Characterizing Edible Oils Using GCxGC–TOF-MS and …images2.advanstar.com/PixelMags/spectroscopy/pdf/2014-03... · 2014. 2. 28. · The compact mass spectrometer delivers full

March 2014

S U P P L E M E N T T O

LCGC North America | LCGC Europe | Spectroscopy

Characterizing Edible Oils Using GCxGC–TOF-MS and

GC–High Resolution TOF-MS

Immunoaffi nity Enrichment for MS-Based Translational Proteomics

Soft Ionization for GC–MS

MS Investigation of Counterfeit Pharmaceuticals

ES395057_SpecCTMS0314_CV1.pgs 02.27.2014 02:22 ADV blackyellowmagentacyan

Research-Grade Technology Meets High Productivity

LC-MS/MSInnovation with Integrity

To meet your throughput goals, you need the fullest possible insight into your sample. With Bruker‘s

"one shot analysis" philosophy and the compact™Oq-TOF mass spectrometer, you can accelerate your

productivity by getting high-quality results...even on the first run.

How? By receiving all specified performance parameters simultaneously.

The compact mass spectrometer delivers full sensitivity resolution so there is no need to choose between

resolution and sensitivity. One shot plug and play acquisition ensures qualitative and quantitative results in

one LC run with the fastest time-to-results. And finally, enhanced dynamic range during real LC time scales

reduces sample preparation, key in high-throughput quantitative applications.

Don‘t accept compromise, choose the compact mass spectrometer. www.bruker.com

ES392620_SPECCTMS0314_CV2_FP.pgs 02.25.2014 20:32 ADV blackyellowmagentacyan

ES392613_SPECCTMS0314_003_FP.pgs 02.25.2014 20:31 ADV blackyellowmagentacyan

www.spec t roscopyonl ine .com4 Current Trends in Mass Spectrometry March 2014

®

PUBLISHING & SALES

485F US Highway One South, Suite 210, Iselin, NJ 08830(732) 596-0276, Fax: (732) 647-1235

Michael J. Tessalone Science Group Publisher, [email protected]

Edward Fantuzzi Publisher, [email protected]

Stephanie Shaffer East Coast Sales Manager, [email protected]

(774) 249-1890

EDITORIAL

Laura Bush Editorial Director, [email protected]

Megan L’HeureuxManaging Editor, [email protected]

Stephen A. Brown Group Technical Editor, [email protected]

Cindy Delonas Associate Editor, [email protected]

Dan WardArt Director, [email protected]

Russell Pratt Vice President Sales, [email protected]

Anne Young Marketing Manager, [email protected]

Tamara Phillips Direct List Rentals, [email protected]

Wright’s MediaReprints, [email protected]

Maureen Cannon Permissions, [email protected]

Jesse Singer Production Manager, [email protected]

Gail Mantay Audience Development Assistant Manager, [email protected]

Joe Loggia Chief Executive Officer

Tom Florio Chief Executive Officer Fashion Group, Executive Vice-President

Tom Ehardt Executive Vice-President, Chief Administrative Officer & Chief Financial Officer

Georgiann DeCenzo Executive Vice-President

Chris DeMoulin Executive Vice-President

Ron Wall Executive Vice-President

Rebecca Evangelou Executive Vice-President, Business Systems

Julie Molleston Executive Vice-President, Human Resources

Tracy Harris Sr Vice-President

Joel Horner Vice-President, Information Technology

Michael Bernstein Vice-President, Legal

Francis Heid Vice-President, Media Operations

Adele Hartwick Vice-President, Treasurer & Controller

MANUSCRIPTS: To discuss possible article topics or obtain manuscript preparation

guidelines, contact the editorial director at: (732) 346-3020, e-mail: [email protected].

Publishers assu me no responsibility for safety of artwork, photographs, or manuscripts.

Every caution is taken to ensure accuracy, but publishers cannot accept responsibility for

the information supplied herein or for any opinion expressed.

SUBSCRIPTIONS: For subscription information: Spectroscopy, P.O. Box 6196, Duluth, MN

55806-6196; (888) 527-7008, 7:00 a.m. to 6:00 p.m. CST. Outside the U.S., +1-218-740-

6477. Delivery of Spectroscopy outside the U.S. is 3–14 days after printing. Single-copy price:

U.S., $10.00 + $7.00 postage and handling ($17.00 total); Canada and Mexico, $12.00 +

$7.00 postage and handling ($19.00 total); Other international, $15.00 + $7.00 postage and

handling ($22.00 total).

CHANGE OF ADDRESS: Send change of address to Spectroscopy, P.O. Box 6196, Duluth,

MN 55806-6196; provide old mailing label as well as new address; include ZIP or postal

code. Allow 4–6 weeks for change. Alternately, go to the following URL for address

changes or subscription renewal: https://advanstar.replycentral.com/?PID=581

RETURN ALL UNDELIVERABLE CANADIAN ADDRESSES TO: IMEX Global Solutions,

P.O. Box 25542, London, ON N6C 6B2, CANADA. PUBLICATIONS MAIL AGREEMENT

No.40612608.

REPRINTS: Reprints of all ar t icles in this issue and past issues are available

(500 minimum). Call 877-652-5295 ext. 121 or e-mail [email protected]. Outside US, UK,

direct dial: 281-419-5725. Ext. 121

DIRECT LIST RENTAL: Contact Tamara Phillips, (440) 891-2773; e-mail: [email protected]

INTERNATIONAL LICENSING: Maureen Cannon, (440) 891-2742,

fax: (440) 891-2650; e-mail: [email protected].

©2014 Advanstar Communications Inc. All rights reserved. No part of this publication

may be reproduced or transmitted in any form or by any means, electronic or mechanical

including by photocopy, recording, or information storage and retrieval without permission

in writing from the publisher. Authorization to photocopy items for internal/educational or

personal use, or the internal/educational or personal use of specific clients is granted by Ad-

vanstar Communications Inc. for libraries and other users registered with the Copyright Clear-

ance Center, 222 Rosewood Dr. Danvers, MA 01923, 978-750-8400 fax 978-646-8700 or

visit http://www.copyright.com online. For uses beyond those listed above, please direct your

written request to Permission Dept. fax 440-756-5255 or email: [email protected].

Advanstar Communications Inc. provides certain customer contact data (such as cus-

tomers’ names, addresses, phone numbers, and e-mail addresses) to third parties who wish

to promote relevant products, services, and other opportunities that may be of interest to

you. If you do not want Advanstar Communications Inc. to make your contact information

available to third parties for marketing purposes, simply call toll-free 866-529-2922 between

the hours of 7:30 a.m. and 5 p.m. CST and a customer service representative will assist you

in removing your name from Advanstar’s lists. Outside the U.S., please phone 218-740-6477.

Spectroscopy/LCGC does not verify any claims or other information appearing in any

of the advertisements contained in the publication, and cannot take responsibility for any

losses or other damages incurred by readers in reliance of such content.

Spectroscopy/LCGC welcomes unsolicited articles, manuscripts, photographs, illustra-

tions and other materials but cannot be held responsible for their safekeeping or return.

To subscribe, call toll-free 888-527-7008. Outside the U.S. call 218-740-6477.

Authorization to photocopy items for internal or personal use or for the internal or

personal use of specific clients is granted by Advanstar Communications for libraries

and other users registered with the Copyright Clearance Center, 222 Rosewood Drive,

Danvers, MA 01923, tel. 978- 750-8400, fax 978-646-8700; call for copying beyond that

permitted by Sections 107 and 108 of the U.S. Copyright law. LCGC/Spectroscopy and

the logos appearing on the cover of this magazine are registered trademarks of Advanstar

Communications, Inc.

Advanstar Communications Inc. (www.advanstar.com) is a leading worldwide media

company providing integrated marketing solutions for the Fashion, Life Sciences and

Powersports industries. Advanstar serves business professionals and consumers in

these industries with its portfolio of 91 events, 67 publications and directories, 150

electronic publications and Web sites, as well as educational and direct marketing

products and services. Market leading brands and a commitment to delivering innovative,

quality products and services enables Advanstar to “Connect Our Customers With

Theirs.” Advanstar has approximately 1000 employees and currently operates from

multiple offices in North America and Europe.

ES392191_SPECCTMS0314_004.pgs 02.25.2014 02:27 ADV blackyellowmagentacyan

[ XEVO TQ-S ]

You’re going to need a bigger graph.[ ]

The Xevo® TQ-S from Waters. Featuring high sensitivity with StepWave,™ our

revolutionary off-axis ion-source technology lets you quantify compounds at

lower levels than you ever thought possible. And its sensitivity, speed

and selectivity will take your results to an entirely new level.

Learn more at waters.com/xevotqs


6 Current Trends in Mass Spectrometry March 2014 www.spec t roscopyonl ine .com

ArticlesApplication of Mass Spectrometry to Support

Verification and Characterization of Counterfeit Pharmaceuticals 8

Michael B. Peddicord, Charles Pathirana, Holly M. Shackman, Mark S. Bolgar, and Scott A. Miller

The steps used to determine if a product is counterfeit are presented and several case studies are examined.

A New Outlook on Soft Ionization for GC–MS 16

Laura McGregor, Nick Bukowski, and David Barden

This article discusses new developments that make lower-energy electron ionization possible without the disadvantages that have historically been associated with it. The specific benefits of this technique are discussed by reference to several examples across the GC–MS field.

