Shotgun proteomic analysis of human-induced sputum

RESEARCH ARTICLE

Shotgun proteomic analysis of human-induced sputum

Ben Nicholas1, Paul Skipp2, Richard Mould1, Stephen Rennard3, Donna E. Davies1,C. David O’Connor2 and Ratko Djukanovic1

1 Division of Infection, Inflammation and Repair, School of Medicine, Southampton General Hospital,Southampton, UK

2 Centre for Proteomic Research and School of Biological Sciences, University of Southampton,Bassett Crescent East, Southampton, UK

3 Nebraska Medical Centre, Pulmonary and Critical Care Section, University of Nebraska, Omaha, NE, USA

Induced sputum is a readily accessible biological fluid whose composition may alter as a con-sequence of disease. To date, however, the proteins that routinely populate this biofluid arelargely unknown, in part due to the technical difficulties in processing such mucin-rich samples.To provide a catalogue of sputum proteins, we have surveyed the proteome of human-inducedsputum (sputome). A combination of 2-D gel analysis and GeLC-MS/MS allowed a total of 191human proteins to be confidently assigned. In addition to the expected components, severalhitherto unreported proteins were found to be present, including three members of the annexinfamily, kallikreins 1 and 11, and peroxiredoxins 1, 2 and 5. Other sets of proteins identifiedincluded four proteins previously annotated as hypothetical or conserved hypothetical. Taken to-gether, these data represent the first extensive survey of the proteome of induced sputum andprovide a platform for future identification of biomarkers of lung disease.

Received: January 4, 2006Revised: May 5, 2006

Accepted: May 5, 2006

Keywords:

2-D PAGE / GeLC-MS/MS / Human bronchoalveolar lavage fluid proteins / Inducedsputum

4390 Proteomics 2006, 6, 4390–4401

1 Introduction

Diseases of the airways cause significant morbidity andmortality and in the case of asthma and COPD, their pre-valence is increasing [1]. Considerable effort has gone intodescribing the cells and mediators which may be involved indriving the disease processes and which determine diseaseseverity and therapeutic responsiveness. To this effect, studyof airway secretions has provided valuable insight into thedynamic processes in the respiratory system. The extra-

cellular fluid of the distal and lower airways comprises amixture of secreted components from the lung parenchyma(alveoli), such as surfactant proteins, which are essential foralveolar function [2], and proximal airways secretions that areenriched for goblet cell secretory products such as mucinsand defensins, which serve to neutralise pathogenic invasionand enable the proper working of the mucocilliary apparatus[3].

The cellular and mediator contents of the airways inhealth and disease can be sampled by bronchoalveolar lavage(BAL), bronchial washing (BW) or bronchial biopsies [4, 5].However, these methods are invasive, cause discomfort tovolunteer subjects, and are expensive and time consuming,making it difficult to obtain repeat samples. Furthermore,BAL, BW and nasal lavage fluid (NLF) cannot be consideredtrue biofluids since their collection inevitably involves sig-nificant dilution of secretions by the fluid instilled for sam-pling. Induced sputum is increasingly recognised as a suit-able alternative to these samples [6], taking advantage of thefact that the secretory products of the proximal and distal

Correspondence: Dr. Ben Nicholas, Inflammatory Cell BiologyGroup, Division of Infection, Inflammation and Repair, School ofMedicine, Southampton General Hospital, Tremona Road,Southampton SO16 6YD, UKE-mail: [email protected]: 144-2380-511761

Abbreviations: BAL, bronchoalveolar lavage; DTE, dithioerythri-tol; NLF, nasal lavage fluid; sputome, sputum proteome

DOI 10.1002/pmic.200600011

© 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com

Proteomics 2006, 6, 4390–4401 Clinical Proteomics 4391

airways are transported by the mucocilliary apparatus to-wards the larger airways where they can be sampled non-invasively by induction with either hypertonic or, in the caseof hyper-responsive airways, isotonic saline [7].

Improvements in sputum induction and processing haveincreased the ability to provide data of clinical value [8]. Al-though there is currently no single standard procedure foreither sputum induction or processing [9], protocols typicallyinvolve pretreatment of subjects with a bronchodilator priorto induction. The expectorated sample is treated with amucolytic agent such as DTT or dithioerythritol (DTE) toreduce disulphide bonds in the oligomeric gel-formingmucins. This allows separation of the cells from the fluidphase by centrifugation [10] and analysis for inflammatorycell content by simple cytology or flow cytometry, andinflammatory mediators, e.g. by ELISA or other immuno-assays [11]. Sputum samples are also routinely used toidentify airway bacterial and viral infections [12].

To date most research into airways diseases has focusedon either individual or a limited number of mediators/celltypes. Recognising the limitations of such highly focusedresearch, more global approaches, looking at total gene (bymicroarray analysis) or protein expression (by proteomics)have been developed in order to enable more comprehensivecharacterisation of the components within the airways and toincrease understanding of both normal biology and changesthat occur in disease.

Proteomic analyses of several biofluid-derived samplesassociated with the human airway have been reported,including NLF [13–17], BAL fluid and BWs [18–21], andsaliva [22–29]. However, there have been no previous reportsof the proteome of sputum (hereafter referred to as the‘sputome’). In part, this is due to the presence of abundant,high-molecular-weight and highly charged mucins in spu-tum samples, which complicates analysis by preventingsatisfactory separation of sputum proteins via conventionaltechniques such as 2-DE, as they readily crosslink via theirsulphydryls and hence decrease gel resolution. 2-DE alsounder-represents other proteins with extreme physico-chemical properties, e.g. those that are poorly soluble, veryhydrophobic or those with extreme pI values. For optimalproteome coverage, it is therefore necessary to supplement2-DE with complementary approaches. One promisingmethod is GeLC-MS/MS, in which proteins are first fractio-nated by conventional SDS-PAGE, prior to excision of mul-tiple gel slices and in situ digestion of proteins with trypsin.The resulting peptides are then resolved using nanocapil-lary LC and identified by MS/MS [30]. Due to the robustnature of conventional SDS-PAGE and the resolving powerof LC-MS/MS, peptides from a diverse range of proteins canbe identified and assigned. In this study, we have used acombination of 2-DE and GeLC-MS/MS to survey the hu-man sputome. The results obtained suggest that this bio-fluid has significant complexity, increasing its potentialvalue as a diagnostic sample for the study of disease mech-anisms in the airways.

