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Research| Volume 103, ISSUE 9, P7761-7774, September 2020

Regioisomeric and enantiomeric analysis of primary triglycerides in human milk by silver ion and chiral HPLC atmospheric pressure chemical ionization-MS

Open ArchivePublished:July 01, 2020DOI:https://doi.org/10.3168/jds.2019-17353

      ABSTRACT

      Triglycerides (TG) not only provide energy for infants but have important physiological functions. Understanding the composition and structure of TG in human milk is conducive to the development of infant formulas. In this study, TG species in human milk from 3 provincial capitals (Zhengzhou, Wuhan, and Harbin) in different regions of China were determined through C18 HPLC electrospray ionization tandem mass spectrometry (MS). The results showed that in human milk from these 3 regions, oleoyl-palmitoyl-linoleoylglycerol (OPL; 16.55, 19.20, and 18.67%, respectively) was more abundant than oleoyl-palmitoyl-oleoylglycerol (OPO; 10.08, 10.22, and 12.03%, respectively). Subsequently, regioisomeric and enantiomeric analysis of main TG in the human milk were performed on silver ion and chiral HPLC atmospheric pressure chemical ionization mass spectrometry (APCI)-MS, respectively. The results showed that rac-OPL (above 85%), rac-OPO (above 85%), rac-palmitoyl-oleoyl-oleoylglycerol (PPO; above 90%), and rac-OLaO (above 70%) were the main regioisomers of OPL, OPO, PPO, and lauroyl-oleoyl-oleoylglycerol (LaOO), respectively. The relative ratios of enantiomer pairs of rac-OPL (rac-OPL1 and rac-OPL2) were about 37 and 63%, respectively.

      Key words

      INTRODUCTION

      Human milk provides optimal natural nutrition for infants. Lipids, as the main energy source of human milk, 98% of which are represented by triglycerides (TG), provide about 50% energy requirements for infants (
      • Ten-Doménech I.
      • Beltrán-Iturat E.
      • Herrero-Martínez J.M.
      • Sancho-Llopis J.V.
      • Simó-Alfonso E.F.
      Triacylglycerol analysis in human milk and other mammalian species: Small-scale sample preparation, characterization, and statistical classification using HPLC-ELSD profiles.
      ). Triglycerides are esterified 3 fatty acids with a glycerol backbone and have a prochiral center at the secondary carbon of glycerol. Triglycerides may possess 3 different fatty acids (ABC type), 2 of the same fatty acids (AAB type), or 3 of the same fatty acids (AAA type). Different fatty acids esterified in the sn-2 and sn-1(3) positions result in regioisomers. Different fatty acids esterified in the sn-1 and sn-3 positions result in enantiomers (
      • Řezanka T.
      • Nedbalová L.
      • Sigler K.
      Enantiomeric separation of triacylglycerols containing polyunsaturated fatty acids with 18 carbon atoms.
      ). It has been reported that 1,3-dioleoyl-2-palmitoylglycerol (OPO) and 1-oleoyl-2-palmitoyl-3-linoleoylglycerol (OPL) are the most predominant TG in human milk. The structure of TG, combined with a specific lipase in the gastrointestinal tract, causes a special process of fat digestion in infants. In infants' digestive systems, the expression of pancreatic triglyceride lipase (PTL), which has sn-1,3 regioselective, is not immaturity. Fat digestion in infants mainly depends on gastric lipase (HGL), pancreatic lipase-related protein 2, and bile salt-stimulated lipase (
      • Bourlieu C.
      • Menard O.
      • Bouzerzour K.
      • Mandalari G.
      • Macierzanka A.
      • Mackie A.R.
      • Dupont D.
      Specificity of infant digestive conditions: some clues for developing relevant in vitro models.
      ;
      • Bourlieu C.
      • Michalski M.C.
      Structure-function relationship of the milk fat globule.
      ). Gastric lipase has strong sn-3 stereoselectivity, mainly releasing medium- and long-chain fatty acids in the stomach (
      • Roman C.
      • Carriere F.
      • Villeneuve P.
      • Pina M.
      • Millet V.
      • Simeoni U.
      • Sarles J.
      Quantitative and qualitative study of gastric lipolysis in premature infants: Do MCT-enriched infant formulas improve fat digestion?.
      ). The long-chain fatty acids released by HGL play an important role in triggering the activity of pancreatic lipase (
      • Bernbäck S.
      • Bläckberg L.
      • Hernell O.
      Fatty acids generated by gastric lipase promote human milk tricylglycerol digestion by pancreatic colipase-dependent lipase.
      ). Meanwhile, fatty acid distribution in human milk TG are not random. Over 70% of the palmitic acid is esterified at the second (sn-2) carbon of the TG glycerol backbone, which reduces extraction of fecal soap fatty acids and calcium malabsorption, and promotes early bone mineralization (
      • Wan J.
      • Hu S.
      • Ni K.
      • Chang G.
      • Sun X.
      • Yu L.
      Characterisation of fecal soap fatty acids, calcium contents, bacterial community and short-chain fatty acids in Sprague Dawley rats fed with different sn-2 palmitic triacylglycerols diets.
      ;
      • Miles E.A.
      • Calder P.C.
      The influence of the position of palmitate in infant formula triacylglycerols on health outcomes.
      ). Thus, in human milk, not only the species of TG but also the regioisomers and enantiomers of TG play important nutritional and physiological roles. However, in human milk fat, only regioisomers of rac-palmitoyl-oleoyl-oleoylglycerol (PPO)/rac-POP and rac-OOP/rac-OPO are separated and identified by silver ion chromatography (
      • Zou X.Q.
      • Huang J.H.
      • Jin Q.Z.
      • Guo Z.
      • Liu Y.F.
      • Cheong L.Z.
      • Xu X.B.
      • Wang X.G.
      Lipid composition analysis of milk fats from different mammalian species: Potential for use as human milk fat substitutes.
      ). The regioisomers of other important TG molecules, such as lauroyl-oleoyl-oleoylglycerol (LaOO) and OPL, were not yet separated. The enantiomers' separation of TG was not applied in human milk.
      Various analytical methods have been used to identify the molecular structure of TG in human milk. Enzymatic (lipase) or chemical (Grignard) hydrolysis, combined with chromatography, have usually been used to analysis the regio- and stereospecific distribution of fatty acids in TG (
      • Qi C.
      • Sun J.
      • Xia Y.
      • Yu R.Q.
      • Wei W.W.
      • Xiang J.Y.
      • Jin Q.Z.
      • Xiao H.
      • Wang X.G.
      Fatty acid profile and the sn-2 position distribution in triacylglycerols of breast milk during different lactation stages.
      ;
      • Sun C.
      • Wei W.
      • Su H.
      • Zou X.
      • Wang X.
      Evaluation of sn-2 fatty acid composition in commercial infant formulas on the Chinese market: A comparative study based on fat source and stage.
      ). However, this has not separated the molecular species of TG, only determining mixed fatty acids on the primary and secondary hydroxyls. Reverse-phase liquid chromatography is a common method to separate TG species, which mainly depends on equivalent carbon numbers of TG (
      • Řezanka T.
      • Pádrová K.
      • Sigler K.
      Regioisomeric and enantiomeric analysis of triacylglycerols.
      ). Partial separation of TG regioisomers in reverse-phase mode requires multiple column coupling and very long times (
      • Momchilova S.
      • Tsuji K.
      • Itabashi Y.
      • Nikolova-Damyanova B.
      • Kuksis A.
      Resolution of triacylglycerol positional isomers by reversed-phase high-performance liquid chromatography.
      ;
      • Momchilova S.
      • Itabashi Y.
      • Nikolova-Damyanova B.
      • Kuksis A.
      Regioselective separation of isomeric triacylglycerols by reversed-phase high-performance liquid chromatography: Stationary phase and mobile phase effects.
      ). In human milk, C18 reverse-phase HPLC has usually been used to separate different species of TG (
      • Pons S.M.
      • Bargalló A.C.
      • Folgoso C.C.
      • López Sabater M.C.
      Triacylglycerol composition in colostrum, transitional and mature human milk.
      ;
      • Beccaria M.
      • Sullini G.
      • Cacciola F.
      • Donato P.
      • Dugo P.
      • Mondello L.
      High performance characterization of triacylglycerols in milk and milk-related samples by liquid chromatography and mass spectrometry.
      ). Reverse-phase liquid chromatography combined with MS detectors has also been used to analyze TG regioisomers in human milk (
      • Kallio H.
      • Nylund M.
      • Bostrom P.
      • Yang B.
      Triacylglycerol regioisomers in human milk resolved with an algorithmic novel electrospray ionization tandem mass spectrometry method.
      ). It is well known that the intensities of diglyceride (DG) fragment ions [M+H–RCOOH]+ depend on the positional distribution of fatty acids in TG; that is, the abundance of DG fragment ions resulting from loss of a fatty acid in the sn-2 position was less than that resulting from loss of a fatty acid from the sn-1 or 3 position (
      • Lísa M.
      • Velínská H.
      • Holčapek M.
      Regioisomeric characterization of triacylglycerols using silver-ion HPLC/MS and randomization synthesis of standards.
      ;
      • Holčapek M.
      • Dvořáková H.
      • Lísa M.
      • Girón A.J.
      • Sandra P.
      • Cvačka J.
      Regioisomeric analysis of triacylglycerols using silver-ion liquid chromatography-atmospheric pressure chemical ionization mass spectrometry: comparison of five different mass analyzers.
      ). But this method requires an extremely high number of reference compounds to obtain accurate correction factors, because each TG may have specific DG fragment ions ratios in MS. Therefore, up to now, integration of chromatographic peak area is still the most accurate method to determine the relative contents of regioisomers. Silver ion chromatography is a powerful technique for the separation of TG regioisomers, the retention time of which is mainly based on the number, geometry, and position of the double bones in the TG (
      • Řezanka T.
      • Pádrová K.
      • Sigler K.
      Regioisomeric and enantiomeric analysis of triacylglycerols.
      ). It has not been possible to identify TG enantiomers by MS, because enantiomers provide the same mass spectra due to loss of fatty acids from the sn-1 or sn-3 positions. Thus, distinguishing TG enantiomers requires standards. Only chiral phase chromatography has made it possible to separate enantiomers with their structures intact. The chiral stationary phases based on cellulose-tris-(3,5-dimethylphenylcarbamate) or cellulose-tris-(3-chlor-4-methyl phenyl carbamate) coated with silica gel have proved to be the most effective method. Chiral phase HPLC has many applications for separation of TG enantiomers, such as those of edible fats and oils (
      • Kalpio M.
      • Nylund M.
      • Linderborg K.M.
      • Yang B.
      • Kristinsson B.
      • Haraldsson G.G.
      • Kallio H.
      Enantioselective chromatography in analysis of triacylglycerols common in edible fats and oils.
      ), hazelnut oil, and human plasma (
      • Lísa M.
      • Holčapek M.
      Characterization of triacylglycerol enantiomers using chiral HPLC/APCI-MS and synthesis of enantiomeric triacylglycerols.
      ). But chiral phase HPLC has not yet been applied to the separation of enantiomers in human milk TG.
      In this study, TG species in human milk from the cities of Zhengzhou (located in the Yellow River drainage area), Wuhan (located in the Yangtze River drainage area), and Harbin (located in Northeast China) were determined through C18 HPLC electrospray ionization (ESI)-MS/MS. Regioisomers and enantiomers of the main TG in human milk were also analyzed by silver ion and chiral HPLC atmospheric pressure chemical ionization (APCI)-MS, respectively.

