Novel sampling strategy for alive animal volatolome extraction combined with GC-MS based untargeted metabolomics: Identifying mouse pup pheromones

Apicomplexan parasites are responsible for devastating diseases, including malaria, toxoplasmosis, and cryptosporidiosis. Current treatments are limited by emerging resistance to, as well as the high cost and toxicity of existing drugs. As obligate intracellular parasites, apicomplexans rely on the uptake of many essential metabolites from their host. Toxoplasma gondii, the causative agent of toxoplasmosis, is auxotrophic for several metabolites, including sugars (e.g., myo-inositol), amino acids (e.g., tyrosine), lipidic compounds and lipid precursors (cholesterol, choline), vitamins, cofactors (thiamine) and others. To date, only few apicomplexan metabolite transporters have been characterized and assigned a substrate. Here, we set out to investigate whether untargeted metabolomics can be used to identify the substrate of an uncharacterized transporter. Based on existing genome- and proteome-wide datasets, we have identified an essential plasma membrane transporter of the major facilitator superfamily in T. gondii—previously termed TgApiAT6-1. Using an inducible system based on RNA degradation, TgApiAT6-1 was depleted, and the mutant parasite’s metabolome was compared to that of non-depleted parasites. The most significantly reduced metabolite in parasites depleted in TgApiAT6-1 was identified as the amino acid lysine, for which T. gondii is predicted to be auxotrophic. Using stable isotope-labeled amino acids, we confirmed that TgApiAT6-1 is required for efficient lysine uptake. Our findings highlight untargeted metabolomics as a powerful tool to identify the substrate of orphan transporters.

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Phytocannabinomics: Untargeted metabolomics as a tool for cannabis chemovar differentiation

Talanta ◽

10.1016/j.talanta.2021.122313 ◽

2021 ◽

Vol 230 ◽

pp. 122313

Author(s):

Andrea Cerrato ◽

Cinzia Citti ◽

Giuseppe Cannazza ◽

Anna Laura Capriotti ◽

Chiara Cavaliere ◽

...

Keyword(s):

Untargeted Metabolomics

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Using Out-of-Batch Reference Populations to Improve Untargeted Metabolomics for Screening Inborn Errors of Metabolism

Metabolites ◽

10.3390/metabo11010008 ◽

2020 ◽

Vol 11 (1) ◽

pp. 8

Author(s):

Michiel Bongaerts ◽

Ramon Bonte ◽

Serwet Demirdas ◽

Edwin H. Jacobs ◽

Esmee Oussoren ◽

...

Keyword(s):

Regression Model ◽

Inborn Errors Of Metabolism ◽

Untargeted Metabolomics ◽

Detection Accuracy ◽

Inborn Errors ◽

Mixed Effect ◽

Metabolomics Data ◽

Normalization Methods ◽

Metabolite Concentrations ◽

Reference Samples

Untargeted metabolomics is an emerging technology in the laboratory diagnosis of inborn errors of metabolism (IEM). Analysis of a large number of reference samples is crucial for correcting variations in metabolite concentrations that result from factors, such as diet, age, and gender in order to judge whether metabolite levels are abnormal. However, a large number of reference samples requires the use of out-of-batch samples, which is hampered by the semi-quantitative nature of untargeted metabolomics data, i.e., technical variations between batches. Methods to merge and accurately normalize data from multiple batches are urgently needed. Based on six metrics, we compared the existing normalization methods on their ability to reduce the batch effects from nine independently processed batches. Many of those showed marginal performances, which motivated us to develop Metchalizer, a normalization method that uses 10 stable isotope-labeled internal standards and a mixed effect model. In addition, we propose a regression model with age and sex as covariates fitted on reference samples that were obtained from all nine batches. Metchalizer applied on log-transformed data showed the most promising performance on batch effect removal, as well as in the detection of 195 known biomarkers across 49 IEM patient samples and performed at least similar to an approach utilizing 15 within-batch reference samples. Furthermore, our regression model indicates that 6.5–37% of the considered features showed significant age-dependent variations. Our comprehensive comparison of normalization methods showed that our Log-Metchalizer approach enables the use out-of-batch reference samples to establish clinically-relevant reference values for metabolite concentrations. These findings open the possibilities to use large scale out-of-batch reference samples in a clinical setting, increasing the throughput and detection accuracy.

