MS MS/MS - Agilent Technologies

Últimos Desarrollos en
Tecnología de Alta Resolución:
GCQTOF – IMS QTOF.
Trabajo con Muestras
Complejas
Jaume C. Morales
MS Product Specialist
February 12, 2014
1
GC/Q-TOF para Target, No-target y Desconocidos :
Las ventajas de la Alta Resolución, Masa Exacta y la alta
Velocidad de adquisición en MS y MS/MS
7200 GC-QTOF
Una nueva herramienta para
solucionar complejos problemas
analíticos
Febrero 2014
Portfolio de Agilent en GC/MS
RENDIMIENTO
GC Q-TOF
7000C TQ
5975T SQ
240 IT
5977A SQ
7890BGC
5977E SQ
Full Scan/SIM
MS/MS
MS/MS masa exacta
7820 GC
PRECIO
Febrero 2014
El reto en GCMS : problemas analíticos complejos
La identificación de compuestos en muestras complejas a nivel de trazas
(ng/mL o menor) es difícil y generalmente requieres estrategias analíticas
no-rutinarias o sistemas de configuración atípica y poco robustas como :
1- Potentes métodos de extracción/enriquecimiento
2- Sistemas GC de alto poder de separación (e.g.GCxGC)
3- Detectores selectivos y/o MS.
Sin embargo, para análisis a nivel rutinario de éste tipo de compuestos se
requieren enfoques con técnicas más simples, rápidas y robustas para
incrementar la productividad.
Desafortunadamente los sistemas GC/MS (SIM) o 1D GC en combinación
con detectores específicos como el PFPD o ECD no son a menudo
suficientes para conseguir la selectividad requerida.
Page 4
El reto en GCMS : problemas analíticos complejos
1a Estrategia :
La tecnología MS-TOF recoge y analiza simultáneamente todos los iones a
lo largo del rango de masas en contraposición a los instrumentos de barrido
convencional donde los iones son filtrados y detectados secuencialmente.
Consecuentemente, el GC-QTOF-MS en modo TOF no tiene parangón en
sensibilidad trabajando en “Full Scan”, comparable a la técnica GC-MS en
modo SIM, pero con el espectro completo y
Además ,el GC-QTOF-MS genera datos en masa exacta lo cual permite
obtener una alta selectividad y sensibilidad utilizando ventanas de
extracción del orden de 0.02-0.05Da.
PERO, ¿Qué pasa cuando la Resolución y la Δ Masa no son suficientes?
2a Estrategia: GC-QTOF-MS/MS
Page 5
¿Que es el 7200?
7200 GC/Q-TOF = 7890 + 7000 + 6500
MS Triple Cuadrupolo
+
=
MS Cuadrupolo /Tiempo de vuelo
MS Tiempo de Vuelo
Page 6
La fusión de dos plataformas
Ion
Mirror
7000 GC/MS 6500 LC/MS
QQQ based Q-TOF based
Quad Mass Filter (Q1)
Ion Source
Transfer
optics
Ion
Pulser
Collision Cell
Turbo 1b
Page 7
Turbo 1a
Ion
Detector
Turbo 2
Turbo 3
Nuevo . . . Pero totalmente probado
Dual-stage ion mirror improves
second-order time focusing for
high mass resolution.
4GHz ADC electronics enable a high
sampling rate (32 Gbit/s) which improves
the resolution, mass accuracy, and
sensitivity for low-abundance samples.
Dual gain amplifiers simultaneously
process detector signals through both lowgain and high gain channels, extending the
dynamic range to 105.
Hot, quartz monolithic quadrupole
analyzer and collision cell identical
to the 7000 Quadrupole MS/MS
Proprietary INVAR flight tube
sealed in a vacuum-insulated
shell eliminates thermal mass
drift due to temperature changes
to maintain excellent mass
accuracy, 24/7. Added length
improves mass resolution.
Analog-to-digital (ADC) Detector:
Unlike time-to-digital (TDC) detectors
which record single ion events, ADC
detection records multiple ion events,
allowing very accurate mass
assignments over a wide mass range
and dynamic range of concentrations.
New Internal Reference Mass
can be delivered to the source at
a low and high concentration
New Removable Ion Source
includes repeller, ion volume,
extraction lens and dual filaments
Two 300L/s t urbos pump the
focusing optics and flight tube
Split-flow turbo differentially
pumps the ion source and
quadrupole analyzer compartments
Page 8
Hexapole collision cell accelerates
ion through the cell to enable faster
generation of high-quality MS/MS
spectra without cross-talk
Removable Ion Source (RIS)
Automated
Gate Valve
RIS
Automated
Retractable
Transfer Line
Page 9
¿Que puede hacer el GC-QTOF por nosotros?
• En modo TOF
• Espectros “full scan” de alta resolución
• Medida de masa exacta
• Adquisición a alta velocidad de espectros “full scan”
• En modo MS/MS
• Espectros “full scan product ion” con alta resolución y
masa exacta
• La herramienta ideal para abordar complejos
problemas analíticos.
Page 10
Aportación de los sistemas de Tiempo de Vuelo
El TOF es un cronómetro que mide el
tiempo que tardan los diferentes iones
en llegar al detector desde que se
disparan en el PULSER.
