Content uploaded by Jiaxin Zhang
Author content
All content in this area was uploaded by Jiaxin Zhang on Oct 08, 2019
Content may be subject to copyright.
J Food Biochem. 2019;00:e13053. wileyonlinelibrary.com/journal/jfbc
|
1 of 20
https://doi.org/10.1111/jc.13053
© 2019 Wiley Periodicals, Inc.
Received:19June2019
|
Revised:1A ugust2019
|
Accepted:20Augus t2019
DOI : 10.1111/jfbc .13053
FULL ARTICLE
iTRAQ‐based mitochondrial proteome analysis of the
molecular mechanisms underlying postharvest senescence of
Zizania latifolia
Haibo Luo1 | Tao Zhou1 | Xiaoxue Kong1 | Mingxuan Tao1 | Jiaxin Zhang1 |
Weihua Wang2 | Li Jiang2 | Lijuan Yu3 | Zhifang Yu2
1School of Food Science and Pharmaceutical
Engineering, Nanjing Normal University,
Nanjing, P.R. China
2College of Food Scie nce and Techn ology,
NanjingA griculturalUniversity,Nanjing,
P.R. China
3InstituteofAgro‐ProductsProcessing,
YunnanAcademyofAgriculturalSciences,
Kunming, P.R. China
Correspondence
Li Jiang, College of Food Science and
Technology,NanjingAgriculturalUniversity,
Nanjing , Jiangsu, 210095, P.R. China.
Email: jiangli@njau.edu.cn
LijuanYu,InstituteofAgro‐Products
Processing,YunnanAcademyofAgricultural
Science s, 650221, Kunming , P.R. China .
Email: yulijuan1000@163.com
Abstract
To explore the molecular mechanisms underlying postharvest senescence of Zizania
latifolia, the changes in the mitochondrial proteome of plants treated with or without
(control) 1‐methyleyelopropene and ethylene during storageat room temperature
for 0, 3 and 6 days were investigated using isobaric tags for relative and absolute
quantitation(iTRAQ)labeling combinedwith two‐dimensional liquidchromatogra‐
phy‐tandemmassspectrometry.Atotalof1,390proteinswithtwoormorepeptides
were identified, of which 211 showed a significant (p < .05) change (at least twofold)
in relative abundance. Monitoring the parallel reaction validated the reliability and
accuracyoftheiTRAQresults.Bioinformaticsandfunctionalanalysisofthesediffer‐
entially expressed proteins (DEPs) revealed that postharvest senescence of Z. latifolia
could be attributed to (a) strengthened pentose phosphate pathway, (b) imbalanced
protein, amino acid, organic acid, and fatty acid metabolism, (c) disordered energy
homeostasis,(d)exacerbatedoxidativedamage,(e)RNAdegradation,(f)activation
of the Ca2+,mitogen‐activatedproteinkinase,andjasmonicacidsignalingpathways,
(g) programed cell death, (h) excessive biosynthesis of secondary metabolites, or (i)
degradation of cell structure. Our findings provide integrated insight into the molecu‐
lar mechanisms of posthar vest senescence during storage as well as the DEPs that
showpromiseastargetsforcontrollingsenescence‐inducedqualitydeteriorationof
Z. latifolia.
Practical applications
Postharvest senescence is the most important factor that causes fast quality deterio‐
ration of Zizania latifolia. The understanding of the processes leading to posthar vest
senescence of Z. latifolia is essential in enhancing the commercial value and extending
the shelf life of the product. It is currently believed that the mitochondrial metabo‐
lism is closely related to postharvest senescence. For this, the changes of proteome
in Z. latifoliamitochondriatreatedwith orwithout(control)1‐MCPandETHduring
storage at room temperature were investigated. Results showed that a variety of
2 of 20
|
LUO et aL.
1 | INTRODUCTION
Zizania latifolia (Griseb.) Turcz. ex Stapf., which is widely distributed
throughoutSoutheast Asia, is a perennial aquatic grassthat grows
alongthelittorals offreshwaterlakes,streams,marshes,and pools
(Fan, Ren, Liu, & Chen, 2016; Li et al., 2019). The plant is usually
parasitized by the smut fungus Ustilago esculenta P. Henn., wh ich
causes thickening and enlargement of the culms. Swollen culms
are commonly called “Jiaobai” in China, “Gausun” in Taiwan, and
“Makomotake”inJapan(Joseetal.,2016)andarewidelyconsumed
asahealthy vegetable in several Southeast Asian countries, espe‐
cially in China, Japan, Taiwan, Vietnam, and India, in which they
haveaconsiderableeconomicimpact(Choietal.,2015;Sinha,Deka,
& Bharal ee, 2016; Yan et al., 2013). However, posth arvest sen es‐
cence of Z. latifolia rapidly undergoes senescence and deterioration
at ambient temperatures. It s vegetable quality is reduced due to
shell etiolation, surface browning, flesh lignification, and tissue hol‐
lowness. Consequently, the shelf life of postharvest senescence of
Z. latifolia is typically only 2–3 days at room temperature (Wang
et al., 2017). Th us, unraveling the molecula r and biochemical changes
that occur during posthar vest senescence of Z. latifolia has biological
and economic importance and enables the development of strate‐
gies to preserve postharvest quality.
Plant senescence is af fected by respiratory metabolism,
which provides the energy for diverse biochemical processes (Li,
Limwachiranon, Li, Du, & Luo, 2016; Yang, Cao, Su, & Jiang, 2014).
The imbalance in energy metabolism caused by changes in respira‐
tory metabolism is an early manifestation and basic characteristic
of plant senescence (Jiang et al., 2007; Li et al., 2018). Increasing
evidence suggest s that appropriate energ y production in harvested
horticultural crops is essential for the maintenance of cell func‐
tions, but energy level requirements may var y between climacteric
and nonclimacteric vegetables (Jiang et al., 2007). Oxidative dam‐
age to proteins, lipids, and nucleic acids caused by intracellular re‐
active oxygen species (ROS),a resultof electron leakage from the
respiratory electron transport chain (ETC), has been implicated in
plantsenescence(Qin,Meng,Wang,&Tian,2009;Wuetal.,2016).
Mitochondria are responsible for adenosine triphosphate (ATP)
synthesis, calcium signaling, ROS production, cell cycle arrest via
programedcelldeath, amongotherfunctions (Liu et al., 2016;Qin,
Wang, Liu, Li, & Tian, 2009). Functional integrity is a critical require‐
ment for mitochondria to meet the cellular energy demand. Thus,
accurate assessment of mitochondrial protein components and the
changes in their abundance would provide insight into the molecu‐
lar mechanisms underlying the postharvest senescence of Z. latifolia
during storage.
Proteomic s enables the evaluation of global changes in the com‐
position and abundance of proteins associated with plant senes‐
cence and the effec ts of posthar vest treatment s on the vegetable
proteome (Das, Chua, Lin, & Wong, 2019; Liet al., 2015). Two‐di‐
mensionalelectrophore sis(2‐DE)isfrequentlyusedtoseparatepro‐
teins prior to their identific ation by mass spectrometry (MS). Indeed,
analyses of the mitochondrial proteomes of the peaches (Wu et al.,
2016),apples(Qin, Wang, et al.,2009),rice(Chen et al.,2009)and
Arabidopsis (Millar, Sweetlove, Giegé, & Leaver, 2001) have been car‐
riedout.However,noinformationisavailableonchangesinthepro‐
tein profiles of Z. latifolia mitochondria in response to senescence. In
addition, it is difficult to separate extremely large/small, acidic/basic,
andhighlyhydrophobicproteinsbytraditional2‐DE.
Theisobarictagsforrelativeandabsolutequantitation(iTRAQ)
techniqu e, which was develo ped by Applied Bio systems in 200 4,
enables high proteome coverage and multiplex labeling (Long
etal.,2019).iTRAQhasbeenappliedtoavarietyofplants,includ‐
ingpeaches(Huan et al.,2019),apples(Zhengetal.,2018),maizes
(Yu et al., 2017), soybean sprouts (Jiao & Gu, 2019), potatoes (Liu
et al., 2015), cucumber plants (Fan, Xu, Du, & Wu, 2015), tomato
roots(Gongetal.,2014),strawberries(Li,Li,Luo,Huang,&Li,2016),
and Citrus sinensis roots ( Yang et al., 2 013).H owever,t o the best
ofourknowledge,themitochondrialproteomeofZ. latifolia has not
beenanalyzedbyiTRAQtechnique.
Ethylene (ETH) is an endogenous plant hormone that plays an
important physiological role in postharvest ripening and postharvest
senescence of horticultural crops (Xu et al., 2018). Modulating the
biosynthesis of ETHisanimportant approach to prolong the shelf
lifeofharvestedhorticulturalcrops.1‐methylcyclopropene(1‐MCP),
aninhibitorofETH,bindsstronglyandirreversiblytoETHreceptors,
preventingtheETHeffectsonplanttissuesanddelayingsenescence
(Luo,Xu,&Yan,2008;Minetal.,2018).1‐MCPhascommercialpo‐
tentialfor controllingETH‐dependentprocessessuchas ripening,
senescence, yellowing, and softening and for extending the shelf
physiobiochemical responses occur during postharvest senescence of Z. latifolia. 1‐
MCP treatment significantly inhibited the changes of these physiobiochemical pro‐
cesses, finally, retarding the postharvest senescence of Z. latifolia.ETHtreatmenthad
oppositeeffects onproteomechangescomparedwith1‐MCPtreatment.Takento‐
gether, these results enrich the understanding of the molecular mechanisms of post‐
harvest senescence of Z. latifolia.
KEYWORDS
iTRAQ,mitochondria,respiratorymetabolism,senescence,Zizania latifolia
|
3 of 20
LUO et aL.
life of vegetables such as broccoli (Xu et al., 2016), green bell pep‐
pers(Cao,Zheng,&Yang,2012), tomatoes(Steelheartetal.,2019),
and “iceberg” lettuces (Saltveit, 200 4). Song et al. (2010) found that
1‐MCPdelayedsenescencebyinhibitingETHproduction,decreasing
cellulose and protopectin contents, and maintaining cell inclusions of
peeled Z. latifolia.We previously reported that1‐MCP significantly
retarded the postharvest senescence of Z. latifolia during storage at
room temp erature (Wan g et al., 2017). However, the mec hanisms
underlyingtheeffectsof1‐MCPandETHonvegetablesenescence
and quality deterioration are unclear.
The objec tives of this study were to (a) evaluate the effects of
1‐MCP and ETH on posthar vest senescence of Z. latifolia during
storage at room temperature (25°C), (b) assess the effects of post‐
harvest1‐MCPandETHtreatmentsonthemitochondrialproteome
of Z. latifoliausingtheiTRAQtechnique,and(c)identifythesenes‐
cence‐responsiveproteinsin Z. latifolia mitochondria and the mo‐
lecular mechanism underlying postharvest senescence of Z. latifolia
during storage at 25°C .
2 | MATERIALS AND METHODS
2.1 | Plant material
Fresh Z. latifoliastemswerehand‐harvestedinJuly9,2016from a
commercialfarmlandin Dabieshan, Anhui, Chinaand immediately
transported to the KeyLaboratoryofFoodProcessingandQuality
Controlof MinistryofAgriculture,NanjingAgricultural University.
They were selected for uniform size, color, and absence of visible de‐
fects and Z. latifoliawasrandomlydividedintothreegroupsof15kg
each. The first group of Z. latifoliawastreatedwith10µl/L 1‐MCP
(AgroFresh,Philadelphia,USA)inasealedchamberatroomtemper‐
ature (25°C) for 20 hr; the second group was immersed in 1,00 0 µl/L
ETH(SinopharmChemicalReagentBeijingCo.,Ltd,China)solution,
air‐dried,andplacedinasealedchamberat25°Cfor20hr;andthe
third group was subjected to the same conditions without exposure
to 1‐MCP or immersion in ETH solution (control, CK). Following
the treatment, the chambers were opened and all Z. latifolia were
stored at 25°C for five days. Z. latifolia samples were removed at Day
0(beforetreatment,CK0),Day3(CK3,1‐MCP3,ETH3),andDay6
(CK6,1‐MCP6,ETH6),respectivelyandmanuallypeeledcarefullyto
removeroots.Next, a5‐cm‐longportionof the stemwasremoved
from each end of Z. latifoliausingasharpstainlesssteelknife;there‐
mainder was used for indices analysis or immediately frozen in liquid
nitrogenandstoredat−80°Cuntilrequired.
2.2 | Determination of color, respiration rate, and
weight loss
The color of the Z. latifolia surface was determined using the Chroma
MeterCR‐400(KonicaMinolta,Inc.,Japan)intheCIEL* a* b* color
space. Ten Z. latifolia per replicate were used.
Ten Z. latifolia with three replicates each at Day 0, Day 3, and
Day 6 were enclosed in 8.7 L glass jars at 20°C for 1 hr. The CO2
concentration was measured using a headspace gas analyzer
(CheckMate3, PBI Dansensor,Denmark)and is expressedin milli‐
grams CO2perkilogramfreshweightperhour.
Weight loss was examined in 10 Z. latifolia per treatment and is
expressed as a percentage of the initial weight.
2.3 | Visualization of ultrastructure
Cell ultr astructure was visualized accordin g to Li, Zhang, and Ge
(2017) and Wu et al. (2017) with some modifications. Z. latifolia
pieces (5 × 5 × 1 mm) from the cut surface of three Z. latifolia per
treatment were excised using a blade and fixed in 2.5% (v/v) glutaral‐
dehydefor4hrfollowedbythreewasheswithcoldphosphate‐buff‐
eredsaline (PBS,0.1mol/L,pH7.2)for15mineach.Subsequently,
thesamplesweresoakedin2%(w/v)osmicacidfixativesolutionfor
2hr andwashedthricewithPBS.The sampleswere dehydratedin
30%, 50%, 70%, 80%, and 90% ethanol for 15 min each, followed
by 100% acetone for 20 min. Next, they were permeated and em‐
bedded inepoxyresinandcut intoslices of50nmthickness.After
staining with uranium acet ate and lead citrate, the cell structure
was observedusing the H‐7650transmissionelectron microscope
(Shanghai Ranchao Photoelectric Technology Co., Ltd, China).
2.4 | Mitochondrial isolation
Mitochon dria were isolate d according to Qin and c oworkers with
somemodifications(Qin,Meng,etal.,2009;Qin,Wang,etal.,2009).
Allstepswereperformedat4°C.Planttissues(150g)werehomog‐
enized using a blender in 450 ml of cold ex trac tion buffer containing
50 mM Tris‐HCl (pH 7.5), 250 mM suc rose, 1 mM ethyle nediami‐
netetraaceticacid(EDTA),0.1%(w/v)bovineserumalbumin(BSA),
0.5%(w/v)polyvinylpyrrolidone‐40,and10mMβ‐mercaptoethanol.
