Últimos desarrollos en tecnología de alta resolución ... · las ventajas de la alta resolución,...

Últimos Desarrollos en Tecnología de Alta Resolución: GCQTOF – IMS QTOF. Trabajo con Muestras Complejas

Jaume C. Morales

MS Product Specialist

February 12, 2014

1

Febrero 2014

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

PRECIO

RE

ND

IMIE

NT

O

240 IT

7000C TQ

5977A SQ 7890BGC

5977E SQ 7820 GC

GC Q-TOF

5975T SQ

Full Scan/SIM

MS/MS

MS/MS masa exacta

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.


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

= +

¿Que es el 7200? 7200 GC/Q-TOF = 7890 + 7000 + 6500

MS Cuadrupolo /Tiempo de vuelo

MS Tiempo de Vuelo

MS Triple Cuadrupolo

La fusión de dos plataformas

Turbo 2

Ion Pulser

Turbo 3

Ion Source

Turbo 1b Turbo 1a

Quad Mass Filter (Q1)

Collision Cell

Transfer

optics

6500 LC/MS

Q-TOF based

7000 GC/MS

QQQ based

Ion Mirror

Ion Detector

Nuevo . . . Pero totalmente probado Dual-stage ion mirror improves

second-order time focusing for

high mass resolution.

Hexapole collision cell accelerates

ion through the cell to enable faster

generation of high-quality MS/MS

spectra without cross-talk

Split-flow turbo differentially

pumps the ion source and

quadrupole analyzer compartments

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 low-

gain and high gain channels, extending the

dynamic range to 105.

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 Removable Ion Source

includes repeller, ion volume,

extraction lens and dual filaments

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.

Hot, quartz monolithic quadrupole

analyzer and collision cell identical

to the 7000 Quadrupole MS/MS

New Internal Reference Mass

can be delivered to the source at

a low and high concentration

Two 300L/s t urbos pump the

focusing optics and flight tube

Removable Ion Source (RIS)

Automated

Retractable

Transfer Line

RIS

Automated

Gate Valve

¿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.

Aportación de los sistemas de Tiempo de Vuelo

11

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.

(Masa Medida - Masa Calculada)

Masa Calculada

= ppm Error en la medida = X 1.000.000

Resolución y exactitud de masa

R = 614/0.68 = 903

Δmz = 0.1/614

= 160 ppm

Pw=0.68

Mz=614

SQ

TQ

IT

TOF

Q-TOF

R = 614/0.0423 = 14522

Δmz = 0.0004/613.96

= 0.7 ppm

Resolución :

R=mz/FWHM

Exactitud de masa:

Δmz=dm/mz*106, partes por millon

(ppm)

PFTBA mass 614

C12F24N=613.964203

1 Da.

1 Da.

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)

Características Clave en el 7200


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


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.

Elucidación estructural por MS/MS.

C16H14O4 (Anillos + Enlaces Dobles = 10)

(M – H)+

269.0802

Estructuras

candidatas m/z

(experimental)

Fórmula Error

(ppm)

Score

269.0802 C16H13O4 2.2 80.7

193.0494 C10H9O4 0.6 96.7

167.0334 C8H7O4 3.0 N/A

166.0259 C8H6O4 0.6 N/A

138.0310 C7H6O3 1.1 98.1

110.0359 C6H6O2 3.0 N/A

95.0127 C5H3O2 0.9 99.5

– CH2=CH–C6H5

– CO

– CH3

– CO

– H

– C6H5

– CH=CH–C6H5

Formula Calculator: fórmulas consistentes con

la masa exacta y fórmula del Ión padre

C5H12O2PS3 m/z = 230.9732

Aplicaciones 1. Metabolic profiling of yeast sterols using the Agilent 7200 Series

