Mass Spectrometric Platform Research Articles

Moderate High Caloric Maternal Diet Impacts Dam Breast Milk Metabotype and Offspring Lipidome in a Sex-Specific Manner.

Lactation is a critical period during which maternal sub- or over-nutrition affect milk composition and offspring development that can have lasting health effects. The consequences of moderate high-fat, high-simple carbohydrate diet (WD) consumption by rat dams, during gestation and lactation, on milk composition and offspring blood lipidome and its growth, at weaning, were investigated by using a comprehensive lipidomic study on mass-spectrometric platform combined to targeted fatty- and free amino-acids analysis. This holistic approach allowed clear-cut differences in mature milk-lipidomic signature according to maternal diet with a similar content of protein, lactose and leptin. The lower WD-milk content in total fat and triglycerides (TGs), particularly in TGs-with saturated medium-chain, and higher levels in both sphingolipid (SL) and TG species with unsaturated long-chain were associated to a specific offspring blood-lipidome with decreased levels in TGs-containing saturated fatty acid (FA). The sexual-dimorphism in the FA-distribution in TG (higher TGs-rich in oleic and linoleic acids, specifically in males) and SL species (increased levels in very long-chain ceramides, specifically in females) could be associated with some differences that we observed between males and females like a higher total body weight gain in females and an increased preference for fatty taste in males upon weaning.

Gingival Crevicular Fluid Peptidome Profiling in Healthy and in Periodontal Diseases.

Given its intrinsic nature, gingival crevicular fluid (GCF) is an attractive source for the discovery of novel biomarkers of periodontal diseases. GCF contains antimicrobial peptides and small proteins which could play a role in specific immune-inflammatory responses to guarantee healthy gingival status and to prevent periodontal diseases. Presently, several proteomics studies have been performed leading to increased coverage of the GCF proteome, however fewer efforts have been done to explore its natural peptides. To fill such gap, this review provides an overview of the mass spectrometric platforms and experimental designs aimed at GCF peptidome profiling, including our own data and experiences gathered from over several years of matrix-assisted laser desorption ionization/time of flight mass spectrometry (MALDI-TOF MS) based approach in this field. These tools might be useful for capturing snapshots containing diagnostic clinical information on an individual and population scale, which may be used as a specific code not only for the diagnosis of the nature or the stage of the inflammatory process in periodontal disease, but more importantly, for its prognosis, which is still an unmet medical need. As a matter of fact, current peptidomics investigations suffer from a lack of standardized procedures, posing a serious problem for data interpretation. Descriptions of the efforts to address such concerns will be highlighted.

Single-Cell Classification Using Mass Spectrometry through Interpretable Machine Learning.

The brain consists of organized ensembles of cells that exhibit distinct morphologies, cellular connectivity, and dynamic biochemistries that control the executive functions of an organism. However, the relationships between chemical heterogeneity, cell function, and phenotype are not always understood. Recent advancements in matrix-assisted laser desorption/ionization mass spectrometry have enabled the high-throughput, multiplexed chemical analysis of single cells, capable of resolving hundreds of molecules in each mass spectrum. We developed a machine learning workflow to classify single cells according to their mass spectra based on cell groups of interest (GOI), e.g., neurons vs astrocytes. Three data sets from various cell groups were acquired on three different mass spectrometer platforms representing thousands of individual cell spectra that were collected and used to validate the single cell classification workflow. The trained models achieved >80% classification accuracy and were subjected to the recently developed instance-based model interpretation framework, SHapley Additive exPlanations (SHAP), which locally assigns feature importance for each single-cell spectrum. SHAP values were used for both local and global interpretations of our data sets, preserving the chemical heterogeneity uncovered by the single-cell analysis while offering the ability to perform supervised analysis. The top contributing mass features to each of the GOI were ranked and selected using mean absolute SHAP values, highlighting the features that are specific to the defined GOI. Our approach provides insight into discriminating the chemical profiles of the single cells through interpretable machine learning, facilitating downstream analysis and validation.

