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A Comparative Proteomic Strategy forSubcellular Proteome ResearchICAT APPROACH COUPLED WITH BIOINFORMATICS PREDICTION TO ASCERTAIN RAT LIVER MITOCHONDRIALPROTEINS AND INDICATION OF MITOCHONDRIAL LOCALIZATION FOR CATALASE*□S
Xiao-Sheng Jiang, Jie Dai, Quan-Hu Sheng, Lei Zhang, Qi-Chang Xia, Jia-Rui Wu,and Rong Zeng‡
Subcellular proteomics, as an important step to functionalproteomics, has been a focus in proteomic research.However, the co-purification of “contaminating” proteinshas been the major problem in all the subcellular pro-teomic research including all kinds of mitochondrial pro-teome research. It is often difficult to conclude whetherthese “contaminants” represent true endogenous part-ners or artificial associations induced by cell disruption orincomplete purification. To solve such a problem, we ap-plied a high-throughput comparative proteome experimen-tal strategy, ICAT approach performed with two-dimen-sional LC-MS/MS analysis, coupled with combinationalusage of different bioinformatics tools, to study the pro-teome of rat liver mitochondria prepared with traditionalcentrifugation (CM) or further purified with a Nycodenzgradient (PM). A total of 169 proteins were identified andquantified convincingly in the ICAT analysis, in which 90proteins have an ICAT ratio of PM:CM >1.0, while another79 proteins have an ICAT ratio of PM:CM <1.0. Almost allthe proteins annotated as mitochondrial according toSwiss-Prot annotation, bioinformatics prediction, and lit-erature reports have a ratio of PM:CM >1.0, while proteinsannotated as extracellular or secreted, cytoplasmic, en-doplasmic reticulum, ribosomal, and so on have a ratio ofPM:CM <1.0. Catalase and AP endonuclease 1, whichhave been known as peroxisomal and nuclear, respec-tively, have shown a ratio of PM:CM >1.0, confirming thereports about their mitochondrial location. Moreover, the125 proteins with subcellular location annotation havebeen used as a testing dataset to evaluate the efficiencyfor ascertaining mitochondrial proteins by ICAT analysisand the bioinformatics tools such as PSORT, TargetP,SubLoc, MitoProt, and Predotar. The results indicatedthat ICAT analysis coupled with combinational usage ofdifferent bioinformatics tools could effectively ascertainmitochondrial proteins and distinguish contaminant pro-teins and even multilocation proteins. Using such a strat-
egy, many novel proteins, known proteins without subcel-lular location annotation, and even known proteins thathave been annotated as other locations have beenstrongly indicated for their mitochondrial location.Molecular & Cellular Proteomics 4:12–34, 2005.
There has been a tendency to focus on subcellular pro-teomes concerning specific subcellular compartments andmacromolecular structures of the cell (1–6). The separation ofthe protein mixture into organelles or other multiprotein com-plex fractions prior to a proteomics analysis can increase theprobability of detecting low-copynumber proteins. Subcellularproteome research cannot only provide information aboutsubcellular location of certain proteins and imply their func-tion, but also tell us the whole-protein components of thespecific subcellular fractions (organelles or other multiproteincomplexes) and then help understand their structures andbiological functions (1–6).
Mitochondria are ubiquitous organelles responsible for theenergy metabolism of eukaryotic cells. They are best knownfor housing the oxidative phosphorylation machinery as wellas enzymes needed for free fatty acid metabolism and theKreb’s cycle. Key steps of heme biosynthesis, ketone bodygeneration, and hormone synthesis also reside within thisorganelle (7). More recent studies suggest an additional role ofthe mitochondrion in ionic homeostasis, apoptosis, and aging(8–13). Consequently, many diseases have been attributed tomitochondrial defects, including Alzheimer’s disease, Parkin-son’s disease, Friedreich ataxia, diabetes mellitus, malignanttumors, cardiovascular disease, and osteoarthritis (14–24).These findings have promoted increasing efforts to define themitochondrial proteome and to discover new molecular tar-gets for drug development and therapeutic intervention (7, 20,25–33).
Mass spectrometric methods and automation of a largepart of the process including robotics application have con-tinued to improve dramatically in recent years, allowing bothincreased sensitivity and higher throughput. Improved soft-ware and databases containing different species genes—known or putative—are also now available, allowing auto-mated data processing of the large volume of acquired mass
From the Research Centre for Proteome Analysis, Key Lab ofProteomics, Institute of Biochemistry and Cell Biology, ShanghaiInstitutes for Biological Sciences, Chinese Academy of Sciences,Graduate School of the Chinese Academy of Sciences, Shanghai200031, China
Received, July 1, 2003, and in revised form, October 18, 2004Published, MCP Papers in Press, October 25, 2004, DOI
10.1074/mcp.M400079-MCP200
Research
© 2005 by The American Society for Biochemistry and Molecular Biology, Inc.12 Molecular & Cellular Proteomics 4.1This paper is available on line at http://www.mcponline.org
spectra. As a result, many largest subcellular proteome data-bases (1–6, 34), especially for mitochondria proteome, havebeen set (7, 25–32). For example, the largest two-dimensional(2D)1-PAGE map database by far for rat liver mitochondriacontains 192 individual proteins from 1,800 spots (25) and foryeast mitochondria contains 253 individual proteins from 459spots (26). On the other hand, the largest shotgun proteomedatabases by far have been set for human heart mitochondriawith 615 individual proteins (27), for mouse mitochondria with591 individual proteins (7), for Saccharomyces cerevisiae mi-tochondria with 750 different proteins (28), and for rat livermitochondria with 227 unique rat proteins (29).
In this new context, the perfect purity of intact proteincomplexes has been crucial to subcellular proteome research(35, 36). In addition to conventional differential centrifugation(25), many further purification methods such as density gra-dient centrifugation (7, 26–29, 37), immunoisolation (37), andfree-flow electrophoresis (38) have been applied to subcellularproteome research and have shown improved effects in iden-tification of more specific subcellular proteins (29, 37, 38).However, the co-purification of “contaminating” proteins isstill the major problem in all the subcellular proteome re-search. For those largest mitochondrial proteome databases,only 33.3�62.8% of the identified proteins have been anno-tated as mitochondrial proteins, while 14.1�43.2% of themhave been annotated as other organelle proteins and9.9�33.9% of them have no subcellular location annotation(7, 25–29). Of the 192 proteins in the 2D-PAGE database forthe rat liver mitochondrial fraction prepared by differentialcentrifugation, only 64 (33.3%) proteins have been annotatedas mitochondrial proteins, while 83 (43.2%) proteins havebeen annotated as other organelle proteins and 45 (23.4%)proteins have no subcellular location annotation in Swiss-Protdatabase (25). Of the 253 proteins in the 2D-PAGE databasefor the S. cerevisiae mitochondrial fraction purified with athree-step sucrose gradient, 159 (62.8%) proteins have beenannotated as mitochondrial proteins, while 69 (27.2%) pro-teins have been annotated as other organelle proteins and 25(9.9%) proteins have no subcellular location annotation (26).In the 591 proteins identified in mouse mitochondria purifiedwith a Percoll gradient, 163 proteins (27.6%) have not previ-ously annotated as associated with mitochondria (7). Amongthe 750 proteins identified in S. cerevisiae mitochondria puri-fied with a three-step sucrose gradient, 436 (58.1%) proteinsare known mitochondrial proteins, while a total of 208 (27.7%)proteins have not been localized so far, and 106 (14.1%)proteins have been reported to be located in other cellularcompartments (28). For the 227 rat proteins identified from therat liver mitochondria purified with a Nycodenz gradient, 80
(35.2%) have been annotated as mitochondrial proteins inSwiss-Prot database, while 70 (30.8%) proteins have beenannotated as other organelle proteins and 77 (33.9%) proteinshave no subcellular location annotation (29). Even though theperoxisome purified with a Nycodenz gradient were furtherimmunoisolated, many mitochondrial and endoplasmic retic-ulum proteins have been detected (37).
It is often difficult to conclude whether these “contami-nants” represent true endogenous partners or artificial asso-ciations induced by cell disruption or incomplete purification(35). At the same time, the novel proteins and proteins withoutsubcellular location annotation need more evidence for theirsubcellular location. Experimental determination of subcellu-lar location is mainly accomplished by three approaches: cellfractionation, electron microscopy, and fluorescence micros-copy. As currently practiced, these approaches are time con-suming, subjective, and highly variable (39). With experimen-tally verified information on protein subcellular locationlagging far behind, a series of bioinformatics tools such asPSORT (40, 41), TargetP (40, 42), SubLoc (43), MitoProtII (44),and Predotar (www.inra.fr/Internet/Produits/Predotar/) havebeen developed and widely used in many subcellular pro-teome data (25, 26, 28–32). PSORT was developed as anexpert system that uses a set of 100 “if-then”-type rulesbased on analysis of characterized protein sequences from avariety of subcellular locations (40, 41). TargetP, based onneural network programming, was developed to predict tar-geting of protein sequences to chloroplasts, mitochondria,and the secretory system using a knowledgebase derivedfrom Swiss-Prot sequence entries (40, 42). SubLoc is a pre-diction system for protein subcellular localization based onamino acid composition alone using a Support Vector Ma-chine method (43). MitoProt was developed to predict mito-chondrial targeting and presequence cleavage sites based ona set of 47 known characteristics of presequences and cleav-age sites (44). Predotar is particularly good at distinguishingmitochondrial and plastid targeting sequences and recog-nizes the N-terminal targeting sequences of classically tar-geted mitochondrial and chloroplast precursor proteins. How-ever, many problems are involved in the prediction (45), and itis questionable whether the efficiency still holds when appliedto proteome data (46). Using an actual subcellular proteomedataset, we have shown that the sensitivity and specificity ofPSORT and TargetP have been overevaluated previously. Butinterestingly, the combinational usage of TargetP and PSORThas a high specificity up to 0.86 for mitochondrial proteinprediction (29).
More recently, Dunkley et al. has just discussed that the useof comparative proteomics to analyze the relative levels ofproteins in different organelle-enriched fractions can solutethe problem of contaminants and distinguish between pro-teins from different subcellular compartments without theneed to obtain pure organelles (36). Implicated from the factthat further purified mitochondrial fractions enriched mito-
1 The abbreviations used are: 2D, two-dimensional; CM, crudemitochondria; PM, purified mitochondria; TM, transmembrane; RP,reversed phase; TCA, tricarboxylic acid; SILAC, stable isotope label-ing with amino acids in cell culture.
ICAT Analysis of Rat Liver Mitochondria with Different Purity
Molecular & Cellular Proteomics 4.1 13
chondrial proteins and decreased apparent contaminant pro-teins compared with crude mitochondrial fraction (29, 38), wethink that comparative proteomic research on the crude andpurified subcellular fraction would be in favor of ascertain-ment of the specific subcellular proteins and exclusion of thecontaminants. In the present study, we apply ICAT technol-ogy, a key strategy in comparative proteomic research (47–49), to compare the crude mitochondrial (CM) fraction of ratliver prepared with differential centrifugation with the purifiedmitochondrial (PM) fraction further purified with a Nycodenzgradient. After 2D-LC-MS/MS analysis, a total of 169 proteinswere identified and quantified. The ICAT data were evaluatedaccording to Swiss-Prot annotation and prediction of fivebioinformatics tools such as PSORT, TargetP, SubLoc, Mito-Prot, and Predotar. The prediction efficiency for mitochondrialprotein of the five bioinformatics tools was compared. Theresults indicated that ICAT analysis coupled with combina-tional usage of different bioinformatics tools could effectivelyascertain mitochondrial proteins and distinguish contaminantproteins and even multilocation proteins. Using such a strat-egy, many novel proteins, known proteins without subcellularlocation annotation, and even known proteins that have beenannotated as other locations have been strongly indicated fortheir mitochondrial location.
EXPERIMENTAL PROCEDURES
Materials—Analytical reagent-grade chemicals were used through-out unless otherwise stated. Water was prepared using a Milli-Qsystem (Millipore, Bedford, MA). Nycodenz, formic acid, guanidinehydrochloride, sodium orthovanadate (Na3VO4), and sodium fluoride(NaF) were obtained from Sigma (St. Louis, MO). Chemicals employedfor gel electrophoresis were purchased from Bio-Rad (Hercules, CA).ACN with HPLC grade was obtained from Fisher (Fair Lawn, NJ).Trypsin sequencing grade was obtained from Promega (Southamp-ton, United Kingdom). EDTA, EGTA, and PMSF were purchased fromAmresco (Solon, OH). Adult male Sprague-Dawley rats were pur-chased from Shanghai Laboratory Animal Center (Jiu-Ting, Shanghai,China).
Differential Centrifugation Separation of Rat Liver Subcellular Frac-tions—Subcellular fractionation of rat liver was performed as de-scribed previously (29). Briefly, Sprague-Dawley rats were sacrificedand the livers were promptly removed and placed in ice-cold homog-enization buffer consisting of 200 mM mannitol, 50 mM sucrose, 1 mM
EDTA, 0.5 mM EGTA, and a mixture of protease inhibitor (1 mM PMSF)and phosphatase inhibitors (0.2 mM Na3VO4, 1 mM NaF) and 10 mM
Tris-HCl at pH 7.4. After mincing with scissors and washing to removeblood, the livers were homogenized in a Potter-Elvejhem homoge-nizer with a Teflon piston, using 10 ml of the homogenization bufferper 2 g of tissue. Centrifugation at successively higher speeds at 4 °Cyielded the following fractions: crude nuclear fraction at 1,000 � g for10 min; mitochondria at 15,000 � g for 15 min; and microsomes at144,000 � g for 90 min. The final supernatant was the cytosol frac-tion. Each successive pellet was washed three times with the homog-enization buffer. The centrifuges used were the Himac CR 21G high-speed refrigerated centrifuge and Himac CP 80MX preparativeultracentrifuge, both from Hitachi Koki Co. Ltd. (Tokyo, Japan).
