Identifying Unknowns: A challenge for Metabolomics

Jeevan K. Prasain, PhDDepartment of Pharmacology and

Toxicology, UABjprasain@uab.edu

Outline• Introduction• How to interpret LC-MS and MS/MS

data.• Identification of some conjugated

metabolites.• Conclusions

Introduction• Identification of metabolites (lipids or any other

metabolites) at a molecular level presents a great challenge due to their structural diversity (isobars and isomers) and dynamic metabolism.

• Considering the number of metabolites is >2000,000, there is a lack of commercial analytical standards (only a few thousands available) or comprehensive databases.– Note that there is the opportunity to make specific metabolite

standards through the NIH Common Fund– Go to http://metabolomicsworkbench.org

• Inclusion of many artifacts in database.• Structural complexity of metabolites.• Low concentrations and difficult to isolate.

Metabolome

LC-MS

NMRGC-MS

CE-MSPDA

Adapted from Moco et al., Trend in Analytical Chemistry, 2007

Majority of metabolites are yet to be identified; LC-MSand NMR are the most commonly used analytical techniques

for metabolite identification

Keys to identifying chemical structures by mass spectrometry

• Combination of the following:

o Retention time in LCo Accurate masso Isotope distributiono MS/MS product ions of a precursor ion

Raw LC-MS data

Interpretation of MS/MS of a precursor ion(accurate mass, isotope data and nitrogen rule)

Putative identification(molecular formula determination)

De novo structure elucidation (NMR and or LC-MS/MS)

Metabolite identification workflow

Metabolomics/chemical database search(known/new or novel)

Data file processed by algorithms(e.g., XCMS)

Platform to process untargeted metabolomic data

• XCMS (developed by the Siuzdak Lab at the Scripps Research Institute) Online, is a web-based version that allows users to easily upload and process LC-MS data. It provides links to METLIN database and produces a list of potential metabolites.

• METLIN (developed by the Siuzdak Lab.) is a metabolite database for metabolomics containing over 64,000 structures and it also has comprehensive tandem mass spectrometry data on over 10,000 molecules.

LCMS-based metabolomics• Detection of intact molecular ions [M+H]+/[M-H]- is

possible with soft ionization such as ESI• High mass accuracy of many instruments (

Points to be considered in LC-MS analysis

• Choice of ionization mode- ESI Vs APCI +ve/-vemodes

• Choice of eluting solvent- methanol Vs acetonitrile• Additives/pH in mobile phase• Molecular ion recognition (adduct formation) • Chromatographic separation- stationary phase C8,

C18 ..• Evaluation of spectral quality- what to look for in a

good quality spectra

Nielsen et al., J Nat Prod. 2011

Adduct formation might complicate metabolite identification

Use of isotope pattern in identification of metabolites

• Very close in mass, but different in isotope patterns.

• Isotope ratio outlier analysis (IROA)– Used for LC‐MS (and possibly GC‐MS)– Designed to distinguish between metabolites of interest and background signals

– Requires uniform labeling at the 95% and 5% 13C‐enrichment levels

Pairing the 5% and 95% 13C‐labeling distinguishes artifactual molecules

Courtesy of IROA Technologies 

Value of knowing the carbon #

IROA Technologies

Isotopic pattern intensity of [M-H]- and 13C and [M-H+2]-signals indicates the number of carbons and hetero atoms

in the molecular ion

287

289288

1H = 99.9%, 2H = 0.02%12C = 98.9%, 13C = 1.1%35Cl = 68.1%, 37Cl = 31.9%

50 100 150 200 250m/z

100

75

50

25

035 91

139

151

167

195

223251

287

36 Da-HClCl-

50 100 150 200 250m/z

35 59 133139

151

167

195

223 251 287

3’-chlorodaidzein standard

Daidzein + PMA induced HL-60 cells

Comparison of product ions between known and unknown can help elucidate the unknown

Prasain et al., 2003; Boersma et al., 2003

Good chromatographic separation and accurate massindicate a number of diastereoisomer/enantiomer

of PGF2alpha in worm extracts

m/z, amu40 100 160 220 280 340

3.8e6193.1

309.2164.9

171.2 291.1208.9

247.2191.1111.2 353.4263.1255.0173.0

229.2273.2

137.1 181.2281.2

219.043.2 113.0

124.8 299.2

335.159.3 138.8

ESI-MS/MS of the [M-H]- from PGF2a m/z 353 using a quadrupole mass spectrometer

O-

O

OH

HO

HO

Fragmentation scheme of PGF2a [M-H]- m/z 353

Ions m/z 309, 291, 273 and 193 are indicative of F2‐ring

Only in chiral normal phase column,PGF2alpha and its enantiomer can be distinguished

McKnight et al., (Science, 2014)

