High-throughput Liquid Chromatography-mass Spectrometry Research Articles

Metabolomic Profiles in Jamaican Children With and Without Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with a wide range of behavioral and cognitive impairments. While genetic and environmental factors are known to contribute to its etiology, metabolic perturbations associated with ASD, which can potentially connect genetic and environmental factors, remain poorly understood. Therefore, we conducted a metabolomic case-control study and performed a comprehensive analysis to identify significant alterations in metabolite profiles between children with ASD and typically developing (TD) controls in order to identify specific metabolites that may serve as biomarkers for the disorder. We conducted metabolomic profiling on plasma samples from participants in the second phase of Epidemiological Research on Autism in Jamaica, an age and sex-matched cohort of 200 children with ASD and 200 TD controls (2-8years old). Using high-throughput liquid chromatography-mass spectrometry techniques, we performed a targeted metabolite analysis, encompassing amino acids, lipids, carbohydrates, and other key metabolic compounds. After quality control and missing data imputation, we performed univariable and multivariable analysis using normalized metabolites while adjusting for covariates, age, sex, socioeconomic status, and child's parish of birth. Our findings revealed unique metabolic patterns in children with ASD for four metabolites compared to TD controls. Notably, three metabolites were fatty acids, including myristoleic acid, eicosatetraenoic acid, and octadecenoic acid. The amino acid sarcosine exhibited a significant association with ASD. These findings highlight the role of metabolites in the etiology of ASD and suggest opportunities for the development of targeted interventions.

Dynamic Interplay between Microbiota Shifts and Differential Metabolites during Dairy Processing and Storage.

Due to the intricate complexity of the original microbiota, residual heat-resistant enzymes, and chemical components, identifying the essential factors that affect dairy quality using traditional methods is challenging. In this study, raw milk, pasteurized milk, and ultra-heat-treated (UHT) milk samples were collectively analyzed using metagenomic next-generation sequencing (mNGS), high-throughput liquid chromatography-mass spectrometry (LC-MS), and gas chromatography-mass spectrometry (GC-MS). The results revealed that raw milk and its corresponding heated dairy products exhibited different trends in terms of microbiota shifts and metabolite changes during storage. Via the analysis of differences in microbiota and correlation analysis of the microorganisms present in differential metabolites in refrigerated pasteurized milk, the top three differential microorganisms with increased abundance, Microbacterium (p < 0.01), unclassified Actinomycetia class (p < 0.05), and Micrococcus (p < 0.01), were detected; these were highly correlated with certain metabolites in pasteurized milk (r > 0.8). This indicated that these genera were the main proliferating microorganisms and were the primary genera involved in the metabolism of pasteurized milk during refrigeration-based storage. Microorganisms with decreased abundance were classified into two categories based on correlation analysis with certain metabolites. It was speculated that the heat-resistant enzyme system of a group of microorganisms with high correlation (r > 0.8), such as Pseudomonas and Acinetobacter, was the main factor causing milk spoilage and that the group with lower correlation (r < 0.3) had a lower impact on the storage process of pasteurized dairy products. By comparing the metabolic pathway results based on metagenomic and metabolite annotation, it was proposed that protein degradation may be associated with microbial growth, whereas lipid degradation may be linked to raw milk's initial heat-resistant enzymes. By leveraging the synergy of metagenomics and metabolomics, the interacting factors determining the quality evolution of dairy products were systematically investigated, providing a novel perspective for controlling dairy processing and storage effectively.

