Two-dimensional liquid chromatography-mass spectrometry for lipidomics using off-line coupling of hydrophilic interaction liquid chromatography with 50 cm long reversed phase capillary columns

Transformative potentials, challenges and innovative solutions of lipidomics in multiple clinical applications

Lipidomics, a rapidly evolving field within metabolomics, provides comprehensive insights into lipid profiles and their roles in health and disease. Advances in lipidomics have enabled the discovery of novel biomarkers with significant clinical applications, revolutionizing the diagnosis, prognosis, and therapeutic monitoring of various diseases. Emerging methodologies, including high-resolution mass spectrometry (HRMS), Ion mobility spectrometry (IMS), and Supercritical Fluid Chromatography (SFC) have enhanced lipid identification and quantification with remarkable analytical whip hands. These advancements are complemented by innovative sample preparation techniques ensuring the recovery of diverse lipid species with minimal degradation. Biomarker discovery with lipidomics has illuminated critical pathways in numerous diseases, including cardiovascular disorders, neurodegenerative conditions, metabolic syndromes, and cancers. Specific lipid classes, such as sphingolipids (SLs) and phospholipids (PLs) have been linked to Alzheimer's disease and diabetes, respectively, while oxylipins and eicosanoids are emerging as inflammatory biomarkers. Furthermore, lipidomic profiles have shown promise in personalized medicine, enabling the stratification of patient sub-populations and tailoring treatment strategies. This review emphasizes the latest innovative developments in analytical technologies, advanced sample preparation techniques and challenges for lipidomics research including bioinformatic tools on multiple clinical conditions. By exploring these cutting-edge developments, this review highlights the transformative potential of lipidomics in biomarker discovery across diverse clinical applications.

Accurate Determination of Circulatory Lipids Using a Combination of HILIC-MRM and RPLC-PRM

Circulatory lipids are important markers for characterizing disease phenotypes; however, accurately determining lipid species remains a significant challenge in lipidomic analysis. Here, we present a novel analytical workflow for accurate lipidome characterization in human plasma using mass spectrometry (MS) through the integration of hydrophilic interaction liquid chromatography (HILIC) and reversed-phase liquid chromatography (RPLC). This workflow enables rapid screening of 1,966 lipid species across 18 lipid classes using HILIC-multiple reaction monitoring (MRM), which enables facile identification of lipid species by lipid class-based separations. In the NIST Standard Reference Material for Human Plasma (SRM 1950), 489 lipid species were identified using HILIC-MRM and subsequently analyzed with RPLC-parallel reaction monitoring (PRM) to resolve potential lipid isobars within the same lipid class. Notably, RPLC-PRM identified 70 additional lipidomic features in SRM 1950 that were not detectable with HILIC-MRM. Furthermore, a high correlation (Pearson correlation coefficient = 0.81) was observed regarding the concentrations of lipid species not carrying isobaric interferences in between HILIC-MRM and RPLC-PRM, indicating that the individual lipid concentrations measured by each platform can be integrated. The workflow was further applied to a cohort of 284 human plasma samples from chronic kidney disease (CKD) patients, successfully profiling lipidomic phenotypes across CKD subtypes. These findings demonstrate that combining HILIC-MRM and RPLC-PRM as complementary platforms enhances the accuracy and comprehensiveness of lipidomic analysis.

Comprehensive Optimization of Packing Parameters for Hydraulic-Packed Capillary Columns

RATIONALE

The performance of the capillary column directly impacts the separation efficiency of complex sample in liquid chromatography-mass spectrometry-based proteomics studies. The hydraulic packing system offers an effective solution by reducing packing time and expediting the preparation process of column preparation. However, its operational complexity and strict parameter regulation requirements hinder efficient application.

METHODS

This study developed an innovative device for the hydraulic capillary column packing, followed by a systematic optimization and evaluation of crucial parameters such as packing pressure, magnetic stirring rate, concentration of solid-phase material, and choice of packing solvent in the capillary column packing process.

RESULTS

The comprehensive evaluation of the prepared capillary columns showed that the hydraulic packing method enabled rapid and large-scale preparation, while also demonstrating exceptional stability and reproducibility.

CONCLUSIONS

The proposed hydraulic capillary column packing strategy in this study holds theoretical and practical implications for advancing the technology of column preparation, enhancing separation efficiency, and expanding the depth of analysis in proteomics research.