Great similarities between C. elegans and Cox dKO pups PGF2 profile

Great similarities between C. elegans and Cox dKO pups PGF2 profile

220 280 300 320 360 380 m/z0

%

0

100

%

255.050

256.057

297.043

267.037

268.041281.051

307.065321.046

363.046335.061351.044 381.055

100

240 260 340

[A]

[B]

-162 Da

Yo+

-120 Da

O

OH

O

O

O

OHOH

CH2OH

OH

daidzin

Puerarin

O

O OH

HO

O

HO

OH

OH

CH2OH

Ions break at weakest points; difference in O- and C-glucoside fragmentation

Prasain et al., J. Agric. Food Chem., 2003

m/z

100 311

Identification of unknowns: comparing the MS/MS spectra of the known compound (puerarin)

150 200 250 300 350 400

%

0

255268

282

‐120 431

O

OOH

HO

O

HO

OH

OH

H2COH

+OH

200 250 300 350 400

100

50

0

267 295

\

415

‐120

Monohydroxylatedpuerarin

Puerarin

Mass/Charge120 180 240 300 360 420 480 540 600 660 720 780 8400

26000 283.2637

419.2557

721.4807

437.2651301.2168152.9960

722.4945284.2669

420.2642808.5115

281.2476438.2742302.2204257.2272 723.4921455.2236

-87 Da

Nitrogen rule-Odd number of nitrogens = odd MW

Even nitrogens = even MW

120 180 240 300 360 420 480 540 600 660 720 780 840 9000

20000 883.5366

884.5405

301.2178

283.2648885.5465241.0129

419.2565 810.5110581.3109257.2312302.2218 811.5135223.0022 582.3122526.2935152.996

4420.2590303.2327 810.5906

-302 [M-FA C20:5]-

Accurate mass (

Library search for eicosanoid http://www.lipidmaps.org/

Targeted metabolomics: identification of conjugated

metabolites (glucuronide/sulfate conjugates/glutathione-GSH)

100 200 300 400

m/z

100

50

0

Relativ

e Intensity

 (%)

5985

113133 181 224

269

Genistein[M‐H]‐

-176 Da

The loss of anhydrous glucuronic acid (176 Da)-the characteristic of all glucuronides

60 120 180 240 300 360 420 480 540 600 660 720 780 840Mass/Charge, Da

0

70 317.2107

306.0739

272.0877143.0447128.0363 254.0739

821.3264514.2514160.0111210.0907179.0504 249.0358

177.0376288.0615

197.055758.029599.0577

74.0250

-307.07 Da

[M-H]-

Inte

nsity

GSH conjugates can be identified with characteristicfragment ions m/z 306, 272, 254, 210, 179, 160

and 143 in -ve ion mode

HS

HN NH

-O

O

OO

NH2HO

O

m/z 306.0765

Jackson et al. unpublished results

The loss of 80 Da from the parent ion and the presence of m/z 80 in the product ion spectra indicates aromatic sulfate

conjugates

20 60 100 140 180 220 260 300

5.5e6

Intensity, cps

116.9

253.0

134.9

252.0132.991.0224.0

207.980.0

96.9 225.0197.0160.0

[A] OHOO

O

SO

O O-

m/z, amu

20 60 100 140 180 220 260 300 340

1.4e7

Intensity, cps

121.0

119.0

135.0

79.993.0 241.0

147.091.0 320.9

[B]

OO

OH

SO

O

O-

80 Da

80 Da

Aliphatic sulfates typically show m/z 97 (HSO4-), whereas aromatics show m/z 80 (SO3-)

Weidolf et al. Biomed. and Environ. Mass Spec. 1988 

Ionization mode Scan

Glucuronides pos/neg NL 176 amuHexose sugar pos/neg NL 162 amuPentose sugar pos/neg NL 132 amuPhenolic sulphate pos NL 80 amuPhosphate neg Prec m/z 79, NL 80/98 GSH Pos/neg NL 129 amuGSH Negtaurines Pos Precursor of m/z 126N-acetylcysteins neg NL 129 amu

NL = neutral loss.

Conjugate

Characteristic fragmentation of metabolite conjugates by MS/MS

Kostiainen et al., 2003

Prec m/z 272

Conclusions• Identifying uncharacterized metabolites in biological

samples is a significant analytical challenge and it requires integrated analytical approaches.

• A well separated metabolite signals in LC-MS/MS is crucial for unambiguous identification of new chemical entity.

• Data processing and data analysis are important for putative identifications.

• The use of high-resolution MS and MSn provides important information to propose structures of fragment and molecular ions.

• Combination of MS with NMR (eg. LC-NMR) is one of the most powerful analytical strategies for structure elucidation of novel metabolites.

Acknowledgements• Stephen Barnes, PhD (UAB)• Michael Miller, PhD (UAB)• Lalita A. Shevde, PhD (UAB) • Ray Moore (ex-TMPL)• Landon Wilson (TMPL)• William P. Jackson (UAB)