An Enhanced Immunoaffinity Enrichment Method

for Mass Spectrometry–Based Translational Proteomics 20

Mary Lopez and Bryan Krastins

A standard high-throughput method for developing targeted biomarker identification of proteins in human plasma and serum for clinical research was developed using an MS immunoassay–selected reaction monitoring workflow.

Comparison of Edible Oils by GC×GC–TOF-MS and GC–High Resolution TOF-MS

for Determination of Food Fraud: A “Foodomics” Approach 26

Elizabeth Humston-Fulmer

A method to characterize edible oils and edible oil mixtures through fingerprinting and the isolation of

individual analyte differences is reported.

Departments

Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

Ad Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Cover image courtesy of Foodcollection RF/Getty Images

March 2014

ES393068_SpecCTMS0314_006.pgs 02.25.2014 23:19 ADV blackyellowmagentacyan

© 2013 Thermo Fisher Scientifi c Inc. All rights reserved. All trademarks

are the property of Thermo Fisher Scientifi c Inc. and its subsidiaries.

Mass spectrometrytransformed.Announcing ground-breaking innovations in mass spectrometry—the Thermo

Scientific™ Orbitrap Fusion™ Tribrid™ MS and the Thermo Scientific™ TSQ

Endura™ and TSQ Quantiva™ triple-stage quadrupole MS—built from the

ground up for uncompromising performance and usability. Together with nano

RSLC; easy online SPLC; or fast, fl exible intelligent multiplexing, these LC-MS

systems deliver unprecedented experimental power and unrivaled sensitivity.

Achieve more results, with more confi dence, more quickly than ever before.

• thermoscientifi c.com/mstransformed

Transform your science.

Innovative Software

Rapid method-building with

drag-and-drop interface

TSQ Endura triple-stage

LC-MS system

Extreme quantitative value

TSQ Quantiva triple-stage

LC-MS system

Extreme quantitative

performance

Orbitrap Fusion

LC-MS system

Unmatched analytical

performance



Michael B. Peddicord, Charles Pathirana, Holly M. Shackman, Mark S. Bolgar, and Scott A. Miller

The production and sale of counterfeit drugs has risen sharply in recent years. The World Health Organization (WHO) estimates that counterfeit medicines account for approximately 1% of sales in developed countries and well over 10% in developing countries. These substandard versions of medications not only represent a significant safety threat to patients, but also challenge the credibility of the pharmaceutical industry and its ability to provide patients with safe and effective products. These counterfeit products may contain either the incorrect dose or none of the intend-ed active compound. In some cases, these counterfeit medicines contain different active drug com-ponents and, in the worst cases, may even contain toxic substances. Because of these concerns, the pharmaceutical industry vigilantly monitors the global market for counterfeit products. When a suspected counterfeit product is detected at Bristol-Myers Squibb, it is fully characterized to assess the potential risks to patient safety. Liquid chromatography coupled to mass spectrometry (LCÐMS), with accurate-mass capability, is a powerful tool for investigating counterfeit pharma-ceuticals because it allows the rapid assignment of the molecular weight and formula of each component, which can then be used to search the literature or internet for a potential match. This approach is frequently successful because counterfeiters often formulate their products from com-monly available, relatively simple materials, rather than novel products.

Application of Mass Spectrometry to Support Verification and Characterization of Counterfeit Pharmaceuticals

The World Health Organization (WHO) defines coun-terfeit drugs as drugs that are ‘‘deliberately mislabeled with respect to identity and/or source. Counterfeiting

can apply to both branded and generic products with coun-terfeit products including drugs with the correct ingredients or with the wrong ingredients; without active ingredients, with insufficient active ingredient or with fake packaging” (1). Counterfeit pharmaceutical products have been detected since approximately 1990 (2). Since then, the number of cases investigated by the US Food and Drug Administration (FDA) quadrupled to an average of about 20 per year in 2001 and 2002 (3). In an effort to ensure patient safety and brand in-tegrity, the pharmaceutical industry vigilantly monitors the global market for counterfeit products. Counterfeit products

at Bristol-Myers Squibb are fully characterized to assess the risks to patient health and safety.

The first step in detecting a counterfeit medicine is to con-duct a visual inspection of its physical characteristics as well as the appearance of the accompanying packaging materials. The effectiveness of a visual inspection may have limited success given the increased sophistication adopted by counterfeiters. An even greater challenge than identifying a pharmaceutical product as a counterfeit is the identification and quantitation of all components present in the material. This process is necessary to make an accurate assessment of toxicology and patient risk. Identification and quantitation of components in a counterfeit product requires chemical analysis. Throughout the industry, various modern analytical techniques have been applied for the

ES392400_SpecCTMS0314_008.pgs 02.25.2014 16:40 ADV blackmagentacyan

www.spec t roscopyonl ine .com March 2014 Current Trends in Mass Spectrometry 9

characterization of counterfeit pharma-ceuticals, including thin-layer chroma-tography (TLC) (4), gas chromatography (GC) (5), high performance liquid chro-matography (HPLC) (6), Raman and near infrared (NIR) spectroscopy (7–11), mass spectrometry (MS) (12,13), and nuclear magnetic resonance (NMR) spectros-copy (14,15). Each of these techniques is capable of providing rich analytical data to assist in the characterization of coun-terfeit medicines. In practice, two or more of these techniques will be used orthogo-nally because the ideal goal of these inves-tigations is to achieve absolute identifica-tion and quantitation of all components that are present (16).

To enable the complete characteriza-tion of detected counterfeit medicines, a general strategy has been developed that uses vibrational spectroscopy (Raman and NIR), liquid chromatography coupled to mass spectrometry (LC–UV-MS), and NMR as an orthogonal structural con-firmational technique. An overview of this strategy is depicted in Figure 1. A vi-sual inspection followed by analysis with Raman or NIR spectroscopy is used as an initial screen to identify product authen-ticity. If the product is deemed authentic based on a comparison of the collected spectra of the possible counterfeit prod-uct to library spectra acquired on the au-thentic product, then the investigation is complete. If the drug product is deemed a counterfeit based on this initial screen, then the material is subjected to low-reso-lution LC–UV-MS to assess the number of components present and assign molecular weights to all components observed in the LC–UV and MS total ion chromatograms (TIC). The initial screen by LC–UV-MS is performed on systems that are equipped and maintained for open-access usage. Use of the open-access systems improves the efficiency of the analysis process since these systems are preconfigured and available to run samples. If low-res-olution MS analysis provides adequate ionization of the counterfeit compo-nents, then the sample is analyzed on a high-resolution instrument for accurate-mass measurement and assignment of molecular formulas. To achieve a narrow list of possible formulas, the elemental composition search is restricted with respect to included elements and the al-

lowed deviation of calculated masses from the measured mass. Initially, the search is restricted to formulas that contain only C, H, N, and O. The allowed deviation from the measured mass is set to a maximum of 1.25 mmu. The isotopic distribution is also evaluated to check for the presence of elements other than C, H, N, and O that should be included in the element set.

As an alternative, the sample can also be analyzed initially on an accurate-mass instrument, thereby bypassing the need for the low-resolution screen. If the low-resolution LC–MS analysis indicates a single component, or if the response in the mass spectrometer is found to be poor

by electrospray ionization (ESI) then the sample is analyzed by NMR next. For samples that fail to ionize by ESI, and were observed to be relatively pure by NMR, desorption chemical ionization (DCI) is attempted to obtain a molecular weight and elemental composition for the un-known component. Quantitation of com-ponents is performed following identifi-cation of the components. For counterfeit products containing a single component, such as aspirin, LC–UV can be utilized to quantify the analyte by comparison with an authentic standard. Quantitative NMR (qNMR) is also used to determine the level of analytes in counterfeit products (17).

Figure 1: Decision-tree diagram of the general strategy for counterfeit product analysis.

Visual inspection and

Raman/NIR spectroscopy of

suspected counterfeit.

Determine elemental

compositions. Conduct

internet search on

resulting formulas.

Collect NMR data for

elucidation/confirmation.

Attempt to elucidate components

in mixture by NMR or preparative

LC isolation of components

followed by NMR.

Perform comprehensive 1D

and 2D NMR analysis for

elucidation of structure and

Desorption Chemical

Ionization (DCI) mass

spectrometry for molecular

weight determination.

Investigation is complete. LC–UV-MS analysis

shows components

in LC–UV trace.

Components ionize

by ESI and allow MW

assignment

1HNMR analysis

indicates a single

component.

Authentic Counterfeit

YesNo

No

NoYesYes

Figure 2: LC–UV chromatogram (210 nm) of product A tablet extract.

Component 1

0

100

0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 2.00

0.57

0.38 1.36

Component 2

Artifact

%

Time (min)



For more-complex mixtures, a combi-nation of techniques may be required to identify and quantify all of the individual components present in the counterfeit medicine. For example, techniques such as LC–UV-MS coupled with NMR spec-

troscopy (qualitative and quantitative), LC–UV-MS coupled with Raman or NIR spectroscopy, or these techniques coupled as needed with preparative LC isolation, X-ray diffractometry, or ICP-MS for met-als analysis (18,19) can be used.

