infinity 2d-lc solution solution - agilent · the 1290 infinity 2d-lc solution • based on the...

The Agilent 1290

Infinity 2D-LC Solution

Achieving highest separation power

with the Agilent 1290 Infinity 2D-LC

Solution

2D-LC - What is it?

Peak capacities multiply for orthogonal separation mechanisms!

Two different modes:

Comprehensive 2D-LC (“LCxLC”)

Heart-cutting 2D-LC (“LC-LC”)

2DLC: Injecting the effluent or a part of the effluent of one column to a second

column, ideally with orthogonal separation behavior.

Purpose: increase total separation power.

Complex/unknown samples:

bio-pharma, food, polymers....

Known samples/improving

confidence: pharma, methdev...

2D-LC - What is it?

Pump Autosampler Column Detector 1D-Chrom.

Standard 1-dimensional LC:

2D-LC - What is it?

Pump Autosampler Column 1

Pump 2

Column 2

Injector

Detector

2-dimensional LC:

2D-LC - comprehensive vs. heart-cutting 2D-LC

Comprehensive 2D-LC (LCxLC):

LC1

LC2

1st peak from

1st dimension

2nd peak from

1st dimension

3rd peak from

1st dimension

LC1

LC2

min

sec

Only parts of the effluent of the first column will be

injected to the second column.

Heart-cutting 2D-LC (LC-LC):

2D-LC - comprehensive vs. heart-cutting 2D-LC

LC1

LC2

The gradients in the 2nd dimension can be much

longer as in comprehensive 2D-LC.

Loss of information.

But better quality data for peak of interest

The 1290 Infinity 2D-LC Solution

• Based on the Agilent 1290 Infinity LC, thus highest performance for 2D-LC

– Excellent retention time precision

– High power range (up to 1200 bar, up to 5 ml/min)

– Highest sensitivity

• Highest flexibility on hardware set-up

– Different pumps, autosamplers and detectors supported

– Different detectors at different positions

– Innovative new 2D-LC valve head , different valve set-up possibilities supported

• Most easy-to-use 2D-LC acquisition SW

– Unique features like automatically shifted gradients or peak-triggered operation

– For comprehensive 2D-LC and heart-cutting 2D-LC

• High performance data analysis by partner-solution

For heart-cutting 2D-LC by Agilent‘s OpenLAB CDS ChemStation ed.

For comprehensive 2D-LC Agilent recommends:

GC Image LCxLC Edition Software

Key features offered:

• Direct Agilent datafile import

• Peak identification, integration, annotation

• Comparative Analysis and Visualization

• Compound-libraries

• MS-data handling

Data-Analysis

Hardware – Module-flexibility

1. Dimension

2. Dimension

1290 Infinity

Binary Pump

1290 Infinity

Binary Pump

1290 Infinity

Autosampler or 1260

HiP Autosampler

Optional

1260/1290

Infinity

Detector

One or two

1290 Infinity

TCC

Optional

1260/1290

Infinity

Detector

1260/1290

Infinity

detector

1260 Infinity Binary

or Quaternary Pump

1260 Infinity

Capillary Pump 1260 Infinity

Autosampler

For 1st

dimension

chromatogram

and peak-

triggering

To monitor

waste-line

Almost any Agilent pump or autosampler in the 1st dimension!

Almost any detectors are supported!

A 1290 Infinity Binary Pump for the 2nd dimension is required.

Hardware – Valves, uniqueness and flexibility

1. Dimension

2. Dimension

waste

Loop1

Loop2

2pos/4port-duo

New Agilent-only special 2D-LC-QucikChange valve.

Single valve with fully symmetric flow-paths and symmetric fill/flush-out

behavior. Only valve that allows countercurrent flush-out of both loops.

Advantages of the new Agilent 2D-LC QuickChange valve head

All flow paths are equal!

Symmetric contercurrent or co-current fill/analyze direction of loops possible

All in one valve

Loop1

Loop2

waste

2D-pump 2D-pump

1D-column

2D-column 2D-column

Fill direction Analyze direction

Valve

switching

1. 2.

Hardware – Valve-flexibility

1. Dimension

2. Dimension

waste

Loop1

Loop2

2pos/

10port

valve

Most other valve configurations for comprehensive and heart-cutting

2D-LC are supported as well. Easy transfer of existing 2D-LC methods!

