Decision letter: Mycobacterium tuberculosis induces decelerated bioenergetic metabolism in human macrophages

Abstract

Article Figures and data Abstract Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract How Mycobacterium tuberculosis (Mtb) rewires macrophage energy metabolism to facilitate survival is poorly characterized. Here, we used extracellular flux analysis to simultaneously measure the rates of glycolysis and respiration in real time. Mtb infection induced a quiescent energy phenotype in human monocyte-derived macrophages and decelerated flux through glycolysis and the TCA cycle. In contrast, infection with the vaccine strain, M. bovis BCG, or dead Mtb induced glycolytic phenotypes with greater flux. Furthermore, Mtb reduced the mitochondrial dependency on glucose and increased the mitochondrial dependency on fatty acids, shifting this dependency from endogenous fatty acids in uninfected cells to exogenous fatty acids in infected macrophages. We demonstrate how quantifiable bioenergetic parameters of the host can be used to accurately measure and track disease, which will enable rapid quantifiable assessment of drug and vaccine efficacy. Our findings uncover new paradigms for understanding the bioenergetic basis of host metabolic reprogramming by Mtb. https://doi.org/10.7554/eLife.39169.001 Introduction Mechanisms underlying the pathogenesis induced by Mycobacterium tuberculosis (Mtb), the etiological agent of tuberculosis (TB), are poorly understood, and increasing evidence suggests that Mtb subverts the host’s immune response to establish a persistent infection (Cambier et al., 2014; Hmama et al., 2015; Józefowski et al., 2008). Crucial to the success of the immune system to control microbial infection is the metabolic plasticity of immune cells to activate antimicrobial mechanisms in macrophages and activate T cells in response to microbial invasion. Precise coordination between diverse metabolic pathways underlies this plasticity (Ganeshan and Chawla, 2014; Loftus and Finlay, 2016; Mathis and Shoelson, 2011), which is disrupted by pathogenic bacteria. Hence, host-directed therapies are increasingly considered for adjunctive treatment of tuberculosis (Guler and Brombacher, 2015; Mahon and Hafner, 2015; Wallis and Hafner, 2015). Studies suggest that Mtb pathogenicity is reinforced with participation of metabolic pathways from the host, including evidence suggesting that Mtb adaptation to the host environment requires catabolism of host-derived lipids (Daniel et al., 2011; Muñoz-Elías and McKinney, 2005; Pandey and Sassetti, 2008; Rohde et al., 2012; Lee et al., 2013). This is assumed to be induced through Mtb regulating metabolic thresholds of the host macrophage (Mehrotra et al., 2014). Recent studies suggested that there is a shift from oxidative phosphorylation towards glycolysis in macrophages infected with an avirulent strain (H37Ra) or dead γ-irradiated Mtb (Gleeson et al., 2016), and in Mtb (H37Rv)-infected mouse lungs using transcriptomic profiling and confocal imaging (Shi et al., 2015). Lachmandas et al. (Lachmandas et al., 2016) demonstrated that the switch to aerobic glycolysis observed in human peripheral blood mononuclear cells stimulated with dead Mtb lysate is TLR2-dependent, and is mediated in part through the AKT-mTOR (mammalian target of rapamycin) pathway. While this evidence supports the conclusion that dead Mtb reprograms host energy metabolism, the actual underlying mechanisms with live virulent Mtb infection enabling it to persist in humans remain elusive. Furthermore, the metabolic health of the Mtb-infected cell is poorly defined as there is a lack of knowledge on exactly what metabolic health comprises, and what should be measured. Thus, development of a technological advance to address these gaps in our knowledge is expected to uncover the fundamental role of host energy metabolism in allowing Mtb to persist for decades without causing disease. Aberrant cellular bioenergetics have been associated with, and are often the cause of, diseases such as diabetes, cancer, neurodegeneration, and cardiac disease. The dysfunctional energy metabolism in these diseases has been successfully investigated using extracellular