November 2022

MedicalIssue Lipidomics
MedicalMass
MassSpectrometry
SpectrometrySpecial
Lipidomics
Vol. 6 No. 2

Research Paper

Comprehensive analysis of fatty acid metabolites produced
by gut microbiota using LC-MS/MS-based lipidomics
1,3,4

Kowa Tsuji
1*, Wataru Shimada4, Shigenobu Kishino5, Jun Ogawa5, Makoto Arita1,2,3
2

Research Center for Drug Discovery, and Division of Physiological Chemistry and Metabolism, Graduate Schoolof Pharmaceutical Sciences, Keio University, Minato-ku, Tokyo 105‒8512, Japan
3
Laboratory for Metabolomics, RIKEN Center for Integrative Medical Sciences,1‒7‒22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230‒0045, Japan
4
R&D, Noster Inc., 35‒3 Minamibiraki, Kamiueno-cho, Muko, Kyoto 617‒0006, Japan
5
Division of Applied Life Sciences, Graduate School of Agriculture, Kyoto University,
Kitashirakawa-oiwakecho, Sakyo-ku, Kyoto 606‒8502, Japan

Abstract

The saturation metabolism of polyunsaturated fatty acids represents a mode of detoxiﬁcation metabolism by thegut microbiota. It generates a series of functional fatty acids, such as hydroxy fatty acids (e.g., 10-hydroxy-cis-12-octadecenoic acid (HYA) from linoleic acid), oxo fatty acids, conjugated fatty acids, and trans fatty acids. In this study, we prepared
45 synthetic standards, including HYA and related fatty acid metabolites, and developed liquid chromatography-tandem
mass spectrometry-based targeted lipidomics. This method was successfully applied for the comprehensive analysis of thegut microbiota-dependent production of fatty acid metabolites in mouse feces, plasma, and tissues under diﬀerent dietaryconditions.
Key words: mass spectrometry, bacteria, hydroxy fatty acids, lipidomics

Introduction

fatty acids. For example, 10-hydroxy-cis-12-octadecenoic
acid (HYA) and 10-oxo-cis-12-octadecenoic acid (KetoA)

Dietary fats are metabolized by host digestive enzymes
and gut microbiota. The saturation metabolism of polyun-

are produced as intermediates when linoleic acid is metabo-saturated fatty acids (PUFAs), which is the detoxiﬁcation

lized to oleic acid. In addition to this metabolic pathway,some lactic acid bacteria hydrate the double bond at the Δ 12-

metabolism of anaerobic bacteria, produces unique fatty
acid metabolites that are not produced by host enzymes .
C18 fatty acids, such as linoleic acid (C18:2 n-6) (LA),position of 18-carbon fatty acids to produce 13-hydroxyα-linolenic acid (C18:3 n-3) (ALA), and γ-linolenic acid
(C18:3 n-6) (GLA), are metabolized by enzymes, such as

and metabolic enzymes contributes to the production of aseries of functional metabolites (Fig. 1). HYA, a LA-de-

CLA-HY, CLA-DH, CLA-DC, and CLA-ER, to generate aseries of functional fatty acids, including hydroxy fatty

rived metabolite, exerts an anti-obesity eﬀect and enhances
intestinal barrier function via G-protein-coupled receptor

acids, oxo fatty acids, conjugated fatty acids, and trans(GPR)40 and GPR120

1)2)

fatty acids . A combination of diﬀerent fatty acid substrates. 10-Oxo-cis-6,trans-11-octadecadienoic acid (γKetoC), a GLA-derived metabolite, sup-* Corresponding author

3,4)

Kowa Tsuji

presses LPS-induced inﬂammatory cytokine production in5)
monocytes . 13-Hydroxy-cis-9,cis-15-octadecadienoic acid

Kyoto 617‒0006, Japan( α HYD), an ALA-derived metabolite, induces M2 macrophage diﬀerentiation from bone marrow-derived cells via

Noster Inc., 35‒3 Minamibiraki, Kamiueno-cho, Mukou-city,
Tel: ＋81‒75‒921‒5303, Fax: ＋81‒75‒924‒2702
E-mail: ko.tsuji@noster.inc

GPR40 . Therefore, it is important to monitor these metab6)olites comprehensively in biological systems to explore
their signiﬁcance and therapeutic potential. Liquid chroma-

Received: May 31, 2022. Accepted: August 19, 2022.
Epub September 22, 2022.

tography tandem mass spectrometry (LC-MS/MS), particu-

DOI: 10.24508/mms.2022.11.003
112

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Fig. 1.

Medical Mass Spectrometry Lipidomics Vol. 6 No. 2

Saturation metabolism pathway of C18 fatty acid. A. Linoleic acid (LA)-derived metabolites B. α -linolenic acid
(ALA)-derived metabolites C. γ-linolenic acid (GLA)-derived metabolites.

113

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Table 1.

