An α-ketoglutarate conformational switch controls iron accessibility, activation, and substrate selection of the human FTO protein.

The fat mass and obesity-associated fatso (FTO) protein is a member of the Alkb family of dioxygenases and catalyzes oxidative demethylation of N6-methyladenosine (m6A), N1-methyladenosine (m1A), 3-methylthymine (m3T), and 3-methyluracil (m3U) in single-stranded nucleic acids. It is well established that the catalytic activity of FTO proceeds via two coupled reactions. The first reaction involves decarboxylation of alpha-ketoglutarate (αKG) and formation of an oxyferryl species. In the second reaction, the oxyferryl intermediate oxidizes the methylated nucleic acid to reestablish Fe(II) and the canonical base. However, it remains unclear how binding of the nucleic acid activates the αKG decarboxylation reaction and why FTO demethylates different methyl modifications at different rates. Here, we investigate the interaction of FTO with 5-mer DNA oligos incorporating the m6A, m1A, or m3T modifications using solution NMR, molecular dynamics (MD) simulations, and enzymatic assays. We show that binding of the nucleic acid to FTO activates a two-state conformational equilibrium in the αKG cosubstrate that modulates the O2 accessibility of the Fe(II) catalyst. Notably, the substrates that provide better stabilization to the αKG conformation in which Fe(II) is exposed to O2 are demethylated more efficiently by FTO. These results indicate that i) binding of the methylated nucleic acid is required to expose the catalytic metal to O2 and activate the αKG decarboxylation reaction, and ii) the measured turnover of the demethylation reaction (which is an ensemble average over the entire sample) depends on the ability of the methylated base to favor the Fe(II) state accessible to O2.

Current approaches and outstanding challenges of functional annotation of metabolites: a comprehensive review.

Metabolite profiling is a powerful approach for the clinical diagnosis of complex diseases, ranging from cardiometabolic diseases, cancer, and cognitive disorders to respiratory pathologies and conditions that involve dysregulated metabolism. Because of the importance of systems-level interpretation, many methods have been developed to identify biologically significant pathways using metabolomics data. In this review, we first describe a complete metabolomics workflow (sample preparation, data acquisition, pre-processing, downstream analysis, etc.). We then comprehensively review 24 approaches capable of performing functional analysis, including those that combine metabolomics data with other types of data to investigate the disease-relevant changes at multiple omics layers. We discuss their availability, implementation, capability for pre-processing and quality control, supported omics types, embedded databases, pathway analysis methodologies, and integration techniques. We also provide a rating and evaluation of each software, focusing on their key technique, software accessibility, documentation, and user-friendliness. Following our guideline, life scientists can easily choose a suitable method depending on method rating, available data, input format, and method category. More importantly, we highlight outstanding challenges and potential solutions that need to be addressed by future research. To further assist users in executing the reviewed methods, we provide wrappers of the software packages at https://github.com/tinnlab/metabolite-pathway-review-docker.

Multiplexed Antibody Glycosylation Profiling Using Dual Enzyme Digestion and Liquid Chromatography-Triple Quadrupole Mass Spectrometry Method.

Antibody glycosylation plays a crucial role in the humoral immune response by regulating effector functions and influencing the binding affinity to immune cell receptors. Previous studies have focused mainly on the immunoglobulin G (IgG) isotype owing to the analytical challenges associated with other isotypes. Thus, the development of a sensitive and accurate analytical platform is necessary to characterize antibody glycosylation across multiple isotypes. In this study, we have developed an analytical workflow using antibody-light-chain affinity beads to purify IgG, IgA, and IgM from 16 µL of human plasma. Dual enzymes, trypsin and Glu-C, were used during on-bead digestion to obtain enzymatic glycopeptides and protein-specific surrogate peptides. Ultra-high-performance liquid chromatography coupled with triple quadrupole mass spectrometry was used in order to determine the sensitivity and specificity. Our platform targets 95 glycopeptides across the IgG, IgA, and IgM isotypes, as well as eight surrogate peptides representing total IgG, four IgG classes, two IgA classes, and IgM. Four stable isotope-labeled internal standards were added after antibody purification to calibrate the preparation and instrumental bias during analysis. Calibration curves constructed using serially diluted plasma samples showed good curve fitting (R2 > 0.959). The intrabatch and interbatch precision for all the targets had relative standard deviation of less than 29.6%. This method was applied to 19 human plasma samples, and the glycosylation percentages were calculated, which were comparable to those reported in the literature. The developed method is sensitive and accurate for Ig glycosylation profiling. It can be used in clinical investigations, particularly for detailed humoral immune profiling.

