Full-scan Analysis Research Articles

LC-MS-Based Direct Quantification of MicroRNAs in Rat Blood.

MicroRNA (miRNA) has recently garnered significant research attention, owing to its potential as a diagnostic biomarker and therapeutic target. Liquid chromatography-mass spectrometry (LC-MS) offers accurate quantification, multiplexing capacity, and high compatibility with various matrices. These advantages establish it as a preferred technique for detecting miRNA in biological samples. In this study, we presented an LC-MS method for directly quantifying seven miRNAs (rno-miR-150, 146a, 21, 155, 223, 181a, and 125a) associated with immune and inflammatory responses in rat whole blood. To ensure miRNA stability in the samples and efficiently purify target analytes, we compared Trizol- and proteinase K-based extraction methods, and the Trizol extraction proved to be superior in terms of analytical sensitivity and convenience. Chromatographic separation was carried out using an oligonucleotide C18 column with a mobile phase composed of N-butyldimethylamine, 1,1,1,3,3,3-hexafluoro-2-propanol, and methanol. For MS detection, we performed high-resolution full scan analysis using an orbitrap mass analyzer with negative electrospray ionization. The established method was validated by assessing its selectivity, linearity, limit of quantification, accuracy, precision, recovery, matrix effect, carry-over, and stability. The proposed assay was then applied to simultaneously monitor target miRNAs in lipopolysaccharide-treated rats. Although potentially less sensitive than conventional methods, such as qPCR and microarray, this direct-detection-based LC-MS method can accurately and precisely quantify miRNA. Given these promising results, this method could be effectively deployed in various miRNA-related applications.

Untargeted Screening and Identification of Contaminants Using Gas Chromatography Coupled to High-Resolution Accurate Mass–Mass Spectrometry: Novel Solutions for Applied Testing Laboratories

The combination of gas chromatography (GC) instruments with quadrupole-based mass spectrometers is a common analytical setup for the detection of a broad range of volatile and semivolatile contaminants. GC–mass spectrometry (MS) (nominal mass) instruments are well known for their robustness and ease of use. However, they have some important limitations. Single quadrupole instruments can perform full scan analysis, but their sensitivity and selectivity in this mode are limited. Triple quadrupole (GC–MS/MS) systems are limited to a targeted acquisition within a specified compound list. High-resolution accurate mass (HRAM) mass spectrometry can overcome these limitations.

Disruptions in Megaregional Network Evacuations: Identifying and Assessing Critical Links

Mass evacuations are a protective action to move large populations from hazardous areas to safety. However, even the best-planned evacuations can be slowed by unexpected disruptions, such as traffic incidents. Even minor disruptions can significantly slow evacuations, so it is critical to understand which links are most vital to the operation of the system. This paper describes a study to address that need by developing a method to evaluate large networks more efficiently to identify links that disproportionately increase network delay when affected by disruptive incidents. The study is unique because it examined the impact of individual link disruptions over a megaregional network covering thousands of square miles while drastically reducing the computation time necessary for a traditional full-scan analysis. In the research, link criticality was quantified by an index using factors such as alternative path availability, global maximum flow properties, modified betweenness centrality, and hazard exposure. Links with high indices established an initial “most-critical” list, then agent-based simulation was used to quantify the network-wide effects of disrupting these most-critical links. Results showed that links with the highest indices often had the fewest alternative paths to avoid them. Thus, while incident effects tended to be localized, findings suggest that networks with more path alternatives tend to have higher overall resilience to disruptions. By giving the ability to reduce computational efforts to evaluate large-scale networks, this methodology can be used in emergency planning to focus monitoring on the most important areas and allow them to be monitored for disruptions to maintain network efficiency.

