Phenotyping of α-1-Antitrypsin by liquid chromatography–high resolution mass spectrometry
Ontology highlight
ABSTRACT:
SUBMITTER: Bengtson P
PROVIDER: S-EPMC11324609 | biostudies-literature | 2016 Dec
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BACKGROUND:?-1-Antitrypsin (A1AT) deficiency results from a genetic disorder at 2 common loci. Diagnosis requires quantification of A1AT and subsequent identification of the specific variant. The current algorithm of laboratory testing for the diagnosis of A1AT deficiency uses a combination of quantification (nephelometry), genotyping, and/or phenotyping. We developed a multiple reaction monitoring liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for simultaneous quantification of A1AT and identification of the 2 most common deficiency alleles present in 95% of the patients with A1AT deficiency. METHODS:Serum samples (n = 40) were digested with trypsin, and appropriate ¹³C/¹?N-labeled standard peptides were added. We performed LC-MS/MS analysis with a 0.5- by 150-mm C18 column and H?O:acetonitrile:n-propanol:formic acid (A:98:1:1:0.2 and B:10:80:10:0.2; flow 12 ?L/min) mobile phase in positive ion mode on a TSQ Quantum triple quadrupole MS system. We measured the A1AT concentration by comparison to a calibration curve and determined the phenotype by the presence or absence of variant peptides. We compared the results to the current phenotyping assay by isoelectric focusing (IEF) and the immunonephelometry quantitative assay. RESULTS:For A1AT allele detection, in 39 of 40 samples the LC-MS/MS results were identical to those obtained by IEF gel electrophoresis. The single discrepant result was rerun by IEF at a lower dilution, and the results were in concordance. The A1AT quantification by LC-MS/MS also compared favorably with nephelometry. CONCLUSIONS:The LC-MS/MS method correlates well with current phenotyping and nephelometric assays and has the potential to improve the laboratory diagnosis of genetic A1AT deficiency.
| S-EPMC3275912 | biostudies-literature
Project description:We present a liquid chromatography/mass spectrometry (LC/MS) method for long-chain and very-long-chain fatty acid analysis and its application to (13)C-tracer studies of fatty acid metabolism. Fatty acids containing 14 to 36 carbon atoms are separated by C(8) reversed-phase chromatography using a water-methanol gradient with tributylamine as ion pairing agent, ionized by electrospray and analyzed by a stand-alone orbitrap mass spectrometer. The median limit of detection is 5 ng/mL with a linear dynamic range of 100-fold. Ratios of unlabeled to (13)C-labeled species are quantitated precisely and accurately (average relative standard deviation 3.2% and deviation from expectation 2.3%). In samples consisting of fatty acids saponified from cultured mammalian cells, 45 species are quantified, with average intraday relative standard deviations for independent biological replicates of 11%. The method enables quantitation of molecular ion peaks for all labeled forms of each fatty acid. Different degrees of (13)C-labeling from glucose and glutamine correspond to fatty acid uptake from media, de novo synthesis, and elongation. To exemplify the utility of the method, we examined isogenic cell lines with and without activated Ras oncogene expression. Ras increases the abundance and alters the labeling patterns of saturated and monounsaturated very-long-chain fatty acids, with the observed pattern consistent with Ras leading to enhanced activity of ELOVL4 or an enzyme with similar catalytic activity. This LC/MS method and associated isotope tracer techniques should be broadly applicable to investigating fatty acid metabolism.
| S-EPMC3230881 | biostudies-literature
Project description:Methylphenidate is a powerful central nervous system stimulant with a high potential for abuse in horse racing. The detection of methylphenidate use is of interest to horse racing authorities for both prior to and during competition. The use of hair as an alternative sampling matrix for equine anti-doping has increased as the number of detectable compounds has expanded. Our laboratory developed a liquid chromatography-high-resolution mass spectrometry method to detect the presence of methylphenidate in submitted samples. Briefly, hair was decontaminated, cut, and pulverized prior to liquid-liquid extraction in basic conditions before introduction to the LC-MS system. Instrumental analysis was conducted using a Thermo Q Exactive mass spectrometer using parallel reaction monitoring using a stepped collision energy to obtain sufficient product ions for qualitative identification. The method was validated and limits of quantitation, linearity, matrix effects, recovery, accuracy, and precision were determined. The method has been applied to confirm the presence of methylphenidate in official samples submitted by racing authorities.
