glucosidase inhibitory activities using 1H N

Metabolite pro fi ling of Neptunia oleracea and correlation with antioxidant and a -glucosidase inhibitory activities using

¹

H NMR- based metabolomics

Soo Yee Lee

^a

, Faridah Abas

^a,b,

*, Al fi Khatib

^a,d

, Intan Sa fi nar Ismail

^a,c

, Khozirah Shaari

^a,c

, Norhasnida Zawawi

^b

aLaboratoryofNaturalProducts,InstituteofBioscience,UniversitiPutraMalaysia,43400Serdang,Selangor,Malaysia

bDepartmentofFoodScience,FacultyofFoodScienceandTechnology,UniversitiPutraMalaysia,43400Serdang,Selangor,Malaysia

cDepartmentofChemistry,FacultyofScience,UniversitiPutraMalaysia,43400UPMSerdang,Selangor,Malaysia

dDepartmentofPharmaceuticalChemistry,FacultyofPharmacy,InternationalIslamicUniversityMalaysia,25200Kuantan,Pahang,Malaysia

ARTICLE INFO

Articlehistory:

Received29December2015

Receivedinrevisedform15February2016 Accepted26February2016

Availableonline3March2016

Keywords:

Neptuniaoleracea

1HNMR Metabolomics

Multivariatedataanalysis(MVDA) Antioxidant

a-Glucosidaseinhibitory

ABSTRACT

Neptunia oleraceaisaplantconsumedasvegetable andusedasatraditional herbtotreat several ailments.ThisstudyevaluatedmetabolitevariationsamongN.oleracealeafandstemsubjectedtoair drying(AD),freezedrying(FD)andovendrying(OD)usingprotonnuclearmagneticresonance(¹HNMR) basedmetabolomics.Thecorrelationwasalsostudiedforthemetabolitecontentwithtotalphenolic content (TPC), DPPH free radical scavenging and a-glucosidase inhibitory activities. A total of 18metaboliteswereidentifiedfromN.oleraceaextracts,including10primarymetabolites,5flavonoids and 3 phenolic acids using NMR. Ultra-high performance liquid chromatography tandem mass spectrometry analysis (UHPLC-MS/MS) confirmedthe presence of the secondary metabolites and revealedtheflavonoidderivativespresent.Alltheidentifiedphenolicsarefirstreportedfromthisplant.

Multivariate data analysis (MVDA) showed strong correlation between the metabolites with the antioxidantanda-glucosidaseinhibitoryactivitiesofFDN.oleracealeaves.Thecompoundssuggestedto beresponsibleforthehighactivityofFDleavesincludevitexin-2-O-rhamnoside,catechin,caffeicacid, gallicacidandderivativesofquercetin,kaempferolandmyricetin.Thisstudydemonstrates thatFD N.oleracealeavesareapotentialnaturalsourceforantioxidantanda-glucosidaseinhibitors.

ã2016PhytochemicalSocietyofEurope.PublishedbyElsevierB.V.Allrightsreserved.

1.Introduction

Neptunia oleracea is a local vegetable in Southeast Asia, particularly in Malaysia, Thailand and Indochina. This plant is alsousedasamedicinalplantforseveraltherapeuticpurposes.The leavesareusedasantipyreticandantidote(Daduangetal.,2011).

Therootsareusedtotreatnecrosisofthenoseandhardpalateand asaremedytocurefever,whereasjuicefromthestemissqueezed intotheeartocureearache(Debetal.,2013).N.oleraceahasbeen reported to exhibit antioxidant, antiulcer, hepatoprotective, antiviral,analgesicandantiinflammatoryactivities(Bhoomanna- varetal.,2011a,2011b;Nakamuraetal.,1996;Pauletal.,2012;

Thalangetal.,2001).Ourpreliminarystudyhasshownthatthis

plantdemonstratespotentantioxidantand

a

-glucosidaseinhibi- tory properties, which may be beneficial for diabetic patients (Lee et al., 2014). Extensive studies on metabolite profile and benefitofthisplantshouldbehenceperformedusingadvanced approaches.

Metabolomics is a versatile tool for evaluating metabolic variations in organisms under certain conditions (Khoo et al., 2015; Kim et al.,2011).Changesin processing proceduresmay affectthemetabolitecompositions.Thisvariationcanbemeasured by a metabolomics approach using certain analytical methods coupledwith multivariatestatistical analysis. Nuclear magnetic resonance(NMR)spectroscopyisoneofthemostcommonlyused analyticaltoolsforplantmetabolomicsapplications.Multivariate data analysis such as principle component analysis (PCA) and partial leastsquares (PLS) areuseful tomanage the huge data generated from NMR analyses and to highlight the potential markersinsamples(Kimetal.,2010).

Metabolomics approach hasbeenapplied in variousscience fields including plant species or varieties classification

* Corresponding author at: Laboratory of Natural Products, Institute of Bioscience, Universiti PutraMalaysia, 43400Serdang, Selangor, Malaysia and DepartmentofFoodScience,FacultyofFoodScienceandTechnology,Universiti PutraMalaysia,43400Serdang,Selangor,Malaysia.