Advances in proteomics methods for the analysis of exhaled breath condensate.

The analysis of exhaled breath condensate (EBC) demonstrates a promising avenue of minimally invasive biopsies for diagnostics. EBC is obtained by cooling exhaled air and collecting the condensation to be utilized for downstream analysis using various analytical methods. The aqueous phase of breath contains a large variety of miscible small compounds including polar electrolytes, amino acids, cytokines, chemokines, peptides, small proteins, metabolites, nucleic acids, and lipids/eicosanoids-however, these analytes are typically present at minuscule levels in EBC, posing a considerable technical challenge. Along with recent improvements in devices for breath collection, the sensitivity and resolution of liquid chromatography coupled to online mass spectrometry-based proteomics has attained subfemtomole sensitivity, vastly enhancing the quality of EBC sample analysis. As a result, proteomics analysis of EBC has been expanding the field of breath biomarker research. We present an au courant overview of the achievements in proteomics of EBC, the advancement of EBC collection devices, and the current and future applications for EBC biomarker analysis.

Advances in targeted liquid chromatography-tandem mass spectrometry methods for endocannabinoid and N-acylethanolamine quantification in biological matrices: A systematic review.

Liquid chromatography paired with tandem mass spectrometry (LC-MS/MS) is the gold standard in measurement of endocannabinoid concentrations in biomatrices. We conducted a systematic review of literature to identify advances in targeted LC-MS/MS methods in the period 2017-2024. We found that LC-MS/MS methods for endocannabinoid quantification are relatively consistent both across time and across biomatrices. Recent advances have primarily been in three areas: (1) sample preparation techniques, specific to the chosen biomatrix; (2) the range of biomatrices tested, recently favoring blood matrices; and (3) the breadth of endocannabinoid and endocannabinoid-like analytes incorporated into assays. This review provides a summary of the recent literature and a guide for researchers looking to establish the best methods for quantifying endocannabinoids in a range of biomatrices.

What is the role of current mass spectrometry in pharmaceutical analysis?

The role of mass spectrometry (MS) has become more important in most application domains in recent years. Pharmaceutical analysis is specific due to its stringent regulation procedures, the need for good laboratory/manufacturing practices, and a large number of routine quality control analyses to be carried out. The role of MS is, therefore, very different throughout the whole drug development cycle. While it dominates within the drug discovery and development phase, in routine quality control, the role of MS is minor and indispensable only for selected applications. Moreover, its role is very different in the case of analysis of small molecule pharmaceuticals and biopharmaceuticals. Our review explains the role of current MS in the analysis of both small-molecule chemical drugs and biopharmaceuticals. Important features of MS-based technologies being implemented, method requirements, and related challenges are discussed. The differences in analytical procedures for small molecule pharmaceuticals and biopharmaceuticals are pointed out. While a single method or a small set of methods is usually sufficient for quality control in the case of small molecule pharmaceuticals and MS is often not indispensable, a large panel of methods including extensive use of MS must be used for quality control of biopharmaceuticals. Finally, expected development and future trends are outlined.

Characterization of the degradation products of lignocellulosic biomass by using tandem mass spectrometry experiments, model compounds, and quantum chemical calculations.

