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The annotated protein database was curated to annotate MS/MS data in the manuscript titled 'Mapping Microhabitats: Metabolome Informed Proteome Imaging of Lignocellulose Decomposition by a Naturally Evolved Microbial Consortium'.&nbsp

The circadian system coordinates daily rhythms in lipid metabolism, storage and utilization. Disruptions of internal circadian rhythms due to altered sleep/wake schedules, such as in night-shift work, have been implicated in increased risk of cardiovascular disease and metabolic disorders. To determine the impact of a night-shift schedule on the human blood plasma lipidome, an in-laboratory simulated shift work study was conducted.Fourteen healthy young adults were assigned to 3 days of either a simulated day or night-shift schedule, followed by a 24-h constant routine protocol with fixed environmental conditions, hourly isocaloric snacks, and constant wakefulness to investigate endogenous circadian rhythms. Blood plasma samples collected at 3-h intervals were subjected to untargeted lipidomics analysis.More than 400 lipids were identified and quantified across 21 subclasses. Focusing on lipids with low between-subject variation per shift condition, alterations in the circulating plasma lipidome revealed generally increased mean triglyceride levels and decreased mean phospholipid levels after night-shift relative to day-shift. The circadian rhythms of triglycerides containing odd chain fatty acids peaked earlier during constant routine after night-shift. Regardless of shift condition, triglycerides tended to either peak or be depleted at 16:30 h, with chain-specific differences associated with the direction of change.The simulated night-shift schedule was associated with altered temporal patterns in the lipidome. This may be premorbid to the elevated cardiovascular risk that has been found epidemiologically in night-shift workers.

Untargeted lipidomics allows analysis of a broader range of lipids than targeted methods and permits discovery of unknown compounds. Previous ring trials have evaluated the reproducibility of targeted lipidomics methods, but inter-laboratory comparison of compound identification and unknown feature detection in untargeted lipidomics has not been attempted. To address this gap, five laboratories analyzed a set of mammalian tissue and biofluid reference samples using both their own untargeted lipidomics procedures and a common chromatographic and data analysis method. While both methods yielded informative data, the common method improved chromatographic reproducibility and resulted in detection of more shared features between labs. Spectral search against the LipidBlast in silico library enabled identification of over 2,000 unique lipids. Further examination of LC-MS/MS and ion mobility data, aided by hybrid search and spectral networking analysis, revealed spectral and chromatographic patterns useful for classification of unknown features, a subset of which were highly reproducible between labs. Overall, our method offers enhanced compound identification performance compared to targeted lipidomics, demonstrates the potential of harmonized methods to improve inter-site reproducibility for quantitation and feature alignment, and can serve as a reference to aid future annotation of untargeted lipidomics data.

Viral infections are a fundamental and universal fact of life. All living organisms are believed to be the host for at least one type of virus [1] with some infections resulting in no visible sympt...

Membrane lipids serve as substrates for the generation of numerous signaling lipids when plants are exposed to environmental stresses, and jasmonic acid, an oxidized product of 18‐carbon unsaturated fatty acids (e.g., linolenic acid), has been recognized as the essential signal in wound‐induced gene expression. Yet, the contribution of individual membrane lipids in linolenic acid generation is ill‐defined. In this work, we performed spatial lipidomic experiments to track lipid changes that occur locally at the sight of leaf injury to better understand the potential origin of linolenic and linoleic acids from individual membrane lipids. The central veins of tomato leaflets were crushed using surgical forceps, leaves were cryosectioned and analyzed by two orthogonal matrix‐assisted laser desorption/ionization mass spectrometry imaging platforms for insight into lipid spatial distribution. Significant changes in lipid composition are only observed 30 min after wounding, while after 60 min lipidome homeostasis has been re‐established. Phosphatidylcholines exhibit a variable pattern of spatial behavior in individual plants. Among lysolipids, lysophosphatidylcholines strongly co‐localize with the injured zone of wounded leaflets, while, for example, lysophosphatidylglycerol (LPG) (16:1) accumulated preferentially toward the apex in the injured zone of wounded leaflets. In contrast, two other LPGs (LPG [18:3] and LPG [18:2]) are depleted in the injured zone. Our high‐resolution co‐localization imaging analyses suggest that linolenic acids are predominantly released from PCs with 16_18 fatty acid composition along the entire leaf, while it seems that in the apex zone PG (16:1_18:3) significantly contributes to the linolenic acid pool. These results also indicate distinct localization and/or substrate preferences of phospholipase isoforms in leaf tissue.

