Comprehensive Analysis of Proteins Secreted by Trichophyton rubrum and Trichophyton violaceum under in Vitro Conditions Karin Giddey,† Michel Monod,† Jachen Barblan,‡ Alexandra Potts,‡ Patrice Waridel,‡ Christophe Zaugg,† and Manfredo Quadroni*,‡ Service de Dermatologie et Venereologie, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland, and Protein Analysis Facility, Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland Received March 20, 2007
Dermatophytes cause most superficial mycoses in humans and animals. Their pathogenicity is probably linked with the secretion of proteins degrading keratinised structures. Using 2D-PAGE and a shotgun mass spectrometry approach, we identified 80 proteins from Trichophyton rubrum and Trichophyton violaceum secretomes, under conditions mimicking those in the host. Identified proteins included endoand exoproteases, other hydrolases, and oxidoreductases. Our findings can contribute to a better understanding of the virulence mechanisms of the two species and the different types of infection they cause. Keywords: dermatophyte • secreted proteins • secretome • two-dimensional electrophoresis • tandem mass spectrometry • expressed sequence tags
Introduction Dermatophytes are highly specialized pathogenic fungi which are the most common agents of superficial mycoses.1,2 They infect healthy individuals and are exclusively found in the skin stratum corneum, nails, or hair. Dermatophytoses are widespread and increasing in prevalence on a global scale. Among the approximately 10 human pathogenic species isolated in Europe, Trichophyton rubrum is the most commonly observed.3 This species is not only responsible for the majority of chronic and recurrent nail and cutaneous superficial infections in humans,3,4 but can also cause deep dermal invasion in immunocompromised patients.5,6 Trichophyton violaceum, which is mainly responsible for infection of the scalp in North African, Middle East, and Mediterranean countries, is closely related to T. rubrum.7 In a medium containing proteins as a sole nitrogen and carbon source, dermatophytes secrete a large number of proteins, especially proteases capable of degrading the substrate into compounds which can be assimilated by the fungus.8-11 Similarly, to degrade host keratinised structures during the infectious process, dermatophytes are believed to secrete a repertoire of enzymes which can therefore be considered as virulence attributes of these fungi. In addition, some of these secreted proteins may be allergenic12-14 and/or be responsible for the selective affinity that dermatophytes tend to have for a specific host and site of infection.15 For these reasons, a comprehensive understanding of dermatophyte * Corresponding author. Phone, +41 21 692 39 47/49; fax, +41 21 692 39 55; e-mail,
[email protected]. † Centre Hospitalier Universitaire Vaudois. ‡ University of Lausanne. 10.1021/pr070153m CCC: $37.00
2007 American Chemical Society
pathogenicity requires the global analysis of proteins secreted by these fungi during growth under adequate in vitro conditions. Up to now, most studies of proteins secreted by fungi have focused on the identification and characterization of single proteins with industrial importance (e.g., amylases, cellulases, proteases),16 and only a few investigations concern a global analysis of fungal extracellular proteomes.17-22 Though some studies on the secreted proteins have been carried out in different clinically relevant fungi, for example Aspergillus and Candida spp.,23-25 to our knowledge, only the identification and characterization of single secreted proteins has been performed in dermatophytes.8,9,15 This can be partially explained by the fact that, in contrast to molds and yeasts, it is very difficult to obtain large amounts of native proteins secreted by dermatophytes. At the same time, the lack of available dermatophyte genome sequence data has made secretome analysis problematic in these fungi. The finding of an adequate culture medium,8,9,11,15 advances in proteomics technology, and the availability of homologous genomic sequence data from other related fungal species make the global identification of secreted proteins in dermatophytes now possible. In the present study, we investigated the major secreted proteins from T. rubrum and T. violaceum under in vitro conditions which promote protein secretion and to some extent mimic in vivo growth parameters. The identification and characterization of novel proteins secreted by dermatophytes could allow a better understanding of the complex interactions existing between these fungi, the host, and their environment during the infection process. Journal of Proteome Research 2007, 6, 3081-3092