Biomass-derived degraded lignin and cellulose serve as possible alternatives to fossil fuels for energy and chemical resources. Fast pyrolysis of lignocellulosic biomass generates bio-oil that needs further refinement. However, as pyrolysis causes massive degradation to lignin and cellulose, this process produces very complex mixtures. The same applies to degradation methods other than fast pyrolysis. The ability to identify the degradation products of lignocellulosic biomass is of great importance to be able to optimize methodologies for the conversion of these mixtures to transportation fuels and valuable chemicals. Studies utilizing tandem mass spectrometry have provided invaluable, molecular-level information regarding the identities of compounds in degraded biomass. This review focuses on the molecular-level characterization of fast pyrolysis and other degradation products of lignin and cellulose via tandem mass spectrometry based on collision-activated dissociation (CAD). Many studies discussed here used model compounds to better understand both the ionization chemistry of the degradation products of lignin and cellulose and their ions' CAD reactions in mass spectrometers to develop methods for the structural characterization of the degradation products of lignocellulosic biomass. Further, model compound studies were also carried out to delineate the mechanisms of the fast pyrolysis reactions of lignocellulosic biomass. The above knowledge was used to assign likely structures to many degradation products of lignocellulosic biomass.

Quantitative Time-Course Analysis of Osmotic and Salt Stress in Arabidopsis thaliana Using Short Gradient Multi-CV FAIMSpro BoxCar DIA.

A major limitation when undertaking quantitative proteomic time-course experimentation is the tradeoff between depth-of-analysis and speed-of-analysis. In high complexity and high dynamic range sample types, such as plant extracts, balance between resolution and time is especially apparent. To address this, we evaluate multiple compensation voltage (CV) high field asymmetric waveform ion mobility spectrometry (FAIMSpro) settings using the latest label-free single-shot Orbitrap-based DIA acquisition workflows for their ability to deeply quantify the Arabidopsis thaliana seedling proteome. Using a BoxCarDIA acquisition workflow with a -30 -50 -70 CV FAIMSpro setting, we were able to consistently quantify >5000 Arabidopsis seedling proteins over a 21-min gradient, facilitating the analysis of ∼42 samples per day. Utilizing this acquisition approach, we then quantified proteome-level changes occurring in Arabidopsis seedling shoots and roots over 24 h of salt and osmotic stress, to identify early and late stress response proteins and reveal stress response overlaps. Here, we successfully quantify >6400 shoot and >8500 root protein groups, respectively, quantifying nearly ∼9700 unique protein groups in total across the study. Collectively, we pioneer a short gradient, multi-CV FAIMSpro BoxCarDIA acquisition workflow that represents an exciting new analysis approach for undertaking quantitative proteomic time-course experimentation in plants.

Top-down mass spectrometry analysis of capsid proteins of recombinant adeno-associated virus using multiple ion activations and proton transfer charge reduction.

Adeno-associated viruses (AAVs) are common vectors for emerging gene therapies due to their lack of pathogenicity in humans. Here, we present our investigation of the viral proteins (i.e., VP1, VP2, and VP3) of the capsid of AAVs via top-down mass spectrometry (MS). These proteins, ranging from 59 to 81 kDa, were chromatographically separated using hydrophilic interaction liquid chromatography and characterized in the gas-phase by high-resolution Orbitrap Fourier transform MS. Complementary ion dissociation methods were utilized to improve the overall sequence coverage. By reducing the overlap of product ion signals via proton transfer charge reduction on the Orbitrap Ascend BioPharma Tribrid mass spectrometer, the sequence coverage of each VP was significantly increased, reaching up to ∼40% in the case of VP3. These results showcase the improvements in the sequencing of proteins >30 kDa that can be achieved by manipulating product ions via gas-phase reactions to obtain easy-to-interpret fragmentation mass spectra.

Wide-scope targeted analysis of bioactive lipids in human plasma by LC/MS/MS.