GC/Q-TOF system

2. Metabolomics of Carbon Fixing Mutants of Cyanobacteria by GC/Q-

TOF

3. Metabolomics of Opiate-Induced Changes in Murine Brain by GC/Q-

TOF

4. Untargeted Metabolomic Analysis of UV Stress Response in C.

reinhardtii by GC-QTOF

5. Simultaneous analysis of tryptophan, kynurenines and amino acids

using the GC/QTOF in Negative CI mode

6. Accurate mass retention time locked flavor database by GC/Q-TOF

7. Analysis of trace levels of sulfur compounds in coffee by the Agilent

7200 GC/Q-TOF system

8. Olive oil characterization using Agilent GC/Q-TOF MS and Mass

Profiler Professional software

9. Rapid simultaneous screening of multiple pesticide residues in Food

matrices

10. Simultaneous targeted and non-targeted screening for pesticides in

vegetables by GC/Q-TOF MS

11. Analysis of biomarkers in crude oil using the Agilent 7200 GC/Q-TOF

12. Characterization and classification of heroin from illicit heroin seizures

by GC/Q-TOF

13. Unknowns analysis of natural products using GC/Q-TOF and

GC/IonTrap in EI and PCI modes with MS/MS

14. Determination of odor compounds in surface water by solid phase

micro-extraction and GC/Q-TOF

15. 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

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

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

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.

Olive Oil Characterization: Visualization of Data Clustering

Principal Component Analysis (PCA) of MPP helps to visualize

clustering of the data

failed

passed

Olive Oil Characterization: Fold Change Analysis

The Volcano Plot (on the right) shows fold-change for each entity on the x-axis and

significance on the y-axis.

Compounds accumulated

in the samples that failed

the sensory test.

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

Olive Oil Characterization: Library Search

Commercial unit mass EI spectral libraries can be searched using accurate mass

EI GC/Q-TOF data to identify compounds

Compound spectrum

NIST library spectrum

Compound spectrum

(accurate mass)

EI

Olive Oil Characterization: MS/MS Example

C12H17

5.11 ppm C9H11

-3.58 ppm

C8H9

-2.63 ppm

C10H13

0.93 ppm

α-Cubebene, full scan

C15H24

α-Cubebene: MS/MS

Precursor: 204

CE: 10 eV

(replib) α-Cubebene

40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 2300

50

100

41

55

69 77

8191

105

119

133147

161

175 189

204

Accurate masses of ion fragments are consistent with molecular formula

Olive Oil Characterization: Combining EI and PCI Data

Tentative NIST ID Formula EI , M*+ PCI, (M+H)+

Calculated Measured Mass error, ppm Calculated Measured Mass error, ppm Hexadecanoic acid C16H32O2 256.2397 256.2385 4.68 257.2475 257.247 1.94

Ethyl-octadecanoate C20H40O2 312.3023 312.3008 4.80 313.3101 313.3091 3.19

Squalene C30H50 410.3907 410.3904 0.73 411.3985 411.3987 0.49

α-Cubebene C15H24 204.1873 204.1883 4.90 205.1951 205.1945 2.92 Unknown C14H26O2 226.1927 N/A N/A 227.2006 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

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’

Photodegradation Products of Beer

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

Changes in the Chromatogram

No exposure to direct sunlight

3 hours

6 hours

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

Summary of MS/MS Experiments Accurate mass measurement of molecular ion and fragments

C4H5

C10H14N

C9H14N C7H8N

C9H11N

C6H7NO

C6H8N C6H6NO

C5H6N

C5H7N

C4H5

C4H6N

(mainlib) 1-Butanamine, N-(2-furanylmethylene)-3-methyl-

50 100 150 200 250 300 350 4000

50

100

39

53

67

81

95

109

122

136

164

O

N

C10H15NO

109 122

C7H8NO 136 C9H14N

148 C10H14N

133 C9H11N

80 C5H6N

94 C6H8N

108 C6H6NO

81 C5H7N

55 C3H5N

53 41 C3H5

66 C4H4N

78 C5H4N

C6H7NO MS

MS/MS

Summary of MS/MS Experiments Calculate possible empirical formulas

C4H5

C10H14N

C9H14N C7H8N

C9H11N

C6H7NO

C6H8N C6H6NO

C5H6N

C5H7N

C4H5

C4H6N


50 100 150 200 250 300 350 4000

50

100

39

53

67

81

95

109

122

136

164

O

N

C10H15NO

109 C6H7NO

122 C7H8NO 136

C9H14N

148 C10H14N

133 C9H11N

80 C5H6N

94 C6H8N

108 C6H6NO

81 C5H7N

55 C3H5N

53 41 C3H5

66 C4H4N

78 C5H4N

MS

MS/MS

Summary of MS/MS Experiments MS/MS on fragments + accurate mass to find empirical formulas