Climate change is globally affecting rainfall patterns, necessitating the improvement of drought tolerance in crops. Sorghum bicolor is a drought-tolerant cereal capable of producing high yields under water scarcity conditions. Functional stay-green sorghum genotypes can maintain green leaf area and efficient grain filling in terminal post-flowering water deprivation, a period of ~10 weeks. To obtain molecular insights into these characteristics, two drought-tolerant genotypes, BTx642 and RTx430, were grown in control and terminal post-flowering drought field plots in the Central Valley of California. Photosynthetic, photoprotective, water dynamics, and biomass traits were quantified and correlated with metabolomic data collected from leaves, stems, and roots at multiple timepoints during drought. Physiological and metabolomic data was then compared to longitudinal RNA sequencing data collected from these two genotypes. The metabolic response to drought highlights the uniqueness of the post-flowering drought acclimation relative to pre-flowering drought. The functional stay-green genotype BTx642 specifically induced photoprotective responses in post-flowering drought supporting a putative role for photoprotection in the molecular basis of the functional stay-green trait. Specific genes are highlighted that may contribute to post-flowering drought tolerance and that can be targeted in crops to maximize yields under limited water input conditions.HighlightPathways contributing to the long-term maintenance of photosynthetic activity in terminal post-flowering drought are revealed by a comprehensive approach combining in-field photosynthetic physiological analysis, metabolomics, and transcriptomics.

Cyclopropane-functionalized hydrocarbons are excellent fuels due their high energy density. However, the organic synthesis of these molecules is challenging. In this work, we produced polycyclopropanated fatty acids in bacteria. These molecules can be converted into renewable fuels for energy-demanding applications such as shipping, long-haul transport, aviation, and rocketry. We explored the chemical diversity encoded in thousands of bacterial genomes to identify and repurpose naturally occurring cyclopropanated molecules. We identified a set of candidate iterative polyketide synthases (iPKSs) predicted to produce polycyclopropanated fatty acids (POP-FAs), expressed them in Streptomyces coelicolor, and produced POP-FAs. We determined the structure of the molecules and increased their production 22-fold. Finally, we produced polycyclopropanated fatty acid methyl esters (POP-FAMEs). Our POP fuel candidates can have net heating values of more than 50 MJ/L. Our research shows that the POP-FAMEs and other POPs have the energetic properties for energy-demanding applications for which sustainable alternatives are scarce.

Lipids play a fundamental role in fungal cell biology, being essential cell membrane components and major targets of antifungal drugs. A deeper knowledge of lipid metabolism is key for developing new drugs and a better understanding of fungal pathogenesis. Here, we built a comprehensive map of the Histoplasma capsulatum lipid metabolic pathway by incorporating proteomic and lipidomic analyses. We performed genetic complementation and overexpression of H. capsulatum genes in Saccharomyces cerevisiae to validate reactions identified in the map and to determine enzymes responsible for catalyzing orphan reactions. The map led to the identification of both the fatty acid desaturation and the sphingolipid biosynthesis pathways as targets for drug development. We found that the sphingolipid biosynthesis inhibitor myriocin, the fatty acid desaturase inhibitor thiocarlide, and the fatty acid analog 10-thiastearic acid inhibit H. capsulatum growth in nanomolar to low-micromolar concentrations. These compounds also reduced the intracellular infection in an alveolar macrophage cell line. Overall, this lipid metabolic map revealed pathways that can be targeted for drug development. IMPORTANCE It is estimated that 150 people die per hour due to the insufficient therapeutic treatments to combat fungal infections. A major hurdle to developing antifungal therapies is the scarce knowledge on the fungal metabolic pathways and mechanisms of virulence. In this context, fungal lipid metabolism is an excellent candidate for developing drugs due to its essential roles in cellular scaffolds, energy storage, and signaling transductors. Here, we provide a detailed map of Histoplasma capsulatum lipid metabolism. The map revealed points of this fungus lipid metabolism that can be targeted for developing antifungal drugs.

The ability to improve the data quality of ion mobility-mass spectrometry (IM-MS) measurements is of great importance for enabling modular and efficient computational workflows and gaining better qualitative and quantitative insights from complex biological and environmental samples. We developed the PNNL PreProcessor, a standalone and user-friendly software housing various algorithmic implementations to generate new MS-files with enhanced signal quality and in the same instrument format. Different experimental approaches are supported for IM-MS based on Drift-Tube (DT) and Structures for Lossless Ion Manipulations (SLIM), including liquid chromatography (LC) and infusion analyses. The algorithms extend the dynamic range of the detection system, while reducing file sizes for faster and memory-efficient downstream processing. Specifically, multidimensional smoothing improves peak shapes of poorly defined low-abundance signals, and saturation repair reconstructs the intensity profile of high-abundance peaks from various analyte types. Other functionalities are data compression and interpolation, IM demultiplexing, noise filtering by low intensity threshold and spike removal, and exporting of acquisition metadata. Several advantages of the tool are illustrated, including an increase of 19.4% in lipid annotations and a two-times faster processing of LC-DT IM-MS data-independent acquisition spectra from a complex lipid extract of a standard human plasma sample. The software is freely available at https://omics.pnl.gov/software/pnnl-preprocessor.

