LIPID MAPS Research Articles

Correlative Imaging for Comprehensive Molecular Mapping of Individual Cell Types in Biological Tissues.

Mass spectrometry imaging (MSI) is a powerful technique for label-free spatial mapping of multiple classes of biomolecules in tissue sections. However, differences in desorption and ionization efficiency of different classes of molecules make it challenging to simultaneously map biomolecules at each omics layer in the same tissue sample. Herein, we present a correlative imaging method using nanospray desorption electrospray ionization (nano-DESI) MSI, which enables the spatial mapping of lipids, metabolites, peptides, and proteins with cellular-level spatial resolution in a single tissue section. We demonstrate the molecular profiling of specific cell types and identify truncated peptides in mouse pancreatic tissue. Distinct chemical gradients of peptides and lipids extending from endocrine cells to exocrine cells indicate their different roles in endocrine-exocrine crosstalk and intracellular signaling. The results underscore the power of the developed imaging approach for spatial multi-omics analysis that provides deep insights into cellular diversity and the intricate molecular interactions that occur within heterogenous biological tissues.

Metabolic Pathways of Acylcarnitine Synthesis.

Acylcarnitines are important markers in metabolic studies of many diseases, including metabolic, cardiovascular, and neurological disorders. We reviewed analytical methods for analyzing acylcarnitines with respect to the available molecular structural information, the technical limitations of legacy methods, and the potential of new mass spectrometry-based techniques to provide new information on metabolite structure. We summarized the nomenclature of acylcarnitines based on historical common names and common abbreviations, and we propose the use of systematic abbreviations derived from the shorthand notation for lipid structures. The transition to systematic nomenclature will facilitate acylcarnitine annotation, reporting, and standardization in metabolomics. We have reviewed the metabolic origins of acylcarnitines important for the biological interpretation of human metabolomic profiles. We identified neglected isomers of acylcarnitines and summarized the metabolic pathways involved in the synthesis and degradation of acylcarnitines, including branched-chain lipids and amino acids. We reviewed the primary literature, mapped the metabolic transformations of acyl-CoAs to acylcarnitines, and created a freely available WikiPathway WP5423 to help researchers navigate the acylcarnitine field. The WikiPathway was curated, metabolites and metabolic reactions were annotated, and references were included. We also provide a table for conversion between common names and abbreviations and systematic abbreviations linked to the LIPID MAPS or Human Metabolome Database.

In Silico Screening Identification of Fatty Acids and Fatty Acid Derivatives with Antiseizure Activity: In Vitro and In Vivo Validation.

High fat diets have been used as complementary treatments for seizure disorders for more than a century. Moreover, many fatty acids and derivatives, including the broad-spectrum antiseizure medication valproic acid, have been explored and used as pharmacological agents to treat epilepsy. In this work, we have explored the anticonvulsant potential of a large library of fatty acids and fatty acid derivatives, the LIPID MAPS Structure Database, using structure-based virtual screening to assess their ability to block the voltage-gated sodium channel 1.2 (NaV1.2), a validated target for antiseizure medications. Four of the resulting in silico hits were submitted for experimental confirmation using in vitro patch clamp experiments, and their protective role was evaluated in an acute mice seizure model, the Maximal Electroshock seizure model. These four compounds were found to protect mice against seizures. Two of them exhibited blocking effects on NaV1.2, CaV2.2, and CaV3.1.

Lipidomics and mass spectrometry imaging unveil alterations in mice hippocampus lipid composition exposed to hypoxia

Lipids are components of cytomembranes that are involved in various biochemical processes. High-altitude hypoxic environments not only affect the body’s energy metabolism, but these environments can also cause abnormal lipid metabolism involved in the hypoxia-induced cognitive impairment. Thus, comprehensive lipidomic profiling of the brain tissue is an essential step toward understanding the mechanism of cognitive impairment induced by hypoxic exposure. In the present study, mice showed reduced new-object recognition and spatial memory when exposed to hypobaric hypoxia for 1 day. Histomorphological staining revealed significant morphological and structural damage to the hippocampal tissue, along with prolonged exposure to hypobaric hypoxia. Dynamic lipidomics of the mouse hippocampus showed a significant shift in both the type and distribution of phospholipids, as verified by spatial lipid mapping. Collectively, a diverse and dynamic lipid composition in mice hippocampus was uncovered, which deepens our understanding of biochemical changes during sustained hypoxic exposure and could provide new insights into the cognitive decline induced by high-altitude hypoxia exposure.