      MATERIALS AND METHODS

      Reagents and Standards

      The following racemic standards of TG were purchased from Larodan Fine Chemicals (Malmö, Sweden): rac-PPO, rac-POP, rac-OPO, rac-OOP, rac-LaOO, rac-OLaO, rac-OPL, rac-POL and rac-PLO. All solvents were HPLC or HPLC-MS grade and purchased from Merck (Darmstadt, Germany).

      Human Milk Samples

      Human milk was collected at 0900 to 1100 h, before breastfeeding, from 4 to 6 mo after delivery. Volunteer mothers (25 to 35 yr old) from the hospitals in 3 provincial capitals, Zhengzhou (Zhenggong Hospital, n = 30), Wuhan (Zhoutoujie Health Service Center, Hanyang District, n = 30), and Harbin (Harbin Gongnong Community Health Service Center, n = 30), representing different regions of China, all received detailed information about the study and provided written informed consent. Mothers were physically healthy by self-evaluation, did not smoke, did not drink alcohol, and had given birth to physically healthy infants. Mothers were instructed to wash their hands carefully with soap and water before expressing milk from 1 breast by breast pump into sterile hard plastic containers. The collection human milk sample information was registered at ClinicalTrials.gov (ID: NCT03675204). All samples were kept frozen at −20°C until delivery to the laboratory and then dispensed and stored at −80°C for subsequent analysis. All samples were analyzed separately.

      Extraction of Total Lipids from Human Milk

      Lipid samples from human milk were extracted using the
      • Folch J.
      • Lee M.
      • Sloane-Stanley G.H.
      A simple method for the isolation and purification of total lipids from animal tissues.
      procedure with modification. Briefly, 500 μL of milk was mixed with 4.5 mL of chloroform and methanol (2:1, vol/vol). The mixture was shaken and equilibrated with one-fourth volume of saline solution (NaCl 0.86%, wt/wt). The solvent phase was filtered and dried under a stream of nitrogen. The obtained total lipids were stored at −20°C for further analysis.

      TG Species Analysis

      Chromatographic Conditions

      For chromatographic separation of TG, a Zorbax Eclipse Plus C18 column (1.8 μm, 2.1 × 100 mm, Agilent Technologies, Wilmington, DE) was used. The mobile phase gradients were as follows: 0 to 5 min 90% A + 10% B; 5 to 25 min 90–60% A + 10–40% B; 25 to 60 min 60–40% A + 40–60% B; 60 to 66 min 40% A + 60% B; where A was the mixture of acetonitrile, methanol, and water (19:19:2 by volume) with 10 mM ammonium acetate and 0.1% formic acid, and B was 2-propanol with 10 mM ammonium acetate and 0.1% formic acid. The flow rate was 0.2 mL/min, injection volume was 2 μL, column temperature was 45°C, and sample concentration was 0.5 mg/mL.

      Qualitative Analysis

      The qualitative analysis of TG used a Bruker maXis UHR-TOF-MS (Bruker Daltonics, Bremen, Germany) combined with UltiMate 3000 RSLCnano liquid chromatography (LC) system (Thermo Fisher Scientific, Waltham, MA). The chromatographic conditions were as previously described in the Chromatographic Conditions section. The parameters of qualitative time-of-flight MS were as follows: data acquisition was performed in positive ion ESI mode; source gas flow was 6 L/min; source temperature was 180°C; and mass range m/z was 50 to 1,200.

      Quantitative Analysis

      Quantification of TG was performed on a Triple Quad LC-MS (Agilent) and by MS/MS using the multiple reaction monitoring acquisition mode. The chromatographic conditions were as previously described. The ESI source parameters, running in positive ionization mode, were 8 L/min of drying gas (N2), 350°C, 35 psi of nebulizer pressure, and 3,500 V of capillary voltage.