Purification of Rat Liver Mitochondria Through Nycodenz DensityGradient Centrifugation—The procedures recommended by Ny-comed Pharma and Invitrogen Life Technologies were followed as
described previously (29). Nycodenz was dissolved to 50% (w/v) in 5mM Tris-HCl, pH 7.4, containing 1 mM EDTA, 0.5 mM EGTA, and amixture of protease inhibitor and phosphatase inhibitors as above.This stock solution was diluted with buffer containing 0.25 M sucrose,5 mM Tris-HCl, 1 mM EDTA, 0.5 mM EGTA, and a mixture of proteaseinhibitor and phosphatase inhibitors at pH 7.4. The crude mitochon-drial pellets obtained from differential centrifugation were suspendedin 12 ml of 25% nycodenz and placed on the following discontinuousnycodenz gradients: 5 ml of 34% and 8 ml of 30%, and this wastopped off with 8 ml of 23% and finally 3 ml of 20%. The sealed tubeswere centrifuged for 90 min at 52,000 � g at 4 °C. The bands ofparticles seen after centrifugation have been identified by NycomedPharma and Invitrogen Life Technologies as follows: nuclei at the40/50% interface; peroxisomes at the 34/40% interface; mitochon-dria at the 25/30% interface, lysosomes at the 15/20% interface, andGolgi membranes at the 10/15% interface. The band at the 25/30%interface was collected and diluted with the same volume homoge-nization buffer and then centrifuged at 15,000 � g for 20 min.
Protein Preparation—The mitochondria pellets from differentialcentrifugation (CM) and nycodenz density gradient purification (PM)were respectively suspended in lysis buffer consisting of 8 M urea, 4%CHAPS, 65 mM DTT, 40 mM Tris, sonicated at 100 W for 30 s, andcentrifuged at 25,000 � g for 1 h. The supernatants were collected asCM and PM fractions. The protein concentration was determined bythe Bradford assay. Then the protein samples were directly used for2D-PAGE or ICAT analysis after another precipitation andredissolving.
ICAT Analysis—ICAT analysis was performed using CleavableICATTM Reagent Kit (Applied Biosystems, Foster City, CA) accordingto the manufacturer’s guidelines with some modifications. For ICATanalysis, the protein samples were precipitated overnight with 5�volumes of �20 °C 50:50:0.1 volumes of ethanol:acetone:acetic acidand resolubilized in denaturing buffer (6 M guanidine hydrochloride,100 mM TrisCl, pH 8.3). One hundred micrograms of the CM or PMprotein sample in 80 �l of denaturing buffer were reduced at 37 °C for2 h with 5 mM tributylphosphine (Bio-Rad) and alkylated at 37 °C for2 h in the dark with ICAT-light and ICAT-heavy reagent, respectively.After reaction, ICAT-light and ICAT-heavy reactants were mixed to-gether and exchanged into 100 mM ammonium bicarbonate, pH 8.5,with ultrafiltration through 3-kDa Microcon Centrifugal Filter Devices(Millipore). The buffer-exchanged sample was digested with 4 �g oftrypsin (50:1) at 37 °C for 20 h. Then the ICAT-labeled peptides werepurified using the kit of ICAT™ Avidin Buffer Pack and Avidin AffinityCartridge (Applied Biosystems) according to the manufacturer’sguidelines. Briefly, the peptide mixture was dried by vacuum centri-fuge and resolubilized in the loading buffer of the kit. The peptidemixture was loaded in the Avidin Affinity Cartridge and washed twicewith two kinds of wash buffer to reduce the salt concentration andremove nonspecifically bound peptides. Then the ICAT-labeled pep-tides were eluted with the elution buffer and dried by vacuum centri-fuge. The dried peptides were cleaved of the biotin portion of the ICATreagent with the cleaving reagents at 37 °C for 2 h. Then the ICAT-labeled peptides were dried by vacuum centrifuge and resolubilized in0.1% formic acid for 2D-LC-MS/MS analysis.
2D-LC-MS/MS—Orthogonal 2D-LC-MS/MS was performed usinga ProteomeX Work station (Thermo Finnigan, San Jose, CA). Thesystem was fitted with a strong cation exchange column (320 �minner diameter � 100 mm, DEV SCX; Thermo Hypersil-Keystone) andtwo C18 reversed-phase columns (RP, 180 �m � 100 mm, Bio-Basic® C18, 5 �m; Thermo Hypersil-Keystone). The salt steps usedwere 0, 25, 50, 75, 100, 150, 200, 400, and 800 mM NH4Cl synchro-nized with nine 140-min RP gradients. RP solvents were 0.1% formicacid in either water (A) or ACN (B). The setting of the LCQ Deca Xplusion-trap mass spectrometer is as following. One full MS scan was
ICAT Analysis of Rat Liver Mitochondria with Different Purity
14 Molecular & Cellular Proteomics 4.1
followed by three MS/MS scans on the three most intense ions fromthe MS spectrum according to such a dynamic exclusion setting:repeat count, 1; repeat duration, 0.5 min; exclusion duration, 3.0 min.
Database Searches—The acquired MS/MS spectra were automat-ically searched against the combined human, mouse, and rat nonre-dundant database (NCBI (www.ncbi.nlm.nih.gov), 12/04/2003 re-leased) using the TurboSEQUEST program in the BioWorks™ 3.1software suite. An accepted SEQUEST result had to have a �Cnscore of at least 0.1 (regardless of charge state). For ICAT analysis,protein identification and quantification was achieved by using SE-QUEST and EXPRESS software tools. Peptides with a �1 chargestate were accepted if they were fully tryptic and had a cross corre-lation (Xcorr) of at least 1.5. Peptides with a �2 charge state wereaccepted if they had an Xcorr �2.0. Peptides with a �3 charge statewere accepted if they had an Xcorr �2.5. Then the peptides werefurther analyzed manually by detailed spectral analysis for confirma-tion of protein identification and quantification as described by Han etal. (48).
Bioinformatics Annotation Tools—The theoretical pI and Mr valuesof proteins were defined by program pepstats (www.hgmp.mrc.ac.uk/Software/EMBOSS). The protein function and subcellular locationannotation was from Swiss-Prot and TrEMBL protein database(us.expasy.org/sprot/). The bioinformatics tools such as PSORT(psort.nibb.ac.jp/form2.html) (40, 41), TargetP (www.cbs.dtu.dk/ser-vices/TargetP/) (40, 42), SubLoc (www.bioinfo.tsinghua.edu.cn/Sub-Loc/) (43), MitoProtII (www.mips.biochem.mpg.de/cgi-bin/proj/med-gen/mitofilter) (44), and Predotar (www.inra.fr/Internet/Produits/Predotar/) have been used to predict protein subcellular location. TheTMHMM (www.cbs.dtu.dk/services/TMHMM/) (50) was used to pre-dict protein transmembrane domains. GRAVY values were deter-mined according to Kyte-Doolittle (51). SIB BLAST2 Network Service(us.expasy.org/tools/blast/) was used for novel protein blast againstthe UniProt knowledgebase (Swiss-Prot � TrEMBL � TrEMBL_NEW).
RESULTS
Proteins Identification and Quantification
Rat liver CM were prepared using conventional differentialcentrifugation and were further purified with a Nycodenz gra-dient to obtain PM. One hundred micrograms of the CM or PMprotein sample were labeled with ICAT-light and ICAT-heavyreagent, respectively. After 2D-LC-MS/MS analysis, theMS/MS spectra were searched against the combined human,mouse, and rat nonredundant database using the programSEQUEST. Protein identification and quantification wasachieved by using SEQUEST and EXPRESS software tools(see “Experimental Procedures” for details).
A total of 169 different proteins were identified and quanti-fied from 755 cysteine-containing peptides (253 unique pep-tides) including 398 �2 charge peptides with Xcorr �2.0, and355 �3 charge peptides with Xcorr �2.5. All the peptideshave a �Cn score of at least 0.1 (regardless of charge state).Only two peptides with a �1 charge were identified, with anXcorr of 1.58 and 1.99, respectively.
For the 169 proteins, 69.8% (118/169) proteins were iden-tified and quantitated on the basis of at least one �2 chargepeptide with Xcorr �2.5 and �Cn �0.15 or �3 charge peptidewith Xcorr �3.0 and �Cn �0.15. For 127 (75.1%, 127/169)proteins identified and quantitated according to one uniquepeptide that could have two ICAT reagent-labeling states,
ICAT-light reagent labeling or ICAT-heavy reagent labeling,62.2% (79/127) of them were identified and quantitated on thebasis of at least one �2 charge peptide with Xcorr �2.5 and�Cn �0.15 or �3 charge peptide with Xcorr �3.0 and �Cn�0.15 (Supplemental Table I).
According to physicochemical characteristics analysis, the169 proteins (Table I) include 22 (13.0%) proteins with molec-ular mass �100 kDa, 22 (13.0%) proteins with pI value �9.0,23 (13.6%) hydrophobic proteins with GRAVY value �0, and20 (11.8%) proteins with one or more predicted transmem-brane (TM) domain (Fig. 1), which indicate the ICAT analysisperformed by 2D-LC-MS/MS have little limitations for identi-fication of proteins with extreme size and charge values, andeven hydrophobic and membrane proteins, which is consist-ent with our former 2D-LC-MS/MS analysis of rat liver sub-cellular fractions (29).
The relative quantification of each peptide was determinedby the ratio of signal intensities of peptide pairs using theExpress software tool (see Ref. 58). Ninety proteins have aratio of PM:CM �1.0 with 45.6% (41/90) of them with a ratio �
2.0, which indicates that those proteins are enriched in the PMfraction and should be mitochondrial proteins. Seventy-nineproteins have a ratio of PM:CM �1.0 with 48.1% (38/79) ofthem with a ratio � 0.5 (–2.0), which indicates that they aredecreased in the PM fraction and should be contaminantproteins. Only 12 (7.1%) proteins have a ratio of PM:CMbetween 0.83 (–1.2) and 1.2, in which four protein have a ratioof PM:CM �1.0 and eight proteins have a ratio of PM:CM�1.0 (Fig. 1). Interestingly, there is no apparent differenceamong the percentage of mitochondrial proteins for proteinswith a ratio of PM:CM �1.0, �1.2, �1.5, and �2.0, or thepercentage of nonmitochondrial proteins for proteins with aratio of PM:CM �1.0, �0.83, �0.67, and �0.50, based on theSwiss-Prot annotation or five bioinformatics prediction results(Fig. 2). Considering that the protein or peptide abundancemight influence many steps in the ICAT analysis such as ICATreagent labeling, peptide enrichment and elution in the AvidinAffinity Cartridge, peptide separation in 2D-LC, and peptideionization and detection by MS, the ratio of PM:CM mightreflect synthetically the mitochondria purification effect, pro-tein abundance, and multilocation influence. The relative lowratio such as PM:CM of 1.0�1.5 might implicate proteins withhigh abundance or mitochondria-associated multilocation,while the relative high ratio such as PM:CM �4.0 or moremight implicate proteins with low abundance. Thus, the 169proteins were classified into two groups of PM:CM �1.0 andPM:CM �1.0 in the following analysis.
Subcellular Location of the Identified Proteins
Swiss-Prot Annotation—As shown in Table I and Fig. 3,about 71.0% (120/169) of the 169 proteins have subcellularlocation annotation in Swiss-Prot database. For the 79 pro-teins with a ratio of PM:CM �1.0, in addition to 20 (25.3%)
ICAT Analysis of Rat Liver Mitochondria with Different Purity
Molecular & Cellular Proteomics 4.1 15
TAB
LEI
Sum
mar
yof
pro
tein
sid
entif
ied
and
qua
ntifi
edin
rat
liver
mito
chon
dria
per
form
edb
yIC
AT
anal
ysis
n,to
taln
umb
erof
ind
epen
den
tp
eptid
eid
entif
icat
ions
and
qua
ntifi
catio
nev
ents
for
each
pro
tein
.uP
,num
ber
ofun
ique
pep
tide
seq
uenc
esid
entif
ied
for
each
pro
tein
.Sub
cellu
lar
loca
tion:
C,
cyto
pla
smic
;CA
V,c
aveo
lae;
CS
K,c
ytos
kele
tal;
ER
,end
opla
smic
retic
ulum
;EX
,ext
race
llula
r;G
,Gol
gico
mp
lex;
L,ly
soso
mal
;Me,
pla
sma
mem
bra
ne;M
,mito
chon
dria
l;M
IM,m
itoch
ond
riali
nner
mem
bra
ne;
MIM
S,
mito
chon
dria
lint
erm
emb
rane
spac
e;M
OM
,m
itoch
ond
rialo
uter
mem
bra
ne;
N,
nucl
ear;
O,
othe
r;P
,p
erox
isom
al;
R,
ribos
omal
;S
,se
cret
ed;
W,
who
llyin
trac
ellu
lar.
PS
OR
TII
and
Sub
Loc
are
used
inth
ew
inne
r-ta
kes-
all
mod
ew
ithou
tse
ttin
ga
spec
ifici
tycu
t-of
ffo
rta
rget
ing.
Targ
etP
(mTP
),M
itoP
rotII
,an
dP
red
otar
pre
dic
tp
rote
ins
asm
itoch
ond
rial
bas
edon
ap
rob
abili
tycu
t-of
fof
�0.
50.
BT,
Bio
info
rmat
ics
tool
s,p
rote
ins
pre
dic
ted
asm
itoch
ond
rialp
rote
ins
by
diff
eren
tb
ioin
form
atic
sto
ols
(BT)
atth
esa
me
time.
BT
�0
and
BT
�5
ind
icat
edth
ata
pro
tein
wer
ep
red
icte
das
am
itoch
ond
rialp
rote
inb
yno
neor
allo
fth
efiv
eb
ioin
form
atic
sto
ols,
resp
ectiv
ely.
NA
,no
anno
tatio
n.S
P,
sub
cellu
lar
loca
tion
anno
tatio
nac
cord
ing
toS
wis
s-P
rot
orlit
erat
ure
rep
ort
(mar
ked
with
Ref
.no
.).
