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. 2024 Mar 5;19(3):707–717. doi: 10.1021/acschembio.3c00724

Bioorthogonal Metabolic Labeling of the Virulence Factor Phenolic Glycolipid in Mycobacteria

Lindsay E Guzmán †,‡, C J Cambier †,‡, Tan-Yun Cheng §, Kubra F Naqvi ∥,⊥, Michael U Shiloh ∥,⊥, D Branch Moody §, Carolyn R Bertozzi †,‡,*
PMCID: PMC10949201  PMID: 38442242

Abstract

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Surface lipids on pathogenic mycobacteria modulate infection outcomes by regulating host immune responses. Phenolic glycolipid (PGL) is a host-modulating surface lipid that varies among clinical Mycobacterium tuberculosis strains. PGL is also found in Mycobacterium marinum, where it promotes infection of zebrafish through effects on the innate immune system. Given the important role this lipid plays in the host–pathogen relationship, tools for profiling its abundance, spatial distribution, and dynamics are needed. Here, we report a strategy for imaging PGL in live mycobacteria using bioorthogonal metabolic labeling. We functionalized the PGL precursor p-hydroxybenzoic acid (pHB) with an azide group (3-azido pHB). When fed to mycobacteria, 3-azido pHB was incorporated into the cell surface, which could then be visualized via the bioorthogonal conjugation of a fluorescent probe. We confirmed that 3-azido pHB incorporates into PGL using mass spectrometry methods and demonstrated selectivity for PGL-producing M. marinum and M. tuberculosis strains. Finally, we applied this metabolic labeling strategy to study the dynamics of PGL within the mycobacterial membrane. This new tool enables visualization of PGL that may facilitate studies of mycobacterial pathogenesis.

Introduction

Mycobacterium tuberculosis (M. tuberculosis), the pathogen responsible for tuberculosis (TB), remains the leading cause of death from a bacterium.1 A factor that contributes to M. tuberculosis’s success is its unique lipid-rich cell envelope (Figure 1a).2 Many mycobacterial cell–surface lipids play important roles in virulence by modulating the host immune system.3 Two structurally related virulence lipids are phthiocerol dimycocerosate (PDIM) and phenolic glycolipid (PGL) (Figure 1b), which are found in the outermost layer of the mycomembrane.4 PDIMs and PGLs contain a lipid core with two esterified mycocerosic acid side chains. PGLs are heterogeneous with respect to their lipid chain lengths and functionalization with methoxy, hydroxy, or keto groups.4 Additionally, PGLs have a phenol moiety and a species-dependent glycan. Mycobacterium marinum (M. marinum) also produces PGL and is required for virulence.5 However, the M. marinum PGL glycan structure differs from those found in M. tuberculosis (Figure 1c).6 Each component of the PGL structure contributes to its effects on virulence.7

Figure 1.

Figure 1

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PGL is a mycobacterial cell–surface virulence factor. (A) Layers of the mycobacterial cell wall. CL = capsular layer, MM = mycomembrane, AG = arabinogalactan, PG = peptidoglycan, and PM = plasma membrane. (B) Simplified representative chemical structures of PDIM and PGL. PDIM and PGL structures are heterogeneous, and reports vary in the literature. For M. tuberculosis: X = 14–16; Y = methoxy, keto, or hydroxy; m = 3–5; n = 15–17; R = CH3 or H. For M. marinum: X = 14–16; Y = methoxy, keto, or hydroxy; m = 3–4; n = 16–18; and R = CH3. (C) Glycans of PGL vary according to the species of the mycobacteria.

The immunomodulatory effects of PGL are dependent on the species. M. tuberculosis PGLs are found in hypervirulent Lineage 2 strains such as HN878.8,9 These PGLs have been shown to suppress the secretion of proinflammatory cytokines TNF-α, IL-6, and MCP-1.7,8,10 In the zebrafish infection model, M. marinum PGLs allow bacterial transfer to permissive monocytes11 through the production of CCL2.12 Overall, PGLs are important virulence factors that give rise to immunomodulatory host responses.13,14

The ability to image PGL could be empowering for studies of its distribution and dynamics in mycobacterial cells. Unlike proteins that can be engineered for biosynthesis with fluorescent protein labels, lipids require chemical tools for labeling and visualization. One such approach is to modify lipids with bioorthogonal handles (e.g., azides or alkynes) then conjugate them to fluorescent probes in living systems.15,16 We and others have used metabolic labeling to incorporate a bioorthogonal handle into trehalose monomycolate (TMM), a major immunogenic lipid of the mycobacterial cell envelope.17−20 Additionally, we developed a chemical approach to visualize a fluorescent PDIM during the infection of zebrafish with M. marinum.21

Here, we report a metabolic labeling strategy to image PGL in live mycobacterial cells. We synthesized an azide-functionalized PGL precursor that is incorporated into native PGL within the outer membrane of the model mycobacterial species, M. marinum. We characterized azide-modified PGL (PGL-N3) using mass spectrometry (MS), demonstrated the selectivity of labeling in M. marinum and M. tuberculosis, and used this imaging tool to study PGL dynamics within the mycobacterial membrane. The ability to image PGL on live mycobacteria adds to the toolkit for experimental studies of mycobacterial lipid biology.

