Proteome Mapping of Human Skim Milk Proteins in …...Proteome Mapping of Human Skim Milk Proteins in Term and Preterm Milk Claire E. Molinari,*,† Ylenia S. Casadio,† Ben T. Hartmann,‡
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Proteome Mapping of Human Skim Milk Proteins in Term andPreterm MilkClaire E. Molinari,*,† Ylenia S. Casadio,† Ben T. Hartmann,‡ Andreja Livk,§ Scott Bringans,§
Peter G. Arthur,† and Peter E. Hartmann†
†School of Chemistry and Biochemistry, The University of Western Australia, Crawley, 6009, Australia‡Perron Rotary Express Milk Bank (PREM Bank) Neonatal Paediatrics, King Edward Memorial Hospital, Subiaco, 6008, Australia§Proteomics International, Perth, Western Australia, Australia
*S Supporting Information
ABSTRACT: The abundant proteins in human milk havebeen well characterized and are known to provide nutritional,protective, and developmental advantages to both term andpreterm infants. However, relatively little is known about theexpression of the low abundance proteins that are present inhuman milk because of the technical difficulties associated withtheir detection. We used a combination of electrophoretictechniques, ProteoMiner treatment, and two-dimensional liquidchromatography to examine the proteome of human skim milkexpressed between 7 and 28 days postpartum by healthy termmothers and identified 415 in a pooled milk sample. Of these,261 were found in human skim milk for the first time, greatlyexpanding our understanding of the human skim milk pro-teome. The majority of the proteins identified were involved in either the immune response (24%) or in cellular (28%) or protein(16%) metabolism. We also used iTRAQ analysis to examine the effects of premature delivery on milk protein composition.Differences in protein expression between pooled milk from mothers delivering at term (38−41 weeks gestation) and preterm(28−32 weeks gestation) were investigated, with 55 proteins found to be differentially expressed with at least 90% confidence.Twenty-eight proteins were present at higher levels in preterm milk, and 27 were present at higher levels in term milk.
KEYWORDS: human milk, protein, proteomics, ProteoMiner, iTRAQ, 2D LC−MS
■ INTRODUCTIONThe importance of human milk proteins to the growth anddevelopment of breastfed infants is well established. They notonly provide a digestible source of amino acids to infants, butalso confer immunological protection and perform developmen-tal and regulatory functions, exerting both long and short-termbenefits compared to formula feeding.1,2
Human milk proteins are particularly important for infantswho are born prematurely. Recent studies stress the importanceof both the total amount of protein and the ratio of protein/energy that preterm infants receive for their growth and devel-opment.3 Significantly, the protein composition of milk frompreterm mothers is known to differ from that of term mothers.The concentration of total protein is typically higher in pretermmilk;4 however, while some individual proteins are expressed athigher levels in preterm milk, others are present at lower con-centrations.5−7
Hitherto, most studies investigating milk protein composi-tion have focused upon the most abundant proteins present,resulting in their relative concentrations in term and pretermmilk being well-defined.8−10 However, it is also important thatthe identity and behavior of the lower abundance proteins in
human milk be characterized. There are two main reasons forthis. First, it is possible that these proteins play significant rolesin infant growth and development. Second, knowledge of howthe expression of low abundance proteins differs between termand preterm milk may be useful diagnostically, as a reflection ofthe developmental changes occurring in the mammary glandduring pregnancy and lactation.Historically, there have been a number of technical
challenges associated with characterizing the low abundanceproteins in human milk. Initial studies using gel electrophoreticmethods coupled with mass spectrometry were unable to detectmore than 10 different gene products in either human orbovine milk, despite observing hundreds of distinct proteinspots.11−13 This difficulty results from the fact that six proteins,α-lactalbumin, β-casein, secretory immunoglobulin A, lysozyme,lactoferrin, and secretory component, constitute over 90% ofthe total protein content in mature human milk,14 obscuringthe detection of less abundant proteins of potential biologicalinterest.
Received: September 2, 2011Published: February 7, 2012
More recently, proteomic studies employing strategies todeplete the high abundance proteins or to extensively frac-tionate the sample prior to analysis have been more successfulat identifying low abundance proteins than the earlier gel-basedmethods.14−17 Two studies in particular have identified a largenumber of low abundance human milk proteins. Palmer et al.18
used immunodepletion columns to deplete the five mostabundant proteins in colostrum prior to 2D LC−MS/MS an-alysis and were able to identify 151 proteins. More recently,Liao et al.19 employed combinatorial hexapeptide ligandlibraries (ProteoMiner) to enrich the low abundance milkproteins before analysis by LC−MS/MS and identified 115proteins. Liao et al.19 also showed that many of these proteinschange in expression over the course of 12 months of lactation,highlighting the dynamic nature of milk composition. One ofthe advantages of using a ProteoMiner bead approach is that itdoes not require tailored antibodies or optimization. When asample is applied to the ligand library, the high abundance pro-teins saturate their ligands and the excess remains unbound,whereas the lower abundance proteins bind completely, result-ing in an overall compression of the dynamic range. Recentstudies have also shown the ProteoMiner treatment to be com-patible with downstream quantitative analyses of low abundanceproteins.20,21
The aim of the present study was two-fold. First, we aimed tofurther characterize the proteome of mature human skim milkfrom established lactation (7−28 days postpartum), using acombination of ultracentrifugation and ProteoMiner enrich-ment to compress the dynamic range of the proteome prior toanalysis by 2D LC−MS/MS. Second, we sought to quanti-tatively examine whether there are differences in proteinexpression between term and preterm milk that reflect thephysiological and metabolic effects of preterm delivery uponthe mammary gland.
■ EXPERIMENTAL PROCEDURES
Materials
Unless otherwise stated, all chemicals and reagents were ob-tained from Sigma-Aldrich (NSW, Australia).
