AiM  Vol.8 No.1 , January 2018
Proteomic Differences between Azole-Susceptible and -Resistant Aspergillus fumigatus Strains
ABSTRACT
Background: Azole-resistance is increasingly reported in Aspergillus fumigatus infections. It remains challenging to rapidly assess antifungal susceptibility to initiate the appropriate therapy. The aim of this study was to map the proteomic differences of azole-susceptible and -resistant strains. Methods: Proteomic studies were performed with ultra-performance liquid chromatography tandem mass-spectrometry (UPLC-MS/MS). Results: UPLC-MS/MS detected 7899 peptides, of which 1792 peptides had a significantly different abundance (p < 0.05) between resistant and susceptible strains. The discriminating proteins were identified and provide an interesting tool for future research into A. fumigatus resistance. Conclusions: UPLC-MS/MS provided proof-of-concept that the proteome of azole-resistant A. fumigatus is diverse enough to serve as a diagnostic tool.

1. Introduction

Triazole resistance in Aspergillus fumigatus is recognized as a cause of therapy failure in patients suffering from Aspergillus diseases [1] . Azole-resistance can occur primarily, when azole-resistant spores present in environmental air are inhaled, or secondary in a patient on long-term antifungal therapy. Aspergillus susceptibility testing in routine laboratory practice is therefore warranted. However, its implementation is cumbersome due to the considerable workload and cost. Another problem microbiologist are facing is the fact that at least 50% of clinical isolates are due to contamination or colonization [2] . The probability that a positive A. fumigatus culture represents a case of invasive aspergillosis (IA) was only 22% in a Spanish university hospital [3] . Susceptibility testing by broth microdilution has a slow turn-around-time (48 h after a pure sporulating culture became available, so at least 72 h after sampling the patient). The recognition of azole-resistance is therefore often a late finding in the management of the individual patient, which is especially unfortunate in the setting of IA. As a result, systematic Aspergillus susceptibility testing is mainly executed in specialized centers for patient care or for surveillance reasons. Screening techniques to detect azole-resistance rapidly, with minimal effort and cost, are highly sought. Currently described options include the subculture of Aspergillus isolates on selective, azole-containing, screening agars [4] or molecular strategies [5] [6] [7] . Subculturing isolates on screening agars achieve a time gain of 24 hours and are less labour intensive compared to conventional broth microdilution. These agars are now commercially available. Molecular techniques have the advantage that resistance detection can theoretically be performed directly on culture-negative samples and is fast, but this is labour intensive and expensive: Batching the samples will be necessary to be feasible, which will also creates longer turn-around times. Real-time PCR approaches will also miss new emerging mutations, or mechanisms not involving the CYP51A gene.

Matrix-assisted laser desorption time-of-flight mass spectrometry (MALDI-TOF MS) has rapidly gained ground in clinical laboratories as a routine method for microbial species identification. The main advantages of this approach are the simplicity, low cost and speed of analysis (identification in minutes) [8] . MALDI-TOF MS separates the proteome of a microorganism on their mass-charge ratio, disclosing a characteristic spectrum. Species identification is obtained by matching this spectrum to a library of reference spectra. A generated spectrum never “matches” with absolute identity; the software expresses the degree of similarity.

MALDI-TOF MS has a potential use in the subtyping of strains [9] or in microbial resistance detection [10] , when distinctive and conserved differences in, respectively, the spectra of the subspecies or in the susceptible and resistant strains can be detected. This is mainly described for beta-lactamase detection in gram-negative bacteria and methicillin resistance in Staphylococcus aureus.

The aim of this study was to provide a proof-of-concept that mass spectrometry can be used to differentiate susceptible from resistant A. fumigatus strains, the trypsin digested proteome of three azole-resistant A. fumigatus strains and of three susceptible A. fumigatus strains, were analyzed in detail via UPLC-MS/MS analysis. This allows quantifying and identifying peptides/proteins specific for resistance or susceptibility.