MedicalIssue Lipidomics
MedicalMass
MassSpectrometry
SpectrometrySpecial
Lipidomics
Vol. 6 No. 2

Classiﬁcation and formal name of the C18 fatty acid metabolites quantiﬁed using LC-MS/MS

Group

Compound

LA

LA
HYA
HYB
HYC
HYD
HYE
KetoA
KetoB
KetoC
KetoD
CLA1
CLA2
CLA3
OA

ALA

10-hydroxy-octadecanoic acid
10-hydroxy-trans-11-octadecenoic acid
13-hydroxy-cis-9-octadecenoic acid
10,13-dihydroxy-octadecanoic acid10-oxo-cis-12-octadecenoic acid10-oxo-octadecanoic acid10-oxo-trans-11-octadecenoic acid13-oxo-cis-9-octadecenoic acidcis-9,trans-11-octadecadienoic acidtrans-9,trans-11-octadecadienoic acidtrans-10,cis-12-octadecadienoic acidcis-9-octadecenoic acidtrans-10-octadecenoic acidALA

cis-9,cis-12,cis-15-octadecatrienoic acid
10-hydroxy-cis-12,cis-15-octadecadienoic acid

αHYB
αHYC
αHYD
αHYE
αKetoA
αKetoB
αKetoCαKetoD
CALA1
CALA2
CALA3
c9c15

10-hydroxy-cis-15-octadecenoic acid
10-hydroxy-trans-11,cis-15-octadecadienoic acid
13-hydroxy-cis-9,cis-15-octadecadienoic acid
10,13-dihydroxy-cis-15-octadecenoic acid10-oxo-cis-12,cis-15-octadecadienoic acid10-oxo-cis-15-octadecenoic acid10-oxo-trans-11,cis-15-octadecadienoic acid13-oxo-cis-9,cis-15-octadecadienoic acidcis-9,trans-11,cis-15-octadecatrienoic acidtrans-9,trans-11,cis-15-octadecatrienoic acidtrans-10,cis-12,cis-15-octadecatrienoic acidcis-9,cis-15-octadecadienoic acidt10c15trans-10,cis-15-octadecadienoic acidGLA

cis-6,cis-9,cis-12-octadecatrienoic acid
10-hydroxy-cis-6,cis-12-octadecadienoic acid

γHYA
γHYB
γHYC
γHYD
γHYE
γKetoA
γKetoB
γKetoCγKetoD
CGLA1
CGLA2
CGLA3

10-hydroxy-cis-6-octadecenoic acid
10-hydroxy-cis-6,trans-11-octadecadienoic acid
13-hydroxy-cis-6,cis-9-octadecadienoic acid
10,13-dihydroxy-cis-6-octadecenoic acid10-oxo-cis-6,cis-12-octadecadienoic acid10-oxo-cis-6-octadecenoic acid10-oxo-cis-6,trans-11-octadecadienoic acid13-oxo-cis-6,cis-9-octadecadienoic acidcis-6,cis-9,trans-11-octadecatrienoic acidcis-6,trans-9,trans-11-octadecatrienoic acidcis-6,trans-10,cis-12-octadecatrienoic acidc6t10

cis-6,cis-9-octadecadienoic acidcis-6,trans-10-octadecadienoic acid

EPA-d5
15(S)-HETE-d8

cis-5,cis-8,cis-11,cis-14,cis-17-eicosapentaenoic-19,19,20,20,20-d5 acid
15S-hydroxy-cis-5,cis-8,cis-11,trans-13-eicosatetraenoic-5,6,8,9,11,12,14,15-d8 acid

c6c9
IS

cis-9,cis-12-octadecadienoic acid
10-hydroxy-cis-12-octadecenoic acid

t10
αHYA

GLA

Formal name

LTB4-d4

5S,12R-dihydroxy-cis-6,trans-8,trans-10,cis-14-eicosatetraenoic-6,7,14,15-d4 acid114

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Medical Mass Spectrometry Lipidomics Vol. 6 No. 2

cis-9-octadecadienoic acid (c6c9), and cis-6,trans-10-octa-

larly triple quadrupole LC-MS/MS, is suitable for targeted
analysis to quantitatively measure the levels of lipid metab-

decadienoic acid (c6t10), were synthesized from OA, LA,
ALA, and GLA by lactic acid bacteria-derived enzymes

7‒9). We previously
demonstrated the targeted analysis of LA- and ALA-derived

olites, such as eicosanoids and bile acids(CLA-HY, CLA-DH, CLA-DC, CLA-ER and FA-HY1) and1,2)

chemical reactions and puriﬁed, as described previously

metabolites
including
HYA,
KetoA
and
3)
10-oxo-cis-12,cis-15-octadecadienoic acid (αKetoA) ;.