2 Materials and methods

2.1 Induction and collection of induced sputum

Three repeat sputum samples were obtained and pooled froma healthy female (age 47; current smoker with 25 pack yearssmoking history), with normal lung function as shown by aseries of tests including spirometry, to exclude significantairways obstruction, assessment of carbon monoxide diffu-sion capacity, to exclude lung parenchymal disease, primarilyemphysema, and bronchodilator reversibility testing with theB2-agonist salbutamol, and histamine challenge to excludebronchial hyper-responsiveness that is typical of asthma. Thesubject was also nonatopic as determined by absence of posi-tive skin prick tests to a panel of common allergens.

A standard induction protocol recommended by theEuropean Respiratory Task Force on induced sputum wasused, involving premedication with 200 mg of salbutamoland inhalation of 4.5% hypertonic saline for 20 min [31]. Thesputum samples were stored on ice during collection, andimmediately processed.

2.2 Sputum processing

Mucoid portions of the sputum were selected as previouslyreported [32]. A portion of the samples was sent to the micro-biology laboratory for culture in order to exclude infection –either clinical or subclinical. The rest of the sample was dividedinto two parts; these were treated with four volumes (w/v) ofPBS alone (PBS sample) or PBS to which DTE had been addedto a final concentration of 5 mM DTE (PBS–DTE sample). Aprotease inhibitor cocktail (Sigma-Aldrich, Poole, UK) wasthen added to the sputum sample (22.5 mL/g of sputum). Thetubes were then placed on a bench roller (Beckton-Dickinson,Oxford, UK) for 30 min at room temperature and the contentswere filtered through a 70-mm mesh (Marathan Lab Supplies,London, UK) and then centrifuged at 4006g for 10 min at 47Cto separate the cells from the fluid phase. The supernatantswere carefully removed and recentrifuged at 12 0006g, 47C for10 min before being aliquoted and stored at 2807C. The cellpellets were resuspended in 1 mL of PBS and the number ofviable cells and differentially stained inflammatory cells weredetermined by trypan blue exclusion and staining of cytospinpreparations using the Diffquik method as previously de-scribed in [33]. The mean relative counts of neutrophils andmacrophages expressed as a percentage of total inflammatorycells were assessed as 53% (63.8%) and 39.3% (64.0%),respectively, and the mean count of squamous cells, anindicator of salivary contamination, expressed as a percentageof all cells counted was 14.6% (64.6%).

2.3 Analysis by 2-DE

The sputum supernatants from pooled PBS and PBS–DTEsamples (133 mg of protein) were precipitated separately bythe addition of four volumes of ice-cold acetone and incu-


4392 B. Nicholas et al. Proteomics 2006, 6, 4390–4401

bated overnight at 2207C. The following day, the pellets werecollected by centrifugation (12 0006g for 10 min), washedthree times with 0.5 mL of ice-cold acetone using the samecentrifugation conditions, and then briefly air-dried prior tosolubilisation in 350 mL of 2-D lysis buffer (8 M urea, 4% w/vCHAPS, 0.2% w/v ampholytes, trace bromophenol blue).The samples were solubilised by incubation at room tem-perature for 1 h, and then centrifuged at 12 0006g for10 min at 207C. The supernatants were collected and thenused to rehydrate 18 cm pH 3–10 nonlinear IPG strips (GEHealthcare, Little Chalfont, Bucks, UK) for 12 h using anIPGphor system (GE Healthcare) with 50 V applied to facil-itate uptake of proteins. The following day, proteins werefocused using a stepwise protocol (500 V for 1 h, 1000 V for1 h, 8000 V for 4.30 h). When focusing was complete, thestrips were incubated in equilibration buffer (50 mM Tris-HCl pH 8.8, 6 M urea, 2% w/v SDS, 30% v/v glycerol, tracebromophenol blue) containing 10 mg/mL DTT for 15 min,and then in the same buffer containing 25 mg/mL iodoacet-amide instead of DTT for a further 15 min. Proteins werethen separated on 12–14% Excelgel XL SDS gels (GEHealthcare) using the Multiphor II system (45 min at 20 mAfollowed by 200 min at 40 mA). When separation was com-plete, the gels were fixed in 10% v/v methanol, 7% v/v aceticacid for 30 min on a rocking platform, rinsed with distilledwater and stained overnight with Sypro Ruby (BioRad,Hemel Hempstead, UK). The following day, the gels wereagain washed with fixative for 1 h, and three times for 30 minwith distilled water prior to imaging on a Versadoc imager(BioRad). Exposure times were typically 10–15 s. Followingimaging, the gels were restained overnight with colloidalCoomassie stain (EZblue, Sigma-Aldrich) and rinsed againin water. The stained gels were then stored in distilled watercontaining 0.1% w/v sodium azide. This restaining step wasperformed to ensure accuracy of the subsequent spot cuttingsteps.

2.4 Image analysis and gel spot picking

Triplicate gel images from the PBS sample gels were ana-lysed for spot detection and matching using PDQuest ver-sion 7.1.1. A total of 694 spots were matched between allthree gels which matched 673, 662 and 611 spots to themaster image, respectively, with only 8 spots remainingunmatched. Annotated PDQuest files of the relevant gelimages are available upon request. The three gels were thenrinsed several times with distilled water, and all 694 gel spotscollected using a ProteomeWorks Plus Spot Picker (BioRad).Acrylamide plugs were placed in 96-well mictotitre platescontaining analytical grade water ready for trypsinisation.

