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Secretome profiling of Cryptococcus neoformans reveals regulation of a subset of virulence-associated… Geddes, Jennifer M H; Croll, Daniel; Caza, Mélissa; Stoynov, Nikolay; Foster, Leonard J; Kronstad, James W Oct 9, 2015

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RESEARCH ARTICLE Open AccessSecretome profiling of Cryptococcusneoformans reveals regulation of a subsetof virulence-associated proteins andpotential biomarkers by protein kinase AJennifer M. H. Geddes1,2, Daniel Croll1, Mélissa Caza1, Nikolay Stoynov3, Leonard J. Foster3and James W. Kronstad1,2*AbstractBackground: The pathogenic yeast Cryptococcus neoformans causes life-threatening meningoencephalitis in individualssuffering from HIV/AIDS. The cyclic-AMP/protein kinase A (PKA) signal transduction pathway regulates the production ofextracellular virulence factors in C. neoformans, but the influence of the pathway on the secretome has not beeninvestigated. In this study, we performed quantitative proteomics using galactose-inducible and glucose-repressibleexpression of the PKA1 gene encoding the catalytic subunit of PKA to identify regulated proteins in the secretome.Methods: The proteins in the supernatants of cultures of C. neoformans were precipitated and identified using liquidchromatography-coupled tandem mass spectrometry. We also employed multiple reaction monitoring in a targetedapproach to identify fungal proteins in samples from macrophages after phagocytosis of C. neoformans cells, as well asfrom the blood and bronchoalveolar fluid of infected mice.Results: We identified 61 secreted proteins and found that changes in PKA1 expression influenced the extracellularabundance of five proteins, including the Cig1 and Aph1 proteins with known roles in virulence. We also observed achange in the secretome profile upon induction of Pka1 from proteins primarily involved in catabolic and metabolicprocesses to an expanded set that included proteins for translational regulation and the response to stress. We furthercharacterized the secretome data using enrichment analysis and by predicting conventional versus non-conventionalsecretion. Targeted proteomics of the Pka1-regulated proteins allowed us to identify the secreted proteins in lysates ofphagocytic cells containing C. neoformans, and in samples from infected mice. This analysis also revealed thatmodulation of PKA1 expression influences the intracellular survival of cryptococcal cells upon phagocytosis.Conclusions: Overall, we found that the cAMP/PKA pathway regulates specific components of the secretomeincluding proteins that affect the virulence of C. neoformans. The detection of secreted cryptococcal proteinsfrom infected phagocytic cells and tissue samples suggests their potential utility as biomarkers of infection.The proteomics data are available via ProteomeXchange with identifiers PXD002731 and PASS00736.Keywords: Quantitative proteomics, Fungal pathogenesis, Secretome, PKA, Virulence factors, Biomarkers,Multiple reaction monitoring* Correspondence: kronstad@msl.ubc.ca1Michael Smith Laboratories, University of British Columbia, Vancouver, BCV6T 1Z4, Canada2Department of Microbiology and Immunology, University of BritishColumbia, Vancouver, BC V6T 1Z4, CanadaFull list of author information is available at the end of the article© 2015 Geddes et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Geddes et al. BMC Microbiology  (2015) 15:206 DOI 10.1186/s12866-015-0532-3BackgroundCryptococcus neoformans is an opportunistic, yeast-likefungus that is a significant threat to immunocompromisedindividuals such as patients with HIV/AIDS [1, 2]. Theability of C. neoformans to cause disease depends on theproduction of virulence factors including a polysaccharidecapsule, melanin deposition in the cell wall, the ability togrow at 37 °C, and the secretion of extracellular enzymes[3–8]. Extracellular enzymes with roles in virulence in-clude phospholipases, which hydrolyze ester bonds andaid in the degradation and destabilization of host cellmembranes and cell lysis, and urease, which hydrolyzesurea to ammonia and carbamate, inducing a localized in-crease in pH [9–12]. Proteinases may also cause tissuedamage, provide nutrients to the pathogen and facilitatemigration to the central nervous system [13–15]. In gen-eral, the secretion of extracellular enzymes is importantfor fungal survival within the host but a comprehensiveinvestigation of the secretome and its regulation by thecyclic-AMP/Protein Kinase A (PKA) signal transductionpathway has not been performed for C. neoformans.The cAMP/PKA pathway regulates capsule produc-tion, melanin formation, mating, and virulence in C. neo-formans [16–20]. Components of the pathway include aGα protein (Gpa1), adenylyl cyclase (Cac1), adenylylcyclase-associated protein (Aca1), a candidate receptor(Gpr4), phosphodiesterases (Pde1 and Pde2), and thePKA catalytic (Pka1, Pka2) and regulatory (Pkr1) sub-units. In response to environmental signals, includingexogenous methionine and nutrient starvation, the G-protein coupled receptor (GPCR), Gpr4 undergoes aconformational change to activate Cacl and subsequentlystimulate the production of cAMP. Mutations in genesencoding the Gpa1, Cac1, Aca1, and Pka1 proteins resultin reduced formation of capsule and melanin, as well assterility and attenuated virulence in a mouse model ofcryptococcosis [16, 21]. In particular, Pka1 is a key regu-lator of virulence in C. neoformans. In contrast, disrup-tion of the gene encoding Pkr1 results in enlargement ofthe capsule and hypervirulence [17].Previous transcriptional profiling experiments com-pared a wild-type strain with pka1Δ and pkr1Δ mutantsof C. neoformans, and identified differences in transcriptlevels for genes related to cell wall synthesis, transport(e.g., iron uptake), the tricarboxylic acid cycle, and gly-colysis [22]. Differential expression patterns were alsoobserved for genes encoding ribosomal proteins, stressand chaperone functions, secretory pathway componentsand phospholipid biosynthetic enzymes. Specifically, lossof PKA1 influenced the expression of genes involved insecretion, and Pka1 was hypothesized to influence cap-sule formation by regulating expression of secretorypathway components that control the export of capsularpolysaccharide to the cell surface. Additionally, thesecretion inhibitors brefeldin A, nocodazole, monensin,and NEM reduced capsule size, a phenotype similar tothat observed in a pka1 mutant [22]. In general, themechanisms and components required for the export ofcapsule polysaccharide and other virulence factors in C.neoformans are poorly understood. Beyond the role ofPKA, other studies have examined exocytosis functions(Sec6, Sec14), the secretion of phospholipases, and theinvolvement of extracellular vesicles [23–28]. Addition-ally, O’Meara et al. (2010) recently demonstrated thatPKA influences capsule attachment via phosphorylationof the pH-responsive transcription factor Rim101, a keyregulator of cell wall functions.The role of PKA in secretion in C. neoformans has alsobeen examined with strains carrying galactose-inducibleand glucose-repressible versions of PKA1 and PKR1 con-structed by inserting the GAL7 promoter upstream ofthe genes [29]. Elevated Pka1 activity, stimulated bygrowth of the PGAL7::PKA1 strain in galactose-containingmedia, was found to influence capsule thickness, cellsize, ploidy, and vacuole enlargement [29]. The authorsalso showed that Pka1 activity was required for wild-type levels of melanization and laccase activity, and in-fluenced the correct localization of laccase. The abilityto regulate expression of PKA1 and, subsequently, theactivity of Pka1, is a powerful tool for investigating themechanisms of its influence on the secretion of viru-lence factors and secretory pathway components.In this study, we used the strain with galactose-inducible and glucose-repressible expression of PKA1 toinvestigate the influence of Pka1 on the secretome usingquantitative proteomics. We identified 61 different se-creted proteins and found that Pka1 regulated the extra-cellular abundance of five. These proteins included threeenzymes (α-amylase, acid phosphatase, and glyoxal oxi-dase), the Cig1 protein (cytokine-inducing glycoprotein)associated with virulence and heme uptake, and a novelprotein containing a carbohydrate-binding domain(CNAG_05312). We also observed a change in the secre-tome profile under Pka1-inducing conditions from proteinsinvolved primarily in catabolic and metabolic processes toan expanded set that included proteins for translationalregulation and the response to stress. Enrichment analysisof our Pka1-influenced secretome data compared to thewhole genome showed over-representation of genes associ-ated with a broad spectrum of processes including meta-bolic and catabolic processing. Although no enrichmentwas observed between our secretome data and the FungalSecretome KnowledgeBase (FunSecKB), a comparison ofGO terms between the data sets showed the majority ofour identified proteins to be represented in the FunSecKB.Next, we exploited our secretome data using a targetedproteomics approach to identify potential biomarkers ofcryptococcal infection. Multiple Reaction MonitoringGeddes et al. BMC Microbiology  (2015) 15:206 Page 2 of 26(MRM) in the presence of stable isotope dilutions (SID) al-lows for identification and quantification of specific pep-tides in a sample. Specifically, we were able to identifyPka1-regulated proteins of C. neoformans in host samplesincluding blood, bronchoalveolar lavage fluid, and infectedmacrophage lysates. Overall, our study reveals that thecAMP/PKA pathway regulates specific components of thesecretome including the Cig1 and Aph1 proteins that con-tribute to virulence in C. neoformans.ResultsControl of PKA1 expression results in a change of theprotein secretion profileGiven the virulence defect of a pka1 mutant, we hypoth-esized that Pka1 influences the secretion of proteins as-sociated with the virulence and survival of C.neoformans in the host. To test this idea, we quantita-tively identified proteins secreted by C. neoformans inthe context of regulated expression of PKA1. For ourinitial analysis, we collected supernatant cultures of WTand PGAL7::PKA1 strains grown under Pka1-repressed(glucose) and Pka1-induced (galactose) conditions at 16,48, 72, and 120 h post-inoculation (hpi), and analyzedthe samples using quantitative mass spectrometry. Theanalysis of these supernatant samples resulted in theidentification of 164 (54 quantifiable) and 207 (83 quan-tifiable) proteins under Pka1-repressed and Pka1-induced conditions, respectively (see Additional file 1:Table S1; Additional file 2: Table S2). As shown inTable 1, 23 proteins were identified and quantified underPka1-repressed and Pka1-induced conditions at the spe-cified time-points. We found that none of the changes inprotein abundance between the two conditions were sta-tistically significant (p > 0.05) and therefore, concludedthat Pka1 did not influence the abundance of any of theobserved proteins under the conditions tested. However,upon comparison of the unique proteins identified undereither Pka1-repressed or Pka1-induced conditions, usingGene Ontology (GO) term biological classifications at alltime points, we were able to observe overall changes inthe secretome profiles under the influence of Pka1(Fig. 1). Additional differentially expressed proteins maybe present in the samples, but we were unable to meas-ure their abundance and they were therefore not in-cluded for further analysis. Under Pka1-repressedconditions, the majority