Los iones más ligeros llegan antes y
los más pesados, más tarde.
Ese tiempo se contrasta con una
calibración del equipo t <-> m/z y
sabemos con exactitud la m/z del ión.
Genéricamente se entiende por masa exacta cuando el error en la medida es menor de 5 ppm.
Los sistemas basados en SQ/QQQ suelen mostrar un error de masa > 150ppm.
Error en la medida = (Masa Medida - Masa Calculada)
Masa Calculada
X 1.000.000 = ppm
11
Resolución y exactitud de masa
Resolución :
R=mz/FWHM
Mz=614
SQ
TQ
IT
R = 614/0.68 = 903
Δmz = 0.1/614
= 160 ppm
Exactitud de masa:
Δmz=dm/mz*106, partes por millon
(ppm)
PFTBA mass 614
C12F24N=613.964203
TOF
Q-TOF
Pw=0.68
R = 614/0.0423 = 14522
Δmz = 0.0004/613.96
= 0.7 ppm
1 Da.
1 Da.
Page 12
Características Clave en el 7200
1. Bloqueo del eje de masas por Referencia Interna o
Calibración simultanea para exactitud sub 5ppm incluso
en muestras con alta carga de matriz
2. Fuente extraíble RIS para una limpieza, cambio de
filamentos o intercambio de fuentes EI/CI rápida y sin
romper vacío.
3. Q-TOF MS/MS:
•
•
•
•
Reducción del ruido químico
Selectividad
Information estructural
Desarrollo de métodos
4. Herramientas de software – Formula calculator / MSC
(MS/MS Structural Correlation Tool)
Page 13
El reto en GCMS : problemas analíticos complejos
1a Estrategia :
La tecnología MS-TOF recoge y analiza simultáneamente todos los iones a
lo largo del rango de masas en contraposición a los instrumentos de barrido
convencional donde los iones son filtrados y detectados secuencialmente.
Consecuentemente, el GC-QTOF-MS en modo TOF no tiene parangón en
sensibilidad trabajando en “Full Scan”, comparable a la técnica GC-MS en
modo SIM, pero con el espectro completo y
Además ,el GC-QTOF-MS genera datos en masa exacta lo cual permite
obtener una alta selectividad y sensibilidad utilizando ventanas de
extracción del orden de 0.02-0.05Da.
PERO, ¿Qué pasa cuando la Resolución y la Δ Masa no son suficientes?
2a Estrategia: GC-QTOF-MS/MS
Page 14
El reto en GCMS : problemas analíticos complejos
2a Estrategia :
El modo QTOF-MS puede :
- Reducir el ruido al seleccionar y filtrar un Precursor, suministrando así
mayor selectividad.
- Confirmar la identidad de un compuesto a través de su espectro MS/MS
de Alta Resolución.
- Elucidación Estructural.
Page 15
Elucidación estructural por MS/MS.
C16H14O4 (Anillos + Enlaces Dobles = 10)
(M – H)+
269.0802
Estructuras
candidatas
m/z
(experimental)
Fórmula
Error
(ppm)
Score
–H
269.0802
C16H13O4
2.2
80.7
– C6H5
193.0494
C10H9O4
0.6
96.7
– CH=CH–C6H5
167.0334
C8H7O4
3.0
N/A
– CH2=CH–C6H5
166.0259
C8H6O4
0.6
N/A
138.0310
C7H6O3
1.1
98.1
– CO
110.0359
C6H6O2
3.0
N/A
– CH3
95.0127
C5H3O2
0.9
99.5
– CO
Page 16
Formula Calculator: fórmulas consistentes con
la masa exacta y fórmula del Ión padre
C5H12O2PS3
Page 17
m/z = 230.9732
Aplicaciones
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Page 18
Metabolic profiling of yeast sterols using the Agilent 7200 Series
GC/Q-TOF system
Metabolomics of Carbon Fixing Mutants of Cyanobacteria by GC/QTOF
Metabolomics of Opiate-Induced Changes in Murine Brain by GC/QTOF
Untargeted Metabolomic Analysis of UV Stress Response in C.
reinhardtii by GC-QTOF
Simultaneous analysis of tryptophan, kynurenines and amino acids
using the GC/QTOF in Negative CI mode
Accurate mass retention time locked flavor database by GC/Q-TOF
Analysis of trace levels of sulfur compounds in coffee by the Agilent
7200 GC/Q-TOF system
Olive oil characterization using Agilent GC/Q-TOF MS and Mass
Profiler Professional software
Rapid simultaneous screening of multiple pesticide residues in Food
matrices
Simultaneous targeted and non-targeted screening for pesticides in
vegetables by GC/Q-TOF MS
Analysis of biomarkers in crude oil using the Agilent 7200 GC/Q-TOF
Characterization and classification of heroin from illicit heroin seizures
by GC/Q-TOF
Unknowns analysis of natural products using GC/Q-TOF and
GC/IonTrap in EI and PCI modes with MS/MS
Determination of odor compounds in surface water by solid phase
micro-extraction and GC/Q-TOF
The role of GC/QTOF in exposomics
Food Testing and Flavors:
Olive Oil Characterization
UC Davis Olive Center
&
Stephan Baumann, Agilent Technologies
• MPP for statistical processing of GC/Q-TOF data
• MS library searching using GC/Q-TOF spectra
• CI data provide accurate mass information for molecular ions
Page 19
Olive Oil Characterization: Workflow
Goals:
- to create a model that could predict whether olive oil sample would pass or
fail sensory test
- to recognize statistically significant olive oil components that are present at
distinct levels depending on whether they passed or failed sensory test
1. Olive oil samples had been subjected to sensory test and classified as passed or failed
2. GC/Q-TOF data then were acquired in both EI and PCI modes
3. Chromatographic deconvolution was performed with MassHunter Qual, and the data
were exported as CEF files to perform statistical analysis using Mass Profiler
Professional (MPP).