2. Methods

Fungal Isolates for UPLC-MS/MS analysis―A large Aspergillus culture collection is at our disposal at the National Reference Center for Mycosis, University Hospitals Leuven.

UPLC-MS/MS analysis―Three azole-resistant A. fumigatus strains (1 with CYP51A genotype TR46/Y121F/T289A, 2 TR34/L98H) and three azole-susceptible A. fumigatus strains, randomly chosen from the culture collection, were each subcultured in triplicate on diluted Sabauroud slants, incubated at 37˚C for 48 h and each subculture was extracted independently. Proteins were extracted in acetonitrile (ACN) 50%, formic acid (FA) 35%, as described by Bruker Daltonics (Bremen, Germany) and dried in a vacuum operator until dry. The resulting protein extracts (n = 18) were dissolved in 40 µl 2 M urea, 50 mM ammonium bicarbonate and reduced with 0.020 M dithiotreitol for 15 min and subsequently alkylated with 0.050 M iodoacetamide for 30 min in the dark. Then the sample was digested with 0.01 µg trypsin (Sigma Aldrich) overnight at 37˚C. The digestion was stopped by adding trifluoroacetic acid to a final concentration of 0.5%. Peptides were purified with Pierce C18 Spin Columns (Thermo Scientific), according to the manufacturer, vacuum dried and dissolved in 10 µl of ACN 5%, FA 0.1%. UPLC-MS/MS analysis was performed on a Q Exactive Orbitrap mass spectrometer (Thermo Scientific). Five microliter from each sample was injected and separated on an Ultimate 3000 UPLC system (Dionex, Thermo Scientific). The samples were separated using as buffer A water 99.9%, FA 0.1% and B ACN 80%, water 20%, FA 0.1%, using an EasySpray C18 column (Thermo Scientific) with a gradient of 4% to 10% B (6 min) followed by 10% - 35% B (25 minutes), 35% - 65% B (5 min) and a final elution and re-equilibration step at 95% and 5% B respectively. The flow-rate was set at 300 µL/min. The Q Exactive was operated in positive ion mode (nanospray voltage 1.5 kV, source temperature 250˚C). The instrument was operated in data-dependent acquisition (DDA) mode with a survey MS scan at a resolution of 70,000 for the mass range of m/z 400 - 1600 for precursor ions, followed by MS/MS scans of the top 10 most intense peaks with +2, +3 and +4 charged ions above a threshold ion count of 16,000 at 35,000 resolution using normalized collision energy (NCE) of 25 eV with an isolation window of 3.0 m/z, an apex trigger 5 - 15 sec and a dynamic exclusion of 10 s. All data were acquired with Xcalibur 2.2 software (Thermo Scientific).

Protein identification―The LC-MS raw data were imported to Progenesis Nonlinear software (version 4.1) and peaks were detected on all aligned runs. An mgf file was generated via Progenesis and searched using Mascot (version 2.2.04) in a first round against our in-house database containing all the uniprot sequences of Neosartorya fumigata (containing 20,414 accessions) and additionally against the whole fungal database of Swissprot taxonomy fungi (containing 16,473 accessions). Parameters were set at: tryptic digestion, one miscleavage allowed, 10 ppm precursor mass tolerance and 0.02 Da for fragment ion tolerance with a fixed modification of cysteine carbamidomethylation and a variable modification of methionine oxidation. Subsequently files were imported in Scaffold (version 3) combining the Mascot search with Xtandem. Proteins were considered as identified when they met the criteria: min 95% protein, min 1 peptide 95%. FDR at those criteria was calculated as 0.1% at protein level and 0.4% peptide level.

Protein annotation―The fasta files of all the identified proteins (min 95% protein, min 1 peptide 95%) were exported from Scaffold and were subsequently annotated via Blast2go Version 2.7.0 (http://www.blast2go.com/b2ghome). Data containing an Interpro annotation were exported and introduced in cytoscape (version 3.0.2) to visualize related proteins.