Lipid Mapping of Lipid Signaling Mediators in Skeletal Muscle

Recent advancements in lipidomic have provided profound insight that goes beyond considering lipids as simple organic compounds that constitute the fundamental components of cell membranes. Beyond their pivotal roles in processes such as energy storage and serving as the fundamental building blocks of life, lipids have emerged as potent signaling molecules of significance. The importance of lipid signaling stems from its ability to orchestrate cellular responses to many environmental stresses, including salinity and pathogen attacks. Lipid signaling plays a significant role by allowing cells to respond to their local environment through reactions such as cell differentiation, inflammation and even immunity. In context with this knowledge, our objective is to comprehensively identify key signaling lipid mediators documented from published scientific literature, followed by a systemic visualization of the resulting data through the process of lipid mediator mapping to identify common signaling mediators pathways/networks that are essential for musculoskeletal (MSK) health and disease. These bioinformatics studies are complemented by our experimental studies in muscle cells. To this end, we are using a customized liquid chromatography-mass spectrometry (LC-MS) approach to profile and quantify lipid mediators (LMs). We were able to identify and profile up to 214 LMs and to precisely quantify 60 of them from various samples including body fluid, plasma, serum, bone marrow, muscle tissue, and other cell tissues. Preliminary screening indicated that 11,12-EET, 12-HETE, and PGE2 are three LMs that regulate physiologic aspects in muscles. In addition, 11,12-EET contributes to the regulation of vasodilation, exhibits anti-inflammatory properties under some conditions and in some specific tissues, and maintains endothelial function, and vascular health. However, our data indicates that 11, 12-EET levels increase with aging, decrease with exercise, and is causal for osteopenia in a zebrafish model, supporting our hypothesis that the effects of LMs are tissue specific and related to environmental factors. PGE2, which also causes inflammation, seems to be a putative LM implicated in tissue regeneration in multiple organs. In skeletal muscles, we found that PGE2 enhances myogenic differentiation and proliferation of muscle cells up to nM concentration. PGE2 also possesses beneficial bronchoprotective and anti-inflammatory effects on the airways. In conclusion, this combination of bioinformatics and experimental studies to deepen the mapping of signaling pathways and networks of LMs is crucially needed to understand the full function of LMs in MSK health and disease. This work was directly supported by NIH-National Institutes of Aging P01AG039355 (MB) and the George W. and Hazel M. Jay and Evanston Research Endowments (MB). Authors were supported by NIH Grants: National Institutes of Aging (NINDS) 2-R01NS105621; NIA-R01AG056504, NIA-2R01AG060341, National Institutes of Diabetes, Digestive, and Kidney Diseases Kidney (NIDDK)-1R01DK119066 to MB, and National Institutes of Neurological Disorders and Stroke (NINDS) 2-R01NS105621 to MB. Also, NIH/NIDC 1R01DE031872-01 (VV). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Mass spectrometry imaging protocol for spatial mapping of lipids, N-glycans and peptides in murine lung tissue.

