Proteomic profiling of serologic response to Candida albicans during host-commensal and host-pathogen interactions

Candida albicans Hyphal Extracellular Vesicles Are Different from Yeast Ones, Carrying an Active Proteasome Complex and Showing a Different Role in Host Immune Response

Candida albicans is the principal causative agent of lethal fungal infections, predominantly in immunocompromised hosts. Extracellular vesicles (EVs) have been described as crucial in the interaction of microorganisms with their host. Since the yeast-to-hypha transition is an important virulence trait with great impact in invasive candidiasis (IC), we have addressed the characterization of EVs secreted by hyphal cells (HEVs) from C. albicans, comparing them to yeast EVs (YEVs). YEVs comprised a larger population of bigger EVs with mainly cell wall proteins, while HEVs were smaller, in general, and had a much higher protein diversity. YEVs were able to rescue the sensitivity of a cell wall mutant against calcofluor white, presumably due to the larger amount of cell wall proteins they contained. On the other hand, HEVs also contained many cytoplasmic proteins related to protein metabolism and intracellular protein transport and the endosomal sorting complexes required for transport (ESCRT) pathway related to exosome biogenesis, pointing to an intracellular origin of HEVs. Interestingly, an active 20S proteasome complex was secreted exclusively in HEVs. Moreover, HEVs contained a greater number of virulence-related proteins. As for their immunogenic role, both types of EV presented immune reactivity with human sera from patients suffering invasive candidiasis; however, under our conditions, only HEVs showed a cytotoxic effect on human macrophages and could elicit the release of tumor necrosis factor alpha (TNF-α) by these macrophages. IMPORTANCE This first analysis of HEVs of C. albicans has shown clear differences between them and the YEVs of C. albicans, showing their relevance and possible use in the discovery of new diagnostic markers and treatment targets against C. albicans infections. The data obtained point to different mechanisms of biogenesis of YEVs and HEVs, as well as different involvements in cell biology and host interaction. YEVs played a more relevant role in cell wall maintenance, while HEVs were more closely related to virulence, as they had greater effects on human immune cells. Importantly, an active 20S proteosome complex was described as a fungal-EV cargo. A deeper study of its role and those of many other proteins exclusively detected in HEVs and involved in different relevant biological processes of this fungus could open up interesting new areas of research in the battle against C. albicans.

Mass Spectrometry-Based Proteomic and Immunoproteomic Analyses of the Candida albicans Hyphal Secretome Reveal Diagnostic Biomarker Candidates for Invasive Candidiasis

Invasive candidiasis (IC) is associated with high morbidity and mortality in hospitalized patients if not diagnosed early. Long-term use of central venous catheters is a predisposing factor for IC. Hyphal forms of Candida albicans (the major etiological agent of IC) are related to invasion of host tissues. The secreted proteins of hyphae are involved in virulence, host interaction, immune response, and immune evasion. To identify IC diagnostic biomarker candidates, we characterized the C. albicans hyphal secretome by gel-free proteomic analysis, and further assessed the antibody-reactivity patterns to this subproteome in serum pools from 12 patients with non-catheter-associated IC (ncIC), 11 patients with catheter-associated IC (cIC), and 11 non-IC patients. We identified 301 secreted hyphal proteins stratified to stem from the extracellular region, cell wall, cell surface, or intracellular compartments. ncIC and cIC patients had higher antibody levels to the hyphal secretome than non-IC patients. Seven secreted hyphal proteins were identified to be immunogenic (Bgl2, Eno1, Pgk1, Glx3, Sap5, Pra1 and Tdh3). Antibody-reactivity patterns to Bgl2, Eno1, Pgk1 and Glx3 discriminated IC patients from non-IC patients, while those to Sap5, Pra1 and Tdh3 differentiated between cIC and non-IC patients. These proteins may be useful for development of future IC diagnostic tests.