4. MPP was used for statistical evaluation of the data including construction of class
prediction model
5. The model was able to correctly predict whether the sample would pass or fail the
sensory test
Page 20
Olive Oil Characterization: Data Filtering
442 unique compounds were
distinguished by
chromatographic
deconvolution, most of which
occur only once or twice and
are filtered out by MPP.
The table shows how many of these 442
compounds were actually found in each sample.
Page 21
Olive Oil Characterization: Visualization of Data Clustering
failed
passed
Principal Component Analysis (PCA) of MPP helps to visualize
clustering of the data
Page 22
Olive Oil Characterization: Fold Change Analysis
Compounds accumulated
in the samples that failed
the sensory test.
The Volcano Plot (on the right) shows fold-change for each entity on the x-axis and
significance on the y-axis.
Page 23
Olive Oil Characterization: Compound Identification
1. EI spectra were used to search NIST library to obtain tentative identification of
the compounds
2. PCI data were used to obtain molecular formula for the compounds
3. Further MS/MS experiments allowed to generate ‘clean’ spectra in the
presence of matrix interference and could possibly be used for structure
elucidation
Page 24
Olive Oil Characterization: Library Search
Compound spectrum
(accurate mass)
Compound spectrum
NIST library spectrum
EI
Commercial unit mass EI spectral libraries can be searched using accurate mass
EI GC/Q-TOF data to identify compounds
Page 25
Olive Oil Characterization: MS/MS Example
105
100
161
119
α-Cubebene, full scan
C15H24
50
41
81
91
55
204
69 77
0
40 50 60
(replib) α-Cubebene
α-Cubebene: MS/MS
Precursor: 204
CE: 10 eV
70
80
133
147
175
189
90 100 110 120 130 140 150 160 170 180 190 200 210 220 230
C9H11
-3.58 ppm
C12H17
5.11 ppm
C8H9
-2.63 ppm
C10H13
0.93 ppm
Accurate masses of ion fragments are consistent with molecular formula
Page 26
Olive Oil Characterization: Combining EI and PCI Data
Tentative NIST ID
Hexadecanoic acid
Ethyl-octadecanoate
Squalene
α-Cubebene
Unknown
EI , M*+
Calculated Measured Mass error, ppm
C16H32O2 256.2397 256.2385
4.68
C20H40O2 312.3023 312.3008
4.80
C30H50
410.3907 410.3904
0.73
C15H24
204.1873 204.1883
4.90
C14H26O2 226.1927
N/A
N/A
Formula
Calculated
257.2475
313.3101
411.3985
205.1951
227.2006
PCI, (M+H)+
Measured Mass error, ppm
257.247
1.94
313.3091
3.19
411.3987
0.49
205.1945
2.92
227.1987
8.36
PCI spectral data provided accurate mass information for molecular ions of the
accumulated compounds in olive oils that fail the sensory test, including the
case where the EI spectrum showed no prominent molecular ion
Page 27
Olive Oil Characterization: MPP Results
• The model correctly predicted the pass or fail status of all samples, including
those not used to construct the model.
