Loss of major nutrient sensing and signaling pathways suppresses starvation lethality in electron transport chain mutants.

The electron transport chain (ETC) is a well-studied and highly conserved metabolic pathway that produces ATP through generation of a proton gradient across the inner mitochondrial membrane coupled to oxidative phosphorylation. ETC mutations are associated with a wide array of human disease conditions and to aging-related phenotypes in a number of different organisms. In this study, we sought to better understand the role of the ETC in aging using a yeast model.

A genome-scale yeast library with inducible expression of individual genes.

The ability to switch a gene from off to on and monitor dynamic changes provides a powerful approach for probing gene function and elucidating causal regulatory relationships. Here, we developed and characterized YETI (Yeast Estradiol strains with Titratable Induction), a collection in which > 5,600 yeast genes are engineered for transcriptional inducibility with single-gene precision at their native loci and without plasmids. Each strain contains SGA screening markers and a unique barcode, enabling high-throughput genetics.

A tps1Δ persister-like state in Saccharomyces cerevisiae is regulated by MKT1.

Trehalose metabolism in yeast has been linked to a variety of phenotypes, including heat resistance, desiccation tolerance, carbon-source utilization, and sporulation. The relationships among the several phenotypes of mutants unable to synthesize trehalose are not understood, even though the pathway is highly conserved. One of these phenotypes is that tps1Δ strains cannot reportedly grow on media containing glucose or fructose, even when another carbon source they can use (e.

Learning causal networks using inducible transcription factors and transcriptome-wide time series.

We present IDEA (the Induction Dynamics gene Expression Atlas), a dataset constructed by independently inducing hundreds of transcription factors (TFs) and measuring timecourses of the resulting gene expression responses in budding yeast. Each experiment captures a regulatory cascade connecting a single induced regulator to the genes it causally regulates. We discuss the regulatory cascade of a single TF, Aft1, in detail; however, IDEA contains > 200 TF induction experiments with 20 million individual observations and 100,000 signal-containing dynamic responses.

Dual threshold optimization and network inference reveal convergent evidence from TF binding locations and TF perturbation responses.

A high-confidence map of the direct, functional targets of each transcription factor (TF) requires convergent evidence from independent sources. Two significant sources of evidence are TF binding locations and the transcriptional responses to direct TF perturbations. Systematic data sets of both types exist for yeast and human, but they rarely converge on a common set of direct, functional targets for a TF.