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Dried urine spots as sampling technique for multi-mycotoxin analysis in human urine

Mycotoxin Research ◽

10.1007/s12550-021-00423-1 ◽

2021 ◽

Author(s):

Jessica Schmidt ◽

Viktoria Lindemann ◽

Monica Olsen ◽

Benedikt Cramer ◽

Hans-Ulrich Humpf

Keyword(s):

Ochratoxin A ◽

Human Urine ◽

Sampling Strategy ◽

Sampling Technique ◽

Human Biomonitoring ◽

Urine Samples ◽

Isotope Dilution Analysis ◽

Tenuazonic Acid ◽

Stable Isotope Dilution Analysis ◽

Mycotoxin Analysis

AbstractA simple and effective approach for HPLC-MS/MS based multi-mycotoxin analysis in human urine samples was developed by application of dried urine spots (DUS) as alternative on-site sampling strategy. The newly developed method enables the detection and quantitation of 14 relevant mycotoxins and mycotoxin metabolites, including citrinin (CIT), dihydrocitrinone (DH-CIT), deoxynivalenol (DON), fumonisin B1 (FB1), T-2 Toxin (T-2), HT-2 Toxin (HT-2), ochratoxin A (OTA), 2′R-ochratoxin A (2′R-OTA), ochratoxin α (OTα), tenuazonic acid and allo-tenuazonic acid (TeA + allo-TeA), zearalenone (ZEN), zearalanone (ZAN), α-zearalenol (α-ZEL), and β-zearalenol (β-ZEL). Besides the spotting procedure, sample preparation includes enzymatic cleavage of glucuronic acid conjugates and stable isotope dilution analysis. Method validation revealed low limits of detection in the range of pg/mL urine and excellent apparent recovery rates for most analytes. Stability investigation of DUS displayed no or only slight decrease of the analyte concentration over a period of 28 days at room temperature. The new method was applied to the analysis of a set of urine samples (n = 91) from a Swedish cohort. The four analytes, DH-CIT, DON, OTA, and TeA + allo-TeA, could be detected and quantified in amounts ranging from 0.06 to 0.97 ng/mL, 3.03 to 136 ng/mL, 0.013 to 0.434 ng/mL and from 0.36 to 47 ng/mL in 38.5%, 70.3%, 68.1%, and 94.5% of the samples, respectively. Additional analysis of these urine samples with an established dilute and shoot (DaS) approach displayed a high consistency of the results obtained with both methods. However, due to higher sensitivity, a larger number of positive samples were observed using the DUS method consequently providing a suitable approach for human biomonitoring of mycotoxin exposure.

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Untargeted Metabolomics Approach for the Discovery of Environment-Related Pyran-2-ones Chemodiversity in a Marine-Sourced Penicillium restrictum

Marine Drugs ◽

10.3390/md19070378 ◽

2021 ◽

Vol 19 (7) ◽

pp. 378

Author(s):

Van-Tuyen Le ◽

Samuel Bertrand ◽

Thibaut Robiou du Pont ◽

Fabrice Fleury ◽

Nathalie Caroff ◽

...

Keyword(s):

Culture Medium ◽

Blue Mussel ◽

Culture Media ◽

Principal Component ◽

Chemical Diversity ◽

Untargeted Metabolomics ◽

High Chemical ◽

Medium Mass ◽

Metabolomics Study ◽

Penicillium Restrictum

Very little is known about chemical interactions between fungi and their mollusc host within marine environments. Here, we investigated the metabolome of a Penicillium restrictum MMS417 strain isolated from the blue mussel Mytilus edulis collected on the Loire estuary, France. Following the OSMAC approach with the use of 14 culture media, the effect of salinity and of a mussel-derived medium on the metabolic expression were analysed using HPLC-UV/DAD-HRMS/MS. An untargeted metabolomics study was performed using principal component analysis (PCA), orthogonal projection to latent structure discriminant analysis (O-PLSDA) and molecular networking (MN). It highlighted some compounds belonging to sterols, macrolides and pyran-2-ones, which were specifically induced in marine conditions. In particular, a high chemical diversity of pyran-2-ones was found to be related to the presence of mussel extract in the culture medium. Mass spectrometry (MS)- and UV-guided purification resulted in the isolation of five new natural fungal pyran-2-one derivatives—5,6-dihydro-6S-hydroxymethyl-4-methoxy-2H-pyran-2-one (1), (6S, 1’R, 2’S)-LL-P880β (3), 5,6-dihydro-4-methoxy-6S-(1’S, 2’S-dihydroxy pent-3’(E)-enyl)-2H-pyran-2-one (4), 4-methoxy-6-(1’R, 2’S-dihydroxy pent-3’(E)-enyl)-2H-pyran-2-one (6) and 4-methoxy-2H-pyran-2-one (7)—together with the known (6S, 1’S, 2’S)-LL-P880β (2), (1’R, 2’S)-LL-P880γ (5), 5,6-dihydro-4-methoxy-2H-pyran-2-one (8), (6S, 1’S, 2’R)-LL-P880β (9), (6S, 1’S)-pestalotin (10), 1’R-dehydropestalotin (11) and 6-pentyl-4-methoxy-2H-pyran-2-one (12) from the mussel-derived culture medium extract. The structures of 1-12 were determined by 1D- and 2D-MMR experiments as well as high-resolution tandem MS, ECD and DP4 calculations. Some of these compounds were evaluated for their cytotoxic, antibacterial, antileishmanial and in-silico PTP1B inhibitory activities. These results illustrate the utility in using host-derived media for the discovery of new natural products.