Organic solutions of fatty acid standards and internal

however in the present study, we expanded the number ofstandards (IS) used in this study (LA, OA, ALA, GLA,
leukotriene B4 (LTB4)-d4, 15S-hydroxyeicosatetraenoic acidmetabolites up to 45 by systemically preparing synthetic(15(S)-HETE)-d8 and eicosapentaenoic acid (EPA)-d5)

standards. Furthermore, we developed a comprehensive
analytical method including GLA-derived metabolites andwere obtained from Cayman Chemical (Michigan, USA).
LC-MS grade acetonitrile, acetic acid and methanol (allmetabolites with diﬀerent positional isomers (Table 1), andfrom Fujiﬁlm Wako Pure Chemical, Osaka, Japan) wereused for sample preparation and LC-MS/MS measurements.

applied it to biological samples, including mouse feces,plasma and tissues, under diﬀerent dietary conditions.

Ultrapure water was obtained using a Milli-Q water puriﬁ-

Material & Method

cation system (Merck, Darmstadt, Germany). Ampicillin,

Chemicalsvancomycin, neomycin, and metronidazole purchased from
Fujiﬁlm Wako Pure Chemical, were used to prepare antibi-

Synthetic standards, including HYA, 10-hydroxy-octadecanoic acid (HYB), 10-hydroxy-trans-11-octadecenoic acidotic-cocktail (AbX) solutions.

(HYC), KetoA, 10-oxo-octadecanoic acid (KetoB), 10-oxotrans-11-octadecenoic acid (KetoC), 13-hydroxy-cis-9-octa-

LC-MS/MSC18 fatty acid metabolites were quantiﬁed using a Nex-

decenoic acid (HYD), 13-oxo-cis-9-octadecenoic acid
(KetoD), 10,13-dihydroxy-octadecanoic acid (HYE), cis-9,trans-11-octadecadienoic acid (CLA1), trans-9,trans-11-oct-era X2 HPLC system (Shimadzu, Kyoto, Japan) coupledwith an LCMS-8060 triple quadrupole mass spectrometer

adecadienoic acid (CLA2), trans-10,cis-12-octadecadienoic
acid (CLA3), trans-10-octadecenoic acid (t10), 10-hydroxy-(Shimadzu). The best resolutions of chromatographic peaks
and separation of analytes were achieved using an Acquity
LC BEH C18 (1.0×150 mm, 1.7 μm, Waters, Milford, Mas-

cis-12,cis-15-octadecadienoic acid ( α HYA), 10-hydroxycis-15-octadecenoic acid ( α HYB), 10-hydroxy-trans-11,

sachusetts, USA) analytical column. The mobile phases

cis-15-octadecadienoic acid ( α HYC), αKetoA, 10-oxo-cis15-octadecenoic acid (αKetoB), 10-oxo-trans-11,cis-15-oct-consisted of 0.1% acetic acid in water (A) and acetonitrile/methanol (4:1, v/v) (B) and were delivered using the fol-adecadienoic acid (αKetoC), α HYD, 13-oxo-cis-9,cis-15octadecadienoic acid (αKetoD), 10,13-dihydroxy-cis-15-oc-

lowing gradient elution program: 27% B for 5.0 min,27‒70% B from 5.0 to 15.0 min, 70‒80% B from 15.0 to

tadecenoic acid ( α HYE), cis-9,trans-11,cis-15-octadecatrienoic acid (CALA1), trans-9,trans-11,cis-15-octadecatrien-

25.0 min, hold 80% B from 25.0 to 33.0 min, 80‒100% B

oic acid (CALA2), trans-10,cis-12,cis-15-octadecatrienoic
acid (CALA3), cis-9,cis-15-octadecadienoic acid (c9c15),

and hold 27% B for 5.0 min for column equilibration
with ﬂow rates of 50 μL/min (0‒30 min), 80μL/min (30‒trans-10,cis-15-octadecadienoic acid (t10c15), 10-hydroxycis-6,cis-12-octadecadienoic acid (γHYA), 10-hydroxy-cis-

33 min),100μL/min (33‒45 min), and 50μL/min (45‒50 min).
Data acquisition was carried out in multiple reaction moni-

6-octadecenoic acid (γHYB), 10-hydroxy-cis-6,trans-11-octadecadienoic acid (γHYC), 10-oxo-cis-6,cis-12-octadecadi-

toring (MRM) mode with negative electrospray ionizationfrom 33.0 to 35.0 min, hold 100% B from 35.0 to 45.0 min,for all C18 fatty acid metabolites and deuterated internal
standards. The ion transitions (Q1/Q3) selected for quantiﬁ-

enoic acid (γKetoA), 10-oxo-cis-6-octadecenoic acid(γKetoB), γKetoC, 13-hydroxy-cis-6,cis-9-octadecadienoic

cation and the collision energy (CE) are listed in Table 2.

13-oxo-cis-6,cis-9-octadecadienoic acid(γKetoD), 10,13-dihydroxy-cis-6-octadecenoic acid ( γ HYE),

acid(γHYD),The desolvation, interface, heatblock, desolvation line andsource temperatures were set at 526, 300, 400, 250 and
150°
C, respectively. MS detection was performed in nega-

cis-6,cis-9,trans-11-octadecatrienoic acid (CGLA1), cis-6,trans-9,trans-11-octadecatrienoic acid (CGLA2), cis-6,trans-10,cis-12-octadecatrienoic

acid(CGLA3),

tive ionization mode, and the source capillary voltage wascis-6,

set to 2 kV.
115

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SpectrometrySpecial
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Vol. 6 No. 2

Table 2.

