Intrinsic OXPHOS limitations underlie cellular bioenergetics in leukemia.

doi:10.21203/rs.3.rs-64203/v2

Download PDF

Research Article

Intrinsic OXPHOS limitations underlie cellular bioenergetics in leukemia.

https://doi.org/10.21203/rs.3.rs-64203/v2

This work is licensed under a CC BY 4.0 License

Version 2

posted

You are reading this latest preprint version

Typified by oxidative phosphorylation (OXPHOS), mitochondria catalyze a wide variety of cellular processes seemingly critical for malignant growth. As such, there is considerable interest in targeting mitochondrial metabolism in cancer. However, notwithstanding the few drugs targeting mutant dehydrogenase activity, nearly all hopeful ‘mito-therapeutics’ cannot discriminate cancerous from non-cancerous OXPHOS and thus suffer from a limited therapeutic index. The present project was based on the premise that the development of efficacious mitochondrial-targeted anti-cancer compounds requires answering two fundamental questions: 1) is mitochondrial bioenergetics in fact different between cancer and non-cancer cells? and 2) If so, what are the underlying mechanisms? Such information is particularly critical for the subset of human cancers, including acute myeloid leukemia (AML), in which alterations in mitochondrial metabolism are implicated in various aspects of cancer biology (e.g., clonal expansion and chemoresistance). Herein, we leveraged an in-house diagnostic biochemical workflow to comprehensively evaluate mitochondrial bioenergetic efficiency and capacity in various hematological cell types, with a specific focus on OXPHOS dynamics in AML. Consistent with prior reports, clonal cell expansion, characteristic of leukemia, was universally associated with a hyper-metabolic phenotype which included increases in basal and maximal glycolytic and respiratory flux. However, despite having nearly 2-fold more mitochondria per cell, clonally expanding hematopoietic stem cells, leukemic blasts, as well as chemoresistant AML were all consistently hallmarked by intrinsic limitations in oxidative ATP synthesis (i.e., OXPHOS). Remarkably, by performing experiments across a physiological span of ATP free energy (i.e, ΔG_ATP), we provide direct evidence that, rather than contributing to cellular ΔG_ATP, leukemic mitochondria are particularly poised to consume ATP. Relevant to AML biology, acute restoration of OXPHOS kinetics proved highly cytotoxic to leukemic blasts, suggesting that active OXPHOS repression supports aggressive disease dissemination in AML. Taken together, these findings argue against ATP being the primary output of mitochondria in leukemia and provide proof-of-principle that restoring, rather than disrupting, OXPHOS and/or cellular ΔG_ATP in cancer may represent an untapped therapeutic avenue for combatting hematological malignancy and chemoresistance.

Cancer Biology

General Biochemistry

Molecular Biology

leukemia

oxidative metabolism

oxidative phosphorylation

In comparison to normal hematopoietic cells, various human leukemias present with increases in mitochondrial mass and higher basal respiration rates (Farge et al., 2017; Goto et al., 2014b, 2014a; Sriskanthadevan et al., 2015; Suganuma et al., 2010), the latter of which appears to sensitize them to global disruptions in mitochondrial flux (Kuntz et al., 2017; Lagadinou et al., 2013; Lee et al., 2015; Mirali et al., 2020; Škrtić et al., 2011; Xiang et al., 2015). Although these studies have ignited interest in mitochondrial-targeted chemotherapeutics (Guièze et al., 2019; Panina et al., 2020), experimental rationale for targeting OXPHOS in leukemia is largely based on the assumption that heightened respiration is representative of the cancerous mitochondrial network’s attempt to accommodate an increased ATP demand (i.e., increased ‘OXPHOS reliance’). However, identical increases in mitochondrial respiration can derive from any number of physiological stimuli, ranging from increased demand for ATP resynthesis to decreased OXPHOS efficiency. Distinguishing between these potential outcomes is critical, as such insight likely demarcates targeted drug efficacy from undesirable systemic toxicity. For example, it is currently unclear how targeting increased ‘OXPHOS reliance’ in leukemia can specifically disrupt leukemic oxidative metabolism without impacting OXPHOS in other highly metabolic organs (e.g., brain, heart, muscle).

Given the ubiquitous necessity of OXPHOS for healthy cellular metabolism, a major barrier to mitochondrial-targeted drugs in leukemia relates to the need for cancer-cell selectivity (Cohen, 2010; Dykens and Will, 2007). The current project was based on the premise that establishing cause and effect between mitochondrial bioenergetics and cancer is one of the keys to developing targeted and more effective therapies. As a first step, this will undoubtedly require advanced technical approaches capable of quantifying the interplay among the major mitochondrial thermodynamic free energy driving forces to distinguish between changes in bioenergetic demand versus efficiency. To this end, our group recently developed a diagnostic biochemical workflow that quantifies the changes in free energy driving forces over the entire range of respiratory demand, thus providing a comprehensive profile of mitochondrial bioenergetic efficiency and capacity, relative to the underlying proteome (Fisher-Wellman et al., 2019, 2018; McLaughlin et al., 2018).

Herein, we leveraged our mitochondrial diagnostics workflow across several hematological cell types, including AML cell lines, primary human leukemias, and AML cells made refractory to the chemotherapeutic venetoclax. Clonal cell expansion in leukemia, including chemoresistant AML, was universally associated with two primary phenotypes; 1) higher basal respiration driven by increased cellular mitochondrial content, and 2) intrinsic OXPHOS repression. Parallel assessment of the underlying mitochondrial proteome linked this unique ability to bolster cellular mitochondrial content while simultaneously constraining oxidative ATP synthesis to shifts in adenine nucleotide translocase (ANT) isoform expression. Specifically, decreased ANT1 and increased ANT2/ANT3 appears to prime leukemic mitochondria for ATP uptake, rather than export, that, in turn directly inhibits the ability of mitochondrial OXPHOS to contribute to the cellular ATP free energy (ΔG_ATP). These findings are consistent with recent evidence demonstrating that mitochondrial OXPHOS is dispensable for tumor growth (Martínez-Reyes et al., 2020), and raise the intriguing possibility that the requirement for mitochondria in leukemia may have little to do with oxidative ATP production but instead reflect a requirement for unimpeded mitochondrial flux to support other aspects of anabolic growth (e.g., NAD⁺ regeneration (Luengo et al., 2020), nucleotide synthesis (Martínez-Reyes et al., 2020)). Critically however, accommodating such a flux demand, at least in leukemia, appears to require intrinsic mitochondrial remodeling that allows for forward electron transport/oxygen consumption to occur alongside ATP consumption. Given that acute restoration of OXPHOS kinetics in AML proved highly cytotoxic to leukemic blasts, the present findings provide proof-of-principle that interventions designed to restore, rather than disrupt, OXPHOS may impart therapeutic efficacy across various hematological malignancies.

Mitochondrial bioenergetic profiling of acute leukemia reveals respiratory flux limitations. To begin to characterize the mitochondrial network in leukemia, we selected three commercially available acute leukemia cell lines – HL-60, KG-1, MV-4-11 – and comprehensively evaluated their bioenergetic profiles. These cells arise from unique precursors along the hematopoietic lineage, express a diverse array of cell surface markers, and have distinct underlying genetics (Inoue et al., 2014; Mrózek et al., 2003; Rücker et al., 2006). Results were compared to peripheral blood mononuclear cells (PBMC) isolated from healthy volunteers. The decision to use PBMC as a control was based on the assumption that comprehensive bioenergetic phenotyping of non-proliferative PBMC compared to various AML cell lines would provide sufficient experimental design contrast to reveal fundamental mitochondrial bioenergetic phenotypes potentially required for clonal cell expansion.

Using intact PBMC and leukemia cell lines, respiratory flux (JO₂) was assessed under basal conditions, as well as in response to ATP synthase inhibition (oligomycin), and FCCP titration (i.e., mitochondrial uncoupler). All experiments were performed in bicarbonate free IMDM growth media, supplemented with 10% FBS. Following FCCP titration, respiration was inhibited with a combination of rotenone (inhibits complex I) and antimycin A (inhibits complex III). Consistent with prior work in human leukemia (Jitschin et al., 2014; Sriskanthadevan et al., 2015), basal respiration normalized to cell count was elevated above PBMC across all leukemia lines and maximal respiratory flux was higher in KG-1 and MV-4-11 (Fig. 1A). When normalized to basal respiration, oligomycin similarly inhibited respiration across groups and the fold change induced by FCCP was consistently blunted in leukemia (Fig. 1B).

Given the large differences in cell size between PBMC and leukemia (Supp. Fig. 1A), we reasoned that normalization to total protein would likely provide the most accurate index of absolute respiratory kinetics across groups. Interestingly, upon normalization to total protein, although basal respiration remained higher in KG-1 and MV-4-11, differences in maximal respiratory flux were eliminated, particularly at higher FCCP concentrations (Fig. 1C). In fact, maximal FCCP-supported JO₂was nearly two-fold lower in HL-60 compared to PBMC when normalized to total protein (Fig. 1C). Relative to PBMC, maximal respiration induced by FCCP occurred at much lower concentrations in leukemia (i.e., lower Km; Fig. 1D), with increasing FCCP concentrations leading to an overt bioenergetic collapse (i.e., diminishing respiration rates; Fig. 1C; compare JO₂ at FC [2.0µM] vs FC [5.0µM]). Similar findings were observed using the mitochondrial uncoupler BAM15 (Supp. Fig. 1B-C). Measurements of extracellular acidification (ECAR), an indirect readout of glycolytic flux, revealed higher extracellular acidification and a rightward shift in ECAR relative to oxygen consumption rate (OCR) in AML cell lines, consistent with prior reports detailing a hyper-metabolic phenotype in leukemia (Supp. Fig. 1E-F) (Suganuma et al., 2010).

To determine if flux differences in leukemia could be explained by differences in mitochondrial content, nuclear and mitochondrial volumes were assessed independently by tetramethylrhodamine methyl ester (TMRM) or MitoTracker fluorescence and confocal microscopy (Fig. 1E-I, Supp. Fig 1D). Absolute nuclear and mitochondrial volumes were higher in all leukemia lines (Fig. 1E-H), consistent with leukemia’s larger cell size (Supp. Fig. 1A). However, when normalized to nuclear volume, mitochondrial content was elevated above PBMC only in HL-60 and MV-4-11 (Fig. 1I). Interestingly, across all cell types, considerable discrepancies were apparent when protein-normalized maximal respiratory flux (Fig. 1C) was compared to mitochondrial content (Fig. 1I). This was particularly evident in HL-60 cells where mean maximal respiration, relative to the size of the underlying mitochondrial network, was ~5-fold lower compared to PBMC (Fig. 1J). Together, these data suggested that at least a portion of the expansive mitochondrial network in AML may be biochemically constrained and thus unable to contribute to oxidative metabolism under basal conditions.

Intrinsic limitations to OXPHOS characterize the mitochondrial network in leukemia cell lines. To directly test OXPHOS kinetics in leukemia, two complementary assays were designed. Both assays used digitonin-permeabilized cells energized with identical carbon substrates, and respiratory flux was stimulated with either FCCP or ATP free energy. In the first assay, the maximal capacity of the electron transport system (ETS) was assessed by energizing permeabilized cells with saturating carbon substrates (P/M/G/S/O) and titrating in FCCP (Fig. 2A-B). The use of multiple substrates was intended to saturate carbon substrate availability such that maximal ETS flux could be quantified. Using this approach, absolute respiration in substrate-replete permeabilized cells was comparable to that observed using intact cells treated with FCCP (Fig. 2C), confirming maximal ETS flux in the permeabilized system. Note, maximum FCCP-supported flux under these conditions is indicated throughout as JH⁺_Total (Fig. 2A). Relative to PBMC, JH⁺_Total was lower in HL-60, unchanged in KG-1, and higher in MV-4-11 (Fig. 2B).

In mammalian cells, the vast majority of the adenylate pool is represented by ATP (i.e., ΔG_ATP), with typical values for ATP free energy ranging from -56 to -64 kJ/mol (Luptak et al., 2018; Roth and Weiner, 1991; Veech et al., 2002). Thus, to evaluate OXPHOS kinetic efficiency in leukemia across a physiological range of ATP resynthesis demands, we utilized the creatine kinase (CK) energetic clamp (Fisher-Wellman et al., 2018; Glancy et al., 2013; Messer et al., 2004). This technique leverages the enzymatic activity of CK, which couples the interconversion of ATP and ADP to that of phosphocreatine (PCR) and free creatine (CR) such that extramitochondrial ATP free energy (i.e., ΔG_ATP) can be empirically titrated using PCR. Using this approach, permeabilized cells were energized with the same carbon substrate mix used for the ETS capacity assay and respiration was stimulated at minimal ATP free energy. Note, ΔG_ATP equal to -54.16 kJ/mol reflects an ATP/ADP ratio in vivo that would be expected to induce ‘maximal’ OXPHOS flux and is thus referred to throughout as ‘JH⁺_OXPHOS’ (Fig. 2D). Cytochrome C (Cyt C) was added to assess the integrity of the mitochondrial outer-membrane, and ΔG_ATPwas then titrated via sequential additions of PCR. With respect to the ETS capacity assay, respiration stimulated by ΔG_ATPpartially normalized JO₂between MV-4-11 and PBMC and revealed decreased respiratory kinetics in both HL-60 and KG-1 (Fig. 2E).

