A pathogenic role for histone H3 copper reductase activity in a yeast model of Friedreich’s ataxia

Histone H3H113 mutations prevent the growth defects caused by disruption of Fe-S cluster biogenesis or distribution

The H3H113N mutation in yeast decreases the Cu¹⁺ pool and diminishes copper utilization for copper-dependent processes without affecting the total intracellular levels of copper (24). We reasoned that this same mutation might provide resistance against Cu¹⁺ toxicity. To test this, we introduced the H113N mutation in the two chromosomal copies of the histone H3 gene to generate the yeast strain H3^H113N. Despite its somewhat slower growth, this strain grew better than wild type (WT) in fermentative media containing toxic levels of copper (Fig. 1A). We considered whether resistance to elevated copper depended on the metallothionein, Cup1, which limits toxicity by sequestering excess intracellular Cu¹⁺ (25, 26). However, H3^H113N still displayed substantial resistance to copper toxicity relative to WT when Cup1 was inactivated (F8stop) (fig. S2). These results are consistent with decreased intracellular Cu¹⁺ abundance in H3^H113N resulting in less damage by copper.

We next hypothesized that when Fe-S cluster assembly is compromised, diminishing histone cupric reductase activity, which decreases Cu¹⁺ abundance (24), should mitigate the ensuing cellular defects, enabling cells to cope with decreased Fe-S cluster production (fig. S1). Deletion of most members of the mitochondrial Fe-S cluster assembly complex is lethal in yeast, except for YFH1. Deletion of YFH1 (yfh1Δ) results in severe growth defects in rich fermentative synthetic complete (SC) medium due to various underlying deficiencies (Fig. 1B) (8, 27). The H3H113N mutation substantially rescued the severe growth defect of yfh1Δ (Fig. 1B).

Although yfh1Δ suffered severe growth defects, individual clones of this strain displayed a relatively high probability of spontaneous recovery of their growth defects over the course of a few days following YFH1 deletion. This suggests a high likelihood of clones acquiring secondary mutations or other adaptations to cope with the disruption of Fe-S cluster homeostasis. Loss of Yfh1 can result in nuclear genome instability (27). To avoid this complication, we instead turned to a conditional transcriptional shutoff approach to deplete cells of Yfh1. We replaced the endogenous promoter of YFH1 with the GAL1 promoter, which is active in galactose-containing media but enables robust suppression of gene expression when cells are grown in the presence of glucose. This approach also allows examination of the time-dependent deterioration of function when Yfh1 is depleted. Transcriptional shutoff of YFH1 expression (YFH1-off) resulted in essentially complete depletion of Yfh1 protein after 1 day (fig. S3A) and a corresponding minor growth defect in SC (Fig. 1C). However, prolonged growth in the absence of YFH1 expression revealed a gradually worsening defect in SC in two different yeast strains (Fig. 1C, fig. S3B, and table S1). The growth defect of YFH1-off cells was exacerbated in media with substantially less amino acids (i.e., minimal medium) likely due to increased demand for Fe-S clusters for amino acid biosynthesis (fig. S3B and see below). H3H113N substantially prevented this gradual growth deterioration in fermentative SC or minimal medium, consistent with diminished toxicity of Cu¹⁺ to Fe-S clusters (Fig. 1C and fig. S3B). Similarly, introduction of the H113Y or H113N mutation (24) in only one copy of the histone H3 gene (i.e., HHT2) was sufficient to prevent the growth defect of YFH1-off in SC medium (fig. S3C). Reverting the HHT2-H113N mutation to the WT sequence (i.e., N113H) suppressed the rescue, corroborating that the histone H3 mutation accounts for the protective effect (fig. S3D).

To determine whether H3H113N could prevent the deterioration resulting from disruptions to Fe-S clusters more generally, we similarly repressed the expression of either GRX5 or ATM1 with the GAL1 promoter (GRX5-off and ATM1-off, respectively). Grx5 and Atm1 function downstream of Yfh1 in the transfer of Fe-S clusters to target proteins in the mitochondria and in the cytoplasm, respectively (28–30). Similar to the effect of Yfh1 depletion, GRX5-off and ATM1-off gradually deteriorated over time, but H3H113N substantially prevented this growth defect (Fig. 1, D and E). These results suggest that H3H113N did not merely compensate for the specific loss of Yfh1, but instead, it more generally prevented the dysfunction when Fe-S cluster homeostasis was disrupted.

H3H113N prevents loss of multiple Fe-S cluster–dependent processes

Depletion of Yfh1 may affect most, if not all, Fe-S cluster–dependent processes in the cell. These processes include the synthesis of certain amino acids that depend on enzymes containing Fe-S clusters (12, 30–33). All 20 amino acids are highly abundant in SC, which obviates the need for amino acid synthesis. We therefore gradually decreased the abundance of amino acids in SC and observed a corresponding gradual exacerbation of growth defects in the YFH1-off strain, even after a single day of Yfh1 shutoff (Fig. 2A and fig. S3B). This is consistent with an increased demand for Fe-S clusters for amino acid synthesis, thereby accentuating the deficiencies of YFH1-off. As in rich medium, the H3H113N mutation rescued the deterioration of growth in YFH1-off caused by amino acid limitation (Fig. 2A). With complete depletion of all amino acids, and thus when demand for Fe-S clusters would be highest, even H3H113N could not prevent the severe growth defect (Fig. 2A). This is likely because, even with decreased Cu¹⁺-induced damage in H3^H113N, the total Fe-S supply remains below the threshold required to sustain sufficient amino acid synthesis.

Fe-S cluster–containing enzymes participate in the syntheses of eight amino acids: methionine, cysteine, leucine, isoleucine, valine, lysine, glutamate, and glutamine. Syntheses of the others are not directly dependent on Fe-S clusters. Consistent with this, supplementation with eight amino acids, the syntheses of which are not dependent on Fe-S clusters, did not alleviate the growth defects of YFH1-off. In contrast, supplementation of amino acid–depleted media with only the eight Fe-S cluster–dependent amino acids restored growth of YFH1-off to the level displayed in complete medium (Fig. 2B). Together, these findings indicate that the growth defect of YFH1-off when amino acids were depleted was due to the diminished function of the Fe-S cluster–containing enzymes for synthesis of specific amino acids and that diminishing copper reductase activity of histone H3 restores the function of these enzymes.

We further examined whether removal of Fe-S cluster–dependent amino acids individually from otherwise replete medium would be sufficient to worsen the growth defect of YFH1-off. Removal of lysine, glutamate, or leucine resulted in diminished growth of YFH1-off (Fig. 2C and fig. S4A). This confirms that the synthesis of even a single amino acid can alone place increased demands for Fe-S clusters and exacerbate the growth defect of the YFH1-off strain. We focused on lysine and glutamate as test cases for Fe-S cluster–dependent function. The removal of lysine and glutamate (SC-lys-glu) substantially diminished growth of the YFH1-off strain almost as much as 100-fold depletion of all 20 amino acids (Fig. 2C). Similar to other conditions, decreased Cu¹⁺ production in H3^H113N, as well as the HHT2^H113N, substantially prevented severe growth defects due to reduced lysine and glutamate syntheses resulting from diminishment (Fig. 2C and fig. S4B) or complete loss of Yfh1 (fig. S4C).