Hardware – Valve-flexibility

1. Dimension

2. Dimension

waste

Loop1 Loop2

2x

2pos/6port

valves

Also dual valve-head configurations supported with automatic

synchronisation of valve-drives!

Dashboard: All modules in one dashboard, all system

parameters immediately visible

2D-LC Acquisition Software

2D-LC Acquisition Software - supported 2D-LC modes

comprehensive LCxLC

Heart-cutting LC-LC

Standard-repeating

Time or peak-triggered

Time-triggered

Peak-triggered

Most easiest 2D-LC System Configuration - “One screen for the entire system”

Most easiest set-up of complex 2D-LC methods - 2D-LC specific parameters of the 2D-pump

Most easiest set-up of complex 2D-LC methods - Time-segmenting for the 2nd dimension

Time-segmenting in comprehensive 2D-LC - Reducing cost!

1D Gradient/

2D Gradients

Idle flow rate

2D Pump flow

rate

2D Pump flow rate

Solvent saving!!!

2D Time-segments

set in software idle

idle

idle

Time-triggered

Peak-triggered

Valve toggling

Increase life time!

%B (2D)

%B (1D)

F (2D)

1D Chromatogram

Example: graphical editing of a gradient shift - replace editing of large timetables by a few mouse operations -

1 Use context menu to enter the editing mode

3 Draw a straight line by dragging the mouse to a new %B value at a

specified runtime of the 1st dimension

2 Timetable entries are marked with circles

4 When releasing the mouse, a new TT entry is made and the gradient

rollout is automatically updated

6 Insert / Delete shift points (mouse cursor and context menu changes

near to a shift line)

5 Repeat step 3 + 4 with other TT entries

2D-LC Acquisition Sofware - supported 2D-gradients modes

Isocratic Advancing Isocratic

Std. Gradient Shifted Gradient

…and most combinations!

2D-LC Acquisition Sofware - supported 2D-gradients modes

Isocratic Advancing Isocratic

Std. Gradient Shifted Gradient

• Start and end time

• Peak-triggered


• Peak-triggered

• Stepwise or gradual

change of isocratic cond.


• Peak-triggered


• Peak-triggered

• constantly shifted %B2D

• constantly shifted %B2D and

shifted Δ%B2D

Agilent 1290 Infinity 2D-LC Solution

Performance and Applications

Performance

Optimization of a 2D RP-RP LC separation

red line: 1st dimension gradient

blue line: repeating 2nd dimension gradient

Current state-of-the-art 2D-LC – narrow spread of peaks

2nd dimension gradient repeats between 5% and 95% organic solvent

Performance


First adjustment of the second dimension gradient to improve

separation by lower organic in the second dimension for the

compounds of higher polarity.

Performance


Second adjustment of the second dimension to the same maximum

organic content as given from the first dimension.

Increase in organic composition during the runtime to improve separation

and focus the compounds by better usage of separation time in the 2nd

dimension

Performance


Performance


1st Dimension (red line): Gradient: 0 min 5% B – 30 min

95% B, 40min stop-time.

Flow rate: 0.1 mL/min.

2nd Dimension (blue line): Initial Gradient: 0 min - 5% B, 0.5

min - 15% B, 0.51 min - 5% B,

0.65 min - 5% B.

Modulation-time: 0.65 min

Gradient development:

5% B at 0 min to 50% B at 30 min

15% B at 0.5 min to 95% B at 30 min



Flow rate: 3 mL/min.

Performance

Test mix of 20 compounds – 2D-Precision

0.00

0.50

1.00

1.50

2.00 Retention Time Precision RSD (%)

0.00

1.00

2.00

3.00

Peak Volume Precision RSD (%)

15 compounds <1% RSD

all compounds <2% RSD

8 compounds <1% RSD

16 compounds <2% RSD

Applications

Separation of polyphenoles in juice and wine

by 2D RP-RP LC Compound Compound Name Peak I (min) Peak II (sec)

