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Changes of glycosylation pattern in serum proteins have been linked to various diseases including cancer, suggesting possible development of novel biomarkers based on the glycomic analysis. In this study, N-linked glycans from human serum were quantitatively profiled by matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) and compared between healthy controls and ovarian cancer patients. A training set consisting of 40 healthy controls and 40 ovarian cancer cases demonstrated an inverse correlation between P value of ANOVA and area under the curve (AUC) of each candidate biomarker peak from MALDI-TOF MS, providing standards for the classification. A multibiomarker panel composed of 15 MALDI-TOF MS peaks resulted in AUC of 0.89, 80~90% sensitivity, and 70~83% specificity in the training set. The performance of the biomarker panel was validated in a separate blind test set composed of 23 healthy controls and 37 ovarian cancer patients, leading to 81~84% sensitivity and 83% specificity with cut-off values determined by the training set. Sensitivity of CA-125, the most widely used ovarian cancer marker, was 74% in the training set and 78% in the test set, respectively. These results indicate that MALDI-TOF MS-mediated serum N-glycan analysis could provide critical information for the screening of ovarian cancer.
Incorporating safety data early in the drug discovery pipeline is key to reducing costly lead candidate failures. For a single drug development project, we estimate that several thousand samples per day require screening (<10 s per acquisition). While chromatography-based metabolomics has proven value at predicting toxicity from metabolic biomarker profiles, it lacks sufficiently high sample throughput. Acoustic mist ionization mass spectrometry (AMI-MS) is an atmospheric pressure ionization approach that can measure metabolites directly from 384-well plates with unparalleled speed. We sought to implement a signal processing and data analysis workflow to produce high-quality AMI-MS metabolomics data and to demonstrate its application to drug safety screening. An existing direct infusion mass spectrometry workflow was adapted, extended, optimized, and tested, utilizing three AMI-MS data sets acquired from technical and biological replicates of metabolite standards and HepG2 cell lysates and a toxicity study. Driven by criteria to minimize variance and maximize feature counts, an algorithm to extract the pulsed scan data was designed; parameters for signal-to-noise-ratio, replicate filter, sample filter, missing value filter, and RSD filter were all optimized; normalization and batch correction strategies were adapted; and cell phenotype filtering was implemented to exclude high cytotoxicity samples. The workflow was demonstrated using a highly replicated HepG2 toxicity data set, comprising 2772 samples from exposures to 16 drugs across 9 concentrations and generated in under 5 h, revealing metabolic phenotypes and individual metabolite changes that characterize specific modes of action. This AMI-MS workflow opens the door to ultrahigh-throughput metabolomics screening, increasing the rate of sample analysis by approximately 2 orders of magnitude.
A new and fully automated newborn screening method for mass spectrometry was introduced in this paper. Pathological relevant amino acids, acylcarnitines, and certain steroids are detected within 4 min per sample. Each sample is treated in an automated and standardized workflow, where a mixture of deuterated internal standards is sprayed onto the sample before extraction. All compounds showed good linearity, and intra- and inter-day variation lies within the acceptance criteria (except for aspartic acid). The described workflow decreases analysis cost and labor while improving the sample traceability towards good laboratory practice.
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.
Deubiquitylases (DUBs) are key regulators of the ubiquitin system which cleave ubiquitin moieties from proteins and polyubiquitin chains. Several DUBs have been implicated in various diseases and are attractive drug targets. We have developed a sensitive and fast assay to quantify in vitro DUB enzyme activity using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. Unlike other current assays, this method uses unmodified substrates, such as diubiquitin topoisomers. By analysing 42 human DUBs against all diubiquitin topoisomers we provide an extensive characterization of DUB activity and specificity. Our results confirm the high specificity of many members of the OTU and JAB/MPN/Mov34 metalloenzyme DUB families and highlight that all USPs tested display low linkage selectivity. We also demonstrate that this assay can be deployed to assess the potency and specificity of DUB inhibitors by profiling 11 compounds against a panel of 32 DUBs.