2.5 Preparation and digestion of sputum proteins

Acrylamide gel plugs bearing proteins were subjected to insitu trypsin digestion using the method of Shevchenko et al.[34]. The resulting peptides were separated by nano-RP LC,

using a Waters C18, 3 mm, 100 Å (150 mm675 mm, id) col-umn (Waters, Elstree, Herts, UK) and electrosprayed into aquadrupole TOF tandem mass spectrometer.

2.6 GeLC-MS/MS

Sputum proteins from the same pooled PBS and PBS–DTEsamples as used for the 2-DE analysis were dissolved in re-ducing sample buffer and heated to 957C for 5 min. Sampleswere fractionated in duplicate (30 mg/lane) on a NuPAGE 4–12% gradient SDS-polyacrylamide gel (Invitrogen, Paisley,UK). After visualisation with CBB, the gel lanes from thePBS–DTE sample (length: 7 cm) were excised, cut into 25equal-sized pieces, and subjected to in situ trypsin digestionas described for 2-D gel acrylamide plugs.

2.7 MS and data processing

Peptides were separated using RP LC prior to application onthe mass spectrometer (as described for 2-DE picked spots).All data were acquired using a Q-tof Global Ultima (Waters)fitted with a nanoLockSpray™ source to achieve better than10 ppm mass accuracy for the precursor ions. A survey scanwas acquired from m/z 375 to 1800, with the switching cri-teria for MS to MS/MS including (i) ion intensity, (ii) chargestate and (iii) exclusion list. The exclusion list was generatedusing the real-time database searching algorithm in Pro-teinLynx Global Server 2.05 (Waters). The collision energyused to perform MS/MS was varied according to the massand charge state of the eluting peptide.

All MS/MS spectra were automatically processed usingMassLynx 4.0 (Waters) and searched against the NCBI non-redundant database (February–May 2004 versions) usingProteinLynx Global Server 2.05. Proteins were only assignedif, for each peptide ion, �3 experimentally derived y ionscould be matched to the predicted spectra (with 0.1 Da toler-ance). Where only one peptide was used in the identificationof a specific protein, manual assignments of the spectra wereperformed. Where peptides matched more than one data-base entry due to redundant protein sequence submissions,assignments to the duplicated sequence were removed.

3 Results and discussion

3.1 Choice of sample

A single healthy smoker donor was chosen to provide thesputum samples for this study for two reasons. Healthysmokers easily produce a good sputum sample which, inview of the absence of disease is likely to be more repre-sentative of sputum in general. Nonsmokers generally do notprovide sufficient material to perform both the analyticaltechniques (1-D and 2-D gel-LC-MS/MS) described here onthe same sample and there is greater risk of salivary con-tamination as the subject attempts to produce sufficient



expectorate. During the optimisation phase of this project,we found that pooled samples do not separate well by 2-DEbecause of the presence of interefering substances in somesamples. In order to establish a standard proteome for futureanalyses, we chose this individual’s sample because it pro-duced a high quality 2-DE image with a large number ofhighly resolved spots. In order to avoid bias of a single sam-ple, three samples from the same donor were obtained dur-ing three separate inductions; these were pooled and run bythe two methods.

3.2 2-D gel analysis of the sputome

Protein extracts from sputum were prepared by solubilisa-tion of samples in lysis buffer and fractionated by 2-DE.Figure 1 shows representative gels of samples processedusing PBS–DTE or PBS alone, respectively. In view of thesolubilising properties of DTE, samples processed with thisreducing agent were expected to produce better images thansamples processed with PBS alone. However, the use ofPBS-processed samples routinely resulted in better qualityprotein separations and less streaking of gels. The gelsobtained from PBS–DTE samples typically resolved poorlyin the pI 3–7 region of the first dimension which causedphysical contraction of the gel image and resulted in smal-ler and poorly resolved images (Fig. 1A) when compared tothe PBS samples (Fig. 1B). Since DTT is routinely presentin the sample buffer at a higher concentration than the DTEpresent in PBS–DTE samples, this effect could not beexplained by the use of this reducing agent during sampleprocessing. We believe that the streaking was caused by thepresence of mucins, molecules which are highly chargedand have a tendency to form viscous gels in nonreducingconditions. The large size of the monomeric mucin mole-cules, which exceed 1 MDa even in fully denaturing condi-tions [35], may prevent entry of these proteins into eitherthe first or second dimension gels, or both. Because DTE isuniversally used as a processing agent for sputum, weattempted to modify its use and thus improve the imagequality. However, the detrimental effect of mucins in 2-Dgels using PBS–DTE samples could not be abrogated byprior alkylation of the mucin molecules with iodoacetamide(results not shown).

The use of PBS samples resulted in a significantimprovement in the number of features that could beresolved (Fig. 1B) and samples prepared in this way routi-nely displayed .600 resolvable features. All the spots thatwere reproducibly present in at least three replicate gels(694) following analysis by PDQuest and generation of amaster gel image (Fig. 1C) were excised, digested in situwith trypsin and the resulting peptides analysed using MS/MS. Sixty-one proteins were identified in this manner,most of which corresponded to the relatively high-abun-dance sputum, saliva, NLF and BAL proteins previouslyreported [13–29] with the exception of mucins which, de-spite constituting approximately 90% of total sputum

Figure 1. Comparision of 2-DE protein profiles obtained withsputum processed using PBS–DTE (Panel A) or PBS alone (PanelB) and a synthetic image generated from triplicate PBS samplegels used for image analysis (Panel C). Sputum samples pro-cessed using either PBS (A) or PBS–DTE (B) (both 133 mg/gel)were isoelectrically focused using 18 cm pH 3–10 nonlinear IPGstrips, and then separated using 12–14% polyacrylamide gels.The gels were stained using Sypro Ruby fluorescent proteinstain. A pooled PBS sample was then prepared in triplicate andseparated by 2-DE using the same procedure (C). The gels wereanalysed using PDQuest and an averaged gel image created wasused for spot picking and MS/MS. Marker protein positions areindicated on the right-hand side of each gel image.

proteins, were not at all represented on the 2-D gels. No hy-pothetical proteins were found and other classes of protein,e.g. integral membrane proteins, were poorly represented(Table 1).