A microfluidic platform integrating paper adsorption-based sample clean-up and voltage-assisted liquid desorption electrospray ionization mass spectrometry for biological sample analysis

Clinical application of direct sampling electrospray ionization mass spectrometry (ESI-MS) remains limited due to problems associated with very “dirty” sample matrices. Herein we report on a microfluidic platform that allows direct mass spectrometric analysis of serum samples of microliter sizes. The platform integrates in-line paper adsorption-based sample clean-up and voltage assisted liquid desorption ESI-MS/MS (VAL DESI-MS/MS) to detect multiple targeted compounds of clinical interest. Adenosine monophosphate (AMP), adenosine diphosphate (ADP), and adenosine triphosphate (ATP) were selected as model analytes. Simultaneous quantification of these compounds in human serum samples was demonstrated. For all the three compounds, linear calibration curves were obtained in a concentration range from 0.20 to 20.0 μmol/L with r2 values ≥ 0.996. Limits of detection were 0.019, 0.015, and 0.011 μmol/L for AMP, ADP, and ATP, respectively. Recovery was found in the range from 96.5% to 103.5% at spiking concentrations of 0.25 and 2.50 μmol/L. The results indicate that the proposed microfluidic mass spectrometric platform is robust and effective. It may have a potential in clinical analysis.

Sample multiplexing for targeted pathway proteomics in aging mice

Pathway proteomics strategies measure protein expression changes in specific cellular processes that carry out related functions. Using targeted tandem mass tags-based sample multiplexing, hundreds of proteins can be quantified across 10 or more samples simultaneously. To facilitate these highly complex experiments, we introduce a strategy that provides complete control over targeted sample multiplexing experiments, termed Tomahto, and present its implementation on the Orbitrap Tribrid mass spectrometer platform. Importantly, this software monitors via the external desktop computer to the data stream and inserts optimized MS2 and MS3 scans in real time based on an application programming interface with the mass spectrometer. Hundreds of proteins of interest from diverse biological samples can be targeted and accurately quantified in a sensitive and high-throughput fashion. It achieves sensitivity comparable to, if not better than, deep fractionation and requires minimal total sample input (∼10 µg). As a proof-of-principle experiment, we selected four pathways important in metabolism- and inflammation-related processes (260 proteins/520 peptides) and measured their abundance across 90 samples (nine tissues from five old and five young mice) to explore effects of aging. Tissue-specific aging is presented here and we highlight the role of inflammation- and metabolism-related processes in white adipose tissue. We validated our approach through comparison with a global proteome survey across the tissues, work that we also provide as a general resource for the community.

Combining Targeted and Untargeted Data Acquisition to Enhance Quantitative Plant Proteomics Experiments.

Most quantitative proteomics experiments either target a limited number of selected proteins for quantification or quantify proteins on a broad scale in an untargeted manner. However, we recently demonstrated that experiments that have both targeted and untargeted components can be particularly advantageous. Using a combined targeted and untargeted liquid chromatography-tandem mass spectrometry data acquisition strategy termed TDA/DDA (shorthand for targeted data acquisition/data-dependent acquisition), which we applied to a model quantitative plant proteomics experiment performed on Arabidopsis, we demonstrated improved quantification of both targeted and untargeted proteins relative to purely untargeted experiments performed using conventional data-dependent acquisition (Hart-Smith et al. Front Plant Sci 8:1669, 2017). This suggests that many quantitative proteomics datasets earmarked for collection using data-dependent acquisition are likely to benefit from the use of TDA/DDA instead.This chapter describes how TDA/DDA liquid chromatography-tandem mass spectrometry methods can be created on commonly used mass spectrometric instrument platforms. It described how, using freely available software, tandem mass spectrometry inclusion lists designed to target proteins of hypothesized interest can be generated. Best practice implementation of these inclusion lists in TDA/DDA strategies is then described. Relative to conventional data-dependent acquisition, the liquid chromatography-tandem mass spectrometry methods created using these guidelines increase the chances of quantifying targeted proteins and can produce widespread improvements in the reproducibility of untargeted protein quantification, without compromising the total numbers of proteins quantified. They are compatible with different quantitative proteomics methodologies, including metabolic labeling, chemical labeling and label-free approaches, and can be used to create tailored assay libraries to aid the interpretation of quantitative proteomics data collected using data-independent acquisition.