Mass spectrometry parameters of C18 fatty acid metabolites

Group

Name

RT

Precursor ion

Product ion

CE

Q1 pre bias

Q3 pre bias

LA

LA
HYA
HYB
HYC
HYD
HYE
HYE (Reference)
KetoA
KetoB
KetoC
KetoD
CLA1
CLA2
CLA3
OA
t10

32.3
23.1
25.7
23.4
22.7
18.2
18.2
23.8
26.6
24.3
23.6
32.8
33.5
32.7
35.4
35.9

279.2
297.2
299.2
297.2
297.2
315.3
315.3
295.2
297.2
295.2
295.2
279.2
279.2
279.2
281.2
281.2

279.2
185.2
141.1
185.2
197.2
185.2
197.2
139.1
139.1
139.1
179.2
261.2
279.2
261.2
281.2
281.2

25
23
26
23
22
27
26
23
23
22
23
25
25
25
30
30

11
15
19
19
11
16
13
11
11
12
19
11
18
19
11
19

35
21
12
19
11
18
11
12
12
12
22
17
18
11
11
17

ALA

ALA
αHYA
αHYB
αHYC
αHYD
αHYE
αHYE (Reference)αKetoA
αKetoB
αKetoCαKetoD
CALA1
CALA2
CALA3
c9c15
t10c15

29.1
21.0
22.6
21.0
21.1
17.1
17.1
21.7
23.4
21.8
21.8
29.3
30.1
29.5
32.2
32.9

277.2
295.2
297.2
295.2
295.2
313.2
313.2
293.2
295.2
293.2
293.2
277.2
277.2
277.2
279.2
279.2

277.2
185.2
141.1
185.2
225.2
243.2
185.2
139.1
155.1
139.1
205.2
277.2
277.2
277.2
279.2
279.2

11
19
25
21
21
22
24
22
23
22
20
12
12
12
25
25

20
11
19
12
12
12
12
12
12
12
11
18
11
11
18
19

17
10
13
18
20
15
17
13
14
12
12
18
11
17
11
12

GLA

GLA
γHYA
γHYB
γHYC
γHYD
γHYE
γHYE (Reference)γKetoA
γKetoB
γKetoCγKetoD
CGLA1
CGLA2
CGLA3
c6c9
c6t10

29.6
21.9
24.2
22.1
21.3
17.7
17.7
22.6
24.8
22.8
21.9
30.1
31.0
29.8
33.0
33.4

277.2
295.2
297.1
295.2
295.2
313.2
313.2
293.2
295.2
293.2
293.2
277.2
277.2
277.2
279.2
279.2

277.2
183.2
155.1
183.2
195.2
155.2
195.2
137.1
155.1
137.1
195.1
277.2
277.2
277.2
261.2
279.2

12
21
23
30
19
25
25
23
22
22
22
12
12
11
25
25

11
20
11
20
11
12
12
19
11
11
11
11
11
11
11
11

17
19
13
17
19
14
20
13
14
12
11
11
18
17
18
18

IS

15-HETE-d8
LTB4-d4
EPA-d5

21.6
18.5
28.5

306.2
327.2
339.2

262.2
226.2
197.1

16
11
14

24
17
22

12
28
14

RT: retention time, CE: collision energy, Reference: parameters set as qualitative ions to aid in compound identiﬁcation.

116

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Medical Mass Spectrometry Lipidomics Vol. 6 No. 2

from 7 weeks of age. Mice were fed normal chow (CE-2;

Lipid extraction from biological samples(10‒100 mg)

10)excluding

CLEA, Tokyo, Japan) . Diets composed of chemicallyplasma were weighted and placed in a 3 mL reinforced
homogenization tube. A metal corn was placed in the tube

deﬁned materials with 4% each dietary oil (saﬄower oil[Saﬀ], linseed oil [Lin], evening primrose oil [Eve]) (Orien-and placed it in liquid nitrogen for 1 min. The samples weretal Yeast, Tokyo, Japan) were supplied for 1 month from 8

homogenized (2,500 rpm, 15 s ×2, pause time, 5 s) by amultiple bead shocker (Yasuikikai, Osaka, Japan). Homoge-

weeks of age . Five mice were used in each experimentalgroup. All animal experiments were approved by the Ani-

nized samples were added with methanol to 50 or 100 mg/

mal Care and Use Committee of Keio University.