The strategy described above has been used to complete numerous counterfeit investigations at Bristol-Myers Squibb. In general, LC–MS has proven to be a pow-erful tool for the characterization of coun-terfeit products. The ability to rapidly as-sign a molecular weight and often a single formula for each counterfeit component affords the opportunity to expedite the putative identification using literature or internet searching. This process could be likened to electron ionization (EI) library searching in its ability to quickly filter po-tential candidates. Investigations using this approach are generally successful because counterfeiters often produce their products from commonly available, relatively simple materials, not novel products. A series of case studies are presented here that dem-onstrate the general strategy for conducting investigations of counterfeit materials.

ExperimentalInitial LC–MS assessment is conducted using a system comprising a Shimadzu analytical HPLC system equipped with an SPD-10AV UV–vis detector and coupled to a Waters ZQ 2000 mass spectrometer. Chromatographic separation is performed using a 50 mm × 4.6 mm, 2.7-μm dp As-centis Express C18 column. The HPLC system is controlled using Shimadzu’s Class VP software and the mass spectrometer is controlled by MassLynx v 4.0 SP4 software (Waters). These systems are configured for open-access use. The mass spectrometer is operated in both positive- and negative-ion modes (alternating). Data are acquired, in both modes, in the m/z 75–1200 range. Typical flow rates are 1.0–1.5 mL/min. The flow is split to deliver approximately 300 μL/min of eluent to the mass spec-trometer. Mobile-phase A is 95:5 0.01 M ammonium acetate in water–acetonitrile. Mobile-phase B is 5:95 0.01 M ammonium acetate in water–acetonitrile. A rapid gradi-ent from 0% B to 100% B is used.

High-resolution mass spectrometry is conducted using a Waters Q-Tof Premier or a Thermo Fisher Scientific LTQ Orbi-trap Discovery mass spectrometer. Both instruments are equipped with a Waters Acquity pump and photodiode-array de-tector. Chromatographic separations are run on a 100 mm × 2.1 mm, 1.7-μm dpWaters BEH C18 column. The Q-Tof Pre-mier system is controlled by MassLynx

Figure 3: Negative-ion ESI mass spectrum of component 1 observed in product A.

[M-H-C2H4O2]-

[M-H]-

100

100 115.0

175.1

HOHO

OH

OH

O O

0

%

120 140 160 180 200 220 240 280 300 320 340 360 380 400

L-Ascorbic acid

Chemical formula: C6H8O6Exact mass: 176.0321

m/z

Figure 5: Positive- and negative-ion ESI total ion chromatograms of the product B extract.

35

38

2.00 4.00

Positive-ion TIC

Negative-ion TIC

Component of interest

Component of interest

6.00

0.43

0.44

8.00 10.00

2.00 4.00 6.00 8.00 10.00

%%

Figure 4: Accurate mass, positive-ion ESI mass spectrum of component 2 observed in product A.

100 200 300 400 500 600 700

m/z

100

90

80

70

60

50

40

30

20

10

0

123.05507

N O

NH2

Rela

tive a

bu

nd

an

ce

[M+H]+

NicotinamideChemical formula: C6H6N2O

Exact mass: 122.048

m/z Theoretical Mass Delta (ppm) RDB Equiv. Composition

123.0557 123.05529 -1.78 4.5 C6H7N2O



v 4.1 software (Waters) and is operated in V-mode with a resolution of 10,000 (full width at half maximum [FWHM]). The LTQ Orbitrap Discovery system is controlled by Xcalibur v 2.0.7 software (Thermo Fisher Scientific) and data are ac-quired at a resolution of 30,000 (FWHM).

Positive-ion DCI with methane is used for the characterization of components that do not ionize adequately by LC–MS with ESI. The analysis is performed on a Waters GCT Premier system equipped with a DCI probe for sample introduction. The instrument is controlled using Mass-Lynx v 4.1. The instrument is operated at a resolution of 7000 (FWHM) and the data is acquired over a range from m/z 50–700. Heptacosa (perfluorotri-n-butylamine) is introduced as an internal reference for accurate-mass measurement.

Results and Discussion

Case Study 1: Product A

Product A tablet was confirmed as coun-terfeit by Raman spectroscopy and was suspected to contain ascorbic acid based on comparison of the Raman spectrum to spectra in the library. A portion of the counterfeit tablet was extracted with 50:50 acetonitrile–water and sonicated for 20 min. The extracted liquid was filtered and diluted (1:15) for LC–UV-MS analysis. Fig-ure 2 shows the LC–UV chromatogram obtained from the preliminary low-reso-lution LC–MS experiment. Component 1 was ionized using negative-ion ESI and was confirmed to be ascorbic acid based on the determined molecular weight of 176 Da as shown in Figure 3. Detection of ascorbic acid was consistent with the initial Raman analysis. The molecular weight of compo-nent 2 was assigned as 122 Da based on the low-resolution mass spectrum. To obtain the molecular formula of component 2, the sample was analyzed on a high-resolu-tion instrument using positive-ion ESI, as shown in Figure 4. For component 2, eval-uation of possible elemental compositions resulted in a single formula (C6H6N2O). Because only a single formula possibility was obtained, the formula was entered into an internet search engine to obtain a list of matching structures. The internet search on C6H6N2O returned nicotinamide as a possible structure. Next, 1H NMR data of the extract were collected to check for organic compounds that may not have

been visible in the LC–UV-MS analysis and to further confirm the structure pro-posals for component 1 and component 2. Component 1 and component 2 were con-firmed by 1H NMR to be ascorbic acid and nicotinamide. No additional components were detected by NMR. The 1H NMR data were also used to determine the mole ratio of ascorbic acid:nicotinamide as 4:1 (qNMR). An internet search confirmed the availability of commercial vitamin supple-

ments with ascorbic acid and nicotinamide present in the same ratio.

Case Study 2: Product B

A tablet of suspected counterfeit product B was received following initial determi-nation of counterfeit status by Raman spectroscopy. No additional structural in-formation was obtained from the Raman analysis. A portion of the counterfeit tablet was extracted with 50:50 acetoni-

Figure 6: Positive- and negative-ion mass spectra of the component at tR = 0.44 min from the

product B extract.

100 132.0

134.0

267.2135.3

0

%%

100

150 200 250 300 3500

Negative-ion mass spectrum

Positive-ion mass spectrum

[M–H]–

[M+H]+

[2M+H]+

Figure 7: Accurate mass, positive-ion mass spectrum of the component at tR = 0.44 min from the

product B extract.

125 130 135 140 145 150 155 160 165 170 175

m/z

2.2

2.0

1.8

1.6

1.4

1.2

1.0

0.8

0.6

0.4

0.2

0.0

134.04430

O

NH2 O

OHHO

Inte

nsi

ty (

X10

5)

[M+H]+

Aspartic acidChemical formula: C4H7NO4

Exact mass: 133.0375


134.04430 134.04478 -3.61 1.5 C4H8NO4



trile–water and sonicated for 20 min. The extracted liquid was filtered and diluted (1:10) for LC–UV-MS analysis. No sig-nificant components were detected in the LC–UV chromatogram; however, a poorly retained component was detected in both the positive- and negative-ion ESI total ion chromatograms as shown in Figure 5. The molecular weight of this component was determined to be 133 Da based on the positive- and negative-ion mass spectra (Figure 6). An accurate-mass analysis was conducted in positive-ion ESI mode and the data is shown in Figure 7. A single possibility for the molecular formula was obtained from the accurate-mass data (C4H7NO4). An internet search conducted on this molecular formula suggested the identification was aspartic acid, which was confirmed by analyzing the extrac-tion mixture by 1H NMR. The 1H NMR data additionally confirmed the absence of other organic components.

Case Study 3: Product C

Product C was received and tested by LC–UV-MS after preliminary Raman screen-ing confirmed its status as a counterfeit. No additional structural information could be gleaned from the Raman spec-tral analysis because the spectrum failed to yield a high-quality match with any of the compounds in the library. Similar to previous work, a portion of the counter-feit tablet was extracted with 50:50 ace-tonitrile–water and sonicated for 20 min. The extracted liquid was filtered and diluted (1:5) for LC–MS analysis. Figure 8 shows the LC–UV chromatogram at 220 nm that was obtained for the tablet extract, which indicates the presence of only one major component. The mass spectrum obtained for the major compo-nent observed in the HPLC analysis using

Figure 11: Partial structure elucidated by

NMR analysis for the active component in

product D.

OH

O O

OH

OH

HO X

Figure 8: LC–UV chromatogram (220 nm) of product C tablet extract.