Molecular networking as a dereplication strategy for monitoring metabolites of natural product treated cancer cells.

Natural products have been great sources for drug discovery. However, the structures of natural products are diverse and difficult to elucidate. Cordyceps militaris is a parasitic fungus which usually grows on host insects. The metabolites of C.militaris have been reported to act as chemotherapeutic agents. In this study, we aimed for the structural elucidation of specialized metabolites derived from C.militaris, and the metabolic impact in leukemia cells. We describe a liquid chromatography data-dependent mass spectrometric platform combining tandem mass analysis and molecular networking. Leukemia cells treated with C.militaris extract and control groups were visualized in terms of their metabolic profiles using Global Natural Product Social (GNPS) molecular networking. By this method, we were able to elucidate the structures of metabolites from medicinal fungus extracts and cancer cells and then to recognize their changes in a semi-quantitative manner. Using C.militaris and leukemia cells as examples, we found that approximately 100 new ion species were present in the treated leukemia cells, suggesting a highly altered metabolic profile. Specifically, based on the tandem mass spectral similarity, we proposed that cordycepin, a key fungus-derived therapeutic agent known for its antitumor activity, was transformed into its methylthio form in leukemia cells. The platform described provides an ability to investigate complex molecular interactions of natural products in mammalian cells. By incorporating tandem mass spectrometry and molecular networking, we were able to reveal the chemical modification of crude bioactive compounds, for example potential bioactive compounds which might be modified from cordycepin. We envision that such a mass spectrometry (MS)-based workflow, combined with other metabolomics platforms, would enable much wider applicability to cell biology and be of great potential to pharmacological study as well as drug discovery.

Comparative study on metabolic profiling and excretion in rat bile between combination of notoginseng total saponins and safflower total flavonoids and its individual extracts by LC–MS/MS

The combination of notoginseng total saponins (NS) and safflower total flavonoids (SF), namely CNS, presents a synergistic protection effect on the myocardial ischemia rats. The aim of this study was to find the clues for their synergistic actions by comparing the biliary metabolism and excretion profiles after oral administration of CNS and its individual extracts. An ultra-performance liquid chromatography coupled with hybrid triple quadrupole-linear ion trap mass spectrometer (UPLC-QTRAP-MS/MS) platform was used to identify and quantify the CNS-derived components in bile. The neutral losses, precursor ions, and predictive multiple reaction monitoring (pMRM) scans were firstly used to detect the CNS-derived ingredients in vivo. A total of 43 components, including 38 flavonoids and 5 ginsenosides were tentatively identified according to the previously established chemical and metabolic profiles of NS and SF. Afterwards, the primary circulating and biological components, hydroxysafflor yellow A (HSYA), ginsenosides Rg1 (GRg1), Re (GRe), and Rd (GRd) were chosen to compare the bile excretion between CNS and its individual extract groups, by using a validated LC-MRM-MS/MS method. The approach was proved to be well satisfied the related requirements from the guidelines of FDA (specificity, calibration curve, sensitivity, precision, accuracy, matrix effect, recovery, and stability). Comparing with the SF and NS groups, the combination group did not affect the metabolic pathways of the CNS-related components, however, it decreased the cumulative excretion ratios of HSYA, GRg1, GRe, and GRd. In conclusion, the compatibility of SF and NS could reduce the bile excretion of the CNS-derived compounds, which may be one of the reasons for the enhancement of anti-myocardial ischemia after combination.

Evaluation of AGP Fucosylation as a Marker for Hepatocellular Carcinoma of Three Different Etiologies

A mass spectrometric analysis platform has been developed to determine whether glycosylation patterns of alpha-1 acid glycoprotein (AGP) could be used as a marker for early detection of hepatocellular carcinoma (HCC) in different etiologies, i.e. non-alcoholic steatohepatitis (NASH), alcoholic liver disease (ALC), and hepatitis C virus (HCV). MALDI-MS profiling of N-glycans of AGP purified from 20 μL of patient serum in HCC (n = 72) and liver cirrhosis (n = 58) showed that a unique trifucosylated tetra-antennary glycan (m/z 3490.76) was predominantly identified in HCCs but was absent in healthy subjects and the majority of cirrhosis patients. Receiver operation characteristic (ROC) curve analysis showed that the trifucosylated N-glycan of AGP (triFc_AGP) could differentiate HCC from cirrhosis with an area under the curve (AUC) of 0.707, 0.726 and 0.751 for NASH, ALC and HCV, respectively. When combining triFc_AGP with INR and AFP, the panel had the greatest benefit in detection of NASH-related HCCs, with a significantly improved AUC of 0.882 for all NASH HCCs and 0.818 for early NASH HCCs compared to AFP alone (0.761 and 0.641, respectively). Moreover, triFc_AGP could serve as a potential marker for monitoring AFP-negative HCC patients.