• The samples that were not used for building the prediction model are listed
with the Training parameter set as ‘None’
Page 28
Photodegradation Products of Beer
Page 29
Problem – identify degradation Products of beer
• Completely untargeted (initially) study of beer
photodegradation
• Method highlights
• 30 min extraction at 30 ˚C using manual
SPME holder and conditioned 50/30 µm
DVB/Carboxen/PDMS StableFlex SPME
fiber (Supelco), no agitation
• Desorption at 300 ˚C for 2 min in the SSL
injector; 1:10 split
• Agilent J&W column DB-5MS 30 m x 0.25
mm x 0.25 µm
Page 30
Changes in the Chromatogram
Appears following the exposure of the sample
to direct sunlight. Peak height is dependent on
the duration of exposure to the sun
Molecular ion
m/z=165.1120
C10H15NO
Page 31
No exposure to direct sunlight
3 hours
6 hours
Summary of MS/MS Experiments
Accurate mass measurement of molecular ion and fragments
109
C6H7NO
81
7
O
C10H14N
N
95
122
C5H7N
136
C4H6N
C6H8N
C5H6N
C6H6NO
C4164
H5
100
150
200
250
300
mine, N-(2-furanylmethylene)-3-methyl-
350
C7H8N
C9H14N
C10H15NO
C9H11N
400
109
C6H7NO
122
C7H8NO
136
C9H14N
148
C10H14N
MS
81
C5 H 7 N
108
C6H6NO
78
C5 H 4 N
Page 32
80
C5 H 6 N
55
C3 H 5 N
94
C6 H 8 N
MS/MS
66
C4 H 4 N
53
C4 H 5
41
C3 H 5
133
C9H11N
Summary of MS/MS Experiments
Calculate possible empirical formulas
109
C6H7NO
81
7
O
C10H14N
N
95
122
C5H7N
136
C4H6N
C6H8N
C5H6N
C6H6NO
C4164
H5
100
150
200
250
300
mine, N-(2-furanylmethylene)-3-methyl-
350
C7H8N
C9H14N
C10H15NO
C9H11N
400
109
C6H7NO
122
C7H8NO
136
C9H14N
148
C10H14N
MS
81
C5 H 7 N
108
C6H6NO
78
C5 H 4 N
Page 33
80
C5 H 6 N
55
C3 H 5 N
94
C6 H 8 N
MS/MS
66
C4 H 4 N
53
C4 H 5
41
C3 H 5
133
C9H11N
Summary of MS/MS Experiments
MS/MS on fragments + accurate mass to find empirical formulas
109
C6H7NO
81
7
O
C10H14N
N
95
-OH
122
C5H7N
136
C4H6N
C6H8N
C5H6N
C6H6NO
C4164
H5
100
150
200
250
300
mine, N-(2-furanylmethylene)-3-methyl-
350
C7H8N
C9H14N
C9H11N
C10H15NO
400
109
C6H7NO
122
C7H8NO
-C5H8
136
C9H14N
148
C10H14N
MS
-CH3
80
C5 H 6 N
-H2
78
C5 H 4 N
Page 34
-CHN
53
C4 H 5
133
C9H11N
MS/MS
Summary of MS/MS Experiments
MS/MS on other fragments
109
C6H7NO
81
7
O
C10H14N
N
95
122
C5H7N
136
C4H6N
C6H8N
C5H6N
C6H6NO
C4164
H5
100
150
200
250
300
mine, N-(2-furanylmethylene)-3-methyl-
350
C7H8N
C9H14N
C10H15NO
C9H11N
400
109
C6H7NO
122
C7H8NO
136
C9H14N
148
C10H14N
MS
81
C5 H 7 N
108
C6H6NO
78
C5 H 4 N
Page 35
80
C5 H 6 N
55
C3 H 5 N
94
C6 H 8 N
MS/MS
66
C4 H 4 N
53
C4 H 5
41
C3 H 5
133
C9H11N
Resumen – Qué recordar
• Los nuevos retos requieren en ocasiones nuevas
herramientas/soluciones.
• El GC Q-TOF ofrece la capacidad de solucionar problemas con
nuevas estrategias.
• La Alta Resolución (HR), Mejor Exactitud de
masa (MA) y Alta Velocidad de barrido mejora
los resultados analíticos.
• Los espectros MS/MS con HR y MA hacen
posible la Elucidación Estructural
• Agilent ofrece el portfolio más amplio en
herramientas GC/MS :
SQ, IT, TQ, & Q-TOF
Page 36
Novel Ion Mobility
Technology for
QTOF LC/MS
April 23, 2014
37
IMS QTOF - Overview
HD QTOF
IMS Background
Ion Mobility Basics
Instrument & Software Overview
Applications
-
Software tools
Ω
Lipids
Carbohydrates
ASMS 2013 Ion Mobility
Abstracts
Summary
April 23, 2014
38
Aportación de los sistemas de Tiempo de Vuelo
El TOF es un cronómetro que mide el
tiempo que tardan los diferentes iones
en llegar al detector desde que se
disparan en el PULSER.
Los iones más ligeros llegan antes y
los más pesados, más tarde.
Ese tiempo se contrasta con una
calibración del equipo t <-> m/z y
sabemos con exactitud la m/z del ión.
Genéricamente se entiende por masa exacta cuando el error en la medida es menor de 5 ppm.
Los sistemas basados en SQ/QQQ suelen mostrar un error de masa > 150ppm.
Error en la medida = (Masa Medida - Masa Calculada)
Masa Calculada
43
X 1.000.000 = ppm
Aportación de los sistemas de Tiempo de Vuelo
TOF
TOF
Adquisición de todo el espectro (Full Scan)
Tiapride 0.8 ppm
QTOF
QTOF
Adquisición de todo el espectro (Full Scan)
Adquisición del espectro MS/MS:
Tiapride 0.8 ppm
New 6550 iFunnel QTOF
10X Sensitivity Gain Enables Applications
Sensitivity
• Dramatically improved quantitative capabilities
• New Qual/Quan Workflows
• Superior metabolite and protein detection
• Non-targeted compound screening
Comprehensive Performance Enhancements
• Mass Resolution >40,000
• 50 spectra /sec MS and 33 spectra/sec MS/MS
• 5 orders of linear dynamic range
• <1 ppm MS mass accuracy; <2 ppm MS/MS
• Unrivalled sensitivity
6550 iFunnel Q-TOF
LC/MS System
2. Instrument and Software Overview
QTOF Acquisition – MS and MS/MS Modes of Operation
• MS Only – “TOF only” mode
• MS/MS All Ions . MS & MS/MS info at the same time.