The application of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to murine lungs is challenging due to the spongy nature of the tissue. Lungs consist of interconnected air sacs (alveoli) lined by a single layer of flattened epithelial cells, which requires inflation to maintain its natural structure. Therefore, a protocol that is compatible with both lung instillation and high spatial resolution is essential to enable multi-omic studies on murine lung disease models using MALDI-MSI. To maintain the structural integrity of the tissue, murine lungs were inflated with 8% (w/v) gelatin for lipid MSI of fresh frozen tissues or 4% (v/v) paraformaldehyde neutral buffer for N-glycan and peptide MSI of FFPE tissues. Tissues were sectioned and prepared for enzymatic digestion and/or matrix deposition. Glycerol-free PNGase F was applied for N-glycan MSI, while Trypsin Gold was applied for peptide MSI using the iMatrixSpray and ImagePrep Station, respectively. For lipid, N-glycan and peptide MSI, α-cyano-4-hydroxycinnamic acid matrix was deposited using the iMatrixSpray. MS data were acquired with 20 μm spatial resolution using a timsTOF fleX MS instrument followed by MS fragmentation of lipids, N-glycans and peptides. For lipid MSI, trapped ion mobility spectrometry was used to separate isomeric/isobaric lipid species. SCiLS™ Lab was used to visualize all MSI data. For analyte identification, MetaboScape®, GlycoMod and Mascot were used to annotate MS fragmentation spectra of lipids, N-glycans and tryptic peptides, respectively. Our protocol provides instructions on sample preparation for high spatial resolution MALDI-MSI, MS/MS data acquisition and lipid, N-glycan and peptide annotation and identification from murine lungs. This protocol will allow non-biased analyses of diseased lungs from preclinical murine models and provide further insight into disease models.

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.

Abstract 6222: Exposing the heterogeneity of the lipidome in the TME of cutaneous melanoma following treatment with NUC-7738 in combination with anti-PD-1 therapy

Abstract Background. Malignant melanoma exhibits distinct lipid profiles compared to normal tissue and changes in the lipidome influence multiple aspects of tumor biology. Lipidomic alterations within the tumor microenvironment (TME) may influence the efficacy of anti-PD-1 therapy. In combination with anti-PD-1 agent pembrolizumab, NUC-7738 (3'-deoxyadenosine [3’-dA] which is phosphorylated and protected with a phosphoramidate moiety attached at the 5’-position) has shown promising activity in anti-PD-1 refractory melanoma (Phase 2; NCT03829254). NUC-7738 generates sustained intracellular levels of 3’-dATP, which profoundly alters RNA regulatory processes in tumor cells, resulting in impaired cellular responses and changes in expression of proteins related to lipid biosynthesis. To interrogate components of the TME before and after NUC-7738 + pembrolizumab treatment, we developed a novel workflow incorporating Mass Spectrometry Imaging (MSI) to co-register lipidomic changes with molecular markers. Machine learning accelerated the interpretation of complex data obtained from paired patient biopsies. Methods. Snap frozen paired biopsies from patients with advanced cutaneous melanoma treated with NUC-7738 ±pembrolizumab were analyzed by desorption electrospray ionization (DESI)-MSI. Specific metabolic (e.g., ASAH1) and immune (e.g., CD8, CD20) markers were investigated by multiplex immunofluorescence (mIF) post DESI-MSI. Target selection was guided by bulk RNA-seq data. Raw MSI data was visualized using Waters HDI® software. Data extracted from selected regions of interest was exported into MetaboAnalyst 5.0 for statistical analysis. LIPID MAPS® Structure Database was used to assign lipid species. mIF/mIHC images were analyzed by HALO® AI. Results. Single 10 µm tissue sections allowed co-registered DESI-MSI and mIF, suitable for further informatic and AI-enabled image analysis. This facilitated direct comparison of lipids, cells, and protein expression in the TME, before and after treatment with NUC-7738, a compound known to cause profound changes in poly(A) tail regulation. MSI data analyses of the TME uncovered intra-tumoral heterogeneity of the lipidome and demonstrated changes following treatment. Conclusion. This platform provides a powerful investigative tool to simultaneously explore the myriad of factors in the TME that contribute to tumorigenesis and therapeutic response. Further analyses of the role of the lipidome in the TME and intra-tumoral heterogeneity will be explored in paired biopsies from patients with PD-1 inhibitor refractory melanoma. Citation Format: Alison L. Dickson, Greice M. Zickuhr, In Hwa Um, Ying Zhang, Ruth Plummer, Sarah P. Blagden, Stefan N. Symeonides, Natalie Cook, T.R. Jeffry Evans, Mustafa Elshani, David J. Harrison. Exposing the heterogeneity of the lipidome in the TME of cutaneous melanoma following treatment with NUC-7738 in combination with anti-PD-1 therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6222.

