scholarly journals Pathway redundancy and protein essentiality revealed in the Saccharomyces cerevisiae interaction networks

2007 ◽  
Vol 3 (1) ◽  
pp. 104 ◽  
Author(s):  
Igor Ulitsky ◽  
Ron Shamir
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Interaction Networks ◽  
Protein Essentiality

scholarly journals Master regulators of genetic interaction networks mediating statin drug response in Saccharomyces cerevisiae vary with genetic background

2018 ◽  
Author(s):  
Bede P. Busby ◽  
Eliatan Niktab ◽  
Christina A. Roberts ◽  
Namal V. Coorey ◽  
Jeffrey P. Sheridan ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Genetic Background ◽  
Drug Response ◽  
Genetic Interaction ◽  
Interaction Networks ◽  
Centrality Measures ◽  
Gene Interactions ◽  
Master Regulators ◽  
Insight Into ◽  
Deletion Libraries

ABSTRACTDetermination of genetic interaction networks (GINs) surrounding drug targets identifies buffering genes and provides molecular insight into drug response in individuals. Here we used backcross methodology to create Saccharomyces cerevisiae deletion libraries in three genetic backgrounds resistant to statins, which are additional to the statin-sensitive S288C deletion library that has provided much of what is known about GINs in eukaryotes. Whole genome sequencing and linkage group analysis confirmed the genomic authenticity of the new deletion libraries. Statin response was probed by drug-gene interactions with atorvastatin and cerivastatin treatments, as well as gene-gene interactions with the statin target HMG1 and HMG2 genes or the sterol homeostatic ARV1 gene. The 20 GINs generated from these interactions were not conserved by function or topology across the four genetic backgrounds. Centrality measures and hierarchical agglomerative clustering identified master regulators that if removed collapsed the networks. Community structure distinguished a characteristic early secretory pathway pattern of gene usage in each genetic background. ER stress in statin-resistant backgrounds was buffered by protein folding genes, which was confirmed by reduced activation of the unfolded protein response in statin-resistant backgrounds relative to the statin-sensitive S288C background. These network analyses of new gene deletion libraries provide insight into the complexity of GINs underlying individual drug response.

scholarly journals The Chemical Genetic Interactions of Statin Drugs with Their Target Genes in Saccharomyces cerevisiae

2021 ◽  
Author(s):  
◽  
Bede P Busby
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Target Genes ◽  
Genetic Interaction ◽  
Retrograde Transport ◽  
Interaction Networks ◽  
Query Gene ◽  
Yeast Saccharomyces Cerevisiae ◽  
Chemical Genetic ◽  
Genome Wide ◽  
Statin Drugs

<p>Statins, competitive inhibitors of the rate limiting cholesterol/ergosterol enzymes HMG-CoA reductase (HMG1 and HMG2), are the most widely prescribed human therapeutic drugs. They are effective in lowering cholesterol levels in atherosclerosis and related syndromes. However, statins exhibit a range of pleiotropic side effects whose mechanisms are poorly understood. This study investigates statin pleiotropy by analysis of genetic interaction networks in yeast, Saccharomyces cerevisiae, which shows high homology to mammalian pathways affected by statins. Synthetic genetic array (SGA) analysis allows elucidation of functional genetic networks of genes of interest ("query genes") by  measurement of genetic epistasis in double mutants of the query gene with the genome - wide deletion mutant array of ~4800 non-essential strains. Chemicalgenetic profiling is similar where a SMP may effectively replace the query gene in genome wide epistatic analysis. The genetic interaction networks resulting from use of HMG1 and HMG2 as query genes for SGA analysis were compared to the chemical-genetic profiles of atorvastatin, cerivastatin and lovastatin. The genes ARV1, BTS1, OPI3 displaying phenotypic enhancements (i.e. their deletion caused major growth inhibition) with statins became essential in the presence of all the statins. Two mitochondrial genes, COX17 and MMM1, showed phenotypic suppressions (i.e. their deletion allowed better growth) in common to all three statin drugs. An attractive hypothesis is that major pleiotropic effects of statins could be due to variation in function or expression of these enhancing or suppressing genes. Other processes compensating statin use were also elucidated. For example, when HMG1 and its epistatically interacting genes are shut down by deletion coupled with inhibition of HMG2 with statin, there is strong evidence that the cell attempts to maintain membrane/lipid homeostasis via anterograde and retrograde transport mechanisms, including the mobilisation of lipid storage droplets. To aid refinement of genetic analysis in this and future studies, a more direct phenotypic assay was developed for quantifying ergosterol. Such an assay may be used as a phenotype to map the effect of up - and downstream - genes, or network genes affecting ergosterol levels. This assay was used to quantify ergosterol in a drug - resistant mutant developed by others aiding confirmation of the drug target.</p>

scholarly journals The Chemical Genetic Interactions of Statin Drugs with Their Target Genes in Saccharomyces cerevisiae