Multifaceted Mass Spectrometric Investigation of Neuropeptide Changes in Atlantic Blue Crab, Callinectes sapidus, in Response to Low pH Stress.

The decrease of pH level in the water affects animals living in aquatic habitat, such as crustaceans. The molecular mechanisms enabling these animals to survive this environmental stress remain unknown. To understand the modulatory function of neuropeptides in crustaceans when encountering drops in pH level, we developed and implemented a multifaceted mass spectrometric platform to investigate the global neuropeptide changes in response to water acidification in the Atlantic blue crab, Callinectes sapidus. Neural tissues were collected at different incubation periods to monitor dynamic changes of neuropeptides under different stress conditions occurring in the animal. Neuropeptide families were found to exhibit distinct expression patterns in different tissues and even each isoform had its specific response to the stress. Circulating fluid in the crabs (hemolymph) was also analyzed after 2-h exposure to acidification, and together with results from tissue analysis, enabled the discovery of neuropeptides participating in the stress accommodation process as putative hormones. Two novel peptide sequences were detected in the hemolymph that appeared to be involved in the stress-related regulation in the crabs.

An In-Depth View of the Porcine Trabecular Meshwork Proteome.

The house swine (Sus scrofa domestica Linnaeus 1758) is an important model organism regarding the study of neurodegenerative diseases, especially ocular neuropathies such as glaucoma. This is due to the high comparability of the porcine and human eye regarding anatomy and molecular features. In the pathogenesis of glaucoma, the trabecular meshwork (TM) forms a key ocular component in terms of intraocular pressure (IOP) elevation. Thereby, functional TM abnormalities are correlated with distinct proteomic alterations. However, a detailed analysis of the TM proteome has not been realized so far. Since the porcine eye has high potential as a model system to study ocular diseases such as glaucoma, the present study focuses on the in-depth analysis of the porcine TM proteome. By use of a bottom-up (BU) mass spectrometric (MS) platform utilizing electrospray ionization liquid chromatography tandem MS (LC-ESI-MS/MS) considering database-dependent and peptide de novo sequencing, more than 3000 TM proteins were documented with high confidence (FDR < 1%). A distinct number of proteins with neuronal association were revealed. To the best to our knowledge, many of these protein species have not been reported for TM tissue before such as reelin, centlein and high abundant neuroblast differentiation-associated protein AHNAK (AHNAK). Thereby, AHNAK might play a superordinate role in the TM regarding proposed tissue involvement in barrier function. Also, a high number of secretory proteins could be identified. The generated TM proteomic landscape underlines a multifunctional character of the TM beyond representing a simple drainage system. Finally, the protein catalogue of the porcine TM provides an in-depth view of the TM molecular landscape and will serve as an important reference map in terms of glaucoma research utilizing porcine animal models, porcine TM tissues and/or cultured TM cells.

Rational selection of reverse phase columns for high throughput LC-MS lipidomics.

Natural lipidomes are characterized by extremely high complexity and dynamic range of lipid concentrations. Furthermore, high diversity of lipid physicochemical properties requires high resolving powers for both chromatographic and mass spectrometric analytical platforms. Reverse-phase chromatography coupled with data-dependent MS/MS acquisition is one of the most popular techniques in untargeted lipidomics. Optimal method should provide good chromatographic separation and resolution, reproducibility, selectivity and sensitivity. Here, we developed and set-up a RPLC-MS/MS workflow capable of resolving complex mixtures of lipids in 32 min of analysis. Human blood plasma was chosen as a representative complex natural lipidome with large variance of lipid classes, species and lipid concentrations. Lipids were separated by RPLC on five different reverse phase columns with different types of stationary phase particles, size and chemistry. High mass accuracy MS analysis and data-dependent MS/MS analysis were performed using a Q Exactive™ HF Hybrid Quadrupole-Orbitrap™ Mass Spectrometer to identify individual lipid molecular species. This workflow was applied to evaluate the separation capability of each column and to identify the lipidomics profile in highly complex biological samples. As a result, we report more than 600 lipid species covering 18 lipid classes in human blood plasma and provide suggestions to the selection of the appropriate reverse phase column for the analysis of specific lipidomes.