Quantitative information on blood metabolites can be used in developing advanced medical strategies such as early detection and prevention of disease. Monitoring bioactive lipids such as steroids, bile acids, and PUFA metabolites could be a valuable indicator of health status. However, a method for simultaneously measuring these bioactive lipids has not yet been developed. Here, we report a LC/MS/MS method that can simultaneously measure 144 bioactive lipids, including steroids, bile acids, and PUFA metabolites, from human plasma, and a sample preparation method for these targets. Protein removal by methanol precipitation and purification of bioactive lipids by solid-phase extraction improved the recovery of the targeted compounds in human plasma samples, demonstrating the importance of sample preparation methods for a wide range of bioactive lipid analyses. Using the developed method, we studied the plasma from healthy human volunteers and confirmed the presence of bioactive lipid molecules associated with sex differences and circadian rhythms. The developed method of bioactive lipid analysis can be applied to health monitoring and disease biomarker discovery in precision medicine.

Lipidomics reveals the reshaping of the mitochondrial phospholipid profile in cells lacking OPA1 and mitofusins.

Depletion or mutations of key proteins for mitochondrial fusion, like optic atrophy 1 (OPA1) and mitofusins 1 and 2 (Mfn 1 and 2), are known to significantly impact the mitochondrial ultrastructure, suggesting alterations of their membranes' lipid profiles. In order to make an insight into this issue, we used hydrophilic interaction liquid chromatography coupled with electrospray ionization-high resolution MS to investigate the mitochondrial phospholipid (PL) profile of mouse embryonic fibroblasts knocked out for OPA1 and Mfn1/2 genes. One hundred sixty-seven different sum compositions were recognized for the four major PL classes of mitochondria, namely phosphatidylcholines (PCs, 63), phosphatidylethanolamines (55), phosphatidylinositols (21), and cardiolipins (28). A slight decrease in the cardiolipin/PC ratio was found for Mfn1/2-knockout mitochondria. Principal component analysis and hierarchical cluster analysis were subsequently used to further process hydrophilic interaction liquid chromatography-ESI-MS data. A progressive decrease in the incidence of alk(en)yl/acyl species in PC and phosphatidylethanolamine classes and a general increase in the incidence of unsaturated acyl chains across all the investigated PL classes was inferred in OPA1 and Mfn1/2 knockouts compared to WT mouse embryonic fibroblasts. These findings suggest a reshaping of the PL profile consistent with the changes observed in the mitochondrial ultrastructure when fusion proteins are absent. Based on the existing knowledge on the metabolism of mitochondrial phospholipids, we propose that fusion proteins, especially Mfns, might influence the PL transfer between the mitochondria and the endoplasmic reticulum, likely in the context of mitochondria-associated membranes.

timsTOF HT Improves Protein Identification and Quantitative Reproducibility for Deep Unbiased Plasma Protein Biomarker Discovery.

Mass spectrometry (MS) is a valuable tool for plasma proteome profiling and disease biomarker discovery. However, wide-ranging plasma protein concentrations, along with technical and biological variabilities, present significant challenges for deep and reproducible protein quantitation. Here, we evaluated the qualitative and quantitative performance of timsTOF HT and timsTOF Pro 2 mass spectrometers for analysis of neat plasma samples (unfractionated) and plasma samples processed using the Proteograph Product Suite (Proteograph) that enables robust deep proteomics sampling prior to mass spectrometry. Samples were evaluated across a wide range of peptide loading masses and liquid chromatography (LC) gradients. We observed up to a 76% increase in total plasma peptide precursors identified and a >2-fold boost in quantifiable plasma peptide precursors (CV < 20%) with timsTOF HT compared to Pro 2. Additionally, approximately 4.5 fold more plasma peptide precursors were detected by both timsTOF HT and timsTOF Pro 2 in the Proteograph analyzed plasma vs neat plasma. In an exploratory analysis of 20 late-stage lung cancer and 20 control plasma samples with the Proteograph, which were expected to exhibit distinct proteomes, an approximate 50% increase in total and statistically significant plasma peptide precursors (q < 0.05) was observed with timsTOF HT compared to Pro 2. Our data demonstrate the superior performance of timsTOF HT for identifying and quantifying differences between biologically diverse samples, allowing for improved disease biomarker discovery in large cohort studies. Moreover, researchers can leverage data sets from this study to optimize their liquid chromatography-mass spectrometry (LC-MS) workflows for plasma protein profiling and biomarker discovery. (ProteomeXchange identifier: PXD047854 and PXD047839).

