Multiple reaction monitoring (MRM)-profiling for biomarker discovery applied to human polycystic ovarian syndrome

Discovery and Identification of Three Homocysteine Metabolites by Chemical Derivatization and Mass Spectrometry Fragmentation

Discovery and identification of a new endogenous metabolite are typically hindered by requirements of large sample volumes and multistage purifications to guide synthesis of the standard. Presented here is a metabolomics platform that uses chemical tagging and tandem mass spectrometry to determine structure, direct synthesis, and confirm identity. Three new homocysteine metabolites are reported: N-succinyl homocysteine, 2-methyl-1,3-thiazinane-4-carboxylic acid (MTCA), and homolanthinone.

Rumen-protected methionine supplementation alters lipid profile of preimplantation embryo and endometrial tissue of Holstein cows

Our objective is to evaluate the effects of feeding rumen-protected Met (RPM) throughout the transition period and early lactation on the lipid profile of the preimplantation embryos and the endometrial tissue of Holstein cows. Treatments consisted of feeding a total mixed ration with top-dressed RPM (Smartamine® M, Adisseo, Alpharetta, GA, United States; MET; n = 11; RPM at a rate of 0.08% of DM: Lys:Met = 2.8:1) or not (CON; n = 9, Lys:Met = 3.5:1). Endometrial biopsies were performed at 15, 30, and 73 days in milk (DIM). Prior to the endometrial biopsy at 73 DIM, preimplantation embryos were harvested via flushing. Endometrial lipid profiles were analyzed using multiple reaction monitoring-profiling and lipid profiles of embryos were acquired using matrix assisted laser desorption/ionization mass spectrometry. Relative intensities levels were used for principal component analysis. Embryos from cows in MET had greater concentration of polyunsaturated lipids than embryos from cows in CON. The endometrial tissue samples from cows in MET had lesser concentrations of unsaturated and monounsaturated lipids at 15 DIM, and greater concentration of saturated, unsaturated (specifically diacylglycerol), and monounsaturated (primarily ceramides) lipids at 30 DIM than the endometrial tissue samples from cows in CON. In conclusion, feeding RPM during the transition period and early lactation altered specific lipid classes and lipid unsaturation level of preimplantation embryos and endometrial tissue.

Interfacial Electromigration for Analysis of Biofluid Lipids in Small Volumes

Lipids are important biomarkers within the field of disease diagnostics and can serve as indicators of disease progression and predictors of treatment effectiveness. Although lipids can provide important insight into how diseases initiate and progress, mass spectrometric methods for lipid characterization and profiling are limited due to lipid structural diversity, particularly the presence of various lipid isomers. Moreover, the difficulty of handling small-volume samples exacerbates the intricacies of biological analyses. In this work, we have developed a strategy that electromigrates a thin film of a small-volume biological sample directly to the air-liquid interface formed at the tip of a theta capillary. Importantly, we seamlessly integrated in situ biological lipid extraction with accelerated chemical derivatization, enabled by the air-liquid interface, and conducted isomeric structural characterization within a unified platform utilizing theta capillary nanoelectrospray ionization mass spectrometry, all tailored for small-volume sample analysis. We applied this unified platform to the analysis of lipids from small-volume human plasma and Alzheimer's disease mouse serum samples. Accelerated electro-epoxidation of unsaturated lipids at the interface allowed us to characterize lipid double-bond positional isomers. The unique application of electromigration of a thin film to the air-liquid interface in combination with accelerated interfacial reactions holds great potential in small-volume sample analysis for disease diagnosis and prevention.

Amyloid β Induces Lipid Droplet-Mediated Microglial Dysfunction in Alzheimer's Disease