C4H5

C10H14N

C9H14N C7H8N

C9H11N

C6H7NO

C6H8N C6H6NO

C5H6N

C5H7N

C4H5

C4H6N


50 100 150 200 250 300 350 4000

50

100

39

53

67

81

95

109

122

136

164

O

N

C10H15NO

109 C6H7NO

122 C7H8NO 136

C9H14N

148 C10H14N

133 C9H11N

80 C5H6N

53 78

C5H4N

MS

MS/MS

-OH

-CH3 -C5H8

-CHN -H2

Summary of MS/MS Experiments MS/MS on other fragments

C4H5

C10H14N

C9H14N C7H8N

C9H11N

C6H7NO

C6H8N C6H6NO

C5H6N

C5H7N

C4H5

C4H6N


50 100 150 200 250 300 350 4000

50

100

39

53

67

81

95

109

122

136

164

O

N

C10H15NO

109 C6H7NO

122 C7H8NO 136

C9H14N

148 C10H14N

133 C9H11N

80 C5H6N

94 C6H8N

108 C6H6NO

81 C5H7N

55 C3H5N

53 41 C3H5

66 C4H4N

78 C5H4N

MS

MS/MS

• Los nuevos retos requieren en ocasiones nuevas

herramientas/soluciones.

• El GC Q-TOF ofrece la capacidad de solucionar problemas con

nuevas estrategias.

Resumen – Qué recordar

• 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

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

Summary

April 23, 2014

38

ASMS 2013 Ion Mobility

Abstracts


43

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.

(Masa Medida - Masa Calculada)

Masa Calculada

= ppm Error en la medida = X 1.000.000


TOF

QTOF

TOF

Adquisición de todo el espectro (Full Scan)

QTOF

Adquisición de todo el espectro (Full Scan)

Adquisición del espectro MS/MS:

Tiapride 0.8 ppm

Tiapride 0.8 ppm

6550 iFunnel Q-TOF

LC/MS System

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

New 6550 iFunnel QTOF

10X Sensitivity Gain Enables Applications

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

2. Instrument and Software Overview

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

ID via

AMRT

DBs

Find

Compounds

MFG of

Compounds

w/ MSMS

MSMS

structural

correlation

ID via

MSMS

libraries

OPTION:

Differential

Analysis

Print

custom

report

Automation

Screening and identification workflow

TOF/

Q-TOF

Analysis

ID via

AMRT

DBs

Molecular

Feature

Finding

MFG of

Compounds

w/ MSMS

MSMS

structural

correlation

ID via

MSMS

libraries

Automation

OPTION:

Differential

Analysis

MS/MS Structural Correlation (MSC)

Print

custom

report

• 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

IMS QTOF - Overview

HD QTOF

IMS Background

Ion Mobility Basics


Applications

- Software tools

- Ω

- Lipids

- Carbohydrates

Summary

April 23, 2014

50


Abstracts

Ion Mobility – A Brief History…

April 23, 2014

51

1905

Ion mobility theory

Paul

Langevin

1969

Transport of Ions in Gases

McDaniel & Mason

1997

Applications to clusters & biomolecules

Clemmer & Jarrold

2006

Synapt Triwave

G2 in 2009

G2S in 2011

2013

Agilent IMS QTOF

1872 - 1946

Mass Spectrograph

Aston & Thomson

1919

Drift Ion Mobility for LC-MS

Cross sectional areas

Complex Samples

Shape and Charge

Conformers

Isomers

Chromatography, Mass Resolution &

now Ion Mobility

2013 ASMS Scientific Presentations:

• Disease research

• Proteomics, Metabolomics, Lipidomics

• Natural Products

• Fundamental studies

Ion Mobility

MS

Pacific Northwest

Labs

Texas A&M

Vanderbilt University

Boston University

NIH

April 23, 2014

52

Solving Analytical Problems

April 23, 2014

53

Better IM resolution

Higher IM sensitivity

Resolve complex samples

Direct measurement

of Ω

Preserve molecular structures

• Enhance throughput, improve sensitivity and quantitation

• For large scale -omics studies PNNL

• Improving glycan analysis

• Disease research - Entamoeba Boston University

• Ion mobility fundamentals

• Study of metallo-protein structures Texas A&M

• Collisional cross section data (Ω)

• Mapping specific chemical classes – natural products

Vanderbilt University

• Separation of androgenic steroids not amenable to LC & MS

• Ω used to identify isobaric steroids NIH

• Characterization of trans membrane domains.