Results and Discussion

The biosynthesis of M. tuberculosis PGLs is a complex multistep process (Scheme 1).22 It is hypothesized that PGL biosynthesis is conserved across PGL-producing mycobacterial species23 apart from the glycan. The first committed step in PGL biosynthesis is the loading of p-hydroxy benzoic acid (pHB) onto the fatty-acid-CoA ligase, FadD22,24 and elaboration by the type 1 polyketide synthase pks15/1.25−27 A variety of polyketide synthases28 and other enzymes29 further extend and embelish the lipid core and decorate it with methoxy, keto, or hydroxy functional groups to form phenolphthiocerol, phenolphthiodiolone, or phenolphthiotriol lipid cores.30,31 In parallel, mycocerosic acids are synthesized by the mycocerosic acid synthase (mas)32 then condensed with the lipid core by the enzyme PapA5 to form p-hydroxyphenol PDIM.33 The glycan of PGL is then decorated by several glycosyl and methyltransferases.30,34,35 Finally, PGL is shuttled to the cell surface by the lipid transporter Mmpl7 and its auxiliary proteins.36

Scheme 1. Simplified PGL Biosynthetic Pathway for M. tuberculosis.

Scheme 1

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PGL structures are heterogeneous, and reports vary in literature, but typically, X = 14–16; Y = methoxy (phenolphthiocerol), keto (phenolphthiodiolone), or hydroxy (phenolphthiotriol); m = 3–5; n = 15–17; and R = CH3 or H.

We focused on pHB as a key intermediate that could be modified with an azide group. Previous work has shown that exogenous radiolabeled pHB is taken up by mycobacterial cells and metabolically incorporated into cell–surface PGL.8 While pHB is also used in the biosynthesis of other p-hydroxybenzoic acid derivatives (pHBADs),37−40 these metabolites are not associated with the cell envelope—they are either cytosolic or secreted—and therefore would not be expected to confound the visualization of membrane-associated PGL. We synthesized both 2- and 3-azido pHB as described in the Supporting Information. We tested these derivatives as substrates for metabolic labeling of cell surface PGL by using the workflow shown in Figure 2a. We used M. marinum as a model mycobacterial species based on its close genetic relationship to M. tuberculosis and its prior use in studies of mycobacterial pathogenesis.41,42

Figure 2.

Figure 2

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Fluorescent labeling of M. marinum upon treatment with 3-azido pHB. (A) Workflow of labeling experiments with 2- or 3-azido pHB. M. marinum was treated for 18 h in the presence of various concentrations of 2- or 3-azido pHB, followed by staining with AF647-DBCO (30 μM). Cells were then fixed and analyzed by flow cytometry. (B) Flow cytometry analysis of the labeled cells. Relative MFI is determined by normalizing against the DMSO control. Flow cytometry data are the averages of three independent replicates. Statistical analysis was performed using a two-way ANOVA followed by a Dunnett’s multiple comparisons test. Significance is represented as follows: ***p < 0.001, ****p < 0.0001, and ns (not significant) for p > 0.05. (C) Effects of bacterial growth (A600) of M. marinum treated with 2- or 3-azido pHB. The data represent three independent replicates. Statistical analysis was performed using an ordinary two-way ANOVA, followed by Šídák’s multiple comparisons test. Significance is represented by ns (not significant) for p > 0.05. (D) TLC analysis of crude lipid extracts from M. marinum cells treated with 3-azido pHB and stained with AF647-DBCO. Crude lipid extracts (50 μg) or AF647-DBCO (1 μg) were loaded onto a silica gel 60 TLC plate, which was then developed with 4:6 methanol/chloroform. TLC was visualized using a ChemiDoc MP Imaging system using the 700 nm wavelength. (E) Confocal images of M. marinum cells treated with 750 μM 3-azido pHB and stained with AF647-DBCO. DIC = differential interference contrast. Scale bar = 2 μm.