Combined Proteomic and Phosphoproteomic Characterization of the Molecular Regulators and Functional Modules During Pancreatic Progenitor Cell Development.

Differentiated multipotent pancreatic progenitors have major advantages for both modeling pancreas development and preventing or treating diabetes. Despite significant advancements in inducing the differentiation of human pluripotent stem cells into insulin-producing cells, the complete mechanism governing proliferation and differentiation remains poorly understood. This study used large-scale mass spectrometry to characterize molecular processes at various stages of human embryonic stem cell (hESC) differentiation toward pancreatic progenitors. hESCs were induced into pancreatic progenitor cells in a five-stage differentiation protocol. A high-performance liquid chromatography-mass spectrometry platform was used to undertake comprehensive proteome and phosphoproteome profiling of cells at different stages. A series of bioinformatic explorations, including coregulated modules, gene regulatory networks, and phosphosite enrichment analysis, were then conducted. A total of 27,077 unique phosphorylated sites and 8122 proteins were detected, including several cyclin-dependent kinases at the initial stage of cell differentiation. Furthermore, we discovered that ERK1, a member of the MAPK cascade, contributed to proliferation at an early stage. Finally, Western blotting confirmed that the phosphosites from SIRT1 and CHEK1 could inhibit the corresponding substrate abundance in the late stage. Thus, this study extends our understanding of the molecular mechanism during pancreatic cell development.

Quantified Metabolomics and Lipidomics Profiles Reveal Serum Metabolic Alterations and Distinguished Metabolites of Seven Chronic Metabolic Diseases.

The co-occurrence of multiple chronic metabolic diseases is highly prevalent, posing a huge health threat. Clarifying the metabolic associations between them, as well as identifying metabolites which allow discrimination between diseases, will provide new biological insights into their co-occurrence. Herein, we utilized targeted serum metabolomics and lipidomics covering over 700 metabolites to characterize metabolic alterations and associations related to seven chronic metabolic diseases (obesity, hypertension, hyperuricemia, hyperglycemia, hypercholesterolemia, hypertriglyceridemia, fatty liver) from 1626 participants. We identified 454 metabolites were shared among at least two chronic metabolic diseases, accounting for 73.3% of all 619 significant metabolite-disease associations. We found amino acids, lactic acid, 2-hydroxybutyric acid, triacylglycerols (TGs), and diacylglycerols (DGs) showed connectivity across multiple chronic metabolic diseases. Many carnitines were specifically associated with hyperuricemia. The hypercholesterolemia group showed obvious lipid metabolism disorder. Using logistic regression models, we further identified distinguished metabolites of seven chronic metabolic diseases, which exhibited satisfactory area under curve (AUC) values ranging from 0.848 to 1 in discovery and validation sets. Overall, quantitative metabolome and lipidome data sets revealed widespread and interconnected metabolic disorders among seven chronic metabolic diseases. The distinguished metabolites are useful for diagnosing chronic metabolic diseases and provide a reference value for further clinical intervention and management based on metabolomics strategy.

A Framework for Quality Control in Quantitative Proteomics.

A thorough evaluation of the quality, reproducibility, and variability of bottom-up proteomics data is necessary at every stage of a workflow, from planning to analysis. We share vignettes applying adaptable quality control (QC) measures to assess sample preparation, system function, and quantitative analysis. System suitability samples are repeatedly measured longitudinally with targeted methods, and we share examples where they are used on three instrument platforms to identify severe system failures and track function over months to years. Internal QCs incorporated at the protein and peptide levels allow our team to assess sample preparation issues and to differentiate system failures from sample-specific issues. External QC samples prepared alongside our experimental samples are used to verify the consistency and quantitative potential of our results during batch correction and normalization before assessing biological phenotypes. We combine these controls with rapid analysis (Skyline), longitudinal QC metrics (AutoQC), and server-based data deposition (PanoramaWeb). We propose that this integrated approach to QC is a useful starting point for groups to facilitate rapid quality control assessment to ensure that valuable instrument time is used to collect the best quality data possible. Data are available on Panorama Public and ProteomeXchange under the identifier PXD051318.