The homogenate was filtered through four layers of sterile cheese‐
cloth and centrifuged at 3,000× g for 15 min. The supernatant was
decanted and centrifuged at 16,000× g for 15 min. The pellet was
resuspended in 30mlofcold washbuffercomprising10mMTris‐
HCl(pH7.2),250mMsucrose,300mMmannitol,1mMEDTA,and
0.1% (w/v) BSA. The cru de fractio ns were separate d on a Percoll
step discontinuous density gradient at 20%, 24%, and 45% (2:4:2)
inwashbuffer.Aftercentrifugationat40,000×g for 45 min, the mi‐
tochondria had accumulated at the interface between the 24% and
45% Percoll layers. The mitochondria were aspirated and washed by
centrifugation at 15,000× g for 15 min in wash buffer and the pellet
was collected.
2.5 | Protein extraction
Protein extraction was performed as described by Isaacson et
al. (2006) with some modifications. The mitochondrial pellet was
crushed to a fine powder in liquid nitrogen, precipitated with 10 ml
ofcoldacetone containing10%(w/v)trichloroacetic acid at −20°C
for 1 hr and centrifuged at 15,000× g for 15 min at 4°C. The de‐
posit was washed twice with cold acetone as in the previous step
4 of 20
|
LUO et aL.
and lyophilized in a vacuum freeze dryer ( Thermo Savant, Germany)
for 5 min. The powder was collected, immediately mixed with 3 ml
ofcoldTris‐HCl‐saturatedphenol(pH7.5),andshakenfor30minat
4°C.Aftercentrifugationat5,000×g for 30 min at 4°C , the phenolic
phase was collected and precipitated with five volumes of cold 0.1 M
ammoniumacetateinmethanolat−20°Cfor1hr.Precipitatedpro‐
teins were centrifuged at 10,00 0× g for 10 min at 4°C and washed
twice with five volumes of cold methanol, followed by t wo washes
with cold acetone. The deposit was vacuum dried and dissolved in
lysis buffer at 30°C for 1 hr. The supernatant was centrifuged at
15,000× g for 15 min at 4°C and the protein concentration was de‐
termined by the bicinchoninic acid method (Smith et al., 1985) using
BSAasthestandard.
2.6 | Trypsin digestion and iTRAQ labeling
Trypsin digestion was performed as described by Wisniewski,
Zougman, Nagaraj, and Mann (2009). Protein samples (100 μg
each) were reduced with 10 mM dithiothreitol for 1 hr at 60°C and
alkylatedwith55mMiodoacetamidefor10minatroomtempera‐
ture in dar kness. Afte r digestion wit h sequencing g rade tryp sin
gold(Promega,Madison,USA)atatrypsin:proteinratioof1:40at
37°C for 12 hr, the samples were reconstituted in 0.5 M triethyl
ammonium bicarbonate buffer (Sigma) and labeled with iTRAQ
reagentsusinganeight‐plexiTRAQkit(ABSCIEXInc.,Foster,MA,
USA)accordingtothemanufacturer'sinstructions.Theproteindi‐
gests obtained from the CK0, CK3, ETH3, 1‐MCP3, CK6, ETH6,
and1‐MCP6treatmentswerelabeledwithiTRAQreagents113,
114, 115, 116, 117, 118, 119, and 120, respectively and incubated
at room temperature for 2 hr. Identical quantities of peptide mix‐
tures from the above seven samples were labeled with reagent
121 and served as the sample internal standard (IS). The peptide
mixtureswerepooledandvacuumdriedfortwo‐dimensionalliq‐
uidchromatography‐tandemMS (2D‐LC‐MS/MS)analysis.Three
biological replicates of each sample were labeled with iTRAQ
reagents.
2.7 | 2D‐LC‐MS/MS
2. 7.1 | Fractionation by strong cation exchange
chromatography
Dried peptide samples were reconstituted in 100 µl of strong cat‐
ionexchangebufferA(10mMKH2PO4in25%acetonitrile,pH2.7)
and frac tionated by strong cation exchange chromatography on
the Agilent 1200 HPLC system (Agilent Technologies, Inc., USA)
equipped with a Poly‐SEA 2.0 × 150 mm column (5 µm, 300 Å ,
Michrom). The peptides were eluted at a flow rate of 0.3 ml/min in
anonlinearbinarygradientstartingwithbufferAandtransitioning
tobufferB(10mMKH2PO4, 500mM KCl in 25% acetonitrile, pH
2.7):0%–5%bufferBfor5min,5%–50%Bover35min,50%–80%
Bover5min(maintainedfor5min),andreturnto5%Bover10min.
The elution was monitored by measuring the absorbance at 215 nm
and 280 nm. In total, 12 fractions were collected, vacuum dried, and
storedat−80°CuntilLC‐MS/MSanalysis.
2. 7. 2 | Reversed‐phase liquid chromatography
(RPLC)‐tandem MS/MS analysis
Sample s were reconstitu ted in Nano‐RPLC buf fer A (0.1% formic
acidand2%acetonitrile).OnlineNano‐RPLCwasperformedonthe
EksigentnanoLC‐Ultra™2DSystem(ABSCIEX).Thesampleswere
loadedontoaC18nanoLCtrapcolumn(100µm×3cm,3µm,150Å)
and washe d with Nano‐RPLC bu ffer A at a flow rate of 2 μl/min
for 10 min. Af ter desalting , peptides were s eparated usin g a C18
reverse d‐phase column (75 μm × 15 cm, 3 μm , 120 Å, ChromXP
Eksigent).Thegradientwasrunat250nl/minfrom5%to30%buffer
B(80%acetonitrileand0.1%formicacid)over70min.
Triple time‐of‐flight (TOF) analysis was performed using the
Triple TOF 5600 System (AB SCIEX) fitted with a Nanospray III
source (AB SCIEX) and a pulled quartz tip as the emitter (New
Objectives,Woburn,MA,USA)accordingtoZhuetal.(2014).Data
wereacquiredusinganionsprayvoltageof2.5kV,curtaingasof30
PSI, nebulizer gas of 5 PSI, and an interface heater temperature of
150°C . For informatio n‐depende nt acquisition , survey sca ns were
acquired over 250 ms and up to 35 produc t ion scans were collected
if they exceeded a threshold of 150 counts/s with a 2+ to 5+ charge
state. The totalcycletime was fixedat2.5s.Arollingcollisionen‐
ergy settingwas applied to allprecursor ionsfor collision‐induced
dissociation. Dynamicexclusion was set for 1/2 peak width (18s)
and theprecursor was refreshed off the exclusion list (Hou et al.,
2015).
2.8 | Protein identification and quantification
The original MS/MS file data (*.wiff) were analyzed using Protein
Pilot Sof tware v. 5.0 (AB SCI EX) agains t the Oryza sativa UniProt
database using the Paragon algorithm (Shilov et al., 2007). The da‐
tabase search parameters were as follows: The iTRAQ eight‐plex
(peptide labeled) was chosen for protein quantification with at least
two unique peptides during the search and a global false discovery
rate from a fit of <1% was considered for fur ther analysis. Relative
quantitation was performed by ttestforthreereplicates.Atwofold
threshold was set to determine up and downregulated proteins using
a p value < .05.
2.9 | Bioinformatics analysis
Bioinformatics analysis of the differentially expressed proteins
(DEPs) was performed using the tools available from DAVID
BioinformaticsResources6.8(http://www.geneontology.org/).The
DEPs were annotated by gene ontolog y (GO) analysis according
tothebiological process (BP) andmolecularfunction (MF)catego‐
ries (Sun et al., 2015). Kyoto Encyclopedia of Genes and Genomes
(KEGG) analysis was performed using the KEGG database (http://
www.genome.jp/kegg/pathway.html)(Chuetal.,2015).
|
5 of 20
LUO et aL.
2.10 | Validation of DEPs
Based on the results of the large‐scale quantitative proteomics
study, proteins were selected for validation by targeted MS analysis
using parallel reaction monitoring (PRM) on the Triple TOF 5600+
LC‐MS/MS system (S CIEX). The p rotein extr action and tr yptic di‐
gestion procedures were the same way as those per formed in the
iTR AQexperiment.MSdataacquisitionwasfirstper formedindata‐
dependent acquisition mode to obtain MS/MS spectra for the 40
most abundant precursor ions following each MS1 sur vey scan in
each cycle. ProteinPilot software was used to identify proteins and
thedatabasesearchresultswereimportedintotheSkylinesoftware
for the spectral librar y building. Target proteins for PRM validation
wereimportedintoSkylineandthepeptidesforproteinquantifica‐
tion were selected according to the ion signals in the spectral library.
Alistofassociatedpeptideswithm/z values and retention times was
exportedfromSkylineandthenimportedintotheMScontrolsoft‐
ware Analyst for PRM acquisitionmethod construction. The PRM
method was run against the biological samples of interest, evaluated,
and refined to develop the highest quality assay. Data collection
wasperformedusingthefinalPRMacquisitionmethodonaQqTOF
mass spec trometer, in which each precursor ion was selected by the
quadrupole and fragmented, and then all fragment ions were quanti‐
fied by the TOF mass analyzer. To eliminate the protein carryover, a
“blank”wasrunbetweenadjacentsamplesforcolumnwashing.Data
processingwasperformedinSkylineandthequantificationresults
were manually inspected for each peptide of the target protein.
2.11 | Statistical analysis
Statistical analysis was performed using SPSS 19.0 software (SPSS
Inc.,Chicago,IL,USA).Dataareexpressedasmeans±standardde‐
viation. One‐wayanalysis of variance (ANOVA)was used to iden‐
tify significant differences between the groups. The associations
betwee n variables we re assessed by Sp earman's correl ation coef‐
ficient. Significance was determined at p < .05.
3 | RESULTS
3.1 | Effect of 1‐MCP and ETH on postharvest
senescence of Z. latifolia during storage at 25°C
The major symptoms of postharvest senescence of Z. latifolia are
shell etiolation, surface browning, transpiration, respiratory disor‐
ders, and tissue hollowness. Therefore, we assessed color change,
weight loss, respiration rate, and ultrastructure to evaluate the ex‐
tent of postharvest senescence of Z. latifolia in this study.
AsshowninFigure1a–c,theL,−a*, and b* values increased rap‐
idly in the CK Z. latifolia samples during Day 6 of storage at 25°C.
1‐MCPtreatmentreducedtheratesofincreaseintheL,−a*, and b*
valuescomparedwiththecontrol.ETHtreatmentenhancedthein‐
crease in the L value during the first three days of storage but atten‐
uatedtheincreaseduringtheremainderofthestorageperiod.Also,
−a* and b*valueswere lower in theETH treated than thecontrol
samples throughout the storage period.
Figure 2a shows that the respiration rate of Z. latifolia in the con‐
troldecreasedwithincreasingstoragetime.1‐MCPtreatmentinhib‐
itedrespirationthroughouttheexperimentalperiod,whereasETH
treatment strengthened respiration during the first 3 days of storage
compared with the control.
Weight loss occurred continually throughout the storage period
in all samples, particularly the control, which showed a weight loss of
approximately 14.91% by the end of storage (Figure 2b). Compared
withthecontrol, both the 1‐MCPandETHtreatmentssignificantly
(p < .05) inhibited the weight loss over 6 days of storage, with the
greatestinhibitionfoundinthe1‐MCP‐treatedsamples.
AsshowninFigure3a,thecellstructureofZ. latifolia in the con‐
trol samples was intact with a clear cell wall, a nucleus, and abundant
mitochondria at the beginning of storage.After6 days ofstorage,
changes in cell structure occurred in the control samples. The cell
wall appeared to have dissolved, with no clear boundary, and a part
of the cell wall remained only as an outline (Figure 3b). In addition,
FIGURE 1 Effectsof1‐MCPandETHontheL, a*, and b* values
of Z. latifolia during storage at room temperature (25°C). Vertical
bars indicate the standard errors of three replicates
6 of 20
|
LUO et aL.
apparent swelling deformation of the mitochondria was observed,
causing the mitochondria to disappear. These observations sug‐
gested that the cell structure of Z. latifolia in the control was signifi‐
cantly degraded.1‐MCPand ETHtreatmentssignificantly (p < .05)
retarded and promoted the degradation of cell structure in Z. latifo‐
lia.In1‐MCP‐treatedsamples,thecellstructurewasrelativelyintact
and the cell wall, plasmodesma, and mitochondria were clearly visi‐
ble, although the number of mitochondria had decreased (Figure 3c).
However,inETH‐treatedsamples,severedissolution wasapparent
in the cell wall after 6 days of storage and a part of the cell wall
was fractured (Figure 3d). Furthermore, mitochondria were no lon‐
ger readily discernable and those observed exhibited severe swelling
and deformation or even degradation.
3.2 | Proteomic profiles by iTRAQ combined with
2D‐LC‐MS/MS
Total proteins extracted from the seven Z. latifolia mitochondrial
sample s with three biolo gical replicat es were analyzed by i TRAQ
labeling combined with 2D‐LC‐MS/MS . A total of 1,390 protei ns
were identified from 43,532 MS/MS spectra and 15,639 peptides,
usinga1%globalfalsediscoveryrateand≥2uniquepeptidesasthe
cut‐offs.Aproteinwasconsidereddifferentiallyexpressedifithad
afold change≥2.0 andap < .05 for at least one storage time point
comparedwiththecontrolatDay0(CK0).Basedonthesetwocri‐
teria, 211 DEPs were identified in Z. latifolia mitochondria, including
80DEPs(76up‐and4downregulated)inCK3,109(77up‐and32
downregulated)in 1‐MCP3,102(66up‐ and 36downregulated)in
ETH3,98(87up‐and11downregulated)inCK6,111(102up‐and9
downregulated)in1‐MCP6,and94(76up‐and18downregulated)in
ETH6(Figure4andSupportingInformationFigureS1).Thedetailsof
these DEPs are listed in Table 1.
3.3 | GO annotation and KEGG pathway
analysis of DEPs
To gain a better underst anding of the newly discovered DEPs, GO
annotation was performed using DAVID 6.8 (http://david.abcc.
ncifc rf.gov/) at each time point and the DEPs were categorized ac‐
cordingtotheirBPsandMFs.TheGOannotationsoftheDEPsare
shown in Supporting Information Table S1. The top 10 enriched
GO terms within each major functional categor y are shown in
Suppor ting Information Table S2 and Figure S2. The GO analysis
yielded377BPand136MFtermsenrichedinCK3,444and148
inETH3, 363and165in1‐MCP3,537and164in CK6, 692 and
234inETH6,and549and180in1‐MCP6(SupportingInformation
Table S1).