M. marinum cells were treated with various concentrations of 2- or 3-azido pHB (250–1000 μM) for 18 h. The bacteria were then washed, stained with the fluorophore AF647-dibenzocyclooctyne (AF647-DBCO), fixed with 4% paraformaldehyde/2.5% glutaraldehyde, and analyzed by flow cytometry (Figures 2b; see S1A for the gating strategy). When bacteria were treated with 2-azido pHB, there was no increase in the mean fluorescence intensity (MFI) in reference to the DMSO control. However, when M. marinum was treated with 3-azido pHB, we saw a significant and dose-dependent increase in MFI up to 750 μM with modestly reduced fluorescence at the highest dose (Figure 2b). We also assessed the effects of 2- or 3-azido pHB treatment on PGL production qualitatively by thin layer chromatography (TLC). When lipids from 2-azido pHB-treated cells were extracted with chloroform/methanol and analyzed by TLC, we observed a significant decrease in PGL’s abundance at all concentrations tested (Figure S2). This outcome suggests that 2-azido pHB strongly inhibits PGL biosynthesis. By contrast, the treatment of cells with 3-azido pHB qualitatively showed much smaller reductions in PGL production by TLC, which were apparent at the highest concentrations tested (Figure S2). Neither 2- nor 3-azido pHB significantly affected cell growth, as measured by A600 (Figure 2c). Importantly, no fluorescence labeling was observed when cells were treated with natural pHB, followed by the labeling reagent, AF647-DBCO, indicating that an azide is required for increases in MFI (Figure S3). Given the outcome of these experiments, we focused on using 3-azido pHB as a metabolic label for the remainder of this study.

To determine whether fluorescence labeling resulted from incorporation of 3-azido pHB into cell surface lipids, we treated M. marinum with 3-azido pHB followed by AF647-DBCO, extracted the lipids with chloroform/methanol, and separated them by TLC (Figure 2d). The extracts contained one major fluorescent species with a Rf consistent with a lipid that is modified with a charged fluorescent dye.

We then used confocal microscopy to determine the localization of fluorescence in labeled M. marinum (Figure 2e). M. marinum expressing a green fluorescent protein (wasabi) was treated with 750 μM 3-azido pHB followed by staining with AF647-DBCO. As shown in Figure 2e, AF647 fluorescence was only observed on the cells treated with 3-azido pHB, consistent with our flow cytometry data (Figure 2b). The fluorescence was concentrated on the outer membrane of the cells, where PGL is located. No difference in cell morphology was observed in comparison to the DMSO control, suggesting that the incorporation of azides into PGL has no dominant effect on M. marinum cellular macrostructures.

To confirm that 3-azido pHB was incorporated into PGL, we used high-performance liquid chromatography quadrupole time-of-flight MS (HPLC-Q-TOF-MS) to analyze M. marinum lipid extracts. The sample without the 3-azido pHB treatment served as a control. Endogenous PGL was detected as an ammonium adduct (1523.3928 m/z) (Figure 3a). We generated a table of predicted molecular formulas and m/z values of the ammonium adducts for known PGL lipoforms (Supporting Information Table S1). Because PGL-N3 would have a net mass gain of 41.0014 m/z due to the replacement of a proton by an azide group, we calculated the theoretical m/z values for PGL-N3 lipoforms (Supporting Information Table S1).

Figure 3.

Figure 3

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MS analysis of crude lipid extracts from 3-azido pHB-treated M. marinum. (A) Ion chromatograms of the representative species of PGL (1523.3915 m/z) and PGL-N3 (1564.3929 m/z) detected in the total lipid extracts of M. marinum treated with 3-azido pHB (750 μM) were generated by positive-mode reversed-phase HPLC-Q-TOF-MS. (B) Mass spectra of indicated PGL and PGL-N3 species. (C) CID-MS of PGL and PGL-N3 showing diagnostic fragments corresponding to the loss of one mycocerosic acyl moiety (PGL: 1095.953 m/z; PGL-N3: 1108.948 m/z with spontaneous loss of N2 from the N3 group), the loss of one mycocerosyl moiety plus the monosaccharide (PGL: 935.879 m/z; PGL-N3: 976.880 m/z and 948.866 m/z with spontaneous loss of N2 from the N3 group), and the loss of both mycocerosic acyl moieties plus the monosaccharide (PGL: 525.467 m/z; PGL-N3: 566.468 m/z and 538.462 m/z with a spontaneous loss of N2 from the N3 group). (D) Effects of M. marinum treated with 3-azido pHB on the abundance of PGL-N3 species, as quantified by MS. The data represented as three repeated mass spectral measurements. Statistical analysis was performed using a two-way ANOVA followed by a Dunnett’s multiple comparisons test. Significance is represented by ****p < 0.0001 and ns (not significant) for p > 0.05. (E) Effects of M. marinum treated with 3-azido pHB on the abundance of PGL-N3, total PGL, PDIM, and PE as determined by MS analysis. Quantified MS data are representative of three repeated mass spectral measurements. Statistical analysis was performed using a two-way ANOVA followed by a Dunnett’s multiple comparisons test. Significance is represented as follows: *p ≤ 0.05, **p < 0.01, ****p < 0.0001, and ns (not significant) for p > 0.05.

