Introduction
Mitochondria are a central hub for many cellular processes, including ATP production, redox control, biosynthetic programs, and signaling (Chandel, 2015; Pagliarini and Rutter, 2013; Spinelli and Haigis, 2018). Each function—critical for cell homeostasis—relies on the ability of mitochondria to maintain a membrane potential across the inner membrane of this double-membrane organelle. This mitochondrial membrane potential (MMP, ΔΨm) directly provides the energy to power ATP synthesis, mitochondrial protein import, and metabolite and ion transport. Either directly or indirectly, it also provides signaling mechanisms to assist in adapting cellular behavior that can be critical to cell health.
Therefore, it is not surprising that impaired MMP is highly correlated with cellular dysfunction in aging (Hagen et al., 1997; Hughes et al., 2020; Leprat et al., 1990; Mansell et al., 2021; Sastre et al., 1996; Sugrue and Tatton, 2001) and a variety of diseases, including primary mitochondrial disease (Burelle et al., 2015; James et al., 1996) and heart failure (Cluntun et al., 2021; Sharov et al., 2005). While it is likely that MMP reduction plays a causal role in the pathogenesis of these diseases, the tools to formally test its impact on each disease are limited. In the context of aging, activating an artificial proton pump in
The canonical mechanism to generate MMP is by complexes I, III, and IV of the ETC, which pump protons from the mitochondrial matrix to the intermembrane space (IMS). This intricate process extracts high-energy electrons and passes them through the ETC complexes while using the resultant energy to pump protons from the matrix to IMS. The energy of these protons passing back to the matrix is then used to power ATP synthase, metabolite carriers, and protein translocases. However, several studies have described an alternative mechanism for the generation of MMP, namely ATP synthase running in reverse—hydrolyzing ATP to ADP and using the energy to pump protons to the IMS and augment the MMP (Junge and Nelson, 2015; Okuno et al., 2011). For example, Vasan et al. reported that the MMP is maintained in complex III-deficient cells through this ATP synthase mechanism (Vasan et al., 2022). Despite this long-standing hypothesis, there is conflicting data that argues against this phenomenon (Vowinckel et al., 2021). Yet, observations for alternative MMP generation mechanism via ATP hydrolysis illustrate that cells will sacrifice hard-earned ATP to sustain their membrane potential, underlining the essentiality of MMP for cell well-being and insinuating the existence of control mechanisms to maintain MMP (Ernst et al., 2019; Liu et al., 2021; Martínez-Reyes et al., 2016).
MMP is required for viability and proliferation in most eukaryotic cells, but the strength of the MMP is highly variable between cells of different tissue origins and is dynamic across biological conditions (Huang et al., 2004; Mitra et al., 2009). For example, relative to normal cells, cancer cells tend to have a higher MMP (Davis et al., 1985; Heerdt et al., 2005; Summerhayes et al., 1982) as do cells experiencing amino acid starvation (Johnson et al., 2014). Generally, nutrient and other biological stress scenarios also modulate MMP (Hübscher et al., 2016, p. 70; Pan et al., 2011); in particular, oxidative stress has been shown to decrease MMP (Korshunov et al., 1997; Satoh et al., 1997). This heterogeneity in MMP amongst cell types and contexts led us to hypothesize that each cell might have an MMP setpoint that is tuned to the energetic and biosynthetic demands of the cell, and is perhaps responsive to nutrients and stressors in the environment. While there are well-appreciated negative consequences when MMP is too low, inappropriately elevated MMP can lead to toxic metabolic byproducts, such as reactive oxygen species. We only have sparse knowledge of whether cells actually have an MMP setpoint. If they do, how is it determined? What are the stimuli that are monitored to determine the setpoint? What are the signaling molecules that communicate this information? How is the machinery of mitochondrial bioenergetics altered to enact the setpoint and maintain this optimal MMP? Answering these questions will provide a much clearer understanding of the connection between cell physiology, mitochondrial bioenergetics, and human disease.
We became interested in MMP and its regulation through our previous studies of the mitochondrial fatty acid synthesis (mtFAS) system. We and others showed that loss of this pathway results in the absence of the lipoic acid cofactor as well as loss of acylated acyl carrier protein (ACP), which is required for the assembly and activation of many mitochondrial complexes, including each ETC complex (Angerer et al., 2017; Brody et al., 1997; Nowinski et al., 2020; Van Vranken et al., 2018). Using a genetic screen in yeast to identify genes required for the transcriptional alterations induced in mtFAS mutants, we found that the deletion of
Results
To understand the transcriptional reprogramming that occurs during the loss of mtFAS, and by extension, the interplay between dysfunctional mitochondrial and cell health, we reanalyzed an RNA-sequencing dataset (Berg et al., 2023) generated from a yeast mutant lacking mtFAS function (
We validated all 73 mutants by performing RT-qPCR on four additional genes that were upregulated in
Figure 1.
(A, B) Normalized gene expression of
Figure 1—figure supplement 1.
Genetic screen to identify
(A, B) Heat map visualizing selected gene expression between wild-type (WT) and
Based on these gene expression data, as well as previous literature suggesting a role for
The import of many mitochondrial proteins from the cytosol depends upon and thus serves as a proxy for MMP. We used a yeast strain expressing a C-terminally FLAG-tagged Ilv2 at its endogenous locus (Dasari and Kölling, 2011). Upon import into mitochondria, the N-terminal mitochondrial targeting sequence (MTS) of Ilv2-FLAG is cleaved, thereby allowing us to distinguish between imported and unimported species and providing a quantitative measurement of Ilv2-FLAG import as assessed by immunoblotting of whole-cell lysates. In wild-type cells, the majority of Ilv2-FLAG is present as a lower molecular weight form with the MTS cleaved (Figure 1F); however, a portion of the Ilv2-FLAG protein is visible as a higher molecular weight form, suggesting it has not been cleaved and thus imported into mitochondria. Depletion of the MMP either by treatment for 6 hr with the ionophore CCCP or by deletion of
Because the changes in mitochondrial function observed in the
Figure 2.
(A) Volcano plot of the transcriptomics data of
Figure 2—figure supplement 1.
