TY  - JOUR
A1  - Gupta, Shishir K.
A1  - Srivastava, Mugdha
A1  - Osmanoglu, Özge
A1  - Xu, Zhuofei
A1  - Brakhage, Axel A.
A1  - Dandekar, Thomas
T1  - Aspergillus fumigatus versus genus Aspergillus: conservation, adaptive evolution and specific virulence genes
JF  - Microorganisms
N2  - Aspergillus is an important fungal genus containing economically important species, as well as pathogenic species of animals and plants. Using eighteen fungal species of the genus Aspergillus, we conducted a comprehensive investigation of conserved genes and their evolution. This also allows us to investigate the selection pressure driving the adaptive evolution in the pathogenic species A. fumigatus. Among single-copy orthologs (SCOs) for A. fumigatus and the closely related species A. fischeri, we identified 122 versus 50 positively selected genes (PSGs), respectively. Moreover, twenty conserved genes of unknown function were established to be positively selected and thus important for adaption. A. fumigatus PSGs interacting with human host proteins show over-representation of adaptive, symbiosis-related, immunomodulatory and virulence-related pathways, such as the TGF-β pathway, insulin receptor signaling, IL1 pathway and interfering with phagosomal GTPase signaling. Additionally, among the virulence factor coding genes, secretory and membrane protein-coding genes in multi-copy gene families, 212 genes underwent positive selection and also suggest increased adaptation, such as fungal immune evasion mechanisms (aspf2), siderophore biosynthesis (sidD), fumarylalanine production (sidE), stress tolerance (atfA) and thermotolerance (sodA). These genes presumably contribute to host adaptation strategies. Genes for the biosynthesis of gliotoxin are shared among all the close relatives of A. fumigatus as an ancient defense mechanism. Positive selection plays a crucial role in the adaptive evolution of A. fumigatus. The genome-wide profile of PSGs provides valuable targets for further research on the mechanisms of immune evasion, antimycotic targeting and understanding fundamental virulence processes.
KW  - molecular evolution
KW  - phylogenetic analysis
KW  - adaptation
KW  - recombination
KW  - positive selection
KW  - human pathogenic fungi
KW  - genus Aspergillus
KW  - Aspergillus fumigatus
Y1  - 2021
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-246318
SN  - 2076-2607
VL  - 9
IS  - 10
ER  - 
TY  - JOUR
A1  - Remmele, Christian W.
A1  - Luther, Christian H.
A1  - Balkenhol, Johannes
A1  - Dandekar, Thomas
A1  - Müller, Tobias
A1  - Dittrich, Marcus T.
T1  - Integrated inference and evaluation of host-fungi interaction networks
JF  - Frontiers in Microbiology
N2  - Fungal microorganisms frequently lead to life-threatening infections. Within this group of pathogens, the commensal Candida albicans and the filamentous fungus Aspergillus fumigatus are by far the most important causes of invasive mycoses in Europe. A key capability for host invasion and immune response evasion are specific molecular interactions between the fungal pathogen and its human host. Experimentally validated knowledge about these crucial interactions is rare in literature and even specialized host pathogen databases mainly focus on bacterial and viral interactions whereas information on fungi is still sparse. To establish large-scale host fungi interaction networks on a systems biology scale, we develop an extended inference approach based on protein orthology and data on gene functions. Using human and yeast intraspecies networks as template, we derive a large network of pathogen host interactions (PHI). Rigorous filtering and refinement steps based on cellular localization and pathogenicity information of predicted interactors yield a primary scaffold of fungi human and fungi mouse interaction networks. Specific enrichment of known pathogenicity-relevant genes indicates the biological relevance of the predicted PHI. A detailed inspection of functionally relevant subnetworks reveals novel host fungal interaction candidates such as the Candida virulence factor PLB1 and the anti-fungal host protein APP. Our results demonstrate the applicability of interolog-based prediction methods for host fungi interactions and underline the importance of filtering and refinement steps to attain biologically more relevant interactions. This integrated network framework can serve as a basis for future analyses of high-throughput host fungi transcriptome and proteome data.
KW  - candida genome database
KW  - computational prediction
KW  - potential role
KW  - network inference
KW  - bioinformatics and computational biology
KW  - protein interaction database
KW  - Aspergillus fumigatus
KW  - cell wall
KW  - functional modules
KW  - alzheimers disease
KW  - molecular cloning
KW  - Candida albicans
KW  - pathogen-host interaction (PHI)
KW  - protein-protein interaction
KW  - pathogenicity
KW  - interolog
Y1  - 2015
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-148278
VL  - 6
IS  - 764
ER  -