Frozenbiologicalsamples11)

mL, and 20μL of plasma was added with methanol to
400μL before vortex. The metal cone was removed andData analysis

stored at −30°
C for at o/n. After centrifuging (2,500 rpm,

Data were analyzed using LabSolutions INSIGHT soft-

10 min, 4°C) the tube, sample were transfered 100μL of theware (Shimadzu, Kyoto, Japan). The chromatogram peaks

supernatant (300μL for plasma) to a 1.5 mL tube andscaled-up with methanol to 300μL. Then, 10μL of IS anderror of the mean (SEM).

were manually curated. Data are shown as mean±standard

an equal volume of water as in total methanol were added.

ResultThe solid phase extraction was performed using Monospin
AX-18 (GLScience, Tokyo, Japan). Methanol was added

Optimization of LC-MS/MS condition

300μL to the set column and centrifuged (2,500 rpm, 1 min,For each fatty acid metabolite, the fragment ion with suf-RT). The same process was carried out with water, and the
prepared sample solution was added and centrifuged (2,500

ﬁcient intensity and speciﬁcity was optimized from themultiple fragment ions generated by collision-induced dis-

rpm, 2 min, RT); washed with 300μL volume of water andsociation. The fragmentation patterns are shown in Fig. S1.

50% methanol, and 75 or 100μL volume eluted with eluent

The fragment ion at m/z 185.2, generated by cleavage near(acetic acid : methanol : water＝2 : 90 : 8).

the hydroxy group at position 10 in HYA, was selected as adiagnostic ion. Similarly, a fragment ion at m/z 139.1 was

Method validation

selected for KetoA, and those at m/z 185.2 and 197.2 wereselected as diagnostic ions for HYE. LA does not cause spe-

Quantiﬁcation curves were prepared from the standard
mixture at ten diﬀerent concentrations (0.03, 0.1, 0.3, 1, 3,
10, 30, 100, 300 and 1,000 ng/mL) using methanol as the

ciﬁc fragmentation, hence, the product ion was set to thesame parameters at m/z 279.2 as the precursor ion. The col-diluent. Accuracy and precision were investigated using

lision energy, Q1 pre bias, and Q3 pre bias for each com-quality control (QC) samples prepared from the standard

pound in the measurement were optimized (Table 2).

mixture at three concentrations of 2, 20, and 200 ng/mL:

LC conditions were implemented based on previous studies. Previous LC conditions used acetonitrile and 2-propa-

namely, low QC (LQC), medium QC (MQC), and high QC

nol as organic solvents in the mobile phase and were opti-(HQC). All QC samples were pretreated and analyzed, withthree replicates for each concentration. Accuracy was calcu-

3)

lated as the average percentage diﬀerence between the mea-

mized only for LA and ALA metabolites ; when GLA
metabolites and metabolites with a modiﬁed group at posi-

sured and real C18 fatty acid metabolite concentrations.

tion 13 were also measured, some compounds could not be

Precision was calculated as the relative standard deviation(RSD) of the measured C18 fatty acid metabolite concen-

separated by the previous method. Therefore, we developed
an optimized method by changing the mobile phase from
2-propanol to methanol to reduce the elution power and bytrations in three replicates of the QC samples.

improving the separation performance by further examiningMice

the gradient conditions.

Male wild-type C57BL/6 mice (CLEA Japan, Inc.,Tokyo, Japan) were maintained in a speciﬁc pathogen-free

The MRM chromatograms of the LA-, ALA- andGLA-derived metabolites are shown in Fig. 2A, S2A, andenvironment. Ampicillin (1 g/L), vancomycin (0.5 g/L),
neomycin (1 g/L), and metronidazole (1 g/L) were adminis-

B. In total, 31 of the 45 compounds displayed well-separated peaks. Most LA-derived metabolites showed a goodtrated in drinking water were administrated for 3 weeks

separation, but some metabolites with the same MRM
117

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Fig. 2.

MedicalIssue Lipidomics
MedicalMass
MassSpectrometry
SpectrometrySpecial
Lipidomics
Vol. 6 No. 2

Multiple reaction monitoring (MRM) chromatograms of C18 fatty acid metabolites. A. Chromatograms of all LA-derived metabolites. B. Chromatograms of C18 fatty acid metabolites detected with the same MS parameters.

(i) Q1‒Q3: 295.2‒139.1, (ii) Q1‒Q3: 293.2‒139.1, (iii) Q1‒Q3: 295.2‒185.2, (iv) Q1‒Q3: 295.2‒183.2, (v) Q1‒Q3: 277.2‒277.2,(vi) Q1‒Q3: 279.2‒279.2.