Pro
tein
acce
ssio
nno
.P
rote
inna
me
Mr
(kD
a)p
IG
RA
VY
Pre
dH
elR
atio
(L:H
)(C
M:P
M)
nuP
SP
PS
OR
TS
ubLo
cTa
rget
Pm
TPM
itoP
rot
Pre
dot
arB
TFu
nctio
nal
clas
sific
atio
n
Non
mito
chon
dria
lpro
tein
sC
ytop
lasm
icO
0917
1B
etai
ne—
hom
ocys
tein
eS
-met
hyltr
ansf
eras
e44
.98
8.02
–0.3
550
1:0.
524
1C
CM
O0.
135
0.63
70.
914
3A
min
oac
idm
etab
olis
mP
0675
7A
lcoh
old
ehyd
roge
nase
Ach
ain
39.6
58.
520.
209
01:
0.79
31
CE
RC
O0.
083
0.06
20.
182
0E
nzym
e
P04
797
Gly
cera
ldeh
yde
3-p
hosp
hate
deh
ydro
gena
se(G
AP
DH
)
35.8
48.
43–0
.084
01:
0.37
31
CC
CM
0.67
70.
937
0.93
83
Gly
coly
sis
P00
884
Fruc
tose
-bis
pho
spha
teal
dol
ase
B39
.62
8.66
–0.2
70
1:0.
551
1C
CM
O0.
135
0.23
20.
000
1G
lyco
lysi
s
P80
316
T-co
mp
lex
pro
tein
1,�
sub
unit
(TC
P-1
-�)
59.6
25.
72–0
.174
01:
0.18
11
CC
CO
0.12
00.
312
0.00
00
Mol
ecul
arch
aper
one
P05
197
Elo
ngat
ion
fact
or2
(EF-
2)95
.28
6.41
–0.2
080
1:0.
42
0.02
22
CC
CO
0.21
80.
118
0.97
31
Tran
slat
ion
fact
or
End
opla
smic
etic
ulum
P16
303
Live
rca
rbox
yles
tera
se10
62.1
46.
34–0
.098
01:
0.59
21
ER
CC
S0.
051
0.51
80.
971
2E
nzym
eP
3083
9Fa
tty
ald
ehyd
ed
ehyd
roge
nase
54.0
87.
56–0
.101
11:
0.63
21
ER
CC
M0.
939
0.50
00.
971
3E
nzym
e
P24
368
Pep
tidyl
-pro
lylc
is-t
rans
isom
eras
eB
(Cyc
lop
hilin
B)
23.0
29.
30–0
.247
11:
0.74
21
ER
EX
CS
0.06
80.
003
0.76
41
Enz
yme
P08
113
End
opla
smin
(GR
P94
)92
.48
4.74
–0.7
20
1:0.
444
1E
RE
RC
S0.
022
0.05
70.
000
0M
olec
ular
chap
eron
eP
1841
8C
alre
ticul
in48
.00
4.33
–1.0
990
1:0.
53
0.03
102
ER
ER
NS
0.02
90.
002
0.66
81
Mol
ecul
arch
aper
one
Q63
617
150
kDa
oxyg
en-r
egul
ated
pro
tein
pre
curs
or(O
rp15
0)
111.
295.
11–0
.565
11:
0.66
0.
282
2E
RG
CS
0.15
20.
502
0.99
62
Mol
ecul
arch
aper
one
P04
785
Pro
tein
dis
ulfid
eis
omer
ase
(PD
I)56
.95
4.82
–0.3
820
1:0.
484
1E
RE
RC
S0.
059
0.45
60.
099
0P
rote
ind
isul
fide
isom
eras
efa
mily
P11
598
Pro
tein
dis
ulfid
eis
omer
ase
A3
(ER
p60
)56
.62
5.88
–0.4
550
1:0.
746
1E
RE
XC
S0.
030
0.05
90.
001
0P
rote
ind
isul
fide
isom
eras
efa
mily
P55
157
Mic
roso
mal
trig
lyce
ride
tran
sfer
pro
tein
,la
rge
sub
unit
99.3
58.
61–0
.177
01:
0.49
31
ER
EX
MS
0.05
40.
089
0.48
21
Tran
spor
ter
orch
anne
lp
rote
in
Ext
race
llula
ror
secr
eted
Q01
177
Pla
smin
ogen
90.5
46.
79–0
.697
01:
0.49
21
SN
EX
S0.
025
0.00
80.
004
0B
lood co
agul
atio
nor
fibrin
olys
is
ICAT Analysis of Rat Liver Mitochondria with Different Purity
16 Molecular & Cellular Proteomics 4.1
TAB
LEI—
cont
inue
d
Pro
tein
acce
ssio
nno
.P
rote
inna
me
Mr
(kD
a)p
IG
RA
VY
Pre
dH
elR
atio
(L:H
)(C
M:P
M)
nuP
SP
PS
OR
TS
ubLo
cTa
rget
Pm
TPM
itoP
rot
Pre
dot
arB
TFu
nctio
nal
clas
sific
atio
n
P18
292
Pro
thro
mb
in70
.41
6.28
–0.5
40
1:0.
681
1E
XE
XE
XS
0.13
50.
487
0.06
20
Blo
od coag
ulat
ion
orfib
rinol
ysis
P26
231
Alp
ha-1
cate
nin
100.
115.
91–0
.366
01:
0.44
11
EX
NN
O0.
092
0.00
50.
001
0In
tera
ctio
nsb
etw
een
cells
and
the
extr
acel
lula
rm
atrix
P10
960
Sul
fate
dgl
ycop
rote
in1
(SG
P-1
)(P
rosa
pos
in)
61.1
25.
13–0
.034
01:
0.46
0.
315
2E
XE
XE
XS
0.03
60.
128
0.94
31
Inte
ract
ions
bet
wee
nce
llsan
dth
eex
trac
ellu
lar
mat
rixP
0493
7Fi
bro
nect
in(F
N)
272.
515.
50–0
.501
01:
0.83
11
EX
NE
XS
0.24
90.
344
0.99
51
Inte
ract
ion
bet
wee
nce
llsan
dth
eex
trac
ellu
lar
mat
rixQ
0335
0Th
rom
bos
pon
din
212
9.91
4.61
–0.6
630
1:0.
921
1E
XN
EX
S0.
061
0.00
70.
008
0In
tera
ctio
nsb
etw
een
cells
and
the
extr
acel
lula
rm
atrix
NP
_075
591.
1�
(1)-
inhi
bito
r3,
varia
ntI
165.
335.
68–0
.222
11:
0.57
0.
093
2S
CE
XS
0.04
30.
021
0.00
60
Pro
teas
ein
hib
itor
Q64
240
AM
BP
pro
tein
38.8
55.
77–0
.363
01:
0.54
21
SC
EX
S0.
012
0.02
50.
019
0P
rote
ase
inhi
bito
rP
1404
6�
-1-i
nhib
itor
III16
3.77
5.70
–0.2
161
1:0.
54
0.30
32
SC
EX
S0.
024
0.01
00.
000
0P
rote
ase
inhi
bito
rP
2866
6M
urin
oglo
bul
in2
(MuG
2)16
2.37
6.34
–0.2
650
1:0.
652
1S
EX
EX
S0.
292
0.16
50.
403
0P
rote
ase
inhi
bito
rP
0277
0S
erum
alb
umin
68.7
26.
09–0
.389
01:
0.30
0.
1348
17S
EX
EX
S0.
405
0.72
10.
507
2R
egul
ator
yp
rote
inP
2409
0�
-2-H
S-g
lyco
pro
tein
pre
curs
or(F
etui
n-A
)37
.98
6.05
–0.0
850
1:0.
39
0.07
83
SE
XE
XS
0.03
30.
376
0.00
00
Sig
nalin
gp
rote
inQ
9Z0M
9IL
-18
bin
din
gp
rote
inp
recu
rsor
(IL-1
8BP
)11
.99
7.79
–0.0
610
1:0.
891
1S
ME
XS
0.01
30.
009
0.00
01
Sig
nalin
gp
rote
inP
0277
3�
-fet
opro
tein
(�-
feto
glob
ulin
)47
.23
5.47
–0.4
130
1:0.
26
0.03
74
SN
EX
O0.
069
0.02
80.
000
0Tr
ansp
orte
ror
chan
nel
pro
tein
NP
_775
443.
1H
emife
rrin
,tr
ansf
errin
-lik
ep
rote
in24
.09
7.86
–0.6
140
1:0.
332
1S
NN
O0.
129
0.10
90.
000
0Tr
ansp
orte
ror
chan
nel
pro
tein
P12
346
Ser
otra
nsfe
rrin
(Tra
nsfe
rrin
)76
.36
6.94
–0.2
520
1:0.
33
0.01
53
SE
XE
XS
0.03
70.
069
0.00
40
Tran
spor
ter
orch
anne
lp
rote
inP
0691
1E
pid
idym
alse
cret
ory
pro
tein
I(E
SP
-I)
16.3
67.
55–0
.038
01:
0.42
0.
054
2S
EX
EX
S0.
017
0.02
40.
984
1Tr
ansp
orte
ror
chan
nel
pro
tein
P06
866
Hap
togl
obin
38.5
56.
10–0
.255
01:
0.43
41
SE
XE
XS
0.01
70.
228
0.02
80
Tran
spor
ter
orch
anne
lp
rote
inQ
91X
72H
emop
exin
51.3
47.
92–0
.442
11:
0.47
41
SE
XC
S0.
023
0.26
30.
620
1Tr
ansp
orte
ror
chan
nel
pro
tein
ICAT Analysis of Rat Liver Mitochondria with Different Purity
Molecular & Cellular Proteomics 4.1 17
TAB
LEI—
cont
inue
d
Pro
tein
acce
ssio
nno
.P
rote
inna
me
Mr
(kD
a)p
IG
RA
VY
Pre
dH
elR
atio
(L:H
)(C
M:P
M)
nuP
SP
PS
OR
TS
ubLo
cTa
rget
Pm
TPM
itoP
rot
Pre
dot
arB
TFu
nctio
nal
clas
sific
atio
n
P04
276
Vita
min
D-b
ind
ing
pro
tein
pre
curs
or(D
BP
)53
.54
5.65
–0.3
580
1:0.
48
0.13
32
SE
XE
XS
0.07
00.
075
0.03
20
Tran
spor
ter
orch
anne
lp
rote
inQ
9CX
I5A
RM
ET
pro
tein
20.3
78.
34–0
.411
01:
0.59
11
SE
XC
S0.
187
0.11
80.
423
0U
nkno
wn
func
tion
P81
828
Urin
ary
pro
tein
2(R
UP
-2)
11.0
77.
530.
262
01:
0.70
81
SE
XE
XS
0.03
40.
020
0.35
20
Unk
now
nfu
nctio
n
Lyso
som
alP
2061
1Ly
soso
mal
acid
pho
spha
tase
(LA
P)
48.3
26.
16–0
.194
21:
0.37
0.
042
2L
ER
NS
0.22
50.
142
0.00
60
Am
ino
acid
met
abol
ism
P80
067
Dip
eptid
yl-p
eptid
ase
I(C
athe
psi
nC
)52
.38
7.01
–0.2
740
1:0.
524
1L
EX
EX
S0.
033
0.02
00.
058
0P
rote
ase
Q9R
0J8
Legu
mai
n(A
spar
agin
ylen
dop
eptid
ase)
49.4
76.
09–0
.399
01:
0.61
21
LE
XE
XS
0.04
20.
053
0.03
30
Pro
teas
e
P14
562
Lyso
som
e-as
soci
ated
mem
bra
negl
ycop
rote
in1
(LA
MP
-1)
43.9
78.
31–0
.051
11:
0.39
0.
193
2L
Me
MS
0.09
50.
153
0.98
42
Reg
ulat
ory
pro
tein
P07
602
Pro
activ
ator
pol
ypep
tide
58.1
15.
06–0
.064
01:
0.15
21
LG
EX
S0.
058
0.11
90.
949
1S
phi
nGip
ids
deg
rad
atio
n
Nuc
lear
Q03
061
cAM
P-r
esp
onsi
veel
emen
tm
odul
ator
36.6
35.
57–0
.434
01:
0.84
11
NN
NO
0.13
70.
174
0.00
10
Tran
scrip
tion
orre
plic
atio
nfa
ctor
P27
706
Elo
ngat
ion
fact
or1-
�2
(EF-
1-�
-2)
50.1
59.
10–0
.257
01:
0.63
21
NC
CO
0.05
60.
005
0.00
30
Tran
slat
ion
fact
or
Per
oxis
omal
NP
_579
833.
1P
erox
isis
omal
2-en
oyl-
CoA
red
ucta
se32
.43
8.89
0.00
70
1:0.
834
1P
CM
S0.
095
0.50
00.
194
2E
nzym
e
P57
093
Phy
tano
yl-C
oAd
ioxy
gena
se38
.59
8.75
–0.4
590
1:0.
72
0.07
53
PC
MM
0.61
00.
441
0.82
73
Fatt
yac
id�
-ox
idat
ion
P21
775
Per
oxis
omal
3-ox
oacy
l-C
oAth
iola
seA
44.8
48.
530.
047
01:
0.60
0.
0910
2P
CN
M0.
690
0.08
50.
165
1Fa
tty
acid
�-
oxid
atio
nP
0787
1P
erox
isom
al3-
oxoa
cyl-
CoA
thio
lase
B43
.82
8.53
0.04
70
1:0.
72
0.19
92
PC
NM
0.71
60.
232
0.35
51
Fatt
yac
id�
-ox
idat
ion
cycl
eN
P_1
1367
8.2
Per
oxis
omal
Ion
pro
teas
e94
.62
6.88
–0.1
950
1:0.
651
1P
PC
O0.
055
0.62
50.
248
1P
rote
ase
Rib
osom
alP
5302
560
Srib
osom
alp
rote
inL1
0a(C
SA
-19)
24.8
39.