flux (XF) analysis (Devarajan et al., 2011; Hill et al., 2009; Salabei et al., 2016; Wu et al., 2007; Lee et al., 2017; Cronin-Furman et al., 2013). XF analysis monitors the rate of oxygen consumed by cells (oxygen consumption rate, OCR) and the release of protons from the cells into the extracellular medium (extracellular acidification rate, ECAR) non-invasively in real time (Figure 1A). Measurements of cellular respiration and acidification form the foundation of our understanding of bioenergetics because cells use two main pathways to produce ATP, namely oxidative phosphorylation (OXPHOS) and glycolysis. This technology is largely unexplored in the field of bacterial pathogenesis, with a few studies focused on Helicobacter pylori infections (Hammond et al., 2015; Saha et al., 2010), but studies on live virulent Mtb pathogenesis are lacking. Figure 1 Download asset Open asset Schematic illustration of cellular metabolism pathways and XF assays used to analyze metabolic pathways. (A) The XF measures oxygen consumption rate (OCR) of the cell, which is mostly consumed at complex IV of the electron transport chain (ETC) in the mitochondria, and extracellular acidification rate (ECAR), which is generated from lactic acid produced from pyruvate, the end-product of glycolysis, and carbonic acid produced from CO2 released during the TCA cycle. Assays performed on the XF include: (B) mitochondrial respiration test, (C) extracellular acidification test, (D) glycolytic rate assay, (E) mitochondrial fuel test, (F) fatty acid oxidation assay and (G) real-time ATP rate assay. Oligo, oligomycin; FCCP, cyanide-4-[trifluoromethoxy]phenylhydrazone; AntiA and Rot, antimycin A and rotenone; 2-DG, 2-Deoxyglucose; G-6-P, glucose-6-phosphate; G-3-P, glyceraldehyde-3-phosphate; PEP, phosphoenolpyruvate; α-KG, α-ketoglutarate; OAA, oxaloacetate. https://doi.org/10.7554/eLife.39169.002 In this study, we used extracellular flux analysis to explore the modulation of the energy metabolism of differentiated THP-1 macrophages and human monocyte derived macrophages (hMDM) infected with live virulent Mtb, the slow-growing non-pathogenic vaccine strain, M. bovis BCG (BCG) and dead-Mtb. We examined how mycobacterial burden affects OXPHOS and the glycolysis of macrophages, we investigated ATP production by glycolysis and OXPHOS during mycobacterial infection, and assessed the capacity, dependency and flexibility of mitochondria on glucose, glutamine or fatty acids during infection. Lastly, we confirmed our findings with [U-13C]glucose stable isotope tracing experiments. By adapting a real-time, non-invasive bioenergetic platform to study the bioenergetics of the Mtb-infected host cell, we have generated new knowledge that may contribute towards a better understanding of Mtb persistence and development of novel approaches for host-directed therapeutic interventions. Results Mtb infection depresses the rate of mitochondrial respiration in macrophages Mitochondria are regarded as the energy factory of the cell that generates ATP through OXPHOS. It is reasonable to expect that on infection with Mtb, host energy metabolism is rewired, which has implications for understanding how Mtb causes disease. To examine the effect of mycobacterial infection on host OXPHOS, we made use of an extracellular flux analyzer (XF, Agilent Seahorse, Santa Clara, CA) and the mitochondrial respiration test (Nicholls et al., 2010) to determine key respiratory parameters in mammalian cells. These include basal respiration (Basal Resp), which is the initial OCR measured before addition of any inhibitors minus the non-mitochondrial respiration; ATP-linked respiration (ATP-linked OCR), which is determined after addition of oligomycin that inhibits ATP synthase (Complex V) and thus approximates the respiration required to drive ATP synthesis; proton leak, which is the difference between the ATP-linked OCR and the non-mitochondrial respiration; maximal respiration (Max Resp), which is induced after addition of carbonyl cyanide-4-(trifluoromethoxy)phenylhydrazone (FCCP) that uncouples ATP synthesis from electron transport; spare respiratory capacity (SRC), which is the difference between maximal respiration and