      Collection of PPO, POO, LaOO, and POL Fractions

      The PPO, POO, LaOO, and POL fractions were collected from eluent of human milk TG using the Zorbax Eclipse Plus C18 column. The chromatographic conditions were as described. The sample concentration was 5 mg/mL, and injection volume was 10 μL. The fractions corresponding to PPO, POO, LaOO, and POL were collected by an automatic fraction collector. The sample volume of each fraction was about 0.4 mL. Collected fractions were concentrated with nitrogen and redissolved with hexane to 50 μL for further separation of regioisomers and enantiomers.

      Separation and Identification of Regioisomers and Enantiomers

      Separation of TG Regioisomers by Silver Ion HPLC

      Separation of TG regioisomers was first performed on an Agilent 1290 Series liquid chromatograph, equipped with an evaporative light-scattering detector (ELSD) to determine the optimal chromatographic conditions. The ELSD was set at 40°C at a gas pressure of 30 psi and a gain value of 150. A Varian ChromSpher 5 Lipids column (5 μm, 250 mm × 4.6 mm; Agilent) was used to separate TG regioisomers, with a flow rate of 0.5 mL/min, injection volume of 5 µL, column temperature of 30°C, and mobile phase gradient as follows: 0 to 20 min 70% A + 30% B; 20 to 21 min 70–57% A + 30–43% B; 21 to 45 min 57% A + 43% B, where A was hexane and B was a mixture of hexane-2-propanol (98:2, vol/vol). The chromatographic system was equilibrated between injections for at least 30 min. The reproducibility of the silver ion column with final chromatographic conditions was determined over 2 d, each day including 5 consecutive injections.

      Separation of TG Enantiomers by Chiral HPLC

      Separation of TG enantioisomers (rac-OPL, rac-PLO, and rac-POL) was also first performed on the ELSD detector, to determine the optimal chromatographic conditions. The LC system used for separation in the chiral mode was as previously described. The final HPLC method for analyses of TG used the following conditions: a chiral chromatographic column Lux Cellulose-1 with cellulose-tris-(3,5-dimethyl phenylcarbamate)-coated silica gel as the stationary phase (3 μm, 250 mm × 4.6 mm, Phenomenex, Torrance, CA), with flow rate of 0.5 mL/min, injection volume of 5 µL, column temperature of 30°C, and mobile phase an isocratic elution of 0 to 180 min 90% A + 10% B, where A was hexane and B was hexane-2-propanol (99:1, vol/vol) mixture. The reproducibility of the chiral column with final chromatographic conditions was determined over 2 d, each day including 5 consecutive injections.

      Identification of Regioisomers and Enantiomers by APCI-MS

      The analysis regioisomers and enantiomers from human milk were performed on an HPLC APCI-MS. The LC system and chromatographic conditions were as previously described. The MS conditions were as follows: APCI source block and probe temperatures, 100 and 400°C, respectively; MS multiplier voltage, 700 V; measurement range, m/z 200–1,500. The relative ratios of the regioisomers and enantiomers were obtained through the extracted ion chromatogram function.

      Statistical Analysis

      All analyses of human milk samples were carried out in triplicate. Results were expressed as means ± standard deviations (SD). Data were subjected to one-way ANOVA and Tukey's test using SPSS version 20.0 (IBM Corp., Armonk, NY).