Next, we searched for PGL-N3 in the lipid extracts from 3-azido pHB-treated cells and found seven ions (1536.3652, 1552.4034, 1564.3939, 1580.4244, 1592.4350, 1606.4491, and 1608.4519 m/z) that corresponded to PGL-N3 species within a mass error of 10 ppm (ppm). The mass intervals between these ions corresponded to differences in methoxy or keto groups and chain length variants (Supporting Information Table S1). Out of the seven PGL-N3 ions identified, four were in major abundance with a high mass accuracy (within 5 ppm). One major PGL-N3 species (1564.3929 m/z) was separated from its endogenous PGL counterpart by HPLC (Figure 3a). The identification of PGL-N3 in the mass spectrum (Figure 3b) was further validated by collision-induced dissociation MS (CID-MS). Like the natural PGL, the PGL-N3 species molecule readily lost both mycocerosic acids and the rhamnose glycan in the MS2 spectrum. This yielded lipid core fragments with or without spontaneous loss of N2 (Figure 3c), consistent with previous observations on aryl azide ionization and fragmentation.43 These data confirm that 3-azido pHB was metabolically incorporated into the PGL.

We next sought to quantify the abundance of PGL-N3 produced in response to treatment with various concentrations of 3-azido pHB. As observed with fluorescence labeling (Figure 2b), a treatment dose of 750 μM gave the maximum MFI by flow cytometry. We hypothesized that the fluorescence observed by flow cytometry was due to the abundance of PGL-N3. To address this hypothesis, we measured the effect of 3-azido pHB on the total production of PGL and PGL-N3 by MS. The highest amount of PGL-N3 detected was 2% of the total PGLs at 750 μM 3-azido pHB (Figure 3e), which confirms our hypothesis that fluorescence and PGL-N3 abundance are correlated. Total PGL abundance was inhibited by 3-azido pHB in a dose-dependent manner (∼50% at 1 mM). Additionally, we measured the abundance of other non-PGL lipids. We observed smaller effects on the abundance of PDIM, which shares some biosynthetic steps with PGL (Figure 3e). PDIM levels were unaffected by 3-azido pHB at concentrations below 1 mM. Phosphatidylethanolamine (PE), a lipid that does not share any biosynthetic steps with PGL, was mostly unaffected by 3-azido pHB treatment except for a slight decrease in abundance at the highest concentration of 1 mM (Figure 3e). Thus, PGL-N3 biosynthesis was optimal at a labeling concentration of 750 μM 3-azido pHB, as indicated by both fluorescence and MS.

As further confirmation that 3-azido pHB primarily labels PGL, we performed similar experiments using PGL-deficient mycobacteria. We tested Mycobacterium smegmatis (M. smegmatis), a commonly used model organism which naturally lacks PGL,44 and M. marinum mutants that are deficient either in pks15/1 or MmpL7.11 PGL deficiency was confirmed by TLC analysis of lipid extracts from these mycobacteria (Figure S4). Indeed, when these mycobacteria were treated with 3-azido pHB followed by AF647-DBCO, no significant fluorescence labeling was observed by flow cytometry (Figure 4a). No fluorescent species were detected by the TLC analysis of lipid extracts from M. marinum mutants treated with 3-azido pHB and AF647-DBCO (Figure 4b). Therefore, 3-azido pHB appears to exclusively label PGL within the lipid extract.

Figure 4.

Figure 4

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Metabolic incorporation of 3-azido pHB occurs only in live M. marinum with an intact PGL biosynthetic pathway. (A) Mycobacteria that lack the PGL biosynthetic pathway were treated with various concentrations of 3-azido pHB and analyzed by flow cytometry. Flow cytometry data are averages of three independent replicates. Statistical analysis was performed using an ordinary two-way ANOVA, followed by Šídák’s multiple comparisons test. Significance is represented, where ****p < 0.0001 and ns (not significant) for p > 0.05. (B) Lipid extracts of PGL-deficient M. marinum strains treated with 3-azido pHB, stained with AF647-DBCO, and analyzed by TLC. Crude lipid extracts (100 μg) or AF647-DBCO (20 μg) were loaded onto a silica gel 60 TLC plate, which was then developed with 4:6 methanol/chloroform. TLC was visualized using a ChemiDoc MP imaging system with a 700 nm wavelength. (C) Competition experiment using various concentrations of pHB added to M. marinum treated with 750 μM 3-azido pHB. Flow cytometry data are averages of three independent replicates. Relative MFI is determined by normalizing against DMSO control. Statistical analysis was performed using a two-way ANOVA followed by a Dunnett’s multiple comparisons test. Significance is represented by ****p < 0.0001 and ns (not significant) for p > 0.05. (D) M. marinum were heat killed (80 °C, 30 min), treated with 3-azido pHB for 18 h, stained with AF647-DBCO, and analyzed by flow cytometry. Statistical analysis was performed using a two-way ANOVA followed by a Dunnett’s multiple comparisons test. Significance is represented by p < 0.001 and ns (not significant) for p > 0.05.

