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The genetic basis of aneuploidy tolerance in wild yeast

  1. James Hose
  2. Leah E Escalante
  3. Katie J Clowers
  4. H Auguste Dutcher
  5. DeElegant Robinson
  6. Venera Bouriakov
  7. Joshua J Coon
  8. Evgenia Shishkova
  9. Audrey P Gasch  Is a corresponding author
  1. University of Wisconsin–Madison, United States
  2. University of Wisconsin-Madison, United States
  3. Great Lakes Bioenergy Research Center, United States
  4. Morgridge Institute for Research, United States
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Cite this article as: eLife 2020;9:e52063 doi: 10.7554/eLife.52063

Abstract

Aneuploidy is highly detrimental during development yet common in cancers and pathogenic fungi – what gives rise to differences in aneuploidy tolerance remains unclear. We previously showed that wild isolates of Saccharomyces cerevisiae tolerate chromosome amplification while laboratory strains used as a model for aneuploid syndromes do not. Here, we mapped the genetic basis to Ssd1, an RNA-binding translational regulator that is functional in wild aneuploids but defective in laboratory strain W303. Loss of SSD1 recapitulates myriad aneuploidy signatures previously taken as eukaryotic responses. We show that aneuploidy tolerance is enabled via a role for Ssd1 in mitochondrial physiology, including binding and regulating nuclear-encoded mitochondrial mRNAs, coupled with a role in mitigating proteostasis stress. Recapitulating ssd1Δ defects with combinatorial drug treatment selectively blocked proliferation of wild-type aneuploids compared to euploids. Our work adds to elegant studies in the sensitized laboratory strain to present a mechanistic understanding of eukaryotic aneuploidy tolerance.

Introduction

Aneuploidy, in which cells carry an abnormal number of one or more chromosomes, is highly detrimental during mammalian development, since amplification of most human chromosomes is inviable during embryogenesis. Imbalanced and especially elevated expression from altered chromosomes is thought to tax cellular proteostasis, both by producing too much protein and when stoichiometric imbalance of interacting proteins disrupts cooperative folding (Donnelly and Storchová, 2015; Oromendia and Amon, 2014; Pavelka and Rancati, 2013). Yet ≥90% of tumors are aneuploid with little detriment and even benefits to cells, and the degree of aneuploidy is associated with poorer patient prognosis (Holland and Cleveland, 2012; Targa and Rancati, 2018). Aneuploidy is also common in several fungal species including fungal pathogens. In fact, chromosome amplification represents a major route to drug resistance in pathogenic infections, when amplification of drug transporters and defense mechanisms promotes drug evasion (Wertheimer et al., 2016; Ni et al., 2013; Bennett et al., 2014). Why aneuploidy is benign or beneficial in some cells but highly deleterious in others is not understood.

The yeast Saccharomyces cerevisiae has been a formidable model to understand why chromosome amplification is toxic in the first place. Several studies characterized suites of aneuploid laboratory strains to understand the mechanisms of aneuploidy toxicity and the effects of chromosomal amplification. In a well-studied laboratory strain, chromosome amplification leads to reduced cell growth, metabolic alterations, altered cell-cycle progression in part through aberrant cyclin regulation, activation of a common transcriptome program regardless of the amplified chromosome, and signatures of protein aggregation and defects clearing misfolded peptides, referred to as proteostasis stress (Torres et al., 2007; Torres et al., 2010; Oromendia et al., 2012; Sheltzer et al., 2012; Thorburn et al., 2013; Dephoure et al., 2014; Dodgson et al., 2016; Brennan et al., 2019). Despite the deleterious effects reported in lab strains, chromosome amplification is beneficial in the right environment and provides a rapid route to phenotypic evolution (Rancati et al., 2008; Pavelka et al., 2010; Yona et al., 2012; Filteau et al., 2015; Fontanillas et al., 2010). This is consistent with the prevalence of chromosome amplification in fungal pathogens emerging after drug-treatment regimens (Ni et al., 2013; Selmecki et al., 2009; Selmecki, 2006).

Studies in laboratory strains have clearly generated important information on the causes and consequences of aneuploidy. However, we previously reported a striking difference among wild isolates: a substantial number of wild strains are naturally aneuploid, in some cases carrying extra copies of multiple chromosomes (Gasch et al., 2016; Hose et al., 2015). Recent large-scale sequencing efforts provide confirmatory evidence, reporting over 20% of sequenced strains as aneuploid, with each of the 16 yeast chromosomes represented across affected strains (Peter et al., 2018). In contrast to well-studied laboratory strain W303, naturally aneuploid yeast show only subtle growth defects, no detectable metabolic differences, and lack evidence of the canonical stress response (Gasch et al., 2016; Hose et al., 2015). The relative tolerance is not a result of adaptation: we showed that naturally euploid strains selected for chromosome amplification also showed relatively mild growth defects, and euploid derivatives of aneuploid isolates grew similarly to the aneuploid parent. Although some strains show variable karyotypes over time, picking up or losing chromosomes during division, chromosome amplification in other strains is generally stable (Gasch et al., 2016). Thus, many wild yeast strains tolerate chromosome amplification whereas W303 cannot.

Here, we mapped the genetic basis for this phenotypic difference, by crossing a naturally aneuploid strain isolated from oak soil, YPS1009 with extra copies of Chromosome XII (Chr12), to laboratory strain W303 carrying an extra copy of Chr12. Mapping and confirmatory genetics reveal that the basis for the difference in aneuploidy tolerance lies in SSD1, encoding an RNA binding protein known to be hypomorphic in W303. Our results point to combinatorial dysfunction in mitochondrial physiology and cytosolic protein homeostasis as the basis for aneuploidy toxicity in ssd1- strains, and in wild-type aneuploids with drug-induced defects. Integrating our results with past yeast and mammalian studies presents a holistic view of eukaryotic responses to chromosome amplification.

Results

To identify the genetic basis of differential aneuploidy tolerance, we crossed a haploid derivative of oak-soil strain YPS1009 disomic for chromosome 12 (YPS1009_Chr12) to W303 disomic for the same chromosome (W303_Chr12, Figure 1A). Haploid F2 segregants all harbor two copies of Chr12 but display quantitatively different growth rates (Figure 1—figure supplement 1). To score aneuploidy sensitivity, we focused on W303_Chr12 phenotypes, namely small colony size, slow growth, and/or propensity of the culture to lose the amplified chromosome during passaging. We realized during tetrad dissection that W303-inherited auxotrophies, especially adenine auxotrophy, influenced aneuploidy tolerance (Figure 1—figure supplement 2A-B). We therefore selected an F2 segregant prototrophic for influential markers (called ‘sp100’), backcrossed it to the tolerant YPS1009_Chr12 parent, and scored aneuploidy sensitivity as above (Figure 1A) to generate pools of aneuploidy-sensitive and aneuploidy-tolerant segregants (Figure 1—figure supplement 2C-D). To control for other genetic influences on growth rate and/or colony size, we also performed a control cross of the euploid parents, generating pools of euploid segregants with small versus large colony sizes (see Materials and methods).

Figure 1 with 5 supplements see all
SSD1 is required for aneuploidy tolerance.

(A) Mapping schema, see Materials and methods. (B) W303 allele frequency across Chr4 in the pool of aneuploidy-sensitive (red) versus -tolerant (blue) B2 segregants or C) small (red) versus large (blue) colony pools from the euploid-control cross. (D) Average and standard deviation of growth rates for denoted strains with amplified chromosomes, indicated above. Number of chromosomes per haploid genome, SSD1 status (Δ, deletion; –, ssd1W303), and star indicating euploid revertant are indicated below. Asterisk, p<0.005, T-test comparing aneuploids with and without SSD1. (E) Average and standard deviation of growth of aneuploid ssd1- strains harboring empty vector (Δ), ssd1W303 (w) or SSD1YPS1009 (Y), relative to the isogenic aneuploid wild type with empty vector (or euploid cells with empty vector in the case of W303 ssd1W303 cells).

Bulk analysis of aneuploidy-sensitive and -tolerant backcrossed segregants revealed a major-effect locus on Chr4 that was nearly fixed for W303 alleles in the aneuploidy-sensitive pool (Figure 1B and Figure 1—figure supplements 3, 4) but not small colonies from a euploid-control cross (Figure 1C, see Materials and methods). The locus spanned SSD1, encoding an RNA-binding protein. This locus harbors a premature stop codon in W303 that deletes 44% of the Ssd1 protein including conserved RNA binding domains (Uesono et al., 1997; Sutton et al., 1991). Ssd1 is best characterized for regulating localization and translation of cell-wall destined mRNAs, delivered by Ssd1 to the growing bud during active growth but to P-bodies for translational silencing following stress or mitotic defects (Jansen et al., 2009; Kurischko et al., 2011a). Ssd1 has also been implicated in a large number of suppressor screens and has a role in aging and quiescence (Miles et al., 2019; Li et al., 2013; Hu et al., 2018). W303 carries a premature stop codon that ablates RNA binding domains, which underlies several phenotypic differences reported between W303 and other strains (Kaeberlein et al., 2004; Moriya and Isono, 1999; Ohyama et al., 2010; Uesono et al., 1994).

Genetic analysis confirmed that SSD1 underlies the difference in aneuploidy tolerance. SSD1 deletion had little effect on the growth of euploid YPS1009 but significantly retarded YPS1009_Chr12 proliferation, comparable to W303_Chr12 (Figure 1D). The phenotype was true in both haploid and diploid versions of the strain (Figure 1—figure supplement 5). Growth rate was restored if cells lost the extra chromosome during passaging (Figure 1D, star) or if SSD1YPS1009 was reintroduced (Figure 1E). To test if Ssd1’s role was exclusive to this genetic background or chromosome amplification, we deleted SSD1 in naturally aneuploid, diploid West African strain tetrasomic for Chr 8 (NCYC110_Chr8) and in a derived aneuploid vineyard strain, KCY40_Chr8 (Hose et al., 2015). SSD1 deletion sensitized cells to chromosome amplification, showing that the effect is independent of genetic background and duplicated chromosome (and is thus also independent of the rDNA locus on Chr 12) (Figure 1D). Reintroducing the YPS1009 allele of SSD1 complemented the aneuploidy sensitivity of multiple strain backgrounds (Figure 1E), whereas the W303 allele provided no complementation in the NCYC110_Chr8 ssd1Δ strain and partial complementation in YPS1009_Chr12 ssd1Δ (Figure 1D). Importantly, expressing the YPS1009 allele in W303_Chr12 largely corrected its sensitivity (with a remaining contribution likely from the adenine auxotrophy, see Figure 1—figure supplement 2B), demonstrating that the ssd1W303 allele is responsible for aneuploidy sensitivity in W303. Thus, Ssd1 plays a generalizable role in tolerating chromosome amplification across multiple strains and chromosome duplications.