Vultures from different trophic guilds show distinct oral pathogenic yeast signatures and co-occurrence networks

Vultures have evolved adaptive mechanisms to prevent infections associated with their scavenging lifestyle. However, food-borne exposure to antimicrobial pharmaceuticals can promote opportunistic infections with adverse outcomes. Here, we used multivariate and network analyses to increase understanding of the behavior of the yeast communities causing oral mycosis outbreaks recently reported in wild nestling cinereous (Aegypius monachus), griffon (Gyps fulvus) and Egyptian (Neophron percnopterus) vultures (CV, GV and EV, respectively) exposed to antibiotics from livestock farming. Common and unique yeast signatures (of Candida, Debaromyces, Diutina, Meyerozyma, Naganishia, Pichia, Rhodotorula, Trichosporon and Yarrowia species) associated with oral mycoses were identified in the three vulture species. Hierarchical clustering analysis (HCA) and principal component analysis (PCA) highlighted that oral lesions from CV and GV shared similar yeast signatures (of major causative pathogens of opportunistic mycoses, such as Candida albicans, Candida parapsilosis and Candida tropicalis), while EV had a distinct yeast signature (of uncommon pathogenic species, such as Candida dubliniensis, Candida zeylanoides, Pichia fermentans and Rhodotorula spp.). Synergistic interactions between yeast species from distinct fungal phyla were found in lesions from CV and GV, but not in EV. These formed co-occurrence subnetworks with partially or fully connected topology. This study reveals that the composition, assembly and co-occurrence patterns of the yeast communities causing oral mycoses differ between vulture species with distinct feeding habits and scavenging lifestyles. Yeast species widely pathogenic to humans and animals, and yeast co-occurrence relationships, are distinctive hallmarks of oral mycoses in CV and GV. These vulture species are more exposed to antibiotics from intensively medicated livestock carcasses provided in supplementary feeding stations and show higher incidence of thrush-like oral lesions than EV. These findings may be useful for development of new initiatives or changes in the conservation of these avian scavengers affected by anthropogenic activities.

Unified feature association networks through integration of transcriptomic and proteomic data

High-throughput multi-omics studies and corresponding network analyses of multi-omic data have rapidly expanded their impact over the last 10 years. As biological features of different types (e.g. transcripts, proteins, metabolites) interact within cellular systems, the greatest amount of knowledge can be gained from networks that incorporate multiple types of -omic data. However, biological and technical sources of variation diminish the ability to detect cross-type associations, yielding networks dominated by communities comprised of nodes of the same type. We describe here network building methods that can maximize edges between nodes of different data types leading to integrated networks, networks that have a large number of edges that link nodes of different-omic types (transcripts, proteins, lipids etc). We systematically rank several network inference methods and demonstrate that, in many cases, using a random forest method, GENIE3, produces the most integrated networks. This increase in integration does not come at the cost of accuracy as GENIE3 produces networks of approximately the same quality as the other network inference methods tested here. Using GENIE3, we also infer networks representing antibody-mediated Dengue virus cell invasion and receptor-mediated Dengue virus invasion. A number of functional pathways showed centrality differences between the two networks including genes responding to both GM-CSF and IL-4, which had a higher centrality value in an antibody-mediated vs. receptor-mediated Dengue network. Because a biological system involves the interplay of many different types of molecules, incorporating multiple data types into networks will improve their use as models of biological systems. The methods explored here are some of the first to specifically highlight and address the challenges associated with how such multi-omic networks can be assembled and how the greatest number of interactions can be inferred from different data types. The resulting networks can lead to the discovery of new host response patterns and interactions during viral infection, generate new hypotheses of pathogenic mechanisms and confirm mechanisms of disease.

Serum Antibody Profile during Colonization of the Mouse Gut by Candida albicans: Relevance for Protection during Systemic Infection

Candida albicans is a commensal microorganism in the oral cavity and gastrointestinal and urogenital tracts of most individuals that acts as an opportunistic pathogen when the host immune response is reduced. Here, we established different immunocompetent murine models to analyze the antibody responses to the C. albicans proteome during commensalism, commensalism followed by infection, and infection (C, C+I, and I models, respectively). Serum anti-C. albicans IgG antibody levels were higher in colonized mice than in infected mice. The antibody responses during gut commensalism (up to 55 days of colonization) mainly focused on C. albicans proteins involved in stress response and metabolism and differed in both models of commensalism. Different serum IgG antibody-reactivity profiles were also found over time among the three murine models. C. albicans gut colonization protected mice from an intravenous lethal fungal challenge, emphasizing the benefits of fungal gut colonization. This work highlights the importance of fungal gut colonization for future immune prophylactic therapies.