To further test the selectivity of 3-azido pHB labeling, we performed a competition experiment using natural pHB. We treated M. marinum with various concentrations of pHB in combination with 750 μM 3-azido pHB (Figure 4c). As the concentration of pHB increased, the fluorescence intensity as measured by flow cytometry decreased in a dose-dependent manner, with complete suppression of metabolic labeling at 100 μM pHB. Additionally, we heat-killed M. marinum at 80 °C for 30 min, which abrogated labeling (Figure 4d). Thus, metabolic labeling of PGL with 3-azido pHB occurs only in live cells with active metabolism.

Having demonstrated the ability to image PGL in model organisms, we shifted our attention to virulent M. tuberculosis. We treated a PGL-producing strain of M. tuberculosis, HN878, with various concentrations of 3-azido pHB and found a significant increase in MFI in comparison to the DMSO control (Figure 5a). We noticed that bacterial growth was significantly affected by the 3-azido pHB treatment (Figure 5b). Next, a PGL-deficient mutant M. tuberculosis strain, HN878 Δpks15/1, and the naturally PGL-deficient Erdman strain were treated with 3-azido pHB, followed by AF647-DBCO (Figure 5c). The absence of PGL in the M. tuberculosis HN878 Δpks15/1 and Erdman strains was confirmed by TLC analysis (Figure S5). We observed no labeling of the two PGL-deficient M. tuberculosis strains (Figure 5c), which matches observations with PGL-deficient M. marinum mutants, confirming the high specificity of the reagent for the PGL pathway (Figure 4a). From these experiments, we conclude that 3-azido pHB metabolically labels PGL in M. tuberculosis in a highly selective manner.

Figure 5.

Figure 5

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Metabolic labeling of PGL-producing M. tuberculosis HN878 treated with 3-azido pHB. (A) M. tuberculosis HN878 treated with various concentrations of 3-azido pHB, stained with AF488-DBCO, and analyzed by flow cytometry. Flow cytometry analysis indicates three replicates seeded from different cells. Relative MFI is determined by normalizing against the DMSO control. Statistical analysis was performed using a two-way ANOVA followed by a Dunnett’s multiple comparisons test. Significance is represented by **p < 0.01. (B) Effects of bacterial growth (A600) of M. tuberculosis HN878 treated with various concentrations of 3-azido pHB. The data are representative of three replicates seeded from different cells. Statistical analysis was performed using a two-way ANOVA followed by a Dunnett’s multiple comparisons test. Significance is represented by **p < 0.01 and ****p < 0.0001. (C) PGL-deficient M. tuberculosis strains (Erdman and HN878 Δpks15/1) and PGL-producing M. tuberculosis strain HN878 treated with 200 μM 3-azido pHB, stained with AF488-DBCO, and analyzed by flow cytometry. Flow cytometry analysis indicates three replicates seeded from different cells. Relative MFI is determined by normalizing against the DMSO control. Statistical analysis was performed using an ordinary two-way ANOVA, followed by Šídák’s multiple comparisons test. Significance is represented by ****p < 0.0001 and ns (not significant) for p > 0.05.

The ability to image PGL in live mycobacteria opens the door to studies of lipid dynamics. Understanding the mobility of cell–surface lipids can inform lipid–host interactions.21 In previous work, we and others have analyzed the dynamics of various mycobacterial cell wall constituents, including mannosylated phosphatidylinositol,45 TMM,46 and PDIM21 using imaging techniques. One such technique is fluorescence recovery after photobleaching (FRAP), which is an in vitro confocal microscopy method to determine the mobility of biomolecules.47 FRAP involves photobleaching a specific cellular region and monitoring fluorescence recovery over time for a fluorescently labeled biomolecule. From the rate of fluorescence recovery, the half-time of recovery (τ1/2) constant can be determined. Additionally, the mobile fraction can be identified, which is the plateau value from each FRAP experiment. The mobile fraction informs on the number of mobile biomolecules within the bleached region.

