Application of multi-dimensional GC techniques to the analysis of - PowerPoint PPT Presentation

Application of multi-dimensional GC techniques to the analysis of cigarette smoke M. Brokl, J. Foçant, University of Liège, Belgium L. Bishop, J.Ticha, C. Wright , British American Tobacco Group Research & Development, Southampton UK 68th Tobacco Science Research Conference, Charlottesville VA, 28 Sept – 1 Oct 2014

Academic Partners - University of Liège � Professor Jean-François Foçant, associate professor, leading researcher in high resolution MS & multidimensional TOF analysis � Dr Michal Brokl, post doctoral researcher, working on project since 2011 2

Overview � Challenges & current methodology � Multidimensional GC � Sample preparation & processing � Example chromatograms � Data processing � Conclusions � Next steps 3

Challenge � Mass spectrometry scans of cigarette smoke are used to evaluate mechanisms of smoke formation and new materials & technologies - Needed to determine changes in smoke profile including toxicants but also aroma & processing components � Need to use GC/MS for volatile/semi-volatile species & LC/MS for non-volatile species � Require high throughput method to evaluate samples before targeted testing � Require automation of data analysis 4

Traditional Methodology � GC-MS (single quadrupole mass analyser) ─ Lacks sensitivity ─ Gives limited chromatographic resolution ─ Non-volatile species not measured ─ Low throughput ─ Labour intensive data analysis ─ Analyst dependent 5

Traditional Methodology - Example � 3R4F Particulate phase, methanol extraction of CFP A b u n d a n c e T I C : 2 0 1 3 0 6 0 6 _ 0 2 . D \d a t a . m s 3 4 0 0 0 0 0 3 2 0 0 0 0 0 Abundance 3 0 0 0 0 0 0 TIC: 20130606_02.D\data.ms 110000 105000 2 8 0 0 0 0 0 100000 95000 90000 2 6 0 0 0 0 0 85000 80000 75000 2 4 0 0 0 0 0 70000 65000 60000 2 2 0 0 0 0 0 55000 50000 45000 2 0 0 0 0 0 0 40000 35000 1 8 0 0 0 0 0 30000 25000 20000 1 6 0 0 0 0 0 15000 10000 1 4 0 0 0 0 0 11.00 11.20 11.40 11.60 11.80 12.00 12.20 12.40 12.60 12.80 13.00 Time--> 1 2 0 0 0 0 0 1 0 0 0 0 0 0 8 0 0 0 0 0 6 0 0 0 0 0 4 0 0 0 0 0 2 0 0 0 0 0 1 0 . 0 0 1 5 . 0 0 2 0 . 0 0 2 5 . 0 0 3 0 . 0 0 3 5 . 0 0 T im e - - > 6

Traditional Methodology - Example � 3R4F Particulate phase, headspace SPME of CFP Abundance TIC: 2012-04-13-13.D 4e+07 3.5e+07 3e+07 2.5e+07 2e+07 1.5e+07 1e+07 5000000 7 Time--> 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00

Smoke Scan Method Improvement � Improve sensitivity –Time of Flight Mass Spectrometer ─ Quad: detection limit ∼ μg/mL ─ TOF: detection limit ∼ ng/mL � Improve capacity & separation ─ Multidimensional GC allows greater resolution ─ ToF MS, high scan rate also gives improved resolution � Use automated software to identify & compare components in the analyses ─ 1D scan detect ~ 200 components in SPME PPS ─ 2D scan detect >2500 components in SPME PPS � Use more robust statistical analysis ─ Improve reproducibility ─ Evaluate product differences 8

GC × × GC × × Conventional Conventional Conventional Conventional column column column column 9 From: http://www.leco.cz/cz/support_service/separation_science.htm. Accessed on 04/09/2014

GC × × GC × × Fast Fast Fast Fast Conventional Conventional Conventional Conventional GC GC column column GC GC column column column column column column 10 From: http://www.leco.cz/cz/support_service/separation_science.htm. Accessed on 04/09/2014

GC × × GC × × Fast Fast Fast Fast Conventional Conventional Conventional Conventional GC GC column column GC GC column column column column column column 11 From: http://www.leco.cz/cz/support_service/separation_science.htm. Accessed on 04/09/2014

GC × × GC × × Fast Fast Fast Fast Conventional Conventional Conventional Conventional GC GC column column GC GC column column column column column column 12

Instrumentation at Liège  4D GCxGC-TOFMS LECO Pegasus    13

Sample Preparation & Analysis Gas Phase Particulate Phase Whole smoke CFP trapped particulate Solvent extraction SPME GC × × GC-TOFMS 14 × × DHS