| S-EPMC8510229 | biostudies-literature
Project description:Hundreds of new psychoactive substances (NPS) covering most drugs-of-abuse classes have been introduced to the recreational drug market in recent years. One class of NPS drugs that has become more common recently is "designer" benzodiazepines. Due to a close structural resemblance with prescription benzodiazepines, some of these substances may elicit a positive response (i.e. cross react) in immunoassay screening. Consequently, it is increasingly important to include NPS benzodiazepines during method confirmation to ensure accurate identification of closely-related compounds as well as detection of the benzodiazepines themselves. Here, we present our efforts to develop a screening and confirmation method for detection of 28 NPS benzodiazepines in urine using reversed-phase liquid chromatographic separation in combination with high-resolution mass spectrometry (LC-HRMS). MS was performed in positive electrospray mode on a Thermo Fischer Scientific Q Exactive Orbitrap instrument using either full scan (for screening) or parallel reaction monitoring (for confirmation). We found the lower quantification limit of the method to range from 5 to 50 ng/mL. Analytical precision and accuracy were ≤15% for both screening and confirmation for all except one analyte. The method was used to analyze patient urine samples from routine drug testing and samples from acute intoxication cases presenting in emergency wards. Altogether, 16 of the 28 benzodiazepines (i.e., clobazam, clonazolam, deschloroetizolam, diclazepam, estazolam, etizolam, flubromazepam, flubromazolam, flunitrazolam, 3-hydroxyflubromazepam, 3-hydroxyphenazepam, ketazolam, meclonazepam, metizolam, nifoxipam, and pyrazolam) were detected in the urine samples. The results from patient sample analysis indicate a high prevalence of NPS benzodiazepine use, emphasizing the importance of including novel drugs of abuse in drug testing menus.
| S-EPMC11322785 | biostudies-literature
Project description:Annotation and interpretation of full scan electrospray mass spectra of metabolites is complicated by the presence of a wide variety of ions. Not only protonated, deprotonated, and neutral loss ions but also sodium, potassium, and ammonium adducts as well as oligomers are frequently observed. This diversity challenges automatic annotation and is often poorly addressed by current annotation tools. In many cases, annotation is integrated in metabolomics workflows and is based on specific chromatographic peak-picking tools. We introduce mzAdan, a nonchromatography-based multipurpose standalone application that was developed for the annotation and exploration of convolved high-resolution ESI-MS spectra. The tool annotates single or multiple accurate mass spectra using a customizable adduct annotation list and outputs a list of [M+H]+ candidates. MzAdan was first tested with a collection of 408 analytes acquired with flow injection analysis. This resulted in 402 correct [M+H]+ identifications and, with combinations of sodium, ammonium, and potassium adducts and water and ammonia losses within a tolerance of 10 mmu, explained close to 50% of the total ion current. False positives were monitored with mass accuracy and bias as well as chromatographic behavior which led to the identification of adducts with calcium instead of the expected potassium. MzAdan was then integrated in a workflow with XCMS for the untargeted LC-MS data analysis of a 52 metabolite standard mix and a human urine sample. The results were benchmarked against three other annotation tools, CAMERA, findMAIN, and CliqueMS: findMAIN and mzAdan consistently produced higher numbers of [M+H]+ candidates compared with CliqueMS and CAMERA, especially with co-eluting metabolites. Detection of low-intensity ions and correct grouping were found to be essential for annotation performance. Graphical abstract.
| S-EPMC7806579 | biostudies-literature
Project description:Pneumococcal type-3 polysaccharide (Pn3P) is considered a major target for the development of a human vaccine to protect against Streptococcus pneumoniae infection. Thus, it is critical to develop methods for the preparation and analysis of Pn3P-derived oligosaccharides to better understand its immunological properties. In this paper, we profile oligosaccharides, generated by the free radical depolymerization of Pn3P, using liquid chromatography (LC)-tandem mass spectrometry (MS/MS). Hydrophilic liquid interaction chromatography (HILIC)-mass spectrometry (MS) revealed a series of oligosaccharides with an even- and odd-number of saccharide residues, ranging from monosaccharide, degree of polymerization (dp1) to large oligosaccharides up to dp 20, generated by free radical depolymerization. Isomers of oligosaccharides with an even number of sugar residues were easily separated on a HILIC column, and their sequences could be distinguished by comparing MS/MS of these oligosaccharides and their reduced alditols. Fluorescent labeling with 2-aminoacridone (AMAC) followed by reversed phase (RP)-LC-MS/MS was applied to analyze and sequence poorly separated product mixtures, as RP-LC affords higher resolution of AMAC-labeled oligosaccharides than does HILIC-based separation. The present methodology can be potentially applied to profiling other capsular polysaccharides.
| S-EPMC4426055 | biostudies-literature
Project description:Broccoli (Brassica oleracea L. var. italica Plenck) is a widely consumed vegetable, very popular due to its various nutritional and bioactive components. Since studies on the lipid components of broccoli have been limited so far, the aim of the present work was the study of free fatty acids (FFAs) present in different broccoli parts, aerial and underground. The direct determination of twenty-four FFAs in broccoli tissues (roots, leaves, and florets) was carried out, using a liquid chromatography-high-resolution mass spectrometry (LC-HRMS) method in a 10 min single run. Linolenic acid was found to be the most abundant FFA in all different broccoli parts in quantities ranging from 0.76 to 1.46 mg/g, followed by palmitic acid (0.17-0.22 mg/g) and linoleic acid (0.06-0.08 mg/g). To extend our knowledge on broccoli's bioactive components, for the first time, the existence of bioactive oxidized fatty acids, namely hydroxy and oxo fatty acids, was explored in broccoli tissues adopting an HRMS-based lipidomics approach. 16- and 2-hydroxypalmitic acids were detected in all parts of broccoli studied, while ricinoleic acid was detected for the first time as a component of broccoli.