1 Gallic acid 7.15 7.56

2 Esculin 9.75 18.63

3 3,4 HO benzoic acid 9.75 9.74

4 HO Phenacetic acid 11.70 13.55

5 6,7 HO coumarin 12.35 19.66

6 HO Benzoic acid 12.35 16.51

7 Syringic acid 13.00 25.78

8 Rutin 13.65 33.63

9 Naringin 14.95 32.43

10 Coumaric acid 14.95 25.44

11 Hesperidin 15.60 34.89

12 Ferulic acid 15.60 27.63

13 Myricetin 17.55 30.20

14 Morin 18.85 30.20

15 Resveratrol 18.85 26.65

16 Salicylic acid 19.50 18.55

17 Luteolin 19.50 32.79

18 Quercetin 20.15 30.20

19 Kaempferol 21.45 30.96

20 Apigenin 22.10 25.84

21 Naringenin 22.10 27.65

22 Hesperetin 22.75 28.74

23 7 HO Flavone 22.75 34.29

24 Pinosylvin 24.70 18.81

25 Chrysin 27.30 27.49

26 Flavone 28.60 26.33

•3-Dimensional display of the separation

of the 26 compound standard mixture.

•40 minutes 1st dimension separation

•39 seconds for each 2nd dimension

separation

1

2

3

4

5

6

7

8 9

10

11

12

13 14

15

16

17

18 19

20

21 22

23

24

25 26

2D-LC plot of the optimized separation of

26 polyphenolic compounds standard

mixture

Applications

Separation of polyphenoles in juice and wine

by 2D RP-RP LC

2D-LC plot with software detected peak

annotation

Applications

Performance data of selected compounds of

the used standard mixture.

Retention time RSD [%]

typically better than 0.6

Peak volume RSD [%]

typically better than 3%.

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

RS

D [

%]

Retention time precision

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0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

RS

D [

%]

Peak volume precision

Gallic acid

Coumaric

acid

Syringic acid

Gallic acid

O

OH

OH

OH

OH

O

OH

OH

O

O

CH3

CH3

O O

OH

The main components are typically hydroxyllic benzoic

acid compounds like Gallic acid

(insert: UV spectrum of gallic acid).

Kivilompolo M., Oburka V.,

Hyötyläninen T., Comprehensive

two-dimensional liquid

chromatography in the analysis of

antioxidant compounds in wines

and juices. Anal. Bioanal. Chem.

2008, 391, 373-380.

Applications

Red Grape juice separated by 2D-LC.

•Besides the simple hydroxy benzoic acid derivatives more

complex glycosidic compounds like Rutin and Esculin were

identified.

•Mixed antioxidant juice containing: Red and green grape,

apple, black current, cherry, cranberry, pomegranate, bilberry

Rutin

O

O

OOH

OHOH

OH

O

OH

OH

OH

OOCH3

OH

OH

OH

Coumaric acid

Ferulic acid

Gallic acid

3,4 HO Benzoic acid

Esculin

Rutin

6,7 HO Coumarin

Syringic acid

Applications

2D-LC separation of a mixed antioxidant juice

•The 2D plot shows a pattern which is typically for the early

eluting polar hydroxy benzoic acid derivatives.

•But there is also one very well known antioxidant compound

typically inherent in red wine: Resveratrol.

OH

OH

OH

Resveratrol

Applications

2D-LC separation of Merlot red wine.

R2=0.9985

Calibration of 2D-LC quantification

for resveratrol , 1 – 50 µg/mL

Applications

Quantification of resveratrol in Merlot red wine

by 2D-LC separation

OH

OH

OH

Found in Merlot red wine:

4.5 µg/mL, 4.5 mg/L

min 19.5 20 20.5 21 21.5 22 22.5 23 23.5

Main Compound – Pure?

Main Compound

1st dimension separation

2nd dimension separation

Additional impurities!

Impurity

Impurity

Impurity

Applications – heart-cutting 2D-LC - impurity profiling of an active pharmaceutical ingredient

Summary

The Agilent 1290 Infinity 2D-LC solution brings the power of two-dimensional LC-

separation to you at a never before experienced ease-of-use!

Highest separation power by 2D-LC combined with outstanding performance of the

1290 Infinity LC – the ideal tool for complex samples form biological origin, polymers,

food-extracs, and many more.

Innovative new hardware and software features for ease-of-use, reduced operation

costs and highest performance.

Upgradability or re-use of existing Agilent LC equipment.