The ancient and conserved mitochondrial aconitase catalyzes the isomerization of citrate to isocitrate in the tricarboxylic acid cycle, which, in turn, contributes to glutamate synthesis (13). Aconitase uses an Fe-S cluster cofactor for its catalytic function (34–36). Deficiencies in aconitase activity have been identified in heart biopsies of patients with FRDA, and similar deficiencies were identified in yeast strains lacking YFH1 (10). We therefore assessed the incorporation of radioactive ⁵⁵Fe into aconitase in vivo, which has been used as an estimate of the presence of the Fe-S cluster in the enzyme (30). We generated strains in which Aco1 was tagged at the C terminus with Myc (Aco1-Myc) and depleted Yfh1 as before, followed by a 4-hour pulse with ⁵⁵Fe. Consistent with the growth defect of YFH1-off in SC-lys-glu, ⁵⁵Fe content was substantially decreased in immunoprecipitated Aco1-Myc in YFH1-off compared to WT (Fig. 2D). We also assessed aconitase activity in whole-cell extracts. Consistent with diminished Fe content in aconitase, enzymatic activity of aconitase was also markedly diminished following Yfh1 depletion (Fig. 2E). However, H3H113N significantly restored ⁵⁵Fe content in Aco1-Myc (Fig. 2D) and aconitase activity to ~60% of normal levels (Fig. 2E), thereby corroborating the rescue of growth, amino acid synthesis defects, and functional Fe-S cluster abundance.

We sought to determine whether the protective effect of the H3H113N mutation was restricted to amino acid synthesis or whether it generally protected Fe-S cluster–dependent function. We tested two disparate cellular processes: respiratory growth, which depends on numerous Fe-S clusters in the tricarboxylic acid cycle and in the electron transport chain (37), and sensitivity to the DNA-damaging agent methyl methanesulfonate (MMS), which challenges the Fe-S cluster–dependent enzymes in the nucleus (38). As expected, depletion of Yfh1 resulted in defective growth in medium containing nonfermentable carbon sources ethanol and glycerol (Fig. 2F) and sensitivity to MMS (Fig. 2G). H3H113N rescued YFH1-off in both contexts, consistent with a broad restoration of Fe-S cluster–dependent functions for various cellular processes (Fig. 2, F and G).

H3H113N prevents global transcriptional rewiring in response to defects in Fe-S cluster production

Yfh1 depletion leads to widespread rewiring of gene expression, including induction of an iron deficiency response (39, 40). We assessed gene expression profiles by mRNA sequencing and found substantial and reproducible alterations in YFH1-off in rich fermentative medium (Fig. 3A). Approximately half of the yeast genome (2867 genes) was significantly differentially expressed in YFH1-off compared to WT (Fig. 3B). However, H3H113N largely prevented most gene expression changes, consistent with the ability to rescue various defects resulting from Yfh1 and Fe-S cluster depletion (Fig. 3B). For example, genes that were at least twofold significantly up-regulated (n = 280) (Fig. 3C) or down-regulated (n = 214) (Fig. 3D) in the YFH1-off strain were largely restored to their normal expression levels in H3^H113N YFH1-off.

As expected, there was significant enrichment for genes involved in iron homeostasis, uptake, and transport among the significantly up-regulated genes in YFH1-off compared to WT (fig. S5A) (39). This is consistent with the function of the transcription factor Aft1, which activates many genes in response to the loss of Fe-S clusters (41, 42). Correspondingly, among the significantly down-regulated genes in YFH1-off compared to WT, cellular processes that use Fe-S clusters as cofactors including the mitochondrial respiratory chain, tricarboxylic acid cycle, and amino acid synthesis were significantly enriched (fig. S5A). This finding is also consistent with previous investigations demonstrating that mRNA abundances of Fe-S cluster genes are generally diminished in concurrence with decreases in cellular iron abundance (43, 44). Among the genes that were rescued by the H3H113N mutation, there was significant enrichment for genes involved in very similar functions, including iron homeostasis and amino acid synthesis (Fig. 3E). Together, the fact that H3H113N prevented most of the transcriptional changes in YFH1-off, as opposed to specific subsets of genes, such as the lysine and glutamate synthesis genes, is consistent with H3H113N broadly preventing disruptions to Fe-S clusters instead of rescuing specific downstream processes.

We considered more closely the expression of genes involved in iron mobilization and utilization, as well as the various Fe-S cluster assembly and target proteins. A majority of the Aft1 target genes displayed significantly elevated expression when Yfh1 was depleted (Fig. 3B and fig. S5B), which is consistent with the enrichment of this set of genes among all up-regulated genes in YFH1-off compared to WT (Fig. 3E). The most highly induced Aft1 target genes were the cell wall mannoproteins FIT1, FIT2, and FIT3, as well as ARN1 and ARN2, which together mediate the uptake of siderophore-iron chelates from the environment (45, 46). H3H113N ameliorated almost all the changes resulting from Yfh1 depletion (Fig. 3B and fig. S5B). As Aft1 responds to the abundance of Fe-S clusters (41), this finding further suggests that H3H113N prevented Fe-S cluster disruptions.

Many of the genes encoding for Fe-S cluster–binding proteins were also differentially expressed in response to Yfh1 depletion (Fig. 3B and fig. S5C). Several members of the mitochondrial Fe-S cluster assembly complex were up-regulated, including ISU1, ISU2, and NFS1 (Fig. 3B and fig. S5C). Induction of these genes suggests a response by cells to compensate for diminished Fe-S cluster assembly in mitochondria. H3H113N almost entirely prevented the up-regulation of the Fe-S cluster assembly proteins in response to Yfh1 depletion (Fig. 3B and fig. S5C), indicating that the histone H3 mutation does not rescue YFH1-off by enhancing the process of Fe-S cluster assembly. Furthermore, genes encoding most other Fe-S cluster–binding proteins displayed significant down-regulation in response to Yfh1 depletion (Fig. 3B and fig. S5C), in correspondence with decreased cellular Fe-S cluster abundance (43). H3H113N mostly prevented the down-regulation of these genes (Fig. 3B and fig. S5C), further suggesting an ability to maintain functional Fe-S clusters despite a diminishment of Fe-S cluster assembly.

Iron abundance, superoxide dismutase, and glutathione do not account for the protective effect of H3H113N when Fe-S cluster assembly is disrupted

Previous studies have identified excessive iron accumulation as a major damaging component when frataxin/Yfh1 function is compromised (47–49). Reduced abundance of cellular Fe-S clusters triggers the activation of Aft1, which, in turn, increases iron uptake from the environment. However, due to ineffective Fe-S cluster assembly in the absence of Yfh1, iron uptake does not effectively restore Fe-S cluster abundance. Instead, iron accumulates in the cell, including in mitochondria, which is proposed to become toxic (42). In agreement with this, we observed that the growth defect of YFH1-off was rescued by the iron chelator bathophenanthrolinedisulfonate (fig. S6A). In addition, YFH1-off displayed sensitivity to highly elevated Fe concentration in media, which the H3H113N mutation ameliorated (fig. S6B).