(A) Mitochondria were isolated from wild-type (WT),
The enriched ETC complex abundance observed in the
The presence of assembled ETC complexes in
The yeast Hap complex has been shown to transcriptionally induce the expression of OXPHOS components (Bonander et al., 2008; Mao and Chen, 2019). We assessed whether increased expression of OXPHOS components by the Hap complex might be sufficient to increase MMP similar to what we observed in
As a result of the OXPHOS complex abundance and activity data, we asked whether the enhanced MMP in
To orthogonally test whether the
The
To discover the mechanisms through which the
Figure 3.
Phosphate starvation increases mitochondrial membrane potential through electron transport chain (ETC)-dependent and independent mechanisms.
(A) Volcano plot of phosphoproteomics data of
Figure 3—figure supplement 1.
Phosphate depletion increases mitochondrial membrane potential in wild-type and
(A) Wild-type (WT) cells expressing Tom70-GFP from its endogenous locus were grown in media containing high phosphate (10 mM Pi) or low phosphate (1 μM Pi) for 4 hr.
Phosphate depletion increases mitochondrial membrane potential in wild-type and
Given the unexpected activation of a phosphate starvation response upon deletion of
Next, we examined respiratory complex assembly to determine additional ETC and ATP synthase-related factors contributing to MMP. Using BN-PAGE, we found that in wild-type cells, phosphate depletion led to a modest enrichment in ETC complex abundance compared to cells grown in normal phosphate concentrations (Figure 4A). Inversely, as expected, depleting phosphate in
Figure 4.
Phosphate depletion promotes mitochondrial membrane potential via ADP/ATP carrier in cells without electron transport chain (ETC) and ATP synthase.
(A) Wild-type (WT) and
We then treated cells with a series of mitochondrial inhibitors to parse out contributions of the ETC, ATP synthase, and other mechanisms to the MMP. Because electron transfer through complexes III and IV is tightly coupled to one another and with proton pumping, the complex III inhibitor antimycin A (AA) is sufficient to block the activities of both complexes. Most of the membrane potential was lost in cells treated with antimycin A in either normal or low phosphate-containing media (Figure 4B); however, even in the presence of antimycin A, low phosphate still triggered a similarly fold elevation in membrane potential. Together with the BN-PAGE results, we concluded that ETC complexes are slightly enriched with phosphate depletion, but this is not required for the increase in MMP.
Bongkrekic acid is an inhibitor of the ADP/ATP carrier (AAC) (Lauquin and Vignais, 1976), which resides on the mitochondrial inner membrane and normally imports ADP and exports ATP to sustain mitochondrial ATP synthesis and cytosolic ATP consumption. Treatment of wild-type cells with bongkrekic acid significantly dampened the phosphate depletion-mediated increase in MMP (Figure 4B). Importantly, combination treatment with both antimycin A and bongkrekic acid completely blocked the induction of MMP in response to low phosphate (Figure 4B). As a genetic alternative to antimycin A inhibition of the ETC, we grew
These experiments suggest a mechanism whereby the depletion of phosphate increases MMP in an ETC- and ATP synthase-independent manner. When the ADP/ATP carrier imports ATP4- and exports ADP3-, a net export of a positive charge occurs out of the matrix to the IMS (Figure 4D). This activity must be coupled to ATP hydrolysis within the mitochondrial matrix. It would also be coupled to the export of phosphate from the matrix, which is co-transported with a proton through the phosphate carrier. Our data suggest that when cells lack the proton-pumping ability of the ETC—either by chemical treatment (i.e., antimycin A) or genetic inhibition (mtDNA loss in
Phosphate starvation signaling induces mitochondrial membrane potential
The phosphate signaling system in yeast (Kaffman et al., 1994; Mouillon and Persson, 2006) employs the cyclin and cyclin-dependent kinase, Pho80 and Pho85, respectively. Under normal phosphate conditions, Pho85 is active but it is inhibited during phosphate depletion. When active, Pho85 phosphorylates and inactivates Pho4, a transcriptional factor that stimulates PHO regulon genes to promote phosphate acquisition, maintenance, and mobilization (Figure 5—figure supplement 1A).
Deletion of
Figure 5.
Activation of phosphate signaling increases mitochondrial membrane potential.
(A) Normalized mitochondrial membrane potential of wild-type (WT),
Figure 5—figure supplement 1.
Phosphate starvation signaling increases mitochondrial membrane potential.
(A) Schematics of phosphate starvation signaling in yeast. (B) Representative images of wild-type (WT),
Next, we asked whether deletion of
We demonstrated that phosphate depletion utilizes mainly the mitochondrial ATP hydrolysis pathway, via the exchange of differentially charged nucleotides, to generate MMP. Similar models have been proposed previously, and it was suggested that the F1 subunit of the ATP synthase (Atp1 and Atp2) catalyzes the ATP hydrolysis (ATP synthase of yeast mitochondria—GIRAUD - 1994, 2023; Lefebvre-Legendre et al., 2003). To test this model, we attempted to generate combination mutants of
Depleting phosphate increases mitochondrial membrane potential in higher eukaryotes
Given the importance of MMP for human health and disease, we tested whether phosphate depletion might also enhance MMP in the HEK293T (embryonic kidney) and A375 (melanoma) human cells. Both HEK293T and A375 cells exhibited increased MMP after 3 d of growth in phosphate-free medium (Figure 6A, Figure 6—figure supplement 1A). We quantified the morphology of the mitochondrial network based on two parameters: summed branch length mean, which describes the mean of summed length of mitochondrial tubules in each independent structure, and network branch number mean, which describes the mean number of attached mitochondrial tubules in each independent structure. Consistent with the increased MMP, HEK293T and A375 cells grown in low phosphate exhibited a more connected and elongated mitochondrial network (Figure 6B, Figure 6—figure supplement 1B). As an alternative strategy to limit phosphate uptake from the media, we treated these same cell lines with the phosphate transporter inhibitor phosphonoformic acid (PFA) for 48 hr. We observed a dose-dependent increase in MMP in both cell lines (Figure 6C). We concluded that phosphate depletion induces a higher MMP in cultured mammalian cell lines.
Figure 6.
Phosphate depletion induces increased mitochondrial membrane potential in higher eukaryotic cells.