Sample Collection
Term and preterm milk samples were obtained from healthylactating mothers at King Edward Memorial Hospital, Subiaco,Western Australia. Participating term mothers had deliveredbetween 38 and 41 weeks of gestation, and their infants had achronological age of between 7 and 28 days at the time ofsample collection. Participating preterm mothers had deliveredbetween 28 and 32 weeks of gestation, and their infants had achronological age of between 7 and 14 days at the time ofsample collection. All donors gave written informed consent fortheir donations to be used in this research, and this study wasapproved by the University of Western Australia, HumanResearch Ethics Committee and King Edward Memorial Hospital,Human Ethics Research Committee. All samples were frozen at−20 °C within an hour of expression and transferred to −80 °Cstorage within 3 days.
Sample Treatment
The sample analysis workflow is described in Figure 1. Forthe purposes of protein identification in mature term milk,milk samples collected from 8 mothers (15−28 days lactation)were pooled. For the quantitative comparison betweenterm and preterm milk, milk samples from 16 preterm mothers
(7−14 days lactation) and 16 term mothers (7−14 days lactation)were used. All milk samples were thawed, pooled, and centri-fuged at 10000g for 10 min to remove the cream layer. Amammalian protease inhibitor cocktail containing 4-(2-aminoethyl)benzenesulfonyl fluoride, E-64, bestatin, leupeptin,aprotinin, and sodium EDTA was added to each pooled sample,which was then depleted of casein using a previously describedmethod.22 Briefly, to deplete the samples of casein, CaCl2 wasadded to a concentration of 60 mM, and the pH was adjustedto pH 4.3. Samples were then centrifuged at 189000g at 4 °Cfor 60 min, and the supernatant was collected.For the ProteoMiner-treated samples (Figure 1), casein-
depleted skim milk was dialyzed against 10 volumes of 10 mMTris, pH 7 at 4 °C, with three buffer changes at two-hour inter-vals using dialysis tubing with a MW cutoff of 3500 Da(Spectrapor Membrane Tubing, Spectrum Medical Industries,Rancho Domingues, CA). The samples were then lyophilizedand reconstituted in water. The samples were analyzed for theirprotein content and diluted such that 1 mL of 50 g/L proteinsolution was loaded onto the hexaligand library beads(ProteoMiner Large Capacity Protein Enrichment Kit, BioRad,Gladesville, NSW, Australia), according to the manufacturer’sinstructions. Briefly, after swelling the beads using the bufferprovided, the samples were loaded onto individual ProteoMinercolumns and rocked for 6 h at room temperature. For thepooled term milk samples (collected 15−28 days postpartum),the unbound proteins were then washed through the column,and the bound proteins were eluted using the acidic elutionbuffer provided in the kit. For the pooled term and pretermmilk samples to be subsequently labeled with iTRAQ reagents(collected 7−14 days postpartum), the bound proteins wereeluted sequentially using four different buffers: 1 M sodiumchloride in 20 mM HEPES (pH 7.0), 0.2 M glycine (pH 2.4),60% (w/v) ethylene glycol in water, and 33.3% (v/v) 2-propanol,16.7% (v/v) acetonitrile, 0.1% (v/v) trifluoroacetic acid.
Protein Concentration Determination
Protein concentrations of human milk samples were deter-mined using a Bicinchoninic acid kit (Sigma-Aldrich, NSW,Australia), as described in a previous study.23
SDS-PAGE analysis was conducted using the HOEFER gelapparatus (HOEFER Scientific Instruments, San Francisco,CA) and the Laemmli gel system using 12.5% polyacrylamidegels.24 Gels were run using a constant current of 15 mA for16 h at 4 °C, fixed for 2 h in 50% methanol/10% trichloroaceticacid, destained using double deionized water, stained usingCoomassie Brilliant Blue R-250 overnight, and scanned usingan Epson Perfection V700 photographic flatbed color imagescanner (Epson, Nagano, Japan). The intensity of proteinbands were measured using the open access software packageImage J 1.410.25
Differential in-Gel Electrophoresis (DIGE)
Cy5 and Cy3 activated ester dyes were purchased fromLumiprobe (Lumiprobe Corp, FL). Skim milk samples beforeand after casein depletion and ProteoMiner treatment wereeach labeled with one of the dyes. The DIGE experiment wasconducted in duplicate, and the order of the dyes were swappedfor the duplicate experiment. Fifty micrograms of protein samplewas labeled according to the CyDye DIGE Flours (minimal dyes)
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for Ettan DIGE system protocol (GE Healthcare, Pittsburgh, PA),and the samples were mixed together.Isoelectric focusing (IEF) and strip equilibration was performed
according to the Ettan DIGE system protocol (GE Healthcare),using ready-to-use Immobiline DryStrip gel strips, linear pHgradient 3−10, length 18 cm (GE Health Care) and anIPGphor isoelectric focusing unit (IPGPhor, GE Health Care).The strips were actively rehydrated for 10 h at a constant volt-age of 200 V and a constant temperature of 20 °C. One hundredmicrograms of protein was loaded. Following rehydration, thestrips were exposed to a linear increase to 1000 V over 4 hfollowed by 8000 V until a total of 45000 V hr was reached.The second dimension separation was carried out in the darkaccording to the method of Lui, Lipscombe, and Arthur.26 Gelswere imaged using a Typhoon Trio scanner (GE Health Care),with the Cy5 and Cy3 labeled samples visible using 633/670 nmand 532/580 nm excitation/emission filters, respectively. Gelswere post stained for total protein content using CoomassieBrilliant Blue. DIGE gels were analyzed using the ProgenesisSameSpots software package (Nonlinear Dynamics Ltd., New-castle upon Tyne, U. K.). Spots with a normalized spot volumeof less than 500 were excluded from the analysis. All data ispresented as mean ± SEM.For the purposes of downstream mass spectrometry analysis,
a preparative 2D gel analysis was also conducted. Five hundredmicrograms of the ProteoMiner-treated skim milk sample wasloaded, and the first and second dimensions were carried out asabove. Gels were fixed and stained as described above. Co-omassie stained bands and spots of interest were cut from thegel, destained, and digested as described by Shevchenko et al.27
Mass spectrometry was conducted as described in a pre-vious study using an UltraFlex MALDI-TOF/TOF instrument(Bruker Daltonics, Bremen, Germany).23 MS/MS data was im-ported into the database search engine Mascot (Version 2.3.01,www.matrixscience.com) and searched against the Swiss-ProtMammalia database (49 887 sequences).