Thetwo most enrichedBP terms were single‐organismmet‐
abolic process (56%) and single‐organism biosynthetic process
(19%) followed by small molecule metabolic process, organic acid
metabolic process, and cellular amino acid metabolic process
(Suppor ting Information Table S2). The most enriched MF terms
were catalytic activity (57%), cofactor binding (13%), and lyase
activity (8%). The most significantly (p<.05)enrichedBPterms
inboththe1‐MCP‐andETH‐treatedgroupswereorganonitrogen
compound metabolic process and cy toplasm. The most signifi‐
cantly ( p<.05)enrichedMFtermsinthe1‐MCP‐andETH‐treated
groups were copper ion binding and anion binding, respectively,
indicating that these functional categories are important in post‐
harvest senescence of Z. latifolia.
KEGG analysis of the DEPs was conduc ted to identify the biolog‐
ical pathways associated with posthar vest senescence of Z. latifolia
(Suppor ting Information Figure S3 and Table S3). The results indi‐
cated that 25, 20, 32, 24, 30, and 19 KEGG pathways were signifi‐
cantly ( p<.05)enrichedintheCK3,E TH3,1‐MCP3,CK6,ETH6,and
1‐MCP6treatments, respectively compared with CK0 (Supporting
Information Table S1). The 10 most enriched KEGG pathways in
Z. latifolia mitochondria during storage at 25°C were metabolic
pathways, biosynthesis of secondary metabolites, biosynthesis of
amino acids, biosynthesis of antibiotics, carbon metabolism, carbon
fixation in photosynthetic organisms, 2‐oxocarboxylic acid metab‐
olism, arginine biosynthesis, alpha‐linolenic acid metabolism, and
glyoxylate and dicarboxylate metabolism. Compared with CK0,
1‐MCPtreatmentresultedinsignificant(p < .05) enrichment of DEPs
involved in t he tricarbox ylic acid (TCA ) cycle, pentose ph osphate
pathway (PPP), alanine, aspartate and glutamate metabolism, valine,
leucine and isoleucinedegradation, and C5‐branched dibasic acid
metabolicpathways;andETHtreatmentresultedintheenrichment
ofDEPsassociatedwithoxidativephosphorylation(OXPHOS),PPP,
glycine, serine and threonine metabolism, and phenylalanine, tyro‐
sine, and tryptophan biosynthesis pathways. Therefore, changes in
these pathways may be closely related to postharvest senescence
of Z. latifolia.
FIGURE 2 Effectsof1‐MCPandETHontherespiratoryrateof
Z. latifolia during storage at room temperature (25°C). Vertical bars
indicate the standard errors of three replicates
|
7 of 20
LUO et aL.
3.4 | Validation by targeted MS protein analysis
TovalidatetheiTRAQresults,weselectedsixDEPs—citratesyn‐
thase(no.10),malatedehydrogenase(no.11),6‐phosphogluconate
dehydrogenase (no. 17), peroxidase (no. 49), lipase class 3‐like
(no. 132) and cinnamate‐4‐hydroxylase (no. 157)—for examina‐
tion by PRM . Among these prote ins, citrate synt hase and malate
dehydrogen ase are related to t he TCA cycle, 6 ‐phosphoglu conate
FIGURE 3 Effectsof1‐MCPandETHonthecellultrastructureofZ. latifolia before and af ter 6 days of storage at room temperature
(25°C)
FIGURE 4 Effectsof1‐MCPandETHonthemitochondrialproteomeofZ. latifolia during storage at room temperature (25°C)
8 of 20
|
LUO et aL.
TABLE 1 Differentially expressed proteins in Z. latifolia mitochondrial after 3 and 6 days of storage as compared with control at day 0
No. ID Protein name Unused Tot a l % Cov Peptides
Fold changes of proteins
CK3 ETH3 1‐M CP3 CK6 ETH6 1‐ MCP6
Tricarboxylicacidcycle(TCA)
1Q9ASP4 Dihydrolipoyl dehydrogenase 37. 9 37. 92 69. 8 25 0. 8710 0.51 52 0.1871 1.3428 1.2 474 0.8872
2Q10S3 4 Aconitatehydratase 57. 19 57. 17 53.6 44 0.9727 0.6792 0.0619 1.4322 1.4191 1.2023
3Q9SDG5 Isocitratedehydrogenase[NAD]subunit 1 7.9 1 18. 01 52. 5 19 1. 076 5 0.7047 0.3802 1. 5136 1. 3062 1 .2246
4Q7XMA0 Isocitratedehydrogenase[NADP] 36.83 36.84 59. 4 20 1.0864 0.9 376 0 .4169 1.2589 1.3552 1.367 7
5Q6YZX6 Putative aconitate hydratase, cytoplasmic 26.21 42.06 44 29 1.0864 0. 8241 0.2270 1.3183 1.4191 1 .0375
6Q6Z5N4 PyruvatedehydrogenaseE1componentsubunitalpha‐1 33.56 33.6 62.6 33 1.10 66 0.4285 0. 2754 1.8365 1 .70 61 1.1695
7Q94JA2 Malate dehydrogenase 35.88 35.9 77.9 47 1.1 272 0. 6792 0 .100 9 1. 1376 1 .1272 0 .9817
8Q6ZI55 NAD‐dependentisocitratedehydrogenasec 19.7 9 19.83 4 7. 4 18 1.2134 0.751 6 0.2333 1.4454 1.4723 1.367 7
9Q6F361 Malate dehydrogenase 11.7 8 32.34 72.1 41 1.4191 0.8 872 0.14 32 1 . 5276 1.5704 1.0864
10 Q6EUF8 Citratesynthase(unknownstereospecificity) 24.46 24. 48 35.4 20 1 .9231 0. 5445 0.2032 1 .5417 1 .5417 0.6486
11 Q42972 Malate dehydrogenase, glyoxysomal 20.68 23.69 64 18 2.2284 1.0666 0.5916 2.0893 2.4889 1.14 82
Pentose phosphate pathway (PPP)
12 Q84ZL6 Os08g0154300 protein 18.47 18.53 35.8 10 0.5808 0.6026 0 .4571 0.6982 0.8395 0.70 47
13 Q6YZC3 Glucose‐6‐phosphate/phosphatetranslocator 2.82 2.94 10.9 21.8030 2.6062 1 .9055 2 .2491 3.4356 1.9770
14 Q2R480 6‐phosphogluconatedehydrogenase,decarboxylating2 17. 6 8 23.85 37. 6 14 1.8535 1.7865 1.3932 2.0701 2.8054 2.0137
15 Q65X97 Os05g0524400 protein 21.52 21.55 2 9. 8 11 1.94 09 2 .53 51 1.9409 1.70 61 2.0 512 1 .556 0
16 Q6ZEZ2 Os07g0176900 protein 10.62 10.66 35 82.3121 2.3988 1.4191 2.7797 3.94 46 2.9923
17 Q9LI00 6‐phosphogluconatedehydrogenase,decarboxylating1 28.26 28 .31 48.8 15 2.3335 1.51 36 1.1 376 2.466 3. 46 74 1.4060
18 Q5JK10 Os01g0926300 protein 2 7. 42 27. 49 6 4.1 19 2.3335 2.5823 0.912 3.3113 4.3652 3.1623
19 Q6YXI1 Glucose‐6‐phosphateisomerase 39.34 39.36 61 .8 24 2 .9107 3.3113 1 .8197 3.6308 5.3456 4.16 87
20 Q94JJ0 Fructose‐bisphosphatealdolase 22.58 2 2.61 3 7. 6 16 3. 047 9 3.281 3.02 3.4356 5.754 4 3.10 46
21 Q0DEU8 Os06g0133800 protein (Fragment) 12.92 13.09 19. 2 73.1333 3. 2211 1 .9231 4.0179 5. 8076 2.9 923
Respiratoryelectron‐transportchainandoxidativephosphorylation
22 Q7G3Y4 ATPsynthasegammachain 21.45 21. 52 47. 2 14 0 . 515 2 0.113 8 0.9036 1.0965 0.7727 0. 5649
23 Q7XXS0 Os08g 0478200 protein 10.17 10.53 42 60 . 515 2 0. 2249 1.0666 1 .0 765 0 .74 47 0 .4169
24 Q6ZG90 ATPsynthase 18.89 18.97 46.7 36 0.6026 0.4093 0.8 551 0.8630 0.6 855 0.5808
25 Q7XZW1 NADH‐ubiquinoneoxidoreductase23kDasubunit,puta‐
tive, expressed
10.95 10.99 34.1 80.6194 0.4529 0.8630 0.8 551 0.6855 0.8166
26 Q0DI31 Cytochrome c 55.11 45.5 40 .631 0 .2679 0.136 8 0.9120 0.8 091 0.3532
27 Q9S827 Succinatedehydrogenase[ubiquinone]iron‐sulfursubunit1 20.3 20.31 48.8 20 0.7727 0. 520 0 0.4571 1.0666 0.955 0.7244
28 Q0DG48 ATPsynthasesubunitbeta 71 .06 71 .05 76 . 8 182 0.7943 0.1355 0 .9638 1.2359 0. 8 551 0.8954
29 Q35322 NADHdehydrogenase[ubiquinone]iron‐sulfurprotein3 21.71 21.73 69.5 14 0.8 017 0.4365 0.8472 0.9638 0.8241 0.8472
(Continues)
|
9 of 20
LUO et aL.
No. ID Protein name Unused Tot a l % Cov Peptides
Fold changes of proteins
CK3 ETH3 1‐M CP3 CK6 ETH6 1‐ MCP6
30 Q6K6A4 Os02g0816800 protein 22.57 22.73 37. 8 19 0.8166 0.4 699 1.10 66 1 .13 76 0.8710 0.4 875
31 Q8W317 NADH‐ubiquinoneoxidoreductase75kDasubunit,puta‐
tive, expressed
42.08 42.08 51 .8 40 0. 8241 0.4699 0 .9462 1 .0375 0.8472 0 .8 472
32 Q5VR12 NADH‐cytochromeb5reductase 14 .81 14. 87 45.7 90 . 85 51 0.3837 0.2805 1.3183 1.2359 0.6 427
33 Q8H2T7 Os07g0645400 protein 32 .69 32 .98 54.8 29 0.8710 0.4699 0.9638 1.1169 0.9817 0.7178
34 Q75LJ3 Electron transfer flavoprotein subunit alpha 12.78 12. 87 38.8 71.0093 0.7656 0.3532 1.6293 1.5849 1.4997
35 Q6ZDY8 Succinatedehydrogenase[ubiquinone]flavoproteinsubunit 34.14 3 4.15 4 9.4 43 1.0666 0. 51 52 0.3908 1.1695 1.0666 0.963 8
36 Q6ZGJ8 Putative inorganic pyrophosphatase 20. 21 20.29 48.3 12 1.2589 1.4454 0.8954 1.7378 2.0 324 1.4723
37 Q7F9U3 Electron transfer flavoprotein subunit beta 10.3 10 .47 43.1 71.3804 0.9727 0.3981 1.7378 1 . 6749 1.556 0
38 Q7DNB0 ATPsynthasesubunitalpha 26. 63 34.98 51.5 19 2 .4210 3 .8 019 4.1687 2.3550 5.6494 3.9811
39 Q8L6I1 Os12g0638700 protein 34.86 57. 3 2 46.3 42 2.5823 2 .2284 1 .9770 2.3988 1. 5704 1.6293
40 P12085 ATPsynthasesubunitbeta 3 3.47 42.91 65 .1 28 5.1051 6.6 069 4.5709 4.13 05 8.0168 5 . 5976
41 Q0J9F5 Os04g0656100 protein 59.96 59.9 7 46.3 53 12 .473 8 10.5682 11. 376 3 15.9956 12.0226 8.9536
Reactive oxygen species (ROS) metabolism
42 Q2RAP0 l‐galactono‐1,4‐lactonedehydrogenase1 8.97 9.18 21.8 60.6310 0 .3837 0.5916 0.70 47 0.7178 0.7516
43 B7EA73 Puromycin‐sensitiveaminopeptidase 7.3 4 7.47 11.1 40.6668 0.62 52 0.3597 0.7943 0.8395 1.0280
44 Q9SDD6 Peroxiredoxin‐2F 4.63 4.71 32.3 20. 8241 0 .6310 0.1213 1.1482 1.0864 0 .9638
45 Q0IM09 Sulfurtransferase 20.68 20.75 40.3 12 0.9036 0.7244 0 .160 0 1.1912 1.3305 1. 0765
46 Q5Z8H5 Peroxidase 7.97 8.05 31.8 51 .1376 2.3335 2.2284 0.6607 1.018 6 0.8166
47 Q43008 Superoxidedismutase[Mn] 10.18 10.24 62. 8 12 1.18 03 0.8017 0.1202 1.8880 2.0893 1.2823
48 Q8S5T1 Glutathione reductase, putative, expressed 10.2 5 10.4 2 7. 2 71.9231 1.69 04 1.3428 2 .1677 2 .4210 2 .1281
49 Q6AV Z8 Peroxidase 6.11 6.12 21.6 31.9770 3. 4041 6.7298 0.6368 0. 520 0 1. 614 4
50 Q0D9C4 CatalaseisozymeB 22.46 22.62 50.2 21 2.0137 0.5702 0.3945 2.0 893 2. 3768 0.8630
51 Q6ER94 2‐CysperoxiredoxinBAS1 15.26 15.29 52 .5 13 4.0926 4.4463 2.6 062 4.4055 6.3680 3. 7670
52 Q0J3N7 Superoxidedismutase[Cu‐Zn] 10.86 11.89 50.2 11 4. 2855 3 .8 019 1. 3428 5. 3456 6.9823 5.9704
Programmed cell death
53 Q6H450 AnnexinV 16 .55 16 .59 28.6 84.1305 4.4 055 3.6644 4.9659 4. 2855 3 .944 6
Protein biosynthesis and degradation
54 Q6Z7F0 PutativeATP‐dependentClpproteaseATP‐bindingsubunit
ClpX1 (CLPX)
4.16 4.19 1 7. 3 40.3 251 0.4285 0. 2938 0. 3597 0.4446 0.7244
55 Q0ILZ4 DEAD‐boxATP‐dependentRNAhelicase9 8.44 8.64 18.8 50.4786 0.3565 0. 2655 0.3532 0.4406 0. 2858
56 Q6Z8F7 26Sproteosomeregulatorysubunit‐like 20.48 21. 22 30.8 11 0.520 0 0.3499 0 .5152 0 .7656 0 . 5152 0.8 091
57 Q84PB3 Eukaryotictranslationinitiationfactorisoform4G‐1 13.91 14. 33 20.6 70 .6138 1.0568 1.018 6 0.5248 0.6081 0 .4 613
(Continues)
TABLE 1 Continued
10 of 20
|
LUO et aL.