Comparative gut proteomics study revealing adaptive physiology of Eurasian spruce bark beetle, Ips typographus (Coleoptera: Scolytinae)

The bark beetle, Ips typographus (L.), is a major pest of Norway spruce, Picea abies (L.), causing enormous economic losses globally. The adult stage of the I. typographus has a complex life cycle (callow and sclerotized); the callow beetles feed ferociously, whereas sclerotized male beetles are more aggressive and pioneers in establishing new colonies. We conducted a comparative proteomics study to understand male and female digestion and detoxification processes in callow and sclerotized beetles. Proteome profiling was performed using high-throughput liquid chromatography-mass spectrometry. A total of &amp;gt;3000 proteins were identified from the bark beetle gut, and among them, 539 were differentially abundant (fold change ±2, FDR &amp;lt;0.05) between callow and sclerotized beetles. The differentially abundant proteins (DAPs) mainly engage with binding, catalytic activity, anatomical activity, hydrolase activity, metabolic process, and carbohydrate metabolism, and hence may be crucial for growth, digestion, detoxification, and signalling. We validated selected DAPs with RT-qPCR. Gut enzymes such as NADPH-cytochrome P450 reductase (CYC), glutathione S-transferase (GST), and esterase (EST) play a crucial role in the I. typographus for detoxification and digesting of host allelochemicals. We conducted enzyme activity assays with them and observed a positive correlation of CYC and GST activities with the proteomic results, whereas EST activity was not fully correlated. Furthermore, our investigation revealed that callow beetles had an upregulation of proteins associated with juvenile hormone (JH) biosynthesis and chitin metabolism, whereas sclerotized beetles exhibited an upregulation of proteins linked to fatty acid metabolism and the TCA cycle. These distinctive patterns of protein regulation in metabolic and functional processes are specific to each developmental stage, underscoring the adaptive responses of I. typographicus in overcoming conifer defences and facilitating their survival. Taken together, it is the first gut proteomic study comparing males and females of callow and sclerotized I. typographus, shedding light on the adaptive ecology at the molecular level. Furthermore, the information about bark beetle handling of nutritionally limiting and defence-rich spruce phloem diet can be utilized to formulate RNAi-mediated beetle management.

Multi-Attribute Monitoring Method for Process Development of Engineered Antibody for Site-Specific Conjugation.

Antibody drug conjugates, a class of biotherapeutic proteins, have been extensively developed in recent years, resulting in new approvals and improved standard of care for cancer patients. Among the numerous strategies of conjugating cytotoxic payloads to monoclonal antibodies, insertion of a cysteine residue achieves a tightly controlled, site-specific drug to antibody ratio. Tailored analytical tools are required to direct the development of processes capable of manufacturing novel antibody scaffolds with the desired product quality. Here, we describe the development of a 12 min, mass-spectrometry-based method capable of monitoring four distinct quality attributes simultaneously: variations in the thiol state of the inserted cysteines, N-linked glycosylation, reduction of interchain disulfide bonds, and polypeptide fragmentation. This method provides new insight into the properties of the antibody intermediate and associated manufacturing processes. Oxidized thiol states are formed within the bioreactor, of which a variant containing an additional disulfide bond was produced and remained relatively constant throughout the fed-batch process; reduced thiol variants were introduced upon harvest. Nearly 20 percent of N-linked glycans contained sialic acid, substantially higher than anticipated for wildtype IgG1. Lastly, previously unreported polypeptide fragmentation sites were identified in the C239i constant domain, and the relationship between fragmentation and glycoform were explored. This work illustrates the utility of applying a high-throughput liquid chromatography-mass spectrometry multi-attribute monitoring method to support the development of engineered antibody scaffolds.

Abstract P203: Healthy Lifestyle Plasma Metabolite Profile and Risk of Mortality in US Prospective Cohort Studies

