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.

Feature-based molecular networking in the GNPS analysis environment.

Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry.

Tattoo Pigment Identification in Inks and Skin Biopsies of Adverse Reactions by Complementary Elemental and Molecular Bioimaging with Mass Spectral Library Matching.

Tattooing has become increasingly popular throughout society. Despite the recognized issue of adverse reactions in tattoos, regulations remain challenging with limited data available and a missing positive list. The diverse chemical properties of mostly insoluble inorganic and organic pigments pose an outstanding analytical challenge, which typically requires extensive sample preparation. Here, we present a multimodal bioimaging approach combining micro X-ray fluorescence (µXRF) and laser desorption ionization-mass spectrometry (LDI-MS) to detect the elemental and molecular composition in the same sample. The pigment structures directly absorb the laser energy, eliminating the need for matrix application. A computational data processing workflow clusters spatially resolved LDI-MS scans to merge redundant information into consensus spectra, which are then matched against new open mass spectral libraries of tattoo pigments. When applied to 13 tattoo inks and 68 skin samples from skin biopsies in adverse tattoo reactions, characteristic signal patterns of isotopes, ion adducts, and in-source fragments in LDI-MS1 scans yielded confident compound annotations across various pigment classes. Combined with µXRF, pigment annotations were achieved for all skin samples with 14 unique structures and 2 inorganic pigments, emphasizing the applicability to larger studies. The tattoo-specific spectral libraries and further information are available on the tattoo-analysis.github.io website.

Complementing Matrix-Assisted Laser Desorption Ionization-Mass Spectrometry Imaging with Chromatography Data for Improved Assignment of Isobaric and Isomeric Phospholipids Utilizing Trapped Ion Mobility-Mass Spectrometry.

Lipids, such for example the multifaceted category of glycerophospholipids (GP), play a major role in many biological processes. High-resolution mass spectrometry is able to identify these highly diverse lipid species in combination with fragmentation experiments (MS/MS) on the basis of the accurate m/z and fragmentation pattern. However, for the differentiation of isomeric lipids or isobaric interferences, more elaborate separation methods are required. Especially for imaging techniques, such as matrix-assisted laser desorption/ionization (MALDI)-MS imaging, the identification is often exclusively based on the accurate m/z. Fragmentation via MS/MS increases the confidence in lipid annotation in imaging approaches. However, this is sometimes not feasible due to insufficient sensitivity and significantly prolonged analysis time. The use of a separation dimension such as trapped ion mobility spectrometry (TIMS) after ionization strengthens the confidence of the identification based on the collision cross section (CCS). Since CCS libraries are limited, a tissue-specific database was initially generated using hydrophilic interaction liquid chromatography-TIMS-MS. Using this database, the identification of isomeric lipid classes as well as isobaric interferences in a lipid class was performed using a mouse spleen sample in a workflow described in this study. Besides a CCS-based identification as an additional identification criterion for GP in general, the focus was on the distinction of the isomeric GP classes phosphatidylglycerol and bis(monoacylglycero)phosphate, as well as the differentiation of possible isobaric interferences based on the formation of adducts by MALDI-TIMS-MS imaging on a molecular level.

Comparison of lipidome profiles of Caenorhabditis elegans-results from an inter-laboratory ring trial.

INTRODUCTION: Lipidomic profiling allows 100s if not 1000s of lipids in a sample to be detected and quantified. Modern lipidomics techniques are ultra-sensitive assays that enable the discovery of novel biomarkers in a variety of fields and provide new insight in mechanistic investigations. Despite much progress in lipidomics, there remains, as for all high throughput "omics" strategies, the need to develop strategies to standardize and integrate quality control into studies in order to enhance robustness, reproducibility, and usability of studies within specific fields and beyond. OBJECTIVES: We aimed to understand how much results from lipid profiling in the model organism Caenorhabditis elegans are influenced by different culture conditions in different laboratories. METHODS: In this work we have undertaken an inter-laboratory study, comparing the lipid profiles of N2 wild type C. elegans and daf-2(e1370) mutants lacking a functional insulin receptor. Sample were collected from worms grown in four separate laboratories under standardized growth conditions. We used an UPLC-UHR-ToF-MS system allowing chromatographic separation before MS analysis. RESULTS: We found common qualitative changes in several marker lipids in samples from the individual laboratories. On the other hand, even in this controlled experimental system, the exact fold-changes for each marker varied between laboratories. CONCLUSION: Our results thus reveal a serious limitation to the reproducibility of current lipid profiling experiments and reveal challenges to the integration of such data from different laboratories.

