FX11 limits Mycobacterium tuberculosis growth and potentiates bactericidal activity of isoniazid through host-directed activity

ABSTRACT Lactate dehydrogenase A (LDHA) mediates interconversion of pyruvate and lactate, and increased lactate turnover is exhibited by malignant and infected immune cells. Hypoxic lung granuloma in Mycobacterium tuberculosis-infected animals present elevated levels of Ldha and lactate. Such alterations in the metabolic milieu could influence the outcome of host-M. tuberculosis interactions. Given the central role of LDHA for tumorigenicity, targeting lactate metabolism is a promising approach for cancer therapy. Here, we sought to determine the importance of LDHA for tuberculosis (TB) disease progression and its potential as a target for host-directed therapy. To this end, we orally administered FX11, a known small-molecule NADH-competitive LDHA inhibitor, to M. tuberculosis-infected C57BL/6J mice and Nos2−/− mice with hypoxic necrotizing lung TB lesions. FX11 did not inhibit M. tuberculosis growth in aerobic/hypoxic liquid culture, but modestly reduced the pulmonary bacterial burden in C57BL/6J mice. Intriguingly, FX11 administration limited M. tuberculosis replication and onset of necrotic lung lesions in Nos2−/− mice. In this model, isoniazid (INH) monotherapy has been known to exhibit biphasic killing kinetics owing to the probable selection of an INH-tolerant bacterial subpopulation. However, adjunct FX11 treatment corrected this adverse effect and resulted in sustained bactericidal activity of INH against M. tuberculosis. As a limitation, LDHA inhibition as an underlying cause of FX11-mediated effect could not be established as the on-target effect of FX11 in vivo was unconfirmed. Nevertheless, this proof-of-concept study encourages further investigation on the underlying mechanisms of LDHA inhibition and its significance in TB pathogenesis.

mice. Splenic CFU counts (means±SD) from two independent experiments (total n = 9-10) are shown. In contrast, CFU data ((means±SD) of INH-treated group are from a single experiment with a group size of 5. Italicized numerical value (in negative) represents reduction or value (in positive) represents a further increase in log10CFU in the specified group, when compared with the control group prior to drug treatment (i.e. day 56, indicated in dotted line). Pooled data from two independent experiments were analyzed using nonparametric Mann-Whitney test (data that did not pass the Shapiro-Wilk normality test).
Statistical significance as compared to the group prior to drug treatment, *p<0.05, **p<0.01, ****p<0.0001.  Disease Models & Mechanisms: doi:10.1242/dmm.041954: Supplementary information Extracellular flux analysis: methodology and statistics. Extracellular flux analysis. Seahorse Assay principle, design, and equations to calculate each of the parameters is schematically illustrated below using the representative data obtained in this study. A more detailed account of these assays can be accessed from the manufacturer's web resources or described in Cumming et al. 2018. (Cumming, B. M., Addicott, K. W., Adamson, J. H. andSteyn, A. J. (2018). Mycobacterium tuberculosis induces decelerated bioenergetic metabolism in human macrophages. eLife 7, e39169. https://doi.org/10.7554/eLife.39169). Glycolytic stress assay: Glucose is converted to pyruvate, and subsequently to lactate, results in proton generation and extrusion that acidify the extracellular medium (recorded as ECAR). This test was carried out to determine the impact of FX11 on ECAR values of BMDMs when sequentially treated with different glycolytic modulators.

Data acquisition: Oxygen consumption (OCR) and extracellular acidification rates (ECAR)
were measured using the Seahorse XF96 extracellular flux analyzer (Agilent, Santa Clara, CA).
Two different assays were performed using the XF96: mitochondrial respiration assay, and glycolytic stress assay. Acquired real-time data were into the XF Report Generators using the Wave Desktop 2.6 software for calculation of the parameters from the specific assays.

Statistical analysis to determine the effect of FX11 on bone marrow derived macrophages bioenergetics and glycolytic response.
Data acquisition: Oxygen consumption (OCR) and extracellular acidification rates (ECAR) were measured using the Seahorse XF96 extracellular flux analyzer (Agilent, Santa Clara, CA). Two different assays were performed using the XF96: mitochondrial respiration assay, and glycolytic stress assay. Acquired real-time data were into the XF Report Generators using the Wave Desktop 2.6 software for calculation of the parameters from the specific assays. The effect of FX11 was statistically analyzed using either t-test or linear regression modelling.

Statistical analysis of calculated respiratory parameters of BMDMs treated with FX11
or DMSO (control).

Box plots showing respiratory response (OCR value) stratified by experiment replicate
(related to Fig. 1A and B).

Linear regression models for each of the six respiratory parameters (see above box plots in 1.1)
For each parameter (readout), the influence of FX11 concentration on the parameter readout was tested using log-linear regression. To this end, the FX11 concentrations were logarithmized (with the control, DMSO, assumed to have a concentration below 0.0143 mM) and a linear model (lm) was fit on the resulting data with the lm() function in R.
Linear regression modeling results (related to data presented in Fig. 1B).

Linear regression models for each of the four outputs (see above box plots in 2.1.)
For each parameter (readout), the influence of FX11 concentration on the parameter readout was tested using log-linear regression. To this end, the FX11 concentrations were logarithmized (with the control, DMSO, assumed to have a concentration below 0.0143 mM) and a linear model (lm) was fit on the resulting data with the lm() function in R. Fig. 1C and D).

Linear regression modeling results (related to glycolytic function parameters presented in
Parameter P values Non-Gly acidification 0.11 (Not significant) Glycolytic capacity 8.57e-09 Glycolysis 0.85 (Not significant) Glycolytic reserve 6.88e-15