E-mailaddress:faridah_abas@upm.edu.my(F.Abas).

http://dx.doi.org/10.1016/j.phytol.2016.02.014

1874-3900/ã2016PhytochemicalSocietyofEurope.PublishedbyElsevierB.V.Allrightsreserved.

ContentslistsavailableatScienceDirect

Phytochemistry Letters

j o u r n al h o m ep a g e: w w w . el s e v i e r . c o m / l o c at e / p h y to l

(Maulidianietal.,2011),diseasediagnosisandtoxicologystudies (González-Domínguez et al., 2015). However, the use of this approach for differentiating different plant parts and different processingconditionsisseldomreported.Thereisalsoascarceof reportsonphytochemicalconstituentsandbioactivityofdifferent plantpartsandtheeffectofdryingmethods(Chanetal.,2009;

Fernandoetal.,2013;Zahmanovetal.,2015).Inaddition,there havebeennodatabeingpublishedwithregardstodryingeffects onthemetabolitesofdifferentpartsofN.oleracea.Therefore,this studyattempts todifferentiatemetabolicvariationsamong air-, oven-andfreeze-driedextractsofN.oleracealeavesandstemsand correlateit withtheirantioxidantand

a

-glucosidase inhibitory activities using a NMR-based metabolomics approach. The obtained information may help in seeking potential drying methodsforpreservingdesiredmetabolitesandbeneficialvalues ofplants.

2.Resultsanddiscussion

2.1.IdentificationofmetabolitesinN.oleraceaextractsusing1Dand 2DNMR

Examinationofthe¹HNMRspectraoffreeze-,air-andoven- driedN.oleracealeavesandstemsdemonstratedthepresenceof differentclassesofmetabolites.Primarymetaboliteswereidenti- fiedusingtheChenomxdatabase,andsecondarymetaboliteswere identifiedbycomparisonwithliteraturedata,authenticstandards

formetabolitesrunwiththesameparametersand2DNMR.The representative¹HNMRspectraofFDN.oleracealeavesandstems areshowninFig.S1,whiletherepresentative¹HNMRspectraofN.

oleracealeavesfromthreedifferentdryingmethodsareshownin Fig.S2.Theidentificationofmetabolitesbasedon¹HNMRspectra appeared to be challenging due to the problem of signals overlapping. However, the application of 2D J-resolved NMR helped byproviding the information aboutsignal splittingand couplingconstants(Fig.S3).

BasedontheNMRdata,atotalof18metaboliteswereidentified fromN.oleracea extracts.Among thesemetabolites,10primary metabolites,5flavonoidsand3phenolic acidswererecognized.

Theprimarymetabolitesidentifiedincluded

a

^-glucose,

b

^-glucose,

sucrose,fructose,malicacid,choline,fattyacidsandaminoacids.

Theflavonoidsidentifiedwerevitexin-2-O-rhamnoside,catechin, and derivatives of quercetin, kaempferol and myricetin. In addition, gallic acid, 3,4-O-dimethylgallic acid and caffeic acid werethethreephenolic acidsfound.TheN.oleracealeavesand stemsprocessedfromthethreedifferentdryingmethodsexhibited quantitative variation rather than qualitative variation in the metabolitecontentwiththeexceptionofvitexin-2-O-rhamnoside, catechin, caffeic and malic acids, which are not present in the stems.Thechemicalshiftsoftheidentifiedmetabolitesareshown inTable1.

The presence of the identified secondary metabolites was confirmed by UHPLC–MS/MS analysis as shown in Table 2. In addition,identificationoftheflavonoidderivativeswasaidedby

Table1

1HNMRcharacteristicsignalsofidentifiedmetabolitesinN.oleraceaextracts.

Compounds ¹HNMRcharacteristicsignals FD AD OD

Leaf Stem Leaf Stem Leaf Stem

Vitexin-2-O-rhamnoside(1) 0.66(d,J=5.5Hz) + + +

5.08(d,J=1.0Hz) 6.26(s) 6.50(s) 6.99(d,J=8.0Hz) 8.01(d,J=8.5Hz)

Quercetinderivatives(2) 6.29(d,J=2.0Hz) + + + + + +

6.39(d,J=2.0Hz) 6.86(d,J=8.5Hz) 7.66(dd,J=3.0,8.5Hz) 7.73(d,J=2.0Hz)

Kaempferolderivatives(3) 6.51(d,J=2.0Hz) + + + + + +

6.70(d,J=2.0Hz) 7.67(dd,J=2.0,8.5Hz) 7.75(dd,J=3.0,9.0Hz)

Myricetinderivatives(4) 7.05(s) + + + + + +

6.51(d,J=2.0Hz) 6.30(d,J=2.0Hz)

Catechin(5) 7.37(d,J=2.0Hz) + + +

4.61(d,J=8.0Hz) 3.99(m)

Caffeicacid(6) 7.13(d,J=2.0Hz) + + +

6.86(d,J=9.0Hz)

Gallicacid(7) 7.04(s) + + + + + +

7.13(s)