basal respiration; and non-mitochondrial respiration (Non-Mito Resp), which is the OCR after addition of rotenone, a complex I inhibitor, and antimycin A, a complex III inhibitor (Figure 1B). SRC is an important parameter that reflects the ability of the cell to increase respiration to increase the supply of ATP in scenarios when the energy demand exceeds supply under conditions of stress or increased work load. Several lines of evidence preclude any contribution of the infecting Mtb to the measured OCR of infected macrophages. Firstly, we have previously demonstrated that 106 Mtb consumed 10–20 pmoles O2/min (Lamprecht et al., 2016) in contrast to 100–200 pmoles O2/min consumed by 80 000 to 100 000 macrophages under the basal conditions measured in this study. Thus, at a multiplicity of infection (MOI) of 1, 105 Mtb would result in a negligible contribution (<1 pmoles O2/min) to the OCR of the uninfected macrophages. Secondly, this basal OCR of Mtb was measured in media favourable for Mtb respiration and growth, whereas the intracellular macrophage environment is not conducive to ‘healthy’ Mtb respiration. Thirdly, Mtb infection at MOI of 1 and 2.5 progressively decreases the basal respiration (OCR) of both THP-1 macrophages and hMDMs (Figure 2—figure supplement 1) relative to that of uninfected macrophages. Should Mtb contribute to basal respiration (OCR), we should see an increase in OCR with increasing number of Mtb infecting the macrophages. Fourthly, the growth media of the infected macrophages after the time of infection and treatment was removed and the cells were washed in the XF assay medium before the XF assay, to remove most extracellular mycobacteria. When the washes of the macrophages were plated out on 7H11 agar plates, less than 200 CFU were obtained per well from the washes of the infected hMDMs (MOI 5), and less than 100 CFU per well from the infected THP-1 cells (MOI 5). To demonstrate that these extracellular mycobacteria do not contribute to the OCR readings of the infected macrophages, the final wash was transferred to a separate XF cell culture microplate and a separate mitochondrial respiration assay was performed on any extracellular bacteria present in the washes. The OCR and ECAR readings obtained were below 0 pmol/min and at 0 mpH/min, respectively, and the extracellular bacteria did not respond to the sequential injections of oligomycin, FCCP and rotenone and antimycin A (Figure 2—figure supplement 2A–D). Thus, the infecting mycobacteria do not contribute to the measured OCR of the infected macrophages under our conditions. It is not possible to ensure that every cell will be infected in in vitro infections, thus the percentage of uninfected cells will contribute to the resulting XF profiles. We infected the macrophages with Mtb-green fluorescent protein reporter strain (Mtb-GFP) and used bright-field and fluorescence microscopy to determine the percentage of cells that were infected. We found that there was an increase in the percentage of infected cells with an increase in MOI of both the THP-1 cells and the hMDMs (Figure 2—figure supplement 2E–G). Although the percentage of uninfected cells will contribute to the readout of the XF profiles, previous studies have demonstrated that lipids shed by intracellular mycobacteria, such as TDM and PIM2, spread via the endocytic network throughout the macrophage, and via exocytic vesicles to neighboring uninfected cells (Beatty et al., 2000; Xu et al., 1994) and can elicit the production of proinflammatory cytokines (Rhoades et al., 2003). Consequently, the bioenergetic metabolism of the ‘by-stander’ uninfected cells will also be modulated. Thus, the XF profiles are providing collective data of a mixed population of macrophages. Overall, our data demonstrated that strain pathogenicity and burden have distinct effects on virtually all respiratory parameters. Figure 2A and B shows that infection of THP-1 macrophages with Mtb or BCG significantly decreased the respiratory parameters: Basal Resp, ATP-linked OCR, proton leak and Max Resp (and SRC in the case of Mtb), and increased Non-Mito Resp. Similar patterns were observed at lower MOIs of 1 and 2.5, but to lesser degrees (Figure 