Peptide/protein quantification―As indicated above the LC-MS raw data were imported to Progenesis Nonlinear software and normalized. Peptides were considered as significantly different between the resistant and susceptible condition, when ANOVA p < 0.05. Protein abundance was calculated via progenesis by considering only the peptides with no conflicts. Proteins were considered as significantly different when ANOVA p < 0.05.

Blind clustering of the proteomes―Protein abundances of the ANOVA significant proteins were exported from Progenesis and imported into Statistica 8 (Nine sigma) to perform a Pincipal Component Analysis (PCA) (NonLinear Iterative Partial Least Squares NIPALS algorithm). Scores were exported and visualized using Microsoft Excel.

3. Results

UPLC-MS/MS analysis―A total of 7899 tryptic peptides were detected, of which 22.7% (1792 peptides) had significantly different abundances (p < 0.050) between the resistant and susceptible strains. Only 2082/7899 (26.4%) peptides were identified, belonging to 553 proteins when matched against all species in swissprot. A blind clustering of the most important proteins using Principle Component Analysis (PCA) shows both sample groups can be separated (Figure 1). Principle component 1 (PC1) explains 44% of the observed variability and PC2 12%. The proteins with confident identification (defined as a confidence score ≥ 40.0) which count at least one peptide with significantly differing abundance between the susceptible and resistant strains (112 proteins) are listed in Supplemental Table S1. Among these proteins, 16% (18/112) are ribosomal proteins, 14% (16/112) are involved in stress response or oxidation-reduction, 12% (13/112) in carbohydrate metabolic processes-including four alpha-1,2- mannosidases. Another 5% (6/112) are specifically involved in glucan metabolism. Proteins with uncharacterized function represent 19.6% (22/112). A Pubmed literature search and Aspergillus Genome Database search (AspGD, http://www.aspergillusgenome.org/) was performed for every protein with (a)

Figure 1. Principal component analysis score plot of the most important proteins of triazole resistant and susceptible Aspergillus fumigatus isolates. Black diamonds represent the resistant strains, grey squares the sensitive stains.

significantly different abundant peptide (s) between susceptible and resistant strains (or its orthologs), to evaluate for a known role in virulence, host response, diagnostic properties or antifungal susceptibility. For 29 proteins (26%), relevant information was obtained (Supplemental Table S1); twelve interesting proteins are highlighted in Table 1. No peptides of lanosterol-5α-demethylase, the target protein of azole therapy (encoded by CYP51A), were identified from azole-resistant or-susceptible strains and the known differences in this protein are therefore no contributing factor in the proteomic differences observed here.

4. Discussion

To the best of our knowledge, this is the first study evaluating proteomic differences between triazole susceptible and resistant A. fumigatus isolates based on UPLC-MS/MS analysis. Our approach of comparative proteome analysis provided proof-of-concept that significant proteomic differences exist. These differences were larger than expected, which indicates that susceptible and resistant A. fumigatus probably accumulated mutations over time. However, only a limited fraction of the differentiating peptides could be identified, which demonstrates the constraints of the current databases. Significant abundancy of a protein in one condition can mean that this protein is indeed less abundant in the other condition, but can also mean that certain peptides of this protein bear mutations/polymorphisms and are therefore not identified in the second condition (independent of their abundancy). Among the proteins which have at least one peptide with significantly different abundance between susceptible and resistant strains, about one out of four proteins (or its orthologs) are known to be relevant in azole resistance, virulence or host response (Supplemental Table S1).

Table 1. Proteins with at least one peptide with significantly different abundance in resistant versus susceptible A. fumigatus strains: Highlights.

$Phylome DB database identification [15] . *Condition (susceptible (S) or resistant (R)) with significant abundance of at least one peptide (p < 0.05). The p-values express the minimal level of significance for abundance at the peptide level.