Expanding the Kendrick Mass Plot Toolbox in MZmine 2 to Enable Rapid Polymer Characterization in Liquid Chromatography-Mass Spectrometry Data Sets.

Technological advances in mass spectrometry (MS) toward more accurate and faster data acquisition result in highly informative but also more complex data sets. Especially the hyphenation of liquid chromatography (LC) and MS yields large data files containing a high amount of compound specific information. Using electrospray-ionization for compounds such as polymers enables highly sensitive detection, yet results in very complex spectra, containing multiply charged ions and adducts. Recent years have seen the development of novel or updated data mining strategies to reduce the MS spectra complexity and to ultimately simplify the data analysis workflow. Among other techniques, the Kendrick mass defect analysis, which graphically highlights compounds containing a given repeating unit, has been revitalized with applications in multiple fields of study, such as lipids and polymers. Especially for the latter, various data mining concepts have been developed, which extend regular Kendrick mass defect analysis to multiply charged ion series. The aim of this work is to collect and subsequently implement these concepts in one of the most popular open-source MS data mining software, i.e., MZmine 2, to make them rapidly available for different MS based measurement techniques and various vendor formats, with a special focus on hyphenated techniques such as LC-MS. In combination with already existing data mining modules, an example data set was processed and simplified, enabling an ever faster evaluation and polymer characterization.

Analysis of artificially oxidized cardiolipins and monolyso-cardiolipins via liquid chromatography/high-resolution mass spectrometry and Kendrick mass defect plots after hydrophilic interaction liquid chromatography based sample preparation.

RATIONALE: Cardiolipins (CL) are a special lipid class which plays a main role in energy metabolism in mitochondria and is involved in apoptosis. In contrast to other glycerophospholipids, they contain four fatty acyl residues which results in a high structural diversity. Oxidation, for example by reactive oxygen species, or lyso forms such as monolyso-CL (MLCL), increases this diversity. Mass spectrometric analysis and computational identification of CL, MLCL and their oxidation products is therefore a challenging task. METHODS: In order to distinguish CL, MLCL and their oxidation products, a liquid chromatography/tandem mass spectrometry (LC/MS/MS) method was developed. A hydrophilic interaction liquid chromatography (HILIC)-based solid-phase extraction (SPE) clean-up approach was developed for CL enrichment. Graphical analysis of CL, MLCL and their oxidation products was carried out by a three-dimensional Kendrick mass defect (3D-KMD) plot module, as well as a refined lipid search module of the open-source metabolomics data mining software MZmine 2. RESULTS: The HILIC-based SPE clean-up enabled complete separation of polar and nonpolar lipid classes. A yeast (Saccharomyces cerevisiae) lipid extract, which was artificially oxidized by means of the Fenton reaction, was analyzed by the developed LC/MS/MS method. CL species with differences in chain length and degree of unsaturation have been separated by high-performance liquid chromatography (HPLC). In total 66 CL, MLCL and oxidized species have been identified utilizing 3D-KMD plots in combination with database matching using MZmine 2. For further characterization of annotated species, MS/MS experiments have been utilized. CONCLUSIONS: 3D-KMD plots capturing chromatographic and high-resolution mass spectrometry data have been successfully used for graphical identification of CL, MLCL as well as their oxidized species. Therefore, we chose multiple KMD bases such as hydrogen and oxygen to visualize the degree of unsaturation and oxidation capturing chromatographic data by means of a color-coded paint scale as the third dimension. In combination with database matching, the analysis of low concentrated lipid species in complex samples has been significantly improved.

