@article{LutherBrandtVylkovaetal.2023,
  author    = {Luther, Christian H. and Brandt, Philipp and Vylkova, Slavena and Dandekar, Thomas and M{\"u}ller, Tobias and Dittrich, Marcus},
  title     = {Integrated analysis of SR-like protein kinases Sky1 and Sky2 links signaling networks with transcriptional regulation in Candida albicans},
  series = {Frontiers in Cellular and Infection Microbiology},
  volume    = {13},
  journal   = {Frontiers in Cellular and Infection Microbiology},
  issn      = {2235-2988},
  doi       = {10.3389/fcimb.2023.1108235},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-311771},
  year      = {2023},
  abstract  = {Fungal infections are a major global health burden where Candida albicans is among the most common fungal pathogen in humans and is a common cause of invasive candidiasis. Fungal phenotypes, such as those related to morphology, proliferation and virulence are mainly driven by gene expression, which is primarily regulated by kinase signaling cascades. Serine-arginine (SR) protein kinases are highly conserved among eukaryotes and are involved in major transcriptional processes in human and S. cerevisiae. Candida albicans harbors two SR protein kinases, while Sky2 is important for metabolic adaptation, Sky1 has similar functions as in S. cerevisiae. To investigate the role of these SR kinases for the regulation of transcriptional responses in C. albicans, we performed RNA sequencing of sky1Δ and sky2Δ and integrated a comprehensive phosphoproteome dataset of these mutants. Using a Systems Biology approach, we study transcriptional regulation in the context of kinase signaling networks. Transcriptomic enrichment analysis indicates that pathways involved in the regulation of gene expression are downregulated and mitochondrial processes are upregulated in sky1Δ. In sky2Δ, primarily metabolic processes are affected, especially for arginine, and we observed that arginine-induced hyphae formation is impaired in sky2Δ. In addition, our analysis identifies several transcription factors as potential drivers of the transcriptional response. Among these, a core set is shared between both kinase knockouts, but it appears to regulate different subsets of target genes. To elucidate these diverse regulatory patterns, we created network modules by integrating the data of site-specific protein phosphorylation and gene expression with kinase-substrate predictions and protein-protein interactions. These integrated signaling modules reveal shared parts but also highlight specific patterns characteristic for each kinase. Interestingly, the modules contain many proteins involved in fungal morphogenesis and stress response. Accordingly, experimental phenotyping shows a higher resistance to Hygromycin B for sky1Δ. Thus, our study demonstrates that a combination of computational approaches with integration of experimental data can offer a new systems biological perspective on the complex network of signaling and transcription. With that, the investigation of the interface between signaling and transcriptional regulation in C. albicans provides a deeper insight into how cellular mechanisms can shape the phenotype.},
  language  = {en}
}
@article{RemmeleLutherBalkenholetal.2015,
  author    = {Remmele, Christian W. and Luther, Christian H. and Balkenhol, Johannes and Dandekar, Thomas and M{\"u}ller, Tobias and Dittrich, Marcus T.},
  title     = {Integrated inference and evaluation of host-fungi interaction networks},
  series = {Frontiers in Microbiology},
  volume    = {6},
  journal   = {Frontiers in Microbiology},
  number    = {764},
  doi       = {10.3389/fmicb.2015.00764},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-148278},
  year      = {2015},
  abstract  = {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.},
  language  = {en}
}