No. ID Protein name Unused Tot a l % Cov Peptides
Fold changes of proteins
CK3 ETH3 1‐M CP3 CK6 ETH6 1‐ MCP6
58 Q6YU81 Putative ribosomal protein S5 10.49 10.65 1 9.8 50.6486 0. 2489 0.55 46 0.8091 0 .6918 0.5495
59 Q7XZF7 ProbableDNAgyrasesubunitA 25.75 25.8 23.5 13 0.6668 0.4285 0.4613 0.9638 0.912 0 1.2589
60 P92812 60S ribosomal protein L2 20.12 20.26 3 8.1 11 0.6668 0.3373 0.4966 0.9638 0.7112 0.8 395
61 Q75IT2 Putativepentatricopeptide(PPR)repeat‐containingprotein,
PF01535
12.86 12.99 12.8 70.70 47 0.4 487 0. 3597 0.6792 0 . 58 61 0.7178
62 Q6ZJS7 Elongation factor Ts 11.24 11. 28 20 60.8166 0.6 081 0.1294 1 .13 76 1.1272 0.9204
63 Q851Y8 Elongation factor Tu 29.4 2 2 9.4 4 58.3 26 0.8395 0. 5916 0.1 271 1.0093 1.0000 0.6982
64 Q53JB5 Putative uncharacterized protein 10.69 10.8 28.9 20. 847 2 0. 8241 0 .5598 0.3192 0. 4571 0. 6792
65 Q6H4L2 Elongation factor 2 61. 2 61.19 60.6 43 0.9036 0. 8017 1.1376 0.4831 0 .41 30 0.5495
66 Q6ASU8 Putative translational activator 53.98 54.03 20.3 28 1 .0 471 1.8707 1.14 82 0. 5297 0.6486 0. 4130
67 Q10QZ6 Elongationfactor1‐alpha 29.38 2 9.41 57. 7 34 1.1695 1. 513 6 1.8535 0.6546 0.70 47 0.4246
68 Q6ZLK0 Dolichyl‐diphosphooligosaccharide‐‐proteinglycosyltrans‐
ferase48kDasubunit
14.17 14.33 41 15 1.6444 2.1478 1. 5 417 0.9817 0.9638 0. 613 8
69 P35683 Eukaryoticinitiationfactor4A‐1 44.34 44.38 70.5 41 1. 70 61 2.2699 1.9588 0.8318 1.2474 0.9550
70 Q6Z7B0 Dnak‐typemolecularchaperoneBip 32.83 38.99 47. 2 26 2.0893 2.0324 1.2823 1. 6596 1.19 12 0.9290
71 Q6ZI53 Elongation factor Tu 17. 4 6 18 .59 40.5 12 2.2491 2. 0324 1.2359 2.5586 3. 8726 2.93 76
RNAdegradation
72 Q8H3I7 10kDachaperonin 9.7 3 9.91 75.5 40.8872 0. 6252 0.0938 1. 367 7 1.3062 1.0000
73 Q0E3C8 ChaperoneproteinClpB3 25.37 30.58 28.5 14 1.0000 0.6607 0.2333 1.2823 1. 4191 1.4454
74 Q6ZFJ9 60kDachaperoninbetasubunit 17. 6 2 41. 56 56 27 1.5849 1. 5417 1 . 2474 1 .690 4 2.1478 1.5276
75 Q7X9A7 60kDachaperoninalphasubunit 14.59 32. 55 48.1 30 1.9770 2.0701 1.556 0 1.9055 2.75 42 2.0137
76 Q7F9I1 Chaperone protein ClpC1 78.58 78.58 61 .6 52 2.2284 2 .3121 1.5996 2 . 376 8 3.49 95 2.3988
77 Q2QU06 60kDachaperoninalphasubunit 37. 9 1 39. 8 6 55. 2 31 2.3550 2.1677 1.4191 2 .1878 3.5318 2 .3768
78 Q69QD5 Chaperonin 5.16 11.54 32.7 64.4 055 5.1051 3.0479 4.9659 5 .8614 4.1305
Hydrolaseactivity
79 Q5Z974 ATP‐dependentzincmetalloproteaseFTSH1 19. 49 19.9 8 25.1 10 1.3305 1.8365 1.8880 1.6293 2.9107 2 . 8576
80 Q655S1 ATP‐dependentzincmetalloproteaseFTSH2 26.4 28.45 39. 2 15 1. 5560 2.1478 2.2080 1.6749 3.0 479 2.9107
81 Q6Z505 ATP‐dependentClpproteaseproteoly ticsubunit 7. 6 7.74 40.7 42.2909 2.3768 1.7539 2.6546 3 .4995 2.4 889
Aminoacidmetabolism
82 P93438 S‐adenosylmethioninesynthase2 9.4 4 9. 49 16.8 50.6081 0 .5297 0.6486 0.3945 0.4571 0.4207
83 Q7Y1F0 Serine hydroxymethyltransferase 32.87 32. 87 61.9 70 .6855 0. 3 076 0.0895 0.7798 0.7727 0.5702
84 Q6ZCF0 Probablegamma‐aminobutyratetransaminase3 13.22 22 .52 4 7.7 18 0.6918 0.5346 0.1259 0 .8 551 0 .76 56 0 .70 47
85 Q10R45 Alanine‐glyoxylateaminotransferase2,putative,expressed 21. 61 21.64 46.7 13 0.7798 0.4 656 0.155 6 0.8017 0.7178 0.6546
86 Q6V9T1 Glycine dehydrogenase P protein 4 0.14 40.16 45.9 33 0.7798 0.5012 0.3048 0. 8017 0.7178 0. 6792
(Continues)
TABLE 1 Continued
|
11 of 20
LUO et aL.
No. ID Protein name Unused Tot a l % Cov Peptides
Fold changes of proteins
CK3 ETH3 1‐M CP3 CK6 ETH6 1‐ MCP6
87 Q850X1 Putative isomerase 7.54 7. 6 6 30.5 50.8790 0. 5395 0.1803 0.7943 0 .7178 1.2942
88 Q10G56 Ornithine aminotransferase 9.6 4 9. 75 34 80 .920 4 0.6252 0.1459 1.2706 1.3552 1.0965
89 Q6L5I4 Putative aldehyde dehydrogenase 13.04 13.1 2 7. 3 60.9638 0. 8395 0.4018 1.4 322 1.3552 1.2942
90 Q7X7S9 Putative alanine aminotransferase 28.42 28 .47 45.7 18 1.0186 0.7047 0.0525 1.7 061 1.556 0 1.0965
91 Q852M0 Glutamate dehydrogenase 23.37 23.45 5 7. 4 16 1.0471 0.8710 0 .3076 1.59 96 1.4322 1.3062
92 Q75IM9 Isovaleryl‐CoAdehydrogenase 23.42 23.46 51 .6 17 1.1169 0 .7311 0.1995 1.6444 1.51 36 1.6144
93 Q7XN11 Gamma‐aminobutyratetransaminase1 29.8 4 29.8 9 52.7 20 1.2023 0.7311 0.0433 1.4859 1.3428 1 .2134
94 Q67UZ0 Aminotransferase 14. 22 14.31 36.3 81.2246 0.6486 0.19 23 1.4322 1. 5136 1.4588
95 Q0INQ6 Serine hydroxymethyltransferase (Fragment) 13.81 13.9 25.3 27 1.4322 1 .0965 1.1 376 1.9231 2.2284 1.7701
96 Q0JPA8 Histidinoldehydrogenase 12. 76 12.84 28.1 81.4 454 1.224 6 1.3 062 1.97 70 2. 4210 1.8030
97 Q5VNW0 3‐phosphoshikimate1‐carboxyvinyltransferase 16.66 16.77 39. 2 12 1 .5136 1.6596 1.0375 1.94 09 2.884 1 .4723
98 Q2QXY9 2‐isopropylmalatesynthaseB,putative,expressed 32.65 32.72 44.9 21 1.5560 2 .1281 1.2246 2.6062 3.7325 2.9107
99 Q6KA J2 Aspartateaminotransferase 32. 74 32.79 60.3 24 1.7378 1.5996 1.1169 2 .1478 2 .729 1. 674 9
100 Q67W99 PutativeD‐3 14.31 16 .35 22.1 10 1.7865 2.1281 1.4191 1. 8197 2 .8314 2. 2284
101 Q69RJ0 Ferredoxin‐dependentglutamatesynthase 65.48 65.45 35.9 31 1.9953 2.2080 1.5849 2.4889 3 .3113 2.6062
102 Q10R10 Hydrolase,carbon‐nitrogenfamilyprotein,expressed 15.24 15.26 38.4 82.0701 1.7701 0 .7656 2.9 923 2.8054 3.0200
103 Q10NW0 ImidazoleglycerolphosphatesynthasehisHF,putative,
expressed
22.88 22.94 38.7 17 2.0701 2.1677 1.674 9 2. 8314 3.5318 3.0200
104 Q7Y096 3‐isopropylmalatedehydrogenase 20.35 20.37 40.4 14 2.0893 1.94 09 1. 4723 2 .1677 3.020 0 2.4660
105 Q688Q9 Glutamate‐‐cysteineligaseA 16.69 16.78 33.9 10 2.2080 2.228 4 1.3305 2.3988 3.4 041 2.4889
106 Q5Z9H5 Putative arogenate dehydrogenase isoform 2 16.63 16.68 34.6 92.6062 2.4660 1. 6596 2.729 5.0582 3.5975
107 Q67VM2 Putative Tryptophan synthase beta chain 9.5 5 9. 69 23.1 62.7290 3.4 674 1.9409 4 .2855 5.6494 3.56 45
108 Q8LMR0 Phosphoserine aminotransferase 22.35 22.45 39 20 2.9107 2. 3768 1. 8707 2.96 48 4.4875 2.4660
109 Q93Y73 Aspartate‐semialdehydedehydrogenasefamilyprotein,
expressed
16.3 4 16.35 4 9.1 20 3 .0761 3. 0479 1.7865 3.8371 5.2000 3.4356
110 Q6H6I1 3‐isopropylmalatedehydratase,smallsubunit‐like 9.3 5 9.4 30.4 73.0761 3.0479 1 .5417 3 .7670 5 . 5976 3.2509
111 Q6Z74 4 Dihydropyrimidine dehydrogenase 23.67 23.72 47. 8 16 4.3652 5.4450 2.3988 9. 036 5 11. 695 7. 3 11 4
112 Q2RAZ7 Alpha‐l‐arabinofuranosidaseC‐terminusfamilyprotein,
expressed
10.5 4 10.71 14.6 76.3680 5. 8076 5.495 4 12.3595 11.5878 10.4713
113 Q7X7N2 Arginase1 11.21 11.37 45.9 80.9638 0 .7178 0.2070 1. 2706 1.1912 1 .1376
114 B9EXM2 Carbamoyl‐phosphatesynthaselargechain 4 8.55 48.55 37 29 1 .180 3 1. 2474 1.1695 1 .70 61 2.0324 1.5704
115 Q6YVI0 Putative ornithine carbamoyltransferase 10. 74 10.78 31.9 10 1.7378 1.7539 1.1588 2.1281 2.7040 1. 8197
116 Q10N79 ArgininebiosynthesisbifunctionalproteinArgJ 12.99 13.03 22 .9 71.9231 1.8707 1 .4859 2.6062 3.4 674 2.2080
117 Q2QVC1 Argininosuccinatesynthase,putative,expressed 29. 6 8 29. 77 47. 2 21 2.4889 2.466 1.8030 3. 047 9 4.0179 2 .7797
(Continues)
TABLE 1 Continued
12 of 20
|
LUO et aL.
No. ID Protein name Unused Tot a l % Cov Peptides
Fold changes of proteins
CK3 ETH3 1‐M CP3 CK6 ETH6 1‐ MCP6
118 Q10MK5 Argininosuccinatelyase 18.0 3 18.07 40 .9 11 2.6303 3.5318 2.5823 4 .130 5 5.0119 3. 8019
119 Q10GQ5 N‐acetyl‐gamma‐glutamyl‐phosphatereductase 13.25 13.29 29. 2 11 3 .3420 3.90 84 3 .1623 4 .6132 6.8549 4.1687
Transaminase activity
120 Q5JJI4 Probable mitochondrial import receptor subunit TOM20 11. 61 11.82 46.5 90.0225 0.6252 0.8241 0.6668 0.5058 0.4656
121 Q2QZ12 Mitochondrial carrier protein, expressed 22.18 22.25 56.2 15 1.4997 0.5808 1. 513 6 2.0 512 1. 6596 1.10 66
122 Q6Z229 Putative glutamate/malate translocator 2.9 3. 24 10.6 32.0701 2.3335 1.8030 2. 3550 3 .0 479 1.7539
123 Q5JL23 ABC‐typetransportsystem‐like 6. 57 6.69 24 .6 32.2491 2.2080 2.1677 2.2491 3.3729 2.4210
124 Q6H8E4 PutativeplastidicATP/ADPtransporter 12.33 12 .35 13. 2 82.5586 2 .53 51 2.0893 2 .3121 3 .4 674 1.6444
125 Q6AV V6 Nitrate transpor ter, putative 6.49 6.7 8.5 35.2966 5.3456 4.24 62 4.786 3 4.4 055 3.9 08 4
Lipid metabolism
126 Q2QYF8 Cytidylyltransferase family protein, expressed 21.7 21 .74 41 10 0.4920 0.4 831 0.5 861 0 .74 47 0.6368 0.5970
127 Q9LRI6 MitochondrialaldehydedehydrogenaseALDH2a 22.48 22.55 3 9. 2 19 0. 8241 0 . 515 2 0.4571 0.9908 0.9036 0.8790
128 Q9FRX7 AldehydedehydrogenaseALDH2b 16.74 21.3 43.7 22 1.1695 0.8630 0.4786 1.4997 1.5704 1.4191
129 Q69QJ7 Probable monogalactosyldiacylglycerol synthase 1 10.21 10.31 26 51.6444 1.3552 1.18 03 1.7865 2.2080 1.4322
130 Q10EH4 Lipoxygenase 4.95 8.24 12.7 52.0324 2. 5119 2.2284 1.0666 1.7378 1.18 03
131 Q75IK4 Putative lipase 12.12 13.5 34.4 92.2080 2.6792 3.7325 0.8318 1.1912 1. 2134
132 Q6Z307 Lipaseclass3‐like 10 10 12.2 63. 8371 5.1523 2.7290 4.9204 5.0582 4.4875
133 Q94LR9 3‐ketoacyl‐CoAthiolase2,peroxisomal,putative,
expressed
14.28 18.56 34.7 11 1.0000 0.3664 0.3802 0 .7178 0.7943 0.5395
134 Q10MS3 MalonylCoA‐acylcarrierproteintransacylasecontaining
protein, expressed
15.34 15.39 41. 3 12 1.4060 1.3183 0 .8 017 1.614 4 2. 0137 1.570 4
135 Q5W6W 7 Longchainacyl‐CoAsynthetase 23.42 23.48 30.4 13 1.8707 2 .1677 1.7219 1 .5996 1.7865 1.3183
136 Q84P96 3‐ketoacyl‐CoAthiolase‐likeprotein 33.34 33.38 61.4 36 2. 2491 0.8091 0.4246 1 .9770 2 .0324 0.9550
137 Q69YA2 3‐oxoacyl‐[acyl‐carrier‐protein]synthase 16.07 16.14 38.5 16 2 . 376 8 2.6 062 1.7865 2.5823 3.6644 2.9107
138 Q0JL46 Neutral ceramidase 13.08 13.15 15 86.0813 6.4863 5. 8614 8.3946 7.11 2 1 6.7920
Nucleic acid metabolism
139 Q6KAI0 Polyribonucleotide nucleotidyltransferase 2 15.52 15.6 17. 1 80. 5970 0.51 05 0.4831 0.6668 0.62 52 0.7311
140 Q08479 Adenylatekinase3 23.96 24.01 59. 8 16 0.6918 0.3802 1.0666 1.4997 1.2359 0. 2911
141 Q0DZG1 Succinyl‐CoAligasesubunitbeta 47. 93 47.95 78 35 1.0000 0.7047 0.0525 1. 5560 1 .3677 1.0568
142 Q9LD61 Aspartatecarbamoyltransferase 26.98 27. 0 4 51 13 1. 513 6 1.6749 1. 4191 1.9055 2.3988 2. 4210
143 Q6ZKK5 Putative aminoimidazolecarboximide ribonucleotide
transformylase
15.23 15 .41 4 6.1 10 1.9055 1.888 1.3428 2.1086 2 .9107 2.2284
144 Q10MD1 Adenylosuccinatelyase 7.5 5 7.6 4 23.4 72.1677 1 .8197 1.3552 2.3768 2.8840 2.6062
145 Q5N821 Putative formylglycineamide ribotide amidotransferase 38. 67 38.69 32.2 23 2.9107 2. 6546 2 .1478 3 .2810 4.9659 3.8 371
(Continues)
TABLE 1 Continued
|
13 of 20
LUO et aL.