Determination of subpicogram levels of airborne polycyclic aromatic hydrocarbons for personal exposure monitoring assessment

A method based on the use of GC coupled to Q-exactive Orbitrap mass spectrometry (GC-Orbitrap-MS) has been developed for the analysis of polycyclic aromatic hydrocarbons (PAHs) at sub-picogram levels. Outdoor ambient air particulate matter (PM2.5) and standard reference materials (SRM2260a) were analyzed in full scan mode showing low instrumental uncertainties (1–22%) and high linearity over a wide concentration range (0.5 pg and 500 pg/μL). Good reproducibility was obtained compared to the use of conventional single quadrupole GC–MS of PM samples. The quantification limit of the GC-Orbitrap-MS method for full scan analysis of PAHs in outdoor ambient air PM samples was 0.5 pg/μL. This low limit allowed the analysis of PAHs in samples collected with low volumes (< 0.5 m3), such as punch samples from whole filters or filter strips from personal exposure monitoring equipment. PAHs were successfully analyzed in filter strips from real-time Aethalometer AE51 equivalent black carbon (eBC) analyzers used in urban and rural sites, and in personal exposure monitors of firefighters during prescribed burns. The correlations between PAHs and eBC in these analyses were very strong (r2 ≥ 0.93). However, the equations obtained reflected the dominance of different emission sources, such as traffic in urban areas, wood burning for domestic heating, or wildfires. The method reported here affords the analyses of PAHs in high precision studies of atmospheric PM samples, e.g., high frequency sampling of low volumes, affording personal exposure monitoring assessments.

Reproducible untargeted metabolomics workflow for exhaustive MS2 data acquisition of MS1 features

Unknown features in untargeted metabolomics and non-targeted analysis (NTA) are identified using fragment ions from MS/MS spectra to predict the structures of the unknown compounds. The precursor ion selected for fragmentation is commonly performed using data dependent acquisition (DDA) strategies or following statistical analysis using targeted MS/MS approaches. However, the selected precursor ions from DDA only cover a biased subset of the peaks or features found in full scan data. In addition, different statistical analysis can select different precursor ions for MS/MS analysis, which make the post-hoc validation of ions selected following a secondary analysis impossible for precursor ions selected by the original statistical method. Here we propose an automated, exhaustive, statistical model-free workflow: paired mass distance-dependent analysis (PMDDA), for reproducible untargeted mass spectrometry MS2 fragment ion collection of unknown compounds found in MS1 full scan. Our workflow first removes redundant peaks from MS1 data and then exports a list of precursor ions for pseudo-targeted MS/MS analysis on independent peaks. This workflow provides comprehensive coverage of MS2 collection on unknown compounds found in full scan analysis using a “one peak for one compound” workflow without a priori redundant peak information. We compared pseudo-spectra formation and the number of MS2 spectra linked to MS1 data using the PMDDA workflow to that obtained using CAMERA and RAMclustR algorithms. More annotated compounds, molecular networks, and unique MS/MS spectra were found using PMDDA compared with CAMERA and RAMClustR. In addition, PMDDA can generate a preferred ion list for iterative DDA to enhance coverage of compounds when instruments support such functions. Finally, compounds with signals in both positive and negative modes can be identified by the PMDDA workflow, to further reduce redundancies. The whole workflow is fully reproducible as a docker image xcmsrocker with both the original data and the data processing template.Graphical

Leachate from plastic food packaging induced reproductive and neurobehavioral toxicity in zebrafish

The present study mimicked daily life exposure to plastic food package bags and evaluated its effects on the reproductive and neurobehavioral responses using zebrafish model. Gas chromatography-mass spectrometer (GC/MS) full scan analysis revealed that phthalic acid, isobutyl octyl ester (DEHP) and its metabolites were the main leachate from plastic bags. Our results demonstrated that during the eight weeks exposure, leaching from plastic bags treated with boiling water (P-high group) significantly affected the spawn egg production, embryo hatching and larval malformation rate. Cross-spawning trails between zebrafish collected from the controls and P-high group at the end of eight weeks showed that these adverse effects were more severe in the offspring derived from paternal exposure than those derived from the maternal exposure, suggesting leached chemicals may have a more pronounced effect in sperm than in eggs. In addition, P-high group male testis weight, sperm motility and sperm swimming velocities were decreased significantly. After eight weeks treatment, neurobehavioral tests demonstrated significant changes in the swimming speed during free swimming and light-dark stimulation in the adult zebrafish from P-high group, with the effects being more severe in the males than females. P-high group males also showed altered response in the light/dark explore and mirror attacks assays.