Example of 2D chromatogram 3R4F, 2 cigarettes at HCI, Polyacrylate SPME 15

Example of 2D chromatogram 3R4F, 2 cigarettes at HCI, Polyacrylate SPME 16

1D GC-MS(Q) vs. 2D GC-TOF 1D GC-MS PPS scan data 2D GC × × GC-TOFMS × × (single quadrupole) Substances typically identified ∼ 200 > 2000 Detector sensitivity 1ng/mL 1 µ g/mL Time required for manual data processing of one ∼ a day 10 days ∼ chromatogram 17

1D GC-MS(Q) vs. 2D GC-TOF 1D GC-MS PPS scan data 2D GC × × GC-TOFMS × × (single quadrupole) Substances typically identified ∼ 200 > 2000 Detector sensitivity 1ng/mL 1 µ g/mL Time required for manual data processing of one ∼ a day 10 days ∼ chromatogram For example, estimated time required for manual data processing of 10 samples from 2D GC × GC……………. 18

1D GC-MS(Q) vs. 2D GC-TOF 1D GC-MS PPS scan data 2D GC × × GC-TOFMS × × (single quadrupole) Substances typically identified ∼ 200 > 2000 Detector sensitivity 1ng/mL 1 µ g/mL Time required for manual data processing of one ∼ a day 10 days ∼ chromatogram Robust Statistical Analysis needed to process complex data 19

Comparison of samples A B Cumulative template Cumulative template PCA PCA Fisher ratio (F) Fisher ratio (F)

2D GC-TOF analysis of particulate phase smoke from cigarette with: Cellulose acetate filter Carbon filter 21

Calculate Fisher ratios � A Fisher ratio is the class-to-class variation of the detector signal divided by the sum of the within-class variations of the detector signal 1 Second Dimension Retention Time Mean [sec] First Dimension Retention Time Mean [min] 22 1. Fisher, R. A. Statistical Methods for Research Workers , 14 ed.; A. Constable Ltd.: Edinburgh, 1970.

Calculate Fisher ratios � A Fisher ratio is the class-to-class variation of the detector signal divided by the sum of the within-class variations of the detector signal 1 Second Dimension Retention Time Mean [sec] First Dimension Retention Time Mean [min] 23 1. Fisher, R. A. Statistical Methods for Research Workers , 14 ed.; A. Constable Ltd.: Edinburgh, 1970.

Example of component identification 1 t R mean 2 t R mean Peak volume Peak volume Peak volume Blob ID Area Name F mean (A) x10 6 mean (B) x10 6 mean ratio [min] [s] 28 Menthol 21.33 1.25 6648 213.12 17.69 0.08 499 Menthyl acetate 26.28 1.25 3900 15.26 2.15 0.14 847 Unknown 25.53 1.03 2712 4.45 0.62 0.14 811 Unknown 25.71 1.07 2436 3.53 0.56 0.16 92 3,3-Dimethyl-4-phenylbutene 24.00 1.38 2316 54.91 8.02 0.15 461 4-methyl-1-(2-methylbutyl)benzene 24.47 1.28 2160 11.67 1.60 0.14 451 Naphthalene, 2,6-dimethyl- 33.19 2.20 2136 1.94 2.37 1.22 51 Benzene, 1-methyl-4-(1-methylethenyl)- 17.07 1.36 2088 89.72 7.95 0.09 548 Benzene, (1,2,2-trimethyl-3-butenyl)- 26.00 1.38 1992 14.81 2.69 0.18 4 Phenol 12.31 1.52 1668 776.82 627.62 0.81 325 Pyrazine, 2-ethenyl-6-methyl- 13.82 1.70 1608 40.68 5.19 0.13 388 1-Naphthalenol, 3-methyl- 32.33 2.29 1464 6.31 7.24 1.15 783 Naphthalene, 1,4,5-trimethyl- 36.44 2.02 1188 1.83 1.95 1.07 685 1H-Indole, 3-methyl- 31.43 2.61 1140 3.91 5.13 1.31 24

Peak volume differences 25

Peak volume differences 26

Conclusions � The methodology developed at Liège is: - Sensitive - Able to separate complex mixture of components in Particulate phase smoke - Capable of automated de-convolution - Capable of identifying differences between samples through sophisticated statistical analysis techniques - Operator independent 27

Next Steps � Currently investigating other modified filters e.g. , cavity filters filled with CR20 resin vs. empty cavity � Extrapolate method for analysis of e-cigarettes � Use of 2D GC coupled to high resolution-TOF MS � Next phase of study to analyse vapour phase of smoke � Integration of 2D GC data into Cheminformatics programme 28

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