of secreted proteins were associ-ated with catabolic and metabolic (33 %), unknown(20 %), and hypothetical (20 %) processes (totaling73 %), with additional proteins associated with transport(8 %), oxidation-reduction processes (4 %), dephosphory-lation (4 %), proteolysis (4 %), glycolysis (4 %), and regu-lation of transcription (3 %). Conversely, a change in thesecretome profile was observed under the Pka1-inductioncondition. Here, we again observed the majority ofproteins to be associated with catabolic and metabolic(26 %), unknown (19 %), and hypothetical (17 %) pro-cesses (totaling 62 %). A slight decline was found for pro-teins associated with transport (from 8 to 6 %), oxidation-reduction processes (from 4 to 3 %), dephosphorylation(from 4 to 2 %), proteolysis (from 4 to 3 %), and regulationof transcription (from 3 to 0 %). However, a greater em-phasis was found for proteins associated with glycolysis(from 4 to 6 %), response to stress (from 0 to 8 %), transla-tion (from 0 to 7 %), and nucleosome assembly (from 0 to3 %). Although, our secretome analysis at specific timesdid not identify Pka1-regulated proteins, a change towardthe secretion of proteins for glycolysis, translational regu-lation, nucleosome assembly, and the response to stresswas observed upon induction of PKA1 expression.Identification of secreted proteins regulated by Pka1Given that we identified secreted proteins from strainswith modulated Pka1 activity, but did not observe anyproteins whose abundance was directly regulated byPka1, we extended our analysis to examine protein se-cretion at an intermediate time point of 96 hpi, and weused an alternative, less stringent method for proteinprecipitation (EtOH/acetate). We chose an end-pointcollection time of 96 hpi based on our coverage of arange of other time points in the previous analysis andbecause this time was sufficient for the culture to reachstationary phase and to accumulate proteins in theextracellular environment. Additionally, because we didnot observe changes in protein abundance under regula-tion of Pka1 following the time-point analysis, we usedthe alternative protein precipitation method in an at-tempt to obtain a more comprehensive view of thesecretome. We collected supernatant cultures of WTand PGAL7::PKA1 strains grown under Pka1-repressed(glucose) and Pka1-induced (galactose) conditions at 96hpi and analyzed the samples using quantitative massspectrometry. Similar trends in protein abundance wereobserved for the majority of proteins in both experimen-tal approaches (EtOH and TCA/acetone precipitation)(see Additional file 3: Table S3) [30]. Although the vari-ability of the time-point analysis was relatively high, thereproducibility observed from the end-point analysissuggested that collecting the samples at different time-points impacted the protein abundance and contributedto the observed variability. This impact may be associ-ated with culture sampling, as well as changes in capsuleproduction during the early- to mid-log growth phasesof the fungal cultures [29]. We identified 61 proteinsunder Pka1-repressed conditions of which 34 were suc-cessfully dimethyl-labeled and quantified (Table 2; seeAdditional file 4: Table S4). These 34 proteins covered abroad spectrum of biological classifications (17 categor-ies) for GO terms, including proteins associated withGeddes et al. BMC Microbiology  (2015) 15:206 Page 3 of 26catabolic and metabolic processes, ubiquitination, trans-port, dephosphorylation, glycolysis, oxidation-reduction,translation, proteolysis, and the response to stress.Under Pka1-induced conditions, we identified 38 proteins,of which 21 were successfully dimethyl-labeled and quan-tified (Table 3; see Additional file 5: Table S5). These 21proteins covered 11 biological classifications for GO termsand included proteins associated with catabolic and meta-bolic processes, along with ubiquitination, transport, de-phosphorylation, oxidation-reduction, proteolysis, and theresponse to stress. In total, 17 proteins were present underboth Pka1-repressed and Pka1-induced conditions. Acomparison of changes in abundance under Pka1-re-pressed and Pka1-induced conditions of these 17 pro-teins revealed that five showed statistically significantdifferences (p-value < 0.05, Student’s t-test) in abun-dance in response to regulation of Pka1 (Fig. 2). Weconcluded that the extracellular abundance of thesefive proteins was influenced by PKA and we focusedour subsequent analysis on these proteins. UnderTable 1 Proteins identified in the secretome of C. neoformans collected at 16, 48, 72, and 120 hpi grown in Pka1-repressed(glucose-containing medium) and Pka1-induced (galactose-containing medium) conditionsGOcategoriesaAccessionnumberProtein Name Fold changeb* Std. Dev.Time point Pka1-repression Pka1-induction Pka1-repression Pka1-inductionCarbohydrate catabolic processCNAG_02189 α-Amylase 16 hpi 0.298 1.096 0.314 1.270GTP catabolic processCNAG_06125 Translation elongation factor 1 α 16 hpi 0.135 0.379 0.145 0.517Carbohydrate metabolic processCNAG_01239 Chitin deacetylase 16 hpi 0.906 1.350 0.310 0.515CNAG_04245 Chitinase 16 hpi 0.448 0.286 0.007 0.29648 hpi 0.826 0.603 1.019 0.017CNAG_06501 1,3-β-glucanosyltransferase 16 hpi 0.573 0.896 0.383 0.169Transmembrane transportCNAG_02974 Voltage-dependent ion-selectivechannel16 hpi 0.223 0.466 0.089 0.645Oxidation-reduction processCNAG_03465 Laccase 16 hpi 0.637 0.870 0.651 1.038Unknown/UnclassifiedCNAG_02030 Glyoxal oxidase 16 hpi 0.278 0.600 0.324 0.67248 hpi 0.242 0.350 0.063 0.144CNAG_06267 Rds1 protein 16 hpi 0.336 0.756 0.303 0.222120 hpi 0.860 5.106 0.444 4.588CNAG_00776 Immunoreactive mannoprotein MP88 16 hpi 0.627 0.994 0.214 1.193CNAG_02864 Predicted protein 16 hpi 0.346 0.259 0.056 0.183CNAG_04753 Lactonohydrolase 16 hpi 1.031 0.751 0.631 0.41348 hpi 1.250 1.055 0.996 0.546HypotheticalCNAG_00587 Hypothetical protein 16 hpi 1.275 1.620 0.018 0.371CNAG_01047 Hypothetical protein 16 hpi 0.279 0.471 0.070 0.27272 hpi 0.928 0.719 1.034 0.432CNAG_03492 Hypothetical protein 16 hpi 0.506 0.799 0.400 0.03072 hpi 0.640 1.180 0.199 0.431CNAG_05893 Hypothetical protein 48 hpi 1.609 1.676 1.380 1.639120 hpi 1.641 1.413 0.953 0.348aProteins were categorized based on GO terms associated with their biological classificationbFold change is reported as the average quantification for PGAL7::PKA1 vs. WT, ± standard deviation*Statistical analysis was performed using a Student’s t-test between the conditions. None of the comparisons resulted in a significant difference in proteinabundance (p-value > 0.05)Geddes et al. BMC Microbiology  (2015) 15:206 Page 4 of 26Pka1-induced conditions, a cytokine-inducing glyco-protein (Cig1), an α-amylase, a glyoxal oxidase, and anovel protein (CNAG_05312) each showed an in-crease in abundance, whereas an acid phosphatase(Aph1) showed a decrease in abundance. Taken to-gether, these findings suggest that Pka1 regulates theextracellular abundance of specific proteins secretedby C. neoformans.Gene ontology analyses of the secretome revealedenrichment of proteins associated with metabolic andcatabolic processesBased on our identification and quantification of 192 pro-teins in the secretome of C. neoformans, we next soughtto classify the corresponding genes according to their GOterms of biological process, cellular component, and mo-lecular function. Our goal was to assess whether subsetsof genes showed significant over-representation relative toall genes in C. neoformans. To perform the enrichmentanalysis, all unique proteins identified under Pka1-repressed conditions were combined into a single data setas were proteins identified under Pka1-induced condi-tions. As shown in Fig. 3, the identified secreted proteinsunder Pka1-repressed conditions were enriched in 15 bio-logical categories, with the most significant enrichmentassociated with carbohydrate metabolic process, catabolicprocess, generation of precursor metabolites and energy,organic substance metabolic process, and primarymetabolic process. Under Pka1-induced conditions, en-richment was only associated with the five most signifi-cantly enriched categories under Pka1-repressedconditions. Classification by cellular components showedthe most significant enrichment associated with the cyto-plasm under both conditions, which may be an artifact ofthe classification process or indicative of the locationof protein synthesis (see Additional file 6: Figure S1),whereas classification by molecular function showedno enrichment.Our gene sets were also compared to all reported se-creted proteins in the Fungal Secretome Knowledge Base(FunSecKB) for C. neoformans strain JEC21 [31, 32]. Theanalysis showed no significant enrichment; however, simi-larities among the identified GO terms were observed(Fig. 4). Forty-seven GO term categories were shared be-tween the FunSecKB and our identified proteins underPka1-repressed and Pka1-induced conditions; the greatestnumber of proteins being associated with metabolic pro-cesses. Twenty-five categories were represented only in oursecretome data, and one category (GO:0009607; responseto biotic stimulus) was represented only in the FunSecKB.Upon comparison of GO term categories for cellular com-ponents, 16 categories were shared between the FunSecKBand our identified proteins under Pka1-repressed andPka1-induced conditions; the greatest number of proteinsbeing associated with the cell, cytoplasm, and intracellularcategories (see Additional file 7: Figure S2). Upon compari-son of GO term categories for molecular function, 17 cat-egories were shared between the FunSecKB and ouridentified proteins under Pka1-repressed and Pka1-inducedconditions; the greatest number of proteins associated withbinding as well as enzyme activity (see Additional file8: Figure S3). Taken together, the enrichment analysis ofour secretome data under modulation of Pka1 activity com-pared to the whole genome showed over-representation ofgenes associated with a broad spectrum of processes in-cluding metabolic and catabolic processing. Although noenrichment was observed between our secretome data andthe FunSecKB, a comparison of GO terms between the datasets showed all but one of our identified proteins to be rep-resented in the FunSecKB.A bioinformatic analysis of the secretome predicts modesof secretionWe next examined the secreted proteins, undermodulation of Pka1 activity, for the presence of pre-dicted signal peptides and GPI anchors. Specifically,we used SignalP 4.1, Signal-3 L, and Phobius for theprediction of protein extracellular location based onthe presence or absence of N-terminal signal peptides.The presence of a signal peptide suggests conven-tional secretion versus potential non-conventional ex-port if a signal peptide is absent. Additionally, weFig. 