scholarly journals Enhanced Metabolome Coverage and Evaluation of Matrix Effects by the Use of Experimental-Condition-Matched 13C-Labeled Biological Samples in Isotope-Assisted LC-HRMS Metabolomics

Metabolites ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 434
Author(s):  
Asja Ćeranić ◽  
Christoph Bueschl ◽  
Maria Doppler ◽  
Alexandra Parich ◽  
Kangkang Xu ◽  
...  

Stable isotope-assisted approaches can improve untargeted liquid chromatography-high resolution mass spectrometry (LC-HRMS) metabolomics studies. Here, we demonstrate at the example of chemically stressed wheat that metabolome-wide internal standardization by globally 13C-labeled metabolite extract (GLMe-IS) of experimental-condition-matched biological samples can help to improve the detection of treatment-relevant metabolites and can aid in the post-acquisition assessment of putative matrix effects in samples obtained upon different treatments. For this, native extracts of toxin- and mock-treated (control) wheat ears were standardized by the addition of uniformly 13C-labeled wheat ear extracts that were cultivated under similar experimental conditions (toxin-treatment and control) and measured with LC-HRMS. The results show that 996 wheat-derived metabolites were detected with the non-condition-matched 13C-labeled metabolite extract, while another 68 were only covered by the experimental-condition-matched GLMe-IS. Additional testing is performed with the assumption that GLMe-IS enables compensation for matrix effects. Although on average no severe matrix differences between both experimental conditions were found, individual metabolites may be affected as is demonstrated by wrong decisions with respect to the classification of significantly altered metabolites. When GLMe-IS was applied to compensate for matrix effects, 272 metabolites showed significantly altered levels between treated and control samples, 42 of which would not have been classified as such without GLMe-IS.

2019 ◽  
Vol 85 (1II)) ◽  
pp. 139-144
Author(s):  
N. P. Zaksas ◽  
A. F. Veryaskin

A two-jet plasma is used for direct atomic emission analysis of powdered samples. It is characterized by relatively weak matrix effects, which allows using unified calibration samples on the basis of graphite powder for analysis of the samples with inorganic, organic, and organomineral matrix. In the present paper the effects limiting the usage of the unified approach due to different thermal stability and evaporation efficiency of the samples are discussed. The understated concentrations of a set of elements (Al, Ba, Ca, La, Mg, Mn, Sr, Ti, and Y) were obtained in analysis of certified reference materials of geological samples. It was shown that determination of rare earth elements should be carried out in the region behind the jet confluence providing their complete evaporation. For other elements, registration of the spectra in this region improves the results to some extent but they do not achieve the certified values. To speed up evaporation of these elements, the experimental conditions were chosen for plasma chemical reactions which provide conversion of the matrix elements into more volatile compounds. Addition of ammonium hydrofluoride to powdered sample considerably increased the line intensities of Al and Ca strongly associated with the silicon matrix. Incomplete evaporation was observed in analysis of biological samples with particle size more than 100 μm. A decrease in consumption of carrier argon is quite enough for effective decomposition of the organic matrix in plasma; the value of gas consumption depends on thermal stability and particle size of the sample. Preliminary sample carbonization is another way to improve evaporation of biological samples.


2016 ◽  
Vol 8 (23) ◽  
pp. 4664-4673 ◽  
Author(s):  
María del Mar Gómez-Ramos ◽  
Łukasz Rajski ◽  
Ana Lozano ◽  
Amadeo R. Fernández-Alba

Matrix fingerprinting of twenty-three different commodities was evaluated.


Separations ◽  
2020 ◽  
Vol 7 (2) ◽  
pp. 32
Author(s):  
Nerea Núñez ◽  
Oscar Vidal-Casanella ◽  
Sonia Sentellas ◽  
Javier Saurina ◽  
Oscar Núñez

In this work, non-targeted ultra-high performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) fingerprints obtained by C18 reversed-phase chromatography were proposed as sample chemical descriptors for the characterization and classification of turmeric and curry samples. A total of 21 turmeric and 9 curry commercially available samples were analyzed in triplicate after extraction with dimethyl sulfoxide (DMSO). The results demonstrated the feasibility of non-targeted UHPLC-HRMS fingerprints for sample classification, showing very good classification capabilities by partial least squares regression-discriminant analysis (PLS-DA), with 100% classification rates being obtained by PLS-DA when randomly selected samples were processed as “unknown” ones. Besides, turmeric curcuma species (Curcuma longa vs. Curcuma zedoaria) and turmeric Curcuma longa varieties (Madras, Erodes, and Alleppey) discrimination was also observed by PLS-DA when using the proposed fingerprints as chemical descriptors. As a conclusion, non-targeted UHPLC-HRMS fingerprinting is a suitable methodology for the characterization, classification, and authentication of turmeric and curry samples, without the requirement of using commercially available standards for quantification nor the necessity of metabolite identification.


2010 ◽  
Vol 1217 (25) ◽  
pp. 4071-4078 ◽  
Author(s):  
Ivano Marchi ◽  
Véronique Viette ◽  
Flavia Badoud ◽  
Marc Fathi ◽  
Martial Saugy ◽  
...  

2021 ◽  
Vol 166 ◽  
pp. 106197
Author(s):  
Natalia Arroyo-Manzanares ◽  
Natalia Campillo ◽  
Ignacio López-García ◽  
Manuel Hernández-Córdoba ◽  
Pilar Viñas

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Kang Hu ◽  
Shaoming Jin ◽  
Hong Ding ◽  
Jin Cao

In order to improve the risk identification ability of the technical support system of food safety supervision, an online screening platform for food risk substances (hereafter referred to as “platform”) was established. The platform aims at the qualitative analysis of unknown compounds and consists of three parts: a standard spectrum library, screening model, and online comparison module. The standard library contains the standard spectra of 527 food risk substances by high-performance liquid chromatography/high-resolution mass spectrometry. The screening comparison algorithm, the core of the screening model, is obtained through the improvement of the existing spectral library search algorithm. The inspector uploads the original spectrum file through the online comparison module; the online comparison module calls the corresponding script to convert the original spectrum file into a standard spectrum file and then uses the screening and comparison algorithm to achieve online real-time comparison. The comparison results are used to determine whether the sample to be tested contains the food risk substances contained in the standard library, so as to realize the preliminary screening of potential food risk substances. The platform supports the spectrogram data format of mainstream instrument manufacturers. The standard spectrogram database can be coconstructed and shared by cooperative laboratories to effectively enrich the types of food risk substances. Through laboratory comparison, data calibration, and model optimization, the screening accuracy of the platform can reach more than 97%. The platform adopts the Internet online screening method, which greatly facilitates the risk investigation and control of national food safety inspection and testing institutions. At the same time, the construction of the screening platform for food risk substances based on high-performance liquid chromatography/high-resolution mass spectrometry, the Internet, big data, and other technologies will provide a new technical means for food safety risk management and control. Hence, it can build a bridge between the screening of risk substances and illegally added substances, as well as risk assessment, risk management, and control.


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