No. ID Protein name Unused Tot a l % Cov Peptides
Fold changes of proteins
CK3 ETH3 1‐M CP3 CK6 ETH6 1‐ MCP6
146 P37833 Aspartateaminotransferase,cytoplasmic 24.8 6 25.61 58.5 22 3.2509 0.7798 0.4093 3.9811 3. 5975 1. 7219
Organic acid met abolism
147 Q337E9 Malic enzyme 9.51 11 .8 9 29. 5 60.6982 0.5649 0.1528 0 .920 4 0. 8472 0. 8551
148 Q7F19 0 Malic enzyme 37. 0 3 38.93 54.3 28 0 .9120 0.5346 0.3020 1.0000 0.94 62 0.9290
149 Q7XPR2 Aminomethyltransferase 23.44 2 3.47 52 .9 16 0.9550 0. 58 61 0.0581 1.1272 1.0093 1.0 093
150 B9F3B6 Succinate‐semialdehydedehydrogenase 19.75 20.02 42 .7 17 1 .0 471 0. 6310 0 .1419 1.4588 1.3677 1 .1912
151 Q7XI14 ProbableD‐2‐hydroxyglutaratedehydrogenase 16.66 16 .74 26. 8 12 1.0471 0 .7311 0 .1019 1.3804 1. 2942 1.1272
152 Q0DC43 Formate dehydrogenase 17.61 19. 2 7 50 31 1.18 03 0.8 472 0.1019 1. 8197 1. 5417 1.3 677
153 Q0DJT2 Lactoylglutathione lyase (Fragment) 19.9 6 19.9 9 50.2 10 1.7378 1.7378 0.8954 2.1281 2 .9376 2.10 86
154 P0C 51 2 Ribulose bisphosphate carboxylase large chain 25.42 25.49 47 24 2.4660 2.4889 2.0893 3. 2211 4.3652 3.0479
155 Q7XUG1 Malate synthase 10.31 10.49 25.2 48.953 6 5.2000 1.4060 13.42 76 15. 2757 6.0813
Phenylpropanoid biosynthesis
156 Q5VNW0 3‐phosphoshikimate1‐carboxyvinyltransferase 16.66 16.77 39. 2 12 1 .513 6 1.6596 1.0375 1.94 09 2.8840 1. 4723
157 Q5W6F1 Cinnamate‐4‐hydroxylase 19. 5 4 19. 6 6 31.2 82 .108 6 2.7040 1. 8197 2 .1878 2.2699 1.7865
158 Q5ZCV1 Putative dehydroquinate dehydratase 16.46 16.56 52 .5 13 2.7290 2. 2699 1.9231 3. 3420 4.6559 2.8054
Biosynthesisofsecondarymetabolites
159 Q8RU48 Cell elongation protein DIMINUTO, putative, expressed 18.1 18 .16 37. 8 11 0.6855 0.8 872 0.8091 0. 3597 0.42 07 0.3664
160 Q10PQ1 CytochromeP45074A2,putative,expressed 9.14 9. 24 20.3 51.3932 1.6596 2.1478 2.2080 2.4434 1.7865
161 Q75KD7 AOC 8 .74 8.84 32.1 10 2. 0324 1 .940 9 1.4060 1.8707 2.8314 2.167 7
162 Q7XUK6 6,7‐dimethyl‐8‐ribityllumazinesynthase 10.21 10.25 33.9 52.0893 1.9953 1.4322 2 .2491 2.9107 2 .3121
163 Q60EI0 Putative ferredoxin sulfite reductase 13.81 13. 87 39.4 14 2.6546 2.6303 1 .556 0 2.93 76 4. 0 551 3.4995
164 Q6K439 Probableplastid‐lipid‐associatedprotein2 12.29 12.3 33.5 92.9648 3 . 46 74 2.9648 4.9204 7. 0 4 69 5.24 81
165 Q6K 7V6 Probable tocopherol cyclase 9.9 6 10.05 21.1 73. 5975 3. 5975 2 .9376 4.4463 6.0256 4. 6559
Stress response and defense
166 Q53NM9 DnaK‐typemolecularchaperonehsp70‐rice 8.25 50.06 58.9 34 0 . 510 5 0.6 081 0.673 0 0. 4130 0.2992 0.2911
167 Q5Z4M2 Putativemicrotubule‐associatedprotein 10.86 11.14 25.2 80 .5200 0.575 4 0 .4130 0.2655 0 .1419 0.1995
168 Q7XS58 Cysteine synthase 12.05 13.4 3 39. 8 70.6546 0 . 5105 0.0973 0.7727 0.7870 0.6252
169 Q655Y3 Dreg‐2likeprotein 16 .26 16 .31 41 .4 10 0.7311 0.6026 0 .133 0 1.1066 0.9550 0.8091
170 Q0 IN14 Hsp90protein,expressed 32.26 3 2.74 38.4 30 0.7798 0.4207 0.0530 0. 8241 0.8091 0 .6026
171 Q10SR3 70kDaheatshockprotein 8.14 35.43 47.8 33 0. 8551 0.4613 0.0773 1.1272 1.0093 0.9036
172 Q6Z7V2 24.1kDaheatshockprotein 5.91 6.09 20.9 40.9550 0.4966 0.2228 1.0864 1.0 093 0.9908
173 Q10Q21 Mitochondrial processing peptidase beta subunit, putative,
expressed
25.93 25.99 35.8 20 0.9908 0.4446 1.1066 1.367 7 1.0666 0.8630
174 Q6ZL94 Probablesuccinyl‐CoAligase[ADP‐forming]subunitalpha 20.66 20. 87 53.5 16 1.0568 0.7516 0.0535 1. 6596 1.4859 1.1066
(Continues)
TABLE 1 Continued
14 of 20
|
LUO et aL.
No. ID Protein name Unused Tot a l % Cov Peptides
Fold changes of proteins
CK3 ETH3 1‐M CP3 CK6 ETH6 1‐ MCP6
175 Q6ZG77 Probable diaminopimelate decarboxylase 17. 3 4 1 7. 37 33.1 81.8030 1.7539 1.18 03 2.1677 3.1333 2.1677
176 Q2QV45 70kDaheatshockprotein 37.1 6 39.2 1 45.3 25 2 . 376 8 2.6303 1 .5 276 2.5586 3.9446 2. 3550
177 Q10MQ2 Probable l,l‐diaminopimelateaminotransferase 33.01 33.02 58.4 22 2.6546 2.6546 1.4588 3.6983 4.8306 3 .767 0
178 Q8L5K0 Ferritin 5.35 5.46 28.6 32 .9 376 2.558 6 2.1878 2.9107 4.0926 3.9811
179 Q7XU28 OSJNBb0034G17.8protein 12.23 12. 41 37. 9 63. 2810 2 . 53 51 1.2474 2.5 351 4.24 62 3.0479
180 Q6ZIV7 Hypersensitive‐inducedresponseprotein 16 .76 22.32 63.7 13 3.6644 3. 2810 2.7542 5. 0119 3.6644 3.2810
181 Q5VS25 Put ative beta 1,3 glucan synthase 18. 29 2 9.67 17. 7 17 4 .32 51 4.3652 3.8726 4. 0179 3 .4 0 41 1.6444
182 Q0JPA6 S alt stress root protein RS1 8.25 8.51 26 .5 57.17 7 9 8.1658 5.6 494 11 .3 763 11. 376 3 7. 51 62
Signal transduction
183 Q67UI5 C2domain‐containingprotein‐like 29. 24 2 9. 27 2 9. 5 16 1 .0 765 0 .9817 1.4060 0.4446 0.6368 0.7870
184 Q10NP2 Calcium‐bindingEF‐handfamilyprotein,putative,
expressed
19.88 20.14 24.4 91.7701 1.556 1.0471 2 .6792 1.8197 1.8535
185 Q5ZBN0 Receptor‐likeproteinkinase1‐like 11.58 12.57 26.2 62.10 86 1.9588 1.7865 2. 83 14 1.6444 2.1878
186 Q69U53 MAP3K‐likeprotein 7.85 7. 9 1 21.4 42.2491 1.8365 1.7701 3.2509 2.5586 1.9231
187 Q851M7 Serine/threonine‐proteinkinase 10.45 10.48 14 .7 52.5823 1.7701 1. 6293 2. 3550 1. 8707 2. 2491
188 Q7XQU7 Probable protein phosphatase 2C 41 12 .81 12.85 31.7 63.0761 2.6303 1.90 55 3. 7670 3.4356 3.1915
189 Q6Z3Y9 Phosphoinositide phospholipase C 6.36 6.44 13.6 63.191 5 2. 8576 2. 4210 3.4995 2.4210 2.6546
190 Q8H4Q9 GTP‐bindingproteinRab6 20.21 22.33 77.9 12 0 .5152 0.7586 0.6982 0.52 00 0 .5395 0.424 6
191 Q53K24 Adenylylcyclase‐associatedprotein 10.3 3 10.65 22.2 50.5495 1.1272 1.0375 0.4093 0.5702 0. 3251
192 Q6ATR5 Mitochondrial Rho GTPase 34. 81 35.12 46.4 26 0.7244 0. 3499 0.9290 0.7943 0.6668 0.7178
Inositol phosphate metabolism
193 Q6Z4E4 Methylmalonatesemi‐aldehydedehydrogenase 23.04 23.11 36.1 17 1.0965 0 .7112 0.1459 1. 5417 1.406 1.3552
Cofactor binding
194 Q0J5J5 G‐boxbindingfactor 21.13 28 .75 61.3 17 0.7586 1.0375 0. 8241 0.6486 0.5058 0. 3133
195 Q10MK9 AMP‐bindingenzymefamilyprotein,expressed 10.42 12.73 1 7. 4 71.2823 0 .4571 0 .5861 1.0000 1.1272 0. 5546
196 Q2R1S1 Harpinbindingprotein1,putative,expressed 5.59 5.66 17 33.56 45 3.2509 3.10 46 4.2462 6.0256 5.0582
Mitochondrial fission
197 Q8W315 Dynamin‐relatedprotein1C,putative,expressed 27. 3 2 27. 5 5 43.5 19 0.8318 0.9204 0.7586 0.5495 0 .44 87 0. 58 61
Protein‐proteininteraction
198 Q84R32 CBSdomaincontainingprotein,expressed 5.86 653.2 11 0.6 427 0.4207 0 .1871 0.7798 0.56 49 0.6368
Unclear functional proteins
199 Q0JLS6 ProteinROOTHAIRDEFECTIVE3 20 .41 20.49 24.1 10 0 .5546 0.9204 0 .5395 0.48 31 0.3873 0.4 875
200 Q5NAB7 PutativeDNA‐bindingprotein 8.73 8.8 10.5 40.5916 0.4786 0.3802 0. 6310 0.54 45 0. 376 7
(Continues)
TABLE 1 Continued
|
15 of 20
LUO et aL.
dehydrogen ase to the PPP, lipase class 3‐like to l ipid metaboli sm,
and cinna mate‐4‐hydroxyl ase and peroxidase to p henylpropanoid
biosynthesis. The PRM results were essentially in accordance with
theproteinprofileobtainedbyiTRAQ(Table2).
4 | DISCUSSION
During senescence and quality deterioration of Z. latifolia, a vari‐
ety of physiobiochemical responses occur, which are influenced
by various internal and external factors via regulation of protein
expression. Therefore, we evaluated the protein profile changes in
mitochondriaandtheeffectsofpostharvest1‐MCPandETHtreat‐
ments onthemitochondrialproteome using iTRAQtechnique.The
results revealed that 211 of the 1,390 identified proteins were dif‐
ferentiallyexpressedaccordingtothecut‐offvalues used(2.0‐fold
expression change and p< .05).A functionalanalysisshowed that
these DEPs are involved in a variet y of metabolic and molecular pro‐
cesses (Table 1), which may be closely related to the postharvest
senescence of Z. latifolia.
The postharvest vegetable is an independent organ free from
metabolic interactions with other plant parts and respiration is
the predominant physiological process that dic tates its shelf life
due to cut‐offof nutrient sources (Li,Li, etal., 2017; Li, Lichter,
et al., 2016). The respiration rate is a measurable indicator of the
metabolicintensityofpostharvestsupplyvegetables.Ahighres‐
piration rate leads to the consumption of metabolic substrates,
accelerates maturity or senescence, and shortens the shelf life of
vegetables (Li, Lichter, et al., 2016; Wang, Luo, Khan, Mao, & Ying,
2015). In this study, although the respiration rate decreased during
storage, it remained at a high level (148.8 mg CO2·kg−1·h−1) afte r
sixdaysofstorageatroomtemperature.1‐MCPtreatmentsignifi‐
cantlysuppressedtherespirationrate,indicatingthat1‐MCPde‐
layed postharvest senescence of Z. latifolia.Theabilityof1‐MCP
treatmenttoreducetherespirationratewasreportedbyArgenta,
Mattheis,Fan,andAmarante(2016)inpearsandLimetal.(2016)
inkiwifruits.ETH treatment had the opposite effecton respira‐
tory metabolism during the first three days of storage compared
with1‐MCPtreatment.
