Accurate Mass Technologies for Metabolomic Applications in Trauma and Critical Care Research Dayanjan (Shanaka) Wijesinghe, Ph.D.
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Accurate Mass Technologies for
Metabolomic Applications
in
Trauma and Critical Care Research
Dayanjan (Shanaka) Wijesinghe, Ph.D.
The Boeing 747
First twin-aisle long range jet airliner produced
Partial double deck configuration
1502 produced since 1970
747-8 variant can carry 467 passengers
The original Jumbo Jet
Worried if one of those crashed?
How about if 6 of them crashed killing everyone on board?
How about if it happens everyday?
Cause for concern???
Two of the diseases I am going to be talking about today claims the same
number of lives in the US everyday.
Yet, very little research is done on these diseases. Why?
# Cardiac
Arrests/yr
Survival
rate
Mortality
rate
# deaths/yr
in USA
Out-of-hospital 359,400 9.5% 90.5% 325,257
In-hospital 209,000 24.2% 75.8% 158,422
Total 483,679
Equivalent loss of life
4 Boeing 747 aircraft crashing & killing
everyone on board each day of the
year!
Heart Disease and Stroke Statistics 2012 Update
A Report from the American Heart Association Go et al. Circulation. 2013;127:e6-e245
Public Health Burden of Cardiac Arrest
Slide: Courtesy of Dr. Mary Ann Peberdy
Cardiac Arrest: Description & Statistics
Post Cardiac Arrest Syndrome
Unique pathophysiologic process involving multiple organs
Whole body ischemia (loss of blood flow)
Global tissue and organ injury
Reperfusion injury (return of blood flow)
On-going inflammation and injury
Key components
Post arrest brain injury
Post arrest myocardial dysfunction
Systemic ischemia / reperfusion response
Sepsis: Disease Description & Statistics
Sepsis– The presence only of systemic inflammatory response syndrome (SIRS) defined as:
fever: >38ºC (any route) or hypothermia: <36ºC (core temp only), tachycardia: heart rate >
90 beats/min or receiving medications that slow heart rate or paced rhythm, leukocytosis:
>12,000 WBC/µL or leukopenia: <4,000 WBC/µL plus suspected or proven infection.
The number of deaths from sepsis per
year equates to approximately two
747s crashing everyday in the US.
Public Health Burden of Sepsis
-800
-600
-400
-200
0
200
400
600
800
0 20 40 60 80 100 120 140 160
Arb
itra
ry In
teg
rate
d M
eta
bo
lic In
de
x
Time
What can we do to change this? Onset and Progression of Disease
Lets give a pill that works on most….
Homogeneous
Clinical
Presentation
Heterogeneous
Molecular
Presentation
personalize medicine, the future!
The Right Treatment
For the Right Patient
At the Right Time
Personalized Medicine – The Future
Genome
Transcriptome
Proteome Metabolome
Current routes to companion diagnostics
Lifestyle
Environment
Microbes
a) Dysregulation of biochemical networks leading to disease b) Identification of drug combinations for treatment c) Monitoring affected networks to verify treatment efficacy
SNP/PTM = 10,000 fold change in Metabolome
•Wound Healing
• Cardiac Disease
• Diabetes
• Allergies
• SIRS and Sepsis
• Nephritis
• Arthritis
• Coagulopathies
Phenome
Metabolome
Sugars
Nucleosides
Organic acids
Ketones
Aldehydes
Amines
Amino acids
Small peptides
Lipids
Steroids
Terpenes
Alkaloids
Xenobiotics
(drugs, bacterial
products etc.)
200,000+ possible chemicals within a mass range of 50 – 1500!