3.3 Analysis of the sputome by GeLC-MS/MS

To increase the proteome coverage obtained by 2-DE, weundertook a GeLC-MS/MS analysis, a procedure whichseparates proteins on the basis of molecular weight in a



standard SDS-PAGE gel which is then cut into 25 pieces as aform of prefractionation to simplify the sample into molec-ular weight groupings. Each gel slice is cleaved by trypsin toobtain peptide fragments and then further fractionated byLC separation. Peptide fragments are then analysed by MS/MS to identify the proteins of origin. The PBS and PBS–DTEsamples (32 mg/lane) were solubilised separately in SDS-PAGE sample buffer as described in Section 2, and fraction-ated by SDS-PAGE (Fig. 2). Some very high-MW (.200 kDa)material was discernable in the stacking gel/resolving gelinterface of the PBS–DTE sample but was absent in the PBSsample. Since the presence of this high-molecular-weightmaterial did not disrupt the fractionation of other proteins,and was likely to increase proteome coverage, proteins fromthe PBS–DTE sample were selected for further analysis. Gellanes were cut into 25 consecutive segments which thenunderwent trypsin digestion and tandem MS. A total of42 640 spectra were analysed, resulting in 590 peptideassignments and the identification of 175 individual humanproteins or protein isoforms, 42 of which were also identifiedby 2-D gel analysis (Table 1). Only 16 of the proteins presentwere not identified by GeLC-MS/MS and were identified bytheir presence on 2-D gels alone.

We conclude, therefore, that GeLC-MS/MS enabled theidentification of a greater number of proteins than 2-D gelanalysis. The other advantage of GeLC-MS/MS is that it alsosampled in a relatively unbiased manner low-abundanceproteins, high-molecular-weight proteins, and proteins withextreme pIs, which could not be detected on 2-D gels (Table 1and Fig. 3). For example, it detected a 2.2 MDa mucin(MUC5B) as well as the 10.1 kDa Uteroglobin related protein

Figure 2. Gel image of sputum proteins fractionated by 1-D elec-trophoresis for GeLC-MS/MS analysis. Sputum samples pro-cessed using either PBS alone, or PBS–DTE (gels loaded with32 mg/lane) were fractionated using reducing SDS-PAGE electro-phoresis as described in Section 2. The gels were stained withcolloidal CBB stain. The samples were run in duplicate. Hashedlines indicate the approximate location of the 25 gel slices usedfor GeLC-MS/MS analysis. TR, top of resolving gel.

Figure 3. Scatterplot of molecular weight and pI distribution ofproteins identified in sputum. The predicted MW in kDa, and pIfor all proteins identified by GeLC-MS/MS in induced sputumlisted in Table 1 are plotted.

2 (Table 1). The most acidic and basic proteins identified bythis GeLC-MS/MS analysis had pIs of 4.6 and 11.8, respec-tively, which is in reasonable agreement with the predictedpI range for the predicted components of the human pro-teome (3.64–12.98). Interestingly, we did not identify pro-teins with a molecular weight below 10.1 kDa, despite theestimated resolution of the SDS-PAGE gel step to approxi-mately 4 kDa. Many small peptides such as defensins, whichhave been implicated in defence mechanisms of the airways,and cytokines/chemokines implicated in inflammatoryresponses have been defined in induced sputum samples butwere not identified in this study. An alternative approachgeared more towards lower molecular weight peptide analy-sis, such as the use of multidimensional LC, would probablyreveal these elements of the proteome. The functional andclinical significance of the identified components is dis-cussed in the following sections.

3.4 Human sources

A total of 258 proteins were detected in our analyses, ofwhich 191 were identified as being of human origin. In con-trast to pure cell or isolated tissue samples, the origins ofproteins in sputum are numerous and complex. Theyinclude bone fide contributing sources (including the lowerand upper airways secretory products, cellular products andinflammatory cell derived products) as well as contaminants,e.g. saliva and, conceivably, gastrointestinal proteins. Someproteins could also be derived from damaged epithelial cellswhich may be sloughed off during sputum expectoration.The degree of contamination of induced sputum by theseother sources is difficult to quantify since some proteins (e.g.PLUNC) may have more than one site of production.Accepting these caveats, the identities of many of the pro-teins assigned in this study are consistent with the results of



Table 1. Proteins identified in human-induced sputum following 1-D or 2-D gel separations, trypsinisation and tandem MS

Protein name NCBI accessioncode

PredictedMW (Da)

PredictedpI

Coverage(%)

No. peptidesmatched

Presenceon 2-D gels

14 3 3 Protein beta/alpha NP_003395 27 951 4.8 10.7 214 3 3 Protein epsilon polypeptide NP_006752 27 951 4.7 14.7 3 Y14 3 3 Protein zeta/delta NP_003397 27 745 4.8 13.6 36-Phosphogluconolactonase NP_036220 27 547 6.0 18.3 4 Y*Actin beta (ACTB) human AAH12854 41 737 5.8 23.3 6 YActin related protein 11 JC7580. 23 712 5.5 5.2 1Airway lactoperoxidase AAG38481 22 478 (partial) 9.3 5.2 2Albumin 1AO6A. 69 367 5.9 6.3 2 YAlcohol dehydrogenase 1D1TA. 40 006 8.4 4.0 1Alcohol dehydrogenase class IV mu/sigma