1 Quantitative proteomic analysis of the C. neoformans secretomeover the course of all time-points (16, 48, 72, and 120 hpi) under (a)Pka1-repressed (glucose) and (b) Pka1-induced (galactose) conditions.Identified proteins were grouped according to GO terms associatedwith their biological classifications. GO term classification wasperformed on unique proteins identified under either Pka1-repressedor Pka1-induced conditions to highlight the overall influence of Pka1regulation on the secretome profileGeddes et al. BMC Microbiology  (2015) 15:206 Page 5 of 26Table 2 Proteins identified in the secretome of C. neoformans collected at 96 hpi from cells grown in Pka1-repressed(glucose-containing medium) conditionsGO categoriesa Accession number Protein name Fold changeb Std. Dev.Carbohydrate catabolic processCNAG_02189 α-Amylase 0.777 0.019GTP catabolic processCNAG_06125 Translation elongation factor 1 α 2.062 2.181Carbohydrate metabolic processCNAG_02860 Endo-1,3(4)-β-glucanase 0.947 0.583CNAG_06501 1,3-β-glucanosyltransferase 0.968 0.100CNAG_05799 Chitin deacetylase 1.439 0.775CNAG_06291 Deacetylase 1.464 0.778CNAG_01239 Chitin deacetylase 2.014 0.584Cellular carbohydrate metabolic processCNAG_03225 Malate dehydrogenase 0.472 0.546Pentose-phosphate pathwayCNAG_07561 Phosphogluconate dehydrogenase >10 >10Protein ubiquitinationCNAG_01920 Polyubiquitin 1.261 0.396ATP hydrolysis coupled proton transportCNAG_05918 F0F1 ATP synthase subunit β 0.451 0.249CNAG_05750 ATPase α subunit 0.604 0.387Transmembrane transportCNAG_06101 Eukaryotic ADP/ATP carrier 7.524 9.753Methionine biosynthetic processCNAG_01890 5-methyltetrahydropteroyltriglutamate-homocysteine S-methyltransferase0.778 0.327DephosphorylationCNAG_02944 Acid phosphatase 1.862 0.083GlycolysisCNAG_03072 Phosphopyruvate hydratase 3.093 3.377Oxidation-reduction processCNAG_01019 Cu/Zn superoxide dismutase 0.302 0.161CNAG_03465 Laccase 0.718 0.668ProteolysisCNAG_00919 Carboxypeptidase D 4.664 5.261Response to stressCNAG_01727 Hsc70-4 1.883 2.094TranslationCNAG_06095 Ribosomal protein L13 0.147 0.057Unknown/UnclassifiedCNAG_01653 Cytokine-inducing glycoprotein 0.134 0.158CNAG_00407 Glyoxal oxidase 0.719 0.230CNAG_04291 Glycosyl-hydrolase 0.583 0.287CNAG_02030 Glyoxal oxidase 0.513 0.109CNAG_06267 Rds1 protein 3.409 0.106Geddes et al. BMC Microbiology  (2015) 15:206 Page 6 of 26used GPI-SOM to predict the presence or absence ofa GPI-anchor on proteins, indicative of plasma mem-brane association, which may or may not be capableof dissociation and subsequent protein secretion. Ofthe 61 proteins used for this analysis, 14 had both anN-terminal signal peptide and a GPI-anchor protein,17 had only an N-terminal signal peptide, one had aGPI-anchor but no N-terminal signal peptide, and 29proteins did not have an N-terminal signal peptide ora GPI-anchor (Table 4). Taken together, these resultssuggest that C. neoformans may employ a non-conventional secretory pathway for regulation of partof its secretome, including potential protein secretionvia vesicle export [24].Examination of transcription and protein abundance inthe context of Pka1 regulationBased on our identification and quantification of five se-creted proteins regulated by Pka1 in C. neoformans, weevaluated whether transcript levels were also influencedby Pka1 regulation and whether there was a correlationwith the observed regulation of protein abundance. Spe-cifically, we performed qRT-PCR on RNA collected at16 and 96 hpi from cells grown in Pka1-repressed andPka1-induced conditions for the WT and PGAL7::PKA1strains, and compared the observed values to our quan-titative proteomic results at 96 hpi. Figure 5 summarizesthe RNA expression levels at 16 hpi and 96 hpi and pro-tein abundance at 96 hpi for Cig1, the acid phosphataseAph1, an α-amylase, a glyoxal oxidase, and a novel pro-tein (CNAG_05312). Cig1 and the novel protein bothshowed down-regulation of their transcripts under Pka1-repressed conditions at 16 and 96 hpi, followed by min-imal or slight up-regulation with induced Pka1 activity.α-Amylase and glyoxal oxidase showed an initial peak intranscript levels at 16 hpi, followed by minimal changeor a decrease in RNA levels at 96 hpi under Pka1-repressed conditions, and the transcript levels decreasedin response to Pka1 induction. Acid phosphatase showedelevated transcript levels upon PKA1 repression at bothtime points, compared to a drop in RNA levels at 16 hpior no change at 96 hpi upon induction of PKA1. In gen-eral, Pka1 appears to positively regulate the transcriptlevels of Cig1 and the novel protein (CNAG_05312), andto negatively regulate the transcript levels of the otherthree proteins. Taken together, our results suggest thatalthough Pka1 activity influences the transcript levelsand extracellular abundance of the five proteins, a cor-relation between transcript and protein levels was not al-ways observed, and this was particularly notable forglyoxal oxidase. The differences may indicate additionallevels of potential influence of Pka1 beyond transcrip-tional regulation, including differences in mRNA versusprotein stability, the timing of expression and the regula-tion of protein export. For example, more detailed stud-ies will be needed to examine the timing of intracellularand extracellular accumulation of the glyoxal oxidaseprotein relative to transcription of the gene.Detection of secreted Pka1-regulated proteins usingMultiple Reaction MonitoringBased on our identification of five Pka1-regulated pro-teins, including two with roles in virulence, we hypothe-sized that these proteins would be secreted duringinfection and that they might be potentially useful bio-markers of cryptococcosis. To test this idea, we usedMultiple Reaction Monitoring (MRM), a powerful andtargeted proteomics approach for the relative quantita-tive measurement of target proteins. In the presence ofan internal standard, a stable isotope-labeled peptide,the amount of natural protein can be measured by com-paring the signals to the labeled species. The isotopicallylabeled, proteotypic peptides terminate with C-terminalheavy arginine or lysine (C-term Arg U-13C6;U-15N4 orLys U-13C6;U-15N2). In principle, the stable isotopes havethe same physiochemical properties as the natural pep-tides and only differ by mass resulting in co-elution ofthe peptides. However, studies have suggested that in theTable 2 Proteins identified in the secretome of C. neoformans collected at 96 hpi from cells grown in Pka1-repressed(glucose-containing medium) conditions (Continued)HypotheticalCNAG_05312 Conserved hypothetical protein 0.341 0.100CNAG_03007 Conserved hypothetical protein 0.518 0.649CNAG_01562 Conserved hypothetical protein 0.942 0.194CNAG_05893 Conserved hypothetical protein 0.991 0.487CNAG_01047 Conserved hypothetical protein 6.714 6.494CNAG_00588 Conserved hypothetical protein >10 >10CNAG_03223 Conserved hypothetical protein >10 >10CNAG_00586 Conserved hypothetical protein >10 >10aProteins were categorized based on GO terms associated with their biological classificationbFold change is reported as the average quantification for PGAL7::PKA1 vs. WT, ± standard deviationGeddes et al. BMC Microbiology  (2015) 15:206 Page 7 of 26presence of complex biological samples, such as bloodor serum, the retention times between the peptides canshift, impacting the co-elution patterns [33]. We specif-ically applied MRM to detect Cig1, Aph1, glyoxal oxi-dase, α-amylase, and the novel protein (CNAG_05312)in samples from a macrophage-like cell line and from in-fected mice.The samples from the J774A.1 macrophage-like cell linecame from cells inoculated with WT and PGAL7::PKA1strains under Pka1-repressed (DMEM medium supple-mented with glucose) and Pka1-induced (DMEM mediumsupplemented with galactose) conditions. Intracellular up-take at 2 hpi showed a significant difference in the numberof colony forming units (CFUs) per macrophage betweenthe WT and PGAL7::PKA1 strains under Pka1-repressedconditions, but not under induced conditions (Fig. 6a).This difference is most likely due to the absence of thecapsule for the Pka1-repressed cells, a phenotype that en-hances phagocytosis. By 24 hpi, rates of intracellular fun-gal cells per macrophage were significantly different forWT and PGAL7::PKA1 strains under both conditions(Fig. 6c). Specifically, intracellular rates of infection at 24Table 3 Proteins identified in the secretome of C. neoformans collected at 96 hpi from cells grown in Pka1-induced(galactose-containing medium) conditionsGO categoriesa Accession number Protein name Fold changeb Std. Dev.Carbohydrate catabolic processCNAG_02189 α-Amylase 1.061 0.080GTP catabolic processCNAG_06125 Translation elongation factor 1 α 0.462 0.555Carbohydrate metabolic processCNAG_04245 Chitinase 0.621 0.562CNAG_06501 1,3-β-glucanosyltransferase 1.101 0.140CNAG_01239 Chitin deacetylase 2.659 1.996CNAG_02860 Endo-1,3(4)-β-glucanase 3.210 1.665Protein ubiquitinationCNAG_01920 Polyubiquitin 0.509 0.501ATP hydrolysis coupled proton transportCNAG_05750 ATPase α subunit 1.785 1.765DephosphorylationCNAG_02944 Acid phosphatase 0.233 0.061Oxidation-reduction processCNAG_01019 Cu/Zn superoxide dismutase 0.350 0.142CNAG_03465 Laccase 1.000 0.107ProteolysisCNAG_00919 Carboxypeptidase D 5.770 3.708Response to stressCNAG_01750 Chaperone >10 >10Unknown/UnclassifiedCNAG_04291 Glycosyl-hydrolase 0.989 0.959CNAG_00407 Glyoxal oxidase 1.209 0.648CNAG_06267 Rds1 protein 2.834 0.518CNAG_01653 Cytokine-inducing glycoprotein 2.951 2.753CNAG_04753 Lactonohydrolase >10 >10HypotheticalCNAG_06109 Conserved hypothetical protein 0.463 0.431CNAG_05893 Conserved hypothetical protein 1.062 0.307CNAG_05312 Conserved hypothetical protein 3.737 2.342aProteins were categorized based on GO terms associated with their biological classificationbFold change is reported as the average quantification for PGAL7::PKA1 vs. WT, ± standard deviationGeddes et al. BMC Microbiology  (2015) 15:206 Page 8 of 26hpi in repressed conditions were 11.49 ± 2.11 % for theWT and 55.67 ± 12.76 % for PGAL7::PKA1 strains. How-ever, intracellular rates under induced conditions were9.06 ± 2.91 % for WT and 1.97 ± 0.82 % for PGAL7::PKA1strains. Importantly, intracellular uptake rates showed nodifferences between WT, PGAL7::PKA1, and the pka1Δstrains under controlled growth conditions (DMEM –high glucose (0.45 %)) at 2 and 24 hpi (Fig. 6b, d). Theseresults indicate that modulation of PKA1 expression influ-ences the intracellular survival of cryptococcal cells.MRM on macrophage lysates infected with fungalcells at 24 hpi identified the Pka1-regulated and se-creted proteins α-amylase and glyoxal oxidase in bothinduced and repressed conditions. Figure 7 showsFig. 2 Quantitative proteomic analysis of the C. neoformans secretome under Pka1-repressed (glucose) and Pka1-induced (galactose) conditions.The secreted proteins were identified and quantified by LC-MS/MS in the PGAL7::PKA1 strain compared to WT, and the log2 of relative fold changesare indicated. Fold change is reported as the average log2 quantification for PGAL7::PKA1 vs. WT, ± standard deviation. Statistical analysis was performedusing a Student’s t-test (p-value< 0.05), between conditionsFig. 3 Enrichment of genes represented in the secretome analysis of cells grown under Pka1-repressed and Pka1-induced conditions comparedto all genes present in the WT strain. The enrichment is based on GO terms associated with biological processesGeddes et al. BMC Microbiology  (2015) 15:206 Page 9 of 26representative chromatographic co-elution patterns ofthe isotopically-labeled and natural peptides, whichallowed for relative quantification of peptides in thereplicates of the experiment. For both enzymes, thehighest amount of protein was detected in the WTstrain in DMEM medium under Pka1-repressed con-ditions, whereas the PGAL7::PKA1 strain under Pka1-induction showed the lowest amount of secreted pro-tein. This observation may be associated with reducedintracellular rates of the PGAL7::PKA1 strain due tothe presence of an enlarged capsule. Overall, we wereable to detect 29.8 ± 37.0 fmol of α-amylase and149.1 ± 130.0 fmol of glyoxal oxidase in 5 μg of totalprotein from the macrophage lysate following the up-take of PGal7::PKA1 under Pka1-induced conditions at24 hpi.The samples from infected mice included BAL andblood from animals inoculated with the WT strain.Three mice were selected for each type of in vivoanalysis based on previous studies of cryptococcosis[34–37]. Representative chromatograms of isotopically-labeled and natural peptides detected in mouse BAL arepresented in Fig. 8. The MRM analysis identified Cig1, α-amylase, glyoxal oxidase, and the novel protein(CNAG_05312) in BAL following infection with WT cells.In 5 μg of total protein, glyoxal oxidase was the mostabundant protein with detection at 779.5 ± 436.1 fmol,followed by the novel protein (CNAG_05312) at 451.0 ±90.5 fmol, Cig1 at 291.3 ± 54.5 fmol, and α-amylase withthe lowest abundance at 40.1 ± 9.4 fmol. Lastly, we wereable to detect Cig1, glyoxal oxidase, and the novel protein(CNAG_05312) in blood. Representative chromatogramsof the isotopically-labeled and natural peptides detected inmouse blood are presented in Fig. 9. Again, glyoxal oxi-dase was the most abundant protein detected at 319.4 ±272.7 fmol, followed by Cig1 at 62.0 ± 17.4 fmol, andFig. 