Several microglia-expressed genes have emerged as top risk variants for Alzheimer's disease (AD). Impaired microglial phagocytosis is one of the main proposed outcomes by which these AD-risk genes may contribute to neurodegeneration, but the mechanisms translating genetic association to cellular dysfunction remain unknown. Here we show that microglia form lipid droplets (LDs) upon exposure to amyloid-beta (Aβ), and that their LD load increases with proximity to amyloid plaques in brains from human patients and the AD mouse model 5xFAD. LD formation is dependent upon age and disease progression and is more prominent in the hippocampus in mice and humans. Despite variability in LD load between microglia from male versus female animals and between cells from different brain regions, LD-laden microglia exhibited a deficit in Aβ phagocytosis. Unbiased lipidomic analysis identified a substantial decrease in free fatty acids (FFAs) and a parallel increase in triacylglycerols (TAGs) as the key metabolic transition underlying LD formation. We demonstrate that DGAT2, a key enzyme for the conversion of FFAs to TAGs, promotes microglial LD formation, is increased in microglia from 5xFAD and human AD brains, and that inhibiting DGAT2 improved microglial uptake of Aβ. These findings identify a new lipid-mediated mechanism underlying microglial dysfunction that could become a novel therapeutic target for AD.

Analysis of Lipid Contents in Human Trabecular Meshwork Cells by Multiple Reaction Monitoring (MRM) Profiling Lipidomics

Lipids are among the major constituents of cells and play many important cellular functions. Lipid levels in the trabecular meshwork (TM) aqueous humor outflow pathway play an important role in the maintenance of aqueous humor drainage and intraocular pressure (IOP) homeostasis. Therefore, it is important to characterize the changes in the lipid contents in the aqueous humor outflow pathway tissues to better understand their functional significance in the maintenance of IOP. The multiple reaction monitoring (MRM)-based profiling aids in the analysis of the metabolome as a collection of functional groups and is utilized as an exploratory metabolomics and lipidomics approach. The MRM-based profiling utilizes tandem mass spectrometry experiments carried out on a commercial triple quadrupole mass spectrometer with three aligned quadrupole mass filters (Q1, Q2, and Q3). This screening methodology can be utilized for targeted lipidomics screening. This chapter focuses on the methodology for isolation and culturing of the TM cells, lipid extraction, and the MRM-based lipidomics approach with data analysis.

Targeted Lipidomics Analysis of Adipose and Skeletal Muscle Tissues by Multiple Reaction Monitoring Profiling

Lipid homeostasis is critical for maintaining normal cellular functions including membrane structural integrity, cell metabolism, and signal transduction. Adipose tissue and skeletal muscle are two major tissues involved in lipid metabolism. Adipose tissue can store excessive lipids in the form of triacylglyceride (TG), which can be hydrolyzed to release free fatty acids (FFAs) under insufficient nutrition states. In the highly energy-demanding skeletal muscle, lipids serve as oxidative substrates for energy production but can cause muscle dysfunction when overloaded. Lipids undergo fascinating cycles of biogenesis and degradation depending on physiological demands, while dysregulation of lipid metabolism has been increasingly recognized as a hallmark of diseases such as obesity and insulin resistance. Thus, it is important to understand the diversity and dynamics of lipid composition in adipose tissue and skeletal muscle. Here, we describe the use of multiple reaction monitoring profiling, based on lipid class and fatty acyl chain specific fragmentation, to explore various classes of lipids in skeletal muscle and adipose tissues. We provide a detailed method for exploratory analysis of acylcarnitine (AC), ceramide (Cer), cholesteryl ester (CE), diacylglyceride (DG), FFA, phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylglycerol (PG), phosphatidylinositol (PI), phosphatidylserine (PS), sphingomyelin (SM), and TG. Characterization of lipid composition within adipose tissue and skeletal muscle under different physiological situations will provide biomarkers and therapeutic targets for obesity-related diseases.

Suspect screening of exogenous compounds using multiple reaction screening (MRM) profiling in human urine samples

Thousands of chemical compounds produced by industry are dispersed in the human environment widely enough to reach the world population, and the introduction of new chemicals constantly occurs. As new synthetic molecules emerge, rapid analytical workflows for screening possible presence of exogenous compounds in biofluids can be useful as a first pass analysis to detect chemical exposure and guide the development and application of more elaborate LC-MS/MS methods for quantification. In this study, a suspect screening workflow using the multiple reaction monitoring (MRM) profiling method is proposed as a first pass exploratory technique to survey selected exogenous molecules in human urine samples. The workflow was applied to investigate 12 human urine samples using 310 MRMs related to the chemical functionalities of 87 exogenous compounds present in the METLIN database and reported in the literature. A total of 11 MRMs associated with five different compounds were detected in the samples. Product ion scans for the precursor ions of the selected MRMs were acquired as a further identification step for these chemicals. The suspect screening results suggested the presence of five exogenous compounds in the human urine samples analyzed, namely metformin, metoprolol, acetaminophen, paraxanthine and acrylamide. LC-MS/MS was applied as a last step to confirm these results, and the presence of four out of the five targets selected by MRM profiling were corroborated, indicating that this workflow can support the selection of suspect compounds to screen complex samples and guide more time-consuming and specific quantification analyses.