Nontargeted Plasma Proteomic Analysis of Renal Disease and Pulmonary Hypertension in Patients with Sickle Cell Disease.

Sickle cell disease (SCD) is characterized by red blood cell sickling, vaso-occlusion, hemolytic anemia, damage to multiple organ systems, and, as a result, shortened life expectancy. Sickle cell disease nephropathy (SCDN) and pulmonary hypertension (pHTN) are common and frequently co-occurring complications of SCD; both are associated with markedly accelerated mortality. To identify candidate circulating biomarkers of SCDN and pHTN, we used mass spectrometry to quantify the relative abundance of >1000 proteins in plasma samples from 189 adults with SCD from the Outcome Modifying Genes in SCD (OMG-SCD) cohort (ProteomeXchange identifier PXD048716). Forty-four proteins were differentially abundant in SCDN, most significantly cystatin-C and collagen α-1(XVIII) chain (COIA1), and 55 proteins were dysregulated in patients with SCDN and pHTN, most significantly insulin-like growth factor-binding protein 6 (IBP6). Network analysis identified a module of 133 coregulated proteins significantly associated with SCDN, that was enriched for extracellular matrix proteins, insulin-like growth factor binding proteins, cell adhesion proteins, EGF-like calcium binding proteins, and several cadherin family members. Collectively, these data provide a comprehensive understanding of plasma protein changes in SCDN and pHTN which validate numerous studies of chronic kidney disease and suggest shared profiles of protein disruption in kidney dysfunction and pHTN among SCD patients.

High-Throughput Glycan Profiling of Human Serum IgG Subclasses Using Parallel Reaction Monitoring Peptide Bond Fragmentation of Glycopeptides and Microflow LC-MS.

LC-MS-based N-glycosylation profiling in four human serum IgG subclasses (IgG1, IgG2, IgG3, and IgG4) often requires additional affinity-based enrichment of specific IgG subclasses, owing to the high amino acid sequence similarity of Fc glycopeptides among subclasses. Notably, for IgG4 and the major allotype of IgG3, the glycopeptide precursors share identical retention time and mass and therefore cannot be distinguished based on precursor or glycan fragmentation. Here, we developed a parallel reaction monitoring (PRM)-based method for quantifying Fc glycopeptides through combined transitions generated from both glycosidic and peptide bond fragmentation. The latter enables the subpopulation of IgG3 and IgG4 to be directly distinguished according to mass differences without requiring further enrichment of specific IgG subclasses. In addition, a multinozzle electrospray emitter coupled to a capillary flow liquid chromatograph was used to increase the robustness and detection sensitivity of the method for low-yield peptide backbone fragment ions. The gradient was optimized to decrease the overall run time and make the method compatible with high-throughput analysis. We demonstrated that this method can be used to effectively monitor the relative levels of 13 representative glycoforms, with a good limit of detection for individual IgG subclasses.

Developing Method for Minor Acidic O-Glycan Analysis in Mucin and Cancer Cell Samples.

Minor acidic glycans, such as sulfated and phosphorylated glycans, constitute only a small fraction of biological glycome, making their analysis a considerable challenge. In this study, we developed a technique to analyze minor acidic O-glycans in biological samples. First, efficient reaction conditions for the release of O-glycans from the proteins were determined. Next, a high-throughput method was established for the recovery of minor acidic glycans using NH2 spin columns. The performance of the established method was evaluated using mucin samples, and sulfated O-glycans were successfully detected in bovine submaxillary gland mucin and porcine stomach mucin. We also analyzed the minor acidic O-glycans in cultured cancer cells. In addition to trifucosylated sulfated O-glycans and disulfated O-glycans, sulfated O-glycans with KDN were detected in LS174T cells. The relative amount of sulfated glycans in LS174T cells was almost 10-fold higher than that in the other cells. Moreover, a large polylactosamine-type sulfated O-glycan with a molecular weight >3500 was detected in MKN45 cells. Interestingly, phosphorylated ribose, possibly bound to serine/threonine, was observed in all the cells used in this study. Thus, our established analytical method allows for the analysis of minor acidic O-glycans that cannot be detected using existing glycomics methods.