A mass spectrometric platform for the quantitation of sulfur mustard-induced nucleic acid adducts as mechanistically relevant biomarkers of exposure.

Despite its worldwide ban, the warfare agent sulfur mustard (SM) still represents a realistic threat, due to potential release in terroristic attacks and asymmetric conflicts. Therefore, the rigorous and quantitative detection of SM exposure is crucial for diagnosis, health risk assessment, and surveillance of international law. Alkylation adducts of nucleic acids can serve as valuable toxicologically relevant 'biomarkers of SM exposure'. Here, we developed a robust and versatile bioanalytical platform based on isotope dilution UPLC-MS/MS to quantify major SM-induced DNA and RNA adducts, as well as adducts induced by the monofunctional mustard 2-chloroethylethylsulfide. We synthesized 15N/13C-labeled standards, which allowed absolute quantitation with full chemical specificity and subfemtomole sensitivities. DNA and RNA mono-alkylation adducts and crosslinks were carefully analyzed in a dose- and time-dependent manner in various matrices, including human cancer and primary cells, derived of the main SM-target tissues. Nucleic acid adducts were detected up to 6days post-exposure, indicating long persistence, which highlights their toxicological relevance and proves their suitability as forensic and medical biomarkers. Finally, we investigated ex vivo-treated rat skin biopsies and human blood samples, which set the basis for the implementation into the method portfolio of Organization for the Prohibition of Chemical Weapons-designated laboratories to analyze authentic samples from SM-exposed victims.

Faster raster matrix-assisted laser desorption/ionization mass spectrometry imaging of lipids at high lateral resolution

The clinical use of mass spectrometry imaging (MSI) is rapidly growing, and applications are expanding. Crucially, the analysis of clinical cohorts requires a combination of higher analytical throughput and higher lateral resolution. Here, we demonstrate the benefits of an improved design of a prototype MALDI source (referred as “uMALDI”) mounted on a SYNAPT HDMS G2-Si mass spectrometer – widely used by the MSI community. The uMALDI source allows for imaging of lipids on histologically well documented rat brain sections at a lateral resolution of 15 μm without oversampling. We also investigate the fast rastering capabilities of the platform enabled by a new web-based MS control program (i.e. “WREnS” Waters Research Enabled Software). The combination of the uMALDI and WREnS allows high spatial resolution images at acquisition rates up to 20 pixels per second. Additionally, we demonstrate the capability of this platform to characterize the lipid distribution of osteoarthritic (OA) cartilage at the cellular level, which highlights potential benefit for broader application in clinical context. Finally, we prove that ion mobility separation of isobaric lipid species is maintained and images can be acquired at a rate of 10 scans per seconds. This renders a unique ion mobility mass spectrometric imaging platform with high acquisition rates and high spatial resolution.

Point-of-care identification of organophosphates in gastric juice by ambient mass spectrometry in emergency settings