Follicular Fluid: A Powerful Tool for the Understanding and Diagnosis of Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) represents one of the leading causes of anovulatory infertility and affects 5% to 20% of women worldwide. Until today, both the subsequent etiology and pathophysiology of PCOS remain unclear, and patients with PCOS that undergo assisted reproductive techniques (ART) might present a poor to exaggerated response, low oocyte quality, ovarian hyperstimulation syndrome, as well as changes in the follicular fluid metabolites pattern. These abnormalities originate a decrease of Metaphase II (MII) oocytes and decreased rates for fertilization, cleavage, implantation, blastocyst conversion, poor egg to follicle ratio, and increased miscarriages. Focus on obtaining high-quality embryos has been taken into more consideration over the years. Nowadays, the use of metabolomic analysis in the quantification of proteins and peptides in biological matrices might predict, with more accuracy, the success in assisted reproductive technology. In this article, we review the use of human follicular fluid as the matrix in metabolomic analysis for diagnostic and ART predictor of success for PCOS patients.

Lipid profiling suggests species specificity and minimal seasonal variation in Pacific Green and Hawksbill Turtle plasma

In this study, we applied multiple reaction monitoring (MRM)-profiling to explore the relative ion intensity of lipid classes in plasma samples from sea turtles in order to profile lipids relevant to sea turtle physiology and investigate how dynamic ocean environments affect these profiles. We collected plasma samples from foraging green (Chelonia mydas, n = 28) and hawksbill (Eretmochelys imbricata, n = 16) turtles live captured in North Pacific Costa Rica in 2017. From these samples, we identified 623 MRMs belonging to 10 lipid classes (sphingomyelin, phosphatidylcholine, free fatty acid, cholesteryl ester, phosphatidylserine, phosphatidylinositol, phosphatidylglycerol, phosphatidylethanolamine, ceramide, and triacylglyceride) and one metabolite group (acyl-carnitine) present in sea turtle plasma. The relative ion intensities of most lipids (80%) were consistent between species, across seasons, and were not correlated to body size or estimated sex. Of the differences we observed, the most pronounced was the differences in relative ion intensity between species. We identified 123 lipids that had species-specific relative ion intensities. While some of this variability is likely due to green and hawksbill turtles consuming different food items, we found indications of a phylogenetic component as well. Of these, we identified 47 lipids that varied by season, most belonging to the structural phospholipid classes. Overall, more lipids (n = 39) had higher relative ion intensity in the upwelling (colder) season compared to the non-upwelling season (n = 8). Further, we found more variability in hawksbill turtles than green turtles. Here, we provide the framework in which to apply future lipid profiling in the assessment of health, physiology, and behavior in endangered sea turtles.

Multiple reaction monitoring profiling (MRM profiling): Small molecule exploratory analysis guided by chemical functionality

Small molecules, including metabolites and lipids, provide information on metabolic pathways and active biological processes in living organisms. They are often diagnostic of disease. Current exploratory methods for metabolomics and lipidomics mostly rely on separation using liquid or gas chromatography (LC or GC) coupled with mass spectrometers capable of acquiring high resolution data to generate an enormous data, but at the cost of lengthy processing and data acquisition. Even though many molecules can be identified and quantified by these methods, the laborious protocols for purification, identification, and validation limit the accessible sample chemical information. To improve the speed and efficiency of exploratory metabolomics and lipidomics, multiple reaction monitoring profiling (MRM profiling) has been developed. This strategy involves a three-stage workflow which starts by considering the metabolome as a collection of functional groups. The Discovery Stage interrogates a representative sample mixture for functional groups using the functional group specific precursor ion (Prec) scans and neutral loss (NL) scans. This experiment usually uses a triple quadrupole mass spectrometer without chromatography, i.e. by direct sample infusion. In the second Screening Stage, the main features seen in the Prec and NL scans are organized into lists of precursor ion/product ion transitions (MRMs) which are then used for the fast, specific, and sensitive interrogation of each individual sample. Data analysis by univariate and multivariate statistical methods is used to identify the most informative MRMs and so classify the individual samples. The compounds (biomarkers) which are responsible for the most informative MRMs in particular sample classes can be investigated in an optional third Identification Stage i.e. in a structural identification study. MRM profiling benefits from the much smaller number of functional groups compared to the number of individual metabolites existing in biological samples (where most metabolites are still unknown), resulting in acquisition of a much smaller data set and a shorter analysis time. The application of MRM Profiling to several biological and clinical problems is used to illustrate its features.