2—figure supplement 1A–D). Infection with the dead Mtb only significantly reduced the respiratory parameters at MOIs of 2.5 and 5 (Figure 2—figure supplement 1C–D and Figure 2A–B). Figure 2 with 3 supplements see all Download asset Open asset Respiratory profiles and parameters of infected macrophages are dependent on cell type, mycobacterial strain and MOI. Respiratory profiles (OCR) and respiratory parameters of (A–B) PMA differentiated THP-1 macrophages, and (C–D) hMDMs infected with Mtb, BCG and ∆Dead Mtb (heat-killed Mtb) at MOIs of 5 for 24 h. Refer to Figure 2—figure supplement 1 for profiles of lower MOIs. After obtaining basal respiration, cells were subjected to oligomycin (Oligo, 1.5 µM), which inhibits ATP synthase and demonstrates the mitochondrial ATP-linked OCR, followed by FCCP (cyanide-4-[trifluoromethoxy]phenylhydrazone), which uncouples mitochondrial respiration and maximizes OCR (1 µM for THP-1 and hMDMs), and finally antimycin A and rotenone (AntiA and Rot), which inhibit complex III and I in the ETC, respectively, and shut down respiration (0.5 µM of each for THP-1; 2.5 µM of each for hMDMs). Profiles and respiratory parameters are representative of three independent experiments. Data shown are the mean ± SD (n = 6 biological replicates). Student’s t test relative to uninfected cells; #, p < 0.0001; χ, p < 0.0005; ϕ, p < 0.001; *p < 0.005; +, p < 0.05. https://doi.org/10.7554/eLife.39169.003 Mtb infection of hMDMs dramatically reduced the respiratory parameters of the macrophage, while significantly increasing Non-Mito Resp (Figure 2C–D). Smaller reductions in the respiratory parameters were observed at lower Mtb MOIs of 1 and 2.5 with an increase in Non-Mito Resp (Figure 2—figure supplement 1E–H). Notably, contrary to Mtb, BCG infection increased the Max Resp and SRC of the hMDMs at all MOIs investigated. At a MOI of 5, BCG decreased the Basal Resp, ATP-linked OCR and proton leak, while increasing the Non-Mito Resp (Figure 2C–D). At lower MOIs, BCG had little effect on the other respiratory parameters (Figure 2—figure supplement 1E–H). Dead Mtb did not affect the respiratory parameters of the hMDMs at MOIs of 1 and 5, but a MOI of 2.5 increased the Max Resp and SRC of the macrophages as in the BCG infection (Figure 2C–D and Figure 2—figure supplement 1E–H). In Mtb-infected macrophages, the oxidative burst (via NADPH oxidase, which consumes O2) induced by a combination of infection, uncoupling with FCCP and inhibition of the ETC after treatment with antimycin A and rotenone increases the OCR above the initial OCR before treatment with oligomycin (Figure 2A and C). This results in the calculated basal respiration having a negative value (Figure 2B and D). As we have used standard equations to calculate the basal respiration (Nicholls et al., 2010), we propose that when the non-mitochondrial respiration is greater than the initial OCR readings before the addition of any inhibitors, an additional mitochondrial respiration assay should be performed without the addition of the FCCP to determine the non-mitochondrial respiration, to obtain the values of basal respiration and proton leak. Using this format, the true (positive) values for basal respiration and proton leak are obtained (Figure 2—figure supplement 3). The basal respiration of both Mtb and BCG infections at a MOI of 2.5 and 5 were less than that of uninfected THP-1 cells, and the proton leak of BCG was less than that of the uninfected THP-1 cells (Figure 2—figure supplement 3A–D). The non-mitochondrial respiration was increased in both of these infections at a MOI of 5. Similar patterns were observed with the Mtb- and BCG-infected hMDMs at a MOI of 5 (Figure 2—figure supplement 3E,F). In sum, there are profound contrasting respiratory differences among Mtb, BCG and dead Mtb infection of the macrophages. In particular, Max Resp, SRC and Non-Mito Resp are strongly influenced by the mycobacterial strain, burden and macrophage type. Mtb infection of hMDMs decreases Max Resp and SRC in contrast to BCG increasing Max Resp and SRC, and both strains increase Non-Mito Resp. SRC has consequences on how the macrophage responds to environmental stresses such as nutrient availability, redox