Loss of Ssd1 recapitulates multiple signatures of aneuploid W303

W303 studies reported a transcriptomic signature of aneuploidy independent of amplified chromosome identity, but this is not seen in wild aneuploid strains (Torres et al., 2007; Hose et al., 2015). To test dependence on Ssd1, we followed transcriptomes of natural aneuploids and their ssd1Δ derivatives, with or without extra chromosomes. We identified 861 genes with altered expression in both YPS1009_Chr12 ssd1Δ and NCYC110_Chr8 ssd1Δ mutants compared to their isogenic wild-type aneuploids (false discovery rate, FDR < 0.05, Figure 2A). Induced genes showed little change in euploid YPS1009 ssd1Δ but were up-regulated when SSD1 was deleted in the context of Chr12 amplification. NCYC110 showed similar trends, except that in this strain we observed a weak expression signature in euploid ssd1Δ cells that was exacerbated when Chr8 was amplified. Repressed genes included rRNA and tRNA processing and cytokinesis factors, whereas induced genes encompassed the environmental stress response (ESR Gasch et al., 2000), oxidoreductases, carbohydrate and energy metabolism, and genes involved in mitochondrial degradation (p<1e-4, hypergeometric test). This response effectively recapitulates the expression signature seen in W303 aneuploids (Torres et al., 2007, Figure 2A). The response was exacerbated with increasing DNA content in W303 carrying multiple extra chromosomes (Figure 2A). Thus, the previously reported aneuploidy transcriptome signature results from defective Ssd1 function, independent of affected chromosome, exacerbated with additional DNA content, and with some strain-specific nuances.

Figure 2 with 1 supplement see all
SSD1 deletion induces aneuploidy signatures.

(A) Replicate-averaged log2 expression differences for strain comparisons (columns) across 861 genes (rows) differentially expressed in mutant versus wild-type aneuploids, see text. Strains include haploid YPS1009 disomic for Chr12, diploid NCYC110 tetrasomic for Chr 8, or haploid W303 derivatives with different chromosome amplifications. Corresponding data from Torres et al. and average log2 differences in expression of induced genes are shown, where colors indicate strain labels from left. (B–C) Quantification of B) VHL-GFP foci and C) Hsp104-GFP in aneuploid strains. Data represent average and standard error of the mean (SEM) across biological triplicates, p from Fisher’s exact test. (D) Distribution of replicate-averaged fitness costs from high-copy plasmid over-expression in each strain (see Materials and methods).

We wondered if other aneuploidy signatures seen in W303 could be explained by defective Ssd1. In addition to growth delay, aneuploid W303 strains reportedly exhibit larger cell size, altered cyclin Cln2 abundance, delayed G1/S progression, metabolic defects, and signatures of proteotoxicity including protein aggregation and a defect degrading misfolded protein (Torres et al., 2007; Oromendia et al., 2012; Thorburn et al., 2013). While these seminal studies generated important information on aneuploidy toxicity in a sensitized strain, many phenotypes likely result from defective Ssd1. YPS1009_Chr12 ssd1Δ grows slower (Figure 1), produces ~33% higher optical versus cell density indicating larger size, and displays metabolic defects encompassing defective respiratory growth (see Figure 4). We confirmed that Ssd1 binds many cell-cycle transcripts including CLN2 (Supplementary file 2), which is translationally regulated by Ssd1 and explains altered G1/S progression (Ohyama et al., 2010).

Loss of SSD1 also explains proteotoxicity observed for aneuploid strains. First, we followed accumulation of human Von Hippel Lindau (VHL) protein upon over-expression. Because VHL cannot fold in the absence of its interacting proteins in yeast, accumulation of VHL-GFP foci reflects misfolded protein that has yet to be cleared by the proteasome (McClellan et al., 2005; Kaganovich et al., 2008). We found that significantly more YPS1009_Chr12 ssd1Δ cells accumulated VHL-GFP foci compared to wild type (Figure 2B). We also followed the protein disaggregase Hsp104, which binds misfolded and aggregated proteins in discrete protein quality-control centers (Kaganovich et al., 2008; Chernova et al., 2017). Wild-type aneuploids showed no obvious difference in the number of Hsp104-GFP foci compared to euploids (Figure 2C and Figure 2—figure supplement 1), indicating that gross protein aggregation is not a universal feature of aneuploid yeast. However, mutant aneuploids lacking SSD1 showed a higher proportion of cells with Hsp104-GFP foci, and more foci within those cells, compared to wild-type aneuploids (Figure 2C). Ssd1 was previously implicated in protein homeostasis after heat shock (Mir et al., 2009), but our results demonstrate that chromosome amplification in the absence of other stresses is enough to provoke misfolding in ssd1Δ cells. Together, these results show that myriad signatures of W303 aneuploidy can occur due to defective Ssd1.

Ssd1 mutants could be sensitive to specific genes on the amplified chromosomes, or they could have a generalized sensitivity to the burden of extra DNA/protein. To distinguish these models, we transformed YPS1009 strains with a barcoded, high-copy gene over-expression library and measured relative fitness costs after 5 generations of growth (see Materials and methods). Both the euploid and aneuploid ssd1Δ mutants were highly sensitive to the library (Figure 2D): genes that were deleterious in wild type were toxic in the mutant, while many genes with neutral effect in parental strains were deleterious in the absence of SSD1. We cannot exclude a defect maintaining the high-copy 2-micron plasmid (indeed, the mutant cells do not grow well with the empty vector, and Ssd1 is already implicated in plasmid maintenance Uesono et al., 1994). Nonetheless, both the euploid and aneuploid ssd1Δ mutants are highly sensitive to the 2-micron overexpression library.

Ssd1 binds RNAs and alters aneuploid proteomes

We focused on YPS1009 strains to elucidate Ssd1 function in aneuploidy tolerance. Revisiting the YPS1009_Chr12 ssd1Δ transcriptome revealed broader induction of genes, including mRNAs whose proteins localize to subcellular compartments such as mitochondria, ER, vacuole, peroxisome, plasma membrane, and the cell wall (p<1e-4, hypergeometric test). Many of these organelles functionally and physical interact (Scorrano et al., 2019), raising the possibility of broader inter-organelle issues. Consistent with this notion, the ssd1Δ aneuploid also showed transcriptional signatures of the unfolded ER-protein response (Travers et al., 2000) and mitochondrial protein import stress (Weidberg and Amon, 2018) (see Materials and methods).

To test if Ssd1 binds a broader set of mRNAs, we sequenced RNAs recovered from Ssd1 immunoprecipitation (see Materials and methods). The 286 associated mRNAs (FDR < 0.05, Supplementary file 2) were heavily enriched for transcripts encoding cell-wall proteins as expected, but the group was also enriched for cell-cycle regulated mRNAs (including cyclins CLN2 and CLB2/4/5) and those involved in budding, RNA metabolism, and sterol transport (p<1e-4). Myriad other functions were also represented, such as proteins in chromatin regulation, transcription, lipid biogenesis, endocytosis, protein homeostasis, and mitochondrial function, some previously noted (Jansen et al., 2009; Hogan et al., 2008). Interestingly, Ssd1 also bound mRNAs encoding osmotic-response regulators (SLN1, SHO1, MSB2, HOT1), notable since osmotic stress was recently implicated in aneuploidy responses of a different lab strain (Tsai et al., 2019). Ssd1-bound mRNAs were not enriched for those encoded on the amplified chromosome, nor transcripts disproportionately expressed compared to DNA content (Hose et al., 2015), suggesting that the mechanism of aneuploidy tolerance is not through modulation of amplified-gene expression. Most (60%) bound transcripts were not differentially expressed in the aneuploid mutant, downplaying a generalizable role in regulating mRNA abundance. In turn, most mRNAs differentially expressed in the aneuploid mutant are not Ssd1-bound, suggesting widespread secondary responses to the primary defect(s).

Since Ssd1 regulates translation via direct RNA binding (Jansen et al., 2009; Wanless et al., 2014; Kurischko et al., 2011b), we next used quantitative proteomics to measure effects on the cellular proteome. 301 of 3906 measured proteins were more abundant in the aneuploid mutant versus wild type (FDR < 0.05, Figure 3A). Many emerge from induced transcripts; however, a large fraction of proteins was elevated beyond mRNA differences, including cell-wall proteins, nuclear-encoded mitochondrial proteins (p=6e-4, hypergeometric test), and others. Many of these proteins were also elevated in the euploid mutant without significant mRNA changes (Figure 3A). Although there was no enrichment for proteins encoded by Ssd1-bound transcripts, several elevated proteins emerge from Ssd1 targets, including cell-wall transcripts and several nuclear transcripts encoding mitochondrial proteins. For example, UTH1 encoding a mitochondrial protein linked to aging is bound by Ssd1 in our and other studies and is known to be translationally regulated by direct Ssd1 binding at specific mRNA locations (Wanless et al., 2014; Camougrand et al., 2004; Camougrand et al., 2000). Although protein induction was evident in euploid ssd1Δ cells, the defect was exacerbated by Chr12 amplification, with ~4X more Uth1 protein despite little difference in mRNA (Figure 3B). Other mitochondrial proteins emanating from Ssd1-bound mRNAs were also significantly elevated in the ssd1Δ aneuploid, including several mitochondrial ribosomal proteins (Figure 3B). Thus, Ssd1 affects the proteome of aneuploid cells, including from bound transcripts.

Ssd1 affects the proteome in aneuploid YPS1009 cells.

(A) Replicate-averaged log2(fold difference) in abundance across 301 significant proteins (FDR < 0.05) and their corresponding mRNAs (rows) for denoted comparisons (columns), where colors represent the magnitude of change according to the key. The indicated cluster is enriched for mitochondrial proteins and respiration factors (hypergeometric test). (B) Representative Ssd1-bound transcripts from (A).