3.51

0.50

0 1 2 3 4 5 6 7

0.45

0.40

0.35

0.30

0.25

0.20

0.15

0.10

0.05

0.00

Ab

sorb

an

ce (

µA

U)

Time (min)

Figure 9: Positive-ion ESI mass spectrum of the tR = 3.51 min component in the product C extract.

m/z

278.190838.0

7.0

6.0

5.0

4.0

3.0

2.0

1.0

0.0

N

[M+H]+

Inte

nsi

ty (

X10

8)

Active component in amitriptyline tabletsChemical formula: C20H23N

Exact mass: 277.183


278.19073 278.19033 1.45 9.5 C20H24N

150 200 250 300 350 400 450 500

Figure 10: Positive-ion ESI–MS-MS spectrum of the tR = 3.51 min component in product C (m/z 278.2).

m/z

1.4

1.6

1.8

1.2

1.0

0.8

0.6

0.4

0.2

0.0

80

Inte

nsi

ty (

X10

8)

Assignment of observed product ions

Amitriptyline

100 120 140 160 180 200 220 240 260 280 300

233.13281

C18H17

278.19125

C20H24N

191.08594

C15H11155.08575

C12H11

117.06992

C9H991.05422

C7H7

–2H

–H

N

m/z 155

m/z 91

m/z 191

m/z 233

+H



positive-ion ESI is shown in Figure 9. The molecular weight of the compound was determined to be 277 Da. The elemental composition obtained from the accurate-mass measurement was C20H23N. This was the only possible formula returned by the software within the restricted ac-curacy window of 1.25 mmu. The formula was searched on the internet for possible structure matches and amitriptyline was the result. For additional confirmation of the identity of the counterfeit as amitrip-tyline, an accurate-mass product ion mass spectrum was collected and the product ion assignments are shown in Figure 10. All of the observed product ions are con-sistent with the identification of the active component of amitriptyline. As in the previous case studies, 1H NMR was used to confirm the structure of amitriptyline and ensure the absence of additional or-ganic components. Amitriptyline is a tri-cyclic antidepressant that is used in the

treatment of a variety of medical condi-tions including depressive and anxiety disorders, attention deficit disorder, hy-

peractivity disorder, migraines, eating disorders, insomnia, and bipolar disorder, among others (20). Though this product

Figure 12: Positive-ion DCI mass spectrum and elemental composition data for Product D analysis.

100

85.0250

60 80 100 120 140 160 180 200 220 240 260 280 300 320

110.0298

111.0430

127.0379

145.0461

163.0614

m/z

73.0293272.0886

M.+

0

%

Elemental composition reportTolerance = 2.0 mDa / DBE: min = -1.5, max = 50.032 formulas evaluated with 1 result within limits

Mass Calc. Mass mDa ppm DBE Formula

272.0886 272.0896 -1.0 -3.7 5.0 C12H16O7

Figure 13: Structure of arbutin.

OH

OH

OH OH

O O

HO

Arbutin

Chemical formula: C12H16O7


Figure 14: LC–UV chromatogram of product E (260 nm).

1.06

1.39

Component 1 (217 Da)

Component 2 (311 Da)

0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00

Time (min)

1.0e-1

2.0e-1

3.0e-1

0.0Ab

sorb

an

ce (

AU

)

0.40

Figure 15: Mass spectrum of the 311 Da component identified in product E.

[M+H]+

[M+H–H2SO3]+

0

100

m/z

100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

201.1052

230.1294

231.1330312.1034

%

Mass Calc. Mass ppm DBE Formula

312.1034 312.1018 5.1 6.5 C13H18N3O4S 230.1294 230.1293 0.3 7.5 C13H16N3O



did contain an approved active pharma-ceutical ingredient, amitriptyline, it did pose a significant risk to the patient be-cause this compound is not an approved therapy or active against the target disease indicated for treatment with product C.

Case Study 4: Product D

Product D was initially tested by Raman and NIR spectroscopy, which indicated a counterfeit material composed of a pos-sible mixture of lactose, hydroxypropyl cellulose (HPC), and starch. The com-pound did not ionize upon LC–UV-MS analysis with either positive- or negative-ion ESI. The sample was found to dissolve completely in H2O, so a D2O solution was used to obtain structural information using NMR. The NMR analysis indicated a single, pure component. Comprehensive one-dimensional (1D) and two-dimen-sional (2D) NMR analysis were success-ful in elucidating the majority of the un-known structure as shown in Figure 11.

Mass spectrometry was needed to identify the para substituent labeled as “X” in Fig-ure 11 because it was not represented in the NMR data set. DCI was used to ob-tain a mass spectrum of the compound because ESI had failed in the preliminary LC–UV-MS sample analysis. The mass spectrum obtained from the DCI analy-sis is shown in Figure 12. The molecular formula was elucidated as C12H16O7 based on the DCI accurate-mass analysis. Cou-pled with the structural information ob-tained from the NMR analysis, the para substituent was identified as a hydroxyl (-OH) group. An internet search using the molecular formula resulted in the further identification of this compound as arbutin (Figure 13). Arbutin is used as a skin-light-ening agent, generally in topical applica-tions, and is extracted from the bearberry plant (21). Its toxicology upon oral inges-tion is unknown. This case study shows another example of a counterfeit product that contains an active component whose

indication is misaligned with the intended disease area of the authentic product.

Case Study 5: Product E

The general strategy that is used for testing counterfeit products has also been applied to the characterization of customer com-plaint samples. A complaint sample (prod-uct E) was received for characterization after preliminary testing by Raman and NIR spectroscopy indicated that the prod-uct contained within the bottle was not au-thentic. Visual examination of the packag-ing revealed the presence of pink residue on the threads of the dropper bottle, which indicates that at one point the bottle con-tained the authentic product (pink liquid), but was subsequently refilled with an un-known yellow liquid material. Two peaks, connected by a low horizontal plateau, were detected in the LC–UV chromatogram (see Figure 14). This type of peak shape is fre-quently indicative of an on-column inter-conversion or degradation (22). Molecular weights of 217 Da and 311 Da were assigned to these two observed components. The mass spectrum of the 311 Da component is shown in Figure 15. Accurate-mass data afforded molecular formula information. The compound was determined to contain sulfur, and a loss of H2SO3 was observed from in-source fragmentation. NMR analysis performed in parallel indicated the presence of a monosubstituted phenyl ring, three methyl groups, and a methylene group. The MS data coupled with the infor-mation obtained from the NMR analysis was used to elucidate the structures of the two compounds as shown in Figure 16. Based on the structures, on-column deg-radation could easily be rationalized. The primary component (311 Da) was identi-fied as metamizole, a powerful analgesic and antipyretic (23) that is available over the counter (OTC) as a yellow solution. The indication for product E does not align with that of metamizole.

Case Study 6: Product F

Product F was received for characteriza-tion after preliminary testing by Raman and NIR spectroscopy indicated that the product packed within the gel capsules was not the authentic drug substance. The investigation focused on characterization of the bulk yellow solid. The solid was observed to be insoluble in virtually all

Figure 16: Structure of the primary component in product E and the resulting on-column

degradation product.

O

OHS

ONN

N

O

N

N NHOn-column degradation

O

Chemical formula: C13H17N3O4S

Exact mass: 311.094

Chemical formula: C12H15N3O


Figure 17: LC–UV chromatograms of product F and an authentic sample of tartrazine (430 nm).

1.0e-2

3.35

3.36

Product F

Tartrazine authentic standard

5.0e-3

0.0

0.0

1.0

2.0

Time (min)

Time (min)

Ab

sorb

an

ce (

AU

)A

bso

rban

ce (

AU

)

3.00 4.00 5.00 6.00 7.00 8.00 9.00

3.00 4.00 5.00 6.00 7.00 8.00 9.00



common solvents; however, it dissolved in hydrochloric acid to produce a yellow solu-tion. Based on the solubility characteristics and the observation of effervescence upon dissolution it was suspected that the solid was primarily composed of an inorganic component. Reevaluation of the Raman data with a library containing inorganic compounds resulted in identification of the primary component as CaCO3. The weight percent of CaCO3 in the bulk solid was determined as 81.6 by titration. NMR analysis performed in DCl identified the presence of starch and acetaminophen in the solid. Quantitative NMR was used to assign a combined weight percent of 17.0 to starch and acetaminophen. Because none of the positively identified components could account for the color of the bulk solid, additional testing was conducted to understand the cause of the yellow color. A sample was analyzed by LC–UV-MS with UV detection at 430 nm and with only a single component observed in the UV chromatogram. The molecular weight and elemental composition of the compo-nent were determined by MS. An internet search on the molecular formula led to its identification as tartrazine (the United States Federal Food, Drug, and Cosmetic Act [FD&C] Yellow 5). Figures 17 and 18 show a comparison of the HPLC retention and UV spectra of the yellow component observed in product F with an authentic standard of tartrazine.

Conclusions

A series of case studies were presented to demonstrate a general strategy for conducting investigations of counterfeit pharmaceutical products. The case stud-ies highlight the role of mass spectrometry in enabling the rapid characterization of suspected counterfeit products. The use of this process enables an efficient assessment of patient safety risks that are introduced by these products. The ability to readily as-sign molecular weights and often a single formula for each counterfeit component expedites the process of identification through literature and internet search-ing. The characterization is enhanced by coupling the information obtained from the LC–UV-MS experiments with NMR data. Analysis of the counterfeit samples by NMR provides full confidence in the structural proposals from the LC–UV-MS

analysis and can be leveraged to enable the quantification of components by qNMR.

References

(1) http://www.who.int/medicines/ser-

vices/counterfeit/overview/en/.

(2) A.K. Deisingh, Analyst 130, 271–279

(2005).

(3) B. Hileman, Chem. Eng. News 81(45),

36–43 (2003).

(4) J. Sherma, Acta Chromatogr. 19, 5–20

(2007).

(5) E. Deconinck, P.Y. Sacré, P. Courselle,

and J.O. De Beer, J. Chromatogr. Sci.

51(8), 791–806 (2013).

(6) Y.Q. Shia, J. Yaob, F. Liuc, C.Q. Hua, J.

