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Activity-based protein profiling for target identification of JCP276 in Mycobacterium tuberculosis

Citation

Babin, Brett (2021), Activity-based protein profiling for target identification of JCP276 in Mycobacterium tuberculosis, Dryad, Dataset, https://doi.org/10.5061/dryad.41ns1rndp

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

Peptides were resuspended in 0.2% formic acid in water. Peptides were separated over a 25-cm EasySpray reversed phase LC column (75 μm inner diameter packed with 2 μm, 100 Å, PepMap C18 particles, Thermo Fisher Scientific). The mobile phases (A: water with 0.2% formic acid and B: acetonitrile with 0.2% formic acid) were driven and controlled by a Dionex Ultimate 3000 RPLC nano system (Thermo Fisher Scientific). Gradient elution was performed at 300 nl min−1. For the FP ABPP experiment, the mobile phase was ramped to 3% B over 3 min, followed by a ramp to 35% B at 93 min, a ramp to 42% B at 103 min, and a wash at 95% B for 10 min. For the BMB034 ABPP experiment, the mobile phase was ramped to 5% B over 4 min, followed by a ramp to 25% B at 72 min, and a wash at 9% B for 6 min. Eluted peptides were analyzed on an Orbitrap Fusion Tribrid MS system (Thermo Fisher Scientific). Survey scans of peptide precursors were collected in the Orbitrap from 300-1500 m/z for the FP ABPP experiment or 350-1350 m/z for the BMB034 ABPP experiment. Monoisotopic precursor selection was enabled for peptide isotopic distributions, precursors of z = 2–5 were selected for data-dependent MS/MS scans for 2 s of cycle time.

Raw data files were analyzed using MaxQuant (v. 1.6.1.0) with the following parameters: trypsin digestion with maximum of 2 missed cleavages, variable modifications of oxidized methionine residues and acetylated N-termini, fixed modifications of carbamidomethylation at cysteine residues, peptide tolerance of 4.5 ppm, and a FDR of 1%. Peptides were quantified using LFQ with a minimum peptide count of 2, MS/MS of at least one peptide required for quantification, and using re-quantification and matches between runs. Data were searched against the reference H37Rv proteome. FP and BMB034 enrichment experiments were analyzed separately and results were merged (Table S4). Protein abundance ratios were calculated by dividing LFQ values from compound-treated samples by those from DMSO-treated samples. In cases where proteins were not identified in compound-treated samples, log2 ratios were arbitrarily set to -10.