FungiFun: a web-based application for functional categorization of fungal genes and proteins.

FungiFun assigns functional annotations to fungal genes or proteins and performs gene set enrichment analysis. Based on three different classification methods (FunCat, GO and KEGG), FungiFun categorizes genes and proteins for several fungal species on different levels of annotation detail. It is web-based and accessible to users without any programming skills. FungiFun is the first tool offering gene set enrichment analysis including the FunCat categorization. Two biological datasets for Aspergillus fumigatus and Candida albicans were analyzed using FungiFun, providing an overview of the usage and functions of the tool. FungiFun is freely accessible at https://www.omnifung.hki-jena.de/FungiFun/.

DistanceScan: a tool for promoter modeling.

SUMMARY: The state of the art in promoter modeling for higher eukaryotes is predicting not single transcription factor binding sites (TFBSs), but their combinations. The new tool utilizes a previously developed method of distance distributions of TFBS pairs. We model the random distribution of distances and compare it with the distribution observed in the query sequences. Comparison of the profiles allows filtering out the 'noise' and retaining the potentially functional combinations. This approach has proved its usefulness as a filtering technique for the selection of TFBS pairs for promoter modeling and is now implemented as a tool in R. As an input, it can use the outputs of three different TFBS- and motif-predictive tools (Gibbs Sampler for motifs, Match and MEME/FIMO for PWM-based search). The output is a list of predicted pairs on overrepresented distances with assigned scores, P-values and plots showing the distribution of pairs in the input sequences. AVAILABILITY: The tool is available at https://www.omnifung.hki-jena.de/Rpad/Distance_Scan/index.htm.

On the way toward systems biology of Aspergillus fumigatus infection.

Pathogenicity of Aspergillus fumigatus is multifactorial. Thus, global studies are essential for the understanding of the infection process. Therefore, a data warehouse was established where genome sequence, transcriptome and proteome data are stored. These data are analyzed for the elucidation of virulence determinants. The data analysis workflow starts with pre-processing including imputing of missing values and normalization. Last step is the identification of differentially expressed genes/proteins as interesting candidates for further analysis, in particular for functional categorization and correlation studies. Sequence data and other prior knowledge extracted from databases are integrated to support the inference of gene regulatory networks associated with pathogenicity. This knowledge-assisted data analysis aims at establishing mathematical models with predictive strength to assist further experimental work. Recently, first steps were done to extend the integrative data analysis and computational modeling by evaluating spatio-temporal data (movies) that monitor interactions of A. fumigatus morphotypes (e.g. conidia) with host immune cells.

Missing values in gel-based proteomics.

Gel-based proteomics is a widely applied technique to measure abundances of proteins in various biological systems. Comparison of two or more biological groups involves matching of 2-D gels. Depending on the software, this can result in spots showing missing values on several gels. Most studies ignore this fact or substitute all missing data by zero. Since a couple of years, scientists have realized that this is not the optimal way of analyzing their data and several studies were published presenting methods of imputing missing proteomics data. Most of these methods have already been applied to microarray data before; the phenomenon of missing data is well known in this field, too. With this review, we intend to further raise awareness of the problem of missing values in gel-based proteomics. We summarize reasons for missing values and explore their distribution in data sets. We also provide a comparison and evaluation of hitherto proposed imputation methods for gel-based proteomics data.

Functional genomic profiling of Aspergillus fumigatus biofilm reveals enhanced production of the mycotoxin gliotoxin.

The opportunistic pathogenic mold Aspergillus fumigatus is an increasing cause of morbidity and mortality in immunocompromised and in part immunocompetent patients. A. fumigatus can grow in multicellular communities by the formation of a hyphal network encased in an extracellular matrix. Here, we describe the proteome and transcriptome of planktonic- and biofilm-grown A. fumigatus mycelium after 24 and 48 h. A biofilm- and time-dependent regulation of many proteins and genes of the primary metabolism indicates a developmental stage of the young biofilm at 24 h, which demands energy. At a matured biofilm phase, metabolic activity seems to be reduced. However, genes, which code for hydrophobins, and proteins involved in the biosynthesis of secondary metabolites were significantly upregulated. In particular, proteins of the gliotoxin secondary metabolite gene cluster were induced in biofilm cultures. This was confirmed by real-time PCR and by detection of this immunologically active mycotoxin in culture supernatants using HPLC analysis. The enhanced production of gliotoxin by in vitro formed biofilms reported here may also play a significant role under in vivo conditions. It may confer A. fumigatus protection from the host immune system and also enable its survival and persistence in chronic lung infections such as aspergilloma.