To determine whether H3H113N was restoring function in YFH1-off by preventing iron accumulation, we generated additional strains in which FET3 was deleted (fet3Δ). The Fet3 multicopper oxidase is part of the high-affinity iron uptake complex and, as an Aft1 target gene, substantially contributes to iron uptake (50–52). Consistent with this, fet3Δ prevented the deterioration of growth of YFH1-off in both SC and SC-lys-glu media (Fig. 4A). However, in contrast to the effect of H3H113N, fet3Δ could not sustain the growth of YFH1-off after several days on solid agar media (Fig. 4A) and did not rescue YFH1-off in liquid culture (Fig. 4B). The H3^H113N YFH1-off fet3Δ triple mutant strain grew substantially more than YFH1-off fet3Δ in SC-lys-glu (Fig. 4A), which suggests that H3H113N prevented the loss of function through a mechanism other than preventing iron uptake.

To corroborate this finding, we examined cellular iron content in YFH1-off strains using inductively coupled plasma mass spectrometry (ICP-MS). Yeast strains were grown in liquid media for the shortest amount of time required for Yfh1 depletion to result in a growth defect in SC-lys-glu medium (and to avoid excessive cell death in the YFH1-off strain). This occurred after 44 hours of YFH1 shutoff (Fig. 4B). Despite the rescue of YFH1-off growth defect by H3H113N, the cellular iron content in YFH1-off and H3^H113N YFH1-off was not significantly different (Fig. 4C). Furthermore, deletion of FET3 decreased cellular iron content similarly in both strains (Fig. 4C). These findings therefore indicate that H3H113N rescues YFH1-off independently of changes in total intracellular iron content.

Fe-S clusters are also highly susceptible to oxidative damage (14, 16). The Cu-Zn superoxide dismutase, Sod1, is a major contributor to antioxidant defense and is likely to protect Fe-S clusters from damage in the presence of oxygen (53). We previously found that H3H113N diminishes Sod1 activity (24). Nonetheless, in the unique context of YFH1-off and the resulting decrease of Fe-S clusters, we considered whether the restoration of function by H3H113N depended on Sod1. We generated additional strains in which SOD1 was deleted (sod1Δ). Consistent with a protective function, sod1Δ exacerbated the deterioration of growth of YFH1-off in both SC and SC-glu media (fig. S7A). Note that we did not use SC-lys-glu medium because sod1Δ is a lysine auxotroph (54). Critically, H3H113N was still able to restore function in the YFH1-off sod1Δ strain (fig. S7A), indicating that the H3H113N protective effects are independent of superoxide dismutase activity.

Glutathione is also a crucial component of cellular redox balance and antioxidant defense. Reduced glutathione (GSH) can also contribute to the maturation of Fe-S cluster proteins (55). Thus, we examined whether H3H113N prevented the dysfunction of YFH1-off by increasing the abundance of GSH. First, we assessed the cellular content of reduced and oxidized glutathione (GSH and GSSG, respectively) in cells growing exponentially in SC medium using MS. The H3^H113N strain did not display significant changes in abundance of GSH or GSSG (fig. S7B). Second, addition of as much as 1 mM exogenous GSH had no effect on the growth defect of YFH1-off or the rescue by H3H113N (fig. S7C). Together, these observations indicate that the rescue of YFH1-off by the H3H113N mutation is unlikely to be related to glutathione abundance.

H3H113N diminishes Cu¹⁺ toxicity to rescue Yfh1 depletion

Our finding that the H3H113N mutation results in resistance to copper toxicity (Fig. 1A) and that Cu¹⁺ ions are especially toxic to Fe-S clusters suggested that the broad rescue of YFH1-off by H3H113N was due to preventing copper toxicity. By the 44-hour time point, total cellular copper content had increased by ~35% in YFH1-off compared to WT (Fig. 5A). This modest accumulation coincided with increased expression of copper mobilization and uptake genes, such as the main copper importer, CTR1 (56), which supports iron homeostasis (56) and may be a direct target of Aft1 (fig. S8A) (57). Conversely, total copper abundance did not change in H3^H113N YFH1-off compared to H3^H113N (Fig. 5A). Addition of 10 μM copper in SC-lys-glu resulted in substantially increased total cellular copper content in YFH1-off and even more so in H3^H113N YFH1-off (fig. S8B). Despite elevated copper accumulation, H3H113N still rescued the growth of YFH1-off in this media (fig. S8C). This indicates that the mechanism by which the H3H113N mutation restores Fe-S cluster homeostasis is not by diminishing total copper accumulation but rather by an impact on copper speciation, namely, a specific decrease in Cu¹⁺ abundance.

To support the notion that H3H113N prevented Cu¹⁺ toxicity when Yfh1 was diminished, we tested whether depletion of total cellular copper would perform similarly. The presence of the copper chelator bathocuproine disulfonate (BCS) rescued the growth of YFH1-off and yfh1Δ in SC-lys-glu medium, similar to but to a lesser extent than the effect of H3H113N (Fig. 5B and fig. S8D). Deletion of CTR1 also prevented the defect in YFH1-off albeit less robustly after several days of growth of YFH1-off cells (fig. S8E). The restoration of function by H3H113N was independent of CTR1, as the H3^H113N YFH1-off ctr1Δ triple mutant grew better than YFH1-off ctr1Δ (Fig. 5C). These findings suggest that the decrease in Cu¹⁺ abundance specifically by H3H113N (24) is a distinct and more substantial protective effect for Fe-S clusters than merely diminishing total copper content. Last, H3H113N ameliorated the increased sensitivity of YFH1-off to excessive exogenous copper (Fig. 5D), consistent with decreased Cu¹⁺ abundance. Together, our findings demonstrate the robust ability of the H3H113N mutation to prevent the deterioration of cellular function when Fe-S cluster assembly is compromised.

Strains and general growth conditions

S. cerevisiae strains used in this study are based on the YLK1879 (S288C background, MATa) and BY4741 (S288C background, MATa) (70) strains, the former of which was a gift from L. Kruglyak (71). Strains are listed in table S1. Strains were generally maintained on YPD (1% yeast extract, 2% peptone, and 2% d-glucose) plates. However, strains with the GAL1 promoter placed upstream of YFH1, GRX5, or ATM1 were maintained on YPG (1% yeast extract, 2% peptone, and 2% galactose) plates. In addition, strains with CTR1 deleted were maintained on YPD/YPG plates supplemented with 20 μM CuSO₄ (normal concentration is ~1 μM Cu) before experiments. The additional copper was not present during experiments. Supplemental copper during routine streaking prevented the accumulation of defects in ctr1∆, thereby improving the reproducibility of experiments. All strains were grown at 30°C in all experiments.

Strain generation

The H3H113N mutation was generated in both chromosomal loci (HHT1 and HHT2) using the CRISPR-Cas9 system optimized for S. cerevisiae (72). For strains in fig. S3D, the H113N mutation was also reversed back to the WT sequence using CRISPR-Cas9. Subsequent gene deletions and promoter insertions were generated by standard yeast gene replacement and targeted insertion methodology using selectable marker integration (73). Successful integrations and deletions were confirmed by polymerase chain reaction. The CUP1 gene was disrupted by the introduction of a stop codon at Phe⁸ at all CUP1 copies using the CRISPR-Cas9 system. Strains in which YFH1 was deleted were phenotypically unstable. Within a few days following the transformation to replace YFH1 with a selectable marker, clones would often spontaneously recover growth rates. Therefore, for the experiments shown in Fig. 1B and figs. S4B and S8D, yfh1Δ strains were used immediately following transformation and were not stored long-term. In all other cases, standard yeast culturing procedures were followed, and strains were continuously maintained on YPD or YPG plates, restreaking cells every 2 weeks for a maximum of four times.