The need for analytical specificity
Prostaglandin E2 Prostaglandin D2
Samples for Metabolomic Studies
Samples
Blood
Plasma
Serum
Urine
Saliva
Tissue Biopsy
Exhaled Breath
Condensates
Dressings
Targeted vs. Untargeted
Confirmatory Analytical Workflow*
Investigational Analytical Workflow*
Harvest Material (50 control
vs. 50 Trtmnt)
Hydrophilic fraction
(amines, sugars, organic acids, nucleic acids)
Hydrophobic Fraction
(steroid hormones,
eicosanoids, sphingolipids, phospholipids
etc.)
Comprehensive and untargeted acquisition of molecular
profiles related to disease of interest
Build targeted LC-MS/MS methods for identified
molecules (MRM)
Re-analyze with larger
cohort (300 samples)
Extract
Identify molecules correlating to
wound healing and its pathologies
Confirmed list of molecules correlating to disease of interest and its pathologies
Waters ACQUITY BEH HILIC 1.7 μm, 2.1 X 100 mm
Waters ACQUITY C18- CSH 2.1 x 100 mm, 1.7μm
Waters ACQUITY BEH HILIC 1.7 μm, 2.1 X 100 mm
Waters ACQUITY C18- CSH 2.1 x 100 mm, 1.7μm
LC Free with gas phase differential mobility separation
1D NP Chromatography
1D RP Chromatography
2D NP-RP Chromatography
No Chromatography
For Research Use Only*
LC-MS/MS Metabolomics Data Analysis Generates large data sets
Retention time
m/z of MS and MS/MS
Intensity
UV-Vis (PDA)
3 biological replicates
Pooled sample instrument replicates
Full mass range at high resolution 30 minute LC (Reverse/Normal and Positive/Negative) with data dependent scans
Multiple time points
Several GB and up to 1TB data / sample
Metabolomics Data Analysis
Give up! Resistance is futile!!
Lots of data (Data Cube/s)
Chemometrics – The Saviour!
Some examples of
the methods in
action
Cardiac Arrest Research
Mary Ann Peberdy (MD)
Advanced Resuscitation
Cooling Therapeutics
and Intensive Care post-
cardiac arrest (ARCTIC)
program
4 centers
92 patient
Presented at AHA Scientific sessions 2013
Surviving Cardiac Arrest
4Z,7Z,10Z,13Z,16Z,19Z-
docosahexaenoic acid (DHA)
5S- hydroxy- 6E,8Z,11Z,14Z-
eicosatetraenoic acid (5-HETE)
Surviving Cardiac Arrest
Sepsis Research
WT/WT KO/KO KI/KI
Not Resistant Delayed Death Highly Resistant
Charles Chalfant Ph.D.
between groups
variation
Data Acquisition
within groups
variation
Cancer
Cardiac Disease
Neurodegerative
Arthritis Diabetes Allergy
ARDS
Sepsis
Wound Healing Nephritis
Trauma/Shock
Coagulopathy
Pre-natal Disorders
Target Identification
Mechanistic Relevance
Supervised Multivariate
Statistical Methods (PLS-DA, PLS-LDA)
Un-supervised Multivariate
Statistical Methods (Cluster Analysis)
Hypothesis Validation
Novel Findings/Treatments
Targeted Analysis
Untargeted Analysis
Novel Hypotheses Generation
Genome Transcriptome
Proteome
Metabolome/Lipidome Phenome
Inflammation
Research Workflow
For Research Use Only*
The cPLA2a knockin mouse and
fecal-induced septic shock
IP inject the mice
16 hours
Serum
PC1 vs PC2 PC1 vs PC2
5.266-7.86
1.875
-1.99
-6.61E-02-0.15
0.313
-0.31
PC1 (24.3%)PC1 (24.3%)
PC
2 (
0.9
%)
PC
2 (
0.9
%) Wild Type
Knock-In20-HETE
8,9 EET
RvE1
17:0 LPA
3-HDHA
15-HEPE
Cys LTE4
13-HDHA