This illustrates the power of comparative proteome analysis to identify interesting targets for research into antimicrobial resistance. Among the differing components, several mitochondrial proteins were detected, involved in stress response (e.g. antigenic mitochondrial protein HSP60, a mitochondrial superoxide dismutase) and also cofilin, which is suggested to play a role in the regulation of mitochondrial function and stress responses and is linked to multi-drug resistance [26] . These data support the hypothesis that mitochondrial activity effects triazole tolerance [27] [28] . Secondly, several conidial proteins (e.g. RodA, RodB, FleA, Arb2, Con-10) and cell-wall modifying enzymes (e.g. glucanases Exg9, EgIC) were also found with significantly different abundances between susceptible and resistant strains. Overall, the identification of many conidial proteins is to be expected as proteomic studies were performed on sporulating strains. A different sporulation rate between resistant or susceptible strains could be an explanation for these different abundances, but could not be objectified visually. A third interesting observation is that many ribosomal proteins are present among the differentiating proteins, which are considered highly conserved intraspecies. This could indicate that the proteome differences reflect a common genomic background of the strains which evolved to azole-resistance. MALDI-TOF MS instruments in clinical laboratories detect proteins in the range of 2000 - 14,000 m/A, which is known to correspond largely with the ribosomal protein fraction.

5. Conclusion

In conclusion, we proved the presence of substantial proteomic differences between azole-susceptible and azole-resistant A. fumigatus strains. We believe that our data provide interesting new options for research into A. fumigatus resistance.

Acknowledgements

JM reports grants and personal fees from Pfizer, grants and personal fees from MSD, personal fees from Astellas, personal fees from Gilead, outside the submitted work. KL reports grants and personal fees from Pfizer, grants and personal fees from Gilead Sciences, grants and personal fees from Merck, outside the submitted work. EV, SC, OK and MS have nothing to disclose.

Supplemental

Table S1. Proteins with at least one peptide with significantly different abundance in resistant versus susceptible A. fumigatus strains.

Vermeulen, E., Carpentier, S., Kniemeyer, O., Sillen, M., Maertens, J. and Lagrou, K. (2018) Proteomic Differences between Azole-Susceptible and -Resistant Aspergillus fumigatus Strains. Advances in Microbiology, 8, 77-99. https://doi.org/10.4236/aim.2018.81007

Cite this paper
Vermeulen, E. , Carpentier, S. , Kniemeyer, O. , Sillen, M. , Maertens, J. and Lagrou, K. (2018) Proteomic Differences between Azole-Susceptible and -Resistant Aspergillus fumigatus Strains. Advances in Microbiology, 8, 77-99. doi: 10.4236/aim.2018.81007.
References
[1]   Fedorova, N.D., Khaldi, N., Joardar, V.S., et al. (2008) Genomic Islands in the Pathogenic Filamentous Fungus Aspergillus fumigatus. PLoS Genetics, 4, e1000046.
https://doi.org/10.1371/journal.pgen.1000046

[2]   Van Pamel, E., Daeseleire, E., De Clercq, N., Herman, L., Verbeken, A., Heyndrickx, M. and Vlaemynck, G. (2012) Restriction Analysis of an Amplified rodA Gene Fragment to Distinguish Aspergillus fumigatus var.ellipticus from Aspergillus fumigatus var.fumigatus. FEMS Microbiology Letters, 333, 153-159.
https://doi.org/10.1111/j.1574-6968.2012.02608.x

[3]   Marti, N., Fonteyne, P.A. and Nolard, N. (2002) Multilocus Sequence Analysis of Aspergillus fumigatus Diversity. Submitted (MAR) to the EMBL/GenBank/DDBJ Databases.