Ssd1 is important for mitochondrial function and inheritance

Our past work revealed that wild aneuploid strains down-regulate many nuclear encoded mitochondrial transcripts, a response also seen in Down syndrome models (Helguera et al., 2013; Liu et al., 2017), hinting that mitochondrial regulation is important for tolerating chromosome amplification (Hose et al., 2015). In the current work, multiple lines implicated mitochondrial effects in ssd1Δ aneuploids. To explore this, we tested mitochondrial function in YPS1009 strains. We found a synergistic defect between SSD1 deletion and aneuploidy when cells experienced mitochondrial stress. YPS1009_Chr12 ssd1Δ, NCYC110_Chr8 ssd1Δ (Figure 4A), and aneuploid W303 (Hose et al., 2015) were all sensitive to non-fermentable acetate, beyond what is expected from the additive effects of aneuploidy and reduced respiratory growth rate. This demonstrates Ssd1-dependent respiratory dysfunction autonomous of strain background or affected chromosome. YPS1009_Chr12 ssd1Δ cells were also susceptible to sub-lethal doses of carbonyl-cyanide 3-chlorophenylhydrazone (CCCP), which uncouples mitochondrial membrane potential (Figure 4B). Notably, aneuploid ssd1Δ cells were no more sensitive than expected to cell wall or ER stress (Figure 4—figure supplement 1), indicating a specific interaction with mitochondrial challenge. In the process of this work, we discovered that ssd1Δ aneuploid cells also showed a striking difference in mitochondrial morphology. Wild-type YPS1009_Chr12 grew well but harbored many globular mitochondria compared to the euploid tubular shape (Figure 4C). Although the impact of this morphology is not clear, YPS1009_Chr12 ssd1Δ displayed significant differences, including more tubular forms and increased mitochondria fragmentation (Figure 4D). The West African aneuploid did not display globular mitochondria but did display dysfunction (Figure 4A). Thus, ssd1Δ cells show numerous signs of mitochondrial dysfunction compared to wild-type aneuploid cells.

Figure 4 with 1 supplement see all
Ssd1 affects mitochondrial function and morphology.

(A) Average and standard deviation of growth rates for denoted aneuploids versus euploids ± SSD1 in glucose (Glu) or acetate (Ac). Asterisk, p<2e-4, replicate-paired T-test. (B) Average growth rates across CCCP doses. (C) Representative images of rhodamine-B stained mitochondria and D) quantified morphologies for cells with any tubular, any globular, only globular, or fragmented mitochondria (average and SEM, see Materials and methods). p<0.0001, Fisher’s exact test.

We wondered if Ssd1 plays a direct role in mitochondrial function, perhaps by localizing nuclear-encoded mitochondrial mRNAs as it does cell-wall mRNAs. We first scored Ssd1 localization by centrifugation-based cellular fractionation. Ssd1 was reproducibly recovered in the organelle-enriched fraction that was depleted of cytosolic actin but enriched for markers of mitochondria (Cox2), ER (Dpm1), and vacuole (Vph1, Figure 5A), which themselves interact. Attempts to separate the components by immunoprecipitation of Ssd1 from the fractions were not successful. We next followed cellular localization of MMR1 transcript, encoding a bud-mitochondria localized protein involved in mitochondrial inheritance (Itoh et al., 2004), by single-molecule RNA FISH (smFISH, Figure 5B). In most wild-type cells, mother-encoded MMR1 was directed to the nascent bud, before the nucleus migrated. Although scoring precise differences in mRNA patterns was challenging, YPS1009_Chr12 ssd1Δ cells displayed twice as many buds lacking MMR1 as wild-type aneuploids (Figure 5C, p<0.02, Fisher’s exact test). In addition, the mutant showed double the cells lacking mitochondria as indicated by Rhodamine staining (Figure 5D), consistent with a defect in mitochondrial inheritance. It is possible that the mutant suffers from delayed dynamics, rather than fully aberrant localization in individual cells. Other nuclear-encoded mitochondrial mRNAs bound by Ssd1 were too abundant to follow by smFISH and will require further delineation. Nonetheless, together our work shows that Ssd1 associates with organelle fractions that include mitochondria (Figure 5A), binds several nuclear-encoded mitochondrial transcripts (Supplementary file 2), and can influence abundance of mitochondrial proteins (Figure 3B) or localization patterns of bound transcript (Figure 5B–C), consistent with the requirement of SSD1 for proper mitochondrial function in aneuploid cells (Figure 4).

Ssd1 affects mRNA localization.

(A) Representative Western blot showing Ssd1-GFP and markers of mitochondria, ER, and vacuole as detected in organelle-depleted and organelle-enriched fractions from SSD1-GFP or untagged-Ssd1 strains (see Methods). Ssd1 fragments migrating below the expected top band emerge during the fractionation incubations. (B) Representative smFISH showing bud-localized MMR1 transcript in wild-type and ssd1Δ aneuploids. (C) Quantification of percent buds lacking MMR1 from smFISH (see Materials and methods). (D) Percent of cells lacking Rhodamine staining. Histograms represent average and SEM across biological triplicates; *, p<0.02, Fisher’s exact test.

Combinatorial mitochondrial dysfunction and proteostasis stress underlie aneuploidy sensitivity in ssd1Δ cells

A remaining question is why Ssd1 dependence and mitochondrial dysfunction are more severe in aneuploids. We reasoned that underlying ssd1Δ defects are exacerbated by effects of chromosome amplification. One candidate is proteome stress that may emerge from over-production of proteins from the amplified chromosome in the absence of Ssd1-dependent translational silencing, which could tax the proteostatic buffering capacity specifically in the mutant (Donnelly and Storchová, 2015; Oromendia and Amon, 2014; Oromendia et al., 2012). Many recent studies have revealed a connection between mitochondrial function and cytosolic proteome stress: defects in mitochondrial protein import induce cytosolic proteostatic defense mechanisms, and misfolded cytosolic proteins interact with and can even be cleared by mitochondria (Qureshi et al., 2017; Ruan et al., 2017; Wrobel et al., 2015). Furthermore, mitochondrial defects and cytosolic proteostasis stress co-emerge in neurological syndromes, aging, and aneuploidy (Oromendia and Amon, 2014; Helguera et al., 2013; Ruan et al., 2017; Franco-Iborra et al., 2018; Kauppila et al., 2017).

To test the model that synergistic dysfunction underlies aneuploidy sensitivity in ssd1Δ aneuploid yeast, we applied nourseothricin (NTC), among the aminoglycoside drugs that induce mistranslation and protein misfolding (Ling et al., 2012). We confirmed that NTC treatment increased the number of Hsp104-GFP foci in the aneuploid wild type, and discovered that CCCP produced an even stronger effect even though wild-type aneuploids grew well in the drug (Figures 6 and 4B). Wild-type aneuploids were slightly sensitive to NTC, but the mutant was significantly more sensitive, beyond the expected additivity of aneuploidy and NTC response, revealing a synergistic defect induced by the drug in combination with aneuploidy (Figure 6A). The NTC sensitivity suggests that wild-type aneuploids with full length SSD1 can largely buffer proteostasis upon chromosome amplification but may exist near capacity. Mitochondrial defect, protein over-abundance, and mislocalized transcripts/proteins resulting from SSD1 deletion may simply push cells over the edge (see Discussion).

Protein misfolding and mitochondrial dysfunction sensitize aneuploids.

(A) Average and standard deviation of relative growth rates in rich YPD medium or with 1 ug/mL NTC. The expected (Exp, light gray) additive effect was calculated based on the fold-drop in growth rate of NTC-treated euploid cells applied to the wild-type aneuploid growth rate in the absence of NTC. (B) Representative Hsp104-GFP foci triggered by 1 ug/mL NTC or 25 uM CCCP and quantification in YPS1009_Chr12 (average and SEM). (C) Average relative growth rate over three generations for indicated treatments or additive expectation (Exp, paired T-test). (D) Relative final optical density after overnight CCCP + NTC treatment in euploid (Eu) and aneuploid (An) strains (see Materials and methods).

This raised an important prediction: if synergistic defects in mitochondrial function and proteostasis sensitize ssd1Δ cells to chromosome amplification, then combinatorial drug treatment to mimic these defects should selectively target wild-type aneuploids. In fact, this was the case: wild-type euploid and aneuploid cells tolerated short-term CCCP and NTC individually, but when combined aneuploid growth was significantly delayed beyond the euploid strain and the expectation of additive effects (Figure 6C). Longer-term combinatorial drug treatment limited growth of euploid YPS1009 but selectively blocked proliferation in YPS1009_Chr12 (Figure 6D). The effect was persistent across strains and chromosome amplifications: combinatorial treatment halted over-night growth of W303 with duplications of Chr8, Chr10, and Chr16 and NCYC110 carrying extra Chr 8 (although in this strain CCCP was actually protective against NTC toxicity in the euploid cells at the doses used)(Figure 6D).

Discussion

Our work has several major implications for understanding the consequences of aneuploidy and how to modulate them. First, we resolve the discrepancy in the literature between wild and laboratory-strain responses to aneuploidy, by showing that mutation of a single gene explains the phenotypic difference among strains studied here. Many of the yeast phenotypes previously reported as signatures of aneuploidy, including proteostasis defects, metabolic defects, cell-cycle defects, and transcriptome response, can be caused by SSD1 deletion or mutation as seen in the commonly used W303 lab strain. This result explains why wild yeast from our studies, other studied S. cerevisiae strains, and pathogenic fungi do not show major defects upon chromosome amplification – these fungi have mechanisms to tolerate extra chromosomes. Our results underscore the importance of studying multiple strain backgrounds to understand model organism biology. At the same time, although W303 is clearly a sensitized strain we highlight that many important insights have come from its dissection. We propose that integrating our results with past yeast and mammalian studies reconciles to a holistic view of eukaryotic aneuploidy physiology.

Our model posits that Ssd1’s function in translational silencing and mitochondrial physiology enable aneuploidy tolerance in wild yeast. The wild aneuploid strains studied here do not show signs of metabolic or proteostatic stress under standard growth conditions. But mimicking ssd1Δ defects through combinatorial drug treatment sensitizes cells to extra chromosomes, showing that it is indeed combined dysfunction in mitochondria and proteome management that is responsible for aneuploidy sensitivity. We propose that, under normal conditions, wild aneuploids handle the extra chromosome by buffering the effects of gene/protein amplification – yet cells may exist close to their proteostatic buffering capacity. Additional stress on the proteostasis system, due to drugs or SSD1 deletion, pushes cells beyond capacity, thereby limiting fitness.

How does Ssd1 fulfill this function? Ssd1 has a clear role in translational regulation: it localizes to P-bodies during times of stress, suppresses encoded protein abundance via direct RNA binding, and is linked to the reduction of polysomes in aged cells (Jansen et al., 2009; Kurischko et al., 2011a; Hu et al., 2018; Wanless et al., 2014; Kurischko et al., 2011b). Ssd1’s role in mitigating proteostatic stress likely emerges via RNA binding, since the ssd1W303 allele lacks the carboxyl-terminal RNA binding domain (Uesono et al., 1997). A remaining question is if mRNAs bound by Ssd1 are especially relevant to proteome homeostasis. Brennan et al. (2019) recently identified aggregation-prone proteins in aneuploid W303, including proteins encoded on and off the amplified chromosomes. The hypothesis was raised that aggregation may be a beneficial mode of protein-dosage compensation (Brennan et al., 2019). However, that aggregation is a hallmark of ssd1 deficiency, which itself causes aneuploidy sensitivity, argues against a beneficial function of aggregates. Instead, it points to a protective role for Ssd1 in handling aggregation-prone proteins. Consistent with this notion, the set of 22 proteins most prone to aggregation across W303 aneuploids is enriched for proteins encoded by Ssd1-bound transcripts identified in our study (p=0.005, hypergeometric test). Furthermore, as a group, proteins encoded by Ssd1 targets are predicted to display substantially higher fractions of disordered regions (based both on median IUPred score compared to all proteins and the fraction of residues with scores > 0.5, Mann Whitney p<2e-16); the trends remain significant even after disordered cell-wall proteins are removed from consideration. Although details of Ssd1’s function remain to be worked out, these results are consistent with a role for Ssd1 in regulating where and when mRNAs are translated to minimize aggregation and misfolding, and to enable normal cells to handle extra chromosomes.