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Medical Mass Spectrometry Lipidomics Vol. 6 No. 2

parameters were not well separated (Fig. 2B). For example,
LA-derived KetoA, KetoC, ALA-derived αKetoB andis a good source of ALA, or Eve, which speciﬁcally con-

GLA-derived γKetoB were well-separated, whereas
ALA-derived αKetoA, αKetoC, GLA-derived γKetoA andfeces as well as in the small intestine (absorptive organs),

tains GLA. In addition, we measured metabolite proﬁles inblood (plasma) transporting lipids throughout the body, andkidney and liver (metabolic organs), to conﬁrm that metab-

γKetoC were not separated under the deﬁned LC conditions (Fig. 2B-i, ii). In addition, fatty acids with a hydroxy

olites produced by the gut bacteria could also be detected ingroup at position 10 and two double bond, such as α HYA,α HYC, γHYA and γ HYC were not separated (Fig. 2B-iii,

the body. The fatty acid composition of each diet group issummarized in Fig. 4A. Quantitative results of these metab-iv). There were eight compounds each of C18:2 and C18:3

olites are provided in Tables 4, S1, and S2, and are summarized as a heat map by Z-score (Fig. 4B). The lipidomic

fatty acids, with LA and c9c15, CLA1 and CLA3, CALA2
and CGLA1, and CALA3 and GLA being inseparable combinations (Fig-2B-v, vi).

proﬁle in feces reﬂected diﬀerent dietary conditions. In thefeces of Lin-fed mice, ALA-derived metabolites (αHYA,Quantiﬁcation performance and method validation

αHYC, αHYD, and α HYE) were predominant, whereasthat of Eve-fed mice contained enhanced levels of GLA-

lites was investigated using synthetic standards (Table 3).

KetoB, CGLA1, CGLA2, c6c9, c6t10, KetoA, KetoC,
CLA1, and CLA3). In contrast, LA-derived metabolites

The quantiﬁcation performance, including sensitivity, linearity, accuracy, and precision, of C18 fatty acid metabo-and LA-derived metabolites (γHYA, γHYB, γHYC, γ

These metabolites showed excellent calibration linearity
with good correlation coeﬃcients (r＞0.99) (Fig. S3). The

with a modiﬁed group at position 13 (HYD, HYE, KetoD)
were frequently detected in Saﬀ-fed mice feces. The lipid-

lower limit of detection was between 0.03 and 10 pg/μL foreach C18 fatty acid metabolite. Deuterium-labeled com-omic proﬁle in SI was similar to that in feces; however,LA-derived metabolites KetoA and KetoC, ALA-derived

pounds such as EPA-d5, 15-HETE-d8 and LTB4-d4 wereused as internal standards to calibrate the deviation intro-

metabolite α HYE, and other compounds present in feces

duced by sample pretreatment processes and instrument

KetoD, and dihydroxy fatty acids, were not detected in theplasma, liver, and kidney. The ALA-derived metabolites

were not detected in SI. Oxo fatty acids, except for KetoB,

ﬂuctuation. The accuracy and precision of the method were
investigated using QC samples of diﬀerent concentrations.
The accuracies of low-, medium-, and high- QC samples(e.g., αHYA, αHYC, and αHYD) and GLA-derived metab-

were between 80% and 118.7%, and the RSDs of precision

showed characteristic proﬁles, each dependent on diet. In
contrast, LA-derived metabolites showed diﬀerent proﬁles

olites (e.g., γHYA and γHYC) detected in these tissues

were less than 15% for all metabolites.

in each tissue and were largely unaﬀected by diet.

Quantiﬁcation of C18 fatty acid metabolites in fecesof antibiotics-treated mice

Discussion

LC-MS/MS-based targeted lipidomics was applied to the

In this study, comprehensive proﬁling and quantiﬁcationof fatty acid metabolites were performed using LC-MS/MS.

biological samples. HYA and related fatty acids including
LA-, ALA- and GLA-derived metabolites in mice feces

We prepared a series of synthetic standards to optimize thequantitative targeted analysis of these metabolites. The sep-

were successfully monitored (Fig. 3). By comparing thesewith the samples from antibiotics-treated mice, we could

aration performance was also improved by examining theilluminate a series of fatty acid metabolites, including HYA

mobile phase and gradient conditions.

and related metabolites uniquely produced by commensal

Several combinations of compounds that could not be

microbiota.

separated even with the method developed in this study,
and their quantitative analysis is an issue that needs to be

Proﬁling of fatty acid metabolites under diﬀerent dietary conditions

improved in the future. In addition to the new method

We also measured the levels of fatty acid metabolites indeveloped in this study, it is a possible that all compounds
can be quantiﬁed by combining this method with LC condi-

mice fed with diets containing Saﬀ, which is a good source

tions speciﬁc for the separation of target compounds orof the substrate LA and free of ALA and GLA, Lin, which

other analytical method, such as gas chromatography or
119

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Vol. 6 No. 2

Table 3.
Group
LA

ALA

GLA

Name

Linearity
2
(R )