Bottom-up Histone Post-translational Modification Analysis using Liquid Chromatography, Trapped Ion Mobility Spectrometry, and Tandem Mass Spectrometry.

The amino acid position within a histone sequence and the chemical nature of post-translational modifications (PTMs) are essential for elucidating the "Histone Code". Previous work has shown that PTMs induce specific biological responses and are good candidates as biomarkers for diagnostics. Here, we evaluate the analytical advantages of trapped ion mobility (TIMS) with parallel accumulation-serial fragmentation (PASEF) and tandem mass spectrometry (MS/MS) for bottom-up proteomics of model cancer cells. The study also considered the use of nanoliquid chromatography (LC) and traditional methods: LC-TIMS-PASEF-ToF MS/MS vs nLC-TIMS-PASEF-ToF MS/MS vs nLC-MS/MS. The addition of TIMS and PASEF-MS/MS increased the number of detected peptides due to the added separation dimension. All three methods showed high reproducibility and low RSD in the MS domain (<5 ppm). While the LC, nLC and TIMS separations showed small RSD across samples, the accurate mobility (1/K0) measurements (<0.6% RSD) increased the confidence of peptide assignments. Trends were observed in the retention time and mobility concerning the number and type of PTMs (e.g., ac, me1-3) and their corresponding unmodified, propionylated peptide that aided in peptide assignment. Mobility separation permitted the annotation of coeluting structural and positional isomers and compared with nLC-MS/MS showed several advantages due to reduced chemical noise.

Nonsevere Burn Induces a Prolonged Systemic Metabolic Phenotype Indicative of a Persistent Inflammatory Response Postinjury.

Globally, burns are a significant cause of injury that can cause substantial acute trauma as well as lead to increased incidence of chronic comorbidity and disease. To date, research has primarily focused on the systemic response to severe injury, with little in the literature reported on the impact of nonsevere injuries (<15% total burn surface area; TBSA). To elucidate the metabolic consequences of a nonsevere burn injury, longitudinal plasma was collected from adults (n = 35) who presented at hospital with a nonsevere burn injury at admission, and at 6 week follow up. A cross-sectional baseline sample was also collected from nonburn control participants (n = 14). Samples underwent multiplatform metabolic phenotyping using 1H nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry to quantify 112 lipoprotein and glycoprotein signatures and 852 lipid species from across 20 subclasses. Multivariate data modeling (orthogonal projections to latent structures-discriminate analysis; OPLS-DA) revealed alterations in lipoprotein and lipid metabolism when comparing the baseline control to hospital admission samples, with the phenotypic signature found to be sustained at follow up. Univariate (Mann-Whitney U) testing and OPLS-DA indicated specific increases in GlycB (p-value < 1.0e-4), low density lipoprotein-2 subfractions (variable importance in projection score; VIP > 6.83e-1) and monoacyglyceride (20:4) (p-value < 1.0e-4) and decreases in circulating anti-inflammatory high-density lipoprotein-4 subfractions (VIP > 7.75e-1), phosphatidylcholines, phosphatidylglycerols, phosphatidylinositols, and phosphatidylserines. The results indicate a persistent systemic metabolic phenotype that occurs even in cases of a nonsevere burn injury. The phenotype is indicative of an acute inflammatory profile that continues to be sustained postinjury, suggesting an impact on systems health beyond the site of injury. The phenotypes contained metabolic signatures consistent with chronic inflammatory states reported to have an elevated incidence postburn injury. Such phenotypic signatures may provide patient stratification opportunities, to identify individual responses to injury, personalize intervention strategies, and improve acute care, reducing the risk of chronic comorbidity.