BackgroundFor emergency management, it is important to promptly identify the organophosphate ingested by self-poisoning patients since different organophosphates cause intoxication through different mechanisms and require different therapeutic strategies. This study aimed at the development of a point-of-care ambient mass spectrometric approach for rapid identification of organophosphate(s) in gastric juice for emergency management. MethodsSix organophosphate insecticides that are commonly ingested by self-poisoning patients in Taiwan were examined. The sample solutions were prepared and diluted with human gastric juice. A direct metallic probe was dipped and removed immediately from the sample solution. The probe was then inserted into the thermal desorption-electrospray ionization/mass spectrometry (TD-ESI/MS) to detect the analyte on the probe. ResultsSince no pretreatment of the specimen was required, the sampling processes followed by thermal desorption-electrospray ionization and mass spectrometric analysis of the organophosphate in the gastric juice were completed within 30 s. The detection limit of the organophosphates is at the 10–100 parts per billion level. Good linearity was observed between the corresponding changes in mass spectrometric signal intensities and the changes of organophosphate concentrations within the range of 5–1000 parts per billion. The high efficiency of this ambient mass spectrometric platform was further confirmed when a real sample of the drained gastric lavage fluid of a patient who suffered from ingestion of chlorpyrifos was collected in the emergency room and tested with this cutting-edge technique. ConclusionsThe results suggested that TD-ESI/MS is promising in promptly providing toxicological information to assist succeeding medical management in an emergency room.

Optimized GC-MS metabolomics for the analysis of kidney tissue metabolites.

Metabolomics is a promising approach for discovery of relevant biomarkers in cells, tissues, organs, and biofluids for disease identification and prediction. The field has mostly relied on blood-based biofluids (serum, plasma, urine) as non-invasive sources of samples as surrogates of tissue or organ-specific conditions. However, the tissue specificity of metabolites pose challenges in translating blood metabolic profiles to organ-specific pathophysiological changes, and require further downstream analysis of the metabolites. As part of this project, we aim to develop and optimize an efficient extraction protocol for the analysis of kidney tissue metabolites representative of key primate metabolic pathways. Kidney cortex and medulla tissues of a baboon were homogenized and extracted using eight different extraction protocols including methanol/water, dichloromethane/methanol, pure methanol, pure water, water/methanol/chloroform, methanol/chloroform, methanol/acetonitrile/water, and acetonitrile/isopropanol/water. The extracts were analyzed by a two-dimensional gas chromatography time-of-flight mass-spectrometer (2D GC-ToF-MS) platform after methoximation and silylation. Our analysis quantified 110 shared metabolites in kidney cortex and medulla tissues from hundreds of metabolites found among the eight different solvent extractions spanning low to high polarities. The results revealed that medulla is metabolically richer compared to thecortex. Dichloromethane and methanol mixture (3:1) yielded highestnumber of metabolites across both the tissue types. Depending on the metabolites of interest, tissue type, and the biological question, different solvents can be used to extract specific groups of metabolites. This investigation provides insights into selection of extraction solvents for detection of classes of metabolites in renal cortex and medulla, which is fundamentally important for identification of prognostic and diagnostic metabolic kidney biomarkers for future therapeutic applications.

Micelles Protect Intact Metallo-supramolecular Block Copolymer Complexes from Solution to Gas Phase during Electrospray Ionization

Supramolecular diblock copolymers using metal-ligand coordination can be synthesized under ambient conditions by delicate design of the end groups of the homopolymer chains. However, mass spectrometric analysis of such metallo-supramolecular copolymers is challenging. One of the reasons is the nonpolarity of the polymer chains, making it hard to disperse the complexes in electrospray ionization (ESI)-friendly environments. The other difficulty is the noncovalent nature of such copolymers, which is easily disrupted during the ionization. Here, we demonstrate that the intact metallo-supramolecular diblock copolymers can be maintained sufficiently during the ESI process in aqueous solution within micelles. The high-resolution mass spectrometric evidence revealed that the surfactant molecules effectively protect the noncovalent binding of the complexes into gaseous ions. Intriguingly, surfactant molecules were sufficiently detached away from the copolymer complexes, giving unambiguous mass spectra that were predominated by intact diblock copolymers. This ESI-based approach allowed us to investigate the relative bond strengths of metal-to-ligand complexation using collision-induced dissociation (CID) in the ion trap mass spectrometry. Conformational features and collision cross sections of the copolymers were thus obtained using subsequent ion mobility spectrometry mass spectrometry (IMS-MS). Remarkable environment-dependent conformations of the denoted diblock copolymers were found using this mass spectrometric platform.

Synthesis, analytical characterization, and monoamine transporter activity of the new psychoactive substance 4-methylphenmetrazine (4-MPM), with differentiation from its ortho- and meta- positional isomers.