In both assays, the utilization of identical substrates (‘P/M/G/S/O’) allowed us to directly quantitate absolute OXPHOS kinetics (‘JH⁺_OXPHOS’), relative to the maximal capacity of the electron transport system, (‘JH⁺_Total’). Together, JH⁺_OXPHOSand JH⁺_Totalprovide a quantitative index of fractional OXPHOS capacity as the ratio of the two reflects the proportion of the entire respiratory system that can be used for OXPHOS (Fig. 2F). A ratio of ‘1’ reflects maximal OXPHOS reliance, whereas a ratio of ‘0’ indicates that the mitochondrial proton current cannot be utilized for ATP synthesis. Strikingly, calculated fractional OXPHOS in leukemic mitochondria was consistently decreased compared to PBMC, corresponding to a factor of ~0.5 (Fig. 2G), indicating that only half of the available ETS capacity in leukemia can be dedicated to OXPHOS under physiological ATP free energy constraints. Given that the OXPHOS network is responsible for driving ATP/ADP disequilibrium to establish cellular ΔG_ATP, low fractional OXPHOS was interpreted to reflect reduced bioenergetic efficiency in leukemia. Moreover, such findings indicate that traditional measurements of ‘OXPHOS’ capacity using intact cells (e.g., extracellular flux analysis) woefully underestimate true OXPHOS kinetics.

To differentiate between bioenergetic signatures inherent to proliferating cells and those which are unique to leukemia, experiments were repeated in mononuclear cells isolated from bone marrow aspirates collected from healthy volunteers. In these experiments, fractional OXPHOS in healthy bone marrow cells was comparable to PBMC and once again elevated above all leukemia cell lines (Fig. 2G; ‘BM_Healthy’, Supp. Fig. 2A-B). As an additional control, identical experiments were carried out in primary human muscle precursor cells (human myoblasts – ‘HMB’ Supp. Fig. 2C-D). These cells were cultured from muscle biopsies uniformly collected from the gastrocnemius muscle (10 cm distal to the tibial tuberosity) of healthy human subjects and were intended to serve as a non-cancerous, proliferative human progenitor control. Importantly, fractional OXPHOS was elevated above leukemia in human muscle progenitor cells (Fig. 2G: ‘HMB’), indicating that decreased bioenergetic efficiency is not an absolute requirement of cellular proliferation, but rather a unique bioenergetic feature of leukemic mitochondria.

Exposure to physiological ΔG_ATP reveals direct inhibition of ETS flux by ATP in leukemic mitochondria. To gain insight into the mechanism of OXPHOS limitations in leukemia, at the end of the ΔG_ATP titration, oligomycin was added to inhibit ATP synthesis and maximal uncoupled respiration was stimulated with FCCP titration. Maximal FCCP-supported flux under these conditions is denoted as ‘FCCP_ΔGATP’ (Fig. 2D). In the intact cell assay (Fig. 1C), increased glycolytic flux is presumed to maintain cellular ΔG_ATP during FCCP titration. Thus, the continued presence of extra-mitochondrial ΔG_ATPin our permeabilized cell system was intended to model the adenylate constraints present in intact cells. By comparing maximal OXPHOS flux (‘JH⁺_OXPHOS’) to maximum FCCP-stimulated respiration in the presence of ΔG_ATP(‘FCCP_ΔGATP’), it becomes possible to quantitate any flux limitations imposed by physiological ATP/ADP. Importantly, ATP synthase is not functional during the assay, thus any flux limitations imposed by ΔG_ATPwould be interpreted to reflect direct ETS regulation (e.g., allostery). In PBMC and human muscle progenitor cells, the addition of FCCP at the end of the ΔG_ATPtitration restored respiration to levels obtained under low (-54.16 kJ/mol) ATP free energy (Fig. 2E, Supp. Fig. 2D-E), indicating minimal ETS flux inhibition by ΔG_ATP. Surprisingly, relative to JH⁺_OXPHOS, FCCP-stimulated respiration was substantially blunted in the presence of high ATP free energy across all three leukemia cell lines (Fig. 2E), as well as healthy bone marrow cells (Supp. Fig. 2C), resulting in a near 2-fold difference in the FCCP_ΔGATP/JH⁺_OXPHOS ratio, termed ‘FCCP Effect’ throughout (Fig. 2H). Importantly, in the absence of ATP, the addition of CK and PCR up to 21mM did not impact FCCP-supported flux in permeabilized MV-4-11 cells (Supp. Fig. 2E). To determine the sensitivity of ETS inhibition by ΔG_ATP, FCCP-supported flux in MV-4-11 cells was assessed at defined ATP free energies. In these experiments, extramitochondrial ΔG_ATP was administered after CV inhibition with oligomycin, followed by FCCP titration. Results revealed a dose-dependent decrease in uncoupled respiration in response to increasing ΔG_ATP (Fig. 2I), confirming that ATP free energy is both necessary and sufficient to induce direct ETS flux inhibition in leukemia.

Inhibition of respiratory flux mediated by ΔG_ATPcould reflect a number of potential mechanisms ranging from cytoskeletal alterations, direct inhibition of the matrix dehydrogenase network (e.g., inhibitory phosphorylation of pyruvate dehydrogenase), and/or ETS inhibition (Fisher-Wellman et al., 2018). To differentiate between these potential outcomes, mitochondria were isolated from PBMC and each of the three leukemia cell lines and similarly assessed for OXPHOS kinetics. In mitochondria energized with saturating carbon, increasing ΔG_ATP led to a more pronounced decrease in respiration in mitochondria of all three leukemia cell lines (Fig. 3A). The ability of FCCP to restore maximal respiratory flux was also once again blunted in leukemic mitochondria (Fig. 3A-B), consistent with lower fractional OXPHOS (Fig 2G). Evidence of ATP-dependent inhibition of ETS flux using both isolated mitochondria and permeabilized cells was used as criteria to rule out any involvement of the cytoskeleton. To differentiate between respiratory flux inhibition localized to the matrix dehydrogenases or the ETS, NADH/NAD⁺ redox poise was measured in substrate-replete isolated mitochondria exposed to an identical ΔG_ATP span. Results are depicted as a percentage of complete reduction, where 0% reduction reflects isolated mitochondria at 37°C without added substrates and 100% reduction is recorded at the end of the assay with the addition of the CIV inhibitor cyanide. Except for a slight hyper-reduction in HL-60 mitochondria, NADH/NAD⁺ redox was similar across groups (Fig. 3C), indicating that ATP-mediated respiratory flux inhibition in leukemia is not due to a generalized impairment in carbon substrate uptake and/or dehydrogenase flux. Having eliminated the cytoskeleton and the dehydrogenase network as potential sites of inhibition, we next turned our attention to the ETS. To determine if flux inhibition induced by ΔG_ATP was specific to a given respiratory complex, OXPHOS kinetics were assessed in isolated mitochondria energized with either complex I (CI)- or CII-linked substrate combinations. Note, the presence of saturating malate in the CI substrate mix results in CII inhibition via malate-fumarate equilibration (Fig. 3D). Likewise, the addition of rotenone in the presence of succinate eliminates residual CI-supported flux by downstream products of succinate oxidation (Fig. 3D). Using either CI- or CII-linked substrates, we once again observed a more pronounced decrease in respiration in response to ΔG_ATP titration in leukemic mitochondria, as well as a relative inability of FCCP to restore maximal respiratory flux (Fig. 3E-H). Taken together these findings demonstrate that leukemic mitochondria are characterized by a unique form of OXPHOS regulation involving ETS inhibition by ATP free energy.

Subcellular proteomics reveals unique isoform expression of the adenine nucleotide translocase (ANT) in leukemia. To identify potential protein mediators responsible for OXPHOS insufficiency in leukemia, we conducted a proteomics screen using TMT-labeled peptides prepared from the same isolated mitochondria samples used for functional characterization. To control for group differences in percent mitochondrial enrichment, nLC-MS/MS raw data were searched using the MitoCarta 2.0 database, as previously described (McLaughlin et al., 2020). Using this approach, total mitochondrial protein abundance was similar between groups (Supp. Table 1), thus allowing for intrinsic mitochondrial signatures to be identified across leukemia. In total, 135 differentially expressed mitochondrial proteins (adjusted P value < 0.01) were identified comparing PBMC to each of the three leukemia lines (Fig. 4A). For pair-wise comparisons of mitochondrial protein expression between PBMC and each of the three leukemia cell lines, see Supp. Table 1. With respect to the shared differentially expressed proteins, several of these proteins have previously been implicated in cancer biology, such as decreased MAOB (Ryu et al., 2018) and HK1 (Rai et al., 2019), and increased MTHFD1L (Lee et al., 2017), and COX17 (Singh et al., 2020) (Fig. 4A).

Focusing on the OXPHOS proteome, we assessed the abundance of the individual protein subunits that comprise CI, CII, CIII, and CIV, as well as the protein components of the phosphorylation system which include ATP synthase (CV), the phosphate carrier (SLC25A3), and ANT (Fig. 4B). Although considerable heterogeneity was present across groups, comparing protein expression profiles of the individual subunits that comprise CI-CV and SLC25A3 (Fig. 4C, Supp. Fig. 3A-D) revealed that only 6 of the 110 subunits were similarly altered in leukemia (Supp. Table 1). With the exception of COX6A1, all protein subunits were involved in the assembly of CI (NDUFB10), CIV (COA4, COA7, COX17) or CV (ATPAF2). In stark contrast, the expression profiles of the three main ANT isoforms were entirely distinct between PBMC and leukemia mitochondria, highlighted by reduced ANT1 (SLC25A4) and increased ANT2 (SLC25A5) and ANT3 (SLC25A6) in leukemia (Fig. 4D).

Inhibition of ETS flux by ΔG_ATP is a result of matrix ATP consumption in leukemia. Given that ATP free energy was required to induce ETS flux inhibition, we hypothesized that this effect may be mediated by ATP transport into the matrix, facilitated by dominant ANT2/3 expression in leukemia (Chevrollier et al., 2011). To test this hypothesis, FCCP-supported respiration was assessed in permeabilized MV-4-11 and HL-60 cells exposed to ΔG_ATPof -61.49 kJ/mol in the absence and presence of the ANT inhibitor carboxyatractyloside (CAT) (Maldonado et al., 2016). Consistent with our prior findings, the addition of FCCP in the presence of ΔG_ATP was incapable of restoring flux to levels obtained with minimal ATP free energy in leukemia (Fig. 5A-B; ‘ΔG_ATP (-61.49 kJ/mol)’). However, relative to no adenylates, as well as minimal ΔG_ATP(e.g., - 54.16 kJ/mol), the addition of CAT restored maximal FCCP-supported ETS flux in the presence of maximal ATP free energy (Fig. 5A-C). Similar experiments performed in MV-4-11 isolated mitochondria (Fig. 5D), as well as with the ANT inhibitor bongkrekic acid (Supp. Fig. 4A) revealed nearly identical results, indicating that ETS flux inhibition by ΔG_ATPrequires matrix ATP uptake via ANT.

As a component of OXPHOS, ANT functions to exchange matrix ATP for cytosolic ADP in a process that consumes (i.e., depolarizes) the electrochemical proton gradient across the inner membrane. It is critical to point out that the directionality of transport by ANT is dependent on inner membrane polarization. Based on this, if indeed ANT2/3 were favoring matrix ATP uptake in leukemia then chemical inhibition of the phosphorylation system should depolarize, rather than hyperpolarize, membrane potential in leukemic isolated mitochondria. To test this, we quantified mitochondrial membrane potential in substrate-replete isolated mitochondria from HL-60 and KG-1, as well as PBMC, across a ΔG_ATP span and then assessed the impact of ANT inhibition with CAT or CV inhibition with oligomycin. Contrary to that seen in PBMC (Fig. 5E), the addition of CAT or oligomycin caused a near complete elimination of mitochondrial membrane potential in HL-60 and KG-1 (Fig. 5F-G, Supp. Fig. 4B), indicative of matrix ATP uptake/consumption. Interestingly, in similar experiments with MV-4-11 mitochondria, the addition of oligomycin partially polarized membrane potential (Fig. 5H), presumably due to the higher ETS capacity of MV-4-11 compared to HL-60 or KG-1 (Fig. 2B). However, in the absence of any carbon substrates (i.e., no forward electron transport), membrane potential generated exclusively by ΔG_ATPwas ~2-fold more polarized in all AML lines compared to PBMC (Fig. 5I). In fact, for each AML line, membrane potential generated by ATP consumption was comparable to that generated during forward electron transport with saturating carbon substrates (Fig. 5J). Together, these data indicate that leukemic mitochondria are particularly poised to consume, rather than produce, ATP. Such a mechanism appears mediated by the dominant expression of ANT2/3 in AML and once inside the matrix, ATP exerts a direct inhibitory effect on ETS flux.

