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Apoptosis of Candida albicans during the interaction with murine macrophages: Proteomics and cell death marker monitoring. Virginia Cabezón, Vital Vialás, Ana Gil-Bona, Jose Antonio Reales-Calderón, Montserrat MartínezGomariz, Dolores Gutiérrez-Blázquez, Lucía Monteoliva, Gloria Molero, Mark Ramsdale, and Concha Gil J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.5b00913 • Publication Date (Web): 06 Apr 2016 Downloaded from http://pubs.acs.org on April 11, 2016

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Journal of Proteome Research is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

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Journal of Proteome Research

Apoptosis of Candida albicans during the interaction with murine macrophages: Proteomics and cell death marker monitoring Virginia Cabezón,†, ‡ Vital Vialás,†,§, ‡ Ana Gil-Bona,†,§,‡ Jose A. Reales-Calderón,†,§ Montserrat Martínez-Gomariz,⊥ Dolores Gutiérrez-Blázquez,⊥ Lucía Monteoliva,†,§ Gloria Molero,†,§,* Mark Ramsdale∥ and Concha Gil†,§,‡,*. †

Departamento de Microbiología II, Facultad de Farmacia, Universidad Complutense de Madrid,

Plaza de Ramón y Cajal s/n, 28040 Madrid, Spain. §

Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Ctra. de Colmenar Viejo, 28034

Madrid, Spain. Unidad de Proteómica, Universidad Complutense de Madrid-Parque Científico de Madrid

⊥

(UCM-PCM), Spain. ∥

Biosciences, University of Exeter, Geoffrey Pope Building, Exeter, Devon, EX4 4QD, United

Kingdom. ‡

These authors contributed equally.

KEYWORDS: Candida albicans, Macrophages, iTRAQ, 2D-DIGE, Apoptosis, Metabolism, Metacaspase, DNA fragmentation.

ACS Paragon Plus Environment

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ABSTRACT Macrophages may induce fungal apoptosis to fight against C. albicans, as previously hypothesized by our group. To confirm this hypothesis, proteins from C. albicans cells after 3h of interaction with macrophages were analyzed using two quantitative proteomic approaches. Fifty-one and 97 proteins were identified as differentially expressed by DIGE and iTRAQ, respectively. The proteins identified and quantified were different, with only 7 in common, but classified in the same functional categories. The analyses of their functions indicated that an increase in the metabolism of amino acids, and purine nucleotides were taking place, while the glycolysis and translation levels dropped after 3h of interaction. Also, the response to oxidative stress and protein translation were reduced. In addition, 7 substrates of metacaspase (Mca1) were identified (Cdc48, Fba1, Gpm1, Pmm1, Rct1, Ssb1, Tal1) as decreased in abundance, plus 12 proteins previously described as related to apoptosis. Besides, the monitoring of apoptotic markers along 24 h of interaction: caspase-like activity, TUNEL assay, measurement of ROS and cell examination by transmission electron microscopy, revealed that apoptotic processes took place for 30% of the fungal cells, thus supporting the proteomic results and the hypothesis of macrophages killing C. albicans by apoptosis. 1. INTRODUCTION Candida albicans is a commensal dimorphic yeast being an assiduous component of the human microbiota, colonizing mucosal surfaces, in up to 50% of the population1. C. albicans does not normally cause disease in immunocompetent hosts; however, as opportunistic pathogen it is capable of creating challenging systemic infections in immunocompromised persons such as cancer and HIV patients, as well as patients in post-operative intensive-care units due to the


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limited antifungal arsenal. Moreover, a lack of efficient diagnostic procedures exacerbates the problem. Understandably, extensive time and effort have been invested in studying the interactions between C. albicans and the host2-5. The innate mammalian immune system plays a key role in fighting Candida infections. Phagocytic cells, such as macrophages and neutrophils, are the primary line of defense against microbial infections and are critical to preventing invasive candidiasis6. Macrophages are phagocytic cells that play an essential role in the primary response to pathogens, in the maintenance of tissue homeostasis, in the promotion and resolution of inflammation and in tissue repair processes7. Their relevance for C. albicans infections is widely studied because they are capable of engulfing the yeast and eliminating them and, where required, triggering the recruitment and activation of other immune cells8. Studies of the interaction between Candida and macrophages could provide insights into putative new virulence factors that may aid the development of new treatments9-12. Furthermore, the study of the macrophage response to the yeast may further help to understand the mechanisms of action by which the body can develop an immune response to Candida infections13-16. C. albicans may undergo programmed cell death (PCD) when subjected to different types of stress, such as antifungal agents, antimicrobial peptides and some previously described compounds and in hostile conditions (Reviewed in 17, 18). It is also important during biofilm formation and when cell density is high and nutrients are insufficient19. PCD in C. albicans is associated with chromatin condensation, DNA fragmentation and phosphatidylserine externalization, and the cysteine-protease Mca1 has been shown to be very important during farnesol and H2O2-PCD in C. albicans19.


