Guiding the choice of informatics software and tools for lipidomics research applications.

Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.

Nonalcoholic fatty liver disease stratification by liver lipidomics.

Nonalcoholic fatty liver disease (NAFLD) is a common metabolic dysfunction leading to hepatic steatosis. However, NAFLD's global impact on the liver lipidome is poorly understood. Using high-resolution shotgun mass spectrometry, we quantified the molar abundance of 316 species from 22 major lipid classes in liver biopsies of 365 patients, including nonsteatotic patients with normal or excessive weight, patients diagnosed with NAFL (nonalcoholic fatty liver) or NASH (nonalcoholic steatohepatitis), and patients bearing common mutations of NAFLD-related protein factors. We confirmed the progressive accumulation of di- and triacylglycerols and cholesteryl esters in the liver of NAFL and NASH patients, while the bulk composition of glycerophospho- and sphingolipids remained unchanged. Further stratification by biclustering analysis identified sphingomyelin species comprising n24:2 fatty acid moieties as membrane lipid markers of NAFLD. Normalized relative abundance of sphingomyelins SM 43:3;2 and SM 43:1;2 containing n24:2 and n24:0 fatty acid moieties, respectively, showed opposite trends during NAFLD progression and distinguished NAFL and NASH lipidomes from the lipidome of nonsteatotic livers. Together with several glycerophospholipids containing a C22:6 fatty acid moiety, these lipids serve as markers of early and advanced stages of NAFL.

Shotgun lipidomics-based characterization of the landscape of lipid metabolism in colorectal cancer.

Solid tumors are characterized by global metabolic alterations which contribute to their growth and progression. Altered gene expression profiles and plasma lipid composition suggested a role for metabolic reprogramming in colorectal cancer (CRC) development. However, a conclusive picture of CRC-associated lipidome alterations in the tumor tissue has not emerged. Here, we determined molar abundances of 342 species from 20 lipid classes in matched biopsies of CRC and adjacent normal mucosa. We demonstrate that in contrast to previous reports, CRC shows a largely preserved lipidome composition that resembles that of normal colonic mucosa. Important exceptions include increased levels of lyso-phosphatidylinositols in CRC and reduced abundance of ether phospholipids in advanced stages of CRC. As such, our observations challenge the concept of widespread alterations in lipid metabolism in CRC and rather suggest changes in the cellular lipid profile that are limited to selected lipids involved in signaling and the scavenging of reactive oxygen species.

Quantitative Fragmentation Model for Bottom-Up Shotgun Lipidomics.

Quantitative bottom-up shotgun lipidomics relies on molecular species-specific "signature" fragments consistently detectable in tandem mass spectra of analytes and standards. Molecular species of glycerophospholipids are typically quantified using carboxylate fragments of their fatty acid moieties produced by higher-energy collisional dissociation of their molecular anions. However, employing standards whose fatty acids moieties are similar, yet not identical, to the target lipids could severely compromise their quantification. We developed a generic and portable fragmentation model implemented in the open-source LipidXte software that harmonizes the abundances of carboxylate anion fragments originating from fatty acid moieties having different sn-1/2 positions at the glycerol backbone, length of the hydrocarbon chain, and number and location of double bonds. The postacquisition adjustment enables unbiased absolute (molar) quantification of glycerophospholipid species independent of instrument settings, collision energy, and employed internal standards.

Intensity-Independent Noise Filtering in FT MS and FT MS/MS Spectra for Shotgun Lipidomics.

Shotgun lipidomics relies on the direct infusion of total lipid extracts into a high resolution tandem mass spectrometer. A single shotgun analysis produces several hundred of densely populated FT MS and FT MS/MS spectra, each of which might comprise thousands of peaks although a very small percentage of those belong to lipids. Eliminating noise by adjusting a minimal peak intensity threshold is biased and inefficient since lipid species and classes vary in their natural abundance and ionization capacity. We developed a method of peak intensity-independent noise filtering in shotgun FT MS and FT MS/MS spectra that capitalizes on a stable composition of the infused analyte leading to consistent time-independent detection of its bona fide components. Repetition rate filtering relies on a single quantitative measure of peaks detection reproducibility irrespectively of their absolute intensities, masses, or assumed elemental compositions. In comparative experiments, it removed more than 95% of signals detectable in shotgun spectra without compromising the accuracy and scope of lipid identification and quantification. It also accelerated spectra processing by 15-fold and increased the number of simultaneously processed spectra by ∼500-fold hence eliminating the major bottleneck in high-throughput bottom-up shotgun lipidomics.