Low fractional OXPHOS in AML is reversed by small-molecule inhibitors of TRAP1. Having established that extramitochondrial ΔG_ATPmust gain access to the matrix space to inhibit ETS flux in leukemia, we next set out to elucidate the potential protein mediator(s) of this effect. To do this, we searched our proteomics dataset for mitochondrial proteins with known kinase and/or ATPase function that were substantially upregulated across all three leukemia lines and identified mitochondrial TRAP1 (Fig. 6A). TRAP1 is the mitochondrial paralog of the heat shock protein 90 (HSP90) family and is widely recognized as a potential anti-cancer drug target across multiple human malignancies, including leukemia (Bryant et al., 2017; Kim et al., 2020; Li et al., 2020; Sanchez-Martin et al., 2020a, 2020b; Sciacovelli et al., 2013; Yoshida et al., 2013). Given that ATPase activity is required for TRAP1 function (Ramkumar et al., 2020), we hypothesized that ΔG_ATP-mediated ETS inhibition may be driven by acute activation of TRAP1. To test this hypothesis, OXPHOS kinetics were assessed in permeabilized MV-4-11 cells in the absence and presence of the purported TRAP1 inhibitor 17-AAG (Kamal et al., 2003). In substrate-replete permeabilized MV-4-11 cells, acute exposure to 17-AAG had no impact on maximal FCCP-supported respiration in the absence of adenylates (Supp. Fig. 5A). Remarkably, the presence of 17-AAG increased JH⁺_OXPHOS and calculated fractional OXPHOS relative to vehicle control and completely restored FCCP-supported respiration in the presence of ATP free energy (Fig. 6B-D). Similar results were observed using permeabilized HL-60 cells (Supp. Fig. 5B-D), as well as using the mitochondrial-targeted TRAP1 inhibitor gamitrinib (Supp. Fig. 4A). Using both MV-4-11 and KG-1 permeabilized cells, the ability of 17-AAG to restore OXPHOS flux was similar in the presence of CI or CII-based carbon substrates (Supp. Fig. 5E-F).

Although ATP is widely understood to be the universal energy currency in cells, it is critical to consider that ATP alone has minimal bio-synthetic power; rather, its utilization as a common energy currency is solely a function of the remarkable displacement of the molecule from equilibrium (~10 orders of magnitude) (Willis et al., 2016). This means that biological processes driven by ATP hydrolysis are presumably fueled by ATP free energy, rather than ATP levels per se. The primary advantage of the CK clamp technique is that it allows for mitochondrial bioenergetics to be evaluated across a physiological ΔG_ATP span without appreciable changes in ATP concentration (Supp. Fig. 5G). Thus, we reasoned that the CK clamp could be utilized to assess 17-AAG effectiveness across a ΔG_ATP span under conditions in which free [ATP] is not rate-limiting. For contrast, we compared the respiratory impact of 17-AAG to that of the commonly used ETC inhibitor antimycin A. Although antimycin A decreased respiratory flux in permeabilized MV-4-11 cells, percent inhibition by the compound was largely insensitive to ΔG_ATP, consistent with its known mechanism of action at CIII (Supp. Fig. 5H). In contrast, across all leukemia cell lines, restoration of respiratory flux by 17-AAG was exquisitely sensitive to ΔG_ATP(Fig. 6E, Supp. Fig. 5I-J).

OXPHOS restoration by 17-AAG and Gamitrinib is independent of TRAP1. To control for potential off-target effects mediated by 17-AAG or gamitrinib, MV-4-11 cells were infected with lentivirus containing pooled short hairpin RNA (shRNA) against TRAP1. Control cells were infected with lentivirus containing scrambled shRNA. All constructs encoded GFP, as well as a puromycin selection gene to allow for stable selection. Following 24hr exposure to lentiviral particles and multiple rounds of puromycin selection, shRNA against TRAP1 led to a > 90% reduction in TRAP1 mRNA (Fig. 6F). Consistent with prior reports (Laquatra et al., 2021; Sciacovelli et al., 2013), TRAP1 knockdown increased basal respiration in intact cells (Fig. 6G). To determine the impact of TRAP1 knockdown on OXPHOS kinetics, JH⁺_Total and JH⁺_OXPHOS were assessed in substrate-replete permeabilized cells. Despite no change in JH⁺_Total (Supp. Fig. 5K), TRAP1 knockdown decreased JH⁺_OXPHOS and exacerbated the ability of ATP free energy to blunt ETS flux (Fig. 6H-J). This was surprising, given that acute administration of 17-AAG/gamitrinib consistently increased fractional OXPHOS across all AML lines (Fig. 6C, Supp. Fig. 5C). Based on this, we hypothesized that the ability of 17-AAG and/or gamitrinib to bolster OXPHOS kinetics may be independent of TRAP1. To test this, we repeated the JH⁺_OXPHOS experiments in control and TRAP1 knockdown cells in the presence of either 17-AAG or gamitrinib. In control cells, acute administration of 17-AAG and gamitrinib once again increased fractional OXPHOS and restored the FCCP effect and near identical results were also apparent in TRAP1 knockdown cells (Fig. 6I-J, Supp. Fig. 5L). Such findings indicated that OXPHOS restoration by 17-AAG/gamitrinib occurs independent of TRAP1 and is thus attributable to an ‘off-target’ mechanism. One such off-target effect documented for 17-AAG relates to the ability of the compound to bind voltage dependent anion transporter (VDAC) (Xie et al., 2011), the principal gatekeeper to adenylate transport across the outer mitochondrial membrane. A similar mechanism has also been described for the anti-cancer compound curcumin (Tewari et al., 2015); however, the implications of these interactions on cellular bioenergetics remain incompletely understood. Interestingly, nearly identical to the effect observed in the presence of 17-AAG/gamitrinib, acute exposure to curcumin also reversed ΔG_ATP-mediated ETS inhibition in MV-4-11 cells (Fig. 6K). Based on the striking functional similarities between 17-AAG, gamitrinib and curcumin, such findings suggest a potential novel mechanism whereby these small molecules are uniquely capable of selectively blocking matrix ATP uptake, while remaining permissive to ADP uptake, presumably via interaction with the VDAC-ANT axis (Fig. 6L). In support of this, curcumin-VDAC interaction is known to lock VDAC in the ‘closed’ confirmation, in turn making it partially selective for cation (i.e., ADP^3-), rather than anion (i.e., ATP^4-), transport (Tewari et al., 2015).

To investigate the relationship between mitochondrial fractional OXPHOS and AML biology, we assessed cellular proliferation and viability in control and TRAP1 knockdown cells exposed to gamitrinib, curcumin, or vehicle control. In the absence of any small-molecule intervention, cellular proliferation was higher in TRAP1 knockdown cells (Fig. 6M), consistent with low fractional OXPHOS being advantageous to AML growth. To determine the therapeutic efficacy of restoring fractional OXPHOS in AML, cells were exposed for 24 hrs to either gamitrinib or curcumin, either alone or in combination with the front-line AML chemotherapeutic cytarabine (Ara-C). Compared to marginal cytotoxicity in response to Ara-C dose escalation, 24hr exposure to either gamitrinib or curcumin decreased cell viability by as much as 60% (Fig. 6N). Note, identical cytotoxicity was observed in control and TRAP1 knockdown cells, and the additional presence of Ara-C had no further impact (Fig. 6N).

Intrinsic limitations in OXPHOS characterize human primary leukemia. To determine if the bioenergetic phenotypes present in leukemia cell lines translated to the clinic, we recruited patients diagnosed with leukemia and comprehensively evaluated mitochondrial bioenergetic function in mononuclear cells isolated from bone marrow aspirates. All patients had confirmed leukemia at the time of sample acquisition. Biochemical results were compared to PBMC isolated from age-matched participants without a prior history of leukemia. As additional controls, OXPHOS kinetics were assessed in mononuclear cells isolated from bone marrow aspirates of heathy subjects (BM_Healthy), as well as purified CD34+ hematopoietic stem cells. To ascertain the impact of clonal cell expansion on the underlying mitochondrial network, experiments in unstimulated (i.e., quiescent) CD34+ cells were also performed following chronic exposure to proliferative stimuli (e.g., TPO, SCF, FLT-3; ‘CD34+_GFs’). Relative to PBMC, BM_Healthy, and quiescent CD34+, intact basal respiration was elevated in primary leukemia, as well as clonally expanding CD34+ (Fig. 7A), reminiscent of that seen in AML cell lines and entirely consistent with their proliferative phenotypes. Relative to quiescent CD34+, JH⁺_Total in substrate-replete permeabilized cells was ~ 2-fold higher in PBMC, CD34+_GFs and primary leukemia (Fig. 7B), consistent with higher cellular mitochondrial density. Despite this apparent increase in mitochondrial content, JH⁺_OXPHOS remained elevated above quiescent CD34+ only in PBMC, as OXPHOS kinetics were completely unaltered comparing clonally expanding CD34+ or primary leukemia to quiescent CD34+ (Fig. 7C). As seen in the AML cell lines, calculated fractional OXPHOS was decreased in clonally expanding CD34+ and primary leukemia, entirely consistent with low fractional OXPHOS being required for hematopoietic clonal expansion (Fig. 7D). To determine the impact of 17-AAG on OXPHOS kinetics, CK clamp experiments were performed in a separate cohort of primary AML samples, as well as clonally expanding CD34+ cells. Relative to vehicle control, 17-AAG increased JH⁺_OXPHOS and restored FCCP-stimulated respiration in the presence of ΔG_ATP in primary AML and CD34+_GFs (Fig. 7E-F). Of note, acute 17-AAG had no impact on OXPHOS kinetics in PBMC or BM_Healthy and 24hr exposure of PBMC to 17-AAG or gamitrinib did not impact cell viability (Supp. Fig. 6A-C).

Intrinsic limitations in OXPHOS power output characterize venetoclax resistance in AML. The preponderance of evidence related to mitochondrial bioenergetics in AML indicates that active repression of OXPHOS is advantageous to the leukemia phenotype. Related to this, although several reports have linked AML chemoresistance to apparent increases in ‘OXPHOS reliance’ (Farge et al., 2017; Guièze et al., 2019; Liu et al., 2020; Roca-Portoles et al., 2020), such conclusions are based largely on intact cellular respirometry in which OXPHOS kinetics are not directly quantified. To address the specific role for OXPHOS in AML chemoresistance, we conducted a series of experiments in chemosensitive HL-60 cells and compared the results to HL-60 cells made to be refractory to venetoclax (Fig. 8A-B). In these experiments, JH⁺_Total and JH⁺_OXPHOS were determined as described above. In addition, OXPHOS kinetic data generated using the CK clamp was integrated with parallel analysis of OXPHOS efficiency (mitochondrial ATP synthesis relative to oxygen consumption; quantified as the P/O ratio). By incorporating empirically derived P/O, respiratory flux at each ΔG_ATP can be converted to ATP production rate. Assuming extra-mitochondrial force applied via the CK clamp is fixed at each titration step, ATP production rate can be used to quantitate OXPHOS power output in Watts (J∙s^-1). Power is an extremely useful parameter because it encompasses thermodynamic, kinetic, as well as stochiometric descriptions that effectively report on the actual quantities of OXPHOS work performed across the demand range. Looking first at intact cellular respirometry, both basal and maximal respiratory capacity were elevated in venetoclax-resistant HL-60 (HL60_VR) (Fig. 8C). Remarkably, despite a near ~2-fold increase in cellular respiratory capacity, OXPHOS kinetics were in fact decreased in HL60_VR, such that JH⁺_OXPHOS failed to reach the respiratory rates observed under basal conditions prior to digitonin permeabilization (Fig. 8D). Of note, the addition of extramitochondrial cytochrome C did not impact JH⁺_OXPHOS in either cell type (Fig. 8E). The combination of increased maximal respiratory capacity combined with decreased JH⁺_OXPHOS translated to a striking decrease in both fractional OXPHOS (Fig. 8F), as well as OXPHOS power output in HL60_VR (Fig. 8G-I), indicating that intrinsic OXPHOS insufficiency also underlies cellular bioenergetics in chemoresistant AML.