Spatial heterogeneity of peri-tumoural lipid composition in postmenopausal patients with oestrogen receptor positive breast cancer

Deregulation of lipid composition in adipose tissue adjacent to breast tumour is observed in ex vivo and animal models. Novel non-invasive magnetic resonance imaging (MRI) allows rapid lipid mapping of the human whole breast. We set out to elucidate the spatial heterogeneity of peri-tumoural lipid composition in postmenopausal patients with oestrogen receptor positive (ER +) breast cancer. Thirteen participants (mean age, 62 ± [SD] 6 years) with ER + breast cancer and 13 age-matched postmenopausal healthy controls were scanned on MRI. The number of double bonds in triglycerides was computed from MRI images to derive lipid composition maps of monounsaturated, polyunsaturated, and saturated fatty acids (MUFA, PUFA, SFA). The spatial heterogeneity measures (mean, median, skewness, entropy and kurtosis) of lipid composition in the peri-tumoural region and the whole breast of participants and in the whole breast of controls were computed. The Ki-67 proliferative activity marker and CD163 antibody on tumour-associated macrophages were assessed histologically. Mann Whitney U or Wilcoxon tests and Spearman’s coefficients were used to assess group differences and correlations, respectively. For comparison against the whole breast in participants, peri-tumoural MUFA had a lower mean (median (IQR), 0.40 (0.02), p < .001), lower median (0.42 (0.02), p < .001), a negative skewness with lower magnitude (− 1.65 (0.77), p = .001), higher entropy (4.35 (0.64), p = .007) and lower kurtosis (5.13 (3.99), p = .001). Peri-tumoural PUFA had a lower mean (p < .001), lower median (p < .001), a positive skewness with higher magnitude (p = .005) and lower entropy (p = .002). Peri-tumoural SFA had a higher mean (p < .001), higher median (p < .001), a positive skewness with lower magnitude (p < .001) and lower entropy (p = .012). For comparison against the whole breast in controls, peri-tumoural MUFA had a negative skewness with lower magnitude (p = .01) and lower kurtosis (p = .009), however there was no difference in PUFA or SFA. CD163 moderately correlated with peri-tumoural MUFA skewness (rs = − .64), PUFA entropy (rs = .63) and SFA skewness (rs = .59). There was a lower MUFA and PUFA while a higher SFA, and a higher heterogeneity of MUFA while a lower heterogeneity of PUFA and SFA, in the peri-tumoural region in comparison with the whole breast tissue. The degree of lipid deregulation was associated with inflammation as indicated by CD163 antibody on macrophages, serving as potential marker for early diagnosis and response to therapy.

Lipidomic analysis of microfat and nanofat reveal different lipid mediator compositions.

Microfat and nanofat are two commonly used techniques in various surgical procedures from skin rejuvenation to scar correction that are known to contribute to tissue regeneration. While microfat mainly contains adipocytes and is well suited for tissue augmentation, nanofat is rich in lipids, adipose derived stem cells, microvascular fragments, and growth factors, making it attractive for esthetic use. We have previously demonstrated that the mechanical processing of microfat into nanofat significantly changes its proteomic profile. Considering that mechanical fractionation leads to adipocyte disruption and lipid release, we aimed to analyze the lipidomic profile for its regenerative properties. Microfat and nanofat samples were isolated from fourteen healthy patients. Lipidomic profiling was performed by liquid chromatography tandem mass spectrometry. Resulting data was compared against the Human Metabolome and LIPID MAPS® Structure Database. Metaboanalyst was used to analyze metabolic pathways and lipids of interest. From 2,388 mass-to-charge ratio features, metabolic pathway enrichment analysis between microfat and nanofat samples revealed 109 pathways that were significantly enriched. While microfat samples revealed higher intensity levels of sphingosines, different eicosanoids and fat-soluble vitamins, increased levels of coumaric acids and prostacyclin were found in nanofat. This is the first study that has analyzed the lipidomic profile of micro- and nanofat, providing evidence that mechanical emulsification of microfat into nanofat leads to changes in their lipid profile. From 109 biological pathways, anti-inflammatory, anti-fibrotic and anti-melanogenic lipid mediators were particularly enriched in nanofat samples when compared to microfat. Although further studies are necessary to have a deeper understanding on the composition of these specific lipid mediators in nanofat samples, we propose that they might contribute to its regenerative effects on tissue.