• Data Dependent MS/MS Experiments
• Precursor selection based on intensity of n-highest
(with relative and absolute threshold)
• Excluded and Preferred mass lists
• Configurable charge-state selection preference
• Data Directed (Targeted) MS/MS experiments
• Import of target mass lists from Mass Profiler or
Mass Profiler Professional software
• Import of mass lists from other applications
• Automatic dynamic creation of time segments
Screening and identification workflow
Agilent’s approach
• Combination of UHPLC separation and accurate mass TOF technology
• Effective data mining algorithms to FIND compounds in a sample
• Optional software to COMPARE samples or sample sets to identify differences
• AMRT Databases and MS/MS Library Search to easily IDENTIFY targeted compounds
• Several algorithms to help IDENTIFYING unknown compounds (MFG, MSC)
• User Interface to easily NAVIGATE RESULTS
• Custom reporting to comprehensively REPORT results
• Full AUTOMATION of data acquisition, processing and reporting
TOF/
Q-TOF
Analysis
Automation
Find
Compounds
OPTION:
Differential
Analysis
ID via
AMRT
DBs
ID via
MSMS
libraries
MFG of
Compounds
w/ MSMS
MSMS
structural
correlation
Print
custom
report
Screening and identification workflow
MS/MS Structural Correlation (MSC)
• Algorithm to correlate “proposed
structures” with accurate mass
MS/MS fragment ion spectrum.
• Favor systematic bond
dissociation approach over rule
based fragmentation prediction
approach.
• Proposed structures can be
selected directly or searched in a
PCDL or via ChemSpider
TOF/
Q-TOF
Analysis
Automation
Molecular
Feature
Finding
OPTION:
Differential
Analysis
ID via
AMRT
DBs
ID via
MSMS
libraries
MFG of
Compounds
w/ MSMS
MSMS
structural
correlation
Print
custom
report
IMS QTOF - Overview
HD QTOF
IMS Background
Ion Mobility Basics
Instrument & Software Overview
Applications
-
Software tools
Ω
Lipids
Carbohydrates
ASMS 2013 Ion Mobility
Abstracts
Summary
April 23, 2014
50
Ion Mobility – A Brief History…
2013
Agilent IMS
QTOF
Mass Spectrograph
Aston & Thomson
1919
1969
Transport of
Ions in
Gases
1997
Applications to
clusters &
biomolecules
2006
Synapt Triwave
G2 in 2009
G2S in 2011
Clemmer & Jarrold
1905
McDaniel &
Ion mobility Mason
theory
Paul
Langevin
1872 - 1946
April 23, 2014
51
Drift Ion Mobility for LC-MS
Chromatography, Mass Resolution &
now Ion Mobility
Pacific
Northwest
Labs
NIH
Texas A&M
Cross sectional
areas
Complex Samples
Ion
Mobility
MS
Shape and Charge
Boston
University
Vanderbilt
University
Conformers
2013 ASMS Scientific Presentations:
•
Disease research
•
Proteomics, Metabolomics, Lipidomics
•
Natural Products
•
Fundamental studies
Isomers
April 23, 2014
52
Solving Analytical Problems
PNNL
Boston University
Texas A&M
Vanderbilt
University
NIH
Agilent
Better IM
resolution
• Enhance throughput, improve sensitivity and quantitation
• For large scale -omics studies
• Improving glycan analysis
• Disease research - Entamoeba
• Ion mobility fundamentals
• Study of metallo-protein structures
• Collisional cross section data (Ω)
• Mapping specific chemical classes – natural products
• Separation of androgenic steroids not amenable to LC & MS
• Ω used to identify isobaric steroids
• Characterization of trans membrane domains.
• Preservation of fragile protein folding structures
Higher IM
sensitivity
Resolve
complex
samples
Direct
measurement
of Ω
Preserve
molecular
structures
April 23, 2014
53
IMS QTOF - Overview
HD QTOF
IMS Background
Ion Mobility Basics
Instrument & Software Overview
Applications
-
Software tools
Ω
Lipids
Carbohydrates
ASMS 2013 Ion Mobility
Abstracts
Summary
April 23, 2014
54
Mass Accuracy Does Not Equal Compound Identification:
Seven Golden Rules - Oliver Fiehn
Empirical formula is not unique above
mass m/z 100 (searching PubChem)
Number of Database Entries
(Assuming Zero Mass Error)
Number of formula: ChemSpider mass
search at m/z 400.3787
• 1 ppm mass error → 1742 entries
• 0 ppm mass error → 340 entries
Need additional physical information to
identify
• MS/MS spectra
• Physical properties such as:
• Chromatographic retention time
• Ion mobility cross section (size,
charge)
April 23, 2014
55
What Does Ion Mobility Bring to Mass Spectrometry?
Separation
• Ion Mobility resolves of many isomeric analytes otherwise impossible to
determine by mass spectrometry alone.
Improves Detection Limits
• Ion Mobility dramatically reduces interference from other analytes and
background.
Confirmation
• Collision Cross Section data gives additional information supporting
compound characterization and identification.
April 23, 2014
56
Resolving Stereoisomers
α-glucose
β-glucose
Ion mobility enables separation of glucose stereoisomers
Resolving Structural Sugar Isomers C18H32O16
Raffinose
Melezitose
Resolving two isobaric trisaccharides
Resolving Different type of Isomers
Melezitose
α-glucose
Raffinose
b-glucose
Resolution Is Important!