Preparation of solutions, media, and glassware

Removal of contaminating metals from glassware and solutions is a critical precaution to ensure reproducibility of experiments. All glassware was treated with 3.7% hydrochloric acid for ≥12 hours, followed in some cases by ≥12 hours with 7% nitric acid to remove trace metal contamination. All solutions, buffers, and washes were prepared using Milli-Q (Millipore Sigma) ultrapure water. Solutions were prepared using BioUltra grade (Sigma-Aldrich) reagents, when available. For yeast media, addition of all components was done without the use of metal spatulas. Media were filtered through 0.2-μm membranes. Fermentative media were SC (SC medium with 2% glucose, all amino acids, and uracil and adenine), SC lacking lysine or glutamate, or minimal medium (with 2% glucose and either no amino acids or only essential auxotrophic metabolites). Agar media were prepared using acid-washed glassware.

Spot tests

Cells from exponentially growing cultures were fourfold serially diluted and spotted on various media conditions as indicated in the figures. For experiments in which the GAL1 promoter was used to shut off expression for 1, 2, or 3 days, cells on YPG were inoculated into SC medium and grown for approximately 15 hours (day 1). For 2 and 3 days of shutoff, cultures were grown for an additional 48 hours in SC and diluted to optical density at 600 nm (OD₆₀₀) = 0.05 every 24 hours. Cells were allowed to grow for an additional 4 hours to enter exponential growth phase, at which point they were collected for spotting. Spotted plates were incubated at 30°C for up to 4 days and imaged daily. Images shown in the figures were captured when sufficient growth had occurred and growth differences could be assessed (2 to 4 days). For the experiment in Fig. 2A, plates with gradually decreasing amounts of SC amino acid powder (Sunrise Science Products) were prepared while keeping all other components the same [2% glucose, yeast nitrogen base (1.7 g/liter), and ammonium sulfate (5 g/liter)].

Growth of YFH1-off strains in liquid culture

For aconitase assay, ICP-MS, and RNA sequencing (RNA-seq) analyses, YFH1-off cells on YPG were inoculated into SC medium at OD₆₀₀ = 1 and grown for 36 hours in a 30°C shaker, diluting to OD₆₀₀ = 1 every 12 hours. After 36 hours, cells were diluted once more to OD₆₀₀ = 1 in either SC or SC-lys-glu and grown for a further 8 hours (44 hours in total) or for 5 hours in the experiment in fig. S8B. Cells were then processed for downstream assays.

Yeast spheroplasts for aconitase assay

Cell density of 44-hour liquid cultures (YFH1-off and H3^H113N YFH1-off), or exponentially growing cells (WT and H3^H113N), was determined, and equal amounts of cells from each culture were used for producing spheroplasts (2.5 × 10⁹ cells). Cells were washed once with 50 ml of water and once with 400 μl of dithiothreitol (DTT) buffer [100 mM tris-H₂SO₄ (pH 9.2) and 10 mM DTT]. The washed cells were resuspended in 400 μl of DTT buffer and incubated for 20 min at 30°C. Treated cells were then washed twice with 1.3 ml of Zymolyase buffer [20 mM tris-HCl (pH 7.5) and 1.2 M sorbitol], resuspended in 1.3 ml of Zymolyase buffer containing 200 μg of Zymolyase-100T (Nacalai Tesque), and incubated at 30°C for 35 min. Spheroplastization of at least 95% of cells was confirmed under the microscope by a 1:10 dilution into water. Spheroplasts were pelleted at 2000g, and the supernatant was removed.

Aconitase assay

Cellular aconitase activity was assessed using the Aconitase Activity Assay Kit (Sigma-Aldrich, MAK051-1KT), and the manufacturer’s protocol was followed with minor adjustments. Spheroplasts were lysed in 200 μl of assay buffer, centrifuged at 13,000g for 10 min at 4°C, and the supernatant (i.e., the lysate) was recovered. Protein concentration was determined using the BCA Protein Assay Kit (Pierce), and 900 μg of protein was diluted into a final volume of 100 μl in assay buffer containing 1× Protease Inhibitor Cocktail (Pierce). Ten microliters of freshly prepared Activator Solution (following the manufacturer’s protocol) was added to the samples and incubated for 1 hour on ice. Fifty microliters of activated lysate was then mixed with 50 μl of reaction mix, which contains either enzyme and substrate or enzyme alone (for background correction). The reaction was incubated for 1 hour at 25°C, after which 10 μl of developer solution was added to each sample and incubated for another 10 min at 25°C. Absorbance at 450 nm was determined, background was subtracted, and the absorbance readings were converted to product concentration (millimolars of isocitrate) using a standard curve as described by the manufacturer.

Western blot

Standard Western blot methodology was used to detect protein content from whole-cell extracts, with the exception of Yfh1-myc. For Yfh1-myc, a crude mitochondrial extract was prepared as previously described (74), except that the final pellet was resuspended in radioimmunoprecipitation assay buffer [150 mM NaCl/50 mM tris-HCl (pH 8)/1% NP-40 (Ipegal), 0.5% Na-deoxycholate/0.1% SDS]. Primary antibody against Myc (Millipore, catalog no. 05-419, lot no. 3713344) was used at a 1:2000 dilution. Primary antibody against Mia40 was a gift from C. Koehler and was used at a 1:10,000 dilution. Primary antibody against β-actin (Abcam, catalog no. ab170325, lot no. GR3371939-5) was used at a 1:5000 dilution.

⁵⁵Fe labeling

Cells harboring a Myc-tagged Aco1 were grown in SC-galactose for 16 hours or SC-glucose for 36 hours before being switched to the same media lacking iron for 13 hours. Labeling with ⁵⁵Fe was then performed as previously described (75), except that Aco1-Myc was immunoprecipitated using 25 μl of anti-Myc magnetic beads (Pierce, catalog no. 88842, lot no. WA314853) incubated with 250 μl of labeled lysate.

RNA extraction

Cells from the 44-hour cultures (YFH1-off and H3^H113N YFH1-off), or exponentially growing cells (WT and H3^H113N), were collected by centrifugation and frozen at −20°C until processed for RNA extraction and RNA-seq. RNA was extracted using previously published methods (76). RNA extracted for subsequent RNA-seq analysis is from four replicate experiments.

Sample preparation for poly-A RNA-seq

Before preparing RNA-seq libraries for Illumina NovaSeq sequencing, contaminating DNA was digested using Turbo™ DNase (Thermo Fisher Scientific). RNA quality was then assessed on a 1% agarose gel to confirm minimal RNA degradation. RNA-seq libraries were then prepared with the KAPA mRNA Hyper Prep Kit (Kapa Biosystems) according to the manufacturer’s protocols. RNA-seq libraries were assessed for correct fragment size and the presence of adapter dimers by running on a 1% agarose gel. Average library sizes of ~270 base pairs were generated. Libraries were pooled for multiplexed sequencing and further purified using KAPA Pure beads. Total DNA concentration was adjusted to 10 nM for Illumina sequencing.