Yuanc, Q.M. Zhanga, and S.H. Jin, J.

Pharm. Biomed. Anal. 46(4), 663–669

(2008).

(7) S.H. Scafi and C. Pasquini, Analyst

126(12), 2218–2224 (2001).

(8) N.W. Broad, C. Dentinger, and J. Pas-

more, Raman Technologogy for Today’s

Spectroscopists, supplement to Spec-

troscopy 28(6), s22–s31 (2013).

(9) C. Eliasson and P. Matousek, Anal.

Chem. 79, 1696–1701 (2007).

(10) R. Kalyanaraman, M. Ribick, and G.

Dobler, Eur. Pharm. Rev. 17(5), 35–39

(2012).

(11) R. Kalyanaraman, G. Dobler, and M.

Ribick, Am. Pharm. Rev. 14(4), 98–104

(2011).

(12) W.C. Samms, Y.J. Jiang, M.D. Dixon, S.S.

Houck, and A. Mozayani, J. Forensic Sci.

56(4), 993–998 (2011).

(13) F.M. Fernández, R.B. Cody, M.D.

Green, C.Y. Hampton, R. McGready,

S. Sengaloundeth, N.J. White, and

P.N. Newton, ChemMedChem 1(7),

702–705 (2006).

(14) V. Silvestre, V. Maroga Mboula, C. Jouit-

teau, S. Akoka, R. J. Robins, and G.S.

Remaud, J. Pharm. Biomed. Anal. 50,

336–341 (2009).

(15) S. Balayssac, V. Gilard, M.A. Delsuc, and

M. Malet-Martino, Spectrosc. Eur. 21(3),

10–14 (2009).

(16) R. Martino, M. Malet-Martino, V. Gi-

lard, and S. Balayssac, Anal. Bioanal.

Chem. 398, 77–92 (2010).

(17) S. Mahajan and I.P. Singh, Magn.

Reson. Chem. 51(2), 76–81 (2013).

(18) J.K. Maurin, F. Plucinski, A. Mazurek,

and Z. Fijalek, J. Pharm. Biomed.

Anal. 43(4), 1514–1518 (2007).

(19) R. Santamaria-Fernandez, R. Hearna,

and J.C. Wolff, J. Anal. Atomic Spec-

trom. 23, 1294–1299 (2008).

(20) http://www.rxlist.com/elavil-drug/

indications-dosage.htm.

(21) http://www.kaviskin.com/info/a-

arbutin.html.

(22) T. Nishikawa, R. Abe, Y. Sudo, A.

Yamada, and K. Tahara, Anal. Sci. 20,

1395–1398 (2004).

(23) http://www.dd-database.org/pain-

pills/metamizole.html.

Michael B. Peddicord, Charles

Pathirana, Holly M. Shackman,

Mark S. Bolgar, and Scott A.

Miller are with Bristol-Myers Squibb,

Analytical and Bioanalytical Development in

New Brunswick, New Jersey.

Please direct correspondence to:

[email protected]. ◾

For more information on this topic, please visit our homepage at: www.spectroscopyonline.com

Figure 18: UV spectra of primary component in product F and an authentic sample of tartrazine

(430 nm).

Product F257.9 428.9

428.9257.9

5.0e-1

5.0e-1

0.0

0.0

1.0

Ab

sorb

an

ce (

AU

)A

bso

rban

ce (

AU

)

Tartrazineauthentic standard

Wavelength (nm)

250 300 350 400 450 500 550 600



Laura McGregor, Nick Bukowski, and David Barden

Despite the advantages of soft ionization ion-source technologies for improving confidence in the identification of a range of challenging analytes, soft ionization remains a niche technique for gas chromatography–mass spectrometry (GC–MS). This article discusses the reasons for this limitation as well as new developments that make lower-energy electron ionization possible without the disadvantages that have historically been associated with it. The specific benefits of this technique are discussed by reference to several examples across the GC–MS field.

A New Outlook on Soft Ionization for GC–MS

The term “soft ionization” encapsulates a range of techniques that ultimately result in analyte molecules that become ion-ized without imparting excess energy to them. The result

is a limited degree of analyte fragmentation, meaning that the molecular ion passes intact through the mass spectrometer and to the detector. This ability to provide information about the unfrag-mented molecule makes soft ionization of great value to analysts.

For macromolecules, the ready fragmentation of the molecu-lar ion means that soft ionization is the only suitable technique and, in this field, matrix-assisted laser desorption–ionization (MALDI) is a popular method for ionizing DNA, proteins, pep-tides, sugars, polymers, and dendrimers.

However, for smaller analytes amenable to gas chromatogra-phy (GC), high-energy electron ionization (EI), typically at 70 eV, is by far the most popular technique. Large libraries of spectra such as those curated by the National Institute of Standards and Technology (NIST) and Wiley are available for matching and identification, and have long been used by analysts across a wide range of gas chromatography–mass spectrometry (GC–MS) ap-plications. In this field, methods for soft ionization have histori-cally been viewed as more specialized, and more often used in cases where EI at 70 eV does not provide adequate results.

There are multiple reasons for this. The major factor is that EI, which although by its nature is applicable to almost every vaporized substance, cannot be used successfully at lower ener-gies. This is because of inefficient channeling of electrons from the filament (“e-gun”) into the ion chamber, giving an extremely low signal and an unacceptable loss of sensitivity.

Therefore, to achieve soft ionization, analysts have turned to other techniques, of which chemical ionization (CI) is the most common. CI also results in a drop in sensitivity, but to a far lesser extent than EI. Unfortunately, however, CI requires a different ion-source configuration, with additional source pressuriza-

tion and the use of reagent gases. If a single instrument is being used, this can be a time-consuming transition and a consider-able drain on laboratory resources if required on a regular basis.

The challenge, therefore, remained of developing a convenient soft ionization technique that retained the performance and wide applicability of standard 70-eV electron ionization. Hence, we were excited by the development of an e-gun design that removes the link between the energy of the electrons and the ionization efficiency, by introducing an additional electrostatic element be-tween the e-gun and the ion chamber. This allows the ioniza-tion energy of the electrons to be varied on a sliding scale from conventional 70 eV to lower energies, without loss of sensitivity.

The Advantages of Variable-Energy Electron IonizationA key feature of this variable-energy electron ionization is the avoidance of sensitivity losses; absolute ion intensities at low en-ergies have been found to be equal to or greater than at 70 eV. On its own, this would not be particularly useful, but in conjunc-tion with the improved signal-to-noise ratios at low energies (see below), the result is lower detection limits for target compounds. Furthermore, greater sensitivity allows analysts to use the same sample loading and analytical conditions for both hard and soft ionization, meaning less time is spent on sample preparation and method development.

Like other soft ionization techniques, using EI at low en-ergies inherently results in reduced fragmentation, and (as a consequence) an enhanced molecular ion. Importantly, how-ever, we have found that a degree of fragmentation is usually retained even at the lowest energies. The ions produced are typically those that arise from the lower-energy fragmenta-tion pathways, that is, larger ions that are more significant in terms of understanding the structure of the molecule. These

ES393072_SpecCTMS0314_016.pgs 02.25.2014 23:20 ADV blackmagentacyan


larger ions are more often those required for quantitation, and so their increased intensities also benefit calibration.

In addition to reduced fragmentation of the analyte, fragmentation of chromato-graphic background and carrier gases is

Figure 2: Comparison of 70-eV and 11-eV EI spectra for hexachloro-cyclopentadiene, showing the

greatly enhanced molecular ion at the lower energy.

70 eV

11 eV

100

6095 130

165

Cl

Cl

Cl

Cl

Cl

Cl

272

272

237

130

237

50

0

100

50

0

Figure 1: Comparison of mass spectra for benzophenone at 70, 16, and 14 eV.

100 70 eV

16 eV

14 eV

50

0

40 50 60 70 80 90 100 110 120 130 140 150 160 170 180

40 50 60 70 80 90 100 110 120 130 140 150 160 170 180

40 50 60 70 80 90 100 110 120 130 140 150 160 170 180

100

O

50

0

100

50

0

39

51

51

55 63

77

77

77

105

105

105

152

182

182

182

�� ∀ ��

��!��

��#��!��

��!�� !��#� ��!�#��

��

��

��

��

��

��

��

��



also reduced. This greatly improves the signal-to-noise ratios for analytes, reduces demand on the dynamic range, and im-proves limits of detection, particularly in complex or more “dirty” samples.

Another important point to note is that switching from regular 70-eV ionization to lower energies is inherent to the de-

sign, and can be carried out by changing a method parameter in the MS software. As well as avoiding the inconvenience of changing from EI to an alternative soft ionization technique, this allows sequences of samples to be repeated au-tomatically at different energies, with subsequent savings of time.

The inherent variability of the tech-nique is also helpful, by allowing the analyst to adjust the ionization energy to suit the situation, and discover optimal parameters during method development. Relatively small differences in ionization energies at the low end of the scale can have significant differences. For example,

Figure 3: Top: GC×GC–TOF-MS contour plot of a crude oil, showing overlaid EICs (m/z 268 + 282 + 296 + 310 + 324 + 338 + 352), analyzed with

an ionization energy of 14 eV. The panels below (a–d) show the 70-eV and 14-eV EI spectra for each of the four labeled peaks A–D, respectively,

illustrating that it is much easier to discriminate between these compounds using the low-energy spectra.