Top-down characterization data on the speciation of the Candida albicans immunome in candidemia

The characterization of pathogen-specific antigenic proteins at the protein species level is crucial in the development and molecular optimization of novel immunodiagnostics, vaccines or immunotherapeutics for infectious diseases. The major requirements to achieve this molecular level are to obtain 100% sequence coverage and identify all post-translational modifications of each antigenic protein species. In this article, we show nearly complete sequence information for five discrete antigenic species of Candida albicans Tdh3 (glyceraldehyde-3-phosphate dehydrogenase), which have been reported to be differentially recognized both among candidemia patients and between candidemia and control patients. A comprehensive description of the top-down immunoproteomic strategy used for seroprofiling at the C. albicans protein species level in candidemia as well as for the chemical characterization of this immunogenic protein (based on high-resolution 2-DE, Western blotting, peptide mass fingerprinting, tandem mass spectrometry and de novo peptide sequencing) is also provided. The top-down characterization data on the speciation of the C. albicans immunome in candidemia presented here are related to our research article entitled “Seroprofiling at the Candida albicans protein species level unveils an accurate molecular discriminator for candidemia” (Pitarch et al., J. Proteomics, 2015, http://dx.doi.org/10.1016/j.jprot.2015.10.022).

A comprehensive Candida albicans PeptideAtlas build enables deep proteome coverage

To provide new and expanded proteome documentation of the opportunistically pathogen Candida albicans, we have developed new protein extraction and analysis routines to provide a new, extended and enhanced version of the C. albicans PeptideAtlas. Two new datasets, resulting from experiments consisting of exhaustive subcellular fractionations and different growing conditions, plus two additional datasets from previous experiments on the surface and the secreted proteomes, have been incorporated to increase the coverage of the proteome. High resolution precursor mass spectrometry (MS) and ion trap tandem MS spectra were analyzed with three different search engines using a database containing allele-specific sequences. This approach, novel for a large-scale C. albicans proteomics project, was combined with the post-processing and filtering implemented in the Trans Proteomic Pipeline consistently used in the PeptideAtlas project and resulted in 49,372 additional peptides (3-fold increase) and 1630 more proteins (1.6-fold increase) identified in the new C. albicans PeptideAtlas with respect to the previous build. A total of 71,310 peptides and 4174 canonical (minimal non-redundant set) proteins (4115 if one protein per pair of alleles is considered) were identified representing 66% of the 6218 proteins in the predicted proteome. This makes the new PeptideAtlas build the most comprehensive C. albicans proteomics resource available and the only large-scale one with detections of individual alleles.

Seroprofiling at the Candida albicans protein species level unveils an accurate molecular discriminator for candidemia

Serum antibodies to specific Candida proteins have been reported as potential diagnostic biomarkers for candidemia. However, their diagnostic usefulness at the protein species level has hardly been examined. Using serological proteome analysis, we explored the IgG-antibody responses to Candida albicans protein species in candidemia and control patients. We found that 87 discrete protein species derived from 34 unique proteins were IgG-targets, although only 43 of them were differentially recognized by candidemia and control sera. An increase in the speciation of the immunome, connectivity and modularity of antigenic species co-recognition networks, and heterogeneity of antigenic species recognition patterns was associated with candidemia. IgG antibodies to certain discrete protein species were better predictors of candidemia than those to their corresponding proteins. A molecular discriminator delineated from the combined fingerprints of IgG antibodies to two distinct species of phosphoglycerate kinase and enolase accurately classified candidemia and control patients. These results provide new insight into the anti-Candida IgG-antibody response development in candidemia, and demonstrate that an immunoproteomic signature at the molecular level may be useful for its diagnosis. Our study further highlights the importance of defining pathogen-specific antigens at the chemical and molecular level for their potential application as immunodiagnostic reagents or even vaccine candidates.

Serum antibody signature directed against Candida albicans Hsp90 and enolase detects invasive candidiasis in non-neutropenic patients