We therefore sought to use FRAP to investigate the membrane dynamics of PGL. We used TMM as a comparison, which has been previously investigated by FRAP.21,46 Mycobacteria synthesize azido-TMM upon treatment with 6-azido trehalose.18 We treated M. marinum with 3-azido pHB or 6-azido trehalose and stained it with AF488-DBCO to produce PGL-488 and TMM-488, respectively. In our FRAP measurements (Figure 6a,b), we found that TMM-488 has a τ1/2 of ∼10 s. However, PGL-488 recovered faster, with τ1/2 ∼ 3 s. The half-time of recovery of PGL was consistent with our previous FRAP experiment with PDIM, which had a τ1/2 ∼ 2 s21 We also plotted the mobile fraction (Figure 6c). We found that the percentage of mobile lipids in TMM-488 and PGL-488 is not significantly different. Taken together, PGL and TMM have the same fraction of mobile lipids, but since PGL has a lower τ1/2, it is a more mobile lipid than TMM.

Figure 6.

Figure 6

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FRAP indicates that PGL has high membrane mobility in comparison to TMM. M. marinum were treated with 3-azido pHB or 6-azido trehalose for 18 h, stained with AF488-DBCO, and imbedded in a 1.5% agarose pad. A ROI was drawn around individual cells and bleached with a 488-laser line. (A) Representative images of the fluorescence recovery after photobleaching over time. The scale bar indicates 2 μm. (B) Rates of FRAP. MFI values of photobleached ROIs were normalized by dividing by the total fluorescence intensities of the corresponding whole cells. The plot of these values as a function of time was fitted to a nonlinear regression with a one-phase association. Each symbol represents the average signal from n = 10 cells. (C) Mean mobile fraction determined as the plateau value from the fitted curves, where each point represents the plateau value of an individual cell. Statistical analysis was performed using an unpaired two-tailed t-test represented by ns (not significant) for p > 0.05.

PGL is an important virulence factor hypothesized to contribute to the hypervirulence of M. tuberculosis Lineage 2 strain HN878. Due to the lack of chemical tools to tag PGL, the interrogation of PGL-host interactions during infection has been underexplored. Here, we demonstrated metabolic incorporation of a bioorthogonal handle into the mycobacterial virulence lipid PGL. We showcased the labeling with 3-azido pHB in the PGL-producing mycobacterial species M. marinum using flow cytometry and fluorescence microscopy. We identified PGL-N3 by MS and determined that the 3-azido pHB label is selective for PGL-producing mycobacteria. Among all lipids, we determined that labeling is highly specific to PGL and established the conditions for optimal bright labeling that minimize effects on native PGL as well as other lipids. Additionally, we showed that 3-azido pHB metabolically labels PGL in M. tuberculosis. Finally, we studied PGL membrane dynamics using metabolic labeling with 3-azido pHB.

Studies of lipid dynamics are fundamental to understanding lipid–host interactions. We previously reported that PDIM has high mobility and attributed its fluidity to being responsible for spreading onto host membranes during infection.21 Considering the structural and membrane fluidity similarities of PDIM and PGL, we hypothesize that PGL may also spread onto host membranes during infection to modulate host immunity. Although the PGL spreading mechanism has yet to be elucidated, we speculate it could be simply due to lipid shedding or the secretion of bacterial membrane vesicles (BMVs). Indeed, PGL has been found in BMVs by performing chloroform/methanol extractions of culture supernatants.48,49

Future directions of this work involve visualizing the mechanisms of PGL during host infection. This involves using our metabolic labeling strategy to identify PGL distribution, trafficking, and dynamics during pathogenesis. Additionally, we theorize that our PGL metabolic labeling approach could be used as a facile method to determine if certain M. tuberculosis strains produce PGL without time-consuming lipid extractions and MS analysis. We envision that our metabolic labeling strategy will aid in the study of PGL during infection, which may inform the therapeutic development of TB.

Methods

Cell Lines and Culture Conditions

M. marinum was cultured at 32 °C in a liquid 7H9 medium containing 10% glycerol, 0.01% tween-80, and 100 μM Hygromycin B. M. smegmatis was cultured at 37 °C in liquid 7H9 media containing 10% glycerol and 0.01% tween-80 shaking at 100 rpm. Starter cultures of M. tuberculosis strains HN878 (BEI resources), Erdman (laboratory of J. Cox, UC Berkley), and HN878 Δpks15/1 (a generous gift from the laboratory of C. Barry III, NIH)8 were grown at 37 °C in liquid 7H9 media containing 10% OADC, 1% glycerol, and 0.05% tween-80.

Flow Cytometry

M. marinum and M. smegmatis were gated based on forward and side scatter emissions, excluding debris. Singlets were gated based on side scatter height vs area. When applicable, M. marinum expressing wasabi was gated using the 488 nm blue laser (530/30 filter). For M. marinum, AF647 staining was determined by fluorescence using a red laser (660/20 filter). M. tuberculosis was gated based on forward and side scatter emissions, excluding debris. For M. tuberculosis, AF488 staining was determined by fluorescence using the 488 nm blue laser (530/30 filter).

