Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2020 Jan 1.
Published in final edited form as: Anal Bioanal Chem. 2018 Nov 8;411(2):367–385. doi: 10.1007/s00216-018-1446-3

Comprehensive analysis of oxylipins in human plasma using reversed-phase liquid chromatography-triple quadrupole mass spectrometry with heatmap-assisted selection of transitions

Guan-yuan Chen 1, Qibin Zhang 1,2,*
PMCID: PMC6457987  NIHMSID: NIHMS1003512  PMID: 30406832

Abstract

Oxylipins, a subclass of lipid mediators, are metabolites of various polyunsaturated fatty acids with crucial functions in regulation of systemic inflammation. Elucidation of their roles in pathological conditions requires accurate quantification of their levels in biological samples. We refined an ultra-performance liquid chromatography-multiple reaction monitoring-mass spectrometry (UPLC-MRM-MS)-based workflow for comprehensive and specific quantification of 131 endogenous oxylipins in human plasma, in which we optimized LC mobile phase additives, column and gradient conditions. We employed heatmap-assisted strategy to identify unique transitions to improve the assay selectivity and optimized solid phase extraction procedures to achieve better analyte recovery. The method was validated according to FDA guidelines. Overall, 94.4% and 95.7% of analytes at tested concentrations were within acceptable accuracy (80–120%) and precision (CV<15%), respectively. Good linearity for most analytes was obtained with R2 > 0.99. The method was also validated using a standard reference material – SRM 1950 frozen human plasma to demonstrate inter-lab compatibility.

Keywords: oxylipins, lipid mediators, LC-MRM-MS, heatmap, human plasma, SRM 1950

Introduction

Oxylipins, a subclass of lipid mediators [1], are originated from various polyunsaturated fatty acid (PUFA) precursors such as arachidonic acid (C20:4 n-6, AA), eicosapentaenoic acid (C20:5 n-3, EPA) and docosahexaenoic acid (C22:6 n-3, DHA), which are released by phospholipase A2 [2] from the membrane phospholipids and further metabolized by cyclooxygenase (COX), lipoxygenase (LOX) and cytochrome P450 (CYP) as well as some non-enzymatic pathways [3]. As a result, hundreds of these mediators are released into circulation and involved in various physiological conditions [4] and pathogenesis, such as inflammation [3], vascular diseases [5–8], metabolic syndrome [9,1,10,11], neurological diseases [12–14] and cancers [15,16]. Elucidation of their roles in enhancing and resolving inflammation and disease progression requires an accurate quantification of their levels in human plasma and other biofluids.

Among the methods for analyzing oxylipins, LC coupled to triple quadrupole mass spectrometry (QqQ-MS) has gained popularity in recently years because of its selectivity and sensitivity. Recent developments of UPLC technology with sub-2μm columns have greatly improved chromatographic separation of eicosanoids and reduced analytical run time from 20~60 min [17–20] to 4–12 min [21,22], which in turn significantly increased the analytical throughput. When coupled with scheduled multiple reaction monitoring (MRM) MS, the number of oxylipins monitored within one single LC run can reach more than 180 [21]. Given these advancements, comprehensive analysis of oxylipins still remains a challenge because of the low concentration (<nM) in the real samples, wide dynamic ranges within sample and prevalence of structurally similar isomeric species [23], an example for the latter is that there are at least 14 HETEs (C20H32O3), 4 EETs (C20H32O3) and 10 hydroxydocosahexaenoic acids (HDoHEs, C22H32O3) isomers reported in LIPID MAPS database.

Differentiation of isomeric lipids mainly relies on LC separation and specific MRM transitions. LC retention time resolves some of these isomers, but oftentimes the close structural similarity makes it incapable of separating all isomeric oxylipins even with the most recent advances in UPLC separation [21]. When chromatographic separation power is limited, specificity of selected MRM transitions is critical to differentiate co-eluting isomeric lipid mediators. Wang et al. used a 5-min LC gradient to separate 184 oxylipin metabolites, including 11 HETEs and 10 HDoHEs with average retention time differences (ΔRT, RTn-RTn-1) of 0.059 and 0.046 min, respectively [21]. Slight RT differences are not sufficient to selectively identify these isomers, in this case some species can be considered as co-eluents, and if the MRM transitions are not unique, then the level of each isomer cannot be accurately determined. Therefore, it is critical to find the unique fragment ions as the surrogate of the particular oxylipin isomer. Considering the structural similarity between the isomers and the subsequent overlap of fragment ions, a strategy to identify selective MRM transitions for each isomer would facilitate their accurate quantification.

Another factor that affects the absolute quantification of oxylipins is extraction. Two major methods for sample clean-up, liquid-liquid extraction (LLE) and solid phase extraction (SPE) are widely used for analyzing these mediators. The LLE shows good recoveries for EETs, HETEs and PGs; however, it exhibited lower recoveries for hydrophilic analytes such as tetranor-PGEM and leukotrienes (LTs) [20]. Various SPE materials and protocols are employed and it is inconclusive which material and protocol is the best for extracting oxylipins from biological matrices [24].

Herein, we report a refined workflow for UPLC-MRM-MS based quantification of 131 endogenous oxylipins with 25 deuterium-labeled stable isotope standards, which incorporates optimized sample preparation and chromatographic separation conditions, and more importantly, utilization of specific MRM transitions for unambiguous identification and accurate quantification of isomeric eicosanoids. The method was validated according to the FDA guidelines and further validated using a standard reference material human plasma, which has been used in the past for interlaboratory comparisons of lipidomics analysis between different analytical platforms [25,26].

Materials and methods

Chemicals and reagents

All lipid mediator and deuterated internal standards were purchased from Cayman Chemical (Ann Arbor, MI). LC-MS grade acetonitrile (ACN), methanol (MeOH), water (H2O) and formic acid (FA) were obtained from Fisher Scientific (Waltham, MA). The pooled plasma from healthy subjects and the standard reference material - metabolites in frozen human plasma (SRM 1950) were purchased from Bioreclamation IVT (Baltimore, MD) and NIST (Gaithersburg, MA), respectively.

Standards and sample preparation

All of the analytical standards were prepared in the concentration of 1000 μg/ml as stock solution. The actual concentration of each species in the standard mixture (Master Mix) was adjusted according to test trial after taking consideration of previously reported analytical ranges. The deuterated internal standard mixture (Master ISTD) was prepared at concentration 10 times of its non-deuterated analogs. They are stored at −20ºC freezer until use.

Aliquots of 200 μl human plasma were mixed with 5 μl Master ISDT before loading onto 96-well SPE cartridges (30 mg, HLB, Waters, Milford, MA), which had been pre-conditioned with 1 ml MeOH and followed by 1 ml water. A 1.5 ml 5% MeOH was used to wash out the unbounded interferents. Elution was carried out by 1.2 ml of MeOH. The eluents were dried under stream nitrogen and reconstituted with 50 μl of 50% MeOH. SPE recoveries were used to assess the extraction efficiency by comparing pre-spike and post-spike of deuterium-labeled standards.

Optimization of selective ion monitoring transitions

All the analytical standards were diluted in MeOH at the final concentration of 10 μg/ml for direct infusion. Surrogate transitions for oxylipins were optimized by using TSQ Quantiva Tune 2.1 (Thermo Fisher Scientific, Haverhill, MA) via direct infusion of individual standard solution with a syringe pump at flow rate of 10 μl/min. Top 6 fragment ions were selected to optimize the collision energy. The following parameters were set for the mass spectrometer: 10 Arb, 2 Arb, 0 Arb, 275 oC and 250 oC for sheath gas, aux gas, sweep gas, ion transfer tube and vaporizer temperature, respectively. The ion source was operated using heated ESI with ion spray voltage set at 2,500 V in negative ion mode. MS/MS spectra were exported from MS raw files for heatmap analysis.

LC-MS analysis

A Vanquish UHPLC coupled with a Quantiva triple quadrupole mass spectrometer (Thermo Fisher Scientific, Haverhill, MA) was used for LC-MS analysis. A HSS T3 column (100 × 2.1 mm, 1.8 μm, Waters, Milford, MA) with T3 VanGuard pre-column (5 × 2.1 mm, 1.8 μm, Waters) was employed for separation of analytes. The column was thermostated at 40°C. The mobile phase was composed of solvent A (0.1% FA in H2O) and solvent B (0.1% FA in ACN). Gradient elution was used for 12 min at a flow rate of 0.3 ml/min. The gradient conditions were as follows: 0–0.5 min, 30% B; 0.5–1.0 min, 40% B; 1.0–2.5 min, 40%B; 2.5–4.5 min, 70% B; 4.5 −6.5 min, 70%B; 6.5–9.0min, 95%B; 9.0–12.0min, 95%B. A 1.5 min equilibrium was used before the next injection. A 10 μl aliquot of each sample was injected onto column for analysis.

The following parameters were set for the mass spectrometer: 45 Arb, 13 Arb, 1 Arb, 350 oC and 350 oC for sheath gas, aux gas, sweep gas, ion transfer tube and vaporizer temperature, respectively. The ion source was operated using heated ESI with ion spray voltage set at 2,500 V in negative ion mode. Scheduled MRM was employed for analysis of all analytes and internal standards. The optimized SRM transitions and their respective collision energies were listed in Table 1.

Table 1.

List of LC retention time and MRM transitions for each of the oxylipins included in the assay.