Pulmonary alveolar microlithiasis (PAM) is an autosomal recessive lung disease caused by a deficiency in the pulmonary epithelial Npt2b sodium-phosphate co-transporter that results in accumulation of phosphate and formation of hydroxyapatite microliths in the alveolar space. The single cell transcriptomic analysis of a PAM lung explant showing a robust osteoclast gene signature in alveolar monocytes and the finding that calcium phosphate microliths contain a rich protein and lipid matrix that includes bone resorbing osteoclast enzymes suggested a role for osteoclast-like cells in the defense against microliths. While investigating the mechanisms of microlith clearance, we found that Npt2b modulates pulmonary phosphate homeostasis through effects on alternative phosphate transporter activity and alveolar osteoprotegerin, and that microliths induce osteoclast formation and activity in a receptor activator of nuclear factor-κB ligand (RANKL) and dietary phosphate dependent manner. This work reveals that Npt2b and pulmonary osteoclast-like cells play key roles in pulmonary homeostasis and suggest potential new therapeutic targets for the treatment of lung disease.

In this study, a suite of complementary environmental geochemical analyses, including NMR and gas chromatography-mass spectrometry (GC-MS) analyses of central metabolites, Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) of secondary metabolites, and lipidomics, was used to investigate the influence of organic matter (OM) quality on the heterotrophic microbial mechanisms controlling peatland CO(2), CH(4), and CO(2):CH(4) porewater production ratios in response to climate warming. Our investigations leverage the Spruce and Peatland Responses under Changing Environments (SPRUCE) experiment, where air and peat warming were combined in a whole-ecosystem warming treatment. We hypothesized that warming would enhance the production of plant-derived metabolites, resulting in increased labile OM inputs to the surface peat, thereby enhancing microbial activity and greenhouse gas production. Because shallow peat is most susceptible to enhanced warming, increases in labile OM inputs to the surface, in particular, are likely to result in significant changes to CO(2) and CH(4) dynamics and methanogenic pathways. In support of this hypothesis, significant correlations were observed between metabolites and temperature consistent with increased availability of labile substrates, which may stimulate more rapid turnover of microbial proteins. An increase in the abundance of methanogenic genes in response to the increase in the abundance of labile substrates was accompanied by a shift toward acetoclastic and methylotrophic methanogenesis. Our results suggest that as peatland vegetation trends toward increasing vascular plant cover with warming, we can expect a concomitant shift toward increasingly methanogenic conditions and amplified climate–peatland feedbacks.

Advancements in molecular separations coupled with mass spectrometry have enabled metabolome analyses for clinical cohorts. A population of interest for metabolome profiling is patients with rare disease for which abnormal metabolic signatures may yield clues into the genetic basis, as well as mechanistic drivers of the disease and possible treatment options. We undertook the metabolome profiling of a large cohort of patients with mysterious conditions characterized through the Undiagnosed Diseases Network (UDN). Due to the size and enrollment procedures, collection of the metabolomes for UDN patients took place over 2 years. We describe the study designed to adjust for measurements collected over a long time scale and how this enabled statistical analyses to summarize the metabolome of individual patients. We demonstrate the removal of time-based batch effects, overall statistical characteristics of the UDN population, and two case studies of interest that demonstrate the utility of metabolome profiling for rare diseases.

Mutations in the torsinA-interacting protein 1 (TOR1AIP1) gene result in a severe muscular dystrophy with minimal literature in the pediatric population. We review a case of TOR1AIP1 gene mutation in a 16-year-old Caucasian female with a long history of muscle weakness. Extensive clinical workup was performed and MRI at time of initial presentation demonstrated no significant muscular atrophy with heterogenous STIR hyperintensity of the lower extremity muscles. MRI findings seven years later included extensive atrophy of the lower extremities, with severe progression, including the gluteal muscles, iliopsoas, rectus femoris, and obturator internus. There was also significant atrophy of the rectus abdominis and internal and external oblique muscles, and iliacus muscles. The MRI findings showed more proximal involvement of lower extremities and no atrophy of the tibialis anterior, making TOR1AIP1 the more likely genetic cause. Muscle biopsy findings supported TOR1AIP1 limb-girdle muscular dystrophy. Though rare, TOR1AIP1 gene mutation occurs in pediatric patients and MRI can aid in diagnosis and help differentiate from other types of muscular dystrophy. Genetic and pathology workup is also crucial to accurate diagnosis and possible treatment of these patients.