Lipidomic Profiling of the Epidermis in a Mouse Model of Dermatitis Reveals Sexual Dimorphism and Changes in Lipid Composition before the Onset of Clinical Disease

Atopic dermatitis (AD) is a multifactorial disease associated with alterations in lipid composition and organization in the epidermis. Multiple variants of AD exist with different outcomes in response to therapies. The evaluation of disease progression and response to treatment are observational assessments with poor inter-observer agreement highlighting the need for molecular markers. SHARPIN-deficient mice (Sharpin^cpdm) spontaneously develop chronic proliferative dermatitis with features similar to AD in humans. To study the changes in the epidermal lipid-content during disease progression, we tested 72 epidermis samples from three groups (5-, 7-, and 10-weeks old) of cpdm mice and their WT littermates. An agnostic mass-spectrometry strategy for biomarker discovery termed multiple-reaction monitoring (MRM)-profiling was used to detect and monitor 1,030 lipid ions present in the epidermis samples. In order to select the most relevant ions, we utilized a two-tiered filter/wrapper feature-selection strategy. Lipid categories were compressed, and an elastic-net classifier was used to rank and identify the most predictive lipid categories for sex, phenotype, and disease stages of cpdm mice. The model accurately classified the samples based on phospholipids, cholesteryl esters, acylcarnitines, and sphingolipids, demonstrating that disease progression cannot be defined by one single lipid or lipid category.

Cytokines in the grass, a lesson learnt: Measuring cytokines in plasma using multiple reaction monitoring mass spectrometry

RATIONALE

Cytokines are cell regulatory molecules of high importance as indicators for homeostasis and pathology in many species. The current method to measure cytokines in body fluids is reagent dependent, requiring highly specific paired antibodies.

METHODS

A liquid chromatography/multiple reaction monitoring mass spectrometry (LC/MRM-MS)-based approach was developed to simultaneously establish the limits of detection (LODs) and quantification (LOQs) for recombinant cytokines IL-1β, IL-6, IFNγ and TNFα as pure standards and in bovine sera. All experimental LC/MRM-MS data are available at CSIRO Data Access Portal repository under identifier doi.org/10.25919/5de8a0232a862.

RESULTS

The present method enabled LODs and LOQs as low as 1.05 and 1.12 fmol/μL in the experiment comprised of pure standards. Comparable results were obtained in the experiment where digested cytokines were mixed with pre-digested sera proteins. The intrinsic matrix effects were evident when intact cytokines were co-digested within undiluted and undigested sera decreasing the ability to detect and quantify cytokines by 10,000-fold compared with pure standards and pre-digested sera.

CONCLUSIONS

The developed LC/MRM-MS method provided insights into the difficulties in detecting the target peptides when embedded in complex matrices. Nonetheless, the method may potentially be readily applied in biomarker-focused research interrogating fluids of lesser complexity such as synovial fluid, cerebrospinal fluid and tissue culture media.

