Chemical genomic analysis reveals the interplay between iron chelation, zinc homeostasis, and retromer function in the bioactivity of an ethanol adduct of the feijoa fruit-derived ellagitannin vescalagin.

Nature has been a rich source of pharmaceutical compounds, producing 80% of our currently prescribed drugs. The feijoa plant, Acca sellowiana, is classified in the family Myrtaceae, native to South America, and currently grown worldwide to produce feijoa fruit. Feijoa is a rich source of bioactive compounds with anticancer, anti-inflammatory, antibacterial, and antifungal activities; however, the mechanism of action of these compounds is largely not known. Here, we used chemical genetic analyses in the model organism Saccharomyces cerevisiae to investigate the mechanism of action of a feijoa-derived ethanol adduct of vescalagin (EtOH-vescalagin). Genome-wide barcode sequencing analysis revealed yeast strains lacking genes in iron metabolism, zinc metabolism, retromer function, or mitochondrial function were hypersensitive to 0.3 µM EtOH-vescalagin. This treatment increased expression of iron uptake proteins at the plasma membrane, which was a compensatory response to reduced intracellular iron. Likewise, EtOH-vescalagin increased expression of the Cot1 protein in the vacuolar membrane that transports zinc into the vacuole to prevent cytoplasmic accumulation of zinc. Each individual subunit in the retromer complex was required for the iron homeostatic mechanism of EtOH-vescalagin, while only the cargo recognition component in the retromer complex was required for the zinc homeostatic mechanism. Overexpression of either retromer subunits or high-affinity iron transporters suppressed EtOH-vescalagin bioactivity in a zinc-replete condition, while overexpression of only retromer subunits increased EtOH-vescalagin bioactivity in a zinc-deficient condition. Together, these results indicate that EtOH-vescalagin bioactivity begins with extracellular iron chelation and proceeds with intracellular transport of zinc via the retromer complex. More broadly, this is the first report of a bioactive compound to further characterize the poorly understood interaction between zinc metabolism and retromer function.

Copy number variation alters local and global mutational tolerance.

Copy number variants (CNVs), duplications and deletions of genomic sequences, contribute to evolutionary adaptation but can also confer deleterious effects and cause disease. Whereas the effects of amplifying individual genes or whole chromosomes (i.e., aneuploidy) have been studied extensively, much less is known about the genetic and functional effects of CNVs of differing sizes and structures. Here, we investigated Saccharomyces cerevisiae (yeast) strains that acquired adaptive CNVs of variable structures and copy numbers following experimental evolution in glutamine-limited chemostats. Although beneficial in the selective environment, CNVs result in decreased fitness compared with the euploid ancestor in rich media. We used transposon mutagenesis to investigate mutational tolerance and genome-wide genetic interactions in CNV strains. We find that CNVs increase mutational target size, confer increased mutational tolerance in amplified essential genes, and result in novel genetic interactions with unlinked genes. We validated a novel genetic interaction between different CNVs and BMH1 that was common to multiple strains. We also analyzed global gene expression and found that transcriptional dosage compensation does not affect most genes amplified by CNVs, although gene-specific transcriptional dosage compensation does occur for ∼12% of amplified genes. Furthermore, we find that CNV strains do not show previously described transcriptional signatures of aneuploidy. Our study reveals the extent to which local and global mutational tolerance is modified by CNVs with implications for genome evolution and CNV-associated diseases, such as cancer.

Neural networks enable efficient and accurate simulation-based inference of evolutionary parameters from adaptation dynamics.

The rate of adaptive evolution depends on the rate at which beneficial mutations are introduced into a population and the fitness effects of those mutations. The rate of beneficial mutations and their expected fitness effects is often difficult to empirically quantify. As these 2 parameters determine the pace of evolutionary change in a population, the dynamics of adaptive evolution may enable inference of their values. Copy number variants (CNVs) are a pervasive source of heritable variation that can facilitate rapid adaptive evolution. Previously, we developed a locus-specific fluorescent CNV reporter to quantify CNV dynamics in evolving populations maintained in nutrient-limiting conditions using chemostats. Here, we use CNV adaptation dynamics to estimate the rate at which beneficial CNVs are introduced through de novo mutation and their fitness effects using simulation-based likelihood-free inference approaches. We tested the suitability of 2 evolutionary models: a standard Wright-Fisher model and a chemostat model. We evaluated 2 likelihood-free inference algorithms: the well-established Approximate Bayesian Computation with Sequential Monte Carlo (ABC-SMC) algorithm, and the recently developed Neural Posterior Estimation (NPE) algorithm, which applies an artificial neural network to directly estimate the posterior distribution. By systematically evaluating the suitability of different inference methods and models, we show that NPE has several advantages over ABC-SMC and that a Wright-Fisher evolutionary model suffices in most cases. Using our validated inference framework, we estimate the CNV formation rate at the GAP1 locus in the yeast Saccharomyces cerevisiae to be 10-4.7 to 10-4 CNVs per cell division and a fitness coefficient of 0.04 to 0.1 per generation for GAP1 CNVs in glutamine-limited chemostats. We experimentally validated our inference-based estimates using 2 distinct experimental methods-barcode lineage tracking and pairwise fitness assays-which provide independent confirmation of the accuracy of our approach. Our results are consistent with a beneficial CNV supply rate that is 10-fold greater than the estimated rates of beneficial single-nucleotide mutations, explaining the outsized importance of CNVs in rapid adaptive evolution. More generally, our study demonstrates the utility of novel neural network-based likelihood-free inference methods for inferring the rates and effects of evolutionary processes from empirical data with possible applications ranging from tumor to viral evolution.