• Preservation of fragile protein folding structures Agilent

IMS QTOF - Overview

HD QTOF

IMS Background

Ion Mobility Basics


Applications

- Software tools

- Ω

- Lipids

- Carbohydrates

Summary

April 23, 2014

54


Abstracts

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 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)

Number of Database Entries

(Assuming Zero Mass Error)

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

Melezitose

Raffinose

Resolving two isobaric trisaccharides

Melezitose

Raffinose

α-glucose b-glucose

Resolving Different type of Isomers

Resolution Is Important!

Chromatographic Ion Mobility Mass

~seconds ~60 milli-seconds ~ 100 m seconds

April 23, 2014

60

It’s All About Separation

Chromatography Ion Mobility Mass

~seconds ~60 milli-seconds ~100 m seconds

April 23, 2014

61

Aldicarb-sulfone (C7H14N2O4S)

[M+Na]+ = 245.056649

Acetamiprid (C10H11ClN4)

[M+Na]+ = 245.056445

D mass is 0.2 mDa requires ~2,000,000 resolution

Separation of Isobaric Pesticides

4 x10

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

19.441

17 17.5 18 18.5 19 19.5 20 20.5 21 21.5

6 x10

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

18.297

Drift Time (ms) 17 17.5 18 18.5 19 19.5 20 20.5 21 21.5

Aldicarb-sulfone

Acetamiprid

Drift Time (ms)

17 17.5 18 18.5 19 19.5 20 20.5 21 21.5

4x10

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

5.5

+IMS DriftSpec (m/z: 245.013827-245.177238) (rt: 0.026-1.987 min) Aldicarbsulfone_A…

* 18.297

* 19.441

Counts vs. Acquisition Time (min)17 17.5 18 18.5 19 19.5 20 20.5 21 21.5

Theoretical Plot

IMS Drift

Separation

April 23, 2014

62

//upload.wikimedia.org/wikipedia/commons/4/4a/Acetamiprid_Structural_Formulae_V.1.svg

//upload.wikimedia.org/wikipedia/commons/f/f5/Aldicarb-2D-skeletal.png

IMS QTOF - Overview

UHPLC

HD QTOF

IMS Background

Ion Mobility Basics


Applications

- Software tools

- Ω

- Lipids

- Carbohydrates

Summary

April 23, 2014

63


Abstracts

tdrift

Detector

Analyte

Ions

Gating

Optics

Ion Mobility Cell

t0

VH VL

Electric Field

Stacked ring ion guide gives linear field

𝑣 = 𝐾 𝐸 ∝𝑒 𝐸

𝑃 𝑇 Ω

Basic Operational Principle of Ion Mobility For Conventional DC Uniform Field IMS

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


Mobility Resolution


April 23, 2014

67








Electric Field

Mobility Resolution


April 23, 2014

68

𝑣 = 𝐾 𝐸 ∝𝑒 𝐸

𝑃 𝑇 Ω







Front-end Instrumentation

Ion funnel technology drives sensitivity gain

April 23, 2014

69

../../../../../../Videos/Agilent Technology/How it works Agilent 6560 Ion Mobility Q-TOF Agilent.mp4

New Agilent MassHunter IM-MS Browser Visualizing Ion Mobility LC/MS Data

322.0481

622.0294

922.0098 1221.9906 1521.9711

1821.9521 2121.9332

2421.9138

2721.8941

IMS/MS Frame

Selection

Chromatogram View

Software

Solutions for

Improving your

Productivity

April 23, 2014

70

• Frame Navigation tool

• Frame viewer

• Heat map

IM Drift TIme

MS

New Agilent MassHunter IM-MS Browser Visualizing Ion Mobility LC/MS Data

IMS/MS Frame

Selection

Software

Solutions for

Improving your

Productivity

April 23, 2014

71

IM Drift TIme

MS

Chromatogram View

Ion Mobility Resolution. How much?

536.5960 536.9300

537.2644

Resolution = 84!

Zipper peptide

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IMS QTOF - Overview

HD QTOF

IMS Background

Ion Mobility Basics


Applications

- Software tools

- Ω

- Lipids

- Carbohydrates

Summary

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74


Abstracts

Published Collisional Cross Sections

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75

Analyte Mass

[Da]

CCS

Literature

[Å2]

CCS

This Work

[Å2]

%

Deviation

from Lit.