Our results also reveal that Ssd1 affects mitochondrial physiology in aneuploid cells. Defects in mitochondrial function and cytosolic proteome management have long been linked, in neurological syndromes, aging, and even aneuploidy. Disruption of mitochondrial protein folding, import, and localization induces cytosolic protein stress and triggers cytosolic proteostasis systems (Wrobel et al., 2015; Wang and Chen, 2015; Nargund et al., 2012), consistent with our observation that CCCP induces cytosolic Hsp104 foci (Figure 6B). Conversely, clearance of misfolded cytosolic proteins relies on mitochondria: in addition to providing sufficient ATP for chaperone function, mitochondria can retain and import misfolded cytosolic proteins for sequestration and degradation (Ruan et al., 2017; Zhou et al., 2014). Extreme cytosolic misfolding, for example aggregated Huntington protein, perhaps consequently causes mitochondrial dysfunction (Franco-Iborra et al., 2018; Ocampo et al., 2010). Defects in these processes also co-occur in aneuploid syndromes, which produce altered mitochondrial morphology and function and premature aging phenotypes (Oromendia and Amon, 2014; Bambrick and Fiskum, 2008; Chang and Min, 2005). It is possible that mitochondrial defects in ssd1Δ cells arise as a secondary consequence of Ssd1 dysfunction; however, that Ssd1 binds several nuclear-encoded mitochondrial mRNAs, controls protein abundance of several of them, and purifies with mitochondria-enriched fractions raises the possibility of a more direct function. Given its role in localizing cell-wall mRNAs to the bud neck during division, Ssd1 may play a broader role in localizing and/or handling mitochondrial mRNAs – we provide evidence for one, MMR1, which showed a defect in localization patterns consistent with a defect in mitochondrial inheritance.

Our model that normal wild strains can handle the stress of extra chromosomes but exist near their buffering capacity is compatible with results from other systems. Some, but notably not all, aneuploid mouse and human cell lines show indirect signs of proteome stress, including increased autophagy and sensitivity to 17-AAG that inhibits Hsp90 chaperone (which is also required for proper chromosome segregation, confounding interpretation Chen et al., 2012). However, not all aneuploid lines display these signatures (Santaguida et al., 2015; Stingele et al., 2013; Stingele et al., 2012; Donnelly et al., 2014; Tang et al., 2011) and observed phenotypes are reportedly weaker than seen in W303 aneuploids (Brennan et al., 2019), as predicted by our study. While some phenotypic differences may result from differences in the load and identity of the aneuploid chromosome, another possibility is that proteostasis stress is not a universal feature of aneuploid cells. Rather, it may reflect a variable response influenced by environmental, developmental, or genetic differences in mitochondrial/proteostatic buffering capacity across lines. It has long been known that trisomy 21 produces phenotypes of variable severity in Down syndrome (DS), implicating genetic modifiers that augment tolerance (Antonarakis, 2017). A recent proteomic study showed that proteomes of unrelated DS skin fibroblasts showed some commonalities, including down-regulation of nuclear-encoded mitochondrial proteins, while other responses (such as altered lysosome activity) were variable across unrelated individuals and may thus contribute to variable DS severity (Liu et al., 2017). It is possible that natural genetic variation in wild yeast strains also contributes to natural variation in aneuploidy sensitivity. Interestingly, a recent large-scale genome sequencing study reported at least five truncated SSD1 alleles segregating in yeast populations (Figure 6—source data 1) (Peter et al., 2018). The power of yeast genetics provides an opportunity to identify other modifiers of aneuploidy tolerance.

Ssd1 is orthologous to human Dis3L2 (Heinicke et al., 2007), an RNA binding protein best characterized for its ability to degrade poly-uridylated RNAs targeted for decay by terminal-uridyl transferases (TUTases) (Astuti et al., 2012; Chang et al., 2013; Lubas et al., 2013; Malecki et al., 2013; Morris et al., 2013; Ustianenko et al., 2013). Ssd1 is thought to have lost its catalytic activity (perhaps concomitant with loss of TUTase enzymes from S. cerevisiae; Uesono et al., 1997; Viegas et al., 2015). Dis3L2 was first identified in the causal mapping of Perlman syndrome, characterized by cellular over-growth, and is also implicated in Wilms tumor (Astuti et al., 2012). Dis3L2 shares several features with Ssd1: both can localize to the cytosol and nucleus, both bind RNAs and interact with P-bodies, and ablation of both proteins produces protein inclusion bodies (Astuti et al., 2012; Malecki et al., 2013; Mori et al., 2018; Liu et al., 2018; Thomas et al., 2015). Dis3L2 is also implicated in apoptosis trigged by mitochondrial signals (Liu et al., 2018; Thomas et al., 2015). Remarkably, mutation of Dis3L2 is also linked to aneuploidy: knockdown of Dis3L2 actually increases chromosome instability, leading to chromosome loss and aneuploidy (Astuti et al., 2012). Dissecting its role in aneuploidy syndromes is an exciting avenue for future work.

