Multiomics Approach to Novel Therapeutic Targets for Cancer and Aging-Related Diseases: Role of Sld7 in Yeast Aging Network

A Drug Repurposing and Protein-Protein Interaction Network Study of Ribosomopathies Using Yeast as a Model System

Ribosomopathies result in various cancers, neurodegenerative and viral diseases, and other pathologies such as Diamond-Blackfan anemia and Shwachman-Diamond syndrome. Their pathophysiology at a proteome and functional level remains to be determined. Protein networks and highly connected hub proteins for ribosome biogenesis in Saccharomyces cerevisiae offer a potential as a model system to inform future therapeutic innovation in ribosomopathies. In this context, we report a ribosome biogenesis protein-protein interaction network in S. cerevisiae, created with 1772 proteins and 22,185 physical interactions connecting them. Moreover, by network decomposition analysis, we determined the linear pathways between the transcription factors and target proteins with a view to drug repurposing. While considering only the paths containing the three C/D box proteins (Nop56, Nop58, and Nop1), the most frequently encountered proteins were Aft1, Htz1, Ssa1, Ssb1, Ssb2, Gcn5, Cka1, Tef1, Nop1, Cdc28, Act1, Krr1, Rpl8B, and Tor1, which were then identified as potential drug targets. For drug repurposing, these candidate proteins were further searched in the DrugBank to find other diseases associated with them, as well as the drugs used to treat these diseases. To support the computational results, an experimental study was conducted using in-house manufactured microfluidic bioreactor platform, while the effect of the drug temsirolimus, Tor1 inhibitor, on yeast cells was investigated by following Nop56 protein expression. In conclusion, these results inform the ways in which ribosomopathies and associated common complex human diseases materialize and how drug repurposing might accelerate therapeutic innovation through bioinformatic studies of yeast.

Identification of Novel Components of Target-of-Rapamycin Signaling Pathway by Network-Based Multi-Omics Integrative Analysis

Target of rapamycin (TOR) is a major signaling pathway and regulator of cell growth. TOR serves as a hub of many signaling routes, and is implicated in the pathophysiology of numerous human diseases, including cancer, diabetes, and neurodegeneration. Therefore, elucidation of unknown components of TOR signaling that could serve as potential biomarkers and drug targets has a great clinical importance. In this study, our aim is to integrate transcriptomics, interactomics, and regulomics data in Saccharomyces cerevisiae using a network-based multiomics approach to enlighten previously unidentified, potential components of TOR signaling. We constructed the TOR-signaling protein interaction network, which was used as a template to search for TOR-mediated rapamycin and caffeine signaling paths. We scored the paths passing from at least one component of TOR Complex 1 or 2 (TORC1/TORC2) using the co-expression levels of the genes in the transcriptome data of the cells grown in the presence of rapamycin or caffeine. The resultant network revealed seven hitherto unannotated proteins, namely, Atg14p, Rim20p, Ret2p, Spt21p, Ylr257wp, Ymr295cp, and Ygr017wp, as potential components of TOR-mediated rapamycin and caffeine signaling in yeast. Among these proteins, we suggest further deciphering of the role of Ylr257wp will be particularly informative in the future because it was the only protein whose removal from the constructed network hindered the signal transduction to the TORC1 effector kinase Npr1p. In conclusion, this study underlines the value of network-based multiomics integrative data analysis in discovering previously unidentified components of the signaling networks by revealing potential components of TOR signaling for future experimental validation.