2021 ◽  
Author(s):  
◽  
Bede P Busby
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Target Genes ◽  
Genetic Interaction ◽  
Retrograde Transport ◽  
Interaction Networks ◽  
Query Gene ◽  
Yeast Saccharomyces Cerevisiae ◽  
Chemical Genetic ◽  
Genome Wide ◽  
Statin Drugs

<p>Statins, competitive inhibitors of the rate limiting cholesterol/ergosterol enzymes HMG-CoA reductase (HMG1 and HMG2), are the most widely prescribed human therapeutic drugs. They are effective in lowering cholesterol levels in atherosclerosis and related syndromes. However, statins exhibit a range of pleiotropic side effects whose mechanisms are poorly understood. This study investigates statin pleiotropy by analysis of genetic interaction networks in yeast, Saccharomyces cerevisiae, which shows high homology to mammalian pathways affected by statins. Synthetic genetic array (SGA) analysis allows elucidation of functional genetic networks of genes of interest ("query genes") by  measurement of genetic epistasis in double mutants of the query gene with the genome - wide deletion mutant array of ~4800 non-essential strains. Chemicalgenetic profiling is similar where a SMP may effectively replace the query gene in genome wide epistatic analysis. The genetic interaction networks resulting from use of HMG1 and HMG2 as query genes for SGA analysis were compared to the chemical-genetic profiles of atorvastatin, cerivastatin and lovastatin. The genes ARV1, BTS1, OPI3 displaying phenotypic enhancements (i.e. their deletion caused major growth inhibition) with statins became essential in the presence of all the statins. Two mitochondrial genes, COX17 and MMM1, showed phenotypic suppressions (i.e. their deletion allowed better growth) in common to all three statin drugs. An attractive hypothesis is that major pleiotropic effects of statins could be due to variation in function or expression of these enhancing or suppressing genes. Other processes compensating statin use were also elucidated. For example, when HMG1 and its epistatically interacting genes are shut down by deletion coupled with inhibition of HMG2 with statin, there is strong evidence that the cell attempts to maintain membrane/lipid homeostasis via anterograde and retrograde transport mechanisms, including the mobilisation of lipid storage droplets. To aid refinement of genetic analysis in this and future studies, a more direct phenotypic assay was developed for quantifying ergosterol. Such an assay may be used as a phenotype to map the effect of up - and downstream - genes, or network genes affecting ergosterol levels. This assay was used to quantify ergosterol in a drug - resistant mutant developed by others aiding confirmation of the drug target.</p>

scholarly journals Genetic interaction networks mediate individual statin drug response in Saccharomyces cerevisiae

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Bede P. Busby ◽  
Eliatan Niktab ◽  
Christina A. Roberts ◽  
Jeffrey P. Sheridan ◽  
Namal V. Coorey ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Genetic Background ◽  
Drug Response ◽  
Genetic Interaction ◽  
Interaction Networks ◽  
Functional Enrichment ◽  
Network Analyses ◽  
Individual Drug Response ◽  
Statin Drug ◽  
Deletion Libraries

Abstract 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.

scholarly journals Publisher Correction: Genetic interaction networks mediate individual statin drug response in Saccharomyces cerevisiae

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Bede P. Busby ◽  
Eliatan Niktab ◽  
Christina A. Roberts ◽  
Jeffrey P. Sheridan ◽  
Namal V. Coorey ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Drug Response ◽  
Genetic Interaction ◽  
Interaction Networks ◽  
Statin Drug

Anti-Saccharomyces cerevisiae Antibodies in Inflammatory Bowel Disease: a Family Study

2001 ◽  
Vol 36 (2) ◽  
pp. 196-201 ◽  
Author(s):  
F. Seibold ◽  
O. Stich ◽  
R. Hufnagl ◽  
S. Kamil ◽  
M. Scheurlen
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Inflammatory Bowel Disease ◽  
Bowel Disease ◽  
Family Study ◽  
Inflammatory Bowel
Sign in / Sign up

Export Citation Format

Share Document