Respiration in plants involves several pathways, such as the
Embden–Meyerhof–Parnas pathway, TCA cycle, mitochondrial
electron transport, and cytochrome pathway, PPP and glyoxylate
pathway; each pathway has unique biological functions (Li et al.,
2015). The Embden–Meyerhof–Parnas pathway, which oxidizes
glucose to pyruvate, is a basic respirator y pathway followed by
the TCA cycle and cytochrome pathway,which areessential for
energy provision in postharvest fruit s and vegetables during stor‐
age (Shen et al., 2017). In fruits and vegetables, the PPP pathway
supplies intermediate reaction products. The respiratory meta‐
bolic pathways of postharvest fruits and vegetables vary during
storage (Li, Lv, Guo, & Wang, 2016). In this study, almost all DEPs
relatedtotheTCAcycle(nos.1–11)andPPP(nos.12–21)wereup‐
regulated,suggestingthattheactivitiesoftheTCAcycleandPPP
No. ID Protein name Unused Tot a l % Cov Peptides
Fold changes of proteins
CK3 ETH3 1‐M CP3 CK6 ETH6 1‐ MCP6
201 Q6Z1Y4 Nicalin 9.92 10.08 27. 6 81.3183 2.0893 1.9055 1.3305 1.14 82 0 .6855
202 Q6Z233 PutativeuncharacterizedproteinOJ1111_H02.6 3.9 4.19 8.3 51.3932 1.4322 1.7061 1.6444 2.0893 1.8365
203 Q7Y1D0 PutativeuncharacterizedproteinOSJNBa0033P04.10 14.91 15.01 14.6 10 1.94 09 1.9588 1. 6749 2 .7542 2.9107 2.1677
204 Q69IP1 Putative uncharacterized protein P0450E05.1 10.95 11.0 5 39. 7 61.9770 1.8880 1. 674 9 2. 5119 3.2810 2.398 8
205 Q7XKE6 OSJNBb0017I01.8protein 7.2 8 7. 3 7 42 .1 72.0137 3. 46 74 1.6293 1 .9055 2.5823 1.8535
206 Q60E58 Os05g0388600 protein 11.7 12.15 33.1 92 .2491 2.3335 2. 0 512 2 . 5119 3.1623 2 .53 51
207 Q84P62 OSJNBa0087O24.10protein 9.95 9.99 28 .9 52.5119 2.4660 2 . 5119 2 .3550 3.9811 2.9376
208 Q75M01 Os05g0157200 protein 8.97 9. 03 63.5 82.5586 2.6792 2.3335 2.6792 3. 2211 2.6303
209 Q7XVF8 OSJNBb0118P14.7protein 5.53 5.67 27.9 32.558 6 2. 8576 2 .5119 2.5823 4.5709 3 .4674
210 Q7XPW1 OSJNBa0 032F06.20protein 12.82 13.26 15.3 72.7290 3.0200 2.70 40 3.1333 3.40 41 2. 6792
211 Q337M4 Os10g0463800 protein 4.44 4.62 24.7 46.9823 7. 51 62 0.9550 7.2444 11.5 878 10.964 8
Note: ID,DNAfingerprinting;Unused,confidencelevel;Cov,sequencecoverage.
TABLE 1 Continued
16 of 20
|
LUO et aL.
pathways were enhanced. This is in accordance with the report s
byKan,Wang,Jin,andX ie(2010)andJiangetal.(20 07).However,
the exact functions of this physiological regulation are obscure.
We speculate that changes in respiratory metabolic pathways may
disrupt energy homeostasis, which may be closely related to the
postharvest senescence of Z. latifolia.
The ETC facilitates redox (simultaneous reduction and oxida‐
tion) reactions that transfer elec trons from a low energy electron
donor (e.g., nicotinamide adenine dinucleotide and flavin adenine
dinucleotide) to an acceptor (e.g., O2), couple this electron trans‐
ferwithOXPHOS,andtherebyreleasingtheenergythat isusedto
produce ATP(Jonckheere,Smeitink,&Rodenburg,2012).Aghdam,
Jannatizadeh, Luo, and Paliyath, G. (2018) repor ted that sufficient
intracellularATPsupplyandfriendlyextracellularATPsignalingare
crucial for attenuating stresses, delaying senescence, and maintain‐
ing qualit y in hor ticultural crops postharvest. In this study, 20 DEPs
(nos.22–41)involvedintheETCandOXPHOSwereidentified.Most
of these proteins were slightly downregulated after three days of
storage. 1‐MCPt reatmentret arded this downregulation, whereas
ETHtreatmentsignificantlypromoteditafterthreedaysofstorage.
TheseresultssuggestthatETCandOXPHOSareweakenedleading
toareducedenergysupply.1‐MCPtreatmentisconducivetomain‐
tain a relatively high level of energy.
TheETCisalsoamajorsiteofprematureelectronleakagetoox‐
ygen,thusgeneratingROSandincreasingoxidativestress(Kirkland
&Franklin,2015).The metabolicstatusofmitochondrial ROS may
play an important role in programed cell death. Xu reported that
10−9 mol/L ROS promote cell proliferation, 10−6 mol/L ROS result
in programed cell death, and 10−3 mol/L ROS cause cell injury and
death, indicating that the ROS status is closely related to posthar‐
vestsenescence of fruits andvegetables(Xu, 2003). An important
strateg y for plants to respond and adapt to dif ferent biotic and abi‐
otic stresses is via the regulation of physiological metabolism. Excess
ROS react with cellular components such as proteins, nucleic acids,
and unsaturated fatty acids to cause oxidative damage (Xia et al.,
2016). To minimize this cellular damage caused by ROS, organisms
have evolved a scavenging system composed of antioxidants and an‐
tioxidant enzymes. The antioxidant enzymes superoxide dismutase,
catalase, peroxidase, peroxiredoxin, and glutathione reductase play
important roles in scavenging ROS (Xu et al., 2016). Of the 11 ROS
proteins (nos. 42–52), seven were related to antioxidant enzymes
and four to nonenzymatic antioxidant s. In this study, the significant
upregulation of these DEPs suggested that mitochondria are under
increased oxidative stress caused by ROS. This result was validated
by the visualization of the cell ultrastructure by transmission elec‐
tron microscopy (Figure 3).
Annexins are found mostly in eukaryotic organisms includ‐
inganimals,plants, and fungi. Among these proteins, Annexin V is
commonly used to detect apoptotic cells based on its abilit y to bind
tophosphatidylserine,a marker of apoptosis when located onthe
outer leaflet of the plasma membrane (Donnelly & Moss, 1997). In
thisstudy,Annexin V (no.53)was significantlyupregulated during
storage,especiallyinthecontrol,anditslevelincreasedby4.13‐and
4.97‐fold after three a nd six days of storage , respective ly.A s ex‐
pected,the1‐MCPandETHtreatmentsinhibitedandpromotedthe
upregulationofAnnexinVduringsixdaysofstorageperiod.
Respiratory metabolism, which provides the energy required for
plant biochemical processes, also supplies a number of intermediate
products for synthesis of proteins, amino acids, fats, nucleic acids,
andsecondarymetabolites(Kiprovskietal.,2018).Inthisstudy,we
identified 28 DEPs (nos. 54–81) related to protein biosynthesis and
degradation, 38 DEPs (nos. 82–119) related to amino acid metab‐
olism, 13 DEPs (nos. 126–138) related to lipid metabolism, 8 DEPs
(nos. 139–146) related to nucleic acid metabolism, 10 DEPs (nos.
188–200) related to organic acid metabolism and 7 DEPs (nos. 159–
165) related to biosynthesis of secondary metabolites. Only 6 of the
18 DEPs related to protein biosynthesis were upregulated compared
with 9 of the 10 DEPs related to protein degradation, indicating that
TABLE 2 TargetedproteomicsdatavalidationbyPRMandcomparisonwithiTRAQproteomicsdata
Proteins Data sources
Fold changes
CK3 ETH3 1‐M CP3 CK6 ETH6 1‐ MCP6
Citrate synthase iTRAQproteomicsdata 1.9231 0.54 45 0.2032 1. 5417 1. 5417 0.6486
PRM validation 1.9229 0.6145 0. 2473 1.8807 1.6 496 0.4828
Malate dehydrogenase iTRAQproteomicsdata 1.1272 0.6792 0.10 09 1 .1376 1.1272 0.9817
PRM validation 2.5791 1.16 00 0.4356 1.70 61 2.140 3 0.7969
6‐phosphogluconate
dehydrogenase
iTRAQproteomicsdata 2.3335 1. 513 6 1.1376 2.466 3 .4 674 1.4060
PRM validation 2.3242 1.4035 0. 8353 2.5379 3.6580 1.4040
Peroxidase iTRAQproteomicsdata 1.9770 3.4 041 6.7298 0.6368 0 .520 0 1.614 4
PRM validation 1.7345 3.1527 5.3949 0.750 5 0.6287 1.0357
Lipaseclass3‐like iTRAQproteomicsdata 3.8 371 5.1523 2.729 4.9204 5.0582 4.4875
PRM validation 4.6290 5.9245 3.0 435 6 .5110 8.7180 3.5652
Cinnamate‐4‐hydroxylase iTRAQproteomicsdata 2.1086 2.70 40 1.8197 2.1878 2.269 9 1.7865
PRM validation 2.10 61 2.530 0 1. 8319 2.0611 2 .3757 1.0436
|
17 of 20
LUO et aL.
protein catabolism was enhanced in Z. latifolia during ambient stor‐
age. The majority of DEPs related to amino acid, lipid, nucleic acid,
and organic acid metabolism and biosynthesis of secondary metabo‐
lites was upregulated during storage. This may reflect the increased
consumption of substrates for the biosynthesis of cellular compo‐
nents to maintain normal physiological functions in Z. latifolia during
storage.
Interestingly,1‐MCPreducedthedegreeofup‐anddownreg‐
ulation of the majority of material metabolism‐related DEPs but
dramatically promoted the upregulation of lipoxygenase (no. 130),
lipase (no.131),and cytochrome P450 74A2(no. 160) after three
days of storage. Lipases catalyze the hydrolysis of fats (lipids).
Polyuns aturated fat ty acids (18:3 and 16:3) are conver ted to cis‐
(+)‐12‐oxo‐phytodienoicacid(OPDA) and dinor‐12‐oxo‐phytodien‐
oicacid (dn‐OPDA)bythe consecutiveactionsofplastid‐localized
lipoxygenase,allene oxidesynthase,alleneoxidecyclase,and 12‐
oxo‐phytodienoic acid reductase, theninto OPDAbyalleneoxide
cyclase and thenintojasmonicacid (JA) afterthreecyclesof β‐ox‐
idation (Delker et al., 2006). JA andits metabolites arecrucialfor
plantgrowth,development,and defense. Based on theseresults,
we hypothesize that postharvest senescence of Z. latifolia may be
related to enhanced biosynthesis of JA. This hypothesis awaits
confirmation.
Plant cell walls, which are composed of three major organic
compounds (cellulose, hemicellulose, and lignin), are crucial for pro‐
viding support and shape to many cell types, forming the interface
between adjacent cells, as well as resisting invasion by pathogens
(Delkeretal.,2006).Inthisstudy,severalligninbiosynthesis‐related
proteins, including 3‐phosphoshikimate 1‐carboxyvinyltransferase
(no.156),cinnamate‐4‐hydroxylase(no.157),andputativedehydro‐
quinate dehydratase (no. 158), were upregulated in the mitochondria
of Z. latifolia during storage. These results are consistent with our
previous observations that the lignin content increased significantly
(p < .05) and cellulose content increased slightly during storage (Luo,
Jiang,Zhang,Jiang,&Yu,2012).
Unlikeprimary metabolites,secondarymetabolitesare organic
compounds that are not directly involved in the normal growth,
development or reproduction of an organism. The absence of sec‐
ondary metabolites does not result in immediate death, but rather
inalong‐term impairmentoftheorganism's survivability,fecundity
or esthe tics, or perhap s in no significant ch ange at all (Kiprovski
et al., 2018). Furthermore, stress response and defense, which are
mediated by profound alterations in gene expression, modulate the
plant transcriptome, proteome, and metabolome. In a recent study,
aproteomicanalysisusing2‐DE/MSofthemitochondriafrompe ach
fruits during senescence was performed and differences in the ex‐
pression of cytoskeleton‐related proteins (e.g., actin and keratin)
were obser ved (Wu et al., 2016). In this study, seven DEPs (nos.
159–165) related to the biosynthesis of secondary metabolites and
17 DEPs (nos. 166–182) related to stress response and defense were
identified. The vast majority of these proteins were upregulated
during storage in the control treatment, suggesting that they play a
role in postharvest senescence of Z. latifolia.
Signal transduction begins with the binding of specific ligands
to receptors located on the sur face of the plasma membrane, re‐
sulting in alterations in intracellular metabolism (Jiang et al., 2015;
Luo, Li, Du, & Mou, 2015). Li and Xue (2010) reported that the Ca2+,
cyclic guanosine monophosphate, and MAPK signaling cascades
function downstream of hydrogen peroxide signaling. Ca2+ medi‐
ates signal transduction in plants and depends on a sensor to con‐
vey changes in its concentration. The main types of proteins that
bind Ca2+ and confer Ca2+‐mediated responses are EF‐hand and
C2‐domain proteins (Reddy & Reddy, 200 4). Protein kinases and
protein phosphatases often act in tandem to phosphorylate and
dephosphorylate proteins. The protein kinase A signaling pathway
plays important roles in a variety of physiological functions, such as
cell growth and differentiation, ion channel conductivity, synaptic
release of neurotransmitters, and gene transcription (Turnham &
Scott, 2016). In this study, the following seven proteins involved in
Ca2+ signal transduction (nos. 183–189) were upregulated in Z. lati‐
folia mitochondria during storage: Phosphoinositide phospholipase
C, calcium‐binding EF‐hand family protein, receptor‐like protein
kinase1‐like,MAP3K‐likeprotein,serine/threonine‐proteinkinase,
probableproteinphosphatase2C41,andC2domain‐containingpro‐
tein‐like.Also,threeproteinkinaseA‐relatedproteins(nos.190–192)
weredownregulatedduringstorage.SmallGTP‐bindingproteins(G
proteins)existineukaryotesfromyeasttohumansandconstitutea
superfamily consisting of more than 100 proteins. This superfamily
is structurally classified into the Ras, Rho, Rab, Sar1/Arf, and Ran
families (Takai, Sasaki, & Matozaki, 20 01). Adenyly l cyclase‐asso‐
ciated protein, which is regulated by G proteins (stimulated by Gs
andinhibitedby Gi),catalyzestheconversionof ATPto3′,5′‐cyclic
adenosinemonophosphate(cAMP)andpyrophosphate.cAMPthen
servesasaregulatorysignalviaspecificcAMP‐bindingtranscription
factors,enzymes(e.g.,cAMP‐dependentkinases),andiontransport‐
ers (Valsecchi, Konrad, & Manfredi, 2014). In this study, all three of
these DEPs were downregulated during storage. Thus, the Ca2+ and
MAPKsignalingpathwaysmayplayimportantroles in postharvest
senescence of Z. latifolia.