Name Formula Type RT Precursor Product1 CE1 Product2 CE2
tetranor 12-HETE C16H26O3 Analyte 6.33 265 109 10 165 12
12-HHTrE C17H28O3 Analyte 6.41 279 179 11 217 10
9-HOTrE C18H30O3 Analyte 6.68 293 171 14
13-HOTrE C18H30O3 Analyte 6.78 293 195 12
13-HOTrE(y) C18H30O3 Analyte 6.86 293 113 19
13-oxoODE C18H30O3 Analyte 7.73 293 113 22 179 10
9-oxoODE C18H30O3 Analyte 7.93 293 185 18 197 21
12,13-EpOME C18H32O3 Analyte 6.15 295 195 15
9,10-EpOME C18H32O3 Analyte 6.23 295 171 15
13-HODE C18H32O3 Analyte 7.33 295 195 17
9-HODE C18H32O3 Analyte 7.34 295 171 16
(d4) 13-HODE C18H28D4O3 IS 7.29 299 198 17
(d4) 9-HODE C18H28D4O3 IS 7.3 299 172 18
Eicosapentaenoic acid C20H30O2 Analyte 9.76 301 257 10 203 13
Arachidonic acid C20H32O2 Analyte 10.21 303 259 13 205 15
(d8) Arachidonic acid C20H24D8O2 IS 10.21 311 267 10
12,13-diHOME C18H34O4 Analyte 6.15 313 183 19
9,10-diHOME C18H34O4 Analyte 6.23 313 171 27
15d PGA2 C20H28O3 Analyte 5.07 315 187 20
15d PGJ2 C20H28O3 Analyte 6.93 315 203 20
(d4) 12,13-diHOME C18H30D4O4 IS 6.15 317 185 21
(d4) 9,10-diHOME C18H30D4O4 IS 6.2 317 203 18
18-HEPE C20H30O3 Analyte 6.78 317 215 10 259 13
11-HEPE C20H30O3 Analyte 6.95 317 167 11 195 15
15-HEPE C20H30O3 Analyte 6.95 317 175 15 247 13
8-HEPE C20H30O3 Analyte 7.03 317 155 11
12-HEPE C20H30O3 Analyte 7.09 317 179 10
9-HEPE C20H30O3 Analyte 7.13 317 149 12
5-HEPE C20H30O3 Analyte 7.19 317 115 10
17(18)-EpETE C20H30O3 Analyte 7.68 317 215 10
15-oxoETE C20H30O3 Analyte 7.95 317 113 15 139 18
14(15)-EpETE C20H30O3 Analyte 7.95 317 207 12
12-oxoETE C20H30O3 Analyte 8.26 317 153 16
5-oxoETE C20H30O3 Analyte 8.82 317 203 17
(d4) 15d PGJ2 C20H24D4O3 IS 4.11 319 275 14
19-HETE C20H32O3 Analyte 6.89 319 231 10 177 15
20-HETE C20H32O3 Analyte 6.92 319 289 15
5,6-EET C20H32O3 Analyte 6.92 319 191 14
18-HETE C20H32O3 Analyte 7.12 319 261 18
17-HETE C20H32O3 Analyte 7.18 319 247 10
16-HETE C20H32O3 Analyte 7.19 319 233 12 189 11
15-HETE C20H32O3 Analyte 7.56 319 175 13 219 10
11-HETE C20H32O3 Analyte 7.7 319 167 16
8-HETE C20H32O3 Analyte 7.83 319 155 10
12-HETE C20H32O3 Analyte 7.88 319 135 13
9-HETE C20H32O3 Analyte 8 319 151 12 123 12
5-HETE C20H32O3 Analyte 8.11 319 115 15
14,15-EET C20H32O3 Analyte 8.7 319 219 10 175 12
11,12-EET C20H32O3 Analyte 8.94 319 208 10
8,9-EET C20H32O3 Analyte 9.03 319 155 12 151 10
15-HETrE C20H34O3 Analyte 8.06 321 221 16
8-HETrE C20H34O3 Analyte 8.21 321 157 16 163 18
5-HETrE C20H34O3 Analyte 9.12 321 115 13
15-oxoEDE C20H34O3 Analyte 9.21 321 223 22 195 20
(d7) 5-oxoETE C20H23D7O3 IS 8.78 323 279 11 130 15
2,3-dinor 8-iso PGF2a C18H30O5 Analyte 2.44 325 237 10
2,3-dinor 11b PGF2α C18H30O5 Analyte 2.62 325 145 15 163 10
(d6) 20-HETE C20H26D6O3 IS 6.91 325 307 15 281 17
10-Nitrooleate C18H33NO4 Analyte 9.74 326 181 15 279 14
9-Nitrooleate C18H33NO4 Analyte 9.75 326 195 27
tetranor-PGDM C16H24O7 Analyte 1.13 327 309 10
(d8) 15-HETE C20H24D8O3 IS 7.47 327 226 11 182 14
(d8) 12-HETE C20H24D8O3 IS 7.82 327 184 14 214 14
(d8) 5-HETE C20H24D8O3 IS 8.05 327 116 14 210 16
Docosahexaenoic acid C22H32O2 Analyte 10.07 327 283 15 229 15
(d11) 14,15-EET C20H21D11O3 IS 8.65 330 219 10 175 13
(d11) 11,12-EET C20H21D11O3 IS 8.9 330 179 11
(d11) 8,9-EET C20H21D11O3 IS 8.98 330 155 12 190 15
Adrenic acid C22H36O2 Analyte 4.7 331 287 14 233 15
PGA2 C20H30O4 Analyte 5.5 333 315 10 271 14
PGJ2 C20H30O4 Analyte 5.53 333 233 10
PGB2 C20H30O4 Analyte 5.68 333 175 15 235 15
bicyclo PGE2 C20H30O4 Analyte 5.85 333 235 20 204 20
15d PGD2 C20H30O4 Analyte 6.01 333 271 14 315 10
12oxo LTB4 C20H30O4 Analyte 6.25 333 179 15 153 15
20cooh AA C20H30O4 Analyte 6.56 333 289 16 297 18
8,15-diHETE C20H32O4 Analyte 5.81 335 155 15 127 15
5,15-diHETE C20H32O4 Analyte 5.9 335 173 14
LTB4 C20H32O4 Analyte 5.98 335 195 14 317 13
5,6-diHETE C20H32O4 Analyte 6.33 335 317 19 317 10
14,15-diHETrE C20H34O4 Analyte 6.38 337 207 15
11,12-diHETrE C20H34O4 Analyte 6.54 337 167 17 169 16
8,9-diHETrE C20H34O4 Analyte 6.68 337 127 19 185 15
5,6-diHETrE C20H34O4 Analyte 6.87 337 145 16 319 15
(d4) LTB4 C20H28D4O4 IS 5.96 339 321 14 153 16
2,3-dinor TXB2 C18H30O6 Analyte 2.49 341 167 10 141 14
2,3-dinor-6k PGF1a C18H30O6 Analyte 3.39 341 323 14 161 20
20-HDoHE C22H32O3 Analyte 7.38 343 241 10
16-HDoHE C22H32O3 Analyte 7.59 343 233 10 189 13
17 HDoHE C22H32O3 Analyte 7.59 343 245 10
19(20)-EpDPE C22H32O3 Analyte 7.59 343 241 10
10-HDoHE C22H32O3 Analyte 7.73 343 153 14 181 10
14-HDoHE C22H32O3 Analyte 7.73 343 205 10 234 10
11-HDoHE C22H32O3 Analyte 7.85 343 149 10 165 11
13-HDoHE C22H32O3 Analyte 7.87 343 193 10 221 10
7-HDoHE C22H32O3 Analyte 7.91 343 141 11 201 15
8-HDoHE C22H32O3 Analyte 7.99 343 189 10 109 13
4-HDoHE C22H32O3 Analyte 8.35 343 101 12
17k DPA C22H32O3 Analyte 8.51 343 247 16
16(17)-EpDPE C22H32O3 Analyte 8.79 343 233 10 201 10
Resolvin E1 C20H30O5 Analyte 2.77 349 161 16 195 15
PGE3 C20H30O5 Analyte 3.41 349 313 10
PGD3 C20H30O5 Analyte 3.7 349 233 10
LXA5 C20H30O5 Analyte 4.16 349 115 14 233 12
PGK2 C20H30O5 Analyte 4.19 349 249 14 287 16
15k PGE2 C20H30O5 Analyte 4.7 349 331 10 287 12
8-iso PGF3a C20H32O5 Analyte 2.79 351 307 17 245 18
20oh LTB4 C20H32O5 Analyte 2.84 351 195 16
PGF3α C20H32O5 Analyte 3.14 351 307 16
dhk PGE2 C20H32O5 Analyte 3.75 351 333 10
PGE2 C20H32O5 Analyte 4.15 351 271 14 315 10
11βPGE2 C20H32O5 Analyte 4.32 351 315 10 271 16
LXB4 C20H32O5 Analyte 4.39 351 221 14 163 16
PGD2 C20H32O5 Analyte 4.54 351 271 16 315 10
15R-LXA4 C20H32O5 Analyte 4.93 351 115 10 217 17
6S-LXA4 C20H32O5 Analyte 5.04 351 115 13 217 18
8-iso-15k PGF2b C20H32O5 Analyte 5.05 351 219 14
PGEM C20H32O5 Analyte 5.06 351 333 10 315 18
dhk PGD2 C20H32O5 Analyte 5.37 351 333 10 315 12
8-iso PGF2αIII C20H34O5 Analyte 3.23 353 309 19 291 20
11β PGF2α C20H34O5 Analyte 3.38 353 309 18 193 24
5-iso PGF2αVI C20H34O5 Analyte 3.53 353 115 18
PGF2α C20H34O5 Analyte 3.75 353 309 17 193 18
PGE1 C20H34O5 Analyte 4.32 353 317 10 273 19
PGD1 C20H34O5 Analyte 4.51 353 235 13
15k PGF1α C20H34O5 Analyte 4.55 353 193 25
dhk PGF2α C18H30O5 Analyte 4.78 353 195 15 113 22
PGFM C20H34O5 Analyte 4.97 353 183 24 223 20
PGF1α C20H36O5 Analyte 3.78 355 311 19 293 22
(d4) PGE2 C20H28D4O5 IS 4.11 355 275 16 319 10
dh PGF2α C20H36O5 Analyte 4.53 355 311 22 337 20
(d4) PGD2 C20H28D4O5 IS 4.58 355 319 10 275 16
(d4) dhk PGD2 C20H28D4O5 IS 5.38 355 337 10 319 11
(d4) 8-iso PGF2αVI C20H30D4O5 IS 3.23 357 197 24 295 20
(d4) PGF2α C20H30D4O5 IS 3.75 357 313 17
(d4) dhk PGF2α C20H30D4O5 IS 4.98 357 187 22 199 22
Protectin D1 C22H32O4 Analyte 5.92 359 153 15 206 15
7(R) Maresin-1 C22H32O4 Analyte 5.92 359 177 15 341 10
19,20-DiHDPA C22H34O4 Analyte 6.36 361 273 15 229 15
20cooh LTB4 C20H30O6 Analyte 2.72 365 347 16 169 20
20oh PGE2 C20H32O6 Analyte 1.5 367 331 10 349 10
d17 6k PGF1α C20H32O6 Analyte 2.14 367 163 24 243 22
6k PGE1 C20H32O6 Analyte 2.8 367 143 18
TXB3 C20H32O6 Analyte 2.81 367 169 14 195 11
11d-TXB2 C20H32O6 Analyte 4.28 367 305 14 161 17
20oh PGF2α C20H34O6 Analyte 1.37 369 325 19 193 26
6k PGF1α C20H34O6 Analyte 2.6 369 163 25 245 24
TXB2 C20H34O6 Analyte 3.27 369 169 15 195 12
6,15-dk-,dh-PGF1α C20H34O6 Analyte 3.32 369 267 20 223 20
TXB1 C20H36O6 Analyte 3.12 371 171 17 197 14
(d4) 6k PGF1α C20H30D4O6 IS 2.61 373 167 25 249 24
(d4) TXB2 C20H30D4O6 IS 3.27 373 173 15 199 12
Resolvin D1 C22H32O5 Analyte 4.98 375 141 13 215 17
dihomo PGE2 C22H36O5 Analyte 5.28 379 343 12 361 10
dihomo PGF2α C22H38O5 Analyte 5.05 381 337 20 319 21
LTE4 C23H37NO5S Analyte 5.2 438 333 17 351 14
11t LTE4 C23H37NO5S Analyte 5.33 438 333 16 351 14
(d5) LTE4 C23H32D5NO5S IS 5.2 443 338 17 356 15
14,15-LTD4 C25H40N2O6S Analyte 4.31 495 177 18 143 22
LTD4 C25H40N2O6S Analyte 5.01 495 177 18 143 23
11t LTD4 C25H40N2O6S Analyte 5.15 495 177 18 143 22
14,15-LTC4 C30H47N3O9S Analyte 4.28 624 272 21 254 23
LTC4 C30H47N3O9S Analyte 5.06 624 272 21 254 22
11t LTC4 C30H47N3O9S Analyte 5.2 624 272 21 254 22
(d5) LTC4 C30H42D5N3O9S IS 5.06 629 272 21 254 23
Open in a new tab