[4]   Aimanianda, V., Bayry, J., Bozza, S., et al. (2009), Surface, Hydrophobin, Prevents, Immune Recognition of Airborne Fungal Spores. Nature, 460, 1117-1121.
https://doi.org/10.1038/nature08264

[5]   Carrion Sde, J., Leal Jr., S.M., Ghannom, M.A., Aimanianda, V., Latgé, J.P. and Pearlman, E. (2013) The Roda Hydrophobin on Aspergillus fumigatus Spores Masks Dectin-1- and Dectin-2-Dependent Responses and Enhances Fungal Survival In Vivo. The Journal of Immunology, 191, 2581-2588.
https://doi.org/10.4049/jimmunol.1300748

[6]   Campoli, P., Perlin, D.S., Kristof, A.S., White, T.C., Filler, S.G. and Sheppard, D.C. (2013) Pharmacokinetics of Posaconazole within Epithelial Cells and Fungi: Insights into Potential Mechanisms of Action during Treatment and Prophylaxis. The Journal of Infectious Diseases, 208, 1717-1728.
https://doi.org/10.1093/infdis/jit358

[7]   Bruns, S., Kniemeyer, O., Hasenberg, M., et al. (2010) Production of Extracellular Traps against Aspergillus fumigatus In Vitro and in Infected Lung Tissue Is Dependent on Invading Neutrophils and Influenced by Hydrophobin RodA. PLoS Pathogens, 6, e1000873.
https://doi.org/10.1371/journal.ppat.1000873

[8]   Nierman, W.C., Pain, A., Anderson, M.J., et al. (2005) Genomic Sequence of the Pathogenic and Allergenic Filamentous Fungus Aspergillus fumigatus. Nature, 438, 1151-1156.
https://doi.org/10.1038/nature04332

[9]   Wood, V., Gwilliam, R., Rajandream, M.A., et al. (2002) The Genome Sequence of Schizosaccharomyces pombe. Nature, 415, 871-880.
https://doi.org/10.1038/nature724

[10]   Silar, P., Koll, F. and Rossignol, M. (1997) Cytosolic Ribosomal Mutations That Abolish Accumulation of Circular Intron in the Mitochondria without Preventing Senescence of Podospora anserina. Genetics, 145, 697-705.

[11]   Galagan, J.E., Calvo, S.E., Cuomo, C., et al. (2005) Sequencing of Aspergillus nidulans and Comparative Analysis with A. fumigatus and A. oryzae. Nature, 438, 1105-1115.
https://doi.org/10.1038/nature04341

[12]   Cerqueira, G.C., Arnaud, M.B., Inglis, D.O., et al. (2013) The Aspergillus Genome Database: Multispecies Curation and Incorporation of RNA-Seq Data to Improve Structural Gene Annotations. Nucleic Acids Research, 42, D705-D710.

[13]   Links, M.G., Dumonceaux, T.J., Hemmingsen, S.M. and Hill, J.E. (2012) The Chaperonin-60 Universal Target Is a Barcode for Bacteria That Enables De Novo Assembly of Metagenomic Sequence Data. PLoS One, 7, e49755.
https://doi.org/10.1371/journal.pone.0049755

[14]   Raggam, R.B., Salzer, H.J., Marth, E., Heiling, B., Paulitsch, A.H. and Buzina, W. (2011) Molecular Detection and Characterisation of Fungal Heat Shock Protein 60. Mycoses, 54, e394-e399.
https://doi.org/10.1111/j.1439-0507.2010.01933.x

[15]   Mittelman, D., Sykoudis, K., Hersh, M., Lin, Y. and Wilson, J.H. (2010) Hsp90 Modulates CAG Repeat Instability in Human Cells. Cell Stress and Chaperones, 15, 753-759.
https://doi.org/10.1007/s12192-010-0191-0

[16]   Gemayel, R., Vinces, M.D., Legendre, M. and Verstrepen, K.J. (2010) Variable Tandem Repeats Accelerate Evolution of Coding and Regulatory Sequences. Annual Review of Genetics, 44, 445-477.
https://doi.org/10.1146/annurev-genet-072610-155046

[17]   Hand, R.A., Jia, N., Bard, M. and Craven, R.J. (2003) Saccharomyces cerevisiae Dap1p, a Novel DNA Damage Response Protein Related to the Mammalian Mem-brane-Associated Progesterone Receptor. Eukaryotic Cell, 2, 306-317.
https://doi.org/10.1128/EC.2.2.306-317.2003