chainAAB22232 40 006 5.8 20.0 1

Aldehyde dehydrogenase 3A1 AAH04370 50 379 6.3 2.7 2Aldehyde dehydrogenase 8 NP_000686 42 795 6.2 3.6 1Aldehyde dehydrogenase A1 CAI12261 25 314 6.0 6.4 1 Y*Alpha 1 acid glycoprotein 1 precursor AAH26238 23 512 5.1 4.5 1Alpha 1 antichymotrypsin precursor P01011 47 651 5.4 5.6 1 YAlpha 1 antitrypsin P01009 46 737 5.5 9.1 2 YAlpha 1 b glycoprotein OMHU1B 54 273 5.9 2.1 1 Y*Alpha 2 macroglobulin 1009174A 163 278 6.3 2.1 3Alpha actinin-1 CAA38970 103 058 5.1 6.6 2Alpha enolase AAH09218 47 038 7.2 18.5 2 YAlpha fetoprotein FPHU 68 678 6.0 1.1 1 Y*Annexin A1 1AIN 38 583 8.1 8.6 3Annexin A2 AAH09564 38 473 8.0 25.1 5Annexin A4 P09525 35 752 6.0 5.4 1Annexin A5 1HVE 35 806 5.0 7.8 1Antibacterial protein Fall-39 precursor S74248. 19 301 9.8 5.3 1Antileukoproteinase 1 precursor NP_003055 14 326 9.2 9.1 2Apolipoprotein A1 precursor 1AV1A 30 778 5.7 20.4 4 YApolipoprotein B-100 precurson AAA51752 515 563 8.3 0.9 1Apolipoprotein J AAN87347 9 056 (partial) 8.5 14.5 1 Y*Apoptosis inducing factor (AIF)-like mito-

chondrion-associated inducer of deathNP_116186 40 526 9.4 2.7 1

Arp2/3 complex 20 kDa subunit BAB14828 19 667 9.2 7.1 1Azurocidin precursor 1617124A 26 886 9.6 31.7 2Bactericidal/permeability-increasing

protein-like 1 precursorAAQ89085 49 130 8.7 3.9 3 Y

Beta-microseminoprotein precursor 1209281A 12 865 5.4 76.2 1 YCalcium and integrin binding protein 1 1DGUA 21 586 4.6 8.2 1Calcyphosine NP_542157 20 967 5.0 8.0 1 YCalgizzarin AAP88914 11 740 7.3 23.8 2 Y*Calgranulin A NP_002955 10 835 7.0 12.9 4Calgranulin B 1IRJA 13 242 6.0 13.2 2 YCalreticulin NP_004334 48 142 4.3 3.4 1 Y*Carbonic anhydrase VI precursor P23280 35 365 7.1 4.5 3Cathepsin D precursor 1LYAB 44 552 5.4 5.4 2 YCathepsin S precursor AAH02642 37 510 8.6 4.2 1Ceruloplasmin precursor AAA51975 122 205 5.4 1.5 5Chloride intracellular channel protein 1 AAC25675 26 792 5.1 9.1 3Clusterin precursor AAN78322 52 495 6.0 5.2 5 YCofilin (nonmuscle) NP_005498 18 371 8.5 6.6 1Complement C3 precurson NP_000055 187 164 6.3 1.8 7 YComplement C4 precursor AAK49811 192 771 6.6 29.3 2Complement C6 precursor BAD02321 104 844 6.8 1.2 3Complement factor 1 precursor 1202205A 65 720 5.3 6.5 1Complement factor H precursor AAA52013 139 125 8.2 4.5 1



Table 1. Continued


PredictedMW (Da)

PredictedpI

Coverage(%)

No. peptidesmatched

Presenceon 2-D gels

Coronin 1A AAA77058 51 026 6.5 3.5 1Cystatin C precursor 1G96A 15 799 8.9 14.2 2Cystatin D CAA49838 16 080 8.1 9.0 1 Y*Cystatin S precursor 1008184A 16 214 4.7 31.9 3Cystatin SA precursor 1312318A 16 445 4.9 12.8 1Cystatin SN precursor NP_001889 16 362 7.4 51.4 3Cysteine rich secretory protein 1 precursor NP_006052 28 481 8.2 21.4 1Cytovillin 2 (fragment) AAF09502 16 241 (partial) 9.6 7.1 1DMBT1 BAA78577 193 990 5.3 7.3 14Erythrocyte membrane protein band 7.2

(Stomatin)AAH10703 31 600 8.2 9.6 1

Ezrin 1NI2A. 69 268 9.2 5.7 1F actin capping protein alpha 1 subunit NP_006126 32 923 5.6 5.2 1 YGalectin 3 binding protein precursor NP_005558 65 331 5.2 2.9 4Gelsolin precursor 1SOL 85 698 11.8 55.0 1Glial fibrillary acidic protein AAA52529 49 880 7.4 16.7 1GST alpha 3 1GSSA 25 302 5.5 9.6 4Glyceraldehyde 3 phosphate

dehydrogenaseCAA25833 35 922 8.5 19.1 4 Y

Haptoglobin precursor AAH58031 45 205 6.4 10.5 2 YHemoglobin alpha chain AAK15770 15 126 7.8 32.1 1Hemoglobin beta chain 1HDBB 15 867 7.3 41.9 3 YHemoglobin beta chain AAQ63175 15 867 6.6 24.8 2Hemopexin precursor AAA52704 51 676 7.0 8.9 4 YHeterogeneous nuclear ribonucleoprotein k XP_209517 47 557 5.2 3.3 1Histone H4 NP_003529 11 236 11.4 36.4 2HLA A2 precursor 1HLAM 40 922 6.9 22.7 1HLA class 1 histocompatibility antigen,