94–0
.419
01:
0.31
11
RN
CO
0.45
00.
682
0.00
21
Rib
osom
alp
rote
inP
0464
560
Srib
osom
alp
rote
inL3
012
.78
9.65
–0.3
140
1:0.
331
1R
CN
O0.
450
0.88
40.
332
1R
ibos
omal
pro
tein
P23
358
60S
ribos
omal
pro
tein
L12
17.8
59.
48–0
.363
01:
0.43
11
RC
MO
0.08
90.
006
0.00
01
Rib
osom
alp
rote
inP
1994
460
Sac
idic
ribos
omal
pro
tein
P1
11.5
04.
280.
132
01:
0.60
31
RC
CS
0.02
90.
024
0.00
00
Rib
osom
alp
rote
in
ICAT Analysis of Rat Liver Mitochondria with Different Purity
18 Molecular & Cellular Proteomics 4.1
TAB
LEI—
cont
inue
d
Pro
tein
acce
ssio
nno
.P
rote
inna
me
Mr
(kD
a)p
IG
RA
VY
Pre
dH
elR
atio
(L:H
)(C
M:P
M)
nuP
SP
PS
OR
TS
ubLo
cTa
rget
Pm
TPM
itoP
rot
Pre
dot
arB
TFu
nctio
nal
clas
sific
atio
n
Cav
eola
eQ
9Z1E
1Fl
otill
in-1
47.5
06.
71–0
.356
01:
0.86
11
CA
VC
MO
0.27
30.
212
0.00
21
Intr
acel
lula
rtr
affic
king
Cyt
oske
leta
lQ
9ER
D7
Tub
ulin
�-3
50.4
24.
82–0
.371
01:
0.76
21
CS
KC
SK
CO
0.08
80.
043
0.00
00
Cyt
oske
leta
l
Gol
gico
mp
lex
Q62
638
Ggi
app
arat
usp
rote
in1
133.
566.
52–0
.48
11:
0.24
11
GM
eN
S0.
468
0.47
40.
982
1S
igna
ling
pro
tein
Pla
sma
mem
bra
neP
2645
3B
asig
in29
.59
5.12
–0.2
21
1:0.
424
1M
eG
CS
0.03
20.
033
0.01
40
Inte
ract
ions
bet
wee
nce
llsan
dth
eex
trac
ellu
lar
mat
rixM
itoch
ond
rial
pro
tein
sM
itoch
ond
rial
Q02
253
Met
hylm
alon
ate-
sem
iald
ehyd
ed
ehyd
roge
nase
(MM
SD
H)
57.8
18.
47–0
.048
11:
1.17
31
MM
MM
0.90
40.
942
0.79
05
Am
ino
acid
met
abol
ism
P23
434
Gly
cine
clea
vage
syst
emH
pro
tein
18.6
15.
36–0
.285
01:
1.38
31
MM
MM
0.89
50.
999
0.98
65
Am
ino
acid
met
abol
ism
O70
351
3-hy
dro
xyac
yl-C
oAd
ehyd
roge
nase
typ
eII
(Typ
eII
HA
DH
)
27.2
58.
910.
237
01:
1.05
11
MC
MM
0.63
10.
858
0.97
94
Enz
yme
P29
266
3-hy
dro
xyis
obut
yrat
ed
ehyd
roge
nase
(HIB
AD
H)
35.3
08.
730.
031
01:
2.07
31
MM
NM
0.94
30.
990
0.42
93
Enz
yme
P13
437
3-ke
toac
yl-C
oAth
iola
se( �
-ket
othi
olas
e)41
.87
8.09
–0.0
440
1:2.
182
1M
CM
M0.
594
0.53
90.
508
4Fa
tty
acid
�-
oxid
atio
nP
2279
1H
ydro
xym
ethy
lglu
tary
l-C
oAsy
ntha
se(H
MG
-CoA
synt
hase
)
56.9
18.
86–0
.36
01:
1.76
31
MM
MM
0.92
50.
952
0.99
45
Ket
one
bod
ym
etab
olis
m
P17
764
Ace
tyl-
CoA
acet
yltr
ansf
eras
e(A
CE
TOA
CE
TYL-
CO
ATH
IOLA
SE
)
44.6
98.
920.
086
01:
3.18
111
MC
MM
0.90
40.
994
0.92
94
Ket
one
bod
ym
etab
olis
m
P48
721
Str
ess-
70p
rote
in(G
RP
75)
(pep
tide-
bin
din
gp
rote
in74
)
73.8
65.
97–0
.424
01:
3.26
21
MM
MM
0.91
20.
939
0.98
95
Mol
ecul
arch
aper
one
Q9Y
4W6
AFG
3-lik
ep
rote
in2
(par
aple
gin-
like
pro
tein
)88
.48
8.87
–0.3
522
1:1.
682
1M
ER
CM
0.71
50.
858
0.96
23
Pro
teas
e
Q9J
HS
4A
TP-d
epen
den
tC
LPp
rote
ase
ATP
-bin
din
gsu
bun
itC
lpX
-lik
e
69.3
18.
07–0
.421
01:
1.81
11
MM
NM
0.55
80.
975
0.01
33
Pro
teas
e
P31
399
ATP
synt
hase
Dch
ain
18.7
66.
16–0
.718
01:
1.25
71
MC
NO
0.09
80.
501
0.17
91
The
oxid
ativ
ep
hosp
hory
latio
n(O
XP
HO
S)
ICAT Analysis of Rat Liver Mitochondria with Different Purity
Molecular & Cellular Proteomics 4.1 19
TAB
LEI—
cont
inue
d
Pro
tein
acce
ssio
nno
.P
rote
inna
me
Mr
(kD
a)p
IG
RA
VY
Pre
dH
elR
atio
(L:H
)(C
M:P
M)
nuP
SP
PS
OR
TS
ubLo
cTa
rget
Pm
TPM
itoP
rot
Pre
dot
arB
TFu
nctio
nal
clas
sific
atio
n
P35
435
ATP
synt
hase
�ch
ain
30.1
98.
87–0
.221
01:
1.73
71
MM
MO
0.44
50.
848
0.85
24
The
oxid
ativ
ep
hosp
hory
latio
n(O
XP
HO
S)
P30
042
ES
1p
rote
inho
mol
og(p
rote
inK
NP
-I)
28.1
48.
500.
030
1:4.
401
1M
MM
M0.
918
0.63
30.
895
5Tr
ansp
orte
ror
chan
nelp
rote
inP
1308
6S
ucci
nyl-
CoA
synt
heta
se�
chai
n(S
CS
-�)
35.0
39.
54–0
.092
01:
1.19
0.
039
2M
MM
M0.
866
0.84
40.
983
5TC
Acy
cle
Q9Z
219
Suc
ciny
l-C
oAsy
nthe
tase
,�
Ach
ain
(SC
S-�
A)
46.2
45.
65–0
.031
01:
1.72
11
MC
CO
0.29
90.
264
0.00
30
TCA
cycl
e
P54
071
Isoc
itrat
ed
ehyd
roge
nase
(IDH
)58
.75
8.89
–0.4
020
1:4.
251
1M
CM
O0.
303
0.01
20.
977
2TC
Acy
cle
P07
756
Car
bam
oyl-
pho
spha
tesy
nthe
tase
I(C
PS
AS
EI)
164.
586.
33–0
.117
01:
2.14
0.
4639
8M
CC
M0.
695
0.94
60.
862
3U
rea
cycl
e
Mito
chon
dria
linn
erm
emb
rane
P99
028
Ub
iqui
nol-
cyto
chro
me
cre
duc
tase
com
ple
x11
-kD
ap
rote
in(c
omp
lex
IIIsu
bun
itV
III)
10.4
34.
81–0
.987
01:
1.25
41
MIM
NN
O0.
063
0.00
30.
000
0Th
eox
idat
ive
pho
spho
ryla
tion
(OX
PH
OS
)
Q16
134
Ele
ctro
ntr
ansf
erfla
vop
rote
in-u
biq
uino
neox
idor
educ
tase
68.2
07.
33–0
.311
01:
1.62
0.
3713
3M
IMM
CO
0.36
00.
952
0.99
63
The
oxid
ativ
ep
hosp
hory
latio
n(O
XP
HO
S)
P52
504
NA
DH
-ub
iqui
none
oxid
ored
ucta
se13
-kD
a-A
sub
unit
(com
ple
xI-
13K
D-A
)
12.7
89.
37–0
.376
01:
1.89
31
MIM
MM
M0.
937
0.96
70.
999
5Th
eox
idat
ive
pho
spho
ryla
tion
(OX
PH
OS
)
P32
551
Ub
iqui
nol-
cyto
chro
me
cre
duc
tase
com
ple
xco
rep
rote
in2
(com
ple
xIII
sub
unit
II)
48.3
79.
16–0
.068
01:
1.85
31
MIM
CM
M0.
781
0.80
50.
999
4Th
eox
idat
ive
pho
spho
ryla
tion
(OX
PH
OS
)
Q9D
6J6
NA
DH
-ub
iqui
none
oxid
ored
ucta
se24
-kD
asu
bun
it
27.3
27.
00–0
.307
01:
3.76
11
MIM
MN
M0.
945
0.99
20.
998
4Th
eox
idat
ive
pho
spho
ryla
tion
(OX
PH
OS
)P
1626
1M
itoch
ond
rials
olut
eca
rrie
rp
rote
inho
mol
og33
.50
8.59
0.25
10
1:3.
751
1M
IMC
EX
S0.
021
0.74
30.
000
1Tr
ansp
orte
ror
chan
nelp
rote
inM
itoch
ond
rial
inte
rmem
bra
nesp
ace
Q07
116
Sul
fite
oxid
ase
54.3
55.
79–0
.408
01:
1.83
11
MIM
SC
EX
O0.
303
0.04
30.
013
0A
min
oac
idm
etab
olis
mQ
9JM
53P
rogr
amm
edce
lld
eath
pro
tein
8(a
pop
tosi
s-in
duc
ing
fact
or)
66.7
29.
06–0
.231
01:
1.31
41
MIM
SC
MM
0.74
60.
850
0.99
64
Ap
opto
sis
Q9D
0M3
Cyt
ochr
ome
c1(c
ytoc
hrom
ec-
1)35
.33
9.24
–0.2
471
1:1.
391
1M
IMS
MM
M0.
876
0.91
40.
704
5Th
eox
idat
ive
pho
spho
ryla
tion
(OX
PH
OS
)
Mito
chon
dria
lmat
rixP
1200
7Is
oval
eryl
-CoA
deh
ydro
gena
se(IV
D)
46.4
48.
03–0
.113
01:
1.02
11
MM
AM
MM
0.92
80.
994
0.99
35
Am
ino
acid
met
abol
ism
P00
507
Asp
arta
team
inot
rans
fera
se(T
rans
amin
ase
A)
47.3
19.
13–0
.23
01:
1.56
11
MM
AC
MM
0.81
80.
643
0.70
44
Am
ino
acid
met
abol
ism
ICAT Analysis of Rat Liver Mitochondria with Different Purity
20 Molecular & Cellular Proteomics 4.1
TAB
LEI—
cont
inue
d
Pro
tein
acce
ssio
nno
.P
rote
inna
me
Mr
(kD
a)p
IG
RA
VY
Pre
dH
elR
atio
(L:H
)(C
M:P
M)
nuP
SP
PS
OR
TS
ubLo
cTa
rget
Pm
TPM
itoP
rot
Pre
dot
arB
TFu
nctio
nal
clas
sific
atio
n
P97
519
Hyd
roxy
met
hylg
luta
ryl-
CoA
lyas
e(H
MG
-CO
ALY
AS
E)
34.1
98.
690.
198
01:
1.85
11
MM
AM
MM
0.88
40.
974
0.99
65
Am
ino
acid
met
abol
ism
P10
860
Glu
tam
ate
deh
ydro
gena
se(G
DH
)61
.43
8.05
–0.3
160
1:3.
031
1M
MA
CC
M0.
614
0.76
80.
823
3A
min
oac
idm
etab
olis
mP
2911
7P
eptid
yl-p
roly
lcis
-tra
nsis
omer
ase
(Cyc
lop
hilin
F)21
.81
9.30
–0.1
640
1:1.
69
0.25
32
MM
AC
CO
0.15
60.
088
0.16
80
Enz
yme
P53
395
Lip
oam
ide
acyl
tran
sfer
ase
com
pon
ent
ofb
ranc
hed
-ch
ain
�-k
eto
acid
deh
ydro
gena
seco
mp
lex
53.4
68.
71–0
.165
01:
2.02
0.
754
2M
MA
MM
M0.
932
0.99
80.
713
5E
nzym
e
P29
147
D- �
-hyd
roxy
but
yrat
ed
ehyd
roge
nase
(BD
H)
38.3
58.
93–0
.234
01:
2.19
0.
5619
4M
MA
CM
M0.
849
0.88
90.
824
4E
nzym
e
O08
749
Dih
ydro
lipoa
mid
ed
ehyd
roge
nase
54.2
17.
97–0
.033
01:
2.21
0.
6612
2M
MA
MC
M0.
914
0.98
70.
987
4E
nzym
e
P11
884
Ald
ehyd
ed
ehyd
roge
nase
(ALD
Hcl
ass
2)(A
LDH
1)(A
LDH
-E2)
56.4
96.
63–0
.138
01:
1.41
0.
195
2M
MA
MM
M0.
907
0.99
60.
937
5E
than
olut
iliza
tion
Q64
428
Trifu
nctio
nale
nzym
eal
pha
sub
unit
(TP
-alp
ha)
82.5
19.
11–0
.05
01:
1.10
21
MM
AM
MM
0.91
30.
998
0.97
65
Fatt
yac
id�
-ox
idat
ion
NP
_032
238.
1H
ydro
xyla
cyl-
Coe
nzym
eA
deh
ydro
gena
se33
.09
7.73
–0.1
691
1:1.
343
1M
MA
CM
O0.
303
0.72
30.