Four-Dimensional Lipidomic Analysis Using Comprehensive Online UHPLC × UHPSFC/Tandem Mass Spectrometry

Multidimensional chromatography offers enhanced chromatographic resolution and peak capacity, which are crucial for analyzing complex samples. This study presents a novel comprehensive online multidimensional chromatography method for the lipidomic analysis of biological samples, combining lipid class and lipid species separation approaches. The method combines optimized reversed-phase ultrahigh-performance liquid chromatography (RP-UHPLC) in the first dimension, utilizing a 150 mm long C18 column, with ultrahigh-performance supercritical fluid chromatography (UHPSFC) in the second dimension, using a 10 mm long silica column, both with sub-2 μm particles. A key advantage of employing UHPSFC in the second dimension is its ability to perform ultrafast analysis using gradient elution with a sampling time of 0.55 min. This approach offers a significant increase in the peak capacity. Compared to our routinely used 1D methods, the peak capacity of the 4D system is 10 times higher than RP-UHPLC and 18 times higher than UHPSFC. The entire chromatographic system is coupled with a high-resolution quadrupole-time-of-flight (QTOF) mass analyzer using electrospray ionization (ESI) in both full-scan and tandem mass spectrometry (MS/MS) and with positive- and negative-ion polarities, enabling the detailed characterization of the lipidome. The confident identification of lipid species is achieved through characteristic ions in both polarity modes, information from MS elevated energy (MSE) and fast data-dependent analysis scans, and mass accuracy below 5 ppm. This analytical method has been used to characterize the lipidomic profile of the total lipid extract from human plasma, which has led to the identification of 298 lipid species from 16 lipid subclasses.

Considerations for Method Development and Method Translation in Capillary Liquid Chromatography: A Tutorial

HPLC continues to be one of the most widely used measurement techniques for chemical analysis. Capillary LC, which utilizes narrow diameter columns operated at lower flow rates than analytical-scale LC, continues to gain adoption based on its reduced mobile phase consumption and increased sensitivity when coupled to MS detection. This tutorial offers practical insights into the most critical aspects of translating analytical-scale separations to the capillary scale. The selection of pumping systems, detectors, and the potential for performance loss due to extra-column effects are examined within the context of separations using columns with inner diameters ≤ 0.3 mm. Column choices within this diameter range are also detailed, both in terms of stationary phase support options and general commercial availability. The impact of these various factors on the effective development/translation of LC methods down to flow rates under 10 μL/min is described to provide readers with a basis for implementing these strategies within their own analytical workflows.

Top-down proteomics

Proteoforms, which arise from post-translational modifications, genetic polymorphisms and RNA splice variants, play a pivotal role as drivers in biology. Understanding proteoforms is essential to unravel the intricacies of biological systems and bridge the gap between genotypes and phenotypes. By analysing whole proteins without digestion, top-down proteomics (TDP) provides a holistic view of the proteome and can decipher protein function, uncover disease mechanisms and advance precision medicine. This Primer explores TDP, including the underlying principles, recent advances and an outlook on the future. The experimental section discusses instrumentation, sample preparation, intact protein separation, tandem mass spectrometry techniques and data collection. The results section looks at how to decipher raw data, visualize intact protein spectra and unravel data analysis. Additionally, proteoform identification, characterization and quantification are summarized, alongside approaches for statistical analysis. Various applications are described, including the human proteoform project and biomedical, biopharmaceutical and clinical sciences. These are complemented by discussions on measurement reproducibility, limitations and a forward-looking perspective that outlines areas where the field can advance, including potential future applications.

Offline Two-Dimensional Liquid Chromatography-Mass Spectrometry for Deep Annotation of the Fecal Metabolome Following Fecal Microbiota Transplantation