A-2 alpha chain precursor1HLAM 40 922 6.9 22.9 3

hsp90 alpha BAB15121 84 543 5.0 14.9 1Similar to tyrosine 3/tryptophan 5

monooxygenase activation proteinXP_016144 14 824 6.7 9.6 2

Hypothetical protein DKFZp686E033231 CAE45995 78 816 6.3 3.3 4Hypothetical protein BAB71022 54 576 5.5 2.5 1Ig alpha 2 chain C region AAB59396 36 508 6.0 24.8 3Ig heavy chain variable region AAC51063 14 142 8.8 19.0 1 YIg J chain P01591 15 594 4.6 42.3 3Ig kappa chain C P01834 11 609 5.8 32.1 2Ig kappa light chain VLJ region BAC01759 8.0 41.2 9Ig lamba 1 variable region CAE18323 6.6 27.5 3Ig lamba chain C region AAA59109 8.3 19.4 3Ig lamba light chain AAF13225 7.3 14.8 2Ig lamba light chain VLH region BAC01849 8.3 22.3 4Ig lambda chain V region AAB48615 8.2 23.2 2Ig lambda light chain C region AAA59106 8.2 37.5 2Ig lambda light chain VLJ region BAC01849 8.3 25.4 5Ig light chain variable region CAB48528 5.0 18.8 1Ig mu chain C region membrane bound

segmentP20769 4604 5.2 8.3 2

IgA heavy chain variable region AAK12851 8.4 21.4 1Ig alpha1 chain C region 1OW0A 37 655 7.5 30.4 4IGF binding protein 2 precursor P18065 35 138 7.8 28.9 1IgG Fc binding protein AAD15624 5.8 2.4 3IgG heavy chain constant region CAA04843 6.3 7.0 1IgG heavy chain variable region AAB69660 8.6 32.8 1IgG2 CAA04747 4.6 21.2 1



Table 1. Continued


PredictedMW (Da)

PredictedpI

Coverage(%)

No. peptidesmatched

Presenceon 2-D gels

IgG2 heavy chain constant region AAN76043 7.9 14.5 4IgH heavy chain Fd fragment AAA87671 8.4 19.9 1IgHD protein BAC87503 62 967 6.2 26.4 7IgM 1QLRA 5.9 55.8 8Immunoglobulin mu chain AAB59419 5.6 25.0 1Kallikrein 1 isoform 3 preprotein AAR10467 19 238 4.7 7.6 1 YKallikrein 11 precursor NP_006844 27 466 8.9 4.4 1Keratin 10 AAA59199 57 247 4.8 8.9 5 YKeratin 1b CAD91892 61 801 5.9 2.1 1 YKeratin type 2, cytoskeletal 1 NP_006112 65 886 8.4 7.9 8 YKeratin type I cytoskeletal 9 NP_000217 61 987 5.3 5.1 3 YKeratin type II cytoskeletal 2 epidermal NP_000414 65 865 8.3 3.7 4 YKeratin type II cytoskeletal 6f P48669 59 936 8.3 5.5 3 YL-plastin (lymphocyte cytosolic protein 1, AAB02845 70 289 5.5 4.9 2Lactoperoxidase (salivary) precursor NP_006142 80 288 9.0 10.5 3Lactotransferrin precursor AAA86665 78 338 8.3 9.3 22 YLeukocyte elastase inhibitor NP_109591 42 742 6.2 2.9 1L-lactate dehydrogenase B chain 1I0ZA 36 507 6.0 11.9 1LOC389429 protein AAH62712 31 176 7.0 15.6 2LPLUNC1 (von Ebner minor salivary gland

proteinNP_149974 52 442 7.2 12.8 14 Y

Lysozyme C precursor 1IP4A 16 537 9.4 63.8 8 YMacrophage capping protein (CapG) 1J72A 38 518 5.5 3.7 2Malate dehydrogenase G01650 36 295 6.2 3.6 2Mammaglobin B precursor NP_002398 10 884 5.7 12.6 1 Y*Megakaryocyte potentiating factor precursor AAH03512 67 908 6.1 1.9 1MGC27165 AAH16369 53 376 8.2 14.7 4MGC45438 protein (Homo sapiens) AAH33681 44 612 6.8 3.3 1MMP-9 CAC10459 78 427 5.9 2.3 1 Y*MUC 7 NP_689504 39 170 9.2 43.5 1MUC1 AAP97014 122 072 6.1 7.3 1Mucin 5AC (fragment) AAC15950 119 328 6.4 1.6 1Mucin 5AC fragment JE0095 130 073 6.9 3.9 5Mucin 5B AAG33673 590 499 5.4 6.1 13Myeloblastin 1FUJA 27 807 8.1 4.2 1Myeloperoxidase precursor 1CXPA 83 869 5.3 11.5 1NADPH dehydrogenase quinone 1 AAP20940 30 868 9.2 3.7 1Neuropolypeptide H3 AAD14234 20 926 9.0 14.3 1Neutrophil gelatinase associated lipocalin

precursor1QQSA 22 588 9.2 13.8 2

Nucleoside diphosphate kinase (NDKNDP) O60361 15 529 9.0 12.4 1OTTHUMP00000000459 AAH09564 38 659 8.0 8.4 2OTTHUMP00000040299 XP_351675 37 926 6.1 10.9 4Peptidylprolyl isomerase A isoform

2 (cyclophilin A)NP_982254 17 881 8.3 36.2 2 Y

Peroxiredoxin 1 NP_002565 22 110 8.5 5.1 1Peroxiredoxin 2 NP_859427 21 892 6.5 19.0 2Peroxiredoxin 5 mitochondrial precursor 1HD2A 22 026 7.4 12.7 1 YPhosphoglycerate kinase 1 NP_000282 44 483 8.5 4.1 1Phospholipid transfer protein CAC36020 54 739 8.8 4.9 2Phospogluconate dehydrogenase NP_002622 53 009 7.3 5.5 1Pigment epithelium-derived factor precursor AAH00522 46 342 6.3 14.1 5Plasma protease C1 inhibitor precursor AAA51849 55 154 9.3 9.2 2Poly Ig receptor precursor NP_002635 83 314 5.7 15.4 17 YProlactin inducible protein precursor NP_002643 16 572 8.5 6.8 6Proline rich protein 4 precursor AAM94338 15 097 7.0 11.2 2 Y