Regarding the other DEPs, three proteins (nos. 194–196) were
related to cofactor binding, one (no. 193) to inositol phosphate
metabolism, one (no. 197) to mitochondrial fission, and one (no.
198)to protein–proteininteractions. Amongthese, harpinbind‐
ing protein 1 was significantly (p < .05) upregulated, whereas the
otherDEPsweredownregulatedduringstorage.1‐MCPandETH
treatments inhibited and promoted changes in the abundances of
theseDEPsandthusaffected senescence.However,theprecise
roles of these DEPs in posthar vest senescence of Z. latifolia are
unclear.
In addition, 13 DEPs (nos. 199–211) were neither annotated nor
associated with a KEGG pathway, of which 11 were upregulated and
two downregulated during storage at room temperature. Compared
with the co ntrol, 1‐MCP treatment in hibited the stora ge‐induced
changes in themajority of theseproteins,whereasETH treatment
promoted the expression of some, indicating that these proteins are
related to postharvest senescence of Z. latifolia.
18 of 20
|
LUO et aL.
5 | CONCLUSIONS
In summary, a proteomics analysis of Z. latifolia mitochondria treated
withorwithout1‐MCPandETHduringstorageatroomtemperature
was conducted using iTRAQ.A total of 1,390 proteinswith two or
more peptides were identified, of which 211 showed a significant
(p< .05) change (atleasttwofold)in relativeabundance.The iTRAQ
results were confirmed by PRM. The DEPs were found to be involved
in various cellular and metabolic processes, including respiratory me‐
tabolism, energy metabolism, ROS metabolism, Ca2+andMAPKsignal
transduction, programed cell death, and degradation of cell structure,
indicating that these processes are closely related to postharvest se‐
nescence of Z. latifolia. Functional analysis of the DEPs suggested that
the mechanisms underlying postharvest senescence of Z. latifolia are
(a) enhanced activity of the PPP, (b) imbalances in protein, amino acid,
organic acid, and fatty acid metabolism, (c) disrupted energy homeo‐
stasis,(d)aggravatedoxidativedamage,(e)RNAdegradation,(f)activa‐
tion of the Ca2+,MAPK,andJAsignalingpathways,(g)programedcell
death, (h) excessive biosynthesis of secondary metabolites, and (i) deg‐
radationofcellstructure.1‐MCPsignificantlyinhibited the changes
in these processes, which retarded the postharvest senescence of Z.
latifolia;incontrast,ETHexertedtheoppositeeffects.Takentogether,
these results enhance our understanding of the molecular mechanisms
of postharvest senescence of Z. latifolia.However,furtherdetailedin‐
vestigation of the roles of these proteins and their functional correla‐
tions with postharvest senescence of Z. latifolia is needed.
ACKNOWLEDGMENTS
ThisworkwassupportedbytheNationalNaturalScienceFoundation
of China (31401612), the resea rch start‐up fundi ng from Nanjing
Normal University (184080H202B117),and theKeyResearch and
DevelopmentProgramofYunnanProvince(YNVP‐3).
CONFLICTS OF INTEREST
The authors declare that they have no conflicts of interest .
ORCID
Haibo Luo https://orcid.org/0000‐0001‐5978‐707X
REFERENCES
Aghdam,M.S.,Jannatizadeh,A.,Luo,Z.,&Paliyath,G.(2018).Ensuring
sufficient intracellularATPsupplying andfriendlyextracellularATP
signaling attenuates stresses , delays senescence and maintains qual‐
ity in horticultural crops during postharvest life. Trends in Fo od Science
& Technology, 76, 67–81. https ://doi.org/10.1016/j.tifs.2018.04.003
Argenta, L. C., Mattheis, J. P., Fan, X., & Amarante, C. V. T. (2016).
Managing“Bartlett”pear fruitripeningwith 1‐methylcyclopropene
reapplication during cold storage. Posthar vest Biology and Technology,
113, 125–130. https ://doi.org/10.1016/j.posth arvbio.2015.11.009
Cao,S.,Zheng,Y.,&Yang,Z.(2012).Effectof1‐methylcyclopeneonse‐
nescence and quality maintenance of green bell pepper fruit during
storage at 20°C . Postharvest Biology and Technology, 70, 1–6. https ://
doi.org/10.1016/j.posth arvbio.2012.03.005
Chen, X., Wang, Y., Li, J., Jiang, A ., Cheng, Y., & Zhang, W. (2009).
Mitochondrialproteomeduringsaltstress‐inducedprogrammedcell
death in rice. Plant Physiolog y & Biochemistr y, 47, 407–415. https ://
doi.org/10.1016/j.plaphy.2008.12.021
Choi,J.‐H.,Suzuki,T.,Kawaguchi,T.,Yamashita,K.,Morita,A .,Masuda,
K.,…Kawagishi, H.(2015).MakomotinesAtoDfrommakomotake,
Zizania latifolia, infected with Ustilago esculenta. Tetrahedron Letters,
45, 3596–3599. https ://doi.org/10.1016/j.tetlet.2014.04.125
Chu,P.,Yan,G.,Yang,Q.,Zhai,L.,Zhang,C.,Zhang,F.,…Guan,R.(2015).
iTRAQ‐based quantitative proteomics analysis of Brassica napus
leaves reveals pathways associated with chlorophyll deficienc y.
Journal of Proteomics, 113, 24 4–259. https ://doi.or g/10.1016/j.
jprot.2014.10.005
Das,P.P.,Chua,G.M.,Lin,Q.,&Wong,S.‐M.(2019).iTRAQ‐basedanal‐
ysis of leaf proteome identifies important proteins in secondary
metabolitebiosynthesisanddefencepathwayscrucial tocross‐pro‐
tection agains t TMV. Journal of Proteomic s, 196, 42–56. https ://doi.
org/10.1016/j.jprot.2019.02.002
Delker,C.,Stenzel,I.,Hause,B.,Miersch,O.,Feussner,I.,&Wasternack,
C.(2006).Jasmonatebiosynthesisinarabidopsisthaliana—Enzymes,
products, regulation. Plant Biology, 8, 297–306 .
Donnel ly,S . R., & Moss, S . E. (1997). Annexin s in the secret ory path‐
way. Cellular & Molecular Life Sciences, 53, 533–538. https ://doi.
org/10.1007/s0001 80050068
Fan,H.,Xu,Y.,Du,C.,&Wu,X.(2015).Phloemsapproteomestudiedby
iTRAQprovidesintegratedinsightintosalinityresponsemechanisms
in cucumber plant s. Journal of Proteomics, 125, 54–67. https ://doi.
org/10.1016/j.jprot.2015.05.001
Fan, X. R., Ren, X . R., Liu, Y. L., & Chen , Y. Y. (2016). Genetic structure of
wild rice Zizania latifolia, and t he implications for its management in
the Sanj iang plain, nor theast china . Biochemical Systematics & Ecology,
64, 81–88. htt ps ://doi.org/10.1016/j.bse.2015.11.017
Gong,B.,Zhang,C.,Li,X.,Wen,D.,Wang,S.,Shi,Q.,…Wang,X.(2014).
IdentificationofNaClandNaHCO3 stress responsive proteins in to‐
matorootsusing iTR AQ‐basedanalysis.Biochemical and Biophysical
Research Communications, 446, 417–422. https ://doi.org/10.1016/j.
bbrc.2014.03.005
Hou, L ., Xiu, Y., Wang, J., Liu, X ., Liu, Y., Gu, W., … Meng , Q. (2015).
iTRAQ‐based quantitative proteomic analysis of Macrobrachium
rosenbergii hemocytes during Spiroplasma eriocheiris infection.
Journal of Proteomics, 136, 112–122. https ://doi.org/10.1016/j.
jprot.2015.12.026
Huan,C.,Xu,Y.,An,X .,Yu,M.,Ma,R.,Zheng,X.,…Yu,Z.(2019).iTR AQ‐
based protein profiling of peach fruit during ripening and senes‐
cence under different temperatures. Postharvest Biology and Tech‐
nology, 151, 88–97. Retrieved from https://www.x‐mol.com/paper
Redir ect/5378848 https ://doi.org/10.1016/j.posth arvbio.2019.
01.017
Isaacson, T., Damasceno, C. M., Saravanan, R. S., He, Y., Catalá, C.,
Saladié, M., … Rose, J. K. C. (2006). Sample extraction techniques
for enhanced proteomic analysis of plant tissues. Nature Protocols, 1,
769–774. https ://doi.org/10.1038/nprot.2006.102
Jiang,L.,Kang,R.,Zhang,L.,Jiang,J.,&Yu,Z.(2015).Differentialprotein
profilesofpostharvestgynurabicolorD.Cleaftreatedby1‐methyl‐
cyclopropene and ethephon. Food Chemistry, 176, 27–39. https ://doi.
org/10.1016/j.foodc hem.2014.11.081
Jiang, Y.,Jiang, Y.,Qu,H.,Duan,X.,Luo,Y.,&Jiang,W.(2007).Energy
aspects in ripening and senescence of har vested horticultural
crops. Stewart Postharvest Review, 3, 1–5. https ://doi.org/10.2212/
spr.2007.2.5
Jiao, C., & Gu, Z. (2019). iTRAQ‐based proteomic analysis reveals
changes in response to sodium nitroprusside treatment in soybean
sprout s. Food Chemistry, 292, 372–376. https ://doi.org/10.1016/j.
foodc hem.2018.02.054
|
19 of 20
LUO et aL.
Jonckheere,A.I.,Smeitink,J.A.,&Rodenburg,R.J.(2012).Mitochondrial
ATP synthase: Architecture, function and pathology. Journal of
Inherited Metabolic Disease, 35, 211–225. https ://doi.org/10.1007/
s10545‐011‐9382‐9
Jose, R. C., Goyari, S., Louis, B., Waikhom, S. D., Handique, P. J., &
Talukdar, N. C. (2016). Inve stigation on th e biotrophic inte raction
of Ustilago esculenta on Zizania latifolia found in the indo‐Burma
biodiversity hotspot. Microbial Pathogenesis, 98, 6–15. https ://doi.
org/10.1016/j.micpa th.2016.06.021
Kan, J., Wan g, H. M., Jin , C. H., & Xie , H. Y.(2 010). Changes of re ac‐
tive oxygen species and related enz ymes in mitochondria re‐
spiratory met abolism during t he ripening of peach fruit. Journal
of Integrative A griculture, 9, 138–146. https ://doi.org/10.1016/
S1671‐29 27 (09)6 0 077‐ 8
Kiprovski, B., Borković, B., Malenčić, Đ., Veberič, R., Štampar, F., &
Mikulič‐Petkovšek, M. (2018). Postharvest changes in primary and
secondary metabolites of sweet cherr y cultivars in duced by Monilinia
laxa. Posthar vest Biology and Technology, 144, 46–54. https ://doi.
org/10.1016/j.posth arvbio.2018.05.012
Kirkland,R.A., &Franklin,J.L.(2015).Baxandcaspasesregulatein‐
creased production of mitochondria‐derived reactive species in
neurona l apoptosis: La ck of a role for deplet ion of cytochr ome
c from the mitochon drial electron transport chain. Biochemistry
& Biophysics Repor ts, 4, 158–168. https ://doi.org/10.1016/j.
bbrep.2015.09.004
Li,D.,Li,L.I.,Ge,Z.,Limwachiranon,J.,Ban,Z.,Yang,D.,&Luo,Z.(2017).
Effects of hydrogen sulfide on yellowing and energy metabolism in
broccoli. Posthar vest Biology and Technology, 129, 136–142. https ://
doi.org/10.1016/j.posth arvbio.2017.03.017
Li, D., Li, L . I., Xiao, G ., Limwachir anon, J., Xu, Y., Lu, H. , … Luo, Z.
(2018). Effects of elevated CO2 on energ y metabolism and γ‐am‐
inobut yric acid shunt pathway in posthar vest s trawberry fruit.
Food Chemistry, 265, 281–289. https ://doi.org/10.1016/j.foodc
hem.2018.05.106
Li,D.,Limwachiranon,J., Li,L.,Du,R.,&Luo,Z.(2016).Involvementof
energ y metabolism to chilling tolerance induced by hydrogen sulfide
incold‐stored banana fruit. Food Chemistry, 208, 272–278. https ://
doi.org/10.1016/j.foodc hem.2016.03.113
Li, J., Guan,Y.,Yuan, L., Hou, J., Wang, C., Liu, F., … Zhu, S. (2019).
Effec ts of exogenou s IAA in regu lating photos ynthetic c apacity,
carbohydrate metabolism and yield of Zizania latifolia. S cientia
Horticulturae, 235, 276–285. https ://doi.org/10.1016/j.scien
ta.2019.04.058
Li,L.,Li, D.,Luo,Z., Huang,X.,&Li,X.(2016).Proteomicresponse and
qualit y maintenance in posthar vest fruit of strawberry (Fragaria×
ananassa) to exogenous cytokinin. Scientific Reports, 6, 27094.
Retrieved from https ://www.nature.com/artic les/srep2 7094
Li,L. I., Lichter,A., Chalupowicz, D., Gamrasni, D., Goldberg,T.,Nerya,
O., … Porat , R. (2016). Effect s of the ethylene‐a ction inhibito r 1‐
methylcyclopropeneonpostharvestqualityofnon‐climactericfruit
crops. Postharvest Biology and Technology, 111, 322–329. https ://doi.
org/10.1016/j.posth arvbio.2015.09.031
Li,L.I.,Luo,Z.,Huang,X.,Zhang,L.U.,Zhao,P.,Ma,H.,…Liu,X.(2015).