      RESULTS AND DISCUSSION

      TG Profiling Analysis in Human Milk

      Reverse-phase HPLC (especially using a C18 column) is a common method to analyze TG, separating TG based on different equivalent carbon numbers (
      • Hu J.
      • Wei F.
      • Dong X.Y.
      • Lv X.
      • Jiang M.L.
      • Li G.M.
      • Chen H.
      Characterization and quantification of triacylglycerols in peanut oil by off-line comprehensive two-dimensional liquid chromatography coupled with atmospheric pressure chemical ionization mass spectrometry.
      ). In our study, the reverse-phase HPLC, combined with ESI-MS/MS full scan mode and ESI multiple reaction monitoring mode, were used to identify and quantify TG in human milk, respectively. The [M+NH4]+, [M+H]+, and [DG]+ ions were first obtained using ESI full scan mode (Figure 1), and TG species were also identified. Then ion pairs of each TG were carefully chosen to quantify TG with multiple reaction monitoring mode.
      Figure thumbnail gr1
      Figure 1Analysis of human milk triglyceride (TG) species via C18 HPLC electrospray ionization-MS/MS. (a) Total ion chromatogram of human milk TG. (b) MS spectrum and MS/MS spectrum of oleoyl-palmitoyl-oleoylglycerol (OPO). (c) MS spectrum and MS/MS spectrum of oleoyl-palmitoyl-linoleoylglycerol (OPL). Intens. = intensity.
      Triglyceride species from 3 regions of China were analyzed and compared with each other to determine whether the relative abundances of TG have regional disparities, especially the contents of OPL and OPO. The results in Table 1 showed that in human milk from the 3 regions (Zhengzhou, Wuhan, and Harbin), the most abundant TG was OPL (16.55, 19.20, and 18.67%, respectively) and the second most abundant was OPO (10.08, 10.22, and 12.03%, respectively). The same results have been reported by other literature (in human milk samples from Wuxi, Beijing, Hubei, and Sichuan, respectively;
      • Sun C.
      • Wei W.
      • Zou X.
      • Huang J.
      • Jin Q.
      • Wang X.
      Evaluation of triacylglycerol composition in commercial infant formulas on the Chinese market: A comparative study based on fat source and stage.
      ). On the contrary, the most abundant TG in human milk samples from European countries is OPO, followed by OPL (
      • Pons S.M.
      • Bargalló A.C.
      • Folgoso C.C.
      • López Sabater M.C.
      Triacylglycerol composition in colostrum, transitional and mature human milk.
      ;
      • Zou X.Q.
      • Huang J.H.
      • Jin Q.Z.
      • Guo Z.
      • Liu Y.F.
      • Cheong L.Z.
      • Xu X.B.
      • Wang X.G.
      Lipid composition analysis of milk fats from different mammalian species: Potential for use as human milk fat substitutes.
      ;
      • Ten-Doménech I.
      • Beltrán-Iturat E.
      • Herrero-Martínez J.M.
      • Sancho-Llopis J.V.
      • Simó-Alfonso E.F.
      Triacylglycerol analysis in human milk and other mammalian species: Small-scale sample preparation, characterization, and statistical classification using HPLC-ELSD profiles.
      ;
      • Kallio H.
      • Nylund M.
      • Bostrom P.
      • Yang B.
      Triacylglycerol regioisomers in human milk resolved with an algorithmic novel electrospray ionization tandem mass spectrometry method.
      ). The composition of human milk components is related to multiple factors, including maternal diet, genetics, lactation stage, breastfeeding practices, maternal and infant health status, and environmental exposures (
      • Miliku K.
      • Duan Q.L.
      • Moraes T.J.
      • Becker A.B.
      • Mandhane P.J.
      • Turvey S.E.
      • Lefebvre D.L.
      • Sears M.R.
      • Subbarao P.
      • Field C.J.
      • Azad M.B.
      Human milk fatty acid composition is associated with dietary, genetic, sociodemographic, and environmental factors in the CHILD Cohort study.
      ). Maternal diet has been considered the most important factor (
      • Wang L.
      • Li X.D.
      • Hussain M.
      • Liu L.
      • Zhang Y.
      • Zhang H.
      Effect of lactation stages and dietary intake on the fatty acid composition of human milk (A study in Northeast China).
      ). The high levels of OPO in European countries are mainly related to the intake of olive oil (containing 63.3% oleic acid) by mothers, as in the Mediterranean diet in Spain, Italy, and Croatia. Other vegetable oils (such as peanut oil and rapeseed oil), nuts, meat, and cheese are also important sources of oleic acid (
      • Orsavova J.
      • Misurcova L.
      • Ambrozova J.V.
      • Vicha R.
      • Mlcek J.
      Fatty acids composition of vegetable oils and its contribution to dietary energy intake and dependence of cardiovascular mortality on dietary intake of fatty acids.
      ;
      • Barreiro R.
      • Diaz-Bao M.
      • Cepeda A.
      • Regal P.
      • Fente C.A.
      Fatty acid composition of breast milk in Galicia (NW Spain): A cross-country comparison.
      ). Therefore, contents of OPO and OPL are very different in different countries. In most Chinese cities, levels of OPL are higher than OPO. The TG with contents exceeding 4% in human milk from the 3 regions studied here (Zhengzhou, Wuhan, and Harbin) were PPO, PLL, OLL, and OOL, which are also the main TG in other literature results (
      • Tu A.
      • Ma Q.
      • Bai H.
      • Du Z.
      A comparative study of triacylglycerol composition in Chinese human milk within different lactation stages and imported infant formula by SFC coupled with Q-TOF-MS.
      ;
      • Zhao P.
      • Zhang S.
      • Liu L.
      • Pang X.
      • Yang Y.
      • Lu J.
      • Lv J.
      Differences in the triacylglycerol and fatty acid compositions of human colostrum and mature milk.
      ). The contents of PPO in human milk from Harbin were significantly higher than those from Zhengzhou and Wuhan (P < 0.05). The contents of PLL, OLL, and OOL in human milk rom Wuhan were significantly higher than those from Zhengzhou and Harbin (P < 0.05). As for other major TG (>1%), the contents of MLaLa, LaMM, LaLaO, MLLa, PLCa, POCa, MLaO, PMM, PPLa, PLLa, LOLa, MOPo, and LaOO in Zhenzhou human milk were significantly higher than those from Wuhan and Harbin (P < 0.05). Among these TG, the contents of LaMM, LaLaO, PLLa, LOLa, MOPo, and LaOO in Wuhan and Harbin human milk, and MLaLa and PPLa in Harbin human milk, exceeded 1%; other TG relative values in Wuhan and Harbin human milk were less than 1%. The contents of POM, PPP, and PPL in Harbin human milk were significantly higher than those in Zhengzhou and Wuhan samples (P < 0.05). There were no significant differences in human milk from the 3 regions for the values of MMO, POLa, MOL, PLPo, and OOO. The results of our study and in the literature reveal that the TG containing linoleic acid, such as OPL, PLL, OLL, OOL, MOL, and LLL, in Chinese human milk were much higher than those in human milk from European countries (
      • Zou X.Q.
      • Huang J.H.
      • Jin Q.Z.
      • Guo Z.
      • Liu Y.F.
      • Cheong L.Z.
      • Xu X.B.
      • Wang X.G.
      Model for human milk fat substitute evaluation based on triacylglycerol composition profile.
      ;
      • Ten-Doménech I.
      • Beltrán-Iturat E.
      • Herrero-Martínez J.M.
      • Sancho-Llopis J.V.
      • Simó-Alfonso E.F.
      Triacylglycerol analysis in human milk and other mammalian species: Small-scale sample preparation, characterization, and statistical classification using HPLC-ELSD profiles.
      ;
      • Sun C.
      • Wei W.
      • Zou X.
      • Huang J.
      • Jin Q.
      • Wang X.
      Evaluation of triacylglycerol composition in commercial infant formulas on the Chinese market: A comparative study based on fat source and stage.
      ). This was consistent with the high levels of linoleic acid in Chinese human milk (
      • Zou L.
      • Pande G.
      • Akoh C.C.
      Infant formula fat analogs and human milk fat: New focus on infant developmental needs.
      ;
      • Qi C.
      • Sun J.
      • Xia Y.
      • Yu R.Q.
      • Wei W.W.
      • Xiang J.Y.
      • Jin Q.Z.
      • Xiao H.
      • Wang X.G.
      Fatty acid profile and the sn-2 position distribution in triacylglycerols of breast milk during different lactation stages.
      ). High intake of soybean oil and sunflower oil, containing about 50 and 60% of linoleic acid, respectively, is mainly responsible for this phenomenon (
      • Orsavova J.
      • Misurcova L.
      • Ambrozova J.V.
      • Vicha R.
      • Mlcek J.
      Fatty acids composition of vegetable oils and its contribution to dietary energy intake and dependence of cardiovascular mortality on dietary intake of fatty acids.
      ;
      • Wang L.
      • Li X.D.
      • Hussain M.
      • Liu L.
      • Zhang Y.
      • Zhang H.
      Effect of lactation stages and dietary intake on the fatty acid composition of human milk (A study in Northeast China).
      ).
      Table 1Triglyceride (TG) compositions in human milk from different cities in China (values given as mean ± SD)
      TG
      TG names do not indicate positional location of fatty acids in the triacylglycerols. Bu = butyric acid; Cp = caproic acid; C = caprylic acid; Ca = capric acid; La = lauric acid; M = myristic acid; P = palmitic acid; Po = palmitoleic acid; S = stearic acid; O = oleic acid; L = linoleic acid.
      ECN
      ECN = equivalent carbon number of TG.
      CN
      CN = acyl carbon number of TG.
      DB
      DB = double-bond number of TG.
      Sampling city
      Zhengzhou (n = 30)Wuhan (n = 30)Harbin (n = 30)
      PLaBu323200.01 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.01 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      ND
      ND = not detected.
      MMBu323200.01 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      ND
      LaOBu323410.01 ± 0.00NDND
      LaLaCa343400.12 ± 0.05
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.05 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.05 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      LaMC343400.01 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.01 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.01 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PMBu343400.01 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.01 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      ND
      LCaC323620.04 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      BuOM343610.01 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.01 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      ND
      SMBu383800.01 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.01 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PLaC363600.02 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.01 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.01 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PBuL343820.11 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.08 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.08 ± 0.04
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      LaCaL364020.02 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.01 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.01 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      LaOC363810.07 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.03 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      OCaCa363810.10 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.05 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.05 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      POBu363810.11 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.05 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.05 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      MLaLa383802.21 ± 0.79
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.98 ± 0.03
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.41 ± 0.22