Increased mitochondrial oxidative metabolism, an established metabolic hallmark of leukemia (Byrd et al., 2013; Kuntz et al., 2017; Lee et al., 2015; Sriskanthadevan et al., 2015; Suganuma et al., 2010), has been historically interpreted to reflect an increased reliance on mitochondrial ATP production. However, fractional OXPHOS kinetics had not been empirically evaluated in leukemia at the onset of this project. Thus, it remained to be determined whether higher basal respiration in leukemia reflected accelerated demand for ATP regeneration or intrinsic OXPHOS insufficiency. Both conditions would be expected to similarly restrict cellular ATP/ADP equilibrium displacement (i.e., ΔG_ATP charge) and thus could potentially result in identical respiratory profiles in intact cells. For example, a small network of mitochondria each respiring near maximal capacity could in theory produce an identical ‘basal’ oxygen consumption rate to that of a comparatively larger mitochondrial network in which forward respiratory flux was constrained across each mitochondrial unit. Our findings provide definitive support for the latter scenario in AML, as application of our diagnostic biochemical workflow revealed that intrinsic limitations in fractional OXPHOS characterize an expansive mitochondrial network in human leukemia. In fact, a substantial portion of the AML mitochondrial network is incapable of contributing to oxidative ATP production, as leukemic mitochondria primarily consume, rather than produce, ATP across a physiological ΔG_ATP span. Intrinsic OXPHOS limitations in AML appear to derive from a unique biochemical mechanism whereby extra-mitochondrial ATP gains access to the matrix space, where it then directly inhibits electron transport flux in a ΔG_ATP dependent manner. Such inhibition is independent of ATP synthase (i.e., CV) and presumably localized to the respiratory complexes downstream of the ubiquinone pool (i.e., CIII, Cyt C, CIV). Given that evidence for this effect was also observed in bone marrow-derived CD34+ stem cells, allosteric and/or post-translation regulation of ETS flux is likely a primary mode of OXPHOS regulation in hematopoietic progenitors that is maintained during leukemogenesis. Importantly, reversal of this effect was strongly cytotoxic to AML, indicating that direct OXPHOS regulation by ΔG_ATP confers a survival advantage during hematopoietic clonal cell expansion. Although additional work will be required to fully elucidate the mechanism(s) by which ATP uptake directly inhibits OXPHOS flux in AML, our preliminary findings leveraging gamitrinib and curcumin provide proof-of-principle that such regulation can indeed be targeted therapeutically.

While prior work has implicated ANT2 (Chevrollier et al., 2011; Lee et al., 2019; Maldonado et al., 2016) in cancer biology, we present for the first time here a potential mechanism whereby ANT2/3 regulate leukemic cell metabolism via ΔG_ATP. Specifically, our findings inform a model of leukemia bioenergetics in which decreased ANT1, and increased ANT2/3 favor the uptake of extra-mitochondrial ATP into the matrix space. The transfer of ΔG_ATP from the cytosol to the matrix in turn constrains OXPHOS via direct inhibition of the ETS. Direct ETS inhibition by ΔG_ATP could derive from multiple sources, such as adenylate-mediated allosteric regulation (Kadenbach, 2020), inhibitory phosphorylation of the respiratory complexes (Helling et al., 2012), or chaperone mediated protein-protein interactions (Sciacovelli et al., 2013). In either case, the exquisite sensitivity of the ETS to ΔG_ATP likely prevents the mitochondrial network from contributing to the cellular ΔG_ATP charge in the leukemic blasts. Consequentially, maintenance of a low cellular ΔG_ATP would be predicted to maximize both glycolytic and mitochondrial metabolism, entirely consistent with the known hyper-metabolic phenotype of human leukemia (Goto et al., 2014a, 2014b; Suganuma et al., 2010). Such conditions are likely advantageous to proliferating leukemic blasts, as insufficient ATPase activity has been demonstrated to be rate-limiting for cellular proliferation (Luengo et al., 2020).

Currently, there is great interest in developing novel pharmacotherapies that target mitochondrial OXPHOS in leukemia (Farge et al., 2017; Guièze et al., 2019; Kuntz et al., 2017; Lee et al., 2015; Panina et al., 2020). Yet, a large caveat of targeting mitochondria is the ubiquitous necessity of OXPHOS for healthy cellular metabolism. If indeed the proliferative potential of leukemia depends upon mitochondrial ATP consumption, rather than production, it is tempting to speculate that a pharmaceutical intervention designed to restore OXPHOS kinetics and/or ΔG_ATP could effectively halt cell proliferation, in turn allowing for proliferating blasts to succumb to apoptosis. Such a targeted approach would be expected to minimize secondary toxicity as increased OXPHOS efficiency is likely advantageous across non-cancerous, highly metabolic tissues (e.g., brain, heart, muscle), as well as in the context of adaptive cellular immunity (Buck et al., 2016; Vardhana et al., 2020). Based upon our proposed model, targeting the acute OXPHOS regulating capabilities of ΔG_ATP through the VDAC-ANT axis provides an appealing, leukemia-specific target for pharmaceutical intervention, as small-molecule interference of this pathway restored OXPHOS kinetics in leukemic mitochondria and induced cytotoxicity (Fig. 6). Although prior work has identified TRAP1 (Bryant et al., 2017; Ramkumar et al., 2020) as a potential anti-cancer target in leukemia, genetic knockdown in MV-4-11 cells increased, rather than decreased, cellular proliferation in the present study. Of note, the mitochondrial-localized TRAP1 inhibitor gamitrinib is currently being evaluated in a first-in-human phase I clinical trial for treatment of advanced cancers (ClinicalTrials.gov Identifier: NCT04827810). It is currently unclear how much of the cytotoxicity induced by 17-AAG and/or gamitrinib is attributable to on-target TRAP1 inhibition vs off-target interference with ATP exchange via VDAC-ANT. Moreover, the mechanism of cytotoxicity induced by 17-AAG/gamitrinib/curcumin requires additional experimentation. Although speculative, it is possible that the ability of these compounds to selectively block matrix ATP uptake acutely restores full respiratory competence of the expansive AML mitochondrial network, in turn increasing redox pressure across the ETS and boosting ROS production above a cytotoxic threshold.

Taken together, the present findings provide novel insight into the hyper-metabolic phenotype characteristic of human leukemia. With respect to the mitochondria, it bears repeating that heightened basal respiration in AML is almost exclusively assumed to reflect an increased reliance on oxidative ATP synthesis (i.e., OXPHOS). Although this assumption largely underscores the growing interest in targeting mitochondrial oxidative metabolism in cancer, direct interrogation of the mitochondrial network herein consistently revealed active OXPHOS repression in AML. Representative of this phenotype, TRAP1 knockdown and venetoclax resistance both resulted in an increase in basal respiration that was subsequently linked to decreased, not increased, OXPHOS kinetics. Such findings highlight the diagnostic limitations of metabolic measurements made in intact cells and suggest that too much reliance on binary readouts of respiration versus glycolysis may in fact be masking ‘actionable’ cancer-specific mitochondrial biology. By leveraging comprehensive mitochondrial diagnostics, our collective findings inform a model whereby intrinsic OXPHOS limitations support aggressive disease dissemination in leukemia and raise the intriguing possibility that pharmaceutical interventions aimed at blocking mitochondrial ATP uptake/consumption warrants further exploration. Given that increased OXPHOS efficiency is advantageous across non-cancerous tissues, a potential benefit to this novel treatment paradigm is the minimization of secondary toxicity (i.e., a wide therapeutic window).

All procedures involving human subjects were approved by the Institutional Review Board of the Brody School of Medicine.

Blood collection and isolation of PBMCs.

Venous blood from the brachial region of the upper arm was collected from healthy volunteers, ranging from 18-70 years. Whole blood was collected in sodium-heparinized Cell Preparation Tubes (CPT) (BD Biosciences, Franklin Lakes, NJ) and centrifuged at 1,800 x g for 15 min. Prior to experimentation, mononuclear cells were washed in ammonium-chloride-potassium (ACK) lysis buffer to remove red blood cells and either used immediately for experiments or cultured overnight in IMDM (Thermo Fisher Scientific, Waltham, MA) supplemented with glutamine, 10% FBS, and 1% penicillin/streptomycin.

Mononuclear cell isolation from bone marrow aspirates

Bone marrow aspirates were collected from healthy donors, ages 26-33, supplied by HemaCare (Northridge, CA). For primary leukemia samples, bone marrow aspirates were collected from patients undergoing confirmatory diagnosis for a range of hematological malignancies. Patients with confirmed leukemia were enrolled in the study. Type of leukemia ranged from acute myeloid leukemia (AML, N=14), chronic myeloid leukemia (CML, N=2), and granular lymphocytic leukemia (N=1). Patient age ranged from 32-78 years (male/female, 8/9). Bone marrow aspirates were collected in sodium-heparinized Cell Preparation Tubes (CPT) (BD Biosciences, Franklin Lakes, NJ) and centrifuged at 1,800 x g for 15 min. Mononuclear cells were isolated and then washed in ACK lysis buffer to remove red blood cells and used immediately for experiments.

CD34⁺ Stem/Progenitor cell collection and culture

CD34⁺cells were purchased from HemaCare (Northridge, CA). These cells were isolated and purified from bone marrow aspirates of healthy donors, ages 20-39. A portion from each vial was cultured in IMDM supplemented with 15% HyClone FBS, recombinant human SCF (25ng/mL), TPO (50ng/mL), and FLT-3 (50ng/mL).

AML cell line culture

HL-60, KG-1, and MV-4-11 (ATCC, Manassas, VA) human leukemia cells were cultured in IMDM (Thermo Fisher Scientific, Waltham, MA) supplemented with glutamax, 10% FBS, and 1% penicillin/streptomycin and incubated at 37°C in 5% CO₂. All cell lines were obtained from ATCC (Manassas, VA). Cell lines were not tested or authenticated over and above documentation provided by ATCC, which included antigen expression, DNA profile, short tandem repeat profiling, and cytogenetic analysis. For experiments involving venetoclax resistance, HL-60 cells were cultured in RPMI-1640, supplemented with glutamax, 10% FBS, and 1% penicillin/streptomycin. To model venetoclax resistance, HL-60 cells were conditionally adapted over time to 1µM venetoclax in a manner previously described for other chemotherapy drugs (L. P. Kao et al., 2019). Upon reaching an average cell density of 1.5x10⁶cell/mL the cells were harvested and used for whole cell, permeabilized cell, and isolated mitochondria experiments. Primary human muscle progenitor cells (human myoblasts, ‘HMB’) were derived from fresh muscle biopsy samples, as described previously (Ryan et al., 2018). Cells were cultured on collagen-coated flasks using HMB growth medium (GM: Ham’s F10, supplemented with 20% FBS and 1% penicillin/streptomycin, and supplemented immediately prior to use with 5 ng/ml basic FGF).

Cell viability assays

Cell viability was determined by viable cell count using Trypan Blue (0.4%). Where indicated, viability was determined by fluorescence measurement as previously described (L.-P. Kao et al., 2019). Briefly, cells were seeded in black-wall, 96-well plates, in growth medium. After addition of agents (0.1 ml final well volume), cells were incubated at 37^oC, 5% CO_2,for the times indicated. Viability was determined using propidium iodide (PI) as follows. Positive control cells were permeabilized by addition of 10 µl of 1.0 mg/ml digitonin and incubated at 37^oC, 5% CO_2,for 20 min. Plates were then centrifuged at 1200 x g for 20 min, and after dumping the media, 0.1 ml of a 5.0 µM PI solution in PBS was added. The plate was again incubated for 20 min, and viability was calculated as the mean fluorescence (minus permeabilized vehicle control) at 530 nm excitation and 620 nm emission. For venetoclax induced cell death assays, cell viability was determined using a standard MTT assay and absorption was read at 570 nm.

TRAP1 Knockdown in MV-4-11 cells

MV-4-11 cells were cultured in IMDM (Thermo Fisher Scientific, Waltham, MA) supplemented with glutamax, 10% FBS, and 1% penicillin/streptomycin and incubated at 37°C in 5% CO₂. Human shRNA lentiviral particles packaged from pGFP-C-shLenti vector (4 unique 29mer TRAP1-specific shRNA [ACAGCCGCAAAGTCCTCATCCAGACCAAG; ATGGTGGCTGACAGAGTGGAGGTCTATTC; GGAGACGGACATAGTCGTGGATCACTACA; TGGCTTTCAGATGGTTCTGGAGTGTTTGA], 1 scramble control; 0.5 ml each, >10^7 TU/ml) were purchased from Origene (CAT#: TL300868V). To facilitate infection, MV-4-11 cells and lentiviral particles were co-cultured for 24 hours in individual wells of a 96-well plate in 0.1mL of IMDM growth media, supplemented with 4µg/mL polybrene (multiplicity of infection of approximately 20). At the end of the 24hrs, cells were spun down and resuspended in culture media devoid of polybrene. Cultures were then subjected to puromycin selection by continuous exposure to 2µg/mL puromycin in the culture media. Confirmation of TRAP1 knockdown was performed via real-time PCR. To do this, total RNA was extracted from cell pellets using Qiagen RNeasy Midi kits per manufacturer instructions. RNA was reverse transcribed using Superscript IV reverse transcriptase according to manufacturer instructions (Invitrogen). Real-time PCR on TRAP1 was performed using a Quantstudio 3 Real-Time PCR system (Applied Biosystems). Relative quantification of mRNA levels was determined using the comparative threshold cycle (ΔΔCT) method using FAM-labeled Taqman gene expression assays (Applied Biosystems) specific to TRAP1 run in multiplex with a VIC-labeled 18S control primer.