RNA-seq and differential gene expression analysis

High-throughput sequencing was performed on Illumina’s NovaSeq system. Total read count per library ranged from ~8 million to 14 million. Demultiplexed reads, in FASTQ file format, were processed to check for read and genome alignment quality and to convert reads to normalized gene counts (https://training.galaxyproject.org/training-material/topics/transcriptomics/tutorials/rna-seq-reads-to-counts/tutorial.html) (77). Processing steps included the assessment of raw read quality using FastQC and genome alignment in strand-specific manner to the R64-1-1 S288C reference genome assembly (sacCer3) using HISAT2 (78). Assigning and counting reads for 6692 annotated open reading frames were performed using featureCounts (79). Determination of adjusted P values for differential gene expression comparisons was done using DESeq2 (https://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html) (80). Principal components analysis was performed using a built-in function as part of the DESeq2 package. Significantly differentially expressed genes (adjusted P < 0.05) identified by DESeq2 were assessed for Gene Ontology term enrichment using the Database for Annotation, Visualization, and Integrated Discovery (81, 82) with default parameters. Gene sets for gene expression visualization in heatmaps were constructed by downloading Gene Ontology term gene lists from AmiGO 2 in March 2017.

Inductively coupled plasma mass spectrometry

Cells (8 × 10⁸) from the 44- or 41-hour cultures (YFH1-off strains) or exponentially growing cells (WT and H3^H113N) were collected and washed twice in 5 mM EDTA, to remove cell surface–associated metals, and once in Milli-Q water. Cell pellets were stored at −20°C until further processed for ICP-MS. Cell pellets were overlaid with 143 μl of 70% nitric acid (Fisher, Optima grade, A467-500, lot 1216040) and digested at room temperature for 24 hours, followed by incubation at 65°C for about 4 hours, and lastly being diluted to a final nitric acid concentration of 2% (v/v) with Milli-Q water. Iron and copper contents were determined by ICP–tandem MS (MS/MS) on an Agilent 8900 Triple Quadrupole ICP-MS/MS instrument, in comparison to an environmental calibration standard (Agilent, 5183-4688), using ⁸⁹Y as an internal standard (Inorganic Ventures, MSY-100PPM). The levels of all analytes were determined in MS/MS mode, where ⁶³Cu was measured directly using He in the collision reaction cell, and ⁵⁶Fe was directly determined using H₂ as a cell gas. The average of three to five technical replicate measurements was used for each individual biological replicate. The average variation between technical replicate measurements was 1.4% for all analytes and never exceeded 5% for an individual sample. All Cu and Fe measurements were within the calibrated linear ranges and above the lower limits of detection, as determined from multiple blank samples. ICP MassHunter software was used for ICP-MS data analysis.

MS analysis of glutathione

Cells (6 × 10⁸) from exponentially growing cultures were collected by centrifugation. The cells were washed once in a 43% ice-cold methanol-water solution. To extract the metabolites, the washed cells were resuspended in 200 μl of ice-cold (stored at −80°C) 80% methanol containing 10 nM trifluoromethanesulfonate (TFMS). The resuspended cells were vortexed for 5 s, frozen immediately in liquid nitrogen for 5 min, and then allowed to thaw in an ice bath for 5 min. The cells were pelleted at 16,000g to collect the supernatant. The cell pellet was resuspended in another 100 μl of methanol-TFMS solution and pelleted to collect the supernatant. The combined supernatant was dried under vacuum, and the dried metabolites were stored at −80°C until MS analysis. Extracted dried metabolites were reconstituted in a 50% acetonitrile and 50% dH₂O solution and processed further for analysis by MS as previously described (83).

Statistical analyses

The number of experimental replicates (n) and the observed significance levels are indicated in the figure legends. All statistical analyses were performed using R version 4.0.0, including use of the DESeq2 package, as described above. For most pairwise comparisons, F tests were first performed to determine whether group variances were significantly different. When variances were not different, P values for group differences were determined with the two-sample unpaired t test. When variances were significantly different, P values were determined with the Welch two-sample t test. For pairwise comparisons of ≥2-fold up-regulated or down-regulated genes (Fig. 3, C and D), expression values (normalized read counts) were first averaged across the four biological replicates, transformed into log₁₀ scale, and P values were determined with the paired t test.

Funding: This work was supported by a W. M. Keck Foundation Award to S.K.K. and S.S.M., a Gordon and Betty Moore Foundation Award to S.K.K., and NIH grants GM140106 to S.K.K., CA215185 to H.R.C., and GM42143 to S.S.M. O.A.C. was supported by the Whitcome Predoctoral Fellowship, O.A.C. and C.C. by UCLA Dissertation Year Fellowships, and N.A. by the National Cancer Institute Ruth L. Kirschstein National Research Service Award CA186619 and NIH grant GM8042.

Author contributions: Conceptualization: O.A.C., N.A., M.V., and S.K.K. Methodology: O.A.C., N.A., M.V., and S.K.K. Investigation: O.A.C., N.A., C.C., M.V., N.V.M., S.S., and N.M. Formal analysis: O.A.C. and M.V. Writing—original draft: O.A.C., N.V.M., and S.K.K. Writing—review and editing: O.A.C., N.A., N.V.M., M.V., S.S., S.S.M., and S.K.K. Resources: O.A.C., N.A., H.R.C., S.S.M., and S.K.K. Visualization: O.A.C., C.C., and M.V. Supervision: S.K.K. Project administration: S.K.K. Funding acquisition: H.R.C., S.S.M., and S.K.K.

Competing interests: The authors declare that they have no competing interests.

Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Gene expression datasets are available on the NCBI GEO database (GSE176575).