state and changes in pH. Thus, an increase in the SRC of hMDMs following infection with potential vaccine candidates may aid identification of promising candidates. Strikingly, dead Mtb infection still alters the bioenergetic metabolism of the macrophage, in particular that of the THP-1 cells. This has implications for pharmacological killing of Mtb, as killing intracellular Mtb will not fully restore the macrophage’s bioenergetic metabolism to that of the uninfected macrophage. However, pharmacological killing will improve the bioenergetic profile of the live Mtb-infected macrophages, in particular, the ATP-linked Resp and the Non-Mito Resp. Therefore, improvements in these parameters of the infected macrophages can be used as indicators of effective pharmacological killing of Mtb during screening of potential anti-TB drug leads in Mtb-infected macrophages. Mtb infection reduces the extracellular acidification rate of the macrophage Glycolysis is the second pathway used to supply ATP for the energy requirements of the cell, in addition to anabolic intermediates. Here, we measured the glycolytic parameters of mycobacterial infected cells, including the glucose metabolism extracellular acidification rate after addition of glucose; the maximal glycolytic capacity (Gly capacity) following inhibition of OXPHOS ATP synthesis with oligomycin; and the non-glycolytic extracellular acidification measured after treatment of the mycobacterial infected cells with 2-deoxyglucose (2-DG), an inhibitor of hexokinase II, which catalyzes the first step of glycolysis (Figure 1C). The difference between the extracellular acidification rate of glucose metabolism rate and the maximal glycolytic capacity of the cells defines the spare glycolytic reserve. Mtb strikingly decreased the glycolytic parameters of both types of macrophages after 24 h (Figure 3). In THP-1 cells, all the mycobacterial strains reduced the glycolytic parameters at MOIs of 5 (Figure 3A–B) and 2.5 (Figure 3—figure supplement 1C,D), with dead Mtb having the least effects. At a MOI of 1, Mtb decreased the glycolytic parameters, BCG increased the glycolytic parameters and dead Mtb had no effect (Figure 3—figure supplement 1A–B). Figure 3 with 1 supplement see all Download asset Open asset Extracellular acidification profiles and glycolytic parameters of THP-1 and hMDMs are affected by macrophage type, mycobacterial strain and MOI. ECAR profiles and glycolytic parameters of (A–B) PMA differentiated THP-1 macrophages, and (C–D) hMDMs infected with Mtb, BCG and dead Mtb at MOI of 5 for 24 h. Refer to Figure 3—figure supplement 1 for profiles at lower MOIs. After obtaining non-glycolytic acidification, glucose (Glc, 10 mM) was added to the cells, followed by oligomycin (1.5 µM), which inhibits ATP synthase inducing maximal glycolysis to compensate for loss of mitochondrial generated ATP, and finally 2-deoxyglucose (2-DG, 100 mM) to inhibit glycolysis and demonstrate that the prior acidification was generated by glycolysis. Profiles and glycolytic parameters are representative of three independent experiments. Data shown are the mean ± SD (n = 6 biological replicates). Student’s t test relative to uninfected cells; #, p < 0.0001; χ, p < 0.0005; ϕ, p < 0.001; *p < 0.005; +, p < 0.05. https://doi.org/10.7554/eLife.39169.007 In hMDMs, Mtb at a MOI of 2.5 had little effect and at a MOI of 1 increased glucose metabolism extracellular acidification. (Figure 3—figure supplement 1E–H). Contrary to THP-1 cells, BCG and dead Mtb infection of hMDMs increased glucose metabolism acidification and the glycolytic capacity at all MOIs investigated. Increases in the non-glycolytic acidification were observed in the BCG and dead Mtb infections, probably as a result of the carbonic acid produced from CO2 generated by the tricarboxylic acid cycle (TCA). These results underscore the different modulations of dead and live Mtb on macrophage bioenergetics. In sum, marked glycolytic differences were observed between the virulent and non-virulent infections, with Mtb infection significantly reducing glucose metabolism extracellular acidification in the macrophages. BCG and dead-Mtb infections induced contrasting effects dependent