4 Comparison of GO terms classifications of biological processes from the identified secreted proteins from cells grown under Pka1-repressed andPka1-induced conditions compared to proteins represented in the Fungal Secretome KnowledgebaseGeddes et al. BMC Microbiology  (2015) 15:206 Page 10 of 26Table 4 Bioinformatic analysis of identified and quantified proteins in the secretome of C. neoformans under Pka1-repressed andPka1-induced conditionsGOcategoriesaAccessionnumberProtein name Signal peptideb(position)GPI anchorc(position)Sample preparationCarbohydrate catabolic processCNAG_02189 α-Amylase Yes (21/22) Yes (C-26) EtOH, TCA/acetoneGTP catabolic processCNAG_06125 Translation elongation factor 1 α No No EtOH, TCA/acetoneCNAG_06840 Translation elongation factor 2 No No TCA/acetoneCarbohydrate metabolic processCNAG_00799 Cellulase Yes (22/23) No TCA/acetoneCNAG_01239 Chitin deacetylase Yes (18/19) Yes (C-28) EtOH, TCA/acetoneCNAG_02860 Endo-1,3(4)-β-glucanase Yes (22/23) No EtOHCNAG_04245 Chitinase Yes (21/22) No EtOH, TCA/acetoneCNAG_05799 Chitin deacetylase Yes (18/19) Yes (C-28) EtOHCNAG_06291 Deacetylase Yes (19/20) No EtOH, TCA/acetoneCNAG_06313 Phosphoglucomutase No No TCA/acetoneCNAG_06501 1,3-β-glucanosyltransferase Yes (20/21) Yes (C-6) EtOH, TCA/acetoneCellular carbohydrate metabolic processCNAG_03225 Malate dehydrogenase No No EtOH, TCA/acetoneTrehalose metabolic processCNAG_03525 Trehalase Yes (18/19) No TCA/acetoneGlyoxylate metabolic processCNAG_01137 Aconitase No No TCA/acetonePentose-phosphate pathwayCNAG_01984 Transaldolase No No TCA/acetoneCNAG_07561 Phosphogluconate dehydrogenase No No EtOHProtein ubiquitinationCNAG_01920 Polyubiquitin No No EtOHATP hydrolysis coupled proton transportCNAG_05750 ATPase α subunit No No EtOH, TCA/acetoneCNAG_05918 F0F1 ATP synthase subunit β No No EtOHTransmembrane transportCNAG_02974 Voltage-dependent ion-selective channel No No TCA/acetoneCNAG_06101 Eukaryotic ADP/ATP carrier No Yes (C-25) EtOH, TCA/acetoneMethionine biosynthetic processCNAG_01890 5-methyltetrahydropteroyltriglutamate-homocysteine S-methyltransferaseNo No EtOHDephosphorylationCNAG_02944 Acid phosphatase Yes (16/17) No EtOH, TCA/acetoneGlycolysisCNAG_03072 Phosphopyruvate hydratase No No EtOH, TCA/acetoneCNAG_06699 Glyceraldehyde-3-phosphatedehydrogenaseNo No TCA/acetoneOxidation-reduction processCNAG_01019 Cu/Zn superoxide dismutase No No EtOHCNAG_03465 Laccase Yes (20/21) No EtOH, TCA/acetoneGeddes et al. BMC Microbiology  (2015) 15:206 Page 11 of 26Table 4 Bioinformatic analysis of identified and quantified proteins in the secretome of C. neoformans under Pka1-repressed andPka1-induced conditions (Continued)ProteolysisCNAG_00581 Endopeptidase Yes (19/20) No TCA/acetoneCNAG_00919 Carboxypeptidase D Yes (21/22) No EtOH, TCA/acetoneResponse to stressCNAG_00334 Heat shock protein No No TCA/acetoneCNAG_01727 Hsc70-4 No No EtOHCNAG_01750 Chaperone No No EtOH, TCA/acetoneCNAG_06150 Heat-shock protein 90 No No TCA/acetoneTranslationCNAG_04021 60S ribosomal protein L26 No No TCA/acetoneCNAG_04114 40S ribosomal protein S0 No No TCA/acetoneCNAG_06095 Ribosomal protein L13 No No EtOHCNAG_06605 Ribosomal protein S2 No No TCA/acetoneRegulation of transcriptionCNAG_00483 Actin No No TCA/acetoneNucleosome assemblyCNAG_06746 Histone h2b No No TCA/acetoneUnknown/UnclassifiedCNAG_00407 Glyoxal oxidase Yes (16/17) Yes (C-27) EtOH, TCA/acetoneCNAG_00776 Immunoreactive mannoprotein MP88 Yes (22/23) Yes (C-30) TCA/acetoneCNAG_01653 Cytokine-inducing glycoprotein Yes (19/20) No EtOHCNAG_02030 Glyoxal oxidase Yes (21/22) Yes (C-32) EtOH, TCA/acetoneCNAG_02850 Glucan endo-1,3-α-glucosidase agn1 Yes (21/22) Yes (C-26) TCA/acetoneCNAG_02864 Predicted protein Yes (16/17) No TCA/acetoneCNAG_02943 Cytoplasmic protein No No TCA/acetoneCNAG_04291 Glycosyl-hydrolase Yes (17/18) Yes (C-31) EtOHCNAG_04753 Lactonohydrolase No No EtOH, TCA/acetoneCNAG_06267 Rds1 protein Yes (20/21) Yes EtOH, TCA/acetoneHypotheticalCNAG_00586 Conserved hypothetical protein Yes (23/24) No EtOH, TCA/acetoneCNAG_00587 Conserved hypothetical protein Yes (19/20) No TCA/acetoneCNAG_00588 Conserved hypothetical protein Yes (16/17) No EtOHCNAG_01047 Conserved hypothetical protein Yes (19/20) No EtOH, TCA/acetoneCNAG_01562 Conserved hypothetical protein Yes (18/19) No EtOHCNAG_03007 Conserved hypothetical protein No No EtOHCNAG_03223 Conserved hypothetical protein Yes (19/20) Yes (C-18) EtOHCNAG_03492 Conserved hypothetical protein Yes (19/20) No TCA/acetoneCNAG_05312 Conserved hypothetical protein Yes (19/20) Yes (C-19) EtOH, TCA/acetoneCNAG_05595 Conserved hypothetical protein Yes (18/19) Yes (C-29) TCA/acetoneCNAG_05893 Conserved hypothetical protein Yes (16/17) Yes (C-13) EtOH, TCA/acetoneCNAG_06109 Conserved hypothetical protein No No EtOHaProteins were categorized based on GO terms associated with their biological classificationbThe presence of a signal peptide was determined using SignalP, Phobius, and Signal-3 LcThe presence of a signal peptide was determined using GPI-SOMGeddes et al. BMC Microbiology  (2015) 15:206 Page 12 of 26the novel protein (CNAG_05312) at 3.1 ± 3.8 fmol in5 μg of total protein. Aph1 levels were below thelimit of detection in all samples. Taken together, ourtargeted proteomics approach identified and quantifiedthe Pka1-regulated secreted proteins as potential bio-markers following host challenge with cryptococcal cells.DiscussionThe secretion of extracellular enzymes and virulence-associated factors is important for the proliferation andsurvival of pathogens in the host environment. For thepathogenic yeast C. neoformans, virulence depends to alarge extent on the export of polysaccharide to form acapsule, as well as targeted delivery of laccase to the cellwall for deposition of melanin, and secretion of extracel-lular enzymes [23, 24, 28, 38]. The cyclic-AMP/ProteinKinase A signal transduction pathway plays a key role inregulating these processes but the underlying mecha-nisms remain to be understood in detail [16, 17]. Wetherefore used a PGAL7::PKA1 strain under Pka1-repressed and Pka1-induced conditions in this study toinvestigate the influence of Pka1 on the secretome of C.neoformans. Quantitative proteomics allowed us to iden-tify 61 different proteins in the secretome including asubset of five whose abundance was regulated by Pka1.These five proteins include a cytokine-inducing glycopro-tein (Cig1), an α-amylase, a glyoxal oxidase, an acid phos-phatase (Aph1), and a novel protein (CNAG_05312). Wealso observed a change in the secretome profile upon in-duction of PKA1 expression thus establishing a view ofthe impact of PKA activity on the extracellular proteincomposition. In general, this analysis highlighted the en-richment of Pka1-regulated biological processes in thesecretome, revealed potential targets for conventional andnon-conventional modes of secretion, and provided candi-date biomarkers for investigating cryptococcosis.Modulation of PKA1 expression leads to a change in thesecretomeOur analysis revealed a change in the abundance of se-creted C. neoformans proteins associated with glycolysis,translational regulation, nucleosome assembly, and stressresponse over a time course from 16 to 120 h. Wespeculate that some of these proteins may result frompackaging in vesicles known to transit through the cellwall and accumulate in the extracellular environment[24, 39]. In this case, modulation of PKA activity may in-directly influence the proteome of vesicles as a reflectionof an impact on the intracellular proteome. This idea issupported by our observed influence of PKA1 modula-tion on the abundance of the translation machinery be-cause ribosomal proteins, in particular, are abundant inextracellular vesicles [39]. It is also well known that PKAinfluences the transcription of ribosomal protein genesin other organisms and this influence is conserved in C.neoformans [22, 40]. Our analysis of the intracellularproteome also revealed suppression of ribosomal cellularprotein abundance upon induction of Pka1 (Geddes etal., unpublished data). We also observed a connectionbetween Pka1 activation and the abundance of glycolyticproteins. This is interesting in light of previous reportsdemonstrating the importance of glycolysis for virulenceand the persistence of C. neoformans in the cerebralspinal fluid [41]. These findings are consistent with aprevious analysis of the transcriptome, which showedthat Pka1 influences the levels of transcript for genes in-volved in glycolysis [22]. Furthermore, the observed in-fluence of Pka1 induction on the secretion of proteinsFig. 5 Comparison of RNA expression levels using qRT-PCR to analyze samples from cells at 16 and 96 hpi, versus secreted protein abundanceusing quantitative proteomics at 96 hpi under Pka1-repressed and Pka1-induced conditions. The samples were evaluated in triplicate, and valuesare reported as average log2 quantification ± standard deviationGeddes et al. BMC Microbiology  (2015) 15:206 Page 13 of 26associated with stress response is consistent with ob-served Pka1 regulation at the transcriptional level. Inthis context, we identified a heat shock protein 70(Hsc70-4), which is associated with the response tostress and which was previously localized to the cell sur-face of C. neoformans [42]. The observed connection be-tween the stress response and Pka1 induction mayindicate coordination for facilitation of fungal survivaland proliferation during colonization of vertebrate hosts.Pka1 regulation of mannoproteins and cell wall functions:connections with Rim101The influence of PKA on the abundance of the manno-protein Cig1 is of particular interest because we previ-ously showed that its transcript is one of the mostabundant in cells grown in low iron medium [43]. Inaddition, the protein is important for iron acquisitionfrom heme and virulence in C. neoformans [44]. Wefound that the extracellular abundance of Cig1 increasedupon induction of Pka1 and that transcript levels andprotein abundance were well correlated. CIG1 is posi-tively regulated by the pH-responsive transcription fac-tor Rim101, which in turn is activated by the cAMP/PKA pathway [45]. Therefore, the regulation of CIG1mRNA and Cig1 protein levels observed upon inductionof Pka1 likely reflect regulation by Rim101. This findingis consistent with recent discoveries that Rim101 con-trols cell wall composition and capsule attachment viaan influence on the expression of cell wall biosyntheticgenes [46, 47].In general, a number of proteins associated with cellwall synthesis and integrity, pathogenesis and the im-mune response were prominent in the secretome of C.neoformans upon modulation of PKA1 expression. Theseproteins included an endo-1,3(4)-β glucanase and a 1,3-β-glucanosyltransferase, both of which have been previ-ously identified in studies of the extracellular proteomesof C. neoformans and other fungal pathogens such asHistoplasma capsulatum [28, 48–51]. Endo-1,3(4)-β glu-canase is located in the surface layers of the cell wall orin the capsule and has roles in metabolism, autolysis,and cell separation [50, 52]. The 1,3-β-glucanosyltrans-ferase is described as a glycolipid protein anchored tothe cell membrane in yeasts and may have a role in viru-lence [53]. Our proteomic analysis also identified chitindeacetylases associated with the formation of chitin andcell wall integrity, and the enzyme laccase, which is re-sponsible for melanin deposition in the cell wall andFig. 