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• 1.Beinert H., Holm R. H., Munck E., Iron-sulfur clusters: Nature’s modular, multipurpose structures. Science 277, 653–659 (1997). [DOI] [PubMed] [Google Scholar]
• 2.Lill R., Function and biogenesis of iron-sulphur proteins. Nature 460, 831–838 (2009). [DOI] [PubMed] [Google Scholar]
• 3.Campuzano V., Montermini L., Molto M. D., Pianese L., Cossee M., Cavalcanti F., Monros E., Rodius F., Duclos F., Monticelli A., Zara F., Canizares J., Koutnikova H., Bidichandani S. I., Gellera C., Brice A., Trouillas P., De Michele G., Filla A., De Frutos R., Palau F., Patel P. I., Di Donato S., Mandel J. L., Cocozza S., Koenig M., Pandolfo M., Friedreich’s ataxia: Autosomal recessive disease caused by an intronic GAA triplet repeat expansion. Science 271, 1423–1427 (1996). [DOI] [PubMed] [Google Scholar]
• 4.Zhang Y., Lyver E. R., Knight S. A., Pain D., Lesuisse E., Dancis A., Mrs3p, Mrs4p, and frataxin provide iron for Fe-S cluster synthesis in mitochondria. J. Biol. Chem. 281, 22493–22502 (2006). [DOI] [PubMed] [Google Scholar]
• 5.Schilke B., Voisine C., Beinert H., Craig E., Evidence for a conserved system for iron metabolism in the mitochondria of Saccharomyces cerevisiae. Proc. Natl. Acad. Sci. U.S.A. 96, 10206–10211 (1999). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 6.Koutnikova H., Campuzano V., Foury F., Dolle P., Cazzalini O., Koenig M., Studies of human, mouse and yeast homologues indicate a mitochondrial function for frataxin. Nat. Genet. 16, 345–351 (1997). [DOI] [PubMed] [Google Scholar]
• 7.Fontecave M., Ollagnier-de-Choudens S., Iron-sulfur cluster biosynthesis in bacteria: Mechanisms of cluster assembly and transfer. Arch. Biochem. Biophys. 474, 226–237 (2008). [DOI] [PubMed] [Google Scholar]
• 8.Muhlenhoff U., Richhardt N., Ristow M., Kispal G., Lill R., The yeast frataxin homolog Yfh1p plays a specific role in the maturation of cellular Fe/S proteins. Hum. Mol. Genet. 11, 2025–2036 (2002). [DOI] [PubMed] [Google Scholar]
• 9.Chen O. S., Hemenway S., Kaplan J., Inhibition of Fe-S cluster biosynthesis decreases mitochondrial iron export: Evidence that Yfh1p affects Fe-S cluster synthesis. Proc. Natl. Acad. Sci. U.S.A. 99, 12321–12326 (2002). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 10.Rotig A., de Lonlay P., Chretien D., Foury F., Koenig M., Sidi D., Munnich A., Rustin P., Aconitase and mitochondrial iron-sulphur protein deficiency in Friedreich ataxia. Nat. Genet. 17, 215–217 (1997). [DOI] [PubMed] [Google Scholar]
• 11.Bulteau A. L., O’Neill H. A., Kennedy M. C., Ikeda-Saito M., Isaya G., Szweda L. I., Frataxin acts as an iron chaperone protein to modulate mitochondrial aconitase activity. Science 305, 242–245 (2004). [DOI] [PubMed] [Google Scholar]
• 12.Fazius F., Shelest E., Gebhardt P., Brock M., The fungal α-aminoadipate pathway for lysine biosynthesis requires two enzymes of the aconitase family for the isomerization of homocitrate to homoisocitrate. Mol. Microbiol. 86, 1508–1530 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 13.Chen X. J., Wang X., Kaufman B. A., Butow R. A., Aconitase couples metabolic regulation to mitochondrial DNA maintenance. Science 307, 714–717 (2005). [DOI] [PubMed] [Google Scholar]
• 14.Jang S., Imlay J. A., Micromolar intracellular hydrogen peroxide disrupts metabolism by damaging iron-sulfur enzymes. J. Biol. Chem. 282, 929–937 (2007). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 15.Boyd E. S., Thomas K. M., Dai Y., Boyd J. M., Outten F. W., Interplay between oxygen and Fe-S cluster biogenesis: Insights from the Suf pathway. Biochemistry 53, 5834–5847 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 16.Imlay J. A., Cellular defenses against superoxide and hydrogen peroxide. Annu. Rev. Biochem. 77, 755–776 (2008). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 17.Tan G., Yang J., Li T., Zhao J., Sun S., Li X., Lin C., Li J., Zhou H., Lyu J., Ding H., Anaerobic copper toxicity and iron-sulfur cluster biogenesis in Escherichia coli. Appl. Environ. Microbiol. 83, (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 18.Shanmuganathan A., Avery S. V., Willetts S. A., Houghton J. E., Copper-induced oxidative stress in Saccharomyces cerevisiae targets enzymes of the glycolytic pathway. FEBS Lett. 556, 253–259 (2004). [DOI] [PubMed] [Google Scholar]
• 19.Avery S. V., Howlett N. G., Radice S., Copper toxicity towards Saccharomyces cerevisiae: Dependence on plasma membrane fatty acid composition. Appl. Environ. Microbiol. 62, 3960–3966 (1996). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 20.Robinson N. J., Winge D. R., Copper metallochaperones. Annu. Rev. Biochem. 79, 537–562 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 21.Brancaccio D., Gallo A., Piccioli M., Novellino E., Ciofi-Baffoni S., Banci L., [4Fe-4S] cluster assembly in mitochondria and its impairment by copper. J. Am. Chem. Soc. 139, 719–730 (2017). [DOI] [PubMed] [Google Scholar]
• 22.Macomber L., Imlay J. A., The iron-sulfur clusters of dehydratases are primary intracellular targets of copper toxicity. Proc. Natl. Acad. Sci. U.S.A. 106, 8344–8349 (2009). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 23.Vallieres C., Holland S. L., Avery S. V., Mitochondrial ferredoxin determines vulnerability of cells to copper excess. Cell Chem. Biol. 24, 1228–1237.e3 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 24.Attar N., Campos O. A., Vogelauer M., Cheng C., Xue Y., Schmollinger S., Salwinski L., Mallipeddi N. V., Boone B. A., Yen L., Yang S., Zikovich S., Dardine J., Carey M. F., Merchant S. S., Kurdistani S. K., The histone H3-H4 tetramer is a copper reductase enzyme. Science 369, 59–64 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 25.Winge D. R., Nielson K. B., Gray W. R., Hamer D. H., Yeast metallothionein. Sequence and metal-binding properties. J. Biol. Chem. 260, 14464–14470 (1985). [PubMed] [Google Scholar]
• 26.Fogel S., Welch J. W., Tandem gene amplification mediates copper resistance in yeast. Proc. Natl. Acad. Sci. U.S.A. 79, 5342–5346 (1982). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 27.Karthikeyan G., Lewis L. K., Resnick M. A., The mitochondrial protein frataxin prevents nuclear damage. Hum. Mol. Genet. 11, 1351–1362 (2002). [DOI] [PubMed] [Google Scholar]