A Study to Recover Si from End-of-Life Solar Cells using Ultrasonic Cleaning Method

본 연구에서는 사용 후 태양광 셀을 HCl 용액 및 초음파세척기의 cavitation효과를 사용하여 셀 표면의 불순물(Al, Zn, Ag 등)을 제거하여 Si을 선택적으로 회수하기 위한 최적 공정 조건을 찾기 위한 연구를 진행하였다. 태양광 셀에서 Si을 선택적으로 회수 하기 위해 HCl 용액 및 초음파세척기를 사용하여 침출을 진행하였고, 반응이 끝난 태양광 셀은 증류수로 세척 후 건조 오븐에 건조를 실시하였고, 반응된 HCl 용액은 감압 여과 실시 후 여과된 용액은 ICP-Full Scan 분석을 실시하였다. 또한, 건조 된 태양광 셀은 유발을 사용하여 파쇄 후 XRD, XRF, 및 ICP-OES 분석을 실시하였으며, 이를 통해 Si의 순도 및 회수율을 알 수 있었다. 실험은 산용액 농도, 반응 온도, 반응 시간, 초음파 세기를 변수로 두고 실험을 진행하였다. 위 과정을 통해 최종적으로 태양광 셀로부터 Si을 선택적으로 회수하기 위한 최적 공정 조건은 산용액 농도 3M HCl, 반응 온도 60&#x2103;, 반응 시간 120min, 초음파 세기 150W인것을 알 수 있었고, 최종적으로 Si의 순도는 99.85%, 회수율은 99.24%로 측정되었다. In this study, we determine the optimal process conditions for selectively recovering Si from a solar cell surface by removal of impurities (Al, Zn, Ag, etc.). To selectively recover Si from solar cells, leaching is performed using HCl solution and an ultrasonic cleaner. After leaching, the solar cells are washed using distilled water and dried in an oven. Decompression filtration is performed on the HCl solution, and ICP-OES (Inductively Coupled Plasma Optical Emission spectroscopy) full scan analysis is performed on the filtered solution. Furthermore, XRD (X-ray powder diffraction), XRF (X-ray fluorescence), and ICP-OES are performed on the dried solar cells after crushing, and the purity and recovery rate of Si are obtained. In this experiment, the concentration of acid solution, reaction temperature, reaction time, and ultrasonic intensity are considered as variables. The results show that the optimal process conditions for the selective recovery of Si from the solar cells are as follows: the concentration of acid solution = 3 M HCl, reaction temperature = 60&#x2103;, reaction time = 120 min, and ultrasonic intensity = 150 W. Further, the Si purity and recovery rate are 99.85 and 99.24%, respectively.

A Downsized and Optimised Intracellular Library-Derived Peptide Prevents Alpha-Synuclein Primary Nucleation and Toxicity Without Impacting Upon Lipid Binding

Misfolding and aggregation of alpha-synuclein (αS) within dopaminergic neurons is a key factor in the development and progression of a group of age-related neurodegenerative diseases, termed synucleinopathies, that include Parkinson’s disease (PD). We previously derived a peptide inhibitor from a 209,952-member intracellular library screen by employing the preNAC region (45–54) as a design template. At least six single-point mutations firmly linked to early-onset Parkinson’s disease (E46K, H50Q, G51D, A53T/E/V) are located within this region, strongly implicating a pathogenic role within αS that leads to increased cytotoxicity. A library-derived ten residue peptide, 4554W, was consequently shown to block αS aggregation at the point of primary nucleation via lipid induction, inhibiting its conversion into downstream cytotoxic species. Here we couple truncation with a full alanine scan analysis, to establish the effect upon the αS aggregation pathway relative to 4554W. This revealed the precise residues responsible for eliciting inhibitory interaction and function, as well as those potentially amenable to modification or functionalisation. We find that modification N6A combined with N-terminal truncation results in a peptide of significantly increased efficacy. Importantly, our data demonstrate that the peptide does not directly disrupt αS lipid-binding, a desirable trait since antagonists of αS aggregation and toxicity should not impede association with small synaptic neurotransmitter vesicles, and thus not disrupt dopaminergic vesicle fusion and recycling. This work paves the way toward the major aim of deriving a highly potent peptide antagonist of αS pathogenicity without impacting on native αS function.