LA

0.99

HYA

0.99

HYB

0.99

HYC

0.99

HYD

0.99

HYE

0.99

KetoA

0.99

KetoB

0.99

KetoC

0.99

KetoD

0.99

CLA1

0.99

CLA2

0.99

CLA3

0.99

OA

0.99

t10

0.99

ALA

0.99

αHYA

0.99

αHYB

0.99

αHYC

0.99

αHYD

0.99

αHYE

0.99

αKetoA

0.99

αKetoB

0.99

αKetoC

0.99

αKetoD

0.99

CALA1

0.99

CALA2

0.99

CALA3

0.99

c9c15

0.99

t10c15

0.99

GLA

0.99

γHYA

0.99

γHYB

0.99

γHYC

0.99

γHYD

0.99

γHYE

0.99

γKetoA

0.99

γKetoB

0.99

γKetoC

0.99

γKetoD

0.99

CGLA1

0.99

CGLA2

0.99

CGLA3

0.99

c6c9

0.99

c6t10

0.99

Quantiﬁcation performance in proﬁling of C18 fatty acid metabolites
Dynamic range(pg/μL)
1‒10000.1‒1000
1‒10000.3‒1000

1‒10001‒10001‒10001‒10001‒10001‒100030‒1000
1‒100030‒1000
10‒1000

3‒10001‒10000.3‒1000
1‒10000.3.‒1000

0.1‒1000
0.1‒1000

1‒10001‒10001‒10003‒10003‒10001‒10001‒10001‒10001‒10001‒10000.3‒1000
0.3‒1000
3‒10000.3‒1000

0.3‒1000
3‒10000.3‒1000
1‒10001‒10001‒10003‒10001‒100030‒1000
3‒1000Accuracy (%)

LOD(pg/μL)

LQC

Precision (%)

MQC

HQC

LQC

MQC

HQC

0.3

114.7

81.6

91.9

14.8

6.7

0.9

0.03

104.6

101.9

94.1

4.5

4.5

3.8

0.3

119.6

116.6

118.3

2.5

3.6

6.5

0.1

105.7

109.6

102.6

6.3

3.6

3.2

0.3

101.1

96.6

92.2

1.6

2.9

2.9

0.3

118.4

95.8

97.0

7.0

4.8

1.7

0.3

84.5

88.3

101.4

13.3

6.8

4.6

0.3

114.3

94.5

97.3

7.3

6.7

5.4

0.3

106.0

103.8

100.8

5.0

5.3

2.1

0.3

111.6

112.8

101.5

7.3

5.8

1.1

10

N.D.

119.8

117.9

―

8.2

4.8

0.3

95.8

80.1

80.8

15.5

3.9

5.2

10

N.D.

90.9

100.2

―

11.1

2.8

3

116.2

116.9

93.9

15.0

2.8

4.1

1

99.0

105.5

87.8

8.3

7.5

5.1

0.3

94.0

80.5

83.1

10.8

12.5

6.6

0.1

104.8

101.5

99.4

9.0

1.9

5.3

0.3

115.8

104.5

113.1

13.8

6.2

3.5

0.1

110.5

103.3

105.3

1.5

5.3

2.5

0.03

100.9

101.8

104.2

1.0

5.3

3.0

0.03

107.7

114.0

111.7

0.6

1.2

0.9

0.3

97.5

109.5

102.3

19.1

5.8

0.6

0.3

98.4

108.7

96.2

2.8

3.5

0.6

0.3

116.5

116.6

112.5

1.6

4.6

5.5

1

98.1

100.7

95.6

1.3

6.3

3.6

1

83.2

81.2

80.4

5.2

5.8

8.8

0.3

81.3

80.3

81.1

0.2

8.2

5.0

0.3

88.2

82.4

80.0

6.4

10.8

3.8

0.3

117.3

109.0

91.7

6.3

4.6

5.5

0.3

118.7

108.9

103.3

6.7

4.1

3.1

0.3

89.0

80.8

81.1

2.2

3.1

5.4

0.1

97.1

89.6

100.4

5.0

6.9

6.5

0.1

101.4

101.2

98.0

6.3

2.2

4.1

1

102.2

93.6

91.8

13.1

9.7

4.4

0.1

95.4

89.8

94.7

5.4

4.7

1.6

0.1

103.7

105.9

112.1

4.1

5.6

2.6

1

107.5

112.9

118.0

2.8

3.2

6.5

0.1

95.4

96.5

89.3

3.7

5.5

2.2

0.3

82.4

80.9

81.5

2.9

8.4

7.4

0.3

109.6

101.8

95.4

3.5

3.8

3.2

0.3

88.2

81.6

80.7

4.8

2.1

0.8

1

95.7

80.6

80.1

14.9

7.0

6.6

0.3

113.5

104.3

110.0

1.3

3.7

2.5

10

N.D.

88.7

83.5

―

2.1

3.0

1

90.4

85.3

81.1

2.0

7.4

6.5

LOD: limit of direction, LOC: low quality control, MQC: medium quality control, HQC: high quality control. The concentrations of the LQC,
MQC, and HQC samples were 5, 20, and 200 ng/mL, respectively. N.D.: not detected because concentrations were lower than the limit of detection.

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Fig. 3.

Medical Mass Spectrometry Lipidomics Vol. 6 No. 2

Detection and quantitative analyses of polyunsaturated fatty acid saturation metabolism intermediates in feces of
SPF or AbX-treated mice.

A. in LA-derived metabolism pathway. B. in ALA-derived metabolism pathway. C. in GLA-derived metabolism pathway. Data arepresented as means＋standard error of the mean (SEM) (n＝5).