Chromatographic
~seconds
Ion Mobility
~60 milli-seconds
Mass
~ 100 m seconds
April 23, 2014
60
It’s All About Separation
Chromatography
~seconds
Ion Mobility
~60 milli-seconds
Mass
~100 m seconds
April 23, 2014
61
Separation of Isobaric Pesticides
Theoretical Plot
Aldicarb-sulfone (C7H14N2O4S)
[M+Na]+ = 245.056649
Acetamiprid (C10H11ClN4)
[M+Na]+ = 245.056445
D mass is 0.2 mDa requires ~2,000,000 resolution
4
x10
IMS Drift
Separation
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
Acetamiprid
x10 4 +IMS DriftSpec (m/z: 245.013827-245.177238) (rt: 0.026-1.987 min) Aldicarbsulfone_A…
* 18.297
5.5
19.441
5
4.5
4
3.5
* 19.441
3
17
17.5 18
18.5 19
19.5 20
20.5 21
21.5
2.5
2
18.297
6
x10
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
1.5
1
Aldicarb-sulfone
0.5
0
17
17
17.5
19 19 19.5 19.520 2020.5 20.5
21
17.5 1818 18.5
18.5 vs.
Counts
Acquisition Time (min)
21.5
21
21.5
Drift Time (ms)
17
17.5 18
18.5 19
19.5 20
20.5 21
21.5
Drift Time (ms)
April 23, 2014
62
IMS QTOF - Overview
UHPLC
HD QTOF
IMS Background
Ion Mobility Basics
Instrument & Software Overview
Applications
-
ASMS 2013 Ion Mobility
Abstracts
Software tools
Ω
Lipids
Carbohydrates
Summary
April 23, 2014
63
Basic Operational Principle of Ion Mobility
For Conventional DC Uniform Field IMS
Ion Mobility Cell
VH
𝑣=𝐾𝐸 ∝
𝑒𝐸
𝑃 𝑇Ω
VL
Analyte
Ions
Detector
Gating
Optics
Electric Field
Stacked ring ion guide gives linear field
t0
tdrift
April 23, 2014
65
The Agilent Ion Mobility System
•
Nitrogen buffer gas
•
Funnels drive sensitivity
•
Uniform Field Drift Tube allows direct determination of Ω
•
Longer drift tube drives resolution approaching theoretical limit
•
Fragmentation after IMS means parents and fragments have common drift times
enables an all ion experiment (with the precursor ions separated by drift times).
Mobility Resolution
∝
𝐿𝐸𝑍𝑒
April 23, 2014
66
The Agilent Ion Mobility System
•
Nitrogen buffer gas
•
Funnels drive sensitivity
•
Uniform Field Drift Tube allows direct determination of Ω
•
Longer drift tube drives resolution approaching theoretical limit
•
Fragmentation after IMS means parents and fragments have common drift times
enables an all ion experiment (with the precursor ions separated by drift times).
Mobility Resolution
∝
𝐿𝐸𝑍𝑒
April 23, 2014
67
The Agilent Ion Mobility System
𝑣=𝐾𝐸 ∝
𝑒𝐸
𝑃 𝑇Ω
Electric Field
•
Nitrogen buffer gas
•
Funnels drive sensitivity
•
Uniform Field Drift Tube allows direct determination of Ω
•
Longer drift tube drives resolution approaching theoretical limit
•
Fragmentation after IMS means parents and fragments have common drift times
enables an all ion experiment (with the precursor ions separated by drift times).
Mobility Resolution
∝
𝐿𝐸𝑍𝑒
April 23, 2014
68
Front-end Instrumentation
Ion funnel technology drives sensitivity gain
April 23, 2014
69
New Agilent MassHunter IM-MS Browser
Visualizing Ion Mobility LC/MS Data
•
•
•
Frame Navigation tool
Frame viewer
Heat map
IMS/MS Frame
Selection
Software
Solutions for
Improving your
Productivity
Chromatogram View
IM
Drift TIme
MS
1221.9906 1521.9711
922.0098
1821.9521
2121.9332
2421.9138
622.0294
2721.8941
322.0481
April 23, 2014
70
New Agilent MassHunter IM-MS Browser
Visualizing Ion Mobility LC/MS Data
IMS/MS Frame
Selection
Software
Solutions for
Improving your
Productivity
Chromatogram View
IM
Drift TIme
MS
April 23, 2014
71
Ion Mobility Resolution. How much?
Resolution = 84!
536.5960
536.9300
Zipper peptide
537.2644
April 23, 2014
72
IMS QTOF - Overview
HD QTOF
IMS Background
Ion Mobility Basics
Instrument & Software Overview
Applications
-
Software tools
Ω
Lipids
Carbohydrates
ASMS 2013 Ion Mobility
Abstracts
Summary
April 23, 2014
74
Published Collisional Cross Sections
Analyte
Mass
[Da]
CCS
Literature
[Å2]
Colchicine1
399.4
196.2
196.2
± 0.54 Å2
Odansetron2
293.4
172.7
173.8
± 0.36 Å2
Threonine
119.1
130.1
±0.45 Å2
140.9
±0.5
Å2
±0.6
Å2
<2%
±0.6
Å2
<2%
±0.5
Å2
<2%
Phenylalanine
Tyrosine
Fructose
Sorbitol
165.2
181.2
180.2
182.2
CCS
This Work
[Å2]
148.4
143.4
142.7
%
Deviation
from Lit.