Invasive candidiasis (IC) adds significantly to the morbidity and mortality of non-neutropenic patients if not diagnosed and treated early. To uncover serologic biomarkers that alone or in combination could reliably detect IC in this population, IgG antibody-reactivity profiles to the Candida albicans intracellular proteome were examined by serological proteome analysis (SERPA) and data mining procedures in a training set of 24 non-neutropenic patients. Despite the high interindividual molecular heterogeneity, unsupervised clustering analyses revealed that serum 22-IgG antibody-reactivity patterns differentiated IC from non-IC patients. Univariate analyses further highlighted that 15 out of the 22 SERPA-identified IgG antibodies could be useful candidate IC biomarkers. The diagnostic performance of one of these candidates (anti-Hsp90 IgG antibodies) was validated using an ELISA prototype in a test set of 59 non-neutropenic patients. We then formulated an IC discriminator based on the combined immunoproteomic fingerprints of this and another SERPA-detected and previously validated IC biomarker (anti-Eno1 IgG antibodies) in the training set. Its consistency was substantiated using their ELISA prototypes in the test set. Receiver-operating-characteristic curve analyses showed that this two-biomarker signature accurately identified IC in non-neutropenic patients and provided better IC diagnostic accuracy than the individual biomarkers alone. We conclude that this serum IgG antibody signature directed against C. albicans Hsp90 and Eno1, if confirmed prospectively, may be useful for IC diagnosis in non-neutropenic patients.

Two-dimensional SDS-PAGE fractionation of biological samples for biomarker discovery

Two-dimensional electrophoresis is still a very valuable tool in proteomics, due to its reproducibility and its ability to analyze complete proteins. However, due to its sensitivity to dynamic range issues, its most suitable use in the frame of biomarker discovery is not on very complex fluids such as plasma, but rather on more proximal, simpler fluids such as CSF, urine, or secretome samples. Here, we describe the complete workflow for the analysis of such dilute samples by two-dimensional electrophoresis, starting from sample concentration, then the two-dimensional electrophoresis step per se, ending with the protein detection by fluorescence.

2D-immunoblotting analysis of Sporothrix schenckii cell wall

We utilized two-dimensional gel electrophoresis and immunoblotting (2D-immunoblotting) with anti-Sporothrix schenckii antibodies to identify antigenic proteins in cell wall preparations obtained from the mycelial and yeast-like morphologies of the fungus. Results showed that a 70-kDa glycoprotein (Gp70) was the major antigen detected in the cell wall of both morphologies and that a 60-kDa glycoprotein was present only in yeast-like cells. In addition to the Gp70, the wall from filament cells showed four proteins with molecular weights of 48, 55, 66 and 67 kDa, some of which exhibited several isoforms. To our knowledge, this is the first 2D-immunoblotting analysis of the S. schenckii cell wall.

Forchlorfenuron-mimicking haptens: from immunogen design to antibody characterization by hierarchical clustering analysis

To obtain highly-specific and selective forchlorfenuron binders, a collection of functionalized derivatives with different spacer arm locations and lengths was prepared. By immunization with target-mimicking haptens, a large battery of monoclonal and polyclonal antibodies against this synthetic cell regulator was produced and exhaustively characterized in two immunoassay formats using homologous and heterologous conjugates. Antibodies with IC(50) values lower than 0.3 nM were successfully raised from the prepared immunogens, thus evidencing the efficacy of the explored strategies. In order to identify significant epitopes in the antibody-antigen interaction, a series of new chemical forchlorfenuron analogues, with slight modifications at both rings of the target molecule, were synthesized and evaluated in competitive assays. As a novel approach in hapten recognition studies, data processing was performed by computational classification methods based on hierarchical clustering. This strategy was shown to be highly valuable for a straightforward profiling of antibodies according to analogue recognition patterns. A relationship could be established between the antigen binding properties of antibodies and the structure of the immunogen. Whereas antibodies with equivalent affinities had been obtained from all of the derivatives, their specificity was found to be largely influenced by the differential exposition of the molecule to the immune system.

Staphylococcus aureus seroproteomes discriminate ruminant isolates causing mild or severe mastitis

Staphylococcus aureus is a major cause of mastitis in ruminants. In ewe mastitis, symptoms range from subclinical to gangrenous mastitis. S. aureus factors or host-factors contributing to the different outcomes are not completely elucidated. In this study, experimental mastitis was induced on primiparous ewes using two S. aureus strains, isolated from gangrenous (strain O11) or subclinical (strain O46) mastitis. Strains induced drastically distinct clinical symptoms when tested in ewe and mice experimental mastitis. Notably, they reproduced mild (O46) or severe (O11) mastitis in ewes. Ewe sera were used to identify staphylococcal immunoreactive proteins commonly or differentially produced during infections of variable severity and to define core and accessory seroproteomes. Such SERological Proteome Analysis (SERPA) allowed the identification of 89 immunoreactive proteins, of which only 52 (58.4%) were previously identified as immunogenic proteins in other staphylococcal infections. Among the 89 proteins identified, 74 appear to constitute the core seroproteome. Among the 15 remaining proteins defining the accessory seroproteome, 12 were specific for strain O11, 3 were specific for O46. Distribution of one protein specific for each mastitis severity was investigated in ten other strains isolated from subclinical or clinical mastitis. We report here for the first time the identification of staphylococcal immunogenic proteins common or specific to S. aureus strains responsible for mild or severe mastitis. These findings open avenues in S. aureus mastitis studies as some of these proteins, expressed in vivo, are likely to account for the success of S. aureus as a pathogen of the ruminant mammary gland.