(A) The indicated cell lines were cultured with 1 mM (+Pi) or no phosphate (-Pi) for 3 d. Mitochondrial membrane potential was quantified by flow cytometry measurement of 10,000 cells stained with MitoTracker Red. n = 3. Error bars represent the SD. Statistical significance was determined using an unpaired two-tailed
Figure 6—figure supplement 1.
Phosphate depletion induces elevated mitochondrial membrane potential in mammalian cells.
(A) HEK293T and A375 cells were cultured in 1 mM (+Pi)- or no phosphate (-Pi)-containing media for 3 d. Cells were treated with 25 μM CCCP for 3 hr, stained with MitoTracker Red, and imaged. Representative images are shown. Scale bar represents 5 μM. (B) Summed branch lengths mean and network branch mean were measured and calculated by Mitochondrial Network Analysis (MiNA). Error bars represent the SD. Statistical significance was determined using an unpaired two-tailed
Immortalized cell lines may have adaptations that are not representative of native cells
Finally, we used the fruit fly
Discussion
The work described herein was initially intended to define the signaling and transcriptional network that underlies the positive and negative gene expression effects of a mutant that lacks the mtFAS system, and therefore lacks assembly of the respiratory system. This line of inquiry led to a series of observations that demonstrated a previously unappreciated role of environmental sensing and cellular signaling in controlling MMP (summarized in Table 1). As a result, we propose a putative model that, based on energetic demand, environmental status, and intracellular signaling, cells establish and maintain a MMP ‘setpoint’, which is tailored to maintain optimal mitochondrial function. We find that cells deploy multiple ETC-dependent and -independent strategies to maintain that setpoint. Critically, we find that cells often prioritize this MMP setpoint over other bioenergetic priorities, even in challenging environments, suggesting an important evolutionary benefit.
Table 1.
Summary of observations in
| Measurement | Background | Perturbation | |
|---|---|---|---|
| Phosphate depletion | |||
| MMP | WT | High | High |
| High | Higher than | ||
| Higher than | Higher than | ||
| Mitochondrial protein import efficiency | WT | More efficient | More efficient |
| More efficient | More efficient than | ||
| ETC | WT | Enriched | Unchanged |
| More enriched than | Complex III, IV: remain absent | ||
We first made the observation that deletion of the
The transcriptional and phosphoproteomic effects of
One of the more surprising findings from this work is that the phosphate starvation response increases MMP independently of either of the two well-established MMP generation mechanisms, proton pumping by the ETC or ATP hydrolysis-dependent proton pumping by the ATP synthase. Phosphate starvation or the deletion of
The elevated MMP setpoint has significant functional consequences, as demonstrated by the partially mitochondrial Ilv2-FLAG protein becoming completely imported and cleaved upon loss of Sit4 or phosphate depletion. It is likely that many other proteins either gain or enhance their mitochondrial matrix localization and activity as well. It has been previously described that reduction in MMP can alter the import properties of proteins and thereby trigger cellular signaling events related to mitophagy, transcriptional responses, and others (Becker et al., 2012.; Berry et al., 2021.; Jin et al., 2010; Miceli et al., 2011; Rolland et al., 2019). The scope of responses elicited in cells experiencing high MMP, however, has not been previously interrogated to the same extent as cells with reduced MMP.
What is the evolutionary advantage of the mitochondrial ATP hydrolysis pathway, which uses the energy of ATP hydrolysis to increase the MMP? We propose a speculative hypothesis that this mechanism enables the liberation of needed phosphate from the most abundant labile store of phosphate, ATP. However, cleaving the phosphodiester bonds of ATP releases energy in addition to releasing phosphate. Using this mitochondrial mechanism enables the cell to capture that energy in the form of the MMP rather than having it be simply lost as heat. As a result, the elevated MMP is able to fuel mitochondrial processes and empowers the cell to better combat nutrient scarcity. This phenomenon also appears to be evolutionarily conserved as cellular phosphate depletion also increases MMP in primary and immortalized human cells and in cells of the fly midgut in vivo (Figure 6).
Our results across the eukaryotic kingdom indicate that the higher MMP induced by phosphate deprivation contributes to improved mitochondrial energetics, morphology, and overall robustness, which could have profound implications for the many diseases, as well as the aging process itself, that are characterized by reduced MMP (Hagen et al., 1997; Hughes et al., 2020; Leprat et al., 1990; Mansell et al., 2021; Sastre et al., 1996; Sugrue and Tatton, 2001). It has been well established that phosphate limitation can extend lifespan in yeast, flies, and mice (Bergwitz et al., 2013; Ebrahimi et al., 2021; Kurosu et al., 2005; Kurosu et al., 2006). In both the fly and mouse, it was also conversely demonstrated that excessive phosphate shortens lifespan (Bergwitz et al., 2013; Kuro-o et al., 1997). In these studies, the exact mechanisms whereby phosphate abundance and sensing affect lifespan were not established. We observed increased MMP in flies treated with PFA, which limits phosphate uptake (Figure 6E). Other measurements showed improvement in gut integrity and negative geotaxis (Figure 6F and G). From the evidence presented herein (Figure 6E–G, Figure 6—figure supplement 1C), as well as the previous study showing that PFA treatment extends lifespan (Bergwitz et al., 2013) and enhances intestinal health in flies (Xu et al., 2023), we hypothesize that phosphate deprivation increased MMP and overall mitochondrial health, and thereby enabled lifespan extension. This connection is supported by a recent study that demonstrated that boosting MMP by photo-activation of an ectopically expressed proton pump is sufficient to prolong lifespan in
This work identified genetic and environmental interventions that appear to elevate the setpoint of MMP. This improves mitochondrial protein import efficiency, results in more connected mitochondrial morphology, and reverses other deficiencies found in mutants that have low MMP. This work thus proposes that MMP can be modulated through cellular signaling, including augmentation of MMP above that typically observed in a wild-type cell. It also demonstrates that this MMP augmentation can occur in the absence of a functional respiratory chain. As a result, these observations lay the foundation for future studies to identify interventions that can impact the signaling mechanisms that control MMP for therapeutic benefit.
Materials and methods
Yeast strains and growth conditions
Table 2.
