abstract Author & Publication

Phospholipid analysis using SimLipid software

Phospholipids (PLs) have a role of constituting a cellular membrane in a living cell and are also related to produce various fatty acids such as arachidonic acids, EPA and DHA which are precursors of bioactive lipids. Fluctuation of PLs concentration in a blood or a tissue is also known to be correlated with various disease.


T. Nakanishi (2017)

Shimadzu Document No. LAAN-A-LM-E120

Automated Lipid Identification Using UPLC/HDMSE in Combination with SimLipid

Lipids constitute one of the largest classes of macromolecules, together with nucleic acids, proteins, and carbohydrates. Lipids play key biological roles in all organisms and therefore their analysis is of major interest in nutritional, pharmaceutical, and biological research.

Isaac, G., McDonald, S., Astarita, G. (2011)

Waters Application Note No. 720004169EN

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A high throughput informatics tool for identification and relative quantitation of lipids using data from LC-, MALDI-, Shotgun-, Mass Spectrometry Workflows

The main biological functions of lipids include energy storage, acting as structural components of cell membranes, and participating as important signaling molecules.

Comparative studies of complex lipid mixtures found in cells and tissues could potentially reveal lipid biomarkers. The presence of lipids in membranes is reflective of the physiological state of an organism at a given time. Targeted and non-targeted approaches based on chromatography and mass spectrometry are employed for such studies. Both the approaches involve identification and measurement of lipids in the samples.

The challenges with mass spectrometry based lipidomics are the chemical complexity and large range of concentration of thousands of lipid species that are present in biological samples. Moreover, identification of lipids requires sophisticated software since automated interpretation of lipid MS/MS spectra is more challenging as compared to other biopolymers such as DNA, carbohydrates or peptides since lipids show much less standardized fragment mass spectra. Each lipid class has its own fragmentation patterns as well as ionization efficiency.

High Throughput DIA Data Processing with Waters® UPLC® SONAR™ and Waters® UPLC® HDMSE along with Waters® TQ-S and Shimadzu LCMS 8060 are now supported!

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  • Robust Lipid Structure Database
  • Project Management and Data Visualization
  • High Throughput Lipid Structural Elucidation using MS, MS/MS and MSE Data
  • High Throughput DIA Data Processing- Waters® UPLC® SONAR™ and Waters® UPLC® HDMSE
  • LC MS and LC- MS/MS (DDA) High Throughput Data Processing
  • Multiplexed Precursor Ion Scan (PIS) and Neutral Loss Scan (NLS) Triple Quadrupole Mass Spectrometry Methods Based Lipid Profiling and Quantitation - Waters® TQ-S, Shimadzu LCMS 8060
  • Normalize Analyte Peaks Based on Peaks of the Internal Standards; either analytes, and the internal standards belong to same lipid class or an analyte and one of the internal standards have the "closest retention time"
  • MALDI-FT-ICR-MS Lipidomics Analysis
  • Mass Spectra Annotation with Identified Lipids
  • Generate Report

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