3,4-O-dimethylgallicacid(8) 3.78(s) + + + + + +

7.04(s) 7.13(s)

b^{-glucose(9) 4.61(d,J=8.0Hz) + + + + + +}

a^{-glucose(10) 5.19(d,J=3.5Hz) + + + + + +}

Sucrose(11) 5.42(d,J=4.0Hz) + + + + + +

Fructose(12) 4.16(d,J=8.6Hz) + + + + + +

Fattyacids(13) 1.35(m) + + + + + +

Alanine(14) 1.49(d,J=7.5Hz) + + + + + +

Leucine(15) 0.94(d,J=6.5Hz) + + + + + +

Valine(16) 0.99(d,J=6.5Hz) + + + + + +

Choline(17) 3.19(s) + + + + + +

Malicacid(18) 4.26(dd,J=3.0,9.0Hz) +

UHPLC–MS/MSanalysisaswell.UHPLC–MS/MSdatarevealedthe presenceofmyricetin-3-O-glucoside,myricetin-3-O-rhamnoside, quercetin-3-O-glucoside,quercetin-3-O-arabinoside,quercetin-3- O-rhamnoside, quercetin, rutin, kaempferol-3-O-glucoside and kaempferol-3-O-rhamnoside.Althoughapreviousstudyreported thepresenceofflavonoidgroupsinN.oleracea,thespecificationof thesecompoundsremainedunidentified(Vijayashreeetal.,2006).

Hence,to thebest of ourknowledge,all of theflavonoids and phenolicacidsidentifiedinthisstudyarereportedforthefirsttime forthisplant.

2.2.ClassificationofdriedleavesandstemsbyPCA

ThemetabolitevariationamongtheFD,ADandODleavesand stemswasfurtherevaluatedusingMVDA.PCAisanunsupervised clusteringmethod that provides a primary understandingwith regardstotherelationshipbetweensamplesstudied.PCAscore plotsshowtheseparationofsamplesintoclusters,whileloading plotshighlightthemetabolitesthatcontributetotheseparation.In thisstudy,¹HNMRdatasetwassubjectedtoPCAtounderstandthe clusteringcharacteristicoftheFD,ADandODleavesandstemsand todeterminethecompoundsresponsiblefortheirdiscrimination.

Theresultedmodelshowed goodfitnessandhighpredictability withR²X=0.952and Q²=0.899,respectively. Leaves and stems fromthethreedryingmethodswereseparatedintofourclusters

withnonotableoutliers(Fig.1).PC1contributedto34.2%ofthe variancefollowedbyPC2,whichcontributedto27.1%.Hence,the firsttwoPCsexhibitedatotalvarianceof61.3%.Itwasobviousthat theFDleavesandstemswerewelldiscriminatedfromtheother samples.

Tomoreclearlyobservethediscriminationofthedifferentparts andthedifferentdryingmethods,twodifferentPCAanalyseswere performed.Fig.2showsthescoreandloadingplotsof¹HNMRdata representing leaves and stems of FD N. oleracea (R²X=0.966, Q²=0.916).Thescoreplot(Fig.2A)showsthattheleavesandstems werewellseparatedintotwoclustersbyPC1,whichcontributed 87.7% of the variance. The loading column plot shows the metabolites that caused the separation of leaves and stems.

AccordingtotheloadingcolumnplotofPC1(Fig.2B),flavonoids andphenolicacidswerenoticeablyresponsiblefordiscrimination oftheleaffromstemextracts.Vitexin-2-O-rhamnoside,catechin, caffeicacid,gallicacidandderivativesofquercetin, kaempferol, andmyricetincontentswerehigherinleavesastheywerelocated inthenegativesideoftheplot.Thiswasfurtherconfirmedbythe results of relative quantification (Fig. 4A). In addition, the intensitiesofmalicacid,choline,fattyacidsandaminoacidswere higherinleaves.Asforstems,sugarswerethemainmetabolites that caused its separation from the leaves. The

a

^-glucose,

b

^{-glucose, sucroseand fructose weremarkedly higherin stem,}

whichwasfurtherobservedintherelativequantification(Fig.4A) Table2

ListofmetabolitesidentifiedinN.oleraceaextractsbasedonLC–MS/MSdata.

Retentiontime(min) (M-H) MS²fragments Tentativecompounds

1.22 132.8667 115.0025,71.0126 Malicacid

3.16 289.0717 245.0816,203.0707,179.0341,137.0234,125.0233 Catechin

3.68 178.9768 134.9868,115.7767,90.9968 Caffeicacid

5.09 197.0448 197.0448,169.0134,125.0232 3,4-O-dimethylgallicacid

5.78 479.0788 316.0222,287.0182,271.0251 Myricetin-3-O-glucoside

6.98 609.1463 300.0274,271.0242,255.0298,178.9977 Rutin

7.10 463.0881 316.0222,301.0356,271.0245,255.0290,151.0025 Myricetin-3-O-rhamnoside

7.29 577.1564 457.1142,413.0877,311.0560,293.0455 Vitexin-2-O-rhamnoside

7.47 463.0883 300.0273,271.0246,255.0296,178.9977 Quercetin-3-O-glucoside

7.87 433.0773 300.0273,271.0246,255.0298,178.9977,151.0026 Quercetin-3-O-arabinoside

8.11 447.0931 284.0326,255.0297,227.0345,178.9978,151.0027 Kaempferol-3-O-glucoside

8.38 447.0932 300.0273,271.0246,255.0296,178.9977,151.0025 Quercetin-3-O-rhamnoside

9.41 431.0978 284.0324,255.0295,227.0346,178.9977 Kaempferol-3-O-rhamnoside

10.01 301.0352 301.0352,273.0406,256.9416,178.9977,151.0026 Quercetin

19.51 169.0133 169.0133,125.0233 Gallicacid

Fig.1.ThePCAscoreplot(PC1vs.PC2)of¹HNMRdatarepresentingallofthedriedN.oleraceamaterials.L,leaf;S,stem;AD,airdrying;FD,freezedrying;OD,ovendrying.

andthismightbeduetotheaccumulationandstorageofsugarsin stem.