• 28.Rodriguez-Manzaneque M. T., Tamarit J., Belli G., Ros J., Herrero E., Grx5 is a mitochondrial glutaredoxin required for the activity of iron/sulfur enzymes. Mol. Biol. Cell 13, 1109–1121 (2002). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 29.Uzarska M. A., Dutkiewicz R., Freibert S. A., Lill R., Muhlenhoff U., The mitochondrial Hsp70 chaperone Ssq1 facilitates Fe/S cluster transfer from Isu1 to Grx5 by complex formation. Mol. Biol. Cell 24, 1830–1841 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 30.Kispal G., Csere P., Prohl C., Lill R., The mitochondrial proteins Atm1p and Nfs1p are essential for biogenesis of cytosolic Fe/S proteins. EMBO J. 18, 3981–3989 (1999). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 31.Miller R. E., Stadtman E. R., Glutamate synthase from Escherichia coli. An iron-sulfide flavoprotein. J. Biol. Chem. 247, 7407–7419 (1972). [PubMed] [Google Scholar]
• 32.Muhlenhoff U., Richter N., Pines O., Pierik A. J., Lill R., Specialized function of yeast Isa1 and Isa2 proteins in the maturation of mitochondrial [4Fe-4S] proteins. J. Biol. Chem. 286, 41205–41216 (2011). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 33.Crane B. R., Siegel L. M., Getzoff E. D., Sulfite reductase structure at 1.6 A: Evolution and catalysis for reduction of inorganic anions. Science 270, 59–67 (1995). [DOI] [PubMed] [Google Scholar]
• 34.Kennedy S. C., Rauner R., Gawron O., On pig heart aconitase. Biochem. Biophys. Res. Commun. 47, 740–745 (1972). [DOI] [PubMed] [Google Scholar]
• 35.Ruzicka F. J., Beinert H., The soluble "high potential" type iron-sulfur protein from mitochondria is aconitase. J. Biol. Chem. 253, 2514–2517 (1978). [PubMed] [Google Scholar]
• 36.Robbins A. H., Stout C. D., Structure of activated aconitase: Formation of the [4Fe-4S] cluster in the crystal. Proc. Natl. Acad. Sci. U.S.A. 86, 3639–3643 (1989). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 37.Lill R., Muhlenhoff U., Maturation of iron-sulfur proteins in eukaryotes: Mechanisms, connected processes, and diseases. Annu. Rev. Biochem. 77, 669–700 (2008). [DOI] [PubMed] [Google Scholar]
• 38.Lukianova O. A., David S. S., A role for iron-sulfur clusters in DNA repair. Curr. Opin. Chem. Biol. 9, 145–151 (2005). [DOI] [PubMed] [Google Scholar]
• 39.Foury F., Talibi D., Mitochondrial control of iron homeostasis. A genome wide analysis of gene expression in a yeast frataxin-deficient strain. J. Biol. Chem. 276, 7762–7768 (2001). [DOI] [PubMed] [Google Scholar]
• 40.Yamaguchi-Iwai Y., Dancis A., Klausner R. D., AFT1: A mediator of iron regulated transcriptional control in Saccharomyces cerevisiae. EMBO J. 14, 1231–1239 (1995). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 41.Chen O. S., Crisp R. J., Valachovic M., Bard M., Winge D. R., Kaplan J., Transcription of the yeast iron regulon does not respond directly to iron but rather to iron-sulfur cluster biosynthesis. J. Biol. Chem. 279, 29513–29518 (2004). [DOI] [PubMed] [Google Scholar]
• 42.Kumanovics A., Chen O. S., Li L., Bagley D., Adkins E. M., Lin H., Dingra N. N., Outten C. E., Keller G., Winge D., Ward D. M., Kaplan J., Identification of FRA1 and FRA2 as genes involved in regulating the yeast iron regulon in response to decreased mitochondrial iron-sulfur cluster synthesis. J. Biol. Chem. 283, 10276–10286 (2008). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 43.Puig S., Askeland E., Thiele D. J., Coordinated remodeling of cellular metabolism during iron deficiency through targeted mRNA degradation. Cell 120, 99–110 (2005). [DOI] [PubMed] [Google Scholar]
• 44.Puig S., Vergara S. V., Thiele D. J., Cooperation of two mRNA-binding proteins drives metabolic adaptation to iron deficiency. Cell Metab. 7, 555–564 (2008). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 45.Protchenko O., Ferea T., Rashford J., Tiedeman J., Brown P. O., Botstein D., Philpott C. C., Three cell wall mannoproteins facilitate the uptake of iron in Saccharomyces cerevisiae. J. Biol. Chem. 276, 49244–49250 (2001). [DOI] [PubMed] [Google Scholar]
• 46.Yun C. W., Ferea T., Rashford J., Ardon O., Brown P. O., Botstein D., Kaplan J., Philpott C. C., Desferrioxamine-mediated iron uptake in Saccharomyces cerevisiae. J. Biol. Chem. 275, 10709–10715 (2000). [DOI] [PubMed] [Google Scholar]
• 47.Foury F., Cazzalini O., Deletion of the yeast homologue of the human gene associated with Friedreich’s ataxia elicits iron accumulation in mitochondria. FEBS Lett. 411, 373–377 (1997). [DOI] [PubMed] [Google Scholar]
• 48.Babcock M., de Silva D., Oaks R., Davis-Kaplan S., Jiralerspong S., Montermini L., Pandolfo M., Kaplan J., Regulation of mitochondrial iron accumulation by Yfh1p, a putative homolog of frataxin. Science 276, 1709–1712 (1997). [DOI] [PubMed] [Google Scholar]
• 49.Delatycki M. B., Camakaris J., Brooks H., Evans-Whipp T., Thorburn D. R., Williamson R., Forrest S. M., Direct evidence that mitochondrial iron accumulation occurs in Friedreich ataxia. Ann. Neurol. 45, 673–675 (1999). [PubMed] [Google Scholar]
• 50.Stearman R., Yuan D. S., Yamaguchi-Iwai Y., Klausner R. D., Dancis A., A permease-oxidase complex involved in high-affinity iron uptake in yeast. Science 271, 1552–1557 (1996). [DOI] [PubMed] [Google Scholar]
• 51.Askwith C., Eide D., Van Ho A., Bernard P. S., Li L., Davis-Kaplan S., Sipe D. M., Kaplan J., The FET3 gene of S. cerevisiae encodes a multicopper oxidase required for ferrous iron uptake. Cell 76, 403–410 (1994). [DOI] [PubMed] [Google Scholar]
• 52.Yamaguchi-Iwai Y., Stearman R., Dancis A., Klausner R. D., Iron-regulated DNA binding by the AFT1 protein controls the iron regulon in yeast. EMBO J. 15, 3377–3384 (1996). [PMC free article] [PubMed] [Google Scholar]
• 53.De Freitas J. M., Liba A., Meneghini R., Valentine J. S., Gralla E. B., Yeast lacking Cu-Zn superoxide dismutase show altered iron homeostasis. Role of oxidative stress in iron metabolism. J. Biol. Chem. 275, 11645–11649 (2000). [DOI] [PubMed] [Google Scholar]
• 54.Lin S. J., Culotta V. C., Suppression of oxidative damage by Saccharomyces cerevisiae ATX2, which encodes a manganese-trafficking protein that localizes to Golgi-like vesicles. Mol. Cell. Biol. 16, 6303–6312 (1996). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 55.Muhlenhoff U., Braymer J. J., Christ S., Rietzschel N., Uzarska M. A., Weiler B. D., Lill R., Glutaredoxins and iron-sulfur protein biogenesis at the interface of redox biology and iron metabolism. Biol. Chem. 401, 1407–1428 (2020). [DOI] [PubMed] [Google Scholar]
• 56.Dancis A., Haile D., Yuan D. S., Klausner R. D., The Saccharomyces cerevisiae copper transport protein (Ctr1p). Biochemical characterization, regulation by copper, and physiologic role in copper uptake. J. Biol. Chem. 269, 25660–25667 (1994). [PubMed] [Google Scholar]