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GIS-Based Approach to Spatio-Temporal Interpolation of Atmospheric CO2 Concentrations in Limited Monitoring Dataset

Atmosphere ◽

10.3390/atmos12030384 ◽

2021 ◽

Vol 12 (3) ◽

pp. 384

Author(s):

Yaroslav Bezyk ◽

Izabela Sówka ◽

Maciej Górka ◽

Jan Blachowski

Keyword(s):

Seasonal Variability ◽

Sampling Strategy ◽

Climate Impacts ◽

Air Pollutant ◽

Urban Atmosphere ◽

Atmospheric Co2 ◽

Spatial Characteristic ◽

Interpolation Methods ◽

Co2 Levels ◽

The City

Understanding the magnitude and distribution of the mixes of the near-ground carbon dioxide (CO2) components spatially (related to the surface characteristics) and temporally (over seasonal timescales) is critical to evaluating present and future climate impacts. Thus, the application of in situ measurement approaches, combined with the spatial interpolation methods, will help to explore variations in source contribution to the total CO2 mixing ratios in the urban atmosphere. This study presents the spatial characteristic and temporal trend of atmospheric CO2 levels observed within the city of Wroclaw, Poland for the July 2017–August 2018 period. The seasonal variability of atmospheric CO2 around the city was directly measured at the selected sites using flask sampling with a Picarro G2201-I Cavity Ring-Down Spectroscopy (CRDS) technique. The current work aimed at determining the accuracy of the interpolation techniques and adjusting the interpolation parameters for estimating the magnitude of CO2 time series/seasonal variability in terms of limited observations during the vegetation and non-vegetation periods. The objective was to evaluate how different interpolation methods will affect the assessment of air pollutant levels in the urban environment and identify the optimal sampling strategy. The study discusses the schemes for optimization of the interpolation results that may be adopted in areas where no observations are available, which is based on the kriging error predictions for an appropriate spatial density of measurement locations. Finally, the interpolation results were extended regarding the average prediction bias by exploring additional experimental configurations and introducing the limitation of the future sampling strategy on the seasonal representation of the CO2 levels in the urban area.

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Identifying VOCs in exhibition cases and efflorescence on museum objects exhibited at Smithsonian’s National Museum of the American Indian-New York

Heritage Science ◽

10.1186/s40494-020-00454-4 ◽

2020 ◽

Vol 8 (1) ◽

Author(s):

Alba Alvarez-Martin ◽

John George ◽

Emily Kaplan ◽

Lauren Osmond ◽

Leah Bright ◽

...

Keyword(s):

New York ◽

American Indian ◽

Solid Phase ◽

Construction Materials ◽

Sampling Strategy ◽

Sampling Technique ◽

Direct Analysis ◽

National Museum ◽

Structural Adhesive ◽

Speed Of Analysis

AbstractTwo mass spectrometry (MS) methods, solid-phase microextraction gas chromatography (SPME–GC–MS) and direct analysis in real time (DART-MS), have been explored to investigate widespread efflorescence observed on exhibited objects at the Smithsonian’s National Museum of the American Indian in New York (NMAI-NY). Both methods show great potential, in terms of speed of analysis and level of information, for identifying the organic component of the efflorescence as 2,2,6,6-tetramethyl-4-piperidinol (TMP-ol) emitted by the structural adhesive (Terostat MS 937) used for exhibit case construction. The utility of DART-MS was proven by detecting the presence of TMP-ol in construction materials in a fraction of the time and effort required for SPME–GC–MS analysis. In parallel, an unobtrusive SPME sampling strategy was used to detect volatile organic compounds (VOCs) accumulated in the exhibition cases. This sampling technique can be performed by collections and conservation staff at the museum and shipped to an off-site laboratory for analysis. This broadens the accessibility of MS techniques to museums without access to instrumentation or in-house analysis capabilities.

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Managing work flow in high enrolling trials: The development and implementation of a sampling strategy in the PREPARE trial

Contemporary Clinical Trials Communications ◽

10.1016/j.conctc.2021.100730 ◽

2021 ◽

Vol 21 ◽

pp. 100730

Author(s):

David Pogorzelski ◽

Uyen Nguyen ◽

Paula McKay ◽

Lehana Thabane ◽

Megan Camara ◽

...

Keyword(s):

Sampling Strategy ◽

Work Flow

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