Background: A healthy lifestyle is associated with a lower risk of premature death. Metabolic pathways of a healthy lifestyle and their association with mortality remain to be understood. This study aimed to identify the metabolomic profile of a healthy lifestyle score and examine its prospective association with all-cause and cause-specific mortality, including death from cardiovascular disease (CVD) and cancer. Methods: The population included 12,146 participants from the Nurses’ Health Study (NHS), NHS II and Health Professionals Follow-Up Study (HPFS)(83% women, 97% white, aged 55±9y). Plasma metabolites were profiled using high-throughput liquid chromatography mass-spectrometry at baseline (NHS:1989-1990; NHSII:1996-1999; HPFS:1993-1995). The healthy lifestyle score was computed by summing the total number of healthy lifestyle factors participants adhered to from validated questionnaires at baseline: healthy diet (Alternative Healthy Eating Index, upper 40%), moderate alcohol intake (women: 5-15 g/d; men: 5-30 g/d), moderate-to-vigorous physical activity (≥30min/d), never smoking and normal BMI (18.5-24.9kg/m 2 ). Deaths were ascertained with death certificates and medical records. The metabolite profile was identified using elastic net regressions with train test validation split (70-30%). Metabolic pathways were determined using Metabolite Set Enrichment Analysis (MSEA). Multivariable-adjusted Cox proportional hazards regressions were used to estimate hazard ratios and 95% confidence intervals (HR[CI]) per unit of score of the healthy lifestyle metabolite profile with mortality risk. Results: The identified profile included 88 metabolites and correlated with the healthy lifestyle score (Pearson r=0.43-0.44; p&lt;0.001). Triglyceride and diglyceride metabolite sets were inversely associated with the healthy lifestyle score, whereas cholesteryl ester and phosphatidylcholine plasmalogen sets were directly associated (p&lt;0.001). Among individual lifestyle factors, the profile was most strongly correlated with normal BMI (r pb =0.43; p&lt;0.001). Over 32y of follow-up, there were 3,851 deaths, including 749 deaths from CVD and 994 from cancer. Participants with a higher healthy lifestyle metabolite profile score had lower risk of all-cause (HR=0.79[0.73, 0.85]) and CVD mortality (HR=0.77[0.58, 0.95]), but not cancer (HR=0.91[0.77, 1.05]). Significant associations persisted after further adjustment for the healthy lifestyle score. Conclusions: In US adults, we identified a metabolite profile related to a healthy lifestyle largely reflecting lipid metabolism pathways. A higher metabolite score was associated with lower subsequent all-cause mortality risk, specifically from CVD. Findings provide novel insights into potential metabolic pathways underlying the association between a healthy lifestyle and lower premature mortality.

Abstract MP22: Plasma Metabolomic Profiles Associated With Mortality and Longevity in a Prospective Study of 13,401 Individuals

Background: Recent advances in metabolomic studies have shown promise in elucidating the biological pathways underpinning aging processes and mortality in animal models, but data in humans are lacking. We aimed to evaluate the associations between metabolite profiles, all-cause and cause-specific mortality, and longevity. Methods: Within three prospective cohorts (Nurses’ Health Study [NHS], NHSII, and Health Professional’s Follow-up Study), we measured plasma metabolites from 11,523 participants (mean age 54 years, 86% female) using high-throughput liquid chromatography-mass spectrometry. Participants were free of cardiovascular disease and cancer at blood collection. Metabolome-wide association analyses were conducted for all-cause, cardiovascular, and cancer mortality using Cox proportional hazards regression and longevity (attaining 85 years of age) using logistic regression. Both pre-defined and data-driven metabolite groups were also evaluated. We further developed a multi-metabolite profile score for all-cause mortality using an elastic-net regularized Cox model and assessed its associations with mortality and longevity. Results for all-cause mortality were replicated among 1878 participants (mean age 67 years, 58% female) from the PREDIMED trial. Results: We documented 4252 deaths (including 864 cardiovascular deaths and 1070 cancer deaths) and 3048 achieving longevity over a median follow-up of 22.6 years in the NHS/NHSII/HPFS, and 126 deaths during a follow-up of 4.7 years in the PREDIMED. Higher levels of three nucleosides (N2,N2-dimethylguanosine, pseudouridine, and N4-acetylcytidine), 4-acetamidobutanoic acid, triacylglycerols with ≤56 carbons and ≤3 double bonds, and several other lipids were associated with increased risk of all-cause mortality and corresponding decreased likelihood of longevity; whereas L-serine, L-glutamine, and TAGs with &gt;56 carbons or &gt;3 double bonds were associated with lower mortality risk and higher odds of achieving longevity. A multi-metabolite profile score comprising 73 metabolites was positively associated with all-cause (HR per 1-SD increment=1.25 [95% CI: 1.21, 1.30] in NHS/NHSII/HPFS and 1.47 [95% CI: 1.22, 1.78] in PREDIMED), cardiovascular (HR=1.34 [95% CI:1.24, 1.45]), and cancer mortality (HR=1.15 [95% CI:1.08, 1.24]) and inversely associated with longevity (OR=0.79 [95% CI: 0.74, 0.86]). Conclusions: We identified multiple metabolites associated with mortality and longevity. Our findings provide insights into the biological pathways that lead to death and open up new avenues to incorporate these metabolomic markers in clinical and research settings.

