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

Ceranic, Asja; Bueschl, Christoph; Doppler, Maria; Parich, Alexandra; Xu, Ke; Lemmens, Marc; Buerstmayr, Hermann; Schuhmacher, Rainer

doi:10.3390/metabo10110434

Cited by 6 publications

(3 citation statements)

References 50 publications

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“…Native plants were cultivated in the glass house without 13 CO 2 and harvested at the flowering stage as described by Ceranic and colleagues [38]. Briefly summarized, the plants were removed from the pot and remaining soil was washed from the roots with water.…”

Section: Fresh Root Samplesmentioning

confidence: 99%

Untargeted Plant Metabolomics: Evaluation of Lyophilization as a Sample Preparation Technique

Maisl,

Doppler,

Seidl

et al. 2023

Metabolites

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Lyophilization is a common method used for stabilizing biological samples prior to storage or to concentrate extracts. However, it is possible that this process may alter the metabolic composition or lead to the loss of metabolites. In this study, the performance of lyophilization is investigated in the example of wheat roots. To this end, native and 13C-labelled, fresh or already lyophilized root samples, and (diluted) extracts with dilution factors up to 32 and authentic reference standards were investigated. All samples were analyzed using RP-LC-HRMS. Results show that using lyophilization for the stabilization of plant material altered the metabolic sample composition. Overall, 7% of all wheat metabolites detected in non-lyophilized samples were not detected in dried samples anymore, and up to 43% of the remaining metabolites exhibited significantly increased or decreased abundances. With respect to extract concentration, less than 5% of the expected metabolites were completely lost by lyophilization and the recovery rates of the remaining metabolites were slightly reduced with increasing concentration factors to an average of 85% at an enrichment factor of 32. Compound annotation did not indicate specific classes of wheat metabolites to be affected.

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Section: Fresh Root Samplesmentioning

confidence: 99%

Untargeted Plant Metabolomics: Evaluation of Lyophilization as a Sample Preparation Technique

Maisl,

Doppler,

Seidl

et al. 2023

Metabolites

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“…Currently, the analytical challenges in metabolomics include the need to integrate data derived from more than one platform to produce more robust data and a wider metabolome coverage, maximizing the detection of possible metabolites in the target system (see Aliferis and Jabaji, 2011;Ćeranić et al, 2020;Roca et al, 2021 for reviews). Recent studies are showing that this integration is particularly powerful.…”

Section: Advanced Cross-platform Data Integrationmentioning

confidence: 99%

Beyond Sperm and Male Accessory Gland Proteins: Exploring Insect Reproductive Metabolomes

2021

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Insect seminal fluid, the non-sperm component of the ejaculate, comprises a variegated set of molecules, including, but not limited to, lipids, proteins, carbohydrates, salts, hormones, nucleic acids, and vitamins. The identity and functional role of seminal fluid proteins (SFPs) have been widely investigated, in multiple species. However, most of the other small molecules in insect ejaculates remain uncharacterized. Metabolomics is currently adopted to deepen our understanding of complex biological processes and in the last 15years has been applied to answer different physiological questions. Technological advances in high-throughput methods for metabolite identification such as mass spectrometry and nuclear magnetic resonance (NMR) are now coupled to an expanded bioinformatics toolbox for large-scale data analysis. These improvements allow for the processing of smaller-sized samples and for the identification of hundreds to thousands of metabolites, not only in Drosophila melanogaster but also in disease vectors, animal, and agricultural pests. In this review, we provide an overview of the studies that adopted metabolomics-based approaches in insects, with a particular focus on the reproductive tract (RT) of both sexes and the ejaculate. Progress in the field of metabolomics will contribute not only to achieve a deeper understanding of the composition of insect ejaculates and how they are affected by endogenous and exogenous factors, but also to provide increasingly powerful tools to decipher the identity and molecular interactions between males and females during and after mating.

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“…For the matrix effect assessment and correction, the postextraction spiking method is more suitable for targeted metabolomics due to the requirement of authentic standards. Hence, PCI is recommended as a more appropriate tool for matrix effect evaluation in untargeted metabolomics, , but only few studies about its application have been reported. , Although stable isotope labeling has also been applied to matrix effect evaluation in untargeted metabolomics, this technique is limited to specific sample types like yeast, cells, or plants due to the requirement of a globally labeled growth medium. − …”

Section: Introductionmentioning

confidence: 99%

Development of an Untargeted LC-MS Metabolomics Method with Postcolumn Infusion for Matrix Effect Monitoring in Plasma and Feces

Zhu,

Dubbelman,

Hunter

et al. 2024

J. Am. Soc. Mass Spectrom.

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Untargeted metabolomics based on reverse phase LC-MS (RPLC-MS) plays a crucial role in biomarker discovery across physiological and disease states. Standardizing the development process of untargeted methods requires paying attention to critical factors that are under discussed or easily overlooked, such as injection parameters, performance assessment, and matrix effect evaluation. In this study, we developed an untargeted metabolomics method for plasma and fecal samples with the optimization and evaluation of these factors. Our results showed that optimizing the reconstitution solvent and sample injection amount was critical for achieving the balance between metabolites coverage and signal linearity. Method validation with representative stable isotopically labeled standards (SILs) provided insights into the analytical performance evaluation of our method. To tackle the issue of the matrix effect, we implemented a postcolumn infusion (PCI) approach to monitor the overall absolute matrix effect (AME) and relative matrix effect (RME). The monitoring revealed distinct AME and RME profiles in plasma and feces. Comparing RME data obtained for SILs through postextraction spiking with those monitored using PCI compounds demonstrated the comparability of these two methods for RME assessment. Therefore, we applied the PCI approach to predict the RME of 305 target compounds covered in our in-house library and found that targets detected in the negative polarity were more vulnerable to the RME, regardless of the sample matrix. Given the value of this PCI approach in identifying the strengths and weaknesses of our method in terms of the matrix effect, we recommend implementing a PCI approach during method development and applying it routinely in untargeted metabolomics.

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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

Cited by 6 publications

References 50 publications

Untargeted Plant Metabolomics: Evaluation of Lyophilization as a Sample Preparation Technique

Untargeted Plant Metabolomics: Evaluation of Lyophilization as a Sample Preparation Technique

Beyond Sperm and Male Accessory Gland Proteins: Exploring Insect Reproductive Metabolomes

Development of an Untargeted LC-MS Metabolomics Method with Postcolumn Infusion for Matrix Effect Monitoring in Plasma and Feces

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