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research articles Materials and Methods Strains and Culture Conditions. Two isolates of T. rubrum (LAU250 and LAU1738) derived from patients with nail infection and one of T. violaceum (LAU 819) derived from a patient with scalp infection were isolated at the University Hospital of Lausanne (Switzerland). All strains were given preliminary or, where possible, definitive identification on the basis of macroscopic appearance and the microscopic characteristics of the cultures. Species determination was subsequently confirmed by sequencing of the 28S ribosomal DNA.26 The fungi were initially grown on Sabouraud agar (Bio-Rad) at 30 °C for 14 days. To promote production of proteases, a plug of freshly growing mycelium from Sabouraud agar was poured into 100 mL of 0.2% (w/v) soy protein medium (Supro 1771, Protein Technologies International). For the preparation of the medium, soy protein powder was dissolved in water and sterilized for 15 min at 120 °C.8 Cultures were incubated for 16 days at 30 °C without shaking. At this time, substantial serine, metalloprotease, aminopeptidase, and dipeptidylpeptidase activities were measured.8,9,11 Precipitation and Separation of Proteins by 1D- SDS-PAGE. The mycelium was separated from culture medium by paper filtration. The supernatant was centrifuged for 10 min at 5000g to remove debris. Secreted proteins in 10 mL of filtrate were precipitated on ice for 10 min with 5% trichloroacetic acid. After 10 min centrifugation at 4 °C and 8000 rpm, the protein pellet was washed two times with glacial acetone, centrifuged, and air-dried. For 1D-SDS-PAGE analysis, the pellet was dissolved in 20 µL of 20 mM Tris-HCl, pH 7.4, and mixed with SDS sample buffer. Proteins were separated on a 4-12% polyacrylamide gradient gel (NuPAGE Novex Pre-cast Gels, Invitrogen) followed by staining with Coomassie brilliant blue R-250 (Bio-Rad). The total optical density in every lane was determined by densitometry and used to calibrate sample loadings onto a preparative gel. For protein digestion, (shotgun experiments) equal amounts of proteins for every sample were subjected to limited electrophoretic separation on a 10% minigel, that is, the migration was stopped after the front had moved by about 2.5 cm into the separating gel. At this time, all bands up to 250 kDa of a prestained molecular weight marker had moved into the gel and were distinguishable. Gels were fixed for 10 min, partially stained with Coomassie Brilliant blue G (15 min), and then destained for 30 min. Every lane was cut into 9 sections starting from the high molecular weights. 2D-PAGE. Precipitated protein pellets were resuspended in 2D-PAGE lysis buffer consisting of 5 mM magnesium acetate, 7 M urea, 2 M thiourea, 4% (w/v) CHAPS, and 30 mM Tris, pH 8. After sonication and centrifugation, the supernatants were diluted with an equal volume of the same buffer supplemented with 2 mg/mL DTT and 2% (v/v) Pharmalyte 3-10 (Amersham Biosciences). Immobiline DryStrip gels pH 3-10 NL, 11 cm (Amersham Biosciences) were rehydrated according to instructions from the manufacturer prior to first-dimension separation with cuploading sample application. Isoelectric focusing was carried out on an Ettan IPGphor electrophoresis system with a total focusing of 30 000 Vh. Prior to the second-dimension, strips were equilibrated for 10 min in a reducing buffer containing 6 M urea, 2% (w/v) SDS, 30%(v/v) glycerol, 32 mM DTT, and 100 mM Tris, pH 8. This was followed by a 10 min alkylation in a 3082