6 Interactions of WT and Pka1-regulated strains with J774A.1 murine macrophages. a Intracellular rate at 2 hpi of WT and PGAL7::PKA1 strainsgrown under Pka1-repression (glucose) and Pka1-induction (galactose). b As a control, the colony forming units (CFUs) per macrophage grown instandard DMEM medium (containing 0.45 % glucose) are presented. c Rate of intracellular fungal cell per macrophage at 24 hpi of WT andPGAL7::PKA1 strains grown under Pka1-repression (glucose) and Pka1-induction (galactose). d The CFUs per macrophage grown in standard DMEMmedium (containing 0.45 % glucose) are presented as a control. The experiments were performed in triplicate; the average percent of survivalwas reported ± standard error of the mean. For statistical analysis, an unpaired t-test with Welch’s correction (p-value< 0.05) was performed betweenconditions (* denotes significant difference). The samples at 24 hpi were employed for the analysis of protein abundance shown in Fig. 7Geddes et al. BMC Microbiology  (2015) 15:206 Page 14 of 26Fig. 7 (See legend on next page.)Geddes et al. BMC Microbiology  (2015) 15:206 Page 15 of 26influences cryptococcal virulence [28, 51, 54–57]. Thesefindings are consistent with our previous transcriptomicanalysis, which revealed an influence of PKA on the ex-pression of cell wall associated genes [22].We also identified a novel protein (CNAG_05312)with a pattern of mRNA and protein regulation by Pka1activity that was quite similar to that of Cig1. This novelprotein contains a predicted carbohydrate-binding do-main and was annotated as a macrophage-activatingglycoprotein (reminiscent of the cytokine-inducingglycoprotein designation of Cig1). These observationssuggest that further investigation is warranted for thisprotein in the context of iron acquisition and virulence.This idea is reinforced by the finding that Rim101 alsopositively regulates expression of the CNAG_05312 gene[45]. Interestingly, the CNAG_05312 gene is also regu-lated at the transcript level by the transcription factorGat201 that, like Pka1, influences capsule size, virulence,and uptake by macrophages [58, 59]. Considering thesesimilar phenotypes, it is possible that Gat201 and Pka1/Rim101 both regulate the expression of the CNAG_05312protein and subsequently influence the activation of mac-rophages during infection. Overall, our investigation ofthe secretome reinforced connections between modula-tion of Pka1 activity, Rim101 and cell wall integrity, and itrevealed an impact of PKA on the extracellular abundanceof proteins with known (Cig1) and potential (the novelCNAG_05312 protein) influences on virulence.Pka1 influences the secretion of α-amylase and glyoxaloxidase enzymesPka1 also positively regulated the abundance in thesecretome of an α-amylase and a glyoxal oxidase whichwere previously identified in the extracellular proteomeof C. neoformans [28, 51]. Amylases are associated withcarbohydrate metabolism, particularly starch degradationfor energy production [60]. In C. neoformans, the secre-tion of amylases in the PKA-regulated strains was re-ported previously and we were able to measure andconfirm α-amylase activity in the extracellular medium[29]. Glyoxal oxidases are extracellular H2O2-producingenzymes associated with cellulose metabolism [61].There is evidence that glyoxal oxidase activity is involvedin filamentous growth and pathogenicity of Ustilagomaydis, as well as fertility in Cryptococcus gattii [61, 62].A similar pattern in response to PKA1 expression wasobserved upon comparison of the transcript and proteinlevels for both the α-amylase and the glyoxal oxidase. Adirect correlation between transcript levels and proteinabundance was not as evident as for Cig1. This couldpotentially be due to post-transcriptional regulation, dif-ferences in mRNA and protein half-lives and issues withtiming [63]. It is also possible that PKA may regulateadditional processes to influence extracellular proteinabundance, such as the activity of the secretory pathway.Overall, the secretome data revealed a new connectionbetween PKA regulation and the α-amylase and glyoxaloxidase enzymes, and this discovery indicates that fur-ther analysis of their potential roles in virulence iswarranted.Pka1 influences the secretion of the virulence-associatedacid phosphatase, Aph1The extracellular abundance of the acid phosphataseAph1 and its transcript levels were negatively regulatedby induction of PKA1 expression thus revealing an op-posite pattern of regulation compared with the otherfour genes. Phosphatases have been predicted to haveroles in cell wall biosynthesis, cell signaling, phosphatescavenging, and in adhesion of C. neoformans to epithe-lial cells [24, 28, 64–67]. The APH1 gene was recentlycharacterized and its expression was found to be in-duced by phosphate limitation; the Aph1 protein wasalso the major conventionally secreted acid phosphatasein C. neoformans [28]. Aph1 was also shown tohydrolyze a variety of substrates to potentially scavengephosphate from the environment, and an aph1 deletionmutant had a slight virulence defect in both Galleria(See figure on previous page.)Fig. 7 Detection of Pka1-regulated proteins in lysates of macrophage-like cells containing C. neoformans. Chromatographic representation of themost abundant peptide and its transition for α-amylase (CNAG_02189) identified from isotopically-labeled peptide or natural peptide for each ofthe following samples: a macrophage lysate challenged with WT cells grown in 0.2 % glucose; (b) macrophage lysate challenged with WT cellsgrown in 0.2 % galactose; (c) macrophage lysate challenged with PGAL7::PKA1 cells grown in 0.2 % glucose; (d) macrophage lysate challenged withPGAL7::PKA1 cells grown in galactose 0.2 %. Chromatographic representation of the most abundant peptide and its transition for glyoxal oxidase(CNAG_00407) identified from isotopically-labeled peptide or natural peptide for each of the following samples: (e) macrophage lysate challengedwith WT cells grown in 0.2 % glucose; (f) macrophage lysate challenged with WT cells grown in 0.2 % galactose; (g) macrophage lysate challengedwith PGAL7::PKA1 cells grown in 0.2 % glucose; (h) macrophage lysate challenged with PGAL7::PKA1 cells grown in 0.2 % galactose. Blackindicates isotopically-labeled peptide; red indicates natural peptide. i Quantification of α-amylase identified in the macrophage lysates wasbased on the area under the curve for the isotopically-labeled peptide versus the natural peptide in WT and PGAL7::PKA1 strains underPka1-repressed (d) and Pka1-induced (g) conditions. The avergae (± S.D.) amount of peptide present in the sample is reported. j Quantification ofglyoxal oxidase identified in the macrophage lysates was based on the area under the curve for the isotopically-labeled peptide versusthe natural peptide in WT and PGAL7::PKA1 strains under Pka1-repressed (D) and Pka1-induced (G) conditions. The avergae (± S.D.) amountof peptide present in the sample is reported. Five micrograms of total protein were used for the assays and all assays were performedin triplicateGeddes et al. BMC Microbiology  (2015) 15:206 Page 16 of 26mellonella and mouse models of cryptococcosis. The lat-ter phenotype is consistent with our recent study show-ing that a high affinity phosphate uptake system isrequired for growth on low-phosphate medium, for for-mation of the virulence factors melanin and capsule, forsurvival in macrophages, and for virulence in mice [68].This study also revealed that defects in PKA influencethe growth of C. neoformans on phosphate-limitedmedium. Our discovery of PKA regulation of Aph1abundance in the secretome therefore further reinforcesa connection between phosphate acquisition and PKAregulation associated with virulence.PKA regulation and the intersection of secretome studiesin C. neoformansOur profiling of the secretome upon modulation of Pka1activity confirmed the presence of previously identifiedextracellular and vesicular proteins, including those as-sociated with virulence and fungal survival within thehost, as well as novel secreted proteins. We identifiedthe classically secreted C. neoformans protein, laccase,associated with fungal virulence, but other proteins suchas urease and phospholipase B were not identified in ourstudy. Their absence could be attributed to growth con-ditions, precipitation methods, supernatant collectionFig. 8 Detection of Pka1-regulated proteins in mouse bronchoalveolar lavage samples. Chromatographic representation of the most abundantpeptide and its transition identified from isotopically-labaled peptide or natural peptide for each of the following proteins: (a) Cig1 (CNAG_01653),(b) α-Amylase (CNAG_02189), (c) Glyoxal oxidase (CNAG_00407), (d) Hypothetical protein (CNAG_05312). Black indicates isotopically-labeled peptide;red indicates natural peptide. e Quantification of proteins identified in the mouse BAL samples based the area under the curve for theisotopically-labeled peptide versus the natural peptide, for Cig1, α-amylase, glyoxal oxidase, and hypothetical (CNAG_05312) proteins. Theavergae (± S.D.) amount of peptide present in the sampleis reported. Five micrograms of total protein were used for the assays and allassays were performed in triplicateGeddes et al. BMC Microbiology  (2015) 15:206 Page 17 of 26times, and relative abundance in the secretome. A recentproteome study that removed free capsular polysacchar-ide from the extracellular environment identified 105 se-creted proteins and a direct comparison with our studyshowed an overlap of 52 % [28]. Previous investigationof the proteins in extracellular vesicles of C. neoformansalso showed an overlap of nearly 56 % with proteinsidentified in our study [24, 39]. This overlap is primarilyassociated with proteins not typically expected in thesecretome. For example, ATP subunits/carriers, transla-tion elongation factor, actin, and multiple ribosomal pro-teins were identified and their presence was attributedto packaging in extracellular vesicles, and not necessarilydue to direct secretion. In the absence of an N-terminalsignal peptide, proteins may be exported via non-conventional secretion. This may include the use ofmembrane-bound, extracellular vesicles capable of tra-versing the cell wall, the possible fusion of multi-vesicularbodies with the plasma membrane, or the capture of cyto-solic material to form vesicles (blebbing), as discussedabove [23, 24, 69–72]. Taken together, our profile of se-creted proteins in C. neoformans is in agreement with pre-vious secretome studies. However, our ability to modulatePka1 activity provides an opportunity to identify novelproteins in the extracellular environment as well asidentify proteins specifically regulated by Pka1. This ap-proach led to the unique identification of the novel se-creted protein (CNAG_05312) that was specificallyassociated with modulation of Pka1 activity and not foundin other proteomic studies.Detection of potential biomarkers during cryptococcalinfectionBiomarkers are indicators of normal or