Method validation

The validation procedures per the FDA draft guidelines on validation of bioanalytical methods were appropriately followed in this study [27]. The assay linearity, lower limit of quantification (LLOQ), lower limit of detection (LLOD), precision and accuracy were measured accordingly.

A serial dilution from the original stock was prepared to make the calibration curve. A total of 12 times serial dilution of highest point (Master Mix) with ISTD working solution was performed to construct the calibration curve and test the sensitivity. The LLOQ is generally defined as the lowest concentration of the standard curve that i) can be measured with acceptable accuracy (± 20%) and precision (< 20%) or ii) signal to noise ratio (S/N) is greater than 10. The LLOD is defined as an S/N ratio that is greater than 3.

The precisions and accuracies were evaluated with QC standards at low (LQC), middle (MQC) and high (HQC) concentrations covering analytical ranges. Precisions were expressed as percent coefficient of variance (CV%) and calculated as dividing standard deviations by the means. Accuracies were denoted as trueness and calculated as observed values divided by expected values.

Data analysis

For selection of unique MRM transitions, MS spectra obtained from direct infusion ESI of isomeric lipids were averaged and exported into Microsoft Excel and normalized to the base peak. The normalized spectra of fragment ions from each isomer were combined into a single data matrix with respective LC retention time (RT) of each isomer. RT sorting was performed using Excel, and heatmap analysis of the resulting data matrix were performed with R language (version 3.3.1) and pheatmap package (1.0.8), which is available from https://cran.r-project.org/web/packages/pheatmap/.

LC-MRM-MS datasets were processed with TraceFinder 4.1, and the auto-integrated peaks were inspected manually. The calibration curve of each analyte was constructed by normalizing to the selected ISTD followed by linear regression with 1/x weighting.

For comparing the measured concentrations of oxylipins in SRM1950 with values reported by other laboratories, measured values were converted to nmol/ml prior to importing into LipidQC software [28].

Result and discussion

Optimization of LC-MS condition

Mobile phase additives could affect ionization efficiency [29]. In order to obtain the optimal ionization efficiency, various mobile phase additives such as acetic acid (HOAc) [21,30], formic acid (FA) [31] and ammonium formate (AF) [20] were compared to see if enhancement of MS signals of standard mixtures can be observed, using the same mobile phases (50/50, ACN/H2O) by flow injection analysis (FIA) with 20 replicates. The pH of tested mobile phase with 0.1% FA, 0.1% HOAc, 10mM AF and 20mM AF were 2.81, 3.51, 6.21 and 6.45, respectively. As shown in Figure S1, after normalizing to that of 0.1% FA, 0.1% FA and 10mM AF exhibited higher average responses compared to 0.1% HOAc and 20mM AF, with 0.1% FA showing less variation in comparison to 10 mM AF. Therefore, 0.1% FA was chosen as our mobile phase additive.

Most lipid mediator-related studies employ C18-based columns to perform the separation; however, C30 column also showed great potential in separation of lipid molecular species [32,33] and could be used as an alternative for analyzing oxylipins. We compared the chromatographic performances of core-shell C30 and HSS T3 C18 column. Overall, both columns were comparable in terms of elution order, peak shape and peak capacity for separation of these mediators, C18 column provided higher efficient separation with less retention for hydrophobic analytes and more retention for hydrophilic analytes. As a result, HSS T3 column was chosen as our analytical column.

To obtain better peak resolution, we further optimized the LC gradient. A linear gradient (0–10 min, 30–95%B) was used which resulted in two crowded chromatographic regions, 2–4 min and 5–7 min, as shown in Figure S2A. Slight adjustment of gradients can reduce the density of peaks to spread the peaks more evenly across the retention time window (Figure S2B-D). Finally, applying a four-stage gradient successfully separated all analytes with the least co-eluted species. The TIC overlay of all the mediators at HQC standard concentration using optimized LC gradient is shown in Figure 1. The obtained retention times were used to construct the scheduled MRM method as listed in Table 1.

Figure 1.

Figure 1.

Open in a new tab

Overlaid total ion chromatograms obtained from scheduled LC-MRM-MS analysis of analytes at HQC. All MRM transitions of all analytes listed in Table 1 were included.

Necessity of selecting unique transitions

Although some isomers can be easily resolved by the reversed phase LC, certain isomers share similar physicochemical properties and form poorly resolved critical pairs [34] in terms of chromatographic separation. Selectivity of MRM transitions is crucial to distinguish these co-eluents. We focused on the selectivity of these critical pairs and employed different MRM transitions reported by others to examine the selectivity. Two critical pairs derived from AA, including HETEs (19-HETE and 20-HETE) and EETs (11,12-EET and 8,9-EET) were chosen to demonstrate the importance of selecting appropriate transitions (Figure 2).

Figure 2.

Figure 2.

Open in a new tab

Issues of inappropriate ion transitions on distinction of isomeric lipids. Extracted ion chromatograms from LC-MRM-MS analysis of 19-HETE and 20-HETE (A), 11,12-EET and 8,9-EET (B) monitored at different transitions.

Shinde et al. used transition 319 301 ([M-H-H2O]-) as a surrogate of 20-HETE [20]. However, the water-loss fragment is not unique among all HETE species. If the LC separation power was sufficient to separate isomers, non-unique fragment ions would not be a problem in terms of differentiating isomers. Unfortunately, even when we used a 12 min LC gradient, the 19-HETE cannot be fully resolved from 20-HETE. For this critical pair, we found fragments m/z 231 (black, Figure 2A) and m/z 245 (green, Figure 2A) employed by Wang et al. [21] were more selective to 19-HETE and 20-HETE, respectively, compared to the water-loss fragment, m/z 301 (red, Figure 2A), which was common in both HETEs. Even though fragment ion m/z 301 was more intensive than other fragments, poor selectivity prevented it from separating 19-HETE and 20-HETE in the mixture (bottom, Figure 2A). The EET pair displayed a slight difference in retention time (ΔRT=0.1) and the reported fragment ion m/z 167 [20] (red, Figure 2B) can be found in both 8,9-EET and 11,12-EET.

The poor selectivity issue is not limited to oxylipins derived from AA, those derived from DHA, such as 14-HDoHE and 10-HDoHE also exhibited identical retention on LC. The fragment ion m/z 161 has been used as specific transition for 14-HDoHE in a previous study [31]; however, we noticed it can be generated by 10-HDoHE as well. Besides, previous study employed fragment ion m/z 281([M-H-H2O-CO2]-) to represent 17-HDoHE [30], yet, this water and CO2 loss is common for all HDoHEs. Given this, good quantitation of 17-HDoHE would not be possible if there was not enough LC resolving power.

Collectively, these evidences demonstrate that some common fragment ions cannot provide enough selectivity to differentiate isomeric lipid mediators. For an unbiased quantification, therefore, it is necessary to take into consideration the fragmentation spectra of neighboring eluting isomers when selecting appropriate MRM transitions.

