Upload
zander
View
33
Download
0
Tags:
Embed Size (px)
DESCRIPTION
Lipids Analytical T ool ( LipidAT ): automated analysis of l ipidomic mass spectrometry data. Jun Ma Advisor: Dr. Haixu Tang Co-Advisor: Dr. David Wild Co-Advisor : Dr. Predrag Radivoja School of Informatics, Indiana University, Bloomington, Indiana. Outline. - PowerPoint PPT Presentation
Citation preview
Lipids Analytical Tool (LipidAT): automated analysis of lipidomic mass
spectrometry data
Jun Ma
Advisor: Dr. Haixu TangCo-Advisor: Dr. David Wild
Co-Advisor : Dr. Predrag Radivoja
School of Informatics, Indiana University, Bloomington, Indiana
Outline• Introduction to lipidomics and mass spectrometry• Objectives• Data and methods• Results• Future work• Acknowledgements
Lipidomics
• Definition: Large-scale study of pathways and networks ofcellular lipids in biological systems
• Methodology:Identification and quantitation of the thousands ofcellular lipid molecular species and theirinteractions with other lipids, proteins, and othermetabolites
Introduction to Lipidomics
Genome DNA
Transcriptome
Proteome
Metabotome
RNA
Proteins
Sugars NucleotidesAminoacids
Lipids(Lipidome)
Metabolites
Phenotype/FunctionRef: Wikipedia
Phospholipids biological functions
• Key participants in the regulation and control of cellular function
• Bioenergetics, signal transduction• Cell recognition
Structures of phospholipid and membrane bilayer
Phospholipids are amphiphilic with hydrophilic head group and hydrophobic fatty acid chain.Phospholipids are building blocks of cellular membranes.
Ref: Children's Hospital Oakland Research Institute
Alteration of Phospholipids structures
Ref: Phil. Trans. R. Soc. A (2006) 364, 2597-2614
Significance of lipidomics• Change in phospholipid, besides affecting the
absolute amounts of phospholipids per cell, also affect the relative ratios of the various phospholipids species in the membrane, which in turn should lead to changes in the membrane structure and consequently the function.
• Altered phospholipid metabolism has been reported in a variety of diseases, such as anemias, malaria, cancer, nuscular dystrophy, ischemia, diabetes, lung diseases, and liver diseases.
Tandem mass spectrometry approach for phospholipids analysis
• Advantage– Detection, separation and identification of various
phospholipids– Quantization analysis of complex individual
phospholipids in complex mixtures
Phospholipid MS/MS
Objectives of LipidAT
• Identifying and quantifying individual phospholipid species in mixture
• Obtaining a comprehensive picture of the differences in membrane phospholipids between contrasting biological conditions
Workflow of automated processing of MS/MS data by LipidAT
MS2 data
Identification- Generation of peak list- Peak identification by matching m/z of candidate species
Report - Identified lipids species - m/z of precursor ion - m/z and intensity of peak
Quantification -Normalization to define multiple internal standards -Combination of multiple runs
Global Visualization
Heatmap
Species comparison
show
Local Visualization
Customer-Defined
Visualization
Show- std of user-defined peak in multiple- difference in the control and sample
Data Preprocessing
Phospholipids Database -Lipid species library -Fragmentation Information
Loading the raw data• Read raw data (.raw or .mzData file)
– Scan number (integer)– Precursor ion(m/z)– Retention time(min)– Product ions
• m/z (mass-to-charge ratio)• intensity (abundance)
Data preprocessing• Baseline subtraction
– m/z < 100–
• Normalization– Similarity of structures and species– Reference peak picking– Absolute quantification
peak ofintensity :Ipeak of m/z :M 1.0IM
)(
)()(
PXI
XAXI
Ref: Journal of Lipid Research Vol. 42, 2001
A(X): original intensity of peak xI(PX): intensity of reference peak px
Data integration • Reduction the noise and error• MS Data from a series of replicate runs• Weighted moving averaging filter– Reducing random noise at high masses – Retaining a sharp step response– Fitting for time domain encoded signals– Equation:
n
i i
n
i ii
dW
MWA
1
1
Wi: the intensity of peak iMi : the m/z of peak i
Phospholipids Identification • Build-in fragmentation ion database– 9 phospholipids species (GPA,GPCho,GPIns,GPEtn,GPGro,GPSer,Sphingomyelin,Cardiolipin, Lysophospholipids)– 10-30 carbon atoms– 0-6 double bonds– Neutral loss– Allowing negative and positive mode of MS
• Identification standards–Peak must be above threshold–Corresponding peak must have high intensity also in nearby spectra
Visualization
• Heatmap– x-axis: m/z of precursor ion or retention time– y-axis: m/z of fragments– z-axis: color scale coded ratio value of peak
intensity in two contrasting condition • Comprehensive picture
– Difference of components– Difference of absolute quantity of species– Difference of fragments
Heatmap
Heatmap click-on
Fragment ion lookup
Error bar• Visualize the intensity distribution of specific
ion in the sample and control User-defined ions Build-in ions for different PLs species
• Visualize the intensity deviation of the specific ion across several runs – Decide if the combination of multiple runs are
feasible
Maintenance of in–house database
• Database operations– Search data– Insert data– Delete data
• Database integration– Allow biological experts to integrate their prior
data with LipidAT database
Applications & functionalities• Load and view .mzData or .raw data format• Perform batch processing • Display separations, survey scans, and MS/MS data in a
single interface• Access sample reproducibility , evaluate sample quality
and instrument performance• Identify the individual phospholipids in large and complex
datasets • View change of whole phospholipids mixture and
specific peaks in contracting biological conditions• Customize layout to meet the users needs
Future work
• Incorporate other lipids species into database• Identify minor components of lipids mixtures
Acknowledgements• Dr. Haixu Tang• Dr. David Wild• Dr. Predrag Radivojac• Lab mates –
– Quanhu Sheng– Yong Li– Chuanyih Yu
• Linda Hostetter• Cheminformatics and Bioinformatics faculty• School of Informatics• Eli Lilly and Company (funder)