Confocal Microscopy

Cells were pre-loaded with 200nM Mitotracker Green-FM dye (MTG-FM; Molecular Probes, Eugene, OR) at 37°C for 1hr. Cells were then centrifuged at 300 x g for 7min at ~25°C and resuspended in MTG-FM-free IMDM formulation media (Thermo Fisher) containing 50nM tetramethyl rhodamine methyl ester (TMRM) and 2μM Hoechst 33342. Cells were plated on glass-bottom dishes (MatTek, Ashland, MA) for imaging. Cells were held in place with a thin 1% agarose pad that was applied immediately prior to imaging in order to minimize rapid motion interference during imaging of live non-adherent cells (Ivanusic et al., 2017).

All imaging was performed using an Olympus FV1000 laser scanning confocal microscope (LSCM) with an onstage incubator at 37°C. Acquisition software was Olympus FluoView FSW (V4.2). The objective used was 60X oil immersion (NA=1.35, Olympus Plan Apochromat UPLSAPO60X(F)). Images were 800x800 pixel with 2μs/pixel dwell time, sequential scan mode, resulting in a 4X digital zoom. Hoechst 33342 was excited using the 405nm line of a multiline argon laser; emission was filtered using a 560nm dichroic mirror and 420-460nm barrier filter. MTG-FM was excited using the 488nm line of a multiline argon laser; emission was filtered using a 560nm dichroic mirror and 505-540nm barrier filter. TMRM was excited using a 559nm laser diode; emission was filtered using a 575-675nm barrier filter. Zero detector offset was used for all images and gain at the detectors was kept the same for all imaging. The pinhole aperture diameter was set to 105μm (1 Airy disc).

Images were analyzed using Fiji (Schindelin et al., 2012). Spatial resolution was measured using sub-resolution fluorescent beads (Thermo Fisher) and curve fitting was performed using the MetroloJ plugin in Fiji. 16-bit images were made into a composite. Circular ROIs were manually selected using the ROI manager plugin. Images were then decomposed into separate 16-bit image stacks leaving the ROI positions intact. A Huang auto-threshold was used for automated selection of signal for all three channels. Following threshold application, each signal was measured using the multi-measure feature. Only whole cells were analyzed (i.e. cells on edges of the FOV were excluded). Slices containing cells above the lowest monolayer were removed from stacks to avoid oversampling. The following calculations were performed to determine the relevant signal volumes.

Signal Volume (μm³) = [A*Z]/N

Where A is the signal-positive area selected using a Huang auto-threshold (μm²), Z is the optical section thickness (axial resolution; μm), and N is the number of steps within each optical section (i.e. axial resolution divided by the step size). The latter operation is necessary to correct for oversampling of the signal volumes.

Respiratory flux in intact and permeabilized cells

Approximately 1-3 x 10⁶cells were used for each intact and permeabilized cell experiment. High-resolution respirometry measurements were performed using the Oroboros Oxgraph-2k (O2k; Oroboros Instruments, Innsbruck, Austria) in a 0.5 or 1.0mL reaction volume at 37°C. For normalization to total protein, at the conclusion of each experiment the cell suspension was collected from each chamber and centrifuged at 2,000 x g for 10 min at 4°C. Cells were lysed using low-percentage detergent buffer (CelLytic M) followed by a freeze-thaw cycle, and protein concentration was determined using a BCA protein assay.

Respiratory flux was measured using previously described methods(Fisher-Wellman et al., 2018). For intact cell measurements, cells were resuspended in Intact Cell Respiratory Media (17.7g/L Iscove’s Modified Dulbecco’s Medium (IMDM), 20mM HEPES, 1% Penicillin/Streptomycin, 10% FBS, pH 7.4). After basal respiration was established, oligomycin (Oligo; 0.02µM) was added followed by FCCP titration (FC; 0.5-5µM), rotenone (Rot; 0.5µM) and antimycin A (Ant; 0.5µM). For permeabilized cell measurements, cells were resuspended in Respiratory Buffer supplemented with creatine (105mM MES potassium salt, 30mM KCl, 8mM NaCl, 1mM EGTA, 10mM KH₂PO₄, 5mM MgCl₂, 0.25% BSA, 5mM creatine monohydrate, pH 7.2). Cells were permeabilized with digitonin (Digi; 0.02mg/mL), and respiratory flux was measured using the creatine kinase (CK) clamp and FCCP titration assays. Within the CK clamp assay, the free energy of ATP hydrolysis (ΔG_ATP) is calculated using the equilibrium constant for the CK reaction (K’_CK) and is based upon the addition of known concentrations of creatine (CR), phosphocreatine (PCR), and ATP in the presence of excess amounts of CK (Fisher-Wellman et al., 2018). Calculation of ΔG_ATPat defined PCR concentrations was done using the online resource (https://dmpio.github.io/bioenergetic-calculators/ck_clamp/) previously described (Fisher-Wellman et al., 2018).

For all assays, various combinations of carbon substrates and inhibitors were employed. Substrates and inhibitors utilized are indicated in the figure legends: CK (20U/mL), ATP (5mM), PCR (1mM, 6mM, 15mM, 21mM), pyruvate (Pyr or P; 5mM), malate (M; 1mM), glutamate (G; 5mM), octanoyl-carnitine (O; 0.2mM), succinate (Succ or S; 5mM) cytochrome C (Cyt C, 10µM), oligomycin (Oligo, 0.02µM), FCCP (FC, 0.5-2µM), rotenone (Rot, 0.5µM), antimycin A (Ant A, 0.5µM), carboxyatractyloside (CAT, 1µM), bongkrekic acid (20µM), 17-AAG (sigma, #100068, 1µM), Gamitrinib TPP hexafluorophosphate (MedChemExpress, #HY-102007A, 1µM).

Extracellular flux analysis

Extracellular acidification rate (ECAR) and oxygen consumption rate (OCR) were measured using a Seahorse XF24e flux analyzer (Agilent Technologies, Santa Clara, CA). Prior to analysis, wells were coated with Cell-Tak (Corning, Cat# 354240). Cells were then seeded at 3x10⁵ cells/well. The assay was performed in bicarbonate free IMDM, supplemented with 2mM HEPES, in the absence of FBS, pH 7.4. The flux analysis protocol was as follows: Basal OCR and ECAR were measured followed by the addition of 5μM Oligomycin, and 50mM 2-deoxyglucose (2-DG). All data were normalized to viable cell count.

Isolation of mitochondria from PBMCs and leukemia cells

In order to pellet cells, PBMC fractions were washed with PBS and centrifuged at 300 x g for 10 min at 4°C and leukemia cells were centrifuged at 300 x g for 10 min followed by a PBS wash. Cell pellets were resuspended in Mitochondrial Isolation Buffer with BSA (100mM KCl, 50mM MOPS, 1mM EGTA, 5mM MgSO₄, 0.2% BSA, pH 7.1) and homogenized using a borosilicate glass mortar and Teflon pestle. Homogenates were centrifuged at 800 x g for 10 min at 4°C. The supernatant was collected, and the remaining pellet was resuspended in Mitochondrial Isolation Buffer with BSA, then homogenized and centrifuged again. This process was repeated a total of 3 times. The collected supernatant was centrifuged at 10,000 x g for 10 min at 4°C to pellet the mitochondrial fraction. The fraction was resuspended in Mitochondrial Isolation Buffer without BSA, transferred to a microcentrifuge tube and subjected to another spin at 10,000 x g. The mitochondrial pellet was resuspended in ~100µL of Mitochondria Isolation Buffer and protein concentration was calculated using the Pierce BCA assay. Respiration assays using isolated mitochondria were similar to that described for permeabilized cells.

Mitochondrial NADH/NAD⁺redox in isolated mitochondria

Fluorescent determination of NADH/NAD⁺was performed using a QuantaMaster Spectrofluorometer (QM-400, Horiba Scientific, Kyoto, Japan). The NADH/NAD+ was detected at Ex/Em: 350/450. NADH/NAD+ was measured in mitochondria isolated from PBMC and leukemia cell lines using the CK clamp assay. Experiments were performed at 37°C in a 200µL reaction volume. To start, Respiratory Buffer supplemented with creatine (200µL), Cyt C (10µM), mitochondrial lysate (100µg) were added into a glass cuvette. Mitochondria were incubated at 37°C for ~ 5 minutes in the absence of substrate to induce 0% reduction of the NADH pool. Saturating carbon substrates were added (P/M/G/S/O), and respiration was stimulated with the CK clamp. Titration of ΔG_ATP was performed via PCR titration (6, 15, 21mM). Oligomycin (0.02µM) was added to inhibit ATP synthesis and cyanide (CN, 10mM) was added to induce 100% reduction of the matrix NADH pool. The NADH/NAD+ was expressed as a percentage reduction of the CN value (i.e. 100% reduction) based upon the formula % Reduction = (F-F_0%)/(F_100%-F_0%)*100.

Mitochondrial membrane potential (ΔΨ) in isolated mitochondria

Fluorescent determination of ΔΨ was carried out via a QuantaMaster Spectrofluorometer (QM-400; Horiba Scientific). Determination of ΔΨ via TMRM was done as described previously (Fisher-Wellman et al., 2018), taking the fluorescence ratio of the following excitation/emission parameters [Ex/Em, 576/590 and 551/590]. The 576/551 ratio was then converted to millivolts via a KCl standard curve performed in the presence of valinomycin as described (Fisher-Wellman et al., 2018).

Mitochondrial JATP synthesis, P/O ratio and OXPHOS power output in permeabilized cells

Parallel respiration and fluorometric experiments were carried out in order to generate an ATP/O (P/O) ratio, as previously described (Lark et al., 2016). Experiments were performed at 37°C in a 2.5mL reaction volume in Respiratory Buffer supplemented with AP5A (0.2mM), and digitonin (0.02mg/mL). ATP synthesis and oxygen consumption were determined in permeabilized cells energized with P/M/G/S/O in the presence of 0.1mM ADP. The P/O ratio was then calculated using the ratio of the JATP and the steady state JO₂, divided by 2. Empirically derived P/O ratios were then used to convert oxygen consumption rates recorded during the CK clamp assay (using identical substrates) to ATP production rate [(oxygen consumption rate) x (P/O x 2)]. A fixed extra-mitochondrial force was assumed to be applied via the CK clamp at each PCR titration. These forces corresponded to -54.16, -58.93, -60.64, and -61.49 kJ/mol. These forces were used along with ATP production rate to quantitate OXPHOS power output in Watts (J/s) according to the following formula [(pmol ATP/s/million cells) x (5.416 or 5.893 or 6.064 or 6.149 * 10^-8 J/pmol ATP) = µWatts/million cells].

Mitochondrial lysis, protein digestion, and peptide labeling for TMT quantitative proteomics

Mitochondrial pellets from leukemia cells and PBMC (approximately 250 µg of protein) were lysed in ice-cold 8 M Urea Lysis Buffer (8 M urea in 50 mM Tris, pH 8.0, 40 mM NaCl, 2 mM CaCl₂, 1x cOmplete ULTRA mini EDTA-free protease inhibitor tablet), as described previously(McLaughlin et al., 2020). The samples were frozen on dry ice and thawed for three freeze-thaw cycles and further disrupted by sonication with a probe sonicator in three 5s bursts set at an amplitude of 30 (Q Sonica, Newtown, CT). Samples were centrifuged at 10,000 × g for 10 min at 4 °C to pellet insoluble material. Protein concentration was determined by BCA, and equal amounts of protein (200 μg, adjusted to 2.5 mg/mL with Urea Lysis Buffer) were reduced with 5 mM DTT at 32 °C for 30 min, cooled to room temperature, and then alkylated with 15 mM iodoacetamide for 30 min in the dark. Unreacted iodoacetamide was quenched by the addition of DTT up to 15 mM. Initial digestion was performed with Lys C (Thermo Fisher) 1:100 w-w; 2 µg enzyme per 200 µg protein) for 4 hr at 32 °C. Following dilution to 1.5 M urea with 50 mM Tris (pH 8.0), 30 mM NaCl, 5 mM CaCl₂, the samples were digested overnight with trypsin (Promega, Madison, WI) 50:1 w/w, protein:enzyme at 32 °C. Samples were acidified to 0.5% TFA and centrifuged at 10,000 × g for 10 min at 4 °C to pellet insoluble material. Supernatant containing soluble peptides was desalted on a 50 mg tC18 SEP-PAK solid phase extraction column (Waters, Milford, MA) and eluted (500 μL 25% acetonitrile/0.1% TFA and 2 × 500 μL 50% acetonitrile/0.1% TFA). The 1.5 mL eluate was frozen and lyophilized.