Biological interpretation of untargeted LC-MS-based metabolomics data depends on accurate compound identification, but current techniques fall short of identifying most features that can be detected. The human fecal metabolome is complex, variable, incompletely annotated, and serves as an ideal matrix to evaluate novel compound identification methods. We devised an experimental strategy for compound annotation using multidimensional chromatography and semiautomated feature alignment and applied these methods to study the fecal metabolome in the context of fecal microbiota transplantation (FMT) for recurrent C. difficile infection. Pooled fecal samples were fractionated using semipreparative liquid chromatography and analyzed by an orthogonal LC-MS/MS method. The resulting spectra were searched against commercial, public, and local spectral libraries, and annotations were vetted using retention time alignment and prediction. Multidimensional chromatography yielded more than a 2-fold improvement in identified compounds compared to conventional LC-MS/MS and successfully identified several rare and previously unreported compounds, including novel fatty-acid conjugated bile acid species. Using an automated software-based feature alignment strategy, most metabolites identified by the new approach could be matched to features that were detected but not identified in single-dimensional LC-MS/MS data. Overall, our approach represents a powerful strategy to enhance compound identification and biological insight from untargeted metabolomics data.

Phospholipidomics in Clinical Trials for Brain Disorders: Advancing our Understanding and Therapeutic Potentials

Phospholipidomics is a specialized branch of lipidomics that focuses on the characterization and quantification of phospholipids. By using sensitive analytical techniques, phospholipidomics enables researchers to better understand the metabolism and activities of phospholipids in brain disorders such as Alzheimer's and Parkinson's diseases. In the brain, identifying specific phospholipid biomarkers can offer valuable insights into the underlying molecular features and biochemistry of these diseases through a variety of sensitive analytical techniques. Phospholipidomics has emerged as a promising tool in clinical studies, with immense potential to advance our knowledge of neurological diseases and enhance diagnosis and treatment options for patients. In the present review paper, we discussed numerous applications of phospholipidomics tools in clinical studies, with a particular focus on the neurological field. By exploring phospholipids' functions in neurological diseases and the potential of phospholipidomics in clinical research, we provided valuable insights that could aid researchers and clinicians in harnessing the full prospective of this innovative practice and improve patient outcomes by providing more potent treatments for neurological diseases.

Lipid Wizard: Analysis Software for Comprehensive Two-Dimensional Liquid Chromatography-Mass Spectrometry-Based Lipid Profiling

Lipids play a significant role in life activities and participate in the biological system through different pathways. Although comprehensive two-dimensional liquid chromatography-mass spectrometry (2DLC-MS) has been developed to profile lipid abundance changes, lipid identification and quantification from 2DLC-MS data remain a challenge. We created Lipid Wizard, open-source software for lipid assignment and isotopic peak stripping of the 2DLC-MS data. Lipid Wizard takes the peak list deconvoluted from the 2DLC-MS data as input and assigns each isotopic peak to the lipids recorded in the LIPID MAPS database by precursor ion m/z matching. The matched lipids are then filtered by the first-dimension retention time (1D RT), followed by the second-dimension retention time (2D RT), where the 2D RT of each lipid is predicted using an equivalent carbon number (ECN) model. The remaining assigned lipids are used for isotopic peak stripping via an iterative linear regression. The performance of Lipid Wizard was tested using a set of lipid standards and then applied to study the lipid changes in the livers of mice (fat-1) fed with alcohol.

Preparation of high-efficiency HILIC capillary columns utilizing slurry packing at 2100 bar

Complex mixture analysis requires high-efficiency chromatography columns. Although reversed phase liquid chromatography (RPLC) is the dominant approach for such mixtures, hydrophilic interaction liquid chromatography (HILIC) is an important complement to RPLC by enabling the separation of polar compounds. Chromatography theory predicts that small particles and long columns will yield high efficiency; however, little work has been done to prepare HILIC columns longer than 25 cm packed with sub-2 μm particles. In this work, we tested the slurry packing of 75 cm long HILIC columns with 1.7 μm bridged-ethyl-hybrid amide HILIC particles at 2,100 bar (30,000 PSI). Acetonitrile, methanol, acetone, and water were tested as slurry solvents, with acetonitrile providing the best columns. Slurry concentrations of 50-200 mg/mL were assessed, and while 50-150 mg/mL provided comparable results, the 150 mg/mL columns provided the shortest packing times (9 min). Columns prepared using 150 mg/mL slurries in acetonitrile yielded a reduced minimum plate height (hmin) of 3.3 and an efficiency of 120,000 theoretical plates for acenaphthene, an unretained solute. Para-toluenesulfonic acid produced the lowest hmin of 1.9 and the highest efficiency of 210,000 theoretical plates. These results identify conditions for producing high-efficiency HILIC columns with potential applications to complex mixture analysis.