Exacerbation of Nanoparticle-Induced Acute Pulmonary Inflammation in a Mouse Model of Metabolic Syndrome

Nanotechnology has the capacity to revolutionize numerous fields and processes, however, exposure-induced health effects are of concern. The majority of nanoparticle (NP) safety evaluations have been performed utilizing healthy models and have demonstrated the potential for pulmonary toxicity. A growing proportion of individuals suffer diseases that may enhance their susceptibility to exposures. Specifically, metabolic syndrome (MetS) is increasingly prevalent and is a risk factor for the development of chronic diseases including type-2 diabetes, cardiovascular disease, and cancer. MetS is a combination of conditions which includes dyslipidemia, obesity, hypertension, and insulin resistance. Due to the role of lipids in inflammatory signaling, we hypothesize that MetS-associated dyslipidemia may modulate NP-induced immune responses. To examine this hypothesis, mice were fed either a control diet or a high-fat western diet (HFWD) for 14-weeks. A subset of mice were treated with atorvastatin for the final 7-weeks to modulate lipids. Mice were exposed to silver NPs (AgNPs) via oropharyngeal aspiration and acute toxicity endpoints were evaluated 24-h post-exposure. Mice on the HFWD demonstrated MetS-associated alterations such as increased body weight and cholesterol compared to control-diet mice. Cytometry analysis of bronchoalveolar lavage fluid (BALF) demonstrated exacerbation of AgNP-induced neutrophilic influx in MetS mice compared to healthy. Additionally, enhanced proinflammatory mRNA expression and protein levels of monocyte chemoattractant protein-1, macrophage inflammatory protein-2, and interleukin-6 were observed in MetS mice compared to healthy following exposure. AgNP exposure reduced mRNA expression of enzymes involved in lipid metabolism, such as arachidonate 5-lipoxygenase and arachidonate 15-lipoxygenase in both mouse models. Exposure to AgNPs decreased inducible nitric oxide synthase gene expression in MetS mice. An exploratory lipidomic profiling approach was utilized to screen lipid mediators involved in pulmonary inflammation. This assessment indicates the potential for reduced levels of lipids mediators of inflammatory resolution (LMIR) in the MetS model compared to healthy mice following AgNP exposure. Statin treatment inhibited enhanced inflammatory responses as well as alterations in LMIR observed in the MetS model due to AgNP exposure. Taken together our data suggests that MetS exacerbates the acute toxicity induced by AgNPs exposure possibly via a disruption of LMIR leading to enhanced pulmonary inflammation.

Spectral deep learning for prediction and prospective validation of functional groups

State-of-the-art identification of the functional groups present in an unknown chemical entity requires the expertise of a skilled spectroscopist to analyse and interpret Fourier transform infra-red (FTIR), mass spectroscopy (MS) and/or nuclear magnetic resonance (NMR) data. This process can be time-consuming and error-prone, especially for complex chemical entities that are poorly characterised in the literature, or inefficient to use with synthetic robots producing molecules at an accelerated rate. Herein, we introduce a fast, multi-label deep neural network for accurately identifying all the functional groups of unknown compounds using a combination of FTIR and MS spectra. We do not use any database, pre-established rules, procedures, or peak-matching methods. Our trained neural network reveals patterns typically used by human chemists to identify standard groups. Finally, we experimentally validated our neural network, trained on single compounds, to predict functional groups in compound mixtures. Our methodology showcases practical utility for future use in autonomous analytical detection.

An Integrative Proteomic/Lipidomic Analysis of the Gold Nanoparticle Biocorona in Healthy and Obese Conditions

Introduction: When nanoparticles (NPs) enter a physiological environment, a coating of biomolecules or biocorona (BC) forms on the surface. Formation of the NP-BC is dependent on NP properties, the physiological environment, and time. The BC influences NP properties and biological interactions such as cellular internalization, immune responses, biodistribution, and others, leading to pharmacological and toxicological consequences. To date, examination of the NP-BC has focused primarily on protein components and healthy conditions. Therefore, we evaluated the protein and lipid content of BCs that formed on physicochemically distinct gold nanoparticles (AuNPs) under healthy and obese conditions. A comprehensive understanding of the NP-BC is necessary for the translation of in vitro toxicity assessments to clinical applications. Materials and Methods: AuNPs with two coatings (poly-N-vinylpyrrolidone [PVP] or citrate) and diameters (20 or 100 nm) were incubated in pooled human serum, and an integrated proteomic/lipidomic approach was used to evaluate BC composition. Macrophages were utilized to evaluate differential immune responses due to variations in the AuNP-BC. Results: AuNPs form distinct BCs based on physicochemical properties and the surrounding environment, with the obese BC containing more proteins and fewer lipids than the healthy BC. Differential macrophage inflammatory responses were observed based on AuNP properties and BC composition. Discussion and Conclusion: Overall, these findings demonstrate that AuNP size and coating, as well as physiological environment, influence the protein and lipid composition of the BC, which impacts cellular responses following exposure. These findings demonstrate that incorporation of BCs representing distinct physiological conditions may enhance the translatability of nanosafety in vitro studies.