Strategy for selecting unique transitions

Our strategy to select unique transitions for isomers is illustrated in Figure 3. We averaged the spectra collected under various collision energies during direct infusion-based optimization of collisional energies. The obtained spectra were then normalized to the base peak of the spectrum and imported to a data matrix. The resulting matrix was then sorted by the chromatographic retention times of each isomer, which was obtained by running each isomeric compound individually using LC-MS. On the basis of the chromatographic resolution and peak width, we can define the minimum difference of retention time (ΔRT). Within an acceptable ΔRT, for example, of 0.15 min, the critical pairs were grouped together. A heatmap was then generated and employed to find out the unique fragment ions to the isomer among a large array of ions. If the isomers were separated very well (ΔRT >>0.15) and there was no co-elution, the same fragment ions can still be used for identification of each isomer.

Figure 3.

Figure 3.

Open in a new tab

Workflow depicting the strategy to select optimal MRM transitions for each isomer.

We took 15 HETEs/EETs (C20H32O3) as an example to demonstrate the process of selecting optimal MRM transitions for series of oxylipin isomers. The average product ion spectra from the same precursor ion (m/z 319) of each of the 15 HETEs/EETs were obtained in the negative ion mode and normalized to the base peak. The isomers were sorted based on their respective LC retention time in ascending order and denoted as “RT1, RT2…..RT14, RT15”. Even after we optimized the LC gradient to obtain the maximum peak capacity in LC separation, there were still a large number of analytes with ΔRT <0.15 min and therefore co-eluted. Figure 4A showed the heatmap of those normalized spectra. The ΔRT of isomers less than 0.15 min were grouped together with the same color. Among all the isomers studied, 5 critical pairs were found and m/z 301 ([M-H-H2O]-), m/z 275 ([M-H-CO2]-) and m/z 257 ([M-H-H2O-CO2]-) were the common fragment ions. These common product ions were not suitable to be selected as specific MRM transitions for these critical pairs even though they usually were the most abundant among fragment ions. Consequently, we excluded these common ions and looked for unique fragments to each isomer within each critical pair. For example, 16-HETE, 17-HETE and 18-HETE did not resolve well with a ΔRT of 0.07 min. Yet, through the heatmap analysis, we could easily identify m/z 233 (break between C-15 and C-16), m/z 247 (break between C-16 and C-17) and m/z 261 (break between C-17 and C-18) as unique fragment ion for 16-HETE, 17-HETE and 18 HETE, respectively (Figure 4B). Alternatively, Willenberg et al. mentioned product ion spectra of 9-HETE and 12-HETE were similar and these two compounds must be separated chromatographically for their identification [23]. Yet, we were able to identify unique fragment m/z 135 (beak at C11–12 and loss of CO2) [35] and m/z 151 for 12-HETE and 9-HETE, respectively, from the heatmap. The optimal transitions and the retention times for each of the 15 HETEs/EETs were listed in Table 1. Similar strategy was applied to other isomeric species of lipid mediators. The most dominant fragment ion for three chromatographically unresolved HDoHEs (11-HDoHE, 10-HDoHE and 14-HDoHE) is m/z 281 ([M-H-H2O-CO2]-). Sharing with other HDoHEs suggested it was not suitable as MRM transitions for the differentiation of HDoHEs. However, the unique fragment ions m/z 149, m/z 153 and m/z 205 for 11-HDoHE, 10-HDoHE and 14-HDoHE, respectively, can be easily identified by visually inspecting the heatmap. Once the fragment ions representing each isomer were chosen, we optimized the corresponding collision energies for each isomer and implemented those values in the following scheduled LC-MRM-MS analysis.

Figure 4.

Figure 4.

Open in a new tab

Identification of unique fragment ions within chromatographically challenged critical pairs. (A) Heatmap analysis of normalized fragment ion spectra of HETEs/EETs isomers, and (B) structure and annotation of common (m/z 301) and unique fragment ions of 16-HETE, 17-HETE and 18-HETE.

Accuracies of selected MRM transitions in quantification of isomeric critical pairs

To demonstrate the accuracies of selected transitions for analysis of critical pairs, we spiked three critical pairs at various ratios in both neat standard solution and human plasma. Physiologically, the concentrations between critical pairs might vary up to 10-fold [30]. Therefore, the ratios used in the accuracy test were 1:1 (20/20 ng, R1), 1:10 (20/200 ng, R2) and 10:1 (200/20 ng, R3). Figure 5 displayed the chromatograms for the critical pair 20-HETE/19-HETE at various ratios. We noticed that the peak areas of critical pairs were not equal at the ratio of 1:1 since they have different sensitivity. Herein, the accuracies were determined by comparing the peak area ratios at R1/R2 and R3/R1 between theoretical values (TV=10) and observed values. Table 2 listed the accuracies for the tested pairs of HETEs. The values for the tested pairs in neat solution and human plasma ranged from 90.0% to 118.0% suggested the transitions selected using the proposed strategy were reliable and accurate. By using this strategy, MRM transitions for 140 analytes and 25 ISTD were optimized and listed in Table 1.

Figure 5.

Figure 5.

Open in a new tab

LC-MRM-MS Chromatograms for 19-HETE and 20-HETE at three different ratios in neat solution. Ratio of 19-HETE/20-HETE: A, 1:1; B, 10:1; C, 1:10.

Table 2.

Accuracies (%) for selected MRM transitions in critical pairs analysis.

Critical pairs
ratio		 Pair 1 Pair 2 Pair 3
8-HETE/
12-HETE		 20-HETE/
19-HETE		 17-HETE/
16-HETE
R1/R2 (S) 90.1 98.3 90.0
R3/R1 (S) 95.2 103.0 105.0
R1/R2 (P) 118.0 98.7 97.0
R3/R1 (P) 116.0 110.0 97.2
Open in a new tab

S: standards in neat solution; P: standards spiked in human plasma.

Amount of spike-in: R1, 20/20 ng; R2, 200/20 ng; R3, 20/200 ng

Optimization of sample preparation procedures for better analyte recovery

Previous studies employed various strategies to clean up samples. One of the most used approaches was solid phase extraction (SPE). We briefly compared different SPE cartridges on the recoveries of spiked ISTD in plasma. As shown in Figure S3A, Waters HLB provided higher recoveries compared to Biotage isolute C18. In addition, we examined factors that might affect recoveries such as solvents used for elution and temperature for sample drying. We found high temperature (40 oC) might decompose the cysteinyl leukotrienes(i.e. LTC4 and LTE4) in the drying process as shown in Figure S3B which is consistent with previous work [36]. Although ethyl acetate (EA) had been used as eluting solvent in previous reports [17,30], we noticed that EA caused poor responses of cysteinyl leukotrienes as well which might be due to decomposition of the thiol group. Although others have demonstrated that using EA as eluting solvent can provide better recoveries for deuterium-labeled mediators than MeOH with the same SPE cartridge [26], they did not consider cysteinyl leukotrienes. Given that EA could cause breakdown of cysteinyl leukotrienes, we chose MeOH as eluting solvent. The effect of eluting volume was also examined and there were no significant changes from 1000 to 2000 μl of eluent (Figure S3C). In the end, we selected Waters HLB column to perform sample cleanup and oxylipins were eluted with 1200 μl MeOH following dryness at room temperature. The SPE recoveries were calculated as peak area of pre-spiked ISTD divided by peak area of post-spiked ISTD. Figure 6 displayed the overall recoveries of SPE under optimized sample preparation conditions. 70% of ISTD were within 80–120% whilst 7 species were at 65–80%, which was comparable to previous studies [30,26,21].

Figure 6.

Figure 6.

Open in a new tab

SPE recoveries assessed by ISTDs on Waters HLC column, calculated as peak area of pre-spiked divided by that of post-spiked (mean +/− RSD, n=3). ISTDs-spiked BR human plasma samples were processed with SPE columns before eluting with 1200 μL MeOH and dried at room temperature and reconstituted for LC-MRM-MS analysis.

Method validation

The developed method was validated and the validation results including linearity, sensitivity, precision and accuracy are listed in Table 3. A total of 131 oxylipins were validated. 94.4% and 95.7% of analytes at tested concentrations were within acceptable accuracy (80–120%) and precision (CV<15%), respectively. The best-fit line of the calibration curve for each analyte was obtained by using a weighting factor of 1/x. Good linearity for most analytes was obtained with R2 > 0.99. LLOQs are listed in Table 3 as well. The sensitivities of the present method on detecting oxylipins are comparable to other studies [21].

Table 3.

Validation of LC-MRM-MS based oxylipin assay.