Phytan

e

n-C20H42 n-C

21H44

n-C22H46

n-C23H48 n-C

24H50

n-C25H52

D

C

3

2

1

35

100

0

70 eV

14 eV

70 eV

14 eV

70 eV

14 eV

70 eV

14 eV

43

43

4343

57 57

5757

4343

4343

57 57

57

57

71 71

7171

8585

85

85

99 99

9999

113 113

113113

127 127

127127

141 141

141141

155 155

155

169

169

169225

239 239253268

268

268

225

225211 211196

197183 183

183

168155

71

71

7171

8585

8585

9999

99

99

113

113

112113

127127

127

141 141

141

155 155

155

183

183 183

225

113

113

183

253253239

225211197

183

169154141

127

268 268

100

100

0

100

Pristane

2-Methyloctadecane n-Nonadecane (n-C19H40)

(a) 7-Methyloctadecane(b)

(c)

100

0

100

(d)

Second-dimension

retention time(s)

First-dimen

sion retent

ion time (m

in)

40

45

50

55

60

B

A



note the difference in relative intensity of the m/z 105 and 182 signals at 16 eV and 14 eV for benzophenone (Figure 1).

The variable-energy ionization tech-nology described above was developed by modifying the ion source for a time-of-flight (TOF) mass spectrometer (Bench-TOF, Markes International), which is able to produce reliable 70 eV spectra that are a close match to those in standard libraries. The following three examples illustrate the use of the new system.

Example 1: Confirming

Compound Identity

Even when using a TOF-MS that pro-duces spectra free from mass discrimi-nation, uncertainties can arise when compounds have weak molecular ions or extensive fragmentation at regular 70-eV ionization energy. As illustrated in Fig-ure 2 for the common pesticide precur-sor hexachlorocyclopentadiene, reducing the ionization energy can greatly enhance the molecular ion, thereby providing an additional degree of confidence in iden-tification.

Example 2: Differentiating

Between Isomeric Compounds

The ability to provide enhanced molecu-lar ions while retaining structurally sig-

nificant fragment ions improves discrim-ination between compounds that have similar spectra at 70 eV. Figure 3 shows an example of this increased orthogonal-ity for four hydrocarbons in a crude oil.

Example 3: Enhancing

Signal-to-Noise Ratios

At low ionization energies, the reduction in the degree of fragmentation of both analytes and chromatographic artifacts helps improve signal-to-noise ratios, with subsequent lowering of the limits of detection. This is illustrated in Figure 4 for the odorous compounds safrole and coumarin, in which the increase in molecular ion intensity and reduction in fragmentation on moving from 70 eV to 15 eV result in an approximately twofold increase in the signal-to-noise values for the molecular ions.

Conclusion

The variable-energy ionization approach described in this article is a rugged tech-nique that has the potential to deliver sig-nificant benefits to GC–MS laboratories across a wide range of applications.

The ability to easily switch between hard and soft EI allows both regular 70-eV spectra to be generated for match-ing against existing libraries, alongside

lower-energy spectra that provide com-plementary information on the mo-lecular ion and structurally significant fragment ions. This complementary in-formation enables more confident iden-tification and discrimination between isomers that previously would not have been resolved.

Furthermore, the reduced fragmenta-tion of analytes, matrix interferences, and carrier gases significantly improve sig-nal-to-noise ratios for target substances, and allow lower limits of detection to be achieved.

For more information about variable-energy electron ionization, and detailed experimental information on the exam-ples covered in this article, please contact the authors.

Laura McGregor, Nick

Bukowski, and David Barden

are with Markes International, at the

Gwaun Elai Medi-Science Campus in

Llantrisant, UK. Direct correspondence

to: [email protected] ◾


Figure 4: Comparison of 70-eV and 15-eV EI spectra for the allergens safrole and coumarin, showing the enhanced signal-to-noise ratios at the

lower energy.

70 eV

S/N 12,199

15 eV

S/N 25,568

100

51

63

77

91

104

104

131

131

162

162

0

100

100

0

100

Safrole Coumarin

O

O

70 eV

S/N 2408

15 eV

S/N 4539

45

63

90

118

118

146

146

O O



Mary Lopez and Bryan Krastins

Translational proteomics has not been as successful as originally anticipated. Because mass spectrom-etry (MS) can separate proteins at the sequence level, it provides the selectivity needed for this appli-cation; however, traditional challenges still exist, including time-to-result, throughput, and sample-size requirements. For analytical validation and verification purposes, sample preparation times must be reduced from days to hours. Scientists recently coupled a previously developed immunoaffinity enrichment method to selected reaction monitoring (SRM) MS. The MS immunoassay–SRM method combines liquid chromatography–tandem mass spectrometry (LC–MS-MS) for target identification, a microscale immunoaffinity capture method for enrichment, and subsequent SRM analysis. Using the MS immunoassay–SRM workflow, a standard high-throughput method for developing targeted bio-marker identification of proteins in human plasma and serum for clinical research was developed.

An Enhanced Immunoaffinity Enrichment Method for Mass Spectrometry–Based Translational Proteomics

Mass spectrometry (MS)-driven proteomics has made progress in the identification and quantification of disease biomarkers, including C-reactive protein as an

indicator for myocardial infarction and prostate-specific anti-gen (PSA) for prostate cancer. Despite these and other successes, translational proteomics, which is defined as the translation of biomarker discovery to routine analysis, has not been nearly as successful as originally anticipated because comprehensive proteomic analysis of plasma, serum, and other biological flu-ids has proved exceedingly challenging. The “look alike” nature of molecular isoforms, the enormous dynamic range of protein concentrations of potential interest (>10 orders of magnitude in blood plasma), and the fact that molecules of interest are often in low abundance have all slowed the progress of biomarker hunters across the globe.

One example of the challenge presented by protein analyte isoforms is demonstrated by the need to distinguish between full-length parathyroid hormone (PTH) 1-84 and multiple N-terminally truncated PTH variants. The differences between these isoforms are critical to accurate diagnosis of endocrine and osteological diseases (1). Similarly, in clinical testing, PSA

typically presents in truncated and modified isoforms, making precise detection and quantification difficult which contributes to a high false-positive rate (2).

From a processing point of view, binding protein detach-ment and the high dynamic range of samples have hampered assays for insulin-like growth factor 1 (IGF-1), a marker for growth-related illness that is important in cell proliferation, differentiation, apoptosis, and tissue growth from a research point of view (3).

To add to these challenges, verification and population-scale biomarker validation require the analysis of hundreds or even thousands of high-quality samples. Sample collection and storage must use standard protocols to reduce potential variations attribut-able to endogenous enzymes or sample contamination. Verifica-tion and validation studies require multiple control groups and subjects in disease subcategories — all gathered over the course of disease progression. The analysis of many samples is required to distinguish normal human genetic heterogeneity and heterogene-ity attributable to disease. High-throughput detection methods are essential to achieving statistical confidence in the accurate identification of molecules of interest (4).

ES392201_SPECCTMS0314_020.pgs 02.25.2014 02:28 ADV blackmagentacyan

Offering unparalleled MS/MS resolution and excellent mass accuracy, Shimadzu’s new MALDI-7090 tandem mass spectrometer achieves a new level of MALDI-TOF MS performance.

The MALDI-7090 features:

The MALDI-7090 is ideal for:

■ Unparalleled MS/MS Resolution

■ Excellent Mass Accuracy

■ 2kHz Acquisitions in All Modes

■ High-Resolution Ion Gate

■ Low and High-Energy Fragmentation

■ TrueClean™ Laser Source Cleaning

■ 10 Plate Sample Loader

■ Multi-User Software Environment

Order consumables and accessories on-line at http://store.shimadzu.comShimadzu Scientific Instruments Inc., 7102 Riverwood Dr., Columbia, MD 21046, USA

Learn more about Shimadzu’s MALDI-7090.

Call (800) 477-1227 or visit us online at

www.ssi.shimadzu.com/7090

Shimadzu’s High Throughput, High Resolution, High Energy MALDI-7090

Introducing a New Dimension in MALDI TOF-TOF Design

■ Tissue Imaging

■ Biomarker Discovery

■ Lipidomics

■ Proteomics

■ Post-translational modifications



Challenges of Current Assay TechnologiesThe current gold standard for biomarker detection uses enzymes to bind antibody ligands to target molecules. The enzyme-linked immunosorbent assay (ELISA) has played a central role in diagnostic and clinical research applications for the last two decades. However, as molecular biol-ogy advances and as scientists are able to access new technologies with higher rec-ognition accuracy, ELISA is emerging as a potential source of inaccuracy leading to imprecise biomarker detection and re-sulting in incorrect diagnosis and treat-ment. In certain cases, demonstrated poor concordance among assays from different manufacturers has raised questions about ELISA’s accuracy (5). Poor concordance stems from the variety of proprietary an-tibodies used to detect different epitopes, as well as natural biological diversity manifested in post-translational modifi-cations, single nucleotide polymorphisms, and cross-reactivities between antibodies to off-target proteins. Various interfer-ences have also been observed, including antireagent antibodies and endogenous auto-antibodies, which can generate in-correct results. These indirect, nonspecific signals mask consequential variations in molecular structures (5). An October 2013 study investigated the specificity of the commercial CUZD1 ELISA assay (6). CUZD1 is a biomarker for ovarian and pancreatic cancer, as well as inflammatory bowel disease (7). Using a combination of western blot, high performance liquid chromatography (HPLC), and MS, the study confirmed that instead of CUZD1, the commercial assay recognizes a non-homologous cancer antigen, CA125. The study concluded that the poor character-ization of the commercial ELISA assays may lead to false biomarker discovery (6).