Yeast strains used in this study.
| Genotype | Source | JRY identifier |
|---|---|---|
| WT (BY4741) | Van Vranken et al., 2018 | JRY 2884 |
| Van Vranken et al., 2018 | JRY 2885 | |
| can1::STE2p-Sp_HIS5 lyp1del btt1::Renilla-BTT1terminator-HygMX cit2::Firefly-CIT2terminator-Met15 ho::pr-cit2-term-pr-btt1-term-ura3 mct1::NatMX | This study | JRY 4614 |
| can1::STE2p-Sp_HIS5 lyp1del btt1::Renilla-BTT1terminator-HygMX cit2::Firefly-CIT2terminator-Met15 ho:: pr-cit2-term-pr-btt1-term-ura3 | This study | JRY 4616 |
| This study | JRY 4144 | |
| This study | JRY 4145 | |
| ILV2-FLAG::KanMX | Dr. Cory Dunn | JRY 4383/CDD1084 |
| This study | JRY 4389 | |
| This study | JRY 4385 | |
| This study | JRY 4387 | |
| This study | JRY 4556 | |
| This study | JRY 4552 | |
| This study | JRY 4631 | |
| This study | JRY 4633 | |
| This study | JRY 4719 | |
| This study | JRY 4720 | |
| This study | JRY 4721 | |
| This study | JRY 4715 | |
| This study | JRY 4716 | |
| This study | JRY 4743 | |
| This study | JRY 4744 | |
|
| This study | JRY 4941 |
| Tom70-yeGFP::hisMX | This study | JRY 7502 |
| Tom70-yeGFP::hisMX | This study | JRY 7504 |
| Tom70-yeGFP::hisMX | This study | JRY 7506 |
| Tom70-yeGFP::hisMX | This study | JRY 7508 |
| Tom70-yeGFP::hisMX | This study | JRY 7510 |
| Tom70-yeGFP::KanMX | This study | JRY 7514 |
| Tom70-yeGFP::KanMX | This study | JRY 7515 |
| Tom70-yeGFP::KanMX | This study | JRY 7516 |
Table 3.
Antibodies used in this study.
| Antibodies | Source |
|---|---|
| FLAG epitope | Sigma-Aldrich, F7425 |
| Sdh2 | Dr. Dennis Winge |
| Rip1 | Dr. Dennis Winge |
| Atp2 | Dr. Dennis Winge |
| Por1 | Abcam, ab110326 |
| Lipoic acid | Abcam, ab58724 |
| Pgk1 | Abcam, ab113687 |
Table 4.
Plasmids used in this study.
| Plasmids | Source |
|---|---|
| pRS416 Acp1-HA-FLAG | Van Vranken et al., 2018 |
| pRS416 Sit4-HA-FLAG | This study |
Table 5.
Chemicals and commercial kits used in this study.
| Chemicals | Source |
|---|---|
| sodium phosphonoformate tribasic hexahydrate | Sigma-Aldrich, P6801 |
| b-mercaptoethanol | Sigma-Aldrich, M6250 |
| Digitonin special-grade (water-soluble) | Gold Biotechnology, D-180 |
| Lyticase from | Sigma-Aldrich, L4025 |
| Protease inhibitor cocktail (yeast) | Sigma-Aldrich, P8215 |
| B-ethylmaleimide | Sigma-Aldrich, E3876 |
| anti-HA antibody-conjugated agarose | Sigma-Aldrich, A2095 |
| NativePAGE 20× running buffer | Invitrogen, BN2001 |
| NativePAGE 20× cathode buffer additive | Invitrogen, BN2002 |
| NativePAGE sample buffer (4×) | Invitrogen, BN20032 |
| NativePAGE 5% G-250 sample additive | Invitrogen, BN20041 |
| Ponceau S solution | Sigma-Aldrich, P7170 |
| Antimycin A | Sigma-Aldrich, A8674 |
| Bongkretic acid | Sigma-Aldrich, B6179 |
| MitoTracker Red CMXROS | Invitrogen Life, M7512 |
| CCCP | Sigma-Aldrich, C2759 |
| TMRE | Invitrogen, T669 |
| Hoechst 33342 | Thermo Scientific, 62249 |
| Bromophenol blue | Sigma-Aldrich, 114391 |
| Pierce BCA protein assay kit | Thermo Scientific, 23225 |
| Direct-zol RNA isolation kit | Zymo Research, R2050 |
| TURBO Dnase free kit | Invitrogen Life, AM1907 |
| LightCycler 480 SYBR Green I Master | Roche Life Science, 04707516001 |
| SuperSignal West Femto Max Sensitivity Substrate | Thermo Scientific, 34096 |
Yeast transformation was performed by the LiAc/TE method, and successfully transformed cells were selected on agar plates containing synthetic complete media with 2% glucose (SD) lacking the corresponding amino acid(s).
For most assays, unless specified, yeast cells were grown in synthetic media with 2% glucose overnight and backdiluted to a much lower OD (the exact number of cells dependent on the assays and mutants being used) in media indicated in each assay. For assays that used carbon sources other than glucose, the carbon source and percentage was specified in the figure or figure legend. Cells were harvested between 0.2–0.6 OD to ensure similar metabolic state. For phosphate depletion assay, saturated or active growing yeast cells (below 0.6 OD) were washed twice with a much larger volume of water. The cells were then grown in synthetic media without inorganic phosphate supplemented with KCl (Formedium, CYN6701) with amino acids, 2% glucose, and the indicated amount of potassium phosphate monobasic, pH 4.1.
Mammalian cells and growth conditions
HEK293T was obtained from ATCC. A375 was obtained from the Martin McMahon’s lab. HEK293T verification was provided by ATCC. A375 was authenticated by STR profiling. Mycoplasma testing was performed once every month, and all cell lines remained mycoplasma-free. HEK293T and A375 cell lines were cultured and maintained in Dulbecco’s modified Eagle medium (DMEM) supplemented with 10% FBS in an incubator at 37°C with 5% CO2.
To deplete phosphate, cells were washed at minimum three times with filter-sterilized normal saline (0.9% NaCl) and trypsinized with 0.25% trypsin in citrate saline (STEMCELL Technologies, 07400). Cells were resuspended with DMEM with no phosphate (Thermo Fisher Scientific, 11971025), supplemented with 10% One Shot Dialyzed FBS (Thermo Fisher Scientific, A3382001), and 2 mM sodium pyruvate, hereby known as -Pi media, divided equally by cell number into 15 ml falcon tubes, and centrifuged to pellet cells.