Topological-Based Measures with Flow Attributes to Identify Critical Links in a Transportation Network

An important part of transportation network vulnerability analysis is identifying critical links where failure may lead to severe consequences, and the potential of such incidents cannot be considered negligible. Existing transportation network vulnerability assessment can be categorized as topological, or traffic based. Topological-based assessment identifies the most critical components in the network by considering network structure and connectivity. Traffic-based assessment identifies the most critical components in the network by full-scan analysis and takes into consideration effects of link failures to traffic flow assignment. The former approach does not consider traffic flow dynamics and fails to capture the non-linearity performance function of transport systems while the latter, even though accurate and robust, requires significant computational power and time and may not always be feasible for real life size networks. The primary objective of this paper is to propose new link criticality measures and evaluate their accuracy for transportation network vulnerability assessment. These measures combine characteristics of traffic equilibrium and network topology to balance accuracy and computational complexity. Nine measures are proposed, and their accuracy is compared with three existing traffic-based measures using three case study transportation networks from the literature. Results indicate that three of the proposed measures show strong correlation to the three traffic-based measures while requiring significantly less computational power and time.

Suitability of High-Resolution Mass Spectrometry for Routine Analysis of Small Molecules in Food, Feed and Water for Safety and Authenticity Purposes: A Review.

During the last decade, food, feed and environmental analysis using high-resolution mass spectrometry became increasingly popular. Recent accessibility and technological improvements of this system make it a potential tool for routine laboratory work. However, this kind of instrument is still often considered a research tool. The wide range of potential contaminants and residues that must be monitored, including pesticides, veterinary drugs and natural toxins, is steadily increasing. Thanks to full-scan analysis and the theoretically unlimited number of compounds that can be screened in a single analysis, high-resolution mass spectrometry is particularly well-suited for food, feed and water analysis. This review aims, through a series of relevant selected studies and developed methods dedicated to the different classes of contaminants and residues, to demonstrate that high-resolution mass spectrometry can reach detection levels in compliance with current legislation and is a versatile and appropriate tool for routine testing.

Exploring lipid biomarkers of coronary heart disease for elucidating the biological effects of gelanxinning capsule by lipidomics method based on LC-MS.

High-throughput lipidomics technology was used to explore the potential therapeutic targets and mechanism of action of gelanxinning capsule on rat model with coronary heart disease (CHD). This study attempts to provide a novel method to interpret the molecular mechanism of traditional medicine. The lipid markers of CHD were determined by full-scan analysis based on ultra-performance liquid chromatography-high-definition mass spectrometry. Then, the metabolic changes associated with gelanxinning capsule treatment via the modulation of lipid biomarkers and pathway in rats were characterized. After gelanxinning treatment, the metabolic profile tended to recover compared with the model group. A total of 26 potential biomarkers were identified to represent the disorders of lipid metabolism in CHD animal model, of which 19 were regulated by gelanxinning capsule administration, and four metabolic pathways such as glycerophospholipid metabolism, sphingolipid metabolism, glycosylphosphatidylinositol-anchor biosynthesis, and glycerolipid metabolism were involved. From the pathway analysis, it was found that glycerophospholipid metabolism and sphingolipid metabolism with significant differences have the potential to be regarded as new targets for the treatment of CHD. Gelanxinning capsule with its good therapeutic effect protects against CHD by regulating lipid biomarkers and pathway from lipidomics-guided biochemical analysis.