Lipid Species Annotation at Double Bond Position Level with Custom Databases by Extension of the MZmine 2 Open-Source Software Package.

In recent years, proprietary and open-source bioinformatics software tools have been developed for the identification of lipids in complex biological samples based on high-resolution mass spectrometry data. These existent software tools often rely on publicly available lipid databases, such as LIPID MAPS, which, in some cases, only contain a limited number of lipid species for a specific lipid class. Other software solutions implement their own lipid species databases, which are often confined regarding implemented lipid classes, such as phospholipids. To address these drawbacks, we provide an extension of the widely used open-source metabolomics software MZmine 2, which enables the annotation of detected chromatographic features as lipid species. The extension is designed for straightforward generation of a custom database for selected lipid classes. Furthermore, each lipid's sum formula of the created database can be rapidly modified to search for derivatization products, oxidation products, in-source fragments, or adducts. The versatility will be exemplified by a liquid chromatography-high resolution mass spectrometry data set with postcolumn Paternò-Büchi derivatization. The derivatization reaction was performed to pinpoint the double bond positions in diacylglyceryltrimethylhomoserine lipid species in a lipid extract of a green algae ( Chlamydomonas reinhardtii) sample. The developed Lipid Search module extension of MZmine 2 supports the identification of lipids as far as double bond position level.

Three-dimensional Kendrick mass plots as a tool for graphical lipid identification.

RATIONALE: The rising field of lipidomics strongly relies on the identification of lipids in complex matrices. Recent technical advances regarding liquid chromatography (LC) and high-resolution mass spectrometry (HRMS) enable the mapping of the lipidome of an organism with short data acquisition times. However, interpretation and evaluation of resulting multidimensional datasets are challenging and this is still the bottleneck regarding overall analysis times. METHODS: A novel adaption of Kendrick mass plot analysis is presented for a rapid and accurate analysis of lipids in complex matrices. Separation of lipids by their respective head group was achieved via hydrophilic interaction liquid chromatography (HILIC) coupled to HRMS. The resulting LC/HRMS datasets are processed to a list of chromatographically separated features by applying an optimized MZmine 2 workflow. All features are plotted in a three-dimensional Kendrick mass plot, which allows a fast identification of present lipid classes, based on equidistant features with fitting retention times and the same Kendrick mass defect. Suspected lipid classes are used for exact mass database matching to annotate features. A second three-dimensional Kendrick mass plot of annotated features of a single lipid class helps to reveal potential database mismatches, resulting in a curated list of identified lipid species. RESULTS: The use of the novel adaption of the Kendrick mass plot has accelerated the identification of the relevant lipid species in the green alga Chlamydomonas reinhardtii. A total of 106 species were identified within the lipid classes: phosphatidylserine, phosphatidylethanolamine, phosphatidylglycerol, phosphatidylinositol, monogalactosyldiacylglycerol, digalactosyldiacylglycerol, and sulfoquinovosyldiacylglycerol. CONCLUSIONS: This work shows how the addition of chromatographic information, i.e. the retention time, to a classical two-dimensional Kendrick mass plot enables rapid and accurate analysis of LC/HRMS datasets, exemplified on a green alga (C. reinhardtii) sample. Three-dimensional Kendrick mass plots have improved lipid class identification and fast spotting of falsely annotated lipid species.

Screening of semifluorinated n-alkanes by gas chromatography coupled to dielectric barrier discharge ionization mass spectrometry.