A Combined EffortMS has been used for quantification of small molecules for years and, more re-cently, has been applied to protein quan-tification and analysis. Because MS can separate proteins at the sequence level, it provides the selectivity needed to address the specificity issues outlined above (4). As noted, for validation and verification pur-poses, high throughput and high accuracy are vital; unfortunately, the traditional Figure 2: Immunoaffinity enrichment workflow.

Antigen binding

Analyticalsample

6.68

6.94 7.13

7.58

7.96

8.73

9.03

6.86

7.17

10.68

11.04

12.09

9.03

9.27

10.18

10.68

1. Buffer2. Water3. Elution

Dispense eluent into amicrotiter plate, and

neutralize

Reduce, alkylate, and digest with trypsin (3 h)

LC–MS SRM assay1.25-7 min/sample

(depending on multiplexing)

Rinse and elute

Sample extraction and elution (2 h)

Figure 1: Automated workflow for optimization of SRM analyses.

Algorithmic prediction of

optimal transitions

Import protein sequences Software

Analyze clinical samples

Mass spectrometer

SRM

Approximately 1 hExhaustive List:

Using digests from recombinantproteins or synthetic peptides

• Peptides

• Transitions

Initial LC-SRM assay

Import discovery data

Iterative optimization

• LC–MS-MS spectra• Peptide libraries• Recombinant protein• Heavy-labeled peptides• QC standard

• Best peptides• Best transitions• Optimize LC gradient

Approximately 30 min per iteration

Total method development time = approximately 2 h



challenges surrounding MS-based tech-niques include time-to-result, throughput, and sample-size requirements. For MS to be used for validation and verification pur-poses in translational proteomics, sample preparation times must be reduced from days to hours (4). Despite their shortcom-ings, both ELISA and MS methods are widely used in routine clinical research and analysis. In recent years, researchers have used immunoaffinity enrichment coupled to MS to combine the selectivity of immu-noaffinity extraction with the specificity of MS detection (8,9).

Sample Processing Before MSOne of the hurdles that scientists have worked to overcome to improve MS ac-curacy involves sample preparation before MS. The wide dynamic range of proteins in biological fluid samples compromises the ability of MS to achieve sufficient sen-sitivity to accurately quantify potential biomarkers. Scientists have explored nu-merous sample preparation approaches to eliminate proteins of little interest that in-crease dynamic range. These approaches include fractionation using multiple liquid chromatography (LC) columns, depletion of abundant proteins, enrichment using solid-phase extraction, nanoparticles, and immunoaffinity enrichment by various techniques that include magnetic beads and microcolumns (10).

MethodScientists at Thermo Fisher Scientific, in partnership with Arizona State Univer-sity, the Institut de Recherche Clinique de Montréal, the Sahlgrenska Academy at the University of Gothenberg, the Uni-versity Health Network at the University of Toronto, and Kings College Hospital in London, have coupled a previously developed immunoaffinity enrichment method (MSIA, Thermo Fisher Scientific) (8) to selected reaction monitoring (SRM)

MS (11). The MS immunoassay–SRM ap-proach combines LC–MS-MS for target identification, a microscale immunoaffin-ity capture method for enrichment, and subsequent SRM analysis.

Target IdentificationTo identify optimal peptides and transi-tions for SRM, the system combines al-gorithmic and spectral library prediction using Pinpoint software with results from high-resolution LC–MS-MS analysis re-sulting in a list of targets. After the first strategy is built and recombinant protein or peptide standards are obtained, scien-tists can narrow the list by iteratively op-timizing collision energies, LC gradient, and SRM scheduling windows. Only the highest intensity transitions are retained and, after three or four repetitions, the system is ready for sample analysis. Figure 1 shows the workflow for the optimiza-tion of SRM analyses.

EnrichmentIn the immunoaffinity capture step, anti-bodies are surface-immobilized in small, porous microcolumns fixed into pipette

tips. Samples are repeatedly aspirated and dispensed through these affinity pipettes to expose the immobilized antibody to the targeted proteins (10). This iterative step has the equivalent effect of lengthen-ing an LC column. After the proteins are captured, they are eluted for subsequent MS detection. In a single iterative sepa-ration step, target proteins and variants are captured using antibodies aimed at epitopes in the protein sequence. The ap-proach is applicable to low-abundance proteins because of the robust immuno-affinity enrichment of the target analyte. Figure 2 summarizes the immunoaffinity enrichment workflow.

Reference StandardsMost targeted protein detection methods add surrogate peptides and corresponding isotope-labeled counterparts to samples for standardization after digestion, just before the MS step. The MS immunoassay–SRM design, however, adds internal reference standards at the outset, before enrichment. This means the standard goes through all the same steps that the sample undergoes, acting as a normalizer for all processing

Table I: Assay format comparison: MS immunoassay tip versus beads

Protein Surface MS Immunoassay DART’s LLOD/LLOQ (ng/mL) Magnetic Bead LLOD/LLOQ (ng/mL)

Protein G 1 (5.2 fmol) 1 (5.2 fmol) 5 (26 fmol) 10 (52 fmol)

Protein A 1 (5.2 fmol) 5 (26 fmol) 10 (52 fmol) 20 (104 fmol)

Protein A/G 1 (5.2 fmol) 1 (5.2 fmol) 10 (52 fmol) 20 (104 fmol)

MS immunoassay tips outperform beads:• >5× more sensitive• enable 10× lower LLOQ

Figure 3: High-resolution orbital trap MS-MS data of IGF-1 peptide obtained from MS

immunoassay tips (top) versus magnetic beads (bottom).

Rela

tive a

bu

nd

an

ceR

ela

tive a

bu

nd

an

ce

1009080706050403020100

1009080706050403020100

94

IgF1 peptide

IgF1 peptide

96 98 100 102 104 106 108 110 112 114 116 118 120 122124 126 128 130



and data collection steps. In this type of MS immunoassay–SRM experimental workflow, recombinant proteins rather than isotope-labeled peptides are used. Recombinant proteins, if available, are less expensive and can be easier to obtain. After digestion, heavy isotope-labeled peptides are added to ensure quality control of the LC and MS detection steps in each sample to measure run-to-run variance.

ResultsUsing the MS immunoassay–SRM work-flow, a standard high-throughput work-flow for developing targeted biomarker

identification of proteins in human plasma and serum was developed (11). The standardized protein identification workflow included targeted methods for 16 different protein analytes, includ-ing members of the apolipoprotein fam-ily: ApoE, ApoA1, ApoCI, ApoCIII, and ApoJ; some medium-high abundance proteins: ceruloplasmin, vitamin D bind-ing protein, beta-2 microglobulin, and C-reactive protein; and several important low-abundance proteins, including pro-calcitonin, PTH, IGF-1, PSA, erythro-poietin, proprotein convertase subtilisin/kexin type 9, and amyloid beta.

Results for PTH and IGF-1 MS immu-noassay–SRM were compared to clinical analyzer immunoassays. Correlation be-tween the two methods yielded R2 values ranging from 0.67 to 0.87, depending on the surrogate target peptide. For PTH, the correlation of the analyzer data with MS immunoassay–SRM of the single, N-terminal peptide versus the average of all peptides suggests that the analyzer-based immunoassay likely includes uncharacter-ized, intact, and truncated protein species, leading to an overestimation of functional protein. In comparison, SRM characterizes all isoforms; therefore, all species of inter-est are individually quantified, resulting in improved accuracy. In addition, the method allowed discovery of previously undescribed isoform variants of PTH.

Subsequently, Thermo Scientific sci-entist Eric Niederkofler presented data in a webinar (12) that compared IGF-1 results obtained using the MS immunoas-say–SRM approach with results obtained using a magnetic bead immunoenrich-ment technique. This work demonstrated that the MS immunoassay technique was five times more effective than the bead method, lowering the limit of quantifica-tion by 10-fold (see Table I) and producing improved signal-to-noise ratio at the MS stage (Figure 3).

In our published results (11), we pre-sented linear regression curves that showed R2 values from 0.089 to 0.098. In Figure 4 we present similar data for two apolipoprotein E peptides.

Sensitivity and PrecisionFigure 5 presents SRM chromatograms for ApoE surrogate peptides from digested human plasma. Peak shapes are symmet-rical and relatively free of significant noise. SRM transition ion ratios were within ±15% of internal standard reference ratios. To ensure selectivity, we used several SRM transitions for each peptide. Detection limits and dynamic ranges for all targeted peptides were well within the useful range for the selected analytes, and lower limit of quantification values were all within the lower portion of existing ranges.

ObservationsProtein or Peptide Level Enrichment?

While developing this approach to im-munoaffinity enrichment over the last five

Figure 4: Calibration curves for ApoE targeted peptides.