Achieving highest separation power with

the Agilent 1290 Infinity 2D LC Solution and GC Image® LCxLC Informatics

Stephen E. Reichenbach1,2

1GC Image, LLC, USA 2University of Nebraska – Lincoln, USA

LCxLC Informatics

Non-targeted, multi-sample analyses require comparing every

constituent of every sample and so are the most challenging.

• Effective data preprocessing (baseline correction)

• Accurate peak detection

• Correct compound identification

• Robust cross-sample feature matching & analysis

• Automation

Adapt 10+ years of GCxGC informatics R&D.

Same informatics are applicable to targeted & single sample analyses.

Data Preprocessing

Baseline correction is required to accurately detect and quantify peaks.

• Estimate baseline (possibly multichannel)

• Remove baseline from data (by subtraction)

LCxLC data exhibits two-dimensional baseline.

GC Image LCxLC Informatics performs baseline correction by two-

dimensional statistical modeling [1,2].

Baseline Correction

Example of LCxLC baseline correction [3]:

• Before baseline correction: μ=3.55, σ=0.81

• After baseline correction: μ=-0.01, σ=0.04

Before (top) and after (bottom) baseline correction.

Peak Detection

Peaks are two-dimensional, with (hopefully) several D2 chromatograms

across each peak.

GC Image LCxLC Informatics performs true two-dimensional peak

detection by Drain algorithm [4] (based on Watershed [5]).

Coeluting peaks may require unmixing, e.g., GC Image LCxLC

Informatics provides deconvolution by Parallel Factor Analysis

(PARAFAC) [6].

Peak Detection & Identification

x Peaks in standards mix. Identifications based

on retention times/indices and/or UV/MS

spectra.

# Compound # Compound

1 Gallic acid 14 Morin

2 Esculin 15 Resveratrol

3 3,4 HO Benzoic acid 16 Salicylic acid

4 HO Phenacetic acid 17 Luteolin

5 6,7 HO Coumarin 18 Quercetin

6 HO Benzoic acid 19 Kaempferol

7 Syringic acid 20 Apigenin

8 Rutin 21 Naringenin

9 Naringin 22 Hesperetin

10 Coumaric acid 23 7 HO Flavone

11 Hesperidin 24 Pinosylvin

12 Ferulic acid 25 Chrysin

13 Myricetin 26 Flavone

Compound Identification (HR-MS)

―Centroid

―Profile

―Isotopic Ratio

(A) Chromatographic image view; (B) Resveratrol peak apex spectrum; (C)

Formula calculator uses accurate mass. [7]

Template Matching

Template matching is a powerful tool for automated identification [8].

Templates record a priori patterns (including retention times and spectra)

and rules with chemical logic for peak matching (CLIC™ [9]).

Template matching uses advanced pattern recognition to identify the

template pattern in new chromatograms.

Template metadata (including identities) are applied to the new

chromatogram.

Template Matching

Open circles

are template

peaks.

Filled circles

are matched

target peaks.

Most peaks are matched, but some peaks may be undetected (trace or

co-eluted peaks), unmatched (retention-times distance or spectral

mismatch), or mismatched (nearer peak).

Automation

Automated non-targeted multi-sample analysis:

1. Preprocessing & peak detection.

2. Pairwise template matching to find reliable peaks

(consistent across samples).

3. Align chromatograms & create composite

chromatogram (all peaks, all samples).

4. Define peak-region features, one per peak in

composite chromatogram.

Automation

5. Create feature template with reliable peaks and

composite peak-regions.

6. Apply feature template to characterize each

chromatogram.

7. Use features for cross-sample analysis:

– Sample classification

– Chemical fingerprinting

– Monitoring

– Sample clustering

– Chemical marker discovery

Example Data

LCxLC chromatograms for samples of three drinks.

Objective: Compare chemical compositions of three drinks:

red grape, antioxidant, merlot

– Four concentrations: 1, 2, 5, 10 μL

– Two replicate injections, 24 chromatograms

Red grape Antioxidant Merlot

Example Results

Blue circles indicate drink-specific average is greater than overall average;

White circles indicate drink-specific average is less than overall average;

Areas indicate magnitudes.

• Differences for peak-region features between drink-specific

averages & overall averages.