In contrast,Fig. 3 showsthePCA score(PC1 vsPC2, A)and loadingcolumn(PC1,BandPC2,C)plotsfordatarepresentingN.

oleracealeavesfromthreedifferentdryingmethods(R²X=0.953, Q²=0.893). Leaves processed with three drying methods were found to be clustered into three groups. The first two PCs cumulativelycontributedto86.6%ofthetotalvarianceinwhich PC1andPC2accountedfor69.4%and17.2%,respectively.FDleaves wereseparatedfromADandODleavesbyPC1,whileADleaves wereseparatedfromtheothersbyPC2.ThePC1loadingcolumn plot(Fig.3B)revealedthatthecompoundsthatcontributedtothe separationoftheFDsamplefromothersampleswereflavonoids andphenolicacids.Vitexin-2-O-rhamnoside, catechin,quercetin derivatives,kaempferolderivatives,myricetinderivatives,caffeic acidandgallicacidwerehigherinFDsamples.Ahighamountof choline,malicacid,

a

^-glucoseand

b

^-glucosealsodistinguishedFD fromother drying methods. The higher concentration of these compoundsinFD compared withADand ODis alsoshownby relativequantification(Fig.4B).Fructose,sucroseandaminoacids wereresponsibleforseparatingADfromFDandOD(Fig.3C).The lossofsugarsignalinNMRdatafromODsampleswaslikelydueto the degradation of sugar by the thermal effect during drying (Mediani et al.,2012). FDwas reported toprovidehigher total amino acids compared with otherdrying methods (Wong and Cheung,2001).However,theeffectsofdryingmethodsondifferent aminoacidsareinconclusive(Korus,2012).Inthisstudy,alanine, leucineandvalinewerefoundtodiscriminateADsamplesfromFD andODsamples,whichmaybeduetothebetterextractabilityof

theseaminoacidsfromADN.oleracea(WongandCheung,2001).A surprisingfindingofthisstudywastheseparationofODsamples fromothersbyfattyacids.Apossiblereasonforthisresultmaybe theliberationoffreefattyacidsfromtriglyceridesduetothehigh temperatureemployedduringtheODprocess.Theincreaseinfree fattyacidsinplantmaterialwithincreaseddryingtemperaturehas beenpreviouslyreported(Guehietal.,2010;Lasisi,2014).

2.3.Effectofdryingmethodsontotalphenoliccontent,DPPHfree radicalscavengingand

a

-glucosidaseinhibitoryactivitiesofdifferent partsofN.oleracea

As shown in Fig. 5, the three different drying methods contributed variation to theTPC, DPPH free radicalscavenging and

a

-glucosidaseinhibitoryactivitiesofthepartsofN.oleracea.

BothleafandstempossessedhighTPC.Whencomparingleaves andstems,therewerenosignificantdifferences(P>0.05)inTPCin allthreedryingmethodswithanexceptiontoOD.Althoughthe TPC of leaf and stem were statistically similar, leaves were observed to contain higher TPC than stem. FD N.oleracea leaf contained327.25

m

^{gGAE/mgextract,whichisslightlyhigherthan}

itsstemwithavalueof316.187

m

^{gGAE/mgextract.Intermsof}

dryingmethod,itwasobviousthatFDhadthehighestTPCvalue comparedwithADand OD.FDtreatedleafcontained327.25

m

^g

GAE/mg extract, followed by AD and OD with TPC values of 226.251and177.264

m

^{gGAE/mgextract,}respectively.

DPPHfreeradicalscavengingactivitywasexaminedtoevaluate the antioxidant activity of dried N. oleracea leaf and stem. N.

oleraceawasfoundtobeastrongfreeradicalscavenger,exhibiting Fig.2. ThePCAscoreplot(PC1vs.PC2,A)andloadingcolumnplotofPC1(B)of¹HNMRdatarepresentingleavesandstemsfromfreeze-driedN.oleracea.1,vitexin-2-O- rhamnoside;2,quercetinderivatives;3,kaempferolderivatives;4,myricetinderivatives;5,catechin;6,caffeicacid;7,gallicacid;9,b-glucose;10,a-glucose;11,sucrose;12, fructose;13,fattyacids;14,alanine;15,leucine;16,valine;17,choline;18,malicacid.L,leaf;S,stem.