Chemical database searching has become a fixture in many non-targeted identification workflows based on high-resolution mass spectrometry (HRMS). However, the form of a chemical structure observed in HRMS does not always match the form stored in a database (e.g., the neutral form versus a salt; one component of a mixture rather than the mixture form used in a consumer product). Linking the form of a structure observed via HRMS to its related form(s) within a database will enable the return of all relevant variants of a structure, as well as the related metadata, in a single query. A Konstanz Information Miner (KNIME) workflow has been developed to produce structural representations observed using HRMS ("MS-Ready structures") and links them to those stored in a database. These MS-Ready structures, and associated mappings to the full chemical representations, are surfaced via the US EPA's Chemistry Dashboard ( https://comptox.epa.gov/dashboard/ ). This article describes the workflow for the generation and linking of ~ 700,000 MS-Ready structures (derived from ~ 760,000 original structures) as well as download, search and export capabilities to serve structure identification using HRMS. The importance of this form of structural representation for HRMS is demonstrated with several examples, including integration with the in silico fragmentation software application MetFrag. The structures, search, download and export functionality are all available through the CompTox Chemistry Dashboard, while the MetFrag implementation can be viewed at https://msbi.ipb-halle.de/MetFragBeta/ .
Background: Spinal muscular atrophy (SMA) is the most common neurodegenerative disorder and the leading genetic cause of infant mortality. Early detection of SMA through newborn screening (NBS) is essential to selecting pre-symptomatic treatment and ensuring optimal outcome, as well as, prompting the urgent need for effective screening methods. This study aimed to determine the feasibility of applying an Agena iPLEX SMA assay in NBS for SMA in China. Methods: We developed an Agena iPLEX SMA assay based on the matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, and evaluated the performance of this assay through assessment of 167 previously-genotyped samples. Then we conducted a pilot study to apply this assay for SMA NBS. The SMN1 and SMN2 copy number of screen-positive patients were determined by multiplex ligation-dependent probe amplification analysis. Results: The sensitivity and specificity of the Agena iPLEX SMA assay were both 100%. Three patients with homozygous SMN1 deletion were successfully identified and conformed by multiplex ligation-dependent probe amplification analysis. Two patients had two SMN2 copies, which was correlated with severe SMA type I phenotype; both of them exhibited neurogenic lesion and with decreased muscle power. Another patient with four SMN2 copies, whose genotype correlated with milder SMA type III or IV phenotype, had normal growth and development without clinical symptoms. Conclusions: The Agena iPLEX SMA assay is an effective and reliable approach for population-based SMA NBS. The first large-scale pilot study using this assay in the Mainland of China showed that large-scale implementation of population-based NBS for SMA is feasible.
Glycosaminoglycans (GAGs) are linear polysaccharides, consisting of repeated disaccharide units, attached to core proteins in all multicellular organisms. Chondroitin sulfate (CS) and dermatan sulfate (DS) constitute a subgroup of sulfated GAGs for which the degree of sulfation varies between species and tissues. One major goal in GAG characterization is to correlate structure to function. A common approach is to exhaustively degrade the GAG chains and thereafter determine the amount of component disaccharide units. In large-scale studies, there is a need for high-throughput screening methods since existing methods are either very time- or samples consuming. Here, we present a new strategy applying MALDI-TOF MS in positive ion mode for semi-qualitative and quantitative analysis of CS/DS derived disaccharide units. Only a few picomoles of sample are required per analysis and 10 samples can be analyzed in 25 min, which makes this approach an attractive alternative to many established assay methods. The total CS/DS concentration in 19 samples derived from Caenorhabditis elegans and mammalian tissues and cells was determined. The obtained results were well in accordance with concentrations determined by a standard liquid chromatography-based method, demonstrating the applicability of the method for samples from various biological matrices containing CS/DS of different sulfation degrees.
High throughput screening (HTS) is important for identifying molecules with desired properties. Mass spectrometry (MS) is potentially powerful for label-free HTS due to its high sensitivity, speed, and resolution. Segmented flow, where samples are manipulated as droplets separated by an immiscible fluid, is an intriguing format for high throughput MS because it can be used to reliably and precisely manipulate nanoliter volumes and can be directly coupled to electrospray ionization (ESI) MS for rapid analysis. In this study, we describe a "MS Plate Reader" that couples standard multiwell plate HTS workflow to droplet ESI-MS. The MS plate reader can reformat 3072 samples from eight 384-well plates into nanoliter droplets segmented by an immiscible oil at 4.5 samples/s and sequentially analyze them by MS at 2 samples/s. Using the system, a label-free screen for cathepsin B modulators against 1280 chemicals was completed in 45 min with a high Z-factor (>0.72) and no false positives (24 of 24 hits confirmed). The assay revealed 11 structures not previously linked to cathepsin inhibition. For even larger scale screening, reformatting and analysis could be conducted simultaneously, which would enable more than 145,000 samples to be analyzed in 1 day.
In view of the current difficulty of clinically diagnosing osteoarticular tuberculosis, our aim was to use mass spectrometry to establish diagnostic models and to screen and identify serum proteins which could serve as potential diagnostic biomarkers for early detection of osteoarticular tuberculosis.