Table 1. Continued


PredictedMW (Da)

PredictedpI

Coverage(%)

No. peptidesmatched

Presenceon 2-D gels

Prominin 1 precursor AAH12089 97 202 7.4 1.6 2Protein PLUNC precursor NP_057667 26 713 5.6 28.5 5 YPulmonary surfactant protein A precursor LNHUPS 26 214 5.1 13.7 3Pulmonary surfactant protein B LNHUB 42 117 5.5 3.2 2Quiescin 6 protein AAH17692 66 860 9.0 3.1 1Ribonuclease 4 precursor AAB28688 16 840 9.3 10.9 1Salivary alpha amylase precursor 1SMD 57 768 6.7 31.7 9 YSAP1 1008184A 58 113 4.7 13.3 3Serotransferrin precursor AAH59367 77 050 7.2 15.9 8 YSerum albumin precursor 1AO6A 69 367 5.9 27.2 11 YSimilar ro RIKEN XP_351675 37 926 6.1 10.9 4Similar to common salivary protein 1 NP_660295 18 879 5.5 12.2 3 YSimilar to Gelsolin (Amyloidosis, Finnish

type)AAH17491 52 372 4.9 7.7 1

SPLUNC2 precursor AAL28113 27 011 5.7 4.8 1Squamous cell carcinoma antigen 1 AAB20405 44 565 6.7 17.7 6 Y*Syndecan binding protein syntenin NP_005616 32 444 7.6 11.4 1TALDO1 protein AAH09680 35 328 9.3 3.5 1 Y*Tetranectin precursor NP_003269 22 567 5.6 5.9 1Tetraspanin 1 A59262 26 301 4.9 5.4 1Thioredoxin P10599 11 606 4.8 61.9 1TIMP 1 precursor 1D2BA 8.4 29.4 3 YTRIF AAH35331 76 421 4.7 3.3 1Transcobalbumin 1 precursor AAH18632 48 195 5.0 4.7 4Transthyretin precursor AAA61181 15 887 5.4 19.7 2TRAP 1 BAC04139 80 011 7.4 4.0 1Triosephosphate isomerase 1HTIB 26 538 6.9 6.0 1 Y*Tubulin A6 AAH33064 36 648 8.3 6.2 1 Y*Unnamed secretory protein NP_872372 21 534 4.9 9.7 1Unnamed secretory protein Q7Z5LO NP_872372 21 534 4.9 8.4 1Uromodulin BAC87070 69 761 6.0 4.5 1 Y*Uteroglobin related protein 2 precursor NP_443095 10 100 9.2 18.3 2Vitamin D binding protein 1J78A 52 964 5.5 2.3 1 Y*Von Ebners gland protein precursor NP_002288 19 250 5.5 40.3 4 YZinc alpha 2 glycoprotein precursor 1ZAGB 33 872 6.0 12.0 4 Y

* Denotes detection by 2-DE and spot picking but not by 1-D GeLC-MS/MS.

previous studies. Thus, mucin isoforms 5B and 5AC, but notMUC2, were detected, in keeping with the results of Thorn-ton and Sheehan [35].

The composition of the sputome obtained in this studywas compared with the known proteomes of related airways-derived and saliva samples reported in studies using othersecretory sources, including BAL, NLF and saliva (Supple-mentary Table 1). The most significant of these are BAL andsaliva because they have been studied extensively and char-acterised in detail. BAL and saliva also probably represent themore compartmentalised proteomes that partly contribute tothe expectorated sputome. The degree of similarity betweenthe sputome and proteomes of saliva and BAL was striking(Fig. 4), reflecting the presence of abundant proteins,including the immunoglobulins and albumin which per-

form similar functions in all mucosal secretions. Whilstmany of the differences and similarities between differentcompartments of the respiratory tract and the salivary secre-tions are related to tissue specific proteins, some of thesemay be related to the types of proteomic studies performed(determining sensitivity and proteome representation) andto any mixing of proteins in the airways or during samplecollection. Multidimensional MS/MS studies as well as con-ventional 2-DE studies on both saliva and BAL have beenperformed [21, 22, 29]; these have identified 2076 proteins intotal, 135 of which are also present in sputum (Fig. 4; Sup-plementary Table 1). Whilst mixing of saliva and sputum ishighly likely to occur when collecting induced sputum, and itis possible that these proteins shared by the sputum andsalivary proteome represent simple contamination, it is also



Figure 4. Venn diagram of the numbers of common proteins be-tween induced sputum, BAL and saliva. The results from GeLC-MS/MS analysis of induced sputum were compared with theproteomes of BAL and saliva previously reported elsewhere [18–29]. The results show the degree of overlap between the sputomeand the published proteomes of these related biological fluids.

possible that these proteins are produced independently inthe salivary and lower airway mucous glands. Contaminationof sputum with saliva could also account for some, possiblyall, of the 94 proteins that were identified in sputum in thisstudy as being shared with saliva [22–29]. We have, in addi-tion, identified 51 proteins which have not yet been identi-fied in any of the other compartments which, therefore,represent proteins that are unique to the airways. Con-tamination by saliva does not apply to the 66 proteins whichwere identified in sputum in this study, and which werereported to be present in both BAL and saliva [18–29]. DuringBAL, the fibreoptic bronchoscope is wedged in a subseg-mental airway such that sampling involves only the airwaysand lung tissue distal to the tip of the instrument. These 66proteins are, therefore, likely to be common proteins sharedby the respiratory secretions and saliva, although it is alsopossible that these proteins are ubiquitous to all mucosalsecretions.