IC50valueslessthan30

m

^{g/mL(Abasetal.,2006).Theresultsof}

DPPHfreeradicalscavengingactivityshowedthesametrendas TPC. Leaves and stems exhibited comparably high DPPH free radicalscavengingactivity.Incomparingleafandstem,therewas nosignificant(P>0.05)differenceintheIC50valuesforallthree dryingmethods,exceptforOD.However,theIC50valuesofleaves werelowerthanthatforstem,demonstratinghigheractivityfor leafthanthestem.TheIC50valueforFDleaveswas6.42

m

^g/mL,

whereas that for FD stems was 6.77

m

^{g/mL. In comparing the}

differentdryingmethods,theFDsampleexhibitedthemostpotent DPPHfreeradicalscavengingactivity.TheIC₅₀valueofFDleaves was 6.42

m

^{g/mL, followed by AD leaves with an IC50 value of}

9.72

m

^{g/mLandODleaveswithanIC50valueof12.86}

m

^g/mL.

InadditiontohavinghighTPCandpotentantioxidantactivity viaDPPH freeradicalscavenging,theresults alsodemonstrated thatN.oleraceaexhibitsstrong

a

-glucosidaseinhibitoryactivity.

The IC50 values of all extracts indicated higher activity than quercetin.TheresultsshowedthesametrendwithbothTPCand DPPH free radical scavenging activity. When comparing the differentpartsofN.oleracea,leavesexhibitedstronger

a

^-glucosi-

daseinhibitoryactivitythanstem.However,unliketheresultsof the TPC and the DPPH free radical scavenging activity, the differencebetweenthe

a

-glucosidaseinhibitoryactivityofleaves andstemswassignificant(P<0.05).TheFDleavesexhibitedstrong

a

-glucosidaseinhibitoryactivitywithanIC50valueof0.34

m

^g/mL,

whichissignificantlyhigherthanthatofFDstem,whichhadan IC₅₀valueof0.59

m

^g/mL.Furthermore,theFDsampleexhibitedthe Fig.3.ThePCAscoreplot(PC1vs.PC2,A)andloadingplotofPC1(B)andPC2(C)of¹HNMRdatarepresentingN.oleracealeavesfromthreedifferentdryingmethods.1, vitexin-2-O-rhamnoside;2,quercetinderivatives;3,kaempferolderivatives;4,myricetinderivatives;5,catechin;6,caffeicacid;7,gallicacid;9,b^-glucose;10,a^-glucose;11, sucrose;12,fructose;13,fattyacids;14,alanine;15,leucine;16,valine;17,choline;18,malicacid.AD,airdrying;FD,freezedrying;OD,ovendrying.

highest

a

-glucosidaseinhibitoryactivitycompared withtheAD and OD samples. The IC50 value of FD leaves was 0.34

m

^g/mL,

followed by AD leaves with 0.5

m

^{g/mL and OD leaves with}

0.7

m

^g/mL.

TheseresultsdemonstratedthatFDisthemostsuitablemethod fordryingN.oleraceabecauseitwasabletopreservethehighest amountof phenoliccompoundsand revealedthehighestDPPH freeradicalscavengingand

a

-glucosidaseinhibitoryactivities.The FDabilitytoretainthequalityofdriedsampleswasattributedto thelowtemperatureandtheabsenceofoxygenduringtheentire drying process (Borchani et al., 2011; Lin et al., 2012). Low temperature and absence of oxygen can help prevent the

destructionofvaluablecompoundsduringthedryingprocess.It has been reported that samples subjected to FD had higher antioxidantactivityandhigherconcentrationsofbothhydrophilic and lipophilic antioxidant compounds (Pinela et al., 2011).

Stronger

a

-glucosidaseinhibitoryforFDsamplescomparedwith otherdryingmethodswasalsoreported(Linetal.,2012).

InadditiontotheeffectivenessofFD,theresultsofthisstudy alsoshowedthatN.oleracealeafwasbetterthanitssteminterms ofTPC,DPPHfreeradicalscavengingand

a

-glucosidaseinhibitory activities.Apossibleexplanationforthisfindingisthattheleafis thesiteofthesynthesisandaccumulationofcompounds,which maycontributetobetteractivitiescomparedwithstems(Bennett Fig.4.Relativequantificationofidentifiedcompoundsinleavesandstemsfromfreeze-driedN.oleracea(A)andN.oleracealeavesfromthreedifferentdryingmethods(B) basedonthemeanpeakareaof¹HNMRsignals.Thechemicalshiftsusedforrelativequantificationincludevitexin-2-O-rhamnosideat0.66,quercetinat6.38,kaempferolat 6.70,myricetinat7.06,catechinat7.38,caffeicacidat7.14,gallicacidat7.10,b^{-glucoseat4.62,}a^{-glucoseat5.22,sucroseat5.42,fructoseat4.18,fattyacidsat1.34,alanineat} 1.46,leucineat0.94,valineat0.98,cholineat3.18andmalicacidat4.26.ThedatapresentedaremeansSD.Meanswithdifferentlettersaresignificantlydifferent(P<0.05).

AD,airdrying;FD,freezedrying;OD,ovendrying.

and Wallsgrove,1994).Leaveswere reportedto containhigher totalphenols and flavonoidsand antioxidantactivitycompared with the flower, fruit, pod, root and stem of the same plant (Fernandoetal.,2013).

