ArticleFrontiers in microbiology2015
Integrated inference and evaluation of host-fungi interaction networks.
Article in Frontiers in microbiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed, 51 citations in OpenAlex.
- Transcriptional Response ofACS biomaterials science & engineering · 2023Article
- The Transcriptome Response to Azole Compounds inJournal of fungi (Basel, Switzerland) · 2023Article
- Decoding the host-pathogen interspecies molecular crosstalk during oral candidiasis in humans: anFrontiers in genetics · 2023Article
- Integrated analysis of SR-like protein kinases Sky1 and Sky2 links signaling networks with transcriptional regulation inFrontiers in cellular and infection microbiology · 2023Article
- Biomarkers of caspofungin resistance inVirulence · 2022Article
- Prediction and validation of host-pathogen interactions by a versatile inference approach usingComputational and structural biotechnology journal · 2022Article
- Article
- Network-based analysis of virulence factors for uncovering Aeromonas veronii pathogenesis.BMC microbiology · 2021Article
- A Molecular Interaction Map ofFrontiers in microbiology · 2021Article
- Comparison of the central human and mouse platelet signaling cascade by systems biological analysis.BMC genomics · 2020Article
- The tapeworm interactome: inferring confidence scored protein-protein interactions from the proteome of Hymenolepis microstoma.BMC genomics · 2020Article
- Sodium New Houttuyfonate InhibitsFrontiers in microbiology · 2020Article
- Comparative analysis of differential proteome-wide protein-protein interaction network ofBiochemistry and biophysics reports · 2019Article
- Interface-Based Structural Prediction of Novel Host-Pathogen Interactions.Methods in molecular biology (Clifton, N.J.) · 2019Article
- PHI-Nets: A Network Resource for Ascomycete Fungal Pathogens to Annotate and Identify Putative Virulence Interacting Proteins and siRNA Targets.Frontiers in microbiology · 2019Article
- Article
- ConnectedAlign: a PPI network alignment method for identifying conserved protein complexes across multiple species.BMC bioinformatics · 2018Article
- Identification of Antifungal Targets Based on Computer Modeling.Journal of fungi (Basel, Switzerland) · 2018Review
- Proteomics ofMolecular & cellular proteomics : MCP · 2018Article
- Prediction of Host-Pathogen Interactions for Helicobacter pylori by Interface Mimicry and Implications to Gastric Cancer.Journal of molecular biology · 2017Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.