Radioinduced Modulatory Response of Lipid Profiles of Wistar Rats Brain Monitored by DESI-MS Imaging

The ionizing radiation used in radiotherapy can break down deoxyribonucleic acid bonds, generate reactive oxygen and nitrogen species, alter intracellular proteins, and induce changes in the lipidome. This study delves into examining lipid classes and their spatial distribution in the brains of Wistar rats exposed to ionizing radiation. Healthy male isogenic Wistar rats (n = 15) were divided into a control group (CG, n = 3) and an irradiated group (IRG, n = 12). The individuals of the IRG group were subjected to total body irradiation (TBI) using a Co-60 source and a radiation dose of 5 Gy. The IRG group was subdivided into four subgroups corresponding to 168, 96, 48, and 24 h before sacrifice. The brains were sliced into the sagittal direction, and the slices were analyzed using the desorption electrospray ionization mass spectrometry imaging (DESI-MSI) approach. The mass spectrometry results and information from the Metabolite and Chemical Entity Database (METLINTM) and Lipid Metabolites and Pathways Strategy (LIPID MAPS) databases enabled the identification of lipids belonging to distinct classes. The DESI-MS images revealed distinctive spatial distributions of these lipids and the modulatory response induced by the radiation over time.

Липидный анализ слезной жидкости в диагностике дисфункции мейбомиевых желез

The tear film lipid layer plays a crucial role in maintaining ocular surface homeostasis by preventing excessive evaporation of the aqueous layer and reducing heat transfer from the corneal and conjunctival surface. The lipid composition of the tear film is unique and consists of two main layers: the outer (nonpolar lipids) and the inner (polar lipids). The thick outer layer of the tear film is composed of non-polar lipids that lack internal distributed charge, while the thin inner layer is formed by polar lipids with positive and negative charges at the ends of the molecule. Both types of lipids are synthesized in the meibomian glands (MG) and contribute to tear film stability. Meibomian gland dysfunction (MGD) alters the composition and physical properties of lipids, leading to pathological changes in both the MG and tear film. In meibomian gland dysfunction (MGD), the meibum thickens and acquires a higher melting point than normal. This leads to a decrease in the amount of nonpolar and amphiphilic lipids in the meibomian gland secretion and tear film. Consequently, the protective effect of the tear lipid layer is impaired, and its stability is compromised. Lipid mapping analyzes the lipid composition of biological samples, such as tear fluid, to study the mechanisms of the development and progression of various ocular surface diseases, including dry eye syndrome, MGD, and recurrent blepharoconjunctivitis. This method provides fundamental data on the properties of the tear film in various ocular surface diseases. It has the potential to establish hallmarks of disease course and develop personalized treatment approaches for specific clinical cases. KEYWORDS: tear, tear film lipids, ocular surface, meibomian gland dysfunction, lipid analysis. FOR CITATION: Takhauova L.R., Guseva A.A., Krylova A.A., Krivosheina O.I. Lipid analysis of tear fluid as a diagnostic tool for meibomian gland dysfunction. Russian Journal of Clinical Ophthalmology. 2024;24(2):83–87 (in Russ.). DOI: 10.32364/2311-7729-2024-24-2-7.