Cells were resuspended in either the aforementioned -Pi media, or in +Pi media, which is media supplemented with 1 mM sodium phosphate monobasic, hereby known as +Pi media, depending on condition cells were to be plated in. Cells were grown in either -Pi or +Pi media in an incubator at 37°C and 5% CO2 for 3 d prior to collection.
Fly stocks and growth condition
Yeast genetic screen library construction and dual luciferase assay
The deletion collection (haploid) was mated with the query strain (
Haploid cells generated from SGA were grown in 384-well plates overnight in SD complete (2% glucose). After back-diluting to around OD 0.1, the cells were grown for 6 hr in SR complete media (2% raffinose). The dual luciferase assay was conducted using the Dual-Glo Luciferase Assay System (Promega) following the product manual. Both firefly and Renilla luciferase were measured using a GloMax plate reader (Promega) with an injector in 96-well plate format.
Mitochondrial membrane potential measurement in yeast
0.2 OD of yeast cells were pelleted down and incubated in the same growth media containing 100 nM of MitoTracker Red CMXRos (Life Technologies) for 30 min at room temperature. Cells were spun down again and resuspended in the same media, which was either imaged by fluorescence microscopy or measured by fluorescence-assisted cell sorting. All experiments were performed with three biological replicates.
MitoTracker Red staining in mammalian cells
Cells were washed 3× and trypsinized as previously stated, and then resuspended in -Pi or +Pi media with a 20 nM final concentration of MitoTracker Red, then incubated at 37°C for 15 min. Cells are centrifuged, washed once with normal saline, centrifuged, and resuspended in -Pi or +Pi media and proceed with flow cytometry analysis. All experiments were performed with three biological replicates.
MitoTracker Red staining and fluorescence microscopy in rat primary hepatocytes
Rat Primary hepatocytes (Wister, Lonza, RICP01) were cultured as instructed. In brief, 0.9 million primary hepatocytes were plated in collagen-coated florodish in HCM SingleQuots Kit (Lonza, CC-4182, containing ascorbic acid, bovine serum albumin-fatty acid free [BSA-FAF], hydrocorticosone, human epidermal growth factor [hEGF], transferrin, insulin and gentamicin/amphotericin-B [GA]), overnight at 37°C. Cells were treated with 3 mM or 1 mM PFA in DMEM with 10% FBS and 1% P/S for 24 hr. Cells were then washed two times with saline-0.9% NaCl before staining with 20 nM MitoTracker Red CMXRos at 37°C for 15 min. After two saline washes, live imaging of MitoTracker Red fluorescence was done in DMEM with 10% FBS on Zeiss 900 Airyscan. The intensity of MitoTracker Red for 80 cells per treatment was quantified using Fiji. Cellular boundaries were defined using the Free-hand tool, and background intensity was subtracted. The graphs were plotted using Prism v9.
TMRE staining and fluorescence microscopy in adult
Three--day-old flies (15 females and 10 males) were transferred in vials with semi-defined media with or without 1 mM sodium phosphonoformate tribasic hexahydrate (PFA) (Sigma, P6801). After 2 wk, fly guts (midgut, R4-R5 section) from both control and PFA-treated groups were dissected in Shields and Sang M3 Insect Media (Sigma, S8398) with or without 1 mM PFA added. Dissected guts were stained with 1 μM TMRE (Sigma, 87917) in the same media condition for 20 min at room temperature. After two washes with the corresponding media supplemented with 1 μM Hoechst 33342 (Thermo Scientific, 62249) and 0.01 μM TMRE, live imaging of the gut was performed on Zeiss 900 Airyscan. Intensity of TMRE was quantified in Fiji, and background was subtracted. Figures were prepared in Prism v9.
Fluorescence microscopy
Yeast containing Tom70-GFP tagged chromosomally at its endogenous locus were grown and stained with MitoTracker Red CMXRos as described for flow cytometry. In short, 5 × 106 yeast were harvested by centrifugation and resuspended in 1 ml media containing 0.2 μM MitoTracker Red CMXRos. Cells were incubated in the dark at room temperature for 30 min, washed once in 1 ml media, and resuspended in 20 μl of media.
For quantitative microscopy, images were collected on an Axio Observer (ZEISS) with a ×63 oil-immersion objective (ZEISS, Plan Apochromat, NA 1.4) and an Axiocam 503 mono camera (ZEISS). Three optical z-sections across 1 μm sections were collected per image. Each image contained on average 19 yeast cells (range: 5–49 yeast cells). Quantifications were derived from average values per picture. Five pictures were averaged for each condition in an experimental replicate. Final values are averages of three experimental replicates. Images were collected in ZEN (ZEISS) and processed in Fiji (Schindelin et al., 2012). All quantifications were done on maximum-intensity projections. All images within each experiment were processed identically.
For mitochondrial membrane potential quantifications, a mask was created from thresholded Tom70-GFP images and used to measure the average MitoTracker Red CMXRos fluorescence intensity of each mitochondria. Each condition within an experimental replicate was normalized to untreated wild-type yeast to control for variations in MitoTracker Red CMXRos staining.
For mitochondrial mass quantifications, mitochondrial area per picture was measured from thresholded Tom70-GFP images. Cell area per picture was measured from Tom70-GFP images at a threshold such that the entirety of each cell was outlined. Plots depict the total mitochondrial area divided by the corresponding cell area.
For mitochondrial morphology quantifications, the contrast of Tom70-GFP images were adjusted for optimal viewing and morphology scored by an unblinded researcher.
For image panels, super-resolution Airyscan images were collected using an LSM800 (ZEISS) equipped with an Airyscan detector and a ×63 oil-immersion objective (Carl Zeiss, Plan Apochromat, NA 1.4). Optical z-sections were acquired across the entire yeast cell at a step size optimal for Airyscan super-resolution, 0.15 μm. Images were acquired on ZEN software and processed using the automated Airyscan processing algorithm in ZEN (ZEISS). Maximum-intensity projections and contrast enhancement were done in Fiji. Contrast changes were kept identical within an experiment.