663
3Fa
tty
acid
�-
oxid
atio
nP
1460
4S
hort
chai
nen
oyl-
CoA
hyd
rata
se(S
CE
H)
31.5
28.
40–0
.104
01:
2.56
0.
3314
2M
MA
MM
M0.
905
0.98
30.
208
4Fa
tty
acid
�-
oxid
atio
nQ
9WV
K7
3-hy
dro
xyac
yl-C
oAd
ehyd
roge
nase
(HC
DH
)34
.45
8.83
–0.1
420
1:3.
86
1.35
42
MM
AM
MM
0.80
90.
995
0.96
65
Fatt
yac
id�
-ox
idat
ion
P49
432
Pyr
uvat
ed
ehyd
roge
nase
E1
com
pon
ent
�su
bun
it(P
DH
E1-
B)
38.8
55.
940.
116
01:
1.28
11
MM
AC
CM
0.76
30.
989
0.97
53
Gly
coly
sis
P26
284
Pyr
uvat
ed
ehyd
roge
nase
E1
com
pon
ent
�su
bun
it(P
DH
E1-
Aty
pe
I)
43.2
18.
49–0
.304
01:
1.36
11
MM
AC
MM
0.90
00.
995
0.96
64
Gly
coly
sis
P08
461
Dih
ydro
lipoa
mid
eac
etyl
tran
sfer
ase
com
pon
ent
ofp
yruv
ate
deh
ydro
gena
seco
mp
lex
(PD
C-E
2)
58.7
65.
700.
034
01:
2.77
0.
648
3M
MA
ER
EX
O0.
110
0.03
80.
000
0G
lyco
lysi
s
P19
226
60-k
Da
heat
shoc
kp
rote
in(H
sp60
)60
.96
5.91
–0.0
850
1:2.
69
0.40
243
MM
AC
CM
0.92
60.
995
0.98
13
Mol
ecul
arch
aper
one
P24
329
Thio
sulfa
tesu
lfurt
rans
fera
se(R
hod
anes
e)
33.1
87.
84–0
.463
01:
2.06
41
MM
AM
MM
0.63
90.
941
0.56
95
The
oxid
ativ
ep
hosp
hory
latio
n(O
XP
HO
S)
P13
803
Ele
ctro
ntr
ansf
erfla
vop
rote
in�
-sub
unit
(�-E
TF)
34.9
88.
670.
120
1:3.
005
1M
MA
MC
M0.
936
0.97
10.
182
3Th
eox
idat
ive
pho
spho
ryla
tion
(OX
PH
OS
)P
0463
6M
alat
ed
ehyd
roge
nase
35.6
68.
920.
121
01:
2.30
0.
5559
5M
MA
MM
M0.
903
0.99
50.
869
5TC
Acy
cle
Mito
chon
dria
lout
erm
emb
rane
P19
643
Mon
oam
ine
oxid
ase
(MA
O-
B)
58.3
98.
30–0
.152
11:
2.01
31
MO
MC
CO
0.02
50.
022
0.00
00
Am
ino
acid
met
abol
ism
Q60
932
Vol
tage
-dep
end
ent
anio
n-se
lect
ive
chan
nelp
rote
in1
(VD
AC
-1)
32.3
58.
55–0
.334
01:
2.48
41
MO
MC
MS
0.05
70.
026
0.02
01
Tran
spor
ter
orch
anne
lpro
tein
ICAT Analysis of Rat Liver Mitochondria with Different Purity
Molecular & Cellular Proteomics 4.1 21
TAB
LEI—
cont
inue
d
Pro
tein
acce
ssio
nno
.P
rote
inna
me
Mr
(kD
a)p
IG
RA
VY
Pre
dH
elR
atio
(L:H
)(C
M:P
M)
nuP
SP
PS
OR
TS
ubLo
cTa
rget
Pm
TPM
itoP
rot
Pre
dot
arB
TFu
nctio
nal
clas
sific
atio
n
Mito
chon
dria
-ass
ocia
ted
mul
tiloc
atio
np
rote
ins
Q62
651
�3,5
-�2,
4-d
ieno
yl-C
oAis
omer
ase
36.1
78.
14–0
.097
01:
0.22
31
M,
PP
NM
0.60
00.
976
0.18
62
Fatt
yac
id�
-oxi
dat
ion
P18
163
Long
-cha
inac
yl-C
oAsy
nthe
tase
2(L
AC
S2)
78.1
86.
60–0
.08
11:
1.13
0.
034
2M
OM
,E
R,
PC
CO
0.09
50.
092
0.02
90
Fatt
yac
id�
-oxi
dat
ion
Q9R
063
Per
oxire
dox
in5
22.1
88.
940.
179
01:
1.42
61
M,
C,
PM
CM
0.61
30.
799
0.98
84
Red
oxin
Q63
272
Tyro
sine
-pro
tein
kina
seJA
K3
(JA
K-3
)12
5.02
6.64
–0.1
360
1:2.
611
1W
CC
O0.
064
0.08
40.
000
0S
igna
ling
pro
tein
P52
759
14.5
-kD
atr
ansl
atio
nal
inhi
bito
rp
rote
in14
.30
7.80
0.20
40
1:0.
672
1M
,C
,N
MM
O0.
425
0.87
10.
977
4Tr
ansl
atio
nfa
ctor
P11
915
Non
spec
ific
lipid
-tra
nsfe
rp
rote
in(N
SL-
TP)
58.8
16.
62–0
.222
01:
1.25
21
M,
C,
PC
MM
0.50
40.
753
0.54
94
Tran
spor
ter
orch
anne
lp
rote
inP
rote
ins
with
sub
cellu
lar
loca
tion
anno
tatio
nno
tin
acco
rdan
cew
ithIC
AT
anal
ysis
Q8V
ID1
NA
DP
-ret
inol
deh
ydro
gena
se27
.58
9.06
0.19
70
1:1.
38
0.03
42
PE
RM
M0.
686
0.52
20.
537
4E
nzym
e
P04
762
Cat
alas
e59
.76
7.07
–0.6
430
1:1.
41
0.26
272
P,
M (37,
53–5
5)
CN
O0.
083
0.11
50.
000
0E
nzym
e
P47
199
Qui
none
oxid
ored
ucta
se(N
AD
PH
:qui
none
red
ucta
se)
( -c
ryst
allin
)
35.2
78.
18–0
.009
01:
1.46
0.
213
2C
CC
O0.
415
0.15
90.
890
1E
nzym
e
Q9Q
XE
02-
hyd
roxy
phy
tano
yl-C
oAly
ase
(2-H
PC
L)63
.62
7.07
–0.0
610
1:2.
721
1P
CS
KC
O0.
103
0.02
90.
000
0Fa
tty
acid
�-o
xid
atio
nP
0789
6P
erox
isom
alb
ifunc
tiona
len
zym
e(P
BFE
)78
.66
9.28
–0.1
090
1:1.
02
0.04
123
PP
MO
0.32
50.
487
0.00
31
Fatt
yac
id�
-oxi
dat
ion
P97
852
Per
oxis
omal
mul
tifun
ctio
nal
enzy
me
typ
e2
(MFE
-2)
79.4
38.
77–0
.104
01:
1.46
0.
378
3P
PM
M0.
562
0.17
20.
404
2Fa
tty
acid
�-o
xid
atio
nO
0880
7P
erox
ired
oxin
4(P
rx-I
V)
31.0
16.
18–0
.249
01:
1.13
21
CE
RC
S0.
023
0.09
00.
000
0R
edox
inP
4313
8D
NA
-(ap
urin
icor
apyr
imid
inic
site
)ly
ase
(AP
end
oNle
ase
1)
35.5
48.
04–0
.597
01:
4.55
11
N,
M (56)
NN
O0.
090
0.05
60.
001
0Tr
ansc
riptio
nor re
plic
atio
nfa
ctor
P16
970
ATP
-bin
din
gca
sset
tesu
b-
fam
ilyD
mem
ber
3(P
MP
70)
75.3
29.
32–0
.152
31:
1.75
11
PC
MM
0.89
10.
781
0.88
64
Tran
spor
ter
orch
anne
lp
rote
inK
now
np
rote
ins
with
out
sub
cellu
lar
loca
tion
anno
tatio
nin
Sw
iss-
Pro
td
atab
ase
NP
_077
057.
1B
ileac
idC
oAlig
ase
76.2
78.
540.
081
11:
0.66
0.
094
2E
R(5
7)E
RC
S0.
012
0.93
90.
113
1B
ileac
idm
etab
olis
mN
P_0
5899
6.1
Bile
acid
-Coe
nzym
eA
:am
ino
acid
N-
acyl
tran
sfer
ase
46.5
06.
97–0
.05
01:
0.71
0.
2510
3C
,P
(57)
CC
O0.
052
0.07
60.
000
0B
ileac
idm
etab
olis
m
P48
500
Trio
sep
hosp
hate
isom
eras
e(T
IM)
26.8
56.
89–0
.10
1:2.
601
1N
AC
CO
0.17
80.
326
0.94
41
Enz
yme
P08
109
Hea
tsh
ock
cogn
ate
71-
kDa
pro
tein
70.8
75.
37–0
.452
01:
0.76
21
C,
Me
(58)
CC
O0.
095
0.02
00.
000
0M
olec
ular
chap
eron
eP
0965
0M
ast
cell
pro
teas
eI
pre
curs
or(R
MC
P-I
)(C
hym
ase)
28.6
29.
54–0
.28
01:
3.03
21
NA
EX
MS
0.02
60.
013
0.69
62
Pro
teas
e
NP
_620
796.
1P
eptid
ylp
roly
liso
mer
ase
C-a
ssoc
iate
dp
rote
in;
mam
a
63.7
75.
14–0
.092
01:
0.70
11
EX
(59)
EX
EX
S0.
026
0.01
40.
067
0R
egul
ator
yp
rote
in
ICAT Analysis of Rat Liver Mitochondria with Different Purity
22 Molecular & Cellular Proteomics 4.1
TAB
LEI—
cont
inue
d
Pro
tein
acce
ssio
nno
.P
rote
inna
me
Mr
(kD
a)p
IG
RA
VY
Pre
dH
elR
atio
(L:H
)(C
M:P
M)
nuP
SP
PS
OR
TS
ubLo
cTa
rget
Pm
TPM
itoP
rot
Pre
dot
arB
TFu
nctio
nal
clas
sific
atio
n
NP
_112
173.
1P
rote
inki
nase
NY
D-S
P15
58.4
68.
34–0
.503
01:
0.40
11
NA
NN
O0.
421
0.03
20.
011
0S
igna
ling
pro
tein
NP
_079
076.
2N
IMA
(nev
erin
mito
sis
gene
a)-r
elat
edki
nase
1174
.16
5.02
–0.5
960
1:12
.34
11
NA
NC
O0.
162
0.70
60.
069
1S
igna
ling
pro
tein
O43
295
SLI
T-R
OB
OR
hoG
TPas
eac
tivat
ing
pro
tein
212
1.43
6.29
–0.7
340
1:4.
901
1N
AN
NO
0.14
30.
008
0.00
50
Sig
nalin
gp
rote
inN
P_0
0909
9.1
ATP
-bin
din
gca
sset
tesu
b-
fam
ilyA
mem
ber
817
9.25
6.81
0.05
513
1:3.
391
1N
AM
eE
XS
0.32
50.
984
0.05
91
Tran
spor
ter
orch
anne
lp
rote
inP
0903
4A
rgin
inos
ucci
nate
synt
hase
(Citr
ullin
e—as
par
tate
ligas
e)
46.5
07.
63–0
.357
01:
0.58
11
C(6
0)C
CO
0.06
00.
033
0.00
00
Ure
acy
cle
NP
_057
128.
1C
GI-
105
pro
tein
34.5
88.
48–0
.028
01:
0.17
41
NA
CC
M0.
881
0.57
40.
906
3U
nkno
wn
func
tion
Nov
elp
rote
ins
XP
_218
339.
2S
imila
rto
CD
NA
seq
uenc
eB
C02
4561
13.8
010
.26
–0.9
140
1:0.
031
1N
AE
XC
S0.
047
0.05
10.
078
0N
ovel
pro
tein
XP
_219
866.
2S
imila
rto
lam
inin
-2�
2ch
ain
356.
536.
33–0
.432
01:
0.05
11
NA
NE
XO
0.21
30.
020
0.00
00
Nov
elp
rote
in
BA
A21
571.
1K
IAA
0315
205.
415.
88–0
.31
01:
0.13
11
NA
ER
CS
0.21
50.
006
0.01
60
Nov
elp
rote
inX
P_1
1142
1.2
Sim
ilar
tom
yosi
nlig
htch
ain
kina
se(M
LCK
)77
.83
5.19
–0.5
840
1:0.
161
1N
AN
NO
0.22
90.
042
0.00
50
Nov
elp
rote
in
XP
_233
583.
2S
imila
rto
CG
8312
-PA
36.6
110
.96
–0.3
460
1:0.
161
1N
AN
NO
0.32
60.
170
0.49
50
Nov
elp
rote
inX
P_3
4158
6.1
Sim
ilar
tohy
pot
hetic
alp
rote
in33
.50
8.17
–0.3
010
1:0.
251
1N
AM
MS
0.12
80.
883
0.99
34
Nov
elp
rote
in
XP
_230
637.
2S
imila
rto
ribos
ome-
bin
din
gp
rote
in1
143.
339.
00–1
.212
01:
0.25
0.
053
2N
AN
NO
0.11
00.
013
0.26
90
Nov
elp
rote
in
XP
_062
871.
4S
imila
rto
cent
rom
eric
pro
tein
E73
1.60
9.07
–0.7
960
1:0.
341
1N
AN
NO
0.13
90.
210
0.00
10
Nov
elp
rote
in
CA
C82
023.
1K
CH
IP2A
pro
tein
23.5
84.
45–0
.562
01:
0.43
11
NA
CN
O0.
063
0.05
00.
000
0N
ovel
pro
tein
XP
_141
021.