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Previous in vitro studies on Candida – macrophage interactions described apoptotic pathways that occurred when the yeast interacted with macrophages10. The purpose of the current work is to acquire a deeper understanding of processes linked to C. albicans response to the mammalian host during the infection and, more specific, changes related to PCD. A murine macrophage cell line RAW 264.7 and the wild-type C. albicans strain SC5314 were used in this research to study the host-pathogen interaction by two quantitative proteomics-based approaches: (i) 2D-differential in gel electrophoresis (2D-DIGE) and (ii) isobaric tags for relative and absolute quantitation (iTRAQ). Both methods allowed the identification of multiple proteins that showed changes in abundance during the interaction, with the current study focusing on proteins related to apoptosis. Both pro- and anti-apoptotic protein changes were detected. Further, the proteomics results were validated by tracking several apoptotic markers in microscopy-based experiments and performing a parallel transmission electron microscopy (TEM) examination of the C. albicans cells along the process. 2. MATERIALS AND METHODS 2.1. Strains, cell line and culture conditions The clinical isolate of C. albicans SC5314 20 was grown on solid YED medium (1% D-glucose, 1% Difco yeast extract and 2% agar) and incubated at 30 ºC for at least 2 d prior to use. For macrophage-Candida interaction experiments, C. albicans was resuspended in RPMI 1640 medium supplemented with 10% heat-inactivated fetal bovine serum (Invitrogen). The RAW 264.7 gamma NO (-) murine macrophage cell line was obtained from the American Type Culture Collection (Rockville, Md) and maintained in complete culture medium (RPMI 1640 medium containing 10% heat-inactivated fetal bovine-serum, 2 mM L-glutamine, 100


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units/ml penicillin and 100 µg/ml streptomycin, Invitrogen) at 37 ºC in a humidified atmosphere with 5% CO2. Cells were split after reaching the confluent state, usually every 2-3 days and plated at the desired density 18-24 hours prior to the start of experiments. 2.2 Preparation of samples for proteome analysis C. albicans protein samples were obtained as previously described by Fernandez-Arenas, with some modifications10. Briefly, C. albicans control and C. albicans interacting with RAW 264.7 macrophages at a ratio 1:1 were grown in complete RPMI 1640 medium. After 3 h of interaction, control and interacting yeasts were washed 3 times with ice-cold PBS and then scraped and collected by centrifugation at 1000 g. Then, yeasts were washed 5 times with cold water to eliminate macrophage debris. Cells pellet were resuspended in lysis buffer (30 mM Tris-HCl pH 8.5, 7M urea, 2M thiourea, 4% CHAPS, 1% protease inhibitor cocktail (Roche) and 0.5% PMSF). Subsequently, an equal volume of 0.4-0.6 mm diameter glass beads was added and cells were disrupted in a FastPrep cell breaker. Lysed cells were centrifuged at 3000 g for 10 min and the soluble cytoplasmic fraction was collected and stored at - 80ºC. Samples used for 2D-DIGE analysis were washed with 2D Clean-Up (Amersham Biosciences) and resuspended in 30mM Tris-HCl, 7 M urea, 2 M thiourea, 4 % CHAPS. Protein concentration was determined using the Bradford assay (Bio-Rad). Five biological replicates were obtained. 2.3. Two-dimensional differential in-gel electrophoresis (2D-DIGE) 2.3.1 Experimental design To eliminate any dye-specific labelling artefacts, half of the samples of each condition were labeled with Cy3 dye, and the other half were labeled with Cy5 dye. The pooled sample internal


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standard was always Cy2-labeled. In every case, 400 pmol of dye was used for 50 µg of protein. Labelling was performed for 30 min on ice in darkness, and the reaction was quenched with 1 µl of 10 mM L-lysine for 10 min under the same conditions. The control and interaction samples from the 5 biological replicates were distributed in 5 DIGE gels, one control sample and one interaction sample per gel randomly distributed, plus the internal standard. For each gel, the 3 samples combined according to the experimental design and an equal volume of 2 × rehydration buffer (7M urea, 2M thiourea, 4% (w/v) CHAPS, 100 mM DeStreak and 2% IPGphor buffer, pH 3-11) were added for the cup loading. The IPG strips (18 cm, pH 3–10 NL) were rehydrated overnight with rehydration buffer as above but with 2% ampholytes, 0.002% bromophenol blue, and 97 mM DeStreak reagent. The labelled samples were then applied to the strips. Isoelectrofocusing (IEF) was performed at 15 °C using the following program: 120 V for 1 h, 500 V for 1 h, 500–2000 V (gradient) for 1 h, 8000 V for 6.5 h. After IEF, the strips were equilibrated for 15 min in equilibration buffer (0.1 M Tris-HCl pH 6.8, 6 M urea, 30% v/v glycerol, and 2% w/v SDS, 0.5% w/v dithioerythritol) and then for 5 min in alkylating solution (100 mM Tris-HCl (pH 6.8), 6 M urea, 30% (v/v) glycerol, 2% (w/v) SDS, and 2.5% (w/v) iodoacetamide and 0.002% bromophenol blue). The equilibrated strips were transferred onto 12% homogenous polyacrylamide gels cast in low fluorescence glass plates using an EttanDALT six system. Electrophoresis was performed at 15 °C at 2 w/gel for 30 min and then 20 w/gel for 4 h. 2.3.2 Image visualization and DIGE data analysis After electrophoresis, the differentially labelled co-resolved proteins within each gel were imaged using a Typhoon 9400 laser scanner (GE Healthcare). For the Cy3, Cy5 and Cy2 image acquisition, the 532-nm/580-nm, 633-nm/670-nm and 488-nm/520-nm excitation/emission