HEK 293T imaging was performed with a Plan-Apochromat ×63/1.40 Oil DIC f/ELYR objective. Images were Airyscan processed using the ZEISS Zen Blue software.
Negative geotaxis assay
Negative geotaxis assays were measured using the RING method (Gargano et al., 2005). Six females and four males of flies per experimental group were transferred to empty vials with markings every 0.5 cm along the side of the vial. Vials were tapped with force five times to ensure that all flies were at the bottom of the vial. After a recovery period of 5 s, the average height per vial that flies were able to travel up the vial was scored across all trials was scored using photos. The assay was repeated for each experimental group with five trials.
Smurf fly assay
Smurf fly assays to report gut barrier integrity were performed as reported in Rera et al., 2012. Also, 15 female and 10 male 3-day-old flies per experimental group were maintained on control food or food supplemented with 1 mM PFA for 1 wk or 4 wk. These flies with reared on blue food with 1% (wt/vol) bromophenol blue (Sigma) for 1 d. The percent of Smurf flies, or flies with visible dye leaking from the abdomen, was counted for each group. The assay was repeated for each experimental group with five trials.
Fly survival assay
In total, 15 female and 10 male 3-day-old flies per experimental group were maintained on control food or food supplemented with 1 mM PFA. For 90 d, the number of dead flies was tallied every 3 d. The assay was repeated for each experimental group with five trials.
Fluorescence-assisted cell sorting
Cells were stained with MitoTracker Red CMXRos. A total of 10,000 events were measured on a BD FACSCanto with BD FACSDiva 8.0.1.1 (BD Biosciences). The median fluorescence values were plotted with Prism 9.
Mitochondrial morphology quantification using MiNA
Using the MiNA plugin (Valente et al., 2017) in Fiji, MitoTracker Red signaling of each cell was outlined as ROI and the skeletonized mitochondria were generated. Then, the mean summed branch lengths and the mean network branch were automatically measured and calculated. Around 30–60 cells were analyzed for each condition. The final bar graphs were plotted with Prism 9.
Mitochondrial protein import assay
Ten OD of total culture (~108 cells) were harvested at an OD600 between 0.3 and 0.5. Cell pellets were washed with water and lysed in 500 μl of 2 M lithium acetate for 10 min on ice. Lysed cells were resuspended in 500 μl of ice-cold 0.4 M NaOH and left on ice for 10 min. The pellets were resuspended with 250 μl of 2× Laemmli buffer with 5% BME. The lysate was boiled for 5 min, and the supernatant was loaded on a 12% SDS-PAGE gel and assessed by immunoblot.
Western blotting
Whole-cell or mitochondria extract were separated on an SDS-PAGE or BN-PAGE gel and transferred to nitrocellulose membranes (SDS-PAGE) or activated PVDF membranes (BN-PAGE) with a Power Station (Bio-Rad). Membranes were blocked in blocking buffer (Tris buffered saline [50 mM Tris–HCl pH 7.4, 150 mM NaCl, 5% nonfat dry milk]) and probed with the primary antibodies listed in Table 3 and the secondary antibodies. Antibodies were either visualized with LI-COR Odyssey or SuperSignal Enhanced Chemiluminescence Solution (Thermo Scientific, 34096) and a Chemidoc MP System (Bio-Rad).
Crude mitochondrial isolation
Crude mitochondrial isolation was performed as described previously (Van Vranken et al., 2018). Cell pellets were resuspended in TD buffer (100 mM Tris–SO4, pH 9.4 and 100 mM DTT) and incubated for 15 min at 30°C. Cells were then washed once in SP buffer (1.2 M sorbitol and 20 mM potassium phosphate, pH 7.4) and incubated in SP buffer with 0.3 mg/ml lyticase (Sigma, L4025) for 1 hr at 30°C to digest the cell wall. Spheroplasts were washed once and homogenized in ice-cold SEH buffer (0.6 M sorbitol, 20 mM HEPES-KOH, pH 7.4, 1 mM PMSF, yeast protease inhibitor cocktail [Sigma, P8215]) by applying 20 strokes in a dounce homogenizer. Crude mitochondria were isolated by differential centrifugation at 3000 ×
Blue native polyacrylamide gel electrophoresis (BN-PAGE)
BN-PAGE was performed as described previously (Van Vranken et al., 2018). 100 μg of mitochondria were resuspended in 1× lysis buffer (Invitrogen, BN20032) supplemented with yeast protease inhibitor cocktail (Sigma, P8215) and solubilized with 1% digitonin for 20 min on ice. Solubilized mitochondria were cleared by centrifugation at 20,000 ×
Mitochondrial isolation and immunoprecipitation for the ACP acylation study
Mitochondrial isolation and immunoprecipitation were performed as described previously (Van Vranken et al., 2018). Briefly, cell pellets were washed and lysed as described in the ‘Crude mitochondrial isolation’ section. Spheroplasts were washed once and homogenized in ice-cold SEH buffer (0.6 M sorbitol, 20 mM HEPES-KOH, pH 7.4, 1 mM PMSF, yPIC) with 10 mM N-ethylmaleimide (NEM) (Sigma, E3876) by applying 20 strokes in a dounce homogenizer. Crude mitochondria were isolated by differential centrifugation. Protein concentrations were determined using a Pierce BCA Protein Assay Kit (Thermo Scientific). 1 mg of crude mitochondria were resuspended in 200 μl of XWA buffer (20 mM HEPES, 10 mM KCl, 1.5 mM MgCl2, 1 mM EDTA, 1 mM EGTA, pH 7.4) with 10 mM NEM and 0.7% digitonin added and incubated on ice for 30 min. After centrifugation at 20,000 ×
RNA isolation and qPCR
RNA was isolated as described previously (Zurita Rendón et al., 2018). Briefly, cell pellets were resuspended in Trizol reagent (Ambion, 15596026) and bead bashed to lyse the cell (20 s bash with 30 s break on ice, six cycles). Equal volume of ethanol was added to the sample and RNA is isolated using the Direct-zol kit (Zymo Research, R2050). The RNA eluted from the column was treated with TURBO DNase kit (Invitrogen, AM1907) to remove remaining DNA contamination. After normalization of RNA content, cDNA was generated by using a High-capacity cDNA Reverse Transcription kit (Applied Biosystems, 4368813). Quantitative PCR was performed using the LightCycler 480 SYBR Green I Master (Roche, 04707516001). The raw data was analyzed by absolute quantification/second derivative of three independent biological replicates with each being the average of three technical replicates.