Flying High with Sensitivity and Selectivity: GC–MS to GC–MS/MS

Mass spectrometry (MS), often termed mass selective detection, is the most powerful detector available for gas chromatography (GC). Multidimensional mass spectrometry (MS/MS) takes mass selective detection to another level on benchtop systems, offering both universal and selective detection along with low detection limits. In this installment of “GC Connections,” we review the fundamentals of MS/MS and how they relate to MS as a detector for GC. We see how using full-scan analyses can make the detector universal, and how, by using selected ion monitoring and multiple reaction monitoring, the detector can be so selective and noise-free that femtogram quantitative analysis is commonplace. We then examine some scenarios that should lead analysts to consider using GC–MS/MS to solve complex problems.

PIIMS Server: A Web Server for Mutation Hotspot Scanning at the Protein-Protein Interface.

Protein-protein interactions (PPIs) play vital roles in regulating biological processes, such as cellular and signaling pathways. Hotspots are certain residues located at protein-protein interfaces that contribute more in protein-protein binding than other residues. Research on the mutational effects of hotspots is important for understanding basic aspects of protein association. Hence, various computational tools have been developed to explore the impact of mutation hotspots, which will allow a better understanding of the forces that drive PPIs. However, tools that may provide comprehensive substitutions at hotspots are still rare. Hence, there is a strong need for a new free web server to explore mutational effects of hotspots. Herein we introduce a web server named PIIMS that integrates molecular dynamics simulation and one-step free energy perturbation. It contains two main computational functions: (1) computational alanine scanning analysis to identify hotspots and (2) full mutation scanning analysis to evaluate the effects of hotspot mutations. We rigidly validated its ability to predict binding free energy changes by using large and diverse datasets including 1,341 mutations from 50 PPIs with the correlation coefficient R = 0.75. The difference from the existing tools is that PIIMS can perform further evaluation of hotspot residues with regard to their different mutations. The PIIMS web server (accessible at http://chemyang.ccnu.edu.cn/ccb/server/PIIMS/index.php) is free and open to all users without login requirements.

Difference between Diabetic Macular Edema and Pseudophakic Macular Edema Using Optical Coherence Tomography

Context: Macular edema (ME) is a common pathologic condition causing vision impairment. Diabetic retinopathy is a common cause of ME which can also develop after cataract surgery. Optical coherence tomography (OCT) is a noninvasive diagnostic technique that provides imaging of fine retinal details. Proper diagnosis of the underlying etiology shall affect the management. Aims: This study aims to differentiation between diabetic and pseudophakic ME (DME and PME) using OCT. Settings and Design: Cross-sectional study of 2 Groups; A: 30 eyes with DME and B: 20 eyes with PME. Subjects and Methods: Full clinical evaluation, OCT scanning, and data analysis were done for both groups. Statistical Analysis Used: SPSS software v. 16 was used for: Descriptive statistics, mean, range, and standard deviation. Student's t-test was used for comparison between means. Pearson correlation coefficient was used to assess correlation between variables. Results: Maximum macular thickness and central macular thickness were elevated in both groups but were higher in PME group (P = 0.042 and P = 0.00001, respectively). Macular thickness/volume ratio (TVR) was higher in PME group (P = 0.00001). Cystic changes had different distribution patterns; ganglion cell layer and retinal nerve fiber layer layers were free in PME(Pseudophakic macular edema) while inner nuclear layer and outer nuclear layer were affected in both groups (P = 0.0061). Epiretinal membranes were found much more in DME group (P = 0.0452). Dome-shaped macula was frequently noticed in PME group (P = 0.043). Conclusions: PME and DME have different OCT features; higher TVR, dome-shaped macula, absence of ERM suggest PME while lower TVR, presence of inner retinal cysts and/or ERM suggest DME.