Applying Multimodal Mass Spectrometry to Image Tumors Undergoing Ferroptosis Following In Vivo Treatment with a Ferroptosis Inducer.

Epithelial ovarian cancer (EOC) is the most common form of ovarian cancer. The poor prognosis generally associated with this disease has led to the search for improved therapies such as ferroptosis-inducing agents. Ferroptosis is a form of regulated cell death that is dependent on iron and is characterized by lipid peroxidation. Precise mapping of lipids and iron within tumors exposed to ferroptosis-inducing agents may provide insight into processes of ferroptosis in vivo and ultimately assist in the optimal deployment of ferroptosis inducers in cancer therapy. In this work, we present a method for combining matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) with secondary ion mass spectrometry (SIMS) to analyze changes in spatial lipidomics and metal composition, respectively, in ovarian tumors following exposure to a ferroptosis inducer. Tumors were obtained by injecting human ovarian cancer tumor-initiating cells into mice, followed by treatment with the ferroptosis inducer erastin. SIMS imaging detected iron accumulation in the tumor tissue, and sequential MALDI-MS imaging of the same tissue section displayed two chemically distinct regions of lipids. One region was associated with the iron-rich area detected with SIMS, and the other region encompassed the remainder of the tissue section. Bulk lipidomics confirmed the lipid assignments putatively assigned from the MALDI-MS data. Overall, we demonstrate the ability of multimodal MSI to identify the spatial locations of iron and lipids in the same tissue section and associate these regions with clinical pathology.

In silico analysis unravels the promising anticariogenic efficacy of fatty acids against dental caries causing Streptococcus mutans

Globally, dental caries is a prevalent oral disease caused by cariogenic bacteria, primarily Streptococcus mutans. It establishes caries either through sucrose-dependent (via glycosyltransferases) or through sucrose-independent (via surface adhesins Antigen I/II) mechanism. Sortase A (srtA) attaches virulence-associated adhesins to host tissues. Because of their importance in the formation of caries, targeting these proteins is decisive in the development of new anticariogenic drugs. High-throughput virtual screening with LIPID MAPS -a fatty acid database was performed. The selected protein-ligand complexes were subjected to molecular dynamics simulation (MDs). The Binding Free Energy of complexes was predicted using MM/PBSA. Further, the drug-likeness and pharmacokinetic properties of ligands were also analyzed. Out of 46,200 FAs scrutinized virtually against the three protein targets (viz., GtfC, Ag I/II and srtA), top 5 FAs for each protein were identified as the best hit based on interaction energies viz., hydrogen bond numbers and hydrophobic interaction. Further, two common FAs (LMFA01050418 and LMFA01040045) that showed high binding affinity against Ag I/II and srtA were selected for MDs analysis. A 100ns MDs unveiled a stable conformation. Results of Rg signified that FAs does not induce significant structural & conformational changes. SASA indicated that the complexes maintain higher thermodynamic stability during MDs. The predicted binding free energy (MM/PBSA) of complexes elucidated their stable binding interaction. ADME analysis suggested the FAs are biologically feasible as therapeutic candidates. Overall, the presented in silico data is the first of its kind in delineating FAs as promising anticaries agents of future. Communicated by Ramaswamy H. Sarma

An In Silico Database for Automated Feature Identification of High-Resolution Tandem Mass Spectrometry 13C-Trimethylation Enhancement Using Diazomethane (13C-TrEnDi)-Modified Lipid Data.