TMT labeling

TMT labeling was performed as previously described(McLaughlin et al., 2020). The samples from isolated mitochondria were re-suspended in 100 μL of 200 mM triethylammonium bicarbonate (TEAB), mixed with a unique 10-plex Tandem Mass Tag (TMT) reagent (0.8 mg re-suspended in 50 μL100% acetonitrile), and shaken for 4 hr at room temperature (Thermo Fisher). A total of 2 x 10-plex kits were used and one sample was TMT-labeled in both kits to control for quantification differences across multiplex preparations. Following quenching with 0.8 μL 50% hydroxylamine samples were frozen, and lyophilized. Samples were re-suspended in ~1 mL of 0.5% TFA and again subjected to solid phase extraction, but with a 100 mg tC18 SEP-PAK SPE column (Waters). The multiplexed peptide sample was subjected to high pH reversed phase fractionation according to the manufacturer’s instructions (Thermo Fisher). In this protocol, peptides (100 µg) are loaded onto a pH-resistant resin and then desalted with water washing combined with low speed centrifugation. A step-gradient of increasing acetonitrile concentration in a high-pH elution solution is then applied to columns to elute bound peptides into 8 fractions. Following elution, fractions were frozen and lyophilized.

nLC-MS/MS for TMT proteomics

nLC-MS/MS was performed as described previously (McLaughlin et al., 2020). Peptide fractions were suspended in 0.1% formic acid at a concentration of 0.25 µg/µL, following peptide quantification (ThermoFisher). All samples were subjected to nanoLC-MS/MS analysis using an UltiMate 3000 RSLCnano system (Thermo Fisher) coupled to a Q Exactive PlusHybrid Quadrupole-Orbitrap mass spectrometer (Thermo Fisher) via nanoelectrospray ionization source. For each injection of 4 µL (1 µg), the sample was first trapped on an Acclaim PepMap 100 20 mm × 0.075 mm trapping column (Thermo Fisher) 5 μl/min at 98/2 v/v water/acetonitrile with 0.1% formic acid, after which the analytical separation was performed over a 90-min gradient (flow rate of 300 nanoliters/min) of 3 to 30% acetonitrile using a 2 µm EASY-Spray PepMap RSLC C18 75 µm × 250 mm column (Thermo Fisher) with a column temperature of 55 °C. MS1 was performed at 70,000 resolution, with an AGC target of 1 × 10⁶ ions and a maximum IT of 60 ms. MS2 spectra were collected by data-dependent acquisition (DDA) of the top 20 most abundant precursor ions with a charge greater than 1 per MS1 scan, with dynamic exclusion enabled for 30s. Precursor ions were filtered with a 1.0 m/z isolation window and fragmented with a normalized collision energy of 30. MS2 scans were performed at 17,500 resolution, AGC target of 1 × 10⁵ ions, and a maximum IT of 60 ms.

Data analysis for TMT proteomics

Proteome Discoverer 2.2 (PDv2.2) was used for raw data analysis, with default search parameters including oxidation (15.995 Da on M) as a variable modification and carbamidomethyl (57.021 Da on C) and TMT6plex (229.163 Da on peptide N-term and K) as fixed modifications, and 2 missed cleavages (full trypsin specificity). Data were searched against human Mito Carta 2.0 database(Calvo et al., 2016). PSMs were filtered to a 1% FDR. PSMs were grouped to unique peptides while maintaining a 1% FDR at the peptide level. Peptides were grouped to proteins using the rules of strict parsimony and proteins were filtered to 1% FDR using the Protein FDR Validator node of PD2.2. MS2 reporter ion intensities for all PSMs having co-isolation interference below 0.5 (50% of the ion current in the isolation window) and an average S/N > 10 for reporter ions were summed together at the peptide and protein level. Imputation was performed via low abundance resampling.

Statistical analysis for TMT proteomic

The protein group tab in the PDv2.2 results was exported as tab delimited.txt. files, and analyzed based on a previously described workflow (McLaughlin et al., 2020). First, M2 reporter (TMT) intensities were summed together for each TMT channel, each channel’s sum was divided by the average of all channels’ sums, resulting in channel-specific loading control normalization factors to correct for any deviation from equal protein input in the 10-plex experiments. Reporter intensities for proteins were divided by the loading control normalization factors for each respective TMT channel. All loading control-normalized reporter intensities were converted to log₂space and the average value from the ten samples per kit was subtracted from each sample specific measurement to normalize the relative measurements to the mean of each kit. Data from each kit were then combined for statistical comparisons. For comparison of PBMC to leukemia cell lines, condition average, standard deviation, p-value (p, two-tailed student’s t-test, assuming equal variance), and adjusted p-value (P_adjusted, Benjamini Hochberg FDR correction) were calculated (Benjamini and Hochberg, 1995; Naugler and Lesack, 2011). For protein-level quantification, only Master Proteins—or the most statistically significant protein representing a group of parsimonious proteins containing common peptides identified at 1% FDR—were used for quantitative comparison.

Proteomics data availability and software

All raw data for proteomics experiments is available online using accession number “PXD020715” for Proteome Xchange (Deutsch et al., 2017) and accession number “JPST000934” for jPOST Repository (Okuda et al., 2017).

Statistical Analysis and Software

Statistical analysis was performed using GraphPad Prism 8.4. All data are represented as mean ± SEM and analysis were conducted with a significance level set at p<0.05. Details of statistical analysis are included within figure legends. Figures were generated using Biorender and GraphPad Prism 8.4.

AKNOWLEDGEMENTS

The work was supported by DOD-W81XWH-19-1-0213 (K.H.F.-W.) and NIH P01 CA171983 (M.C.C). This project used the North Carolina Tissue Consortium (NCTC) shared resource which is supported in part by the University Cancer Research Fund (UCRF).

AUTHOR CONTRIBUTIONS

M.A.N., K.L.M., J.T.H., H.S.C., C.S., M.K., J.M.M., M.C.C, and K.H.F.-W conceived and designed the study. M.A.N., K.L.M., J.T.H., H.S.C., C.S., M.K., K.A.K., and K.H.F.-W performed the experiments. N.A.V. and D.L. supplied clinical samples. M.A.N, K.L.M., and K.H.F.-W prepared the figures and wrote the manuscript. All authors reviewed and approved the manuscript.

ETHICS DECLARATION

The authors of this manuscript declare no competing interests.

Benjamini Y, Hochberg Y. 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B. doi:10.2307/2346101

Bryant KG, Chae YC, Martinez RL, Gordon JC, Elokely KM, Kossenkov A V., Grant S, Childers WE, Abou-Gharbia M, Altieri DC. 2017. A Mitochondrial-targeted purine-based HSP90 antagonist for leukemia therapy. Oncotarget. doi:10.18632/oncotarget.23097

Buck MDD, O’Sullivan D, Klein Geltink RII, Curtis JDD, Chang CH, Sanin DEE, Qiu J, Kretz O, Braas D, van der Windt GJJW, Chen Q, Huang SCC, O’Neill CMM, Edelson BTT, Pearce EJJ, Sesaki H, Huber TBB, Rambold ASS, Pearce ELL. 2016. Mitochondrial Dynamics Controls T Cell Fate through Metabolic Programming. Cell. doi:10.1016/j.cell.2016.05.035

Byrd JC, Furman RR, Coutre SE, Flinn IW, Burger JA, Blum KA, Grant B, Sharman JP, Coleman M, Wierda WG, Jones JA, Zhao W, Heerema NA, Johnson AJ, Sukbuntherng J, Chang BY, Clow F, Hedrick E, Buggy JJ, James DF, O’Brien S. 2013. Targeting BTK with ibrutinib in relapsed chronic lymphocytic leukemia. N Engl J Med. doi:10.1056/NEJMoa1215637

Calvo SE, Clauser KR, Mootha VK. 2016. MitoCarta2.0: An updated inventory of mammalian mitochondrial proteins. Nucleic Acids Res. doi:10.1093/nar/gkv1003

Chevrollier A, Loiseau D, Reynier P, Stepien G. 2011. Adenine nucleotide translocase 2 is a key mitochondrial protein in cancer metabolism. Biochim Biophys Acta - Bioenerg. doi:10.1016/j.bbabio.2010.10.008

Cohen BH. 2010. Pharmacologic effects on mitochondrial function. Dev Disabil Res Rev. doi:10.1002/ddrr.106

Deutsch EW, Csordas A, Sun Z, Jarnuczak A, Perez-Riverol Y, Ternent T, Campbell DS, Bernal-Llinares M, Okuda S, Kawano S, Moritz RL, Carver JJ, Wang M, Ishihama Y, Bandeira N, Hermjakob H, Vizcaíno JA. 2017. The ProteomeXchange consortium in 2017: Supporting the cultural change in proteomics public data deposition. Nucleic Acids Res. doi:10.1093/nar/gkw936

Dykens JA, Will Y. 2007. The significance of mitochondrial toxicity testing in drug development. Drug Discov Today. doi:10.1016/j.drudis.2007.07.013

Farge T, Saland E, de Toni F, Aroua N, Hosseini M, Perry R, Bosc C, Sugita M, Stuani L, Fraisse M, Scotland S, Larrue C, Boutzen H, Féliu V, Nicolau-Travers ML, Cassant-Sourdy S, Broin N, David M, Serhan N, Sarry A, Tavitian S, Kaoma T, Vallar L, Iacovoni J, Linares LK, Montersino C, Castellano R, Griessinger E, Collette Y, Duchamp O, Barreira Y, Hirsch P, Palama T, Gales L, Delhommeau F, Garmy-Susini BH, Portais JC, Vergez F, Selak M, Danet-Desnoyers G, Carroll M, Récher C, Sarry JE. 2017. Chemotherapy-resistant human acute myeloid leukemia cells are not enriched for leukemic stem cells but require oxidative metabolism. Cancer Discov 7:716–735. doi:10.1158/2159-8290.CD-16-0441

Fisher-Wellman KH, Davidson MT, Narowski TM, Lin C Te, Koves TR, Muoio DM. 2018. Mitochondrial Diagnostics: A Multiplexed Assay Platform for Comprehensive Assessment of Mitochondrial Energy Fluxes. Cell Rep Sep 25;24:3593–3606. doi:10.1016/j.celrep.2018.08.091

Fisher-Wellman KH, Draper JA, Davidson MT, Williams AS, Narowski TM, Slentz DH, Ilkayeva OR, Stevens RD, Wagner GR, Najjar R, Hirschey MD, Thompson JW, Olson DP, Kelly DP, Koves TR, Grimsrud PA, Muoio DM. 2019. Respiratory Phenomics across Multiple Models of Protein Hyperacylation in Cardiac Mitochondria Reveals a Marginal Impact on Bioenergetics. Cell Rep. doi:10.1016/j.celrep.2019.01.057

Glancy B, Willis WT, Chess DJ, Balaban RS. 2013. Effect of calcium on the oxidative phosphorylation cascade in skeletal muscle mitochondria. Biochemistry 52:2793–2809. doi:10.1021/bi3015983

Goto M, Miwa H, Shikami M, Tsunekawa-Imai N, Suganuma K, Mizuno S, Takahashi M, Mizutani M, Hanamura I, Nitta M. 2014a. Importance of glutamine metabolism in leukemia cells by energy production through TCA cycle and by redox homeostasis. Cancer Invest 32:241–247. doi:10.3109/07357907.2014.907419

Goto M, Miwa H, Suganuma K, Tsunekawa-Imai N, Shikami M, Mizutani M, Mizuno S, Hanamura I, Nitta M. 2014b. Adaptation of leukemia cells to hypoxic condition through switching the energy metabolism or avoiding the oxidative stress. BMC Cancer 14:1–9. doi:10.1186/1471-2407-14-76

Guièze R, Liu VM, Rosebrock D, Jourdain AA, Hernández-Sánchez M, Martinez Zurita A, Sun J, Ten Hacken E, Baranowski K, Thompson PA, Heo JM, Cartun Z, Aygün O, Iorgulescu JB, Zhang W, Notarangelo G, Livitz D, Li S, Davids MS, Biran A, Fernandes SM, Brown JR, Lako A, Ciantra ZB, Lawlor MA, Keskin DB, Udeshi ND, Wierda WG, Livak KJ, Letai AG, Neuberg D, Harper JW, Carr SA, Piccioni F, Ott CJ, Leshchiner I, Johannessen CM, Doench J, Mootha VK, Getz G, Wu CJ. 2019. Mitochondrial Reprogramming Underlies Resistance to BCL-2 Inhibition in Lymphoid Malignancies. Cancer Cell 36:369-384.e13. doi:10.1016/j.ccell.2019.08.005

Helling S, Hüttemann M, Ramzan R, Kim SH, Lee I, Müller T, Langenfeld E, Meyer HE, Kadenbach B, Vogt S, Marcus K. 2012. Multiple phosphorylations of cytochrome c oxidase and their functions. Proteomics 12:950–959. doi:10.1002/pmic.201100618

Inoue T, Swain A, Nakanishi Y, Sugiyama D. 2014. Multicolor analysis of cell surface marker of human leukemia cell lines using flow cytometryAnticancer Research.