on macrophage cell type, with a decrease in THP-1 glucose metabolism extracellular acidification versus an increase in hMDM extracellular acidification. Mtb infection shifts the bioenergetic phenotype of the macrophage towards quiescence To determine how mycobacterial infection shifts the energy metabolism of the macrophage, basal OCR was plotted as a function of ECAR to form a bioenergetic phenogram that depicts the overall energy phenotypes of the macrophages. The energy phenotype of cells can be described as more aerobic, energetic, glycolytic or quiescent (Figure 4). Figure 4 Download asset Open asset Phenograms demonstrate that increasing MOI of Mtb shifts macrophages towards quiescent energy phenotypes. Basal OCR and ECAR measurements from the respiratory assay (Figure 2) before addition of oligomycin were plotted to generate phenograms of (A–C) PMA-differentiated THP-1 cells and (D–F) hMDMs infected with Mtb, BCG and ∆Dead Mtb at MOIs of 1, 2.5 and 5. Data are representative of three independent experiments. Data shown are the mean ± SD (n = 6 biological replicates). Student’s t test relative to uninfected cells; #, p < 0.0001; χ, p < 0.0005; ϕ, p < 0.001; *p < 0.005; +, p < 0.05. https://doi.org/10.7554/eLife.39169.009 In THP-1 cells and hMDMs, infection with Mtb exhibited the most pronounced shift from an Energetic phenotype towards that of a Quiescent phenotype with increasing MOI (Figure 4A and D). In contrast, BCG and dead Mtb infections of THP-1 cells (MOIs 2.5 and 5) induced much smaller shifts towards quiescence (Figure 4B and C); whereas in hMDMs, only BCG infection at a MOI of 5 engendered a small shift towards quiescence. Dead Mtb did not affect the OCR of the hMDMs but decreased the ECAR at lower MOIs (Figure 4F), again underscoring the differences between live and dead Mtb. In sum, our data clearly demonstrate that Mtb infection shifts the energy phenotypes of human macrophages towards a metabolic quiescent state. Mtb decreases the glycolytic proton efflux rate of macrophages Previous studies using Mtb lysates (Lachmandas et al., 2016), irradiated killed Mtb and lactate measurements (Gleeson et al., 2016), or transcription profiling (Shi et al., 2015) led to the supposition that Mtb induces aerobic glycolysis for ATP generation, known as the Warburg effect. In XF analysis, bulk acidification of the extracellular medium, as measured by ECAR, is not specific for glycolysis as the mitochondrial TCA produces CO2 that is partially hydrated in the extracellular medium and contributes to the acidification of the extracellular medium (Mookerjee et al., 2015a). In the glycolytic rate assay (Mookerjee and Brand, 2015b), inhibition of mitochondrial respiration after addition of rotenone and antimycin A enables calculation of the contribution of the mitochondrial respiration to the rate of proton efflux (Figure 5A). Subtraction of the mitochondrial proton efflux rate from the total proton efflux rate provides the glycolytic proton efflux rate (glycoPER) (Figure 5—figure supplement 1A–D). To confirm the specificity, 2-DG is added to inhibit glycolytic acidification (Figure 5A). Compensatory glycolysis refers to the ability of the cell to increase glycolysis after OXPHOS has been inhibited with rotenone and antimycin A. Figure 5 with 1 supplement see all Download asset Open asset Mtb infection reduces the glycolytic proton efflux rate of macrophages. (A) Extracellular acidification can be caused by both lactate and protons produced from pyruvate, the final product of glycolysis, in addition to carbonic acid generated from CO2 from pyruvate oxidation in the mitochondria. Calculating proton efflux rate (PER) enables the glycolytic PER to be elucidated separately from the mitochondrial PER (Figure 5—figure supplement 1A–D). (B–E) Basal and compensatory glycolytic PER of THP-1 cells (B–C) and hMDMs (D–E) infected with Mtb, BCG and ∆Dead Mtb at MOI of 5 for 18 h. Refer to Figure 5—figure supplement 1E–L for profiles at lower MOIs. Following basal measurement of ECAR and OCR, to determine basal glycolytic PER, rotenone and antimycin A were added to determine compensatory PER. This was followed by addition of 2-DG to ensure that the PER observed was