13C-Trimethylation enhancement using diazomethane (13C-TrEnDi) is a chemical derivatization technique that uses 13C-labeled diazomethane to increase mass spectrometry (MS) signal intensities for phosphatidylcholine (PC) and phosphatidylethanolamine (PE) lipid classes, both of which are of major interest in biochemistry. In silico mass spectrometry databases have become mainstays in lipidomics experiments; however, 13C-TrEnDi-modified PC and PE species have altered m/z and fragmentation patterns from their native counterparts. To build a database of 13C-TrEnDi-modified PC and PE species, a lipid extract from nutritional yeast was derivatized and fragmentation spectra of modified PC and PE species were mined using diagnostic fragmentation filtering by searching 13C-TrEnDi-modified headgroups with m/z 199 (PC) and 202 (PE). Identities of 25 PC and 10 PE species were assigned after comparing to predicted masses from the Lipid Maps Structure Database with no false positive identifications observed; neutral lipids could still be annotated after derivatization. Collision energies from 16 to 52 eV were examined, resulting in three additional class-specific fragment ions emerging, as well as a combined sn-1/sn-2 fragment ion, allowing sum-composition level annotations to be assigned. Using the Lipid Blast templates, a NIST-compatible 13C-TrEnDi database was produced based on fragmentation spectra observed at 36 eV and tested on HEK 293T cell lipid extracts, identifying 47 PC and 24 PE species, representing a 1.8-fold and 2.2-fold increase in annotations, respectively. The 13C-TrEnDi database is freely available, MS vendor-independent, and widely compatible with MS data processing pipelines, increasing the throughput and accessibility of TrEnDi for lipidomics applications.

Step-by-Step Approach to Build Multiple Reaction Monitoring (MRM) Profiling Instrument Acquisition Methods for Class-based Lipid Exploratory Analysis by Mass Spectrometry.

Multiple reaction monitoring (MRM) profiling is a strategy for the exploratory analysis of small molecules and lipids by direct sample injection, ie, without the use of chromatographic separation. It is based on instrument methods that comprise a list of ion transitions (MRMs), in which the precursor ion is the expected ionized m/z of the lipid at its species level, ie, the description of lipid class and number of carbon and double bonds in the fatty acid chain(s), and the product ion is a fragment expected for the lipid class or for the fatty acid neutral loss. The Lipid Maps database is expanding constantly, and therefore the MRM-profiling methods associated with this database need to be continuously updated. Here, we provide a comprehensive overview and the key references for the MRM-profiling methodology and workflow, followed by a step-by-step approach to build MRM-profiling instrument acquisition methods for class-based lipid exploratory analysis based on the Lipid Maps database. The detailed workflow includes (1) importing the list of lipids from the database; (2) for a given class, combining isomeric lipids described at full structural level into 1 entry to obtain the neutral mass at species level; (3) attributing the standard Lipid Maps abbreviated nomenclature for the lipid at its species level; (4) predicting the ionized precursor ions; and (5) adding the expected product ion. We also describe how to simulate the precursor ion for the suspect screening of modified lipids using lipid oxidation and their expected product ions as an example. After determining the MRMs, information about collision energy, dwell time, and other instrument parameters are added to finalize the acquisition method. As an example of final method output, we describe the format for Agilent MassHunter v.B.06 and provide the parameters in which optimization can be performed by lipid class using one or more lipid standards.

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.

Molecular-level evidence of early lipid transformations throughout oceanic depths