Cellular quiescence in budding yeast.

Cellular quiescence, the temporary and reversible exit from proliferative growth, is the predominant state of all cells. However, our understanding of the biological processes and molecular mechanisms that underlie cell quiescence remains incomplete. As with the mitotic cell cycle, budding and fission yeast are preeminent model systems for studying cellular quiescence owing to their rich experimental toolboxes and the evolutionary conservation across eukaryotes of pathways and processes that control quiescence. Here, we review current knowledge of cell quiescence in budding yeast and how it pertains to cellular quiescence in other organisms, including multicellular animals. Quiescence entails large-scale remodeling of virtually every cellular process, organelle, gene expression, and metabolic state that is executed dynamically as cells undergo the initiation, maintenance, and exit from quiescence. We review these major transitions, our current understanding of their molecular bases, and highlight unresolved questions. We summarize the primary methods employed for quiescence studies in yeast and discuss their relative merits. Understanding cell quiescence has important consequences for human disease as quiescent single-celled microbes are notoriously difficult to kill and quiescent human cells play important roles in diseases such as cancer. We argue that research on cellular quiescence will be accelerated through the adoption of common criteria, and methods, for defining cell quiescence. An integrated approach to studying cell quiescence, and a focus on the behavior of individual cells, will yield new insights into the pathways and processes that underlie cell quiescence leading to a more complete understanding of the life cycle of cells. TAKE AWAY: Quiescent cells are viable cells that have reversibly exited the cell cycle Quiescence is induced in response to a variety of nutrient starvation signals Quiescence is executed dynamically through three phases: initiation, maintenance, and exit Quiescence entails large-scale remodeling of gene expression, organelles, and metabolism Single-cell approaches are required to address heterogeneity among quiescent cells.

An evolving view of copy number variants.

Copy number variants (CNVs) are regions of the genome that vary in integer copy number. CNVs, which comprise both amplifications and deletions of DNA sequence, have been identified across all domains of life, from bacteria and archaea to plants and animals. CNVs are an important source of genetic diversity, and can drive rapid adaptive evolution and progression of heritable and somatic human diseases, such as cancer. However, despite their evolutionary importance and clinical relevance, CNVs remain understudied compared to single-nucleotide variants (SNVs). This is a consequence of the inherent difficulties in detecting CNVs at low-to-intermediate frequencies in heterogeneous populations of cells. Here, we discuss molecular methods used to detect CNVs, the limitations associated with using these techniques, and the application of new and emerging technologies that present solutions to these challenges. The goal of this short review and perspective is to highlight aspects of CNV biology that are understudied and define avenues for further research that address specific gaps in our knowledge of these complex alleles. We describe our recently developed method for CNV detection in which a fluorescent gene functions as a single-cell CNV reporter and present key findings from our evolution experiments in Saccharomyces cerevisiae. Using a CNV reporter, we found that CNVs are generated at a high rate and undergo selection with predictable dynamics across independently evolving replicate populations. Many CNVs appear to be generated through DNA replication-based processes that are mediated by the presence of short, interrupted, inverted-repeat sequences. Our results have important implications for the role of CNVs in evolutionary processes and the molecular mechanisms that underlie CNV formation. We discuss the possible extension of our method to other applications, including tracking the dynamics of CNVs in models of human tumors.

Adaptation to diverse nitrogen-limited environments by deletion or extrachromosomal element formation of the GAP1 locus.