Lipids have been recognized as key players in cell signaling and disease. Information on their location and distribution within a biological system, under varying conditions, is necessary to understand the contributions of different lipid species to an altered phenotype. Imaging mass spectrometry techniques, such as time-of-flight secondary ion mass spectrometry (ToF-SIMS) and matrix-assisted laser desorption/ionization (MALDI), are capable of revealing global lipid distributions in tissues in an untargeted fashion. However, to confidently identify the species present in a sample, orthogonal analyses like tandem MS (MS/MS) are often required. This can be accomplished by bulk sample analysis with liquid chromatography (LC)-MS/MS, which can provide confident lipid identifications, at the expense of losing location-specific information. Here, using planarian flatworms as a model system, we demonstrate that imaging gas cluster ion beam (GCIB)-ToF-SIMS has the unique capability to simultaneously detect, identify, and image lipid species with subcellular resolution in tissue sections. The parallel detection of both, intact lipids and their respective fragments, allows for unique identification of some species without the need of performing an additional orthogonal MS/MS analysis. This was accomplished by correlating intact lipid and associated fragment SIMS images. The lipid assignments, respective fragment identities, and locations gathered from ToF-SIMS data were confirmed via LC-MS/MS on lipid extracts and ultrahigh mass resolution MALDI-MS imaging. Together, these data show that the semidestructive nature of ToF-SIMS can be utilized advantageously to enable both confident molecular annotations and to determine the locations of species within a biological sample.

Optimal lysosome function requires maintenance of an acidic pH maintained by proton pumps in combination with a counterion transporter such as the Cl(−)/H(+) exchanger, CLCN7 (ClC-7), encoded by CLCN7. The role of ClC-7 in maintaining lysosomal pH has been controversial. In this paper, we performed clinical and genetic evaluations of two children of different ethnicities. Both children had delayed myelination and development, organomegaly, and hypopigmentation, but neither had osteopetrosis. Whole-exome and -genome sequencing revealed a de novo c.2144A>G variant in CLCN7 in both affected children. This p.Tyr715Cys variant, located in the C-terminal domain of ClC-7, resulted in increased outward currents when it was heterologously expressed in Xenopus oocytes. Fibroblasts from probands displayed a lysosomal pH approximately 0.2 units lower than that of control cells, and treatment with chloroquine normalized the pH. Primary fibroblasts from both probands also exhibited markedly enlarged intracellular vacuoles; this finding was recapitulated by the overexpression of human p.Tyr715Cys CLCN7 in control fibroblasts, reflecting the dominant, gain-of-function nature of the variant. A mouse harboring the knock-in Clcn7 variant exhibited hypopigmentation, hepatomegaly resulting from abnormal storage, and enlarged vacuoles in cultured fibroblasts. Our results show that p.Tyr715Cys is a gain-of-function CLCN7 variant associated with developmental delay, organomegaly, and hypopigmentation resulting from lysosomal hyperacidity, abnormal storage, and enlarged intracellular vacuoles. Our data supports the hypothesis that the ClC-7 antiporter plays a critical role in maintaining lysosomal pH.

Lipids are essential to all living organisms, as an energy source, as an important cellular structural component, and as a communication tool. In this study, we used global lipidomic methods to evaluate the lipids in leaf-cutter ant fungal gardens. Leaf-cutter ants and their coevolved fungal cultivar, Leucoagaricus gongylophorus, are a model mutualistic system. The fungus enzymatically digests fresh plant material that the ants cut and deliver, converting energy and nutrients from plants, and providing them to the ants through specialized hyphal swellings called gongylidia. Using combined liquid chromatography, ion mobility spectrometry, and tandem mass spectrometry we evaluated differences between the molecular speciation of lipids in the leaf-cutter ant fungal garden ecosystem. This lipidomic study characterized leaves that are fed to the gardens, gongylidia that are produced by the fungus to feed the ants, and spatially resolved regions of the fungal garden through stages of leaf degradation. Lipids containing alpha-linolenic acid (18:3) were enriched in leaves and the top of the gardens, but not dominant in the middle or bottom regions. Gongylidia were dominated by lipids containing linoleic acid (18:2). To evaluate the communicative potential of the lipids in fungal gardens we conducted a behavioral experiment that showed Atta leaf-cutter ants responded differently to 18:3 and 18:2 fatty acids, with aggression towards 18:3 and attraction for 18:2. This work demonstrates the role of lipids in both the transfer of energy and as an inter-kingdom communication tool in leaf-cutter ant fungal gardens.ImportanceIn this work we examined the role of lipids in the mutualism between leaf-cutter ants and fungus. These ants cut fresh leaf material, which they provide to their fungal cultivar, that converts energy and nutrients from the plants and provides it to the ants in specialized hyphal swellings called gongylidia. This work constitutes the first example of a global lipidomics study of a symbiotic system and provides insights as to how the fungus modifies plant lipids into a usable source for the ants. Through a behavioral experiment, this work also demonstrates how lipids can be used as an inter-kingdom communication tool, in this case an attractant, rather than as a repellant, which is more often seen.

