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Lipidomic profiling of Mycobacterium tuberculosis treated with JCP276, BMB034, or THL

Cite this dataset

Babin, Brett (2021). Lipidomic profiling of Mycobacterium tuberculosis treated with JCP276, BMB034, or THL [Dataset]. Dryad. https://doi.org/10.5061/dryad.6q573n5zv

Abstract

The increasing incidence of antibiotic-resistant Mycobacterium tuberculosis infections is a growing global health threat necessitating the development of new antibiotics. Serine hydrolases (SHs) are a promising class of targets because of their importance for the synthesis of the mycobacterial cell envelope. We screened a library of small molecules containing serine-reactive electrophiles and identified a series of narrow spectrum inhibitors of M. tuberculous growth. Using these lead molecules we performed competitive activity-based protein profiling and identified SH targets, including enzymes with uncharacterized functions. Lipidomic analyses of compound-treated cultures revealed an accumulation of free lipids and a substantial decrease in lipooligosaccharides, linking SH inhibition to defects in cell envelope biogenesis. Mutant analysis revealed a path to resistance via the synthesis of mycocerates, but not through mutations to target enzymes. We conclude that simultaneous inhibition of multiple SH enzymes is likely to be an effective therapeutic strategy.

Methods

M. tuberculosis H37Rv liquid cultures at OD600 of 1 were transferred to 0.22 µm membranes placed on 7H10 solid medium and incubated for 1 week at 37 ºC to yield a lawn of bacteria on each membrane. Membranes were transferred to 6-well plates containing 7H10 solid medium with 1% DMSO, 100 µM JCP276, 100 µM BMB034, or 100 µM THL. Membranes were incubated for 24 h at 37 ºC. Each membrane was transferred to an O-ring tube and lipids were extracted form whole cells by vortexing once each with 0.5 ml 1:2 chloroform:methanol, 0.5 ml 1:1 chloroform:methanol, and 0.5 ml 2:1 chloroform:methanol. Supernatants from the three extractions were combined and filtered twice through 0.22 µm syringe filters before removal from the BSL3 facility. Extracts were transferred to glass vials and solvent was dried under nitrogen gas. Samples were dried completely by rotary evaporation. The dry mass of each lipid sample was measured and lipids were resuspended in 2:1 chloroform:methanol to a final concentration of 5 mg/ml.

Mass spectrometry analysis was performed with an electrospray ionization source on an Agilent 6520 Q-TOF LC/MS in negative ionization mode. For Q-TOF acquisition parameters, the mass range was set from 100 to 1700 m/z with an acquisition rate of 1 spectra/second and time of 1000 ms/spectrum. For Dual AJS ESI source parameters, the drying gas temperature was set to 250°C with a flow rate of 12 l/min, and the nebulizer pressure was 20 psi. The capillary voltage was set to 3500 V and the fragmentor voltage was set to 100 V. Reversed-phase chromatography was performed with a Luna 5 mm C5 100 Å LC column (Phenomenex cat #00B-4043-E0). Samples were injected at 20 ul each. Mobile phases for were as follows: Buffer A, 95:5 water/methanol with 0.1% ammonium hydroxide; Buffer B, 60:35:5 isopropanol/methanol/water with 0.1% ammonium hydroxide. All solvents were HPLC-grade. The flow rate for each run started with 0.5 minutes 95% A / 5% B at 0.6 ml/min, followed by a gradient starting at 95% A / 5% B changing linearly to 5% A / 95% B at 0.6 ml/min over the course of 19.5 minutes, followed by a hold at 5% A / 95% B at 0.6 ml/min for 8 minutes and a final 2 minute at 95% A / 5% B at 0.6 ml/min.

Raw files were converted to mzXML format with MSConvert (ProteoWizard) using the Peak Picking Vendor algorithm. Files were analyzed using the web-based XCMS platform (Tautenhahn et al., 2012) with the following settings: signal to noise threshold, 6; maximum tolerated m/z deviation, 30 ppm; frame width for overlapping peaks, 0.01; and peak width, 10-60 s. Integrated peak intensities were normalized between conditions by median fold change. Tables containing mass features and ion intensities from each experiment were downloaded from the XCMS platform. Identified ions were matched to the MycoMass database (Layre et al., 2011) using a custom python script. Ions were matched if the measured m/z was within 10 ppm of the annotated m/z.