RNA sequencing
For dataset GSE151606, yeast cultures were initially grown in synthetic media supplemented with 2% glucose, then removed from original media and transferred to synthetic media with 2% raffinose. Cultures were flash frozen and later total RNA was isolated using the Direct-zol kit (Zymo Research, R2050) with on-column DNase digestion and water elution. Sequencing libraries were prepared by purifying intact poly(A) RNA from total RNA samples (100–500 ng) with oligo(dT) magnetic beads and stranded mRNA sequencing libraries were prepared as described using the Illumina TruSeq Stranded mRNA Library Preparation Kit (RS-122-2101, RS-122-2102). Sequencing libraries (25 pM) were chemically denatured and applied to an Illumina HiSeq v4 single read flow cell using an Illumina cBot. Hybridized molecules were clonally amplified and annealed to sequencing primers with reagents from an Illumina HiSeq SR Cluster Kit v4-cBot (GD-401-4001). Fifty cycle single-read sequence run was performed using HiSeq SBS Kit v4 sequencing reagents (FC-401-4002). Read pre-processing was performed using Fastp, v0.20.0 (Chen et al., 2018). Read alignment was performed using STAR, v2.7.3a (Dobin et al., 2013). Read quantification was performed using htseq, v0.11.3 (Anders et al., 2015). Read QC was performed using fastqc, v0.11.9 (Andrews, 2010). Total QC was performed using multiqc, v1.8 (Andrews, 2010). Library complexity QC was performed using dupradar, v1.10.0 (Sayols et al., 2016). Genome_build Ensembl R64-1-1 (GCA_000146045.2) version 100 was used during alignment and quantification. Genes with fewer than 10 reads in any sample were excluded from analysis. The scripts for data processing can be found at https://github.com/j-berg/ouyang_eLife2024/tree/main/rnaseq/GSE151606_mct1_timecourse (Berg, 2024).
For dataset GSE209726, yeast cultures were grown in SD-complete overnight and harvested at OD600 between 0.2–0.4. Intact poly(A) RNA was purified from total RNA samples (100–500 ng) with oligo(dT) magnetic beads. Stranded mRNA sequencing libraries were prepared as described using the Illumina TruSeq Stranded mRNA Library Prep kit (20020595) and TruSeq RNA UD Indexes (20022371). Purified libraries were qualified on an Agilent Technologies 2200 TapeStation using a D1000 ScreenTape assay (Cat# 5067-5582 and 5067-5583). The molarity of adapter-modified molecules was defined by quantitative PCR using the Kapa Biosystems Kapa Library Quant Kit (Cat# KK4824). Individual libraries were normalized to 1.30 nM in preparation for Illumina sequence analysis. Sequencing libraries were chemically denatured and applied to an Illumina NovaSeq flow cell using the NovaSeq XP workflow (20043131). Following transfer of the flowcell to an Illumina NovaSeq 6000 instrument, a 150 × 150 cycle paired end sequence run was performed using a NovaSeq 6000 S4 reagent Kit v1.5 (20028312). Read preprocessing was performed using Fastp, v0.20.1 (Chen et al., 2018). Read alignment was performed using STAR, v2.7.7a (Dobin et al., 2013). Read postprocessing was performed using samtools v1.11 (Li et al., 2009). Read quantification was performed using htseq, v0.13.5 (Anders et al., 2015). Genome_build Ensembl R64-1-1 (GCA_000146045.2) version 100 was used during alignment and quantification. The scripts for data processing can be found at https://github.com/j-berg/ouyang_eLife2024/tree/main/rnaseq/GSE209726_mct1_sit4_deletions (Berg, 2024).
For dataset GSE212790, yeast were grown in the indicated media overnight and harvested between OD600 = 0.2–0.4, with a total OD of 5 per sample. After QC procedures, mRNA from eukaryotic organisms is enriched from total RNA using oligo(dT) beads. The mRNA is then fragmented randomly in fragmentation buffer, followed by cDNA synthesis using random hexamers and reverse transcriptase. After first-strand synthesis, a custom second-strand synthesis buffer (Illumina) is added, with dNTPs, RNase H, and
Data analysis and statistics for RNA sequencing
Analysis code notebooks can be accessed at https://github.com/j-berg/ouyang_eLife2024. Differential expression analysis was performed using DESeq2 (Love et al., 2014) with the FDR threshold (α) set at 0.1. Data visualization was performed in Python using Pandas (McKinney, 2010), numpy (Oliphant, 2006; van der Walt et al., 2011), scikit-learn (Buitinck et al., 2013), matplotlib (Hunter, 2007), and seaborn (Waskom et al., 2022).