Colchicine1 399.4 196.2 196.2 ± 0.54 Å2 0%

Odansetron2 293.4 172.7 173.8 ± 0.36 Å2 0.6%

Threonine 119.1 130.1 ±0.45 Å2 <2%

Phenylalanine 165.2 140.9 ±0.5 Å2 <2%

Tyrosine 181.2 148.4 ±0.6 Å2 <2%

Fructose 180.2 143.4 ±0.6 Å2 <2%

Sorbitol 182.2 142.7 ±0.5 Å2 <2%

1. Anal.Chem. 2012;84:1026.

2. Int. J. MS. 2010;298:78

3. JASMS.2007;18:1163

New Analyte Ion

CCS

IMS QTOF

[Å2]

5α-dihydrotestosterone (M+H)+ 181.6 ± 0.

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

Excellent agreement between published

and measured cross sections

Collaboration with NIH

Reveal Greater Detail All Ions: Ondansetron, Colchicine, Reserpine

Reserpine

Colchicine

Ondansetron

609.2800

400.1749

294.1597

IM Drift TIme

MS

All Ion MS using 20 Volt Fragmentation Energy

Collective drift spectrum includes all ions generated from 3 compounds

Reserpine

Colchicine Ondansetron

100 m/z 600

12

dri

ft t

ime (

ms)

4

0

Drift Time Separated Fragmentation

Simultaneous separation and fragmentation for ondansetron

Ondansetron

[M+H]+

100 m/z 600

12

dri

ft t

ime (

ms)

4

0

Simultaneous separation and fragmentation for colchicine


Colchicine

[M+H]+

100 m/z 600

12

dri

ft t

ime (

ms)

4

0

Simultaneous separation and fragmentation for reserpine


Reserpine

[M+H]+

100 m/z 600

12

dri

ft t

ime (

ms)

4

0

Collision Cross Section Benchmark Vanderbilt University

• 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

+2 ions

+3 ions

+1 ions TAA-16

TAA-18

TAA-12

TAA-10

TAA-8 TAA-7

TAA-6 TAA-5

TAA-4

0

10

30

40

200 400 600 800

0

20

Mo

bilit

y D

rift

Tim

e (

ms)

Mass-to-Charge (m/z) 1000 1200

50

TAA-5 N-(CH2CH2CH2CH2CH3)4

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Tetraalkylammonium Salts CCS Values Compared to Literature

April 23, 2014

84

Analyte

Measured

Cross-Section

[Å2]

TAA-4 166.61 ± 0.5%

TAA-5 189.21 ± 0.6%

TAA-6 212.71 ± 0.3%

TAA-7 236.34 ± 0.2%

TAA-8 257.19 ± 0.1%

TAA-10 294.53 ± 0.1%

TAA-12 323.62 ± 0.2%

TAA-16 362.03 ± 0.2%

TAA-18 381.58 ± 0.3%

Literature

Cross-Section

[Å2]

166.00 ± 0.3%

190.10 ± 0.1%

214.00 ± 0.3%

236.80 ± 0.2%

258.30 ± 0.4%

Relative Standard

Deviation

[%]

0.56

0.28

0.41

0.01

0.24

• High experimental precision

(< 0.5% relative deviation)

• Agreement with literature

(most < 0.5% deviation)

Conformational Space Occupancy of Biomolecules: Class Association by Trend Curves

Size Shape

Charge

Using a Synapt does NOT allow compound class association

Drift tube IMS allows

Class association

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&docid=7xG7DkWZuB6omM&tbnid=6vqYjCAxSCgbbM:&ved=0CAUQjRw&url=http://www.npr.org/blogs/thesalt/2012/09/26/161770336/how-food-and-clothing-size-labels-affect-what-we-eat-and-what-we-wear&ei=c5K0Uc7yMKOkigKT84FY&bvm=bv.47534661,d.cGE&psig=AFQjCNFqT5diWE50Sy-EKl2vvCrF_M_CiQ&ust=1370874826176948

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&docid=W158WVoYJlBaTM&tbnid=E6XrsqTMmOXFPM:&ved=0CAUQjRw&url=http://www.learningresources.com/product/hands-on+soft--8482-+large+geometric+shapes.do&ei=DJO0UayMMYKQiAKz7oHQAw&bvm=bv.47534661,d.cGE&psig=AFQjCNG1JbIft3YgF4Pwkv-mod_3MBBoaA&ust=1370874964423709