Improvements in mass spectrometry (MS) technologies coupled with bioinformatics developments have allowed considerable advancement in the measurement and interpretation of lipidomics data in recent years. Since research areas employing lipidomics are rapidly increasing, there is a great need for bioinformatic tools that capture and utilize the complexity of the data. Currently, the diversity and complexity within the lipidome is often concealed by summing over or averaging individual lipids up to (sub)class-based descriptors, losing valuable information about biological function and interactions with other distinct lipids molecules, proteins and/or metabolites.To address this gap in knowledge, novel bioinformatics methods are needed to improve identification, quantification, integration and interpretation of lipidomics data. The purpose of this mini-review is to summarize exemplary methods to explore the complexity of the lipidome.Here we describe six approaches that capture three core focus areas for lipidomics: (1) lipidome annotation including a resolvable database identifier, (2) interpretation via pathway- and enrichment-based methods, and (3) understanding complex interactions to emphasize specific steps in the analytical process and highlight challenges in analyses associated with the complexity of lipidome data.

Tissue- and cell-specific expression patterns are highly variable within and across individuals, leading to altered host responses after acute virus infection. Unraveling key tissue-specific response patterns provides novel opportunities for defining fundamental mechanisms of virus-host interaction in disease and the identification of critical tissue-specific networks for disease intervention in the lung. Currently, there are no approved therapeutics for Middle East respiratory syndrome coronavirus (MERS-CoV) patients, and little is understood about how lung cell types contribute to disease outcomes. MERS-CoV replicates equivalently in primary human lung microvascular endothelial cells (MVE) and fibroblasts (FB) and to equivalent peak titers but with slower replication kinetics in human airway epithelial cell cultures (HAE). However, only infected MVE demonstrate observable virus-induced cytopathic effect. To explore mechanisms leading to reduced MVE viability, donor-matched human lung MVE, HAE, and FB were infected, and their transcriptomes, proteomes, and lipidomes were monitored over time. Validated functional enrichment analysis demonstrated that MERS-CoV-infected MVE were dying via an unfolded protein response (UPR)-mediated apoptosis. Pharmacologic manipulation of the UPR in MERS-CoV-infected primary lung cells reduced viral titers and in male mice improved respiratory function with accompanying reductions in weight loss, pathological signatures of acute lung injury, and times to recovery. Systems biology analysis and validation studies of global kinetic transcript, protein, and lipid data sets confirmed that inhibition of host stress pathways that are differentially regulated following MERS-CoV infection of different tissue types can alleviate symptom progression to end-stage lung disease commonly seen following emerging coronavirus outbreaks. IMPORTANCE Middle East respiratory syndrome coronavirus (MERS-CoV) causes severe atypical pneumonia in infected individuals, but the underlying mechanisms of pathogenesis remain unknown. While much has been learned from the few reported autopsy cases, an in-depth understanding of the cells targeted by MERS-CoV in the human lung and their relative contribution to disease outcomes is needed. The host response in MERS-CoV-infected primary human lung microvascular endothelial (MVE) cells and fibroblasts (FB) was evaluated over time by analyzing total RNA, proteins, and lipids to determine the cellular pathways modulated postinfection. Findings revealed that MERS-CoV-infected MVE cells die via apoptotic mechanisms downstream of the unfolded protein response (UPR). Interruption of enzymatic processes within the UPR in MERS-CoV-infected male mice reduced disease symptoms, virus-induced lung injury, and time to recovery. These data suggest that the UPR plays an important role in MERS-CoV infection and may represent a host target for therapeutic intervention.

Glioblastoma (GBM) is the most aggressive nervous system cancer. Understanding its molecular pathogenesis is crucial to improving diagnosis and treatment. Integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs provides insights to GBM biology. We identify key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation, as well as potential targets for EGFR-, TP53-, and RB1-altered tumors. Immune subtypes with distinct immune cell types are discovered using bulk omics methodologies, validated by snRNA-seq, and correlated with specific expression and histone acetylation patterns. Histone H2B acetylation in classical-like and immune-low GBM is driven largely by BRDs, CREBBP, and EP300. Integrated metabolomic and proteomic data identify specific lipid distributions across subtypes and distinct global metabolic changes in IDH-mutated tumors. This work highlights biological relationships that could contribute to stratification of GBM patients for more effective treatment. Wang et al. perform integrated proteogenomic analysis of adult glioblastoma (GBM), including metabolomics, lipidomics, and single nuclei RNA-Seq, revealing insights into the immune landscape of GBM, cell-specific nature of EMT signatures, histone acetylation in classical GBM, and the existence of signaling hubs which could provide therapeutic vulnerabilities.