Proteome profiling and functional classification of intracellular proteins from conidia of the human-pathogenic mold Aspergillus fumigatus.

Aspergillus fumigatus is a ubiquitously distributed filamentous fungus that has emerged as one of the most serious life-threatening pathogens in immunocompromised patients. The mechanisms for its pathogenicity are poorly understood. Here, we analyzed the proteome of dormant A. fumigatus conidia as the fungal entity having the initial contact with the host. Applying two-dimensional polyacrylamide gel electrophoresis (2-D PAGE), we established a 2-D reference map of conidial proteins. By MALDI-TOF mass spectrometry, we identified a total number of 449 different proteins. We show that 57 proteins of our map are over-represented in resting conidia compared to mycelium. Enzymes involved in reactive oxygen intermediates (ROI) detoxification, pigment biosynthesis, and conidial rodlet layer formation were highly abundant in A. fumigatus spores and most probably account for their enormous stress resistance. Interestingly, pyruvate decarboxylase and alcohol dehydrogenase were detectable in dormant conidia, suggesting that alcoholic fermentation plays a role during dormancy or early germination. Moreover, we show that enzymes for rapid reactivation of protein biosynthesis and metabolic processes are preserved in resting conidia, which therefore feature the potential to immediately respond to an environmental stimulus by germination. The generated data lay the foundations for further proteomic analyses and a better understanding of fungal pathogenesis.

Integrative analysis of the heat shock response in Aspergillus fumigatus.

BACKGROUND: Aspergillus fumigatus is a thermotolerant human-pathogenic mold and the most common cause of invasive aspergillosis (IA) in immunocompromised patients. Its predominance is based on several factors most of which are still unknown. The thermotolerance of A. fumigatus is one of the traits which have been assigned to pathogenicity. It allows the fungus to grow at temperatures up to and above that of a fevered human host. To elucidate the mechanisms of heat resistance, we analyzed the change of the A. fumigatus proteome during a temperature shift from 30 degrees C to 48 degrees C by 2D-fluorescence difference gel electrophoresis (DIGE). To improve 2D gel image analysis results, protein spot quantitation was optimized by missing value imputation and normalization. Differentially regulated proteins were compared to previously published transcriptome data of A. fumigatus. The study was augmented by bioinformatical analysis of transcription factor binding sites (TFBSs) in the promoter region of genes whose corresponding proteins were differentially regulated upon heat shock. RESULTS: 91 differentially regulated protein spots, representing 64 different proteins, were identified by mass spectrometry (MS). They showed a continuous up-, down- or an oscillating regulation. Many of the identified proteins were involved in protein folding (chaperones), oxidative stress response, signal transduction, transcription, translation, carbohydrate and nitrogen metabolism. A correlation between alteration of transcript levels and corresponding proteins was detected for half of the differentially regulated proteins. Interestingly, some previously undescribed putative targets for the heat shock regulator Hsf1 were identified. This provides evidence for Hsf1-dependent regulation of mannitol biosynthesis, translation, cytoskeletal dynamics and cell division in A. fumigatus. Furthermore, computational analysis of promoters revealed putative binding sites for an AP-2alpha-like transcription factor upstream of some heat shock induced genes. Until now, this factor has only been found in vertebrates. CONCLUSIONS: Our newly established DIGE data analysis workflow yields improved data quality and is widely applicable for other DIGE datasets. Our findings suggest that the heat shock response in A. fumigatus differs from already well-studied yeasts and other filamentous fungi.

Two-dimensional proteome reference maps for the human pathogenic filamentous fungus Aspergillus fumigatus.

