High Throughput Lipid Identification and Quantification Using a Directed HRAM LC-MS-MS approach on a Modified Quadrupole-Orbitrap Mass Spectrometer

Importance of the topic

Mass-spectrometry-based lipidomics provides molecular-level insight into metabolic states relevant to disease, toxicology and systems biology. Combining broad discovery with reliable quantitation in one high-throughput LC-MS/MS run addresses a major bottleneck: efficient detection of low-abundance lipids while providing concentration estimates for many lipid species. The directed high-resolution accurate-mass (HRAM) LC-MS/MS strategy presented here aims to merge untargeted coverage and targeted quantitation to support biomarker discovery and cross-study comparability.

Objectives and overview of the study

The primary goals were to develop a robust, reproducible HPLC LC-MS/MS workflow on a quadrupole–Orbitrap platform that:

• Provides deep, untargeted lipid identification across complex samples (e.g., human plasma).
• Delivers estimated concentrations for a large number of identified lipid species in the same single run by using isotopically labeled internal standards.
• Maintains high throughput and sensitivity, including low-abundance species.

To achieve this, the authors implemented a very large, in-silico inclusion list to direct MS/MS acquisition while retaining the ability to identify lipids not present on the list.

Methodology

Samples and preparation:
The method was demonstrated on bovine heart total lipid extract and two human EDTA plasma samples (control and diabetic). An isotopically labeled standard mixture (SPLASH Lipidomix) was spiked into samples prior to extraction. Lipids were extracted using a chloroform–methanol–water protocol, dried and reconstituted in IPA/MeOH (1:1).

Chromatography:
Reversed-phase separations employed a Vanquish UHPLC with an Accucore C30 column (2.1 × 150 mm, 2.6 µm) at 45 °C and 260 µL/min. Mobile phase A: 60:40 acetonitrile:water; B: 90:10 isopropanol:acetonitrile; both containing 10 mM ammonium formate and 0.1% formic acid. Injection volumes were small (2–3 µL) to support peak capacity and throughput.

Directed MS/MS acquisition strategy:
A large inclusion list (≈4,089 entries: ~4,074 predicted lipid precursor ions plus 14 isotopic standards) was generated in-silico using LipidSearch software. During LC-MS/MS the instrument prioritized MS/MS acquisition for detected precursors present in the inclusion list in order of intensity, while still allowing MS/MS of other observed ions to enable discovery of unknown lipids. Data-dependent MS2 (Top20) with HRAM Orbitrap detection and short injection times was used to preserve cycle time and capture many co-eluting species.

Data processing and quantitation:
LipidSearch 4.1 SP2 software performed lipid identification and peak-area extraction. Estimated concentrations were calculated relative to the known amounts of the isotopically labeled SPLASH standards, producing class-based semi-quantitative values for identified species across multiple lipid classes.

Used instrumention

Key hardware and software components used in the workflow include:

• Thermo Scientific Q Exactive HF-X hybrid quadrupole–Orbitrap mass spectrometer (and comparative data on Q Exactive HF).
• Thermo Scientific Vanquish UHPLC system.
• Accucore C30 column (2.1 × 150 mm, 2.6 µm).
• SPLASH Lipidomix isotopically labeled lipid standard (Avanti Polar Lipids).
• LipidSearch 4.1 SP2 software for inclusion-list generation, identification and quantitation.

Main results and discussion

Identification and coverage:
The directed HRAM LC-MS/MS workflow achieved deep lipidome coverage in plasma. Using the brighter ion source and improved ion transfer of the Q Exactive HF-X platform resulted in higher identification rates compared with the Q Exactive HF (the HF-X gave ≈18% more identified molecular lipid species in the test comparison). The approach detected and identified approximately 1,244 lipid molecular species after quality filtering.

Quantitation and precision:
Estimated concentrations were assigned for well over one thousand identified lipids across major classes (reported values vary across sections of the source document; approximately 1,100–1,200 species are stated as having estimated concentration results). The workflow achieved good reproducibility: many lipid species had coefficients of variation (CV) <30% across replicates, and a spiked deuterated PE standard showed CVs around 5% (demonstrating good intra-assay precision). For phosphatidylethanolamine (PE) species the reported LOD/LOQ reached approximately 2 ng/mL.

Detection of low-abundance and unknown lipids:
By prioritizing MS/MS acquisition for a comprehensive inclusion list, the method triggered MS/MS on very low-abundance precursors that otherwise might be missed, producing high-quality fragment spectra sufficient for confident annotation (example: low-abundance PS species identified by rich MS2 spectra). The workflow retained capacity to identify lipids not present in the inclusion list, enabling untargeted discovery alongside targeted coverage.

Throughput and run design:
The method targets high throughput by using short ion injection times and efficient MS/MS scheduling to keep cycle time low while maximizing the number of MS/MS events per chromatographic peak.

Benefits and practical applications

Practical advantages of this directed HRAM LC-MS/MS approach include:

• Simultaneous broad identification and class-based concentration estimation in a single LC-MS/MS run, reducing need for separate targeted assays.
• Improved detection of low-abundance lipids via inclusion-list-directed MS/MS acquisition.
• Use of a commercial isotopic standard (SPLASH) supports comparability across labs and studies for semi-quantitative results.
• Applicability to a range of complex biological matrices: plasma, serum, tissues, cells, food.

Limitations and critical considerations

While the workflow provides estimated concentrations, these are relative to class-level isotopic standards and are not fully absolute without compound-specific calibration. Biases due to differential ionization, isomeric overlap, and class-dependent response factors remain considerations. The success of identification still depends on MS2 spectral quality and chromatographic resolution; some isomeric discrimination may be limited without additional targeted methods or ion-mobility/LC orthogonality.

Future trends and potential uses

Future developments that would complement and extend this workflow include:

• Integration of ion mobility or isomer-resolving separations to better resolve structural isomers.
• Expanded isotopic standard suites covering more lipid subclasses for improved absolute quantitation.
• Automated, cloud-enabled data processing and spectral libraries to speed identification and inter-laboratory harmonization.
• Application to larger cohort studies and clinical validation pipelines for biomarker discovery and verification.

Conclusion

The directed HRAM LC-MS/MS workflow on a quadrupole–Orbitrap platform combines a large in-silico inclusion list, isotopic internal standards and efficient MS/MS scheduling to deliver deep lipidome coverage and class-based concentration estimates in a single high-throughput run. The approach demonstrated identification of ~1,200+ lipid species with acceptable precision and sensitivity (PE LOD/LOQ ≈2 ng/mL) and is applicable to diverse biological matrices. Although concentration results are semi-quantitative and depend on class-level standards, the workflow provides a practical balance between discovery and screening that enhances throughput and comparability for lipidomics studies.