New Analyte
Ion
CCS
IMS QTOF
[Å2]
0%
5α-dihydrotestosterone
(M+H)+
181.6 ± 0.
0.6%
5α-dihydrotestosterone
(M+Na)+
201.5±1.0
5β-dihydrotestosterone
(M+H)+
179.8±0.8
5β-dihydrotestosterone
(M+Na)+
199.5±0.8
androsterone
(M+Na)+
200.0±0.7
etiocholanolone
(M+Na)+
196.3±1.1
5-androstenediol
(M+Na)+
174.0±1.5
epiandrosterone
(M+Na)+
197.0±0.8
<2%
<2%
Collaboration with NIH
Excellent agreement between published
and measured cross sections
1. Anal.Chem. 2012;84:1026.
2. Int. J. MS. 2010;298:78
3. JASMS.2007;18:1163
April 23, 2014
75
Reveal Greater Detail All Ions: Ondansetron, Colchicine,
Reserpine
IM
Reserpine
Drift TIme
Colchicine
Ondansetron
MS
400.1749
294.1597
609.2800
40
All Ion MS using 20 Volt Fragmentation Energy
drift time (ms)
Reserpine
Colchicine
12
Ondansetron
100
m/z
600
Collective drift spectrum includes all ions generated from 3 compounds
12
drift time (ms)
40
Drift Time Separated Fragmentation
Ondansetron
[M+H]+
100
m/z
Simultaneous separation and fragmentation for ondansetron
600
12
drift time (ms)
40
Drift Time Separated Fragmentation
Colchicine
[M+H]+
100
m/z
Simultaneous separation and fragmentation for colchicine
600
12
drift time (ms)
40
Drift Time Separated Fragmentation
Reserpine
[M+H]+
100
m/z
Simultaneous separation and fragmentation for reserpine
600
Collision Cross Section Benchmark
Vanderbilt University
TAA-5
N-(CH2CH2CH2CH2CH3)4
• Tetraalkylammonium salts (TAA)
• Proposed as an “ideal” ion mobility standard
• Wide CCS range (TAA-4 to TAA-18; 100 to 400 Å2)
• TAA salts do not form clusters
• Literature CCS values exist N2 drift gas
TAA-16
Mobility Drift Time (ms)
50
TAA-18
+1 ions
TAA-12
TAA-10
40
+2 ions
TAA-8
TAA-7
TAA-6
TAA-5
TAA-4
30
+3 ions
20
10
0
0
200
400
600
800
1000
1200
Mass-to-Charge (m/z)
April 23, 2014
83
Tetraalkylammonium Salts
CCS Values Compared to Literature
Analyte
Measured
Cross-Section
[Å2]
Literature
Cross-Section
[Å2]
TAA-4
TAA-5
TAA-6
TAA-7
TAA-8
TAA-10
TAA-12
TAA-16
TAA-18
166.61
189.21
212.71
236.34
257.19
294.53
323.62
362.03
381.58
166.00
190.10
214.00
236.80
258.30
± 0.5%
± 0.6%
± 0.3%
± 0.2%
± 0.1%
± 0.1%
± 0.2%
± 0.2%
± 0.3%
Relative Standard
Deviation
[%]
± 0.3%
± 0.1%
± 0.3%
± 0.2%
± 0.4%
0.56
0.28
0.41
0.01
0.24
• High experimental precision
(< 0.5% relative deviation)
• Agreement with literature
(most < 0.5% deviation)
April 23, 2014
84
Conformational Space Occupancy of Biomolecules:
Class Association by Trend Curves
Size
Shape
Drift tube IMS allows
Charge
Class association
Using a Synapt does NOT allow compound class association
Conformational Space Occupancy of Biomolecules
Hypothetical Ordering of
Biomolecular Classes
lipids
Collision Cross Section (Å2)
peptides
carbohydrates
oligonucleotides
Mass (Da)
April 23, 2014
86
Lipid nomenclature
Trivial nomenclature Palmitoleic acid
Trivial names (or common names) are non-systematic historical names.
Systematic
nomenclature
(9Z)-octadecenoic
acid
Systematic names (or IUPAC names) derive from the standard IUPAC Rules for
the Nomenclature of Organic Chemistry, published in 1979,[1] along with a
recommendation published specifically for lipids in 1977.[2] Counting begins from
the carboxylic acid end. Double bonds are labelled with cis-trans isomerism/trans- notation or E-/Z- notation, where appropriate.
Δx nomenclature
In Δx (or delta-x) nomenclature, each double bond is indicated by Δx, where the
cis,cis-Δ9,Δ12
double bond is located on the xth carbon–carbon bond, counting from the
octadecadienoic acid carboxylic acid end. Each double bond is preceded by a cis- or trans- prefix,
indicating the conformation of the molecule around the bond.
n−x nomenclature
n−3
n−x (n minus x; also ω−x or omega-x) nomenclature both provides names for
individual compounds and classifies them by their likely biosynthetic properties in
animals. A double bond is located on the xth carbon–carbon bond, counting from
the terminal methyl carbon (designated as n or ω) toward the carbonyl carbon.