Ivanusic D, Madela K, Denner J. 2017. Easy and cost-effective stable positioning of suspension cells during live-cell imaging. J Biol Methods 4:80. doi:10.14440/jbm.2017.203

Jitschin R, Hofmann AD, Bruns H, Gießl A, Bricks J, Berger J, Saul D, Eckart MJ, Mackensen A, Mougiakakos D. 2014. Mitochondrial metabolism contributes to oxidative stress and reveals therapeutic targets in chronic lymphocytic leukemia. Blood 123:2663–2672. doi:10.1182/blood-2013-10-532200

Kadenbach B. 2020. Complex IV– the regulatory center of mitochondrial oxidative phosphorylation. Mitochondrion. doi:10.1016/j.mito.2020.10.004

Kamal A, Thao L, Sensintaffar J, Zhang L, Boehm MF, Fritz LC, Burrows FJ. 2003. A high-affinity conformation of Hsp90 confers tumour selectivity on Hsp90 inhibitors. Nature 425:407–410. doi:10.1038/nature01913

Kao L-P, Morad SAF, Davis TS, MacDougall MR, Kassai M, Abdelmageed N, Fox TE, Kester M, Loughran TP, Abad JL, Fabrias G, Tan S-F, Feith DJ, Claxton DF, Spiegel S, Fisher-Wellman KH, Cabot MC. 2019. Chemotherapy selection pressure alters sphingolipid composition and mitochondrial bioenergetics in resistant HL-60 cells. J Lipid Res 60. doi:10.1194/jlr.RA119000251

Kao LP, Morad SAF, Davis TS, MacDougall MR, Kassai M, Abdelmageed N, Fox TE, Kester M, Loughran TP, Abad JL, Fabrias G, Tan SF, Feith DJ, Claxton DF, Spiegel S, Fisher-Wellman KH, Cabot MC. 2019. Chemotherapy selection pressure alters sphingolipid composition and mitochondrial bioenergetics in resistant HL-60 cells. J Lipid Res. doi:10.1194/jlr.RA119000251

Kim Darong, Kim SY, Kim Dongyoung, Yoon NG, Yun J, Hong KB, Lee C, Lee JH, Kang BH, Kang S. 2020. Development of pyrazolo[3,4-d]pyrimidine-6-amine-based TRAP1 inhibitors that demonstrate in vivo anticancer activity in mouse xenograft models. Bioorg Chem 101:103901. doi:10.1016/j.bioorg.2020.103901

Kuntz EM, Baquero P, Michie AM, Dunn K, Tardito S, Holyoake TL, Helgason GV, Gottlieb E. 2017. Targeting mitochondrial oxidative phosphorylation eradicates therapy-resistant chronic myeloid leukemia stem cells. Nat Med 23:1234–1240. doi:10.1038/nm.4399

Lagadinou ED, Sach A, Callahan K, Rossi RM, Neering SJ, Minhajuddin M, Ashton JM, Pei S, Grose V, O’Dwyer KM, Liesveld JL, Brookes PS, Becker MW, Jordan CT. 2013. BCL-2 inhibition targets oxidative phosphorylation and selectively eradicates quiescent human leukemia stem cells. Cell Stem Cell 12:329–341. doi:10.1016/j.stem.2012.12.013

Laquatra C, Sanchez-Martin C, Dinarello A, Cannino G, Minervini G, Moroni E, Schiavone M, Tosatto S, Argenton F, Colombo G, Bernardi P, Masgras I, Rasola A. 2021. HIF1α-dependent induction of the mitochondrial chaperone TRAP1 regulates bioenergetic adaptations to hypoxia. Cell Death Dis 12:434. doi:10.1038/s41419-021-03716-6

Lark DS, Torres MJ, Lin C Te, Ryan TE, Anderson EJ, Neufer PD. 2016. Direct real-time quantification of mitochondrial oxidative phosphorylation efficiency in permeabilized skeletal muscle myofibers. Am J Physiol - Cell Physiol. doi:10.1152/ajpcell.00124.2016

Lee CH, Kim MJ, Lee HH, Paeng JC, Park YJ, Oh SW, Chai YJ, Kim YA, Cheon GJ, Kang KW, Youn H, Chung JK. 2019. Adenine Nucleotide Translocase 2 as an Enzyme Related to [18F] FDG Accumulation in Various Cancers. Mol Imaging Biol 21:722–730. doi:10.1007/s11307-018-1268-x

Lee D, Xu IMJ, Chiu DKC, Lai RKH, Tse APW, Li LL, Law CT, Tsang FHC, Wei LL, Chan CYK, Wong CM, Ng IOL, Wong CCL. 2017. Folate cycle enzyme MTHFD1L confers metabolic advantages in hepatocellular carcinoma. J Clin Invest. doi:10.1172/JCI90253

Lee EA, Angka L, Rota SG, Hanlon T, Mitchell A, Hurren R, Wang XM, Gronda M, Boyaci E, Bojko B, Minden M, Sriskanthadevan S, Datti A, Wrana JL, Edginton A, Pawliszyn J, Joseph JW, Quadrilatero J, Schimmer AD, Spagnuolo PA. 2015. Targeting mitochondria with avocatin B induces selective leukemia cell death. Cancer Res 75:2478–2488. doi:10.1158/0008-5472.CAN-14-2676

Li XT, Li YS, Shi ZY, Guo XL. 2020. New insights into molecular chaperone TRAP1 as a feasible target for future cancer treatments. Life Sci 254:117737. doi:10.1016/j.lfs.2020.117737

Liu F, Kalpage HA, Wang D, Edwards H, Hüttemann M, Ma J, Su Y, Carter J, Li X, Polin L, Kushner J, Dzinic SH, White K, Wang G, Taub JW, Ge Y. 2020. Cotargeting of mitochondrial complex i and bcl-2 shows antileukemic activity against acute myeloid leukemia cells reliant on oxidative phosphorylation. Cancers (Basel) 12:1–19. doi:10.3390/cancers12092400

Luengo A, Li Z, Gui D, Sullivan L, Zagorulya M, Do B, Ferreira R, Naamati A, Ali A, Lewis C, Thomas C, Spranger S, Matheson N, Vander Heiden M. 2020. Increased demand for NAD+ relative to ATP drives aerobic glycolysis. Mol Cell 1–17. doi:10.1101/2020.06.08.140558

Luptak I, Sverdlov AL, Panagia M, Qin F, Pimentel DR, Croteau D, Siwik DA, Ingwall JS, Bachschmid MM, Balschi JA, Colucci WS. 2018. Decreased ATP production and myocardial contractile reserve in metabolic heart disease. J Mol Cell Cardiol 116:106–114. doi:10.1016/j.yjmcc.2018.01.017

Maldonado EN, DeHart DN, Patnaik J, Klatt SC, Gooz MB, Lemasters JJ. 2016. ATP/ADP turnover and import of glycolytic ATP into mitochondria in cancer cells is independent of the adenine nucleotide translocator. J Biol Chem 291:19642–19650. doi:10.1074/jbc.M116.734814

Martínez-Reyes I, Cardona LR, Kong H, Vasan K, McElroy GS, Werner M, Kihshen H, Reczek CR, Weinberg SE, Gao P, Steinert EM, Piseaux R, Budinger GRS, Chandel NS. 2020. Mitochondrial ubiquinol oxidation is necessary for tumour growth. Nature. doi:10.1038/s41586-020-2475-6

McLaughlin KL, Kew KA, McClung JM, Fisher-Wellman KH. 2020. Subcellular proteomics combined with bioenergetic phenotyping reveals protein biomarkers of respiratory insufficiency in the setting of proofreading-deficient mitochondrial polymerase. Sci Rep. doi:10.1038/s41598-020-60536-y

McLaughlin KL, McClung JM, Fisher-Wellman KH. 2018. Bioenergetic consequences of compromised mitochondrial DNA repair in the mouse heart. Biochem Biophys Res Commun 3–9. doi:10.1016/j.bbrc.2018.09.022

Messer JI, Jackman MR, Willis WT. 2004. Pyruvate and citric acid cycle carbon requirements in isolated skeletal muscle mitochondria. Am J Physiol Cell Physiol 286:C565-572. doi:10.1152/ajpcell.00146.2003

Mirali S, Botham A, Voisin V, Xu C, St-Germain J, Sharon D, Hoff FW, Qiu Y, Hurren R, Gronda M, Jitkova Y, Nachmias B, MacLean N, Wang X, Arruda A, Minden MD, Horton TM, Kornblau SM, Chan SM, Bader GD, Raught B, Schimmer AD. 2020. The mitochondrial peptidase, neurolysin, regulates respiratory chain supercomplex formation and is necessary for AML viability. Sci Transl Med 12:1–17. doi:10.1126/scitranslmed.aaz8264

Mrózek K, Tanner SM, Heinonen K, Bloomfield CD. 2003. Molecular cytogenetic characterization of the KG-1 and KG-1a acute myeloid leukemia cell lines by use of spectral karyotyping and fluorescence in situ hybridization. Genes Chromosom Cancer 38:249–252. doi:10.1002/gcc.10274

Naugler C, Lesack K. 2011. An open-source software program for performing Bonferroni and related corrections for multiple comparisons. J Pathol Inform. doi:10.4103/2153-3539.91130

Okuda S, Watanabe Y, Moriya Y, Kawano S, Yamamoto T, Matsumoto M, Takami T, Kobayashi D, Araki N, Yoshizawa AC, Tabata T, Sugiyama N, Goto S, Ishihama Y. 2017. JPOSTrepo: An international standard data repository for proteomes. Nucleic Acids Res. doi:10.1093/nar/gkw1080

Panina SB, Pei J, Baran N, Konopleva M, Kirienko N V. 2020. Utilizing Synergistic Potential of Mitochondria-Targeting Drugs for Leukemia Therapy. Front Oncol 10. doi:10.3389/fonc.2020.00435

Rai Y, Yadav P, Kumari N, Kalra N, Bhatt AN. 2019. Hexokinase II inhibition by 3-bromopyruvate sensitizes myeloid leukemic cells K-562 to anti-leukemic drug, daunorubicin. Biosci Rep. doi:10.1042/bsr20190880

Ramkumar B, Dharaskar SP, Mounika G, Paithankar K, Sreedhar AS. 2020. Mitochondrial chaperone, TRAP1 as a potential pharmacological target to combat cancer metabolism. Mitochondrion 50:42–50. doi:10.1016/j.mito.2019.09.011

Roca-Portoles A, Rodriguez-Blanco G, Sumpton D, Cloix C, Mullin M, Mackay GM, O’Neill K, Lemgruber L, Luo X, Tait SWG. 2020. Venetoclax causes metabolic reprogramming independent of BCL-2 inhibition. Cell Death Dis 11. doi:10.1038/s41419-020-02867-2

Roth K, Weiner MW. 1991. Determination of cytosolic ADP and AMP concentrations and the free energy of ATP hydrolysis in human muscle and brain tissues with 31P NMR spectroscopy. Magn Reson Med. doi:10.1002/mrm.1910220258

Rücker FG, Sander S, Döhner K, Döhner H, Pollack JR, Bullinger L. 2006. Molecular profiling reveals myeloid leukemia cell lines to be faithful model systems characterized by distinct genomic aberrations. Leukemia. doi:10.1038/sj.leu.2404235

Ryan TE, Yamaguchi DJ, Schmidt CA, Zeczycki TN, Shaikh SR, Brophy P, Green TD, Tarpey MD, Karnekar R, Goldberg EJ, Sparagna GC, Torres MJ, Annex BH, Neufer PD, Spangenburg EE, McClung JM. 2018. Extensive skeletal muscle cell mitochondriopathy distinguishes critical limb ischemia patients from claudicants. JCI insight. doi:10.1172/jci.insight.123235