Analysis of Anabolic Agents in Whey Protein by Gas Chromatography Coupled to Triple Quadrupole Mass Spectrometry

Whey protein-based supplements are one of the most consumed products to improve performance, and they are, generally, recognized as being safe. However, recent studies indicated different types of adulterations in these products, including the presence of diuretics and stimulants, allowing the possibility of contamination by other substances with pharmacological activities, such as anabolic agents. In this sense, the aim of this study was to develop and validate a method for the screening of 46 anabolic agents in whey protein. The analytical method consisted of sample preparation using liquid-liquid extraction, followed by analytes derivatization and, finally, analysis by gas chromatography coupled to triple quadrupole mass spectrometry in two different experiments: multiple reaction monitoring and full scan. After validation, the method proved to be specific, accurate, and precise; no carry over effect was observed, and the limit of detection values varied between 0.5 and 100 ng g−1. The analysis of 44 commercial samples did not detect the presence of any anabolic agent. However, full scan analysis detected caffeine in 14 samples and bisphenol A in one of them. Therefore, these results indicate that the analyzed samples are safe concerning the presence of the evaluated anabolic agents, but it does not mean that they are free from the presence of other substances with pharmacological activities which are not declared on label.

The Presence of 2-Thiaadamantane in Niger Delta Oils may indicate Souring in Niger Delta Reservoirs

Abstract Some oil samples from various Nigerian oil fields were examined for the presence of Thermochemical Sulphate Reduction (TSR) derived organo sulphur compounds. Oil samples were diluted with DCM and injected into the GC–MS for full scan analysis. The GC–MS results show the presence 2–thiaadamantane, 1–methyl-2-thiaadamanatane and 5–methyl-2-thiaadamanatane, the compounds were identified by comparison of extracted spectras with literature. The presence of these compounds in oils has been accepted on a wider horizon as indicators of reservoir souring. The plot of 5–Methyl-2-thiaadamantane/Adamantane and Dibenzothiophene/Adamanatane showed a fair correlation, corroborating the presence of 5–Methyl-2-thiaadamantane and fairly high abundance of Dibenzothiophene, the plot of 2-thiaadamantane/Adamantane and 5–Methyl-2-Thiaadamantane/Adamantane corroborating the presence of 2-thiaadamantane and 5–Methyl-2-Thiaadamantane inferring that the presence of 2-thiaadamantane and 5–Methyl-2-Thiaadamantane indicate that reservoir souring is active.

Lower limit of detection achieved by raw band-target entropy minimization (rBTEM) for trace and coeluted gas chromatography-mass spectrometry components

Full-scan gas chromatography-mass spectrometry (GC-MS) provides rapid untargeted screening and detection for trace and coeluting components. Even though modern mass spectrometers have sufficient sensitivity to detect signals of trace components, this does not translate to the ability of the data-processing approach to isolate interference signals and extract pure component spectra. The raw band-target entropy minimization (rBTEM) approach based on band-target entropy minimization was previously reported to enable accurate spectra reconstruction from severely coeluting and trace GC-MS components. In this study, we evaluate the limit of detection for the approach. This study is systematically compared to classical spectral deconvolution for measurements of chlorpyrifos pesticide standards sampled with solid-phase microextraction at various concentration levels in both distilled and seawater media. The rBTEM approach was able to detect chlorpyrifos at 0.5 ppb in distilled water and 1.0 ppb in seawater while the classical approach provided numerous false negative results. In addition, rBTEM consistently provided higher match scores for chlorpyrifos. Attaining accurate identification of trace and coeluting components from full-scan GC-MS analysis has immense potential impact in biomedical, agricultural, and environmental work.