2.4.Correlationbetweenbioactivityandphytochemicalconstituents usingPLS

Tounderstandtherelationshipbetweenstudiedbioactivities and theeffects of thedrying methods onN.oleracea, PLSas a supervisedMVDAwasapplied.PLSprovidesacorrelationbetween metabolitesandbioactivities;hencemetabolitesplayingrolesas phytochemicalmarkersmaybesuggested.Fig.6showsthebiplot obtainedfromPLSthatexplainthevariationsbetweenAD,FDand ODleavesandstems.Fromthebiplot,fourclusterswereobserved without notable outlier as previously shown by PCA. The FD sampleswereseparatedfromothersbyPC1.Incontrast,stemsand leaveswereseparatedbyPC2.ComparedwithODandADsamples, FD samples were more correlated with TPC, DPPH and

a

-glucosidase inhibitions. OD and AD samples were projected onthenegativesideoftheplot,whichwerefarawayfromtheTPC, DPPHand

a

-glucosidase.ThisshowedthatFDsamplesweremore activethanADandODsamples.Thisconfirmstheresultsofthe bioassays performed, showingthat FD is a valuable method in preservingthephenoliccompoundsandexhibitedthebetterDPPH freeradicalscavengingand

a

-glucosidaseinhibitoryactivities.The vitexin-2-O-rhamnoside,catechin,quercetinderivatives, kaemp- ferol derivatives, myricetin derivatives, caffeic acid, gallic acid,

a

^-glucose,

b

^{-glucose,sucroseandfructosewerelocatedcloserto}

theFDsamplescomparedwithADandODsamples.Theymightbe the compounds responsible for the higher TPC, DPPH and

a

-glucosidaseinhibitionsofFDsamples.

By comparing FD leaves and stems, they were comparably correlatedwithTPCand DPPHinhibition.However,leaveswere found to be more correlated with

a

-glucosidase inhibition, confirmingthebioassayresultsthatshowed thatFDleaves and stemshad nosignificantdifference(P>0.05)forTPC and DPPH inhibition, whileleaves weresignificantly (P<0.05)betterthan Fig.5. Totalphenoliccontent(A),DPPHIC50(B)anda-glucosidaseIC50(C)ofN.oleracealeavesandstemsbydifferentdryingmethods.Thefirstletterreferstocomparison betweendifferentdryingmethodsforthesameparts.Thesecondletterreferstocomparisonsbetweendifferentpartsforthesamedryingmethod.Meanswithdifferent lettersaresignificantlydifferent(P<0.05).AD,airdrying;FD,freezedrying;OD,ovendrying.

stemsfor

a

-glucosidaseinhibition. Amongthemetabolitesthat discriminatedtheFDsamplesfromtheODandADsamples,allof theidentifiedflavonoidsandphenolicacidswerelocatednearFD leavesratherthanitsstem,whichmightcontributetothehighTPC, DPPHand

a

-glucosidaseinhibitionsofFDleaves.Incontrast,the highTPCandDPPHinhibitionofFDstemscanbecontributedby unidentified compounds that are present. The contribution of phenoliccompoundsforDPPHand

a

-glucosidaseinhibitionshas beenwellreported(Nacefetal.,2010;Zhangetal.,2013).Quercetin andkaempferolaswellastheirderivativeswereshowntohave valuableantioxidantandantidiabeticproperties(Hungetal.,2012;

Medianietal.,2015).Furthermore,caffeicacid,gallicacidandits derivativewerealsoreportedtobepotent

a

-glucosidaseinhibitors (Obohetal.,2012;Wansietal.,2007).

To increasethecredibilityofourresults,thevariableimpor- tanceintheprojection(VIP)valuesofthemetabolitesignalswere examinedtoevaluatethediscriminatorypowerofthemetabolites incorrelatedwiththetestedbioactivities.Normally,metabolites withVIP0.5areconsideredimportantfordiscrimination(Azizan etal.,2012).Allofthemetabolitescontributingtothethreetested bioactivitiesareimportantdiscriminatingmetabolitesbecauseof theirVIP signals values were greater than 0.5 (Supplementary TableS1).ThePLSmodelwasfurthervalidatedusinginternalcross validationbymeansofR²andQ²cumulativeandpermutationtests with 100 permutations. In this study, a good fitness value, R²Y=0.932 and predictive value, Q²=0.876 was obtainedfrom theautofitofSIMCAtreatment,demonstratingthatthisPLSmodel isgood(González-Domínguezetal.,2015).Permutationplotsof thePLSmodelareshowninFig.S4.TheY-interceptsofR²andQ² werelessthan0.3and0.05,respectively,whichfurtherdemon- stratedthat thePLS modelis validand doesnot showover fit (Maulidianietal.,2013).Therefore,thePLSmodelmeetthecriteria ofagoodperformancemodel.