General Procedure for Metabolic Labeling Experiments of M. marinum

M. marinum were cultured using 7H9 media +0.01% tween-80 with Hygromycin B until an A600 of 0.8–1.2. Mycobacteria were then diluted such that A600 = 0.25 in 2 mL of T-25 culture flasks. DMSO or azide compounds were added to the bacterial culture, with DMSO not increasing by 1%. Mycobacteria were then cultured until A600 of 0.8–1.2. The bacteria were then washed with PBS-T (3×) and with PBS. Bacteria were then labeled with AF647-DBCO or AF680-DBCO (30 μM in PBS) for 1 h at RT (rt) in the dark. The bacteria were then washed with PBS-T (4×) and with PBS. Bacteria were then fixed using 4% paraformaldehyde and 2.5% glutaraldehyde for 1 h at RT (rt) in the dark. Bacteria were again washed with PBS-T (2×) and PBS prior to analysis by flow cytometry or microscopy.

General Procedure for Lipid Extractions

Large-scale cultures (200 mL) of bacteria were grown until an A600 of 0.8–1.2 shaking at 100 rpm. Bacteria were then washed 3× with PBS-T and once with PBS. Bacteria were then lyophilized until completely dry. Bacteria were then treated with a fluorophore (30 μM, 5 mL) for 1 h at rt, washed with 4× PBS-T, and then 1× with PBS. Bacteria were then lyophilized until completely dry. After the cells were completely dry, the dry mass of the cells was measured. Then, 20 mL of chloroform and 10 mL of methanol were added to the cells with a stir bar. The cells were stirred in the organic solvent mixture overnight at rt. The cells were then filtered using Whatman 1 filter paper and rinsed with chloroform and methanol. The filtrate was collected and evaporated under reduced pressure. Lipid residue was then resuspended in chloroform, filtered using a 0.22 μm syringe filter, and evaporated under reduced pressure.

General Procedure for Developing TLC Plates

Lipid extracts were dissolved in a concentrated solution of chloroform (i.e., 20 mg mL–1). A 2 μL pipet was used to apply the sample to a silica gel 60 TLC plate. A small latch-lock prep TLC chamber was used to develop the TLC plates in 8:2 toluene/acetone, 95:5 chloroform/methanol, or 4:6 methanol/chloroform. After development, TLC plates were dried with a heat gun. If fluorescent lipids were loaded onto the plate, they were scanned using a ChemiDoc MP Imaging system at 700 nm prior to staining with iodine or anthrone. TLC plates were then stained in a chamber containing iodine adhered to silica. After the image of the TLC plate was captured, a heat gun was used to remove most of the iodine stain. Then, the TLC plate was lightly sprayed with a solution of 0.2% anthrone in sulfuric acid. The TLC plate was then exposed to a heat gun with high heat. TLC plates were visualized using a ChemiDoc MP Imaging system with a 590 nm wavelength.

HPLC-QTOF-MS and CID-MS Analysis of PGL-N3

Total bacterial lipids were extracted into chloroform and methanol for analysis by HPLC-MS. The lipid samples were prepared at 1 mg mL–1 in the starting mobile phase (50% A and 50% B), and 10 μL was injected into a reversed-phase HPLC system (Agilent 1260 series) using an Agilent Poroshell EC-C18 column (1.9 μm, 3 × 50 mm) coupled with an Agilent guard column (2.7 μm, 3 × 5 mm) and analyzed by an Agilent 6546 Accurate-Mass Q-TOF mass spectrometer. The mobile phases were A [2 mM ammonium formate in 90/10 methanol/water (v/v) and B (3 mM ammonium formate in 85/15/0.1 1-propanol/cyclohexane/water (v/v/v)]. The gradients were: 0–2 min, 50% A; 2–10 min, from 50% A to 100% B; 10–15 min, 100% B; 15–17 min, from 100% B to 50% A; and 17–20 min, 50% A. CID-MS was carried-out with a collision energy of 35 V, and the isolation width was set to 1.3 m/z.

Metabolic Labeling of M. tuberculosis

For each strain, starter cultures were subcultured into sterile square media bottles (Nalgene) at an A600 = 0.3 in 5 mL of 7H9. Cultures designated for labeling received 200–1000 μM final concentration of 1 M 3-azido pHB or an equivalent volume of DMSO vehicle control and were wrapped in foil to protect from light. Labeled and control cultures were incubated at 37 °C shaking (100 rpm) until A600 = 0.8–1.0 was reached, approximately 3 days. Following the labeling period, cultures were pelleted at 3,000×g for 3 min and washed 3 times with PBS + 0.5% tween-80 and once with PBS. Bacterial pellets were then resuspended in PBS containing 10 μM AF488-DBCO or PBS alone (unstained) and incubated for 1 h at RT, protected from light. The bacterial suspensions were then pelleted, washed 3 times with PBS + 0.5% tween-80, and fixed with a 4% paraformaldehyde solution for 24 h. For flow cytometry analysis of 3-azido labeling, fixed bacterial samples were washed with PBS and acquired on a BD FACSCalibur cytometer. Flow cytometry analysis was performed using FlowJo software.