5-oxo-ETE
PGE1
The cPLA2a knockin mouse and
fecal-induced septic shock
IP inject the mice
16 hours
Serum
Top lipid networks in relevant to
survival in mouse sepsis
between groups
variation
Data Acquisition
within groups
variation
Cancer
Cardiac Disease
Neurodegerative
Arthritis Diabetes Allergy
ARDS
Sepsis
Wound Healing Nephritis
Trauma/Shock
Coagulopathy
Pre-natal Disorders
Target Identification
Mechanistic Relevance
Supervised Multivariate
Statistical Methods (PLS-DA, PLS-LDA)
Un-supervised Multivariate
Statistical Methods (Cluster Analysis)
Hypothesis Validation
Novel Findings/Treatments
Targeted Analysis
Untargeted Analysis
Novel Hypotheses Generation
Genome Transcriptome
Proteome
Metabolome/Lipidome Phenome
Inflammation
Research Workflow
For Research Use Only*
Hypothesis Validation
6keto-PGF1α PGE3 PGE2 RvD2
WT Cntrol 1.99 0.36 1.61 0.12
WT - Ecoli-2hr 0.15 0.08 4.63 0.09
WT - Ecoli-2hr 0.14 0.09 5.21 0.05
WT - Ecoli-4hr 0.11 0.02 8.93 0.18
WT - Ecoli-4hr 2.45 1.15 8.39 0.05
KI - Ecoli-2hr 36.33 19.31 2.50 3.91
KI - Ecoli-2hr 27.18 19.36 2.16 2.97
KI - Ecoli-4hr 0.12 21.81 2.89 5.42
KI - Ecoli-4hr 0.12 20.59 2.80 6.92
PGE3 PGE2 RVD2 6-keto-PGF1a
Control
WT-FI 8 hr
WT-FI 8 hr
WT-FI 16 hr
WT-FI 16 hr
KI-FI 8 hr
KI-FI 8 hr
KI-FI 16 hr
KI-FI 16 hr
Sepsis Research
Alfa Fowler M.D.
Sepsis Complications in Human Population
Mouse Network Human Network
Top lipid networks in relevant to survival in human and mouse sepsis
Targeted Validation
What is different?
WT/WT KO/KO KI/KI
Not Resistant Delayed Death Highly Resistant
High PGE2
Low EPA lipids
Low DHA lipids
Low PGE2
Low EPA lipids
Low DHA lipids
Low PGE2
High EPA lipids
High DHA lipids
Primary lipid affected network,
PUFA metabolism!
Summary
Encapsulating targeted therapeutic intervention in
nanoliposomes
Delivery of the therapeutic agent/s and monitoring the
biochemical response
Analytical Characterization Chemometrics
(data reduction)
Identifying Chemicals of
Interest
Understanding Biochemical Relevance
Understanding Therapeutic
Requirements
Genome
Transcriptome
Proteome
Metabolome
Acknowledgement
Charles Chalfant Ph.D.
Bruce Spiess M.D.
Robert Diegelmann Ph.D.
Mary Ann Peberdy M.D.
Alfa Fowler M.D.
Vigneshwar Kasirajan M.D.
Rio Beardsley
Lt. Col. Thomas Shaak Ph.D.
Sudha Jayamaraman M.D.
Lt. Joesph Roderique M.D.
Ekta Patel Patrick MacKnight Brian Griffin Quoc Huynh
Christopher Brindle RN
Kimberly Jefferson Ph.D.
Massimo Bertino Ph.D.
Acknowledgement
Funding
2014 SCIEX Young Investigator Award for the “Development of mass spectrometry applications for clinical lipidomic research”
VLMC – Assistant Director
NIH – U54 “Evaluation of Multi-omics data in understanding the Human Microbiomes role in Health and Disease
NIH-Multi-PI R01 “Role of C1P-cPLA2α interaction in sepsis”
DoD – “Pre-hospital use of plasma for the treatment of trauma hemorrhagic shock”
VA CDA1 “Development of Mass Spectrometry Applications for the Investigation of Wound Healing”
NRSA T32 “Signaling in Tissue Injury and Repair” 2009-2010
Thank You!
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