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PMC383800.03 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.01 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.01 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PPCp383800.03 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PSBu383800.02 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.01 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      BuOL344030.09 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.04 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.05 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      BuOO364020.11 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.05 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.05 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      POCp384010.11 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.06 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.04 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      OLaCa384010.58 ± 0.13
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.31 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.28 ± 0.05
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      OCM384010.05 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      LaMM404001.87 ± 0.63
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.10 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.04 ± 0.24
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PPC404000.04 ± 0.020.02 ± 0.010.02 ± 0.00
      PLC384220.09 ± 0.03
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.05 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.05 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      OOCp384220.02 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      LaLaO404211.87 ± 0.43
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.10 ± 0.08
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.84 ± 0.12
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      POC404210.20 ± 0.04
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.09 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.09 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PMLa424200.78 ± 0.23
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.42 ± 0.03
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.58 ± 0.11
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PPCa424200.30 ± 0.05
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.19 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.28 ± 0.03
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      LLC364440.04 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      LOC384430.21 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.13 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.13 ± 0.03
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      MLLa404421.16 ± 0.25
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.82 ± 0.11
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.74 ± 0.06
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PLCa404421.27 ± 0.09
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.96 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.94 ± 0.08
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      POCa424411.10 ± 0.06
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.78 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.90 ± 0.05
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      MLaO424411.03 ± 0.21
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.67 ± 0.07
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.68 ± 0.09
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PMM444401.09 ± 0.24
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.68 ± 0.06
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.83 ± 0.15
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PPLa444401.34 ± 0.22
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.91 ± 0.06
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.23 ± 0.16
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PSCa444400.24 ± 0.03
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.18 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.28 ± 0.03
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      LLCa384640.71 ± 0.05
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.65 ± 0.04
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.53 ± 0.10
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PLLa424621.95 ± 0.16
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.64 ± 0.22
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.55 ± 0.09
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      OOCa424620.51 ± 0.03
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.40 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.28 ± 0.14
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      MMO444611.41 ± 0.34
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.16 ± 0.18
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.23 ± 0.20
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      POLa444612.68 ± 0.19
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      2.08 ± 0.21
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      2.13 ± 0.45
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      SOCa444610.12 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.10 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.11 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PPM464600.72 ± 0.13
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.54 ± 0.03
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.67 ± 0.13
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      SPLa464600.43 ± 0.06
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.34 ± 0.03
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.48 ± 0.07
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      LLLa404840.01 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.01 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      LOLa424832.57 ± 0.12
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      2.53 ± 0.38
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.86 ± 0.17
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      MOPo444823.20 ± 0.14
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      2.77 ± 0.22
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      2.42 ± 0.15
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PML444820.87 ± 0.05
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.81 ± 0.13
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.85 ± 0.08
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      LaOO444821.41 ± 0.10
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.25 ± 0.09
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.15 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      POM464811.32 ± 0.09
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.12 ± 0.06
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.42 ± 0.14
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PPP484801.34 ± 0.06
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.21 ± 0.08
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.81 ± 0.33
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      SPM484800.19 ± 0.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.17 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.23 ± 0.04
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      LLM425041.25 ± 0.08
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.46 ± 0.27
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.04 ± 0.06
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      MOL445033.85 ± 0.18
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      3.66 ± 1.25
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      3.31 ± 0.17
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PLPo445031.36 ± 0.32
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.16 ± 0.12
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.39 ± 0.17
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PPL465021.93 ± 0.10
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      2.04 ± 0.05
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      2.45 ± 0.28
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PPoO465020.86 ± 0.16
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.71 ± 0.08
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.93 ± 0.08
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      MOO465020.97 ± 0.07
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.97 ± 0.07
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.91 ± 0.09
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PPO485014.57 ± 0.22
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      4.48 ± 0.19
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      5.98 ± 0.78
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PPS505000.30 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.30 ± 0.04
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.48 ± 0.12
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      MSS505000.02 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PoLL425250.79 ± 0.16
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.90 ± 0.05
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.89 ± 0.19
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PLL445246.56 ± 0.81
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      8.22 ± 0.10
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      7.38 ± 0.65
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      OPL4652316.55 ± 1.42
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      19.20 ± 1.24
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      18.67 ± 1.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      OPO4852210.08 ± 0.67
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      10.22 ± 1.04
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      12.03 ± 0.60
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      POS505210.97 ± 0.05
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.03 ± 0.14
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      1.43 ± 0.34
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      PSS525200.02 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.02 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      LLL425461.91 ± 0.20
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      2.96 ± 0.19
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      2.17 ± 0.48
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      OLL445454.28 ± 0.59
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      5.97 ± 0.27
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      4.55 ± 0.58
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      OOL465444.83 ± 0.46
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      5.66 ± 0.22
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      4.92 ± 0.48
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      OOO485432.98 ± 0.33
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      3.42 ± 0.32
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      3.16 ± 0.25
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      SOO505420.40 ± 0.09
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.49 ± 0.08
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.53 ± 0.11
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      SSO525410.05 ± 0.00
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.05 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      0.06 ± 0.01
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      a–c Different superscript letters indicate significant differences (P < 0.05) within a row.
      1 TG names do not indicate positional location of fatty acids in the triacylglycerols. Bu = butyric acid; Cp = caproic acid; C = caprylic acid; Ca = capric acid; La = lauric acid; M = myristic acid; P = palmitic acid; Po = palmitoleic acid; S = stearic acid; O = oleic acid; L = linoleic acid.
      2 ECN = equivalent carbon number of TG.
      3 CN = acyl carbon number of TG.
      4 DB = double-bond number of TG.
      5 ND = not detected.