General Procedure for FRAP

FRAP experiments were based on previous methods.46 Bacteria were cultured in the presence of 750 μM 3-azido pHB or 50 μM 6-azido trehalose for ∼18 h according to general labeling procedures. The bacteria were then washed with PBS-T (3×) and with PBS. Bacteria were then labeled with AF488-DBCO fluorophore (5 μM in PBS) for 1 h at rt in the dark. The bacteria were then washed with PBS-T (4×) and with PBS. Low-melting agarose (1.5%) pads were made, and 1 μL of bacteria were dropped onto the center of the pad. A coverslip was then put on the agar pad, and the slide was sealed using nail polish. The acquisition laser power was set to 2% with bidirectional scans. Photobleaching was obtained after 4 scans using 100% bleaching power and 50 iterations. Data was obtained over 70 s after photobleaching. MFI values of photobleached regions of interest (ROIs) were normalized by dividing the total fluorescence intensities of the corresponding whole cells. The plot of these values as a function of time was fitted to a nonlinear regression with a one-phase association. The mean mobile fraction was determined as the plateau value from the fitted curves. FRAP was performed on an inverted Zeiss 780 multiphoton laser scanning confocal microscope.

Statistical Analysis and Software

GraphPad Prism 9 software was used for all statistical analyses. Significance is represented as follows: *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, and ns (not significant) for p ≥ 0.05. The specific statistical methods for individual experiments are indicated in the figure legends.

Flow cytometry data was analyzed using FlowJo 10.8.1 software. The NMR data was analyzed using MNova software version 14.2.3. MS data was analyzed using Agilent MassHunter software. Figures were constructed using Adobe Illustrator version 26.5 software.

Acknowledgments

L.E.G. would like to thank M. Morimoto, D. Roberts, W. Sinclair, and J. Buonomo for useful discussions. L.E.G. would also like to thank M. Mishra for technical assistance with FRAP experiments and data analysis.

Glossary

Nomenclature/Abbreviations

AF647

AlexaFluor647 fluorophore

AF488

AlexaFluor488 fluorophore

AG

arabinogalactan

CL

capsular layer

DBCO

dibenzylcyloocytne

DIC

differential interference contrast

DMSO

dimethyl sulfoxide

MFI

mean fluorescence intensity

M. smegmatis

Mycoabacterium smegmatis

M. tuberculosis

Mycobacterium tuberculosis

M. marinum

Mycobacterium marinum

MM

mycomembrane

MS

mass spectrometry

m/z

mass/charge ratio

NMR

nuclear magnetic resonance

A600

optical density measured by absorbance at a wavelength of 600 nm

PBS

phosphate-buffered saline

PBS-T

phosphate-buffered saline +0.01% tween-20

PDIM

phthiocerol dimycocerosate

PG

peptidoglycan

PGL

phenolic glycolipid

pHB

p-hydroxy benzoic acid

Q-TOF

quantitative time-of flight

TB

tuberculosis

TLC

thin-layer chromatography

TMM

trehalose monomycolate

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acschembio.3c00724.

  • Additional experimental details, materials, methods, and spectra (PDF)

We are grateful for the financial support from the National Institutes of Health: R01 AI051622 (to C.R.B.), R01 AI165573 (to D.B.M.), R01 AI049313 (to D.B.M.), R01 AI158688 (to M.U.S.), and P01 AI159402 (to M.U.S). M.U.S. thanks the Welch Foundation (I-1964–20210327) and the Burroughs Wellcome Fund (1017894). C.J.C. was supported by the Damon Runyon Postdoctoral Fellowship. K.F.N. was supported by the NIH T32 AI007520 fellowship. Additionally, we thank the NIH High End Instrumentation grant (1 S10 OD028697-01) for the Bruker Neo-500 MHz instrument.

The authors declare the following competing financial interest(s): C.R.B. is a cofounder and Scientific Advisory Board member of Lycia Therapeutics, Palleon Pharmaceuticals, Enable Bioscience, OliLux Bio, InterVenn Bio, Firefly Bio, Redwood Bioscience (a subsidiary of Catalent), Neuravid Therapeutics, and GanNa Bio. C.R.B. is a member of the Board of Directors of Alnylam and OmniAb.

Supplementary Material

cb3c00724_si_001.pdf (10.1MB, pdf)

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Supplementary Materials

cb3c00724_si_001.pdf (10.1MB, pdf)

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