LC−MS/MS
Sample Preparation. Protein samples were precipitated byadding five volumes of cold acetone to the treated samples(Figure 1), incubating for 1 h at −20 °C, and pulse centrifugingfor 5−10 s. The protein pellets were resuspended in 0.5 Mtriethylammonium bicarbonate (TEAB) (pH 8.5) by shakingbefore reduction and alkylation according to the iTRAQprotocol (Applied Biosystems, Foster City, CA). A total of55 μg of each sample was digested overnight with 5.5 μg trypsinat 37 °C in 0.5 M TEAB.
1D-LC. Peptides were separated on a C18 PepMap100,3 μm column (LC Packings, Sunnyvale, CA) with a gradient of10−45% acetonitrile, 0.1% trifluoroacetic acid over 165 min,using the Ultimate 3000 nano HPLC system (LC Packings-Dionex). Every 30 s, the eluent was mixed with matrix solution(5 mg/mL CHCA) and spotted onto a 384 well Opti-TOFplate (Applied Biosystems) using a Probot Micro FractionCollector (LC Packings-Dionex).
2D-LC. Peptides were desalted on a Strata-X 33 μm poly-meric reversed phase column (Phenomenex) and dissolved in abuffer containing 10 mM potassium hydrogen phosphate, pH 3in 10% acetonitrile, before separation by strong cation exchangechromatography on an Agilent 1100 HPLC system (AgilentTechnologies, Palo Alto, CA) using a PolySulfethyl column(4.6 × 100 mm, 5 μm, 300 Å, Nest Group, Southborough,MA). Peptides were eluted with a linear gradient of 0−400 mMKCl. Eight fractions containing the peptides were collected anddesalted on Strata-X columns. Each peptide fraction was thenseparated and spotted onto a 384-well Opti-TOF plateaccording to the 1D-LC protocol described above, exceptingthat a 10−40% acetonitrile (0.1% trifluoracetic acid) gradientwas used.
iTRAQ. The tryptic digests were dried in a SpeedVac, re-suspended in 30 μL of 0.5 M TEAB, and labeled by addingiTRAQ reagents to preterm and term milk samples, respectively,according to the iTRAQ protocol (Applied Biosystems). Forthe iTRAQ experiment comparing term and preterm milksamples without ProteoMiner treatment (Figure 1), duplicatepooled preterm milk samples were labeled with iTRAQ reagents
Figure 1. Experimental workflow.
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114 and 116. Duplicate pooled term milk samples were labeledwith iTRAQ reagents 115 and 117. For the iTRAQ experimentcomparing term and preterm milk samples after ProteoMinertreatment (Figure 1), duplicate pooled preterm milk sampleswere labeled with iTRAQ reagents 116 and 117. Duplicatepooled term milk samples were labeled with iTRAQ reagents114 and 115. Excess iTRAQ reagent was quenched by adding1 mL of water; the samples were then combined, desalted on aStrata-X 33 μm polymeric reverse phase column (Phenomenex,Torrance, CA), and analyzed using the 2D-LC protocol de-scribed above.MALDI-MS/MS. Peptides were analyzed on a 5800 MALDI-
TOF/TOF mass spectrometer (Applied Biosystems) operatedin reflector positive mode. MS data were acquired over a massrange of 800−4000 m/z, and for each spectrum, a total of 400shots were accumulated. A job-wide interpretation methodselected the 20 most intense precursor ions above a signal/noise ratio of 20 from each spectrum for MS/MS acquisitionbut only in the spot where their intensity was at its peak. MS/MS spectra were acquired with 4000 laser shots per selected ionwith a mass range of 60 to the precursor ion −20.Data Analysis. Protein identification was performed using
ProteinPilot 4.0.8085 Software (Applied Biosystems). MS/MSspectra were searched against the Swiss-Prot human genomicdatabase (2011_3 for the 2D-LC analysis, 2011_5 for the 1D-LC analysis). Search parameters were as follows: Cys alkylation,MMTS; Digestion, trypsin; Instrument, 5800; Special factors,none; Species, none; Quantitate tab, unchecked; Detectedprotein threshold (unused ProtScore), 1.3, which correspondsto proteins identified with <95% confidence.For the iTRAQ experiment, MS/MS spectra were analyzed
as above with ProteinPilot 4.0.8085 software, with the addition
of the parameter, iTRAQ 4plex (peptide labeled) modification,and the Quantitate tab checked. MS/MS spectra were searchedagainst the Swiss-Prot human genomic database (2011_5). Forquantitation analysis, the duplicates were analyzed separately.Average protein ratios and p-values to indicate significant differ-ential expression were calculated by the software. To be con-sidered as being differentially expressed, proteins were requiredto have an unused protein score greater than 1.3, correspondingto a confidence interval of 95%, and have significantly differentprotein ratios in both replicates, also at a confidence level of95% (p < 0.05). Identified proteins for which a difference wasfound at a confidence level of 90% (p < 0.1) in both replicateswere also reported. The p values represent the variation in thereported iTRAQ ratios for all the peptides of the associatedprotein and do not relate to either biological variation ortechnical reproducibility.The false discovery rate was less than 1%, calculated using a
database containing reversed sequences. In order to categorizethe identified proteins, the results were analyzed using thesoftware program IPA (Ingenuity Databases) and the UniProtDatabase release 2011_6 (http://www.uniprot.org/). Resultswere compared to a recent comprehensive review publication28
and a subsequent research paper19 in order to determine whichproteins had not been previously identified.