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&docid=op-_rbSUa-nDTM&tbnid=u_UDV9PB2qmwyM:&ved=0CAUQjRw&url=http://cnx.org/content/m42317/latest/?collection=col11406/latest&ei=-5O0Uf7fOLHyigLfkYHACw&bvm=bv.47534661,d.cGE&psig=AFQjCNFBKTjgVA8rad7MgHT82HakebnErg&ust=1370875211767917

Conformational Space Occupancy of Biomolecules

Co

llis

ion

Cro

ss

Se

cti

on

(Å

2)

Mass (Da)

Hypothetical Ordering of

Biomolecular Classes

lipids

carbohydrates

peptides

oligonucleotides

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 cis,cis-Δ9,Δ12

octadecadienoic acid

In Δx (or delta-x) nomenclature, each double bond is indicated by Δx, where the

double bond is located on the xth carbon–carbon bond, counting from the

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,cis-

Δ9,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

//upload.wikimedia.org/wikipedia/commons/e/e4/Fatty_acid_numbering.png

Lipid classes

Source: Wikipedia

Fatty acids

Glycerolipids

Glycerophospholipids

Sphingolipids

Sterol lipids

Prenol lipids

Saccharolipids

Polyketides

Main classes Examples of Glycerophospholipids

April 23, 2014

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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

Tetraalkylammonium Salts

+2 ions

+3 ions

+1 ions

+4 ions

Ion

Mo

bilit

y D

rift

Tim

e (

ms)

Mass (Da)

0

0

20

40

50

500 1000 1500 2000

10

30

60

70

L-α-phosphotidylethanolamines (PE)

TAA-3

TAA-16

TAA-12

TAA-10

TAA-8 TAA-7

TAA-6

TAA-5

TAA-4

April 23, 2014

91

Lipid Analysis Io

n M

ob

ilit

y D

rift

Tim

e (

ms)

Mass (Da)

0

0

20

40

50

500 1000 1500 2000

10

30

60

70

PE 60:N PE 62:N

PE 64:N

PE 33:N PE 35:N

PE 37:N PE 39:N

PE 41:N

PE 23:N PE 21:N

PE 19:N

PE oligomers (+1)

PE oligomers (+2)

L-α-phosphotidylethanolamines (PE)

April 23, 2014

92

Lipid Analysis Io

n M

ob

ilit

y D

rift

Tim

e (

ms)

Mass (Da)

0

0

20

40

50

500 1000 1500 2000

10

30

60

70

PE 35:(6-2) PE 37:(8-4) PE 39:(10-6) PE 33:(4-2)

+Na +K

Mass (Da)

740 760 770 780 790 750 800 810 820

PE 60:N PE 62:N

PE 64:N

PE 33:N PE 35:N

PE 37:N PE 39:N

PE 41:N

PE 23:N PE 21:N

PE 19:N

PE oligomers (+1)

PE oligomers (+2)

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

maltodextrins (1 to 8) cyclodextrins (α, β, γ)

human milk oligosaccharides (7)

Tetraalkylammonium Salts

+2 ions

+3 ions

+1 ions

+4 ions

Ion

Mo

bilit

y D

rift

Tim

e (

ms)

Mass (Da)

0

0

20

40

50

500 1000 1500 2000

10

30

60

April 23, 2014

95

Carbohydrates IM-MS Io

n M

ob

ilit

y D

rift

Tim

e (

ms)

Mass (Da) 0

0

20

40

50

500 1000 1500 2000

10

30

60

Mixture of Lacto-N-difucohexaose I & II

Mass (Da)

1018 1022 1024 1026 1028 1020

Drift Time (ms)

37 39 40 41 42 38 36 35

Lacto-N-

difucohexaose II

Drift Time (ms)

37 39 40 41 42 38 36 35

Lacto-N-

difucohexaose I

Lacto-N-difucohexaose I

Lacto-N-difucohexaose II

Gal Glc Gal GlcNAc

Fuc Fuc

Gal Glc Gal GlcNAc

Fuc Fuc

April 23, 2014

96

• 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

Summary

April 23, 2014

97

MUCHAS GRACIAS

Jaume C. Morales Especialista de Producto

[email protected]

AGILENT TECHNOLOGIES

901.11.68.90

mailto:[email protected]

mailto:[email protected]

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