Materials and methods

Key resources table
Reagent type
(species) or resource
DesignationSource or referenceIdentifierAdditional information
Gene (kanr)kanrYeast Knockout Collection; Horizon DiscoverykanMX
Gene (Klebsiella pneumoniae)hphpAG26; Goldstein AL, McCusker JHhphMX
Gene (Streptomyces noursei)nat1pPKInatMX
Gtrain (Saccharomyces cerevisiae)YPS1009 Mat a Euploid, hoΔ::HYGthis studyAGY731Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009 Mat alpha Euploid, hoΔ::HYGthis studyAGY732Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009_Chr12 Mat a Disome12, hoΔ::HYGthis studyAGY735Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009_Chr12 Mat alpha Disome12, hoΔ::HYGthis studyAGY736Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009 Mat a Euploid, hoΔ::HYG, ssd1Δ::KANthis studyAGY1444Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009_Chr12 Mat a Disome12, hoΔ::HYG, ssd1Δ::KANthis studyAGY1445Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009 Mat a Euploid, hoΔ::HYG, ssd1-Δ2 (KANMX removed)this studyAGY1503Haploid, marker rescued for plasmid expression, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009_Chr12 Mat a Disome12, hoΔ::HYG, ssd1-Δ2 (KANMX removed)this studyAGY1517Haploid, marker rescued for plasmid expression, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009 Mat a Euploid, hoΔ::HYG, SSD1-GFP-SSD1YPS1009-terminator-NATMXthis studyAGY1446Haploid, GFP tagged Ssd1, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009_Chr12 Mat a Disome12, hoΔ::HYG, SSD1-GFP-SSD1YPS1009-terminator-NATMXthis studyAGY1447Haploid, GFP tagged Ssd1, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009 Mat a Euploid, hoΔ::HYG, his3Δ::KANthis studyAGY1504Haploid, his3 deletion enabling HIS3 selection, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009_Chr12 Mat a Disome12, hoΔ::HYG, his3Δ::KANthis studyAGY1505Haploid, his3 deletion enabling HIS3 selection, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009 Mat a Euploid, hoΔ::HYG, his3Δ::KAN, ssd1Δ::KANthis studyAGY1506Haploid, his3 deletion enabling HIS3 selection, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009_Chr12 Mat a Disome12, hoΔ::HYG, his3Δ::KAN, ssd1Δ::KANthis studyAGY1507Haploid, his3 deletion enabling HIS3 selection, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009 Mat a Euploid, hoΔ::HYG, his3Δ::KAN, PET123-GFP-ADH1terminator-HIS3M × 6this studyAGY1513Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009_Chr12 Mat a Disome12, hoΔ::HYG, his3Δ::KAN, PET123-GFP-ADH1terminator-HIS3M × 6this studyAGY1514Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009 Mat a Euploid, hoΔ::HYG, his3Δ::KAN, HSP104-GFP-ADH1terminator-HIS3M × 6this studyAGY1518Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009_Chr12 Mat a Disome12, hoΔ::HYG, his3Δ::KAN, HSP104-GFP-ADH1terminator-HIS3M × 6/HSP104this studyAGY1519Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009 Mat a Euploid, hoΔ::HYG, his3Δ::KAN, ssd1Δ::KAN, HSP104-GFP-ADH1terminator-HIS3M × 6this studyAGY1520Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009_Chr12 Mat a Disome12, hoΔ::HYG, his3Δ::KAN, ssd1Δ::KAN, HSP104-GFP-ADH1terminator-HIS3M × 6/HSP104this studyAGY1521Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)d-YPS1009_Chr12.2n EuploidHose et al.AGY613Diploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)d-YPS1009_Chr12.4n AneuploidHose et al.AGY614Diploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)d-YPS1009_Chr12.2n Euploid, ssd1Δ::KAN/ssd1Δ::KANthis studyAGY1560Diploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)d-YPS1009_Chr12.4n Aneuploid, ssd1Δ::KAN/ssd1Δ::KANthis studyAGY1561Diploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)W303 Mat a Euploid ade2-1 his3-11,15 leu2-3,112 trp1-1 ura3-1 can1-100 Gal+ ade16Δ::KANthis studyAGY1387Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)W303_Chr12 Mat a Disome12 ade2-1 his3-11,15 leu2-3,112 trp1-1 ura3-1 can1-100 Gal+ ade16Δ::KAN/ade16Δ::HYGthis studyAGY768Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)W303 Mat a Euploid ADE2+ his3-11,15 leu2-3,112 trp1-1 ura3-1 can1-100 Gal+ ade16Δ::KANthis studyAGY1388Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)W303_Chr12 Mat a Disome12 ADE2+ his3-11,15 leu2-3,112 trp1-1 ura3-1 can1-100 Gal+ ade16Δ::KAN/ade16Δ::HYGthis studyAGY1389Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)W303 Mat a Euploid ade2-1 his3-11,15 leu2-3,112 trp1-1 ura3-1 can1-100 Gal+this studyAGY103Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)W303_Chr8 Mat a Disome8 ade2-1 his3-11,15 leu2-3,112 trp1-1 ura3-1 can1-100 Gal+this studyAGY1495Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)W303_Chr8-15 Mat a Disome8,15 ade2-1 his3-11,15 leu2-3,112 trp1-1 ura3-1 can1-100 Gal+this studyAGY1496Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)W303_Chr8-10-16 Mat a Disome8,10,16 ade2-1 his3-11,15 leu2-3,112 trp1-1 ura3-1 can1-100 Gal+this studyAGY1497Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009xW303 (sp100) Mat alpha Disome12 trp1-1 ade16Δ::KAN HYG+this studyAGY1548Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)d-NCYC110 EuploidHose et al.AGY729Diploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)d-NCYC110_Chr8-4n AneuploidHose et al.AGY703Diploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)d-NCYC110 Euploid, ssd1Δ::KAN/ssd1Δ::KANthis studyAGY1493Diploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)d-NCYC110_Chr8-4n Aneuploid, ssd1Δ::KAN/ssd1Δ::KANthis studyAGY1494Diploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)KCY40 (or VC580) Euploid, hoΔ::MFAprom-HYGMX-NATMXHose et al.AGY806Haploid
Strain (Saccharomyces cerevisiae)KCY40 (or VC580) Disome8, hoΔ::MFAprom-HYGMX-NATMXHose et al.AGY1105Haploid
Strain (Saccharomyces cerevisiae)KCY40 (or VC580) Euploid, hoΔ::MFAprom-HYGMX-NATMX, ssd1Δ::KANthis studyAGY1385Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)KCY40 (or VC580) Disome8, hoΔ::MFAprom-HYGMX-NATMX, ssd1Δ::KANthis studyAGY1386Haploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009_Chr12 Mat a Disome12, hoΔ::HYG + pPKIthis studyAGY735 transformed with plasmidHaploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009_Chr12 Mat a Disome12, hoΔ::HYG, ssd1Δ::KAN + pPKIthis studyABY1445 transformed with plasmidHaploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009_Chr12 Mat a Disome12, hoΔ::HYG, ssd1Δ::KAN + pJH1-SSD1-W303this studyABY1445 transformed with plasmidHaploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)YPS1009_Chr12 Mat a Disome12, hoΔ::HYG, ssd1Δ::KAN + pJH1-SSD1-YPS1009this studyABY1445 transformed with plasmidHaploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)d-NCYC110_Chr8-4n Aneuploid + pJH1this studyAGY703 tranformed with plasmidDiploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)d-NCYC110_Chr8-4n Aneuploid, ssd1Δ::KAN/ssd1Δ::KAN + pJH1this studyAGY1494 transformed with plasmidDiploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)d-NCYC110_Chr8-4n Aneuploid, ssd1Δ::KAN/ssd1Δ::KAN + pJH1-SSD1-W303this studyAGY1494 transformed with plasmidDiploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)d-NCYC110_Chr8-4n Aneuploid, ssd1Δ::KAN/ssd1Δ::KAN + pJH1-SSD1-YPS1009this studyAGY1494 transformed with plasmidDiploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)W303 Mat a Euploid ade2-1 his3-11,15 leu2-3,112 trp1-1 ura3-1 can1-100 Gal+ ade1::HIS3, lys2::KANTorres et al.AGY487Haploid
Strain (Saccharomyces cerevisiae)W303_Chr12 Mat a Disome12 ade2-1 his3-11,15 leu2-3,112 trp1-1 ura3-1 can1-100 Gal+ ade16::HIS3 ade16::KANTorres et al.AGY488Haploid
Strain (Saccharomyces cerevisiae)W303 Mat a Euploid ade2-1 his3-11,15 leu2-3,112 trp1-1 ura3-1 can1-100 Gal+ ade1::HIS3, lys2::KAN + pJH1this studyAGY487 transformed with plasmidHaploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)W303_Chr12 Mat a Disome12 ade2-1 his3-11,15 leu2-3,112 trp1-1 ura3-1 can1-100 Gal+ ade16::HIS3 ade16::KAN + pJH1this studyAGY488 transformed with plasmidHaploid, available on request from the Gasch Lab
Strain (Saccharomyces cerevisiae)W303_Chr12 Mat a Disome12 ade2-1 his3-11,15 leu2-3,112 trp1-1 ura3-1 can1-100 Gal+ ade16::HIS3 ade16::KAN + pJH1-SSD1-YPS1009this studyAGY488 transformed with plasmidHaploid, available on request from the Gasch Lab
AntibodyRabbit polyclonal Anti-GFPAbcamAbcam catalog #ab290Rabbit polyclonal; 1:2000
AntibodyMouse monoclonal Anti-ActinThermo Fisher ScientificThermo Fisher Scientific catalog #MA1-744Mouse monoclonal; 1:1000
AntibodyMouse monoclonal Anti-COX2AbcamAbcam catalog #ab110271Mouse monoclonal; 1:500
AntibodyMouse monoclonal Anti-DPM1AbcamAbcam catalog #ab113686Mouse monoclonal; 1:250
AntibodyMouse monoclonal Anti-VPH1AbcamAbcam catalog #ab113683Mouse monoclonal; 1:1000
Recombinant DNA reagentpXIPHOSGenBank accession MG897154PAM sgRNA sequence (GAATCGAATG CAACCGGCGC) that targeted KanMXHiggins et al., Wrobel et al.
Recombinant DNA reagentpPKIthis studyAGB185CEN plasmid with the natMX selection marker.
Recombinant DNA reagentpJH1this studyAGB090CEN plasmid derived from pKI that has natMX selection marker. pJH is equivalent to pKI except for a fragment of unexpressed DNA that was removed during generation.
Recombinant DNA reagentpJH1-SSD1-YPS1009this studyORF + 1000 bp upstream and 337 bp downstream of SSD1 from YPS1009 genomic DNA. Plasmid has natMX selection marker
Recombinant DNA reagentpJH1-SSD1-W303this studyORF + 1000 bp upstream and 337 bp downstream of SSD1 from aW303 genomic DNA. Plasmid has natMX selection marker
Recombinant DNA reagentMolecular Barcoded Yeast (MoBY) v2.0 ORF Libraryotherobtained from Great Lakes Bioenergy Research Center (GLBRC)Ho, CH. et al. A molecular barcoded yeast ORF library enables mode-of-action analysis of bioactive compounds. Nat. Biotech. 27 (Holland and Cleveland, 2012), 369–377 (2009).
Sequence-based reagentMMR1 FISH probesStellarisdesigned against MMR1 mRNA
Sequence-based reagentMitochondrial rRNA FISH probesStellarisdesigned against 15 s and 21 s rRNA
Peptide, recombinant proteinvon Hippel-Lindau (VHL) tumor suppressorKaganovich et al.Addgene catalog #21053Kaganovich D, Kopito R, Frydman J. Misfolded proteins partition between two distinct quality control compartments. Nature. 2008 Aug 28. 454 (7208):1088–95.
Peptide, recombinant proteinAequorea victoria GFP (S65T)Huh et al.Huh W, Falvo JV, Gerke LC, Carroll AS, Howson RW, Weissman JS, and O'Shea EK (2003) Global Analysis of Protein Localization in Budding Yeast Nature 425:686–691.
Commercial assay or kitMitochondrial Yeast Isolation KitAbcamAbcam catalog #ab178779
Commercial assay or kitIllumina TruSeq Total RNA StrandedIlluminaIllumina catalog #20020597; previously RS-122–2203
Commercial assay or kitNEBNext Ultra DNA Library Prep Kit for IlluminaNew England BiolabsNEB catalog #E7370L
Commercial assay or kitYeast Mitochondrial Stain Sampler KitThermo Fisher ScientificThermo Fisher Scientific catalog #Y7530
Chemical compound, drugNourseothricin-dihydrogen sulfate(clonNAT)Werner BioAgentsWerner BioAgents catalog #5.005.000
Chemical compound, drug4',6-Diamidino-2-phenylindole, dihydrochloride (DAPI)Thermo Fisher ScientificThermo Fisher Scientific catalog #PI62247
Chemical compound, drugCarbonyl cyanide 3-chlorophenylhydrazone (CCCP)Sigma-AldrichSigma catalog #C2759
Chemical compound, drugRadicicol, Humicola fuscoatraA.G. ScientificA.G. Scientific catalog #R-1130
Chemical compound, drugGFP-Trap Magnetic AgaroseChromotekChromotek catalog #gtma-20

Strains and plasmids

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Strains used in this study are listed in the Resource Table. W303_Chr8, W303_Chr8-Chr15, and W303_Chr8-Chr10-Chr16 were generated using the method of Chen et al. (2012), passaging 16 generations in 20 μg/mL radicicol (A.G. Scientific) and plating on 8 or 16 μg/mL fluconazole to select for Chr8 aneuploidy. Karyotype was determined by array-comparative genomic hybridization and sequencing. W303 strains shown in Figure 1E were grown in SC-his + G418 to maintain marked copies of Chr12 (or corresponding markers in the otherwise isogenic wild type Torres et al., 2007). In general, deletions were generated by homologous recombination of relevant makers (e.g. KAN-MX or HIS3) into the designated locus, followed by diagnostic PCR to confirm correct integration and absence of the target gene. Because ssd1Δ cultures lose extra chromosomes (perhaps simply due to overtaking of the culture by stochastic euploid revertants), deletions were generated in wild-type strains that were then crossed to YPS1009_Chr12 ssd1Δ, followed by tetrad dissection to isolate aneuploid spore clones with desired genotypes. In all cases, aneuploidy was confirmed and periodically checked through diagnostic qPCR of one or two genes on the affected chromosomes (AAT1 and SDH2) normalized to a single-copy gene elsewhere in the genome (ERV25 or ACT1) – normalized ratios close to two reflect gene duplication, and ratios between 1.2–1.8X indicated partial loss of aneuploidy in the cell population. GFP-tagged genes were generated by integrating a GFP-ADH2terminator-HIS3 cassette (Huh et al., 2003) via homologous recombination into strain series AGY1504-1507 in which HIS3 was previously deleted by replacement with KAN-MX marker. In the case of SSD1-GFP strains, a cassette consisting of GFP followed by the native SSD1 terminator, 337 bp downstream of SSD1YPS1009, was generated by PCR sewing with the NAT-MX marker. In all cases, cloned or tagged genes were confirmed by sequencing. SSD1YPS1009 plus 1000 bp upstream and 300 bp downstream was cloned into a pRS-derived CEN plasmid for complementation. Because YPS1009_Chr12 ssd1Δ cannot tolerate the 2-micron plasmid, the VHL-GFP gene plus promoter and terminator sequences were cloned from pESC-LEU-GFP-VHL (ADDGENE #21053) into a pRS-derived CEN plasmid. Human VHL cannot fold without cofactors but is typically cleared from cells through proteasome activity (McClellan et al., 2005). Accumulation of VHL-GFP foci is generally taken as an inability to clear misfolded proteins.

