Proteomic characterization of the arsenic response locus in S. cerevisiae

Adaptation of the yeast gene knockout collection is near-perfectly predicted by fitness and diminishing return epistasis

Adaptive evolution of clonally dividing cells and microbes is the ultimate cause of cancer and infectious diseases. The possibility of constraining the adaptation of cell populations, by inhibiting proteins enhancing the evolvability, has therefore attracted interest. However, our current understanding of how genes influence adaptation kinetics is limited, partly because accurately measuring adaptation for many cell populations is challenging. We used a high-throughput adaptive laboratory evolution platform to track the adaptation of >18,000 cell populations corresponding to single-gene deletion strains in the haploid yeast deletion collection. We report that the preadaptation fitness of gene knockouts near-perfectly (R2= 0.91) predicts their adaptation to arsenic, leaving at the most a marginal role for dedicated evolvability gene functions. We tracked the adaptation of another >23,000 gene knockout populations to a diverse range of selection pressures and generalized the almost perfect (R2=0.72-0.98) capacity of preadaptation fitness to predict adaptation. We also reconstructed mutations in FPS1, ASK10, and ARR3, which together account for almost all arsenic adaptation in wild-type cells, in gene deletions covering a broad fitness range and show that the predictability of arsenic adaptation can be understood as a by global epistasis, where excluding arsenic is more beneficial to arsenic unfit cells. The paucity of genes with a meaningful evolvability effect on adaptation diminishes the prospects of developing adjuvant drugs aiming to slow antimicrobial and chemotherapy resistance.

OUP accepted manuscript

In a high-throughput yeast two-hybrid screen of predicted coiled-coil motif interactions in the Saccharomyces cerevisiae proteome, the protein Etp1 was found to interact with the yeast AP-1-like transcription factors Yap8, Yap1 and Yap6. Yap8 plays a crucial role during arsenic stress since it regulates expression of the resistance genes ACR2 and ACR3. The function of Etp1 is not well understood but the protein has been implicated in transcription and protein turnover during ethanol stress, and the etp1∆ mutant is sensitive to ethanol. In this current study, we investigated whether Etp1 is implicated in Yap8-dependent functions. We show that Etp1 is required for optimal growth in the presence of trivalent arsenite and for optimal expression of the arsenite export protein encoded by ACR3. Since Yap8 is the only known transcription factor that regulates ACR3 expression, we investigated whether Etp1 regulates Yap8. Yap8 ubiquitination, stability, nuclear localization and ACR3 promoter association were unaffected in etp1∆ cells, indicating that Etp1 affects ACR3 expression independently of Yap8. Thus, Etp1 impacts gene expression under arsenic and other stress conditions but the mechanistic details remain to be elucidated.

Protein-DNA/RNA Interactions: An Overview of Investigation Methods in the -Omics Era

The fields of application of functional proteomics are not limited to the study of protein–protein interactions; they also extend to those involving protein complexes that bind DNA or RNA. These interactions affect fundamental processes such as replication, transcription, and repair in the case of DNA, as well as transport, translation, splicing, and silencing in the case of RNA. Analytical or preparative experimental approaches, both in vivo and in vitro, have been developed to isolate and identify DNA/RNA binding proteins by exploiting the advantage of the affinity shown by these proteins toward a specific oligonucleotide sequence. The present review proposes an overview of the approaches most commonly employed in proteomics applications for the identification of nucleic acid-binding proteins, such as affinity purification (AP) protocols, EMSA, chromatin purification methods, and CRISPR-based chromatin affinity purification, which are generally associated with mass spectrometry methodologies for the unbiased protein identification.