• Analysis reveals differing compositions.

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Red grape

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Merlot

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35.00

40.00

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Antioxidant

Example Results

Blue circles indicate first average is greater than second average; White

circles indicate second average is greater than first average; Areas indicate

differences.

• Pairwise differences for peak-region features between

drink-specific averages.

• Analysis reveals compositional differences.

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5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

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Merlot – Antioxidant

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5.00

10.00

15.00

20.00

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30.00

35.00

40.00

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Antioxidant – Red grape

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40.00

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Merlot – Red grape

Example Results

Blue circles indicate first average is greater than second average; White

circles indicate second average is greater than first average; Areas relative

to sqrt of summed variances.

• Pairwise relative differences for peak-region features between drink-

specific averages.

• Analysis reveals varying relative compositions.

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5.00

10.00

15.00

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35.00

40.00

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Antioxidant – Red grape

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5.00

10.00

15.00

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25.00

30.00

35.00

40.00

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Merlot – Red grape

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10.00

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20.00

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30.00

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0.00 5.00 10.00 15.00 20.00

Merlot – Antioxidant

Conclusions

• Automated workflow for LCxLC requires many operations.

• GC Image LCxLC informatics adapted from 10+ years of GCxGC

informatics R&D.

• Automated data processing allows fast, robust non-targeted, multi-

sample analyses.

• Example analysis shows capabilities for classification, fingerprinting,

etc.

www.gcimage.com

http://www.gcimage.com/

References 1. S. Reichenbach, M. Ni, D. Zhang, E. Ledford. "Image Background Removal in Comprehensive Two-Dimensional Gas

Chromatography." Journal of Chromatography A, 985(1-2):47–56, 2003.

2. S. Reichenbach, P. Carr, D. Stoll, Q. Tao. "Smart Templates for Peak Pattern Matching with Comprehensive Two-Dimensional Liquid

Chromatography." Journal of Chromatography A, 1216(16):3458–3466, 2009.

3. Data courtesy of P. Carr et al., University of Minnesota, 2011.

4. S. Reichenbach, M. Ni, V. Kottapalli, A. Visvanathan. "Information Technologies for Comprehensive Two-Dimensional Gas

Chromatography." Chemometrics and Intelligent Laboratory Systems, 71(2):107–120, 2004.

5. S. Beucher, C. Lantuejoul. "Use of watersheds in contour detection.", Int’l Workshop on Image Processing, Real-Time Edge and

Motion Detection/Estimation, pp. 17–21, 1979.

6. V. van Mispelaar, A. Tas, A. Smilde, P. Schoenmakers, A. van Asten. "Quantitative analysis of target components by comprehensive

two-dimensional gas chromatography." Journal of Chromatography A, 1019:15–29, 2003.

7. Data courtesy of E. Naegele et al., Agilent Technologies, 2012.

8. S. Reichenbach, P. Carr, D. Stoll, Q. Tao. "Smart Templates for Peak Pattern Matching with Comprehensive Two-Dimensional Liquid

Chromatography."Journal of Chromatography A, 1216(16):3458-–3466, 2009.

9. S. Reichenbach, V. Kottapalli, M. Ni, A. Visvanathan. "Computer Language for Identifying Chemicals with Comprehensive Two-

Dimensional Gas Chromatography and Mass Spectrometry (GCxGC-MS)." Journal of Chromatography A, 1071(1-2):263–269, 2005.

10. S. Reichenbach, X. Tian, Q. Tao, E. Ledford, Z. Wu, O. Fiehn. "Informatics for Cross-Sample Analysis with Comprehensive Two-

Dimensional Gas Chromatography and High-Resolution Mass Spectrometry (GCxGC-HRMS)." Talanta, 83(4):1279-1288, 2011.

11. S. Reichenbach, X. Tian, C. Cordero, Q. Tao. "Features for non-targeted cross-sample analysis with comprehensive two-dimensional

chromatography."Journal of Chromatography A, 1226:140-148, 2012.

Learn more

For more information about the Agilent 1290 Infinity 2D-LC

Solution, visit www.agilent.com/chem/infinity-2D-LC to watch

video and get Technical Overviews.

60

http://www.chem.agilent.com/en-US/promotions/Pages/infinity-2dlc.aspx





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