RATIONALE: The potential of an atmospheric pressure ionization source based on a dielectric barrier discharge in helium for the hyphenation of gas chromatography and mass spectrometry (GC/DBDI-MS) has been demonstrated only recently and for a limited range of compounds. Due to its 'soft' ionization properties and the possibility to choose from a variety of atmospheric pressure ionization MS instruments, GC/DBDI-MS has the potential to be an interesting alternative to 'classic' GC/MS techniques. METHODS: The hyphenation of GC with DBDI-MS at atmospheric pressure is used for the determination of semifluorinated n-alkanes in ski wax samples. RESULTS: Different to perfluorinated n-alkanes, which are typically detected as [M - F + O]- and [M - F]- , semifluorinated n-alkanes can be detected both in positive mode as [M - 3H + nO]+ and [M - H + nO]+ (n = 0, 1, 2, and 3) ions, as well as in negative mode as a fragment ion representing the fluorinated part of the respective semifluorinated n-alkane. The method allowed the sensitive detection of semifluorinated n-alkanes with achievable limits of detection (LODs) in the single digit pg range injected on column. To examine the applicability of the GC/DBDI-MS method, semifluorinated n-alkanes were determined in fluorinated ski waxes. Results were confirmed by complimentary GC/electron ionization MS measurements. CONCLUSIONS: The unique SFA ionization patterns serve for complementary unambiguous identification of semifluorinated n-alkane species in positive mode and screening of contained n-alkanes fluorinated chain lengths in negative mode.

Reproducible mass spectrometry data processing and compound annotation in MZmine 3.

Untargeted mass spectrometry (MS) experiments produce complex, multidimensional data that are practically impossible to investigate manually. For this reason, computational pipelines are needed to extract relevant information from raw spectral data and convert it into a more comprehensible format. Depending on the sample type and/or goal of the study, a variety of MS platforms can be used for such analysis. MZmine is an open-source software for the processing of raw spectral data generated by different MS platforms. Examples include liquid chromatography-MS, gas chromatography-MS and MS-imaging. These data might typically be associated with various applications including metabolomics and lipidomics. Moreover, the third version of the software, described herein, supports the processing of ion mobility spectrometry (IMS) data. The present protocol provides three distinct procedures to perform feature detection and annotation of untargeted MS data produced by different instrumental setups: liquid chromatography-(IMS-)MS, gas chromatography-MS and (IMS-)MS imaging. For training purposes, example datasets are provided together with configuration batch files (i.e., list of processing steps and parameters) to allow new users to easily replicate the described workflows. Depending on the number of data files and available computing resources, we anticipate this to take between 2 and 24 h for new MZmine users and nonexperts. Within each procedure, we provide a detailed description for all processing parameters together with instructions/recommendations for their optimization. The main generated outputs are represented by aligned feature tables and fragmentation spectra lists that can be used by other third-party tools for further downstream analysis.

On-tissue dataset-dependent MALDI-TIMS-MS2 bioimaging.

Trapped ion mobility spectrometry (TIMS) adds an additional separation dimension to mass spectrometry (MS) imaging, however, the lack of fragmentation spectra (MS2) impedes confident compound annotation in spatial metabolomics. Here, we describe spatial ion mobility-scheduled exhaustive fragmentation (SIMSEF), a dataset-dependent acquisition strategy that augments TIMS-MS imaging datasets with MS2 spectra. The fragmentation experiments are systematically distributed across the sample and scheduled for multiple collision energies per precursor ion. Extendable data processing and evaluation workflows are implemented into the open source software MZmine. The workflow and annotation capabilities are demonstrated on rat brain tissue thin sections, measured by matrix-assisted laser desorption/ionisation (MALDI)-TIMS-MS, where SIMSEF enables on-tissue compound annotation through spectral library matching and rule-based lipid annotation within MZmine and maps the (un)known chemical space by molecular networking. The SIMSEF algorithm and data analysis pipelines are open source and modular to provide a community resource.

Ion identity molecular networking for mass spectrometry-based metabolomics in the GNPS environment.

Molecular networking connects mass spectra of molecules based on the similarity of their fragmentation patterns. However, during ionization, molecules commonly form multiple ion species with different fragmentation behavior. As a result, the fragmentation spectra of these ion species often remain unconnected in tandem mass spectrometry-based molecular networks, leading to redundant and disconnected sub-networks of the same compound classes. To overcome this bottleneck, we develop Ion Identity Molecular Networking (IIMN) that integrates chromatographic peak shape correlation analysis into molecular networks to connect and collapse different ion species of the same molecule. The new feature relationships improve network connectivity for structurally related molecules, can be used to reveal unknown ion-ligand complexes, enhance annotation within molecular networks, and facilitate the expansion of spectral reference libraries. IIMN is integrated into various open source feature finding tools and the GNPS environment. Moreover, IIMN-based spectral libraries with a broad coverage of ion species are publicly available.