An update on the aspects of Zika virus infection on male reproductive system

Zika virus (ZIKV) is mainly transmitted through Aedes mosquito bites, but sexual and post-transfusion transmissions have been reported. During acute infection, ZIKV is detectable in most organs and body fluids including human semen. Although it is not currently epidemic, there is a concern that the virus can still reemerge since the male genital tract might harbor persistent reservoirs that could facilitate viral transmission over extended periods, raising concerns among public health and assisted reproductive technologies (ART) experts and professionals. So far, the consensus is that ZIKV infection in the testes or epididymis might affect sperm development and, consequently, male fertility. Still, diagnostic tests have not yet been adapted to resource-restricted countries. This manuscript provides an updated overview of the cellular and molecular mechanisms of ZIKV infection and reviews data on ZIKV persistence in semen and associated risks to the male reproductive system described in human and animal models studies. We provide an updated summary of the impact of the recent ZIKV outbreak on human-ART, weighing on current recommendations and diagnostic approaches, both available and prospective, with special emphasis on mass spectrometry-based biomarker discovery. In the light of the identified gaps in our accumulated knowledge on the subject, we highlight the importance for couples seeking ART to follow the constantly revised guidelines and the need of specific ZIKV diagnosis tools for semen screening to contain ZIKV virus spread and make ART safer.

Challenges in Identifying the Dark Molecules of Life

Metabolomics is the study of the metabolome, the collection of small molecules in living organisms, cells, tissues, and biofluids. Technological advances in mass spectrometry, liquid- and gas-phase separations, nuclear magnetic resonance spectroscopy, and big data analytics have now made it possible to study metabolism at an omics or systems level. The significance of this burgeoning scientific field cannot be overstated: It impacts disciplines ranging from biomedicine to plant science. Despite these advances, the central bottleneck in metabolomics remains the identification of key metabolites that play a class-discriminant role. Because metabolites do not follow a molecular alphabet as proteins and nucleic acids do, their identification is much more time consuming, with a high failure rate. In this review, we critically discuss the state-of-the-art in metabolite identification with specific applications in metabolomics and how technologies such as mass spectrometry, ion mobility, chromatography, and nuclear magnetic resonance currently contribute to this challenging task.

Histologic analysis and lipid profiling reveal reproductive age-associated changes in peri-ovarian adipose tissue

BACKGROUND

Reproductive aging is a robust phenotype that occurs in all females and is characterized by a significant reduction in gamete quantity and quality, which can have negative consequences on both endocrine function and fertility. Age-associated differences in the oocyte, follicle, and ovary have been well-documented, but how the broader environment changes with age is less well understood. Fat is one of the largest organs in the body, and peri-gonadal adipose tissue surrounds the rodent ovary and comprises a local ovarian environment. The goal of this study was to characterize how peri-ovarian adipose tissue changes with advanced reproductive age.

METHODS

We isolated peri-gonadal adipose tissue from two cohorts of CB6F1 mice: reproductively young (6-12 weeks) and reproductively old (14-17 months). A comparative histological analysis was performed to evaluate adipocyte architecture. We then extracted lipids from the tissue and performed multiple reaction monitoring (MRM)-profiling, a mass spectrometry-based method of metabolite profiling, to compare the lipid profiles of peri-gonadal adipose tissue in these age cohorts.

RESULTS

We found that advanced reproductive age was associated with adipocyte hypertrophy and a corresponding decrease in the number of adipocytes per area. Of the 10 lipid classes examined, triacylglycerols (TAGs) had significantly different profiles between young and old cohorts, despite quantitative analysis revealing a decrease in the total amount of TAGs per weight of peri-gonadal adipose tissue with age.

CONCLUSIONS

These findings pinpoint age-associated physiological changes in peri-gonadal adipose tissue with respect to adipocyte morphology and lipid profiles and lay the foundation for future studies to examine how these alterations may influence both adipocyte and ovarian function.