The lipid composition of HIV-1 virions is enriched in sphingomyelin (SM), but the roles that SM or other sphingolipids (SLs) might play in the HIV-1 replication pathway have not been elucidated. In human cells, SL levels are regulated by ceramide synthase (CerS) enzymes that produce ceramides, which can be converted to SMs, hexosylceramides, and other SLs. In many cell types, CerS2, which catalyzes the synthesis of very long chain ceramides, is the major CerS. We have examined how CerS2 deficiency affects the assembly and infectivity of HIV-1. As expected, we observed that very long chain ceramide, hexosylceramide, and SM were reduced in CerS2 knockout cells. CerS2 deficiency did not affect HIV-1 assembly or the incorporation of the HIV-1 envelope (Env) protein into virus particles, but it reduced the infectivites of viruses produced in the CerS2-deficient cells. The reduced viral infection levels were dependent on HIV-1 Env, since HIV-1 particles that were pseudotyped with the vesicular stomatitis virus glycoprotein did not exhibit reductions in infectivity. Moreover, cell–cell fusion assays demonstrated that the functional defect of HIV-1 Env in CerS2-deficient cells was independent of other viral proteins. Overall, our results indicate that the altered lipid composition of CerS2-deficient cells specifically inhibit the HIV-1 Env receptor binding and/or fusion processes.

SummaryLipids have been implicated as mediators of insulitis and β-cell death in type 1 diabetes development, but the mechanisms underlying this association are poorly understood. Here, we investigated the changes in islet/β-cell lipid composition using three models of insulitis: human islets and EndoC-βH1 β-cells treated with the cytokines IL-1β and IFN-γ, and islets from non-obese diabetic mice. Across all three models, lipidomic analyses showed a consistent change in abundance of the lysophosphatidylcholine, phosphatidylcholine and triacylglycerol species. We also showed that lysophosphatidylcholine and its biosynthetic enzyme PLA2G6 are enriched in murine islets. We determined that the ADP-ribosyl-acceptor glycohydrolase ARH3 is regulated by cytokines downstream of PLA2G6, which in turn regulates proteins involved in apoptosis, lipid metabolism, antigen processing and presentation and chemokines. ARH3 reduced cytokine-induced apoptosis, which may represent a negative feedback mechanism. Overall, these data show the importance of lipid metabolism in regulating β-cell death in type 1 diabetes.HighlightsLipidomics of 3 insulitis models revealed commonly regulated lipid classes.Identification of 35 proteins regulated by cytokines via PLA2G6 signaling.ARH3 reduces cytokine-induced apoptosis via PLA2G6 regulation.ARH3 regulates the levels of proteins related to insulitis and type 1 diabetes.

Lipids play a fundamental role in fungal cell biology, being essential cell membrane components and major targets of antifungal drugs. A deeper knowledge of lipid metabolism is key for developing new drugs and a better understanding of fungal pathogenesis. Here we built a comprehensive map of theHistoplasma capsulatumlipid metabolic pathway by incorporating proteomic and lipidomic analyses. We performed genetic complementation and overexpression ofH. capsulatumgenes inSaccharomyces cerevisiaeto validate reactions identified in the map and to determine enzymes responsible for catalyzing orphan reactions. The map led to the identification of both the fatty acid desaturation and the sphingolipid biosynthesis pathways as targets for drug development. We found that the sphingolipid biosynthesis inhibitor myriocin, the fatty acid desaturase inhibitor thiocarlide and the fatty acid analog 10-thiastearic acid inhibitH. capsulatumgrowth in nanomolar to low micromolar concentrations. These compounds also reduced the intracellular infection in an alveolar macrophage cell line. Overall, this lipid metabolic map revealed pathways that can be targeted for drug development.

Mass spectrometry (MS)-based lipidomics is revolutionizing lipid research with high throughput identification and quantification of hundreds to thousands of lipids with the goal of elucidating lipid metabolism and function. Estimates of statistical confidence in lipid identification are essential for downstream data interpretation in a biological context. In the related field of proteomics, a variety of methods for estimating false-discovery are available, and understanding the statistical confidence of identifications is typically required for data analysis and hypothesis testing. However, there is no current method for estimating the false discovery rate (FDR) or statistical confidence for MS-based lipid identifications. This has slowed the adoption of MS-based lipidomics research, as all identifications require manual inspection and validation to ensure their accuracy. We present here the first generalizable method for FDR estimation, a target/decoy approach, that allows those conducting MS-based lipidomics research to confidently adjust spectral score thresholds to minimize false discovery and to enable full automation of data analysis.