Ryu I, Ryu MJ, Han J, Kim SJ, Lee MJ, Ju X, Yoo BH, Lee YL, Jang Y, Song IC, Chung W, Oh E, Heo JY, Kweon GR. 2018. L-Deprenyl exerts cytotoxicity towards acute myeloid leukemia through inhibition of mitochondrial respiration. Oncol Rep 40:3869–3878. doi:10.3892/or.2018.6753

Sanchez-Martin C, Menon D, Moroni E, Ferraro M, Masgras I, Elsey J, Arbiser JL, Colombo G, Rasola A. 2020a. Honokiol Bis-Dichloroacetate Is a Selective Allosteric Inhibitor of the Mitochondrial Chaperone TRAP1. Antioxid Redox Signal 00:1–13. doi:10.1089/ars.2019.7972

Sanchez-Martin C, Moroni E, Ferraro M, Laquatra C, Cannino G, Masgras I, Negro A, Quadrelli P, Rasola A, Colombo G. 2020b. Rational Design of Allosteric and Selective Inhibitors of the Molecular Chaperone TRAP1. Cell Rep 31:107531. doi:10.1016/j.celrep.2020.107531

Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, Preibisch S, Rueden C, Saalfeld S, Schmid B, Tinevez JY, White DJ, Hartenstein V, Eliceiri K, Tomancak P, Cardona A. 2012. Fiji: An open-source platform for biological-image analysis. Nat Methods. doi:10.1038/nmeth.2019

Sciacovelli M, Guzzo G, Morello V, Frezza C, Zheng L, Nannini N, Calabrese F, Laudiero G, Esposito F, Landriscina M, Defilippi P, Bernardi P, Rasola A. 2013. The mitochondrial chaperone TRAP1 promotes neoplastic growth by inhibiting succinate dehydrogenase. Cell Metab 17:988–999. doi:10.1016/j.cmet.2013.04.019

Singh RP, Jeyaraju D V., Voisin V, Hurren R, Xu C, Hawley JR, Barghout SH, Khan DH, Gronda M, Wang X, Jitkova Y, Sharon D, Liyanagae S, MacLean N, Seneviratene AK, Mirali S, Borenstein A, Thomas GE, Soriano J, Orouji E, Minden MD, Arruda A, Chan SM, Bader GD, Lupien M, Schimmer AD. 2020. Disrupting Mitochondrial Copper Distribution Inhibits Leukemic Stem Cell Self-Renewal. Cell Stem Cell 26:926-937.e10. doi:10.1016/j.stem.2020.04.010

Škrtić M, Sriskanthadevan S, Jhas B, Gebbia M, Wang X, Wang Z, Hurren R, Jitkova Y, Gronda M, Maclean N, Lai CK, Eberhard Y, Bartoszko J, Spagnuolo P, Rutledge AC, Datti A, Ketela T, Moffat J, Robinson BH, Cameron JH, Wrana J, Eaves CJ, Minden MD, Wang JCY, Dick JE, Humphries K, Nislow C, Giaever G, Schimmer AD. 2011. Inhibition of Mitochondrial Translation as a Therapeutic Strategy for Human Acute Myeloid Leukemia. Cancer Cell 20:674–688. doi:10.1016/j.ccr.2011.10.015

Sriskanthadevan S, Jeyaraju D V., Chung TE, Prabha S, Xu W, Skrtic M, Jhas B, Hurren R, Gronda M, Wang X, Jitkova Y, Sukhai MA, Lin FH, Maclean N, Laister R, Goard CA, Mullen PJ, Xie S, Penn LZ, Rogers IM, Dick JE, Minden MD, Schimmer AD. 2015. AML cells have low spare reserve capacity in their respiratory chain that renders them susceptible to oxidative metabolic stress. Blood 125:2120–2130. doi:10.1182/blood-2014-08-594408

Suganuma K, Miwa H, Imai N, Shikami M, Gotou M, Goto M, Mizuno S, Takahashi M, Yamamoto H, Hiramatsu A, Wakabayashi M, Watarai M, Hanamura I, Imamura A, Mihara H, Nitta M. 2010. Energy metabolism of leukemia cells: Glycolysis versus oxidative phosphorylation. Leuk Lymphoma 51:2112–2119. doi:10.3109/10428194.2010.512966

Tewari D, Ahmed T, Chirasani VR, Singh PK, Maji SK, Senapati S, Bera AK. 2015. Modulation of the mitochondrial voltage dependent anion channel (VDAC) by curcumin. Biochim Biophys Acta - Biomembr 1848:151–158. doi:10.1016/j.bbamem.2014.10.014

Vardhana SA, Hwee MA, Berisa M, Wells DK, Yost KE, King B, Smith M, Herrera PS, Chang HY, Satpathy AT, van den Brink MRM, Cross JR, Thompson CB. 2020. Impaired mitochondrial oxidative phosphorylation limits the self-renewal of T cells exposed to persistent antigen. Nat Immunol. doi:10.1038/s41590-020-0725-2

Veech RL, Kashiwaya Y, Gates DN, King MT, Clarke K. 2002. The energetics of ion distribution: The origin of the resting electric potential of cells. IUBMB Life 54:241–252. doi:10.1080/15216540215678

Willis WT, Jackman MR, Messer JI, Kuzmiak-Glancy S, Glancy B. 2016. A simple hydraulic analog model of oxidative phosphorylation. Med Sci Sports Exerc. doi:10.1249/MSS.0000000000000884

Xiang W, Cheong JK, Ang SH, Teo B, Xu P, Asari K, Sun WT, Than H, Bunte RM, Virshup DM, Chuah C. 2015. Pyrvinium selectively targets blast phase-chronic myeloid leukemia through inhibition of mitochondrial respiration. Oncotarget. doi:10.18632/oncotarget.5615

Xie Q, Wondergem R, Shen Y, Cavey G, Ke J, Thompson R, Bradley R, Daugherty-Holtrop J, Xu Y, Chen E, Omar H, Rosen N, Wenkert D, Xu HE, Vande Woud GF. 2011. Benzoquinone ansamycin 17AAG binds to mitochondrial voltage-dependent anion channel and inhibits cell invasion. Proc Natl Acad Sci U S A 108:4105–4110. doi:10.1073/pnas.1015181108

Yoshida S, Tsutsumi S, Muhlebach G, Sourbier C, Lee MJ, Lee S, Vartholomaiou E, Tatokoro M, Beebe K, Miyajima N, Mohney RP, Chen Y, Hasumi H, Xu W, Fukushima H, Nakamura K, Koga F, Kihara K, Trepel J, Picard D, Neckers L. 2013. Molecular chaperone TRAP1 regulates a metabolic switch between mitochondrial respiration and aerobic glycolysis. Proc Natl Acad Sci U S A 110. doi:10.1073/pnas.1220659110

There is NO Competing Interest.

SupplementaryTable1.xlsx
Supplementary Table 1. Mitochondrial proteome of AML cell lines, relative to PBMC. (A) Exported results from PDv2.2. (B) Analyzed master protein expression by group.
RevisedSuppFig1RelatedtoFig1.tif
Supplementary Figure 1. Morphology of leukemia and respiratory flux stimulated by BAM15, a mitochondrial uncoupler. (Related to Figure 1.) (A) Comparison of cell size of leukemia cells and PBMC. Respiratory flux driven by BAM15 (B15), a mitochondrial uncoupler (B) and observed Km (C). (D) Cellular focal planes used to obtain confocal images. (E) Extracellular acidification rate (ECAR) in intact cell. (F) Relationship between ECAR and OCR in intact cells under basal conditions. Data are presented as mean ±SEM and analyzed by one-way ANOVA (A, C), two-way ANOVA (B), or unpaired t-tests (E). n= 5-7 independent experiments. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.
RevisedSuppFig2RelatedtoFig2.tif
Supplementary Figure 2. Respiratory profile of healthy bone marrow mononuclear cells and primary human myoblasts. (Related to Figure 2.) (A-E) Permeabilized cells were used for all experiments. ETS capacity (A) and OXPHOS kinetic (B) protocols were performed in permeabilized BMHealthy. Data depict results from each replicate across samples from three independent donors. ETS capacity (C) and OXPHOS kinetic (D) protocols were performed in permeabilized primary human myoblasts; n=4 independent experiments. (E) OXPHOS kinetics were performed with PCr and creatine kinase but in the absence of ATP in permeabilized MV-4-11 cells; n=6 independent experiments. Data are presented as mean ±SEM and analyzed by two-way ANOVA. *p<0.05
RevisedSuppFig3RelatedtoFig4.tif
Supplementary Figure 3. Heatmap analysis depicting abundance of subunits and assembly factors that comprise the ETS complexes. (Related to Figure 4.) Heatmap displaying relative protein abundance of the individual subunits and assembly factors belonging to (A) complex I (B) complex II (C) Complex III and (D) Complex IV.
RevisedSuppFig4RelatedtoFig5.tif
Supplementary Figure 4. ETS flux in the presence of ΔGATP is restored by ANT inhibition ANT. (Related to Figure 5.) (A) OXPHOS kinetics in permeabilized HL-60 cells in the presence of DMSO (vehicle), bongkrekic acid (20µM; ANT inhibitor) or gamitrinib (1µM; TRAP1 inhibitor with mitochondria-targeted moiety); n=3 independent experiments. (B) Mitochondrial membrane potential (ΔΨ) in HL-60 isolated mitochondria across a ΔGATP span, followed by CV inhibition with oligomycin; n=3 independent experiments.. Data are presented as mean ±SEM and analyzed by one-way ANOVA. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.
RevisedSuppFig5RelatedtoFig6.tif
Supplementary Figure 5. Effects of 17-AAG on OXPHOS kinetics. (Related to Figure 6.) (A) Comparison of FCCP-stimulated respiration with the addition of 17-AAG (15µM) in permeabilized MV-4-11 cells; n=3 independent experiments. (B-D) OXPHOS kinetics in permeabilized HL-60 cells in the presence of DMSO or 17-AAG (15µM); n=3 independent experiments. (E-F) OXPHOS kinetics in permeabilized MV-4-11 or KG-1 cells in the presence of DMSO or 17-AAG (15µM). Cell were energized with either CI (Pyr/M) or CII linked substrates (S/R); n=3 independent experiments. (G) Schematic of changes in ATP, ADP, PCR and CR concentrations across a range of ΔGATP. (H) Inhibition of respiration by antimycin A (ANT) across a range of ΔGATP in permeabilized HL-60 cells; n=3 independent experiments. (I-J) Comparison of respiratory flux inhibition within permeabilized AML cells across a range of ΔGATP induced by functional TRAP1. Respiration was stimulated by the addition of FCCP (1µM), followed by PCR titration to manipulate ΔGATP; n=3 independent experiments. (K) ETS capacity assay in permeabilized MV-4-11 cells infected with lentivirus encoding shRNA targeted to TRAP1 (TRAP1 KD) or scrambled shRNA (Control); n=3 independent experiments. (L) Comparison of OXPHOS kinetics in the presence of DMSO, 17-AAG (15µM), or gamitrinib (1µM) in Control and TRAP1 KD cells. Data depicted as a percentage of basal respiration based on oxygen consumption rates obtained prior to digitonin permeabilization; n=3 independent experiments. Data are presented as mean ±SEM and analyzed by two-way ANOVA (A, K, L), paired t-tests (B-J). *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.
RevisedSuppFig6RelatedtoFig7.tif
Supplementary Figure 6. Effects of 17-AAG on OXPHOS kinetics and cell viability in PBMC and healthy bone marrow mononuclear cells. (Related to Figure 7.) (A) Comparison of OXPHOS kinetics in the presence of DMSO or 17-AAG (15µM) in permeabilized PBMC from healthy donors; n=5 independent experiments. (B) Comparison of OXPHOS kinetics in the presence of DMSO or 17-AAG (15µM) in permeabilized BMHealthy. Graph to the right depicts JH+OXPHOS depicted as a fold change from DMSO. Data depicted as a percentage of basal respiration based on oxygen consumption rates obtained in intact cells; n=3 independent cell experiments. (C) Cell viability in PBMC from healthy donors cultured for 24 hours in the presence of vehicle (DMSO), 17-AAG (15µM), or gamitrinib (1µM) plus increasing concentrations of Ara-C. Data depicted as viability based on the percentage of vehicle using the propidium iodide assay; n=3-4 independent experiments. (D) Effect of cytochrome C addition on JH+OXPHOS. Data expresses as fold change from rates obtained prior to cytochrome C addition; n=3 independent experiments. Data are presented as mean ±SEM and analyzed by two-way ANOVA.

Download PDF

Version 2

posted

You are reading this latest preprint version

Intrinsic OXPHOS limitations underlie cellular bioenergetics in leukemia.

Status:

Version 2

Abstract

Figures

Introduction

Results

Discussion

Methods

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 2