■ RESULTSCasein Depletion
The SDS-PAGE gel analysis showed that casein depletion re-sulted in the removal of 67 ± 3% (n = 5) of the 30 kDa β-caseinband present in the pooled skim milk sample (Figure 2). The κ-casein protein band at 38 kDa and a number of other β-caseinbands in the 20−30 kDa region present in the skim milk sample
Figure 2. SDS-PAGE electrophoretograms and mass spectrometry identifications of milk protein fractions. Proteins (15 μg) from (A) skim milk, (B)skim milk after ProteoMiner treatment, (C) skim milk after casein depletion, and (D) skim milk after casein depletion and ProteoMiner treatmentwere analyzed (n = 4, 2 depicted). Significant protein identifications obtained using MALDI MS/MS are displayed adjacent to the correspondingband of the casein-depleted ProteoMiner-treated skim milk.
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also appear to be present at considerably lower levels in thecasein-depleted sample (Figure 2).
ProteoMiner Treatment: SDS-PAGE
The ProteoMiner treatment compressed the dynamic range ofthe proteins present in human milk. However, ProteoMinertreatment resulted in a far greater enrichment of lower abun-dance proteins when used after casein depletion, compared towhen it was performed on the delipidated skim milk alone(Figure 2). As a result, all samples were depleted of casein priorto further treatment and analysis (Figure 1). In the SDS-PAGEanalysis of the casein-depleted protein sample, the five mostintense protein bands constituted 52% before ProteoMinertreatment and 24% after treatment (p < 0.001) (Figure 2). Themajor protein bands of β-casein (30 kDa), α-lactalbumin(14 kDa), serum albumin (65 kDa), and sIgA α-chain C region(60 kDa) were all depleted after the combinatorial ligandlibrary treatment (p < 0.002) (Figure 2). It is also possible tosee the resulting enrichment of lower abundance proteins. Thexanthine dehydrogenase band at ∼170 kDa was enriched by 5.4fold (p < 0.001), and there were a number of additional bandsseen in the 30−50 kDa range and between 20 and 25 kDa(Figure 2).
ProteoMiner Treatment: 2D-DIGE
The compression of the protein dynamic range caused by thecasein depletion and ProteoMiner treatment was visible to agreater extent in the 2D-DIGE analysis. There were 308 and320 spots present on the duplicate skim milk gels, compared to359 and 364 spots on the duplicate gels of the casein-depleted,ProteoMiner-treated samples (Figure 3). Over two-thirds(68 ± 5%) of the spots were present at a relatively higher in-tensity after casein depletion and ProteoMiner treatment com-pared to in the skim milk. Similarly, 28 ± 3% of the spots in thetreated sample occupied a 2-fold greater percentage intensity,and 20 ± 0.5% of spots were present at a 3-fold higher per-centage intensity relative to the skim milk.In the skim milk gels, 60 ± 4% of the total gel intensity was
occupied by the β-casein and α-lactalbumin spot clusters at 25−30 kDa and 14.4 kDa, respectively. Casein depletion andProteoMiner treatment reduced the dominance of the abun-dant proteins, with only 40 ± 3% of the total gel intensity beingoccupied by the same β-casein and α-lactalbumin spots aftertreatment (Figure 3). In the skim milk gels, 54 ± 0.1% of spotswere present at very low levels, each occupying less than 0.04%of the total gel intensity. In the treated sample, however, only29 ± 0.5% of the spots on the gel were present at an intensityless than this 0.04% threshold.For the preparative 2DE analysis, 110 spots were processed
for MALDI-MS/MS analysis, and 61 of these spots werepositively identified. Many of the spots that were not identifiedwere of extremely low abundance and were only faintly visibleusing Coomassie Brilliant Blue staining. There was a great dealof redundancy, with the 61 spots corresponding to only21 gene products (Supporting Information Data Files 2 and 3).
Protein Identifications
A total of 415 proteins were identified at a confidence level of95% in human milk collected between 7 and 28 days post-partum from term mothers, 261 of which had not previouslybeen identified in human skim milk (Table 1). With regard tomethodology, the majority of these proteins were identified inthe 2D LC−MS/MS analyses after ProteoMiner treatment,with 15 proteins being identified in only the 1D LC−MS/MS
analysis, and 29 proteins being identified in the iTRAQ experi-ment without ProteoMiner treatment (Figure 4A,B). Withregard to the stage of lactation, 174 proteins were identified inboth the pooled term milk collected 7−14 days postpartum andin the pooled term milk collected 15−28 days postpartum. Therewere 141 proteins unique to the pool collected earlier in lactation,and 100 proteins were identified only in the pooled term milkcollected 15−28 days postpartum (Figure 4C). The 415 proteinswere categorized by both their subcellular location and theirfunctions, according to their annotations in the UniProt Databaserelease 2011_6 (http://www.uniprot.org/) (Figure 5). Themajority of the proteins found in the present study were cyto-plasmic (46%) or extracellular space proteins (38%). Functionally,the majority of the proteins identified were involved in either inthe immune response (24%) or in cellular metabolism andcellular growth (28%). See Supporting Information Data File 4for a description of how each protein was categorized.
Figure 3. Two-dimensional fluorescent differential in-gel expression(DIGE) experiment. (A) Skim milk protein fraction, (B) skim milkprotein fraction after casein depletion and ProteoMiner treatment.The gels depicted are one pair out of a set of duplicate experiments.