Effect of Epichloë gansuensis Endophyte on Seed-Borne Microbes and Seed Metabolites in Achnatherum inebrians.

The seed-borne microbiota and seed metabolites of the grass Achnatherum inebrians, either host to Epichloë gansuensis (endophyte infected [EI]) or endophyte free (EF), were investigated. This study determined the microbial communities both within the seed (endophytic) and on the seed surface (epiphytic) and of the protective glumes by using Illumina sequencing technology. Epichloë gansuensis decreased the richness of the seed-borne microbiota except for the epiphytic fungi of glumes and also decreased the diversity of seed-borne microbiota. In addition, metabolites of seeds and glumes were detected using liquid chromatography-mass spectrometry (LC-MS). Unlike with the seeds of EF plants, the presence of E. gansuensis resulted in significant changes in the content of 108 seed and 31 glume metabolites. A total of 319 significant correlations occurred between seed-borne microbiota and seed metabolites; these correlations comprised 163 (147 bacterial and 16 fungal) positive correlations and 156 (136 bacterial and 20 fungal) negative correlations. Meanwhile, there were 42 significant correlations between glume microbiota and metabolites; these correlations comprised 28 positive (10 bacterial and 18 fungal) and 14 negative (9 bacterial and 5 fungal) correlations. The presence of E. gansuensis endophyte altered the communities and diversities of seed-borne microbes and altered the composition and content of seed metabolites, and there were many close and complex relationships between microbes and metabolites. IMPORTANCE The present study was to investigate seed-borne microbiota and seed metabolites in Achnatherum inebrians using high-throughput sequencing and LC-MS technology. Epichloë gansuensis decreased the richness of the seed-borne microbiota except for the epiphytic fungi of glumes and also decreased the diversity of seed-borne microbiota. Compared with endophyte-free plants, the content of 108 seed and 31 glume metabolites of endophyte-infected plants was significantly changed. There were 319 significant correlations between seed-borne microbiota and seed metabolites and 42 significant correlations between glume microbiota and metabolites.

Rapid, sensitive, and high-throughput quantification of broad serological ceramides by using isotope dilution liquid chromatography-negative ion electrospray tandem mass spectrometry.

Ceramides are important intermediates in the metabolism of sphingolipids. High-throughput liquid chromatography-mass spectrometry has been used extensively for monitoring the levels of serological ceramides, but is still limited by inadequate coverage or lack of sensitivity. Herein, a rapid, sensitive, and high-throughput isotope dilution liquid chromatography-negative ion electrospray tandem mass spectrometry (IDLC-nESI-MS/MS) method was developed and verified for accurate quantification of 41 ceramides, involving ceramides with C16-20 sphingosine, dihydro-ceramide, and dehydro-ceramide. This method was validated with excellent linearity (R2 > 0.99) and good recovery in the range of 90-110%. Intra- and inter-day imprecision were below 5.57% and 7.83% respectively. The improved high-throughput quantitative method developed in this study may aid in the accurate characterization of ceramides for understanding ceramide biology and application in disease diagnosis.

Comparative high-throughput analysis of sperm membrane proteins from crossbred bulls with contrasting fertility.