• 57.MacIsaac K. D., Wang T., Gordon D. B., Gifford D. K., Stormo G. D., Fraenkel E., An improved map of conserved regulatory sites for Saccharomyces cerevisiae. BMC Bioinformatics 7, 113 (2006). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 58.Darash-Yahana M., Pozniak Y., Lu M. Y., Sohn Y. S., Karmi O., Tamir S., Bai F., Song L. H., Jennings P. A., Pikarsky E., Geiger T., Onuchic J. N., Mittler R., Nechushtai R., Breast cancer tumorigenicity is dependent on high expression levels of NAF-1 and the lability of its Fe-S clusters. Proc. Natl. Acad. Sci. U.S.A. 113, 10890–10895 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 59.Oshiro S., Morioka M. S., Kikuchi M., Dysregulation of iron metabolism in Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis. Adv. Pharmacol. Sci. 2011, 1–8 (2011). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 60.Rouault T. A., Tong W. H., Iron-sulfur cluster biogenesis and human disease. Trends Genet. 24, 398–407 (2008). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 61.Rudolf J., Makrantoni V., Ingledew W. J., Stark M. J. R., White M. F., The DNA repair helicases XPD and FancJ have essential iron-sulfur domains. Mol. Cell 23, 801–808 (2006). [DOI] [PubMed] [Google Scholar]
• 62.Jain R., Vanamee E. S., Dzikovski B. G., Buku A., Johnson R. E., Prakash L., Prakash S., Aggarwal A. K., An iron-sulfur cluster in the polymerase domain of yeast DNA polymerase ε. J. Mol. Biol. 426, 301–308 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 63.Ye H., Jeong S. Y., Ghosh M. C., Kovtunovych G., Silvestri L., Ortillo D., Uchida N., Tisdale J., Camaschella C., Rouault T. A., Glutaredoxin 5 deficiency causes sideroblastic anemia by specifically impairing heme biosynthesis and depleting cytosolic iron in human erythroblasts. J. Clin. Invest. 120, 1749–1761 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 64.Boultwood J., Pellagatti A., Nikpour M., Pushkaran B., Fidler C., Cattan H., Littlewood T. J., Malcovati L., Della Porta M. G., Jadersten M., Killick S., Giagounidis A., Bowen D., Hellstrom-Lindberg E., Cazzola M., Wainscoat J. S., The role of the iron transporter ABCB7 in refractory anemia with ring sideroblasts. PLOS ONE 3, e1970 (2008). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 65.Vaubel R. A., Isaya G., Iron-sulfur cluster synthesis, iron homeostasis and oxidative stress in Friedreich ataxia. Mol. Cell. Neurosci. 55, 50–61 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 66.Ast T., Meisel J. D., Patra S., Wang H., Grange R. M. H., Kim S. H., Calvo S. E., Orefice L. L., Nagashima F., Ichinose F., Zapol W. M., Ruvkun G., Barondeau D. P., Mootha V. K., Hypoxia rescues frataxin loss by restoring iron sulfur cluster biogenesis. Cell 177, 1507–1521 e16 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 67.Pandey A. K., Pain J., Dancis A., Pain D., Mitochondria export iron-sulfur and sulfur intermediates to the cytoplasm for iron-sulfur cluster assembly and tRNA thiolation in yeast. J. Biol. Chem. 294, 9489–9502 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 68.Pearson S. A., Wachnowsky C., Cowan J. A., Defining the mechanism of the mitochondrial Atm1p [2Fe-2S] cluster exporter. Metallomics 12, 902–915 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 69.Allikmets R., Raskind W. H., Hutchinson A., Schueck N. D., Dean M., Koeller D. M., Mutation of a putative mitochondrial iron transporter gene (ABC7) in X-linked sideroblastic anemia and ataxia (XLSA/A). Hum. Mol. Genet. 8, 743–749 (1999). [DOI] [PubMed] [Google Scholar]
• 70.Brachmann C. B., Davies A., Cost G. J., Caputo E., Li J., Hieter P., Boeke J. D., Designer deletion strains derived from Saccharomyces cerevisiae S288C: A useful set of strains and plasmids for PCR-mediated gene disruption and other applications. Yeast 14, 115–132 (1998). [DOI] [PubMed] [Google Scholar]
• 71.Bloom J. S., Ehrenreich I. M., Loo W. T., Lite T. L., Kruglyak L., Finding the sources of missing heritability in a yeast cross. Nature 494, 234–237 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 72.Ryan O. W., Skerker J. M., Maurer M. J., Li X., Tsai J. C., Poddar S., Lee M. E., DeLoache W., Dueber J. E., Arkin A. P., Cate J. H., Selection of chromosomal DNA libraries using a multiplex CRISPR system. eLife 3, (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 73.Longtine M. S., McKenzie A. III, Demarini D. J., Shah N. G., Wach A., Brachat A., Philippsen P., Pringle J. R., Additional modules for versatile and economical PCR-based gene deletion and modification in Saccharomyces cerevisiae. Yeast 14, 953–961 (1998). [DOI] [PubMed] [Google Scholar]
• 74.Meisinger C., Pfanner N., Truscott K. N., Isolation of yeast mitochondria. Methods Mol. Biol. 313, 33–39 (2006). [DOI] [PubMed] [Google Scholar]
• 75.Pierik A. J., Netz D. J., Lill R., Analysis of iron-sulfur protein maturation in eukaryotes. Nat. Protoc. 4, 753–766 (2009). [DOI] [PubMed] [Google Scholar]
• 76.Schmitt M. E., Brown T. A., Trumpower B. L., A rapid and simple method for preparation of RNA from Saccharomyces cerevisiae. Nucleic Acids Res. 18, 3091–3092 (1990). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 77.Batut B., Hiltemann S., Bagnacani A., Baker D., Bhardwaj V., Blank C., Bretaudeau A., Brillet-Gueguen L., Cech M., Chilton J., Clements D., Doppelt-Azeroual O., Erxleben A., Freeberg M. A., Gladman S., Hoogstrate Y., Hotz H. R., Houwaart T., Jagtap P., Lariviere D., Le Corguille G., Manke T., Mareuil F., Ramirez F., Ryan D., Sigloch F. C., Soranzo N., Wolff J., Videm P., Wolfien M., Wubuli A., Yusuf D.; Galaxy Training Network, Taylor J., Backofen R., Nekrutenko A., Gruning B., Community-driven data analysis training for biology. Cell Syst. 6, 752–758 e1 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 78.Kim D., Paggi J. M., Park C., Bennett C., Salzberg S. L., Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat. Biotechnol. 37, 907–915 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 79.Liao Y., Smyth G. K., Shi W., featureCounts: An efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014). [DOI] [PubMed] [Google Scholar]
• 80.Love M. I., Huber W., Anders S., Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 81.Huang D. W., Sherman B. T., Lempicki R. A., Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44–57 (2009). [DOI] [PubMed] [Google Scholar]
• 82.Huang D. W., Sherman B. T., Lempicki R. A., Bioinformatics enrichment tools: Paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 37, 1–13 (2009). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 83.Mullen P. J., Garcia G. Jr., Purkayastha A., Matulionis N., Schmid E. W., Momcilovic M., Sen C., Langerman J., Ramaiah A., Shackelford D. B., Damoiseaux R., French S. W., Plath K., Gomperts B. N., Arumugaswami V., Christofk H. R., SARS-CoV-2 infection rewires host cell metabolism and is potentially susceptible to mTORC1 inhibition. Nat. Commun. 12, 1876 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

Supplementary Materials