Accelerating Lipidomic Method Development through in Silico Simulation

LC-ESI-HRMS - lipidomics of phospholipids : Characterization of extraction, chromatography and detection parameters

Lipids are a diverse class of molecules involved in many biological functions including cell signaling or cell membrane assembly. Owing to this relevance, LC-MS/MS-based lipidomics emerged as a major field in modern analytical chemistry. Here, we thoroughly characterized the influence of MS and LC settings - of a Q Exactive HF operated in Full MS/data-dependent MS2 TOP N acquisition mode - in order to optimize the semi-quantification of polar lipids. Optimization of MS-source settings improved the signal intensity by factor 3 compared to default settings. Polar lipids were separated on an ACQUITY Premier CSH C18 reversed-phase column (100 × 2.1 mm, 1.7 µm, 130 Å) during an elution window of 28 min, leading to a sufficient number of both data points across the chromatographic peaks, as well as MS2 spectra. Analysis was carried out in positive and negative ionization mode enabling the detection of a broader spectrum of lipids and to support the structural characterization of lipids. Optimal sample preparation of biological samples was achieved by liquid-liquid extraction using MeOH/MTBE resulting in an excellent extraction recovery > 85% with an intra-day and inter-day variability < 15%. The optimized method was applied on the investigation of changes in the phospholipid pattern in plasma from human subjects supplemented with n3-PUFA (20:5 and 22:6). The strongest increase was observed for lipids bearing 20:5, while 22:4 bearing lipids were lowered. Specifically, LPC 20:5_0:0 and PC 16:0_20:5 were found to be strongest elevated, while PE 18:0_22:4 and PC 18:2_18:2 were decreased by n3-PUFA supplementation. These results were confirmed by targeted LC-MS/MS using commercially available phospholipids as standards.

Simulation of mass spectrometry-based proteomics data with Synthedia

Motivation

A large number of experimental and bioinformatic parameters must be set to identify and quantify peptides in mass spectrometry experiments and each of these will impact the results. An ability to simulate raw data with known contents would allow researchers to rapidly explore the effects of varying experimental parameters and systematically investigate downstream processing software. A range of data simulators are available for established data-dependent acquisition methodologies, but these do not extend to the rapidly developing field of data-independent acquisition (DIA) strategies.

Results

Here, we present Synthedia-a software package to simulate DIA liquid chromatography-mass spectrometry for bottom-up proteomics experiments. Synthedia can generate datasets with known peptide precursor ions and fragments and allows for the customization of a wide variety of chromatographic and mass spectrometry parameters.

Availability and implementation

Synthedia is freely available via the internet and can be used through a graphical website (https://synthedia.org/) or locally via the command line (https://github.com/mgleeming/synthedia/).

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Prioritize biologically relevant ions for data-independent acquisition (BRI-DIA) in LC-MS/MS-based lipidomics analysis

INTRODUCTION

Data-dependent acquisition (DDA) is the most commonly used MS/MS scan method for lipidomics analysis on orbitrap-based instrument. However, MS instrument associated software decide the top N precursors for fragmentation, resulting in stochasticity of precursor selection and compromised consistency and reproducibility. We introduce a novel workflow using biologically relevant lipids to construct inclusion list for data-independent acquisition (DIA), named as BRI-DIA workflow.

OBJECTIVES

To ensure consistent coverage of biologically relevant lipids in LC-MS/MS-based lipidomics analysis.

METHODS

Biologically relevant ion list was constructed based on LIPID MAPS and lipidome atlas in MS-DIAL 4. Lipids were extracted from mouse tissues and used to assess different MS/MS scan workflow (DDA, BRI-DIA, and hybrid mode) on LC-Orbitrap Exploris 480 mass spectrometer.

RESULTS

DDA resulted in more MS/MS events, but the total number of unique lipids identified by three methods (DDA, BRI-DIA, and hybrid MS/MS scan mode) is comparable (580 unique lipids across 44 lipid subclasses in mouse liver). Major cardiolipin molecular species were identified by data generated using BRI-DIA and hybrid methods and allowed calculation of cardiolipin compositions, while identification of the most abundant cardiolipin CL72:8 was missing in data generated using DDA method, leading to wrong calculation of cardiolipin composition.

CONCLUSION

The method of using inclusion list comprised of biologically relevant lipids in DIA MS/MS scan is as efficient as traditional DDA method in profiling lipids, but offers better consistency of lipid identification, compared to DDA method. This study was performed using Orbitrap Exploris 480, and we will further evaluate this workflow on other platforms, and if verified by future work, this biologically relevant ion fragmentation workflow could be routinely used in many studies to improve MS/MS identification capacities.