Analyte Regression Sensitivity a Accuracy (%) Precision (%)
Formula R2 LOD(pg) LOQ(pg) LQC MQC HQC LQC MQC HQC
10-HDoHE Y = −0.0109037+0.0272432*X 0.9974 2.44 4.88 86.44 101.49 99 2.44 5.15 2.36
10-Nitrooleate Y = −0.00703+0.00136237*X 0.9947 78.13 156.25 - 95.22 98.91 - 10.33 3.79
11,12-diHETrE Y = −0.009776+0.013691*X 0.9965 0.49 0.98 86.02 92.5 98.13 4.34 3.73 0.31
11,12-EET Y = −0.00816802+0.00600753*X 0.9953 9.77 19.53 98.96 90.08 102.24 15.55 7.62 4.71
11d-TXB2 Y = −0.0491238+0.0219417*X 0.9878 9.77 19.53 99.64 85.96 102.36 9.63 15.22 5.61
11-HDoHE Y = −0.0202172+0.0176525*X 0.9966 4.88 9.77 94.71 100.33 99.53 6.45 3.45 0.91
11-HEPE Y = −0.00235828+0.00203465*X 0.9936 3.91 7.81 131.61 99.04 98.37 3.85 12.65 4.46
11-HETE Y = −0.0108311+0.0132479*X 0.9972 0.98 1.95 106.5 99.54 100.03 8.14 4.22 1.36
11t LTC4 Y = 0.00217414+0.000563321*X 0.9924 3.91 7.81 - 95.45 110.27 - 8.4 3.42
11t LTD4 Y = 0.000139865+0.00209018*X 0.9957 0.98 1.95 126.91 97.24 103.19 10.08 7.62 6.17
11t LTE4 Y = 0.00529497+0.000698434*X 0.9921 15.63 31.25 - 93.17 106.29 - 8.84 2.93
11β PGF2α Y = −0.0204599+0.0155092*X 0.9938 0.98 1.95 117.85 93.67 105.42 3.63 10.83 3.22
12,13-diHOME Y = −0.000903627+0.0123171*X 0.9988 0.49 0.98 97.8 95.44 99.08 11.48 1.64 2.82
12-HEPE Y = −0.00801699+0.00382348*X 0.9982 1.95 3.91 102.31 96.19 99.88 4.11 6.34 1.65
12-HETE Y = 0.00575988+0.00219425*X 0.9939 1.95 3.91 90.97 110.35 97.74 12.14 2.81 2.89
12-HHTrE Y = −0.012523+0.00485223*X 0.9943 9.77 19.53 99.51 88.87 96.62 9.36 9.8 1.19
12oxo LTB4 Y = −0.0407613+0.00390706*X 0.9909 7.81 15.63 - 75.3 100.27 - 2.7 4.44
12-oxoETE Y = −0.00494085+0.00459273*X 0.9921 7.81 15.63 - 121.17 97.96 - 6.8 1.17
13-HDoHE Y = −0.00261673+0.00247811*X 0.9922 9.77 19.53 100.84 87.04 107.78 20.1 3.63 3.09
13-HODE Y = −0.00433048+0.00785322*X 0.9977 0.98 1.95 103.94 96.19 98.49 4.26 4.28 1.41
13-HOTrE Y = −0.011928+0.00375363*X 0.9972 3.91 7.81 95.48 98.32 99.28 10.83 10.65 1.65
13-HOTrE(y) Y = −0.0133511+0.00167496*X 0.9927 15.63 31.25 - 90.33 98.2 - 9.55 2.36
13-oxoODE Y = −0.00671703+0.00995266*X 0.9957 4.88 9.77 111.53 91.69 102.02 5.84 4.49 2.52
14(15)-EpETE Y = −0.0276261+0.0197225*X 0.9949 9.77 19.53 94.07 99.05 95.45 15.19 13.81 2.31
14,15-diHETrE Y = −0.0299797+0.0250185*X 0.9945 0.49 0.98 78.02 91.9 96.62 3.05 1.18 0.75
14,15-EET Y = −0.0520585+0.0288804*X 0.9976 9.77 19.53 115.74 95.26 95.55 5.92 4.59 1.43
14,15-LTD4 Y = −0.0165509+0.000486832*X 0.9914 15.63 31.25 - 107.83 100.53 - 7.26 5.58
14-HDoHE Y = −0.0175391+0.0140231*X 0.9958 4.88 9.77 91.17 94.73 99.77 20.82 6.26 1.45
15d PGD2 Y = −0.047299+0.0181792*X 0.9938 1.95 3.91 107.57 79.93 101.09 3.27 12.67 3.45
15d PGJ2 Y = −0.00518629+0.00906777*X 0.9983 0.98 1.95 96.63 106.97 97.31 2.92 2.96 2.43
15-HEPE Y = −0.00497533+0.0036944*X 0.9975 1.95 3.91 109.91 96.54 97.29 9.67 5.62 2.33
15-HETE Y = −0.00123146+0.00436834*X 0.9975 3.91 7.81 114.25 101.31 98.74 17.03 3.21 0.63
15-HETrE Y = −0.0592895+0.0293608*X 0.9962 1.95 3.91 102.65 98.38 96.1 6.9 5.02 0.99
15k PGE2 Y = 0.011296+0.0650588*X 0.9954 0.98 1.95 100.22 110.83 98.27 6.83 5.22 4.35
15k PGF1α Y = 0.0162384+0.0079837*X 0.9909 1.95 3.91 95.37 120.26 99.76 1.97 11 6.92
15-oxoEDE Y = −0.058245+0.119673*X 0.995 9.77 19.53 109.94 95.89 100.51 8.61 2.96 6.22
15-oxoETE Y = −0.0103203+0.00404482*X 0.9902 7.81 15.63 - 101.34 95.92 - 9.32 4.72
15R-LXA4 Y = 2.54549e-005+0.00445501*X 0.9968 2.44 4.88 98.26 101.97 100.04 13.5 2.34 3.22
16(17)-EpDPE Y = −0.0119976+0.0200056*X 0.996 19.53 39.06 79.81 96.46 100.9 3.72 2.75 3.54
16-HDoHE Y = −0.0301663+0.0483778*X 0.9979 2.44 4.88 90.02 95.71 98.84 5.23 2.55 1.64
16-HETE Y = −0.00439201+0.00738173*X 0.9969 1.95 3.91 110.91 91.78 98.73 2.9 6.66 1.7
17(18)-EpETE Y = −0.0069115+0.00400072*X 0.9964 9.77 19.53 105.5 92.45 98.49 10.91 2.76 4.89
17 HDoHE Y = −0.00371709+0.00633553*X 0.9955 9.77 19.53 105.91 97.53 96.04 4.91 7.15 0.56
17-HETE Y = −0.00216451+0.0057664*X 0.9967 0.98 1.95 114.01 90.05 98.42 2.21 5.87 1.22
17k DPA Y = −0.040765+0.00973775*X 0.9963 3.91 7.81 109.2 93.29 94.75 8.44 5.72 1.03
18-HEPE Y = −0.00558342+0.00344369*X 0.998 1.95 3.91 107.7 99.16 98.81 11.29 9.28 3.42
18-HETE Y = −0.00504199+0.00721175*X 0.9964 0.98 1.95 118.94 92.89 100.23 1.12 2.25 2.47
19(20)-EpDPE Y = −0.0198214+0.0200159*X 0.9973 2.44 4.88 84.55 96.84 97.84 3.97 3.3 1.23
19,20-DiHDPA Y = −0.154147+0.0170745*X 0.9913 1.95 3.91 - 84.73 95.98 3.67 1.31 2.8
19-HETE Y = −0.00308487+0.00206641*X 0.9963 3.91 7.81 112.94 82.43 98.58 11.8 2.84 1.54
2,3-dinor 11b PGF2α Y = −0.00573246+0.00446358*X 0.9961 3.91 7.81 116.02 93.04 105.17 8.38 2.07 2.54
2,3-dinor 8-iso PGF2a Y = −0.00681802+0.00386933*X 0.9968 1.95 3.91 117.36 97.01 103.24 1.54 2.43 7.23
2,3-dinor TXB2 Y = −0.0159749+0.00203039*X 0.9944 19.53 39.06 - 111.54 99.89 - 17.82 2.16
2,3-dinor-6k PGF1a Y = 0.4589+0.00829456*X 0.9802 39.06 78.13 - 112.19 108.8 - 14.26 6.11
20cooh AA Y = −0.0779621+0.0897709*X 0.9981 4.88 9.77 84.93 97.8 98.72 7.89 3.41 1.46
20cooh LTB4 Y = −0.0217471+0.00785531*X 0.9951 3.91 7.81 - 85.1 107.89 0.19 4.94 4.3
20-HDoHE Y = −0.0297813+0.0307731*X 0.9946 2.44 4.88 85.53 95.67 94.64 4.83 0.31 4.05
20-HETE Y = 0.0153093+0.00260037*X 0.9967 1.95 3.91 93.09 110.3 95.55 33.11 3.9 2.05
20oh LTB4 Y = −0.0259249+0.012246*X 0.9947 0.98 1.95 83.87 81.55 102.15 8.32 6.88 4.57
20oh PGE2 Y = 0.000253512+0.00896078*X 0.9964 1.95 3.91 - 89.54 99.64 10.44 3.57 3.23
20oh PGF2α Y = −0.0202579+0.0225324*X 0.9981 0.98 1.95 90.96 98.94 100.82 6.86 2.06 3.05
4-HDoHE Y = −0.0608019+0.0445828*X 0.9967 2.44 4.88 90.04 96.04 94.27 6.56 1.64 2.35
5,15-diHETE Y = −0.0868644+0.0407013*X 0.9931 3.91 7.81 112.95 88.45 97.47 7.47 2.12 1.3
5,6-diHETrE Y = −0.0138686+0.00851191*X 0.9974 0.98 1.95 88.74 97.17 98.73 5.2 1.21 1.34