Toward the goal of increasing the throughput of high-resolution mass characterization of intact antibodies, we developed a RapidFire-mass spectrometry (MS) assay using electrospray ionization. We achieved unprecedented screening throughput as fast as 15 s/sample, which is an order of magnitude improvement over conventional liquid chromatography (LC)-MS approaches. The screening enabled intact mass determination as accurate as 7 ppm with baseline resolution at the glycoform level for intact antibodies. We utilized this assay to characterize and perform relative quantitation of antibody species from 248 samples of 62 different cell line clones at four time points in 2 h using RapidFire-time-of-flight MS screening. The screening enabled selection of clones with the highest purity of bispecific antibody production and the results significantly correlated with conventional LC-MS results. In addition, analyzing antibodies from a complex plasma sample using affinity-RapidFire-MS was also demonstrated and qualified. In summary, the platform affords high-throughput analyses of antibodies, including bispecific antibodies and potential mispaired side products, in cell culture media, or other complex matrices.
There is increasing evidence that the ∼20 routinely monitored perfluoroalkyl and polyfluoroalkyl substances (PFASs) account for only a fraction of extractable organofluorine (EOF) occurring in the environment. To assess whether PFAS exposure is being underestimated in marine mammals from the Northern Hemisphere, we performed a fluorine mass balance on liver tissues from 11 different species using a combination of targeted PFAS analysis, EOF and total fluorine determination, and suspect screening. Samples were obtained from the east coast United States (US), west and east coast of Greenland, Iceland, and Sweden from 2000 to 2017. Of the 36 target PFASs, perfluorooctane sulfonate (PFOS) dominated in all but one Icelandic and three US samples, where the 7:3 fluorotelomer carboxylic acid (7:3 FTCA) was prevalent. This is the first report of 7:3 FTCA in polar bears (∼1000 ng/g, ww) and cetaceans (<6-190 ng/g, ww). In 18 out of 25 samples, EOF was not significantly greater than fluorine concentrations derived from sum target PFASs. For the remaining 7 samples (mostly from the US east coast), 30-75% of the EOF was unidentified. Suspect screening revealed an additional 37 PFASs (not included in the targeted analysis) bringing the total to 63 detected PFASs from 12 different classes. Overall, these results highlight the importance of a multiplatform approach for accurately characterizing PFAS exposure in marine mammals.
Bladder cancer (BC) is a common urological malignancy with a high probability of death and recurrence. Cystoscopy is used as a routine examination for diagnosis and following patient monitoring for recurrence. Repeated costly and intrusive treatments may discourage patients from having frequent follow-up screenings. Hence, exploring novel non-invasive ways to help identify recurrent and/or primary BC is critical. In this work, 200 human urine samples were profiled using ultra-high-performance liquid chromatography and ultra-high-resolution mass spectrometry (UHPLC-UHRMS) to uncover molecular markers differentiating BC from non-cancer controls (NCs). Univariate and multivariate statistical analyses with external validation identified metabolites that distinguish BC patients from NCs disease. More detailed divisions for the stage, grade, age, and gender are also discussed. Findings indicate that monitoring urine metabolites may provide a non-invasive and more straightforward diagnostic method for identifying BC and treating recurrent diseases.
Contemporary medicinal chemistry considers fragment-based drug discovery (FBDD) and inhibition of protein-protein interactions (PPI) as important means of expanding the volume of druggable chemical space. However, the ability to robustly identify valid fragments and PPI inhibitors is an enormous challenge, requiring the application of sensitive biophysical methodology. Accordingly, in this study, we exploited the speed and sensitivity of nanoelectrospray (nano-ESI) native mass spectrometry to identify a small collection of fragments which bind to the TPR2AB domain of HOP. Follow-up biophysical assessment of a small selection of binding fragments confirmed binding to the single TPR2A domain, and that this binding translated into PPI inhibitory activity between TPR2A and the HSP90 C-terminal domain. An in-silico assessment of binding fragments at the PPI interfacial region, provided valuable structural insight for future fragment elaboration strategies, including the identification of losartan as a weak, albeit dose-dependent inhibitor of the target PPI.