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Compatibility of ProteoMiner Treatment with DownstreamiTRAQ Quantitation
Low abundance proteins retain their relative abundance afterProteoMiner treatment, whereas high abundance proteins donot.20,21,29 As described in previous studies,20,30 we conductedtwo parallel iTRAQ experiments in order to distinguish
between proteins of high and low abundance: one in whichcasein-depleted skim milk samples were subjected to Proteo-Miner treatment prior to iTRAQ analysis and one in whichcasein-depleted skim milk samples were left untreated (Figure 1).The 80 proteins identified in the untreated milk samples wereclassified as proteins of high-abundance. The iTRAQ analysis of
Table 1. continued
protein name accession no. unuseda % covb peptides methodc
aUnused ProtScore is a measure of the protein confidence for a detected protein. An Unused ProtScore of 1.3 corresponds to 95% confidence, witha higher score representing a higher level of confidence. bThe percentage of the total protein sequence covered by the identified peptides. cTheexperiment in which the protein was identified. (1) SDS-PAGE, (2) 2D DIGE, (3) 1D LC−MALDI, (4) 2D LC−MALDI, (5) iTRAQ withoutProteoMiner treatment, (6) iTRAQ after ProteoMiner treatment. When the protein was identified using more than one experiment, the reportedresults are from the experiment that gave the highest Unused ProtScore. dProteins that have not previously been identified in human skim milk.
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the untreated samples enabled accurate quantitation of thesehigh abundance proteins, whereas the iTRAQ analysis of theProteoMiner-treated samples enabled quantitation of the lowabundance proteins.To assess whether ProteoMiner treatment does in fact affect
the relative abundance ratios of the high abundance proteins,
the quantitative information from the 51 proteins identified inboth iTRAQ experiments (Figure 4) was compared. Of the 11proteins found to be differentially expressed in the iTRAQexperiment without ProteoMiner treatment, only four were alsodifferentially expressed after ProteoMiner treatment. Of the 40proteins found not to be differentially expressed in the iTRAQexperiment without ProteoMiner treatment, 14 were found tobe differentially expressed after ProteoMiner treatment. Of thetotal 51 proteins, only 28 displayed homodirectional changes inthe two iTRAQ experiments. These results indicate that theProteoMiner treatment does introduce significant error into therelative abundance ratios of these higher abundance proteins.Therefore, in accordance with previous studies,20 only therelative abundance ratios of the low abundance proteins (thosenot also identified in the iTRAQ analysis of untreated samples)were considered to be accurate in the iTRAQ analysis ofProteoMiner-treated samples.
Quantitative Comparison of Term and Preterm Milk
The protein concentration of the pooled term and preterm milksamples were similar both before casein depletion (15.9 mg/mLand 16.0 mg/mL, respectively) and afterward (7.1 mg/mL and7.0 mg/mL, respectively). There were 80 abundant proteinsidentified in the iTRAQ experiment of the non-ProteoMiner-treated samples (Table 1). All of the 80 proteins were found inboth the term and preterm milk samples and in each duplicate.Five proteins constituted a significantly greater proportion of theprotein content in the pooled preterm milk, and 10 proteins
Figure 4. Protein identifications in human term milk using differentanalytical techniques. (A) Human term milk (38−41 weeks gestation)was collected from 8 mothers between 15 and 28 days postpartum,pooled together, treated with ProteoMiner beads to deplete the mostabundant proteins, and then analyzed using different techniques. 274proteins were identified in total. (B) Sixteen term (38−41 weeksgestation) and 16 preterm (28−32 weeks gestation) mothers donatedmilk samples between 7 and 14 days postpartum. Samples in each groupwere pooled. Two iTRAQ experiments were conducted: one comparingthe protein expression in term and preterm milk without ProteoMinertreatment and one comparing the protein expression after ProteoMinertreatment. 315 proteins were identified in total in the iTRAQ experi-ments. (C) Combining the results from the experiments described in (A)and (B), 415 proteins were identified in total from human term milk(38−41 weeks gestation), expressed between 7 and 28 days postpartum.
Figure 5. Protein classifications. (A) Subcellular location of all 415proteins identified in the 1D LC−MALDI and 2D LC−MALDIanalyses. (B) Functional categorization of 415 proteins identified inthe 1D LC−MALDI and 2D LC−MALDI analyses. A number ofproteins are included in multiple categories. The number of proteins ineach category is indicated in parentheses.
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were present at a significantly higher level in the pooled termmilk (Table 2). The remaining 65 proteins did not differ inabundance between the two samples.In the iTRAQ analysis of the ProteoMiner-treated pooled
term and preterm milk samples, 286 proteins were identified.Fifty-one of these proteins were also identified in the iTRAQexperiment without ProteoMiner treatment and were thusclassed as high abundance proteins. Of the 235 low abundanceproteins identified, 40 differed in abundance between the pooledterm and preterm milk samples (Table 2). Twenty-three of theselow abundance proteins were present at higher levels in pretermmilk, and 17 were present at higher levels in term milk. The re-maining 195 low abundance proteins were present at similarlevels in both term and preterm milk.SDS-PAGE analysis of the pooled preterm and term samples
was conducted to confirm the iTRAQ results of the highlyabundant proteins (Figure 6). The identity of protein bandswas confirmed using MALDI-MS/MS in a previous study.23
Bile salt-stimulated lipase, lactoferrin, and serum albumin werepresent at significantly higher levels in preterm milk (p < 0.05).Levels of β-casein and α-lactalbumin were similar in the termand preterm milk.