The availability of new psychoactive substances (NPS) on the recreational drug market continues to create challenges for scientists in the forensic, clinical and toxicology fields. Phenmetrazine (3-methyl-2-phenylmorpholine) and an array of its analogs form a class of psychostimulants that are well documented in the patent and scientific literature. The present study reports on two phenmetrazine analogs that have been encountered on the NPS market following the introduction of 3-fluorophenmetrazine (3-FPM), namely 4-methylphenmetrazine (4-MPM), and 3-methylphenmetrazine (3-MPM). This study describes the syntheses, analytical characterization, and pharmacological evaluation of the positional isomers of MPM. Analytical characterizations employed various chromatographic, spectroscopic, and mass spectrometric platforms. Pharmacological studies were conducted to assess whether MPM isomers might display stimulant-like effects similar to the parent compound phenmetrazine. The isomers were tested for their ability to inhibit uptake or stimulate release of tritiated substrates at dopamine, norepinephrine and serotonin transporters using in vitro transporter assays in rat brain synaptosomes. The analytical characterization of three vendor samples revealed the presence of 4-MPM in two of the samples and 3-MPM in the third sample, which agreed with the product label. The pharmacological findings suggest that 2-MPM and 3-MPM will exhibit stimulant properties similar to the parent compound phenmetrazine, whereas 4-MPM may display entactogen properties more similar to 3,4-methylenedioxymethamphetamine (MDMA). The combination of test purchases, analytical characterization, targeted organic synthesis, and pharmacological evaluation of NPS and their isomers is an effective approach for the provision of data on these substances as they emerge in the marketplace.

Metabolomic profiles in breast cancer:a pilot case-control study in the breast cancer family registry

BackgroundMetabolomics is emerging as an important tool for detecting differences between diseased and non-diseased individuals. However, prospective studies are limited.MethodsWe examined the detectability, reliability, and distribution of metabolites measured in pre-diagnostic plasma samples in a pilot study of women enrolled in the Northern California site of the Breast Cancer Family Registry. The study included 45 cases diagnosed with breast cancer at least one year after the blood draw, and 45 controls. Controls were matched on age (within 5 years), family status, BRCA status, and menopausal status. Duplicate samples were included for reliability assessment. We used a liquid chromatography/gas chromatography mass spectrometer platform to measure metabolites. We calculated intraclass correlations (ICCs) among duplicate samples, and coefficients of variation (CVs) across metabolites.ResultsOf the 661 named metabolites detected, 338 (51%) were found in all samples, and 490 (74%) in more than 80% of samples. The median ICC between duplicates was 0.96 (25th – 75th percentile: 0.82–0.99). We observed a greater than 20% case-control difference in 24 metabolites (p < 0.05), although these associations were not significant after adjusting for multiple comparisons.ConclusionsThese data show that assays are reproducible for many metabolites, there is a minimal laboratory variation for the same sample, and a large between-person variation. Despite small sample size, differences between cases and controls in some metabolites suggest that a well-powered large-scale study is likely to detect biological meaningful differences to provide a better understanding of breast cancer etiology.

Mass Spectrometry-Based Screening Platform Reveals Orco Interactome in Drosophila melanogaster.

Animals use their odorant receptors to receive chemical information from the environment. Insect odorant receptors differ from the G protein-coupled odorant receptors in vertebrates and nematodes, and very little is known about their protein–protein interactions. Here, we introduce a mass spectrometric platform designed for the large-scale analysis of insect odorant receptor protein–protein interactions. Using this platform, we obtained the first Orco interactome from Drosophila melanogaster. From a total of 1,186 identified proteins, we narrowed the interaction candidates to 226, of which only two-thirds have been named. These candidates include the known olfactory proteins Or92a and Obp51a. Around 90% of the proteins having published names likely function inside the cell, and nearly half of these intracellular proteins are associated with the endomembrane system. In a basic loss-of-function electrophysiological screen, we found that the disruption of eight (i.e., Rab5, CG32795, Mpcp, Tom70, Vir-1, CG30427, Eaat1, and CG2781) of 28 randomly selected candidates affects olfactory responses in vivo. Thus, because this Orco interactome includes physiologically meaningful candidates, we anticipate that our platform will help guide further research on the molecular mechanisms of the insect odorant receptor family.