High-throughput lipidomics characterize key lipid molecules as potential therapeutic targets of Kaixinsan protects against Alzheimer's disease in APP/PS1 transgenic mice

Alzheimer's disease (AD) is still a major problem nowadays. Under the circumstance of many chemical drugs have poor effects on AD, traditional Chinese medicine has become a hot spot for us due to its multi-target and multi-path advantages. To explore the potential therapeutic targets of Kaixinsan (KXS) protects against AD in APP/PS1 transgenic mice model. All mice were divided into three groups: control group, model group and KXS group. Orally given KXS from two month old, and the control and model groups were given the same dose of distilled water. We collected all mice's serum samples at the 12th month age to determine the lipid markers of AD by compare with the model and control groups in full-scan analysis based on high-throughput serum lipidomics technology. Then we found the lipid molecules called back by KXS from the KXS protects against AD. Compared with the control group, the metabolic profile of the model mice was obviously disordered, and we identified 16 lipid-related biomarkers associated with AD. After KXS treatment, the metabolic profiles of these disorders tended to recover compared with the model group. And we identified eight key lipid molecules, of which four had statistical significance. We found that the main perturbation pathways related to AD were linoleic acid metabolism, arachidonic acid metabolism and sphingolipid metabolism. All these metabolic pathways showed different degrees of rotation after KXS administration. Through the pathways analysis, we found 4 lipids molecules with significant differences, which could be used as new targets for the treatment of AD.

LC-HRMS Metabolomics for Untargeted Diagnostic Screening in Clinical Laboratories: A Feasibility Study

Today’s high-resolution mass spectrometers (HRMS) allow bioanalysts to perform untargeted/global determinations that can reveal unexpected compounds or concentrations in a patient’s sample. This could be performed for preliminary diagnosis attempts when usual diagnostic processes and targeted determinations fail. We have evaluated an untargeted diagnostic screening (UDS) procedure. UDS is a metabolome analysis that compares one sample (e.g., a patient) with control samples (a healthy population). Using liquid chromatography (LC)-HRMS full-scan analysis of human serum extracts and unsupervised data treatment, we have compared individual samples that were spiked with one xenobiotic or a higher level of one endogenous compound with control samples. After the use of different filters that drastically reduced the number of metabolites detected, the spiked compound was eventually revealed in each test sample and ranked. The proposed UDS procedure appears feasible and reliable to reveal unexpected xenobiotics (toxicology) or higher concentrations of endogenous metabolites. HRMS-based untargeted approaches could be useful as preliminary diagnostic screening when canonical processes do not reveal disease etiology nor establish a clear diagnosis and could reduce misdiagnosis. On the other hand, the risk of overdiagnosis of this approach should be reduced with mandatory biomedical interpretation of the patient’s UDS results and with confirmatory targeted and quantitative determinations.

A Survey of Orbitrap All Ion Fragmentation Analysis Assessed by an R MetaboList Package to Study Small-Molecule Metabolites

Leukemia cell and melanoma tumor tissue extracts were studied for small (mostly m/z < 250) polar metabolites by LC-ESI-HRMSn analysis powered by a hybrid Quadrupole-Orbitrap. MS data were simultaneously acquired in fast polarity switching mode operating in MS1 and MS/MS (All Ion Fragmentation, AIF) full-scan analyses at high mass resolution. Positive metabolite assignments were achieved by AIF analysis considering at least two characteristic transitions. Targeted metabolite profiling was achieved by the relative quantification of 18 metabolites through spiking of their respective deuterated counterparts. Manual data processing of MS1 and AIF scans were compared for the accurate determination of natural metabolites and their deuterated analogs by chromatographic alignment and peak area integration. Evaluation of manual and automated (MetaboList R package) AIF data processing yielded comparable results. The versatility of AIF analysis also enabled the untargeted metabolite profiling of leukemia and melanoma samples in which 22 and 53 compounds were, respectively, identified outside those studied by labeling. The main limitation of this method was that low abundance metabolites with scan rates below 8 scans/peak could not be accurately quantified by AIF analysis. The combination of AIF analysis with MetaboList R package represents an opportunity to move towards automated, faster, and more global metabolomics approaches supported by an entirely flexible open source data processing platform freely available from Comprehensive R Archive Network (CRAN, https://CRAN.R-project.org/package=MetaboList ).