To study adaptive evolution in defined environments, we performed evolution experiments with Saccharomyces cerevisiae (yeast) in nitrogen-limited chemostat cultures. We used DNA microarrays to identify copy-number variation associated with adaptation and observed frequent amplifications and deletions at the GAP1 locus. GAP1 encodes the general amino acid permease, which transports amino acids across the plasma membrane. We identified a self-propagating extrachromosomal circular DNA molecule that results from intrachromosomal recombination between long terminal repeats (LTRs) flanking GAP1. Extrachromosomal DNA circles (GAP1(circle)) contain GAP1, the replication origin ARS1116, and a single hybrid LTR derived from recombination between the two flanking LTRs. Formation of the GAP1(circle) is associated with deletion of chromosomal GAP1 (gap1Δ) and production of a single hybrid LTR at the GAP1 chromosomal locus. The GAP1(circle) is selected following prolonged culturing in L-glutamine-limited chemostats in a manner analogous to the selection of oncogenes present on double minutes in human cancers. Clones carrying only the gap1Δ allele were selected under various non-amino acid nitrogen limitations including ammonium, urea, and allantoin limitation. Previous studies have shown that the rate of intrachromosomal recombination between tandem repeats is stimulated by transcription of the intervening sequence. The high level of GAP1 expression in nitrogen-limited chemostats suggests that the frequency of GAP1(circle) and gap1Δ generation may be increased under nitrogen-limiting conditions. We propose that this genomic architecture facilitates evolvability of S. cerevisiae populations exposed to variation in levels and sources of environmental nitrogen.

Predicting cellular growth from gene expression signatures.

Maintaining balanced growth in a changing environment is a fundamental systems-level challenge for cellular physiology, particularly in microorganisms. While the complete set of regulatory and functional pathways supporting growth and cellular proliferation are not yet known, portions of them are well understood. In particular, cellular proliferation is governed by mechanisms that are highly conserved from unicellular to multicellular organisms, and the disruption of these processes in metazoans is a major factor in the development of cancer. In this paper, we develop statistical methodology to identify quantitative aspects of the regulatory mechanisms underlying cellular proliferation in Saccharomyces cerevisiae. We find that the expression levels of a small set of genes can be exploited to predict the instantaneous growth rate of any cellular culture with high accuracy. The predictions obtained in this fashion are robust to changing biological conditions, experimental methods, and technological platforms. The proposed model is also effective in predicting growth rates for the related yeast Saccharomyces bayanus and the highly diverged yeast Schizosaccharomyces pombe, suggesting that the underlying regulatory signature is conserved across a wide range of unicellular evolution. We investigate the biological significance of the gene expression signature that the predictions are based upon from multiple perspectives: by perturbing the regulatory network through the Ras/PKA pathway, observing strong upregulation of growth rate even in the absence of appropriate nutrients, and discovering putative transcription factor binding sites, observing enrichment in growth-correlated genes. More broadly, the proposed methodology enables biological insights about growth at an instantaneous time scale, inaccessible by direct experimental methods. Data and tools enabling others to apply our methods are available at http://function.princeton.edu/growthrate.

Coordination of growth rate, cell cycle, stress response, and metabolic activity in yeast.

We studied the relationship between growth rate and genome-wide gene expression, cell cycle progression, and glucose metabolism in 36 steady-state continuous cultures limited by one of six different nutrients (glucose, ammonium, sulfate, phosphate, uracil, or leucine). The expression of more than one quarter of all yeast genes is linearly correlated with growth rate, independent of the limiting nutrient. The subset of negatively growth-correlated genes is most enriched for peroxisomal functions, whereas positively correlated genes mainly encode ribosomal functions. Many (not all) genes associated with stress response are strongly correlated with growth rate, as are genes that are periodically expressed under conditions of metabolic cycling. We confirmed a linear relationship between growth rate and the fraction of the cell population in the G0/G1 cell cycle phase, independent of limiting nutrient. Cultures limited by auxotrophic requirements wasted excess glucose, whereas those limited on phosphate, sulfate, or ammonia did not; this phenomenon (reminiscent of the "Warburg effect" in cancer cells) was confirmed in batch cultures. Using an aggregate of gene expression values, we predict (in both continuous and batch cultures) an "instantaneous growth rate." This concept is useful in interpreting the system-level connections among growth rate, metabolism, stress, and the cell cycle.

Accumulation of recessive lethal mutations in Saccharomyces cerevisiae mlh1 mismatch repair mutants is not associated with gross chromosomal rearrangements.

We examined mismatch repair (MMR)-defective diploid strains of budding yeast grown for approximately 160 generations to determine whether decreases in spore viability due to the uncovering of recessive lethal mutations correlated with an increase in gross chromosomal rearrangements (GCRs). No GCRs were detected despite dramatic decreases in spore viability, suggesting that frameshift and/or other unrepaired DNA replication lesions play a greater role than chromosomal instability in decreasing viability in MMR-defective strains.