The aim of the present study was to identify fertility associated sperm membrane proteins in crossbred bulls. Sperm membrane proteins from high- and low-fertile Holstein Friesian crossbred bulls (n=3 each) were subjected to high-throughput liquid chromatography-mass spectrometry (LC-MS/MS) for comparative proteomic analysis. Proteomic profiling identified a total of 456 proteins in crossbred bull spermatozoa; it was found that 108 proteins were up regulated while 26 proteins were down regulated (>1.5-folds) in spermatozoa from low- compared to high-fertile bulls. Gene ontology classification revealed that upregulated proteins in low-fertile bulls were involved in biological process such as oxidation-reduction process (p=3.14E-06), fusion of sperm to egg plasma membrane (p=7.51E-04), sperm motility (p=0.03), and capacitation (p=0.09), while down regulated proteins were associated with transport (p=6.94E-04), superoxide metabolic process (p=0.02), and tricarboxylic acid cycle (p=0.04). KEGG pathway analysis revealed that oxidative phosphorylation and tricarboxylic acid cycle pathways are the most significantly affected pathway in low-fertile bulls. It was concluded that expression of proteins associated with oxidative phosphorylation and tricarboxylic acid cycle pathways were altered in low-fertile crossbred bulls, and expression levels of SPATA19, ELSPBP1, ACRBP, CLU, SUCLA2, and SPATC1 could aid in assessing potential fertility of crossbred bulls.

High-throughput LC-MS method for the rapid characterisation and comparative analysis of multiple ingredients of four hawthorn leaf extracts.

The comprehensive component characterisation of Chinese herbal medicine is the premise of effectively driving the discovery of pharmacodynamic substances or new drugs in recent years. To use the high-throughput liquid chromatography-mass spectrometry (LC-MS) approach to systematically characterise phytochemical compounds from four hawthorn leaf extracts, along with evaluating their classification. In the present study, the compounds from 50% ethanol extract, macro porous resin extract, ethyl acetate extract and standard decoction of hawthorn leaves were completely analysed by ultrahigh-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS). Eight-nine compounds were putatively identified by comparison with secondary MS data and available references. Of these compounds identified, 56 compounds were found for the first time in hawthorn leaves, which was somewhat inconsistent with the findings of other studies. It could be inferred that falconoid, organic acids and nitrogenous compounds were the most abundant in 50% ethanol extract and standard decoction extract, which were considered as better choices for extracting hawthorn leaves. This work developed a simple, accurate and rapid method for the compound identification of hawthorn leaves, which laid the basis for further discovering pharmacodynamic material basis or new drugs from hawthorn leaves.

Lipid profiling in malignant mesothelioma reveals promising signatures for diagnosis and prognosis: A plasma-based LC-MS lipidomics study

Background and aimMalignant mesothelioma (MM), being a rare and aggressive carcinoma, can barely be cured. Incidence of this cancer will keep climbing up in the next few decades since its major carcinogen, asbestos, is still in use in many countries. Unfortunately, prognosis of MM is unsatisfactory principally due to poor early diagnosis as a result of its long latency period and ambiguous symptoms. Lipids are known to contribute to cellular structure, signaling, and energy storage, and are widely reported to be related with tumorigenesis. Therefore, we aim to discover novel lipid biomarkers by plasma-based lipidomics that may improve MM diagnosis. MethodsPlasma samples from 25 MM patients and 32 healthy controls (HCs) were collected and analysed using a high-throughput liquid chromatography-mass spectrometry (LC-MS). Univariate and multivariate analyses were subsequently performed to visualize the separation trend between two groups and to screen for differential feature ions. Ions were annotated using LipidSearch 4.2 and their enriched pathways were detected on LIPEA. Receiver operating characteristic (ROC) curves were used for analysing each annotated lipid’s diagnostic value. Survival analyses were performed to investigate each lipid’s prognostic value. ResultsIn supervised partial least squares discriminant analysis (PLS-DA), clear separation between MM and HC groups was observed. A total of 34 differential lipids were annotated, among which 5 upregulated and 29 downregulated. Levels of plasma triacylglycerols (TGs) were higher in smoking versus non-smoking patients, and lower in female versus male patients. The top six lipids possessing highest diagnostic value included two phosphatidylethanolamines (PEs), two phosphatidylcholines (PCs) and two ceramides. Moreover, elevated circulating TG levels were associated with poorer survival, whereas increased monohexosylceramide (Hex1Cer) might be beneficial. ConclusionsOur study revealed differentially expressed lipid patterns in MM compared to HC. PC, PE, and ceramides showed outstanding diagnostic performance, while TG and Hex1Cer exhibited significant prognostic values. Nevertheless, more studies should verify these trends as well as further investigating on underlying mechanisms.