Growth conditions

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Unless otherwise noted, strains were cultured for ~3 generations into log phase in rich YPD medium at 30°C, with the exception of microscopy experiments where cells were grown in low-fluorescence synthetic-complete medium and imaged live. Induction of VHL-GFP was performed by growing cells in YP with 2% raffinose + 2% galactose for 4 hr. Wild-type strains shown in Figure 6C–D were grown over-night in log-phase before addition of 1 ug/mL nourseothricin (Werner BioAgents, Jena, Germany) or 25 uM CCCP (Millipore-Sigma, St. Louis, MO). Growth rates were calculated by exponentially fitting changes in optical density. Relative final OD in Figure 6D was measured in biological triplicate after 24 hr growth of YPS1009, NCYC110, and W303 strains exposed to 25 uM CCCP with 0.5 ug/mL (NCYC, W303) or 1 ug/mL (YPS1009) NTC, respectively. Aneuploidy was periodically verified through diagnostic qPCR as described above. Expected growth rates under an additive model were estimated based on the fold-defect in one condition (e.g. aneuploidy versus euploidy) multiplied by the fold-defect in a second condition (e.g. NTC sensitivity in the euploid); significant differences in observed versus expected data were assessed with replicate-paired T-tests. Unless otherwise noted, all studies used at least biological triplicates with data represented as the average and standard deviation (except count data in Figures 2B–C, 4D, 5C–D and 6B in which average and standard error of the mean across biological replicates is shown).

Bulk-segregant phenotyping and mapping

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Haploid strain AGY736 (YPS1009_Chr12 Mat alpha ho::HYGMX) was crossed with AGY768 (W303_Chr12 Mat a) and the resulting diploid sporulated and dissected evenly on agar plates. Colony diameter after 72 hr was scored for 208 spores; 76 spores ranking in the smallest ~40% of the distribution were scored for their propensity to lose Chr12 within 20 culture generations of growth: each spore was passaged for 2 days in liquid YPD, after which genomic DNA was isolated and Chr12 abundance scored by diagnostic PCR as described above. Loss of Chr12 signal was taken as aneuploidy sensitivity (20 spores, Pool A1) whereas cells that maintained Chr12 signal were taken as enriched for aneuploid tolerant cells (40 spores, Pool B1). Spore sp100 (Mat alpha ADE2 HIS3 LEU2 trp- URA3) that was prototrophic for influential markers was selected, its aneuploidy status verified by qPCR, and it was backcrossed to AGY735 (YPS1009_Chr12 Mat a ho::HYGMX). 37 segregants were scored only for their propensity to lose aneuploidy after 2 days of passage, generating an aneuploidy-sensitive pool (10 spores, Pool A2) and a pool enriched for aneuploidy-tolerant strains (25 spores, Pool B2). A control cross of euploid hYPS1009 X euploid W303 was generated and phenotyped for colony size as above. 46 and 50 spores were taken as ‘small’ (colony diameter <437 square pixels) or ‘large’ (colony >591 square pixels) for Pool D and Pool F, respectively.

Each clone was grown to saturation, an equal volume of each culture pooled appropriately, and genomic DNA isolated (Qiagen, Germantown, MD) from ach pool. Pooled genomic DNA was sequenced using NEBNext Ultra DNA Library Prep Kit for Illumina on an Illumina HiSeq 2000 to an average of 20M 100 bp reads per pool. To avoid potential mapping biases, an artificial reference genome was created where single nucleotide polymorphisms (SNPs) between the two parental genomes were substituted for a third allele not present in either genome. Reads from sequenced pools were aligned to the artificial reference using bwa-mem (Li and Durbin, 2010). A pileup at known parental SNPs was created using samtools (Li et al., 2009), and allele counts at each SNP were calculated. SNP positions were filtered to retain SNPs with at least 15X coverage, both parental alleles scored, and allele frequency between 0.1–0.9 to eliminate false signals during bulk segregant analysis. Bulk-segregant analysis was performed using MULTIPOOL (v 0.10.1) (Edwards and Gifford, 2012) run across ~60,000 SNPs in contrast mode using the default recombination fraction (3300 cM) with -N set to the number of segregants in the aneuploidy-sensitive/small-colony pool in each cross (A1 = 20; A2 = 10; D = 46). Potential QTLs were identified at loci where allele frequency varied the greatest between the two pools. SSD1 was validated as the causal locus through gene deletions and complementation as shown in Figure 1. Sequencing data for each pool are available in the Short Read Archive (SRA) under access number PRJNA548343, and MULTIPOOL output files are available in Supplementary file 1, as described in Edwards and Gifford (2012).

RNA sequencing, RNA immunoprecipitation, and plasmid barcode sequencing

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RNA-seq was done as previously described (Jovaisaite et al., 2014) using total RNA isolated from log-phase cultures. Illumina reads were mapped to the S288c genome substituted with SNPs from YPS1009, NCYC110, or W303 as called in Sardi et al. (2018), using bwa-meme. In general, data represent the average of biological triplicate, with the exception of h-YPS1009 strains shown in Figure 2 done in quadruplicate and W303_Chr8-Chr15 and W303_Chr8-Chr10-Chr16 done in duplicate. Replicates for each strain suite were paired on the same day, enabling replicate-paired statistical analysis, done in edgeR (Robinson et al., 2010). Genes in Figure 2 were selected by considering both YPS1009_Chr12 ssd1Δ versus YPS1009_Chr12 wild type and NCYC110_Chr8 ssd1Δ versus NCYC110_Chr8 wild type. Hierarchical clustering was performed using Cluster 3.0 (Eisen et al., 1998) and visualized in Java Treeview (Saldanha, 2004). Functional enrichment of GO terms was performed using the program SetRank (Simillion et al., 2017). Activation of the UPR was inferred from enrichment of Hac1 targets among induced genes (p<1e-4, hypergeometric test, compiled in Chasman et al., 2014), and signatures of mito-CPR was indicated as up-regulation of Pdr3 targets including CIS3 as reported in Weidberg and Amon (2018). Sequencing data are available from the GEO database under accession number GSE132425. Processed data are also available in Supplementary file 2.

RNA-immunoprecipitation (RIP) was performed similar to previously described (Jansen et al., 2009) with the following modifications: Cell lysate was treated with RQ1 RNase-free DNase (Promega, Madison, WI) for 15 min at room temperature, an aliquot was removed as the input material, and RNA was immunoprecipitated using GFP-Trap Magnetic Agarose (Chromotek, Planegg-Martinsried, Germany) against Ssd1-GFP from euploid and aneuploid lysate for 1 hr at 4°C (due to Ssd1-GFP degradation with longer incubation). An identical procedure was performed with untagged YPS1009 cells as a mock-RIP. Recovered RNA was subjected to Illumina sequencing as described above. RIP-seq was performed in duplicate for euploid and for aneuploid cells; bound transcripts were identified through combined edgeR (Robinson et al., 2010) analysis of the four RIP-seq samples, contrasting RIP to input for each sample and then to mock-IP normalized to its own input. Bound transcripts were taken as those with FDR < 0.05 (Supplementary file 2). Sequencing data are available from the GEO database under accession number GSE132425.

The suite of YPS1009_Chr12 strains (AGY731, AGY735, AGY1503, AGY1517) was transformed with Moby 2.0 high-copy expression library (Magtanong et al., 2011) and an aliquot removed as the starting pool. Cells were grown in biological triplicate for five generations in YPD medium, plasmid DNA collected from the starting and ending pools, and barcodes sequenced as previously described (Magtanong et al., 2011). Pools were normalized by total barcode reads per sample and fitness costs taken as the log2(fold change) in barcode abundance after versus before outgrowth. Data in Figure 2D represent the distribution of replicate-averaged data.

Proteomics

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Cell pellets were resuspended in 6 M guanidine HCl and boiled for 5–10 min; proteins were precipitated with methanol up to 90%, spun 5 min at 15 K g, and resuspended in lysis buffer (8 M urea, 100 mM Tris, pH = 8.0, 10 mM TCEP, 40 mM chloroacetamide). Samples were diluted to 1.5 M urea and digested overnight at room temperature with LysC (Wako Chemicals, USA) and for 3 hr with trypsin (Promega, USA) at 1:50 enzyme to protein ratio. Samples were desalted using Strata X columns (Phenomenex Strata-X Polymeric RP, USA). For LC-MS/MS, samples were resuspended in 0.2% formic acid and separated via reversed phase (RP) chromatography. 2 µg of tryptic peptides were injected onto a capillary RP column prepared in-house and packed with 1.7 μm diameter Bridged Ethylene Hybrid C18 particles as described in Shishkova et al. (2018). Columns were installed onto Dionex nanoHPLC (Thermo, Sunnyvale CA) and heated to 50°C using a home-built column heater. Mobile phase buffer A was composed of water and 0.2% formic acid, mobile phase B - 70% ACN and 0.2% formic acid. Samples were separated over a 120 min gradient at flow rate of 325 nl/min. Peptide cations were converted into gas-phase ions via electrospray ionization and analyzed using a Thermo Orbitrap Fusion Lumos (Thermo, San Jose CA) mass spectrometer, according to the previously published methods (Hebert et al., 2018). Raw data were searched using MaxQuant (v. 1.6.1.0) against Saccharomyces cerevisiae database (SGD, downloaded 10.15.2018). Searches were performed using precursor mass tolerance of 27 ppm and a product mass tolerance of 0.3 Da. Proteins were identified and quantified via MaxLFQ using default settings with enabled ‘Match between runs,’ requiring LFQ ratio of 1, and MS/MS spectra not required for LFQ comparisons. Raw data are available in the PRIDE database (Project accession # PXD013847). Prior to publication, reviewers can access the files using the following credentials: Username: reviewer95858@ebi.ac.uk, Password: 6w9IaMi3. Processed data and a list of proteins shown in Figure 3 are available in Supplementary file 2, and normalized protein abundance data are available in Supplementary file 3.