5,6-EET Y = 0.00280349+0.000532731*X 0.9854 156.25 312.5 - 119.98 98.49 - 11.64 4.68
5-HEPE Y = 0.00140558+0.00294769*X 0.9957 0.98 1.95 106.41 95.11 98.73 10.74 2.98 4.8
5-HETE Y = −0.0376006+0.00756184*X 0.9962 3.91 7.81 - 102.15 96.9 - 8.32 1.83
5-HETrE Y = −0.0106957+0.0304337*X 0.9954 1.95 3.91 111.16 89.77 98.28 2.61 6.3 4.78
5-iso PGF2αVI Y = 0.000736148+0.00603093*X 0.9969 0.98 1.95 83.39 114.65 99.12 9.47 9.73 4.76
5-oxoETE Y = −0.0669815+0.0213273*X 0.9971 1.95 3.91 105.94 101.01 99.96 24.35 4.24 3.21
6,15-dk-,dh-PGF1α Y = 0.00134409+0.00533188*X 0.9966 1.95 3.91 92.21 111.79 98.56 21.14 7.28 0.9
6k PGE1 Y = −0.00561738+0.00486436*X 0.995 0.98 1.95 86.03 93.54 105.51 4.26 6.35 4.42
6S-LXA4 Y = 0.0106072+0.00345495*X 0.9914 19.53 39.06 - 109 92.95 - 7.63 4.19
7(R) Maresin-1 Y = −0.00996824+0.00777101*X 0.9945 1.95 3.91 84.51 78.9 98.63 5.57 2.68 5.6
7-HDoHE Y = −0.00925436+0.013752*X 0.9974 2.44 4.88 87.09 99.4 99.81 13.49 5.75 1.77
8,15-diHETE Y = 0.00898316+0.00250198*X 0.9886 7.81 15.63 - 85.19 110.95 15.18 2.16 5.1
8,9-diHETrE Y = −0.00808737+0.00410411*X 0.9969 0.98 1.95 94.08 96.58 98.96 1.38 0.58 0.92
8,9-EET Y = −0.0248726+0.00708235*X 0.997 19.53 39.06 107.54 105.75 106.53 3.76 1.95 2.39
8-HDoHE Y = −0.0256942+0.0235549*X 0.9969 4.88 9.77 105.07 97.32 94.51 2.94 2.97 1.71
8-HEPE Y = −0.00242834+0.00341065*X 0.9984 0.98 1.95 92.79 100.35 101.1 8.93 3.94 2.04
8-HETE Y = −0.173772+0.0356632*X 0.9937 7.81 15.63 126.15 84.92 98.15 6.67 3.83 6.87
8-HETrE Y = −0.0261272+0.00770905*X 0.9948 1.95 3.91 86.76 96.41 96.04 4.55 7.37 1.68
8-iso PGF2αIII Y = −0.0103351+0.0121181*X 0.9968 0.98 1.95 99.22 95.28 96.99 3.82 2.65 2.12
8-iso PGF3α Y = −0.0456402+0.00699653*X 0.9953 7.81 15.63 - 93.1 105.06 - 5.9 4.3
9,10-diHOME Y = −0.00765706+0.00337784*X 0.9899 1.95 3.91 108.51 80 97.01 1.37 2.88 2.43
9,10-EpOME Y = −0.00494373+0.000335517*X 0.9924 78.13 156.25 - 91.62 101.28 - 18.78 2.3
9-HEPE Y = −0.0230474+0.00424271*X 0.9961 7.81 15.63 130.38 95.03 99.88 3.59 20.2 2.57
9-HETE Y = −0.0176336+0.00714602*X 0.9973 1.95 3.91 104.79 96.23 100.36 2.84 4.67 1.21
9-HODE Y = 0.00844371+0.00729797*X 0.9952 0.98 1.95 113.38 94.89 94.96 10.68 6.18 4.2
9-HOTrE Y = −0.000376633+0.00659175*X 0.9981 0.98 0.98 99.72 92.79 100.46 5.31 7.77 0.88
9-Nitrooleate Y = 0.017519+0.0757139*X 0.9988 4.88 4.88 104.89 107.14 102.21 10 2.07 1.99
9-oxoODE Y = −0.0169786+0.0239847*X 0.996 9.77 19.53 97.05 98.28 95.82 2.94 8.59 3.87
Adrenic acid Y = −0.394973+0.0223128*X 0.9953 1562.5 3125 - 108.49 96.09 - 4.82 4.14
Arachidonic acid Y = −0.00556938+0.0146891*X 0.9981 97.66 195.31 102.61 95.07 100.05 5.01 1.9 0.49
bicyclo PGE2 Y = −0.00289952+0.000906674*X 0.9908 7.81 15.63 - 117.2 96.1 5.76 10.17 2.62
d17 6k PGF1α Y = −0.00882442+0.0146*X 0.9976 0.49 0.49 108.3 96.21 99.28 6.68 2.27 4.56
dh PGF2α Y = −0.00208584+0.00850272*X 0.9957 1.95 3.91 90.34 101.07 96.52 8.02 3.04 4
Docosahexaenoic acid Y = −0.0852456+0.163768*X 0.9982 48.83 48.83 98.36 108.66 103.38 5.48 2.49 1.73
dhk PGD2 Y = −0.00243871+0.00447801*X 0.9934 1.95 3.91 107.96 85.64 101.43 5.39 4.59 2.72
dhk PGE2 Y = −0.00490411+0.00440119*X 0.9966 1.95 3.91 101.26 96.04 95.1 3.38 8.42 3.99
dhk PGF2α Y = −0.0118497+0.00538533*X 0.9959 3.91 7.81 108.54 100.62 98.8 5.39 9.34 3.42
dihomo PGE2 Y = −0.0282368+0.0385317*X 0.9979 0.49 0.98 83.68 100.44 103.78 10.37 1.72 6.08
dihomo PGF2α Y = −0.0227349+0.00528333*X 0.9955 3.91 7.81 - 94.16 102.45 - 16.02 6.08
Eicosapentaenoic acid Y = −0.00726793+0.044985*X 0.9977 48.83 97.66 101.86 110.94 100.45 8.22 3.55 4.74
LTB4 Y = −0.0317264+0.107824*X 0.997 0.49 0.49 82.34 84.36 101.99 9.44 2.61 6.7
LTC4 Y = 0.00172598+0.000680304*X 0.9924 3.91 7.81 - 87.83 101.18 - 8.94 2.18
LTD4 Y = −0.0118855+0.00133122*X 0.9953 7.81 15.63 - 99.93 100.68 - 6.31 1.05
LTE4 Y = 0.000709438+0.000835493*X 0.9904 7.81 15.63 - 87 106.72 - 5.21 4.86
LXB4 Y = −0.0102955+0.00539339*X 0.9946 9.77 19.53 84.9 106.04 95.97 12.7 4.84 7.91
PGA2 Y = −0.0393577+0.0211829*X 0.9918 0.98 1.95 92.8 84.98 98.34 3.93 4.61 0.55
PGB2 Y = −0.00996138+0.0113116*X 0.9957 2.44 4.88 86.27 92.54 103.24 5.02 3.12 1.67
PGD1 Y = 0.0134629+0.00660275*X 0.9939 0.98 1.95 94.68 125.3 96.6 6.21 1.71 5.41
PGD2 Y = 0.069616+0.00794019*X 0.9939 3.91 7.81 - 116.43 100.2 22.59 9.56 2.31
PGD3 Y = −0.0252769+0.0132198*X 0.9966 4.88 9.77 97.96 112.46 98.86 5.99 6.88 6.19
PGE1 Y = −0.00880038+0.0122419*X 0.9969 0.24 0.49 104.29 95.83 102.16 5.4 7.17 3.9
PGE2 Y = −0.0388571+0.0229049*X 0.9928 0.98 1.95 92.22 89.61 96.12 5.14 1.31 4.28
PGE3 Y = −0.017804+0.00304922*X 0.994 3.91 7.81 - 82.06 100.13 - 3.5 2.22
PGF1α Y = −0.0422301+0.0331548*X 0.9939 0.49 0.98 90.4 75.38 102.09 4.93 5.48 4.11
PGF2α Y = −0.0443765+0.0205826*X 0.9951 1.95 3.91 94.47 84.18 98.81 5.39 5.41 0.65
PGF3α Y = −0.00530456+0.00644135*X 0.9971 1.95 3.91 119.46 96.83 104.21 6.9 5.94 2.3
PGFM Y = −0.0128176+0.00680921*X 0.9963 1.95 3.91 104.87 85.51 97.88 13.82 9.1 0.99
PGJ2 Y = −0.0117915+0.00657162*X 0.9956 4.88 9.77 95.32 88.66 99.5 6.32 6.87 2.15
PGK2 Y = −0.0342431+0.00407618*X 0.9845 7.81 15.63 - 103.14 92.45 - 2.27 10.67
Protectin D1 Y = −0.0217126+0.0247917*X 0.9953 0.98 1.95 72.08 80.67 99.74 8.95 1.67 4.32
Resolvin D1 Y = −0.00442084+0.00313776*X 0.9948 3.91 7.81 102.28 91.76 101.84 5.27 9.57 2.99
Resolvin E1 Y = −0.0136544+0.00695023*X 0.996 3.91 7.81 93.01 95.95 106.05 11.48 9.71 5.18
tetranor 12-HETE Y = 0.00424854+0.00430041*X 0.9972 0.98 1.95 89.3 103.16 99.83 19.21 4.32 1.29
tetranor-PGDM Y = −0.0324347+0.00971906*X 0.9987 1.95 3.91 102.57 97.85 99.99 3.1 2.95 3.26
TXB1 Y = −0.0295277+0.0196896*X 0.994 9.77 19.53 99.15 110.99 93.52 11.92 11.37 3.72
TXB2 Y = −0.044364+0.048052*X 0.9941 2.44 4.88 105.04 103.38 102.75 7.51 6.3 2.98
TXB3 Y = −0.0386312+0.00743354*X 0.9938 9.77 19.53 - 99.94 99.76 0.5 3.35 1.09
Open in a new tab
a,