      Regioisomers of OPL, OPO, PPO, and LaOO

      Optimization of Silver Ion HPLC Conditions

      In human milk, the regioisomers of OPO and PPO are usually separated using silver ion chromatography (
      • Zou X.Q.
      • Huang J.H.
      • Jin Q.Z.
      • Guo Z.
      • Liu Y.F.
      • Cheong L.Z.
      • Xu X.B.
      • Wang X.G.
      Model for human milk fat substitute evaluation based on triacylglycerol composition profile.
      ), but the regioisomers of OPL, which is most abundant in Chinese human milk, have not been separated and analyzed by silver ion chromatography. Although the relative ratios of regioisomers of TG can be calculated based on the relative abundance of ion fragments produced by MS/MS product ion scan (
      • Kallio H.
      • Nylund M.
      • Bostrom P.
      • Yang B.
      Triacylglycerol regioisomers in human milk resolved with an algorithmic novel electrospray ionization tandem mass spectrometry method.
      ), this method is limited by the high number of specific reference compounds required. At the same time, TG possesses the same molecular weight, but esterified with different fatty acids, and the same fragment ions may also be produced by MS/MS product ion scan. For example, LaLaO and POC produce the same [DG]+ 439.4 and different [DG]+ 521.5, [DG]+ 577.5, and 465.4, respectively. In this situation, depending only on ion fragment calculation to determine regioisomers was inaccurate. In human milk, lauric acid is the main medium-chain fatty acid and is usually supplemented in infant formulas, due to its rapid digestion and fast energy supplement (
      • Mu H.
      • Høy C.E.
      Effects of different medium-chain fatty acids on intestinal absorption of structured triacylglycerols.
      ;
      • Sun C.
      • Zou X.Q.
      • Yao Y.P.
      • Jin J.
      • Xia Y.
      • Huang J.H.
      • Jin Q.Z.
      • Wang X.G.
      Evaluation of fatty acid composition in commercial infant formulas on the Chinese market: A comparative study based on fat source and stage.
      ). In our study LaOO was also the main TG (>1%), and it has high contents reported in other literature results (>4%;
      • Zou X.Q.
      • Huang J.H.
      • Jin Q.Z.
      • Guo Z.
      • Liu Y.F.
      • Cheong L.Z.
      • Xu X.B.
      • Wang X.G.
      Lipid composition analysis of milk fats from different mammalian species: Potential for use as human milk fat substitutes.
      ;
      • Ten-Doménech I.
      • Beltrán-Iturat E.
      • Herrero-Martínez J.M.
      • Sancho-Llopis J.V.
      • Simó-Alfonso E.F.
      Triacylglycerol analysis in human milk and other mammalian species: Small-scale sample preparation, characterization, and statistical classification using HPLC-ELSD profiles.
      ;
      • Sun C.
      • Wei W.
      • Zou X.
      • Huang J.
      • Jin Q.
      • Wang X.
      Evaluation of triacylglycerol composition in commercial infant formulas on the Chinese market: A comparative study based on fat source and stage.
      ). Therefore, we selected the regioisomers of OPL, OPO, PPO, and LaOO to analyze via silver ion chromatography.
      To best separation the regioisomers of PPO (rac-PPO/rac-POP), OPO (rac-OPO/rac-OOP), LaOO (rac-LaOO/rac-OLaO), and OPL (rac-OPL/rac-POL/rac-PLO), optimization chromatographic conditions of the silver ion column were performed on HPLC-ELSD equipment. It has been reported that, compared with a hexane-acetonitrile system, a hexane-2-propanol system can yield much better reproducibility of retention time for TG regioisomers, because 2-propanol possesses a higher mutual miscibility with hexane than acetonitrile (
      • Holčapek M.
      • Dvořáková H.
      • Lísa M.
      • Girón A.J.
      • Sandra P.
      • Cvačka J.
      Regioisomeric analysis of triacylglycerols using silver-ion liquid chromatography-atmospheric pressure chemical ionization mass spectrometry: comparison of five different mass analyzers.
      ). In our study the hexane-2-propanol system was selected as the mobile phase. To precision-regulate the concentrations of 2-propanol, the mobile phase was prepared with 2 solvents, where A was hexane and B was a mixture of hexane and 2-propanol (99:2). The mobile phase gradients 20% A + 80% B, 60% A + 40% B, 65% A + 35% B, and 60% A + 30% B were used to determine optimal gradient composition, at a flow rate of 0.5 mL/min and a column temperature of 30°C. The results showed that decreasing the percentage of mobile phase B resulted in higher chromatographic resolution and longer retention time (Supplemental Figure S1; https://doi.org/10.3168/jds.2019-17353). The mobile phase gradient of 65% A + 35% B was selected to determine the effects of column temperature (20°C, 30°C, or 40°C) and flow rate (0.3 mL/min, 0.5 mL/min, or 1 mL/min) on the resolution of regioisomers. The change of flow rate can also strongly influence the chromatographic resolution of regioisomers and retention times. With increasing flow rate, chromatographic resolution decreased, and shorter retention times appeared (Supplemental Figure S2; https://doi.org/10.3168/jds.2019-17353). The column temperature had a slight effect on the chromatographic resolution and retention time. The increase of column temperature from 20°C to 40°C resulted in increased retention time of PPO, OPO, and LaOO. Although the retention times of OPL at 20°C and 40°C were longer than at 30°C, chromatographic resolution showed no obvious change (Supplemental Figure S3; https://doi.org/10.3168/jds.2019-17353). The best separation of individual isomers is achieved at 30°C. It has been reported that increasing the silver ion column temperature results in significantly increased retention time of TG (
      • Adlof R.
      • List G.
      Analysis of triglyceride isomers by silver-ion high-performance liquid chromatography. Effect of column temperature on retention times.
      ). Finally, chromatographic conditions were as follows: 0–20 min 70% A + 30% B, 20–21 min, 70–57% A + 30–43% B, 21–45 min 57% A + 43% B, where A was hexane, B was the mixture of hexane-2-propanol (98:2, vol/vol), with a flow rate of 0.5 mL/min, injection volume of 5 µL, and column temperature of 30°C. Good reproducibility of retention time was obtained under these chromatographic conditions, as the relative SD of retention times were 0.32, 0.34, 0.45, 0.47, 0.51, 0.74, 0.77, and 0.83% for 5 consecutive injections in the first day measurements and 0.65, 0.67, 1.13, 1.16, 1.27, 1.28, 1.51, and 1.76% for 5 consecutive injection in the second day measurements, respectively (Supplemental Figure S4; https://doi.org/10.3168/jds.2019-17353).
      It was observed that the regioisomers of rac-POP/rac-OOP, rac-OPO/rac-OOP, rac-LaOO/rac-OLaO, and rac-OPL/rac-POL/rac-PLO can be separated with each other, but a strong overlap appeared between rac-OPO and rac-LaOO (Figure 2a). Coinstantaneous separation of rac-PPO, rac-POP, rac-POO, rac-OPO, rac-LaOO and rac-OLaO, rac-POL, rac-PLO, and rac-OPL by silver ion chromatography only may take a very long time. It is well known that APCI-MS can identify TG based on [M+H]+ and [DG]+ ions in a strong nonpolar environment (
      • Lísa M.
      • Velínská H.
      • Holčapek M.
      Regioisomeric characterization of triacylglycerols using silver-ion HPLC/MS and randomization synthesis of standards.
      ). Thus, we replaced ELSD detector with APCI-MS to analyze regioisomers of TG in human milk samples. The results in Figure 2 b and c show that APCI-MS can distinguish well between rac-OPO and rac-LaOO by extracted ion chromatogram. Therefore, HPLC APCI-MS was finally used to identify the regioisomers of PPO (rac-PPO/rac-POP), OPO (rac-OPO/rac-OOP), LaOO (rac-LaOO/rac-OLaO), and OPL (rac-OPL/rac-POL/rac-PLO), with chromatographic conditions as described earlier.
      Figure thumbnail gr2
      Figure 2Silver ion HPLC atmospheric pressure chemical ionization-MS analysis of triglyceride (TG) standards. (a) Total ion chromatogram of TG in the regioisomers of PPO (rac-PPO/rac-POP), oleoyl-palmitoyl-oleoylglycerol (OPO; rac-OPO/rac-OOP), lauroyl-oleoyl-oleoylglycerol (LaOO; rac-LaOO/rac-OLaO), and POL [rac-oleoyl-palmitoyl-linoleoylglycerol (OPL)/rac-POL/rac-PLO]. (b) Extract ion chromatogram of rac-OOP and rac-OPO. (c) Extract ion chromatogram of rac-LaOO and rac-OLaO.