0.16.001483x+0.0 R^2=0.952

Standard points Standard points

N .002431x+0.0 R^2=0.952N

Are

a r

ati

o

Are

a r

ati

o

0.15

0.13

0.12

0.1

0.09

0.07

0.06

0.04

0.03

0.01 0.02

0.05

0.07

0.12

0.15

0.17

0.19

0.22

0.24

0.27

LGPLVEQGRLAVYQAGAR

0.1

00 20 40 60

Spiked-in amount (µg/mL) Spiked-in amount (µg/mL)80 100 120

00 20 40 60 80 100 120

Figure 5: Representative SRM chromatogram results.

100474.767->502.273(2.342e+3) 484.780->489.241(1.381e+4)

484.780->588.309(2.114e+4)

484.780->701.393(5.378e+3)

484.780->798.446(3.460e+3)

474.767->665.336(2.613e+3)

474.767->764.404(4.192e+3)

474.767->835.442(1.785e+3)

479.771->512.281(6.677e+4)

479.771->675.344(1.447e+5)

479.771->774.413(1.228e+5)

479.771->845.450(3.518e+4)

90

80

70

60

50

40

30

20

10

0

100

90

80

70

60

Re

lati

ve

in

ten

sity

(2

.11

4e

+4

)

Re

lati

ve

in

ten

sity

(1

.44

7e

+5

)

50

40

30

20

10

011.55 12.73 12.91 13.1 13.28 13.47 13.65 13.84 14.011.73 11.91 12.09 12.27 12.45 12.63 12.8

LAVYQAGAR LGPLVEQGR



years, we found that, in many cases and for several reasons, antiprotein antibodies are preferable binding agents to antipep-tide antibodies. Antiprotein antibodies typically enrich multiple protein isoforms, making it easier for SRM analyses to distinguish active from inactive forms. Because antipeptide antibodies must be highly specific, each target requires a separate antibody. For example, for PTH protein detection using MS immunoas-say–SRM and antipeptide antibodies, in-vestigators would need to generate seven different antipeptide antibodies to reveal the same information available from one antiprotein antibody. Using an antiprotein antibody raised toward an epitope com-mon to all isoforms or variants costs less, because only one protein is required to bind multiple forms. Using antipeptide antibodies also makes it more difficult to add new targets to a test, because multiple new antipeptide antibodies must be devel-oped for each analyte.

Antiprotein antibody capture provides distinct advantages in the trypsin digestion stage as well. Because digestion depends on the protein-to-trypsin ratio, complex sam-ples such as raw plasma or serum require relatively large amounts of trypsin and long digestion times. Samples enriched at the protein level are digested after enrich-ment. Because they are less complex than raw samples, this results in reduced diges-tion times, typically 3 h or less.

In comparison, samples enriched at the peptide level require crude digestion be-fore enrichment and, as a result, take more time to process. Crude digestion also in-jects a potential source of error stemming from uncontrolled or unknown causes. By their nature, samples from different states of disease are expected to contain vary-ing levels of proteins. Digestion variability because of illness may impact results and has not been adequately studied. Finally, if surrogate peptides are not unique, di-gestion and subsequent enrichment may result in incorrect measurements, because one peptide sequence may be present in multiple proteins.

Enrichment for All

In our observation, all samples can benefit from immunoenrichment, not just those in which tests are searching for low-abun-dance molecules. Enrichment of high-

abundance targets reduces processing times, lowers costs, and improves specific-ity. First, the lower the sample complexity, the faster it can go through trypsin diges-tion. Second, the process uses less trypsin than if the sample were unenriched; using less trypsin makes a test less expensive. Third, although protein targets may be in high abundance, important isoforms are probably rarer, and enrichment pro-motes isoform capture. The work with PTH and ApoAI showed that immu-noenrichment and detection with the MS immunoassay–SRM method identi-fied new isoforms, as well as new C- and N-terminally truncated variants, which may be present in much lower amounts. A practical advantage lies in reduced cleaning and maintenance requirements for mass spectrometers and LC columns because they are not injected with plasma or serum. Using purified samples also im-proves routine measurement consistency.

Multiplexing

Multiplexed ELISA or other immunoas-say technologies present limitations be-cause as the number of analytes increases, sensitivity typically decreases. The im-munoenrichment technique allows mul-tiplexing of analytes by serial extraction of the same sample. To test for different targets, samples can be enriched using different antibodies embedded in the mi-crocolumns on the pipette tips. This ap-proach is fast, conserves sample volumes, and avoids the problem of accommodat-ing several antibodies with different op-tima for binding and elution conditions on a single substrate.

Conclusion:

Immunoenrichment for MS-Based

Translational Proteomics

MS-based proteomics is a powerful tool for research and facilitates two impor-tant areas: identification, verification, and validation of new biomarkers, and detection and quantification of those markers in clinical research settings. Potential clinical research and biophar-maceutical applications might include screening, tracking progression, predict-ing course and outcome, monitoring for recurrence, and personalized assessment of drug response and toxicity (4). MS im-munoassay–SRM–based proteomics,

using the immunoenrichment method described, may offer a significantly shorter development time, reduced costs, and higher specificity for the iden-tification of proteins and their isoforms in comparison to existing methods.

References

(1) M. Lopez et al., Clin. Chem. 56(2),

281–290 (2010).

(2) H.B. Carter, Asian J. Androl. 14, 355–

360 (2012).

(3) E. Niederkofler et al., PLoS ONE 8(11),

e81125 (2013).

(4) E.S. Baker et al., Genome Med. 4, 63

(2012).

(5) J. Becker and A. Hoofnagle, Bioanalysis

4(3), 281–290 (2012).

(6) I. Prassas et al., Clin. Chem. 60(2),

290–291 (2014).

(7) C. Liaskos et al., Clin. Dev. Immu-

nol., vol. 2013, article ID 968041

(2013). Available at: http://dx.doi.

org/10.1155/2013/968041.

(8) R. Nelson and C.R. Borges, J. Am.

Soc. Mass Spectrom. 22(6), 960–968

(2011).

(9) O. Stoevesandt and M. Taussig, Expert

Reviews Proteomics 9(4), 401–414

(2012).

(10) D. Nedelkov, Expert Rev. Mol. Diagn.

12, 235–239 (2012).

(11) B. Krastins et al., Clin. Biochem. 46,

399–410 (2013).

(12) E. Niederkofler, “MSIA-SRM: Next

Generation Method for Insulin-Like

Growth Factor-1 Measurement,”

(2012). Available at: http://www.

thermoscientific.com/en/about-us/

events/Solve-Challenging-Protein-

Quantitation-Problems-in-Clinical-

Research-with-Mass-Spectrometric-

Immunoassay-Application-MSIA.

html#sthash.2AhLquTf.dpuf.

Mary Lopez and Bryan

Krastins are with the Thermo Fisher

Biomarkers Research Initiatives in Mass

Spectrometry Center (BRIMS) in Cambridge,

Massachusetts. Direct correspondence to:

[email protected] ◾


ES392202_SPECCTMS0314_025.pgs 02.25.2014 02:28 ADV blackmagentacyan


Elizabeth Humston-Fulmer

Here, a method to characterize edible oils and edible oil mixtures through fingerprinting and the isolation of individual analyte differences is reported. Aroma and flavor analytes in extra virgin olive, olive, peanut, grapeseed, and vegetable oils were sampled with headspace solid-phase microextraction (HS-SPME). The samples were analyzed with complementary gas chromatography (GC) systems; two-dimensional GC paired with time-of-flight mass spectro-metry (GC×GC–TOF-MS) and one-dimensional GC coupled to high resolution TOF-MS. These methods allowed for comparing edible oil varieties by their chromatographic finger-prints, characterizing the samples with the identification of individual analyte differences, differentiating oil mixtures from pure oil varieties with principal component analysis (PCA), and confirming analyte identities with accurate mass data.

Comparison of Edible Oils by GC×GC–TOF-MS and GC–High Resolution TOF-MS for Determination of Food Fraud: A “Foodomics” Approach

Characterization of food products, including distinguishing differences, is important in the food industry. Differences that are intentionally introduced are of particular interest.

The global marketplace has seen an increase in cases of food fraud, which is loosely defined as the deliberate misrepresentation of a product for the purpose of monetary gain, with cost estimates of these types of fraud at $10–15 billion dollars per year (1). Olive oil adulteration ranks near the top of all reported food fraud cases with common adulterations including the substitution of olive-derived oils with other less expensive edible oils or the mislabeling of regular olive oils as extra virgin olive oil (2).

These adulterations are often difficult for a consumer to detect, but can decrease health benefits and have the potential for unin-tended exposure to allergens — for example, by adulteration with nut oils. Detecting food fraud experimentally is also challenging because of the inherent variations of natural products and the wide range of potential methods of adulteration. Targeted analytical tools

to screen for specific analytes or known adulterants have the risk of missing new or unanticipated mechanisms of food fraud. Non-targeted analytical methods, especially those that isolate individual analytes within a food matrix and characterize complex food prod-ucts, are well-suited for addressing these challenges.

Gas chromatography (GC) is a well-established analytical ap-proach used in the food industry for isolating individual analytes within a complex matrix. For many samples, one-dimensional GC is sufficient to isolate the components of the mixture, but as sample complexity increases so does the occurrence of coelution. One app

Documents

Characterizing Edible Oils Using GCxGC–TOF-MS and …images2.advanstar.com/PixelMags/spectroscopy/pdf/2014-03... · 2014. 2. 28. · The compact mass spectrometer delivers full