Zika virus (ZIKV), an arbovirus of global concern, remodels intracellular membranes to form replication sites. How ZIKV dysregulates lipid networks to allow this, and consequences for disease, is poorly understood. Here, we perform comprehensive lipidomics to create a lipid network map during ZIKV infection. We find that ZIKV significantly alters host lipid composition, with the most striking changes seen within subclasses of sphingolipids. Ectopic expression of ZIKV NS4B protein results in similar changes, demonstrating a role for NS4B in modulating sphingolipid pathways. Disruption of sphingolipid biosynthesis in various cell types, including human neural progenitor cells, blocks ZIKV infection. Additionally, the sphingolipid ceramide redistributes to ZIKV replication sites, and increasing ceramide levels by multiple pathways sensitizes cells to ZIKV infection. Thus, we identify a sphingolipid metabolic network with a critical role in ZIKV replication and show that ceramide flux is a key mediator of ZIKV infection., Zika virus (ZIKV) remodels intracellular membranes for replication, but the role of different lipid types for infection and disease is unclear. Here, the authors perform lipidomics, show perturbation of the lipid network during ZIKV infection and show that ceramides are important for ZIKV infection.

Lipidomics data generated using untargeted mass spectrometry techniques can offer great biological insight to metabolic status and disease diagnoses. As the community's ability to conduct large-scale studies with deep coverage of the lipidome expands, approaches to analyzing untargeted data and extracting biological insight are needed. Currently, the function of most individual lipids are not known; however, meaningful biological information can be extracted. Here, I will describe a step-by-step approach to identify patterns and trends in untargeted mass spectrometry lipidomics data to assist users in extracting information leading to a greater understanding of biological systems.

Contains fulltext : 218305.pdf (Publisher’s version ) (Closed access) BACKGROUND: The X-chromosome gene USP9X encodes a deubiquitylating enzyme that has been associated with neurodevelopmental disorders primarily in female subjects. USP9X escapes X inactivation, and in female subjects de novo heterozygous copy number loss or truncating mutations cause haploinsufficiency culminating in a recognizable syndrome with intellectual disability and signature brain and congenital abnormalities. In contrast, the involvement of USP9X in male neurodevelopmental disorders remains tentative. METHODS: We used clinically recommended guidelines to collect and interrogate the pathogenicity of 44 USP9X variants associated with neurodevelopmental disorders in males. Functional studies in patient-derived cell lines and mice were used to determine mechanisms of pathology. RESULTS: Twelve missense variants showed strong evidence of pathogenicity. We define a characteristic phenotype of the central nervous system (white matter disturbances, thin corpus callosum, and widened ventricles); global delay with significant alteration of speech, language, and behavior; hypotonia; joint hypermobility; visual system defects; and other common congenital and dysmorphic features. Comparison of in silico and phenotypical features align additional variants of unknown significance with likely pathogenicity. In support of partial loss-of-function mechanisms, using patient-derived cell lines, we show loss of only specific USP9X substrates that regulate neurodevelopmental signaling pathways and a united defect in transforming growth factor beta signaling. In addition, we find correlates of the male phenotype in Usp9x brain-specific knockout mice, and further resolve loss of hippocampal-dependent learning and memory. CONCLUSIONS: Our data demonstrate the involvement of USP9X variants in a distinctive neurodevelopmental and behavioral syndrome in male subjects and identify plausible mechanisms of pathogenesis centered on disrupted transforming growth factor beta signaling and hippocampal function.

Lipidomics data generated using untargeted mass spectrometry techniques can offer great biological insight to metabolic status and disease diagnoses. As the community's ability to conduct large-scale studies with deep coverage of the lipidome expands, approaches to analyzing untargeted data and extracting biological insight are needed. Currently, the function of most individual lipids are not known; however, meaningful biological information can be extracted. Here, I will describe a step-by-step approach to identify patterns and trends in untargeted mass spectrometry lipidomics data to assist users in extracting information leading to a greater understanding of biological systems.

Mass spectrometry (MS)-based, integrated proteomics, metabolomics, and lipidomics (collectively, multi-omics) studies provide a very detailed snapshot of virus-induced changes to the host following infection and can lead to the identification of novel prophylactic and therapeutic targets for preventing or lessening disease severity. Multi-omics studies with Middle East respiratory syndrome coronavirus (MERS-CoV) are challenging as the requirements of biosafety level 3 containment limit the numbers of samples that can be safely managed. To address these issues, the multi-omics sample preparation technique MPLEx (metabolite, protein, and lipid extraction) was developed to partition a single sample into three distinct parts (metabolites, proteins, and lipids) for multi-omics analysis, while simultaneously inactivating MERS-CoV by solubilizing and disrupting the viral envelope and denaturing viral proteins. Here we describe the MPLEx protocol, highlight the step of inactivation, and describe the details of downstream processing, instrumental analysis of the three separate analytes, and their subsequent informatics pipelines.