[18]   Hagiwara, D., Takahashi, H., Watanabe, A., Takahashi-Nakaguchi, A., Kawamoto, S., Kamei, K. and Gonoi, T. (2014) Whole-Genome Comparison of Aspergillus fumigatus Strains Serially Isolated from Patients with Aspergillosis. Journal of Clinical Microbiology, 52, 4202-4209.
https://doi.org/10.1128/JCM.01105-14

[19]   Holdom, M.D., Hay, R.J. and Hamilton, A.J. (1996) The Cu,Zn Superoxide Dismutases of Aspergillus flavus, Aspergillus niger, Aspergillus nidulans, and Aspergillus terreus: Purification and Biochemical Comparison with the Aspergillus fumigatus Cu,Zn Superoxide Dismutase. Infection and Immunity, 64, 3326-3332.

[20]   Leal Jr., S.M., Vareechon, C., Cowden, S., Cobb, B.A., Latgé, J.P., Momany, M. and Pearlman, E. (2012) Fungal Antioxidant Pathways Promote Survival against Neutrophils during Infection. The Journal of Clinical Investigation, 122, 2482-2498.
https://doi.org/10.1172/JCI63239

[21]   Lambou, K., Lamarre, C., Beau, R., Dufour, N. and Latge, J.P. (2010) Functional Analysis of the Superoxide Dismutase Family in Aspergillus fumigatus. Molecular Microbiology, 75, 910-923.
https://doi.org/10.1111/j.1365-2958.2009.07024.x

[22]   Abadio, A.K., Kioshima, E.S., Teixeira, M.M., Martins, N.F., Maigret, B. and Felipe, M.S. (2011) Comparative Genomics Allowed the Identification of Drug Targets against Human Fungal Pathogens. BMC Genomics, 12, 75.
https://doi.org/10.1186/1471-2164-12-75

[23]   Shi, L.N., Li, F.Q., Lu, J.F., et al. (2012) Antibody Specific to Thioredoxin Reductase as a New Biomarker for Serodiagnosis of Invasive Aspergillosis in Non-Neutropenic Patients. Clinica Chimica Acta, 413, 938-943.
https://doi.org/10.1016/j.cca.2012.02.011

[24]   Glaser, A.G., Menz, G., Kirsch, A.I., Zeller, S., Crameri, R. and Rhyner, C. (2008) Auto- and Cross-Reactivity to Thioredoxin Allergens in Allergic Bronchopulmonary Aspergillosis. Allergy, 63, 1617-1623.
https://doi.org/10.1111/j.1398-9995.2008.01777.x

[25]   Alarco, A.M. and Raymond, M. (1999) The bZip Transcription Factor Cap1p Is Involved in Multidrug Resistance and Oxidative Stress Response in Candida albicans. Journal of Bacteriology, 181, 700-708.

[26]   Schwienbacher, M., Weig, M., Thies, S., Regula, J.T., Heesemann, J. and Ebel, F. (2005) Analysis of The Major Proteins Secreted by the Human Opportunistic Pathogen Aspergillus fumigatus under In Vitro Conditions. Medical Mycology, 43, 623-630.
https://doi.org/10.1080/13693780500089216

[27]   Sharpton, T.J., Stajich, J.E., Rounsley, S.D., et al. (2009) Comparative Genomic Analyses of the Human Fungal Pathogens Coccidioides and Their Relatives. Genome Research, 19, 1722-1731.
https://doi.org/10.1101/gr.087551.108

[28]   Liu, D., Zhang, R., Yang, X., Zhang, Z., Song, S., Miao, Y. and Shen, Q. (2012) Characterization of a Thermostable β-Glucosidase from Aspergillus fumigatus Z5, and Its Functional Expression in Pichia pastoris X33. Microbial Cell Factories, 11, 25.
https://doi.org/10.1186/1475-2859-11-25