2S
imila
rto
pep
tidyl
pro
lyl
isom
eras
eA
17.3
76.
58–0
.526
01:
0.44
31
NA
CC
O0.
123
0.06
00.
000
0N
ovel
pro
tein
XP
_077
170.
2R
IKE
NcD
NA
2310
005D
1232
.40
8.60
–0.0
040
1:0.
501
1N
AC
NM
0.85
20.
537
0.77
23
Nov
elp
rote
inX
P_2
1592
0.2
Sim
ilar
top
rote
ctiv
ep
rote
inp
recu
rsor
�m
ouse
57.1
15.
74–0
.326
01:
0.58
71
NA
EX
EX
O0.
413
0.77
20.
948
2N
ovel
pro
tein
XP
_358
748.
1S
imila
rto
hyp
othe
tical
pro
tein
FLJ3
3071
47.9
95.
80–0
.758
01:
0.69
11
NA
NN
O0.
072
0.01
40.
000
0N
ovel
pro
tein
XP
_235
656.
2S
imila
rto
exp
ress
edse
que
nce
AI3
1723
717
8.35
8.63
–0.0
390
1:1.
241
1N
AM
eM
O0.
103
0.02
90.
000
1N
ovel
pro
tein
XP
_345
943.
1S
imila
rto
chai
nA
,so
lutio
nst
ruct
ure
ofth
eb
ola-
like
pro
tein
from
Mus
mus
culu
s
48.0
07.
93–0
.262
01:
1.53
21
NA
CE
XO
0.14
30.
181
0.01
40
Nov
elp
rote
in
NP
_705
771.
1R
IKE
NcD
NA
D33
0038
I09
101.
565.
96–0
.196
01:
1.37
41
NA
EX
CM
0.79
10.
950
0.99
43
Nov
elp
rote
inN
P_7
7727
1.2
RIK
EN
cDN
A62
3041
0P16
55.2
96.
190.
120
1:1.
411
1N
AC
CM
0.75
00.
986
0.56
23
Nov
elp
rote
inX
P_2
1621
2.2
Sim
ilar
toR
IKE
NcD
NA
0710
001P
0935
.25
6.21
–0.8
830
1:1.
511
1N
AN
EX
O0.
078
0.07
10.
000
0N
ovel
pro
tein
XP
_230
613.
2S
imila
rto
glyc
olat
eox
idas
e40
.97
6.92
–0.0
890
1:1.
664
1N
AC
MO
0.07
80.
185
0.00
21
Nov
elp
rote
inX
P_2
1446
4.2
Sim
ilar
toP
ecip
rote
in39
.31
8.67
–0.2
950
1:1.
70
0.27
42
NA
MM
O0.
102
0.12
80.
000
2N
ovel
pro
tein
ICAT Analysis of Rat Liver Mitochondria with Different Purity
Molecular & Cellular Proteomics 4.1 23
TAB
LEI—
cont
inue
d
Pro
tein
acce
ssio
nno
.P
rote
inna
me
Mr
(kD
a)p
IG
RA
VY
Pre
dH
elR
atio
(L:H
)(C
M:P
M)
nuP
SP
PS
OR
TS
ubLo
cTa
rget
Pm
TPM
itoP
rot
Pre
dot
arB
TFu
nctio
nal
clas
sific
atio
n
XP
_217
417.
2S
imila
rto
RIK
EN
cDN
A99
3002
6A05
79.4
15.
65–0
.101
01:
1.24
21
NA
MC
M0.
736
0.65
20.
985
4N
ovel
pro
tein
XP
_342
795.
1S
imila
rto
alco
hol
deh
ydro
gena
se8
50.8
16.
23–0
.012
01:
1.73
31
NA
CM
O0.
143
0.03
70.
000
1N
ovel
pro
tein
XP
_129
663.
1R
IKE
NcD
NA
1300
013F
1537
.98
8.91
–0.1
381
1:1.
795
1N
AM
MS
0.51
60.
930
0.97
34
Nov
elp
rote
inX
P_2
1506
9.2
Sim
ilar
toR
IKE
NcD
NA
2300
002G
0249
.52
7.23
–0.1
790
1:1.
881
1N
AM
MM
0.90
90.
966
0.98
05
Nov
elp
rote
in
XP
_214
838.
1S
imila
rto
HS
CO
pro
tein
27.6
86.
58–0
.102
01:
1.96
11
NA
ME
XM
0.90
70.
968
0.95
34
Nov
elp
rote
inX
P_2
2526
9.1
Sim
ilar
tose
rine
pro
tein
ase
inhi
bito
rR
8641
.19
5.58
–0.2
440
1:2.
211
1N
AC
CO
0.09
90.
028
0.00
00
Nov
elp
rote
in
XP
_224
605.
1S
imila
rto
hyp
othe
tical
pro
tein
MG
C30
702
66.3
98.
75–0
.387
01:
2.37
11
NA
MM
M0.
929
0.95
10.
985
5N
ovel
pro
tein
XP
_351
356.
1S
imila
rto
hyp
othe
tical
pro
tein
DJ3
28E
19.C
1.1
147.
594.
47–0
.877
01:
2.65
11
NA
CN
O0.
228
0.00
70.
709
1N
ovel
pro
tein
XP
_358
637.
1H
ypot
hetic
alp
rote
inX
P_3
5863
722
.10
6.36
0.04
80
1:2.
681
1N
AE
XE
XS
0.10
50.
029
0.00
40
Nov
elp
rote
in
XP
_213
509.
2S
imila
rto
�-2
-gly
cop
rote
inI
44.1
48.
50–0
.167
01:
3.23
0.
8239
10N
AE
XE
XS
0.11
50.
138
0.48
40
Nov
elp
rote
in
XP
_226
323.
2S
imila
rto
Fant
omp
rote
in15
0.18
5.56
–0.6
970
1:3.
341
1N
AN
NO
0.20
40.
150
0.00
00
Nov
elp
rote
inX
P_2
1492
2.1
Sim
ilar
toR
IKE
NcD
NA
0610
0091
1627
.69
7.61
–0.0
760
1:3.
5116
1N
AC
MO
0.28
00.
119
0.20
91
Nov
elp
rote
in
XP
_230
555.
2S
imila
rto
KIA
A09
12p
rote
in22
5.98
5.78
–0.7
380
1:5.
031
1N
AN
NO
0.10
50.
008
0.01
00
Nov
elp
rote
in
BA
A91
171.
1U
nnam
edp
rote
inp
rod
uct
26.2
46.
12–0
.358
01:
5.20
11
NA
CC
O0.
136
0.02
70.
022
0N
ovel
pro
tein
BA
C86
004.
1U
nnam
edp
rote
inp
rod
uct
38.0
19.
71–0
.216
01:
7.87
11
NA
NN
O0.
565
0.90
20.
587
2N
ovel
pro
tein
XP
_342
531.
1S
imila
rto
cyst
eine
-ric
hp
rote
in2
bin
din
gp
rote
in90
.65
6.34
–0.5
180
1:7.
521
1N
AC
NO
0.10
90.
024
0.00
00
Nov
elp
rote
in
NP
_034
548.
1H
ect
(hom
olog
ous
toth
eE
6-A
P(U
BE
3A)
carb
oxyl
term
inus
)d
omai
nan
dR
CC
1(C
HC
1)-l
ike
dom
ain
(RLD
)2
527.
485.
84–0
.185
01:
10.0
51
1N
AM
eC
O0.
137
0.01
70.
001
0U
nkno
wn
func
tion
ICAT Analysis of Rat Liver Mitochondria with Different Purity
24 Molecular & Cellular Proteomics 4.1
proteins without subcellular location annotation, 22 (27.8%) ofthem have been annotated as extracellular or secreted pro-teins, 9 (11.4%) as endoplasmic reticulum, 6 (7.6%) as cyto-plasmic, 5 (6.3%) as peroxisomal, 5 (6.3%) as lysosomal, 4(5.1%) as ribosomal, 2 (2.5%) as nuclear, and 1 (1.3%) ascaveolae, membrane, Golgi complex, and cytoskeletal, re-spectively (Fig. 3A). Only two multilocation proteins have beenassociated with mitochondria (Table I). Delta-3,5-�2,4-dien-oyl-CoA isomerase with the ratio of PM:CM being 0.22 hasbeen annotated as mitochondrial and peroxisomal, and 14.5-kDa translational inhibitor protein with the ratio of PM:CMbeing 0.67 has been annotated as mitochondrial, cytoplas-mic, and nuclear.
On the contrary, for the 90 proteins with a ratio of PM:CM�1.0, 17 (18.9%) proteins have been annotated as mitochon-drial, 20 (22.2%) as mitochondrial matrix, 6 (6.7%) as mito-chondrial inner membrane, 3 (3.3%) as mitochondrial inter-membrane space, and 2 (2.2%) as mitochondrial outermembrane (Fig. 3B). Four mitochondria-associated multiloca-tion proteins have a ratio of PM:CM �1.0 (Table I). Long-chainacyl-CoA synthetase 2 (LACS 2) (1.13 0.03) has been an-notated as microsomes, outer mitochondrial membrane, andperoxisomal membrane. Nonspecific lipid-transfer protein(with the ratio of PM:CM being 1.25) has been annotated ascytoplasmic and mitochondrial. Peroxiredoxin 5 (1.42) hasbeen annotated as mitochondrial, peroxisomal, and cytoplas-mic. Tyrosine-protein kinase JAK3 (2.61) has been annotatedas wholly intracellular, possibly membrane associated.
As expected, all the annotated mitochondrial proteins have
a ratio of PM:CM �1.0, indicating their enrichment in PMfraction, while most proteins annotated as other organellessuch as endoplasmic reticulum, cytoplasmic, lysosomal, ribo-somal, nuclear, Golgi complex, caveolae, cytoskeletal, andmembrane, and some apparent contaminant proteins such assome extracellular or secreted proteins, for example, serumalbumin (0.30 0.13) and plasminogen (0.49), all have a ratioof PM/CM �1.0, indicating their decrease in PM fraction.Thus, using such a comparative proteomics research, mito-chondrial proteins have been effectively distinguished fromother contaminant proteins.
Bioinformatics Prediction—The five bioinformatics tools,PSORT II, SubLoc, TargetP, MitoProtII, and Predotar, havebeen used to predict subcellular location of the 169 proteins,respectively. For the overview prediction, PSORT II and Sub-Loc are used in the winner-takes-all mode without setting aspecificity cut-off for targeting. TargetP (mTP), MitoProtII, andPredotar predict proteins as mitochondrial based on a prob-ability cut-off of �0.50 (Fig. 2, Table I).
For the 79 proteins with a ratio of PM:CM �1.0, PSORTpredicted 3.8% (3/79) proteins as mitochondrial and 96.2%(76/79) as nonmitochondrial including 32.9% (26/79) as cyto-plasmic, 25.3% (20/79) as extracellular, 19.0% (15/79) asnuclear, 8.9% (7/79) as endoplasmic reticulum, 3.8% (3/79) asGolgi complex, 2.5% (2/79) as peroxisomal, 2.5% (2/79) asplasma membrane, and 1.3% (1/79) as cytoskeletal. SubLocpredicted 12.7% (10/79) proteins as mitochondrial and 87.3%(69/79) as nonmitochondrial including 34.2% (27/79) as cyto-plasmic, 30.4% (24/79) as extracellular, and 22.8% (18/79) as
FIG. 1. Category of the identified and quantitated 169 different proteins. The 169 proteins are categorized according to the number ofunique peptides used for protein identification and quantitation, physicochemical characteristics such as molecular mass, pI value, GRAVYvalue, and PredHel predicted by TMHMM, and ICAT ratio.
ICAT Analysis of Rat Liver Mitochondria with Different Purity
Molecular & Cellular Proteomics 4.1 25
nuclear. TargetP predicted 10.1% (8/79) proteins as mito-chondrial and 89.9% (71/79) as nonmitochondrial including51.9% (41/79) as secreted and 38.0% (30/79) as other. Mito-ProtII and Predotar predicted 21.5% (17/79) and 27.8% (22/79) proteins as mitochondrial in the 79 proteins with a ratio ofPM:CM �1.0, respectively. Moreover, for the 79 proteins witha ratio of PM:CM �1.0, 55.7% (44/79) proteins have beenpredicted as nonmitochondrial by all the five bioinformaticstools (BT � 0), only 8.9% (7/79) proteins have been predictedas mitochondrial by three of the five bioinformatics tools at thesame time (BT � 3), and only 2.5% (2/79) proteins predictedas mitochondrial by four of the five bioinformatics tools at thesame time (BT � 4) (Table II).
On the other hand, for the 90 proteins with a ratio of PM:CM�1.0, PSORT predicted 34.4% (31/90) proteins as mitochon-drial and 65.6% (59/90) as nonmitochondrial including 41.1%(37/90) as cytoplasmic, 4.4% (4/90) as extracellular, 8.9%(8/90) as nuclear, 4.4% (4/90) as endoplasmic reticulum, 2.2%(2/90) as peroxisomal, 3.3% (3/90) as plasma membrane, and1.1% (1/90) as cytoskeletal. SubLoc predicted 47.8% (43/90)proteins as mitochondrial and 52.2% (47/90) as nonmitochon-drial including 27.8% (25/90) as cytoplasmic, 10.0% (9/90) asextracellular, and 14.4% (13/90) as nuclear. TargetP predicted51.1% (46/90) proteins as mitochondrial and 48.9% (44/90) asnonmitochondrial including 8.9% (8/90) as secreted and40.0% (36/90) as other. MitoProtII and Predotar predicted
FIG. 2. Percentage of the proteins annotated or predicted as mitochondrial or nonmitochondrial in the proteins with different PM:CMratio cut-offs. A, percentage of nonmitochondrial proteins for proteins with ratios of PM:CM �1.0, �0.83, �0.67, and �0.50. B, percentageof mitochondrial proteins for proteins with ratios of PM:CM �1.0, �1.2, �1.5, and �2.0. For Swiss-Prot, only proteins with subcellular locationannotation are concerned. PSORT II and SubLoc are used in the winner-takes-all mode without setting a specificity cut-off for targeting.TargetP (mTP), MitoProtII, and Predotar predict proteins as mitochondrial based on a probability cut-off of �0.50.