Two Multidimensional Chromatography/High-Resolution Mass Spectrometry Approaches Enabling the In-Depth Metabolite Characterization Simultaneously from Three Glycyrrhiza Species: Method Development, Comparison, and Integration

Two offline multidimensional chromatography/high-resolution mass spectrometry systems (method 1: fractionation and online two-dimensional liquid chromatography, 2D-LC; method 2: fractionation and offline 2D-LC) were established to characterize the metabolites simultaneously from three Glycyrrhiza species. Ion exchange chromatography in the first-dimensional (1D) separation was well fractionated between the acidic (mainly triterpenoids) and weakly acidic components (flavonoids). These obtained subsamples got sophisticated separation by the second (2D) and third dimension (3D) of chromatography either by online reversed-phase chromatography × reversed-phase chromatography (RPC × RPC) or offline hydrophilic interaction chromatography × RPC (HILIC × RPC). Orthogonality for the 2D/3D separations reached 0.73 for method 1 and 0.81 for method 2, respectively. We could characterize 1097 compounds from three Glycyrrhiza species based on an in-house library and 33 reference standards, involving 618 by method 1 and 668 by method 2, respectively. They exhibited a differentiated performance and complementarity in identifying the multiple subclasses of Glycyrrhiza components.

Offline Two-dimensional Liquid Chromatography-Mass Spectrometry for Deep Annotation of the Fecal Metabolome

Compound identification is an essential task in the workflow of untargeted metabolomics since the interpretation of the data in a biological context depends on the correct assignment of chemical identities to the features it contains. Current techniques fall short of identifying all or even most observable features in untargeted metabolomics data, even after rigorous data cleaning approaches to remove degenerate features are applied. Hence, new strategies are required to annotate the metabolome more deeply and accurately. The human fecal metabolome, which is the focus of substantial biomedical interest, is a more complex, more variable, yet lesser-investigated sample matrix compared to widely studied sample types like human plasma. This manuscript describes a novel experimental strategy using multidimensional chromatography to facilitate compound identification in untargeted metabolomics. Pooled fecal metabolite extract samples were fractionated using offline semi-preparative liquid chromatography. The resulting fractions were analyzed by an orthogonal LC-MS/MS method, and the data were searched against commercial, public, and local spectral libraries. Multidimensional chromatography yielded more than a 3-fold improvement in identified compounds compared to the typical single-dimensional LC-MS/MS approach and successfully identified several rare and novel compounds, including atypical conjugated bile acid species. Most features identified by the new approach could be matched to features that were detectable but not identifiable in the original single-dimension LC-MS data. Overall, our approach represents a powerful strategy for deeper annotation of the metabolome that can be implemented with commercially-available instrumentation, and should apply to any dataset requiring deeper annotation of the metabolome.

Trapping mode two-dimensional liquid chromatography for quantitative low-level impurity enrichment in pharmaceutical development

Trapping mode two-dimensional liquid chromatography (2D-LC) has recently found applications in pharmaceutical analysis to clean, refocus, and enrich analytes. Given its enrichment capability, 2D-LC with multiple trappings is appealing for low-level impurity monitoring that cannot be solved by single dimensional LC (1D-LC) or unenriched 2D-LC analysis. However, the quantitative features of multi-trapping 2D-LC remain largely unknown at impurity levels from parts-per-million (ppm) to 0.15% (w/w). We present a simple heart-cutting trapping mode 2D-LC workflow using only common components and software found in typical off-the-shelf 1D-LC instruments. This robust, turn-key system's quantitative capabilities were evaluated using a variety of standard markers, demonstrating linear enrichment for up to 20 trapping cycles and achieving a recovery of over 97.0%. Next, the trapping system was applied to several real-world low-level impurity pharmaceutical case studies including (1) the identification of two unknown impurities at sub-ppm levels resulting in material discoloration, (2) the discovery of a new impurity at 0.05% (w/w) co-eluted with a known impurity, making the undesired summation above the target specification, and (3) the quantification of a potential mutagenic impurity at 10-ppm level in a poorly soluble substrate. The recovery in all studies was better than 97.0% with RSD lower than 3.0%, demonstrating accuracy and precision of the 2D-LC trapping workflow. As no specialized equipment or software is required, we envision that the system could be used to develop low-impurity monitoring methods suitable for validation and potential execution in quality-control laboratories.