■ DISCUSSIONIn the present study, 415 proteins were identified using anumber of separation and identification techniques, 261 ofwhich had not been previously found in human skim milk. Themajority of the identified proteins (371 of 415) were foundusing a combination of casein depletion, ProteoMiner treat-ment, and a 2D LC separation (Figure 4). The efficacy of theProteoMiner treatment was highlighted by the iTRAQ experi-ment, in that when using a 2D LC separation alone withoutprior ProteoMiner treatment, only 80 proteins were identifiedin human skim milk, much fewer than the 286 proteins identi-fied in the corresponding analysis after ProteoMiner treatment.Similarly, the 2D LC separation provided a far greater level ofproteome coverage compared to a 1D LC separation or gel-based approach (Figure 4A). Indeed, we identified over threetimes as many proteins as a recent study that coupled ProteoMinertreatment to a 1D LC separation.19
ProteoMiner treatment was found to be reproducible, with ahigh degree of consistency observed in both the SDS-PAGEand 2D-DIGE analysis of the samples treated in duplicate(Figures 2, 3). However, it was apparent in the SDS-PAGEanalysis that not all proteins of equivalent initial concentrationwere depleted or enriched to the same extent. For example,α-lactalbumin was nearly completely removed, whereas lacto-ferrin remained at a relatively high concentration afterProteoMiner treatment, despite both being present at similarlevels in milk samples (Figure 2). Furthermore, 29 of the 80proteins that were identified in the casein-depleted skim milkby 2D LC−MS/MS in the iTRAQ experiment were not foundin the corresponding ProteoMiner-treated sample (Figure 4C).This indicates that some proteins of medium abundance mayhave a very low binding affinity for the hexapeptide ligandlibrary and are not retained on the ProteoMiner beads. Indeed,the different binding affinities of proteins for the ProteoMinerpeptide library have been described as one of the major limita-tions of the technique, with an estimated 5−15% of the proteinsin any given mixture not binding at all.31 Therefore, while our re-sults represent a considerable expansion of the known proteomeof human milk, it is likely that many other milk proteins remainto be identified, with some proteins escaping capture by the
ProteoMiner beads, and others present at levels too low to bedetected.The protein identification study yielded no direct informa-
tion about the relative concentration of the proteins in humanmilk. However, comparing the results to those of previousstudies in which fewer proteins were identified suggests that thecytoplasmic proteins are among those of least abundance inhuman milk. Liao et al.19 found that 23.5% of the 115 proteinsthey identified were cytoplasmic. Similarly, of the 80 proteinsidentified in the iTRAQ experiment without ProteoMinertreatment in the present study, only 15% were cytoplasmic. Bycontrast, nearly half (46%) of the total 415 proteins we identi-fied were of cytoplasmic origin. As these additional cytoplasmicproteins were only identified after an extensive enrichment andseparation process, it is likely that they represent the proteins ofleast abundance in milk. This is consistent with the notion thatsome cytoplasmic proteins are present in human milk as anincidental consequence of the secretory process rather thanbeing under regulatory control and are thus found in onlytrace amounts. Indeed, Patton and Huston32 reported thepresence of cytoplasmic crescents within milk fat globules,having being entrained within the fat globule membraneduring the secretory process. Alternatively, the cytoplasmicproteins found in human milk may be derived from thebreakdown of its cellular content. Histological studies havefound significant levels of cellular debris in human milk,mostly derived from secretory epithelial cells.33 It is likely thatcytoplasmic proteins enter human milk through both pro-cesses, and thus it may be possible to view them as a reflectionof the protein content of the cytosol of mammary secretoryepithelial cells.One of the challenges associated with proteomic mapping
experiments is processing and applying the large amounts ofinformation generated within a particular biological context.One way in which the expanded proteome of human milkmay be useful is if the proteins identified reveal any infor-mation about either the metabolism or function of the mam-mary gland. Selected metabolites in human milk are currentlyused in this manner as markers of mammary gland develop-ment and health. For example, levels of milk citrate, sodium,and lactose are used to indicate successful secretory differentia-tion and activation of the mammary gland.34 Similarly, milklactose and glucose can be used as markers of mastitis35 andmetabolites in the lactose synthesis pathway used to identifydiabetic mothers.36 In the present study, 140 of the proteinsidentified (28% of total) are constitutively involved in cellularmetabolism and normal cellular function. This includes 44proteins of the glycolysis, pentose phosphate, citrate, and carbo-hydrate metabolism pathways, many of which such as pyruvatekinase (PKM2), transketolase (TKT), malate dehydrogenase(MDH1), and fructose-1,6-bisphosphatase (FBP) were identi-fied for the first time in human milk. While further researchis required to investigate the expression of these proteinsthroughout lactation, it is possible that they may prove usefulas markers of events that involve alterations to the meta-bolic activity of the mammary gland, such as lactogenesis andinvolution.Proteins in human milk may also be used as markers of in-
fection and inflammation of the mammary gland. Several studieshave reported changes to the levels of immunological andinflammatory proteins during mastitis. For example, lactoferrin,sIgA, secretory leukocyte protease inhibitor, and serum albuminhave all been found to be present at higher levels in human milk
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Table 2
name peptidesa unusedb fold differencec
Up-regulated in preterm milkAbundant proteins Serum albumin 57 57.57 2.35
aThe number of peptides identified. bUnused ProtScore is a measure of the protein confidence for a detected protein. An Unused ProtScore of 1.3corresponds to 95% confidence, with a higher score representing a higher level of confidence. cThe ratio between the abundance of each protein inthe pooled term and preterm samples, expressed as an average of the duplicate experiments. The value is positive when the protein is more abundantin the preterm milk, and negative when the reverse is true. dProteins that were found to be differentially expressed in one replicate at a confidencelevel >95% and in the other replicate at a confidence level >90%. eProteins that were found to be differentially expressed in both replicates at aconfidence level >90%.