Lipid numbers
18:3; or 18:3, n-6; or
18:3, cis,cis,cisΔ9,Δ12,Δ15
Lipid numbers take the form C:D, where C is the number of carbon atoms in the
fatty acid and D is the number of double bonds in the fatty acid. This notation can
be ambiguous, as some different fatty acids can have the same numbers.
Source: Wikipedia
April 23, 2014
87
Lipid classes
Main classes
Examples of Glycerophospholipids
Fatty acids
Glycerolipids
Glycerophospholipids
Sphingolipids
Sterol lipids
Prenol lipids
Saccharolipids
Polyketides
Source: Wikipedia
April 23, 2014
88
Cerebrosides
Cerebrosides are glycosphingolipids called
monoglycosylceramides which are important components in
animal muscle and nerve cell membranes.
April 23, 2014
89
Diseases Based on Sphingolipids
Disease
Deficient enzyme
Accumulated products
Niemann-Pick disease
Sphingomyelinase
Sphingomyelin in brain and RBCs
Fabry disease
α-galactosidase A
Glycolipids in brain, heart, kidney
Krabbe disease
Galactocerebrosidase
Glycolipids in oligodendrocytes
Gaucher disease
Glucocerebrosidase
Glucocerebrosides in RBCs, liver and
spleen
Tay-Sachs disease
Hexosaminidase A
GM2 gangliosides in neurons
Metachromatic
leukodystrophy
Arylsulfatase A or
prosaposin
Sulfatide compounds in neural tissue
Source: Wikipedia
April 23, 2014
90
Lipid Analysis
70
+1 ions
Ion Mobility Drift Time (ms)
60
Tetraalkylammonium Salts
50
TAA-16
+2 ions
TAA-12
+3 ions
TAA-10
40
+4 ions
TAA-8
TAA-7
TAA-6
TAA-5
TAA-4
TAA-3
30
20
10
L-α-phosphotidylethanolamines (PE)
0
0
500
1000
1500
2000
Mass (Da)
April 23, 2014
91
Lipid Analysis
70
PE oligomers (+1)
Ion Mobility Drift Time (ms)
60
50
PE oligomers (+2)
PE 41:N
PE 39:N
PE 37:N
PE 35:N
PE 33:N
40
PE 64:N
PE 62:N
PE 60:N
30
PE 23:N
PE 21:N
PE 19:N
20
10
L-α-phosphotidylethanolamines (PE)
0
0
500
1000
1500
2000
Mass (Da)
April 23, 2014
92
Lipid Analysis
70
PE oligomers (+1)
Ion Mobility Drift Time (ms)
60
50
PE oligomers (+2)
PE 41:N
PE 39:N
PE 37:N
PE 35:N
PE 33:N
40
30
PE 23:N
PE 21:N
PE 19:N
PE 64:N
PE 62:N
PE 60:N
PE 33:(4-2) PE 35:(6-2)
PE 37:(8-4) PE 39:(10-6)
20
+Na
740
10
750
760
+K
770
780
790
800
810
820
Mass (Da)
0
0
500
1000
1500
2000
Mass (Da)
April 23, 2014
93
Carbohydrates; Great complexity by linkage
Source: Blixt et al., PNAS, 2004
Current dominant strategies: MS(n) or Library searches
April 23, 2014
94
Carbohydrates Analysis
60
+1 ions
50
Ion Mobility Drift Time (ms)
Tetraalkylammonium Salts
40
+2 ions
+3 ions
+4 ions
30
20
maltodextrins (1 to 8)
cyclodextrins (α, β, γ)
human milk oligosaccharides (7)
10
0
0
500
1000
1500
2000
Mass (Da)
April 23, 2014
95
Carbohydrates IM-MS
Mixture of Lacto-N-difucohexaose I & II
Lacto-N-difucohexaose I
Ion Mobility Drift Time (ms)
60
Fuc
Fuc
Gal
50
GlcNAc
Gal
Glc
1018
1020
1022
40
Lacto-N-difucohexaose
II
Fuc
1024
1026
1028
Mass (Da)
Fuc
30
Gal
GlcNAc
Gal
Glc
35
36
37
20
38
39
Lacto-N40
41
42
difucohexaose I
Drift Time (ms)
Lacto-Ndifucohexaose II
10
35
36
37
38
39
40
41
42
Drift Time (ms)
0
0
500
1000
1500
2000
Mass (Da)
April 23, 2014
96
Summary
• Next generation of IMS QTOF Technology
• Added dimension of separation based on size, charge and
molecular conformation
• Resolve and characterize the complex samples
- Increased peak capacity
• Direct determination collision cross sections
• Preservation of molecular structures via lower thermal
excitation
April 23, 2014
97
MUCHAS GRACIAS
Jaume C. Morales
Especialista de Producto
[email protected]
AGILENT TECHNOLOGIES
901.11.68.90
LY BBEETTTTEERR MMSS SSOOL LUUTTI OI ONNSS
CCLLEEAARRLY
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