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Fig. 4.

MedicalIssue Lipidomics
MedicalMass
MassSpectrometry
SpectrometrySpecial
Lipidomics
Vol. 6 No. 2

C18 fatty acid metabolite proﬁle in Lin-mice and Saﬀ-mice and Eve-mice. A.
Fatty acid composition of each oil. B. Heat map of C18 fatty acid metabolites. Heat map of C18 fatty acid metabolites detected in
the intestine following Z-score transformation of the raw data. Hierarchical clustering was performed on both animals and C18 fatty
acid metabolites. Red color indicates Z-scores＞0, blue color indicates Z-scores＜0, white color indicates Z-scores＝0. Gray color
indicates not detected (N.D.).

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Table 4.
Group
LA

ALA

Concentration of C18 fatty acid metabolites (ng/100 mg) in feces of Saﬀ-, Lin-, and Eve-miceCompoundLA [c9c15]

Saﬄower

Linseed

Evening primrose

1969.54±693.32

1530.46±685.34

6439.68±3376.55

HYA

12.57±5.27

9.01±1.92

18.14±13.58

HYB

231.06±58.45

517.2±139.04

180.04±105.93

HYC

3.35±4.74

N.D.

N.D.

HYD

126.27±59.11

20.54±11.49

38.71±30.05

HYE

17.21±8.02

3.27±1.77

3.43±1.44

KetoA

1.86±0.33

2.1±1.5

10.34±2.61

KetoB135.41±19.32

159.32±49.07

95.48±38.93

KetoC

6.22±4.37

6.47±8.88

12.45±2.81

KetoD

219.57±94.57

54.01±35.79

102.92±30.96

CLA1 [CLA3]

574.7±243.39

75.27±22.02

1875.56±1621.83

CLA2

52.95±28.05

16.38±11142.82±131.15

OA

5835.1±973.01

10302.02±3075.43

6769.36±637.15

t10

267.5±115.37

662.49±690.82

346.2±160.99

ALA

49.66±15.85

1451.39±709.8

99.31±24.57

0.2±0.07

4.55±1.74

0.67±0.47

αHYA [αHYC]
αHYB

11.6±6.58

6.83±2.7

0.57±0.72

αHYD

0.44±0.12

19.01±6.84

0.16±0.05

αHYE

N.D.

0.42±0.15

N.D.

αKetoA [αKetoC]

N.D.

N.D.

N.D.

αKetoB

N.D.

N.D.

N.D.

αKetoD

N.D.

N.D.

N.D.

CALA1

N.D.

N.D.

N.D.

29.33±11.68

30.25±14.18

1575.47±381.15

CALA2 [CGLA1]
CALA3 [GLA]

64.44±21.66

63.93±29.77

2554.45±689.82

1969.54±693.32

1530.46±685.34

6439.68±3376.55

N.D.

N.D.

N.D.

GLA [CALA3]

64.44±21.66

63.93±29.77

2554.45±689.82

γHYA [γHYC]

0.57±0.31

N.D.

9.05±1.64

γHYB

1.57±1.47

0.02±0.03

2.95±1.05

γHYD

N.D.

N.D.

N.D.

γKetoA

N.D.

N.D.

N.D.

γKetoB

N.D.

N.D.

0.43±0.21

γKetoC

N.D.

N.D.

N.D.

γKetoD

N.D.

N.D.

N.D.

γHYE

N.D.

N.D.

N.D.

29.33±11.68

30.25±14.18

1575.47±381.15

N.D.

N.D.

93.89±46.07

c9c15 [LA]t10c15
GLA

Feces

CGLA1 [CALA2]
CGLA2
CGLA3

N.D.

N.D.

N.D.

c6c9

80.84±37.26

32.68±18.1

249.85±114.51

c6t10

90.82±41.83

50.08±28286.09±46.37

Data are expressed as the mean±SE, n＝5. N.D.: not detected because concentrations were lower than the limit of detection.
[ ]: not separated metabolite.

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Acknowledgements

supercritical ﬂuid chromatography, which have diﬀerent

We thank laboratory members of Division of Physiological Chemistry and Metabolism (Keio University) and Labo-

separation characteristics from LC. The developed method
was applied to mouse feces, where we successfully

ratory for Metabolomics (RIKEN) for stimulating discus-

detected a series of HYA and related fatty acid metabolites
produced by the gut microbiota. The estimated concentra-

sions and comments on this work.

tion of HYA and KetoA in mouse feces was 0.4 and 0.06μM,

Conﬂict of Interest

respectively. As these metabolites are bioactive in the3‒6,12‒14), the established method using
micromolar range
LC MS/MS appears to be sensitive enough to monitor

Kowa Tsuji is an employee of Noster Inc. and is engaged
in metabolome analysis services.

endogenous levels of HYA and related fatty acid metaboReference

lites in biological systems.
Additionally, we applied this method to mouse tissues

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125