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during episodes of mastitis.35,37 A recent study in bovine milkalso identified a number of immunological proteins as being up-regulated during Escherichia coli infection.38 Of the proteins weidentified, 120 (24% of total) were associated with immune andinflammatory pathways and may have the potential to act assensitive biomarkers of mammary gland inflammation. Promisingcandidates include eight heat shock proteins that we identified inhuman milk for the first time (Table 1), which are known torespond to cellular insults.39
In addition to yielding information regarding mammarygland function, the expansion of the human milk proteome inthe present study is also of potential interest from an infantcentered perspective, in that many of the proteins may beinvolved in providing nutritional, protective, and developmentaladvantages to breastfed infants. With respect to infant growthand development, we identified 33 proteins (7%) as being in-volved in tissue development, including a number of proteinsidentified for the first time, such as granulin (GRN), cysteine-rich motor neuron protein (CRIM1), gremlin-2 (GREM2),nephronectin (NPNT), and bone morphogenetic protein 1(BMP1). GRN is a growth factor with marked functionalsimilarities to the epidermal growth factor family and has beenshown to regulate cellular proliferation, particularly in thehematopoietic and reproductive systems.40 Similarly, GREM2also regulates cellular differentiation and is involved in the Wntsignaling pathways.41 NPNT, BMP1, and CRIM1 have beenshown to interact with several growth factors and to play im-portant roles in the differentiation of osteoclasts, chondrocytes,and motor neurons, respectively, although more general roles indevelopment have also been proposed.42−44 While furtherresearch is required to assess whether these proteins retain theiractivity upon digestion, it is known that human-milk-fed infantsexperience developmental advantages over formula-fed in-fants,45−47 and it is possible that proteins within this groupmay be partly responsible.Proteins involved in immunity and inflammation constitute
24% of the proteins identifed (Figure 5), signifying the critical
role that human milk plays in protecting infants from infection.Indeed, Vorbach et al.48 argued that it was immune protectionrather than the provision of nutrition that was the original func-tion of the mammary gland in premammals. Although there isan abundance of literature describing the protective advantagesconferred upon infants through breastfeeding, the mechanismsinvolved are far from delineated.49 Individual proteins havebeen shown to exert protective effects through multiple path-ways, even after proteolytic digestion.50,51 Furthermore, there is agreat deal of interaction between different proteins involved inthe immune response, as well as with the infant’s own defenses.49
The identification of additional potential immune proteins pre-sent in human milk (Table 1) may be of use in further elucidat-ing these complex protective mechanisms. Immune responseproteins that we identified in human milk for the first timeinclude C1q and tumor necrosis factor related protein-1(CTRP1), peroxiredoxins-1, -2, and -6 (PRDX1, PRDX2,PRDX6), glutathione peroxidase 3 (GPX3), and HLA class Iand II histocompatibility antigens (HLA-A, HLA-DRA). CTRP1is a cytokine that possesses both immunomodulatory and meta-bolic functionality, inhibiting common pro-inflammatory path-ways, as well as being involved in glucose and insulinregulation.52,53 PRDX1, PRDX2, PRDX6, and GPX3 are allinvolved in systems of oxidative stress regulation, protecting cells,enzymes, and other proteins from oxidative damage,54 whereasHLA-A and HLA-DRA are both membrane proteins, involved inpresenting foreign antigens to the immune system.55 While thepresence of these proteins in human milk does not indicate thatthey are functionally active in the infant gut, they nonethelessprovide useful targets for further investigation.To investigate whether the human milk proteome under-
goes detectable changes at different stages of mammary glanddevelopment, a pilot study involving iTRAQ analysis was usedto compare the protein composition of term and preterm milk.Although iTRAQ experiments are designed to detect differ-ences in the fractional composition of protein samples, in thepresent study the original protein concentration of each pooled
Figure 6. SDS-PAGE analysis of differences in protein composition of pooled term (T) and preterm (PT) milk samples. (A) Representative SDS-PAGE electrophoretograms of PT and T milk. Each sample was run in triplicate (n = 3). (B) The intensity of the protein bands corresponding tobile-salt stimulated lipase (BSSL), lactoferrin (LF), serum albumin (SA), sIgA, β-casein, and α-lactalbumin (ALA) were expressed as percentages ofthe total intensity of each lane. Differences between the two samples were analyzed using a Student’s t-test. All significant differences between groupsare indicated (p < 0.05).
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sample was equivalent. This means that the differences infractional composition also directly correspond to differences inthe concentration of individual proteins between term and pre-term milk.In order to detect differentially expressed proteins of both
high and low abundance in term and preterm milk we adopteda workflow including parallel iTRAQ experiments. In a similarmanner to a recent publication,20 iTRAQ comparisons of pool-ed term and preterm milk samples were conducted both withand without prior ProteoMiner treatment. This enabled us todistinguish between high abundance proteins, those identifiedwithout ProteoMiner treatment, and low abundance proteins,those identified only when ProteoMiner treatment was usedprior to iTRAQ analysis. We found that ProteoMiner treat-ment did significantly alter the relative quantitation of the highabundance proteins, and therefore in the iTRAQ analysis ofProteoMiner-treated samples, only the relative abundance ratiosof the low abundance proteins were considered to be accurate.SDS-PAGE analysis was performed to verify the iTRAQ
quantitative analysis of high abundance proteins. The directionof the differences in expression of five proteins, bile-salt-stimu-lated lipase, lactoferrin, β-casein, sIgA, and serum albumin, interm and preterm milk were consistent between the twoanalytical methods; however, the iTRAQ experiment over-estimated the magnitude of the difference. Alpha-lactalbuminwas found to be differentially expressed in the iTRAQ experi-ment but not by SDS-PAGE. It is likely that these differencesbetween the two methods are due to an overestimation of thelevel of background contamination of the iTRAQ spectra bythe analysis software.56 Although previous studies report thequantitative accuracy of iTRAQ analysis of low abundanceproteins after ProteoMiner-treated samples,20 these results werenot verified in the present study. Despite these limitations,these results provide support for the use of an iTRAQ approachto identify differentially expressed proteins in human milk andillustrate how ProteoMiner treatment can be incorporatedwithin a quantitative analysis.We found 28 proteins that had significantly higher expression