The exact source of proteins identified in sputum butalso detected in BAL is unclear. Some proteins and lipids,such as surfactant and SP-D, are produced by alveolar cellsand transported by the mucociliary escalator, making themdetectable in sputum [36]. The good correlation between BALand sputum for surfactant suggests that sputum is a repre-sentative sample for this product of alveolar cells. However,there is poor quantitative correlation between sputum andBAL in respect of most read-outs, including cell types andseveral mediators [37]. It is likely that some proteins undergoproteolytic degradation and/or are consumed by the homeo-static processes in the airways. This could explain theabsence of 1375 proteins detected in BAL but not in sputum,although a more likely explanation for this is that BAL itselfcauses microvascular leakage resulting in the presence ofserum proteins in the lavage fluid, a process avoided by spu-tum induction.

While the present study has identified proteins fromseveral of the major functional classes, including predictedlow-abundance proteins, certain components previously

reported to be present in saliva and/or BAL were not detec-ted in induced sputum. These include antithrombin andseveral apolipoprotein isoforms [18–29]. Given the relativesensitivity of GeLC-MS/MS, it is possible that the absence ofthese proteins is genuine. The proteins may, therefore, havepotential in the definition of sputum and for assessing thedegree of sputum contamination by saliva. A major reasonfor any discrepancy between these various studies may alsolie in the differences between the chosen experimentalmethods. Whilst multidimensional MS studies have nowbeen performed on saliva, BAL and sputum, there weredifferences in these studies in respect of health status ofdonors, the method of sample handling (including removalof abundant proteins), and also in terms of specific MStechnique and machine used. These differences are likely tobe reflected in the total numbers of proteins found, thusaffecting their degree of overlap when compared in thisstudy. There are also likely to be genuine differences inprotein content between these compartments. Studies inwhich individual mediators and cell types have been com-pared in BAL and induced sputum from the same individ-uals have shown little or no correlation between these twomethods which, as already stated, sample the periphery ofthe lungs (small- to medium-sized airways and alveoli) andlarger, more proximal bronchi, respectively. Clear differ-ences exist between sputum and BAL in relative counts ofinflammatory cells, with neutrophils being the prevalentcell type in sputum and the macrophage being the mostnumerous in BAL. As stated above, the differences in pro-tein content between the two compartments may be due todifferent degrees of microvascular leakage, more intenseexchange of fluids between the alveoli and the capillaries ofthe lung parenchyma during BAL, and different activity ofproteases.

Also evident from our studies is the contribution of othercell sources, such as inflammatory cells, to the sputome.Several proteins identified in the current study are mostlikely derived from neutrophils, more specifically from theneutrophil granules which play an important role in innatetissue defenses. A more detailed examination of the increas-ingly well-defined proteomes of these inflammatory celltypes [38, 39] will provide a valuable contribution to ourunderstanding of the contributory factors to the inducedsputome. Although the secretory products of neutrophils arerelatively well known, their specificity is not, and at presentthere are no proteomes available for related granulocytes ormacrophages which are the other major inflammatory cellpopulations in the sputum of healthy smokers.

Despite the obvious benefits of the discovery of 175 indi-vidual proteins in the induced sputome using GeLC-MS/MS,the limitations of this method (and the 2-DE method also)are apparent in the under-representation of known sputumcomponents such as cytokines, defensins, growth factors andantioxidant proteins, all of which have been reported instudies of induced sputum. The low-molecular weight ofmost of these components means that they are likely to have



few trypsin cleavage sites. This, coupled with the low abun-dance of many of these components, may account for theirunder-representation in the present study, and a separatelow-molecular-weight proteome analysis may be required toidentify and characterise these important elements.

3.5 Microbial proteins

The presence of proteins derived from nonhuman sources,in particular bacterial but also fungal, yeast, invertebrate andplant proteins is not surprising. Despite the near-sterile na-ture of the airways, sputum is expectorated via the mouthand may in this way become exposed to nonhuman proteinsources, including nonpathogenic bacteria that colonise themouth and pharynx. It is also possible that bacterial andfungal proteins are inhaled as particulates from the environ-ment rather than being present as living organisms. Thelarge number (32) of bacterial-derived proteins identified(data not shown) belies the fact that sputum samples rarelycontain significant numbers of pathogenic bacteria, al-though nonpathogenic bacteria, constituting the normal oralflora are often detected. Although during exacerbations andin chronically infected airways in patients with bronch-iectasis, bacterial and fungal colonies can be established [40],in the healthy smoker donor in this study sputum culturewas negative for both commensal and noncommensal bac-teria. The majority (65 of 67) of the microbial proteins foundwere identified with single peptide matches, and in anyregard, their presence may be donor specific. Future studiesmay elucidate the significance of the presence of these pro-teins.

3.6 Other processes

Only four proteins designated as ‘hypothetical’, ‘conservedhypothetical’ or ‘unnamed protein product’ in the humangenome were detected in this study, and 17 others werefound from nonhuman sources. The detection of peptidesfrom the predicted proteins substantiates the existence of thelatter and paves the way for more detailed studies to deter-mine their origins and to characterise their functions.

4 Concluding remarks

In this study we have combined a 2-D gel proteomicsapproach with GeLC-MS/MS to identify more than 250 pro-teins in human sputum, the vast majority of these being ofhuman origin and a minority being derived from bacterial/fungal sources. Whilst some deficiencies of this approachwere identified, notably (and not unexpectedly) the lack oflow-molecular-weight proteins, we have revealed proteinsthat are unique to sputum which would, therefore, appear tobe markers of events in the large airways which sputumpredominantly samples. This study establishes the proof ofthe concept that proteomics can be applied to sputum. It

opens the prospect that proteomics can be applied to identifymarkers of disease severity and, possibly, response to treat-ment.

This work was supported by project grant NIH RO1-HL72356–01 from the National Institutes of Health (USA). We areindebted to Therese Nestor and Gilbert Angco for their excellenttechnical support.

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Shotgun proteomic analysis of human-induced sputum