the LOQ and LOD were determined in actual amount on column.

Lipid mediator levels in human plasma

The developed method was applied to analyze two sources of human plasma, standard reference material metabolites in frozen human plasma (SRM 1950) from NIST and healthy donor plasma from Bioreclamation IVT (BR). A total of 77 and 32 oxylipins can be detected in BR and SRM 1950 plasma, respectively and they are listed in Table 4. Although both samples were from healthy individuals, large variations in the concentration of oxylipins were observed, which is in agreement with previous work [37]. SRM 1950 has been employed in an inter laboratory comparison study for lipid profiling, we compared our results to the concentrations of oxylipins reported by Bowden et al., [25] using LipidQC software [28]. A total of 11 mediators in our result were matched by LipidQC and 10 of them were within 99% expanded uncertainty as shown in Figure S4, which suggests that our results were consistent to the NIST-ILCE summary report [25].

Table 4.

Concentrations of oxylipins in human blood specimen measured in this work and reported in literature.

Lipid mediators Concentrations measured with our assay in plasma Concentrations reported in literature
Sources BR (ng/ml) SRM1950 (ng/ml) SRM1950 Ref [25] (ng/ml)a Pooled plasma Ref [20] (ng/ml) Serum from 27 healthy subjects Ref [37] (ng/ml)
10-HDoHE 3.067 ± 0.138
11,12-diHETrE 0.053 ± 0.01 0.261 ± 0.04 0.278 ± 0.09
11-HDoHE 3.924 ± 0.15 0.217 ± 0.03
11-HEPE 0.74 ± 0.138
11-HETE 15.068 ± 1.029 0.216 ± 0.031 0.3 0.4–13.6
12,13-diHOME 0.709 ± 0.028 1.481 ± 0.107 1.601 ± 0.119
12-HEPE 0.971 ± 0.045 0.164 ± 0.038
12-HETE 13.795 ± 0.429 2.296 ± 0.521 2.176 ± 0.48 3.12 6.8–167.3
12-HHTrE 0.417 ± 0.057 0.064 ± 0.01
13-HDoHE 30.203 ± 18.077
13-HODE 101.506 ± 0.982 4.069 ± 0.306
13-HOTrE 4.534 ± 0.383 0.159 ± 0.02
13-HOTrE(y) 2.118 ± 0.181
13-oxoODE 3.266 ± 0.452
14,15-diHETrE 0.078 ± 0.014 0.375 ± 0.078
14-HDoHE 7.245 ± 0.282 0.411 ± 0.065 0.447 ± 0.038
15d PGA2 67.743 ± 4.316
15d PGD2 1.839 ± 0.479 0.17 ± 0.03
15-HEPE 0.629 ± 0.05
15-HETE 31.087 ± 2.052 0.648 ± 0.093 0.768 ± 0.205 1.3 0.5–14.1
15-HETrE 4.652 ± 0.044 0.155 ± 0.031
15k PGE2 0.129 ± 0.024
15-oxoETE 0.897 ± 0.123
16-HDoHE 3.972 ± 0.084
16-HETE 0.14 ± 0 0.018–0.18
17 HDoHE 17.137 ± 0.634 0.282 ± 0.01
18-HEPE 1.309 ± 0.227 0.089 ± 0.02
18-HETE 0.157 ± 0.029 0.065–0.2
19(20)-EpDPE 4.405 ± 0.181
19,20-DiHDPA 0.071 ± 0.002 0.107 ± 0.016
20cooh AA 0.419 ± 0.007 0.695 ± 0.118 0.5–7.1
20-HDoHE 4.293 ± 0.166
20-HETE 0.504 ± 0.049 0.672 ± 0.17
20oh PGF2α 0.407 ± 0.021
4-HDoHE 7.61 ± 0.599 0.852 ± 0.158
5,15-diHETE 1.241 ± 0.261
5,6-diHETE 27.351 ± 5.131 0.5 ± 0.042
5,6-diHETrE 1.053 ± 0.046
5,6-EET 7.663 ± 0 0.263 ± 0.09
5-HEPE 5.034 ± 0.376 0.271 ± 0.01
5-HETE 127.093 ± 1.311 2.037 ± 0.161 3.2 ± 0.416 0.3 0.3–3.2
5-HETrE 1.808 ± 0.023
5-iso PGF2αVI 0.794 ± 0.171 0.102 ± 0.016
5-oxoETE 2.201 ± 0.082
6S-LXA4 1.491 ± 0.379
6t LTB4 0.465 ± 0.142 0.029 ± 0.005
7(R) Maresin-1 0.231 ± 0.011
7-HDoHE 1.401 ± 0.068
8,15-diHETE 2.152 ± 0.135 1.803 ± 0.264
8,9-diHETrE 0.164 ± 0.018 0.005–0.09
8,9-EET 32.835 ± 2.316 0.15
8-HDoHE 7.845 ± 0.216
8-HEPE 0.444 ± 0.052
8-HETrE 4.881 ± 0.064 0.123 ± 0.03
8-iso PGF2αIII 0.074 ± 0.017 0.052
8-iso PGF3a 6.136 ± 0.584
9,10-diHOME 0.797 ± 0.006 1.775 ± 0.422 2.104 ± 0.138
9-HEPE 0.655 ± 0 0.137 ± 0.03
9-HETE 18.637 ± 1.524 0.272 ± 0.03 0.3 0.2–4.7
9-HODE 95.31 ± 1.605 2.864 ± 0.3 2.96 ± 0.77
9-HOTrE 3.722 ± 0.038 0.129 ± 0.021
9-oxoODE 1.861 ± 0.137 0.712 ± 0.183 2.146 ± 0.382
Arachidonic acid 927.891 ± 52.743 862.171 ± 130.811 1428.8 ± 456 1143 800–2500
bicyclo PGE2 2.781 ± 0.222
DHA 280.291 ± 17.21 538.442 ± 67.604 492 ± 55.76
dhk PGD2 0.471 ± 0.041
dhk PGE2 1.18 ± 0.3
dhk PGF2α 0.287 ± 0.01
dihomo PGE2 0.057 ± 0.009
EPA 56.159 ± 3.895 81.197 ± 13.999 126.84 ± 16.912
LTB4 0.259 ± 0.08 <0.01 0.002–0.9
PGA2 0.341 ± 0.04 0.013–0.365
PGB2 1.115 ± 0.086 0.012–0.124
PGD1 0.437 ± 0.027
PGD2 1.315 ± 0.383 0.042
PGE2 0.097 ± 0.016 0.012 ± 0.005 0.029
PGF2α 0.096 ± 0 <0.05
PGFM 0.111 ± 0.01
PGJ2 0.262 ± 0.001 <0.05 0.03–1.054
Protectin D1 0.743 ± 0.226
tetranor-PGDM 0.129 ± 0.006
Open in a new tab
a,

Concentrations were converted from nmol/ml to ng/ml from the original source.

Conclusion

The MRM transitions can be easily obtained from mass spectrometry vendor’s software such as Compound Optimizer from Agilent or Optimization in TSQ Tune from Thermo via either direct infusion with a syringe pump or flow injection with an autosampler. These tools provide great convenience for researchers to effectively acquire dominant fragment ions at optimal collisional energies for individual compound; however, they are not designed to determine unique fragments to distinguish isomeric compounds. Biased interpretation of lipid mediator networks could be made based on inaccurate quantification resulted from using inappropriate MRM transitions.

Herein, we proposed a heatmap-assisted strategy to effectively select the unique fragment ions as specific MRM transitions to a large number of isomers. This greatly facilitated our development of an unbiased and reliable MRM-based LC-MS method to determine the concentrations of oxylipins in human plasma, which monitors 131 endogenous oxylipins and 25 deuterium-labeled internal standards in a single LC run. Whilst the selection of MRM transitions is based on unique fragment ions and not the top abundant ions may result in reduction in assay’s sensitivity; the optimization of mobile phase composition and LC gradient, together with improvements in SPE sample preparation helped to improve the method’s sensitivity, as demonstrated by quantification of 77 oxylipins in human plasma. The method was rigorously validated according to the FDA guidelines, and further validated by the consistent results obtained when measuring a standard reference human plasma, as compared to the NIST inter-laboratory reported values.

Although most oxylipins are highly expressed under inflammatory conditions, and it is reported by others and also demonstrated in this work that oxylipin levels have high inter individual variation, it is still worthwhile to investigate the basal levels of oxylipins in healthy individuals, in particular for longitudinal follow-up of a person’s health. Temporal changes of lipid mediator levels, together with other measurable clinical parameters are integral components of precision diagnosis and personalized medicine.

Supplementary Material

SI

ACKNOWLEDGMENT

This work was partially supported by the American Heart Association (Grant 17CSA33570025) and the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health (Grant R01 DK116731).

Footnotes

Compliance with Ethical Standards

The authors have no conflicts of interests to declare.

Deidentified, commercial human plasma were used in this work. Research conducted with unidentified samples is not human subjects research and is not regulated by the Federal Policy for the Protection of Human Subjects (45 CFR Part 46).