Effect of food processing (fish burger preparation and frying) on residual levels of enrofloxacin and ciprofloxacin

ABSTRACT The influence of fish burger preparation and frying on residual levels of enrofloxacin (ENR) and ciprofloxacin (CIP) was evaluated. For this purpose, a high-throughput liquid chromatography-mass spectrometry analytical method for the quantitation of ENR and CIP residues in tilapia products (fillet, raw fish burger and fried fish burger) was developed and validated based on European and Brazilian guidelines. Sample preparation was accomplished by extraction with acidified acetonitrile followed by clean-up with hexane. Chromatographic analysis was performed on a C18 column using isocratic elution with 0.1% formic acid and acetonitrile (85:15 v:v). The analytical method showed suitable performance to quantify the residual levels of ENR and CIP in the studied matrices. No reduction in the residual levels of ENR and CIP was observed during fish burger preparation and only a 10% reduction occurred as a consequence of frying, indicating that both compounds were stable to the preparation of the fish burger and to frying conditions.

Putting Proteomics Into Immunotherapy for Glioblastoma.

In glioblastoma, the most aggressive brain cancer, a complex microenvironment of heterogeneity and immunosuppression, are considerable hurdles to classify the subtypes and promote treatment progression. Treatments for glioblastoma are similar to standard therapies for many other cancers and do not effectively prolong the survival of patients, due to the unique location and heterogeneous characteristics of glioblastoma. Immunotherapy has shown a promising effect for many other tumors, but its application for glioma still has some challenges. The recent breakthrough of high-throughput liquid chromatography–mass spectrometry (LC-MS/MS) systems has allowed researchers to update their strategy for identifying and quantifying thousands of proteins in a much shorter time with lesser effort. The protein maps can contribute to generating a complete map of regulatory systems to elucidate tumor mechanisms. In particular, newly developed unicellular proteomics could be used to determine the microenvironment and heterogeneity. In addition, a large scale of differentiated proteins provides more ways to precisely classify tumor subtypes and construct a larger library for biomarkers and biotargets, especially for immunotherapy. A series of advanced proteomic studies have been devoted to the different aspects of immunotherapy for glioma, including monoclonal antibodies, oncolytic viruses, dendritic cell (DC) vaccines, and chimeric antigen receptor (CAR) T cells. Thus, the application of proteomics in immunotherapy may accelerate research on the treatment of glioblastoma. In this review, we evaluate the frontline applications of proteomics strategies for immunotherapy in glioblastoma research.

Proteomics and phosphoproteomics revealed molecular networks of stomatal immune responses.

Dynamic protein and phosphoprotein profiles uncovered the overall regulation of stomata movement against pathogen invasion and phosphorylation states of proteins involved in ABA, SA, calcium and ROS signaling, which may modulate the stomatal immune response. Stomatal openings represent a major route of pathogen entry into the plant, and plants have evolved mechanisms to regulate stomatal aperture as innate immune response against bacterial invasion. However, the mechanisms underlying stomatal immunity are not fully understood. Taking advantage of high-throughput liquid chromatography mass spectrometry (LC-MS), we performed label-free proteomic and phosphoproteomic analyses of enriched guard cells in response to a bacterial pathogen Pseudomonas syringae pv. tomato (Pst) DC3000. In total, 495 proteins and 1229 phosphoproteins were identified as differentially regulated. These proteins are involved in a variety of signaling pathways, including abscisic acid and salicylic acid hormone signaling, calcium and reactive oxygen species signaling. We also showed that dynamic changes of phosphoprotein WRKY transcription factors may play a crucial role in regulating stomata movement in plant immunity. The identified proteins/phosphoproteins and the pathways form interactive molecular networks to regulate stomatal immunity. This study has provided new insights into the multifaceted mechanisms of stomatal immunity. The differential proteins and phosphoproteins are potential targets for engineering or breeding of crops for enhanced pathogen defense.