Our understanding of lipid biogeochemistry of the ocean’s interior is still in its infancy. Here we focus on early lipid transformation and the formation of lipid degradation products in the NE Atlantic Ocean (49.0°N, 16.5°W). We employed high resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), a method that allows observation and elemental composition assignment of thousands of lipids in a single sample. Using these data, we infer molecular-level changes that occur during lipid transformation in the oceanic water column to shed new light on early lipid transformation processes and the formation of lipid decomposition intermediates, here termed CHO compounds (i.e., lipid-derived species that contain carbon, hydrogen and oxygen in their molecular formula). We considered the distribution of molecular rings and/or double bonds (DBE), H/C and O/C ratios, molecular diversity based on the number of mass spectral signals for monoisotopic species, and carbon number in CHO molecules. Data are elaborated for the four ocean zones, the epipelagic, mesopelagic, bathypelagic and abyssal. The highest molecular diversity characterizes CHO compounds associated with the epipelagic zone, which is explained by numerous and diverse planktonic communities inhabiting the epipelagic and by the effects of both biotic and abiotic processes on lipid transformation. Lipid transformations include crosslinking (condensation), partial degradation or fragmentation, double bond reduction, oxidation, hydrogenation, dehydrogenation and cyclization. Crosslinking likely results in a unimodal distribution of carbon number of CHO compounds, in contrast to cell lipids (referred to as Reported lipids based on the Lipid Maps Database), which have a bimodal distribution of carbon number. CHO compounds that appear to be formed by fragmentation (decrease of the number of C atoms) and ring/double bond reduction were more stable to further transformation and remained longer in the water column, i.e., these compounds were transferred deeper into the water column. Low unsaturation and fast transport to depth promotes CHO compound preservation in the water column. Dehydrogenation leads to increased unsaturation (average DBE up to 21.3), condensation, and cyclization, resulting in high molecular weight compounds with a high degree of unsaturation. Our data demonstrate that lipids with cyclic structures are more refractory than those with acyclic structures. The formation of aromatic structures is not a significant process during early lipid transformation in the oceanic water column.

Differential Kendrick's Plots as an Innovative Tool for Lipidomics in Complex Samples: Comparison of Liquid Chromatography and Infusion-Based Methods to Sample Differential Study.

Lipidomics has developed rapidly over the past decade. Nontargeted lipidomics from biological samples remains a challenge due to the high structural diversity, the concentration range of lipids, and the complexity of biological samples. We introduce here the use of differential Kendrick's plots as a rapid visualization tool for a qualitative nontargeted analysis of lipids categories and classes from data generated by either liquid chromatography-mass spectrometry (LC-MS) or direct infusion (nESI-MS). Each lipid class is easily identified by comparison with the theoretical Kendrick plot pattern constructed from exact mass measurements and by using MSKendrickFilter, an in-house Python software. The lipids are identified with the LIPID MAPS database. In addition, in LC-MS, the software based on the Kendrick plots returns the retention time from all the lipids belonging to the same series. Lipid extracts from a yeast (Saccharomyces cerevisiae) are used as a model. An on/off case comparing Kendrick plots from two cell lines (prostate cancer cell lines treated or not with a DGAT2 inhibition) clearly shows the effect of the inhibition. Our study demonstrates the good performance of direct infusion as a fast qualitative screening method as well as for the analysis of chromatograms. A fast screening semiquantitative approach is also possible, while the targeted mode remains the golden standard for precise quantitative analysis.

RaMP-DB 2.0: a renovated knowledgebase for deriving biological and chemical insight from metabolites, proteins, and genes.

Functional interpretation of high-throughput metabolomic and transcriptomic results is a crucial step in generating insight from experimental data. However, pathway and functional information for genes and metabolites are distributed among many siloed resources, limiting the scope of analyses that rely on a single knowledge source. RaMP-DB 2.0 is a web interface, relational database, API and R package designed for straightforward and comprehensive functional interpretation of metabolomic and multi-omic data. RaMP-DB 2.0 has been upgraded with an expanded breadth and depth of functional and chemical annotations (ClassyFire, LIPID MAPS, SMILES, InChIs, etc.), with new data types related to metabolites and lipids incorporated. To streamline entity resolution across multiple source databases, we have implemented a new semi-automated process, thereby lessening the burden of harmonization and supporting more frequent updates. The associated RaMP-DB 2.0 R package now supports queries on pathways, common reactions (e.g. metabolite-enzyme relationship), chemical functional ontologies, chemical classes and chemical structures, as well as enrichment analyses on pathways (multi-omic) and chemical classes. Lastly, the RaMP-DB web interface has been completely redesigned using the Angular framework. The code used to build all components of RaMP-DB 2.0 are freely available on GitHub at https://github.com/ncats/ramp-db, https://github.com/ncats/RaMP-Client/ and https://github.com/ncats/RaMP-Backend. The RaMP-DB web application can be accessed at https://rampdb.nih.gov/. Supplementary data are available at Bioinformatics online.