Evidence of the involvement of epigenetics in pathologies such as cancer, diabetes, and neurodegeneration has increased global interest in epigenetic modifications. For nearly thirty years, it has been known that cancer cells exhibit abnormal DNA methylation patterns. In contrast, the large-scale analysis of histone post-translational modifications (hPTMs) has lagged behind because classically, histone modification analysis has relied on site specific antibody-based techniques. Mass spectrometry (MS) is a technique that holds the promise to picture the histone code comprehensively in a single experiment. Therefore, we developed an MS-based method that is capable of tracking all possible hPTMs in an untargeted approach. In this way, trends in single and combinatorial hPTMs can be reported and enable prediction of the epigenetic toxicity of compounds. Moreover, this method is based on the use of human cells to provide preliminary data, thereby omitting the need to sacrifice laboratory animals. Improving the workflow and the user-friendliness in order to become a high throughput, easily applicable, toxicological screening assay is an ongoing effort. Still, this novel toxicoepigenetic assay and the data it generates holds great potential for, among others, pharmaceutical industry, food science, clinical diagnostics and, environmental toxicity screening. •There is a growing interest in epigenetic modifications, and more specifically in histone post-translational modifications (hPTMs).•We describe an MS-based workflow that is capable of tracking all possible hPTMs in an untargeted approach that makes use of human cells.•Improving the workflow and the user-friendliness in order to become a high throughput, easily applicable, toxicological screening assay is an ongoing effort.
Underlying coronary artery disease (CAD) is the primary cause of sudden cardiac death in masters athletes (>35 years). Preparticipation screening may detect cardiovascular disease; however, the optimal screening method is undefined in this population. The Physical Activity Readiness Questionnaire for Everyone (PAR-Q+) and the American Heart Association (AHA) Preparticipation Screening Questionnaire are often currently used; however, a more comprehensive risk assessment may be required. We sought to ascertain the cardiovascular risk and to assess the effectiveness of screening tools in masters athletes.
G protein-coupled receptors (GPCRs) represent the largest class of cell surface proteins and thus constitute an important family of therapeutic targets. Therefore, significant effort has been put towards the identification of novel ligands that can modulate the activity of a GPCR target with high efficacy and selectivity. However, due to limitations inherent to the most common techniques for GPCR ligand discovery, there is a pressing need for more efficient and effective ligand screening methods especially for the identification of potential allosteric modulators. Here we present a high-throughput, label-free and unbiased screening approach for the identification of small molecule ligands towards GPCR targets based on affinity mass spectrometry. This new approach features the usage of target-expressing cell membranes rather than purified proteins for ligand screening and allows the detection of both orthosteric and allosteric ligands targeting specific GPCRs. Screening a small compound library with this approach led to the rapid discovery of an antagonist for the 5-HT receptor and four positive allosteric modulators for GLP-1 receptor that were not previously reported.
Tri-ponderal mass index (TMI) and fat mass index (FMI) have been proposed as alternative approaches for assessing body fat since BMI does not ensure an accurate screening for obesity and overweight status in children and adolescents. This study proposes thresholds of the TMI and FMI for the prediction of metabolic syndrome (MetS) in children and young people. For this purpose, a cross-sectional study was conducted on 4673 participants (57.1% females), who were 9-25 years of age. As part of the study, measurements of the subjects' weight, waist circumference, serum lipid indices, blood pressure and fasting plasma glucose were taken. Body composition was measured by bioelectrical impedance analysis (BIA). The TMI and FMI were calculated as weight (kg)/height (m³) and fat mass (kg)/height (m³), respectively. Following the International Diabetes Federation (IDF) definition, MetS is defined as including three or more metabolic abnormalities. Cohort-specific thresholds were established to identify Colombian children and young people at high risk of MetS. The thresholds were applied to the following groups: (i) a cohort of children where the girls' TMI ≥ 12.13 kg/m³ and the boys' TMI ≥ 12.10 kg/m³; (ii) a cohort of adolescents where the girls' TMI ≥ 12.48 kg/m³ and the boys' TMI ≥ 11.19 kg/m³; (iii) a cohort of young adults where the women's TMI ≥ 13.21 kg/m³ and the men's TMI ≥ 12.19 kg/m³. The FMI reference cut-off values used for the different groups were as follows: (i) a cohort of children where the girls' FMI ≥ 2.59 fat mass/m³ and the boys' FMI ≥ 1.98 fat mass/m³; (ii) a cohort of adolescents where the girls' FMI ≥ 3.12 fat mass/m³ and the boys' FMI ≥ 1.46 fat mass/m³; (iii) a cohort of adults where the women's FMI ≥ 3.27 kg/m³ and the men's FMI ≥ 1.65 kg/m³. Our results showed that the FMI and TMI had a moderate discriminatory power to detect MetS in Colombian children, adolescents, and young adults.
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