ICAT Analysis of Rat Liver Mitochondria with Different Purity
26 Molecular & Cellular Proteomics 4.1
FIG. 3. Summary of the subcellular location of the identified proteins according to Swiss-Prot annotation. A, proteins with ratios ofPM:CM �1.0. B, proteins with ratios of PM:CM �1.0.
ICAT Analysis of Rat Liver Mitochondria with Different Purity
Molecular & Cellular Proteomics 4.1 27
60.0% (54/90) and 56.7% (51/90) proteins as mitochondrial inthe 90 proteins with a ratio of PM:CM �1.0, respectively.Moreover, for the 90 proteins with a ratio of PM:CM �1.0,74.4% (67/90) proteins have been predicted as mitochondrialby at least one bioinformatics tools (BT � 1), and 54.4%(49/90) proteins have been predicted as mitochondrial by atleast three of the five bioinformatics tools at the same time(BT � 3), in which 18 proteins have been predicted as mito-chondrial by all the five bioinformatics tools (BT � 5) (Table III).
As we can see, the prediction results also indicate the ICATanalysis has effectively distinguished mitochondrial proteinsfrom possible contaminant proteins. At the same time, thedifference among the results from the bioinformatics predic-tion, Swiss-Prot annotation, and ICAT analysis may resultfrom the limitations of the bioinformatics tools (45), proteinmultilocation, and even the faulty of Swiss-Prot database.
Proteins with Subcellular Location Annotation not in Ac-cordance with ICAT Analysis—Nine proteins that have beenannotated as nonmitochondrial in Swiss-Prot have a ratio ofPM:CM �1.0 (Table I). They include quinone oxidoreductase(-crystallin) (1.46 0.21) that was annotated as cytoplasmic,AP endonuclease 1 (4.55) annotated as nuclear, and catalase(1.41 0.26), ATP-binding cassette sub-family D member 3(1.75), peroxisomal multifunctional enzyme type 2 (MFE-2)(1.46 0.37), NADP-retinol dehydrogenase (1.38 0.03), and2-hydroxyphytanoyl-CoA lyase (2.72), which were annotatedas peroxisomal.
Catalase, a scavenger of H2O2, has been long known as themost abundant matrix protein within peroxisomes (52). How-ever, the presence of catalase in rat heart mitochondria wasdemonstrated by biochemical and immunocytochemical anal-ysis (53). Yeast catalase A (Cta1p) contains two peroxisomaltargeting signals localized at its carboxyl terminus (SSNSKF)and within the N-terminal third of the protein, which both cantarget foreign proteins to peroxisomes. It has been morerecently demonstrated that Cta1p can also enter mitochon-dria, although the enzyme lacks a classical mitochondrialimport sequence. Peroxisomal and mitochondrial coimport ofcatalase A were tested qualitatively by fluorescence micros-copy and functional complementation of a �cta1 null muta-tion, and quantitatively by subcellular fractionation followedby Western analysis and enzyme activity assays (54). Moreinterestingly, in the proteomic analysis of the rat liver peroxi-some obtained by differential centrifugation and further puri-fied by density gradient and by immunopurification, accordingto the SDS-PAGE band intensity, the amount of the mostabundant matrix protein, catalase, seemed to decrease, whilethe band corresponding to another major matrix protein,uricase, clearly increased in its intensity (37). In addition, in therat liver subcellular fractions obtained with one-step subcel-lular fractionation using a Nycodenz density gradient pre-pared by freezing-thawing, catalase has shown more abun-dance in the mitochondria fraction than in the peroxisomefraction according to Western blotting detection though cat-
alase was used as a peroxisome marker protein (55). In thepresent study, catalase has been quantified according to twounique peptides and has a ratio of PM:CM as 1.41 0.26(Supplemental Fig. 1), which confirm its mitochondrial target-ing and further implicate its abundance may be higher in ratliver mitochondria than in peroxisome (37, 55).
Mutations of mitochondrial DNA (mtDNA) are associatedwith different human diseases, including cancer and aging(11, 12). Reactive oxygen species produced during oxidativephosphorylation are a major source of mtDNA damage. APE/Ref-1 is a nuclear protein possessing both redox activity andDNA repair activity over apurinic/apyrimidinic sites. Immuno-histochemical evidences indicate that in follicular thyroidcells, APE/Ref-1 is located in both nucleus and cytoplasm.Electronmicroscopy immunocytochemistry performed in therat thyroid FRTL-5 cell line indicates that part of the cytoplas-mic APE/Ref-1 is located in mitochondria. The presence ofAPE/Ref-1 inside mitochondria is further demonstrated byWestern blot analysis after cell fractionation (56). In the pres-ent study, the ICAT ratio of PM:CM for AP endonuclease 1 isup to 4.55 (Supplemental Fig. 2), which also indicate its loca-tion in mitochondrial and may further implicate its low abun-dance in mitochondria.
Known Proteins Without Subcellular Location Annotation inthe Swiss-Prot Database—Twelve proteins are known pro-teins without subcellular location annotation in the Swiss-Protdatabase (Table I). Fortunately, many of them have beenreported about their subcellular locations that are consistentwith our ICAT analysis results (57–60). For example, bile acidCoA:amino acid N-acyltransferase (BAT) is responsible for theamidation of bile acids with the amino acids taurine andglycine. Immunoblot analysis of rat tissues detected rat liverBAT (rBAT) only in rat liver cytosol prepared with homogeni-zation and ultracentrifugation. Subcellular localization of rBATdetected activity and immunoreactive protein in both cytosoland isolated peroxisomes (57). Rat bile acid CoA ligase(rBAL), the enzyme responsible for the formation of bile acidCoA esters, was detected only in rat liver microsomes (57). Inthe present study, bile acid CoA ligase and bile acid-CoA:amino acid N-acyltransferase have a ratio of PM:CM as0.66 0.09 and 0.71 0.25, respectively.
Novel Proteins—Thirty-seven novel proteins have beenidentified in the ICAT analysis. SIB BLAST2 Network Service(us.expasy.org/tools/blast/) was used for novel protein blastagainst the UniProt knowledgebase (Swiss-Prot � TrEMBL �
TrEMBL_NEW). Twenty-one novel proteins show high identi-ties (�70%) with known proteins, respectively, most of whichwith subcellular location annotation consistent with ICATanalysis results (Supplemental Table II). For example, novelprotein XP_230637.2, with ratio of PM:CM being 0.25 0.05,shows 83% identities with mouse ribosome-binding protein 1,which is annotated as endoplasmic reticulum membrane pro-tein. Protein XP_224605.1, predicted as mitochondrial proteinby all the five bioinformatics tools, with a ratio of PM:CM
ICAT Analysis of Rat Liver Mitochondria with Different Purity
28 Molecular & Cellular Proteomics 4.1
TAB
LEII
Eva
luat
ion
ofth
eef
ficie
ncy
toas
cert
ain
mito
chon
dria
lpro
tein
sb
yIC
AT
anal
ysis
and
ase
ries
ofb
ioin
form
atic
sto
ols
usin
gth
e12
5p
rote
ins
with
sub
cellu
lar
loca
tion
anno
tatio
nas
ate
std
atas
et
Test
dat
aset
(pro
tein
sw
ithS
wis
s-P
rot
anno
tatio
n)
ICA
Tra
tio(P
M/C
M)
Pro
tein
sp
red
icte
das
mito
chon
dria
lP
ossi
bili
tyto
be
mito
chon
dria
lp
rote
inp
red
icte
db
yM
itoP
rot
IIP
ossi
bili
tyto
be
mito
chon
dria
lp
rote
inp
red
icte
db
yTa
rget
P(m
TP)
�0.
50.
5�1.
01.
0�2.
0�
2.0
�1.
0�
1.0
PS
OR
TTa
rget
PS
ubLo
c�
0.50
�0.
50�
0.70
�0.
85�
0.95
�0.
50�
0.50
�0.
70�
0.85
�0.
95
Pro
tein
sin
test
dat
aset
125
2638
3724
6461
2746
4368
5745
3622
7946
3224
0
Mito
chon
dria
l48
00
2721
048
2435
298
4036
3121
1335
2922
0S
ensi
tivity
a0.
000.
000.
560.
440.
001.
000.
500.
730.
600.
170.
830.
750.
650.
440.
270.
730.
600.
460.
00S
pec
ifici
tyb
0.00
0.00
0.73
0.88
0.00
0.79
0.89
0.76
0.67
0.12
0.70
0.80
0.86
0.95
0.16
0.76
0.91
0.92
0.00
Non
mito
chon
dria
l69
2537
61
627
18
1256
135
30
618
32
0S
ensi
tivity
0.36
0.54
0.09
0.01
0.90
0.10
0.01
0.12
0.17
0.81
0.19
0.07
0.04
0.00
0.88
0.12
0.04
0.03
0.00
Sp
ecifi
city
0.96
0.97
0.16
0.04
0.97
0.11
0.04
0.17
0.28
0.82
0.23
0.11
0.08
0.00
0.77
0.17
0.09
0.08
0.00
Mito
,an
dot
herc
81
14
22
62
32
44
42
15
30
00
Sen
sitiv
ity0.
130.
130.
500.
250.
250.
750.
250.
380.
250.
500.
500.
500.
250.
130.
630.
380.
000.
000.
00S
pec
ifici
ty0.
040.
030.
110.
080.
030.
100.
070.
070.
050.
060.
070.
110.
060.
050.
060.
070.
000.
000.
00
No
anno
tatio
n44
123
1217
1529
78
1030
1411
96
3410
85
0
Rat
io_P
M/C
M�
1.0
900
049
410
9031
4643
3654
4839
2742
4836
260
Rat
io_P
M/C
M�
1.0
7938
410
079
03
810
6217
86
171
84
30
Tota
lpro
tein
s16
938
4149
4179
9034
5453
9871
5645
2811
356
4029
0
TAB
LEII—
cont
inue
d
Test
dat
aset
(pro
tein
sw
ithS
wis
s-P
rot
anno
tatio
n)
Pos
sib
ility
tob
em
itoch
ond
rial
pro
tein
pre
dic
ted
by
Pre
dot
arP
rote
ins
pre
dic
ted
asm
itoch
ond
rialp
rote
ins
by
one
orm
ore
bio
info
rmat
ics
tool
s(B
T)an
dIC
AT
anal
ysis
atth
esa
me
timed
�0.
50�
0.50
�0.
70�
0.85
�0.
95B
T�0
BT�
0/R
�B
T�1
BT�
1/R
�B
T�2
BT�
2/R
�B
T�3
BT�
3/R
�B
T�4
BT�
4/R
�B
T�5
BT�
5/R
�
Pro
tein
sin
test
125
6758
5042
3045
3380
4955
4448
4333
3216
16
Mito
chon
dria
l48
1335
3226
206
042
4239
3938
3828
2816
16S
ensi
tivity
a0.
270.
730.
670.
540.
420.
130.
000.
880.
880.
810.
810.
790.
790.
580.
580.
330.
33S
pec
ifici
tyb
0.19
0.60
0.64
0.62
0.67
0.13
0.00
0.53
0.86
0.71
0.89
0.79
0.88
0.85
0.88
1.00
1.00
Non
mito
chon
dria
l69
4920
1614
835
3334
512
37
32
20
0S
ensi
tivity
0.71
0.23
0.23
0.20
0.12
0.51
0.48
0.49
0.07
0.17
0.04
0.10
0.04
0.03
0.03
0.00
0.00
Sp
ecifi
city
0.73
0.34
0.32
0.33
0.27
0.78
1.00
0.43
0.10
0.31
0.07
0.15
0.07
0.07
0.06
0.00
0.00
Mito
,an
dot
herc
85
32
22
40
42
42
32
32
00
Sen
sitiv
ity0.
630.
380.
250.
250.
250.
500.
000.
500.
250.
500.
250.
380.
250.
380.
250.
000.
00S
pec
ifici
ty0.
070.
050.
040.
050.
070.
090.
000.
050.
040.
070.
050.
060.
050.
090.
060.
000.
00
No
anno
tatio
n44
2915
1210
722
1122
1814
1010
76
52
2
Rat
io_P
M/C
M�
1.0
9039
5143
3627
230
6767
5454
4949
3737
1818
Rat
io_P
M/C
M�
1.0
7957
2219
1610
4444
350
150
90
20
00
Tota
lpro
tein
s16
996
7362
5237
6744
102
6769
5458
4939
3718
18a
Sen
sitiv
ity:
Per
cent
age
ofth
ep
rote
ins
anno
tate
das
mito
chon
dria
l,no
nmito
chon
dria
l,or
mito
chon
dria
land
othe
rlo
catio
np
rote
ins
that
wer
eid
entif
ied
ind
iffer
ent
ICA
Tan
alys
isfr
actio
nsor
pre
dic
ted
asm
itoch
ond
rialp
rote
ins
by
diff
eren
tb
ioin
form
atic
sto
ols,
resp
ectiv
ely.
bS
pec
ifici
ty:
Per
cent
age
ofth
ep
rote
ins
iden
tifie
din
diff
eren
tIC
AT
anal
ysis
frac
tions
orp
red
icte
das
mito
chon
dria
lp
rote
ins
by
diff
eren
tb
ioin
form
atic
sto
ols
that
wer
ean
nota
ted
asm
itoch
ond
rial,
nonm
itoch
ond
rial,
orm
itoch
ond
riala
ndot
her
loca
tion
pro
tein
s,re
spec
tivel
y.c
Pro
tein
slo
cate
din
mito
chon
dria
land
othe
rsu
bce
llula
rlo
catio
nsac
cord
ing
toS
wis
s-P
rot
anno
tatio
n.d
Pro
tein
sp
red
icte
das
mito
chon
dria
lpro
tein
sb
yd
iffer
ent
bio
info
rmat
ics
tool
s(B
T)or
ICA
Tan
alys
isat
the
sam
etim
e.To
pre
dic
ta
mito
chon
dria
lpro
tein
,the
dire
ctp
red
ictio
nre
sults
wer
ese
tas
crite
riafo
rPS
OR
Tan
dS
ubLo
c,an
dp
ossi
bili
tyto
be
am
itoch
ond
rialp
rote
in�
0.50
wer
ese
tas
crite
riafo
rTar
getP
(mTP
),P
red
otar
,and
Mito
Pro
tII.