The filamentous fungus Aspergillus fumigatus has become the most important airborne fungal pathogen causing life-threatening infections in immunosuppressed patients. We established a 2-D reference map for A. fumigatus. Using MALDI-TOF-MS/MS, we identified 381 spots representing 334 proteins. Proteins involved in cellular metabolism, protein synthesis, transport processes and cell cycle were most abundant. Furthermore, we established a protocol for the isolation of mitochondria of A. fumigatus and developed a mitochondrial proteome reference map. 147 proteins represented by 234 spots were identified.

Differential RelA- and RelB-dependent gene transcription in LTbetaR-stimulated mouse embryonic fibroblasts.

BACKGROUND: Lymphotoxin signaling via the lymphotoxin-beta receptor (LTbetaR) has been implicated in biological processes ranging from development of secondary lymphoid organs, maintenance of spleen architecture, host defense against pathogens, autoimmunity, and lipid homeostasis. The major transcription factor that is activated by LTbetaR crosslinking is NF-kappaB. Two signaling pathways have been described, the classical inhibitor of NF-kappaB alpha (IkappaBalpha)-regulated and the alternative p100-regulated pathway that result in the activation of p50-RelA and p52-RelB NF-kappaB heterodimers, respectively. RESULTS: Using microarray analysis, we investigated the transcriptional response downstream of the LTbetaR in mouse embryonic fibroblasts (MEFs) and its regulation by the RelA and RelB subunits of NF-kappaB. We describe novel LTbetaR-responsive genes that were regulated by RelA and/or RelB. The majority of LTbetaR-regulated genes required the presence of both RelA and RelB, revealing significant crosstalk between the two NF-kappaB activation pathways. Gene Ontology (GO) analysis confirmed that LTbetaR-NF-kappaB target genes are predominantly involved in the regulation of immune responses. However, other biological processes, such as apoptosis/cell death, cell cycle, angiogenesis, and taxis were also regulated by LTbetaR signaling. Moreover, LTbetaR activation inhibited expression of a key adipogenic transcription factor, peroxisome proliferator activated receptor-gamma (pparg), suggesting that LTbetaR signaling may interfere with adipogenic differentiation. CONCLUSION: Microarray analysis of LTbetaR-stimulated fibroblasts provided comprehensive insight into the transcriptional response of LTbetaR signaling and its regulation by the NF-kappaB family members RelA and RelB.

p100 Deficiency is insufficient for full activation of the alternative NF-κB pathway: TNF cooperates with p52-RelB in target gene transcription.

BACKGROUND: Constitutive activation of the alternative NF-κB pathway leads to marginal zone B cell expansion and disorganized spleen microarchitecture. Furthermore, uncontrolled alternative NF-κB signaling may result in the development and progression of cancer. Here, we focused on the question how does the constitutive alternative NF-κB signaling exert its effects in these malignant processes. METHODOLOGY/PRINCIPAL FINDINGS: To explore the consequences of unrestricted alternative NF-κB activation on genome-wide transcription, we compared gene expression profiles of wild-type and NF-κB2/p100-deficient (p100(-/-)) primary mouse embryonic fibroblasts (MEFs) and spleens. Microarray experiments revealed only 73 differentially regulated genes in p100(-/-) vs. wild-type MEFs. Chromatin immunoprecipitation (ChIP) assays showed in p100(-/-) MEFs direct binding of p52 and RelB to the promoter of the Enpp2 gene encoding ENPP2/Autotaxin, a protein with an important role in lymphocyte homing and cell migration. Gene ontology analysis revealed upregulation of genes with anti-apoptotic/proliferative activity (Enpp2/Atx, Serpina3g, Traf1, Rrad), chemotactic/locomotory activity (Enpp2/Atx, Ccl8), and lymphocyte homing activity (Enpp2/Atx, Cd34). Most importantly, biochemical and gene expression analyses of MEFs and spleen, respectively, indicated a marked crosstalk between classical and alternative NF-κB pathways. CONCLUSIONS/SIGNIFICANCE: Our results show that p100 deficiency alone was insufficient for full induction of genes regulated by the alternative NF-κB pathway. Moreover, alternative NF-κB signaling strongly synergized both in vitro and in vivo with classical NF-κB activation, thereby extending the number of genes under the control of the p100 inhibitor of the alternative NF-κB signaling pathway.