Optimized Identification of Triacylglycerols in Milk by HPLC-HRMS

This work has developed an optimized workflow for the targeted analysis of triacylglycerols (TAGs) in milk by liquid chromatography coupled with a Q-Exactive Orbitrap mass spectrometer. First, the effects of resolution (17,500; 35,000; 70,000; 140,000) and automatic gain control target (AGC, from 2×104, 2×105, 1×106, and 3×106) have been optimized with the goal to minimize the injection time, maximize the number of scans, and minimize the mass error. Then, the flow rate of the liquid chromatography system was also optimized by maximizing the number of theoretical plates. The resulting optimized parameters consisted of a flow rate of 200 μL/min, mass resolution of 35,000, and AGC target of 2×105. Such optimal conditions were applied for targeted TAG analysis of milk fat extracts. Up to 14 target triglycerides in milk fat were identified performing a data-dependent HPLC-HRMS-MS2 experiment (t-SIM-ddMS2). The findings reported here can be helpful for MS-based lipidomic workflows and targeted milk lipid analysis.

In Silico Method Development of Achiral and Chiral Tandem Column Reversed-phase Liquid Chromatography for Multicomponent Pharmaceutical Mixtures

Tandem column liquid chromatography (LC) is a convenient, cost-effective approach to resolve multicomponent mixtures by serially coupling columns on readily available one-dimensional separation systems without specialized user training. Yet, adoption of this technique remains limited, mainly due to the difficulty in identifying optimal selectivity out of many possible tandem column combinations. At this point, method development and optimization require laborious "hit-or-miss" experimentation and "blind" screening when investigating different column selectivity without standard analytes. As a result, many chromatography practitioners end up combining two columns of similar selectivity, limiting the scope and potential of tandem column LC as a mainstay for industrial applications. To circumvent this challenge, we herein introduce a straightforward in silico multifactorial approach as a framework to expediently map the separation landscape across multiple tandem columns (achiral and chiral) and eluent combinations (isocratic and gradient elution) under reversed-phase LC conditions. Retention models were built using commercially available LC simulator software showcasing less than 2% difference between experimental and simulated retention times for analytes of interest in multicomponent pharmaceutical mixtures (e.g., metabolites and cyclic peptides).

Data Processing of Product Ion Spectra: Quality Improvement by Averaging Multiple Similar Spectra of Small Molecules

In metabolomics studies using high-resolution mass spectrometry (MS), a set of product ion spectra is comprehensively acquired from observed ions using the data-dependent acquisition (DDA) mode of various tandem MS. However, especially for low-intensity signals, it is sometimes difficult to distinguish artifact signals from true fragment ions derived from a precursor ion. Inadequate precision in the measured m/z value is also one of the bottlenecks to narrowing down the candidate compositional formula. In this study, we report that averaging multiple product ion spectra can improve m/z precision as well as the reliability of fragment ions that are observed in such spectra. A graph-based method was applied to cluster a set of similar spectra from multiple DDA data files resulting in creating an averaged product-ion spectrum. The error levels for the m/z values declined following the central limit theorem, which allowed us to reduce the number of candidate compositional formulas. The improved reliability and precision of the averaged spectra will contribute to a more efficient annotation of product ion spectral data.

In-silico-library-based method enables rapid and comprehensive annotation of cardiolipins and cardiolipin oxidation products using high resolution tandem mass spectrometer

Accumulated evidences suggest that cardiolipins (CLs) and cardiolipin oxidation products (oxCLs) are a class of essential molecules that play critical roles in many physiological functions. Diversity of four acyl chains leads to high structure complexity for cardiolipin species including CLs, monolysocardiolipins (MLCLs) and their oxCLs. The ability to rapidly identify CL species can be implemented by the match of mass spectrometry (MS)-based in-silico spectral database. In this study, after optimizing the chromatography conditions and MS detection, an in-silico library containing 377,754 simulated tandem mass spectra deducing from 31,578 CLs to 52,160 of MLCLs was successfully augmented based on LipidBlast templates. For the construction of the oxCLs' library, twenty-five fatty acyls oxidation products relating to nine oxidation types were permuted and combined. A total of 42,180 oxCL spectra were predicted based on the experimental measurements of oxCLs forming by artificially oxidation. Applying the in-silico database to murine mitochondria and cell samples enabled the sensitive and comprehensive annotation of 86 MLCLs, 307 CLs and 112 oxCLs with high annotation confidence. Compared to the conventional method, our proposed in-silico database provides a more comprehensive interpretation for CL species' characterization with high throughput and sensitivity in nontarget lipidomic study.

The role of lipids in exosome biology and intercellular communication: Function, analytics and applications

Exosomes are extracellular vesicles that in recent years have received special attention for their regulatory functions in numerous biological processes. Recent evidence suggests a correlation between the composition of exosomes in body fluids and the progression of some disorders, such as cancer, diabetes and neurodegenerative diseases. In consequence, numerous studies have been performed to evaluate the composition of these vesicles, aiming to develop new biomarkers for diagnosis and to find novel therapeutic targets. On their part, lipids represent one of the most important components of exosomes, with important structural and regulatory functions during exosome biogenesis, release, targeting and cellular uptake. Therefore, exosome lipidomics has emerged as an innovative discipline for the discovery of novel lipid species with biomedical applications. This review summarizes the current knowledge about exosome lipids and their roles in exosome biology and intercellular communication. Furthermore, it presents the state-of-the-art analytical procedures used in exosome lipidomics while emphasizing how this emerging discipline is providing new insights for future applications of exosome lipids in biomedicine.