Mitochondrial fractionation, microscopy and single-molecule smFISH

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Organelle-enriched and -depleted fractions were generated for euploid (AGY1446) and aneuploid YPS1009_Ch12 SSD1-GFP (AGY1447) and untagged SSD1 cells as a control, using Mitochondrial Yeast Isolation Kit (Abcam, Cambridge, United Kingdom) according to manufacturer protocol with slight modifications to minimize protein degradation. Western blots were developed using anti-GFP ab290 (Abcam), anti-Actin MA1-744 (Thermo Fisher Scientific), anti-Cox2 ab110271 (Abcam), anti-Vph1 ab113683 (Abcam), and anti-Dpm1 ab113686 (Abcam) on a Li-COR Odyssey instrument (Model 9120). Cells for microscopy were plated on plain or poly-L-Lysine coated slides and either single images (HSP104-GFP in Figure 6) or z-stack images (all other microscopy) every 0.5 µm were acquired with an EVOS FL Auto two equipped with an RFP EVOS light cube. Z-stacks were collapsed into a single image with EVOS software for publication. Mitochondria in Figure 4C were visualized with Rhodamine B Hexyl Ester (ThermoFisher, R648MP) according to manufacturer’s protocol; images represent an overlay of the bright-field image onto the fluorescence image to highlight cell boundaries. Cells were scored by marking total cells in bright-field images and the scoring presence or absence of Rhodamine B Hexyl Ester signal. A minimum of 380 cells were scored per strain across three biological replicates. Very similar results were obtained tracking Pet123-GFP signal.

smFISH was performed as previously described (Gasch et al., 2017) except performed on an EVOS FL Auto two and with transcripts detected manually in FIJI (Schindelin et al., 2012). FISH probe sets were designed against MMR1 (conjugated to Quasar 670) and mitochondrial 15 s and 21 s rRNAs (conjugated to Quasar 570, Stellaris, Middlesex, United Kingdom). Mitochondrial morphology in Figure 3D was quantified using mitochondrial rRNA probes, which produced images very similar to Rhodamine staining but enabled visualization independent of mitochondrial membrane potential. Morphology was scored in each cell manually using the multi-point tool in FIJI, recording the number of cells with any tubular, any globular, or only globular morphologies. Cells with fragmented mitochondria were defined as those with at least three discontinuous fragments from the tubular structure or having at least three fragments in addition to the largest globular focus. >200–400 cells were scored for all microscopy experiments and across multiple biological replicates per strain. MMR1 localization was scored by identifying buds (scored as cells lacking DAPI or containing bar nuclei by DAPI staining) and scoring those either containing or lacking MMR1 transcripts.

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Decision letter

  1. Hannah Klein
    Reviewing Editor; New York University School of Medicine, United States
  2. Jessica K Tyler
    Senior Editor; Weill Cornell Medicine, United States
  3. David Gresham
    Reviewer; New York University, United States
  4. Juan Lucas Argueso
    Reviewer; Colorado State University, United States
  5. Kerry Bloom
    Reviewer; The University of North Carolina at Chapel Hill, United States

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Acceptance summary:

The paper sheds light on the complicated story of aneuploidy in yeast and tolerance to aneuploidy in different strains. By extension, it should have relevance to aneuploidy tolerance in different human cells, especially tumor cells. Of interest also will be the quantitative genetics methodology used to identify a private mutation that leads to the differences in anueploidy tolerance in yeast strains. It will be important for future studies to delineate the mechanisms of aneuploidy tolerance.

Decision letter after peer review:

Thank you for submitting your article "The genetic basis of aneuploidy tolerance in wild yeast" for consideration by eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Jessica Tyler as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: David Gresham (Reviewer #1); Juan Lucas Argueso (Reviewer #2); Kerry Bloom (Reviewer #3).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

The authors study aneuploidy in yeast, investigating the differences between wild yeast and a commonly used laboratory strain in aneuploidy tolerance. The authors use QTL mapping to pinpoint a variant version of SSD1 in the laboratory strain as the causative agent of aneuploidy intolerance in the laboratory strain. The authors suggest that this SSD1 variant impacts mitochondrial function and that this combined with proteostasis stress contributes to aneuploidy intolerance.

As this issue has been a source of much discussion in the yeast field, a resolution to the strain differences in terms of stress defects would be welcome. However, the current manuscript does not formally show that the SSD1 variant is the causative agent. Two of the reviewers were enthusiastic about the potential impact of the manuscript while the third found the discussion of the SSD1 variant not novel as it has long been known that the W303 strain contains this variant and that it contributes to some of the differing phenotypes of the W303 strain.

Essential revisions:

1) The authors need to formally show that the ssd1 allele of W303 is causative for aneuploidy intolerance. The right way to do this is to engineer the W303 allele into an otherwise pure YPS1009 strain background. Moreover, the exact nature of the W303 allele is very difficult to understand from the manuscript as the authors simply refer to other papers that have shown it is a hypomorph. Looking at the alignment in Figure 6—figure supplement 1, it is hard to understand where the truncating mutation appears. Therefore, basing all subsequent analyses on a complete gene deletion doesn't seem justified. The authors should provide more information on the nature of the allele and the rationale for using a null allele, rather than the W303 allele for subsequent assays.

The authors discuss aneuploidy sensitive and euploid crosses, based on propensity to lose Chr12. Presumably they are also losing other chromosomes? The authors should comment on the potential consequences of having a duplicated rDNA region in these cells; it seems this could have major phenotypic consequences.

As SSD1 is involved in many pathways (TOR pathway, cell cycle regulation), it is possible that the mitochondrial effects are indirect. Claims that the effects are direct need to be unambiguously supported.

2) The statistical methods and the methodologies need to be better described.

Examples of points of confusion are listed here:

In Figure 2D how are the fitness data normalized? The median fitness differs between genotypes suggesting that these are absolute rather than relative values, but the Materials and methods states otherwise.

A key result is the identification of the sp100 segregant spore. It is stated "we realized during tetrad dissection, that adenine auxotrophy influenced aneuploidy tolerance (Figure 1—figure supplement 2)". All that is shown in Figure 1—figure supplement 2 is doubling time and growth. What are the data that the difference in growth rate is due to aneuploidy? The authors cite Figure 1—figure supplement 1 for showing growth rates of one vs two copies of Chr12 (Results section). They state that the number of copies of the chromosome was determined by qPCR. Methodology for the qPCR is not apparent.

The morphological differences in mitochondria were difficult to evaluate. The authors refer to globular and tubular morphologies described in Materials and methods. However, the Materials and methods just state that the multipoint tool in FIJI was used and do not define how these morphologies were quantitated. Disturbingly, they state in the supplemental figure legend (Supplementary figure 6) that mitochondrial morphologies were difficult to score, but were different. Which is the case, and why weren't the tools presumably used in Figure 4, used for Supplementary figure 6.

3) The studies here are limited to aneuploidy in haploid cells. However, aneuploidy is less deleterious in diploids and as wild yeasts are diploid, the effects of aneuploidy and the impact of the W303 ssd1 variant should be tested in diploids, comparing SSD1/SSD1 2N and 2N+1 versus ssd1D/ssd1D 2N and 2N+1. Whatever results are found, this should be added as an important point in the Discussion.

4) The general conclusions need to be further discussed. Examples are listed here:

The authors find that aneuploidy exacerbates aneuploidy sensitivity, but don't provide an explanation as to why this is the case.

I think this is a great example of the potential limitation of drawing conclusions on the basis of studies in a single strain background. The authors could discuss that in their conclusion.

https://doi.org/10.7554/eLife.52063.sa1

Author response

Summary:

The authors study aneuploidy in yeast, investigating the differences between wild yeast and a commonly used laboratory strain in aneuploidy tolerance. The authors use QTL mapping to pinpoint a variant version of SSD1 in the laboratory strain as the causative agent of aneuploidy intolerance in the laboratory strain. The authors suggest that this SSD1 variant impacts mitochondrial function and that this combined with proteostasis stress contributes to aneuploidy intolerance.

As this issue has been a source of much discussion in the yeast field, a resolution to the strain differences in terms of stress defects would be welcome. However, the current manuscript does not formally show that the SSD1 variant is the causative agent. Two of the reviewers were enthusiastic about the potential impact of the manuscript while the third found the discussion of the SSD1 variant not novel as it has long been known that the W303 strain contains this variant and that it contributes to some of the differing phenotypes of the W303 strain.

We thank the reviewers for their positive assessment of our work and their recognition of the importance of settling this debate to better understand eukaryotic responses to aneuploidy.

The revised manuscript now shows definitively that the W303 allele of Ssd1 explains aneuploidy sensitivity in W303: expressing the SSD1YPS1009allele in multiple strain backgrounds recovers the growth defect of ssd1- aneuploid cells, whereas expressing the ssd1W303allele provides either no complementation or partial complementation depending on strain background. Most importantly, expressing SSD1YPS1009in aneuploid W303 almost completely complements its growth rate (with a residual contribution from the adenine auxotrophy). Thus, there is no ambiguity that it is the W303 allele of Ssd1 that explains the sensitivity of W303 to extra chromosomes.

However, we also wish to clarify why this work is important. The importance is not that we identified the allele explaining a phenotypic difference, but rather that we show that results that were previously taken to represent eukaryotic responses to aneuploidy – results that have been used to make inferences about human biology including aneuploidy syndromes and cancers – are specific to a mutant yeast strain: wild aneuploids do not show any phenotypes previously reported in W303 unless SSD1 is defective. We go on to use the clean SSD1 deletion to understand the role of an RNA binding protein in aneuploidy tolerance, studying multiple different strain backgrounds. Together with our model, this work will have a significant contribution to the aneuploidy field, much beyond defining a strain-specific difference.

Essential revisions:

1) The authors need to formally show that the ssd1 allele of W303 is causative for aneuploidy intolerance. The right way to do this is to engineer the W303 allele into an otherwise pure YPS1009 strain background. Moreover, the exact nature of the W303 allele is very difficult to understand from the manuscript as the authors simply refer to other papers that have shown it is a hypomorph. Looking at the alignment in Figure 6—figure supplement 1, it is hard to understand where the truncating mutation appears. Therefore, basing all subsequent analyses on a complete gene deletion doesn't seem justified. The authors should provide more information on the nature of the allele and the rationale for using a null allele, rather than the W303 allele for subsequent assays.

As described above, we now provide definitive proof through allele swaps that the YPS1009 allele of Ssd1 maximally complements the growth defects in multiple strain backgrounds (including W303), whereas the truncated W303 allele expressed in the same strains does not. Allele swap experiments are provided in new Figure 1E. We also augmented the text to better describe the W303 allele: “The locus spanned SSD1, encoding an RNA-binding protein and known to harbor a premature stop codon in W303 that deletes 44% of the protein including conserved RNA binding domains (27-29).”

After describing the genetic basis of aneuploidy tolerance, we set out to better understand how Ssd1 enables cells to tolerate chromosome amplifications. For this we focused on the clean SSD1 deletion to best interpret mutant phenotypes. We highlight that wild-type aneuploids with functional SSD1 show none of the phenotypes of aneuploid W303 unless Ssd1 is defective. Thus, there is no ambiguity that Ssd1 is critical for handling extra chromosomes in multiple strains. We believe our work (and future work that emerges from it) will have a major contribution to understanding why extra chromosomes can be toxic and how normal cells deal with that stress.

The authors discuss aneuploidy sensitive and euploid crosses, based on propensity to lose Chr12. Presumably they are also losing other chromosomes? The authors should comment on the potential consequences of having a duplicated rDNA region in these cells; it seems this could have major phenotypic consequences.