BT
�0
and
BT
�5
ind
icat
edth
ata
pro
tein
wer
ep
red
icte
das
am
itoch
ond
rialp
rote
inb
yno
neor
allo
fthe
five
bio
info
rmat
ics
tool
s.R
�:R
atio
_PM
/CM
�1.
00,R
�,R
atio
_PM
/CM
�1.
00.B
T�
n(n
�1,
2,3,
4)in
dic
ated
that
ap
rote
inw
ere
pre
dic
ted
asa
mito
chon
dria
lpro
tein
by
atle
ast
nof
the
five
bio
info
rmat
ics
tool
s.B
T�
n/R
�in
dic
ated
that
ap
rote
inw
ithR
atio
_PM
/CM
�1.
00w
ere
pre
dic
ted
asa
mito
chon
dria
lpro
tein
by
atle
ast
nof
the
five
bio
info
rmat
icst
ools
.B
T�
0/R
�in
dic
ated
that
ap
rote
inw
ithR
atio
_PM
/CM
�1.
00w
ere
pre
dic
ted
asa
mito
chon
dria
lpro
tein
by
none
ofth
efiv
eb
ioin
form
atic
sto
ols.
ICAT Analysis of Rat Liver Mitochondria with Different Purity
Molecular & Cellular Proteomics 4.1 29
being 2.37, has been just confirmed as choline dehydrogen-ase and localized in mitochondrial (61). The novel proteinXP_214838.1 predicted as mitochondrial protein by fourbioinformatics tools, with ratio of PM:CM being 1.96, shows88% identities with human HSCO protein, which has just beenrenamed as “ETHE1” and localized in mitochondrial matrix(62).
Thirteen novel proteins have a ratio of PM:CM �1.0, inwhich 10 (76.9% ,10/13) proteins have been predicted asnonmitochondrial by all the five bioinformatics tools (BT � 0)and are strongly implicated as nonmitochondrial proteins (Ta-ble II). For the 24 novel proteins with a ratio of PM:CM �1.0,14 (58.3%) proteins have been predicted as mitochondrial byat least one bioinformatics tools (BT � 1), in which 7 (29.2%)proteins have been predicted as mitochondrial by at leastthree bioinformatics tools.
Functional Classification
The 169 proteins are categorized according to Swiss-Protfunctional annotation (Fig. 4). As we know, many physiologicalactivities such as amino acid metabolism, fatty acid metabo-lism, glycolysis, urea cycle, transcription, and replication arefulfilled in or associated with multi-organelles including mito-chondria. It is not surprising to find proteins involved in thoseactivities distribute in the two groups of proteins with a ratio ofPM:CM �1.0 or �1.0. As expected, proteins involved in theoxidative phosphorylation (such as ATP synthase D chain and� chain, NADH-ubiquinone oxidoreductase 13-kDa-A subunitand 24-kDa subunit, ubiquinol-cytochrome c reductase com-plex 11-kDa protein and core protein 2, electron transferflavoprotein-ubiquinone oxidoreductase, and electron trans-fer flavoprotein �-subunit), the tricarboxylic acid (TCA) cycle(such as succinyl-CoA ligase �-chain and �-chain, isocitratedehydrogenase, and malate dehydrogenase), and ketonebody metabolism (such as HMG-CoA synthase and aceto-acetyl-CoA thiolase), all have a ratio of PM:CM �1.0 (Fig. 4B).On the other hand, proteins that function in interactions be-tween cells and the extracellular matrix (such as �-1 catenin,sulfated glycoprotein 1 precursor (SGP-1), fibronectin, throm-bospondin 2, and basigin), blood coagulation or fibrinolysis(such as plasminogen and prothrombin), bile acid metabolism(such as bile acid CoA ligase and bile acid-CoA:amino acidN-acyltransferase), and ribosomal proteins (such as 60S ribo-somal protein L10a (CSA-19), L30, L12, and 60S acidic ribo-somal protein P1), all have a ratio of PM:CM �1.0 (Fig. 4A).
As we can see, in accordance with multifunction of mito-chondria (7–13), proteins with a ratio of PM:CM �1.0 includemany proteins that function in amino acid metabolism, fattyacid metabolism, glycolysis, the oxidative phosphorylation,the TCA cycle, ketone body metabolism, urea cycle, andtranscription and replication. Moreover, many novel proteinshave been implicated their mitochondrial location.
Evaluation of the Efficiency to Ascertain MitochondrialProteins by ICAT Analysis and a Series of
Bioinformatics Tools
The 125 proteins with subcellular location informationhave been used as a test dataset to evaluate the efficiencyto ascertain mitochondrial proteins by ICAT analysis and thefive bioinformatics tools (Table II). When PSORT II andSubLoc are used in the winner-takes-all mode without set-ting a specificity cut-off for targeting, the sensitivity andspecificity to predict mitochondrial proteins is 0.50 and 0.89for PSORT and 0.60 and 0.67 for SubLoc, respectively.Based on a probability cut-off of �0.50, the sensitivity andspecificity to predict mitochondrial proteins is 0.73 and 0.76for TargetP (mTP), 0.83 and 0.70 for MitoProtII, and 0.73 and0.60 for Predotar, respectively. Moreover, TargetP (mTP) andMitoProtII show increased specificity based on the probabilitycut-off of �0.70 or �0.85, while Predotar shows low speci-ficity even if based on the probability cut-off of �0.85 or�0.95.
For ICAT analysis, according to the ratio of PM:CM �1.0,the sensitivity and specificity to ascertain mitochondrial pro-teins is 1.00 and 0.79, respectively, almost higher than everybioinformatics tools. Moreover, according to the ratio ofPM:CM �1.0, the sensitivity and specificity to ascertain non-mitochondrial proteins is 0.90 and 0.97, respectively, alsohigher than every bioinformatics tools based on a probabilitycut-off of �0.50. So ICAT analysis, as a high-throughputproteomics experimental strategy, has shown great superior-ity in ascertaining mitochondrial proteins than the most widelyused bioinformatics tools such as PSORT, SubLoc, TargetP,MitoProtII, and Predotar.
The different sensitivity and specificity of the bioinformaticstools would favor in combinational usage of those bioinfor-matics tools to predict mitochondrial proteins. In the testdataset, prediction based on at least one bioinformatics tool(BT � 1) shows sensitivity high up to 0.88 with specificity as0.53. At the same time, the more bioinformatics tools usedcombinationally, the higher specificity for the prediction ofmitochondrial proteins. For prediction based on all the fivebioinformatics tools (BT � 5), the specificity is high up to 1.00.Interestingly, when in combination with the ICAT analysis, thespecificity increased from 0.53 to 0.86 for the predictionbased on at least one bioinformatics tool (BT � 1).
DISCUSSION
More recently, the combination of LC, stable ICAT, andMS/MS has emerged as an alternative quantitative proteom-ics technology (47). In ICAT analysis, two pools of proteins,labeled with light and heavy reagent, respectively, are chem-ically identical and therefore serve as a good internal stand foraccurate quantification. The method has been proved com-plementary to traditional 2D-PAGE (63, 64) and widely appliedin comparative proteomics research such as quantification ofmicrosomal proteins in differentiated versus undifferentiated
ICAT Analysis of Rat Liver Mitochondria with Different Purity
30 Molecular & Cellular Proteomics 4.1
HL-60 cells and quantification of protein expression in ratmyc-null cells versus myc-plus cells (48, 65).
In the present study, we apply such a high-throughput
comparative proteomic experimental strategy, the ICAT tech-nique, to analyze rat liver mitochondria fractions with differentdegrees of purity, prepared with traditional centrifugation or
FIG. 4. Functional classification of the identified proteins according to Swiss-Prot annotation. A, proteins with ratios of PM:CM �1.0.B, proteins with ratios of PM:CM �1.0.
ICAT Analysis of Rat Liver Mitochondria with Different Purity
Molecular & Cellular Proteomics 4.1 31
further purified with a Nycodenz gradient, in the aim to ascer-tain mitochondrial proteins and distinguish contaminantproteins.
A total of 169 different proteins were identified and quanti-fied convincingly. Ninety proteins have a ratio of PM:CM�1.0, while 79 proteins have a ratio of PM:CM �1.0. Accord-ing to Swiss-Prot annotation, bioinformatics prediction, andliterature reports, almost all the proteins with a ratio of PM:CM�1.0 are mitochondrial proteins, while proteins annotated asextracellular or secreted, cytoplasmic, ribosome, endoplas-mic reticulum, and lysomal have a ratio of PM:CM �1.0 (Figs.2 and 3; Table I). Thus, such a comparative proteome exper-imental strategy has been proven effective in ascertainingmitochondrial proteins in a high-throughput way. Many novelproteins, known proteins without subcellular location annota-tion and even known proteins that have been annotated asother locations have been strongly indicated for their mito-chondrial location. Especially, protein catalse and AP endo-nuclease 1, which have been known as peroxisomal andnuclear, respectively, have shown a ratio of PM:CM �1.0(1.41 0.26 and 4.55, respectively) (Supplemental Figs. 1 and2), confirming the reports about their mitochondrial location(37, 53–56). Functional study of those proteins will promoteour understanding on mitochondria structure and function.
In all eukaryotic cells, peroxisomes and mitochondria sharea great variety of enzymatic reactions that are catalyzed byisozymes present in both organelles. For some of these en-zymes it is known that they can be cotargeted to differentorganelles, for example, �3,5-�2,4-dienoyl-CoA isomeraseand long-chain acyl-CoA synthetase 2 (LACS 2), which areresponsible for fatty acid �-oxidation, have been annotated asmultilocation in both mitochondria and peroxisome. A mostrecent example for such a cotargeting has been given for theyeast peroxisomal citrate synthase Cit2p, an enzyme of theTCA cycle that contains a cryptic amino-terminal signal se-quence that functions in both peroxisomal and mitochondrialtargeting (66). Besides enzymes that catalyze related reac-tions within the fatty acid �-oxidation, TCA, and the glyoxylatecycle, enzymes involved in the detoxification of oxygen radi-cals are also present in both peroxisome and mitochondria.Peroxiredoxins (Prxs) form a recently discovered large familyof antioxidant enzymes that act as peroxidases reducing hy-drogen peroxide and alkyl hydroperoxides to water or thecorresponding alcohol, respectively (67). Peroxiredoxin 5 hasbeen annotated as mitochondrial, peroxisomal, and cytoplas-mic. In the present study, in addition to catalase, ATP-bindingcassette subfamily D member 3 (1.75), peroxisomal multifunc-tional enzyme type 2 (MFE-2) (1.46 0.37), NADP-retinoldehydrogenase (1.38 0.03), and 2-hydroxyphytanoyl-CoAlyase (2.72), which were annotated as peroxisomal, all have aratio of PM:CM �1.0 and have been implicated their locationin mitochondria as multilocation proteins.
Comparison of the results from the five bioinformatics toolsand Swiss-Prot annotation and ICAT analysis have shown the
limitations of the bioinformatics tools (45) and even the faultynature of Swiss-Prot annotation (Fig. 2, Table II). The ICATanalysis coupled with combinational usage of different bioin-formatics tools can effectively ascertain mitochondrial pro-teins with high sensitivity and specificity (Table II). Moreover,the inconsistence between ICAT analysis and bioinformaticsprediction could implicate mitochondria-associated multilo-cation. For example, in the present study, �3,5-�2,4-dienoyl-CoA isomerase and 14.5-kDa translational inhibitor protein,with the ratio of PM:CM �1.0 (0.22 and 0.69, respectively),have been predicted as mitochondrial proteins by two andfour bioinformatics tools, respectively. AP endonuclease 1and catalase, which have been predicted as nonmitochondrialproteins by all five bioinformatics tools, have a ratio of PM:CMas 4.55 and 1.41 0.26, respectively. All four proteins havebeen annotated as mitochondria-associated multilocationproteins according to Swiss-Prot database or literature reports(37, 53–56).
In summary, we have applied a high-throughput compara-tive proteome experimental strategy, the ICAT approach per-formed with 2D-LC-MS/MS, coupled with combinational us-age of different bioinformatics tools, to study the proteome ofrat liver mitochondria, with the major problem of contamina-tion in subcellular proteomics research effectively circum-vented. Concerning the limitation of the ICAT approach foranalyzing proteins lacking cysteine residues, acidic proteins,or proteins with low molecular mass (63, 64), other compar-ative proteomics approaches, such as traditional 2D-PAGE,DIGE (68, 69), and stable isotope labeling with amino acids incell culture (SILAC) (70, 71), should be used as complemen-tary methods. Such a comparative proteomics strategyshould be widely used in subcellular proteomics research toprovide more subcellular proteome data with high quality.
* This work was supported by National High-Technology Project(2002BA711A11) and Basic Research Foundation (2001CB210501,2002CB713807). The costs of publication of this article were defrayedin part by the payment of page charges. This article must therefore behereby marked “advertisement” in accordance with 18 U.S.C. Section1734 solely to indicate this fact.
□S The on-line version of this manuscript (available at http://www.mcponline.org) contains supplemental material.
‡ To whom correspondence should be addressed: Research Cen-tre for Proteome Analysis, Institute of Biochemistry and Cell Biology,Shanghai Institutes for Biological Sciences, Chinese Academy ofSciences, 320 YueYang Road, Shanghai 200031, China. Tel.: 86-21-54920170; Fax: 86-21-54920171; E-mail: zr@sibs.ac.cn.
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