pathogenic pro-cesses as well as the efficacy of therapy [73]. In this regard,targeted detection of secreted cryptococcal proteins pro-vides an opportunity to identify potential biomarkers forearly diagnosis of infection and to monitor antifungaltherapy. Early and rapid diagnosis remains limited for sys-temic fungal infections, such as those caused by Candidaand Aspergillus species, as well as C. neoformans and C.gattii [74]. Biomarkers of infection by specific fungal spe-cies would therefore be valuable for identification and forprecise measurements of fungal burden. A recent studyusing the presence of the cell wall component galacto-mannan in BAL as a diagnostic tool for invasive fungaldisease highlights an opportunity for biomarker discoveryin fungal pathogens [75]. Additionally, the use of targetedproteomics (and MRM in particular) is a novel approachto study the secretion of virulence factors in C.Fig. 9 Detection of Pka1-regulated proteins in mouse blood samples. Chromatographic representation of the most abundant peptide and itstransition identified from isotopically-labaled peptide or natural peptide for each of the following proteins: (a) Cig1 (CNAG_01653), (b) Glyoxal oxidase(CNAG_004070), (c) Hypothetical protein (CNAG_05312). Black indicates isotopically-labeled peptide; red indicates natural peptide. d Quantification ofproteins identified in the mouse blood samples based the area under the curve for the isotopically-labeled peptide versus the naturalpeptide, for Cig1, glyoxal oxidase, and hypothetical (CNAG_05312) proteins. The average (± S.D.) amount of peptide present in the sampleis reported. Five micrograms of total protein were used for the assays and all assays were performed in triplicateGeddes et al. BMC Microbiology  (2015) 15:206 Page 18 of 26neoformans, particularly in the context of signaling func-tions like PKA that sense conditions relevant to the hostenvironment.The secreted proteins that we identified to be regu-lated in abundance by Pka1 provide an opportunity todevelop diagnostic biomarkers that are also informativeabout signaling via the cAMP/PKA pathway in vitro andduring infection. For example, Cig1 is an important can-didate biomarker given its abundance in iron-starvedcells and its role in virulence through iron acquisitionand uptake. Our ability to detect Cig1 in the blood andBAL fluid of infected animals confirms its expressionand establishes the protein as a potential biomarker.These findings may also indicate a role for Cig1 in ironuptake in these environments although, interestingly, wedid not detect Cig1 in macrophage lysates. Based on ourobserved differences in intracellular replication, Pka1seems to impact the intracellular environment of macro-phages. In this regard, we did detect the glyoxal oxidaseand α-amylase proteins by MRM in macrophages con-taining cryptococcal cells. Expression of these proteinshas not previously been reported during interactionswith macrophages, although the production of H2O2and induction of oxidative stress via glyoxal oxidasecould potentially influence intracellular survival. It isknown that oxidative stress induces autophagy in macro-phages and can impair phagocytic activity [76, 77]. Add-itionally, loss of an α-amylase in H. capsulatumattenuated the ability of the fungus to kill macrophagesand to colonize murine lungs [78]. This influenceappeared to be related to the ability to produce α-(1,3)-glucan. The regulation of glyoxal oxidase and α-amylaseby Pka1 activity and their detection in macrophage ly-sates suggests that it would be interesting to examinethe roles of these enzymes in intracellular survival andvirulence. Our approach with MRM is also informativeabout tissue specific expression of fungal proteins duringdisease. In addition to the examples described above, wefound that colonization of murine lungs resulted in se-cretion of α-amylase, glyoxal oxidase and the novel pro-tein from gene CNAG_05312. The novel protein wasalso found in blood and, given its similar regulation withCig1 these results suggest future studies on the role ofthis protein in iron acquisition and virulence.ConclusionIn this study we characterized the overall impact ofPKA1 modulation on the secretome and discovered fiveproteins regulated by Pka1. The identified proteins hadknown roles associated with cell wall functions, fungalsurvival within the host, and virulence. Our identifica-tion of a novel protein with potential roles in iron up-take and virulence also suggested a previously unknownconnection between Pka1 and Gat201. We were alsoable to detect Pka1-regulated secreted proteins in bio-logical samples as potential biomarkers, providing a newopportunity for diagnosing fungal infection and moni-toring disease progression.MethodsFungal strains and culture conditionsThe C. neoformans var. grubii wild-type strain H99(WT) and the PGAL7::PKA1 strain with galactose-inducible/glucose repressible expression of PKA1 wereused for this study [16, 29]. The strains were maintainedon yeast extract peptone dextrose (YPD) medium (1 %yeast extract, 2 % peptone, 2 % dextrose, and 2 % agar).For studies involving regulation of PKA1, cells of theWT and regulated strains were pre-grown overnight withagitation at 30 °C in YPD broth, transferred to yeast ni-trogen base medium with amino acids (YNB, Sigma-Aldrich) and incubated overnight with agitation at 30 °C.Cell counts were performed and 5 x 107 cells/ml weretransferred to Minimal Medium (MM) (29.4 mMKH2PO4, 10 mM MgSO4 • 7H2O, 13 mM glycine, 3 μMthiamine, 0.27 % carbon source) containing either glu-cose (MM+D) or galactose (MM +G). For end-pointstudies, cells were incubated with agitation at 30 °C inMM+D or MM+G for 96 h; for time-course studies,cells were incubated with agitation at 30 °C in MM+Dor MM+G for 16, 48, 72, and 120 h. Time points wereselected based on previous studies on the timing of pro-tein secretion as well as the analysis of proteins in extra-cellular vesicles of C. neoformans, which used samplescollected at 48 and 72 h of growth [23, 24, 64]. Sampleswere collected in triplicate for analysis.Protein quantification, precipitation and in-solutiondigestionTo collect supernatant samples, cells were removed bycentrifugation at 3,500 rpm for 15 min at 4 °C and theculture medium was transferred to new tubes; this stepwas repeated four times until all cell debris had been re-moved. Supernatant samples were kept on ice and totalprotein concentration was measured by a BCA-Protein-assay (Pierce). Ultrapure bovine serum albumin was usedas a calibration standard. In addition to using two ap-proaches for protein precipitation as described below,we also used a combination of sample collection timepoints (time-point and end-point analyses) to maximizeprotein detection and obtain a comprehensive view ofthe secretome. The first approach involved a time-course study in which a stringent trichloroacetic acid(TCA)/acetone precipitation was performed [79]. Inbrief, an aliquot of culture supernatant (50 μg total pro-tein) was mixed with five volumes of ice-cold TCA/acet-one (20 %/80 % w/v) and incubated overnight at −20 °C.Precipitated proteins were collected by centrifugationGeddes et al. BMC Microbiology  (2015) 15:206 Page 19 of 26at 10,000 rpm for 20 min at 4 °C. The pellet waswashed four times with ice-cold acetone, air-driedand stored at −20 °C. The second approach, whichwas less stringent than the TCA/acetone method, wasused for the end-point studies and involved ethanol(EtOH)/acetate precipitation [80]. In brief, an aliquotof culture supernatant (50 μg total protein) was dilutedwith 4 volumes of absolute EtOH, 2.5 M NaCH3COO wasused to bring the solution to 50 mM NaCH3COO, pH 5.0and 20 μg of glycogen was added to the sample. Sampleswere vortexed and incubated at room temperature for 2 hwith periodic agitation. Precipitated proteins werecollected by centrifugation at 15,000 rpm for 10 minat 4 °C. The pellet was washed twice with EtOH, thenair-dried and stored at −20 °C. All supernatantsamples were subjected to in-solution digestion usingACS grade chemicals or HPLC grade solvents(Thermo Scientific and Sigma-Aldrich) [81]. In brief,the precipitated protein pellet was solubilized indigestion buffer (1 % sodium deoxycholate, 50 mMNH4HCO3), incubated at 99 °C for 5 min with agita-tion, followed by reduction (2 mM of dithiothreitol(DTT) for 25 min at 56 °C), alkylation (4 mM ofiodoacetamide (IAA) for 30 min at room temperaturein the dark), and trypsinization (0.5 μg/μl of sequen-cing grade modified trypsin (Promega)) overnight at37 °C. Based on our results, the TCA/acetone precipi-tation method appeared to be more stringent, perhapsdue to more extensive washing in the protocol.Peptide chemical labeling and purificationDigested peptides from supernatants were desalted,concentrated, and filtered on C18 STop And Go Ex-traction (STAGE) tips [82]. Reductive dimethylationusing formaldehyde isotopologues was performed todifferentially label peptides from the different experi-mental conditions. Light formaldehyde (CH2O) andmedium formaldehyde (CD2O) (Cambridge IsotopeLaboratories, Andover, MA) were combined with cya-noborohydride (NaBH3CN, Sigma-Aldrich) to give a4 Da difference for labeled peptides [83]. Samplesfrom the WT strain were routinely labeled with lightformaldehyde, and PGAL7::PKA1 samples were labeledwith medium formaldehyde. Briefly, eluted and driedSTAGE-tip peptides were resuspended in 100 mMtriethylammonium bicarbonate, and incubated in200 mM formaldehyde and 20 mM sodium cyanobor-ohydride for 90 min in the dark. After labeling,125 mM NH4Cl was added and incubated for 10 minto react with excess formaldehyde, followed by theaddition of acetic acid to a pH < 2.5 to degrade so-dium cyanoborohydride. For each comparison, equalamounts of labeled peptides were mixed and desaltedon C18 STAGE tips.Protein identification by liquid chromatography-tandemmass spectrometry (LC-MS/MS) and mass spectrometrydata analysisPurified peptides were analyzed using a linear-trappingquadrupole - Orbitrap mass spectrometer (LTQ-Orbitrap Velos; Thermo Fisher Scientific) on-linecoupled to an Agilent 1290 Series HPLC using ananospray ionization source (Thermo Fisher Scientific).This includes a 2-cm-long, 100-μm-inner diameter fusedsilica trap column, 50-μm-inner diameter fused silica frit-ted analytical column and a 20-μm-inner diameter fusedsilica gold coated spray tip (6-μm-diameter opening,pulled on a P-2000 laser puller from Sutter Instruments,coated on Leica EM SCD005 Super Cool SputteringDevice). The trap column was packed with 5 μm-diameterAqua C-18 beads (Phenomenex, www.phenomenex.com)while the analytical column was packed with 3.0 μm-diameter Reprosil-Pur C-18-AQ beads (Dr. Maisch,www.Dr-Maisch.com). Buffer A consisted of 0.5 % aque-ous acetic acid, and buffer B consisted of 0.5 % acetic acidand 80 % acetonitrile in water. Samples were resuspendedin buffer A and loaded with the same buffer. Standard90 min gradients were run from 10 % B to 32 % B over51 min, then from 32 % B to 40 % B in the next 5 min,then increased to 100 % B over a 2 min period, held at100 % B for 2.5 min, and then dropped to 0 % B for an-other 20 min to recondition the column. The HPLC sys-tem included Agilent 1290 series Pump and Autosamplerwith Thermostat; temperature was set at 6 °C. The samplewas loaded on the trap column at 5 μl/min and the ana-lysis was performed at 0.1 μl/min. The LTQ-Orbitrap wasset to acquire a full-range scan at 60,000 resolution from350 to 1600 Th in the Orbitrap to simultaneously frag-ment the top ten peptide ions by CID and top 5 by HCD(resolution 7500) in each cycle in the LTQ (minimum in-tensity 1000 counts). Parent ions were then excluded fromMS/MS for the next 30 s. Singly charged ions were ex-cluded since in ESI mode peptides usually carry multiplecharges. The Orbitrap was continuously recalibrated usinglock-mass function [84]. Mass accuracy included an errorof mass measurement within 5 ppm and did not exceed10 ppm.For analysis of mass spectrometry data, centroid frag-ment peak lists were processed with Proteome Discovererv. 