Sample preparation for mass spectrometry
Yeast proteomes were extracted using a buffer containing 200 mM EPPS, 8 M urea, 0.1% SDS, and 1× protease inhibitor (Pierce protease inhibitor mini tablets). 100 μg of each proteome was prepared as follows. 10 mM tris(2-carboxyethyl)phosphine hydrochloride was incubated at room temperature for 10 min. Iodoacetimide was added to a final concentration of 10 mM to each sample and incubated for 25 min in the dark. Finally, DTT was added to each sample to a final concentration of 10 mM. A buffer exchange was carried out using a modified SP3 protocol (Hughes et al., 2014; Hughes et al., 2019). Briefly, ~500 μg of each type of SpeedBead Magnetic Carboxylate modified particles (Cytiva; 45152105050250, 65152105050250) were mixed at a 1:1 ratio and added to each sample. Then, 100% ethanol was added to each sample to achieve a final ethanol concentration of at least 50%. Samples were incubated with gentle shaking for 15 min. Samples were washed three times with 80% ethanol. Protein was eluted from SP3 beads using 200 mM EPPS pH 8.5 containing trypsin (Thermo Fisher Scientific) and Lys-C (Wako). Samples were digested overnight at 37°C with vigorous shaking. Acetonitrile was added to each sample to achieve a final concentration of 30%. Each sample was labeled in the presence of SP3 beads with ~250 μg of TMTpro-16plex reagents (Thermo Fisher Scientific) (Li et al., 2020; Thompson et al., 2019) for 1 hr. Following confirmation of satisfactory labeling (>97%), excess TMTpro reagents were quenched by addition of hydroxylamine to a final concentration of 0.3%. The full volume from each sample was pooled and acetonitrile was removed by vacuum centrifugation for 1 hr. The pooled sample was acidified using formic acid and peptides were de-salted using a Sep-Pak Vac 200 mg tC18 cartridge (Waters). Peptides were eluted in 70% acetonitrile, 1% formic acid, and dried by vacuum centrifugation. Phosphopeptides were enriched using a Hugh Select Phosphopeptide Enrichment Kit (Thermo Fisher Scientific). Flow through from the phosphopeptide enrichment column was collected for whole proteome analysis. The peptides were resuspended in 10 mM ammonium bicarbonate pH 8, 5% acetonitrile, and fractionated by basic pH reverse-phase HPLC. In total, 24 fractions were collected. The fractions were dried in a vacuum centrifuge, resuspended in 5% acetonitrile, 1% formic acid, and desalted by stage-tip. Final peptides were eluted in 70% acetonitrile, 1% formic acid, dried, and finally resuspended in 5% acetonitrile, 5% formic acid. In the end, eight fractions were analyzed by LC-MS/MS.
Mass spectrometry data acquisition
Data were collected on an Orbitrap Eclipse mass spectrometer (Thermo Fisher Scientific) coupled to a Proxeon EASY-nLC 1000 LC pump (Thermo Fisher Scientific). Whole proteome peptides were separated using a 90 min gradient at 500 nl/min on a 30 cm column (i.d. 100 μm, Accucore, 2.6 μm, 150 Å) packed in house. High-field asymmetric-waveform ion mobility spectroscopy (FAIMS) was enabled during data acquisition with compensation voltages (CVs) set as −40 V, −60 V, and −80 V (Schweppe et al., 2019). MS1 data were collected using the Orbitrap (60,000 resolution; maximum injection time 50 ms; AGC 4 × 105). Determined charge states between 2 and 6 were required for sequencing, and a 60 s dynamic exclusion window was used. Data-dependent mode was set as cycle time (1 s). MS2 scans were performed in the Orbitrap with HCD fragmentation (isolation window 0.5 Da; 50,000 resolution; NCE 36%; maximum injection time 86 ms; AGC 1 × 105). Phosphopeptides were separated using a 120 min gradient at 500 nl/min on a 30 cm column (i.d. 100 μm, Accucore, 2.6 μm, 150 Å) packed in house. The phosphopeptide enrichment was injected twice using two different FAIMS methods. For the first injection, the FAIMS CVs were set to –45 V and –65 V. For the second injection, the FAIMS CVs were set to –40 V, –60 V, and –80 V (Schweppe et al., 2019). For both methods, MS1 data were collected using the Orbitrap (120,000 resolution; maximum ion injection time 50 ms, AGC 4 × 105). Determined charge states between 2 and 6 were required for sequencing, and a 60 s dynamic exclusion window was used. Data-dependent mode was set as cycle time (1 s). MS2 scans were performed in the Orbitrap with HCD fragmentation (isolation window 0.5 Da; 50,000 resolution; NCE 36%; maximum injection time 250 ms; AGC 1 × 105).
Phosphoproteomics data analysis
Raw files were first converted to mzML format, and monoisotopic peaks were re-assigned using Monocle (Rad et al., 2021). Searches were performed using the Comet search algorithm against the most recent yeast gene database downloaded from UniProt in June 2014. We used a 50 ppm precursor ion tolerance and 0.9 Da product ion tolerance for MS2 scans collected in the ion trap and 0.02 Da product ion tolerance for MS2 scans collected in the Orbitrap. TMTpro on lysine residues and peptide N-termini (+304.2071 Da) and carbamidomethylation of cysteine residues (+57.0215 Da) were set as static modifications, while oxidation of methionine residues (+15.9949 Da) was set as a variable modification. For phosphorylated peptide analysis, +79.9663 Da was set as a variable modification on serine, threonine, and tyrosine residues.
Peptide-spectrum matches (PSMs) were adjusted to a 1% false discovery rate (FDR) (Elias and Gygi, 2007). PSM filtering was performed using linear discriminant analysis (LDA) as described previously (Huttlin et al., 2010), while considering the following parameters: comet log expect, different sequence delta comet log expect (percent difference between the first hit and the next hit with a different peptide sequence), missed cleavages, peptide length, charge state, precursor mass accuracy, and fraction of ions matched. Each run was filtered separately. Protein-level FDR was subsequently estimated at a data set level. For each protein across all samples, the posterior probabilities reported by the LDA model for each peptide were multiplied to give a protein-level probability estimate. Using the Picked FDR method (Savitski et al., 2015), proteins were filtered to the target 1% FDR level. Phosphorylation site localization was determined using the AScore algorithm (Beausoleil et al., 2006).
For reporter ion quantification, a 0.003 Da window around the theoretical
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Abstract
Mitochondrial membrane potential directly powers many critical functions of mitochondria, including ATP production, mitochondrial protein import, and metabolite transport. Its loss is a cardinal feature of aging and mitochondrial diseases, and cells closely monitor membrane potential as an indicator of mitochondrial health. Given its central importance, it is logical that cells would modulate mitochondrial membrane potential in response to demand and environmental cues, but there has been little exploration of this question. We report that loss of the Sit4 protein phosphatase in yeast increases mitochondrial membrane potential, both by inducing the electron transport chain and the phosphate starvation response. Indeed, a similarly elevated mitochondrial membrane potential is also elicited simply by phosphate starvation or by abrogation of the Pho85-dependent phosphate sensing pathway. This enhanced membrane potential is primarily driven by an unexpected activity of the ADP/ATP carrier. We also demonstrate that this connection between phosphate limitation and enhancement of mitochondrial membrane potential is observed in primary and immortalized mammalian cells as well as in
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