[29]   Potenza, L., Vallerini, D., Barozzi, P., et al. (2013) Characterization of Specific Immune Responses to Different Aspergillus Antigens during the Course of Invasive Aspergillosis in Hematologic Patients. PLoS One, 8, e74326.
https://doi.org/10.1371/journal.pone.0074326

[30]   Zhao, Y., Paderu, P., Park, S., Dukhan, A., Senter, M. and Perlin, D.S. (2012) Expression Turnover Profiling to Monitor the Antifungal Activities of Amphotericin B, Voriconazole, and Micafungin against Aspergillus fumigatus. Antimicrobial Agents and Chemotherapy, 56, 2770-2772.
https://doi.org/10.1128/AAC.06163-11

[31]   Thompson, L.M., Sutherland, P., Steffan, J.S. and McAlister-Henn, L. (1988) Gene Sequence and Primary Structure of Mitochondrial Malate Dehydrogenase from Saccharomyces cerevisiae. Biochemistry, 27, 8393-8400.
https://doi.org/10.1021/bi00422a015

[32]   Zhang, X., Wang, Y., Chi, W., Shi, Y., Chen, S., Lin, D. and Jin, Y. (2014) Metalloprotease Genes of Trichophyton Mentagrophytes Are Important for Pathogenicity. Medical Mycology, 52, 36-45.

[33]   Rappleye, C.A. and Goldman, W.E. (2006) Defining Virulence Genes in the Dimorphic Fungi. Annual Review of Microbiology, 60, 281-303.
https://doi.org/10.1146/annurev.micro.59.030804.121055

[34]   Lessing, F., Kniemeyer, O., Wozniok, I., Loeffler, J., Kurzai, O., Haertl, A. and Brakhage, A.A. (2007) The Aspergillus fumigatus Transcriptional Regulator AfYap1 Represents the Major Regulator for Defense against Reactive Oxygen Intermediates but Is Dispensable for Pathogenicity in an Intranasal Mouse Infection Model. Eukaryotic Cell, 6, 2290-2302.
https://doi.org/10.1128/EC.00267-07

[35]   Asif, A.R., Oellerich, M., Amstrong, V.W., Gross, U. and Reichard, U. (2010) Analysis of the Cellular Aspergillus fumigatus Proteome That Reacts with Sera from Rabbits Developing an Acquired Immunity after Experimental Aspergillosis. Electrophoresis, 31, 1947-1958.
https://doi.org/10.1002/elps.201000015

[36]   Kumar, A., Ahmed, R., Singh, P.K. and Shukla, P.K. (2011) Identification of Virulence Factors and Diagnostic Markers Using Immunosecretome of Aspergillus fumigatus. Journal of Proteomics, 74, 1104-1112.
https://doi.org/10.1016/j.jprot.2011.04.004

[37]   Oosthuizen, J.L., Gomez, P., Ruan, J., Hackett, T.L., Moore, M.M., Knight, D.A. and Tebbutt, S.J. (2011) Dual Organism Transcriptomics of Airway Epithelial Cells Interacting with Conidia of Aspergillus fumigatus. PLoS One, 6, e20527.
https://doi.org/10.1371/journal.pone.0020527

[38]   Da Silva Ferreira, M.E., Malavazi, I., Savoldi, M., et al. (2006) Transcriptome Analysis of Aspergillus fumigatus Exposed to Voriconazole. Current Genetics, 50, 32-44.
https://doi.org/10.1007/s00294-006-0073-2

[39]   Xu, D., Jiang, B., Ketela, T., et al. (2007) Genome-Wide Fitness Test and Mechanism-of-Action Studies of Inhibitory Compounds in Candida albicans. PLoS Pathogens, 3, e92.
https://doi.org/10.1371/journal.ppat.0030092

[40]   Tsitsigiannis, D.I., Bok, J.W., Andes, D., Nielsen, K.F., Frisvad, J.C. and Keller, N.P. (2005) Aspergillus Cyclooxygenase-Like Enzymes Are Associated with Prostaglandin Production and Virulence. Infection and Immunity, 73, 4548-4559.
https://doi.org/10.1128/IAI.73.8.4548-4559.2005

[41]   Li, Y.J. and Jin, C. (2004) Mannosidase I from Aspergillus fumigatus YJ-407. Submitted to the EMBL/GenBank/DDBJ Databases.