1.2 (Thermo Fisher Scientific). The search was per-formed with the Mascot algorithm (v. 2.4) against a data-base comprised of 6,692 predicted protein sequences fromthe source organism C. neoformans H99 database (C. neo-formans var. grubii H99 Sequencing Project, Broad Insti-tute of Harvard and MIT, http://www.broadinstitute.org/)using the following parameters: peptide mass accuracy 10parts per million; fragment mass accuracy 0.6 Da; trypsinenzyme specificity with 1 max missed cleavages; fixedmodifications - carbamidomethyl, variable modifications -Geddes et al. BMC Microbiology  (2015) 15:206 Page 20 of 26methionine oxidation, deamidated N, Q and N-acetyl pep-tides, dimethyl (K), dimethyl (N-term), dimethyl 2H(4)(K), and dimethyl 2H(4) (N-term), ESI-TRAP fragmentcharacteristics. Only those peptides with Ion Scores ex-ceeding the individually calculated 99 % confidence limit(as opposed to the average limit for the whole experiment)were considered as accurately identified. The acceptancecriteria for protein identification were as follows: only pro-teins containing at least one unique peptide with a Mascotscore > 25 were considered in the dataset. Quantitativeratios were extracted from the raw data using ProteomeDiscoverer. Proteome Discoverer parameters – EventDetector: mass precision 4 ppm (corresponds to extractedion chromatograms at ±12 ppm max error), S/N threshold1; Precursor Ion Quantifier method set for ‘2 labels’ for theformaldehyde labeled samples; Quantitation Method –Ratio Calculation – Replace Missing Quantitation Valueswith Minimum Intensity – yes, Use Single Peak Quantita-tion Channels – yes, − Protein Quantification – Use AllPeptides – yes.Experimentally determined fold changes for WT andPGAL7::PKA1 strains grown under Pka1-repressed (glu-cose-containing medium) and Pka1-induced (galactose-containing medium) conditions were converted to a log2scale and the average fold change and standard deviationwere used for analysis. A fold change of >10 was used asa cut-off limit for the time-point and end-point analyses.For the comparative analysis of the time-point samples,the statistical significance of the fold changes of theidentified secreted proteins present under both Pka1-repressed and Pka1-induced conditions and at equivalenttime points (i.e. 16, 48, 72, and 120 hpi) was assessed foran influence of PKA regulation using a Student’s t-test(p-value < 0.05). For the comparative analysis of the end-point samples, the statistical significance of the foldchanges of the identified secreted proteins present underboth Pka1-repressed and Pka1-induced conditions wasevaluated using a Student’s t-test (p-value < 0.05). Toconfirm the statistically significant Pka1-regulated pro-teins identified from the end-point analysis, a multiple-hypothesis testing correction was performed on thesecretome data using the Benjamini and Hochbergmethod with a false discovery rate of 0.05.Gene ontology analysesProteins were characterized with Gene Ontology (GO)terms using a local installation of Blast2GO [85]. Geneannotation data of the C. neoformans H99 reference gen-ome were retrieved from the Broad Institute (May 2014)and a copy of the non-redundant (nr) protein databasewas downloaded from NCBI (May 2014) [86]. The mostcurrent associations between the nr protein databaseand GO terms were retrieved in May 2014 from Blas-t2GO. GO terms were assigned to WT proteins andfiltered using default settings of the Blast2GO pipeline[85]. We performed GO term enrichment analyses forsets of proteins using hypergeometric tests and theBenjamini and Hochberg false discovery rate multipletesting correction (p-value < 0.05) implemented in the Rpackages GSEABase and GOstats. GO term categoriescontaining singleton entries were excluded. GO categor-ies and enrichment datasets were visualized using the Rpackage ggplot2 [87]. For time-point analyses, GO termclassification was performed on unique proteins identifiedunder either Pka1-repressed or Pka1-induced conditionsto highlight the overall influence of Pka1 regulation on thesecretome profile.Prediction of the extracellular location of identifiedproteinsSignalP 4.1 (http://www.cbs.dtu.dk/services/SignalP/)was used to predict whether identified proteins were se-creted based on the presence of a signal peptide. Identi-fied protein sequences were also analyzed using Signal-3 L (http://www.csbio.sjtu.edu.cn/bioinf/Signal-3L/) andPhobius (http://phobius.sbc.su.se) to confirm results.Additionally, secreted proteins were analyzed for thepresence of a glycophosphatidylinositol (GPI) anchorusing GPI-SOM (http://gpi.unibe.ch).RNA isolation and quantitative Real-Time PCR (qRT-PCR)analysisCells from WT and PGAL7::PKA1 strains were preparedfor the examination of gene expression by overnightgrowth in YNB medium followed by dilution to 5.0 x107 cells/ml in 5 ml of MM+D or MM+G and incuba-tion at 30 °C with agitation for 16 and 96 h. Sampleswere collected in triplicate for analysis. Cells were col-lected at the designated time points, flash frozen in li-quid N2, and stored at −80 °C. Total RNA was extractedusing an EZ-10 DNAaway RNA Miniprep kit (Bio Basic)according to the manufacturer’s protocol. Complemen-tary DNA was synthesized using a Verso cDNA kit(Thermo Scientific) and used for quantitative real-timePCR (qRT-PCR). Primers were designed using Primer3v.4.0 (http://bioinfo.ut.ee/primer3-0.4.0/) and targeted tothe 3’ regions of transcripts. qRT-PCR primer sequences(see Additional file 9: Table S6). Relative gene expressionwas quantified using the Applied Biosystems 7500 FastReal-time PCR system. Control genes CNAG_00483(Actin) and CNAG_06699 (GAPDH) were used fornormalization, and tested for statistical significanceusing the Student’s t-test. As a control, PKA1 RNA ex-pression levels under Pka1-repressed and Pka1-inducedconditions in the WT and PGAL7::PKA1 strains were alsoanalyzed at various time points to confirm the regulatedPKA expression (see Additional file 10: Figure S4).Geddes et al. BMC Microbiology  (2015) 15:206 Page 21 of 26RNA blot analysisTo confirm qRT-PCR results, total RNA was isolated forthe PGAL7::PKA1 strain grown in 50 ml of MM+D orMM+G for 16 h. Briefly, cell pellets were collected andflash frozen in liquid N2, followed by overnightlyophilization. One milliliter of buffer 1 (2 % SDS,68 mM Na3C6H5O7, 132 mM C6H8O7, 10 mM EDTA)was added to the samples, along with 600 μl of glassbeads; samples were subjected to bead beating for two,3 min intervals at power 3 (BioSpec, Mini-Beadbeater)and subsequently stored on ice. Next, 340 μl of buffer 2(4 M NaCl, 17 mM Na3C6H5O7, 33 mM C6H8O7) wasadded and samples were inverted several times and incu-bated on ice for 5 min. Samples were then centrifuged at15,000 rpm for 10 min, the supernatant fraction was col-lected and transferred to a new tube, one volume of iso-propanol was added, and samples were mixed andincubated at room temperature for 15 min. The pelletwas collected following centrifugation at 15,000 rpm for5 min, and washing of the pellet with 70 % DEPC(Diethylpyrocarbonate)-EtOH was performed. The pelletwas collected, air dried, and dissolved in 20 μl of DEPC-H2O. The hybridization probes were prepared with aPCR-amplified DNA fragment of CNAG_00483 (Actin)or CNAG_00396 (PKA1) using specific primers (seeAdditional file 9: Table S6) and labeled with 32P using anOligolabeling kit (Amersham Biosciences). Scannedimages were analyzed using a Bio-Rad ChemiDoc MPImaging System (see Additional file 11: Figure S5).Multiple Reaction Monitoring (MRM) sample collectionfrom macrophages, mouse bronchoalveolar lavage, andmouse bloodThe survival rates of the WT, pka1Δ mutant, andPGAL7::PKA1 strains during incubation with macro-phages were determined and lysates were prepared forprotein analysis [88]. Briefly, cells of the J774A.1macrophage-like cell line were grown to 80 % confluencein Dulbecco’s Modified Eagle’s Medium (DMEM; Sigma)supplemented with 10 % fetal bovine serum and2 mM L-glutamine at 37 °C and 5 % CO2. The macro-phages were stimulated 1 h prior to infection with150 ng/ml phorbol myristate acetate (PMA). Fungal cellswere grown in YNB overnight at 30 °C, followed by in-oculation in MM+D or MM+G at 5.0 x 107 cells/ml.Following overnight growth, the fungal cells werewashed with phosphate-buffered saline (PBS, Invitrogen)and opsonized with 0.5 μg/ml of the anti-capsule mono-clonal antibody 18B7 in DMEM or DMEM supple-mented with 0.20 % glucose or galactose (30 min at 37 °C). Stimulated macrophages were infected with 2.0 x 105opsonized fungal cells at a multiplicity of infection(MOI) of 1:1 for 2 h and 24 h at 37 °C and 5 % CO2. Tomeasure fungal survival, macrophages containinginternalized cryptococcal cells were washed thoroughlyfour times with PBS and then lysed in 1 ml of steriledH2O for 30 min at room temperature. Lysate dilutionswere plated on YPD agar and incubated at 30 °C for48 h, at which time the resulting colony formingunits (CFUs) were counted and intracellular rates ofinfection (%) were calculated as the ratio of the CFUsat 2 h and 24 h over the initial number of macro-phages. The statistical significance of differences be-tween WT, pka1Δ mutant, and PGAL7::PKA1 strainswere determined by unpaired t-tests. For proteomicanalysis, lysates from infected macrophage at 24 h ofincubation were collected, flash frozen in liquid N2and stored at −80 °C.Female BALB/c mice (10–12 weeks old) obtained fromCharles River Laboratories (Senneville, Ontario, Canada)were used to collect bronchoalveolar lavage (BAL) andblood samples following cryptococcal infection. Threedifferent cultures of C. neoformans WT cells were grownovernight in YPD at 30 °C with agitation, washed in PBSand re-suspended at 1.0 x 108 cells/ml in PBS. For col-lection of BAL, intranasal inoculation of three mice with100 μl of the different WT cell suspensions (1.0 x 107cells) was performed. For collection of blood samples,intravenous inoculation of three mice with 100 μl of theWT cell suspensions (1.0 x 107 cells) was performed.Three mice were selected for the analysis based onestablished methods for studying fungal burden inmouse models of cryptococcosis [34–37]. At 48 hpi, theinfected mice were euthanized by CO2 inhalation and1 ml of BAL fluid and 500 μl of blood samples were col-lected from each mouse [89]. Mouse lavage and bloodsamples were flash frozen with liquid N2 and storedat −80 °C. Mouse assays were conducted in accord-ance with University of British Columbia’s Committeeon Animal Care (protocol A13-0093).MRM sample preparationMacrophage lysate samples were prepared as describedabove, followed by trypsin in-solution digestion. Sampleswere collected for WT and PGAL7::PKA1 strains at 24 hpiin triplicate. Mouse BAL samples were prepared as de-scribed above, followed by trypsin in-solution digestion.Samples were collected at 48 hpi following WT inocula-tion of each of the three mice. For mouse blood samples,highly abundant proteins were removed as previouslydescribed [90]. Briefly, proteins were precipitated by theaddition of two volumes of acetonitrile and 1.0 % aceticacid, followed by centrifugation at 10,000 rpm for 5 minat 4 °C. The supernatant was collected and evaporatedand the residual proteins