pathogenesis ( 4-6 ). The abundance and biological importance of the Mtb lipids has resulted in extensive and elegant studies to elucidate their structures and functions ( 1-3 ). In many cases, the lipids of Mtb are unique to this pathogen or shared only with other members of this genus.Earlier studies demonstrate variability in lipid profi les among different strains of Mtb ( 7-11 ) and that minor variations in the structure of individual lipids can occur with changes in the growth environment (12)(13)(14)(15)(16)(17)(18)(19)(20). However, targeted and nontargeted assays that monitor changes in Mtb lipid profi les are generally performed by traditional TLC-based methods ( 21 ), and global lipidomics analyses in Mtb have been restricted due to limits in the technology to detect and rapidly identify a large number of lipids in a single experiment. Two-dimensional NMR was recently applied to examine global mycobacterial lipid profi les, and this approach allowed for the identifi cation of key lipid differences in 13 C-enriched cellular extracts ( 22 ). Although this approach easily detects changes in lipid patterns, it is limited by the complexity of the NMR spectra and the overlapping chemical properties of many lipids. Alternatively, MS-based lipidomic strategies allowing simultaneous detection, identifi cation, and quantifi cation of structurally diverse lipid components of Mtb also were evaluated. Leavell and Leary ( 23 ) developed an algorithm to analyze high-resolution Fourier transform-ion cyclotron Abstract The cellular envelope of Mycobacterium tuberculosis is highly distinctive and harbors a wealth of unique lipids possessing diverse structural and biological properties. However, the ability to conduct global analyses on the full complement of M. tuberculosis lipids has been missing from the repertoire of tools applied to the study of this important pathogen. We have established methods to detect and identify lipids from all major M. tuberculosis lipid classes through LC/MS lipid profi ling. This methodology is based on efficient chromatographic separation and automated ion identifi cation through accurate mass determination and searching of a newly created database ( Mtb LipidDB) that contains 2,512 lipid entities. We demonstrate the sensitive detection of molecules representing all known classes of M. tuberculosis lipids from a single crude extract. We also demonstrate the ability of this methodology to identify changes in lipid content in response to cellular growth phases. This work provides a customizable framework and resource to facilitate future studies on mycobacterial lipid biosynthesis and