| S-EPMC10891939 | biostudies-literature
Project description:IntroductionOsteoarthritis (OA) is a common cause of disability in older people, but its aetiology is not yet fully understood. Biomarkers of OA from metabolomics studies have shown potential use in understanding the progression and pathophysiology of OA.ObjectivesTo investigate possible surrogate biomarkers of knee OA in urine using metabolomics to contribute towards a better understanding of OA progression and possible targeted treatment.MethodLiquid chromatography-high resolution mass spectrometry (LC-HRMS) was applied in a case-control approach to explore the possible metabolic differences between the urinary profiles of symptomatic knee OA patients (n = 74) (subclassified into inflammatory OA, n = 22 and non-inflammatory OA, n = 52) and non-OA controls (n = 68). Univariate, multivariate and pathway analyses were performed with a rigorous validation including cross-validation, permutation test, prediction and receiver operating characteristic curve to identify significantly altered metabolites and pathways in OA.ResultsOA datasets generated 7405 variables and multivariate analysis showed clear separation of inflammatory OA, but not non-inflammatory OA, from non-OA controls. Adequate cross-validation (R2Y = 0.874, Q2 = 0.465) was obtained. The prediction model and the ROC curve showed satisfactory results with a sensitivity of 88%, specificity of 71% and accuracy of 77%. 26 metabolites were identified as potential biomarkers of inflammatory OA using HMDB, authentic standards and/or MS/MS database.ConclusionUrinary metabolic profiles were altered in inflammatory knee OA subjects compared to those with non-inflammatory OA and non-OA controls. These altered profiles associated with perturbed activity of the TCA cycle, pyruvate and amino acid metabolism linked to inflammation, oxidative stress and collagen destruction. Of note, 2-keto-glutaramic acid level was > eightfold higher in the inflammatory OA patients compared to non-OA control, signalling a possible perturbation in glutamine metabolism related to OA progression.
| S-EPMC7925472 | biostudies-literature
Project description:The increasing frequency of episodes of harmful algal blooms of cyanobacterial origin is a risk to ecosystems and human health. The main human hazard may arise from drinking water supply and recreational water use. For this reason, efficient multiclass analytical methods are needed to assess the level of cyanotoxins in water reservoirs and tackle these problems. This work describes the development of a fast, sensitive, and robust analytical method for multiclass cyanotoxins determination based on dual solid-phase extraction (SPE) procedure using a polymeric cartridge, Oasis HLB (Waters Corporation, Milford, MA, USA), and a graphitized non-porous carbon cartridge, SupelcleanTM ENVI-CarbTM (Sigma-Aldrich, St. Louis, MO, USA), followed by ultra-high-performance liquid chromatography high-resolution mass spectrometry (SPE-UHPLC-HRMS). This method enabled the analysis of cylindrospermopsin, anatoxin-a, nodularin, and seven microcystins (MC-LR, MC-RR, MC-YR, MC-LA, MC-LY, MC-LW, MC-LF). The method limits of detection (MLOD) of the validated approach were between 4 and 150 pg/L. The analytical method was applied to assess the presence of the selected toxins in 21 samples collected in three natural water reservoirs in the Ter River in Catalonia (NE of Spain) used to produce drinking water for Barcelona city (Spain).
| S-EPMC7232229 | biostudies-literature
Project description:The application of metabolic phenotyping to epidemiological studies involving thousands of biofluid samples presents a challenge for the selection of analytical platforms that meet the requirements of high-throughput precision analysis and cost-effectiveness. Here direct infusion-nanoelectrospray (DI-nESI) was compared with an ultra-performance liquid chromatography (UPLC)-high-resolution mass spectrometry (HRMS) method for metabolic profiling of an exemplary set of 132 human urine samples from a large epidemiological cohort. Both methods were developed and optimized to allow the simultaneous collection of high-resolution urinary metabolic profiles and quantitative data for a selected panel of 35 metabolites. The total run time for measuring the sample set in both polarities by UPLC-HRMS was 5 days compared with 9 h by DI-nESI-HRMS. To compare the classification ability of the two MS methods, we performed exploratory analysis of the full-scan HRMS profiles to detect sex-related differences in biochemical composition. Although metabolite identification is less specific in DI-nESI-HRMS, the significant features responsible for discrimination between sexes were mostly the same in both MS-based platforms. Using the quantitative data, we showed that 10 metabolites have strong correlation (Pearson's r > 0.9 and Passing-Bablok regression slope of 0.8-1.3) and good agreement assessed by Bland-Altman plots between UPLC-HRMS and DI-nESI-HRMS and thus can be measured using a cheaper and less sample- and time-consuming method. A further twenty metabolites showed acceptable correlation between the two methods with only five metabolites showing weak correlation (Pearson's r < 0.4) and poor agreement due to the overestimation of the results by DI-nESI-HRMS.
| S-EPMC6184476 | biostudies-literature