were then subjected to trypsinin-solution digestion as described above. Samples werecollected at 48 hpi following WT inoculation of each ofthe three mice. Following trypsin digestion, all samplesGeddes et al. BMC Microbiology  (2015) 15:206 Page 22 of 26were desalted, concentrated, and filtered on high-capacity C18 STAGE tips.Peptide selection, internal standardization, and MRMmethod developmentSkyline (v2.1) was used to build and optimize the MRMmethod for the relative quantification of peptides [91].Synthesized peptides for MRM analysis were designedin-house using the following parameters: tryptic peptides, 0max missed cleavages, minimum of seven and maximum of25 amino acids, excluding peptides containing Met or Cysresidues (if possible) and N-terminal glutamine,hydrophobicity between 10–40 (Sequence Specific Re-tention Calculator, http://hs2.proteome.ca/SSRCalc/SSRCalcX.html), desirable spectral intensities (Gene-Pattern ESPPredictor, http://www.broadinstitute.org/cancer/software/genepattern/modules), and transitionsettings selecting for precursor charges of 2 and 3,ion charge of 1, monitoring both b and y ions. Spike-Tides labeled with stable isotopes (C-term Arg U-13C6;U-15N4 or Lys U-13C6;U-15N2) were purchasedfrom JPT Peptide Technologies GmbH (Berlin,Germany). N-terminal Arginine (R) and Lysine (K)were labeled with a stable isotope mass of 10.008269and 8.014199, respectively. Collision energy (CE) andfragmentor voltage (FV) for each peptide was pre-dicted utilizing Skyline software and then confirmedexperimentally [92]. Doubly and triply charged pre-cursor ions were optimized and three to five transi-tions were measured per peptide. The final MRMmethod included the monitoring of a total of 23 pep-tides, representing five proteins (see Additional file12: Table S7). Stable isotope-labeled peptides were re-suspended in 100 μl of 0.5 % acetic acid with agita-tion at room temperature. The peptides were furtherdiluted and combined to result in final concentrationsof 100 fmol/μl to 1 pmol/μl of each peptide. Five μlof the peptide mixture was injected into an Agilent6460 Triple Quadrupole (Agilent) for data acquisitionand peptide optimization.Mass spectrometry and data analysis for MRMMRM assays were performed on an Agilent 6460 TripleQuadrupole coupled with Agilent 1200 Series HPLC.The instrument was operated in positive electrosprayionization mode using MassHunter Workstation DataAcquisition (v.B.04.04, Agilent). Chromatography wasperformed on a Large Capacity Chip with 160 nl Trap,analytical column was 150 mm x 75 μm, stationaryphase for both trapping and analytical columns wereZorbax-SB C-18, 300 A and 5 μm particles (Agilent).Peptides were separated using gradient elution with astable flow of 0.30 μl/min, beginning with 97 % buffer A(97 % dH2O, 3 % acetonitrile, 0.1 % formic acid (FA))and 3 % buffer B (10 % dH2O, 90 % ACN, 0.1 % FA)followed by a step gradient of buffer B from 3 to 80 %,which was achieved at 10.5 min. Subsequent equilibra-tion was performed for 4.5 min at 3 % buffer B. The col-umn was maintained at room temperature duringanalysis, and the samples were kept at 4-7 °C. The MSwas operating in selective reaction mode using electro-spray ionization in positive ion mode, with a capillaryvoltage of 1850 V and a source temperature of 325 °C.Cone voltage was static, collision energies and fragmentorvoltages were optimized for each compound individually(see Additional file 13: Table S8). Peak identificationwas performed using MassHunter Qualitative Analysis(Agilent).Quantification of natural proteins was performedusing peak areas relative to the known amounts of addedisotopically-labeled synthetic peptides during a multi-plexed MRM run. Natural protein levels were identifiedin triplicate from the following matrices: WT andPGAL7::PKA1 macrophage lysate MM+D and MM+Gcollected at 24 hpi; BAL collected at 48 hpi from threedifferent mice inoculated independently with the WTstrain; and blood collected at 48 hpi from three differentmice inoculated independently with the WT strain. Eachbiological sample was assayed independently in tripli-cate. Experimentally determined peak areas and the sub-sequent quantification values were converted to a log2scale, and the average amount of identified peptide +/−S.D. was reported. Positive association of natural pep-tides to their respective isotopically-labeled peptides wasdetermined based on co-elution patterns. For positiveidentification of a natural protein in a collected sample,at least one peptide with a minimum of two transitionsmust be identified or a minimum of two peptides with atleast one transition each must be present.Validation of secretome dataEnzymatic activity was assayed for α-amylase and acidphosphatase. The assays were performed with kits forboth enzymes according to the manufacturer’s proto-col (BioVision Incorporated) (see Additional file 14:Figure S6). To confirm that proteins identified in thesecretome were a result of secretion and not a prod-uct of cell lysis, a PCR was performed on secretomesamples from Pka1-repressed conditions for WTstrain at 96 hpi. Actin (CNAG_00483) and PKA1(CNAG_00396) were used as control genes for ampli-fication (see Additional file 15: Figure S7) [48].Availability of supporting dataThe mass spectrometry proteomics data have been de-posited to the ProteomeXchange Consortium [93] viathe PRIDE partner repository [94] with the datasetGeddes et al. BMC Microbiology  (2015) 15:206 Page 23 of 26identifier PXD002731 and the PASSEL partner reposi-tory with the dataset identifier PASS00736.Ethics statementMouse assays were conducted in accordance with Uni-versity of British Columbia’s Committee on Animal Care(protocol A13-0093).Additional filesAdditional file 1: Table S1. Quantitative proteomic analysis of thesecretome of C. neoformans at 16, 48, 72, and 120 hpi under Pka1-repressed(glucose-containing medium) conditions. (DOCX 94 kb)Additional file 2: Table S2. Quantitative proteomic analysis of thesecretome of C. neoformans at 16, 48, 72, and 120 hpi under Pka1-induced(galactose-containing medium) conditions. (DOCX 99 kb)Additional file 3: Table S3. Proteins identified in the secretome of C.neoformans from both the 96 hpi (end-point) samples and the timecourse (16, 48, 72, 120 hpi) samples prepared in Pka1-repressed(glucose-containing medium) and Pka1-induced (galactose-containingmedium) conditions. (DOCX 94 kb)Additional file 4: Table S4. Quantitative proteomic analysis of thesecretome of C. neoformans at 96 hpi under Pka1-repressed (glucose-containing medium) conditions. (DOCX 92 kb)Additional file 5: Table S5. Quantitative proteomic analysis of thesecretome of C. neoformans at 96 hpi under Pka1-induced (galactose-containing medium) conditions. (DOCX 82 kb)Additional file 6: Figure S1. Enrichment of genes represented in thesecretome for cells grown under Pka1-repressed (D) and Pka1-induced(G) conditions compared to all genes present in the WT strain. Enrichmentbased on GO terms associated with cellular compartment (CC). (TIFF 275 kb)Additional file 7: Figure S2. Comparison of GO terms classifications ofcellular components from the identified secreted proteins grown underPka1-repressed and Pka1-induced conditions compared to proteinsrepresented in the Fungal Secretome Knowledgebase. (TIFF 1613 kb)Additional file 8: Figure S3. Comparison of GO terms classifications ofmolecular function from the identified secreted proteins grown underPka1-repressed and Pka1-induced conditions compared to proteinsrepresented in the Fungal Secretome Knowledgebase. (TIFF 1149 kb)Additional file 9: Table S6. Primers sequences used for amplification ofcDNA for qRT-PCR analysis and genomic DNA for cell lysis control PCR.(DOCX 21 kb)Additional file 10: Figure S4. RNA expression levels of PKA1 measuredby qRT-PCR in PGAL7::PKA1 and WT strains, grown in Pka1-repressed(glucose-containing medium) and Pka1-induced (galactose-containingmedium) conditions at 4, 16, 48 and 96 hpi. Samples evaluated in triplicate,values reported as average log2 fold change ± S.D. Actin and GAPDH wereused as controls and PKA1 expression was assessed under the differentgrowth conditions. The results show an up-regulation of PKA1 mRNA underPka1-inducible conditions. (TIFF 610 kb)Additional file 11: Figure S5. RNA expression levels of PKA1 measuredby Northern blot as a method for validating the qRT-PCR results. RNAwas extracted from PGAL7::PKA1 cells grown under Pka1-repressed (glucose-containing medium) and Pka1-induced (galactose-containing medium)conditions 16 hpi. Actin was used as a control and PKA1 expression wasassessed under the different growth conditions. The results show anup-regulation of PKA1 mRNA under Pka1-inducible conditions.(TIFF 342 kb)Additional file 12: Table S7. Proteins selected for Multiple ReactionMonitoring assays and their respective isotopically-labeled syntheticpeptides (DOCX 87 kb)Additional file 13: Table S8. Isotopically-labeled peptides monitoredduring MRM multiplex assay. (DOCX 112 kb)Additional file 14: Figure S6. Enzyme activity for A) Amylase and B)Acid phosphatase in the WT and PGAL7::PKA1 strains of C. neoformansunder Pka1-repressed (glucose-containing medium) and Pka1-induced(galactose-containing medium) conditions. Values are reported as anaverage ± standard deviation for three independent replicates. Forstatistical analysis, a Student’s t-test was performed and a line denotesp-value < 0.05. (TIFF 489 kb)Additional file 15: Figure S7. PCR to confirm absence of cellularfactors due to cell lysis in secretome of C. neoformans. PCR for the A)Actin and B) PKA1 genes were performed using either C. neoformans WTgenomic DNA (6 pg to 100 ng) or WT supernatant samples (250 ng or1000 ng of total protein). Control lane contains 6 pg of gDNA spiked into250 ng of supernatant. (TIFF 1093 kb)AbbreviationsAIDS: Acquired immune deficiency syndrome; BAL: Bronchoalveolar lavage;cAMP: cyclic-adenosine monophosphate; CID: Collision induced dissociation;CFU: Colony forming units; DEPC: Diethylpyrocarbonate; DMEM: Dulbecco’smodified eagle medium; FunSecKB: Fungal Secretome KnowledgeBase;GO: Gene ontology; GPCR: G-protein coupled receptor;GPI: Glycophosphatidylinositol; HCD: Higher-energy collision dissociation;HIV: Human immunodeficiency virus; hpi: Hours post inoculation; HPLC: Highperformance liquid chromatography; MM (D/G): Minimal media (glucose/galactose); MRM: Multiple reaction monitoring; NEM: N-ethylmaleimide;PBS: Phosphate buffered saline; PKA: Protein kinase A; PMA: Phorbolmyristate acetate; qRT-PCR: Quantitative real time – polymerase chainreaction; SID: Stable isotope dilutions; STAGE: Stop and go extraction;WT: Wild-type; YPD: Yeast peptone dextrose.Competing interestsThe authors declare that they have no competing interests.Authors’ contributionsJMHG, LJF, and JWK conceived of the study and participated in its design.JMHG carried out the quantitative proteomic sample preparation, dataanalysis, and interpretation, the targeted proteomic sample preparation, dataanalysis, and interpretation, validation studies, and drafted the manuscript.DC performed the GO enrichment analyses. MC performed the macrophageassays. NS provided technical assistance for the quantitative proteomicanalysis and data processing. JWK assisted in drafting of the manuscript. Allauthors read and approved the final manuscript.Authors’ informationNot applicable.AcknowledgementsThe authors thank J. Choi for strain construction, and M. Kretschmer, J.Gouw, J. Rogalski, and N. Scott for discussions and technical assistance. Wealso thank D. Oliveira for the collection of mouse samples. 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