Multiple reaction monitoring (MRM)-profiling with biomarker identification by LC-QTOF to characterize coronary artery disease

Metabolite profiling by mass spectrometry (MS) is an area of interest for disease diagnostics, biomarker discovery, and therapeutic evaluation. A recently developed approach, multiple reaction monitoring (MRM)-profiling, searches for metabolites with precursor (Prec) and neutral loss (NL) scans in a representative sample and creates a list of ion transitions. These are then used in an MRM method for fast screening of individual samples and discrimination between healthy and diseased. A large variety of functional groups are considered and all signals discovered are recorded in the individual samples, making this a largely unsupervised method. MRM-profiling is described here and then demonstrated with data for over 900 human plasma coronary artery disease (CAD) samples. Representative pooled samples for each condition were interrogated using a library of over a hundred Prec and NL scans on a triple quadrupole MS. The data from the Prec and NL experiments were converted into ion transitions, initially some 1266 transitions. Each ion transition was examined in the individual samples on a time scale of milliseconds per transition, which allows for rapid screening of large sample sets (<5 days for 1000 samples). Use of univariate and multivariate statistics allowed classification of the sample set with high accuracy. The metabolite profiles classified the CAD female, CAD male, and peripheral artery disease (PAD) samples relative to controls with an accuracy of 90%, 78%, and 85%, respectively. The compounds responsible for informative ion transitions were identified by chromatography and high resolution MS; some have been previously reported and found to be associated with coronary artery disease metabolism, indicating that the methodology generates a meaningful metabolite profile while being faster than traditional methodologies.

Using single cell analysis for translational studies in immune mediated diseases: Opportunities and challenges

The difficulty of studying small tissue samples and rare cell populations have been some of the main limitations in performing efficient translational studies of immune mediated diseases. Many of these conditions are grouped under the name of a single disease whilst there are strong suggestions that disease heterogeneity leads to variable disease progression as well as therapeutic responses. The recent development of single cell techniques, such as single cell RNA sequencing, gene expression profiling, or multiparametric cytometry, is likely to be a turning point. Single cell approaches provide researchers the opportunity to finally dissect disease pathology at a level that will allow mechanistic classifications and precision therapeutic strategies. In this review, we will give an overview of the current and developing repertoire of single cell techniques, the benefits and limitations of each, and provide an example of how single cell techniques can be utilized to understand complex immune mediated diseases and their translation from mouse to human.

Mass Spectrometry for Synthesis and Analysis

Mass spectrometry is the science and technology of ions. As such, it is concerned with generating ions, measuring their properties, following their reactions, isolating them, and using them to build and transform materials. Instrumentation is an essential element of these activities, and analytical applications are one driving force. Work from the Aston Laboratories at Purdue University's Department of Chemistry is described here, with an emphasis on accelerated reactions of ions in solution and small-scale synthesis; ion/surface collision processes, including surface-induced dissociation (SID) and ion soft landing; and applications to tissue imaging. Our special interest in chirality and the chemistry behind the origins of life is also featured together with the exciting area of tissue diagnostics.

Profiling of epidermal lipids in a mouse model of dermatitis: Identification of potential biomarkers

Lipids are important structural and functional components of the skin. Alterations in the lipid composition of the epidermis are associated with inflammation and can affect the barrier function of the skin. SHARPIN-deficient cpdm mice develop a chronic dermatitis with similarities to atopic dermatitis in humans. Here, we used a recently-developed approach named multiple reaction monitoring (MRM)-profiling and single ion monitoring to rapidly identify discriminative lipid ions. Shorter fatty acyl residues and increased relative amounts of sphingosine ceramides were observed in cpdm epidermis compared to wild type mice. These changes were accompanied by downregulation of the Fasn gene which encodes fatty acid synthase. A profile of diverse lipids was generated by fast screening of over 300 transitions (ion pairs). Tentative attribution of the most significant transitions was confirmed by product ion scan (MS/MS), and the MRM-profiling linear intensity response was validated with a C17-ceramide lipid standard. Relative quantification of sphingosine ceramides CerAS(d18:1/24:0)2OH, CerAS(d18:1/16:0)2OH and CerNS(d18:1/16:0) discriminated between the two groups with 100% accuracy, while the free fatty acids cerotic acid, 16-hydroxy palmitic acid, and docosahexaenoic acid (DHA) had 96.4% of accuracy. Validation by liquid chromatography tandem mass spectrometry (LC-MS/MS) of the above-mentioned ceramides was in agreement with MRM-profiling results. Identification and rapid monitoring of these lipids represent a tool to assess therapeutic outcomes in SHARPIN-deficient mice and other mouse models of dermatitis and may have diagnostic utility in atopic dermatitis.