3.Conclusions

1HNMR-basedmetabolomicsrevealsthemetabolitevariation amongtheN.oleracealeafandstemsubjectedtodifferentdrying methods.ThepresentfindingsdemonstratethattheFDN.oleracea leavespossessedthehighestTPCandexhibitedthegreatestDPPH freeradicalscavengingand

a

-glucosidaseinhibitoryactivities.The MVDAfurthersupportedthisresultbecausestrongcorrelationwas

found between the phytochemicals presented and the tested bioactivities.Thepotentialactivemetabolitesthatcontributeto the bioactivity of FD leaves include vitexin-2-O-rhamnoside, catechin,quercetinderivatives,kaempferolderivatives,myricetin derivatives,gallicacidandcaffeicacid.Thepresentworkindicates that metabolomics approach is a useful tool for discriminating samplesfromdifferentprocessingparameters.Itcanbesuggested that thephytochemicals ofFD N.oleracea leaves arepromising antioxidantand

a

-glucosidaseinhibitorsforthepreventionorthe treatmentofdiabetesanditscomplications.

4.Experimental

4.1.Chemicals

Absolute ethanol, deuterated methanol-d4 (CH3OH-d4), non deuteratedKH2PO4,sodiumdeuterium oxide(NaOD),trimethyl- silyl propionic acid-d4 sodium salt (TSP) and deuterium oxide (D2O) were supplied by Merck (Darmstadt, Germany). Sodium carbonate, Folin-Ciocalteu reagent, gallic acid, quercetin, phosphate buffer,

a

-glucosidase enzyme, glycine, 2,2-diphenyl- 1-picrylhydrazyl (DPPH) and p-nitrophenyl-

a

-D-glucopyranose (PNPG)weresuppliedbySigma(Aldrich,Germany).

4.2.Plantmaterialandsampling

N.oleraceawasidentifiedbyanin-housebotanistofInstituteof Bioscience, Dr. ShamsulKhamis and thevoucher specimen(SK 2516/14)wasdepositedintheHerbariumofInstituteofBioscience.

TheplantswereplantedinUPMAgriculturalParkbydistributing obtainedstemsina cornerofapond fencedinbybamboo.For harvestingandsampling,theplotwasdividedintosixparts,and theleavesandstemsofthesamplesineachsubplotwereseparated tobesubjectedtothreedifferentdryingmethods.

4.3.Samplepreparation

Theplantswereharvestedafterthreemonthsofplanting.As soonastheplantswereharvested,theleaveswereseparatedfrom thestemsoftheplants.Thestemswerecutintosmallpieces.For FD,leafandstemsampleswerekeptat 80Cforfreezingpriorto lyophilization ina vacuum flaskat 0.064mbarand 50C in a Fig.6.BiplotobtainedfromPLS,describingthevariationbetweenAD,FDandODleavesandstems.1,vitexin-2-O-rhamnoside;2,quercetinderivatives;3,kaempferol derivatives;4,myricetinderivatives;5,catechin;6,caffeicacid;7,gallicacid;9,b^-glucose;10,a^{-glucose;11,sucrose;12,fructose;13,fattyacids;14,alanine;15,leucine;16,} valine;17,choline;18,malicacid.L,leaf;S,stem;AD,airdrying;FD,freezedrying;OD,ovendrying.

freezedryer.ForAD,leafandstemsampleswereplacedinawell- ventilatedspaceawayfromdirectsunlightexposure andunder ambient temperature. OD involved drying the leaf and stem samplesinaventilateddryingovenat45C.Thedryingwasended whentheweightoftheleafandstemsampleswasconstant.The dried samples were then ground to a fine powder using a laboratoryblender.Thepowdersofallofthedriedmaterialswere keptinaluminumpouchandmaintainedat4Ctoprotectfrom lightexposureandhumidityuntilfurtheranalysis.

4.4.Extraction

Grindedleafandstemsamplesfromeachofthethreedrying methods wereextractedusing absoluteethanol. Theextraction wasperformedbyweighing2gofgroundsamples,mixingthem with100mL ofabsoluteethanol ina 150mL Schott bottleand subjecting to sonication (at controlled temperature) in an ultrasonicbathsonicator(Branson,model8510E-MTH,Danbury, USA)for1h.Themixturesweretransferredto250mLpolypropyl- ene copolymer centrifuge bottles (Nalgene, NY, USA) and centrifuged for 30min at 13,000rpm to separate supernatants andprecipitates.Thesupernatantswerecollectedandconcentrat- edusingarotaryevaporatortoyieldthecrudeextract.Thecrude extractswerestoredinamberbottleat4Cuntilfurtheranalysis.

4.5.Totalphenoliccontent(TPC)

Total phenolic content was determined using the Folin- Ciocalteureagent accordingto apreviously reportedprocedure (Lee et al.,2014).Briefly, to20

m

^{L oftest samplesorstandards}

preloadedon96-wellplates,100

m

^LofFolin-Ciocalteureagentand 80

m

^{Lof7.5%sodiumcarbonatesolutionwereaddedandmixed}

well.Afterincubationinthedarkfor30min,theabsorbancewas checkedat765nmusingamicro-platereader(SPECTRAmaxPLUS, Sunnyvale,CA,USA).Theanalysiswasperformedwith6replicates.

Astandardcurveofgallicacidwasobtainedtocalculatethetotal phenoliccontentandtheresultswereexpressedin

m

^gGAE/mg

extract.