High-Throughput Metabolomics for Identification of Metabolic Pathways and Deciphering the Effect Mechanism of Dioscin on Rectal Cancer From Cell Metabolic Profiles Coupled With Chemometrics Analysis.

High-throughput liquid chromatography–mass spectrometry (LC-MS)-based metabolomics can provide the holistic analysis of the low molecular weight endogenous metabolites in cells and reflect the changes of cellular regulation and metabolic pathways. Our study designed to reveal the potentially pharmacological effects of dioscin on SW480 rectal cancer cells using nontargeted metabolomics method to probe into small molecular metabolites and pathway changes. After the cell assay of proliferation, apoptosis, migration, and invasion, the dioscin-treated cell samples were prepared for nontargeted metabolomics analysis based on LC-MS tool to describe the metabolic profiles. Dioscin has prevented cell proliferation and accelerated cell apoptosis, and it also inhibited the SW480 rectal cancer cells’ migration and invasion. A total of 22 metabolites were selected as promising biomarkers of pharmacological reaction of dioscin to rectal cancer, and eight highly correlated pathways including D-glutamine and D-glutamate metabolism, pyruvate metabolism, arachidonic acid metabolism, phenylalanine metabolism, tryptophan metabolism, glycolysis or gluconeogenesis, citrate cycle (TCA cycle), and butanoate metabolism were identified. It showed that strategies based on cell metabolomics are helpful tools to discover the small molecular metabolites to elucidate the action mechanism of drug.

Metabolomic Applications in Radiation Biodosimetry.

Metabolomics, the collective assessment and quantification of small molecules in a given biofluid or tissue sample, has provided new ways in evaluating an individual's exposure level to ionizing radiation or other genotoxic stressors. Protocols that are routinely utilized for the preparation of samples from rodents to patients are presented here in order to be analyzed by high-throughput liquid chromatography-mass spectrometry techniques. These protocols are based on established methods in our laboratory that have been used extensively in radiation biodosimetry through metabolomics. These protocols are focused on general profiling of samples and therefore do not concentrate on extraction of specific classes on metabolites (e.g., eicosanoids).

Top-Down Characterization of Heavily Modified Histones Using 193 nm Ultraviolet Photodissociation Mass Spectrometry.

The characterization of protein post-translational modifications (PTMs) remains a significant challenge for traditional bottom-up proteomics methods owing to the lability of PTMs and the difficulty of mapping combinatorial patterns of PTMs based on analysis of small peptides. These shortcomings have accelerated interest in top-down MS/MS methods that focus on analysis of intact proteins. Simultaneous mapping of all PTMs requires extensive sequence coverage to confidently localize modifications. 193 nm ultraviolet photodissociation (UVPD) has been shown to generate unparalleled sequence coverage for intact proteins compared to traditional MS/MS methods. This study focuses on identification and localization of PTMs of histones by UVPD, higher-energy collisional dissociation (HCD), and the hybrid method electron-transfer/higher-energy collision dissociation (EThcD) via a high throughput liquid chromatography-mass spectrometry strategy. In total, over 500 proteoforms were characterized among these three activation methods with 46% of the identifications found in common by two or more activation methods. EThcD and UVPD afforded more extensive characterization of proteoforms than HCD with average gains in sequence coverage of 15% and C-scores that doubled on average.