levels in preterm milk compared to term milk and 27 proteinsthat had significantly lower levels of expression (Table 2). Anumber of these differentially expressed proteins such as lacto-ferrin, lysozyme, polymeric immunoglobulin receptor, lactadher-in, prolactin inducible protein, Ig heavy chain, mucin-4, vitro-nectin, and complement C3 are associated with the immuneresponse, protecting infants against infection.57 A number oftargeted studies have found higher levels of specific immunologicfactors in preterm milk and have accounted for these differenceson a teleological basis, arguing that the composition of pretermmilk differs from term milk to render it more suited to theprotection of vulnerable preterm infants.10,58 Our data contra-dicts this assertion, in that we found no concerted difference inthe expression of immunological proteins between term and pre-term milk, with some present at higher levels in preterm milkand vice versa (Table 2). This suggests that differences in proteincomposition between term and preterm milk are due to phys-iological differences in the mammary gland affecting proteinsynthetic and transport pathways, rather than being the result ofdiffering infant requirements, and supports the idea that aspreterm infants have only been able to survive in recent years,there has not been any selection pressure to encourage an in-crease in protective proteins in preterm milk.4
Similarly, three digestive enzymes, biotinidase (BTD), lipo-protein lipase (LPL), and bile-salt-stimulated lipase (BSSL)
were differentially expressed in term and preterm milk, withBSSL present at a higher level in preterm milk and both LPLand BTD found at a higher level in term milk. The presence ofthese enzymes in human milk is thought to compensate for alack of endogenous enzymes in the immature pancreatic juiceof newborns, enabling the efficient digestion of triacylglycerolsand biotin, respectively.59−61 Given the importance of theabsorption of fat and biotin to an infant’s growth and develop-ment, it is likely that the delivery of these enzymes is ofparticular importance to preterm infants. Again, their pattern ofexpression defies teleological explanation, in that while thehigher levels of BSSL in preterm milk may promote additionalgrowth in preterm infants, the lower levels of BTD and LPLmay be of detriment.Identifying proteins that are differentially expressed in term
and preterm milk may also be useful diagnostically. There havebeen a number of studies investigating the differences in mam-mary gland physiology and metabolism after preterm birth;however, the link between these physiological differences andpreterm milk composition largely remain unknown.4,34,62 Thedifferential expression of proteins in preterm milk may highlightpotential regulatory and metabolic pathways that are disruptedafter preterm delivery. For example, the higher levels of serumalbumin that we found in preterm milk may be due to the per-sistence of an open paracellular pathway after delivery in pre-term mothers, allowing the flow of serum proteins into themammary alveoli. Indeed, levels of serum albumin in milk havebeen used previously as a marker of an open paracellularpathway.63,64 Similarly, the low level of prolactin-inducible pro-tein in preterm milk is interesting from a diagnostic perspective,in that it may reflect low levels of circulating maternal prolactin.Indeed, it has been shown that preterm mothers are more likelyto have lower levels of serum prolactin, which may be re-sponsible in part for lower levels of milk production in pretermmothers.65 Tenascin is another protein that was found to bepresent at much lower levels in preterm milk compared to termmilk (Table 2). Having been previously implicated in mammarygland development and differentiation,66,67 its concentration inmilk may also potentially be useful as a marker of mammarygland development after preterm delivery.It is also of interest that distinct sets of proteins were identi-
fied in the iTRAQ analysis of pooled term milk collected 7−14days postpartum and in the 2D-LC analysis of pooled term milkcollected 15−28 days postpartum, with over 100 proteinsunique to each sample (Figure 4C). Although no quantitativecomparison was conducted comparing these samples, it is likelythat many of these proteins change in relative abundance interm milk over this time period and therefore may also re-present proteins of interest with regard to mammary glanddevelopment throughout lactation.In summary, the present study represents the most com-
prehensive study to date of the human milk proteome, iden-tifying 261 novel proteins, as well as documenting changes inthe relative abundance of proteins in term and preterm milk.Knowledge obtained from this characterization of the proteinsin human milk will provide insights into the regulatory mech-anisms involved in the synthesis and secretion of human milk,particularly after preterm delivery, as well as identifying poten-tial proteins in human milk responsible for the nutritional,immunological, and developmental advantages conferred ontothe breastfed infant.
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■ CONCLUSIONS
We investigated the effectiveness of a number of different an-alytical techniques to analyze the human milk proteome. Dynamicrange compression of human skim milk by the depletion of caseinand ProteoMiner treatment followed by 2D LC−MS/MS was themost successful approach. In total, 415 proteins were identified,over half of which had not been found before in human milk. Inaddition, iTRAQ analysis was used to identify differentiallyexpressed proteins between term and preterm milk, providinginsights into metabolic differences in the mammary gland afterpreterm birth in comparison to term birth.
■ ASSOCIATED CONTENT
*S Supporting Information
Supporting Information Data File 1 contains individualannotated MS/MS spectra of each of the proteins for whichonly one peptide was identified. Supporting Information DataFile 2 displays the preparative 2DE gel of the skim milk aftercasein depletion and ProteoMiner treatment and each of thespots that was analyzed by MS. Supporting Information DataFile 3 contains tables displaying all of the peptides used foridentifying proteins in the 1D-LC, 2D-LC, iTRAQ, 1D SDS-PAGE, and 2DE experiments and their correspondingidentification strengths. Supporting Information File 4 is atable displaying the classification of the proteins according totheir function and location. This material is available free ofcharge via the Internet at http://pubs.acs.org.
The MS analyses were performed in facilities provided by theLotterywest State Biomedical Facility-Proteomics node at theWestern Australian Institute for Medical Resesarch. This study wasfunded by an unrestricted grant from Medela AG (Switzerland) tothe University of Western Australia. C.E. Molinari was supportedby a scholarship from the Western Australian Women’s ServiceGuild (2009−2011), and an Australian Postgraduate Award(2009−2011).
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