The phenotype we observe is that ssd1- cultures rapidly lose cells that harbor the chromosome duplication. At this point, we do not know if the SSD1 mutant loses chromosomes at a higher cellular rate or if the extreme growth-rate advantage of stochastic euploid revertants fully explains loss of aneuploidy from the culture. This is something we are currently investigating. We clarified the text in several places to state that the culture loses the aneuploid cells, perhaps simply because euploid revertants rapidly take over the culture.

The rDNA locus on Chr12 cannot explain the phenotypes we observed, because those phenotypes are also seen when other chromosomes are duplicated. We tested strains harboring extra copies of several different chromosomes (including Chr8, Chr10, Chr15, and/or Chr16) and show that growth reduction, transcriptome response, and sensitivity to mitochondrial stress and NTC are all caused by SSD1 deletion or mutation. Furthermore, the phenotypes we study were previously reported in W303 harboring extra of any of the 16 yeast chromosomes (Torres et al., 2007 and other papers). Thus, these phenotypes cannot be explained by the rDNA locus on Chr 12. We added a statement to this effect in the Results section.

As SSD1 is involved in many pathways (TOR pathway, cell cycle regulation), it is possible that the mitochondrial effects are indirect. Claims that the effects are direct need to be unambiguously supported.

We agree that until the complete mechanism is known the mitochondrial effect could be indirect; however, that Ssd1 binds nuclear-encoded mitochondrial transcripts, affects protein abundance from several of those transcripts, and purifies with mitochondria-enriched fractions raises the possibility of a more direct role. We clarified the text to this effect: “It is possible that mitochondrial defects in ssd1- cells arise as a secondary consequence of Ssd1 dysfunction; however, that Ssd1 binds several nuclear-encoded mitochondrial mRNAs, controls protein abundance of several of them, and purifies with mitochondria-enriched fractions raises the possibility of a more direct function.

2) The statistical methods and the methodologies need to be better described.

Examples of points of confusion are listed here:

In Figure 2D how are the fitness data normalized? The median fitness differs between genotypes suggesting that these are absolute rather than relative values, but the materials and methods states otherwise.

We apologize for the confusion. We spent considerable time providing very detailed Materials and methods including statistical analysis. We have now clarified the Materials and methods to state that, “Pools were normalized by total barcode reads per sample and fitness costs taken as the log2(fold change) in barcode abundance after versus before outgrowth.”

A key result is the identification of the sp100 segregant spore. It is stated "we realized during tetrad dissection, that adenine auxotrophy influenced aneuploidy tolerance (Figure 1—figure supplement 2)". All that is shown in Figure 1—figure supplement 2 is doubling time and growth. What are the data that the difference in growth rate is due to aneuploidy?

The key result is in Figure 1—figure supplement 2B, which shows that reintroducing the ADE2 gene into W303 significantly improves growth of the aneuploid cells but not the euploids. Thus, there is a synergistic benefit only when these cells are aneuploid.

The authors cite Figure 1—figure supplement 1 for showing growth rates of one vs two copies of Chr12 (Results section). They state that the number of copies of the chromosome was determined by qPCR. Methodology for the qPCR is not apparent.

qPCR was performed as described: “... aneuploidy was confirmed and periodically checked through diagnostic qPCR of one or two genes on the affected chromosomes (AAT1 & SDH2) normalized to a single-copy gene elsewhere in the genome (ERV25 or ACT1) – normalized ratios close to 2 reflect gene duplication, and ratios between 1.2-1.8X indicated partial loss of aneuploidy in the cell population.”

The morphological differences in mitochondria were difficult to evaluate. The authors refer to globular and tubular morphologies described in Materials and methods. However the Materials and methods just state that the multipoint tool in FIJI was used and do not define how these morphologies were quantitated. Disturbingly, they state in the supplemental figure legend (Supplementary figure 6) that mitochondrial morphologies were difficult to score, but were different. Which is the case, and why weren't the tools presumably used in Figure 4, used for Supplementary figure 6.

We apologize for the confusion. The globular versus tubular morphology is very distinctive, and thus mitochondria in these forms were scored manually for Figure 4, as we now clarify. As stated in the Materials and methods, “Cells with fragmented mitochondria were defined as those with at least 3 discontinuous fragments from the tubular structure or having at least 3 fragments in addition to the largest globular focus.”

Because the other strains do not have globular types, it was much harder to score differences in mitochondrial character for other strains. To be fair, we removed the original Supplementary figure 6 and reference to other strains’ mitochondrial morphology from the manuscript.

3) The studies here are limited to aneuploidy in haploid cells. However, aneuploidy is less deleterious in diploids and as wild yeasts are diploid, the effects of aneuploidy and the impact of the W303 ssd1 variant should be tested in diploids, comparing SSD1/SSD1 2N and 2N+1 versus ssd1D/ssd1D 2N and 2N+1. Whatever results are found, this should be added as an important point in the Discussion.

Strains used in the original manuscript represented both haploid and diploid strains: YPS1009 and W303 examples in the original manuscript were haploid, but NCYC110 is a diploid strain tetrasomic for Chr 8. We now add additional data showing that diploid YPS1009 tetrasomic for Chr12 is even more sensitive to loss of SSD1 than haploid YPS1009 disomic for Chr12 (compare new Figure 1—figure supplement 5C to Figures 1D and 4A). Thus, aneuploidy is not less delirious in diploids (the reviewer may be thinking of diploid strains that are trisomic for extra chromosomes and thus carry a lower load). Ssd1 is required in both haploid and diploid aneuploids of multiple genetic backgrounds.

4) The general conclusions need to be further discussed. Examples are listed here:

The authors find that aneuploidy exacerbates aneuploidy sensitivity, but don't provide an explanation as to why this is the case.

We reworked the Discussion to make our model and supporting results clearer:

“Our model posits that Ssd1’s function in translational silencing and mitochondrial physiology enable aneuploidy tolerance in wild yeast. […] Additional stress on the proteostasis system, due to drugs or SSD1 deletion, pushes cells beyond capacity, thereby limiting fitness.”

We go on to explain how Ssd1 could play a role through translational regulation and possibly mitochondrial physiology. Ssd1-bound mRNAs encoded proteins with a high fraction of intrinsic disorder, and this set includes proteins prone to aggregation in aneuploid W303. Because we see relatively few phenotypes in euploid cells lacking Ssd1 (albeit with strain-specific and base-ploidy nuances, see new Figure 1—figure supplement 5), we propose that the added stress of chromosome amplification, which produces additional protein burden especially in the absence of Ssd1, is especially toxic to cells lacking Ssd1. Ongoing work in our lab is dissecting the mechanistic details.

I think this is a great example of the potential limitation of drawing conclusions on the basis of studies in a single strain background. The authors could discuss that in their conclusion.

We thank the reviewer for this suggestion, and we added a statement to this effect in Discussion.

https://doi.org/10.7554/eLife.52063.sa2

Article and author information

Author details

  1. James Hose

    Center for Genomic Science Innovation, University of Wisconsin–Madison, Madison, United States
    Contribution
    Conceptualization, Formal analysis, Investigation, Methodology
    Competing interests
    No competing interests declared
  2. Leah E Escalante

    1. Center for Genomic Science Innovation, University of Wisconsin–Madison, Madison, United States
    2. Laboratory of Genetics, University of Wisconsin-Madison, Madison, United States
    Contribution
    Investigation, Methodology
    Competing interests
    No competing interests declared
  3. Katie J Clowers

    Laboratory of Genetics, University of Wisconsin-Madison, Madison, United States
    Present address
    Ginkgo Bioworks, Boston, United States
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  4. H Auguste Dutcher

    1. Center for Genomic Science Innovation, University of Wisconsin–Madison, Madison, United States
    2. Laboratory of Genetics, University of Wisconsin-Madison, Madison, United States
    Contribution
    Formal analysis, Investigation
    Competing interests
    No competing interests declared
  5. DeElegant Robinson

    Center for Genomic Science Innovation, University of Wisconsin–Madison, Madison, United States
    Contribution
    Investigation, Methodology
    Competing interests
    No competing interests declared
  6. Venera Bouriakov

    1. Center for Genomic Science Innovation, University of Wisconsin–Madison, Madison, United States
    2. Great Lakes Bioenergy Research Center, Madison, United States
    Contribution
    Investigation
    Competing interests
    No competing interests declared
  7. Joshua J Coon

    1. Center for Genomic Science Innovation, University of Wisconsin–Madison, Madison, United States
    2. Great Lakes Bioenergy Research Center, Madison, United States
    3. Department of Biomolecular Chemistry, University of Wisconsin–Madison, Madison, United States
    4. Department of Chemistry, University of Wisconsin–Madison, Madison, United States
    5. Morgridge Institute for Research, Madison, United States
    Contribution
    Supervision
    Competing interests
    No competing interests declared
  8. Evgenia Shishkova

    1. Center for Genomic Science Innovation, University of Wisconsin–Madison, Madison, United States
    2. Morgridge Institute for Research, Madison, United States
    Contribution
    Methodology
    Competing interests
    No competing interests declared
  9. Audrey P Gasch

    1. Center for Genomic Science Innovation, University of Wisconsin–Madison, Madison, United States
    2. Laboratory of Genetics, University of Wisconsin-Madison, Madison, United States
    3. Great Lakes Bioenergy Research Center, Madison, United States
    Contribution
    Conceptualization, Formal analysis, Supervision, Funding acquisition, Project administration
    For correspondence
    agasch@wisc.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8182-257X

Funding

National Cancer Institute (R01CA229532)

  • Audrey P Gasch

U.S. Department of Energy (DE-SC0018409)

  • Joshua J Coon
  • Audrey P Gasch

National Institutes of Health (P41 GM108538)

  • Joshua J Coon

National Institutes of Health (T32 GM007133)

  • H Auguste Dutcher

National Institutes of Health (T32 HG002760)

  • DeElegant Robinson

National Science Foundation (GRFP)

  • Leah E Escalante

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We thank Mike Place and Kevin Myers for experimental support, and Christina Scribano, Beth Weaver, and members of the Gasch Lab for constructive discussions.

Senior Editor

  1. Jessica K Tyler, Weill Cornell Medicine, United States

Reviewing Editor

  1. Hannah Klein, New York University School of Medicine, United States

Reviewers

  1. David Gresham, New York University, United States
  2. Juan Lucas Argueso, Colorado State University, United States
  3. Kerry Bloom, The University of North Carolina at Chapel Hill, United States

Publication history

  1. Received: September 20, 2019
  2. Accepted: January 7, 2020
  3. Accepted Manuscript published: January 7, 2020 (version 1)
  4. Version of Record published: January 20, 2020 (version 2)

Copyright

© 2020, Hose et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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