References

  • 1.Murakami M Lipid mediators in life science. Exp Anim. 2011; 60 (1):7–20 [DOI] [PubMed] [Google Scholar]
  • 2.Burke JE, Dennis EA. Phospholipase A2 structure/function, mechanism, and signaling. J Lipid Res. 2009; 50 Suppl:S237–242 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Dennis EA, Norris PC. Eicosanoid storm in infection and inflammation. Nat Rev Immunol. 2015; 15 (8):511–523 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Nieman DC, Meaney MP, John CS, Knagge KJ, Chen H. 9- and 13-Hydroxy-octadecadienoic acids (9+13 HODE) are inversely related to granulocyte colony stimulating factor and IL-6 in runners after 2h running. Brain Behav Immun. 2016; 56:246–252 [DOI] [PubMed] [Google Scholar]
  • 5.Caligiuri SPB, Parikh M, Stamenkovic A, Pierce GN, Aukema HM. Dietary modulation of oxylipins in cardiovascular disease and aging. Am J Physiol Heart Circ Physiol. 2017; 313 (5):H903–H918 [DOI] [PubMed] [Google Scholar]
  • 6.Hanif A, Edin ML, Zeldin DC, Morisseau C, Falck JR, Nayeem MA. Vascular endothelial overexpression of human CYP2J2 (Tie2-CYP2J2 Tr) modulates cardiac oxylipin profiles and enhances coronary reactive hyperemia in mice. PLoS One. 2017; 12 (3):e0174137. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Yeung J, Tourdot BE, Adili R, Green AR, Freedman CJ, Fernandez-Perez P, Yu J, Holman TR, Holinstat M. 12(S)-HETrE, a 12-Lipoxygenase Oxylipin of Dihomo-gamma-Linolenic Acid, Inhibits Thrombosis via Galphas Signaling in Platelets. Arterioscler Thromb Vasc Biol. 2016; 36 (10):2068–2077 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Sun Y, Koh HW, Choi H, Koh WP, Yuan JM, Newman JW, Su J, Fang J, Ong CN, van Dam RM. Plasma fatty acids, oxylipins, and risk of myocardial infarction: the Singapore Chinese Health Study. J Lipid Res. 2016; 57 (7):1300–1307 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Tessaro FH, Ayala TS, Martins JO. Lipid mediators are critical in resolving inflammation: a review of the emerging roles of eicosanoids in diabetes mellitus. Biomed Res Int. 2015; 2015:568408. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Tourdot BE, Ahmed I, Holinstat M. The emerging role of oxylipins in thrombosis and diabetes. Front Pharmacol. 2014; 4:176. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Hellmann J, Tang Y, Spite M. Proresolving lipid mediators and diabetic wound healing. Curr Opin Endocrinol Diabetes Obes. 2012; 19 (2):104–108 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Medeiros R, Kitazawa M, Passos GF, Baglietto-Vargas D, Cheng D, Cribbs DH, LaFerla FM. Aspirin-triggered lipoxin A4 stimulates alternative activation of microglia and reduces Alzheimer disease-like pathology in mice. Am J Pathol. 2013; 182 (5):1780–1789 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Palacios-Pelaez R, Lukiw WJ, Bazan NG. Omega-3 essential fatty acids modulate initiation and progression of neurodegenerative disease. Mol Neurobiol. 2010; 41 (2–3):367–374 [DOI] [PubMed] [Google Scholar]
  • 14.Montgomery CL, Keereetaweep J, Johnson HM, Grillo SL, Chapman KD, Koulen P. Changes in Retinal N-Acylethanolamines and their Oxylipin Derivatives During the Development of Visual Impairment in a Mouse Model for Glaucoma. Lipids. 2016; 51 (7):857–866 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Greenhough A, Smartt HJ, Moore AE, Roberts HR, Williams AC, Paraskeva C, Kaidi A. The COX-2/PGE2 pathway: key roles in the hallmarks of cancer and adaptation to the tumour microenvironment. Carcinogenesis. 2009; 30 (3):377–386 [DOI] [PubMed] [Google Scholar]
  • 16.Chen EP, Smyth EM. COX-2 and PGE2-dependent immunomodulation in breast cancer. Prostaglandins Other Lipid Mediat. 2011; 96 (1–4):14–20 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Yang J, Schmelzer K, Georgi K, Hammock BD. Quantitative profiling method for oxylipin metabolome by liquid chromatography electrospray ionization tandem mass spectrometry. Anal Chem. 2009; 81 (19):8085–8093 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Masoodi M, Eiden M, Koulman A, Spaner D, Volmer DA. Comprehensive lipidomics analysis of bioactive lipids in complex regulatory networks. Anal Chem. 2010; 82 (19):8176–8185 [DOI] [PubMed] [Google Scholar]
  • 19.Blewett AJ, Varma D, Gilles T, Libonati JR, Jansen SA. Development and validation of a high-performance liquid chromatography-electrospray mass spectrometry method for the simultaneous determination of 23 eicosanoids. J Pharm Biomed Anal. 2008; 46 (4):653–662 [DOI] [PubMed] [Google Scholar]
  • 20.Shinde DD, Kim KB, Oh KS, Abdalla N, Liu KH, Bae SK, Shon JH, Kim HS, Kim DH, Shin JG. LC-MS/MS for the simultaneous analysis of arachidonic acid and 32 related metabolites in human plasma: Basal plasma concentrations and aspirin-induced changes of eicosanoids. J Chromatogr B Analyt Technol Biomed Life Sci. 2012; 911:113–121 [DOI] [PubMed] [Google Scholar]
  • 21.Wang Y, Armando AM, Quehenberger O, Yan C, Dennis EA. Comprehensive ultra-performance liquid chromatographic separation and mass spectrometric analysis of eicosanoid metabolites in human samples. J Chromatogr A. 2014; 1359:60–69 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Edpuganti V, Mehvar R. UHPLC-MS/MS analysis of arachidonic acid and 10 of its major cytochrome P450 metabolites as free acids in rat livers: effects of hepatic ischemia. J Chromatogr B Analyt Technol Biomed Life Sci. 2014; 964:153–163 [DOI] [PubMed] [Google Scholar]
  • 23.Willenberg I, Ostermann AI, Schebb NH. Targeted metabolomics of the arachidonic acid cascade: current state and challenges of LC-MS analysis of oxylipins. Anal Bioanal Chem. 2015; 407 (10):2675–2683 [DOI] [PubMed] [Google Scholar]
  • 24.Yang Y, Zhong Q, Mo C, Zhang H, Zhou T, Tan W. Determination of endogenous inflammation-related lipid mediators in ischemic stroke rats using background subtracting calibration curves by liquid chromatography-tandem mass spectrometry. Anal Bioanal Chem. 2017; 409 (28):6537–6547 [DOI] [PubMed] [Google Scholar]
  • 25.Bowden JA, Heckert A, Ulmer CZ, Jones CM, Koelmel JP, Abdullah L, Ahonen L, Alnouti Y, Armando AM, Asara JM, Bamba T, Barr JR, Bergquist J, Borchers CH, Brandsma J, Breitkopf SB, Cajka T, Cazenave-Gassiot A, Checa A, Cinel MA, Colas RA, Cremers S, Dennis EA, Evans JE, Fauland A, Fiehn O, Gardner MS, Garrett TJ, Gotlinger KH, Han J, Huang Y, Neo AH, Hyotylainen T, Izumi Y, Jiang H, Jiang H, Jiang J, Kachman M, Kiyonami R, Klavins K, Klose C, Kofeler HC, Kolmert J, Koal T, Koster G, Kuklenyik Z, Kurland IJ, Leadley M, Lin K, Maddipati KR, McDougall D, Meikle PJ, Mellett NA, Monnin C, Moseley MA, Nandakumar R, Oresic M, Patterson R, Peake D, Pierce JS, Post M, Postle AD, Pugh R, Qiu Y, Quehenberger O, Ramrup P, Rees J, Rembiesa B, Reynaud D, Roth MR, Sales S, Schuhmann K, Schwartzman ML, Serhan CN, Shevchenko A, Somerville SE, St John-Williams L, Surma MA, Takeda H, Thakare R, Thompson JW, Torta F, Triebl A, Trotzmuller M, Ubhayasekera SJK, Vuckovic D, Weir JM, Welti R, Wenk MR, Wheelock CE, Yao L, Yuan M, Zhao XH, Zhou S. Harmonizing lipidomics: NIST interlaboratory comparison exercise for lipidomics using SRM 1950-Metabolites in Frozen Human Plasma. J Lipid Res. 2017; 58 (12):2275–2288 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Ostermann AI, Willenberg I, Schebb NH. Comparison of sample preparation methods for the quantitative analysis of eicosanoids and other oxylipins in plasma by means of LC-MS/MS. Anal Bioanal Chem. 2015; 407 (5):1403–1414 [DOI] [PubMed] [Google Scholar]
  • 27.U.S. Department of Health and Human Services FDA (2013) Guidance for Industry: Bioanalytical Method Validation [Google Scholar]
  • 28.Ulmer CZ, Ragland JM, Koelmel JP, Heckert A, Jones CM, Garrett TJ, Yost RA, Bowden JA. LipidQC: Method Validation Tool for Visual Comparison to SRM 1950 Using NIST Interlaboratory Comparison Exercise Lipid Consensus Mean Estimate Values. Anal Chem. 2017; 89 (24):13069–13073 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Liigand J, Kruve A, Leito I, Girod M, Antoine R. Effect of mobile phase on electrospray ionization efficiency. J Am Soc Mass Spectrom. 2014; 25 (11):1853–1861 [DOI] [PubMed] [Google Scholar]
  • 30.Strassburg K, Huijbrechts AM, Kortekaas KA, Lindeman JH, Pedersen TL, Dane A, Berger R, Brenkman A, Hankemeier T, van Duynhoven J, Kalkhoven E, Newman JW, Vreeken RJ. Quantitative profiling of oxylipins through comprehensive LC-MS/MS analysis: application in cardiac surgery. Anal Bioanal Chem. 2012; 404 (5):1413–1426 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Le Faouder P, Baillif V, Spreadbury I, Motta JP, Rousset P, Chene G, Guigne C, Terce F, Vanner S, Vergnolle N, Bertrand-Michel J, Dubourdeau M, Cenac N. LC-MS/MS method for rapid and concomitant quantification of pro-inflammatory and pro-resolving polyunsaturated fatty acid metabolites. J Chromatogr B Analyt Technol Biomed Life Sci. 2013; 932:123–133 [DOI] [PubMed] [Google Scholar]
  • 32.Narvaez-Rivas M, Zhang Q. Comprehensive untargeted lipidomic analysis using core-shell C30 particle column and high field orbitrap mass spectrometer. J Chromatogr A. 2016; 1440:123–134 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Narvaez-Rivas M, Vu N, Chen GY, Zhang Q. Off-line mixed-mode liquid chromatography coupled with reversed phase high performance liquid chromatography-high resolution mass spectrometry to improve coverage in lipidomics analysis. Anal Chim Acta. 2017; 954:140–150 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Dolan JW. Temperature selectivity in reversed-phase high performance liquid chromatography. J Chromatogr A. 2002; 965 (1–2):195–205 [DOI] [PubMed] [Google Scholar]
  • 35.Cui L, Isbell MA, Chawengsub Y, Falck JR, Campbell WB, Nithipatikom K. Structural characterization of monohydroxyeicosatetraenoic acids and dihydroxy- and trihydroxyeicosatrienoic acids by ESI-FTICR. J Am Soc Mass Spectrom. 2008; 19 (4):569–585 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Chappell GP, Xiao X, Pica-Mendez A, Varnell T, Green S, Tanaka WK, Laterza O. Quantitative measurement of cysteinyl leukotrienes and leukotriene B(4) in human sputum using ultra high pressure liquid chromatography-tandem mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci. 2011; 879 (3–4):277–284 [DOI] [PubMed] [Google Scholar]
  • 37.Yasumoto A, Tokuoka SM, Kita Y, Shimizu T, Yatomi Y. Multiplex quantitative analysis of eicosanoid mediators in human plasma and serum: Possible introduction into clinical testing. J Chromatogr B Analyt Technol Biomed Life Sci. 2017; 1068-1069:98–104 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

SI
NIHMS1003512-supplement-SI.pdf (974.9KB, pdf)

RESOURCES