Prediction of the clinical outcome in invasive candidiasis patients based on molecular fingerprints of five anti-Candida antibodies in serum

Better prognostic predictors for invasive candidiasis (IC) are needed to tailor and individualize therapeutic decision-making and minimize its high morbidity and mortality. We investigated whether molecular profiling of IgG-antibody response to the whole soluble Candida proteome could reveal a prognostic signature that may serve to devise a clinical-outcome prediction model for IC and contribute to known IC prognostic factors. By serological proteome analysis and data-mining procedures, serum 31-IgG antibody-reactivity patterns were examined in 45 IC patients randomly split into training and test sets. Within the training cohort, unsupervised two-way hierarchical clustering and principal-component analyses segregated IC patients into two antibody-reactivity subgroups with distinct prognoses that were unbiased by traditional IC prognostic factors and other patients-related variables. Supervised discriminant analysis with leave-one-out cross-validation identified a five-IgG antibody-reactivity signature as the most simplified and accurate IC clinical-outcome predictor, from which an IC prognosis score (ICPS) was derived. Its robustness was confirmed in the test set. Multivariate logistic-regression and receiver-operating-characteristic curve analyses demonstrated that the ICPS was able to accurately discriminate IC patients at high risk for death from those at low risk and outperformed conventional IC prognostic factors. Further validation of the five-IgG antibody-reactivity signature on a multiplexed immunoassay supported the serological proteome analysis results. The five IgG antibodies incorporated in the ICPS made biologic sense and were associated either with good-prognosis and protective patterns (those to Met6p, Hsp90p, and Pgk1p, putative Candida virulence factors and antiapoptotic mediators) or with poor-prognosis and risk patterns (those to Ssb1p and Gap1p/Tdh3p, potential Candida proapoptotic mediators). We conclude that the ICPS, with additional refinement in future larger prospective cohorts, could be applicable to reliably predict patient clinical-outcome for individualized therapy of IC. Our data further provide insights into molecular mechanisms that may influence clinical outcome in IC and uncover potential targets for vaccine design and immunotherapy against IC.

An approach to characterize the membrane proteome of Candida albicans

Evaluation of: Cabezon V, Llama-Palacios A, Nombela C, Monteoliva L, Gil C: Analysis of Candida albicans plasma membrane proteome. Proteomics 9, 4770–4786 (2009). The opportunistic human fungal pathogen Candida albicans causes a wide variety of infections, including deep systemic infection. The C. albicans plasma membrane is an important interface in the host–pathogen relationship. Plasma membrane proteins mediate a variety of functions, including sensing and signaling to the external environment, in which the glycosylphosphatidylinositol (GPI)-anchored membrane proteins play a crucial role. A subproteomic approach to obtain a global picture of the protein composition of the C. albicans plasma membrane was developed, and different strategies were tested in order to extract the largest number of yeast plasma membrane proteins and GPI-anchored membrane proteins. These methods involved protoplast generation, mechanical disruption, ultracentrifugation in sucrose gradients and Na2CO3 treatments. To isolate GPI-anchored proteins two additional steps were performed: two-phase separation and phosphatidylinositol-phospholipase C treatment. After liquid chromatography tandem mass spectrometry analysis using both a MALDI-TOF/TOF and a linear ion trap quadrupole, a total of 214 membrane proteins were identified, including 41 already described as plasma membrane proteins, 20 plasma membrane-associated proteins and 22 proteins with unknown membrane localization. Bioinformatic analysis revealed that this set of C. albicans membrane proteins is highly enriched in proteins involved in biopolymer biosynthesis or transport processes. Furthermore, following phosphatidylinositol-phospholipase C treatment, 12 GPI-anchored membrane proteins were released and identified; most of them are associated with cell wall glucan synthesis and maintenance or are virulence factors, such as phospholipases or aspartyl proteinases.