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wavelengths were used, adjusting the pixel size resolution to 100 microns. Fifteen image gels were obtained, 5 from internal standard labeled with Cy2, 5 from samples labeled with Cy3 and 5 from samples labeled with Cy5. The gel images obtained were cropped in the ImageQuant v5.1 software (GE Healthcare). For spot detection, determination of quantity, inter-gel matching and statistics gel images were analyzed using DeCyder v6.5 software (GE Healthcare). The differential in-gel analysis (DIA) module was used to assign spot boundaries and to calculate parameters such as normalized spot volumes. The inter gel variability was corrected by matching and normalizing it with the internal standard spot maps in the biological variation analysis (BVA) module. Control versus Candida after interaction comparison was carried out. Statistical significance was assessed for each change in abundance between control and interaction conditions using Student’s t-test. Those protein spots present in 4 of 5 gels (i.e., 12 of the 15 analyzed images) exhibiting changes in abundance with + or -1.2-fold in the average ratio, and pvalues under 0.05, were considered as differentially expressed with statistical significance in the comparison between control and interacting cells21. 2.3.3 Protein identification by MALDI-TOF MS After fluorescence scanning, the total protein profile was detected by staining the DIGE gels with Colloidal Coomassie Blue (CCB). The changes observed by 2D-DIGE analysis were aligned with CCB profiling and the spots of interest were manually excised from the gels and transferred to microcentrifuge tubes. Samples selected for analysis were in-gel reduced, alkylated, and digested with trypsin according to Sechi and Chait22. After digestion, the supernatant was collected, and 1 µl was spotted onto a MALDI target plate and allowed to air dry at room temperature. Subsequently 0.5 µl of a 3 mg/ml solution of α-cyano-4-hydroxy-trans-


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cinnamic acid matrix in 0.1% trifluoroacetic acid and 50% acetonitrile was added to the dried peptide digest spots and again allowed to air dry. MS analyses were performed in a MALDI-TOF/TOF mass spectrometer 4700 Plus Proteomics Analyzer (Applied Biosystems, Framingham, MA). MALDI-TOF spectra were acquired in reflector positive ion mode using 1000 laser shots per spectrum. 4000 Series Explorer v 3.4 and Data Explorer version 4.2 (Applied Biosystems) were used for spectra analyses and generating peak picking lists. All mass spectra were internally calibrated using autoproteolytic trypsin fragments. TOF/TOF fragmentation spectra were acquired by selecting up to 10 most abundant ions of each MALDI-TOF peptide mass map (excluding trypsin autolytic peptides and other known background ions) and averaging 2000 laser shots per fragmentation spectrum. The parameters used to analyze the data were a signal to noise threshold of 12, a minimum area of 100 and a resolution higher than 10,000 with a mass accuracy of 50 ppm. Protein identification was done at the Proteomics Facility of Universidad Complutense de Madrid-Parque Científico de Madrid, Spain (UCM-PCM), a member of the ProteoRed Network. For protein identification, both MS and MS/MS spectra were automatically searched using a Local license of Mascot 1.9 from Matrix Science through the Protein Global Server (GPS) v 3.4 from Applied Biosystems. The search parameters for peptide mass fingerprints and tandem MS spectra obtained were set as follows: two sequence databases were used separately, SwissProt/TrEMBL non-redundant protein database (www.uniprot.org) as well as CandidaDB (genolist.Pasteur. fr/CandidaDB)23 with 6165 sequences and 2952183 residues was used for searching. Fixed and variable modifications were considered (Cys as S-carbamidomethyl derivative and Met as oxidized methionine), allowing for one missed cleavage site; precursor


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tolerance was 50-100 ppm and MS/MS fragment tolerance was 0.3 Da. In PMF or combined searches, proteins were considered identified when the MASCOT probability scores were greater than the score fixed as significant with a p value

Proteomics and Cell-Death Marker Monitoring - ACS Publications

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