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buffer containing 6 M urea, 2% (w/v) SDS, 30% (v/v) glycerol, 240 mM iodoacetamide, and 100 mM Tris, pH 8. Seconddimension separation was carried out on precast 8-16%, 13 × 9 cm Criterion gels (Bio-Rad) followed by protein detection by Coomassie blue staining and image acquisition on a visible light densitometer. 2D-Gel Image Analysis. Spots were detected and matched with PDQuest 4.0 software (Bio-Rad). The clustering of spots in Figure 2 takes into account MS identification results. Integrated volumes of spots found to belong to a cluster likely representing the same protein were added to give the relative volumes reported in Table 1. Digestion and Mass Spectrometry (MS) Analysis: 2D GelsMS Experiments. Gel spots were excised from the SDS-PAGE and transferred to 96-well plates (Genomic Solutions). In-gel proteolytic cleavage with sequencing-grade trypsin (Promega, Madison, WI) was performed automatically in the robotic workstation Investigator ProGest (Genomic Solutions) according to a described protocol.27,28 Half of all digests were evaporated to dryness and resuspended in 3 µL of R-cyano-hydroxycinnamic acid matrix (5 mg/ mL in 60% (v/v) acetonitrile/water), of which 0.7 µL was deposited on a target plate. MALDI-MS-MS analysis was performed on a 4700 Proteomics Analyzer (Applied Biosystems, Framingham, MA). After MALDI-TOF MS analysis, internal calibration on trypsin autolysis peaks, and subtraction of matrix peaks, the 10 most intense signals were selected for MS/MS analysis. Whenever identification by MALDI-MS alone was not satisfactory (MASCOT score lower than 80), the other half of the digest was concentrated and used for LC-MS/MS analysis, which was carried out as described below for the shotgun experiment, only with a shorter gradient time (50 min). For de novo sequencing of spots from clusters 4/5 LC-MS/ MS analysis was carried out on a hybrid linear trap LTQOrbitrap mass spectrometer (Thermo Fisher Scientific, Bremen, Germany). The MS instrument was interfaced via a TriVersa Nanomate (Advion Biosciences, Norwich, U.K.) to an Agilent 1100 nano HPLC system (Agilent Technologies, Waldbronn, Germany) equipped with a ZORBAX 300SB C18 (300 µm i.d. × 5 mm, 5 µm) trapping column and a ZORBAX 300SB C18 (75 µm i.d. × 150 mm, 3.5 µm) capillary column (Agilent Technologies). Peptides were separated on the capillary column along a 25 min gradient from 5 to 85% acetonitrile in 0.1% formic acid. The four most intense precursor ions detected in the full MS survey performed in the Orbitrap (range 350-1500 m/z, resolution 60 000 at m/z 400, charge state +2 and higher) were selected and fragmented. Fragment ions were analyzed in the Orbitrap at a resolution of 7500. Digestion and MS Analysis: Shotgun MS Experiments. Proteins in 1D gel slices were manually digested with trypsin according to a described protocol.27,28 Tryptic peptides were recovered in the supernatant of the digestion, concentrated by evaporation to 30 µL, and analyzed by liquid chromatographytandem mass spectrometry (LC-MS/MS) on a SCIEX QSTAR Pulsar i (Concord, Ontario, Canada) hybrid quadrupole-timeof-flight instrument equipped with a nanoelectrospray source and interfaced to an LC-Packings Ultimate (Amsterdam, Holland) HPLC system. Separation was performed on a PepMap (LC-Packings, Amsterdam) reversed-phase capillary C18 (75 µm i.d. × 15 cm, 300 Å, 3 µm) column at a flow rate of 200 nL/min along a 90-min gradient of acetonitrile (0-40%). The SCIEX Analyst instrument controlling software was used to select the two most intense ions in the mass range 400-1200 with charge
research articles
Analysis of Proteins Secreted by T. rubrum and T. violaceum
state +2 to +4 for MS/MS fragmentation after a 1-s survey scan. Every sample was analyzed twice, once with a method that maximizes sensitivity (2 precursor ions fragmented per cycle, every one repeated 4 times) and a second time with a method able to sample a larger number of precursors (3 precursors accumulated once for 1, 2, and 3 s, respectively). CID Data Generation from LC-MS/MS Data. Collections of tandem mass spectra for database searching were generated from Analyst raw data files with the script Mascot.dll version 21b4 (Matrix Science, London, U.K.). The script was set to try to determine precursor charge state from the