38 research outputs found

    Current practices in lc-ms untargeted metabolomics: a scoping review on the use of pooled quality control samples

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    Untargeted metabolomics is an analytical approach with numerous applications serving as an effective metabolic phenotyping platform to characterize small molecules within a biological system. Data quality can be challenging to evaluate and demonstrate in metabolomics experiments. This has driven the use of pooled quality control (QC) samples for monitoring and, if necessary, correcting for analytical variance introduced during sample preparation and data acquisition stages. Described herein is a scoping literature review detailing the use of pooled QC samples in published untargeted liquid chromatography-mass spectrometry (LC-MS) based metabolomics studies. A literature query was performed, the list of papers was filtered, and suitable articles were randomly sampled. In total, 109 papers were each reviewed by at least five reviewers, answering predefined questions surrounding the use of pooled quality control samples. The results of the review indicate that use of pooled QC samples has been relatively widely adopted by the metabolomics community and that it is used at a similar frequency across biological taxa and sample types in both small- and large-scale studies. However, while many studies generated and analyzed pooled QC samples, relatively few reported the use of pooled QC samples to improve data quality. This demonstrates a clear opportunity for the field to more frequently utilize pooled QC samples for quality reporting, feature filtering, analytical drift correction, and metabolite annotation. Additionally, our survey approach enabled us to assess the ambiguity in the reporting of the methods used to describe the generation and use of pooled QC samples. This analysis indicates that many details of the QC framework are missing or unclear, limiting the reader's ability to determine which QC steps have been taken. Collectively, these results capture the current state of pooled QC sample usage and highlight existing strengths and deficiencies as they are applied in untargeted LC-MS metabolomics

    Identification of fungal metabolites from inside Gallus gallus domesticus eggshells by non-invasively detecting volatile organic compounds (VOCs)

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    The natural porosity of eggshells allows hen eggs to become contaminated with microbes from the nesting material and environment. Those microorganisms can later proliferate due to the humid ambient conditions while stored in refrigerators, causing a potential health hazard to the consumer. The microbes' volatile organic compounds (mVOCs) are released by both fungi and bacteria. We studied mVOCs produced by aging eggs likely contaminated by fungi and fresh eggs using the non-invasive detection method of gas-phase sampling of volatiles followed by gas chromatography/mass spectrometry (GC/MS) analysis. Two different fungal species (Cladosporium macrocarpum and Botrytis cinerea) and two different bacteria species (Stenotrophomas rhizophila and Pseudomonas argentinensis) were identified inside the studied eggs. Two compounds believed to originate from the fungi themselves were identified. One fungus-specific compound was found in both egg and the fungi: trichloromethane. Graphical abstract Trichloromethane is a potential biomarker of fungal contamination of eggs

    Supervised semi-automated data analysis software for gas chromatography / differential mobility spectrometry (GC/DMS) metabolomics applications

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    Modern differential mobility spectrometers (DMS) produce complex and multi-dimensional data streams that allow for near-real-time or post-hoc chemical detection for a variety of applications. An active area of interest for this technology is metabolite monitoring for biological applications, and these data sets regularly have unique technical and data analysis end user requirements. While there are initial publications on how investigators have individually processed and analyzed their DMS metabolomic data, there are no user-ready commercial or open source software packages that are easily used for this purpose. We have created custom software uniquely suited to analyze gas chromatograph / differential mobility spectrometry (GC/DMS) data from biological sources. Here we explain the implementation of the software, describe the user features that are available, and provide an example of how this software functions using a previously-published data set. The software is compatible with many commercial or home-made DMS systems. Because the software is versatile, it can also potentially be used for other similarly structured data sets, such as GC/GC and other IMS modalities

    Preconcentrator-based sensor mu -system for low-level benzene detection

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    In this paper, a preconcentrator-based sensor mu -system for low level benzene detection is presented. It consists of a spiral-shaped mu -reconcentrator with dimensions of 10 cm * 300 mu m * 300 mu m, followed by a mu -hotplate sensor matrix. The mu -preconcentrator was fabricated on a silicon wafer by means of DRIE and anodic bonding techniques. To obtain the concentration factor of the fabricated devices, a GC/MS: Shimadzu-QP5000 equipment was used. The results obtained showed excellent repeatability and preconcentration factors up to 286. A considerable improvement (1500%) in the sensor responses was achieved with Pd doped SnO/sub 2/ sensors. The small size of the manufactured devices enables their incorporation in an integrated GC/MS gas sensor system.Anglai
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