Novel Interactions between Actin and the Proteasome Revealed by Complex Haploinsufficiency

Saccharomyces cerevisiae has been a powerful model for uncovering the landscape of binary gene interactions through whole-genome screening. Complex heterozygous interactions are potentially important to human genetic disease as loss-of-function alleles are common in human genomes. We have been using complex haploinsufficiency (CHI) screening with the actin gene to identify genes related to actin function and as a model to determine the prevalence of CHI interactions in eukaryotic genomes. Previous CHI screening between actin and null alleles for non-essential genes uncovered ∼240 deleterious CHI interactions. In this report, we have extended CHI screening to null alleles for essential genes by mating a query strain to sporulations of heterozygous knock-out strains. Using an act1Δ query, knock-outs of 60 essential genes were found to be CHI with actin. Enriched in this collection were functional categories found in the previous screen against non-essential genes, including genes involved in cytoskeleton function and chaperone complexes that fold actin and tubulin. Novel to this screen was the identification of genes for components of the TFIID transcription complex and for the proteasome. We investigated a potential role for the proteasome in regulating the actin cytoskeleton and found that the proteasome physically associates with actin filaments in vitro and that some conditional mutations in proteasome genes have gross defects in actin organization. Whole-genome screening with actin as a query has confirmed that CHI interactions are important phenotypic drivers. Furthermore, CHI screening is another genetic tool to uncover novel functional connections. Here we report a previously unappreciated role for the proteasome in affecting actin organization and function

The Repertoire and Dynamics of Evolutionary Adaptations to Controlled Nutrient-Limited Environments in Yeast

The experimental evolution of laboratory populations of microbes provides an opportunity to observe the evolutionary dynamics of adaptation in real time. Until very recently, however, such studies have been limited by our inability to systematically find mutations in evolved organisms. We overcome this limitation by using a variety of DNA microarray-based techniques to characterize genetic changes—including point mutations, structural changes, and insertion variation—that resulted from the experimental adaptation of 24 haploid and diploid cultures of Saccharomyces cerevisiae to growth in either glucose, sulfate, or phosphate-limited chemostats for ∼200 generations. We identified frequent genomic amplifications and rearrangements as well as novel retrotransposition events associated with adaptation. Global nucleotide variation detection in ten clonal isolates identified 32 point mutations. On the basis of mutation frequencies, we infer that these mutations and the subsequent dynamics of adaptation are determined by the batch phase of growth prior to initiation of the continuous phase in the chemostat. We relate these genotypic changes to phenotypic outcomes, namely global patterns of gene expression, and to increases in fitness by 5–50%. We found that the spectrum of available mutations in glucose- or phosphate-limited environments combined with the batch phase population dynamics early in our experiments allowed several distinct genotypic and phenotypic evolutionary pathways in response to these nutrient limitations. By contrast, sulfate-limited populations were much more constrained in both genotypic and phenotypic outcomes. Thus, the reproducibility of evolution varies with specific selective pressures, reflecting the constraints inherent in the system-level organization of metabolic processes in the cell. We were able to relate some of the observed adaptive mutations (e.g., transporter gene amplifications) to known features of the relevant metabolic pathways, but many of the mutations pointed to genes not previously associated with the relevant physiology. Thus, in addition to answering basic mechanistic questions about evolutionary mechanisms, our work suggests that experimental evolution can also shed light on the function and regulation of individual metabolic pathways

SBML Level 3: an extensible format for the exchange and reuse of biological models

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution

Hsp90 shapes protein and RNA evolution to balance trade-offs between protein stability and aggregation

It remains poorly understood whether and how chaperones control protein evolution. Here the authors show how the chaperone Hsp90 shapes the sequence space of its client, poliovirus protein P1, at the polypeptide and RNA level to balance the evolutionary trade-offs between protein stability, aggregation and translation rate