Hyper response to ovarian stimulation affects the follicular fluid metabolomic profile of women undergoing IVF similarly to polycystic ovary syndrome

INTRODUCTION

During in vitro fertilization (IVF), the hyper response to controlled ovarian stimulation (COS) is a common characteristic among patients diagnosed with polycystic ovary syndrome (PCOS), although non-diagnosed patients may also demonstrate this response.

OBJECTIVES

In an effort to investigate follicular metabolic characteristics associated with hyper response to COS, the present study analyzed follicular fluid (FF) samples from patients undergoing IVF.

METHODS

FF samples were obtained from patients with PCOS and hyper response during IVF (PCOS group, N = 15), patients without PCOS but with hyper response during IVF (HR group, N = 44), and normo-responder patients receiving IVF (control group, N = 22). FF samples underwent Bligh and Dyer extraction, followed by metabolomic analysis by ultra-performance liquid chromatography mass spectrometry, considering two technical replicates. Clinical data was analyzed by ANOVA and chi-square tests. The metabolomic dataset was analyzed by multivariate statistics, and the significance of biomarkers was confirmed by ANOVA.

RESULTS

Clinical data showed differences regarding follicles production, oocyte and embryo quality. From the 15 proposed biomarkers, 14 were of increased abundance in the control group and attributed as fatty acids, diacylglycerol, triacylglycerol, ceramide, ceramide-phosphate, phosphatidylcholine, and sphingomyelin. The PCOS patients showed increased abundance of a metabolite of m/z 144.0023 that was not attributed to a class.

CONCLUSION

The clinical and metabolic similarities observed in the FF of hyper responders with and without PCOS diagnosis indicate common biomarkers that could assist on the development of accessory tools for assessment of IVF parameters.

Multiple Reaction Monitoring Profiling to Assess Compliance with an Almond Consumption Intervention

Background: Almonds are extremely rich sources of lipids and flavonoids, and their consumption is associated with several health benefits. However, there are no analytical methods available to document compliance with prescribed or self-reported chronic almond consumption. Objective: The aim was to use an analytical approach that identifies metabolic profiles associated with long-term almond consumption to ascertain compliance with prescribed consumption. Methods: A multiple reaction monitoring (MRM)-profiling strategy was designed to isolate metabolic changes in erythrocytes after 12 wk of almond consumption. MRM-profiling data acquisition and analysis involve performing separate discovery and screening steps to detect molecular features related to metabolic changes between experimental groups. Samples used for this research were erythrocytes recovered at baseline, after 12 wk of almond consumption (W12-almond group), and after 12 wk of a nut-free diet (W12-control group). For the MRM-profiling discovery step, representative samples (pools) of erythrocytes from individuals of all groups were interrogated by precursor ion and neutral loss scan experiments on the basis of previous knowledge of chemical functional groups present in the samples. The outputs of the discovery phase were methods used for the MRM-profiling screening phase to interrogate individual samples on the basis of fast-MRM measurements. In addition, we screened the literature for flavonoids identified in almond skins and included them for individual sample screening. Results: Of the 254 m/z values monitored, 5 ratios and combinations of specific ions with receiver operating characteristic curve AUCs >0.89 provided a sensitivity of 74.2% and a specificity of 90% for blind samples presented in the model. Eight of the 31 participants (25.8%) in the W12-almond group and 3 of the 30 (10%) participants in the W12-control group were misclassified by all 5 ratios. Ratios and combinations of specific transitions were mainly related to membrane lipids. Conclusion: The misclassifications observed as a result of ratio performance evaluation may indicate noncompliance as supported by the dietary intake data. The parent trial was registered at www.clinicaltrials.gov as NCT02360787.