4.6.DPPHfreeradicalscavengingassay

The DPPH free radical scavenging assay was conducted as previouslydescribed(Leeetal.,2014).Thisassaywasperformedin 96-well format using serial dilutions of 50

m

^{L aliquots of test}

samples and quercetin (positive control). Then, 100

m

^{L DPPH}

(5.9mg/100mLmethanol)wasaddedtoeachwell.Theplatewas incubated in the dark for 30min followed by absorbance measurementat517nmwithamicro-platereader(SPECTRAmax PLUS, Sunnyvale, CA, USA). The scavenging capacity (SC) was calculatedasSC%=[(Ao As)/Ao]100,whereAoistheabsorbance ofthereagentblankandA_sistheabsorbanceofthetestedsamples.

Alltestswereperformedinsixreplicates.Alltestswereperformed insixreplicatesandtheresultswereexpressedasIC50valuein

m

^g/mL.

4.7.Alpha-glucosidaseinhibitionassay

The

a

-glucosidaseinhibitionassaywasperformedaccordingto apreviousreport(Leeetal.,2014),withsomemodifications.The

a

-glucosidaseenzymewasdilutedusing50mMphosphatebuffer (pH 6.5) to get a final concentration of 0.02U/well. The PNPG substratewaspreparedataconcentrationof1mMusingthesame buffersolution. The130

m

^{L of 30mM phosphate,10}

m

^{L sample}

extract or quercetin(positive control) and 10

m

^{L enzyme were}

mixed in the 96-well plates and incubated for 5min at room temperature.PNPGsubstrate(50

m

^{L)wereaddedandtheplatewas}

furtherincubatedfor15minatroomtemperature.Then,50

m

^Lof

glycine(pH10)wereaddedtostopthereaction.Theplatewasread with a spectrophotometer (SPECTRAmax PLUS, Sunnyvale, CA, USA)at405nm.Thepercentage(%)ofinhibitionwascalculatedas follows:%=[(an as)/an]100%,whereanistheabsorbanceofthe negativecontrol,andasistheabsorbanceoftestedsamples.All testswereperformedinsixreplicates.Theresultswereexpressed asIC50valuein

m

^g/mL.

4.8.NMRmeasurement

The sample preparation and NMR measurements were performedaccordingtopreviousmethod(Medianietal.,2012).

A10mgcrudeextractwastransferredtoEppendorftubebeforethe additionofthesamevolume(375

m

^L)ofbothCH3OH-d4solvent andKH2PO4buffer(pH6.0).ThisbufferwaspreparedinD2Oand contain0.1%TSP.Thesamplewasthenvortexedandsonicatedfor 15min at controlled temperature prior to centrifugation at 13,000rpmfor10min.A 600

m

^{L of}supernatantwastransferred toNMRtubetobesubjectedto¹HNMRanalysis.TheVarianINOVA NMRspectrometer(500MHz)wasused.Theanalysistemperature was 26C and thetime of each ¹H NMR spectrumwithpresat settingwas3.54min,acquiring64scans.Chenomxsoftware(v.5.1, Alberta,Canada)wasusedtocorrectthephasingandbaselineofall oftheNMRspectra.TwodimensionalJ-resolvedNMRwasusedas additionalsupportfortheassignmentandconfirmationofsome compounds.

4.9.Bucketingof¹HNMRspectra

Chenomx software (v. 5.1, Alberta, Canada) was used for bucketingofthe¹HNMRspectra.AllspectrawerereducedtoASCII files.The

d

^0.5–10.0regionwas binnedwitha widthof

d

^0.04,

providingatotalof245integratedregions.Theresidualsignalsfor waterandmethanolat

d

^4.70–4.88and

d

^3.27–3.35,respectively were excluded. The standardized binned data was used for multivariatedataanalysis(MVDA).

4.10.Relativequantificationofmetabolites

For relative quantification of the identified metabolites, the meanpeakareaofthesignalsofinterestafterthebinningof¹H NMR spectra was used. ANOVA was performed to determine significantdifferencesinmetabolitesamongsamples.

4.11.Ultra-highperformanceliquidchromatographytandemmass spectrometryanalysis(UHPLC–MS/MS)

Ultra-high performance liquid chromatography(UHPLC)was performed following a method previously describe (Zemmouri etal.,2014),withsomemodifications.Toperformtheanalysis,a reversed-phaseUHPLCThermosystemfittedwithaHypersilGold, Thermo C18 column (2.1mm100mm, 1.9

m

^{m) was used. The}

mobilephasewas0.1%formicacidindeionizedwater(solventA) and0.1%formicacidinLC–MSgradeacetonitrile(solventB).The analysistimewas25min,andtheflowratewas250

m

^L/min.The

injection volume was set to 5

m

^{L. The programmed gradient}

proceeded using thefollowing sequence for solvent A, percen- tages: 90% at 0min, 80% at 5.50min, 50% at10.50min, 30% at 15.50min,0%at18.00min,0%at20.00min,50%at21.00min,90%

at 22.00minand 90% at25.00min.The samplesand standards werepreparedbydissolving4mgofextractin2mLofHPLCgrade methanol, which was then centrifuged and filtered through a 0.22

m

^{mnylonmembraneintoa2-mL}screw-cappedsamplevial.

Mass spectra identification was attained using the Thermo Finnigan model (San Jose, CA, USA) Thermo Scientific^TM Q