      Regioisomers of PPO, OPO, LaOO, and OPL in Human Milk

      The relative ratios of TG regioisomers are important to the digestion and absorption of human milk fat in infants, for the specific lipase selectivity in infant digestive system. In human milk, palmitic acid esterified at sn-2 position is associated with improved bone strength, increased fecal bifidobacteria, and reduced crying in infants (
      • Miles E.A.
      • Calder P.C.
      The influence of the position of palmitate in infant formula triacylglycerols on health outcomes.
      ). The regioisomers of PPO (rac-PPO/rac-POP), OPO (rac-OPO/rac-OOP), LaOO (rac-LaOO/rac-OLaO), and OPL (rac-OPL/rac-POL/rac-PLO) in human milk from Zhengzhou, Wuhan, and Harbin were analyzed by 2-dimensional chromatography of reverse-phase and silver ion HPLC combined with APCI-MS. Two-dimensional HPLC in online or offline mode is a practical method to analyze isomers in complex samples, especially in milk samples, which can effectively avoid the distraction of other TG. It is observed that the relative ratios of regioisomers of PPO (rac-PPO/rac-POP), OPO (rac-OPO/rac-OOP), LaOO (rac-LaOO/rac-OLaO), and OPL (rac-OPL/rac-POL/rac-PLO) can be well obtained by extracted ion chromatogram (Figure 3). The relative ratios of regioisomers of OPO, PPO, and OPL also illustrate the important role of sn-2 position palmitic acid. The results showed that in human milk, the main regioisomers of PPO, OPO, and OPL were rac-PPO, rac-OPO, and racc-OPL, respectively (Table 2). The relative ratios of regioisomers of PPO (rac-PPO/rac-POP) in human milk from the 3 studied regions had no statistical differences. In Zhengzhou, Wuhan, and Harbin, the relative ratios of rac-PPO were 93.92, 94.41, and 93.81%, respectively, and rac-POP were 6.08, 5.59, and 6.19%, respectively. The regioisomers of OPL (rac-OPL and rac-POL) also showed no obvious differences among human milk from the 3 regions. In the 3 regions, the relative ratios of rac-OPL were 90.59, 86.63, and 85.59%, respectively, and those of rac-POL were 4.22, 6.06, and 6.66%, respectively. The contents of rac-PLO (5.19%) in Zhengzhou human milk were lower than those in milk from Wuhan and Harbin, 7.30 and 7.75%, respectively. In the case of the regioisomers of OPO, human milk from Zhengzhou possessed higher rac-OPO (88.46%) than Harbin (84.65%) and Wuhan (86.65%). The relative ratios of rac-OPO and rac-OPL occupied above 85% of OPO and OPL, respectively, the 2 most abundant TG in human milk. This phenomenon revealed that, besides rac-OPO, rac-OPL should also be prepared and added to infant formulas. The main regioisomer of LaOO is rac-OLaO, the relative ratios of which in Zhengzhou, Wuhan, and Harbin were 73.40, 71.95, and 74.97%, respectively. Results in other literature have also reported most lauric acid at sn-2 position of TG in human milk (
      • Kallio H.
      • Nylund M.
      • Bostrom P.
      • Yang B.
      Triacylglycerol regioisomers in human milk resolved with an algorithmic novel electrospray ionization tandem mass spectrometry method.
      ).
      Figure thumbnail gr3
      Figure 3Silver ion HPLC atmospheric pressure chemical ionization-MS analysis of human milk regioisomers. (a) Total ion chromatogram of triglycerides in the regioisomers of PPO (rac-PPO/rac-POP), oleoyl-palmitoyl-oleoylglycerol (OPO; rac-OPO/rac-OOP), lauroyl-oleoyl-oleoylglycerol (LaOO; rac-LaOO/rac-OLaO), and OPL (rac-OPL/rac-POL/rac-PLO). (b) Extract ion chromatogram of rac-POP and rac-PPO. (c) Extract ion chromatogram of rac-OOP and rac-OPO. (d) Extract ion chromatogram of rac-lauroyl-oleoyl-oleoylglycerol (LaOO) and rac-OLaO. (e) Extract ion chromatogram of rac-PLO, rac-POL and rac-OPL.
      Table 2Relative ratios of regioisomers of OPO, PPO, LaOO, and OPL in human milk from 3 cities in China (values given as mean ± SD)
      TG
      TG = triglycerides. Names do not indicate positional location of fatty acids in the triacylglycerols. La = lauric acid; P = palmitic acid; L = linoleic acid; O = oleic acid.
      RegioisomersRelative ratio (%)
      Zhengzhou (n = 30)Wuhan (n = 30)Harbin (n = 30)
      POPrac-POP6.08 ± 0.88
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      5.59 ± 0.98
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      6.19 ± 2.29
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      rac-PPO93.92 ± 0.88
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      94.41 ± 0.98
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      93.81 ± 2.29
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      LaOOrac-LaOO26.60 ± 1.88
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      28.05 ± 4.52
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      25.03 ± 2.62
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      rac-OLaO73.40 ± 1.88
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      71.95 ± 4.52
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      74.97 ± 2.62
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      POOrac-OOP11.54 ± 0.51
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      13.64 ± 2.57
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      14.35 ± 1.11
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      rac-OPO88.46 ± 0.51
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      86.36 ± 2.57
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      85.65 ± 1.11
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      POLrac-PLO5.19 ± 1.02
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      7.30 ± 0.19
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      7.75 ± 1.09
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      rac-POL4.22 ± 1.23
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      6.06 ± 1.84
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      6.66 ± 3.56
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      rac-OPL90.59 ± 2.09
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      86.63 ± 1.73
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      85.59 ± 4.63
      Different superscript letters indicate significant differences (P < 0.05) within a row.
      a,b Different superscript letters indicate significant differences (P < 0.05) within a row.
      1 TG = triglycerides. Names do not indicate positional location of fatty acids in the triacylglycerols. La = lauric acid; P = palmitic acid; L = linoleic acid; O = oleic acid.

      Enantiomer Pairs of Rac-OPL

      Optimization of Chiral HPLC Conditions

      The most important ABC type of TG in human milk, OPL has not only regioisomers but enantiomers. In infants' digestion systems, HGL may be the only lipase that has sn-3 stereoselectivity (
      • Roman C.
      • Carriere F.
      • Villeneuve P.
      • Pina M.
      • Millet V.
      • Simeoni U.
      • Sarles J.
      Quantitative and qualitative study of gastric lipolysis in premature infants: Do MCT-enriched infant formulas improve fat digestion?.
      ). The limited hydrolysis of milk TG by HGL could trigger the activity of bile salt-stimulated lipase and pancreatic lipase-related protein 2 (
      • Bernbäck S.
      • Bläckberg L.
      • Hernell O.
      The complete digestion of human milk triglycerol in vitro requires gastric lipase, pancreatic colipase-dependent lipase, and bile salt-stimulated lipase.
      ). Thus, we also analyzed the enantiomers of OPL. A chiral HPLC column packed with cellulose-tris-3,5-dimethylphenylcarbamate was used for separation of the enantiomers of rac-OPL, rac-POL, and rac-PLO. The selection of mobile phase composition was based on the literature results of
      • Lísa M.
      • Holčapek M.
      Characterization of triacylglycerol enantiomers using chiral HPLC/APCI-MS and synthesis of enantiomeric triacylglycerols.
      , who reported that hexane-2-propanol was a better mobile phase system for separation TG enantiomers compared with hexane-acetonitrile-2-propanol and hexane-acetonitrile mixtures, which can separate enantiomeric pairs with 1 to 3 DB. But the isomers of OPL were not separated in their experiments. Therefore, new chromatographic conditions should be optimized to determine the enantiomers of rac-OPL, rac-PLO and rac-POL in human milk. The mobile chiral phase was composed of hexane (A) and a mixture of hexane:2-propanol, 99:1 (B). The standard of rac-OPL was first eluted with mobile phase compositions of 40% A + 60% B, 50% A + 50% B, 75% A + 25% B, and 90% A + 10% B, respectively, at a column temperature of 30°C and a flow rate of 0.5 mL/min. The results showed that increasing the concentrations of 2-propanol resulted in shortened retention time and lower chromatographic resolution of enantiomeric pairs (Supplemental Figure S5; https://doi.org/10.3168/jds.2019-17353). Then the standards of rac-PLO and rac-POL, and the mixture of rac-OPL/rac-PLO/rac-POL, were eluted with a mobile phase composition of 90% A + 10% B, at a column temperature of 30°C and a flow rate of 0.5 mL/min. It has been observed that the enantiomeric pairs of rac-OPL and rac-PLO can be separated into 2 enantiomers, rac-OPL1/rac-OPL2 and rac-PLO1/rac-PLO 2, respectively (Figure 4a, b). But rac-POL cannot be separated at all (Figure 4c). The mixture of rac-OPL/rac-PLO/rac-POL appeared strongly overlapped and was very difficult to simultaneously separate into 6 enantiomers (Figure 4d). Therefore, the enantiomers of rac-OPL, rac-PLO, and rac-POL were considered to separate respectively. Flow rate and column temperature were also valid factors affecting resolution of enantiomeric pairs. In our study, rac-OPL was selected to determine the optimal column temperature and flow rate. The results showed that increasing column temperature and flow rate caused shortened retention time and lower chromatographic resolution of enantiomeric pairs (Supplemental Figure S6–S7; https://doi.org/10.3168/jds.2019-17353). Thus, column temperature and flow rate were set to 30°C and 0.5 mL/min, respectively. Separation of TG enantiomers is mainly based on DB numbers, and the DB numbers of outer position (sn-1 and sn-3) esterified fatty acyls had no significant influence by fatty acyl in sn-2 position (
      • Lísa M.
      • Holčapek M.
      Characterization of triacylglycerol enantiomers using chiral HPLC/APCI-MS and synthesis of enantiomeric triacylglycerols.
      ;
      • Řezanka T.
      • Kolouchová I.
      • Čejková A.
      • Cajthaml T.
      • Sigler K.
      Identification of regioisomers and enantiomers of triacylglycerols in different yeasts using reversed- and chiral-phase LC-MS.
      ;
      • Řezanka T.
      • Sigler K.
      Separation of enantiomeric triacylglycerols by chiral-phase HPLC.
      ). Palmitic acid, linoleic acid, and oleic acid, containing similar chain length and low DB numbers, may be responsible for the overlap of rac-OPL, rac-PLO, and rac-POL. Thus, it is a challenge to separate OPL into 6 isomers (regio- and enantio-isomers). The results for rac-POL, having combinations of saturated and di-unsaturated fatty acyls in the sn-1 and sn-3 positions, not separated into 2 enantiomer pairs, were same as the results reported by
      • Lísa M.
      • Holčapek M.
      Characterization of triacylglycerol enantiomers using chiral HPLC/APCI-MS and synthesis of enantiomeric triacylglycerols.
      . Optimization conditions were determined for chromatographic resolution of rac-OPL and rac-PLO enantiomeric pairs, respectively. The final method was as described previously. The reproducibility of rac-OPL1 and rac-OPL2 retention times was determined. Relative SD of retention times under final chromatographic conditions were 0.44 and 0.46% for 1-d measurements and 1.11 and 1.32% for 2-d measurements, demonstrating good reproducibility (Supplemental Figure S8; https://doi.org/10.3168/jds.2019-17353).
      Figure thumbnail gr4
      Figure 4Chiral HPLC evaporative light-scattering detector analysis of enantiomers of 1-oleoyl-2-palmitoyl-3-linoleoylglycerol (OPL). (a) Enantiomer pairs of rac-OPL (rac-OPL1 and rac-OPL2). (b) Enantiomers pairs of rac-PLO (rac-PLO1 and rac-PLO2). (c) Rac-POL. (d) The mixture of rac-OPL, rac-PLO, and rac-POL. LSU = light scattering units.