[42]   Sugui, J.A., Kim, H.S., Zarember, K.A., Chang, Y.C., Gallin, J.I., Nierman, W.C. and Kwon-Chung, K.J. (2008) Genes Differentially Expressed in Conidia and Hyphae of Aspergillus fumigatus upon Exposure to Human Neutrophils. PLoS One, 3, e2655.
https://doi.org/10.1371/journal.pone.0002655

[43]   Willger, S.D., Puttikamonkul, S., Kim, K.H., et al. (2008) A Sterol-Regulatory Element Binding Protein Is Required for Cell Polarity, Hypoxia Adaptation, Azole Drug Resistance, and Virulence in Aspergillus fumigatus. PLoS Pathogens, 4, e1000200.
https://doi.org/10.1371/journal.ppat.1000200

[44]   Kuboi, S., Ishimaru, T., Tamada, S., Bernard, E.M., Perlin, D.S. and Armstrong, D. (2013) Molecular Characterization of AfuFleA, An L-Fucose-Specific Lectin from Aspergillus fumigatus. Journal of Infection and Chemotherapy, 19, 1021-1028.
https://doi.org/10.1007/s10156-013-0614-9

[45]   Ishimaru, T., Kuboi, S., Bernard, E.M., Tamada, S., Tong, W., Soteropuolos, P., Perlin, D.S. and Armstrong, D. (2002) Aspergillus fumigatus Fucose-Specific Lectin (AFL1) Gene, Complete Cds. Submitted to the EMBL/GenBank/DDBJ databases.

[46]   Houser, J., Komarek, J., Kostlanova, N., et al. (2013) A Soluble Fucose-Specific Lectin from Aspergillus fumigatus Conidia—Structure, Specificity and Possible Role in Fungal Pathogenicity. PLoS One, 8, e83077.
https://doi.org/10.1371/journal.pone.0083077

[47]   Kotiadis, V.N., Leadsham, J.E., Bastow, E.L., et al. (2012) Identification of New Surfaces of Cofilin That Link Mitochondrial Function to the Control of Multi-Drug Resistance. Journal of Cell Science, 125, 2288-2299.
https://doi.org/10.1242/jcs.099390

[48]   Blatzer, M., Barker, B.M., Willger, S.D., et al. (2011) SREBP Coordinates Iron and Ergosterol Homeostasis to Mediate Triazole Drug and Hypoxia Responses in the Human Fungal Pathogen Aspergillus fumigatus. PLoS Genetics, 7, e1002374.
https://doi.org/10.1371/journal.pgen.1002374

[49]   Dujon, B., Sherman, D., Fischer, G., et al. (2004) Genome Evolution in Yeasts. Nature, 430, 35-44.
https://doi.org/10.1038/nature02579

[50]   Tkach, J.M., Yimit, A., Lee, A.Y., et al. (2012) Dissecting DNA Damage Response Pathways by Analysing Protein Localization and Abundance Changes during DNA Replication Stress. Nature Cell Biology, 14, 966-976.
https://doi.org/10.1038/ncb2549

[51]   Rambach, G., Dum, D., Mohsenipour, I., Hagleitner, M., Würzner, R., Lass-Flörl, C. and Speth, C. (2010) Secretion of a Fungal Protease Represents a Complement Evasion Mechanism in Cerebral Aspergillosis. Molecular Immunology, 47, 1438-1449.
https://doi.org/10.1016/j.molimm.2010.02.010

[52]   Behnsen, J., Lessing, F., Schindler, S., et al. (2010) Secreted Aspergillus fumigatus Protease Alp1 Degrades Human Complement Proteins C3, C4, and C5. Infection and Immunity, 78, 3585-3594.
https://doi.org/10.1128/IAI.01353-09

 
 
Top