Mass spectrometric investigation of cardiolipins and their oxidation products after two-dimensional heart-cut liquid chromatography.

The anionic phospholipid class of cardiolipins (CL) is increasingly attracting scientific attention in the recent years. CL can be found as a functional component of mitochondrial membranes in almost all living organisms. Changes in the CL composition are favored by oxidative stress. Based on this finding, the investigation of CL and their oxidation products in relation to various disease patterns, including neurodegenerative ones, is moving into the focus of current research. The analysis of this diverse lipid class is still challenging and requires sensitive and selective methods. In this work, we demonstrate an online two-dimensional liquid chromatography (2D-LC) approach by means of a heart-cut setup. In the first dimension, a fast hydrophilic interaction liquid chromatography (HILIC) method was developed for the separation of CL and their oxidation products from other phospholipid classes, but more important from nonpolar lipid classes, such as triacylglycerol and cholesterol. Those classes can negatively affect the electrospray ionization and also the chromatography. For the heart-cut approach, the CL fraction was selectively transferred to a loop using a six-port valve followed by the transfer to a reversed phase (RP) column in second dimension. On the RP column, the transferred CL fraction including the oxidation products were separated according to the hydrophobicity of acyl chain moieties. Matrix effects were significantly reduced compared to the one-dimensional LC-MS method. In addition, the total separation time had not to be prolonged by shifting the equilibration step of the RP column parallel to the separation in first dimension. The heart-cut LC-LC approach was applied to artificially oxidized lipid extracts of bovine heart and yeast by means of Fenton reaction. In summary, 42 species have been identified by high resolution mass spectrometry and database matching. 31 species thereof have been further characterized by MS/MS experiments.

Digging deeper - A new data mining workflow for improved processing and interpretation of high resolution GC-Q-TOF MS data in archaeological research.

Gas chromatography-mass spectrometry profiling is the most established method for the analysis of organic residues, particularly lipids, from archaeological contexts. This technique allows the decryption of hidden chemical information associated with archaeological artefacts, such as ceramic pottery fragments. The molecular and isotopic compositions of such residues can be used to reconstruct past resource use, and hence address major questions relating to patterns of subsistence, diet and ritual practices in the past. A targeted data analysis approach, based on previous findings reported in the literature is common but greatly depends on the investigator's prior knowledge of specific compound classes and their mass spectrometric behaviour, and poses the risk of missing unknown, potentially diagnostic compounds. Organic residues from post-prehistoric archaeological samples often lead to highly complex chromatograms, which makes manual chromatogram inspection very tedious and time consuming, especially for large datasets. This poses a significant limitation regarding the scale and interpretative scopes of such projects. Therefore, we have developed a non-targeted data mining workflow to extract a higher number of known and unknown compounds from the raw data to reduce investigator's bias and to vastly accelerate overall analysis time. The workflow covers all steps from raw data handling, feature selection, and compound identification up to statistical interpretation.

Lipid profiling and analytical discrimination of seven cereals using high temperature gas chromatography coupled to high resolution quadrupole time-of-flight mass spectrometry.

Minor lipids in cereals (such as phytosterols and alkylresorcinols) can be important for human nutrition and/or be used as biomarkers for cereal intake. However, the analysis of cereal lipids is very challenging due to the complex lipidome comprising several hundred individual compounds present over a wide range of concentrations. Here we present a method for the profiling of cereal lipids using high temperature gas chromatography coupled to high resolution mass spectrometry (GC/Q-TOF MS). The method was used to investigate the lipid profiles of 77 samples of bread wheat, spelt, einkorn, emmer, barley, rye and oats. Distinct differences in the patterns of alkylresorcinols, free and conjugated sterols and tocopherols between the cereals could be observed. Furthermore, traces of tocomonoenols and diunsaturated and methyl-alkylresorcinols (not previously reported in cereals) could be detected. Finally, the lipid patterns in the cereals could be used to separate the cereals by Principal Component Analysis.