Nanospray Desorption Electrospray Ionization mass spectrometry imaging (nano-DESI MSI) enables ambient imaging of biological samples with high sensitivity and minimal sample pretreatment. Recently, we developed an approach for constant-distance mode MSI using shear force microscopy to precisely control the distance between the sample and the nano-DESI probe. Herein, we demonstrate the power of this approach for robust imaging of pancreatic islets with high spatial resolution of ~11 μm. Pancreatic islets are difficult to characterize using traditional mass spectrometry approaches due to their small size (~100 μm) and molecular heterogeneity. Nano-DESI MSI was used to examine the spatial localization of several lipid classes including phosphatidylcholine (PC), phosphatidylethanolamine (PE), sphingomyelin (SM), phosphatidylinositol (PI), and phosphatidylserine (PS) along with fatty acids and their metabolites (e.g. prostaglandins) in the individual islets and surrounding tissue. Several lipids were found to be substantially enhanced in the islets indicating these lipids may be involved in insulin secretion. Remarkably different distributions were observed for several pairs of Lyso PC (LPC) and PC species differing only by one double bond, such as LPC 18:1 vs LPC 18:0, PC 32:1 vs PC 32:0, and PC 34:2 vs PC 34:1. These findings indicate that minor variations in the fatty acid chain length and saturation have a pronounced effect on the localization of PC and LPC species in pancreatic islets. Interestingly, a small number of oxidized PC species observed experimentally were found to be specifically localized to pancreatic islets. These PCs are potential biomarkers for reactive oxygen species in the islets, which could be harmful to pancreatic beta cells. The experimental approach presented in this study will provide valuable information on the heterogeneity of individual pancreatic islets, which is difficult to assess using bulk characterization techniques.

Glioblastoma (GBM) is the most aggressive nervous system cancer, with median survival under 2 years. Understanding its molecular pathogenesis is crucial for improving diagnosis and treatment. We performed an integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs. We identified key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation as well as potential targets for EGFR-, TP53- and RB1-altered tumors. We detected immune subtypes, driven by the presence of distinct immune cell populations using bulk omics, validated by single nulcei RNA sequencing (snRNA-seq), and they were correlated with specific expression and histone acetylation patterns. Acetylation of histone H2B in classical-like and immune-low GBM was driven largely by BRDs, CREBBP, and EP300. Integrated metabolomic and proteomic data identified specific lipid distributions across subtypes and distinct global metabolic changes in IDH mutated tumors. This work highlights biological relationships which could potentially aid GBM patient stratifications for more effective treatments.

Glioblastoma (GBM) is the most aggressive nervous system cancer, with median survival under 2 years. Understanding its molecular pathogenesis is crucial for improving diagnosis and treatment. We performed an integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs. We identified key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation as well as potential targets for EGFR-, TP53- and RB1-altered tumors. We detected immune subtypes, driven by the presence of distinct immune cell populations using bulk omics, validated by snRNA-seq, and they were correlated with specific expression and histone acetylation patterns. Acetylation of histone H2B in classical-like and immune-low GBM was driven largely by BRDs, CREBBP, and EP300. Integrated metabolomic and proteomic data identified specific lipid distributions across subtypes and distinct global metabolic changes in IDH mutated tumors. By comparing the adult GBM proteomics to the adolescent and young adult (AYA) GBM cohort from the HOPE study, we found downregulated IDH1 expression and up-regulated expression of genes in the NADH dehydrogenase family, including NDUFB1, and NDUFB3 among others, which may be related to high IDH1 mutation frequency in AYA. This work highlights biological relationships which could potentially aid GBM patient stratifications for more effective treatments. Citation Format: Liang-Bo Wang, Alla Karpova, Marina A. Gritsenko, Jennifer E. Kyle, Song Cao, Yize Li, Dmitry Rykunov, Antonio Colaprico, Joseph Rothstein, Runyu Hong, Vasileios Stathias, MacIntosh Cornwell, Francesca Petralia, Richard D. Smith, Antonio Iavarone, Milan G. Chheda, Jill S. Barnholtz-Sloan, Karin D. Rodland, Tao Liu, Li Ding, Clinical Proteomic Tumor Analysis Consortium. Proteogenomic and metabolomic characterization of human glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2170.