Identification and characterization of protein interactions with the major Niemann-Pick type C disease protein in yeast reveals pathways of therapeutic potential.

Niemann-Pick type C (NP-C) disease is a rare lysosomal storage disease caused by mutations in NPC1 (95% cases) or NPC2 (5% cases). These proteins function together in cholesterol egress from the lysosome, whereby upon mutation, cholesterol and other lipids accumulate causing major pathologies. However, it is not fully understood how cholesterol is transported from NPC1 residing at the lysosomal membrane to the endoplasmic reticulum (ER) and plasma membrane. The yeast ortholog of NPC1, Niemann-Pick type C-related protein-1 (Ncr1), functions similarly to NPC1; when transfected into a mammalian cell lacking NPC1, Ncr1 rescues the diagnostic hallmarks of cholesterol and sphingolipid accumulation. Here, we aimed to identify and characterize protein-protein interactions (PPIs) with the yeast Ncr1 protein. A genome-wide split-ubiquitin membrane yeast two-hybrid (MYTH) protein interaction screen identified 11 ER membrane-localized, full-length proteins interacting with Ncr1 at the lysosomal/vacuolar membrane. These highlight the importance of ER-vacuole membrane interface and include PPIs with the Cyb5/Cbr1 electron transfer system, the ceramide synthase complex, and the Sec61/Sbh1 protein translocation complex. These PPIs were not detected in a sterol auxotrophy condition and thus depend on normal sterol metabolism. To provide biological context for the Ncr1-Cyb5 PPI, a yeast strain lacking this PPI (via gene deletions) exhibited altered levels of sterols and sphingolipids including increased levels of glucosylceramide that mimic NP-C disease. Overall, the results herein provide new physical and genetic interaction models to further use the yeast model of NP-C disease to better understand human NP-C disease.

Phosphoinositide and redox dysregulation by the anticancer methylthioadenosine phosphorylase transition state inhibitor.

Methylthio-DADMe-immucillin-A (MTDIA) is an 86 picomolar inhibitor of 5'-methylthioadenosine phosphorylase (MTAP) with potent and specific anti-cancer efficacy. MTAP salvages S-adenosylmethionine (SAM) from 5'-methylthioadenosine (MTA), a toxic metabolite produced during polyamine biosynthesis. Changes in MTAP expression are implicated in cancer growth and development, making MTAP an appealing target for anti-cancer therapeutics. Since SAM is involved in lipid metabolism, we hypothesised that MTDIA alters the lipidomes of MTDIA-treated cells. To identify these effects, we analysed the lipid profiles of MTDIA-treated Saccharomyces cerevisiae using ultra-high resolution accurate mass spectrometry (UHRAMS). MTAP inhibition by MTDIA, and knockout of the Meu1 gene that encodes for MTAP in yeast, caused global lipidomic changes and differential abundance of lipids involved in cell signaling. The phosphoinositide kinase/phosphatase signaling network was specifically impaired upon MTDIA treatment, and was independently validated and further characterised via altered localization of proteins integral to this network. Functional consequences of dysregulated lipid metabolism included a decrease in reactive oxygen species (ROS) levels induced by MTDIA that was contemporaneous with changes in immunological response factors (nitric oxide, tumour necrosis factor-alpha and interleukin-10) in mammalian cells. These results indicate that lipid homeostasis alterations and concomitant downstream effects may be associated with MTDIA mechanistic efficacy.

Functional genomics and metabolomics advance the ethnobotany of the Samoan traditional medicine "matalafi".

The leaf homogenate of Psychotria insularum is widely used in Samoan traditional medicine to treat inflammation associated with fever, body aches, swellings, wounds, elephantiasis, incontinence, skin infections, vomiting, respiratory infections, and abdominal distress. However, the bioactive components and underlying mechanisms of action are unknown. We used chemical genomic analyses in the model organism Saccharomyces cerevisiae (baker's yeast) to identify and characterize an iron homeostasis mechanism of action in the traditional medicine as an unfractionated entity to emulate its traditional use. Bioactivity-guided fractionation of the homogenate identified two flavonol glycosides, rutin and nicotiflorin, each binding iron in an ion-dependent molecular networking metabolomics analysis. Translating results to mammalian immune cells and traditional application, the iron chelator activity of the P. insularum homogenate or rutin decreased proinflammatory and enhanced anti-inflammatory cytokine responses in immune cells. Together, the synergistic power of combining traditional knowledge with chemical genomics, metabolomics, and bioassay-guided fractionation provided molecular insight into a relatively understudied Samoan traditional medicine and developed methodology to advance ethnobotany.

Erratum: Publisher Correction: Genetic interaction networks mediate individual statin drug response in Saccharomyces cerevisiae.

[This corrects the article DOI: 10.1038/s41540-019-0112-5.].

Genetic interaction networks mediate individual statin drug response in Saccharomyces cerevisiae.

Eukaryotic genetic interaction networks (GINs) are extensively described in the Saccharomyces cerevisiae S288C model using deletion libraries, yet being limited to this one genetic background, not informative to individual drug response. Here we created deletion libraries in three additional genetic backgrounds. Statin response was probed with five queries against four genetic backgrounds. The 20 resultant GINs representing drug-gene and gene-gene interactions were not conserved by functional enrichment, hierarchical clustering, and topology-based community partitioning. An unfolded protein response (UPR) community exhibited genetic background variation including different betweenness genes that were network bottlenecks, and we experimentally validated this UPR community via measurements of the UPR that were differentially activated and regulated in statin-resistant strains relative to the statin-sensitive S288C background. These network analyses by topology and function provide insight into the complexity of drug response influenced by genetic background.