Label‐free quan titative proteo mics to investiga te strawberr y fruit
proteome changes under controlled atmosphere and low tem‐
perature storage. Journal of Proteomics, 120, 44–57. https ://doi.
org/10.1016/j.jprot.2015.02.016
Li,L.,Lv,F.Y.,Guo,Y.Y.,&Wang,Z.Q.(2016).Respiratorypathwayme‐
tabolism and energy metabolism associated with senescence in post‐
harvest broccoli. Brass ica oleracea L. var. italica) florets in response to
O2/CO2 controlled atmospheres. Postharvest Biology and Technology,
111, 330–336. https ://doi.org/10.1016/j.posth arvbio.2015.09.032
Li, S. W., & Xue, L . (2010). The interaction bet ween H2O2, and NO,
Ca2+,cGMP,and MAPKs during adventitiousrootinginmung bean
seedlings. Vitro Cellular & Developmental Biology‐Plant, 46, 142–148.
https://doi.org/10.10 07/s11627‐009‐9275‐x
Li, Z., Zhang, Y., & Ge, H.(2017). Themembrane may beanimportant
factorinbrowningoffresh‐cutpear.Food Chemistry, 230, 265–270.
https ://doi.org/10.1016/j.foodc hem.2017.03.044
Lim,S.,Han,S.H.,Kim,J.,Lee,H.J.,Lee,J.G.,&Lee,E.J.(2016).Inhibition
ofhardy kiwifruit (Actinidia aruguta)ripening by 1‐methylcyclopro‐
pene during cold storage and anticancer properties of the fruit ex‐
tract. Food Chemistry, 190, 150–157. https ://doi.org /10.1016/j.foodc
hem.2015.05.085
Liu, B., Zhang, N., Zhao,S., Chang,J., Wang, Z.,Zhang, G.,…Wang, D.
I. (2015). Proteomic changes during tuber dormancy release pro‐
cess revealed by iTR AQ quantitative proteomics in potato. Plant
Physiology & Biochemistry, 86, 181–190. https ://doi.org/10.1016/j.
plaphy.2014.12.003
Liu,Z.,Li,L.,Luo,Z.,Zeng,F.,Jiang,L.,&Tang,K .(2016).Effectofbrass‐
inolide on energ y status and proline metabolism in postharvest bam‐
boo shoot during chilling stress. Postharvest Biology and Technology,
111, 240–246. https ://doi.org/10.1016/j.posth arvbio.2015.09.016
Long,R.,Sun,H.,Cao,C.,Zhang,T.,Kang,J.,Wang,Z.,…Yang,Q.(2019).
Identificationofalkali‐responsiveproteinsfromearlyseedlingstage
oftwo contrastingMedicago species by iTRAQ‐based quantitative
proteomic analysis. Environmental & Experimental Botany, 157, 24–36.
https ://doi.org/10.1016/j.envex pbot.2018.09.021
Luo,H.,Jiang,L.I.,Zhang,L.I.,Jiang,J.,&Yu,Z.(2012).Qualitychanges
of whole and fresh‐cut Zizania latifolia during refrigerated (1°C)
storage. Food & Biop rocess Technology, 5, 1411–1415. ht t ps ://doi .
org/10.1007/s11947‐010‐0 459‐5
Luo, Z., L i, D., Du, R., & Mou , W. (2015). Hydr ogen sulfide all eviates
chilling injury of banana fruit by enhanced antioxidant system and
proline content. Scientia Horticulturae, 183, 144–151. htt ps ://doi.
org/10.1016/j.scien ta.2014.12.021
Luo,Z.,Xu,X.,&Yan,B.(2008).Useof1‐methylcyclopropeneforallevi‐
ating chilling injury and lignification of bamboo shoot (Phyllostachys
praecox f. prevernalis) during cold storage. Journal of the Science of
Food and Agriculture, 88, 151–157. https ://doi.org/10.1002/jsfa.3064
Millar,A.H.,Sweetlove,L.J.,Giegé,P.,&Leaver,C.J.(2001).Analysisof
the Arabidopsis mitochondrial proteome. Plant Physiology, 127, 1711–
1727. https ://doi.org/10 .1104/p p.010387
Min,D.,Dong,L.,Shu,P.,Cui,X.,Zhang,X.,&Li,F.(2018).Theapplica‐
tion of carbon dioxide and 1‐methylcyclopropeneto maintain fruit
qualit y of “niuxin” persimmon during storage. Scientia Horticulturae,
229, 201–206. https ://doi.org/10.1016/j.scien ta.2017.11.012
Qin,G.,Meng,X.,Wang,Q.,&Tian,S.(20 09).Oxidativedamageofmito‐
cho nd rialproteinscontributestofruitsenescence:Aredoxproteo m‐
ics analysis. Journal of Proteome Research, 8, 2449–2462. https ://doi.
org /10.1021 /pr8 01 0 46m
Qin,G.,Wang, Q.,Liu, J.,Li,B.,&Tian, S.(2009).Proteomic analysisof
changes in mitochondrial protein expression during fruit senescence.
Proteomics, 9, 4241–4253. https ://doi.org/10.1002/pmic. 20090
0133
Reddy, V. S., & Reddy, A. S. (2004). Proteomics of calcium‐signaling
components in plants. Phytochemistry, 65, 1745–1776. https ://doi.
org/10.1016/j.phyto chem.2004.04.033
Saltv eit, M. E. (200 4). Effect of 1‐methyl cycloprope ne on phenylpro‐
panoid metabolism, the accumulation of phenolic compounds, and
browning of whole and fresh‐cut “iceberg” lettuce. Postharvest
Biology and Technology, 34, 75–80. https ://doi.org /10.1016/j.posth
arvbio.2004.05.001
Shen,Z.,Lin,H.,Lin,Y.,Lin,Y.,Hung,Y.C.,Chen,Y.,…Shi,J.(2017).Energy
status regulates disease development and respiratory metabolism of
Lasiodiplpdia theobromae, (Pat.) Griff. and Maubl.‐infected longan
fruit. Food Chemistry, 231, 238–246. https ://doi.org/10.1016/j.foodc
hem.2017.03.132
20 of 20
|
LUO et aL.
Shilov,I.V.,Seymour,S.L.,Patel,A.A.,Loboda,A.,Tang,W.H.,Keating,
S.P.,…Schaeffer,D. A.(20 07). The paragon algorithm, a nextgen‐
eration search engine that uses sequence temperature values and
feature probabilities to identify peptides from tandem mass spec‐
tra. Molecular & Cellular Proteomics, 6, 1638–1655. ht tps ://doi.
org/10.1074/mcp.t600050‐mcp200
Sinha,S.,Deka,A.C.,&Bharalee,R.(2016).Morphogenesisofediblegall
in Zizania latifolia (griseb.) Turcz. ex Stapf due to Ustilago esculenta
Henn.infectioninIndia.African Journal of Microbiology Research, 10,
1215–1223.https://doi.org/10.5897/AJMR2016.8207
Smith, P.K.,Krohn, R. I., Hermanson,G.T.,Mallia,A .K.,Gartner,F.H.,
Provenzano, M. D., … Klenk,D.C. (1985). Measurementofprotein
using bicinchoninic acid. Analytical Biochemistry, 150, 76–85. https ://
doi.org/10.1016/0003‐2697(85)90442‐7
Song,L.,Gao,H.Y.,Fang,X.J.,Mao,J.L.,Zhou,Y.J.,&Chen,H.J.(2010).
Effect of 1‐methylcyclopropene (1‐MCP) on lignification and cell
ultrastructure of peeled water bamboo shoot. The Chinese Society
for Agricultural Machinery, 41, 111–116. https ://doi.or g/10 .3 969/j.
issn.10002 1298.2010.01.022
Steelheart,C.,Alegre,M.L.,Bahima,J.V.,Senn,M.E.,Simontacchi,M.,
Bartoli, C. G.,…Grozeff,G. E. G.(2019).Nitric oxide improvesthe
effectof1‐methylcyclopropeneextendingthetomato(Lycopersicum
esculentum L.) fruit posthar vest life. Scientia Horticulturae, 255, 193–
201. https ://doi.org/10.1016/j.scien ta.2019.04.035
Sun,Z.L.,Xu,X.,Zhou,D.P.,Wang,L.,Wang,F.Q.,Xu,Z.Y.,…Ji,W.(2015).
Serumproteomic‐basedanalysisbyiTRAQofdamp‐heatimpeding
syndrome of rheumatoid arthritis. European Journal of Integrative
Medicine, 7, 479–484. https ://doi.org/10.1016/j.eujim.2015.07.001
Takai,Y.,Sasaki,T.,& Matozaki, T. (2001).SmallGTP‐binding proteins.
Physiological Reviews, 81, 153–208. https ://doi.org/10.1152/physr
ev.2001.81.1.153
Turnham, R. E.,&Scott,J.D.(2016).Proteinkinase a catalytic subunit
isoform p rkaca; histor y, function an d physiology. Gene, 577, 101–
108. https ://doi.org/10.1016/j.gene.2015.11.052
Valsecchi, F., Konrad, C., & Manfredi, G. (2014). Role of soluble adenylyl
cyclase in mitochondria. Biochimica et Biophysica Acta, 18 42, 2555–
2560. https ://doi.org/10.1016/j.bbadis.2014.05.035
Wang,W.,Jiang,L., Wang, L.,Luo,H.,He,X.,&Yu, Z. (2017). Effectof
1‐methyleyelopropeneandethylenetreatmentsonrespiratoryme‐
tabolism and cell struc ture of posthar vest Zizania latifolia. Modern
Food Scien ce and Technology, 33, 129–136. https ://doi.org/10.13982/
j.mfst.1673‐9078.2017.12.021
Wang,Y.,Luo,Z.,Khan,Z.U.,Mao,L.,&Ying,T.(2015).Effectofnitric
oxide on energy metabolism in posthar vest banana fruit in response
to chilling stress. Postharvest Biology and Technology, 108, 21–27.
https ://doi.org/10.1016/j.posth arvbio.2015.05.007
Wisniewski, J. R., Zougman, A., Nagaraj, N., & Mann, M. (20 09).
Universal sample preparation method for proteome analysis. Nature
Methods, 6, 359–362. Retrieved from http://www.nature.com/doifi
nder/10.1038/nmeth.1322
Wu,X.,Jiang,L.,Yu,M.,An,X.,Ma,R.,&Yu,Z.(2016).Proteomicanaly‐
sis of changes in mitochondrial protein expression during peach fruit
ripening and senescence. Journal of Proteomic s, 147, 197–211. https
://doi.org/10.1016/j.jprot.2016.06.005
Wu, X., Yin, H., Chen, Y., Li, L., Wang, Y., Hao, P., … Zhang, S. (2017).
Chemical composition, crystal morphology and key gene expres‐
sion of cuticular waxes of Asia n pears at harvest and af ter stor‐
age. Postharvest Biology and Technology, 132 , 71–80. https ://doi.
org/10.3389/fpls.2018.00679
Xia, C. G ., Zhang, D., Ma, C., Zhou, J., He, S., & Su, X. R. (2016).
Characterization and comparison of proteomes of albino sea cu‐
cumber Apostichopus japonicus(selenka)byiTRAQanalysis.Fish
& Shellfish Immunology, 51, 229–239. https ://doi.org/10.1016/j.
fsi.2015.12.027
Xu, F., Wang, H., Tang, Y., Dong , S., Qiao, X ., Chen, X. , … Zheng, Y.
(2016).Effectof1‐methylcyclopropeneonsenescenceandsugar
metabolism in harvested broccoli florets. Postharvest Biology
and Technology, 116 , 45–49. https ://doi.org/10.1016/j.posth
arvbio.2016.01.0 04
Xu, H., Chen, Y., Wang, L., Xie, Z., Shao, C., & Zhang, S. (2018).
Transcriptome analysis reveals a regulation of ethylene‐induced
post‐harvest senescence in pear fruit. Scientia Horticulturae, 240,
585–591. https ://doi.org/10.1016/j.scien ta.2018.05.019
Xu,J.(2003). Theroleofelectron leakageofmitochondrial respiratory
chain in cell apoptosis. Progre ss in Biochemistr y & Biophysics, 30, 655–
657.https://doi.org/10.1016/S0168‐9452(03)00209‐7
Yan,N., Wang, X.‐Q., Xu, X.‐F.,Guo,D.‐P.,Wang,Z.‐D.,Zhang,J.‐Z.,…
Liu, H.‐L. (2013). Plant growth andphotosynthetic performance of
Zizania latifolia, are altered by endophy tic Ustilago esculenta infec‐
tion. Physiological & Molecular Plant Pathology, 83, 75–83. https ://doi.
org/10.1016/j.pmpp.2013.05.005
Yang,L.‐T.,Qi,Y.‐P.,Lu,Y.‐B., Guo,P.,Sang, W.,Feng,H., …Chen,L.‐S.
(2013).iTRAQproteinprofileanalysisofCitrus sinensis roots in re‐
sponse to long‐term boron‐deficiency. Journal of Proteomic s, 93,
179–206. https ://doi.org/10.1016/j.jprot.2013.04.025
Yang,Z.,Cao,S.,Su,X.,&Jiang,Y.(2014).Respiratoryactivityandmito‐
chondrial membrane associated with fruit senescence in postharvest
peachesinresponsetoUV‐Ctreatment.Food Chemistry, 161, 16–21.
https ://doi.org/10.1016/j.foodc hem.2014.03.120
Yu,T., Li,G., Liu,P.,Dong, S., Zhang, J.,&Zhao, B. (2017).Proteomics
analysis of maize (Zea mays,l.)grainbasedoniTRAQrevealsmo‐
lecular mechanisms of poor grain filling in inferior grains. Plant
Physiology & Biochemistry, 115, 83–96. htt ps ://doi.or g/10.1016/j.
plaphy.2017.03.008
Zheng,L.,Ma,J.,Zhang,L.,Gao,C.,Zhang,D.,Zhao,C.,…Han,M.(2018).
Revealing critical mechanisms of br‐mediated apple nursery tree
growthusingiTRAQ‐basedproteomicanalysis.Journal of Proteomics,
173, 139–154. https ://doi.org/10.1016/j.jprot.2017.12.007
Zhu, Y.I.,Xu,H., Chen, H., Xie,J., Shi, M.,Shen,B.,…Peng, C.(2014).
Proteomic analysis of solid pseudopapillary tumor of the pancreas
reveals dysfunction of the endoplasmic reticulum protein processing
pat hw ay. Molecular & Cellular Proteomics, 13, 2593–2603. https ://doi.
org /10.1074/mc p.m114.0 38786
SUPPORTING INFORMATION
Additional supporting information may be found online in the
Suppor ting Information section at the end of the article.
How to cite this article:LuoH,ZhouT,KongX,etal.iTRAQ‐
based mitochondrial proteome analysis of the molecular
mechanisms underlying postharvest senescence of Zizania
latifolia. J Food Biochem. 2019;e13053. ht t p s : //d o i .
org /10.1111/jfbc.13053
A preview of this full-text is provided by Wiley.
Content available from Journal of Food Biochemistry
This content is subject to copyright. Terms and conditions apply.