      Enantiomer Pairs of Rac-OPL in Human Milk

      The main regioisomer of OPL-TG in human milk was rac-OPL (above 85%). Therefore, only enantiomer pairs of rac-OPL were really determined in the human milk samples, because the contents of rac-PLO were too low and difficult to collect, and rac-POL failed to separate into 2 enantiomer pairs. To avoid interference of other TG, enantiomer pairs of rac-OPL (rac-OPL1 and rac-OPL2) in human milk were analyzed using chiral HPLC APCI-MS, with chromatographic conditions as described earlier. The results showed that the ion chromatogram of rac-OPL enantiomer pairs (rac-OPL1 and rac-OPL2) can be well extracted from the total ion chromatogram of human milk samples (Figure 5a, b). The results also showed that the 2 enantiomer pairs of rac-OPL in human milk were not equally distributed. In Zhengzhou, Wuhan, and Harbin human milk, the relative ratios of rac-OPL1 were 38.14, 35.28, and 37.81%, respectively, and the relative ratios of rac-OPL2 were 61.86, 64.72, and 62.70%, respectively (Figure 5c). There were no statistical differences among the 3 cities. In infants, about 10 to 30% of dietary lipids are first digested by gastric lipase, which specifically hydrolyzes the sn-3 position of TG (
      • Bourlieu C.
      • Menard O.
      • Bouzerzour K.
      • Mandalari G.
      • Macierzanka A.
      • Mackie A.R.
      • Dupont D.
      Specificity of infant digestive conditions: some clues for developing relevant in vitro models.
      ). The expression of pancreatic lipase is very different between adults and infants. In adults, small intestine lipid digestion is mainly performed by colipase-dependent PTL. In infants, the expression level of PTL is only 3% that of adults. The immaturity of PTL is compensated by pancreatic lipase-related protein 2 and bile salt-stimulated lipase (
      • Andersson E.-L.
      • Hernell O.
      • Bläckberg L.
      • Fält H.
      • Lindquist S.
      BSSL and PLRP2: Key enzymes for lipid digestion in the newborn examined using the Caco-2 cell line.
      ;
      • Bourlieu C.
      • Menard O.
      • Bouzerzour K.
      • Mandalari G.
      • Macierzanka A.
      • Mackie A.R.
      • Dupont D.
      Specificity of infant digestive conditions: some clues for developing relevant in vitro models.
      ;
      • Casper C.
      • Carnielli V.P.
      • Hascoet J.M.
      • Lapillonne A.
      • Maggio L.
      • Timdahl K.
      • Olsson B.
      • Vågerö M.
      • Hernell O.
      rhBSSL improves growth and LCPUFA absorption in preterm infants fed formula or pasteurized breast milk.
      ). It has been reported that limited gastric hydrolysis of long-chain fatty acids plays a major role in the subsequent TG digestion by pancreatic lipase (
      • Bernbäck S.
      • Bläckberg L.
      • Hernell O.
      Fatty acids generated by gastric lipase promote human milk tricylglycerol digestion by pancreatic colipase-dependent lipase.
      ;
      • Bernbäck S.
      • Bläckberg L.
      • Hernell O.
      The complete digestion of human milk triglycerol in vitro requires gastric lipase, pancreatic colipase-dependent lipase, and bile salt-stimulated lipase.
      ;
      • Johnson K.
      • Ross L.
      • Miller R.
      • Xiao X.
      • Lowe M.E.
      Pancreatic lipase-related protein 2 digests fats in human milk and formula in concert with gastric lipase and carboxyl ester lipase.
      ). A hypothesis may be put forward that the unequal distribution of enantiomers pairs of rac-OPL may have important effects on lipid digestion in infants.
      Figure thumbnail gr5
      Figure 5Chiral HPLC atmospheric pressure chemical ionization-MS analysis enantiomer pairs of rac-OPL (rac-OPL1 and rac-OPL2) in human milk. (a) Total ion chromatogram of enantiomer pairs of rac-OPL. (b) Extract ion chromatogram of enantiomer pairs of rac-OPL. (c) Relative ratios of enantiomers pairs of rac-OPL (rac-OPL1 and rac-OPL2) in human milk from Zhengzhou, Wuhan, and Harbin, China.

      CONCLUSIONS

      In human milk samples from 3 cities in China, Zhengzhou, Wuhan, and Harbin, OPL was the most abundant TG (16.55, 19.20, and 18.67%, respectively), followed by OPO (10.08, 10.22, and 12.03%, respectively). The regioisomers of PPO (rac-PPO/rac-POP), OPO (rac-OPO/rac-OOP), LaOO (rac-LaOO/rac-OLaO), and POL (rac-OPL/rac-POL/rac-PLO) can be well analyzed by silver ion HPLC APCI-MS. The racemic TG of rac-PPO, rac-OPO, rac-OLaO, and rac-OPL were the main regioisomers of POP, OOP, OOLa, and POL, the relative ratios of which ranged from 93.81 to 94.41%, 85.59 to 90.59%, 84.65 to 88.46%, and 71.95 to 74.97%, respectively, in the 3 regions. In the case of the enantiomer pairs of rac-OPL in human milk, the distributions of rac-OPL1 and rac-OPL2 were not the same. In human milk from Zhengzhou, Wuhan, and Harbin, the relative ratios of rac-OPL2 (61.86, 64.72, and 62.70%, respectively) were higher than those of rac-OPL1 (38.14, 35.28, and 37.81%, respectively).

      ACKNOWLEDGMENTS

      This work was financially supported by National Key R & D of China 2018YFC160 4302, the Major Program for the Applied Technology R & D Plan of Heilongjiang Province, China (GA16B201-2). The authors have not stated any conflicts of interest.

      Supplementary Material

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