Liquid chromatography mass spectrometry-based profiling of phosphatidylcholine and phosphatidylethanolamine in the plasma and liver of acetaminophen-induced liver injured mice

BackgroundAcetaminophen (APAP) overdose is one of the most common causes of acute liver failure in many countries. The aim of the study was to describe the profiling of phosphatidylcholine (PC) and phosphatidylethanolamine (PE) in the plasma and liver of Acetaminophen -induced liver injured mice.MethodsA time course study was carried out using C57BL/6 mice after intraperitoneal administration of 300 mg/kg Acetaminophen 1 h, 3 h, 6 h, 12 h and 24 h. A high-throughput liquid chromatography mass spectrometry (LC-MS) lipidomic method was utilized to detect phosphatidylcholine and phosphatidylethanolamine species in the plasma and liver. The expressions of phosphatidylcholine and phosphatidylethanolamine metabolism related genes in liver were detected by quantitative Reverse transcription polymerase chain reaction (qRT-PCR) and Western-blot.ResultsFollowing Acetaminophen treatment, the content of many PC and PE species in plasma increased from 1 h time point, peaked at 3 h or 6 h, and tended to return to baseline at 24 h time point. The relative contents of almost all PC species in liver decreased from 1 h, appeared to be lowest at 6 h, and then return to normality at 24 h, which might be partly explained by the suppression of phospholipases mRNA expressions and the induction of choline kinase (Chka) expression. Inconsistent with PC profile, the relative contents of many PE species in liver increased upon Acetaminophen treatment, which might be caused by the down-regulation of phosphatidylethanolamine N-methyltransferase (Pemt).ConclusionsAcetaminophen overdose induced dramatic change of many PC and PE species in plasma and liver, which might be caused by damaging hepatocytes and interfering the phospholipid metabolism in Acetaminophen -injured liver.

Gaussian Process Modeling of Protein Turnover.

We describe a stochastic model to compute in vivo protein turnover rate constants from stable-isotope labeling and high-throughput liquid chromatography-mass spectrometry experiments. We show that the often-used one- and two-compartment nonstochastic models allow explicit solutions from the corresponding stochastic differential equations. The resulting stochastic process is a Gaussian processes with Ornstein-Uhlenbeck covariance matrix. We applied the stochastic model to a large-scale data set from (15)N labeling and compared its performance metrics with those of the nonstochastic curve fitting. The comparison showed that for more than 99% of proteins, the stochastic model produced better fits to the experimental data (based on residual sum of squares). The model was used for extracting protein-decay rate constants from mouse brain (slow turnover) and liver (fast turnover) samples. We found that the most affected (compared to two-exponent curve fitting) results were those for liver proteins. The ratio of the median of degradation rate constants of liver proteins to those of brain proteins increased 4-fold in stochastic modeling compared to the two-exponent fitting. Stochastic modeling predicted stronger differences of protein turnover processes between mouse liver and brain than previously estimated. The model is independent of the labeling isotope. To show this, we also applied the model to protein turnover studied in induced heart failure in rats, in which metabolic labeling was achieved by administering heavy water. No changes in the model were necessary for adapting to heavy-water labeling. The approach has been implemented in a freely available R code.

High-throughput liquid chromatography tandem mass spectrometry method for simultaneous determination of fampridine, paroxetine, and quinidine in rat plasma: Application to in vivo perfusion study

A selective and high-throughput liquid chromatography–mass spectrometry method has been developed and validated for the simultaneous quantification of paroxetine, fampridine, and quinidine in rat plasma using imipramine as an internal standard. Following protein precipitation extraction, the analytes and internal standard were run on XBridge C18 column (150 mm × 4.6 mm, 5 μm) using a gradient mobile phase consisting of 5mM ammonium formate in water (pH 9.0) and acetonitrile in a flow gradience program. The precursor and product ions of the drugs were monitored on a triple quadrupole instrument operated in the positive ionization mode. The method was validated over a concentration range of 0.1–100 ng/mL for all the three analytes, with relative recoveries ranging from 69% to 82%. The intra- and interbatch precision (percent coefficient of variation) across four validation runs were less than 13.4%. The accuracy determined at four quality control (QC) levels (lower limit of quantitation, low QC, medium QC, and high QC) was within ±6.5% of coefficient of variation values. The method proved highly reproducible and sensitive, and was successfully applied in a pharmacokinetic study after single-dose oral administration to rats and also in perfusion study sample analysis.