caused by glycolysis. Profiles and PER are representative of two independent experiments. Data shown are the mean ± SD (n = 6). Student’s t test relative to the uninfected cells; #, p < 0.0001; χ, p < 0.0005; ϕ, p < 0.001; *p < 0.005; +, p < 0.05. (F–G) Total rate of ATP production was calculated as the sum of glycolytic ATP rate formation (equivalent to glycoPER) and mitochondrial-derived ATP rate formation that was estimated from the ATP-linked OCR, assuming a P/O ratio of 2.79. Rate of ATP formation in (F) THP-1 cells and (G) hMDM cells infected with Mtb, BCG or ∆Dead Mtb at indicated MOI for 18 h. Refer to Figure 5—figure supplement 1M–N for % contribution of glycolysis and OXPHOS to the total rate of ATP production. Error bars are SD (n = 6 biological replicates). Student’s t test; #, p < 0.0001; χ, p < 0.0005; ϕ, p < 0.001; *p < 0.005; +, p < 0.05. https://doi.org/10.7554/eLife.39169.010 The proton efflux rates illustrated in Figure 5B–E are the calculated values of the glycolytic PER without the acidification contribution from mitochondrial respiration. Basal glycolysis and compensatory glycolysis of the macrophages, which is induced when mitochondrial ATP synthase is inhibited thereby forcing the cell to use glycolysis to meet the cell’s ATP requirements, are expressed as glycoPER (pmol/min/µg protein). An immediate observation is that Mtb significantly reduces the basal and compensatory glycolytic rates of THP-1 cells (MOI 2.5 and 5, Figure 5B–C, Figure 5—figure supplement 1E–H). In contrast, BCG and dead Mtb infections increased the basal glycolytic rates of THP-1 cells at all MOIs examined. Furthermore, compensatory glycolysis was increased in BCG-infected cells at all MOIs, and in dead Mtb infections at a MOI of 1. Again, noticeable differences were observed between the live and dead Mtb infections. In hMDMs, Mtb (MOI 5) decreased both the glycolytic rate and the compensatory glycolytic rate significantly (Figure 5D–E), but lower MOIs (1 and 2.5) did not affect the glycolytic rates of hMDMs (Figure 5—figure supplement 1I–L). BCG infection increased both the glycolytic rate and the compensatory glycolytic rates at all MOIs, whereas dead Mtb had no effect (Figure 5D–E, Figure 5—figure supplement 1I–L). In sum, profound differences were observed in the glycoPER of infections with virulent versus non-virulent mycobacterial strains. Noticeably, Mtb decreases the glycolytic PER in human macrophages at higher mycobacterial burdens, whereas BCG increases the glycolytic PER. However, dead Mtb infection increases the glycoPER in THP-1 cells and has no effect in hMDMs. When we compared the glycoPER data, which is considered a more accurate measurement of the glycolytic rate (Mookerjee and Brand, 2015b), with ECAR data of the infected macrophages, we found that the observed discordances were dependent on the infecting mycobacterial strain. To illustrate, the reduced basal and compensatory glycoPER of Mtb-infected THP-1 cells (Figure 5B–C, Figure 5—figure supplement 1E–H) resembled the observed decreased glycolytic ECAR and glycolytic capacity (Figure 3A–B, Figure 3—figure supplement 1A–D). In contrast, distinct differences were observed in the BCG infection of the THP-1 cells, where significant increases in both basal and compensatory glycoPER (Figure 5B–C, Figure 5—figure supplement 1E–H) were counter to significant reductions in the glucose metabolism ECAR and glycolytic capacity (Figure 3A–B, Figure 3—figure supplement 1C–D). These opposing trends were not observed in the BCG infection of hMDMs, rather increased basal and compensatory glycoPER (Figure 5D–E, Figure 5—figure supplement 1I–L) were reflected by increased glucose metabolism ECAR and glycolytic capacity (Figure 3C–D, Figure 3—figure supplement 1E–H). However, conflicting observations between glycoPER and ECAR were again observed with dead Mtb infection of THP-1 cells with increased basal glycoPER (Figure 5B–C, Figure 5—figure supplement 1E–H) compared to marginal or no reductions in glycolytic ECAR (Figure 3A–B, Figure 3—figure supplement 1A–D). Similarly, in hMDMs, the insignificant changes in basal and compensatory glycoPER in Mtb infection (MOIs 1 and 2.5) reflected the minimal chang