survey scan, after centroiding peaks at 50% height and merging data points within a distance of 0.1 amu. Charge state information thus determined was used whenever available, while all the default charge states +2, +3, and +4 were written when charge state could not be auto-determined. CID spectra from the same precursor were added and averaged to yield one spectrum if they fell within a mass window of 1.0 amu and a time window of 10 measurement cycles (maximum of 2.5 min). Spectra containing less than 10 peaks before treatment were discarded. Accepted CID spectra were processed as follows: peaks below 0.5% of the base peak were removed; remaining peaks were not smoothed but were centroided at 50% height with a merge distance of 2.0 amu. Collections of spectra were written as flat text files in Mascot Generic Format (.mgf). From Thermo Excalibur raw files (Orbitrap), MS/MS spectra were exported as .dta (text format) files using BioWorks 3.2 software (Thermo Fisher Scientific) with the following settings: peptide mass range, 500-3500; minimum total ion intensity threshold, 10 000; minimum number of fragment ions, 1; minimum signal-to-noise needed for a peak to be written, 2. Dta files were then merged by a Perl script into a Mascot Generic File (.mgf) for Mascot search and de novo sequencing. T. rubrum Amino Acid Sequence Database Construction. The database used for searching with MS data was based on the TrED database.29 The 9280 EST-derived amino acid sequences were downloaded from the public TrED repository (http://www.mgc.ac.cn/TrED/downloads.html) and supplemented with the 65 T. rubrum protein sequences present in release 10.5 (May 15, 2007) of the Uniprot database. The TrED database includes a certain number of sequences derived from an EST collection deposed in Genbank (2006) by some of the authors of this manuscript. This EST database was generated in culture conditions identical to the ones used to produce proteins in this study (C. Zaugg, personal communication). The completed (TrED plus Uniprot) database used in this study contained 9345 amino acid sequences, all validated by MASCOT during the indexing process, and was used for all searches. Database Searching with MS Data. All MS/MS samples were analyzed using Mascot (Matrix Science, London, U.K.; version 2.1.0). Mascot was set up to search the composite T. rubrum protein sequence database described above, assuming the digestion enzyme trypsin. Searches yielding no identifications were repeated with the same input data in the Uniprot database (Swiss-Prot + TrEMBL, www.expasy.org) without taxonomic restriction. For QSTAR data, searches were carried out with a fragment ion mass tolerance of 0.6 Da and a parent ion tolerance of 0.6 Da, whereas, for LTQ-Orbitrap data, a fragment ion mass tolerance of 0.02 Da and a parent ion tolerance of 10 ppm were selected. The iodoacetamide derivative of cysteine
was specified as a fixed modification, and oxidation of methionine as a variable modification. Criteria for Protein Identification. 1. Shotgun Experiment. The software Scaffold (version Scaffold-01_05_06, Proteome Software, Inc., Portland, OR) was used to validate MS/MS-based peptide and protein identifications. Peptide identifications were accepted if they could be established at greater than 85.0% probability as specified by the embedded Peptide Prophet algorithm.30 Protein identifications were accepted if they could be established at greater than 95.0% probability and contained at least 2 identified peptides. Protein probabilities were assigned by the Protein Prophet algorithm.31 Proteins that contained similar peptides and could not be differentiated based on MS/MS analysis alone were grouped to satisfy the principles of parsimony. Of all the proteins identified and validated by Scaffold, those with less than 4 unique peptides were manually examined. Eight of them were discarded on the basis of criteria described below. 2. Identification from 2D Gel Spots. Generally, identifications with a minimum of two peptides with a score above the Mascot threshold (90% confidence of identification) were considered. All hits were further validated by manual examination of the peptide rms mass error (
